Intra- vs. Interhost Evolution of SARS-CoV-2 Driven by Uncorrelated Selection-The Evolution Thwarted

Tradeoffs between proliferation and transmission in virus evolution- insights from evolutionary and functional analyses of SARS-CoV-2

To be successful, a virus must maintain high between-host transmissibility while also effectively adapting within hosts. The impact of these potentially conflicting demands on viral genetic diversity and adaptation remains largely unexplored. These modes of adaptation can induce uncorrelated selection, bring mutations that enhance certain fitness aspects at the expense of others to high freqency, and contribute to the maintenance of genetic variation. The vast wealth of SARS-CoV-2 genetic data gathered from within and across hosts offers an unparalleled opportunity to test the above hypothesis. By analyzing a large set of SARS-CoV-2 sequences (~ 2 million) collected from early 2020 to mid-2021, we found that high frequency mutations within hosts are sometimes detrimental during between-host transmission. This highlights potential inverse selection pressures within- versus between-hosts. We also identified a group of nonsynonymous changes likely maintained by pleiotropy, as their frequencies are significantly higher than neutral expectation, yet they have never experienced clonal expansion. Analyzing one such mutation, spike M1237I, reveals that spike I1237 boosts viral assembly but reduces in vitro transmission, highlighting its pleiotropic effect. Though they make up about 2% of total changes, these types of variants represent 37% of SARS-CoV-2 genetic diversity. These mutations are notably prevalent in the Omicron variant from late 2021, hinting that pleiotropy may promote positive epistasis and new successful variants. Estimates of viral population dynamics, such as population sizes and transmission bottlenecks, assume neutrality of within-host variation. Our demonstration that these changes may affect fitness calls into question the robustness of these estimates.

SARS-CoV-2 genomic evolution during a severe and long-lasting omicron infection under antiviral therapy

BACKGROUND

Prolonged SARS-CoV-2 infection observed in immunocompromised individuals even in the presence of antiviral treatment provides opportunities for viruses to evolve in immune escape and drug-resistant variants.

CASE PRESENTATION

A 72-year-old male with IgG4-related disease was admitted to the Emergency Department of a city Hospital in Milan and then transferred to Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico in December 2023, due to respiratory distress due to SARS-CoV-2 infection diagnosed in November 2023. After 117 days since the onset of the infection, and two cycles of sotrovimab/remdesivir combined therapy, the clinical improvement allowed the hospital discharge, notwithstanding the persistent SARS-CoV-2 positivity. Fifteen days later, the patient was re-admitted to the hospital due to worsening clinical conditions. After a third cycle of sotrovimab/remdesivir combined therapy prolonged with nirmatrelvir/ritonavir, nasopharyngeal load dropped and clinical conditions improved, ending with a successful discharge. SARS-CoV-2 whole genome sequences, obtained at six time-points of infection, showed an FL.1.5.1 recombinant form infection and a genetic distance of median (IQR) 0.00052 (0.00041-0.00066) similar to the genetic distance observed among the 43 contemporaneous FL.1.5.1 recombinant forms (p = 0.098). De novo SNPs were observed at all time points, with a peak (n = 70) at day 133 of infection, corresponding to the time of the second hospitalization. Six non-synonymous mutations (three in the RdRp and three in the spike protein, four of them known to be associated with drug resistance) appeared transiently, after the third and fourth course of sotrovimab 500 mg/remdesivir combination. Five de novo SNPs, three of them in the spike protein, were fixed over the long-lasting infection. The spike N856K, associated with reduced fusogenicity and infectivity in Omicron BA.1, was completely replaced by constitutive N at day 136.

CONCLUSIONS

This clinical case confirms the intra-host evolution dynamics of SARS-CoV-2 in an immunocompromised, prolonged-infected individual, involving positions associated with drug resistance and fusogenic traits of SARS-CoV-2. These results underscore the importance of the early detection of SARS-CoV-2 infection in immunocompromised individuals, and its rapid containment using highly effective treatment, to limit serious complications and the risk of new and potentially concerning viral variants emergence.

Within-Host Fitness and Antigenicity Shift Are Key Factors Influencing the Prevalence of Within-Host Variations in the SARS-CoV-2 S Gene

Within-host evolution plays a critical role in shaping the diversity of SARS-CoV-2. However, understanding the primary factors contributing to the prevalence of intra-host single nucleotide variants (iSNVs) in the viral population remains elusive. Here, we conducted a comprehensive analysis of over 556,000 SARS-CoV-2 sequencing data and prevalence data of different SARS-CoV-2 S protein amino acid mutations to elucidate key factors influencing the prevalence of iSNVs in the SARS-CoV-2 S gene. Within-host diversity analysis revealed the presence of mutational hotspots within the S gene, mainly located in NTD, RBD, TM, and CT domains. Additionally, we generated a single amino acid resolution selection status map of the S protein. We observed a significant variance in within-host fitness among iSNVs in the S protein. The majority of iSNVs exhibited low to no within-host fitness and displayed low alternate allele frequency (AAF), suggesting that they will be eliminated due to the narrow transmission bottleneck of SARS-CoV-2. Notably, iSNVs with moderate AAFs (0.06-0.12) were found to be more prevalent than those with high AAFs. Furthermore, iSNVs with the potential to alter antigenicity were more prevalent. These findings underscore the significance of within-host fitness and antigenicity shift as two key factors influencing the prevalence of iSNVs in the SARS-CoV-2 S gene.

An Expanding Universe of Mutational Signatures and Its Rapid Evolution in Single-Stranded RNA Viruses

The study of mutational processes in somatic genomes has gained recent momentum, uncovering a wide array of endogenous and exogenous factors associated with somatic changes. However, the overall landscape of mutational processes in germline mutations across the tree of life and associated evolutionary driving forces are rather unclear. In this study, we analyzed mutational processes in single-stranded RNA (ssRNA) viruses which are known to jump between different hosts with divergent exogenous environments. We found that mutational spectra in different ssRNA viruses differ significantly and are mainly associated with their genetic divergence. Surprisingly, host environments contribute much less significantly to the mutational spectrum, challenging the prevailing view that the exogenous cellular environment is a major determinant of the mutational spectrum in viruses. To dissect the evolutionary forces shaping viral spectra, we selected two important scenarios, namely the inter-host evolution between different viral strains as well as the intra-host evolution. In both scenarios, we found mutational spectra change significantly through space and time, strongly correlating with levels of natural selection. Combining the mutations across all ssRNA viruses, we identified a suite of mutational signatures with varying degrees of similarity to somatic signatures in humans, indicating universal and divergent mutational processes across the tree of life. Taken together, we unraveled an unprecedented dynamic landscape of mutational processes in ssRNA viruses, pinpointing important evolutionary forces shaping fast evolution of mutational spectra in different species.

Multi-Organ Spread and Intra-Host Diversity of SARS-CoV-2 Support Viral Persistence, Adaptation, and a Mechanism That Increases Evolvability

Intra-host diversity is an intricate phenomenon related to immune evasion, antiviral resistance, and evolutionary leaps along transmission chains. SARS-CoV-2 intra-host variation has been well-evidenced from respiratory samples. However, data on systemic dissemination and diversification are relatively scarce and come from immunologically impaired patients. Here, the presence and variability of SARS-CoV-2 were assessed among 71 tissue samples obtained from multiple organs including lung, intestine, heart, kidney, and liver from 15 autopsies with positive swabs and no records of immunocompromise. The virus was detected in most organs in the majority of autopsies. All organs presented intra-host single nucleotide variants (iSNVs) with low, moderate, and high abundances. The iSNV abundances observed within different organs indicate that the virus can mutate at one host site and subsequently spread to other parts of the body. In agreement with previous data from respiratory samples, our lung samples presented no more than 10 iSNVs each. But interestingly, when analyzing different organs we were able to detect between 11 and 45 iSNVs per case. Our results indicate that SARS-CoV-2 can replicate, and evolve in a compartmentalized manner, in different body sites, which agrees with the "viral reservoir" theory. We elaborate on how compartmentalized evolution in multiple organs may contribute to SARS-CoV-2 evolving so rapidly despite the virus having a proofreading mechanism.

Sequence signatures within the genome of SARS-CoV-2 can be used to predict host source

We conducted an in silico analysis to better understand the potential factors impacting host adaptation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in white-tailed deer, humans, and mink due to the strong evidence of sustained transmission within these hosts. Classification models trained on single nucleotide and amino acid differences between samples effectively identified white-tailed deer-, human-, and mink-derived SARS-CoV-2. For example, the balanced accuracy score of Extremely Randomized Trees classifiers was 0.984 ± 0.006. Eighty-eight commonly identified predictive mutations are found at sites under strong positive and negative selective pressure. A large fraction of sites under selection (86.9%) or identified by machine learning (87.1%) are found in genes other than the spike. Some locations encoded by these gene regions are predicted to be B- and T-cell epitopes or are implicated in modulating the immune response suggesting that host adaptation may involve the evasion of the host immune system, modulation of the class-I major-histocompatibility complex, and the diminished recognition of immune epitopes by CD8+ T cells. Our selection and machine learning analysis also identified that silent mutations, such as C7303T and C9430T, play an important role in discriminating deer-derived samples across multiple clades. Finally, our investigation into the origin of the B.1.641 lineage from white-tailed deer in Canada discovered an additional human sequence from Michigan related to the B.1.641 lineage sampled near the emergence of this lineage. These findings demonstrate that machine-learning approaches can be used in combination with evolutionary genomics to identify factors possibly involved in the cross-species transmission of viruses and the emergence of novel viral lineages.IMPORTANCESevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible virus capable of infecting and establishing itself in human and wildlife populations, such as white-tailed deer. This fact highlights the importance of developing novel ways to identify genetic factors that contribute to its spread and adaptation to new host species. This is especially important since these populations can serve as reservoirs that potentially facilitate the re-introduction of new variants into human populations. In this study, we apply machine learning and phylogenetic methods to uncover biomarkers of SARS-CoV-2 adaptation in mink and white-tailed deer. We find evidence demonstrating that both non-synonymous and silent mutations can be used to differentiate animal-derived sequences from human-derived ones and each other. This evidence also suggests that host adaptation involves the evasion of the immune system and the suppression of antigen presentation. Finally, the methods developed here are general and can be used to investigate host adaptation in viruses other than SARS-CoV-2.