Regulatory Diversity and Functional Analysis of Two-Component Systems in Cyanobacterium Synechocystis sp. PCC 6803 by GC-MS Based Metabolomics

Abstract

Two-component signal transduction systems are still poorly functionally characterized in the model cyanobacterium Synechocystis sp. PCC 6803. To address the issue, a GC-MS based comparative metabolomic analysis was conducted on a library of 44 knockout mutants for the response regulators (RRs) in Synechocystis. The metabolomic profiling analysis showed that 7 RRs mutants, namely slr1909, sll1291, slr6040, sll1330, slr2024, slr1584, and slr1693, were significantly different at metabolomic level, although their growth patterns are similar to the wild type under the normal autotrophic growth condition, suggesting regulatory diversity of RRs at metabolite level in Synechocystis. Additionally, a detailed metabolomic analysis coupled with RT-PCR verification led to useful clues for possible function of these 7 RRs, which were found involved in regulation of multiple aspects of cellular metabolisms in Synechocystis. Moreover, an integrative metabolomic and evolutionary analysis of all RR showed that four groups of RR genes clustered together in both metabolomic and evolutionary trees, suggesting of possible functional conservation of these RRs during the evolutionary process. Meanwhile, six groups of RRs with close evolutionary origin were found with different metabolomic profiles, suggesting possible functional changes during evolution. In contrast, more than 10 groups of RR genes with different clustering patterns in the evolutionary tree were found clustered together in metabolomics-based tree, suggesting possible functional convergences during the evolution. This study provided a metabolomic view of RR function, and the most needed functional clues for further characterization of these regulatory proteins in Synechocystis.

Cyanobacteria as a potential bioasset for restoring degraded land

“…Preliminary studies using genomics, proteomics, and metabolomics (Babele et al, 2019, Babele & Young, 2020, Jaiswal & Wangikar, 2020, Shi et al, 2020) approaches can aid in comparative analysis of cyanobacteria. Metabolic models of various cyanobacterial species have been designed like genome‐scale metabolic models using next‐generation sequencing (Koboldt et al, 2013).…”