Benli Chai

The Ribosomal Database Project: improved alignments and new tools for rRNA analysis

The Ribosomal Database Project (RDP) provides researchers with quality-controlled bacterial and archaeal small subunit rRNA alignments and analysis tools. An improved alignment strategy uses the Infernal secondary structure aware aligner to provide a more consistent higher quality alignment and faster processing of user sequences. Substantial new analysis features include a new Pyrosequencing Pipeline that provides tools to support analysis of ultra high-throughput rRNA sequencing data. This pipeline offers a collection of tools that automate the data processing and simplify the computationally intensive analysis of large sequencing libraries. In addition, a new Taxomatic visualization tool allows rapid visualization of taxonomic inconsistencies and suggests corrections, and a new class Assignment Generator provides instructors with a lesson plan and individualized teaching materials. Details about RDP data and analytical functions can be found at http://rdp.cme.msu.edu/.

The Ribosomal Database Project (RDP-II): sequences and tools for high-throughput rRNA analysis

The Ribosomal Database Project (RDP-II) provides the research community with aligned and annotated rRNA gene sequences, along with analysis services and a phylogenetically consistent taxonomic framework for these data. Updated monthly, these services are made available through the RDP-II website (http://rdp.cme.msu.edu/). RDP-II release 9.21 (August 2004) contains 101 632 bacterial small subunit rRNA gene sequences in aligned and annotated format. High-throughput tools for initial taxonomic placement, identification of related sequences, probe and primer testing, data navigation and subalignment download are provided. The RDP-II email address for questions or comments is rdpstaff@msu.edu.

Ribosomal Database Project: data and tools for high throughput rRNA analysis

Ribosomal Database Project (RDP; http://rdp.cme.msu.edu/) provides the research community with aligned and annotated rRNA gene sequence data, along with tools to allow researchers to analyze their own rRNA gene sequences in the RDP framework. RDP data and tools are utilized in fields as diverse as human health, microbial ecology, environmental microbiology, nucleic acid chemistry, taxonomy and phylogenetics. In addition to aligned and annotated collections of bacterial and archaeal small subunit rRNA genes, RDP now includes a collection of fungal large subunit rRNA genes. RDP tools, including Classifier and Aligner, have been updated to work with this new fungal collection. The use of high-throughput sequencing to characterize environmental microbial populations has exploded in the past several years, and as sequence technologies have improved, the sizes of environmental datasets have increased. With release 11, RDP is providing an expanded set of tools to facilitate analysis of high-throughput data, including both single-stranded and paired-end reads. In addition, most tools are now available as open source packages for download and local use by researchers with high-volume needs or who would like to develop custom analysis pipelines.

The ribosomal database project (RDP-II): introducing myRDP space and quality controlled public data

Substantial new features have been implemented at the Ribosomal Database Project in response to the increased importance of high-throughput rRNA sequence analysis in microbial ecology and related disciplines. The most important changes include quality analysis, including chimera detection, for all available rRNA sequences and the introduction of myRDP Space, a new web component designed to help researchers place their own data in context with the RDPs data. In addition, new video tutorials describe how to use RDP features. Details about RDP data and analytical functions can be found at the RDP-II website ().

In-feed antibiotic effects on the swine intestinal microbiome.

Antibiotics have been administered to agricultural animals for disease treatment, disease prevention, and growth promotion for over 50 y. The impact of such antibiotic use on the treatment of human diseases is hotly debated. We raised pigs in a highly controlled environment, with one portion of the littermates receiving a diet containing performance-enhancing antibiotics [chlortetracycline, sulfamethazine, and penicillin (known as ASP250)] and the other portion receiving the same diet but without the antibiotics. We used phylogenetic, metagenomic, and quantitative PCR-based approaches to address the impact of antibiotics on the swine gut microbiota. Bacterial phylotypes shifted after 14 d of antibiotic treatment, with the medicated pigs showing an increase in Proteobacteria (1–11%) compared with nonmedicated pigs at the same time point. This shift was driven by an increase in Escherichia coli populations. Analysis of the metagenomes showed that microbial functional genes relating to energy production and conversion were increased in the antibiotic-fed pigs. The results also indicate that antibiotic resistance genes increased in abundance and diversity in the medicated swine microbiome despite a high background of resistance genes in nonmedicated swine. Some enriched genes, such as aminoglycoside O-phosphotransferases, confer resistance to antibiotics that were not administered in this study, demonstrating the potential for indirect selection of resistance to classes of antibiotics not fed. The collateral effects of feeding subtherapeutic doses of antibiotics to agricultural animals are apparent and must be considered in cost-benefit analyses.

FunGene: the functional gene pipeline and repository

Ribosomal RNA genes have become the standard molecular markers for microbial community analysis for good reasons, including universal occurrence in cellular organisms, availability of large databases, and ease of rRNA gene region amplification and analysis. As markers, however, rRNA genes have some significant limitations. The rRNA genes are often present in multiple copies, unlike most protein-coding genes. The slow rate of change in rRNA genes means that multiple species sometimes share identical 16S rRNA gene sequences, while many more species share identical sequences in the short 16S rRNA regions commonly analyzed. In addition, the genes involved in many important processes are not distributed in a phylogenetically coherent manner, potentially due to gene loss or horizontal gene transfer. While rRNA genes remain the most commonly used markers, key genes in ecologically important pathways, e.g., those involved in carbon and nitrogen cycling, can provide important insights into community composition and function not obtainable through rRNA analysis. However, working with ecofunctional gene data requires some tools beyond those required for rRNA analysis. To address this, our Functional Gene Pipeline and Repository (FunGene; http://fungene.cme.msu.edu/) offers databases of many common ecofunctional genes and proteins, as well as integrated tools that allow researchers to browse these collections and choose subsets for further analysis, build phylogenetic trees, test primers and probes for coverage, and download aligned sequences. Additional FunGene tools are specialized to process coding gene amplicon data. For example, FrameBot produces frameshift-corrected protein and DNA sequences from raw reads while finding the most closely related protein reference sequence. These tools can help provide better insight into microbial communities by directly studying key genes involved in important ecological processes.

Gene-targeted-metagenomics reveals extensive diversity of aromatic dioxygenase genes in the environment

Understanding the relationship between gene diversity and function for important environmental processes is a major ecological research goal. We applied gene-targeted metagenomics and pyrosequencing to aromatic dioxygenase genes to obtain greater sequence depth than possible by other methods. A polymerase chain reaction (PCR) primer set designed to target a 524-bp region that confers substrate specificity of biphenyl dioxygenases yielded 2000 and 604 sequences from the 5′ and 3′ ends of PCR products, respectively, which passed our validity criteria. Sequence alignment showed three known conserved residues, as well as another seven conserved residues not reported earlier. Of the valid sequences, 95% and 41% were assigned to 22 and 3 novel clusters in that they did not include any earlier reported sequences at 0.6 distance by complete linkage clustering for sequenced regions. The greater diversity revealed by this gene-targeted approach provides deeper insights into genes potentially important in environmental processes to better understand their ecology, functional differences and evolutionary origins. We also provide criteria for primer design for this approach, as well as guidance for data processing of diverse functional genes, as gene databases for most genes of environmental relevance are limited.

RNAcentral: an international database of ncRNA sequences

Abstract The field of non-coding RNA biology has been hampered by the lack of availability of a comprehensive, up-to-date collection of accessioned RNA sequences. Here we present the first release of RNAcentral, a database that collates and integrates information from an international consortium of established RNA sequence databases. The initial release contains over 8.1 million sequences, including representatives of all major functional classes. A web portal (http://rnacentral.org) provides free access to data, search functionality, cross-references, source code and an integrated genome browser for selected species.

Bacterial Communities in the Rhizosphere of Biofuel Crops Grown on Marginal Lands as Evaluated by 16S rRNA Gene Pyrosequences

Microbes are key components of the soil environment and are important contributors to the sustainability of agricultural systems, which is especially significant for biofuel crops growing on marginal lands. We studied bacterial communities in the rhizosphere of five biofuel crops cultivated in four locations in Michigan to determine which factors were correlated to changes in the structure of those communities. Three of these sites were marginal lands in that two were not suitable for conventional agriculture and one was regulated as a brownfield due to prior industrial pollution. Bacterial community composition and structure were assessed by 454 sequencing of the 16S rRNA gene. A total of 387,111 sequences were used for multivariate statistical analysis and to test for correlation between community structure and environmental variables such as plant species, soil attributes, and location. The most abundant bacterial phyla found in the rhizosphere of all crops were Acidobacteria, Proteobacteria, Actinobacteria, and Verrucomicrobia. Bacterial communities grouped by location rather than by crop and their structures were correlated to soil attributes, principally pH, organic matter, and nutrients. The effect of plant species was low but significant, and interactions between locations, plant species, and soil attributes account for most of the explained variation in the structure of bacterial communities, showing a complex relationship between bacterial populations and their environment. Bacterial diversity was higher in the agricultural sites compared to adjacent forest sites, indicating that the cultivation of those biofuel crops increased the rRNA diversity.

ARGs-OAP: Online analysis pipeline for antibiotic resistance genes detection from metagenomic data using an integrated structured ARG-database

MOTIVATION Environmental dissemination of antibiotic resistance genes (ARGs) has become an increasing concern for public health. Metagenomics approaches can effectively detect broad profiles of ARGs in environmental samples; however, the detection and subsequent classification of ARG-like sequences are time consuming and have been severe obstacles in employing metagenomic methods. We sought to accelerate quantification of ARGs in metagenomic data from environmental samples. RESULTS A Structured ARG reference database (SARG) was constructed by integrating ARDB and CARD, the two most commonly used databases. SARG was curated to remove redundant sequences and optimized to facilitate query sequence identification by similarity. A database with a hierarchical structure (type-subtype-reference sequence) was then constructed to facilitate classification (assigning ARG-like sequence to type, subtype and reference sequence) of sequences identified through similarity search. Utilizing SARG and a previously proposed hybrid functional gene annotation pipeline, we developed an online pipeline called ARGs-OAP for fast annotation and classification of ARG-like sequences from metagenomic data. We also evaluated and proposed a set of criteria important for efficiently conducting metagenomic analysis of ARGs using ARGs-OAP. AVAILABILITY AND IMPLEMENTATION Perl script for ARGs-OAP can be downloaded from https://github.com/biofuture/Ublastx_stageone ARGs-OAP can be accessed through http://smile.hku.hk/SARGs CONTACT zhangt@hku.hk or tiedjej@msu.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.