Dataset Information

Prevalence and Genetic Diversity of Group A Rotavirus Genotypes in Moscow (2019-2020).

ABSTRACT: Group A rotavirus (RVA) infection is the leading cause of hospitalization of children under 5 years old, presenting with symptoms of acute gastroenteritis. The aim of our study was to explore the genetic diversity of RVA among patients admitted to Moscow Infectious Disease Clinical Hospital No. 1 with symptoms of acute gastroenteritis. A total of 653 samples were collected from May 2019 through March 2020. Out of them, 135 (20.67%) fecal samples were found to be positive for rotavirus antigen by ELISA. RT-PCR detected rotavirus RNA in 80 samples. Seven G-genotypes (G1, G2, G3, G4, G8, G9, and G12) and three P-genotypes (P[8], P[4], and P[6]) formed 9 different combinations. The most common combination was G9P[8]. However, for the first time in Moscow, the combination G3P[8] took second place. Moreover, all detected viruses of this combination belonged to Equine-like G3P[8] viruses that had never been detected in Russia before. The genotype G8P[8] and G9P[4] rotaviruses were also detected in Moscow for the first time. Among the studied rotaviruses, there were equal proportions of Wa and DS-1-like strains; previous studies showed that Wa-like strains accounted for the largest proportion of rotaviruses in Russia.

SUBMITTER: Yuzhakov A

PROVIDER: S-EPMC8228337 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

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Prevalence and Genetic Diversity of Group A Rotavirus Genotypes in Moscow (2019-2020).

Yuzhakov Anton A Yuzhakova Ksenia K Kulikova Nadezhda N Kisteneva Lidia L Cherepushkin Stanislav S Smetanina Svetlana S Bazarova Marina M Syroeshkin Anton A Grebennikova Tatiana T

Pathogens (Basel, Switzerland) 20210530 6

Group A rotavirus (RVA) infection is the leading cause of hospitalization of children under 5 years old, presenting with symptoms of acute gastroenteritis. The aim of our study was to explore the genetic diversity of RVA among patients admitted to Moscow Infectious Disease Clinical Hospital No. 1 with symptoms of acute gastroenteritis. A total of 653 samples were collected from May 2019 through March 2020. Out of them, 135 (20.67%) fecal samples were found to be positive for rotavirus antigen by ...[more]

PMID: 34070814

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Project description:Porcine circovirus type 3 (PCV3), a virus belonging to the Circoviridae family, is considered to be associated with respiratory and neurological signs, cardiac and multisystemic inflammation, reproductive failure, and porcine dermatitis and nephropathy syndrome-like disease in pigs (Sus scrofa). In this study, epidemiological and serological investigations of PCV3 in clinically healthy pigs from different regions of China were performed. Overall, 42.87% (1,101/2,568) of pigs were positive for PCV3 Cap antibody via indirect enzyme-linked immunosorbent assay, with a higher prevalence of PCV3 in multiparous sows (62.22%, 881/1,416) and fattening pigs (28.96%, 159/549) than in suckling piglets (8.96%, 32/357) and nursery pigs (11.79%, 29/246). Of the 2,568 samples, 255 were further tested for PCV3 DNA using real-time polymerase chain reaction, and 63.14% of these were positive, with nearly half having <10 virus copies. The PCV3 DNA and antibody positivity rates were high in the pig serum samples; however, the virus titers and antibody levels were both low, indicating that the humoral immune response of PCV3-infected pigs was weak or lagging, and persistent or repeated infections could occur. Additionally, the complete genomes of 23 PCV3 strains were sequenced and analyzed, which showed nucleotide identities of 98.5~100.0%, 98.6~100.0%, and 99.2~100.0% in the complete genome, open reading frame (ORF)2, and ORF1 sequences, respectively, and amino acid identities of 96.7~100.0% and 99.3~100.0% in the capsid and replicase proteins, respectively. Phylogenetic analysis based on ORF2 nucleotide sequences indicated that the PCV3 strains obtained in the present study could be classified into three sub-clades, with most strains clustered into clade 3c, indicating that PCV3c is the dominant subtype in the regions of China investigated. In general, the present study revealed a high prevalence and high genetic divergence of PCV3 among Chinese pig herds, and indicated that the potential effect of PCV3 on the pig industry may be a concern.

Project description:Background Group A rotavirus (RVA) is a common causative agent of acute gastroenteritis in infants and young children worldwide. RVA P genotypes, determined by VP4 sequences, have been confirmed to infect humans and animals. However, their codon usage patterns that are essential to obtain insights into the viral evolution, host adaptability, and genetic characterization remained unclear, especially across animal hosts. Results We performed a comprehensive codon usage analysis of eight host-specific RVA P genotypes, including human RVA (P[4] and P[8]), porcine RVA (P[13] and P[23]), and zoonotic RVA (P[1], P[6], P[7] and P[19]), based on 233 VP4 complete coding sequences. Nucleotide composition, relative synonymous codon usage (RSCU), and effective number of codons (ENC) were calculated. Principal component analysis (PCA) based on RSCU values was used to explore the codon usage patterns of different RVA P genotypes. In addition, mutation pressure and natural selection were identified by using ENC-plot, parity rule 2 plot, and neutrality plot analyses. All VP4 sequences preferred using A/U nucleotides (A: 0.354-0.377, U: 0.267-0.314) than G/C nucleotides across genotypes. Similarly, majority of commonly used synonymous codons were likely to end with A/U nucleotides (A: 9/18-12/18, U: 6/18-9/18). In PCA, human, porcine, and zoonotic genotypes clustered separately in terms of RSCU values, indicating the host-specific codon usage patterns; however, porcine and zoonotic genotypes were partly overlapped. Human genotypes, P[4] and P[8], had stronger codon usage bias, as indicated by more over-represented codons and lower ENC, compared to porcine and zoonotic genotypes. Moreover, natural selection was determined to be a predominant driver in shaping the codon usage bias across the eight P genotypes. In addition, mutation pressure contributed to the codon usage bias of human genotypes. Conclusions Our study identified a strong codon usage bias of human RVA P genotypes attributable to both natural selection and mutation pressure, whereas similar codon usage bias between porcine and zoonotic genotypes predominantly attributable to natural selection. It further suggests possible cross-species transmission. Therefore, it warrants further surveillance of RVA P genotypes for early identification of zoonotic infection. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08730-2.

Project description:Introduction: Group A rotaviruses are major pathogens in causing severe diarrhea in young children and neonates of many different species of animals worldwide and group A rotavirus sequence data are becoming increasingly available over time. Different methods exist that allow for rotavirus genotyping, but machine learning methods have yet to be explored. Usage of machine learning algorithms such as random forest alongside alignment-based methodology may allow for both efficient and accurate classification of circulating rotavirus genotypes through the dual classification system. Methods: Random forest models were trained on positional features obtained from pairwise and multiple sequence alignment and cross-validated using methods of repeated 10-fold cross-validation thrice and leave one- out cross validation. Models were then validated on unseen data from the testing datasets to observe real-world performance. Results: All models were found to perform strongly in classification of VP7 and VP4 genotypes with high overall accuracy and kappa values during model training (0.975-0.992, 0.970-0.989) and during model testing (0.972-0.996, 0.969-0.996), respectively. Models trained on multiple sequence alignment generally had slightly higher overall accuracy and kappa values than models trained on pairwise sequence alignment method. In contrast, pairwise sequence alignment models were found to be generally faster than multiple sequence alignment models in computational speed when models do not need to be retrained. Models that used repeated 10-fold cross-validation thrice were also found to be much faster in model computational speed than models that used leave-one-out cross validation, with no noticeable difference in overall accuracy and kappa values between the cross-validation methods. Discussion: Overall, random forest models showed strong performance in the classification of both group A rotavirus VP7 and VP4 genotypes. Application of these models as classifiers will allow for rapid and accurate classification of the increasing amounts of rotavirus sequence data that are becoming available.

Dataset Information

Prevalence and Genetic Diversity of Group A Rotavirus Genotypes in Moscow (2019-2020).

Publications

Prevalence and Genetic Diversity of Group A Rotavirus Genotypes in Moscow (2019-2020).

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