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Insights into the presence of multiple RecQ helicases in the ancient cyanobacterium, Nostoc sp. strain PCC7120: bioinformatics and expression analysis approach

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Abstract

Owing to their crucial role in genome maintenance, RecQ helicases are ubiquitous and present across organisms. Though the multiplicity of RecQ helicases is well known in higher organisms, it is rare among bacteria. The ancient cyanobacterium Nostoc sp. strain PCC7120 was found to have three annotated RecQ helicases. This study aims at understanding its structural differences and evolution through bioinformatics approach and functionality through expression analysis studies. Nostoc RecQ helicases were found to be transcriptionally regulated by LexA and DNA damage inducing stresses. Bioinformatic analysis revealed that all three RecQ helicases of Nostoc possess helicases_C and Zn+2-binding domains. Two of the helicases (AnRecQ and AnRecQ2) lacked the complete RQC and HRDC domains, and AnRecQ2 had an additional Phosphoribosyl transferase domain (Pribosyltran), also seen in RecQ-like helicase (RqlH) protein of Mycobacterium smegmatis. AnRecQ1, which was similar to most bacterial RecQ helicases, differed in having a long C-terminal tail. STRING analysis revealed that the proteins also differed in their predicted protein interactome. Phylogenetic analysis suggested that the multiple recQ genes may have been acquired through duplication and acquisition of additional domains from the smallest of the RecQ helicases (AnRecQ) to cater multiple functions required to deal with the harsh environmental conditions. In course of evolution, however, the multiplicity was lost with the modern-day bacteria and lower eukaryotes which retained fewer RecQ helicases, while further duplication of the acquired RECQ occurred in higher animals and plants to deal with cellular complexity.

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Correspondence to Hema Rajaram.

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Kumar, A., Rajaram, H. Insights into the presence of multiple RecQ helicases in the ancient cyanobacterium, Nostoc sp. strain PCC7120: bioinformatics and expression analysis approach. Mol Genet Genomics 298, 37–47 (2023). https://doi.org/10.1007/s00438-022-01963-6

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