doi: 10.3389/fgene.2014.00210 Objective: biochemical function

DNA sequencing enables the discovery of new genes in high-throughput, low-cost experiments. Conversely, gene function is determined by low-throughput, high-cost experiments. This inverse relationship for these two types of data is a major impedi-ment inmeeting one of themajor scientific challenges of our time—the understand-ing of genomes. This mismatch in throughput is illus-trated by considering the progress made for one of the earliest sequenced genomes, that of Mycobacterium tuberculosis H37Rv (Mtb). When its genome was published in 1998, more than a quarter of its genes had no known function (Cole et al., 1998). Our lack of knowledge about these approximately 1000 “conserved hypotheti-cal ” genes in Mtb represents a serious defi-ciency in our understanding of its biology. Now, after more than a decade of progress, our knowledge of those proteins ’ func-tions is essentially unchanged—there are still greater than 900 genes with no known function (Lew et al., 2011). In contrast, during this same period, the scientific community has sequenced approximately 18,000 new genomes (Pagani et al., 2012), containing millions of new hypothetical proteins. Apparently, the vector of our progress has tipped decisively away from data interpretation and comprehension, and toward mere data collection. To address the issue of gene function testing and annotation for all microbes, we founded COMBREX (COMputational BRidge to EXperiments), an endeavor aimed at accelerating the rate of gene func-tion validation (Anton et al., 2013). Two of COMBREX’s more prominent initiatives were the creation of a comprehensive database for protein function dat