Author
Michael S. Robeson
Other affiliations: United States Department of Agriculture, University of Arkansas, Colorado State University ...read more
Bio: Michael S. Robeson is an academic researcher from University of Arkansas for Medical Sciences. The author has contributed to research in topics: Microbiome & Gut flora. The author has an hindex of 22, co-authored 57 publications receiving 6443 citations. Previous affiliations of Michael S. Robeson include United States Department of Agriculture & University of Arkansas.
Topics: Microbiome, Gut flora, Medicine, Genome, Metagenomics
Papers published on a yearly basis
Papers
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Northern Arizona University1, National Institutes of Health2, University of Minnesota3, Woods Hole Oceanographic Institution4, University of California, Davis5, Massachusetts Institute of Technology6, University of Copenhagen7, University of Trento8, Chinese Academy of Sciences9, University of California, San Francisco10, University of Pennsylvania11, Pacific Northwest National Laboratory12, North Carolina State University13, University of California, San Diego14, Institute for Systems Biology15, Dalhousie University16, University of British Columbia17, Statens Serum Institut18, Anschutz Medical Campus19, University of Washington20, Michigan State University21, Stanford University22, Harvard University23, Broad Institute24, Australian National University25, University of Düsseldorf26, University of New South Wales27, Sookmyung Women's University28, San Diego State University29, Howard Hughes Medical Institute30, Cornell University31, Max Planck Society32, Colorado State University33, Google34, Syracuse University35, Webster University36, United States Department of Agriculture37, University of Arkansas for Medical Sciences38, Colorado School of Mines39, University of Southern Mississippi40, National Oceanic and Atmospheric Administration41, University of California, Merced42, Wageningen University and Research Centre43, University of Arizona44, Environment Agency45, University of Florida46, Merck & Co.47
TL;DR: QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and R.K.P. and partial support was also provided by the following: grants NIH U54CA143925 and U54MD012388.
Abstract: QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and 1565057 to R.K. Partial support was also provided by the following: grants NIH U54CA143925 (J.G.C. and T.P.) and U54MD012388 (J.G.C. and T.P.); grants from the Alfred P. Sloan Foundation (J.G.C. and R.K.); ERCSTG project MetaPG (N.S.); the Strategic Priority Research Program of the Chinese Academy of Sciences QYZDB-SSW-SMC021 (Y.B.); the Australian National Health and Medical Research Council APP1085372 (G.A.H., J.G.C., Von Bing Yap and R.K.); the Natural Sciences and Engineering Research Council (NSERC) to D.L.G.; and the State of Arizona Technology and Research Initiative Fund (TRIF), administered by the Arizona Board of Regents, through Northern Arizona University. All NCI coauthors were supported by the Intramural Research Program of the National Cancer Institute. S.M.G. and C. Diener were supported by the Washington Research Foundation Distinguished Investigator Award.
8,821 citations
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TL;DR: Acidobacteria communities were more phylogenetically clustered as soil pH departed from neutrality, suggesting that pH is an effective habitat filter, restricting community membership to progressively more narrowly defined lineages as pH deviates from neutrality.
Abstract: Acidobacteria are ubiquitous and abundant members of soil bacterial communities. However, an ecological understanding of this important phylum has remained elusive because its members have been difficult to culture and few molecular investigations have focused exclusively on this group. We generated an unprecedented number of acidobacterial DNA sequence data using pyrosequencing and clone libraries (39 707 and 1787 sequences, respectively) to characterize the relative abundance, diversity and composition of acidobacterial communities across a range of soil types. To gain insight into the ecological characteristics of acidobacterial taxa, we investigated the largescale biogeographic patterns exhibited by acidobacterial communities, and related soil and site characteristics to acidobacterial community assemblage patterns. The 87 soils analyzed by pyrosequencing contained more than 8600 unique acidobacterial phylotypes (at the 97% sequence similarity level). One phylotype belonging to Acidobacteria subgroup 1, but not closely related to any cultured representatives, was particularly abundant, accounting for 7.4% of bacterial sequences and 17.6% of acidobacterial sequences, on average, across the soils. The abundance of Acidobacteria relative to other bacterial taxa was highly variable across the soils examined, but correlated strongly with soil pH (R ¼� 0.80, Po0.001). Soil pH was also the best predictor of acidobacterial community composition, regardless of how the communities were characterized, and the relative abundances of the dominant Acidobacteria subgroups were readily predictable. Acidobacterial communities were more phylogenetically clustered as soil pH departed from neutrality, suggesting that pH is an effective habitat filter, restricting community membership to progressively more narrowly defined lineages as pH deviates from neutrality.
950 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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Northern Arizona University1, National Institutes of Health2, University of Minnesota3, University of California, Davis4, Woods Hole Oceanographic Institution5, Massachusetts Institute of Technology6, University of Copenhagen7, University of Trento8, Chinese Academy of Sciences9, University of California, San Francisco10, University of Pennsylvania11, Pacific Northwest National Laboratory12, North Carolina State University13, University of Montana14, Institute for Systems Biology15, Dalhousie University16, University of British Columbia17, Statens Serum Institut18, Anschutz Medical Campus19, University of Washington20, University of California, San Diego21, Michigan State University22, Stanford University23, Broad Institute24, Harvard University25, Australian National University26, University of Düsseldorf27, University of New South Wales28, Sookmyung Women's University29, San Diego State University30, Howard Hughes Medical Institute31, Max Planck Society32, Cornell University33, Colorado State University34, Google35, Syracuse University36, Webster University37, United States Department of Agriculture38, University of Arkansas for Medical Sciences39, Colorado School of Mines40, National Oceanic and Atmospheric Administration41, University of Southern Mississippi42, University of California, Merced43, Wageningen University and Research Centre44, University of Arizona45, Environment Agency46, University of Florida47, Merck & Co.48
TL;DR: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Abstract: In the version of this article initially published, some reference citations were incorrect. The three references to Jupyter Notebooks should have cited Kluyver et al. instead of Gonzalez et al. The reference to Qiita should have cited Gonzalez et al. instead of Schloss et al. The reference to mothur should have cited Schloss et al. instead of McMurdie & Holmes. The reference to phyloseq should have cited McMurdie & Holmes instead of Huber et al. The reference to Bioconductor should have cited Huber et al. instead of Franzosa et al. And the reference to the biobakery suite should have cited Franzosa et al. instead of Kluyver et al. The errors have been corrected in the HTML and PDF versions of the article.
301 citations
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TL;DR: The COmparative GENomic Toolkit is implemented in Python, a fully integrated and thoroughly tested framework for novel probabilistic analyses of biological sequences, devising workflows, and generating publication quality graphics.
Abstract: We have implemented in Python the COmparative GENomic Toolkit, a fully integrated and thoroughly tested framework for novel probabilistic analyses of biological sequences, devising workflows, and generating publication quality graphics. PyCogent includes connectors to remote databases, built-in generalized probabilistic techniques for working with biological sequences, and controllers for third-party applications. The toolkit takes advantage of parallel architectures and runs on a range of hardware and operating systems, and is available under the general public license from http://sourceforge.net/projects/pycogent.
214 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
01 Jun 2012
TL;DR: SPAdes as mentioned in this paper is a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler and on popular assemblers Velvet and SoapDeNovo (for multicell data).
Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.
10,124 citations
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TL;DR: The faecal microbial communities of adult female monozygotic and dizygotic twin pairs concordant for leanness or obesity, and their mothers are characterized to address how host genotype, environmental exposure and host adiposity influence the gut microbiome.
Abstract: The human distal gut harbours a vast ensemble of microbes (the microbiota) that provide important metabolic capabilities, including the ability to extract energy from otherwise indigestible dietary polysaccharides. Studies of a few unrelated, healthy adults have revealed substantial diversity in their gut communities, as measured by sequencing 16S rRNA genes, yet how this diversity relates to function and to the rest of the genes in the collective genomes of the microbiota (the gut microbiome) remains obscure. Studies of lean and obese mice suggest that the gut microbiota affects energy balance by influencing the efficiency of calorie harvest from the diet, and how this harvested energy is used and stored. Here we characterize the faecal microbial communities of adult female monozygotic and dizygotic twin pairs concordant for leanness or obesity, and their mothers, to address how host genotype, environmental exposure and host adiposity influence the gut microbiome. Analysis of 154 individuals yielded 9,920 near full-length and 1,937,461 partial bacterial 16S rRNA sequences, plus 2.14 gigabases from their microbiomes. The results reveal that the human gut microbiome is shared among family members, but that each person's gut microbial community varies in the specific bacterial lineages present, with a comparable degree of co-variation between adult monozygotic and dizygotic twin pairs. However, there was a wide array of shared microbial genes among sampled individuals, comprising an extensive, identifiable 'core microbiome' at the gene, rather than at the organismal lineage, level. Obesity is associated with phylum-level changes in the microbiota, reduced bacterial diversity and altered representation of bacterial genes and metabolic pathways. These results demonstrate that a diversity of organismal assemblages can nonetheless yield a core microbiome at a functional level, and that deviations from this core are associated with different physiological states (obese compared with lean).
6,970 citations
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TL;DR: Some notable features of IQ-TREE version 2 are described and the key advantages over other software are highlighted.
Abstract: IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.
4,337 citations