Deep Phylogeny—How a Tree Can Help Characterize Early Life ...archer/deep_earth... · Deep Phylogeny—How a Tree Can Help Characterize Early Life on Earth Eric A. Gaucher, James

Deep Phylogeny—How a Tree Can HelpCharacterize Early Life on Earth

Eric A. Gaucher, James T. Kratzer, and Ryan N. Randall

School of Biology, School of Chemistry, and Parker H. Petit Institute for Bioengineering and Biosciences,Georgia Institute of Technology, Atlanta, Georgia

Correspondence: [email protected]

The Darwinian concept of biological evolution assumes that life on Earth shares a commonancestor. The diversification of this common ancestor through speciation events and verticaltransmission of genetic material implies that the classification of life can be illustrated in atree-like manner, commonly referred to as the Tree of Life. This article describes featuresof the Tree of Life, such as how the tree has been both pruned and become bushier throughoutthe past centuryas our knowledge of biology has expanded. We present current views that theclassification of life may be best illustrated as a ring or even a coral with tree-like character-istics. This article also discusses how the organization of the Tree of Life offers clues aboutancient life on Earth. In particular, we focus on the environmental conditions and tempera-ture history of Precambrian life and show how chemical, biological, and geological data canconverge to better understand this history.

“You know, a tree is a tree. How many more do you need to look at?”–Ronald Reagan (Governor of California), quoted in the Sacramento Bee,

opposing expansion of Redwood National Park, March 3, 1966

The following article addresses a period in lifemost removed from life’s origins compared

with other articles in this collection. The articlediscusses an advanced form of life that seems tohave lived on the order of 3.5–4.0 billion yearsago, around the time when life as we know it be-gan to diversify in a Darwinian sense. The lifefrom this geological period is located deep with-in an illustrated taxonomic tree of life. The hopeis that by understanding how early life evolved,we can better understand how life originated.In this sense, the article attempts to travel

backwards in time, starting from modern organ-isms, to understand life’s origin.

The Darwinian concept of evolution suggeststhat all modern life shares a single common an-cestor, often referred to as the last universal com-mon ancestor (LUCA). Throughout evolutionaryhistory, this ancestor has for the most part gener-ated descendants as successive bifurcations in atree-like manner. This so called Tree of Life, andphylogenetics in general provides much of theframework for the field of molecular evolution.Taxonomic trees allow us to better understand re-

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lationships and commonalities shared by life. Forinstance, a tree may tell us whether a trait or phe-notype shared between two organisms is the re-sult of shared-common ancestry (termedhomologous traits) or whether the trait hasevolved multiple times independent of ancestry(analogous traits such as wings).

Taxonomic trees can be built using diversesources of information. These can include mor-phological and phenotypic data at the macro-level down to DNA and protein sequence dataat the micro-level. Ideally, trees built from mul-tiple sources of input have identical taxonomicrelationships and branching patterns, and suchtrees are said to be congruent. In practice, how-ever, trees built from morphological data (say,presence or absence of wings) are often differentthan a tree built from molecular data (DNA orprotein sequences). This requires the biologistto determine which of the two data sets is mis-leading and/or which taxonomic tree-buildingalgorithm is most appropriate to use for a par-ticular data set. Such an artform is commonin the field of molecular evolution becauserarely are trees congruent when built from twosources of input data.

In light of this fact, we have provided thequote at the beginning of this article as a reflec-tion about the field of molecular evolution andits interpretations of taxonomic trees. AlthoughReagan was not speaking about taxonomic treesin his quote, the same sort of disconnect existsbetween evolutionary biologists and molecularbiologists (Woese and Goldenfeld 2009), as itdid between conservationists and Ronald Rea-gan. A molecular biologist may be inclined tosay that once you have seen one phylogenetictree, you have seen them all. And in fairness,there is some validity to such a notion becausehistorically a phylogenetic tree could not helpa molecular biologist to better describe theirsystem. An evolutionary biologist, however,will argue that individual trees have nuancesthat can dramatically alter our interpretationof evolutionary processes.

We intend to show in this article that not all(taxonomic) trees look similar and describeidentical evolutionary scenarios. We will discusshow our concept of the Tree of Life has changed

over the past couple of decades, how trees can beinterpreted, and what a tree can tell us aboutearly life. In particular, the article will focuson the temperature conditions of early life be-cause this topic has received much attentionover the past few years as a direct result of im-proved DNA sequencing technology and a bet-ter understanding of molecular evolutionaryprocesses. We will also describe how trees canbe used to guide laboratory experiments inour attempt to understand ancient life. Lastly,we will discuss how phylogenetic trees will serveas the foundation for an “evolutionary syntheticbiology” that should allow us to better under-stand the evolution of cellular pathways, macro-molecular machines such as the ribosome, andother emergent properties of early life.

BACKGROUND

Prokaryotes and Eukaryotes

All natural and physical scientists have beentaught that biological classification is the man-ner in which organisms are categorized accord-ing to common or shared traits. Two organismswill be located in close proximity within a clas-sification system if those two organisms havesimilar characteristics. The greater the numberof shared characteristics, the closer the two or-ganisms will be grouped within the classifica-tion system.

The ability to classify organisms is probablya reflection of the notion that all living organ-isms share a common ancestor. In essencethen, Darwinian evolution has already createda classification scheme, and it is our job to illus-trate this scheme in a taxonomic context. Ourability to recapitulate life’s phylogeny dependsof course on our ability to identify all life formsand describe these life forms at a sufficiently de-tailed level, allowing us to identify shared char-acteristics resulting from common ancestry.

Biologists have made tremendous progressin their classification scheme during the pastcouple of centuries. For instance, EdouardChatton outlined his classification scheme thatdivided life into two categories in the 1920s—he divided life into prokaryotes and eukaryotes

E.A. Gaucher, J.T. Kratzer, and R.N. Randall

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(Fig. 1A) (Chatton 1925). Eukaryotic cells had anucleus that encapsulates their genomic DNA,whereas prokaryotic cells had no nuclear organ-elle. From an evolutionary perspective, and bydefinition, prokaryotes (meaning before nucleus)were the progenitors to eukaryotes (dawn of thenucleus). Prokaryotic organisms were micro-scopic and morphologically similar but metabol-ically very diverse in their ability to inhabit“extreme” environments. Conversely, eukaryoticorganisms were both microscopic and macro-scopic and metabolically similar but morpholog-ically they are very diverse because of theirmulticellularity. The prokaryotic/eukaryotic per-spective seemed reasonable at the time becauseprokaryotes were for the most part morphologi-cally “simple” single-celled organisms, whereaseukaryotes were for the most part “complex”multicellular organisms. The use of simple andcomplex were of course anthropomorphic. A flat-worm would be considered complex because itmorphologically looks more similar to humansthan say to a simple bacterium, even if that bacte-rium can live in an anoxic, lightless, and boilinghot environment. The notion of similarity andcomplexity, however, would be uprooted nearly50 years after Chatton’s classification scheme asa result of a revolution in biochemistry and mo-lecular biology.

Three Domains of Life

Although the field of biology is fundamentallyconcerned with the classification of living andextinct organisms, the field is highly dependenton technological advances that allow the biolo-gist to gather ever more information that canin turn be used to classify organisms (e.g., themicroscopic). One such technological advancetook place in the1970s, when chemistsdevelopedefficient methods to sequence DNA. The abilityto extract information from the heritable mate-rial of life and use this information to classifylife would revolutionize the classification system.

Carl Woese and George Fox would turn outto be the leaders of the revolution (Woese andFox 1977). These microbiologists sequencedthe DNA that encodes the RNA componentsof the ribosome from a diverse set of organisms.

The DNA sequence information was then usedto construct taxonomic trees (or so-called phy-logenetic trees when they are generated fromsequence data). Using the basic principles oftaxonomy, a phylogenetic analysis attempts togroup organisms, or gene sequences, based onsimilarity. The rRNA gene was an ideal gene tostudy because certain portions of the gene accu-mulate mutations very slowly so these portionscould be used to elucidate ancient evolutionaryrelationships “deep” in the Tree of Life. Thephylogenetic analysis of rRNA sequences byWoese and Fox would show that prokaryotesare divided into two groups, and that one ofthese groups shared a common ancestor witheukaryotes to the exclusion of the other pro-karyotic group (Fig. 1B). This meant that pro-karyotes should no longer be consideredmonophyletic (that all prokaryotes share a com-mon ancestor to the exclusion of eukaryotes)and it meant that our Lemarckian notion ofeukaryotes evolving from prokaryotes neededto be abandoned.

The use of DNA sequence information notonly changed our view about the classificationof life, but it also changed our confidence intaxonomy. Comparing sequences provides adiscrete observation on a level at which develop-ment proceeds from and evolution acts on. Bi-ologists identified the level at which naturalselection and Darwinian evolution enabled lifeto diversify, thus comparing organisms at thislevel would allow biologists to accurately illus-trate the natural classification scheme of life.

Root of the “Tree of Life”

The Darwinian notion of the Tree of Life im-plies that a trunk exists from which all branchesextend if life does indeed share a common an-cestor. The point where the all branches collapseand connect to the trunk is called the root intaxonomy and phylogenetics. Rooting (curi-ously not termed trunking) trees is theoreticallypossible if life shared a common ancestor and ifa gene made a duplicate copy of itself (paralog)before the three domains of life divergedand both copies have since been retained in allthree domains. A phylogenetic analysis of such

Temperature History of Life

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Prokaryotes

Root

B B A E B A E EA

BB

BB

Root

Tree of life Tree of life Ring of life

B A EB

Coral of life

A

D

C

B

Root

Dominated byvertical inheritance

Dominated byhorizontal inheritance

Phenotypic/Morphologicalanalysis

No root

Bacteria(prokaryotes)

Archaea(prokaryotes)

Eukaryotes

DNA/Amino acid sequenceanalysis

No root

Eukaryotes

Figure 1. Tree of Life and its evolution over 100 years. (A) Taxonomy of life based on morphologicalcharacteristics (Chatton 1925). (B) Phylogenetic tree of life based on DNA sequence analysis (Woese and Fox1977). (C) Competing views for the rooting of the phylogenetic tree of life. Initials A, B, and E representArchaea, Bacteria, and Eukarotes, respectively. The tree on the left is based on membrane architecture andinsertion/deletion events in gene (Cavalier-Smith 2002), the tree in the center is based on ancient geneduplication events (Gogarten et al. 1989; Iwabe et al. 1989; Brown and Doolittle 1995; Brown et al. 1997;Gribaldo and Cammarano 1998), and the tree on the right is based on phylogenetic analysis of hundreds ofgenes (Rivera and Lake 2004). (D) Most recent view about the tree of life in light of vertical and horizontalgene transmission (Fournier et al. 2009).





anciently duplicated paralogs could then gener-ate a tree consisting of two subtrees. Each sub-tree would be topologically identical to theTree of Life and the point or node where thetwo subtrees connected to one another wouldthen represent the root of the phylogeny. Root-ing a tree in this manner requires explicit mod-els of sequence evolution because the analysis isattempting to extract a very ancient signal fromthe DNA/amino acid sequences.

The accumulation of DNA sequence datahas allowed biologists to identify multiple paral-ogous gene families that appear to have under-gone duplications before the three domains oflife emerged and yet these genes have been evolv-ing slowly enough to identify them clearly as pa-ralogs. Some examples of gene families includeATPases, elongation factors, tRNA synthetases,signal recognition particles, and inter alia (Go-garten et al. 1989; Iwabe et al. 1989; Brownand Doolittle 1995; Brown et al. 1997; Gribaldoand Cammarano 1998). Initial phylogeneticanalyses of these families place the root ofthe tree on the branch that separates bacteriafrom archaea/eukaryotes (Fig. 1C). This impliesthat the oldest separation or bifurcation onthe Tree of Life was when LUCA split to giverise to the branch that would evolve into bac-teria on one side of the tree and a branch thatwould later serve as the common ancestor ofarchaea and eukaryotes on the other side ofthe tree.

This is currently the prevailing view for theroot of the Tree of Life. We must note, however,that other studies have criticized details of theapproach discussed previously and reach differ-ent conclusions. In one alternative view, a ringhas replaced the tree properties for illustratingthe taxonomy of life. The so-called Ring ofLife developed by Jim Lake suggests that ge-nomes have been created by multiple fusionevents during the evolution of early life andthat these obviate a bifurcating branching pat-tern in the tree (Fig. 1C) (Rivera and Lake2004). One advantage of this view is that it con-siders the likely widespread horizontal or lateraltransfer of DNA during early life. Such transferviolates assumptions of the phylogenetic mod-els used to analyze sequence data.

Another approach to root the Tree of Life isto use morphological or phenotypic observa-tions in an attempt to define a clear splitting orbifurcation in the tree. For instance, membranearchitecture and insertion/deletion events (in-dels) in gene sequences have been used to arguethat the root of the Tree of Life exists withinthe bacterial domain, not on the branch thatseparates bacteria from archaea/eukaryotes(Fig. 1C) (Cavalier-Smith 2002; Cavalier-Smith2006). Whereas a phylogenetic analysis of paral-ogous genes is heavily dependent on explicitmodels of sequence evolution (which can po-tentially and grossly mislead or bias results),the use of membrane architecture and indelevents are conversely independent of models(but which cannot account for parallel or con-vergent evolution).

Biologists’ ability to model evolution hasimproved substantially over the past decade. Bi-ologists concede that the models are not perfectand that it will be a long road before the modelsaccurately capture all evolutionary processes.Despite this hurdle, they are energized by theprospect of delineating evolution at the se-quence level as opposed to being paralyzed bythe challenges.

Lateral Gene Transfer: The “Coral of Life”

Biology’s confidence in illustrating the relation-ships among living organisms has been a roller-coaster ride during the past 20 years. One ofthe most recent challenges has been the realiza-tion that DNA is not solely transmitted in a ver-tical manner to descendents. Multiple studieshave shown that horizontal gene transfer(HGT) has played a major role in the flow ofgenetic information between organisms—espe-cially deep in life’s phylogeny. This obviouslyblurs the phylogenetic picture for life becausea basic assumption of the Tree of Life is thatinformation only flows in a one-way verticaldirection (from parent to offspring in its broad-est sense), not a horizontal direction (from onespecies to another species). This would be theequivalent of violating the linearity of timein the Universe because you cannot be in twoplaces at a single time. HGT essentially allows





two identical pieces of DNA to exist at the sametime in complete disregard to evolutionaryrelatedness.

Does this require that we abandon the conceptof vertical transmission and the Tree of Life? Yesand no. As mentioned previously, one alternativeview is the Ring of Life. This model assumesthat life intermixed so much genetic informationshortly after LUCA diverged that there are nodominate traces of vertical inheritance until wellafter the three of domains of life emerged.

Another alternative not yet mentioned is theCoral of Life (Fig. 1D). This concept is beingdeveloped by Peter Gogarten, and like the Ringof Life, allows for genetic information to flowin a horizontal manner from species to species(Fournier et al. 2009). Unlike the Ring of Life,however, the Coral of Life permits a dominantpath of vertical inheritance to have occurredfor ancient life deep in a phylogeny. This pathis thought to be present in the tree by the obser-vation that some genes appear to be resistant toHGT. Some genes and their protein products areso entrenched in biochemical and cellular path-ways, and protein–protein interactions thathave evolved covariantly, that there is no selec-tive advantage, and in all likelihood there wouldprobably be a disadvantage, for a species to ac-quire a foreign copy of the gene.

These observations have resuscitated thenotion of the Tree of Life (or whatever life-likecreature it illustrates) and shown that biologistsneed not be paralyzed by HGTwhen attemptingto understand early life. Now that we have hope-fully convinced the reader that some phylogenyof life exists, we now discuss how researchers ex-ploit this phylogeny in attempts to understandearly life.

Early Life and Its Temperature History

The temperature history of life is a topic that hasinterested scientists for at least two centuriessince Darwin’s famous statement regarding awarm little pond and the origins of life. Althoughthis article does not deal with the origins of lifeper se, there has been an equal interest in thetemperature history for early life, in particularthe close descendents of LUCA.

All of modern life is categorized into one offour temperature ranges. Heat-loving organismscome in the form of thermophiles (grow opti-mally �458 to 808C) and hyperthermophiles(grow optimally�808C). Cold-loving organismsare called psychrophiles (grow optimally�158C),and middle-loving organisms are called meso-philes (grow optimally �158C to 458C).

Before the mid 1990s, most conclusionsabout the temperature history of life were basedon chemical considerations and the physical be-haviors of biomolecules. This changed with theaccumulation of DNA sequence informationfrom a broad range of species and the topologyof the inferred phylogenies built from this se-quence information. For instance, the first com-prehensive discussion about thermostabilityand ancient life was based on the distributionof hyperthermophilic archaea and bacteria inthe Tree of Life (Stetter 1996). The groupingof hyperthermophilic species on short branchesnear the bases of both the bacterial and archaealdomains of the tree parsimoniously suggestedthat LUCA was a hyperthermophile (Fig. 2).

This conclusion, however, was disputedshortly after it was presented. Some argued fora long-branch attraction artifact in the phyloge-netic approach that caused hyperthermophiles

Archaea

Eukarya

Bacteria

Figure 2. Distribution of modern hyperthermophilicorganisms (Stetter 1996). Thick terminal brancheslead to hyperthermophiles and thin terminal brancheslead to nonhyperthermophiles. Thick internal branchesare inferred based on the distribution and relatednessof modern hyperthermophiles.





to be randomly attracted/grouped instead ofgrouped because of common ancestry. Othersargued that species sampling was sparse andthe distribution of hyperthermophiles was co-incidental. Still others argued that all hyper-thermophiles require a particular protein tosurvive (reverse gyrase) and this protein evolvedthrough a fusion of two other nonrelated pro-teins (Forterre 2002). So, if reverse gyrase is re-quired for hyperthermophiles, and if the reversegyrase cannot be “spontaneously” evolved froma random sequence, then hyperthermophilesmust have evolved from a species that lived ata lower temperature.

A genomic-wide approach to understandingthe temperature history of early life exploitedthe observation that the genomic GþC contentof modern organisms correlates to the optimalgrowth temperature of the host organism itself(Galtier et al. 1999). Higher GþC contentequates to a higher growth temperature becauseGs and Cs form an extra hydrogen bond be-tween base pairs (bps) compared with an A:Tbp. The accumulation of extra hydrogen bondsthroughout the genome would therefore makeit more stable and resistant to heat denatura-tion. These researchers used models of molecu-lar sequence evolution to infer the GþCcontent for gene families believed to have beenpresent in LUCA and inferred to have traverseda mostly vertical descent through the Tree of Lifewith minimal horizontal gene transfer. The re-searchers concluded that LUCA did not have agenomic GþC content consistent with a hyper-thermophilic life style.

To show how sensitive inferences can be tothe use of evolutionary models as input for phy-logenetic analysis, Di Giulio analyzed the samegenomic dataset as previously discussed butused a different phylogenetic algorithm to inferthe GþC content of LUCA (Di Giulio 2000).This analysis resulted in an ancient GþC con-tent for LUCA that is consistent with thermo-philic and hyperthermophilic life styles.

The previous contention represents one ofmultiple examples in which analyses have ledto competing conclusions. Table 1 presents acondensed chronological list of studies thathave attempted to determine the temperature

history of early life. The majority of these stud-ies are strictly computational and were not veri-fied in any experimental manner. The nextsections show how phylogenetic analysis canbe used to guide laboratory experiments toaddress the temperature history of early life.

Ancestral Sequence Reconstruction

The recent accumulation of DNA sequence data,combined with advances in evolutionary theoryand computational power, have paved theway for innovative approaches to understandingthe origins, evolution, and distribution of lifeand its constituent biomolecules (Pauling andZuckerkandl 1963; Benner et al. 2002; Gaucheret al. 2004). One approach to understanding an-cestral states follows a present-day-backwardsstrategy, whereby genomic sequences from ex-tant (modern) organisms are incorporatedinto evolutionary models that estimate the ex-tinct (ancient) character statesofgenes no longerpresent on Earth (Fitch 1971; Shih et al. 1993;Benner 1995; Koshi and Goldstein 1996; Schultzet al. 1996; Cunningham 1999; Omland 1999;Pagel 1999; Schultz and Churchill 1999; Changand Donoghue 2000; Thornton 2004; Hall2006; Liberles 2007). These inferred ancestralgene sequences act as hypotheses that can betested in the laboratory through the resurrectionof the ancestral proteins themselves. Resultsfrom functional assays of the protein productsfrom these ancient genes permit us to accept/reject hypotheses about the sequence them-selves, or about their interactions/bindingspecificities/environments, etc.

Ancestral sequence reconstruction uses stan-dard statistical theory to generate posteriorprobabilities of different reconstructions giventhe data at a site from aligned sequences. Foreach site of the inferred sequence at a phyloge-netic node, posterior values for all 20 aminoacids are calculated and represent the probabil-ity of a particular amino acid occupying a speci-fic site in the protein during its evolutionaryhistory. This posterior probability distributionis calculated from patterns of amino acidsin modern sequences as described by a phy-logeny, a matrix of amino acid replacement





Table 1. Temperature History of Life

Citation

Taxonomic

unit? Study design and observations Conclusion

(Stetter 1996) LUCA A review of hyperthermophilic archaea andbacteria. In the 16S rRNA-based universalphylogenetic tree, hyperthermophiles arerepresented in the deepest and shortestlineages.

Hyperthermophile

(Forterre 1996) LUCA Reverse gyrase is a hyperthermophile-specificprotein formed by the association of a putativetopoisomerase and helicase. If reverse gyrase isa prerequisite to life at high temperatures, itsuggests that hyperthermophiles descendedfrom less thermophilic organisms thatpossessed these putative enzymes.

Mesophile orthermophile

(Galtier et al. 1999) LUCA A model of sequence evolution, assumingvarying GþC content among lineages andunequal substitution rates among sites, wasapplied to estimate ancestral basecompositions of rRNA sequences. The inferredGþC content of the LUCA is incompatiblewith survival at a high temperature.

Mesophile

(Di Giulio 2000) LUCA Reanalysis of the alignment used by Galtier(Science 1999) by maximum parsimonyimplies that the LUCA may have been athermophile or hyperthermophile.

Thermophile orhyperthermophile

(Brochier andPhilippe 2002)

LUB Applied the heterotacy method on the rRNAbacterial phylogeny and found that thePlanctomycetales are the first branchingbacterial group; therefore, concluding themost recent common ancestor of bacteria wasnot hyperthermophilic.


(Gaucher et al. 2003) LUB The most probabilistic ancestral sequences ofelongation factor Tu (EF-Tu) werereconstructed at nodes in the bacterialevolutionary tree. These resurrected proteinswere assayed and their temperature optima of558–658C corresponds to ancient bacterialiving as thermophiles.

Thermophile

(Brooks et al. 2004) LUCA Inferred amino acid composition of 65 proteinsdating to the LUCA by maximum-likelihoodusing expectation-maximization. The inferredprotein sequences were more similar to thosefound in modern-day thermophilic organismsthan mesophilic ones.

Thermophile

(Knauth and Lowe2003; Knauth 2005)

Ocean Low oxygen isotopes in diagenetic cherts(3.5–3.2 Ga) in South Africa indicateextremely high ocean temperatures of 558–858C. Early thermophilic microbes couldhave been global and not huddled aroundhydrothermal vents.

Thermophile

(Continued)





Table 1. Continued

Citation

Taxonomic

unit? Study design and observations Conclusion

(Iwabata et al. 2005) LUCA Studied the thermostabilty of ancestral isocitratedehydrogenase (ICDH) mutants. Theincorporation of ancestral residues into amodern ICDH led to an increase inthermostability.

Hyperthermophile

(Robert andChaussidon 2006)

Ocean Study of oxygen isotope ratios of cherts (siliceoussediments) as a measure of the Earth’s climatein the Precambrian. The observed siliconisotope variations imply seawater temperaturechanges from 708C 3.5 billion years ago to 208Cabout 800 million years ago.

Thermophile

(Becerra et al. 2007) LUCA A study on the evolution of protein disulfideoxidoreductases (PDO) and its implications tothen thermostabilty of the LUCA. The resultsimply that the LUCA lacked PDO-encodingsequences, and may not have been athermophile.

Mesophile

(Shimizu et al. 2007) LUCA Ancestral glycyl-tRNA synthetases (GlyRS) werededuced and residues were introduced inThermus thermophilus GlyRS. Thethermostabilty of these mutants were studiedand several were found with higherthermostabilty and activity than wild-typeThermus. These results suggest a highlythermophilic protein translation system in theLUCA.

Hyperthermophile

(Gaucher et al. 2008) LUB Extensions of earlier work with more than 25phylogenetically dispersed ancestral EF-Tu’s.The resurrected proteins at basal nodes arecompatible with thermophilic environments.

Thermophile

(Boussau et al. 2008) LUCA A computational analysis of both rRNAs andprotein sequences whose results imply that theLUCA was a mesophile. This implies that thetwo lineages descending from LUCA andleading to the ancestors of Bacteria andArchaea-Eukaryota convergently adapted tohigh temperatures.

Mesophile

(Glansdorff et al.2008)

LUCA Archaea have a uniform membrane lipidcomposition that is suited to life at extremeconditions (heat and pH); in contrast,bacterial membranes show a high variability incomposition. The authors suggest thatArchaea emerged from a nonthermophilicLUCA under strong selective pressure foradaptation to high temperature; whereas,bacteria were initially nonthermophilic andadapted by convergent evolution to hightemperatures.


(LUCA) last universal common ancestor of life; (LUB) last common ancestor of bacteria.





probabilities, amino acid equilibrium (station-ary) frequencies, phylogenetic branch lengths,and site-specific replacement rates. The most-probabilistic ancestral sequence (M-PAS) usesthe amino acid with the highest posterior prob-ability at each site within the distribution.

RECENT RESULTS

Elongation factor Tu (Bacteria)/1A (Archaeaand Eukarya) is an ideal protein family tocomputationally reconstruct and then resurrectin the laboratory in our attempts to betterunderstand the temperature history of life.There is no evidence that EF genes have beenlaterally transferred between bacterial lineages,and the thermal stabilities of EFs correlatewith the growth temperature of their host or-ganisms. Thus, EFs are optimally stable at tem-peratures of 158–458C, 458–808C, and .808Cwhen isolated from mesophiles, thermophiles,and hyperthermophiles, respectively. This rela-tionship is consistent with a correlation coeffi-cient of 0.91 between melting temperatures ofproteins and environmental temperatures oftheir host organisms (Gromiha et al. 1999).

Reconstruction of ancestral EF sequenceswere computed across two bacterial phylogeniesselected from the literature (Battistuzzi et al.2004; Ciccarelli et al. 2006). Both phylogenieswere constructed from the concatenation ofnumerous gene families and are thus less sus-ceptible to systematic error compared withphylogenies based on single genes. The twophylogenies capture the main competing viewsfor bacterial relationships. One scenario positsthat hyperthermophilic lineages occupy basalbranches of the bacterial tree, whereas the otherplaces these lineages in a more derived portionof the tree. To accommodate the latter scenario,a phylogeny was selected in which the Firmicutelineage (void of hyperthermophiles) is locatedat the base of the bacterial tree, although othertopologies have been suggested (Brochier andPhilippe 2002).

Thermostability of modern and ancestralEF proteins was monitored using circular di-chroism spectroscopy. Melting temperatures(Tm) of two modern EFs were determined.

The Tm values for EFs from Escherichia coli andT. thermophilus (HB8) are 42.88C and 76.78C.These values highlight the relationship betweenEF stability and the optimal growth temperatureof their respective hosts, �408C and �748C(Williams and da Costa 1992).

Tm values for ancestral EF proteins weredetermined across the two phylogenies. The ther-mostability profiles of the ancestral proteins dis-play the same general trend despite the fact thatthe two phylogenies represent competing hy-potheses. Ancestral EF proteins resurrected atbasal nodes are compatible with thermophilicenvironments, whereas ancestral proteins frommore derived nodes are compatible with coolerenvironments. Consistent with this temperaturetrend is the observation that the node repre-senting the presumed last common ancestor ofbacteria (and thus oldest) had the most thermo-stable protein within each phylogeny (64.88C and73.38C).Thesimilarity inthermostability(,98C)between these two ancestral proteins is note-worthy because the sequences were identicalacross only 78% of the amino acid sites.

The environmental temperature of ancientbacteria inferred from resurrected EF proteinscan be connected to divergence times of majorbacterial lineages to gain a more detailed under-standing of temperature trends for Precambrianlife (Battistuzzi et al. 2004). Divergence esti-mates from Battistuzzi et al. (2004) were appliedto nodes in the current study. Figure 3 high-lights the progressive cooling trend of ancientEF proteins from approximately 3.5 billion to500 million years ago. This temperature trendis strikingly similar to the temperature trendof the ancient ocean inferred from depositionof oxygen and silicon isotopes (Knauth andLowe 1978; Knauth and Lowe 2003; Robertand Chaussidon 2006).

Reconstruction of ancestral EF proteinsthroughout the bacterial domain of life suggeststhat the organisms that hosted these extinct bio-molecules lived in environments that have pro-gressively cooled for approximately 3 billionyears. This evidence is predicated on multipleassumptions. For instance, it assumes that an-cestral sequence reconstruction recapitulatesancient phenotypes and that phylogenies and





divergence dates capture the evolutionary rela-tionships and timing of bacterial divergences.

The inability (short of time travel) to knowthe true relationships of bacterial lineages andtheir divergence times should not preclude at-tempts to understand Precambrian life. Rather,a coherent description of ancient life can begenerated when empirical evidence from di-verse studies converge on analogous conclu-sions. For instance, the same paleotemperaturetrend was observed for ancestral EF proteins re-gardless of the phylogeny. And for the phy-logeny with divergence dates, this trend wassubstantiated when aligned to the inferred pale-otemperature curve of the ancient ocean.

These descriptions are particularly usefulwhen they have predictive value. For instance,the last common ancestor of the mitochondrialbacterium is estimated to have lived 1.66–1.88Ga based on the Tm’s for ancestral EF proteinsfrom the node representing the origins of mito-chondria (51.08C–53.08C). This is consistentwith the origins of mitochondria estimated at1.8 Ga based on a molecular clock (Hedgeset al. 2001), despite the controversial natureof the clock (Graur and Martin 2004) and

assuming the last common mitochondrial bac-terium lived at a time close to the endosymbioticevent between a-proteobacteria and eukaryoticcells.

Our results suggest early life lived at an envi-ronmental temperature similar to today’s hotsprings. Particular geologic theory and evidencesuggests the ancient ocean also had temp-eratures similar to hot springs (Hoyle 1972;Knauth and Lowe 1978; Knauth and Lowe2003). As the ocean cooled from 3.5 to 0.5billion years ago, life may have respondedby adapting its range of growth temperaturesto correspond to its surrounding environment.This connection assumes early life lived in theancient ocean, which seems practical based ongeologic and biologic constraints such as oceandepth/circulation, land mass exposed to the at-mosphere, susceptibility to desiccation, and ul-traviolet radiation, among others. Alternatively,it is possible that the inferred paleotemperaturetrend reflects an ecological trajectory as ancientbacteria transitioned from hot springs/thermalvents to the open ocean.

We note that correlating isotope ratios (d18Oand d30Si) to ancient ocean temperatures is

Phanero-zoic

PrecambrianProterozoic Archaean Hadean

Time (Ga)

Tem

pera

ture

(°C

)

020

30

40

50

60

70

80

90

1 2 3 4

Figure 3. Plot of ancestral EF melting temperatures versus geologic time in billions of years (Ga) (Gaucher et al.2008). Molecular clock estimates and their confidence intervals (horizontal bars) from Battistuzzi et al., using a2.3 Ga minimum constraint for the great oxidation event (Battistuzzi et al. 2004). Solid lines are temperaturecurves of the ancient ocean inferred from maximum d18O (light gray [Knauth and Lowe 1978; Knauth andLowe 2003], dark gray [Robert and Chaussidon 2006]). Although not shown, an analogous trend is seenwith d30Si isotopes (Robert and Chaussidon 2006).





controversial (Kasting et al. 2006; Jaffres et al.2007). In particular, the correlation could be in-valid if isotope ratios were caused by variationin seawater composition alone. This wouldtranslate into a more temperate ancient oceanand be consistent with ancient glaciation events.The similarity, however, in paleotemperaturetrends inferred from d18O, d30Si and ancientEF proteins is striking. Further, the overall trendis compatible with biological evolution. For in-stance, the thermostability of ancient EFs sug-gest the origins of cyanobacteria occurred atan environmental temperature approximating63.78C. This is consistent with an upper tem-perature limit of typical cyanobacterial mats inhot springs (�658C) (Ward et al. 1998).

Overall, the results show that ancient EFthermostability profiles (phenotypes) are ro-bust to uncertainties and potential biases asso-ciated with inferring ancestral character states(genotypes). The results also show how ances-tral sequence reconstruction can connect phys-ical and natural sciences in our attempts tounderstand the environmental conditions thathosted early life.

CHALLENGES

Statistical Models of Molecular SequenceEvolution

Despite insightful studies, the field of ancestralsequence reconstruction is encumbered by itsinability to know whether inferred sequencestruly recapitulate ancestral forms (Williamset al. 2006). Practitioners in the field acknowl-edge a certain degree of inaccuracy associatedwith reconstructing ancestral sequences. Theconcern is not necessarily whether the resur-rected form has the exact composition (geno-type) of the true ancestral form, but ratherthat the resurrected form displays the exact be-havior (phenotype). A reconstructed sequencecan be considered a consensus of a gene distrib-uted throughout a population before speciesdiverge, or before gene duplication. Inaccu-racies in a reconstructed sequence can resultfrom sequence variation of the gene itself withinan ancient population. Assuming the variants

of a homologous gene within a populationhad the same phenotype at a specific geologictime, it does not necessarily matter which indi-vidual genotype is reconstructed.

This assumption is invalid if recombinationof individual genotypes generate new pheno-types and if the reconstructed ancestral geneitself represents a consensus of those genotypes.Additional concerns arise if the reconstructionprocess generates inaccurate sequences becauseof (1) bias in the evolutionary models used toinfer ancestral states or (2) phylogenetic con-ditions such as long branches and incorrectbranching patterns (Felsenstein 1978; Williamset al. 2006; Kelchner and Thomas 2007).

All methods of phylogenetic inference makeassumptions about the underlying evolutionaryprocess of their characters and it is these as-sumptions that determine their relative suc-cesses and failures in the estimation of thetrue phylogeny for a group (Hillis et al. 1992).Much like the manner in which phylogenetictree building algorithms were developed, tested,and critiqued during the 1990s, we anticipatethat ancestral sequence reconstruction algo-rithms and methods will go through a similarprocess in the next couple of years now thatthe reconstruction field is burgeoning. In par-ticular, we anticipate that the developmentand use of mixture models will play an impor-tant role in the development of the field(Gaucher et al. 2002a; Pagel and Meade 2004;Gaucher and Miyamoto 2005).

Experimental Phylogenetics as a Way toBenchmark Ancestral SequenceReconstruction

Computer simulations of reconstructed ances-tral sequences have unequivocally shown thesuperior performance of the “maximum likeli-hood” (ML) sequence in terms of accuracy inrecovering a true ancestral sequence when itis inferred from tip/leaf/extinct/modern se-quences (Huelsenbeck 1995; Yang et al. 1995;Zhang and Nei 1997; Cai et al. 2004; Krishnanet al. 2004; Williams et al. 2006). Although com-puter simulations of ancestral genotypes andphenotypes are an intriguing approximation





for reality, a true benchmark of method per-formance requires an evaluation of biologicalsequences and phenotypes measured in thelaboratory. As such, it would be useful to usemembers of the green fluorescent protein familyto generate an “experimental phylogeny” (Hilliset al. 1992; Bull et al. 1993). Green fluorescentproteins (GFP) and their varying-colored ho-mologs are widely used as in vivo fluorescentmarkers and have also been used in experimen-tal paleogenetic studies (Matz et al. 1999; Matzet al. 2002; Ugalde et al. 2004).

Research in our lab is currently generatingleaf/tip sequences from an evolved experimen-tal GFP phylogeny that will in turn be used toestimate ancestral genotypes and phenotypes.Because the leaf/tip sequences will be sequen-tially evolved from nodes on the experimentalphylogeny in the laboratory, we will know thetrue ancestral genotypes and phenotypes. Thispresents us with the unique opportunity to com-pare/contrast different approaches attemptingto reconstruct ancestral sequences from biolog-ically relevant conditions. Our work representsthe first time evolved sequences will be used tobenchmark ancestral sequence reconstructionapproaches to address issues of ambiguity andbias associated with both reconstructed geno-types and phenotypes.

Sequences at the tips (leaves) of the evolvedphylogeny will then be used to computationallyreconstruct the inferred ancestral fluorescentsequences at all nodes of the experimental-derived tree. DNA-, codon-, and amino acid-based approaches will be exploited (Yang et al.1995; Chang et al. 2002; Thornton 2004; Thom-son et al. 2005). For each type of data input, wewill test different models of sequence evolutionand their potential effects on ancestral sequencereconstruction(e.g., transition/transversionratios,codon tables, amino acid matrices, rate het-erogeneity, and others) (Gaucher et al. 2001;Gaucher et al. 2002b; Gaucher and Miyamoto2005).

RESEARCH DIRECTIONS

We anticipate that our understanding of thetemperature history of early life will continue

to improve in the coming years. This improve-ment will not be driven by any single advance-ment. Rather, a combination of advances inmultiple scientific disciplines will enhance ourunderstanding. This is due in large part tothe multidisciplinary nature of studying thetemperature history of life. For instance, ourunderstanding of taxonomic and evolutionaryrelationships of bacteria and archaea will greatlyenhance our understanding of deep phylogeny,and this in turn will improve our understandingof the environmental conditions that supportedthese ancient life forms.

More sophisticated models of molecular se-quence evolution will help us to better under-stand ancient life. Such models will improveour ability to accurately construct phylogenetictrees as well as add rigor to ancestral sequencereconstruction methods. The biologists andcomputational scientists will not be making im-provements alone. We anticipate that advancesin chemical and geological techniques will alsohelp us define properties of early life.

We are further energized by the prospect ofjoining evolutionary biology and synthetic biol-ogy in our attempts to dissect early life. The nextlogical extension of molecular reconstructionbeyond natural history is to synthetic biology.Synthetic biology means different things todifferent scientific disciplines (Benner and Sis-mour 2005; Endy 2005). Surprisingly, however,biologists seem to have taken a backseat tochemists and engineers in the development ofthis field. It seems apparent that synthetic biol-ogy would stand to benefit if “molecular recon-structionists” contributed to its progress. In thisway, an evolutionary synthetic biology isformed. A couple of examples come to mind:cellular machines and recombinant genomes.

Cellular machines have a broad range of po-tentials, from simple expression of heterologousgenes for laboratory analysis to the synthesis ofminimal artificial cells (Deamer et al. 2002;Martin et al. 2003; Noireaux and Libchaber2004; Chen et al. 2005). We anticipate that an-cestral reconstructed sequences will providesome of the foundation of genetic informationfor these machines in the future. As a firststep, we have shown that ancestral EF proteins





can participate in a reconstituted in vitro trans-lation system designed to incorporate unnaturalamino acids (unpubl. data). Further, experi-mental evolution studies of these ancestralgenes introduced into laboratory organismswill enhance our biological understanding ofadaptive and sequence landscapes, shed lighton the transition to protein synthesis by earlylife, and help elucidate the evolution and adap-tation of biochemical pathways. This work willhave obvious extensions to natural history andthe origins of (early) life.

We also anticipate that the synthesis of re-combinant, minimal, and/or ancestral genomeswill have a profound effect on our understand-ing of early life. The Venter Institute, for in-stance, is in the process of constructing aminimal synthetic Mycoplasma genome (Glasset al. 2006; Lartigue et al. 2007; Gibson et al.2008). As molecular reconstructionists, wewould ask why not construct a complete ances-tral biochemical pathway (e.g., operon), or evena complete ancestral genome? The ancestral re-construction field would no longer be confinedto single gene analysis. It is also quite possiblethat our understanding of what constitutes asustaining minimal genome required to supportlife will be altered through ancestral reconstruc-tions. In this way, homologous genes perform-ing two different, but related, functions mayshare a single common ancestor that performedboth of these functions, albeit with less effi-ciency or specificity.

We anticipate that our understanding of theorigins of life and its early evolution will be greatlyenhanced by advances in molecular evolutiontechniques in the coming years. Phylogeneticmethods and ancestral sequence reconstructionwill continue to be combined in innovativeways to contribute to the Origins of Life field.

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November 25, 20092010; doi: 10.1101/cshperspect.a002238 originally published onlineCold Spring Harb Perspect Biol

Eric A. Gaucher, James T. Kratzer and Ryan N. Randall Earth

How a Tree Can Help Characterize Early Life on−−Deep Phylogeny

Subject Collection The Origins of Life

Constructing Partial Models of Cells

et al.Norikazu Ichihashi, Tomoaki Matsuura, Hiroshi Kita,

The Hadean-Archaean EnvironmentNorman H. Sleep

RibonucleotidesJohn D. Sutherland

An Origin of Life on MarsChristopher P. McKay

Characterize Early Life on EarthHow a Tree Can Help−−Deep Phylogeny

RandallEric A. Gaucher, James T. Kratzer and Ryan N.

Primitive Genetic PolymersAaron E. Engelhart and Nicholas V. Hud

Medium to the Early EarthCosmic Carbon Chemistry: From the Interstellar

Pascale Ehrenfreund and Jan Cami

Membrane Transport in Primitive CellsSheref S. Mansy

Origin and Evolution of the RibosomeGeorge E. Fox

The Origins of Cellular LifeJason P. Schrum, Ting F. Zhu and Jack W. Szostak

BiomoleculesPlanetary Organic Chemistry and the Origins of

Kim, et al.Steven A. Benner, Hyo-Joong Kim, Myung-Jung

From Self-Assembled Vesicles to ProtocellsIrene A. Chen and Peter Walde

the Origins of LifeMineral Surfaces, Geochemical Complexities, and

Robert M. Hazen and Dimitri A. Sverjensky

The Origin of Biological HomochiralityDonna G. Blackmond

Historical Development of Origins ResearchAntonio Lazcano

Earth's Earliest AtmospheresKevin Zahnle, Laura Schaefer and Bruce Fegley

http://cshperspectives.cshlp.org/cgi/collection/ For additional articles in this collection, see

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