Dataset Information

Human rotavirus VP4 and VP7 genetic diversity and detection of GII norovirus in Ibadan as Nigeria introduces rotavirus vaccine.

ABSTRACT:

Objective

This cross-sectional study investigated the circulating strains of rotavirus and screened for noravirus in Ibadan, Nigeria as the country introduces the rotavirus vaccine into its national immunization program.

Methods

Sixty-five stool samples were collected from children younger than 5 years with clinically diagnosed diarrhea and screened for the presence of rotavirus and norovirus using RT-PCR. Rotavirus-positive samples were further analyzed to determine the G and P genotypes using semi-nested multiplex PCR.

Results

The rates of rotavirus and norovirus positivity were 30.8% and 10.8%, respectively, whereas the rate of rotavirus and norovirus mixed infection was 4.6%. G1 was the predominant VP7 genotype, followed by G2, G9, and G1G2G9, whereas the predominant VP4 genotype was P[4], followed by P[6], P[8], and P[9]. The mixed P types P[4]P[8] and P[4]P[6] were also detected. G1P[4] was the most common VP4 and VP7 combination, followed by G2P[4], G1[P6], G1P[8], G2P[6], G2P[9], G9P[6], G2G9P[4], G2P[4]P[6], G1P[4]P[8], G2G9P[8], G1G2G9P[8], and G1[non-typable] P[non-typable], which were detected in at least 5% of the samples. Four samples had a combination of non-typable G and P types.

Conclusions

It is essential to monitor the circulation of virus strains prior to and during the implementation of the immunization program.

SUBMITTER: Maina MM

PROVIDER: S-EPMC9511342 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Publications

Human rotavirus VP4 and VP7 genetic diversity and detection of GII norovirus in Ibadan as Nigeria introduces rotavirus vaccine.

Maina Meshach Maunta MM Faneye Adedayo Omotayo AO Motayo Babatunde Olanrewaju BO Nseabasi-Maina Ntung N Adeniji Adekunle Johnson AJ

The Journal of international medical research 20220901 9

<h4>Objective</h4>This cross-sectional study investigated the circulating strains of rotavirus and screened for noravirus in Ibadan, Nigeria as the country introduces the rotavirus vaccine into its national immunization program.<h4>Methods</h4>Sixty-five stool samples were collected from children younger than 5 years with clinically diagnosed diarrhea and screened for the presence of rotavirus and norovirus using RT-PCR. Rotavirus-positive samples were further analyzed to determine the G and P g ...[more]

PMID: 36138570

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Project description:Species A rotaviruses (RVs) are a leading cause of severe acute gastroenteritis in infants and children younger than 5 years. Currently available RV vaccines were adapted from wild-type RV strains by serial passage of cultured cells or by reassortment between human and animal RV strains. These traditional methods require large-scale screening and genotyping to obtain vaccine candidates. Reverse genetics is a tractable, rapid, and reproducible approach to generating recombinant RV vaccine candidates carrying any VP4 and VP7 genes that provide selected antigenicity. Here, we developed a vaccine platform by generating recombinant RVs carrying VP4 (P[4] and P[8]), VP7 (G1, G2, G3, G8, and G9), and/or VP6 genes cloned from human RV clinical samples using the simian RV SA11 strain (G3P[2]) as a backbone. Neutralization assays using monoclonal antibodies and murine antisera revealed that recombinant VP4 and VP7 monoreassortant viruses exhibited altered antigenicity. However, replication of VP4 monoreassortant viruses was severely impaired. Generation of recombinant RVs harboring a chimeric VP4 protein for SA11 and human RV gene components revealed that the VP8* fragment was responsible for efficient infectivity of recombinant RVs. Although this system must be improved because the yield of vaccine viruses directly affects vaccine manufacturing costs, reverse genetics requires less time than traditional methods and enables rapid production of safe and effective vaccine candidates.IMPORTANCE Although vaccines have reduced global RV-associated hospitalization and mortality over the past decade, the multisegmented genome of RVs allows reassortment of VP4 and VP7 genes from different RV species and strains. The evolutionary dynamics of novel RV genotypes and their constellations have led to great genomic and antigenic diversity. The reverse genetics system is a powerful tool for manipulating RV genes, thereby controlling viral antigenicity, growth capacity, and pathogenicity. Here, we generated recombinant simian RVs (strain SA11) carrying heterologous VP4 and VP7 genes cloned from clinical isolates and showed that VP4- or VP7-substituted chimeric viruses can be used for antigenic characterization of RV outer capsid proteins and as improved seed viruses for vaccine production.

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.

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Dataset Information

Human rotavirus VP4 and VP7 genetic diversity and detection of GII norovirus in Ibadan as Nigeria introduces rotavirus vaccine.

Objective

Methods

Results

Conclusions

Publications

Human rotavirus VP4 and VP7 genetic diversity and detection of GII norovirus in Ibadan as Nigeria introduces rotavirus vaccine.

Similar Datasets

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