These findings, linked to the severity of symptoms like severe diarrhea and dehydration, could pave the way for new strategies to combat cholera, a disease threatening millions worldwide.
In a recent study published in Nature Communications, researchers combined machine learning (ML), genome-scale metabolic modeling (GSSM), and three-dimensional (3D) analysis to identify genetic factors that drive Vibrio cholera transmission and disease severity.
Background
Cholera is an acute diarrheal disease affecting millions globally, with significant mortality rates, particularly in endemic regions like Bangladesh. V. cholera is the bacterial organism that causes cholera. Variants in the O1 serogroup (Inaba and Ogawa serotypes) of the bacteria, like BD-1 and BD-1.2, caused the recent 2022 outbreak.
The emergence of new variants indicates that the bacteria is evolving. Genetic mutations increase the transmissibility and virulence of the microbe. Understanding the genetic factors that make Vibrio more pathogenic could facilitate the development of novel treatments to lower the disease burden.
About the study
In the present study, researchers used GSMM and machine learning with 3D structural analysis to identify genetic mutations that make V. cholerae more transmissible and virulent.
Researchers analyzed 129 V. cholera isolates from fecal samples of individuals hospitalized due to diarrhea in Bangladesh (Chittagong, Barisal, Khulna, Dhaka, Sylhet, and Rajshahi regions) in 2015- 2021. Participants provided clinical data covering diarrhea, abdominal pain, stool frequency, dehydration, and vomiting, in addition to their age and sex.
Researchers cultured Vibrio cholera, followed by serotyping it with monoclonal antibodies. Whole-genome sequencing (WGS) confirmed the isolates, which underwent antibiotic susceptibility testing. In addition, researchers analyzed WGS data from 1,140 V. cholera isolates obtained from Africa, India, Yemen, and Haiti.
Researchers investigated the genetic signature of the BD-1.2 strain. The genetic analyses included several determinants, accessory genes, core traits, and mutations or single-nucleotide polymorphisms (SNPs). The researchers performed pangenome analysis, including 218 isolates collected in Bangladesh between 2004 and 2022, obtained from the European Nucleotide Archive (ENA). They also performed phylogenetic analysis.
Machine learning models determined whether correlations exist between the genetic mutations in the BD-1.2 strain and clinical symptoms. Protein-protein interaction analyses investigated proteins encoding for genes related to clinical symptoms mapped to the STRING database. Gene ontology (GO) analysis annotated protein function. The 3D analysis enabled structural and stability analysis of proteins. GSMM, flux variability analysis (FVA), and flux balance analysis (FBA) evaluated the effects of genetic mutations on V. cholera growth and metabolism in the generalized iAM-Vc960 and strain-specific models. Researchers compared the findings to 219 Vibrio cholera O1 isolates from Dhaka and Kolkata from 2004 to 2022.
Results
Mutations in SXT-related integrating conjugative elements (SXT ICE), Vibrio pathogenic island 1 (VPI-1), Vibrio seventh pandemic island II (VSP-II), cholera toxin B subunit (ctxB), and gryA alleles increased the transmissibility and virulence of BD-2 and BD-1.2. These genetic changes correlate with clinical symptoms and disease severity.
Interactions between genes associated with transcription regulation, protein stability, and metabolism, involving genes like translocation and assembly module subunit T (tamA), 17-kilodalton protein (skp), cysteine (cysG), and chloride channel accessory (clcA), increased intestinal colonization and acid tolerance of V. cholerae.
Accessory genes like endonuclease (endA), B-cell lymphoma 2 (bcr_2), hdfR_4, and alcohol dehydrogenase (adh) present exclusively in BD-1.2 improved antibiotic resistance and biofilm formation. The researchers identified 77 mutations in the coding region, mapped to 50 genes, including 12 annotated accessory genes, that increased the transmission potential of BD-1.2. The study showed an overlap of four accessory genes, 11 mutations, and one intergenic SNP between the genetic determinants related to BD-1.2 transmission and disease presentation.
Four SNPs, 39 accessory genes, and 17 mutations were associated with symptom severity. Triclosan-resistant enoyl-acyl-carrier protein reductase (FabV) and glutathione synthetase (GshB) SNPs increased symptom severity. SNPs in the translation elongation factor EF-Tu 1 (tufB), diaminopimelate epimerase (dapF), and colipase (clpS) genes were associated with symptom duration. Genes like dapF and gshB significantly altered the growth, flux, and metabolic yield of V. cholera in the generalized and strain-specific models.
Of 28 core SNPs associated with clinical symptoms, 11 differed between BD-1.2 and BD-2. Over 50% of core mutations and 11% of accessory genes significantly differed among the two variants. Tetracycline resistance protein (TetA) and Tetracycline repressor protein (tetR) genes were predominant antibiotic-resistant genes in BD-2 (98%).
Phylogenetic analysis showed tryptophan at the 249th position in BD-2, whereas leucine filled the position in BD-1.2. BD2 lacked the phage-inducible chromosomal island-like element 1 (PLE1) detected in BD-1.2. The comparative study of 1,134 isolates from 84 nations confirmed the findings.
Conclusion
The study highlights the genetic evolution of Vibrio cholerae, particularly in Bangladesh, identifying genetic mutations in core and accessory genes that increase the spread and virulence of the organism.
Genomic analyses reveal variations in pathogenicity and transmission mechanisms between BD-2 and BD-1.2 allelic variants correlating with clinical symptoms. The genetic complexity of V. cholera indicates the need for advanced techniques and strategies to manage cholera outbreaks.