Mitochondria retrograde ODE model

Codes, data and notebooks for the manuscript titled “Mathematical Modeling and Analysis of Mitochondrial Retrograde Signaling Dynamics”

Graphical abstract

Mitochondrial Retrograde Signalling

Mitochondrial retrograde signaling reports mitochondrial status to the nucleus. However, there is a lack of understanding of how the nucleus capture mitochondrial status in dynamics and information processing. It is a complicated biochemical reaction that occurs in most eukaryotic organisms. In this repository, we focus on the RTG pathway in yeast. This pathway is the simplest retrograde signaling pathway that has been investigated thoroughly. Data are collected from [1] and [2] (See Dataset). This repository aims to compose known protein interactions and nucleus relocation that fulfills all known responses of the yeast RTG pathway. Monte-Carlo approach is used to solve this Boolean satisfiability problem, and the parameter searching/ simulation/ threading is facilitated by DifferentialEquations.jl [3].

Installation

Julia v1.7+ is needed (https://julialang.org/).

RTG protein levels

ntumitolab/rnaseq_rtg_expression

Parameters of retrograde signaling model

Table of parameters: solution_rtgM4.csv

This file is generated and modified from a script. All solutions are corresponding to the knockout experiments of [1] and [2] with the conditions in boolean_table_RTG13.csv. The solutions are stored in solution_rtgM4.csv.

Responses of Yeast RTG proteins to mitochondrial damage

Data: boolean_table_RTG13.csv

This folder contains summarized responses of mitochondrial retrograde signaling in yeast.

Components

Standard Name	Variable Name	Details
RTG1	rtg1	https://www.yeastgenome.org/locus/S000005428
RTG2	rtg2	https://www.yeastgenome.org/locus/S000005428
RTG3	rtg3	https://www.yeastgenome.org/locus/S000000199
Mks1	mks1	https://www.yeastgenome.org/locus/S000005020

Definition of Response

In [1] and [2], RTG response is observed via GFP tags on either RTG1 or RTG3. In wild-type, mitochondrial damage can cause these proteins to accumulate in the nucleus, resulting in the intensified brightness of the nucleus region observed by fluorescent microscopy. As shown in boolean_table_RTG13.csv, the responses are categorized in binary results: whether GFP is accumulated in the nucleus in a given condition. Based on [1] and [2], there are 20 reactions listed in the table.

For example, the following is one of the conditions mentioned in [1]:

Rtg1	Rtg2	Rtg3	s	Mks	gfp	Trans2Nuc
0	0	1	1	1	rtg3	1

Under the columns of Rtg1, Rtg2, Rtg3 and Mks, 0 means that the given protein is suppressed by knockout. On the other hand, 1 represent an expression of wild type. Also, 1 in s represent mitochondrial dysfunction, and 0 means the absence of mitochondrial damage. The gfp column describes the location of GFP tag. In this example, GFP tag is on Rtg3. As known in [1], Rtg3-GFP translocates to the nucleus under this condition. Therefore, Trans2Nuc is marked as 1, which means the GFP tags nucleus translocation happens.

Reactions

There are 20 reactions summarized in the table. Some conditions are yet to be explored; some are from [1] (Sekito et al. 2000) or [2] (Sekito et al. 2002). Missing conditions are labeled with NA.

Line Number	Reference
2	NA
3	[1]
4	[1]
5	[1]
6	[1]
7	[1]
8	[1]
9	[1]
10	NA
11	NA
12	[1]
13	[1]
14	[1]
15	[1]
16	[1]
17	[1]
18	[2]
19	[2]
20	[2]
21	[2]

References

1. Sekito, Takayuki, Janet Thornton, and Ronald A. Butow. “Mitochondria-to-nuclear signaling is regulated by the subcellular localization of the transcription factors Rtg1p and Rtg3p.” Molecular biology of the cell 11.6 (2000): 2103-2115.

2. Sekito, Takayuki, Zhengchang Liu, Janet Thornton, and Ronald A. Butow. “RTG-Dependent Mitochondria-to-Nucleus Signaling Is Regulated by MKS1 and Is Linked to Formation of Yeast Prion [URE3].” Molecular Biology of the Cell 13, no. 3 (March 2002): 795–804.

3. Rackauckas, Christopher, and Qing Nie. “DifferentialEquations.Jl – A Performant and Feature-Rich Ecosystem for Solving Differential Equations in Julia.” Journal of Open Research Software 5, no. 1 (May 25, 2017): 15. https://doi.org/10.5334/jors.151.

4. Gasch, Audrey P., et al. “Single-cell RNA sequencing reveals intrinsic and extrinsic regulatory heterogeneity in yeast responding to stress.” PLoS biology 15.12 (2017): e2004050. URL: https://doi.org/10.1371/journal.pbio.2004050

5. Delmans, Mihails, and Martin Hemberg. “Discrete distributional differential expression (D3E)-a tool for gene expression analysis of single-cell RNA-seq data.” BMC bioinformatics 17.1 (2016): 1-13. URL: https://doi.org/10.1186/s12859-016-0944-6

Runtime information

versioninfo()

Julia Version 1.10.4
Commit 48d4fd48430 (2024-06-04 10:41 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 4 × AMD EPYC 7763 64-Core Processor
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-15.0.7 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)
Environment:
  JULIA_CONDAPKG_BACKEND = Null
  JULIA_PYTHONCALL_EXE = /home/runner/work/mitochondria-retrograde-model/mitochondria-retrograde-model/.venv/bin/python
  JULIA_CI = true
  LD_LIBRARY_PATH = /opt/hostedtoolcache/Python/3.12.3/x64/lib

using Pkg
Pkg.status()

Project RetroSignalModel v0.12.0
Status `~/work/mitochondria-retrograde-model/mitochondria-retrograde-model/Project.toml`
  [336ed68f] CSV v0.10.14
  [a93c6f00] DataFrames v1.6.1
  [0c46a032] DifferentialEquations v7.13.0
  [b964fa9f] LaTeXStrings v1.3.1
⌃ [961ee093] ModelingToolkit v8.76.0
  [429524aa] Optim v1.9.4
  [91a5bcdd] Plots v1.40.4
  [bd369af6] Tables v1.11.1
Info Packages marked with ⌃ have new versions available and may be upgradable.