Screening for novel enzymes from metagenome and SIGEX, as a way to improve it
Jiae Yun, Sangryeol Ryu
Abstract
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Jiae Yun, Sangryeol Ryu
Abstract
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Metagenomics has been successfully applied to isolate novel biocatalysts from the uncultured microbiota in the environment. Two types of screening have been used to identify clones carrying desired traits from metagenomic libraries: function-based screening, and sequence-based screening. Both function- and sequence- based screening have individual advantages and disadvantages, and they have been applied successfully to discover biocatalysts from metagenome. However, both strategies are laborious and tedious because of the low frequency of screening hits. A recent paper introduced a high throughput screening strategy, termed substrate-induced gene-expression screening (SIGEX). SIGEX is designed to select the clones harboring catabolic genes induced by various substrates in concert with fluorescence activated cell sorting (FACS). This method was applied successfully to isolate aromatic hydrocarbon-induced genes from a metagenomic library. Although SIGEX has many limitations, it is expected to provide economic advantages, especially to industry.
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Metagenomics has been successfully applied to isolate novel biocatalysts from the uncultured microbiota in the environment. Two types of screening have been used to identify clones carrying desired traits from metagenomic libraries: function-based screening, and sequence-based screening. Both function- and sequence- based screening have individual advantages and disadvantages, and they have been applied successfully to discover biocatalysts from metagenome. However, both strategies are laborious and tedious because of the low frequency of screening hits. A recent paper introduced a high throughput screening strategy, termed substrate-induced gene-expression screening (SIGEX). SIGEX is designed to select the clones harboring catabolic genes induced by various substrates in concert with fluorescence activated cell sorting (FACS). This method was applied successfully to isolate aromatic hydrocarbon-induced genes from a metagenomic library. Although SIGEX has many limitations, it is expected to provide economic advantages, especially to industry.
Key concepts: Metagenomics, Computational biology, Function (biology), Biology, Gene, Sorting, High-throughput screening, Biotechnology