“Waste not, want not.”

Maria Edgeworth, The Parent’s Assistant, 1796

It is rare to hear this bit of sound advice today, given we live in a throwaway society. But growing up, I often witnessed my parents living by this adage.

My mom’s parents lived through the Great Depression so she learned never to throw things away that might be useful later. My father’s family lost everything they had as a result of the Partition of India (when India won its independence from Great Britain in 1947). As a result of that experience, my father became extremely frugal.

Conserving goods and energy makes sense. If we don’t needlessly waste things during times of abundance, then we are less likely to be without them when things are sparse.

As it turns out, researchers have discovered that the design of the genetic code evinces a biochemical version of the “waste not, want not” principle.¹ Investigators from Israel have learned that the genetic code is optimized for resource conservation. This optimization is vital, contributing to life’s ability to persist during times when carbon- and nitrogen-containing resources in the environment become depleted.

The Importance of Resource Conservation
Carbon and nitrogen hold immense value for living organisms, serving as two of life’s key raw materials. In fact, ecologists regard the carbon and nitrogen levels in an ecosystem as limiting factors. In other words, the amount of available carbon and nitrogen in the environment controls an ecosystem’s biomass (amount of living matter). When the levels of nutrients containing these two elements are low, the ecosystem can’t sustain the number of organisms that it can when the levels of carbon- and nitrogen-containing nutrients are high.

Life-forms use carbon and nitrogen atoms to assemble the building block materials that, in turn, are used to construct important biomolecules such as proteins, the nucleic acids (DNA and RNA), and cell membrane components such as phospholipids. Additionally, organisms use carbon-containing compounds as a source of energy to power their operations.

Not all biomolecules are created equal. Some require more carbon and nitrogen atoms to assemble than others. Consider proteins. These biomolecules are built from amino acids that have been linked together in a chain-like manner by the cell’s biosynthetic machinery. As a general rule, the cell’s machinery uses twenty chemically and physically distinct amino acids to build proteins. The assembly of each of these amino acids requires differing amounts of carbon and nitrogen atoms, with some necessitating more carbon atoms or, conversely, more nitrogen atoms than others.

Biochemists have learned that the composition of biomolecules is influenced by nutrient availability. Organisms that live in low-carbon environments tend to have proteins that are predominantly made up of amino acids that are relatively rich in nitrogen. However, organisms that reside in a low-nitrogen environment possess proteins that are relatively low in nitrogen-rich amino acids.

Biochemists have also observed that the composition of an organism’s genome reflects the availability of nutrients in the environment. The DNA that makes up an organism’s genome consists of linear chains of nucleotides. The cell’s biosynthetic apparatus assembles DNA from four nucleotides: adenosine, guanosine, cytidine, and thymidine (abbreviated A, G, C, and T, respectively).

Organisms that live in low-carbon environments have genomes made up of a higher guanosine and cytidine (G+C) content, both of which have a higher ratio of nitrogen to carbon atoms in their molecular makeup. Conversely, organisms that reside in a low-nitrogen environment have genomes made up of a higher fraction of adenosine and thymidine (A+T), both of which have a higher ratio of carbon to nitrogen in their molecular compositions.

Resource-Driven Selection
Given the critical and limiting role carbon and nitrogen play in ecosystems, it isn’t surprising that the Israeli scientists discovered that nutrient availability serves as a driver for purifying selection.

In a nutshell, purifying selection refers to a type of natural selection in which harmful mutations are eliminated from the genomes because they render the organism less fit for the environment. The research team coined the term “resource-driven selection” to describe situations in which nutrient availability provides the dominant contribution to purifying selection.

This process shapes the nucleotide sequences of an organism’s genes so that the genes encode proteins made up of either nitrogen-rich or nitrogen-lean amino acids, depending on the availability of nitrogen in the environment. Along these lines, they discovered that in nitrogen-depleted environments, any mutation that causes an amino acid change in a protein’s primary structure will be “selected against” if the replacement amino acid contains more nitrogen atoms than its predecessor.

The research team also discovered that genes expressed at high levels tended to experience purifying selection to a much greater extent than genes expressed at low levels. This observation makes sense if resource-driven selection is at work.

As part of their investigation, the researchers suspected that the structure of the genetic code, which influences mutational changes, plays a role in resource conservation. Previous research carried out by other investigators has demonstrated that the structure of the genetic code buffers against the harmful effects of single-point and framework mutations. (See the Resources section for articles describing this earlier work.) Based on these earlier studies, the scientists wondered if the structure of the genetic code would also buffer against mutations that would add to the organism’s resource demands.

To fully appreciate their findings and why they pursued this line of inquiry, it is important to have a basic understanding of the genetic code. (For readers who have this understanding, feel free to skip ahead to The Impact of the Genetic Code’s Redundancy on the Effects of Mutations.)

The Genetic Code
The genetic code is a biochemical code comprised of a set of rules that define 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.

Nucleotide triplets or codons represent the fundamental communication units of the genetic code. In other words, the genetic code uses combinations of three nucleotides to signify a particular amino acid in the amino acid sequences used to build proteins.

Sixty-four codons make up the genetic code. Because the genetic 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.

Mutations
A mutation refers to any change that takes place in the DNA nucleotide sequence. DNA can experience several different types of mutations. Substitution mutations are one common type. In a substitution mutation, one or more of the nucleotides in the DNA strand is replaced by another nucleotide. For example, an A may be replaced by a G, or a C may be replaced by a T.

This type of substitution changes the codon which is impacted by the mutation. As a consequence, the amino acid specified by that codon may change, leading to an altered chemical and physical profile along the protein chain. If the substituted amino acid possesses dramatically different physicochemical properties from the native amino acid, it can cause the protein to fold improperly. This improper folding can yield a protein with reduced or even lost function. Many mutations harm cellular health because they significantly and negatively impact protein structure and function.

The Impact of the Genetic Code’s Redundancy on the Effects of Mutations
Biochemists have discovered that the redundancy in the genetic code allows the cell to avoid the harmful effects of substitution mutations. For example, six codons encode the amino acid leucine (Leu). If at a particular amino acid position in a protein Leu is encoded by 5′ CUU, substitution mutations in the 3′ position from U to C, A, or G produce three new codons, 5′ CUC, 5′ CUA, and 5′ CUG, all of which code for Leu. In other words, this mutation does not change the amino acid sequence of the protein chain and, hence, its structure and function. For this scenario, the cell successfully avoids the negative effects of a substitution mutation.

Likewise, a change of C in the 5′ position to a U generates a new codon, 5′ UUU, that specifies phenylalanine, an amino acid with similar physical and chemical properties to Leu. A change of C to an A or to a G produces codons that code for isoleucine and valine, respectively. These two amino acids also possess chemical and physical properties similar to leucine. It becomes apparent through visual inspection alone that the genetic code appears to be constructed to minimize errors that result from substitution mutations.

The Optimal Genetic Code
As I describe in The Cell’s Design and in articles listed in the Resource section, biochemists have demonstrated that the universal genetic code appears better optimized to withstand the potentially harmful effects of substitution and frameshift mutations than a vast number of other conceivable codes.

Additionally, biochemists have learned that the genetic code’s optimization extends beyond minimizing the effects of mutations. It also displays an optimality that includes its capacity to support overlapping genes and its capacity to harbor overlapping codes. This second feature is vital because in addition to the genetic code, regions of DNA harbor additional overlapping codes that direct the binding of histone proteins, transcription factors, and the machinery that splices genes after they have been transcribed.

The Genetic Code Is Optimized for Resource Conservation
The researchers from Israel added to this impressive list of optimized properties by demonstrating that the genetic code has also been optimized to minimize the excess resource cost that results when one amino acid is replaced with another as a result of a substitution mutation.

Toward this end, the team developed parameters that measure the cost of substituting one amino acid for another based on the number of additional carbon and nitrogen atoms the new amino acid contains compared to the original one. For example, the change of the codon 5′ CCA (which specifies proline) to 5′ CGA (which specifies arginine) results in an amino acid with 1 additional carbon and 3 additional nitrogen atoms for an N cost of 3 and a C cost of 1.

Using this set of parameters, they calculated that the expected random mutation cost for the genetic code found in nature is 0.44 for carbon, 0.16 for nitrogen, and 0.16 for oxygen.

When researchers compared these parameters for the naturally occurring genetic code with 1 million randomly generated codes, they found that the naturally occurring code has a lower expected random mutation cost than all but 128 random codes. They also discovered that this optimization is independent from the optimization that resists the harmful effects of substitution and framework mutations.

The more scientists learn about the structure of the genetic code found in nature the more remarkable it appears to be. This latest insight not only provides us with a deeper scientific understanding about the nature of biochemical systems, it has profound theological implications.

Codes Come from Intelligent Agents
In The Cell’s Design, I argue from analogy that the mere existence of the genetic code suggests that biochemical systems come from a Mind. 

Experience teaches us that it takes intelligent agents to devise codes. The more sophisticated a code, the greater the level of ingenuity required to develop it.

This conclusion gains added support considering the sophistication and the exquisite optimization of the genetic code on multiple fronts. The genetic code found in nature displays a multidimensional optimality that is difficult to explain through evolutionary mechanisms. And, yet, its biochemical properties are precisely what I would expect if life stems from the work of a Mind.

Resources

• The Cell’s Design: How Chemistry Reveals the Creator’s Artistry by Fazale Rana (book)
• “FYI: ID in DNA Deciphering Design in the Genetic Code” by Fazale Rana (article)
• “The Genetic Code: Simply the Best” by Fazale Rana (article)
• “The Optimal Design of the Genetic Code” by Fazale Rana (article)
• “New Insights into Genetic Code Optimization Signal Creator’s Handiwork” by Fazale Rana (article)
• “Origin and Design of the Genetic Code: A One-Two Punch for Creation” by Fazale Rana (article)
• “Deviant by Design, Part 1” by Fazale Rana (article)
• “Deviant by Design, Part 2” by Fazale Rana (article)
• “Mitochondria’s Deviant Genetic Code: Evolution or Creation?” by Fazale Rana (article)
• “Biochemical Synonyms Optimized, Part 1” by Fazale Rana (article)
• “Biochemical Synonyms Optimized, Part 2” by Fazale Rana (article)

It’s a remarkable discovery—and a bit gruesome, too.

It is worth learning a bit about some of its unseemly details because this find may have far-reaching implications that shed light on our origins as a species.

In 2018, a group of locals discovered the remains of a two-year-old male puppy in the frozen mud (permafrost) in the eastern part of Siberia. The remains date to 18,000 years in age. Remarkably, the skeleton, teeth, head, fur, lashes, and whiskers of the specimen are still intact.

Of Dogs and People

The Russian scientists studying this find (affectionately dubbed Dogor) are excited by the discovery. They think Dogor can shed light on the domestication of wolves into dogs. Biologists believe that this transition occurred around 15,000 years ago. Is Dogor a wolf? A dog? Or a transitional form? To answer these questions, the researchers have isolated DNA from one of Dogor’s ribs, which they think will provide them with genetic clues about Dogor’s identity—and clues concerning the domestication process.

Biologists study the domestication of animals because this process played a role in helping to establish human civilization. But biologists are also interested in animal domestication for another reason. They think this insight will tell us something about our identity as human beings.

In fact, in a separate study, a team of researchers from the University of Milan in Italy used insights about the genetic changes associated with the domestication of dogs, cats, sheep, and cattle to identify genetic features that make human beings (modern humans) stand apart from Neanderthals and Denisovans.¹ They conclude that modern humans share some of the same genetic characteristics as domesticated animals, accounting for our unique and distinct facial features (compared to other hominins). They also conclude that our high level of cooperativeness and lack of aggression can be explained by these same genetic factors.

This work in comparative genomics demonstrates that significant anatomical and behavioral differences exist between humans and hominins, supporting the concept of human exceptionalism. Though the University of Milan researchers carried out their work from an evolutionary perspective, I believe their insights can be recast as scientific evidence for the biblical conception of human nature; namely, creatures uniquely made in God’s image.

Biological Changes that Led to Animal Domestication

Biologists believe that during the domestication process, many of the same biological changes took place in dogs, cats, sheep, and cattle. For example, they think that during domestication, mild deficits in neural crest cells resulted. In other words, once animals are domesticated, they produce fewer, less active neural crest cells. These stem cells play a role in neural development; thus, neural crest cell defects tend to make animals friendlier and less aggressive. This deficit also impacts physical features, yielding smaller skulls and teeth, floppy ears, and shorter, curlier tails.

Life scientists studying the domestication process have identified several genes of interest. One of these is BAZ1B. This gene plays a role in the maintenance of neural crest cells and controls their migration during embryological development. Presumably, changes in the expression of BAZ1B played a role in the domestication process.

Neural Crest Deficits and Williams Syndrome

As it turns out, there are two genetic disorders in modern humans that involve neural crest cells: Williams-Beuren syndrome (also called Williams syndrome) and Williams-Beuren region duplication syndrome. These genetic disorders involve the deletion or duplication, respectively, of a region of chromosome 7 (7q11.23). This chromosomal region harbors 28 genes. Craniofacial defects and altered cognitive and behavioral traits characterize these disorders. Specifically, people with these syndromes have cognitive limitations, smaller skulls, and elf-like faces, and they display excessive friendliness.

Among the 28 genes impacted by the two disorders is the human version of BAZ1B. This gene codes for a type of protein called a transcription factor. (Transcription factors play a role in regulating gene expression.)

The Role of BAZ1B in Neural Crest Cell Biology

To gain insight into the role BAZ1B plays in neural crest cell biology, the European research team developed induced pluripotent stem cell lines from (1) four patients with Williams syndrome, (2) three patients with Williams-Beuren region duplication syndrome, and (3) four people without either disorder. Then, they coaxed these cells in the laboratory to develop into neural crest cells.

Using a technique called RNA interference, they down-regulated BAZ1B in all three types of neural crest cells. By doing this, the researchers learned that changes in the expression of this gene altered the migration rates of the neural crest cells. Specifically, they discovered that neural crest cells developed from patients with Williams-Beuren region duplication syndrome migrated more slowly than control cells (generated from test subjects without either syndrome) and neural crest cells derived from patients with Williams syndrome migrated more rapidly than control cells.

The discovery that the BAZ1B gene influences neural crest cell migration is significant because these cells have to migrate to precise locations in the developing embryo to give rise to distinct cell types and tissues, including those that form craniofacial features.

Because BAZ1B encodes for a transcription factor, when its expression is altered, it alters the expression of genes under its control. The team discovered that 448 genes were impacted by down-regulating BAZ1B. They learned that many of these impacted genes play a role in craniofacial development. By querying databases of genes that correlate with genetic disorders, researchers also learned that, when defective, some of the impacted genes are known to cause disorders that involve altered facial development and intellectual disabilities.

Lastly, the researchers determined that the BAZ1B protein (again, a transcription factor) targets genes that influence dendrite and axon development (which are structures found in neurons that play a role in transmissions between nerve cells).

BAZ1B Gene Expression in Modern and Archaic Humans

With these findings in place, the researchers wondered if differences in BAZ1B gene expression could account for anatomical and cognitive differences between modern humans and archaic humans—hominins such as Neanderthals and Denisovans. To carry out this query, the researchers compared the genomes of modern humans to Neanderthals and Denisovans, paying close attention to DNA sequence differences in genes under the influence of BAZ1B.

This comparison uncovered differences in the regulatory region of genes targeted by the BAZ1B transcription factor, including genes that control neural crest cell activities and craniofacial anatomy. In other words, the researchers discovered significant genetic differences in gene expression among modern humans and Neanderthals and Denisovans. And these differences strongly suggest that anatomical and cognitive differences existed between modern humans and Neanderthals and Denisovans.

Did Humans Domesticate Themselves?

The researchers interpret their findings as evidence for the self-domestication hypothesis—the idea that we domesticated ourselves after the evolutionary lineage that led to modern humans split from the Neanderthal/Denisovan line (around 600,000 years ago). In other words, just as modern humans domesticated dogs, cats, cattle, and sheep, we domesticated ourselves, leading to changes in our anatomical features that parallel changes (such as friendlier faces) in the features of animals we domesticated. Along with these anatomical changes, our self-domestication led to the high levels of cooperativeness characteristic of modern humans.

On one hand, this is an interesting account that does seem to have some experimental support. But on the other, it is hard to escape the feeling that the idea of self-domestication as the explanation for the origin of modern humans is little more than an evolutionary just-so story.

It is worth noting that some evolutionary biologists find this account unconvincing. One is William Tecumseh Fitch III—an evolutionary biologist at the University of Vienna. He is skeptical of the precise parallels between animal domestication and human self-domestication. He states, “These are processes with both similarities and differences. I also don’t think that mutations in one or a few genes will ever make a good model for the many, many genes involved in domestication.”²

Adding to this skepticism is the fact that nobody has anything beyond a speculative explanation for why humans would domesticate themselves in the first place.

Genetic Differences Support the Idea of Human Exceptionalism

Regardless of the mechanism that produced the genetic differences between modern and archaic humans, this work can be enlisted in support of human uniqueness and exceptionalism.

Though the claim of human exceptionalism is controversial, a minority of scientists operating within the scientific mainstream embrace the idea that modern humans stand apart from all other extant and extinct creatures, including Neanderthals and Denisovans. These anthropologists argue that the following suite of capacities uniquely possessed by modern humans accounts for our exceptional nature:

• symbolism
• open-ended generative capacity
• theory of mind
• capacity to form complex social systems

As human beings, we effortlessly represent the world with discrete symbols. We denote abstract concepts with symbols. And our ability to represent the world symbolically has interesting consequences when coupled with our abilities to combine and recombine those symbols in a countless number of ways to create alternate possibilities. Our capacity for symbolism manifests in the form of language, art, music, and even body ornamentation. And we desire to communicate the scenarios we construct in our minds with other human beings.

But there is more to our interactions with other human beings than a desire to communicate. We want to link our minds together. And we can do this because we possess a theory of mind. In other words, we recognize that other people have minds just like ours, allowing us to understand what others are thinking and feeling. We also have the brain capacity to organize people we meet and know into hierarchical categories, allowing us to form and engage in complex social networks. Forming these relationships requires friendliness and cooperativeness.

In effect, these qualities could be viewed as scientific descriptors of the image of God, if one adopts a resemblance view for the image of God.

This study demonstrates that, at a genetic level, modern humans appear to be uniquely designed to be friendlier, more cooperative, and less aggressive than other hominins—in part accounting for our capacity to form complex hierarchical social structures.

To put it differently, the unique capability of modern humans to form complex, social hierarchies no longer needs to be inferred from the fossil and archaeological records. It has been robustly established by comparative genomics in combination with laboratory studies.

A Creation Model Perspective on Human Origins

This study not only supports human exceptionalism but also affirms RTB’s human origins model.

RTB’s biblical creation model identifies hominins such as Neanderthals and the Denisovans as animals created by God. These extraordinary creatures possessed enough intelligence to assemble crude tools and even adopt some level of “culture.” However, the RTB model maintains that these hominids were not spiritual creatures. They were not made in God’s image. RTB’s model reserves this status exclusively for Adam and Eve and their descendants (modern humans).

Our model predicts many biological similarities will be found between the hominins and modern humans, but so too will significant differences. The greatest distinction will be observed in cognitive capacity, behavioral patterns, technological development, and culture—especially artistic and religious expression.

The results of this study fulfill these two predictions. Or, to put it another way, the RTB model’s interpretation of the hominins and their relationship to modern humans aligns with “mainstream” science.

But what about the similarities between the genetic fingerprint of modern humans and the genetic changes responsible for animal domestication that involve BAZ1B and genes under its influence?

Instead of viewing these features as traits that emerged through parallel and independent evolutionary histories, the RTB human origins model regards the shared traits as reflecting shared designs. In this case, through the process of domestication, modern humans stumbled upon the means (breeding through artificial selection) to effect genetic changes in wild animals that resemble some of the designed features of our genome that contribute to our unique and exceptional capacity for cooperation and friendliness.

It is true: studying the domestication process does, indeed, tell us something exceptionally important about who we are.

Resources

• Who Was Adam? A Creation Model Approach to the Origin of Humanity by Fazale Rana with Hugh Ross (book)
• “Were Neanderthals People, Too? A Response to Jon Mooallem” by Fazale Rana (article)
• “What Does It Mean To Be Made in the Image of God?” by Kenneth Samples (article)
• “Did Neanderthals Self-Medicate?” by Fazale Rana (article)
• “Did Neanderthals Make Glue?” by Fazale Rana (article)
• “Glue Production Is Not Evidence for Neanderthal Exceptionalism” by Fazale Rana (article)
• “One of a Kind: Three Discoveries Affirm Human Uniqueness” by Fazale Rana (article)
• “Did Neanderthals Start Fires?” by Fazale Rana (article)
• “Did Neanderthals Make Jewelry?” by Fazale Rana (article)
• “Are Perforated Shells Evidence for Neanderthal Symbolism?” by Fazale Rana (article)
• “Did Neanderthals Produce Cave Paintings?” by Fazale Rana (article)
• “Further Review Overturns Neanderthal Art Claim” by Fazale Rana (article)
• “Did Neanderthals Bury Their Dead with Flowers?” by Fazale Rana (article)
• “Rabbit Burrowing Churns Claims about Neanderthal Burials” by Fazale Rana (article)
• “Dietary Differences Separate Neanderthals from Humans” by Fazale Rana (article)
• “Neanderthal Brains Make Them Unlikely Social Networkers” by Fazale Rana (article)
• “Blood Flow to Brain Contributes to Human Exceptionalism” by Fazale Rana (article)
• “Differences in Human and Neanderthal Brains Explain Human Exceptionalism” by Fazale Rana (article)
• “Did Neanderthals Have the Brains to Make Art?” by Fazale Rana (article)
• “When Did Modern Human Brains and the Image of God Appear?” by Fazale Rana (article)

True confession: I am a sports talk junkie. It has gotten so bad that sometimes I would rather listen to people talk about the big game than actually watch it on TV.

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.

 

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

• • • The Cell’s Design: How Chemistry Reveals the Creator’s Artistry by Fazale Rana (book)
    • “FYI: ID in DNA” by Fazale Rana (article)
    • “The Genetic Code: Simply the Best” by Fazale Rana (article)
    • “The Optimal Design of the Genetic Code” by Fazale Rana (article)
    • New Insights into Genetic Code Optimization Signal Creator’s Handiwork by Fazale Rana
    • “Mitochondria’s Deviant Genetic Code: Evolution or Creation?” by Fazale Rana (article)
    • “Biochemical Synonyms Optimized, Part 1” by Fazale Rana (article)
    • “Biochemical Synonyms Optimized, Part 2” by Fazale Rana (article)

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.

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:

• The Cell’s Design: How Chemistry Reveals the Creator’s Artistry by Fazale Rana (book)
• “FYI: ID in DNA” by Fazale Rana (article)
• “The Genetic Code: Simply the Best” by Fazale Rana (article)
• “The Optimal Design of the Genetic Code” by Fazale Rana (article)
• “Mitochondria’s Deviant Genetic Code: Evolution or Creation” by Fazale Rana (article)
• “Biochemical Synonyms Optimized, Part 1” by Fazale Rana (article)
• “Biochemical Synonyms Optimized, Part 2” by Fazale Rana (article)

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 Theology, William 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.

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.

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.

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.

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

• The Cell’s Design: How Chemistry Reveals the Creator’s Artistry by Fazale Rana (book)
• “FYI: I. D. IN DNA Deciphering Design in the Genetic Code” by Fazale Rana (article)
• “The Genetic Code: Simply the Best” by Fazale Rana (article)
• “Mitochondria’s Deviant Genetic Code: Evolution or Creation?” by Fazale Rana (article)
• “Biochemical Synonyms Optimized, Part 1 of 2” by Fazale Rana (article)
• “Biochemical Synonyms Optimized, Part 2 of 2” by Fazale Rana (article)
• “Protein Amino Acids Form a ‘Just Right’ Set of Biological Building Blocks” by Fazale Rana (article)
• “Why These 20 Amino Acids?” by Fazale Rana (article)
• “The Optimal Design of Metabolism” by Fazale Rana (article)
• “Metabolism: A Cascade of Design” by Fazale Rana (article)

Since the 1960’s, the drug noscapine has been used in many parts of the world as a non-narcotic cough-suppressant. Recently, biomedical researchers have learned that that noscapine (and chemically-modified derivatives of this drug) has potential as a cancer drug. And that is nothing to sneeze at.

The use of the drug for nearly a half century as a cough suppressant means the safety of noscapine has already been established. In fact, pre-clinical studies indicate that noscapine has fewer side effects than many anti-cancer drugs.

Unfortunately, the source of noscapine is opium poppies. Even though tens of tons of noscapine is isolated each year from thousands of tons of raw plant material, biochemical engineers question if the agricultural supply line can meet the extra demand if noscapine finds use as an anti-cancer agent. Estimates indicate that the amounts of noscapine needed for cancer treatments would be about ten times the amount currently produced for its use as a cough suppressant. Complicating matters are the extensive regulations and bureaucratic red tape associated with growing poppy plants and extracting chemical materials from them.

It takes about 1 year to grow mature poppy plants. And once grown, the process of isolating pure noscapine is time intensive and expensive. This drug has to be separated from narcotics and other chemicals found in the opium extract, and then purified. Because poppy plants are an agricultural product, considerable batch-to-batch variation occurs for noscapine supplies.

Chemists have developed synthetic routes to make noscapine. But, these chemical routes are too complex and costly to scale up for large scale production of this drug.

But, researchers from Stanford University believe that they have come up with a solution to the noscapine supply problem. They have genetically engineered brewer’s yeast to produce large quantities of noscapine.¹ This work demonstrates the power of synthetic biology to solve some of the world’s most pressing problems. But, the importance of this work extends beyond science and technology. This work has significant theological implications, as well. This work provides empirical proof that intelligent agency is necessary for the large-scale transformation of life forms.

Genetically Engineered Yeast

To modify brewer’s yeast to produce noscapine, the Stanford University research team had to: 1) first, construct a biosynthetic pathway that would convert simple carbon- and nitrogen-containing compounds into noscapine, and then, 2) add genes to the yeast’s genome that would produce the enzymes needed to carry out this transformation. Specifically, they added 25 genes from plants, bacteria, and mammals to this microbe’s genome. On top of the gene additions, they also had to modify 6 of genes in the yeast’s genome.

Biosynthetic pathways that yield complex molecules such as noscapine can be rather elaborate. Enzymes form these pathways. These protein machines bind molecules and convert them into new materials by facilitating chemical reactions. In biosynthetic pathways the starting molecule is modified by the first enzyme in the pathway and after its transformation is shuttled to the second enzyme in the pathway. This process continues until the original molecule is converted step-by-step into the final product.

Designing a biosynthetic route from scratch would be nearly impossible. Fortunately, the team from Stanford took advantage of previous work done by other life scientists who have characterized the metabolic reactions that produce noscapine in opium poppies. These pioneering researchers have identified a cluster of 10 genes that encode enzymes that work collaboratively to convert the compound scoulerine to noscapine.

The Stanford University researchers used these 10 poppy genes as the basis for the noscapine biosynthetic route they designed. They expanded this biosynthetic pathway by using genes that encode for the enzymes that convert glucose into reticuline. This compound is converted into scoulerine by the berberine bridge enzyme. They discovered that the conversion of glucose to reticuline is tricky, because one of the intermediary compounds in the pathway is dopamine. Life scientists don’t have a good understanding how this compound is made in poppies, so they used the genes that encode the enzymes to make dopamine from rats.

They discovered that when they added all of these genes into the yeast, these modified microbes produced noscapine, but at very low levels. At this point, the research team carried out a series of steps to optimize noscapine production, which included:

• Genetically altering some of the enzymes in the noscapine biosynthetic pathway to improve their efficiency
• Manipulating other metabolic pathways (by altering the expression of the genes that encode enzymes in these metabolic routes) to divert the maximum amounts of metabolic intermediates into the newly constructed noscapine pathway
• Varying the media used to grow the yeast

These steps led to an 18,000-fold improvement in noscapine production.

With accomplishment, the scientific community is one step closer to have a commercially-viable source of noscapine.

Synthetic Biology and the Case for a Creator

Without question, the engineering of brewer’s yeast to produce noscapine is science at its very best. The level of ingenuity displayed by the research team from Stanford University is something to behold. And, it is for this reason, I maintain that this accomplishment (along with other work in synthetic biology) provides empirical evidence that a Creator must play a role in the origin, history, and design of life.

In short, these researchers demonstrated that intelligent agency is required to originate new metabolic capabilities in an organism. This work also illustrates the level of ingenuity required to optimize a metabolic pathway once it is in place.

Relying on hundreds of years of scientific knowledge, these researchers rationally designed the novel noscapine metabolic pathway. Then, they developed an elaborate experimental strategy to introduce this pathway in yeast. And then, it took highly educated and skilled molecular biologists to go in the lab to carry out the experimental strategy, under highly controlled conditions, using equipment that itself was designed. And, afterwards, the researchers employed rational design strategies to optimize the noscapine production.

Given the amount of insight, ingenuity, and skill it took to engineer and optimize the metabolic pathway for noscapine in yeast, is it reasonable to think that unguided, undirected, historically contingent evolutionary processes produced life’s metabolic processes?

Resources:

Creating Life in the Lab: How New Discoveries in Synthetic Biology Make a Case for a Creator by Fazale Rana (book)

“New Discovery Fuels the Case for Intelligent Design” by Fazale Rana (article)

“Fattening Up the Case for Intelligent Design” by Fazale Rana (article)

“A Case for Intelligent Design, Part 1” by Fazale Rana (article)

“A Case for Intelligent Design, Part 2” by Fazale Rana (article)

“A Case for Intelligent Design, Part 3” by Fazale Rana (article)

“A Case for Intelligent Design, Part 4” by Fazale Rana (article)

“The Blueprint for an Artificial Cell” by Fazale Rana (article)

“Do Self-Replicating Protocells Undermine the Evolutionary Theory” by Fazale Rana (article)

“A Theology for Synthetic Biology, Part 1” by Fazale Rana (article)

“A Theology for Synthetic Biology, Part 2” by Fazale Rana (article)

Before joining Reasons to Believe, I worked for nearly a decade in research and development (R&D) for a Fortune 500 company. During my tenure, on several occasions I was assigned to work on a “resurrected” project—one that was mothballed years earlier for one reason or another but was then deemed worthy of another go-around by upper management.

Of course, the first thing we did when we began work on the “old-project-made-new” was to review the work done by the previous R&D team. Invariably, we would come across things they had done that didn’t make sense to us whatsoever. I quickly learned that instead of deriding the previous team members for their questionable decision-making skills and flawed strategy, it was better to track down past team members and find out why they did things the way they did. Almost always, there were good reasons justifying their decisions. In fact, understanding their rationale often revealed an ingenuity to their approach.

The same can be said for mitochondria—bean-shaped organelles found in eukaryotic cells. Mitochondria play a crucial role in producing the energy that powers the cell’s operations. Based on a number of features possessed by these organelles—features that seemingly don’t make sense if mitochondria were created by a Divine Mind—many biologists believe that mitochondria have an evolutionary origin. Yet, as we learn more about mitochondria, scientists are discovering that the features that we thought made little sense from a creation model vantage point have a rationale for why they are the way they are. In fact, these features reflect an underlying ingenuity, as work by biochemists from Germany attests.¹

We will take a look at the work of these biochemists later in this article. But first, it would be helpful to understand why evolutionary biologists think that the design of mitochondria makes no sense if these subcellular structures are to be understood as a Creator’s handiwork.

The Endosymbiont Hypothesis

Most evolutionary biologists believe the best explanation for the origin of mitochondria is the endosymbiont hypothesis. Lynn Margulis (1938–2011) advanced this idea to explain the origin of eukaryotic cells in the 1960s, building on the ideas of Russian botanist Konstantin Mereschkowsky.

Taught in introductory high school and college biology courses, Margulis’s work has become a cornerstone idea of the evolutionary paradigm. This classroom exposure explains why students often ask me about the endosymbiont hypothesis when I speak on university campuses. Many first-year biology students and professional life scientists alike find the evidence for the idea compelling and, consequently, view it as providing broad support for an evolutionary explanation for the history and design of life.

According to this hypothesis, complex cells originated when symbiotic relationships formed among single-celled microbes after free-living bacterial and/or archaeal cells were engulfed by a “host” microbe. (Ingested cells that take up permanent residence within other cells are referred to as “endosymbionts.”)

Presumably, organelles such as mitochondria were once endosymbionts. Once taken into the host cell, the endosymbionts then took up permanent residency within the host, with the endosymbiont growing and dividing inside the host. Over time, the endosymbionts and the host became mutually interdependent, with the endosymbionts providing a metabolic benefit for the host cell. The endosymbionts gradually evolved into organelles through a process referred to as “genome reduction.” This reduction resulted when genes from the endosymbionts’ genomes were transferred into the genome of the host organism. Eventually, the host cell evolved the machinery to produce the proteins needed by the former endosymbiont and processes to transport those proteins into the organelle’s interior.

Evidence for the Endosymbiont Hypothesis

The similarities between organelles and bacteria serve as the main line of evidence for the endosymbiont hypothesis. For example, mitochondria—which are believed to be descended from a group of alphaproteobacteria—are about the same size and shape as a typical bacterium and have a double-membrane structure like these gram-negative cells. These organelles also divide in a way that is reminiscent of bacterial cells.

Biochemical evidence also exists for the endosymbiont hypothesis. Evolutionary biologists view the presence of the diminutive mitochondrial genome as a vestige of this organelle’s evolutionary history. Additionally, biologists view the biochemical similarities between mitochondrial and bacterial genomes as further evidence for the evolutionary origin of these organelles.

The presence of the unique lipid cardiolipin in the mitochondrial inner membrane also serves as evidence for the endosymbiont hypothesis. This is an important lipid component of bacterial inner membranes. Yet it is not found in the membranes of eukaryotic cells—except for in the inner membranes of mitochondria. In fact, biochemists consider it a signature lipid for mitochondria and a vestige of this organelle’s evolutionary history.

Does the Endosymbiont Hypothesis Successfully Account for the Origin of Mitochondria?

Despite the seemingly compelling evidence for the endosymbiont hypothesis, when researchers attempt to delineate the details of a presumed evolutionary transition, it becomes readily apparent that biologists lack a genuine explanation for the origin of mitochondria and, in a broader context, the origin of eukaryotic cells. In three previous articles, I detail some of the scientific challenges facing the endosymbiont hypothesis:

• “Complex Protein Biogenesis Hints at Intelligent Design”
• “Evolutionary Paradigm Lacks Explanation for Origin of Mitochondria and Eukaryotic Cells”
• “Biology’s Big Bangs”

A Creation Model Approach for the Origin of Mitochondria

Given the scientific shortcomings of the endosymbiont hypothesis, is it reasonable to view mitochondria (and eukaryotic cells) as the work of a Creator?

I would maintain that it is. I argue that the shared similarities between mitochondria and alphaproteobacteria—which stand as the chief evidence for the endosymbiont hypothesis—reflect shared designs rather than a shared evolutionary history. It is common for human designers and engineers to reuse designs. So, why wouldn’t a Creator? See this article for more on this idea:

• “Archetype or Ancestor? Sir Richard Owen and the Case for Design.”

Why Do Mitochondria Have Their Own Genome and Cardiolipin in Their Inner Membranes?

However, to legitimately interpret the genesis of mitochondria from a creation model perspective, there must be a rationale for why mitochondria have their own diminutive genomes. And there has to be an explanation for why these organelles possess cardiolipin in their inner membranes, because on the surface, it appears as though mitochondrial genomes and cardiolipin are vestiges of the evolutionary history of these organelles.

As I have described previously (see the articles listed below), biochemists have recently learned that there are good reasons why mitochondria have their own genome—independent of the nuclear genome—and a sound rationale for the presence of cardiolipin in the inner membrane of these organelles. In other words, these features of mitochondria make sense from the vantage point of a creation model.

• “Why Do Mitochondria Have DNA?”
• “Mitochondrial Genomes: Evidence for Evolution or Creation?”
• “Can a Creation Model Explain the Origin of Mitochondria?”

Why Do Mitochondria Have Their Own Genetic Code?

But, there is at least one other troubling feature of mitochondrial genomes that requires an explanation if we are to legitimately view these organelles as the handiwork of a Creator. For if they are a Creator’s handiwork, then why do mitochondria make use of deviant, nonuniversal genetic codes? Again, at first blush it would seem that the nonuniversal genetic code in mitochondria reflects their evolutionary origin. To understand why mitochondria have their own genetic code, a little background information is in order.

A Universal Genetic Code

The genetic code is 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. The genetic code consists of coding units, called “codons,” where each codon corresponds to one of the 20 amino acids found in proteins.

To a first approximation, all life on Earth possesses the same genetic code. To put it another way, the genetic code is universal. However, there are examples of organisms that possess 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.

The Deviant Genetic Codes of Mitochondria

Quite frequently, mitochondrial genomes employ deviant codes. One of the most common differences between the universal genetic code and the one found in mitochondrial genomes is the reassignment of one of the codons that specifies isoleucine (in the universal code) so that it specifies methionine. In fact, evolutionary biologists believe that this evolutionary transition happened five times in independent mitochondrial lineages.²

So, while many biologists believe that the nonuniversal genetic codes in mitochondria can be explained through evolutionary mechanisms, creationists (and ID proponents) must come up with a compelling reason for a Creator to alter the universal genetic code in the genome of these organelles. This issue becomes particularly pressing because biochemists have come to learn that the rules that define the genetic code are exquisitely optimized for error minimization (among other things), as I discuss in these articles:

• “FYI: I.D. in DNA Deciphering Design in the Genetic Code”
• “The Genetic Code: Simply the Best”

The Genius of Deviant Codes in Mitochondria

So, is there a rationale for the reassignment of the isoleucine codon?

Work by a team of German biochemists provides an answer to this question—one that underscores an elegant molecular logic to the deviant genetic codes in mitochondria. These researchers provide evidence that the reassignment of the isoleucine codon for methionine protects proteins in the inner membrane of mitochondria from oxidative damage.

Metabolic reactions that take place in mitochondria during the energy harvesting process generate high levels of reactive oxygen species (ROS). These highly corrosive compounds will damage the lipids and the proteins of the mitochondrial inner membranes. The amino acid methionine is also readily oxidized by ROS to form methionine sulfoxide. Once this happens, the enzyme methionine sulfoxide reductase (MSR) reverses the oxidation reaction by reconverting the oxidized amino acid to methionine.

As a consequence of reassigning the isoleucine codon, methionine replaces isoleucine in the proteins encoded by the mitochondrial genome. Many of these proteins reside in the mitochondrial inner membrane. Interestingly, many of the isoleucine residues of the inner mitochondrial membrane proteins are located on the surfaces of the biomolecules. The replacement of isoleucine by methionine has minimal effect on the structure and function of these proteins because these two amino acids possess a similar size, shape, and hydrophobicity. But because methionine can react with ROS to form methionine sulfoxide and then be converted back to methionine by MSR, the mitochondrial inner membrane proteins and lipids are protected from oxidative damage. To put it another way, the codon reassignment results in a highly efficient antioxidant system for mitochondrial inner membranes.

The discovery of this antioxidant mechanism leads to another question: Why is the codon reassignment not universally found in the mitochondria of all organisms? As it turns out, the German biochemists discovered that this codon reassignment occurs in animals that are active, placing a high metabolic demand on mitochondria (and with it, concomitantly elevated production of ROS). On the other hand, this codon reassignment does not occur in Platyhelminthes (flatworms, which live without requiring oxygen) and inactive animals, such as sponges and echinoderms.

From a creation model vantage point, there are good reasons why things are the way they are regarding mitochondrial biochemistry. In fact, understanding the rationale for the design of mitochondria reveals an ingenuity to life’s designs.