Biofidelic colloidal interactions : advanced computational representation and impacts on cellular biology
Abstract/Contents
- Abstract
- The interior of biological cells is a dynamic milieu of interacting molecules that work together to carry out life-essential functions. Mechanistic understanding of cellular behavior thus requires integration of physics and chemistry across multiple length- and timescales, from molecular self-assembly to whole-cell processes. The established modeling paradigms of structural and systems biology excel at interrogating the extremes of these scales. In the past few decades, emergent computational efforts have closed this divide, aiming to predict whole-cell behaviors based solely on knowledge of microscopic biomolecular details. This 'mesoscale' is the domain of colloidal physics, suspension mechanics, and fluid dynamics. In this dissertation, I describe our work developing colloidal-scale computational models of biological systems, with explicit representation of molecular size, interactions, reaction chemistry, and first-principles diffusive transport. Across three specific applications in cell biology, I demonstrate how such physico-chemical phenomena underpin emergent molecular behaviors essential to predicting cell function. My work enables interrogation of dynamics below experimental resolution limits, illustrated by our model of ultra-weak protein-protein interactions (PPIs) in minimal cells. I then expand our group's previous model of bacterial protein synthesis, which identified that physical transport of translation molecules was rate limiting. I demonstrate a 'pre-loading' mechanism by which PPIs between translation molecules further shorten transport times, thus speeding protein synthesis and supporting faster cellular growth rates. Finally, I present our whole-cell colloidal model of E. coli, developed alongside in vivo particle tracking experiments, which demonstrates how molecular interactions and cell-scale characteristics organize the cellular interior. Overall, these results support a broader colloidal basis for cell fitness and lay a foundation for prediction and engineering of whole-cell behaviors by tuning molecular and mesoscale physical features.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2023; ©2023 |
| Publication date | 2023; 2023 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Hofmann, Jennifer |
|---|---|
| Degree supervisor | Fuller, Gerald G |
| Degree supervisor | Zia, Roseanna |
| Thesis advisor | Fuller, Gerald G |
| Thesis advisor | Zia, Roseanna |
| Thesis advisor | Endy, Andrew D |
| Degree committee member | Endy, Andrew D |
| Associated with | Stanford University, School of Engineering |
| Associated with | Stanford University, Department of Chemical Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Jennifer L. Hofmann. |
|---|---|
| Note | Submitted to the Department of Chemical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2023. |
| Location | https://purl.stanford.edu/dp088yg6206 |
Access conditions
- Copyright
- © 2023 by Jennifer Hofmann
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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