Exposed, uninfected infants born to mothers living with HIV (HEU) are at higher risk for HIV acquisition and display reduced vaccine responses and increased disease susceptibility compared to HIV unexposed infants (HU). The gut microbiota of HEU infants also differs from HU infants, which is attributed to altered profiles of oligosaccharides received in breastmilk and to altered communities of bacteria, and possibly viruses, inherited from maternal sources. Indeed, adults living with HIV have been shown to display an expansion in the diversity of certain viral groups. However, it remains unclear how this expanded viral diversity may affect mucosal immunity and bacterial succession patterns in related infants. Early life gut microbiota are critical to the development of certain T cell subsets, both in the mucosa and systemically, with the presence of specific microbes in the gut representing a significant determinant of adaptive immunity, further complicating the equation for HEU infants. Thus, the hypothesis for this project is that the enteric virome is a contributing factor influencing the morbidity of HEU infants, either by directly altering immunity or by skewing the composition of enteric bacteria through bacteriophage or other viral dynamics. 

The female genital tract (FGT) is colonized by millions of microbial taxa that affect mucosal immune responses, the risk of sexually transmitted infection (STIs) acquisition, and maternal health and birth outcomes. Broadly, lactobacilli, persistent members of the FGT across continents and demographics, are associated with low overall bacterial diversity and inflammation and reduced risk of acquisition of HIV and other STIs, relative to high-diversity, proinflammatory communities. Shifts from these optimal, Lactobacillus-dominant bacterial states to bacterial vaginosis (BV), characterized by a diverse community of anaerobic bacteria and depletion of Lactobacillus spp., is associated with elevated STI acquisition risk and adverse birth outcomes, relative to communities dominated by lactobacilli (especially non-iners Lactobacillus spp.). Unfortunately, the standard treatment for BV (metronidazole) demonstrates variable efficacy after several months and many women experience recurrent BV (rBV) within six months of antibiotic therapy, though the causative factors remain unknown. The vaginal virome and its contributions to recurrent and incident BV, especially via bacterial-phage dynamics, remain largely unexplored due to challenges associated with the isolation and sequencing of viral nucleic acid from the FGT. Likewise, the effect of resident prophages in bacterial hosts and their effect on host fitness and susceptibility to further infection remains almost entirely unexplored in the context of the FGT. Here, we hypothesize that the resident virome of the FGT induces microbial dysbiosis and contributes to bacterial vaginosis states recalcitrant to current treatment. 

The sequencing revolution has enabled researchers to study complex microbial communities with unprecedented resolution and speed. However, quantitative insights from these datasets are mostly limited to those generated by directly sequencing universal marker genes (e.g. segments of rRNA genes in bacteria and fungi), or by basing abundance estimates of each taxon on the assembly and annotation of those genes in metagenomic datasets due to issues with whole genome amplification bias and uneven genomic coverage. However, unlike bacteria and fungi, there are no universal genes present across all viral genomes and the biomass of viral communities is typically overshadowed by other microbial counterparts by at least an order of magnitude. Consequently, viral communities (especially those isolated from human sources) must be characterized and quantitated by shotgun metagenomic sequencing and require some amount of whole genome amplification to generate sufficient quantity for sequencing, in addition to the challenges associated with distinct, nonstandardized methods for RNA and DNA viruses. We aim to develop better molecular and computational tools to accurately characterize challenging microbial communities with variable biomass, such as sequence-independent amplification strategies (SIA) useful for characterizing challenging genomes such as RSV!