Author
Peter Fischer Hallin
Other affiliations: Technical University of Denmark
Bio: Peter Fischer Hallin is an academic researcher from Novozymes. The author has contributed to research in topics: Genome & Bacterial genome size. The author has an hindex of 19, co-authored 39 publications receiving 5549 citations. Previous affiliations of Peter Fischer Hallin include Technical University of Denmark.
Topics: Genome, Bacterial genome size, Genome evolution, Genome project, Gene
Papers
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TL;DR: 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.
Abstract: 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.
4,949 citations
TL;DR: The presence of pathways and loci associated often with non-host-associated organisms, as well as genes associated with virulence, suggests that A. butzleri is a free-living, water-borne organism that might be classified rightfully as an emerging pathogen.
Abstract: Background
Arcobacter butzleri is a member of the epsilon subdivision of the Proteobacteria and a close taxonomic relative of established pathogens, such as Campylobacter jejuni and Helicobacter pylori. Here we present the complete genome sequence of the human clinical isolate, A. butzleri strain RM4018.
199 citations
TL;DR: It has become clear that a genome sequence represents more than just a collection of gene sequences for an organism and that information concerning the environment and growth conditions for the organism are important for interpretation of the genomic data.
Abstract: It has been more than 10 years since the first bacterial genome sequence was published. Hundreds of bacterial genome sequences are now available for comparative genomics, and searching a given protein against more than a thousand genomes will soon be possible. The subject of this review will address a relatively straightforward question: “What have we learned from this vast amount of new genomic data?” Perhaps one of the most important lessons has been that genetic diversity, at the level of large-scale variation amongst even genomes of the same species, is far greater than was thought. The classical textbook view of evolution relying on the relatively slow accumulation of mutational events at the level of individual bases scattered throughout the genome has changed. One of the most obvious conclusions from examining the sequences from several hundred bacterial genomes is the enormous amount of diversity—even in different genomes from the same bacterial species. This diversity is generated by a variety of mechanisms, including mobile genetic elements and bacteriophages. An examination of the 20 Escherichia coli genomes sequenced so far dramatically illustrates this, with the genome size ranging from 4.6 to 5.5 Mbp; much of the variation appears to be of phage origin. This review also addresses mobile genetic elements, including pathogenicity islands and the structure of transposable elements. There are at least 20 different methods available to compare bacterial genomes. Metagenomics offers the chance to study genomic sequences found in ecosystems, including genomes of species that are difficult to culture. It has become clear that a genome sequence represents more than just a collection of gene sequences for an organism and that information concerning the environment and growth conditions for the organism are important for interpretation of the genomic data. The newly proposed Minimal Information about a Genome Sequence standard has been developed to obtain this information.
182 citations
TL;DR: To predict origins of replication in prokaryotic chromosomes, the leading and lagging strands of 200 chromosomes are analysed for differences in oligomer composition and it is found that these correlate strongly with taxonomic grouping, lifestyle and molecular details of the replication process.
Abstract: Summary To predict origins of replication in prokaryotic chro- mosomes, we analyse the leading and lagging strands of 200 chromosomes for differences in oligo- mer composition and show that these correlate strongly with taxonomic grouping, lifestyle and molecular details of the replication process. While all bacteria have a preference for Gs over Cs on the leading strand, we discover that the direction of the A/T skew is determined by the polymerase- α subunit that replicates the leading strand. The strength of the strand bias varies greatly between both phyla and environments and appears to correlate with growth rate. Finally we observe much greater diversity of skew among archaea than among bacteria. We have developed a program that accurately locates the ori- gins of replication by measuring the differences between leading and lagging strand of all oligonucle- otides up to 8 bp in length. The program and results for all publicly available genomes are available from http://www.cbs.dtu.dk/services/GenomeAtlas/suppl/origin .
115 citations
TL;DR: The C. jejuni pan-genome is identified, as well as the core genome, the auxiliary genes, and genes unique between strains M1 and 81116, and the findings are discussed in the background of the proven virulence potential of M1.
Abstract: Campylobacter jejuni strain M1 (laboratory designation 99/308) is a rarely documented case of direct transmission of C. jejuni from chicken to a person, resulting in enteritis. We have sequenced the genome of C. jejuni strain M1, and compared this to 12 other C. jejuni sequenced genomes currently publicly available. Compared to these, M1 is closest to strain 81116. Based on the 13 genome sequences, we have identified the C. jejuni pan-genome, as well as the core genome, the auxiliary genes, and genes unique between strains M1 and 81116. The pan-genome contains 2,427 gene families, whilst the core genome comprised 1,295 gene families, or about two-thirds of the gene content of the average of the sequenced C. jejuni genomes. Various comparison and visualization tools were applied to the 13 C. jejuni genome sequences, including a species pan- and core genome plot, a BLAST Matrix and a BLAST Atlas. Trees based on 16S rRNA sequences and on the total gene families in each genome are presented. The findings are discussed in the background of the proven virulence potential of M1.
102 citations
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TL;DR: 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.
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.
18,256 citations
TL;DR: Prokka is introduced, a command line software tool to fully annotate a draft bacterial genome in about 10 min on a typical desktop computer, and produces standards-compliant output files for further analysis or viewing in genome browsers.
Abstract: UNLABELLED: The multiplex capability and high yield of current day DNA-sequencing instruments has made bacterial whole genome sequencing a routine affair. The subsequent de novo assembly of reads into contigs has been well addressed. The final step of annotating all relevant genomic features on those contigs can be achieved slowly using existing web- and email-based systems, but these are not applicable for sensitive data or integrating into computational pipelines. Here we introduce Prokka, a command line software tool to fully annotate a draft bacterial genome in about 10 min on a typical desktop computer. It produces standards-compliant output files for further analysis or viewing in genome browsers. AVAILABILITY AND IMPLEMENTATION: Prokka is implemented in Perl and is freely available under an open source GPLv2 license from http://vicbioinformatics.com/.
10,432 citations
TL;DR: 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, and a new Pyrosequencing Pipeline that provides tools to support analysis of ultra high-throughput rRNA sequencing data.
Abstract: 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/.
4,616 citations
TL;DR: The properties of three well-known N-terminal sequence motifs directing proteins to the secretory pathway, mitochondria and chloroplasts are described and a brief history of methods to predict subcellular localization based on these sorting signals and other sequence properties are sketched.
Abstract: Determining the subcellular localization of a protein is an important first step toward understanding its function. Here, we describe the properties of three well-known N-terminal sequence motifs directing proteins to the secretory pathway, mitochondria and chloroplasts, and sketch a brief history of methods to predict subcellular localization based on these sorting signals and other sequence properties. We then outline how to use a number of internet-accessible tools to arrive at a reliable subcellular localization prediction for eukaryotic and prokaryotic proteins. In particular, we provide detailed step-by-step instructions for the coupled use of the amino-acid sequence-based predictors TargetP, SignalP, ChloroP and TMHMM, which are all hosted at the Center for Biological Sequence Analysis, Technical University of Denmark. In addition, we describe and provide web references to other useful subcellular localization predictors. Finally, we discuss predictive performance measures in general and the performance of TargetP and SignalP in particular.
3,235 citations
TL;DR: The results reveal that transmissible and modifiable interactions between diet and microbiota influence host biology and that adiposity is transmissible from human to mouse and that it was associated with changes in serum levels of branched-chain amino acids.
Abstract: How much does the microbiota influence the host's phenotype? Ridaura et al. ([1241214][1] ; see the Perspective by [ Walker and Parkhill ][2]) obtained uncultured fecal microbiota from twin pairs discordant for body mass and transplanted them into adult germ-free mice. It was discovered that adiposity is transmissible from human to mouse and that it was associated with changes in serum levels of branched-chain amino acids. Moreover, obese-phenotype mice were invaded by members of the Bacteroidales from the lean mice, but, happily, the lean animals resisted invasion by the obese microbiota.
[1]: http://www.sciencemag.org/content/341/6150/1241214.full
[2]: /lookup/doi/10.1126/science.1243787
2,929 citations