David W. Ussery

RNAmmer: consistent and rapid annotation of ribosomal RNA genes

The publication of a complete genome sequence is usually accompanied by annotations of its genes. In contrast to protein coding genes, genes for ribosomal RNA (rRNA) are often poorly or inconsistently annotated. This makes comparative studies based on rRNA genes difficult. We have therefore created computational predictors for the major rRNA species from all kingdoms of life and compiled them into a program called RNAmmer. The program uses hidden Markov models trained on data from the 5S ribosomal RNA database and the European ribosomal RNA database project. A pre-screening step makes the method fast with little loss of sensitivity, enabling the analysis of a complete bacterial genome in less than a minute. Results from running RNAmmer on a large set of genomes indicate that the location of rRNAs can be predicted with a very high level of accuracy. Novel, unannotated rRNAs are also predicted in many genomes. The software as well as the genome analysis results are available at the CBS web server.

Genome sequencing and analysis of the versatile cell factory Aspergillus niger CBS 513.88

The filamentous fungus Aspergillus niger is widely exploited by the fermentation industry for the production of enzymes and organic acids, particularly citric acid. We sequenced the 33.9-megabase genome of A. niger CBS 513.88, the ancestor of currently used enzyme production strains. A high level of synteny was observed with other aspergilli sequenced. Strong function predictions were made for 6,506 of the 14,165 open reading frames identified. A detailed description of the components of the protein secretion pathway was made and striking differences in the hydrolytic enzyme spectra of aspergilli were observed. A reconstructed metabolic network comprising 1,069 unique reactions illustrates the versatile metabolism of A. niger. Noteworthy is the large number of major facilitator superfamily transporters and fungal zinc binuclear cluster transcription factors, and the presence of putative gene clusters for fumonisin and ochratoxin A synthesis.

Multilocus Sequence Typing of Total Genome Sequenced Bacteria

ABSTRACT Accurate strain identification is essential for anyone working with bacteria. For many species, multilocus sequence typing (MLST) is considered the “gold standard” of typing, but it is traditionally performed in an expensive and time-consuming manner. As the costs of whole-genome sequencing (WGS) continue to decline, it becomes increasingly available to scientists and routine diagnostic laboratories. Currently, the cost is below that of traditional MLST. The new challenges will be how to extract the relevant information from the large amount of data so as to allow for comparison over time and between laboratories. Ideally, this information should also allow for comparison to historical data. We developed a Web-based method for MLST of 66 bacterial species based on WGS data. As input, the method uses short sequence reads from four sequencing platforms or preassembled genomes. Updates from the MLST databases are downloaded monthly, and the best-matching MLST alleles of the specified MLST scheme are found using a BLAST-based ranking method. The sequence type is then determined by the combination of alleles identified. The method was tested on preassembled genomes from 336 isolates covering 56 MLST schemes, on short sequence reads from 387 isolates covering 10 schemes, and on a small test set of short sequence reads from 29 isolates for which the sequence type had been determined by traditional methods. The method presented here enables investigators to determine the sequence types of their isolates on the basis of WGS data. This method is publicly available at www.cbs.dtu.dk/services/MLST.

Comparison of 61 Sequenced Escherichia coli Genomes

Escherichia coli is an important component of the biosphere and is an ideal model for studies of processes involved in bacterial genome evolution. Sixty-one publically available E. coli and Shigella spp. sequenced genomes are compared, using basic methods to produce phylogenetic and proteomics trees, and to identify the pan- and core genomes of this set of sequenced strains. A hierarchical clustering of variable genes allowed clear separation of the strains into clusters, including known pathotypes; clinically relevant serotypes can also be resolved in this way. In contrast, when in silico MLST was performed, many of the various strains appear jumbled and less well resolved. The predicted pan-genome comprises 15,741 gene families, and only 993 (6%) of the families are represented in every genome, comprising the core genome. The variable or ‘accessory’ genes thus make up more than 90% of the pan-genome and about 80% of a typical genome; some of these variable genes tend to be co-localized on genomic islands. The diversity within the species E. coli, and the overlap in gene content between this and related species, suggests a continuum rather than sharp species borders in this group of Enterobacteriaceae.

Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes.

Most current approaches for analyzing metagenomic data rely on comparisons to reference genomes, but the microbial diversity of many environments extends far beyond what is covered by reference databases. De novo segregation of complex metagenomic data into specific biological entities, such as particular bacterial strains or viruses, remains a largely unsolved problem. Here we present a method, based on binning co-abundant genes across a series of metagenomic samples, that enables comprehensive discovery of new microbial organisms, viruses and co-inherited genetic entities and aids assembly of microbial genomes without the need for reference sequences. We demonstrate the method on data from 396 human gut microbiome samples and identify 7,381 co-abundance gene groups (CAGs), including 741 metagenomic species (MGS). We use these to assemble 238 high-quality microbial genomes and identify affiliations between MGS and hundreds of viruses or genetic entities. Our method provides the means for comprehensive profiling of the diversity within complex metagenomic samples.

PanViz: interactive visualization of the structure of functionally annotated pangenomes

Summary: PanViz is a novel, interactive, visualization tool for pangenome analysis. PanViz allows visualization of changes in gene group (groups of similar genes across genomes) classification as different subsets of pangenomes are selected, as well as comparisons of individual genomes to pangenomes with gene ontology based navigation of gene groups. Furthermore it allows for rich and complex visual querying of gene groups in the pangenome. PanViz visualizations require no external programs and are easily sharable, allowing for rapid pangenome analyses. Availability and Implementation: PanViz is written entirely in JavaScript and is available on https://github.com/thomasp85/PanViz. A companion R package that facilitates the creation of PanViz visualizations from a range of data formats is released through Bioconductor and is available at https://bioconductor.org/packages/PanVizGenerator. Contact: thomasp85@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.

The transcriptional landscape and small RNAs of Salmonella enterica serovar Typhimurium

More than 50 y of research have provided great insight into the physiology, metabolism, and molecular biology of Salmonella enterica serovar Typhimurium (S. Typhimurium), but important gaps in our knowledge remain. It is clear that a precise choreography of gene expression is required for Salmonella infection, but basic genetic information such as the global locations of transcription start sites (TSSs) has been lacking. We combined three RNA-sequencing techniques and two sequencing platforms to generate a robust picture of transcription in S. Typhimurium. Differential RNA sequencing identified 1,873 TSSs on the chromosome of S. Typhimurium SL1344 and 13% of these TSSs initiated antisense transcripts. Unique findings include the TSSs of the virulence regulators phoP, slyA, and invF. Chromatin immunoprecipitation revealed that RNA polymerase was bound to 70% of the TSSs, and two-thirds of these TSSs were associated with σ70 (including phoP, slyA, and invF) from which we identified the −10 and −35 motifs of σ70-dependent S. Typhimurium gene promoters. Overall, we corrected the location of important genes and discovered 18 times more promoters than identified previously. S. Typhimurium expresses 140 small regulatory RNAs (sRNAs) at early stationary phase, including 60 newly identified sRNAs. Almost half of the experimentally verified sRNAs were found to be unique to the Salmonella genus, and <20% were found throughout the Enterobacteriaceae. This description of the transcriptional map of SL1344 advances our understanding of S. Typhimurium, arguably the most important bacterial infection model.

The chromatin-associated protein H-NS alters DNA topology in vitro.

H‐NS is one of the two most abundant proteins in the bacterial nucleoid and influences the expression of a number of genes. We have studied the interaction of H‐NS with DNA; purified H‐NS was demonstrated to constrain negative DNA supercoils in vitro. This provides support for the hypothesis that H‐NS influences transcription via changes in DNA topology, and is evidence of a structural role for H‐NS in bacterial chromatin. The effects of H‐NS on topology were only observed at sub‐saturating concentrations of the protein. In addition, a preferred binding site on DNA was identified by DNase I footprinting at sub‐saturating H‐NS concentrations. This site corresponded to a curved sequence element which we previously showed, by in vivo studies, to be a site at which H‐NS influences transcription of the proU operon. When present in saturating concentrations, H‐NS did not constrain supercoils and bound to DNA in a sequence‐independent fashion, covering all DNA molecules from end to end, suggesting that H‐NS may form distinct complexes with DNA at different H‐NS:DNA ratios. The data presented here provide direct support for the hypothesis that H‐NS acts at specific sites to influence DNA topology and, hence, transcription.

On the total number of genes and their length distribution in complete microbial genomes

In sequenced microbial genomes, some of the annotated genes are actually not protein-coding genes, but rather open reading frames that occur by chance. Therefore, the number of annotated genes is higher than the actual number of genes for most of these microbes. Comparison of the length distribution of the annotated genes with the length distribution of those matching a known protein reveals that too many short genes are annotated in many genomes. Here we estimate the true number of protein-coding genes for sequenced genomes. Although it is often claimed that Escherichia coli has about 4300 genes, we show that it probably has only approximately 3800 genes, and that a similar discrepancy exists for almost all published genomes.

Genomic taxonomy of vibrios

BackgroundVibrio taxonomy has been based on a polyphasic approach. In this study, we retrieve useful taxonomic information (i.e. data that can be used to distinguish different taxonomic levels, such as species and genera) from 32 genome sequences of different vibrio species. We use a variety of tools to explore the taxonomic relationship between the sequenced genomes, including Multilocus Sequence Analysis (MLSA), supertrees, Average Amino Acid Identity (AAI), genomic signatures, and Genome BLAST atlases. Our aim is to analyse the usefulness of these tools for species identification in vibrios.ResultsWe have generated four new genome sequences of three Vibrio species, i.e., V. alginolyticus 40B, V. harveyi-like 1DA3, and V. mimicus strains VM573 and VM603, and present a broad analyses of these genomes along with other sequenced Vibrio species. The genome atlas and pangenome plots provide a tantalizing image of the genomic differences that occur between closely related sister species, e.g. V. cholerae and V. mimicus. The vibrio pangenome contains around 26504 genes. The V. cholerae core genome and pangenome consist of 1520 and 6923 genes, respectively. Pangenomes might allow different strains of V. cholerae to occupy different niches. MLSA and supertree analyses resulted in a similar phylogenetic picture, with a clear distinction of four groups (Vibrio core group, V. cholerae-V. mimicus, Aliivibrio spp., and Photobacterium spp.). A Vibrio species is defined as a group of strains that share > 95% DNA identity in MLSA and supertree analysis, > 96% AAI, ≤ 10 genome signature dissimilarity, and > 61% proteome identity. Strains of the same species and species of the same genus will form monophyletic groups on the basis of MLSA and supertree.ConclusionThe combination of different analytical and bioinformatics tools will enable the most accurate species identification through genomic computational analysis. This endeavour will culminate in the birth of the online genomic taxonomy whereby researchers and end-users of taxonomy will be able to identify their isolates through a web-based server. This novel approach to microbial systematics will result in a tremendous advance concerning biodiversity discovery, description, and understanding.