PROBING STRUCTURE AND DYNAMICS OF CELL CYCLE CONTROL

The Seventh International Conference on Systems Biology Yokohama, October 9, 2006

Lilia Alberghina Dept. of Biotechnology and Biosciences University of Milano-Bicocca Milan, Italy 2 = 1

2 –TD/T +2 λ -1/T ρ 2 –TP/T –TP/T = K T = ln2/ λ 2 asymmetrical cell division in balanced exponential growth Mass duplication time (T) Cell size distribution Cell size Critical cell size (Ps) Signal Transduction Ras/Tor/Sch9/Snf1 /Ck2/Hog1 Transcriptional remodeling Sfp1 etc NUTRIENTS Cell cycle machinery Cell cycle Cyclin/Cdk/Cki/SCF/ APC etc Nutrient uptake nutrient sensing Metabolism AMP/ATP etc all together ±products 1000 gene NUTRIENTS AND CELL CYCLE IN BUDDING YEAST 3 Network identification quantitatively l, describing the more relevant

BIOLOGY lecular network for the module ystems Biology, Springer Verlag 2005 strategy for each module M rounds of 4

A ROADMAP FOR MODULAR SYSTEMS modules of the process ining of data bases anipulation of genetic and metabolic conditions easurements and localization of relevant molecular components odeling and simulation of a mo M M M Validation of its dynamics by simulation Validation of its dynamics M Global functional analysis of a process Construction of a “coarse-grain” mode Iterative Achievement of a satisfactory molecular model able to account for the entire process in: Alberghina and Westerhoff, eds., S and Westerhoff, in: Alberghina 4 but universal is a M known for thirty years,known but its molecular G2 S Ps to enter into S phase. G1 coupling of cell growth to cell division cell to growth cell of coupling poorly understood feature of the cell cycle basis is still under investigation. critical cell size (Ps) • has been key regulatory function This •The •The • The main regulatory event takes place at START, when cells must reach a GLOBAL FUNCTIONAL ANALYSIS OF CELL CYCLE CONTROL 2003 5 , 165-171, : shorter G1, larger cells → shorter smaller G1, cells FEMS Microbiol. Letters, 229 FEMS Microbiol. longer G1, larger cells Respiratory metabolism Respiro-fermentative metabolism Porro D. et al. increased level Cln3 the cell/nucleus critical and cell size? modulate the length of the G1 phase (h-1) → → → Dilution rate

AND BY METABOLIC CONDITIONS 0,05 0,1 0,15 0,2 0,25

3,0 2,0 1,0 0,0 Ps The Cln3-Cdk1 complex is the most upstream activator of entrance into S phase Changes in the availability of Cln3 Cln3 over-expressed Cln3 deletion IN BUDDING YEAST Ps IS MODULATED BY GENETIC BACKGROUND Ps IS MODULATED IN BUDDING YEAST Is there a link between amount Cln3 in Growth on rich medium 6 DNA DNA BUDDING BUDDING REPLICATION REPLICATION to enter S phase Cln1,2.Cdk1 Clb 5,6.Cdk1

to S network:

1 , have a smaller critical cell size than SBF/MBF transcription activation Cyclin.Cdk complexes THE BASIC EVENTS

Reconstructing the G cells, unable to stimulate the synthesis ribosomes of when growing on Cln3.Cdk1 sfp1 wild type cells Δ fermentable sugars (high growth rates) upstream activator 7 Resetting Subsystem M Cki END STRESS y growth at conditions) the G1 to S MITOSIS 3 C Pro Meta Ana Telo Kinesis 2 2 fast fast 2 C growth growth S G 1 C cAMP cAMP growth growth START 1 fast fast cell sizer (Ps) Master Control hyperactivation hyperactivation hyperactivation hyperactivation Cki GROWTH M G Genomics 5, 615-627, 2004 execution, at metaphase/anaphase (End2) and at anaphase/telophase control (involving Cki modulated and b

A COARSE-GRAIN MODEL OF CELL CYCLE Alberghina et al – Oncogene 20, 1128-1134, 2001 Alberghina et al – Current a cell sizer delays of mitosis (End3), modulated by (DNA and spindle stress damages, conflicting metabolic signals, etc.) transition Two areas major control of ƒ ƒ 8 , 1128-1134, 2001 The model predicts, cell for population during transitory state, a continuous increase of Ps and an increase in duration of budded phase, followed by decrease its to the new steady state Alberghina et 20 al., Oncogene

ANALYSIS OF A SHIFT UP BY SIMULATION 9 er in fast-growing cells as compared to , 433-443, 2004 d therefore the amount of accumulated Cln3 n3/Far1 ratio is almost constant J. Cell. Biol., 167 Alberghina L. etAlberghina al., is proportional to cell mass slow-growing ones, the average Cl TO BE INVOLVED IN MATING DEPENDENT ARREST AT G1/S The Cln3 level in G1 cells is constant an • • high the average Cln3 level is much While

A NEW ROLE IN MITOTIC CYCLE FOR FAR1 PREVIOUSLY KNOWN 10 Clb5-Cdc28 DNA replication

Cln1,2-Cdc28 s

SCF

u e

Sic1/Clb5-Cdc28

cl

m

u

s

n

a

l

p

o

t

y Sic1-6P c ethanol glucose Clb5-Cdc28 Sic1/Clb5-Cdc28 Sic1

LOCALIZATION OF Sic1 , 1798-1807, 2005 Sic1 is localized both the nucleus in and in cytoplasm Sic1 is localized the nucleus in in glucose in ethanol CARBON SOURCE MODULATES THE NUCLEO/CYTOPLASMIC MODULATES SOURCE CARBON In unbudded G1 cells grown - - Rossi R.L. et al., Cell Cycle 4 • • Sic1 requires• a NLS to be imported in the nucleus Sic1 facilitates nuclear accumulation of Clb5 11a

TO S TRANSITION

1

STARTING FROM SMALL UNBUDDED CELLS

MATHEMATICAL MODEL OF THE G 11b

TO S TRANSITION

1

STARTING FROM SMALL UNBUDDED CELLS

MATHEMATICAL MODEL OF THE G 11c

TO S TRANSITION

1

STARTING FROM SMALL UNBUDDED CELLS

MATHEMATICAL MODEL OF THE G 11d

TO S TRANSITION

1

STARTING FROM SMALL UNBUDDED CELLS

MATHEMATICAL MODEL OF THE G 11e

TO S TRANSITION

1

STARTING FROM SMALL UNBUDDED CELLS

MATHEMATICAL MODEL OF THE G Barberis et al, 2006, submitted 1 12 differential equations text mining for kinetic constants, by erimental time series, by utilization of ties, and by parameter values utilized ll as the cell size growth during G ed throughout all simulations of small ed throughout all simulations of of the concentrations of the involved of the concentrations of the involved ted of ordinary ted by a set

EQUATIONS AND PARAMETERS OF THE MODEL The model has been implemen The model considers the localization of components in different cell Parameter identification has been done by The best sets of parameters has been us The ƒ ƒ phase. • compartments (cytoplasm or nucleus)compartments as we (ODEs), that describe the temporal change proteins and complexes. mathematical fitting of simulated versus exp available experimental data as input quanti in literature models. ƒ elutriated cells. details) (see poster by Barberis et al for 13 [t] * [whi5cyt][t] [t] n [t] * [far1nuc][t] [t] [t] * [t] n n [t] * [t] / vol n [t]*[clb5cdk1sic1cyt][t] [t] * [sic1cyt][t] c c dt) dt) / vol / t] * [sbfwhi5nuc][t] * t] [t] * [clb5cdk1sic1pnuc][t] * [t] / vol n [t] n [t] * [cln3cdk1far1pnuc][t] * [t] ]/ / vol c n n /vol dt) dt) / vol [t] * [whi5cyt][t] [t] dt) dt) c ]/ dt) dt) [t] * [sbfwhi5pnuc][t] [t] / vol / n / vol / dt) n [vol ]/ / vol / dt) dt) [t] * [far1cyt][t] [t] n ]/ d c c ( ]/ dt) dt) dt) / vol / c [vol dt) dt) − ]/ ]/ / vol [voln]/ d n n [vol ]/ ( d [vol n dt) dt) d / vol / ( = k59 * vol = k59 ( [vol d − dt) dt) ]/ ( v42 d c − [vol [vol − ]/ ( dt dt) dt) − n [vol d d ]/ ( ( ]/ − d c v30 c ( [vol v21 − − v39 v39 v25 − d [vol − ( d − − v38 [vol [vol ( − Growth d d v9 v9 v22 v22 v36 − ( − − − − v51 v46 v46 − v41 v41 v26v52 + − − − v40 − − v8 + v46 v52 v29 − − [cln3cdk1far1nuc][t] [clb5cdk1sic1nuc][t] = v39 − = v21 − = v8 = v25 / k55 − k55 / v25 = v11 = v24 dt dt v24 + v51 + v51 v24 − dt v4 dt dt = v36 − = v26 dt dt = v11 / k55= v11 / = v10 = v4 / k55= v4 / = v1 = v23 − = v23 dt dt dt dt dt [far1cyt]/ [cln3cdk1far1pnuc]/ [clb5cdk1sic1nuc]/ [clb5cdk1sic1pnuc]/ [whi5nuc]/ [far1nuc]/ [sbfwhi5nuc]/ [clb5cdk1sic1cyt]/ [sbfwhi5pnuc]/ [sic1cyt]/ [whi5cyt]/ [cln3cdk1far1nuc]/ d d d d d Inhibitors of kinase complexes d Inactive complexes d d d d d d [t] * [clb5cdk1cyt][t] * [t] [t] * [cln2cdk1cyt][t] * [t] [t] * * [t] − c c c [t] * [cln3cdk1nuc][t] [t] n v33 v33 / vol / / vol / / vol / − [t] * [cln3nuc][t] [t] / vol / dt) dt) n dt) dt) dt) dt) ]/ ]/ ]/ c c [t] * [clb5cyt][t] [t] * [cln2cyt][t] n dt) dt) c c [t] * [clb5cdk1nuc][t] [t] * [cln2cdk1nuc][t] [t] ]/ / vol / n n n t] * [mcln2nuc][t] [ t] * [mclb5nuc][t] [t] [vol [vol [vol n n [t] *[mcln2cyt][t] [t] [t] * [mclb5cyt][t] d d dt) / vol / vol / c c d ( ( v19 + v50 v50 + v19 ( ]/ / vol [t] * [sbfnuc][t] [t] / vol / [vol n n − − d − − dt) dt) dt) [t] * [cln3cyt][t] [t] ( / vol / vol / c / vol / vol / ]/ ]/ dt) dt) dt) dt) c c − [vol ]/ ]/ / vol v43 dt) dt) dt) n n v34 EQUATIONS OF THE MODEL d dt) dt) dt) ( ]/ ]/ / vol / − ]/ ]/ n n [vol [vol c c dt) dt) − d d [vol [vol ( ( ]/ dt) dt) d d n ( ( [vol [vol ]/ − − v18 + v49 + v18 v49 [vol [vol c v32 d d − − d d ( ( ( ( [vol − − d v35 v37 − − [vol ( v7 + v47 − + v47 v7 v20 + v53*k55 v24 + v51 v53 d [t] * [cdk1cyt][t] [t] v8 + v46 + v9v46v8 + + ( − c − − − − − − v27 v27 v28 − − v48 / vol v7+ v47 − v49 v49 v50 v50 v47 v31 v31 − − v15 + v45 + v15 v45 v14 + v44 + v14 v44 − dt) dt) − ]/ v18v49 + − v19v50 + − c v26 + v52 + v52 v26 v6 + v48 * k55 − * k55 v6 + v48 v5 − = v22 + v43k55 / = v7 = v20 / k55= v20 / = v18 − = v18 = v19 − = v19 [vol d dt dt dt [cdk1nuc][t] = v12 − = v12 = v13 − = v13 dt dt ( = v14 * k55 * k55 = v14 * k55 = v15 = v6 / k55= v6 / = v5 / k55= v5 / = v3 = v16 − = v2 − = v17 − dt dt dt dt = v40 − = v40 dt dt dt dt dt dt [clb5cdk1nuc]/ [cln2cyt]/ [cdk1nuc]/ dt [mcln2cyt]/ [mclb5cyt]/ [mclb5nuc]/ [sbfnuc]/ [mcln2nuc]/ [cln3nuc]/ [cln2cdk1cyt]/ [cdk1cyt]/ [cln3cyt]/ [clb5cdk1cyt]/ [cln3cdk1nuc]/ [cln2cdk1nuc]/ [clb5cyt]/ d d d d d d d mRNAs and transcription factors d Cyclins and cyclin-dependent kinase d Cyclin-dependent kinase complexes d d d d d d d PARAMETERS OF THE MODEL

14 15 T2 T1

SIMULATED DYNAMICS OF G1 TO S TRANSITION FROM INDIVIDUAL CELLS TO POPULATION VALIDATION OF SIMULATED OVERALL DYNAMICS

Simulated - Glucose Experimental - Glucose

Simulated - Ethanol Experimental - Ethanol

The model predicts properties (budding curve) not taken into account during model construction Overall consistency between input data and output performance 16 17 OE-CLN2

Δ Δ OE-CLN2 sic1 sic1 Δ Δ Δ Δ Δ Δ

sic1

sic1 OE-CLB5 CLB5 stabilized mbf mbf mbf mbf Δ Δ Δ Δ Δ Δ Δ Δ

cln3 far1 sic1 sic1 stabilized OE-SIC1 and SIC1 stabilized OE-SIC1 OE-CLN2 sbf sbf OE-SBF sbf sbf OE-MBF

Δ

sic1 OE-CLB5 OE-CDK1 OE-CLN2 CLN2 stabilized OE-CLN3 OE-CLN3 and stabilized

Δ Δ Δ Δ Δ Δ Δ Δ

CLN3 stabilized cln3 cln3 cln3 cln3 cln3 cln3 cln3 cln3

Δ Δ Δ Δ Δ Δ Δ Δ Δ Δ

cln2 cln2 cln2 cln2 cln2 cln2 cln2 cln2 cln2 OE-SIC1 OE-WHI5 far1

Δ Δ Δ Δ Δ Δ Δ Δ Δ Δ Δ Δ

cln1 cln1 cln1 cln1 cln1 cln1 cln1 cln1 cln1 cln3 cln3 CLN2 stabilized CLN3 stabilized cln3 CELL CYCLE MUTANTS

Δ clb6 Δ Δ Δ POSITIVE TESTING OF THE MODEL WITH Δ

cdk1 clb5 far1 sic1 OE-SIC1 OE-SIC1 OE-CLN2 OE-WHI5 OE-CLN2

Δ Δ Δ Δ Δ Δ Δ Δ

Δ clb6 Δ clb6 cln2 cln2 cln2 cln2 cln2 cln2 cln2 cln2

Δ Δ Δ Δ Δ Δ Δ Δ Δ Δ Δ

cdk1 clb5 clb5 cln1 OE-CLB5 CLB5 stabilized OE-CLB5 and stabilized cln1 cln1 cln1 cln1 cln1 cln1 cln1 18 S − − 1.54 1.26 1.44 1.20 3.31 6.57 1.50 1.20 Estimated P

Δ Δ Δ Δ sic1 cln3 far1 whi5 OE-SIC1 OE-CLN3 OE-FAR1 OE-WHI5 Wild type glucose Wild type ethanol Relevant genotype 140 Ps 120 100 80 HOW TO ESTIMATE Ps 60 Time (minutes) 40 20 Cdk1-Clb5,6 nuclear Ps is estimated as the at value of the cell size the time when DNA replication starts 0 0

0.06 0.05 0.04 0.03 0.02 0.01

μ M) ( Concentration 19 cyt Growth rate Far1 initial concentration Cln3 initial concentration Binding value of Sic1 to Cdk1-Clb5,6 the entire G1 to S network

SENSITIVITY ANALYSIS OF Ps Ps is an emergent property of 20 S phase S phase 2 T Time (minutes) 1 T 0 20 40 60 80 100 120 140 160 180 200

2.00 1.80 1.60 1.40 1.20 1.00 Cell size Cell

WHY GROWTH RATE MODULATES Ps proposed regulatory events for setting of Ps the This model allows to set in a unified framework all previously RIBOSOME BIOGENESIS AND MODULATION OF Ps: A NEW INTERPRETATION

Growth rate is linked to the level and rate of synthesis of ribosome

Our model predicts that spf1Δ cells in exponential growth in glucose have lower Ps than wild type since they have lower RNA biosynthesis and hence lower growth rate

Jorgensen P. and Tyers M., Curr. Biol., 14, R1014 - R1027, 2004 21 DISTINCTIVE FEATURES OF THE MILAN/BERLIN MODEL FOR BUDDING YEAST

• Entrance into S phase requires the overcoming of two thresholds (both involving cyclin Cdk and Cki)

–agrowth sensitive threshold involves a cyclin, whose amount in the cell is proportional to cell mass. This threshold is executed at closely similar cell sizes in fast-growing cells as well as in slow-growing ones – a second threshold involves the cyclin that, together with its Cdk, promotes onset of DNA replication

• Nucleo/cytoplasmic localization: Cki facilitates transport of cyclin/Cdk into the nucleus in a controllable way thereby affecting the dynamics of entrance into S phase

• During exponential growth the setting of Ps is sensitive to growth rate (and therefore to ribosome biosynthetic activity) for the existence of a sizable time delay between the two thresholds

22 NETWORK IDENTIFICATION FOR THE G1 TO S TRANSITION IN MAMMALIAN CELLS

• We assume an evolutionary conservation of the general features of cell cycle control from yeast to mammalian cells (Nurse, 1990, 1992)

growth-sensitive cyclin cyclin D

DNA replication cyclin cyclin E

• We consider nucleo/cytoplasmic localization the Cki p27Kip1 is preferentially localized in the cytoplasm of transformed cells, and correlates with tumour aggressiveness

• Data mining and experimental analysis

(see poster by Milanesi/Alfieri et al)

23 NETWORK FOR THE GI TO S TRANSITION IN MAMMALIAN CELLS

24 WHAT NEXT?

•Links between cell signaling and cell cycle NUTRIENTS machinery in yeast

- modulation of the Sic1 threshold in perturbed growth Signal Transduction Nutrient uptake Ras/Tor/Sch9/Snf1 nutrient sensing /Ck2/Hog1

Metabolism Transcriptional phosphorylation signature of Sic1 AMP/ATP remodelling Sfp1 etc etc • Molecular model of the entire yeast cycle

• Molecular model of normal and transformed mammalian cell cycle

all together Cell size distribution ± 1000 gene products Critical cell size (Ps)

Mass duplication time

25 26 DNA damage in G1 results in a phase, S delay to enter into to the inhibition of Sic1 linked degradation by Pho85 . NatStructMolBiol. 2006 NatStructMolBiol. Nat Cell Biol 2004 et al., et al.,

THRESHOLD DURING PERTURBED GROWTH Wysocki Sic1 is the molecular target for Hog1,modulate G1 that to is S transition required in responseHog1 phosphorylates to to Sic1 promoting its stabilization and osmostress. progression. inhibition of cell-cycle Escotè

MODULATION OF THE ACTIVITY SIC1

OSMOSTRESS DAMAGE DNA 27 2006, submitted et al.,

Rapamycin causes G1 arrestmechanism by a dual comprises that regulation of Cln1-3 and up-regulation of down- Sic1. Rapamycin-mediated up-regulation Sic1of involves an increase in mRNA and nuclear accumulationa more of stable, non ubiquitinated protein. Zinzalla

THRESHOLD DURING PERTURBED GROWTH (rapamycin) MODULATION OF THE ACTIVITY SIC1 inhibition pathway TOR 28 New circuits target of perturbed new insight into cell cycle is a relevant Sic1 the critical cell size is an emergent property sensitive to growth rate and therefore to ribosome

CONCLUSIONS to account for growth perturbations. Simulations of delaying/blocking entrance into entrance delaying/blocking S phase. ITERATIVE PROCEEDING OF SYSTEMS BIOLOGY . Simulation analysisSimulation of budding yeast cell cycle indicate model balanced exponential growth, that, during the G1of to S network biosynthesis Molecular investigations indicate that growth conditions growth have to be modeled extended molecular networks should offer control • • imentazione –imentazione Avellino CNR, E. Klipp S. Sarno O. Marin R. Alfieri L. A. Pinna L. Milanesi G. L. Russo M. Ruzzene M. Barberis G. Tedeschi M. A. Pagano DIPAV – Biochimica Max Planck Institute Università di Milano Università di Padova for Molecular Genetics, Berlin In collaboration with Dipartimento di Chimica Biologica CNR - Institute of Biomedical Technologies, Milano Istituto di Scienze dell’Al

ACKNOWLEDGEMENTS Università di Milano-Bicocca M. Vanoni R. Rossi V. Zinzalla L. Querin P. Coccetti A. Mastriani M. Graziola F. Tripodi F. Sternieri D. Porro A. Di Fonzo F. Magni S. Fantinato L. De Gioia P. Fantucci R. Sanvito F. Chiaradonna D. Gaglio E. Sacco gineering, 2004, Wiley and Sons

BLOCK DIAGRAMS IN SYSTEMS CONTROL N. S. Nise, Control Systems En splicing budding budding budding; budding; biosynthesis biosynthesis biosynthesis biosynthesis nucleus export Protein folding Protein biosynthesis; Cell Cell biosynthesis; Protein lomere maintenance; Mitosis Mitosis maintenance; lomere Threonine and Methionine and Methionine Threonine Threonine and Methionine and Methionine Threonine Protein biosynthesis; Polar Polar Protein biosynthesis; Protein biosynthesis; Polar Polar Protein biosynthesis; Protein biosynthesis; RNA RNA Protein biosynthesis; Xanthine catabolism; GMP growth and/or maintenance growth Regulation of transcription; transcription; of Regulation Protein-nucleus import rRNA- import Protein-nucleus dehydrogenase GMP synthetase associated complex Ribosomal protein S1 S1 protein Ribosomal biosynthesis Protein Ribosomal protein L26 L26 protein Ribosomal biosynthesis Protein Aspartate-semialdehyde Aspartate-semialdehyde 40S Ribosomal protein S2 S2 protein Ribosomal 40S 40S Ribosomal protein S4 S4 protein Ribosomal 40S biosynthesis Protein Ribosomal 40S protein S7 40S Ribosomal protein S12 S12 protein Ribosomal 40S S18 protein Ribosomal 40S biosynthesis Protein S24 protein Ribosomal 40S biosynthesis Protein S17 protein Ribosomal 40S Homoserine dehydrogenase Ribosome-associated protein Te

DNA and RNA binding protein

MOLECULAR FUNCTIONMOLECULAR BIOLOGICAL PROCESS Uracil phosphoribosyltransferaseUracil salvage Pyrimidine subunit of the nascent polypeptide polypeptide nascent of the subunit

FAR1

tet

Δ far1

EXPONENTIAL GROWTH IN GLUCOSE EXPONENTIAL GROWTH PROTEIN

FAR1 tet

mutant/wt

Δ far1

mRNA Rel. expression ratio Not detected in 2D gel protein Not changed protein or mRNA RPS4 1 1 1 6,7 RPS2 1 1 1 6,2 NPL3 1 -1,9 1 1,5 FUR11,812,21 EGD2 1 1 -2 1 STM1 1 1 1 6,9 GUA1 1 1 1 -2,8 RPS12RPS18 1 1RPS24 1 1 1 1 1,8 1 1RPS17 2,8 1 1 2,8 1 1 2,8 RPL26 1 1 1 2,4 HOM2HOM6 1 1 1 1 RPS1A 1 1 1 6,2 RPS7A 1 1 1 7,9 NAME selection Glycolysis Glycolysis Glycolysis Glycolysis Glycolysis Polar budding; Bud site BIOLOGICAL PROCESS e metabolism Lactate L2 Protein biosynthesis Protein L2

AND PROTEOME FINDINGS isomerase synthase Enolase 1 Hexokinase I Hexokinase Pyruvate kinase Pyruvate dehydrogenase 3 Ribosomal protein L8 L8 protein Ribosomal biosynthesis Protein Lysyl-tRNA synthetaseLysyl-tRNA aminoacylation Lysyl-tRNA D-lactate dehydrogenas D-lactate Alcohol dehydrogenase I Carbohydrate metabolism 60S Ribosomal protein protein Ribosomal 60S Glyceraldehyde-3-phosphate Glyceraldehyde-3-phosphate

Tryptophanyl-tRNAsynthetase Cell growth and/or maintenance NAD(P)H-dependent reductaseNAD(P)H-dependent metabolism Carbohydrate 6,7-dimethyl-8-ribityllumazine Glucose-6-phosphate Glucose-6-phosphate

Homocysteine methyltransferase methyltransferase Homocysteine biosynthesis Methionine MOLECULAR FUNCTION Translation elongation factor EF2 factor elongation Translation biosynthesis Protein Pyruvate decarboxylase isozyme 1 isozyme decarboxylase Pyruvate metabolism Carbohydrate

FAR1 tet

increased protein or mRNA decreased protein or mRNA

Δ far1

EXPONENTIAL GROWTH INGLUCOSE EXPONENTIAL GROWTH

FAR1 tet mutant/wt

FAR1 ON SELECTED TRANSCRIPTOME GENE DOSAGE

Δ far1

mRNA PROTEIN Rel. expression ratio PGI1 1 1 RIB4 1 1 -2,2 1 EFT1 1 1 RPL21116,7 RPL81116,7 PDC11117,9 KRS1111-10 ENO1 -2,9-4-3,1 TDH3 1 1DLD31 1 -3,3 1 -1,5 -1,8 -1,6 MET6 1 1 ADH1WRS1 1 1 1 1HXK1 -2,3 -2,9 1 1 1 9,1 NAME CDC19 1 1 1 10 YDL124W 1 1 1,8 2,1 y l tet ** etanolo FAR1tet 0,0255 0,1332 0,0631 0,0785 0,0514 1 FAR1

Δ 0,98 + 1,45 + 0,40 + 0,45 + 0,52 + Et a nolo far1 t t te te Δ Δ ethanol Wt Wt far1 far1 Strain Mean Wt FAR1 FAR1 Wt Etanolo Etanolo Wt far1 Delta Glucose Ethanol tet ** FAR1tet Glucosio Glucosio FAR1

Δ mutant shows statistical a Gluc osio far1 glucose tet Wt Wt Gluc osio De lt a fa r1 significant RNA level increase if compared with wild type strain, both in glucosein ethanol and supplemented media FAR1

ES RNA CONTENT OF THE CELLS 1,8 1,6 1,4 1,2 1,0 0,8 0,6 0,4 0,2 0,0 Relative RNA content RNA Relative t conten RNA Relative , 2003) et al. ribosomal proteins mutant has more rRNA too? tet biogenesis could place take cells show induction a coordinate of tet tet the translation/stability of several Loss of balance ribosomal in protein FAR1 When exponentially grown in glucose, When exponentially A

FAR1 OVEREXPRESSION INCREAS An imbalance in the synthesis two of the autoregulation process (Zhao ribosome subunits 40S and 60S can induce FAR1 ribosomal protein and rRNA synthesis by an .It is is .It the critical cell size. The ental maintenance of Ps value at components (of no direct experimental elation assumed is between Cln3 and cell estimated from cell mass increase in average in controlling entrance into S phase is played kip /p27 cip1 vation as cell grows through calization is modeled . In order to account for the experim

ASSUMPTIONS INASSUMPTIONS TYSON’S MODELS down volume of the size atcalculated from which [SBF] = ½ (to be entered as a relationdetermination) a obtaining with about parameter into a the model) cell entering value to compared cell newborn ten S (1,2) is phase easily et (Chen al, Mol. Biol. 2000) Cell, assumed that the activationactivities showing of SBF/MBF depends upon a the sharp acti balance of kinase/phosphatase Zero-order ultrasensitive switch for transcription factors (SBF/MBF) activation increasing Cln3 dosage, et (Chen mass al, an Mol. hoc ad Biol. saturation Cell, 2000) r Cln3 dosage and Ps • The role of cyclin E/CDK2 in controlling onset of DNA replication is not considered. For budding yeast •• Very few cell cycle players involved • No nucleus/cytoplasmic localization considered • No role for ribosome biosynthesis in setting critical cell size • For mammalian cells •• No lo nuclear/cytoplasmic The role of cyclin D/CDK4/p21 “IN VIVO” ROBUSTNESS OF CELL CYCLE IS LARGER THAN THAT PREDICTED BY CHEN et al (2004) MODEL