Post on 15-Jan-2016
Chemical Evolution by Natural Selection
Chemical Evolution by Natural Selection
Chrisantha Fernando
School of Computer Science
University of Birmingham
16th October 2006
Chrisantha Fernando
School of Computer Science
University of Birmingham
16th October 2006
My ClaimMy Claim
I claim that the spontaneous origin of a geophysical natural selection machine was necessary for the production of increasingly ordered chemical organizations ultimately leading to a nucleotide producing metabolism.
I reject other “self-organizing principles” that have been proposed to explain the origin of metabolism.
I claim that the spontaneous origin of a geophysical natural selection machine was necessary for the production of increasingly ordered chemical organizations ultimately leading to a nucleotide producing metabolism.
I reject other “self-organizing principles” that have been proposed to explain the origin of metabolism.
How did unlimited heredity arise?
How did unlimited heredity arise?
Template replication of sequences allows unlimited heredity, 4100 ~1060 messages.
If a new message was produced each second for 4 billion years, we would still have only ~ 1038
of the 1060 possible
messages. How could template replication arise?
Template replication of sequences allows unlimited heredity, 4100 ~1060 messages.
If a new message was produced each second for 4 billion years, we would still have only ~ 1038
of the 1060 possible
messages. How could template replication arise?
Ribonucleotides could not have formed spontaneously.
Ribonucleotides could not have formed spontaneously.
Specific synthesis of ribose, specific phosphorylating agents.
Specific synthesis of ribose, specific phosphorylating agents.
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The need for ‘Self-Organization’.The need for ‘Self-Organization’.
“Clearly, some complex chemistry must have “self-organized” on the primitive earth and facilitated the appearance of the RNA world.” Leslie Orgel, (2000).
Graham Cairns-Smith: Clay Templates. PNAs etc.. Eschenmoser. Metabolic Self-Organization. I will discuss how
metabolic self-organization could arise through natural selection.
“Clearly, some complex chemistry must have “self-organized” on the primitive earth and facilitated the appearance of the RNA world.” Leslie Orgel, (2000).
Graham Cairns-Smith: Clay Templates. PNAs etc.. Eschenmoser. Metabolic Self-Organization. I will discuss how
metabolic self-organization could arise through natural selection.
Chemical EvolutionChemical Evolution
Miller’s non-random synthesis of formic acid, alanine, glycine etc… eventually resulted in tar; a combinatorial explosion of polymers, but no increasingly ordered chemical organizations.
Miller’s non-random synthesis of formic acid, alanine, glycine etc… eventually resulted in tar; a combinatorial explosion of polymers, but no increasingly ordered chemical organizations.
What modifications must be made to this protocol to allow…
What modifications must be made to this protocol to allow…
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What do we want? What do we want?
Open ended evolution (Bedau et al 2000) Origin of basic autonomy, i.e. a dissipitive system capable of the
recursive generation of functional constraints (Ruiz-Mirazo, 2004). Production of nucleotides (Maynard-Smith & Szathmary, 1995). Coupled cycling of bioelements (Morowitz, 1968) Maximization of entropy production by the biosphere (Kleidon, 2004) The minimal unit of life: Membrane, Template Replication,
Metabolism. (Ganti, 2003) Autopoetic units, (Membrane, Metabolism) (Maturana and Verala,
1992).
Open ended evolution (Bedau et al 2000) Origin of basic autonomy, i.e. a dissipitive system capable of the
recursive generation of functional constraints (Ruiz-Mirazo, 2004). Production of nucleotides (Maynard-Smith & Szathmary, 1995). Coupled cycling of bioelements (Morowitz, 1968) Maximization of entropy production by the biosphere (Kleidon, 2004) The minimal unit of life: Membrane, Template Replication,
Metabolism. (Ganti, 2003) Autopoetic units, (Membrane, Metabolism) (Maturana and Verala,
1992).
What is Metabolism?What is Metabolism? The set of processes (e.g. chemical reactions) producing
the constituents of the ‘organism’. An organism is a spatially distinct unit. But some people try to define metabolism non-spatially,
e.g. a closed and self-maintaining set of chemicals and reactions (Dittrich and Spironi, 2005, Kauffman, Fontana, etc…).
But organismal metabolism is not closed, it is externally recycled.
A spatially distinct individual necessary for ‘organismal metabolism’, the sort which interests us.
The set of processes (e.g. chemical reactions) producing the constituents of the ‘organism’.
An organism is a spatially distinct unit. But some people try to define metabolism non-spatially,
e.g. a closed and self-maintaining set of chemicals and reactions (Dittrich and Spironi, 2005, Kauffman, Fontana, etc…).
But organismal metabolism is not closed, it is externally recycled.
A spatially distinct individual necessary for ‘organismal metabolism’, the sort which interests us.
Theories of Self-Organization of Metabolism are Flawed.
Theories of Self-Organization of Metabolism are Flawed.
Eigen’s idea and Kauffman’s model of Reflexive autocatalytic sets of proteins.
Fontana’s idea of self-organization of higher order chemical organizations in a flow reactor, modeled with Lambda Calculus.
Morowitz’ idea (and recently Dewer’s arguments for) a self-organizing force due to the existence of a steady state energy flux.
Eigen’s idea and Kauffman’s model of Reflexive autocatalytic sets of proteins.
Fontana’s idea of self-organization of higher order chemical organizations in a flow reactor, modeled with Lambda Calculus.
Morowitz’ idea (and recently Dewer’s arguments for) a self-organizing force due to the existence of a steady state energy flux.
Reflexive Autocatalytic SetsReflexive Autocatalytic Sets
Each member has its formation catalyzed by one or more members of the set.
Each member has its formation catalyzed by one or more members of the set.
Kauffman Side-steps Side-Reactions
Kauffman Side-steps Side-Reactions
Calculations of probabilities about suchsystems always assume that a protein may or may notcatalyse a given legitimate reaction in the system but thatit would not catalyse harmful side reactions. This isobviously an error. Hence the paradox of specificitystrikes again -- the feasibility of autocatalytic attractorsets seems to require a large number of component types(high n), whereas the plague of side reactions calls forsmall systems (low n). (Eors Szathmary, 2000)
The system is ‘spreading’if the problem of poisoningcatalysis is not completelyignored as Kauffman did.
Kauffman’sUniverse
OurUniverse
Kauffman Ignores Precursor Depletion
Kauffman Ignores Precursor Depletion
If there is depletion then…the precursors of the setmust be re-cycled!
In Kauffman’s universe there is constant excess of a vast diversity of precursors.
In our universe, we need to assume more limited initialrecycling capability.
Kauffman’sUniverse
OurUniverse
Conclusion on KauffmanConclusion on Kauffman
Kauffman has proposed an alternative self-organizing principle in addition to natural selection, but it does not work if We take side-reactions seriously. We assume limited diversity of recyclable precursors.
No reflexive autocatalytic set has been produced. We reject this as a relevant self-organizing
princple in the origin of life.
Kauffman has proposed an alternative self-organizing principle in addition to natural selection, but it does not work if We take side-reactions seriously. We assume limited diversity of recyclable precursors.
No reflexive autocatalytic set has been produced. We reject this as a relevant self-organizing
princple in the origin of life.
Fontana and Buss’ Lambda Calculus.
Fontana and Buss’ Lambda Calculus.
They claim, “self-organization arises in a system lacking any formulation of Darwinian selection”.
Flow reactor consisting of string re-writing expressions, no mass or energy conservation, but chemical reactions are modeled as equivalence classes of operations.
If self-copying is forbidden, larger (L1) organizations of string subsets arise that are self-maintaining.
They claim NS could not happen, but it could since there could be > 1 L1 organization present.
String > a maximum length are forbidden, i.e. again the problem of a combinatorial explosion producing tar is nicely forgotten.
In conclusion: We reject that any self-organizing principle other than natural selection acts in Fontana’s reactor, and we reject that it would work in real chemistry since the same problem of side-reactions is ignored.
They claim, “self-organization arises in a system lacking any formulation of Darwinian selection”.
Flow reactor consisting of string re-writing expressions, no mass or energy conservation, but chemical reactions are modeled as equivalence classes of operations.
If self-copying is forbidden, larger (L1) organizations of string subsets arise that are self-maintaining.
They claim NS could not happen, but it could since there could be > 1 L1 organization present.
String > a maximum length are forbidden, i.e. again the problem of a combinatorial explosion producing tar is nicely forgotten.
In conclusion: We reject that any self-organizing principle other than natural selection acts in Fontana’s reactor, and we reject that it would work in real chemistry since the same problem of side-reactions is ignored.
Energy Flow “Organizes a System”.
Energy Flow “Organizes a System”.
Claims that life is driven by radiant energy to attain complexity in the form of coupled cycling of material.
Although careful to mention that “complexity alone is an insufficient measure for characterizing the transition from non-living to living”, he goes on to claim that…
“Miller type experiments indicate the great potential for a directed energy input to organize a system.”, organization being defined as compressible complexity.
Claims that life is driven by radiant energy to attain complexity in the form of coupled cycling of material.
Although careful to mention that “complexity alone is an insufficient measure for characterizing the transition from non-living to living”, he goes on to claim that…
“Miller type experiments indicate the great potential for a directed energy input to organize a system.”, organization being defined as compressible complexity.
The Logical Error.The Logical Error.
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The last statement does not follow from the first.
e.g.the continued steady state flux through a cloud or aBernard cell does not arise because the physical propertiesof the system were ‘informationally’ specified (ordered) by the energy flux itself.
Energy Flux not a ‘driving force’ for organization.
Energy Flux not a ‘driving force’ for organization.
Only a small subset of systems driven by external energy become increasingly organized, in others the size of the sink increases, with loss of capacity for recycling.
How does the subset of dissipative systems increase their capacity for recycling and their rate of entropy production?
I propose it is the subset capable of natural selection that have this property. A steady-state energy flux is necessary for the maintenance of the initial natural selection machine.
Only a small subset of systems driven by external energy become increasingly organized, in others the size of the sink increases, with loss of capacity for recycling.
How does the subset of dissipative systems increase their capacity for recycling and their rate of entropy production?
I propose it is the subset capable of natural selection that have this property. A steady-state energy flux is necessary for the maintenance of the initial natural selection machine.
Natural SelectionNatural Selection
Algorithmic process occurring in populations of entities having multiplication, heredity and variation (JMS, 1986).
What is the simplest machine capable of sustaining natural selection, that is likely to have formed spontaneously?
The Oparin school first proposed natural selection as a mechanism of prebiotic evolution, but with little experimental success.
Algorithmic process occurring in populations of entities having multiplication, heredity and variation (JMS, 1986).
What is the simplest machine capable of sustaining natural selection, that is likely to have formed spontaneously?
The Oparin school first proposed natural selection as a mechanism of prebiotic evolution, but with little experimental success.
Alexander Oparin 1894-1980Alexander Oparin 1894-1980
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Coacervates = spontaneously formed polypeptide structures. He distinguished between artificial and natural coacervates.He proposed variation in polypeptide composition. No self-replication or heredity was demonstrated.
Fox & Dose, Folsome, Bahinder, Weber
Fox & Dose, Folsome, Bahinder, Weber
Fox and Dose: Polypeptide microspheres in which budding occurred due to potentially non-random polycondensation reactions. Details of heredity were not studied. (1977).
Folsome observed that the ‘thin oily scum’ on the surface of the water in the Miller experiment formed exponentially growing microstructures and then sank to the bottom of the flask (no continued lineage). (1979)
Bahinder showed that formaldehyde, ammonium phosphate, mineral salts and ammonium molybdate exposed to sunlight formed spherical microstructured called “Jeewanu”.(1954).
Weber (2005) described a synthesis of microspherules from sugers and ammonia without reference to Bahinder’s work.
But no-one has demonstrated natural selection in populations of spontaneously formed phase separated individuals.
Fox and Dose: Polypeptide microspheres in which budding occurred due to potentially non-random polycondensation reactions. Details of heredity were not studied. (1977).
Folsome observed that the ‘thin oily scum’ on the surface of the water in the Miller experiment formed exponentially growing microstructures and then sank to the bottom of the flask (no continued lineage). (1979)
Bahinder showed that formaldehyde, ammonium phosphate, mineral salts and ammonium molybdate exposed to sunlight formed spherical microstructured called “Jeewanu”.(1954).
Weber (2005) described a synthesis of microspherules from sugers and ammonia without reference to Bahinder’s work.
But no-one has demonstrated natural selection in populations of spontaneously formed phase separated individuals.
Chemical Evolution by Natural Selection
Chemical Evolution by Natural Selection
The origin of metabolism occurred under the following conditions. A spontaneous natural selection machine arose capable
of… Production of lipophilic material to replenish phase separated
individuals formed from that material. A process of agitation to replicate a liposome A reaping of liposomes to impose selective pressure. The capacity for variation by ‘chemical avalanches’ within
liposomes. Some novel chemicals produced in an avalanche can aid I.
liposome growth, ii. liposome division.
The origin of metabolism occurred under the following conditions. A spontaneous natural selection machine arose capable
of… Production of lipophilic material to replenish phase separated
individuals formed from that material. A process of agitation to replicate a liposome A reaping of liposomes to impose selective pressure. The capacity for variation by ‘chemical avalanches’ within
liposomes. Some novel chemicals produced in an avalanche can aid I.
liposome growth, ii. liposome division.
1
The artificial version for the lab.
1
(1) Basal Liposome Growth(1) Basal Liposome Growth
a a
a
a
a
a
aa
a
a
No chemical reactions
Just phase separation
(2) Liposome Division(2) Liposome Division
a a
a
a
a
a
aa
a
a a
a
a
aa
(3) Chemical Avalanches? (3) Chemical Avalanches?
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Pyrite
a
b
bc + d
a
RARE (low flux) reaction
bc + d
a c + e
High flux reaction
But now we must calculatethe reactions of e and so on.
?
C happens to be autocatalytically produced, it need not have been.
This is the avalanche.
The model asks… The model asks…
Is the production of increasingly ordered metabolism possible when variation is by chemical avalanches, most of which are harmful or neutral?
What metabolic topology is evolved? What thermodynamic organization of metabolism is
evolved? What are the fundamental constraints for natural
selection to act in such a system?
Is the production of increasingly ordered metabolism possible when variation is by chemical avalanches, most of which are harmful or neutral?
What metabolic topology is evolved? What thermodynamic organization of metabolism is
evolved? What are the fundamental constraints for natural
selection to act in such a system?
The AlgorithmThe Algorithm
A hill-climbing algorithm is used to select for liposomes that maximize their growth after a fixed period.
Parental (liposome) fitness is assessed, a child is produced that inherits half the parental material, and has experienced an avalanche. If its fitness is greater than the parent, it replaces the parent, else a new offspring is produced and assessed.
A hill-climbing algorithm is used to select for liposomes that maximize their growth after a fixed period.
Parental (liposome) fitness is assessed, a child is produced that inherits half the parental material, and has experienced an avalanche. If its fitness is greater than the parent, it replaces the parent, else a new offspring is produced and assessed.
Algorithm 1 An Overview
Require: generation = 0. t = 0. Initialize reactor with food set and initial reactions. Assume initial fitness
of ‘virgin’ liposome = 0. Generation_time = 10,000 x 0.0001 seconds. Time-step = 0.0001 seconds.
1: for generation = 0 to Max_Gen do
2: Create offspring reactor by taking 50% of liposome phase material present at end of parental generation,
and replenishing the food set to its original concentration.
3: Generate Avalanche: Randomly (but a ccording to the rmodynamic and m ass conservation constraints
described later) create novel rare reactions and the subsequent high flux reaction avalanche. Initialize each
novel species at very low concentration (e.g. 10-7mM).
4: Simulate Offspring: Using the novel reaction network and initial concentrations use Eular Integration to
simulate generation_time seconds of reaction dynamics, measuring fitness at 1000 time-step intervals.
4.1: Simulate 3 offspring consecutive produced from the original offspring (with no chemical avalanches
between divisions), in order to ex clude non-inheritable avalanches. Calculate fitness only of the 3 rd
offspring.
5: if Offspring fitness > Parent fitness x 1.1 (i.e. offspring fitness must be at least 10% greater than parent)
6: Replace Parental reactor with Offspring reactor.
7: end if
8: end for
The Artificial ChemistryThe Artificial Chemistry
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Energy Energy
Each species is assigned a free energy of formation, Gf.
Any novel reaction must be spontaneous,
G = Gproducts – Greactants < 0. The equilibrium ratio of a reaction is given by K = e-
G/RT.
kb = 0.01 and kf = 0.01K A species has an 80% chance of being lipophilic. If a
product is lipophilic, the reaction is effectively irreversible.
Each species is assigned a free energy of formation, Gf.
Any novel reaction must be spontaneous,
G = Gproducts – Greactants < 0. The equilibrium ratio of a reaction is given by K = e-
G/RT.
kb = 0.01 and kf = 0.01K A species has an 80% chance of being lipophilic. If a
product is lipophilic, the reaction is effectively irreversible.
Initial conditionsInitial conditions
Food set. 100 mM: { aab, aaab, aabb, bbbb, aaaab, aaabb, aabbb, abbbb. }
Gf= 1.0
Growth set. 0mM: : {abb (0.1), abbb (0.01), abbbb (1), abbbbb (2), abbbbbb (3), abbbbbbb (4), abbbbbbbb (5), abbbbbbbbb (5)}.
Food set. 100 mM: { aab, aaab, aabb, bbbb, aaaab, aaabb, aabbb, abbbb. }
Gf= 1.0
Growth set. 0mM: : {abb (0.1), abbb (0.01), abbbb (1), abbbbb (2), abbbbbb (3), abbbbbbb (4), abbbbbbbb (5), abbbbbbbbb (5)}.
Algorithm 2: Generate Avalanche
0: for N = 0 to num_low_propensity_reactions.
1: Choose two existing species (r1, r2) to react in a low propensity reaction (kf ~ 0, kb ~ 0) to produce two
potential products p1 and p2.
2: Generate the free energies of p1 and p2 (if they don’t already exist) so that the following relation holds,
Gp1 + Gp2 + heat = G r1 + Gr2 , by portioning energies according to a uniform random distribution, heat
being positive.
3: if it is not possible to satisfy this relation, e.g. because Gp1 > Gr1 + Gr2, then the reaction is not permitted,
and no new products are created.
4: else if the condition that the reaction is spontaneous can be satisfied, create novel products at low
concentration (e.g. 10-7 M) and increment newSpec ++ //Store the number of novel species produced.
5: kf = kb = 0.
6: end if
7: end for
8: while newSpec != 1 do
9: for i = 0 to newSpec
10: for j = 0 to number of species currently existing
11: if rand() < PROB_HIGH_FLUX x 1/(species[i].length)2
12: *See tempNewSpecies = output of Algorithm 3
//Make high flux reaction with new species[i] and a random species
13: //Store tempNewSpecies produced in that high flux reaction.
14: end if
15: end for
16: end for
17: newSpec = tempNewSpecies, tempNewSpecies = 0.
18: end while
Algorithm 3: Calculate a high flux reaction
1: Choose species to react with rare species i as follows.
2: for j = 0 to num species
3: score += 1/(length [j] – length [i])2 x (length [j])2
4: end for
5: Use roulette wheel selection to find species j biased by the above scores.
6: Once r1 = i and r2 have b een chosen, generate random p1 and p2 pro ducts based on a bimolecular
rearrangement of r1 and r2 . This reaction can be biased in va rious ways, e.g. let the probability of a
catalytic reaction, i.e. where r1 = p1, or r2 = p2, be rel ated linearly to the proportion of ‘b’ atoms in r1 or
r2. etc… Many such structure specific probabilistic rules may be applied.
7: Check that Gp1 + Gp2 + heat = G r1 + G r2 can be satisfied, and only if i t can, store this new high flux
reaction, and set kf = rand(C) x 0.01K, and
9: if p1 and p2 already exist, kb = 0 //C = 100 or 1000 and is a uniformly randomly
assigned rate. A log normal distribution has also been used Logrand(C).
10: else kb = rand(C) x 0.01. //This is to ensure that the exploration of the adjacent possible is correct
11: Return the number of new species produced legitimately, i.e. 0, 1 or 2.
Definition of FitnessDefinition of FitnessFitness is defined as the integral over the trial of the product of [species[i]] x length of
Species i , where i is a molecule in the growth set. The second term introduces a biomass
effect. This is approximated by sampling concentrations at internals of 1000 time steps.
All trials are of fixed duration. The bolus of food molecules is allowed to deplete if the
chemical avalanche has produced species that react with the bolus, or if material has been
inherited that reacts with the bolus. This replicates the effect of a potential microfluidic
experiment in which a s ingle liposome is isolated in a small compartment containing a
bolus of food molecules, and its size measured after a fixed duration. In many of the
trials, fi tness is assessed not on the first offspring produced after a chemical avalanche,
but on the 3rd post-avalanche offspring. This is to increase the probability that any fitness
benefit due to an avalanche is heritable, rather than beneficial only to the offspring in
which the avalanche occurs.
Results. Results.
Agent I.D. Num. Species Num. Reactions
12648 61 47
20567 99 63
28807 122 76
33659 147 89
Energy dissipation increases
Avalanche properties change over the course of evolution.
As molecule size increases the chance of an autocatalytic product from an avalanche Decreases.
Mean Avalanche Properties
ConclusionsConclusions1. Liposome level selection maintains molecular
replicators arising in chemical avalanches. 2. Autocatalytic constituents are more likely to be short
molecules with few atom types (given random rearrangement reactions).
3. An ecology of autocatalysts exists, non-competitive, competitive, parasitic, cross-catalytic, but all selected on the basis of by-product mutualism of autocatalysts within the same liposome.
4. Lipophobic side products drive irreversible reactions, whilst lipophilic non-reactive products prevent continued drainage.
1. Liposome level selection maintains molecular replicators arising in chemical avalanches.
2. Autocatalytic constituents are more likely to be short molecules with few atom types (given random rearrangement reactions).
3. An ecology of autocatalysts exists, non-competitive, competitive, parasitic, cross-catalytic, but all selected on the basis of by-product mutualism of autocatalysts within the same liposome.
4. Lipophobic side products drive irreversible reactions, whilst lipophilic non-reactive products prevent continued drainage.
ConclusionsConclusions
5. A more diverse food set promotes more complex autocatalytic cycles, 1,2, & 3 member cycles observed.
6. Energy flux increases over evolutionary time for two reasons; energy demands of memory, energy demands of growth.
7. Large generation numbers and large population sizes will be necessary since most avalanches are harmful or neutral, thus automated microfluidics is required, perhaps under high pressure to promote chemical avalanches.
5. A more diverse food set promotes more complex autocatalytic cycles, 1,2, & 3 member cycles observed.
6. Energy flux increases over evolutionary time for two reasons; energy demands of memory, energy demands of growth.
7. Large generation numbers and large population sizes will be necessary since most avalanches are harmful or neutral, thus automated microfluidics is required, perhaps under high pressure to promote chemical avalanches.
AcknowledgementsAcknowledgements
Jon Rowe Eors Szathmary Hywel Williams Kepa Ruiz-Mirazo Fabio Mavelli Alvero Moreno Xabier Barandieran
Jon Rowe Eors Szathmary Hywel Williams Kepa Ruiz-Mirazo Fabio Mavelli Alvero Moreno Xabier Barandieran