Thesis Central

Biomolecular condensates are an active area of research that offers tremendous promise, and research is helping to uncover their function in cellular biology and the potential for therapeutic intervention in pathological condensates. Experiments and simulations have led to continuous improvement in our understandings of biomolecular condensate thermodynamics, but the kinetic properties of condensation remain under-explored. In this project, we explore the nucleation properties of the intrinsically-disordered region (IDR) of human Ribonucleoprotein A1, also known as A1LCD. This protein’s thermodynamic properties are well-characterized by experimental studies, but its energetic barrier to nucleation is unknown. We propose a workflow to broadly resolve nucleation barriers for A1LCD from simulations alone, taking advantage of the Mpipi coarse-grained intrinsically disordered protein (IDP) model’s accuracy and performance to run microsecond-long simulations enabling the calculation of kinetic barriers to rare events. We make predictions of condensate nucleation barriers and correlate nucleation barrier height with known critical temperature values across six A1LCD mutants. We find that energetic barriers to nucleation are relatively constant across these mutant strains that condense at different critical temperatures, and additionally see that nucleation barriers rise as we approach the critical temperature for low system densities. In addition, we offer insights to future calculation of nucleation barriers for other IDPs.

This research explores the structural and catalytic implications of using melamine cyanurate (MCA), a supramolecular hydrogen-bonded framework, as a novel support material for heterogeneous palladium catalysts. Palladium nanoparticles were supported on MCA using both sol immobilization and impregnation–reduction methods, with additional samples incorporating a sulfur-containing ligand (MTT) to probe surface interactions. Structural, compositional, and morphological analyses were performed using XRD, XPS, TEM, and TGA. Catalyst performance was assessed using the Suzuki–Miyaura cross-coupling reaction. While palladium was successfully incorporated with small particle sizes, MCA-supported catalysts demonstrated low catalytic activity and significant evidence of support degradation under basic reaction conditions. These findings suggest that while MCA offers favorable nanoparticle dispersion and tunability, its structural instability under certain conditions limits its application as a robust catalyst support. Further optimization of reaction conditions and support modifications are proposed to improve its viability.

The iron and steel industry accounts for a large proportion of fossil fuel consumption and carbon emissions. In total, 11% of the global carbon emission and 7-9% of the global greenhouse gas emissions is due to iron and steel production, and the average total emission of the steel sector is approximated to be around 3.7 bn tonnes of carbon dioxide per year for the last six years (Dollinger). Thus, an important project concerning the industry is finding modifications to the ironmaking and steelmaking process, either through alternative energy sources or new technology/process implementations, that would reduce the amount of carbon emitted into the atmosphere. An avenue that has/is being explored is process electrification, which redistributes the energy source of the process towards electricity as a prevalent source of energy. This has manifested itself into a greater shift towards a pathway called the “secondary steelmaking” or electric arc furnace (EAF) route. The EAF route uses electric arcs and chemical energy from fuel gas burners to heat up furnace charge. However, most of the carbon emissions that come out of the US iron and steelmaking industry are still produced from the “primary steelmaking” route, also known as the blast furnace - basic oxygen furnace (BF-BOF) route; 85% of steel emissions come from BF-BOF production, while 15% of come from EAF production (Evans). Thus, my independent research throughout the semester was to perform an in-depth literature review on the energy source breakdown of both pathways, and look at how the increase of electricity usage can provide an avenue for decarbonization through a cleaner electric grid. The total energies and flows were then encoded into Python, and different electric grid emission rates were tested to calculate the impact of cleaner grids on the total carbon emissions. Additionally, the distribution of steelmaking using the DRI-EAF pathway and the BF-BOF pathway was altered to look at the resulting benefits of prevalent electricity usage.

Microtubules (MTs) are key components of the cytoskeleton and play a critical role in cell growth and division. During mitosis, the mitotic spindle, composed of dynamic MTs, acts as a structural framework that captures and segregates chromosomes into daughter cells. Although MTs begin assembling the spindle during prophase, the precise mechanisms initiating this process remain unclear. It is known that RCC1, the most upstream regulator of the Ran pathway, generates RanGTP to release spindle assembly factors that promote MT formation. However, the spatial and quantitative requirements for RCC1 in spindle assembly are still poorly understood. Given RCC1’s essential role in initiating this process, determining its minimum effective concentration and localization could provide important insights into how the spindle facilitates mitosis and where errors might arise. To investigate this, I used microfluidic devices to generate cell-like droplets encapsulating MTgenerating particles, allowing for precise titration of RCC1 concentrations. These devices were fabricated using the soft lithography method, where PDMS with the channel design was bonded to glass coverslips using plasma treatment. The encapsulated RCC1-coated particles facilitate the exchange of RanGDP for RanGTP, establishing a Ran gradient that drives MT formation and spindle assembly. Droplets were formed by injecting Xenopus egg extract as the aqueous phase and HFE-7500 oil as the oil phase. Xenopus egg extract is a cell-free system derived from frog eggs that preserves the biochemical machinery of cell division, making it an ideal model for studying MT dynamics in vitro. HFE-7500 is a fluorinated oil widely used in droplet microfluidics due to its chemical inertness, low solubility of aqueous components, and compatibility with surfactants that maintain droplet stability. My experiments revealed a power-law relationship between the volumetric flow rate ratio of the oil and egg extract and the resulting droplet sizes. Additionally, I observed that larger numbers of smaller RCC1-coated particles produced more complex MT network architectures around the self-localizing particles. To deepen our understanding of how RCC1 drives spindle formation, further experiments using varying concentrations of RanQ69L and RCC1 particles in microfluidic systems are needed.

Caldicellulosiruptor is a unique genus of bacteria that produces lignocellulose-degrading Carbohydrate Active enZymes (CAZymes). CAZymes are of particular interest because of their potential utility in processing cellulose for sustainable biofuel pathways. However, studying the CAZyme efficiently has been difficult both experimentally and computationally due to the enzyme’s large size, over 1700 amino acid residues in length. Previous computational studies have studied the CAZyme in a limited capacity, simulating only small sections of the protein with atomistic approaches. In this paper, I present Mpipi- Cellulose, the extension of the coarse-grained Mpipi force field to cellulose. Mpipi-Cellulose represents each monomer of cellulose as a single interaction site (or bead), allowing for more efficient computations yet still accurately capturing the cellulose-protein interactions of CAZyme binding to cellulose. Through a series of umbrella sampling simulations, potentials of mean force were constructed for interactions between cellulose and a variety of ligands, including peptide fragments and subdomains of CelA, the primary CAZyme produced by the Caldicellulosiruptor genus of bacteria. Mpipi-Cellulose demonstrated strong qualitative agreement with Martini3, a higher resolution coarse-grained model optimized for cellulose, across these simulations. Mpipi-Cellulose was then used to simulate the entire CelA interacting with a slab of crystalline cellulose. Using the newly developed model, I tracked the number of contacts between the enzyme and the cellulose, showing that the majority of the residues that interact with the cellulose come from the binding domains as predicted by experiments. Further simulations were performed with various CelA mutants, removing different binding domains and exploring the impact on interaction with the cellulose. These simulations demonstrated that the second and third binding domains in CelA are particularly important for proper binding to the cellulose surface. With this knowledge and further use of the Mpipi-Cellulose model, a wide number of mutants can be screened to optimize CAZyme performance for degradation of cellulose to produce biofuels.