Logo image
Back
Gene expression networks and molecular pathways underlying biofilm formation in Haemophilus influenzae
Dissertation

Gene expression networks and molecular pathways underlying biofilm formation in Haemophilus influenzae

Evangeline Morgan Williams
Doctor of Philosophy (Ph.D.), Drexel University
Apr 2026
DOI:
https://doi.org/10.17918/00011335
pdf
Williams_Evangeline_202611.75 MB
PDF Embargoed Access, Embargo ends: 30 Nov 2026

Abstract

Haemophilus influenzae Otitis media Transcriptomics Molecular Biology Biofilms
Chronic bacterial infections arise from dynamic interactions between pathogen and host that require coordinated regulation of metabolism, immune evasion, nutrient acquisition, and community behavior. Understanding these processes therefore requires systems-level approaches that integrate genetic diversity with environmental context rather than focusing solely on individual virulence genes. This thesis examines the commensal-to-pathogen transition of Haemophilus influenzae, a common nasopharyngeal colonizer capable of causing otitis media, sinusitis, pneumonia, and exacerbations of chronic obstructive pulmonary disease. First, H. influenzae is placed in the broader context of health and disease, by examining how comparative genomics and pan-genome analyses have reshaped our understanding of strain diversity and accessory gene content. Virulence traits are then examined in greater detail through functional analysis of a disease-associated gene family with Sel1-like repeat proteins. Transcriptomic profiling across multiple growth conditions demonstrates that the accessory gene msf (macrophage survival factor) exerts condition-dependent effects on gene expression, particularly in pathways associated with adhesion, metabolism, and translation in static culture conditions. Expanding beyond single-strain frameworks, transcriptional responses to biofilm development were examined across a diverse panel of clinical isolates. Finally, methodological challenges including transcriptomic experimental design and limitations of current annotation frameworks are addressed and expanded upon. Gene co-expression network analyses demonstrate that coordinated transcriptional modules can link strain diversity to physiological traits and provide a framework for predicting gene function. Together, these findings support a model in which pathogenic potential emerges from the interaction of genomic diversity, environmental context, and coordinated regulatory programs.

Metrics

1 Record Views

Details

Logo image