Nyeo2 Week 3

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The purpose of this assignment is to read the article given and gain scientific evidence about the correlation between mutation/evolution and progression of HIV-1 in seroconverted patients.

Journal Club Article: "Patterns of HIV-1 evolution in individuals with differing rates of CD4 T cell decline"


  • Seroconversion: The change of a serologic test from negative to positive, indicating the development of antibodies in response to infection or immunization(biology-online.org).
  • Nested(PCR and primers): A set of oligonucleotide primers used for the amplification of DNA by the polymerase chain reaction ( PCR ) in which the outermost 5′ and 3′ pair are used in the first phase of amplification and a second pair is designed to prime within that PCR product to produce a shorter amplified sequence(Oxford, 2008).
  • Synonymous mutation: a point mutation usually in the third position of a nucleotide triplet (q.v.), in which a nucleotide-pair substitution results in changing a codon for an amino acid into a different codon for the same amino acid (Oxford, 2014).
  • Nonsynonymous mutation: a missense mutation in which a nucleotide-pair substitution results in changing a codon for one amino acid to a codon for a different amino acid. Such a mutation gives rise to an altered polypeptide, which can have a deleterious effect, no effect, or a beneficial effect(Oxford, 2014).
  • Viral load: The number of viral particles (usually HIV) in a sample of blood plasma. HIV viral load is increasingly employed as a surrogate marker for disease progression. It is measured by pCR and bDNA tests and is expressed in number of HIV copies or equivalents per millilitre(biology-online.org).
  • Peripheral blood mononuclear cells(PBMC): A mixture of monocytes and lymphocytes; blood leucocytes from which granulocytes have been separated and removed(Lackie, 2007). p. 317
  • Epitope: That part of an antigenic molecule to which the T-cell receptor responds; a cite on a large molecule against which an antibody will be produced and to which it will bind(Lackie, 2007). P. 147
  • Chemostat: An apparatus in which a bacterial population can be maintained in the exponential phase of growth by regulating the input of a rate-limiting nutrient and the removal of exhausted medium and cells
  • Sanger chain termination method: A general method for deriving the primary sequence of a polypeptide chain based on selective hydrolytic degredation of the chain into msaler peptides(Cammack et al., 2008).
  • Tamura-Nei distance measure: Model that corrects for multiple hits and takes into account the differences in substitution rate between nucleotides and the inequality of nucleotide frequencies(Nei and Kumar, 2000).

Article Outline

  1. Previous limitations
    • Examined only small cohorts
    • Did not utilize direct examination of sequence patterns
    • Only had a limited number of time points during which subjects were examined
  2. Experimental solutions to previous limitations
    • Used 15 subjects
      • Each analyzed over a period of up to four years
        • Subjects were at-risk injection drug users who visited every 6 months after seroconversion
      • Synonymous and nonsynonymous mutations in env gene sequence quantified in a ratio(dS/dN)
  3. Significance
  4. Main result
    • Analysis of seroconverted subjects showed that the evolutionary selection that led to viral diversity of HIV-1 differed between subjects with differing levels of viral progression
    • The more the virus showed genetic diversity, the more likely the subject showed quicker CD4 T cell decline
  5. Methods
    • Study population
      • Selected 15 participants who were injection drug users, who visited every 6 months after HIV-1 seroconversion
      • Rapid progressors: fewer than 200 CD4 T-cells within 2 years after seroconversion
      • Moderate progressors: CD4 T-cell level of 200-650 within 4 years after seroconversion
      • Nonprogressors: CD4 T-cell level above 650 for all visits.
    • Sequencing HIV-1 env genes
      • Performed nested PCR on a 285-bp region of env gene from PBMC
      • Used nested primers on the region, then cloned and sequenced the sequences using the Sanger chain termination method
    • Plasma viral load and phylogenetic trees
      • Plasma viral load found by reverse-transcription PCR
      • Phylogenetic trees were created using the neighbor-joining algorithm and the Tamura-Nei distance measure
    • Correlation Analysis
      • Determined the correlation between genetic diversity and CD4 T cell count 1 year after seroconversion by using units as pairs of visits
      • CD4 T cell count values were stratified to see the relation to the diversity or divergence
    • dS/dN ratios
      • Used the Jukes-Cantor correction to remove bias for smaller values of the ratio
      • Median value used for the average
      • dS=synonymous strain and dN=nonsynonymous strain
    • Subjects 9 and 15 were analyzed using phylogenetic trees
      • Suspected of having two different viruses because of high genetic variation
    • Rate of change in diversity and divergence
      • Fit a regression line of divergence/diversity for each patient
      • Each line summarized with a slope
  6. Figures and Tables
    • Figure 1
      • Shows the trajectory of CD4 T cells(circles), divergence(squares), and diversity(diamonds) over time since seroconversion
      • Graphs divided by progressor groups
      • CD4 T cell patterns fluctuated quite a lot between all the subjects
    • Table 1
      • Displays data gathered on the 15 subjects, who were grouped based on progressor groups
      • Included baseline CD4 T cell levels, annual CD4 T cell decline rate, intravisit nucleotide diversity, virus copy number, slope of nucleotide changes between visits, slope of divergence(mutation), and median dS/dN ratios for each patient
      • Although most of the data was quite variable, there was a pattern of increased CD4 T cell decline from nonprogressors to rapid progressors
      • The dS/dN ratio values were different between the nonprogressors and other categories, meaning that there was not a selective advantage for viral changes in nonprogressors
    • Figure 2
      • Box and whisker plots showing the mean slopes of viral diversity and nucleotide divergence for different progressor groups
      • On average, the slopes for diversity and divergence increased from nonprogressors to moderate progressors to rapid progressors, suggesting a greater amount of mutation in the latter groups
    • Figure 3
      • The phylogenetic tree for the HIV-1 strain from subject 9
      • There is no predominance of a single strain; the viral isolates for visit 4 come from a point close to that of visit 1
      • There is a single mutation in the strain of this subject
    • Figure 4
      • Viral phylogenetic trees of four random subjects in the study
      • Shows that evolution is not sustained within one branch
  7. Discussion
    • Results conflict with Mcdonald et al.
      • Intravisit diversity was less in rapid progressors than in slow progressors, which was the opposite
      • Fewer visits for each subject, and they were not followed from the time of seroconversion
    • Wolinsky et al.saw less viral diversity in subjects with higher rates of CD4 T cell decline, whereas in Markham et al., the rapid progressors generally showed a higher level of diversity and divergence
      • The two exceptions may be subjects who failed to produce an immune response to the virus
    • In the Nowak model, the same rapid CD4 T cell decline rate that was associated with increased genetic diversity and divergence in Markham et al. was observed
      • For all but two subjects, an increase in diversity was seen in in those who progressed to AIDS
    • The results from Markham et al. show that there was no sufficient immune response to HIV-1 because the response was not targeting the full spread of different strains, rather than the emergence of resistant strains
      • May be important for future treatments, as the root cause of progression is important to target
      • In future studies, the focus could shift into the analysis of immune response to viruses with a large diversity and divergence, and to viruses that are more replication-competent
    • I personally would like more explanation for the statistical tests. They provided which tests they used, but failed to explain it in an understandable way. This can be interpreted as not fully understanding the purpose of what they were doing, or just adding it because it looked good. I think that the table was a good visual, but I did not think the trees were useful at all because they were a jumble of letters that could not be readily understood by the reader. Other than that, the paper does prove to provide important information moving forward, but there is still more work to be done as HIV is a constantly evolving virus.

Scientific Conclusion

This paper aims to elucidate the correlation of CD4 T cell decline with other patterns, such as genomic diversity and nucleotide divergence. It shows the difference between the progressor groups: nonprogressors, moderate progressors, and rapid progressors. After the experiments, it was concluded that rapid progressors have a higher rate of diversity and CD4 T cell decline than that of the other groups.


  • I worked with my partner, Jenny Chua, during the class period and over text to better understand the reading.
  • The article read and analyzed was "Patterns of HIV-1 evolution in individuals with differing rates of CD4 T cell decline" by Markham et al.
  • The sites used to define the terms were Biology Online, Lexico, and Oxford Dictionary of Biochemistry and Molecular Biology.
  • I followed the protocol on the assignment page BIOL368/S20:Week 3 to complete this assignment.
  • Except for what is noted above, this individual journal entry was completed by me and not copied from another source.

Nyeo2 (talk) 23:19, 5 February 2020 (PST)