New Insights on Environmental Occurrence of Pathogenic Fungi Based on Metagenomic Data from Brazilian Cerrado Biome

Abstract: Cerrado is the second largest biome in Brazil and majorly contributes to the country's grain production. Previous studies on soil metagenomics from the Cerrado revealed an outstanding microbial diversity. In this study, the abundance of pathogenic fungi was analyzed using metagenomic sequences of the Cerrado soils under native vegetation, and under agriculture with no-tillage and conventional tillage. In total, 128,627 sequences of fungi were identified, with 43,439 representing pathogenic fungi and were distributed as follows: native 17,301 (40%), no-tillage 13,780 (32%), and conventional tillage 12,358 (28%). We identified 41 pathogenic fungal species associated with human and animal infections. The data analysis revealed that the native soils had a higher relative abundance of fungal sequences, similar to pathogenic species sequences, in relation to the total eukaryotic sequences, than the conventional tillage and no-tillage treatments, which observed a reduction in fungal abundance because of anthropogenic activities.

Prediction and Analysis in silico of Genomic Islands in Aeromonas hydrophila.

Aeromonas are Gram-negative rods widely distributed in the environment. They can cause severe infections in fish related to financial losses in the fish industry, and are considered opportunistic pathogens of humans causing infections ranging from diarrhea to septicemia. The objective of this study was to determine in silico the contribution of genomic islands to A. hydrophila. The complete genomes of 17 A. hydrophila isolates, which were separated into two phylogenetic groups, were analyzed using a genomic island (GI) predictor. The number of predicted GIs and their characteristics varied among strains. Strains from group 1, which contains mainly fish pathogens, generally have a higher number of predicted GIs, and with larger size, than strains from group 2 constituted by strains recovered from distinct sources. Only a few predicted GIs were shared among them and contained mostly genes from the core genome. Features related to virulence, metabolism, and resistance were found in the predicted GIs, but strains varied in relation to their gene content. In strains from group 1, O Ag biosynthesis clusters OX1 and OX6 were identified, while strains from group 2 each had unique clusters. Metabolic pathways for myo-inositol, L-fucose, sialic acid, and a cluster encoding QueDEC, tgtA5, and proteins related to DNA metabolism were identified in strains of group 1, which share a high number of predicted GIs. No distinctive features of group 2 strains were identified in their predicted GIs, which are more diverse and possibly better represent GIs in this species. However, some strains have several resistance attributes encoded by their predicted GIs. Several predicted GIs encode hypothetical proteins and phage proteins whose functions have not been identified but may contribute to Aeromonas fitness. In summary, features with functions identified on predicted GIs may confer advantages to host colonization and competitiveness in the environment.

Origin and evolution of nonulosonic acid synthases and their relationship with bacterial pathogenicity revealed by a large-scale phylogenetic analysis.

Nonulosonic acids (NulOs) are a group of nine-carbon monosaccharides with different functions in nature. N-acetylneuraminic acid (Neu5Ac) is the most common NulO. It covers the membrane surface of all human cells and is a central molecule in the process of self-recognition via SIGLECS receptors. Some pathogenic bacteria escape the immune system by copying the sialylation of the host cell membrane. Neu5Ac production in these bacteria is catalysed by the enzyme NeuB. Some bacteria can also produce other NulOs named pseudaminic and legionaminic acids, through the NeuB homologues PseI and LegI, respectively. In Opisthokonta eukaryotes, the biosynthesis of Neu5Ac is catalysed by the enzyme NanS. In this study, we used publicly available data of sequences of NulOs synthases to investigate its distribution within the three domains of life and its relationship with pathogenic bacteria. We mined the KEGG database and found 425 NeuB sequences. Most NeuB sequences (58.74 %) from the KEGG orthology database were classified as from environmental bacteria; however, sequences from pathogenic bacteria showed higher conservation and prevalence of a specific domain named SAF. Using the HMM profile we identified 13 941 NulO synthase sequences in UniProt. Phylogenetic analysis of these sequences showed that the synthases were divided into three main groups that can be related to the lifestyle of these bacteria: (I) predominantly environmental, (II) intermediate and (III) predominantly pathogenic. NeuB was widely distributed in the groups. However, LegI and PseI were more concentrated in groups II and III, respectively. We also found that PseI appeared later in the evolutionary process, derived from NeuB. We use this same methodology to retrieve sialic acid synthase sequences from Archaea and Eukarya. A large-scale phylogenetic analysis showed that while the Archaea sequences are spread across the tree, the eukaryotic NanS sequences were grouped in a specific branch in group II. None of the bacterial NanS sequences grouped with the eukaryotic branch. The analysis of conserved residues showed that the synthases of Archaea and Eukarya present a mutation in one of the three catalytic residues, an E134D change, related to a Neisseria meningitidis reference sequence. We also found that the conservation profile is higher between NeuB of pathogenic bacteria and NanS of eukaryotes than between NeuB of environmental bacteria and NanS of eukaryotes. Our large-scale analysis brings new perspectives on the evolution of NulOs synthases, suggesting their presence in the last common universal ancestor.

Comparative Genomics Provides Insights into the Taxonomy of Azoarcus and Reveals Separate Origins of Nif Genes in the Proposed Azoarcus and Aromatoleum Genera.

Among other attributes, the Betaproteobacterial genus Azoarcus has biotechnological importance for plant growth-promotion and remediation of petroleum waste-polluted water and soils. It comprises at least two phylogenetically distinct groups. The "plant-associated" group includes strains that are isolated from the rhizosphere or root interior of the C4 plant Kallar Grass, but also strains from soil and/or water; all are considered to be obligate aerobes and all are diazotrophic. The other group (now partly incorporated into the new genus Aromatoleum) comprises a diverse range of species and strains that live in water or soil that is contaminated with petroleum and/or aromatic compounds; all are facultative or obligate anaerobes. Some are diazotrophs. A comparative genome analysis of 32 genomes from 30 Azoarcus-Aromatoleum strains was performed in order to delineate generic boundaries more precisely than the single gene, 16S rRNA, that has been commonly used in bacterial taxonomy. The origin of diazotrophy in Azoarcus-Aromatoleum was also investigated by comparing full-length sequences of nif genes, and by physiological measurements of nitrogenase activity using the acetylene reduction assay. Based on average nucleotide identity (ANI) and whole genome analyses, three major groups could be discerned: (i) Azoarcus comprising Az. communis, Az. indigens and Az. olearius, and two unnamed species complexes, (ii) Aromatoleum Group 1 comprising Ar. anaerobium, Ar. aromaticum, Ar. bremense, and Ar. buckelii, and (iii) Aromatoleum Group 2 comprising Ar. diolicum, Ar. evansii, Ar. petrolei, Ar. toluclasticum, Ar. tolulyticum, Ar. toluolicum, and Ar. toluvorans. Single strain lineages such as Azoarcus sp. KH32C, Az. pumilus, and Az. taiwanensis were also revealed. Full length sequences of nif-cluster genes revealed two groups of diazotrophs in Azoarcus-Aromatoleum with nif being derived from Dechloromonas in Azoarcus sensu stricto (and two Thauera strains) and from Azospira in Aromatoleum Group 2. Diazotrophy was confirmed in several strains, and for the first time in Az. communis LMG5514, Azoarcus sp. TTM-91 and Ar. toluolicum TT. In terms of ecology, with the exception of a few plant-associated strains in Azoarcus (s.s.), across the group, most strains/species are found in soil and water (often contaminated with petroleum or related aromatic compounds), sewage sludge, and seawater. The possession of nar, nap, nir, nor, and nos genes by most Azoarcus-Aromatoleum strains suggests that they have the potential to derive energy through anaerobic nitrate respiration, so this ability cannot be usefully used as a phenotypic marker to distinguish genera. However, the possession of bzd genes indicating the ability to degrade benzoate anaerobically plus the type of diazotrophy (aerobic vs. anaerobic) could, after confirmation of their functionality, be considered as distinguishing phenotypes in any new generic delineations. The taxonomy of the Azoarcus-Aromatoleum group should be revisited; retaining the generic name Azoarcus for its entirety, or creating additional genera are both possible outcomes.

Environmental prospecting of black yeast-like agents of human disease using culture-independent methodology.

Melanized fungi and black yeasts in the family Herpotrichiellaceae (order Chaetothyriales) are important agents of human and animal infectious diseases such as chromoblastomycosis and phaeohyphomycosis. The oligotrophic nature of these fungi enables them to survive in adverse environments where common saprobes are absent. Due to their slow growth, they lose competition with common saprobes, and therefore isolation studies yielded low frequencies of clinically relevant species in environmental habitats from which humans are thought to be infected. This problem can be solved with metagenomic techniques which allow recognition of microorganisms independent from culture. The present study aimed to identify species of the family Herpotrichiellaceae that are known to occur in Brazil by the use of molecular markers to screen public environmental metagenomic datasets from Brazil available in the Sequence Read Archive (SRA). Species characterization was performed with the BLAST comparison of previously described barcodes and padlock probe sequences. A total of 18,329 sequences was collected comprising the genera Cladophialophora, Exophiala, Fonsecaea, Rhinocladiella and Veronaea, with a focus on species related to the chromoblastomycosis. The data obtained in this study demonstrated presence of these opportunists in the investigated datasets. The used techniques contribute to our understanding of environmental occurrence and epidemiology of black fungi.

SWeeP: representing large biological sequences datasets in compact vectors.

Vectoral and alignment-free approaches to biological sequence representation have been explored in bioinformatics to efficiently handle big data. Even so, most current methods involve sequence comparisons via alignment-based heuristics and fail when applied to the analysis of large data sets. Here, we present "Spaced Words Projection (SWeeP)", a method for representing biological sequences using relatively small vectors while preserving intersequence comparability. SWeeP uses spaced-words by scanning the sequences and generating indices to create a higher-dimensional vector that is later projected onto a smaller randomly oriented orthonormal base. We constructed phylogenetic trees for all organisms with mitochondrial and bacterial protein data in the NCBI database. SWeeP quickly built complete and accurate trees for these organisms with low computational cost. We compared SWeeP to other alignment-free methods and Sweep was 10 to 100 times quicker than the other techniques. A tool to build SWeeP vectors is available at https://sourceforge.net/projects/spacedwordsprojection/.

RAFTS3G: an efficient and versatile clustering software to analyses in large protein datasets.

BACKGROUND: Clustering methods are essential to partitioning biological samples being useful to minimize the information complexity in large datasets. Tools in this context usually generates data with greed algorithms that solves some Data Mining difficulties which can degrade biological relevant information during the clustering process. The lack of standardization of metrics and consistent bases also raises questions about the clustering efficiency of some methods. Benchmarks are needed to explore the full potential of clustering methods - in which alignment-free methods stand out - and the good choice of dataset makes it essentials. RESULTS: Here we present a new approach to Data Mining in large protein sequences datasets, the Rapid Alignment Free Tool for Sequences Similarity Search to Groups (RAFTS3G), a method to clustering aiming of losing less biological information in the processes of generation groups. The strategy developed in our algorithm is optimized to be more astringent which reflects increase in accuracy and sensitivity in the generation of clusters in a wide range of similarity. RAFTS3G is the better choice compared to three main methods when the user wants more reliable result even ignoring the ideal threshold to clustering. CONCLUSION: In general, RAFTS3G is able to group up to millions of biological sequences into large datasets, which is a remarkable option of efficiency in clustering. RAFTS3G compared to other "standard-gold" methods in the clustering of large biological data maintains the balance between the reduction of biological information redundancy and the creation of consistent groups. We bring the binary search concept applied to grouped sequences which shows maintaining sensitivity/accuracy relation and up to minimize the time of data generated with RAFTS3G process.

Comparative Analysis of Genomic Island Prediction Tools.

Tools for genomic island prediction use strategies for genomic comparison analysis and sequence composition analysis. The goal of comparative analysis is to identify unique regions in the genomes of related organisms, whereas sequence composition analysis evaluates and relates the composition of specific regions with other regions in the genome. The goal of this study was to qualitatively and quantitatively evaluate extant genomic island predictors. We chose tools reported to produce significant results using sequence composition prediction, comparative genomics, and hybrid genomics methods. To maintain diversity, the tools were applied to eight complete genomes of organisms with distinct characteristics and belonging to different families. Escherichia coli CFT073 was used as a control and considered as the gold standard because its islands were previously curated in vitro. The results of predictions with the gold standard were manually curated, and the content and characteristics of each predicted island were analyzed. For other organisms, we created GenBank (GBK) files using Artemis software for each predicted island. We copied only the amino acid sequences from the coding sequence and constructed a multi-FASTA file for each predictor. We used BLASTp to compare all results and generate hits to evaluate similarities and differences among the predictions. Comparison of the results with the gold standard revealed that GIPSy produced the best results, covering ~91% of the composition and regions of the islands, followed by Alien Hunter (81%), IslandViewer (47.8%), Predict Bias (31%), GI Hunter (17%), and Zisland Explorer (16%). The tools with the best results in the analyzes of the set of organisms were the same ones that presented better performance in the tests with the gold standard.

New Tools in Orthology Analysis: A Brief Review of Promising Perspectives.

Nowadays defying homology relationships among sequences is essential for biological research. Within homology the analysis of orthologs sequences is of great importance for computational biology, annotation of genomes and for phylogenetic inference. Since 2007, with the increase in the number of new sequences being deposited in large biological databases, researchers have begun to analyse computerized methodologies and tools aimed at selecting the most promising ones in the prediction of orthologous groups. Literature in this field of research describes the problems that the majority of available tools show, such as those encountered in accuracy, time required for analysis (especially in light of the increasing volume of data being submitted, which require faster techniques) and the automatization of the process without requiring manual intervention. Conducting our search through BMC, Google Scholar, NCBI PubMed, and Expasy, we examined more than 600 articles pursuing the most recent techniques and tools developed to solve most the problems still existing in orthology detection. We listed the main computational tools created and developed between 2011 and 2017, taking into consideration the differences in the type of orthology analysis, outlining the main features of each tool and pointing to the problems that each one tries to address. We also observed that several tools still use as their main algorithm the BLAST "all-against-all" methodology, which entails some limitations, such as limited number of queries, computational cost, and high processing time to complete the analysis. However, new promising tools are being developed, like OrthoVenn (which uses the Venn diagram to show the relationship of ortholog groups generated by its algorithm); or proteinOrtho (which improves the accuracy of ortholog groups); or ReMark (tackling the integration of the pipeline to turn the entry process automatic); or OrthAgogue (using algorithms developed to minimize processing time); and proteinOrtho (developed for dealing with large amounts of biological data). We made a comparison among the main features of four tool and tested them using four for prokaryotic genomas. We hope that our review can be useful for researchers and will help them in selecting the most appropriate tool for their work in the field of orthology.

Genome Sequence of Type Strain Fonsecaea multimorphosa CBS 980.96T, a Causal Agent of Feline Cerebral Phaeohyphomycosis.

A draft genome sequence of type strain Fonsecaea multimorphosa CBS 980.96T was obtained. This species was first isolated from a cat with cerebral phaeohyphomycosis in Queensland, Australia.

The genome anatomy of Corynebacterium pseudotuberculosis VD57 a highly virulent strain causing Caseous lymphadenitis.

Corynebacterium pseudotuberculosis strain VD57 (Cp_VD57), a highly virulent, nonmotile, non-sporulating, and a mesophilic bacterium, was isolated from a goat's granulomatous lesion in the municipality of Juazeiro, Bahia State, Brazil. Here, we describe a set of features of the strain, together with the details of its complete genome sequence and annotation. The genome comprises of a 2.5 Mbp long, single circular genome with 2,101 protein-coding genes, 12 rRNA, 49 tRNA and 47 pseudogenes and a G + C content of 52.85 %. Genetic variation was detected in Cp_VD57 using C. pseudotuberculosis strain 1002 as reference, wherein small genomic insertions and deletions were identified. The comparative analysis of the genome sequence provides means to better understand the host pathogen interactions of this strain and can also help us to understand the molecular and genetic basis of virulence of this bacterium.

ProClaT, a new bioinformatics tool for in silico protein reclassification: case study of DraB, a protein coded from the draTGB operon in Azospirillum brasilense.

BACKGROUND: Azopirillum brasilense is a plant-growth promoting nitrogen-fixing bacteria that is used as bio-fertilizer in agriculture. Since nitrogen fixation has a high-energy demand, the reduction of N2 to NH4+ by nitrogenase occurs only under limiting conditions of NH4+ and O2. Moreover, the synthesis and activity of nitrogenase is highly regulated to prevent energy waste. In A. brasilense nitrogenase activity is regulated by the products of draG and draT. The product of the draB gene, located downstream in the draTGB operon, may be involved in the regulation of nitrogenase activity by an, as yet, unknown mechanism. RESULTS: A deep in silico analysis of the product of draB was undertaken aiming at suggesting its possible function and involvement with DraT and DraG in the regulation of nitrogenase activity in A. brasilense. In this work, we present a new artificial intelligence strategy for protein classification, named ProClaT. The features used by the pattern recognition model were derived from the primary structure of the DraB homologous proteins, calculated by a ProClaT internal algorithm. ProClaT was applied to this case study and the results revealed that the A. brasilense draB gene codes for a protein highly similar to the nitrogenase associated NifO protein of Azotobacter vinelandii. CONCLUSIONS: This tool allowed the reclassification of DraB/NifO homologous proteins, hypothetical, conserved hypothetical and those annotated as putative arsenate reductase, ArsC, as NifO-like. An analysis of co-occurrence of draB, draT, draG and of other nif genes was performed, suggesting the involvement of draB (nifO) in nitrogen fixation, however, without the definition of a specific function.

Draft genome sequence of Herbaspirillum lusitanum P6-12, an endophyte isolated from root nodules of Phaseolus vulgaris.

Herbaspirillum lusitanum strain P6-12 (DSM 17154) is, so far, the only species of Herbaspirillum isolated from plant root nodules. Here we report a draft genome sequence of this organism.

Draft genome sequence of the nitrogen-fixing symbiotic bacterium Bradyrhizobium elkanii 587.

The draft sequence of the genome of Bradyrhizobium elkanii 587 is presented. This was obtained using Illumina Next-Gen DNA sequencing combined with Sanger sequencing. Genes for the pathways involved in biological nitrogen fixation (the nif gene cluster), nod genes including nodABC, and genes for the type III protein secretion system (T3SS) are present.