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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?