Construction of integrated gene logic-chip.

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 products1. 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 introduced2. 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.

Culture-independent method for identification of microbial enzyme-encoding genes by activity-based single-cell sequencing using a water-in-oil microdroplet platform.

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 ß-glucosidase genes from uncultured bacterial cells in marine samples. Our method contributes to the screening and identification of genes encoding industrially valuable enzymes.