Faculty Candidate Research Statement
As the start date for both PI and graduate students will be August 16th, 2024, we have not begun research. To give an idea of some of our potential research plans, the research statement from Wheaton Schroeder for his faculty application. The variety of projects presented here serves to highlight the variety of applications of metabolic modeling.
Quantitative study of cancer biology focusing on biomarker mechanisms, phenotype, and drug-target interaction networks for drug repurposing
Motivation: Most often, cancer refers to a set of more than 100 related genetic diseases which arise due to genetic mutations which cause cells to divide uncontrollably, damaging the tissue in which they arose and/or other tissues throughout the body and is the leading cause of death worldwide. A recent wealth of in vivo biomarker data with large- and multi- scale human models provides a hitherto unparalleled opportunity for computational investigation of cancer cell metabolism and mechanisms underlying biomarkers. As cancer arises from genetic mutations, different cancers have different biomarkers, biological signatures of disease type, prognosis, and mechanism, which are often used to inform patient treatment including on an individual level due to fast and cheap genome sequencing, the ‘omics’ revolution, single-cell ‘omics’, producing a wealth of in vivo biological data. Recent research is increasingly understanding and investigating cancer as a metabolic disease, and recent advances in both human cellular (with the Virtual Metabolic Human, VHM in 2019) and whole-body human modeling (2020, capable of modeling more than two dozen interconnected tissue types in personalized, sex-specific models) have resulted in highly detailed models of human metabolism suitable for such investigations.
Objectives: This project will leverage computational models and analysis tools to i) reconstruct sophisticated type-specific models of cancer cell metabolism from existing models; ii) using biomarker databases, hypothesize biomarker mechanism and phenotype; and iii) from available data reconstruct genome-scale drug-target interactions which can reduce or disrupt the viability of cancer cells.
Reconstruction of two Coffea species models for the engineering of improved drought- and heat- stress tolerance
Motivation: Coffee has been called the second-most traded commodity in the world and the most important commodity in international agricultural trade, as it is a significant export for tropical countries and is largely imported by developed nations such as the United States and Europe. Worldwide, its cultivation is estimated to provide for the livelihoods of 20 to 25 million families and its cultivation is important in parts of the United States including Hawai’i, Puerto Rico, and (to a much lesser extent) California. Coffee is produce from two species, Coffea species: C. arabica (Arabic coffee, 70% of total market) and C. canephora (Robust coffee, 30% of total market) with both species vulnerable to the effects of climate change including increased drought severity and higher temperatures, leading to predictions that climate change will decrease the total area suitable for coffee production by 15-50% by 2050. To sustain C. arabica as an important agricultural species, heat and drought stress tolerance must be bolstered. Recent omics-based efforts have been made to understand the effects on and responses of Coffea species to increased temperature, elevated carbon dioxide, drought, and the interaction of drought and elevated temperature. However, the metabolic implications and molecular mechanisms of these responses are still unexplored or only explored in generalities66.
Objectives: This project will apply model reconstruction techniques, computational modeling tools, and available multi-omics datasets to i) reconstruct GSMs of Coffea canephora then Coffea arabica; ii) Use those reconstructions as bases to create drought- and heat- stressed metabolic reconstructions of both species; iii) use regulatory network elucidation techniques, like the MiReN algorithm12, to identify key regulators in drought and heat stress responses of both species; and iv) use computational tools to engineer improved tolerances of both species to both stresses.
In silico engineering of heterocyst-forming cyanobacteria for inducible carbon dioxide and light to bioproduct platforms
Motivation: Human-caused climate change is threatening the global ecosystem with myriad political, human, economic, and ecological effects stemming from these changes. A popular idea to mitigate further climate change is the development of a circular carbon economy, for which carbon capture and upcycle technology will play a key role. The development of carbon-negative platforms to produce biofuels or chemical feedstocks which replace petrochemicals will be one key carbon capture technology. Cyanobacteria are emerging chassis for carbon-neutral bioproduction due to key advantages such as higher photosynthetic efficiency, ease of genetic manipulation, and being prokaryotic. Diazotrophic (nitrogen-fixing) cyanobacteria can be a CO2 to biochemical chassis which requires few inputs. As nitrogen fixation is strongly inhibited by oxygen, in some species specialized, terminally differentiated, heterocyst cells to create anoxic environments. While often slow-growing, it offers the opportunity of an inducible system, as nitrogen starvation induces cell differentiation, and large changes in transcriptional regulation which could be harnessed to bioproduction without forsaking photosynthesis. This research aim would be interested in designing an inducible biochemical production platform using heterocyst forming cyanobacteria, where cells are grown to a desired density, followed by bioproduction triggered by nitrogen starvation and facilitated by cellular differentiation. This would minimize competition between growth and bioproduction.
Objectives: This project will apply model reconstruction techniques, computational modeling tools, and available transcriptomic and proteomic datasets to i) reconstruct a GSM of model heterocyst forming cyanobacteria Anabaena sp. PCC 7120; ii) Use those reconstructions as bases to develop normal and differentiated Anabaena cell models; iii) incorporate these two models into a “beads on a string” model of differentiated, nitrogen-starved Anabaena filaments which models diffusion of carbon and nitrogen; and iv) use differentiated models to design an inducible system for biochemical production.
