Activity 1: Mitochondrial Evolution and Endosymbiosis

According to the mitochondrial endosymbiosis hypothesis, these organelles were once free-living but parasitic bacteria (protozoa?). One lineage of cells survived the initial infection by these pre-mitochondria, and the two began to co-evolve. Eventually, the parasitic interaction developed into a tight symbiosis, such that now neither can exist without the other. (A similar hypothesis has been developed for chloroplasts.)

Purpose

The goal of this project is to test the endosymbiosis hypothesis by seeing whether the distribution of mitochondria in protozoa is concordant with the protozoan phylogeny, and will give the student some appreciation of the evolutionary debate surrounding the origins of some eukaryotic organelles.

Procedure

Import rRNA sequence data for species from the following six groups: amoeboflagellates, diplomonads, euglenoids, kinetoplasts, microsporans, and parabasalians. Use Clustal_W to align the sequences and to construct a phylogeny.

Do the phylogenetic relationships match the distribution of mitochondria over these groups?

Group	Mitochondria present?
Amoeboflagellates	Yes
Diplomonads	No
Euglenoids	Yes
Kinetoplasts	Yes
Microsporans	No
Parabasalians	No

What other sources of molecular data might enable you examine to support or reject the evidence suggesting the endosymbiotic theory of organellar development in eukaryotes.

Activity 2: Relationship between HIV evolution and host progression to AIDS

As discussed in Module I, HIV evolves extensively within a human host. This evolution is thought to relate closely to how the virus actually causes AIDS. According to one theory, the antigenic diversity model, the key to understanding AIDS lies in the vir us’s generation of "escape mutants," mutants that are sufficiently different from the parental virus to go temporarily unrecognized by the host’s immune system. The host may soon develop a response to this new invader, but then the virus mutates again…and again…and again. Eventually, the immune system collapses under the diverse virus population, and the patient develops full-blown AIDS.

If this theory is correct, the rate at which a host progresses to AIDS will depend on the amount of viral evolution and diversity within that host. We would expect patients with diverse, rapidly evolving viral populations to progress more rapidly than oth ers whose viral populations remain relatively constant.

Purpose

The goal of this project is to evaluate the antigenic diversity model by testing one of its predictions, a positive correlation between HIV evolution and host progression rate.

Procedure

As in Module I, access the HIV nucleotide sequence database. For this study, however, we will be using viral sequence from only one subject at a time. Import the first subject’s sequences into the Workbench, align them, and perform phylogenetic reconstruc tion using Clustal_W. Print the resulting trees.

We will now need to measure the amount of viral evolution in this subject. One such measure consists of the maximum pairwise genetic distance between sequences from that subject. To determine this, return to the phylogenetic reconstruction menu and again select Clustal_W. On the following page, under the menu "Output format," select "Distance matrix." The output should consist of a large matrix, each entry of which represents the genetic distance between two of the host’s sequences. Search the matrix for its largest entry and record this value. Then delete the sequences from the Workbench, import the next subject’s sequences, and repeat the procedure until you have a measure of the amount of evolution for each of the 15 subjects.

Subjects are often divided into three progression categories: rapid progressors, who develop AIDS within two years of initial infection; moderate progressors, who develop AIDS within approximately ten years; and nonprogressors, whose immune systems remain functional for ten years or more. Based on your findings and on your understanding of the antigenic diversity model, which of the 15 subjects do you think were rapid progressors? Which do you think were nonprogressors?

After you have made these predictions, your instructor will provide the actual progression data. How accurate were your predictions? To what extent do the data support the antigenic diversity model? Can you think of ways to improve this analysis?

For instructor only:

The actual progression categories are:

Rapid Progressors	Moderate Progressors	Nonprogressors
Subject 1	Subject 5	Subject 2
Subject 3	Subject 6	Subject 12
Subject 4	Subject 7	Subject 13
Subject 10	Subject 8
Subject 11	Subject 9
Subject 15	Subject 14

An ANOVA test reveals no significant differences among categories’ evolutionary rates (F_2,12=1.46, P=0.27). This procedure therefore does not support the antigenic diversity model.

Possible ways to improve the analysis

1. Use protein rather than nucleotide sequences. This will eliminate from consideration synonymous substitutions undetectable by the immune system.

2. Use a better measure of the amount of evolution within a host. The present measure, d_max, is biased by several factors. First, it omits any consideration of the time interval over which a subject’s data are gathered. Second, it may be conf ounded with N, the number of sequences sampled from a given subject. On average, a subject with many sequences sampled will yield a larger d_max than will a patient with fewer sequences. Finally, and most importantly, this measure fails to refle ct the distribution of genetic distances. Subject 12, for example, has very low overall diversity, but one sequence () is very distant from all the others. The d_max measure detects this large distance but doesn’t account for all the smal l distances between the other sequences.

Subject	Number of sequences (N)	Maximum pairwise genetic distance (dmax)	Progression category
1	42	0.131
2	24	0.051
3	39	0.051
4	47	0.083
5	43	0.059
6	54	0.066
7	43	0.090
8	49	0.074
9	64	0.079
10	49	0.075
11	32	0.032
12	37	0.066
13	26	0.032
14	77	0.062
15	40	0.120

For the instructor:

Subject	Number of sequences (N)	Maximum pairwise genetic distance (dmax)	Progression category
1	42	0.131	Rapid
2	24	0.051	Nonprogressor
3	39	0.051	Rapid
4	47	0.083	Rapid
5	43	0.059	Moderate
6	54	0.066	Moderate
7	43	0.090	Moderate
8	49	0.074	Moderate
9	64	0.079	Moderate
10	49	0.075	Rapid
11	32	0.032	Rapid
12	37	0.066	Nonprogressor
13	26	0.032	Nonprogressor
14	77	0.062	Moderate
15	40	0.120	Rapid

Activity 3: Sodium channel proteins: a revealing story about the evolution of tissues, organs and taxa

This activity will stimulate the student to grapple with the question of which came first, the organs and tissues, or the taxa as we now know them.