2018
DOI: 10.1049/iet-syb.2017.0070
|View full text |Cite
|
Sign up to set email alerts
|

Hybrid CME–ODE method for efficient simulation of the galactose switch in yeast

Abstract: It is well known that stochasticity in gene expression is an important source of noise that can have profound effects on the fate of a living cell. In the galactose genetic switch in yeast, the unbinding of a transcription repressor is induced by high concentrations of sugar particles activating gene expression of sugar transporters. This response results in high propensity for all reactions involving interactions with the metabolite. The reactions for gene expression, feedback loops and transport are typicall… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
11
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
6

Relationship

3
3

Authors

Journals

citations
Cited by 7 publications
(11 citation statements)
references
References 16 publications
0
11
0
Order By: Relevance
“…Computational modeling of spatially-resolved kinetics in Syn3A is done by simulating the reaction-diffusion master equation (RDME) in Lattice Microbes (LM) (Roberts et al, 2013;Hallock et al, 2014;Earnest et al, 2017Earnest et al, , 2018Bianchi et al, 2018) using a stochastic simulation algorithm. When using the RDME, physical space is discretized into a cubic lattice representation.…”
Section: Spatial Model Of Jcvi-syn3amentioning
confidence: 99%
“…Computational modeling of spatially-resolved kinetics in Syn3A is done by simulating the reaction-diffusion master equation (RDME) in Lattice Microbes (LM) (Roberts et al, 2013;Hallock et al, 2014;Earnest et al, 2017Earnest et al, , 2018Bianchi et al, 2018) using a stochastic simulation algorithm. When using the RDME, physical space is discretized into a cubic lattice representation.…”
Section: Spatial Model Of Jcvi-syn3amentioning
confidence: 99%
“…The model is not molecularly detailed, i.e., it does not model individual proteins and their interactions. The model also does not consider the stochastic nature of individual gene expression and protein synthesis [10][11][12][13]. Rather, we model the overall population of proteins and ribosomes, and therefore is a coarsegrained cell scale model.…”
Section: Introductionmentioning
confidence: 99%
“…The first term is the chemical master equation (CME) probabilistic description of the subvolume-localized reactions for every subvolume in the system and the second term is the diffusion operator D for each particle type a in the x, y, and z directions specified by i, j, and k. For clarity, within the context of the spatially-resolved simulations, we will use the term local CME to describe the modeling of subvolume-localized stochastic reactions and the term global CME to describe the modeling of cell-wide stochastic reactions between species assumed to be well-stirred in the full cellular volume. In the whole-cell simulations presented in this study, we combine the above simulation methods with ordinary differential equation (ODE) solvers in hybrid methods that use the results of each method to update the particle counts of the subsequent method in a backward-updating fashion (Bianchi et al, 2018), which we present schematically in Figure S3. LM allows for periodic communication between its stochastic CME and RDME solvers and other simulation methods, such as an ordinary differential equations solver for metabolic reactions.…”
Section: Methods Detailsmentioning
confidence: 99%