| Literature DB >> 25374486 |
Thomas Weissgerber1, Mutsumi Watanabe2, Rainer Hoefgen2, Christiane Dahl1.
Abstract
Environmental fluctuations require rapid adjustment of the physiology of bacteria. Anoxygenic phototrophic purple sulfur bacteria, like Allochromatium vinosum, thrive in environments that are characterized by steep gradients of important nutrients for these organisms, i.e., reduced sulfur compounds, light, oxygen and carbon sources. Changing conditions necessitate changes on every level of the underlying cellular and molecular network. Thus far, two global analyses of A. vinosum responses to changes of nutritional conditions have been performed and these focused on gene expression and protein levels. Here, we provide a study on metabolite composition and relate it with transcriptional and proteomic profiling data to provide a more comprehensive insight on the systems level adjustment to available nutrients. We identified 131 individual metabolites and compared availability and concentration under four different growth conditions (sulfide, thiosulfate, elemental sulfur, and malate) and on sulfide for a ΔdsrJ mutant strain. During growth on malate, cysteine was identified to be the least abundant amino acid. Concentrations of the metabolite classes "amino acids" and "organic acids" (i.e., pyruvate and its derivatives) were higher on malate than on reduced sulfur compounds by at least 20 and 50 %, respectively. Similar observations were made for metabolites assigned to anabolism of glucose. Growth on sulfur compounds led to enhanced concentrations of sulfur containing metabolites, while other cell constituents remained unaffected or decreased. Incapability of sulfur globule oxidation of the mutant strain was reflected by a low energy level of the cell and consequently reduced levels of amino acids (40 %) and sugars (65 %).Entities:
Keywords: Allochromatium vinosum; Assimilatory sulfate reduction; Metabolomic profiling; Purple sulfur bacteria; Sulfur oxidation
Year: 2014 PMID: 25374486 PMCID: PMC4213376 DOI: 10.1007/s11306-014-0649-7
Source DB: PubMed Journal: Metabolomics ISSN: 1573-3882 Impact factor: 4.290
Fig. 1Current models of dissimilatory sulfur oxidation (a), assimilatory sulfate reduction, cysteine and glutathione biosynthesis (b) as well as methionine biosynthesis and methylation reactions (c) in Allochromatium vinosum. a Polysulfides are the first products of sulfide oxidation. Polysulfur chains (HS−) in the periplasm are probably very short (n probably around 3 or 4), whereas the polysulfur chains in the sulfur globules can be very long (n > 3 and possibly up to n > 105 as for polymeric sulfur) (Dahl and Prange 2006; Prange et al. 2002). Transport of sulfane sulfur into the cytoplasm is proposed to proceed via a low molecular weight carrier molecule, possibly glutathione (amide). The carrier molecule is indicated as “RSH”. Sulfite is formed in the cytoplasm by the enzymes of the Dsr (dissimilatory sulfite reductase) system. Sgp sulfur globule proteins, FccAB flavocytochrome c, Sqr sulfide:quinone oxidoreductase, TsdA thiosulfate dehydrogenase, Sox periplasmic thiosulfate oxidizing multienzyme complex, Rhd rhodanese-like protein, Apr adenosine-5′-phosphosulfate reductase, Sat dissimilatory ATP sulfurylase, Soe sulfite oxidizing enzyme. b Assimilatory sulfate reduction in A. vinosum does not involve formation of phosphoadenosine-5′-phosphosulfate (Neumann et al. 2000). CysE serine O-acetyltransferase (Alvin_0863), CysM cysteine synthase B (Alvin_2228), GshA glutamate/cysteine ligase (Alvin_800), GshB glutathione synthetase (Alvin_0197), γ-GluCys γ-glutamylcysteine, GSH glutathione, XSH glutathione, reduced thioredoxin or glutaredoxin, XSSX oxidized glutathione, thioredoxin or glutaredoxin (see text for further explanation), OAS O-acetyl-serine, NAS N-acetyl-serine, Cys-SO S-sulfocysteine. c Biosynthesis of homocysteine (HomoCys), methionine and biological methylation in A. vinosum. AdoMet S-adenosylmethionine, AdoHomoCys S-adenosylhomocysteine, N5-CH -THF N5-methyl-5,6,7,8-tetrahydrofolate, MetZ O-succinyl-l-homoserine sulfhydrylase (Alvin_1027), MetE cobalamin-independent methionine synthase (Alvin_2262), MetH cobalamin-dependent methionine synthase (Alvin_1622), AhcY adenosylhomocysteinase (Alvin_0320), BchM magnesium protoporphyrin O-methyltransferase (Alvin_2638), MetK S-adenosylmethionine synthetase (Alvin_0318); 0319, methyltransferase type 11 (Alvin_0319). The transcriptomic (boxes) (Weissgerber et al. 2013), proteomic (circles) (Weissgerber et al. 2014) and metabolomic profiles (triangles) (all relative to growth on malate) are depicted next to the respective protein/metabolite. Relative fold changes in mRNA levels above 2 (red) were considered significantly enhanced. Relative changes smaller than 0.5 (blue) were considered as indicating significant decreases in mRNA levels. Relative fold changes between 0.5 and 2 (grey) indicated unchanged mRNA levels. The same color coding is applied to changes on the protein and metabolome levels. Here, values above 1.5 (red) and below 0.67 (blue) were considered significant. Those cases, where transcriptomic data was not available or the respective protein or metabolite was not detected in the proteomic or metabolomic approach, respectively, are indicated by white squares, circles or triangles. Sulfur compounds added from left to right: sulfide, thiosulfate, elemental sulfur and sulfite. Changes on sulfite were not determined on the proteome and metabolome levels
Fig. 2Simplified scheme of A. vinosum central metabolism comparing metabolite concentrations after growth on malate with those after growth on sulfide, thiosulfate and elemental sulfur. Color range visualizes changes of at least 1.5-fold, twofold and tenfold, respectively
Fig. 3Principal component analysis (PCA) score plot of transcript data (a) protein data (b) and metabolite data (c) for A. vinosum wild type. The plots were applied for the 3,271 genes, 1,876 proteins and the 131 metabolites. The average data from 3 to 4 biological replications and 2 biological replications, which were previously published (Weissgerber et al. 2013, 2014) were used for the PCA of transcript data and protein data, respectively. d PCA score plot of metabolite data including ΔdsrJ mutant strain. The plot was applied for the 131 metabolites. PCA was conducted by the MultiExperiment Viewer (Saeed et al. 2003). PC principal component
Fig. 4Transcript (Weissgerber et al. 2013), protein (Weissgerber et al. 2014) (a) and metabolite changes (b) in sulfur oxidizing and sulfate reduction pathways. The transcriptomic (boxes) (Weissgerber et al. 2013) and proteomic (circles) (Weissgerber et al. 2014) profiles (all relative to growth on malate) are depicted next to the respective locus tag. Relative fold changes in mRNA levels above 2 (red) were considered significantly enhanced. Relative changes smaller than 0.5 (blue) were considered as indicating significant decreases in mRNA levels. Relative fold changes between 0.5 and 2 (grey) indicated unchanged mRNA levels. The same color coding is applied to changes on the protein levels. Here, values above 1.5 (red) and below 0.67 (blue) were considered significant. Those cases, where transcriptomic data was not available or the respective protein not detected in the proteomic approach, respectively, are indicated by white squares or circles. Sd sulfide, Th thiosulfate, S elemental sulfur
Fig. 5Comparison between metabolite, transcript (Weissgerber et al. 2013) and protein (Weissgerber et al. 2014) data of glycolysis/gluconeogenesis (a) and the citric acid cycle/glyoxylic acid cycles (b). Reactions of gluconeogenesis are additionally outlined in table (a). The transcriptomic (boxes) (Weissgerber et al. 2013) and proteomic (circles) (Weissgerber et al. 2014) profiles (all relative to growth on malate) are depicted next to the respective locus tag. Relative fold changes in mRNA levels above 2 (red) were considered significantly enhanced. Relative changes smaller than 0.5 (blue) were considered as indicating significant decreases in mRNA levels. Relative fold changes between 0.5 and 2 (grey) indicated unchanged mRNA levels. The same color coding is applied to changes on the protein levels. Here, values above 1.5 (red) and below 0.67 (blue) were considered significant. Those cases, where transcriptomic data was not available or the respective protein not detected in the proteomic approach, respectively, are indicated by white squares or circles. Sd sulfide, Th thiosulfate, S elemental sulfur
Fig. 6Simplified scheme of A. vinosum central metabolism comparing metabolite concentrations after growth on sulfide for the ΔdsrJ mutant strain with those for the wild type. Color range visualizes changes of at least 1.5-fold, twofold and tenfold, respectively