Post-acute infection syndromes may develop after acute viral disease¹. Infection with SARS-CoV-2 can result in the development of a post-acute infection syndrome known as long COVID. Individuals with long COVID frequently report unremitting fatigue, post-exertional malaise, and a variety of cognitive and autonomic dysfunctions^2–4. However, the biological processes that are associated with the development and persistence of these symptoms are unclear. Here 275 individuals with or without long COVID were enrolled in a cross-sectional study that included multidimensional immune phenotyping and unbiased machine learning methods to identify biological features associated with long COVID. Marked differences were noted in circulating myeloid and lymphocyte populations relative to the matched controls, as well as evidence of exaggerated humoral responses directed against SARS-CoV-2 among participants with long COVID. Furthermore, higher antibody responses directed against non-SARS-CoV-2 viral pathogens were observed among individuals with long COVID, particularly Epstein–Barr virus. Levels of soluble immune mediators and hormones varied among groups, with cortisol levels being lower among participants with long COVID. Integration of immune phenotyping data into unbiased machine learning models identified the key features that are most strongly associated with long COVID status. Collectively, these findings may help to guide future studies into the pathobiology of long COVID and help with developing relevant biomarkers.

Research has shown that RNA virus populations are highly variable, most likely due to low fidelity replication of RNA genomes. It is generally assumed that populations of DNA viruses will be less complex and show reduced variability when compared to RNA viruses. Here, we describe the use of high throughput sequencing for a genome wide study of viral populations from urine samples of neonates with congenital human cytomegalovirus (HCMV) infections. We show that HCMV intrahost genomic variability, both at the nucleotide and amino acid level, is comparable to many RNA viruses, including HIV. Within intrahost populations, we find evidence of selective sweeps that may have resulted from immune-mediated mechanisms. Similarly, genome wide, population genetic analyses suggest that positive selection has contributed to the divergence of the HCMV species from its most recent ancestor. These data provide evidence that HCMV, a virus with a large dsDNA genome, exists as a complex mixture of genome types in humans and offer insights into the evolution of the virus. Human Cytomegalovirus (HCMV) is a dsDNA virus that is the leading source of birth defects associated with an infectious agent. There is currently no effective HCMV vaccine and few treatment strategies for congenital infections exist. Thus, a better understanding of HCMV infections is warranted. Limited data has shown that HCMV exists as a mixture of a few genotypes in human hosts. Here, we describe our use of high throughput sequencing to study the extent of genome wide variability within HCMV infections sampled from congenital infections. Surprisingly, we find that HCMV populations are as variable as quasispecies RNA viruses; it is commonly believed that DNA viruses are more genetically stable than RNA viruses, and thus produce homogenous populations. Additionally, we find evidence of evolutionary pressures acting on the HCMV genome, both within and among populations. These results provide the first evidence that diversity of DNA virus populations can be comparable to that of RNA virus populations.

Populations of human cytomegalovirus (HCMV), a large DNA virus, are highly polymorphic in patient samples, which may allow for rapid evolution within human hosts. To understand HCMV evolution, longitudinally sampled genomic populations from the urine and plasma of 5 infants with symptomatic congenital HCMV infection were analyzed. Temporal and compartmental variability of viral populations were quantified using high throughput sequencing and population genetics approaches. HCMV populations were generally stable over time, with ∼88% of SNPs displaying similar frequencies. However, samples collected from plasma and urine of the same patient at the same time were highly differentiated with approximately 1700 consensus sequence SNPs (1.2% of the genome) identified between compartments. This inter-compartment differentiation was comparable to the differentiation observed in unrelated hosts. Models of demography (i.e., changes in population size and structure) and positive selection were evaluated to explain the observed patterns of variation. Evidence for strong bottlenecks (>90% reduction in viral population size) was consistent among all patients. From the timing of the bottlenecks, we conclude that fetal infection occurred between 13–18 weeks gestational age in patients analyzed, while colonization of the urine compartment followed roughly 2 months later. The timing of these bottlenecks is consistent with the clinical histories of congenital HCMV infections. We next inferred that positive selection plays a small but measurable role in viral evolution within a single compartment. However, positive selection appears to be a strong and pervasive driver of evolution associated with compartmentalization, affecting ≥34 of the 167 open reading frames (∼20%) of the genome. This work offers the most detailed map of HCMV in vivo evolution to date and provides evidence that viral populations can be stable or rapidly differentiate, depending on host environment. The application of population genetic methods to these data provides clinically useful information, such as the timing of infection and compartment colonization. The large, dsDNA virus Human cytomegalovirus (HCMV) is the most genetically complex viral pathogen of humans. HCMV populations are highly variable, which may allow the virus to evolve in human hosts on short timescales. We tested this hypothesis by longitudinally sampling HCMV populations from the urine and/or plasma of congenitally infected infants. We found that HCMV is generally stable within a compartment, but rapidly evolves when crossing host compartments. In fact, HCMV sampled from two compartments of the same host is as different as HCMV collected from unrelated hosts. We used mathematical modeling and population genetic analysis to show that both a bottleneck (i.e., a reduction in population size) associated with compartment colonization as well as positive selection are necessary to explain the observed differences between compartments. We also conclude from these data that fetal infection in these patients occurred between 13–18 weeks gestational age, consistent with the timing of symptomatic congenital HCMV infections. This study is the most detailed investigation of DNA virus evolution in human hosts to date, provides a framework for the study of other viral infections using similar techniques, and will aid in the development of new antiviral therapies and vaccines.

Significance: Human cytomegalovirus (HCMV) is the leading cause of birth defects associated with infections and a leading cause of transplantation failure. This study reveals the patterns and limits of HCMV genomic diversity by performing a large-scale analysis of HCMV sequences sampled from human hosts, identifying the hot and cold spots of variability. We find that the diversity is unevenly distributed across three host compartments and show that HCMV populations of vascular compartments are genetically constrained while enriched for polymorphisms of glycoproteins and regulatory proteins. This work significantly advances our understanding of the genomic diversity of HCMV in humans and has clear implications for the development of therapeutics against HCMV.

Human cytomegalovirus (HCMV) has been found in malignant gliomas at variable frequencies with efforts to date focused on characterizing the role(s) of single gene products in disease. Here, we reexamined the HCMV prevalence in malignant gliomas using different methods and began to dissect the genetics of HCMV in tumors. HCMV DNA was found in 16/17 (94%) tumor specimens. Viral DNA copy numbers were found to be low and variable, ranging from 10 ² to 10 ⁶ copies/500 ng of total DNA. The tumor tissues had incongruences between viral DNA copy numbers and protein levels. However, nonlatent protein expression was detected in many tumors. The viral UL83 gene, encoding pp65, was found to segregate into five cancer-associated genotypes with a bias for amino acid changes in glioblastoma multiforme (GBM) in comparison to the low-grade tumors. Deep sequencing of a GBM-associated viral population resulted in 81,224 bp of genome coverage. Sequence analysis revealed the presence of intact open reading frames and higher numbers of high-frequency variations within the repeat long region compared to the unique long region, which harbors many core genes, and the unique short region ( P = 0.001). This observation was in congruence with phylogenetic analyses across replication-competent viral strains in databases. The tumor-associated viral population was less variable (π = 0.1% and π _AA = 0.08%) than that observed in other clinical infections. Moreover, 42/46 (91.3%) viral genes analyzed had dN/dS scores of <1, which is indicative of high amino acid sequence conservation. Taken together, these findings raise the possibility that replication-competent HCMV may exist in malignant gliomas.