tetano
Editor, Senior Moderator
Virus Evol
. 2025 Jun 15;11(1):veaf047.
doi: 10.1093/ve/veaf047. eCollection 2025. Diverse patterns of intra-host genetic diversity in chronically infected SARS-CoV-2 patients
Adi Ben Zvi[SUP] 1 2 [/SUP], Natalie Rutsinsky[SUP] 1 [/SUP], Bar Jacobi[SUP] 1 2 [/SUP], Ido Fabian[SUP] 1 2 [/SUP], Shir T Segev[SUP] 1 [/SUP], Sheri Harari[SUP] 1 2 [/SUP], Suzy Meijer[SUP] 3 4 [/SUP], Yael Paran[SUP] 3 4 [/SUP], Adi Stern[SUP] 1 2 [/SUP]
Affiliations
In rare individuals with a severely immunocompromised system, chronic infections of SARS-CoV-2 may develop, where the virus replicates in the body for months. Sequencing of some chronic infections has uncovered dramatic adaptive evolution and fixation of mutations reminiscent of lineage-defining mutations of variants of concern (VOCs). This has led to the prevailing hypothesis that VOCs emerged from chronic infections. To examine the mutation dynamics and intra-host genomic diversity of SARS-CoV-2 during chronic infections, we focused on a cohort of nine immunocompromised individuals with chronic infections and performed longitudinal sequencing of viral genomes. We showed that sequencing errors may cause erroneous inference of genetic variation, and to overcome this, we used duplicate sequencing across patients and time points, allowing us to distinguish errors from low-frequency mutations. We further found recurrent low-frequency mutations that we flagged as most likely sequencing errors. This stringent approach allowed us to reliably infer low-frequency mutations and their dynamics across time. We applied a generalized linear model that accounts for gradual mutation accumulation and episodic divergence shifts to infer a synonymous mutation rate of 1.9 × 10[SUP]-6[/SUP] mutations/site/day. Using the same framework, we inferred patient-specific non-synonymous divergence rates that exhibited marked heterogeneity across individuals. This framework also uncovered episodes of high non-synonymous rates consistent with selective sweeps or subpopulation replacement. Overall, we observed diverse evolutionary dynamics across chronic infections, highlighting variation in patient-specific selection pressures and within-host demographic histories that shape intra-host viral evolution.
Keywords: COVID-19; SARS-Coronavirus-2; chronic infections; intra-host evolution.
. 2025 Jun 15;11(1):veaf047.
doi: 10.1093/ve/veaf047. eCollection 2025. Diverse patterns of intra-host genetic diversity in chronically infected SARS-CoV-2 patients
Adi Ben Zvi[SUP] 1 2 [/SUP], Natalie Rutsinsky[SUP] 1 [/SUP], Bar Jacobi[SUP] 1 2 [/SUP], Ido Fabian[SUP] 1 2 [/SUP], Shir T Segev[SUP] 1 [/SUP], Sheri Harari[SUP] 1 2 [/SUP], Suzy Meijer[SUP] 3 4 [/SUP], Yael Paran[SUP] 3 4 [/SUP], Adi Stern[SUP] 1 2 [/SUP]
Affiliations
- PMID: 40662161
- PMCID: PMC12257100
- DOI: 10.1093/ve/veaf047
In rare individuals with a severely immunocompromised system, chronic infections of SARS-CoV-2 may develop, where the virus replicates in the body for months. Sequencing of some chronic infections has uncovered dramatic adaptive evolution and fixation of mutations reminiscent of lineage-defining mutations of variants of concern (VOCs). This has led to the prevailing hypothesis that VOCs emerged from chronic infections. To examine the mutation dynamics and intra-host genomic diversity of SARS-CoV-2 during chronic infections, we focused on a cohort of nine immunocompromised individuals with chronic infections and performed longitudinal sequencing of viral genomes. We showed that sequencing errors may cause erroneous inference of genetic variation, and to overcome this, we used duplicate sequencing across patients and time points, allowing us to distinguish errors from low-frequency mutations. We further found recurrent low-frequency mutations that we flagged as most likely sequencing errors. This stringent approach allowed us to reliably infer low-frequency mutations and their dynamics across time. We applied a generalized linear model that accounts for gradual mutation accumulation and episodic divergence shifts to infer a synonymous mutation rate of 1.9 × 10[SUP]-6[/SUP] mutations/site/day. Using the same framework, we inferred patient-specific non-synonymous divergence rates that exhibited marked heterogeneity across individuals. This framework also uncovered episodes of high non-synonymous rates consistent with selective sweeps or subpopulation replacement. Overall, we observed diverse evolutionary dynamics across chronic infections, highlighting variation in patient-specific selection pressures and within-host demographic histories that shape intra-host viral evolution.
Keywords: COVID-19; SARS-Coronavirus-2; chronic infections; intra-host evolution.