Author
Rob Knight
Other affiliations: Anschutz Medical Campus, University of Sydney, Veterans Health Administration ...read more
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 published on a yearly basis
Papers
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Harvard University1, Broad Institute2, University of Colorado Boulder3, Michigan State University4, Northern Arizona University5, Argonne National Laboratory6, Icahn School of Medicine at Mount Sinai7, San Diego State University8, University of Minnesota9, Cornell University10, University of Maryland, Baltimore11
TL;DR: There are opportunities in interdisciplinary research, analytical rigor, standardization, and policy development for this relatively new and rapidly developing field of human microbiome biology.
63 citations
TL;DR: This analysis suggests that the present distribution of integrons is due to multiple losses and gene transfer events, while, in some cases, the ability to integrate and excise foreign DNA may be selectively advantageous, the gain, loss, or rearrangment of gene cassettes could also be deleterious, selecting against functional integrases.
Abstract: Integrons are mechanisms that facilitate horizontal gene transfer, allowing bacteria to integrate and express foreign DNA. These are important in the exchange of antibiotic resistance determinants, but can also transfer a diverse suite of genes unrelated to pathogenicity. Here, we provide a systematic analysis of the distribution and diversity of integron intI genes and integron-containing bacteria. We found integrons in 103 different pathogenic and non-pathogenic bacteria, in six major phyla. Integrons were widely scattered, and their presence was not confined to specific clades within bacterial orders. Nearly 1/3 of the intI genes that we identified were pseudogenes, containing either an internal stop codon or a frameshift mutation that would render the protein product non-functional. Additionally, 20% of bacteria contained more than one integrase gene. dN/dS ratios revealed mutational hotspots in clades of Vibrio and Shewanella intI genes. Finally, we characterized the gene cassettes associated with integrons in Methylobacillus flagellatus KT and Dechloromonas aromatica RCB, and found a heavy metal efflux gene as well as genes involved in protein folding and stability. Our analysis suggests that the present distribution of integrons is due to multiple losses and gene transfer events. While, in some cases, the ability to integrate and excise foreign DNA may be selectively advantageous, the gain, loss, or rearrangment of gene cassettes could also be deleterious, selecting against functional integrases. Thus, such a high fraction of pseudogenes may suggest that the selective impact of integrons on genomes is variable, oscillating between beneficial and deleterious, possibly depending on environmental conditions.
63 citations
01 Jan 2013
TL;DR: The combination of Malawian diet and kwashiorkor microbiome produced marked weight loss in recipient mice, accompanied by perturbations in amino acid, carbohydrate, and intermediary metabolism that were only transiently ameliorated with RUTF.
62 citations
TL;DR: It is suggested that IHC, a hallmark of OSA, accelerates the progression of atherosclerosis in the aorta and especially in the PA, and this process is partly inhibited by DMB, demonstrating that microbial metabolites may serve as therapeutic targets for OSA‐induced Atherosclerosis.
Abstract: Obstructive sleep apnea (OSA) is a common disorder characterized by intermittent hypoxia and hypercapnia (IHC) during sleep. OSA has been shown to be a risk factor for atherosclerosis, but the relation of IHC to the induction or progression of atherosclerosis is not well understood. To dissect the mechanisms involved, we compared atherosclerotic lesion formation in two mouse models, i.e., apolipoprotein E (ApoE) and low density lipoprotein receptor (Ldlr)-deficient mice, with or without IHC exposure. Ten-week-old ApoE-/- or Ldlr-/- mice were fed a high-fat diet for 4 or 8 weeks while being exposed to IHC for 10 hours/day or room air (RA) for 24 hours/day. En face lesions of the aorta, aortic arch, and pulmonary artery (PA) were examined. Moreover, 3,3-dimethyl-1-butanol (DMB), an inhibitor of microbial trimethylamine (TMA) production, was used to determine the contribution of TMA-oxide (TMAO) to IHC-induced atherosclerosis. Eight weeks of IHC exposure expedited the formation of atherosclerosis in both the PA and aortic arch of ApoE-/- mice, but only in the PA of Ldlr-/- mice (ApoE-/- PA 8 wk, IHC 35.4 ± 1.9% versus RA 8.0 ± 2.8%, P < 0.01). The atherosclerotic lesions evolved faster and to a more severe extent in ApoE-/- mice as compared with Ldlr-/- mice (PA IHC 8 wk, ApoE-/- 35.4 ± 1.9% versus Ldlr-/- 8.2 ± 1.5%, P < 0.01). DMB significantly attenuated but did not totally eliminate IHC-induced PA atherosclerosis. Our findings suggest that IHC, a hallmark of OSA, accelerates the progression of atherosclerosis in the aorta and especially in the PA. This process is partly inhibited by DMB, demonstrating that microbial metabolites may serve as therapeutic targets for OSA-induced atherosclerosis.
62 citations
TL;DR: Qemistree uses fragmentation spectra to predict molecular fingerprints and represent their relationships as a tree, enabling comparison of metabolomics data across different experimental conditions and exploration of chemical diversity in mixtures.
Abstract: Untargeted mass spectrometry is employed to detect small molecules in complex biospecimens, generating data that are difficult to interpret. We developed Qemistree, a data exploration strategy based on the hierarchical organization of molecular fingerprints predicted from fragmentation spectra. Qemistree allows mass spectrometry data to be represented in the context of sample metadata and chemical ontologies. By expressing molecular relationships as a tree, we can apply ecological tools that are designed to analyze and visualize the relatedness of DNA sequences to metabolomics data. Here we demonstrate the use of tree-guided data exploration tools to compare metabolomics samples across different experimental conditions such as chromatographic shifts. Additionally, we leverage a tree representation to visualize chemical diversity in a heterogeneous collection of samples. The Qemistree software pipeline is freely available to the microbiome and metabolomics communities in the form of a QIIME2 plugin, and a global natural products social molecular networking workflow.
61 citations
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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
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
University of Massachusetts Amherst1, University of Michigan2, University of New Mexico3, University of British Columbia4, Texas A&M University5, University of Minnesota6, University of Warwick7, Dalhousie University8, Colorado School of Mines9, University of Ljubljana10, Graz University of Technology11, Louisiana State University12
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
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