Patent Publication Number: US-2023133186-A1

Title: Point-of-care digital microfluidics for sepsis diagnosis

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims priority from U.S. Provisional Application Ser. No. 62/992,061, filed Mar. 19, 2020. 
    
    
     BACKGROUND 
     1. Technical Field 
     This document relates to digital microfluidics devices for diagnosis of a disease. For example, this document relates to point-of-care digital microfluidics devices for removing target cells from a blood sample and identifying bacterial DNA in the remaining sample to diagnose a disease. 
     2. Background Information 
     Sepsis occurs in the body when an immune response, initiated by an infection, causes inflammation to ensue throughout the body. The National Institute of Health (NIH) estimates that at least 1.7 million people in the United States are diagnosed with Sepsis each year, and 25-50% of these patients may die from the condition. According to Centers for Disease Control and Prevention (CDC), one in every three deaths in a hospital are due to Sepsis. The standard approach for identifying Sepsis relies on diagnostic tools, such as vital signs, blood tests, imaging, and lab tests. 
     The standard approach generally relies on a bacterial culture, which can take days or weeks to complete. In addition, standard methods for detecting and/or identifying a bacterial infection can include steps such as obtaining a culture, conducting quantitative polymerase chain reaction (qPCR), and applying standard sequencing, which often require bulky, costly equipment and are relatively complex and time-consuming. During medical emergencies, it is logistically challenging to have immediate access to standard tests to identify bacterial strains such as those that lead to life-threatening infections in a rapid manner. However, these types of situations are exactly when rapid and accurate disease diagnosis is critical and can prevent secondary deaths caused by undiagnosed, untreated diseases. 
     SUMMARY 
     This document provides digital microfluidics (DMF) devices for disease diagnosis, such as Sepsis diagnosis. For example, this document provides point-of-care digital microfluidics devices that can remove white blood cells from a blood sample and identify bacterial DNA in the remaining biological sample to diagnose Sepsis. In various embodiments, the systems, devices, and methods provided herein provide a digital microfluidic platform for a rapid, portable, and automated approach for providing microbial whole genome amplification (WGA) and sequencing (e.g., nanopore sequencing) for Sepsis diagnosis in various settings, such as in an urgent care setting. 
     The systems, devices, and methods provided herein can provide several advantages for bacterial infectious disease screening. In particular, the DMF devices provided herein can provide a portable point-of-case diagnosis tool to diagnosis a disease, such as Sepsis. In some embodiments, the DMF devices provided herein can allow for a rapid diagnosis of bacterial Sepsis, for example, a diagnosis within hours (e.g., 6 hours) after taking a sample from a patient. 
     The DMF devices provided herein can be capable of rapidly identifying pathogenic and bacterial infections in human whole blood samples and of identifying genetically driven antibiotic resistance in various embodiments. In some cases, a DMF device described herein can be a single, portable device to perform multiple processes and provide functionalities, normally performed in different laboratories. For example, a DMF device provided herein can be configured to perform several integrated processes, including sample pre-processing, bacterial nucleic acid (e.g., DNA) extraction, nucleic acid (e.g., DNA) amplification, and library construction. In some cases, a device provided herein can be configured to perform multiple processes (e.g., bacterial nucleic acid (e.g., DNA) extraction, nucleic acid (e.g., DNA) amplification, and library construction) as part of a system that employs an automated process. 
     The systems, devices, and methods described herein can used as a diagnosis tool having a high sensitivity with up to 100 times less than standard? sample size volume at affordable costs that provides critical information for timely medical intervention. In some embodiments, the devices can provide rapid diagnosis using physiological fluids such as blood, saliva, and sputum for detecting bacterial infectious diseases. 
     In one aspect, a microfluidics device includes a substrate including a first location comprising one or more immobilized analytes, a second location, and a third location. The device also includes an array of electrodes configured to move a biological sample of a mammal from said first location to said second location and from said second location to said third location. The first location is configured to capture at least some cells of said mammal from said sample via said one or more immobilized analytes to form a cell-free sample. The second location is configured to receive said cell-free sample and one or more reagents for performing WGA to form an amplified sample. The third location is configured to receive said amplified sample and one or more reagents for performing library construction to form a sequencing ready sample. 
     In some embodiments, the device is a digital microfluidic chip. In some embodiments, the biological sample comprise blood. In some embodiments, the biological sample comprises human blood. In some embodiments, the one or more immobilized analytes comprise an anti-CD45 antibody. In some embodiments, the at least some cells comprise white blood cells, red blood cells, platelets, or combinations thereof. In some embodiments, the at least some cells comprise white blood cells. 
     In some embodiments, the one or more analytes are configured to bind from about 1,000 to about 100,000 cells per each droplet of the biological sample. In some embodiments, the one or more immobilized analytes are configured to bind from about 5,000 to about 50,000 cells per each droplet of the biological sample. In some embodiments, the one or more immobilized analytes are configured to bind from about 7,000 to about 25,000 cells per each droplet of the biological sample. In some embodiments, the one or more immobilized analytes are configured to bind from about 10,000 to about 15,000 cells per each droplet of the biological sample. 
     In some embodiments, the array of electrodes comprise chrome. In some embodiments, the array of electrodes comprise a coating disposed on the array of electrodes. In some embodiments, the coating comprises an insulative material. In some embodiments, the coating comprises a hydrophobic material. In some embodiments, the coating comprises indium tin oxide. 
     In some embodiments, the array of electrodes are configured to define one or more microfluidic channels on the substrate. In some embodiments, the device is further configured to transfer the sequence ready sample. In some embodiments, the second and third locations are at different locations on the substrate. In some embodiments, the second and third locations are the same location. 
     In another aspect, a method of preparing a biological sample for diagnosis of a disease includes: providing a biological sample on the substrate of the device of claim  1 ; and moving said biological sample from the first location to the second location, and from the second location to the third location. In some embodiments, the second location and the third location are the same location. In some embodiments, the method further includes moving one or more reagents from an initial location to the second location, the third location, or both. In some embodiments, the method further includes moving one or more reagents to the second location for performing WGA. In some embodiments, the method further includes moving one or more reagents to the third location for performing library construction. In some embodiments, the moving the biological sample from one location to another location comprises activating and deactivating electrodes in a path defined between the first and second locations. 
     In some embodiments, the method further includes moving the biological sample from the second location to the third location. In some embodiments, further includes capturing said at least some cells of said mammal from said sample via said one or more immobilized analytes to form a cell-free sample at the first location. In some embodiments, further includes performing WGA at the second location to form the amplified sample. In some embodiments, further includes performing library construction to form the sequencing ready sample. 
     In some embodiments, the biological sample comprises blood. In some embodiments, the biological sample comprises serum. In some embodiments, the biological sample comprises saliva. In some embodiments, the providing comprises placing one or more droplets of the biological sample on the substrate. In some embodiments, the method further includes obtaining the blood sample from the patient. In some embodiments, the patient is a mammal. In some embodiments, the patient is a human. 
     In some embodiments, the cell-free biological sample comprise less than 10,000 cells per droplet. In some embodiments, the cell-free biological sample comprise less than 7,000 cells per droplet. In some embodiments, the cell-free biological sample comprise less than 5,000 cells per droplet. In some embodiments, the cell-free biological sample comprise less than 5×10 9  cells per liter (cells/L). In some embodiments, the cell-free biological sample comprise less than 3×10 9  cells/L. In some embodiments, the cell-free biological sample comprise less than 1×10 9  cells/L. In some embodiments, the cell-free biological sample comprise less than 1×10 6  cells/L. In some embodiments, the cell-free biological sample comprise less than 1×10 3  cells/L. 
     In some aspects, a procedure comprising performing any of the methods provided herein during an emergency medicinal procedure, therapeutic response monitoring, disease prognosis, or early detection of a cancer. 
     Other advantages of the devices provided herein include its suitable use in a wide range of applications, including emergency medicine, therapeutic response monitoring in intensive care unit and critical disease diagnosis and prognosis. 
     Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Although methods and materials similar or equivalent to those described herein can be used to practice the invention, suitable methods and materials are described below. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. In case of conflict, the present specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and not intended to be limiting. 
     The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims. 
    
    
     
       DESCRIPTION OF DRAWINGS 
         FIG.  1    shows a photo of an example digital microfluidics (DMF) device, according to some embodiments. 
         FIGS.  2 A- 2 F  includes a series of photos showing time-lapse images of droplet transport, merging, and splitting in the DMF device of  FIG.  1   , according to some embodiments. 
         FIGS.  3 A- 3 B  are photos showing examples of a DMF device, depicting a sample (e.g., a blood sample) moving across a substrate (shown by arrows) that includes an immobilized CD45 antibody region for capturing white blood cells (WBCs), according to some embodiments. 
         FIG.  4    depicts an example schematic platform showing several processes, including cell separation, bacterial WGA, and library construction, which can be performed by a DMF device provided herein according to some embodiments. 
         FIG.  5    shows a photo of a portable sequencer connected to a laptop, according to some embodiments. 
         FIG.  6    is a flow diagram depicting the workflow in a method for bacterial whole genome amplification (WGA) in a DMF device, with whole genome sequencing (WGS) in MinION sequencer. The process is completed within 3 hours. 
         FIGS.  7 A and  7 B  show an overview an embodiment of a DMF device.  FIG.  7 A  is a photo showing a close-up of a DMF device inserted into the Dropbot system, with fluids on reservoir electrodes.  FIG.  7 B  is a cross-sectional diagram of a DMF device, showing fluid manipulation between the top and bottom substrates. 
         FIGS.  8 A- 8 D  show comparisons between the amount of  C. glutamicum  DNA amplified in-tube and on-chip. Each amplification experiment was performed three times, and one replicate was sequenced.  FIG.  8 A  is a graph plotting the amount of DNA obtained after amplification in-tube and on-chip.  FIG.  8 B  is a graph plotting the amount of sequencing data generated for samples amplified in-tube for 2 hours.  FIG.  8 C  is a graph plotting the percent of sequencing reads that passed quality control (Qscore&gt;7) for samples amplified in-tube and on-chip.  FIG.  8 D  is a graph plotting the amount of sequencing data generated for samples amplified on-chip for 2 hours or 30 minutes. 
         FIGS.  9 A and  9 B  show contamination profiles for sequenced samples.  FIG.  9 A  is a graph plotting the contamination profile for samples with different starting amounts of  C. glutamicum  DNA amplified on-chip and in-tube. The results show the profile after 30 minutes of sequencing. Sequencing failed for samples with &lt;1 pg starting DNA amplified in-tube.  FIG.  9 B  is a graph plotting the contamination profile of 100 pg  C. glutamicum  DNA amplified for 2 hours on-chip. Extended sequencing times led to increased numbers of target species reads, with marginal increases of contaminant reads. 
         FIG.  10    is a graph plotting the coverage of sequencing reads processed and mapped to the  C. glutamicum  reference genome, from samples amplified for 2 hours. 
         FIGS.  11 A- 11 D  are graphs plotting sequencing results of on-chip amplified samples with different initial amounts of  C. glutamicum, P. somerae , and  E. coli  bacteriophage lambda DNA. Three amplification tests and sequencing were performed on each sample. Initial amounts used were: 100 fg lambda, 100 fg  C. glutamicum , and 50 fg  P. somerae  DNA ( FIG.  11 A ); 10 fg lambda, 10 fg  C. glutamicum , and 50 fg  P. somerae  DNA ( FIG.  11 B ); 10 fg lambda, 20 fg  C. glutamicum , and 100 fg  P. somerae  DNA ( FIG.  11 C ), and 1 pg lambda, 50 fg  C. glutamicum , and 10 fg  P. somerae  DNA ( FIG.  11 D ). 
         FIG.  12    is a graph plotting the number of reads for a single  C. glutamicum  cell that was lysed and amplified on a chip, demonstrating the feasibility of effective bacterial cell lysis followed by amplification on a single cell level. 
     
    
    
     DETAILED DESCRIPTION 
     This document provides point-of-care digital microfluidics (DMF) devices that can be used to quickly diagnose a disease, such as Sepsis. The point-of-care DMF devices (as well as systems) provided herein can be used to diagnose a disease within a short period of time (e.g., in about 6 hours or less), as well as to provide a portable means for diagnosis. 
     In various embodiments, the DMF systems and devices provided herein can provide a reliable diagnosis of Sepsis from a biological sample by producing a cell-free specimen and performing subsequent bioinformatic analysis on the cell-free specimen. A “cell-free” specimen as used herein refers to a biological product produced after a desired number or amount (e.g., at least 50%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%) of target cells (e.g., cells that contain DNA, such as white blood cells) has been removed from a biological sample, such that the “cell-free” specimen has a reduced number of the target cells that would otherwise be present in the biological sample. Reducing the number of one or more particular types of cells from a biological sample prior to performing genomic processing (e.g., genome amplification and/or nanopore sequencing) can advantageously reduce noise and reduce test time during the diagnosis of a disease, such as Sepsis. In some cases, the devices and methods provided herein can identify the source of a bacterial infection in human blood samples within a few hours. 
       FIG.  1    shows an example of a portable system  100  comprising a DMF device  110  (e.g., a microfluidic chip) configured for diagnosing a disease (e.g., Sepsis). System  100  is configured for programmable control droplet manipulation through use of a microfluidics controller and graphic user interface. In various embodiments, system  100  can be a portable system that is easily transported from one location to another. In some embodiments, system  100  can be used to identify any bacterial infectious disease that may be identified through bioinformatics analysis of blood, saliva, or other physiological fluids (e.g., urine, plasma, serum, or cerebrospinal fluid). 
     System  100  includes a processor  120  for compiling information and processing data. System  100  also includes a control system  130  for executing programs to perform activation/deactivation of electrodes of DMF device  110  that manipulate microfluidic flow (e.g., create microfluidic channels). A graphic user interface (GUI)  140  is also provided for visually displaying microfluidic information to a user and receiving input from the user. System  100  includes a voltage amplifier  142  and a power source  144  to provide and amplify power delivered to the system, applying an electrostatic driving force for influencing microfluidics flow in DMF device  110 . System  100  can optionally include a portable sequencer  150  for, without limitation, bacterial identification and analysis of their genetically encoded antibiotic resistance genes. Components of system  100  may be readily assembled together, disassembled, and/or reassembled. System  110  is configured for rapid diagnosis of a disease (e.g., bacterial Sepsis) within a short period of time, for example, about 6 hours or less (e.g., about 5 hours or less, about 4 hours or less, about 3 hours or less, about 2 hours or less, about 1 hour or less, about 30 minutes or less, about 15 minutes or less, or about 10 minutes or less). 
     As shown in  FIG.  1   , DMF device  110  is a microfluidic chip (which also can be referred to as a platform). DMF device  110  includes a substrate having a planar surface that includes a plurality of discrete areas. The discrete areas are formed by an array of electrodes coated with a hydrophobic insulator. Each discrete area is formed by at least one electrode that can be readily activated, deactivated, and/or reactivated. Activation of the electrodes creates an electric current at the corresponding discrete region(s), which results in droplet movement, as desired, along the substrate. By using electric current to drive droplet movement, a DMF device can be configured to, based on electrowetting principles, rapidly move, mix, and separate liquid droplets that facilitates reliable, controllable liquid transport. In some embodiments, a DMD device provided herein can generate a plurality of fluidic channels on its substrate based on specific pathways formed by a given sequence of electrode activations and deactivations. 
     DMF device  110  can be configured to receive a liquid sample, such as a biological sample, a reagent, or a buffer. The liquid sample can be a biological sample, such as blood, saliva, plasma, serum, or the like. The liquid samples can be provided in the form of one or multiple droplets. In some embodiments, the substrate of DMF device  110  can receive the sample in one or more designated areas, such as a reservoir. The designated area may be labeled on the substrate, in some embodiments. 
     DMF device  110  can include one or more reservoirs, wherein each reservoir is configured to receive and hold an amount of liquid, such as a reagent, in excess of one droplet (e.g., an amount equivalent to 3 droplets, 4 droplets, 5 droplets, 10 droplets, 15 droplets, 20 droplets, 25 droplets, 30 droplets, 40 droplets, or 50 droplets or more). In some cases, the reservoirs can be configured to hold one or more liquids used for WGA and/or sequencing (e.g., nanopore sequencing), which will be discussed in later sections. 
     In some embodiments, a DMF device provided herein can include an array of electrodes coupled to the substrate, where the electrodes are configured for agitating, mixing, moving, and/or splitting a liquid sample on a substrate. For example, as shown in  FIGS.  2 A- 2 F , time-elapsed images of droplets show transport, merging and splitting on the substrate of a DMF device. Two droplets along the substrate can be moved ( FIGS.  2 A-C ) or merged ( FIG.  2 D ). Alternatively, a single droplet can be split to form multiple droplets ( FIGS.  2 E-F ). Droplet movement is driven by a series of electrode activation on or adjacent to the substrate that can be programmed through a graphic user interface. For example, rapid activation and deactivation of the same electrode can promote agitation of the liquid sample, while sequential activation and deactivation of adjacent electrodes can promote droplet movement in a desired direction along the substrate. The substrate can include visible markings (e.g., grid-like markings) to identify to the user the relative size and/or general location of the electrodes that make up the array. 
     DMF device  110  further includes one or more analytes immobilized on the substrate. Such an analyte can be selected based on its ability to bind to particular target cells to be removed from a sample. As shown in  FIGS.  3 A- 3 B , a blood droplet on a substrate of an exemplary DMF device can be moved across a portion of the substrate where analytes are immobilized. One or more analytes may be selected to bind with mammalian cells, for example, human cells. The analytes can be selected to bind with blood cells. In some embodiments, the analytes can be selected to bind with white blood cells, such as human white blood cells. In various embodiments, the analytes can be selected to bind with mammalian cells that have particular CD markers. A non-limiting example of a suitable analyte is an anti-CD45 antibody. Example of methods for using anti-CD45 antibodies for white blood cell capture in microfluidic devices are described elsewhere (see e.g., Gawk et al., “Progress in Circulating Tumor Cell Research Using Microfluidic Devices,” Micromachines  ( Basel ) 9(7):353 (July 2018); Lee et al., “An integrated microfluidic chip for one-step isolation of circulating tumor cells,”  Sensors and Actuators B: Chemical , vol. 238 (January 2017); and US Pat. Publication No. 2015/0260711, titled “Microfluidic Device For Cell Separation And Uses Thereof”), which are incorporated by reference in their entirety. In some embodiments, the analytes are configured to bind to about 1,000 to about 100,000 cells per droplet (e.g., about 5,000 to about 50,000 cells per droplet, about 7,000 to about 25,000 cells per droplet, or about 10,000 to about 15,000 cells per droplet). Inclusion of one or more target-cell-binding analytes can advantageously provide the DMF devices with improved detection of specific disease-causing bacteria, such as those associated with Sepsis, by removing select target cells from the sample before bioinformatic analysis is performed. 
       FIG.  4    shows a schematic platform of an exemplary DMF device. The schematic platform illustrates one or more functionalities provided by the substrate of the DMF device that facilitates a diagnosis of a disease. Three functionalities of the platform include cell separation, sample processing, and library construction (see also  FIG.  3 B ). Each functionality can be designated to occur at a specific region of the substrate, such as at a cell separation region, a processing region, and a library construction region. The cell separation region can include one or more areas of the substrate configured for removing specific human cells (e.g., white blood cells) from a biological sample (e.g., blood). The processing region can include one or more areas of the substrate configured for processing the biological sample. In some embodiments, the processing region can be designed to perform one or more sample processing steps that include, but are not limited to, bacterial nucleic acid (e.g., DNA) extraction, genome or nucleic acid amplification (e.g., WGA), and/or sequencing (e.g., nanopore sequencing) of the nucleic acid from the biological sample. 
     Incorporation of WGA functionality within a microfluidic device can be performed as described elsewhere (see e.g., Gorgannezhad et al., “Microfluidic-Based Nucleic Acid Amplification Systems in Microbiology,” Micromachines  10(7), 408 (July 2019); Yu et al., “Microfluidic Whole Genome Amplification Device for Single Cell Sequencing,”  Analytical Chemistry,  86, 19 (September 2014); and WIPO Publication No. WO 2017/205304A1, titled “Single cell whole genome amplification via micropillar arrays under flow conditions”, which are incorporated by reference in their entirety). 
     The library construction region can include one or more areas of the substrate configured for compiling data collected from the processing region. Any appropriate method can be applied to incorporate and use a DNA library preparation functionality within a microfluidic device, including those methods described elsewhere (see e.g., Kim et al., “A Microfluidic DNA Library Preparation Platform for Next-Generation Sequencing,”  PloS One  (July, 2013); and US Application Publication No. US 2013/0225452, titled “Method of Preparing a Nucleic Acid Library”, which are incorporated by reference in their entirety). In various embodiments, the devices provided herein can be configured for providing library transfer to a portable sequencer, for example, as described elsewhere (e.g., U.S. Patent Application Publication No. 2013/0225452). Commercial portable sequencers are available, such as MinION, which is manufactured by Oxford Nanopore Technologies. In some embodiments, a DMF device provided herein can include multiple cell separation, processing, and library construction regions. In some embodiments, a DMF device provided herein can be configured to perform cell separation, processing, and library construction without the use of any designated regions on the substrate. In some embodiments, each processing region can be located within a distinct area of the substrate that is exclusive to other regions. 
     In some embodiments, the device provided herein includes a substrate that includes a first location with one or more immobilized analytes, a second location, and a third location, and an array of electrodes configured to move a biological sample of a mammal from the first location to the second location and from the second location to the third location, The first location can be configured to capture at least some cells from the sample via the one or more immobilized analytes to form a cell-free sample. In some embodiments, the cell-free biological sample includes about 100 cells per droplet to about 10,000 cells per droplet (e.g., about or less than 7,000 cells per droplet, about or less than 5,000 cells per droplet, about or less than 3,000 cells per droplet, about or less than 1,000 cells per droplet, about or less than 500 cells per droplet, about 100 to about 1000 cells per droplet, about 1000 to about 3000 cells per droplet, about 3000 to about 5000 cells per droplet, or about 5000 to about 10,000 cells per droplet). In some embodiments, the cell-free biological sample contains less than 5×10 9  cells per liter (cells/L). In some embodiments, the cell-free biological sample contains from about 1×10 3  cells/L to about 3×10 9  cells/L (e.g., less than 1×10 9  cells/L, less than 1×10 6  cells/L, about or less than 1×10 3  cells/L, about 1×10 3  to about 1×10 4  cells/L, about 1×10 4  to about 1×10 5  cells/L, about 1×10 5  to about 1×10 6  cells/L, about 1×10 6  to about 1×10 7  cells/L, about 1×10 7  to about 1×10 8  cells/L, or about 1×10 8  to about 1×10 9  cells/L). 
     The second location can be configured to receive a cell-free sample and one or more reagents for performing WGA to generate an amplified sample. The third location can be configured to receive the amplified sample and one or more reagents for performing library construction to form a sequencing ready sample. 
     In some cases, the DMF devices provided herein can be used for diagnosing a disease (e.g., Sepsis) by performing the following steps. A biological sample (e.g., blood) is placed on a substrate of the DMF device. The sample may be placed in a designated receiving region of the substrate, such as a reservoir electrode. The biological sample can be in the form of one or more droplets. 
     The received sample is then pretreated by moving the sample droplet across a pretreatment region having one or more immobilized analytes (e.g., anti-CD45 antibodies) configured to bind to target cells within the biological sample. The sample may be agitated in the pretreatment region to promote cell binding, which can promote target cell removal from the sample. Cell binding agitation can occur for about 1 second to about 10 minutes (e.g., from about 5 seconds to about 60 seconds, from about 1 minute to about 5 minutes, or from about 5 minutes to about 10 minutes). After cell-binding has taken place, a cell-free sample can be further processed for bioinformatic analysis. 
     To facilitate bioinformatics analysis, the sample can be combined with at least one liquid agent in one or more mixing steps to facilitate WGA or library construction. Exemplary liquid agents can include a lysis buffer, a stop solution, a polymerase solution (e.g., a solution containing a DNA polymerase), a fragmentation mixture, a rapid adapter mixture, or any combination thereof. 
     Potential bacteria within the sample can be lysed using any suitable method. For example, a lysis buffer may be mixed with the sample for lysing. In some embodiments, suitable lysis buffers include one or more active agents including, without limitation, enzymes, alkalines (e.g., NaOH or other solutions with a pH&gt;7), dithiothreitol or the like, and any combination thereof. Commercial lysis buffers are also available in Repli-G single cell kits, which are manufactured by Qiagen N.V. In some embodiments, the lysis buffer can include from about 10 μ/L to about 500 U/μL (e.g., about 20 U/μL to about 400 U/μL, about 50 U/μL to about 300 U/μL, about 100 U/μL to about 300 U/μL) active agent. In some embodiments, the lysis buffer can include from about 10 mM to about 500 mM (e.g., about 20 mM to about 400 mM, about 50 mM to about 300 mM, about 100 mM to about 300 mM) active agent. 
     In some embodiments, after a lysis buffer has been introduced to the sample, the sample can be mixed with a stop solution to stop enzymatic activity by, for example, denaturing the enzyme used for lysis. Non-limiting examples of a stop solution can include solutions containing sodium dodecyl sulfate (e.g., 3% (w/v) sodium dodecyl sulfate), or commercially available stop solutions (e.g., stop solution in kits provided by ThermoFisher Scientific Co. or stop solutions available in Repli-G single cell kits, which are manufactured by Qiagen N.V.). Suitable stop solutions include, but are not limited to, solutions containing acids, such as HCl, to neutralize the lysis buffer. The sample can be agitated with the stop solution for any suitable time, for example, about 1 minute to about 10 minutes or more (e.g., about 2 minutes, 3 minutes, 4 minutes, 5 minutes, 6 minutes, 7 minutes, 9 minutes, about 10 minutes or more, about 1 to about 3 minutes, about 3 to about 5 minutes, about 5 to about 7 minutes, or about 7 to about 10 minutes). 
     The lysed, cell-free sample can also be mixed with a solution containing at least one DNA polymerase for enzymatic synthesis of DNA from deoxyribonucleotides for WGA. Commercial DNA polymerases for enzymatic synthesis of DNA from deoxyribonucleotides for WGA can be found, for example, in Repli-G single cell kits, which are manufactured by Qiagen N.V. In some embodiments, the sample can be mixed with a solution containing at least one DNA polymerase for PCR-based WGA. In some embodiments, the sample can be mixed with a solution containing at least one DNA polymerase solution for multiple displacement amplification WGA. The sample can be agitated with at least one DNA polymerase solution for any suitable time, for example, about 1 hour to about 5 hours (e.g., about 2 hours, 3 hours, 4 hours, about 5 hours or more, about 1 to about 2 hours, about 2 to about 3 hours, about 3 to about 4 hours, or about 4 to about 5 hours). 
     The lysed, cell-free sample can also be mixed with a fragmentation mixture and subjected to a thermocycling process. Suitable fragmentation solutions include any agent that can break long strands of DNA into shorter pieces. Fragmentation solutions are available in Qiagen Repli-G single cell kits, for example. In some embodiments, the fragmentation solution contains one or more enzymes suitable for fragmenting DNA strands. The sample can be agitated with a fragmentation mixture for about 5 seconds to about 10 minutes or more (e.g., about 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 1 minute, about 2 minutes, 3 minutes, 4 minutes, 5 minutes, 6 minutes, 7 minutes, 9 minutes, about 10 minutes or more, about 10 to about 30 seconds, about 30 seconds to about 1 minute, about 1 to about 3 minutes, about 3 to about 5 minutes, about 5 to about 7 minutes, or about 7 to about 10 minutes). The thermocycling process can include a first heating step at a first temperature (e.g., about 20-40° C.), followed by a second heating step at a second temperature (e.g., about 70-90° C.), followed by a rapid cooling step (e.g., cool sample with ice). Each thermocycling step can last about 30 seconds to about 5 minutes or more (e.g., about 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes or more, about 30 seconds to about 1 minute, about 1 to about 2 minutes, about 2 to about 3 minutes, about 3 to about 4 minutes, or about 4 to about 5 minutes). 
     The lysed, cell-free sample can be further mixed with a rapid adapter mixture. Commercial rapid adapter mixtures can be found in Repli-G single cell kits, which are manufactured by Qiagen N.V. The sample can be agitated with a rapid adapter mixture for about 5 seconds to about 10 minutes or more (e.g., about 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 1 minute, about 2 minutes, 3 minutes, 4 minutes, 5 minutes, 6 minutes, 7 minutes, 9 minutes, 10 minutes or more, about 10 to about 30 seconds, about 30 seconds to about 1 minute, about 1 to about 3 minutes, about 3 to about 5 minutes, about 5 to about 7 minutes, or about 7 to about 10 minutes). The thermocycling process can include a first heating step at a first temperature (e.g., about 20-40° C.), followed by a second heating step at a second temperature (e.g., about 70-90° C.), and followed by a rapid cooling step (e.g., cool sample with ice). Each thermocycling step can last about 30 seconds to about 5 minutes or more (e.g., 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes or more, about 30 seconds to about 1 minute, about 1 to about 3 minutes, or about 3 to about 5 minutes). 
     The ratio of the amount of sample combined with any of the liquid agents discussed herein can range from 1:10 to about 10:1 (e.g., about 1:9, 1:8. 1:7, 1:6, 1:5, 1:4, 1:3, 1:2, 1:1, 2:1, 3:1, 4:1, 5:1, 6:1, 7:1, 8:1, or 9:1). For example, in some embodiments, a 1 μL droplet of blood may be mixed with 1 μL droplet of a lysis buffer, 1 μL droplet of a stop solution, 6 μL of DNA polymerase, 1 μL droplet of fragmentation mix, and 1 μL droplet of rapid adapter, respectively, in a DMF device. Any appropriate method can be applied to perform WGA using the systems and devices provided herein, including methods described elsewhere (see e.g., Gorgannezhad et al., supra; Yu et al., supra; and WIPO Publication No. WO 2017/205304 A1, which are incorporated by reference in their entirety). 
     Any appropriate method can be applied to incorporate and use a DNA library preparation functionality within the systems and devices provided herein, including techniques described elsewhere (see e.g., Kim et al., supra); and US Application Publication No. US 2013/0225452). 
     Examples 
     Example 1. Bacterial Reads on Blood Sample 
     Direct nanopore sequencing was conducted on a human blood sample to obtain baseline results on detectable bacterial reads (see Table 1 below). A clinical blood sample from a patient with myocardial infection was directly sequenced, and only 0.0347% of the total 302,604 reads were detected as bacteria, while the vast majority of reads appeared to be from human components. Direct nanopore sequencing was performed on 1 mL of blood sample spiked with 1,000 and 10,000  E. coli  cells, respectively, but resulted in a very low number of bacterial reads. 
     
       
         
           
               
               
               
               
               
               
             
               
                 TABLE 1 
               
               
                   
               
               
                   
                 Total 
                   
                   
                 Total 
                 Total 
               
               
                   
                 raw 
                 Human 
                 Bacterial 
                 human 
                 bacterial 
               
               
                 Sample 
                 reads 
                 reads 
                 reads 
                 reads 
                 reads 
               
               
                   
               
             
            
               
                   
               
            
           
           
               
               
               
               
               
               
            
               
                 Blood (myocardial infarction) 
                 302604 
                 99.80% 
                 0.03% 
                 301998 
                 105 
               
               
                 Blood spiked with 1,000  E. coli   
                 9006 
                 96.40% 
                 0.04% 
                 8682 
                 3 
               
               
                 Blood spiked with 10,000  E. coli   
                 4957 
                 98.90% 
                 0.26% 
                 4902 
                 12 
               
               
                   
               
            
           
         
       
     
     The results of the sequencing data were not suitable for downstream bioinformatic analyses, and thus would not lead to the detection of bacteria. It was reported that when a patient begins to show clinical symptoms of Sepsis, the concentration of bacteria in blood is very low (only 1 to 100 CFU/mL in adults and &lt;10 CFU/mL in neonates). Therefore, the infectious agents would remain undetected using direct sequencing. 
     Example 2. Bacterial Reads on a Blood Sample Using a DMF Device 
     The following procedure was used to prepare a blood sample for determining the bacterial reads associated with using a DMF device. 
     1. A 1 μL droplet of human blood was placed on the reservoir electrode using a pipette. 
     2. The blood droplet was moved to the electrode with anti-CD45 antibodies, and the droplet was agitated by turning on and off the electrode. 
     3. A 1 μL droplet of lysis buffer containing lysozyme, alkaline (e.g., NaOH or another solution with a pH&gt;7), and dithiothreitol was mixed with the blood droplet by agitating through turning on and off the electrodes for 3 minutes. 
     4. A 1 μL droplet of stop solution containing HCL was mixed into the sample by turning on and off the electrodes for 3 minutes. 
     5. DNA polymerase (6 μL; Qiagen Repli-G single cell kit) was mixed with the sample by agitating for 2 hours. 
     6. A 1 μL droplet of fragmentation mix (Qiagen Repli-G single cell kit) was mixed into the sample by agitation using the electrodes for 1 minute. The device was placed on a heating plate at 30° C. for 1 minute, followed by 80° C. for 1 minute. The device was then placed on ice for 1 minute. 
     7. A 1 μL droplet of rapid adapter mixture was added into the sample and mixed electrode agitation for 5 minutes. 
     8. The sample was moved to the collection electrode, and a pipette was used to transfer the sample for loading into a MinION Nanopore sequencer (Oxford Nanopore Technologies). 
     Following the steps described above, WGA was performed on 0.5 ng lambda DNA (equivalent to the genomic material in ˜10,000  E. coli  cells) in a DMF device. 
     The results showed that the number of reads of the target strains drastically increased and were within an acceptable range (e.g., a minimum range value of at least 2,000-3,000 reads) for performing bioinformatic analyses, as shown in Table 2. 
     
       
         
           
               
               
               
             
               
                   
                 TABLE 2 
               
               
                   
                   
               
               
                   
                 name 
                 numReads 
               
               
                   
                   
               
             
            
               
                   
               
            
           
           
               
               
               
            
               
                   
                 
                   Escherichia coli 
                 
                 109378 
               
               
                   
                 synthetic construct 
                 34121 
               
               
                   
                   Escherichia coli  ‘BL21-Gold(DE3)pLysS AG’ 
                 5006 
               
               
                   
                 
                   Escherichia 
                 
                 4138 
               
               
                   
                 
                   Enterobacteriaceae 
                 
                 1927 
               
               
                   
                 
                   Escherichia albertii 
                 
                 972 
               
               
                   
                   Escherichia coli  B 
                 772 
               
               
                   
                   
               
            
           
         
       
     
     Example 3—Amplification and Sequencing of 10 Femtograms of Bacterial DNA within 3 Hours Using a DMF Platform 
     Materials and Methods 
     Cell Culture and DNA Extraction 
       Corynebacterium glutamicum  ATCC 13032 was cultured in LB broth (Research Product International) at 37° C. in a shaker incubator (Thermo Fisher).  Porphyromonas somerae  ATCC BAA1230 was cultured in chopped meat carbohydrate broth (DB) at 37° C. in an anaerobic chamber (Coy). Both cultures were harvested during log phase (˜10 7 /mL) and pelleted at 10,000 g for 3 minutes at 4° C., followed by supernatant removal. DNA was extracted using DNeasy Powersoil Kit (Qiagen) following the manufacturer&#39;s instructions. Extracted  C. glutamicum  and  P. somerae  DNA was diluted to 100 pg/μL, 10 pg/μL, 1 pg/μL, 100 fg/μL and 10 fg/μL in nuclease-free water (Ambion).  Escherichia coli  bacteriophage lambda DNA was included in the Oxford Nanopore Technologies Rapid Sequencing Kit (ONT, SQK-RAD004). DNA mixture samples were produced by diluting and mixing the extracted DNA from these three species. 
     DMF Device Microfabrication 
     The DMF device layout was designed in AutoCAD (Autodesk), and the electrode contact pads were placed to fit into a DropBot system (Fobel et al.,  Applied Physics Letters  102(19): 193513, 2013). The DMF device was microfabricated on a 2″×3″ glass slide pre-coated with a 200 nm chromium layer, with an AZ1500 photoresist layer (Telic Company) as a bottom plate, and an indium-tin oxide (ITO)—coated glass slide (Delta Technologies) used as a top plate. The electrodes were photolithographically patterned on the bottom plate in a mask aligner (KLOE), developed in 1:4 MF 351 developer (Microposit) and etched in CR-Chrome Etch (KMG Electronic Chemicals). Each interdigitated electrode was 2.2 mm×2.2 mm in size. The bottom plate was coated with 5 μm Parylene C (Specialty Coating Systems). 1 mm through-holes were drilled (MicroLux) on the top plate as inlets and outlets of the device. The patterned side of the bottom plate and the ITO side of the top plate were spin coated (1000 rpm, 60 seconds) with 2.25% type M fluoropolymer CYTOP solution (Bellex International Corporation) and incubated on a hotplate at 180° C. for 15 minutes. A copper tape (76.2 μm thick) and an electrically conductive adhesive transfer tape (3M, 102 μm thick) were used as spacers between the top and bottom plates. All sides of the device were sealed using epoxy glue and incubated for an hour at room temperature. 
     DMF Experimental Setup 
     The overall workflow of using the DMF platform for rapid low-abundance bacterial WGA and MinION sequencing is illustrated in  FIG.  6   . Briefly, the DMF device was operated by a Dropbot system (Sci-bot Inc.; Fobel et al., supra) that consisted of electrical circuitry compacted into a portable black case (5.7″×4″×3″). The Dropbot system was connected to a laptop through USB cable (see, e.g.,  FIG.  5   ) to control the DMF device via MicroDrop software. A 2″×3″ DMF device was inserted into the Dropbot system, where the user can set parameters (e.g., voltage, frequency, timing) to operate the DMF device to perform droplet transport, splitting and mixing in a programmed manner based on electrowetting principles (Cho et al., J  Microelectromech Syst  12 (1):70-80, 2003). 
     The structure of the DMF device is illustrated in  FIGS.  3 A,  3 B,  7 A, and  7 B . Overall, the device was composed of a bottom glass substrate patterned with chromium electrodes and an ITO-coated glass substrate as a top plate. The two substrates were connected through double-sided electrically conductive tape and copper tape as the spacer layer ( FIG.  7 A ). The device was pre-filled with OS-30 silicone oil (Dow Corning) prior to loading aqueous samples and was operated at 80V RMS  at 1k Hz, while the ITO glass was connected to electrical ground. Fluids were transferred into the device by pipetting through the drilled inlets on the top plate and onto the electrically activated reservoir electrodes ( FIG.  7 B ). To avoid cross-contamination, different samples were introduced onto different reservoir electrodes. Each square electrode in the matrix could hold ˜1 μL droplet. The final product was transported to an unused reservoir electrode, and transferred out of the device by pipetting. All supplies and reagents were filtered (0.2 μm), autoclaved or UV-sterilized, except for DNA polymerase and library preparation reagents. All samples and reagents used into the DMF device except library preparation reagents contain a final volume of 0.1% v/v poloxamine detergent Tetronic 90R4 (Octochem) to enhance droplet movement and minimize biofouling (Rackus et al.,  Lab on a Chip  17 (13):2272-2280, 2017; and Leipert and Tholey,  Lab on a Chip  19 (20):3490-3498, 2019). 
     Bacterial WGA and Library Preparation in DMF Device 
     A REPLI-g Single Cell Kit (Qiagen) was used for bacterial WGA. The kit contained DNA denaturing buffer (D2), neutralization buffer, and DNA polymerase. Briefly, 1 μL droplet of bacterial DNA and 1 μL droplet of D2 buffer were mixed in the device and incubated at room temperature for 3 minutes. A 1 μL droplet of neutralization buffer was added to the sample and incubated for 10 minutes to terminate DNA denaturing process. 9 μL of the DNA polymerase was introduced into the device to mix with the sample. The sample was incubated at room temperature for 2 hours, while the electrodes were programmed to turn on and off alternately in a constant manner to agitate the droplets to enhance mixing and thus amplification efficiency. To terminate amplification, the DMF device was taken out of the Dropbot system and incubated at 65° C. on a hotplate for 3 minutes, and was then placed on ice for 1 minute before sliding it back into the Dropbot system. The same procedure was used for amplifying DNA from  C. glutamicum  of different concentrations as well as DNA mixture samples. 
     A Rapid Sequencing Kit (ONT, SQK-RAD004) was used for library preparation in the DMF device and sequencing using a MinION. Three (3) μL of fragmentation reagent (FRA) were introduced into the device and mixed with the sample. The device was then incubated on a hotplate at 30° C. for 1 minute followed by 80° C. for 1 minute, and was then briefly placed on ice. One (1) μL of rapid adapter (RAP) was added to the sample in the device, and the mixture was incubated at room temperature for 5 minutes. As the aqueous fluid was within ambient silicone oil, evaporation was not observed. The sample was moved to an unused reservoir electrode and transferred out of the device into a 0.2 mL microcentrifuge tube. DNA was quantified using Qubit assay. 
     Bacterial WGS in MinION Sequencer 
     A FLO-MIN106D flow cell was primed and the sample prepared for loading according to the manufacturer&#39;s instruction. Briefly, 11 μt DNA library, 4.5 μL nuclease-free water, 34 μL sequencing buffer and 25.5 μL loading beads were added into a qPCR tube in a sequential manner and mixed. The final 75 μL sample was immediately loaded into the flow cell sample port in a drop-wise manner to avoid bead aggregation. The sample port, priming port and MinION lid were then closed. The MinION sequencer was controlled by MinKNOW software that performs data acquisition, real-time DNA quality analysis and basecalling. Reads that passed quality filters after basecalling were stored in time-stamped fast5 and fastq files, with 4,000 reads in each of the latter. 
     Bioinformatics Post-Processing 
     For Oxford Nanopore reads, adapter sequences were removed from the raw reads using Porechop v0.2.4 (Wick et al.,  Microbial Genom  3 (10), 2017). The fastq files were then concatenated based on their time stamps, and reads mapped using Minimap2 v2.17 (Li,  Bioinformatics  34 (18):3094-3100, 2018) to a reference genome of  C. glutamicum  ATCC 13032 in NCBI genome database (RefSeq assembly accession GCF_000011325.1). Mapped reads were coordinate-sorted using samtools v1.8 (Li et al.,  Bioinformatics  25 (16):2078-2079, 2009). All processed sequences were visualized in Integrative Genomics Viewer (v.2.8.0) (Robinson et al.,  Nature Biotechnol  29 (1):24-26, 2011). For the profiling of taxonomy, reads with adapter removed were processed using BBDuk entropy filtering from the BBMap tool set v38.69 (Bushnell et al.,  PloS One  12 (10):e0185056, 2017) to mask low complexity regions of the reads. Then, reads were profiled using Centrifuge v1.0.4 (Kim et al.,  Genome Res  26 (12):1721-1729, 2016), using a database based on NCBI RefSeq complete genomes from Bacteria, Archaea and Viruses (as of October 2018), as well as human genome hg38 and mouse genome GRCm38. Taxonomy calls were reported only of their Centrifuge score was larger than 150. The taxonomy pipeline was implemented using Nextflow v19.10.0 (Di Tommaso et al.,  Nature Biotechnol  35 (4):316-319, 2017). As a clarification, Centrifuge was used to test for the presence of amplified DNA from the target organism and to survey putative environmental contaminants in the sample. The database used RefSeq genomes marked as “complete” (as opposed to contigs or scaffolds only) from Bacteria, Archaea and Viruses. The per-read score in Centrifuge is roughly the sum of the square of the k-mer lengths of the matching segments in a read. A threshold of 150 can be interpreted as a matching segment of length 27 bp. 
     Results and Discussion 
     In-Tube WGA and Sequencing Quality Control 
     A set of  C. glutamicum  DNA WGA experiments was performed in 0.2 mL microcentrifuge tubes and DMF devices followed by MinION sequencing as a comparative study. Each WGA experiment was repeated 3 times, with one replicate randomly selected from each sample set for sequencing. For in-tube experiments, 2 hours of WGA showed success for samples with 100 pg, 10 pg and 1 pg starting DNA, generating an average of 3.3 μg, 832 ng and 120 ng DNA ( FIG.  8 A ). After a 30 minute sequencing run, &gt;20 Mb data was generated and ready for processing ( FIG.  8 B ). Samples with higher amounts of starting DNA led to larger amounts of DNA available for sequencing after WGA, and thus more data was generated. The amount of DNA obtained between these samples was significantly different from each other (p&lt;0.005). During sequencing, DNA sequences with quality score (Qscore)&lt;7.0 were filtered and discarded; over 85% of reads passed quality checks with a medium Qscore of 9.6 ( FIG.  8 C ). The Qscore threshold was the default setting of the basecaller for the MinION sequencing platform. Due to constant advancement in sequencing technology and bioinformatic tools, the basecalling accuracy has continuously improved for the same raw signal. In this work, the per-read nucleotide identity to the reference  C. glutamicum  genome rarely dropped below around 89%. 
     For samples with 100 fg and 10 fg starting DNA, however, only about 4 ng DNA was generated after 2 hours of WGA, with no data generated with 30 minutes of sequencing. The amount of DNA obtained after amplification was not significantly different between samples or compared with the negative control (p=0.3-0.35). Extending sequencing time to 120 minutes led to only about 0.2 Mb data output. These results demonstrated that DNA can be sufficiently amplified in-tube for rapid MinION sequencing if the sample contains at least 1 pg starting DNA, but in-tube WGA is not suitable for processing samples with femtograms of starting DNA for rapid sequencing due to the low post-amplification DNA amount. 
     To test the utility of amplifying femtograms of DNA in-tube for an extended time, 10 fg and 100 fg DNA were amplified for up to 4 hours with three replicates each. For samples with 10 fg starting DNA, only one replicate had a measurement of ˜9 ng DNA after amplification, while the other two replicates were below the detection limit of Qubit assay (High Sensitivity). For samples with 100 fg starting DNA, an average of ˜11 ng amplified DNA was obtained, but all failed sequencing. These tests showed the advantage of using DMF device for amplifying minute amounts of DNA in a relatively rapid manner. 
     On-Chip WGA and Sequencing Quality Control 
     Five different starting amounts of  C. glutamicum  DNA, ranging from 100 pg to 10 fg, were amplified in a DMF device followed by on-chip library preparation and MinION sequencing. Each on-chip WGA was repeated 3 times, with one replicate randomly selected from each sample set for sequencing. After performing WGA in the DMF device for 2 hours, samples with 100 pg were amplified to an average of 1.7 μg DNA ( FIG.  8 A ), significantly higher (p=0.01) than the samples with 10 pg and 1 pg starting DNA (˜1.1 μg and 933 ng). For samples with 100 fg and 10 fg starting DNA, the average amplified DNA was about 400 ng and about 118 ng, respectively (p&lt;0.005). 
     To test the feasibility of obtaining sufficient DNA within a minimal time, the on-chip WGA experiments were repeated with reduced amplification time ( FIG.  8 A ). For samples with 100 pg and 10 pg starting DNA, the average DNA after 1 hour of amplification was 367 ng and 164 ng, respectively (p=0.04); while for the samples with lower starting DNA amounts, amplified DNA was within the range of negative control (p=0.3) or below the detection limit of the High Sensitivity Qubit assay. Further reducing on-chip amplification time to 0.5 hour led to only ˜7 ng DNA for samples with 100 pg starting DNA, while the DNA amount in the rest of the samples was below the Qubit assay detection limit. Therefore, to obtain the minimum amount of DNA needed for downstream rapid sequencing from as low as 10 fg starting DNA, the minimum time for DNA amplification was determined to be 2 hours. However, the time for DNA amplification can be increased to achieve larger amount of amplified DNA, if necessary. 
     For samples with all five starting DNA amounts amplified on-chip for 2 hours, the first fastq files were generated within 20-30 minutes after sequencing started, with each of the fastq file containing about 20 Mb data (4000 reads) with a medium Qscore of 9.5; 65-90% sequenced reads passed quality check ( FIGS.  8 C and  8 D ). These generated fastq files were immediately sent to the taxonomy calling pipeline to identify the bacterial species, which takes about 10 minutes. Extending sequencing to 2 hours generated multiple fastq files that were concatenated and processed in the same manner. As a comparison, samples amplified for 1 hour and 0.5 hour on-chip with a detectable range of DNA were also sequenced ( FIGS.  8 C and  8 D ). These samples had low amounts of DNA and insufficient high-quality DNA; the percentage of sequencing reads passing quality check was low and required extended sequencing time to obtain minimal data (˜0.5 Mb). Since the aim of this work was to achieve bacterial identification with 30 minutes of sequencing in a reliable manner, samples amplified on-chip that were below the detection limit of Qubit assay were not sequenced. 
     Contamination profile in MinION sequencing 
     Contaminants detected by MinION sequencing are shown in  FIGS.  9 A and  9 B . For the 100 pg  C. glutamicum  DNA amplified on-chip, the target species was reliably detected after 30 minutes of sequencing, with 3900  C. glutamicum  reads and &lt;10 contaminant reads. Extending the sequencing time led to a higher number of  C. glutamicum  reads, with the number of reads doubling every 30 minutes. 120 minutes of sequencing generated about 5 times more  C. glutamicum  reads than 30 minutes of sequencing; the number of reads of the contaminants also increased by about 5 times but still remained low overall (&lt;50 reads) ( FIG.  9 A ).  FIG.  9 B  shows the contamination profile within 30 minutes of sequencing for samples with different amount of starting DNA amplified for 2 hours on-chip and in-tube. Despite the contaminants present in the samples sequenced, the target species displayed at least 10× higher number of reads. 
     Possible contaminating sources include the original culture, reagent and airborne contaminants, human-related contamination, and equipment sources.  Homo sapiens  is reported as an expected contamination in whole genome amplification (Hammond et al.,  Microbiome  4 (1):52, 2016). Contamination can be introduced at any stage of the process, including initial cell cultivation, handling, experimentation, sample transfer, library preparation, and sequencing. Among the reads of the contaminants,  Cutibacterium acnes  reads appeared higher than other contaminants; this species is commonly found on human skin (Lewin et al., Ann Rev Microbiol 70:235-254, 2016; and Platsidaki and Dessinioti,  F 1000Research 7, 2018). A low percentage of contaminant reads appeared as  Corynebacterium . This is likely due to the low quality of some  C. glutamicum  reads that could not be called beyond genus level, and therefore were not assigned to the target species. To investigate the level of contamination of reagents, negative control samples (sterile PBS) amplified in-tube and on-chip for 2 hours were sequenced.  C. glutamicum  and  E. coli  lambda virus DNA was detected in these negative control samples, but at a low amount. To investigate if the cross-contamination stemmed from the original DNA samples, direct sequencing was performed on the extracted  C. glutamicum  DNA,  P. somerae  DNA, and  E. coli  lambda DNA, respectively, without amplification. The results showed that there was no cross-contamination of any of the three species in the original samples. 
     Coverage of MinION Sequenced Reads 
     Raw reads were mapped to the reference genome of  C. glutamicum  ATCC 13032 after adapters were removed ( FIG.  10   ). As a general trend, samples with higher starting DNA amounts showed more genome coverage after 30 minutes of sequencing (Table 3). For samples with picograms of starting DNA, those that were amplified in-tube showed more complete genome coverage than those amplified on-chip. However, for samples with femtograms of starting DNA, not enough DNA was obtained for rapid MinION sequencing with in-tube amplification. Therefore, to obtain sufficient DNA from samples with low DNA amounts in a rapid manner, it is essential to enhance amplification efficiency by implementing constant mixing strategies. For samples amplified on-chip, higher amounts of starting DNA led to increased genome coverage. About 76.7% genome coverage was achieved for the sample with 100 pg starting DNA, but genome coverage decreased as the amount of starting DNA decreased. It is noted that three replicates were sequenced for samples with femtograms of starting DNA, as this is the range that DMF-based amplification is advantageous over in-tube amplification. 
     
       
         
           
               
             
               
                 TABLE 3 
               
             
            
               
                   
               
               
                 Genome coverage of  C. glutamicum  DNA 
               
               
                 after 30 minute sequencing in MinION 
               
            
           
           
               
               
               
               
               
               
            
               
                   
                 100 pg 
                 10 pg 
                 1 pg 
                 100 fg 
                 10 fg 
               
               
                   
                   
               
            
           
           
               
               
               
               
               
               
            
               
                 In-tube 
                 74.5% 
                 58.6% 
                 50.0% 
                 N/A 
                 N/A 
               
               
                 On-chip 
                 76.8% 
                 43.6% 
                 16.9% 
                 18.6% (±1.5%) 
                 10.5% (±5.0%) 
               
               
                   
               
            
           
         
       
     
     Despite the relatively low genome coverage for samples with as low as 10 fg starting DNA (equivalent to the amount of DNA within a single bacterial cell), the genome sequence was unique enough to identify the bacterial strain. Individual reads also can be taxonomically assigned, furthering the certainty of the call. However, the accuracy can vary for different microbial species, depending on the extent of their representation in genomic databases. Taken into consideration hands-on time, including flow cell priming, sample loading and running the sequencing data through the taxonomy calling pipeline, it was feasible to keep sample-to-answer time within 3 hours. Such a rapid turnaround time for bacterial identification is especially essential in urgent medical situations involving bacterial infections such as Sepsis, as timely diagnosis can lead to effective and targeted treatment in a prompt manner. It is noted that in some cases, a lysis buffer effective for lysing single bacterial cells for microfluidic-based whole genome amplification is used, including buffers adapted from those described elsewhere (see, e.g., Liu et al.,  Micromachines  9 (8):367, 2018). Such a buffer can provide the ability to effectively lyse low-abundance bacterial cells without compromising DNA quality. 
     Rapid WGA and Sequencing of Multiple Bacterial Species 
     The method described herein was tested for its ability to detect multiple bacterial species. In these experiments, samples with  C. glutamicum  DNA,  P. somerae  DNA, and  E. coli  bacteriophage lambda DNA were used, with starting DNA amounts ranging from 1 pg to 10 fg in randomly generated combinations. As indicated in  FIGS.  11 A- 11 C , it was possible to detect all three species if the amount of starting DNA between these species did not differ by more than 10×. In these cases, the number of reads for all three species was more than 8-fold higher than the number of contaminating reads, therefore reliably detecting the presence of these species within the samples. However, when the initial amount of  E. coli  bacteriophage lambda DNA exceeded the amounts of  C. glutamicum  DNA and  P. somerae  DNA by more than 20-fold, the number of reads of  C. glutamicum  and  P. somerae  fell within the range of contaminating reads and thus remained undetected ( FIG.  11 D ). 
     To determine whether low-abundance bacterial cells could be effectively lysed without compromising DNA quality, 1 μL of cultured  C. glutamicum  cells at a concentration of 10 3  cells/mL was tested in the device, following a protocol for amplifying purified DNA. Amplified products were below the detection limit of High Sensitivity Qubit assay, possibly due to lack of lysis. To improve the efficiency of bacterial lysis, cells were incubated for 15 minutes at 37° C. in a custom lysis buffer (Liu et al., supra) containing 100 mM DTT and 200 U/μL lysozyme. Results showed amplification of  C. glutamicum  cells at a single cell level, with the number of sequenced reads showing larger variability between amplification tests compared with amplified purified DNA ( FIG.  7 A ), perhaps due to cell-to-cell variability of  C. glutamicum  lysis. Nevertheless, the number of  C. glutamicum  reads was ˜100-fold higher than contaminant reads, from which they were easily distinguished. 
     To investigate the possibility of rapid detection of bacteria in the presence of human cells, samples of cultured  C. glutamicum  were tested alone or mixed with human KLE cells. No  C. glutamicum  sequencing reads were detected when the two were mixed at a 100:1 ratio for amplification, but when the ratio of  C. glutamicum  to KLE cells was increased to 500:1, about 30  C. glutamicum  sequencing reads were detected (about 100 times lower than the number of  Homo sapiens  reads;  FIG.  12   ). To enable detection of bacterial cells in clinical samples, as many human cells as possible should be removed prior to amplification and sequencing. This can be achieved using strategies such as dielectrophoretic separation (Chen et al.,  Micromachines  11(7):700, 2020; and Zhang et al.,  Micromachines  10(6):423, 2019), deterministic lateral displacement (Hochstetter et al.,  ACS nano  14(9):10784-10795, 2020; and McGrath et al.,  Lab on a Chip  14(21):4139-4158, 2014), and/or microfiltration (Shields et al.,  Lab on a Chip  15(5):1230-1249, 2015) into microfluidic platforms. At the current stage, we focused on rapid amplification of minute amounts of bacterial DNA with minimal contamination. Future efforts will be centered on whole genome amplification of low-abundance bacterial cells and integration of the aforementioned human cell depletion into the to improve sensitivity and potential clinical applications. 
     Taken together, the studies described herein utilized novel technologies including palm-sized DMF devices and MinION sequencer to support a 2 hour amplification of as little as 10 fg bacterial DNA (equivalent to the amount of DNA in a single bacterial cell) with high purity, yielding bacterial species identity with 30 minutes of sequencing. This approach also showed success in identifying bacterial species within samples with multiple bacteria in a rapid manner. Thus, bacterial species were identified using WGS from samples harboring femtograms of DNA within 3 hours, with minimal contamination. 
     OTHER EMBODIMENTS 
     It is to be understood that while the invention has been described in conjunction with the detailed description thereof, the foregoing description is intended to illustrate and not limit the scope of the invention, which is defined by the scope of the appended claims. Other aspects, advantages, and modifications are within the scope of the following claims.