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.

Comparison of lenalidomide in combination with dexamethasone to dexamethasone alone in patients who have received prior thalidomide in relapsed or refractory multiple myeloma

Abstract: 7522 Background: Lenalidomide (len), an analog of thalidomide (thal) is a novel, oral immunomodulatory agent that is effective against multiple myeloma (MM). Two randomized, Phase III trials (MM009...

Identifying qualitative effects of different grazing types on below-ground communities and function in a long-term field experiment.

Abstract: Herbivory is an important modulator of plant biodiversity and productivity in grasslands, but our understanding of herbivore-induced changes on below-ground processes and communities is limited. Using a long-term (17 years) experimental site, we evaluated impacts of rabbit and invertebrate grazers on some soil functions involved in carbon cycling, microbial diversity, structure and functional composition. Both rabbit and invertebrate grazing impacted soil functions and microbial community structure. All functional community measures (functions, biogeochemical cycling genes, network association between different taxa) were more strongly affected by invertebrate grazers than rabbits. Furthermore, our results suggest that exclusion of invertebrate grazers decreases both microbial biomass and abundance of genes associated with key biogeochemical cycles, and could thus have long-term consequences for ecosystem functions. The mechanism behind these impacts are likely to be driven by both direct effects of grazing altering the pattern of nutrient inputs and by indirect effects through changes in plant species composition. However, we could not entirely discount that the pesticide used to exclude invertebrates may have affected some microbial community measures. Nevertheless, our work illustrates that human activity that affects grazing intensity may affect ecosystem functioning and sustainability, as regulated by multi-trophic interactions between above- and below-ground communities.

Compositional and genetic alterations in Graves’ disease gut microbiome reveal specific diagnostic biomarkers

Abstract: Graves' Disease is the most common organ-specific autoimmune disease and has been linked in small pilot studies to taxonomic markers within the gut microbiome. Important limitations of this work include small sample sizes and low-resolution taxonomic markers. Accordingly, we studied 162 gut microbiomes of mild and severe Graves' disease (GD) patients and healthy controls. Taxonomic and functional analyses based on metagenome-assembled genomes (MAGs) and MAG-annotated genes, together with predicted metabolic functions and metabolite profiles, revealed a well-defined network of MAGs, genes and clinical indexes separating healthy from GD subjects. A supervised classification model identified a combination of biomarkers including microbial species, MAGs, genes and SNPs, with predictive power superior to models from any single biomarker type (AUC = 0.98). Global, cross-disease multi-cohort analysis of gut microbiomes revealed high specificity of these GD biomarkers, notably discriminating against Parkinson's Disease, and suggesting that non-invasive stool-based diagnostics will be useful for these diseases.

Defining Host Responses During Systemic Bacterial Infection Through Construction of a Murine Organ Proteome Atlas

Abstract: Group A Streptococcus (GAS) remains one of the top 10 deadliest human pathogens worldwide despite its sensitivity to penicillin. Although the most common GAS infection is pharyngitis (strep throat), it also causes life-threatening systemic infections. A series of complex networks between host and pathogen drive invasive infections, which have not been comprehensively mapped. Attempting to map these interactions, we examined organ-level protein dynamics using a mouse model of systemic GAS infection. We quantified over 11,000 proteins, defining organ-specific markers for all analyzed tissues. From this analysis, an atlas of dynamically regulated proteins and pathways was constructed. Through statistical methods, we narrowed organ-specific markers of infection to 34 from the defined atlas. We show these markers are trackable in blood of infected mice, and a subset has been observed in plasma samples from GAS-infected clinical patients. This proteomics-based strategy provides insight into host defense responses, establishes potentially useful targets for therapeutic intervention, and presents biomarkers for determining affected organs during bacterial infection.

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.