BIOL368/F14:Isabel Gonzaga Week 3

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Contents

Annotated Bibliography for HIV Evolution Project

Questions

  1. Write three questions (or more) that you have about HIV that you would like answered.
    1. What is the current status of research on treatments on HIV today?
    2. With the high mutation rate of HIV sequences, has any success been found in targeting conserved sequence sections?
    3. What is the current understanding of the HIV replication pathway?
  2. Keyword Search
    1. What original keyword(s) did you use? How many results did you get?
      • Using Google Scholar: HIV+ENV: 103,000 Results
    2. Which terms in which combinations were most useful to narrow down the search? How many results did you get after narrowing the search?
      • HIV+env+envelope: 6,220
      • HIV+ENV+Markham: 3,730
      • hiv+env+envelope+Markham: 2,990
      • The more search terms included, the more narrow the results
      • Including the author in the search terms greatly reduced the total number of results
  3. Advanced Search - For all three, which advanced search functions were most useful to narrow down the search? How many results did you get?
    1. Google Scholar
      • HIV Env OR Envelope: 390,000
      • allintitle: HIV Env OR Envelope: 42,600
      • allintitle: HIV Env OR Envelope author:Markham: 11
      • The more functions utilized greatly reduced the number of results. Searching by author and/or reducing the words to search titles only really narrowed the search.
      • The 'OR' function was important to use, so that more relevant articles are included in the initial search
    2. PubMed
      • (HIV[Title/Abstract]) AND ENV[Title/Abstract]: 5,251
      • (HIV-1[Title/Abstract]) AND (ENV[Title/Abstract] OR ENVELOPE[Title/Abstract]): 8,540
      • (HIV-1[Title/Abstract]) AND (ENV[Title/Abstract] OR ENVELOPE[Title/Abstract]) + 5 Years: 2,046
      • (HIV-1[Title/Abstract]) AND (Markham[Author]) AND (ENV[Title/Abstract] OR ENVELOPE[Title/Abstract]): 32
      • (HIV-1[Title/Abstract]) AND (Markham[Author]) AND (ENV[Title/Abstract] OR ENVELOPE[Title/Abstract]) + 5 Years: 1
      • Searching by Author greatly reduced the number of results. Using Title/Abstract and accounting for both 'env' and 'envelope' terms allowed for greater relevance in the results displayed, although it increased overall numbers. Additionally, applying a 'last 5 years' filter was also imperative to finding recent and relevant articles.
    3. Web of Science
      • TOPIC: (HIV-1) AND TOPIC: (ENV): 4,827
      • TOPIC: (HIV-1) AND TOPIC: (ENV) AND AUTHOR: (Markham): 26
      • TOPIC: (HIV-1) AND TOPIC: (ENV) Timespan: 2009-2014: 1,570
      • Searching by author and reducing the time span were, again, very useful in narrowing results. The feature 'Sort by Times Cited' was also very helpful, in terms of finding relevant articles.
      • The ability to go to an article and view articles which had cited the original makes it very easy to find more recent, related studies.
  4. Prospective Search on Markham et al. (1998)
    • Markham et al. (1998) cited 51 articles
    • Markham et al. (1998) has been cited 70 times

Bibliography

Primary Research Articles

  1. Hoot S., McGuire A.T., Cohen K.W., Strong R.K., Hangartner L., Klein, F. Diskin, R., Sceid, J.F., Sather, D.N., Burton, D.R., & Stamatatos, L. (2013). Recombinant HIV envelope proteins fail to engage germline versions of anti-CD4bs bNAbs. PLoS Pathog 9(1): e1003106. doi:10.1371/journal.ppat.1003106
  2. Rolland, M., Edlefsen, P.T., Larsen, B.B., Tovanabutra, S., Sanders-Buell, E, Hertz, T. deCamp A.C., Carrico, C., Menis, S., Magaret, C.A., Ahmed, H., Juraska, M., Chen, L., Konopa, P., Nariya, S., Stoddard, J.N., Wong, K., Zhao, H., Deng, W., Maust, B.S., Bose, M., Howell, S., Bates, A., Lazzaro, M., O'Sullivan, A., Lei, E., Bradfield, A., Ibitamuno, G., Assawadarachai, V., O'Connell, R.J., deSouza, M.S., Nitayaphan, S., Rerks-Ngarm, S., Robb, M.L., McLellan, J.S., Georgiev, I., Kwong, P.D., Carlson, J.M., Michael, N.L., Schief, W.R., Gilbert, P.B., Mullins, J.I., & Kim, J.H. (2012). Increased HIV-1 vaccine efficacy against viruses with genetic signatures in Env V2. Nature. 490(7420), 417-20. doi: 10.1038/nature11519.
  3. White, T.A., Bartesaghi, A., Borgnia, M.J., Meyerson, J.R., de la Cruz, M.J., Bess, J.W., Nandwani, R., Hoxie, K.A., Lifson, K.D., Milne, J.L.S., & Subramaniam, S. (2010). Molecular architectures of trimeric SIV and HIV-1 envelope glycoproteins on intact viruses: strain-dependent variation in quaternary structure. PLoS Pathog 6(12): e1001249. doi:10.1371/journal.ppat.1001249.

Review Article

  1. Affranchino, J.L., & Gonzalez, S.A. (2014). Understanding the process of envelope glycoprotein incorporation into virions in simian and feline immunodeficiency viruses. Viruses. 6(1), 264-83. doi: 10.3390/v6010264.

Preparation for Week 4 Journal Club

Vocabulary

  1. Competent: (adj.) in bacterial or eukaryotic cells, the ability of cells to bind and internalize exogenous DNA molecules, thereby allowing transformation Source: Oxford Dictionary of Genetics, 8ed.
  2. Chemostat: (n.) a device for the continuous culture of bacterial (and other) cells. Growth occurs in an aerated fermenter vessel and its rate is controlled by the rate of addition of fresh nutrient from a reservoir (i.e. the dilution rate); this in turn controls the rate of removal of cells (and culture medium). In a chemostat, as opposed to an auxostat, the dilution rate is constant. At equilibrium, the rate of production of new cells by multiplication is equal to the rate of removal of grown cells. Source: Oxford Dictionary of Biochemistry and Molecular Biology, 2ed
  3. Epitope: (n.) any immunological determinant group of an antigen.Source: Oxford Dictionary of Biochemistry and Molecular Biology, 2ed
  4. Monophyletic: (adj.) a group of organisms stemming from a most recent common ancestor. Source: Oxford Dictionary of Biology, 6ed
  5. Nested PCR Primers: (n.) 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. Greater specificity of amplification is expected from this use of two pairs of primers. Source: Oxford Dictionary of Biochemistry and Molecular Biology, 2ed
  6. Regression Line: (n.) a line fitted to a series of two variable quantities, x and y, so as to minimize the sum of the squares of the distances parallel to the y axis of the observations from the line. Source: Oxford Dictionary of Biochemistry and Molecular Biology, 2ed
  7. Sanger Chain Termination: (n.) a rapid technique for determining nucleotide sequences in DNA in which the 2′,3′‐dideoxy analogues of the normal deoxynucleoside triphosphates are used as specific chain‐terminating inhibitors of DNA polymerase Source: Oxford Dictionary of Biochemistry and Molecular Biology, 2ed
  8. Seropositive: (adj.): denoting a connection within or origin in serum. Source: Oxford Dictionary of Biochemistry and Molecular Biology, 2ed
  9. Synonymous (adj.): a nucleotide substitution that does not result in an amino acid substitution in the translation product owing to the redundancy of the genetic code. ie. a silent mutation. Source: Oxford Dictionary of Biochemistry and Molecular Biology, 2ed
  10. Viral Load (n.): the amount [virus] given in a metabolic test. Source: Oxford Dictionary of Biochemistry and Molecular Biology, 2ed

Article Outline

Introduction

  • HIV-1 has high mutation and replication rates and are highly adaptable to dynamic host environments
  • Immune systems cause variable effects on virus DNA because they are unstable.
    • If immune systems indiscriminately target HIV coreceptors, the most abundant one is likely to be leftover (high load, low variability)
    • If immune systems target the most abundant variant, the total load will be decreased (low load, high variability)
      • Diverse strains mutate and continue to replicate and may develop resistance to immune system
      • Necessary to examine diversity patterns in HIV-1 evolution to view forces of evolution causing adaptation
  • Limitations of previous work: small samples, did not directly examine sequence patterns, or limited timeframe
  • The present research:
    • HIV evolution studied for 4 year span for 15 subjects
    • Shows that the number of CD4 T Cells within certain time frames lead to different selection patterns in evolution
    • Shows that rapid CD4 T Cell decline is linked to greater diversity for HIV-1 viral strains
      • Contradictory to previous studies

Materials and Methods

Study Population

  • 15 infected or at-risk IV drug users selected from AIDS Linked to Intravenous Experiences (ALIVE) study in Baltimore
  • Participants selected were followed from initial HIV-1 seroconversion and identified by changes in CD4 T Cell levels as follows:
    • Rapid Progressors: less than 200 CD4 T Cells within 2 years of seroconversion
    • Moderate Progressors: 200-650 CD4 T Cells within 4 years of seroconversion
    • Nonprogressors: 650+ CD4 T Cells through observation period

Sequencing HIV-env Genes

  • Peripheral Blood Mononuclear Cells were used to extract viral DNA from, as supported in the literature
    • Cells were recently infected
  • 185bp region of env gene from PBMC amplified through nested PCR
    • external env and nested primers were identified, containing BamGU and EcoRI restriction sites
  • Cloned into pUC19 using 'standard methods'
  • Sequenced using Sagner chain termination method
  • Plasma Viral Load determined by reverse transcription-PCR

Generation of Phylogenetic Trees

  • Constructed using MEGA computer software, using neighbor gaining algorithms and correcting for base composition and transition/transversion bias (Tamura Nei distance measure)
  • Taxon labels identify when he strain was isolated, and number of replicates
  • Taxa color-coded chronically (based on visit number)
    • Red: V1, Orange: V2; Green: V3; Light Blue: V4; Dark Blue: V5; Purple: V6; Brown: V7; Gray: V8; Black: V9
    • Sequences between visit dates were assigned the color of the MRCA

Correlation Analysis

  • Units of analysis defined as pairs within individuals (ie. comparing sequence data and CD4 T Cell count 1 year later)

Determination of dS/dN Ratios

  • Initial consensus sequence and observed sequences classified as synonymous or nonsynonymous
    • Corrections for nonsynonymous bias was made using Jukes-Cantor correction
  • dS/dN ratio found and averaged for all strains within a visit to remove bias in varying sample sizes
  • Median value used to determine average

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

  • High genetic variation between subjects 9 and 15 in their first visit - Needed to confirm if they were two different viruses are not
  • Clones from subjects 9&15 were compared against randomly selected clones from the study to determine relationship
  • Viruses shown to be monophyletic
  • Reconfirmed that subjects 9 and 15 were HIV-1 seronegative before study began
  • Analyzed Subject 15 and showed that, even without recombinations, the subject's diversity value was still higher than the rest at the 6month visit

Comparison of Rate of Change of Divergence and Diversity

  • Subject data was graphed for divergence/diversity over time. Slope of line of best fit was used to determine relationship
  • Slope averages between the three progressor groups were linked to the decline of CD4 T Cell counts

Results

  • CD4 decline patterns variable between all subjects
  • Nonprogressors had significantly lower viral loads than progressors (ANOVA; p<.02)
  • A total of 872 clones of the env region were sequenced and analyzed; changes defined by diversity and divergence
    • Diversity and divergence increased over time in all three progressor groups
    • Rates of diversity and divergence increase in order from nonprogressor, to moderate progressor to rapid progressor
      • Difference between progressor and nonprogressor was significant, close but insignificant for rapid progressor to moderate
  • Diversity and divergence negatively correlated with CD4 T Cell count 1 year later at a significant level
    • ie. subjects with increased diversity or divergence showed greater CD4 t cell decline in the next year
  • Ratio of dS/dN (synonnyous mutation per potential site of synonymous mutation to nonsynonyous mutation per potential site of non synonymous mutation) trended toward selection to synonynous selection.
    • Suggests that there is no advantage in changing envelope protein structure for nonprogressors
    • Progressors favored nonynonymous mutation
  • Phylogenetic trees showed no predominance of a strain for extended period of time; viruses sequenced from each visit are interspersed within each others' branches (shown in 10 subjects)
    • ie. a later clone would be more genetically similar to a clone several visits before
    • Shows that there are strong enough forces to select against new virus strains at each visit, forcing the virus to constantly mutate and adapt (however, inefficient in affecting all viruses at a given time)

Figures and Tables

Figure 1

Figure 1 graphs the changes in CD4 T Cell counts over time since seroconversion for all 15 subjects, as sorted by Rapid Progressors, Moderate Progressors or Non-Progressor identification. Diversity and divergence over time is also shown. Diversity was found by the average of nucleotide differences between intravisit clones per person. Divergence was determined as the median percentage of nucleotides per clone that mutated from the original postseroconversion consensus sequence.

Table 1

Table 1 displays the overall data and calculations found by the study for all 15 subjects, as sorted by progressor groups. It indicates shows each subjects original CD4 counts, divergence, and virus copy numbers. The calculations displayed show the annual rate of CD4 T Cell decline, rate of diversity, rate of divergence and dS/dN ratios]. Subject 7 experienced a large rate of CD4 T cell decline but was not moved to the rapid progressor group because he did not exceed the threshold level.

Figure 2

Figure 2 compares the three progressor groups against their slope of diversity and slope of divergence. Graph A shows the mean slope per year of intravisit genetic diversity, showing rapid progressors to have the highest rate of diversity, followed by moderate progressors and nonprogressors. The same trend is found in Graph B, in comparing the average annual slope for the percentage of nucleotides mutated from the original seroconversion viruses across the three progressor groups. In both graphs, Rapid progressors show a significant value difference from non-progressors.

Figure 3

Figure 3 shows the phylogenetic tree generated from the viral sequencing across visits for Subject 9. The tree was generated using MEGA computer software, and is color coded chronologically, based on visit number (See: Methods). This tree demonstrates the virus' non-linear evolution, and ability to mutate and replicate previous genome patterns.

Figure 4

Figure 4 shows the phylogenetic trees generated for four subjects (5,7,8 and 14), using the MEGA computer software. Each tree shows the genetic evolution of cloned sequences from each visit. The trees similarly demonstrate the non-linear evolution of the virus along an individual branch. Rather, the virus will adapt, mutate and become more similar to a previous genome.

Discussion

Comparison to Previous Literature

McDonald et al.
  • Compared env gene variation in rapid and slow progressors (2.5 years, 10 subjects, 2 time points)
  • Similar findings
    • Rapid progressors experienced greater HIV sequence divergence
  • Differences
    • McDonald et al. found rapid progressors to have lower intravisit diversity than slow progressors
    • McDonald et al.'s conclusions on diversity changed, dependent on the gene region analyzed (C2-C5 or C2-V3 env)
  • Reasons for differences: subjects not studied from initial seroconversion, short period of time with fewer data points
Wolinsky et al.
  • Studied 6 adults, similar analyses to Markham et al.
  • Less diversity found in rapid progressors than slower progressors in 2 subjects
    • Only 1/6 showed low divergence and diversity in Markham et al, but had a higher viral load
  • Reasons for differences: The 3 subjects (from both studies) are 'exceptional'
    • ie. do not have an effective response to select against HIV infection so that the virus can keep replicating without mutations; immunologically stable
Nowak et al.
  • Nowak et al. found negative correlation between viral diversity and CD4 T cell decline - consistent with Markham et al.
  • Hypothesized that viral diversity creates clones that mutate to be unrecognizable by host T Cells, making the immune system ineffective in HIV control
  • Based off this, one should expect to see increased diversity (until cell develops unrecognizable epitopes) and then reduced diversity to these strains
    • Inconsistent with Markham et al.: found that only 2/6 of subjects that developed AIDS experienced lowered diversity
Sala et al.
  • Model suggests that virus strains changed independently depending on geographical or environmental conditions in body
  • Virus in PBMC indicates which site is most conducive for viral growth - continuously changing due to specificity and localization of immune responses
    • Markhams observations support this
    • Suggests frequency-dependent selection
    • Nonprogressors shows more nonsynonymous mutations, which creates more 'replication competent viruses' that better recognized by immune systems - this is favorable.




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