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http://creativecommons.org/licenses/by-sa/2.0/. Generic and specific constraints shaping adaptive gene expression profiles in yeast. Prof:Rui Alves [email protected] 973702406 Dept Ciencies Mediques Basiques, 1st Floor, Room 1.08

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http://creativecommons.org/licenses/by-sa/2.0/


Generic and specific constraints shaping adaptive gene expression profiles in yeast

Generic and specific constraints shaping adaptive gene expression profiles in yeast

Prof:Rui Alves

[email protected]

973702406

Dept Ciencies Mediques Basiques,

1st Floor, Room 1.08

Website of the Course:http://web.udl.es/usuaris/pg193845/Courses/Bioinformatics_2007/

Course: http://10.100.14.36/Student_Server/


Introduction

Introduction

  • To survive yeast changes its gene expression profile

  • This allows adaptation of fluxes and concentrations

  • Environmental conditions change. Cells living in those environments need to adapt to those changes in order to survive environmental stresses (heat shock, osmotic...).

Stress


Introduction1

Introduction

  • In principle different quantitative and qualitative gene expression profiles (GEP) could produce the same physiological adaptation

  • However, what has been observed is that GEPs are specific for each type of stress


Constraints to the changes in gene expression

Constraints to the changes in gene expression

  • Adaptation is multiobjective.

  • Gene expression profiles (GEPs) must induce expression of genes whose proteins are needed for the response

    • SPECIFIC CONSTRAINTS

  • There may be constraints that are common to most stress conditions?

    • GENERAL CONTRAINTS?


Goals

Goals

  • Can we identify general and specific constraints that shape an adaptive gene expression profile (GEP) of yeast under stress conditions?

  • If so, can we use them to characterize the quantitative changes (design principles) required for a given response?


Outline

Outline

  • Identification of a general type of constraints to GEP design

  • Identification of specific constraints for heat shock & Quantitative design of GEPs in heat shock response


What is common to all stress responses

What is common to all stress responses?

  • To adapt quickly cells need to synthesize proteins quickly and using as few resources as possible.

  • Globally, changes in gene expression correlate well with changes in protein levels.

  • Proteins are the most expensive of macromolecules.

  • Synthesis of new metabolites is expensive but stress specific.

  • Therefore a general selective pressure in stress response to adapt quickly and at low cost could shape the regulation of expression for the different genes in the GEP


How to save resources in protein synthesis

How to save resources in protein synthesis?

  • H1: If proteins are abundant in the basal state, the cell is spending energy synthesizing them and keeping them at high level. Because their activity is already abundant, to save energy cells could inhibit expression of abundant proteins.

Change in

gene

expression

after stress

Basal

protein

abundance

Correlation


Abundant proteins are inhibited

1/changefold

Protein abundance/103

Abundant proteins are inhibited


How to achieve a fast increase in activity

How to achieve a fast increase in activity?

  • H2: Low abundance proteins have almost no total activity. To achieve larger relative increases in activity, cell could express proteins of low abundance

Change in

gene

expression

after stress

Basal

protein

abundance

Correlation


Proteins of low abundance are overexpressed

changefold

Protein abundance/103

Proteins of low abundance are overexpressed


Are there other ways to design gep that use resources efficiently

Are there other ways to design GEP that use resources efficiently?

  • H3: If in addition to downregulation of abundant proteins, the cell downregulates genes that code for large proteins, it will save more energy.


Are there other ways to design gep that respond fast and use resources efficiently

Are there other ways to design GEP that respond fast and use resources efficiently?

  • H4: Upregulation of genes that code for small proteins. This will produce new proteins quicker and at lower cost than if upregulated proteins where larger.

Change in

gene

expression

after stress

Protein size

(MW or

length)

Correlation


Size matters in modulation of gene expression

changefold

1/changefold

Protein size (MW)

Protein size (MW)

Size matters in modulation of gene expression?

Size matters in modulation of gene expression

H3

Overexpressed genes

H4

Repressed genes


Resource usage and quickness of response general constraints for adaptive gep

Resource usage and quickness of response general constraints for adaptive GEP?

Resource usage and quickness of response general constraints for many adaptive GEP

  • H1: To save energy cells should inhibit proteins that are abundant

  • H2: To achieve larger relative increases in activity, cell should express proteins of low abundance

  • H3: Downregulation of genes that code for large proteins.

  • H4: Upregulation of genes that code for small proteins.

The hypotheses are consistent with these selective pressures in the design of adaptive GEPs


Outline1

Outline

  • Identification of a general constraint to GEP

  • Identification of specific constraints for heat shock & Quantitative design of GEPs in heat shock response


Heat shock response

Heat shock response

  • Well characterized physiologically

  • Previous work (Voit & Radivovevitch)

  • Enough information to identify contraints

  • Enough information for mathematical modelling of the relevant reactions


Metabolic network physiological constraints

Glycogen Trehalose

Metabolic network & physiological constraints

REDUCING POWER

New synthesis of sphingolipids in order to change the membrane fluidity

C3

NADPH

STRUCTURAL INTEGRITY

-Avoids aggregation of denatured proteins

-Membrane

-Acts in synergism with chaperones

C2

HIGH ENERGY DEMAND

C1

 Curto, Sorribas, Cascante (1995) Math. Biosci. 130, 25-50

Voit, Radivovevitch (2000) Bioinformatics 16: 1023-1037


Methodology

×5

×2

×3

×3

7 ×

3 ×

5 ×

×7

×3

×5

Glycogen Trehalose

×3

×3

×2

×3

×5

Methodology

NADPH

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]


Implementation of stress responses

Implementation of stress responses

Evaluate HS performance

Metabolic network

Mathematical model

Gene expression changes

Power Law form Biochemical System Theory (Savageau, 1969)

Generalised Mass Action

Each GEP has associated a new steady state→ functional changes → HS index of performance

Reproduce basal conditions (25ºC)


Criteria of performance

C1- Synthesis of ATP

C2- Synthesis of trehalose

C3- Synthesis of NADPH

Criteria of performance

“Well-known” and studied by experimentalist


C1 c3 production of trehalose atp and nadph

% of total GEPs

Fold change in gene expression

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.

  • 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

HXT: Hexose transporters

GLK: Glucokinase

PFK: Phosphofructokinase

TDH: Glyceraldhyde 3P dehydrogenase

PYK: Pyruvate kinase

TPS: Trehalose phosphate syntase

G6PDH: Glucose-6-P dehydrogenase


Criteria of performance1

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

50 %

cost

Criteria of performance

“Well-known” and studied by experimentalist

  • C1- Synthesis of ATP

  • C2- Synthesis of trehalose

  • C3- Synthesis of NADPH

Well-studied within a system biology perspective

No experimental measures are available, so we have chosen as a threshold the value that includes de 50% of all the cases


Criteria of performance2

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

Criteria of performance

“Well-known” and studied by experimentalist

Well-studied within a system biology perspective


C6 glycerol production

Glycerol production helps in producing NADPH from NADH

New synthesis of glycerolipids required

Genes are over-expressed

C6- Glycerol production

50%

Selecting GEPs with the highest glycerol production is synonymous of selecting GEPs with low PYK over-expression

Glicerol rate


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 C5 (cost)

Sensitivity analysis shows that the system is highly sensible to change PFK

Glycogen Trehalose

C7- TPS and PFK

50%


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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

C8- F16P levels should be maintained


Results based on all previous criteria

Results based on all previous criteria

C8

C7

C1

C6

C2

C5

C3

C4


Selected profiles

% of total GEPs

Fold change in gene expression

Selected profiles

■% of the change-folds before any selection

■% of the change-folds after selecting by ALL criteria

HXT: Hexose transporters

GLK: Glucokinase

PFK: Phosphofructokinase

TDH: Glyceraldhyde 3P dehydrogenase

PYK: Piruvate kinase

TPS: Trehalose phosphate syntase

G6PDH: Glucose-6-P dehydrogenase

Fulfill all criteria of HS performance:

  • SIMULATION: 0.06% of GEPs (4238 )

  • All experimental databases


Are the eight criteria of performance specific for heat shock

Are the eight criteria of performance specific for heat shock?

We analyzed 294 GEPs from microarray experiments under different environmental conditions

 Only heat shock conditions are selected


What happens under other conditions principal component analysis

factor1

factor2

factor3

factor4

factor2

factor3

factor4

factor1

What happens under other conditions? (Principal Component Analysis)

HeatS

factor1

Diamide

Stationary

H2O2

HeatS

factor3

factor2

Sporulation

Stationary

Diamide

H2O2


Summary

Summary

  • Identification of general constraints in GEP

  • Identification of a set of constraints that are specific for heat shock

  • Identification of the quantitative design of the heat shock GEP

  • Support by experimental evidence

  • Specificity of the set of constraints


Acknowledgments

Acknowledgments

  • FCT

  • Ramon y Cajal Program MCyT

  • FUP program MCyT


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