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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: A household pair study largely overcomes common inherent limitations and increases statistical power in population-based microbiome studies.
Abstract: Background: Evidence for a role of human gut microbiota in multiple sclerosis (MS) risk is mounting, yet large variability is seen across studies. This is, in part, due to the lack of standardization of study protocols, sample collection methods, and sequencing approaches. Objective: This study aims to address the effect of a household experimental design, sample collection, and sequencing approaches in a gut microbiome study in MS subjects from a multi-city study population. Methods: We analyzed 128 MS patient and cohabiting healthy control pairs from the International MS Microbiome Study (iMSMS). A total of 1005 snap-frozen or desiccated Q-tip stool samples were collected and evaluated using 16S and shallow whole-metagenome shotgun sequencing. Results: The intra-individual variance observed by different collection strategies was dramatically lower than inter-individual variance. Shallow shotgun highly correlated with 16S sequencing. Participant house and recruitment site accounted for the two largest sources of microbial variance, while higher microbial similarity was seen in household-matched participants as hypothesized. A significant proportion of the variance in dietary intake was also dominated by geographic distance. Conclusion: A household pair study largely overcomes common inherent limitations and increases statistical power in population-based microbiome studies.

25 citations

Journal ArticleDOI
TL;DR: Keemei will save researchers time and frustration by providing a convenient interface for tabular bioinformatics file format validation, and will reduce the validation and formatting bottlenecks that are commonly encountered when human-generated data files are first used with a bioInformatics system.
Abstract: Bioinformatics software often requires human-generated tabular text files as input and has specific requirements for how those data are formatted. Users frequently manage these data in spreadsheet programs, which is convenient for researchers who are compiling the requisite information because the spreadsheet programs can easily be used on different platforms including laptops and tablets, and because they provide a familiar interface. It is increasingly common for many different researchers to be involved in compiling these data, including study coordinators, clinicians, lab technicians and bioinformaticians. As a result, many research groups are shifting toward using cloud-based spreadsheet programs, such as Google Sheets, which support the concurrent editing of a single spreadsheet by different users working on different platforms. Most of the researchers who enter data are not familiar with the formatting requirements of the bioinformatics programs that will be used, so validating and correcting file formats is often a bottleneck prior to beginning bioinformatics analysis. We present Keemei, a Google Sheets Add-on, for validating tabular files used in bioinformatics analyses. Keemei is available free of charge from Google’s Chrome Web Store. Keemei can be installed and run on any web browser supported by Google Sheets. Keemei currently supports the validation of two widely used tabular bioinformatics formats, the Quantitative Insights into Microbial Ecology (QIIME) sample metadata mapping file format and the Spatially Referenced Genetic Data (SRGD) format, but is designed to easily support the addition of others. Keemei will save researchers time and frustration by providing a convenient interface for tabular bioinformatics file format validation. By allowing everyone involved with data entry for a project to easily validate their data, it will reduce the validation and formatting bottlenecks that are commonly encountered when human-generated data files are first used with a bioinformatics system. Simplifying the validation of essential tabular data files, such as sample metadata, will reduce common errors and thereby improve the quality and reliability of research outcomes.

24 citations

Journal ArticleDOI
TL;DR: DNA from the environment is extracted, followed by high-throughput sequencing of its genetic instructions, to reveal that your local park is an untapped resource with enormous potential for discovery.
Abstract: Can you imagine New York’s Central Park as a source of the next generation of antibiotics that can treat hundreds of millions of people? The work by Charlop-Powers et al. in PNAS (1) suggests this possibility. Antibiotic-resistant microbes pose one of the main health threats of the 21st century (2). According to the Centers for Disease Control and Prevention, more people die today of bacterial infections than HIV (3) and more people will die of bacterial infections than cancer by 2050 (4). Because antibiotic resistance is a global threat that affects hundreds of millions of people worldwide (5), it has become a key issue for the White House and the United Nations. In 2015, the White House developed an action plan to combat antibiotic resistance and the General Assembly of the United Nations had a high-level meeting addressing worldwide antibiotic resistance (6, 7). Most (∼75%) of today’s antibiotics are derived from natural products (2, 8). Penicillin was isolated from a fungus, and azithromycin, commonly prescribed in the form of a Z-Pak, was isolated from a bacterium (8). The period from the 1930s through the 1980s represented the “Golden Age” for the discovery of antibiotics. Since 1975, very few antibiotics have emerged (rare exceptions include vancomycin and daptomycin), and some pathogens are resistant to all known antibiotics. To combat these “superbugs,” researchers are exploring new natural sources that were missed in previous screens (3). Exotic areas, usually in regions of the planet minimally impacted by people and with high biodiversity, such as rainforests or coral reefs, are most often explored for natural sources of next-generation antibiotics. Charlop-Powers et al. (1) extracted DNA from the environment, followed by high-throughput sequencing of its genetic instructions, to reveal that your local park is an untapped resource with enormous potential for discovery … [↵][1]1To whom correspondence should be addressed. Email: pdorrestein{at}ucsd.edu. [1]: #xref-corresp-1-1

24 citations

Journal ArticleDOI
TL;DR: Intestinal surgeries seem to reduce the diversity of the gut microbiome and metabolome in IBD patients, and these changes may persist and need to be studied in prospective longitudinal trials linked to microbiome-involved phenotypes.
Abstract: Author(s): Fang, Xin; Vazquez-Baeza, Yoshiki; Elijah, Emmanuel; Vargas, Fernando; Ackermann, Gail; Humphrey, Gregory; Lau, Rebecca; Weldon, Kelly C; Sanders, Jon G; Panitchpakdi, Morgan; Carpenter, Carolina; Jarmusch, Alan K; Neill, Jennifer; Miralles, Ara; Dulai, Parambir; Singh, Siddharth; Tsai, Matthew; Swafford, Austin D; Smarr, Larry; Boyle, David L; Palsson, Bernhard O; Chang, John T; Dorrestein, Pieter C; Sandborn, William J; Knight, Rob; Boland, Brigid S | Abstract: BackgroundMany studies have investigated the role of the microbiome in inflammatory bowel disease (IBD), but few have focused on surgery specifically or its consequences on the metabolome that may differ by surgery type and require longitudinal sampling. Our objective was to characterize and contrast microbiome and metabolome changes after different surgeries for IBD, including ileocolonic resection and colectomy.MethodsThe UC San Diego IBD Biobank was used to prospectively collect 332 stool samples from 129 subjects (50 ulcerative colitis; 79 Crohn's disease). Of these, 21 with Crohn's disease had ileocolonic resections, and 17 had colectomies. We used shotgun metagenomics and untargeted liquid chromatography followed by tandem mass spectrometry metabolomics to characterize the microbiomes and metabolomes of these patients up to 24 months after the initial sampling.ResultsThe species diversity and metabolite diversity both differed significantly among groups (species diversity: Mann-Whitney U test P value = 7.8e-17; metabolomics, P-value = 0.0043). Escherichia coli in particular expanded dramatically in relative abundance in subjects undergoing surgery. The species profile was better able to classify subjects according to surgery status than the metabolite profile (average precision 0.80 vs 0.68).ConclusionsIntestinal surgeries seem to reduce the diversity of the gut microbiome and metabolome in IBD patients, and these changes may persist. Surgery also further destabilizes the microbiome (but not the metabolome) over time, even relative to the previously established instability in the microbiome of IBD patients. These long-term effects and their consequences for health outcomes need to be studied in prospective longitudinal trials linked to microbiome-involved phenotypes.

24 citations

Posted ContentDOI
25 May 2020-bioRxiv
TL;DR: A selection mechanism wherein hippocampal SWR and cortical slow-wave synchronization governs the transient engagement of distributed neuronal populations supporting hippocampal-dependent memory consolidation is suggested.
Abstract: Hippocampal-dependent memory consolidation during sleep is hypothesized to depend on the synchronization of distributed neuronal ensembles, organized by the hippocampal sharp-wave ripples (SWRs, 80-150 Hz) and subcortical/cortical slow-waves (0.5-4 Hz). However, the precise role of SWR-slow-wave interactions in synchronizing subcortical/cortical neuronal activity is unclear. Here, we leverage intracranial electrophysiological recordings from the human hippocampus, amygdala, temporal and frontal cortices, to examine activity modulation and cross-regional coordination during SWRs. Hippocampal SWRs are associated with widespread modulation of high frequency activity (HFA; 70-200 Hz) a measure of local neuronal activation. This peri-SWR HFA modulation is predicted by the coupling between hippocampal SWRs and local subcortical/cortical slow-waves. Finally, local cortical slow-wave phase offsets during SWRs predicted functional connectivity between the frontal and temporal cortex. These findings suggest a selection mechanism wherein hippocampal SWR and cortical slow-wave synchronization governs the transient engagement of distributed neuronal populations supporting hippocampal-dependent memory consolidation.

24 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