New Reasons to Doubt Darwinism – Chicken-and-Egg Dilemmas and More | Amy Wang

dna-program

This is a WordPress repost of an outstanding article originally authored by Amy Wang. While it is acknowledged that this post is a tad on the lengthy side, please be assured that it is well worth the read.


Below, we will investigate the many challenges that proponents of intelligent design have raised for evolution.

Outline

  1. Fossil Evidence: Cambrian Explosion, Missing Links, No New Species
  2. Irreducible Complexity: Human Body Systems and Reproduction
  3. Chicken and Egg Dilemmas: Which Came First, DNA or Protein?
  4. DNA: More Information than Shakespeare and More Complexity than Microsoft Word
  5. First Cell: Challenges to Create the First Reproducing Cell Without Spontaneous Generation
  6. Probabilistic Challenges: Programming complexity, irreducible complexity, and vast improbabilities
  7. Responding to Objections: Vestigial organs, Junk DNA, and common use of DNA across organisms

1. Fossil Evidence: Cambrian Explosion, Missing Links, Loss of Species

a. The Challenge of the Cambrian Layer

The fossil record shows virtually every phyla appearing abruptly within a narrow period of geological time in the Cambrian layer. The relatively quick emergence of complex animals has been called the Cambrian Explosion. It challenges Darwin’s idea of gradual biological changes over a long period of time. (Even if we considered all the time of the universe, we still have a probabilistic challenge. See How to Calculate the Improbability of Evolution.)

b. The Lack of Innumerable Transitional Life Forms

Darwin was stumped by the lack of fossils for intermediate life forms. His book, Origin of Species (See ch. 9and 6), includes some of his doubts. Darwin hoped future findings would clarify the issue, but in recent times, the Burgess shale in the Canadian rockies have only confirmed this lack of transitional fossils. Furthermore, many proposed missing links, i.e., transitional fossils, turned out to be hoaxes, including Java man. To deal with these issues, Harvard University evolutionary theorist Stephen Jay Gould proposed the theory of “punctuated equilibria.” However, that theory still cannot explain how to overcome the additional issues which will be presented further below.

c. Losing, Not Gaining Species

With evolution, we might expect more species to be created over time. However, Hugh Ross writes that the fossil record suggests the creation of new species is finished. According to him, we are losing species, not gaining new species (Hugh Ross, The Fingerprint of God, 149). Since the Cambrian period, many species have become extinct (possibly 98% of all that ever existed is now extinct.) Later, in our comparison to programming software, we will investigate further why it is easier to lose biological functions than gain new ones and how some alleged cases of microevolution may actually be due to the loss of a function.

2. Irreducible Complexity

Michael Behe proposes the concept of “irreducibly complex” systems, where many complex parts all need to be in place simultaneously to achieve the required function; the removal of just one of these critical parts would make the whole nonfunctional. He provides examples such as the mechanical mouse trap, various human systems, and even bacterial flagellum. Evolution cannot easily explain how successive, slight modifications can result in complex systems in which “nothing works until everything works.”

a. Human Body Systems

Our complex human body systems (e.g., reproductive, circulatory, and nervous systems) might be considered irreducibly complex– they require many components to be in place at the same time to work properly. A student of mine pointed out, “What good is a circulatory system without a heart?” In a circulatory system, the heart, veins, arteries, and so forth, are all are extremely complex, and yet must all be in place to work and to enable survival. Prior to the completion of its evolution, how could the precursor animal even have survived? Similarly, the nervous system is highly complex, involving a brain, neurons, nerves, electrical and chemical signal mechanisms, and so forth. If only one of these many pieces is not working, the entire system may break down. Does it mean for many generations, animals survived with absolutely no cognition or means of making choices for survival? How could all the parts of each system come into being simultaneously? And if they did not arise simultaneously, how did these creatures survive beforehand, and how were the individual components separately favoured by natural selection, if there were no functional advantage until all pieces were in place?

b. The First Reproducing Male and Female Pair

Matching male and female reproductive machinery is another interesting challenge to explain for evolutionary theory. Howard Peth asked, “How could male and female sex organs that perfectly complement each other arise gradually, paralleling each other, yet remaining useless until completed?” The process of evolution is impossible without reproduction. How then can we get from asexual reproduction to sexual reproduction? The differences between male and female are not small. The probability of male and female both developing different reproductive organs of a highly complex nature, at the same time, and in a complementary fashion, seems highly improbable by chance. The successive small modifications of traditional Darwinian theory would probably not accomplish it. However, without reproduction, all evolutionary theories fall flat.

3. Chicken and Egg Dilemmas

Stephen C. Meyer has observed chicken-and-egg dilemmas in biological life. For example, how did DNA and protein arise? Their creation is interdependent. DNA does not self-reproduce on its own, but relies upon cell machinery composed of proteins. Protein synthesis, in turn, relies on DNA. This includes “transcription” of DNA to mRNA and “translation”, a process which builds sequences of amino acids based on mRNA information. These processes require mediation by a complex information-processing system involving many nucleic acids (mRNAs and tRNAs) and many specific enzymes (which are proteins). However, that machinery itself consists of at least 50 macromolecular components coded in DNA. Stephen C. Meyer says,

“The cell needs proteins to process and express the information in DNA in order to build proteins. But the construction of DNA molecules (during the process of DNA replication) also requires proteins so which came first, the chicken (nucleic acids) or the egg (proteins)” — Meyer, Signature in the Cell, pp133-134

Another chicken and egg problem is that proteins are involved in the production of proteins. Transcription and translation systems depend upon numerous proteins jointly needed for protein synthesis. The proteins that run the process are also made by this process. Hence, Lewontin asks, “What makes the proteins that are necessary to make the protein?” and David Goodsell asks “which came first, proteins or protein synthesis?”

4. DNA Information and Software Programming

Software Programming: Scientists like Francis Collins have likened DNA to a software program with a coding language of 4 letters and complex instructions, which direct a protein factory to create proteins (Collins, 102-104). This program is highly sophisticated, since it includes built-in-redundancy, error-minimization techniques, parity codes, tightly regulated feedback control systems like calcium homeostasis, nested coding, and functional logic and design patterns that remind us of operating systems (Ref and Ref 2). Frank Turek says that claiming our DNA does not have an intelligence behind it is like saying no programmer developed Microsoft Word, and yet the coding in our DNA is more complicated than Microsoft Word (Ref). Stephen C. Meyer tells the story of a former Microsoft software engineer who recognized a sophistication similar to that found in the design of computer design engineers:

He walks into my office one day, throws a book down on the table. It’s called Design Patterns —standard textbook for computer design engineers — and he says, ‘I get the eerie feeling, when I’m looking at what’s going on in the cell, that’s somebody’s figured this out before us.’ And I said ‘What do you mean?’ And he says, ‘Well, it’s the design patterns,’ and then he points to the book. . . . ‘We’ve got design logic for processing information, for doing error correction, for doing distributed data retrieval and reassembly, and for hierarchical organization — we’ve got files within folders, like on your desktop, you know, in the hierarchical filing system.’ And he says, ‘All those design patterns are inside the cell, except they’re using a design logic that’s like an 8.0, 9.0, 10.0 version of ours. It’s the same basic logic, but it’s more elegantly executed,’ and he says, ‘It gives me an eerie feeling'” (Meyer, 369)

Random changes to software programs likely to result in function loss: Programming complexity in life not only hints at design, but also presents a problem for evolution. Have you ever tried to randomly edit your software program? Without using your brain, it is perhaps more likely than not that your random changes would add in lethal bugs rather than useful functions. French mathematician M. P. Schützenberge found that random changes to computer programs are more likely than not to result in jams. Thus, with random changes, you are more likely to get the loss of a function than the gain of a new function.

Indeed, this might explain an example Collins provides of microevolution of the stickleback fish. He says in this case, the microevolution was not actually a result of the gain of a new function, but rather the loss of a function. A mutant gene resulted in the loss of a function, thus creating a different variety of the stickleback fish (Ref). This may also explain why scientists observe a trend where we are losing species rather than gaining new species.

Furthermore, Francis Crick found that evolution of the genetic code itself would be problematic because a change in codon assignment would change amino acids in every polypeptide produced by a cell, resulting in a lot of defective proteins. Very few changes would be anything but lethal (Ref 1Ref 2).

DNA Information and Probabilistic Concerns: DNA is similar to a language, with the nucleotides A, G, C, and T as its alphabet. Even if science can explain the mechanics of how these letters stick to the paper (in this case, the sugar-phosphate backbone), it is quite another thing to explain the origin of lengthy, complex, and meaningful sentences in DNA by chance alone. Stephen C. Meyer notes that there is no significant attraction between the individual letters themselves that might explain the natural origin of this information (Strobel, 235). If Carl Sagan admitted that a single message from outerspace would indicate intelligence there, should we not then see the information in DNA as a possible sign of intelligence? (Gungor, 109-110). Let us consider the purpose, length, and complexity of DNA:

  • Purpose: DNA sequences found in life are meaningful and purposeful, being able to to construct an amino acid in the right sequence. Just as not all combinations of letters form meaningful words, not all amino acid sequences can form a functional protein. At one point scientists thought that perhaps only 3 percent of the DNA sequence was actually useful and the rest was junk, but later studies suggest that as much as 80 percent of the genome may be functional (Ref).
  • Length: The amount of information found in DNA is staggering. Darwinist Richard Dawkins conceded that the cell nucleus of a tiny amoeba has more than thirty volumes of the Encyclopedia Britannica combined, the entire amoeba having as much information as 1,000 complete sets of the Encyclopedia Britannica (Geisler and Turek, 116). The longer a sequence of purposeful information, the more improbabilistic it becomes by chance.
  • Complexity: The information in DNA cannot be explained by repetitive sequences or self-organization alone (Strobel, 233). Unlike ice crystals, which Dr. Walter L. Bradley says have a simple and repetitive order, but little information content, the DNA of biological life has high information content.

The more complex, long, and purposeful the information is, the less plausible it is to have occurred by chance alone. See more information on probabilistic concerns and calculations further below.

5. The First Reproducing Cell

a. Spontaneous Generation Refuted

The Darwinian theory of Evolution (survival of the fittest) is useless without the first replicating/reproducing cell. But how do we get the first cell? How does non-life acquire life? (Geisler and Turek, 115, pp120-121)

In 1861, two years after Darwin’s publication of the 1st edition of On the Origin of Species, Louis Pasteur proved that non-living matter could not spawn life by itself, an idea known as spontaneous generation. However, that has not stopped scientists from trying to use naturalistic reasons to explain the first living cell.

Stanley Miller’s Experiment

In 1871, Darwin speculated that the right components “in some warm little pond” could have resulted in the chemical formation of a protein. However, all test tube attempts so far have failed to produce a DNA molecule by combining chemicals (Geisler and Turek, 118).

Most notably, Stanley Miller’s experiment in 1953 showed that organic compounds like amino acids could be created by a spark of light added to a set of gases. However, there are a couple challenges to the idea of producing a cell without design and intervention.

  • Amino acids are nitrogenous, but in 1985, Jim Brooks wrote that early organic matter had low nitrogen content (0.015%) (Strobel, 227).
  • The early atmosphere was not like that of Miller’s experiment. Miller assumed a hydrogen-rich mixture of methane, ammonia, and water vapor, but later scientists like Jonathan Wells believe that there was little hydrogen in the atmosphere because it would have escaped into space. Instead, it probably contained carbon dioxide, nitrogen, and water vapor (Strobel, 37).
  • Furthermore, Stephen Meyer tells us that without intervention in these experiments, undesirable by-products react with desirable building blocks resulting in inert compounds such as a tar called melanoidin (Meyer, 334). Wells said you would get formaldehyde and cyanide (Strobel, 38).
  • Another problem relates to the chirality (left or right-handedness) of the amino acids. Amino acids in proteins are all left-handed. Sugars in DNA and metabolic pathways are right-handed. Ordinary chemistry, however, produces a roughly 50/50 mixture of left-handed and right-handed molecules. It is a scientific challenge for science to explain homochirality. In a random situation, you would expect to see both types of molecules. (See Origin of Life: The Chirality Problem.)
  • Additionally, the nucleotide cytosine has a short half-life of only 19 days. RNA building blocks are hard to synthesize and easy to destroy, and it’s rare for RNA to have much self-replicating ability (Meyer, p 301, 302, 313).
  • Finally, leaping to a reproducing cell with DNA machinery, we still have the chicken-and-egg problems mentioned earlier.

Complexity of Single Cells

Many scientists, such as Robert Hazen, Michael Denton, Paul Davies, and Nobel Prize in Chemistry winner Ilya Prigogine, have acknowledged the extreme complexity of simple living cells or simple organisms like bacteria, noting for example, a multi-dimensional complexity (Robert Hazen) with “thousands of elegantly designed pieces of molecular machinery” (Dr. Michael Denton) (Denton, Evolution: A Theory in Crisis) .

Even if we did accept that organic compounds such as amino acids could be created under special conditions, it’s a long way from there to a reproducing cell, which is far more complex. Stephen C. Meyer says one single protein requires at least 75 amino acids to attain to a certain level of folding, called tertiary structure, needed to function. The right bonds are needed between amino acids, the amino acids must be of the left-handed version, and they must be linked in sequence. The probability for random formation of just one functional protein was estimated to be 1 in 10164. On top of this, a cell needs 300-500 proteins, and this has to be done in the time between the cooling of the Earth and the first microfossils, which is approximated at 100 million years (Strobel, 229). Michael Behe compared the probability of getting one protein molecule by chance to a blindfolded man finding a marked grain of sand in the Sahara desert three times in a row (Geisler and Turek, 125). Darwinist Richard Dawkins conceded that the cell nucleus of a tiny amoeba has more than thirty volumes of the Encyclopedia Britannica combined, the entire amoeba having as much information as 1,000 complete sets of the Encyclopedia Britannica (Geisler and Turek, 116).

Finally, information-rich DNA and proteins are needed for cell reproduction. Nobel Laureate Dr. Francois Jacob said, “It goes without saying that the emergence of this RNA and the transition to a DNA World implies an impressive number of stages, each more improbable than the previous one” (Jacob, Of Flies, Mice and Men, 21). Meyer tells us that scientists thought RNA World might solve some of the problems, but what sounds good in theory still has a number of practical problems (Meyer, 296-). However, starting with RNA rather than DNA does not make the problem of origins any simpler. The information from the RNA needs to be explained. The RNA strand has to have an identical molecule close by of the right length. This would require ten billion billion billion billion billion billion RNA molecules (Strobel, 231).

Finally, going a level above single cell organisms, we have even greater challenges of irreducible complexity when it comes to complex systems found in animals, and as mentioned before, the complementary evolution of male and female reproductive systems. It is unlikely that this would happen by chance alone.

6.Probabilistic Challenges

Irreducible complexity presents a challenge for probability. Atheists may say that time and chance can explain the creation of complexity in life. However, some types of design, such as irreducibly complex designs, cannot be explained by chance. A student of mine once shared the argument that shaking the pieces of a clock in a box will not make a clock in a million years. The same might be true with the pieces of a watch. If you took them apart and put them in a box and shook it, you probably wouldn’t get a watch in a million years. Besides materials and temperature, certain complex devices indicate careful organization and assembly.

Software programs present a problem for probability. When programming is involved, random changes are successive/additive and not independent lotteries. All it takes is one bug in a program to completely jam the program. It is difficult randomly to create new programming functions/features that work well by chance alone. That might explain why we are losing species faster than we are gaining new species, and why the new varieties we are seeing may be explained by the loss of functions rather than gain of functions.

DNA and Protein alone are a probabilistic challenge, let alone a single cell, or complex multicellular organism. The rise of lengthy, complex, and meaningful information in DNA by chance is one probabilistic challenge. The formation of a functional protein by chance is another probabilistic challenge (estimated to 1 in 10^164). Furthermore, these two have a chicken-and-egg interdependency. On top of this, we must advance from proteins to single-cell organisms, to sexually reproducing multi-cellular organisms with multiple complex systems and programming-like complexity. The time just to bring together 200,000 amino acids by chance for a single cell could take approximately 293.5 times the estimated age of the earth of 4.6 billion years. Hoyle compares this to the likelihood of a tornado blowing through a junkyard with the parts of the 747 to assemble them into a plane ready for takeoff (Paul E. Little, Know Why You Believe, p.23). For a sample probability calculation used to argue in favour of intelligent design, even given all the time since the beginning of the universe, see How to Calculate the Improbability of Evolution

7. Responding to Objections

What About Vestigial Organs and Junk DNA? If life arises from chance, where are all the failed attempts? A mathematician found that a trillion monkeys for a trillion years could type out the first paragraph of Hamlet by chance (Kreeft, The Philosophy of Thomas Aquinas, p.20). With this scenario, however, scientists would be looking for evidence of all the other billions of failed typing attempts. Junk DNA and vestigial organs were once used to explain the useless, but benign, changes that got propagated by evolution. However, the problem is that many of these proposals were later disproven when important functions were found. The coccyx(tailbone), the appendix, the thymus, and the thyroid were found to serve important functions (Groothuis, ch.13). Junk DNA was found to be useful for things such as gene regulation (Ref).

What About the Common Use of DNA Across Living Things? Evolution is not the only possible explanation for the common use of DNA across living things. The common use of DNA across living things could equally imply a designer who used the same building blocks and body plans in creating more than one organism. Even if living things are similar, because of their common use of DNA, it does not mean they evolved from one another. Stephen C. Meyer provides an analogy with cars. Although different models of cars have similar organizational plans with a motor, drive shaft, two axles, four wheels, etc, they do not evolve from one another, but simply have designers who share similar design principles. Furthermore, there are challenges with evolutionary trees based on computer analysis of DNA data have resulted in contradictory results, and have also contradicted other sources such as morphological analysis (based on shape and structure of organisms).

For Further Reading

 

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Disciple of Jesus, married to Peggy, with 5 grown up children, 6 grand children, ex-Canadian military and residing in beautiful Dartmouth, Nova Scotia, Canada. a.k.a. "Papa"

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Posted in Apologetics, Defending Christianity, Evolution, Intelligent Design
One comment on “New Reasons to Doubt Darwinism – Chicken-and-Egg Dilemmas and More | Amy Wang
  1. I’m going to bookmark this post, Bruce, and read it when I can give my full attention to it! Just skimming it, I can tell it is outstanding. But I want to go back and really absorb this! Thank you so much for posting it here and bringing it to our attention! I so appreciate all that you do here to keep us informed. God bless you greatly!

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