The Re-emergence of Chikungunya in Sri Lanka: A Genomic investigation

The Re-emergence of Chikungunya in Sri Lanka: A Genomic investigation | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (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];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search The Re-emergence of Chikungunya in Sri Lanka: A Genomic investigation Tibutius Thanesh Pramanayagam Jayadas , Malithi de Silva , Bhagya Senadheera , Laksiri Gomes , Heshan Kuruppu , Radanee Rathnapriya , Farha Bary , Sahan Madusanka , Ananda Wijewickrama , Damayanthi Idampitiya , Suranga Manilgama , Ruklanthi de Alwis , Chandima Jeewandara , Gathsaurie Neelika Malavige doi: https://doi.org/10.1101/2025.05.23.25328206 Tibutius Thanesh Pramanayagam Jayadas 1 Institute of Allergology and Immunology, University of Sri Jayewardenepura , Gangodawila, Nugegoda, Sri Lanka Find this author on Google Scholar Find this author on PubMed Search for this author on this site Malithi de Silva 1 Institute of Allergology and Immunology, University of Sri Jayewardenepura , Gangodawila, Nugegoda, Sri Lanka Find this author on Google Scholar Find this author on PubMed Search for this author on this site Bhagya Senadheera 1 Institute of Allergology and Immunology, University of Sri Jayewardenepura , Gangodawila, Nugegoda, Sri Lanka Find this author on Google Scholar Find this author on PubMed Search for this author on this site Laksiri Gomes 1 Institute of Allergology and Immunology, University of Sri Jayewardenepura , Gangodawila, Nugegoda, Sri Lanka Find this author on Google Scholar Find this author on PubMed Search for this author on this site Heshan Kuruppu 1 Institute of Allergology and Immunology, University of Sri Jayewardenepura , Gangodawila, Nugegoda, Sri Lanka Find this author on Google Scholar Find this author on PubMed Search for this author on this site Radanee Rathnapriya 1 Institute of Allergology and Immunology, University of Sri Jayewardenepura , Gangodawila, Nugegoda, Sri Lanka Find this author on Google Scholar Find this author on PubMed Search for this author on this site Farha Bary 1 Institute of Allergology and Immunology, University of Sri Jayewardenepura , Gangodawila, Nugegoda, Sri Lanka Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sahan Madusanka 1 Institute of Allergology and Immunology, University of Sri Jayewardenepura , Gangodawila, Nugegoda, Sri Lanka Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ananda Wijewickrama 2 National Institute of Infectious Diseases , Angoda, Sri Lanka Find this author on Google Scholar Find this author on PubMed Search for this author on this site Damayanthi Idampitiya 2 National Institute of Infectious Diseases , Angoda, Sri Lanka Find this author on Google Scholar Find this author on PubMed Search for this author on this site Suranga Manilgama 2 National Institute of Infectious Diseases , Angoda, Sri Lanka Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ruklanthi de Alwis 3 Programme in Emerging Infectious Diseases, Duke-NUS Medical School , Singapore 4 Center for Outbreak Preparedness, Duke-NUS Medical School , Singapore Find this author on Google Scholar Find this author on PubMed Search for this author on this site Chandima Jeewandara 1 Institute of Allergology and Immunology, University of Sri Jayewardenepura , Gangodawila, Nugegoda, Sri Lanka Find this author on Google Scholar Find this author on PubMed Search for this author on this site Gathsaurie Neelika Malavige 1 Institute of Allergology and Immunology, University of Sri Jayewardenepura , Gangodawila, Nugegoda, Sri Lanka Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: gathsaurie.malavige{at}ndm.ox.ac.uk Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Sri Lanka is currently experiencing a large Chikungunya outbreak, since the end of 2024, after 16 years. We carried out whole genomic sequencing of the currently circulating Chikungunya virus (CHIKV) strain and found that it was of the Indian ocean lineage (IOL), similar to the currently circulating CHIKV strains in South Asia. While the E:226V mutation, which has been associated with Aedes albopictus transmission efficiency, was absent in all 2025 CHIKV viral sequences, they carried the E1:K211E and E2: V264A mutations, which result in enhanced viral fitness within the Aedes aegpti mosquito. The mutations nsP1:I167V, nsP2:I171V, nsP2:T224I, nsP3:A382I and nsp4: were detected in the non-structural protein, with the Sri Lankan 2025 CHIKV strains showing unique mutations within nsP3:T224I and nsP4: S90A. As some of these novel mutations have not been characterized previously, it is important to find out how they affect fitness within mosquitoes, viral replication and immune evasion. One-sentence summary line The currently ongoing large outbreak in Sri Lanka, is due to the Indian-ocean lineage and E1:K211E/E2:V264A sub lineage of the Chikungunya virus, which has acquired certain previously uncharacterized unique mutations. Introduction Chikungunya has been causing significant outbreaks in the last two decades and is now reported in over 110 countries [ 1 ]. It is transmitted by the Aedes species of mosquitoes and as all other mosquito-borne viral infections, the number of cases has been rising with geographical expansion of the virus [ 2 ]. Global estimates show that 33.7 million individuals are infected annually with the Chikungunya virus (CHIKV), with 8.4% of the population estimated to be infected during each new Chikungunya outbreak [ 3 ]. Although Chikungunya infection is characterized by a sudden onset of fever accompanied by headache, arthralgia and myalgia [ 1 ], 4.7% to 78.6% have shown to progress to chronic arthritis (lasting >3 months) [ 4 ]. Due to persistence of symptoms in many individuals, it is estimated that the Chikungunya was responsible for 1.95 million disability-adjusted life years (DALYs) and $2.8 billion in direct costs and $47.1 billion in indirect costs worldwide, between 2011 and 2020 [ 2 ]. Therefore, due to the recent surge in Chikungunya globally, it is crucial to characterize the evolution of the virus, which could adapt to increased transmissibility within vectors and persistence. There are three main lineages (East/Central/South African, West African and Asian) of the CHIKV, which have been responsible for outbreaks during the last two decades in many countries in the tropics and sub-tropics [ 5 ]. The Indian ocean lineage (IOL), evolved from the East/Central/South African (ECSA) major lineage, and has been causing outbreaks predominantly in South Asia, Southeast Asia and the islands of the Indian ocean [ 5 ]. Although the Asian genotype was responsible for the initial CHIKV outbreaks in India during the 1960 and 1970s, this was subsequently replaced by the IOL which emerged from the ECSA genotype during the outbreaks following 2005 [ 6 ]. In recent years, the same IOL lineage was found to cause outbreaks in India, Bangladesh and Pakistan [ 7 – 9 ]. Although these CHIKV strains were observed to have acquired different mutations from the strains that circulated prior to 2015 [ 10 ]. For instance, the CHIKV strains that most recently found to be circulating in India did not have the E1:A226V mutation, which increases transmissibility by Aedes albopictus , but had the E1:K211E, which increases fitness in Aedes aegypti [ 7 , 10 ]. The impact of these mutations on overall transmission of CHIKV has not been studied. Furthermore, the virus has also acquired additional mutations such as nsP4: R82S giving rise to a sub-lineage, which enhances the viral replication in human hosts [ 10 ]. Therefore, given that CHIKV is evolving and causing large outbreaks in many regions, it is important to conduct molecular epidemiology and characterize the strains causing outbreaks in different regions. Sri Lanka experienced the first outbreak of CHIKV between the years 2006 to 2008, which led to 37,667 clinically suspected infections [ 11 ]. Although CHIKV had caused outbreaks in the region, including in India from 1960s onwards, serosurveys have shown that CHIKV is unlikely to have circulated in Sri Lankans prior to 2006 [ 11 ]. After the outbreak waned in 2008, CHIKV cases were not reported in Sri Lanka for the next decade. However, febrile surveillance during years 2017 to 2018, has shown that in some regions in Sri Lanka, around 1% of febrile patients were infected with CHIKV, indicating that the virus had been circulating in Sri Lanka despite not causing outbreaks [ 12 ]. After 16 years around the end of 2024, patients presenting with a Chikungunya-like illness was reported in Colombo, Sri Lanka, which was later confirmed as CHIKV cases. Since then, the reported CHIKV cases have rapidly increased and now Sri Lanka is experiencing a large outbreak. Due to a lack of widespread access to CHIKV diagnostics and a concurrent dengue outbreak, the true estimates of cases from this outbreak are unknown. The genomic sequence of the currently circulating CHIKV strain is needed to guide decisions around diagnostics and outbreak control. Therefore, here in this study we report the molecular characteristics of CHIKV isolated from patients from the current large outbreak in Sri Lanka. The genomic sequence findings show that the currently circulating CHIKV is of the IOL, which despite containing similar mutations to the recently reported CHIKV strains in South Asia have also acquired unique mutations. The epidemiological, virological or immunological implications of the new mutations are currently unclear. Methodology Recruitment of Patients and samples We have been carrying out arbovirus surveillance at the National Institute of Infectious Diseases, a tertiary care hospital in the Western Province of Sri Lanka, since 2022. Between November 2024 and April 2025, patients with clinical symptoms suggestive of CHIKV infection were admitted to this hospital and 65 adult patients who presented with a febrile illness were recruited following informed written consent. All cases were recruited within the first 5 days since the onset of illness and tested negative for dengue by the NS1 rapid antigen test. Ethics approval Ethics approval was obtained from the Ethics Review Committee, University of Sri Jayewardenepura (21/21) and administrative clearance was obtained from the Ministry of Health, Sri Lanka. Screening for CHIKV using quantitative PCR Viral RNA was extracted from serum samples using the MagMAX™ Viral/Pathogen Nucleic Acid Isolation Kit (Applied Biosystems™, Thermo Fisher Scientific, USA). All 65 samples were screened for chikungunya, dengue, and Zika viruses using a TIAN LONG multiplex quantitative PCR (qPCR) kit, according to the manufacturer’s instructions. Library preparation and sequencing of CHIKV CHIKV positive samples with CT value of <26 were reverse transcribed using LunaScript™ RT SuperMix. Tiling PCR was carried out using a previously published primer scheme specific to chikungunya virus [ 13 ]. Two primer pools (10 µM each), labeled Pool A and Pool B, were prepared and combined with Q5® High-Fidelity DNA Polymerase (New England Biolabs) and nuclease-free water. Amplification was performed on a QuantStudio™ 5 Real-Time PCR Instrument (Applied Biosystems, Singapore) under the following thermal cycling conditions: initial denaturation at 98 °C for 30 seconds, followed by 40 cycles of 98 °C for 15 seconds and 65 °C for 5 minutes, and a final hold at 4 °C. Libraries for sequencing were generated from the amplified samples using the ONT Rapid Barcoding Kit (SQK-RBK110.96) and previously published primers [ 13 ], following the protocol version RBK_9126_v110_revO_24Mar2021. The pooled barcoded MinION library was subsequently loaded onto the MinION Mk1b sequencer from Oxford Nanopore Technologies, Oxford, United Kingdom, equipped with an R9.4 flow cell. Real-time base calling was performed using MinKNOW version 3.0.4 with the Guppy base calling software version 3.2.10. EPI2ME wf alignment (v1.0.2) and reference: NC_004162.2 was used to filter the CHIKV reads. Medaka (V1.4.4) tool was used to develop consensus sequences. CHIKV Phylogenetic tree construction Six CHIKV sequences with >70% genome coverage (based on reference sequence NC_004162.2) were included in a phylogenetic analysis alongside 898 complete CHIKV genomes downloaded from GenBank. All 904 sequences were aligned using MAFFT (Galaxy Version 7.526) with the FFT-NS-2 algorithm. A maximum likelihood (ML) phylogenetic tree was reconstructed using IQ-TREE (Galaxy Version 2.4.0), with ModelFinder identifying the GTR+I+R4 substitution model as the best fit. Branch support was assessed using 1000 ultrafast bootstrap replicates [ 14 , 15 ]. Phylogenetic and temporal signal analysis of IOL CHIKV sequences Sequences clustering within the Indian Ocean Lineage (IOL) clade were identified from the full ML tree and extracted for focused analysis. To ensure geographic and temporal representativeness, the IOL subset was pruned to 137 sequences by retaining at least two sequences per country-year group. Three representative sequences from the West African (HM045785.1), Asian (HM045813.1), and East/Central/South African (ON009843.1) lineages were included to provide a broader phylogenetic context [ 16 ]. A total of 137 CHIKV genomes classified under the Indian Ocean Lineage (IOL), including six newly sequenced 2025 Sri Lankan AICBU genomes, were selected from the full dataset of 904 sequences (Supplementary Figure 1). The resulting dataset of 140 sequences was realigned using MAFFT, and a second ML phylogeny was constructed in IQ-TREE using the same model and bootstrap settings. Temporal signal was assessed using root-to-tip regression in TempEst v1.5.3 [ 17 ], and rate variation across branches was explored using Clockor2 v1.9.1 [ 18 ]. All phylogenetic trees and visualizations were generated in R using treeio, ggtree, dplyr, stringr, readr, ggpubr, and tidyverse. CHIKV mutation analysis Mutation analysis was conducted on the 2025 Sri Lankan CHIKV sequences using consensus sequences generated from Medaka (Medaka v1.4.4). Ammino acid sequences of structural protein (E1- E3) and nonstructural polyprotein (NSP1- NSP4) were aligned and compared to the CHIKV reference sequence (NC_004162.2) to identify amino acid substitutions. Additionally, 11 Sri Lankan CHIKV sequences from the 2006-2008 outbreak were included in the analysis to compare the differences in the mutations with the current circulating CHIKV strains in Sri Lanka. To compare the mutations within the CHIKV Sri Lankan 2025 strains to those of the other currently circulating South Asian strains, CHIKV sequences from India and Pakistan (detected in 2024) were also incorporated into the analysis. Mutations were identified through pairwise comparisons and visualized using R packages (version 4.1.2). Results Detection of CHIKV Infections Between December 2024 to April 2025, 23/65 (35.4%) patients who presented with clinical features suggestive of CHIKV infection, tested positive for CHIKV and 7 (10.8%) for DENV by multiplex qPCR assay. No patients tested positive for Zika virus, and no co-infections were identified. All individuals with confirmed CHIKV infection reported fever, arthralgia, and myalgia. Of the 23 patients who were infected with CHIKV, 6 were female and 17 were male. Low to medium qPCR cycle threshold (Ct) values for CHIKV were observed, ranging from 16 to 29. Twenty-two samples with Ct values below 26 were selected for whole-genome sequencing using Oxford Nanopore Technologies (ONT). Of these, 6 samples yielded genome coverage exceeding 70% and were included in downstream analyses. Phylogenetic analysis of the CHIKV sequences from the current outbreak The 2025 Sri Lankan sequences (PV660466 to PV660471) formed a well-supported monophyletic clade (bootstrap = 100) within IOL, characterized by short internal branch lengths and high genetic similarity ( Figure 1 ). This clade was nested within a broader group of South Asian strains and showed the closest relationship to CHIKV sequences from originating from India (PP896909.1) and Pakistan (PV054364.1) in year 2024. The high bootstrap support (≥99) at all nodes leading to these sequences shows that the Sri Lankan sequences from early 2025, fell within the same cluster. This suggests that the CHIKV strains causing the current ongoing chikungunya outbreak in Sri Lanka were likely to have been introduced from a single location/source. Download figure Open in new tab Figure 1: Maximum likelihood phylogenetic tree of chikungunya virus (CHIKV) genomes, highlighting the Indian Ocean Lineage (IOL). The tree includes Sri Lankan 2006-2008 sequences (blue) and 2025 (green), along with global reference sequences. Colored dots indicate the country of origin. None of the 2025 Sri Lankan CHIKV sequences clustered with Sri Lankan CHIKV strains responsible for the last Chikungunya outbreak in Sri Lanka during 2006 to 2008. While the CHIKV 2025 strains were closely clustered together, the CHIKV strains from 2006 to 2008 from Sri Lanka, were found to be dispersed in three distinct clades within IOL. These different clades were interspersed with sequences from India (FJ000066.10), Bangladesh (FJ807898.1) Singapore (FJ807896.1) and USA (KY575570), suggesting that the CHIKV strains causing the outbreak in Sri Lanka from 2006 to 2008 were most likely to have originated from multiple locations, which is different from the single introduction seen in current CHIKV outbreak. Evolutionary rate of the Sri Lankan CHIKV strains within the IOL Molecular clock analysis was performed to estimate the evolutionary rate of Sri Lankan CHIKV strains within the IOL, by comparing global sequences with Sri Lankan genomes collected between 2006 and 2025. The root-to-tip regression analysis estimated a substitution rate of 5.35 × 10⁻⁴ substitutions/site/year for the global IOL dataset, with a strong temporal signal (R² = 0.8479). The estimated time to the most recent common ancestor (tMRCA) for these sequences was approximately 2003. In contrast, the Sri Lankan subset exhibited a higher substitution rate of 7.20 × 10⁻⁴ substitutions/site/year and an even stronger temporal signal (R² = 0.9630). These results that the Sri Lankan sequences are evolving at a relatively faster rate compared to the broader IOL population, possibly due to the ongoing rapid transmission ( Figure 2 ). Download figure Open in new tab Figure 2: Root-to-tip regression plot comparing the temporal signal of global and Sri Lankan CHIKV genomes within the Indian Ocean Lineage (IOL). Each point represents a genome, with the x-axis showing sampling date (in decimal years) and the y-axis representing genetic divergence from the tree root. Global sequences are shown in blue, while Sri Lankan sequences are highlighted in orange—distinguishing AICBU 2025 sequences (squares) from earlier Sri Lankan sequences (triangles). Mutation analysis within the structural proteins (E1-E3) of CHIV All Sri Lankan CHIKV 2025 sequences carried K211E and I55V substitution with the E1 protein, a consistent set of mutations, I418V and V264A within the E2 protein. These mutations were also seen in the recently detected CHIKV sequences in outbreaks reported in 2024 from India and Pakistan ( Figure 3A ). However, A3V substitution was detected with the E3 protein in the Sri Lankan CHIKV strains but was absent in the Indian and Pakistani genomes. Further, the I23T substitution in the E3 protein was observed only in Sri Lankan and Indian sequences, but not in the Pakistani strains. In contrast, E1:M269V, found frequently in Indian and Pakistani sequences, were detected in only one Sri Lankan genome. Download figure Open in new tab Figure 3: Heatmap of amino acid substitutions in the E1-E3 region of the CHIKV 2025 strains in Sri Lanka. Heatmap of amino acid mutations in structural protein (E1 -E3) envelope proteins of Sri Lankan CHIKV sequences from 2025 in comparison to the most recent CHIKV sequences identified from the region (A). The amino acid mutations in structural protein (E1 -E3) were also compared to the Sri Lankan CHIKV sequences from 2006–2008 (B). Each row represents an individual genome, and each column denotes a specific amino acid substitution relative to the reference strain (NC_004162.2). Dark red cells indicate the presence of a mutation at the corresponding position. Additionally, three of the 2025 sequences exhibited a mutation in the E3 protein at position A3V. These amino acid changes were absent in all Sri Lankan sequences that caused the outbreak in years 2006 to 2008 ( Figure 3B ). In contrast, earlier sequences displayed greater mutational heterogeneity and included mutations such as E1:A226V and K211N, E2:R198Q and E2:V222I, E3: S18F which were not observed in the 2025 group. Notably, E1: A226V, which has been associated with Aedes albopictus transmission efficiency, was absent in all 2025 samples [ 10 ]. Mutations analysis within the nonstructural proteins (nsP1–nsP4) Similar to the CHIKV strains from recent outbreaks from India and Pakistan, the 2025 Sri Lankan sequences also showed a similar pattern of mutations in the nonstructural proteins, such as I167V in nsP1, I171V, T224I and A382I in nsP3 and V21A in nsP4. However, certain mutations such as R171Q in nsP1, S420P, I376T, R524Stop and V437A in nsP3, which were found in the Indian and Pakistan sequences were not detected in any of the CHIKV strains in Sri Lanka. On the other hand, certain unique mutations were seen in the 2025 Sri Lankan strains, which were not detected in the CHIKV strains in the region such as the T224I within the nsP3 protein and S90A mutation within the nsP4 protein. None of the above mutations were detected in the 2006–2008 Sri Lankan strains ( Figure 4B ). Meanwhile, several mutations present in the 2006-2008 Sri Lankan CHIKV sequences including T376M in nsP1, A702S in nsP2, I376T and R524stop and Y38H in nsP3 were absent in the 2025 Sri Lankan sequences. Download figure Open in new tab Figure 4: Heatmap of amino acid substitutions in the non-structural proteins of the CHIKV 2025 strains in Sri Lanka. Heatmap of amino acid mutations in non-structural proteins of Sri Lankan CHIKV sequences from 2025 in comparison to the most recent CHIKV sequences identified from the region (A) and also in comparison to the the nonstructural proteins (nsP1–nsP4) of Sri Lankan CHIKV sequences from 2006–2008 and 2025 (B). Each row represents an individual genome, and each column denotes a specific amino acid substitution relative to the reference strain (NC_004162.2). Dark red cells indicate the presence of a mutation at the corresponding position. Discussion Sri Lanka is currently experiencing a large CHIKV outbreak after 16 years. Patients with clinical features suggestive of Chikungunya were reported from the National Institute of Infectious Diseases, Colombo, Sri Lanka in 2024, were confirmed by real-time PCR by routine arbovirus surveillance carried out by us. We found that the CHIKV strains causing the current outbreak were similar to the current circulating CHIKV strains in India, Pakistan and Bangladesh, while being different to the CHIKV strains that caused the last Chikungunya outbreak in Sri Lanka during 2006 to 2008. Interestingly, while the E:226V mutation which has been associated with Aedes albopictus transmission efficiency, was absent in all 2025 samples [ 10 ], it carried the E1:K211E and E2: V264A, which result in enhanced viral fitness within Aedes aegpti [ 19 ]. Therefore, these mutations could lead to higher transmission rates in urban areas, where the predominant Aedes specifies is Aedes aegpti . Indeed, the higher evolutionary rates observed in the Sri Lankan CHIKV 2025 strains (7.20 × 10⁻⁴ substitutions/site/year), could be a result of intense transmission. The emergence of the E1:K211E/E2:V264A sub lineage of the IOL, has also been responsible for the large Chikungunya outbreak reported in Malaysia in 2021 [ 20 ]. Apart from the mutations detected with the E1-E3 protein, many mutations were detected within the non-structural proteins such as nsP1:I167V, nsP2:I171V, nsP2:T224I, nsP3:A382I, nsp4: V21A and nsP4:S90A. Although the significance of mutations, which are also seen in the most recent circulating CHIKV strains in South Asia are unknown, the non-structural proteins of CHIKV are unknown to interact with host proteins and have also shown to be important in immune evasion [ 21 , 22 ]. Interestingly, the Sri Lankan 2025 CHIV strains showed unique mutations within nsP3:T224I and nsP4: S90A. These mutations have not been previously reported, and it would be important to find out how these mutations within the non-structural proteins affect viral replication and virulence within the host. In summary, we have characterized the CHIKV strains responsible for current ongoing large outbreak in Sri Lanka. This strain is similar to currently circulating CHIKV strains in the region, although it has certain unique mutations. Given that Sri Lanka did not have outbreaks with CHIKV for 16 years (from 2008 to end of 2024), despite evidence of the virus circulating in certain regions in Sri Lanka [ 12 ], it would be important to understand the factors that led to emergence of CHIKV that resulted in this outbreak. Data Availability The data is available in the manuscript, figures and the supplementary data. Supplementary Figure 1:Maximum likelihood phylogenetic tree of 904 complete chikungunya virus (CHIKV) genome sequences reconstructed using IQ-TREE (GTR+I+R4 model, 1000 ultrafast bootstrap replicates). The dataset includes six newly sequenced Sri Lankan CHIKV genomes from 2025 (PV660466–PV660471). The tree reveals four well-supported monophyletic lineages. Sri Lankan sequences from 2025 cluster within the Indian Ocean Lineage (IOL) clade. Clade shading corresponds to lineage classification: West African (WA, purple), Asian (red), East/Central/South African (ECSA, green), and Indian Ocean Lineage (IOL, blue). Acknowledgement We are grateful to NIH, USA (grant number 5U01AI151788-02) and Gates Foundation (Investment ID INV-064510) for funding this study. 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Share The Re-emergence of Chikungunya in Sri Lanka: A Genomic investigation Tibutius Thanesh Pramanayagam Jayadas , Malithi de Silva , Bhagya Senadheera , Laksiri Gomes , Heshan Kuruppu , Radanee Rathnapriya , Farha Bary , Sahan Madusanka , Ananda Wijewickrama , Damayanthi Idampitiya , Suranga Manilgama , Ruklanthi de Alwis , Chandima Jeewandara , Gathsaurie Neelika Malavige medRxiv 2025.05.23.25328206; doi: https://doi.org/10.1101/2025.05.23.25328206 Share This Article: Copy Citation Tools The Re-emergence of Chikungunya in Sri Lanka: A Genomic investigation Tibutius Thanesh Pramanayagam Jayadas , Malithi de Silva , Bhagya Senadheera , Laksiri Gomes , Heshan Kuruppu , Radanee Rathnapriya , Farha Bary , Sahan Madusanka , Ananda Wijewickrama , Damayanthi Idampitiya , Suranga Manilgama , Ruklanthi de Alwis , Chandima Jeewandara , Gathsaurie Neelika Malavige medRxiv 2025.05.23.25328206; doi: https://doi.org/10.1101/2025.05.23.25328206 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Infectious Diseases (except HIV/AIDS) Subject Areas All Articles Addiction Medicine (568) Allergy and Immunology (863) Anesthesia (300) Cardiovascular Medicine (4435) Dentistry and Oral Medicine (444) Dermatology (382) Emergency Medicine (608) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1509) Epidemiology (15229) Forensic Medicine (30) Gastroenterology (1124) Genetic and Genomic Medicine (6600) Geriatric Medicine (668) Health Economics (997) Health Informatics (4538) Health Policy (1368) Health Systems and Quality Improvement (1613) Hematology (541) HIV/AIDS (1264) Infectious Diseases (except HIV/AIDS) (15916) Intensive Care and Critical Care Medicine (1103) Medical Education (623) Medical Ethics (146) Nephrology (667) Neurology (6599) Nursing (346) Nutrition (998) Obstetrics and Gynecology (1144) Occupational and Environmental Health (957) Oncology (3333) Ophthalmology (974) Orthopedics (369) Otolaryngology (420) Pain Medicine (436) Palliative Medicine (130) Pathology (663) Pediatrics (1693) Pharmacology and Therapeutics (691) Primary Care Research (711) Psychiatry and Clinical Psychology (5447) Public and Global Health (9232) Radiology and Imaging (2198) Rehabilitation Medicine and Physical Therapy (1370) Respiratory Medicine (1196) Rheumatology (593) Sexual and Reproductive Health (712) Sports Medicine (530) Surgery (712) Toxicology (99) Transplantation (289) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'a00cf75f28f106eb',t:'MTc3OTYzMjY5MQ=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();