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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University of Colorado Boulder1, University of Colorado Denver2, Vrije Universiteit Brussel3, Katholieke Universiteit Leuven4, Massachusetts Institute of Technology5, Chinese Academy of Sciences6, University of Oklahoma7, Stanford University8, University of Pennsylvania9, University of California, San Diego10, University of Southern California11, Lawrence Berkeley National Laboratory12, Tsinghua University13
TL;DR: This work benchmarks the performance of eight correlation techniques on simulated and real data in response to challenges specific to microbiome studies: fractional sampling of ribosomal RNA sequences, uneven sampling depths, rare microbes and a high proportion of zero counts.
Abstract: Disruption of healthy microbial communities has been linked to numerous diseases, yet microbial interactions are little understood. This is due in part to the large number of bacteria, and the much larger number of interactions (easily in the millions), making experimental investigation very difficult at best and necessitating the nascent field of computational exploration through microbial correlation networks. We benchmark the performance of eight correlation techniques on simulated and real data in response to challenges specific to microbiome studies: fractional sampling of ribosomal RNA sequences, uneven sampling depths, rare microbes and a high proportion of zero counts. Also tested is the ability to distinguish signals from noise, and detect a range of ecological and time-series relationships. Finally, we provide specific recommendations for correlation technique usage. Although some methods perform better than others, there is still considerable need for improvement in current techniques.
522 citations
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TL;DR: This work introduces a new method to detect typically rare microbial taxa that occasionally become very abundant (conditionally rare taxa [CRT]) and quantifies their contributions to temporal shifts in community structure and reveals that many rareTaxa contribute a greater amount to microbial community dynamics than is apparent from their low proportional abundances.
Abstract: Microbial communities typically contain many rare taxa that make up the majority of the observed membership, yet the contribution of this microbial "rare biosphere" to community dynamics is unclear. Using 16S rRNA amplicon sequencing of 3,237 samples from 42 time series of microbial communities from nine different ecosystems (air; marine; lake; stream; adult hu- man skin, tongue, and gut; infant gut; and brewery wastewater treatment), we introduce a new method to detect typically rare microbial taxa that occasionally become very abundant (conditionally rare taxa (CRT)) and then quantify their contributions to temporal shifts in community structure. We discovered that CRT made up 1.5 to 28% of the community membership, repre- sented a broad diversity of bacterial and archaeal lineages, and explained large amounts of temporal community dissimilarity (i.e., up to 97% of Bray-Curtis dissimilarity). Most of the CRT were detected at multiple time points, though we also identified "one-hit wonder" CRT that were observed at only one time point. Using a case study from a temperate lake, we gained additional insights into the ecology of CRT by comparing routine community time series to large disturbance events. Our results reveal that many rare taxa contribute a greater amount to microbial community dynamics than is apparent from their low proportional abundances. This observation was true across a wide range of ecosystems, indicating that these rare taxa are essential for under- standing community changes over time. IMPORTANCE Microbial communities and their processes are the foundations of ecosystems. The ecological roles of rare microor- ganisms are largely unknown, but it is thought that they contribute to community stability by acting as a reservoir that can rap- idly respond to environmental changes. We investigated the occurrence of typically rare taxa that very occasionally become more prominent in their communities ("conditionally rare"). We quantified conditionally rare taxa in time series from a wide variety of ecosystems and discovered that not only were conditionally rare taxa present in all of the examples, but they also contributed disproportionately to temporal changes in diversity when they were most abundant. This result indicates an important and gen- eral role for rare microbial taxa within their communities.
512 citations
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TL;DR: The findings show that mice containing a sequenced model human gut microbiome can serve as part of a preclinical discovery pipeline designed to identify the effects of existing or new bacterial species with purported health benefits on the gut microbiomes of various human populations.
Abstract: Understanding how the human gut microbiota and host are affected by probiotic bacterial strains requires carefully controlled studies in humans and in mouse models of the gut ecosystem where potentially confounding variables that are difficult to control in humans can be constrained. Therefore, we characterized the fecal microbiomes and metatranscriptomes of adult female monozygotic twin pairs through repeated sampling 4 weeks before, 7 weeks during, and 4 weeks after consumption of a commercially available fermented milk product (FMP) containing a consortium of Bifidobacterium animalis subsp. lactis, two strains of Lactobacillus delbrueckii subsp. bulgaricus, Lactococcus lactis subsp. cremoris, and Streptococcus thermophilus. In addition, gnotobiotic mice harboring a 15-species model human gut microbiota whose genomes contain 58,399 known or predicted protein-coding genes were studied before and after gavage with all five sequenced FMP strains. No significant changes in bacterial species composition or in the proportional representation of genes encoding known enzymes were observed in the feces of humans consuming the FMP. Only minimal changes in microbiota configuration were noted in mice after single or repeated gavage with the FMP consortium. However, RNA-Seq analysis of fecal samples and follow-up mass spectrometry of urinary metabolites disclosed that introducing the FMP strains into mice results in significant changes in expression of microbiome-encoded enzymes involved in numerous metabolic pathways, most prominently those related to carbohydrate metabolism. B. animalis subsp. lactis, the dominant persistent member of the FMP consortium in gnotobiotic mice, up-regulates a locus in vivo that is involved in the catabolism of xylooligosaccharides, a class of glycans widely distributed in fruits, vegetables, and other foods, underscoring the importance of these sugars to this bacterial species. The human fecal metatranscriptome exhibited significant changes, confined to the period of FMP consumption, that mirror changes in gnotobiotic mice, including those related to plant polysaccharide metabolism. These experiments illustrate a translational research pipeline for characterizing the effects of FMPs on the human gut microbiome.
510 citations
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TL;DR: In this first study to comprehensively survey viral communities using a metagenomic approach, it is found that soil viruses are taxonomically diverse and distinct from the communities of viruses found in other environments that have been surveyed using a similar approach.
Abstract: Recent studies have highlighted the surprising richness of soil bacterial communities; however, bacteria are not the only microorganisms found in soil. To our knowledge, no study has compared the diversities of the four major microbial taxa, i.e., bacteria, archaea, fungi, and viruses, from an individual soil sample. We used metagenomic and small-subunit RNA-based sequence analysis techniques to compare the estimated richness and evenness of these groups in prairie, desert, and rainforest soils. By grouping sequences at the 97% sequence similarity level (an operational taxonomic unit [OTU]), we found that the archaeal and fungal communities were consistently less even than the bacterial communities. Although total richness levels are difficult to estimate with a high degree of certainty, the estimated number of unique archaeal or fungal OTUs appears to rival or exceed the number of unique bacterial OTUs in each of the collected soils. In this first study to comprehensively survey viral communities using a metagenomic approach, we found that soil viruses are taxonomically diverse and distinct from the communities of viruses found in other environments that have been surveyed using a similar approach. Within each of the four microbial groups, we observed minimal taxonomic overlap between sites, suggesting that soil archaea, bacteria, fungi, and viruses are globally as well as locally diverse.
505 citations
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TL;DR: The mechanisms underlying microbiota restoration following insult (antibiotic or otherwise) to the skin, oral cavity, and gastrointestinal and urogenital tracts are explored, highlighting recovery by natural processes and after probiotic administration.
Abstract: In a healthy host, a balance exists between members of the microbiota, such that potential pathogenic and non-pathogenic organisms can be found in apparent harmony. During infection, this balance can become disturbed, leading to often dramatic changes in the composition of the microbiota. For most bacterial infections, nonspecific antibiotics are used, killing the non-pathogenic members of the microbiota as well as the pathogens and leading to a substantial delay in the restoration of a healthy microbiota. However, in some cases, infections can self-resolve without the intervention of antibiotics. In this Review, we explore the mechanisms underlying microbiota restoration following insult (antibiotic or otherwise) to the skin, oral cavity, and gastrointestinal and urogenital tracts, highlighting recovery by natural processes and after probiotic administration.
498 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
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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
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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
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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