Rob Knight

Bio: Rob Knight is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Microbiome & Gut flora. The author has an hindex of 201, co-authored 1061 publications receiving 253207 citations. Previous affiliations of Rob Knight include Anschutz Medical Campus & University of Sydney.

Perinatal Bisphenol A Exposure Induces Chronic Inflammation in Rabbit Offspring via Modulation of Gut Bacteria and Their Metabolites.

Abstract: Bisphenol A (BPA) accumulates in the maturing gut and liver in utero and is known to alter gut bacterial profiles in offspring. Gut bacterial dysbiosis may contribute to chronic colonic and systemic inflammation. We hypothesized that perinatal BPA exposure-induced intestinal (and liver) inflammation in offspring is due to alterations in the microbiome and colonic metabolome. The 16S rRNA amplicon sequencing analysis revealed differences in beta diversity with a significant reduction in the relative abundances of short-chain fatty acid (SCFA) producers such as Oscillospira and Ruminococcaceae due to BPA exposure. Furthermore, BPA exposure reduced fecal SCFA levels and increased systemic lipopolysaccharide (LPS) levels. BPA exposure-increased intestinal permeability was ameliorated by the addition of SCFA in vitro. Metabolic fingerprints revealed alterations in global metabolism and amino acid metabolism. Thus, our findings indicate that perinatal BPA exposure may cause gut bacterial dysbiosis and altered metabolite profiles, particularly SCFA profiles, leading to chronic colon and liver inflammation. IMPORTANCE Emerging evidence suggests that environmental toxicants may influence inflammation-promoted chronic disease susceptibility during early life. BPA, an environmental endocrine disruptor, can transfer across the placenta and accumulate in fetal gut and liver. However, underlying mechanisms for BPA-induced colonic and liver inflammation are not fully elucidated. In this report, we show how perinatal BPA exposure in rabbits alters gut microbiota and their metabolite profiles, which leads to colonic and liver inflammation as well as to increased gut permeability as measured by elevated serum lipopolysaccharide (LPS) levels in the offspring. Also, perinatal BPA exposure leads to reduced levels of gut bacterial diversity and bacterial metabolites (short-chain fatty acids [SCFA]) and elevated gut permeability-three common early biomarkers of inflammation-promoted chronic diseases. In addition, we showed that SCFA ameliorated BPA-induced intestinal permeability in vitro. Thus, our study results suggest that correcting environmental toxicant-induced bacterial dysbiosis early in life may reduce the risk of chronic diseases later in life.

Cognitive neuropsychology is more than single-case studies.

Abstract: S. M. Sokol et al. (1991) claim that "The Cognitive Neuropsychology Approach" (p. 355) is limited to the single-case study design. The present article takes issue with this claim. Contrary to the beliefs of Sokol et al., we argue (a) that cognitive modularity is best studied by group design, (b) that the possibility of neural reorganization in patients should be tested through converging evidence from different populations using various methods, and (c) that cognitive neuropsychology can benefit from being a part of cognitive neuroscience where both neural and cognitive mechanisms underlying normal cognition are relevant.

Impacts of the Human Gut Microbiome on Therapeutics.

Abstract: The human microbiome contains a vast source of genetic and biochemical variation, and its impacts on therapeutic responses are just beginning to be understood. This expanded understanding is especially important because the human microbiome differs far more among different people than does the human genome, and it is also dramatically easier to change. Here, we describe some of the major factors driving differences in the human microbiome among individuals and populations. We then describe some of the many ways in which gut microbes modify the action of specific chemotherapeutic agents, including nonsteroidal anti-inflammatory drugs and cardiac glycosides, and outline the potential of fecal microbiota transplant as a therapeutic. Intriguingly, microbes also alter how hosts respond to therapeutic agents through various pathways acting at distal sites. Finally, we discuss some of the computational and practical issues surrounding use of the microbiome to stratify individuals for drug response, and we envisi...

Uncovering the Horseshoe Effect in Microbial Analyses.

Abstract: The horseshoe effect is a phenomenon that has long intrigued ecologists. The effect was commonly thought to be an artifact of dimensionality reduction, and multiple techniques were developed to unravel this phenomenon and simplify interpretation. Here, we provide evidence that horseshoes arise as a consequence of distance metrics that saturate-a familiar concept in other fields but new to microbial ecology. This saturation property loses information about community dissimilarity, simply because it cannot discriminate between samples that do not share any common features. The phenomenon illuminates niche differentiation in microbial communities and indicates species turnover along environmental gradients. Here we propose a rationale for the observed horseshoe effect from multiple dimensionality reduction techniques applied to simulations, soil samples, and samples from postmortem mice. An in-depth understanding of this phenomenon allows targeting of niche differentiation patterns from high-level ordination plots, which can guide conventional statistical tools to pinpoint microbial niches along environmental gradients. IMPORTANCE The horseshoe effect is often considered an artifact of dimensionality reduction. We show that this is not true in the case for microbiome data and that, in fact, horseshoes can help analysts discover microbial niches across environments.

Disease-modifying therapies alter gut microbial composition in MS.

Abstract: Objective To determine the effects of the disease-modifying therapies, glatiramer acetate (GA) and dimethyl fumarate (DMF), on the gut microbiota in patients with MS. Methods Participants with relapsing MS who were either treatment-naive or treated with GA or DMF were recruited. Peripheral blood mononuclear cells were immunophenotyped. Bacterial DNA was extracted from stool, and amplicons targeting the V4 region of the bacterial/archaeal 16S rRNA gene were sequenced (Illumina MiSeq). Raw reads were clustered into Operational Taxonomic Units using the GreenGenes database. Differential abundance analysis was performed using linear discriminant analysis effect size. Phylogenetic investigation of communities by reconstruction of unobserved states was used to investigate changes to functional pathways resulting from differential taxon abundance. Results One hundred sixty-eight participants were included (treatment-naive n = 75, DMF n = 33, and GA n = 60). Disease-modifying therapies were associated with changes in the fecal microbiota composition. Both therapies were associated with decreased relative abundance of the Lachnospiraceae and Veillonellaceae families. In addition, DMF was associated with decreased relative abundance of the phyla Firmicutes and Fusobacteria and the order Clostridiales and an increase in the phylum Bacteroidetes. Despite the different changes in bacterial taxa, there was an overlap between functional pathways affected by both therapies. Interpretation Administration of GA or DMF is associated with differences in gut microbial composition in patients with MS. Because those changes affect critical metabolic pathways, we hypothesize that our findings may highlight mechanisms of pathophysiology and potential therapeutic intervention requiring further investigation.

QIIME allows analysis of high-throughput community sequencing data.

Abstract: Supplementary Figure 1 Overview of the analysis pipeline. Supplementary Table 1 Details of conventionally raised and conventionalized mouse samples. Supplementary Discussion Expanded discussion of QIIME analyses presented in the main text; Sequencing of 16S rRNA gene amplicons; QIIME analysis notes; Expanded Figure 1 legend; Links to raw data and processed output from the runs with and without denoising.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

Abstract: SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.

Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities

Abstract: mothur aims to be a comprehensive software package that allows users to use a single piece of software to analyze community sequence data. It builds upon previous tools to provide a flexible and powerful software package for analyzing sequencing data. As a case study, we used mothur to trim, screen, and align sequences; calculate distances; assign sequences to operational taxonomic units; and describe the alpha and beta diversity of eight marine samples previously characterized by pyrosequencing of 16S rRNA gene fragments. This analysis of more than 222,000 sequences was completed in less than 2 h with a laptop computer.

Search and clustering orders of magnitude faster than BLAST

Abstract: Motivation: Biological sequence data is accumulating rapidly, motivating the development of improved high-throughput methods for sequence classification. Results: UBLAST and USEARCH are new algorithms enabling sensitive local and global search of large sequence databases at exceptionally high speeds. They are often orders of magnitude faster than BLAST in practical applications, though sensitivity to distant protein relationships is lower. UCLUST is a new clustering method that exploits USEARCH to assign sequences to clusters. UCLUST offers several advantages over the widely used program CD-HIT, including higher speed, lower memory use, improved sensitivity, clustering at lower identities and classification of much larger datasets. Availability: Binaries are available at no charge for non-commercial use at http://www.drive5.com/usearch Contact: [email protected] Supplementary information:Supplementary data are available at Bioinformatics online.