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CATCH-EVseq, an Ultra-Sensitive Capture Assay to Monitor Human Enterovirus RNA

Year: 2026
Type: article
Abstract: The detection of low-abundance viral RNA in chronic or persistent infections remains a major challenge in virology, constrained by the sensitivity and specificity of traditional methods. One such infection, chronic enterovirus (EV) infection, has been proposed as a potential underlying factor in Myalgic Encephalomyelitis (ME), although this hypothesis remains debated. Supporting evidence for EVs as a viral trigger includes historical spatiotemporal overlaps between ME outbreaks and poliomyelitis epidemics, frequent reports of “flu-like” illness at disease onset, seasonal outbreaks patterns, and serological findings. To address the problem of EV detection, we developed CATCH-EVseq, an ultra-sensitive platform built on the CATCH framework. By integrating high-throughput sequencing with cDNA capture using 49,847 probes targeting 3410 EV genomes, CATCH-EVseq achieved a detection limit in artificially created samples as low as one copy in a microgram of RNA for two out of three biological replicates. Additionally, spike-in controls allow for rigorous validation of the capture and sequencing throughout the CATCH-EVseq procedure. When applied to a small number of blood samples from both ME patients and healthy controls, CATCH-EVseq detected no EV RNA, either in direct assays or after in vitro viral amplification. While these results do not support the presence of circulating EV RNA in the blood of individuals with ME, they do not rule out persistent infection in other tissues or organs. Critically, CATCH-EVseq establishes a robust, ultra-sensitive framework for future investigations of low-level EV persistence in biopsies, post-mortem tissues, or other clinical contexts where chronic enterovirus infection is suspected.
Institution: Cornell University
Language: English
Field: Medicine
Open Access status: gold
Estimated APC paid: $3,499
OpenAlex ID: W7221649247
FWCI:
Cites: 18
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