Refinement of the Listeria monocytogenes σB regulon through quantitative proteomic analysis

Abstract

σ(B) is an alternative σ factor that regulates stress response and virulence genes in the foodborne pathogen Listeria monocytogenes. To gain further insight into σ(B)-dependent regulatory mechanisms in L. monocytogenes, we (i) performed quantitative proteomic comparisons between the L. monocytogenes parent strain 10403S and an isogenic ΔsigB mutant and (ii) conducted a meta-analysis of published microarray studies on the 10403S σ(B) regulon. A total of 134 genes were found to be significantly positively regulated by σ(B) at the transcriptomic level with >75 % of these genes preceded by putative σ(B)-dependent promoters; 21 of these 134 genes were also found to be positively regulated by σ(B) through proteomics. In addition, 15 proteins were only found to be positively regulated by σ(B) through proteomics analyses, including Lmo1349, a putative glycine cleavage system protein. The lmo1349 gene is preceded by a 5' UTR that functions as a glycine riboswitch, which suggests regulation of glycine metabolism by σ(B) in L. monocytogenes. Herein, we propose a model where σ(B) upregulates pathways that facilitate biosynthesis and uptake of glycine, which may then activate this riboswitch. Our data also (i) identified a number of σ(B)-dependent proteins that appear to be encoded by genes that are co-regulated by multiple transcriptional regulators, in particular PrfA, and (ii) found σ(B)-dependent genes and proteins to be overrepresented in the 'energy metabolism' role category, highlighting contributions of the σ(B) regulon to L. monocytogenes energy metabolism as well as a role of PrfA and σ(B) interaction in regulating aspects of energy metabolism in L. monocytogenes.

Fig. 1.

Genes or proteins identified as positively regulated by σ^B through microarray meta-analysis, RNA-sequencing or proteomics. Venn diagram of genes and proteins identified as positively regulated by σ^B, in L. monocytogenes 10403S stationary phase cells, through (i) proteomic data reported here (P^C<0.05; mean FC ≥1.5), (ii) a meta-analysis of previous microarray studies (Oliver et al., 2010; Ollinger et al., 2009; Raengpradub et al., 2008) (P^c <0.05; FC ≥1.5 in each of the three microarray studies) and (ii) previously reported RNA-Seq data (Oliver et al., 2009) (Q <0.05; FC ≥2.0 in each of the four comparisons). Group names (A–G) correspond to the groups in Fig. 2 and Table S2.

Fig. 2.

Heat map comparing FC of genes or proteins identified as positively regulated by σ^B through microarray, RNA-Seq or proteomics. Heat map comparing FC of genes and proteins identified, in L. monocytogenes 10403S stationary phase cells, as positively regulated by σ^B through (i) proteomics data reported here (reported as both replicate 1 and 2; shown as Rep. 1 and Rep. 2), (ii) a meta-analysis of previous microarray studies (Raengpradub et al., 2008; Ollinger et al., 2009; Oliver et al., 2010) and (iii) previously reported RNA-Seq data [all four comparisons reported by Oliver et al. (2009) are shown; indicated as Comp. 1 through 4]. Blank cells indicate that a given protein was not identified in the proteomic experiments. The heat map colour scale applies to microarray data columns, proteomics data columns, and RNA-Seq data columns separately; red indicates negative FC, while green indicates positive FC values; the darker the respective colour the larger the absolute FC value is. Detailed descriptions of genes and encoded proteins can be found in Table S2.

Fig. 2.

Heat map comparing FC of genes or proteins identified as positively regulated by σ^B through microarray, RNA-Seq or proteomics. Heat map comparing FC of genes and proteins identified, in L. monocytogenes 10403S stationary phase cells, as positively regulated by σ^B through (i) proteomics data reported here (reported as both replicate 1 and 2; shown as Rep. 1 and Rep. 2), (ii) a meta-analysis of previous microarray studies (Raengpradub et al., 2008; Ollinger et al., 2009; Oliver et al., 2010) and (iii) previously reported RNA-Seq data [all four comparisons reported by Oliver et al. (2009) are shown; indicated as Comp. 1 through 4]. Blank cells indicate that a given protein was not identified in the proteomic experiments. The heat map colour scale applies to microarray data columns, proteomics data columns, and RNA-Seq data columns separately; red indicates negative FC, while green indicates positive FC values; the darker the respective colour the larger the absolute FC value is. Detailed descriptions of genes and encoded proteins can be found in Table S2.

Fig. 3.

Glycine cleavage system in L. monocytogenes 10403S. (a) Operon map for glycine cleavage system genes, gcvT, gcvPA and gcvPB, including the putative promoter and the aptamer and putative terminator of the glycine riboswitch upstream of the genes. The FC and P values for the genes from Raengpradub et al. (2008), Ollinger et al. (2009) and Oliver et al. (2009, are included. *In the Oliver et al. (2010) study, the FC and P values for gcvT in lineage I, IIIA, and IIIB (IV) strains were FC = 1.7, P = 0.044; FC = 0.5, P = 0.006; and FC = 1.4, P = 0.625, respectively. (b) Extended operon map showing the sequences and positions for the glycine riboswitch (aptamer and putative terminator) based on RNA-Seq data (unpublished). (c) Structure of the glycine riboswitch aptamer based on the putative base pairing for lmo1348 provided by Mandal et al. (2004); the leader–linker interaction is based on the data for lmo1348 provided by Sherman et al. (2012). The terminator was identified using TransTermHP (Kingsford et al., 2007).