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 Δslr1909, Δsll1291, Δslr6040, Δsll1330, Δslr2024, Δslr1584, and Δslr1693, 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.

Keywords: GC-MS; Synechocystis; metabolomics; response regulators; two-component signal transduction systems.

Figure 1

Repeatability analysis three different batches of the wild type and 3 randomly selected mutants. (A) PCA plots of 3 different batches wild type and three randomly selected mutants; different colors represent different samples. (B–D) RSD analysis of different metabolites detected in the wild type and the mutants; different colors represent different samples.

Figure 2

PCA plots of the GC-MS metabolomic profiles at 48 h. Different mutants were represented by different colors.

Figure 3

Integrated analysis of GC-MS and LC-MS profiles. (A) Pathway view of metabolite changes in Δsll1330, differential regulated metabolites were represented by color, red for down-regulated and green for up-regulated. (B) Pathway view of metabolite changes in Δslr6040, differential regulated metabolites were represented by color, red for down-regulated and green for up-regulated.

Figure 4

Heat map presentation of the metabolomic changes in 7 most regulated mutants compared with the wild type.

Figure 5

Correlation between changes of gene expression level and metabolomics level in mutants. The changes of gene expression level and metabolomics level showed a good correlation since R² = 0.70.

Figure 6

Comparative analysis of metabolomics- and evolution-based trees of RRs. (A) Phylogenetic analysis of RRs based on the receiver domains. Different cube colors beside the gene names and mutants represent different subfamilies: gray for NarL family, yellow for OmpR family, red for CheY family, blue for PatA family and green for others, respectively. (B) Hierarchical clustering analysis based on metabolomic profiles. Different cube colors beside the gene names and mutants represent different subfamilies: gray for NarL family, yellow for OmpR family, red for CheY family, blue for PatA family and green for others, respectively. Four groups of RR genes that shared close relationship in both phylogenetic tree and metabolomics-based tree were marked in bold. Genes clustered in both metabolomics- and evolution-based trees were linked by lines with same colors of their subfamilies. The seven most regulated mutants were marked with black frame. The bootstrap values were represented in different colors of nodes: green for 1,000–750, blue for 750–500, yellow for 500–250, and orange for 250–0.