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What Lenski’s Long-Term Evolution Experiment Actually Shows

What Lenski’s Long-Term Evolution Experiment Actually Shows

Apr 14, 2026
37 Years. 80,000 Generations. E. coli Is Still E. coli. — Fingerofthomas
Fingerofthomas Apologetics · Science & Faith
Evolution & Creation

37 Years. 80,000 Generations.
E. coli Is Still E. coli.

The world’s longest-running evolution experiment was supposed to prove Darwin right. What it actually showed is far more interesting.

5 min read · Science & Faith · fingerofthomas.org
37 Years Running
80K+ Generations
12 Populations
0 New Protein Folds
Genetic changes tracked across 80,000 generations of E. coli in the Lenski LTEE

Genetic changes tracked across 80,000 generations of E. coli in the Lenski Long-Term Evolution Experiment (LTEE) — the largest dataset of its kind in history.

In 1988, Richard Lenski launched an experiment with twelve populations of E. coli. Thirty-seven years have passed. The experiment has surpassed 80,000 generations — the equivalent of roughly 1.6 million human years.

Richard Lenski, evolutionary biologist, Michigan State University
Richard Lenski, Michigan State University. Founder of the LTEE — the most closely watched evolution experiment in history.

Richard Dawkins called it “a beautiful demonstration of evolution in action” in The Greatest Show on Earth. Jerry Coyne called it “a poke in the eye for creationists.” A Veritasium video with millions of views declared it “one of the most direct demonstrations of Darwinian adaptation by natural selection you can imagine.”

So after 80,000 generations, what has E. coli become?

Still E. coli. Unchanged in every fundamental way that matters for the theory of macroevolution.

First, Let’s Correct the Misunderstanding

Evolutionists often claim that Lenski’s experiment makes creationists uncomfortable. That isn’t true.

Creationism predicts microevolution — variation and adaptation within existing genetic information — from the outset. If a Creator designed organisms with flexibility to adapt to changing environments, it follows naturally that E. coli would optimize for a glucose-limited flask. What creationists contest is not the existence of natural selection. What they contest is the claim that natural selection can generate entirely new functional information from nothing.

For macroevolution — single cell to human — to be explained, we need to observe the spontaneous emergence of new protein folds, new biochemical pathways, and new developmental programs. Lenski’s experiment has failed to show any of these. That is the heart of the debate.

The Citrate Affair

The most celebrated finding of the LTEE is the emergence of aerobic citrate metabolism at around generation 31,500. A population that could not feed on citrate in the presence of oxygen gained that ability. Evolutionists called it “the origin of a new function.” Three facts deserve scrutiny.

Three Things the Headlines Missed
1

E. coli already metabolizes citrate. It does so under anaerobic conditions as part of its basic TCA cycle. What changed is that the repression of the citrate transporter gene (citT) under aerobic conditions was lifted. No new gene was created. An existing switch was turned on.

2

The identical mutation appears in as few as 12 generations under direct selection. In 2016, Van Hofwegen, Hovde, and Minnich (University of Idaho) published in the Journal of Bacteriology that when citrate was the sole carbon source, 46 independent Cit+ mutants appeared — all via the same mechanism: promoter capture of the existing citT gene. The reason it took 31,500 generations in Lenski’s lab was simply the absence of selection pressure, not the rarity of the mutation.

3

Delete citT, and the ability never appears — under any condition. The entire event was dependent on the pre-existing gene. Fellow evolutionary biologists John Roth and Sophie Maisnier-Patin confirmed this in a published commentary: Lenski’s “historical contingency” interpretation required reinterpretation. Creationists’ analysis was confirmed by evolutionary scientists themselves.

The 2024 Proto-Gene Discovery — A Real Breakthrough?

A 2024 analysis of LTEE genomes (Uz-Zaman et al., PLOS Biology) identified cases where previously unexpressed DNA regions had begun to be transcribed and translated — so-called “proto-genes.” Some evolutionists called this “evidence of de novo gene birth.”

Two critical limitations deserve attention.

First: these proto-genes were formed primarily by recruiting existing promoters. The regulatory information was not newly created; existing regulatory sequences were repositioned.

Second: the function of these transcripts remains unconfirmed. The paper itself acknowledges this. Transcription is not the same as function. A gene requires both stable expression and a beneficial function. This study demonstrated only the first.

Scribbling a few notes on a page is not the birth of a symphony.

The Tree of Life — Evolution and Creation
The Tree of Life: a central claim of macroevolution. For this narrative to hold, we need evidence of genuinely new genetic information — something the LTEE has not produced in 37 years of daily observation.
The Silence of 80,000 Generations
37 years · 12 populations · daily observation
✓  Observed
→Changes in gene regulation
→Optimization of existing pathways
→Loss of existing gene functions
→Increased cell size & growth speed
→Aerobic citrate use — existing gene switch
✗  Not Observed — Yet Required for Macroevolution
✗A new protein fold
✗A new biochemical pathway
✗A new cellular organelle
✗A fully novel functional gene unrelated to pre-existing genes
✗Any increase in functional information
⚖️
This is not silence. This is testimony. Macroevolution requires thousands of the items in the right column. The most controlled, longest-running evolution experiment in history — 37 years, 80,000 generations — produced not one.

A Question for Evolutionists

If a completely new protein fold had appeared in this experiment, how would the evolutionary community have responded? With enormous fanfare, no doubt. It did not appear. And on that point, the evolutionary community is quiet.

Lenski’s experiment continues. Jeffrey Barrick has taken it over and continues to press forward. Perhaps something new will emerge someday, they say. But is that expectation a scientific prediction — or a statement of faith?

What thirty-seven years of experiment has taught us is this: the information inside E. coli was there from the beginning. Natural selection can filter it. It cannot create what was never there.

E. coli is still E. coli.

After 80,000 generations, the most-watched bacterium in history has adapted — but never transformed. The mechanism for macroevolution has not appeared. The information was already there.

Want to go deeper?

Deep Dive — 37 Years. 80,000 Generations.
E. coli Is Still E. coli.

Read the Deep Dive

References

  1. Blount ZD, Borland CZ, Lenski RE. Historical contingency and the evolution of a key innovation in an experimental population of Escherichia coli. PNAS, 2008.
  2. Dawkins R. The Greatest Show on Earth. Bantam Books, 2009.
  3. Holmes B. Bacteria make major evolutionary shift in the lab. New Scientist, 2008.
  4. Blount ZD, Barrick JE, Davidson CJ, Lenski RE. Genomic analysis of a key innovation in an experimental E. coli population. Nature, 2012.
  5. Purdom G. A Poke in the Eye? Answers in Genesis, 2008.
  6. Van Hofwegen DJ, Hovde CJ, Minnich SA. Rapid evolution of citrate utilization by E. coli by direct selection requires citT and dctA. Journal of Bacteriology, 2016.
  7. Roth JR, Maisnier-Patin S. Reinterpreting long-term evolution experiments. Journal of Bacteriology, 2016.
  8. Uz-Zaman MH, D’Alton S, Barrick JE, Ochman H. Promoter recruitment drives the emergence of proto-genes in a long-term evolution experiment with E. coli. PLOS Biology, 2024.
  9. Chihoub D et al. The evolution of robustness and fragility during long-term bacterial adaptation. PNAS, 2025.
Five Problems with Dawkins’ Weasel Program

Five Problems with Dawkins’ Weasel Program

Apr 9, 2026
Five Problems with Dawkins’ Weasel Program
Evolution · Scientific Evidence

Five Problems with Dawkins’ Weasel Program

A clever simulation — but one that quietly smuggles in everything it claims to do without.

~5 min read 09 Apr 2026
Richard Dawkins
“Cumulative selection, by contrast, is a totally different process… it is the kind of selection that is cumulative, that builds up… It works by gradual degrees.”
— Richard Dawkins, The Blind Watchmaker (1986)

In The Blind Watchmaker (1986), Richard Dawkins introduced a computer simulation that became one of the most cited illustrations in evolutionary biology. Starting from a random 28-character string, the program converged on Shakespeare’s phrase “METHINKS IT IS LIKE A WEASEL” in just 43 generations. He called it cumulative selection — proof, he argued, that complexity can build itself without a designer.

It’s a compelling demonstration. But there are five serious problems with it as an argument for evolution.

Gen 1 WDLTMNLT DTJBKWIRZREZLMQCO P 0/28 correct
Gen 10 MDLDMNLS ITJISWHRZREZ MECS P 7/28 correct
Gen 30 METHINGS IT ISWLIKE B WECSEL 21/28 correct
Gen 43 METHINKS IT IS LIKE A WEASEL 28/28 ✓

White = correct letter position · Dark green = wrong position · Target phrase known in advance

01
Natural Selection Is Missing
Evolution requires two mechanisms: random mutation and natural selection. The Weasel program simulates only the first. Generation 1 produces a string like WDLTMNLT DTJBKWIRZREZLMQCO P — no functional proteins, no biological role whatsoever. In the real world, natural selection would eliminate this organism immediately, before it ever reproduced. In Dawkins’ simulation, it becomes a parent without question. Every intermediate stage survives automatically. The very mechanism that supposedly drives evolutionary progress has been silently removed.
02
The Junk DNA Prediction Has Failed
If the Weasel analogy maps to real biology, every organism at an intermediate stage should contain large amounts of non-functional DNA. Dawkins was for many years a prominent advocate of “junk DNA” — genomic sequences with no function, accumulating as evolutionary debris. In 2012, the ENCODE project found that roughly 80% of the human genome has at least one biochemical function. Sequences once dismissed as junk are now known to regulate gene expression, maintain chromosomal structure, and guide cell differentiation. The junk DNA argument is under significant revision.
03
The Fossil Record Doesn’t Match
If the Weasel model is correct, we should find continuous, gradual transitions in the fossil record — far more intermediate forms than finished ones. Even Stephen Jay Gould, Harvard paleontologist and one of the 20th century’s most prominent evolutionary biologists, acknowledged the problem:

“The evolutionary trees that adorn our textbooks have data only at the tips and nodes of their branches; the rest is inference, however reasonable, not the evidence of fossils.”

— Stephen Jay Gould, Natural History, Vol. 86 (1977)

Gould wasn’t rejecting evolution — he was proposing punctuated equilibrium to explain the gaps. But his acknowledgment stands: the fossil record does not show the unbroken chain of gradual transitions that the Weasel model predicts. And right now, the living world should also be populated by far more incomplete organisms than complete ones — creatures with half-formed wings, eyes in mid-development, hearts not yet connected. We simply don’t observe this.

The Weasel Program
🎯
Has a Target
Every generation is evaluated against a fixed, pre-defined phrase. Letters in the “right” position are preserved.
Real Evolution (as claimed)
🎲
Has No Target
No foresight. No destination. Selection simply preserves what happens to work better right now.
04
The Program Has a Goal — Evolution Doesn’t
Dawkins consistently argues that evolution is undirected — no foresight, no destination. The Weasel program does the exact opposite. It has a target phrase fixed from the very beginning. Every generation is evaluated against that target. Without it, there is no basis for deciding which letters are “right” and should be preserved.

A process converging on a predetermined goal is not evolution — it’s optimization. And optimization requires someone who set the objective. In attempting to show that complexity can arise without a designer, the Weasel program actually demonstrates exactly why a designer is necessary to generate complex, specified information.
05
Mutations Are Neither Random Nor Uniform
The Weasel program assumes mutations can occur at any position with equal probability. Real genomic mutation doesn’t work that way. Certain chemical changes (transitions) are far more frequent than others (transversions). And mutations cluster at hotspots — in the TP53 gene, around 70% of observed mutations occur at just 3–4 positions out of more than 1,000 base pairs.

Meanwhile, a 2025 Nature study (Yoo et al.) using whole-genome sequencing found that humans and chimpanzees differ by approximately 448 million nucleotides — roughly 14–14.9% of the total genome. This overturns the widely cited “1% difference” by a factor of 14. A biased, hotspot-concentrated mutation mechanism cannot plausibly account for divergence of this scale.
Problem Weasel Program Real Evolution
Natural selection ✗ All variants survive ✓ Most variants eliminated
Junk DNA ✗ Predicts vast non-functional sequences ENCODE: ~80% of genome is functional
Fossil record ✗ Predicts continuous gradual change Shows stasis + punctuated change (Gould)
Direction / goal ✗ Fixed target from step one Claimed to be completely undirected
Mutation realism ✗ Uniform random at all positions Biased, hotspot-concentrated

The Bottom Line

The Weasel program is mathematically elegant. But it works precisely because an intelligent programmer set the target, defined the selection criteria, and ran the process. Strip out the programmer — and you have no target, no selection basis, no reason for any letter to be preserved. Dawkins intended to show complexity arising without a designer. His program shows exactly what it looks like when a designer is generating complexity.

Read the Full Deep Dive
Richard Dawkins Weasel Program Junk DNA Creation Evolution

3 Fatal Flaws That Completely Destroy Evolution

3 Fatal Flaws That Completely Destroy Evolution

Apr 6, 2026
3 Reasons Evolution Cannot Be True — fingerofthomas
Apologetics · Faith & Reason
fingerofthomas
Evolution — from microorganism to complex life
Science & Faith

3 Reasons Evolution
Cannot Be True

fingerofthomas  ·  ~5 min read

Open any biology textbook and evolution is presented as settled fact. Students memorize it, accept it, and move on — because questioning it feels like questioning science itself. But when you actually examine the evidence, something surprising happens: the evidence doesn’t support it. In many cases, it actively contradicts it.

You don’t need a science degree to see this. You just need common sense and three basic ideas in mind.

Quick Primer

Big numbers are incomprehensibly big. The difference between 10⁻⁵⁰ and 10⁻¹⁰⁰ isn’t “twice as small” — it’s a gap our minds cannot picture. Predict the exact outcome of 100 coin flips in advance and the odds are 1 in 10³⁰. Every person on Earth, flipping non-stop, couldn’t expect it once in 24 trillion years.

DNA is code. Not metaphorically — literally. It is a four-letter digital language that stores and transmits biological instructions. Like any code, random changes don’t produce upgrades. They produce errors.

Probability compounds. When each step is already improbable, chaining steps together doesn’t help — it makes things exponentially worse.

With that in mind, here are the three big-picture reasons.

Reason One

The Math Doesn’t Work

Some of evolution’s own admirers have done the numbers — and the results are staggering.

Astronomer Fred Hoyle — who spent his career defending naturalistic cosmology — calculated the odds of a single functional protein assembling by chance at roughly 1 in 1040,000. The calculation shook him. He concluded that a designing intelligence behind life’s origin could not be dismissed on scientific grounds. He didn’t arrive there through religion. He arrived there through arithmetic.

1 in 1040,000 Fred Hoyle’s estimated odds of a single protein forming by chance

Douglas Axe (PhD, Cambridge) approached the same question more conservatively, asking only whether a short protein — just 150 amino acids — could fold into any functional shape at all, regardless of what that function might be. His answer: 1 in 1077.

And the simplest living cell requires not one protein but hundreds — all working together in precise, interdependent coordination.

Imagine closing your eyes, typing randomly, and producing working software. Now imagine that same software randomly upgrading itself into something more complex. Evolution demands exactly this logic — applied to systems vastly more intricate than any code humans have ever written.

Reason Two

Genetic Information Only Goes Down, Never Up

DNA as digital code
DNA: a four-letter digital language storing billions of instructions in every living cell.

For evolution to work, genetic information must increase over time. Single-celled bacteria must somehow gain the new instructions needed to eventually produce eyes, limbs, and brains. This is not a side detail — it is the central claim of the entire theory.

Here’s the problem: it has never been observed.

Richard Dawkins — the most publicly prominent voice for evolutionary biology in the world — was once asked on camera to give a single example of genetic information increasing through mutation. He went silent for ten seconds. He later published a lengthy written response, pointing to gene duplication as his answer: the process by which an existing gene is copied into the genome. But duplication reproduces what is already there. It does not write new instructions. Copying an existing page of code is not the same as authoring new code. The fundamental question — where does genuinely new, functional genetic information come from? — went unanswered.

Not a single mutation has been observed that adds a little information to the genome… The mutations we have observed are just what we would expect to see if the genome were deteriorating.
— Lee Spetner, MIT PhD · biophysicist, Johns Hopkins Applied Physics Laboratory

Evolutionists often point to natural selection as the engine here. But natural selection doesn’t create information — it only selects from information that already exists. It is a filter, not a generator. Watching a boulder roll downstream does not prove the boulder can travel uphill. The evidence consistently points in one direction: information degrades. It does not build itself.

Reason Three

The Fossil Record Tells the Wrong Story

The human evolution progression
The iconic march of human evolution — a story the fossil record itself has trouble telling.

If evolution happened gradually over millions of years, the fossils should show it: a smooth, continuous chain of transitional creatures, species slowly and visibly becoming other species. That is the prediction. That is not what we find.

And the people saying so are leading evolutionary scientists themselves.

The evolutionary trees that adorn our textbooks have data only at the tips and nodes of their branches; the rest is inference — not the evidence of fossils.
— Stephen Jay Gould · Harvard University
The fossil record does not convincingly document a single transition from one species to another.
— S. M. Stanley · Johns Hopkins University

The problem is sharpest at the Cambrian Explosion: virtually every major animal body plan appears in the fossil record suddenly, fully formed, with no gradual lead-up. Gould found this so troubling that he developed an entirely new theory — Punctuated Equilibrium — proposing that evolution happened in rapid bursts rather than gradually.

But rapid, large-scale changes in genetic information are statistically impossible (see Reason 1). Dawkins himself attacked Gould on precisely these grounds. The two dominant camps of evolutionary thought are caught in a direct contradiction — and neither side has resolved it.

So Why Do Most Scientists Still Accept It?

Because modern science operates under a methodological rule: only natural explanations are permitted. Supernatural causes are ruled out before any evidence is examined — not because the evidence eliminates them, but because the methodology does. Under those constraints, you have no choice but to explain the code without allowing for a programmer.

Evolution is a religion. This was true of evolution in the beginning, and it is still true of evolution today.
— Michael Ruse, philosopher of science · University of Guelph

The probability is impossible. The mechanism runs in the wrong direction. The fossil record shows the wrong pattern. Evolution is not a conclusion drawn from evidence — it’s a framework required by a prior philosophical commitment. Follow the evidence without that constraint, and it points somewhere very different.

🌊
Deeper waters ahead.

Enjoyed the overview? The deep dive unpacks every argument in full — sources, counterarguments, and all the details.

Read the Deep Dive →

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