Murder by HIV? Grades 9-12 Edition Laura B. Regassa, Department of Biology, Georgia Southern University Naowarat (Ann) Cheeptham, Department of Biological Sciences, Thompson Rivers University Michèle 1. Shuster, Department of Biology, New Mexico State University Introduction HIV-1 mutates very rapidly. Because of its high mutation rate, the virus will continue to change (evolve) after a person is infected. Thus, within an infected individual, there may be multiple variants of the virus, all of which diverged from the same strain since the time of infection. Similarly, if many people were all infected by a common source (the same infected individual), over time we would expect to see different sequence variants arise in each infected individual but for all those variants to be genetically related to one another. We can use the genetic sequences to generate a phylogenetic tree and test hypotheses about the genetic (and evolutionary) relationships between different viral strains Student Background Knowledge Students should have the following knowledge prior to completing this activity: 1. Know how to use a web browser. 2. Have a basic understanding of the function of DNA, RNA, and proteins 3. Be familiar with the ways in which scientists traditionally classify organisms Vocabulary Bioinformatics: the unified discipline formed from the combination of biology, computer science, and information technolo gy. GenBank: an open access sequence database that has the collection of all publicly available nucleotide sequences and their protein translations Phylogeny: a branching diagram or “tree” showing the evolutionary relationships among various organisms based upon their overall similarities and differences Materials Checklist Access to a laptop or desktop computer. Part I – An IlI-Fated Argument In July of 1994, a nurse broke off her relationship with her married boyfriend (a doctor). On August 4, 1994, her ex-boyfriend showed up at her residence and administered a shot that he claimed was a vitamin B-12 injection. He had given her vitamin B-12 injections in the past, but this one was very painful. Prior to that time, the nurse had had several HIV tests (each time she gave blood, and one after having the saliva of an infected patient splash on her skin) and she had always tested negative. Her most recent blood donation was in April of 1994, and her blood tested negative for HIV at that time. In January of 1995, however, she tested positive for HIV. At that time, she accused her ex-boyfriend of deliberately infecting her during the argument back in August. He was brought to trial on charges of attempted second-degree murder. Questions You can imagine that the defense team posed alternative means by which the woman could have become infected. What are some other possibilities? List them below. 1. What kinds of tests or information could be used to rule out these alternative hypotheses for her infection with HIV? 2. Part Il CompaingSequences Other possible sources of the infection included the woman’s prior sexual contacts and occupational exposure, given that she was a nurse. All seven of the men that she had been in sexual contact with (including her former boyfriend) were tested and found to be HIV-negative. Her employment records were examined, and there were no reports of any accidental or occupational exposures other than the saliva that was splashed on her skin sometime in the mid-1980s. Her file did not have any documentation of any needle sticks at work As the investigation proceeded, it was found that an HIV-positive patient under the care of the ex-boyfriend/doctor had blood drawn at the physician’s offices on August 4, 1994. The paperwork for this procedure was deliberately hidden (the log book was found in a box of “1982 records” in a storage room with other records from the 1980s) and was not filled out in a manner that was consistent with standard office practices. Based on the circumstantial case against the physician, the reverse transcriptase (RT) sequences from the victim (the nurse/ex-girlfriend) and from the physician’s HIV-positive patient (the putative source of the nurse’s infection via the injection administered during the ill-fated argument) were analyzed. As HIV-1 mutates rapidly, we don’t expect to find identical sequences in the victim and patient. Instead, we expect to find related sequences that share a common ancestor. We can investigate this by using patient and victim HIV RI sequences to generate a phylogenetic tree and look at the clustering of the sequences Procedure Go to the NCBI homepage (http://www.ncbi.nlm.nih.govl). On the right toolbar, use the dropdown menu to select Nucleotide (see red arrow in screen capture below) and then search for AY156807. AY156807 is the accession number for a reverse transcriptase gene sequence from an HIV isolate. The accession number is a way to locate or reference the sequence, like a books call number in a library card catalog 1. NCBI Resources How To NucleotideAY156807 National Canter for When you get to the page that opens with all of the record information, look near the top of the page and change the “Display Settings” from GenBank to FASTA. FASTA is a format for DNA sequences that is compatible with programs 2. used for bioinformatics analysis NCBIResourcesHow To Nucleotide Nucleotide Limits Advanced RT from USA reverse transcriptase (pol) gene, partial cds C Summary GerBank FASTA C FASTA (text) Graphics C ASN. 805 bp DNA linear VRL 22 OCT-2002 .HIC.RT from USA reverat transcriptase (pel) gene. Revision History Accession List Gl List Apply 1 24210021 virus 1 〔HIV-1) ORGANISM Bunan imaunodefLelescy virus 1ruse Retro-sranscribing viruses7 Retroviridse You will get the complete nucleotide sequence of that particular sequence. Highlight it and copy it (ONLY the sequence, not the blah blah on the first line). Remember, the DNA sequence will only have four different letters representing the four nucleotides (A, T, C, G) Now go back to the NCBI homepage and click on BLAST on the right. BLAST is a program that allows you to search for similar DNA sequences in a large database of sequences 3. 4. NCBI Resources How To All Databases NCBl Home Welcome to NCBI Popular Resources BLAST Site Map (A- The National Center for Biotechnology Information advances science and health by providing access to biomedical and genomic information Chemicals& Bloassays Gene Genome About the NCBI Mission | Organization | Research I RSS Feeds Data & Software 5. When you get to the BLAST homepage, click on the “nucleotide blast” link (left-side, about half-way down) When you get to the nucleotide blast page, paste your sequence into the top box (Enter Query Sequence) blastn blastpblastx tblastn tblastx Enter Query Sequence Enter accession number(s), gi(s), or FASTA sequence(s) , upload file Browse Job Title Enter a descriptive title for your BLAST search 6. Under “Choose Search Set,” select “Others” for the database and “nucleotide collection (nr/nt)” from the database dropdown menu. Some databases have just a subset of all available sequences (e.g., Human genome), but we are looking in a much larger database collection that includes viral nucleotide sequences. Choose Search Set Database r Human genomic + transcript C Mouse genomic + transcript (;Others (nr etc Nucleotide collection (nr/nt) Organism Optional -「Exclude H Enter organism name or id-completions will be suggested Enter organism common name, binomial, or tax id. Only 20 top taxa will be shown. 9 Exclude Optional Entrez Query Optional Models (XM/XP)Uncultured/environmental sample sequences Enter an Entrez query to limit search9 7. Under Program Selection, Optimize for Somewhat similar sequences (blastn), then click on the BLAST button BLAST Program Selection Optimize for Highly similar sequences (megablast) More dissimilar sequences (discontiguous megablast) Somewhat similar sequences (blastn) Choose a BLAST algorithm 8. After a few moments, you will get a list of “hits” that have nucleotide similarities to your Query sequence (from the victim). Scroll past the graphical representation and the abbreviated list by accession number until you get to the listing of individual sequences. The most similar sequences will be listed first. Not surprisingly, the top hits are patient and victim sequences from this case. Click in the first 8 boxes (to check them) of the victim sequences (e.g., HIV-1 clone V2.MIC.RT) and patient sequences (e.g., HIV-1 clone P6-MIC-RT). You will have a total of 8 boxes checked 9. Once you have selected the sequences you want to compare, click on the “download” button at the top Sequences producing significant alignments Select Al None Selected 8 Max Total Query Max Accession score score cover value ident 1452 1452 100% 0.0 100% 156aoz1 1447 1447 100% 00 99% Al15AOLI 1429 1429 100% 00 99% 1522011 1420 1420 10096 0.0 99% &issao11 1389 1389 10096 00 98% 1522021 1389 1389 100% 00 98% artsse00.1 1380 1380 100% 0.0 98% Al1567971 1371 1371 10096 0.0 9896 15072의 図 10. A menu will appear-select “FASTA (complete sequence)” and press the “Continue” button. Sequences producing significant alignments Select A1 Non Selected 8 Max Total Query E Max Accession Description scor๑ score cover value ident 1452 น52 100% 00 100% r1550071 1447 1447 100% 00 99% AY155006.1 1429 29 100% 00 99% AY156802.1 1420 1420 100% 00 99% 1558011 1389 1389 100% 0.0 98% 148021 1389 1389 100% 00 98% gusanoo 1380 1380 100% 00 98% gusarau 1371 1371 100% 0.0 98% AY156799 1 FASTA (complete sequence OFASTA (aligned sequences) GenBank (complete sequence) Hr Table (text) Hit Table (CSV) XML ASN. 1 Copy-and-paste all of the resulting sequences into a text document (use Microsoft Notepad or Word, but save file as a txt file, not doc). Now you need to re-name the sequences to a shorter name that will be visible on the final phylogenetic tree. When re-naming the sequences, it is important to preserve the FASTA format. To ensure that you are preserving the FASTA format, be sure to keep the “>” at the start of the name of each sequence, and to use “_” instead of spaces (for example, >LA1). Also remember that V represents HIV RT 11. sequences from the victim and P represents HIV RT sequences from the patient. So, V2.MIC.RT can be changed to victim_clone2. The sequence title (e.g., V2.MIC.RT) is within the first line of each record that you copied (see the example below) Example change gil24210021 gbAY156807.1| HIV-1 clone V2.MIC.RT from USA reverse transcriptase (pol) gene, partial cds to victim_clone2 Add six reverse transcriptase gene sequences from HIV isolates not related to the case to the text document; all of these HIV samples were isolated from patients in the U.S., but had no known connection to the case under study. You will need to retrieve each of these sequences using the nucleotide search engine (see Step 1) and then change the sequence to FASTA (text) format (see Step 10). Copy the sequence title line and title to 12. your document that already has eight sequences from the victim and patient. Change the title for each of the sequences as indicated (e.g., change HIV-1 isolate 5018-83 clone to USA 1) USA Isolate AY835777 AY835778 AY835769 AY156793 AY156789 AY156788 New title USA 1 USA_2 USA 3 LA 1 LA 2 LA 3 Go to 13. 14. 15. On the left hand menu, click on MAFFT Copy your sequences (from step 12), MAFFT and past them into the window: MAFFT V6.864 is a multiple alignment program for vnno acid or nucleotide sequences. The oniginal website for this application is http// ware/ Paste your sequences in the FASTA format into the window Fl Pasted Choose Fe No file chose 16. Click on the “compute” button beneath the sequence window 17. Wait.. 18. You will see what looks like a mostly blank screen called “Results for MAFFT” Results for MAFFT Click on the “View Tree” button on the left: Input file(s) Engut det Output file(s) 19. The tree will appear in a new window on the same page Aligement Questions 1. Describe the tree (in general terms). Draw a quick sketch of the tree Does there appear to be a relationship between the patient and victim sequences? Do they appear to diverge from a common ancestor? 2. 3. What conclusion can you draw from this tree? 4. Given the circumstantial evidence and the phylogenetic evidence, what do you think the verdict was in this case

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