tetano
Editor, Senior Moderator
Microbiol Spectr
. 2026 Sep 14:e0180626.
doi: 10.1128/spectrum.01806-26. Online ahead of print.
Kyle A Long # 1 2 , Adrian C Paskey # 1 2 , Bishwo N Adhikari 1 3 , Anthony C Fries 4 , Katrin Mende 5 6 , Stephanie A Richard 5 7 , Francisco Malagon 1 2 , Regina Z Cer 1 , Robin H Miller 1 2 , J Alexander Chitty 1 2 , Logan J Voegtly 1 2 , Haven Miner 1 2 , Charlotte Lanteri 5 , David R Tribble 5 , Brian K Agan 5 7 , Mark P Simons 5 , Timothy H Burgess 5 , Simon D Pollett 5 7 , Kimberly A Bishop-Lilly 1
Affiliations Expand
Mixed-genotype severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections are a concern due to the potential generation of novel recombinants that give rise to new variants. To better understand intra-host viral dynamics, we analyzed specimens from 24 participants from the U.S. Military Health System's Epidemiology, Immunology, and Clinical Characteristics of Emerging Infectious Diseases with Pandemic Potential COVID-19 cohort with suspected mixed-genotype SARS-CoV-2 infections. From an initial 24 suspected cases, we confirmed 17 as genuine coinfections and graded them by evidence: 7 were "strong"; 4 were "moderate"; 6 were "weak"; and 7 were deemed unlikely to be true mixed-genotype infections. Access to swabs from multiple body sites across the course of infection allowed us to observe compartmentalization and shifts in variant dominance that would have been missed by a single-timepoint analysis, as well as one recombinant Omicron BA.1/BA.2 genome. By using an evidence-based bioinformatic framework to assess sequencing data from well-characterized clinical cases, we distinguished genuine coinfections from bioinformatic artifacts. Our findings emphasize the importance of both extensive specimen collection and careful bioinformatic approaches in ascertaining dual genotype infections.
Importance: Novel recombinants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) arise from coinfections with different lineages, but mixed infections are not screened for despite risk to public health, and most surveillance relies on single swabs. We analyzed a longitudinal data set with specimens from multiple body sites, providing an opportunity to assess intra-host dynamics. To distinguish true coinfection from bioinformatic artifacts with confidence, we applied a framework that grades evidence for mixed genotypes by incorporating lineage and clade with manually validated variant calls. This allowed investigation beyond abundance levels of mixed genotypes within a single specimen, including observations of compartmentalization and a recombinant virus. This work enables further study of evolutionary, immunological, and clinical implications of mixed SARS-CoV-2 genotypes. Detecting dual-genotype infections and discriminating between true dual-genotype infection vs potential bioinformatics-based artifacts support public health and military readiness. These efforts provide evidence to bolster decision-making in molecular epidemiological studies to track transmission and for the choice of effective countermeasures.
Keywords: SARS-CoV-2; bioinformatics; mixed-genotype infection; whole genome sequencing.
. 2026 Sep 14:e0180626.
doi: 10.1128/spectrum.01806-26. Online ahead of print.
Longitudinal characterization of mixed-genotype SARS-CoV-2 infections in a military cohort reveals compartmentalized viral populations
Kyle A Long # 1 2 , Adrian C Paskey # 1 2 , Bishwo N Adhikari 1 3 , Anthony C Fries 4 , Katrin Mende 5 6 , Stephanie A Richard 5 7 , Francisco Malagon 1 2 , Regina Z Cer 1 , Robin H Miller 1 2 , J Alexander Chitty 1 2 , Logan J Voegtly 1 2 , Haven Miner 1 2 , Charlotte Lanteri 5 , David R Tribble 5 , Brian K Agan 5 7 , Mark P Simons 5 , Timothy H Burgess 5 , Simon D Pollett 5 7 , Kimberly A Bishop-Lilly 1
Affiliations Expand
- PMID: 42734363
- DOI: 10.1128/spectrum.01806-26
Abstract
Mixed-genotype severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections are a concern due to the potential generation of novel recombinants that give rise to new variants. To better understand intra-host viral dynamics, we analyzed specimens from 24 participants from the U.S. Military Health System's Epidemiology, Immunology, and Clinical Characteristics of Emerging Infectious Diseases with Pandemic Potential COVID-19 cohort with suspected mixed-genotype SARS-CoV-2 infections. From an initial 24 suspected cases, we confirmed 17 as genuine coinfections and graded them by evidence: 7 were "strong"; 4 were "moderate"; 6 were "weak"; and 7 were deemed unlikely to be true mixed-genotype infections. Access to swabs from multiple body sites across the course of infection allowed us to observe compartmentalization and shifts in variant dominance that would have been missed by a single-timepoint analysis, as well as one recombinant Omicron BA.1/BA.2 genome. By using an evidence-based bioinformatic framework to assess sequencing data from well-characterized clinical cases, we distinguished genuine coinfections from bioinformatic artifacts. Our findings emphasize the importance of both extensive specimen collection and careful bioinformatic approaches in ascertaining dual genotype infections.
Importance: Novel recombinants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) arise from coinfections with different lineages, but mixed infections are not screened for despite risk to public health, and most surveillance relies on single swabs. We analyzed a longitudinal data set with specimens from multiple body sites, providing an opportunity to assess intra-host dynamics. To distinguish true coinfection from bioinformatic artifacts with confidence, we applied a framework that grades evidence for mixed genotypes by incorporating lineage and clade with manually validated variant calls. This allowed investigation beyond abundance levels of mixed genotypes within a single specimen, including observations of compartmentalization and a recombinant virus. This work enables further study of evolutionary, immunological, and clinical implications of mixed SARS-CoV-2 genotypes. Detecting dual-genotype infections and discriminating between true dual-genotype infection vs potential bioinformatics-based artifacts support public health and military readiness. These efforts provide evidence to bolster decision-making in molecular epidemiological studies to track transmission and for the choice of effective countermeasures.
Keywords: SARS-CoV-2; bioinformatics; mixed-genotype infection; whole genome sequencing.