CHAPTER 1 INTRODUCTION
1.7 Measurement of viral fitness or replication capacity
1.7.1 Starting material
49 were not detectable in the blood but may have been present in the lymph nodes or other compartments. Also, CD8+ T cell responses to B*57-associated variants have previously been detected in HLA-B*57 positive infants [230]. Further, in contrast to the findings of Schneidewind et al. (2009) [227], other groups have reported that individuals with HLA- B*57 or HLA-B*27 who received a virus with escape mutations in Gag from individuals with these same HLA alleles did not display a favourable clinical course [187, 231].
An overview of the factors influencing HIV-1 disease progression is illustrated in Figure 1.3.
Figure 1.3 Spectrum and markers of HIV-1 disease progression rate and factors influencing the rate of progression
(i) Timeline indicating the wide variability in time of progression to AIDS in individuals infected with HIV-1.
(ii) The graph shows early viral set point as a predictor of HIV-1 disease progression and other commonly used and/or significant markers of disease progression rate are listed. The graph was adapted from Kuritzkes and Walker (2007) [74].
(iii) Overlapping and interacting host genetic, host immune and viral factors influencing the rate of HIV-1 disease progression are outlined. HLA class I alleles are most strongly associated with disease progression rate and interactions between HLA alleles and other immune factors which may partly explain the association are shown. Highlighted with red arrows is the interaction pathway suggesting that certain HLA alleles restrict Gag-specific CD8+ T cell responses which select for escape mutations in Gag that impact viral fitness and therefore disease progression. This pathway is highlighted, and HLA and viral fitness factors are underlined, since the focus of the present study is to investigate the influence of HLA-driven mutations in Gag-protease on HIV-1 fitness and therefore disease progression.
HIV-1 – human immunodeficiency virus type 1; AIDS – acquired immunodeficiency syndrome; LTNP – long-term non- progressors; EC – elite controllers; RNA – ribonucleic acid; CD – cluster of differentiation; CCR5 – C-C chemokine receptor 5; Tsg101 – tumour susceptibility gene 101 protein; IFN-α - interferon alpha; APOBEC3G - apolipoprotein B messenger RNA editing catalytic subunit-like protein 3G; TRIM5α - tripartite motif-containing 5 alpha; KIR – killer cell immunoglobulin-like receptor; HLA – human leukocyte antigen; ADCC – antibody-dependent cell-mediated cytotoxic activity; Gag – group specific antigen; Nef – negative regulation factor.
50
D ete rm in a n ts o f d is ea se p ro g re ss io n
Viral set point
60 000
30 000 (average)
12 000
Viral load (HIV-1 RNA copies/ml)
1 0 Time post-infection (years)
Disease progression:
FAST
SLOW
Progression Markers Viral set point
Viral load
Immune activation markers
CD4+ T cell count CD4+ T cell decline Time to AIDS following HIV-1 infection (years)
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
indefinite
Rapid progressors Typical progressors
Slow progressors:
LTNP, EC
CCR5 mutations IFN-α mutations Tsg101 mutations APOBEC3G mutations
Cyclophilin A mutations TRIM5α mutations Cytokine gene mutations KIR profile
HLA class I profile Potency of ADCC Immune activation levels HIV-specific CD4 activity HIV-specific CD8 activity
Gag-specific CD8 responses
H o st F a ct o rs V ir a l f a cto rs
Host immune responses Host genetic factors
Nef deletions HIV-1 fitness Escape mutations (Gag)
i
ii
iii
fluorescent protein (GFP; which can be detected by flow cytometry) [219, 234, 235]. Other methods of detection include direct detection of viral gene products/activities or reporter genes engineered into cells [232] (Section 1.7.1.3). Fitness differences can be directly attributed to the mutation and results are therefore easily interpreted. However, a limitation of this approach is the consideration of the fitness consequences of a particular mutation outside of the context of the natural viral sequence background, where co-existing mutations are likely to occur [236]. Introduction of numerous secondary mutations through site- directed mutagenesis is possible, however this process is labour-intensive and still may not recapitulate natural conditions.
1.7.1.2 Recombinant viruses
In contrast to point mutations, a entire genomic region may be inserted into a standard viral backbone (with or without a reporter gene for detection), allowing for a direct link between measured fitness and the viral protein or region of interest [236].
The genomic region analysed may be a single clone or a pool of sequences amplified from clinical samples or other sources [236]. The advantage of using a single clone is that the precise sequence is known, while a population sequence reflects mutations present in the virus pool but not necessarily occurring in combination in one virus strain. However, analysis of a virus pool may be more representative of the diversity in vivo.
The construction of recombinant viruses may be performed using restriction enzymes, a yeast recombination system, or homologous recombination of the viral genomic region (amplified using primers complementary to the vector) and vector in mammalian cells [237,
52 238]. Due to the variability of HIV-1, there is often a lack of convenient, unique restriction sites [238, 239]. A yeast recombination system does not require unique restriction sites, but (with the exception of a very recently developed system [238]) sub-cloning is required to achieve full infectivity [238-240]. Homologous recombination is less labour-intensive, although it is time-consuming as eukaryotic recombination is of poor efficiency [238].
Another alternative is gene complementation involving transfection of cells with a gene expression vector and a full length vector with the relevant gene deleted to produce pseudovirions [233, 241]. However, this introduces foreign genetic elements [238] and since pseudovirions may only complete one replication cycle, this may only be applied in single cycle fitness assays (Section 1.7.3.1).
Although viral fitness effects measured by this approach can be attributed to a genomic region, it may not be clear which mutations are primarily responsible, necessitating further investigations [236]. Another limitation is that since the genomic region is not in the natural context, interactions with other genes are not taken into account [232, 236]. For example, Gag interactions with gp41 in Env (Section 1.3.7) may be disrupted by examining either protein in isolation. A measurement of whole viral isolates is therefore likely to yield the most reliable fitness results [232, 236].
1.7.1.3 Whole isolates
HIV-1 may be isolated from peripheral blood mononuclear cells (PBMCs) or plasma, with similar or higher rates of success from PBMCs and greater efficiency from PBMCs [242, 243]. There are also methods to extract clones from viral isolates [244] to allow fitness of specific clones to be measured. Despite accuracy of measurement, the genetic determinant
for the fitness effect is not known and isolation of virus requires extra costs, is time- consuming and difficult for some strains [236]. If the fitness of whole isolates is measured in primary cells (e.g. PBMCs), measurement of fitness is limited to the direct detection of viral products (e.g. p24 antigen by enzyme-linked immunosorbent assay [ELISA]) or activity (e.g. reverse transcriptase activity) [232], neither of which assess particle infectivity [71].
However, if isolates are grown in a cell line, the cell line may be manipulated to express a reporter gene, such as GFP, on infection, thereby allowing an easy, convenient, and relatively inexpensive measure of viral spread in the culture [71, 235].