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.

Tracking down the sources of experimental contamination in microbiome studies.

Abstract: A recent report warns that DNA extraction kits and other laboratory reagents are considerable sources of contamination in microbiome experiments. The issue of contamination is particularly problematic for samples of low biomass.

Immunization with a heat-killed preparation of the environmental bacterium Mycobacterium vaccae promotes stress resilience in mice

Abstract: The prevalence of inflammatory diseases is increasing in modern urban societies. Inflammation increases risk of stress-related pathology; consequently, immunoregulatory or antiinflammatory approaches may protect against negative stress-related outcomes. We show that stress disrupts the homeostatic relationship between the microbiota and the host, resulting in exaggerated inflammation. Repeated immunization with a heat-killed preparation of Mycobacterium vaccae, an immunoregulatory environmental microorganism, reduced subordinate, flight, and avoiding behavioral responses to a dominant aggressor in a murine model of chronic psychosocial stress when tested 1–2 wk following the final immunization. Furthermore, immunization with M. vaccae prevented stress-induced spontaneous colitis and, in stressed mice, induced anxiolytic or fear-reducing effects as measured on the elevated plus-maze, despite stress-induced gut microbiota changes characteristic of gut infection and colitis. Immunization with M. vaccae also prevented stress-induced aggravation of colitis in a model of inflammatory bowel disease. Depletion of regulatory T cells negated protective effects of immunization with M. vaccae on stress-induced colitis and anxiety-like or fear behaviors. These data provide a framework for developing microbiome- and immunoregulation-based strategies for prevention of stress-related pathologies.

Genomic Encyclopedia of Bacteria and Archaea: Sequencing a Myriad of Type Strains

Abstract: Microbes hold the key to life. They hold the secrets to our past (as the descendants of the earliest forms of life) and the prospects for our future (as we mine their genes for solutions to some of the planet's most pressing problems, from global warming to antibiotic resistance). However, the piecemeal approach that has defined efforts to study microbial genetic diversity for over 20 years and in over 30,000 genome projects risks squandering that promise. These efforts have covered less than 20% of the diversity of the cultured archaeal and bacterial species, which represent just 15% of the overall known prokaryotic diversity. Here we call for the funding of a systematic effort to produce a comprehensive genomic catalog of all cultured Bacteria and Archaea by sequencing, where available, the type strain of each species with a validly published name (currently∼11,000). This effort will provide an unprecedented level of coverage of our planet's genetic diversity, allow for the large-scale discovery of novel genes and functions, and lead to an improved understanding of microbial evolution and function in the environment.

Heritable components of the human fecal microbiome are associated with visceral fat.

Abstract: Variation in the human fecal microbiota has previously been associated with body mass index (BMI). Although obesity is a global health burden, the accumulation of abdominal visceral fat is the specific cardio-metabolic disease risk factor. Here, we explore links between the fecal microbiota and abdominal adiposity using body composition as measured by dual-energy X-ray absorptiometry in a large sample of twins from the TwinsUK cohort, comparing fecal 16S rRNA diversity profiles with six adiposity measures. We profile six adiposity measures in 3666 twins and estimate their heritability, finding novel evidence for strong genetic effects underlying visceral fat and android/gynoid ratio. We confirm the association of lower diversity of the fecal microbiome with obesity and adiposity measures, and then compare the association between fecal microbial composition and the adiposity phenotypes in a discovery subsample of twins. We identify associations between the relative abundances of fecal microbial operational taxonomic units (OTUs) and abdominal adiposity measures. Most of these results involve visceral fat associations, with the strongest associations between visceral fat and Oscillospira members. Using BMI as a surrogate phenotype, we pursue replication in independent samples from three population-based cohorts including American Gut, Flemish Gut Flora Project and the extended TwinsUK cohort. Meta-analyses across the replication samples indicate that 8 OTUs replicate at a stringent threshold across all cohorts, while 49 OTUs achieve nominal significance in at least one replication sample. Heritability analysis of the adiposity-associated microbial OTUs prompted us to assess host genetic-microbe interactions at obesity-associated human candidate loci. We observe significant associations of adiposity-OTU abundances with host genetic variants in the FHIT, TDRG1 and ELAVL4 genes, suggesting a potential role for host genes to mediate the link between the fecal microbiome and obesity. Our results provide novel insights into the role of the fecal microbiota in cardio-metabolic disease with clear potential for prevention and novel therapies.

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.