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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.
Topics: Microbiome, Gut flora, Medicine, Metagenomics, Biology


Papers
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Journal ArticleDOI
TL;DR: The evidence for coev evolution between symbionts and their hosts, the role of horizontal gene transfer in coevolution, and genomic and metagenomic approaches to identify drug targets are reviewed.

105 citations

Journal ArticleDOI
TL;DR: The ability to restore homeostasis provides a rationale for conjoint use of probiotics with antibiotic treatment of BV, and changes in the bacterial microbiota following oral antimicrobial and probiotic interventions are characterized.
Abstract: Background : The composition of the vaginal microbiota is known to be important for health When infections occur, antimicrobial therapy is often poorly efficacious Objective and design : We used 16S rRNA gene sequencing to characterize changes in the bacterial microbiota following oral antimicrobial and probiotic interventions Results : While the bacterial vaginal profiles of women with vulvovaginal candidiasis were dominated by lactobacilli as in healthy women, and unchanged by therapy, Gardnerella vaginalis , Prevotella , Atopobium , Sneathia , and Megasphaera dominated the vagina of women with bacterial vaginosis (BV), and treatment with tinidazole plus Lactobacillus reuteri RC-14+ L rhamnosus GR-1 resulted in an increased relative abundance of indigenous L iners or L crispatus Conclusions : The ability to restore homeostasis provides a rationale for conjoint use of probiotics with antibiotic treatment of BV Keywords: Lactobacillus; bacterial vaginosis; vulvovaginal candidiasis; probiotics (Published: 14 August 2015) Citation: Microbial Ecology in Health & Disease 2015, 26 : 27799 - http://dxdoiorg/103402/mehdv2627799

104 citations

Journal ArticleDOI
01 Mar 2014-Gut
TL;DR: Patients complaining of flatulence have a poor tolerance of intestinal gas, which is associated with instability of the microbial ecosystem and challenged with flatulogenic diet developed instability in composition.
Abstract: Objective To characterise the influence of diet on abdominal symptoms, anal gas evacuation, intestinal gas distribution and colonic microbiota in patients complaining of flatulence. Design Patients complaining of flatulence (n=30) and healthy subjects (n=20) were instructed to follow their usual diet for 3 days (basal phase) and to consume a high-flatulogenic diet for another 3 days (challenge phase). Results During basal phase, patients recorded more abdominal symptoms than healthy subjects in daily questionnaires (5.8±0.3 vs 0.4±0.2 mean discomfort/ pain score, respectively; p=<0.0001) and more gas evacuations by an event marker (21.9±2.8 vs 7.4±1.0 daytime evacuations, respectively; p=0.0001), without differences in the volume of gas evacuated after a standard meal (262±22 and 265±25 mL, respectively). On flatulogenic diet, both groups recorded more abdominal symptoms (7.9±0.3 and 2.8±0.4 discomfort/ pain, respectively), number of gas evacuations (44.4±5.3 and 21.7±2.9 daytime evacuations, respectively) and had more gas production (656±52 and 673±78 mL, respectively; p<0.05 vs basal diet for all). When challenged with flatulogenic diet, patients’ microbiota developed instability in composition, exhibiting variations in the main phyla and reduction of microbial diversity, whereas healthy subjects’ microbiota were stable. Taxa from Bacteroides fragilis or Bilophila wadsworthia correlated with number of gas evacuations or volume of gas evacuated, respectively. Conclusions Patients complaining of flatulence have a poor tolerance of intestinal gas, which is associated with instability of the microbial ecosystem.

103 citations

Posted ContentDOI
13 Sep 2020-medRxiv
TL;DR: A combination of genetics and dietary habits was shown to strongly shape the abundances of certain key bacterial members of the gut microbiota, and explain their genetic association, and this work identifies putative causal relationships between gut microbes and complex diseases using MR.
Abstract: Co-evolution between humans and the microbial communities colonizing them has resulted in an intimate assembly of thousands of microbial species mutualistically living on and in their body and impacting multiple aspects of host physiology and health. Several studies examining whether human genetic variation can affect gut microbiota suggest a complex combination of environmental and host factors. Here, we leverage a single large-scale population-based cohort of 5,959 genotyped individuals with matched gut microbial shotgun metagenomes, dietary information and health records up to 16 years post-sampling, to characterize human genetic variations associated with microbial abundances, and predict possible causal links with various diseases using Mendelian randomization (MR). Genome-wide association study (GWAS) identified 583 independent SNP-taxon associations at genome-wide significance (p

101 citations

Journal ArticleDOI
TL;DR: The proposed microbial indices of gingivitis classified host types with 74% reliability, and, when tested on another 41-member cohort, distinguished healthy from diseased individuals with 95% accuracy.
Abstract: Predictive modeling of human disease based on the microbiota holds great potential yet remains challenging. Here, 50 adults underwent controlled transitions from naturally occurring gingivitis, to healthy gingivae (baseline), and to experimental gingivitis (EG). In diseased plaque microbiota, 27 bacterial genera changed in relative abundance and functional genes including 33 flagellar biosynthesis-related groups were enriched. Plaque microbiota structure exhibited a continuous gradient along the first principal component, reflecting transition from healthy to diseased states, which correlated with Mazza Gingival Index. We identified two host types with distinct gingivitis sensitivity. Our proposed microbial indices of gingivitis classified host types with 74% reliability, and, when tested on another 41-member cohort, distinguished healthy from diseased individuals with 95% accuracy. Furthermore, the state of the microbiota in naturally occurring gingivitis predicted the microbiota state and severity of subsequent EG (but not the state of the microbiota during the healthy baseline period). Because the effect of disease is greater than interpersonal variation in plaque, in contrast to the gut, plaque microbiota may provide advantages in predictive modeling of oral diseases.

99 citations


Cited by
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Journal ArticleDOI
TL;DR: An overview of the analysis pipeline and links to raw data and processed output from the runs with and without denoising are provided.
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.

28,911 citations

28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组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�ly.
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。

18,940 citations

Journal ArticleDOI
TL;DR: 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.
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.

18,256 citations

Journal ArticleDOI
TL;DR: M mothur is used as a case study to trim, screen, and align sequences; calculate distances; assign sequences to operational taxonomic units; and describe the α and β diversity of eight marine samples previously characterized by pyrosequencing of 16S rRNA gene fragments.
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.

17,350 citations

Journal ArticleDOI
TL;DR: UCLUST is a new clustering method that exploits USEARCH to assign sequences to clusters and 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.
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.

17,301 citations