Experimental evolution

The outcome of selection for high and low oil content in the Illinois corn experiment.

William Dallinger

1880-1886

Selected for thermotolerance of microorganisms

60 F 158 F

How experimental evolution works

• Batch (serial) culture

• Chemostat

• Turbidostat

• Static culture (liquid or solid)

Chemostat

Chemostats select for nutrient affinity

Static culture

What are the key variables? (brainstorm)

• Population size (N), and effective population size (Ne)

• Mutation rate

• Recombination?

• Parasites?

• Constant or fluctuating environment?

• Mass-action or structured environment?

Some questions addressed by experimental evolution

• What is the tempo and mode of evolution? (gradual or punctuated, limits, etc?)

• What factors promote or constrain adaptation?• What are the consequences of adaptation?• What are the mechanisms of adaptation?• Is the mutation rate optimal or minimal?• How do mutations interact?

Is evolution repeatable?

“I call this experiment ‘replaying life’s tape.’ You press the rewind button and, making sure you thoroughly erase everything that actually happened, go back to any time and place in the past – say to the seas of the Burgess Shale. Then let the tape run again and see if the repetition looks at all like the original.”

“The bad news is that we cannot possibly perform the experiment…”

-S.J. Gould, Wonderful Life: the Burgess Shale and the nature of history (1989)

We CAN replay evolution

Replicate populations evolving under identical conditions address whether evolution is repeatable.

Do you predict phenotypic repeatability (parallelism)?

Do you predict genetic repeatability?

Some more questions

• Why has sex evolved?• Why do we age?• How does virulence evolve?• How does cooperation (or cheating) evolve?• How does speciation begin?• Is evolution Wrightian (many different outcomes)

or Fisherian (one universal solution)?• How do competitors coexist?

The most conspicuous evidence of evolution by natural selection is the fit of organisms to their environment.

Yet quantifying adaptation continues to elude biologists.

Adaptation may be quantified directly

Evolved

Ancestor

Day 0 Day 1

Plate on agar to determine the ratio of 1 : 2

Determine 1 : 2

Fitness = Ln [ N 1 (Day 1) / N1 (Day 0) ]

Ln [ N 2 (Day 1) / N2 (Day 0) ]

Generation 0 ------------------------- Generation 20,000+

Experimental Conditions

• 12 replicate cultures

• single genotype of Escherichia coli B

• daily serial transfer

• single resource and temperature

• no sex+

-

Mutation rate itself evolves in certain populations

Non-mutator

Mutator

Pop

ulat

ion

Sniegowski et al., Nature 387, 703-705 (1997)

Generations

Ara+3

Ara-4

Ara-2

0 2000 4000 6000 8000 10000

“Part of the folk wisdom of evolutionary biology is that specialization leads to adaptive decay

for environments outside the domain of specialization.”

-R.D. Holt, Evol. Ecol. (1996)

Q1: Is the “folk wisdom” true?

Does specialization lead to adaptive decay? (Can we find such an association?)

Specialization: adaptation by an organism to a subset of its original environment

Adaptive decay: decay in niche breadth that is associated with adaptation

Why is this association so elusive?

• To determine if specialization leads to adaptive decay, we need to:

• quantify adaptation

• know the history of adaptation

• Both have proven challenging in most natural and experimental systems.

Is adaptation associated with loss of function?

0 5000 10000 15000 20000

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

Fitn

ess

Generations

?

Important environmental factors

37° CGlucose

Time (Generations)

1.0

1.2

1.4

1.6

1.8

2.0

0 5000 10000 15000 20000

Fitn

ess

I used Biolog plates to measure diet breadth

What are the consequences of adaptation?

Hypothetical curves describing loss of function:

Tot

al C

atab

olic

Fun

ctio

n

0 5000 10000 15000 20000

MA

AP

MA*

Time (Generations)

Parallel and convergent changes across lineages are hallmarks of adaptive evolution

?

evolvedancestors

Is the pattern consistent with AP?Time (Generations)

Carbon source 2,000 10,000 20,000 bromosuccinic acid 7 11 12 D-alanine 1 3 6 D-malic acid 5 12 12 D-ribose 12 12 12 D-saccharic acid 9 11 11 D-serine 12 11 10 D-sorbitol 12 11 11 fructose-6-phosphate 11 10 9 fumaric acid 9 12 12 glucose-1-phosphate 12 11 10 glucose-6-phosphate 11 12 8 glucuronamide 0 4 8 L-asparagine 8 12 12 L-aspartic acid 9 12 12 L-glutamine 12 12 12 L-lactic acid 11 12 10 L-malic acid 7 12 12 malic acid 9 12 12 mono-methylsuccinate 2 12 12 mucic acid 12 8 9 P-hydroxyphenylacetic acid 5 12 11 succinic acid 9 12 12 uridine 12 12 10 Sum of parallel losses 9 16 16

Diet breadth decays over time

0 2,000 10,000 20,000Time (Generations)

Tot

al C

atab

olic

Fun

ctio

n

0

0.25

0.50

0.75

1.00

1.25 Red = mutators

White = non-mutators

Cooper and Lenski (2000) Nature 407:736-739.

Specialization in diet breadth was caused mostly by antagonistic pleiotropy

• Antagonistic pleiotropy:

– Most losses of catabolic function occurred in replicate populations (parallelism) and when adaptation was most rapid (early in the experiment).

• Mutation accumulation:

– Mutator populations tend to lose more catabolic functionality…

– …but this additional loss is not proportional to the increase in mutation rate.

Vm

ax

Generation time

Evolution of thermal niche

Temperature (C)

0

0.2

0.4

0.6

0.8

1

1.2

20 25 30 35 40

0

2,000

5,000

10,000

15,000

20,000

Cooper, Bennett, and Lenski. (2001) Evolution 55(5):889-896.

Adaptation to moderate temperatures leads to reduced performance at extreme temperatures

0.5

0.6

0.7

0.8

0.9

1

1.1

1.2

1.3

0 5,000 10,000 15,000 20,000

20

27

32

34.5

37

39

40

41

42

Time (Generations)

Rel

ativ

e V

max

Cooper, Bennett, and Lenski. (2001) Evolution 55(5):889-896.

Case study: What explains the rapid loss of D-ribose catabolism?

Time (Generations)

Fre

quen

cy R

bs

B

B B B

J

J

J

J

H

H

H

H

F

F

F F

Ñ

Ñ ÑÑ

É

É É É

Ç

Ç Ç Ç

Ö

Ö

Ö

Ö

M

M MM

â

â

ââ

Ö

Ö Ö Ö

7

7

7

7

0

0.2

0.4

0.6

0.8

1

0 500 1,000 1,500 2,000

Cooper, V. S., D. Schneider, M. Blot, and R. E. Lenski. (2001) J. Bact. 183: 2834–2841.

Ribose function is hypermutable

• Mutation rate for ribose loss = 5.4 X 10-5 per generation.

• 2-5 orders of magnitude higher than mutation rates measured for other traits.

• Time required to reach a frequency of 50% under mutation pressure alone = 18,519 generations.

1 k b

IS150

G5

G6

G76

Hinc

II

rbsD rbsA rbsC rbsB rbsK rbsR yieOleft IS150

adjacent sequenceright IS150

adjacent sequenceG77

Extent of the deletionAra-1

Hyb. (bp )

PCR (bp )

2,812 2,071

Ara-23,043 2,302

Ara-33,854 7,373

Ara-43,338 2,597

Ara-52,483 3,378

Ara-63,034 2,293

Ara+11,972 2,867

Ara+33,332 2,591

Ara+44,163 5,058

Ara+52,999 3,894

Ara+63,329 2,588

2,662 9,005 Ancestor

Hinc

II Hinc

II Hinc

II Hinc

II Hinc

II

A.

B.

G269

G268

G266

G267

Cooper, V. S., D. Schneider, M. Blot, and R. E. Lenski. (2001) J. Bact. 183: 2834–2841.

Rbs- mutation alone improves fitness

Independent Rbs- mutants of ancestor

Fitn

ess

1 2 3 4 5 6 70.98

0.99

1

1.01

1.02

1.03

1.04

1.05

What accounts for the rapid loss of ribose catabolism?

Time to 50% of population

• MA alone = 18,519 generations

• Selection = 1,774 generations

• Selection plus MA = 781 generations

• Genetic hitchhiking = priceless (< 500 generations)

0 5 10 15 20

0

1

2

3

4

5

6

7

8

Cat

abol

ic f

unct

ion

Time (1000 generations)

Loss of succinate, fumarate, malate function

• suite of functions compromised in part by IS insertion in pykF

• different pykF mutations found in other populations; same reversibility?

• suggests selection to regain succinate function and study of evolution of phenotypic plasticity

Summary

• Is specialization caused more by AP or MA?– Antagonistic pleiotropy explains the majority of change in

diet breadth and thermal range. – Mutation accumulation is only detectable among mutator

populations; may require more time?

• Should adaptive decay be “folk wisdom?”– Most functions were retained.– Selection in permissive environments may yield a greater

frequency of specialists.– The mechanisms responsible for loss of function cannot

be assumed.