NEW YORK (GenomeWeb News) – The National Institute of General Medical Sciences wants researchers to find new ways to use genomic and metagenomic sequencing data to develop new tools for discovering natural products, and plans to award $6.8 million to fund these projects next year.
NIGMS plans to award three grants in Fiscal Year 2014 to investigators who will delve into the wealth of data being generated by the genome sequencing community to develop new methods and approaches for discovering these natural products, which serve as defensive and signaling molecules and could be used as antibacterial and anticancer drugs.
The hope is that sequencing data will speed up the current discovery process for natural products, which uses a "grind and find" method that involves phenotypic screening of cultivable organisms and has "intrinsic limitations," according to NIGMS.
Although around 75 percent of antibacterial and anticancer drugs are natural products or are inspired by natural products, recent studies have suggested that less than 1 percent of bacteria and fungi can be cultivated, hinting that the current approach "has barely tapped into the potential pool of encoded products," NIGMS said.
These grants will fund multidisciplinary teams with genomics, synthetic biology, and bioinformatics expertise who will develop high-throughput, genome-based methods for discovering natural products. The teams will also aim to overcome current technical barriers and knowledge gaps that impede the translation of genetic information into chemical information.
Investigators will seek to advance current knowledge of biosynthetic pathways, regulatory networks, and chemical scaffolds that are encoded in the genomes of natural product produces, and to develop new tools, model organisms, and chemical methods to support such research.
NIGMS hopes that these tools and technologies will provide novel approaches for determining quickly the potential of an organism as a natural products producer.
Specifically, these teams may seek to develop molecular biology and bioinformatics toolboxes for designing and assembling biosynthetic operons; develop model organisms for producing natural products; identify and characterize transcriptional and translational regulators; develop a robust set of expression production tools; develop biosynthetic pathways from uncultivable organisms in models; characterize unpredictable biosynthetic enzymes; develop high-throughput analytical methods for structural characterization of natural products; and develop bioinformatics tools for analyzing genomic and functional data and predicting natural products structures.