Life Sciences Commons^™

Insights To Protein Pathogenicity From The Lens Of Protein Evolution, Janelle Nunez-Castilla

FIU Electronic Theses and Dissertations

As protein sequences evolve, differences in selective constraints may lead to outcomes ranging from sequence conservation to structural and functional divergence. Evolutionary protein family analysis can illuminate which protein regions are likely to diverge or remain conserved in sequence, structure, and function. Moreover, nonsynonymous mutations in pathogens may result in the emergence of protein regions that affect the behavior of pathogenic proteins within a host and host response. I aimed to gain insight on pathogenic proteins from cancer and viruses using an evolutionary perspective. First, I examined p53, a conformationally flexible, multifunctional protein mutated in ~50% of human cancers. Multifunctional …

In Silico Characterization Of Protein-Protein Interactions Mediated By Short Linear Motifs, Heidy Elkhaligy

FIU Electronic Theses and Dissertations

Short linear motifs (SLiMs), often found in intrinsically disordered regions (IDPs), can initiate protein-protein interactions in eukaryotes. Although pathogens tend to have less disorder than eukaryotes, their proteins alter host cellular function through molecular mimicry of SLiMs. The first objective was to study sequence-based structure properties of viral SLiMs in the ELM database and the conservation of selected viral motifs involved in the virus life cycle. The second objective was to compare the structural features for SliMs in pathogens and eukaryotes in the ELM database. Our analysis showed that many viral SliMs are not found in IDPs, particularly glycosylation motifs. …

Understanding Exosomal Extracellular Vesicles And Morphine In The Neuropathology Of Human Immunodeficiency Virus And Differential Zika Virus Strain-Associated Pathology, Allen Caobi

FIU Electronic Theses and Dissertations

Exosomal Extracellular Vesicles (xEVs), integral to intercellular communication and regulation of immune responses, have functional effects based on their contents, which they transport to neighboring cells. However, in the context of infection, EV cargo can be modulated, by either infected or uninfected cells. We hypothesize that CNS-associated neuropathology, is partially, due to the cargo transported by the exosomes. We theorize that the cargo released from infected cell-derived xEVs may either facilitate or inhibit viral neuropathogenicity. Here we investigated xEVs in the case of two neurotropic viruses, Zika virus (ZIKV) and Human Immunodeficiency Virus (HIV). The hallmark characteristic of ZIKV-infection is …

Development Of A Microwave-Based Dna Extraction Method To Increase The Success Of Direct And Rapid Pcr Technique, Fabiana Taglia

FIU Electronic Theses and Dissertations

The goal of this project was to develop a fast, microwave-based extraction technique that could be employed for direct and rapid DNA analysis. The hypothesis was that the use of a microwave could increase the yield of DNA by opening the cell membrane, rendering the DNA available without the use of any other chemical treatment, and improving results from very low quantity samples.

At present rapid human DNA analysis is mainly restricted to genotyping saliva and sometimes blood samples. We hypothesized that microwave processing could expand the types of samples assessable to these procedures and increase sensitivity.

There were two …

A Machine Learning Framework For Identifying Molecular Biomarkers From Transcriptomic Cancer Data, Md Abdullah Al Mamun

FIU Electronic Theses and Dissertations

Cancer is a complex molecular process due to abnormal changes in the genome, such as mutation and copy number variation, and epigenetic aberrations such as dysregulations of long non-coding RNA (lncRNA). These abnormal changes are reflected in transcriptome by turning oncogenes on and tumor suppressor genes off, which are considered cancer biomarkers.

However, transcriptomic data is high dimensional, and finding the best subset of genes (features) related to causing cancer is computationally challenging and expensive. Thus, developing a feature selection framework to discover molecular biomarkers for cancer is critical.

Traditional approaches for biomarker discovery calculate the fold change for each …