The pan-genome of the emerging multidrug-resistant pathogen Corynebacterium striatum.

Corynebacterium striatum, a common constituent of the human skin microbiome, is now considered an emerging multidrug-resistant pathogen of immunocompromised and chronically ill patients. However, little is known about the molecular mechanisms in the transition from colonization to the multidrug-resistant (MDR) invasive phenotype in clinical isolates. This study performed a comprehensive pan-genomic analysis of C. striatum, including isolates from "normal skin microbiome" and from MDR infections, to gain insights into genetic factors contributing to pathogenicity and multidrug resistance in this species. For this, three novel genome sequences were obtained from clinical isolates of C. striatum of patients from Brazil, and other 24 complete or draft C. striatum genomes were retrieved from GenBank, including the ATCC6940 isolate from the Human Microbiome Project. Analysis of C. striatum strains demonstrated the presence of an open pan-genome (α = 0.852803) containing 3816 gene families, including 15 antimicrobial resistance (AMR) genes and 32 putative virulence factors. The core and accessory genomes included 1297 and 1307 genes, respectively. The identified AMR genes are primarily associated with resistance to aminoglycosides and tetracyclines. Of these, 66.6% are present in genomic islands, and four AMR genes, including aac(6')-ib7, are located in a class 1-integron. In conclusion, our data indicated that C. striatum possesses genomic characteristics favorable to the invasive phenotype, with high genomic plasticity, a robust genetic arsenal for iron acquisition, and important virulence determinants and AMR genes present in mobile genetic elements.

Computational identification of putative common genomic drug and vaccine targets in Mycoplasma genitalium.

Mycoplasma genitalium is an obligate intracellular bacterium that is responsible for several sexually transmitted infections, including non-gonococcal urethritis in men and several inflammatory reproductive tract syndromes in women. Here, we applied subtractive genomics and reverse vaccinology approaches for in silico prediction of potential vaccine and drug targets against five strains of M. genitalium. We identified 403 genes shared by all five strains, from which 104 non-host homologous proteins were selected, comprising of 44 exposed/secreted/membrane proteins and 60 cytoplasmic proteins. Based on the essentiality, functionality, and structure-based binding affinity, we finally predicted 19 (14 novel) putative vaccine and 7 (2 novel) candidate drug targets. The docking analysis showed six molecules from the ZINC database as promising drug candidates against the identified targets. Altogether, both vaccine candidates and drug targets identified here may contribute to the future development of therapeutic strategies to control the spread of M. genitalium worldwide.

Proteins from the core genome of Corynebacterium ulcerans respond for pathogenicity and reveal promising vaccine targets for diphtheria.

Corynebacterium ulcerans is an emerging pathogen able to transmit the acute infection diphtheria to humans. Although there is a well-established vaccine based on the toxin produced by Corynebacterium diphtheriae, another species of this genus known to cause the disease, there is still no vaccine formulations described for C. ulcerans; this fact contributes to the increase in cases of infection that has been observed. In this study, we want to provide information at the genomic level of this bacterium in order to suggest proteins as possible vaccine targets. We carried out an in silico prospection of vaccine candidates through reverse vaccinology for targets that exhibit antigenic potential against diphtheria. We found important virulence factors, such as adhesion-related ones, that are responsible for pathogen-host interaction after infection, but we did not find the diphtheria toxin, which is the main component of the currently available vaccine. This study provides detailed information about the exoproteome and hypothetical proteins from the core genome of C. ulcerans, suggesting vaccine targets to be further tested in vitro for the development of a new vaccine against diphtheria.

Evaluation of the Common Molecular Basis in Alzheimer's and Parkinson's Diseases.

Alzheimer's disease (AD) and Parkinson's disease (PD) are the most common neurodegenerative disorders related to aging. Though several risk factors are shared between these two diseases, the exact relationship between them is still unknown. In this paper, we analyzed how these two diseases relate to each other from the genomic, epigenomic, and transcriptomic viewpoints. Using an extensive literature mining, we first accumulated the list of genes from major genome-wide association (GWAS) studies. Based on these GWAS studies, we observed that only one gene (HLA-DRB5) was shared between AD and PD. A subsequent literature search identified a few other genes involved in these two diseases, among which SIRT1 seemed to be the most prominent one. While we listed all the miRNAs that have been previously reported for AD and PD separately, we found only 15 different miRNAs that were reported in both diseases. In order to get better insights, we predicted the gene co-expression network for both AD and PD using network analysis algorithms applied to two GEO datasets. The network analysis revealed six clusters of genes related to AD and four clusters of genes related to PD; however, there was very low functional similarity between these clusters, pointing to insignificant similarity between AD and PD even at the level of affected biological processes. Finally, we postulated the putative epigenetic regulator modules that are common to AD and PD.

SIMBA: a web tool for managing bacterial genome assembly generated by Ion PGM sequencing technology.

BACKGROUND: The evolution of Next-Generation Sequencing (NGS) has considerably reduced the cost per sequenced-base, allowing a significant rise of sequencing projects, mainly in prokaryotes. However, the range of available NGS platforms requires different strategies and software to correctly assemble genomes. Different strategies are necessary to properly complete an assembly project, in addition to the installation or modification of various software. This requires users to have significant expertise in these software and command line scripting experience on Unix platforms, besides possessing the basic expertise on methodologies and techniques for genome assembly. These difficulties often delay the complete genome assembly projects. RESULTS: In order to overcome this, we developed SIMBA (SImple Manager for Bacterial Assemblies), a freely available web tool that integrates several component tools for assembling and finishing bacterial genomes. SIMBA provides a friendly and intuitive user interface so bioinformaticians, even with low computational expertise, can work under a centralized administrative control system of assemblies managed by the assembly center head. SIMBA guides the users to execute assembly process through simple and interactive pages. SIMBA workflow was divided in three modules: (i) projects: allows a general vision of genome sequencing projects, in addition to data quality analysis and data format conversions; (ii) assemblies: allows de novo assemblies with the software Mira, Minia, Newbler and SPAdes, also assembly quality validations using QUAST software; and (iii) curation: presents methods to finishing assemblies through tools for scaffolding contigs and close gaps. We also presented a case study that validated the efficacy of SIMBA to manage bacterial assemblies projects sequenced using Ion Torrent PGM. CONCLUSION: Besides to be a web tool for genome assembly, SIMBA is a complete genome assemblies project management system, which can be useful for managing of several projects in laboratories. SIMBA source code is available to download and install in local webservers at http://ufmg-simba.sourceforge.net .

Differential transcriptional profile of Corynebacterium pseudotuberculosis in response to abiotic stresses.

BACKGROUND: The completion of whole-genome sequencing for Corynebacterium pseudotuberculosis strain 1002 has contributed to major advances in research aimed at understanding the biology of this microorganism. This bacterium causes significant loss to goat and sheep farmers because it is the causal agent of the infectious disease caseous lymphadenitis, which may lead to outcomes ranging from skin injury to animal death. In the current study, we simulated the conditions experienced by the bacteria during host infection. By sequencing transcripts using the SOLiDTM 3 Plus platform, we identified new targets expected to potentiate the survival and replication of the pathogen in adverse environments. These results may also identify possible candidates useful for the development of vaccines, diagnostic kits or therapies aimed at the reduction of losses in agribusiness. RESULTS: Under the 3 simulated conditions (acid, osmotic and thermal shock stresses), 474 differentially expressed genes exhibiting at least a 2-fold change in expression levels were identified. Important genes to the infection process were induced, such as those involved in virulence, defence against oxidative stress, adhesion and regulation, and many genes encoded hypothetical proteins, indicating that further investigation of the bacterium is necessary. The data will contribute to a better understanding of the biology of C. pseudotuberculosis and to studies investigating strategies to control the disease. CONCLUSIONS: Despite the veterinary importance of C. pseudotuberculosis, the bacterium is poorly characterised; therefore, effective treatments for caseous lymphadenitis have been difficult to establish. Through the use of RNAseq, these results provide a better biological understanding of this bacterium, shed light on the most likely survival mechanisms used by this microorganism in adverse environments and identify candidates that may help reduce or even eradicate the problems caused by this disease.

Omics profiles used to evaluate the gene expression of Exiguobacterium antarcticum B7 during cold adaptation.

BACKGROUND: Exiguobacterium antarcticum strain B7 is a Gram-positive psychrotrophic bacterial species isolated in Antarctica. Although this bacteria has been poorly studied, its genome has already been sequenced. Therefore, it is an appropriate model for the study of thermal adaptation. In the present study, we analyzed the transcriptomes and proteomes of E. antarcticum B7 grown at 0°C and 37°C by SOLiD RNA-Seq, Ion Torrent RNA-Seq and two-dimensional difference gel electrophoresis tandem mass spectrometry (2D-DIGE-MS/MS). RESULTS: We found expression of 2,058 transcripts in all replicates from both platforms and differential expression of 564 genes (absolute log2FC≥1, P-value<0.001) comparing the two temperatures by RNA-Seq. A total of 73 spots were differentially expressed between the two temperatures on 2D-DIGE, 25 of which were identified by MS/MS. Some proteins exhibited patterns of dispersion in the gel that are characteristic of post-translational modifications. CONCLUSIONS: Our findings suggest that the two sequencing platforms yielded similar results and that different omic approaches may be used to improve the understanding of gene expression. To adapt to low temperatures, E. antarcticum B7 expresses four of the six cold-shock proteins present in its genome. The cold-shock proteins were the most abundant in the bacterial proteome at 0°C. Some of the differentially expressed genes are required to preserve transcription and translation, while others encode proteins that contribute to the maintenance of the intracellular environment and appropriate protein folding. The results denote the complexity intrinsic to the adaptation of psychrotrophic organisms to cold environments and are based on two omic approaches. They also unveil the lifestyle of a bacterial species isolated in Antarctica.

Reference genes for RT-qPCR studies in Corynebacterium pseudotuberculosis identified through analysis of RNA-seq data.

Reference genes presenting stable expression profiles over a wide variety of conditions are required in relative expression studies of specific bacterial genes by quantitative reverse transcription PCR (RT-qPCR). High-throughput sequencing of bacterial transcriptomes using the RNA-seq methodology now provides a wealth of data that may be searched for identification of the most stably expressed genes of a given bacterium. Herein, we searched a RNA-seq dataset from various experiments with the pathogenic bacterium Corynebacterium pseudotuberculosis, grown under different stress conditions, in order to select appropriate candidate reference genes for this species. Nineteen genes involved in maintenance of basic cellular functions, so-called housekeeping genes, were chosen for study and their expression profiles in C. pseudotuberculosis were evaluated throughout all growth conditions. Eight of these genes (atpA, dnaG, efp, fusA, gyrA, gyrB, rpoB, and rpoC), mostly participating in DNA replication and transcription, matched the defined criteria to be included as candidate reference genes. Transcriptional levels of these genes were quantified by RT-qPCR assays after growth of C. pseudotuberculosis under two additional conditions. Expression stability analysis by NormFinder indicated the combination of genes encoding DNA gyrase subunit A (gyrA) and elongation factor P (fusA) as the most suitable for normalization of RT-qPCR studies in C. pseudotuberculosis.

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.

High-throughput sequencing of black pepper root transcriptome.

BACKGROUND: Black pepper (Piper nigrum L.) is one of the most popular spices in the world. It is used in cooking and the preservation of food and even has medicinal properties. Losses in production from disease are a major limitation in the culture of this crop. The major diseases are root rot and foot rot, which are results of root infection by Fusarium solani and Phytophtora capsici, respectively. Understanding the molecular interaction between the pathogens and the host's root region is important for obtaining resistant cultivars by biotechnological breeding. Genetic and molecular data for this species, though, are limited. In this paper, RNA-Seq technology has been employed, for the first time, to describe the root transcriptome of black pepper. RESULTS: The root transcriptome of black pepper was sequenced by the NGS SOLiD platform and assembled using the multiple-k method. Blast2Go and orthoMCL methods were used to annotate 10338 unigenes. The 4472 predicted proteins showed about 52% homology with the Arabidopsis proteome. Two root proteomes identified 615 proteins, which seem to define the plant's root pattern. Simple-sequence repeats were identified that may be useful in studies of genetic diversity and may have applications in biotechnology and ecology. CONCLUSIONS: This dataset of 10338 unigenes is crucially important for the biotechnological breeding of black pepper and the ecogenomics of the Magnoliids, a major group of basal angiosperms.

Text mining for identification of biological entities related to antibiotic resistant organisms.

Antimicrobial resistance is a significant public health problem worldwide. In recent years, the scientific community has been intensifying efforts to combat this problem; many experiments have been developed, and many articles are published in this area. However, the growing volume of biological literature increases the difficulty of the biocuration process due to the cost and time required. Modern text mining tools with the adoption of artificial intelligence technology are helpful to assist in the evolution of research. In this article, we propose a text mining model capable of identifying and ranking prioritizing scientific articles in the context of antimicrobial resistance. We retrieved scientific articles from the PubMed database, adopted machine learning techniques to generate the vector representation of the retrieved scientific articles, and identified their similarity with the context. As a result of this process, we obtained a dataset labeled "Relevant" and "Irrelevant" and used this dataset to implement one supervised learning algorithm to classify new records. The model's overall performance reached 90% accuracy and the f-measure (harmonic mean between the metrics) reached 82% accuracy for positive class and 93% for negative class, showing quality in the identification of scientific articles relevant to the context. The dataset, scripts and models are available at https://github.com/engbiopct/TextMiningAMR.

Comparative genomics of Bordetella pertussis and prediction of new vaccines and drug targets.

Pertussis is a highly contagious respiratory disease caused by Bordetella pertussis, a Gram-negative bacterium described over a century ago. Despite broad vaccine coverage and treatment options, the disease is remerging as a public health problem especially in infants and older children. Recent data indicate re-emergence of the disease is related to bacterial resistance to immune defences and decreased vaccine effectiveness, which obviously suggests the need of new effective vaccines and drugs. In an attempt to contribute with solutions to this great challenge, bioinformatics tools were used to genetically comprehend the species of these bacteria and predict new vaccines and drug targets. In fact, approaches were used to analysis genomic plasticity, gene synteny and species similarities between the 20 genomes of Bordetella pertussis already available. Furthermore, it was conducted reverse vaccinology and docking analysis to identify proteins with potential to become vaccine and drug targets, respectively. The analyses showed the 20 genomes belongs to a homogeneous group that has preserved most of the genes over time. Besides that, were found genomics islands and good proteins to be candidates for vaccine and drugs. Taken together, these results suggests new possibilities that may be useful to develop new vaccines and drugs that will help the prevention and treatment strategies of pertussis disease caused by these Bordetella strains. Communicated by Ramaswamy H. Sarma.

Pan-genomic analyses of 47 complete genomes of the Rickettsia genus and prediction of new vaccine targets and virulence factors of the species.

The genus Rickettsia belongs to the Proteobacteria phylum and these bacteria infect animals and humans causing a range of diseases worldwide. The genus is divided into 4 groups and despite the public health threat and the knowledge accumulated so far, the mandatory intracellular bacteria behaviour and limitation for in vitro culture makes it difficult to create new vaccines and drug targets to these bacteria. In an attempt to overcome these limitations, pan-genomic approaches has used 47 genomes of the genus Rickettsia, in order to describe species similarities and genomics islands. Moreover, we conducted reverse vaccinology and docking analysis aiming the identification of proteins that have great potential to become vaccine and drug targets. We found out that the bacteria of the four Rickettsia groups have a high similarity with each other, with about 90 to 100% of identity. A pathogenicity island and a resistance island were predicted. In addition, 8 proteins were also predicted as strong candidates for vaccine and 9 as candidates for drug targets. The prediction of the proteins leads us to believe in a possibility of prospecting potential drugs or creating a polyvalent vaccine, which could reach most strains of this large group of bacteria.Communicated by Ramaswamy H. Sarma.

Pan-genomic analysis of Corynebacterium amycolatum gives insights into molecular mechanisms underpinning the transition to a pathogenic phenotype.

Corynebacterium amycolatum is a nonlipophilic coryneform which is increasingly being recognized as a relevant human and animal pathogen showing multidrug resistance to commonly used antibiotics. However, little is known about the molecular mechanisms involved in transition from colonization to the MDR invasive phenotype in clinical isolates. In this study, we performed a comprehensive pan-genomic analysis of C. amycolatum, including 26 isolates from different countries. We obtained the novel genome sequences of 8 of them, which are multidrug resistant clinical isolates from Spain and Tunisia. They were analyzed together with other 18 complete or draft C. amycolatum genomes retrieved from GenBank. The species C. amycolatum presented an open pan-genome (α = 0.854905), with 3,280 gene families, being 1,690 (51.52%) in the core genome, 1,121 related to accessory genes (34.17%), and 469 related to unique genes (14.29%). Although some classic corynebacterial virulence factors are absent in the species C. amycolatum, we did identify genes associated with immune evasion, toxin, and antiphagocytosis among the predicted putative virulence factors. Additionally, we found genomic evidence for extensive acquisition of antimicrobial resistance genes through genomic islands.

Performance Comparison of Deep Learning Autoencoders for Cancer Subtype Detection Using Multi-Omics Data.

A heterogeneous disease such as cancer is activated through multiple pathways and different perturbations. Depending upon the activated pathway(s), the survival of the patients varies significantly and shows different efficacy to various drugs. Therefore, cancer subtype detection using genomics level data is a significant research problem. Subtype detection is often a complex problem, and in most cases, needs multi-omics data fusion to achieve accurate subtyping. Different data fusion and subtyping approaches have been proposed over the years, such as kernel-based fusion, matrix factorization, and deep learning autoencoders. In this paper, we compared the performance of different deep learning autoencoders for cancer subtype detection. We performed cancer subtype detection on four different cancer types from The Cancer Genome Atlas (TCGA) datasets using four autoencoder implementations. We also predicted the optimal number of subtypes in a cancer type using the silhouette score and found that the detected subtypes exhibit significant differences in survival profiles. Furthermore, we compared the effect of feature selection and similarity measures for subtype detection. For further evaluation, we used the Glioblastoma multiforme (GBM) dataset and identified the differentially expressed genes in each of the subtypes. The results obtained are consistent with other genomic studies and can be corroborated with the involved pathways and biological functions. Thus, it shows that the results from the autoencoders, obtained through the interaction of different datatypes of cancer, can be used for the prediction and characterization of patient subgroups and survival profiles.

Genome Sequence of Pseudomonas sp. Strain LAP_36, A Rhizosphere Bacterium Isolated from King George Island, Antarctica.

Pseudomonas sp. strain LAP_36 was isolated from rhizosphere soil from Deschampsia antarctica on King George Island, South Shetland Islands, Antarctica. Here, we report on its draft genome sequence, which consists of 8,794,771 bp with 60.0% GC content and 8,011 protein-coding genes.

Extended Spectrum Beta-Lactamase-Producing Gram-Negative Bacteria Recovered From an Amazonian Lake Near the City of Belém, Brazil.

Aquatic systems have been described as antibiotic resistance reservoirs, where water may act as a vehicle for the spread of resistant bacteria and resistance genes. We evaluated the occurrence and diversity of third generation cephalosporin-resistant gram-negative bacteria in a lake in the Amazonia region. This water is used for human activities, including consumption after appropriate treatment. Eighteen samples were obtained from six sites in October 2014. Water quality parameters were generally within the legislation limits. Thirty-three bacterial isolates were identified as Escherichia (n = 7 isolates), Acinetobacter, Enterobacter, and Klebsiella (n = 5 each), Pseudomonas (n = 4), Shigella (n = 3), and Chromobacterium, Citrobacter, Leclercia, Phytobacter (1 isolate each). Twenty nine out of 33 isolates (88%) were resistant to most beta-lactams, except carbapenems, and 88% (n = 29) were resistant to antibiotics included in at least three different classes. Among the beta-lactamase genes inspected, the bla CTX-M was the most prevalent (n = 12 positive isolates), followed by bla TEM (n = 5) and bla SHV (n = 4). bla CTX-M-15 (n = 5), bla CTX-M-14 (n = 1) and bla CTX-M-2 (n = 1) variants were detected in conserved genomic contexts: bla CTX-M-15 flanked by ISEcp1 and Orf477; bla CTX-M-14 flanked by ISEcp1 and IS903; and bla CTX-M-2 associated to an ISCR element. For 4 strains the transfer of bla CTX-M was confirmed by conjugation assays. Compared with the recipient, the transconjugants showed more than 500-fold increases in the MICs of cefotaxime and 16 to 32-fold increases in the MICs of ceftazidime. Two isolates (Escherichia coli APC43A and Acinetobacter baumannii APC25) were selected for whole genome analysis. APC43A was predicted as a E. coli pathogen of the high-risk clone ST471 and serotype O154:H18. bla CTX-M-15 as well as determinants related to efflux of antibiotics, were noted in APC43A genome. A. baumannii APC25 was susceptible to carbapenems and antibiotic resistance genes detected in its genome were intrinsic determinants (e.g., bla OXA-208 and bla ADC-like). The strain was not predicted as a human pathogen and belongs to a new sequence type. Operons related to metal resistance were predicted in both genomes as well as pathogenicity and resistance islands. Results suggest a high dissemination of ESBL-producing bacteria in Lake Água Preta which, although not presenting characteristics of a strongly impacted environment, contains multi-drug resistant pathogenic strains.

Genomic Architecture of the Two Cold-Adapted Genera Exiguobacterium and Psychrobacter: Evidence of Functional Reduction in the Exiguobacterium antarcticum B7 Genome.

Exiguobacterium and Psychrobacter are bacterial genera with several cold-adapted species. These extremophiles are commonly isolated from the same habitats in Earth's cryosphere and have great ecological and biotechnological relevance. Thus, through comparative genomic analyses, it was possible to understand the functional diversity of these psychrotrophic and psychrophilic species and present new insights into the microbial adaptation to cold. The nucleotide identity between Exiguobacterium genomes was >90%. Three genomic islands were identified in the E. antarcticum B7 genome. These islands contained genes involved in flagella biosynthesis and chemotaxis, as well as enzymes for carotenoid biosynthesis. Clustering of cold shock proteins by Ka/Ks ratio suggests the occurrence of a positive selection over these genes. Neighbor-joining clustering of complete genomes showed that the E. sibiricum was the most closely related to E. antarcticum. A total of 92 genes were shared between Exiguobacterium and Psychrobacter. A reduction in the genomic content of E. antarcticum B7 was observed. It presented the smallest genome size of its genus and a lower number of genes because of the loss of many gene families compared with the other genomes. In our study, eight genomes of Exiguobacterium and Psychrobacter were compared and analysed. Psychrobacter showed higher genomic plasticity and E. antarcticum B7 presented a large decrease in genomic content without changing its ability to grow in cold environments.

PhageWeb - Web Interface for Rapid Identification and Characterization of Prophages in Bacterial Genomes.

This study developed a computational tool with a graphical interface and a web-service that allows the identification of phage regions through homology search and gene clustering. It uses G+C content variation evaluation and tRNA prediction sites as evidence to reinforce the presence of prophages in indeterminate regions. Also, it performs the functional characterization of the prophages regions through data integration of biological databases. The performance of PhageWeb was compared to other available tools (PHASTER, Prophinder, and PhiSpy) using Sensitivity (Sn) and Positive Predictive Value (PPV) tests. As a reference for the tests, more than 80 manually annotated genomes were used. In the PhageWeb analysis, the Sn index was 86.1% and the PPV was approximately 87%, while the second best tool presented Sn and PPV values of 83.3 and 86.5%, respectively. These numbers allowed us to observe a greater precision in the regions identified by PhageWeb while compared to other prediction tools submitted to the same tests. Additionally, PhageWeb was much faster than the other computational alternatives, decreasing the processing time to approximately one-ninth of the time required by the second best software. PhageWeb is freely available at http://computationalbiology.ufpa.br/phageweb.