Microevolution and phylogenomic characterization of Respiratory Syncytial Virus Type A: An outlook of 2022-2023 outbreak

Microevolution and phylogenomic characterization of Respiratory Syncytial Virus Type A: An outlook of 2022-2023 outbreak | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Microevolution and phylogenomic characterization of Respiratory Syncytial Virus Type A: An outlook of 2022-2023 outbreak Ashfaq Ahmad, Sidra Majaz, Aamir Saeed, Shumaila Noureen, Hamid Ur Rahman, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3961604/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract A communal respiratory syncytial virus (RSV) causes mild to severe illness, predominantly in older adults, or people with certain chronic medical conditions, and in children. Symptoms may include runny nose, cough, fever, and difficulty breathing. In most cases, the infection is mild and resolves on its own, but in some cases, it can lead to more serious illness such as bronchiolitis or pneumonia. The RSV genome codes for ten proteins, NS1, NS2, N, P, M, SH, G, F, M2 and L. We aimed to identify the RSV geographical distribution and transmission pattern using site parsimonious frequencies, and investigate hotspot regions across the complete RSV genomes. These results indicated that RSV strains circulating in South and North America are not mixed to the European samples, however, genomes reported from Australia are the direct decedents of European samples. Samples reported from the United Kingdom were found diverse. Further, this report provides a comprehensive mutational analysis of all the individual RSV genes and in particular the 32 hotspot substituting regions circulating across the globe in RSV type A samples. This is the first comprehensive analysis of RSV type A that features mutational frequencies across the whole genome providing more clues for epidemiological control and drug development. Respiratory syncytial virus Transmission network Mutation frequencies Hotspot identification Phylodynamics Figures Figure 1 Figure 2 Figure 3 Introduction Viruses have become a new threat to mankind and thus drawn more attention due to their potential to cause large scale pandemic as we learned the lesson from COVID-19 [ 1 ]. Respiratory syncytial virus (RSV), also known as human respiratory syncytial virus (hRSV) contributes to the infection of respiratory tract [ 2 ]. Initially, RSV was isolated from Chimpanzee in 1956 and was also simultaneously recovered from infants with severe lower tract respiratory disease [ 3 ]. In clinical manifestations, RSV is linked to mild upper respiratory tract illness (URTI) or otitis media to severe and potentially life-threatening lower respiratory tract involvement (LRTI). The most prevalent form of LRTI in RSV-infected newborns is bronchiolitis, however there are reports indicating pneumonia and croup. Approximately, in infants and young children ∼15–50% of the lower airways were found affected in primary RSV infection that results in hospitalization and higher mortality [ 4 , 5 ]. Apart from supportive care like fluid intake and rest, so far there is no specific treatment for RSV infection [ 6 ]. RSV is a non-segmented negative-sense single-stranded enveloped RNA virus that belongs to the family of Paramyxoviridae, genus Pneumovirus, and subfamily Pneumovirinae. The complete genome of RSV encodes ten proteins, M, M2, three envelope proteins, the fusion (F) glycoprotein, the G glycoprotein, and the small hydrophobic (SH) protein. Besides, five other structural and non-structural proteins are coded by the RSV genome, i.e., the large (L) protein, phosphoprotein (P), nucleocapsid (N), and non-structural proteins 1 and 2 (NS1 and NS2). Among them, protein G and F are important in host cell attachment, fusion and cellular entry [ 5 , 7 – 9 ]. The RSV has been classified into two subtypes A and B which further includes strains like GA1 - GA7, SAA1, NA1 - NA4 and ON1 (RSV-A), and GB1 - GB4, SAB1 - SAB4, URU1 - URU2, BA1 - BA10, BA - C and THB (RSV-B) [ 10 , 11 ]. There are few reports discussing mutations in individual genes like G, however we did not find any extensive analysis for RSV genomes. Here we are reporting for the first time all the mutational frequencies, hotspot regions and transmission of RSV subtype A. These analyses highlight a wider view of RSV transmission across different geological zones that could aid in predicting the oncoming pandemic and vaccine development. Besides transmission, this report provides all the observed mutations in genome coding regions and particularly the hotspot nucleotide sites prone to mutations in individual genes of RSV. Methodology All the sequences used in these analyses were collected from the NCBI Virus database [ 12 ], where we selected taxonomic identification or taxid 208893, and spotted 11956 nucleotide sequences. Specific filters were applied for genome completeness, thus the final dataset we found contained 871 sequences. The whole dataset was exported to MAFFT for whole genome alignment [ 13 ]. Next, the aligned dataset was fed to the viral genome evolutionary analysis system (VENAS) for further analyses [ 14 ]. Calculation for effective parsimony-informative site (ePIS) and network construction To calculate ePIS, we followed a rule that the site will be considered parsimony-informative if it contains a minimum of two types of nucleotides in the aligned data, and at least two sites of them should occur with a minimum nucleotide frequency of two. Besides, the ePIS was considered effective only in the case that the site must contain unambiguous bases ≥ 80% of the total genomes. Keeping the above rules, 474 genomes were found satisfactory, and thus all the remaining analyses were carried out on the dataset containing 474 genomes. The derived ePIS results were used to classify all the genomes in haplotypes, and for this reason sequences containing similar ePIS were grouped onto the similar nodes and vice versa. Visualization, graph rendering and community detections were performed by Gephi. Mutational Analysis Mutational analyses for individual genes were performed by NGS analysis package BioAider [ 15 ]. To retrieve codon information, aligned sets for individual genes were extracted from the aligned dataset used for VENAS. All the gaps (InDel operations) were removed and aligned them again using the codon alignment tool. The complete reports for individual genes substitutions can be found in table S1 . To detect hotspot regions, only those non-synonymous substitutions were considered which showed changes in amino acid properties and more than 200 samples responded. The axillary art work was drawn by illustrator for the visualization of biological sequences (IBS) and Paint.net [ 16 ]. Results We retrieved the complete nucleotide sequence dataset for RSV type A (taxid. 1439707) from the NCBI Virus database. By December 2022, it contained 1166 nucleotide records, including 871 complete genomes. After initial filtration and name tagging that includes, genome ID, reported year and country, we applied viral genome evolutionary analysis system (VENAS) [ 14 ] and analyzed the evolutionary relationship between different genomes or RSV strains. Among them the earlier reported genome U39662.1 in 1997 was considered as a reference. Based on the effective parsimony informative sites (ePIS), and removal of redundant genome sequences, VENAS picked 474 genomes for further analyses. The final genome dataset contains sequences from the USA (2014, 2017, 2019, and 2021), Brazil (2021), Kenya (2021), Philippines (2017), Jordan (2018), Thailand (2019), Netherland (2021), Australia (2020, and 2022), China (2018), UK (2021), Spain (2021), Germany (2020), and four Unknown sequences (2022). RSV transmission distribution on the country scale In order to trace the transmission routes, and contribution, we mapped 474 RSV genomes on the viral evolution network. Our data indicated individual clusters such as cluster of the USA 2014 sequences, connected to cluster of the USA 2017, which further connected the Brazilian cluster 2021, whereas sequences from Jordan 2018 and Philippines 2017 were also observed. Apparently, we found that samples of North and South America were cluster separated from the European samples. However, genomes reported from the USA 2019 were found mixed with genomes reported from Europe (Fig. 1 A). To understand the transmission pattern, we used a network modularity function and clustered the whole network beyond their country or year-wise taglines. We retrieved 12 clades (clade A to clade L). Interestingly, our data predicted a unique pattern, for instance the terminal clade A, contained purely genomes reported from the USA in the year 2014, which connected clade B retaining genomes reported from the USA in the year 2014 and 2017. Further, clade C, a direct descendent of clade B contains all the genomes reported in 2017, except one sequence from the USA 2021. Apart from few genomes reported from the USA 2017, Philippines 2017 and Jordan 2018, clade D contain > 95% of the genomes reported from Brazil 2021. To our interest the smaller clade E, contains representation of almost all the previous clades and connects the bigger node clade F. All the previous clades did not show a single genome reported from the Europe therefore, for better understanding, we call clade F, a European clade, as it is the first with European representation that also gave birth to diverse nodes reported from European countries. The European node (clade F), is tetra-furcated into clade G, H, I and L. Among them, clade H contained samples of Nederland, Spain and the United Kingdom reported in 2021 while clade G was found enriched with all the sequences reported from Nederland 2021. Likewise, clade L is formed from the genomes reported in the United Kingdom 2021, the USA 2019, and two genomes from Spain 2021. Interestingly, clade L emerged from the European cluster through genomes reported from Philippines 2017 and the USA 2019. Finally, Clade I that contains genomes from Spain, Nederland and the United Kingdom 2021 which is bifurcated to clade J and K, where clade J contains samples from the United Kingdom 2021 that leads to Australia 2022 and the clade K only contains all the genomes reported from Australia reported in 2022. All the samples are mapped with country, year and transmission wise in (Fig. 1BC). Collectively, these analyses indicate the global prevalence and the presence of different RSV type A strains. For instance, genomes reported from Australia in 2022 were gathered in two different clusters emerging from the European genomes, suggesting the presence of two different strains. However, genomes reported from Australia in 2020, are lying distantly for those reported in 2022. Likewise, genomes from the UK reported in 2021, were found almost everywhere with European genomes, depicting the possibility of numerous RSV strains. Genomes from Spain and the Netherlands were also found in 2 and 3 different nodes, highlighting the circulation of more than one strain in that country. Mutation and substitution frequencies of synonymous and non-synonymous sites in RSV genomes According to the NCBI records, RSV contains ten to eleven protein coding genes, i.e., non-structural protein 1 and 2 (NS1 and NS2), nucleoprotein (N), phosphoprotein (P), matrix 1 protein (M), small hydrophobic protein (SH), attachment protein (G), fusion protein (F), matrix 2 protein (M2), and polymerase (L). We calculated substitution observed in RSV genomes for all coding sequences (CDS) of all ten genes, particularly synonymous and non-synonymous substitutions. All the substitutions were accessed and calculated against the reference strain U39662.1. A total of 6257 (45%) sites were observed in substitutions, and among them 2099 (15.1%), 3027 (21.7%), 611 (4.3%), and 473 (3.4%) were synonymous, non-synonymous, both and terminations, respectively. Among the non-synonymous substitutions, 1442 (10%) sites were found to have changes in amino acid properties. The highest termination substitutions were found in L followed by N and G proteins (Table. 1). Table 1 Statistics of all types substitutions observed in individual genes of RSV Gene Length (CDS) Proportion of Mutation sites S(p)/N(p)/S-N(p)/Termination(p) NS1 420 105(25.0%) 79(17.3%)/29(6.9%)/3(0.7%)/0 NS2 503 110(21.8) 75(14.9%)/30(5.9%)/5(0.9%)/0 N 1176 554(47.1%) 200(17.0%)/253(21.5%)/67(5.6%)/34(2.8%) P 726 214(29.4%) 138(19.0%)/67(9.2%)/9(1.2%)/0 M 771 177(22.9%) 138(17.8%)/33(4.2%)/6(0.7%)/0 SH 195 63(32.3%) 33(16.9%)/25(12.8%)/4(2.0%)/1(0.5%) G 897 496(55.2%) 162(18.0%)/298(33.2%)/28(3.1%)/8(0.8%) F 1725 468(27.1%) 349(20.2%)/106(6.1%)/13(0.7%)/0 M2 585 150(25.6%) 94(16.0%)/47(8.0%)/8(1.3%)/1(0.1%) L 6498 3920(60.32%) 831(12.7%)/2139(32.9%)/468(7.2)/432(6.6%) Complete 13892 6257(45.0%) 2099(15.1%)/3027(21.7%)/611(4.3%)/476(3.4%) In protein L and G, we also observed higher and similar non-synonymous mutation frequency compared to all other genes of RSV. However, F and P proteins have relatively shown a higher number of synonymous substitutions than non-synonymous. Complete details for substitutions and substitution type for all individual genes can be accessed in form (Table S1 ). To evaluate the overall substitution frequency of the mutated sites, present in all ten CDSs, we alienated the substitution frequency into seven different groups (G1 to G7), and depicted the frequency distribution of 5126 substituted sites (3027 non-synonymous and 2097 synonymous) of the 474 sequenced genomes. Group number on the X-axis indicates the number of strains participating in a substitution event at a particular site, whereas the Y-axis shows the number of substitutions in a respective CDS (Fig. 2 ). Our results indicated that apart from the initial groups, where non-synonymous mutations were found relatively higher than the distribution of synonymous mutations. Comparing all the CDSs, the CDS of G protein showed the highest number of non-synonymous mutations where 55 mutations were found in G4 - G7, meaning the participation of 200 samples. We have also observed that CDSs of NS1, NS2, SH, and M proteins offered relatively lower sites for non-synonymous mutations in the majority of the sequenced RSV strains. The distribution of substitution frequency of each codon in each gene can be found in the supplementary Table. Overall, these analyses provide complete mutational information of all ten RSV’s CDSs. Such key features can also be used to assess the evolutionary pressure on selected sites or response to therapeutic agents. Substitution hot-spots in RSV type A genomes Next, we were interested to identify the hot-spot substitution sites in RSV CDSs. Similar to the analysis [ 15 ] for SARS-CoV-2, we defined a criterion for hotspot regions. A site with a substitution frequency over 200 will be considered a hot-spot site, or a site that offered substitution to more than 200 RSV strains (42% in our case) will be considered a potential substitution hot-spot. Second, the respective site must allow non-synonymous substitution and the observed amino acid should record a change in amino acid properties. A total of 367 substitution sites were found with > 200 substitution frequency where 290, and 77 were synonymous and non-synonymous respectively. Among 77 non-synonymous substitution sites, 32 were those affecting amino acid properties (either changing polarity or charge difference) were considered hot-spot substitution sites. These 32 hot-spots were found distributed across F protein (4), G protein (13), L protein (10), N1, N2, P, N, and M2 (1 each) (Fig. 3 ). Two hot-spots that resulted in CAA to TTA (Q142L) in G protein and ATA to ACG and ACA (I184T) in M2 protein offered double substitutions. Discussion Respiratory syncytial virus (RSV) is a communal respiratory virus that can cause mild to severe illness, predominantly in young children, elderly adults, and people with certain chronic medical conditions. In some cases, it can lead to more serious illness such as bronchiolitis or pneumonia. Here, we detected a probable transmission pattern that in turn may also explain the classification of different strains circulating worldwide. Reference to the hotspot substitutions, we identified 32 hotspots positions, where 13 and 4 are detected only the G and F protein. Both G and F proteins are considered important because both can induce neutralizing antibodies, and are heavily glycosylated, which has been shown to affect with antibody recognition [ 17 – 19 ]. Structurally, the G protein comprises three domains; a cytoplasmic domain (1–37 amino acids), a transmembrane domain (38–66 amino acids), and an ectodomain region (67–312) [ 20 , 21 ]. Interestingly, all the hotspot positions we identified belong to the ectodomain of the G protein. There are individual reports in G, F, and L proteins [ 22 – 27 ] and we believe that this report will assist researchers to directly pick the hotspot regions for biochemical testing. Conclusion This report provides an idea to probe the presence of any viral species and classify them into different strains. Such approaches can be further utilized towards personalized medication therapy particularly in children to cope pandemic. Declarations Data Availability All data generated or analysed during this study are included in this published article and its supplementary information files a. Ethics approval and consent to participate Not Applicable b. Consent for publication Not Applicable c. Availability of data and materials Yes d. Competing interests All the authors have read the manuscript and are aware of the submission to Nature Communication. Further, all the authors have declared no conflicting of interest of any kind. e. Funding There is no specific grant for the project, but one of the corresponding author obtained grant during the project; Nazarbayev University Faculty-Development Competitive Research Grants Program, with reference ID 32729571, ID 15798117 (Funder Project References: 11022021FD2920 and 110119FD4531) to Yingqiu Xie; AUA-UAEU grant (2019; 12R118) to Amr Amin and Yingqiu Xie. The funder had no function in research design, data collection/analysis, preparation of the manuscript or decision to publish. f. Authors' contributions Idea conceived by AA and SN and refined by YX. Experiments performed and data analysis by SM, AA, AS, HR. Manuscript write-up was performed by SM, AA, AAm and AS. Artwork was generated by AA, AS, SM and HR. Critical reading and directions were given by SN, AAm, FN, and YX. Supervised by AA and YX. References Arvin AM, et al. A perspective on potential antibody-dependent enhancement of SARS-CoV-2. Nature. 2020;584(7821):353–63. Bohmwald K, et al. 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McLellan JS, Ray WC, Peeples ME. Structure and function of respiratory syncytial virus surface glycoproteins. Curr Top Microbiol Immunol. 2013;372:83–104. Garcia-Barreno B, Delgado T, Melero JA. Oligo(A) sequences of human respiratory syncytial virus G protein gene: assessment of their genetic stability in frameshift mutants. J Virol. 1994;68(9):5460–8. Collins PL, Murphy BR. New generation live vaccines against human respiratory syncytial virus designed by reverse genetics. Proc Am Thorac Soc. 2005;2(2):166–73. Juhasz K, et al. The two amino acid substitutions in the L protein of cpts530/1009, a live-attenuated respiratory syncytial virus candidate vaccine, are independent temperature-sensitive and attenuation mutations. Vaccine. 1999;17(11–12):1416–24. Whitehead SS, et al. A single nucleotide substitution in the transcription start signal of the M2 gene of respiratory syncytial virus vaccine candidate cpts248/404 is the major determinant of the temperature-sensitive and attenuation phenotypes. Virology. 1998;247(2):232–9. Whitehead SS, et al. Addition of a missense mutation present in the L gene of respiratory syncytial virus (RSV) cpts530/1030 to RSV vaccine candidate cpts248/404 increases its attenuation and temperature sensitivity. J Virol. 1999;73(2):871–7. Whitehead SS, et al. Recombinant respiratory syncytial virus (RSV) bearing a set of mutations from cold-passaged RSV is attenuated in chimpanzees. J Virol. 1998;72(5):4467–71. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3961604","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":275418967,"identity":"d380d0c2-9dcb-4e00-bdf8-7db971f3cc33","order_by":0,"name":"Ashfaq Ahmad","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDklEQVRIiWNgGAWjYFACHoYPQDIBiA0ffKg4ABY78AC/FsYZUC3GhjPOHAAaAdSSQKQWM2neNogWBnxa+PvPHmz4UWaXp9t+eLMB77w7cvZihx8CbbGT023ArkXiRl5iY8+55GKzM2mFDyS3PTPmkU4zAGpJNjY7gMOaGzzmD3jbmBO3HcgxNjDcdjixRzoBpOUAUAS7DvnzZwwb/7bVJ247/8ZMInEOSEv6B7xaDA7kGDbzth1O3HYjx0ziYANISw5+WwxvALXInDsO1PKs2LDh2GFjnts5BQcSDHD7RQ7ksDdl1UCHJW98/KfmsBz77PTNHz5U2Mnh9D4YsGE6GJ9y7FpGwSgYBaNgFCAAALj0brWYpovtAAAAAElFTkSuQmCC","orcid":"","institution":"Hazara University","correspondingAuthor":true,"prefix":"","firstName":"Ashfaq","middleName":"","lastName":"Ahmad","suffix":""},{"id":275418968,"identity":"dd44b0ca-d00a-4454-9e3d-1dae46e4af58","order_by":1,"name":"Sidra Majaz","email":"","orcid":"","institution":"Hazara University","correspondingAuthor":false,"prefix":"","firstName":"Sidra","middleName":"","lastName":"Majaz","suffix":""},{"id":275418969,"identity":"ec9caa6b-ba53-4b66-8398-d0882b1756ff","order_by":2,"name":"Aamir Saeed","email":"","orcid":"","institution":"Hazara University","correspondingAuthor":false,"prefix":"","firstName":"Aamir","middleName":"","lastName":"Saeed","suffix":""},{"id":275418970,"identity":"ef8c73de-a522-4400-8810-70b231c03040","order_by":3,"name":"Shumaila Noureen","email":"","orcid":"","institution":"Hazara University","correspondingAuthor":false,"prefix":"","firstName":"Shumaila","middleName":"","lastName":"Noureen","suffix":""},{"id":275418971,"identity":"39f2f43c-82f8-448c-86ba-38f3bb7b8c19","order_by":4,"name":"Hamid Ur Rahman","email":"","orcid":"","institution":"Hazara University","correspondingAuthor":false,"prefix":"","firstName":"Hamid","middleName":"Ur","lastName":"Rahman","suffix":""},{"id":275418972,"identity":"3df6517d-71dc-40d0-a6eb-41839eaf091e","order_by":5,"name":"Faisal Nouroz","email":"","orcid":"","institution":"Hazara University","correspondingAuthor":false,"prefix":"","firstName":"Faisal","middleName":"","lastName":"Nouroz","suffix":""},{"id":275418973,"identity":"ff63f9d8-e44d-439d-87a6-7676c733ce17","order_by":6,"name":"Yingqiu Xie","email":"","orcid":"","institution":"Nazarbayev University","correspondingAuthor":false,"prefix":"","firstName":"Yingqiu","middleName":"","lastName":"Xie","suffix":""},{"id":275418974,"identity":"7af82439-8417-485b-a1d6-4293d5c293b5","order_by":7,"name":"Amr Amin","email":"","orcid":"","institution":"UAE University","correspondingAuthor":false,"prefix":"","firstName":"Amr","middleName":"","lastName":"Amin","suffix":""}],"badges":[],"createdAt":"2024-02-16 15:04:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3961604/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3961604/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51970573,"identity":"8a362305-750d-42ac-94d0-6d38ed648766","added_by":"auto","created_at":"2024-03-04 18:48:17","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":452807,"visible":true,"origin":"","legend":"\u003cp\u003eRSV genome distribution. (A), Country wise network distribution of the RSV genomes derived through effective parsimony informative sites (ePIS). (B), Country and year wise network of complete RSV genomes. (C), Calculated transmission pattern via community detection by modularity approach.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3961604/v1/b9428c353a8e25a37e5f5f22.jpeg"},{"id":51972377,"identity":"21e5dc75-885b-461f-96c8-cf733ffcba1b","added_by":"auto","created_at":"2024-03-04 18:56:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":66815,"visible":true,"origin":"","legend":"\u003cp\u003eOverall substitution frequencies of all coding genes coded by the RSV genome. Frequencies of only synonymous and non-synonymous substitutions are shown here. Y-axis represent the number of substitutions and the X-axis depicts number of genomes or samples participated.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3961604/v1/22621bba219fae426f5d1093.png"},{"id":51970571,"identity":"b784e7fd-3d2c-4c27-8522-ef6109ef5bd0","added_by":"auto","created_at":"2024-03-04 18:48:17","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":257430,"visible":true,"origin":"","legend":"\u003cp\u003ePresentation of hotspots mutations in all proteins. The nucleotide positions are numbered according to the reference genome U39662.1 while the proteins are numbered as per protein.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-3961604/v1/959021365f8105a03fc1ff2d.png"},{"id":52663968,"identity":"0413e92d-be1c-4a06-880e-9df1ce7cd72b","added_by":"auto","created_at":"2024-03-14 08:29:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":794006,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3961604/v1/7fa2810d-58d4-466e-837e-86075c23a83c.pdf"},{"id":51970575,"identity":"8b87e351-52a7-4fab-8bde-d03adecdd1cd","added_by":"auto","created_at":"2024-03-04 18:48:17","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":165005,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3961604/v1/0cfdc011a49fc8c685ecc3d7.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Microevolution and phylogenomic characterization of Respiratory Syncytial Virus Type A: An outlook of 2022-2023 outbreak","fulltext":[{"header":"Introduction","content":"\u003cp\u003eViruses have become a new threat to mankind and thus drawn more attention due to their potential to cause large scale pandemic as we learned the lesson from COVID-19 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Respiratory syncytial virus (RSV), also known as human respiratory syncytial virus (hRSV) contributes to the infection of respiratory tract [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Initially, RSV was isolated from Chimpanzee in 1956 and was also simultaneously recovered from infants with severe lower tract respiratory disease [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In clinical manifestations, RSV is linked to mild upper respiratory tract illness (URTI) or otitis media to severe and potentially life-threatening lower respiratory tract involvement (LRTI). The most prevalent form of LRTI in RSV-infected newborns is bronchiolitis, however there are reports indicating pneumonia and croup. Approximately, in infants and young children \u0026sim;15\u0026ndash;50% of the lower airways were found affected in primary RSV infection that results in hospitalization and higher mortality [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Apart from supportive care like fluid intake and rest, so far there is no specific treatment for RSV infection [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRSV is a non-segmented negative-sense single-stranded enveloped RNA virus that belongs to the family of Paramyxoviridae, genus Pneumovirus, and subfamily Pneumovirinae. The complete genome of RSV encodes ten proteins, M, M2, three envelope proteins, the fusion (F) glycoprotein, the G glycoprotein, and the small hydrophobic (SH) protein. Besides, five other structural and non-structural proteins are coded by the RSV genome, i.e., the large (L) protein, phosphoprotein (P), nucleocapsid (N), and non-structural proteins 1 and 2 (NS1 and NS2). Among them, protein G and F are important in host cell attachment, fusion and cellular entry [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe RSV has been classified into two subtypes A and B which further includes strains like GA1 - GA7, SAA1, NA1 - NA4 and ON1 (RSV-A), and GB1 - GB4, SAB1 - SAB4, URU1 - URU2, BA1 - BA10, BA - C and THB (RSV-B) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. There are few reports discussing mutations in individual genes like G, however we did not find any extensive analysis for RSV genomes. Here we are reporting for the first time all the mutational frequencies, hotspot regions and transmission of RSV subtype A. These analyses highlight a wider view of RSV transmission across different geological zones that could aid in predicting the oncoming pandemic and vaccine development. Besides transmission, this report provides all the observed mutations in genome coding regions and particularly the hotspot nucleotide sites prone to mutations in individual genes of RSV.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003eAll the sequences used in these analyses were collected from the NCBI Virus database [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], where we selected taxonomic identification or taxid 208893, and spotted 11956 nucleotide sequences. Specific filters were applied for genome completeness, thus the final dataset we found contained 871 sequences. The whole dataset was exported to MAFFT for whole genome alignment [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Next, the aligned dataset was fed to the viral genome evolutionary analysis system (VENAS) for further analyses [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCalculation for effective parsimony-informative site (ePIS) and network construction\u003c/h2\u003e \u003cp\u003eTo calculate ePIS, we followed a rule that the site will be considered parsimony-informative if it contains a minimum of two types of nucleotides in the aligned data, and at least two sites of them should occur with a minimum nucleotide frequency of two. Besides, the ePIS was considered effective only in the case that the site must contain unambiguous bases\u0026thinsp;\u0026ge;\u0026thinsp;80% of the total genomes. Keeping the above rules, 474 genomes were found satisfactory, and thus all the remaining analyses were carried out on the dataset containing 474 genomes. The derived ePIS results were used to classify all the genomes in haplotypes, and for this reason sequences containing similar ePIS were grouped onto the similar nodes and vice versa. Visualization, graph rendering and community detections were performed by Gephi.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMutational Analysis\u003c/h2\u003e \u003cp\u003eMutational analyses for individual genes were performed by NGS analysis package BioAider [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. To retrieve codon information, aligned sets for individual genes were extracted from the aligned dataset used for VENAS. All the gaps (InDel operations) were removed and aligned them again using the codon alignment tool. The complete reports for individual genes substitutions can be found in table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. To detect hotspot regions, only those non-synonymous substitutions were considered which showed changes in amino acid properties and more than 200 samples responded. The axillary art work was drawn by illustrator for the visualization of biological sequences (IBS) and Paint.net [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eWe retrieved the complete nucleotide sequence dataset for RSV type A (taxid. 1439707) from the NCBI Virus database. By December 2022, it contained 1166 nucleotide records, including 871 complete genomes. After initial filtration and name tagging that includes, genome ID, reported year and country, we applied viral genome evolutionary analysis system (VENAS) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and analyzed the evolutionary relationship between different genomes or RSV strains. Among them the earlier reported genome U39662.1 in 1997 was considered as a reference. Based on the effective parsimony informative sites (ePIS), and removal of redundant genome sequences, VENAS picked 474 genomes for further analyses. The final genome dataset contains sequences from the USA (2014, 2017, 2019, and 2021), Brazil (2021), Kenya (2021), Philippines (2017), Jordan (2018), Thailand (2019), Netherland (2021), Australia (2020, and 2022), China (2018), UK (2021), Spain (2021), Germany (2020), and four Unknown sequences (2022).\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eRSV transmission distribution on the country scale\u003c/h2\u003e \u003cp\u003eIn order to trace the transmission routes, and contribution, we mapped 474 RSV genomes on the viral evolution network. Our data indicated individual clusters such as cluster of the USA 2014 sequences, connected to cluster of the USA 2017, which further connected the Brazilian cluster 2021, whereas sequences from Jordan 2018 and Philippines 2017 were also observed. Apparently, we found that samples of North and South America were cluster separated from the European samples. However, genomes reported from the USA 2019 were found mixed with genomes reported from Europe (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo understand the transmission pattern, we used a network modularity function and clustered the whole network beyond their country or year-wise taglines. We retrieved 12 clades (clade A to clade L). Interestingly, our data predicted a unique pattern, for instance the terminal clade A, contained purely genomes reported from the USA in the year 2014, which connected clade B retaining genomes reported from the USA in the year 2014 and 2017. Further, clade C, a direct descendent of clade B contains all the genomes reported in 2017, except one sequence from the USA 2021. Apart from few genomes reported from the USA 2017, Philippines 2017 and Jordan 2018, clade D contain\u0026thinsp;\u0026gt;\u0026thinsp;95% of the genomes reported from Brazil 2021. To our interest the smaller clade E, contains representation of almost all the previous clades and connects the bigger node clade F. All the previous clades did not show a single genome reported from the Europe therefore, for better understanding, we call clade F, a European clade, as it is the first with European representation that also gave birth to diverse nodes reported from European countries.\u003c/p\u003e \u003cp\u003eThe European node (clade F), is tetra-furcated into clade G, H, I and L. Among them, clade H contained samples of Nederland, Spain and the United Kingdom reported in 2021 while clade G was found enriched with all the sequences reported from Nederland 2021. Likewise, clade L is formed from the genomes reported in the United Kingdom 2021, the USA 2019, and two genomes from Spain 2021. Interestingly, clade L emerged from the European cluster through genomes reported from Philippines 2017 and the USA 2019. Finally, Clade I that contains genomes from Spain, Nederland and the United Kingdom 2021 which is bifurcated to clade J and K, where clade J contains samples from the United Kingdom 2021 that leads to Australia 2022 and the clade K only contains all the genomes reported from Australia reported in 2022. All the samples are mapped with country, year and transmission wise in (Fig.\u0026nbsp;1BC).\u003c/p\u003e \u003cp\u003eCollectively, these analyses indicate the global prevalence and the presence of different RSV type A strains. For instance, genomes reported from Australia in 2022 were gathered in two different clusters emerging from the European genomes, suggesting the presence of two different strains. However, genomes reported from Australia in 2020, are lying distantly for those reported in 2022. Likewise, genomes from the UK reported in 2021, were found almost everywhere with European genomes, depicting the possibility of numerous RSV strains. Genomes from Spain and the Netherlands were also found in 2 and 3 different nodes, highlighting the circulation of more than one strain in that country.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eMutation and substitution frequencies of synonymous and non-synonymous sites in RSV genomes\u003c/h2\u003e \u003cp\u003eAccording to the NCBI records, RSV contains ten to eleven protein coding genes, i.e., non-structural protein 1 and 2 (NS1 and NS2), nucleoprotein (N), phosphoprotein (P), matrix 1 protein (M), small hydrophobic protein (SH), attachment protein (G), fusion protein (F), matrix 2 protein (M2), and polymerase (L). We calculated substitution observed in RSV genomes for all coding sequences (CDS) of all ten genes, particularly synonymous and non-synonymous substitutions. All the substitutions were accessed and calculated against the reference strain U39662.1. A total of 6257 (45%) sites were observed in substitutions, and among them 2099 (15.1%), 3027 (21.7%), 611 (4.3%), and 473 (3.4%) were synonymous, non-synonymous, both and terminations, respectively. Among the non-synonymous substitutions, 1442 (10%) sites were found to have changes in amino acid properties. The highest termination substitutions were found in L followed by N and G proteins (Table. 1).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistics of all types substitutions observed in individual genes of RSV\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLength (CDS)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProportion of Mutation sites\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS(p)/N(p)/S-N(p)/Termination(p)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNS1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e105(25.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e79(17.3%)/29(6.9%)/3(0.7%)/0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNS2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e503\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110(21.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75(14.9%)/30(5.9%)/5(0.9%)/0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e554(47.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e200(17.0%)/253(21.5%)/67(5.6%)/34(2.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e214(29.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e138(19.0%)/67(9.2%)/9(1.2%)/0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e177(22.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e138(17.8%)/33(4.2%)/6(0.7%)/0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63(32.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33(16.9%)/25(12.8%)/4(2.0%)/1(0.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eG\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e496(55.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e162(18.0%)/298(33.2%)/28(3.1%)/8(0.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e468(27.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e349(20.2%)/106(6.1%)/13(0.7%)/0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eM2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e585\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e150(25.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e94(16.0%)/47(8.0%)/8(1.3%)/1(0.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3920(60.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e831(12.7%)/2139(32.9%)/468(7.2)/432(6.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComplete\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6257(45.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2099(15.1%)/3027(21.7%)/611(4.3%)/476(3.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn protein L and G, we also observed higher and similar non-synonymous mutation frequency compared to all other genes of RSV. However, F and P proteins have relatively shown a higher number of synonymous substitutions than non-synonymous. Complete details for substitutions and substitution type for all individual genes can be accessed in form (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo evaluate the overall substitution frequency of the mutated sites, present in all ten CDSs, we alienated the substitution frequency into seven different groups (G1 to G7), and depicted the frequency distribution of 5126 substituted sites (3027 non-synonymous and 2097 synonymous) of the 474 sequenced genomes. Group number on the X-axis indicates the number of strains participating in a substitution event at a particular site, whereas the Y-axis shows the number of substitutions in a respective CDS (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOur results indicated that apart from the initial groups, where non-synonymous mutations were found relatively higher than the distribution of synonymous mutations. Comparing all the CDSs, the CDS of G protein showed the highest number of non-synonymous mutations where 55 mutations were found in G4 - G7, meaning the participation of 200 samples. We have also observed that CDSs of NS1, NS2, SH, and M proteins offered relatively lower sites for non-synonymous mutations in the majority of the sequenced RSV strains. The distribution of substitution frequency of each codon in each gene can be found in the supplementary Table.\u003c/p\u003e \u003cp\u003eOverall, these analyses provide complete mutational information of all ten RSV\u0026rsquo;s CDSs. Such key features can also be used to assess the evolutionary pressure on selected sites or response to therapeutic agents.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSubstitution hot-spots in RSV type A genomes\u003c/h2\u003e \u003cp\u003eNext, we were interested to identify the hot-spot substitution sites in RSV CDSs. Similar to the analysis [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] for SARS-CoV-2, we defined a criterion for hotspot regions. A site with a substitution frequency over 200 will be considered a hot-spot site, or a site that offered substitution to more than 200 RSV strains (42% in our case) will be considered a potential substitution hot-spot. Second, the respective site must allow non-synonymous substitution and the observed amino acid should record a change in amino acid properties. A total of 367 substitution sites were found with \u0026gt;\u0026thinsp;200 substitution frequency where 290, and 77 were synonymous and non-synonymous respectively. Among 77 non-synonymous substitution sites, 32 were those affecting amino acid properties (either changing polarity or charge difference) were considered hot-spot substitution sites. These 32 hot-spots were found distributed across F protein (4), G protein (13), L protein (10), N1, N2, P, N, and M2 (1 each) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Two hot-spots that resulted in CAA to TTA (Q142L) in G protein and ATA to ACG and ACA (I184T) in M2 protein offered double substitutions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eRespiratory syncytial virus (RSV) is a communal respiratory virus that can cause mild to severe illness, predominantly in young children, elderly adults, and people with certain chronic medical conditions. In some cases, it can lead to more serious illness such as bronchiolitis or pneumonia. Here, we detected a probable transmission pattern that in turn may also explain the classification of different strains circulating worldwide. Reference to the hotspot substitutions, we identified 32 hotspots positions, where 13 and 4 are detected only the G and F protein. Both G and F proteins are considered important because both can induce neutralizing antibodies, and are heavily glycosylated, which has been shown to affect with antibody recognition [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Structurally, the G protein comprises three domains; a cytoplasmic domain (1\u0026ndash;37 amino acids), a transmembrane domain (38\u0026ndash;66 amino acids), and an ectodomain region (67\u0026ndash;312) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Interestingly, all the hotspot positions we identified belong to the ectodomain of the G protein. There are individual reports in G, F, and L proteins [\u003cspan additionalcitationids=\"CR23 CR24 CR25 CR26\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and we believe that this report will assist researchers to directly pick the hotspot regions for biochemical testing.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis report provides an idea to probe the presence of any viral species and classify them into different strains. Such approaches can be further utilized towards personalized medication therapy particularly in children to cope pandemic.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article and its supplementary information files\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea. Ethics approval and consent to participate \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb. Consent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec. Availability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ed. Competing interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors have read the manuscript and are aware of the submission to Nature Communication. Further, all the authors have declared no conflicting of interest of any kind.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ee. Funding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no specific grant for the project, but one of the corresponding author obtained grant during the project; Nazarbayev University Faculty-Development Competitive Research Grants Program, with reference ID 32729571, ID 15798117 (Funder Project References:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e11022021FD2920 and 110119FD4531) to Yingqiu Xie; AUA-UAEU grant (2019; 12R118) to Amr Amin and Yingqiu Xie. The funder had no function in research design, data collection/analysis, preparation of the manuscript or decision to publish.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ef. Authors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIdea conceived by AA and SN and refined by YX.\u003c/p\u003e\n\u003cp\u003eExperiments performed and data analysis by SM, AA, AS, HR.\u003c/p\u003e\n\u003cp\u003eManuscript write-up was performed by SM, AA, AAm and AS.\u003c/p\u003e\n\u003cp\u003eArtwork was generated by AA, AS, SM and HR.\u003c/p\u003e\n\u003cp\u003eCritical reading and directions were given by SN, AAm, FN, and YX.\u003c/p\u003e\n\u003cp\u003eSupervised by AA and YX.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eArvin AM, et al. A perspective on potential antibody-dependent enhancement of SARS-CoV-2. Nature. 2020;584(7821):353\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBohmwald K, et al. Contribution of Cytokines to Tissue Damage During Human Respiratory Syncytial Virus Infection. Front Immunol. 2019;10:452.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNoor F, et al. Comprehensive computational analysis reveals H5N1 influenza virus-encoded miRNAs and host-specific targets associated with antiviral immune responses and protein binding. PLoS ONE. 2022;17(5):e0263901.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKant K, Lal UR, Ghosh M. Computational Breakthrough of Natural Lead Hits from the Genus of Arisaema against Human Respiratory Syncytial Virus. Pharmacogn Mag. 2018;13(Suppl 4):S780\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBorchers AT, et al. Respiratory syncytial virus\u0026ndash;a comprehensive review. Clin Rev Allergy Immunol. 2013;45(3):331\u0026ndash;79.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeng S, et al. Discovery of imidazopyridine derivatives as highly potent respiratory syncytial virus fusion inhibitors. ACS Med Chem Lett. 2015;6(3):359\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAfonso CL, et al. Taxonomy of the order Mononegavirales: update 2016. Arch Virol. 2016;161(8):2351\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarvajal JJ, et al. Host Components Contributing to Respiratory Syncytial Virus Pathogenesis. Front Immunol. 2019;10:2152.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCollins PL, Fearns R, Graham BS. Respiratory syncytial virus: virology, reverse genetics, and pathogenesis of disease. Curr Top Microbiol Immunol. 2013;372:3\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThongpan I, et al. Respiratory syncytial virus genotypes NA1, ON1, and BA9 are prevalent in Thailand, 2012\u0026ndash;2015. PeerJ. 2017;5:e3970.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMufson MA, et al. Two distinct subtypes of human respiratory syncytial virus. J Gen Virol. 1985;66(Pt 10):2111\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrister JR, et al. NCBI viral genomes resource. Nucleic Acids Res. 2015;43(Database issue):D571\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKatoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol. 2013;30(4):772\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLing Y, et al. An interactive viral genome evolution network analysis system enabling rapid large-scale molecular tracing of SARS-CoV-2. Sci Bull (Beijing). 2022;67(7):665\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou ZJ, et al. BioAider: An efficient tool for viral genome analysis and its application in tracing SARS-CoV-2 transmission. Sustain Cities Soc. 2020;63:102466.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXie Y et al. \u003cem\u003eIBS 2.0: an upgraded illustrator for the visualization of biological sequences\u003c/em\u003e. Nucleic Acids Res, 2022. 50(W1): p. W420-6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePalomo C, Cane PA, Melero JA. Evaluation of the antibody specificities of human convalescent-phase sera against the attachment (G) protein of human respiratory syncytial virus: influence of strain variation and carbohydrate side chains. J Med Virol. 2000;60(4):468\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarcia-Beato R, Melero JA. The C-terminal third of human respiratory syncytial virus attachment (G) protein is partially resistant to protease digestion and is glycosylated in a cell-type-specific manner. J Gen Virol. 2000;81(Pt 4):919\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJones HG, et al. 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New generation live vaccines against human respiratory syncytial virus designed by reverse genetics. Proc Am Thorac Soc. 2005;2(2):166\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJuhasz K, et al. The two amino acid substitutions in the L protein of cpts530/1009, a live-attenuated respiratory syncytial virus candidate vaccine, are independent temperature-sensitive and attenuation mutations. Vaccine. 1999;17(11\u0026ndash;12):1416\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhitehead SS, et al. A single nucleotide substitution in the transcription start signal of the M2 gene of respiratory syncytial virus vaccine candidate cpts248/404 is the major determinant of the temperature-sensitive and attenuation phenotypes. Virology. 1998;247(2):232\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhitehead SS, et al. Addition of a missense mutation present in the L gene of respiratory syncytial virus (RSV) cpts530/1030 to RSV vaccine candidate cpts248/404 increases its attenuation and temperature sensitivity. J Virol. 1999;73(2):871\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhitehead SS, et al. Recombinant respiratory syncytial virus (RSV) bearing a set of mutations from cold-passaged RSV is attenuated in chimpanzees. J Virol. 1998;72(5):4467\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Respiratory syncytial virus, Transmission network, Mutation frequencies, Hotspot identification, Phylodynamics","lastPublishedDoi":"10.21203/rs.3.rs-3961604/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3961604/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eA communal respiratory syncytial virus (RSV) causes mild to severe illness, predominantly in older adults, or people with certain chronic medical conditions, and in children. Symptoms may include runny nose, cough, fever, and difficulty breathing. In most cases, the infection is mild and resolves on its own, but in some cases, it can lead to more serious illness such as bronchiolitis or pneumonia. The RSV genome codes for ten proteins, NS1, NS2, N, P, M, SH, G, F, M2 and L. We aimed to identify the RSV geographical distribution and transmission pattern using site parsimonious frequencies, and investigate hotspot regions across the complete RSV genomes. These results indicated that RSV strains circulating in South and North America are not mixed to the European samples, however, genomes reported from Australia are the direct decedents of European samples. Samples reported from the United Kingdom were found diverse. Further, this report provides a comprehensive mutational analysis of all the individual RSV genes and in particular the 32 hotspot substituting regions circulating across the globe in RSV type A samples. This is the first comprehensive analysis of RSV type A that features mutational frequencies across the whole genome providing more clues for epidemiological control and drug development.\u003c/p\u003e","manuscriptTitle":"Microevolution and phylogenomic characterization of Respiratory Syncytial Virus Type A: An outlook of 2022-2023 outbreak","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-04 18:48:12","doi":"10.21203/rs.3.rs-3961604/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e7134b57-48e6-4e0d-9e7e-d667ea1b109f","owner":[],"postedDate":"March 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-14T08:21:03+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-04 18:48:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3961604","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3961604","identity":"rs-3961604","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}