Differentially Methylated Genomic Regions in Birth-Weight Discordant Twin Pairs.

Poor nutrition during critical growth phases may alter the structural and physiologic development of vital organs thus "programming" the susceptibility to adult-onset diseases and disease-related health conditions. Epigenome-wide association studies have been performed in birth-weight discordant twin pairs to find evidence for such "programming" effects, but no significant results emerged. We further investigated this issue using a new computational approach: Instead of probing single genomic sites for significant alterations in epigenetic marks, we scan for differentially methylated genomic regions. Whole genome DNA methylation levels were measured in whole blood from 150 pairs of adult identical twins discordant for birth-weight. Intrapair differential DNA methylation was associated with qualitative (large or small) and quantitative (percentage) birth-weight discordance at each genomic site using regression models adjusting for age and sex. Based on the regression results, genomic regions with consistent alteration patterns of DNA methylation were located and tested for significant robustness using computational permutation tests. This yielded an interesting genomic region on chromosome 1, which is significantly differentially methylated for quantitative birth-weight discordance. The region covers two genes (TYW3 and CRYZ) both reportedly associated with metabolism. We conclude that prenatal conditions for birth-weight discordance may result in persistent epigenetic modifications potentially affecting even adult health.

Mature Epitope Density--a strategy for target selection based on immunoinformatics and exported prokaryotic proteins.

BACKGROUND: Current immunological bioinformatic approaches focus on the prediction of allele-specific epitopes capable of triggering immunogenic activity. The prediction of major histocompatibility complex (MHC) class I epitopes is well studied, and various software solutions exist for this purpose. However, currently available tools do not account for the concentration of epitope products in the mature protein product and its relation to the reliability of target selection. RESULTS: We developed a computational strategy based on measuring the epitope's concentration in the mature protein, called Mature Epitope Density (MED). Our method, though simple, is capable of identifying promising vaccine targets. Our online software implementation provides a computationally light and reliable analysis of bacterial exoproteins and their potential for vaccines or diagnosis projects against pathogenic organisms. We evaluated our computational approach by using the Mycobacterium tuberculosis (Mtb) H37Rv exoproteome as a gold standard model. A literature search was carried out on 60 out of 553 Mtb's predicted exoproteins, looking for previous experimental evidence concerning their possible antigenicity. Half of the 60 proteins were classified as highest scored by the MED statistic, while the other half were classified as lowest scored. Among the lowest scored proteins, ~13% were confirmed as not related to antigenicity or not contributing to the bacterial pathogenicity, and 70% of the highest scored proteins were confirmed as related. There was no experimental evidence of antigenic or pathogenic contributions for three of the highest MED-scored Mtb proteins. Hence, these three proteins could represent novel putative vaccine and drug targets for Mtb. A web version of MED is publicly available online at http://med.mmci.uni-saarland.de/. CONCLUSIONS: The software presented here offers a practical and accurate method to identify potential vaccine and diagnosis candidates against pathogenic bacteria by "reading" results from well-established reverse vaccinology software in a novel way, considering the epitope's concentration in the mature portion of the protein.

Genome sequence of the Corynebacterium pseudotuberculosis Cp316 strain, isolated from the abscess of a Californian horse.

The bacterium Corynebacterium pseudotuberculosis is of major veterinary importance because it affects livestock, particularly sheep, goats, and horses, in several countries, including Australia, Brazil, the United States, and Canada, resulting in significant economic losses. In the present study, we describe the complete genome of the Corynebacterium pseudotuberculosis Cp316 strain, biovar equi, isolated from the abscess of a North American horse.

Complete genome sequence of Corynebacterium pseudotuberculosis Cp31, isolated from an Egyptian buffalo.

Corynebacterium pseudotuberculosis is of major veterinary importance because it affects many animal species, causing economically significant livestock diseases and losses. Therefore, the genomic sequencing of various lines of this organism, isolated from different hosts, will aid in the development of diagnostic methods and new prevention and treatment strategies and improve our knowledge of the biology of this microorganism. In this study, we present the genome of C. pseudotuberculosis Cp31, isolated from a buffalo in Egypt.

Genome sequence of Exiguobacterium antarcticum B7, isolated from a biofilm in Ginger Lake, King George Island, Antarctica.

Exiguobacterium antarcticum is a psychotropic bacterium isolated for the first time from microbial mats of Lake Fryxell in Antarctica. Many organisms of the genus Exiguobacterium are extremophiles and have properties of biotechnological interest, e.g., the capacity to adapt to cold, which make this genus a target for discovering new enzymes, such as lipases and proteases, in addition to improving our understanding of the mechanisms of adaptation and survival at low temperatures. This study presents the genome of E. antarcticum B7, isolated from a biofilm sample of Ginger Lake on King George Island, Antarctic peninsula.

Whole-genome sequence of Corynebacterium pseudotuberculosis strain Cp162, isolated from camel.

Corynebacterium pseudotuberculosis is a pathogen of great veterinary and economic importance, since it affects livestock, mainly sheep and goats, worldwide, together with reports of its presence in camels in several Arabic, Asiatic, and East and West African countries, as well as Australia. In this article, we report the genome sequence of Corynebacterium pseudotuberculosis strain Cp162, collected from the external neck abscess of a camel in the United Kingdom.

Complete genome sequence of Corynebacterium pseudotuberculosis strain Cp267, isolated from a llama.

In this work we report the genome of Corynebacterium pseudotuberculosis strain 267, isolated from a llama. This pathogen is of great veterinary and economic importance, as it is the cause of caseous lymphadenitis in several livestock species around the world and causes significant losses due to the high cost of treatment.

Complete genome sequence of Corynebacterium pseudotuberculosis strain 1/06-A, isolated from a horse in North America.

Corynebacterium pseudotuberculosis causes disease in several animal species, although distinct biovars exist that appear to be restricted to specific hosts. In order to facilitate a better understanding of the differences between biovars, we report here the complete genome sequence of the equine pathogen Corynebacterium pseudotuberculosis strain 1/06-A.

Complete genome sequences of Corynebacterium pseudotuberculosis strains 3/99-5 and 42/02-A, isolated from sheep in Scotland and Australia, respectively.

Here, we report the whole-genome sequences of two ovine-pathogenic Corynebacterium pseudotuberculosis isolates: strain 3/99-5, which represents the first C. pseudotuberculosis genome originating from the United Kingdom, and 42/02-A, the second from Australia. These genome sequences will contribute to the objective of determining the global pan-genome of this bacterium.

The Corynebacterium pseudotuberculosis in silico predicted pan-exoproteome.

BACKGROUND: Pan-genomic studies aim, for instance, at defining the core, dispensable and unique genes within a species. A pan-genomics study for vaccine design tries to assess the best candidates for a vaccine against a specific pathogen. In this context, rather than studying genes predicted to be exported in a single genome, with pan-genomics it is possible to study genes present in different strains within the same species, such as virulence factors. The target organism of this pan-genomic work here presented is Corynebacterium pseudotuberculosis, the etiologic agent of caseous lymphadenitis (CLA) in goat and sheep, which causes significant economic losses in those herds around the world. Currently, only a few antigens against CLA are known as being the basis of commercial and still ineffective vaccines. In this regard, the here presented work analyses, in silico, five C. pseudotuberculosis genomes and gathers data to predict common exported proteins in all five genomes. These candidates were also compared to two recent C. pseudotuberculosis in vitro exoproteome results. RESULTS: The complete genome of five C. pseudotuberculosis strains (1002, C231, I19, FRC41 and PAT10) were submitted to pan-genomics analysis, yielding 306, 59 and 12 gene sets, respectively, representing the core, dispensable and unique in silico predicted exported pan-genomes. These sets bear 150 genes classified as secreted (SEC) and 227 as potentially surface exposed (PSE). Our findings suggest that the main C. pseudotuberculosis in vitro exoproteome could be greater, appended by a fraction of the 35 proteins formerly predicted as making part of the variant in vitro exoproteome. These genomes were manually curated for correct methionine initiation and redeposited with a total of 1885 homogenized genes. CONCLUSIONS: The in silico prediction of exported proteins has allowed to define a list of putative vaccine candidate genes present in all five complete C. pseudotuberculosis genomes. Moreover, it has also been possible to define the in silico predicted dispensable and unique C. pseudotuberculosis exported proteins. These results provide in silico evidence to further guide experiments in the areas of vaccines, diagnosis and drugs. The work here presented is the first whole C. pseudotuberculosis in silico predicted pan-exoproteome completed till today.

Genetic variation influencing DNA methylation provides insights into molecular mechanisms regulating genomic function.

We determined the relationships between DNA sequence variation and DNA methylation using blood samples from 3,799 Europeans and 3,195 South Asians. We identify 11,165,559 SNP-CpG associations (methylation quantitative trait loci (meQTL), P < 10-14), including 467,915 meQTL that operate in trans. The meQTL are enriched for functionally relevant characteristics, including shared chromatin state, High-throuhgput chromosome conformation interaction, and association with gene expression, metabolic variation and clinical traits. We use molecular interaction and colocalization analyses to identify multiple nuclear regulatory pathways linking meQTL loci to phenotypic variation, including UBASH3B (body mass index), NFKBIE (rheumatoid arthritis), MGA (blood pressure) and COMMD7 (white cell counts). For rs6511961 , chromatin immunoprecipitation followed by sequencing (ChIP-seq) validates zinc finger protein (ZNF)333 as the likely trans acting effector protein. Finally, we used interaction analyses to identify population- and lineage-specific meQTL, including rs174548 in FADS1, with the strongest effect in CD8+ T cells, thus linking fatty acid metabolism with immune dysregulation and asthma. Our study advances understanding of the potential pathways linking genetic variation to human phenotype.

Whole-genome sequence of Corynebacterium pseudotuberculosis PAT10 strain isolated from sheep in Patagonia, Argentina.

In this work, we report the complete genome sequence of a Corynebacterium pseudotuberculosis PAT10 isolate, collected from a lung abscess in an Argentine sheep in Patagonia, whose pathogen also required an investigation of its pathogenesis. Thus, the analysis of the genome sequence offers a means to better understanding of the molecular and genetic basis of virulence of this bacterium.

Complete genome sequence of type strain Campylobacter fetus subsp. venerealis NCTC 10354T.

Campylobacter fetus subsp. venerealis is the etiologic agent of bovine genital campylobacteriosis, a sexually transmitted disease of cattle that is of worldwide importance. The complete sequencing and annotation of the genome of the type strain C. fetus subsp. venerealis NCTC 10354(T) are reported.

Complete genome sequence of Corynebacterium pseudotuberculosis strain CIP 52.97, isolated from a horse in Kenya.

In this work, we report the whole-genome sequence of Corynebacterium pseudotuberculosis bv. equi strain CIP 52.97 (Collection Institut Pasteur), isolated in 1952 from a case of ulcerative lymphangitis in a Kenyan horse, which has evidently caused significant losses to agribusiness. Therefore, obtaining this genome will allow the detection of important targets for postgenomic studies, with the aim of minimizing problems caused by this microorganism.

Orthologous proteins of experimental de- and remyelination are differentially regulated in the CSF proteome of multiple sclerosis subtypes.

OBJECTIVE: Here, we applied a multi-omics approach (i) to examine molecular pathways related to de- and remyelination in multiple sclerosis (MS) lesions; and (ii) to translate these findings to the CSF proteome in order to identify molecules that are differentially expressed among MS subtypes. METHODS: To relate differentially expressed genes in MS lesions to de- and remyelination, we compared transcriptome of MS lesions to transcriptome of cuprizone (CPZ)-induced de- and remyelination. Protein products of the overlapping orthologous genes were measured within the CSF by quantitative proteomics, parallel reaction monitoring (PRM). Differentially regulated proteins were correlated with molecular markers of inflammation by using MesoScale multiplex immunoassay. Expression kinetics of differentially regulated orthologous genes and proteins were examined in the CPZ model. RESULTS: In the demyelinated and remyelinated corpus callosum, we detected 1239 differentially expressed genes; 91 orthologues were also differentially expressed in MS lesions. Pathway analysis of these orthologues suggested that the TYROBP (DAP12)-TREM2 pathway, TNF-receptor 1, CYBA and the proteasome subunit PSMB9 were related to de- and remyelination. We designed 129 peptides representing 51 orthologous proteins, measured them by PRM in 97 individual CSF, and compared their levels between relapsing (n = 40) and progressive MS (n = 57). Four proteins were differentially regulated among relapsing and progressive MS: tyrosine protein kinase receptor UFO (UFO), TIMP-1, apolipoprotein C-II (APOC2), and beta-2-microglobulin (B2M). The orthologous genes/proteins in the mouse brain peaked during acute remyelination. UFO, TIMP-1 and B2M levels correlated inversely with inflammation in the CSF (IL-6, MCP-1/CCL2, TARC/CCL17). APOC2 showed positive correlation with IL-2, IL-16 and eotaxin-3/CCL26. CONCLUSIONS: Pathology-based multi-omics identified four CSF markers that were differentially expressed in MS subtypes. Upregulated TIMP-1, UFO and B2M orthologues in relapsing MS were associated with reduced inflammation and reflected reparatory processes, in contrast to the upregulated orthologue APOC2 in progressive MS that reflected changes in lipid metabolism associated with increased inflammation.

LifeStyle-Specific-Islands (LiSSI): Integrated Bioinformatics Platform for Genomic Island Analysis.

Distinct bacteria are able to cope with highly diverse lifestyles; for instance, they can be free living or host-associated. Thus, these organisms must possess a large and varied genomic arsenal to withstand different environmental conditions. To facilitate the identification of genomic features that might influence bacterial adaptation to a specific niche, we introduce LifeStyle-Specific-Islands (LiSSI). LiSSI combines evolutionary sequence analysis with statistical learning (Random Forest with feature selection, model tuning and robustness analysis). In summary, our strategy aims to identify conserved consecutive homology sequences (islands) in genomes and to identify the most discriminant islands for each lifestyle.

Metagenomic evidence for the presence of phototrophic Gemmatimonadetes bacteria in diverse environments.

Gemmatimonadetes represents a poorly understood bacterial phylum with only a handful of cultured species. Recently, one of its few representatives, Gemmatimonas phototrophica, was found to contain purple bacterial photosynthetic reaction centres. However, almost nothing is known about the environmental distribution of phototrophic Gemmatimonadetes bacteria. To fill this gap, we took advantage of fast-growing public metagenomic databases and performed an extensive survey of metagenomes deposited into the NCBI's WGS database, the JGI's IMG webserver and the MG-RAST webserver. By employing Mg protoporphyrin IX monomethyl ester oxidative cyclase (AcsF) as a marker gene, we identified 291 AcsF fragments (24-361 amino acids long) that are closely related to G. phototrophica from 161 metagenomes originating from various habitats, including air, river waters/sediment, estuarine waters, lake waters, biofilms, plant surfaces, intertidal sediment, soils, springs and wastewater treatment plants, but none from marine waters or sediment. Based on AcsF hit counts, phototrophic Gemmatimonadetes bacteria make up 0.4-11.9% of whole phototrophic microbial communities in these habitats. Unexpectedly, an almost complete 37.9 kb long photosynthesis gene cluster with identical gene composition and arrangement to those in G. phototrophica was reconstructed from the Odense wastewater metagenome, only differing in a 7.2 kb long non-photosynthesis-gene insert. These data suggest that phototrophic Gemmatimonadetes bacteria are much more widely distributed in the environment and exhibit a higher genetic diversity than previously thought.

GIPSy: Genomic island prediction software.

Bacteria are highly diverse organisms that are able to adapt to a broad range of environments and hosts due to their high genomic plasticity. Horizontal gene transfer plays a pivotal role in this genome plasticity and in evolution by leaps through the incorporation of large blocks of genome sequences, ordinarily known as genomic islands (GEIs). GEIs may harbor genes encoding virulence, metabolism, antibiotic resistance and symbiosis-related functions, namely pathogenicity islands (PAIs), metabolic islands (MIs), resistance islands (RIs) and symbiotic islands (SIs). Although many software for the prediction of GEIs exist, they only focus on PAI prediction and present other limitations, such as complicated installation and inconvenient user interfaces. Here, we present GIPSy, the genomic island prediction software, a standalone and user-friendly software for the prediction of GEIs, built on our previously developed pathogenicity island prediction software (PIPS). We also present four application cases in which we crosslink data from literature to PAIs, MIs, RIs and SIs predicted by GIPSy. Briefly, GIPSy correctly predicted the following previously described GEIs: 13 PAIs larger than 30kb in Escherichia coli CFT073; 1 MI for Burkholderia pseudomallei K96243, which seems to be a miscellaneous island; 1 RI of Acinetobacter baumannii AYE, named AbaR1; and, 1 SI of Mesorhizobium loti MAFF303099 presenting a mosaic structure. GIPSy is the first life-style-specific genomic island prediction software to perform analyses of PAIs, MIs, RIs and SIs, opening a door for a better understanding of bacterial genome plasticity and the adaptation to new traits.

On the limits of computational functional genomics for bacterial lifestyle prediction.

We review the level of genomic specificity regarding actinobacterial pathogenicity. As they occupy various niches in diverse habitats, one may assume the existence of lifestyle-specific genomic features. We include 240 actinobacteria classified into four pathogenicity classes: human pathogens (HPs), broad-spectrum pathogens (BPs), opportunistic pathogens (OPs) and non-pathogenic (NP). We hypothesize: (H1) Pathogens (HPs and BPs) possess specific pathogenicity signature genes. (H2) The same holds for OPs. (H3) Broad-spectrum and exclusively HPs cannot be distinguished from each other because of an observation bias, i.e. many HPs might yet be unclassified BPs. (H4) There is no intrinsic genomic characteristic of OPs compared with pathogens, as small mutations are likely to play a more dominant role to survive the immune system. To study these hypotheses, we implemented a bioinformatics pipeline that combines evolutionary sequence analysis with statistical learning methods (Random Forest with feature selection, model tuning and robustness analysis). Essentially, we present orthologous gene sets that computationally distinguish pathogens from NPs (H1). We further show a clear limit in differentiating OPs from both NPs (H2) and pathogens (H4). HPs may also not be distinguished from bacteria annotated as BPs based only on a small set of orthologous genes (H3), as many HPs might as well target a broad range of mammals but have not been annotated accordingly. In conclusion, we illustrate that even in the post-genome era and despite next-generation sequencing technology, our ability to efficiently deduce real-world conclusions, such as pathogenicity classification, remains quite limited.

KeyPathwayMiner 4.0: condition-specific pathway analysis by combining multiple omics studies and networks with Cytoscape.

BACKGROUND: Over the last decade network enrichment analysis has become popular in computational systems biology to elucidate aberrant network modules. Traditionally, these approaches focus on combining gene expression data with protein-protein interaction (PPI) networks. Nowadays, the so-called omics technologies allow for inclusion of many more data sets, e.g. protein phosphorylation or epigenetic modifications. This creates a need for analysis methods that can combine these various sources of data to obtain a systems-level view on aberrant biological networks. RESULTS: We present a new release of KeyPathwayMiner (version 4.0) that is not limited to analyses of single omics data sets, e.g. gene expression, but is able to directly combine several different omics data types. Version 4.0 can further integrate existing knowledge by adding a search bias towards sub-networks that contain (avoid) genes provided in a positive (negative) list. Finally the new release now also provides a set of novel visualization features and has been implemented as an app for the standard bioinformatics network analysis tool: Cytoscape. CONCLUSION: With KeyPathwayMiner 4.0, we publish a Cytoscape app for multi-omics based sub-network extraction. It is available in Cytoscape's app store http://apps.cytoscape.org/apps/keypathwayminer or via http://keypathwayminer.mpi-inf.mpg.de.