A 2020 paper in the journal Science by Jia Zheng et al., titled “Selection enhances protein evolvability by increasing mutational robustness and foldability,” purports to demonstrate how natural selection itself can create the conditions for future evolution. The authors claim that strong selection for an existing function coincidentally favors proteins that are more robust and “foldable,” which in turn makes them more “evolvable”—better able to acquire new functions later. While presented as a victory for neo-Darwinian theory, a critical analysis reveals that the study’s experimental design sidesteps the fundamental problems of evolutionary theory and, in fact, provides a stunningly clear illustration of the principles of intelligent design and the pervasive reality of genetic decay. The results do not demonstrate the creative power of an unguided process but rather the necessity of foresight, engineering, and intelligent intervention to achieve even minor functional modifications in a biological system.
A Fair Summary of the Research
The researchers conducted a two-phase directed evolution experiment on Yellow Fluorescent Protein (YFP) expressed in E. coli.
In Phase I, they created three sets of populations and subjected them to different selection pressures for four “generations”:
- Strong Selection (S): Only the top ~20% of cells with the brightest yellow fluorescence were allowed to survive.
- Weak Selection (W): Any cell that fluoresced above a background level was allowed to survive.
- No Selection (N): Populations were subject to neutral drift with no selection for fluorescence.
In Phase II, all populations from Phase I were then subjected to the same strong selection pressure, but for a new, related function: green fluorescence.
The key finding was that the ‘S’ populations, which had been under strong selection for the original yellow function, evolved the new green function much more rapidly and effectively than the ‘W’ or ‘N’ populations. The authors determined that this was because strong selection in Phase I had favored mutations that increased the protein’s “foldability” (the efficiency of its folding into a functional shape) and its “mutational robustness” (its tolerance for new mutations). This pre-acquired robustness then buffered the destabilizing effects of the new “neofunctionalizing” mutations required for green fluorescence, accelerating their fixation and allowing the ‘S’ group to climb the new adaptive peak faster.
The Core Analysis: An Experiment in Intelligent Design
The authors’ conclusion—that Darwinian selection can build its own capacity for future success—is an extrapolation that the experiment’s own design and data cannot support. The study is a textbook example of illegitimate investigator interference and actually provides more evidence for genetic entropy and the need for a designer than for the creative power of unguided nature.
1. The “Assume a Protein” Fallacy: Modifying, Not Originating, Information
The most significant flaw in extrapolating these results to molecules-to-man evolution is that the experiment begins with a fully-formed, highly complex, information-rich protein (YFP). This is a classic “assume a gene” fallacy. The central problem for evolutionary theory is not explaining how a fluorescent protein can be tweaked to fluoresce at a slightly different wavelength, but how a non-fluorescent sequence of amino acids could, through unguided mutations, find the one functional fold out of a hyper-astronomical number of non-functional possibilities (what Douglas Axe’s research calculated as a 1 in 10^77 chance for a modest 150-amino-acid protein). This study explains the modification of existing specified information, not its origin. It is analogous to claiming you’ve explained the origin of the English language by showing you can change the word “RUN” to “RAN.” The real work was done by whoever wrote the original language.
2. Investigator Interference: The Ghost in the Machine
This experiment is not a simulation of “natural” selection; it is a demonstration of highly intelligent, goal-directed design.
- Foresight-Driven Selection: A blind, unguided process has no future goal. The researchers, however, selected for a known target: green fluorescence.
- Artificial Selection Mechanism: “Natural selection” was performed by a Fluorescence-Activated Cell Sorter (FACS), a piece of high-end laboratory equipment that uses lasers, optics, and fluidics to precisely identify and isolate individual cells based on a pre-programmed threshold of fluorescence. This is not a blind force of nature; it is a sophisticated, intelligently designed sorting machine executing the will of the scientists.
- Artificial Mutation Rate: The researchers used mutagenic PCR to induce an extremely high mutation rate, forcing the system to explore sequence space at a pace unrealistic for most of natural history.
The outcome was determined not by an unguided process, but by the researchers’ intelligence, which designed the protocol, defined the selection criteria, and deployed technology to execute the plan. They are the “intelligent designers” in this scenario.
3. A Stark Demonstration of Genetic Entropy
The experiment’s own control groups provide a devastating confirmation of Dr. John Sanford’s principle of Genetic Entropy.
- The No Selection (N) group, left to drift, saw its yellow fluorescence plummet, indicating a rapid accumulation of damaging mutations that destroyed the protein’s function.
- The Weak Selection (W) group, where selection was not stringent, also saw an initial fitness drop and was unable to improve. It could only maintain a low level of function against the constant onslaught of deleterious mutations.
This is the real lesson of the paper: in the absence of intense, artificial, heroic, and intelligent purifying selection, the default trajectory of a complex, information-bearing system is downward into functional decay. The paper doesn’t show evolution creating; it shows that an intelligent selector must work relentlessly just to prevent a system from falling apart.
The Alternative Explanation: Robustness as an Engineering Feature
The paper’s findings are more powerfully and parsimoniously explained by a design-based framework. The “evolvability” observed is not a lucky byproduct of blind selection, but a predictable feature of good engineering.
Applying the principle of vera causa—appealing to causes known to have the power to produce the effect in question—we can compare the competing hypotheses.
- The Darwinian Hypothesis: A blind, unguided process of mutation and selection, which this very experiment showed leads to rapid decay under realistic (weak) selection, somehow also creates “evolvability.” This is not a known causal power; in fact, it contradicts the experiment’s own data.
- The Design Hypothesis: Intelligent agents design systems with robustness and modularity to allow for future modification and adaptation. This is a known causal power we observe in every complex technology humans create, from software libraries to engine platforms.
The YFP protein behaved like a well-engineered piece of code. It was “front-loaded” with a degree of robustness (what engineers would call good design) that allowed it to tolerate minor modifications without crashing. The “evolvability” discovered by the researchers is simply a testament to the quality of the original design of the fluorescent protein family. This provides a powerful model for how life adapts within a “kind.” Organisms were designed with pre-engineered adaptive capacity and robust systems that allow them to unpack genetic diversity and respond to environmental challenges—but only within the limits of their original design. The shift from yellow to green fluorescence is a minor variation on a pre-existing theme, not the invention of a new symphony.
Conclusion
The Zheng et al. paper, while an excellent piece of protein engineering, fails as evidence for the creative power of unguided evolution. It begins far too late in the game, starting with a fully-formed protein and thus ignoring the critical problem of information origin. Its methodology relies entirely on the foresight and intervention of the researchers, making it a case study in intelligent design, not natural selection.
Most profoundly, its data provides a compelling confirmation of genetic entropy, showing that without intense, artificial selection, complex functional systems inevitably and rapidly decay. The observed “evolvability” is not an emergent property of a blind Darwinian process but is better understood as “robustness”—a hallmark of good engineering. The protein was designed with the capacity for limited variation, a principle that explains the rapid, but bounded, adaptation we see in nature. When stripped of its evolutionary narrative, the evidence points not to a blind watchmaker, but to a master engineer whose creations were built to last, yet now degrade in a fallen world.
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