HIV Exercise

Phylogeny of HIV

Background: AIDS, HIV1, HIV2, and SIV

Acquired Immune Deficiency Syndrome (AIDS) is caused by two divergent viruses, Human Immunodeficiency Virus one (HIV-1) and Human Immunodeficiency Virus two (HIV-2). HIV-1 is responsible for the global pandemic, while HIV-2 has, until recently, been restricted to West Africa and appears to be less virulent in its effects. Viruses related to HIV have been found in many species of non-human primates (monkeys, apes, ...) and have been named Simian Immunodeficiency Virus, SIV.

These primate viruses are lentiviruses, a subfamily of the retroviruses. Retroviruses have RNA genomes but are unique among RNA viruses because they have a replication cycle that involves the reverse transcription of their RNA genome into DNA (this is the opposite direction compared to the usual flow of information from DNA to RNA). The reverse-transcribed viral DNA is stably incorporated into the genomic DNA of an infected cell and subsequent transcription can then create multiple copies of mRNA encoding new viral material.

Like other retroviruses, particles of HIV are made up of 2 copies of the single-stranded RNA genome packaged inside a protein core, or capsid. The core particle also contains viral proteins that are essential for the early steps of the virus life cycle, such as reverse transcription and integration. A lipid envelope, derived from the infected cell, surrounds the core particle. Embedded in this envelope are the surface glycoproteins of HIV: gp120; and, gp41. The gp120 protein is crucial for binding of the virus particle to target cells. It is the specific affinity of gp120 for the CD4 protein that targets HIV to those cells of the immune system that express CD4 on their surface (e.g., T-helper lymphocytes, monocytes, and macrophages).

The Pol gene is encoded by the RNA genome and encodes three different polypeptides: integrase, reverse transcriptase, and protease. It is expressed as a single polyprotein and is subsequently cleaved by protease into its three separate parts.

Purpose of exercise, description of data

In this exercise you are going to investigate the phylogenetic relationship between HIV and SIV. You will do this using two different data sets:

1. a set consisting of 27 different gp120 protein sequences from isolates of HIV1, HIV2, chimpanzee SIV and macaque monkey SIV: gp120.fasta
2. a set consisting of 20 different POL-polyprotein sequences from HIV1, HIV2, chimpanzee SIV and sooty mangabey SIV: hiv-siv-pol.fasta
3. and with the HTLV-1 sequence: htlv-hiv-siv-pol.fasta

Note for enthusiasts: a number of lines of evidence have indicated that macaques are not naturally infected with SIV and that they have acquired their SIV infection while in captivity by cross-species transmission of SIV from sooty mangabeys. This means that both the macaque SIVs and the sooty mangabey SIVs originate from sooty mangabeys.

Multiple alignment

1. Open ClustalX program, load files
2. Discard all the previously opened browser- and ClustalX-windows and open a fresh ClustalX window on your own computer. Load the gp120.fasta file you just saved.
3. Have a look at the alignment parameters:
4. From the "Alignment" pull-down menu choose "Alignment parameters", and then "Pairwise alignment parameters". In this window you are able to change gap-penalties and substitution matrix for the initial, pairwise part of the multiple alignment.
5. QUESTION 1: Note the substitution matrix, the gap opening penalty and the gap elongation penalty in your report.
6. You can also specify whether you want the pairwise alignments performed using a slower but accurate method, or a faster but approximate method. For now just leave everything as is and exit the window.
7. There is a similar window for changing the multiple alignment parameters ("Alignment", "Alignment parameters", "Multiple alignment parameters".) Have a look, but keep the default values for now.
8. Finally, there is also a window for changing a special set of gap parameters used by ClustalX ("Alignment", "Alignment parameters", "Protein gap parameters".).
9. QUESTION 2: Check what the parameters are set to in the "Protein gap parameters" window. Explanations of the various parameters are listed below
   • RESIDUE SPECIFIC PENALTIES: are amino acid specific gap penalties that reduce or increase the gap opening penalties at each position in the alignment or sequence. See the documentation for details. As an example, positions that are rich in glycine are more likely to have an adjacent gap than positions that are rich in valine.
   • HYDROPHILIC GAP PENALTIES are used to increase the chances of a gap within a run (5 or more residues) of hydrophilic amino acids; these are likely to be loop or random coil regions where gaps are more common. The residues that are "considered" to be hydrophilic can be entered in HYDROPHILIC RESIDUES.
   • GAP SEPARATION DISTANCE tries to decrease the chances of gaps being too close to each other. Gaps that are less than this distance apart are penalised more than other gaps. This does not prevent close gaps; it makes them less frequent, promoting a block-like appearance of the alignment.
   • END GAP SEPARATION treats end gaps just like internal gaps for the purposes of avoiding gaps that are too close (set by GAP SEPARATION DISTANCE above). If you turn this off, end gaps will be ignored for this purpose. This is useful when you wish to align fragments where the end gaps are not biologically meaningful.
10. Start the multiple alignment:
11. From the "Alignment" menu choose "Do complete alignment". This opens a window giving you the opportunity to rename output files. Make sure the files are named "gp120.dnd" and "gp120.aln" respectively, and start the alignment by clicking "OK".
12. You may be able to get a glimpse of how ClustalX is working in the bottom part of the window: first, it does all the pairwise alignments. These alignments are then used to construct a "guide tree". (The guide tree should not be confused with the phylogenetic tree we will construct later. The guide tree is entirely based on the pairwise alignments, and is used to guide the construction of the multiple alignment). Finally, ClustalX constructs the multiple alignment by progressively "aligning algnments" following the guide tree.
13. Inspect the alignment:
14. When the alignment is done you can inspect the result by scrolling along the sequences in the ClustalX window. You will notice that the conservation graph at the bottom of the window now has several peaks and plateaus corresponding to the conserved regions of gp120. An additional summary of conservation is given above the sequences. "*" indicates positions which have a single, fully conserved residue, ":" indicates positions with strong functional conservation, and "." indicates positions with weaker functional conservation. Don't close ClustalX after inspecting the alignment (you can iconize it if it clutters the screen).

Computing an unrooted tree

In this part of the exercise we will use ClustalX to produce a phylogenetic tree. The tree is built with the neighbour joining algorithm, and is based on distances computed from the multiple alignment you just constructed.

1. Re-open the ClustalX window containing the multiple alignment from before.
2. (Don't panic if you accidentally closed the ClustalX program after the multiple alignment: start the program as before, and use "File", "Load sequences" to load the alignment file: "gp120.aln")
3. Select output of treefile and distance matrix:
4. From the "Trees" menu choose "Output format options" and select "PHYLIP format tree" and "PHYLIP distance matrix". Click "OK".
5. Construct the tree:
6. From the "Trees" menu choose "Clustering Algorithm" and make sure "NJ" is selected. Then, from the "Trees" menu choose "Draw Tree". This gives you a window where you can change the name of the tree-file and the distance matrix. Make sure they are named "gp120.ph" and "gp120.dst" respectively, and then click "OK" to calculate the tree. ClustalX uses the multiple alignment to calculate a distance matrix with all pairwise distances between the 27 sequences, and then constructs a tree by progressively clustering sequences that are close to each other (using the neighbor-joining algorithm). (Note: the construction of the NJ-tree is so fast that its practically finished the second you have clicked "Draw Tree" - so no need to sit around and wait for the result).
7. Inspect the output files:
8. Use a text editor like notepad to open gp120.ph. This treefile is in a text-based format that is obviously mostly meant for computers. Also look at the file containing all pairwise distances between all sequences: gp120.dst.
9. These are the numbers that were used by the neighbor joining algorithm for constructing the tree. For each sequence the distance to all other sequences are listed on a number of consecutive lines (there are too many distances to fit on a single line). The format is such that you should imagine a table where the order on the (unlabeled) horizontal axis is the same as on the vertical axis (i.e., the first sequence is HV1EL, the second is HV1Z2, etc.)
10. QUESTION 3: Scroll down to the entry for the sequence named HV2BE. Note the first and last distances on the results form (these are the distances to the sequences HV1EL and SIVM1, respectively).

View a plot of the unrooted tree:

There are several programs for visualizing tree-files like the PHYLIP-file gp120.ph. Today we will use the program FigTree version 1.2, which can be downloaded from here: http://tree.bio.ed.ac.uk/software/figtree/.

Click here to download Figtree

or you can use Bioedit program

1. Load the PHYLIP file in FigTree
2. On some operating systems, FigTree starts out by asking for a tree file. If FigTree doesn't ask for a tree file select "Open..." from the "File" menu. Select the gp120.ph file.
3. Under "Layout" in the column to the left, select the button furthest to the right with an unrooted tree on it. As our tree has not yet been rooted it is only appropriate to visualize it as unrooted. You can enlarge the Tip labels under "Tip labels"->"Font size" if necessary.
1. QUESTION 4: Include a screenshot of the tree in your report (or create a separate file for this) and indicate where the HIV1 cluster, the HIV2 cluster, the SIVCZ sequence, and the SIVMK sequences are located.
2. Think for a minute about the implications:
3. What does this tree tell us about the phylogenetic relationship of HIV-1, HIV-2 and SIV? Notice especially where the two different groups of SIV cluster compared to the two different groups of HIV.

Sample Explanation

Rooting a tree using an outgroup

In this part of the exersize you will use a data set of 20 different POL-polyprotein sequences isolated from HIV-1, HIV-2, chimpanzee SIV, and sooty mangabey SIV. The Pol gene encodes three different polypeptides: integrase, reverse transcriptase, and protease. It is expressed as a single polyprotein and is subsequently cleaved by protease into its three separate parts.

First, you will construct a neighbor-joining tree like before and investigate whether this new, independent data set confirms the conclusions you made based on the alignment of gp120 sequences. Then you will add a POL-polyprotein sequence from HTLV-1 to the data set and construct a new tree, that you can then root using the HTLV sequence as an outgroup. (HTLV-1 is another member of the family of retroviruses and is thus more distantly related to HIV - which was originally named HTLV-3 by the way)

1. Download and have a look at the POL sequence file:
2. Download the hiv-siv-pol.fasta file to the working directory, and inspect the alignment with a text editor.
3. As mentioned, this file contains POL-polyprotein sequences from HIV-1, HIV-2, chimpanzee SIV, and sooty mangabey SIV.
4. Align the POL sequences using ClustalX:
5. Re-open the ClustalX window and load the sequence file hiv-siv-pol.fasta. Now, start the alignment by choosing "Do complete alignment" from the "Alignment" menu as before.
6. Construct a neighbor-joining (NJ) tree with no outgroup:
7. Make sure "Clustering Algorithm" is set to "NJ". From the "Trees" menu choose "Draw Tree". Make sure the tree will be named "hiv-siv-pol.ph".
8. Inspect the unrooted tree:
9. Open FigTree and load the PHYLIP tree file hiv-siv-pol.ph.
10. This tree has been constructed from an entirely independent set of sequences. Does it support the conclusions that could be made from the gp120-based tree? (again, remember to use the unrooted layout).
11. QUESTION 5: Create a screenshot (again you may create a new file for this) indicating the position of the HIV1-cluster, the HIV2-cluster, the HIVCZ sequence and the HIVSmanga sequences.
12. Have a look at the POL sequence file with an added outgroup:
13. Download the htlv-hiv-siv-pol.fasta file to the working directory, and inspect the data set with a text editor.
14. This file contains the same sequences as the file hiv-siv-pol.fasta plus an additional POL-sequence from the related virus HTLV-1 (the first sequence in this file). The HTLV POL sequence will be used as an outgroup in this part of the exercise.
15. Align the outgroup-containing data set using ClustalX and create neighbor-joining tree:
16. Re-open the ClustalX window and load the sequence file htlv-hiv-siv-pol.fasta.
17. Now, start the alignment by choosing "Do complete alignment" from the "Alignment" menu as before.
18. From the "Trees" menu choose "Draw Tree" (make sure that clustering algorithm is set to "NJ"). Make sure the tree will be named "htlv-hiv-siv-pol.ph".
19. Inspect the unrooted tree:
20. Load the treefile htlv-hiv-siv-pol.ph in FigTree, and in the Layout menu choose the button furthest to the right, with the unrooted tree on it.
21. Observe how the outgroup HTLV is located quite distantly from the other sequences.

Root the tree by using an outgroup:

1. We will now construct a rooted tree, using the HTLV sequence as an outgroup. The outgroup will be used to place the root of the tree.
2. The rationale is as follows: our data set consists of sequences from HIV-1, HIV-2, SIV and HTLV. We know from other evidence that the lineage leading to HTLV branched off before any of the remaining viruses diverged from each other. The root of the tree connecting the organisms investigated here, must therefore be located between the HTLV sequence (the "outgroup") and the rest (the "ingroup"). This way of finding a root is called "outgroup rooting", and constructs a tree where the outgroup is a monophyletic sister group to the ingroup.
3. In FigTree select the branch leading to the HTLV sequence by clicking on it.
4. In the "Tree" menu choose "Root on Branch...". This places the root on the branch leading to the HTLV sequence. But we won't see any change since the tree is being viewed as an unrooted tree.
5. In the "Layout" option choose the button furthest to the left to view the tree as a rooted tree.
6. Have a look at the outgroup-rooted tree:
7. QUESTION 6: On the screenshot you made before, indicate which branch the root is located on. Was this were you expected it?

Explanation of results