# Patent

## Title
Nucleic acid arrays to monitor water and other ecosystems

## Abstract

Disclosed are arrays for monitoring ecosystems, such as bodies of water, and methods and systems for making such arrays. In one embodiment, the array may include a plurality of oligonucleotides immobilized at known locations on a substrate, such that each location on the array is an oligonucleotide having a sequence derived from a single, predetermined operational taxonomic unit (OTU). The sequences immobilized on the array may be from known, or unknown organisms. Also disclosed are methods for identifying and isolating bioindicators diagnostic of specific ecosystems. The arrays and bioindicators of the invention may be used for rapid, and continual monitoring of ecosystems.

## Background
RELATED APPLICATIONS
This application is a continuation-in-part of U.S. patent application Ser. No. 10/131,618, filed Apr. 24, 2002 now abandoned and a divisional application of U.S. patent application Ser. No. 11/071,849 filed Mar. 3, 2005 now U.S. Pat. No. 7,214,492. The disclosure of U.S. patent application Ser. No. 10/131,618, and U.S. patent application Ser. No. 11/071,849 is hereby incorporated by reference in its entirety.


FEDERAL FUNDING
Parts of this work were supported by federal funding in the form of a Cooperative Agreement #82946501 with the Environmental Protection Agency to C. Neal Stewart, Vincent C. Henrich and Parke A. Rublee and an Environmental Protection Agency STAR Grant #R831627 to Parke A. Rublee.


FIELD OF THE INVENTION
The present invention relates to nucleic acid arrays to monitor water and other ecosystems.
BACKGROUND
As the threat of bioterrorist activities has become evident in recent years, concern about the vulnerability of ecosystems such as municipal water supplies to deliberate contamination has grown. Additionally, human development can result in chemicals, waste, and/or agricultural runoff being introduced into the ecosystem. Increases in population may lead to over-harvesting of marine resources, landscape alterations that alter the ecosystem, and the introduction of living and non-living contaminants into the ecosystem (Mallin, J. M., et al. 2000, Marine Pollution Bulletin, 41:56-75). For example, spills from concentrated animal feeding operations can degrade water quality and stimulate algal blooms (Mallin, M. A., 2000, American Scientist, 88:26-37). Also, over-development of coastal areas may introduce coliform bacteria, and the introduction of nutrients and or chemical compounds may lead to eutrophication or other changes in microbial communities (Mallin, M. A., et al. 2000, Ecological Applications, 10:1047-1056; Paerl, H. W., et al. 2003, FEMS Microbiology Ecology, 46:233-246; DeLorenzo, M. E., et al., 1999, Environmental Toxicology and Chemistry, 18:2824-2835).
Reservoirs, recreational lakes, and coastal areas can be difficult to secure against accidental or intentional contamination. Further, the contamination of a water source has the propensity to impact a relatively large population, and water filtration systems may not sufficiently alleviate the threat. Perhaps most troubling is the lack of a real-time test to detect the agents that are most likely to contaminate water supplies. The turnaround times for culturing microbes is slow enough that consumption of contaminated water may occur before the test results are known. Also, the expense involved in frequent monitoring of the water supply with currently available laboratory tests can be prohibitive.
As yet, there has not been a large-scale, deliberate contamination of a municipal water source. However, sporadic and relatively confined natural contaminations have demonstrated the importance in being able to monitor the water supply. The number of outbreaks attributable to contaminated drinking water supplies more than doubled in 1999-2000 over the previous two-year period, with contamination of well water also on the rise. In addition, recreational water sources have also reported significant increases in contamination (Bowman, 2002, Outbreaks of waterborne illnesses on the rise in US, Scripps-Howard News Service, Nov. 23, 2002). These incidents of water contamination were exacerbated by the difficulty in pinpointing the cause of the outbreak and subsequent misdiagnosis of the symptoms, illustrating the importance of “early warning” diagnostics of water supplies.
A number of microbial genome sequencing projects have been initiated to characterize pathogenic organisms. Although identification and characterization of genomic sequence data for individual pathogens may provide for the identification of specific microbes, such targeted testing fails to provide a comprehensive, economically feasible system for monitoring ecosystems of interest, such as municipal water supplies. The accuracy of a molecular diagnostic test for a microbe may be compromised where the pathogenic agent is endemic, or possesses substantial genetic similarity to non-pathogenic organisms (Leff et al., 1995, Appl. Environ. Microbiol., 61:1634-1636; Xiao et al, 1999, Appl Environ. Microbiol., 65:3386-3391). Also, although some putative contaminants of water have been identified, anticipating all possible contaminants is not feasible, and thus, specific tests are inherently limited.
Thus, there is a need for devices and methods that enable real-time monitoring of water supplies and other ecosystems of interest. The monitoring system should allow for detection of known, as well as unknown, contaminants. The monitoring system should be available in a format that is accessible for routine monitoring, as well as for rapid testing in response to a specific event.
SUMMARY
The present invention provides devices and systems for monitoring water and other ecosystems. The present invention may be embodied in a variety of ways.
One embodiment of the present invention comprises an array for monitoring an ecosystem comprising a plurality of oligonucleotides immobilized at known locations on a substrate, such that each location on the array comprises an oligonucleotide having a sequence derived from a single, predetermined microbial operational taxonomic unit (OTU).
In another embodiment, the present invention may comprise a device for monitoring water quality comprising an array, wherein the array comprises a plurality of oligonucleotides immobilized at known locations on a substrate, and wherein each location on the array comprises an oligonucleotide having a sequence that is derived from a single, predetermined microbial operational taxonomic unit (OTU).
Another embodiment of the present invention comprises a system for monitoring an ecosystem of interest. The system may comprise an array comprising a plurality of oligonucleotides immobilized at known locations on a substrate. In one embodiment, the array may be designed such that each location on the array comprises an oligonucleotide having a sequence derived from a single, predetermined microbial operational taxonomic unit (OTU). The system may further include a device able to measure hybridization of a DNA sample to the array. Also, the system may include a DNA sample for hybridizing to the array. In one embodiment, the ecosystem may comprise a body of water.
Yet other embodiments of the present invention comprise methods for monitoring ecosystems. The method may comprise the step of generating an array comprising a plurality of oligonucleotides immobilized at known locations on a substrate, such that each location on the array comprises an oligonucleotide having a sequence derived from a single predetermined microbial operational taxonomic unit (OTU). The method may also comprise the step of preparing a nucleic acid sample derived from a water sample of interest and hybridizing the nucleic acid sample to the array. Also, the method may comprise the step of measuring hybridization of the nucleic acid sample to the array, and correlating the hybridization of the nucleic acid to the array with a parameter that comprises at least part of the ecosystem. In one embodiment, the ecosystem of interest comprises a body of water.
In yet another embodiment, the present invention comprises a method of analyzing a pattern to evaluate the status of a biosystem. The method may comprise the step of measuring hybridization of a DNA sample to an array of oligonucleotides immobilized at known locations on a substrate, wherein each location on the array comprises an oligonucleotide having a sequence that is derived from a single, predetermined microbial operational taxonomic unit (OTU), and correlating the hybridization of the DNA to the array with a parameter that comprises at least part of the ecosystem. A single change in the pattern of hybridization to the array for a first DNA sample isolated from an ecosystem of interest as compared to a second DNA sample isolated from an ecosystem of interest may be associated with a change in one parameter, or a plurality of parameters. Additionally or alternatively, a plurality of changes in the pattern of hybridization to the array for a first DNA sample isolated from an ecosystem of interest as compared to a second DNA sample isolated from an ecosystem of interest is associated with a change in one or more parameters. Samples may vary by location of the ecosystem, the time of sampling of a single ecosystem, or the location of sampling within a single ecosystem.
Embodiments of the present invention also comprise methods for identifying and/or generating bioindicators for ecosystems of interest. In one embodiment, a method of generating a bioindicator may comprise preparing a nucleic acid sample comprising a plurality of DNA molecules from an ecosystem of interest. The method may also comprise determining the sequence of at least some of the plurality of DNA molecules in the isolated DNA sample. The method may further comprise grouping the DNA sequences into operational taxonomic units (OTUs). Also, the method may comprise identifying at least one nucleic acid sequence that is specific to a single OTU. In one embodiment, the ecosystem of interest comprises a body of water.
Embodiments of the present invention also comprise bioindicators isolated using the methods and systems of the present invention. In one embodiment, the present invention comprises a bioindicator, or a collection of bioindicators, for the analysis of an ecosystem of interest, wherein a bioindicator comprises an isolated nucleic acid having a sequence derived from a single predetermined microbial operational taxonomic unit.
In yet another embodiment, the present invention also comprises a method to prepare a nucleic acid sample from a biosystem of interest, the nucleic acid sample comprising a plurality of bioindicator DNA sequences, comprising the step of amplifying a DNA sample isolated from a biosystem with a plurality of primers that have the ability to specifically amplify nucleic acid sequences comprising bioindicators. Also, in an embodiment, the present invention comprises an oligonucleotide primer having a sequence identical to any one of SEQ ID NO: 114-SEQ ID NO: 316 or a fragment thereof.
In yet another embodiment, the present invention may comprise a method to identify a microbe comprising the ability to modify, or adjust to, an ecosystem. The method may comprise the step of identifying a bioindicator that is associated with a particular microbe. Also, the method may comprise the steps of identifying the bioindicator in at least one ecosystem, and correlating the presence of the microbe with a parameter specific to the ecosystem. Also, the method may comprise identifying the nature of the ability of the microbe to modify, or adjust to, the ecosystem.
There may be certain advantages that may be realized with various embodiments of the present invention. By using a microarray comprising nucleic acid sequences that are specific to microbial operational taxonomic units, the array may cover a wide variety of microbial taxa. Thus, the array may provide a single test that provides substantially comprehensive information on community structure.
The array may, in certain embodiments, provide quantitative data. For example, by using quantifiable labels to label individual samples, or to differentially label specific sequences in a single sample, the array may provide information on the abundance of specific organisms of interest, such as key bioindicators, pathogens, or microbial contaminants in a water system.
Also, the array, if applied to a number of samples over time, may be able to indicate the “trajectory” of the system as either improving or degrading, where probes associated with the quality of the ecosystem of interest are known.
Microorganisms generally respond rapidly to environmental changes. The microarrays of the present invention may therefore provide results in near “real-time” (i.e., within hours) of an event, such as a contamination, occurring. Thus, the array may detect changes in ecosystem perturbations early, so that potential problems may be quickly rectified.
There may be a large number of microorganisms specific to any one ecosystem of interest, such as a specific body of water. Also, the prevalence of particular microorganisms may vary depending upon the water source. Still, by prudent selection of the nucleic acid sequences used as part of an array, the array may be diagnostic of a plurality of microorganisms that are specific to many types of ecosystems. Thus, once developed, the array can be a highly cost-effective way to monitor a variety of ecosystems. Also, the microarray platform may be easily modified and expanded to include new targets of interest as they are identified.
A microbial community may be affected by biological changes, physical changes, or chemical changes to the environment. Because the microarrays of the present invention provide a measure of the microbial community, the array may be sensitive to a wide variety of changes that may occur in the ecosystem of interest.
The present invention may be better understood by reference to the description and figures that follow. It is to be understood that the invention is not limited in its application to the specific details as set forth in the following description and figures. The invention is capable of other embodiments and of being practiced or carried out in various ways.



BRIEF DESCRIPTION OF THE FIGURES
The file of this patent contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee. The present invention may be better understood by reference to the following figures.
FIG. 1 shows a method for identification of a bioindicator in accordance with an example embodiment of the present invention.
FIG. 2 shows rank-abundance curves for 16S rDNA libraries from three different lakes (Lake Townsend, NC; City Lake, NC; and Lake Toolik, AK) in accordance with an embodiment of the present invention. The curves on left-hand side represent Lake Townsend samples taken from different stations (Station 1 or Station 2) or at different times of the year (March or June). The median for each distribution partitions the operational taxonomic units (OTUs) into two groups shown in black and white; a stippled pattern is used where the median falls within an OTU.
FIG. 3 shows rank-abundance curves for 18S rDNA libraries from three different lakes (Lake Townsend, NC; City Lake, NC; and Lake Toolik, AK) in accordance with an embodiment of the present invention. The curves on left-hand side represent Lake Townsend samples taken from different stations (Station 1 or Station 2) or at different times of the year (March or June). The median for each distribution partitions the operational taxonomic units (OTUs) into two groups shown in black and white; a stippled pattern is used for a median that falls within an OTU.
FIG. 4 shows a phylogenetic tree of 16S rDNA operational taxonomic units (OTUs) derived by an Unweighted Pair-Group Method with Arithmetic Mean (UPGMA) analysis using DNA isolated from three different lakes in accordance with an embodiment of the present invention. Numbers in parentheses designate the size of OTUs (i.e., the number of unique sequences per OTU). Identifications by BLAST analysis using the GenBank database are shown. Water samples from which the rDNA was isolated were as follows: LT-1J: Lake Townsend, station 1, June; LT-2J: Lake Townsend, station 2, June; LT-1M: Lake Townsend, station 1, March; CL: City Lake; TL: Toolik Lake.
FIG. 5 shows a phylogenetic tree of 18S rDNA operational taxonomic units (OTUs) derived by an Unweighted Pair-Group Method with Arithmetic Mean (UPGMA) analysis using DNA isolated from three different lakes in accordance with an embodiment of the present invention. Numbers in parentheses designate the size of OTUs (i.e., the number of unique sequences per OTU). Identifications by BLAST analysis using the GenBank database are shown. Water samples from which the rDNA was isolated were as follows: LT-1J: Lake Townsend, station 1, June; LT-2J: Lake Townsend, station 2, June; LT-1M: Lake Townsend, station 1, March; CL: City Lake; TL: Toolik Lake.
FIG. 6 shows Venn diagrams that illustrate the relative patterns of shared operational taxonomic units (OTUs) for five separate fresh water samples in accordance with an embodiment of the present invention. The size of each sample component is based on the total number of OTUs for that water sample relative to the other samples. Water samples from which the rDNA was isolated were as follows: LT-1J: Lake Townsend, station 1, June; LT-2J: Lake Townsend, station 2, June; LT-1M: Lake Townsend, station 1, March; CL: City Lake; TL: Toolik Lake.
FIG. 7 shows quantitative PCR (Q-PCR) product accumulation curves generated using operational taxonomic unit (OTU)-specific primers and genomic DNA isolated from lake samples in accordance with an embodiment of the present invention where Panel (A) shows the relative abundance of the OTU for an unidentified cyanobacterium LD27 initially detected in Lake Townsend Station 1, March (LT-1M), panel (B) shows the relative abundance of OTU for Zoogloea ramigera initally detected in City Lake (CL), and panel (C) shows the relative abundance of OTU for Asterionella formosa initially detected in Lake Townsend Station 1, March (LT-1M). Pos: a positive control including a mixture of the three test DNAs; Neg: a negative control having no DNA; LT-1J: Lake Townsend, station 1, June; LT-1M: Lake Townsend, station 1, March; CL: City Lake.
FIG. 8 shows a method for monitoring water in accordance with an example embodiment of the present invention.
FIG. 9 illustrates the use of pattern analysis for assessing changes in an ecosystem in accordance with an embodiment of the present invention.
FIG. 10 illustrates the sequences from prokaryotic rDNA (Panels A-1 and A-2), eukaryotic rDNA (Panels B-1 and B-2), prokaryotic variable regions (Panels C-1 and C-2), and prokaryotic variable regions (Panels D-1 and D-2), in accordance with an embodiment of the present invention.
FIG. 11 shows a schematic diagram of amplification and labeling of two DNA samples for array analysis with universal primers for 16S rDNA or 18S rDNA (Panel A); and results of one hybridization experiment (Panel B), where the eukaryotic and prokaryotic PCR products are detected on the microarray, in accordance with an embodiment of the present invention.
FIG. 12 shows a schematic diagram of hybridization of an array to two samples, in accordance with an embodiment of the present invention, where multiplex PCR reactions of each sample use the same primers, but the product of the amplification reaction from the first sample is labeled with CY3 (green) and the product of the amplification reaction from the second sample is labeled with CY5 (red). Panel A shows a schematic representation of the red (darkest arrowhead) and green (lighter arrowhead) amplified DNA hybridizing to immobilized DNA at an individual position on the array; Panel B shows a schematic representation of the color as viewed at each array position, wherein the overall color may comprise an average of the colors of the hybridizing probes; and Panel C shows an actual results of a hybridization experiment using red and green labeled probes, where the top panel shows PCR reactions using 16S primers, and the bottom panel shows the same samples amplified with 18S primers, and where prokaryotic oligonucleotides are spotted on the left side of each panel and eukaryotic oligonucleotides are spotted on the right side of each panel; green spots in lower right-hand position of each grid are for orientation.
FIG. 13 shows an array that contains cyanobacteria sequences probed with amplification products generated using cyanobacteria multiplex primers from two water samples (one sample labeled in green and one sample labeled in red) that each contained cyanobacteria in accordance with an embodiment of the present invention, where oligonucleotide probes to 18S rDNA are spotted in Grid A and B, probes to 16S rDNA of Escherichia coli are spotted in Grid C, and twenty-one 16S rDNA probes containing cyanobacteria sequences, sequences associated with arsenic-responsive microbes, and other sequences identified in collected lake samples, are spotted in Grid D.
FIG. 14 shows hybridization of two samples to an array, where multiplex PCR reactions for both samples were identical and reaction products were either labeled with a red dye (CY5) or a green dye (CY3), allowing comparison of samples in accordance with an embodiment of the present invention. Shown are results from a test of two lake samples used to hybridize first singly (top panels) (left panel: CY3-labeled sample; right panel: CY5-labeled sample) and then together (bottom panel) to the same array of 105 oligonucleotide probes. The array is partitioned into duplicates of eight grids.



DETAILED DESCRIPTION
Ecogenomics is the recovery, characterization, and analysis of genomes recovered from organisms living in the natural environment. The present invention utilizes ecogenomics to develop nucleic acid based arrays for monitoring water supplies and other ecosystems.
Thus, the present invention provides methods, systems, and devices to monitor ecosystems. The methods, systems, and devices of the present invention may be used to monitor water. Embodiments of the present invention comprise bioindicators, and methods for isolating a bioindicator for the analysis of an ecosystem of interest. In one embodiment, the present invention comprises a method for developing bioindicators for monitoring water. The bioindicator may comprise a biological system, such as a microorganism, or a molecule, such as a nucleic acid sequence, that changes in response to a parameter that is related to the ecosystem of interest. The bioindicators may comprise known microorganisms or unknown microorganisims. Rather than measuring the microorganism itself, the present invention provides molecular bioindicators to monitor ecosystems of interest.
A bioindicator for the analysis of an ecosystem of interest may comprise an isolated nucleic acid having a sequence derived from a single predetermined microbial operational taxonomic unit (OTU). In one embodiment, the present invention may comprise a method for preparing a bioindicator for the analysis of a biosystem of interest comprising the steps of: preparing a nucleic acid sample comprising a plurality of DNA molecules from an ecosystem of interest; determining the sequence of at least some of the plurality of DNA molecules in the isolated DNA sample; grouping the DNA sequences into operational taxonomic units (OTUs); and identifying at least one nucleic acid sequence that is specific to a single OTU.
DNA from a variety of ecosystems may be used to develop bioindicators. In one embodiment, the ecosystem may comprise a body of water. For example, water from freshwater lakes may be used. Additionally or alternatively, water from estuaries may be used. Additionally or alternatively, water from other types of biosystems, such as tidal pools, wetlands, streams, rivers, and salt water may be used.
The method may utilize bioindicators that are shared among biosystems, and/or bioindicators that are specific to one, or a few, biosystems. Thus, a plurality of bioindicators may be developed. The bioindicators may be used as a means to analyze biosystems of interest. In one embodiment, the method may comprise the step of identifying the distribution of at least one of the OTUs in at least two ecosystems of interest.
Once the DNA molecules have been categorized and grouped by OTU, the sequences of the DNA molecules in each of the OTUs may be used to develop the collection of bioindicators as an assay system. Thus, the method may comprise preparing a collection of bioindicators wherein at least one of the OTUs comprises sequences that are unshared between at least two of the ecosystems of interest. Additionally and alternatively, the method may comprise preparing a collection of bioindicators wherein at least one of the OTUs comprises sequences that are shared between at least two of the ecosystems of interest.
The method may also include a step of immobilizing a plurality of oligonucleotide bioindicators at known locations on a substrate to form an array, wherein each oligonucleotide has a sequence that is derived from a single, predetermined microbial operational taxonomic unit (OTU). In one embodiment, at least one of the OTUs comprises sequences that are shared between at least two of the ecosystems of interest. Alternatively or additionally, at least one of the OTUs may comprise sequences that are unshared between at least two of the ecosystems of interest.
The oligonucleotides immobilized on the array should be of sufficient length to provide specific hybridization to nucleic acid molecules isolated from various water samples that are used to probe the array. The immobilized oligonucleotides may be at least 20 nucleotides in length. In alternate embodiments, the immobilized oligonucleotides may range from about 30 to 200, or from 40 to 100 nucleotides in length. In one example embodiment, the immobilized oligonucleotides are each about 50 nucleotides in length. Specific hybridization does not require a perfect match between the oligonucleotide immobilized on the array and the ecosystem sample used to probe the array. As used herein, specific hybridization comprises hybridization such that a nucleic acid molecule isolated from the ecosystem of interest hybridizes to a single location (i.e., a single oligonucleotide sequence) on the array. As is known in the art, specific hybridization does not require that the immobilized oligonucleotide and the DNA sequence from the sample comprise perfect complementarity, but may allow for a mismatch at one or several base pairs. The level of mismatch will be determined at least in part by the sequence and length of the oligonucleotide immobilized on the array, as well as the hybridization conditions.
Also, the amount of the oligonucleotide immobilized on the array should be sufficient to allow detection of complementary nucleic acid sequences by the array, but in an amount such that background hybridization to unrelated sequences is avoided. In alternate embodiments, the oligonucleotides immobilized on the array range from about 1 fg to about 10 μg, or from about 50 fg to about 10 ng, or from about 0.5 pg to 1,000 pg, or from about 2 pg to 200 pg, or from about 8 pg to about 50 pg, at each location.
The operational taxonomic units may utilize variable ribosomal DNA (rDNA) sequences as a means to detect specific organisms. Thus, the immobilized oligonucleotides may comprise eukaryotic ribosomal DNA sequences, and/or prokaryotic ribosomal DNA sequences. Additionally, or alternatively, the immobilized oligonucleotides may comprise pathogen-specific sequences. Additionally, or alternatively, the immobilized oligonucleotides may comprise novel sequences from as yet unidentified microbes.
The oligonucleotides immobilized on the array may be derived from sequences found by analysis of microbes present in various sources of water. In one embodiment, oligonucleotides having sequences specific to organisms found in freshwater lakes may be used. Additionally or alternatively, oligonucleotides having sequences specific to organisms found in estuaries may be used. Additionally or alternatively, oligonucleotides having sequences specific to organisms found in other types of water systems, such as tidal pools, wetlands, streams, rivers, and salt water may be used.
In one embodiment, at least one immobilized oligonucleotide comprises a sequence identical to any one of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof. In alternative embodiments, the array may comprise at least 10 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or at least 20 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or at least 50 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or at least 100 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof.
The bioindicators may be used to probe an array comprising nucleic acid sequences that are specific to organisms of interest. In one embodiment, the bioindicator may be evaluated to determine how the presence and/or absence of the bioindicator may correlate with a parameter of the ecosystem. Thus, the method may comprise using the polymerase chain reaction (PCR) to amplify a DNA sequence comprising a predetermined OTU. In one embodiment, at least one of the PCR primers comprises a sequence identical to any one of SEQ ID NO: 114-SEQ ID NO: 316 or a fragment thereof. For example, the bioindicator may be used to probe an array comprising a plurality of oligonucleotides immobilized at known locations on a substrate, and wherein each location on the array comprises an oligonucleotide having a sequence that is derived from a single, predetermined microbial operational taxonomic unit (OTU) so as to correlate the pattern of hybridization with a parameter that comprises at least part of the ecosystem. In an embodiment, the parameter comprises water quality.
Also, the method may use a first bioindicator from a particular microbe as an “entry point” for isolating other bioindicators from the microbe. Thus, in one embodiment, a bioindicator isolated from a portion of the genome of a microbe is used to identify a second bioindicator nucleic acid sequence from the same microbe. For example, the sequence of a first bioindicator nucleic acid molecule may be used to identify and isolate contiguous DNA sequence from the microbe that can serve as a bioindicator.
Embodiments of the present invention also comprise bioindicators isolated using the methods and systems of the present invention. In one embodiment, the present invention comprises a bioindicator, or a collection of bioindicators, for the analysis of an ecosystem of interest, wherein a bioindicator comprises an isolated nucleic acid having a sequence derived from a single predetermined microbial operational taxonomic unit (OTU). The bioindicator may comprise a sequence identical to any one of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof. Or, in alternate embodiments, the collection of bioindicators may comprise at least 2, or 5, or 10, or 20, or 40, or 50 distinct nucleic acid sequences that individually comprise a sequence identical to SEQ ID NO: 5-SEQ. ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof.
The present invention also comprises methods to monitor ecosystems. For example, one embodiment of the present invention may comprise a method for monitoring the water quality in a water sample of interest comprising measuring the hybridization of a nucleic acid sample from a water sample of interest to a plurality of oligonucleotides, and assessing at least one parameter of water quality based upon hybridization of the nucleic acid sample to the plurality of oligonucleotides. In one embodiment, an array of oligonucleotides is used. Thus, the plurality of oligonucleotides may be immobilized at known locations on a substrate, such that each location on the array comprises an oligonucleotide.
In one embodiment, the method may comprise the steps of: generating an array comprising a plurality of oligonucleotides immobilized at known locations on a substrate, wherein each location on the array comprises an oligonucleotide having a sequence derived from a single, predetermined microbial operational taxonomic unit (OTU); preparing a nucleic acid sample from the ecosystem of interest; hybridizing the nucleic acid sample to the array; measuring hybridization of the nucleic acid sample to the array; and correlating hybridization of the nucleic acid sample to the array with a parameter that comprises at least part of the ecosystem.
In one embodiment, the ecosystem may comprise a body of water. For example, water from freshwater lakes may be used. Additionally or alternatively, water from estuaries may be used. Additionally or alternatively, water from other types of biosystems, such as tidal pools, wetlands, streams, rivers, and salt water may be used.
Where the ecosystem of interest comprises water, the parameter comprising at least part of the ecosystem may relate to the quality of the water. Thus, the parameter may relate to a quality that is important to evaluate if the water is suitable for drinking, cooking, bathing, agriculture, or other uses of water.
In one approach, the oligonucleotides are each selected to comprise different taxonomic units. Or, the oligonucleotides may be selected such that at least some are from the same microbial operational taxonomic unit (OTU).
The oligonucleotides immobilized on the array should be of sufficient length to provide specific hybridization to nucleic acid molecules isolated from various ecosystem samples that are used to probe the array. The immobilized oligonucleotides may be at least 20 nucleotides in length. In alternate embodiments, the immobilized oligonucleotides may range from about 30 to 200, or from 40 to 100 nucleotides in length. In one example embodiment, the immobilized oligonucleotides are each about 50 nucleotides in length.
Also, the amount of the oligonucleotide immobilized on the array should be sufficient to allow detection of complementary nucleic acid sequences by the array, but in an amount such that background hybridization to unrelated sequences is avoided. In alternate embodiments, the oligonucleotides immobilized on the array range from about 1 fg to about 10 μg, or from about 50 fg to about 10 ng, or from about 0.5 pg to 1,000 pg, or from about 2 pg to 200 pg, or from about 8 pg to about 50 pg, at each location.
The operational taxonomic units may utilize variable ribosomal DNA (rDNA) sequences as a means to detect specific organisms. Thus, the immobilized oligonucleotides may comprise eukaryotic ribosomal DNA sequences, and/or prokaryotic ribosomal DNA sequences. Additionally, or alternatively, the immobilized oligonucleotides may comprise pathogen-specific sequences. Additionally, or alternatively, the immobilized oligonucleotides may comprise novel sequences from as yet unidentified microbes.
The oligonucleotides immobilized on the array may be derived from sequences found by analysis of microbes present in various ecosystems of interest. In one embodiment, oligonucleotides having sequences specific to organisms found in freshwater lakes may be used. Additionally or alternatively, oligonucleotides having sequences specific to organisms found in estuaries may be used. Additionally or alternatively, oligonucleotides having sequences specific to organisms found in other types of water systems, such as tidal pools, wetlands, streams, rivers and salt water may be used.
In one embodiment, at least one immobilized oligonucleotide comprises a sequence identical to any one of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof. In alternative embodiments, the array may comprise at least 10 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or at least 20 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or at least 50 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or at least 100 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof.
The array may be hybridized with a nucleic acid sample comprising at least one bioindicator that is isolated from the sample of interest. For example, PCR may be used to amplify rDNA sequences from genomic DNA from a water sample of interest, and the array used to probe those sequences. Alternatively or additionally, PCR may be used to amplify known pathogen-specific sequences from a water sample of interest, and the array used to probe those sequences. Alternatively and additionally, PCR may be used to amplify unidentified (i.e., novel) sequences specific to a water sample of interest, and the array used to probe those sequences. Alternatively or additionally, PCR may be used to amplify known non-pathogen specific sequences specific to a water sample of interest, and the array used to probe those sequences.
The bioindicator isolated from the ecosystem of interest may comprise nucleic acid sequences isolated from rDNA. In one embodiment, the nucleic acid sample hybridized to the array sequence comprises a plurality of rDNA sequences. For example, the nucleic acid sequence hybridized to the array may be generated using PCR primers derived at least in part from a ribosomal variable region so as to specifically amplify rDNA sequences. For example, the primers may comprise at least one oligonucleotide molecule having a sequence identical to any one of SEQ ID NO: 114-SEQ ID NO: 316 or a fragment thereof. In separate and alternative embodiments, the primers used for amplification of DNA from a sample of interest may comprise at least 10 oligonucleotide molecules having a sequence identical to any one of SEQ ID NO: 114-SEQ ID NO: 316 or a fragment thereof, or at least 20 oligonucleotide molecules having a sequence identical to any one of SEQ ID NO: 114-SEQ ID NO: 316 or a fragment thereof, or at least 40 oligonucleotide molecules having a sequence identical to any one of SEQ ID NO: 114-SEQ ID NO: 316 or a fragment thereof. In one example embodiment, the primers used for amplification of a sample of interest include about 50 oligonucleotide molecules having a sequence identical to any one of SEQ ID NO: 114-SEQ ID NO: 316 or a fragment thereof.
By measuring hybridization of the array to a sample from an ecosystem of interest, changes in at least one parameter that are indicative of a change in the ecosystem may be measured. Thus, in one embodiment, the present invention comprises a method for analyzing a pattern to evaluate the status of a biosystem comprising the step of measuring hybridization of a nucleic acid sample to an array of oligonucleotides immobilized at known locations on a substrate, wherein each location on the array comprises an oligonucleotide having a sequence that is derived from a single, predetermined microbial operational taxonomic unit (OTU), and correlating the hybridization of the nucleic acid to the array with a parameter that comprises at least part of the ecosystem. In one embodiment, a single change in the pattern of hybridization to the array for a first nucleic acid sample isolated from an ecosystem of interest as compared to a second nucleic acid sample isolated from an ecosystem of interest is associated with a change in one parameter. Or, a single change in the pattern of hybridization to the array for a first nucleic acid sample isolated from an ecosystem of interest as compared to a second nucleic acid sample isolated from an ecosystem of interest may be associated with a change in a plurality of parameters. Additionally or alternatively, a plurality of changes in the pattern of hybridization to the array of a first nucleic acid sample isolated from an ecosystem of interest as compared to a second nucleic acid sample isolated from an ecosystem of interest is associated with a change in one parameter. Or, a plurality of changes in the pattern of hybridization to the array of a first nucleic acid sample isolated from an ecosystem of interest as compared to a second nucleic acid sample isolated from an ecosystem of interest may be associated with a change in a plurality of parameters. In one embodiment, the pattern analysis may comprise a computer program including known patterns such that samples may be analyzed using a computer. Samples may vary by location of the ecosystem, the time of sampling of a single ecosystem, or the location of sampling within a single ecosystem.
Embodiments of the present invention also comprise arrays of oligonucleotides for monitoring an ecosystem of interest. For example, one embodiment of the present invention comprises a device comprising an array comprising a plurality of oligonucleotides immobilized at known locations on a substrate, such that each location on the array comprises an oligonucleotide having a sequence that is derived from a single, predetermined microbial operational taxonomic unit (OTU).
For example, in an embodiment the present invention comprises a device for monitoring water quality comprising an array, wherein the array comprises a plurality of oligonucleotides immobilized at known locations on a substrate, and wherein each location on the array comprises an oligonucleotide having a sequence that is derived from a single, predetermined microbial operational taxonomic unit (OTU).
Also included as part of the present invention are systems for monitoring ecosystems of interest. Thus, another embodiment of the present invention comprises a system for monitoring an ecosystem of interest comprising an array comprising a plurality oligonucleotides immobilized at known locations on a substrate, such that each location on the array comprises an oligonucleotide having a sequence that is derived from a single predetermined microbial operational taxonomic unit (OTU), and a device able to measure hybridization of the nucleic acid sample to the array. The system may further include a DNA sample comprising a plurality of nucleic acid sequences derived from an ecosystem sample of interest.
In one embodiment, the ecosystem analyzed using the devices and or systems of the present invention may comprise a body of water. For example, water from freshwater lakes may be used. Additionally or alternatively, water from estuaries may be used. Additionally or alternatively, water from other types of biosystems, such as tidal pools, wetlands, streams, rivers and salt water may be used.
The oligonucleotides immobilized on the array should be of sufficient length to provide specific hybridization to nucleic acid molecules isolated from various water samples that are used to probe the array. The immobilized oligonucleotides may be at least 20 nucleotides in length. In alternate embodiments, the immobilized oligonucleotides may range from about 30 to 200, or from 40 to 100 nucleotides in length. In one example embodiment, the immobilized oligonucleotides are each about 50 nucleotides in length.
Also, the amount of the oligonucleotide immobilized on the array of the devices and/or systems of the present invention should be sufficient to allow detection of complementary nucleic acid sequences by the array, but in an amount such that background hybridization to unrelated sequences is avoided. In alternate embodiments, the oligonucleotides immobilized on the array range from about 1 fg to about 10 μg, or from about 50 fg to about 10 ng, or from about 0.5 pg to 1,000 pg, or from about 2 pg to 200 pg, or from about 8 pg to about 50 pg, at each location.
The operational taxonomic units may utilize variable ribosomal DNA (rDNA) sequences as a means to detect specific organisms. Thus, the immobilized oligonucleotides may comprise eukaryotic ribosomal DNA sequences, and/or prokaryotic ribosomal DNA sequences. Additionally, or alternatively, the immobilized oligonucleotides may comprise pathogen-specific sequences. Additionally, or alternatively, the immobilized oligonucleotides may comprise novel sequences from as yet unidentified microbes.
The oligonucleotides immobilized on the array of the devices and/or systems of the present invention may be derived from sequences found by analysis of microbes present in various sources of water. In one embodiment, oligonucleotides having sequences specific to organisms found in freshwater lakes may be used. Additionally or alternatively, oligonucleotides having sequences specific to organisms found in estuaries may be used. Additionally or alternatively, oligonucleotides having sequences specific to organisms found in other types of water systems, such as tidal pools, wetlands, streams, rivers, and salt water may be used.
In one embodiment, at least one immobilized oligonucleotide comprises a sequence identical to any one of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof. In alternative embodiments, the array may comprise at least 10 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or at least 20 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5-SEQ. ID NO: 113 or a fragment thereof, or at least 50 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or at least 100 immobilized oligonucleotides that individually comprises a sequence identical to any one of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof, or the complement of SEQ ID NO: 5-SEQ ID NO: 113 or a fragment thereof.
The array devices and/or systems of the present invention may be hybridized with a nucleic acid sample that is isolated from the sample of interest. For example, PCR may be used to amplify rDNA sequences from genomic DNA from a water sample of interest, and the array used to probe those sequences. The nucleic acid sequence for hybridizing to the array may be generated using polymerase chain reaction (PCR) primers derived at least in part from at least one of a eukaryotic or prokaryotic ribosomal variable region. In an embodiment at least one of the PCR primers comprises a sequence identical to any one of SEQ ID NO: 114-SEQ ID NO: 316 or a fragment thereof. In alternate embodiments, the PCR primers comprise at least 2, or 5, or 10, or 20, or 40, or 50 primers that individually have a sequence identical to any one of SEQ ID NO: 114-SEQ ID NO: 316 or a fragment thereof. Alternatively or additionally, PCR may be used to amplify known pathogen-specific sequences from a water sample of interest, and the array used to probe those sequences. Alternatively and additionally; PCR may be used to amplify unidentified (i.e., novel) sequences specific to a water sample of interest, and the array used to probe those sequences. Alternatively or additionally, PCR may be used to amplify known non-pathogen specific sequences specific to a water sample of interest, and the array used to probe those sequences.
The present invention also provides methods for isolating samples from an ecosystem of interest that may be analyzed using molecular methods. Thus, in yet another embodiment, the present invention comprises a method to prepare a nucleic acid sample from a biosystem of interest, the nucleic acid sample comprising a plurality of bioindicator DNA sequences, wherein the method comprises amplifying a DNA sample isolated from a biosystem with a plurality of primers that have the ability to specifically amplify nucleic acid sequences comprising bioindicators. In one embodiment, at least some of the primers comprise at least a portion of a variable region of a ribosomal RNA. For example, the primers may comprise at least one oligonucleotide molecule having a sequence identical to any one of SEQ ID NO: 114-SEQ ID NO: 316 or a fragment thereof. In separate and alternative embodiments, the primers used for amplification of DNA from a sample of interest may comprise at least 10 oligonucleotide molecules having a sequence identical to any one of SEQ ID NO: 114-SEQ ID NO: 316, or a fragment thereof, or at least 20 oligonucleotide molecules having a sequence identical to any one of SEQ ID NO: 114-SEQ ID NO: 316 or a fragment thereof, or at least 40 oligonucleotide molecules having a sequence identical to any one of SEQ ID NO: 114-SEQ ID NO: 316, or a fragment thereof. In one example embodiment, the primers used for amplification of a sample of interest include about 50 oligonucleotide molecules having a sequence identical to any one of SEQ ID NO: 114-SEQ ID NO: 316 or a fragment thereof.
The present invention also comprises compositions for isolating samples from an ecosystem of interest that may be analyzed using molecular methods. Thus, in yet another embodiment, the present invention comprises an oligonucleotide having a sequence identical to any one sequence of SEQ ID NO: 114-SEQ ID NO: 316 or a fragment thereof.
The present invention may also comprise a method to identify microbes that are able to modify, or adjust to, an a particular ecosystem. In one embodiment, the method may comprise the steps of: (a) identifying a bioindicator that is associated with a particular microbe; (b) identifying the bioindicator in at least one ecosystem; and (c) correlating the presence of the microbe with a parameter specific to the ecosystem. The method may further comprise identifying the nature of the ability of the microbe to modify, or adjust to, the ecosystem. For example, the identification of a microbe whose presence shows an association with a particular toxin may indicate that the microbe has the ability to modify the toxin and/or modify the effect of the toxin on the environment.
DEFINITIONS
As used herein, the following terms shall have the definitions set out below. Also, in accordance with the present invention, conventional molecular biology, microbiology, and recombinant DNA techniques may be used that will be apparent to those skilled in the relevant art. Such techniques are explained fully in the literature (see, e.g., Maniatis, Fritsch & Sambrook, “Molecular Cloning: A Laboratory Manual (1982); “DNA Cloning: A Practical Approach,” Volumes I and II (D. N. Glover ed. 1985).
As used herein, “taxonomic unit” is a group of organisms that are considered distinct enough to be treated as a separate unit. A taxonomic unit may comprise a family, genus or species but is not limited as such. Also as used herein, each “operational taxonomic unit (OTU)” comprises a group of one or more microorganisms that are treated as a unit based on a SSU rDNA sequence identity of ≧97.5% among all members of the group.
As used herein, a bioindicator is an organism or part thereof, or a biological process, whose change in numbers, structure, or function points to a change, or a plurality of changes, in the environment. Generally, a bioindicator has a relatively high and easily identifiable sensitivity to selective environmental influences. The changes in the environment may relate to various changes in the ecosystem such as changes in a single chemical or chemical combinations in either absolute abundance or relative abundance to each other, changes in temperature, changes in biological populations, and the like. Any microbe whose relative abundance depends upon a biotic and/or an abiotic aspect(s) of biosystem of interest, or whose appearance is restricted to a subset of biosystems, is a bioindicator. Moreover, a plurality of two or more bioindicators (two or more present or more abundant than in the absence of a condition, two or more absent or less abundant than in the absence of the condition, or combinations of two or more in abundance and/or presence) may together indicate a condition of the ecosystem of interest. A condition of an ecosystem may refer to either a single biotic or abiotic factor or a combination of such factors.
A “vector” is a replicon, such as plasmid, phage or cosmid, to which another DNA segment may be attached so as to bring about the replication of the attached segment.
A “DNA molecule” refers to the polymeric form of deoxyribonucleotides (adenine, guanine, thymine, or cytosine) in either single stranded form, or a double-stranded helix. This term refers only to the primary and secondary structure of the molecule, and does not limit it to any particular tertiary forms. Thus, this term includes double-stranded DNA found, inter alia, in linear DNA molecules (e.g., restriction fragments), microbes, viruses, plasmids, and chromosomes.
DNA molecules may be identified by their nucleic acid sequences, which are generally presented in the 5′ to 3′ direction, wherein 5′ and 3′ indicate the linkages formed between the 5′-phosphate group of one nucleotide and the 3′-hydroxyl group of the next. For a sequence presented in the 5′-3′ direction, its complement is the DNA strand which hybridizes to that sequence according to the Watson-Crick base pairing model. Thus, the sequence of the complement is defined by the sequence of the original strand, such that adenine base-pairs with thymine, and cytosine base-pairs with guanine.
The term “gene” means a region of DNA encoding for the mRNA sequence that codes for a given protein/polypeptide along with elements regulating mRNA expression, or a region of DNA encoding for a ribosomal RNA (rRNA) sequence that performs a structural function as a subunit of ribosomes along with elements regulating rRNA expression.
“Messenger RNA” or “mRNA” shall mean a RNA molecule that encodes for a polypeptide. “Ribosomal RNA” or “rRNA” shall mean a RNA molecule that performs a structural function in ribosomes.
“Complementary DNA” or “cDNA” shall mean the DNA molecule synthesized by polymerization of deoxyribonucleotides from an RNA template by an enzyme with reverse transcriptase activity.
An “isolated nucleic acid” is a nucleic acid the structure of which is not identical to that of any naturally occurring nucleic acid or to that of any fragment of a naturally occurring genomic nucleic acid spanning more than three separate genes. The term therefore covers, for example, (a) a DNA which has the sequence of part of a naturally occurring genomic DNA molecule but is not flanked by both of the coding sequences that flank that part of the molecule in the genome of the organism in which it naturally occurs; (b) a nucleic acid incorporated into a vector or into the genomic DNA of a prokaryote or eukaryote in a manner such that the resulting molecule is not identical to any naturally occurring vector or genomic DNA; (c) a separate molecule such as an oligonucleotide, a genomic fragment, a fragment produced by polymerase chain reaction (PCR), or a restriction fragment; and (d) a recombinant nucleotide sequence that is part of a hybrid gene, i.e., a gene encoding a fusion protein.
“Oligonucleotide”, as used herein, is defined as a molecule comprised of two or more deoxy- or ribonucleotides, preferably more than eight. Its exact size will depend upon many factors which, in turn, depend upon the ultimate function and use of the oligonucleotide. As is known in the art, it is possible that each of the olignucleotide molecules may vary by a few bases. For example, the synthesis of the oligonucleotide may result in a portion of the oligonucleotides being less than full length. Or, a portion of the oligonucleotides immobilized at a particular location may degrade by a small percentage over time. Such oligonucleotides are considered to be “fragments” of the original oligonucleotide. Thus, an oligonucleotide sequence that is derived from, and specific to, a single, individual OTU may include fragments of that oligonucleotide.
A “DNA fragment” includes polynucleotides and/or oligonucleotides and refers to a plurality of joined nucleotide units formed from naturally-occurring bases and cyclofuranosyl groups joined by native phosphodiester bonds. This term effectively refers to naturally-occurring species or synthetic species formed from naturally-occurring subunits. “DNA fragment” also refers to purine and pyrimidine groups and moieties which function similarly but which have non naturally-occurring portions. Thus, DNA fragments may have altered sugar moieties or inter-sugar linkages. Exemplary among these are the phosphorothioate and other sulfur containing species. They may also contain altered base units or other modifications, provided that biological activity is retained. DNA fragments may also include species that include at least some modified base forms. Thus, purines and pyrimidines other than those normally found in nature may be so employed. Similarly, modifications on the cyclofuranose portions of the nucleotide subunits may also occur as long as biological function is not eliminated by such modifications.
The term “identical” refers to sequence identity between two amino acid sequences or between two nucleic acid sequences. Percent identity can be determined by aligning two sequences and refers to the number of identical residues (i.e., amino acid or nucleotide) at positions shared by the compared sequences. Sequence alignment and comparison may be conducted using the algorithms standard in the art (e.g. Smith and Waterman, Adv. Appl. Math. 2:482 (1981); Needleman and Wunsch, J. Mol. Biol. 48:443 (1970); Pearson and Lipman, Proc. Natl. Acad. Sci. (USA), 85:2444 (1988)) or by computerized versions of these algorithms (Wisconsin Genetics Software Package Release 7.0, Genetics Computer Group, 575 Science Drive, Madison, Wis.) publicly available as BLAST and FASTA. Also, ENTREZ, available through the National Institutes of Health, Bethesda Md., may be used for sequence comparison. In one embodiment, percent identity of two sequences may be determined using GCG with a gap weight of 1, such that each amino acid gap is weighted as if it were a single amino acid or nucleotide mismatch between the two sequences.
“Primer” shall refer to an oligonucleotide, whether occurring naturally or produced synthetically, which is capable of acting as a point of initiation of DNA synthesis when placed under conditions in which synthesis of a primer extension product, which is complementary to a nucleic acid strand, is induced, i.e., in the presence of nucleotides and an inducing agent such as a DNA polymerase and at a suitable temperature and pH. The primer may be either single-stranded or double-stranded and must be sufficiently long to prime the synthesis of the desired extension product in the presence of the inducing agent. The exact length of the primer will depend upon many factors, including temperature, the source of primer and the method used. For example, for multiplex PCR amplification of genomic DNA, the oligonucleotide primer typically contains 15-30 or more nucleotides, although it may contain fewer nucleotides.
The primers herein are selected to be “substantially” complementary to different strands of a particular target DNA sequence. This means that the primers must be sufficiently complementary to hybridize with their respective strands. Therefore, the primer sequence need not reflect the exact sequence of the template. For example, a non-complementary nucleotide fragment may be attached to the 5′ end of the primer, with the remainder of the primer sequence being complementary to the strand. Alternatively, non-complementary bases or longer sequences can be interspersed into the primer, provided that the primer sequence has sufficient complementarity with the sequence or hybridize therewith and thereby form the template for the synthesis of the extension product.
“Probe” shall refer to any oligonucleotide that can be immobilized at individual addresses on the array. Such probes are single-stranded DNA molecules. The act of “probing” as used herein describes the step of hybridizing a nucleic acid sample with a probe having a known sequence, or a plurality of probes having known sequences (i.e., an array), to determine whether any of the sequences in the sample are complementary to the probe sequence(s).
As used herein, the term “hybridization” refers generally to a technique wherein denatured RNA or DNA is combined with complementary nucleic acid sequence that is either free in solution or bound to a solid phase. As recognized by one skilled in the art, complete complementarity between the two nucleic acid sequences is not a pre-requisite for hybridization to occur. Hybridization conditions can be described as ranging from low to high stringency. Hybridization that occurs under high stringency conditions is specific in that a large percentage of complementarity between two nucleotide molecules is required for hybridization to occur under stringent conditions. Hybridization that occurs under low stringency conditions is less specific in that a lower percentage of complementarity between two nucleotide molecules is required for hybridization to occur under stringent conditions. Even under highly stringent conditions, there may not be perfect complementarity between two oligonucleotide molecules that hybyridize. Generally, highly stringent conditions refer to washing hybrids in low salt buffer at high temperatures. Hybridization may be to filter bound DNA using hybridization solutions standard in the art such as 0.5M NaHPO4, 7% sodium dodecyl sulfate (SDS) at 65° C., and washing in 0.25 M NaHPO4, 3.5% SDS followed by washing 0.1×SSC/0.1% SDS at a temperature ranging from room temperature to 68° C. depending on the length of the probe (see e.g. Ausubel, F. M. et al., Short Protocols in Molecular Biology, 4th Ed., Chapter 2, John Wiley & Sons, N.Y). For example, a high stringency wash comprises washing in 6×SSC/0.05% sodium pyrophosphate at 37° C. for a 14 base oligonucleotide, or at 48° C. for a 17 base oligonucleotide, or at 55° C. for a 20 base oligonucleotide, or at 60° C. for a 25 base oligonucleotide, or at 65° C. for a nucleotide probe about 250 nucleotides in length. Equivalent stringencies may be obtained with other wash solutions by varying the temperature as is known in the art. The nucleic acids in a sample will generally be labeled to facilitate detection in subsequent steps. Labeling may be carried out during the amplification, in vitro transcription or nick translation processes. In particular, amplification, in vitro transcription or nick translation may incorporate a label into the amplified or transcribed sequence, either through the use of labeled primers or the incorporation of labeled dNTPs or NTPs into the amplified sequence. Labeling may also be carried out by attaching an appropriately labeled (e.g. FICT, or biotin), dNTP to the 3′-end of DNAase fragmented PCR product using terminal deoxy-transferase (TdT). Nucleic acid probes may be labeled with radionucleotides by end-labeling with, for example, [γ-32P]ATP, or by incorporation of radiolabeled nucleotides such as [α-32P]dCTP by random primer labeling. Alternatively, probes may be labeled by incorporation of biotinylated or fluorescein labeled nucleotides, and the probe detected using antibodies to the label, or by chemical incorporation of cyanin dyes as described herein.
As used herein, “restriction endonucleases” and “restriction enzymes” shall refer to bacterial enzymes that cleave double-stranded DNA at or near a specific nucleotide sequence.
A polypeptide refers to any peptide generated from a protein or the full-length protein itself. A polypeptide may include the full-length protein or a fragment generated by proteolytic cleavage, chemical cleavage, or other means.
As used herein, an array or microarray is a solid-state grid containing short sequences of nucleic acid (usually DNA) of known sequence fixed at a particular position (i.e., location or address) on the grid. DNA arrays are usually termed microarrays due to the small size of the grid and the small amounts of nucleotide (e.g., μM or nM amounts) present at each address. The distinct nucleic acid sequences may be determined using a microsystem that may further include a carrier. An example of a microsystem is a microarray. Examples of a carrier include any one of a bead or beads, a silicon support such as a wafer, glass, a filter and a polymeric material such as a resin.
As used herein, a computer program comprises a computer-encoded language that encodes the steps required for the computer to perform a specific task or tasks.
Also, as used herein, software comprises the computer program(s) used in conjunction with any other operating systems required for computer function.
As used herein, the singular forms “a”, “an” and “the” include plural references unless the context clearly dictates otherwise.
Water Surveillance Using Nucleic Acid Based Arrays
The present invention recognizes that the abundance of certain microorganisms may be affected by local water conditions. These conditions may vary for individual species and strains. For example, whereas one species might proliferate in phosphate-rich water, another species may prefer low-phosphate water (Kilham et al, 1986, Limnol. Oceanogr., 31:1169-1181; Siver et al., 1999, Limnol. Oceanograph., 44:1928-1955). Also, phytoplankton and benthic algae may be used as indicators of eutrophication (Shubert, L. E. (ed.), 1984, Algae as ecological indicators. Academic Press, N.Y; Stoermer, E. F. and J. P. Smol, 1999, The Diatoms: applications for the environmental and earth sciences, Cambridge Univ. Press, Cambridge, UK). Or, the abundance of known microbial species can vary as a function of pollution levels (Lemke et al., 1997, Microb. Ecol., 34:224-231). It has been shown that the presence of high levels of heavy metals in water may be reflected in the tissue of the marine limpet (Pérez-López, M., et al., 2003, Journal of Environmental Health, Part A-Toxic/Hazardous Substances and Environmental Engineering, 38:2845-2856). Also, coliform bacteria may be used as an indicator of the presence of human sewage in aquatic systems.
Over the past decade, direct observation and culturing of microbes has been complemented by emerging molecular approaches, including: in situ hybridization (Schohuber, W., et al. 1991, Appl. Environ. Microbiol. 65:1258-1267), selective PCR detection of individual taxa (e.g. Oldach, D. W., et al. 2000, Proc. Natl. Acad. Sci. USA, 97:4303-4308; Rublee, P. A., et al. 2001, Environ. Health Perspectives, 109 [Supplement 5]:765-767), community assays such as Differential Gradient Gel Electrophoresis (DGGE) analyses (e.g., Díez, B., et al. 2001, Appl. Environ. Microbiol., 67:2942-2951) and filter macroarray hybridization (e.g., Rudi, K., et al. 2000, Appl. Environ. Microbiol., 66:4004-4011). In situ hybridization allows taxon-specific identification and enumeration of target organisms. Although highly specific, the method is time consuming as it generally involves microscopic observation of the sample. PCR, the polymerase chain reaction, may detect a targeted organism that exists in low abundance in the natural environment. Selective PCR detection of individual microbes is highly specific, rapid, and may even be quantitative (e.g., real-time quantitative PCR), but may be limited in that primers specific to the sequence to be amplified must be available. DGGE analysis has become a relatively common approach to community assessment of prokaryotic or even eukaryotic communities, but is limited in that it relies on the assumption that different nucleic acid sequences will display differential mobility in a gradient gel, which is not always the case.
From the standpoint of environmental investigations, recent microarray development efforts have increasingly focused on the identification of genes from specific microbial organisms associated with environmental processes, such as nitrogen fixation, or with the detection of specific microbes (Wu et al., 2001, Appl Environ. Microbiol., 67:5780-5790). Most of the microbes that exist in freshwater sources, however, are unknown and/or unculturable (Kaeberlein et al., 2002, Science, 296:1127-1129; Hiorns et al., 1997, Appl. Evnviron. Microbiol., 63: 2957-2960; Lopez-Garcia et al., 2001, Nature, 409:603-607).
A first step of developing methods and systems to monitor water may be the identification of suitable bioindicator molecules. For example, one aspect of developing an array to monitor a water supply is to develop nucleic acid sequences that are diagnostic of the aqueous microbial population. FIG. 1 shows an embodiment of a method of the present invention that may be used to identify potential ecosystem biomarkers. As shown in FIG. 1, the method 2 may comprise a first step of isolating a sample from an ecosystem of interest 4. The ecosystem may comprise a body of water. In alternate embodiments, water from a freshwater lake, an estuary, a tidal pool, wetlands, a stream, river, or salt water may be used.
The bioindicator may comprise the microorganism itself, or a molecule that provides information about the microorganism. The bioindicator may comprise a nucleic acid molecule. Nucleic acid molecules may be useful as bioindicators as nucleic acid molecules comprise a source of qualitative and quantitative information. By analyzing the sequence of the DNA molecules in the water sample, information about the genetic make-up of the microbes present in the sample may be obtained. Also, by measuring the amount of DNA molecules in the water sample, information about the amount of specific microbes in the sample may be obtained. As described herein, nucleic acid molecules, such as DNA, may be used to identify and classify microorganisms into operational taxonomic units (OTUs). Thus, the method may comprise the step of isolating nucleic molecules from the water sample 6.
The method may next comprise the step of determining the sequence of DNA molecules isolated from the sample of interest 8. In an embodiment, rDNA may be used as diagnostic sequences. Thus, to make an array for monitoring water, a first step may comprise the isolation and sequence characterization of 16S rDNA (prokaryotic) and 18S (eukaryotic) rDNA species from selected water reservoir samples. The DNA molecules selected for analysis may comprise small subunit (SSU) ribosomal RNA genes (SSU rDNA). In this way, recovery of DNA sequences may be based on the endogenous abundance of individual microbes, and is not restricted to the recovery of known microorganisms.
The DNA sequences isolated from the ecosystem of interest may be used to generate bioindicator probes. In one embodiment, the bioindicator probes are categorized into operational taxonomic units (OTUs) 10. Both prokaryotic and eukaryotic SSU rDNA can be useful targets for determination of operational taxonomic units because SSU rDNA sequences contain highly conserved nucleotide regions interspersed with variable regions. The conserved sequences provide an anchor by which a plurality of different rDNA sequences may be isolated from a sample. By using primers that hybridize to the conserved regions of either eukaryotic or prokaryotic rRNA genes, a library of amplified rDNA sequences that are different in the variable regions may be isolated from a single sample. Primers that may be used for amplification of prokaryotic rDNA sequences may comprise SEQ ID NOS: 1 and 2 (Table 1). Primers that may be used for amplification of eukaryotic rDNA sequences may comprise SEQ ID NOS: 3 and 4 (Table 1).







TABLE 1







Sequences and target positions of primers used to amplify rRNAs










Primer
Sequence
SEQ ID NO:
Location





16S Forward
AGAGTTTGATCCTGGCTCAG1
1
 8-272


16S Reverse
AAGGAGGTGATCCAGCCGCA1
2
1541-15222


18S Forward
AACCTGGTTGATCCTGCCAGT3
3
 1-214


18S Reverse
TGATCCTTCTGCAGGTTCACCTAC3
4
1795-17724





1Primers from Edwards et al., 1989, Nucleic Acids Res., 17,7843-7853; Bruce et al., 1992, Appl. Environ. Microbiol., 58, 3413-3416.


2Position in E. coli (Brosius et al., 1981, J. Mol. Biol., 148, 107-127).


3Primers from Medlin et al., 1988, Gene 71, 491-499.


4Position in S. cerevisiae (Rubstov et al., 1980, Nucl. Acids Res., 8, 5779-5794).






The amplified rDNA products may be used to provide a foundation for phylogenetic classification and comparison of both prokaryotic and eukaryotic microbial species isolated from the water samples of interest (see e.g., McCaig, A. E., et al., 1999, Appl. Environ. Microbiol., 65:1721-173036, Reysenbach, A. L., et al., 1992, Appl. Environ. Microbiol., 58:3417-3418; Pace et al., 1986, Adv. Microb. Ecol., 9:1-55; Sogin and Gunderson, 1987, Annals. NY Acad. Sci. 503:125-139). A level of 97.5% sequence identity is a generally accepted criterion by which rDNAs may be placed in the same operational taxonomic unit (OTU). Because multiple small subunit rDNAs may reside within a genome for any single species (Farrelly et al., 1995, Appl. Environ. Microbiol. 61:2798-2801), a 97.5% level of sequence identity generally allows for the possibility that sequences in the same species are recovered. In performing this type of analysis, it may be necessary to check for artifactual sequences resulting from the amplification protocal (e.g., CHIMERA-CHECK; Kopzcysnski et al., 1994, Appl. Environ. Microbiol., 60:746-748; Wang and Wang, 1995, Appl. Environ. Microbiol., 63:4645-4650; Qui et al., 2001, App. Environ. Microbiol., 58: 2717-2722).
The present invention recognizes that the sequences of small subunit rRNAs in prokaryotes and eukaryotes may allow for phylogenetic classification of known and novel species as operational taxonomic units (OTUs). For example, FIGS. 2 and 3 show rank-abundance curves for 16S rDNA sequences, and 18S sequences, respectively, isolated from five separate samplings from three different lakes that were organized as operational taxonomic units. The water samples were taken from the following lakes: Lake Townsend, NC, Station 1, in June; Lake Townsend, NC, Station 2 in June; Lake Townsend, Station 1, in March; City Lake, NC; and Lake Toolik, AK. It can be seen that some of the OTUs have multiple members (i.e., # clones >1), whereas many of the OTUs were represented by only one sequence. In one embodiment, a sequence from a defined OTU will recognize (i.e., hybridize to) other members of the OTU under the conditions used for hybridization of the array. Thus, in one embodiment, an array may be made using unique OTUs as isolated from the various samples.
The sequences of rDNAs from isolated samples may be used to generate phylogenetic trees. In one embodiment, the Unweighted Pair Group Method with Arithmetic Mean (UPGMA) may be used to compare the sequence data from OTUs and to generate a phylogenetic tree. This type of analysis may be used to confirm the relationship between known sequences, and to order newly identified sequences and OTUs. For example, FIG. 4 shows a prokaryote tree constructed using 111 different 16S rDNA OTUs, including 40 OTUs that are based on known rDNA sequences. FIG. 5 shows a eukaryote tree constructed using 109 18S rDNA OTUs, and including 22 known rDNA sequences. In FIGS. 4 and 5, Lake Townsend, NC, samples are denoted LT (1J, Station 1 in June; 2J, Station 2 in June; 1M, Station 1 in March), City Lake, NC samples are denoted CL, and Toolik Lake, AK samples are denoted TL.
The sequence information may also permit the development of species specific primers. Species-specific primers may be used to characterize a variety of prokaryotic and eukaryotic microbes such as cyanobacteria, Mycobacterium, Pfiesteria piscicida, and other types of microbial species (see e.g., Edwards, U., et al., 1989, Nucleic Acids Res., 17:7843-7853; Reysenbach, A. L., et al., 1992, Appl. Environ. Microbiol., 58:3417-3418; Shi, W., et al., 2002, Appl. Environ. Microbiol., 68:3859-3866; and O'Brien, W. J., et al., 1997, The Limnology of Toolik Lake, p. 61-106, In: Freshwaters of Alaska—ecological syntheses, A. M. Milner and M. W. Oswood (eds), Springer-Verlag Publishers, New York, N.Y.).
Bioindicators may be unique to a specific biosystem, or may be shared among a plurality of biosystems. A diversity of microbial species may be readily retrievable even from a single body of water. Also, while any one body of water may have several unique OTUs, it is highly likely that the sample will include OTUs that are common to other biosystems. Such common OTUs may represent 10% or more of the rDNAs analyzed in the sample, and may be shared across water samples. Also, an environmental event that occurs in an environmental community, such as a contamination, may alter the abundance of individual microbial species and related bioindicators in that community. The method may therefore comprise the step of determining whether an operational taxonomic unit (OTU) and/or an individual or species-specific DNA sequence is specific to a particular ecosystem, or varies in abundance between ecosystems. For example, a bioindicator for assessing freshwater microbial communities may comprise nucleic acid sequences that are characteristic of the freshwater system, or that are diagnostic of the response of microbes to certain changes in the fresh water environment. Or, a bioindicator for assessing marsh water microbial communities may comprise nucleic acid sequences that are characteristic of the marsh environment, or that are diagnostic of the response of microbes found in the marsh environment to certain changes in a marsh water environment. Thus, referring back to FIG. 1, the method may therefore comprise identifying bioindicators or OTUs that vary among ecosystems 12. The method may also comprise identifying bioindicators or OTUs that are shared among ecosystems 13.
To determine which OTUs, if any, appear in more than one ecosystem, the sequences from a library of DNA sequences isolated from a biosystem of interest may be compared to those sequences in every other library from biosystems of interest in pairwise library comparisons, and a similarity coefficient may be calculated for each pairing. For example, in an analysis of five different samplings of DNA molecules from three different lakes (Lake Townsend, NC; City Lake, NC; and Toolik Lake, AK) there was some overlap between every pair of samples. There were also notable differences between the lakes. For example, none of the prokaryotic sequences were shared between Lake Townsend, a mesotrophic lake in North Carolina, and Toolik Lake, an oligotrophic lake in Alaska.
Venn diagrams may be used depict sample comparisons at different spatial and temporal scales to identify sequences that may differ between biosystems. Referring now to FIG. 6, in a fine-scale spatial comparison of samples taken in June from stations 1 and 2 at Lake Townsend, NC (LT-1J and LT-2J), it can be seen that even between samples that may be expected to be highly similar, differences in sequences may be found. For example, for LT-1J and LT-2J, there were two rDNA sequences that occurred four times as often in LT-2J as in LT-1J: an unidentified 16S rDNA OTU, and an 18S rDNA from Geminigera cryophila (not shown). Such unequal occurrences of an OTU between samples may signify a detectable difference in the relative abundance of a specific microbial population between samples, and OTUs that consistently vary in frequency among samples are potential bioindicators.
Once the nucleic acid sequences isolated from various ecosystems have been identified and compared, it may be possible to compile OTUs as putative bioindicators 14 (FIG. 1). For example, for five samplings from three different lakes, 26 different eukaryotic OTUs represented by multiple copies, including 11 that are associated with known species, may be identified. Another 79 eukaryotic OTUs may be obtained as single copy clones, with many of the single-copy OTUs representing unidentified species (Marshall, 2002, Masters Thesis, University of North Carolina at Greensboro). Also, 45 different prokaryotic OTUs may be detected in multiple copies. Of these, 10 species are associated with a known species, and 19 species display substantial homology to reported sequences for as yet unidentified species. Another 92 single copy rDNA sequences, most from unidentified prokaryotes, may be recovered (Amos, 2002, Masters Thesis, University of North Carolina at Greensboro). As described in more detail herein, all of the sequences identified from the ecosystems of interest (e.g., water samples), whether derived from known or previously unidentified rDNA sequences, may be used as probes printed on an array of the present invention.
The method may next comprise the step of organizing a nucleic acid array that can reflect microorganisms that are common to multiple communities, as well as organisms that are specific to one or only a few communities to thereby monitor the effect of an ecological change 16. Thus, the ability to assess environmental parameters of water quality may require a sufficient number of bioindicator species that have unique profiles in different ecosystems, but may also require species that are shared among samples to allow for general application.
The basic strategy for detection and identification involves the use of gene microarrays: a set of single-stranded DNA sequences covalently bound to glass as an array of several thousand spots. Each array sequence (“spot”) corresponds to the DNA sequence of a particular pathogen or aquatic microbe. The array may comprise nucleic acids that are specific to known organisms. Additionally or alternatively, the array may comprise nucleic acids that are grouped to provide information about various taxonomic groups. For example, the array may comprise a plurality of prokaryotic and/or eukaryotic nucleic acid sequences derived from specific rDNAs. Or, the array may comprise a plurality of nucleic acid sequences organized by operational taxonomic unit. Notably, there is no requirement that the environmental DNA samples used to develop the array are the same as the environmental communities to be analyzed. Examples of an electrochemical detector are described in e.g., U.S. Pat. No. 6,338,820; U.S. Pat. No. 6,326,228; U.S. Pat. No. 6,203,981; U.S. Pat. No. 6,168,948; U.S. Pat. No. 6,129,896; U.S. Pat. No. 6,074,725; U.S. Pat. No. 6,048,692; U.S. Pat. No. 6,033,546; and U.S. Pat. No. 5,858,195. The subject matter of each patent is incorporated by reference in its entirety. Oligonucleotide arrays generally include a substrate having a large number of positionally distinct oligonucleotide probes attached to the substrate. These oligonucleotide arrays, also described as “GENECHIPTM arrays,” have been generally described in the art, for example, U.S. Pat. No. 5,143,854 and PCT patent publication Nos. WO 90/15070 and 92/10092. These pioneering arrays may be produced using mechanical or light directed synthesis methods which incorporate a combination of photolithographic methods and solid phase oligonucleotide synthesis methods. See Fodor et al., Science, 251:767-777 (1991), Pirrung et al., U.S. Pat. No. 5,143,854 (see also PCT Application No. WO 90/15070) and Fodor et al., PCT Publication No. WO 92/10092, all incorporated herein by reference. These references disclose methods of forming vast arrays of peptides, oligonucleotides and other polymer sequences using, for example, light-directed synthesis techniques. Techniques for the synthesis of these arrays using mechanical synthesis strategies are described in, e.g., PCT Publication No. 93/09668 and U.S. Pat. No. 5,384,261, each of which is incorporated herein by reference in its entirety for all purposes. Incorporation of these arrays in injection molded polymeric casings has been described in Published PCT Application No. 95/33846. The basic strategy for light directed synthesis of oligonucleotide arrays is as follows. The surface of a solid support, modified with photosensitive protecting groups is illuminated through a photolithographic mask, yielding reactive hydroxyl groups in the illuminated regions. A selected nucleotide, typically in the form of a 3′-O-phosphoramidite-activated deoxynucleoside (protected at the 5′ hydroxyl with a photosensitive protecting group), is then presented to the surface and coupling occurs at the sites that were exposed to light. Following capping and oxidation, the substrate is rinsed and the surface is illuminated through a second mask, to expose additional hydroxyl groups for coupling. A second selected nucleotide (e.g., 5′-protected, 3′-O-phosphoramidite-activated deoxynucleoside) is presented to the surface. The selective deprotection and coupling cycles are repeated until the desired set of products is obtained. Since photolithography is used, the process can be readily miniaturized to generate high density arrays of oligonucleotide probes. Furthermore, the sequence of the oligonucleotides at each site is known. See, Pease, et al. Mechanical synthesis methods are similar to the light directed methods except involving mechanical direction of fluids for deprotection and addition in the synthesis steps. This technology may include the use of complex micro-robotics or the adaptation of ink-jet technology to apply chemical and biochemical substances to chosen sites on the substrates. Frequently, at least one of the reactants in a chemical assay to be performed is chemically linked to or otherwise immobilized at the reaction site. This is done, so that fluids may be added to and removed from the reaction site without removing at least one intermediate or end product of the reaction, which intermediate or end product(s) is (are) to be retained at the reaction site, so that the outcome of the chemical assay may thereby be detected.
Samples that are derived from very different environmental communities may be expected to vary more than samples that are derived from similar communities, or the same community. Still, samples taken from a single lake, but either at a different location, or a different season, may also show variation (e.g., FIG. 6). The variation may be qualitative, in that specific OTUs are either absent from, or present in, a water sample. Or, it may be that a certain OTU is much less abundant in one sample than another sample. For example, FIG. 7 illustrates a quantitative PCR determination of the relative amounts of three nucleic acid sequences found in each of three lake samples tested, but in highly varied amounts. For each of the curves shown in FIG. 7 (7A, 7B, and 7C), the second curve from the left represents the sample from which the nucleic acid of interest was detected in high abundance, and the third and fourth curves from the left represent other lake samples tested. Also, results for a positive control, including each of the test samples, and a negative control with no DNA, are shown. Such skewed amplification curves may be found where DNAs vary in quantity between samples. In alternate embodiments, the template DNAs may vary 10-fold, or 20-fold, or 50-fold, or more than 200-fold, between samples.
FIG. 8 provides a schematic representation of a method that may be used to monitor water in accordance with an embodiment of the present invention. The method may comprise the first step 16 of generating an array comprising a plurality of oligonucleotides immobilized at known locations on a substrate, wherein each location on the array comprises an oligonucleotide having a sequence derived from a single, predetermined microbial operational taxonomic unit (OTU) as is described herein for FIG. 1.
Next, the method may comprise the step of isolating a sample from an ecosystem of interest 22. In one embodiment, the ecosystem may comprise water. Samples may be collected from one body of water at different levels, or at different locations, and/or during different times of the year. Also, samples from different bodies of water may be used. For example, samples may be collected from different lakes, pools, estuaries, or marshes. Or, bodies of water comprising different types of growth levels may be used (e.g., eutrophic, mesotrophic, or oligotrophic). Or, samples may be obtained from a body of water because there is a reason to suspect that the body of water has been contaminated in some way.
The method may next comprise the step of preparing a DNA sample from the ecosystem of interest 24. For example, the polymerase chain reaction (PCR) may be used to amplify DNA sequences from a water sample of interest. The PCR amplification may use primers designed to amplify sequences that, if present in the sample and amplified, are complementary to the sequences on the array. In that way, if a sequence on the array is present in the sample of interest, it may be detected. In one example, a multiplex (i.e., multiple primer) PCR amplification is used to amplify multiple sequences from the sample of interest that are complementary to sequences immobilized on the array. Primer pairs that may be used for multiplex PCR may include a sequence selected from the group of SEQ ID NO: 114-SEQ ID NO: 316.
The amplified DNA molecules from the sample of interest may be then labeled in some manner 26. For example, the amplified DNA molecules may be labeled by the chemical incorporation of a fluorescent dye(s) as described herein.
Next, the method may comprise the step of hybridizing the labeled DNA sample from the ecosystem of interest to the array 28. In one embodiment, a high stringency hybridization is used. For example, the hybridization conditions may comprise the conditions as described herein.
The presence of sequences in the sample of interest that are complementary to putative bioindicator sequences on the array may be determined by measuring locations on the array that exhibit hybridization to the labeled probe 30. In this way, the identity, and in some cases, the relative amounts, of sequences that are in the sample may be determined.
The method may then comprise the step of correlating hybridization of the DNA sample to the array with a parameter that comprises at least part of the ecosystem. For example, if two samples of water (e.g., sample A and sample B) are hybridized to the same array, and different hybridization patterns result, than the oligonucleotide(s) on the array that displays a change in hybridization may correspond to a DNA sequence(s) that is diagnostic of a difference, or a plurality of differences between the two samples. Thus, the method may comprise the step of determining whether the pattern of hybridization at any one position or at a plurality of positions on the array changes 32.
In one embodiment, no change in the pattern of hybridization at any one position or at a plurality of positions on the array is detected upon hybridization with two different samples. In this, case, no change in water quality is detected, and no action is required 34. Alternatively, a change in the pattern of hybridization at any one position or at a plurality of positions on the array is detected upon hybridization with two different samples. In this case the change in the water quality may be recorded 36 and the nature of the change determined 38 such that appropriate action may be taken.
An example of the application of pattern analysis to the evaluation of a biosystem is shown in FIG. 9. As a first step, the method may include determining the pattern of hybridization on the array 32. Methods for measuring hybridization may include use of a radiolabeled dNTP during amplification of the sample DNA such that DNA sequences that hybridize to the array may be detected by autoradiography. Alternatively, the amplified PCR products may be labeled with a fluorescent dye and hybridization detected using a fluorometer. Once the pattern of hybridization has been measured and recorded, the pattern may be compared with the pattern of hybridization produced by a separate sample, such that any changes in hybridization may be documented. At this point, a determination may be made as to whether the new hybridization pattern has a change that is associated with a known hybridization pattern 39. If it is determined that the pattern of hybridization is not associated with a known biological change 52, the sample may be analyzed to determine the nature of the change 54. Once the nature of the change is known, the pattern may be added to a database 40 of patterns associated with known biological changes 56.
Still referring to FIG. 9, in some cases, it may be possible to correlate the pattern of hybridization with known a biological change(s) 40. This may be possible even where at least some of the sequences on the array, or the changes in the hybridization pattern, arise from novel, or previously uncharacterized, organisms. For example, there may be a single change in the pattern of hybridization to an array for two samples that is diagnostic of a single change between the two samples. Thus, as shown in FIG. 9, hybridization at the position corresponding to an oligonucleotide having the nucleic acid sequence of A may be associated with the presence of chromium 42. Again, it may not be necessary to identify or characterize the organism from which sequence A is derived as such information may be ascertained merely by prior characterization that sequence A is associated with chromium in a water sample. Alternatively, a single change in the pattern of hybridization to an array for two samples may be diagnostic of a plurality of changes between the two samples. For example, a change in hybridization at sequence B may be associated with a change in the ratio of nitrogen to phosphate in a water sample 44. Or, there may be multiple changes in the pattern of hybridization to an array for two samples that are diagnostic of a single change between the two samples. For example, the presence of hybridization at oligonucleotides having sequences C, D, and E and the absence of hybridization at oligonucleotide corresponding to sequence F may be diagnostic of the introduction of arsenic into the water system 46. In yet another embodiment, there may be multiple changes in the pattern of hybridization to an array for two samples that are diagnostic of multiple changes between the two samples. For example, the presence of hybridization at oligonucleotides corresponding to sequences G, H, and I, in combination with the lack of hybridization at oligonucleotides corresponding to sequence J, may be diagnostic of a loss of multiple eukaryotes from the system. The information provided by the array may be comprehensive and allow for any remedial steps that may be required to be taken. The analysis may be formatted as part of a computer program so as to be run on a computer. In one embodiment, the known patterns may be included as a part of the computer program. Alternatively, the information provided by the array may be considered to provide a preliminary screening which may then be verified by chemical and/or microbiological analysis of the sample 60.
As described herein, primers that may be used for amplification of bioindicator nucleic acid molecules from an ecosystem may be designed to amplify sequences from the variable regions of rDNA. Small subunit rRNA genes (SSU rDNA) are especially useful targets for the molecular identification of microbial species because these sequences contain highly conserved nucleotide regions interspersed with variable regions. The variable regions may be used as a foundation for phylogenetic classification and comparison of both prokaryotic and eukaryotic microbial species (e.g., Sogin and Gunderson, 1987, Annals. NY Acad. Sci., 503:125-139). The sequence information also permits detection and quantification of microbial species by PCR amplification using species-specific primers.
Thus, in one embodiment, ribosomal DNA that includes highly conserved and highly variable regions is used to characterize the presence of microbial community members. Species-specific or OTU-specific primers that anneal to internal variable regions can then be used to test for the presence of individual species. For both eukaryotic and prokaryotic rDNA, the variable rDNA regions show sufficient variability to develop amplification primers and probes that may be sensitive and specific to the organism to be tested.
For increased specificity and sensitivity in microarray experiments, variable sequence regions within the SSU rDNA may be utilized in a two-tiered strategy: (1) species-specific or OTU-specific PCR primers (e.g., Tables 2 and 3) can be multiplexed in individual PCR reactions to selectively amplify individual species or OTUs; (2) PCR products may then be labeled and hybridized to corresponding species-specific or OTU-specific oligonucleotide probes (e.g., Tables 2 and 3) immobilized on a microarray, where the probes immobilized on the array have sequences that are included in the amplified DNA products. The process may provide improved specificity and sensitivity because each of the species-specific or OTU-specific primer pairs and probes are designed using the same rDNA sequence.
To determine nucleic acid sequences that are specific to a single OTU, and thus can be used to detect the presence of a specific OTU in an ecosystem of interest, water samples were used to isolate DNA sequences derived from microbial ribosomal DNA. The individual ribosomal DNAs were cloned and the nucleic acid sequence for each clone was determined. Then, sequences from each rDNA clone were simulataneously aligned with either a prokaryotic rDNA sequence or a eukaryotic rDNA sequence to determine regions of variability for the cloned rDNAs. In this way, primers and probes (e.g., Tables 2 and 3) specific a particular OTU (or microbe population) were identified.
To ascertain the relative location and degree of variability among variable regions, rDNA sequences can be initially aligned using the multiple alignment computer program CLUSTAL W (Thompson et al., 1994, Nucleic Acids Res., 22:4673-4680). Multiple alignment parameters including a gap initiation penalty of three, a gap extension penalty of one, a base match score of one, and a base mismatch penalty of one were used. Transitions were not weighted and terminal gaps were not penalized. By aligning the cloned sequences with either the prokaryotic or eukaryotic rDNA, the SSU rDNA was demarcated into conserved and variable sequence regions, which were further aligned by hand to optimize the multiple alignment result where necessary. For prokaryotic primer sequences and probes (Table 3), variable sequence regions were used within nucleotides 50-880 (V1, V2, V3, and V4), based on alignments with E. coli rDNA (SEQ ID NO: 317) (FIG. 10A) (Brosius et al., 1981, J. Mol. Biol., 148:107-127; GenBank Accession No. V00348). Specifically, nucleotides 50-150 (V1 region) (SEQ ID NO: 319) or 160-250 (V2 region) (SEQ ID NO: 320) in the forward direction and nucleotides 430-510 (V3 region) (SEQ ID NO: 321) or 820-880 (V4 region) (SEQ ID NO: 322) (FIG. 10C) in the reverse direction allow for OTU-specific amplification by PCR that includes a region that complements microarray probes, which include nucleotides 160-250 (V2) (SEQ ID NO: 320) or 430-510 (V3) (SEQ ID NO: 321). Primer sequences within these regions were selected to maximize specificity for each individual organism. Based on alignments with S. cerevisiae (Rubstov et al., 1980, Nucl. Acids Res., 8:5779-5794; GenBank Accession No. V01335) (SEQ ID NO: 318) (FIG. 10B) using the same alignment conditions, eukaryotic primer sequences and probes (Table 2) included variable sequence regions within nucleotides 50-1100 (V1, V2, V3, and V4). Specifically, positions 50-550 (V1 plus flanking sequence region) (SEQ ID NO: 324) in the forward direction and positions 800-870 (V3) (SEQ ID NO: 326) or 1000-1100 (V4) (SEQ ID NO: 327) in the reverse direction allow for OTU-specific amplification of a region that includes a region that complements probes within nucleotides 600-800 (V2) (SEQ ID NO: 325) or 1000-1100 (V4). When the sequence regions specified for primer and probe design do not include OTU-specific sequences, such that primers designed for two microbes would be the same or substantially similar, other variable regions are used. For example, prokaryotic primer sequences have also included nucleotides 1100-1160 (V6) (SEQ ID NO: 323) in the reverse direction and eukaryotic primer sequences have also included nucleotides 1350-1450 (V5) (SEQ ID NO: 328) in the reverse direction, where necessary.
Thus, in one embodiment of the present invention, amplification of a genomic sample DNA may be performed by multiplex PCR using primers chosen to provide products that can hybridize to taxon-specific ribosomal DNAs. Using this protocol can dramatically reduce non-specific labeling, and eliminate the need for intermediate PCR reactions, which reduce sensitivity. Oligonucleotide probes that may be spotted to provide a taxon-specific array (e.g., SEQ ID NOS: 5-113), and the primers used to detect (i.e., amplify) such sequences in water samples (e.g., SEQ ID NOS. 114-316), are shown in Tables 2 and 3. For example, primers having the sequences SEQ ID NOS. 114 and 115 (1F and 1R, respectively) may be used to amplify DNA from a water sample such that the amplification product contains sequences that will hybridize with an oligonucleotide probe (1P) immobilized on an array, where probe 1P has the sequence described by SEQ ID NO: 5. In one embodiment, multiple primer pairs (e.g., SEQ ID NOS: 114-214) are used to amplify DNA sequences that include SEQ ID NOS: 5-60). In addition, as is known in the art, the reverse complementary sequence of each probe sequence in Tables 2 and 3 may also be spotted as an oligonucleotide on the array.







TABLE 2







Eukaryotic probes and primer pairs used for multiplex PCR














Eukaryotic
SEQ


GenBank

SEQ



primer sequence 
ID
PCR

Accession 
Probe Sequence
ID
Oligo


(5′-3′)
NO:
No.
Template
No.
(5′-3′)
NO:
No.

















ATACAGGCGC
114
1F
Acanthamoeba
AY351647
ACTAACTCAATAGC
5
1P


TCGATAAGAG


mauritaniensis

AGGAACGGGAATC




AGCTGCTAGG
115
1R


CAGAAGGAGGGGA




GGAGTCATTC




CGGGCGGGCC




AACTCGACTTT
116
2F
Cryptosporidi
AF222998
GATTTCTCATAAGG
6
2P


ATGGAAGGG


um parvum

TGCTGAAGGAG




CAAAGTCCCTC
117
2R


TAAGGAACAACCT




TAAGAAGAC




CCAATCTCTAGT




TTGGCTTTAGC
118
3F
Cyclospora
AF111183
AGTTCCGGAACACC
7
3P


CGGCGATAG


cayetanensis

AACGCACGCAGCG




AAGCCAAGGT
119
3R


AAGCGCGGAAGGC




AGGCGTTTCC




TACCGGAAGA




GACGACACAT
120
4F
Entamoeba
X65163
GAAATGTCTTATTG
8
4P


AACTCTAGAG


histolytica

ACATCCCCTCAGCA




TCATCCAATCC
121
4R


TTGTCCCATGCTTG




TTGGTTGAC




AATATTCA




AACTTGCCCAA
122
5F
Giardia
AF199449
CCCACGCGGCGGG
9
5P


TGCGCGG


intestinalis

TCCAACGGGCCTGC




GGGAATACGG
123
5R
isolate Dog19

CTGGAGCGCTCCCG




TGGTGTCTG




TTTCCTCGT




GATTGGAATG
124
6F
Isospora belli
AF106935
GAATTTCACCACGT
10
6P


ATGGGAATCC




ACACACCCCTAAG




AGGAGAAGTC
125
6R


GGCGGACTGGCTG




AAGTATGACG




CTTCCAGCAG




GCGGTAGTAA
126
7F
Microsporidium
AY140647
CTTTATCATCGGAC
11
7P


GGAGACGTG


sp. STF

TCGCCCCTGGCCAG




GCATCGGCATC
127
7R


CGCTTTCGCCTCTG




GTTTACTGC




TCGCTCCT




TTCGGTGGTGA
128
8F
Naegleria
AF338423
CCTCCAACCATCTC
12
8P


GGTATTATC


fowleri

CTGATGGAACTAGT




AAGATCGCTG
129
8R


TACCCCGTAAACAC




GGATAGTGTC




TCTTAGGT




ATCGAGTATCA
130
9F
OTU LT3A27,
N/A
ACGGAGACAAACA
13
9P


ATTGGAGGG


multi-copy,

AGCACCAACACAA




GACGGGGTCA
131
9R
identified as

GTGAAGGGCACGT




ATACAACGAC


Asterionella

TGCTCCAACCA







formosa






GCCAATGGTCT
132
10F
OTU LT1A42,
N/A
CAAGCAGAAAGGC
14
10P


TCTTATTGG


multi-copy,

ACGCGCGCACCGTC




GAGGTCGTAA
133
10R
identified as

CAACCAGAGGCTG




ATTGACACTC


Cryptomonas

ACAGTTCACA







sp., strain









M420






TTCAAACCGGC
134
11F
OTU LT1A4,
N/A
GCACGCGCATGCC
15
11P


CTCGTTCTG


multi-copy,

GTCCGACCAGAGG




CCCATAACCA
135
11R
identified as

CCGACAGCCCACA




ACGAAATAGC


Cryptomonas

CGCGCCCAAAA







ovata, strain









CCAP 979/61






TTAGCGAATCG
136
12F
OTU LT2A7,
N/A
TAACTGTCCCTGAT
16
12P


TGGCACGTC


multi-copy,

GGGACTAGTAGGG




AATGTATTCCT
137
12R
identified as

ATTGGTTTAAAGCC




GCAAACGCC


Dileptus sp.

TCTCCCTAG




GGGTTCTTACG
138
13F
OTU LT2A19,
N/A
TCTCAGACGGATGA
17
13P


AACTTTGGG


single-copy,

ACGCCTATACCTCG




CTGATCGGGCT
139
13R
identified as

ACCGGAGCCGCTGT




TGAAAGACC


Coleps sp.

ACAAACGC




TATCGAGGAC
140
14F
OTU LT3A2,
N/A
ACCTAATGCCACAC
18
14P


CAATTGGAGG


single-copy,

AGATTCCACCCAAG




GACGGAGTCA
141
14R
unidentified

GATGGACGAGCTG




ATACAACGAC




CCCAAGTAC




TGGACTCTTTT
142
15F
OTU LT1A3,
N/A
CCATCTGCGCCTCA
19
15P


GAGTCCGGC


single-copy,

ACATGCAGGTAAA




ATCAATACTAA
143
15R
unidentified

TCGTAAAGAAAAG




CACCCACCG




GCCAAATAGC




TAACGATAGC
144
16F
OTU LT1A10,
N/A
GTATCACACCAGG
20
16P


GGGCTCGTTC


multi-copy,

GAGGTTATTGAACG




CATAGGGTGCT
145
16R
unidentified

CAGACCACCTAGGT




GATAGAGTC




AACACCTAA




CCGAGATTTCT
146
17F
OTU LT2A12,
N/A
AAGGATGCTTTCAG
21
17P


CGGAAATTG


multi-copy,

GCACTGATCGCGCA




TTTCTCACGAG
147
17R
unidentified

CACTGAGGTGGGA




CTGCTGAGG




AGTGCCGTT




ATGGTGGAGG
148
18F
OTU TL1A16, 
N/A
TAAGTGCAACGGG
22
18P


TGATTCATTC


multi-copy,

ATCCTCATGCAGAA




AATTGACATCC
149
18R
unidentified

AGACCCGAGCCTG




ACTGATCCC




CCGTCCGACC




GATACAGGAC
150
19F
OTU TL1A1,
N/A
AAAGTAAACCTGC
23
19P


TCATCCGAGG


multi-copy,

CAGCACAGACGGA




AAACGCCTGC
151
19R
unidentified

CACTCGGCGAAGA




AGATCGCTAG




GCACCCGCCTG




ACAATGCCGG
152
20F
OTU TL1A2,
N/A
TTAATGCCAGATAT
24
20P


GCCTTTCAAG


multi-copy,

GCTCTCCCCGAGGA




TGGAGTCGTTA
153
20R
unidentified

TGGCTGCAGACAC




CAAACTTCC




ATAGTACAG




TCGGCGACGA
154
21F
OTU TL1A9,
N/A
AGTCGACCAGTTCT
25
21P


TGATTCATTC


multi-copy,

GACCCATGAGGCC




TGAACAAACC
155
21R
unidentified

GACCGGCTGAGCTC




ACGCCCAATC




ACTCTGAAC




CGGTTTACCGG
156
22F
OTU TL1A12,
N/A
TCAAACCTGATTCA
26
22P


CGATAGATC


multi-copy,

AACCCGTATGGGTC




TTCTCTCGAGG
157
22R
unidentified

GATCGGTCGTCCTC




TGCTGAAGG




AGCAGAAA




AATCGGATCG
158
23F
OTU TL1A21,
N/A
TGGTAGGCTACCAC
27
23P


CATGGGCTAG


multi-copy,

TGCGCATCCACAAG




GAACGGGATA
159
23R
unidentified

GAGGCAGAAACTA




ATTCTCGCCC




GCCAACCAG




CCCACTTATGT
160
24F
OTU CL1A3,
N/A
GCTTCATGCAGGAG
28
24P


GGGTTTGAC


single-copy,

CATCTCAGCATCCA




GAAGTAGAGG
161
24R
unidentified

GTGTTGGGACCAG




ATCTTGCCTC




GACATACTG




GACAGCTTCTT
162
25F
OTU CL1A4,
N/A
GTTATGATTCTATC
29
25P


TAATGGAGG


single-copy,

TCAAGGAGGAGCG




ATCTGTTGGTC
163
25R
unidentified

TCCTGTGCTCTCCC




CTCCAAATC




ACTTCACTC




AATACAGGGC
164
26F
OTU CL1A5,
N/A
TCCAGAAGGTGAG
30
26P


TCTTTGAGTC


single-copy,

GCCGACGCAAAGA




AAGACGTACC
165
26R
unidentified

GTACTCACCGCTAG




ACCGATCCTG




GTGGACCCTC




TAACAATGCG
166
27F
OTU CL1A6,
N/A
ACAGTAAAGGACG
31
27P


GAGCCTTCGG


single-copy,

CAGGTCCGGACGC




AAGAACGTCC
167
27R
unidentified

CGACAAGTGAATG




GCCAATCCTG




CCGACGCCTTC




TATCTGGCGCT
168
28F
OTU CL1A8,
N/A
TCTCTAGAAGGATG
32
28P


TTTGCGTCG


multi-copy,

CCCAACCCGCACCG




CAACGTCTACC
169
28R
unidentified

GCACTCACAGGCC




CATCCCAAG




AAAAAGGCC




ACTCGGGAAC
170
29F
OTU LT2A20,
N/A
CGAAGACGGATGA
33
29P


CTAGTTCTAC


single-copy,

CTAACTATATACTG




TCTCTTACGGC
171
29R
unidentified

ACGTAAGCCAGCA




GCCGAAAAG




TATAAATAGC




AGGGCCAACG
172
30F
OTU LT1A5,
N/A
CACAATTAAGTGCA
34
30P


GTCTTGTTAT


multi-copy,

ACGGGATCCTCATG




TCGCAAATTGA
173
30R
unidentified

CAGAAAGACCCGA




CATCCACTG




GCCTGCCGT




CTCTCTCCGAG
174
31F
OTU LT1A8,
N/A
TATTAACGCACTAC
35
31P


TATCAATTG


multi-copy,

GCCCTGGAAGGAT




ACTTCCCTCAA
175
31R
unidentified

GCTTTCAGGCACTG




TCGCTAGTC




ATCGCGCAC




GCAGAGCTTC
176
32F
OTU LT1A9,
N/A
ACAGCTACCACCAC
36
32P


ACAGTTTTGC


single-copy,

CCTAAGGTGGGGA




AGACGTCTCCT
177
32R
unidentified

GGTCATCCCGATCA




GATCGCAAG




GAGATTCAA




N/A


OTU LT1A11,
N/A
TTCCAAGAGGATGC
37
33P





single-copy,

CTCGGTCTAACCAG







unidentified

ACACAAACCCGTAT









GGGTCGGT




N/A


OTU LT1A13,
N/A
AAGTGTTTTCCGGA
38
34P





single-copy,

AGATGGACGCAAA







unidentified

CACCCGGTACACA









GACCGCGAGT




ATACGTCCCGG
178
35F
OTU LT3A5,
N/A
TAACAGAAGGATG
39
35P


GACTGCAAT


multi-copy,

GTAGGGCGGCTCA




CGAAGGCGGA
179
35R
unidentified

GCGCACTCAACTTG




TAATTCTCGC




AGGGCAAAGT




ACAATGCAGG
180
36F
OTU LT3A6,
N/A
ACAGTACAAGTCTT
40
36P


GCCTTTACGG


multi-copy,

GCGACTAGACCGTC




GAATAACACT
181
36R
unidentified

CGGCCCAAAACCT




CACTGATCCC




GAAATCCAA




ATACAGGACT
182
37F
OTU LT3A7,
N/A
AAACAAGCCAGTA
41
37P


CATCCGAGGC


multi-copy,

CCGAAAGCATTCG




AAACGCCTGC
183
37R
unidentified

GACCGACTTCTGTC




AGATCGCTAG




CGCCGAGATC




N/A


OTU LT3A11,
N/A
GCAAGCGGATGAC
42
38P





single-copy,

TGTCAGAATCCCCG







unidentified

TCTAATGACTGAAG









ACCTGAACA




CTTTACAGGTC
184
39F
OTU LT3A13,
N/A
ACCTAATGCCACAC
43
39P


TGGCAATTG


single-copy,

AGATTCCACCCAAG




CATACAGTGCT
185
39R
unidentified

GATGGACGAGCTG




GACAGGGTC




CCCAAGTAC




CAGGGCCTTTT
186
40F
OTU LT1A1,
N/A
TTCAGAAAAGAAG
44
40P


CAGGTCTTG


multi-copy,

TGTCGTCCCGATCG




CACAAGGTGC
187
40R
unidentified

CACTACCGTAAGGC




CAACAGAGTC




GGCAAGCGT




AACAATGTCTG
188
41F
OTU LT1A38, 
N/A
AATGCCGCTGGTCA
45
41P


GCCCTACGG


multi-copy,

CACGGAAGAAAGA




GTAAACAACG
189
41R
unidentified

AGCCGACCAAACA




CCCACCGATC




GTGCGACTTG




GAGGGCAAGT
190
42F
All LT1A &
N/A
N/A




CTGGTGCCAG


LT3A OTUs
















TABLE 3







Prokaryotic probes and primer pairs used for multiplex PCR














Prokaryotic
SEQ


GenBank

SEQ



primer Sequence 
ID
PCR

Accession 
Probe Sequence
ID
Oligo


(5′-3′)
NO:
No.
Template
No.
(5′-3′)
NO:
No.

















CGAATGGATT
191
43F
Bacillus
AB116124
GTGACAGCCGAA
46
43P


AAGAGCTTGC


anthraces strain:

GCCGCCTTTCAAT




TGCCAGCTTAT
192
43R
S51

TTCGAACCATGC




TCAACTAGC




GGTTCAAAATGTT




GAACGTACCA
193
44F
Brucella
AF220149
CCAACGCGGGCC
47
44P


TTTGCTACGG


melitensis

GATCATTTGCCG




ACCGTCATTAT
194
44R


ATAAATCTTTCCC




CTTCACCGG




CCGAAGGGCACAT




ACGGGCTTCG
195
45F
Burkholderia
AY305760
AGGCCCGAAGGT
48
45P


GCCTGGTG


mallei strain

CCCCCGCTTTCAT




TCCGGGTATTA
196
45R
2000031063

CCTCAGATCGTAT




GCCAGAATG




GCGGTATTAATC




GCTTGCTAGAA
197
46F
Campylobacter
AF550630
TCCTACACCGAA
49
46P


GTGGATTAG


jejuni strain

AAACTTTCCCTAC




CGTCAGAATTC
198
46R
B99/206

TCAACTTGTGTTA




TTCCCTAAG




AGCAGGAGTATA




TTTAGTGGCGG
199
47F
Chlamydophila
AY334530
GGTCCGAAGATC
50
47P


AAGGGTTAG


psittaci clone

CCCTTCTTTAATA




ATCTCTCTTAT
200
47R
cvCps2

TGTTTTAGATGCC




TCCCAAGCG




TAAACATACCAC




AAGCTTCCTTC
201
48F
Clostridium
AY303799
CGCCGCGGGTCC
51
48P


GGGAAGTGG


botulinum strain

ATCTCAAAGCAA




GGTACCGTCAT
202
48R
AIP 355.02

TAAATCTTTGATA




TATCGTCC




AGAAAATCATGCG




ATAACCTGGG
203
49F
Coxiella burnetii
Y11502
TCATCTTATAGCA
52
49P


GAAACTCGGG


strain Nine Mile

CGAGGTCCGAAG




CCAAGGATATT
204
49R


ATCCCCCGCTTTG




ACCCTTGAG




CTCCAAAGAGAT




AGAAGCTTGCT
205
50F
Escherichia coli
AB035920
ACATCCGATGGC
53
50P


TCTTTGCTG


O157:H7

AAGAGGCCCGAA




TTCCTCCCCGC
206
50R


GGTCCCCCTCTTT




TGAAAGTAC




GGTCTTGCGACGT




CAATTCTGGGA
207
51F
Escherichia coli
NC 002655
CAATTCTGGGAA
54
51P


AGCGTGG


O157:H7

GCGTGGCATTAA




CGATGCATGAT
208
51R
EDL933

TACTGAATTGTCA




GATGACA




TCATCATGCATCG




N/A


Escherichia coli
NC 002655
GGTTGATGAAAA
55
52P





O157:H7

AGCATTTGGAGC







EDL933

CGCGAAATTTAC









CAGTGTCTTAAAAC




N/A


Escherichia coli
NC 002655
TGTCCGATTCAGC
56
53P





O157:H7

ACGGGTAAATAG







EDL933

TCGTATTGTTAGT









GGCCGAATTTAA




N/A


Escherichia coli
NC 002655
TTGCTGGAGAGT
57
54P





O157:H7

CCTTCTCGGGTAT







EDL933

CGATTGTCGAAG









ATAAACATATTTA




GTGGTGGATTA
209
55F
Escherichia coli
NC 002655
GTGGTGGATTAC
58
55P


CGCCATG


O157:H7

GCCATGACATGG




GCTATTACTCC
210
55R
EDL933

GAGGATTAACGG




CCCCCGT




GGGGGAGTAATAGC




TCTGGAGTATC
211
56F
Escherichia coli
NC 002655
TCTGGAGTATCA
59
56P


AAGCACT


O157:H7

AGCACTTATAAC




CCAGGAAGAG
212
56R
EDL933

CTAATAACACAA




GGTTTTGT




AACCCTCTTCCTGG




GCCCTGACGTA
213
57F
Escherichia coli
NC 002655
GCCCTGACGTAT
60
57P


TGGCGGG


O157:H7

GGCGGGTACGAA




GTAATGGTCAC
214
57R
EDL933

ATGAAGCCAGTG




CGTCACT




ACGGTGACCATTAC




N/A


Escherichia coli
NC 002655
ACTGGCGGGAAC
61
58P





O157:H7

ACATGAAAACGT







EDL933

AACCACGCTACC









AGTAGCCAGAAGAA




N/A


Escherichia coli
NC 002655
CCATTAAAACTA
62
59P





O157:H7

ATGCCTGTCATA







EDL933

ATGGAGGGGGAT









TCAGCGAAGTTATT




AAGACATCTTC
215
60F
Escherichia coli
NC 000913
AAGACATCTTCA
63
60P


ACCGTTC


K12

CCGTTCACGATAT




TCAGATTTCCC
216
60R


TTTGAAAGCACG




CTCGTGC




AGGGGAAATCTGA




N/A


Escherichia coli
NC 000913
CACCGTCGCTTTA
64
61P





K12

AAACGCGCCCGG









TGGGAGAATCGT









CGTTGTACATTTA




N/A


Escherichia coli
NC 000913
TTTCTGATCGCGT
65
62P





K12

TGCTGCGCTGATC









AAAGAAGTAAAC









AAAGCAGCTTAA




ATGGCATCCGT
217
63F
Escherichia coli
NC 000913
ATGGCATCCGTG
66
63P


GGTATCC


K12

GTATCCCGACTCT




CACTTCACCGT
218
63R


GCTGCTGTTCAA




TTTTGAA




AAACGGTGAAGTG




AACAGCTTGCT
219
64F
Shigella sonnei
X96964
N/A




GTTTCGCTG









TTCCTCCCCGC
220
64R







TGAAAGTAC









CAGGTCTTAGG
221
65F
Francisella
AY243028
AGGCTCATCCAT
67
65P


ATGCTGACG


tularensis strain

CTGCGACACGCC




AAGGCTATTA
222
65R
3523

GAAAGCCACCTT




ACCTTGAGGC




TAATCCACAGATAT




AGACTATCTAC
223
66F
Legionella
AJ496383
AATCCTTAAAAG
68
66P


TTCTGGTGC


pneumophila

TCGGTCGTAGTCC




ATACAGGTGCT
224
66R
serogroup 6

GGATTGGAGTCT




GCATGGCTG




GCAACTCGACTCC




GAGTAGCAAT
225
67F
Leptospira
Z12817
ATCTCCGAGCAA
69
67P


ACTCAGCGGC


interrogans

TAAATCTTTACCC




TACCATCATCA
226
67R


GAAAAATCTTAT




CATTGCTGC




GATCTCTCGGGAC




GAGCTTGCTCC
227
68F
Pseudomonas
AB117953
TCATCTGATAGC
70
68P


TGGATTCAG


aeruginosa

GTGAGGTCCGAA




GTAACGTCAA
228
68R
strain WatG

GATCCCCCACTTT




AACAGCAAGG




CTCCCTCAGGACG




AGTTAATTAGT
229
69F
Rickettsia
M21789
ATCTGACGCGGG
71
69P


GGCAGACGG


prowazekii

CCCATCCATCAG




ACTAAACCGC
230
69R


CGATAAATCTTTC




CTACGCACTC




CTCCGTAGAGAAT




AGCTTGCTGCT
231
70F
Salmonella
Z49264
CTTGGTGAGCCG
72
70P


TTGCTGACG


typhimurium

TTACCTCACCAAC




TAACCACAAC
232
70R


AAGCTAATCCCA




ACCTTCCTCC




TCTGGGCACATCT




GAACTTGTTCC
233
71F
Vibrio cholerae
X76337
ATCCCACCTGGG
73
71P


TTGGGTGGC


CECT 514 T

CATATCCGGTAG




TTAACCACCTT
234
71R


CGCAAGGCCCGA




CCTCCCTAC




AGGTCCCCTGCTTT




GTAGTTTACTA
235
72F
Yersinia pestis
AF366383
TCTGGGTTCATCC
74
72P


CTTTGCCGG




GATGGCGTGAGG




GAGCGTATTA
236
72R


CCCTAAGGTCCC




AACTCAACCC




CCACTTTGCTCTT




GCAAAGTGGC
237
73F
Arsenite-
AF406554
TCAAGACCCACG
75
73P


CCTCTGATTC


oxidizing

GCTATTAACCGT




CCATAAATGA
238
73R
bacterium

AAGCTTTTCCTCC




ACCCAACGGC


MLHE-1

CTGCTGAAAGTGC




ACCGGATACA
239
74F
Thiomicrospira
U46506
GCCGGTGCTTATT
76
74P


CCTTCATACC


sp. CVO

CATATGCTACCGT




CCGCAATGAC
240
74R


CATTTTCTTGACA




AAGCATCACG




TATAAAAGGAG




ACGCTCCGATT
241
75F
Desulfovibrio
Z24450
GTACCGTCAGAC
77
75P


TCACAGTTC


longreachii

CATGGCTGATTA




AAGTCCAGCA
242
75R


GCACCATGGCGG




GTATCAAGGG




TTCTTCCCTCCTGA




TGGGTTTACCT
243
76F
Bacillus
AF064705
CAAGGTACCGCC
78
76P


AACACTACG


arsenicoselenatis

CTATTTGAACGGT




TAGAGTCGAG
244
76R


ACTTGTTCTTCCC




TTACAGACCG




TAGCAACAGAGC




ATCATGAGTTC
245
77F
Uncultured
AF233412
TATTCATAAGGT
79
77P


ACATGTCCG


human fecal

ACATACAAAACA




CAATCGGAGTT
246
77R
bacterium HF74

CCACACGTGGCG




CTTCGTG




AACTTTATTCCCTT




ATCATGAGTTC
247
78F
Uncultured
AF233408
TATTCATAAAGT
80
78P


ACATGTCCG


human fecal

ACATGCAAACGG




CAATCGGAGTT
248
78R
bacterium HF8

GTATGCATACCC




CTTCGTG




GACTTTATTCCTTT




GCCGTCTACTC
249
79F
Uncultured
AF233413
TATTCATACGGTA
81
79P


TTGGCC


human fecal

CATACAAAAAGG




CCTGCCTCTAC
250
79R
bacterium HF10

CACACGTGCCTC




TGTACTC




ACTTTATTCCCGT




ACGGGTGCTTG
251
80F
Burkholderia
AB091761
AGGCCCGAAGGT
82
80P


CACCTGG


cepacia

CCCCCGCTTTCAT




CGACTGTATTA
252
80R


CCGTAGATCGTA




GAGCCAAGG




TGCGGTATTAATC




GTTGGCCGATG
253
81F
Burkholderia
AF148556
CGGTACCGTCAT
83
81P


GCTGATTAG


cepacia

CCCCCGACTGTAT




TCTGCCATACT
254
81R
genomovar III

TAGAGCCAAGGA




CTAGCCTGC




TTTCTTTCCGGAC




ACATGCAAGT
255
82F
OTU LT3A11,
N/A
AGCCGCAAGCTT
84
82P


CGTACGAGAG


multi-copy,

CTCTTTAGGCGG







identified as

AAATCCATTTCAC




ACACGTCATTT
256
82R
Unidentified

TCGAAAGCATATG




ATTCCTCCC


cyanobacterium









clone LD27






ACGAACCTTCG
257
83F
OTU LT1A53-
N/A
AGACGCGAGCTC
85
83P


GGTTAGTGG


3A9, multi-copy,

ATCCTCAGGCGA




TCAAGTACCGT
258
83R
identified as

AATTCATTTCACC




CAGATCTTC


Synechococcus

TCTCGGCATATGG







sp.






AAAGGCCTAC
259
84F
OTU LT1A53,
N/A
CCATCGCAGTAA
86
84P


CAAGGCTTCG


multi-copy,

TGGAGTTAAGCT




GGCACTCTCTC
260
84R
identified as

CCACGCTTTGAC




GTTTCCAAG


Synechococcus

GACAGACTTAAAAG







sp. LBG2






AAAGGCTTAC
261
85F
OTU LT3A9,
N/A
CCATCGCTGAAA
87
85P


CAAGGCATTG


multi-copy,

TGGAGTTGAGCT




CCTCCGGTTTC
262
85R
identified as

CCACGCTTTAAC




CCAGAG


Synechococcus

GACAGACTTGTAAA







sp. LBP1






GTAACAGGTCT
263
86F
OTU TL1A7,
N/A
CGCTCTAGTAGC
88
86P


TTCGGGATG


multi-copy,

ACAAGGCCCGAA







identified as

GGTCCCCTGCTTT




CAAGACTTTTC
264
86R
Uncultured beta

CATCCATAGATCT




GTTCCGTAC


proteobacterium









clone OS1L-16






TCTTTCACCGG
265
87F
OTU TL1A9,
N/A
TCAGTGACGCAA
89
87P


AGCTTGCTC


multi-copy,

AAGCGCCTTTCA







identified as

ACTTTCTTCCATG




CTCTCATCCTT
266
87R
Enterococcus

CGGAAAATAGTGT




GTTCTTCTC


gallinarum strain









LMG 13129






ACGGTCGCGT
267
88F
OTU LT1A31,
N/A
TCCTGAAGCGAT
90
88P


AACACGTAAG


multi-copy,

AAATCTTTAGAC







identified as

ACAAGTCGATGC




CGTCAAATTTC
268
88R
Uncultured

CGACTCGTGACCAC




TTCCCACTC


Crater Lake









bacterium









CL500-18






ATGAAGCTACT
269
89F
OTU CL1A15,
N/A
AGGTCATCTTCA
91
89P


TCGGTAGTG


single-copy,

ACCGAAAAACTT







identified as

TCCAGCCCCGAT




TGTAGGTACCG
270
89R
Uncultured

CATGCGATCAGAGC




TCACTTTCG


Crater Lake









bacterium CL0-









27






ATGAAGCACC
271
90F
OTU LT1A54,
N/A
TCATCTTCAACCG
92
90P


TTCGGGTGTG


multi-copy,

AAAAACTTTCCA







identified as

AACCCGCGGATG




TGCAGGTACC
272
90R
Uncultured

CCCGCAGGTTTCA




GTCACTTTCG


Crater Lake









bacterium









CL0-64






GATCTTTGATC
273
91F
OTU LT1A55,
N/A
CAGACGCGAGCT
93
91P


TTAGTGGCG


multi-copy,

CTTCCTAAGGTG







identified as

GATAAATCCTTTT




TCAAGTACCGT
274
91R
Uncultured

ACCTCTCGGCGTA




CAGAACTTC


freshwater









bacterium









LCK-26






AACGTACCCA
275
92F
OTU CL1A9,
N/A
GGCCGCTCCAGG
94
92P


AGAGTGGG


multi-copy,

AGCACGAGGTCT




AAGGATATTA
276
92R
identified as

TGCGATCCCCCG




GCCTCTACCG


Zoogloea

CTTTCATCCTTAGA







ramigera






TGAAGTTCCTT
277
93F
OTU LT1A27,
N/A
ATCTTTCATCAAA
95
93P


CGGGAATGG


multi-copy,

ATTTTTTCCCGGC







identified as

TCGGCGATGCCG




TTCTTCCCTAC
278
93R
Uncultured

CCAAGACGGAGT




TGAAAGAGG


actinomycete









clone SFD1-39






CTCATCAGCAA
279
94F
OTU LT1A46,
N/A
TCATGTAAGCCG
96
94P


TGGTGGGAG


multi-copy,

CTCCTCCGGCGG







identified as

AATCACACCTTTG




TCAACTCCGGA
280
94R
Uncultured

CTCCGCAGAGTTC




GGAGAACC


planctomycete









clone CY0ARA-









031E04






GGCAGCACGG
281
95F
OTU TL1A1,
N/A
TATTCTTAAAGCG
97
95P


TCTAGTTTAC


multi-copy,

CCAGGCCTTGCG




TCAAATCCTCC
282
95R
unidentified

GTCCCCAGCTTTT




TCCCCACTG




CTCCTCAGAGAT




GTCAGACTTCG
283
96F
OTU TL1A2,
N/A
CTCCATCAGCGC
98
96P


GTCTGA'TTG


multi-copy,

CCTTGCGAGCTTT




GGTACTTCTTC
284
96R
unidentified

CATCCCTTCTGCG




CCGAGCAAC




ACGAAGGGATCG




ATGTAGCAAT
285
97F
OTU TL1A6,
N/A
GGGGCACGGGCT
99
97P


ACAGGACAGC


single-copy,

CATCTTGGGGCG




CGTACATTTGA
286
97R
unidentified

GAATCACACCTTT




TTCCCTACG




GGTCCGCAAACAT




ATGAAGCTGG
287
98F
OTU CL1A2,
N/A
TCCTTGACCAAA
100
98P


AGCTTGCTCC


multi-copy,

ATTCTTTCCACGC




GCGAGCTCATC
288
98R
unidentified

CCGTGGGATGCC




CTTGACC




CCAAGGCGTCGTA




ACGGGAGCAA
289
99F
OTU CL1A10,
N/A
TGATATCGGCCG
101
99P


TCCTGGTG


multi-copy,

CTCCAATCGCGC




CCACTGTATTA
290
99R
unidentified

GAGGTCTTGCGA




GAGCAGACC




TCCCCCGCTTTCAT




ACGGCTTCGGC
291
100F
OTU LT2A3,
N/A
GCTCTTGCGAGCT
102
100P


CTAGTAAAG


multi-copy,

CCCTTTCCCGAAA




AGGGCTGTTCA
292
100R
unidentified

AACTCCTTACGA




CCCTAATGG




GTTCCGTCGCTC




TTAACTTAAGT
293
101F
OTU LT2A12,
N/A
AGACGCGAGCTT
103
101P


GGCGGACGG


multi-copy,

CTCTTTAGGCGG




GGTACACGTC
294
101R
unidentified

ATTACTCCATTTC




GTTTTATTCC




ACTCGGAAGCATA




TAACGCGGGG
295
102F
OTU LT2A16,
N/A
CGCTCCAATAGC
104
102P


CAACCTGG


multi-copy,

GAGAGGTCTTGC




GGGTATTAGCC
296
102R
unidentified

GATCCCCCCCTTT




CAGAGCG




CACCCGAAGGTCG




AGAGTTTGATC
297
103F1 
OTU LT1A15,
N/A
CGGTCCCAGCCTT
105
103P


CTGGCTCAG
298
103F2,
single-copy

TCCAGTAATCTCT




ACGGAGGTAG


unidentified

CTCTAGACTACTG




CAATACCTTA




CTTACGACGTA




GTGCTTCTTCT
299
103R







TCCGGTACC









TTCGGTTATGT
300
104F
OTU LT1A16,
N/A
TAATCCTAAAGC
106
104P


TGATGGCGA


multi-copy,

GCCAGGCCTTGC




TCGGGTAACGT
301
104R
unidentified

GGTCCCCAGCTTT




CAATAAACC




CCTCCTAAGAGAT




AACCCCGGTG
302
105F1
OTU LT1A18,
N/A
GTCCCCCGCTTTC
107
105P


GCGAGTGG
303
105F2
multi-copy,

ATCCATAGATCG




AACCCTGGTG


unidentified

TATGCGGTATTA




GCGAGTGG




GCGTAACTTTCGC




TTCTTACGGTA
304
105R







CCGTCATG









GAGCGATGAA
305
106F
OTU LT3A1,
N/A
CAATATTCGGTAT
108
106P


GTTTCTTCGG


single-copy,

TAGCACCGGTTTC




AGCCGGTGCTT
306
106R
unidentified

CCGGTGTTATCCC




CTTTTGTAG




AAAGTGGAGGG




GGTAACAGGT
307
107F
OTU LT3A2,
N/A
AGGTCTTGCGAT
109
107P


TAAGCTGACG


multi-copy,

CCCCCCCTTTCAC




CAGAGTATTA
308
107R
unidentified

CCGTAGGTCGTA




ATCCGAAGCG




TGCGGTATTAATC




GGTCTAGTTTA
309
108F
OTU LT3A7,
N/A
CAGCTTTTCTCCT
110
108P


CTAGATGGG


multi-copy,

CAGAGATTACGC




TTCTTCTGTGG
310
108R
unidentified

GGTATTAGCCTG




GTAACGTCC




AGTTTCCCCAGGT




CATCGGAACG
311
109F
OTU LT1A35,
N/A
CTTTCCCCCTCAG
111
109P


TACCTTATCG


multi-copy,

GGCGTATGCGGT




CGCAGTCTGTG
312
109R
unidentified

ATTAGCGCAACT




TTAGAGCTG




TTCGCTGCGTTAT




CGTGAGAATCT
313
110F
OTU LT1A55,
N/A
CAGACGCGAGCT
112
110P


ACCCTTAGG


multi-copy,

CTTCCTAAGGTG




GCTTGCATCCT
314
11OR
unidentified

GATAGATCCTTTT




CTGTATTAC




ACCTCTCGGCATA




TGTCGTCAGCT
315
111F
Control 1372
N/A
TGACGGGCGGTG
113
111P


CGTGTCG




TGTACAAGGCCCG




AAGGAGGTGA
316
111R







TCCAGCCG
















The PCR products in each reaction mixture (e.g., 16S rDNA and 18S rDNA) may be generated from dNTPs which contain a mixture of dATP, dGTP, dCTP, dTTP, and amino allyl-dUTP. The labeling step may employ dye incorporation resulting from a coupling reaction between a cyanine (Cy) and the PCR product. The pools of labeled PCR products may be hybridized with the array, whose immobilized oligonucleotides specify 50-mer sequences that are complementary to at least some of the individual rDNA sequences amplified from each sample. In some cases, the experiment may be replicated by performing a second “dye swap” experiment to minimize any false signals due to differential incorporation of the dye in the amplification products.
Also, probes that target taxa at different hierarchical levels may be included in the array in order to optimize detection of desired bioindicator organisms. For example, in addition to developing PCR primers that are specific to a single species, primers that are capable of detecting several species in a particular genus may be developed (e.g., Oldach, D. W., et al., 2000, Proc. Natl Acad. Sci. U.S.A. 97:4303-4308). The more generic primers may be used both as a confirmation that a particular genus is present in any sample that tested positive with the more specific primers, and as an indicator that potentially unknown or undetected members of the genus are also present.
The array may provide a qualitative result and/or a quantitative result. For example, as shown in FIG. 11, an array of prokaryotic rDNA sequences and/or an array of eukaryotic rDNA sequences may be probed using PCR amplified rDNA sequences amplified from genomic DNA from a water sample to provide qualitatively different patterns of hybridization. For example, DNA from a water sample may be amplified using prokaryotic specific primers and then labeled with a red dye (CY5) to provide a “red” prokaryotic probe (FIG. 11A-1) that recognizes prokaryotic sequences immobilized at designated positions on an array (FIG. 11B). Alternatively or additionally, DNA from a water sample may be amplified using eukaryotic specific primers and then labeled with a green dye (CY3) to provide a “green” eukaryotic probe (FIG. 11A-2) that recognizes eukaryotic sequences immobilized at designated positions on an array (FIG. 11B).
The array may also be used as a quantitative assessment tool, to monitor the change in various microbes over time, or to monitor the relative amounts of a microbe between two samples that vary in location (e.g., for two different bodies of water, or two locations in one body of water) or time of sampling (e.g., a single body of water sampled at two different seasons). Referring now to FIG. 12, an array may be probed with amplified DNA that corresponds to both 16S (prokaryotic) rDNA sequences and/or 18S (eukaryotic) rDNA sequences. To distinguish the two samples, amplification from the first sample may be labeled with a first dye (e.g., CY3, green), whereas the amplification from the second sample may be labeled with a second dye (e.g., CY5, red). As shown in FIG. 12A, the nucleic acids immobilized at a particular position (e.g., location or address) on the array, will bind to a complementary nucleic acid probe that is labeled either with the green dye (from the first sample), or the red dye (from the second sample). Upon hybridization, if hybridization is specific to probe from sample 1, a green spot will result; if hybridization is specific to probe from sample 2, a red spot will result; if hybridization occurs for probe molecules that are found in both samples, the color will vary dependent upon relative abundance of the amplified probe, and also the target, in each sample (FIGS. 12A and 12B). FIG. 12C shows the results for this type of experiment for two lake samples amplified by PCR to generate either 16S probes (top panel) or 18S probes (bottom panel). In an embodiment, there may be at least one position per array for a known sequence that serves as a control to allow for orientation of the array (e.g., green spots in lower right hand position of each grid in FIG. 12C).
As described herein, the array may also be used to determine how chemical additions to water (e.g. cadmium, atrazine, perchlorate) may change the microbial community, and/or to detect known water pathogens. For example, the microarray may include 16S rDNA sequences from several known pathogens. FIG. 13 shows results for such an experiment, where multiplex PCR amplification and direct labeling of cyanobacteria present in a water sample are detected using cyanobacterial sequences on the array (Panel 13D).
In one embodiment, an array of oligonucleotides that are isolated from known and unknown OTUs may be prepared. As used herein, known OTUs comprise sequences that are ≧97.5% identical to sequences that have been reported in public databases, whereas unknown OTUs comprise sequences that do not meet this criterion and are believed to represent as yet unknown organisms. FIG. 14 shows an array comprising 105 olignonucleotides isolated from predetermined known and unknown freshwater lake OTUs probed with amplified DNAs from two different lake samples, where multiplex PCR reactions of each sample were identical and products each reaction were either labeled with a red dye CY5 or a green dye CY3, allowing comparison of samples. Shown are results from a test of two lake samples used to hybridize first singly (top panels) (left panel: green probe, sample 1; right panel: red probe, sample 2) and then together (bottom panel) to the same array of 105 oligonucleotide probes.
Such taxon-specific arrays may be used to detect microbes that are known to be characteristic of a particular type of water system. For example, in one embodiment, the array may be formulated to detect microbes common to fresh water systems. Or, the array may be formulated to detect microbes common to marshlands or small tidal pools. Or, arrays having nucleic acids derived from estuary water samples may be used to analyze water from various estuaries. The development of an array that utilizes freshwater nucleotide sequences is described in the Examples, below.
EXAMPLES
Example 1
Materials and Methods
Sample Collection and DNA Extraction.
To develop probes for an array, three lakes were sampled: Lake Townsend (LT) (Greensboro, N.C.); City Lake (CL) (High Point, N.C.); and Toolik Lake (T L) (Alaska). Lake Townsend and City Lake are temperate mesotrophic and eutrophic municipal drinking water reservoirs, respectively. Toolik Lake is a highly oligotrophic, glacial lake located in the Arctic Long Term Ecological Research Site above the Arctic Circle in Alaska (Moon-van der Staay, S. Y., et al., 2001, Nature, 409:607-610).
Five samples of surface water were collected: (1) LT-1J—at an open water location in Lake Townsend (station 1), depth=8.3 m, on Jun. 14, 2000; (2) LT-2J—at a shallow, near shore location in Lake Townsend (station 2), depth=1.3 m, on Jun. 14, 2000; (3) LT-1M—at station 1 of Lake Townsend, on Mar. 28, 2001; (4) CL—at an artificially aerated location in City Lake near a subsurface water treatment system intake on May 22, 2001; and (5) TL—at a location near the main LTER sampling station in Toolik Lake on Aug. 11, 2000. Each sample ( ̃100 ml) was drawn through GF/C and GF/F glass fiber filters that were placed in cetyltrimethylammonium bromide (CTAB) buffer for storage at room temperature until later DNA extraction. Other lake samples, such as water samples from lakes that may be diagnostic of deformities found in members of the ecosystem may be used. For example, tests have been conducted using a group of North Dakota lakes that were paired according to geographical proximity. Each pair of lakes includes one lake that has been associated with a high level of frog deformities and one lake that has not been associated with any known deformities in frogs or any other organism. Samples from the lakes were used to isolate DNA for array analysis to ascertain microbial bioindicators associated with conditions leading to such deformities.
Genomic DNA was extracted from each water sample using a CTAB (cetyltrimethylammonium bromide) buffer DNA isolation technique (Rublee, P. A., et al., 1999, Va. J. Sci., 50:325-335). Briefly, the glass fiber filter was macerated in 2 ml CTAB in a 15 ml polypropylene conical tube using a sterile wooden applicator stick. After heating for 1 hr at 65° C., the mixture was extracted with 2 ml 24:1 (v/v) chloroform-isoamyl alcohol, and the DNA isolated from the aqueous portion by precipitation with 0.7 volumes 100% 2-propanol. The precipitate was pelleted, air-dried, and the DNA rehydrated in 25 μl TE buffer (pH 7.4) and stored at −20° C.
PCR Amplification of Genomic DNA from Water Samples for Cloning rDNAs.
SSU rDNA was amplified by PCR using prokaryotic-specific and eukaryotic-specific forward and reverse primers in 50 μl reactions (Table 1). Using the appropriate primer pairs, separate reactions were prepared for 16S rDNA and 18S rDNA. The amplification reactions consisted of: 5 μl 10×PCR Buffer; 5 μl PROMEGA Promoga 25 mM MgCl2; 5 μl 100 mM BSA; 2.5 μl 16 mM dNTP stock (4 mM each of dATP, dCTP, dGTP and dTTP); 1 μl each of 10 μM forward and reverse primers; 1 U Taq DNA Polymerase; 30.2 μl sterile deionized H2O; and 1 μl genomic DNA. An MJ RESEARCH PTC-100 Programmable Thermal Controller was used to amplify samples under the following conditions: 2 min initial denaturation at 94° C.; 30 cycles of 1 min denaturation at 94° C.; 1 min annealing at 56° C. for 16S primers or 58° C. for 18S primers; and 2 min extension at 72° C.; 5 min final extension at 72° C. PCR products were verified by gel electrophoresis.
Cloning and Sequencing of Amplified PCR Products.
Purified PCR products were subcloned in plasmid vectors using a cloning kit (INVITROGEN TOPO TA CLONING KIT) according to the manufacturer's protocol. Ligation reaction mixtures were then used to transform TOP10 Chemically Competent E. coli cells and recombinant plasmids were identified by growth of bacterial colonies on LB agar plates containing 50 μg/ml ampicillin. Individual colonies from each plating were inoculated into LB liquid medium containing 50 μg/ml ampicillin and grown overnight with antibiotic selection. Inserts were purified from cultures using a miniprep kit (QIAGEN QIAPREP SPIN MINIPREP KIT) according to the manufacturer's protocol. After removal of the insert, gel electrophoresis was used to verify the presence of a DNA fragment corresponding in size to 16S rDNA or 18S rDNA.
Fifty verified clones from each library were sequenced using a LI-COR GLOBAL EDITION IR2 SYSTEM for automated DNA sequencing. Sequencing reactions were prepared using an EPICENTRE TECHNOLOGIES SEQUITHERM EXCELTM II DNA Sequencing Kit-LC (for 25-41 cm gels) according to the Cycle Sequencing Protocol provided. Sequencing reactions included: 3.5× SEQUITHERM EXCEL II Sequencing Buffer; fluorescent (IR)-labeled M13-20 forward and reverse primers; purified cloned 16S rDNA or 18S rDNA; sterile deionized H2O; SEQUITHERM EXCEL II DNA Polymerase; and SEQUITHERM EXCEL II-LC Termination Mixes A, C, G and T (each containing dATP, dCTP, dTTP, 7-deaza-dGTP, and one ddNTP). Using an MJ RESEARCH PTC-100 Programmable Thermal Controller, reactions were amplified by PCR using the following conditions: 4.5 min initial denaturation at 95° C., followed by 30 cycles of 30 sec denaturation at 95° C., 30 sec annealing at 51° C., and 1 min extension at 70° C. After amplification, Stop/Loading Buffer was added to reaction products, which were denatured for 5 min at 95° C. and loaded into a 41 cm polyacrylamide gel. During electrophoresis of reaction products, dual 700 and 800 nm detection channels were used for simultaneous bidirectional sequencing of each clone and sequence read lengths were at least 550 bp in each direction.
Sequence Alignments and Community Analyses.
It is generally accepted in the art that 1000 nucleotides of sequence information is sufficient for even a detailed phylogenetic analysis (Oldach, D. W., et al., 2000, Proc. Natl Acad. Sci., U.S.A. 97:4303-4308). Thus, partial sequences were obtained for each clone and the first 500 nucleotides from both 5′ and 3′ ends. The use of 1000 nucleotides for phylogenetic ordering of the sequences was subsequently verified by generating complete sequences for 18S rDNA clones, with no improvement in the data (results not shown). After checking each sequence for the presence of chimeric properties using the program CHIMERA_CHECK (version 2.7; Ribosomal Database Project II, Center for Microbial Ecology, Michigan State University, available on-line), one sequence was excluded. The remaining sequences were submitted to the National Center for Biotechnology Information website for BLAST analysis (Altschul, S. F., et al., 1990, J Mol. Biol., 215:403-410).
Sequence alignments and analyses were performed using the BIOEDIT SEQUENCE ALIGNMENT EDITOR AND ANALYSIS SOFTWARE (version 5.0.9; Department of Microbiology, North Carolina State University, available on-line), which includes CLUSTAL W as an accessory application for multiple alignments. Libraries were compared in pairwise fashion by combining and aligning two libraries at a time (100 sequences of 16S rDNA or 18S rDNA). Libraries were also merged into one group for alignment and comparison (249 16S rDNA sequences or 250 18S rDNA sequences).
Taxonomic classifications were based on identity matrices generated using an analysis tool incorporated into the BIOEDIT sequence editor. Sequences having identity scores of 0.975 or greater were considered to be sufficiently similar to group them into the same operational taxonomic unit (OTU). After grouping clones into OTUs, several diversity indices were calculated for each library. These included: (1) species richness, or total number of OTUs; (2) Simpson's dominance index, used to describe the distribution of clones among OTUs, or evenness; and (3) the Shannon-Wiener index, which serves as a statistical measure of the probability of correctly guessing the OTU identity of a randomly selected clone (Colinvaux, P. 1993. Ecology 2. John Wiley & Sons, Inc., New York, U.S.A). In addition, Sorensen coefficients (Lemke, M. J., et al., 1997, Microb. Ecol., 34:224-231) were calculated to measure the similarity in species composition between two communities, or the proportion of OTUs shared between two libraries.
Also total species richness (S) can be estimated using four methods based on the distribution of OTUs within a library. These include: Scov, an estimate based on “coverage” (Finlay, B. J., 2002, Science, 296:1061-1063; Giovannoni, S. J., et al., 1990, Nature, 345:60-63); Smax, an estimate based on rarefaction analysis (Haldeman, D. L., et al, 1994, Appl. Environ. Microbiol., 60:2697-2703; Methe, B. A., and J. P. Zehr, 1999, Hydrobiologia, 401:77-96), which can be performed using the program ANALYTIC RAREFACTION (version 1.3; Stratigraphy Lab, University of Georgia, available on-line); and SACE and SChao1, two estimates that can be evaluated using a form processor and spreadsheet available through a web-based interface (Kemp and Aller, 2004, Limnol., Oceanogr. Methods, 2:114-125).
Phylogenetic analyses were conducted to assess molecular evolutionary relationships using MEGA software (version 2.1; Molecular Evolutionary Genetics Analysis, available on-line). All phylogenetic analyses are sensitive to alignment methods, assumptions regarding mutational rates, and the types and amount of sequence data used (Troesch, A., et al., 1999, J. Clin. Microbiol., 37:49-55.). Trees were constructed using the Unweighted Pair-Group Method with Arithmetic Mean (UPGMA) and distances were estimated according to the Kimura 2-parameter model for nucleotide exchange with a transition/transversion ratio of 2.0 (Hurlbert, S. H., 1971, Ecology 52:577-586).
Real-Time Quantitative PCR.
Real-time Quantitative PCR (Q-PCR) experiments were designed to analyze the relative abundance of two 16S rDNA OTUs and one 18S rDNA OTU in three different samples using a CEPHEID SMART CYCLER SYSTEM Cycler system. The presence and accumulation of fluorescence bound to each target OTU was measured directly and compared among LT-1J, LT-1M and CL. Individual 25 μl reactions included: 2.5 μl TAKARA 10×EX TAQ Taq Buffer; 1.25 μl TAKARA dNTP Mixture (2.5 mM each); 1.25 μl SYBR® Green I nucleic acid gel stain (10×); 0.25 μl TAKARA EX TAQTM; 1 μl OTU-specific forward and reverse primers (10 μM each); 16.75 μl sterile deionized H2O; and 1 μl experimental template (genomic DNA sample—0.025 μg/μl), positive control (mixed clone standard—25 pg/μl each), or negative control (sterile deionized H2O). The mixed clone standard was prepared by combining three clones representing three experimental samples used in the experiment (i.e., genomic DNA samples from three different OTUs). Relative abundance estimates were calculated using a 1:10 dilution series of the mixed clone standard to determine cycle number differences between 25 pg, 2.5 pg, 0.25 pg, and 0.025 pg template concentrations.
Multiplex PCR of Probes for Array.
To generate the target sequences used for hybridization to the array, a multiplex PCR amplification using at least 45 primer pairs developed from an analysis of individual OTUs, may be performed. The sequences of the eukaryotic primers and associated 50-mer probes are shown in Table 2. The sequences of the prokaryotic primers and associated 50-mer probes are shown in Table 3.
The conditions for multiplex PCR are as follows. Multiplexed PCR reactions containing  ̃250 ng genomic DNA are prepared in 0.5 ml thin-walled microcentrifuge tubes. The final reaction volume is 50 μl and contains a 200 nM final concentration of each primer, 5 μl 10× buffer, 5 μl BSA, 5 μl dNTPs, 1.25 U Taq, and sd H2O (remaining volume). Reactions are placed in a programmable thermal controller and DNA amplification by PCR is carried out under the following conditions: initial denaturation at 94° C. for 2 minutes; 30 cycles of denaturation at 94° C. for 1 minute, annealing at 1 to 3 degrees below lowest primer Tm, extension at 72° C. for 1 minute; final extension at 72° C. for 1 minute; and storage at 4° C. of reaction product until use. The dNTP mixture is prepared by adding 16.6 μl sd H2O to 2 μl 50× dNTP stock solution for an 8.33-fold dilution, where 50× dNTP stock solution is 10 μl each 100 mM dATP, dGTP, dCTP; 8 μl 100 mM amino allyl-dUTP; and 2 μl 100 mM dTTP.
The PCR products may, in some cases, be labeled using fluorescent dyes. The PCR product is transferred to a 1.5 ml microcentrifuge tube and 5 μl 3 M sodium acetate and 500 μl 100% ethanol are added. The contents are thoroughly mixed and stored overnight at −70° C. The samples are removed from −70° C. storage and spun in a microcentrifuge at 14,000 rpm for 20 minutes. After pouring off the supernatant, 500 μl 70% ethanol is added to wash the DNA pellet and this mixture is microcentrifuged at 14,000 rpm for 10 minutes. The supernatant is again poured off, the tube is allowed to air dry to remove all ethanol, and the pellet is then resuspended in 15 μl nuclease-free H2O. The dyes are removed from −20° C. storage and resuspended in 15 μl 0.1 M sodium bicarbonate, pH 9.0. The dye and DNA resuspensions are combined, mixed well, and allowed to incubate for 1 hr at room temperature in the dark. To quench any unbound dye after the dye coupling reaction, 15 μl 4 M hydroxylamine are added to each sample and these are incubated for 15 minutes at room temperature in the dark. Labeled samples are then purified using a PCR purification kit according to the manufacturer's protocol.
Spotting of Oligonucleotides on the Array.
To immobilize nucleic acids on the array the following protocol was used. Each 50-mer oligonucleotide to be used as a probe sequence (i.e., sequences corresponding to SEQ ID NOS: 5-113 or the complement of these sequences) on the array is diluted 1:10 with 3×SSC/0.1% sarkosyl in a 96-well microplate for a final oligonucleotide concentration of  ̃250 ng/μl. Epoxy-coated slides are secured in slide positions of arrayer for printing. After the oligonucleotides are printed, the slides are UV cross-linked at 60 mJoules, baked at 80° C. in an oven for 2 hours, and stored at room temperature. The 3×SSC is prepared using a 20×SSC concentrate containing 3 M NaCl and 0.3 M sodium citrate, pH 7.0.
Hybridization of DNA Sample to Array.
After purification, the CY3 and CY5-labeled sample eluates may be combined and lyophilized until almost dry, leaving approximately 5-10 μl behind. The sample may be resuspended using 80 μl Roche DIG EASY HYB hybridization buffer and a clean lifterslip is placed on the microarray being used. The sample is heated at 95° C. for 2 minutes, cooled on ice for 1 minute, spun down to collect any condensation, and pipetted under the lifterslip. Next, the microarray is sealed within a hybridization cassette using the cassette lid and placed into a 45-55° C. water bath overnight. The next morning, three wash solutions are heated to 37° C., the hybridization cassette is removed from the water bath, and the microarray is removed from the cassette. The microarray with lifterslip is gently dipped into a staining dish containing wash buffer #1 (1×SSC, 0.1% SDS), to release the lifterslip. The microarray is then placed in a staining dish cassette and gently washed in wash buffer #1 for 5 minutes. Using the same technique, the microarray is next washed in wash buffer #2 (1×SSC), for 5 minutes. Finally, the microarray is washed in wash buffer #3 (0.05×SSC), by gently dipping it 5-10 times. The microarray is removed from the staining dish cassette and tapped on edge against the benchtop to remove all solution droplets. Once dry, the microarray is scanned.
Example 2
Grouping rDNAs into Operational Taxonomic Units
Analysis of Clones.
Approximately 50 prokaryotic rDNA and 50 eukaryotic rDNA clones for each of the five lake samples (500 rDNA sequences) were sequenced through a 1700 bp segment of the eukaryotic 18S rDNA, or a 1540 bp segment of the prokaryotic 16S rDNA, to provide for phylogenetic classification of known and novel species (Pace et al., 1986, Adv. Microb. Ecol., 9:1-55; Sogin and Gunderson, 1987, Annals. NY Acad. Sci., 503:125-139). Based on the rDNA sequencing alignments, a level of 97.5% sequence identity was the criterion by which rDNAs were placed in the same operational taxonomic unit (OTU). Because multiple small subunit rDNA copies may reside within a species genome (Farrelly et al., 1995, Appl. Environ. Microbiol., 61:2798-2801), a 97.5% level of sequence identity allows for the possibility that a different sequence in the same species was recovered. A software program (CHIMERA-CHECK; Kopzcysnski et al., 1994, Appl. Environ. Microbiol., 60:746-748; Wang and Wang, 1995, Appl. Environ. Microbiol., 63:4645-4650; Qui et al, 2001, App. Environ. Microbiol., 58:2717-2722) was also employed to reduce the possibility of misidentifying a chimeric rDNA as an unique clone.
For each sample, libraries of SSU rDNA clones were produced, individual clones were sampled, sequences for each clone were generated, and standard diversity statistics were computed (Table 4). Based on a comparative analysis of all prokaryotic (16S) rDNA sequences, it was determined that 49 OTUs contained multiple sequences and that 62 OTUs were unique, each containing a single sequence. An analysis of all eukaryotic (18S) sequences resulted in 42 OTUs containing multiple sequences and 67 unique OTUs.







TABLE 4







Comparison of prokaryotic and eukaryotic diversity













LT-1J
LT-2J
LT-1M
CL
TL

















rDNA library
16S
18S
16S
18S
16S
18S
16S
18S
16S
18S




















Number of clones
50
50
50
50
50
50
49
50
50
50


Number of OTUs
33
31
31
32
26
34
28
28
23
12


Evenness
0.039
0.049
0.050
0.053
0.089
0.043
0.079
0.102
0.078
0.358


Shannon-Wiener
3.38
3.24
3.24
3.24
2.84
3.35
3.00
2.90
2.86
1.62


index















LT-1J: Lake Townsend, station 1, June;


LT-2J: Lake Townsend, station 2, June;


LT-1M: Lake Townsend, station 1, March;


CL: City Lake;


TL: Toolik Lake.






Species Diversity Measures.
Prokaryotic and eukaryotic species richness, evenness, and the Shannon-Wiener index differed among lakes. In general, Lake Townsend, NC, contained more species and showed the most even distribution of species; consequently, its Shannon-Wiener index values were the highest. In contrast, Toolik Lake, AK, had the lowest richness estimates, especially for eukaryotes, indicating that species diversity was much lower here than in the temperate lakes and that a few successful competitors dominated the arctic community.
As a first indication of diversity, various statistical measurements of the recovered sequences were made to determine the species coverage, species evenness (Simpson's Index of Dominance; Colinvaux, 1993, Ecology 2, John Wiley & Sons, Inc. New York, N.Y.), species richness (the number of recovered species in a sample), species diversity (Shannon-Wiener index; Nubel et al., 1999, Appl. Environ. Microbiol., 65:422-430) and the estimated proportion of shared OTUs between samples (Sorenson similarity coefficient; Lincoln et al, 1998, A Dictionary of Ecology, Evolution, and Systematics, Cambridge University Press, New York, N.Y.; McCaig et al., 1999, Appl. Environ. Microbiol., 65:1721-1730). Coverage estimates of the percentage of OTUs recovered from a source were based on the relative abundance of the clones already obtained, and indicated that 48 to 76% of the prokaryotic rDNAs, and between 48 and 90% of the eukaryotic rDNAs, had been recovered from the samples. The highest coverage (i.e., 90%) was for Toolik Lake; apparently caused by the high level of recovery of a single rDNA. Not unexpectedly, the species evenness and richness was about the same for all the North Carolina lake samples, but the distribution of recovered species was much more skewed and lower in Toolik Lake, Alaska. To generate a nucleic acid array for monitoring water, however, the purpose of the census is not necessarily to identify all the microbial species that exist in these samples, but rather to survey water sources for relatively common microbes whose appearance and abundance can be monitored on a microarray platform.
Rank-abundance curves (FIGS. 2 and 3) for most samples showed that a few taxa were abundant and that many taxa were represented by a single clone. It is highly likely that the samples also contain several other clones at low frequencies. In Toolik Lake, fewer species were detected and these were more abundant relative to the other lakes tested, implying that Toolik Lale contained a smaller number of species. This was supported by the estimates of total taxonomic diversity using the four methods described above (Table 5).







TABLE 5







Estimates of species richness (S) for each prokaryotic and eukaryotic community













LT-1J
LT-2J
LT-IM
CL
TL

















rDNA library
16S
18S
16S
18S
16S
18S
16S
18S
16S
18S




















Number of OTUs
33
31
31
32
26
34
28
28
23
12


Scov
57
56
54
62
44
71
46
47
29
14


smax
93
72
73
74
40
93
53
47
40
12


SAC E
61
80
77
110
110
106
67
65
38
17


SChaol
54
77
63
88
91
99
54
60
28
14





LT-1J: Lake Townsend, station 1, June;


LT-2J Lake Townsend, station 2, June;


LT-1M: Lake Townsend, station 1, March;


CL: City Lake;


TL: Toolik Lake.






Sequence Identifications and Library Comparisons.
Clone sequences were submitted for BLAST analysis to assess phylogenetic affiliations with reported sequences in the GenBank database. Sequence alignments having ≧97.5% identity were used to propose OTU identifications and determine the proportion of known OTUs for each library (Table 6). The Lake Townsend March sample contained the lowest average proportion of known OTUs (24.8%), while Toolik Lake had the highest (43.0%). Identifications for clones within the same OTU were consistent, suggesting that a 97.5% identity threshold grouped individuals at the species level.







TABLE 6







Summary of prokaryotic and eukaryotic OTUs













LT-1J
LT-2J
LT-1M
CL
TL

















rDNA library
16S
18S
16S
18S
16S
18S
16S
18S
16S
18S




















No. known clones
21
17
16
21
21
19
31
20
25
32


Proportion known
12/33 
8/31
10/31
8/32
6/26
9/34
13/28
6/28
14/23
3/12


OTUs (% )
(36.4)
(25.8)
(32.3)
(25.0)
(23.1)
(26.5)
(46.4)
(21.4)
(60.9)
(25.0)





LT-1J: Lake Townsend, station 1, June;


LT-2J: Lake Townsend, station 2, June;


LT-1M: Lake Townsend, station 1, March;


CL: City Lake;


TL: Toolik Lake.


Number of known OTUs = number of OTUs with clones having ≧97.5 % sequence similarity to GenBank entries. Known clones refer to clones whose sequences correspond to known microbial species or unidentified species in the GenBank database.






Samples having similar estimates of species diversity were distinguished by differences in community composition. For instance, 8 eukaryotic OTUs were identified in each Lake Townsend sample, but the species composition of this group varied between samples. Comparing only the OTUs with multiple sequences, the following observations were made: LT-1J species included Chilomonas paramecium, Cryptomonas ovata, and Geminigera cryophila; LT-2J species included Brachionus plicatilis, Cryptomonas ovata, Didinium nasutum, and Dileptus sp., and the LT-1M species included Cryptomonas ovata and Tabularia tabulata. A comparison of the unique OTUs distinguished these samples even more.
Based on sequence alignments and comparisons that included all OTUs, phylogenetic trees were generated according to the UPGMA method to show the overall distribution of OTUs among the five samples. The prokaryote tree in FIG. 4 was constructed using 111 different 16S rDNA OTUs, including 40 that are known rDNAs (about 36%). The eukaryote tree in FIG. 5 represents 109 18S rDNA OTUs and includes 22 known rDNA sequences (about 20%).







TABLE 7







Sorensen coefficients for prokaryotic and eukaryotic sample comparisons













LT-IJ
LT-2J
LT-1M
CL
TL

















rDNA library
16S
18S
16S
18S
16S
18S
16S
18S
16S
18S




















LT-1J
1
1
0.344
0.159 
0.169
0.215
0.230 
0.068
0.071 
0.093





(11)
(5)
(5)
(7)
(7)
(2)
(2)
(2)


LT-2J


1
1
0.070 
0.061
0.169
0.133
0
0.091








(2)
(2)
(5)
(4)
(2)


LT-1M




1
1
0.074 
0.161
0.122
0.174









(2)
(5)
(3)
(4)


CL






1
1
0.039
0.200











(1)
(4)


TL








1
1





Coefficientswere calculated as follows: S = 2 × C/(A + B) where A and B represent the numbers of OTUs in libraries A and B, respectively, and C represents the number of OTUs shared by A and B (34, 40).


( ) indicate the number of OTUs that were shared by the paired libraries.


LT-1J: Lake Townsend, station 1, June;


LT-2J: Lake Townsend, station 2, June;


LT-1M: Lake Townsend, station 1, March;


CL: City Lake;


TL: Toolik Lake.






To determine which OTUs, if any, appeared in more than one library, the sequences from each library were compared to those in every other library in pairwise library comparisons and a similarity coefficient was calculated for each pairing (Table 7). Although no prokaryotic sequences were shared between LT-2J and TL, there was some overlap between every pair of samples and the degree of overlap varied considerably. In some comparisons, roughly equal proportions of prokaryotic and eukaryotic OTUs were shared, but other comparisons revealed different patterns.
Venn diagrams depict sample comparisons at different spatial and temporal scales (FIG. 6). In the fine-scale spatial comparison of LT-1J and LT-2J, each shared OTU contained nearly equal numbers of sequences from both samples, except for two sequences that occurred four times as often in LT-2J. One of these, a 16S rDNA OTU, was not identified, while the other 18S rDNA OTU aligned with Geminigera cryophila, and was also found in Toolik Lake (three copies). Such unequal occurrences of an OTU between samples may signify a detectable difference in the relative abundance of this particular microbial population between samples. OTUs that consistently vary in frequency among samples are potential bioindicators. For instance, one new bacterial species and the Geminigera cryophila OTU appear to be more abundant in temperate lakes, especially pelagic waters.
Thus, it was found that for the five lake samples analyzed, 26 different eukaryotic OTUs were represented by multiple copies, including 11 that are associated with known species. Another 79 eukaryotic OTUs were obtained as single copy clones and almost all of these represent unidentified species (Marshall, 2002, Masters Thesis, University of North Carolina at Greensboro). Similarly, 45 different prokaryotic OTUs were found in multiple copies among the collection of samples, of which 10 are associated with a known species, and another 19 resemble reported sequences for as yet unidentified species. Another 92 single copy rDNA sequences, most from unidentified prokaryotes, were recovered from the samples (Amos, 2002, Masters Thesis, University of North Carolina at Greensboro). Both known and unidentified rDNA sequences may be used as probes printed on the assay matrix of the present invention.
The ability to assess environmental parameters of water quality may require a sufficient number of potential bioindicator species, but may also require sequences having sufficient similarity across samples to allow for some general application. As noted in Table 8, a diversity of microbial species may be readily retrievable from a single body of water for even an oligotrophic source such as Toolik Lake, Alaska. While every sample produced several unique OTUs, all of the lakes produced multiply represented OTUs, and the most common OTU in each sample accounted for 10% or more of all the rDNAs analyzed in each of the samples.







TABLE 8







Relative abundance of eukaryotic and prokaryotic OTUs












Most abundant
2X 
1X
Total



OTU
OTUs
OTUs
OTUs
















Eukary. 
Prokary.
Eukary.
Prokary.
Eukary.
Prokary.
Eukary.
Prokary.


















LT-1J
10%
 8%
9
10
23
26
32
36


LT-2J
14%
10%
9
8
22
26
31
34


LT-1M
10%
14%
8
7
26
23
34
30


CL
14%
22%
10
9
21
22
31
31


TL
58%
20%
7
12
5
12
12
24





LT-1J; Townsend, NC; June, Station 1;


LT-2J; Townsend, NC; June, Station 2;


LT-1M, Townsend, NC; March, Station 1;


CL, City Lake, NC May;


TL, Toolik Lake, AK; August.


2X represents OTUs with at least 2 members;


1X represents OTUs with only one member.






Table 9 shows the pattern of shared and unshared OTUs among the five freshwater lake samples. Unshared OTUs refer to rDNA sequences that were recovered and characterized only in the designated sample either as a single copy, referred to as a unique OTU, or in multiple copies. It can be seen that the distribution of some OTUs is broad, while for others it is more localized (Table 9), suggesting that many microbial species exist across a range of watersheds and that a general purpose DNA microarray, that may be used for multiple watersheds, may be developed. An example analysis of specific OTUs is shown in Table 10.
A preliminary analysis of rDNA sequences from paired North Dakota lake samples (where one lake sample that exhibits substantial deformities in the frog population and one lake sample does not) acquired from the Fargo, N. Dak. USDA station indicates that some of the OTUs for unknown species are shared with sequences found in North Carolina lakes. Moreover, preliminary real-time PCR experiments suggest that at least some microbes exist an endemic level in almost all freshwater lakes, suggesting that that relative abundance for these endemic microbes is primarily dictated by local water conditions.







TABLE 9







Shared and unshared OTUs among the five freshwater lake samples













A
B
C
D
E


















Euk.
Prok. 
Euk.
Prok.
Euk. 
Prok. 
Euk.
Prok.
Euky.
Prok.




















Unshared
18
22
19
19
19
19
18
20
5
12


OTUs












OTUs in 2
2
5
1
4
3
8
2
4
2
19


samples only












Toolik only 
0
0
0
0
0
0
0
0
—
—


Townsend
5
6
3
6
5
2
—
—
—
—


only












Townsend or 
2
2
1
3
2
1
5
6
—
—


City












All lakes*
4
0
3
0
5
0
5
0
5
0





*All lakes does not necessarily mean all samples.


A: Townsend, NC, June, Station 1;


B: Townsend, NC, June, Station 2;


C: Townsend, NC, March, Station 1;


D: City Lake, NC, May;


E: Toolik Lake, AK, August


Euk = Eukaryotic;


Prok = Prokaryotic













TABLE 10







Relative abundance of five eukaryotic rDNA 


species found in all three sampled lakes















A
B
C
D
E







Cryptomonas
30%
12%
20%
30%
 8%



ovata








Unidentified 
 0%
 0%
10%
 6%
58%



18s rDNA-1








Ochromonas
12%
 6%
 6%
 8%
 4%



tuberculata








Oxytricha
 2%
10%
 2%
 8%
10%



longa








Unidentified
10%
 0%
 4%
 2%
10%



18s rDNA-2







A: Townsend, NC, June, Station 1;



B: Townsend, NC, June, Station 2;



C: Townsend, NC, March, Station 1;



D: City Lake, NC, May,



E: Toolik Lake, AK, August






Library Screening Vs. Real-Time Q-PCR.
Several OTUs may be found at quantitatively different levels in different ecosystems. Three OTUs that appeared to be recovered differentially from one water sample were used in fluorescence detection real-time PCR experiments to determine if they were also present in other water samples (FIG. 7). It was found that each of the test OTUs was in fact present in all of the samples investigated. Panels (7A) and (7C) show the detection of two OTUs that appeared in LT-1M clone libraries at frequencies of 10 and four copies (out of 50), respectively. The OTU in panel (7B) was originally recovered from a City Lake library (11 copies of 50).
The relative abundance of each OTU was compared and estimated across the same three samples based on a dilution series of a known standard (data not shown). According to cycle threshold differences between growth curves in FIG. 7A, the amount of product in the LT-1M sample was estimated to be 34 times greater than the amount of this product in LT-1J and 13 times greater than the amount in CL. For the experiment shown in FIG. 7B, it was found that the amount of product in CL was about 219 times greater than that found in LT-1J and 41× greater than that found in LT-1M. For the experiment shown in FIG. 7C, it was found that the amount of product in LT-1M was about 29 times more abundant than in LT-1J and 55 times more abundant than in CL.
Real-time PCR assays also allowed for an estimation of the sensitivity of rDNA amplification for detecting community members. Based on four completed E. coli genomes from GenBank entries AE014075 (Venter, J. C., et al., 2004, Science, 304:66-74), U00096 (Blattner, F. R., et al., 1997, Science, 277:1453-1474), BA000007 (Lincoln, R., G. Boxshall, and P. Clark, 1998, A Dictionary of Ecology, Evolution and Systematics. Cambridge University Press, New York, N.Y.), and AE005174 (Pace, N. R., et al., 1986, Adv. Microb. Ecol., 9:1-55), it was estimated that 16S rDNA makes up about 0.206% of the E. coli genome, and therefore, about 52 pg of 16S rDNA should be present in 25 ng of genomic DNA material. Experiments indicated that Q-PCR detected a specific rDNA signal from as little as 3.6×10−3 pg of genomic DNA, based on a comparison with the Q-PCR signal evoked by individual rDNA clones, indicating that clones occurring at a frequency as low as 6.9×10−5 should be detectable by Q-PCR, and that a sampling of 14.5×103 clones would be required for a mean recovery of one target clone. Assuming a Poisson distribution of clones in a library, it was estimated that to ensure the recovery of any one clone at a probability of greater than 99%, a library screening method would require 66.7×103 clones.
Generally, the results indicated that the Toolik Lake microbial community differs more from the North Carolina lakes than the North Carolina lake communities differ from each other. The three Lake Townsend samples also showed variation as the samples differed with respect to the location and season of sampling. While the March and June collections at the same Lake Townsend location shared several OTUs with the other Lake Townsend and City lake samples, several multiple-copy OTUs were only found in the March collection, indicating that some microbial species thrive in the relatively cold waters of early Spring. Also, the two Lake Townsend samples collected on the same day showed the highest level of overall similarity. The library sampling method was able to detect similarities between samples, indicating that the microbial community is not too heterogeneous to analyze with molecular methods. In addition, the existence of unshared OTUs and the ability to detect quantitative differences between shared OTUs indicated differences between microbial communities that may be diagnostic of specific environmental conditions.
Example 3
Qualitative and Quantitative Analysis of Water Samples Using Microarrays
Based on the sequence information provided by the clones and information available in GenBank, two microarrays for testing water samples were made. The protocol for testing the microarray was as follows: appropriate prokaryotic and eukaryotic primers were used to amplify either 16S rDNA or 18S rDNA, respectively, from DNA that was extracted from the water samples as described above. The PCR products were then labeled by chemical attachment to either CY3 (green) or CY5 (red) dye, and upon denaturation, the labeled PCR products were hybridized to the array.
To make the arrays, 50-mer oligonucleotide sequences were spotted onto the surface of epoxy-coated glass slides. In Table 11, sequence identifications from Tables 2 and 3 are provided for each probe that was spotted to make the array shown in FIGS. 11 and 12. As indicated, there were some locations at which no probes were spotted.







TABLE 11







Prokaryotic (16S rDNA) probes












103P


103P




103P
103P
104P
105P
106P
107P


108P
109P
110P
103F1
103F1*
103F1*







CY3







9mer







Eukaryotic (18S rDNA) probes












15P
15P
30P
31P
32P
16P


33P
34P
14P
35P
36P
38P


39P
40P
41P
37P
42F
42F**







CY5







9mer





*reverse complementary sequence of 103F1;


**reverse complementary sequence of 42F






The experimental design is illustrated in FIG. 11A, showing labeling of a subset of sequences (e.g., prokaryotic) with red dye (FIG. 11A-1) and labeling of a second subset of sequences (e.g., eukaryotic) with green dye (FIG. 11A-2). Aligned sequences were used to design taxon-specific PCR primers (20-26 mer) and oligonucleotide probes (50-mers) to complementary variable regions. As a printing control and orientation marker, a CY3-labeled random 9-mer probe was also printed with each grouping of probes.
In the experiment shown in FIG. 11B, two aliquots drawn from a single genomic DNA sample (Lake Townsend, Station 1, June) were subjected to PCR with either a universal prokaryotic rDNA primer pair or a universal eukaryotic rDNA primer pair (Table 1) with dUTP added to the reaction mixture. The conditions for amplification were as described above for generation of the libraries. As described herein, the PCR reactions were then labeled with either CY5 (red, prokaryotic), or CY3 (green, eukaryotic) by chemically attaching the incorporated dUTP. The reactions were mixed and hybridized to a glass slide spotted with the oligonucleotide probes. As shown in FIG. 11B, the eukaryotic and prokaryotic PCR products are clearly detected on the prototype microarray. The scanned array image showed complete specificity of 12 of 12 prokaryotic probes and 19 of 21 eukaryotic probes. The green spot in the lower right of each sub-array was a CY3-labeled 9-mer marker for orientation. Also, locations at which no spots appear were printed with probes for sequences that were not experimental targets, thus acting as negative controls and, indicating that there was minimal DNA carryover during the array printing process. The actual array carried three sets of each grid, and scanned images of the replicate grids produced substantially identical images.
The experiment illustrated in FIG. 12 illustrated that the microarray may be used as a semi-quantitative assessment to compare two samples (for instance, the same location within a lake at two different times), or a sample and a standard. In this approach, two multiplex PCR amplifications were run—one for each lake sample. Both 16S and 18S rDNA were amplified together in a single reaction, and the amplified products from each sample were then labeled with either the red (Sample 1) or green (Sample 2) dye. When the amplified products were hybridized to a microarray, any resulting signal varied in color from red (target found in only sample 1) to yellow (target in both samples) to green (target found only in sample 2). The continuum from red to green is indicative of the relative abundance of the target in the samples.
Example 4
Testing for Specific Pathogens
The microarray is also capable of detecting known water pathogens and contaminants which affect water quality, thus raising the possibility of an “all in one” testing system. To test the feasibility of this additional feature, a microarray including 16S rDNA sequences from several cyanobacteria species was made. This microarray was tested with primers designed to amplify the rDNA of these species specifically, and the labeled products were hybridized to the microarray. As FIG. 13 shows, the multiplex/direct labeling methodology resulted in the appearance of signals specific for the cyanobacterial sequences from water samples known to contain cyanobacteria. For the experiment shown in FIG. 13, oligonucleotide probes to 18S rDNA are spotted in Grid A (16 probes) and B (15 probes). Twelve probes to 16S rDNA of Escherichia coli (strains K12 and 0157:H7; Prena et al, 2001, Nature, 409: 465-466) are spotted in Grid C, and twenty one 16S rDNA probes are spotted in Grid D, which contains cyanobacteria sequences, sequences associated with arsenic-responsive microbes (Oremland and Stolz, 2003, Science 300:939-943), and sequences identified in collected samples. Grids A, B, C, and D from FIG. 13 are shown in Table 12, and the identity of each probe (Tables 2 and 3) is provided at its location on the array







TABLE 12





Oligonucleotide probes on array of FIG. 13







A












15P
30P 
31P
32P 
16P
33P


34P
14P 
35P
36P 
38P
39P


40P
41P






17P
29P



CY3







9mer







B












10P
11P
12P
13P




19P
20P 
21P
22P 
18P
23P


24P 
25P
26P
27P
28P








Cy3







9mer







C












51P
52P
53P
54P
55P
56P


57P
58P
60P
61P 
62P
63P







CY3







9mer







D












83P 
81P 
73P 
74P
75P 
76P


84P 
85P
82P 
80P




103P
104P
105P
106P
107P
108P


109P
110P
77P
78P
79P 
CY3







9mer









To generate the labeled probe for this experiment, Toolik Lake, AK and City Lake, NC genomic samples were amplified using cyanobacteria specific PCR primers in a multiplex format. Toolik Lake products were labeled with CY3 (green) and City Lake products were labeled with CY5 (red). The primer pairs were: Synechococcus. sp. LBP1, Synechococcus sp. LBG2, an unknown cyanobacteria clone LD27, and a degenerate Synechococcus primer set (Table 3). The four probes to cyanobacteria hybridized with amplicons from both lake samples as evidenced by the yellow signal in grid D (FIG. 13). The additional signal in Grid D resulted from a labeled product that recognized a probe corresponding to the bacterium Burkholderia cepacia genomovar III. Subsequent analysis revealed that at least one of the Synechococus primers resembled the B. cepacia sequence, and that it likely amplified B. cepacia rDNA in the sample, indicating the importance of designing primer pairs to prevent cross-reactivity.
Example 5
Taxon-Specific Arrays
Amplification of genomic sample DNA may be performed by multiplex PCR using primers chosen to provide products that can hybridize to taxon-specific DNAs. Using this protocol can dramatically reduce non-specific labeling, and eliminates the need for intermediate PCR reactions, which reduce sensitivity.
FIG. 14 shows a taxon-specific array comprising 105 oligonucleotides generated from known and unknown OTUs isolated from freshwater lakes and from GenBank pathogen sequences. DNA samples from two different lakes were amplified in identical multiplex PCR reactions and reaction products were either labeled with a red dye (CY5) or a green dye (CY3), allowing for comparison of samples. Shown are results from a test of two lake samples used to hybridize first singly (top panels) (left panel: CY3-labeled sample, sample 1; right panel: CY5-labeled sample) and then together (bottom panel) to the same array of 105 oligonucleotide probes.
The arrays included nucleic acid sequences from variable regions of individual eukaryotic and prokaryotic rDNAs. Sequences spotted on the arrays included 32 probes derived from the literature that target known pathogens or contaminant microbes and 73 probes to sequences derived from freshwater environmental samples, including both known and novel sequences, and four cyanobacteria. The actual probe sequences spotted on the array shown in FIG. 14 are provided in Table 13, and the location of each sequence on the array is provided in Table 14.







TABLE 13







Primer/Probe combinations spotted on microarrays











GenBank

GenBank



accession

accession 


16S rDNA sequence
no.
18S rDNA sequence
no.





Enterococcus gallinarum, strain LMG 13129
AJ301833
Cryptosporidium parvum
AF222998


Burkholderia cepacia
AB091761
Acanthamoeba mauritaniensis
AY351647


Burkholderia cepacia genomovar III
AF148556
Cyclospora cayetanensis
AF111183


Uncultured human fecal bacterium HF74
AF233412
Entamoeba histolytica
X65163


Uncultured human fecal bacterium HF8
AF233408
Giardia intestinalis isolate
AF199449


Uncultured human fecal bacterium HF10
AF233413
Isospora belli
AF106935


Bacillus anthracis strain S51
AB116124
Microsporidium sp. STF
AY140647


Clostridium botulinum strain AIP 355.02
AY303799
Naegleria fowleri
AF338423


Francisella tularensis strain 3523
AY243028
OTU TL1A1, multi-copy, unidentified



Yersinia pestis
AF366383
OTU TL1A2, multi-copy, unidentified



Brucella melitensis
AF220149
OTU TL1A9, multi-copy, unidentified



Burkholderia mallei strain 2000031063
AY305760
OTU TL1A12, multi-copy,





unidentified



Chlamydophila psittaci clone cvCps2
AY334530
OTU TL1A16, multi-copy,





unidentified



Coxiella burnetii, strain Nine Mile
Y11502
OTU TL1A21, multi-copy,





unidentified



Escherichia coli O157:H7
AB035920
OTU CL1A3, single-copy,





unidentified



Escherichia coli O157:H7 EDL933
NC 002655
OTU CL1A4, single-copy,





unidentified



Escherichia coli O157:H7 EDL933
NC 002655
OTU CL1A5, single-copy,





unidentified



Escherichia coli O157:H7 EDL933
NC 002655
OTU CL1A6, single-copy,





unidentified



Escherichia coli O157:H7 EDL933
NC 002655
OTU CL1A8, multi-copy,





unidentified



Escherichia coli O157:H7 EDL933
NC 002655
OTU LT2A12, multi-copy,





unidentified



Escherichia coli O157:H7 EDL933
NC 002655
OTU LT2A20, single-copy,





unidentified



Escherichia coli O157:H7 EDL933
NC 002655
OTU LT1A3, single-copy,





unidentified



Escherichia coli O157:H7 EDL933
NC 002655
OTU LT1A42, multi-copy, identified





as Cryptomonas sp., strain M420



Escherichia coli K12
NC 000913
OTU LT1A5, multi-copy, unidentified



Escherichia coli K12
NC 000913
OTU LT1A4, multi-copy, identified





as Ctyptomonas ovata, strain CCAP





979/61



Escherichia coli K12
NC 000913
OTU LT1A8, multi-copy, unidentified



Escherichia coli K12
NC 000913
OTU LT2A7, multi-copy, identified





as Dileptus sp.



Rickettsia prowazekii
M21789
OTU LT1A9, single-copy,





unidentified



Salmonella typhimurium
Z49264
OTU LT2A19, single-copy, identified





as Coleps sp.



Vibrio cholerae (CECT 514 T)
X76337
OTU LT1A10, multi-copy,





unidentified



Campylobacter jejuni strain B99/206
AF550630
OTU LT1A11, single-copy,





unidentified



Legionella pneumophila serogroup 6
AJ496383
OTU LT1A13, single-copy,





unidentified



Leptospira interrogans
Z12817
OTU LT3A2, single-copy,





unidentified



Pseudomonas aeruginosa, strain WatG
AB117953
OTU LT3A5, multi-copy, unidentified



OTU TL1A1, multi-copy, unidentified

OTU LT3A6, multi-copy, unidentified



OTU TL1A2, multi-copy, unidentified

OTU LT3A11, single-copy,





unidentified



OTU TL1A6, single-copy, unidentified

OTU LT3A13, single-copy,





unidentified



OTU TL1A7, multi-copy, identified as

OTU LT1A1, multi-copy, unidentified



Uncultured beta proteobacterium clone 





OS1L-16





OTU LT1A31, multi-copy, identified as

OTU LT1A38, multi-copy,



Uncultured Crater Lake bacterium CL500-18

unidentified



OTU LT1A55, multi-copy, identified as





Uncultured freshwater bacterium LCK-26





OTU CL1A2, multi-copy, unidentified





OTU CL1A9, multi-copy, identified as





Zoogloen ramigera





OTU CL1A10, multi-copy, unidentified





OTU CL1A15, single-copy, identified as





Uncultured Crater Lake bacterium CL0-27





OTU LT1A54, multi-copy, identified as





Uncultured Crater Lake bacterium CL0-64





OTU LT1A27, multi-copy, identified as





Uncultured actinomycete clone SFD1-39





OTU LT2A3, multi-copy, unidentified





OTU LT1A46, multi-copy, identified as





Uncultured planctomycete clone





CY0ARA031E04





OTU LT2A12, multi-copy, unidentified





OTU LT2A16, multi-copy, unidentified





OTU LT1A53-3A9, multi-copy, identified as





Synechococcus sp.





OTU LT1A53, multi-copy, identified as





Synechococcus sp. LBG2





OTU LT3A9, multi-copy, identified as





Synechococcus sp. LBP1





OTU LT3A11, multi-copy, identified as





Unidentified cyanobacterium clone LD27





Arsenite-oxidizing bacterium MLHE-1





Thiomicrospira sp. CVO





Desulfovibrio longreachii





Bacillus arsenicoselenatis





OTU LT3A1, single-copy, unidentified





OTU LT3A2, multi-copy, unidentified





OTU LT3A7, multi-copy, unidentified





OTU LT1A15, single-copy, unidentified





OTU LT1A16, multi-copy, unidentified





OTU LT1A18, multi-copy, unidentified





OTU LT1A35, multi-copy, unidentified





OTU LT1A55, multi-copy, unidentified
















TABLE 14





Oligonucleotide probes on array of FIG. 14







A


B












19P
20P 
21P
22P
18P
23P


24P
25P
26P
27P
28P



17P
29P











CY3







9mer







C












43P
44P
45P
46P
47P
48P


49P
50P
65P
66P
67P
68P


69P
70P
71P
72P









D












95P
96P
97P
86P
87P
88P


91P
98P
92P
99P
89P
90P


93P
100P
94P
101P
102P








CY3







9mer







E












15P
30P
31P
32P
16P
33P


34P
14P
35P
36P
38P
39P


40P
41P











F












10P
11P
12P
13P
1P
2P


3P
4P
5P
6P
7P
8P







CY3







9mer







G












51P
52P
53P
54P
55P
56P


57P
58P
60P
61P
62P
63P







H












83P
81P
73P
74P
75P
76P


84P
85P
82P
80P
77P
78P


79P
106P
107P
108P




103P
104P
105P
109P
110P
CY3







9mer









Such taxon-specific arrays may be developed for specific bodies of water. For example, arrays may be developed for lakes, marshes, tidal pools, or estuaries. Such arrays may include probes developed for freshwater systems, as these may be diagnostic for known pathogens (e.g., coliform bacteria) or environmental conditions (e.g., eutrophication). Also, sequences specific to microbes known to be common in the body of water of interest may be used. For example, for estuaries, phytoplankton populations have been described (Williams, R. B. and M. B. Murdoch 1966, Limnology and Oceanography 11:73-82, Thayer, G. W., 1971 Estuaries 12:240-253; Mallin 1994, Mallin, et al. 2000). A review of the literature indicates that many of the sequences that may be used are known (Table 15). Using this information, primers and probes to these common organisms, may be designed. Finally, probes for the array may be derived by sequencing clonal libraries derived from field samples as described herein for the lake samples to develop additional OTUs. For example, to develop an estuary array, water samples may be collected every few months in estuarine tidal creeks at various sites representing a range of estuarine conditions. Specific sampling locations may be water quality monitoring stations, and samples may be taken late on the flooding tide and six hours later on the ebbing tide, to provide a representative sample of both the community that enters the estuarine site as well as the community that leaves the estuarine site with the falling tide.
It should be understood that various changes and modifications to the embodiments described herein will be apparent to those skilled in the art. Such changes and modifications can be made without departing from the spirit and scope of the present invention and without diminishing its attendant scope and/or advantages.







TABLE 15





Examples of organisms of interest for North Carolina


estuarine microarray targets based on literature reports4
















Phytoplankton



Cyclotella spp.
Melosira spp.


Nitzschia spp.
Navicula spp.


Psuedo-nitzschia australis3
Skeletonema costatum1


Thalassiosira spp.



Amphidinium spp.
Ceratium spp.


Chattonella spp.3 (C. antiqua, C. verruculosa)
Gymnodinium sanguineum


Heterocapsa triquetral
Heterosgima akashiwo3


Hematodinium perezi3
Karenia brevis3


Karlodinium micrum1
Katodinium rotundatum1


Pfiesteria piscicida3, P. shumwayae3
Prorocentrum minimum1


Calicomonas ovalis
Chlamydomonas spp.


Chroomonas spp. (C. minuta, C. amphioxiae)
Cyrptomonas testaceae


Hemiselmis virescens
Phaeocystis globosa


Pyramimonas
Eutreptia1


Bacteria



Acinetobcter spp.
Alcaligenes spp.


Bacteroides spp.2
Enterococcus spp.2 (E. faecalis, E. faecium)


Escherichia spp.2,3 (E. coli, E. coli O157H7)
Flavobacterium spp.


Oceanospirillum spp.
Salmonella spp.2,3 (S. typhi, S. non-typhi)


Psuedomonas aeruginosa
Shigella sp.2,3







Clostridium sp.2,3 (C. perfringens, C. botulinum Type E)


Vibrio sp.3 (V. anguillarum, V. cholerae 01, V. cholerae non 01, V. parahaemolyticus V. vulnificus








Virus



Hepatitis A3
Norwalk virus3


Adenovirus3
rotavirus3


Protozoa



Kudoa spp.3 (K. clupeidae, K. fundulae)
Cryptosporidium spp.2,3


Giardia2,3
Perkinsus marinus3


Haplosporidium3



Fungi



Aphanomyces invadens3





1Genera or species referenced in the literature as commonly found in southeastern estuarine systems, and likely to be indicators of good ecosystem health (e.g. Campbell, 1973, Univ. of N.C. Sea Grant Publication, UNC-SG-73-07; Mallin, et al. 2000, American Scientist, 88:26-37; Shubert, 1984, In Algae as Ecological Markers, Academic Press, NY, p. 434; Stoermer and Smo1,1999, In The Diatoms: Applications For the Environmental and Earth Sciences, Cambridge Univ. Press, Cambridge, UK, page 469; Thayer, 1971, Estuaries, 12:240-253, Williams and Murdoch, 1966, Limnology and Oceanography, 11:73-82;).


2Microbes linked to specific contamination sources (e.g. human sewage) which indicate point or non-point source pollution (e.g. Bernhard and Field, 2000, Applied and Environmental Microbiology, 66:4641-4648; Lipp, et al. 2001, Marine Pollution Bull., 42:286-293; Mallin, et al., 2000b, Ecological Applications, 10:1047-1056' USEPA, 1985, Test methods for Escherichia coli and Enterococci in water by the membrane filter procedure, EPA600/4-85/076)


3Known human, fish, or shellfish pathogens or parasites (e.g. DeLeon, et al. 1990, In Proceeding of the Water Quality Conference, San Diego, CA, American Water Works Association, 18:833-853; Grimes 1991, Estuaries, 14:345-360; Kane, et al., 1998, Maryland Medical Journal, 37:106-112; Lipp, 1999, Reed and Francis-Floyd, 1996, Vibrio Infecitons of Fish, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida web-site; Shields, 1997, An investigation into the epidemiology of Hematodinium perezi, a parasitic dinoflagellate in the blue crab, Callinectes sapidus, available on-line)


4Many of the taxa listed have GenBank sequence entries for one or more species.

## Claims

1. A device comprising an array, wherein the array comprises a plurality of oligonucleotides covalently immobilized at known locations of the array, and wherein each location on the array comprises an oligonucleotide having a sequence as set forth in any one of SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100 and SEQ ID NO: 106 or the complement of SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100 and SEQ ID NO: 106.

2. The device of claim 1, wherein the oligonucleotides at each location of the array range from about 30 to 200 nucleotides in length.

3. The device of claim 1, wherein the oligonucleotides at each location of the array range from about 40 to 100 nucleotides in length.

4. The device of claim 1, wherein the oligonucleotides at each location of the array are each about 50 nucleotides in length.

5. The device of claim 1, wherein at least one of the oligonucleotides comprises a eukaryotic ribosomal DNA sequence.

6. The device of claim 1, wherein at least one of the oligonucleotides comprises a prokaryotic ribosomal DNA sequence.

7. The device of claim 1, wherein at least one of the oligonucleotides further comprises the sequence as set forth in any one of SEQ ID NO: 5-SEQ ID NO: 25; or SEQ ID NO: 27-SEQ ID NO: 31, or SEQ ID NO: 33-SEQ ID NO: 39, or SEQ ID NO: 41-SEQ ID NO: 97, or SEQ ID NO: 99, or SEQ ID NO:101-SEQ ID NO: 105, or SEQ ID NO: 107-SEQ ID NO: 113, or the complement of SEQ ID NO: 5-SEQ ID NO: 25, or SEQ ID NO: 27-SEQ ID NO: 31, or SEQ ID NO: 33-SEQ ID NO: 39, or SEQ ID NO: 41-SEQ ID NO: 97, or SEQ ID NO: 99; or SEQ ID NO:101-SEQ ID NO: 105, or SEQ ID NO: 107-SEQ ID NO: 113.

8. The device of claim 1, wherein there are at least 10 different oligonucleotides, each at a distinct location on the array, and each of the at least 10 different oligonucleotides individually comprises the sequence as set forth in any one of SEQ ID NO: 5-SEQ ID NO: 113, or the complement of SEQ ID NO: 5-SEQ ID NO: 113.

9. The device of claim 1, wherein there are at least 50 different oligonucleotides, each at a distinct location on the array, and each of the at least 50 different oligonucleotides individually comprises the sequence as set forth in any one of SEQ ID NO: 5-SEQ ID NO: 113, or the complement of SEQ ID NO: 5-SEQ ID NO: 113.

10. The device of claim 1, wherein the individual oligonucleotides on the array range from 1 femtogram (fg) to about 10 micrograms (μg) at each location of the array.

11. A system for monitoring an ecosystem comprising:
(a) an array comprising a plurality oligonucleotides covalently immobilized at known locations of the array, such that each location on the array comprises an oligonucleotide having a sequence as set forth in any one of SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100 or SEQ ID NO: 106, or the complement of SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100 or SEQ ID NO: 106; and
(b) polymerase chain reaction primers for amplifying DNA isolated from an ecosystem to generate oligonucleotides complementary to at least some of the plurality of oligonucleotides of the array to generate an amplified nucleic acid sample from the ecosystem.

12. The system of claim 11, wherein at least one of the oligonucleotides further comprises the sequence as set forth in any one of SEQ ID NO: 5-SEQ ID NO: 25, or SEQ ID NO: 27-SEQ ID NO: 31, or SEQ ID NO: 33-SEQ ID NO: 39, or SEQ ID NO: 41-SEQ ID NO: 97, or SEQ ID NO: 99, or SEQ ID NO:101-SEQ ID NO: 105, or SEQ ID NO: 107-SEQ ID NO: 113, or the complement of SEQ ID NO: 5-SEQ ID NO: 25, or SEQ ID NO: 27-SEQ ID NO: 31, or SEQ ID NO: 33-SEQ ID NO: 39, or SEQ ID NO: 41-SEQ ID NO: 97, or SEQ ID NO: 99, or SEQ ID NO:101-SEQ ID NO: 105, or SEQ ID NO: 107-SEQ ID NO: 113.

13. The system of claim 11, wherein at least two of the oligonucleotides comprises the sequence as set forth in any one of SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100 or SEQ ID NO: 106, or the complement of SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100 or SEQ ID NO: 106.

14. The system of claim 11, wherein at least four of the oligonucleotides comprises the sequence as set forth in any one of SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100 or SEQ ID NO: 106, or the complement of SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100 or SEQ ID NO: 106.

15. The system of claim 11, wherein at least one of the PCR primers comprises the sequence as set forth in any one of SEQ ID NO: 156-SEQ ID NO: 157, SEQ ID NO: 168-SEQ ID NO: 169, SEQ ID NO: 180-SEQ ID NO: 181, SEQ ID NO: 283-SEQ ID NO: 284, SEQ ID NO: 287-SEQ ID NO: 288, or SEQ ID NO: 300-SEQ ID NO: 301.

16. The system of claim 11, wherein at least one of the oligonucleotides comprises a eukaryotic ribosomal DNA sequence and at least one of the immobilized oligonucleotides comprises a prokaryotic ribosomal DNA sequence.

17. The system of claim 11, wherein each of the plurality of oligonucleotides is selected from at least one of a prokaryotic small subunit ribosomal DNA based on alignments with E. Coli V1, V2, V3 or V4 variable region for each prokaryotic operational taxonomic unit, or at least one of a eukaryotic small subunit ribosomal DNA based on alignments with S. cerevisiae V1, V2, V3 or V4 variable region for each eukaryotic operational taxonomic unit.

18. The system of claim 11, wherein there are at least 10 different oligonucleotides, each at a distinct location on the array, and each of the at least 10 different immobilized oligonucleotides individually comprises the sequence as set forth in any one of SEQ ID NO: 5-SEQ ID NO: 113, or the complement of SEQ ID NO: 5-SEQ ID NO: 113.

19. The system of claim 11, wherein there are at least 50 different oligonucleotides, each at a distinct location on the array, and each of the at least 50 different immobilized oligonucleotides individually comprises the sequence as set forth in any one of SEQ ID NO: 5-SEQ ID NO: 113, or the complement of SEQ ID NO: 5-SEQ ID NO: 113.

20. The system of claim 11, wherein the ecosystem comprises water.

21. A system for monitoring water quality comprising an array, wherein the array comprises a plurality of oligonucleotides covalently immobilized at known locations of the array, and wherein each location on the array comprises an oligonucleotide having a sequence that is derived from a single, predetermined microbial operational taxonomic unit; and
a plurality of oligonucleotides having a detectable label covalently attached thereto for hybridizing to the array wherein at least one of the detectably labeled oligonucleotides comprises the sequence as set forth in any one of SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100 or SEQ ID NO: 106, or the complement of SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100 or SEQ ID NO: 106.

22. The system of claim 21, wherein the system further comprises a detectably labeled oligonucleotide having the sequence as set forth in any one of SEQ ID NO: 5-SEQ ID NO: 25, or SEQ ID NO: 27-SEQ ID NO: 31, or SEQ ID NO: 33-SEQ ID NO: 39, or SEQ ID NO: 41-SEQ ID NO: 97, or SEQ ID NO: 99, or SEQ ID NO:101-SEQ ID NO: 105, or SEQ ID NO: 107-SEQ ID NO: 113, or the complement of SEQ ID NO: 5-SEQ ID NO: 25, or SEQ ID NO: 27-SEQ ID NO: 31, or SEQ ID NO: 33-SEQ ID NO: 39, or SEQ ID NO: 41-SEQ ID NO: 97, or SEQ ID NO: 99, or SEQ ID NO:101-SEQ ID NO: 105, or SEQ ID NO: 107-SEQ ID NO: 113.

23. The system of claim 12, wherein at least one of the PCR primers comprises the sequence as set forth in any one of SEQ ID NO: 114-SEQ. ID NO: 316.

24. The system of claim 21, wherein there are at least 2 different oligonucleotides, each at a distinct location on the array, and each of the at least 2 different immobilized oligonucleotides individually comprises the sequence as set forth in any one of SEQ ID NO: 5-SEQ ID NO: 113, or the complement of SEQ ID NO: 5-SEQ ID NO: 113.

25. The system of claim 21, wherein at least three of the plurality of detectably labeled oligonucleotides comprises the sequence as set forth in any one of SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100 or SEQ ID NO: 106, or the complement of SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100 or SEQ ID NO: 106.

26. The system of claim 21, wherein at least two of the plurality of detectably labeled oligonucleotides individually comprises the sequence as set forth in any one of SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100 or SEQ ID NO: 106, or the complement of SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100 or SEQ ID NO: 106.

27. The system of claim 21, wherein at least four of the plurality of detectably labeled oligonucleotides individually comprises the sequence as set forth in any one of SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100 or SEQ ID NO: 106, or the complement of SEQ ID NO: 26, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 98, SEQ ID NO: 100 or SEQ ID NO: 106.

28. The device of claim 1, wherein the plurality of oligonucleotides are derived from at least one of a prokaryotic ribosomal DNA sequence that corresponds to nucleotides 160-250 of the prokaryotic small subunit ribosomal DNA V2 region as set forth in SEQ ID NO: 320 or nucleotides 430-510 of a prokaryotic small subunit ribosomal DNA V4 region as set forth in SEQ ID NO: 321, or from at least one of a eukaryotic ribosomal DNA sequences that correspond to nucleotides 600 to 800 of a eukaryotic small subunit ribosomal DNA V2 region as set forth in SEQ ID NO: 325; or nucleotides 1000 to 1100 of the eukaryotic small subunit ribosomal DNA V4 region as set forth in SEQ ID NO: 327.

29. The system of claim 11, wherein the plurality of oligonucleotides are derived from at least one of a prokaryotic ribosomal DNA sequence that corresponds to nucleotides 160-250 of the prokaryotic small subunit ribosomal DNA V2 region as set forth in SEQ ID NO: 320 or nucleotides 430-510 of a prokaryotic small subunit ribosomal DNA V4 region as set forth in SEQ ID NO: 321, or from at least one of a eukaryotic ribosomal DNA sequences that correspond to nucleotides 600 to 800 of a eukaryotic small subunit ribosomal DNA V2 region as set forth in SEQ ID NO: 325; or nucleotides 1000 to 1100 of the eukaryotic small subunit ribosomal DNA V4 region as set forth in SEQ ID NO: 327.

30. The device of claim 1, wherein each oligonucleotide has a sequence that is specific to a single, predetermined microbial operational taxonomic unit, wherein an operational taxonomic unit is comprised of sequences having at least 97.5% identity to each other.

31. The device of claim 1, wherein each of the plurality of oligonucleotides is selected from at least one of a prokaryotic small subunit ribosomal DNA based on alignments with E. Coli V1, V2, V3 or V4 variable regions for each prokaryotic operational taxonomic unit, or at least one of a eukaryotic small subunit ribosomal DNA based on alignments with S. cerevisiae V1, V2, V3 or V4 variable regions for each eukaryotic operational taxonomic unit.

32. The system of claim 11, wherein each oligonucleotide has a sequence that is specific to a single, predetermined microbial operational taxonomic unit and wherein an operational taxonomic unit is comprised of sequences having at least 97.5% identity to each other.

33. The system of claim 21, wherein the plurality of oligonucleotides immobilized at known locations of the array are derived from at least one of a prokaryotic ribosomal DNA sequence that corresponds to nucleotides 160-250 of the prokaryotic small subunit ribosomal DNA V2 region as set forth in SEQ ID NO: 320 or nucleotides 430-510 of a prokaryotic small subunit ribosomal DNA V4 region as set forth in SEQ ID NO: 321, or from at least one of a eukaryotic ribosomal DNA sequences that correspond to nucleotides 600 to 800 of a eukaryotic small subunit ribosomal DNA V2 region as set forth in SEQ ID NO: 325; or nucleotides 1000 to 1100 of the eukaryotic small subunit ribosomal DNA V4 region as set forth in SEQ ID NO: 327.

34. The system of claim 21, wherein the detectable label comprises one of a radionucleotide, a biotinylated nucleotide or a fluorescein-labeled nucleotide.