MALDI-TOF MS Supplementary database for species identification employing the yeast diversity encountered on southern Brazil grapes.

The study of grape microflora is of interest when autochthonous yeasts, which are related to typical wine characteristics, are intended to be used in winemaking. The election of matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF MS) as the first method for yeast identification was based on its accuracy and rapidity compared to alternative laboratory protocols for identification. The aims of this study are to consolidate the MALDI-TOF MS Supplementary database for environmental yeasts already constructed, to expand it through the addition of standard spectra of not included yeast species, and to discuss the grape microflora encountered in Southern Brazil. A total of 358 strains, isolated from grape berries, were submitted to protein profiling employing Biotyper and Supplementary database. Molecular biology techniques were used as alternatives to identify 6.4% of strains not promptly designated by protein profiling. These strains corresponded to the species Candida californica, Zygoascus meyerae, Candida akabanensis, Candida azyma, and Hanseniaspora vineae. The MALDI-TOF MS spectra of the identified species were added to Supplementary database. The presented results strengthen the need for further expansion of the mass spectra database to broaden its microbiological application.

Fine-mapping analysis revealed complex pleiotropic effect and tissue-specific regulatory mechanism of TNFSF15 in primary biliary cholangitis, Crohn's disease and leprosy.

Genetic polymorphism within the 9q32 locus is linked with increased risk of several diseases, including Crohn's disease (CD), primary biliary cholangitis (PBC) and leprosy. The most likely disease-causing gene within 9q32 is TNFSF15, which encodes the pro-inflammatory cytokine TNF super-family member 15, but it was unknown whether these disparate diseases were associated with the same genetic variance in 9q32, and how variance within this locus might contribute to pathology. Using genetic data from published studies on CD, PBC and leprosy we revealed that bearing a T allele at rs6478108/rs6478109 (r(2) = 1) or rs4979462 was significantly associated with increased risk of CD and decreased risk of leprosy, while the T allele at rs4979462 was associated with significantly increased risk of PBC. In vitro analyses showed that the rs6478109 genotype significantly affected TNFSF15 expression in cells from whole blood of controls, while functional annotation using publicly-available data revealed the broad cell type/tissue-specific regulatory potential of variance at rs6478109 or rs4979462. In summary, we provide evidence that variance within TNFSF15 has the potential to affect cytokine expression across a range of tissues and thereby contribute to protection from infectious diseases such as leprosy, while increasing the risk of immune-mediated diseases including CD and PBC.

A novel Markov Blanket-based repeated-fishing strategy for capturing phenotype-related biomarkers in big omics data.

BACKGROUND: We propose a novel Markov Blanket-based repeated-fishing strategy (MBRFS) in attempt to increase the power of existing Markov Blanket method (DASSO-MB) and maintain its advantages in omic data analysis. RESULTS: Both simulation and real data analysis were conducted to assess its performances by comparing with other methods including χ(2) test with Bonferroni and B-H adjustment, least absolute shrinkage and selection operator (LASSO) and DASSO-MB. A serious of simulation studies showed that the true discovery rate (TDR) of proposed MBRFS was always close to zero under null hypothesis (odds ratio = 1 for each SNPs) with excellent stability in all three scenarios of independent phenotype-related SNPs without linkage disequilibrium (LD) around them, correlated phenotype-related SNPs without LD around them, and phenotype-related SNPs with strong LD around them. As expected, under different odds ratio and minor allel frequency (MAFs), MBRFS always had the best performances in capturing the true phenotype-related biomarkers with higher matthews correlation coefficience (MCC) for all three scenarios above. More importantly, since proposed MBRFS using the repeated fishing strategy, it still captures more phenotype-related SNPs with minor effects when non-significant phenotype-related SNPs emerged under χ(2) test after Bonferroni multiple correction. The various real omics data analysis, including GWAS data, DNA methylation data, gene expression data and metabolites data, indicated that the proposed MBRFS always detected relatively reasonable biomarkers. CONCLUSIONS: Our proposed MBRFS can exactly capture the true phenotype-related biomarkers with the reduction of false negative rate when the phenotype-related biomarkers are independent or correlated, as well as the circumstance that phenotype-related biomarkers are associated with non-phenotype-related ones.

Integrative analyses of leprosy susceptibility genes indicate a common autoimmune profile.

BACKGROUND: Leprosy is an ancient chronic infection in the skin and peripheral nerves caused by Mycobacterium leprae. The development of leprosy depends on genetic background and the immune status of the host. However, there is no systematic view focusing on the biological pathways, interaction networks and overall expression pattern of leprosy-related immune and genetic factors. OBJECTIVES: To identify the hub genes in the center of leprosy genetic network and to provide an insight into immune and genetic factors contributing to leprosy. METHODS: We retrieved all reported leprosy-related genes and performed integrative analyses covering gene expression profiling, pathway analysis, protein-protein interaction network, and evolutionary analyses. RESULTS: A list of 123 differentially expressed leprosy related genes, which were enriched in activation and regulation of immune response, was obtained in our analyses. Cross-disorder analysis showed that the list of leprosy susceptibility genes was largely shared by typical autoimmune diseases such as lupus erythematosus and arthritis, suggesting that similar pathways might be affected in leprosy and autoimmune diseases. Protein-protein interaction (PPI) and positive selection analyses revealed a co-evolution network of leprosy risk genes. CONCLUSIONS: Our analyses showed that leprosy associated genes constituted a co-evolution network and might undergo positive selection driven by M. leprae. We suggested that leprosy may be a kind of autoimmune disease and the development of leprosy is a matter of defect or over-activation of body immunity.

MycoBASE: expanding the functional annotation coverage of mycobacterial genomes.

BACKGROUND: Central to most omic scale experiments is the interpretation and examination of resulting gene lists corresponding to differentially expressed, regulated, or observed gene or protein sets. Complicating interpretation is a lack of functional annotation assigned to a large percentage of many microbial genomes. This is particularly noticeable in mycobacterial genomes, which are significantly divergent from many of the microbial model species used for gene and protein functional characterization, but which are extremely important clinically. Mycobacterial species, ranging from M. tuberculosis to M. abscessus, are responsible for deadly infectious diseases that kill over 1.5 million people each year across the world. A better understanding of the coding capacity of mycobacterial genomes is therefore necessary to shed increasing light on putative mechanisms of virulence, pathogenesis, and functional adaptations. DESCRIPTION: Here we describe the improved functional annotation coverage of 11 important mycobacterial genomes, many involved in human diseases including tuberculosis, leprosy, and nontuberculous mycobacterial (NTM) infections. Of the 11 mycobacterial genomes, we provide 9899 new functional annotations, compared to NCBI and TBDB annotations, for genes previously characterized as genes of unknown function, hypothetical, and hypothetical conserved proteins. Functional annotations are available at our newly developed web resource MycoBASE (Mycobacterial Annotation Server) at strong.ucdenver.edu/mycobase. CONCLUSION: Improved annotations allow for better understanding and interpretation of genomic and transcriptomic experiments, including analyzing the functional implications of insertions, deletions, and mutations, inferring the function of understudied genes, and determining functional changes resulting from differential expression studies. MycoBASE provides a valuable resource for mycobacterial researchers, through improved and searchable functional annotations and functional enrichment strategies. MycoBASE will be continually supported and updated to include new genomes, enabling a powerful resource to aid the quest to better understand these important pathogenic and environmental species.

MycoCAP - Mycobacterium Comparative Analysis Platform.

Mycobacterium spp. are renowned for being the causative agent of diseases like leprosy, Buruli ulcer and tuberculosis in human beings. With more and more mycobacterial genomes being sequenced, any knowledge generated from comparative genomic analysis would provide better insights into the biology, evolution, phylogeny and pathogenicity of this genus, thus helping in better management of diseases caused by Mycobacterium spp.With this motivation, we constructed MycoCAP, a new comparative analysis platform dedicated to the important genus Mycobacterium. This platform currently provides information of 2108 genome sequences of at least 55 Mycobacterium spp. A number of intuitive web-based tools have been integrated in MycoCAP particularly for comparative analysis including the PGC tool for comparison between two genomes, PathoProT for comparing the virulence genes among the Mycobacterium strains and the SuperClassification tool for the phylogenic classification of the Mycobacterium strains and a specialized classification system for strains of Mycobacterium abscessus. We hope the broad range of functions and easy-to-use tools provided in MycoCAP makes it an invaluable analysis platform to speed up the research discovery on mycobacteria for researchers. Database URL: http://mycobacterium.um.edu.my.

LSHGD: a database for human leprosy susceptible genes.

Studies aiming to explore the involvement of host genetic factors to determine susceptibility to develop disease and individual's response to the infection with Mycobacterium leprae have increased in recent years. To address this issue, we have developed a Leprosy Susceptible Human Gene Database (LSHGD) to integrate leprosy and human associated 45 genes by profound literature search. This will serve as a user-friendly and interactive platform to understand the involvement of human polymorphisms (SNPs) in leprosy, independent genetic control over both susceptibility to leprosy and its association with multi-drug resistance of M. leprae. As the first human genetic database in leprosy it aims to provide information about the associated genes, corresponding protein sequences, available three dimensional structures and polymorphism related to leprosy. In conclusion, this will serve as a multifunctional valuable tool and convenient information platform which is freely available at http://www.vit.ac.in/leprosy/leprosy.htm and enables the user to retrieve information of their interest.

Mycobacterial species as case-study of comparative genome analysis.

The genus Mycobacterium represents more than 120 species including important pathogens of human and cause major public health problems and illnesses. Further, with more than 100 genome sequences from this genus, comparative genome analysis can provide new insights for better understanding the evolutionary events of these species and improving drugs, vaccines, and diagnostics tools for controlling Mycobacterial diseases. In this present study we aim to outline a comparative genome analysis of fourteen Mycobacterial genomes: M. avium subsp. paratuberculosis K­10, M. bovis AF2122/97, M. bovis BCG str. Pasteur 1173P2, M. leprae Br4923, M. marinum M, M. sp. KMS, M. sp. MCS, M. tuberculosis CDC1551, M. tuberculosis F11, M. tuberculosis H37Ra, M. tuberculosis H37Rv, M. tuberculosis KZN 1435 , M. ulcerans Agy99,and M. vanbaalenii PYR­1, For this purpose a comparison has been done based on their length of genomes, GC content, number of genes in different data bases (Genbank, Refseq, and Prodigal). The BLAST matrix of these genomes has been figured to give a lot of information about the similarity between species in a simple scheme. As a result of multiple genome analysis, the pan and core genome have been defined for twelve Mycobacterial species. We have also introduced the genome atlas of the reference strain M. tuberculosis H37Rv which can give a good overview of this genome. And for examining the phylogenetic relationships among these bacteria, a phylogenic tree has been constructed from 16S rRNA gene for tuberculosis and non tuberculosis Mycobacteria to understand the evolutionary events of these species.

The MycoBrowser portal: a comprehensive and manually annotated resource for mycobacterial genomes.

In this paper, we present the MycoBrowser portal (http://mycobrowser.epfl.ch/), a resource that provides both in silico generated and manually reviewed information within databases dedicated to the complete genomes of Mycobacterium tuberculosis, Mycobacterium leprae, Mycobacterium marinum and Mycobacterium smegmatis. A central component of MycoBrowser is TubercuList (http://tuberculist.epfl.ch), which has recently benefited from a new data management system and web interface. These improvements were extended to all MycoBrowser databases. We provide an overview of the functionalities available and the different ways of interrogating the data then discuss how both the new information and the latest features are helping the mycobacterial research communities.

Validating divergent ORF annotation of the Mycobacterium leprae genome through a full translation data set and peptide identification by tandem mass spectrometry.

Mycobacterium leprae has undergone extensive degenerative evolution, with a large number of pseudogenes. It is also the organism with the greatest divergence between gene annotations from independent institutes. Therefore, M. leprae is a good model to verify the currently predicted coding sequence regions between different annotations, to identify new ones and to investigate the expression of pseudogenes. We submitted a total extract of the bacteria isolated from Armadillo to Gel-LC-MS/MS using a linear quadrupole ion trap-Orbitrap mass spectrometer. Spectra were analyzed using the Leproma (1614 genes and 1133 pseudogenes) and TIGR (5446 genes) databases and a database containing the full genome translation. We identified a total of 1046 proteins, including five proteins encoded by previously predicted pseudogenes, which upon closer inspection appeared to be proper genes. Only 11 of the additional annotations by TIGR were verified. We also identified six tryptic peptides from five proteins from regions not considered to be coding sequences, in addition to peptides from two unannotated gene candidates that overlap with other genes. Our data show that the Leproma annotation of M. leprae is quite accurate, and there were no peptide observations corresponding to true pseudogenes, except for a new gene candidate, overlapping with an essential enolase on the complementary strand.

Long simple sequence repeats in host-adapted pathogens localize near genes encoding antigens, housekeeping genes, and pseudogenes.

Simple sequence repeats (SSRs) in DNA sequences are tandem iterations of a single nucleotide or a short oligonucleotide. SSRs are subject to slipped-strand mutations and a common source of phase variation in bacteria and antigenic variation in pathogens. Significantly long SSRs are generally rare in prokaryotic genomes, and long SSRs composed of iterations of mono-, di-, tri-, and tetranucleotides are mostly restricted to host-adapted pathogens. We present new results concerning associations between long SSRs and genes related to different cellular functions in genomes of host-adapted pathogens. We found that in the majority of the analyzed genomes, at least some of the genes associated with SSRs encode potential antigens, which is expected if the primary function of SSRs is their contribution to antigenic variation. However, we also found a number of long SSRs associated with housekeeping genes, including rRNA and tRNA genes, genes encoding ribosomal proteins, amino acyl-tRNA synthetases, chaperones, and important metabolic enzymes. Many of these genes are probably essential and it is unlikely that they are phase-variable. Few statistically significant associations between SSRs and gene functional classifications were detected, suggesting that most long SSRs are not related to a particular cellular function or process. Long SSRs in Mycobacterium leprae are mostly associated with pseudogenes and may be contributing to gene loss following the adaptation to an obligate pathogenic lifestyle. We speculate that LSSRs may have played a similar role in genome reduction of other host-adapted pathogens.

A fungal phylogeny based on 42 complete genomes derived from supertree and combined gene analysis.

BACKGROUND: To date, most fungal phylogenies have been derived from single gene comparisons, or from concatenated alignments of a small number of genes. The increase in fungal genome sequencing presents an opportunity to reconstruct evolutionary events using entire genomes. As a tool for future comparative, phylogenomic and phylogenetic studies, we used both supertrees and concatenated alignments to infer relationships between 42 species of fungi for which complete genome sequences are available. RESULTS: A dataset of 345,829 genes was extracted from 42 publicly available fungal genomes. Supertree methods were employed to derive phylogenies from 4,805 single gene families. We found that the average consensus supertree method may suffer from long-branch attraction artifacts, while matrix representation with parsimony (MRP) appears to be immune from these. A genome phylogeny was also reconstructed from a concatenated alignment of 153 universally distributed orthologs. Our MRP supertree and concatenated phylogeny are highly congruent. Within the Ascomycota, the sub-phyla Pezizomycotina and Saccharomycotina were resolved. Both phylogenies infer that the Leotiomycetes are the closest sister group to the Sordariomycetes. There is some ambiguity regarding the placement of Stagonospora nodurum, the sole member of the class Dothideomycetes present in the dataset. Within the Saccharomycotina, a monophyletic clade containing organisms that translate CTG as serine instead of leucine is evident. There is also strong support for two groups within the CTG clade, one containing the fully sexual species Candida lusitaniae, Candida guilliermondii and Debaryomyces hansenii, and the second group containing Candida albicans, Candida dubliniensis, Candida tropicalis, Candida parapsilosis and Lodderomyces elongisporus. The second major clade within the Saccharomycotina contains species whose genomes have undergone a whole genome duplication (WGD), and their close relatives. We could not confidently resolve whether Candida glabrata or Saccharomyces castellii lies at the base of the WGD clade. CONCLUSION: We have constructed robust phylogenies for fungi based on whole genome analysis. Overall, our phylogenies provide strong support for the classification of phyla, sub-phyla, classes and orders. We have resolved the relationship of the classes Leotiomyctes and Sordariomycetes, and have identified two classes within the CTG clade of the Saccharomycotina that may correlate with sexual status.

GenoMycDB: a database for comparative analysis of mycobacterial genes and genomes.

Several databases and computational tools have been created with the aim of organizing, integrating and analyzing the wealth of information generated by large-scale sequencing projects of mycobacterial genomes and those of other organisms. However, with very few exceptions, these databases and tools do not allow for massive and/or dynamic comparison of these data. GenoMycDB (http://www.dbbm.fiocruz.br/GenoMycDB) is a relational database built for large-scale comparative analyses of completely sequenced mycobacterial genomes, based on their predicted protein content. Its central structure is composed of the results obtained after pair-wise sequence alignments among all the predicted proteins coded by the genomes of six mycobacteria: Mycobacterium tuberculosis (strains H37Rv and CDC1551), M. bovis AF2122/97, M. avium subsp. paratuberculosis K10, M. leprae TN, and M. smegmatis MC2 155. The database stores the computed similarity parameters of every aligned pair, providing for each protein sequence the predicted subcellular localization, the assigned cluster of orthologous groups, the features of the corresponding gene, and links to several important databases. Tables containing pairs or groups of potential homologs between selected species/strains can be produced dynamically by user-defined criteria, based on one or multiple sequence similarity parameters. In addition, searches can be restricted according to the predicted subcellular localization of the protein, the DNA strand of the corresponding gene and/or the description of the protein. Massive data search and/or retrieval are available, and different ways of exporting the result are offered. GenoMycDB provides an on-line resource for the functional classification of mycobacterial proteins as well as for the analysis of genome structure, organization, and evolution.

GenoMycDB: a database for comparative analysis of mycobacterial genes and genomes

Several databases and computational tools have been created with the aim of organizing, integrating and analyzing the wealth of information generated by large-scale sequencing projects of mycobacterial genomes and those of other organisms. However, with very few exceptions, these databases and tools do not allow for massive and/or dynamic comparison of these data. GenoMycDB (http://www.dbbm.fiocruz.br/GenoMycDB) is a relational database built for large-scale comparative analyses of completely sequenced mycobacterial genomes, based on their predicted protein content. Its central structure is composed of the results obtained after pair-wise sequence alignments among all the predicted proteins coded by the genomes of six mycobacteria: Mycobacterium tuberculosis (strains H37Rv and CDC1551), M. bovis AF2122/97, M. avium subsp. paratuberculosis K10, M. leprae TN, and M. smegmatis MC2 155. The database stores the computed similarity parameters of every aligned pair, providing for each protein sequence the predicted subcellular localization, the assigned cluster of orthologous groups, the features of the corresponding gene, and links to several important databases. Tables containing pairs or groups of potential homologs between selected species/strains can be produced dynamically by user-defined criteria, based on one or multiple sequence similarity parameters. In addition, searches can be restricted according to the predicted subcellular localization of the protein, the DNA strand of the corresponding gene and/or the description of the protein. Massive data search and/or retrieval are available, and different ways of exporting the result are offered. GenoMycDB provides an on-line resource for the functional classification of mycobacterial proteins as well as for the analysis of genome structure, organization, and evolution.

A surprisingly large RNase P RNA in Candida glabrata.

We have found an extremely large ribonuclease P (RNase P) RNA (RPR1) in the human pathogen Candida glabrata and verified that this molecule is expressed and present in the active enzyme complex of this hemiascomycete yeast. A structural alignment of the C. glabrata sequence with 36 other hemiascomycete RNase P RNAs (abbreviated as P RNAs) allows us to characterize the types of insertions. In addition, 15 P RNA sequences were newly characterized by searching in the recently sequenced genomes Candida albicans, C. glabrata, Debaryomyces hansenii, Eremothecium gossypii, Kluyveromyces lactis, Kluyveromyces waltii, Naumovia castellii, Saccharomyces kudriavzevii, Saccharomyces mikatae, and Yarrowia lipolytica; and by PCR amplification for other Candida species (Candida guilliermondii, Candida krusei, Candida parapsilosis, Candida stellatoidea, and Candida tropicalis). The phylogenetic comparative analysis identifies a hemiascomycete secondary structure consensus that presents a conserved core in all species with variable insertions or deletions. The most significant variability is found in C. glabrata P RNA in which three insertions exceeding in total 700 nt are present in the Specificity domain. This P RNA is more than twice the length of any other homologous P RNAs known in the three domains of life and is eight times the size of the smallest. RNase P RNA, therefore, represents one of the most diversified noncoding RNAs in terms of size variation and structural diversity.

Analysis of Mycobacterium leprae genome: in silico searching for drug targets.

The author performed a database search to find the recorded complete genes with complete sequences of Mycobacterium leprae and studied their homology to human genomes by BLAST method. From a total of 35 genes, the potential candidates for further target-based drug development were identified.

Génolevures: comparative genomics and molecular evolution of hemiascomycetous yeasts.

The Génolevures online database (http://cbi.labri.fr/Genolevures/) provides data and tools to facilitate comparative genomic studies on hemiascomycetous yeasts. Now, four complete genome sequences recently determined (Candida glabrata, Kluyveromyces lactis, Debaryomyces hansenii, Yarrowia lipolytica) have been added to the partial sequences of 13 species previously analysed by a random approach. The database also includes the reference genome Saccharomyces cerevisiae. Data are presented with a focus on relations between genes and genomes: conservation of genes and gene families, speciation, chromosomal reorganization and synteny. The Génolevures site includes a community area for specific studies by members of the international community.