Evolution and the Immune System

 

Sean D. Pitman M.D.

©September 2006

 

 

 

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Everyone has experienced sickness at one time or another in his or her life.  However, most people get better and often do not get that same "bug" again.  Why is this?  There are literally millions of "bugs" and other things in our everyday environment that can make us sick.  Why then do we generally remain so healthy?  The reason is because most of us have a highly effective immune system.  A healthy immune system is very good at searching out and killing foreign invaders that can make the body sick.  However, if the immune system is not functioning well, there will certainly be a lot of problems.  

As an example of this, consider the famous HIV virus (Human Immunodeficiency Virus).  This virus causes the disease known as AIDS (Acquired Immune Deficiency Syndrome).  A person with AIDS has a very weakened immune system.  Because of a lack of immunity, infections plague the AIDS victim that do not normally infect humans.  Interestingly enough, it is not the HIV virus itself that makes these people sick.  The HIV virus specifically attacks immune cells called T-helper cells (click on the video illustration - i.e., the black box).  When these cells are lost in high enough numbers, the immune system starts to shut down.  The symptoms of AIDS are the result of a loss of immunity.  With the loss of immunity, a host of infectious processes start to overwhelm the body.  Eventually, these infections kill their unfortunate host.  

Now that we understand just how important it is to recognize bad "bugs", how do our bodies become capable of recognizing the millions and billions and even trillions of different arrangements of things that can make us sick?  

Well, it is through a Darwinian-style selection process where the fittest survive and the weakest die.  In our bodies we have cells that are specialized immune cells called T-cells.  They go to "school" to learn the difference between "self" and "non-self".  Certainly one would not want his/her own immune system to attack his/her own body!  Sometimes this does happen and it is referred to as an autoimmune disease.  However, normally, the T-cells are educated in a very tough school so that they do not attack one's own body or "self".  But how exactly are they trained to recognize the difference between self and non-self? 

Well, T-cells are capable of being able to tell the difference between certain molecules (antigens) that are presented (by MHC class I molecules) on the surfaces of all "self" cells in the body that they are supposed to protect compared to all foreign or "abnormal" antigens that are associated with outside invaders or internal disease processes (like cancer). For example, when an outside invader, like a bacterium, enters the body, other cells (macrophages) may catch this invader and "eat" it.  The macrophage then presents small parts of the invader on its own surface in association with a certain molecule called MHC class II.  If a cell within the body gets "sick" or diseased (i.e., cancerous), certain molecules that are usually hidden from the immune system may be produced.  These are now presented on the surface of this sick cell in association with MHC class I molecules.  T-cells recognize these new molecules as "non-self" and kill the sick or diseased cell.  Once the T-lymphocyte recognizes an infected cell, it produces a set of new proteins that it places on the surface of the sick or diseased cell. Those proteins then bind to receptors on the infected cell called "death domain receptors" (including the Fas ligand and Trail receptors). This binding triggers a cascade of events in the infected cell that leads to cell suicide, called apoptosis.

T-cells sense or "feel" these antigen molecules with their own fairly tall Y-shaped molecules called T-cell receptors (like little hands on the ends of long arms). These T-cell receptors (TCRs) are analogous to wider Y-shaped antibody molecules (also known as "immunoglobulins") produce by B-cells (see illustrations below).  However, TCRs exist only in a membrane-bound form. They are able to carry out their particular function without the need to leave the cell surface.  Their receptors are used for the detection of foreign antigens, and do not directly mediate an effector response (except in the case of specialized "cytotoxic" T-cells).4

Those T-cells that do not recognize self-antigens as being part of the body are killed off before they get out of school (and this is a rather large majority of the "students" that enter this school).  It is a tough school indeed if the students do not learn their lessons!  Those cells that do recognize self-antigens as "self" graduate to go and search the body for non-self antigens to attack and eliminate. 

Each educated T-cell has only one type of receptor so only one specific antigen can be recognized.  But, how many possible antigens are there?  "The total number of possible epitopes is, therefore, 20B since there are 20 different amino acids."5  Well, the typical length of an antigen epitope ("B" in the preceding formula) is about 20 amino acid residues.5  So, the total number of possible antigen epitopes is about 2020 or  104,857,600,000,000,000,000,000,000 or ~100 trillion trillion. 

Since there are trillions of different possible antigen epitopes, how does one's immune system cope with such a variety of potential enemies?  Well, there are many immune cells produced by the body.  In humans, in particular, about 1012 lymphocytes are present at any given time.6

  Not all the T-cells have different Y-shaped receptors, but many of them do.  Chances are that if enough non-self enemies get into the body at least one of the immune cells will recognize the non-self marker sequences or "antigens" located on this invader as "foreign" to at least some useful degree.   The odds that a single T-cell will recognize a random epitope to at least some useful degree is about 1 in 1012.  So, does this mean it would take a trillion different T-cells to cover all possible invaders?  Well, no.  The reason is because an average cell or foreign invader "bug" has about 1012 different epitopes.  So, on average, a single T-cell will recognize at least one of the potential antigen epitopes of a foreign invader.

  When this happens this particular T-cell sounds the alarm that the body has been invaded.  Other immune cells, called B-cells, are also activated, but only those that specifically produce antibodies that have a pretty good match to the foreign antigen epitope expressed by the invading organism.   The invader, with its non-self antigens, is attacked.  However, if only a few immune cells recognize the invader upon initial exposure, the initial attack might be rather weak.  The  resulting sickness may linger on for some time before the body  can kill off the offending invader.  The good thing is that the immune system remembers this particular invader for the future so it can kill the invader more quickly if it ever sees its particular antigen marker again.  But how does this memory work?

The B-cell that recognized the foreign antigen clones itself to make many nearly identical copies of itself - with slight variations.  Now, there are many B-cells that will recognize this particular foreign antigen.  If infected again by an invader with this particular antigen, the immune system is ready and produces many more specific antibodies than before.  This kills the invader much more quickly - making the body "immune" to this particular bug. 

This is how vaccines work.  A vaccine presents the body with the antigens of either a dead or a weakened bug.  In this way the body can prepare to kill that particular bug without first having to go through the sickness that the bug may causes. 

 

 

Programmed Variability

 

Many people, including scientists, claim that this process is evolution in action.3,4,5  Is this actually true?  After all, this system does use survival of the fittest and a function-based selection process to create an incredible diversity of immune cells.  Is this not evolution in action?  In thinking about this question, remember that the immune system had no initial knowledge about all the evil antigens in the world or just which ones it might have to combat.  So, how did it get its gigantic arsenal of options? 

Well, the initial production of variety of T-cell receptors and B-cell produced antibodies is done by purely random mutation without any function-based selection.  However, subsequent refinements of immune system function are indeed based on both random mutations and function-based selection over several generations of B-cells.   

This may be a form of evolution in action, but it isn't quite what many evolutionists think it is.  Lets look into this process in a bit more detail.

 

 

Antibody Structure

 

Antibodies are proteins and so they are coded for by DNA. Antibodies are Y-shaped molecules with two different protein strands called heavy and light chains.  At the tips of the V-ends of the Y there are "variable regions" on both the light and heavy chains that can be different from cell to cell.  Also, within this variable region are half a dozen or so "hypervariable regions".  The rest of the antibody does not vary in its protein sequencing from other antibodies within the body.  Each one of the two chains (heavy and light) are coded for by specific sections of DNA.  Each section of DNA can code for part of the final antibody for that cell if it becomes an immune cell.  Even though there are many options for each section only one option will be chosen for a particular section.  This choice is determined by the random recombination of one option for one section with one option for each one of the other sections (see illustration).

 For light chains there are about 250 V-segments (or separate options in the original DNA), four J-segments, and three different ways that a V-segment can join to a J-segment when the DNA is spliced.  The final product for a light chain in DNA is one V-segment followed by a single J-segment.  This makes up the "variable region" of the light chain.  The constant region of DNA for the light chain follows this region.  The rest of the gene options are discarded for that cell. 

For the heavy chains, there are about 250 V-segments, 15 D-segments, and 5 J-segments - followed by the constant region.  Just like in the light chain DNA, only one option from each segment type is chosen for the final splicing of DNA so that just one V-option is followed by one D-option which is followed by one J-option.  This makes up the "variable region" of the heavy chain.  The constant region follows just like in the light chain. 

The large number of different options and their different possible combinations give rise to the huge variety of antibody possibilities.  This number can be roughly calculated as follows:  Light chains have 250 V-segments, 4 J-segments, and 3 possible joining frames.  This gives a total of 250 x 4 x 3 or 3000 different kinds of complete light chain possibilities.  Heavy chains have 250 V-segments, 15 D-segments, 5 J-segments, and 3 different joining frames.  This gives a total of 250 x 15 x 5 x 3 or 56,250 different kinds of complete heavy chain possibilities.  Combining the chains gives around 1.7 x 108 (~170 million) different possible antibody arrangements.  Adding in the various hypervariable differences within the variable regions gives around 1 x 1010 (~10 billion) different antibody specificities.1,2

     

 

 

Discussion

 

      Certainly, the potential for immune cell variety is great, but is the process that produces this variety really an example of the Darwinian-style evolution at work? 3  According to the theory of evolution all living things evolved from a single common ancestor over time.  The differences between the resulting life forms arose when random mutations happened upon some sort of new beneficial function that was beneficial to a particular life form in a particular environment or situation. More and more of these differences added up over time until it resulted in the vast diversity of living things that we see today.  That's the theory of evolution in a nut shell. That's how it is supposed to have worked.

       Now, in thinking about the immune system, is there a parallel with the theory of evolution?  What is evolving in the immune system?  The overall structure and function of the immune cells does not evolve over time and neither do the types of antibodies that are produced. All the major types of immune cells and antibodies are produced before any functional selection takes place.  Only after the T-cells are formed do they go to school to be "selected".  Also, this selection process only selects for a very limited ability - the ability to recognize and refrain from attacking self antigens.  This particular selection process is very specific and it does not change over time to produce anything new. So, the major differences in antibody specificity that are maintained were all made before any selection process took place.  As far as the immune system is concerned, the initial action of "selection" and survival of the fittest only narrows the field. It reduces the antibody diversity that was initially created before selection came along. 

        This is different from Darwinian-style evolution where natural selection is supposed to be able to create diversity. Selection, in the case of the immune system, does not expand or create more diversity - at least not in the initial steps of immune system education.  Perhaps, then, later steps in the function of the immune system show Darwinian-style evolution of truly novel functions?

 

 

Real Evolution

 

       As a review, remember that only a small fraction of the T-cells survive the first selection step.  When the body is exposed to a foreign invader with a specific antigenic marker sequence, T-cells that match that marker stimulate B-cells that also match to reproduce themselves - in a clonal fashion.  If just any immune cell was allowed to clone or reproduce itself, the immune system would not be nearly as effective.  However, mass reproduction of nearly identical copies of a B-cell that did in fact recognize a specific type of foreign invader, is very helpful in preventing future sickness by that particular invader should it ever invade the body again.  

        Interestingly though, once a particular B-cell is selected for mass replication, the offspring of that parent cell are not exactly the same.  The antibodies that are produced by the offspring B-cells are slightly different - usually in their "hypervariable regions".  These changes are indeed random changes that were not present in the original pool of immune system options. In other words, they are truly new sequences.  When the same foreign antigen is encountered again, those slightly different clones of the original B-cell that recognize the antigen better will be preferentially selected, over the siblings that do not have as close a match, to be cloned and produce the offspring of the next generation.   In this manner the specificity of immunity will indeed evolve in a stepwise truly Darwinian-style fashion of improvement over time. 

 

        "The B-cells expressing low affinity antibody on their surface become progressively less able to bind and be stimulated by antigen; in the environment of the germinal center, these poorly stimulated B cells are programmed to die by a specific process known as "apoptosis" (Choe et al, J Immunol 157:1006,1996). In contrast, the cells with high affinity antibody continue to bind antigen, and thus continue be stimulated to proliferate and secrete antibody. As the antigen concentration progressively falls while mutation and selection continue, the intensity of the selective pressure for high affinity increases. Repeated cycles of mutation and selection can lead to affinity levels 100-fold higher than that of the original unmutated antibody. The 'competition' for efficient antigen binding has been shown to be the selective force driving the rise in antibody affinity, since if antigen is repeatedly administered to prevent the drop in antigen level and thereby eliminate the selective pressure for efficient antigen binding, antibody affinity does not rise (Eisen and Siskind, Biochemistry 3:996, 1964). Furthermore, when selection pressure has been experimentally removed by engineering mice with impaired capacity for programmed death by apoptosis, many B cells are found that make mutated antibodies with low affinity (Takahashi et al. J Exp Med. 190:39, 1999).

        Late in the course of an immune response, as antigen becomes completely cleared from the bloodstream the amount of antibody secreted gradually falls and the immune response ends; but a subset of the last group of highly efficient cells persists as a quiescent population known as 'memory cells,' ready to respond with rapid secretion of high affinity antibody should they ever be triggered by another encounter with the same antigen in the future." 3

        

        So, basically what we have here is random mutation combined with function-based selection that makes improvements over time. By definition, this sounds an awful lot like real evolution in action, but there is just one little catch.  

 

 

One Little Catch

 

        Imagine a sequence space of all possible antibody specificities that an immune system can make. Such a space would contain literally billions upon billions, and probably even trillions of potential antibody specificities - - right? Now, from the perspective of a given antigen (actually an epitope or a small portion of an antigen), there would be a continuum of reactivity if it were brought in contact with each one of the potential antibodies in sequence space. The continuum would range from an extremely poor fit to an extremely good fit. Imagining this continuum as a line where, on every point of that line, there may be a number of antibodies that would match our particular antigen to exactly the same degree of selectability (i.e., they would activate the immune response to the same selectable degree). Although there may be a few equivalent antibody options at every point on our continuum, the odds are that the majority of potential antibodies are fairly evenly spread out over the entire continuum. 

        Given such a continuum as a true picture of reality, there are basically no significant neutral gaps (with regard to the function of immunity) to cross in the evolution of antibody specificity of a given antigen. In other words, the odds are therefore very high that a give change/recombination/mutation to an antibody sequence will actually be functionally different (either more or less binding affinity for a specific antigen epitope) compared to what came before. Since a high ratio of potential changes would be functionally different, evolution, even of highly specific sequences, will occur rapidly. This explains the relatively rapid refinement of antibody specificity when immune cells are repeatedly exposed to the same antigen. 

        Another way to look at it is to think of the foreign antigen as a pre-formed pattern, model, goal sequence, or type of template. The goal of creating random antibody sequences is to change sequences that already match the antigen template to see if random changes can keep what already matches and yet come up with additional matches to create an even better fit.  This system of evolution works because the antigen is limited to a certain number of potential characters at each position of its sequence, and the random antibody sequence generator is programmed to cover all of these possibilities at each possible sequence position.

 

 

Methinks it is Like a Weasel

 

        For example, say that the antigen target or "goal" reads like Dawkins's famous, "Methinks it is like a weasel" illustration. Starting with a bunch of random phrases (antibodies) and mutating them at random sequence positions in each "generation" of phrases, all that has to be done is to find out which one matches the goal phrase, "Methinks it is like a weasel" at the most positions and then use that "best" phrase to populate the next generation. Obviously, if the goal is already in place ahead of time, it is easy to evolve other phrases to match the goal phrase in short order using random changes and sequence-based comparison - as Dawkins's illustration clearly establishes. 

        Exactly the same thing happens with antibody evolution. It is already pre-established that certain molecules will be attracted to each other. If more of these molecules are lined up in the right places, there will be a stronger attraction. If the immune system is programmed to recognize stronger binding as "beneficial", stronger and stronger binding will quickly evolve with the random changes of the sequences of each subsequent generation. 

 

 

The Non-Beneficial Gap Problem

 

        Of course, the problem for evolutionists is clearly illustrated by Behe and many others in their devastating critique of Dawkins's "Methinks it is like a weasel" scenario. If all potentially beneficial types of functions could be built by matching sequences to other pre-established sequences, then Darwinian-style evolution of all types of functional systems would be a piece of cake. Of course, for most functions found in operation within living things, evolution is not thought to have worked like this at all. There simply is no pre-established sequence or "ideal" with which to compare the evolving sequence. For many types of complex functions, like bacterial motility for example, there simply is no pathway of step-by-step improvements for each and every single amino acid change/mutation. The forces of Darwinian-style evolution run into the Non-Beneficial Gap Problem when it comes to such higher-level functions.

        Consider the function of bacterial motility more closely for comparison. Bacterial motility will not be realized at all until a minimum number and specified arrangement of amino acids are entirely in place.  Before such assembly is realized, there is no motility and there is no pre-established model sequence available to guide the random changes via function-based selection to produce such an integrated system one single step or single character change at a time. Without such a model sequence acting as a function-based guide directing each change toward continual improvement, the system of function-based selection gets blinded pretty quickly.  The exponentially expanding gaps of neutral and detrimental sequences quickly separate the fewer and fewer potentially beneficial sequences at higher and higher levels of functional/meaningful complexity.

        It is the resulting random walk created by the huge ocean of functionally neutral and detrimental sequences in sequence space at higher levels of functional complexity that destroys the evolutionary mechanism of random mutation and natural selection. The random walk is made possible by the blindness of nature to functionally neutral sequence changes/mutations as well as nature's aversion to functionally detrimental changes. Because of this blindness to neutral differences and aversion to detrimental differences in different sequences, a seemingly small neutral/detrimental gap between potentially beneficial functions translates into a correspondingly enormous random walk, which grows exponentially in length (by a factor of 2) with each doubling of the average neutral gap. So, beyond the lowest levels of functional complexity evolution simply stalls out this side of a practical eternity of time (i.e., trillions upon trillions upon "zillions" of years of time).

 

 

Low Level Evolution

 

    So, we see that even though the immune system does undergo random mutation with function-based selection and survival of the fittest with improved fitness over time, this is not a very close parallel to Darwinian-style evolution when it comes to explaining the evolution of many systems of function that exist within all living things. Most of the great varieties within "kinds" in the animal and plant kingdoms can easily be explained by "preprogrammed" or inherent genetic abilities for variety (such as the phenomenon of genetic recombination as first described by Gregor Mendel).  There are certain limited situations were new functions can and do evolve without pre-established templates, such as in the cases of lactase and nylonase evolution as well as antibiotic resistance in bacteria, but these examples of evolution in action have clear boundaries that have never been crossed.  However, even with their limitations, the evolution of antibiotic resistance, lactase function, computer codes, and the like, are far better examples of evolution creating novel sequences than is the process of directed immune system variability which does nothing more "evolutionary" than evolve a string of characters to match another pre-established string of characters.  Such template-matching evolution just doesn't solve the problem for the larger Theory of Evolution.

 

 

  1. Stryer, Lubert. Biochemistry,  3rd ed., 1988.

  2. Janeway & Travis, Immunobiology, Garland Publishers, 4th ed. 2000.

  3. Max, Edward E., The Evolution of Improved Fitness by Random Mutation Plus Selection, The Talk.Origins Archive,  © 1999-2001 ( Link )

  4. Inlay, Matt, Evolving Immunity - A Response to Chapter 6 of Darwin's Black Box, The Talk.Origins Archive, July 17, 2002   ( Link )

  5. Jun Sun, David J. Earl, and Michael W. Deem, Glassy Dynamics in the Adaptive Immune Response Prevents Autoimmune Disease, Physical Review Letters, 95, 148104, September 30, 2005 (Link )

  6. Niels K. Jerne, The Generative Grammar of the Immune System, Nobel Lecture, 8 December 1984 ( Link )

 

 

. Home Page                                                                           . Truth, the Scientific Method, and Evolution   

. Methinks it is Like a Weasel                                                 . The Cat and the Hat - The Evolution of Code   

. Maquiziliducks - The Language of Evolution             . Defining Evolution    

. The God of the Gaps                                                           . Rube Goldberg Machines  

. Evolving the Irreducible                                                     . Gregor Mendel  

. Natural Selection                                                                  . Computer Evolution  

. The Chicken or the Egg                                                         . Antibiotic Resistance  

. The Immune System                                                            . Pseudogenes  

. Genetic Phylogeny                                                                . Fossils and DNA  

. DNA Mutation Rates                                                            . Donkeys, Horses, Mules and Evolution  

. The Fossil Record                                                                . The Geologic Column  

.  Early Man                                                                                . The Human Eye  

. Carbon 14 and Tree Ring Dating                                     . Radiometric Dating  

 . Amino Acid Racemization Dating                   . The Steppingstone Problem

.  Quotes from Scientists                                                           . Ancient Ice

 . Meaningful Information                                                          . The Flagellum

 . Harlen Bretz                                   . Milankovitch Cycles


 

 

 

 

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