Design Principles in Biology:

a consequence of evolution and natural selection

Rui AlvesUniversity of Lleidaralves@cmb.udl.es

Climbing down mount improbable

• Overtime, edged stones would accumulate on the slope.

• Smooth, round, stonesaccumulate at the bottom.

Design Principles:- Smooth, roundish rocks roll down the mountain.- Edged, flat, rocks don’t.

Design principles in molecular biology

• Similarly, if a topology or set of parameters can be shown to create a molecular network that functionally outperforms all other possible alternatives in a given set of conditions, one can talk about a design principle for the system under those conditions.

[sensu engineering]

Index of talk

• How to identify design principles in molecular networks

• Design principles in:– Gene expression– Metabolic networks– Signal transduction– Development

• Design principles, what are they good for?• Summary

First step, define the alternatives

Gene

Regulator

+Gene

Regulator_

X0 X1 X2 X3

X0 X1 X2 X3

First step, define the alternatives

X0 X1 X2 X3

X3

t

How strong should the feedback be?

Then, create models for each alternative

Gene

Regulator

+Gene

Regulator_

Then, create models for each alternative

X0 X1 X2 X3

X0 X1 X2 X3

Characterization of network behavior

Biological functional effectiveness criteria for the network.

Alternative designs

X1 … Xj …

X1 … Xj …

…

Mathematical models

Enforce mathematical controls before analyzing model behavior

Comparison of behavior between networks

Index of talk

• How to identify design principles in molecular networks

• Design principles in:– Gene expression– Metabolic networks– Signal transduction– Development

• Design principles, what are they good for?• Summary

The demand theory for gene expression

• Are there situations where positive regulation of gene expression outperforms negative regulation of gene expression and vice versa?

Gene

Regulator

+Gene

Regulator_

Regulating gene expression has principles

• Positive regulator:– More effective when gene product in demand for large

fraction of life cycle.– Less noise sensitive if signal is low.

• Negative regulator:– More effective when gene product in demand for small

fraction of life cycle.– Less noise sensitive if signal is high.

Gene

Regulator

+Gene

Regulator_

Genetics 149:1665; PNAS 103:3999; PNAS 104:7151;Nature 405: 590

Glycogen Trehalose

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20HXT

GLK

PFK

TDHPYK

TPS

G6PDH

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20HXT

GLK

PFK

TDHPYK

TPS

G6PDH

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20HXT

GLK

PFK

TDHPYK

TPS

G6PDH

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20HXT

GLK

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TDHPYK

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G6PDH

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20HXT

GLK

PFK

TDHPYK

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G6PDH

(a) (b)

(c) (d)

Regulating gene expression has principles

Design principles in development

Design principles in development

Index of talk

• How to identify design principles• Design principles in:

– Gene expression– Metabolic networks– Signal transduction– Development

• Design principles, what are they good for?• Summary

Negative overall feedback is a design principle in metabolic biosynthesis

X0 X1 X2 X3

• Negative overall feedback:– More effective in coupling production to demand.– More robust to fluctuations.

Bioinformatics 16:786; Biophysical J. 79:2290

Index of talk

• How to identify design principles• Design principles in:

– Gene expression– Metabolic networks– Signal transduction– Development

• Design principles, what are they good for?• Summary

Bifunctional sensors can be a design principle in signal transduction

• Bifunctional sensor:– Performs best against cross talk

• Independent deactivator:– Better integrator of signals

Mol. Microbiol. 48:25; Mol. Microbiol. 68: 1196

Signal

SensorSensor

EfectorEfectorDeactivator

Effect

Index of talk

• How to identify design principles• Design principles in:

– Gene expression– Metabolic networks– Signal transduction– Development

• Design principles, what are they good for?• Summary

Gene

Regulator_

Design principles in development

Gene

Regulator

+

High demand, low signal

Signal

+

High demand, high signal

Low demand, high signal

Low demand, low signal

Signal _

Genetics 149:1665; PNAS 103:3999; PNAS 104:7151;Nature 405: 590

Index of talk

• How to identify design principles• Design principles in:

– Gene expression– Metabolic networks– Signal transduction– Development

• Design principles, what are they good for?• Summary

Biological design principles are good to understand why biology works as it does

• Biological design principles may connect molecular determinants to functional effectiveness.

Heat shock

Expr

essio

n of

im

port

ant g

enes

time

Grow

th ra

te

time

BMC Bioinformatics 7:184

Underlying assumption

• Evolution of molecular networks can be treated as modules.

• Work in the group of Uri Alon suggests that– networks evolving to meet simultaneous goals

evolve in a modular fashion– Networks evolving to meet a single goal evolve

globally• Modularity seems like a reasonable first

assumptionPNAS 102:13773; PLOS Comp Biol 4:e1000206;BMC Evol biol 7: 169

The good news about function

• Sometimes, you get stuff for free!!!

• For example:– networks that are responsive to signals, just because

they are responsive may have inbuilt buffering of noise.

– Functions that are associated with marginally stable proteins are favored because due to the large dimensions of sequence space most randomly selected sequences have a structure that is marginally stable.

PNAS 100:14463; PNAS 103:6435; Proteins 46:105

How can biological design principles be applied?

• Design of molecular circuits with specific behaviors!!

Stable Systems

Unstable systems

Oscilations

Bistable systems

Cell 113: 597; PLoS Comput Biol. 5:e1000319; PNAS 106: 6435

Index of talk

• How to identify design principles• Design principles in:

– Gene expression– Metabolic networks– Signal transduction– Development

• Design principles, what are they good for?• Summary

Summary

• Design principles can be found in molecular networks.

• Such principles can sometimes be connected to selection for function effectiveness.

• Even in the absence of such a connection, if they are valid they can be used to build biological circuits with specific behaviors.

Acknowledgments

Mike SavageauAlbert SorribasArmindo SalvadorOleg Igoshin

Programa Ramon y Cajal MCyT

MCyTFCTNIH