17 research outputs found
Multiple controls affect arsenite oxidase gene expression in Herminiimonas arsenicoxydans
<p>Abstract</p> <p>Background</p> <p>Both the speciation and toxicity of arsenic are affected by bacterial transformations, i.e. oxidation, reduction or methylation. These transformations have a major impact on environmental contamination and more particularly on arsenic contamination of drinking water. <it>Herminiimonas arsenicoxydans </it>has been isolated from an arsenic- contaminated environment and has developed various mechanisms for coping with arsenic, including the oxidation of As(III) to As(V) as a detoxification mechanism.</p> <p>Results</p> <p>In the present study, a differential transcriptome analysis was used to identify genes, including arsenite oxidase encoding genes, involved in the response of <it>H. arsenicoxydans </it>to As(III). To get insight into the molecular mechanisms of this enzyme activity, a Tn<it>5 </it>transposon mutagenesis was performed. Transposon insertions resulting in a lack of arsenite oxidase activity disrupted <it>aoxR </it>and <it>aoxS </it>genes, showing that the <it>aox </it>operon transcription is regulated by the AoxRS two-component system. Remarkably, transposon insertions were also identified in <it>rpoN </it>coding for the alternative N sigma factor (σ<sup>54</sup>) of RNA polymerase and in <it>dnaJ </it>coding for the Hsp70 co-chaperone. Western blotting with anti-AoxB antibodies and quantitative RT-PCR experiments allowed us to demonstrate that the <it>rpoN </it>and <it>dnaJ </it>gene products are involved in the control of arsenite oxidase gene expression. Finally, the transcriptional start site of the <it>aoxAB </it>operon was determined using rapid amplification of cDNA ends (RACE) and a putative -12/-24 σ<sup>54</sup>-dependent promoter motif was identified upstream of <it>aoxAB </it>coding sequences.</p> <p>Conclusion</p> <p>These results reveal the existence of novel molecular regulatory processes governing arsenite oxidase expression in <it>H. arsenicoxydans</it>. These data are summarized in a model that functionally integrates arsenite oxidation in the adaptive response to As(III) in this microorganism.</p
Reconstruction of the Core and Extended Regulons of Global Transcription Factors
The processes underlying the evolution of regulatory networks are unclear. To address this question, we used a comparative genomics approach that takes advantage of the large number of sequenced bacterial genomes to predict conserved and variable members of transcriptional regulatory networks across phylogenetically related organisms. Specifically, we developed a computational method to predict the conserved regulons of transcription factors across α-proteobacteria. We focused on the CRP/FNR super-family of transcription factors because it contains several well-characterized members, such as FNR, FixK, and DNR. While FNR, FixK, and DNR are each proposed to regulate different aspects of anaerobic metabolism, they are predicted to recognize very similar DNA target sequences, and they occur in various combinations among individual α-proteobacterial species. In this study, the composition of the respective FNR, FixK, or DNR conserved regulons across 87 α-proteobacterial species was predicted by comparing the phylogenetic profiles of the regulators with the profiles of putative target genes. The utility of our predictions was evaluated by experimentally characterizing the FnrL regulon (a FNR-type regulator) in the α-proteobacterium Rhodobacter sphaeroides. Our results show that this approach correctly predicted many regulon members, provided new insights into the biological functions of the respective regulons for these regulators, and suggested models for the evolution of the corresponding transcriptional networks. Our findings also predict that, at least for the FNR-type regulators, there is a core set of target genes conserved across many species. In addition, the members of the so-called extended regulons for the FNR-type regulators vary even among closely related species, possibly reflecting species-specific adaptation to environmental and other factors. The comparative genomics approach we developed is readily applicable to other regulatory networks
Light-enhanced bioaccumulation of molybdenum by nitrogen-deprived recombinant anoxygenic photosynthetic bacterium Rhodopseudomonas palustris
Expanding the genomic encyclopedia of <em>Actinobacteria </em>with 824 isolate reference genomes
The National Microbiome Data Collaborative Data Portal: An integrated multi-omics microbiome data resource
The National Microbiome Data Collaborative (NMDC) Data Portal (https://data.microbiomedata.org) supports microbiome multi-omics data exploration and access through an integrated, distributed data framework aligned with the FAIR (Findable, Accessible, Interoperable and Reusable) data principles (1). The NMDC Data Portal currently hosts 10.2 terabytes of multi-omics microbiome data, spanning five data types (metagenomes, metatranscriptomes, metaproteomes, metabolomes, and natural organic matter characterizations), generated at two Department of Energy User Facilities, the Joint Genome Institute (JGI) at Lawrence Berkeley National Laboratory (LBNL) and the Environmental Molecular Systems Laboratory (EMSL) at Pacific Northwest National Laboratory (PNNL). A flexible data schema (https://github.com/microbiomedata/nmdc-schema) leveraging community-driven standards underpins how data is managed and integrated. Annotated multi-omic data products are produced by the NMDC workflows and linked through common biosamples to enable search capabilities based on environmental context, instrumentation, and functional attributes. As a pilot system, the NMDC Data Portal offers download capabilities and several search components, including interactive geographic visualization of samples; environmental classification distribution visualized through an interactive Sankey diagram; time-series slider to select longitudinal samples of interest; and an upset plot displaying the number of multi-omics data generated from the same biosample within a study