A Comprehensive Bioinformatics Resource Guide for Genome-Based Antimicrobial Resistance Studies.

The use of high-throughput sequencing technologies and bioinformatic tools has greatly transformed microbial genome research. With the help of sophisticated computational tools, it has become easier to perform whole genome assembly, identify and compare different species based on their genomes, and predict the presence of genes responsible for proteins, antimicrobial resistance, and toxins. These bioinformatics resources are likely to continuously improve in quality, become more user-friendly to analyze the multiple genomic data, efficient in generating information and translating it into meaningful knowledge, and enhance our understanding of the genetic mechanism of AMR. In this manuscript, we provide an essential guide for selecting the popular resources for microbial research, such as genome assembly and annotation, antibiotic resistance gene profiling, identification of virulence factors, and drug interaction studies. In addition, we discuss the best practices in computer-oriented microbial genome research, emerging trends in microbial genomic data analysis, integration of multi-omics data, the appropriate use of machine-learning algorithms, and open-source bioinformatics resources for genome data analytics.

Emerging Pathogens in Planetary Health and Lessons from Comparative Genome Analyses of Three Clostridia Species.

Clostridioides difficile (CD) is a major planetary health burden. A Gram-positive opportunistic pathogen, CD, colonizes the large intestine and is implicated in sepsis, pseudomembranous colitis, and colorectal cancer. C. difficile infection typically following antibiotic exposure results in dysbiosis of the gut microbiome, and is one of the leading causes of diarrhea in the elderly population. While several studies have focused on the toxigenic strains of CD, gut commensals such as Clostridium butyricum (CB) and Clostridium tertium (CT) could harbor toxin/virulence genes, and thus pose a threat to human health. In this study, we sequenced and characterized three isolates, namely, CT (MALS001), CB (MALS002), and CD (MALS003) for their antimicrobial, cytotoxic, antiproliferative, genomic, and proteomic profiles. Although in vitro cytotoxic and antiproliferative potential were observed predominantly in CD MALS003, genome analysis revealed pathogenic potential of CB MALS002 and CT MALS001. Pangenome analysis revealed the presence of several accessory genes typically involved in fitness, virulence, and resistance characteristics in the core genomes of sequenced strains. The presence of an array of virulence and antimicrobial resistance genes in CB MALS002 and CT MALS001 suggests their potential role as emerging pathogens with significant impact on planetary health.

How Can Omics Inform Diabetic Foot Ulcer Clinical Management? A Whole Genome Comparison of Four Clinical Strains of Staphylococcus aureus.

Foot ulcers and associated infections significantly contribute to morbidity and mortality in diabetes. While diverse pathogens are found in the diabetes-related infected ulcers, Staphylococcus aureus remains one of the most virulent and widely prevalent pathogens. The high prevalence of S. aureus in chronic wound infections, especially in clinical settings, is attributed to its ability to evolve and acquire resistance against common antibiotics and to elicit an array of virulence factors. In this study, whole genome comparison of four strains of S. aureus (MUF168, MUF256, MUM270, and MUM475) isolated from diabetic foot ulcer (DFU) infections showing varying resistance patterns was carried out to study the genomic similarity, antibiotic resistance profiling, associated virulence factors, and sequence variations in drug targets. The comparative genome analysis showed strains MUM475 and MUM270 to be highly resistant, MUF256 with moderate levels of resistance, and MUF168 to be the least resistant. Strain MUF256 and MUM475 harbored more virulence factors compared with other two strains. Deleterious sequence variants were observed suggesting potential role in altering drug targets and drug efficacy. This comparative whole genome study offers new molecular insights that may potentially inform evidence-based diagnosis and treatment of DFUs in the clinic.

Horizon Scanning: Rise of Planetary Health Genomics and Digital Twins for Pandemic Preparedness.

The Covid-19 pandemic accelerated research and development not only in infectious diseases but also in digital technologies to improve monitoring, forecasting, and intervening on planetary and ecological risks. In the European Commission, the Destination Earth (DestinE) is a current major initiative to develop a digital model of the Earth (a "digital twin") with high precision. Moreover, omics systems science is undergoing digital transformation impacting nearly all dimensions of the field, including real-time phenotype capture to data analytics using machine learning and artificial intelligence, to name but a few emerging frontiers. We discuss the ways in which the current ongoing digital transformation in omics offers synergies with digital twins/DestinE. Importantly, we note here the rise of a new field of scholarship, planetary health genomics. We conclude that digital transformation in public and private sectors, digital twins/DestinE, and their convergence with omics systems science are poised to build robust capacities for pandemic preparedness and resilient societies in the 21st century.

Exploring the signature gut and oral microbiome in individuals of specific Ayurveda prakriti.

Diagnosis and treatment of various diseases in Ayurveda, the Indian system of medicine, relies on 'prakriti' phenotyping of individuals into predominantly three constitutions, kapha, pitta and vata. Recent studies propose that microbiome play an integral role in precision medicine. A study of the relationship between prakriti - the basis of personalized medicine in Ayurveda and that of gut microbiome, and possible biomarker of an individual's health, would vastly improve precision therapy. Towards this, we analyzed bacterial metagenomes from buccal (oral microbiome) and fecal (gut microbiome) samples of 272 healthy individuals of various predominant prakritis. Major bacterial genera from gut microbiome included Prevotella, Bacteroides and Dialister while oral microbiome included Streptococcus, Neisseria, Veilonella, Haemophilus, Porphyromonas and Prevotella. Though the core microbiome was shared across all individuals, we found prakriti specific signatures such as preferential presence of Paraprevotella and Christensenellaceae in vata individuals. A comparison of core gut microbiome of each prakriti with a database of 'healthy' microbes identified microbes unique to each prakriti with functional roles similar to the physiological characteristics of various prakritis as described in Ayurveda. Our findings provide evidence to Ayurvedic interventions based on prakriti phenotyping and possible microbial biomarkers that can stratify the heterogenous population and aid in precision therapy.

Global Open Health Data Cooperatives Cloud in an Era of COVID-19 and Planetary Health.

Big data in both the public domain and the health care industry are growing rapidly, for example, with broad availability of next-generation sequencing and large-scale phenomics datasets on patient-reported outcomes. In parallel, we are witnessing new research approaches that demand sharing of data for the benefit of planetary society. Health data cooperatives (HDCs) is one such approach, where health data are owned and governed collectively by citizens who take part in the HDCs. Data stored in HDCs should remain readily available for translation to public health practice but at the same time, governed in a critically informed manner to ensure data integrity, veracity, and privacy, to name a few pressing concerns. As a solution, we suggest that data generated from high-throughput omics research and phenomics can be stored in an open cloud platform so that researchers around the globe can share health data and work collaboratively. We describe here the Global Open Health Data Cooperatives Cloud (GOHDCC) as a proposed cloud platform-based model for the sharing of health data between different HDCCs around the globe. GOHDCC's main objective is to share health data on a global scale for robust and responsible global science, research, and development. GOHDCC is a citizen-oriented model cooperatively governed by citizens. The model essentially represents a global sharing platform that could benefit all stakeholders along the health care value chain.

Signaling pathways promoting epithelial mesenchymal transition in oral submucous fibrosis and oral squamous cell carcinoma.

Epithelial-mesenchymal transition (EMT) is a critical process that occurs during the embryonic development, wound healing, organ fibrosis and the onset of malignancy. Emerging evidence suggests that the EMT is involved in the invasion and metastasis of cancers. The inflammatory reaction antecedent to fibrosis in the onset of oral submucous fibrosis (OSF) and the role of EMT in its malignant transformation indicates a hitherto unexplored involvement of EMT. This review focuses on the role of EMT markers which are regulators of the EMT mediated complex network of molecular mechanisms involved in the pathogenesis of OSF and OSCC. Further the gene enrichment analysis and pathway analysis supports the association of the upregulated and downregulated genes in various EMT regulating pathways.