Phylogenetic approach reveals that virus genotype largely determines HIV set-point viral load

HIV virulence, i.e. the time of progression to AIDS, varies greatly among patients. As for other rapidly evolving pathogens of humans, it is difficult to know if this variance is controlled by the genotype of the host or that of the virus because the transmission chain is usually unknown. We apply the phylogenetic comparative approach (PCA) to estimate the heritability of a trait from one infection to the next, which indicates the control of the virus genotype over this trait. The idea is to use viral RNA sequences obtained from patients infected by HIV-1 subtype B to build a phylogeny, which approximately reflects the transmission chain. Heritability is measured statistically as the propensity for patients close in the phylogeny to exhibit similar infection trait values. The approach reveals that up to half of the variance in set-point viral load, a trait associated with virulence, can be heritable. Our estimate is significant and robust to noise in the phylogeny. We also check for the consistency of our approach by showing that a trait related to drug resistance is almost entirely heritable. Finally, we show the importance of taking into account the transmission chain when estimating correlations between infection traits. The fact that HIV virulence is, at least partially, heritable from one infection to the next has clinical and epidemiological implications. The difference between earlier studies and ours comes from the quality of our dataset and from the power of the PCA, which can be applied to large datasets and accounts for within-host evolution. The PCA opens new perspectives for approaches linking clinical data and evolutionary biology because it can be extended to study other traits or other infectious diseases.     

Assessing predicted HIV-1 replicative capacity in a clinical setting

HIV-1 replicative capacity (RC) provides a measure of within-host fitness and is determined in the context of phenotypic drug resistance testing. However it is unclear how these in-vitro measurements relate to in-vivo processes. Here we assess RCs in a clinical setting by combining a previously published machine-learning tool, which predicts RC values from partial pol sequences with genotypic and clinical data from the Swiss HIV Cohort Study. The machine-learning tool is based on a training set consisting of 65000 RC measurements paired with their corresponding partial pol sequences. We find that predicted RC values (pRCs) correlate significantly with the virus load measured in 2073 infected but drug na?ve individuals. Furthermore, we find that, for 53 pairs of sequences, each pair sampled in the same infected individual, the pRC was significantly higher for the sequence sampled later in the infection and that the increase in pRC was also significantly correlated with the increase in plasma viral load and with the length of the time-interval between the sampling points. These findings indicate that selection within a patient favors the evolution of higher replicative capacities and that these in-vitro fitness measures are indicative of in-vivo HIV virus load.     

Inferring epidemic contact structure from phylogenetic trees

Contact structure is believed to have a large impact on epidemic spreading and consequently using networks to model such contact structure continues to gain interest in epidemiology. However, detailed knowledge of the exact contact structure underlying real epidemics is limited. Here we address the question whether the structure of the contact network leaves a detectable genetic fingerprint in the pathogen population. To this end we compare phylogenies generated by disease outbreaks in simulated populations with different types of contact networks. We find that the shape of these phylogenies strongly depends on contact structure. In particular, measures of tree imbalance allow us to quantify to what extent the contact structure underlying an epidemic deviates from a null model contact network and illustrate this in the case of random mixing. Using a phylogeny from the Swiss HIV epidemic, we show that this epidemic has a significantly more unbalanced tree than would be expected from random mixing.     

Design, expression, and processing of epitomized hepatitis C virus-encoded CTL epitopes

Hepatitis C virus (HCV) vaccine efficacy may crucially depend on immunogen length and coverage of viral sequence diversity. However, covering a considerable proportion of the circulating viral sequence variants would likely require long immunogens, which for the conserved portions of the viral genome, would contain unnecessarily redundant sequence information. In this study, we present the design and in vitro performance analysis of a novel "epitome" approach that compresses frequent immune targets of the cellular immune response against HCV into a shorter immunogen sequence. Compression of immunological information is achieved by partial overlapping shared sequence motifs between individual epitopes. At the same time, sequence diversity coverage is provided by taking advantage of emerging cross-reactivity patterns among epitope variants so that epitope variants associated with the broadest variant cross-recognition are preferentially included. The processing and presentation analysis of specific epitopes included in such a compressed, in vitro-expressed HCV epitome indicated effective processing of a majority of tested epitopes, although re-presentation of some epitopes may require refined sequence design. Together, the present study establishes the epitome approach as a potential powerful tool for vaccine immunogen design, especially suitable for the induction of cellular immune responses against highly variable pathogens.     

Abacavir Induced T Cell Reactivity from Drug Na?ve Individuals Shares Features of Allo-Immune Responses

Abacavir hypersensitivity is a severe hypersensitivity reaction which occurs exclusively in carriers of the HLA-B*57∶01 allele. In vitro culture of PBMC with abacavir results in the outgrowth of abacavir-reacting CD8⁺ T cells, which release IFNγ and are cytotoxic. How this immune response is induced and what is recognized by these T cells is still a matter of debate. We analyzed the conditions required to develop an abacavir-dependent T cell response in vitro. The abacavir reactivity was independent of co-stimulatory signals, as neither DC maturation nor release of inflammatory cytokines were observed upon abacavir exposure. Abacavir induced T cells arose in the absence of professional APC and stemmed from naïve and memory compartments. These features are reminiscent of allo-reactivity. Screening for allo-reactivity revealed that about 5% of generated T cell clones (n = 136) from three donors were allo-reactive exclusively to the related HLA-B*58∶01. The addition of peptides which can bind to the HLA-B*57∶01-abacavir complex and to HLA-B*58∶01 during the induction phase increased the proportion of HLA-B*58∶01 allo-reactive T cell clones from 5% to 42%. In conclusion, abacavir can alter the HLA-B*57∶01-peptide complex in a way that mimics an allo-allele (‘altered self-allele’) and create the potential for robust T cell responses.     

Biofilm structure differentiation based on multi-resolution analysis

Quantitative parameters for describing the morphology of biofilms are crucial towards establishing the influence of growing conditions on biofilm structure. Parameters used in earlier studies generally fail to differentiate complex three-dimensional structures. This article presents a novel approach of defining a parameter vector based on the energy signature of multi-resolution analysis, which was applied to differentiating biofilm structures from confocal laser scanning microscopy (CLSM) biofilm images. The parameter vector distinguished differences in the spatial arrangements of synthetic images. For real CLSM images, this parameter vector detected subtle differences in biofilm structure for three sample cases: (1) two adjacent images of a CLSM stack; (2) two partial stacks from the same CLSM stack with equal numbers of images but spatially offset by one image; and (3) three complete CLSM stacks from different bacterial strains. It was also observed that filtering the noise in CLSM images enhanced the sensitivity of the differentiation using our parameter vector.     

Metal ions may suppress or enhance cellular differentiation in Candida albicans and Candida tropicalis biofilms

Candida albicans and Candida tropicalis are polymorphic fungi that develop antimicrobial-resistant biofilm communities that are characterized by multiple cell morphotypes. This study investigated cell type interconversion and drug and metal resistance as well as community organization in biofilms of these microorganisms that were exposed to metal ions. To study this, Candida biofilms were grown either in microtiter plates containing gradient arrays of metal ions or in the Calgary Biofilm Device for high-throughput susceptibility testing. Biofilm formation and antifungal resistance were evaluated by viable cell counts, tetrazolium salt reduction, light microscopy, and confocal laser scanning microscopy in conjunction with three-dimensional visualization. We discovered that subinhibitory concentrations of certain metal ions (CrO(4)(2-), Co(2+), Cu(2+), Ag(+), Zn(2+), Cd(2+), Hg(2+), Pb(2+), AsO(2)(-), and SeO(3)(2-)) caused changes in biofilm structure by blocking or eliciting the transition between yeast and hyphal cell types. Four distinct biofilm community structure types were discerned from these data, which were designated "domed," "layer cake," "flat," and "mycelial." This study suggests that Candida biofilm populations may respond to metal ions to form cell-cell and solid-surface-attached assemblages with distinct patterns of cellular differentiation.