CHIKVdb: A comprehensive genomic resource for chikungunya virus surveillance and outbreak response

Chikungunya virus (CHIKV) is a medically significant arbovirus transmitted by Aedes mosquitoes, responsible for chikungunya fever, which is characterized by severe and often chronic arthralgia. With increasing frequency and geographic expansion of CHIKV outbreaks in recent years, there is a pressing need for robust genomic surveillance and efficient outbreak response tools. However, existing public repositories of CHIKV genomic data are often fragmented, poorly annotated, and lack integrated analytical capabilities, limiting their utility during emergencies.

To address these limitations, we developed the Chikungunya Virus Database (CHIKVdb), a comprehensive genomic resource accessible at https://nmdc.cn/gcpathogen/chikv. CHIKVdb integrates 8,193 nucleotide sequences and 10,637 protein sequences from five major host categories across 99 countries, spanning 40 years. The database combines curated, high-quality genomic data with an online phylogenetic analysis platform, providing one-stop tools for source tracing, significantly streamlining traditionally complex bioinformatic workflows.

The web interface of CHIKVdb offers an intuitive overview of sequence data, with clickable metrics leading to detailed metadata tables that include isolate name, geographic origin, sampling time, and host etc. Additional subpages provide biological summaries, spatiotemporal visualizations, and a knowledge graph displaying research collaborations and curated literature. An interactive molecular surveillance module enables dynamic mapping of CHIKV spread from 2000 to 2024 at global and regional levels. A dedicated data submission portal also allows registered users to contribute new sequences.

Key analytical tools embedded within CHIKVdb include a source tracing system that reconstructs transmission chains via sequence alignment and phylogenetic inference, a Single Nucleotide Polymorphism (SNP) analysis tool for variation identification, and a genotype identification tool that matches queries against 327 experimentally validated reference sequences.

Analysis of global data reveals that India, Brazil, and Thailand contributed the most sequences. Humans and mosquitoes are the dominant hosts globally, though significant regional variations exist, for instance, China reported a high proportion (20%) of mosquito-derived sequences. Genotype distribution analysis shows that ECSA (East, Central and South Africa-Indian ocean linage) and ECSA-IOL (East, Central and South Africa-Indian ocean linage) are the most widespread lineages, with high prevalence in countries such as Singapore, Sudan, and Paraguay etc. Temporal analysis indicates consistent detection of human and mosquito-derived sequences, whereas wildlife hosts (e.g., bats, monkeys) appear only sporadically. The ECSA genotype has shown a marked increase in frequency since 2020, exceeding 93% after 2023.

Phylogenetic reconstruction of 76 high-quality genomes using CHIKVdb’s tools revealed potential transmission links between Bangladesh and Thailand, and distinct clustering of pre-2016 Asian-Pacific strains, highlighting spatiotemporal heterogeneity in CHIKV spread.

CHIKVdb addresses critical gaps in CHIKV genomic surveillance by integrating globally sourced sequences with standardized metadata and user-friendly analytical tools. It supports rapid response during outbreaks and facilitates research into transmission dynamics and viral evolution. Future efforts will focus on expanding wildlife host sequencing and enhancing regional genomic surveillance to further elucidate CHIKV ecology and inform public health strategies. The database will be regularly updated to ensure data currency and accuracy.

About Author

Dr. Linhuan Wu is a Principal Engineer at the Institute of Microbiology, Chinese Academy of Sciences (IMCAS), and serves as the Deputy Director of the National Microbiology Data Center (NMDC). She has long been engaged in methodological research and system development for the integration and mining of microbial big data. Dr. Wu has authored over thirty publications in renowned journals such as Nucleic Acids Research, Nature Communications, GigaScience, and BMC Genomics, and has applied for more than fourty software copyrights. She has led and participated in multiple national research initiatives, including the National 863 Program, the National Key R&D Program of China, and the Emergency Project of the CAS Strategic Priority Research Program.

In 2017, Dr. Wu was awarded the World Data System (WDS) Data Stewardship Award in recognition of her contributions to data management. In recent years, she has led the team at the National Microbiology Data Center (also serving as the World Data Center for Microbiology, WDCM) in constructing an internationally leading microbial big data platform ecosystem. To improve the accuracy and efficiency of data sharing among microbial communities, she spearheaded the design and establishment of ISO 21710:2020—Biotechnology—Specification on data management and publication in microbial resource centers—which standardizes information management and data sharing for microbial resources.

As the chair of the Global Catalogue of Microorganisms (GCM), Dr. Wu pioneered the development of a global data sharing platform that integrates data from 520,000 microbial strains held across 148 microbial resource centers in 52 countries. She also acts as the Chief Scientist of the WDCM and previously served as Secretary of the CODATA Working Group on Advancing Informatics for Microbiology.

Digital Object Identifier (DOI): 10.1016/j.hlife.2025.09.001