The nitrogen-fixing symbiont of alfalfa, Sinorhizobium meliloti, is able to use myo-inositol as the sole carbon source. Putative inositol catabolism genes (iolA and iolRCDEB) have been identified in the S. meliloti genome based on their similarities with the Bacillus subtilis iol genes. In this study, functional mutational analysis revealed that the iolA and iolCDEB genes are required for growth not only with the myo-isomer but also for growth with scyllo-and D-chiro-inositol as the sole carbon source. An additional, hypothetical dehydrogenase of the IdhA/MocA/GFO family encoded by the smc01163 gene was found to be essential for growth with scyllo-inositol, whereas the idhA-encoded myo-inositol dehydrogenase was responsible for the oxidation of D-chiro-inositol. The putative regulatory iolR gene, located upstream of iolCDEB, encodes a repressor of the iol genes, negatively regulating the activity of the myo-and the scyllo-inositol dehydrogenases. Mutants with insertions in the iolA, smc01163, and individual iolRCDE genes could not compete against the wild type in a nodule occupancy assay on alfalfa plants. Thus, a functional inositol catabolic pathway and its proper regulation are important nutritional or signaling factors in the S. meliloti-alfalfa symbiosis.The sugar alcohol inositol, or cyclohexanehexol, occurs in several different stereoisomers, of which the myo-form (Fig. 1, compound 1) is the most abundant (1). myo-Inositol plays important structural and signaling roles in animal and plant cells (22). In the environment, myo-inositol mainly occurs in the phosphorylated form and is involved in the phosphate cycle of terrestrial and freshwater ecosystems (41). The stereoisomers D-chiro-and scylloinositol have recently attracted attention, because they have shown therapeutic potentials for diabetes and Alzheimer's disease, respectively (11, 21). Although there is only limited knowledge about the metabolism of D-chiro-and scyllo-inositol (25, 50), the catabolism of myo-inositol has been studied in a variety of microorganisms, including some members of the Firmicutes (17, 46, 51), Enterobacteriaceae (4,19,40), and Rhizobiaceae (16,29). The myo-inositol catabolic pathway and its regulation are best understood in the Gram-positive bacterium Bacillus subtilis. The B. subtilis iol genes are organized in a divergon comprising iolABCDEFGHIJ and iolRS (47-49). In the proposed inositol catabolic pathway, the myo-inositol dehydrogenase oxidizes myoinositol to its corresponding ketone 2-keto-myo-inositol (2KMI), which is then further catabolized by the actions of IolE, -D, -B, -C, -J, and -A (Fig. 1). The inducer of the inositol catabolic pathway in B. subtilis is the product of the IolC reaction, 2-deoxy-5-keto-D-gluconic acid 6-phosphate (DKGP; compound 6 in Fig. 1), which antagonizes the binding of the IolR repressor to the iol promoter region (51).Sinorhizobium meliloti, the nitrogen-fixing symbiont of alfalfa, can use myo-inositol as the sole carbon source (15). The idhA-encoded myo-inositol dehydrogenase had been s...
Sinorhizobium meliloti, the nitrogen-fixing symbiont of alfalfa, has the ability to catabolize myo-, scyllo-, and D-chiro-inositol. Functional inositol catabolism (iol) genes are required for growth on these inositol isomers, and they play a role during plant-bacterium interactions. The inositol catabolism genes comprise the chromosomally encoded iolA (mmsA) and the iolY(smc01163)RCDEB genes, as well as the idhA gene located on the pSymB plasmid. Reverse transcriptase assays showed that the iolYRCDEB genes are transcribed as one operon. The iol genes were weakly expressed without induction, but their expression was strongly induced by myoinositol. The putative transcriptional regulator of the iol genes, IolR, belongs to the RpiR-like repressor family. Electrophoretic mobility shift assays demonstrated that IolR recognized a conserved palindromic sequence (5-GGAA-N 6 -TTCC-3) in the upstream regions of the idhA, iolY, iolR, and iolC genes. Complementation assays found IolR to be required for the repression of its own gene and for the downregulation of the idhA-encoded myo-inositol dehydrogenase activity in the presence and absence of inositol. Further expression studies indicated that the late pathway intermediate 2-keto-5-deoxy-D-gluconic acid 6-phosphate (KDGP) functions as the true inducer of the iol genes. The iolA (mmsA) gene encoding methylmalonate semialdehyde dehydrogenase was not regulated by IolR. The S. meliloti iolA (mmsA) gene product seems to be involved in more than only the inositol catabolic pathway, since it was also found to be essential for valine catabolism, supporting its more recent annotation as mmsA.
The discovery of the third domain of life, the Archaea, is one of the most exciting findings of the last century. These remarkable prokaryotes are well known for their adaptations to extreme environments; however, Archaea have also conquered moderate environments. Many of the archaeal biochemical processes, such as methane production, are unique in nature and therefore of great scientific interest. Although formerly restricted to biochemical and physiological studies, sophisticated systems for genetic manipulation have been developed during the last two decades for methanogenic archaea, halophilic archaea and thermophilic, sulfur-metabolizing archaea. The availability of these tools has allowed for more complete studies of archaeal physiology and metabolism and most importantly provides the basis for the investigation of gene expression, regulation and function. In this review we provide an overview of methods for genetic manipulation of Methanosarcina spp., a group of methanogenic archaea that are key players in the global carbon cycle and which can be found in a variety of anaerobic environments.
BackgroundWhile a few studies on the variations in mRNA expression and half-lives measured under different growth conditions have been used to predict patterns of regulation in bacterial organisms, the extent to which this information can also play a role in defining metabolic phenotypes has yet to be examined systematically. Here we present the first comprehensive study for a model methanogen.ResultsWe use expression and half-life data for the methanogen Methanosarcina acetivorans growing on fast- and slow-growth substrates to examine the regulation of its genes. Unlike Escherichia coli where only small shifts in half-lives were observed, we found that most mRNA have significantly longer half-lives for slow growth on acetate compared to fast growth on methanol or trimethylamine. Interestingly, half-life shifts are not uniform across functional classes of enzymes, suggesting the existence of a selective stabilization mechanism for mRNAs. Using the transcriptomics data we determined whether transcription or degradation rate controls the change in transcript abundance. Degradation was found to control abundance for about half of the metabolic genes underscoring its role in regulating metabolism. Genes involved in half of the metabolic reactions were found to be differentially expressed among the substrates suggesting the existence of drastically different metabolic phenotypes that extend beyond just the methanogenesis pathways. By integrating expression data with an updated metabolic model of the organism (iST807) significant differences in pathway flux and production of metabolites were predicted for the three growth substrates.ConclusionsThis study provides the first global picture of differential expression and half-lives for a class II methanogen, as well as provides the first evidence in a single organism that drastic genome-wide shifts in RNA half-lives can be modulated by growth substrate. We determined which genes in each metabolic pathway control the flux and classified them as regulated by transcription (e.g. transcription factor) or degradation (e.g. post-transcriptional modification). We found that more than half of genes in metabolism were controlled by degradation. Our results suggest that M. acetivorans employs extensive post-transcriptional regulation to optimize key metabolic steps, and more generally that degradation could play a much greater role in optimizing an organism’s metabolism than previously thought.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3219-8) contains supplementary material, which is available to authorized users.
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