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Culture-Independent Method for Screening and Identifying Microbial Enzyme-Encoding Genes Using Microdroplet-Based Single Cell Genomics K

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Culture-Independent Method for Screening and Identifying Microbial Enzyme-Encoding Genes Using Microdroplet-Based Single Cell Genomics K CULTURE-INDEPENDENT METHOD FOR SCREENING AND IDENTIFYING MICROBIAL ENZYME-ENCODING GENES USING MICRODROPLET-BASED SINGLE CELL GENOMICS K. Nakamura1, R. Iizuka1*, T. Yoshida2, Y. Hatada2, Y. Takaki2, S. Nishi2, A. Iguchi3, D. H. Yoon3, T. Sekiguchi3, S. Shoji3, and T. Funatsu1* 1The University of Tokyo, Japan; 2Japan Agency for Marine-Earth Science and Technology, Japan; and 3Waseda University, Japan ABSTRACT Environmental microbes are a great source of industrially valuable enzymes with high and unique catalytic activities. However, a vast majority of microbes remain unculturable and thus are not accessible by culture-based methods. Here, we present a rapid and efficient method to screen and identify enzyme- encoding genes from environmental microbes in a culture-independent manner. This method combines activity-based single cell screening using microdroplets and single cell genomics. Using this method, we successfully identified 13 novel β-glucosidase genes from uncultured marine bacteria. This method will facilitate the identification of genes encoding industrially valuable enzymes. KEYWORDS: Microdroplet, Single cell genomics, Enzyme, Screening INTRODUCTION Enzymes have been increasingly used in a wide range of industrial applications because of their prominent properties such as substrate specificity and efficiency, generally at mild pH values, temperatures, and pressures. The most enzymes are identified from environmental microbes using culture-based methods, and industrially valuable enzymes are often obtained from newly identified microbes. However, a vast majority of microbes have not been cultivated in the laboratory and thus their resources cannot be accessed by using culture-based methods. Recently, culture-independent metagenomic approaches have been successfully applied to access the untapped genetic resources. However, the results of these approaches are not outstanding, despite requiring a huge amount of time, cost, and effort. Thus, we have developed a rapid and efficient method for the screening and identification of enzyme-encoding genes from environmental microbes in a culture-independent manner, with a combination of activity-based single cell screening using microdroplets and single cell genomics. METHODOLOGY A schematic representation of our workflow is shown in Figure 1a. Using a microfluidic device, environmental microbes are first encapsulated at a single-cell level in picoliter-sized water-in-oil (W/O) microdroplets with a fluorogenic substrate for the target enzyme (Figure 1a, step 1, and Figure 1b). Microfluidic systems enable the generation of uniform-sized microdroplets and the rapid isolation of single cells in individual compartments. Following incubation at an ambient temperature, the microdroplets are observed under a fluorescence microscope to screen and collect those containing a fluorescent microbe, which exhibits the desired enzymatic activity (Figure 1a, step 2, and Figure 1c). Each fluorescent microbe is recovered from the microdroplets and then subjected to whole genome amplification using multiple displacement amplification (MDA) with phi29 DNA polymerase (Figure 1a, step 3). The resulting MDA products are subjected to next generation sequencing (Figure 1a, step 4) and bioinformatics analysis to identify the genes encoding the target enzymes (Figure 1a, step 5). The entire process can be completed in 4–5 days and is cost-effective. th 978-0-9798064-8-3/µTAS 2015/$20©15CBMS-0001 513 19 International Conference on Miniaturized Systems for Chemistry and Life Sciences October 25-29, 2015, Gyeongju, KOREA Figure 1. (a) Schematic representation of the workflow for the screening and identification of microbial enzyme-encoding genes using microdroplet-based single cell genomics. (b) Schematic representation of single microbial cell isolation in W/O microdroplets using a microfluidic device. (c) Schematic represen- tation of cell-based screening for enzymatic activity and recovery of target cells. EXPERIMENTAL AND RESULTS We applied our method to obtain novel β-glucosidase (BGL) genes from bacteria in seawater sampled from two different sites: surface seawater collected from the coast of Tokyo Bay and deep seawater collected at a depth of 857 m off Hatsushima Island, Sagami Bay. Using microfluidic devices with a flow-focusing junction, environmental bacteria (approximately 107 cells/mL) were encapsulated in W/O microdroplets (diameter, approximately 25 µm; volume, approximately 8 pL) with fluorescein di-β- D-glucopyranoside (FDGlu) as a fluorogenic substrate for the detection of BGL activity [1, 2]. Bacterial cells were encapsulated at the one-cell-per-ten-microdroplet level, ensuring that few microdroplets contained multiple cells. Approximately 10% of the cell-containing microdroplets were estimated to contain a fluorescent cell with BGL activity (Figure 2a), indicating that a large number of cells showed little or no BGL activity. Approximately 2 × 103 microdroplets with or without bacterial cells were screened under a fluorescence microscope. A total of nine microdroplets containing a single bacterial cell with a high fluorescence signal were picked up using a glass capillary attached to a micromanipulator, and each of the cells was lysed and subjected to MDA. To identify successful MDA reactions, the resulting MDA products were screened by polymerase chain reaction (PCR) amplification of the 16S rRNA gene using the bacterial universal primers 27F and 1492R. Six of the nine MDA products gave the PCR amplification product (Figure 2b, lanes 2, 4, 5, 7–9). Direct sequencing of the amplicons revealed that the genome from each single bacterial cell isolated from our environmental samples was successfully amplified without contamination (Table 1) and that all of the isolates represented uncultured bacteria. Among them, MDA products derived from isolates B, C, E, and F (Figure 2B) were shotgun sequenced, assembled, and analyzed. From these four isolates, we then identified four novel genes encoding glycoside hydrolase family 1 (GH1) BGLs (BGL1B1, BGL1C1, BGL1E1, and BGL1E2) and nine novel genes encoding GH family 3 (GH3) BGLs (BGL3B1, BGL3C1, BGL3C2, BGL3E1, BGL3E2, BGL3F1, BGL3F2, BGL3F3, and BGL3F4) (Table 2). Some of the gene products were functionally identified as BGLs (Table 3). CONCLUSION The method described here enables the rapid and efficient screening and identification of microbial enzyme-encoding genes from environmental samples without microbe cultivation. In addition, our meth- od does not require large, expensive equipment and highly-specialized microfluidic platforms used for collecting microbial cells. Thus, our method can be performed in a standard biology laboratory with equipment that is commonly available. Our method will facilitate the identification of genes encoding in- dustrially valuable enzymes. 514 Figure 2. Isolation and genome amplification of bacteria exhibiting BGL activities from surface and deep seawater. (a) Bright-field (left) and fluorescence (right) images of W/O microdroplets encapsulating environmental bacteria with FDGlu. The white arrowhead shows a fluorescent bacterial cell in a W/O microdroplet. The scale bar represents 20 μm. (b) PCR amplification of 16S rRNA genes from MDA products. The amplicons were analyzed by agarose gel electrophoresis. The estimated amplicon size is approximately 1466 bp. Lane M, DNA marker; lanes 1– 4, MDA products from surface seawater; lanes 5–9, MDA products from deep seawater. Table 1. Taxonomic assignment of single amplified genomes based on 16S rRNA sequence. Sequence identity to the Isolate Taxonomy closest relative (%) B Proteobacteria; Gammaproteobacteria; Oceanospirillales; OM182 clade 96% (AY386343.1) C Proteobacteria; Gammaproteobacteria; Alteromonadales; Colwelliaceae; Colwellia hornerae 99% (JN175346.1) E Proteobacteria; Gammaproteobacteria; Alteromonadales; Colwelliaceae; Colwellia sp. 96% (HQ203946.1) F Bacteroidetes; Flavobacteria; Flavobacteriales; Flaviramulus basaltis 98% (EU090719.1) Table 2. Characteristics of deduced BGLs. Table 3. BGL activities of the deduced GH1 BGLs against p-nitrophenyl-β-D-glucopyranoside. Accession number of the Identity Origin Family Km (mM) kcat (1/s) most similar (%) sequence BGL1B1 2.20 ± 0.454 13.2 ± 1.00 BGL1B1 Isolate B GH1 WP_015935647.1 56 BGL1C1 1.60 ± 0.168 0.0145 ± 0.000511 BGL3B1 Isolate B GH3 WP_028040971.1 59 BGL1E1 1.06 ± 0.254 28.4 ± 2.05 BGL1C1 Isolate C GH1 WP_011044459.1 74 BGL1E2 1.23 ± 0.254 0.0217 ± 0.00139 BGL3C1 Isolate C GH3 WP_010381006.1 53 BGL3C2 Isolate C GH3 WP_011044492.1 66 Data are expressed as the mean and standard BGL1E1 Isolate E GH1 WP_019026132.1 70 BGL1E2 Isolate E GH1 WP_010557357.1 72 deviation from three independent experiments. BGL3E1 Isolate E GH3 WP_010558142.1 61 BGL3E2 Isolate E GH3 WP_033093521.1 74 BGL3F1 Isolate F GH3 KGL60449.1 95 BGL3F2 Isolate F GH3 KGL60450.1 98 BGL3F3 Isolate F GH3 WP_036784331.1 73 BGL3F4 Isolate F GH3 KGE87595.1 63 ACKNOWLEDGEMENTS This work was supported by JSPS KAKENHI Grant Numbers 15K18668 (to RI). REFERENCES [1] T. Sakurai et al., Proc. MicroTAS 2014, 965–967, 2014. [2] H. Okada et al., Proc. MicroTAS 2014, 1259–1261, 2014. CONTACT *R. Iizuka: [email protected]; T. Funatsu: [email protected] 515.
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