Pool deconvolution approach for high-throughput gene mining from Bacillus thuringiensis.

Abstract

Novel genes from Bacillus thuringiensis (Bt) are required for effective deployment in agriculture, human health, and forestry. In an improvement over conventional PCR-based screening, next generation sequencing (NGS) has been used for identification of new genes of potential interest from Bt strains, but cost becomes a constraint when several isolates are to be sequenced. We demonstrate the potential of a DNA pooling strategy known as pool deconvolution to identify commercially important toxin genes from 36 native Bt isolates. This strategy is divided into three steps: (a) DNA pooling, (b) short read sequence assembly followed by gene mining, and (c) host isolate identification. With this approach, we have identified insecticidal protein (ip) genes including nine three-domain (3D) cry genes, three cyt-type genes, three mtx genes (mosquitocidal toxin), and one bin and vip-type gene each. Three cry-type and three cyt-type genes were cloned, out of which, two cry-type genes, ip11 and ip13, were named as cry4Ca2 and cry52Ca1, respectively by the Bacillus thuringiensis nomenclature committee ( http://www.biols.susx.ac.uk/Home/Neil_Crickmore/BT/ ). Our results show that the pool deconvolution approach is well suited for high-throughput gene mining in bacteria.