SBIR-STTR Award

It is believed that the enzymatic machinery of microorganisms can be harnessed to produce sustainable bioenergy as well as biosequestration of carbon. However, the ability to engineer organisms is contingent on being able to both understand and take advantage of these functions of interest. Recent advances in high-throughput sequencing have dramatically increased the speed of progress in these areas. However, the task of connecting this genomic scale information with catabolic functions is progressing relatively slowly. Annotating genes by quickly connecting large-scale functions of interest to their genetic circuits and catabolic pathways is a difficult task that requires new tools that do not currently exist. We propose a high-throughput, microfluidic platform technology to identify genes and metabolic networks involved in producing enzymes with specific activity. This technology operates with a three-tiered approach. First a metagenomics library of genetic elements from soil microbiota is created and transferred into an Escherichia coli host. Cells that affect selected enzyme substrates are identified and isolated within the microfluidic chip. Finally, the expression vector of the selected cells will be sequenced. This raw data can then be subjected to bioinformatic analysis to trace the genetic elements back to their microbial origin and annotate them with the detected enzymatic activity. In summary, the concept this technology is to take a enzyme substrate and rapidly find metagenomic sequences involved in its conversion. In contrast with a horizontal approach where the function of all genetic elements of a single organism would be annotated, this is a vertical approach to the identification and annotation of all enzymes coding genetic elements in the library comprising numerous species acting on a specific substrate. Our method allows us to quickly sample the enormous functional reservoir of novel genes from a metagenome for applications in bioenergy, biosequestration, bioremediation and beyond.

Through the creation of carbon neutral biofuels and environmentally friendly methods for chemical and pharmaceutical synthesis, synthetic biology hopes to produce biology-based solutions to some of the worlds grand challengesdisease, energy supply, and pollution. Many of these challenging problems require the discovery of genes, proteins, and metabolic pathways with new and different chemistries. Nature is a vast repository of genetic and chemical diversity, and by extracting the genomes of microbial communities (i.e. the metagenome) from environmental samples, it is possible to identify genes for these biotechnology applications. However, gene identification currently requires both large sequencing efforts and massive screens of recombinant bacterial cells using slow and labor-intensive plate based assays. This platform technology uses an innovative microfluidic cell-sorting technology that will revolutionize the process of gene annotation for synthetic biology. This device physically implements simple yet powerful computer search algorithms as fluidic circuits in a microfluidic chip, and has the potential to screen a single strain out of billions based on the activity of secreted enzymes. This will enable us to rapidly search libraries of millions of E. coli expressing diverse metagenomic DNA for useful secreted enzymes and other gene products. During Phase I we demonstrated proof of concept of the device by using our prototype device to sort a single luciferase secreting yeast cell out of a heterogenous population that was not producing the enzyme. During the grant period we built and tested the prototype microfluidic device, engineered luciferase secreting yeast and e coli strains and used them to demonstrate the power of the microfluidic device. Lastly we created an E. coli library expressing diverse metagenomic DNA from sites likely to contain bacteria that produce enzymes with lignocellulose degrading capabilities. As part of our initial proof of concept for our device, we are using our device to discover metagenomic genes for enzymes that degrade cellulose, and more specifically lignocellulose. These enzymes are essential for cellulosic ethanol biofuel productionefficient lignocellulose catalysis is currently the bottleneck in development of this technology. We created metagenomic libraries created from soil samples and use our device to identify variants producing enzymes for these two applications. During the Phase II grant, we have three aims: (i) develop our core sorting technology, (ii) use it to identify microbial genes for enzymes catalyzing lignocellulose breakdown for use in cellulosic biofuel production, and (iii) develop the technology as a standalone system. Commercial Applications and Other

Benefits:
Our product and our service will both address the need for research and development of enzymes with novel functions for the $3 billion enzyme market. We will meet this growing need by disrupting the current paradigm of one colony at a time plate-based assays; accelerating the pace of scientific discovery.