Mixed cytomegalovirus genotypes in HIV positive mothers show compartmentalization and distinct patterns of transmission to infants
Abstract
Cytomegalovirus (CMV) is the commonest cause of congenital infection (cCMVi) and particularly so among infants born to HIV-infected women. Studies of cCMVi pathogenesis are complicated by the presence of multiple infecting maternal CMV strains, especially in HIV-positive women, and the large, recombinant CMV genome. Using newly developed tools to reconstruct CMV haplotypes, we demonstrate anatomic CMV compartmentalization in five HIV-infected mothers and identify the possibility of congenitally transmitted genotypes in three of their infants. A single CMV strain was transmitted in each congenitally infected case, and all were closely related to those that predominate in the cognate maternal cervix. Compared to non-transmitted strains, these congenitally transmitted CMV strains showed statistically significant similarities in 19 genes associated with tissue-tropism and immunomodulation. In all infants, incident superinfections with distinct strains from breast milk were captured during follow-up. The results represent potentially important new insights into the virologic determinants of early CMV infection.
Data availability
Sequence reads have been deposited in NCBI Sequence Read Archive under BioProject ID PRJNA605798.
Article and author information
Author details
Funding
EUFP7 (304875)
- Judith Breuer
UCL/UCLH NIHR Biomedical Research Centre
- Judith Breuer
Sir Henry Wellcome Fellowship
- Sofia Morfopoulou
Sir Henry Wellcome Fellowships
- Josephine Bryant
Wellcome Trust (204870)
- Paul Griffiths
NIH National Institute of Allergy and Infectious Diseases (AI087369)
- Jennifer A Slyker
NIH National Institute of Allergy and Infectious Diseases (AI027757)
- Jennifer A Slyker
NIH National Institute of Allergy and Infectious Diseases (AI076105)
- Carey Farquhar
NIH National Institute of Allergy and Infectious Diseases (AI087399)
- Carey Farquhar
National Institute of Child Health and Human Development (HD057773-01)
- Carey Farquhar
National Institute of Child Health and Human Development (HD054314)
- Carey Farquhar
Rosetreees Trust PhD Studentship (M876)
- Juanita Pang
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2020, Pang et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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- Developmental Biology
- Genetics and Genomics
New developmental programs can evolve through adaptive changes to gene expression. The annelid Streblospio benedicti has a developmental dimorphism, which provides a unique intraspecific framework for understanding the earliest genetic changes that take place during developmental divergence. Using comparative RNAseq through ontogeny, we find that only a small proportion of genes are differentially expressed at any time, despite major differences in larval development and life history. These genes shift expression profiles across morphs by either turning off any expression in one morph or changing the timing or amount of gene expression. We directly connect the contributions of these mechanisms to differences in developmental processes. We examine F1 offspring – using reciprocal crosses – to determine maternal mRNA inheritance and the regulatory architecture of gene expression. These results highlight the importance of both novel gene expression and heterochronic shifts in developmental evolution, as well as the trans-acting regulatory factors in initiating divergence.
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- Epidemiology and Global Health
- Genetics and Genomics
Background:
Maternal smoking has been linked to adverse health outcomes in newborns but the extent to which it impacts newborn health has not been quantified through an aggregated cord blood DNA methylation (DNAm) score. Here, we examine the feasibility of using cord blood DNAm scores leveraging large external studies as discovery samples to capture the epigenetic signature of maternal smoking and its influence on newborns in White European and South Asian populations.
Methods:
We first examined the association between individual CpGs and cigarette smoking during pregnancy, and smoking exposure in two White European birth cohorts (n=744). Leveraging established CpGs for maternal smoking, we constructed a cord blood epigenetic score of maternal smoking that was validated in one of the European-origin cohorts (n=347). This score was then tested for association with smoking status, secondary smoking exposure during pregnancy, and health outcomes in offspring measured after birth in an independent White European (n=397) and a South Asian birth cohort (n=504).
Results:
Several previously reported genes for maternal smoking were supported, with the strongest and most consistent association signal from the GFI1 gene (6 CpGs with p<5 × 10-5). The epigenetic maternal smoking score was strongly associated with smoking status during pregnancy (OR = 1.09 [1.07, 1.10], p=5.5 × 10-33) and more hours of self-reported smoking exposure per week (1.93 [1.27, 2.58], p=7.8 × 10-9) in White Europeans. However, it was not associated with self-reported exposure (p>0.05) among South Asians, likely due to a lack of smoking in this group. The same score was consistently associated with a smaller birth size (–0.37±0.12 cm, p=0.0023) in the South Asian cohort and a lower birth weight (–0.043±0.013 kg, p=0.0011) in the combined cohorts.
Conclusions:
This cord blood epigenetic score can help identify babies exposed to maternal smoking and assess its long-term impact on growth. Notably, these results indicate a consistent association between the DNAm signature of maternal smoking and a small body size and low birth weight in newborns, in both White European mothers who exhibited some amount of smoking and in South Asian mothers who themselves were not active smokers.
Funding:
This study was funded by the Canadian Institutes of Health Research Metabolomics Team Grant: MWG-146332.