Proteome Allocation Models
| Model type |
|---|
| Approach: Mechanistic optimized |
| Computational demand: Local |
| Spatial resolution: grid: sub μm
domain: μm |
| Temporal resolution: time step & output: steady-state |
Model overview
These models optimize proteome allocation and cell physiology to maximize cellular growth rate. The models provide mechanistic insights into the trade-offs between resource allocation, respiration, cellular space, and management of environmental conditions that limit the metabolic choices of the cell [1].
Scales of interest
Proteome allocation models typically represent a single cell, often including subcellular compartments such as a bacterial periplasm or an alga's vacuole. The modeled cell is commonly placed in a diffusive or advective & diffusive environment from which it acquires resources [2].
Data inputs
Reactions represented in proteome allocation models require input parameters that define stoichiometry and rate constants. In addition, physical parameters such as density or size constraints, molecular weights and metabolite concentration ranges are required as input.
Example Studies & Code
Classic examples
- Molenaar et al. (2009) Shifts in growth strategies reflect tradeoffs in cellular economics.[3]
Recent applications
- Leles & Levine (2023) Mechanistic constraints on the trade-off between photosynthesis and respiration in response to warming.[1] e.g. Model's github
Limitations
Currently, these models are confined to solving for steady-state and do not include environmental fluctuations.
References
- ↑ 1.0 1.1 Leles SG, Levine NM. Mechanistic constraints on the trade-off between photosynthesis and respiration in response to warming. Sci Adv. 2023 Sep;9(35):eadh8043. doi: 10.1126/sciadv.adh8043
- ↑ Norris N, Levine NM, Fernandez VI, Stocker R. Mechanistic model of nutrient uptake explains dichotomy between marine oligotrophic and copiotrophic bacteria. PLoS Comput Biol. 2021 May 19;17(5):e1009023. doi: 10.1371/journal.pcbi.1009023
- ↑ Molenaar, D., van Berlo, R., de Ridder, D. et al. Shifts in growth strategies reflect tradeoffs in cellular economics. Mol Syst Biol 5, MSB200982 (2009). https://doi.org/10.1038/msb.2009.82