Why I believe in Creation
Sean D. Pitman
Is God real? Is the Bible true? What about all those amazing stories in the Bible? Specifically, what about the Genesis stories? Did God really create the world and all that is in it in a literal week? Did that Creation occur only some 10,000 years ago? How could all these biblical accounts be true when so many brilliant scientists advocate otherwise?
Discovering a problem
Call me inquisitive or just plain annoying, but I came up with many such questions even as a young child. My parents did the very best they could to answer my questions. And, for a long time, they seemed to do a very good job. But, eventually there came a point in time when they just couldn’t answer my questions to my satisfaction. That’s OK, though. No one else could either.
I remember in 5th or 6th grade, thinking to myself that if small changes could happen over time, like slowly breeding a rose bush that produced red roses into a bush that could produce purple or even black roses, why couldn’t evolution be true? I asked my Dad about this and he assured me that although “microevolution,” like changing the color of a rose or the look of a dog, could happen, “macroevolution,” like changing a dog into a cat or a pig into a cow, could not happen. I asked him why such “macroevolution” couldn’t happen, given enough time? No one, not even my dad, seemed to be able to explain it to me.
I asked the same questions in grade school, high school, college, and even medical school and was given the same basic answers time and again. Finally, after finishing medical school I decided one day that I would search for myself to see if what I was reading in the Bible actually made sense in light of the seemingly reasonable theory of evolution.
Changing without changing
After few years of serious search, it dawned on me that things can change without really changing. I had known about this interesting phenomenon for some time, but had never tied it in with the notions of “micro” and “macro” evolution before. You see, a famous monk, by the name of Gregor Mendel (1822-1884), a contemporary of Charles Darwin (1809-1882), discovered something quite amazing while studying pea plants.1 Unfortunately, however, Mendel’s discovery remained pretty much unknown until well after Darwin’s theory of evolution became popular.
I’m sure even Darwin would have been quite amazed to learn that pretty much all of his most famous examples of evolution in action were the result of nothing more than Mendelian variation. But, what about all of those different finch beaks that Darwin wrote about? Well, they weren’t really the result of anything “new.” In other words, the beaks changed without any new genetic information coming into the gene pool. The pool of options stayed exactly the same. All the options for the different beak shapes were already there ahead of time—preprogrammed, so to speak. The same thing is true of many of the most significant differences between different breeds of dogs, cats, chickens, cows, fish, and so on. Every living thing that uses sexual reproduction has the ability to change individual reflections of the gene pool of that “kind” of creature without the gene pool itself changing.
So, now that I knew that change could happen without change happening I started thinking about what it might take to get the underlying gene pool to change.
Truly novel changes
The gene pool is basically a codebook with many different codes for many different types of functional systems used to build a living thing. If the spelling of the “words” in the codebook is changed or “mutated,” the function of that code or “word” may also be changed or even destroyed. Such functional changes are what I would call “real evolution”. And, they happen all the time. They really do. Evolution is a fact. But, it isn’t quite the fact that most modern scientists think it is.
Consider the following word sequence: cat to hat to bat to bad to dad to did to dig to dog. That’s an evolutionary sequence. By changing just one letter at a time we were able to “evolve” from cat to dog along a pathway were each step was meaningful and potentially beneficial in the English language system. Easy, right? But why is it so easy to do this?
As it turns out, every language system in the world has a higher concentration of defined or meaningful sequences when the sequences are shorter as compared to longer words, phrases, sentences, paragraphs and so on. Just as an example, the English language system has about 676 potential 2-letter sequences. Of these, about 100 are defined as meaningful, creating a ratio of meaningful to meaningless to about 1 in 7. Now, there are almost three times as many meaningful 3-letter words and phrases, around 980 of them, but 26 times the number of potential 3-letter sequences (17,576 of them) resulting in a significantly reduced ratio of meaningful vs. meaningless of about 1 in 18. The ratio for 7-letter words and phrases drops precipitously to about 1 in 250,000.
The pattern is obvious and is essentially the same for every language. With each increase in the minimum sequence length of any coded message in any language system, to include computer codes and languages, the isolation of that message from other potentially meaningful as well as beneficial messages increases exponentially.
So, what happens then when mindless evolutionary forces try to achieve a higher level of informational complexity? What happens when a sequence code steps off its beneficial island into the ocean of meaningless sequences?
The blind leading the blind
The problem is that natural selection is supposed to be the guiding force for evolutionary change. Yet, natural selection, as a very real force, can only see genetic spelling changes that result in meaningful changes in the sequence code. Nature cannot see actual spelling changes/genetic mutations. It can only recognize the differences in function that may or may not result.
For example, what’s the difference between the sequences “quiziligook” and “quiziliguck”? They are both equally meaningless sequences. Right? Therefore, changing from one to the other would not be detectable by a selection system like natural selection. However, what about the meaningful difference between “vacation” and “vocation”? They are only one letter different, but mean very different things. A function-based system of selection would easily be able to select between these two sequences. Right? Now, what about going from “vacation” to “vucation”? That would also result in a detectable change in meaning since the meaning of vacation is lost if mutated to vucation. That loss of meaning might be selectable as either beneficial or detrimental.
Note, however, that destroying something is always easier than creating something new because there are so many ways to destroy versus the relatively few ways there are to create. For example, there are many ways to mess up the function of the word vacation, but relatively few ways to find a new meaningful sequence of equivalent length. Logically then, it would be very easy for a gene pool to get rid of a pre-established function, but relatively hard for it to gain a new type of function.
Real life examples of evolution in action
Well, this is all fine and good on paper, but what about real life? I’ve looked into it in some detail now and it seems as though evolution works the very same way as I’ve just described for language sequence evolution. It is capable of “micro” changes but not “macro” changes because of what I like to call the “Neutral Gap Problem.” At very low levels of informational complexity, evolution works just fine. However, as one starts moving up the ladder of informational complexity, evolution starts stalling out in an exponential manner until, for functions requiring a minimum of more than a few hundred fairly specified characters, evolution simply cannot work this side of trillions upon trillions of years of average time. It just wanders around blindly and aimlessly forever at such levels of complexity.
For instance, consider bacterial antibiotic resistance as a famous example of evolution in action. Functional mutations in the underlying gene pool are actually responsible for the resistance of bacteria to the effects of this or that antibiotic. That’s real evolution in my book.
Of course, many forms of antibiotic resistance occur at the very lowest levels of functional complexity. In fact, most forms of antibiotic resistance are the result of a disruption of a pre-established interaction of the antibiotic with a specific target within the bacteria. All that has to change is one or two characters in the target sequence and the antibiotic will no longer bind to the target. And, voila, the function of antibiotic resistance is evolved—just like that. It’s quick and easy in real life because there are so many ways to disrupt the antibiotic-target interaction. That’s why antibiotic evolution is such a problem in hospitals today. It happens so quickly and easily in just about every bacterial population when presented with just about any antibiotic.2
But, what happens when we move up a level? What happens when we try to evolve a novel function that is not based on the destruction of a pre-established function or interaction?
Interestingly enough, there are quite a number of examples of this sort of evolution in real life. Some of these examples involve the evolution of new protein sequences with truly novel protein functions. These proteins are made up of strings of “amino acid residues” that are very much like sequences of letters in human language systems. Different sequences and shapes translate into different functions, as in any language system. But, just like in any language system, not every potential sequence or shape has a meaningful, much less beneficial function. However, for functions requiring only short protein sequences, the density of potentially beneficial sequences in sequence space is high enough (as discussed above for 3-letter words) that evolution can and does happen at this level of functional complexity in relatively short order given the proper environment.
A striking example of protein evolution can be found in Barry Hall’s work with E. coli bacteria. What Hall did was delete the genetic codes or “genes” that produce a lactase enzyme in E. coli. This enzyme digests the sugar lactose into the sugars glucose and galactose, which are then used to provide energy for the bacterium. Hall did this to see if these mutant bacteria would evolve a new gene to produce a new lactase enzyme to replace the one that was lost when placed in a lactose-rich environment. Sure enough, the bacteria quickly evolved a brand new enzyme that did not have the lactose function before. Somehow, it just so happened to be one point mutation away from a functional lactose code in sequence space.3
Amazing! Of course, this is where most descriptions of Hall’s experiments end, such as the one listed in Kenneth Miller’s popular book, Finding Darwin’s God.4 However, what happened next is most interesting. Hall deleted the newly evolved gene as well to see if any other gene would evolve…and nothing happened! Despite tens of thousands of generations of observation, these unfortunate double mutant bacteria never evolved a sequence with the very beneficial lactose function. Frustrated, Hall described these double mutant bacteria as having, “limited evolutionary potential.” So, what is it, exactly, that “limited” the “evolutionary potential” of Hall’s bacteria?
As it turns out, the apparent minimum sequence length needed for the most basic lactase enzyme is around 400 amino acid residues. With 20 different residue options, the total number of potential sequences is a staggering 20400. Certainly, there may be many useable lactase sequences within that huge sequence space, but no doubt the large majority of these sequences are not usable lactases or else Hall’s mutant bacteria would have found many of them in short order using a simple blind random walk. The fact that Hall’s double-mutant bacteria failed is very good evidence that the ratio of lactases versus non-lactases in minimum sequence space, at this level of function complexity, is quite low. Nature simply could not sort through all the junk sequences fast enough to find another lactase sequence even given tens of thousands of generations of time.
The outer limits of evolutionary potential
Beyond this level of complexity, nothing evolves. There simply is no real life example of any novel function evolving that requires more than a thousand or so amino acid “parts” working together in a fairly specified order. Yet, there are many systems of function, even in supposedly “simple” life forms, like bacteria, that will not work at all without a large highly specified minimum amount of genetic real estate in place. Take bacterial motility, for example. The flagellar system of motility requires at least 10,000 fairly specified amino acid residues, working in a fairly specific order, or the function of flagellar motility simply won’t work at all.5 Such a high-level function has never been shown to evolve in the lab or anywhere else.
The signature of God
So, microevolution happens, but macroevolution doesn’t. The reason for this seems so simple—exponentially expanding neutral gaps. Quite simple, really—even “elementary,” as Sherlock Holmes might say. But, what a big difference this understanding has made in my faith and respect for God as the Creator whose obvious signature and continued interest and care are written all over the world around and within each one of us. Of course, I’ve found a great many other overwhelming evidences to believe in God and in His word, the Bible, but finding the neutral gap problem is certainly one of the highlights.
Sean Pitman (M.D., Loma Linda University School of Medicine) is a pathologist and current fellow in the hematology program at the City of Hope National Medical Center. For further information and references about the neutral gap problem and many other topics concerning the theories of evolution and intelligent design, see his website at: www.DetectingDesign.com
His email: Seanpit@gmail.com.
1. Gregor Mendel, Experiments in Plant Hybridization, 1865.
2. Sean Pitman, “Antibiotic Resistance” ( http://www.detectingdesign.com/antibioticresistance.html), December, 2004.
3. Barry G. Hall, “Evolution on a petri dish: The evolved b-galactosidase system as a model for studying acquisitive evolution in the laboratory,” Evolutionary Biology 15 (1982):85-150.
4. Kenneth Miller, Finding Darwin’s God (New York: Harper Collins, 1999).
5. BLAST Search: http://www.ncbi.nlm.nih.gov/BLAST.