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This presentation explores the fundamental design principles shaped by evolution and natural selection within biological systems. It discusses how specific molecular networks are optimized for effectiveness under varying conditions, highlighting principles in gene expression, metabolic networks, signal transduction, and development. By examining alternative designs and regulatory mechanisms, we aim to characterize network behavior and assess their biological functionality. Understanding these principles enriches our knowledge of how biology operates, connecting molecular determinants to functional outcomes.
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DesignPrinciples in Biology: a consequence of evolution and natural selection Rui Alves University of Lleida ralves@cmb.udl.es
Climbingdownmount improbable • Overtime, edgedstoneswould accumulateontheslope. • Smooth, round, stones accumulate at the bottom. DesignPrinciples: - Smooth, roundishrocks roll downthemountain. - Edged, flat, rocksdon’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 Regulator Regulator _ + Gene Gene X0 X1 X2 X3 X0 X1 X2 X3
First step, define the alternatives X3 X0 X1 X2 X3 How strong should the feedback be? t
Then, create models for each alternative Regulator Regulator _ + Gene Gene
Then, create models for each alternative X0 X1 X2 X3 X0 X1 X2 X3
Characterization of networkbehavior Biological functional effectiveness criteria for the network. Alternativedesigns … Comparison of behaviorbetweennetworks X1 … Xj … X1 … Xj … Mathematical models Enforce mathematical controls before analyzing model behavior
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 Regulator Regulator _ • Are there situations where positive regulation of gene expression outperforms negative regulation of gene expression and vice versa? + Gene Gene
Regulating gene expression has principles Regulator Regulator _ • 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 Gene Genetics 149:1665; PNAS 103:3999; PNAS 104:7151;Nature405: 590
Glycogen Trehalose Regulating gene expression has principles
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 • Negative overall feedback: • More effective in coupling production to demand. • More robust to fluctuations. X0 X1 X2 X3 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 Signal Sensor Sensor Efector Deactivator Efector Effect • Bifunctional sensor: • Performs best against cross talk • Independent deactivator: • Better integrator of signals Mol. Microbiol. 48:25; Mol. Microbiol. 68: 1196
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
Design principles in development Regulator Regulator _ Signal Highdemand, lowsignal + Signal _ Gene Gene + Highdemand, highsignal Lowdemand, lowsignal Lowdemand, highsignal 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. Expression of important genes Heat shock Growthrate time 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 assumption PNAS 102:13773; PLOS CompBiol 4:e1000206;BMC Evolbiol7: 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!! Bistablesystems Unstablesystems StableSystems Oscilations Cell 113: 597; PLoSComputBiol. 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 Programa Ramon y CajalMCyT MCyT FCT NIH Mike Savageau Albert Sorribas Armindo Salvador Oleg Igoshin