Biology · Evolutionary Processes & Adaptation
Experimental and observed evolution, including resistance
Evolution can be investigated while populations reproduce. Researchers can compare starting material with descendants, record conditions and test alternative explanations. A change observed under one set of conditions is evidence to analyse, not a licence to assume every future population will repeat the same outcome.
The introductory inheritance chapter distinguishes alleles, genotypes and phenotypes. Meiosis explains segregation and crossing over; the DNA chapter explains sequence changes. Fractions and simple multiplication are enough for the constructed examples here. No example represents a measured natural population unless explicitly identified as published research.
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Use lineage history, controls and direct observations to test evolutionary explanations, including the origin and spread of resistance.
When a variant arose can change how many descendants it has
In 1943, Salvador Luria and Max Delbrück examined bacterial resistance to a virus, or bacteriophage. Their comparison addressed whether resistance variants arose before the viral challenge or only as an induced response to it. Uneven numbers of resistant descendants among independently growing groups supported the existence of variants before exposure in that studied system.
An early sequence change can be inherited by a large clone, while a later change has fewer opportunities to produce descendants before the comparison. Therefore, counting resistant individuals is not the same as counting independent mutation events. One event can give many resistant descendants.
The original lineage diagram illustrates that logic without reproducing the experiment. It follows four rounds of equal binary division from one starting cell and assumes faithful inheritance, no death and only one assigned variant event. An event in one cell at generation 1 leaves three further divisions, yielding eight variant descendants. An event in one cell at generation 3 leaves one division, yielding two.
The historical result does not establish a constant mutation rate under every condition or prove that all resistance variants always arise before any exposure. Mutation mechanisms can depend on conditions, as the preceding lesson explains. The test separated specific hypotheses in a particular system.
One early origin can leave more descendants
Read the diagram in words
Two complete constructed four-generation binary trees differ only in the assigned generation when one S cell changes to R.
Early event
| Cell identity | Generation | Inherited variant |
|---|---|---|
| early-g0-i0 | 0 | S |
| early-g1-i0 | 1 | R |
| early-g1-i1 | 1 | S |
| early-g2-i0 | 2 | R |
| early-g2-i1 | 2 | R |
| early-g2-i2 | 2 | S |
| early-g2-i3 | 2 | S |
| early-g3-i0 | 3 | R |
| early-g3-i1 | 3 | R |
| early-g3-i2 | 3 | R |
| early-g3-i3 | 3 | R |
| early-g3-i4 | 3 | S |
| early-g3-i5 | 3 | S |
| early-g3-i6 | 3 | S |
| early-g3-i7 | 3 | S |
| early-g4-i0 | 4 | R |
| early-g4-i1 | 4 | R |
| early-g4-i2 | 4 | R |
| early-g4-i3 | 4 | R |
| early-g4-i4 | 4 | R |
| early-g4-i5 | 4 | R |
| early-g4-i6 | 4 | R |
| early-g4-i7 | 4 | R |
| early-g4-i8 | 4 | S |
| early-g4-i9 | 4 | S |
| early-g4-i10 | 4 | S |
| early-g4-i11 | 4 | S |
| early-g4-i12 | 4 | S |
| early-g4-i13 | 4 | S |
| early-g4-i14 | 4 | S |
| early-g4-i15 | 4 | S |
| Parent cell | Daughter cell |
|---|---|
| early-g0-i0 | early-g1-i0 |
| early-g0-i0 | early-g1-i1 |
| early-g1-i0 | early-g2-i0 |
| early-g1-i0 | early-g2-i1 |
| early-g1-i1 | early-g2-i2 |
| early-g1-i1 | early-g2-i3 |
| early-g2-i0 | early-g3-i0 |
| early-g2-i0 | early-g3-i1 |
| early-g2-i1 | early-g3-i2 |
| early-g2-i1 | early-g3-i3 |
| early-g2-i2 | early-g3-i4 |
| early-g2-i2 | early-g3-i5 |
| early-g2-i3 | early-g3-i6 |
| early-g2-i3 | early-g3-i7 |
| early-g3-i0 | early-g4-i0 |
| early-g3-i0 | early-g4-i1 |
| early-g3-i1 | early-g4-i2 |
| early-g3-i1 | early-g4-i3 |
| early-g3-i2 | early-g4-i4 |
| early-g3-i2 | early-g4-i5 |
| early-g3-i3 | early-g4-i6 |
| early-g3-i3 | early-g4-i7 |
| early-g3-i4 | early-g4-i8 |
| early-g3-i4 | early-g4-i9 |
| early-g3-i5 | early-g4-i10 |
| early-g3-i5 | early-g4-i11 |
| early-g3-i6 | early-g4-i12 |
| early-g3-i6 | early-g4-i13 |
| early-g3-i7 | early-g4-i14 |
| early-g3-i7 | early-g4-i15 |
One assigned event at generation 1: early-g1-i0. 8 R, 8 S; one assigned mutation event
Late event
| Cell identity | Generation | Inherited variant |
|---|---|---|
| late-g0-i0 | 0 | S |
| late-g1-i0 | 1 | S |
| late-g1-i1 | 1 | S |
| late-g2-i0 | 2 | S |
| late-g2-i1 | 2 | S |
| late-g2-i2 | 2 | S |
| late-g2-i3 | 2 | S |
| late-g3-i0 | 3 | R |
| late-g3-i1 | 3 | S |
| late-g3-i2 | 3 | S |
| late-g3-i3 | 3 | S |
| late-g3-i4 | 3 | S |
| late-g3-i5 | 3 | S |
| late-g3-i6 | 3 | S |
| late-g3-i7 | 3 | S |
| late-g4-i0 | 4 | R |
| late-g4-i1 | 4 | R |
| late-g4-i2 | 4 | S |
| late-g4-i3 | 4 | S |
| late-g4-i4 | 4 | S |
| late-g4-i5 | 4 | S |
| late-g4-i6 | 4 | S |
| late-g4-i7 | 4 | S |
| late-g4-i8 | 4 | S |
| late-g4-i9 | 4 | S |
| late-g4-i10 | 4 | S |
| late-g4-i11 | 4 | S |
| late-g4-i12 | 4 | S |
| late-g4-i13 | 4 | S |
| late-g4-i14 | 4 | S |
| late-g4-i15 | 4 | S |
| Parent cell | Daughter cell |
|---|---|
| late-g0-i0 | late-g1-i0 |
| late-g0-i0 | late-g1-i1 |
| late-g1-i0 | late-g2-i0 |
| late-g1-i0 | late-g2-i1 |
| late-g1-i1 | late-g2-i2 |
| late-g1-i1 | late-g2-i3 |
| late-g2-i0 | late-g3-i0 |
| late-g2-i0 | late-g3-i1 |
| late-g2-i1 | late-g3-i2 |
| late-g2-i1 | late-g3-i3 |
| late-g2-i2 | late-g3-i4 |
| late-g2-i2 | late-g3-i5 |
| late-g2-i3 | late-g3-i6 |
| late-g2-i3 | late-g3-i7 |
| late-g3-i0 | late-g4-i0 |
| late-g3-i0 | late-g4-i1 |
| late-g3-i1 | late-g4-i2 |
| late-g3-i1 | late-g4-i3 |
| late-g3-i2 | late-g4-i4 |
| late-g3-i2 | late-g4-i5 |
| late-g3-i3 | late-g4-i6 |
| late-g3-i3 | late-g4-i7 |
| late-g3-i4 | late-g4-i8 |
| late-g3-i4 | late-g4-i9 |
| late-g3-i5 | late-g4-i10 |
| late-g3-i5 | late-g4-i11 |
| late-g3-i6 | late-g4-i12 |
| late-g3-i6 | late-g4-i13 |
| late-g3-i7 | late-g4-i14 |
| late-g3-i7 | late-g4-i15 |
One assigned event at generation 3: late-g3-i0. 2 R, 14 S; one assigned mutation event
Resistance has an origin and a subsequent population history
Antimicrobial resistance concerns microbes with reduced susceptibility to a relevant antimicrobial; it does not mean the patient’s body has become resistant. In antibiotic comparisons, resistant bacteria can grow under conditions that inhibit susceptible alternatives. Genetic changes can alter a target, transport or other cellular functions, and resistance-associated material can also be acquired from other microbes.
A selective condition can increase the representation of heritable resistant variants because their descendants contribute more than susceptible alternatives under that condition. That enrichment need not create the original change. Moving resistant microbes or transferring resistance-associated genetic material adds routes of spread beyond a local lineage’s reproduction.
A surviving cell is not, by that observation alone, proof of a new heritable resistance mutation. Temporary physiological states, different exposure and other explanations may affect survival. Establishing heritability and the relevant mechanism requires appropriate evidence. This chapter supplies evolutionary reasoning, not treatment decisions or a procedure for growing resistant microbes.
A resistant lineage can originate, expand and move
Read the diagram in words
Distinct pathways show a sequence change in one microbe, inheritance by descendants, and genetic material entering a recipient from another microbe. A selective context changes reproductive representation rather than reaching back to choose the original change.
| Selected entity | Inherited material or context |
|---|---|
| Starting microbe | Initial genetic material |
| Microbe with an inherited variant | Changed genetic material |
| Descendants inherit the variant | Variant in descendants |
| Another microbial source | Resistance-associated material |
| Recipient acquiring inherited material | Acquired material |
| Changed reproductive representation | Inherited variation in a population |
| Relevant selective context | Different reproductive contributions under specified conditions |
| Source | Destination | Relationship |
|---|---|---|
| Starting microbe | Microbe with an inherited variant | Variant arises |
| Microbe with an inherited variant | Descendants inherit the variant | Inherited during reproduction |
| Another microbial source | Recipient acquiring inherited material | Genetic material enters another microbe |
| Descendants inherit the variant | Changed reproductive representation | Contributes descendants |
| Recipient acquiring inherited material | Changed reproductive representation | Contributes descendants if inherited |
| Relevant selective context | Changed reproductive representation | Selection affects representation |
Replay experiments can test the role of history
A 2008 study by Zachary Blount, Christina Borland and Richard Lenski examined the emergence of citrate use in an experimental Escherichia coli lineage under oxygen-containing conditions. Comparisons using stored earlier material investigated whether previous evolutionary changes affected the later outcome. The results supported a role for historical genetic background in that studied innovation.
The point is not that a population consciously prepared for a future trait. Earlier variants arose and spread under their own conditions; they could change the consequences or accessibility of later changes. Replaying from different earlier backgrounds tests that dependence more directly than inventing a story after seeing the endpoint.
Even carefully controlled experimental populations are finite and have specific environments. Repeated populations need not reach identical outcomes. Their results can reveal mechanisms and constraints, while extrapolation to other species, habitats or clinical situations needs additional evidence. The diagram represents the comparison logic, not the study’s measured success frequencies.
Stored earlier material can test historical dependence
Read the diagram in words
A source lineage changes through time; retained samples of different earlier backgrounds separately seed repeated comparisons under the same specified assay context.
| Source | Destination | Relationship |
|---|---|---|
| Earlier background A | Later background B | Inherited changes over time |
| Later background B | Subsequent source lineage | Further lineage history |
| Earlier background A | Retained A material | Retain material |
| Later background B | Retained B material | Retain material |
| Retained A material | Independent comparisons from A | Start comparisons from A |
| Retained B material | Independent comparisons from B | Start comparisons from B |
Same specified assay context; compare inherited outcomes
Design comparisons that distinguish explanations
For a field population, record what changed, what was sampled and how inherited variation was identified. Compare environments, reproductive outcomes and possible movement between populations. For an experimental population, ancestral material and repeated independent lineages can help separate inherited change from immediate environmental effects.
An increase at a locus, a changed character and a reproductive advantage are related observations that still answer different questions. Evidence becomes more persuasive when those observations form a tested causal account and plausible alternatives are checked. A negative result can also narrow an explanation: failure to repeat an outcome may reveal dependence on history or conditions.
Worked example
Count events separately from descendants
In the constructed early-event tree, one variant cell at generation 1 becomes 2, then 4, then 8 variant cells by generation 4. In the late-event tree, one variant cell at generation 3 becomes 2 by generation 4. Each full tree ends with 16 cells: eight variants and eight other cells, or two variants and fourteen others.
Both trees contain one assigned mutation event. The final variant frequencies are 8/16 = 0.50 and 2/16 = 0.125. Their difference follows from timing under this model, without a difference in division rate or an extra mutation. These small deterministic trees are not estimates of real mutation rates or the distribution in Luria and Delbrück’s data.
Check your understanding
Does eight resistant descendants necessarily mean eight independent resistance mutations?
Show reasoning
No. A single inherited change can expand through a clone. Lineage relationships and the timing of changes help distinguish the number of origins from the number of descendants.
Why compare an evolved phenotype with ancestral material under the same assay conditions?
Show reasoning
It helps separate an inherited difference from a difference caused merely by the immediate environment or measurement. Appropriate replication and other controls are still needed; the comparison is not sufficient for every mechanism claim.
If only one of several experimental lineages develops a new trait, has the evidence for evolution failed?
Show reasoning
No. The observed inherited change remains evidence. Different outcomes can reveal the influence of mutation supply, chance and history. A mechanism does not have to guarantee the same endpoint in every finite lineage to operate.
What to carry forward
Observed evolution is tested through inherited differences, reproductive histories and explicit comparisons; origins, enrichment and spread are separate parts of a resistance explanation.
References
Resources supporting this lesson’s explanations and examples.
- Mutations of Bacteria from Virus Sensitivity to Virus Resistance (Genetics 28(6), 491–511, 1943; DOI 10.1093/genetics/28.6.491)Salvador E. Luria and Max DelbrückOriginal research
- Salvador Luria and Max Delbrück on Random Mutation and Fluctuation Tests (Genetics 202(2), 367–368, 2016; DOI 10.1534/genetics.115.186163)Andrew MurrayAuthor historical perspective
- Historical contingency and the evolution of a key innovation in an experimental population of Escherichia coli (PNAS 105(23), 7899–7906, 2008; DOI 10.1073/pnas.0803151105)Zachary D. Blount, Christina Z. Borland and Richard E. LenskiOriginal research
- About Antimicrobial Resistance (Institutional explanation dated 2025-01-31; inspected 2026-10-12)United States Centers for Disease Control and PreventionInstitutional resource
- Mutation as a Stress Response and the Regulation of Evolvability (Critical Reviews in Biochemistry and Molecular Biology 42(5), 399–435, 2007; DOI 10.1080/10409230701648502)Rodrigo S. Galhardo, P. J. Hastings and Susan M. RosenbergAuthor scientific review
- Definitions and guidelines for research on antibiotic persistence (Nature Reviews Microbiology 17, 441–448, 2019; DOI 10.1038/s41579-019-0196-3)Nathalie Q. Balaban and international coauthorsAuthor consensus statement