Endless evolutionary paths to Virtual Microbes

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1 Endless evolutionary paths to Virtual Microbes Thomas Cuypers Paulien Hogeweg Theoretical Biology Utrecht University

2 OUTLINE BACKGROUND evolution in Virtual Cells MODEL OVERVIEW OBSERVATIONS Metabolisms in Flux TF regulation CONCLUSIONS ACKNOWLEDGEMENTS

3 EVOLVABILITY (micro) organisms show a remarkable ability to adapt rapidly under stress or changing conditions in vivo rapid extensive transcriptional changes (yeast) 1 adaptation to experimental condition by parallel gene loss and point mutations (e. coli) 2 1 Ferea, Schneider, Hindré

4 EVOLVABILITY (micro) organisms show a remarkable ability to adapt rapidly under stress or changing conditions in vivo rapid extensive transcriptional changes (yeast) 1 adaptation to experimental condition by parallel gene loss and point mutations (e. coli) 2 Question: does evolvability evolve? 1 Ferea, Schneider, Hindré

5 IN SILICO when environment alternates between discreet states genome restructuring regulatory changes biases spectrum towards favourable mutations 1 1 Crombach & Hogeweg, 2008

6 IN BIOLOGY However environmental change on continuum (vs. predictable) organisms sense their environment ecological interactions may promote or reduce need for adaptation

7 IN BIOLOGY However environmental change on continuum (vs. predictable) organisms sense their environment ecological interactions may promote or reduce need for adaptation Redefined question: how do evolvability, regulation and ecosystem interact?

8 EVOLUTION OF EVOLVABILITY defining the problem space: manifests when conditions change (intrinsic or extrinsic)

9 EVOLUTION OF EVOLVABILITY defining the problem space: manifests when conditions change (intrinsic or extrinsic) regulation may interfere with evolution of evolvability

10 EVOLUTION OF EVOLVABILITY defining the problem space: manifests when conditions change (intrinsic or extrinsic) regulation may interfere with evolution of evolvability evolution of evolvability can imprint GRN as well as genome structure

VIRTUAL CELLS Virtual Cell model has TFs sense internal metabolites continuous environment also drastic environmental change evolve for homeostasis Mutations: genome

11 VIRTUAL CELLS Virtual Cell model has TFs sense internal metabolites continuous environment also drastic environmental change evolve for homeostasis Mutations: genome scale dup, del, invert, translocate genes: enzymes alter metabolic constants 1 sequences bit string mutations 1 Cuypers & Hogeweg, 2012; adapted from Neyfakh et al, 2006

drastic competition between evolutionary adaptation and

12 DIFFERENT STRATEGIES EVOLVE We observed: evolution of homeostasis regulation fast readaptation when change is drastic competition between evolutionary adaptation and regulation (timescales) 1 1 in collaboration with Jaap Rutten (in progress)

13 TOWARDS VIRTUAL MICROBES

14 WHAT IS THERE TO DO? no explicit fitness function that can be optimized (cf. Virtual Cell), instead: increase production through metabolism avoid toxic build up of internal metabolites ecosystem feedback changes the fitness seascape.

COUNTING GENES at t = 200000 change from fluctuating to constant environment Fast initial

15 COUNTING GENES at t = change from fluctuating to constant environment Fast initial increase, and tendency to reduce on long time scale (cf. Knibbe & Beslon, Cuypers & Hogeweg)

16 B ACKGROUND M ODEL O VERVIEW GENE EXPRESSION O BSERVATIONS C ONCLUSIONS A CKNOWLEDGEMENTS

17 B ACKGROUND M ODEL O VERVIEW O BSERVATIONS C ONCLUSIONS GENE EXPRESSION why do pump and enzyme expression have opposite evolutionary pattern? A CKNOWLEDGEMENTS

18 B ACKGROUND M ODEL O VERVIEW O BSERVATIONS C ONCLUSIONS GENE EXPRESSION why do pump and enzyme expression have opposite evolutionary pattern? I too high internal concentrations can be toxic A CKNOWLEDGEMENTS

19 B ACKGROUND M ODEL O VERVIEW O BSERVATIONS C ONCLUSIONS A CKNOWLEDGEMENTS GENE EXPRESSION why do pump and enzyme expression have opposite evolutionary pattern? I too high internal concentrations can be toxic I increasing metabolic enzymes can dissipate high resource concentration (metabolic regulation)

20 B ACKGROUND M ODEL O VERVIEW O BSERVATIONS C ONCLUSIONS A CKNOWLEDGEMENTS GENE EXPRESSION why do pump and enzyme expression have opposite evolutionary pattern? I too high internal concentrations can be toxic I increasing metabolic enzymes can dissipate high resource concentration (metabolic regulation) I once, established, it becomes safe to pump

21 B ACKGROUND M ODEL O VERVIEW O BSERVATIONS C ONCLUSIONS A CKNOWLEDGEMENTS GENE EXPRESSION why do pump and enzyme expression have opposite evolutionary pattern? I too high internal concentrations can be toxic I increasing metabolic enzymes can dissipate high resource concentration (metabolic regulation) I once, established, it becomes safe to pump I fine tuning of enzymes can minimize cost of expression

22 EVOLVING RESOURCE EXPLOITATION

23 CONTINUOUS CHANGE IN LINE OF DESCENT

24 METABOLISMS IN FLUX even though organisms quickly learn to exploit all metabolites, metabolism network remains in flux. sustained flux in constant environment driven by external HGT

25 WITHIN POPULATION DIVERSITY

26 WITHIN POPULATION DIVERSITY different metabolic types coexist at intermediate evolutionary time scales

27 BETWEEN POPULATION METABOLIC DIVERSITY 2.2_0 2.1_0 1.1_0 1.2_ _ _3 2.2.stop_hgt_4 2.2.stop_hgt_3 2.2.stop_hgt_2 2.2_ _ _ _ _ _ _ _ _ _ _ _2 1.1.stop_hgt_4 1.1.stop_hgt_3 1.1.stop_hgt_2 2.1.stop_hgt_4 2.1.stop_hgt_3 2.1.stop_hgt_2 2.1_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _3 1.2.stop_hgt_4 1.2.stop_hgt_3 1.2_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _2 1.1_1 1.2_1 2.0

28 BETWEEN POPULATION METABOLIC DIVERSITY 2.2_0 2.1_0 1.1_0 1.2_ _ _3 2.2.stop_hgt_4 2.2.stop_hgt_3 2.2.stop_hgt_2 2.2_ _ _ _ _ _ _ _ _ _ _ _2 1.1.stop_hgt_4 1.1.stop_hgt_3 1.1.stop_hgt_2 2.1.stop_hgt_4 2.1.stop_hgt_3 2.1.stop_hgt_2 2.1_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _3 1.2.stop_hgt_4 1.2.stop_hgt_3 1.2_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _2 1.1_1 1.2_1 2.0 strong evolutionary contingency in evolving metabolisms

29 WHAT ABOUT REGULATION?

30 WHAT ABOUT REGULATION? highly variable between evolutionary runs maintenance depends on environmental change

31 CONCLUSIONS microbes quickly evolve metabolic networks despite strong selection due to toxicity, high metabolic variation metabolisms in flux over evolutionary time continuous evolution of population diversity strong contingency of evolutionary trajectories

32 ACKNOWLEDGEMENTS Paulien Hogeweg Bram van Dijk all members of the evoevo ECAL organizers

EvoEvo Deliverable 6.6

EvoEvo Deliverable 6.6 Guillaume Beslon, Paulien Hogeweg To cite this version: Guillaume Beslon, Paulien Hogeweg. EvoEvo Deliverable 6.6:. [Research Report] INRIA Grenoble - Rhône-Alpes. 2016.