Norman R. Pace

Bio: Norman R. Pace is an academic researcher from University of Colorado Boulder. The author has contributed to research in topics: RNA & RNase P. The author has an hindex of 101, co-authored 297 publications receiving 50252 citations. Previous affiliations of Norman R. Pace include University of California, Berkeley & University of Michigan.

Molecular-phylogenetic characterization of microbial community imbalances in human inflammatory bowel diseases

Abstract: The two primary human inflammatory bowel diseases, Crohn's disease (CD) and ulcerative colitis (UC), are idiopathic relapsing disorders characterized by chronic inflammation of the intestinal tract. Although several lines of reasoning suggest that gastrointestinal (GI) microbes influence inflammatory bowel disease (IBD) pathogenesis, the types of microbes involved have not been adequately described. Here we report the results of a culture-independent rRNA sequence analysis of GI tissue samples obtained from CD and UC patients, as well as non-IBD controls. Specimens were obtained through surgery from a variety of intestinal sites and included both pathologically normal and abnormal states. Our results provide comprehensive molecular-based analysis of the microbiota of the human small intestine. Comparison of clone libraries reveals statistically significant differences between the microbiotas of CD and UC patients and those of non-IBD controls. Significantly, our results indicate that a subset of CD and UC samples contained abnormal GI microbiotas, characterized by depletion of commensal bacteria, notably members of the phyla Firmicutes and Bacteroidetes. Patient stratification by GI microbiota provides further evidence that CD represents a spectrum of disease states and suggests that treatment of some forms of IBD may be facilitated by redress of the detected microbiological imbalances.

Rapid determination of 16S ribosomal RNA sequences for phylogenetic analyses

Abstract: Although the applicability of small subunit ribosomal RNA (16S rRNA) sequences for bacterial classification is now well accepted, the general use of these molecules has been hindered by the technical difficulty of obtaining their sequences. A protocol is described for rapidly generating large blocks of 16S rRNA sequence data without isolation of the 16S rRNA or cloning of its gene. The 16S rRNA in bulk cellular RNA preparations is selectively targeted for dideoxynucleotide-terminated sequencing by using reverse transcriptase and synthetic oligodeoxynucleotide primers complementary to universally conserved 16S rRNA sequences. Three particularly useful priming sites, which provide access to the three major 16S rRNA structural domains, routinely yield 800-1000 nucleotides of 16S rRNA sequence. The method is evaluated with respect to accuracy, sensitivity to modified nucleotides in the template RNA, and phylogenetic usefulness, by examination of several 16S rRNAs whose gene sequences are known. The relative simplicity of this approach should facilitate a rapid expansion of the 16S rRNA sequence collection available for phylogenetic analyses.

A Molecular View of Microbial Diversity and the Biosphere

Abstract: Over three decades of molecular-phylogenetic studies, researchers have compiled an increasingly robust map of evolutionary diversification showing that the main diversity of life is microbial, distributed among three primary relatedness groups or domains: Archaea, Bacteria, and Eucarya. The general properties of representatives of the three domains indicate that the earliest life was based on inorganic nutrition and that photosynthesis and use of organic compounds for carbon and energy metabolism came comparatively later. The application of molecular-phylogenetic methods to study natural microbial ecosystems without the traditional requirement for cultivation has resulted in the discovery of many unexpected evolutionary lineages; members of some of these lineages are only distantly related to known organisms but are sufficiently abundant that they are likely to have impact on the chemistry of the biosphere.

Impact of Culture-Independent Studies on the Emerging Phylogenetic View of Bacterial Diversity

Abstract: Our perspective on microbial diversity has improved enormously over the past few decades. In large part this has been due to molecular phylogenetic studies that objectively relate organisms. Phylogenetic trees based on gene sequences are maps with which to articulate the elusive concept of

RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models

Abstract: Summary: RAxML-VI-HPC (randomized axelerated maximum likelihood for high performance computing) is a sequential and parallel program for inference of large phylogenies with maximum likelihood (ML). Low-level technical optimizations, a modification of the search algorithm, and the use of the GTR+CAT approximation as replacement for GTR+Γ yield a program that is between 2.7 and 52 times faster than the previous version of RAxML. A large-scale performance comparison with GARLI, PHYML, IQPNNI and MrBayes on real data containing 1000 up to 6722 taxa shows that RAxML requires at least 5.6 times less main memory and yields better trees in similar times than the best competing program (GARLI) on datasets up to 2500 taxa. On datasets ≥4000 taxa it also runs 2--3 times faster than GARLI. RAxML has been parallelized with MPI to conduct parallel multiple bootstraps and inferences on distinct starting trees. The program has been used to compute ML trees on two of the largest alignments to date containing 25 057 (1463 bp) and 2182 (51 089 bp) taxa, respectively. Availability: icwww.epfl.ch/~stamatak Contact: Alexandros.Stamatakis@epfl.ch Supplementary information: Supplementary data are available at Bioinformatics online.

Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA

Abstract: We describe a new molecular approach to analyzing the genetic diversity of complex microbial populations. This technique is based on the separation of polymerase chain reaction-amplified fragments of genes coding for 16S rRNA, all the same length, by denaturing gradient gel electrophoresis (DGGE). DGGE analysis of different microbial communities demonstrated the presence of up to 10 distinguishable bands in the separation pattern, which were most likely derived from as many different species constituting these populations, and thereby generated a DGGE profile of the populations. We showed that it is possible to identify constituents which represent only 1% of the total population. With an oligonucleotide probe specific for the V3 region of 16S rRNA of sulfate-reducing bacteria, particular DNA fragments from some of the microbial populations could be identified by hybridization analysis. Analysis of the genomic DNA from a bacterial biofilm grown under aerobic conditions suggests that sulfate-reducing bacteria, despite their anaerobicity, were present in this environment. The results we obtained demonstrate that this technique will contribute to our understanding of the genetic diversity of uncharacterized microbial populations.

phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data.

Abstract: Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.