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Background: Human populations are structured by social networks, in which individuals tend to form relationships based on shared attributes. Certain attributes that are ambiguous, stigmatized or illegal can create a OhiddenO population, so-called because its members are difficult to identify. Many hidden populations are also at an elevated risk of exposure to infectious diseases. Consequently, public health agencies are presently adopting modern survey techniques that traverse social networks in hidden populations by soliciting individuals to recruit their peers, e.g., respondent-driven sampling (RDS). The concomitant accumulation of network-based epidemiological data, however, is rapidly outpacing the development of computational methods for analysis. Moreover, current analytical models rely on unrealistic assumptions, e.g., that the traversal of social networks can be modeled by a Markov chain rather than a branching process., Methodology/principal Findings: Here, we develop a new methodology based on stochastic context-free grammars (SCFGs), which are well-suited to modeling tree-like structure of the RDS recruitment process. We apply this methodology to an RDS case study of injection drug users (IDUs) in Tijuana, México, a hidden population at high risk of blood-borne and sexually-transmitted infections (i.e., HIV, hepatitis C virus, syphilis). Survey data were encoded as text strings that were parsed using our custom implementation of the inside-outside algorithm in a publicly-available software package (HyPhy), which uses either expectation maximization or direct optimization methods and permits constraints on model parameters for hypothesis testing. We identified significant latent variability in the recruitment process that violates assumptions of Markov chain-based methods for RDS analysis: firstly, IDUs tended to emulate the recruitment behavior of their own recruiter; and secondly, the recruitment of like peers (homophily) was dependent on the number of recruits., Conclusions: SCFGs provide a rich probabilistic language that can articulate complex latent structure in survey data derived from the traversal of social networks. Such structure that has no representation in Markov chain-based models can interfere with the estimation of the composition of hidden populations if left unaccounted for, raising critical implications for the prevention and control of infectious disease epidemics.

Compensatory mutations improve fitness in genotypes that contain deleterious mutations but have no beneficial effects otherwise. As such, compensatory mutations represent a very specific form of epistasis. We show that intragenic compensatory mutations occur non-randomly over gene sequence. Compensatory mutations are more likely to appear at some sites than others. Moreover, the sites of compensatory mutations are more likely than expected by chance to be near the site of the original deleterious mutation. Furthermore, compensatory mutations tend to occur more commonly in certain regions of the protein even when controlling for clustering around the site of the deleterious mutation. These results suggest that compensatory evolution at the protein level is partially predictable and may be convergent.

Natural selection is a fundamental process affecting all evolving populations. In the simplest case, positive selection increases the frequency of alleles that confer a fitness advantage relative to the rest of the population, or increases its genetic diversity, and negative selection removes those alleles that are deleterious. Codon-based models of molecular evolution are able to infer signatures of selection from alignments of homologous sequences by estimating the relative rates of synonymous (dS) and non-synonymous substitutions (dN). Datamonkey (http://www.datamonkey.org) provides a user-friendly web interface to a wide collection of state-of-the-art statistical techniques for estimating dS and dN and identifying codons and lineages under selection, even in the presence of recombinant sequences.

Objective: Missense mutations in HIV-1 reverse transcriptase are frequently selected in response to therapy; we examined whether silent mutations were also selected for by HIV therapy., Design: Retrospective, observational analysis. Biochemical assays., Methods: A comparison of the reverse transcriptase gene, from antiretroviral- naive (N = 812) and experienced individuals (N = 2212), reveals two silent mutations (K65K and K66K) that are strongly associated with treatment experience. To assess reverse transcription efficiency, steady-state kinetic assays were carried out using recombinant purified HIV-1 reverse transcriptase and a series of synthetic RNA/DNA template/primer substrates. The RNA templates spanned codons 60-77 in the reverse transcriptase and included different combinations of mutations at codons 65, 66, 67, and 70., Results: Silent AAG mutations (or mixtures) at reverse transcriptase codons 65 and/or 66 were observed in 812 samples from 351 patients and 2129 samples from 829 patients, respectively. In clade B samples, there was a very strong relationship between the silent mutations and the thymidine analogue mutations, in particular D67N. Steady-state kinetic experiments demonstrated that HIV-1 reverse transcriptase exhibited a strong tendency to pause and/or dissociate at codons 65 and 66 on RNA templates that contained the D67N and K70R mutations. However, when the K66 or K66 AAA to AAG mutations were added to the background of the 67 and 70 mutational changes, these pausing and/or dissociation events were largely alleviated., Conclusion: Silent mutations at codons 65 and/or 66 are strongly coselected with thymidine analogue mutations. These data provide the first evidence for an RNA-level mechanism of direct relevance to drug resistance.

Human immunodeficiency virus (HIV-1) can rapidly evolve due to selection pressures exerted by HIV-specific immune responses, antiviral agents, and to allow the virus to establish infection in different compartments in the body. Statistical models applied to HIV-1 sequence data can help to elucidate the nature of these selection pressures through comparisons of non-synonymous (or amino acid changing) and synonymous (or amino acid preserving) substitution rates. These models also need to take into account the non-independence of sequences due to their shared evolutionary history. We review how we have developed these methods and have applied them to characterize the evolution of HIV-1 in vivo. To illustrate our methods, we present an analysis of compartment-specific evolution of HIV-1 env in blood and cerebrospinal fluid and of site-to-site variation in the gag gene of subtype C HIV-1.

Unlabelled: Spidermonkey is a new component of the Datamonkey suite of phylogenetic tools that provides methods for detecting coevolving sites from a multiple alignment of homologous nucleotide or amino acid sequences. It reconstructs the substitution history of the alignment by maximum likelihood-based phylogenetic methods, and then analyzes the joint distribution of substitution events using Bayesian graphical models to identify significant associations among sites., Availability: Spidermonkey is publicly available both as a web application at http://www.data-monkey.org and as a stand-alone component of the phylogenetic software package HyPhy, which is freely distributed on the web (http://www.hyphy.org) as precompiled binaries and open source.

We develop a model-based phylogenetic maximum likelihood test for evidence of preferential substitution toward a given residue at individual positions of a protein alignment--directional evolution of protein sequences (DEPS). DEPS can identify both the target residue and sites evolving toward it, help detect selective sweeps and frequency-dependent selection--scenarios that confound most existing tests for selection, and achieve good power and accuracy on simulated data. We applied DEPS to alignments representing different genomic regions of influenza A virus (IAV), sampled from avian hosts (H5N1 serotype) and human hosts (H3N2 serotype), and identified multiple directionally evolving sites in 5/8 genomic segments of H5N1 and H3N2 IAV. We propose a simple descriptive classification of directionally evolving sites into 5 groups based on the temporal distribution of residue frequencies and document known functional correlates, such as immune escape or host adaptation.

After acute HIV infection, CD8(+) T cells are able to control viral replication to a set point. This control is often lost after superinfection, although the mechanism behind this remains unclear. In this study, we illustrate in an HLA-B27(+) subject that loss of viral control after HIV superinfection coincides with rapid recombination events within two narrow regions of Gag and Env. Screening for CD8(+) T cell responses revealed that each of these recombination sites (approximately 50 aa) encompassed distinct regions containing two immunodominant CD8 epitopes (B27-KK10 in Gag and Cw1-CL9 in Env). Viral escape and the subsequent development of variant-specific de novo CD8(+) T cell responses against both epitopes were illustrative of the significant immune selection pressures exerted by both responses. Comprehensive analysis of the kinetics of CD8 responses and viral evolution indicated that the recombination events quickly facilitated viral escape from both dominant WT- and variant-specific responses. These data suggest that the ability of a superinfecting strain of HIV to overcome preexisting immune control may be related to its ability to rapidly recombine in critical regions under immune selection pressure. These data also support a role for cellular immune pressures in driving the selection of new recombinant forms of HIV.

We assessed the effect of herpes simplex virus type 2 (HSV-2) acquisition on the plasma HIV RNA and CD4 cell levels among individuals with primary HIV infection using a retrospective cohort analysis. We studied 119 adult, antiretroviral-naive, recently HIV-infected men with a negative HSV-2-specific enzyme immunoassay (EIA) result at enrollment. HSV-2 acquisition was determined by seroconversion on HSV-2 EIA, confirmed by Western blot analysis. Ten men acquired HSV-2 infection a median of 1.3 years after HIV infection (HSV-2 incidence rate of 7.4 per 100 person-years of follow-up). The median time of follow-up after acquiring HSV-2 infection was 303 days. All men except 1 were asymptomatic during HSV-2 acquisition, and only 1 HSV-2 seroconverter, who was asymptomatic, had a transient increase in blood HIV load (0.5 log10 copies/mL over 11 days). The HSV-2 incidence rate was high in our cohort of recently HIV-infected individuals; however, HSV-2 acquisition did not significantly change the plasma HIV dynamics and CD4 cell levels.

Resistance genotyping provides an important resource for the clinical management of patients infected with human immunodeficiency virus type 1 (HIV-1). However, resistance to protease (PR) inhibitors (PIs) is a complex phenotype shaped by interactions among nearly half of the residues in HIV-1 PR. Previous studies of the genetic basis of PI resistance focused on fixed substitutions among populations of HIV-1, i.e., host-specific adaptations. Consequently, they are susceptible to a high false discovery rate due to founder effects. Here, we employ sequencing "mixtures" (i.e., ambiguous base calls) as a site-specific marker of genetic variation within patients that is independent of the phylogeny. We demonstrate that the transient response to selection by PIs is manifested as an excess of nonsynonymous mixtures. Using a sample of 5,651 PR sequences isolated from both PI-naive and -treated patients, we analyze the joint distribution of mixtures and eight PIs as a Bayesian network, which distinguishes residue-residue interactions from direct associations with PIs. We find that selection for resistance is associated with the emergence of nonsynonymous mixtures in two distinct groups of codon sites clustered along the substrate cleft and distal regions of PR, respectively. Within-patient evolution at several positions is independent of PIs, including those formerly postulated to be involved in resistance. These positions are under strong positive selection in the PI-naive patient population, implying that other factors can produce spurious associations with resistance, e.g., mutational escape from the immune response.

The third variable loop (V3) of the human immunodeficiency virus type 1 (HIV-1) envelope is a principal determinant of antibody neutralization and progression to AIDS. Although it is undoubtedly an important target for vaccine research, extensive genetic variation in V3 remains an obstacle to the development of an effective vaccine. Comparative methods that exploit the abundance of sequence data can detect interactions between residues of rapidly evolving proteins such as the HIV-1 envelope, revealing biological constraints on their variability. However, previous studies have relied implicitly on two biologically unrealistic assumptions: (1) that founder effects in the evolutionary history of the sequences can be ignored, and; (2) that statistical associations between residues occur exclusively in pairs. We show that comparative methods that neglect the evolutionary history of extant sequences are susceptible to a high rate of false positives (20%-40%). Therefore, we propose a new method to detect interactions that relaxes both of these assumptions. First, we reconstruct the evolutionary history of extant sequences by maximum likelihood, shifting focus from extant sequence variation to the underlying substitution events. Second, we analyze the joint distribution of substitution events among positions in the sequence as a Bayesian graphical model, in which each branch in the phylogeny is a unit of observation. We perform extensive validation of our models using both simulations and a control case of known interactions in HIV-1 protease, and apply this method to detect interactions within V3 from a sample of 1,154 HIV-1 envelope sequences. Our method greatly reduces the number of false positives due to founder effects, while capturing several higher-order interactions among V3 residues. By mapping these interactions to a structural model of the V3 loop, we find that the loop is stratified into distinct evolutionary clusters. We extend our model to detect interactions between the V3 and C4 domains of the HIV-1 envelope, and account for the uncertainty in mapping substitutions to the tree with a parametric bootstrap.

CD8(+) cytotoxic T-lymphocytes (CTLs) perform a critical role in the immune control of viral infections, including those caused by human immunodeficiency virus type 1 (HIV-1) and hepatitis C virus (HCV). As a result, genetic variation at CTL epitopes is strongly influenced by host-specific selection for either escape from the immune response, or reversion due to the replicative costs of escape mutations in the absence of CTL recognition. Under strong CTL-mediated selection, codon positions within epitopes may immediately "toggle" in response to each host, such that genetic variation in the circulating virus population is shaped by rapid adaptation to immune variation in the host population. However, this hypothesis neglects the substantial genetic variation that accumulates in virus populations within hosts. Here, we evaluate this quantity for a large number of HIV-1- (n > or = 3,000) and HCV-infected patients (n > or = 2,600) by screening bulk RT-PCR sequences for sequencing "mixtures" (i.e., ambiguous nucleotides), which act as site-specific markers of genetic variation within each host. We find that nonsynonymous mixtures are abundant and significantly associated with codon positions under host-specific CTL selection, which should deplete within-host variation by driving the fixation of the favored variant. Using a simple model, we demonstrate that this apparently contradictory outcome can be explained by the transmission of unfavorable variants to new hosts before they are removed by selection, which occurs more frequently when selection and transmission occur on similar time scales. Consequently, the circulating virus population is shaped by the transmission rate and the disparity in selection intensities for escape or reversion as much as it is shaped by the immune diversity of the host population, with potentially serious implications for vaccine design.

The addition of asparagine (N)-linked polysaccharide chains (i.e., glycans) to the gp120 and gp41 glycoproteins of human immunodeficiency virus type 1 (HIV-1) envelope is not only required for correct protein folding, but also may provide protection against neutralizing antibodies as a "glycan shield." As a result, strong host-specific selection is frequently associated with codon positions where nonsynonymous substitutions can create or disrupt potential N-linked glycosylation sites (PNGSs). Moreover, empirical data suggest that the individual contribution of PNGSs to the neutralization sensitivity or infectivity of HIV-1 may be critically dependent on the presence or absence of other PNGSs in the envelope sequence. Here we evaluate how glycan-glycan interactions have shaped the evolution of HIV-1 envelope sequences by analyzing the distribution of PNGSs in a large-sequence alignment. Using a "covarion"-type phylogenetic model, we find that the rates at which individual PNGSs are gained or lost vary significantly over time, suggesting that the selective advantage of having a PNGS may depend on the presence or absence of other PNGSs in the sequence. Consequently, we identify specific interactions between PNGSs in the alignment using a new paired-character phylogenetic model of evolution, and a Bayesian graphical model. Despite the fundamental differences between these two methods, several interactions are jointly identified by both. Mapping these interactions onto a structural model of HIV-1 gp120 reveals that negative (exclusive) interactions occur significantly more often between colocalized glycans, while positive (inclusive) interactions are restricted to more distant glycans. Our results imply that the adaptive repertoire of alternative configurations in the HIV-1 glycan shield is limited by functional interactions between the N-linked glycans. This represents a potential vulnerability of rapidly evolving HIV-1 populations that may provide useful glycan-based targets for neutralizing antibodies.

Epistasis is an important and poorly understood aspect of mutations and strongly influences the evolutionary impact of genetic variation on adaptation and fitness. Although recent studies have begun to characterize the distribution of epistatic effects between mutations affecting fitness, there is currently a lack of empirical information on the underlying biological causes of these epistatic interactions. What are the functional constraints that determine the effectiveness of a compensatory mutation at restoring fitness? We have measured the effect-sizes of 52 compensatory mutations affecting nine different deleterious mutations in the major capsid and spike proteins of the DNA bacteriophage phiX174. On average, an experimentally detectable compensatory mutation recovers about two-thirds of the fitness cost of the preceding deleterious mutation. Variation in fitness effect-sizes is only weakly associated with measures of the distance separating the deleterious and compensatory mutations in the amino acid sequence or the folded protein structure. However, there is a strong association of fitness effect-size with the correlation in the effects of the mutations on the biochemical properties of amino acids. A compensatory mutation has the largest effect-size, on average, when both the compensatory and deleterious mutations have radical effects on the overall biochemical make-up of the amino acids. By examining the relative contributions of specific biochemical properties to variation in fitness effect-size, we find that the area and charge of amino acids have a major influence, which suggests that the complexity of the amino acid phenotype is simplified by selection into a reduced number of phenotypic components.