Recently, Nick Lane, a biochemist and Provost’s Venture Research Fellow in the Department of Genetics, Evolution and Environment at University College London, published a new book, Life Ascending: The Ten Great Inventions of Evolution.
Nick Lane lays out ten biological phenomena for which he seeks to propose plausible evolutionary explanations. Among the phenomena discussed by Lane are the origin of life, DNA, photosynthesis, the complex cell, sex, movement, sight, hot blood, consciousness, and death. But does Darwinism have the goods? Or does Nick Lane offer us only a series of wishful speculations?
New Scientist offered the following praise for Lane’s work:
What makes this such a great read is that Lane, a biochemist by training, does not simply rehash the standard evolutionary tales – unlike many books published recently. Instead, he is familiar with all the latest research and has made up his own mind about who is right. The result is an original and awe-inspiring account. The first two chapters are the most coherent and convincing summaries of the dawn of life and of DNA that I have ever read.
But is Lane’s book all that it is touted to be? Lane certainly demonstrates a significant grasp of the relevant fields and conveys his understanding and insights with a masterful eloquence and gripping style. Moreover, Lane’s book is of a unique kind. Very few books are written today which make such a determined and courageous attempt at resolving such fiendish puzzles for modern evolutionary thought.
While I certainly do not attempt to disparage Lane’s refreshing and brilliantly constructed work, I do seek to offer a critical appraisal of some of the evolutionary explanations he offers. In so doing, I hope to provide insight into where further work needs to be done, and where I think the explanations offered by Lane are inadequate.
Chapter 1 – The Origin of Life
Lane’s first chapter provides a refreshing overview of the contemporary models concerned with the origin of the building blocks necessary for the first life, discussing the presented material in the context of Lane’s own work related to the origin of life in hydrothermal vents.
However, numerous problems abound for the hydrothermal vent hypothesis for the origin of life, as will be discussed in more detail later in this review. For example, as Stanley Miller has pointed out, the polymers are “too unstable to exist in a hot prebiotic environment.” Miller has also noted that the RNA bases are destroyed very quickly in water when the water boils. Intense heating also has the tendency to degrade amino acids such as serine and threonine. A more damning problem lies in the fact that the homochirality of the amino acids is destroyed by heating.
Of course, accounting for the required building blocks is an interesting problem, but from the vantage of ID proponents, it is only one of many problems facing materialistic accounts of the origin of life. After all, it is the sequential arrangement of the chemical constituents — whether that happens to be amino acids in proteins, or nucleotides in DNA or RNA — to form complex specified information (a process which requires the production of specified irregularity), which compellingly points toward the activity of rational deliberation. To his credit, unlike many origin of life theorists, Lane does not entirely ignore this problem. In fact, it is to this puzzle that Lane turns his attention in the second chapter.
Chapter 2 – The Origin of DNA
After explaining the basic principals of molecular biology that everyone learns as a college freshman, and having provided a brief overview of the history behind the elucidation of the structure and nature of the DNA molecule, Lane seeks explanation for a mystery that has haunted biology for half a century — the optimality of the genetic code.
The genetic code consists of a total of sixty-four triplets of nucleotide bases (a “codon”), each of which codes for an amino acid. There are only twenty different amino acids, and so some of the codons are redundant. This means that several codons can code for the same amino acid. Such a choice of genetic code is not arbitrary, but seemingly the product of rational scheming, such that the cell would be optimally protected from the detrimental effects of substitution mutations.
For example, the amino acid leucine is specified by six codons. One of them is CUU. Substitution mutations in the 3′ position which change a U to a C, A or G result in the alteration of the codons to ones which also specify leucine: CUC, CUA and CUG respectively. On the other hand, if the C in the 5′ position is substituted for a U, the codon UUU results. This codon specifies phenylalanine, an amino acid which exhibits similar physical and chemical properties to leucine. The fact in need of explaining is thus that codon assignments are ordered in such a way as to minimize ORF degradation.
[Lawrence Hurst and Stephen Freeland] made science headlines when they compared the genetic code with millions of random computer-generated codes. They considered the damage that could be done by point mutations, in which one letter of a codon is switched for another. Which code, they wondered, could resist such point mutations best, either by retaining exactly the same amino acid, or by substituting a similar one? They found that the real genetic code is startlingly resistant to change: point mutations often preserve the amino acid sequence, and if a change does occur, a physically related amino acid tends to be substituted. In fact, Hurst and Freeland declared the genetic code to be better than a million alternative randomly generated codes. Far from being the folly of nature’s blind cryptographer, the code is one in a million. Not only does it resist change, they say, but also by restricting the catastrophic consequences of the changes that do occur, the code actually speeds up evolution: obviously, mutations are more likely to be beneficial if they are not catastrophic. (p. 48)
Lane argues — and I would agree — that the only way to rescue dysteleological evolution (e.g. to avoid an inference to design) is to posit the action of selection to account for such an error minimization property. On page 49, Lane writes:
Short of positing celestial design, the only way to explain optimization is via the workings of selection. If so, the code of life must have evolved.
Students of logic will immediately notice that this is what one might call a circular argument — that is, when the conclusion of your argument is assumed in your premise. But to Lane’s credit, he does attempt to offer some justification for this view. Let’s examine Lane’s reasons for favoring the selection hypothesis over the design hypothesis.
Immediately following the preceding quotation, Lane argues:
Certainly, a number of trivial variations in the ‘universal’ code among bacteria and mitochondria do show that, if nothing else, the code can evolve, at least under exceptional circumstances. But how does it change without causing mayhem, you may ask, with Crick? The answer is: discretely. If an amino acid is encoded by four or even six different codons, some tend to be used more often than others. The rarely used codons can in practice be redesignated to a different (but probably related) amino acid without catastrophic consequences. And so the code evolves.
Lane rightly acknowledges that changes in codon assignments would be catastrophic to the cell because such a mutation would ultimately lead to changes in amino acids in every polypeptide made by the cell. Lane tries to argue round this by positing that the lesser-used codons can be redesignated to a different but related amino acid, thus allowing the genetic code to become optimized. There are, however, significant difficulties with this proposal.
First, his entire evolutionary scheme requires a functional genetic code to begin with. This code essentially operates just like our modern-code, with codons encoding amino acids. He believes that once this system is in place, new amino acids can be added into the system. But we must not forget that his entire scheme requires a primitive — but entirely functional — form of the genetic code as its starting point. He may seek to explain how the code can change, but he does not explain how the code can originate.
Second, even if we grant Lane his premise that the genetic code can be modified over time, it still remains to be determined whether there are sufficient probabilistic resources at hand to justify appeals to the out-workings of chance and necessity. How many different codes would need to be evaluated? How does this figure compare to the temporal and spacial resources available? Lane does not answer either of these questions.
Let’s do the math.
Hubert Yockey, a biophysicist and information theorist, has argued that the number of potential genetic codes is of the order of 1.40 x 1070. Yockey concedes the extremely conservative figure of 6.3 x 1015 seconds for the time available for the genetic code to evolve. Note that this assumes that the genetic code has been evolving since the Big Bang. So, how many codes per second would be required to be evaluated in order for natural selection to “stumble across” the universal genetic code found in nature? The math works out at roughly 1055 codes per second.
Think about that. Even granting such absurd estimates — all the time available since the Big Bang — natural selection would be required to evaluate 10 55 genetic codes per second in order to have a reasonable chance of stumbling across the optimized genetic code found in nature. This treacherous hurdle is accentuated when one considers more reasonable estimates. The earth likely became bio-habitable about 3.85 billion years ago, with signs of the first life appearing around 3.8 billion years ago. More realistic estimates for the time available make the problem only more daunting.
By Lane’s own concession, if the combination of chance and selection cannot save the day, our only available recourse is to design. And such an explanation is, to me, the most plausible — most reasonable — explanation for this important feature of living systems.
But it only gets worse.
The genetic code found in nature — with only a few exceptions — is universal. Lane rightly points out that there are small variations on the conventional genetic code found in, for example, mitochondria. But these are organisms with small genomes, and hence only a small number of polypeptides in the cell would experience an altered sequence of amino acids. This would allow a small amount of evolution to take place, but within limited parameters.
It stands to reason that had the genetic code experienced such permutations (randomly sampling a large proportion of all the available codes), one would expect to see far more variation in the genetic code than one sees, perhaps — at the very least — at the level of the three major domains of life: the eukaryotes, the archae and the eubacteria.
Lane also entertains the possibility of a doublet code, which, he proposes, existed prior to the emergence of the triplet code. But Lane’s proposed scenario suffers many shortfalls. Lane writes:
We’ve already noted that a doublet code could encode up to 16 out of the 20 different amino acids. If we eliminate the 5 most complex amino acids (leaving 15, plus a stop codon), the patterns in the first two letters of the code become even stronger. It might be, then, that the primordial code was a doublet, and was only later expanded into a triplet code, by ‘codon capture’; the amino acids competed among themselves for the third position. (p. 47-48)
“Codon capture”? Lane offers no explanation as to how a subsequent transition from two to three bases would occur without seriously disrupting the code. Secondly, and much more serious, are the implications for proteins based on a severely limited set of amino acids. In particular, it must be presumed that early activating enzymes comprised fewer types of amino acids and yet had the necessary level of specificity for reliable implementation of the code. Such a proposal also has to account for the protein components of the ribosomes (while utilizing no more than 15 or 16 amino acids).
One final, and equally detrimental, difficulty for Lane’s suggestion, lies in accounting for the reason for the addition of the new amino acids. These amino acids would lack utility until they were incorporated into proteins (which won’t happen until they are included in the genetic code). Thus, these enzymes must be synthesized by enzymes which lack not only the amino acids they produce, but also all of the necessary machinery for including them in the code (activating enzymes, tRNAs, aaRS enzymes, etc). In other words, incorporating a new amino acid into the genetic code requires a whole suite of integrated parts — not an event that is amenable to stepwise evolution. Lane’s proposal, then, lacks plausibility.
Following his discussion of the genetic code, Lane turns his attention to the chicken-and-egg paradox pertaining to the relationship of DNA to proteins. Lane explains,
The problem was that DNA is more or less inert, and requires specific proteins even to replicate itself. On the other hand, specific proteins don’t get to be specific by chance. They evolve by natural selection, and for that to happen their structure must be both inheritable and variable. Proteins don’t act as their own heritable template: they are coded by DNA. And so proteins act as their own heritable template: they are coded by DNA. And so proteins can’t evolve without DNA, while DNA can’t evolve without proteins. If neither can evolve without the other, selection can never get started. (p. 49)
Again, Lane offers us a prediction by which we can test the causal efficacy of blind, undirected, mindless material processes to account for living systems. To falsify the supposition, one could demonstrate that such a closed loop evolving by chance and necessity is exceedingly implausible. One cannot, of course, entirely prove a negative — there is no means by which you can demonstrate that a given proposition is entirely impossible. But you can demonstrate that it is implausible enough such that the said supposition should be rejected — until, that is, the proponents of the theory provide evidence to the contrary.
Before turning to Lane’s suggested resolution to the problem, let’s examine what has just been said. We have just been told that specific proteins evolve by selection. Leaving aside other difficulties associated with the origin of protein folds, this only holds if the ratio of functional amino-acid sequences to gibberish sequences is sufficiently high. On the other hand, if this ratio is astronomically small, selection would forever be searching for the functional combination in the vast sea of combinatorial sequence space. But as Douglas Axe (and others) has pointed out, it seems that the latter is closer to the truth. If, as I maintain, the odds in obtaining an individual functional protein by chance and selection are astronomically small, what might the odds be of obtaining an assembly of mutually-interacting and mutually-dependent proteins evolving by chance and selection?
In an attempt to resolve the dilemma of the mutual dependancy of DNA and proteins, Lane appeals to the RNA-world hypothesis. He writes,
Then in the mid-1980s came the startling discovery that RNA acts as a catalyst. RNA rarely forms a double helix, instead forming smaller molecules with complex shapes that lend themselves to catalysis. And so RNA breaks the loop. In a hypothetical ‘RNA world’, it takes over the role of both proteins and DNA, catalyzing its own synthesis, along with many other reactions. Suddenly there was no need for the code to be all about DNA: it could have grown from the direct interaction of RNA with proteins. (p. 49)
Even conceding that such a system is plausible (and ignoring the lack of an explanation for the transition from an RNA-based system to a DNA-based system), the proposal still fails to account for the origin of the sequential arrangement of the chemical constituents of the RNA molecule. It is this feature which eludes explanation by non-intelligent means. Thus, Lane’s proposal should not be of concern to ID proponents, even if the RNA world proves a workable model. It still presupposes the availability of information.
As Stephen Meyer has comprehensively documented in his book, Signature in the Cell, the RNA-world hypothesis is fraught with problems, quite apart from those pertaining to the origin of information. For example, the formation of the first RNA molecule would have required the prior emergence of smaller constituent molecules, including ribose sugar, phosphate molecules, and the four RNA nucleotide bases. However, it turns out that both synthesizing and maintaining these essential RNA building blocks — especially ribose — and the nucleotide bases is a very difficult task under origin-of-life conditions.
There also exists the difficulty that ribozymes possess very few of the many functions performed by protein-based enzymes.
Moreover, there is another difficulty with the RNA-first model, as Lane himself acknowledges, and attempts to account for. Lane writes,
It’s hard enough to make individual RNA letters (nucleotides) but they will only join together in a polymer (a proper RNA molecule) if the nucleotides are present at high concentrations. If present in bulk, nucleotides condense spontaneously into long chains. But if the concentration is low, the opposite happens: RNA breaks down into its constituent nucleotides. The trouble is that every time an RNA replicates itself, it consumes nucleotides, so lowering their concentration. Unless the pool of nucleotides is replenished continuously, and faster than it is consumed, the RNA world could never work, for all its explanatory power. That would never do. So, for those who just wanted to get on with some productive science, it was best to take RNA as a given. (p. 52)
How does Lane attempt to resolve this difficulty? He continues:
They were right to do so for the answer was a long time in the coming, if ultimately emerging in dramatic fashion. It’s true that RNA doesn’t grow on trees, but it does grow in vents, or at least in simulated vents. In an important theoretical paper of 2007, indefatigable geochemist Mike Russell (whom we met in Chapter 1), working with Dieter Braun and his colleagues in Germany, reported that nucleotides should accumulate to extreme levels in vents. The reason relates to the strong thermal gradients that develop there. Recall from Chapter 1 that alkaline hydrothermal vents are riddled with interconnecting pores. Thermal gradients produce two types of current, which circulate through these pores, convection currents (as in a boiling kettle) and thermal diffusion (the dissipation of heat into cooler waters). Between them, these two thermal currents gradually silt up the lower pores with many small molecules, including nucleotides. In their simulated hydrothermal system, the concentration of nucleotides reached thousands and even millions of times the starting level. Such high levels should comfortably condense nucleotides into RNA or DNA chains. As the authors concluded, these conditions provide a ‘compelling high-concentration starting point for the molecular evolution of life’.
But that isn’t all the vents can do. Longer RNA or DNA molecules theoretically accumulate to even higher levels than single nucleotides: their greater size makes them more likely to silt up in the pores. DNA molecules composed of 100 base pairs are predicted to accumulate at fantastic levels, up to a million billion times the starting concentrations. Such high concentrations should in principle enable all the types of interaction we’ve been discussing, such as the binding of RNA molecules to each other, and so on. Even better, oscillating temperatures (thermal cycling) promotes RNA replication in the same way as the ubiquitous lab technique PCR (the polymerase chain reaction). In PCR, high temperatures unravel DNA, enabling it to act as a template, while condensing in cooler temperatures permits the complementary strand to polymerize. The outcome is an exponential rate of replication.
Taken together, thermal gradients should concentrate single nucleotides to extreme levels in vents, promoting the formation of RNA. Then these same gradients should concentrate RNA, fostering physical interactions between molecules. Finally the oscillating temperatures should promote RNA replication. It’s hard to imagine a better setting for the primordial RNA world.
However, as noted previously, problems abound for this hypothesized account. For one thing, at the boiling point of water, Adenine and Guanine possess a half life of 1 year. The half life of Uracil and Cytosine is 12 years and 19 days respectively. Remember that in hydrothermal vents the temperatures would be much higher than this.
But there is a further, and even more damning, problem with Lane’s proposed solution. If the origin of life took place in an aqueous solution of pre-biotic monomers (as Lane’s proposal maintains), then — according to Le Chateliers Principle — the presence of a reaction product will significantly decrease the reaction rate. Thus, it is not easy to envision the formation of an appreciable amount of polymers.
As ENV’s Casey Luskin observes here, polymerization reactions require an input of energy. However, heating or drying has to take place in such a way as to not wipe out the created polymers. Lane might argue that, in the setting of hydrothermal vents, the process of heating and drying is a repeated cycle. However, the problem is that all the water must be removed, but care must be taken not to over-heat — and thus rapidly break down — the synthesized polymers. Such would need to be a very delicate state of affairs and would seem to be without traction. Casey Luskin notes that “This would have to be a very fine balancing act that would also requires rapid input of organic material to overcome the rate at which the heat would destroy the molecules.”
Lane also attempts to resolve another difficulty confronting models which involve primordial RNA-based replicative molecules. He writes,
So what about our second question: how do we go from replicating RNAs, competing among themselves, to a more sophisticated system in which RNA begins to code for proteins? Again, vents may hold the answer.
Put RNA in a test tube, along with the raw materials and energy (as ATP) it needs, and it will replicate. In fact, it won’t just replicate, but as molecular biologist Sol Spiegalman and others discovered in the 1960s, it will evolve. Over test-tube generations, RNA gets faster and faster at replicating, finally becoming monstrously efficient. It becomes Spiegelman’s monster – a prolifically replicating strand of RNA, capable only of the most artificial and frenzied existence. Curiously, it doesn’t matter where the starting point is: you can start out with a whole virus or with an artificial length of RNA. You can even begin with a mixture of nucleotides and a polymerase to zip them up together. Wherever you start, there is always a tendency to home in on the same ‘monster’, the same frenetically replicated strand of RNA, barely fifty letters long, Spiegelman’s monster. It’s a molecular groundhog day. (p. 53-54)
Lane refers to Spiegelman’s demonstration of the ability of RNA (taken from a Bacteriophage Qβ) to replicate in a solution which contained the enzyme RNA replicase, some free nucleotides and some salts. Spiegelman found that shorter RNA chains were able to replicate at a faster rate, and hence the RNA became shorter and shorter, before eventually — after 74 generations — reaching 218 bases (the original strand possessed around 4,500 bases).
However, as David Swift has noted in his groundbreaking work, Evolution Under The Microscope,
…it takes a finite time to make a copy of RNA and, whatever the reaction time available, there will always be some RNA incompletely copied and transferred to the next reaction vessel as an incomplete copy. The shorter the reaction time is, the higher will be the proportion of incomplete to complete copies, and then no complete copies will be made. Also, because shorter strands will make take less time to replicate, in a given time more copies of these will be produced than of longer ones, so this will increase their proportion of the overall RNA as well. Consequently, it is inevitable that serial transfers will take less time to duplicate. In these experiments the RNA was reduced to about 500 nucleotides – and had lost its ability to code for the proteins. And this loss of useful genes is portrayed as evolution – as support for natural selection operating at the prebiotic, molecular, level to generate biologically relevant macromolecules! The significant point is, of course, that in these contrived experiments the RNA no longer has a biological function to maintain.
Another thing which needs to be remembered is that in this experiment the complete enzyme was provided, in addition to a supply of ribonucleotide triphosphates, and the reaction conditions are deliberately chosen to facilitate RNA synthesis. Moreover, the RNA replicase enzyme cannot cannot arise directly from the RNA it produces — rather, it requires the host cell’s translation machinery, including the full complement of ribosomes and tRNAs (along with their activating enzymes). The RNA does not even code for all of the replicase, but for just one of its four subunits.
Lane himself notes some of these problems:
The point is that Spiegelman’s monster does not become more complex. The reason it ends up as a stretch of fifty letters is that this is the binding sequence of the replicase enzyme, without which the strand could not replicate at all. Effectively, RNA can’t see past its own nose and is never going to generate complexity in a solution. So how and why did RNA begin to code for proteins, at the cost of its own replicative speed? The only way out of this loop is for selection to occur at a ‘higher level’, for RNA to become part of a larger entity, which is now the unit of selection, a cell for example. The trouble is that all organic cells are far too complex to just pop into existence without evolution, which is to say, there must be selection for the traits that make the cell, rather than selection for the speed of RNA replication. This is a chicken-and-egg situation just as ineluctable as the DNA-protein loop, albeit less celebrated. (p. 54)
Lane attempts a resolution to this dilemma as well. He continues,
We’ve seen that RNA breaks the DNA-protein loop beautifully; but what breaks the selection loop? The answer is staring us in the face; it’s the ready-made inorganic cells in hydrothermal vents. Such cells are about the same size as organic cells and are formed all the time in active vents. So, if the contents of a cell are especially good at regenerating the raw materials needed to replicate themselves, the cell begins to replicate itself, budding off into new inorganic cells. In contrast, ‘selfish’ RNAs, which replicate themselves as fast as possible, start to lose out, as they are unable to regenerate the raw materials needed to sustain their own replication.
One is justified in wondering how exactly this proposed solution succeeds in resolving the problem besides lamely proclaiming, “selection done it.” He offers us no detailed and testable account of how such an event could have taken place, nor how the information necessary to produce the first organic cell could have been produced.
Lane also takes a shot at explaining the origin of DNA biosynthesis. He writes,
,,,in a fluke of fortune bordering on the unbelievable, it might be that both the bacteria and archaea emerged from the very same hydrothermal mound. Little else could explain the fact that they share the same genetic code, as well as many details of protein synthesis, but apparently only learnt to replicate their DNA later on, totally independently. For while DNA and the genetic code certainly evolved only once, DNA replication – the physical mechanism of inheritance in all living cells – apparently evolved twice.
He cites the work of Eugene Koonin, which suggests that the process of DNA biosynthesis evolved not only once, but twice — emerging independently in both the archaea and in the eubacteria.
From detailed gene-sequence comparisons Koonin and his colleagues found that bacteria and archaea broadly share the same mechanisms of protein synthesis. For example, the way in which DNA is read off into RNA, and then RNA translated into proteins, is basically similar, with bacteria and archaea using enzymes that (from their gene sequences) are obviously inherited from a common ancestor. Yet this is far from the case for the enzymes needed for DNA replication. Most of them have nothing at all in common. This curious state of affairs could be explained just by their deep divergence, but then the question arises, why did the equally deep divergence of DNA transcription and translation not lead to such an utter dissimilarity? The simplest explanation is Koonin’s own radical supposition: DNA replication evolved twice, once in the archaea and once in the bacteria. (p. 55-56)
Such a conclusion, while perceived to be radical by some of Koonin’s detractors, does seem to be the most logical deduction from the observed evidence. But what are the implications for Darwinism? Darwinism would have us believe that two identical replication systems emerged independently in both the bacteria and the archaea — after these two evolutionary lineages supposedly diverged from the last universal common ancestor. But surely, if indeed evolutionary processes explain the origin of DNA replication (which is itself a dubious supposition), then two different systems of DNA biosynthesis should exist in the archaea and bacteria. But this is not the case.
The bottom line is that Nick Lane’s book, Life Ascending: The Ten Great Inventions of Evolution, as far as the origin of life is concerned, fails to account for the most fundamental property shared among all living organisms — information. Without a theory which accounts for the rise of this entity, Lane’s central thesis falls at the same hurdle as all other attempts to explain the origin of life with reference to undirected chemical interactions — the dual forces of chance and necessity. On the other hand, one cause — one type of cause — has been shown to be able to produce large volumes of information. Perhaps it is time to open the door of science to an alternative explanation — an explanation that accords with humanity’s sensory experience of the world; its cause-and-effect relationship. Perhaps it is time to follow the evidence wherever it ultimately leads, to a cause that has been staring us in the face ever since the elucidation of the structure and information-bearing properties of DNA and RNA in the 1950s — intelligent design.