MCB Seminar | From reductionism to globalism: Whole-cell modeling, Oct. 5

The Molecular and Cellular Biology Seminar series features Shiyu Yuan on Oct. 5 from 4:35 to 5:55 p.m.

• Contact Dr. Sarah Wyatt , MCB director, for more information.

Yuan is a graduate student in Biological Sciences and  Molecular Cellular Biology .

Abstract: Biology has traditionally followed a reductionist approach in which individual components of a living system are studied separately. As next-generation experiments yield data that is high throughput and complex, there is an increasing need for corresponding computational methods to derive knowledge from the data and study how components interact to form complex systems ¹ . Whole-cell models that incorporate every known gene function to make predictions about integrated and complex biological phenomena may address this need. The concept and application of whole-cell modeling was first demonstrated in the simple organism Mycoplasma genitalium . The model was able to track all of the molecules and interactions within a life cycle of a bacterium, offering a detailed look into the behavior and function of the cell. The simulations generated by this highly integrated model also compared favorably with published data sets including metabolic fluxes, metabolite concentrations, growth rates, and gene and protein expression ² . Since then, the whole-cell modeling approach has been extended to, a more complicated organism, E. coli , allowing researchers to tap into the extensive data that have resulted from decades of research into this model organism ³ . Whole-cell modeling can be best used for integrating heterogeneous database, identifying limits of current knowledge, predicting multi-network phenotypes, suggesting future experiments that may lead to new knowledge, and provide a framework for the safe and effective design of genetically modified organisms ⁴ .

Key reference:

1              Macklin, D. N., Ruggero, N. A. & Covert, M. W. The future of whole-cell modeling. Curr Opin Biotechnol 28 , 111-115, doi:10.1016/j.copbio.2014.01.012 (2014).

2              Karr, J. R. et al. A whole-cell computational model predicts phenotype from genotype. Cell 150 , 389-401, doi:10.1016/j.cell.2012.05.044 (2012).

3              Macklin, D. N. et al. Simultaneous cross-evaluation of heterogeneous E. coli datasets via mechanistic simulation. Science 369 , doi:10.1126/science.aav3751 (2020).

4              Carrera, J. & Covert, M. W. Why Build Whole-Cell Models? Trends Cell Biol 25 , 719-722, doi:10.1016/j.tcb.2015.09.004 (2015).