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What can theoretical physics tell us about
the evolution of early life?
Nigel Goldenfeld
With material from: Kalin Vetsigian, Tommaso Biancalani,
Farshid Jafarpour, Carl Woese, Hong-Yan Shih
Department of Physics and
Carl R. Woese Institute for Genomic Biology
University of Illinois at Urbana-Champaign
Funded by NASA grant NNA13AA91A to the NASA Astrobiology Institute for Universal Biology and the
National Science Foundation Center for the Physics of Living Cells
What can theoretical physics tell
us about anything?
What can theoretical physics tell
us about anything?
And actually … what is theoretical
physics?
Nobel Prize 2016: condensed matter theory
David Thouless
Mike Kosterlitz
https://magaratimes.com/en/2016/10/04/
nobel-prize-physics-winners-elevate-hopes-for-brand-spanking-new-gen-of-electronics/
Duncan Haldane
Superfluids
Honey – normal fluid
with viscosity at
room temperature
http://www.honeyassociation.com/
Superfluid helium –
no viscosity at one
degree above
absolute zero
http://pitp.physics.ubc.ca/archives/CWSS/sh
owcase/topics/He4-fountain.jpg
Arrows on a plane
Arrows on a plane – predict
superfluid film phase transitions
Arrows on a plane – predict
superfluid film phase transitions
Measurements done
at UIUC
Amazing and surprising fact
• Superfluids in two dimensions are pretty
complicated
• Kosterlitz and Thouless’ Nobel Prize work
predicted how helium goes from behaving like
a normal liquid to a superfluid just by …
• Looking at the simplest way that arrows on a
plane could be described energetically
Amazing and surprising fact
• Superfluids in two dimensions are pretty
The moral of the story is that simple
complicated
models can predict very complex
phenomena. In fact everything we
• Kosterlitz
andabout
Thouless’
Nobelworld
Prizecomes
work
know
the physical
predicted how
from
behaving like
fromhelium
lookinggoes
for the
simplest
a normalmathematical
liquid to a superfluid
just
bythe
…
models (that
have
right symmetry and topology).
• Looking at the simplest way that arrows on a
plane could be described energetically
Theoretical condensed matter physicists at UIUC
Is this theoretical physics?
Is this theoretical physics?
It’s my blackboard,
so probably!
Is this theoretical physics?
But it’s in the
Institute for
Genomic Biology,
so who knows?
Is this theoretical physics?
Is this theoretical physics?
Nope! This is
mathematical
physics, not
theoretical physics!
Is this theoretical physics?
It’s just a
complicated
calculation. Like a
maths homework
problem.
Is this theoretical physics?
Is this theoretical physics?
How about this
bit?
Is this theoretical physics?
Yup! It’s a guess
about how
something behaves -- actually how fluids
become turbulent!
Is this theoretical physics?
Mathematical
physics
Theoretical physics
Is this theoretical physics?
Theoretical physics = simple guess + maths
What can theoretical physics tell us
about the evolution of early life?
Can simple models predict real biological
phenomena, like they do in condensed
matter theory?
Part 1: What is universal about
biology?
“Everything in biology has an exception”
29
Tree of life
Network of Life --- The “Progenote”
Spiral galaxy
Chiral molecule
Chiral molecule
Tree of life
Network of Life --- The “Progenote”
Universal Biology
WE KNOW THE WAVES ON THE OCEAN
OF TITAN ARE MISSING BECAUSE THERE
IS A GENERAL THEORY OF TWO-PHASE
FLUID FLOW INTERFACES THAT
PREDICTS WAVES AND THEIR
DISPERSION CHARACTERISTICS
Mystery of the Missing Life on Titan
Long-sought Life
WE DON’T KNOW IF THERE IS “MISSING
LIFE” BECAUSE WE DO NOT HAVE A
THEORY THAT PREDICTS THE EXISTENCE
OF LIFE AS A PHYSICAL PHENOMENON,
NOR DO WE UNDERSTAND WHAT SORT
OF LIFE CAN ARISE IN DIFFERENT
ENVIRONMENTS
BECAUSE WE ARE INTERESTED IN GENERAL PRINCIPLES AND
NOT SPECIFIC CARBON CHEMISTRY DETAILS, WE NEED TO
DEVELOP A THEORY OF UNIVERSAL BIOLOGY, DIVORCED
FROM IDIOSYNCRATIC DETAILS
THE GOAL OF OUR WORK IS TO
COME CLOSER TO SUCH A THEORY
Universal Biology
Universal Computation
Universal Computation
Universal Computation
Universal Computation
Universal Computation
• A computer is neither a shiny chunk of glass, plastic and
silicon not a bunch of cog wheels, springs and levers.
• It is an abstract concept (Turing machine with a von
Neumann architecture etc.) that can be instantiated in
many ways.
The medium is not the message
The program is the data; the data is the program.
Nils Barricelli (1912-1993)
Image courtesy of George Dyson
Universal Biology: the inverse problem
• Inverse problem: If you were given a modern
computer, could you work backwards and
deduce the abstract mathematical theory of
computation?
• In biology, we have the inverse problem: the
biology is already created and we want to
understand what is the abstract theory of
which it is an instantiation!
– This abstract theory would underlie all systems
that exhibit the characteristics of life
Part 2: Evolution of the genetic
code
K. Vetsigian, C.R. Woese and Nigel Goldenfeld. Communal
evolution of the genetic code. Proc. Natl. Acad. Sci. 103,
10696-10701 (2006).
Tommaso Biancalani, NG (unpublished): Darwinian
Transition
gatcctccatatacaacggtatctccacctcaggtttagatctcaaca
acggaaccattgccgacatgagacagttaggtatcgtcgagagtta
caagctaaaacgagcagtagtcagctctgcatctgaagccgctga
agttctactaagggtggataacatcatccgtgcaagaccaagaacc
gccaatagacaacatatgtaacatatttaggatatacctcgaaaata
ataaaccgccacactgtcattattataattagaaacagaacgcaaa
aattatccactatataattcaaagacgcgaaaaaaaaagaacaac
gcgtcatagaacttttggcaattcgcgtcacaaataaattttggcaa
cttatgtttcctcttcgagcagtactcgagccctgtctcaagaatgta
ataatacccatcgtaggtatggttaaagatagcatctccacaacctc
aaagctccttgccgagagtcgccctcctttgtcgagtaattttcacttt
tcatatgagaacttattttcttattctttactctcacatcctgtagtgatt
gacactgcaacagccaccatcactagaagaacagaacaattactt
aatagaaaaattatatcttcctcgaaacgatttcctgcttccaacatct
gatcctccatatacaacggtatctccacctcaggtttagatctcaaca
acggaaccattgccgacatgagacagttaggtatcgtcgagagtta
caagctaaaacgagcagtagtcagctctgcatctgaagccgctga
agttctactaagggtggataacatcatccgtgcaagaccaagaacc
gccaatagacaacatatgtaacatatttaggatatacctcgaaaata
ataaaccgccacactgtcattattataattagaaacagaacgcaaa
aattatccactatataattcaaagacgcgaaaaaaaaagaacaac
This is not the genetic code
gcgtcatagaacttttggcaattcgcgtcacaaataaattttggcaa
cttatgtttcctcttcgagcagtactcgagccctgtctcaagaatgta
ataatacccatcgtaggtatggttaaagatagcatctccacaacctc
aaagctccttgccgagagtcgccctcctttgtcgagtaattttcacttt
tcatatgagaacttattttcttattctttactctcacatcctgtagtgatt
gacactgcaacagccaccatcactagaagaacagaacaattactt
aatagaaaaattatatcttcctcgaaacgatttcctgcttccaacatct
Watson-Crick pairs
http://www.stanford.edu/group/hopes/basics/dna/b3.html
Translation
DNA built from 4
nucleotide bases
Proteins built from 20
amino acids
mRNA built from 4
nucleotide bases
http://biology.kenyon.edu/courses/biol114/Chap05/Chapter05.html
Translation
Translation
DNA built from 4
nucleotide bases
Proteins built from 20
amino acids
mRNA built from 4
nucleotide bases
Genetic code is the map
used by the ribosome to
translate the message from
mRNA triplets of 4 bases into
the 20 amino acids of life
http://biology.kenyon.edu/courses/biol114/Chap05/Chapter05.html
U(T)
C
Phe
U (T)
Tyr
Ser
Leu
The
canonical
genetic
code
A
STOP
G
Cys
Leu
Pro
A
Trp
G
U
Arg
Gln
A
Ile
Asn
Lys
Ser
Arg
Val
Ala
Gly
Glu
A
U
C
A
G
U
Asp
G
C
G
Thr
Met
C
STOP
His
C
U
C
A
G
You are
here
Last Universal
Common Ancestor ?
Simple facts about early life
Bacterial ribosomal phenotypes have been basically constant for about 3 billion years (the age of blue-green
bacterial fossil evidence …) The divergence of the bacterial from the cytoplasmic line of descent could not have
antedated this by more one billion years. Thus unless the tempo of evolution were faster at the earlier time, the
large number of bacterial-cytoplasmic differences cannot be rationalized. We feel it more reasonable, of course,
to assume the mode, not the tempo, of evolution to have changed; the bacterial-cytoplasmic differences reflect
the independent evolution of the final, "fine tuning" aspects to translation, after which the functional character
of the translation mechanism remained constant … [Woese and Fox: The Concept of Cellular Evolution (1977)]
71
Photos courtesy of: Ken Luehrsen (1979)
A different mode: Horizontal gene transfer
Microbes can do this … but what happens
when they all do it?
Spread of antibiotic resistance genes
• Virtually identical copies
of resistance genes found
in distantly related
bacteria
– Genes are being
expressed
• Genes cross species and
phylum boundaries
– Gram-positive/enteric
– Bacteroides/enteric
• Genes cross physical
locations
Salyers & Amabile-Cuevas (1997)
– Bacteroides spp.
(colon)/Bacillus spp.
(soil)
U(T)
C
Phe
U (T)
Tyr
Ser
Leu
The
canonical
genetic
code
A
STOP
G
Cys
Leu
Pro
A
Trp
G
U
Arg
Gln
A
Ile
Asn
Lys
Ser
Arg
Val
Ala
Gly
Glu
A
U
C
A
G
U
Asp
G
C
G
Thr
Met
C
STOP
His
C
U
C
A
G
U
C
Phe
Hydrophobicity
Most hydrophobic amino
acids are Phe, Leu, Ile,
Met and Val.
U
Woese (1965), Volkenstein
(1966)
Tyr
Ser
Leu
STOP
G
Cys
C
Leu
Pro
Trp
G
U
Arg
A
Asn
Lys
Ser
Arg
Val
Ala
Gly
Glu
A
U
C
A
G
U
Asp
G
C
G
Thr
Met
C
A
Gln
Ile
U
STOP
His
Most hydrophilic amino
acids are His, Gln, Asn,
Lys, Asp, Glu.
Amino acids with
complementary anticodons tend to have
opposite hydrophobicity.
A
C
A
G
U
U
Phe
5.0
Leu
4.9
C
Tyr
Ser
STOP
Polar requirement
Amino acids with shared
doublet have similar “polar
requirement” – a
quantification of amino acidpyridine affinity.
(Woese et al. 1966)
C
A
Leu
Ile
4.9
Pro
Thr
Met 5.3
G
Val
A
Ala
His
8.4
Gln
8.6
Asn
10.0
Lys
10.1
Asp
13.0
Glu
12.5
G
Cys
U
C
STOP
A
Trp
G
U
Arg
C
A
G
Ser
Arg
U
C
A
G
U
Gly
C
A
G
The genetic code is not just universal …
it’s nearly optimal in minimizing errors
Simulated genetic codes
U
C
Phe
U
A
G
Tyr
Cys
Ser
Leu
STOP
Leu
Pro
Trp
G
Ile
Met
Ser
Arg
Val
Ala
Gly
Glu
U
C
A
Leu
A
A
G
Tyr
Cys
C
Phe
Pro
Ile
Trp
G
U
Arg
Lys
Ser
Asn
Arg
Val
Ala
Gly
Glu
• Permute labels – new codes with same pattern of degeneracy
• 20! ~ 1018 possible codes
A
U
C
A
G
U
Asp
G
C
G
Thr
Met
C
A
Gln
A
U
STOP
His
G
C
G
STOP
U
C
A
Ser
U
Asp
G
Leu
G
Thr
Lys
C
U
Gln
A
C
A
Arg
Asn
U
STOP
His
C
U
C
A
G
Simulated genetic codes
• Basic idea: generate by Monte Carlo simulation a large
number of simulated genetic codes
• For each code, score the effect of point substitutions in 1st,
2nd & 3rd codon positions by summing the square of the
differences in polar requirement numbers, summed over
the whole code
• Plot a histogram
of the scores obtained
• Compare with the
canonical genetic
code
Rob Knight, Ph.D thesis (2001)
Knight Ph.D thesis (2001)
Simulated genetic codes
Naïve expectation – current
code is frozen accident
Actual result – current code is
not a frozen accident
Polar Carl, p= 1 .Ter ignored. One in: 2.1557
Polar Carl, p= 1 .Ter ignored. One in: 40000
Probability distribution
12000
15000
10000
8000
10000
6000
4000
5000
2000
0
700
800
900
1000
1100
1200
1300
1400
1500
Code property
0
700
800
900
1000
1100
1200
1300
1400
1500
Optimality of the genetic code with respect to
the polar requirement
Freeland and Hurst 1998
Simulations of code evolution
K. Vetsigian, C.R. Woese and Nigel Goldenfeld. Communal evolution of the
genetic code. Proc. Natl. Acad. Sci. 103, 10696-10701 (2006)
Simulations of code evolution
K. Vetsigian, C.R. Woese and Nigel Goldenfeld. Communal evolution of the
genetic code. Proc. Natl. Acad. Sci. 103, 10696-10701 (2006)
Coevolution of genetic code and
proteins in a digital life simulation
• Asexual population of evolving, reproducing digital organisms (e.g. like
computer viruses)
• Phenotype of individuals is distribution of proteins
– Fitness is a function of the phenotype
• Proteins obtained by translating genome with code, with errors
• Individual reproduction rate function of fitness
• Messages change faster than codes:
– Quasi-static equilibrium: codon usage equilibrates to code
– Mutate code
– Mutant code with higher fitness than existing code with existing message can
invade the population
• Hence, code can evolve due to selection at the phenotype!
Evolution of code quality
Code quality
Distribution of code
quality scores
without HGT
random
codes
evolved code
with HGT
time
HGT leads to optimality
Evolution of code Distribution
distances
of code
Average code distance
distances
random
codes
evolved code
Time
HGT leads to universality
The phase diagram of life …
… as inferred from the collective
dynamics of innovation-sharing
protocols
Archaea
Bacteria
Time
Eukaryotes
Last Universal
Common
Ancestor
Archaea
Eukaryotes
Time
Bacteria
Communal state: competing codes
Ambiguity + multiple codes => no global HGT
Archaea
Bacteria
Time
Eukaryotes
Universal genetic
code.
First Universal Common
Ancestors
Communal state: competing codes
Ambiguity good for
Ambiguity + multiple codes => no global HGT
evolving
communal state
Archaea
Time
Bacteria
Universal genetic
code + toleration of
ambiguity leads to …
First Universal Common
Universal genetic
Ancestors
code.
Eukaryotes
… communal state
with explosive
growth in
innovation-sharing
Communal state: competing codes
Ambiguity good for
Ambiguity + multiple codes => no global HGT
evolving
communal state
Archaea
Time
Bacteria
Ambiguity not tolerated
vertical evolution of
individual organismal lineage
Darwinian transition:
ambiguity bad for
Universal genetic
highly precise
code + toleration of
complex system
ambiguity leads to …
Universal genetic
code.
Eukaryotes
First Universal Common
Ancestors
… communal state
with explosive
growth in
innovation-sharing
Communal state: competing codes
Ambiguity good for
Ambiguity + multiple codes => no global HGT
evolving
communal state
Archaea
Bacteria
Time
Eukaryotes
Progenote: Reticulate
evolution, no notion of
phylogeny
Community varies in
descent, not individual
organismal lineages
Part 3: Homochirality
124
Homochirality
• Homochirality
– Biological amino acids are
left handed (L)
– Biological sugars are
right handed (D)
• Homochirality is 100%
– Not simply enantiomeric excess
– Rules out naïve biasing mechanisms, e.g. based on
catalytic surfaces, weak interactions (!) …
http://en.wikipedia.org/wiki/Chirality
Homochirality as a universal
biosignature
• All the requirements for the model are essential ingredients of life
– Homochirality as a universal property of life
– Can be used as a biosignature
• Astrobiology and the Search for Life Beyond Earth
– Assess the prospects of finding life beyond Earth over the next decade
• Detection of circular polarization in light scattered by
photosynthetic microbes1
• Lunar based observation of the earth2
Conclusion
Homochirality ?
Start = -4.6B
Darwinian transition
Genetic code
LUCA ~ -3.8B
Conclusion
Homochirality ?
Start = -4.6B
Autocatalysis
leads to 100%
homochirality
HGT drives
evolution of
unique, optimal
genetic code
Genetic code
Darwinian transition
HGT eventually
becomes
ineffective
compared to
vertical
selection
LUCA ~ -3.8B
What can theoretical physics tell us
about the evolution of early life?
Can simple models predict real biological
phenomena, like they do in condensed matter
theory?
Yes if you ask the right questions, in the right way!
Take-home messages
• Theoretical physics starts with a simple guess
– Then you calculate the consequences of that guess
– And compare with experiment, or predict a new experiment for
someone to do.
– And the experiments suggest new guesses etc…
• Simple models --- but not too simple --- can describe very
complicated phenomena
– Physics is successful because we only work on simple problems
– We do not really know to what extent this approach can be used
in more complex sciences like biology
• We should try and understand universal features of systems
first, because there is a chance that the methods of
theoretical physics can be successful
– The genetic code, homochirality are examples in biology
– Are there other universal features of biology?