| Literature DB >> 35610217 |
John-Sebastian Eden1,2, Chisha Sikazwe3,4, Ruopeng Xie5,6, Yi-Mo Deng7,8, Sheena G Sullivan7,9, Alice Michie4, Avram Levy3, Elena Cutmore1,2, Christopher C Blyth3,10,11,12, Philip N Britton2,13, Nigel Crawford14,15,16, Xiaomin Dong7,8, Dominic E Dwyer2,17, Kimberly M Edwards5,6, Bethany A Horsburgh1,2, David Foley3, Karina Kennedy18, Cara Minney-Smith3, David Speers3,10, Rachel L Tulloch1,2, Edward C Holmes2, Vijaykrishna Dhanasekaran19,20, David W Smith21,22, Jen Kok23, Ian G Barr24,25.
Abstract
Human respiratory syncytial virus (RSV) is an important cause of acute respiratory infection with the most severe disease in the young and elderly. Non-pharmaceutical interventions and travel restrictions for controlling COVID-19 have impacted the circulation of most respiratory viruses including RSV globally, particularly in Australia, where during 2020 the normal winter epidemics were notably absent. However, in late 2020, unprecedented widespread RSV outbreaks occurred, beginning in spring, and extending into summer across two widely separated regions of the Australian continent, New South Wales (NSW) and Australian Capital Territory (ACT) in the east, and Western Australia. Through genomic sequencing we reveal a major reduction in RSV genetic diversity following COVID-19 emergence with two genetically distinct RSV-A clades circulating cryptically, likely localised for several months prior to an epidemic surge in cases upon relaxation of COVID-19 control measures. The NSW/ACT clade subsequently spread to the neighbouring state of Victoria and to cause extensive outbreaks and hospitalisations in early 2021. These findings highlight the need for continued surveillance and sequencing of RSV and other respiratory viruses during and after the COVID-19 pandemic, as mitigation measures may disrupt seasonal patterns, causing larger or more severe outbreaks.Entities:
Mesh:
Year: 2022 PMID: 35610217 PMCID: PMC9130497 DOI: 10.1038/s41467-022-30485-3
Source DB: PubMed Journal: Nat Commun ISSN: 2041-1723 Impact factor: 17.694
Fig. 1The epidemiology of RSV detections in three Australian states—New South Wales (NSW), Western Australia (WA), and Victoria (VIC).
Laboratory testing for RSV in 2020 as weekly percent positive (red line, left y-axis) and as total number of tests performed (grey bars, right y-axis). In each panel, the dashed red line represents mean monthly RSV percent positive over the three previous seasons, and corresponding red shading represents minimum and maximum weekly percent positive. Pink-shaded bars across the top of each plot indicate the severity of pandemic restrictions, with darker colours indicative of greater stringency. Blue bars across the top of each plot indicate the periods during which students did not attend school either due to pandemic restrictions or school holiday periods, with darker colours indicative of more stringent school restrictions.
Fig. 2Phylogenetic analysis of global and Australian RSV-A genome sequences.
A RSV-A genome sequences were aligned with NCBI GenBank reference sequences and analysed using a Bayesian molecular clock approach estimated with BEAST (v1.10) focused on recent ON1-like viruses. Australian states—New South Wales (NSW), Australia Capital Territory (ACT), Western Australia (WA) and Victoria (VIC), and South Australia (SA)—and globally-derived sequences are coloured according to the key provided. The light red dotted line marks March 2020 and the beginning of extensive COVID-19-related restrictions. The blue shaded box is expanded in panel (B), which is a focused analysis of NSW/ACT/VIC and WA 2020 lineages. Amino acid mutations inferred by TreeTime are labelled on select branches, and those under significant selection pressure are shown in bold. C Temporal signal in RSV-A genomic dataset determined by linear-regression of root-to-tip distance (y-axis) against sample collection date (x-axis).
Fig. 3Phylogenetic analysis of global and Australian RSV-A glycoprotein sequences.
A RSV-A sequences in this study were aligned with all available RSV-A sequences from NCBI GenBank. The glycoprotein coding region was extracted, and sequences less than 300 nt were removed. B A detailed examination of recently circulating ON1-like viruses showed only two pre-COVID-19 lineages (coloured red) survived into the post-COVID-19 period (blue). These two lineages were associated with outbreaks in NSW/ACT and WA in late 2020, and VIC in early 2021. No sequences sourced globally (yellow) were found to be related to the these lineages, suggesting the sources remain unknown. Australian states—New South Wales (NSW), Australia Capital Territory (ACT), Western Australia (WA) and Victoria (VIC), South Australia (SA) and Queensland (QLD)—and globally-derived sequences are coloured according to the key provided. Diamonds at nodes indicate bootstrap support values >70%. Branches are proportional to the number of nucleotide substitutions per site.
Mean time of most recent common ancestors (tMRCA) for NSW/ACT/VIC 2020 and WA 2020 clades estimated by different methods.
| Method | tMRCA (NSW/ACT/VIC)a | tMRCA (WA)a | Evolution rate (per site per year) |
|---|---|---|---|
| Beast | 2020-01-10 [2019-11-05, 2020-03-16] | 2019-11-23 [2019-08-08, 2020-02-20] | 6.624 × 10−4 |
| Beast-SLACb | 2020-05-03 [2020-03-16, 2020-06-20] | 2020-06-03 [2020-04-01, 2020-07-25] | NSW/ACT/VIC: 9.092 × 10−4 WA: 1.124 × 10−3 |
| Beast-SNAPb | 2020-03-25 [2020-01-31, 2020-05-18] | 2020-05-06 [2020-02-26, 2020-07-03] | NSW/ACT/VIC: 8.070 × 10−4 WA: 1.021 × 10−3 |
| Beast-Contrast-FELb | 2020-05-08 [2020-03-22, 2020-06-25] | 2020-06-01 [2020-03-30, 2020-07-24] | NSW/ACT/VIC: 9.245 × 10−4 WA: 1.117 × 10−3 |
aRanges in brackets show confidence intervals (95% highest probability densities).
btMRCA corrected according to dN/dS ratio.