Network Motifs in		 Prebiotic Metabolic Networks
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Network Motifs in Prebiotic Metabolic Networks. Omer Markovitch and Doron Lancet, Department of Molecular Genetics, Weizmann Institute of Science. “Prebiotic Soup” 4,000,000,000 years ago. The emergence of the first cell-like entity, the Protocell.

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Network Motifs in Prebiotic Metabolic Networks

Omer Markovitch and Doron Lancet,

Department of Molecular Genetics,

Weizmann Institute of Science


“Prebiotic Soup”

4,000,000,000 years ago

The emergence of the first cell-like entity, the Protocell.



The Lipid World Scenario for the Origin of Life Darwinian evolution.

Spontaneous formation of lipid assemblies may seed life

Spontaneous aggregation

Micelle / Assembly

Lipid

(Hydrophilic head; Hydrophobic tail)

Membrane

Segre, Ben-Eli, Deamer and Lancet, Orig. Life Evol. Biosph. 31 (2001)


Assemblies / Clusters / Vesicles / Membranes Darwinian evolution. Composition

DNA / RNA / Polymers  Sequence

<<Bridging Metabolism and Replicator>>

Segre and Lancet, EMBO Reports 1 (2000)


Two scenarios for increasing Darwinian evolution.network complexity

RNA world: Increasing node count

Lipid World: Increasing node fidelity

How the network structure & properties affect evolution ?


GARD model (Graded Autocatalysis Replication Domain) Darwinian evolution.

Homeostatic growth

b

Composition

Symbolic lipids

Fission / Split

Solving a set of coupled differential equations, using Gillespie’s algorithm.

b Environmental Chemistry

Segre, Ben-Eli and Lancet, Proc. Natl. Acad. Sci. 97 (2000)


Example of GARD Similarity ‘Carpet’ Darwinian evolution.

Following a single lineage.

Composome, quasi-stationary state

Compositional Similarity


Populations in GARD Darwinian evolution.

Fixed population size.


b Darwinian evolution. ; Catalytic Network of Rate-Enhancments

bij

j

i

bij

b

More mutualistic

More selfish

*Self-catalysis is the chemical manifestation of self-replication [Orgel, Nature 358 (1992)]


Examples for selection in GARD Darwinian evolution.

Slightly biasing the growth rate of assemblies, depending on similarity / dis-similarity to a target composome.

Target before selection

Target after selection

Positive response

Negative response


Selection in GARD Darwinian evolution.

Positive

Negative

Hits

Based of 1,000 simulations.

Markovitch and Lancet, Artificial Life (2012)


How the Darwinian evolution.b network effects selection ?

Probability (log10 scale)

Based of 1,000 simulations, each based on a different b network.

Self | Mutual

Markovitch and Lancet, Artificial Life (2012)


High Darwinian evolution.mutual-catalysis is required for effective evolvability.

Too much self-catalysis hampers evolution (dead-end).

Metabolic networks tend to be mutualistic.

Micro  Macro


So we need more mutual-catalysis Darwinian evolution.

But of what type / shape?

Network motifs – design patterns of nature. (sub-graphs that appear more then random)

Uri Alon, Nature Review Genetics (2007)


Network motifs in GARD Darwinian evolution.

Graded b (weights)

Binary b (1, 0)

Graded to binary

Find motifs

Catalytic score

( Feed forward loop {5} )


(omitted from web presentation) Darwinian evolution.


Families of networks Darwinian evolution.

Milo et al, Science (2004)


Principle Component analysis (PCA) Darwinian evolution.

Project the 13th dimensional space of network motifs into another 13th dimensional space, that maximizes the variance in the original data.

For each b, a 13-long vector describes its network motifs profile, but this time with linear combination that maximizes the variance.


(omitted from web presentation) Darwinian evolution.


Acknowledgments Darwinian evolution.:

Uri Alon.

Avi Mayo.

Lancet group.

Omer Markovitch


Compotype diversity of 10,000 GARD lineages Darwinian evolution.

Each based on a different b network.

Probability (log10 scale)

Self | Mutual

Markovitch and Lancet, Artificial Life (2012)


Real GARD (Rafi Zidovezki from U. California Riverside) Darwinian evolution.

Real lipids: phosphate-idyl-(serine / amine / choline), sphingo-myelin and cholesterol.

Actual physical properties (charge, length, unsaturation).

R = -0.85

Armstrong, Markovitch, Zidovetzki and Lancet, Phys. Biol. 8 (2011).


Selection towards a specific target composition Darwinian evolution.

  • Selection of GARD assemblies towards a target compotype.

  • Identify most frequent compotype (= target).

  • Rerun the same simulation while modifying the bij values at each generation, biasing the growth rate towards the target.

H: compositional similarity between current and target.

Markovitch and Lancet, Artificial Life (2012)


GARD model Darwinian evolution.(graded autocatalytic replication domain)

Rate enhancement

Molecular repertoire

Assembly growth

backward (leave)

forward (join)

Fission (split)


Selection response of 1,000 GARD populations Darwinian evolution.

Probability (log10 scale)

Target frequency, after selection

Target frequency, before selection

Each based on a different b network.

Markovitch and Lancet, Artificial Life (2012)


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