Justine R. Hall

Bio: Justine R. Hall is an academic researcher from University of New Mexico. The author has contributed to research in topics: mothur & Aquificae. The author has an hindex of 2, co-authored 3 publications receiving 15041 citations.

Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities

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.

Molecular Characterization of the Diversity and Distribution of a Thermal Spring Microbial Community by Using rRNA and Metabolic Genes

Abstract: The diversity and distribution of a bacterial community from Coffee Pots Hot Spring, a thermal spring in Yellowstone National Park with a temperature range of 39.3 to 74.1°C and pH range of 5.75 to 6.91, were investigated by sequencing cloned PCR products and quantitative PCR (qPCR) of 16S rRNA and metabolic genes. The spring was inhabited by three Aquificae genera—Thermocrinis, Hydrogenobaculum, and Sulfurihydrogenibium—and members of the Alpha-, Beta-, and Gammaproteobacteria, Firmicutes, Acidobacteria, Deinococcus-Thermus, and candidate division OP5. The in situ chemical affinities were calculated for 41 potential metabolic reactions using measured environmental parameters and a range of hydrogen and oxygen concentrations. Reactions that use oxygen, ferric iron, sulfur, and nitrate as electron acceptors were predicted to be the most energetically favorable, while reactions using sulfate were expected to be less favorable. Samples were screened for genes used in ammonia oxidation (amoA, bacterial gene only), the reductive tricarboxylic acid (rTCA) cycle (aclB), the Calvin cycle (cbbM), sulfate reduction (dsrAB), nitrogen fixation (nifH), nitrite reduction (nirK), and sulfide oxidation (soxEF1) by PCR. Genes for carbon fixation by the rTCA cycle and nitrogen fixation were detected. All aclB sequences were phylogenetically related and spatially correlated to Sulfurihydrogenibium 16S rRNA gene sequences using qPCR (R2 = 0.99). This result supports the recent finding of citrate cleavage by enzymes other than ATP citrate lyase in the rTCA cycle of the Aquificaceae family. We briefly consider potential biochemical mechanisms that may allow Sulfurihydrogenibium and Thermocrinis to codominate some hydrothermal environments.

QIIME allows analysis of high-throughput community sequencing data.

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.

The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

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.

Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities

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.

DADA2: High-resolution sample inference from Illumina amplicon data

Abstract: We present the open-source software package DADA2 for modeling and correcting Illumina-sequenced amplicon errors (https://github.com/benjjneb/dada2). DADA2 infers sample sequences exactly and resolves differences of as little as 1 nucleotide. In several mock communities, DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.

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.