Whole genome sequencing of two human rhinovirus A types (A101 and A15) detected in Kenya, 2016-2018

Abstract

Background: Virus genome sequencing is increasingly utilized in epidemiological surveillance. Genomic data allows comprehensive evaluation of underlying viral diversity and epidemiology to inform control. For human rhinovirus (HRV), genomic amplification and sequencing is challenging due to numerous types, high genetic diversity and inadequate reference sequences. Methods: We developed a tiled amplicon type-specific protocol for genome amplification and sequencing on the Illumina MiSeq platform of two HRV types, A15 and A101. We then assessed added value in analyzing whole genomes relative to the VP4/2 region only in the investigation of HRV molecular epidemiology within the community in Kilifi, coastal Kenya. Results: We processed 73 samples collected between 2016-2018, and 48 yielded at least 70% HRV genome coverage. These included all A101 samples (n=10) and 38 (60.3%) A15 samples. Phylogenetic analysis revealed that the Kilifi A101 sequences interspersed with global A101 genomes available in GenBank collected between 1999-2016. On the other hand, our A15 sequences formed a monophyletic group separate from the global genomes collected in 2008 and 2019. Improved phylogenetic resolution was observed with the genome phylogenies compared to the VP4/2 phylogenies. Conclusions: We present a type-specific full genome sequencing approach for obtaining HRV genomic data and characterizing infections.

Current Methods for Recombination Detection in Bacteria

“…In RDP5, run time speed has been increased up to five times and the number of analyzed bacterial genomes up to 120 times [ 67 ]. Still, it cannot handle large batches of bacterial genomes, and therefore, it has been used to trace recombination predominantly in viral genomes, for example, in porcine reproductive and respiratory syndrome virus (PRRSV) [ 69 ], SARS-CoV-2 [ 70 ], human rhinovirus [ 71 ], and feline parvovirus [ 72 ]. However, it should be noted that the algorithm inherits limitations of phylogenetic algorithms, the most evident of which is its inability to reveal distant events [ 26 ].…”

Rhinovirus dynamics across different social structures

“…First, discrepancies in the individual study designs and differences in study periods across the different social structures made comparisons difficult. Second, the VP4/2 region is relatively short, which may result in a high statistical uncertainty when inferring transmission, as previously demonstrated 51 . Third, our approach to investigating global transmission dynamics of frequent RV types in Kenya was centered on publicly available sequence data.…”

Spatio-temporal distribution of rhinovirus types in Kenya: A retrospective analysis, 2014

“…Although our analyses were limited to the VP4/VP2 genomic region, we highlight the use of sequence data to trace the introduction and spread of rhinovirus at the countrywide level and show the benefit of systematic, continuous, and geographically representative surveillance to detect and monitor the occurrence of types at a larger scale. Whole genome sequencing could provide more insight into virus diversity and transmission 47 , and we recommend that future studies should combine genomic data with epidemiological and anthropological data (e.g., host migration, immunity profiles, population densities, and social contact patterns) to further elucidate patterns of RV infections.…”