Prebiotic Evolution of Molecular Assemblies:
From Molecules to Ecology
Omer Markovitch and Doron Lancet
Department of Molecular Genetics, Weizmann Institute of Science, Israel
1
Metabolism
Eco-system
Lipid world
RNA world
DNA / RNA / Polymers 
Sequence
covalent bonds
Assemblies / Clusters /
Vesicles / Membranes 
Composition
non-covalent bonds
Segre and Lancet, EMBO Reports 1 (2000)
3
GARD model (Graded Autocatalysis Replication Domain)
Homeostatic growth
 Synthetic chemistry
 Kinetic model
 Catalytic network (b) of
rate-enhancement values
b
Rate enhancement
Fission / Split
nj 
 NG
dni
 k f i N  kb ni  1   bij 
dt
N
 j 1
i  1...NG  Molecular repertoire
Segre, Ben-Eli and Lancet, Proc. Natl. Acad. Sci. 97 (2000)
b ; Catalytic Network (environmental chemistry)
NG = 100
b
bij
“Metabolic” network
More mutualistic
More selfish
GARD model (Graded Autocatalysis Replication Domain)
Following a single lineage.
Similarity ‘carpet’
Composome (compositional genome) =
a
faithfully
replicating
composition/assembly.
ng=30; split=1.5; seed=361
1
800
0.8
600
0.6
400
0.4
200
0.2
200
400 600
Generation
800 1000
0
Compositional Similarity
Generation
1000
Compotype (composome type) = a
collection of similar composomes 
quasispecies.
6
Present-day organism –
Complex
From organisms to food webs
– Complex
Prebiotic Ecology: From molecules to Ecosystem.
( from species inner structure to food web )
Population Dynamics in GARD
Following the dynamics of a constant-size
population of assemblies.
Buffered environment (=unlimited food).
seed=45
Assembly
of population
Member
100
90
80
70
60
50
40
30
20
10
0.5
0.4
each time point, each
seed=45; omer new; no At
selection
assembly is colored by its
compotype.
C1
C2
C3
1000
2000
3000
Time [split]
4000
5000
8
Population Dynamics in GARD
Simulations exhibiting a single compotype species:
27
One example
1
Compotype population fraction
Compotype population fraction
1
0.8
0.6
0.4
0.2
0
0
0.5
1
1.5
2
2.5
3
Another1 example
3.5
4
C1
0.8
4.5
C1
0.6
0.4
0.2
0
0
5
4
Time [10 splits]
Each simulation with a different
chemistry (b network).
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
4
Time [10 splits]
9
Population Dynamics in GARD
Simulations exhibiting multiple compotypes:
0.7
0.6
0.5
C1
C2
0.4
0.3
0.2
0.1
0
0
0.5
1
1.5
2
2.5
3
3.5
45
Another example
0.6
Compotype population fraction
Compotype population fraction
One170
example
4
4.5
5
Time [104 splits]
Each simulation with a different
chemistry (b network).
C1
C2
C3
0.5
0.4
0.3
0.2
0.1
0
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Time [104 splits]
10
5
Logistic Growth
[Gause (1934)]
Independently
cultivated
Lotka-Volterra
0
5
10
15
20
10-6 m
C = compotype frequency in the population
r = compotype intrinsic growth rate
K = compotype carrying capacity
a = competition parameters between two species
11
Population Dynamics in GARD
<<Data removed from published version>>
Why plateau is
lower than 1.0 ?
<<Data removed from published version>>
GARD’s Ecology
Compotype sub-network  part of b
<<Data removed from published version>>
14
GARD’s Ecology
Freilich 2009; SOM;
35
Correlation = -0.38
P-value = 0.000031
Based on experimental
data of 111 bacteria.
Doubling time [hour]
30
25
20
15
10
5
0
0
6
Doubling rate [1/hour]
Freilich et al, Genome Biology (2009)
Freilich 2009; SOM;
100
200
300
400
500
600
700
600
700
Metabolic network size
5
4
3
2
1
0
0
100
200
300
400
500
Metabolic network size
15
Population Dynamics in GARD
“Takeover” of a fastrising compotype by a
slower one.
<<Data removed from published version>>
Population Dynamics in GARD
17
Lipid-world & GARD model: compositional assemblies
 Compotypes (clusters of faithfully replicating compositions)
Populations dynamics
 Logistic behavior
 Species competition, takeover
Molecular parameters  Population ecology
 Carrying capacity (K)
 Molecular repertoire effects r & K
Complicated
Simple
Acknowledgements:
Doron Lancet.
Avi Mayo (Weizmann).
Raphael Zidovetzki (U. California Riverside, USA).
Natalio Krasnogor (U. Nottingham, UK).
Lancet group.
Funding:
* Minerva Center for Life Under Extreme
Planetary Conditions, at Weizmann Institute.
* E.U. FP7 “MATCHIT”.
Omer Markovitch
20
Selection in GARD
seeds=1-1000; ng=split=100;
Selection of GARD assemblies
towards a target compotype.
0.6
Probability
0.5
0.4
Negative
Positive
0.3
0.2
0.1
0
0
GARD portrays
selection.
0.5
1
1.5
2
Selection excess
Selection Excess 
2.5
3
Target frequency after
Target frequency before
Markovitch and Lancet, Artificial Life 18:3 (2012)
21
Lack of selectivity in GARD? NO.
Frequency
Vasas, Szathmary & Santos, PNAS 107, 1470-1475 (2010): Imposing
Darwinian selection in GARD has, at most, negligible effect…
–– Regular
–– Beneficial
–– Detrimental
Their weak points:
Index of assembly composition
(1) Target is not a composome.
(2) Only a single simulation performed.
(3) Small repertoire (NG=10) and assembly size (Nmax=6).
(4) Arbitrary fitness threshold.
22