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Microbial respiration via extracellular electron transfer (EET) is a ubiquitous reaction that occurs throughout anoxic environments and is a driving force behind global biogeochemical cycling of metals. Here we identify specific EET-active microbes and genes in a diverse biofilm using an innovative approach to analyse the dynamic community-wide response to changing EET rates. We find that the most significant gene expression responses to applied EET stimuli occur in only two microbial groups, Desulfobulbaceae and Desulfuromonadales . Metagenomic analyses reveal high coverage draft genomes of these abundant and active microbes. Our metatranscriptomic results show known and unknown genes that are highly responsive to EET stimuli and associated with our identified draft genomes. This new approach yields a comprehensive image of functional microbes and genes related to EET activity in a diverse community, representing the next step towards unravelling complex microbial roles within a community and how microbes adapt to specific environmental stimuli. Extracellular electron transfer is a ubiquitous process that occurs in natural microbial communities. Here, Ishii et al. identify specific microbial strains and genes involved in extracellular electron transfer in a biofilm community that is associated with a microbial fuel cell.

OP9 is a yet-uncultivated bacterial lineage found in geothermal systems, petroleum reservoirs, anaerobic digesters and wastewater treatment facilities. Here we use single-cell and metagenome sequencing to obtain two distinct, nearly complete OP9 genomes, one constructed from single cells sorted from hot spring sediments and the other derived from binned metagenomic contigs from an in situ -enriched cellulolytic, thermophilic community. Phylogenomic analyses support the designation of OP9 as a candidate phylum for which we propose the name ‘Atribacteria’. Although a plurality of predicted proteins is most similar to those from Firmicutes, the presence of key genes suggests a diderm cell envelope. Metabolic reconstruction from the core genome suggests an anaerobic lifestyle based on sugar fermentation by Embden–Meyerhof glycolysis with production of hydrogen, acetate and ethanol. Putative glycohydrolases and an endoglucanase may enable catabolism of (hemi)cellulose in thermal environments. This study lays a foundation for understanding the physiology and ecological role of the ‘Atribacteria’. OP9 is a yet-uncultivated bacterial lineage found in anaerobic environments. Dodsworth et al . use single-cell genomics and metagenomics to construct two near-complete OP9 genomes, revealing a fermentative metabolism and supporting the designation of OP9 as candidate phylum 'Atribacteria'.

Significance In animals, gut microbes are essential for digestion. Here, we show that bacteria outside the gut can also play a critical role in digestion. In shipworms, wood-eating marine bivalves, endosymbiotic bacteria are found within specialized cells in the gills. We show that these endosymbionts produce wood-degrading enzymes that are selectively transported to the shipworm’s bacteria-free gut, where wood digestion occurs. Because only selected wood-degrading enzymes are transported, the shipworm system naturally identifies those endosymbiont enzymes most relevant to lignocellulose deconstruction without interference from other microbial proteins. Thus, this work expands the known biological repertoire of bacterial endosymbionts to include digestion of food and identifies previously undescribed enzymes and enzyme combinations of potential value to biomass-based industries, such as cellulosic biofuel production. Bacteria play many important roles in animal digestive systems, including the provision of enzymes critical to digestion. Typically, complex communities of bacteria reside in the gut lumen in direct contact with the ingested materials they help to digest. Here, we demonstrate a previously undescribed digestive strategy in the wood-eating marine bivalve Bankia setacea , wherein digestive bacteria are housed in a location remote from the gut. These bivalves, commonly known as shipworms, lack a resident microbiota in the gut compartment where wood is digested but harbor endosymbiotic bacteria within specialized cells in their gills. We show that this comparatively simple bacterial community produces wood-degrading enzymes that are selectively translocated from gill to gut. These enzymes, which include just a small subset of the predicted wood-degrading enzymes encoded in the endosymbiont genomes, accumulate in the gut to the near exclusion of other endosymbiont-made proteins. This strategy of remote enzyme production provides the shipworm with a mechanism to capture liberated sugars from wood without competition from an endogenous gut microbiota. Because only those proteins required for wood digestion are translocated to the gut, this newly described system reveals which of many possible enzymes and enzyme combinations are minimally required for wood degradation. Thus, although it has historically had negative impacts on human welfare, the shipworm digestive process now has the potential to have a positive impact on industries that convert wood and other plant biomass to renewable fuels, fine chemicals, food, feeds, textiles, and paper products.

Microbial communities are essential for the maintenance of human health, and when these communities are altered, hosts can become susceptible to inflammation and disease. Dysbiosis contributes to gastrointestinal cancers, and specific bacterial species are associated with this phenotype. This study uses a robust and reproducible animal model to demonstrate that H. pylori infection induces gastric dysbiosis in a cagA -dependent manner and further that dysbiosis and altered microbial community structure parallel the severity of H. pylori -induced gastric injury. Ultimately, such models of H. pylori infection and cancer that can effectively evaluate multiple determinants simultaneously may yield effective strategies for manipulating the gastric microbiota to prevent the development of gastric cancer. Helicobacter pylori is the strongest risk factor for gastric adenocarcinoma; however, most infected individuals never develop this malignancy. Strain-specific microbial factors, such as the oncoprotein CagA, as well as environmental conditions, such as iron deficiency, augment cancer risk. Importantly, dysbiosis of the gastric microbiota is also associated with gastric cancer. To investigate the combinatorial effects of these determinants in an in vivo model of gastric cancer, Mongolian gerbils were infected with the carcinogenic cag + H. pylori strain 7.13 or a 7.13 cagA isogenic mutant, and microbial DNA extracted from gastric tissue was analyzed by 16S rRNA sequencing. Infection with H. pylori significantly increased gastric inflammation and injury, decreased α-diversity, and altered microbial community structure in a cagA- dependent manner. The effect of iron deficiency on gastric microbial communities was also investigated within the context of infection. H. pylori -induced injury was augmented under conditions of iron deficiency, but despite differences in gastric pathology, there were no significant differences in α- or β-diversity, phyla, or operational taxonomic unit (OTU) abundance among infected gerbils maintained on iron-replete or iron-depleted diets. However, when microbial composition was stratified based solely on the severity of histologic injury, significant differences in α- and β-diversity were present among gerbils harboring premalignant or malignant lesions compared to gerbils with gastritis alone. This study demonstrates that H. pylori decreases gastric microbial diversity and community structure in a cagA- dependent manner and that as carcinogenesis progresses, there are corresponding alterations in community structure that parallel the severity of disease. IMPORTANCE Microbial communities are essential for the maintenance of human health, and when these communities are altered, hosts can become susceptible to inflammation and disease. Dysbiosis contributes to gastrointestinal cancers, and specific bacterial species are associated with this phenotype. This study uses a robust and reproducible animal model to demonstrate that H. pylori infection induces gastric dysbiosis in a cagA -dependent manner and further that dysbiosis and altered microbial community structure parallel the severity of H. pylori -induced gastric injury. Ultimately, such models of H. pylori infection and cancer that can effectively evaluate multiple determinants simultaneously may yield effective strategies for manipulating the gastric microbiota to prevent the development of gastric cancer.

Regulation of research on microbes that cause disease in humans has historically been focused on taxonomic lists of ‘bad bugs’. However, given our increased knowledge of these pathogens through inexpensive genome sequencing, 5 decades of research in microbial pathogenesis, and the burgeoning capacity of synthetic biologists, the limitations of this approach are apparent. With heightened scientific and public attention focused on biosafety and biosecurity, and an ongoing review by US authorities of dual-use research oversight, this article proposes the incorporation of sequences of concern (SoCs) into the biorisk management regime governing genetic engineering of pathogens. SoCs enable pathogenesis in all microbes infecting hosts that are ‘of concern’ to human civilization. Here we review the functions of SoCs (FunSoCs) and discuss how they might bring clarity to potentially problematic research outcomes involving infectious agents. We believe that annotation of SoCs with FunSoCs has the potential to improve the likelihood that dual use research of concern is recognized by both scientists and regulators before it occurs.

Background Many tools exist in the analysis of bacterial RNA sequencing (RNA-seq) transcriptional profiling experiments to identify differentially expressed genes between experimental conditions. Generally, the workflow includes quality control of reads, mapping to a reference, counting transcript abundance, and statistical tests for differentially expressed genes. In spite of the numerous tools developed for each component of an RNA-seq analysis workflow, easy-to-use bacterially oriented workflow applications to combine multiple tools and automate the process are lacking. With many tools to choose from for each step, the task of identifying a specific tool, adapting the input/output options to the specific use-case, and integrating the tools into a coherent analysis pipeline is not a trivial endeavor, particularly for microbiologists with limited bioinformatics experience. Results To make bacterial RNA-seq data analysis more accessible, we developed a Simple Program for Automated reference-based bacterial RNA-seq Transcriptome Analysis (SPARTA). SPARTA is a reference-based bacterial RNA-seq analysis workflow application for single-end Illumina reads. SPARTA is turnkey software that simplifies the process of analyzing RNA-seq data sets, making bacterial RNA-seq analysis a routine process that can be undertaken on a personal computer or in the classroom. The easy-to-install, complete workflow processes whole transcriptome shotgun sequencing data files by trimming reads and removing adapters, mapping reads to a reference, counting gene features, calculating differential gene expression, and, importantly, checking for potential batch effects within the data set. SPARTA outputs quality analysis reports, gene feature counts and differential gene expression tables and scatterplots. Conclusions SPARTA provides an easy-to-use bacterial RNA-seq transcriptional profiling workflow to identify differentially expressed genes between experimental conditions. This software will enable microbiologists with limited bioinformatics experience to analyze their data and integrate next generation sequencing (NGS) technologies into the classroom. The SPARTA software and tutorial are available at sparta.readthedocs.org.

ABSTRACT Novel cellulolytic microorganisms can potentially influence second-generation biofuel production. This paper reports the draft genome sequence of Bacillus licheniformis strain YNP1-TSU, isolated from hydrothermal-vegetative microbiomes inside Yellowstone National Park. The assembled sequence contigs predicted 4,230 coding genes, 66 tRNAs, and 10 rRNAs through automated annotation.

SPARTA is a reference-based bacterial RNA-seq analysis workflow application for single-end Illumina reads. SPARTA is turnkey software that simplifies the process of analyzing RNA-seq data sets, making bacterial RNA-seq analysis a routine process that can be undertaken on a personal computer or in the classroom. The easy-to-install, complete workflow processes whole transcriptome shotgun sequencing data files by trimming reads and removing adapters, mapping reads to a reference, counting gene features, calculating differential gene expression, and, importantly, checking for potential batch effects within the data set. SPARTA outputs quality analysis reports, gene feature counts and differential gene expression tables and scatterplots. The workflow is implemented in Python for file management and sequential execution of each analysis step and is available for Mac OS X, Microsoft Windows, and Linux. To promote the use of SPARTA as a teaching platform, a web-based tutorial is available explaining how RNA-seq data are processed and analyzed by the software. Availability and Implementation: Tutorial and workflow can be found at sparta.readthedocs.org. Teaching materials are located at sparta-teaching.readthedocs.org. Source code can be downloaded at www.github.com/abramovitchMSU/, implemented in Python and supported on Mac OS X, Linux, and MS Windows. Contact: Robert B. Abramovitch (abramov5@msu.edu) Supplemental Information: Supplementary data are available online

Humans routinely share information with one another. What drives this behavior? We used neuroimaging to test an account of information selection and sharing that emphasizes inherent reward in self-reflection and connecting with other people. Participants underwent functional MRI while they considered personally reading and sharing New York Times articles. Activity in neural regions involved in positive valuation, self-related processing, and taking the perspective of others was significantly associated with decisions to select and share articles, and scaled with preferences to do so. Activity in all three sets of regions was greater when participants considered sharing articles with other people rather than selecting articles to read themselves. The findings suggest that people may consider value not only to themselves but also to others even when selecting news articles to consume personally. Further, sharing heightens activity in these pathways, in line with our proposal that humans derive value from self-reflection and connecting to others via sharing.