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.

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.

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.

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.

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.

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.

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.

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.

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.

Whole-genome sequencing reveals misidentification of a multidrug-resistant urine clinical isolate as Corynebacterium urealyticum.

OBJECTIVES: Corynebacterium urealyticum is a non-diphtherial urease-producing clinically relevant corynebacterium associated with urinary tract infections. Most clinical C. urealyticum isolates are multidrug-resistant. Whole-genome sequencing (WGS) of C. urealyticum VH4248 isolated from a clinical urine sample at Hospital Universitario Marqués de Valdecilla, Santander, Spain, was performed to predict its antimicrobial resistance profile and to compare it with results of culture-based phenotypic antimicrobial susceptibility testing. METHODS: Classical microbiological methods and VITEK® MS were used for isolation and initial identification of strain VH4248. Draft genome sequencing was performed on an Illumina HiSeq 2500 platform, followed by assembly and annotation using SPAdes and RAST. Resistance genes were identified through PATRIC, the Pathosystems Resource Integration Center. Average nucleotide identity (ANI) analysis was done using the EDGAR and OrthoANI databases. Antimicrobial susceptibility was determined by Etest. RESULTS: Isolate VH4248 was initially identified asC. urealyticum. Its genome size is 2 261 231 bp with 64.4% GC content. Genome-based identification tools showed an average 93.7% similarity between VH4248 and C. urealyticum genomes deposited in public databases. Therefore, this isolate must be classified as Corynebacterium sp. The blaA and ermX genes as well as a class 1 integron including the aadB and sul1 genes are present in the VH4248 genome. This isolate is highly resistant to ampicillin, erythromycin and trimethoprim/sulfamethoxazole, and moderately resistant to gentamicin and kanamycin. CONCLUSIONS: WGS is a powerful tool forCorynebacterium identification to species level and for detection of unusual resistance determinants, such as that encoded by the class 1 integron in isolate VH4248.

Distribution of Beta-Lactamase Producing Gram-Negative Bacterial Isolates in Isabela River of Santo Domingo, Dominican Republic.

Bacteria carrying antibiotic resistance genes (ARGs) are naturally prevalent in lotic ecosystems such as rivers. Their ability to spread in anthropogenic waters could lead to the emergence of multidrug-resistant bacteria of clinical importance. For this study, three regions of the Isabela river, an important urban river in the city of Santo Domingo, were evaluated for the presence of ARGs. The Isabela river is surrounded by communities that do not have access to proper sewage systems; furthermore, water from this river is consumed daily for many activities, including recreation and sanitation. To assess the state of antibiotic resistance dissemination in the Isabela river, nine samples were collected from these three bluedistinct sites in June 2019 and isolates obtained from these sites were selected based on resistance to beta-lactams. Physico-chemical and microbiological parameters were in accordance with the Dominican legislation. Matrix-assisted laser desorption ionization-time of flight mass spectrometry analyses of ribosomal protein composition revealed a total of 8 different genera. Most common genera were as follows: Acinetobacter (44.6%) and Escherichia (18%). Twenty clinically important bacterial isolates were identified from urban regions of the river; these belonged to genera Escherichia (n = 9), Acinetobacter (n = 8), Enterobacter (n = 2), and Klebsiella (n = 1). Clinically important multi-resistant isolates were not obtained from rural areas. Fifteen isolates were selected for genome sequencing and analysis. Most isolates were resistant to at least three different families of antibiotics. Among beta-lactamase genes encountered, we found the presence of blaTEM, blaOXA, blaSHV, and blaKPC through both deep sequencing and PCR amplification. Bacteria found from genus Klebsiella and Enterobacter demonstrated ample repertoire of antibiotic resistance genes, including resistance from a family of last resort antibiotics reserved for dire infections: carbapenems. Some of the alleles found were KPC-3, OXA-1, OXA-72, OXA-132, CTX-M-55, CTX-M-15, and TEM-1.

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.

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.

Searching whole genome sequences for biochemical identification features of emerging and reemerging pathogenic Corynebacterium species.

Biochemical tests are traditionally used for bacterial identification at the species level in clinical microbiology laboratories. While biochemical profiles are generally efficient for the identification of the most important corynebacterial pathogen Corynebacterium diphtheriae, their ability to differentiate between biovars of this bacterium is still controversial. Besides, the unambiguous identification of emerging human pathogenic species of the genus Corynebacterium may be hampered by highly variable biochemical profiles commonly reported for these species, including Corynebacterium striatum, Corynebacterium amycolatum, Corynebacterium minutissimum, and Corynebacterium xerosis. In order to identify the genomic basis contributing for the biochemical variabilities observed in phenotypic identification methods of these bacteria, we combined a comprehensive literature review with a bioinformatics approach based on reconstruction of six specific biochemical reactions/pathways in 33 recently released whole genome sequences. We used data retrieved from curated databases (MetaCyc, PathoSystems Resource Integration Center (PATRIC), The SEED, TransportDB, UniProtKB) associated with homology searches by BLAST and profile Hidden Markov Models (HMMs) to detect enzymes participating in the various pathways and performed ab initio protein structure modeling and molecular docking to confirm specific results. We found a differential distribution among the various strains of genes that code for some important enzymes, such as beta-phosphoglucomutase and fructokinase, and also for individual components of carbohydrate transport systems, including the fructose-specific phosphoenolpyruvate-dependent sugar phosphotransferase (PTS) and the ribose-specific ATP-binging cassette (ABC) transporter. Horizontal gene transfer plays a role in the biochemical variability of the isolates, as some genes needed for sucrose fermentation were seen to be present in genomic islands. Noteworthy, using profile HMMs, we identified an enzyme with putative alpha-1,6-glycosidase activity only in some specific strains of C. diphtheriae and this may aid to understanding of the differential abilities to utilize glycogen and starch between the biovars.

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.

Efficient differentiation of Corynebacterium striatum, Corynebacterium amycolatum and Corynebacterium xerosis clinical isolates by multiplex PCR using novel species-specific primers.

A multiplex-PCR (mPCR) assay was designed with species-specific primers which generate amplicons of 226bp, 434bp and 106bp for differentiating the species C. striatum, C. amycolatum, and C. xerosis, respectively. mPCR results were 100% in agreement with identifications achieved by 16S rRNA and rpoB gene sequencing and by VITEK-MS.

PanWeb: A web interface for pan-genomic analysis.

With increased production of genomic data since the advent of next-generation sequencing (NGS), there has been a need to develop new bioinformatics tools and areas, such as comparative genomics. In comparative genomics, the genetic material of an organism is directly compared to that of another organism to better understand biological species. Moreover, the exponentially growing number of deposited prokaryote genomes has enabled the investigation of several genomic characteristics that are intrinsic to certain species. Thus, a new approach to comparative genomics, termed pan-genomics, was developed. In pan-genomics, various organisms of the same species or genus are compared. Currently, there are many tools that can perform pan-genomic analyses, such as PGAP (Pan-Genome Analysis Pipeline), Panseq (Pan-Genome Sequence Analysis Program) and PGAT (Prokaryotic Genome Analysis Tool). Among these software tools, PGAP was developed in the Perl scripting language and its reliance on UNIX platform terminals and its requirement for an extensive parameterized command line can become a problem for users without previous computational knowledge. Thus, the aim of this study was to develop a web application, known as PanWeb, that serves as a graphical interface for PGAP. In addition, using the output files of the PGAP pipeline, the application generates graphics using custom-developed scripts in the R programming language. PanWeb is freely available at http://www.computationalbiology.ufpa.br/panweb.

Whole-Genome Sequence of Corynebacterium pseudotuberculosis PA04, Isolated from the Lymph Node of a Sheep in the Amazon, Brazil.

This study reports the complete genome sequence of Corynebacterium pseudotuberculosis strain PA04, isolated from a sheep in the Amazon, Brazil. This bacterium is the etiological agent of caseous lymphadenitis. This genome contains 2,338,093 bp, 52.2% G+C content, and a total of 2,104 coding sequences (CDSs), 41 pseudogenes, 12 rRNAs, and 49 tRNAs.

Draft Genome Sequence of Corynebacterium pseudotuberculosis Strain PA05 Isolated from an Ovine Host in Pará State, Brazil.

We report here the draft genome sequence of Corynebacterium pseudotuberculosis PA05, isolated from an ovine host in Pará State, Brazil. C. pseudotuberculosis is an etiological agent of diseases with veterinary and medical importance. The genome contains 2,435,137 bp, a G+C content of 52.2%, 2,295 coding sequences, five pseudogenes, 53 tRNAs, and six rRNAs.