Nicolette S. Harmon Week 3

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Contents

Activity 1

Methods

  1. I accessed the Markham et.al paper on PubMed in order to find the HIV sequences that are stored in GenBank.
  2. I selected the sequence labeled GenBank/AFO16772, this sequence was then formatted using FASTA.
  3. This newly formatted sequence was then saved on Workbench.
  4. I repeated steps 2 and 3 with the sequences GenBank/AFO16782 and GenBank/AFO16762.
  5. Using the ClustalW tool on Workbench, I ran a multiple sequence alignment using the GenBank/AFO16772, GenBank/AFO16782, and Genbank/AFO16762 sequences.
  6. I recorded the scores for these sequences in the Results section.

Results

  1. When I ran the ClustalW tool on workbench for all 3 sequences the overall score was 5250.
  2. The program then reported the score for the GenBank/AFO16782 and GenBank/AFO16762 sequences as 99.
  3. The score for GenBank/AFO16772 and GenBank/AFO16782 was 96.
  4. The score for GenBank/AFO16772 and GenBank/AFO16762 was 96.

Activity 2

Methods

  1. I uploaded the "Visit_1_Subjects_1_thru_9_HIV.txt" and the "Visit_1_Subjects_10_thru_15_HIV.txt" files onto Workbench.
  2. I ran a multiple sequence alignment using the ClustalW tool for Subjects 2,3,4,7 using the first 3 clones from each subject.
  3. The unrooted tree for these sequences is recorded in the Results section.
  4. Next, I aligned all of the clones for Subject 14 so that I could calculate the number of non-identical positions in each sequence.
  5. The ClustDist tool was accessed to determine the minimum and maximum differences in sequence for Subject 14.
  6. Steps 4 and 5 were repeated for Subjects 5 and 10.
  7. The table used to record this information for these three subjects is below.
  8. ClustDist was then used to compare the different combinations of pairing for these sequences.

Results

  • This is the unrooted tree diagram for Subjects 2,3,4,7.

Image: UnrootedtreeS2347NicoletteHarmon.JPG

  • These results for the table below were calculated using the multiple alignment tool on Workbench.

Image: HIVSubjectTableNicoletteHarmon.JPG

  • The results in the table below were calculated by using the multiple alignment tool for each pairing possible.

Image: HIVSubjectDifferenceNicoletteHarmon.JPG

Questions

Activity 1 Part 2

  1. The accession number of the sequence I chose was AFO16772.
  2. The HIV sequence I used came from Subject 1.

Activity 2 Part 1

  1. The clones from Subjects 2 and 4 were clustered together.
  2. 2 of the 3 clones selected for Subject 3 were clustered while the third clone was somewhat isolated. All of the clones selected from Subject 7 were more diverse.
  3. Subjects 2 and 4 were somewhat clustered together with Subject 7 being a little further away. Subject 3 was the most diverse of the subjects.

Lists of Terms for Week 4

  1. Intravenous- into or within a vein. National Cancer Institute September 20 2011
  2. Epidemiology- study of causes, patterns, and control of disease in groups. National Cancer Institute September 20 2011
  3. Cohort- a group of organisms that are apart of the same species that are studied over a period of time. Biology Online September 20 2011
  4. Seroconversion- the change of a serologic test from negative to postive, indicating the development of antibodies in response to an infection or immunisation. Biology Online September 20 2011
  5. Divergence- spreading apart in different directions. Biology Online September 20 2011
  6. Epitope- a site on a large molecule in which and an antibody will be produced and bound to. Biology Online September 20 2011
  7. Phylogenetic- of or relating to the race history of an organism. Biology Online September 20 2011
  8. CD4- a glycoprotein that serves as a differentiation antigen found on the surface of T lymphocytes and macrophages. Biology Online September 20 2011
  9. Plasma Viral Load- the number of viral particles in a sample of blood plasma. Biology Online September 20 2011
  10. Taxon- any group or rank in a biological classification into which related organisms are classified. Biology Online September 20 2011

Outline for Markham Paper

Abstract

  • 15 subjects with HIV were studied to see determine the decline of CD4 T cells
  • Nonsynonymous mutations were selectively favored in progressors while they were selected against in nonprogressors
  • The subjects had different types of mutations that were likely due to different environments of each host
  • The subjects in this experiment were brought in at different intervals over the course of four year
  • The purpose of this experiment is to show that increased rates in genetics diversity is linked to rapid decreasing rates of CD4 T cells

Methods

  • The subjects in this study were brought in every 6 months so data could be collected
  • Rapid progressors= <200 CD4 T cells in a two year period
  • Moderate progressors= 200-650 CD4 T cells in 4 years
  • Nonprogressors= >650 CD4 T cells throughout the entire observation period
  • PCR was used to look at base pair sequences in the subject's blood cells in order to compare them to the RNA of the virus
  • 35 cycles of PCR were done and samples were held at 72degrees for 10 minutes
  • The sequences from the PCR were cloned and then sequenced using the Sanger chain termination method
  • Most of the clones were shown to be derived from a diverse viral genome template
  • Reverse transcription was used to determine the number of viral particles in a blood plasma sample
  • Taxon labels were assigned based on times that the subjects came in for their visit, although some data is lacking on visits of some subjects
  • The taxa were colored to correspond with the time that they were observed
  • Phylogenetic trees determined independent segregation of clones except subject 1 and 2
  • 76 time points, 15 subjects in 1 year is the correlation analysis
  • Each subject's sequence was compared to an observed strain
  • Mutations were either synonymous or nonsynonymous
  • Numbers were adjusted based on mutation class that occurred to eliminate bias towards nonsynonymous
  • Since values had a skewed distribution, average values were adjusted to the median values
  • Subjects 9 and 15 displayed high genetic variation at their first visit
  • Phylogenetic trees were constructed and subjects were determined to have monophyletic viruses
  • These subjects were seronegative up to 7 months before their first visit


  • To compare rate, a regression line of divergence/diversity was placed over time
  • The slopes for each of the three groups was compared

Results

  • The median annual changes in CD4 T cells ranged from +53 to -593 per year
  • Nonprogressors had a low viral load that was distinguishable from moderate and rapid
  • Rapid and moderate viral loads were non-distinguishable
  • A total of 873 clones were sequenced and analyzed
  • Changes in HIV sequences were quantified by: genetic diversity per visit and divergence per visit
  • The rate of change in median diversity ranged from -2.94 to 5.10 nucleotides per clone
  • Initial visit: subjects 9 and 15 displayed heterogeneity while all others displayed homogeneity
  • Diversity and divergence increased over time in all three categories
  • The increasing rates were greater in the more progressive categories

Links

BIOL368/F11:Week 1

BIOL368/F11:Week 2

BIOL368/F11:Week 3

BIOL368/F11:Week 4

BIOL368/F11:Week 5

BIOL368/F11:Week 6

BIOL368/F11:Week 7

BIOL368/F11:Week 8

BIOL368/F11:Week 9

BIOL368/F11:Week 10

BIOL368/F11:Week 11

BIOL368/F11:Week 12

BIOL368/F11:Week 14

BIOL368/F11:Class Journal Week 1

BIOL368/F11:Class Journal Week 2

BIOL368/F11:Class Journal Week 3

BIOL368/F11:Class Journal Week 4

BIOL368/F11:Class Journal Week 5

BIOL368/F11:Class Journal Week 6

BIOL368/F11:Class Journal Week 7

BIOL368/F11:Class Journal Week 8

BIOL368/F11:Class Journal Week 9

BIOL368/F11:Class Journal Week 10

BIOL368/F11:Class Journal Week 11

BIOL368/F11:Class Journal Week 12

BIOL368/F11:Class Journal Week 14

Nicolette S. Harmon Week 2

Nicolette S. Harmon Week 3

Nicolette S. Harmon Week 4

Nicolette S. Harmon Week 5

Nicolette S. Harmon Week 6

Nicolette S. Harmon Week 7

Nicolette S. Harmon Week 8

Nicolette S. Harmon Week 9

Nicolette S. Harmon Week 10

Nicolette S. Harmon Week 11

Nicolette S. Harmon Week 12

Nicolette S. Harmon Week 14

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