Moving Towards Interpretable Mechanisms in Human Systems Biology
- Author(s): Thomas, Alex
- Advisor(s): Lewis, Nathan E
- Tesler, Glenn
- et al.
A detailed understanding of biomolecular mechanisms enables predictive modeling in biological systems. In the late 1990's, whole-genome sequencing and the development of various high-throughput technologies led to the emergence of systems biology, primarily in simple model organisms such as bacteria and yeast. Mechanisms between biological components and processes were cataloged and placed in mathematical frameworks to explain the role of genotype and environmental factors on phenotypes. Some modeling formalisms, such as constraints-based modeling, have been shown to accurately recapitulate biological findings, and provided new insights for applications ranging from metabolic engineering to evolutionary landscapes. Recently, systems biology of human cells, with the same aim of characterizing mechanisms, has been employed to study drug off-target effects, host-pathogen interactions, cancer metabolism, and multicellular interactions between brain cell types. However, mechanism-based systems biology of human cells is still in its infancy and has not achieved the level of adoption as systems biology in unicellular organisms. Therefore, a broad, mechanism-centric approach to human systems biology is expounded in this dissertation, and was used to address open problems concerning blood platelets and cancer cells to make inroads in the study of disease, longevity, and phenotypic diversity with regard to human cells. Mechanisms were cataloged into a computable database for blood platelet metabolism. This systems-level assessment of the platelet was used to study the effects of aspirin resistance and delineate pathway utilization during platelet storage. Computational methods were developed to handle the scale of information in these systems biology applications with the motivation of reporting digestible results. To this end, BioNetView was developed as a clustering and visualization tool to utilize structural information to build interpretable, data-influenced pathway maps. Discovery of new mechanisms for future systems biology applications was also explored. Representing an initial foray towards large-scale mechanistic discovery in human cells, a novel bioinformatics pipeline was developed and deployed for processing and scoring genetic interactions in cancer cell lines via gene knockout screens utilizing the unprecedented precision of CRISPR/Cas9 genome editing. Therefore, in an effort to contextualize and understand mechanisms, several aspects are presented, geared towards a comprehensive, interpretable systems-level perspective of human biology.