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Begum, Y.

Publications and source records attributed to Begum, Y..

4 recordsLinked to original sources

Vibrio cholerae lineage and pangenome diversity varies geographically across Bangladesh over one year

Cholera is a diarrhoeal disease caused by Vibrio cholerae. It remains a major public health challenge in the endemic region around the Bay of Bengal. Over decadal time scales, one lineage typically dominates the others and spreads in global pandemic waves. However, it remains unclear to what extent diverse lineages co-circulate during a single outbreak season. Defining the pool of diversity during finer time scales is important because the selective pressures that impact V. cholerae - namely antibiotics and phages - are dynamic on these time scales. To study the nationwide diversity of V. cholerae, we long-read sequenced 273 V. cholerae genomes from seven hospitals over one year (2018) in Bangladesh. Four major V. cholerae lineages were identified: known lineages BD-1, BD-2a, and BD-2b, and a novel lineage that we call BD-3. In 2022, BD-1 caused a large cholera outbreak in Dhaka, apparently outcompeting BD-2 lineages. We show that, in 2018, BD-1 was already dominant in the five northern regions, including Dhaka, consistent with an origin from India in the north. By contrast, we observed a higher diversity of lineages in the two southern regions near the coast. The four lineages differed in pangenome content, including integrative and conjugative elements (ICEs) and genes involved in resistance to bacteriophages and antibiotics. Notably, BD-2a lacked an ICE and is predicted to be more sensitive to phages and antibiotics, but nevertheless persisted throughout the year-long sampling period. Genes associated with antibiotic resistance in V. cholerae from Bangladesh in 2006 were entirely absent from all lineages in 2018-19, suggesting shifting costs and benefits of encoding these genes. Together, our results highlight the dynamic nature of the V. cholerae pangenome and the geographic structure of its lineage diversity.

microbiology↗

Phage predation and antibiotic exposure are inversely associated with disease severity and shape pathogen genetic diversity in cholera patients

Despite an increasingly detailed picture of the molecular mechanisms of phage-bacterial interactions, we lack an understanding of how these interactions evolve and impact disease within patients. Here we report a year-long, nation-wide study of diarrheal disease patients in Bangladesh. Among cholera patients, we quantified Vibrio cholerae (prey) and its virulent phages (predators) using metagenomics and quantitative PCR, while accounting for antibiotic exposure using quantitative mass spectrometry. Virulent phage (ICP1) and antibiotics suppressed V. cholerae to varying degrees and were inversely associated with severe dehydration depending on resistance mechanisms. In the absence of anti-phage defenses, predation was effective, with a high predator:prey ratio that correlated with increased genetic diversity among the prey. In the presence of anti-phage defenses, predation was ineffective, with a lower predator:prey ratio that correlated with increased genetic diversity among the predators. Phage-bacteria coevolution within patients should therefore be considered in the deployment of phage-based therapies and diagnostics. One Sentence SummaryA survey of cholera patients in Bangladesh identifies phage predation as a biomarker of disease severity and driver of coevolution within patients.

microbiology↗

Optimization of conditions for conjugation of outer membrane vesicles of Salmonella Typhimurium with oral delivery systems using response surface method

BackgroundOuter membrane vesicles (OMVs) released from Salmonella Typhimurium can become the effective vaccine candidate. For efficient delivery through oral route, the OMVs are conjugated with some delivery systems. The current study was aimed at optimization of conditions required for conjugation of OMVs with nano- or microparticles for maximum entrapment of OMV in terms of protein concentration. MethodsThe OMVs of Salmonella Typhimurium were conjugated under three optimum conditions of pH, temperature and ratio (nanoparticles or microparticles: OMVs) predicted by response surface method. The efficiency of conjugation was determined by entrapment of OMVs in nano/microparticles. ResultThe pH and temperature were not influential conditions in case of conjugation of OMVs with chitosan nanoparticles (Ch-NP) and poly-lactide co-glycolide microparticles (PLG-MP) while they had influence in case of poly(anhydride) nanoparticles. In case of Ch-NP and PLG-MP, the optimum ratio for maximum entrapment was found to be 1:10 and 1:9 respectively. The optimum pH and temperature was found to be 7 and 24{degrees}C respectively for conjugation of poly(anhydride) nanoparticles. The optimized conditions did not alter the protein profile and immunogenic potential of conjugated vaccines.

biochemistry↗

Predicting Vibrio cholerae infection and disease severity using metagenomics in a prospective cohort study

BackgroundSusceptibility to Vibrio cholerae infection is impacted by blood group, age, and pre-existing immunity, but these factors only partially explain who becomes infected. A recent study used 16S rRNA amplicon sequencing to quantify the composition of the gut microbiome and identify predictive biomarkers of infection with limited taxonomic resolution. MethodsTo achieve increased resolution of gut microbial factors associated with V. cholerae susceptibility and identify predictors of symptomatic disease, we applied deep shotgun metagenomic sequencing to a cohort of household contacts of patients with cholera. ResultsUsing machine learning, we resolved species, strains, gene families, and cellular pathways in the microbiome at the time of exposure to V. cholerae to identify markers that predict infection and symptoms. Use of metagenomic features improved the precision and accuracy of prediction relative to 16S sequencing. We also predicted disease severity, although with greater uncertainty than our infection prediction. Species within the genera Prevotella and Bifidobacterium predicted protection from infection, and genes involved in iron metabolism also correlated with protection. ConclusionOur results highlight the power of metagenomics to predict disease outcomes and suggest specific species and genes for experimental testing to investigate mechanisms of microbiome-related protection from cholera. SUMMARYCholera infection and disease severity can be predicted using metagenomic sequencing of the gut microbiome pre-infection in a prospective cohort, and suggests potentially protective bacterial species and genes.

microbiology↗