e-LiSe--an online tool for finding needles in the '(Medline) haystack'.

UNLABELLED Using literature databases one can find not only known and true relations between processes but also less studied, non-obvious associations. The main problem with discovering such type of relevant biological information is 'selection'. The ability to distinguish between a true correlation (e.g. between different types of biological processes) and random chance that this correlation is statistically significant is crucial for any bio-medical research, literature mining being no exception. This problem is especially visible when searching for information which has not been studied and described in many publications. Therefore, a novel bio-linguistic statistical method is required, capable of 'selecting' true correlations, even when they are low-frequency associations. In this article, we present such statistical approach based on Z-score and implemented in a web-based application 'e-LiSe'. AVAILABILITY The software is available at http://miron.ibb.waw.pl/elise

Exploring the genomic diversity of black yeasts and relatives (Chaetothyriales, Ascomycota)

The order Chaetothyriales (Pezizomycotina, Ascomycetes) harbours obligatorily melanised fungi and includes numerous etiologic agents of chromoblastomycosis, phaeohyphomycosis and other diseases of vertebrate hosts. Diseases range from mild cutaneous to fatal cerebral or disseminated infections and affect humans and cold-blooded animals globally. In addition, Chaetothyriales comprise species with aquatic, rock-inhabiting, ant-associated, and mycoparasitic life-styles, as well as species that tolerate toxic compounds, suggesting a high degree of versatile extremotolerance. To understand their biology and divergent niche occupation, we sequenced and annotated a set of 23 genomes of main the human opportunists within the Chaetothyriales as well as related environmental species. Our analyses included fungi with diverse life-styles, namely opportunistic pathogens and closely related saprobes, to identify genomic adaptations related to pathogenesis. Furthermore, ecological preferences of Chaetothyriales were analysed, in conjuncture with the order-level phylogeny based on conserved ribosomal genes. General characteristics, phylogenomic relationships, transposable elements, sex-related genes, protein family evolution, genes related to protein degradation (MEROPS), carbohydrate-active enzymes (CAZymes), melanin synthesis and secondary metabolism were investigated and compared between species. Genome assemblies varied from 25.81 Mb (Capronia coronata) to 43.03 Mb (Cladophialophora immunda). The bantiana-clade contained the highest number of predicted genes (12,817 on average) as well as larger genomes. We found a low content of mobile elements, with DNA transposons from Tc1/Mariner superfamily being the most abundant across analysed species. Additionally, we identified a reduction of carbohydrate degrading enzymes, specifically many of the Glycosyl Hydrolase (GH) class, while most of the Pectin Lyase (PL) genes were lost in etiological agents of chromoblastomycosis and phaeohyphomycosis. An expansion was found in protein degrading peptidase enzyme families S12 (serine-type D-Ala-D-Ala carboxypeptidases) and M38 (isoaspartyl dipeptidases). Based on genomic information, a wide range of abilities of melanin biosynthesis was revealed; genes related to metabolically distinct DHN, DOPA and pyomelanin pathways were identified. The MAT (MAting Type) locus and other sex-related genes were recognized in all 23 black fungi. Members of the asexual genera Fonsecaea and Cladophialophora appear to be heterothallic with a single copy of either MAT-1-1 or MAT-1-2 in each individual. All Capronia species are homothallic as both MAT1-1 and MAT 1-2 genes were found in each single genome. The genomic synteny of the MAT-locus flanking genes (SLA2-APN2-COX13) is not conserved in black fungi as is commonly observed in Eurotiomycetes, indicating a unique genomic context for MAT in those species. The heterokaryon (het) genes expansion associated with the low selective pressure at the MAT-locus suggests that a parasexual cycle may play an important role in generating diversity among those fungi

Dominance from the perspective of gene-gene and gene-chemical interactions.

In this study, we used genetic interaction (GI) and gene-chemical interaction (GCI) data to compare mutations with different dominance phenotypes. Our analysis focused primarily on Saccharomyces cerevisiae, where haploinsufficient genes (HI; genes with dominant loss-of-function mutations) were found to be participating in gene expression processes, namely, the translation and regulation of gene transcription. Non-ribosomal HI genes (mainly regulators of gene transcription) were found to have more GIs and GCIs than haplosufficient (HS) genes. Several properties seem to lead to the enrichment of interactions, most notably, the following: importance, pleiotropy, gene expression level and gene expression variation. Importantly, after these properties were appropriately considered in the analysis, the correlation between dominance and GI/GCI degrees was still observed. Strikingly, for the GCIs of heterozygous strains, haploinsufficiency was the only property significantly correlated with the number of GCIs. We found ribosomal HI genes to be depleted in GIs/GCIs. This finding can be explained by their high variation in gene expression under different genetic backgrounds and environmental conditions. We observed the same distributions of GIs among non-ribosomal HI, ribosomal HI and HS genes in three other species: Schizosaccharomyces pombe, Drosophila melanogaster and Homo sapiens. One potentially interesting exception was the lack of significant differences in the degree of GIs between non-ribosomal HI and HS genes in Schizosaccharomyces pombe

The evolutionary rate of antibacterial drug targets

Background One of the major issues in the fight against infectious diseases is the notable increase in multiple drug resistance in pathogenic species. For that reason, newly acquired high-throughput data on virulent microbial agents attract the attention of many researchers seeking potential new drug targets. Many approaches have been used to evaluate proteins from infectious pathogens, including, but not limited to, similarity analysis, reverse docking, statistical 3D structure analysis, machine learning, topological properties of interaction networks or a combination of the aforementioned methods. From a biological perspective, most essential proteins (knockout lethal for bacteria) or highly conserved proteins (broad spectrum activity) are potential drug targets. Ribosomal proteins comprise such an example. Many of them are well-known drug targets in bacteria. It is intuitive that we should learn from nature how to design good drugs. Firstly, known antibiotics are mainly originating from natural products of microorganisms targeting other microorganisms. Secondly, paleontological data suggests that antibiotics have been used by microorganisms for million years. Thus, we have hypothesized that good drug targets are evolutionary constrained and are subject of evolutionary selection. This means that mutations in such proteins are deleterious and removed by selection, which makes them less susceptible to random development of resistance. Analysis of the speed of evolution seems to be good approach to test this hypothesis. Results In this study we show that pN/pS ratio of genes coding for known drug targets is significantly lower than the genome average and also lower than that for essential genes identified by experimental methods. Similar results are observed in the case of dN/dS analysis. Both analyzes suggest that drug targets tend to evolve slowly and that the rate of evolution is a better predictor of drugability than essentiality. Conclusions Evolutionary rate can be used to score and find potential drug targets. The results presented here may become a useful addition to a repertoire of drug target prediction methods. As a proof of concept, we analyzed GO enrichment among the slowest evolving genes. These may become the starting point in the search for antibiotics with a novel mechanism