Genetic characterization of influenza A(H3N2) viruses circulating in coastal Kenya, 2009-2017

Background Influenza viruses evolve rapidly and undergo immune driven selection, especially in the hemagglutinin (HA) protein. We report amino acid changes affecting antigenic epitopes and receptor‐binding sites of A(H3N2) viruses circulating in Kilifi, Kenya, from 2009 to 2017. Methods Next‐generation sequencing (NGS) was used to generate A(H3N2) virus genomic data from influenza‐positive specimens collected from hospital admissions and health facility outpatients presenting with acute respiratory illness to health facilities within the Kilifi Health and Demographic Surveillance System. Full‐length HA sequences were utilized to characterize A(H3N2) virus genetic and antigenic changes. Results From 186 (90 inpatient and 96 outpatient) influenza A virus‐positive specimens processed, 101 A(H3N2) virus whole genomes were obtained. Among viruses identified in inpatient specimens from 2009 to 2015, divergence of circulating A(H3N2) viruses from the vaccine strains A/Perth/16/2009, A/Texas/50/2012, and A/Switzerland/9715293/2013 formed 6 genetic clades (A/Victoria/208/2009‐like, 3B, 3C, 3C.2a, 4, and 7). Among viruses identified in outpatient specimens from 2015 to 2017, divergence of circulating A(H3N2) viruses from vaccine strain A/Hong Kong/4801/2014 formed clade 3C.2a, subclades 3C.2a2 and 3C.2a3, and subgroup 3C.2a1b. Several amino acid substitutions were associated with the continued genetic evolution of A(H3N2) strains in circulation. Conclusions Our results suggest continuing evolution of currently circulating A(H3N2) viruses in Kilifi, coastal Kenya and suggest the need for continuous genetic and antigenic viral surveillance of circulating seasonal influenza viruses with broad geographic representation to facilitate prompt and efficient selection of influenza strains for inclusion in future influenza vaccines

Recent sequence variation in probe binding site affected detection of respiratory syncytial virus group B by real-time RT-PCR

Background Direct immuno-fluorescence test (IFAT) and multiplex real-time RT-PCR have been central to RSV diagnosis in Kilifi, Kenya. Recently, these two methods showed discrepancies with an increasing number of PCR undetectable RSV-B viruses. Objectives Establish if mismatches in the primer and probe binding sites could have reduced real-time RT-PCR sensitivity. Study design Nucleoprotein (N) and glycoprotein (G) genes were sequenced for real-time RT-PCR positive and negative samples. Primer and probe binding regions in N gene were checked for mismatches and phylogenetic analyses done to determine molecular epidemiology of these viruses. New primers and probe were designed and tested on the previously real-time RT-PCR negative samples. Results N gene sequences revealed 3 different mismatches in the probe target site of PCR negative, IFAT positive viruses. The primers target sites had no mismatches. Phylogenetic analysis of N and G genes showed that real-time RT-PCR positive and negative samples fell into distinct clades. Newly designed primers-probe pair improved detection and recovered previous PCR undetectable viruses. Conclusions An emerging RSV-B variant is undetectable by a quite widely used real-time RT-PCR assay due to polymorphisms that influence probe hybridization affecting PCR accuracy

Whole genome analysis of local Kenyan and global sequences unravels the epidemiological and molecular evolutionary dynamics of RSV genotype ON1 strains

The respiratory syncytial virus (RSV) group A variant with the 72-nucleotide duplication in the G gene, genotype ON1, was first detected in Kilifi in 2012 and has almost completely replaced previously circulating genotype GA2 strains. This replacement suggests some fitness advantage of ON1 over the GA2 viruses, and might be accompanied by important genomic substitutions in ON1 viruses. Close observation of such a new virus introduction over time provides an opportunity to better understand the transmission and evolutionary dynamics of the pathogen. We have generated and analyzed 184 RSV-A whole genome sequences (WGS) from Kilifi (Kenya) collected between 2011 and 2016, the first ON1 genomes from Africa and the largest collection globally from a single location. Phylogenetic analysis indicates that RSV-A transmission into this coastal Kenya location is characterized by multiple introductions of viral lineages from diverse origins but with varied success in local transmission. We identify signature amino acid substitutions between ON1 and GA2 viruses within genes encoding the surface proteins (G, F), polymerase (L) and matrix M2-1 proteins, some of which were identified as positively selected, and thereby provide an enhanced picture of RSV-A diversity. Furthermore, five of the eleven RSV open reading frames (ORF) (i.e. G, F, L, N and P), analyzed separately, formed distinct phylogenetic clusters for the two genotypes. This might suggest that coding regions outside of the most frequently studied G ORF play a role in the adaptation of RSV to host populations with the alternative possibility that some of the substitutions are nothing more than genetic hitchhikers. Our analysis provides insight into the epidemiological processes that define RSV spread, highlights the genetic substitutions that characterize emerging strains, and demonstrates the utility of large-scale WGS in molecular epidemiological studies

Evolution of respiratory syncytial virus genotype BA in Kilifi, Kenya, 15 years on

Respiratory syncytial virus (RSV) is recognised as a leading cause of severe acute respiratory disease and deaths among infants and vulnerable adults. Clinical RSV isolates can be divided into several known genotypes. RSV genotype BA, characterised by a 60-nucleotide duplication in the G glycoprotein gene, emerged in 1999 and quickly disseminated globally replacing other RSV group B genotypes. Continual molecular epidemiology is critical to understand the evolutionary processes maintaining the success of the BA viruses. We analysed 735 G gene sequences from samples collected from paediatric patients in Kilifi, Kenya, between 2003 and 2017. The virus population comprised of several genetically distinct variants (n = 56) co-circulating within and between epidemics. In addition, there was consistent seasonal fluctuations in relative genetic diversity. Amino acid changes increasingly accumulated over the surveillance period including two residues (N178S and Q180R) that mapped to monoclonal antibody 2D10 epitopes, as well as addition of putative N-glycosylation sequons. Further, switching and toggling of amino acids within and between epidemics was observed. On a global phylogeny, the BA viruses from different countries form geographically isolated clusters suggesting substantial localized variants. This study offers insights into longitudinal population dynamics of a globally endemic RSV genotype within a discrete location

Promoting SME cooperative aggregations: main criteria and contractual models

Collaboration is considered an effective solution to improve business strategies. However, small and medium enterprises (SMEs) often lack common principles and common forms of contractual coordination. Several policies implemented by the EU have addressed the set-up of a comprehensive SME policy framework, but European institutions seem to have focused more on organisational devices to conduct business activities rather than on contractual forms of coordination. In April 2009, Italy adopted a law in network contract to promote the development of inter-firm cooperation strategies to foster enterprises' innovation and growth. Even if this law represents a novelty in Europe and may offer new challenges and hints, it still presents some lacks in its formulation. The current research aims at presenting the Italian law for network contract and a comparison with other models of SME aggregations adopted in EU countries. A formal model to support the design of an SME network was proposed, by providing both an ontology-based model to help the definition of the contract in a structured way, and a basic workflow to identify the important phases of the network design, i.e. the feasibility study and the negotiatio

Genetic and potential antigenic evolution of influenza A(H1N1)pdm09 viruses circulating in Kenya during 2009-2018 influenza seasons

Influenza viruses undergo rapid evolutionary changes, which requires continuous surveillance to monitor for genetic and potential antigenic changes in circulating viruses that can guide control and prevention decision making. We sequenced and phylogenetically analyzed A(H1N1)pdm09 virus genome sequences obtained from specimens collected from hospitalized patients of all ages with or without pneumonia between 2009 and 2018 from seven sentinel surveillance sites across Kenya. We compared these sequences with recommended vaccine strains during the study period to infer genetic and potential antigenic changes in circulating viruses and associations of clinical outcome. We generated and analyzed a total of 383 A(H1N1)pdm09 virus genome sequences. Phylogenetic analyses of HA protein revealed that multiple genetic groups (clades, subclades, and subgroups) of A(H1N1)pdm09 virus circulated in Kenya over the study period; these evolved away from their vaccine strain, forming clades 7 and 6, subclades 6C, 6B, and 6B.1, and subgroups 6B.1A and 6B.1A1 through acquisition of additional substitutions. Several amino acid substitutions among circulating viruses were associated with continued evolution of the viruses, especially in antigenic epitopes and receptor binding sites (RBS) of circulating viruses. Disease severity declined with an increase in age among children aged < 5 years. Our study highlights the necessity of timely genomic surveillance to monitor the evolutionary changes of influenza viruses. Routine influenza surveillance with broad geographic representation and whole genome sequencing capacity to inform on prioritization of antigenic analysis and the severity of circulating strains are critical to improved selection of influenza strains for inclusion in vaccines

Genomic epidemiology of the rotavirus G2P[4] strains in coastal Kenya pre- and post-rotavirus vaccine introduction, 2012 – 2018

The introduction of rotavirus vaccines into the national immunization programme in many countries has led to a decline of childhood diarrhoea disease burden. Coincidentally, the incidence of some rotavirus group A (RVA) genotypes, has increased, which may result from non-vaccine-type replacement. Here we investigate the evolutionary genomics of rotavirus G2P[4] which has shown an increase in countries that introduced the monovalent Rotarix® vaccine. We examined 63 RVA G2P[4] strains sampled from children (aged below 13 years) admitted to Kilifi County Hospital, Coastal Kenya, pre- (2012 to June 2014) and post-(July 2014-2018) rotavirus vaccine introduction. All the 63 genome sequences showed a typical DS-1 like genome constellation G2-P[4]-I2-R2-C2-M2-A2-N2-T2-E2-H2. Pre-vaccine G2 sequences predominantly classified as sub-lineage IVa-3 and co-circulated with low numbers of sub-lineage IVa-1 strains, whereas post-vaccine G2 sequences mainly classified into sub-lineage IVa-3. In addition, in the pre-vaccine period, P[4] sub-lineage IVa strains co-circulated with low numbers of P[4] lineage II strains, but P[4] sub-lineage IVa strains predominated in the post-vaccine period. On the global phylogeny, the Kenyan pre- and post-vaccine G2P[4] strains clustered separately, suggesting that different virus populations circulated in the two periods. However, the strains from both periods exhibited conserved amino acid changes in the known antigenic epitopes, suggesting that replacement of the predominant G2P[4] cluster was unlikely a result of immune escape. Our findings demonstrate that the pre- and post-vaccine G2P[4] strains circulating in Kilifi, coastal Kenya, differed genetically, but likely were antigenically similar. This information informs the discussion on the consequences of rotavirus vaccination on rotavirus diversity

Optimization of the SARS-CoV-2 ARTIC network V4 primers and whole genome sequencing protocol

Introduction: The ARTIC Network's primer set and amplicon-based protocol is one of the most widely used SARS-CoV-2 sequencing protocol. An update to the V3 primer set was released on 18th June 2021 to address amplicon drop-off observed among the Delta variant of concern. Here, we report on an in-house optimization of a modified version of the ARTIC Network V4 protocol that improves SARS-CoV-2 genome recovery in instances where the original V4 pooling strategy was characterized by amplicon drop-offs. Methods: We utilized a matched set of 43 clinical samples and serially diluted positive controls that were amplified by ARTIC V3, V4 and optimized V4 primers and sequenced using GridION from the Oxford Nanopore Technologies'. Results: We observed a 0.5% to 46% increase in genome recovery in 67% of the samples when using the original V4 pooling strategy compared to the V3 primers. Amplicon drop-offs at primer positions 23 and 90 were observed for all variants and positive controls. When using the optimized protocol, we observed a 60% improvement in genome recovery across all samples and an increase in the average depth in amplicon 23 and 90. Consequently, ≥95% of the genome was recovered in 72% (n = 31) of the samples. However, only 60–70% of the genomes could be recovered in samples that had 0.05) correlation between Ct value and genome recovery. Conclusion: Utilizing the ARTIC V4 primers, while increasing the primer concentrations for amplicons with drop-offs or low average read-depth, greatly improves genome recovery of Alpha, Beta, Delta, Eta and non-VOC/non-VOI SARS-CoV-2 variants

Global disparities in SARS-CoV-2 genomic surveillance

Genomic sequencing is essential to track the evolution and spread of SARS-CoV-2, optimize molecular tests, treatments, vaccines, and guide public health responses. To investigate the global SARS-CoV-2 genomic surveillance, we used sequences shared via GISAID to estimate the impact of sequencing intensity and turnaround times on variant detection in 189 countries. In the first two years of the pandemic, 78% of high-income countries sequenced >0.5% of their COVID-19 cases, while 42% of low- and middle-income countries reached that mark. Around 25% of the genomes from high income countries were submitted within 21 days, a pattern observed in 5% of the genomes from low- and middle-income countries. We found that sequencing around 0.5% of the cases, with a turnaround time <21 days, could provide a benchmark for SARS-CoV-2 genomic surveillance. Socioeconomic inequalities undermine the global pandemic preparedness, and efforts must be made to support low- and middle-income countries improve their local sequencing capacity