Advanced Modeling of Cellular Proliferation: Toward a Multi-scale Framework Coupling Cell Cycle to Metabolism by Integrating Logical and Constraint-Based Models.

Biological functions require a coherent cross talk among multiple layers of regulation within the cell. Computational efforts that aim to understand how these layers are integrated across spatial, temporal, and functional scales represent a challenge in Systems Biology. We have developed a computational, multi-scale framework that couples cell cycle and metabolism networks in the budding yeast cell. Here we describe the methodology at the basis of this framework, which integrates on off-the-shelf logical (Boolean) models of a minimal yeast cell cycle with a constraint-based model of metabolism (i.e., the Yeast 7 metabolic network reconstruction). Models are implemented in Python code using the BooleanNet and COBRApy packages, respectively, and are connected through the Boolean logic. The methodology allows for incorporation of interaction data, and validation through -omics data. Furthermore, evolutionary strategies may be incorporated to explore regulatory structures underlying coherent cross talks among regulatory layers.

[1]  L. Johnston,et al.  The CDC8 transcript is cell cycle regulated in yeast and is expressed coordinately with CDC9 and CDC21 at a point preceding histone transcription. , 1987, Experimental cell research.

[2]  Chia-Yi Chien,et al.  Ung1p‐mediated uracil‐base excision repair in mitochondria is responsible for the petite formation in thymidylate deficient yeast , 2009, FEBS letters.

[3]  L. Hartwell,et al.  Three Additional Genes Required for Deoxyribonucleic Acid Synthesis in Saccharomyces cerevisiae , 1973, Journal of bacteriology.

[4]  J. Nielsen,et al.  Mathematical modelling of metabolism. , 2000, Current opinion in biotechnology.

[5]  B. Palsson,et al.  Constraining the metabolic genotype–phenotype relationship using a phylogeny of in silico methods , 2012, Nature Reviews Microbiology.

[6]  Song Li,et al.  Boolean network simulations for life scientists , 2008, Source Code for Biology and Medicine.

[7]  D. Thieffry,et al.  Modular logical modelling of the budding yeast cell cycle. , 2009, Molecular bioSystems.

[8]  Edda Klipp,et al.  A Clb/Cdk1-mediated regulation of Fkh2 synchronizes CLB expression in the budding yeast cell cycle , 2017, npj Systems Biology and Applications.

[9]  Tom M. Conrad,et al.  Omic data from evolved E. coli are consistent with computed optimal growth from genome-scale models , 2010, Molecular systems biology.

[10]  Richard Bonneau,et al.  Quantitative proteomic analysis of the budding yeast cell cycle using acid‐cleavable isotope‐coded affinity tag reagents , 2006, Proteomics.

[11]  Sergio Rossell,et al.  Towards a quantitative prediction of the fluxome from the proteome. , 2011, Metabolic engineering.

[12]  T M Murali,et al.  From START to FINISH: computational analysis of cell cycle control in budding yeast , 2015, npj Systems Biology and Applications.

[13]  Katherine C. Chen,et al.  Kinetic analysis of a molecular model of the budding yeast cell cycle. , 2000, Molecular biology of the cell.

[14]  Susumu Goto,et al.  Data, information, knowledge and principle: back to metabolism in KEGG , 2013, Nucleic Acids Res..

[15]  R. Storms,et al.  Cell cycle-dependent expression of thymidylate synthase in Saccharomyces cerevisiae , 1984, Molecular and cellular biology.

[16]  Katherine C. Chen,et al.  Integrative analysis of cell cycle control in budding yeast. , 2004, Molecular biology of the cell.

[17]  Edda Klipp,et al.  Sic1 plays a role in timing and oscillatory behaviour of B-type cyclins. , 2012, Biotechnology advances.

[18]  B. Palsson,et al.  Regulation of gene expression in flux balance models of metabolism. , 2001, Journal of theoretical biology.

[19]  Hyeon-Son Choi,et al.  Phosphorylation of Phosphatidate Phosphatase Regulates Its Membrane Association and Physiological Functions in Saccharomyces cerevisiae , 2010, The Journal of Biological Chemistry.

[20]  R. Thomas,et al.  Boolean formalization of genetic control circuits. , 1973, Journal of theoretical biology.

[21]  Jeffrey D Orth,et al.  What is flux balance analysis? , 2010, Nature Biotechnology.

[22]  Madeleine Udell,et al.  Incorporation of flexible objectives and time-linked simulation with flux balance analysis. , 2014, Journal of theoretical biology.

[23]  Paul Russell,et al.  Constraining G1-specific transcription to late G1 phase: the MBF-associated corepressor Nrm1 acts via negative feedback. , 2006, Molecular cell.

[24]  Nicola Zamboni,et al.  The Yeast Cyclin-Dependent Kinase Routes Carbon Fluxes to Fuel Cell Cycle Progression. , 2016, Molecular cell.

[25]  Matteo Barberis,et al.  GEMMER: GEnome‐wide tool for Multi‐scale Modeling data Extraction and Representation for Saccharomyces cerevisiae , 2018, Bioinform..

[26]  Edda Klipp,et al.  Cell Size at S Phase Initiation: An Emergent Property of the G1/S Network , 2007, PLoS Comput. Biol..

[27]  Q. Ouyang,et al.  The yeast cell-cycle network is robustly designed. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[28]  Christoph Wittmann,et al.  Dynamics of intracellular metabolites of glycolysis and TCA cycle during cell-cycle-related oscillation in Saccharomyces cerevisiae. , 2005, Biotechnology and bioengineering.

[29]  S. Henry,et al.  Revising the Representation of Fatty Acid, Glycerolipid, and Glycerophospholipid Metabolism in the Consensus Model of Yeast Metabolism. , 2013, Industrial biotechnology.

[30]  Joshua A. Lerman,et al.  COBRApy: COnstraints-Based Reconstruction and Analysis for Python , 2013, BMC Systems Biology.

[31]  D. Irons,et al.  Logical analysis of the budding yeast cell cycle. , 2009, Journal of theoretical biology.