An Analysis of Michael Behe’s book, The Edge of Evolution
In his previous post, Ussery discussed his personal reasons for being interested in “The Edge of Evolution.” He went on to discuss two aspects of the book he appreciates, and he showed that he and Behe are in agreement that all living organisms have arisen through common descent from a single ancestral species.
In this post, however, Ussery says that Behe has presented a vastly over-simplified view of what scientists know about the origin of genetic diversity in the history of life. Here is his analysis based on Chapters Two and Three.
The accompanying figure illustrates the amount of genetic diversity in the bacterial world and beyond. It shows that even a single species of bacteria (E. coli) contains a vast reservoir of different genes. The term “orthologous” refers to genes in different species that clearly resemble one another and are thereby believed to have a common ancestry. Genes which are not orthologous are found in the species on the right side but not on the comparator species on the left.
Chapter 2 - Arms Race or Trench Warfare?
This chapter is about one of the classic examples of evolution: malaria and sickle cell anemia in humans. Behe observes (correctly, in my opinion) that the mutations that are responsible for helping some humans fight malaria are bad mutations. 'The first point is that the two examples he cites, sickle and Hemoglobin C (HbC), (two mutations that help the body resist malaria), are quintessentially hurtful mutations because they diminish the functioning of the human body. A second point is that “the mutations are not in the process of joining to build a more complex, interactive biochemical system.” (page 34).
Fair enough—and it is well known that harmful mutations, in the sense of wrecking something or making a pathway not work, occur much more frequently than beneficial mutations. However, Behe goes on to claim that there are “absolutely no studies' to document a molecular basis for the “coherent development of a single trait in a Darwinian arms race.” But this is highly erroneous. True, the example he gives us is not a “good mutation”—but to just blatantly claim that nothing has been done is showing his ignorance of the literature.
For example, consider this from the abstract of a recent review article, with the title “Origins, evolution, and phenotypic impact of new genes,” published in Genome Research. “The array of mechanisms underlying the origin of new genes is compelling, extending way beyond the traditionally well-studied source of gene duplication. Thus, it was shown that novel genes also regularly arose from messenger RNAs of ancestral genes, protein-coding genes metamorphosed into new RNA genes, genomic parasites were co-opted as new genes, and that both protein and RNA genes were composed from scratch (i.e., from previously non-functional sequences).” This is a new article, but many of the references in this article date to long before The Edge of Evolution was written, and some even date to before Darwin's Black Box was published, more than a decade ago.
Then there's another article about recent evolution of beneficial mutations in humans. There are many, many articles published on this sort of idea, and to claim that not a single study has been done is essentially a play on the ignorance of the readers! It is as if the hope is that the readers are ignorant of the scientific literature, and either too lazy or not competent to have a look through PubMed and see what is really out there.
Chapter 3 - The Mathematical Limits of Darwinism
One of my Ph.D. students was a mathematician, and I can still remember trying to read through his paper—lots of formulas—and sometimes they were difficult for me to understand. I have since learned that many people in math departments have a strong disliking for statisticians—I used to naively think that the two are the same. In this chapter, it looks as though Behe has confused mathematics (in the title) with statistics (what is actually discussed in the chapter). What's worse, the numbers he uses are based on bad assumptions, and are way off from what is known in the field by experimentalists doing current research in this area. Thus, unfortunately, his conclusions are not as strong as they might seem at first glance.
First, in calculating the odds of a single mutation in a protein, one has to take into account the chances of a mutation in the DNA sequence, because this is where mutations happen in biology—this is part of the 'central dogma' of molecular biology—that the information flows from DNA to RNA to protein, but not from proteins back to DNA. Thus, if a protein has a particular amino acid changed, this can be traced back to a change in the DNA sequence. Behe says ”resistance to chloroquine has appeared fewer than ten times in the whole world in the past century”—but what is meant by this shorthand is that we have documented evidence of this happening only a few times - that's not the same as knowing definitively that this HAS happened only those few times. Lots of things [like mutations leading to drug resistance] happen all the time that don't get seen and documented.
Then, based on this vastly over-simplified estimate, he suggests that the odds of a parasite developing resistance to chloroquine is one in 1020, whilst the odds of developing resistance to another drug (atovaquone) is one in 1012. Since the former, he says, involves two amino acid changes, while the latter involves on one, from these two numbers, it is concluded that the chance of having mutations which change two amino acids in a protein is a hundred million times lower (10-20 vs 10-12) than that for just getting one.
But this just simply does not make sense. Even within E. coli, the well known work-horse of molecular biology, take the order of amino acids in any one of its 5000 or so proteins, and compare that arrangement to that in otherE. coli strains and you will find LOTS of differences. For many proteins in E. coli, the level of identity between strains is around 80%—that is, about twenty out of every hundred amino acids are different—so to say that the odds for a double mutation (2 amino acid changes out of 100), is essentially impossible, when we observe 10 times that amount of diversity (20 differences for every 100 amino acids) in natural populations is speaking from ignorance. We see ten times the number of changes which Behe says is almost impossible all around us within a single species without even the need to generate new mutations.
I’ll discuss the vast differences found with various sequenced E. coli genomes later, but getting back to this chapter and the mutations in the two different spots within a single gene, Behe concludes:
On average, for humans to achieve a mutation like this by chance, we would need to wait a hundred million times ten million years. Since this is many times the age of the universe, it's reasonable to conclude the following: No mutation that is the same complexity of chloroquine resistance in malaria arose by Darwinian evolution in the line leading to humans in the past ten million years. (page 61, emphasis in the original).
But again, if one takes a deep breath, and looks at what is known, the mutational frequency that we can actually measure in humans is many times greater than that upon which Behe's assumptions are based. His argument is that the chances of getting useful mutations at two sites in the same gene are highly unlikely. But can we assess how likely mutations, which are likely to change the function of a gene, occur? One of the underlying assumptions of molecular biology is that sequence determines structure, and that this structure determines function. Hence, a major structural change is likely to have a different function. So how common are mutations that result in structural changes in proteins?
Surprisingly Common! One out of every 21 births in humans have some sort of STRUCTURAL change (and hence likely a functional change) in a protein, just from insertions from a single transposable element (alu), common in humans. It is already evident that Behe has a real problem with “random” mutations—but I think perhaps he is confusing ‘randomness’ with ‘purposelessness’.1 More about that in my next post.