Anuj Gupta, Bioinformatics Thesis Defense

In partial fulfillment of the requirements for the degree of
Doctor of Philosophy in Bioinformatics
in the School of Biological Sciences
 
Anuj Gupta
 
Defends his thesis:
Computational investigation of the molecular basis of susceptibility and resilience in different macaque species infected with malaria causing Plasmodium pathogens
 
Tuesday, November 30, 2021
11:15am Eastern Time
BlueJeans link: https://bluejeans.com/375899958/4887
 
Thesis Advisor:
Dr. Eberhard O. Voit 
Department of Biomedical Engineering
Georgia Institute of Technology
 
Committee Members:
Dr. I. King Jordan
School of Biological Sciences
Georgia Institute of Technology
 
Dr. Mark P. Styczynski 
School of Chemical and Biomolecular Engineering
Georgia Institute of Technology
 
Dr. Peng Qiu 
Department of Biomedical Engineering
Georgia Institute of Technology

Dr. Mary R. Galinski 
School of Medicine
Emory University

Summary:
Malaria has a complex pathology with varying manifestations and symptoms, effects on host tissues, and different degrees of severity and ultimate outcome, depending on the causative Plasmodium pathogen species. The studies in this dissertation analyze consequences of transcriptomic changes in the blood of two closely related macaque species (Macaca mulatta and Macaca fascicularis) in response to acute primary infection by Plasmodium knowlesi. P. knowlesi is an emanant zoonotic pathogen that causes acute severe infection in humans. Although the two macaque species are very closely related to each other and to humans, the infection in M. mulatta is fatal, unless aggressively treated (similar to humans), whereas M. fascicularis develops a chronic, but tolerable infection.
   
The comparative analysis described here suggests that a reason for this stark difference in outcome is that the two hosts differ in immune cell programs and expression of important genes. Specifically, the analyses establish a delayed pathogen detection in M. mulatta followed by extended inflammation that overwhelms this monkey’s immune response. By contrast, M. fascicularis was found to detect the pathogen earlier and to control the inflammation. Additionally, M. fascicularis limits cell proliferation pathways until peak infection, presumably in an attempt to reinforce recovery through the adaptive immune system. To compliment this transcriptomics analysis, a gene expression aided metabolic modeling approach was developed that combined multi-omics knowledge to give a molecular interpretation to biological systems. This helped to interpret changes in inflammation biomarker, Kyn/Trp ratio, and relate it to differences in immune response and cell proliferation. In depth analysis of observed differences reveals that pattern-recognition receptor (PRR) signaling pathways are crucial for detection of pathogen and transcriptomic differences in early liver phase of infection revealed an early detection in M. fascicularis. Correlation analysis between host and pathogen transcripts reveals a pathogenic surface antigen, SICAvar Type 1, as an important regulator throughout the infection. The log phase of infection in hosts is similar with macrophages and monocytes responsible for innate immune responses. During this phase, M. mulatta shows higher inflammation signals with upregulated inflammasome IL6-JAK-STAT3 signaling and IL10 expression, which continues to peak-infection phase. In contrast, M. fascicularis controls inflammation, presumably by means of the p53 pathway, which is distinctly downregulated near the peak of infection, thereby enabling adaptive immunity with various cell proliferation pathways that aid CD4+ T-cells and memory B-cells. Integrative metabolic modeling shows the potential role of tryptophan metabolism in regulating inflammation and stress response.  

A complete understanding of the exact dynamics of the immune response is difficult to reach. Nonetheless, studies in this dissertation provide clear indication toward processes that underlie an effective immune response. Thus, this study may pave the way for future immune strategies toward treating malaria and identifies multiple points of intervention that are apparently responsible for a balanced and effective immune response.