An integrated structural proteomics approach along the druggable genome of Corynebacterium pseudotuberculosis species for putative druggable targets

Subtractive sequence analysis aided druggable targets mining in Burkholderia cepacia complex and finding inhibitors through bioinformatics approach

Burkholderia cepacia complex (BCC) is a group of gram-negative bacteria composed of at least 20 different species that cause diseases in plants, animals as well as humans (cystic fibrosis and airway infection). Here, we analyzed the proteomic data of 47 BCC strains by classifying them in three groups. Phylogenetic analyses were performed followed by individual core region identification for each group. Comparative analysis of the three individual core protein fractions resulted in 1766 ortholog/proteins. Non-human homologous proteins from the core region gave 1680 proteins. Essential protein analyses reduced the target list to 37 proteins, which were further compared to a closely related out-group, Burkholderia gladioli ATCC 10,248 strain, resulting in 21 proteins. 3D structure modeling, validation, and druggability step gave six targets that were subjected to further target prioritization parameters which ultimately resulted in two BCC targets. A library of 12,000 ZINC drug-like compounds was screened, where only the top hits were selected for docking orientations. These included ZINC01405842 (against Chorismate synthase aroC) and ZINC06055530 (against Bifunctional N-acetylglucosamine-1-phosphate uridyltransferase/Glucosamine-1-phosphate acetyltransferase glmU). Finally, dynamics simulation (200 ns) was performed for each ligand-receptor complex, followed by ADMET profiling. Of these targets, details of their applicability as drug targets have not yet been elucidated experimentally, hence making our predictions novel and it is suggested that further wet-lab experimentations should be conducted to test the identified BCC targets and ZINC scaffolds to inhibit them.

A journey through the Corynebacterium pseudotuberculosis proteome promotes insights into its functional genome

Background

Corynebacterium pseudotuberculosis is a Gram-positive facultative intracellular pathogen and the etiologic agent of illnesses like caseous lymphadenitis in small ruminants, mastitis in dairy cattle, ulcerative lymphangitis in equines, and oedematous skin disease in buffalos. With the growing advance in high-throughput technologies, genomic studies have been carried out to explore the molecular basis of its virulence and pathogenicity. However, data large-scale functional genomics studies are necessary to complement genomics data and better understating the molecular basis of a given organism. Here we summarize, MS-based proteomics techniques and bioinformatics tools incorporated in genomic functional studies of C. pseudotuberculosis to discover the different patterns of protein modulation under distinct environmental conditions, and antigenic and drugs targets.

Methodology

In this study we performed an extensive search in Web of Science of original and relevant articles related to methods, strategy, technology, approaches, and bioinformatics tools focused on the functional study of the genome of C. pseudotuberculosis at the protein level.

Results

Here, we highlight the use of proteomics for understating several aspects of the physiology and pathogenesis of C. pseudotuberculosis at the protein level. The implementation and use of protocols, strategies, and proteomics approach to characterize the different subcellular fractions of the proteome of this pathogen. In addition, we have discussed the immunoproteomics, immunoinformatics and genetic tools employed to identify targets for immunoassays, drugs, and vaccines against C. pseudotuberculosis infection.

Conclusion

In this review, we showed that the combination of proteomics and bioinformatics studies is a suitable strategy to elucidate the functional aspects of the C. pseudotuberculosis genome. Together, all information generated from these proteomics studies allowed expanding our knowledge about factors related to the pathophysiology of this pathogen.

From Genome to Drugs: New Approaches in Antimicrobial Discovery

Decades of successful use of antibiotics is currently challenged by the emergence of increasingly resistant bacterial strains. Novel drugs are urgently required but, in a scenario where private investment in the development of new antimicrobials is declining, efforts to combat drug-resistant infections become a worldwide public health problem. Reasons behind unsuccessful new antimicrobial development projects range from inadequate selection of the molecular targets to a lack of innovation. In this context, increasingly available omics data for multiple pathogens has created new drug discovery and development opportunities to fight infectious diseases. Identification of an appropriate molecular target is currently accepted as a critical step of the drug discovery process. Here, we review how diverse layers of multi-omics data in conjunction with structural/functional analysis and systems biology can be used to prioritize the best candidate proteins. Once the target is selected, virtual screening can be used as a robust methodology to explore molecular scaffolds that could act as inhibitors, guiding the development of new drug lead compounds. This review focuses on how the advent of omics and the development and application of bioinformatics strategies conduct a "big-data era" that improves target selection and lead compound identification in a cost-effective and shortened timeline.

New insights into minor splicing-a transcriptomic analysis of cells derived from TALS patients

Minor intron splicing plays a central role in human embryonic development and survival. Indeed, biallelic mutations in RNU4ATAC, transcribed into the minor spliceosomal U4atac snRNA, are responsible for three rare autosomal recessive multimalformation disorders named Taybi-Linder (TALS/MOPD1), Roifman (RFMN), and Lowry-Wood (LWS) syndromes, which associate numerous overlapping signs of varying severity. Although RNA-seq experiments have been conducted on a few RFMN patient cells, none have been performed in TALS, and more generally no in-depth transcriptomic analysis of the ∼700 human genes containing a minor (U12-type) intron had been published as yet. We thus sequenced RNA from cells derived from five skin, three amniotic fluid, and one blood biosamples obtained from seven unrelated TALS cases and from age- and sex-matched controls. This allowed us to describe for the first time the mRNA expression and splicing profile of genes containing U12-type introns, in the context of a functional minor spliceosome. Concerning RNU4ATAC-mutated patients, we show that as expected, they display distinct U12-type intron splicing profiles compared to controls, but that rather unexpectedly mRNA expression levels are mostly unchanged. Furthermore, although U12-type intron missplicing concerns most of the expressed U12 genes, the level of U12-type intron retention is surprisingly low in fibroblasts and amniocytes, and much more pronounced in blood cells. Interestingly, we found several occurrences of introns that can be spliced using either U2, U12, or a combination of both types of splice site consensus sequences, with a shift towards splicing using preferentially U2 sites in TALS patients' cells compared to controls.

Prediction of new vaccine targets in the core genome of Corynebacterium pseudotuberculosis through omics approaches and reverse vaccinology

Corynebacterium pseudotuberculosis is the etiologic agent of veterinary relevance diseases, such as caseous lymphadenitis, affecting different animal species causing damage to the global agribusiness. So far, there are no completely effective treatment methods to overcome the impacts caused by this pathogen. Several genomes of the species are deposited on public databases, allowing the execution of studies related to the pan-genomic approach. In this study, we used an integrated in silico workflow to prospect novel putative targets using the core genome, a set of shared genes among 65 C. pseudotuberculosis strains. Subsequently, through RNA-Seq data of the same abiotic stresses in two strains, we selected only induced genes to compose the reverse vaccinology workflow based in two different strategies. Our results predicted six probable antigens in both analysis, which indicates that they have a strong potential to be used in further studies as vaccine targets against this bacterium.

An integrative, multi-omics approach towards the prioritization of Klebsiella pneumoniae drug targets

Klebsiella pneumoniae (Kp) is a globally disseminated opportunistic pathogen that can cause life-threatening infections. It has been found as the culprit of many infection outbreaks in hospital environments, being particularly aggressive towards newborns and adults under intensive care. Many Kp strains produce extended-spectrum β-lactamases, enzymes that promote resistance against antibiotics used to fight these infections. The presence of other resistance determinants leading to multidrug-resistance also limit therapeutic options, and the use of 'last-resort' drugs, such as polymyxins, is not uncommon. The global emergence and spread of resistant strains underline the need for novel antimicrobials against Kp and related bacterial pathogens. To tackle this great challenge, we generated multiple layers of 'omics' data related to Kp and prioritized proteins that could serve as attractive targets for antimicrobial development. Genomics, transcriptomics, structuromic and metabolic information were integrated in order to prioritize candidate targets, and this data compendium is freely available as a web server. Twenty-nine proteins with desirable characteristics from a drug development perspective were shortlisted, which participate in important processes such as lipid synthesis, cofactor production, and core metabolism. Collectively, our results point towards novel targets for the control of Kp and related bacterial pathogens.

The Druggable Pocketome of Corynebacterium diphtheriae: A New Approach for in silico Putative Druggable Targets

Diphtheria is an acute and highly infectious disease, previously regarded as endemic in nature but vaccine-preventable, is caused by Corynebacterium diphtheriae (Cd). In this work, we used an in silico approach along the 13 complete genome sequences of C. diphtheriae followed by a computational assessment of structural information of the binding sites to characterize the “pocketome druggability.” To this end, we first computed the “modelome” (3D structures of a complete genome) of a randomly selected reference strain Cd NCTC13129; that had 13,763 open reading frames (ORFs) and resulted in 1,253 (∼9%) structure models. The amino acid sequences of these modeled structures were compared with the remaining 12 genomes and consequently, 438 conserved protein sequences were obtained. The RCSB-PDB database was consulted to check the template structures for these conserved proteins and as a result, 401 adequate 3D models were obtained. We subsequently predicted the protein pockets for the obtained set of models and kept only the conserved pockets that had highly druggable (HD) values (137 across all strains). Later, an off-target host homology analyses was performed considering the human proteome using NCBI database. Furthermore, the gene essentiality analysis was carried out that gave a final set of 10-conserved targets possessing highly druggable protein pockets. To check the target identification robustness of the pipeline used in this work, we crosschecked the final target list with another in-house target identification approach for C. diphtheriae thereby obtaining three common targets, these were; hisE-phosphoribosyl-ATP pyrophosphatase, glpX-fructose 1,6-bisphosphatase II, and rpsH-30S ribosomal protein S8. Our predicted results suggest that the in silico approach used could potentially aid in experimental polypharmacological target determination in C. diphtheriae and other pathogens, thereby, might complement the existing and new drug-discovery pipelines.

PBIT: Pipeline Builder for Identification of drug Targets for infectious diseases

Summary

PBIT (Pipeline Builder for Identification of drug Targets) is an online webserver that has been developed for screening of microbial proteomes for critical features of human drug targets such as being non-homologous to human proteome as well as the human gut microbiota, essential for the pathogen's survival, participation in pathogen-specific pathways etc. The tool has been validated by analyzing 57 putative targets of Candida albicans documented in literature. PBIT integrates various in silico approaches known for drug target identification and will facilitate high-throughput prediction of drug targets for infectious diseases, including multi-pathogenic infections.

Availability and Implementation

PBIT is freely accessible at http://www.pbit.bicnirrh.res.in/ .

Contact

thomass@nirrh.res.in.

Supplementary information

Supplementary data are available at Bioinformatics online.

LigQ: A Webserver to Select and Prepare Ligands for Virtual Screening

Virtual screening is a powerful methodology to search for new small molecule inhibitors against a desired molecular target. Usually, it involves evaluating thousands of compounds (derived from large databases) in order to select a set of potential binders that will be tested in the wet-lab. The number of tested compounds is directly proportional to the cost, and thus, the best possible set of ligands is the one with the highest number of true binders, for the smallest possible compound set size. Therefore, methods that are able to trim down large universal data sets enriching them in potential binders are highly appreciated. Here we present LigQ, a free webserver that is able to (i) determine best structure and ligand binding pocket for a desired protein, (ii) find known binders, as well as potential ligands known to bind to similar protein domains, (iii) most importantly, select a small set of commercial compounds enriched in potential binders, and (iv) prepare them for virtual screening. LigQ was tested with several proteins, showing an impressive capacity to retrieve true ligands from large data sets, achieving enrichment factors of over 10%. LigQ is available at http://ligq.qb.fcen.uba.ar/ .

Recombinant esterase from Corynebacterium pseudotuberculosis in DNA and subunit recombinant vaccines partially protects mice against challenge

PURPOSE

We tested the efficacy of the esterase encoded by cp1002_RS09720 from Corynebacteriumpseudotuberculosis in recombinant subunit and DNA caseous lymphadenitis (CLA) vaccines. This target was predicted as one of the best CLA vaccine candidates by mature epitope density analysis.

METHODOLOGY

Gene cp1002_RS09720 was cloned into two different vectors (pAE for subunit vaccine and pTARGET for DNA vaccine). Four groups of 15 mice each were immunized with the recombinant esterase rCP09720 associated with aluminium hydroxide adjuvant (G1), pTARGET/cp09720 DNA vaccine (G2), a naked pTARGET (G3) or PBS as a negative control (G4). Immunization occurred in two doses intercalated by a 21 day interval. Twenty-one days after the last dose administration, animals were challenged with a virulent C. pseudotuberculosis MIC-6 strain.

RESULTS

G1 showed high levels of IgG1 and IgG2a on days 21 and 42 post-immunization and a significant level of IFN-γ (P<0.05), suggesting a Th1 response. The protection levels obtained were 58.3 and 16.6 % for G1 and G2, respectively.

CONCLUSION

The subunit vaccine composed of the recombinant esterase rCP09720 and Al(OH)3 is a promising antigenic formulation for use against CLA.

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.

Granulosa cell biomarkers to predict pregnancy in ART: pieces to solve the puzzle

Cumulus and mural granulosa cells of the ovarian follicle surround and interact with the developing oocyte. These follicular cells reflect the oocyte's overall health and may indicate subsequent developmental competence of embryos. Biomarkers of granulosa cells associated with individual oocytes could potentially be used in assisted reproduction to indicate which embryos have the best chance of implanting in the uterus and completing gestation. In this review, we have performed a comprehensive assessment of the recent literature for human cumulus and mural granulosa cell mRNA biomarkers as they relate to pregnancy and live birth. A critical discussion of variables affecting granulosa gene expression profiles for in vitro fertilization patients, including patient demographics and ovarian stimulation regimens, is presented. Although studies with microarray data were evaluated, this synopsis focuses on expressed genes that have been validated by quantitative RT-PCR. Furthermore, we summarize the current published data that support or refute identified granulosa expressed genes as potential biomarkers of embryos that give rise to ongoing pregnancy and live birth. Finally, we review studies that offer predictive models for embryo selection for uterine transfer based on biomarkers that show differential gene expression.

Pitfalls of the Geographic Population Structure (GPS) Approach Applied to Human Genetic History: A Case Study of Ashkenazi Jews

In a recent interdisciplinary study, Das et al. have attempted to trace the homeland of Ashkenazi Jews and of their historical language, Yiddish (Das et al. 2016 Localizing Ashkenazic Jews to Primeval Villages in the Ancient Iranian Lands of Ashkenaz. Genome Biol Evol. 8:1132-1149). Das et al. applied the geographic population structure (GPS) method to autosomal genotyping data and inferred geographic coordinates of populations supposedly ancestral to Ashkenazi Jews, placing them in Eastern Turkey. They argued that this unexpected genetic result goes against the widely accepted notion of Ashkenazi origin in the Levant, and speculated that Yiddish was originally a Slavic language strongly influenced by Iranian and Turkic languages, and later remodeled completely under Germanic influence. In our view, there are major conceptual problems with both the genetic and linguistic parts of the work. We argue that GPS is a provenancing tool suited to inferring the geographic region where a modern and recently unadmixed genome is most likely to arise, but is hardly suitable for admixed populations and for tracing ancestry up to 1,000 years before present, as its authors have previously claimed. Moreover, all methods of historical linguistics concur that Yiddish is a Germanic language, with no reliable evidence for Slavic, Iranian, or Turkic substrata.

Toward high-resolution population genomics using archaeological samples

The term ‘ancient DNA’ (aDNA) is coming of age, with over 1,200 hits in the PubMed database, beginning in the early 1980s with the studies of ‘molecular paleontology’. Rooted in cloning and limited sequencing of DNA from ancient remains during the pre-PCR era, the field has made incredible progress since the introduction of PCR and next-generation sequencing. Over the last decade, aDNA analysis ushered in a new era in genomics and became the method of choice for reconstructing the history of organisms, their biogeography, and migration routes, with applications in evolutionary biology, population genetics, archaeogenetics, paleo-epidemiology, and many other areas. This change was brought by development of new strategies for coping with the challenges in studying aDNA due to damage and fragmentation, scarce samples, significant historical gaps, and limited applicability of population genetics methods. In this review, we describe the state-of-the-art achievements in aDNA studies, with particular focus on human evolution and demographic history. We present the current experimental and theoretical procedures for handling and analysing highly degraded aDNA. We also review the challenges in the rapidly growing field of ancient epigenomics. Advancement of aDNA tools and methods signifies a new era in population genetics and evolutionary medicine research.

Whole-Genome Sequence of Corynebacterium pseudotuberculosis 262 Biovar equi Isolated from Cow Milk

We report the complete genome sequence ofCorynebacterium pseudotuberculosis262, isolated from a bovine host.C. pseudotuberculosisis an etiological agent of diseases with medical and veterinary relevance. The genome contains 2,325,749 bp, 52.8% G+C content, 2,022 coding sequences (CDS), 50 pseudogenes, 48 tRNAs, and 12 rRNAs.