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Chapter 4 : The Study of Microbial Adaptation by Long-Term Experimental Evolution
Author:
Vaughn S. Cooper1
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Affiliations:
1: Department of Microbiology, 212 Rudman Hall, University of New Hampshire, Durham, NH 03824
Content Type: Monograph
Publication Year:
2006
Category: Bacterial Pathogenesis; Microbial Genetics and Molecular Biology
Book DOI:
10.1128/9781555815622
Chapter DOI:
10.1128/9781555815622.ch4
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The Study of Microbial Adaptation by Long-Term Experimental Evolution, Page 1 of 2
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Abstract:
Experimental evolution, the research approach discussed in this chapter, permits study of the fundamental processes of adaptation that underlie microbial evolution under controlled laboratory conditions. Long-term evolution experiments with microbes have displayed numerous elements of the complexity of natural systems and have therefore permitted the study of fundamental questions in evolutionary biology, ecology, physiology, and genetics. This chapter focuses on a few long-term, open-ended studies as well as other relevant experiments that best illustrate specific problems. Despite many excellent studies using fungal and viral models, the chapter is focused primarily on bacterial systems with occasional mention of viral systems. Specific topics under consideration include the dynamics of adaptation, the genetic and physiological bases of fitness, causes of specialization and functional losses, evolution of mutation rates, and models of the evolution of virulence. At the end of the chapter, the author addresses prospects for future experiments to study the evolution of pathogens. The author refers repeatedly to two longterm experiments throughout this chapter. The first involves the long-term experimental evolution of 12 populations of Escherichia coli B, originally founded by Richard Lenski in 1988. The second experiment of this review was derived from this first one. The chapter discusses selected examples in which the mechanisms and consequences of genetic adaptation were discovered. The evidence that important steps in microbial evolution have been driven significantly, and perhaps mostly, by interspecies recombination continues to grow.
Citation:
Cooper V.
2006.
The Study of Microbial Adaptation by Long-Term Experimental Evolution,
p 55-81.
In
Seifert H, DiRita V (ed),
Evolution of Microbial Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815622.ch4
Key Concept Ranking
- Bacterial Evolution
- 0.5490394
- Population Genetics
- 0.5490394
- Microbial Evolution
- 0.5076751
- Microbial Genetics
- 0.4700483
- Yellow Fever Vaccine
- 0.45861357
- Sabin Polio Vaccine
- 0.4222699
0.5490394
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The Study of Microbial Adaptation by Long-Term Experimental Evolution
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Citation:
Cooper V.
2006.
The Study of Microbial Adaptation by Long-Term Experimental Evolution,
p 55-81.
In
Seifert H, DiRita V (ed),
Evolution of Microbial Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815622.ch4
/content/10.1128/9781555815622.ch04.ch04figure01
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Citation:
Cooper V.
2006.
The Study of Microbial Adaptation by Long-Term Experimental Evolution,
p 55-81.
In
Seifert H, DiRita V (ed),
Evolution of Microbial Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815622.ch4
/content/10.1128/9781555815622.ch04.ch04figure02
Untitled
10.1128/9781555815622/e0057-02_thmb.gif
10.1128/9781555815622/e0057-02.gif
Untitled
Citation:
Cooper V.
2006.
The Study of Microbial Adaptation by Long-Term Experimental Evolution,
p 55-81.
In
Seifert H, DiRita V (ed),
Evolution of Microbial Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815622.ch4
/content/10.1128/9781555815622.ch04.ch04fig01
FIGURE 1
Trajectory for mean fitness of 12 E. coli populations during 20,000 generations in minimal glucose medium. Each point is the population mean measured relative to the ancestor with fivefold replication. Curves are the best fit of a hyperbolic model.
10.1128/9781555815622/f0060-01_thmb.gif
10.1128/9781555815622/f0060-01.gif
FIGURE 1
Trajectory for mean fitness of 12 E. coli populations during 20,000 generations in minimal glucose medium. Each point is the population mean measured relative to the ancestor with fivefold replication. Curves are the best fit of a hyperbolic model.
Citation:
Cooper V.
2006.
The Study of Microbial Adaptation by Long-Term Experimental Evolution,
p 55-81.
In
Seifert H, DiRita V (ed),
Evolution of Microbial Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815622.ch4
/content/10.1128/9781555815622.ch04.ch04fig02
FIGURE 2
Evolution of fitness during 1,000 generations in maltose, after 2,000 generations of prior evolution in glucose. (A) Derived versus ancestral values for mean fitness in the 36 experimental populations. Symbols A through L reflect 12 different progenitor genotypes. (B) Relative contributions of adaptation, chance, and history to mean fitness (triangles) and fitness after (circles) 1,000 generations in maltose. Error bars represent 95% confidence intervals. Reprinted from reference
118
with permission.
10.1128/9781555815622/f0062-01_thmb.gif
10.1128/9781555815622/f0062-01.gif
FIGURE 2
Evolution of fitness during 1,000 generations in maltose, after 2,000 generations of prior evolution in glucose. (A) Derived versus ancestral values for mean fitness in the 36 experimental populations. Symbols A through L reflect 12 different progenitor genotypes. (B) Relative contributions of adaptation, chance, and history to mean fitness (triangles) and fitness after (circles) 1,000 generations in maltose. Error bars represent 95% confidence intervals. Reprinted from reference 118 with permission.
Citation:
Cooper V.
2006.
The Study of Microbial Adaptation by Long-Term Experimental Evolution,
p 55-81.
In
Seifert H, DiRita V (ed),
Evolution of Microbial Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815622.ch4
/content/10.1128/9781555815622.ch04.ch04fig03
FIGURE 3
A Wrightian landscape, illustrating that maladaptive “valleys” may separate two adaptive “peaks” of unequal relative value. A Fisherian landscape, on the other hand, would be dominated by a single adaptive peak. See reference
99
for a more detailed discussion of these alternative population genetic models.
10.1128/9781555815622/f0063-01_thmb.gif
10.1128/9781555815622/f0063-01.gif
FIGURE 3
A Wrightian landscape, illustrating that maladaptive “valleys” may separate two adaptive “peaks” of unequal relative value. A Fisherian landscape, on the other hand, would be dominated by a single adaptive peak. See reference 99 for a more detailed discussion of these alternative population genetic models.
Citation:
Cooper V.
2006.
The Study of Microbial Adaptation by Long-Term Experimental Evolution,
p 55-81.
In
Seifert H, DiRita V (ed),
Evolution of Microbial Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815622.ch4
/content/10.1128/9781555815622.ch04.ch04fig04
FIGURE 4
Punctuated evolution caused by periodic selection of beneficial mutations, which produced correlated increases in cell size. Data are from one population of Escherichia coli adapting to a minimal laboratory environment. Reprinted from reference
41
with permission.
10.1128/9781555815622/f0065-01_thmb.gif
10.1128/9781555815622/f0065-01.gif
FIGURE 4
Punctuated evolution caused by periodic selection of beneficial mutations, which produced correlated increases in cell size. Data are from one population of Escherichia coli adapting to a minimal laboratory environment. Reprinted from reference 41 with permission.
Citation:
Cooper V.
2006.
The Study of Microbial Adaptation by Long-Term Experimental Evolution,
p 55-81.
In
Seifert H, DiRita V (ed),
Evolution of Microbial Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815622.ch4
/content/10.1128/9781555815622.ch04.ch04fig05
FIGURE 5
Frequency of Rbs– cells over time in the 12 evolving LT populations. Seven of 12 populations became 100% Rbs– by generation 500, which is best explained by genetic linkage to other “big-benefit” mutations (genetic hitchhiking). In the remaining five populations, ribose function acts as a marker for other selective sweeps (periodic selection), including positive selection on the Rbs– mutation itself. Adapted from reference
26
.
10.1128/9781555815622/f0069-01_thmb.gif
10.1128/9781555815622/f0069-01.gif
FIGURE 5
Frequency of Rbs– cells over time in the 12 evolving LT populations. Seven of 12 populations became 100% Rbs– by generation 500, which is best explained by genetic linkage to other “big-benefit” mutations (genetic hitchhiking). In the remaining five populations, ribose function acts as a marker for other selective sweeps (periodic selection), including positive selection on the Rbs– mutation itself. Adapted from reference 26 .
Citation:
Cooper V.
2006.
The Study of Microbial Adaptation by Long-Term Experimental Evolution,
p 55-81.
In
Seifert H, DiRita V (ed),
Evolution of Microbial Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815622.ch4
/content/10.1128/9781555815622.ch04.ch04fig06
FIGURE 6
Nonsynonymous mutations in spoT in eight independently evolved E. coli populations. Only the variable amino acid residues are shown, with the ancestor listed first and the eight mutant alleles shown below. Four other populations retained the ancestral sequence. Reprinted from reference
21
with permission.
10.1128/9781555815622/f0072-01_thmb.gif
10.1128/9781555815622/f0072-01.gif
FIGURE 6
Nonsynonymous mutations in spoT in eight independently evolved E. coli populations. Only the variable amino acid residues are shown, with the ancestor listed first and the eight mutant alleles shown below. Four other populations retained the ancestral sequence. Reprinted from reference 21 with permission.
Citation:
Cooper V.
2006.
The Study of Microbial Adaptation by Long-Term Experimental Evolution,
p 55-81.
In
Seifert H, DiRita V (ed),
Evolution of Microbial Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815622.ch4
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