This paper proposes a high-throughput, function-based screening approach of a metagenomic library for isolating novel microbial enzymes by droplet-based microfluidics. We used gel microdroplets (GMDs) dispersed in oil as picoliter-volume reaction vessels for lipolytic enzyme by encapsulating cells in individual GMDs. Using this approach, we monitored the growth of individual cells encapsulated in GMDs and assessed the enzyme reaction activities at the level of an individual GMD. We then applied this method to screen lipolytic enzyme genes from the metagenomic library constructed from soil collected from a quercus serrate forest of Mount Tsukuba, Ibaraki, Japan. In the workflow presented in this study, metagenomic library clones were encapsulated in 100-pL GMDs with a fluorogenic reporter substrate. A total of 67,000 metagenomic library clones can be screened in only 24 h with reduced consumption of reagents (i.e., <10 μL). As a result, we identified a novel lipolytic enzyme, EstT1, belonging to the EstD2 family of esterases and containing a putative signal peptide, which facilitates enzyme export and catalyzation of substrates in the periplasm. Our study demonstrates the potential of microfluidic GMDs as an efficient tool for metagenomic library screening of industrially relevant enzymes with the potential of significantly reducing the cost and time factors involved in successful practical application of microbial enzymes.

This paper presents a microscale benefit of a secondary flow obtained in a curved rectangular microchannel, which is generally unfavorable and negligible in conventional fluid flow. We have demonstrated the separation and sorting of micro beads by their size using secondary flow. The physical mechanism occurring in the size-selective separation was explained based on the numerical analysis of the characteristic velocity distribution on the cross-sectional plane normal to the main flow stream. The dynamic trajectories of micro beads of different sizes and materials are visualized and compared for the experimental demonstration. We also discuss the effects of both the shape uniformity of the micro beads and the inlet condition on the size-selective separation.

No abstract

In synthetic biology, the control of gene expression requires a multistep processing of biological signals. The key steps are sensing the environment, computing information and outputting products. To achieve such functions, the laborious, combinational networking of enzymes and substrate-genes is required, and to resolve problems, sophisticated design automation tools have been introduced. However, the complexity of genetic circuits remains low because it is difficult to completely avoid crosstalk between the circuits. Here, we have made an orthogonal self-contained device by integrating an actuator and sensors onto a DNA origami-based nanochip that contains an enzyme, T7 RNA polymerase (RNAP) and multiple target-gene substrates. This gene nanochip orthogonally transcribes its own genes, and the nano-layout ability of DNA origami allows us to rationally design gene expression levels by controlling the intermolecular distances between the enzyme and the target genes. We further integrated reprogrammable logic gates so that the nanochip responds to water-in-oil droplets and computes their small RNA (miRNA) profiles, which demonstrates that the nanochip can function as a gene logic-chip. Our approach to component integration on a nanochip may provide a basis for large-scale, integrated genetic circuits.

Environmental microbes are a great source of industrially valuable enzymes with potent and unique catalytic activities. Unfortunately, the majority of microbes remain unculturable and thus are not accessible by culture-based methods. Recently, culture-independent metagenomic approaches have been successfully applied, opening access to untapped genetic resources. Here we present a methodological approach for the identification of genes that encode metabolically active enzymes in environmental microbes in a culture-independent manner. Our method is based on activity-based single-cell sequencing, which focuses on microbial cells showing specific enzymatic activities. First, at the single-cell level, environmental microbes were encapsulated in water-in-oil microdroplets with a fluorogenic substrate for the target enzyme to screen for microdroplets that contain microbially active cells. Second, the microbial cells were recovered and subjected to whole genome amplification. Finally, the amplified genomes were sequenced to identify the genes encoding target enzymes. Employing this method, we successfully identified 14 novel β-glucosidase genes from uncultured bacterial cells in marine samples. Our method contributes to the screening and identification of genes encoding industrially valuable enzymes.