BIOL368/S20:Sahil Patel Week 3

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Purpose

The purpose of this assignment is to prepare us for our first Journal club as well as to help us read and understand primary research articles, specifically in literature exploring patterns of HIV evolution in individuals with differing rates of CD4 T cell decline.

Definitions

  1. Retrovirus = Any of a family of viruses, many of which produce tumors, that contain RNA and reverse transcriptase, including HIV. (https://medical-dictionary.thefreedictionary.com/retrovirus)
  2. Serology = The scientific study of fluid components of the blood, esp. antigens and antibodies (https://medical-dictionary.thefreedictionary.com/serology)
  3. Nonsynonymous mutations = usually an insertion or deletion of a single nucleotide in the sequence during transcription when the messenger RNA is copying the DNA causing a frame shift mutation which throws off the entire reading frame of the amino acid sequence and mixes up the codons. (https://www.sciencedirect.com/topics/biochemistry-genetics-and-molecular-biology/nonsynonymous-substitution)
  4. CD4 T cell = A type of lymphocyte. CD4 T lymphocytes (CD4 cells) help coordinate the immune response by stimulating other immune cells, such as macrophages, B lymphocytes (B cells), and CD8 T lymphocytes (CD8 cells), to fight infection. HIV weakens the immune system by destroying CD4 cells. (https://aidsinfo.nih.gov/understanding-hiv-aids/glossary/113/cd4-t-lymphocyte)
  5. Virologic = of or pertaining to viruses and viral diseases (https://www.biology-online.org/dictionary/Virology)
  6. Immunology = The branch of biomedicine concerned with the structure and function of the immune system, innate and acquired immunity, the bodily distinction of self from nonself, and laboratory techniques involving the interaction of antigens with specific antibodies. (https://www.biology-online.org/dictionary/Immunology)
  7. Epidemiology = The study of the distribution and determinants of health-related states and events in populations and the control of health problems, the study of epidemic disease. (https://www.biology-online.org/dictionary/Epidemiology)
  8. Phylogenetic Trees = The phylogenetic tree is a tree diagram to show the evolutionary histories and relationships among taxonomic groups. (https://www.biology-online.org/dictionary/Phylogenetic_tree)
  9. Plasma viral load = the plasma level of viral RNA, as determined by various techniques including target amplification assay by reverse transcriptase polymerase chain reaction and branched DNA technology with signal amplification. (https://medical-dictionary.thefreedictionary.com/plasma)
  10. Seroconversion = The change of a serologic test from negative to positive, indicating the development of antibodies in response to infection or immunization. (https://medical-dictionary.thefreedictionary.com/seroconversion)

Introduction

  • What is the importance or significance of this work?
    • HIV-1 is variable and difficult to manage, so this study aims to provide information of the selective forces directing evolution. Using this information, researchers try to gather as much information as possible to work towards finding a cure or vaccine.
  • What were the limitations in previous studies that led them to perform this work?
    • Small sample sizes as well as short duration. This study aimed to address these limitations.
  • How did they overcome these limitations?
    • 15 patients were enrolled in the study that spanned 4 years. This was believed to be a more optimal sample size as well as length of time.

Methods

The Study Population

  • 15 participants selected from AIDS Linked to Intravenous Experiences
    • Rapid progressors defined as having attained <200 CD4 T cell within 2 years of seroconversion
    • Moderate progressors' CD4 T cells declined to 200-650 during 4 year observation period
    • Nonprogressors maintained CD4 T cell levels >650 during observation period

Sequencing of HIV-1 env Genes

  • Nested PCR used to amplify a 285-bp region of the env gene from PBMC
    • PBMC = peripheral blood mononuclear cells
  • Preponderance of viral DNA is obtained from recently infected, unactivated PBMC
    • Because the DNA is derived from recently infected cells, it should be closely related to the RNA in viruses currently in the plasma
  • 1st and 2nd round PCR were run for 2 min at 95°C, followed by:
    • 35 cycles of 94°C for 30 sec, 60°C for 30 sec, 72°C for 45 sec
    • After the 35 cycles, the saples were kept at 72°C for 10 min until returning to the 4°C temp at which they were held until further analysis
  • The amplified sequences from nested PCR were cloned into pUC19 and sequenced using the Sanger chain termination method with appropriate nested primers
  • Limited dilution single-round PCR was used initially to screen for input viral DNA copy number and 5 samples that had PCR product detected only at the lowest cellular dilution were subjected to 2nd round PCR
  • Even these samples had >125 input copies of viral DNA for the initial round of PCR amplification

Plasma Viral Load

  • Plasma viral load was determined using reverse transcription-PCR

Generation of Phylogenetic Trees

  • Trees constructed using MEGA computer package using neighbor-joining algorithm and the Tamura-Nei distance measure, correcting for base composition and transition/transverion bias
  • Taxon labels indicate the time at which each strain was isolated and the number of identical replicates sampled
    • ex:S1V2-8(2) = two identical replicates were obtained of clone 8 from subject S1's second visit.
  • Taxa are given colors according to the time point at which they were observed:
    • V1: red
    • V2: orange
    • V3: green
    • V4: light blue
    • V5: dark blue
    • V6: purple
    • V7: brown
    • V8: gray
    • V9: black
      • Intermediate sequences were given the same color as their earlies observed descendent sequence
  • This tree demonstrated the independent segregation of those clones, with the exception of clones from two subjects who were known epidemiologically to be related (S1 & S2)

Correlation Analysis

  • Correlation between genetic diversity or mutational divergence and CD4 T cell count 1 year later was determined
    • the units of analysis were defined by pairs of visits within individuals
    • 76 time points were available from the 15 subjects
      • X0 = value of either diversity (π) or percent mutational divergence
      • Y0 = value of CD4 T cell count at visit at which X0 was determined
      • Y1 = value of CD4 T cell count in that subject 1 year later

Determination of dS/dN Ratios

  • Initial consensus sequence for each subject was computed and compared with each subsequently observed strain
    • classified as either synonymous or nonsynonymous
  • Jukes-Cantor correction was used to remove possible bias which would make values smaller
  • Values exhibited a skewed distribution so median vale was used for mean.

Examination of Source of Greater Initial Visit Diversity in Subjects 9 and 15

  • 3 different phylogenetic trees were constructed using clones from the first visit of subjects 9 & 15 and between 150-200 randomly selected clones from other individuals from the study
    • determined whether viruses from the first visits of subjects 9 & 15 segregated as independent or as monophyletic viruses
    • clearly grouped as monophyletic
  • Reexamination of history of subjects confirmed that they were HIV-1 seronegative up to 7 months before the first visit
  • Exclusion of subject 15 did not change conclusion of this analysis

Comparison of the Rate of Change of Divergence and Diversity

  • A regression line of divergence/diversity over time was fit and summarized with the slope, βi, for the ith individual
  • The averages of the slopes for each of the 3 groups were compared by random effects models

Results

  • Increasing viral genetic diversity is associated with CD4 T cell decline
  • Figure 1 - CD4 T cell trajectory, diversity, and divergence
    • X-axis: time since seroconversion (years) for rapid, moderate, and non-progressors
    • Y-axis (left): CD4 T cell count
    • Y-axis (right): Diversity and Divergence values
  • Table 1 - Summary data on 15 seroconverters
    • Includes Subject, # of observations, CD4 count, Median intravisit nucleotide differences among clones, virus copy number, slope of change in intravisit nucleotide differences per clone per year, slope of divergence, and Median dS/dN
  • Figure 2 - Means obtained from a weighted average using number of observations and precision of the slopes of each subject
    • X-axis: Non-progressors, moderate progressors, and rapid progressors
    • Y-axis (A): Mean slope/year of intravisit genetic diversity
    • Y-axis (B): Mean slope/year of % of nucleotides mutated from seroconversion virus
  • Figure 3 - Phylogenetic Tree of Subject 9
    • Horizontal distance between S9V2-1 and S9V2-2 represents a single mutation
  • Figure 4 - Phylogenetic Trees of 4 randomly selected subjects from the original remaining 14
    • Horizontal distance between S14V4-7 and S14V4-8 represents a single mutation

Discussion

  • How do the results of this study compare to the results of previous studies?
    • Higher level of diversity in rapid progressors in Markham et al whereas Wolinsky et al were not able to identify effective immune responses to the viruses in their rapid progressors.
  • How do the results of this study support published HIV evolution models?
    • This study was consistent wit Nowak in its main result where diversity and divergence increase throughout the observed time of infection.
  • What are the important implications of this work?
    • The immune response was not broadly targeting the full array of viruses present, targeting instead only the most frequent virus.
  • What future directions should the authors take?
    • Making a more comprehensive study targeting multiple viruses/infections as well as increasing sample size.

Conclusion

Acknowledgments

  • I would like to thank my journal club partner Lizzy Urbina for helping me outside of class with interpreting some of the figures in the paper.
  • Journal assignment was obtained from Week 3 wiki.

Except for what is noted above, this individual journal entry was completed by me and not copied from another source.

References

  1. seroconversion. (n.d.). Retrieved January 30, 2020, from https://medical-dictionary.thefreedictionary.com/seroconversion
  2. Customers. (2014, May 12). Epidemiology. Retrieved January 30, 2020, from https://www.biology-online.org/dictionary/Epidemiology
  3. plasma viral load. (n.d.). Retrieved January 30, 2020, from https://medical-dictionary.thefreedictionary.com/plasma viral load
  4. Customers. (2014, May 12). Phylogenetic tree. Retrieved January 30, 2020, from https://www.biology-online.org/dictionary/Phylogenetic_tree
  5. Nonsynonymous Substitution. (n.d.). Retrieved January 30, 2020, from https://www.sciencedirect.com/topics/biochemistry-genetics-and-molecular-biology/nonsynonymous-substitution
  6. retrovirus. (n.d.). Retrieved January 30, 2020, from https://medical-dictionary.thefreedictionary.com/retrovirus
  7. serology. (n.d.). Retrieved January 30, 2020, from https://medical-dictionary.thefreedictionary.com/serology
  8. CD4 T Lymphocyte Definition. (n.d.). Retrieved January 30, 2020, from https://aidsinfo.nih.gov/understanding-hiv-aids/glossary/113/cd4-t-lymphocyte
  9. Customers. (2014, May 12). Virology. Retrieved January 30, 2020, from https://www.biology-online.org/dictionary/Virology
  10. Customers. (2014, May 12). Immunology. Retrieved January 30, 2020, from https://www.biology-online.org/dictionary/Immunology
  11. Markham, R. B., Wang, W. C., Weisstein, A. E., Wang, Z., Munoz, A., Templeton, A., ... & Yu, X. F. (1998). Patterns of HIV-1 evolution in individuals with differing rates of CD4 T cell decline. Proceedings of the National Academy of Sciences, 95(21), 12568-12573. doi: 10.1073/pnas.95.21.12568
  12. BIOL368/S20:Week 3. (n.d.). Retrieved January 30, 2020, from https://openwetware.org/wiki/BIOL368/S20:Week_3

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Sahil Patel (talk) 14:25, 30 January 2020 (PST)