Session N13: New physics-based perspectives on building and understanding biological cells

COLLOIDAL PHYSICS THAT INSTANTIATE LIFE IN BIOLOGICAL CELLS

We are interested in how physics at the colloidal scale instantiate life in biological cells. While principles from physics have driven recent paradigm shifts in how collective biomolecular behaviors orchestrate life, many mechanistic aspects of e.g. transcription, translation, and condensation remain mysterious because understanding and controlling them requires unifying two disparate physical regimes: the atomistic (structural biology) and the microscopic (systems biology). Colloidal-scale modeling bridges this divide and links molecular-scale behaviors to whole-cell function. Today I will discuss our computational model of a bacterial cell, where we represent biomolecules and their interactions physically and chemically, individually and explicitly. With it, we tackle a fundamental open question in biology, from a physico-chemical perspective: why protein synthesis speeds up during faster E. coli growth. We report a new mechanism, “stoichiometric crowding”, that leads to a previously undiscovered increase in ribosome productivity that in turn drives the speedup in protein synthesis. More generally, our computational study of protein synthesis in E. coli from the tandem perspective of cell biology and meso-scale physics presents a unique opportunity to broadly explore how the physical state of the cell impacts biological function.    

Design, Construction, and Analysis of a Synthetic Minimal Bacterial Cell

The minimal cell is the hydrogen atom of cellular biology. Such a cell, because of its simplicity and absence of redundancy would be a platform for investigating just what biological components are required for life, and how those parts work together to make a living cell.  Since the late 1990s, our team at the Venter Institute has been developing a suite of synthetic biology tools that enabled us to build what previously has only been imagined, a minimal cell. Specifically, a bacterial cell with a genome that expresses only the minimum set of genes needed for the cell to divide every two hours that can be grown in pure culture.  That minimal cell has about half of the genes that are in the bacterium on which it was based, Mycoplasma mycoides JCVI syn1.0, the so-called synthetic bacteria we reported on in 2010. We used transposon bombardment to identify non-essential genes, and genes needed to maintain rapid growth in M. mycoides.  Based on those data, we designed and synthesized a reduced genome in eight overlapping segments. All segments were individually viable when combined with wild type versions of the seven other segments. Combinations of reduced segments that were not viable allowed us to identify synthetic lethal pairs of genes. These occur when two genes each encode an essential function. Those findings required re-design and re-synthesis of some reduced genome segments. Three cycles of design, synthesis, and testing, with retention of quasi-essential genes, produced synthetic bacterium JCVI-Syn3.0 (531 kb, 474 genes), which has a genome smaller than that of any autonomously replicating cell found in nature. Synthetic bacterium JCVI-Syn3.0 retains almost all genes involved in synthesis and processing of macromolecules. Surprisingly, it also contained 149 genes with unknown biological functions, suggesting the presence of undiscovered functions essential for life. This minimal cell is a versatile platform for investigating the core functions of life, and for exploring whole-genome design. Since it was initially reported in 2016, we have identified functions for about 70 of the original 149 genes of unknown function, developed a computational model of the cell, and have made great progress in understanding the biology of this simple representative of all living cells.

    

Physical Modeling of the Three-Dimensional Architecture of the Human Genome

In vivo, the human genome folds into a characteristic ensemble of 3D structures. The mechanism driving the folding process remains unknown. A theoretical model for chromatin (the minimal chromatin model) explains the folding of interphase chromosomes and generates chromosome conformations consistent with experimental data is presented. The energy landscape of the model was derived by using the maximum entropy principle and relies on two experimentally derived inputs: a classification of loci into chromatin types and a catalog of the positions of chromatin loops. This model was generalized by utilizing a neural network to infer these chromatin types using epigenetic marks present at a locus, as assayed by ChIP-Seq. The ensemble of structures resulting from these simulations completely agree with HI-C data and exhibits unknotted chromosomes, phase separation of chromatin types, and a tendency for open chromatin to lie at the periphery of chromosome territories. Although this theoretical methodology was trained in one cell line, the human GM12878 lymphoblastoid cells, it has successfully predicted the structural ensembles of multiple human cell lines. Finally, going beyond Hi-C, our predicted structures are also consistent with microscopy measurements.  Analysis of both structures from simulation and microscopy reveals that short segments of chromatin make two-state transitions between closed conformations and open dumbbell conformations. For gene active segments, the vast majority of genes appear clustered in the linker region of the chromatin segment, allowing us to speculate possible mechanisms by which chromatin structure and dynamics may be involved in controlling gene expression.