Patent Publication Number: US-11661577-B2

Title: Co-incubating confined microbial communities

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     The present application is a continuation of U.S. patent application Ser. No. 14/746,494 filed on Jun. 22, 2015 which is a divisional of U.S. patent application Ser. No. 12/670,725, filed Jan. 26, 2010, which is the national phase application of PCT Application No. PCT/US2008/071370, filed Jul. 28, 2008, which claims priority to U.S. Provisional Application No. 60/962,426, filed Jul. 26, 2007, and U.S. Provisional Application No. 61/052,490, filed May 12, 2008, the entireties of all of which are herein incorporated by reference. 
    
    
     GOVERNMENT INTERESTS 
     This invention was made with government support under Grant No. OD003584 awarded by the National Institutes of Health. The government has certain rights in the invention. 
    
    
     FIELD OF THE INVENTION 
     This invention is related to the field of methods and devices for co-incubating at least two different microorganisms, such that one of those microorganisms performs a function differently than it would if the second organism was absent. 
     BACKGROUND OF THE INVENTION 
     Microbial communities perform a wide range of functions, such as microbial growth, nitrogen processing in the soil, cellulose degradation, lignin degradation, dehalogenation of hydrocarbons and aromatic hydrocarbons, decomposition of organic matter in the carbon cycle, and environmental remediation such as oxidation of hydrocarbons. Many tasks are difficult or impossible for a single microorganism to perform. These functions typically require balancing competition and interactions among multiple species. For example, bacteria form biofilms and other forms of interactions, where several types of bacteria survive through symbiotic relationships, in which nutrients and signaling molecules are exchanged. These processes may be better performed by a synthetic community of microorganisms. Furthermore, some of these processes may require microorganisms that cannot be cultured without other microorganisms present. 
     The vast majority of bacteria cannot be cultured and cannot be studied with traditional techniques. Under homogeneous laboratory conditions, most attempts to co-incubate multiple microbial species do not result in stable communities due to lopsided competition for nutrients among the cultured species. Attempted methods of co-incubate have potential problems: different microorganisms may be toxic to one another on contact; they may need to be kept apart with within diffusion contact; one microorganism may grow at a much faster rate than others; shared molecules such as nutrients are lost by diffusion unless the microorganisms are cultured close together. 
     It is known that spatial structure influences competition and interactions between microbes. Environments in which the microbes live are highly spatially heterogeneous, and it has been shown that microbes exist as isolated patches. In nature, microbial communities inhabit matrices with intricate spatial structure, for example, many species of soil bacteria stably coexist as microcolonies separated by a few hundred micrometers. Thus, spatial structure is important in microbial ecology. However, spatial structure is difficult to control in natural environments and has not been systematically experimentally varied to understand its effect on the stability of bacterial communities. 
     It is also known that microbial communities perform important functions that require the stable interaction of multiple species. The combined effects of competition and chemical communication dictate that some multi-species communities have required spatial structures in order to stably function. The trade-off between reduced competition and effective communication define a specific range of spatial structures for each community. Spatial structures thus may be able to stabilize microbial communities. Natural habitats provide such spatial structures and recreating some communities in the laboratory will require culturing the microorganisms in specific structures and under specific conditions. 
     Aspects of methods for culturing communities of interacting bacteria, are disclosed in, for example: Swenson et al., 2000,  Environmental Microbiology  2: 564-571 (artificial selection of microbial ecosystems for 3-chloroaniline biodegradation); in Swenson et al., 2000,  Proc. Natl. Acad. Sci. USA  97: 9110-9114 (artificial ecosystem selection); and in Williams and Lenton, 2007,  Proc. Natl. Acad. Sci. USA  104: 8918-8923 (artificial selection of simulated microbial ecosystems). 
     Aspects of how mixed communities do not survive due to competition are disclosed in, for example: Dechesne et al., 2008,  FEMS Microbiology Ecology  64: 1-8 (limited diffusive fluxes of substrate facilitate coexistence of two competing bacterial strains); in Ferrari et al., 2005,  Applied and Environmental Microbiology  71:8714-8720 (microcolony cultivation on a soil substrate membrane system, which selects for previously uncultured soil bacteria); in Treves et al., 2002,  Microbial Ecology,  45: 20-28 (two-species test of the hypothesis that spatial isolation influences microbial diversity in soil); in Hassell et al., 1994,  Nature  370: 290-292 (species coexistence and self-organizing spatial dynamics); in Allison, 2005,  Ecology Letters  8: 626-635 (cheaters, diffusion, and nutrients constrain decomposition by microbial enzymes in spatially structured environments); in Kerr et al., 2002,  Nature  418: 171-174 (local dispersal promotes biodiversity in a real-life game of rock-paper-scissors); and in Rainey and Travisano, 1998,  Nature  394: 69-72 (adaptive radiation in a heterogeneous environment). 
     Aspects of how dependent microbial strains require close proximity are disclosed in, for example: Nunan et al., 2003,  FEMS Microbiology Ecology  44: 203-215 (spatial distribution of bacterial communities and their relationship with the micro-architecture of soil); in Hansen et al., 2006,  Nature  445: 533-536 (evolution of species interactions in a biofilm community); and in Nielsen et al., 2000,  Environmental Microbiology  2: 59-68 (role of commensal relationships on the spatial structure of a surface-attached microbial consortium). 
     Aspects of how function and viability of some strains requires partner strains are disclosed in, for example, Ohno et al., 1999,  Biosci. Biotechnol. Biochem.  63: 1083-1090 (establishing the independent culture of a strictly symbiotic Bacterium  Symbiobacterium thermophilum  from its supporting  Bacillus  strain); in Kaeberlein et al., 2002, Science, 296: 1127-1129 (isolating “uncultivable” microorganisms in pure culture in a simulated natural environment); in Ou and Thomas, 1994,  Soil Science Soc. Am. J.  58: 1148-1153 (influence of soil organic matter and soil surface on a bacterial consortium that mineralizes fenamiphos, a pesticide); in Kato et al., 2005,  Applied and Environmental Microbiology  71: 7099-7106 (stable coexistence of five bacterial strains as a cellulose-degrading community); in Price-Whelan et al., 2006,  Nature Chemical Biology  2: 71-78 (rethinking ‘secondary’ metabolism: physiological roles for phenazine antibiotics); and in Cosgrove et al., 2007,  Applied and Environmental Microbiology  73: 5817-5824 (different fungal communities are associated with degradation of polyester polyurethane in soil). 
     Aspects of how soil is spatially complex, with patchy distribution of microbes, are disclosed in, for example, Young and Crawford, 2004,  Science  304: 1634-1637 (interactions and self-organization in the soil-microbe complex); and in Grundmann et al., 2001,  Soil Science Soc. Am. J.  65: 1709-1716 (spatial modeling of nitrifier microhabitats in soil). 
     Aspects of methods for in vitro spatial culture are disclosed in, for example, Abhyankar and Beebe, 2007,  Anal. Chem.  79: 4066-4073 (spatiotemporal micropatteming of cells on arbitrary substrates); in Weibel et al., 2007,  Nature Reviews Microbiology  5: 209-218 (microfabrication meets microbiology); in Keymer et al. 2006,  Proc. Natl. Acad. Sci. USA  103: 17290-17295 (bacterial metapopulations in nanofabricated landscapes); and in Ingham et al., 2007,  Proc. Natl. Acad. Sci. USA  104: 18217-18222 (the micro-Petri dish, a million-well growth chip for the culture and high-throughput screening of microorganisms). 
     BRIEF SUMMARY 
     The present invention provides a device for co-incubating microorganisms, comprising a lower layer, and upper layer and a barrier. The lower layer comprises a first compartment for a first microorganism and a second compartment for a second microorganism (different than the first). The first and second compartments are physically separated by a distance x. The upper layer comprises at least one communication channel. The lower layer and the upper layer are positioned such that the communication channel overlays the first and the second compartments. The barrier isolates the microorganisms in one compartment from those in another compartment, but allows culture products to pass between compartments via the communication channel in the upper layer. 
     The present invention also provides a device for co-incubating microorganisms, comprising a gel microdroplet. The gel microdroplet comprises at least two areas: a first area with a first microorganism and a second area with a second microorganism (different than the first). The first and second areas are physically separated by a distance x. The microorganisms are in a gel that prevents their migration from one area to another. Alternatively, the two areas can be separated by a layer that prevents their commingling. 
     One important feature of the devices of the present invention is that they provide for compartmentalized culturing of microorganisms. A compartment may refer to separate division or section and can take a variety of forms, geometries, and shapes, e.g. it can be a well, chamber, channel, droplet, bead, plug, etc. In general, what is important is that the compartment provides for a confined area where a particular type of microorganism may be cultured without being intermixed with a different type of microorganism. Thus, a multitude (two or more) compartments provide culturing space of two or more different species of microorganisms without any cross-contaminations. Localized growth of a single microbial type (e.g. strain, species) in a single compartment is important for the confined culturing method of these devices. From a single microbe these devices enable one to grow the microorganisms in a tiny separated culture compartment. Based on this concept, it may be possible to culture pre-mixed bacterial broth with several different species. By dilution and stochastic seeding into the culture compartments of a device, it is possible to culture a single species in a single culture well as long as the culture broth is diluted enough to adjust the appropriate cell density as the number of culture compartments in a device. 
     The devices of the present invention can be used in a method for co-incubating at least two different microorganisms such that at least one of the microorganisms performs a function differently than it would if the second organism was absent. This method can be used in various applications described below. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The invention can be better understood with reference to the following drawings and description. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the invention. 
         FIGS.  1 A- 1 G  are schematic drawings of a device for co-incubating microorganisms according to the present invention, which illustrates how individual microorganism (or microorganism culture) wells can be connected with various 3D spatial architectures. 
         FIGS.  2 A- 2 F  are schematic drawings that illustrate the concept of using stencils to control the loading of cells into compartments on a microfluidic device. 
         FIGS.  3 A- 3 C  show schematic drawings (a, c) and a graph (b) that illustrate the concept of how a synthetic community of three microorganism species requires spatial structure to maintain stable coexistence. 
         FIGS.  4 A-C  show graphs that illustrate how the stability of the community requires communication among the microbial species (three in the example shown). 
         FIGS.  5 A- 5 B  show a schematic drawing and microscopic images (a) and a graph (b) that illustrate the concept of how a synthetic microbial community only coexists at intermediate separations. 
         FIGS.  6 A- 6 I  show a schematic drawing and graphs illustrating a mathematical model of a two-species syntrophic microbial community. 
         FIGS.  7 A- 7 C  show schematic drawings that illustrate some possible embodiments of co-incubating of microorganisms using gel microdroplets (GMDs). 
         FIGS.  8 A- 8 C  show one schematic drawing and two microscopic images of the plug-based microfluidic techniques can be used to generate gel microdroplets for spatially structured co-incubates of microbial cells. 
         FIGS.  9 A- 9 F  are schematic drawings that illustrate embodiments of the methods of encapsulation a plurality of microbial cells. 
         FIG.  10   . Amplification of a small particle by stochastic confinement and autocatalytic amplification in microfluidic plugs. When a sample containing a low concentration of analyte particles and many interfering particles is isolated into plugs, the concentration of analyte particles will increase in each plug. An above-threshold response in an individual plug will initiate a multi-stage amplification reaction for macroscale output, illustrated here as the change in color of a plug. 
         FIG.  11   . Two-stage, threshold-dependent amplification in a chemical and microfluidic system achieved 5000-fold amplification. (a) Schematic drawing shows the two-stage amplification device, (b) An image of the microfluidic channel shows the transition point of the autocatalytic reaction from below the threshold Co2+ (purple plugs) to above the threshold Co2+ (colorless plugs). (c) Distribution of reaction times in the lame section for varied [Co2+] input in Stage 1. Frequency is defined as the number of microphotographs displaying a particular transition time. 
         FIG.  12   . Characterizing and recreating the mechanism of amplification in blood coagulation. (A) The network of blood coagulation uses ˜80 reactions to perform threshold-dependent amplification and the formation of a solid clot. (B) A graph illustrates the proposed kinetic mechanism for threshold-dependent amplification in the coagulation cascade. (C) The mechanism of amplification was recreated in a synthetic chemical model system. (D) Predictions made by the chemical model were confirmed with human blood plasma. indicating that the proposed mechanism is reasonable. 
         FIG.  13   . Blood coagulation can be used to detect  B. anthracis . (A and B) Clusters of  B. anthracis  cause blood coagulation (blue fluorescence) on a surface (A) and in a test tube (B left), but not when dispersed in solution (Bright). (C) InhAl, a secreted protease of  B. anthracis . is able to activate thrombin generation and initiate blood coagulation. 
         FIG.  14   . Confinement of bacteria into plugs reduces bacterial detection time. (a) Bacteria are combined with a viability indicator (red fluorescence) and confined into nanoliter-sized plugs. Most plugs are empty, but a few are occupied by single bacterium at a cell density greater than the initial cell density. (b) The same cell culture was incubated at 37° C. for 2.8 h in nanoliter-sized plugs and at the milliliter-scale. After incubation, the milliliter scale culture was used to form plugs. Confining the bacteria at t=0 led to a few occupied plugs with a high fluorescence intensity and many empty plugs with low intensity (solid line). All plugs made from mL scale culture had an intermediate intensity (dotted line). (c) When confining single bacterium into plugs, the detection time decreased with the log of the plug volume. (d) The detection times measured for bacteria incubated in plugs (circles) were similar to detection times measured for bacteria incubated in 96 well plates (crosses) with similar initial cell densities. 
         FIG.  15   . On the left, a series of plugs of contains different concentrations of interfering particles and analyte particle, where darker plugs contain a higher concentration of analyte particles than lighter plugs. While the lighter colored plugs (three bottom plugs) are below threshold of detection and give no macroscale output signal, the darker colored plugs (three top plugs) exceed threshold of detection and give macroscale output signal, illustrated here a color change reaction to a red color. 
         FIG.  16   . Basis set of rate laws; these functions were given arbitrary parameters for better display. Markers were provided purely to distinguish different curves of exact functions. 
         FIG.  17   . Examples of different combinations of production rate (solid lines) and consumption rate (dotted lines). 
         FIG.  18   . Rate plots show examples of modifications to threshold amplification schemes with sigmoidal production rate and 1st-order consumption rate by (A) reduction of slope of consumption rate. (B) upward translation of production rate, and (C) left translation of both production rate and consumption rate. Markers were provided purely to distinguish different curves of exact functions. 
         FIG.  19   , Concept of stimulus driven two-stage amplification with signal amplification. A minimal stimulus above threshold level is input to autocatalytic reaction with non-linear amplified output. Output (designated as C) is input into a second autocatalytic reaction with output (designated as E) detectable on macroscopic level. 
         FIG.  20   . The autocatalytic blood coagulation reaction network. 
         FIG.  21   . The autocatalytic caspase reaction network. 
         FIG.  22   . Stochastic confinement of particles by (A) encapsulation in droplets, (B) placement in pores of a membrane, and (C) confinement on materials with restricted transport. Confinement will separate target particles (red circles) from interfering particles (black triangles) for single particle measurements and will concentrate molecules attached to or secreted by the particle. 
         FIG.  23   , Confinement schemes for analyte detection. (A) Particles can be stochastically confined into plugs and then undergo two-stage amplification on chip to give a microscale readout. (B) Membranes can be used to confine particles. Active particles then translate their activity to a signal seen by the naked eye on an upper layer. (C) Particles trapped in a gel are also confined by restricted transport. Amplification cascades incorporated into a gel will localize the output signal over the active particle. 
         FIG.  24   . Scheme for detecting active and inactive particles. In a solution of both target (large gray circles) and non-target (small gray circles) particles (A), inactive particles can be decorated with antibodies or small peptides (B). Decorated target particles (red) can be separated from non-target particles (blue) and concentrated by stochastic confinement (B) for rapid detection and optical readout (D) These results from Objective 2 will lay a foundation for performing detection experiments outlined in Objective 3. 
         FIG.  25   . Proposed two-step amplification reconstructed from blood coagulation factors. Two loops of amplification with a final degree of amplification of 10 5.    
         FIG.  26   , Combining amplification cascades with stochastic confinement will enable sensitive detection of single particles. (A and B) Ni-NTA beads will be added to a beaker containing the protease InhAl. (C) The beads will bind to the protease and will be stochastically confined in plugs. (D) In plugs loaded with beads. the concentration of protease will be above the detection threshold and produce a threshold signal, while plugs without beads will not. (E and F) In solutions with excess but sub-threshold concentrations of protease, stochastic confinement of beads into plugs (G) will result in a few plugs containing a bead with multiple copies of the protease attached and many plugs with a few copies of protease, (H) Plugs containing a bead will initiate the cascade, because stochastic confinement of the beads will concentrate the protease in occupied plugs, whereas plugs without a bead will remain at the sub-threshold protease concentration of the bulk solution. 
         FIG.  27   . Selective detection of bacteria by using stochastic confinement. (A and B) In a bulk solution containing both a high concentration of  B. circulans  (low protease activity, small gray particles) and a low concentration of target  B. anthracis  (high protease activity. large gray particle), the protease activity of the excess  B. circulans  will dominate. Therefore, solutions with excess  B. circulans  alone (A) and excess  B. circulans  with a low concentration of  B. anthracis  (B) will both trigger a detection response (pink). (C and D) When stochasticly confined in plugs, the protease activity in each plug made from solution A will remain below the detectible level, while the protease activity of plugs containing  B. anthracis  from solution B will result in optical detection of  B. anthracis  (pink plug) and not interfering bacteria (dark gray plugs). 
         FIG.  28   . Stochastic confinement of single bacterium into nL plugs enables rapid screening against multiple antibiotics. 
         FIG.  29    Stochastic confinement of bacteria into plugs reduces detection time. (a) A schematic drawing illustrates the increase in cell density resulting from the stochastic confinement of an individual bacterium in a nanoliter-sized plug. While most plugs are empty, a few are occupied by a single bacterium at an effective concentration greater than the initial concentration. (b) A schematic drawing illustrates the experimental procedure to compare the detection of bacteria incubated in nanoliter-sized plugs and bacteria incubated in a milliliter-scale culture. See text for details. Line scans indicate that confining the bacteria a the beginning of incubation (t=0), led to a few occupied plugs with a high fluorescence intensity and many empty plugs with low fluorescence intensity (solid line). All plugs made from the milliliter-scale culture had an intermediate intensity (dotted line). (c) When confining single bacterium into plugs, the detection time decreased with the log of the plug volume. (d) The detection times measured for bacteria incubated in plugs (circles) were similar to detection times measured for bacteria incubated in 96 well plates (crosses) with similar initial cell densities. 
         FIG.  30   . A combination of stochastic confinement with microfluidic hybrid method was used to screen many antibiotics against the same bacterial sample. (a) A schematic drawing illustrates the formation of plugs of bacteria, viability indicator, and antibiotic from a preformed array of plugs of different antibiotics. Approximately 50 plugs were formed with each antibiotic in the screen. (b) The increase in fluorescence intensity of the control plugs with no antibiotic (+, blank-1, positive control) and vancomycin (β˜, VCM, negative control) are shown. After incubation, four plugs contained live bacteria in the control sample, but no plugs contained live bacteria in the sample treated with Vancomycin, indicating that bacteria were not resistant to this antibiotic. (c) A bar graph shows the results of the antibiotic screen against the Methicillin Resistant  S. aureus  (MRSA), indicating that this strain of MRSA was resistant to four antibiotics, but sensitive to two. The bars show the average increase in fluorescence intensity of all plugs that were above (solid) or below (striped) the 3 times intensity of the VCM baseline (see methods for details). N. shown above each bar, equals the number of plugs for each condition, and the error bars show standard error. (d) A chart shows the agreement between the susceptibility profiles (S, sensitive and R, resistant) of MRSA determined by the plug-based microfluidic screen and the control susceptibility screen using Mueller Hinton plates. 
         FIG.  31   . A microfluidic device was used to identify the minimal inhibitory concentration (MIC) of cefoxitin (CFX) for Methicillin Sensitive  S. aureus  (MSSA) and Methacillin Resistant  S. aureus  (MRSA). (a) A schematic drawing illustrates formation of plugs of bacteria, viability indicator, and an antibiotic at varying concentrations. In the schematic, numbers inside the pre-formed plugs symbolize the concentration of CFX in those plugs. (band c) Using 24 mg/L CFX as the baseline, graphs show the average change in intensity of plugs greater than (solid) and less than (striped) 3 times the baseline for MRSA (b) and MSSA (c), N, shown above each bar, equals the number of plugs for each condition, and the error bars show standard error. These results indicated that MRSA has a higher MIC than MSSA. 
         FIG.  32   . A combination of stochastic confinement with the plug-based microfluidic assay was used to determine susceptibility of bacteria to an antibiotic in a natural matrix, blood plasma. (a) A schematic drawing illustrates formation of plugs of bacteria, viability indicator, antibiotic, and plasma/LB mixture. (b and c) Images and linescans of four representative plugs made from a 1:1 blood plasma/LB sample inoculated with MRSA without (left) and with (right) the addition of AMP. (d and e) Images and linescans of four representative plugs made from a 1:1 blood plasma/LB sample inoculated with MSSA without (left) and with (right) the addition of AMP. Linescans show change in fluorescence intensity (FI) across width of the images for plugs at t=0 (red dashed line) and t=7.5 =h (solid blue line), The scale bar in (b) applies to all images. All images were contrast-enhanced for clarity and should be interpreted qualitatively: line scans of raw intensities are provided to convey the information quantitatively. 
     
    
    
     DETAILED DESCRIPTION OF THE PRESENTLY PREFERRED EMBODIMENTS 
     For the purpose of promoting an understanding of the principles of the invention, reference will now be made to certain preferred embodiments thereof and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of the invention is thereby intended. Any alterations, further modifications and applications of the principles of the invention as described herein are being contemplated as would normally occur to one skilled in the art to which the invention relates. 
     Certain features disclosed in the below-referenced patents, patent applications, and other references are related to the present invention and their disclosures are herein incorporated by reference. 
     Definitions 
     In biological terms, a “community” is a group of interacting organisms sharing an environment. A “microbial community” is a community of microorganisms, i.e. microbes. The term “microorganism” refers to both refers to both prokaryotic and eukaryotic microorganisms, including, for example bacteria, protozoa, viruses, or fungi. In microbial communities, resources, preferences, and a number of other conditions may be present and common, affecting the identity of the community members and their degree of cohesiveness. As one example of a microbial community, a gut bacterial community refers to the collection of discrete bacterial species that are present in the gut, and that may contribute to each others&#39; survival by providing nutrients or processing wastes. It is contemplated that the term “microbial community” refers to two or more different microbes, or populations of microbes. A microbial community (or simply “community”) could thus include two or more microorganisms, two or more strains, two or more species, two or more genera, two or more families, or any mixtures of the above. The interaction between the two or more community members may take different forms. For example, interactions among various community members may be competitive, they may be mutually beneficial, or they may be mutually harmful (e.g., via production of toxic products, competition for nutrients, etc), as long as the interactions together can provide a function or a structure that is not available through either one individual community member. The devices and methods of the present invention might provide one or more community members with conditions that allow those members to perform certain function while reducing accompanying undesirable or harmful effects. In one embodiment, the present invention provides for conditions that enable culturing of microorganisms that in nature prefer mutually less compatible, incompatible, or exclusive conditions, such as different partial concentration of oxygen, different pH, different composition of nutrients, etc. The cultivation of some microbial communities may require externally controlled environments that can be provided according to the present invention. Some microbial communities may distinguish themselves by producing, consuming, modifying, degrading, and/or accumulating particular compounds. There are also microbial communities that can over time themselves create preferred different environments (e.g. aerobic, anaerobic, facultative anaerobic, etc.), again by producing, consuming, modifying, degrading, and/or accumulating particular compounds. The practice of the present invention specifically contemplates all of the above types of microbial communities. 
     In biological terms, “culture” is the act or process of cultivating living material (as microbes, e.g. bacteria or viruses) in prepared nutrient media; culture also refers to a product of such cultivation. Culturing of microorganisms may be performed by inoculating a known concentration of microorganisms into a solution (culture medium typically containing nutrient media; optionally nutrient media that is modified, that contains desired additives, etc.) and measuring growth over time. Growth of cultured microorganisms can be measured in a variety of ways, including direct counts of microorganisms, plate counts of colony forming units, and turbidimetric measurements. 
     “Culture medium” (also called “nutrient medium”, “growth medium”, and “medium”) refers to a substance, either solid or liquid, used for the incubation, cultivation, isolation, identification, or storage of microorganisms. Culture medium may include various components such as nutrients and optionally a variety of additives, including minerals, vitamins, amino acids, peptides, hormones, cell culture extracts of unknown composition, cell lysates of unknown composition, etc. The composition of the culture medium may differ when different types of microorganisms are cultured. The culture medium may optionally be modified (e.g. some compounds may be omitted from the culture medium when one wants to starve the microorganisms, or one wants to apply selection pressure). 
     “Co-incubation” of microorganisms refers to joint incubation or incubation together, of two or more types (e.g. organisms, populations, strains, species, genera, families, etc.) of microorganisms. In the context of the present invention, co-incubation of microorganisms refers to the joint incubation of two or more types of microorganisms in a microbial community. Co-incubation of microorganisms is also meant to include co-culture (i.e., joint culture, or culture together) of microorganisms, but growth is not required for co-incubation. 
     “Syntrophy” refers to a biological relationship in which microorganisms of two or more different species or strains are mutually dependent on one another for nutritional requirements. A set of such microorganisms are “syntrophic.” Communities may perform “syntrophic functions” if the function is dependent on the exchange of chemicals/enzymes/molecules/proteins/genetic material. A “syntrophic function” requires at least two community members to be present and the role of at least one community member is dependent on a chemical received from at least one other community member. While in some embodiments of co-incubation the co-incubated microorganisms can be syntrophs, not all embodiments of the present invention require this feature. Community function thus refers to a syntrophic function, or any other function that is enhanced by the co-incubation of more than one organism in the community, and includes functions such as such as growth of microorganisms, degradation or removal of external components, production of incubation components, etc. 
     An “antimicrobial” is a substance (e.g., drug) that kills or inhibits the growth of microbes (microorganisms) such as bacteria, fungi, or viruses. Antimicrobials either kill microbes (microbicidal) or prevent the growth of microbes (microbistatic). Antimicrobials include antibiotics, antivirals, antifungals, antiparasitics, and synthetically formed compounds as well. The antimicrobials used in the practice of the present invention also may be non-pharmaceutical, for example they may include essential oils having antimicrobial activity, heavy metal cations (e.g., colloidal silver, Hg 2+ , Cu 2+ , Pb 2+ ) having antimicrobial activity, etc. 
     Microfabricated Devices 
     The present invention provides a device for culturing microorganisms, comprising (a) a lower layer comprising a first compartment and a second compartment, physically separated from the first compartment by a distance x, (b) an upper layer comprising a communication channel; and (c) a barrier positioned between the lower layer and upper layer, wherein the barrier is impermeable to the microorganisms and permeable to soluble compounds; wherein the lower layer and the upper layer are positioned such that the communication channel overlays the first and the second compartments. 
     In one embodiment, the device of the invention may have dimensions between about 0.3 cm to about 15 cm per side and thickness of about 1 μm to about 1 cm, but the dimensions may also lie outside these ranges. The surface of the upper and lower layers can be smooth or patterned. When multiple layers are present, different layers can have different surfaces. 
     The upper and lower layers can be formed from a suitable material such as a polymer, metal, glass, composite, or other relatively inert materials. 
     The compartments of the upper layer are sized and shaped to be suitable for culturing a microorganism. The upper layer comprises at least two compartments (See  FIGS.  1 A- 1 G , compartments A and B). Any number of compartments can be present (See  FIGS.  1 A-G , compartments A-D). 
     The compartments are separated by a distance x. In general, the distance can be anything that allows physical separation of the microorganisms. Typically, it is between about 50 μm and about 500 μm, preferably between 100 μm and about 300 μm. 
     The compartments may be connected to culture media channels to allow addition, removal or continuously replacement of culture media in the compartments. 
     In some examples (e.g. for high throughput experimentation), multiple upper layers (i.e., those containing compartments) can be present. In this embodiment, one upper layer may contain a set of compartments with one set of microorganisms, and another upper layer may contain another set of microorganisms. A lower layer could then be positioned between with two upper layers with a barrier layer separating each upper layer from the lower layer (the barrier layers could be the same or different). More than two layers may be used in the fabrication of the device as well. 
     The communication channel is sized and shaped such that when the upper layer is positioned over the lower layer, the channel overlays (or links) at least two compartments. Multiple communication channels can be present. In some cases all the communication channels will overlay the same compartments (parallel). In some cases, the entire lower layer can be the communication channel. 
     Typically, the communication channel is larger than the distance x between the two compartments, so as to overlap into each compartment. Typically it is between about 50 μm and about 500 μm, preferably between 100 μm and about 300 μm. 
     The compartments may be connected non-directionally (e.g., by diffusion through the communication channel) or directionally (e.g., using flow through the communication channel). Alternatively, compartments may be connected to combinations of other compartments using both non-directional and directional communication channels. Some compartments may not have influx of nutrients (e.g. by controlling flow away from those compartments or by using barriers impermeable to those nutrients). 
     When multiple compartments are present in the upper layer, the communication channel(s) can overlay all of the compartments or just select compartments. In the latter case, further channels can be present to link further compartments (See  FIGS.  1 A- 1 G , compartments A and B, B and C, B and D, and C and D linked via channels). 
     The barrier is a structure that blocks passage of microorganisms from one compartment to another, but allows soluble compounds to pass from one compartment to another. The barrier according to the present invention can be a membrane, gel, nanostructure, pore, or any other structure that is not permeable to microorganisms but permeable to components of interest, such as molecules, complexes, assemblies, etc. Examples of membranes useful in the culture of bacteria are shown in Kaeberlein et al., 2002,  Science,  296: 1127-1129, incorporated herein by reference. In certain embodiments of the invention, the barrier itself may include one or more desired molecules, one or more cells, or one or more microorganisms; for example, the barrier may include a biofilm. 
     The dimensions, geometry, and size of the barriers may vary and will depend on the microorganisms that need to be confined and/or separated. For example, if the goal is to co-incubate bacteria, the general size of bacteria is about 2-3 μm. The sizes of the barriers that separate the bacterial compartments should be approximately below about 0.1 μm. The typical cut-off size of membrane for the filtration of bacterial culture broth is about 0.45 μm, but in some cases smaller size of bacteria can be shown. In terms of bacterial moving, migrations speed of bacteria has been known as 5-10 μm/s. In general, the devices of the present invention should be able to deliver fresh media or stimuli to the microbes, while allowing communication among colonies. 
     In an alternate embodiment, barriers are not present and the microorganisms are instead tethered/trapped in the compartments (for example, in gel particles, posts or other traps). 
     The compartments and communication channels can have different dimensions and geometries such as length, width, thickness, depth, and can also have different form of cross-sections, including square, rectangle, triangle, circular cross-section, etc. The compartments, channels, etc. can also have different dimensions and geometries ( FIGS.  1 A- 4 C ). 
     In one example of a device of the present invention, the upper layer comprises 100 nm culture wells separated from each by approximately 500 μm. In the lower layer, a communication channel overlays the wells in the upper layer. A polycarbonate membrane separates the upper and lower wells. Above the culture wells, each culture well may be connected with individual media channels of 5 μm hole (Ismagilov et al., 2001,  J. Anal. Chem.  73: 5207-5213). 
     Droplets 
     The present invention also provides droplets for co-incubating microorganisms. The droplets comprise at least two areas: a first area with a first microorganism and a second area with a second microorganism (different than the first). The first and second areas are physically separated by a distance x. The droplets are composed of a material that prevents migration of microorganisms from one area to another. Alternatively, the two areas can be separated by a layer that prevents their commingling. 
     In general, a “droplet” refers to a relatively small volume of material. Droplets according to this invention can be polymeric or solid particles, gel microdroplets, beads, or plugs. 
     Suitable droplets may have different shapes and sizes. The droplets may have different sizes and geometries, and may be symmetric or asymmetric. For example, droplets may refer to a single sphere or oval, may refer to a core-shell configuration, to a group of smaller particles attached together (e.g. to form grape-like structure), to a string of particles some of which are in contact with each other, etc. In general, the droplets have a volume of between about 1×10 −9  microliters to about 1×10 3  microliters. If spherical or roughly spherical, the droplets typically have a diameter between about 1 μm to about 1.00 mm, and preferably between about 1 μm and about 500 μm. 
     Droplets may contain two or more, if desired multiple, types of microorganisms or colonies of microorganisms. Each type of microorganisms may be positioned anywhere in or on the droplets (so long as at least one type is confined from at least one other type). Alternatively, microorganisms may be encapsulated in the droplets. 
     Gel Microdroplets 
     A “gel microdroplet” (GMD)(also referred to herein as a gel bead, or a gel particle) refers to very small droplets, i.e. very small volume entities comprised of gel (and optionally liquid) material, and which can contain zero, one or multiple biological entities. For example, two or more types of bacteria may be encapsulated in agarose GMDs. In particular, aqueous droplets containing bacteria, growth media, and liquid agarose may be formed in fluorinated oil. The GMDs may optionally contain inorganic and/or organic chemical compounds; these compounds may optionally be in solution. GMDs have volumes which may be defined by a boundary comprised of another liquid, such as a non-aqueous fluid, or by a permeability barrier such as a membrane, such that the membrane is capable of retaining biological entities (e.g. microbes) of interest within a GMD, and also capable of passing other biological entities such as molecules (smaller than microbes). For example, it would be possible to generate two or more streams of two or more different microorganism strains, then combine them into a single droplet, and then polymerize it into a GMD (e.g. agarose GMD), where the microorganism strains are compartmentalized and spatially separated, i.e. they are not in direct contact with each other. Although GMDs can be of any shape, GMDs are often approximately spherical because of the tendency of forces associated with the boundaries of GMDs to round up the deformable GMDs. Other forces, for example hydro-dynamic shear associated with stirring a GMD suspension, adhesion to a surface, or gravity, tend to cause departure from a spherical shape. Further, GMDs which contain or occupied by entities whose volume is a relatively large fraction of the GMD volume can result in GMDs which are non-spherical. Thus, for example, cell or a population of cells surrounded by a thin gel coating (and optionally with an aqueous solution), which in turn is surrounded by a non-aqueous fluid, is a GMD. Similarly, a non-biological particle s surrounded by a thin gel coating (and optionally with an aqueous solution), which in turn is surrounded by a non-aqueous fluid, is also a GMD. 
     When spherical, GMDs have diameters between about 1 μm to about 30 mm, and preferably between about 5 μm and about 1000 μm. Generally, GMD volumes are between about 1×10 −12  to about 10 ml, preferably between about 1×10 −10  to about 1 ml.  FIGS.  7 A- 7 C  schematically illustrate some possible embodiments of co-incubating of microorganisms using GMDs. Examples of various encapsulating approaches are shown. The inventors have been able to grow microbial cultures in certain types of GMDs. 
     Various types of gels can be used in the practice of the invention. They include: standard gel, when growth and potential of mixing of bacteria is slow or is not a concern; gels that are impermeable to microorganisms, so the microorganisms do not move through the gel; and arbitrary gels, where the interfaces among the gels have membranes impermeable to microorganisms, yet permeable to desired chemicals. When generating gel beads, such membranes could be formed chemically as the beads are being made, e.g. by reacting two polymers on the surface of the bead, or by incorporating those two polymers into the individual gels, so at interfaces of gels membranes form. The formation of gel or polymeric substances in a plugs could also be initiated by an externally by light, temperature change, additional of a small molecule, pH change, pressure change, contact with carrier fluid, or contact with channel walls. 
     It is possible to insert a relatively hydrophobic intermediate layer between the layers including different species 1 and 2. For example, a single GMD can comprise the one half spheres of species 1 and the other half sphere of species 2, and between the half spheres a disk-like layer is inserted. This disk-like layer provides relatively hydrophobic environments, which enhance the mass transport of hydrophobic compounds (products, intermediates, etc.). Biosynthesis via co-incubation of species 1 and 2 can be promoted by the intermediate layer that induces close contact of hydrophobic compounds near the each layer. 
     In another embodiment, a two-layer GMD microfluidic device, which is separated by the relatively hydrophobic intermediate layer, can be used. On both sides of layers, different species of 1 and 2 are inoculated for the co-incubation, then the hydrophobic precursor A by species 1 can easily migrate to intermediate layer, then the species 2 tightly connected into the intermediate layer convert the precursor A into the final product X. 
     As well, it is possible to use a double-layered GMD, which is constructed by the core sphere of species 1, and the species 2 covers the core like shell. Between the core and shell of GMD, relatively hydrophobic intermediate layer is inserted. Examples of relatively hydrophobic intermediate layers can be found in Femandez-Lafuente et al., 1998, Chemistry and Physics of Lipids 93: 185-197. 
     The processes for making gel microdroplets may involve forming first GMDs, and subsequently processes for forming GMDs where the first GMDs are incorporated within second GMDs. This yields GMDs with two or more distinguishable regions, and can be extended to the formation of composite GMDs with a plurality of distinguishable gel regions. The various gel regions can be provided with different properties, or used to entrap biological entities at different relative locations within GMDs, or used to provide or entrap assay-assisting entities at different locations within GMDs. Further, one or more gel regions can be subsequently liquefied, such that composite GMDs with one or more interior liquid regions are formed. Composite GMDs may also be formed where two or more types (e.g. species) of microorganisms are mixed together. Thus, in some embodiments of the present invention, gel droplets or other types of particles that would structure the position of microbial cells (by imposing boundaries on the movement of cells within in the particle, either by immobilizing them in a gel or having a particle with liquid compartments separated by a barrier) can be used to create co-incubated cultures of cells with spatial structure. Several methods have been established for the creation of such particles, including using microfluidic techniques to generate Janus (two-sided) particles and either using a gelation mechanism or polymerization process to make the structure of the particle permanent. Such particles could also be made using micromolding techniques or self-assembly techniques. Important parameters in the design of a particle for co-incubation include: 1) distance between the different types of cells; 2) total size of the particle; 3) the volume of the particle available to each type of cell; 4) length of the diffusion path connecting the different cell types to each other and also to the external environment (tortuosity of the path and iterations of various molecules with the particle material); 5) ratio of the number of different types of compartments; 6) the topology of network of compartments inside particles (side by side, inside vs. outside, 3 compartments connected in a line vs. in a triangle, which compartments have access to external environment); 7) compartments in which some types of cells are excluded but not others (partial mixing of some compartments). 
     In some embodiments, this invention contemplates the use of GMD particle technology to generate co-incubated cultures that can be used in a fermentation tank, or spread around the environment to degrade unwanted stuff or accumulate desirable stuff (gold, plutonium, etc.) One way to practice this invention is to create GMDs (layer by layer, or composites) that get better results than simply mixing microorganisms in a flask (for example, locally high concentration of metabolites, local consumption of waste, or a combination of high oxygen outside and low oxygen inside the particles—something that would typically be hard to do in a single fermentation tank). In addition, it is possible to control whether microorganisms mix or don&#39;t mix before microdroplets polymerize. 
     The present invention contemplates encapsulation of microbial cells. Encapsulation may be used for making GMD-like particles and enclosures. Aspects useful for encapsulating confined and separated microbial communities may be found in, for example: United States Patent Application Pub. No. 20060051329 (microfluidic device for the encapsulation of cells with low and high cell densities); in Green et al., 2008,  Advanced Functional Materials  15: 917-923 (biomineralized polysaccharide capsules for encapsulation, organization, and delivery of human cell types and growth factors), all of which are incorporated herein by reference. Thus, in one aspect, this invention provides for the generation of bead-in-bead capsules consisting of spatially separated cell populations and with temporally separated biomolecule release. 
     Beads 
     In another embodiment, the droplets contains two or more beads. Each bead can be of the same or different type, shape, and size. Beads may be connected. The beads may be gel beads, for example they may be agarose beads. By putting individual strains or species of microorganisms onto beads (where each bead has only one strain or species), and then mixing beads in the right ratios, a community can be created that includes a variety of members, e.g. members who are toxic to one another on contact. Compound beads may be generated as well, with one type of microorganism in each half (or part) of the bead. Layered beads may be generated, where each layer will have discrete types of microorganisms. 
     The beads may be in homogeneous or heterogeneous layers of the microdroplet, e.g. the microdroplet may be core-shell, side-by-side, etc. 
     Intermediate layers may be used to create additional spacing (distance) between the microorganisms. Such intermediate layers may or may not have microorganisms. One layer containing one type of microbes may be surrounded (coated) by another layer containing another type of microbes, etc. Multiple layers may be used, to produce multilayered beads with a plurality of microbes. The bead assembly could rely on surface tension or the Torii or Weitz methods for making double emulsions (Nisisako et al., 2005,  Soft Matter  1: 23-27; Utada et al., 2005,  Science  308: 537-541. 
       FIGS.  7 A- 9 F  illustrate schematics of various examples of droplets useful for practicing the present invention. 
     In some examples, by making beads magnetic, the beads can be distributed in the desired area, e.g. environment, and then easily picked up when desired, for example, by using an electromagnet or a permanent magnet, when the beads are no longer needed. 
     Plugs 
     Droplets can be liquid (usually aqueous) which exists either in a two-phase system (e.g., organic phase/aqueous phase, fluorous phase/aqueous phase) or in a single phase with an emulsifying agent/surfactant (e.g., aqueous droplets surrounded by aqueous bulk solution). A “plug” is a specific type of droplet (Song et al., 2006,  Angew. Chem. Int. Ed.  45: 7336-7356; Chen et al., 2006,  Curr. Opin. Chem. Bio.  10: 226-231). 
     Formation of liquid plugs was previously described by this inventor in U.S. Pat. No. 7,129,091. In the present invention, different types of microorganisms are introduced into different plug fluids. 
     Methods of incorporating multiple and different microbes into a spatially structured plug include combination of fluids containing microbes with fluids containing components necessary to form a gel or a polymer or a solid matrix. Upon forming the plug, the different types of microbes would have a non-uniform spatial distribution throughout the plug and this initial spatial distribution can be controlled using microfluidic techniques such as laminar flow of multiple streams. Before the microbes are able to substantially intermix, the components would form a gel or a polymer or a solid matrix and prevent significant further intermixing of the microbes. In this way, the non-uniform distribution of the microbes in the plug would be preserved. Formation of a gel or a polymer or a solid matrix could be accomplished in a number of ways, including spontaneous formation, as takes place when a supercooled gel or solid transitions from a liquid state into a gel or solid state; stimulation formation, as takes place when pressure, temperature or UV or visible light or another form of radiation is applied, or a chemical reagent is added. Chemical reagents include cross-linking agents, changes in pH, change in ionic composition, or the additional of a small molecule, ions, or a macromolecule. Chemical reagents may be pre-loaded into the plug fluids, or added after the formation of a plug. 
     In addition, methods of incorporating multiple and different microbes into a spatially structured plug include sequentially forming layers containing microbes. In this method, a plug containing microbe A would be coated with a barrier layer consisting of either a gel or a polymer or a solid matrix that would inhibit the movement of microbes across the barrier. A layer of microbe B could then be formed outside of the barrier layer. In this way, microbes A and B would exist in the same plug separated by a barrier which prevents microbes A and B from mixing. Controlling the type of barrier layer, the thickness of the barrier layer, and the number of barrier layers in the plug could be used to control the spatial structure of the plug containing multiple types of microbes. The barrier layer may not be always necessary in these applications. If the gel or a polymer or a solid matrix in which either microorganism A or B are embedded do not allow migration of the organism, the barrier layer is not required. 
     In addition, methods of incorporating multiple and different microbes into a spatially structured plug include combinations of plugs into larger objects. A plug is made containing microbe A. A separate plug is made containing microbe B. The plugs form a gel of polymeric matrix using methods described above. The plugs are then physically combined such that there is a chemical exchange path connecting the microbes A and B. Additionally, separator plugs could be used to control the amount of space between the plug containing microbe A and the plug containing microbe B. 
     Another method of using plugs to co-incubate multiple microbes in a structured space would be to allow the carrier fluid of the plug to transport chemicals between adjacent plugs. In this way, plugs containing different microbes could be positioned in a microfluidic device and adjacent plugs could exchange chemical information. 
     Forming particles containing multiple interacting microorganisms is not limited to the use of plugs. Beads or gel or solid or polymer particles containing microorganisms may be directly combined into larger objects containing multiple interacting microorganisms. A barrier layer impermeable to microorganisms but permeable to exchanging molecules may be used to bind particles containing different microorganisms together. Alternatively, such particles may be held together by an external membrane impermeable to microorganisms but permeable to exchanging molecules. 
     Forming particles containing multiple interacting microorganisms may be accomplished by generating a long string of gel or a polymer or a solid matrix containing the first microorganism, generating a long string of a gel or a polymer or a solid matrix containing the second microorganism, then connecting the two strings lengthwise, and then cutting the combined strings perpendicular to the direction of the strings to produce particles containing both organisms. Strings may be obtained by extrusion or any other method commonly used for forming polymeric fibers. This method is not limited to two strings; three or more strings may be used in this way to produce particles containing three or more different microorganisms. 
     Forming particles containing multiple interacting microorganisms may be accomplished by generating a sheet of gel or a polymer or a solid matrix containing the first microorganism, generating a sheet of a gel or a polymer or a solid matrix containing the second microorganism, then connecting the two sheets face to face, and then cutting the combined sheets perpendicular to their long dimensions to produce particles containing both organisms. Sheets may be obtained by extrusion, molding, or any other method commonly used for forming polymeric sheets and films. This method is not limited to two sheets; three or more sheets may be used in this way to produce particles containing three or more different microorganisms. 
     Forming particles containing multiple interacting microorganisms may be accomplished by direct molding, such as provided by Pattern Replication In Non-wetting Templates technologies such as that provided by Liquidia technologies (described, for example, in US 2007/0178133 A1 and http://www.liquidia.com/technology_platform.html which are incorporated here by reference) 
     The methods described above can be used to construct communities of two or more different microbes. The spatial structure of the community can be controlled including: separation distance between the microbes, ratio of microbes inoculated, pattern of connectivity (for example three types of microbes with all three possible connections, versus three types of microbes connected with only two connections), total volume of the space, and tortuosity of chemical exchange path between microbes. 
     Plugs are especially suitable for applications that combine aerobic and anaerobic community or communities. In some embodiments, the structure of GMD can be suggested as a GMD sphere with two different layers, consisting of an inner core sphere and an outer covering shell. Since anaerobic microorganisms are sensitive to oxygen in the atmosphere, this strain should be immobilized inside the sphere of GMD. In the outer covering shell, aerobic microorganisms can be placed by immobilization. Both aerobes and anaerobes can do cross-talking by diffusion of chemicals they produce, but cells are physically entrapped in each side of the GMD sphere. Various parameters for tuning environment inside the GMD can be modulated such as diffusion path, porosity and tortuosity of gel matrices, etc. 
     Combinatorial Systems 
     Thus, useful for the practice of the present invention may be microfluidic devices (e.g. with compartments such as chambers or wells), droplets (e.g. beads or GMDs), or combinations thereof (e.g. combinations of channels with GMDs). 
     In some embodiments, this invention provides a novel combinatorial biosynthesis system by using a microfluidic device. This combinatorial biosynthesis system provides the cascade of continuous reaction centers. In a reaction center, different species of microorganisms are entrapped in the GMDs. At least two approaches are possible: use one bead with multiple microorganism strains; or use one microorganism strain per one bead, but beads are close together in a device to create a community, and optionally use controlled fluid flow to control communication among beads. In such a device, the reaction centers are connected with microchannels. This device takes advantage of the successive connections of reaction centers that are occupied by different strains of microorganisms. For example, compound X is synthesized from a substrate A and a substrate B. In this case, a complex reaction system comprising a reaction center 1 and a reaction center 2 can be provided. In a reaction center 1, species 1 producing a substrate A is deposited in a GMD. In a reaction center 2, species 2 producing a substrate B in deposited in a GMD. If these reaction centers are tightly incorporated with adjacent distance, but still physically separated in a microfluidic device, it is possible to make a continuous reaction system. Similar devices can be constructed for other synthetic schemes. 
     Furthermore, if one of the substrates is insoluble in the culture medium, e.g. hydrophobic (i.e. poorly soluble in water), it is possible to use a device having a separating layer that can selectively transport intermediates. Described herein are structures of devices for the biosynthesis via co-incubation of microbial communities, where the substrate is insoluble in the reaction media. There are many examples to enhance the water solubility of hydrophobic substrates via media engineering such as solubilization and dispersion in organic solvent media, biosynthesis in solid-phase media, or biosynthesis in eutectic media. However, it is still limited in single enzyme or single species biosynthesis. 
     Methods of Co-Incubating Microorganisms 
     The devices of the present invention can be used in a method for co-incubating at least two different microorganisms such that at least one of the microorganisms performs a function differently than it would if the second organism was absent. For example, a microorganism may produce an incubation product that it otherwise would not produce when the second microorganism is present. Alternatively, a microorganism may not produce an incubation product that it otherwise would produce when the second microorganism is present. Alternatively, a microorganism may change the amount of an incubation product produced when a second microorganism is present compared to when it is not. 
     Incubation products include gases, liquids, or solids, or amorphous materials. Examples of incubation products are the small molecules or mono-, oligo-, or polymeric compounds, for example, bioenergy materials such as methane gas, hydrogen gas, biodiesel (fatty acids methyl- or ethyl esters), isoprenoids, probiotics, prebiotics, amino acids, sugars and sugar derivatives, glycoproteins, proteins (such as bacterial ice nucleation proteins), enzymes (such as heat stable polymerases, lipases, esterases), anti microbial agents, biologically active compounds and industrial compounds including natural products, fine chemicals, food additives (texturizing agent, sweetener), functional cosmetic materials (emulsifier, skin moisturizing compounds, antiperspirants, deodorants, microemulsions, skin sanitizing compositions), health-care compounds (personal-care emulsions, hair care compounds, antioxidants, anti-aging agents, anti-cancer agent, anti-hypochondria), biologically active polymers (such as polyhydroxybutyric acids), polyphenolic compounds (such as flavonoids), and xenobiotics (such as utilizing nitroaromatic compounds o-nitrobenzoate (ONB), p-nitrophenol (PNP) and 4-nitrocatechol (NC) as the sole source of carbon, nitrogen and energy). In addition, examples of products include molecules or processes involved in the production of bio-electricity. Applications include agricultural applications (such as production of insecticidal delta-endotoxins, soil fertility), food manufacture (fermentation processes and flavor enhancement, food safety), health care industry, fine chemical industry, drug development, bio-inspired energy industry, and medical/medicinal applications. 
     In another embodiment, during the co-incubating step, the first microorganism degrades or otherwise removes an external component in an amount that differs from what it would otherwise degrade when the second microorganism is absent. 
     Examples of external components which could be degraded or removed are the mono-, oligo- or polymeric molecules. They can be gases, liquids, or solids, or amorphous materials. Examples of gas include greenhouse gases such as CO 2  and methane. For example, polymeric compounds cellulose, hemicellulose, lignin, hydrocarbon (such as n-alkanes), aromatic compounds and their derivatives (such as polychlorinated biphenyls), halogenated organic compounds, polycyclic aromatic hydrocarbons, petroleum fuel compounds (including fuel-contaminated soil or marine samples), complex xenobiotics (such as insecticides, herbicides, or pesticides), sludge compounds (including heavy metals), organic wastes compounds (such as carbon disulfide, organic pollutants), waste water (such as self-contained water remediation), compost compounds, methane, ammonia, phenol and its derivatives, plastics, and heterocyclic compound of sulfur, nitrogen, and oxygen (such as dibenzothiophenene or dibenzofuran). These examples of compounds are applicable to the applications for bioremediation (such as heavy metal bioremediation and chemoattraction), bioaugmentation, bioenergy generation, reduction of natural contaminants, natural polymer reductions, agricultural applications (such as digesting grasses, coating of legume seeds, such as beans and peas). 
     The devices of the present invention can be used for drug discovery. Examples of isolation and cultivation of microorganisms from natural environments and drug discovery based thereon are disclosed in U.S. Pat. No. 7,011,957, which is herein incorporated by reference. 
     The devices of the present invention can be used for high throughput or capillary-based screening for a bioactivity or biomolecule similar to methods disclosed in PCT Patent Application Publication No. WO05010169A2, which is herein incorporated by reference. 
     The devices of the present invention can be ingested by a patient (human, cow, cat, dog or other animal). In some embodiments, the devices contain at least two microorganisms. In this embodiment, the first microorganism that produces (or produces more of) a therapeutic product in the presence, versus absence, of the second microorganism. 
     In another embodiment of an ingested product, the devices again contain at least two microorganisms. In this embodiment, the first microorganism degrades an undesirable substance in the intestinal tract of the patient in the presence, but not absence, of the second microorganism. 
     There are numerous other applications of the methods of the present invention. The methods can be used to look for combinations of microorganisms that naturally compete for a specific resource. In some embodiments, different microorganisms or microorganism populations can be forced to compete, not by mixing them where they can outcompete—e.g. simply outeat—one another, but by keeping them on separate fluxes of nutrients, which are still coupled. So, if one microorganism type can kill the other, it would get more nutrients. For example, bacteria may be used to kill fungi, fungi may be used to kill bacteria, viruses may be used to kill bacteria, etc. (Cowen and Lindquist, 2005, Science 309: 2185-2819). An assay could be performed to determine if the microorganisms have relatively increased the secretion of compounds that can kill the other microorganisms. Spatial separation in this instance may be important to decouple food and waste killing from a more selective killing. Such interacting microorganism colonies may be used to culture microorganisms that cannot be cultured by other means. 
     Commercial applications for microbes and microbial products include: a) bioremediation and bioaugmentation. Microbes have been put to use degrading organic chemicals through direct metabolism (in which the microbe uses the material for food or energy) and through co-metabolism (through which the microbe apparently gains nothing). They have also been used to carry out chemical transformations of inorganic materials in order to make those products less mobile or bioavailable in the environment. Applications include both in situ treatment (at the site of contamination) and treatment of waste streams in manufacturing settings; b) aids in mining operations. Bacteria are used in microbial enriched oil recovery and to extract precious materials from ore; c) Probiotics. Numerous probiotics products (consumables containing microorganisms that are thought to offer health benefits) are available to consumers today. Probiotics are occasionally used in medical settings as well; patients are sometimes administered a collection of probiotic microorganisms to head off colonization by  Clostridium difficile  after a dose of broad-spectrum antimicrobials; d) Manufacture of biofuel and other energy products. Bacteria are used to digest corn and sugarcane in the manufacture of ethanol, and researchers are exploring their use in transforming chemical energy into electrical energy in microbial fuel cells; e) Agricultural applications. Bacteria are used to digest grasses and other fodder to make silage, a feed material that can be stored for use during winter months when pastures are not available. Also, legume seeds, such as beans and peas, are often coated with nitrogen-fixing bacteria prior to planting to ensure the plants develop the proper nitrogen-fixing communities. A gene that encodes the insecticidal delta-endotoxin of  Bacillus thuringiensis  (a bacterium commonly called Bt) has been inserted into certain crops to improve insect resistance, and the bacteria themselves are sometimes sprinkled on crops to limit infestations. Although the neurotoxins produced by  Clostridium botulinum  have been a persistent problem in the food canning industry, the botulinum toxin is used in the medical and cosmetic (Botox) industries. Finally, the bacterial compound monensin is used to increase digestion efficiency in dairy cattle; f) Food manufacture. Microorganisms are put to work in food manufacture in many different capacities, including fermentation processes and flavor enhancement. Microbes are also significant in terms of food spoilage and food safety. There have been enormous and frequent food recalls due to microbial contamination; g) Industrial applications. Heat stable enzymes isolated from thermophilic bacteria, like Taq, lipase, esterases and others, have proven extremely useful in biotechnology; h) Wastewater treatment. This exploits the natural capability of microorganisms to degrade and recycle the essential elements on Earth. Millions of tons of organic and inorganic waste are treated annually, and more and more of the energy contained in this waste is recovered as biogas (methane). Important advances have also been made in recycling of sulfur and heavy metals; i) Microbial enhanced oil recovery is an efficient alternative to improve oil recovery, especially in mature fields and in oil reservoirs with high paraffinic content. Some bacterial strains could be co-incubated and can find utility in oil recovery applications and for the prevention and control of paraffin deposits. These strains include:  Pseudomonas aeruginosa; Bacillus licheniformis; Bacillus brevis; Bacillus polymyxa; Micrococcus  varians;  Micrococcus  sp. and  Vibrio  sp. (Almeida et al., 2004,  Engineering in Life Sciences  4: 319-352); j) Application of microorganisms for the biodegradation of xenobiotics, especially xenobiotics that have accumulated in soil and water over the years, may include the use of  Burkholderia cepacia  and  Arthrobacter protophormiae , capable of utilizing nitroaromatic compounds o-nitrobenzoate (ONB), p-nitrophenol (PNP) and 4-nitrocatechol (NC) as the sole source of carbon, nitrogen and energy (Jain et al., 2005,  Current Science  89: 101-112); k) Other applications, such as manufacture of biodegradable plastics, green chemistry applications, and bacterial ice nucleation proteins are used in snow manufacture. 
     The methods can be used to identify microorganisms that secrete waste or other byproducts that could compromise the productivity of the other members of the community in a mixed culture. 
     In another embodiment, this invention could also be used to evolve strains of microorganisms that can kill undesirable strains of microorganisms. For example, an antibiotic-resistant strain of bacteria may be placed in chemical contact with another strain and the two strains may be stressed to compete for resources. Bacteria will evolve/adapt rapidly under stress, and it is possible that the second strain can evolve/adapt to kill the antibiotic-resistant strain. Analyzing the chemicals produced by the killer bacteria may provide new antibiotics/antibacterial molecules that will find utility in human medicine. In one example, sporulating  B. subtilis  are used, where sporulating cells induce lysis of un-sporulated cells to preserve resources. Microfluidics may allow performing these experiments in a high throughput format. 
     The devices of the present invention can be used to create an environment useful for testing the affects of environment changes on two or more populations of microorganisms. For example, after the systematic functional relationships of natural microorganism consortia are confirmed (e.g. symbiotic or syntrophic relationships), those relationships can be reproduced in the microfluidic devices of this invention. For example, a microbial community that degrades cellulose can be analyzed to understand the structure of the community, characteristics of each community member, functional correlation between members, and synergistic reactions in the community. Then, this community can be mimicked with different species that perform the same functions with better performance (e.g. higher enzymatic activity, better thermal stability, etc). In this process, it is possible to optimize the artificial community by creating synthetic community with different origin. One could thus make the “artificial symbiosis” system based on the mimicry of natural symbiosis. The major difference between artificial symbiosis and natural symbiosis is that one can replace the strains in a community with more powerful and cooperative strains. Such an artificial community may resemble an enzyme cascade in a whole cell of a microorganism. 
     Examples of suitable systems include: 1) a community which performs cellulose degradation and alcohol fermentation (community members would include: cellulose solubilizing species (anaerobe), cellulose degrading species (anaerobe), oxygen consuming species (aerobe), oligosaccharides saccharifying species (aerobe, anaerobe), alcohol producer (anaerobe)); 2) a community which performs cellulose degradation and methane generation (community members could include: cellulose degrading species (cellulose→oligosaccharides), oligosaccharide degrading species (oligosaccharides→acetate), and methane generating species (acetate→methane)); and 3) a community which performs hydrocarbon degradation and oxidation (community members would include: hydrocarbon degrading species, acetate generating species, methane and methanol generating species, pH tuning species etc). 
     In another example, lipase activity may be induced. Lots of bacterial lipases have shown their optimum catalytic activity in the alkaline condition, whereas they are inactivated in acidic condition. To mitigate this, a bacterial cocktail of strain A (lipase producing bacteria in alkaline conditions) and strain B (alkali producing bacteria) could be placed in separate compartments in a microfluidic device of the present invention. The compartments could be linked by communication channels containing lipase assay chemicals (e.g. rhodamine B) and acids (making acidic conditions). When the two-strain-community (A-B) functions, rhodamine B color will be changed because lipases produced by strain A can work in the neutralized (or alkalified) region by the strain B. In this way, a community comprised of a lipase producing species and a species which lowers the pH of the local environment could be used to produce lipase activity. 
     In another example using lipase, the lipase production via yeast (e.g.  Candida rugosa ) can be inhibited by the presence of antifungal agent (e.g. cycloheximide). Interestingly, cycloheximide can be degraded by alkali over pH 7.0. Therefore, strain A (lipase producing yeast) and strain B (alkali producing bacteria) are placed in different compartments of a microfluidic device of the present invention. These compartments are linked via a communication channel containing lipase assay chemicals (e.g. rhodamine B) and cycloheximide. When the two-strain-community (A-B) functions, the color of rhodamine B will be changed after the degradation of cycloheximide by the alkali producing strain B. If a strain B which degrades the cycloheximide enzymatically is identified, then strain B can be replaced. 
     In yet another example using lipase, bacterial lipase cannot work in the presence of lipase inhibitor (e.g. tetrahydrolipstatin or orlistat). In this case, strains A (lipase producing bacteria) and B (lipase inhibitor producing bacteria) are separated into two compartments on a microfluidic device of the present invention. Then, this device is placed on the agar plate containing lipase assay chemicals (e.g. rhodamine B) and lipase inhibitors. When the two-strain-community (A-B) functions, color of rhodamine B will be changed after the degradation of lipase inhibitor by the strain B. 
     In an example using antibiotics, it is possible that the combination of two antibiotic-resistant bacteria can make other bacteria survive in an agar medium containing two antibiotics with different mode (e.g. β-lactam and aminoglycoside). For this example, the  E. coli  strain would be placed in the communication channel containing antibiotics, penicillin G and kanamycin. Strains A (β-lactamase producing) and B (kanamycin-modifying enzyme producing) would be place in separate communication compartments. When the two-strain-community (A-B) functions,  E. coli  on the same region can grow because β-lactamases and kanamycin modifying enzymes will degrade the penicillin G and kanamycin by secretion. In this case, growth profile (growth rate of  E. coli  over time) should be traced, instead of clear zone. 
     This invention takes advantage of the discovery that a defined spatial structure is required for the stable coexistence of multiple bacterial species in a synthetic community. A community of two or more interacting populations may be created by using a microfluidic device to control spatial structure and fluid communication (e.g. chemical communication) between the populations. For example, a community of two or more strains (species, etc.) of wild-type soil bacteria with syntrophic interactions can be created by using a microfluidic device to control spatial structure and chemical communication between the colonies (microcolonies). 
     In one example, a microfluidic device may be used to localize individual types of microorganisms (e.g. discrete bacterial species) into individual culture compartments (e.g. chambers, wells) separated from a microfluidic communication channel by a nano-porous membrane ( FIGS.  1 A- 4 C ). In those embodiments when a microfluidic device is used, this device spatially localizes each type of microorganisms (e.g. discrete bacterial species) while allowing fluid (e.g. chemical) communication among the types of microorganisms. Control experiments may be performed, if desired, to verify that the microorganisms remain confined and that chemicals are exchanged by diffusion through the communication channel(s). This microbial community is stable only when the microcolonies are separated by a certain distance, such as, e.g., hundreds of micrometers, but unstable when the microorganisms are cultured together or separated by longer distances. A mathematical model can be developed to suggest how spatial structure can balance the competition and interactions within the community, even when the rates of production and consumption of nutrients by species are mismatched, by taking advantage of nonlinearities of these processes. These devices may support the growth and co-incubating of any desired number of microorganisms, thus providing for the co-incubating of a class of communities that require spatial structure for stability. Controlling spatial structure may enable harnessing the function of natural and synthetic multi-species communities in the laboratory. 
     It is contemplated that the present invention is suitable for practice with microbial communities that are either mixed communities or spatially structured communities. Some microbial communities could be unstable over long times when mixed, but still functional/stable enough over short times. Thus, for purposes of the present invention, even mixed communities are considered spatial communities when there is at least one aspect that benefits from spatial control of the community, i.e. when they are relatively more stable under spatial control. Such aspects of spatial control may include, for example, increased stability, functionality, etc. Also, in terms of spatial structures, the present invention allows some degree of intermixing since it would be beneficial even just having a gradient, rather than abrupt transition, from one composition of microbes to another composition of microbes. 
       FIGS.  1 A-G  illustrate one example of the devices of the present invention. In this embodiment, the device has at least two layers, referred as “lower” and “upper” for simplicity. The lower layer contains various sizes, shapes, and separation distances of structure. In this lower layer of a device, different microorganisms, species or strains can be individually inoculated within their own confined space. In the upper layer of the device, various sizes and shapes of communication means can be structured, which connect the culture compartments (e.g. wells) of the lower layer. These communication means mainly serve the purpose of transporting chemical, biological, and/or physical information and/or substances between the different microorganisms. The communication means can be, e.g., communication channels in a variety of sizes, shapes, or forms. The actual number, size, and dimensions of the channels may be varied as desired ( FIGS.  1 A-G ), to provide a certain amount of communication between the compartments with microorganisms. For example, the communication means can be small channels that will allow flow of liquid between the two microbial compartments. In some embodiments, the flow of fluid between the two microbial compartments may be directional (from one microbial compartment to another). Alternatively, or in addition, the communication means may provide only the possibility for diffusion of molecules or compounds between the two microbial compartments, without any flow of liquids between the microbial compartments. Between these two (lower and upper) layers, a barrier may be positioned. Suitable examples of a barrier may include a 0.1 μm pore sized polycarbonate (or other types of materials) membrane. The polycarbonate membrane permits the chemical diffusion of small molecules. Thus, the device contains an upper layer (for exchange of released chemicals) and a lower layer (to be inoculated with various strains of microorganisms, e.g. bacteria). The upper and lower layer are separated by a membrane or other barrier structure that would enable exchange of chemical information between the upper and lower layer, but would prevent the movement of intact/whole microbial cells from the lower layer to the upper layer. In one example, the upper layer contains a microchannel that allows weak flow of media (or reaction solutions) to go through at the end of the channel, and then eventually pass through the 0.1 μm membrane. The upper layer could either have no flow (transport by diffusion only) or could have flow such that compounds released from one lower layer compartment are transported to other compartments downstream. The procedure of chemical (and/or physical, biological) communications is as follows: small molecules diffuse from the culture compartments in the lower layer, move to communication channel in a upper layer, and are then transferred to other culture compartments in the lower layer. In this system, it is possible to modulate the chemostat-style culture with longer operation times by supporting some nutrients. Furthermore, one can use the upper channel as a pipeline for fluctuating the amount of nutrient being delivered, to look at responses. 
     The type of system shown in  FIGS.  1 A-G  could be implemented using various other geometries. The key components are 1) chambers which contain cells which are physically separated from one another 2) chamber separated by a membrane or structure that acts as a barrier to cells but enables chemical exchange. Other systems which could be used for similar purposes include: 1) gel beads with different types of microbes spatially located in different regions of the bead; 2) a chamber containing a microbe covered with either a layer of gel or a membrane and other type of microbe placed on top of the gel/membrane. 
     This method can be applied to culture the microbial communities comprising two or more different species. In this system, structural geometry and the chemical communications provide the interactions between species, which promotes the co-incubation of functional microbial communities depending on their enzymatic reactions for the stable coexistence. 
       FIGS.  1 A-G  illustrate how each culture compartment (e.g. well) can be connected with various 3D spatial architectures. The device therefore allows coupling of multiple (two, three, or more) microorganisms or communities of microorganisms. Especially, this concept can be effectively applied to microbial communities showing synergistic interactions of degradation, synthesis, and modification of natural compounds. 
     The structure of the compartments can be tuned and adjusted depending on the microbial species or culture types. The structure of culture compartments in the lower layer of a device is various and it may be, for example, of a small patchy well type or a long stripe type. The structure of a communication channel in the upper layer of a device should contain the supporting posts, which is aligned with the structure of culture wells in a lower layer. The structure of the compartments may be able to provide cultivability of microbial communities from natural sources, even presumably the uncultivable microbial communities. The number of culture compartments per any device or unit device may vary. 
     The individual culture compartments can be functioning as individual continuously stirred tank reactors (chemostats) that are stirred by active flow or diffusion. Coupling among such culture compartments by fluidic connections or other methods that provide chemical exchange can provide a platform for implementing microbial communities. 
     The concept of culture compartments can be further developed by exchanging or extending layers to the lower layer or upper layer. For example, the thin agar layer containing microorganisms can be replaced with the lower layer. In this case, the agar gel provides a reduced flow but permeable path to microorganisms. When this gel layer is attached with various shapes of upper channel layer, communication channels in an upper layer can provide the concentration profiles. This device setup can be applied to investigate chemotaxis of microorganisms by switching the nutrients with the inhibitors (or chemorepellents). Furthermore, one can analyze how microorganisms can adapt to periodic fluctuations of chemicals, how microorganisms evolve by themselves against the environments in the periodic life cycle, and how microorganisms die as the spatiotemporal changes. 
     In one aspect of the invention, provided are devices and methods that are useful for co-incubating discrete populations of microorganisms, and for the detection and/or screening of discrete populations of microorganisms. This invention could also be use to perform assays by forming random groupings of cells and screening in the sense of replacing/adding one member to an existing group to modify and/or improve a desired function. 
     Once microbial communities have been formed, functional screening can be used to determine if any of the communities exhibit functions of interest. Control functional screens could be done on droplets containing only a single member of the community in order to distinguish community functions from those functions which only require single species. 
     Screening for functions could be done in the following ways: 1) Deposit the droplets containing communities onto gel surface which contains an indicator for a specific function. For instance, if the gel surface changes color around one of the droplets, then that droplet contains a communities which performs that function. A similar test could be run for communities in compartments such as microwells. The gel containing an indicator could be placed over the wells. The gel directly above the active wells would indicate function through color change or change in opacity or clearing zone around growing cells (as in an antibiotic test); 2) Add an indicator (such as fluorescent indicator) to the droplets and use established techniques such as FACS or flow cytometry to determine which droplets perform the function; 3) A self-sorting mechanism could be used to perform functional screens. If the function has an output that would enable the active droplets to segregate from the inactive particles (through changes in response to an electric or magnetic field, to changes in density, to resistance to chemical degradation, etc.). The self-sorting mechanism could also involve breaking through a barrier. For instance, droplets could be deposited on top of a thin plastic film, and those droplets that are able to degrade the film and fall through have the function of being able to decompose the material in the film; 4) The function of the community in a droplet or in a microwell could also be recorded on a surface. The droplets could be placed on a surface and left to incubate. The surface which is in contact with the droplet would then have a residue that would be associated with the activity of the droplet. Techniques such as MALDI mass spec, SIMS, or other techniques that are able to scan a surface to find specific Chemicals could be used to find the communities with a specific function. Useful aspects that include microengraving methods for rapid selection of single cells producing antigen-specific antibodies can also be found in Love et al., 2006,  Nature Biotechnology  24: 703-707. 
     Numerous examples of functional communities that can be identified and screened according to the present invention can be provided. Some examples of (artificial) functional communities are listed below. These functional communities include two or more of: producer P (antagonist), receiver R (sensitive to antagonist), sensitive to antagonist strain S; and resistant helper R (resistant to antagonist): 1) Antibiotic producer (P), sensitive strain (S), antibiotic resistance (R); 2) Quorum sensing strain (P), QS sensitive strain (S), quorum quencher (R); 3) Bacteriocin producer (P), sensitive strain (S), protease/peptidase producer (R); 4) Peroxide producer (P), sensitive strain (S), scavenging strain (R); 5) Acid producer (P), sensitive strain (S), acid decomposing strain (R); 6) Alcohol producer (P), sensitive strain (S), alcohol degrading strain (R); 7) Surfactant producer (P), sensitive strain (S), surfactant decomposing strain containing lipases/esterases (R); 8) Sugar alcohol producer (P), Sugar alcohol sensitive; disable to use sugar alcohol (S), sugar alcohol resistant; enable to use sugar alcohol (R). 
     The apparatuses and methods of the present invention can be used to perform functional screens for the identification of microorganisms based on their functional properties, such as enzymatic activity, secreted molecules, etc. The devices of the present invention are seeded with a plurality of microorganisms, which are compartmentalized in respective confined spaces. A high enough seeding density is needed so that communicating/adjacent compartments are likely to be occupied; at the same time, the seeding density is low enough so that these compartments are not occupied by multiple microorganisms. A functional assay is then performed and the candidate microorganisms are identified. These functional screens can also be performed in a high throughput fashion. In different embodiments the device may be added into a solution, or placed onto a substrate or bacterial culture. 
     If this method is used to select for individual microorganisms out of many, the barrier is preferably re-sealable, so once the organism that breached it passes through, the barrier reseals itself to prevent other organisms from escaping 
     The apparatuses and methods of the present invention can be used for co-incubating two or more populations of microorganisms. Maintaining interactions among microbial populations can be performed on a microfluidic chip, where the microorganism are localized in some areas and allowed to directly or indirectly interact through barriers. Examples or suitable barriers include fluid or gas or gel or solid materials, such as droplets or membranes. In an apparatus, the microorganisms may be confined by barriers with pores small enough to be not permeable to bacteria, but large enough to allow diffusion of molecules and flow of fluid. Several architectures can be used, including multilayer architectures. Ideas resembling chemostats and continuously stirred tank reactors can be implemented on a microfluidic chip using these methods. Gels may also be used to trap microorganisms and allow transport of molecules. 
     An important concept in the devices and methods of the present invention is the ability to separate individual microbes by intermediate distances. If microbes are too close (mixed together such that there is no spatial structure, physically touching, not immobilized, immobilized but only micrometers apart) then the microbes will directly compete (either through competition for shared nutrients, one microbe releasing waste or a chemical that inhibits the growth or activity of another microbe). By physically separating the microbes over space, competition is reduced. However, communities&#39; functions may involve the exchange of chemical between different microbes. Therefore, although the microbes should be separated to reduce competition, they also should be close enough such that they can effectively exchange chemicals. The distance over which a group of microbes can effectively communicate with another group of microbes through diffusive gradients has been estimated to be approximately 25 microbe lengths. Generally, the spatial structure/separation distance between microbes should be on the order of hundreds of μm. Generally, millimeter and centimeter scale separations are too large. Effective intercellular communication distances can also be determined by methods such as the relative time constants for secretion and diffusion of molecules (Francis and Palsson, 1997, PNAS, 94: 12258-12262). 
       FIGS.  3 A- 3 C : illustrate the concept of how a synthetic community of three bacterial species requires spatial structure to maintain stable coexistence.  FIG.  3 A : a schematic drawing of the wild-type soil bacteria and their functions used to create a synthetic community with syntrophic interactions.  FIG.  3 B : graphs show the survival ratio of each species (N/No) as a function of time when cultured in well-mixed conditions in a test tube in nutrient-rich (left) and nutrient-poor (right) media, indicating instability of the community under spatially unstructured conditions.  FIG.  3 C : a schematic drawing of the microfluidic device used to stably co-incubate the three species by imposing spatial structure with culture wells and a communication channel. 
       FIGS.  4 A- 4 C  illustrate how the stability of the community requires communication among microbial species, as explained below.  FIGS.  5 A- 5 B  illustrate the concept of how a synthetic community only coexists at intermediate separations, as explained below. 
     In some embodiments, stencils could be used to control the loading of cells into an array of compartments (e.g. microwells) on a device. An example of this method is schematically shown in  FIGS.  2 A- 2 F . The device would consist of an array of microwells on a lower layer, a membrane, and an upper layer which would contain fluidic connections for sets of microwells (i.e. a set of 4 microwells on the lower layer would all be connected to the same channel on the lower layer creating a community of the cells in the 4 microwells). Stencils could be used to cover a portion of the holes on the upper layer during seeding. For example, if communities of 4 connected microwells (i, ii iii, iv) are generated, a stencil could be used to cover all of the wells ii, iii, and iv on the chip and cells could be loaded into well i. The stencil could then be moved to enable access only to well ii and another type of cell could be loaded into well ii. In this way, specific cell types could be loaded into specific wells in each set of wells, and therefore a large array of community could be seeded each containing the same types of cells (i.e. every set of 4 wells has 1 well with species A, 1 well with species B, 1 well with species C, and 1 well with species D). A variation on this type of loading would be to load all of the wells i, ii, and iii on the array with a preset combination of cells and then to load well iv with a random strain of cell. For example, each community may contain  Pseudomonas aeruginosa, Bacillus cereus, Streptomyces coelicolor , plus one additional community member randomly seeded from a mixture of soil microbes. In this way, one could screen for how the addition of a new community member influenced the function of a specific community of microbes. 
     The following mathematical model is provided to better understand the role of spatial structure and is not intended to limit the present invention.  FIGS.  6 A- 6 I  are a mathematical model of a two-species syntrophic community. As indicated in  FIGS.  6 A- 6 I  and in the text, individual planes represent: the rate of consumption; the concentration of nutrient B at species alpha, [B alpha ]; the rate of production of nutrient A; and the minimum rate of consumption of nutrient A.  FIG.  6 A : colony alpha produces nutrient A and colony beta produces nutrient B. Both nutrients establish gradients over a distance L (m), which is the distance between the centers of colonies alpha and beta.  FIG.  6 B : 3D rate plot of consumption of A (plane) varied with L.  FIG.  6 C : 3D plot of [B alpha ] (plane) varied with L.  FIGS.  6 B- 6 I , 3D rate plots and 2D sections show the state of the community when colonies of species alpha and beta are separated by small ( 6 D,  6 G), intermediate ( 6 E,  6 H), and large ( 6 F,  6 I) L. The steady-state concentration of nutrient A occurs where the consumption and production curves intersect at the given concentration of nutrient B.  FIG.  6 D- 6 F : 3D rate plots from a Class II community predict a non-zero steady-state only at intermediate L, indicating that the synthetic community experimentally tested here is Class II.  FIG.  6 G- 6 I : 2D sections of representative production and consumption curves for Class I, II and III communities. 
     While the exchange of essential nutrients between the colonies is considered herein, these results should apply for the exchange of other diffusible molecules that regulate the functions of neighboring colonies. This model considers a bacterial colony of species alpha that produces nutrient A and a colony of species beta that produces nutrient B. Nutrients A and B diffuse between colonies of species alpha and beta, which are separated by distance L (m). The production function is known to be nonlinear: onset of production typically occurs above a critical concentration of nutrients, and production saturates or is even inhibited at high concentrations of nutrients. This nonlinear dependence of production of nutrient A on the concentration of both nutrients was approximated as the product of two Hill functions: 
     
       
         
           
             
               
                 
                   
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     where K 1 , K 2 , K 3  are rate constants, L is the distance between the colonies (m), N alpha  is the size of colony alpha (number of cells), t is time (s), [A] is concentration of A (M). For simplicity, a model in which species beta is a constant source of nutrient B is considered ( FIG.  6 A- 6 I , vertical planes in  6 C,  6 D,  6 E,  6 F) at a fixed ratio of species populations S alpha /S beta,  where S alpha  is the number cells in colony alpha and S beta  is the number cells in colony beta ( FIGS.  6 A- 6 I ). S alpha  and S beta  are taken to be constant, assuming that the number of cells changes slowly on the time scale of metabolic activity, as could be expected for many strains of soil bacteria that are slow growing. The same conclusions are obtained for the more general model using analysis of nullclines. The production of nutrient A calculated with equation (1) is shown as the curved gray plane in  FIGS.  6 A- 6 I . 
     Each species also consumes both nutrients; this consumption is taken to be linear for simplicity, where the rate of consumption of nutrient A by colony alpha is defined as 
     
       
         
           
             
               
                 
                   
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     The total consumption of nutrient A is take as the combined total of equations (2) and (3) and is shown as the dark gray flat plane in  FIGS.  6 B- 6 F . The shapes of consumption and production curves of glucose by Pc were confirmed experimentally. Nonlinearity must be present for spatial effects to be observed. The concentrations of A beta  and B alpha  are a function of L such that [A] beta =[A] alpha  and [B] alpha =[B] beta  when species alpha and beta are close together, and [A] beta =[B] alpha =0 when they are infinitely far apart, e.g. mimicking the profile of a diffusive gradient connecting species alpha and beta. S alpha  and S are functions of [A] and [B] over time. 
     The system is stable at a distance L only when the combined consumption rate of a nutrient is matched by the production rate. This criterion is only met when the three surfaces for [B] alpha , production of A, and consumption of A in  FIGS.  6 A- 6 I  cross at a non-zero point. As L is increased, two effects compete: the consumption of nutrient A by species beta decreases ( FIG.  6 B ), and [B] alpha  decreases ( FIG.  6 C ). The spatial dependence observed in  FIGS.  5 A- 5 B  is recapitulated in this model. For small L, [B] alpha  is high, but mutual consumption exceeds production and the criterion for stability is not satisfied ( FIG.  6 D ). For larger L, both [B] alpha  and the consumption rate decrease ( FIG.  6 E ), and a stable steady state appears. The nonlinearity (saturability) of the production curve is critical in this model: species alpha is insensitive to a decrease in [B] alpha  but sensitive to a decrease in the consumption of nutrient A. No stable steady state is found at very large L ( FIG.  6 F ): while the consumption rate of nutrient A by species beta becomes insignificant and the total consumption rate approaches the rate of consumption of nutrient A by species alpha only ( FIGS.  6 A- 6 I , plane labeled consumption from alpha only in  6 B, straight line with lowest slope in  6 G- 6 I), [B] alpha  becomes so low that it becomes limiting. 
     Space affects the interaction of community members in important ways. First, when colonies are too far apart, the concentration gradients of nutrients they produce approaches zero due to diffusive loss, resulting in colonies that are essentially isolated. Second, when colonies are too close, they directly compete for nutrients. Both the intrinsic rate each species performs its function and the transport dynamics of the system determine the relative contribution of diffusive loss and interspecific competition on the community. 
     This model predicts three classes microbial communities ( FIG.  6 G- 6 I ) with obligate interactions. A “Class I” community is stable even in a well-mixed environment ( FIG.  6 G ) as well as at intermediate separations ( FIG.  6 H ), because production rates are sufficiently high to accommodate consumption by all species. However, a Class I community is not stable beyond a maximum separation where metabolic coupling is lost ( FIG.  6 I ). A “Class II” community is not stable when colonies are well-mixed or too close, because consumption exceeds production ( FIGS.  6 D and  6 G ). A Class II community is one that requires intermediate spatial separation of the species in order to form a stable/functional community. As the species become spatially separated, interspecific competition is reduced, and the community becomes stable ( FIGS.  6 E and  6 H ) until the maximum separation where metabolic coupling is lost ( FIGS.  6 F and  6 I ). Class II communities require spatial structure for stability; the synthetic community described herein is Class II. A “Class III” community is not stable at any separation distance, because the distance at which the colonies are metabolically decoupled is smaller than the distance at which cross-consumption is sufficiently reduced ( FIGS.  6 G- 6 I ). 
     Several Class I communities have been characterized and cultured, but the number of natural communities vastly exceeds the number of communities cultured in the laboratory. Metabolic requirements for a Class II community are less restrictive and one may expect them to occur more frequently. It remains to be established whether many natural communities are Class II; if so, they would not be cultivable by traditional methods but could be cultured by methods that control spatial structure, such as microfluidic devices presented herein. Using the devices and methods of the present invention, it is possible to examine the spatial structure and transport in natural environments, to understand how communities of microbes interact and perform community-level functions in natural ecosystems, and to understand how species diversity of microbial communities is maintained. In addition, control of spatial structures in the laboratory may be used to test known microbial strains for new functions, to discover communities that perform various (desired or not) functions, to stabilize natural microbial communities and harness their functions, or create synthetic communities with new functions. Once a community is identified, it can be scaled up and multiplied, to produce microbial amounts sufficient for desired applications, e.g. in numbers that can be useful for antibiotic production or environmental remediation, for running reactions by exchanging metabolites among types of microorganisms, etc. 
     In one aspect, this invention may be thought of as a three-dimensional matrix of co-incubating systems that includes a variety of devices suitable for confinement and/or separation of microorganisms in the first dimension, a variety of microbes and microbial communities in the second dimension, a variety of applications in the third dimension. Such a 3D matrix provides for any three-dimensional interactions, i.e. any device with any community with any application is possible according to the present invention. As well, the interactions may involve more than one device, community, and application. Suitable examples of a variety of systems, devices, microorganisms, microbe communities, and applications, can be found herein. 
     Since community viability and function relies on an approximately constant spatial structure (microbes or immobilized, structure is not fluid), one might imagine that simply spreading mixtures of microbes onto agar plates may be able to provide such structure. However, using the devices and the methods of the present invention has at least the following advantages: 1) culture compartments can precisely define the structure of community. It is likely that communities require a specific range of spatial separation (e.g. microbes 1 and 2 have to be between 100-500 μm apart to form a functional/viable community). Randomly generated structures, where the distance between the microbes in random and the number of microbes in a given area is random, such as spreading microbial mixture on an agar plate, will result in a very small percentage of communities with microbe 1 and 2 100-500 μm apart with no other microbes nearby. Estimates such as how far apart community members should be based on chemical production and consumption rates as well as transport rates should be able to predict approximate spatial structures that will enable community function/viability. Thus, culture compartments can be created that only try a small set of possible geometries, therefore greatly increasing the odds of finding a functional community; 2) culture compartments have the ability to limit growth. For example, if two microbes are spread onto an agar plate, the microbial colonies may continue to expand until they occupy the entire plate. Therefore if one of the microbes grows much more rapidly than the other, the spatial structure of the community (two microbial colonies 200 μm apart) will not be maintained over time). Culture compartments could have finite volumes and barriers which would inhibit the extent of growth of a microbial colony. In this way, fast growing colonies will only grow to a finite and controllable size, allowing for slow growing microbial colonies to form. 
     Spatial structures also enable communities of cells to tolerate one another. For example, a community of cells “A” and “B” may not be able to survive in a mixed culture, however if they are placed in a structured space then the competitive interactions would be decreased. The cells might not have positive (symbiotic) interactions, but space would enable them to both survive and tolerate being near one another. Tolerance could lead to community level functions as the cells in the community could perform complimentary functions that would combine to enable higher level functions (such as multi-step degradations, multi-step synthesis, induction of specific cell behaviors, etc.). 
     Stochastic confinement can also be used in combination with screening for community functions. By taking a sample containing multiple species of microbes all mixed together, generating small volumes plugs (stochastic confinement) can be used to separate this mixture into discrete volumes each containing a single microbe. In this way rare and slow growing microbes can be separated from fast growing and ubiquitous microbes. After confining the microbes, they can be cultured (since inter-species competition is reduced) and the culture inside each droplet could benefit from stochastic confinement effects such as the accumulation of released molecules which could speed the transition out of the lag phase. The separated microbes could then be seeding into communities either by combining droplets or loading each droplet into a separate microwell with structures that would enable the exchange of chemicals between the wells. Confinement effects are again important for the community structure, as confinement will enable the accumulation of released molecules (decreased dilution) which will increase the flux of chemicals between species and may increase the overall rate of community function. Preincubation of individual microbes in confined droplets before seeding into community structures would also enable rare microbes to increase in number (which means they could be incorporated into more communities) and also would enable the seeding of replicate communities by splitting the droplet into multiple droplets containing the same microbe before seeding the community. 
     One advantage of the devices, systems, and methods of the present invention is that release of compounds from microorganisms is highly dependent on culturing conditions. For example phosphate levels, temperature, nutrient availability, and other environmental conditions, all influence the production and release of various metabolites. This invention thus enables the screening of media conditions and concentrations of additives both for communities, common species, and rare species of microbes. Thus, if desired, it may be possible to grow certain communities for much longer if some nutrients are provided, or it might be possible to fluctuate the amount of nutrients being delivered, to look at corresponding responses. 
     Various aspects of assays that can be used in the practice of the present invention can be found in Balagadde et al., 2005,  Science  309: 137-140 (long-term monitoring of bacteria undergoing programmed population control in a microchemostat), and in Groisman et al., 2005,  Nature Methods  2: 685-689 (microfluidic chemostat for experiments with bacterial and yeast cells). 
     There are numerous applications for encapsulated microorganisms in GMD. For example, certain bacteria accumulate precious metals or radioactive contaminants or heavy metal contaminants. Screens can be devised that select for such types of bacteria that tend to accumulate heavy metal elements. Different bacteria can be encapsulated into gel beads (e.g., a library of mutants of one species, or a combinatorial library of mutants of several species to create communities). The gel should be chosen to have similar density to the density of encapsulated bacteria. These beads are then exposed to a sufficiently large volume of solution than contains salts of the heavy element that should be collected (accumulated). The density of the solution is adjusted so the beads barely float. The volume of the solution is adjusted to provide for separation of floating beads from sunken beads. If bacteria accumulate the heavy element significantly, the beads would sink. The sunken beads are collected, and the bacteria from these beads are sequenced as candidates for element accumulation. The screen may be optionally repeated. The screening threshold can be adjusted by simply increasing the density of the fluid to which the beads are exposed; in this case, the beads would have to accumulate more of the element to sink in it. 
     Once the strain (or the community) that accumulates metal is identified, these microorganisms can be encapsulated in beads that contain magnetic particles, can be dispersed in the environment. Let them soak up the heavy elements, then use a magnet to collect the product. Bacteria that metabolize these elements into insoluble derivatives would be especially useful; each bacterium then could have a product of accumulated element (e.g. metallic gold or uranium, or a piece of insoluble strontium sulfate). 
     This is potentially more efficient than trying to accumulate a protein-element complex. Also, it could potentially require a combination of bacteria—one accumulates the other produces the precipitating agent. If the protein-element complex is found, then the protein could be used outside of bacteria, if it is economical, but accumulation of metabolized products may be easier. Some secondary concentration by using predators that would eat the bacteria (even without beads) could be useful. 
     The present invention contemplates the use of 2D methods for encapsulation of cells ( FIGS.  9 A- 9 F ). The methods for encapsulating large numbers of cells are similar to sequential merging of reagents to plugs flowing in a 1 D microfluidic channel (straight channel). Examples of micro cell encapsulation and its hydrogel-beads production using microfluidic device are shown in Shintaku et al., 2007,  Microsystem Technologies  13: 951-958; however, here the cells are introduced into a 2D channel (width of channel much larger than width of cell) and the cells flow through regions in which various reagents are applied to the cells. The 2D channel should be approximately the similar in height to the cells such that the cells flowing through the device form a monolayer ( FIGS.  9 A- 9 F ). 
     In the 2D devices, cells or plugs containing cells enter a region in which the width of the channel gets much larger than the width of the cell. In the top of this wide region is a membrane or structure with small pores. On the other side of the membrane are channels which deliver reagents to the cell/plugs. For example, as the plugs pass by the region of reagent 1, the plugs come into contact with reagent 1 passing through the pores of the membrane and pick up reagent 1. In this way, the plugs can pass through multiple regions of reagent of multiple layers of reagents can be deposited. Key parameters in the design of the 2D device will be 1) flow rate of cells 2) pressure drop in the reagent channels (porosity of membrane, size of pores, length of pores (in direction of flow), width of reagent channel, width of cell channel) 3) width of reagent region 4) number of reagent regions. The amount of time spent in each reagent region and the pressure drop in the reagent channel will determine the amount reagent deposited on each cell. A 2D such as the one above could be much wider (e.g. hundreds to hundred thousands of cell lengths wide) to enable a large scale process of cell encapsulation. Reagents added to the plugs/cells could include gel components, drugs, screening targets, other types of cells, cell extracts, genetic material, magnetic particles, antibodies, and emulsifiers. 
     The 2D method is useful for high throughput/larger scale applications. A comparable 1 D method could also be useful for some applications. In some embodiments, two or more 2D devices may be stacked in multiple layers to make 3D devices to increase throughput. 
     An alternative encapsulation method could involve the formation of plugs using a multiple inlet junction to mix several fluids together. Additional layers could be added the plugs by flowing them past subsequent multiple inlet junctions. For example, a plug could pick up a layer of gel by flowing past a junction with an aqueous stream of Ca 2+  solution and an aqueous stream of alginate. The two streams would mix and surround the plug, creating a gel layer around the initial plug. In preferred embodiments the surface tension at the interface of the carrier and the first plug fluid is higher than the surface tension at the interface of the second plug fluid and the carrier. 
     For such plugs containing multiple layers of fluid, some of the fluid layers will contain cells or a single cell and some of the layer will act as a barrier to physically isolate each cell layer. This would enable layers of cells to exchange chemicals but would prevent mixing of the different cell types. The barrier layer thickness, porosity, transport rate, permeability, material can be optimized to control the spacing between the layers of cells (as some cell combinations will require specific separations). The order of layers, volume of layer, shape of layer, inoculum size, and the addition of other layers containing assay/detection reagents, nutrients, metabolites, will influence the overall viability and function of each layer and the community as a whole. 
     In some embodiments, it is possible to combine the GMD and a microfluidic device. In detail, species A and B can be entrapped in the GMD with appropriate sizes and shapes, respectively. On the other hand, a microfluidic device provides a bioreactor that GMDs are packed and interacts to each other. Several microfluidic devices will be connected, which contains different GMDs as the cascade of microfluidic reaction centers. Once the GMD is packed into the microfluidic device, GMD cannot be secreted out of the device. After GMDs containing each species of A and B are prepared, each GMD is packed into the microfluidic device A and B, respectively. In this system, once species A entrapped in a GMD in a microfluidic device A produces a precursor A, then this secreted out and move to microfluidic device B. Then the precursor molecules are moving into the GMD bearing species B in a microfluidic device B, and glycosylation reactions are performed by the enzymatic reaction of glycosyl transferases. Then the final products will be secreted out of device B to next stage. 
     The GMD-based co-incubation in a microfluidic system can be a new model system for a variety of applications, for example for novel natural products discovery, for one or more of the following reasons: 1) GMD-based co-incubation makes communication among some strains to be more stable compared to bulk co-incubation. In most cases, co-incubation of different strains makes one strain less viable. Physical confinement by the GMD has been proved to maintain the viability of microorganisms; 2) microfluidic system can produce novel natural products with shorter culture time and smaller volume; 3) co-incubation in microfluidic devices enables to study the importance of spatial structure where microorganisms interact with each other. 
     Confinement of microorganisms using GMDs, compartments, or in any other ways according to the present invention, has advantages for screening rare cells/communities. It is known that some strains of microbes will not initiate growth or some cellular functions unless cell density is above a minimal threshold. It is also possible that although the process is occurring, the rate at low cell densities may be so slow that it would take weeks or months to observe growth or the function. Therefore, by placing single cells in very confined spaces with small volumes it is likely that they will initiate high density processes and that many processes will have increased rates. This is especially important in the case of rare cells, since the sample may only contain one or a few copies of the rare cell, thus with small volume confinement it would not be possible to achieve high cell densities of rare cell types. It would also be important for creating communities of cells which contain rare cell types. 
       FIGS.  9 A- 9 E  illustrate the schematics of some embodiments for GMD-based co-incubation. 
     Various aspects useful for practicing this invention, in particular related to methods to making gel particles or other types of droplets/particles, are disclosed in: Ho et al., 2008,  Langmuir  24: 5663-5666 (fabrication of Janus particles from the surfaces of electrospun polymer fibers); Jiang et al., 2008,  Industr. Eng. Chem. Res.  47: 2495-2501 (fabrication of polysaccharide-inorganic hybrid biocapsules with improved catalytic activity and stability); Laulia et al., 2008, Small 4: 69-76 (stretched cavity-assisted molding of micrometer and submicrometer photopolymerized hydrogel particles); Liu et al., 2008,  Int. J. Pharmaceutics  351: 104-112 (fabrication of core-shell hybrid alginate hydrogel beads); Walther et al., 2008,  Angewandte Chemie - International Edition  47: 711-714 (emulsion polymerization using Janus particles as stabilizers); Jang et al., 2007,  Angewandte Chemie - International Edition  46: 9027-9031 (three-dimensional structures in a microfluidic device; stop-flow interference lithography); Khademhosseini and Langer, 2007,  Biomaterials  28: 5087-5092 (microengineered hydrogels for tissue engineering); Glotzer and Solomon, 2007,  Nature Materials  6: 557-562 (anisotropy of building blocks and their assembly into complex structures); Wang et al., 2007,  Chemphyschem  8: 1157-1160 (facile fabrication of hybrid colloidosomes with alginate gel cores and shells of porous CaCO 3  microparticles); Nisisako and Torii, 2007,  Advanced Materials  19: 1489-1493 (formation of biphasic Janus droplets in a microfabricated channel for the synthesis of shape-controlled polymer microparticles); Cheung et al., 2007, Lab on a Chip 7: 574-579 (direct patterning of composite biocompatible microstructures using microfluidics); Shepherd et al., 2006,  Langmuir  22: 8618-8622 (microfluidic assembly of homogeneous and janus colloid-filled hydrogel granules); Nie et al., 2006,  J. Am. Chem. Soc.  128: 9408-9412 (design, synthesis, and self-assembly of Janus and ternary particles generated by microfluidic synthesis); Dendukuri et al., 2006,  Nature Materials  5: 365-369 (continuous-flow lithography for high-throughput microparticle synthesis); Fialkowski et al., 2005,  Nature Materials  4: 93-97 (self-assembly of polymeric microspheres of complex internal structures); Zengler et al., 2002,  Proc. Natl. Acad. Sci. USA  99: 15681-15686 (encapsulation of cells in GMDs for parallel microbial cultivation under low nutrient flux conditions), all of which are incorporated herein by reference. 
     The devices and methods of the present invention find a variety of uses. Non-limiting examples of applications include: 1) co-incubating sets of microbes that cannot be cultured independently (either obligate symbiosis or the culturing conditions have not yet been determined) (and in this way determine the functions of these microbes that cannot be grown in pure (single species) culture); 2) co-incubating sets of microbes to perform a community function (a function which does not occur when individual species are cultured); 3) community functions include: multi-step degradations (such as cellulose/complex saccharides, environmental pollutants, waste materials such as plastics) and multi-step synthesis in which the product of one microbe serves as the intermediate and is further chemically modified by another microbe; 4) spatially structured droplets could be used as a high throughput screening method to identify functional communities/culture species which cannot be grown in pure culture; 5) spatially structured droplets could be used to determine the interactions of microbe communities in the nature (in aquatic and soil environments as well as communities found within another organisms (such as in the roots of plants and in the digestive tract of various organisms) and also determine the response of microbe communities to changing conditions in the external environment (temperature, pH, gas levels, pressure changes, chemical contaminants, changes in nutrient composition, moisture content); 6) community functions also include sets of chemicals which perform new function or have increased function in response to being combined. An example would be two molecules that individually could not act as an antibiotic together have there individual functions combine to act as an antibiotic; 7) spatially structured gel droplets could also be used to create multispecies microbial communities that could be used to perform various tasks such as: droplet as a pill that could be ingested or injected into the body, droplets that could be used in bioprocesses (for instance a tank of the species mixed could not coexist, but a tank full of structured droplets would be able to perform communities functions on a large scale), droplets could be used for bioremediation (for instance droplets containing microbial communities could be added to the soil, aquatic environments, waste treatment for functions such as absorbing/decomposing contaminants, increasing nutrient flux (such as nitrogen, phosphorous, trace elements, or dissolved carbon sources), reduce the population of another organism); 8) it should be noted that because some such communities require local interactions (communities members communicate through local gradients) then communities may not be scalable, in the sense that if the community were cultured on a larger droplet or in a large tank divided into two compartments it may not work because some only the microbes near the interface (i.e., physically close to other community members) would be active. Some of these applications are discussed in greater detail below. 
     The devices and methods of the present invention can be used to investigate interactions between killer bacteria (with respect to either same type of bacteria or other species). Microfluidic microbial compartments provide spatial segregation of different species or strains, allowing chemical communications between cells. Based on these devices and systems, potential strategies such as distance between different species, different stages of microbial cells, vegetative cells vs. spores, etc., can be applied. In some examples, it is possible to set up a system where the microorganisms are arrested in sporulation state and can produce factors (e.g. antibacterial) that can kill other bacteria. 
     The devices and methods of the present invention can be used to identify and/or combine environmentally incompatible microorganisms. These microorganisms include those isolated from multicellular hosts and natural environments, genetically engineered strains, strains evolved in a laboratory setting, as well as any combination of organisms from these groups. This can be done, e.g., in beads, where species A can be protected by species B and/or C. For example, it is possible to co-incubate two or more strains that may not be easily (or at all) found in the nature. More specifically, these microbial consortia may not be found in nature frequently and also may not be easy to handle in culture in the laboratory because those two or more strains are not compatible for coexistence owing to different environment to survive. The functional communities of aerobic and anaerobic microorganisms can be a representative example. Using the spatially structured culturing methods in a microfluidic device or GMDs, microbial communities that are environmentally incompatible to coexist but are potentially expected for novel functions can be cultured and broadly applied in the fields of bioremediations, bio-refinery technologies, bio-energy and bio-fuel, degradation processes of natural products, food/cosmetic engineering, etc. Examples of environmentally incompatible communities include culturing microbial strains with different growth rates. In the laboratory, it has not been aggressively attempted to co-incubate microbial communities with different growth rates in a well-mixed flask. This mismatched growth rate of different species or strains of microorganisms may be a big bottleneck in co-incubate of microbial communities. Under the environment that spatially segregated culture wells in the devices of the present invention, the co-incubation of microbial communities with different growth rates may be possible. 
     In an alternative embodiment, it may be advantageous to selectively enrich or perturb the initial source population by physical or chemical treatments. The goal is to improve the relative abundance of species that are likely to possess a desired gene or metabolic pathway. For example, a microbial sample can be subjected to a period of elevated temperature to select for thermophilic species or reduced temperature to select for psychrophiles. Other physical treatments include the addition of particles of various sizes and compositions for adherent species, agitation of liquid or semi-liquid samples, high pressure treatment, exposure to light, exposure to high-energy radiation, and the like. The population can also be exposed to an exogenous carbon source such as cellulose to enrich for species that possess cellulolytic enzymes. Other chemical treatments include changes in mineral nutrients or cofactors, atmospheric composition, redox potential, osmolarity and pH. Likewise, one may add chemicals such as quorum-sensing agents, antibiotics or non-aqueous solvents. Selection can also be done crudely by creating conditions wherein some of the cells will lyse (e g, by changing the osmotic strength or adding detergents). Intact cells can be removed by centrifugation It may also be desirable in some cases to derive the genomic material from a population that has been partially cultured in a laboratory microcosm (e g, a Winogradsky column) to deliberately ‘shape’ its genetic profile through complex interactions among community members. 
     Physical separation (e.g. fractionation and sorting) of the desired organisms by dispersion and fractionation can also be used to adjust the species composition. A useful method for obtaining genomic source material is through bioprospecting. The simplest method for dispersing and fractionating soil bacteria is to homogenize the sample in a Waring blender and then to pellet the soil particles, plant material, protists and fungi by low-speed centrifugation. A second, high-speed centrifugation is then used to pellet the bacteria. Another type of fractionation comprises filtering the cells through porous membranes or columns of coarse particles (which can also be used to separate adherent from non-adherent species). Filtration/capture can also be accomplished by affinity or size-exclusion chromatography. Affinity capture can be coupled with magnetic bead technology to aid in removing particular cell types from the medium. Density gradient centrifugation using, for example, Percoll and sucrose can be used to separate microbial cells from other material. Species that prefer to form biofilms can also be separated out by allowing them to adhere to a solid surface, such as a modified Robbins device or flow cell, which can be removed from the medium for harvesting. 
     Cells can also be sorted individually using fluorescence activated cell sorting. In addition to separating classes of cells based on their light scattering properties, a FACS instrument can sort microbial cells that have been selectively labeled with one or more fluorescent dyes. Thus, cells can be sorted based on fluorescence emission wavelength and intensity by choosing the appropriate laser excitation wavelength and emission windows. Fluorescent labeling may comprise direct labeling with reactive dyes. 
     Microorganisms for practicing the present invention can be obtained from a variety of sources. Environments for finding organisms include, but are not limited to: geothermal and hydrothermal fields, acidic soils, sulfotara and boiling mud pots, pools, hot-springs and geysers where the enzymes are neutral to alkaline, marine actinomycetes, metazoan, endo and ectosymbionts, tropical soil, temperate soil, arid soil, compost piles, manure piles, marine sediments, freshwater sediments, water concentrates, hypersaline and super-cooled sea ice, arctic tundra, Sargasso Sea, open ocean pelagic, marine snow, microbial mats (such as whale falls, springs and hydrothermal vents), insect and nematode gut microbial communities, plant endophytes, epiphytic water samples, industrial sites and ex situ enrichments. Additionally, the enzymes may be isolated from eukaryotes, prokaryotes, myxobacteria (epothilone), air, water, sediment, soil or rock, a plant sample, a food sample, a gut sample, a salivary sample, a blood sample, a sweat sample, a urine sample, a spinal fluid sample, a tissue sample, a vaginal swab, a stool sample, an amniotic fluid sample and/or a buccal mouthwash sample. The invention provides a universal and novel method that provides access to immense reservoirs of untapped microbial diversity. The invention provides the ability to grow and study these organisms. It revolutionizes our understanding of microbial physiology and metabolic adaptation and provides new sources of novel microbial metabolites. The invention can be applied to samples from several different environments, including seawater, sediments, and soil. As well, the invention provides methods to identify and modify enzymatic pathways useful for chemical, pharmaceutical, textile, food and feed, detergent, etc. applications. Various aspects of methods similar to those discussed above are disclosed in PCT Patent Applications Pub. Nos. WO05010169A2 WO0229101A2, both which are herein incorporated by reference 
     The devices and methods of the present invention can be used to screen for and identify compounds that microorganisms are capable of producing, and that have not been identified using standard microbe cultivation techniques. Small changes in culturing conditions (for example, media composition, aeration, culture vessel, addition of enzyme inhibitors) drastically change the metabolites that are released from a cell. One strain may be producing many compounds. Even though it is possible to culture a microorganism, e.g. the bacterial strain  B. subtilis , and even though a fair amount is known about its genome, some useful compounds that it is capable of releasing may be missed simply because the organism has never been controllably grown under particular environmental conditions and/or with particular inducers. Therefore, using hybrid-like approaches it is possible to probe a larger range of metabolite/released compounds/drug leads simply by running high throughput screens of various media conditions/additives. Some aspects of the possible ways to explore chemical diversity are disclosed in Bode et al., 2002, ChemBioChem 3: 619-627. 
     Implementation of the screenings can be done in the following ways: 1) take a known organism and screen many media and culturing conditions (vary ion concentrations, known autoinducers, amount of confinement, temperature, pH, protein additives, reaction oxygen species, stress inducers, change carbon source and concentration of carbon source, change nitrogen source and concentration of nitrogen source, change availability of various trace metals (Mn, Mo, Cu, Pt, etc.), add drugs known to interfere with specific cellular activities, add transport and ion channel inhibitors, small molecules involved in cellular communication, virulence activators, etc.). After using hybrid method to screen through many conditions, perform functional tests or other assays in plugs (Song et al., 2006,  Angew. Chem. Int. Ed.  45: 7336-7356; Chen et al., 2006,  Curr. Opin. Chem. Bio.  10: 226-231) to determine if compounds have been generated with properties of interest (such as drug targets, antibiotic compounds, ion channel inhibitors, virulence activation, virulence inhibition, degradation of various compounds, binding affinity, etc.); 2) perform the same method described in 1) except perform this type of screen with rare cells isolated from natural samples such as the soil, aquatic environments, animal digestive tract, etc.; 3) perform the same method described in 1) except perform this type of screen with cells which are uncultivable (no known conditions cause them to divide/reproduce outside of natural environment). If small volumes are used, should be able to detect activity even from a single cell without division. 4) use plug-based methods to collect the lysate or cell free supernatant from various types of cells and merge these solutions with other cells to elicit metabolite/compound production. Lysate/supematant could be diluted during the screen (concentration screen using hybrid method). In this way, uncharacterized/unknown compounds/combinations of compounds could be screened to elicit production of useful compounds. 
     The devices and methods of the present invention can be used for the biosynthesis of biologically active compounds and industrial compounds including natural products, antimicrobial agents, fine chemicals, food additives, functional cosmetic materials, health-care compounds, and xenobiotics. While lots of the biologically active compounds have been chemically synthesized via combinatorial chemical synthesis, trends of the synthesis of bioactive compounds move from chemical methods to biological methods. According to the present invention, it is possible to use dominantly microorganisms, more specifically the enzyme systems, in a microbial community. This application provides for the development of a co-incubating system from different species of microorganisms. Representative examples of co-incubating systems include: 1) a simultaneous coupling of first and second species. Example: species 1 produces the substrate A, and species 2 produces the substrate B, respectively. If both substrates of A and B can autocatalytically react to each other via chemical reactions, the final compound X can be eventually produced by the co-incubate of species 1 and 2 together; 2) a linear synthetic sequence of species. Example: species 1 produces the substrate A, which molecule is transferred to species 2 when they are co-incubated. Then the substrate A is converted into the final compound X via enzymatic reactions of species 2. Example: when the substrate A is directly added into the reaction mixture, species 1 converts the substrate A into intermediate B. If the species 2 is co-incubated with species 1, then species 2 converts this intermediate B into the final product X; 3) a branched pathway. Example: when the substrate A is directly added into the reaction mixture, species 1 convert the substrate A into intermediate B. If the species 2 is co-incubated with species 1, then species 2 converts the intermediate B into the compound X or the compound Y depending on the environmental conditions (e.g. pH, temperature etc); 4) a repeated back and forth interactions. In an example for oligomer (or polymer) productions by the co-incubation of microbial communities, species 1 and 2 can show mutual interactions to make oligomer/polymer by adding a small unit molecule to the intermediate molecules. When the starting material and unit molecules are directly supplied into the microfluidic co-incubation bioreactor, species 1 can initiate to polymerize monomers to dimer, and then species 2 can help to modify the dimer intermediates to trimers. Under the same manner, both species can produce oligomer/polymer by interacting with each other continuously; 5) an induction by second species. Example: species 1 can convert the substrate A to the final product X only when the induction pressure exists. In this case, species 2, which can produce the inducing molecules for species, 1 can be co-incubated with species 1, resulting in the production of the compound X by species 1. 
     The devices and methods of the present invention can be used as medicinal or dietary preparations, in the form of pills or other pharmaceutical or dietary compositions. In some embodiments, pills may typically be shaped in a small rounded mass to be swallowed whole. The pills of the present invention contain one or more devices of the present invention. Thus, for example, a dieting pill can be made by incorporating into the pill a co-incubated community of microorganisms that can consume nutrients. Variations may include incorporating into the pill a co-incubated community of microorganisms that can degrade foods more completely, for example by increased cellulose degradation. A variety of carriers and additives may be used in the pill as well. The pill may have permeable or semipermeable walls. A subject can consume this pill pre, during, and/or post-food consumption. The pill may be made of a size that is large enough to accommodate one ore more devices or droplets of the present invention, yet small enough so that so that it freely passes through a subject&#39;s intestines. Alternatively, the pill may be removed by the natural digestive processes in the intestine. As well, the pill may be made by making the community-containing devices magnetic, and then swallowing a magnet that would attract and remove all of them. This may extend the duration of activity of the pill&#39;s components. Such pills may be suitable for dieting purposes, as well for improved food digestion. 
     EXAMPLES 
     Methods. The microfluidic device was fabricated by using multilayer soft lithography in polydimethylsiloxane (PDMS) (Anderson et al., 2000,  Analytical Chemistry  72: 3158-3164). The culture wells and the communication channel were separated by a 0.2 μm polycarbonate membrane and bonded together by using PDMS pre-polymer (Chueh et al., 2007,  Analytical Chemistry  79: 3504-3508). 
     To make 2-sided GMDs cell cultures of  Escherichia coli  DsRed and  Bacillus cereus  GFP were grown in Luria-Bertani (Miller formulation, BD) at 37° C., 160 rpm overnight. Liquid agarose was made by adding 4 wt % Type IX Agarose (Sigma) to Luria-Bertani broth and melted in a 65° C. oven for one hour. One-mL aliquots of liquid agarose were cooled to 37° C. and inoculated with 100 μL of cell culture. The warm agarose with cells was then loaded into Teflon tubing connected to a Hamilton Gastight syringe backfilled with fluorinated oil FC40. The Teflon tubing containing the warm agarose was placed over a hot plate set to 45° C. to prevent the agarose from forming a gel before plug formation. Plugs were formed in a PDMS device with two aqueous inlets and a carrier fluid inlet, using a standard PDMS plug making device, similar to devices used for protein crystallization applications (Li et al., 2006,  Proc. Natl. Acad. Sci. USA  103: 19243-19248.). Carrier fluid was the fluorinated oil FC40. Plugs were formed by flowing the warm agarose streams at 2 μL/min and flowing the carrier fluid at 10 μL/min. Plugs were collected in a 200 μm ID Teflon tubing and briefly passed over a chilling plate set to 1° C. to solidify the gel. Gel plugs were incubated in the Teflon tubing by immersing the tubing in Luria-Bertani broth and placing in a 30° C. oven overnight. Plugs were imaged after incubation using an IRE2 microscope (Leica) with a 1OX 0.3 NA objective and a 0.5× camera coupler. Fluorescent images were acquired with a Texas red filter set (TX2) with a 100 ms exposure time or a GFP filter set (L5) with a 100 ms exposure time. GFP and Texas Red images were overlayed using Metamorph software. 
     Bacterial strains of  Azotobacter vinelandii  (Av, ATCC 12837),  Bacillus licheniformis  (BI, ATCC 25972), and  Paenibacillus curdlanolyticus  (Pc, ATCC 51899) at exponential phase were individually inoculated into individual culture wells in the microfluidic device at a concentration ˜500-1000 live cells/well. The number of live cells loaded into each well varied by ±10%. The inoculated device was placed over a droplet of appropriate media on a siliconized glass cover slide, and the media filled the communication channel below the wells. The device was inverted and incubated at 30° C. The low nutrient-antibiotic media (CP media) contained carboxymethyl cellulose (1 g/L) as a sole carbon source, no nitrogen source, and penicillin G (100 μg/L). The high-nutrient media was TSB/1771 in a 4:1 (v/v) ratio. The number of viable cells in macro-scale cultures was estimated by agar plate counting, whereas the number of live cells in a microfluidic device was manually counted after the live/dead staining with solutions of SYTO9 (live) and propidium iodide (dead) (Molecular Probes). 
     Images of bacteria stained with live/dead dye were acquired by using an epi-fluorescence microscope (Leica) with either GFP (L5) or Texas red (TX2) filter sets, respectively. The GFP and Texas red images with the same background levels and exposure times were overlaid by using MetaMorph image software (Molecular Devices). 
     Mathematical modeling was performed by using Mathematica (Wolfram Research, Champaign, Ill.). 
     Statistical analysis was performed by using 2-way ANOVA with standard weighted-means analysis, where independent variables were time and community composition. P-values indicate the combined comparison of both variables. All error bars indicate standard errors. 
     Co-incubation of bacteria. A synthetic community (syntrophic in this case) was constructed by using three soil bacteria,  Azotobacter vinelandii  (Av),  Bacillus licheniformis  (BI), and  Paenibacillus curdlanolyticus  (Pc). This community was designed to survive under nutrient-limited conditions by reciprocal syntrophy, where each species performs a unique function required for the survival of the community ( FIG.  3 A ). In this community, only Av supplies nitrogen sources by fixing gaseous nitrogen into amino acids with a molybdenum-coupled nitrogenase under aerobic conditions, only BI reduces antibiotic pressure by degrading penicillin G with β-lactamases, and only Pc provides a carbon energy source, such as glucose, by using cellulases to cleave carboxymethyl-cellulose. 
     Initial attempts were conducted to co-incubate all three species of the community under well-mixed conditions in a test tube in either nutrient-rich or nutrient-poor media ( FIG.  3 B ). Here, the nutrient-poor media was cellulose/penicillin media (CP), which contained the β-lactam antibiotic penicillin G as the antibiotic pressure, only carboxymethyl cellulose (CM) as the carbon source, and N2 from the atmosphere as the nitrogen source. Av, BI, and Pc cannot maintain viability over time when cultured individually in CP media. In this co-incubation, the community was unstable regardless of nutrient availability ( FIG.  3 B ). In nutrient-rich media, the population size of BI rapidly increased, while the population sizes of Av and Pc rapidly decreased below the limit of detection. In CP media, the population size of Av increased, while the population sizes of BI and Pc decreased. Control experiments demonstrated that BI grew faster in nutrient-rich media, whereas Av grew faster in nutrient-poor media and showed the highest substrate affinity. In addition, neither the presence of heat-killed BI nor the degradation products of penicillin G had a critical effect on the viability of Av or Pc cells. These results indicate that, although the community has the potential for reciprocal syntrophic interactions, this potential is not realized under well-mixed culture conditions. 
     Space influences interactions between groups of bacteria. To test whether the community is stabilized by spatial structure, a microfluidic device was used that localized each bacterial species into an individual culture well separated from a microfluidic communication channel by a nano-porous membrane. This device spatially localized each species while allowing chemical communication among the species. Control experiments indicated that the bacteria remain confined and that chemicals were exchanged by diffusion through the communication channel. The device supported growth of all three species when Av, BI, and Pc were separated into individual culture wells of the same device and cultured in nutrient-rich media. 
     To test the influence of changes in spatial structure on this stability, the distance between the individual culture wells of the microfluidic device was varied, and the diameter of the communication channel between the wells was proportionally changed ( FIGS.  5 A- 5 B ). When all wells were inoculated with a mixture of all three species, effectively reducing the separation distance between species to a few micrometers, the community experienced a significant, overall population decline in 36 h ( FIG.  5 A ). Pc could not be reliably differentiated from Av, but there was no Pc in the mixture after 36 h. A similar decline was observed when each species was individually inoculated into a culture well separated from the other wells by 1800 μm ( FIG.  5 B ). As well, similar results were obtained when only two members of the community were cultured in the microfluidic device, where live cell numbers in cultures of two-member community were significantly less than those in cultures of all three community members. The community stably coexisted only at intermediate separation distances of the order of a few hundreds of micrometers ( FIG.  5 B ). These results suggest that a specific spatial structure is required for the stability of the community. 
       FIGS.  4 A- 4 C  illustrate how the stability of the community requires communication among the three species. Fluorescence images of each species cultured in an individual culture well of the microfluidic device with either all three species in individual culture wells or the same species occupying all three culture wells were taken. Bacteria were stained with a fluorescent dye to indicate live (green in original) and dead (red in original) cells. Figure shows graphs comparing the number of live bacteria over time in a device containing all three species in individual wells (circle) or in a device containing the same species in all three wells (triangles); error bars represent standard error with N=3, except for (Av, 0 h) with N=4 and (BI, community, 24 h), (Pc, community, 12 h), (Pc, community, 36 h), and (Pc, single species, 36 h) with N=2. P values were calculated by using two-way ANOVA. 
       FIGS.  5 A- 5 B  illustrate the concept of how a synthetic community only coexists at intermediate separations.  FIG.  5 A : a schematic drawing (left) of a mixed culture of all three species in every well of the microfluidic device and representative images (right) of a culture well containing all three species over time; bacteria were stained to indicate live (green in original) and dead (red in original) cells. Scale bar represents 50 μm.  FIG.  5 B : graph comparing the number of live cells of each species in devices with culture wells separated by four different distances. 
     Biosynthesis via co-incubation of microbial communities. It is possible to produce natural products by GMD-based co-incubation in a microfluidic device. To accomplish that, microorganisms that are involved in biosynthesis of desired natural products are used. Examples include the production of novel antibiotic derivatives by the co-incubation of two or more different species. In terms of co-incubation, species A produce the structural precursor of antibiotics, then species B modify the structure of antibiotics p oduced by species A by changing side chain or attaching sugars to the precursor. These synergistic reactions promote the derivatizations of precursors combinatohally. Technically, GMD and a microfluidic device may be applied together. This technique provides several advantages: i) GMD-based co-incubation via communications between species A and species B without cross-contamination; ii) physical confinement in a GMD may maintain the viability of microorganisms; iii) shorter culture time and smaller volume. Some examples of synthesis of natural products are listed below: 
     1) Production of novel antimicrobial agents. Example of biosynthesis system in a microfluidic device is the biosynthesis of novel antimicrobial agents by the co-incubation of different several Streptomyces species (Table 1). Some of species produce the hydrophobic precursor of streptomycin antibiotics, and some of other species modify the hydrophobic precursors by adding sugar moieties. 
     
       
         
           
               
             
               
                 TABLE 1 
               
             
            
               
                   
               
               
                   Streptomyces  species that can be used for the biosynthesis 
               
               
                 of novel antimicrobial agents by co-incubation 
               
            
           
           
               
               
               
               
            
               
                 Microorganisms 
                 ATCC 
                 Products 
                 Comments 
               
               
                   
               
            
           
           
               
               
               
               
            
               
                 
                   Streptomyces venezuelae 
                 
                 15439 
                 Pikromycin 
                 SV 
               
               
                 
                   Streptomyces fradiae 
                 
                 19609 
                 Tylosin 
                 SF 
               
               
                 
                   Saccharopolyspora erythraea 
                 
                 11635 
                 Erythromycin 
                 SE 
               
               
                 
                   Streptomyces antibioticus 
                 
                 11891 
                 Oleandomycin 
                 SA 
               
               
                 
                   Streptomyces peucetius 
                 
                 29050 
                 Daunorubicin 
                 SP 
               
               
                 
                   Bacillus subtilis 
                 
                 6051 
                   
                 BS 
               
               
                   
                   
                   
                 (test organism) 
               
               
                   
               
            
           
         
       
     
     2) Electricity-producing bacterial communities. Examples of biofuel cells that select for microbial consortia that self-mediate electron transfer have been identified by two methods (based on either the occurrence of a dominant band in a denaturing gradient gel electrophoresis pattern or on plating), and these are disclosed in Rabaey et al., 2004,  Appl. Environ. Microbiol.  70: 5373-5382. Thus, some communities of microbes may have the ability to generate electricity in fuel cells. The strains shown in Table 2 could be used as a starting point to identify active combinations of co-incubated microorganisms. Since the methods of the present invention have the ability to create communities and control spatial structure, one could conceivably screen various combinations in various structures in order to optimize fuel cell performance. 
     
       
         
           
               
             
               
                 TABLE 2 
               
             
            
               
                   
               
               
                 Overview of bacterial species that may have the ability to generate 
               
               
                 electricity in fuel cells (from Rabaey et al., 2004) 
               
            
           
           
               
               
               
               
               
               
            
               
                   
                   
                 Highest 
                 % 
                 No. of 
                   
               
               
                 Band or 
                 Accession 
                 homology 
                 Simi- 
                 identical 
               
               
                 isolate 
                 no. 
                 (accession no.) 
                 larity 
                 base pairs 
                 Taxon 
               
               
                   
               
            
           
           
               
               
               
               
               
               
            
               
                 2 
                 AY483162 
                 
                   Eubacterium 
                 
                 96 
                 114/ 
                 Firmicutes 
               
               
                   
                   
                 
                   aggregans 
                 
                   
                 118 a   
               
               
                   
                   
                 (AF073898) 
               
               
                 3 
                 AY483163 
                 
                   Lactococcus 
                 
                 100 
                 160/ 
                 Firmicutes 
               
               
                   
                   
                   lactis  subsp. 
                   
                 160 
               
               
                   
                   
                 
                   lactis 
                 
               
               
                   
                   
                 (AF515226) 
               
               
                 4 
                 AY483164 
                 
                   Pseudomonas 
                 
                 99 
                 129/ 
                 Gamma- 
               
               
                   
                   
                 sp. strain 
                   
                 130 
                 proteo- 
               
               
                   
                   
                 ARDRA PSI 
                   
                   
                 bacteria 
               
               
                   
                   
                 (AY364085) 
               
               
                 5 
                 AY483165 
                 
                   Enterococcus 
                 
                 100 
                 153/ 
                 Firmicutes 
               
               
                   
                   
                 
                   gallinarum 
                 
                   
                 153 
               
               
                   
                   
                 CECT9707T 
               
               
                   
                   
                 (AJ420805) 
               
               
                 6 
                 AY483166 
                 
                   Alcaligenes 
                 
                 100 
                 158/ 
                 Beta- 
               
               
                   
                   
                 sp. strain 2-6 
                   
                 158 
                 proteo- 
               
               
                   
                   
                 (AY296717) 
                   
                   
                 bacteria 
               
               
                 7 
                 AY483167 
                 Uncultured 
                 95 
                 97/ 
                 Bacteria 
               
               
                   
                   
                 bacterium 
                   
                 102 
               
               
                   
                   
                 clone up. 2 
               
               
                   
                   
                 (AY212541) 
               
               
                 8 
                 AY483168 
                 Swine manure 
                 98 
                 69/ 
                 Bacteria 
               
               
                   
                   
                 pit bacterium 
                   
                 70 
               
               
                   
                   
                 PPC89 
               
               
                   
                   
                 (AF445290) 
               
               
                 9 
                 AY483169 
                 Uncultured 
                 97 
                 144/ 
                 Bacteria 
               
               
                   
                   
                 earthworm 
                   
                 147 
               
               
                   
                   
                 intestine 
               
               
                   
                   
                 bacterium 
               
               
                   
                   
                 (AY154530) 
               
               
                 11 
                 AY483170 
                 
                   Lactobacillus 
                 
                 94 
                 145/ 
                 Firmicutes 
               
               
                   
                   
                   casei  YDT21 
                   
                 153 
               
               
                   
                   
                 (AF375931) 
               
               
                 12 
                 AY483171 
                 
                   Clostridium 
                 
                 100 
                 127/ 
                 Firmicutes 
               
               
                   
                   
                 sp. strain 
                   
                 127 
               
               
                   
                   
                 MDA2315 
               
               
                   
                   
                 (AY238334) 
               
               
                 13 
                 AY483172 
                 Uncultured 
                 100 
                 158/ 
                 Firmicutes 
               
               
                   
                   
                 
                   Enterococcus 
                 
                   
                 158 
               
               
                   
                   
                 sp. clone 
               
               
                   
                   
                 T8- 20 
               
               
                   
                   
                 (AF526922) 
               
               
                 Isolates 
               
               
                 KRP1 
                 AY483173 
                 
                   Pseudomonas 
                 
                 95 
                 189/ 
                 Gamma- 
               
               
                   
                   
                 
                   aeruginosa 
                 
                   
                 197 
                 proteo- 
               
               
                   
                   
                 ATCC 27853 
                   
                   
                 bacteria 
               
               
                   
                   
                 (AY268175) 
               
               
                 KRP3 
                 AY483173 
                 
                   Pseudomonas 
                 
                 95 
                 189/ 
                 Gamma- 
               
               
                   
                   
                 
                   aeruginosa 
                 
                   
                 197 
                 proteo- 
               
               
                   
                   
                 ATCC 27853 
                   
                   
                 bacteria 
               
               
                   
                   
                 (AY268175) 
               
               
                 KRP4 
                 AY483174 
                   Bacillus  sp. 
                 100 
                 693/ 
                 Firmicutes 
               
               
                   
                   
                 strain A24 
                   
                 693 
               
               
                   
                   
                 (AF397399) 
               
               
                 KRA1 
                 AY483175 
                 
                   Alcaligenes 
                 
                 98 
                 696/ 
                 Beta- 
               
               
                   
                   
                 
                   faecalis 
                 
                   
                 704 
                 proteo- 
               
               
                   
                   
                 (AF155147) 
                   
                   
                 bacteria 
               
               
                 KRA3 
                   
                 
                   Enterococcus 
                 
                 99 
                 1,101/ 
                 Firmicutes 
               
               
                   
                   
                 sp. strain 
                   
                 1,102 
               
               
                   
                   
                 CDC PNS-E2 
               
               
                   
                   
                 (AY321376) 
               
               
                 KRA4 
                 AY489119 
                 
                   Bacillus cereus 
                 
                 100 
                 1,101/ 
                 Firmicutes 
               
               
                   
                   
                 ATCC14579 
                   
                 1,101 
               
               
                   
                   
                 (AF290547) 
               
               
                 KRA5 
                 AY489119 
                 
                   Bacillus cereus 
                 
                 100 
                 1,059/ 
                 Firmicutes 
               
               
                   
                   
                 ATCC14579 
                   
                 1,059 
               
               
                   
                   
                 (AF290547) 
               
               
                 KRAN1 
                 AY489118 
                 
                   Enterococcus 
                 
                 99 
                 1,101/ 
                 Firmicutes 
               
               
                   
                   
                 sp. strain 
                   
                 1,102 
               
               
                   
                   
                 CDC PNS-E2 
               
               
                   
                   
                 (AY321376) 
               
               
                 KRAN2 
                 AY483175 
                 
                   Alcaligenes 
                 
                 98 
                 696/ 
                 Beta- 
               
               
                   
                   
                 
                   faecalis 
                 
                   
                 704 
                 proteo- 
               
               
                   
                   
                 (AF155147) 
                   
                   
                 bacteria 
               
               
                 KRAN3 
                 AY489118 
                 
                   Enterococcus 
                 
                 99 
                 1,101/ 
                 Firmicutes 
               
               
                   
                   
                 sp. strain 
                   
                 1,102 
               
               
                   
                   
                 CDC PNS-E2 
               
               
                   
                   
                 (AY321376) 
               
               
                 KRISO1 
                 AY483176 
                 
                   Ochrobactrum 
                 
                 98 
                 664/ 
                 Alpha- 
               
               
                   
                   
                 sp. strain 
                   
                 673 
                 proteo- 
               
               
                   
                   
                 LMG 20570 
                   
                   
                 bacteria 
               
               
                   
                   
                 (AY040351) 
               
               
                   
               
            
           
         
       
     
     3) Biosynthesis of various antibiotics by different stimulations. For example,  Streptomyces tenjimariensis  produces different kinds of antibiotics by the stimulation of other bacterial species when they are co-incubated (Slattery et al., 2001,  Microbial Ecology  41: 90-96). This information can be used as a starting point for the identification of novel antibiotics that are produced Streptomyces tenjimariensis. Of course, similar assays could be performed using other microorganisms as starting points. 
     4) Biosynthesis of poly-beta-hydroxybutyrate (PHB) via bacterial community. For example, it is possible to use combinations of various microorganisms, e.g. six cyanobacteria ( Microcoleus chthonoplastes, Lyngbya aestuarii, Leptolyngbya  sp.,  Oscillatoria  sp.,  Geitlerinema  sp., and  Gloeocapsa  sp.), one phototrophic, anoxygenic bacteria ( Chloroflexus  sp.), and several heterotrophic bacteria (Lopez-Cortes et al., 2008,  Microbial Ecology  56: 112-120). It is possible to co-incubate microorganisms for the production of antimicrobial agents (Iwami et al., 1992,  Appl. Environ. Microbiol.  58: 3879-3882). In another example, it is possible to form new lipoaminopeptides, acremostatins A, B, and C, by co-incubation of  Acremonium  sp. Tbp-5 and  Mycogone rosea  DSM 12973 (Degenkolb et al, 2002,  Biosci Biotechnol Biochem.  66: 883-886). 
     Induction and/or stimulation of competition and selection pressure. The devices and methods of the present invention can be used for inducing and/or competition to therefore stimulate evolution of microorganisms. Since local environmental conditions within a community could be defined using microfluidic methods, this would enable the creation of a landscape of selection pressures (over the space occupied by the community, overlapping gradients of various chemical and physical environments would create a space which is highly heterogeneous). In simple terms, providing selection pressure may result in one microorganism outcompeting (even starving to death) another microorganism. Spatial heterogeneity could aid in the rate of evolution as having heterogeneity in the local environments would enable the total population of the community to maintain diversity (for instance if all of the microorganisms in the community experienced a temperature of 45° C. then all of the communities will evolve to tolerate a 45° C. temperature, therefore the population may lose communities that have adapted to survive at low temperatures). In addition, since the evolution of some functions may require multiple separate evolutionary steps, the optimal evolutionary path may be to obtain a first evolutionary change in one environment and then acquire the second evolutionary change in another environment. In some examples, gradients of food/nutrients may be applied to bacterial co-incubation in order to elicit antibiotic production/antibiotic evolution. The separation of the microbes in the community would also maintain diversity by varying the selection pressure and reducing competitive dynamics in the system. 
     In some examples, providing selection pressure could be used to identify “killer microorganisms”, i.e. microorganisms that kill other organisms (Cowen and Lindquist, 2005,  Science  309: 2185-2819). Some bacteria under stress even cannibalize their siblings (Gonzalez-Pastor et al., 2003,  Science  301: 510-513). Assays for determining killer microorganisms may be direct, using a direct readout (cell death), or indirect readout (secreted molecules). Once such killer microorganism is identified, selection pressure could be created and applied on the killer microorganism, by having a second microorganism consume some of the nutrients from the first one. This could induce the killer microorganism to evolve into an even more potent killer. 
     Precise control of the local environment and microfluidic sorting techniques also enable the use of artificial selection schemes. In general, natural evolutionary processes rely on the ability of an adaptation of increase the fitness of the organism. In this context, fitness is the rate at which the organism reproduces and passes on their genetic material to offspring or the rate at which the organism increases the proportion of the total population with its genetic information. Artificial selection schemes can involve selection for organisms based on function of the organism, regardless of the rate at which the organism reproduces (i.e., a trait which does not influence fitness). For example, if one is trying to evolve a microbe that produces a fluorescent protein, since the fluorescence of a protein cannot be detected by the organism itself or by other organisms, it is unlikely that producing a fluorescent protein would increase the fitness of organism, so fluorescence is not a trait which would be selected for under natural selection. However, under artificial selection, the microbes can be passed through a fluorescence detecting device such as a Fluorescence Activated Cells Sorter (FACS) and the most fluorescent microbes can be separated from the non-fluorescent population of cells to pass on genetic information to the next generation. The ability to set the selection criteria (e.g., red fluorescent vs. green fluorescent, quantum efficiency of the fluorophore between 5-10%) enables the design of criteria that would optimize the rate of evolution. 
     In some examples, multi-functional complexes made by microbial communities can be constructed. Such a functional community can, e.g., involve degradation of pollutant polymers as well as generation of new useful materials such as renewable energy sources. 
     Self-sorting of microbial communities. The devices and methods of the present invention can be used for inducing self-sorting among microorganisms. Instead of using Fluorescence Activated Cells Sorter or some other active method of sorting, a passive method of sorting can be used. For example, droplets containing the microorganism of interest may get sorted based on a density, viscosity, and/or size. In this embodiment, spatially separated microorganisms are placed in/on droplets, and are then subjected to a functional screen. The function is coupled with a particular measurable reaction (chemical, physical, biological), which in essence creates a sorting mechanism. For example, changes in density, surface tension, CO 2  generation, surfactant generation, hydrophobicity change, electronegativity change, magnetic change, and/or size change, may be indicators of self sorting mechanisms. The droplets/plugs might be generated randomly and mixed (although compartmentalized) with many other droplets with different compositions; the sorting mechanism would allow simple identification and transfer of “good” plugs to other selection rounds. The selection round(s) can be repeated. One advantage is that one does not have to screen/measure plugs that don&#39;t perform the function of interest, test droplets self-segregate. 
     Self-sorting may lead to directed evolution of target functions (Wang et al., 2004,  Proc. Natl. Acad. Sci. USA  101: 16745-16749). Therefore, the generated self-sorting systems can be used to direct the evolution of preferred functions which are related to the sorting mechanism. Self-sorting will allow for high-throughput screening of conditions (essential for efficient evolution because need high diversity in screening populations) while also imposing a (possibly adjustable) selection criteria/selection pressure (those that don&#39;t separate themselves will not go on to further optimization rounds. 
     Self-sorting can be performed using direct screening: for example, if one is looking for polymerization catalysts, they would make more viscous by polymerizing substrate inside. Then one could apply high shear to break up all of the drops in a bucket except the most viscous ones, and then filter out the small fragments and capture the big drops (there are also separations based on size using hydrodynamics)—or just resort only to the big ones using standard sorting techniques. Alternatively, self-sorting can be performed using indirect screening, that requires more engineering: coupling the process of interest to the process that can be easily detected if one is looking for cellulases secreted by a bacterium so they can degrade a particular form of cellulose into sugars, adding to each drop enzyme cocktail (or have it expressed in the microbes) that converts sugars to CO 2 , and these bubbles float the “productive” drops. In a system where collecting the top 1/10 x  droplets, where X is large is important, self-sorting takes place in a field that changes more slowly than the drops are sorted. In the limit, the field is constant as gravity or magnetism. 
     Self-sorting can be used to evolve chemical systems (sets of interacting chemical reactions) to perform complex functions. The devices and methods of the present invention can be used to effectively control selection pressure/criteria, control local conditions, and do high throughput screening (automated sorting tricks, generating diversity in trials). Examples of directed evolution are disclosed in: a method for rapid screening and simultaneous amplification of bacterial surface-display libraries (Patel et al., 2001,  Biochem J.  357: 779-785); optical processing of Bacterial Libraries for directed evolution (Scruggs and Woodbury, 2003,  Biotechnology and Bioengineering  84: 445-451); and laboratory-directed protein evolution (Yuan et al., 2005,  Microbiology and Molecular Biology Reviews  69: 373-392) 
     One variant of the self-sorting method is magnetic self-sorting. Reactions with change in magnetism (any combination with any direction of changes among diamagnetism, paramagnetism, and ferromagnetism) could be used in self-sorting. Examples of reactions that produce paramagnetic solid from liquid or diamagnetic materials that can be used include (but are not restricted to): 1) Ag + -→ Ag: Ag +  has electron configuration of d10, so it is diamagnetic. Ag has electron configuration of s1d1 0, so it is paramagnetic. The autocatalyst is Ag (or its surface to be more detailed); 2) Guyard reaction: Mn(VII) (such as, KMnO 4 ) reacts with Mn(II) (some soluble salt such as nitrate or chloride) and makes MnO 2  which is a black paramagnetic powder. The autocatalyst is MnO 2  solid (its surface). Initially, all particles are not magnetic or are only weakly magnetic. As a result of detecting a specific molecule/function, a particle initiates a set of reactions which will create magnetic material (solid or liquid) inside or attached to the active particles. A magnetic field could then be applied to all of the particles and those which have created a magnetic material could be separate from inactive particles that have not created a magnetic material. If the amount of magnetic material created is proportional to the level of activity (more active, more magnetic) then a magnetic field could be used to measure a graded response (could detect high active, medium activity, low activity, no activity particles). Also, if a desired activity leads, directly or indirectly, to formation of a magnetic material, for example, by leading to a change in the redox state. 
     Screen for new compounds: This can be done in a variety of ways. One is to use methods to assemble communities of cells from soil extract. Once communities have been obtained, incubate plugs containing cells overnight. Then use the plug containing the communities as a condition, in the hybrid method: merge the gel droplet containing the community a buffer plug to extract the compounds which have been released by the community. Then use this with many, e.g. thousands of plugs, containing cells of  Streptomyces  species. After plugs containing  Streptomyces  have been merged with rare cell supernatant and incubated, screen for antibiotic production. In this way, compounds in the supernatant of the rare cell could induce the production of new antibiotic compounds. Another way is to use stochastic confinement to isolate communities of cell from ocean sediments using co-incubation in gel beads or in a spatially structure device. Once plugs containing the community have been collected, use the hybrid method to screen various media conditions such as (phosphate concentration from 0 to 100 μM, autoinducer 2 concentration from 0 to 100 μM, glucose from 0 to 10 mM). Then incubate the cells in the new media conditions. Then various functional/genetic tests can be performed in the plugs to determine which media conditions yield growth and/or production of compounds with desired properties. 
     Schematic explanation of synthetic communities. All of the members of species A, B, and C should depend on other members for the survival at particular conditions. For example, it can be assumed that one condition that it doesn&#39;t have essential components of I, II, and III for each community member. However, each member only can provide one of the essential components, for example species A can provide component I, but still requires B and C for its survival at particular condition. Other two species are placed in the same conditions, so they need to cooperate with each other at a particular condition for their survival. This condition can be tested by omitting one of the members in particular conditions, in which case the knock-out community cannot survive under the imposed harsh conditions. 
     Artificial Symbiosis Among Microbial Strains/Communities. 
     In an example of studying the natural symbiosis among the uncultured strains/unknown communities, a high throughput screening (HTS) for the identification of an antibiotic degrading community may be performed. If some bacterial community from natural soil sample can survive under the penicillin antibiotic condition, they will probably produce β-lactamases. Thus, the soil sample treated with cycloheximide (for growth inhibition of eukaryotes) is inoculated into a device of the present invention with various sub-geometries (A) or without any sub-geometry (B). This device is placed on the media supplemented by the penicillin G. The results are then analyzed. By comparing (A) and (B), it is possible to identify the smallest community producing β-lactamases. If the natural sample is chosen, then all strains attained from the sample should be identified. 
     In an example of high throughput screening (HTS) for quorum sensing (QS) community, quorum sensing bacteria and the reporter strains can be used to screen other QS strains in the sample. Based on the quorum sensing between Pseudomonas strain (PAO1) and reporter strain ( E. coli  LC4), it is possible to screen for new quorum sensing bacteria from soil bacteria. Thus, a QS reporter is mixed with soil bacteria and inoculated into the device of the present invention. The results are then analyzed. If luminescence is detected from several connected bacterial communities, high throughput method of screening for HSL producers is achieved. 
     In an example of high throughput screening for quorum quenching community, the coupled community of quorum sensing bacteria and the reporter strains can be used to screen the novel quorum quenching (QQ) strain/community in a sample (e.g. soil sample). A reporter strain is inoculated on an agar plate, and the cocktail of QS bacteria and soil bacteria is inoculated on the device by vacuum. Control experiment can be done without soil bacteria. The results are then analyzed. Potent candidates of quorum quenching bacteria can be identified in the non-luminescent region. 
     In an example of high throughput screening for a co-incubated bacterial community, e.g. syntrophic bacterial community, syntrophic bacteria may be used. If, for example,  Symbiobacterium thermophilum  is used, then it is important to indicate the one whose growth depends on co-incubating with cognate bacteria (e.g. thermophilic  Bacillus  sp.). Syntrophic bacteria can be used to find the alternative counterpart for co-incubation or for the elucidation of syntrophy mechanism. The syntrophic strain and the other (e.g. soil) bacteria are inoculated on the device, and a growing community is identified. The mode of syntrophism is the compensation against the lack of essential enzymes. Syntrophic model organisms are a rare find in the nature, yet they are very important with respect to microbial taxonomy, ecology, uncultivability, and genome library of microorganisms. The obtained results may help identify potent candidates of novel cognate bacteria. 
     Detecting bacteria and their susceptibility to antibiotics by stochastic confinement in nanoliter droplets using plug-based microfluidics 
     The followings are incorporated by reference in their entirety for descriptions of uses, applications and techniques for plug-based methods of analysis, manipulation of plugs, and fluid handling: 
     U.S. Pat. No. 7,029,091, Provisional application Ser. No. 60/881,012, Device and Method for Crystallization, Provisional application Ser. No. 60/875,856, Using Three-Phase Flow of Immiscible Liquids to Prevent Coalescence of Droplets in Microfluidic Channels: Criteria to Identify the Third Liquid and Validation with Protein Crystallization, Provisional application Ser. No. 60/763,574. Method and Apparatus for Assaying Blood Clotting Continuation application Ser. No. 11/174,298, Application of a Microfluidic System, US Utility application Ser. No. 11/082,187, Microfluidic System Provisional application Ser. No. 60/623,261, Microfluidic Devices, Provisional application Ser. No. 60/585,801, Applications of a Microfluidic System. Continuation in Part application Ser. No. 10/765,718, Device and Method for Pressure-Driven Plug Transport and Reaction, Divisional application Ser. No. 11/589,700. Device and Method for Pressure-Driven Plug Transport and Reaction. Provisional application Ser. No. 60/394,544, Device and method for pressure-driven plug transport. Provisional application Ser. No. 60/379,927. Device and Method for Pressure-Driven Plug Transport. 
     Rapid detection of small particles such as pathogens, environmental pollutants, and microorganisms is important for both the security and health of society at large. This project will establish the scientific foundations for rapidly detecting small particles at low concentrations by combining controlled chemical autocatalytic amplification and stochastic confinement of small particles with the microfluidic expertise that has been developed in the inventors&#39; laboratories. We will focus on developing computational models to predict the optimal single step amplification and multi-step amplification cascades, and we will compare these models to existing biological amplification networks, including blood clotting and apoptosis. Simultaneously, we will identify microfluidic technologies for optimal stochastic confinement. Lastly. we will evaluate the outcomes of the first two project phases by performing ultrasensitive detection of a bacterial protease. InhAl. using the blood coagulation cascade. Ultimately. this research will develop a method of detecting single particles that will be adaptable for the detection of different analytes, responsive to multiple signals, and insensitive to the effects of noise and fluctuations. 
     Scientific Background 
     Detection of small particles from sources including pathogens, environmental pollutants; and microorganisms is important for both the security and health of society at large. Such detection is integral to ensuring the purity of drinking water, the safety of the food supply, and to diagnose sudden illnesses, especially those resulting from bacterial pathogens like anthrax or other biological agents. For example, bacterial infections of the blood, one of the major causes of sepsis, generally require a minimum of a day or more to diagnose, increasing the chances of patient mortality (Carrigan, S. D.; Scott, G.: Tabrizian, M. Clin. Chem. 2004, 50, 1301-1314). Shortening the time necessary to detect bacterial infections could significantly decrease the mortality rate and reduce the cost of treating patients with sepsis and other aggressive bacterial infections (Nguyen, H.B.; et al Emerg. Med, 2006, 48, 28-54). Similarly. reduced detection time would expedite efforts to eliminate or mitigate harmful effects of other small particles. We are interested in using controlled chemical autocatalytic amplification to detect small particles problematic in drinking water, biological fluids, and chemical waste. (Epstein, I. R.; Showalter. K., J. Phys. Chem. 1996, 100. 13132-13147; Igarashi, T.; Takahata, K et al Inorg. Chim. Acta 1983, 76, L167; Andres Ordax, F. et al Anales de Quimica 1992, 88, 440-443: Simoyi, R.H. J. Phys. Chem, 1985, 89, 3570-3574: Dateo, C. E.; et al Chirality 2002, 14, 166-168; Soai, K. et al Acc. Chem. Res. 2000, 33, 382-390.) 
     Amplification methods are the cornerstone of modem detection technologies, including ELISA and PCR. ELISA is a powerful tool for detecting target antibodies or antigens in a sample, and PCR has revolutionized molecular biology by enabling amplification of a specific genetic sequence. While ELISA has a high degree of sensitivity for detecting target particles for which an antigen is available, this method is less effective for detecting uncharacterized species. Also, PCR only provides a genetic profile of a particular molecule or enzyme and lacks the ability to directly assay the function of the detected species, such as reactivity or drug susceptibility. Although some types of antibiotic resistance have genetic markers, the mecA gene for instance (Murakami, K et al J. Clin. Microbial. 1991,29,2240-2244), genetic markers have not been identified for all antibiotic resistant strains of bacteria. 
     Therefore, a general method of amplifying and detecting a single molecule (for example a pathogenic enzyme or a non-biological chemical agent) or particle (a pathogenic bacterium) is needed with the sensitivity of an ELISA and the amplification capabilities of PCR. 
     Autocatalytic reactions are one means to amplify signals. (Epstein, I. R.; Showalter, K. J. Phys. Chem. 1996. 100, 13132-13147; Igarashi, T.; et al Inorg. Chim. Acta 1983. 76, L167: Andres Ordax, et al Anales de Quimica 1992, 88, 440-443: Simoyi, R.H. J. Phys. Chem. 1985. 89, 3570-3574: Dateo, C. et al J. Am. Chem. Soc. 1982, 104, 504-509: Metsger, L.; Bittner, S., Tetrahedron 2000, 56. 1905-1910; Sato. I.; et al Chirality 2002, 14, 166-168; Soai, K. et al Acc. Chem. Res. 2000, 33, 382-390; Murakami, K et al Clin. Microbial. 1991,29, 2240-2244; Vaskelis, A.; et al J. Electroanal. Chem. 1999,465, 142-152; Vaskelis, A.; et al J. Appl. Electrochem. 2002, 32, 297-303; Esumi, K. et al J. Coll. Interf. Sci. 2000, 226, 346-352.) However, autocatalytic amplification must be carefully controlled-excessive amplification of a signal would result in a system responsive to noise and insignificant fluctuations, leading to false-positive results. To create an efficient and robust detection method, we are interested in understanding and mimicking the ways nature has created amplification mechanisms of biological systems. Already, it is clear that creating threshold responses seems to be at least part of the solution to regulating autocatalytic amplification. 
     For example, innately amplifying biological networks of hemostasis and apoptosis are comprised of many autocatalytic enzymatic reactions that are held in check by inhibitors and produce a large autocatalytic response only under the proper conditions. The blood coagulation cascade is regulated by autocatalytic (positive feedback) reactions and inhibition reactions that produce a threshold response to stimulus, in this case, vascular damage. This robust system only shows a full amplification response to biologically significant vascular damage and neglects the random noise like metabolism of endothelial cells. Biological enzymes like those in the coagulation cascade are abundant in natural amplification processes, including caspases in apoptosis, kinases in regulation and amplification, metabolic enzymes, and transduction enzymes (Khosla, C.; Harbury, P. B, Nature 2001, 409, 247-252; Baldwin, J.E.; Krebs, H. , Nature 1981, 291, 381-382: Strogatz, S. H. Nature 2001, 410, 268-276; Davidson, E. H. et al, Science 2002, 295, 1669-1678; Brivanlou. A. H.; Darnell, J. E., Science 2002, 295, 813-818; Kuharsky, A. L.; Fogelson, A. L. Biophys. J. 2001, 80, 1050-1074, FIELD Reference Number: FIELD Journal Code:0370626 FIELD Call Number:). 
     Here, we propose to develop a general approach to achieve rapid detection of low concentrations of small particles that are adaptable for the detection of different analytes. responsive to multiple signals, and insensitive to the effects of noise and fluctuations. The overall approach for detection and amplification is described schematically in  FIG.  10   . This approach will rely on autocatalytic amplification in combination with stochastic confinement to improve detection sensitivity and time. We will focus our description on detection of single particles. but this approach can ultimately be expanded to detect single molecules. 
     Objectives 
     To achieve the overall goal of developing a method to rapidly detect small particles at low concentrations, we will pursue the following three objectives, which form a roadmap for the proposed work. 
     Objective 1. We will develop computational models to predict the optimal detection in a single amplification step by comparing many approaches and to predict how multiple steps can be combined into more efficient cascades. To validate these models, we will compare the models to the architecture of existing biological amplification networks, including blood clotting and apoptosis. This comparison will enable us to identify the key elements that must be retained in the simplified network and the elements that could be removed without a significant sacrifice in performance of the network. 
     Objective 2. We will identify microfluidic technologies suitable for stochastic confinement in the context of amplification. We will compare the effectiveness of confinement by encapsulation in droplets, by confinement in pores of membranes, and by confinement in materials that significantly restrict lateral diffusion, such as gels. In addition, we will analyze the potential effectiveness of physical, rather than chemical, multi-stage amplification by using the output of the first stage to trigger amplification in the second stage. We will also evaluate methods of tagging inactive particles with active molecules in the context of these methods of confinement and amplification. 
     Objective 3. We will experimentally evaluate the predictions from the threshold amplification cascades developed in Objective 1 and the stochastic confinement developed in Objective 2 by comparing these results to the interactions of a bacterial protease, InhAl, with the blood coagulation. 
     Preliminary Results 
     Below, we discuss preliminary results that are relevant to the proposed work to achieve rapid amplification of low concentrations of small particles. We have accomplished the following four goals: i) created a microfluidic two-stage amplification system for amplifying trace levels Co 2 + autocatalyst; ii) demonstrated that amplification in the reaction network of blood clotting is controlled by a threshold response, which can be modulated by controlling the spatial localization of initiators and autocatalysts; iii) demonstrated that bacterial proteases are potent initiators of blood coagulation, and this initiation can be controlled by spatial localization; iv) demonstrated that microfluidics and stochastic confinement can be used to accelerate detection of single bacterium in nL plugs of aqueous medium. 
     I) We have achieved two-stage chemical amplification by using a nonequilibrium inorganic reaction network with a time-dependent threshold ( FIG.  11   ).(Gerdts, C. J et al,  J. Am. Chem. Soc . 2004, 126, 6327-6331) 
     To create a system for amplifying trace levels of Co 2 +, an environmental pollutant, we built a two-stage microfluidic-based chemical amplification system, where two chemical reactions were coupled in a time—controlled manner. This system provided an optical, color-change output, making the amplification event visible to the naked eye. The purple Co 3 + complex (1) and KHSO 5  (2) decompose autocatalytically in the presence of Co 2 + to yield a colorless solution in which all of the Co 3 +has been reduced to Co 2 +. In the first stage, Co 3 + complex and KHSO 5  were merged with a small amount of Co 2 + to form small droplets. In the second stage, the output of the first stage, captured in these small droplets, was used as the input for the second stage, merging with more Co 3 + complex (1), KHSO5 (2), and KH 2 PO 4  buffer (4). We set the detection limit, or threshold, of Co 2 + by controlling the time allotted for the reaction in the first stage. When the initial Co 2 + concentration was above the threshold, the reaction completed during the first stage, and the reduced Co 2 + served as a cobalt source during the second stage, leading to rapid reaction in the second stage, This two stage amplification system achieved an amplification of more than 5000-fold. 
     ii) We have characterized the mechanisms by which amplification is initiated and modulated in the blood coagulation cascade ( FIG.  12   ). (Kastrup, C. J.; et al,  Proc. Nati, Acad, Sci, U. S.A. 2006, 103, 15747-15752; Kastrup. C. J. et al  Angew. Chem. - Int. Edit . 2007, 46, 3660-3662; Kastrup, C. J. et al  Biophysical Journal  2007.  In Pres ; Runyon, M. K. et al  Angew. Chem. - Int. Edit .    2004 ,  43 ,  1531   -   1536   ; Runyon, M. K et al  J. Am. Chem. Soc.  2007, 129, 7014-7015). 
     To characterize the mechanism of initiation of blood coagulation, we grouped ˜80 reactions of the hemostasis network into three modules based on their kinetics. These modules provide a mechanistic explanation of the function of the network—the threshold-dependent amplification effect of blood coagulation to stimuli is regulated by production and consumption of active coagulation factors. When the concentration of active coagulation factors exceeds a threshold value, the production rate is always higher than consumption rate. In this case, the signal can be amplified through the autocatalytic reaction. To test this idea, we built a chemical model that substituted one reaction for each module. 
     Interestingly, this artificial chemical model reproduced the threshold-dependent amplification of the biological amplification network. The chemical model for coagulation can amplify 1 mL of 10- 11 M acid to 10- 3  M in approximately 30 s. 
     By using micropatterned surfaces, we found that this amplification process has a threshold to both concentration of stimuli and the size of surfaces presenting the stimuli. The value of the threshold concentration of stimuli and the threshold size of a patch of stimuli can be adjusted by tuning the kinetics of reactions of production and consumption in the coagulation cascade. Only a stimulus above a critical size (signal) can initiate coagulation, while a small stimulus below a critical size (noise) cannot trigger the coagulation cascade. The robust threshold response of initiation of coagulation to the size of a patch of stimulus can be used as a detection method. 
     iii) Bacterial proteases are potent initiators of blood coagulation, and this initiation can be controlled by spatial localization ( FIG.  13   ). 
     We found that a secreted protease of  Bacillus anthracis  ( B. anthracis ), the anthrax-causing pathogen, can directly activate coagulation factors and initiate coagulation. This protease was identified as zinc metalloprotease InhAl and was found to activate prothrombin and factor X. We also demonstrated that blood coagulation displayed a threshold response to the spatial localization of bacteria. Bacteria initiated coagulation when localized into clusters, while an equal or larger amount of bacteria did not initiate coagulation when dispersed in the same volume of blood. This threshold response could be used to detect colonies of bacteria above a specific size. Presumably, this threshold could be shifted to enable detection of single bacteria. 
     iv) Detection of single bacteria can be accelerated by stochastic spatial confinement by using plug-based microfluidics ( FIG.  14   ). 
     In addition to designing and understanding amplification networks, our previous work has also focused on the role that confinement can play in detecting low amounts of stimuli. In an open environment, proteases and other chemicals secreted by bacteria diffuse away, diluting the concentration of these signals below the detectable level. To overcome this limitation, we have designed a microfluidic plug-based assay that reduces detection time by confining bacterium into nanoliter-sized plugs. This approach increases the effective concentration of the bacterium and allows released molecules to accumulate to detectible levels in the plug. 
     We used previously characterized resazurin redox indicator to detect  Staphylococus aureus . While the detection of 10 5  bacteria in 1 mL (which gives a concentration of 1 bacterium per microliter) would require 12 h in microliter-scale culture, confining a single bacterium in a plug one nanoliter in volume (which gives a concentration of 1000 bacteria per microliter) reduced detection time to as little as 2 h. 
     By combining the approaches of microfluidics, threshold-dependent amplification, bacterial detection, and stochastic confinement, the detection of single bacteria and other particles can be done on the time-scale of minutes. 
     Proposed Work 
     Our goal is to provide sufficient amplification to detect single particles or molecules with the naked eye. Assuming our readout molecule has a high extinction coefficient of approximately 100,000 cm· 1 M- 1  and the smallest particle than can be easily seen is 10 um, the amplification cascade would have to generate on the order of 6+10′ 11  molecules to provide the absorbance value of 1. Detecting a particle carrying approximately 6000 active molecules would require an amplification of 10 8  We will consider less than one hour to be a reasonable time scale of detection. Taking 1000 s (˜20 min) as a guide, the average turnover required will be on the order of 10 5  s. This is a reasonable number, accessible, in principle, even to direct enzymatic and non-enzymatic kinetic schemes. This number could be significantly improved by using multi-stage amplification with careful network design, leading to more rapid detection with stronger signal. 
     Proposed work to achieve Objective 1. 
     To design an efficient amplification cascade, we will develop computational models for amplification and compare these models to biological amplification networks. The robust amplification of this scheme will rely on a threshold that makes the system unresponsive to stimuli below the threshold, or desired detection limit, such as “noise”. The underlying threshold required for this approach is shown schematically in  FIG.  15    below. Biological networks of hemostasis and apoptosis have solved this problem of threshold-driven amplification successfully, and we have been able to learn from the network of hemostasis and mimic it chemically. These results have provided confirmation that such networks can be understood and their functions reproduced. These networks have been optimized by evolution and are good models for in-depth understanding. On the other hand, these networks have evolved under many constraints (such as available protein chemistry). There could exist network architectures that are intrinsically superior to the existing biological networks that did not evolve due to the cellular constraints but could be built chemically by using inorganic reactions driven at high rates by pH and redox gradients not accessible to mammalian cells. 
     Comparing individual amplification schemes. 
     To generate thresholds and steady states of a detectible species (called A) in the reaction network, there must be a competition between production and consumption of A. Therefore, to describe thresholds and steady states, we could look at the rate of production and consumption. In each scheme of amplification in our computational model, we will look at a binary combination of production and consumption rate laws. Each rate law follows one function in a basis set or a linear combination of some functions in the basis set. The functions in the basis set are chosen to be those that correspond to 0 th -order, 1 st -order. 2 nd -order, Michaelis- Menten, and cooperative (sigmoidal) kinetics, as plotted in  FIG.  16   , 
       FIG.  17    illustrates how thresholds and steady states could be generated from simple binary combinations of production and consumption rates of functions in the basis set, At an intersection between production and consumption curves (denoted Ccrit), the overall rate is zero, If the consumption rate is higher than the production rate on the right hand side of the Ccrit, such as the intersection on the right-hand side of  FIG.  17    panel D, we have a stable steady state because any deviation of [A] from Ccrit, either to the left or the right, will lead to a higher rate of production or consumption, respectively, that brings [A] back to Ccrit ⋅ In the other case, such as the left non-zero Ccrit in  FIG.  17    panel D, the system is at an unstable steady state, because any fluctuation in [A] will be further amplified to bring [A] away from Ccrit in the same direction as the fluctuation. Therefore, the unstable Ccrit is referred to as the threshold, because [A] needs to be above that concentration to further facilitate the product of [A] and thus amplify the signal, while the stable steady state is referred to as steady state. It is noted that a steady state requires infinite influx of reagents, which is unrealistic in actual analytical experiments. Therefore, in these computational models, we make the approximation that the reagents required to maintain steady states are unlimited. This approximation is reasonable at the beginning of the experiments, 
     We will evaluate each amplification scheme by the following  5  parameters:
           1 . Degree of amplification: amp = output/input. per initial recognition event or per one initial reaction or input catalytic turnover event.     2 . Time of response: time for an output substance to reach a detectable concentration, or a relatively infinitely large concentration.   Sensitivity to noise and the potential for false positives or false negatives: sen = d(output)/d(input) If this value is low, a small change of input by noise marginally affects output, making the system insensitive to noise.     4 . Inefficiency: ine {rate-at-steady-state}*W, where Wis the cost in energy or materials to make one molecule of interest at its steady state. We will not choose to use the integrated cost from the beginning to the time of response, because we generally work with rapidly responding models. The higher the inefficiency, the worse the approximation of unlimited reagents to maintain steady state becomes.     5 . Adjustability: the ability to change the parameters above by simple modifications of the kinetics (e.g. by adding or removing production or consumption via simple reactions). This will be either qualitatively or quantitatively defined in specific cases.       

     The question we will address in this objective will be one of strategy. If we have chemical activity on a particle (referred to as S for “signal”), and we will use it to provide 10 8  amplification in 20 min, what is the best strategy? For example, suppose we have a sigmoidal production rate and a 1 st -order consumption rate as shown in  FIG.  18   . If we want to reduce the threshold. there are several approaches. Two approaches would be adding a reaction that produces A through 1 st  -order or 0 th -order kinetics. The first case is shown by the reduction in the slope of the 1 st -order consumption of A ( FIG.  18    panel A). The second case is shown by the upward translation of the production curve ( FIG.  18    panel B). Another way to reduce the threshold is to translate both the production and consumption curves to the left ( FIG.  18    panel C). Physically, this means changing the rate constants of the sigmoidal production and adding a 0 th -order consumption. For each case, we will then determine the parameters and compare them to the parameters we will have for the actual experiment to decide which are the most suitable to achieve our goals. 
     In certain situations with constraints, we will also need to modify amplification schemes accordingly. For example, if the system has no threshold, we may want to add a consumption reaction to generate one or multiple thresholds. However, if we have to refrain from doing that, we will need to carefully look at the time of response. In another case, if we have a constant threshold. we will have to change the concentration of the activator. If, however, we have constant initial concentration of activators, we may change the threshold by changing the kinetics of production or consumption (adding or removing production or consumption). 
     To analyze a small number of particles, we will also need to take into account stochasticity. For example, populations of cells generally exhibit substantial phenotypic variation. Elowitz et al Science 2002, 297, 1183-1186. showed that gene expression in  Escherichia coli  experiences noise generated by fluctuations in the gene expression system itself and in other cellular components. Reactions on the scale of single molecules exhibit fluctuation as well, such as mechanochemical coupling reaction of a single kinesin molecule waddling on a microtubule (in which energy from ATP drives the conformation change of kinesin that translates into movement along the microtubule) (Lau, A. W. C et al Phys. Rev. Lett. 2007, 99). More generally, since 1993, fluctuation theory has shown that the Second Law of thermodynamics, which implies directionality of physical events at nonequilibrium, is violated with a quantifiable probability, and this phenomenon is obvious in small systems observed in a short time, which could be relevant in some of our experiments (Evans, D. J.; Searles, D. J. Advances in Physics 2002, 51, 1529-1585), Qian and Reluga Phys. Rev. Lett. 2005, 94 considered nonequilibrium thermodynamics of a cellular signaling switch based on a reaction network involving phosphorylation and dephosphorylation. They showed that the fault safety factor, which was their definition of resistance to noise, increased as the phosphorylation free energy increased. 
     In cases when we will need to consider fluctuation, we will consider our models more carefully. One approach will be to modify the reaction networks. For example, Brandman et al. Science 2005, 310, 496-498, showed that a network composed of a fast feedback loop and a slow feedback loop sharing the same output and stimulus would provide a fast time of response as well as decent resistance to noise compared to networks each having two fast loops, two slow loops, one fast loops, or one slow loop. In the model, fluctuation can be accounted for in several ways, including expressing input or network parameters as probabilistic variables whose distributions could be determined from experiments or calculations and using nonequilibrium thermodynamics explicitly to consider the networks. 
     Combining individual amplification schemes into cascades. 
     The second part of this objective will be to develop a computational model to predict how multiple steps can be combined into more efficient, robust cascades having low sensitivity to noise while at the same time provide a higher degree of amplification and a more rapid detection response. A combination of two steps will be important, because a combination of many steps can be considered by combining two steps at a time into one. The idea of combing many steps was motivated from theoretical calculations by Goldbeter and Koshland Proceedings of the National Academy of Sciences of the United States of America-Biological Sciences 1981, 78, 6840-6844 who showed that 0 th -order ultrasensitivity could be achieved with a bicyclic cascade. 
     If we have sequential amplification steps 1 and 2, with the output of step 1 as the input of step 2, the overall parameters can be considered as below. 
     Degree of amplification: amp = amp 1  * amp 2 . Amplification can be improved by sequential steps. However, the improved amplification may be at the expense of other parameters. 
     Time of response: sum of the time of response for step 1 to have output exceeding threshold of step 2 and the time of response for step 2. Therefore, the time of response will be increased over single-step amplification. 
     Sensitivity to noise and the potential for false positives or false negatives: 
     
       
         
           
             
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     Inefficiency: ine = ine1 + ine2 (again, ignoring the integrated cost). As time of response increases, it will be more important to look at the approximation of unlimited reagents to maintain steady state, especially for step 2. 
     Adjustability: There will obviously be more room to adjust the parameters of each step. However, as the system becomes more complicated, the parameters become less independent and optimization of all parameters simultaneously will be challenging. 
     Generally, we could combine steps so that we have an optimal combination of suitable threshold, high amplification, small response time, and small sensitivity to noise. Some of these ideas are shown in  FIG.  19   . 
     For example, if we consider three different steps, 1, 2, and 3 and a combined sequence of 1-2 and 1-3. Rate curves for step 2 and step 3 are shown in  FIG.  17    panel A and  FIG.  17    panel B, respectively, We will also consider two cases in which output from step 1 can help amplification in step 2 or 3 by increasing the slope of the production rate (case A) or decreasing the slope of the consumption rate right after the threshold (case B). 
     Provided the kinetics in step 2 and step 3 do not change dramatically after the input from step 1, a qualitative comparison of sequences 1-2 and 1-3 are shown in Table 3. Quantitative comparisons will be performed in the computational model. 
     
       
         
           
               
               
               
               
               
               
             
               
                   
               
               
                   
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     Table 3. Comparison of amplification, time of response, and sensitivity to noise of the two sequences of amplification steps described in the paragraph above. 
     Compare the model to the architecture of the existing networks. such as blood clotting and apoptosis. 
     In reality, reaction networks are complicated. Our challenge lies in collapsing a reaction network into only two reactions-production and consumption-while retaining the features pertinent to amplification. We will identify the elements that must be retained in the simplified network, and the elements that could be removed or simplified without a significant sacrifice in performance of the network. The idea of coarse—graining reaction networks has been proposed in the past, such as in the work by Itzkovitz et al. Phys. Rev. E 2005, 71. These researchers simplified networks by collapsing network motifs, which are patterns significantly recurring in the network, into nodes. Another approach to simplify reaction networks is to use design space, which represents the effects of all parameters by the kinetic order for activation of the activator module and the product of kinetic orders for activation of the repressor module and repression of the activator module (Atkinson, M. R.; et al J.Cell 2003, 113, 597-607). We will choose a suitable approach or combination of approaches for this Objective. Generally, network features to retain will be the desired input and output species and the species with the threshold concentration. Particularly, we will need to look at the rate laws and rate constants of each reaction, combine reactions, and simplify rate laws into a linear combination of basis functions in our basis set. Rate laws with smaller rate constants will be allowed to have a higher degree of simplification. 
     For example,  FIG.  20    shows the reaction network in blood clotting. One of the features in this network is the positive feedback loop involving thrombin (shown as factor Ila in  FIG.  20   ), which allows amplification in this network. In fact, our group has characterized the threshold behavior of this network. We were able to make correct predictions by considering the kinetics of this network with higher-order autocatalytic production of the activators and 1 st -order consumption of the activators (Kastrup, C. J et al Proc. Natl. Acad. Sci. U. S.A.2006, 103, 15747-15752; Runyon, M. K. et al Angew. Chem.-Int. Edit. 2004, 43, 1531-1536). The works cited here demonstrated that we captured the properties of the network, at least in the context of amplification. 
     Another example of a naturally occurring network that has a threshold concentration and exhibits amplification via autocatalytic kinetics is the network of caspases.  FIG.  21    shows a simplified version of this network involving caspase-9 and caspase-3, which are involved in a signaling pathway leading to apoptosis. This simplified network shows two positive feedback loops, each involving caspase-9 or caspase-3. These feedback loops play a role in providing higher-order production rates. The combination of these feedback loops and inhibition reactions generates threshold concentrations for caspase-9 and caspase-3. Thus, a network similar to this could be used as an amplification scheme. Generally, we will look for ways to simplify complicated networks while capturing features for an amplification scheme that will not be too computationally expensive. 
     To complete the discussion of Objective 1, steady state kinetic diagrams will not be entirely predictive for static, batch-style experiments. In other words, these diagrams may work well to describe the clotting cascade in vivo, because clotting factors are continuously synthesized in the liver and secreted into the blood stream. This production balances the degradation that also takes place, and the system can maintain the steady state for dozens of years. A similar argument may be used to describe a network operating inside a cell. 
     However, in a batch-style experiment, the starting materials are intrinsically limited. While steady-state approximation may be predictive at early times, the starting materials are rapidly consumed as amplification proceeds, and the rates of all processes are affected. In addition, for sub-threshold stimulations with an activator, only a finite amount of inhibitors will be available to resist activation and maintain the system under the threshold. This point raises additional considerations for the design of optimal amplification networks that operate in this batch mode. For example, catalytic inhibitors may be more suitable than stochiometric inhibitors in this mode. The maiority of inhibitors in the clotting cascade are stochiometric, which will be a good design in the steady-state mode of operation and may be superior to catalytic inhibitors by providing a more rapid and stable response. We propose comparing three different approaches to confinement in the following section. 
     Proposed work to achieve Objective 2. 
     We will identify microfluidic technologies suitable for stochastic confinement in the context of amplification by comparing confinement by encapsulation in droplets (as demonstrated in  FIG.  14    of preliminary results), placement in pores of membranes, and by confinement in materials, such as gels, that significantly restrict lateral diffusion. In addition, we will analyze the potential effectiveness of physical, rather than chemical, multi-stage amplification by using the output of the first stage to trigger amplification in the second stage. To detect inactive particles, we will evaluate methods of tagging inactive particles with active molecules in the context of these methods of confinement and amplification. 
     The proof of concept for confinement in plug-based microfluidic devices has been recently described by our group (see  FIG.  14    in the preliminary results). Here, we will consider it in the context of detection and amplification. We will use plug-based microfluidic methods to describe the advantages and characteristics of stochastic confinement, but the same arguments apply to the other two methods. This discussion assumes that the particles targeted for detection are active. Active particles may have intrinsic activity; secreted bacterial proteases such as InhAl provide a good example of an activity associated with particles. Alternatively, particles may have no intrinsic activity, such as bacterial spores. This problem can be overcome by decorating inactive particles with binding molecules (e.g. antibodies) conjugated to active molecules. We consider this scenario later in this Objective. 
     Stochastic confinement as an approach to increase sensitivity and selectivity. 
     Consider a mixture of highly active, target particles and interfering particles with lower activity. 
     Stochastic confinement achieves two goals. First, it increases the local concentration of active particles in each plug compared to the concentration of active particles in the bulk solution. When combined with the threshold-based amplification, stochastic confinement increases local concentration and enables detection of lower activities and concentrations than would be possible otherwise. Second, stochastic confinement provides additional selectivity in this process of amplification. When interfering particles are in a large excess, the total activity of interfering particles may be higher than the total activity of active particles of interest. 
     Even with kinetic amplification via a threshold response, there is no apparent way to detect the signal from the particles of interest in the presence of high background signal from the interfering particles unless separation is used to isolate the particles of interest. This situation may be commonly encountered in the microbiological analysis of environmental samples. For example, human samples. including skin, saliva, and stool samples, being analyzed for microorganisms are routinely contaminated with bacteria or other cells (blood). Stochastic confinement is an attractive method to compartmentalize the active particles separately from the interfering particles. Therefore, as long as the threshold is tuned properly, the amplification cascade can selectively respond to only the active, target particles even in the presence of a large excess of interfering particles. 
     We will use results of our simulations in Objective 1 to identify confinement concentrations and volumes required to initiate the amplification cascades by a single bacterium, such as a  B. anthracis  bacterium secreting InhAl and NprB proteases. These volumes would provide a guide for comparison of the three confinement approaches given in  FIG.  22   . 
     Comparing three approaches to stochastic confinement. 
     Stochastic confinement in plugs is a method for detection of particles, because this method is substantially complete. well-defined, and previously utilized in our research, as demonstrated in the preliminary results section. Non-specific adsorption of active molecules to interfaces can be minimized, (Roach, L. S.; et al Anal. Chem. 2005, 77, 785-796) a problem for many confinement techniques. We will also consider the problem of storing 2D and 3D arrays of plugs in optically accessible geometries and with minimal coalescence of plugs. In addition, this substantially complete confinement could be detrimental for some methods of amplification that do not operate optimally under batch conditions, such as those that require an influx of stochiometric inhibitors to maintain the threshold response. Confinement in membranes, such as anodically etched alumina membranes, is a possibility. because this method can provide large-area confinement inexpensively and with no need for fluid handling. We will evaluate interference from the walls of the membranes with the reactions and potential “leakage” of molecules into and from the unconfined third dimension. This leakage could be beneficial for some reaction network designs by providing a better threshold response. Confinement in gels is perhaps the most technically simple method, and a number of materials can be used to reduce diffusion constants of molecules and provide confinement, including liquid crystal phases, lipidic cubic phases, and polymer gels. (Wachsstock, D. H.; et al Biophysical Journal 1994, 66, 801-809) The drawback of gels is the lack of well-defined confinement, possibly unpredictable dependence of diffusion constants on charge and size of molecules, and potential limitations on rates of reactions than can be achieved when diffusion of reagents is dramatically slowed down. Nevertheless, these systems can be investigated (especially intrinsically nanostructured phases like lipidic cubic phases), as some of these disadvantages could be overcome and even utilized. For example, the difference in diffusion constants between reagents and autocatalysts could be used to provide rapid amplification without local loss of autocatalysts. 
     Expanding stochastic confinement to multi-step amplification. 
     Two-step amplification by physically separating the chemical stages could be valuable for increasing the speed and degree of amplification by broadening the range of chemistries that can be used in the two stages. In a single-step, single-stage amplification cascade, the chemistry may limit the “gain” of an amplification cascade that can be achieved reliably. In a single-step, two-stage amplification cascade, the chemistries of the two stages must be mutually compatible and must not interfere. By separating amplification into two independent physical steps, we could use the same chemistry twice and increase the gain of the cascade as gain squared. Alternatively, we could access chemistries that provide amplification but are incompatible in the same solution, such as those requiring oxidizing and reducing conditions, or acidic or basic pH conditions. Finally, volumes in the first step of amplification may have to be sufficiently small to ensure that stochastic confinement is effective. If these volumes are too small to be visible by the naked eye, a second physical amplification step would significantly enhance the usefulness of such detection. We will evaluate the feasibility of introducing a second physical step of amplification into the plug-based microfluidic confinement, the membrane confinement, and the gel confinement systems ( FIG.  23    below). 
     Detection of active and inactive particles. 
     Active particles are abundant targets for detection. Bacteria secrete a number of virulence factors and other enzymes, such as phosphatases, sidephores, exotoxins, lipases, coagulases, elastases, immune response inhibitors, and proteases that can be detected via their intrinsic activity. The advantage of confinement methods is that active molecules do not have to be secreted. For example, gentle lysis of a bacterium trapped in a plug can provide a high local concentration of released bacterial enzymes that can be used in detection and amplification. Viruses produce neuramidase, which cleaves sialic acid from a large array of glycoproteins. We will estimate the degree of confinement and amplification for selective detection of single viral particles. 
     We will test several schemes to initiate the amplification cascade with the target analyte. The analyte could be labeled with the autocatalyst (Igarashi, T.; Takahata, K. et al Jpn. Kokai Tokkyo Koho; (Fuji Electric Co., Ltd., Japan). Jp, 2001, p 10 pp)-or the analyte could activate the autocatalyst in the first stage of an amplification cascade. Activation could be achieved through a binding event, such as avidin-biotin or antibody-antigen. Self-cleaving enzymes with protecting groups could be used as the autocatalyst, (Wood. D. W. J. Chem. Technol. Biotechnol. 2003, 78. 103-110; Wood, D. W.: et al Nat. Biotechnol. 1999, 17, 889-892) with the analyte initiating the activation of the enzyme. We will also investigate the possibility of decorating intrinsically inactive particles, such as bacterial spores, with binding molecules (e.g. antibodies, peptide ligands Knurr, J.; et al. Appl. Environ. Microbial. 2003, 69, 6841-6847) conjugated to active molecules (e.g. enzymes) ( FIG.  24   ). Stochastic confinement may provide a selective method of detection of particles that are capable of binding multiple active molecules without the need for separating the excess of the active molecules. This approach would only apply when the confinement can produce sufficiently small volumes that single particles decorated with active molecules contain a much larger number of active molecules than contained in the blank plugs. 
     We will demonstrate this detection idea by using plug-based stochastic confinement of single active or inactive bacterium. Based on the affinity of antibodies toward bacterial cell surface (&lt;100 nM affinities Sblattero, D.; Bradbury, A. Nat. Biotechnol. 2000, 18, 75-80), we can estimate the minimal concentration of antibodies that we need. In terms of possible numbers that can bind to a single bacterium, a previous report claims that more than 1000 nanoparticles can bind to a single bacterium. Provided antibody molecules are smaller than nanoparticles, even more antibody molecules can attach to a single bacterium (Zhao, X. J.; et al Proc. Natl. Acad. Sci. U.S.A. 2004, 101, 15027-15032). We will ensure that the concentration of antibodies is high enough to achieve sufficient binding, but not so high that confinement in extremely small volumes would be needed to localize the antibodies at a below-threshold concentration. 
     Proposed work to achieve Objective 3. 
     To experimentally evaluate the combined predictions from the threshold amplification cascades developed in Objective 1 and the stochastic confinement developed in Objective 2, we will use the interactions of InhAl with the blood coagulation cascade. We will begin these experiments concurrently with simulations and analyses in Objectives 1 and 2. These experiments will serve two goals. First, they will validate the overall approach and identify potential weaknesses to be addressed and refined in the work in Objectives 1 and 2. This goal will be important to ensure that the work in Objectives 1 and 2 is connected to experimental reality. Second, they will provide a realistic experimental benchmark against which all of the improvements provided by work in Objective 1 and Objective 2 can be tested. This goal will ensure that the improvements in one aspect of the system do not cause problems in other aspects and that these improvements enhance the overall performance of the system. 
     We will then use the optimal designs and approaches from Objectives 1 and 2 to perform ultrasensitive detection of single particles. To provide some specific details on the approaches we will use, we describe planned benchmark experiments that will utilize the blood coagulation cascade to detect the bacterial protease InhAl ( FIG.  25    below) by providing 10 5  fold amplification in a few hundred seconds. This amplification will likely improve further as we incorporate knowledge gained from Objectives 1 and 2 to optimize this cascade. We hypothesize that this two-step amplification can achieve lamer degree of amplification as compared to a single amplification loop. We will also look into the ability of this two-step amplification to improve resistance to noise. such as using one loop to amplify the signal and another loop as a buffer to noise. The time of response would be obviously more than one we would expect for one amplification loop only. 
     The effects of confinement methods outlined in Objective 2 will be considered as well. We will study how to tweak the kinetics as well as confinement of these reactions to achieve desired sets of parameters such as the threshold concentration, degree of amplification, resistance to noise, and time of response based on the kinetics of the blood clotting network we are familiar with. Once the theoretical consideration of this two-step amplification is well-understood, we will use it to do benchmark experiments described below. The results obtained from these experiments will also be used to improve simulations and analyses in Objectives 1 and 2. 
     Detection by capturing active molecules on beads. 
     First, we will use nickel-nitrilotriacetate (Ni-NTA) beads with known binding capacities to collect InhAl from solution. to mimic detection of bacteria. NTA group will bind, in the presence of Ni2+ ions, proteins modified with polyhistidine tags. Our collaborators have demonstrated expression and purification of InhAl by using polyhistidine tags, and we will use such methods to prepare this protease. Having beads with defined binding capacity, affinity, and kinetics will provide a much more controlled experimental system than working with live bacteria, which may show variability in protein synthesis and secretion. This controlled system would enable us to perform much more quantitative experiments than bacteria would provide. 
     Then, we will prepare beads coated with InhAl and will remove the excess of the protease. 
     Purification protocols based on magnetic Ni—NTA beads are well established. We will then perform an amplification reaction by using stochastic confinement ( FIG.  26    panels A to D) and evaluate the effectiveness of the clotting-derived amplification cascade. Our goal would be to understand the minimal loading (in molecules per bead) that can be reliably detected by this method. In addition, we will test the relationship between the number of molecules loaded on the bead versus the confinement volume required for detection. 
     In the second part of these experiments, we will perform a more stringent test. We will mix an excess of InhAl with beads and will not separate the beads from the excess but sub-threshold concentration of protease. We will then perform stochastic confinement and detection ( FIG.  26    panels E-H). Our hypothesis is that even for small beads that bind 10 6  molecules of the protease per bead, we would get reliable detection even in the presence of 10 3  molecules of background protease in the same volume. This number of molecules will correspond roughly to nanomolar concentration of the protease in picoliter volumes, easily accessible with today&#39;s fabrication and microfluidic technologies. Stochastic confinement of low number beads will result in concentration of the protease in plugs containing a bead. Because there will be a large number of excess, unbound protease molecules, all plugs will receive the same concentration of unbound protease molecules found in the initial bulk solution which will be below the initiation threshold. We will establish the detection limits and test the minimal number of molecules of the protease that need to be associated with the bead to reliably detect this bead in the presence of background activity. We will use this information to identify detection protocols that would be suitable for detection of single bacteria, as described in the next section. 
     Detection of single bacteria by stochastic confinement. 
     We will begin these experiments by utilizing  B. anthracis . These experiments can also be done with  B. cereus , a non-pathogenic bacterial species. We will use the information obtained in the previous section to predict the confinement volume needed to detect a single bacterium. While detecting single bacteria would be preferred, we will use antibody-coated beads to bind and concentrate bacteria should we find the activity of individual bacteria too low for detection. These types of beads are commonly used in agglutination assays. 
     We will perform stochastic confinement of the bacterial sample with the amplification mixture and monitor the reaction. The volumes that “turn on” the amplification cascade will indicate the presence of a bacterium. Simply by counting these volumes, we will establish the number of bacterial cells present in the original sample. In this experiment, we will achieve the goals outlined in the beginning of the proposal: visual detection of individual bacteria in less than 20 min. Overall designs that accelerate detection further would be even more attractive, since detection in 100 s rather than 1000 s could be used to make decisions in real time, such as establishing whether a water supply or a food source is contaminated and then decide on the alternatives or evaluating whether an individual is infected and administer treatment immediately. 
     To demonstrate enhanced selectivity of detection by this approach, we will perform the following experiment. To a sample containing low concentration of  B. anthracis  (100 CFU/mL), we will add a lame excess of interfering bacteria (10 5  CFU /mL) that have much lower protease activity individually (100 fold), but much higher combined protease activity (10 fold at this ratio of 10 5  to 10 2 ), We have several candidates for interfering bacteria that appear to be unable to initiate clotting, such as  B. circulans . The enzymatic activity of proteases secreted by these candidates will be evaluated by standard fluorogenic assays against the targets used in the amplification scheme. Under bulk detection mechanisms, either with amplification or by classical methods for measuring enzyme concentrations, the activity due to the excess of  B. circulans  will dominate the response ( FIG.  27    panels A and B). 
     We will then stochastically confine these bulk solutions in plugs. Under these conditions, the activity of individual  B. anthracis  will be sufficient to exceed the threshold and induce amplification, but the activity of individual  B. circulans  will not ( FIG.  27    panels C and D). Therefore, we hypothesize that we will be able to detect highly active  B. anthracis , even in the presence of a large excess of  B. circulars  with a higher total activity. These experiments would present an opportunity for rapid strongly amplified detection that is robust both to the presence of noise-due to threshold responses bunt into the amplification cascades-and to the presence of a large excess of partially active particles, even when the combined activity of these partially active particles exceeds the activity of particles being detected. This feature could also be useful for detecting inactive particles by binding active molecules to them, as outlined in Objective 2. Even when binding is not perfectly specific, the detection could proceed with high specificity. 
     Outlook 
     The work described in this proposal will establish the scientific basis for threshold-driven amplification that is augmented by stochastic confinement. A number of issues in the development of practical devices and methods-such as temperature sensitivity of the systems, selectivity in a complex background, cost and ease of use, and integration with imaging technologies or plug manipulationtechnologies, can be addressed separately. (Tan, Y. C.; et al PMicrofluid. Nanofluid, 2008, 4, 343-348; Huh. D et al Anal. Chem. 2007, 79, 1369-1376; Ahn, K.; Kerbage, C et al Appl. Phys. Lett. 2006, 88: Chabert, M.; Viovy, J.-L. Proceedings of the National Academy of Sciences 2008, 105, 3191-3196) We have focused on the first step, detection of particles, but the same design principles could be extended in the future to detection of single molecules. 
     Other applications for stochastic single-cell confinement: 
     Separating and testing mixed populations of microorganisms. Because we are able to segregate and test individual cells, we can both determine the composition of a mixed population of cells and also functionally test each type of cell in a monoculture. These types of measurements are important for functional testing rare members of a population whose activity may be masked by the maiority. In addition, it has been well-known that measurements at the single-cell level are important because population averaging can obscure contributions of individuals, even in clonal populations of cells (all the same species. generations of a single cell), lots of functional heterogeneity will exist. The function of sub-populations in a mixture can only be measured in single-cell experiments and these functions may be of use to determining understanding group behaviors and the range of responses which may occur after fractionation of the population through events which isolate low #s of cells such as by spatial structure or transplantation of a small # of organisms. 
     For example: 
     Sleeman and Cremers (J.P. Sleeman and N. Cremers,  Clin. Exp. Metastasis , 2007, 24, 707-715) show that tumor metastasis may be the result of a sub-population of cells which initiate tumor growth. Measuring the activity of these cells in different microenvironments may be more accurate diagnosis of different types of cancers. In addition, using stochastic confinement is a tool to study how individual cells behave which may lead to new therapies to prevent diseases such as cancer from spreading throughout the body. Wells and Ichim (C. V. Ichim and R. A. Wells,  Leuk. Lymphoma , 2006. 47, 2017-2027) state that “the frequency of stem cells in a tumor and their propensity to undergo self-renewal (P-sr) would have a direct impact on the curability of that tumor.” 
     Immune cells also are heterogeneous. The activity of individual cell types may have the ability to fight infections or may contribute to autoimmunity. (S. Jacquot and O. Boyer,  MS - Med. Sci. , 2006, 22, 1075-1080) 
     Determining heterogeneity in bacterial populations is also important. There can be heterogeneous responses to antibiotics (N. Dhar and J. D. McKinney,  Curr. Opin. Microbial. , 2007, 10, 30-38). Traditional screening methods might miss low frequency resistant cells because of the time it may take for a single resistant cell in a large volume to produce a measurable response. In addition, biofilms consist of multiple cell types, some of which swim away to initiate new biofilms. (P. S. Stewart and M. J. Franklin,  Nat. Rev. Microbial. , 2008, 6, 199-210.) 
     Stochastic confinement tests might also be useful in identifying trace contaminants. Although in some cases it might be possible to select for the response and growth of a specific type of organism (rare types/species), the contaminant may be similar enough to the majority species that there is no known way of differentiating between the species without sensitive tests that require isolation of single cells. It also may simply be easier to screen the cells individually than to develop a system for functionally isolating a set of cells in a sample with unknown composition. 
     Somboonna (N. Somboonna, et al,  Emerg. infect. Dis , 2008, 14, 445-453) also discusses how measuring mixed populations of cells is important for understanding mixed- population infections. 
     Taking multiple functional tests: 
     The ability to form multi tests on a single sample is also useful. Many testing agents may be incompatible or have similar readouts (for fluorescence testing there are only so many fluorophores, cannot test for two different activities that require GFP readout unless tests are in separate volumes). On a similar line of thought, you could design a series of field tests whose readout are all GFP. but since you are doing the test in single confined cells, you can simplify the # of technologies needed to take the measurements (only need a GFP detector). 
     Read LaFratta and Walt (C. N. LaFratta and D.R. Waft,  Chem. Rev. , 2008, 108 614-637) on high density testing arrays. 
     Nose-type measurements (not measuring volatiles, but instead taking hundreds of different measurements in order to characterize something) will become useful for diagnosis and screening for cells with optimal performance (either mutants or new species). Our method enables nose-type arrays of functional assay which will be superior to genetic based approaches which will be difficult to translate directly into cell phenotype. 
     It may also be useful to determine population ratios for bioprocesses (waste treatment, fermentations, engineered populations for chemical/drug production). Optimal conditions for various bioprocesses are probably not a homogeneous cell population, but rather a specific ratio of species/phenotypes. 
     See N. Somboonna, S. Mead, J. Liu and D. Dean,  Emerg. Infect. Dis , 2008, 14, 445-453; P. S. Stewart and M. J. Franklin,  Nat. Rev. Microbial. , 2008, 6, 199-210: C. N. LaFratta and D.R. Walt,  Chem. Rev. , 2008, 108, 614-637; A. P. Degenaar, A. Ismail and F. Bux,  J Appl. Microbial. , 2008, 104, 353-363; J.P. Sleeman and N. Cremers,  Clin. Exp. Metastasis , 2007. 24, 707-715; N. Dhar and J. D. McKinney  Curr. Opin. Microbial. , 2007, 10, 30-38; S. Jacquot and O. Boyer,  MS - Med. Sci. , 2006, 22, 1075-1080; C. V. Ichim and R. A. Wells,  Leuk. Lymphoma , 2006, 47, 2017-2027: E. R. Thaler and C. W. Hanson,  Expert Rev. Med. Devices , 2005, 2, 559-566; N. Szita, P. Boccazzi, Z. Y. Zhang, A. Zanzotto, A. J. Sinskey and K. F. Jensen,  J Biotechnol. , 2005, 118, S35-S35; C. A. Fux, J. W. Costerton, P. S. Stewart and P. Stoodley,  Trends Microbial. , 2005, 13, 34-40; and E. Y. Bridson and G. W. Gould,  Lett. Appl. Microbial. , 2000, 30, 95-98 
     Detecting Bacteria and Their Susceptibility to Antibiotics by Stochastic Confinement in Nanoliter Droplets Using Plug-based Microfluidics 
     This example describes plug-based microfluidic technology that enables rapid detection and drug susceptibility screening of bacteria in samples, including complex biological matrices, without pre-incubation. Unlike conventional bacterial culture and detection methods, which rely on incubation of a sample to increase the concentration of bacteria to detectible levels, this method confines individual bacteria into droplets nanoliters in volume. This confinement increases cell density and allows released molecules to accumulate around the cell, eliminating the pre-incubation step and reducing the time required to detect the bacteria. We refer to this approach as “stochastic confinement” (see  FIG.  28   ). This technology was used to determine the antibiogram or antibiotic sensitivity of Methicillin Resistant  S. aureus  (MRSA) to many antibiotics in a single experiment and to measure the minimal inhibitory concentration (MIC) of the drug cefoxitin (CFX) against this strain. In addition, this technology was used to distinguish between sensitive and resistant strains of  S. aureus  in samples of human blood plasma. High-throughput microfluidic techniques combined with single cell measurements also enable multiple tests to be performed simultaneously on a single sample containing bacteria. This technology may provide a method of rapid and effective patient-specific treatment of bacterial infections and could be extended to a variety of applications which require multiple functional tests of bacterial samples on reduced time scales. 
     Introduction 
     In this example, we demonstrate a method of rapid bacterial detection and drug susceptibility screening by using plug-based microfluidics to expedite diagnosis and treatment of bacterial infections. Bacterial infections are a major health problem, leading to more than 130,000 deaths annually in the United States alone (G. S. Martin, et al,  N Engl. J Med. , 2003, 348, 1546-1554). These deaths are often the result of nosocomial, or hospital acquired, infections and frequently involve drug resistant strains of bacteria (B. M. Farr,  Curr. Opin, Infect. Dis. , 2004, 17, 317-322; G. J. Moran, et al,  N Engl. J Med. , 2006, 355, 666-674). In addition, bacteremia, the presence of bacteria in the blood, is one of the major causes of sepsis and generally requires a minimum of a day or more to diagnose, increasing the chances of patient mortality (S. D. Carrigan, et al,  Clin. Chem. , 2004, 50, 1301-1314). Patient mortality rates further increase when inappropriate antimicrobial treatment is administered, which is estimated to occur in 23-30% of cases,  4    
     Shortening the time necessary to detect and identify an effective antibiotic regiment to treat bacterial infections could significantly decrease the mortality rate and reduce the cost of treating patients with sepsis and other aggressive bacterial infections (H.B. Nguyen, E et al  Ann. Emerg. Med. , 2006, 48, 28-54). However, attempts to reduce the assay time of traditional diagnosis and characterization techniques are impeded by the necessity to incubate bacterial specimens for hours to days to increase the cell density of the sample to detectible levels. To overcome this challenge, new PCR-based detection methods enable diagnosis in the one to four hour time frame (S. Poppert, et al  J Clin, Microbial. , 2005, 43, 3390-3397; K. P. Hunfeld,  Int. J Med. Microbial. , 2007, 297, 32-32). However, these methods only provide a genetic profile of the infecting bacterial species and lack the ability to directly test the bacteria&#39;s function, such as susceptibility to particular antibiotics. Although some types of antibiotic resistance have genetic markers, the mecA gene for instance (K. Murakami, et al,  J Clin. Microbial. , 1991,29,2240-2244), genetic markers have not been identified for all antibiotic resistant strains of bacteria. Therefore, antibiotic susceptibility is more accurately determined by a functional assay, especially for bacterial strains with unknown resistance mechanisms. 
     Microfluidics is an attractive platform for rapid single-cell functional analysis (M. Y. He, et al,  Anal. Chem. , 2005, 77, 1539-1544; A. Grodrian, et al  Biosens. Bioelectron. , 2004, 19, 1421-1428; D. B. Weibel. et al  Nat. Rev. Microbial. , 2007, 5, 209-218: Y. Marcy, et al  PLoS Genet. , 2007, 3, 1702-1708; J. El-Ali, et al  Anal. Chem. , 2005, 77, 3629-3636; A. Huebner, et al,  Chem. Commun. ,2007, 1218-1220; H. M. Yu, et al,  Lab Chip , 2007, 7, 726-730; C. J. Ingham, et al,  Proc. Natl. Acad. Sci. US. A. , 2007, 104, 18217-18222; R. D. Whitaker and D.R. Walt,  Anal. Chem. , 2007, 79, 9045-   9053   ). Plugs-droplets of aqueous solution surrounded by a fluorinated carrier fluid-provide a simple platform for manipulating samples with no dispersion or losses to interfaces 9 H. Song, et al, Angew.  Chem. - Int. Edit. , 2006, 45, 7336-7356; H. Song, Jet al,  Angew. Chem .- Int. Edit. , 2003, 42, 768-772). Here we show that microfluidic plug-based assays provide the ability to reduce detection time by confining bacterium into nanoliter-sized plugs. This confinement-we refer to it as “stochastic confinement”—decreases detection time by confining the sample into plugs that either have a single bacterium, or are empty. This approach increases the effective concentration of the bacterium, and allows released molecules to accumulate in the plug. Such stochastic trapping is commonly used for single-cell analysis in microfluidic devices (M. Y. He, et al ,  Anal. Chem. , 2005, 77, 1539-1544; Y. Marcy, et al,  PLoS Genet. , 2007, 3, 1702-1708; A. Huebner, et al,  Chem. Commun. ,2007, 1218-1220; P. Boccazzi, et al  App. Microbio. Biotech. , 2005, 68, 518-532; V. V. Abhyankar and D. J. Beebe.  Anal. Chem. , 2007, 79, 4066-4073; H. H. Gorris, et al  Proc. Natl. Acad. Sci. US. A. , 2007, 104, 17680-17685), and similar techniques have been used for single molecule and single enzyme work (P. Boccazzi. et al  App. Microbio. Biotech. , 2005, 68, 518-532: V. V. Abhyankar and D. J. Beebe,  Anal, Chem. , 2007, 79, 4066-4073; H. H. Gorris, et al  Proc. Natl. Acad. Sci. US. A. , 2007. 104, 17680-17685; A. Aharoni, et al  Chem. Biol. , 2005, 12, 1281-1289, O. J. Miller, et al  Nat. Methods , 2006, 3, 561-570; J. Huang and S. L. Schreiber,  Proc. Natl. Acad. Sci. US. A. , 1997, 94, 13396-13401: D. T. Chiu,et al  Science , 1999, 283, 1892-1895: J. Yu, Jet al  Science , 2006, 311, 1600-1603; Y. Akselband, et al,  J Microbial. Methods , 2005, 62, 181-197). Microfluidics also enables simultaneous execution of numerous assays of bacterial function from a single bacterial sample in the same experiment, which is especially useful for rapid antibiotic susceptibility screening. Previously, gel microdroplets have been utilized for susceptibility screening (C. Ryan, B. T. Nguyen and S, J. Sullivan,  J Clin. Microbial. , 1995, 33, 1720-1726; Y. N. Xia and G. M. Whitesides,  Annu. Rev. Mater, Sci. , 1998, 28, 153-184.) However, this method did not take advantage of the stochastic confinement effects in plugs or high-throughput screening methods of current microfluidic technologies. We applied this technology to characterize the drug sensitivity of a drug resistant strain of  Staphylococcus aureus  ( S, aureus ) and measure the minimal inhibitory concentration of the antibiotic cefoxitin (CFX). We also successfully distinguished between sensitive and resistant strains of  S. aureus  in infected samples of human blood plasma. This technology offers two advantages over traditional bacterial detection and drug screening methods: 1) stochastic confinement of single cells from dilute samples concentrates the bacteria, eliminates the need for pre-incubation, and reduces detection time; 2) each assay can be performed by using an individual bacterium, enabling hundreds of assays to be performed using a single, low density bacterial sample without pre-incubation. This technology will reduce the time needed to diagnose bacterial infections and enable patient-specific antibiotic regiments, 
     Experimental 
     Microfluidic device design and fabrication 
     Microfluidic devices were fabricated by using soft lithography (L. S. Roach, et al,  Anal. Chem. , 2005, 77, 785-796) as described previously (H. Song and R. F. Iamagilov,  J Am. Chem. Soc , 2003, 125, 14613-14619; L. Li, D. Mustafi, et al  Proc. Natl. Acad. Sci, US. A. , 2006, 103, 19243-19248; D. N. Adamson, et al,  Lab Chip , 2006, 6, 1178-1186) Except where noted below, plugs were collected in PFA or PTFE Teflon tubing (Zeus, Orangeburg, SC) with 150 □m or  200  μm inner diameter (I. D.). The tubing was cut at a 45° angle, inserted into the outlet of the microfluidic device up to the inlet junction, and sealed into the device by using PDMS prepolymer (10:1 elastomer to curing agent). To aid in imaging of the plugs, the Teflon tubing was wound in a spiral on a glass slide, and PDMS prepolymer was poured over the tubing to fix it in place. The device with attached tubing was then autoclaved at 135° C. for 10 min to sterilize, Once sterilized. the glass slide containing the tubing was transferred to a sterile Petri dish. 
     Flowing solutions into the microfluidic devices 
     All solutions were loaded into 1700 series Gastight syringes (Hamilton, Reno, NV) with removable 27 gauge needles and 30 gauge Teflon tubing (Weico, Wire &amp; Cable, Edgewood. NY). To maintain sterility, the syringes were filled and attached to the device within a biosafety cabinet, Syringes were connected to the microfluidic devices by using 30 gauge Teflon tubing. Solutions where flowed into the microfluidic devices by using previously described methods (D. N, Adamson, et al,  Lab Chip , 2006, 6, 1178-1186). Flow rates were controlled by using PHD 2000 infusion syringe pumps (Harvard Apparatus, Holliston, MA). 
     Bacterial Cell Culture 
     Cells were obtained from ATCC ( Staphylococcus aureus  ATCC# 25923 (MSSA) and  Staphylococcus aureus  ATCC# 43300 (MRSA)). Stock solutions of the cells were made by using Luria-Bertani media Miller formulation (LB) (BD, Sparks, MD) containing 30% (v/v) glycerol and stored at −80° C., For each experiment, a vial of frozen stock was brought to room temperature and streaked onto a Modified Trypticase Soy Agar (TSA II, BD, Sparks, MD) plate and incubated overnight at 30° C. Colonies from the plates were transferred to LB and cultured at 37° C. 140 rpm for 3 hat which point OD 600  was 1.5-2.0, Cell densities were then adjusted by diluting in LB. To maintain sterility. all procedures were performed in a biosafety cabinet and all tubing, devices syringes, and solutions used were either autoclaved, sterilized by EtOH, packaged sterile, or filtered through a 0.45 μm PES or PTFE filter. 
     Antibiotic preparation 
     Antibiotic stock solutions of ampicillin (AMP), oxacillin (OXA), cefoxitin (CFX), levofloxacin (LVF), vancomycin (VCM), erythromycin (ERT) were made by using 150 mM NaClaq at a concentration of 4000 times greater than the final concentration in the plugs, filter sterilized, and then frozen at −80° C. (AMP, Fisher Bioreagents. Fair Lawn. NJ; OXA, LVF, Fluka, Fuchs, Switzerland; CFX. VCM, ERT, Sigma, St, Louis, MO). Before each experiment, vials of the antibiotics were thawed and diluted IO00x with saline containing 80 μM fluorescein carboxylate. Fluorescein carboxylate was used to aid in indexing the resultant array of plugs. The plugs in  FIG.  32    contain no fluorescein carboxylate, since indexing was not required. The blank conditions consisted of 150 mM NaCl. Antibiotic solution were further diluted on chip 1:3 (v/v) during plug formation. 20 μM fluorescein carboxylate did not interfere with the viability assay. the activity of the cells, or effectiveness of antibiotic in tests performed on 96 well plates (data not shown). 
     Antibiotic testing on plates 
     Plates were made from Mueller Hinton Agar (Fluka, Switzerland). After autoclaving, the agar was cooled and antibiotics were added and 20 mL plates were poured. For CFX and OXA testing, 50 μL of MRSA and MSSA bacterial culture at 4×10 3  CFU/mL was spread onto separate TSA plates. The plates were incubated at 30° C. After 16.5 h and 40 h the plates were examined for colonies. MRSA colonies appeared on CFX after 16.5 h and on the OXA plates after 40 h. Even after 40 h, MSSA colonies did not appear on the CFX or OXA plates. For AMP, ERT, LVF, and VCM, 5 μL of culture at  2 × 10   4  CFU/mL were spread onto plates, and the plates were incubated at 37° C. for 12 h. After 12 h, growth of colonies on the plates was considered resistance to the antibiotic and no colonies on the plates were considered sensitivity to the antibiotic. 
     Comparing detection times of bacteria in nanoliter plugs and milliliter-scale culture 
     Plugs were formed by using the general methods described previously (D. N. Adamson, et al,  Lab Chip , 2006, 6, 1178-1186; J. O&#39;Brien and F. Pognan,  Toxicology , 2001, 164, 132-132). Plugs were formed in a 3 inlet PDMS device with 100 μm wide channels by flowing  S. aureus  culture in LB at 2×10 5  CFU/mL at 1 μL/min, a 20% alamarBlue solution in saline at 1 μL/min, and fluorinated carrier fluid at 5 μL/min. 25 plugs were collected in the channel Inlets and the outlet were sealed with silicon grease and the device was placed in a Petri dish containing LB for incubation. The same aqueous solutions were mixed 1:1 (total volume O.6 mL) in a 14 mL polypropylene round-bottom tube (BD Falcon, Franklin Lakes, NJ). After 2.8 h, plugs were made from the milliliter-scale culture by using the same method, with the cell culture containing alamarBlue for both aqueous inlets. Both sets of plugs were immediately imaged by using an epi- fluorescence microscope (IRE2, Leica) with a Cy3 (Chroma 41007, Cy3) filter and a 10×0.3 NA objective for a 5 ms exposure time with binning set to 4 and gain set to 200. Fluorescent images of plugs were processed by subtracting the average background intensity from all images. Line scans ( FIG.  29   b   ) with a width of 25 pixels were taken along the long axis of each plug. 
     Experiment to compare plug size to detection time 
     PDMS devices with channel widths ranging from 200 to 800 μm were prepared. Teflon tubing with diameter similar to that of the channel was cut at a 45° angle, inserted into the device up to the inlet junction. and sealed in place using PDMS. For  FIG.  29   , panels e and d, plugs were formed as above, with the exception that the˜1500 nL plugs were made via aspiration by using a manual aspirator. Plugs were collected in the Teflon tubing, the tubing was sealed with wax, and the tubing was placed in a Petri dish containing LB for incubation and imaging. Incubation and imaging was performed in a microscope incubator (Pecan GmbH, Erbach, Germany). Time zero is defined as the time at which the sample entered the incubator, which was less than 20 min after sample preparation. Fluorescence measurements were taken with 5 ms exposure times with a 5×0.15 NA objective using a 1×camera coupler for plug sizes 1, 12.6, 100, and 690 nL plugs and a 0.63×camera coupler for 1500 nL plugs. Plugs 125 nL in voulume were imaged with 10 ms exposure times with a 5×0.15 NA and a 0.63×camera coupler. 
     Plugs were analyzed by first separating them from the background by thresholding to exclude intensity below 250. The average intensity of the thresholded plugs was measured. Over time. the intensity of the plugs diverged into 2 groups, occupied plugs and unoccupied plugs. AH occupied plugs had a change in intensity more than 2 fold unoccupied plugs. Detection time is defined as the time at which the fold change of the occupied plugs compared to the intensity of unoccupied plugs reaches a maximum. Fold change in intensity is defined as the change in intensity of an occupied plugs divided by the average change in intensity of unoccupied plugs (Eq. 4). 
     Fold changet( t=ti ) =Occupied plug (I t=ti −I t=1 )/ Unoccupied plugs (I t=ti −I t=1 )(4) 
     In Eq. 4, I t=ti  is intensity at time point i. The intensity of the empty plugs is the average of all empty plugs in each experiment. 
     Comparing detection times of bacteria in nanoliter plugs and 96 well plates 
     For  FIG.  29    panel D, 96 well plates results for  FIG.  29    panel D were acquired in a Tecan Safire II plate reader (MTX Lab Systems, Vienna, VA) with Ex/Em 560/630 nm, gain 25, and 40 μs integration time. 200 μL of cell culture suspended in LB with 10% alamarBlue was added to wells of a Costar 96 well assay plate with black sides and dear, flat bottom (Corning, Corning, NY). Each data represents triplicate measurements taken at 37°C. Fold change in intensity from 96 well plate results were calculated by using Eq. 4 where the well with LB and alamar Blue only was the unoccupied plug condition. 
     Screening susceptibility of bacteria to many antibiotics 
     For anitbiotic screening experiments ( FIG.  30   ), an array of ˜50 nL antibiotic plugs was aspirated into Teflon tubing (200 μm ID) using a manual aspirator. Air spacers were included between each antibiotic plug to prevent merging of adjacent antibiotic plugs and to enable indexing of plugs in the output array. Plugs of saline solution were included as the first and last plugs in the preformed array to serve as positive controls. The Teflon tubing containing the array of antibiotic plugs was sealed into a device inlet by using wax (Hampton Research, Aliso Viejo, CA). To screen the susceptibility of MRSA and MSSA to each antibiotic, bacterial samples and indicator were merged with the preformed array of antibiotic. Bacterial samples were at a density of 4×10 5  CFU/mL in LB, and viability indicator solution was made by mixing 4 parts alamarBlue solution (AbD Serotec, Oxford, UK) with 6 parts 150 mM NaCl., The flow rate of the antibiotic array was 0.25 μL/min; the flow rate of the bacterial solution was 0.5 μL/min, and the flow rate of the viability indicator was 0.25 /min. The carrier fluid was FC40 (Acros Organics, Morris Plains, NJ) with a flow rate of 1.6 μL/min. For each antibiotic plug in the preformed array, approximately 50 smaller plugs (4 nL in volume) were formed, each potentially containing a single bacterium. The resulting plugs were collected in the coil PTFE Teflon tubing (I.D. =150 μm). 
     After plug formation, the tubing was disconnected from the PDMS device, and the ends were sealed with wax. The Petri dish containing the tubing was filled with 20 mL of LB solution to prevent evaporation of the plugs during incubation. The plugs were immediately transferred to a microscope incubator (Pecan GmbH, Erbach. Germany). Time zero is defined as the time which the plugs entered the incubator, which was about 20 minutes after plugs were formed. Fluorescence measurements for plugs were recorded by using an inverted epi-fluorescence microscope (DM16000, Leica, Bannockburn, IL) with a 10×0.3 NA objective (HCX PL Fluotar) coupled to a CCD camera ORCA ERG 1394 (12-bit, 1344×1024 resolution) (Hamamatsu Photonics) by using a 0.63× camera coupler. Images were taken of each plug using Metamorph Imaging Software (Molecular Devices. Sunnyvale, CA) every 30 min with exposure times of 5 ms. Plugs were analyzed by first separating them from the background by thresholding to exclude intensity below 250. The average intensity of the thresholded plugs was measured. The change in intensity at time point ti is I t=1 −I t=1 . In the experiment described in  FIG.  30    panel c, fluorescence intensity of plugs was normalized by setting the intensity of the brightest plug to 100. 
     Determining the minimal inhibitory concentration of a drug against a bacterial sample 
     For MIC determination in plugs ( FIG.  31   ), a procedure similar to screening susceptibility of many antibiotics was used. The input array of antibiotics consisted of plugs of CFX at a range of concentrations. Bacterial samples were MRSA or MSSA in LB at cell densities near 10 6  CFU/ml, In  FIG.  31    panel b and c, fluorescence intensity of plugs was normalized as described for  FIG.  30    panel c. 
     Detection and Drug Screening of MRSA and MSSA in Human Blood Plasma 
     For  FIG.  32   . cells were suspended in a 1:1 mixture of human blood plasma (Pooled normal plasma George King Bio-Medical, Overland Park, KS) and LB containing 40% alamarBlue. Plugs were formed and collected in Teflon tubing (200 μm ID). Images were taken with a 5×0.15 NA objective with a 0.63×camera coupler. 
     Texas red pictures were taking every 10 minutes with exposure times of 25 ms. A bright-field image was taken at beginning and end of experiment. Linescans of original plug images were taken at time 0 and time 7.5 h. Adobe Photoshop was used to enhance contrast of plugs shown in  FIG.  32   . 
     Results and Discussion 
     Stochastic confinement of individual bacteria into plugs nanoliters in volume reduces detection time. 
     To reduce the time required to detect bacteria in a sample, we designed a microfluidic device to confine single bacterium into plugs nanoliters in volume. In principle, when generating plugs with a small volume from a solution with a low concentration of bacteria, much of the volume of the initial solution forms plugs that contain no bacteria. There are a few occupied plugs, each occupied by single bacterium. As a result, the concentration of bacteria in the occupied plugs is greater than the concentration of bacteria in the initial solution. For example. if plugs nanoliters in volume were made from a culture with an initial bacterial concentration of 10 5  CFU/mL, one in ten plugs would receive a single bacterium, as illustrated in  FIG.  14    panel a. The concentration of cells in these occupied plugs would be one bacterium per nanoliter or 10 6  CFU/mL. In other words, 10 5  CFU/mL. corresponds on average to 0.1 bacterium per 1 nL, and confining this solution into nanoliter plugs creates plugs with 0 bacteria per nanoliter plug and with 1 bacterium per nanoliter plug.CFU/mL refers to the colony forming units (CFU), a measure of live bacteria, per milliliter. 
     To monitor the presence and metabolically active bacteria in plugs, a fluorescent viability indicator alamarBlue was added to the cultures. The active ingredient of alamarBlue is the fluorescent redox indicator resazurin (S. G. Franzblau, et al,  J Clin. Microbial. , 1998, 36, 362-366). Resazurin is reduced by electron receptors used in cellular metabolic activity, such as NADH and FADH, to produce the fluorescent molecule resofurin. Therefore, fluorescence intensity in a plug is correlated with the presence and metabolic activity of a cell, in this case, a bacterium. Because resazurin indicates cell viability, resazurin-based assays have been used previously in antibiotic testing (A. Martin, et al  Antimicrob. Agents Chemother. , 2003, 47, 3616-3619; K. T. Mountzouros and A. P. Howell,  J Clin. Microbial. , 2000, 38, 2878-2884; C. N. Baker and F. C. Tenover,  J Clin. Microbial. , 1996, 34, 2654-2659; P. Kaltsas et al,  Clin. Microbial. Infect. , 2005, 11, 109-114). Here, we use resazurin to detect both the presence of a live bacterium and the response of bacteria to drugs, such as antibiotics. We postulated that stochastic confinement would decrease detection time because in a plug that has the bacterium, the bacterium is at an effectively higher concentration than in the starting solution, and the signal-to-noise required for detection would be reached sooner as the product of reduction of resazurin accumulates in the plug more rapidly. 
     To demonstrate the ability of stochastic confinement to reduce detection time, a single sample of  Staphylococcus aureus  ( S. aureus ) containing the fluorescent viability indicator was split-half of the culture was used to generate plugs nanoliters in volume, and the other half remained as a milliliter-scale culture. Both the nanoliter plugs and the milliliter-scale culture were incubated for 2.8 hat 37° C. After incubation, the milliliter-scale culture was also used to form plugs. This experimental procedure is illustrated in  FIG.  29    panel b. 
     Confining bacteria into plugs nanoliters in volume reduced the time required to detect a change in fluorescence intensity of the viability indicator. Bacteria confined to and incubated in nanoliter-sized plugs showed a greater change in fluorescence intensity after 2.8 h than the bacteria incubated in the “unconfined” milliliter-scale culture (FIG. 29  panel e). Line scans of the plugs of bacteria that were incubated in plugs showed many empty plugs with low fluorescence intensity and a few occupied plugs with high fluorescence intensity (FIG. 29  panel b, top). However, lines scans of plugs of bacteria that were incubated the milliliter-scale culture have a lower, uniform fluorescence intensity ( FIG.  29    panel b, bottom). Therefore, bacteria confined to nanoliter-sizes plugs could be detected earlier than bacteria in a milliliter-scale culture. 
     In plugs containing single bacterium, the detection time was proportional to plug volume. Detection time was defined as the time at which the increase in fluorescence intensity reached a maximum. When single bacterium were confined in plugs ranging from 1 nL to 1500 nL in volume, detection time increased with the log of plug volume ( FIG.  30    panel d). implying that bacteria were dividing exponentially inside the plugs. This result is similar to previous estimates that detection time decreases by about 1.5 h for every order of magnitude increase in cell density (British Society for Antimicrobial Chemotherapy, BSAC Methods for Antimicrobial Susceptiblity Testing, 2007). The detection times measured for bacteria incubated in plugs were similar to detection times measured for bacteria incubated in a 96 well plate from cultures with similar initial cell densities ( FIG.  29    panel e). This result implies that incubation in plugs had no adverse effects on growth of bacteria. 
     The sensitivity of a bacterial strain to many antibiotics can be screened in a single experiment by using plug-based microfluidics. 
     Next, we extended this system to screen a single bacterial sample against many antibiotics to generate an antibiogram, or chart of drug susceptibility. A pre-formed array of plugs of six antibiotics-two beta-lactams (ampicillin, AMP, and oxicillin, OXA); a cephalosporin (cefoxitin, CFX); a fluoroquinolone (levofloxicin. LVF); vancomycin, VCM; and a macrolide (erythromycin, ERT)-was generated by aspiration. Antibiotics were tested at the breakpoint concentration (B. T. Tsuji, et al,  Diagn, Microbial. Infect. Dis. , 2007,58, 41-47), the accepted concentration of antibiotic at which bacterial susceptibility is determined ( FIG.  30    panel d). Since stochastic confinement of the bacterium into nanoliter-sized plugs generates many empty plugs, 50 plugs of each antibiotic were generated such that it was statistically likely that each condition would contain several plugs each occupied by a single bacterium. The plugs in this antibiotic array were merged with Methicillin Resistant  S. aureus  (MRSA, ATCC# 43300) at an initial cell density of 4×10 5  CFU/mL and the viability indicator on-chip to form plugs approximately 4 nL in volume, as illustrated in  FIG.  30    panel a. The merged plugs were collected and incubated for 7 hat 37° C. After incubation, the fluorescence intensity of the plugs was measured. 
     Occupied plugs containing an antibiotic to which the bacterial strain was resistant showed increased fluorescence intensity, whereas plugs containing an antibiotic to which the bacterial strain was sensitive showed no significant increase in fluorescence intensity ( FIG.  30    panel C). Plugs containing VCM were used as a negative control, because VCM inhibited this S. aureus strain in macro- scale experiments, in agreement with expectations (E. Keeler, et al,  Nature , 2006, 444 Suppl 1, 49-57) (data not shown). The average increase in fluorescence from all plugs containing VCM was used a baseline to which the increase in fluorescence intensity of all other plugs was compared ( FIG.  30    panel B. VCM). Four out of 49 (12 %) control plugs with no antibiotic ( FIG.  30    panel B, +blankl) showed an increase in fluorescence intensity more than three times greater than the VCM baseline, indicating that they were occupied by bacteria. However, the other plugs with no antibiotic showed an increase in fluorescence intensity similar to the baseline, indicating that they were unoccupied ( FIG.  30    panel B, + blank 1). 
     By comparing the fluorescence increase in each plug to the VCM baseline, we can determine which antibiotics were toxic to the bacteria. Plugs occupied with a viable bacterium showed an increase in fluorescence intensity greater than three times the VCM baseline.  FIG.  30    panel C shows the average intensities of plugs that showed an increase in fluorescence intensity greater than 3 times the baseline (black bars) and plugs that showed an increase in fluorescence intensity less than 3 times the baseline (hatched bars). No plugs containing VCM or LVF had a fluorescence increase greater than 3 times the baseline. indicating that MRSA was sensitive to these antibiotics. Poisson statistics (Eq. 5) can be used to predict the probability of not loading a bacterium into any of plugs in the conditions LVF or VCM. In other words, Eq. 4 predicts the possibility of the LVF or VCM results being false-negative. 
     
       
         
           
             
               
                 
                   
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     In Eq. 5, ƒ the probability of having κ bacteria in a plug given an average bacterial loading of λ bacteria per plugs. The experimentally determined λ was 0.12, as 12% of control plugs with no antibiotics received bacteria ( FIG.  30    panel b, + blank plugs). For κ=0 and λ=0.12, we calculated the probability of having an unoccupied plug to be 0.887. The probability of having 49 unoccupied plugs is 0.887 49 , or 0.0028. Given that LVF and VCM had at least 49 plugs, the probability of a false-negative due to loading is less than 0.3%. 
     The results from the MRSA antibiotic screen were used to make the antibiogram in  FIG.  29    panel d. The antibiotics were tested at the breakpoint concentration, and the fluorescence data was used to determine if the bacterial strain was sensitive (S) or resistant (R) to the antibiotic. Sensitive means that no plugs containing a specific antibiotic showed an increase in fluorescence intensity greater than 3 times the VCM baseline. Resistant means that at least one plug containing a specific antibiotic showed increased fluorescence intensity greater than 3 times the VCM baseline. The susceptibility profile generated for MRSA by using the microfluidic screen was identical to the profile generated by using Mueller-Hinton agar plate tests and similar to previous reports in the literature for MRSA (B. T. Tsuji, et al,  Diagn. Microbial. Infect. Dis , 2007,58, 41-4). 
     Plug-based methods can also be used to determine the minimal inhibitory concentration (MIC) of an antibiotic against a bacterial sample. 
     Next, this microfluidic approach was used to determine the MIC of the antibiotic cefoxitin (CFX) for MRSA and MSSA ( FIG.  31   ). This assay was similar to the antibiotic screening assay described above, except that the pre-formed array of antibiotic plugs all contained the same antibiotic and the concentration of that antibiotic in each plug of the pre-formed array was different. Again, plugs containing saline solution were included at the ends of the array to serve as negative controls. The positive control plugs consisted of CFX at a concentration of 24 mg/L, as both strains are known to be inhibited by CFX at this concentration. Plugs of the antibiotic array were merged with bacteria and the fluorescent viability indicator as illustrated in  FIG.  31    panel a and incubated at 32° C. Plugs with MRSA were incubated for 6.75 hand plugs with MSSA were incubated for 6.5 h. 
     After incubation, the fluorescence intensity of the plugs was measured. Here, the average increase in fluorescence intensity of plugs containing 24 mg/L CFX was used as the baseline to which the increase in fluorescence intensity of other plugs was compared. Because MRSA is resistant to many beta-lactam antibiotics, CFX should be less effective against the strain MRSA. As expected, the MIC of CFX was higher for MRSA (&lt; 8 mg/mL) than the MIC of CFX for MSSA (&lt; 4.0 mg/mL) ( FIG.  31    panel b). These results validate the use of this plug-based technology for screening both the susceptibility and the minimal inhibitory concentration of many antibiotics against a single bacterial sample. 
     Microfluidic bacterial detection and drug screening are applicable to complex, natural matrices, including human blood plasma. 
     To validate the applicability of this method to detecting bacteria in natural matrices, this method was used to detect bacteria in a sample of human blood plasma. Bacterial strains MSSA or MRSA were inoculated into pooled human blood plasma at a concentration of 3×10 5  CFU mL, To test the sensitivity of the bacteria to beta-lactams. the antibiotic ampicillin (AMP) was added to the culture at the breakpoint concentration. The inoculated plasma was then combined on-chip with viability indicator as illustrated  FIG.  32    panel a. After 7.5 h of incubation at 37° C., plasma samples infected with MRSA were distinguishable from samples infected by MSSA by screening the samples against AMP at the breakpoint concentration. While plugs containing MRSA and AMP showed a similar increase in fluorescence intensity to plugs containing MRSA and no AMP ( FIG.  32    panels b and c), plugs containing MSSA and AMP showed no increase in fluorescence intensity ( FIG.  32    panels d and e). 
     Conclusions 
     Stochastic confinement combined with plug-based microfluidic handling methods accelerates bacterial detection and enables rapid functional antibiotic screening. By using this method, assays can be performed on a single bacterium, potentially eliminating the need for pre-incubation. By confining and analyzing single bacterium in plugs, detection time is now determined by plug volume. We were able to achieve detailed functional characterization of a bacterial sample in less than  7  hours. We also demonstrated that a bacterium in a 1 nL plug can be detected in as little as 2 hours. The detection time is limited by the formation and measurement of plugs of small volume and is less dependent on the initial concentration and growth rate of bacteria in the sample. This feature could be potentially important for accelerated detection of slowly-growing species such as M. tuberculosis, a pathogen of significant importance world-wide (E. Keeler, et al,  Nature , 2006. 444 Suppl 1, 49-57). This method would further benefit from handling of lamer numbers of smaller plugs, and automated sorting and analysis (E. Keeler. et al,  Nature , 2006, 444 Suppl 1, 49-57; Y. C. Tan,  Microfluid. Nanofluid. , 2008, 4, 343-348; D. Huh, Jet al,  Anal. Chem.,  2007, 79, 1369-1376; K. Ahn, Cet al,  Appl. Phys. Lett. , 2006, 88; M. Chabert and J.-L. Viovy,  Proceedings of the National Academy of Sciences , 2008, 105, 3191-3196). 
     Given that a typical 5 mL blood sample from a patient with bacteremia contains a cell density of 100 CFU/mL (L. G. Reimer, et al,  Clin. Microbial. Rev. , 1997, 10, 444-&amp;), this method is capable of performing dozens of functional tests on such a sample. Patient-specific characterization of bacterial species would not only lead to more rapid and effective treatment, but such an advance would also enable in-depth characterization of bacterial infections at the population level. Such detailed characterization may aid in tracking and identifying new resistance patterns in bacterial pathogens (S. K. Fridkin, et al  Clin. Infect. Dis. , 2001, 33, 324-329; R. T. Horvat, N. E. et al  J Clin. Microbial. , 2003, 41, 4611-4616). The principles of these methods, stochastic single-cell confinement and multiple functional assays without sample pre-incubation, could also be applied to other areas, including performing functional tests on field samples, detecting contamination of food or water, separating and testing samples with mixtures of species, measuring functional heterogeneity in bacterial populations, and monitoring industrial bioprocesses. 
     Amplification 
     Amplification is defined as making a large amount of object B&#39;s from a starting small number of objects A&#39;s (or even single A). A and B are defined as, for example but are not limited to. molecules (e.g. chloride or phosphatase), cells (e.g.  Mycabacterium tuberculosis ), chemical events (e.g. the breaking of amide bonds), or biological events (e.g. cell division). A and B could also be identical or different. For example, a single molecule of enzyme can be amplified into 10 5  molecules of the same enzyme, 10 12  of dye molecules, or the hydrolyses of 10 18  ester bonds. 
     Amplification as defined here has a threshold. Only when the number of A is larger than the threshold can amplification be activated. Detection rules can also be extended to more complicated schemes like A or B, A and B, ratio A/B. There are examples of detection problems which would require this type of rule, such as a threshold amount of bacteria in drinking water, exceeding certain ratio of cell types/proteins in the body which may be a biomarker for disease. Any complex system probably always has low amounts of A or B, but detecting imbalances in ratios could be important. 
     Examples of autocatalytic reactions that could be used for amplification include, but are not limited to, a plethora of reactions which use inexpensive and readily available common chemicals. The autocatalytic production of Co(II) from a Co(III)-pyridilazo dye complex was used to detect trace amount of Co(II) (Endo, M., et al  Talanta  47, 349-353 (1998)) and to demonstrate chemical amplification using this autocatalytic reaction coupled in time (Gerdts, C.J., et al  Journal of the American Chemical Society  126, 6327-6331 (2004)). The oxidation of thiosulfate by chlorite was extensively studied (Nagypal, I. &amp; Epstein, I.R.  Journal of Physical Chemistry  90, 6285-6292 (1986); Epstein, I.R. &amp; Showalter, K.  Journal of Physical Chemistry  100, 13132-13147 (1996)) and was used to demonstrate a threshold generated by autocatalytic production and linear removal of the product (Kastrup. C.J. et al.  Biophysical Journal  93, 2969-2977 (2007); Runyon, M.K. , et al  Angewandte Chemie International Edition  43, 1531-1536 (2004)). Other autocatalytic reactions include those of iodide and chlorite (Epstein. I.R. &amp; Showalter, K.  Journal of Physical Chemistry  100, 13132-13147 (1996); Dateo, C.E. et al.  Journal of the American Chemical Society  104, 504-509 (1982)), bromide and chlorite (Simoyi, R.H.  Journal of Physical Chemistry  89, 3570-3574 (1985)), formic acid and permanganate  9  Perezbenito, J.F., et al.  International Journal of Chemical Kinetics  22, 261-287 (1990)), formaldehyde and chlorite, Mn(II) and oxygen (Coichev, N. &amp; Vaneldik, R  Inorganica Chimica Acta  185, 69-73 (1991)), Mn(II) and hypochlorous acid (Angusdunne, S.J., et al  Journal of the Chemical Society - Dalton Transactions , 2717-2726 (1993)), etc. In the reactions mentioned above, the time of response (from the initial conditions to when autocatalysis shows dramatic effects) is small and ranges from less than 1 second to 20 minutes, depending on the reaction and initial conditions. 
     Besides inorganic molecules shown above, autocatalytic reactions can involve a wide range of organic, and biological molecules, or even organisms. For example, chirality of products of organic reactions could be determined by asymmetric autocatalysis (Soni, K Shibata, T. &amp; Sato, I,  Accounts of Chemical Research  33, 382-390 (2000).; Soai, K.. Sato, I. &amp; Shibata, T.  Methodologies in Asymmetric Catalysis  880, 85-102 (2004)) . Autocatalysis also plays a crucial role in the existence of threshold in the blood clotting network, in which thrombin and Factor X are involved in important positive feedback loops (Kastrup, C.J et al.  Biophysical Journal  93 2969-2977 (2007); Runyon, M.K., et al  Angewandte Chemie - International Edition  43, 1531-1536 (2004)). In the apoptotic reaction network. caspase-9 dimer and caspase-3 are also autocatalysts because they fasten the production of caspase-9 from pro-caspase-9. Autocatalytic processes are also relevant at the cellular scale, such as in blooming of plankton (Tel. T., et al,  Physics Reports - Review Section of Physics Letters  413, 91-196 (2005)). In daily life and in industry, autocatalysis can also be found in reduction of metals such as in photography (Ag(I) to Ag) and in electroless plating of metal, 
     Oligonucleotide coated gold nanoparticles (Au—NP) (Xu, X.Y., et al.  Angewandte Chemie - international  Edition 46, 3468-3470 (2007); Han, M.S., et al.  Angewandte Chemie - International  Edition 45, 1807-1810 (2006); Hill, H.D. &amp; Mirkin, C.A.  Nature Protocols  1, 324-336 (2006); Lee, J.S., et al  Angewandte Chemie - International  Edition 46, 4093-4096 (2007); Seferos, D.S., et al  Journal of the American Chemical Society  129, 15477-+(2007)) have been used for sensitive detection. Molecules can directly bind to the Au—NP and upon treatment the oliganucleotides are released. The sequence of the released oligonucleotides can then be used to identify the binding molecule. Amplification is achieved because each NP might only bind 1 molecule but can release many oligonucleotides. A similar method detects specific mRNAs by releasing fluorescent molecules upon the mRNA binding to the NP. The non-linearity in the response here is that fluorescent molecules clustered around Au-NP are quenched, but released molecules have an increased fluorescent signal. 
     A single autocatalytic reaction or coupled reactions can be used. This decision will be determined by specific experiments with certain requirements of degrees of amplification, times of response, and resistance to noise. Extra materials and techniques could be used to allow for a better and more versatile control of autocatalytic reactions when using them in amplification. A physical barrier could be used to separate the reagents and/or the catalyst. Upon addition or increase of molecule A which degrades the barrier, the barrier breaks down and the reagents on either side are allowed to mix. For example, in the reaction between thiosulfate and chlorate, both hydronium and chloride are autocatalysts. Therefore, a material of control would capture these ions normally and release them when the input is present. More specifically, the coating (e.g. hydrogel) of sodium chloride crystals breaks down only by reacting with a specific enzyme and exposes the crystal when that enzyme is introduced or activated. Alternatively, a vesicle containing a solution of one or both autocatalysts could be used. An example of this is a liposome containing hydrochloric acid that can be burst open when some specific molecules are present in the solution. 
     Amplification with threshold can also be achieved without using a direct autocatalytic reaction. A material of control (e.g. coated crystal or gel like above) may contain an excess amount of X, which is a reagent or a catalyst. As discussed above, a small disruption of the coating will release X and lead to the production of a huge number of products (molecules or events) in a short amount of time. The main reaction may not be autocatalytic, but it needs to be fast and produce a large amount of products (or events). 
     Another method would be to change transport dynamics. Molecule X is diffusing from source 1 and molecule Y is diffusing from source 2. If the two molecules degrade quickly, in the limit of slow transport the two gradients do not overlap. If transport rate is increased (gel goes to liquid, diffusion vs. convection, ionic driven flow) then the gradients overlap and the molecules could react. 
     Another way to have a threshold is to use a reaction with a non-linear response (that is not necessarily autocatalytic). Many reactions respond non-linearly such as pH buffering systems. Above or below a certain pH, a reaction might be drastically slowed down. If an inhibitor is turned off in this way you could change the threshold concentration in the system and initiate amplification. 
     Threshold of amplification, which is the minimal number of input objects to activate amplification, can be created by coupling inhibition reaction (and/or transport mechanism such as diffusion) with autocatalysis (Andres Ordax, et al. Anales de Quimica 1992, 88, 440-443) or by using a material of control (e.g. through how thick the coating layers are, the amount of reagent/catalyst/autocatalyst each crystal/vesicle contains, the number of crystals/vesicles that need to be activated to start the reaction). 
     The ability to tune thresholds will enable the development of detection system that can be adapted to a variety of applications. The threshold detection level may want to be increased for a detection system that only detects high concentrations of signal. A low threshold cannot distinguish between high and mid-level signals. Other properties of arnplification, including the degree of amplification, resistance to noise, and time of response can also be adjusted to fit particular applications by the design of the material of control and the choice of amplification reaction or coupled reactions. 
     According to the above examples a first set of embodiments is directed to a method of detecting an analyte. combination of analytes, ratio of analytes, or at least one member of a class of analytes in a sample, the method comprising:
         providing a first set of molecules that constitutes an autocatalytic loop that is capable of amplification of at least one component of the autocatalytic loop, wherein the analyte, combination of analytes, ratio of analytes, or at least one member of the class of analytes initiates or accelerates the autocatalytic loop; and   contacting the sample with the first set of molecules, wherein a product of the autocatalytic loop is detectable.       

     In some embodiments of the first set of embodiments, the method is capable of detecting a single particle or molecule of analyte. 
     In some embodiments of the first set of embodiments, the method is capable of detecting about ten particles or molecules of analyte. 
     In some embodiments of the first set of embodiments, the analyte is selected from the group consisting of bacteria, pollen, a spore. a toxin, and a virus. 
     In some embodiments of the first set of embodiments, the analyte is an enzyme, peptide , polynucleic acid. polysaccharide or small molecule. 
     In some embodiments of the first set of embodiments, the sample is an environmental sample, human fluid, animal fluid, food or drink. 
     In some embodiments of the first set of embodiments, the first set of molecules constituting the autocatalytic loop comprises small molecules, inorganic molecules, enzymes, or nucleic acids. 
     In some embodiments of the first set of embodiments. the detectable product of the autocatalytic loop generates a signal by cleaving a fluorescent substrate. or precipitating out of solution. 
     In some embodiments of the first set of embodiments, the analyte reacts with a molecule in the autocatalytic loop such that the reactivity of the molecule in the autocatalytic loop is increased. 
     In some embodiments of the first set of embodiments, the analyte cleaves ligands off a metal atom that is part of the autocatalytic loop. 
     In some embodiments of the first set of embodiments, the analyte modulates the reactivity of a molecule in the autocatalytic loop by changing the conformation of the molecule. 
     In some embodiments of the first set of embodiments, the molecule is a protein, polysaccharide or polynucleic acid. 
     In some embodiments of the first set of embodiments, the sample is divided up into a number of portions such that on average each portion contains less than one analyte molecule or particle. 
     In some embodiments of the first set of embodiments, the method further comprises a set of molecules capable of modulating the reactivity of the autocatalytic loop upon reacting with the analyte. 
     In some embodiments of the first set of embodiments, the set of molecules capable of modulating the reactivity of the autocatalytic loop upon reacting with the analyte are shuttling molecules that bring molecules that are part of the autocatalytic loop from a solid phase into another phase where the autocatalytic loop can take place. In some of those embodiments, the set of molecules capable of modulating the reactivity of the autocatalytic loop upon reacting with the analyte include lipopolysacharide covalently attached to an enzyme cleavable group, and the autocatalytic loop includes enzymes from crab lysate. 
     In some embodiments of the first set of embodiments, the product of the autocatalytic loop is detectable visually, spectroscopically, or electrochemically, 
     In a second set of embodiments a method is described of detecting an analyte, combination of analytes, ratio of analytes, or at least one member of a class of analytes in a sample comprising:
         providing a first set of molecules that constitutes a first autocatalytic loop that is capable of amplification of at least one component of the autocatalytic loop, wherein the analyte. combination of analytes, ratio of analytes. or at least one member of the class of analytes initiates or accelerates the autocatalytic loop;   contacting the sample with the set of molecules.       

     contacting a product of the first autocatalytic loop with a second set of molecules that constitutes a second autocatalytic loop, wherein the product of the first autocatalytic loop initiates or accelerates the second autocatalytic loop wherein a product of the second autocatalytic loop is detectable. 
     In some embodiments of the second set of embodiments, the first and second autocatalytic loops are separated in space. 
     In some embodiments of the second set of embodiments, the second autocatalytic loops is initiated downstream of the first autocatalytic loop on a microfluidic chip. 
     In some embodiments of the second set of embodiments, the product of the second autocatalytic loop is detectable visually. spectroscopically, or electrochemically. 
     In a third set of embodiments, a method is described of detecting an analyte, combination of analytes. ratio of analytes. or at least one member of a class of analytes in a sample, the method comprising: 
     providing a first set of molecules that constitutes a first reaction, wherein the analyte, combination of analytes, ratio of analytes. or at least one member of the class of analytes modulates the first reaction:
         contacting the sample with the first set of molecules,   contacting a product of the first reaction with a second set of molecules that constitutes a second reaction, wherein the product of the first reaction modulates the second reaction:   wherein a product of the second reaction is detectable.       

     In some embodiments of the third set of embodiments, the analytes are confined in a gel. 
     In some embodiments of the third set of embodiments, the product of the second reaction is detectable visually, spectroscopically, or electrochemically. 
     In some embodiments of the third set of embodiments. the analytes are transferred to a gel, microfluidic device or microporous membrane. 
     In a fourth set of embodiments an apparatus is described that can perform any of the methods ff the first set of embodiments, the second set of embodiments and the third set of embodiments, 
     In some embodiments of the fourth set of embodiments, at least one component of the autocatalytic loop or the analyte is localized on a strip 
     In some embodiments of the fourth set of embodiments, any of the reactive components are physically separated, such as by a membrane. 
     In some embodiments of the fourth set of embodiments, any of the reactive components are physically separated by a vesicle membrane. 
     In some embodiments of the fourth set of embodiments, any of the reactive components are physically separated by a coating. 
     In some embodiments of the fourth set of embodiments, any of the reactive components are physically separated in space. 
     In some embodiments of the fourth set of embodiments, the reagents are contained on different levels of a solid test strip 
     In a fifth set of embodiments a method is described of detecting an analyte in a sample comprising:
         dividing up the sample into a number of portions such that on average each portion contains less than one analyte molecule or particle.       

     In some embodiments of the fifth set of embodiments, the method further comprises performing an autocatalytic assay on each portion. 
     In some embodiments of the fifth set of embodiments, the autocatalytic assay comprises two stages. 
     In some embodiments of the fifth set of embodiments, the portions are plugs in a microfluidic channel. 
     In some embodiments of the fifth set of embodiments, the portions are droplets in a microfluidic channels. 
     In some embodiments of the fifth set of embodiments, the portions are individual pores in a membrane. 
     In some embodiments of the fifth set of embodiments, the portions are separated spots in a gel with restricted analyte transport. 
     In some embodiments of the fifth set of embodiments, the analyte is secreted by a cell. 
     In some embodiments of the fifth set of embodiments, the analyte is a virus or eukaryotic or prokaryotic cell. 
     In a sixth set of embodiments a method is described of detecting an analyte, combination of analytes. ratio of analytes, or at least one member of a class of analytes in a sample comprising:
         providing a first set of molecules that constitutes a first reaction, wherein the analyte, combination of analytes, ratio of analytes, or at least one member of the class of analytes modulates the first reaction . ,   contacting the sample with the first set of molecules,   contacting a product of the first reaction with a second set of molecules that constitutes a second reaction, wherein the product of the first reaction modulates the second reaction;       

     wherein a product of the second reaction is detectable, 
     In some embodiments of the fifth set of embodiments, the product of the second reaction is detectable visually, spectroscopically, or electrochemically. 
     In a seventh set of embodiments, a kit is described for carrying out any of the methods above comprising a plurality of sections, each of which is capable of carrying out the method independently, wherein the sections each are capable of detecting a different threshold concentration or amount of analyte, 
     It is to be understood that this invention is not limited to the particular devices, methodology, protocols, subjects, or reagents described, and as such may vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to limit the scope of the present invention, which is limited only by the claims. Other suitable modifications and adaptations of a variety of conditions and parameters normally encountered and obvious to those skilled in the art, are within the scope of this invention. All publications, patents, and patent applications cited herein are incorporated by reference in their entirety for all purposes. Also incorporated by reference in their entirety for all purposes are the supplementary materials (including information, text, graphs, images, tables, and movies) available online, and associated with some of the above-referenced publications.