Michelle G. Giglio

A catalog of reference genomes from the human microbiome.

News from the Inner Tube of Life A major initiative by the U.S. National Institutes of Health to sequence 900 genomes of microorganisms that live on the surfaces and orifices of the human body has established standardized protocols and methods for such large-scale reference sequencing. By combining previously accumulated data with new data, Nelson et al. (p. 994) present an initial analysis of 178 bacterial genomes. The sampling so far barely scratches the surface of the microbial diversity found on humans, but the work provides an important baseline for future analyses. Standardized protocols and methods are being established for large-scale sequencing of the microorganisms living on humans. The human microbiome refers to the community of microorganisms, including prokaryotes, viruses, and microbial eukaryotes, that populate the human body. The National Institutes of Health launched an initiative that focuses on describing the diversity of microbial species that are associated with health and disease. The first phase of this initiative includes the sequencing of hundreds of microbial reference genomes, coupled to metagenomic sequencing from multiple body sites. Here we present results from an initial reference genome sequencing of 178 microbial genomes. From 547,968 predicted polypeptides that correspond to the gene complement of these strains, previously unidentified (“novel”) polypeptides that had both unmasked sequence length greater than 100 amino acids and no BLASTP match to any nonreference entry in the nonredundant subset were defined. This analysis resulted in a set of 30,867 polypeptides, of which 29,987 (~97%) were unique. In addition, this set of microbial genomes allows for ~40% of random sequences from the microbiome of the gastrointestinal tract to be associated with organisms based on the match criteria used. Insights into pan-genome analysis suggest that we are still far from saturating microbial species genetic data sets. In addition, the associated metrics and standards used by our group for quality assurance are presented.

Whole-Genome Sequence Analysis of Pseudomonas syringae pv. phaseolicola 1448A Reveals Divergence among Pathovars in Genes Involved in Virulence and Transposition

Pseudomonas syringae pv. phaseolicola, a gram-negative bacterial plant pathogen, is the causal agent of halo blight of bean. In this study, we report on the genome sequence of P. syringae pv. phaseolicola isolate 1448A, which encodes 5,353 open reading frames (ORFs) on one circular chromosome (5,928,787 bp) and two plasmids (131,950 bp and 51,711 bp). Comparative analyses with a phylogenetically divergent pathovar, P. syringae pv. tomato DC3000, revealed a strong degree of conservation at the gene and genome levels. In total, 4,133 ORFs were identified as putative orthologs in these two pathovars using a reciprocal best-hit method, with 3,941 ORFs present in conserved, syntenic blocks. Although these two pathovars are highly similar at the physiological level, they have distinct host ranges; 1448A causes disease in beans, and DC3000 is pathogenic on tomato and Arabidopsis. Examination of the complement of ORFs encoding virulence, fitness, and survival factors revealed a substantial, but not complete, overlap between these two pathovars. Another distinguishing feature between the two pathovars is their distinctive sets of transposable elements. With access to a fifth complete pseudomonad genome sequence, we were able to identify 3,567 ORFs that likely comprise the core Pseudomonas genome and 365 ORFs that are P. syringae specific.

The IGS Standard Operating Procedure for Automated Prokaryotic Annotation

The Institute for Genome Sciences (IGS) has developed a prokaryotic annotation pipeline that is used for coding gene/RNA prediction and functional annotation of Bacteria and Archaea. The fully automated pipeline accepts one or many genomic sequences as input and produces output in a variety of standard formats. Functional annotation is primarily based on similarity searches and motif finding combined with a hierarchical rule based annotation system. The output annotations can also be loaded into a relational database and accessed through visualization tools.

BioCreative III interactive task: an overview

BackgroundThe BioCreative challenge evaluation is a community-wide effort for evaluating text mining and information extraction systems applied to the biological domain. The biocurator community, as an active user of biomedical literature, provides a diverse and engaged end user group for text mining tools. Earlier BioCreative challenges involved many text mining teams in developing basic capabilities relevant to biological curation, but they did not address the issues of system usage, insertion into the workflow and adoption by curators. Thus in BioCreative III (BC-III), the InterActive Task (IAT) was introduced to address the utility and usability of text mining tools for real-life biocuration tasks. To support the aims of the IAT in BC-III, involvement of both developers and end users was solicited, and the development of a user interface to address the tasks interactively was requested.ResultsA User Advisory Group (UAG) actively participated in the IAT design and assessment. The task focused on gene normalization (identifying gene mentions in the article and linking these genes to standard database identifiers), gene ranking based on the overall importance of each gene mentioned in the article, and gene-oriented document retrieval (identifying full text papers relevant to a selected gene). Six systems participated and all processed and displayed the same set of articles. The articles were selected based on content known to be problematic for curation, such as ambiguity of gene names, coverage of multiple genes and species, or introduction of a new gene name. Members of the UAG curated three articles for training and assessment purposes, and each member was assigned a system to review. A questionnaire related to the interface usability and task performance (as measured by precision and recall) was answered after systems were used to curate articles. Although the limited number of articles analyzed and users involved in the IAT experiment precluded rigorous quantitative analysis of the results, a qualitative analysis provided valuable insight into some of the problems encountered by users when using the systems. The overall assessment indicates that the system usability features appealed to most users, but the system performance was suboptimal (mainly due to low accuracy in gene normalization). Some of the issues included failure of species identification and gene name ambiguity in the gene normalization task leading to an extensive list of gene identifiers to review, which, in some cases, did not contain the relevant genes. The document retrieval suffered from the same shortfalls. The UAG favored achieving high performance (measured by precision and recall), but strongly recommended the addition of features that facilitate the identification of correct gene and its identifier, such as contextual information to assist in disambiguation.DiscussionThe IAT was an informative exercise that advanced the dialog between curators and developers and increased the appreciation of challenges faced by each group. A major conclusion was that the intended users should be actively involved in every phase of software development, and this will be strongly encouraged in future tasks. The IAT Task provides the first steps toward the definition of metrics and functional requirements that are necessary for designing a formal evaluation of interactive curation systems in the BioCreative IV challenge.

Strains, functions and dynamics in the expanded Human Microbiome Project

The characterization of baseline microbial and functional diversity in the human microbiome has enabled studies of microbiome-related disease, diversity, biogeography, and molecular function. The National Institutes of Health Human Microbiome Project has provided one of the broadest such characterizations so far. Here we introduce a second wave of data from the study, comprising 1,631 new metagenomes (2,355 total) targeting diverse body sites with multiple time points in 265 individuals. We applied updated profiling and assembly methods to provide new characterizations of microbiome personalization. Strain identification revealed subspecies clades specific to body sites; it also quantified species with phylogenetic diversity under-represented in isolate genomes. Body-wide functional profiling classified pathways into universal, human-enriched, and body site-enriched subsets. Finally, temporal analysis decomposed microbial variation into rapidly variable, moderately variable, and stable subsets. This study furthers our knowledge of baseline human microbial diversity and enables an understanding of personalized microbiome function and dynamics.

Comparative Genomic Evidence for a Close Relationship between the Dimorphic Prosthecate Bacteria Hyphomonas neptunium and Caulobacter crescentus

The dimorphic prosthecate bacteria (DPB) are alpha-proteobacteria that reproduce in an asymmetric manner rather than by binary fission and are of interest as simple models of development. Prior to this work, the only member of this group for which genome sequence was available was the model freshwater organism Caulobacter crescentus. Here we describe the genome sequence of Hyphomonas neptunium, a marine member of the DPB that differs from C. crescentus in that H. neptunium uses its stalk as a reproductive structure. Genome analysis indicates that this organism shares more genes with C. crescentus than it does with Silicibacter pomeroyi (a closer relative according to 16S rRNA phylogeny), that it relies upon a heterotrophic strategy utilizing a wide range of substrates, that its cell cycle is likely to be regulated in a similar manner to that of C. crescentus, and that the outer membrane complements of H. neptunium and C. crescentus are remarkably similar. H. neptunium swarmer cells are highly motile via a single polar flagellum. With the exception of cheY and cheR, genes required for chemotaxis were absent in the H. neptunium genome. Consistent with this observation, H. neptunium swarmer cells did not respond to any chemotactic stimuli that were tested, which suggests that H. neptunium motility is a random dispersal mechanism for swarmer cells rather than a stimulus-controlled navigation system for locating specific environments. In addition to providing insights into bacterial development, the H. neptunium genome will provide an important resource for the study of other interesting biological processes including chromosome segregation, polar growth, and cell aging.

Standardized description of scientific evidence using the Evidence Ontology (ECO).

The Evidence Ontology (ECO) is a structured, controlled vocabulary for capturing evidence in biological research. ECO includes diverse terms for categorizing evidence that supports annotation assertions including experimental types, computational methods, author statements and curator inferences. Using ECO, annotation assertions can be distinguished according to the evidence they are based on such as those made by curators versus those automatically computed or those made via high-throughput data review versus single test experiments. Originally created for capturing evidence associated with Gene Ontology annotations, ECO is now used in other capacities by many additional annotation resources including UniProt, Mouse Genome Informatics, Saccharomyces Genome Database, PomBase, the Protein Information Resource and others. Information on the development and use of ECO can be found at http://evidenceontology.org. The ontology is freely available under Creative Commons license (CC BY-SA 3.0), and can be downloaded in both Open Biological Ontologies and Web Ontology Language formats at http://code.google.com/p/evidenceontology. Also at this site is a tracker for user submission of term requests and questions. ECO remains under active development in response to user-requested terms and in collaborations with other ontologies and database resources. Database URL: Evidence Ontology Web site: http://evidenceontology.org

The Confidence Information Ontology: A Step Towards a Standard for Asserting Confidence in Annotations

Biocuration has become a cornerstone for analyses in biology, and to meet needs, the amount of annotations has considerably grown in recent years. However, the reliability of these annotations varies; it has thus become necessary to be able to assess the confidence in annotations. Although several resources already provide confidence information about the annotations that they produce, a standard way of providing such information has yet to be defined. This lack of standardization undermines the propagation of knowledge across resources, as well as the credibility of results from high-throughput analyses. Seeded at a workshop during the Biocuration 2012 conference, a working group has been created to address this problem. We present here the elements that were identified as essential for assessing confidence in annotations, as well as a draft ontology—the Confidence Information Ontology—to illustrate how the problems identified could be addressed. We hope that this effort will provide a home for discussing this major issue among the biocuration community. Tracker URL: https://github.com/BgeeDB/confidence-information-ontology Ontology URL: https://raw.githubusercontent.com/BgeeDB/confidence-information-ontology/master/src/ontology/cio-simple.obo

Applying the Gene Ontology in microbial annotation

The ever-increasing number of microbial sequencing projects necessitates a standardized system for the capture of genomic data to ensure that the flood of information produced can be effectively utilized. The Gene Ontology (GO) provides the standard for gene product annotations in the areas of molecular function, biological process and cellular component. A recent effort by the Plant-Associated Microbe Gene Ontology (PAMGO) Consortium has produced more than 800 new GO terms specific for annotating interactions between microbes and their hosts and other symbiotic interactions. In addition, there have been changes and additions to the GO annotation format and evidence storage system to reflect the needs of the microbial annotation community. The capture of annotation information with systems like the GO is absolutely essential to enable the efficient mining of annotation information across diverse genomes and thus to further biological research in meaningful ways.

An ontology for microbial phenotypes

BackgroundPhenotypic data are routinely used to elucidate gene function in organisms amenable to genetic manipulation. However, previous to this work, there was no generalizable system in place for the structured storage and retrieval of phenotypic information for bacteria.ResultsThe Ontology of Microbial Phenotypes (OMP) has been created to standardize the capture of such phenotypic information from microbes. OMP has been built on the foundations of the Basic Formal Ontology and the Phenotype and Trait Ontology. Terms have logical definitions that can facilitate computational searching of phenotypes and their associated genes. OMP can be accessed via a wiki page as well as downloaded from SourceForge. Initial annotations with OMP are being made for Escherichia coli using a wiki-based annotation capture system. New OMP terms are being concurrently developed as annotation proceeds.ConclusionsWe anticipate that diverse groups studying microbial genetics and associated phenotypes will employ OMP for standardizing microbial phenotype annotation, much as the Gene Ontology has standardized gene product annotation. The resulting OMP resource and associated annotations will facilitate prediction of phenotypes for unknown genes and result in new experimental characterization of phenotypes and functions.