Date of Award
Spring 5-7-2026
Degree Type
Thesis
Degree Name
Master of Science - Biology
Department
Biology
First Advisor
Alexandra Martynova-Van Kley
Second Advisor
James Van Kley
Third Advisor
Matthew Kwiatkowski
Fourth Advisor
Reuber Antoniazzi
Abstract
ABSTRACT
The human cervicovaginal microbiome is a complex and dynamic community that plays a crucial role in maintaining female reproductive health. This study characterizes the cervicovaginal microbiota of asymptomatic women using 16S rRNA high-throughput gene sequencing, focusing on how microbial diversity and composition vary across demographic, physiological, and lifestyle factors including ethnicity, body mass index (BMI), menstrual cycle phase, antibiotic use, and contraceptive use. Samples targeting the V3 and V4 hypervariable regions of the 16S rRNA gene were analyzed, revealing that Lactobacillus species dominate the microbiome in most individuals, although significant inter-individual variation exists with the presence of other taxa such as Gardnerella, Prevotella, and Escherichia/Shigella. While there were no significant differences in species richness or evenness related to host factors after measuring the alpha diversity, the beta analysis indicated that the menstrual cycle phase significantly varied the microbial community. Redundancy analysis models explained up to 61% of variation in microbiome composition, highlighting the combined influences of menstrual cycle, contraceptive use, and antibiotic exposure. When analyzing the co-occurrence network, I found that there are potentially important hub taxa that affect the community structure by interacting with other microbes. In the CVM among healthy women, it was observed that the composition could be quite heterogeneous, and the host and environmental factors are essential. This study provides a basis for further research on the implications of CVM for women's health.
Repository Citation
Ngetich, Daisy C., "CHARACTERIZATION OF THE CERVICOVAGINAL MICROBIOTA OF ASYMPTOMATIC WOMEN USING 16S RRNA THROUGHPUT GENE SEQUENCING" (2026). Electronic Theses and Dissertations. 692.
https://scholarworks.sfasu.edu/etds/692
Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Included in
Bioinformatics Commons, Biology Commons, Microbiology Commons
Tell us how this article helped you.
