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SARS-CoV-2 Biology Points to Endogenous Retrovirus Design

Fazale “Fuz” Rana — Wed, 28 Jul 2021 12:00:00 +0000

“I’ve been dealing with viral outbreaks for the last 40 years. I’ve never seen a single virus—that is, one pathogen—have a range where 20% to 40% of the people have no symptoms.”

—Dr. Anthony Fauci, National Institute of Allergy and Infectious Diseases

Many of the disease characteristics of COVID-19 continue to baffle life scientists and biomedical practitioners. The confusion is not limited to the high rate of asymptomatic infections—other aspects of COVID-19 are puzzling as well. For example, some patients who have recovered from an initial COVID-19 infection will return positive PCR tests for SARS-CoV-2 weeks, even months, after their recovery. (The PCR test detects the presence and levels of SARS-CoV-2 genetic material in the patient.) These patients show no indication that they were reinfected and they pose no threat to spread the virus to others.

Recently, a team of life scientists from MIT offered an explanation for these unexpected observations.¹ These investigators discovered that once the SARS-CoV-2 virus gains entrance into human cells, its genetic material (which is made up of a single plus strand of RNA) can be converted into DNA by cellular enzymes called reverse transcriptases. In turn, the SARS-CoV-2 DNA can then become integrated into the infected cell’s genome. Once in the genome, the SARS-CoV-2 DNA sequences can be transcribed, producing viral RNA that is detected by PCR tests.

This important insight adds to our understanding of the biology and replication cycle of SARS-CoV-2. It also holds significance for assessing the performance of antiviral therapies.

This discovery also has unexpected significance for the RTB creation model. It suggests a possible explanation for the presence of sequence elements called endogenous retroviruses (ERVs) in the human genome (and the genomes of other organisms). Many people regard the ERV sequences in the human genome as the most compelling evidence for human evolution. But, instead of baffling those of us who embrace a creation model for biology, the insights from the MIT team now make it possible to view ERVs as intentional features of genomes designed to serve a variety of purposes—including functioning as part of the innate immune system, offering protection from retrovirus invaders.

Before unpacking the impact of this study on the RTB creation model, a discussion of the work of the MIT scientists (which in and of itself is fascinating and important) is in order. And to do this well, we first need to briefly review the biology and replication of SARS-CoV-2.

SARS-CoV-2 Biology and Replication²
Viral invasion begins when SARS-CoV-2 virions attach to the surface of the host cell. Mediating this binding event is the interaction between the spike proteins that decorate the surface of the SARS-CoV-2 viral particles and the ACE-2 proteins which reside on the host cell’s surface. Once binding takes place, a protease in the host cell membrane cleaves the spike proteins. (Proteases are proteins that break apart protein chains.) This cleavage causes the host cell to engulf the attached SARS-CoV-2 virion, forming an endosome (which is a membrane-bound vesicle that arises from an invagination of the cell membrane). Once formed, the endosome migrates to the cell’s cytoplasm. Within the endosome, an unsheathing process takes place releasing the viral RNA from the protein capsid that surrounds it. As a result of the unsheathing process, the viral RNA finds its way into the host cell’s cytoplasm.

Here, the viral RNA makes its way to a ribosome where it is translated into two large polyproteins. Each of these large polyproteins consists of several individual protein sequences catenated together. Two of the individual proteins contained within the polyproteins are proteases. These internal proteases self-catalyze the cleavage of the two polypeptides. In doing so, they cause the other protein molecules harbored in the two polyproteins to be released as free-standing proteins.

Once released from the two polyproteins, some of the newly released proteins interact with one another to form a complex called the viral replication and transcription complex. This complex produces more copies of the viral genetic material through the activity of several enzymes, including one called an RNA-dependent RNA polymerase. The resulting viral RNA molecules are, in turn, translated to form more copies of the viral replication and transcription complex. They are also translated to produce the structural proteins needed to assemble more viral particles.

The viral replication and transcription complex associate with the host cell’s endoplasmic reticulum. This association leads to the formation of convoluted areas in the membrane of the endoplasmic reticulum. These convoluted areas form protected spaces that allow the viral RNA (produced by the viral replication and transcription complex) to be packaged with capsid proteins. Other structural proteins, such as the spike protein, which are found in the lipid envelope surrounding the viral RNA-protein capsid complex incorporate into the convoluted membranes of the endoplasmic reticulum. From here the encapsulated viral RNA and viral membrane proteins can be processed through the Golgi apparatus to be secreted into the extracellular space through the process of exocytosis.

A Bold Hypothesis
Though life scientists possess detailed insight into much of the biology and the replication of SARS-CoV-2, nothing in their understanding immediately sheds light on the positive PCR tests that persist after COVID–19 patients recover from their initial infection. The MIT investigators think that we may have overlooked a significant aspect of the molecular biology of SARS-CoV-2. Along these lines, they speculate that the SARS-CoV-2 genetic material becomes incorporated into the host cell’s genome and then becomes expressed, generating an ongoing source of viral genetic material.

Their hypothesis is a bit daring, because based on our current understanding of the replication of SARS-CoV-2—which relies on an RNA-dependent RNA polymerase to replicate its genetic material—researchers are hard-pressed to identify a mechanism for the SARS-CoV-2 material to make its way into the host genome.

However, retroviruses (which are also RNA viruses) have a well-characterized mechanism for incorporating their genetic material into the genome of the host cell. Before replication takes place, the retroviral RNA becomes converted into DNA. An enzyme called reverse transcriptase carries out this conversion. The genetic instructions needed to make reverse transcriptase are encoded in the retroviral genome. This protein is packaged in the retroviral capsid along with the retroviral RNA.

The newly made retroviral DNA can then use the invaded cell’s biosynthetic pathways to direct the production of new retroviral particles. The DNA copy of the retroviral genetic material can also become incorporated into the host cell’s genome. When this insertion takes place, the retroviral DNA becomes part of the host cell’s genome. This process is called endogenization.

Even though SARS-CoV-2 doesn’t encode a reverse transcriptase in its genome, the MIT scientists postulated that the SARS-CoV-2 RNA may still be reverse transcribed at some point during its replication cycle by endogenous copies of reverse transcriptase, encoded in the host genome. Biologists know that DNA sequences associated with retrotransposons (such as LINE sequences) found in the host cell’s genome encode for proteins with reverse transcriptase activity.

LINE sequences comprise about 20 percent of the human genome. These mobile DNA elements can make copies of themselves, with the copies becoming randomly inserted throughout the genome. Some LINE DNA sequences lie dormant in the human genome. Others can be transcribed into mRNA that, in turn, can be translated into a protein with reverse transcriptase activity. The LINE reverse transcriptase can make a copy of the LINE mRNA, converting it into DNA that can be integrated into the genome at a new location.

The research team speculated that once it has been synthesized by endogenous reverse transcriptase activity, the SARS-CoV-2 DNA can become integrated into the host cell’s genome. Here, the SARS-CoV-2 DNA sequences can be transcribed, producing viral RNAs that are detected by PCR tests.

An Unexpected Discovery
In support of their hypothesis, the MIT team discovered that:

1) Cultured human cells exposed to SARS-CoV-2 in the laboratory and cells taken from patients infected with SARS-CoV-2 both produce mRNA molecules that include those with hybrid sequences made up of host cell genes and viral genes. This observation suggests that viral genetic material has been incorporated in the host cell’s genome.
2) The predominant viral gene sequences that occur in the hybrid RNA molecules encode the capsid proteins. mRNA molecules that encode the capsid proteins are the most abundant of the viral mRNAs in the cell. These mRNA molecules would be readily available to be transcribed by endogenously sourced reverse transcriptase.
3) In the laboratory, when cells belonging to the HEK293 line are forced to overexpress LINE DNA sequences, SARS-CoV-2 RNA becomes reverse transcribed upon exposure of the cells to virions. The resulting SARS-CoV-2 DNA becomes incorporated into the genome of the HEK293 cells.
4) Exposure of cells to SARS-CoV-2 virions induces LINE expression.

Collectively, these findings provide compelling circumstantial evidence that endogenous reverse transcriptase converts SARS-CoV-2 RNA into DNA and this DNA, in turn, becomes integrated into the host cell’s genome. The evidence also indicates that only portions of the SARS-CoV-2 genome become incorporated into the host cell’s genome. As a result, when the host cell’s machinery transcribes these sequences to produce RNA, it can’t produce virions that can be transmitted to other people.

This discovery carries several important scientific and biomedical implications.

• It explains the unusual PCR results returned for patients who have recovered from COVID–19.

• It will help guide the development of antiviral therapies if the presence of SARS-CoV-2 genetic material in the patient is used to monitor the effectiveness of the antiviral treatment.

• It indicates that the reverse transcription of viral genetic material and its incorporation into the host cell genome may not be limited to SARS-CoV-2. It might be a general feature of other RNA viruses.

This discovery also has implications for the RTB creation model. It gives insight as to why ERV sequences are found in genomes. By doing so, it becomes increasingly reasonable to view ERV sequence elements as the intentional handiwork of a Creator, instead of a reflection of our evolutionary history.

Endogenous Retroviruses and the Case for Human Evolution
On becoming incorporated into an organism’s genome, retroviral DNA is called an ERV. If the ERV infects a germline cell (a sperm cell or an egg cell), it can be inherited, transmitted from generation to generation as a permanent feature of the genome.

If the ERV DNA suffers severe mutations, it becomes disabled, remaining in the genome as nonfunctional, junk DNA.
As it turns out, about 8 percent of the human genome consists of ERVs.

Evolutionary biologists consider the endogenous retroviral populations found in the human genome as evidence that humans have an evolutionary history shared with the great apes. Many human ERVs are also found in the genomes of chimpanzees, bonobos, gorillas, and orangutans. Not only do these ERVs share many of the same sequence patterns, but they also appear in corresponding locations in the genomes.

Evolutionary biologists explain this data by assuming that the shared ancestor of humans and chimpanzees, for example, became infected by these specific retroviruses. Later, the endogenized retroviruses experienced mutations that disabled them. These ERV sequences were retained in the genomes of humans and chimpanzees as their separate evolutionary lineages diverged from the common ancestor. According to the model, the ERVs shared by humans and chimpanzees represent the molecular artifacts of infections that occurred millions of years ago and left their imprint on contemporary genomes via this (presumed) shared ancestor.

Many people consider the presence of ERVs in the human genome (and the genomes of other organisms) to be baffling for the RTB creation model.

• Why would the Creator introduce the same nonfunctional sequence elements in the same locations within the genomes of organisms that naturally group together (based on other biological features)?

• And why would he create these shared sequence elements to bear such strong similarity to retroviruses?

Yet, the RTB creation model predicts that the Creator would have intentionally designed and incorporated ERVs into genomes to serve vital roles. The unexpected discovery that SARS-CoV-2 genetic material becomes incorporated into the host cell’s genome bears on this key prediction. Once incorporated into the genome of host cells, the activity and impact of the SARS-CoV-2 sequences suggest at least one reason why a Creator would intentionally incorporate ERV sequences into the human genome (and the genomes of other creatures) and why these sequences share so much similarity to retroviral sequences.

Impact of SARS-CoV-2 Sequences in the Host Cell Genome
The MIT researchers believe that the SARS-CoV-2 genetic material only becomes incorporated into the genomes of a limited number of cells. And of those cells, only a limited number express the viral genes. Still, they argue that this expression could have important consequences. They speculate that viral proteins that result from the expression of the incorporated viral genes could continuously stimulate the immune system. In doing so, the viral proteins provide the patient with ongoing immunity against SARS-CoV-2, serving as part of the repertoire of proteins and cells that imparts immune memory to the infected individual long after they clear the infection. Toward this end, the incorporated SARS-CoV-2 genetic material housed in the genomes of host cells acts as a type of endogenous DNA vaccine.

As it turns out, the MIT team’s discovery is not the first time that life scientists have detected genetic material from nonretroviral RNA viruses becoming incorporated into the genome of host cells during a viral infection. In 1997, a Swiss research team reported that the genetic material from lymphocytic choriomeningitis virus (LCMV)—an RNA virus—also becomes reverse transcribed into DNA by endogenous reverse transcriptase activity. In turn, the viral DNA then becomes incorporated in the genomes of mouse cells. This DNA serves as an ongoing source of viral proteins that also appear to contribute to immune memory in mice.³

A Proposed Function for ERVs
Based on this insight, I propose a similar role for ERVs in the human genome (and genomes of other animals). That is, I predict that one of the roles of ERVs is to function as a type of DNA vaccine designed into the genomes of organisms, with the proteins produced from the expressed ERV proteins stimulating the immune system, helping it ward off retroviral infections.

In 2019, a research team from China discovered that ERVs in the mouse genome produced RNA transcripts at high expression levels during exposure to RNA viruses.⁴These ERV transcripts played a role in activating genes that led to interferon production, contributing to innate immunity in mice. While key aspects of this mechanism differ from the one I propose, it does demonstrate that RNA viral infections upregulate the expression of ERV sequences and establishes the link between expression of ERV DNA sequences and innate immunity.

Considering my proposal, it is also worth noting the work of researchers from the United States, Germany, and Australia. These investigators demonstrated that ERVs in the koala genome serve an antiretroviral role by disrupting the endogenization process of the koala endogenous retrovirus (KoRV). (See “Koala Endogenous Retroviruses (ERVs) Protect Against Retroviral Infections.”) This mechanism is also distinct from the one I propose. Yet it highlights the fact that ERV sequences may play an antiviral role through a variety of distinct mechanisms.

ERVs: Common Descent or Common Design?
Many life scientists regard the shared biological features possessed by organisms (that naturally cluster together) as evidence for their shared evolutionary ancestry. Yet, it is possible to advance an alternative explanation for biological similarities. Instead of evincing common descent, they could be interpreted as shared biological designs. In fact, prior to Charles Darwin, Sir Richard Owen produced a theoretical framework to interpret anatomical and physiological similarities shared among organisms. Owen saw these mutual features as manifestations of a common blueprint—an archetype that arose out of the Mind of the One True Cause.

The RTB creation model employs Owen’s insight by interpreting the shared features in the genomes of organisms as manifestations of genomic archetypes. In other words, the genetic similarities in the genomes of humans and the great apes were intentionally introduced by the Creator. To justify this interpretation, the shared genomic features must serve a function. And, indeed, this is the case for ERVs. These sequence elements appear to function as part of the innate immune system, helping to ward off retroviral infections through a variety of mechanisms that life scientists are just beginning to understand.

The antiviral role played by ERVs is largely possible because of the similarity between these DNA sequences and the genetic material of retroviruses. This requirement explains why a Creator would introduce genetic elements into the human genome (and the genome of other creatures) that share sequence elements with retroviruses.

If the last decade or so has taught us anything, it is this: Science is in its infancy when it comes to understanding the human genome. Increasingly, features that we originally thought were junk sequences turn out to make critical contributions. Such is the case for ERVs. The more we learn about these abundant sequence elements in the human genome, the more sense these sequence elements make for those of us who view biology through the lens of a creation model.

Resources

“Koala Endogenous Retroviruses (ERVs) Protect Against Retroviral Infections” by Fazale Rana (article)

“Questioning Evolutionary Presuppositions about Endogenous Retroviruses” by Anjeanette Roberts (article)

“A Common Design View of ERVs Encourages Scientific Investigation” by Anjeanette Roberts (article)

“Archetype or Ancestor? Sir Richard Owen and the Case for Design” by Fazale Rana (article)

Endnotes

1. Liguo Zhang et al., “Reverse-Transcribed SARS-CoV-2 RNA Can Integrate into the Genome of Cultured Human Cells and Can Be Expressed in Patient-Derived Tissues,” Proceedings of the National Academy of Sciences, USA 118, no. 21 (May 25, 2021): e2105968118, doi:10.1073/pnas.2105968118.

2. Philip V’kovski et al., “Coronavirus Biology and Replication: Implications for SARS-CoV-2” Nature Reviews Microbiology 19 (March 2021): 155–170, doi:10.1038/s41579-020-00468-6.

3. Paul Klenerman, Hans Hengartner and Rolf M. Zinkernagel, “A Non-Retroviral RNA Virus Persists in DNA Form,” Nature 390 (November 20, 1997): 298–301 doi:10.1038/36876.

4. Bin Zhou et al., “Endogenous Retrovirus-Derived Long Noncoding RNA Enhances Innate Immune Responses via Derepressing RELA Expression,” mBio 10, no. 4 (July/August 2019): e00937-19, doi:10.1128/mBio.00937-19.

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Book Review: General Biology by Heather Ayala and Katie Rogstad

Guest Writer — Mon, 01 Feb 2021 17:56:00 +0000

Book reviewed by Dan Bakken, George Haraksin, and Krista Bontrager

General Biology by Heather Ayala and Katie Rogstad is a high school level volume targeted at Christian schools and homeschoolers. The content is accommodating for students with little previous science education, although it is not just for entry-level students. Even students in advanced science will find this material informative.

This handsome work offers a great mix of traditional textbook-style presentation and modern visual appeal, with color diagrams and photos throughout. Within the chapters are breakout boxes covering current topics of interest that should draw in even the most uninterested students. The problem exercises at the end of each chapter are well thought out and complement the material.

The text’s strongest contribution is the guiding philosophy behind it. The authors list four goals in the introduction: wonder, integration, mastery, and kingdom. Two of these goals had us cheering: wonder and kingdom. Wonder is what drives most people to study creation in the first place. The beauty and incredible designs in the natural world should draw students into the material. Dry, monotonous science teaching frequently displaces wonder in schools, so this emphasis on wonder is an important tool to keep students interested. We also valued the Kingdom aspect of the text—showing how creation all works together in God’s plans. This valuable component is, of course, missing in secular treatments. We applaud science teaching that incorporates these undergirding themes.

That being said, is this the biology textbook that RTB followers are looking for, one that supports our view of concordance between Scripture and science from an old-earth creation perspective? Probably not. The authors do state that (naturalistic) evolution is only a theory and that they aren’t forcing their readers toward a particular conclusion on that theory. And they do seem open to allowing room for testability and the adjustment of the framework over time as new data is discovered.

But, to be clear, the authors present all the data through the lens of theistic evolution (aka evolutionary creationism), or what they refer to as the “consensus of science.” They see the evolutionary framework as the current, best explanation for the data. The preface explicitly directs students to BioLogos, a science-faith ministry that advocates for theistic evolution (evolutionary creationism).

The authors do cite a couple of examples of evidence that question evolution. On pages 405–408, the authors address the concern that minor changes (point mutations) in the genetic code over time are simply not enough to cause major morphologic changes. Also, the “Hmmmm….Interesting” section on pages 412–413 highlights secular scientist Lynn Margulis, who has gone against the grain in questioning some of the major tenets of evolutionary theory. But these types of examples are limited. Instructors who are of an old-earth creationist persuasion are likely to find this lack of data countering the naturalistic evolutionary framework disappointing.

The text’s integration with the Christian worldview is fairly general. The authors do occasionally draw students’ attention to the wonder of God’s creation. For example, the opening image description for chapter 2 says, “We can use the physical and chemical properties of biologically important molecules to explain the related properties at higher levels of organization, giving us amazing insight into how all things work together according to the laws of nature designed by the Creator” (p. 32). Chapter 3 describes how emergent properties of higher levels of biological organization point to an intelligent purpose behind life: “Mixing some DNA, proteins, and lipids together cannot account for the marvelous complexity of a cell—a cell that is precisely arranged to conduct thousands of metabolic reactions to carry out each and every function of life. The highly complex, elegantly designed nature of the cell points to a higher intelligence—the Author of Life” (p. 72).

These mentions of design are rare and fairly general, and we were left hoping for a more detailed look at design. This lack is likely due to the authors’ support for the evolutionary framework and what they see as the fairly limited role of general revelation: inspiring awe and wonder. Because they see the Creator’s role as a providential unfolding and holding together of the physical world, the authors present the history of life as being the result of natural processes. They do not discuss direct, miraculous interventions at key moments in creation’s history, such as the origin of life, the origin of new animal species, or the origin of humanity. And integration with the Bible (e.g. the creation descriptions in Genesis) is limited and fairly broad in scope.

Does that mean we don’t recommend this textbook? It depends. We highly recommend the philosophy behind the book. We affirm the closing words in the text,

There can be no conflict between studying the world God made and belief in the One who made it . . . When we finally are able to read both [the book of nature and the book of Scripture] correctly, they will be seen to be in harmony, not in conflict . . . Soli Deo Gloria!

Unfortunately, the application of that philosophy is not implemented as extensively as we had hoped. For that reason, we would recommend this text only for those who can supplement it with additional material that provides a more specific integration framework for God’s supernatural interventions.

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Biology Continues to Inspire New Technology

Jeff Zweerink — Mon, 28 Jan 2013 19:08:00 +0000

Scientific literature seems filled with examples of ways living organisms inspire engineers to develop new technology. It happens so often that scientists developed a whole new discipline called biomimicry. Usually, copying nature’s designs leads to better solutions than using human intellect alone. The latest two examples involve water striders and rays.

Someone in an uncomfortable situation is often referred to as “a fish out of water.” Conversely, people who swim well are referred to as fish. Either way, almost all land animals struggle in the water and most water creatures flail on land. Perhaps it is not surprising then that land-dwelling humans would look to aquatic life to devise better machines to operate in the water. Specifically, water striders and rays recently inspired two different technologies for navigating over and through the water.

Walking on Water
Water striders perform the seemingly magical feat of walking on water. They not only move across the surface effortlessly, they can also jump over obstacles. Water’s high surface tension makes these movements possible. Studies of the strider’s feet helped a team of scientists develop a microrobot that uses the surface tension of water to mimic both the strider’s “walking” and jumping—and the machine weighs more than 1,000 water striders combined. The key innovation was finding a porous, highly water-repellant and lightweight material, in this case, a nickel-based foam.

Three pads made from this water-repellant foam provided the necessary force to keep the microrobot from sinking. Two similar paddles could then strike the water’s surface and provide the impetus for the robot to jump. Tests of the robot demonstrated a vertical leap of nearly 6 inches and the ability to jump forward by 14 inches.¹ Such technology would provide microrobots great agility and adaptability as they gather data on remote, hard-to-reach bodies of water.

Cruising through the Deep Seas
A ray’s movement through the water matches (if not exceeds) the elegance of the water strider’s capacity to navigate across the water’s surface. Further, a ray travels effortlessly to places difficult to access with sensors deployed from a ship. By analyzing the swimming motion of a cow-nosed ray (one common to the Atlantic Ocean and Chesapeake Bay), a team of researchers built a prototype mechanical ray that mimics the movements of the actual organisms. Currently, scientists must control the prototype remotely, but they hope to manufacture a self-contained, autonomous machine that could be deployed for long periods of time. Such a device could carry instruments for monitoring spills, investigate delicate marine environments, and have potential military applications. Modeling the mechanical ray after existing creatures means that the machines operate without affecting the other organisms in their natural habitat. However, I would not want to be the shark that accidentally eats one of these things.

The number of biologically-inspired technologies continues to grow. From transportation networks to adhesives (at least two different kinds), myriad other examples show the awesome creative power of the Author of creation.

Endnotes

Jie Zhao et al., “Why Superhydrophobicity is Crucial for a Water-Jumping Microbot? Experimental and Theoretical Investigations,” ACS Applied Materials & Interfaces 4 (June 25, 2012): 3706–711.

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Biology’s Morse Code

Guest Writer — Fri, 06 Aug 2010 13:00:00 +0000

by Katie Galloway

Long before Samuel Morse put his telegraphic code to work, neurons and other cells were processing extracellular dash- and dot-type signals into instructions for cellular decisions. Researchers in Germany recently reported on how the cell reads and responds to these directions.¹

Signals from outside the cell control many intracellular programs, even directing how cells develop into organs and whole organisms. Among other outcomes, these signals lead to bone growth, wound healing, and programmed cell death. In fact, nearly every type of cell utilizes extracellular instructions.

Receptor proteins on the cell surface comprise the first layer in signal-relays that control whether a cell grows, divides, specializes, or dies. When a receptor binds to its target molecule, it initiates an internal cascade of protein messengers that directs the cell to activate a genetic program. For example, when a growth factor like the epidermal growth factor (EGF) binds to a growth receptor, the signal induces the cell to grow and divide via the genetic growth program. If instead a neuronal growth factor (NGF) is added to the extracellular environment, a cell differentiates (transforms) into a neuron.

This seems like a straightforward system, but scientists were surprised to find that the internal signals for growth (triggered by EGF) and differentiation (triggered by NGF) are sent to the nucleus via the same exact proteins, known as ERKs. To biologists, this is like going to a busy restaurant and ordering a hamburger without giving the server your name or describing what you want on the burger. How could the server get the order right or expect to get it back to the correct customer? The same kinds of questions could be asked of cellular signaling systems. There simply isn’t enough information communicated—or so it seems. Despite the potential for scrambled instructions, biological systems get it right. But how do cellular signals produce the correct genetic “order”?

By studying the activation of the internal signaling proteins over time, German researchers at European Molecular Biology Laboratory noticed emerging patterns. When they hit (bio-slang for “dosed”) rat brain cells with EGF, the ERK protein spiked in activation and then dropped back to pre-stimulated levels within fifteen minutes (equivalent to a dot in Morse code), causing the cells to grow and divide.² When NGF was used instead, ERK spiked and remained elevated for nearly an hour (similar to a dash), causing the cells to differentiate. It turns out the signal types (ERK profiles) produced by each growth factor send different messages to the cell, thus, prompting different activities. Somehow the cells use this telegraph-like signaling to communicate information.

To confirm their theory that the signal types control cell behavior, the research team molecularly cross-wired the systems so that each growth factor would produce the opposite ERK profile. Would cell responses be decided by the growth factor or by the signal type? Somewhat surprisingly, the researchers found that the signal type was the deciding factor. Even if hit with NGF, cells wired for a spike and quick recovery grew and divided; whereas when wired for a sustained signal, cells hit with EGF transformed into neurons.

Just like a telegraph system, these cells demonstrate that the intensity of the signal over time, not the initiator type, conveys the critical information. (See here³ for the technical review on this work). The advent of molecular systems biology has just begun to uncover this new level of elegance in biological systems. As this field of study develops, researchers are likely to uncover even more examples of sophisticated natural gene circuits.

The ability of cells to make accurate decisions via complex signal-processing strategies demonstrates that biological systems possess design. Further, experiments such as those conducted by the German research team lend insight into potential therapeutic strategies for reregulating diseased cells. Over one third of human cancers and many other diseases are known to result from improper activation of cellular programs via the described ERK pathway.

Understanding how cells make decisions gives researchers the tools they need to appropriately design therapies for intervention in improper responses like cancer. As our knowledge of biological strategies improves, the more we see how nature reveals intricate designs and further builds the case for a merciful Creator.

Endnotes

Silvia D. M. Santos, Peter J. Verveer, and Philippe I. H. Bastiaens, “Growth Factor-Induced MAPK Network Topology Shapes Erk Response Determining PC-12 Cell Fate,” Nature Cell Biology 9, no. 3 (March 2007): 324–30.
Ibid.
Boris N. Kholodenko, “Untangling the Signalling Wires,” Nature Cell Biology 9, no. 3 (March 2007): 247–49.

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Biology-Inspired Adhesion

Jeff Zweerink — Wed, 03 Mar 2010 08:00:00 +0000

Ever wanted to scale a shear wall without worrying about losing your grip? How about meander across the ceiling? Thanks to inspiration from beetles and some hard work in the lab, equipment for such purposes may be at hand.

Accomplishing this type of gravity-defying feat requires a lightweight device with strong and repeatable adhesion that also easily detaches. Combining all four requirements into one piece of equipment has proven formidable for scientists, but beetle feet have led two Cornell researchers to a possible solution. The leaf beetle, in particular, uses the surface tension of water to adhere to surfaces. By making numerous tiny water bridges between its feet and the surface, the beetle generates an adhesive force 100 times its own weight. Yet, by using a peeling motion the beetle can quickly “unstick” its legs. Mimicking this design concept, the scientists fabricated a one-square-inch device capable of suspending 30 grams using only the power supplied by a 9V battery.

The prototype device consists of three plates. The top plate contains one thousand holes, each the size of a human hair, and the bottom plate holds a water reservoir. The middle plate consists of a porous layer that pumps water in a specific direction when voltage is applied. When the voltage is briefly switched on, water squeezes through each hole and forms a bridge to the target surface. The cumulative force resulting from the surface tension of the water bridges provides the adhesion. Briefly reversing the voltage pumps the water back into the reservoir, thus, breaking the bond.

According to the authors of the paper submitted to the PNAS,1 the adhesive force grows as the density of the holes grows. They estimate that the same device with one million holes (each with diameters even smaller than a human hair) could hold up more than 15 pounds. Such an apparatus covering the bottom of a standard size 12 shoe could suspend more than 500 pounds and a quick toggle of a switch would apply or release the “stickiness.” Furthermore, the whole piece of equipment would weigh a few pounds at most.

This discovery represents a growing trend of biomimicry, the utilization of designs found in nature to build devices better than previously conceived human ideas. Past advances took advantage of other beetle adhesion mechanisms, others used amoeba behavior to design better transport networks. Why do our human minds draw inspiration from other living organisms to build superior technology? And, why does our ability to draw inspiration increase as our scientific knowledge increases? I think it is difficult to answer these questions within a strictly naturalistic worldview. However, such questions find ready answers if a divine Being created all life and then fashioned humanity in His image.

Endnotes

Michael J. Vogel and Paul H. Steen, “Capillarity-based Switchable Adhesion”, Proceedings of the National Academy of Science, preprint (February 3, 2010), doi: 10.1073/pnas.0914720107.

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Error Control Coding in Biology Implies Design, Part 4 (of 5)

Guest Writer — Fri, 12 Dec 2008 08:00:00 +0000

Anyone up for tic-tac-toe and genetics? It’s not exactly a game, but grab a cup of coffee and let’s explore the intriguing design in genetic systems.

In parts 1, 2, and 3 of this series, we observed three features of genetic systems that suggest design. In this article we look at isomorphic systems to find yet another analogy in the genetic code.

Analogy: Genetic Code-Like (GCL) Binary Representation

Recall the genetic code mapping table discussed in part 1 and part 2 of this series. This table describes the mapping between the 64 codons and the 20 amino acids.

Researchers in Venice, Italy, have identified a specific and unique number system and have used it to mathematically model the genetic code. In this work, the 64 codons and the 20 amino acids are assigned to numerical elements within the system, referred to as the genetic code-like (GCL) binary representation. The GCL binary representation is a unique model that holds true to the specific redundancy features in the natural genetic code mapping.¹ It is a mathematical model of the underlining physical/chemical processes related to genetic information processing—a so-called structural isomorphism.

An isomorphism is a one-to-one correspondence between the elements of two sets such that the result of an operation on elements of one set corresponds to the result of the analogous operation on their images in the other set. If two sets are isomorphic with respect to certain properties, then those properties that are true of one of the sets must also be true of the other.

For example, a six-sided die and a bag from which a number 1 through 6 is chosen are isomorphic. As another example, tic-tac-toe and the “game of 15” are isomorphic. In the game of 15, players take turns saying a number between 1 and 9. Numbers may not be repeated. Both players aim to say three numbers that add up to 15. Although perhaps not obvious, the defining characteristics of this number game are identical to those of tic-tac-toe. It turns out that both games are based on the well-known (to mathematicians) magic square.

The GCL binary representation and the genetic code are also isomorphic systems (sets). So, characteristics that are true of the GCL binary representation must also be true of the genetic code. (See here and here for more details of isomorphic systems.)

What are the characteristics of the GCL binary representation? The European researchers noted that this mathematical model exhibits:²

Palindromic symmetry
Parity symmetry
Organized redundancy
A rich mathematical structure

Such elegant symmetry, organization, and structure speak of a code that has been designed for a purpose—no mere afterthought of evolutionary chance events.

Also, the GCL binary representation makes possible the existence of error detection/correction codes that operate along the strands of DNA. A parity code (as discussed in part 3 of this series) is one example of such a technique.

If a parity code or similar technique functions along strands of DNA using the GCL binary representation, then dependence must exist in the genetic data along the strand. In other words, the data must be correlated to some degree.

Assuming the GCL binary representation and using two different robust statistical analysis methods, the research team discovered significant short- and long-range correlation peaks in actual DNA sequences. These results confirm that actual DNA sequences using this specific model satisfy a basic prerequisite for such error-minimizing techniques.

The team noted that “an error-control mechanism implies the organization of the redundancy in a mathematically structured way,” and that “[t]he genetic code exhibits a strong mathematical structure that is difficult to put in relation with biological advantages other than error correction.”

Thus, scientific advance has uncovered a peculiar and unique mathematical model that accounts for the key properties of the genetic code. This model exhibits symmetry, organized redundancy, and a mathematical structure that would be vital for the existence of error-coding techniques operating along the DNA strands. Actual DNA data tested using this model gives a strong hint that such further error-coding techniques may very well exist and provides impetus for future study in this area. Purposeful creation seems a reasonable conclusion.

Part 5 (the last entry) of this series will discuss the impact of these analogies on William Paley’s watchmaker argument.

Keith McPherson

Keith McPherson received his Master of Science in Electrical Engineering from Georgia Institute of Technology in 1993, and currently works as an electrical engineer in Melbourne, FL, in the fields of communications and signal processing.

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Endnotes

It describes exactly the 1st level of degeneracy (i.e., redundancy) in the natural genetic code (i.e., the number of codons which map to specific amino acids), and gives deep insight into the 2nd level of degeneracy (i.e., the association between specific codons and specific amino acids).
A full treatment of how the GCL binary representation displays these features is very technical and difficult to communicate without active use of visual aids. Nevertheless, this note is a brief attempt. See here for the necessary visual aid. Table 3 shows the actual GCL binary representation of the natural genetic code. The numerical elements in the model are associated with biochemical elements in the genetic code. The whole numbers 0–23 along the table edges map to amino acids. The 6-bit binary strings map to codons. The degeneracy number is shown in the center of the table, along with the amino acids coded for. The degeneracy number indicates how many different codons code for each particular amino acid. A careful inspection will show that all 64 codons are present, along with all 20 amino acids. Palindromic symmetry is seen as a reflection through the middle of the table in a left to right fashion. Palindromic amino acids are always associated in pairs. For example, tryptophan (Trp) and methionine (Met) are a pair of palindromic amino acids. Note that if the 6-bit codewords are folded on top of each other through the middle of the table, they form bitwise negated pairs, reflecting a very peculiar mathematical structure for palindromic symmetry. Also note the symmetry evident in the parity, again through the middle of the table. The light entries are odd parity (odd number of 1’s) and the dark entries are even parity (even number of 1’s). The interested reader is referred to the journal paper for further details.

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Error Control Coding in Biology Implies Design, Part 3 (of 5)

Guest Writer — Fri, 05 Dec 2008 08:00:00 +0000

Parts 1 and2 of this series observed that biological genetic systems function as information-processing systems, and a case was made for coding techniques that protect the genetic data. As a specific example, the genetic code appears designed to minimize the effects of errors in a way that is directly analogous to Gray codes. Gray codes are commonly used by engineers to protect data processed by many modern digital communications systems.

We now turn our attention to another analogy.

Analogy: Complementary Base Pairing Parity Code

A useful concept to have in mind to better appreciate this analogy is Hamming distance.¹ Good codes reduce the probability of error by increasing the minimum Hamming distance between codewords relative to the distance that would have been obtained if no code (or a less powerful code) was used. This minimum distance of a code is like the weakest link in a chain and, therefore, characterizes the code’s strength.

As the code’s minimum distance is increased, it is easier for a recipient to detect a message with no errors. Consider a scavenger hunt game where you “hide” something for a toddler to find, for example, a large blue ball among a pile of smaller white balls. The intent is to make the target blue ball stand out among the others. This exercise is roughly analogous to high Hamming distance. The large blue ball (the intended message) among a number of smaller white balls (errors) exhibits a relatively large dissimilarity, and so the blue ball is easily visible and detectable.

On the other hand, as the code’s minimum distance is decreased the recipient is more likely to make errors in message detection. Now consider an adult scavenger hunt where objects are “hidden” in plain sight because they blend in so nicely in their surroundings. It is difficult to “see” an object you are looking for, even if you are staring straight at it. The intent here is to make the object blend in with the objects around it. This is roughly analogous to low Hamming distance. The target object (the intended message) is hidden among very similar objects (errors) and exhibits a relatively large similarity. Thus, the desired object is not easily visible and detectable.

In digital communications perhaps one of the simplest examples of an error-detecting code (see here and here) is an even parity code. This code is used on a binary message frame (i.e., a sequence of binary digits, 1’s and 0’s). In this code, one parity bit is added to a message frame and its value is chosen to “round” the frame “value” out, to make the message stand out more among the possibilities by increasing the code’s minimum distance (like the example with the blue ball). This allows the recipient to more easily detect that an error has occurred if it detects a “non-round value” (i.e., a white ball). Values that are “round” or “non-round” have precise mathematical definitions in coding theory. The main point is that all parity codes, and the even parity code in particular, impart a precise mathematical structure to the protected (coded) data. This mathematical structure increases the minimum distance between valid codewords and allows for more robust error detection. (See here for more information on parity codes used in engineering.)

Recall that the DNA is a double-strand structure, specifically a double helix. And the four nucleotide bases in the DNA chemical alphabet are A, C, G, and T. Nucleotides A and T are complementary, as are G and C, and these pairings are the basis for the double-stranded structure, where each strand carries the same information as the other strand. Research into the chemical bonds at work between these complementary base pairs reveals that the natural nucleotide alphabet has been chosen to minimize the probability that a given nucleotide on one strand will be incorrectly paired with a partner on the opposite strand. More specifically, a researcher found that the nucleotides used for the DNA chemical alphabet actually form an even parity code. (See research work here and here.)

A convention was used to consistently assign binary values (i.e., 1 or 0) to certain features associated with the four nucleotides that comprise the chemical alphabet in DNA. The relevant features are the relative size of the nucleotide, and its donor-acceptor pattern. The donor-acceptor pattern is relevant for hydrogen bonding. Hydrogen bonds are formed between a nucleotide and its partner on the opposite strand. Careful observation of the resulting binary values reveals that they form an even bit parity code. To be more precise, the relative size of a nucleotide is related to its hydrogen donor-acceptor (D/A) pattern as a parity bit.²

In nature, there are actually 16 nucleotides. Why did nature settle on these specific four, and why only four? At first glance, one may impugn a designer’s inefficiency because there are more nucleotides that could have been used to increase the size of the alphabet, leading to a more efficient genetic code and protein synthesis mechanism. In fact, there has been speculation along these lines. The researcher used the same binary convention to determine the binary representation for the other 12 nucleotides. Upon close inspection, he found that the 16 total nucleotides can be arranged using this framework as eight belonging to the even parity set, and eight belonging to the odd parity set, where the natural alphabet uses a subset of the even parity nucleotides. “Nucleotide Hamming distance” is maximized as a result, as is typical for parity codes, leading to a robust mechanism for error minimization.

The resulting specific four nucleotides emerge as optimal. From this perspective, the genetic machinery is directly analogous to a 1-bit, even-parity code decoder as used routinely in engineering applications. Such a decoder is the optimal way to recover the intended message when a parity code has been used.

The parity code model is an interpretation that readily flows from the relevant chemical bonds that bind the complementary nucleotide pairs. It is a way to mathematically represent or express what is happening at a chemical level. The researcher comments that:

The purine-pyrimidine and hydrogen donor-acceptor patterns governing nucleotide recognition are shown to correspond formally to a digital error-detecting (parity) code, suggesting that factors other than physiochemical issues alone shaped the natural nucleotide alphabet…When this error-coding approach is coupled with chemical constraints, the natural alphabet of A, C, G, and T emerges as the optimal solution for nucleotides.³

In summary, we have seen that an error-detecting code (a parity code) is at work to minimize incorrect bonding between nucleotide pairs on the complementary strands of DNA. For DNA replication to be accurate it is critical that the strands be the true complement of each other. We furthermore note that the specific code used by DNA, an even parity code, is a mainstay in modern communications systems.

The next article in this series will examine another coding analogy between modern digital communications systems and the genetic information-processing system.

Keith McPherson

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Endnotes

See here and here for more information on Hamming distance.
Refer to Figure 1 here. A and G are larger nucleotides called purines, C and T are smaller nucleotides called pyrimidines. Lone pairs are rich in electrons and participate in weak bonding with hydrogen atoms to form hydrogen bonds between complementary pairs. Hydrogen atoms are also referred to as hydrogen donors, and lone pairs as hydrogen acceptors. A binary “1” was assigned for hydrogen (i.e., hydrogen donors, D). A binary “0” was assigned to “lone pairs” (i.e., hydrogen acceptors, A). A binary “1” was assigned to the smaller nucleotides (i.e., pyrimidines). A binary “0” was assigned to the larger nucleotides (i.e., purines).
Dónall A. Mac Dónaill, “A Parity Code interpretation of Nucleotide Alphabet Composition,” ChemComm 18 (2002): 2062-63.

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Feedback Control in Biology

Guest Writer — Thu, 19 Nov 2009 11:00:00 +0000

Calcium levels of pregnant cows in Iowa may not be the first image that comes to mind when Christian apologists invoke supernatural design, but that appears to be the case based on a recent feedback control study. As an electrical engineer, I can appreciate the level of design and fine-tuning required in making such systems work properly. The next several paragraphs examine and compare (in some technical detail) human-designed control systems with natural ones found in cows.

In engineering, feedback control is a common method used to maintain specified levels of important system outputs and quantities in the face of a variety of disturbances. A very typical design approach used to accomplish this is a 2nd order control system using a Proportional plus Integral (PI) controller. In this scheme, the overall system, the PI controller, and the two associated controller constants¹ are very carefully designed to produce the desired transient system response. Such a response seeks an appropriate trade-off between the settling time, overshoot, and oscillatory behavior, to name a few characteristics of interest. An optimally designed control system will ensure that the system output tracks to the desired level after a disturbance within a reasonable time and with a reasonable transient characteristic.

(See here for a schematic diagram of a typical feedback control system.)

Apparently, God is an engineer, and a very good one. The very same scheme of feedback control as described above and the network topology reflected in the diagram has been found in mammals for calcium homeostasis, which is the regulation of plasma calcium concentration (calcium concentration in the blood). (See hereand here for the researchers’ reports.)

In the biological world, calcium homeostasis is necessary for the survival of mammals. The plasma calcium concentration needs to be maintained very tightly in mammals² in spite of various disturbances related to diet or the calcium demand to meet milk production and fetal growth needs. Researchers studied the transient response of calcium concentration of a total of 38 dairy cows during a 10-day period surrounding the process of calving. They concluded that the cows were able to maintain a life-essential level of calcium in the blood only with the aid of the functional equivalent of a 2nd order PI feedback control system. As their studies show, such a control system can be realistically implemented biologically using two hormones. This biological control system is a strict and rigorous analogy to 2nd order PI control systems widely used in engineering applications.

For one engineering example, I have recently completed the design and characterization of a 2nd order PI control system for a communications application. The two controller constants were judiciously calculated, tested, and the final set chosen to produce the best transient response, thereby optimizing the overall system performance. A scaled response of this control system was compared with the calcium concentration experimental data ³ and was found to match very closely. ⁴ This suggests to me that in addition to the design implied by having the correct network topology, the two effective constants for the biological controller have likewise been judiciously “chosen” to produce the best transient response and, thereby, provide optimal results for the mammals subject to stringent calcium concentration regulatory demands.

This analogy between manmade and natural control systems implies stringent design at various levels, irreducible complexity, and fine-tuning. The researchers seem to recognize the level of complexity involved.

Yet, the most important implication of integral feedback does not lie in producing a simple dynamical model that agrees well with the actual data. Rather, it lies in the severe structural constraints that it imposes in the underlying homeostatic mechanism.

The “severe structural constraints” associated with the homeostatic mechanism, coupled with the seemingly optimal controller constants, display a system that has been designed and fine-tuned.

The researchers also reference the results of other research in conjunction with their own.

These results as well as those reported in this article seem to point to the prevalence of integral control in mechanisms where physiological quantities must be maintained with a narrow range despite internal and external disturbances.

Finally, they suggest that “[f]urther work is needed to catalog and uncover the architecture of these systems where integral control is at work.”

This analogy specifically, and feedback control in biological systems in general, reinvigorates William Paley’s famous Watchmaker argument. The biological feedback control system discussed in this article is the direct counterpart to feedback control systems used in engineering, systems that without question are recognized to require design and exquisite fine-tuning by intelligent agents. Consistent logic suggests that a divine Intelligent Agent is responsible for similar systems found in biology.

Such purposeful design and fine-tuning fits nicely with Christian theism and with the Reasons To Believe creation model.

Keith McPherson

Endnotes

For a typical 2nd order PI control system, the designer has two constants to specify as part of the system design: the proportional constant (Kp), and the integral constant (Ki).
0.085-0.105 g/l in humans and 0.08-0.1 g/l in dairy cows.
See Figure 2.b for the biological transient response.
In addition to the characteristic shape of the two responses, the damping ratio was investigated. The so-called damping ratio is a parameter used to design and characterize control systems in engineering. The mentioned engineering control system was designed for a damping ratio of exactly 1.0. Analysis and side by side comparison of the two transient responses suggest that the damping ratio of the calcium homeostasis PI control system is slightly larger than 1.0, but probably no larger than 1.1. Damping ratios on this order are known to yield good system results in many engineering contexts. In engineering applications, the damping ratio typically lies between 0.5 and 2. A system with a damping ratio of 1.0 is referred to as a critically damped system. These systems converge faster than any other without oscillating. See here for more information on damping.

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Biology’s Big Bangs

Fazale “Fuz” Rana — Thu, 13 Dec 2007 11:00:00 +0000

Explosive Innovations Point to a Creator’s Role in Life’s History

My wife loves to garden. She gets the most pleasure from designing the landscape around our house. Since we have lived in our home, she has reworked the gardens in our yard several times. These redesigns, of course, involve putting in new plants and taking out old ones.

To my dismay, Amy doesn’t limit her activities to small plants and bushes. Her redesigns frequently involve trees. I can’t tell you how many trees I have taken out and planted in the last ten years. I dislike nothing more than cutting down a tree and taking out the stump. (In fact, as I write this piece there is a tree trunk in our backyard awaiting my attention.)

A recent “big picture” analysis of life’s history forces evolutionary biologists to rethink the landscape of life’s history. Instead of life unfurling in a gradual, branching tree-like fashion, the data indicates that the major transitions in the history of life happened explosively. This latest analysis chops down the evolutionary tree of life, one of the most enduring metaphors for evolutionary biology; and at the same time comports nicely with the RTB creation model for life’s history.

According to Eugene Koonin, the author of the article, phlyogenetic studies indicate that biological innovations happen abruptly in life’s history without any trace of intermediate forms. Examples include: 1) the origin of protein folds; 2) the origin of cells; 3) origin of bacteria and archaea and major divisions within these domains; 4) origin of eukaryotes and major eukaryotic divisions; and 5) the origin of animal phyla. These major transitions appear to occur rapidly. Once completed, diversification takes place in a slow tree-like manner.

Koonin proposes a mechanism to account for this pattern of changes. He suggests that at certain periods in life’s history extensive genetic “scrambling” (horizontal gene transfer, recombination, fusion, fission, transposition) took place. Most of this genetic chaos proved nonproductive, but on rare occasions—by chance—a stable genetic combination emerged. These robust islands of genetic novelty represent a transition to a new regime of biological complexity.

Koonin points out that his idea merely extends the speculations made by other biologists such as the late Stephen Jay Gould, Niles Eldredge, Lynn Margulis, Carl Woese, and Thomas Cavalier Smith, who have all suggested the identical pattern for aspects of the history of the biosphere.

The primary implication of Koonin’s proposal is that no evolutionary tree of life exists.

Koonin’s proposal is intriguing, and on the surface makes sense, but upon more careful reflection raises a number of questions. Why is this pattern of explosive innovation repeated throughout life’s history? What causes the genetic scrambling to take place? Why doesn’t this process happen continuously throughout the history of life? Why should the mechanism Koonin envisions ever result in coherent changes that lead to stable genetic islands that represent discontinuous increases in biological complexity?

Interestingly, the pattern Koonin identifies is similar to the one predicted by RTB’s creation model. This model asserts that a Creator intervened repeatedly to bring about progressive changes in life’s history. This intervention should produce discontinuities in the history of life and take place without any trace of transitional forms. If nothing else, Koonin’s analysis affirms that the patterns of the history of the biosphere match the predictions of the RTB model and validate the notion that a Creator must be responsible for life’s history.

Koonin’s hypothesis has one other interesting consequence for RTB’s creation model. Could he have identified a possible means by which God could have brought about biological innovations? Could the Creator have engaged in extensive genetic engineering to create? Perhaps He reworked preexisting genetic templates to generate new levels of biological complexity, a type of Divine genetic engineering. From an evolutionary perspective, it would look as if dramatic and rapid bouts of horizontal gene transfer, recombination, fusion, fission, and transposition took place. From a creation model vantage point, these changes are not random, but carefully orchestrated by the Creator.

This suggestion is fun speculation. What is certain, however, is that the landscape of life’s history has been reworked and the new design no longer features the evolutionary tree of life. Now that’s a tree stump I don’t mind removing.

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Biology Textbooks Get It Wrong on Life’s Origin

Fazale “Fuz” Rana — Wed, 01 Aug 2007 16:22:00 +0000

Chemist Stanley L. Miller died in late May (March 7, 1930 – May 20, 2007).

If you don’t recognize the name, you are probably familiar with his famous experiment. Virtually every high school biology text describes the work Miller performed in the early 1950s. He filled the confines of a carefully assembled glass apparatus with methane, ammonia, and hydrogen after diligently excluding oxygen from the system. At that time, scientists thought the gases Miller used in his experimental setup had existed in early Earth’s atmosphere. A boiling flask of water connected to the glassware introduced water vapor into the headspace and simulated early Earth’s oceans. Miller passed a continuous electric discharge through the gas mix and showed that the primitive atmosphere of the early Earth could, in principle, generate amino acids, one of the key building blocks of life.

Miller’s work was the first experimental validation of the Oparin-Haldane hypothesis. This model, based on the principles of chemical evolution, was one of the first scientific models to describe a mechanistic pathway to life from simple chemical compounds.

Stanley Miller’s experiment launched origin-of-life studies as an exciting area of experimental research. His success has prompted scientists over the course of the last 50+ years to conduct similar experiments seeking chemical routes to other critical biomolecules.

Status of the Miller-Urey Experiment

Today, the Miller-Urey experiment is considered to be irrelevant to the origin-of-life question. Current understanding of the composition of early Earth’s atmosphere differs significantly from the gas mix used by Miller. Most planetary scientists now think that the Earth’s primeval atmosphere consisted of carbon dioxide, nitrogen, and water vapor. Laboratory experiments indicate that this gas mixture is incapable of yielding organic materials in Miller-Urey-type experiments.

In May 2003 origin-of-life researchers Jeffrey Bada and Antonio Lazcano, long-time associates of Miller, wrote an essay for Science (May 2, 2003, pp. 745-746) commemorating the 50-year anniversary of the publication of Miller’s initial results. They pointed out that the Miller-Urey experiment has historical significance, but not scientific importance in contemporary origin-of-life thought. Bada and Lazcano wrote:

Is the “prebiotic soup” theory a reasonable explanation for the emergence of life? Contemporary geoscientists tend to doubt that the primitive atmosphere had the highly reducing composition used by Miller in 1953.

In his book Biogenesis, origin-of-life researcher Noam Lahav passes similar judgment:

The prebiotic conditions assumed by Miller and Urey were essentially those of a reducing atmosphere. Under slightly reducing conditions, the Miller-Urey reaction does not produce amino acids, nor does it produce the chemicals that may serve as the predecessors of other important biopolymer building blocks. Thus, by challenging the assumption of a reducing atmosphere, we challenge the very existence of the “prebiotic soup”, with its richness of biologically important organic compounds.

For many people, the generation of amino acids from simple chemical compounds thought to be present in early Earth’s atmosphere meant that life could originate all on its own without the need for a Creator. Work done on the early planetary conditions of Earth in the intervening decades between Miller’s famous experiment and his death, however, have invalidated this famous experiment and its support for an evolutionary explanation for life’s origin, in spite of what textbooks report.

For more detailed discussions on other problems confronting the evolutionary paradigm for the origin of life see the article “Origins-of-Life Predictions Face Off: Evolution Vs. Biblical Creation” and the book Origins of Life: Biblical and Evolutionary Models Face Off.

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