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Comparative Analysis of Spatial-temporal Patterns of Human Metapneumovirus and Respiratory Syncytial Virus in Africa Using Genetic Data, 2011-2014
John W Oketch
KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast
Corresponding Author
ORCiD: https://orcid.org/0000-0002-8020-0787
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Human metapneumovirus (HMPV) and respiratory syncytial virus (RSV) are leading causes of viral severe acute respiratory illnesses in childhood. Both the two viruses belong to the Pneumoviridae family and show overlapping clinical, epidemiological and transmission features. However, it is unknown whether these two viruses have similar geographic spread patterns which may provide insight into designing and evaluating their epidemic control measures.
Methods: We conducted comparative phylogenetic and phylogeographic analyses to explore the spatial-temporal patterns of HMPV and RSV across Africa using 232 HMPV and 842 RSV attachment (G) glycoprotein gene sequences obtained from 5 countries (The Gambia, Zambia, Mali, South Africa, and Kenya) between August 2011 and January 2014.
Results: Phylogeographic analyses found frequently similar patterns of spread of RSV and HMPV. Viral sequences commonly clustered by region, i.e., West Africa (Mali, Gambia), East Africa (Kenya) and Southern Africa (Zambia, South Africa), and similar genotype dominance patterns were observed between neighbouring countries. Both HMPV and RSV country epidemics were characterized by co-circulation of multiple genotypes. Sequences from different African sub-regions (East, West and Southern Africa) fell into separate clusters interspersed with sequences from other countries globally.
Conclusion: The spatial clustering patterns of viral sequences and genotype dominance patterns observed in our analysis suggests strong regional links and predominant local transmission. The geographical clustering further suggests independent introduction of HMPV and RSV variants in Africa from the global pool, and local regional diversification.
Keywords
Human metapneumovirus, respiratory syncytial virus, Phylogeographic analysis, spatial-temporal
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This is a list of supplementary files associated with this preprint. Click to download.
- Additionalfile1.xls
Additional file 1: The GenBank accession numbers of HMPV and RSV attachment (G) glycoprotein gene sequences generated in this study and the contemporaneous sequences retrieved from GenBank. Sheet1: RSV accession numbers grouped by African country of sampling and global sequences. Sheet2: HMPV accession numbers grouped by African country and global sequences.
- Additionalfile2.pdf
Additional file 2: ML phylogenies of G gene sequences collected from Kenya, Mali, Gambia, South Africa and Zambia. Sequences were subtyped using subgroup reference sequences retrieved from GenBank. Panel a: HMPV G gene sequences constructed using 231G gene sequences. Reference sequences are coloured in red. The numbers next to branches indicate the bootstrap values. Subgroups were confirmed if sequences clustered with the reference sequences within a major branch with > 70% bootstrap support. Panel b: RSV G ML phylogeny constructed using 627 unique gene sequences.
- Additionalfile3.pdf
Additional file 3: ML phylogenies of subgroup B1 sequences showing within country sequence diversity for Kenya, Gambia, Mali and South Africa sequences. Clustering patterns were determined by within country sampling location and or case/control status. For Gambia, only case/control clustering patterns were determined.
- Additionalfile4.png
Additional file 4: Panel A; Temporal scaled maximum clade credibility (MCC) tree constructed using HMPV B2 G gene sequences obtained from Africa and GenBank collected between 2000 to 2018. Branches are coloured according to the most probable location as inferred using symmetric discrete phylogeographic diffusion model. Geographic locations considered are shown in the figure key. Sequences from Kenya, Mali, Gambia, South Africa and Zambia collected beyond the study period are indicated with a suffix GB. Posterior probabilities are shown next to nodes. Clades containing African sequences falling in monophyletic clades are highlighted in grey boxes. For each clade, the mean estimated time of the most recent common ancestor (tMRCA) and respective 95% Bayesian credible intervals are shown in a black box alongside the most probable location leading to each clade. Panel B; MCC tree of B2 sequences collected from Africa.
- Additionalfile5.png
Additional file 5: Panel A; Temporal scaled maximum clade credibility (MCC) tree constructed using HMPV A2c G gene sequences obtained from Africa and GenBank collected between 2000 to 2018. Branches are coloured according to the most probable location as inferred using symmetric discrete phylogeographic diffusion model. Geographic locations considered are shown in the figure key. Sequences from Kenya, Mali, Gambia, South Africa and Zambia collected beyond the study period are indicated with a suffix GB. Posterior probabilities are shown next to nodes. Clades containing African sequences falling in monophyletic clades are highlighted in grey boxes. For each clade, the mean estimated time of the most recent common ancestor (tMRCA) and respective 95% Bayesian credible intervals are shown in a black box alongside the most probable location leading to each clade. Panel B; MCC tree of A2c sequences collected from Africa.
- Additionalfile6.png
Additional file 6: Panel A; Temporal scaled maximum clade credibility (MCC) tree constructed using HMPV A2a G gene sequences obtained from Africa and GenBank collected between 2000 to 2018. Branches are coloured according to the most probable location as inferred using symmetric discrete phylogeographic diffusion model. Geographic locations considered are shown in the figure key. Posterior probabilities are shown next to nodes. Clades containing African sequences falling in monophyletic clades are highlighted in blue and red. For each clade, the mean estimated time of the most recent common ancestor (tMRCA) and respective 95% Bayesian credible intervals are shown in a black box alongside the most probable location leading to each clade. Panel B; MCC tree of B2 sequences collected from Africa.
- Additionalfile7.png
Additional file 7: Statistically supported state transitions indicating viral migration events between locations globally. Bayes factor >100 and Posterior probability ≥95% was considered significant.
- Additionalfile8.pdf
Additional file 8: ML phylogenies of RSV genotype BA sequences showing within country sequence diversity for Mali and South Africa sequences. Clustering patterns were determined by within country sampling location and or case/control status.
- Additionalfile9.png
Additional file 9: Statistically supported state transitions indicating viral migration events between African countries. Bayes factor >100 and Posterior probability ≥95% was considered significant.
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This preprint is under consideration at Virology Journal. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Comparative Analysis of Spatial-temporal Patterns of Human Metapneumovirus and Respiratory Syncytial Virus in Africa Using Genetic Data, 2011-2014
John W Oketch
KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast
Corresponding Author
ORCiD: https://orcid.org/0000-0002-8020-0787
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 29 Dec, 2020
No community comments so far
Review #1 received
Received 04 Jan, 2021
Review #2 received
Received 03 Jan, 2021
Reviewer #2 agreed
On 21 Dec, 2020
Reviewers invited
Invitations sent on 20 Dec, 2020
Reviewer #1 agreed
On 20 Dec, 2020
Editor assigned
On 19 Dec, 2020
Submission checks complete
On 19 Dec, 2020
Editor invited
On 19 Dec, 2020
First submitted
On 16 Dec, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Virology
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Human metapneumovirus (HMPV) and respiratory syncytial virus (RSV) are leading causes of viral severe acute respiratory illnesses in childhood. Both the two viruses belong to the Pneumoviridae family and show overlapping clinical, epidemiological and transmission features. However, it is unknown whether these two viruses have similar geographic spread patterns which may provide insight into designing and evaluating their epidemic control measures.
Methods: We conducted comparative phylogenetic and phylogeographic analyses to explore the spatial-temporal patterns of HMPV and RSV across Africa using 232 HMPV and 842 RSV attachment (G) glycoprotein gene sequences obtained from 5 countries (The Gambia, Zambia, Mali, South Africa, and Kenya) between August 2011 and January 2014.
Results: Phylogeographic analyses found frequently similar patterns of spread of RSV and HMPV. Viral sequences commonly clustered by region, i.e., West Africa (Mali, Gambia), East Africa (Kenya) and Southern Africa (Zambia, South Africa), and similar genotype dominance patterns were observed between neighbouring countries. Both HMPV and RSV country epidemics were characterized by co-circulation of multiple genotypes. Sequences from different African sub-regions (East, West and Southern Africa) fell into separate clusters interspersed with sequences from other countries globally.
Conclusion: The spatial clustering patterns of viral sequences and genotype dominance patterns observed in our analysis suggests strong regional links and predominant local transmission. The geographical clustering further suggests independent introduction of HMPV and RSV variants in Africa from the global pool, and local regional diversification.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6