Novel Drug Targets for Food-Borne Pathogen Campylobacter jejuni: An Integrated Subtractive Genomics and Comparative Metabolic Pathway Study

Five centuries of genome evolution and multi-host adaptation of Campylobacter jejuni in Brazil

Consumption of raw, undercooked or contaminated animal food products is a frequent cause of Campylobacter jejuni infection. Brazil is the world's third largest producer and a major exporter of chicken meat, yet population-level genomic investigations of C. jejuni in the country remain scarce. Analysis of 221 C. jejuni genomes from Brazil shows that the overall core and accessory genomic features of C. jejuni are influenced by the identity of the human or animal source. Of the 60 sequence types detected, ST353 is the most prevalent and consists of samples from chicken and human sources. Notably, we identified the presence of diverse bla genes from the OXA-61 and OXA-184 families that confer beta-lactam resistance as well as the operon cmeABCR related to multidrug efflux pump, which contributes to resistance against tetracyclines, macrolides and quinolones. Based on limited data, we estimated the most recent common ancestor of ST353 to the late 1500s, coinciding with the time the Portuguese first arrived in Brazil and introduced domesticated chickens into the country. We identified at least two instances of ancestral chicken-to-human infections in ST353. The evolution of C. jejuni in Brazil was driven by the confluence of clinically relevant genetic elements, multi-host adaptation and clonal population growth that coincided with major socio-economic changes in poultry farming.

Identification of Therapeutic Targets in an Emerging Gastrointestinal Pathogen Campylobacter ureolyticus and Possible Intervention through Natural Products

Campylobacter ureolyticus is a Gram-negative, anaerobic, non-spore-forming bacteria that causes gastrointestinal infections. Being the most prevalent cause of bacterial enteritis globally, infection by this bacterium is linked with significant morbidity and mortality in children and immunocompromised patients. No information on pan-therapeutic drug targets for this species is available yet. In the current study, a pan-genome analysis was performed on 13 strains of C. ureolyticus to prioritize potent drug targets from the identified core genome. In total, 26 druggable proteins were identified using subtractive genomics. To the best of the authors’ knowledge, this is the first report on the mining of drug targets in C. ureolyticus. UDP-3-O-acyl-N-acetylglucosamine deacetylase (LpxC) was selected as a promiscuous pharmacological target for virtual screening of two bacterial-derived natural product libraries, i.e., postbiotics (n = 78) and streptomycin (n = 737) compounds. LpxC inhibitors from the ZINC database (n = 142 compounds) were also studied with reference to LpxC of C. ureolyticus. The top three docked compounds from each library (including ZINC26844580, ZINC13474902, ZINC13474878, Notoginsenoside St-4, Asiaticoside F, Paraherquamide E, Phytoene, Lycopene, and Sparsomycin) were selected based on their binding energies and validated using molecular dynamics simulations. To help identify potential risks associated with the selected compounds, ADMET profiling was also performed and most of the compounds were considered safe. Our findings may serve as baseline information for laboratory studies leading to the discovery of drugs for use against C. ureolyticus infections.

Top Trends in Multiomics Research: Evaluation of 52 Published Studies and New Ways of Thinking Terminology and Visual Displays

Multiomics study designs have significantly increased understanding of complex biological systems. The multiomics literature is rapidly expanding and so is their heterogeneity. However, the intricacy and fragmentation of omics data are impeding further research. To examine current trends in multiomics field, we reviewed 52 articles from PubMed and Web of Science, which used an integrated omics approach, published between March 2006 and January 2021. From studies, data regarding investigated loci, species, omics type, and phenotype were extracted, curated, and streamlined according to standardized terminology, and summarized in a previously developed graphical summary. Evaluated studies included 21 omics types or applications of omics technology such as genomics, transcriptomics, metabolomics, epigenomics, environmental omics, and pharmacogenomics, species of various phyla including human, mouse, Arabidopsis thaliana, Saccharomyces cerevisiae, and various phenotypes, including cancer and COVID-19. In the analyzed studies, diverse methods, protocols, results, and terminology were used and accordingly, assessment of the studies was challenging. Adoption of standardized multiomics data presentation in the future will further buttress standardization of terminology and reporting of results in systems science. This shall catalyze, we suggest, innovation in both science communication and laboratory medicine by making available scientific knowledge that is easier to grasp, share, and harness toward medical breakthroughs.

Questing functions and structures of hypothetical proteins from Campylobacter jejuni: a computer-aided approach

Campylobacter jejuni (C. jejuni) is considered to be one of the most frequent causes of bacterial gastroenteritis globally, especially in young children. The genome of C. jejuni contains many proteins with unknown functions termed as hypothetical proteins (HPs). These proteins might have essential biological role to show the full spectrum of this bacterium. Hence, our study aimed to determine the functions of HPs, pertaining to the genome of C. jejuni. An in-silico work flow integrating various tools were performed for functional assignment, three-dimensional structure determination, domain architecture predictors, subcellular localization, physicochemical characterization, and protein-protein interactions (PPIs). Sequences of 267 HPs of C. jejuni were analyzed and successfully attributed the function of 49 HPs with higher confidence. Here, we found proteins with enzymatic activity, transporters, binding and regulatory proteins as well as proteins with biotechnological interest. Assessment of the performance of various tools used in this analysis revealed an accuracy of 95% using receiver operating characteristic (ROC) curve analysis. Functional and structural predictions and the results from ROC analyses provided the validity of in-silico tools used in the present study. The approach used for this analysis leads us to assign the function of unknown proteins and relate them with the functions that have already been described in previous literature.

Identification of Potential Drug Targets in Helicobacter pylori Using In Silico Subtractive Proteomics Approaches and Their Possible Inhibition through Drug Repurposing

The class 1 carcinogen, Helicobacter pylori, is one of the World Health Organization's high priority pathogens for antimicrobial development. We used three subtractive proteomics approaches using protein pools retrieved from: chokepoint reactions in the BIOCYC database, the Kyoto Encyclopedia of Genes and Genomes, and the database of essential genes (DEG), to find putative drug targets and their inhibition by drug repurposing. The subtractive channels included non-homology to human proteome, essentiality analysis, sub-cellular localization prediction, conservation, lack of similarity to gut flora, druggability, and broad-spectrum activity. The minimum inhibitory concentration (MIC) of three selected ligands was determined to confirm anti-helicobacter activity. Seventeen protein targets were retrieved. They are involved in motility, cell wall biosynthesis, processing of environmental and genetic information, and synthesis and metabolism of secondary metabolites, amino acids, vitamins, and cofactors. The DEG protein pool approach was superior, as it retrieved all drug targets identified by the other two approaches. Binding ligands (n = 42) were mostly small non-antibiotic compounds. Citric, dipicolinic, and pyrophosphoric acid inhibited H. pylori at an MIC of 1.5-2.5 mg/mL. In conclusion, we identified potential drug targets in H. pylori, and repurposed their binding ligands as possible anti-helicobacter agents, saving time and effort required for the development of new antimicrobial compounds.

In Silico Screening and Analysis of Broad-Spectrum Molecular Targets and Lead Compounds for Diarrhea Therapy

Diarrhoeal disease kills about 1.5 million human beings per year across the continents. The enterotoxigenic Escherichia coli (ETEC) pathotype has been noted as a major cause of diarrheal disease in human and livestock. The aim of this study is to identify broad-spectrum molecular targets in bacteria and broad-spectrum lead compounds (functional inhibitors) with high efficacy and no significant adverse implication on human systems, in relevance to diarrhea therapy through computational approaches which include phylogenetics, target prediction, molecular docking, and molecular flexibility dynamic simulations. Three molecular target genes, murA, dxr, and DnaE, which code for uridine diphosphate-N-acetylglucosamine-1-carboxyvinyltransferase, 1-deoxy-D-xylulose-5-phosphate reductoisomerase, and deoxyribonucleic acid polymerase III alpha subunit, respectively, were found to be highly conserved in 7 diarrhea-causing microbes. In addition, 21 potential compounds identified showed varied degree of affinity to these enzymes. At free energy cutoff of -8.0 kcal/mol, the highest effective molecular target was DNA polymerase III alpha subunit (PDB ID: 4JOM) followed by UDP-N-acetylglucosamine-1-carboxyvinyltransferase (PDB ID: 5UJS), and 1-deoxy-D-xylulose-5-phosphate reductoisomerase (PDB ID: 1ONN), while the highest effective lead compound was N-coeleneterazine followed by amphotericin B, MMV010576, MMV687800, MMV028694, azithromycin, and diphenoxylate. The flexibility dynamics of DNA polymerase III alpha subunit unraveled the atomic fluctuation which potentially implicated Asp593 as unstable active site amino acid residue. In conclusion, bacteria DnaE gene or its protein is a highly promising molecular target for the next generation of antibacterial drugs of the class of N-coeleneterazine.

Computational Systems Biology of Metabolism in Infection

A systems approach to elucidate the effect of infection on cell metabolism provides several opportunities from a better understanding of molecular mechanisms to the identification of potential biomarkers and drug targets. This is obvious from the fact that we have witnessed the accelerated use of computational systems biology in the last five years to study metabolic changes in pathogen and/or host cells in response to infection. In this chapter, we aim to present a comprehensive review of the recent research by focusing on genome-scale metabolic network models of pathogen-host systems and genome-wide metabolomics and fluxomics analysis of infected cells.