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Genetic characterization and phylogenetic variations of human adenovirus-F strains circulating in eastern India during 2017-2020.

Pritam ChandraMahadeb LoSuvrotoa MitraAnindita BanerjeePriyanka SahaKeinosuke OkamotoAlok Kumar DebSanat Kumar GhoshAsis MannaShanta DuttaChawla Sarkar Mamta
Published in: Journal of medical virology (2021)
Human adenovirus-F (HAdV-F) (genotype 40/41) is the second-most leading cause of pediatric gastroenteritis after rotavirus, worldwide, accounting for 2.8%-11.8% of infantile diarrheal cases. Earlier studies across eastern India revealed a shift in the predominance of genotypes from HAdV41 in 2007-09 to HAdV40 in 2013-14. Thus, the surveillance for HAdV-F genotypes in this geographical setting was undertaken over 2017-2020 to analyze the viral evolutionary dynamics. A total of 3882 stool samples collected from children (≤5 years) were screened for HAdV-F positivity by conventional PCR. The hypervariable regions of the hexon and the partial shaft region of long fiber genes were amplified, sequenced, and phylogenetically analyzed with respect to the prototype strains. A marginal decrease in enteric HAdV prevalence was observed (9.04%, n = 351/3882) compared to the previous report (11.8%) in this endemic setting. Children <2 years were found most vulnerable to enteric HAdV infection. Reduction in adenovirus-rotavirus co-infection was evident compared to the sole adenovirus infection. HAdV-F genotypes 40 and 41 were found to co-circulate, but HAdV41 was predominant. HAdV40 strains were genetically conserved, whereas HAdV41 strains accumulated new mutations. On the basis of a different set of mutations in their genome, HAdV41 strains segregated into 2 genome type clusters (GTCs). Circulating HAdV41 strains clustered with GTC1 of the fiber gene, for the first time during this study period. This study will provide much-needed baseline data on the emergence and circulation of HAdV40/41 strains for future vaccine development.
Keyphrases
  • escherichia coli
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  • gene expression
  • risk factors
  • south africa
  • machine learning
  • big data
  • dna methylation
  • gene therapy