Poster Presentation HUPO 2019 - 18th Human Proteome Organization World Congress

Modelling life and death in mammalian cells to generate rational engineering strategies (#425)

Craig Barry 1 , Esteban Marcellin 1
  1. Australian Institute for Bioengineering and Nanotechnology, Fairfield, QLD, Australia

Dysregulation of checkpoint mechanisms which govern mammalian cell cycle and programmed death results in important cell proliferation phenotypes, spanning research interests from cancer studies to industrial cell line development. For example, the circadian oscillator has evolved into an autonomous timekeeping mechanism which coordinates metabolic requirements in synchrony with the sun. Each cell is equipped with its own circadian clock to confer rhythm across an entire organism. This metabolic control requires a coordinated protein interactome.

A protein interactome principally represents the mammalian cell cycle, and is subject to intrinsic and extrinsic noises which affect the trajectory of cell fate. In silico mathematical models have demonstrated an ability of accurately representing the dynamics of cell cycle regulatory networks and experimentally observed phenotypes, yet computational models of this kind require parameter training using experimental data.

Utilising a high resolution Q-Exactive HF-X Orbitrap mass spectrometer, we can capture and quantify crucial regulators of cell proliferation during the cell cycle. The Q Exactive HF-X enables MS/MS acquisition above 40 Hz at 7500 resolution resulting in impressive proteome coverage, achieving 3000 proteins in a single 1 h injection in capillary mode. Having established reliable methods for protein detection and quantification we have constructed mammalian cells which express four cell cycle phase-dependant fluorescent markers (FUCCI4) for discrete fluorescence activated cell sorting (FACS) for subsequent intracellular protein detection and quantification. This will allow us to build proteomic distributions of important nodes within the cell cycle interactome for parameter training of a detailed mathematical model. Using the protein expression profiles of discrete cell cycle phases, we aim to identify the boundary of intrinsic noise which determines normal cell proliferation and dysregulated phenotypes, leading to cell death. Identifying these protein markers will facilitate rational engineering strategies in areas of targeted medicine and mammalian cell line development of biologics-producing strains.