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.
SARS-CoV-2 infection can result in the development of a constellation of persistent sequelae following acute disease called post-acute sequelae of COVID-19 (PASC) or Long COVID. Individuals diagnosed with Long COVID frequently report unremitting fatigue, post-exertional malaise, and a variety of cognitive and autonomic dysfunctions; however, the basic biological mechanisms responsible for these debilitating symptoms are unclear. Here, 215 individuals were included in an exploratory, cross-sectional study to perform multi-dimensional immune phenotyping in conjunction with machine learning methods to identify key immunological features distinguishing Long COVID. Marked differences were noted in specific circulating myeloid and lymphocyte populations relative to matched control groups, as well as evidence of elevated humoral responses directed against SARS-CoV-2 among participants with Long COVID. Further, unexpected increases were observed in antibody responses directed against non-SARS-CoV-2 viral pathogens, particularly Epstein-Barr virus. Analysis of circulating immune mediators and various hormones also revealed pronounced differences, with levels of cortisol being uniformly lower among participants with Long COVID relative to matched control groups. Integration of immune phenotyping data into unbiased machine learning models identified significant distinguishing features critical in accurate classification of Long COVID, with decreased levels of cortisol being the most significant individual predictor. These findings will help guide additional studies into the pathobiology of Long COVID and may aid in the future development of objective biomarkers for Long COVID.
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.
Human cytomegalovirus (HCMV) exhibits surprisingly high genomic diversity during natural infection although little is known about the limits or patterns of HCMV diversity among humans. To address this deficiency, we analyzed genomic diversity among congenitally infected infants. We show that there is an upper limit to HCMV genomic diversity in these patient samples, with ∼25% of the genome being devoid of polymorphisms. These low diversity regions were distributed across 26 loci that were preferentially located in DNA-processing genes. Furthermore, by developing, to our knowledge, the first genome-wide mutation and recombination rate maps for HCMV, we show that genomic diversity is positively correlated with these two rates. In contrast, median levels of viral genomic diversity did not vary between putatively single or mixed strain infections. We also provide evidence that HCMV populations isolated from vascular compartments of hosts from different continents are genetically similar and that polymorphisms in glycoproteins and regulatory proteins are enriched in these viral populations. This analysis provides the most highly detailed map of HCMV genomic diversity in human hosts to date and informs our understanding of the distribution of HCMV genomic diversity within human hosts.human cytomegalovirus | HCMV | congenital CMV | virology | evolution
Human papillomavirus type 16 (HPV-16) E2 protein negatively regulates transcription of the E6 and E7 genes. This study was done to test the hypothesis that methylation of the HPV 16 long control region (LCR) is overrepresented among cervical cancer (CaCx) cases compared to cytologically normal controls harboring intact E2 gene. Methylation of the E2 binding site (E2BS-I), proximal to the P97 promoter, was assessed by HpaII/ MspI restriction digestion while McrBC digestion was used to assess LCR-E6 (7289-540) for 57 CaCx samples and 15 normal controls. E2BS-I methylation was found to be significantly higher (56.14%) in cases compared to (20%) controls [OR(age-adjusted) (95% CI): 4.53 (1.05-19.43) p=0.042]. The difference between cases (54.39%) and controls (40%) with respect to LCR-E6 methylation status [OR(age-adjusted) (95% CI): 1.77(0.5-6.3); p=0.38] was not significant. Sequencing of a randomly selected set of 13 methylated malignant samples revealed absence or rare presence, of methylation at CpGs 7579, 7535, 7683 and 7862 respectively. Methylation was found to be more at CpGs within E2 binding sites proximal to the P97 promoter. These results indicate the involvement of E2 binding site methylation in presence of intact E2, leading to loss of E2 repressor activity in CaCx.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.