Origin and Design of the Genetic Code: A One-Two Punch for Creation

00015

By Fazale Rana – October 23, 2019

So, in the spirit of the endless debates that take place on sports talk radio, I ask: What duo is the greatest one-two punch in NBA history? Is it:

  • Kareem and Magic?
  • Kobe and Shaq?
  • Michael and Scottie?

Another confession: I am a science-faith junkie. I never tire when it comes to engaging in discussions about the interplay between science and the Christian faith. From my perspective, the most interesting facet of this conversation centers around the scientific evidence for God’s existence.

So, toward this end, I ask: What is the most compelling biochemical evidence for God’s existence? Is it:

  • The complexity of biochemical systems?
  • The eerie similarity between biomolecular motors and machines designed by human engineers?
  • The information found in DNA?

Without hesitation I would say it is actually another feature: the origin and design of the genetic code.

The genetic code is a biochemical code that consists of a set of rules defining the information stored in DNA. These rules specify the sequence of amino acids used by the cell’s machinery to synthesize proteins. The genetic code makes it possible for the biochemical apparatus in the cell to convert the information formatted as nucleotide sequences in DNA into information formatted as amino acid sequences in proteins.

 

blog__inline--origin-and-design-of-the-genetic-code

Figure: A Depiction of the Genetic Code. Image credit: Shutterstock

In previous articles (see the Resources section), I discussed the code’s most salient feature that I think points to a Creator’s handiwork: it’s multidimensional optimization. That optimization is so extensive that evolutionary biologists struggle to account for it’s origin, as illustrated by the work of biologist Steven Massey1.

Both the optimization of the genetic code and the failure of evolutionary processes to account for its design form a potent one-two punch, evincing the work of a Creator. Optimization is a marker of design, and if it can’t be accounted for through evolutionary processes, the design must be authentic—the product of a Mind.

Can Evolutionary Processes Generate the Genetic Code?

For biochemists working to understand the origin of the genetic code, its extreme optimization means that it is not the “frozen accident” that Francis Crick proposed in a classic paper titled “On the Origin of the Genetic Code.”2

Many investigators now think that natural selection shaped the genetic code, producing its optimal properties. However, I question if natural selection could evolve a genetic code with the degree of optimality displayed in nature. In the Cell’s Design (published in 2008), I cite the work of the late biophysicist Hubert Yockey in support of my claim.3 Yockey determined that natural selection would have to explore 1.40 x 1070 different genetic codes to discover the universal genetic code found in nature. Yockey estimated 6.3 x 1015 seconds (200 million years) is the maximum time available for the code to originate. Natural selection would have to evaluate roughly 1055 codes per second to find the universal genetic code. And even if the search time was extended for the entire duration of the universe’s existence, it still would require searching through 1052 codes per second to find nature’s genetic code. Put simply, natural selection lacks the time to find the universal genetic code.

Researchers from Germany raised the same difficulty for evolution recently. Because of the genetic code’s multidimensional optimality, they concluded that “the optimality of the SGC [standard genetic code] is a robust feature and cannot be explained by any simple evolutionary hypothesis proposed so far. . . . the probability of finding the standard genetic code by chance is very low. Selection is not an omnipotent force, so this raises the question of whether a selection process could have found the SGC in the case of extreme code optimalities.”4

Two More Evolutionary Mechanisms Considered

Life scientist Massey reached a similar conclusion through a detailed analysis of two possible evolutionary mechanisms, both based on natural selection.9

If the genetic code evolved, then alternate genetic codes would have to have been generated and evaluated until the optimal genetic code found in nature was discovered. This process would require that coding assignments change. Biochemists have identified two mechanisms that could contribute to coding reassignments: (1) codon capture and (2) an ambiguous intermediate mechanism. Massey tested both mechanisms.

Massey discovered that neither mechanism can evolve the optimal genetic code. When he ran computer simulations of the evolutionary process using codon capture as a mechanism, they all ended in failure, unable to find a highly optimized genetic code. When Massey ran simulations with the ambiguous intermediate mechanism, he could evolve an optimized genetic code. But he didn’t view this result as success. He learned that it takes between 20 to 30 codon reassignments to produce a genetic code with the same degree of optimization as the genetic code found in nature.

The problem with this evolutionary mechanism is that the number of coding reassignments observed in nature is scarce based on the few deviants of the genetic code thought to have evolved since the origin of the last common ancestor. On top of this problem, the structure of the optimized codes that evolved via the ambiguous intermediate mechanism is different from the structure of the genetic code found in nature. In short, the result obtained via the ambiguous intermediate mechanism is unrealistic.

As Massey points out, “The evolution of the SGC remains to be deciphered, and constitutes one of the greatest challenges in the field of molecular evolution.”10

Making Sense of Explanatory Models

In the face of these discouraging results for the evolutionary paradigm, Massey concludes that perhaps another evolutionary force apart from natural selection shaped the genetic code. One idea Massey thinks has merit is the Coevolution Theory proposed by J. T. Wong. Wong argued that the genetic code evolved in conjunction with the evolution of biosynthetic pathways that produce amino acids. Yet, Wong’s theory doesn’t account for the extreme optimization of the genetic code in nature. And, in fact, the relationships between coding assignments and amino acid biosynthesis appear to result from a statistical artifact, and nothing more.11 In other words, Wong’s ideas don’t work.

That brings us back to the question of how to account for the genetic code’s optimization and design.

As I see it, in the same way that two NBA superstars work together to help produce a championship-caliber team, the genetic code’s optimization and the failure of every evolutionary model to account for it form a potent one-two punch that makes a case for a Creator.

And that is worth talking about.

Resources

Endnotes
  1. Steven E. Massey, “Searching of Code Space for an Error-Minimized Genetic Code via Codon Capture Leads to Failure, or Requires at Least 20 Improving Codon Reassignments via the Ambiguous Intermediate Mechanism,” Journal of Molecular Evolution 70, no. 1 (January 2010): 106–15, doi:10.1007/s00239-009-9313-7.
  2. F. H. C. Crick, “The Origin of the Genetic Code,” Journal of Molecular Biology 38, no. 3 (December 28, 1968): 367–79, doi:10.1016/0022-2836(68)90392-6.
  3. Hubert P. Yockey, Information Theory and Molecular Biology (Cambridge, UK: Cambridge University Press, 1992), 180–83.
  4. Stefan Wichmann and Zachary Ardern, “Optimality of the Standard Genetic Code Is Robust with Respect to Comparison Code Sets,” Biosystems 185 (November 2019): 104023, doi:10.1016/j.biosystems.2019.104023.
  5. Massey, “Searching of Code Space.”
  6. Massey, “Searching of Code Space.”
  7. Ramin Amirnovin, “An Analysis of the Metabolic Theory of the Origin of the Genetic Code,” Journal of Molecular Evolution 44, no. 5 (May 1997): 473–76, doi:10.1007//PL00006170.

Reprinted with permission by the author

Original article at:
https://www.reasons.org/explore/blogs/the-cells-design/read/the-cells-design/2018/11/21/vocal-signals-smile-on-the-case-for-human-exceptionalism

New Insights into Genetic Code Optimization Signal Creator’s Handiwork

00014

By Fazale Rana – October 16, 2019

I knew my career as a baseball player would be short-lived when, as a thirteen-year-old, I made the transition from Little League to the Babe Ruth League, which uses official Major League Baseball rules. Suddenly there were a whole lot more rules for me to follow than I ever had to think about in Little League.

Unlike in Little League, at the Babe Ruth level the hitter and base runners have to know what the other is going to do. Usually, the third-base coach is responsible for this communication. Before each pitch is thrown, the third-base coach uses a series of hand signs to relay instructions to the hitter and base runners.

blog__inline--new-insights-into-genetic-code

Credit: Shutterstock

My inability to pick up the signs from the third-base coach was a harbinger for my doomed baseball career. I did okay when I was on base, but I struggled to pick up his signs when I was at bat.

The issue wasn’t that there were too many signs for me to memorize. I struggled recognizing the indicator sign.

To prevent the opposing team from stealing the signs, it is common for the third-base coach to use an indicator sign. Each time he relays instructions, the coach randomly runs through a series of signs. At some point in the sequence, the coach gives the indicator sign. When he does that, it means that the next signal is the actual sign.

All of this activity was simply too much for me to process. When I was at the plate, I couldn’t consistently keep up with the third-base coach. It got so bad that a couple of times the third-base coach had to call time-out and have me walk up the third-base line, so he could whisper to me what I was to do when I was at the plate. It was a bit humiliating.

Codes Come from Intelligent Agents

The signs relayed by a third-base coach to the hitter and base runners are a type of code—a set of rules used to convert and convey information across formats.

Experience teaches us that it takes intelligent agents, such as baseball coaches, to devise codes, even those that are rather basic in their design. The more sophisticated a code, the greater the level of ingenuity required to develop it.

Perhaps the most sophisticated codes of all are those that can detect errors during data transmission.

I sure could have used a code like that when I played baseball. It would have helped me if the hand signals used by the third-base coach were designed in such a way that I could always understand what he wanted, even if I failed to properly pick up the indicator signal.

The Genetic Code

As it turns out, just such a code exists in nature. It is one of the most sophisticated codes known to us—far more sophisticated than the best codes designed by the brightest computer engineers in the world. In fact, this code resides at the heart of biochemical systems. It is the genetic code.

This biochemical code consists of a set of rules that define the information stored in DNA. These rules specify the sequence of amino acids that the cell’s machinery uses to build proteins. In this process, information formatted as nucleotide sequences in DNA is converted into information formatted as amino acid sequences in proteins.

Moreover, the genetic code is universal, meaning that all life on Earth uses it.1

Biochemists marvel at the design of the genetic code, in part because its structure displays exquisite optimization. This optimization includes the capacity to dramatically curtail errors that result from mutations.

Recently, a team from Germany identified another facet of the genetic code that is highly optimized, further highlighting its remarkable qualities.2

The Optimal Genetic Code

As I describe in The Cell’s Design, scientists from Princeton University and the University of Bath (UK) quantified the error-minimization capacity of the genetic code during the 1990s. Their work indicated that the universal genetic code is optimized to withstand the potentially harmful effects of substitution mutations better than virtually any other conceivable genetic code.3

In 2018, another team of researchers from Germany demonstrated that the universal genetic code is also optimized to withstand the harmful effects of frameshift mutations—again, better than other conceivable codes.4

In 2007, researchers from Israel showed that the genetic code is also optimized to harbor overlapping codes.5 This is important because, in addition to the genetic code, regions of DNA harbor other overlapping codes that direct the binding of histone proteins, transcription factors, and the machinery that splices genes after they have been transcribed.

The Robust Optimality of the Genetic Code

With these previous studies serving as a backdrop, the German research team wanted to probe more deeply into the genetic code’s optimality. These researchers focused on potential optimality of three properties of the genetic code: (1) resistance to harmful effects of substitution mutations, (2) resistance to harmful effects of frameshift mutations, and (3) capacity to support overlapping genes.

As with earlier studies, the team assessed the optimality of the naturally occurring genetic code by comparing its performance with sets of random codes that are conceivable alternatives. For all three property comparisons, they discovered that the natural (or standard) genetic code (SGC) displays a high degree of optimality. The researchers write, “We find that the SGC’s optimality is very robust, as no code set with no optimised properties is found. We therefore conclude that the optimality of the SGC is a robust feature across all evolutionary hypotheses.”6

On top of this insight, the research team adds one other dimension to multidimensional optimality of the genetic code: its capacity to support overlapping genes.

Interestingly, the researchers also note that the results of their work raise significant challenges to evolutionary explanations for the genetic code, pointing to the code’s multidimensional optimality that is extreme in all dimensions. They write:

We conclude that the optimality of the SGC is a robust feature and cannot be explained by any simple evolutionary hypothesis proposed so far. . . . the probability of finding the standard genetic code by chance is very low. Selection is not an omnipotent force, so this raises the question of whether a selection process could have found the SGC in the case of extreme code optimalities.7

While natural selection isn’t omnipotent, a transcendent Creator would be, and could account for the genetic code’s extreme optimality.

The Genetic Code and the Case for a Creator

In The Cell’s Design, I point out that our common experience teaches us that codes come from minds. It’s true on the baseball diamond and true in the computer lab. By analogy, the mere existence of the genetic code suggests that biochemical systems come from a Mind—a conclusion that gains additional support when we consider the code’s sophistication and exquisite optimization.

The genetic code’s ability to withstand errors that arise from substitution and frameshift mutations, along with its optimal capacity to harbor multiple overlapping codes and overlapping genes, seems to defy naturalistic explanation.

As a neophyte playing baseball, I could barely manage the simple code the third-base coach used. How mind-boggling it is for me when I think of the vastly superior ingenuity and sophistication of the universal genetic code.

And, just like the hitter and base runner work together to produce runs in baseball, the elegant design of the genetic code and the inability of evolutionary processes to account for its extreme multidimensional optimization combine to make the case that a Creator played a role in the origin and design of biochemical systems.

With respect to the case for a Creator, the insight from the German research team hits it out of the park.

Resources:

Endnotes
  1. Some organisms have a genetic code that deviates from the universal code in one or two of the coding assignments. Presumably, these deviant codes originate when the universal genetic code evolves, altering coding assignments.
  2. Stefan Wichmann and Zachery Ardern, “Optimality of the Standard Genetic Code Is Robust with Respect to Comparison Code Sets,” Biosystems 185 (November 2019): 104023, doi:10.1016/j.biosystems.2019.104023.
  3. David Haig and Laurence D. Hurst, “A Quantitative Measure of Error Minimization in the Genetic Code,” Journal of Molecular Evolution 33, no. 5 (November 1991): 412–17, doi:1007/BF02103132; Gretchen Vogel, “Tracking the History of the Genetic Code,” Science 281, no. 5375 (July 17, 1998): 329–31, doi:1126/science.281.5375.329; Stephen J. Freeland and Laurence D. Hurst, “The Genetic Code Is One in a Million,” Journal of Molecular Evolution 47, no. 3 (September 1998): 238–48, doi:10.1007/PL00006381; Stephen J. Freeland et al., “Early Fixation of an Optimal Genetic Code,” Molecular Biology and Evolution 17, no. 4 (April 2000): 511–18, 10.1093/oxfordjournals.molbev.a026331.
  4. Regine Geyer and Amir Madany Mamlouk, “On the Efficiency of the Genetic Code after Frameshift Mutations,” PeerJ 6 (May 21, 2018): e4825, doi:10.7717/peerj.4825.
  5. Shalev Itzkovitz and Uri Alon, “The Genetic Code Is Nearly Optimal for Allowing Additional Information within Protein-Coding Sequences,” Genome Research 17, no. 4 (April 2007): 405–12, doi:10.1101/gr.5987307.
  6. Wichmann and Ardern, “Optimality.”
  7. Wichmann and Ardern, “Optimality.”

Reprinted with permission by the author

Original article at:
https://www.reasons.org/explore/blogs/the-cells-design/read/the-cells-design/2018/11/21/vocal-signals-smile-on-the-case-for-human-exceptionalism

The Optimal Design of the Genetic Code

theoptimaldesign

BY FAZALE RANA – OCTOBER 3, 2018

Were there no example in the world of contrivance except that of the eye, it would be alone sufficient to support the conclusion which we draw from it, as to the necessity of an intelligent Creator.

–William Paley, Natural Theology

In his classic work, Natural TheologyWilliam Paley surveyed a range of biological systems, highlighting their similarities to human-made designs. Paley noticed that human designs typically consist of various components that interact in a precise way to accomplish a purpose. According to Paley, human designs are contrivances—things produced with skill and cleverness—and they come about via the work of human agents. They come about by the work of intelligent designers. And because biological systems are contrivances, they, too, must come about via the work of a Creator.

For Paley, the pervasiveness of biological contrivances made the case for a Creator compelling. But he was especially struck by the vertebrate eye. For Paley, if the only example of a biological contrivance available to us was the eye, its sophisticated design and elegant complexity alone justify the “necessity of an intelligent creator” to explain its origin.

As a biochemist, I am impressed with the elegant designs of biochemical systems. The sophistication and ingenuity of these designs convinced me as a graduate student that life must stem from the work of a Mind. In my book The Cell’s Design, I follow in Paley’s footsteps by highlighting the eerie similarity between human designs and biochemical systems—a similarity I describe as an intelligent design pattern. Because biochemical systems conform to the intelligent design pattern, they must be the work of a Creator.

As with Paley, I view the pervasiveness of the intelligent design pattern in biochemical systems as critical to making the case for a Creator. Yet, in particular, I am struck by the design of a single biochemical system: namely, the genetic code. On the basis of the structure of the genetic code alone, I think one is justified to conclude that life stems from the work of a Divine Mind. The latest work by a team of German biochemists on the genetic code’s design convinces me all the more that the genetic code is the product of a Creator’s handiwork.1

To understand the significance of this study and the code’s elegant design, a short primer on molecular biology is in order. (For those who have a background in biology, just skip ahead to The Optimal Genetic Code.)

Proteins

The “workhorse” molecules of life, proteins take part in essentially every cellular and extracellular structure and activity. Proteins are chain-like molecules folded into precise three-dimensional structures. Often, the protein’s three-dimensional architecture determines the way it interacts with other proteins to form a functional complex.

Proteins form when the cellular machinery links together (in a head-to-tail fashion) smaller subunit molecules called amino acids. To a first approximation, the cell employs 20 different amino acids to make proteins. The amino acids that make up proteins possess a variety of chemical and physical properties.

optimal-design-of-the-genetic-code-1

Figure 1: The Amino Acids. Image credit: Shutterstock

Each specific amino acid sequence imparts the protein with a unique chemical and physical profile along the length of its chain. The chemical and physical profile determines how the protein folds and, therefore, its function. Because structure determines the function of a protein, the amino acid sequence is key to dictating the type of work a protein performs for the cell.

DNA

The cell’s machinery uses the information harbored in the DNA molecule to make proteins. Like these biomolecules, DNA consists of chain-like structures known as polynucleotides. Two polynucleotide chains align in an antiparallel fashion to form a DNA molecule. (The two strands are arranged parallel to one another with the starting point of one strand located next to the ending point of the other strand, and vice versa.) The paired polynucleotide chains twist around each other to form the well-known DNA double helix. The cell’s machinery forms polynucleotide chains by linking together four different subunit molecules called nucleotides. The four nucleotides used to build DNA chains are adenosine, guanosine, cytidine, and thymidine, familiarly known as A, G, C, and T, respectively.

optimal-design-of-the-genetic-code-2

Figure 2: The Structure of DNA. Image credit: Shutterstock

As noted, DNA stores the information necessary to make all the proteins used by the cell. The sequence of nucleotides in the DNA strands specifies the sequence of amino acids in protein chains. Scientists refer to the amino-acid-coding nucleotide sequence that is used to construct proteins along the DNA strand as a gene.

The Genetic Code

A one-to-one relationship cannot exist between the 4 different nucleotides of DNA and the 20 different amino acids used to assemble polypeptides. The cell addresses this mismatch by using a code comprised of groupings of three nucleotides to specify the 20 different amino acids.

The cell uses a set of rules to relate these nucleotide triplet sequences to the 20 amino acids making up proteins. Molecular biologists refer to this set of rules as the genetic code. The nucleotide triplets, or “codons” as they are called, represent the fundamental communication units of the genetic code, which is essentially universal among all living organisms.

Sixty-four codons make up the genetic code. Because the code only needs to encode 20 amino acids, some of the codons are redundant. That is, different codons code for the same amino acid. In fact, up to six different codons specify some amino acids. Others are specified by only one codon.

Interestingly, some codons, called stop codons or nonsense codons, code no amino acids. (For example, the codon UGA is a stop codon.) These codons always occur at the end of the gene, informing the cell where the protein chain ends.

Some coding triplets, called start codons, play a dual role in the genetic code. These codons not only encode amino acids, but also “tell” the cell where a protein chain begins. For example, the codon GUG encodes the amino acid valine and also specifies the starting point of the proteins.

optimal-design-of-the-genetic-code-3

Figure 3: The Genetic Code. Image credit: Shutterstock

The Optimal Genetic Code

Based on visual inspection of the genetic code, biochemists had long suspected that the coding assignments weren’t haphazard—a frozen accident. Instead it looked to them like a rationale undergirds the genetic code’s architecture. This intuition was confirmed in the early 1990s. As I describe in The Cell’s Design, at that time, scientists from the University of Bath (UK) and from Princeton University quantified the error-minimization capacity of the genetic code. Their initial work indicated that the naturally occurring genetic code withstands the potentially harmful effects of substitution mutations better than all but 0.02 percent (1 out of 5,000) of randomly generated genetic codes with codon assignments different from the universal genetic code.2

Subsequent analysis performed later that decade incorporated additional factors. For example, some types of substitution mutations (called transitions) occur more frequently in nature than others (called transversions). As a case in point, an A-to-G substitution occurs more frequently than does either an A-to-C or an A-to-T mutation. When researchers included this factor into their analysis, they discovered that the naturally occurring genetic code performed better than one million randomly generated genetic codes. In a separate study, they also found that the genetic code in nature resides near the global optimum for all possible genetic codes with respect to its error-minimization capacity.3

It could be argued that the genetic code’s error-minimization properties are more dramatic than these results indicate. When researchers calculated the error-minimization capacity of one million randomly generated genetic codes, they discovered that the error-minimization values formed a distribution where the naturally occurring genetic code’s capacity occurred outside the distribution. Researchers estimate the existence of 1018 (a quintillion) possible genetic codes possessing the same type and degree of redundancy as the universal genetic code. Nearly all of these codes fall within the error-minimization distribution. This finding means that of 1018 possible genetic codes, only a few have an error-minimization capacity that approaches the code found universally in nature.

Frameshift Mutations

Recently, researchers from Germany wondered if this same type of optimization applies to frameshift mutations. Biochemists have discovered that these mutations are much more devastating than substitution mutations. Frameshift mutations result when nucleotides are inserted into or deleted from the DNA sequence of the gene. If the number of inserted/deleted nucleotides is not divisible by three, the added or deleted nucleotides cause a shift in the gene’s reading frame—altering the codon groupings. Frameshift mutations change all the original codons to new codons at the site of the insertion/deletion and onward to the end of the gene.

optimal-design-of-the-genetic-code-4

Figure 4: Types of Mutations. Image credit: Shutterstock

The Genetic Code Is Optimized to Withstand Frameshift Mutations

Like the researchers from the University of Bath, the German team generated 1 million random genetic codes with the same type and degree of redundancy as the genetic code found in nature. They discovered that the code found in nature is better optimized to withstand errors that result from frameshift mutations (involving either the insertion or deletion of 1 or 2 nucleotides) than most of the random genetic codes they tested.

The Genetic Code Is Optimized to Harbor Multiple Overlapping Codes

The optimization doesn’t end there. In addition to the genetic code, genes harbor other overlapping codes that independently direct the binding of histone proteins and transcription factors to DNA and dictate processes like messenger RNA folding and splicing. In 2007, researchers from Israel discovered that the genetic code is also optimized to harbor overlapping codes.4

The Genetic Code and the Case for a Creator

In The Cell’s Design, I point out that common experience teaches us that codes come from minds. By analogy, the mere existence of the genetic code suggests that biochemical systems come from a Mind. This conclusion gains considerable support based on the exquisite optimization of the genetic code to withstand errors that arise from both substitution and frameshift mutations, along with its optimal capacity to harbor multiple overlapping codes.

The triple optimization of the genetic code arises from its redundancy and the specific codon assignments. Over 1018 possible genetic codes exist and any one of them could have been “selected” for the code in nature. Yet, the “chosen” code displays extreme optimization—a hallmark feature of designed systems. As the evidence continues to mount, it becomes more and more evident that the genetic code displays an eerie perfection.5

An elegant contrivance such as the genetic code—which resides at the heart of biochemical systems and defines the information content in the cell—is truly one in a million when it comes to reasons to believe.

Resources

Endnotes

  1. Regine Geyer and Amir Madany Mamlouk, “On the Efficiency of the Genetic Code after Frameshift Mutations,” PeerJ 6 (2018): e4825, doi:10.7717/peerj.4825.
  2. David Haig and Laurence D. Hurst, “A Quantitative Measure of Error Minimization in the Genetic Code,” Journal of Molecular Evolution33 (1991): 412–17, doi:1007/BF02103132.
  3. Gretchen Vogel, “Tracking the History of the Genetic Code,” Science281 (1998): 329–31, doi:1126/science.281.5375.329; Stephen J. Freeland and Laurence D. Hurst, “The Genetic Code Is One in a Million,” Journal of Molecular Evolution 47 (1998): 238–48, doi:10.1007/PL00006381.; Stephen J. Freeland et al., “Early Fixation of an Optimal Genetic Code,” Molecular Biology and Evolution 17 (2000): 511–18, doi:10.1093/oxfordjournals.molbev.a026331.
  4. Shalev Itzkovitz and Uri Alon, “The Genetic Code Is Nearly Optimal for Allowing Additional Information within Protein-Coding Sequences,” Genome Research(2007): advanced online, doi:10.1101/gr.5987307.
  5. In The Cell’s Design, I explain why the genetic code cannot emerge through evolutionary processes, reinforcing the conclusion that the cell’s information systems—and hence, life—must stem from the handiwork of a Creator.
Reprinted with permission by the author
Original article at:
https://www.reasons.org/explore/blogs/the-cells-design/read/the-cells-design/2018/10/03/the-optimal-design-of-the-genetic-code

Mitochondria’s Deviant Genetic Code: Evolution or Creation?

mitochondriasdeviantgeneticcode

BY FAZALE RANA – APRIL 18, 2018

When I was in high school, I had the well-deserved reputation of being a wise guy—though the people who knew me then might have preferred to call me a wise—, instead. Either way, for being a wise guy, I sure didn’t display much wisdom during my teenage years.

I would like to think that I am wiser today. But, the little wisdom I do possess didn’t come easy. To quote singer and songwriter, Helen Reddy, “It’s wisdom born of pain.”

Life’s hardships sure have a way of teaching you lessons. But, I also learned that there is a shortcut to gaining wisdom—if you are wise enough to recognize it. (See what I did there?) It is better to solicit the advice of wise people than to gain wisdom through life’s bitter experiences. And, perhaps there was no wiser person ever than Solomon. Thankfully, Solomon’s wisdom was captured in the book of Proverbs. Many of life’s difficulties can be sidestepped if we are willing to heed Solomon’s advice.

Solomon gained his wisdom through observation and careful reflection. But, his wisdom also came through divine inspiration, and according to Solomon, it was through wisdom that God created the world in which we live (Proverbs 8:22–31). And, it is out of this wisdom that the Holy Spirit inspired Solomon to offer the insights found in the Proverbs.

In Psalm 104, the Psalmist (presumably David) echoes the same idea as Solomon: God created our world through wisdom. The Psalmist writes:

How many are your works, Lord!

In wisdom you made them all;

Based on Proverbs 8 and Psalm 104, I would expect God’s wisdom to be manifested in the created order. The Creator’s fingerprints—so evident in nature—should not only reflect the work of intelligent agency but also display undeniable wisdom. In my view, that wisdom should be reflected in the elegance, cleverness, and ingenuity of the designs seen throughout nature. Designs that reflect an underlying purpose. And these features are exactly what we observe when we study the biological realm—as demonstrated by recent work on aquatic mammal body size conducted by investigators from Stanford University.1

Body Sizes of Aquatic Mammals

Though the majority of the world’s mammals live in terrestrial habitats, the most massive members of this group reside in Earth’s oceans. For evolutionary biologists, common wisdom has it that the larger size of aquatic mammals reflects fewer evolutionary constraints on their body size because they live in the ocean. After all, the ocean habitat is more expansive than those found on land, and aquatic animals don’t need to support their weight because they are buoyed by the ocean.

As it turns out, common wisdom is wrong in this case. Through the use of mathematical modeling (employing body mass data from about 3,800 living species of aquatic mammals and around 3,000 fossil species), the research team from Stanford learned that living in an aquatic setting imposes tight constraints on body size, much more so than when animals live on land. In fact, they discovered (all things being equal) that the optimal body mass for aquatic mammals is around 1,000 pounds. Interestingly, the body mass distributions for members of the order Sirenia (dugongs and manatees), and the clades Cetacea (whales and dolphins), and Pinnipeds (sea lions and seals) cluster near 1,000 pounds.

Scientists have learned that the optimal body mass of aquatic mammals displays an underlying biological rationale and logic. It reflects a trade-off between two opposing demands: heat retention and caloric intake. Because the water temperatures of the oceans are below mammals’ body temperatures, heat retention becomes a real problem. Mammals with smaller bodies can’t consume enough food to compensate for heat loss to the oceans, and they don’t have the mass to retain body heat. The way around this problem is to increase their body mass. Larger bodies do a much better job at retaining heat than do smaller bodies. But, the increase in body mass can’t go unchecked. Maintaining a large body requires calories. At some point, metabolic demands outpace the capacity for aquatic mammals to feed, so body mass has to be capped (near 1,000 pounds).

The researchers noted a few exceptions to this newly discovered “rule.” Baleen whales have a body mass that is much greater than 1,000 pounds. But, as the researchers noted, these creatures employ a unique feeding mechanism that allows them to consume calories needed to support their massive body sizes. Filter feeding is a more efficient way to consume calories than hunting prey. The other exception is creatures such as otters. The researchers believe that their small size reflects a lifestyle that exploits both aquatic and terrestrial habitats.

Argument for God’s Existence from Wisdom

The discovery that the body mass of aquatic mammals has been optimized is one more example of the many elegant designs found in biological systems—designs worthy to be called the Creator’s handiwork. However, from my perspective, this optimization also reflects the Creator’s sagacity as he designed mammals for the purpose of living in the earth’s oceans.

But, instead of relying on intuition alone to make a case for a Creator, I want to present a formal argument for God’s existence based on the wisdom of biology’s designs. To make this argument, I follow after philosopher Richard Swinburne’s case for God’s existence based on beauty. Swinburne argues, “If God creates a universe, as a good workman he will create a beautiful universe. On the other hand, if the universe came into existence without being created by God, there is no reason to suppose that it would be a beautiful universe.”2 In other words, the beauty in the world around us signifies the Divine.

In like manner, if God created the universe, including the biological realm, we should expect to see wisdom permeating the designs in nature. On the other hand, if the universe came into being without God’s involvement, then there is no reason to think that the designs in nature would display a cleverness and ingenuity that affords a purpose—a sagacity, if you will. In fact, evolutionary biologists are quick to assert that most biological designs are flawed in some way. They argue that there is no purpose that undergirds biological systems. Why? Because evolutionary processes do not produce biological systems from scratch, but from preexisting systems that are co-opted through a process dubbed exaptation (by the late evolutionary biologist Stephen Jay Gould), and then modified by natural selection to produce new designs.3 According to biologist Ken Miller:

“Evolution . . . does not produce perfection. The fact that every intermediate stage in the development of an organ must confer a selective advantage means that the simplest and most elegant design for an organ cannot always be produced by evolution. In fact, the hallmark of evolution is the modification of pre-existing structures. An evolved organism, in short, should show the tell-tale signs of this modification.”4

And yet we see designs in biology that are not just optimized, but characterized by elegance, cleverness, and ingenuity—wisdom.

Truly, God is a wise guy.

Resources

Endnotes

  1. William Gearty, Craig R. McClain, and Jonathan L. Payne, “Energetic Tradeoffs Control the Size Distribution of Aquatic Mammals,” Proceedings of the National Academy of Sciences USA (March 2018): doi:10.1073/pnas.1712629115.
  2. Richard Swinburne, The Existence of God, 2nd ed. (New York: Oxford University Press, 2004), 190–91.
  3. Stephen Jay Gould and Elizabeth S. Vrba, “Exaptation: A Missing Term in the Science of Form,” Paleobiology8 (January 1, 1982): 4–15, doi:10.1017/S0094837300004310.
  4. Kenneth R. Miller, “Life’s Grand Design,” Technology Review 97 (February/March 1994): 24–32.
Reprinted with permission by the author
Original article at:
https://www.reasons.org/explore/blogs/the-cells-design/read/the-cells-design/2018/04/11/mitochondria-s-deviant-genetic-code-evolution-or-creation