Evolution of Optimal Accuracy and Stability in Biological Systems

REVIEW

Evolution of Optimal Accuracy and Stability in Biological Systems

by Robin Holliday

The Australian Academy of Science, Canberra, Australia, 12 Roma Court, West Pennant Hills, N.S.W.2125, Australia

(phone: 61298733476; fax: 61298712159; e-mail: [email protected])

Dedicated to Professor Leslie Orgel on the occasion of his 80th birthday

Introduction. – Unicellular Organisms. When the first replicating molecules arosethey would have been highly error-prone. The critical issue is whether a replicatingmolecule produces sufficient progeny molecules to continue their survival, or whetherthe error level is so high that all are doomed to extinction. Assuming there is survival,there should then be gradual selection for improved accuracy. The question of optimalaccuracy does not arise at this very early stage of evolution, because any improvementin accuracy would be advantageous and, through selection, lead to further improve-ment. These early stages of the origin of life are discussed by other authors, and will notbe considered further here.

Instead, the starting point can be taken to be the first primitive cells containing anucleic acid genome, proteins and associated structures such as a membrane. Thisintroduces the first likely optimum error levels in the strategy and likelihood ofsurvival. One strategy is to replicate as quickly as possible, utilising all available energyresources, whilst errors in macromolecules also produce a proportion of nonviable cells.A somewhat different strategy, with higher accuracy, is to reduce the number ofnonviable cells produced during slower replication. Which will win out? It is likely thatthe production of nonviable cells is more costly than the increase in accuracy by proof-reading and repair. In this context, it is interesting to consider some present daymicrobial models. Rec BC mutants of Escherichia coli produce at least 50% nonviablecells, but continue to grow [1] [2]. Another example is a strain of the fungus Ustilagomaydiswith three different defects in DNA repair which produces 80% nonviable cells,but continues to grow [3]. We can expect that, in both cases, wild-type cells wouldoutgrow the mutant ones, because the production of a significant proportion onnonviable cells will reduce the growth rate of a clonal population. We can also concludethat the loss of a small number of gene products, involved in DNA repair or cell cycle,introduces lethal defects perhaps comparable to what might be expected in primitiveorganisms.

Thus the first optimum is the balance between investment in proof-reading devicesand repair, and the rate of cell division. An organism which was able to eliminate everymolecular defect would be investing resources that could otherwise be used for celldivision. In this connection, it is interesting that a mutant of E.coli with increasedaccuracy of ribosome translation grows more slowly than wild type [4]. Strains or

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mutants that invested fewer resources in eliminating errors might grow more quickly,but they are more likely to produce nonviable cells. In present-day microorganisms,there is a very minor fraction of nonviable cells, perhaps in the range of 0.01–0.5%.Orgel [5] considered an experiment in which a bacterium divides, and one daughter cellis chosen at random. This then divides, and one daughter is chosen at random, and soon. Sooner or later, there will be a lethal event, and the daughter chosen will not divide.The machinery for cell division will never be perfect, and there will certainly bevariation between species.Multicellular Organisms. The first multicellular organisms probably consisted of

undifferentiated cells, and propagation might have just involved the mechanicalseparation of one population into two or more groups of cells. Primitive error-pronecells could form such cellular aggregates, because the presence of nonviable cells wouldhave relatively little effect. As soon as multicellular organisms with differentiated cellsappear, the situation is different. Assuming these early organisms had a defined formand shape, then their development from a single cell demands regulatory controls,including the unfolding of cell lineages. In this situation, the production of dead cellswould be disadvantageous, because it would have deleterious effects on developmentand the adult. We can, therefore, be fairly sure that the evolution of differentiatedmulticellular organisms depended on the prior evolution of accurate largely error-freecellular systems. Some simple present-day animals and many plants have strikingpowers of regeneration, so that if some part of the organism is damaged it can readily bereplaced. This process can continue indefinitely, provided energy resources areavailable. Thus, the organism is potentially immortal. However, other animals evolvedin a different direction. Having developed to an adult, the constituent cells lose theircapacity to divide, apart from the germ cells which will form the next generation. Thisraises another question: how long are these non-dividing cells likely to survive? We canillustrate this life-style strategy with the small free living nematode Caenorhabditiselegans. These organisms develop according to a very rigid programme: there arestrictly defined cell lineages which lead to the formation of a constant number of cells inevery adult individual of the same sex [6]. During this process, specific cells areeliminated by programmed cell death. The adult lifespan depends on the survival of thenon-dividing cells. For a nematode, this is measured in days, but the longest lived non-dividing cells in some vertebrates, such as neurones or cells of the retina, may survivefor a century or more. Possible relationships between cell stability and defects inmacromolecules will be considered later.Errors inMacromolecules.Many studies of mutation frequencies suggest that errors

or mistakes in DNA replication occur at the rate of about one in 108 nucleotides [7].The DNA polymerase complex has a proof-reading mechanism, and, if this fails, thenthe resulting mismatched base pair is recognised by a repair system which removes theincorrect base in a daughter DNA molecule. Obviously, primitive organisms withoutthese mechanisms would have a very much higher mutation rate, so we can concludethat natural selection favoured a low mutation rate. As has often been pointed out, acomplete absence of mutation would eliminate the genetic variation on which naturalselection can act. Thus, we can conclude that there is a low optimal rate of errors inDNA in present-day organisms, but it is highly likely that this optimum varies betweentaxonomic groups, or even between species.

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The error level in RNA synthesis has been measured less frequently, but it is knownto be about four orders of magnitude higher than that in DNA [8]. Thus, viruses whichhave RNA genomes, such as influenza virus, mutate much more frequently than DNAviruses. It is not surprising that large or small DNA genomes are maintained in a verystable state, whereas this is less important in the synthesis of cellular RNA, whichcommonly has a fairly transient existence.

Errors in the synthesis of messenger RNA (mRNA) will often result in themisincorporation of an amino acid in a polypeptide chain. In addition to that, there willbe errors in the translation of mRNA, so the synthesis of proteins will be less accuratethan the synthesis of RNA. There is a dearth of accurate information about the actualerror levels, but, for proteins, it is likely to be higher than one in 104 amino acids, andlower than one in 103 amino acids [9]. There can be proof-reading mechanisms duringprotein synthesis, but they may require either energy in the form of ATP, or a slowerrate of translation [8–11].

What sets a likely optimum? Some polypeptide chains have 1000 amino acids ormore, so if the errors were too high, few would be error-free. One also has to considerthe stability of the mechanism of protein synthesis. It was pointed out by Orgel thaterrors in the synthesis of proteins may lower the specificity of the componentsnecessary, and this could have the effect of producing more errors [12]. This errorfeedback could gradually increase and produce what has somewhat misleadingly beencalled an Jerror catastropheK. Orgel later pointed out that errors could under somecircumstances increase in this way, or they could be stabilised at a given level [13].There has been much debate about the possible relationship of protein errors to cellularageing, but a dearth of experimental information [14].

It can be concluded that the optimum accuracy of protein synthesis is set by fiveparameters: 1) the resources used in proof-reading; 2) the speed of transcription andtranslation; 3) the length of polypeptide chains; 4) the breakdown of abnormalmolecules by proteases, and 5) the stability of the processes of transcription andtranslation. It is very likely that these parameters vary between different species(microbial, plant, and animal), and also in different biological contexts, for example, ingerm line cells, stem cells, and differentiated somatic cells.Evolution of Accuracy and Stability. This raises many complex questions about the

evolution of optimal accuracy, all relating in one way or another to the Darwinianfitness of the organism. Some specialised organisms may live in a fairly constantenvironment, whereas others live in environments which are very variable, and thisrequires plasticity in physiological and biochemical processes, and allows the organismto adapt to particular environmental situations. The relationship of different life stylesto accuracy are at present unclear.

Surprisingly, some of the most important information comes from the successfulstudy of ageing, which can no longer be regarded as an unsolved problem in biology[15–20]. It is now evident that the evolution of lifespan relates to an animalKs strategyfor survival in natural environments. Populations are age-structured, because the causesof death are primarily from predators, disease, starvation, and drought. Thus, very fewanimals survive to old age. Under these circumstances, it increasesDarwinian fitness tochannel resources into reproduction, and not into the preservation of the soma or body.However, it is clear that natural selection can favour the evolution of shorter lifespans


or of longer lifespans. The lifespan of mammals vary by a factor of thirty. Small groundliving mammals, such as rodents, have a high natural mortality, and they breed veryquickly. Large mammals, such as pachyderms, whales, the great apes, and man, breedfar more slowly and have the longest lifespans. It is evident that lifespan depends on themaintenence of the soma, and that short-lived species invest much less in maintenancethan long-lived ones. This is now supported by a considerable body of experimentalevidence which comes from the comparison of species with different life spans ([16]cites 15 studies providing positive evidence, and since then there have been others[21]). For example, there are many studies of DNA repair and metabolism thatdemonstrate that there is a correlation between the efficiency of repair, or the activityof enzymes with nucleic acid substrates, and longevity. There are many maintenancemechanisms, including defence against free radicals, the immune system, DNA repair,breakdown of abnormal proteins, detoxification, wound healing, physiological homeo-stasis, and apoptosis. Together they consume a significant proportion of all energyresources.

A study of somatic mutation frequencies is particularly revealing. One can measurequite accurately the frequency of lymphocytes lacking the enzyme HGPRT (hypo-xanthine-guanine phosphoribosyl transferase). When this was done in humans, it wasfound that there was about a tenfold increase throughout ca. 80 years of lifespan. Whenthe same measurement were made in mice, there was again ca. a tenfold increase, butthis was over a less than three-year period. Therefore, the somatic mutation frequencyin mice is very much higher than it is in man. The mutation rate per cell per year is 5–12�10�5 in mouse lymphocytes, and 5�10�7 for human lymphocytes [22] [23].Similarly, the appearance of neoplasms is far higher in rodents than in man. This meansthat the stability of normal somatic cells is much greater in man than it is in rodents, anobservation that has been known for a long time [24]. It is reasonable to assume thatthese rates of mutation or neoplastic transformation are optima that have evolvedduring the evolution of longevity over a very long time. Another example is the stabilityof the mitochondrial genome. It is well-established that deletions in the mitochondrialDNA accumulate in cells during ageing irrespective of maximum longevity of thespecies studied [21] [25]. This means that they are far more stable and accumulate muchmore slowly in long-lived animals

We also know that the stability of long-lived proteins also relates to longevity. Thecross-linking of collagen is a good biomarker of ageing, but the rate of cross-linking isfar higher in the rat than in man. Similarly, irreversible changes in the crystalline lens(leading to cataracts) occur much more slowly in humans than in rodents. If the rate ofpost-synthetic changes in proteins is species-specific and relates directly to longevity, itmight also be expected that the accuracy of protein synthesis would also relate tolongevity. Unfortunately, in this case we do not have any solid information about theaccuracy in different species.

Stability at the cell level must also be optimised. Neurons in the brain of a mouse orrat must survive for about three years, whereas those in the human can survive for acentury. The same applies to other types of non-dividing cells, such as the muscle cellsof the heart, or the cells of the retina. Many invertebrates, such as nematode worms andinsects, consist of non-dividing cells, apart from germ cells. The survival of C. elegansand the fruit fly Drosophila is measured in days or a few weeks.


What determines these different cell stabilities? It is easy to say that cell-maintenance mechanisms are responsible, but the actual reasons for a cell to reach theend of its lifespan are not at all well defined. Some causes are unequivocal, such as, inmammals, the loss of a single indispensible gene on the X chromosome, but there areprobably many others involving changes in proteins and cellular structures. It is obviousthat a cell is dead when it can no longer synthesise proteins, or produce ATP, but thereare likely to be many more subtle events that can lead to its death.

There are good biological reasons why the accuracy of DNA synthesis is muchgreater than that of RNA and protein synthesis. The preservation of the geneticmaterial is vital for survival and further evolution. In the same way, it can be arguedthat the germ line must be protected, whereas the somatic cells are dispensible. Thereare not obvious differences between the germ-line mutation rates in man and mice [7],whereas, as we have seen, the mutation rates in somatic mouse cells are much higherthan in human somatic cells. Thus, there are likely to be different optimum rates for thetwo types of cell.

With regard to an animalKs longevity, it is evident that natural selection can act toreduce lifespan, or alternatively, it can act to increase it. These trends depend on theanimalKs lifestyle, its ecological niche, and, above all, its mortality in its naturalenvironment. In general, if mortality increases, a species may become extinct unless itcan adapt to the new environment by developing more quickly and producing moreoffspring. Resources previously used for maintenance are instead channeled intogrowth and reproduction. If the mortality is reduced, more animals survive to breed,and the population can be maintained with fewer offspring. This trend leads to theselection of later breeding and a greater longevity. Resources previously used forreproduction can instead be channelled into maintenance and stability.

Conclusions. – Although the accuracy of synthesis of macromolecules has not, orcannot, be measured in a variety of biological contexts, at least one general conclusioncan be drawn. In the evolution of optimal accuracies, there is a trade-off between rateor speed of synthesis, and the accuracy. This is illustrated in the Figure. Errors can intheory be eliminated if sufficient resources are invested, but this will slow down growthrate, so it becomes non-adaptive. Saving resources by reducing proof-reading mayincrease the growth rate, but the consequence may be instability and the loss ofphysiological homeostasis. The rules determining optimum error levels will be verydifferent for DNA synthesis, in comparison to RNA and protein synthesis, or theassembly of various cellular components. In organisms that have finite lifespans, thestability of cells and tissues plays a central role, and this will be greater in long-livedspecies, and less in short-lived ones. The role of cell division and cell replacement inmaintaining stability is very important, and the survival time of post-mitotic non-dividing differentiated cells will also be critically important. It is probably safe toconclude that cells with very long lifetimes, such as neurons, have the means to preventthe occurrence of lethal events. Such events may occur more frequently in exactly thesame type of cell in an animal which has a shorter lifespan. The evidence stronglysuggests that dividing somatic cells, apart from stem cells, have finite proliferativepotential. In contrast, germ line cells are potentially immortal, and they have the meansto propagate themselves indefinitely. This ability may well include the elimination of


defective cells, by one or more Jquality controlK mechanisms. This is like a proof-readingmechanism at the level of the cell. This keeps the germ line in a steady state, and meansthat germ cells show few signs of ageing, apart from a slightly increased likelihood ofsome genetic defects. In general, offspring from young adults have the same lifespan asoffspring from older adults. This must mean that the optimal levels of errors and defectsis kept very low in germ line cells.

REFERENCES

[1] K. Haefner, J. Bacteriol. 1968, 96, 652.[2] J. E. Miller, S. D. Barbour, J. Bacteriol. 1977, 130, 160.[3] R. Holliday, R. E. Halliwell, M. W. Evans, V. Rowell, Genet. Res. 1976, 27, 413.[4] T. Ruusala, A. S. Andersson, M. Ehrenberg, C. G. Kurland, EMBO J. 1984, 3, 2575.[5] L. E. Orgel, Nature 1973, 243, 441.[6] J. E. Sulston, E. Schierenberg, J. G. White, J. N. Thomson, Dev. Biol. 1983, 100, 64.[7] J. M. Drake, JThe Molecular Basis of MutationK, Holden Day, San Francisco, 1977.[8] JAccuracy in Molecular ProcessesK, Eds. T. B. L. Kirkwood, R. F. Rosenberger, D. J. Galas, Chapman

& Hall, London, 1986.[9] T. B. L. Kirkwood, R. Holliday, R. F. Rosenberger, Int. Rev. Cytol. 1984, 92, 93.

[10] J. J. Hopfield, Proc. Natl. Acad. Sci. U.S.A. 1974, 71, 4135.[11] J. Ninio, Biochemie 1975, 57, 587.[12] L. E. Orgel, Proc. Natl. Acad. Sci. U.S.A. 1963, 49, 517.


Figure. The general relationships between optimal accuracy and Darwinian fitness. The importantparameters setting the optimum are the rate of growth, the energy resources available, and the error

levels in macromolecular synthesis, which are the converse of accuracy.

[13] L. E. Orgel, Proc. Natl. Acad. Sci. U.S.A. 1970, 676, 1476.[14] R. Holliday, Exp. Geront. 1996, 31, 449.[15] L. Hayflick, JHow and Why We AgeK, Ballantine, New York, 1994, 1996.[16] R. Holliday, JUnderstanding AgeingK, Cambridge University Press, Cambridge, 1995.[17] S. N. Austad, JWhy We AgeK, John Wiley & Sons, New York, 1996.[18] T. B. L. Kirkwood, Cell 2005, 120, 437.[19] R. Holliday, Ann. N.Y. Acad. Sci. 2006, 1067, 1.[20] R. Holliday, JAging: the Paradox of LifeK, Springer, Dordrecht, The Netherlands, 2007.[21] G. Barja, Biol. Rev. 2004, 79, 235.[22] A. A. Morley, Ann. NY. Acad. Sci. 1998, 854, 20.[23] A. A. Morley, Flinders Medical Centre, Adelaide, personal communication, March, 2007.[24] R. Peto, in JOrigins of human cancerK, Eds. H. H. Hiatt, J. D. Watson, J. A. Winston, Cold Spring

Harbor Laboratory Press, New York, 1977, p. 1403.[25] I. A. Trounce, University of Melbourne, Australia, personal communication, August 2006.

Received April 9, 2007


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Evolution of Optimal Accuracy and Stability in Biological Systems