Congenital Zika virus infection impacts on male mouse offspring's reproductive biology.
Natália Teixeira WnukAndré Felipe Almeida FigueiredoTalita de Oliveira FariasMarcos Rocha Gouvêa BrenerSamyra Maria Dos Santos Nassif LacerdaVidyleison Neves CamargosPaulo Henrique AmaralLídia Maria AndradeMaria Ivonete Nogueira SilvaRoberta Araujo LopesRaphael Escorsim SzawkaJuan Carlos GonzálezMauro Martins TeixeiraDanielle da Glória de SouzaVivian Vasconcelos CostaGuilherme Mattos Jardim CostaPublished in: Reproduction (Cambridge, England) (2024)
Infection with ZIKV during pregnancy is associated with fetal developmental problems. Although neurological issues are being explored more in experimental studies, limited research has focused on the reproductive health consequences for offspring born to infected mothers. In this context, this study aimed to assess the impact of ZIKV infection during pregnancy on the testes and sperm of adult male offspring. Female mice were intraperitoneally inoculated with a Brazil strain of ZIKV during the 5.5th day of embryonic gestation. The offspring were evaluated 12 weeks after birth to analyze cellular and molecular changes in the testes and sperm. A novel approach combining variable-angle spectroscopic ellipsometry and machine learning modeling was also introduced for sperm sample analysis. The study revealed the presence of ZIKV protein in the testis parenchyma of adult male offspring born to infected mothers. It was shown that the testes exhibited altered steroidogenesis and inflammatory mediators, in addition to significant issues with spermiogenesis that resulted in sperm with DNA fragmentation, head defects, and protamination failure. Additionally, sperm dielectric properties and artificial intelligence showed potential for rapid identification and classification of sperm samples from infected mice. These findings provide crucial insights into the reproductive risks for men born from ZIKV-infected pregnant women.
Keyphrases
- zika virus
- machine learning
- gestational age
- artificial intelligence
- high fat diet
- pregnant women
- deep learning
- low birth weight
- big data
- preterm infants
- preterm birth
- adipose tissue
- single molecule
- high fat diet induced
- high resolution
- molecular docking
- human health
- risk assessment
- binding protein
- single cell
- skeletal muscle
- young adults
- climate change
- optical coherence tomography
- circulating tumor
- sensitive detection
- childhood cancer
- circulating tumor cells