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Updated: Jan 13, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
Published on: December 7, 2021
A phylogeny-based method in detecting the species-specialized genes in microbes and its application to a marine
Xiaolin Zhou1, Weijie Li2, Siya Xie3
1Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing, China.
Abstract:
Different microbes possess special traits that enable adaptation to their specific niches, often through specialized genes. Beyond orphan genes, few methods identify homologous genes with unusual functional regions. To address this, we investigated the extreme recombination frequency of the marine symbiont Ca. E. kahalalidifaciens and developed an unbiased computational approach to detect genes deviating from phylogenetic expectations. This method identified Rec family genes as key contributors to the exceptional recombination capacity in Ca. E. kahalalidifaciens. Heterologous expression in Escherichia coli demonstrated that these gene variants significantly enhance recombination efficiency. These efficient Rec variants offer potential for improving genetic manipulation tools, while our pipeline provides a versatile strategy for microbial genome mining.IMPORTANCELike how polar bears can survive extreme cold or how bats can navigate in darkness, different bacteria have special talents in surviving in their unique environments. However, finding the genes responsible for these special abilities is like looking for a needle in a haystack. We developed a new computer method for finding these special genes. We tested it on an amazing bacterium that lives inside marine algae and is exceptionally good at mixing and matching its DNA. We found the genes responsible for this ability and showed that when we put them into common laboratory bacteria, they gained this enhanced DNA-recombination ability too. This discovery is exciting because it gives scientists both a new way to find special genes in any bacteria and new tools that could make genetic engineering more efficient in laboratories around the world.
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