Sediment, a special realm in aquatic environments, has high microbial diversity. While there are numerous reports about the microbial community in marine sediment, freshwater and intertidal sediment communities have been overlooked. The present study determined millions of Illumina reads for a comparison of bacterial communities in freshwater, intertidal wetland, and marine sediments along Pearl River, China, using a technically consistent approach. Our results show that both taxon richness and evenness were the highest in freshwater sediment, medium in intertidal sediment, and lowest in marine sediment. The high number of sequences allowed the determination of a wide variety of bacterial lineages in all sediments for reliable statistical analyses. Principal component analysis showed that the three types of communities could be well separated from phylum to operational taxonomy unit (OTU) levels, and the OTUs from abundant to rare showed satisfactory resolutions. Statistical analysis (LEfSe) demonstrated that the freshwater sediment was enriched with Acidobacteria , Nitrospira , Verrucomicrobia , Alphaproteobacteria , and Betaproteobacteria . The intertidal sediment had a unique community with diverse primary producers (such as Chloroflexi , Bacillariophyta , Gammaproteobacteria , and Epsilonproteobacteria ) as well as saprophytic microbes (such as Actinomycetales , Bacteroidetes , and Firmicutes ). The marine sediment had a higher abundance of Gammaproteobacteria and Deltaproteobacteria , which were mainly involved in sulfate reduction in anaerobic conditions. These results are helpful for a systematic understanding of bacterial communities in natural sediment environments.

Background: Gut microbiota has been suggested to play a role in almost all major diseases including cardio‐ and cerebrovascular diseases. A possible mechanism is the transformation of dietary choline and l ‐carnitine into trimethylamine by gut bacteria. This metabolite is further oxidized into trimethylamine‐N‐oxide ( TMAO ) in liver and promotes atherogenesis. Nevertheless, little is known about gut microbial diversity and blood TMAO levels in stroke patients. Methods and Results: We performed a case‐control study of patients with large‐artery atherosclerotic ischemic stroke and transient ischemic attack. TMAO was determined with liquid chromatography tandem mass spectrometry. Gut microbiome was profiled using Illumina sequencing of the 16S rRNA V4 tag. Within the asymptomatic control group, participants with and without carotid atherosclerotic plaques showed similar levels of TMAO without a significant difference in gut microbiota; however, the gut microbiome of stroke and transient ischemic attack patients was clearly different from that of the asymptomatic group. Stroke and transient ischemic attack patients had more opportunistic pathogens, such as Enterobacter , Megasphaera , Oscillibacter , and Desulfovibrio , and fewer commensal or beneficial genera including Bacteroides , Prevotella , and Faecalibacterium . This dysbiosis was correlated with the severity of the disease. The TMAO level in the stroke and transient ischemic attack patients was significantly lower, rather than higher, than that of the asymptomatic group. Conclusions: Participants with asymptomatic atherosclerosis did not exhibit an obvious change in gut microbiota and blood TMAO levels; however, stroke and transient ischemic attack patients showed significant dysbiosis of the gut microbiota, and their blood TMAO levels were decreased.

We present a performance-optimized algorithm, subsampled open-reference OTU picking, for assigning marker gene (e.g., 16S rRNA) sequences generated on next-generation sequencing platforms to operational taxonomic units (OTUs) for microbial community analysis. This algorithm provides benefits over de novo OTU picking (clustering can be performed largely in parallel, reducing runtime) and closed-reference OTU picking (all reads are clustered, not only those that match a reference database sequence with high similarity). Because more of our algorithm can be run in parallel relative to “classic” open-reference OTU picking, it makes open-reference OTU picking tractable on massive amplicon sequence data sets (though on smaller data sets, “classic” open-reference OTU clustering is often faster). We illustrate that here by applying it to the first 15,000 samples sequenced for the Earth Microbiome Project (1.3 billion V4 16S rRNA amplicons). To the best of our knowledge, this is the largest OTU picking run ever performed, and we estimate that our new algorithm runs in less than 1/5 the time than would be required of “classic” open reference OTU picking. We show that subsampled open-reference OTU picking yields results that are highly correlated with those generated by “classic” open-reference OTU picking through comparisons on three well-studied datasets. An implementation of this algorithm is provided in the popular QIIME software package, which uses uclust for read clustering. All analyses were performed using QIIME’s uclust wrappers, though we provide details (aided by the open-source code in our GitHub repository) that will allow implementation of subsampled open-reference OTU picking independently of QIIME (e.g., in a compiled programming language, where runtimes should be further reduced). Our analyses should generalize to other implementations of these OTU picking algorithms. Finally, we present a comparison of parameter settings in QIIME’s OTU picking workflows and make recommendations on settings for these free parameters to optimize runtime without reducing the quality of the results. These optimized parameters can vastly decrease the runtime of uclust-based OTU picking in QIIME.

Objective Stroke is a leading cause of death and disability worldwide. Neuroprotective approaches have failed in clinical trials, thus warranting therapeutic innovations with alternative targets. The gut microbiota is an important contributor to many risk factors for stroke. However, the bidirectional interactions between stroke and gut microbiota remain largely unknown. Design We performed two clinical cohort studies to capture the gut dysbiosis dynamics after stroke and their relationship with stroke prognosis. Then, we used a middle cerebral artery occlusion model to explore gut dysbiosis post-stroke in mice and address the causative relationship between acute ischaemic stroke and gut dysbiosis. Finally, we tested whether aminoguanidine, superoxide dismutase and tungstate can alleviate post-stroke brain infarction by restoring gut dysbiosis. Results Brain ischaemia rapidly induced intestinal ischaemia and produced excessive nitrate through free radical reactions, resulting in gut dysbiosis with Enterobacteriaceae expansion. Enterobacteriaceae enrichment exacerbated brain infarction by enhancing systemic inflammation and is an independent risk factor for the primary poor outcome of patients with stroke. Administering aminoguanidine or superoxide dismutase to diminish nitrate generation or administering tungstate to inhibit nitrate respiration all resulted in suppressed Enterobacteriaceae overgrowth, reduced systemic inflammation and alleviated brain infarction. These effects were gut microbiome dependent and indicated the translational value of the brain–gut axis in stroke treatment. Conclusions This study reveals a reciprocal relationship between stroke and gut dysbiosis. Ischaemic stroke rapidly triggers gut microbiome dysbiosis with Enterobacteriaceae overgrowth that in turn exacerbates brain infarction.

Gut microbiota dysbiosis contributes to the onset and perpetuation of inflammatory bowel disease (IBD). Given that gut microbiotas vary across geography and ethnicity, it remains obscure whether any universal microbial signatures for IBD diagnosis and prognosis evaluation exist irrespective of populations. Here we profiled the fecal microbiota of a series of Chinese IBD patients and combined them with two Western IBD cohorts, PRISM and RISK, for meta-analyses. We found that the gut microbial alteration patterns in IBD are similar among Chinese and Westerners. Our prediction model based on gut microbiome for IBD diagnosis is robust across the cohorts, which showed 87.5% and 79.1% prediction accuracy in Crohn’s disease (CD) and ulcerative colitis (UC) patients, respectively. A relative increase in the levels of Actinobacteria and Proteobacteria (Enterobacteriaceae) and a relative decrease in the levels of Firmicutes (Clostridiales) were strongly correlated with IBD severity (P < 0.05). Additionally, restoration of gut microbiota diversity and a significant increase in Clostridiales relative abundance were found in patients responding to infliximab (IFX [Remicade]) treatment compared to those in relapse. Moreover, certain microbes, mainly Clostridiales, predicted the treatment effectiveness with 86.5% accuracy alone and 93.8% accuracy in combination with calprotectin levels and Crohn’s disease activity index (CDAI). Taking the results together, we conclude that gut microbiota can offer a set of universal biomarkers for diagnosis, disease activity evaluation, and infliximab treatment response prediction in IBD. IMPORTANCE In the present report, we show that the human fecal microbiota contains promising and universal biomarkers for the noninvasive evaluation of inflammatory bowel disease severity and IFX treatment efficacy, emphasizing the potential ability to mine the gut microbiota as a modality to stratify IBD patients and apply personalized therapy for optimal outcomes.