1. Announcements

2. Microbial evolution I evolution in Action

3. Fitness and Natural selection exercise
Definition of fitness: Fitness is a trait that determines the probability you will contribute a quantity of progeny to the next generation.

4. Learning outcomes
Describe examples of microbial evolution occurring in the laboratory, the environment, and in medicine
Based on population parameters such as mutation rates, and population size, and selection coefficients, be able to predict the rate of evolution by natural selection.
Be able to explain how, spatial structure, clonal interference, trait complexity, and hitchhiking affect the rate and outcomes of microbial evolution
Choose the correct technique or approach for addressing questions about microbial evolution.

5. Calculating rate of evolution in large asexual population
Tau = number of generations until mutant reaches desired population size
= (log2 Nt)/S
Does Tau tell you how much time evolution takes?
W is relative fitness S

6. Problem 1: rate of compensatory mutation evolution
You have just invented a mutant that degrades toxic benzene, but this comes at a cost to its fitness. How long do you have to propagate it in benzene before a compensatory mutation arises and takes over?
Mutation rate = mutation rate = ;
population size = 1e8
(m=mutant, c=compensatory mutant)
1/10,000 mutations is compensatory for mutant defect
Scenario 1: Wm = 1; Wc = 1.1
Scenario 2: Wm = 1; Wc = 1.5

7. Problem 2: Slower growth rate
You want to go on vacation, so you put your culture in the fridge. Your species can grow in the fridge, but it grows at 25% its normal rate.
Does this slow down the rate of evolution? Why or why not?

8. Problem 3: Effect of mutation rate
You want to get the compensatory mutation faster, so you add a mutagen to the culture. The mutation rate is now 10 times higher. How will this affect the rate of evolution?

9. Problem 4: Two compensatory mutants at same time
By chance, 2 different compensatory mutants arise at the same time. How does this affect the rate at which the most beneficial mutant grows?
Wm=1; Wc1 = 1.2; Wc2=1.3
Wm=1; Wc1=1.2; Wc2=1.9

10. Problem 5: identifying the beneficial mutation
You sequence the genome of the mutant with the highest fitness to find out how it compensated for the tradeoff with benzene degradation.
The mutant has 2 mutations relative to the ancestor.
How would you test whether each is beneficial or not?
One mutation is beneficial and the other is neutral. How can you explain the fact that both took over the large population, given what you know about genetic drift?

11. Terms affecting rate of evolution in asexual populations
Clonal interference
Hitchhiking
Mutation rate
Selection coefficient

12. Spatial structure affects evolution of populations

13. Spatial structure affects evolution of populations

14. Spatial structure affects evolution of Cystic Fibrosis
Case study: Cystic fibrosis
Genetic disorder
Thick mucus in lungs
difficulty breathing
Lung infection and colonization
Ok. Today we are starting with another example of evolution, an example that is relevant to many people’s lives. We are going to come back to this example later when we talk about approaches to studying evolution…

15. Burkholderia evolves in biofilms in lab
The experiment
Evolved phenotypes

16. The evolutionary process on glass beads
This is a picture of one entire population of Burkholderia evolving. Think of this middle picture like the hockey table in the video. What do you see happening here?
This is an example of what evolution looks like when divergence occurs.
Population genomics and ecological structure of the biofilm community over time. Allele frequencies were determined at four time points (vertical dashed lines), and dynamics were interpolated. (A) Frequency of majority mutations belonging to the dominant haplotype throughout the community. (B) Mutational dynamics within and among niches. Each color transition represents a new haplotype (labeled as in Table 1), and color breadth shows haplotype frequency in the community, to scale. The earliest mutants arose on the ancestral genotype, and subsequent mutations evolved within the ecotypes that subdivided the community. Lines crossing ecotype boundaries (light blue lines) represent invasion of the dominant S haplotype into the R or W niche associated with novel mutations. Horizontal light blue lines highlight the ecological boundaries that evolved within this community. Additional low-frequency mutations were detected in the metagenomes and are reported in Table S1, and other mutants likely evolved before the first samples. *, R isolate with unknown niche-specifying mutation; **, W isolate with unknown niche-specifying mutation. (C) Dynamics of niche invasions by mutants of S over time. Each blue arrow represents the invasion of an S type into an R or W niche.
The researchers ended up with 5 of these, and this is just one example

17. Evolution in lab mimics lung

18. How does spatial structure affect evolutionary rates?

19. Experimental evolution of a complex trait with E. coli

20. Why did it take 30,000 generations for E. coli to evolve Cit+?

21. Zachary Blount studies evolution of citrate utilization in the Lenski lab

22. Citrate utilization required 3 mutations
Figure 17.26a Evolution of citrate utilization in E. coli.
A. One or more of the mutations accumulated over 30,000 generations potentiated evolution of the Cit+ trait. The Cit+ trait first appeared in about generation 31,000. Subsequent mutations refined the phenotype, increasing the rate of citrate utilization. Ball symbols indicate genomes from the population’s history that were sequenced for analysis. Source: Adapted from Zachary Blount et al Nature 489:513.

23. Genome rearrangements in citrate utilization
Figure 17.26b Evolution of citrate utilization in E. coli.
B. The Cit+ mutation. After 31,000 generations, a tandem duplication event placed a copy of the rnk promoter, which directs expression when oxygen is present, upstream of the citT gene encoding a citrate transporter that is normally expressed only without oxygen. This new rnk-citT module allows the CitT citrate transporter to be expressed during aerobic metabolism, giving the bacteria access to the citrate present in the medium. Source: Adapted from Zachary Blount et al Nature 489:513.