albert sorribas rui alves ester vilaprinyó grup de bioestadística i biomatemàtica
DESCRIPTION
Identifying selective pressures that shape the adaptive responses of yeast to stress: design and operating principles in metabolism. Albert Sorribas Rui Alves Ester Vilaprinyó Grup de Bioestadística i Biomatemàtica Departament de Ciències Mèdiques Bàsiques - PowerPoint PPT PresentationTRANSCRIPT
Identifying selective pressures that shape the adaptive responses of yeast to stress: design and operating principles in metabolism
Albert SorribasRui Alves Ester Vilaprinyó
Grup de Bioestadística i BiomatemàticaDepartament de Ciències Mèdiques BàsiquesInstitut de Recerca Biomèdica de Lleida (IRBLLEIDA)Universitat de Lleida
web.udl.es/Biomath/Group
Summary Introduction: Design and operating principles in
metabolism Strategies for identifying design and operating principles The role of mathematical models Examples
Results: Adaptive responses of yeast to stress Phisiological contraints that shape the response to heat
shock Common selective pressures in different stress conditions
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Introduction
Identifying design and operating principles in metabolism
Design principles: recurring qualitative organizational rules of biological systems with the same function
Operating principles: set of quantitative changes, limited by the qualitative design of the system (design principles), that create an effective adaptive response in a biological system
Examples: Regulatory gene circuits Functional constraints in metabolic pathways Evolution of enzyme molecules Response to stress conditions
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Issues at stake while identifying design and operational principles in metabolism
Biological systems are a result of evolution Natural selection results in designs that optimize (in some
sense…) survival and reproductive success.
Different biological functional effectiveness criteria are important Metabolic efficiency (maximize fluxes, etc.) Energetic limitations (minimize energy expenditure) Cost of gene expression changes (gene expression profiles) Temporal responsiveness (time scales) Parameter sensitivity (robustness) Metabolite concentrations (limited capacity)
Salvador A, Savageau MA. Proc Natl Acad Sci U S A. 2006, 14;103(7):2226-31.
Wall ME et al. J Mol Biol. 2003, 332(4):861-76. Hlavacek WS, Savageau MA. J Mol Biol. 1995, 248(4):739-55. Kollmann et al. (2005) Nature 438(7067):504-7. Vilaprinyo E, Alves R, Sorribas A. (2006) BMC Bioinformatics. 7:184.
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A basic example: Why is feedback inhibition a prevalent regulatory design?
Xn+1 X1 X2 Xn-1 Xn
(-)
(a)
Xn+1 X1 X2 Xn-1 Xn
(-)
(-)
(b)
(c) Xn+1 X1 X2 Xn-1 Xn
(-)
(-)
Savageau MA. Optimal design of feedback control by inhibition.J Mol Evol. (1974) 4(2):139-56.
Design and operating principles in feedback regulation
Design: Feedback by end-product is the preferred design Robustness, stability, dynamic response
Operation: Once the feedback is in place, which are the optimal changes as to adapt to some new condition? Interplay between different designs System-level response
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Strategy for identifying design principles in metabolism
Evaluate design alternatives: Analyze class of systems Mathematical controlled comparisons
Define criteria for functional effectiveness Best design that realizes the different criteria for functional
effectiveness Statistical analysis of design performance Simulate alternative scenarios
Appropriate mathematical models are required Systematic representation Semi-quantitative models (lack of precise parameters,
incorporate model assumptions..) Ensure comparability between alternative designs
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Investigating design principles in metabolismMathematical controlled comparisons
Define the basic systemic structure and its design alternatives (biological knowledge)
Write an S-system (aggregated node equations in power-law) representation (or equivalent (log)linear/lin-log) for each design Find the analytical steady-state solution and fix parameter
constraints between alternative designs (external and internal equivalences)
Compare equivalent systemic properties of alternative designs (based on criteria for functional effectiveness)
If the advantage of a given design depends on parameter values, a systematic parameter screening is required. Use the SC formalism for extending the steady-state
conclusions and explore dynamic responses
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Example
X5 X1 X2 X3 X4
(-)
(a)
X5 X1 X2 X3 X4
(-)
(-)
(b)
ahagg XXXX 111514115411
bb hhbgg XXXXX 121115142115411
Internal equivalence: Same parameters for all those processesthat do not changeFix external equivalence: Same flux, same responsivenessto changes in the source metabolite.Compare system performance: What is left after those equivalences?
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Some well established results So far, the issue of design principles has been mainly analyzed by using
the power-law formalism and S-system models Regulatory gene circuits (demand theory)
Savageau MA. Design of molecular control mechanisms and the demand for gene expression. Proc Natl Acad Sci U S A. (1977) 74(12):5647-51.
Savageau MA. Demand theory of gene regulation. I. Quantitative development of the theory. Genetics. (1998) 149(4):1665-76.
Wall ME, Hlavacek WS, Savageau MA. Design principles for regulator gene expression in a repressible gene circuit. J Mol Biol. (2003) 332(4):861-76.
Wall ME, Hlavacek WS, Savageau MA. Design of gene circuits: lessons from bacteria. Nat Rev Genet. 2004 Jan;5(1):34-42.
Signal transduction Alves R, Savageau MA. Comparative analysis of prototype two-component systems
with either bifunctional or monofunctional sensors: differences in molecular structure and physiological function. Mol Microbiol. (2003 ) 48(1):25-51.
Igoshin O, Alves R, Savageau MA. (2007) Hysteretic and graded responses in bacterial two-component signal transduction. Mol Microbiol. 2008 (in press)
Igoshin OA, Brody MS, Price CW, Savageau MA. Distinctive topologies of partner-switching signaling networks correlate with their physiological roles. J Mol Biol. 2007 Jun 22;369(5):1333-52
Igoshin OA, Price CW, Savageau MA. Signalling network with a bistable hysteretic switch controls developmental activation of the sigma transcription factor in Bacillus subtilis.Mol Microbiol. 2006 Jul;61(1):165-84.
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Operating principlesAdaptive responses at a cellular level
Search for common changes that allows adaptive response to new conditions Gene expression patterns Changes in enzyme activity Activation of specific pathways
Identify the physiological constraints that shape those changes Understand the evolution outcome
Operating principles are constrained by physiological requirements Specific for a prevalent situation (for instance, heat shock) Common to different situations (for instance economy in protein
synthesis)
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Identification of constraints that shape the gene expression response of yeast to stress
Motivations and Goals Environmental stresses (heat shock, osmotic...) trigger
gene expression changes in yeast
ADAPTATION:There is a redistribution of fluxes and metabolite concentrations (physiology).
This can be achieved by different strategies. Only one of them have been selected. Voit & Radivoyevitch (2000) Bioinformatics. 16(11):1023-37.
Seek the constraints that shape the gene expression profile (GEP) of yeast to stress conditions
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Methodology Collect information on the physiological (macroscopic) response of
yeast to heat shock Identify appropriate response in terms of fluxes, metabolite levels, etc. Which are the involved pathways?
Define performance criteria: physiological requirements Fluxes, metabolites, cost of over-expression, etc.
Build-up a mathematical model of the main pathways involved Consider kinetic properties, regulatory effects, etc. We shall use the power-law formalism so that it provides an appropriate
framework for modeling and analysis
Perform an exhaustive set of simulations to explore the effect of different levels of enzymes on the resulting fluxes and metabolite levels.
Identify those patterns that are compatible with an appropriate physiological response
Compare the selected patterns with actual gene expression data
Voit & Radivoyevitch (2000) Bioinformatics. 16(11):1023-37. Vilaprinyo, Alves, Sorribas (2006) BMC Bioinformatics 7(1):184
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Main characteristics of heat shock response in yeast
Adaptive response of yeast to heat shock Physiological requirements
Increase of trehalose synthesis Stabilization of proteins, general protection of cellular structures
Need for appropriate NADPH levels Reducing power is mainly needed for an appropriate response
Need for ATP Stress conditions increase energy demand
Main pathways involved: Glycolysis, Glycerol, Trehalose, Pentoses.
Many genes are overexpressed: chaperones, heat shock proteins,…, and glycolytic enzymes, glucose transporters, etc.
►15Abril 2008 CRG
Metabolic network
Glycogen Trehalose
NADPH
HIGH ENERGY DEMANDC1
STRUCTURAL INTEGRITY-Avoids aggregation of denatured proteins-Membrane -Acts in synergism with chaperonesC2
REDUCING POWERNew synthesis of sphingolipids in order to change the membrane fluidityC3
Curto, Sorribas, Cascante (1995) Math. Biosci. 130, 25-50Voit, Radivovevitch (2000) Bioinformatics 16: 1023-1037
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Glycogen Trehalose
Methodology
×5
×5
×5
5 ×
HXT GLK PFK TDH PYK TPS G6PDH
hip1 5 1 1 1 5 1 5
HXT GLK PFK TDH PYK TPS G6PDH
hip1 5 1 1 1 5 5 5hip2 3 3 3 3 3 3 3
HXT GLK PFK TDH PYK TPS G6PDH
hip1 5 1 1 1 5 5 5hip2 3 3 3 3 3 3 3
hip3 2 1 1 1 2 7 7
×2
×7
×2
7 ×
SIMULATIONS To explain why expression of particular genes is changed, we scanned the gene expression space and translated that procedure into different gene expression profiles (GEP)
Consider a set of possible values for each enzyme.Explore all possible combinations.Total: 4.637.360 hypothetical GEPs
GLK, TPS [ 1, 2.5, 4, ..., 14.5, 16, 17.5, 19]
HXT [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
G6PDH [1, 2, 3, 4, 5, 6, 7, 8]
PFK, TDH, PYK [ 0.25, 0.33, 0.5, 1, 2, 3, 4]
HXT
GLK PFK TDH PYKTPS G6PDH
hip1 5 1 1 1 5 5 5hip2 3 3 3 3 3 3 3
hip3 2 1 1 1 2 7 7......
...
.........
...
.........
...
.........
...
...
...
.........
...
.........
...
.........
...
.........
hip4637360
×3
×3
×3
3 ×
×3
×3
×3
NADPH
Implementation of stress responses
Metabolic network
Mathematical model
Power Law form Biochemical System Theory
(Savageau, 1969)
16 25 2712 21
25 27 32 35 38 62 611 72 71521
83 84 85 812
32 35 38 43 45 49 414
43 45 49
.
1 1 2 6 2 1 5 7
.
2 2 1 5 7 3 2 5 8 6 2 11 7 2 15
.8 3 4 5 12
3 3 2 5 8 4 3 5 9 14
.
4 4 3 5 9 14
2
2
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f f f
X X X X X X
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X X X X X
53 54 55 510414
43 45 49 53 54 55 510 25 27 32 35 38 62 611 95 913414 21
5 3 4 5 10
.
5 4 3 5 9 14 5 3 4 5 10 2 1 5 7 3 2 5 8 6 2 11 9 5 132
f f f ff
f f f f f f f f f f f f f f f ff f
X X X X
X X X X X X X X X X X X X X X X X X X
Each GEP has associated a new steady state→ functional changes → HS index of performance
Reproduce basal conditions (25ºC)
Generalised Mass Action
Gene expression changes
Evaluate HS performance
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Eisen et al. PNAS. 1998 Dec 8;95(25):14863-8. DB1 http://genome-www.stanford.edu/clustering
Causton et al. Mol Biol Cell. 2001 Feb;12(2):323-37 DB2http://web.wi.mit.edu/young/environment
Gasch et al. Mol Biol Cell. 2000 Dec;11(12):4241-57 DB3http://WW-genome.stanford.edu/yeast_stress
Conceptual model
Mathematical model
Reproduce basal conditions 25ºC
Calculate new steady states (37º)
SIMULATION OF GEPs
Select which fulfill the criteria of performance
CASE 1CASE 2………
etc
MICROARRAY (3DB)
Conceptual model
Mathematical model
Reproduce basal conditions 25ºC
Calculate new steady states (37º)
SIMULATION OF GEPs
Select which fulfill the criteria of performance
CASE 1CASE 2………
etc
MICROARRAY (3DB)
Define Heat Shock performance
SIMULATIONS
4.637.360 hypothetical gene expression profiles (GEPs)
Criteria of performance
C1- Synthesis of ATP C2- Synthesis of trehalose C3- Synthesis of NADPH
“Well-known” and studied by experimentalist
►20Abril 2008 CRG
C1-C3 Production of trehalose, ATP, and NADPH
If we only consider the criteria concerning an increase of fluxes selects a wide set of possible GEPs (27.8 %, 1.290.454)
The enzymes involved directly in the synthesis should be over-expressed. No clear conclusion can be reached.
In many cases, flux increase involve large metabolite accumulation, which is an undesirable situation in terms of appropriate response
■ % of the change-folds before any selection ■ % of the change-folds after selecting by C1-C3
Fold change in gene expression
% o
f to
tal G
EP
s
HXT: Hexose transporters
GLK: Glucokinase
PFK: Phosphofructokinase
TDH: Glyceraldhyde 3P dehydrogenase
PYK: Pyruvate kinase
TPS: Trehalose phosphate syntase
G6PDH: Glucose-6-P dehydrogenase
21
Criteria of performance
C4- Accumulation of intermediates: High fluxes with high metabolite concentrations are considered a sub-optimal adaptation Reactivity Cell solubility Metabolic waste
C5- Cost of changing gene expression: GEPs that allow adaptation with minimal changes in gene expression are favoured Adaptation should be economic Minimize protein burden
“Well-known” and studied by experimentalist
Well-studied within a system biology perspective
C1- Synthesis of ATP C2- Synthesis of trehalose C3- Synthesis of NADPH
abs ln mRNA change foldCost cost
50 %
No experimental measures are available, so we have chosen as a threshold the value that includes de 50% of all the cases
Evaluation of physiological requeriments Accumulation of intermediates (C4)
High fluxes with unnecessary high metabolite concentrations are considered a sub-optimal adaptation G6P is required for trehalose synthesis F16P is required for glycerol synthesis We allow for increase in some metabolites but select those cases
that fulfill C1-C3 with the lowest metabolite increment
Values for Criteria Percentage of GEPs selected using each
criteria
Absolute values Ratio to basal values Individual Accumulated
C1 VATPa > 180.6 3 45.13e
C2 VTREa > 0.03 25 60.95e
C3 VNADPHa > 3.54 2 85.86e 27.83
C4 GLCb < 0.04 1.2 86.40f
G6Pb < 20.22 20 76.04f
F16Pb < 22.86 2.5 51.91f
PEPb < 0.01 1.2 65.44f
ATPb < 6.77 6 89.32f 2.40
C5 Costc < 12.06 12.06 50 0.59
C6 VGlycerola > 0.39 0.22 50 0.25
C7 d < 28.10 0.391 50 0.16
C8 F16Pb > 8.64 0.95 61.93 0.06
►23Abril 2008 CRG
Evaluation of physiological requeriments Adaptation should be economic (C5)
GEPs that allow adaptation with minimal changes in gene expression should be favoured, among other things because they minimize protein burden to the cell and avoid an exaggerated cost in changing the gene expression.
Values for Criteria Percentage of GEPs selected using each
criteria
Absolute values Ratio to basal values Individual Accumulated
C1 VATPa > 180.6 3 45.13e
C2 VTREa > 0.03 25 60.95e
C3 VNADPHa > 3.54 2 85.86e 27.83
C4 GLCb < 0.04 1.2 86.40f
G6Pb < 20.22 20 76.04f
F16Pb < 22.86 2.5 51.91f
PEPb < 0.01 1.2 65.44f
ATPb < 6.77 6 89.32f 2.40
C5 Costc < 12.06 12.06 50 0.59
C6 VGlycerola > 0.39 0.22 50 0.25
C7 d < 28.10 0.391 50 0.16
C8 F16Pb > 8.64 0.95 61.93 0.06
fold changelnabsCost
Compute the Cost for each pattern
Select those cases that have a Cost below the median
Cost
50%
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Criteria of performance
C1- Synthesis of ATP C2- Synthesis of trehalose C3- Synthesis of NADPH
C4- Accumulation of intermediates C5- Cost of changing gene expression
C6- Glycerol production C7- TPS and PFK over-expression C8- F16P levels should be maintained
“Well-known” and studied by experimentalist
Well-studied within a system biology perspective
►25Abril 2008 CRG
C6- Glycerol production
Glycerol production helps in producing NADPH from NADH
New synthesis of glycerolipids required
Genes are over-expressed
Glicerol rate
50%Selecting GEPs with the highest glycerol production is synonymous of selecting GEPs with low PYK over-expression
►26Abril 2008 CRG
C7- TPS and PFK
TPS is directly related with vtrehalose PFK is inversely related with vtrehalose If PFK is over-expressed, then TPS should also be
over-expressed, which compromises the cost Sensitivity analysis shows that the system is
highly sensible to change PFK
F16P is required for glycerol synthesis F16P feed-forward effect to the lower part of the
glycolysis PYK velocity is increased in vitro by as much as 20 by F16P and hexose
phosphates in their physiological concentration ranges This enzyme modulation facilitates the flow of material and avoids
accumulation of intermediates
/ t r e h a lo s eT P S P F K v
50%
C8- F16P levels should be maintained
Glycogen Trehalose
►27Abril 2008 CRG
Results based on all previous criteria
Values for Criteria Percentage of GEPs selected
using each criteria
Absolute values Ratio to basal
values Individual Accumulated
C1 VATPa > 180.6 3 45.13e
C2 VTREa > 0.03 25 60.95e
C3 VNADPHa > 3.54 2 85.86e 27.83
C4 GLCb < 0.04 1.2 86.40f G6Pb < 20.22 20 76.04f F16Pb < 22.86 2.5 51.91f PEPb < 0.01 1.2 65.44f ATPb < 6.77 6 89.32f 2.40
C5 Costc < 12.06 12.06 50 0.59 C6 VGlycerol
a > 0.39 0.22 50 0.25 C7 d < 28.10 0.391 50 0.16 C8 F16Pb > 8.64 0.95 61.93 0.06
►28Abril 2008 CRG
Selected profiles
HXT: Hexose transporters
GLK: Glucokinase
PFK: Phosphofructokinase
TDH: Glyceraldhyde 3P dehydrogenase
PYK: Piruvate kinase
TPS: Trehalose phosphate syntase
G6PDH: Glucose-6-P dehydrogenase
■ % of the change-folds before any selection ■ % of the change-folds after selecting by ALL criteria
Fold change in gene expression
% o
f to
tal G
EP
s
Fulfill all criteria of HS performance:• SIMULATION: 0.06% of GEPs (4238 ) • All experimental databases
Eisen et al. at 10 min (BD1 10’) Causton et al. at 15’ (BD2 15’) Gasch et al. at 10’ (DB3 10’) Gasch et al. at 15’ (DB3 15’) Gasch et al. at 20’ (DB3 20’)
►29Abril 2008 CRG
Interpretation To generate an appropriate HS response some enzymes have a
restricted range of allowable variation. High sensitivity towards these enzymes can explain this result Enzymes (genes) that show no changes may be very important to
understand adaptive responses Fine tuning of fluxes and metabolite levels should be achieved
through coordinated changes in several enzyme levels. The experimental GEPs are situated within the predicted
ranges Our analysis helps identifying the more appropriate GEPs. Also,
we can explain why most of the hypothetical GEPs are inappropriate for HS response.
The considered criteria can be seen as constrains for heat shock performance
►30Abril 2008 CRG
Dynamic gene expression after heat shock Obtain precise measurements of gene expression changes
Heat shock from 25ºC to 37ºC 12 data points to characterize the time profile 8 replicates (2+3+3) for each data point
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Preliminary results and questions Gene expression profiles
Maximum increases (decreases) are observed after 10-20 min
Short time effects must have an important role (activity changes due to temperature)
This analysis requires dynamic models and a combination of genomic, proteomic, and metabolomic data (not yet available).
Mapping into each pathway Within the same pathway, up- and down-regulation may
occur
Which is the meaning of the unchanged genes?
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Protein biosynthesis
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A coordinated rearrangement of fluxes and metabolites is required for an adaptive response.
Evolution of specific gene expression profiles allow to fulfill these requirements.
Abril 2008 CRG ►35
0 10 20 30 40 50 600
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15 00
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30 00
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Y D R07 4W TP S2
0 10 20 30 40 50 600
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trehalose phosphatases
Trehalose is very important in heat shock response.
Trehalose phosphatases genes increase their expression after heat shock (although it takes about 10 min. to reach a maximum in expression)
Short term effects on activity may play an important role in increasing trehalose
Abril 2008 CRG ►36
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20 00
30 00
40 00
Time
26 75 H SP 1 2
0 10 20 30 40 50 600
10 00
20 00
30 00
40 00
Time
33 01 SSA 3
0 10 20 30 40 50 600
10 00
20 00
30 00
40 00
Time
34 57 CA R2
0 10 20 30 40 50 600
10 00
20 00
30 00
40 00
Time
36 20 P IN 3
0 10 20 30 40 50 600
10 00
20 00
30 00
40 00
Time
37 38 SSE 2
0 10 20 30 40 50 600
10 00
20 00
30 00
40 00
Time
39 72 G RE 3
0 10 20 30 40 50 600
10 00
20 00
30 00
40 00
Time
47 30 un kn ow n
0 10 20 30 40 50 600
10 00
20 00
30 00
40 00
Time
48 16 H SP 7 8
0 10 20 30 40 50 600
10 00
20 00
30 00
40 00
Time
50 74 P RX1
0 10 20 30 40 50 600
10 00
20 00
30 00
40 00
Time
56 69 Y G P 1
ORF that are almost undetectable a t=0 and that reach high values after heat shock
Out[168]/ /TableF orm =
YGL037C PNC1 nicotinamidase chromatin silencing at ribosomal DNA rDNA, chromatin silencing at telomere, nicotinate nucleotide biosynthesis, salvageYNL006W LST8 unknown signal transduction, transportYOR120W GCY1 aldoketo reductase activity salinity responseYER150W SPI1 unknown unknownYMR105C PGM2 phosphoglucomutase activity glucose 1phosphate utilization, glucose 6phosphate utilizationYFL014W HSP12 heat shock protein activity cell adhesion, hyperosmotic response, response to dessication, response to heat, response to oxidative stressYBL075C SSA3 heat shock protein SRPdependent, cotranslational membrane targeting, translocation, protein folding, response to stressYLR438W CAR2 ornithineoxoacid aminotransferase arginine catabolismYPR154W PIN3 unknown unknownYBR169C SSE2 heat shock protein protein foldingYHR104W GRE3 aldehyde reductase activity arabinose metabolism, response to stressYHR087W unknown unknown unknownYDR258C HSP78 ATPdependent peptidase activity, chaperone activity, heat shock protein activity protein folding, mitochondrial genome maintenance, response to stress, mitochondrial translocationYBL064C PRX1 thioredoxin peroxidase activity regulation of redox homeostasisYNL160W YGP1 unknown response to nutrients, response to stressYKL035W UGP1 UTPglucose1phosphate uridylyltransferase activity UDPglucose metabolism, protein amino acid glycosylationYNL274C unknown oxidoreductase activity, acting on the CHOH group of donors, NAD or NADP as acceptor metabolism
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PNC1 (YGL037C ): Nicotinamidase that converts nicotinamide to nicotinic acid as part of the NAD(+) salvage pathway, required for life span extension by calorie restriction; PNC1 expression responds to all known stimuli that extend replicative life span
0 10 20 30 40 50 600
10 00
20 00
30 00
40 00
Time
14 P N C1
Which is the connection of these changes with survival after heat shock?
Dynamic changes Questions, problems, and more
Dynamic changes at the gene level should be correlated to enzyme levels Delays in changing enzyme levels must be considered Post-transcriptional changes can be very important
Which are the relevant changes short after heat shock? Changes in enzyme activity due to temperature and other
factors (independent from gene expression changes) Metabolite profiles would be required to reconstruct the
adaptive response at the level of enzyme changes Models are required to interpret and understand the
dynamic changes
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Conclusions
Adaptive response to stress conditions requires a fine tuning of metabolic processes
Compensatory changes in enzyme activity leads to an appropriate response
Gene expression changes remain to be fully understood
Mathematical models play a central role in solving this puzzle
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►40
Relevance of models based in approximated representations for Systems Biology applications
Approximated representations are required for practical reasons. Systematic representation. Models can be produced
automatically from schemes. Qualitative information can be incorporated into these
models. Models can be easily updated and shared.
The power-law formalism has a whole set of tools and strategies that facilitates the investigation of design and operational principles. (log)linear and lin-log approximations, at best, can produced
results similar to those obtained using a power-law formalism.
The SC formalism can be used to complement the results of the power-law formalism, particularly in the dynamic range.
Abril 2008 CRG
►41
Research projects in our groupweb.udl.es/Biomath/Group
Mathematical models for Systems Biology Sorribas A, Hernandez-Bermejo B, Vilaprinyo E, Alves R Cooperativity
and saturation in biochemical networks: a saturable formalism using Taylor series approximations. Biotechnol Bioeng. (2007) 97(5):1259-77.
Alves R, Antunes F, Salvador A. Tools for kinetic modeling of biochemical networks. Nat Biotechnol. (2006) Jun;24(6):667-72.
Pathway identification through integration of information and automatic model generation and screening Alves R, Sorribas A. In silico pathway reconstruction: Iron-sulfur
cluster biogenesis in Saccharomyces cerevisiae. BMC Syst Biol. (2007) 1:10.
Alves R, Herrero E, Sorribas A. Predictive reconstruction of the mitochondrial iron-sulfur cluster assembly metabolism. II. Role of glutaredoxin Grx5. Proteins. (2004) 57(3):481-92.
Alves R, Herrero E, Sorribas A. Predictive reconstruction of the mitochondrial iron-sulfur cluster assembly metabolism: I. The role of the protein pair ferredoxin-ferredoxin reductase (Yah1-Arh1). Proteins. (2004) 56(2):354-66.
Design principles in the yeast stress response Vilaprinyo E, Alves R, Sorribas A. Use of physiological constraints to
identify quantitative design principles for gene expression in yeast adaptation to heat shock. BMC Bioinformatics. (2006) 7:184.
Abril 2008 CRG
Acknowledgements Benito Hernández-Bermejo URJ Madrid, Spain Armindo Salvador, U.Coimbra, Portugal Eberhard O. Voit, Georgia Tech, Atlanta, USA Michael A. Savageau, UCDavis, USA José Enrique Perez Ortín, U.Valencia, Spain Enric Herrero, Gemma Bellí, U.Lleida, Spain Alex Sánchez, Maria del Carmen Ruiz de Villa, U.Barcelona,
Spain
MEC BFU2005-00234/BMC Ramon y Cajal Fellowship
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