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Zinc is essential for cellular functions as it is a catalytic and structural component of many proteins. In contrast, cadmium is not required in biological systems and is toxic. Zinc and cadmium levels are closely monitored and regulated as their excess causes cell stress. To maintain homeostasis, organisms induce metal detoxification gene programs through stress responsive transcriptional regulatory complexes. In Caenorhabditis elegans, the MDT-15 subunit of the evolutionarily conserved Mediator transcriptional coregulator is required to induce genes upon exposure to excess zinc and cadmium. However, the regulatory partners of MDT-15 in this response, its role in cellular and physiological stress adaptation, and the putative role for mammalian MED15 in the metal stress responses remain unknown. Here, we show that MDT-15 interacts physically and functionally with the Nuclear Hormone Receptor HIZR-1 to promote molecular, cellular, and organismal adaptation to cadmium and excess zinc. Using gain- and loss-of-function mutants and qRT-PCR and reporter analysis, we find that mdt-15 and hizr-1 cooperate to induce zinc and cadmium responsive genes. Moreover, the two proteins interact physically in yeast-two-hybrid assays and this interaction is enhanced by the addition of zinc or cadmium, the former a known ligand of HIZR-1. Functionally, mdt-15 and hizr-1 mutants show defective storage of excess zinc in the gut and are hypersensitive to zinc-induced reductions in egg-laying. Furthermore, mdt-15 but not hizr-1 mutants are hypersensitive to cadmium-induced reductions in egg-laying, suggesting potential divergence of regulatory pathways. Lastly, mammalian MDT-15 orthologs bind genomic regulatory regions of metallothionein and zinc transporter genes in a cadmium and zinc-stimulated fashion, and human MED15 is required to induce a metallothionein gene in lung adenocarcinoma cells exposed to cadmium. Collectively, our data show that mdt-15 and hizr-1 cooperate to regulate cadmium detoxification and zinc storage and that this mechanism is at least partially conserved in mammals., Competing Interests: The authors have declared that no competing interests exist.

Objectives: HIV drug resistance, measured by the genotypic susceptibility score (GSS), has a deleterious effect on the virological outcome of HIV-1-infected patients. However, it is not known if GSS retains any predictive value for CD4 recovery in patients with suppressed viral load., Methods: Four hundred and six patients on virological failure (>500 copies/mL) with GSS  : <6 months prior to switch therapy who achieved undetectable plasma viral load (<50 copies/mL) within 1 year, remained undetectable >1 year on an unchanged regimen and had CD4 data available during entire follow-up were included. Adjusted and unadjusted analyses of all characteristics at switch related to CD4 recovery were made for three time frames: (i) 'switch-suppression'; (ii) 'suppression-1 year'; and (iii) 'switch-1 year'., Results: Higher GSS was associated with a greater CD4 recovery between 'switch' and '1 year' in the unadjusted analysis (P = 0.010); however, the effect of GSS was no longer statistically significant after adjusting for pre-switch clinical (CD4 count and plasma viral load) and demographic variables. Furthermore, only a lower pre-switch CD4 count was associated with increased CD4 recovery in the 'suppression-1 year' period in both unadjusted and adjusted models. The main CD4 recovery occurred in 'switch-suppression' and the variables associated, both unadjusted and adjusted, were CD4 and plasma viral load at switch, maintaining a trend for GSS (P = 0.06)., Conclusions: In individuals who re-suppressed HIV viraemia after switching therapy, regimens having a higher GSS were associated with improved CD4 recovery only during the period from switch to virological suppression, but, once viral load is re-suppressed, the GSS of the new regimen has no further effect on subsequent CD4 recovery., (© The Author 2016. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Viral phylogenetic methods contribute to understanding how HIV spreads in populations, and thereby help guide the design of prevention interventions. So far, most analyses have been applied to well-sampled concentrated HIV-1 epidemics in wealthy countries. To direct the use of phylogenetic tools to where the impact of HIV-1 is greatest, the Phylogenetics And Networks for Generalized HIV Epidemics in Africa (PANGEA-HIV) consortium generates full-genome viral sequences from across sub-Saharan Africa. Analyzing these data presents new challenges, since epidemics are principally driven by heterosexual transmission and a smaller fraction of cases is sampled. Here, we show that viral phylogenetic tools can be adapted and used to estimate epidemiological quantities of central importance to HIV-1 prevention in sub-Saharan Africa. We used a community-wide methods comparison exercise on simulated data, where participants were blinded to the true dynamics they were inferring. Two distinct simulations captured generalized HIV-1 epidemics, before and after a large community-level intervention that reduced infection levels. Five research groups participated. Structured coalescent modeling approaches were most successful: phylogenetic estimates of HIV-1 incidence, incidence reductions, and the proportion of transmissions from individuals in their first 3 months of infection correlated with the true values (Pearson correlation > 90%), with small bias. However, on some simulations, true values were markedly outside reported confidence or credibility intervals. The blinded comparison revealed current limits and strengths in using HIV phylogenetics in challenging settings, provided benchmarks for future methods' development, and supports using the latest generation of phylogenetic tools to advance HIV surveillance and prevention., (© The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Models of the spread of disease in a population often make the simplifying assumption that the population is homogeneously mixed, or is divided into homogeneously mixed compartments. However, human populations have complex structures formed by social contacts, which can have a significant influence on the rate of epidemic spread. Contact network models capture this structure by explicitly representing each contact which could possibly lead to a transmission. We developed a method based on approximate Bayesian computation (ABC), a likelihood-free inference strategy, for estimating structural parameters of the contact network underlying an observed viral phylogeny. The method combines adaptive sequential Monte Carlo for ABC, Gillespie simulation for propagating epidemics though networks, and a kernel-based tree similarity score. We used the method to fit the Barabási-Albert network model to simulated transmission trees, and also applied it to viral phylogenies estimated from ten published HIV sequence datasets. This model incorporates a feature called preferential attachment (PA), whereby individuals with more existing contacts accumulate new contacts at a higher rate. On simulated data, we found that the strength of PA and the number of infected nodes in the network can often be accurately estimated. On the other hand, the mean degree of the network, as well as the total number of nodes, was not estimable with ABC. We observed sub-linear PA power in all datasets, as well as higher PA power in networks of injection drug users. These results underscore the importance of considering contact structures when performing phylodynamic inference. Our method offers the potential to quantitatively investigate the contact network structure underlying viral epidemics.

For infectious diseases, a genetic cluster is a group of closely related infections that is usually interpreted as representing a recent outbreak of transmission. Genetic clustering methods are becoming increasingly popular for molecular epidemiology, especially in the context of HIV where there is now considerable interest in applying these methods to prioritize groups for public health resources such as pre-exposure prophylaxis. To date, genetic clustering has generally been performed with ad hoc algorithms, only some of which have since been encoded and distributed as free software. These algorithms have seldom been validated on simulated data where clusters are known, and their interpretation and similarities are not transparent to users outside of the field. Here, I provide a brief overview on the development and inter-relationships of genetic clustering methods, and an evaluation of six methods on data simulated under an epidemic model in a risk-structured population. The simulation analysis demonstrates that the majority of clustering methods are systematically biased to detect variation in sampling rates among subpopulations, not variation in transmission rates. I discuss these results in the context of previous work and the implications for public health applications of genetic clustering.

Effective surveillance and treatment strategies are required to control the hepatitis C virus (HCV) epidemic. Phylogenetic analyses are powerful tools for reconstructing the evolutionary history of viral outbreaks and identifying transmission clusters. These studies often rely on Sanger sequencing which typically generates a single consensus sequence for each infected individual. For rapidly mutating viruses such as HCV, consensus sequencing underestimates the complexity of the viral quasispecies population and could therefore generate different phylogenetic tree topologies. Although deep sequencing provides a more detailed quasispecies characterization, in-depth phylogenetic analyses are challenging due to dataset complexity and computational limitations. Here, we apply deep sequencing to a characterized population to assess its ability to identify phylogenetic clusters compared with consensus Sanger sequencing. For deep sequencing, a sample specific threshold determined by the 50th percentile of the patristic distance distribution for all variants within each individual was used to identify clusters. Among seven patristic distance thresholds tested for the Sanger sequence phylogeny ranging from 0.005-0.06, a threshold of 0.03 was found to provide the maximum balance between positive agreement (samples in a cluster) and negative agreement (samples not in a cluster) relative to the deep sequencing dataset. From 77 HCV seroconverters, 10 individuals were identified in phylogenetic clusters using both methods. Deep sequencing analysis identified an additional 4 individuals and excluded 8 other individuals relative to Sanger sequencing. The application of this deep sequencing approach could be a more effective tool to understand onward HCV transmission dynamics compared with Sanger sequencing, since the incorporation of minority sequence variants improves the discrimination of phylogenetically linked clusters., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Background & Aims: Understanding HCV transmission among people who inject drugs (PWID) is important for designing prevention strategies. This study investigated whether HCV infection among younger injectors occurs from few or many transmission events from older injectors to younger injectors among PWID in Vancouver, Canada., Methods: HCV antibody positive participants at enrolment or follow-up (1996-2012) were tested for HCV RNA and sequenced (Core-E2). Time-stamped phylogenetic trees were inferred using Bayesian Evolutionary Analysis Sampling Trees (BEAST). Association of age with phylogeny was tested using statistics implemented in the software Bayesian Tip Significance (BaTS) testing. Factors associated with clustering (maximum cluster age: five years) were identified using logistic regression., Results: Among 699 participants with HCV subtype 1a, 1b, 2b and 3a infection (26% female, 24% HIV+): 21% were younger (<27years), and 10% had recent HCV seroconversion. When inferred cluster age was limited to <5years, 15% (n=108) were in clusters/pairs. Although a moderate degree of segregation was observed between younger and older participants, there was also transmission between age groups. Younger age (<27 vs. >40, AOR: 3.14; 95% CI: 1.54, 6.39), HIV (AOR: 1.97; 95% CI: 1.22, 3.18) and subtype 3a (AOR: 2.12; 95% CI: 1.33, 3.38) were independently associated with clustering., Conclusions: In this population of PWID from Vancouver, HCV among young injectors was seeded from many transmission events between HCV-infected older and younger injectors. Phylogenetic clustering was associated with younger age and HIV. These data suggest that HCV transmission among PWID is complex, with transmission occurring between and among older and younger PWID., (Copyright © 2016 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.)

Background: HIV evolves rapidly and therefore infections with similar genetic sequences are likely linked by recent transmission events. Clusters of related infections can represent subpopulations with high rates of transmission. We describe the implementation of an automated near real-time system to monitor and characterise HIV transmission hotspots in British Columbia, Canada., Methods: In this implementation case study, we applied a monitoring system to the British Columbia drug treatment database, which holds more than 32 000 anonymised HIV genotypes for nearly 9000 residents of British Columbia living with HIV. On average, five to six new HIV genotypes are deposited in the database every day, which triggers an automated reanalysis of the entire database. We extracted clusters of five or more individuals with short phylogenetic distances between their respective HIV sequences. The system generated monthly reports of the growth and characteristics of clusters that were distributed to public health officers., Findings: In June, 2014, the monitoring system detected the expansion of a cluster by 11 new cases during 3 months, including eight cases with transmitted drug resistance. This cluster generally comprised young men who have sex with men. The subsequent report precipitated an enhanced public health follow-up to ensure linkage to care and treatment initiation in the affected subpopulation. Of the nine cases associated with this follow-up, all had already been linked to care and five cases had started treatment. Subsequent to the follow-up, three additional cases started treatment and most cases achieved suppressed viral loads. During the next 12 months, we detected 12 new cases in this cluster with reduction in the onward transmission of drug resistance., Interpretation: Our findings show the first application of an automated phylogenetic system monitoring a clinical database to detect a recent HIV outbreak and support the ensuing public health response. By making secondary use of routinely collected HIV genotypes, this approach is cost-effective, attains near real-time monitoring of new cases, and can be implemented in all settings in which HIV genotyping is the standard of care., Funding: BC Centre for Excellence in HIV/AIDS, the Canadian Institutes for Health Research, the Genome Canada-CIHR Partnership in Genomics and Personalized Health, and the US National Institute on Drug Abuse., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Rare individuals homozygous for a naturally-occurring 32 base pair deletion in the CCR5 gene (CCR5∆32/∆32) are resistant to infection by CCR5-using ("R5") HIV-1 strains but remain susceptible to less common CXCR4-using ("X4") strains. The evolutionary dynamics of X4 infections however, remain incompletely understood. We identified two individuals, one CCR5wt/wt and one CCR5∆32/∆32, within the Vancouver Injection Drug Users Study who were infected with a genetically similar X4 HIV-1 strain. While early-stage plasma viral loads were comparable in the two individuals (~4.5-5 log10 HIV-1 RNA copies/ml), CD4 counts in the CCR5wt/wt individual reached a nadir of <20 CD4 cells/mm(3) within 17 months but remained >250 cells/mm(3) in the CCR5∆32/∆32 individual. Ancestral phylogenetic reconstructions using longitudinal envelope-V3 deep sequences suggested that both individuals were infected by a single transmitted/founder (T/F) X4 virus that differed at only one V3 site (codon 24). While substantial within-host HIV-1 V3 diversification was observed in plasma and PBMC in both individuals, the CCR5wt/wt individual's HIV-1 population gradually reverted from 100% X4 to ~60% R5 over ~4 years whereas the CCR5∆32/∆32 individual's remained consistently X4. Our observations illuminate early dynamics of X4 HIV-1 infections and underscore the influence of CCR5 genotype on HIV-1 V3 evolution.

Unlabelled: Human leukocyte antigen (HLA) class I-associated polymorphisms in HIV-1 that persist upon transmission to HLA-mismatched hosts may spread in the population as the epidemic progresses. Transmission of HIV-1 sequences containing such adaptations may undermine cellular immune responses to the incoming virus in future hosts. Building upon previous work, we investigated the extent of HLA-associated polymorphism accumulation in HIV-1 polymerase (Pol) through comparative analysis of linked HIV-1/HLA class I genotypes sampled during historic (1979 to 1989; n = 338) and modern (2001 to 2011; n = 278) eras from across North America (Vancouver, BC, Canada; Boston, MA; New York, NY; and San Francisco, CA). Phylogenies inferred from historic and modern HIV-1 Pol sequences were star-like in shape, with an inferred most recent common ancestor (epidemic founder virus) sequence nearly identical to the modern North American subtype B consensus sequence. Nevertheless, modern HIV-1 Pol sequences exhibited roughly 2-fold-higher patristic (tip-to-tip) genetic distances than historic sequences, with HLA pressures likely driving ongoing diversification. Moreover, the frequencies of published HLA-associated polymorphisms in individuals lacking the selecting HLA class I allele was on average ∼2.5-fold higher in the modern than in the historic era, supporting their spread in circulation, though some remained stable in frequency during this time. Notably, polymorphisms restricted by protective HLA alleles appear to be spreading to a greater relative extent than others, though these increases are generally of modest absolute magnitude. However, despite evidence of polymorphism spread, North American hosts generally remain at relatively low risk of acquiring an HIV-1 polymerase sequence substantially preadapted to their HLA profiles, even in the present era., Importance: HLA class I-restricted cytotoxic T-lymphocyte (CTL) escape mutations in HIV-1 that persist upon transmission may accumulate in circulation over time, potentially undermining host antiviral immunity to the transmitted viral strain. We studied >600 experimentally collected HIV-1 polymerase sequences linked to host HLA information dating back to 1979, along with phylogenetically reconstructed HIV-1 sequences dating back to the virus' introduction into North America. Overall, our results support the gradual spread of many-though not all-HIV-1 polymerase immune escape mutations in circulation over time. This is consistent with recent observations from other global regions, though the extent of polymorphism accumulation in North America appears to be lower than in populations with high seroprevalence, older epidemics, and/or limited HLA diversity. Importantly, the risk of acquiring an HIV-1 polymerase sequence at transmission that is substantially preadapted to one's HLA profile remains relatively low in North America, even in the present era., (Copyright © 2016, American Society for Microbiology. All Rights Reserved.)

Limited access to HIV drug resistance testing in low- and middle-income countries impedes clinical decision-making at the individual patient level. An efficient protocol to address this issue must be established to minimize negative therapeutic outcomes for HIV-1-infected individuals in such settings. This is an observational study to ascertain the potential of newer genomic sequencing platforms, such as the Illumina MiSeq instrument, to provide accurate HIV drug resistance genotypes for hundreds of samples simultaneously. Plasma samples were collected from Canadian patients during routine drug resistance testing (n = 759) and from a Ugandan study cohort (n = 349). Amplicons spanning HIV reverse transcriptase codons 90 to 234 were sequenced with both MiSeq sequencing and conventional Sanger sequencing methods. Sequences were evaluated for nucleotide concordance between methods, using coverage and mixture parameters for quality control. Consensus sequences were also analyzed for disparities in the identification of drug resistance mutations. Sanger and MiSeq sequencing was successful for 881 samples (80%) and 892 samples (81%), respectively, with 832 samples having results from both methods. Most failures were for samples with viral loads of <3.0 log10 HIV RNA copies/ml. Overall, 99.3% nucleotide concordance between methods was observed. MiSeq sequencing achieved 97.4% sensitivity and 99.3% specificity in detecting resistance mutations identified by Sanger sequencing. Findings suggest that the Illumina MiSeq platform can yield high-quality data with a high-multiplex "wide" sequencing approach. This strategy can be used for multiple HIV subtypes, demonstrating the potential for widespread individual testing and annual population surveillance in resource-limited settings., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

Associations between HIV-1 cytotoxic T lymphocyte (CTL) escape mutations and their restricting human leukocyte antigen (HLA) alleles imply that HIV could adapt to divergent HLA repertoires of human populations globally. Using publicly available databases, we examine the relationship between the frequencies of 19 experimentally validated CTL escape mutations in HIV-1 reverse transcriptase and their restricting HLA alleles in 59 countries. From these extensive data, we find evidence of differential HIV adaptations to human populations at only a limited number of the studied epitope sites., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

The shapes of phylogenetic trees relating virus populations are determined by the adaptation of viruses within each host, and by the transmission of viruses among hosts. Phylodynamic inference attempts to reverse this flow of information, estimating parameters of these processes from the shape of a virus phylogeny reconstructed from a sample of genetic sequences from the epidemic. A key challenge to phylodynamic inference is quantifying the similarity between two trees in an efficient and comprehensive way. In this study, I demonstrate that a new distance measure, based on a subset tree kernel function from computational linguistics, confers a significant improvement over previous measures of tree shape for classifying trees generated under different epidemiological scenarios. Next, I incorporate this kernel-based distance measure into an approximate Bayesian computation (ABC) framework for phylodynamic inference. ABC bypasses the need for an analytical solution of model likelihood, as it only requires the ability to simulate data from the model. I validate this "kernel-ABC" method for phylodynamic inference by estimating parameters from data simulated under a simple epidemiological model. Results indicate that kernel-ABC attained greater accuracy for parameters associated with virus transmission than leading software on the same data sets. Finally, I apply the kernel-ABC framework to study a recent outbreak of a recombinant HIV subtype in China. Kernel-ABC provides a versatile framework for phylodynamic inference because it can fit a broader range of models than methods that rely on the computation of exact likelihoods., (© The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Persons with hepatitis C virus (HCV) genotype 1a (GT1a) infections harboring a baseline Q80K polymorphism in nonstructural protein 3 (NS3) have a reduced virologic response to simeprevir in combination with pegylated interferon-alfa and ribavirin. We aimed to develop, validate, and freely disseminate an NS3 clinical sequencing assay to detect the Q80K polymorphism and potentially other HCV NS3 drug resistance mutations. HCV RNA was extracted from frozen plasma using a NucliSENS easyMAG automated nucleic acid extractor, amplified by nested reverse transcription-PCR, and sequenced using Sanger and/or next-generation (MiSeq) methods. Sanger chromatograms were analyzed using in-house software (RECall), and nucleotide mixtures were called automatically. MiSeq reads were iteratively mapped to the H77 reference genome, and consensus NS3 sequences were generated with nucleotides present at >20% called as mixtures. The accuracy, precision, and sensitivity for detecting the Q80K polymorphism were assessed in 70 samples previously sequenced by an external laboratory. A comparison of the sequences generated by the Sanger and MiSeq methods with those determined by an external lab revealed >98.5% nucleotide sequence concordance and zero discordant calls of the Q80K polymorphism. The results were both highly repeatable and reproducible (>99.7% nucleotide concordance and 100% Q80K concordance). The limits of detection (>2 and ∼5 log10 IU/ml for the Sanger and MiSeq assays, respectively) are sufficiently low to allow genotyping in nearly all chronically infected treatment-naive persons. No systematic bias in the under- or overamplification of minority variants was observed. Coinfection with other viruses (e.g., HIV and hepatitis B virus [HBV]) did not affect the assay results. The two independent HCV NS3 sequencing assays with the automated analysis procedures described here are useful tools to screen for the Q80K polymorphism and other HCV protease inhibitor drug resistance mutations., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

Sequencing is important for understanding the molecular epidemiology and viral evolution of hepatitis C virus (HCV) infection. To date, there is little standardisation among sequencing protocols, in-part due to the high genetic diversity that is observed within HCV. This study aimed to develop a novel, practical sequencing protocol that covered both conserved and variable regions of the viral genome and assess the influence of each subregion, sequence concatenation and unrelated reference sequences on phylogenetic clustering analysis. The Core to the hypervariable region 1 (HVR1) of envelope-2 (E2) and non-structural-5B (NS5B) regions of the HCV genome were amplified and sequenced from participants from the Australian Trial in Acute Hepatitis C (ATAHC), a prospective study of the natural history and treatment of recent HCV infection. Phylogenetic trees were constructed using a general time-reversible substitution model and sensitivity analyses were completed for every subregion. Pairwise distance, genetic distance and bootstrap support were computed to assess the impact of HCV region on clustering results as measured by the identification and percentage of participants falling within all clusters, cluster size, average patristic distance, and bootstrap value. The Robinson-Foulds metrics was also used to compare phylogenetic trees among the different HCV regions. Our results demonstrated that the genomic region of HCV analysed influenced phylogenetic tree topology and clustering results. The HCV Core region alone was not suitable for clustering analysis; NS5B concatenation, the inclusion of reference sequences and removal of HVR1 all influenced clustering outcome. The Core-E2 region, which represented the highest genetic diversity and longest sequence length in this study, provides an ideal method for clustering analysis to address a range of molecular epidemiological questions.

Unlabelled: Improved surveillance methods are needed to better understand the current hepatitis C virus (HCV) disease burden and to monitor the impact of prevention and treatment interventions on HCV transmission dynamics. Sanger sequencing (HCV NS5B, HVR1 and Core-E1-HVR1) and phylogenetics were applied to samples from individuals diagnosed with HCV in British Columbia, Canada in 2011. This included individuals with two or three sequential samples collected <1 year apart. Patristic distances between sequential samples were used to set cutoffs to identify recent transmission clusters. Factors associated with transmission clustering were analyzed using logistic regression. From 618 individuals, 646 sequences were obtained. Depending on the cutoff used, 63 (10%) to 92 (15%) unique individuals were identified within transmission clusters of predicted recent origin. Clustered individuals were more likely to be <40 years old (Adjusted Odds Ratio (AOR) 2.12, 95% CI 1.21-3.73), infected with genotype 1a (AOR 6.60, 95% CI 1.98-41.0), and to be seroconverters with estimated infection duration of <1 year (AOR 3.13, 95% CI 1.29-7.36) or >1 year (AOR 2.19, 95% CI 1.22-3.97)., Conclusion: Systematic application of molecular phylogenetics may be used to enhance traditional surveillance methods through identification of recent transmission clusters., (Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.)

Hepatitis C virus (HCV) has a naturally occurring polymorphism, Q80K, in the nonstructural protein 3 (NS3) gene encoding the viral protease, which has been associated with reduced susceptibility to the direct-acting antiviral inhibitor simeprevir. Q80K is observed predominantly in HCV genotype 1a and seldom in other HCV genotypes; moreover, it has a markedly high prevalence in the United States. Here, we reconstruct the evolutionary history of this polymorphism to investigate why it is so highly localized in prevalence and whether it is stably transmitted between hosts. We found that the majority (96%) of HCV infections carrying Q80K were descended from a single lineage in which a Q80K substitution occurred around the 1940s in the United States, which implies that this polymorphism is likely highly transmissible. Furthermore, we identified 2 other substitutions in NS3 that may interact with Q80K and contribute to its stability. Our results imply that the current distribution and prevalence of Q80K are unlikely to change significantly in the short term., (© The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Background: The diversification of human immunodeficiency virus (HIV) is shaped by its transmission history. We therefore used a population based province wide HIV drug resistance database in British Columbia (BC), Canada, to evaluate the impact of clinical, demographic, and behavioral factors on rates of HIV transmission., Methods: We reconstructed molecular phylogenies from 27,296 anonymized bulk HIV pol sequences representing 7747 individuals in BC-about half the estimated HIV prevalence in BC. Infections were grouped into clusters based on phylogenetic distances, as a proxy for variation in transmission rates. Rates of cluster expansion were reconstructed from estimated dates of HIV seroconversion., Results: Our criteria grouped 4431 individuals into 744 clusters largely separated with respect to risk factors, including large established clusters predominated by injection drug users and more-recently emerging clusters comprising men who have sex with men. The mean log10 viral load of an individual's phylogenetic neighborhood (composed of 5 other individuals with shortest phylogenetic distances) increased their odds of appearing in a cluster by >2-fold per log10 viruses per milliliter., Conclusions: Hotspots of ongoing HIV transmission can be characterized in near real time by the secondary analysis of HIV resistance genotypes, providing an important potential resource for targeting public health initiatives for HIV prevention., (© The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Unlabelled: Little is known about factors associated with hepatitis C virus (HCV) transmission among people who inject drugs (PWID). Phylogenetic clustering and associated factors were evaluated among PWID in Vancouver, Canada. Data were derived from the Vancouver Injection Drug Users Study. Participants who were HCV antibody-positive at enrolment and those with HCV antibody seroconversion during follow-up (1996 to 2012) were tested for HCV RNA and sequenced (Core-E2 region). Phylogenetic trees were inferred using maximum likelihood analysis and clusters were identified using ClusterPicker (90% bootstrap threshold, 0.05 genetic distance threshold). Factors associated with clustering were assessed using logistic regression. Among 655 eligible participants, HCV genotype prevalence was: G1a: 48% (n=313), G1b: 6% (n=41), G2a: 3% (n=20), G2b: 7% (n=46), G3a: 33% (n=213), G4a: <1% (n=4), G6a: 1% (n=8), G6e: <1% (n=1), and unclassifiable: 1% (n=9). The mean age was 36 years, 162 (25%) were female, and 164 (25%) were HIV+. Among 501 participants with HCV G1a and G3a, 31% (n=156) were in a pair/cluster. Factors independently associated with phylogenetic clustering included: age <40 (versus age≥40, adjusted odds ratio [AOR]=1.64; 95% confidence interval [CI] 1.03, 2.63), human immunodeficiency virus (HIV) infection (AOR=1.82; 95% CI 1.18, 2.81), HCV seroconversion (AOR=3.05; 95% CI 1.40, 6.66), and recent syringe borrowing (AOR 1.59; 95% CI 1.07, 2.36)., Conclusion: In this sample of PWID, one-third demonstrated phylogenetic clustering. Factors independently associated with phylogenetic clustering included younger age, recent HCV seroconversion, prevalent HIV infection, and recent syringe borrowing. Strategies to enhance the delivery of prevention and/or treatment strategies to those with HIV and recent HCV seroconversion should be explored, given an increased likelihood of HCV transmission in these subpopulations., (© 2014 by the American Association for the Study of Liver Diseases.)

Primer IDs (pIDs) are random oligonucleotide tags used in next-generation sequencing to identify sequences that originate from the same template. These tags are produced by degenerate primers during the reverse transcription of RNA molecules into cDNA. The use of pIDs helps to track the number of RNA molecules carried through amplification and sequencing, and allows resolution of inconsistencies between reads sharing a pID. Three potential issues complicate the above applications. First, multiple cDNAs may share a pID by chance; we found that while preventing any cDNAs from sharing a pID may be unfeasible, it is still practical to limit the number of these collisions. Secondly, a pID must be observed in at least three sequences to allow error correction; as such, pIDs observed only one or two times must be rejected. If the sequencing product contains copies from a high number of RT templates but produces few reads, our findings indicate that rejecting such pIDs will discard a great deal of data. Thirdly, the use of pIDs could influence amplification and sequencing. We examined the effects of several intrinsic and extrinsic factors on sequencing reads at both the individual and ensemble level., (© The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Next generation, "deep", sequencing has increasing applications both clinically and in disparate fields of research. This study investigates the accuracy and reproducibility of "deep" sequencing as applied to co-receptor prediction using the V3 loop of Human Immunodeficiency Virus-1. Despite increasing use in HIV co-receptor prediction, the accuracy and reproducibility of deep sequencing technology, and the factors which can affect it, have received only a limited level of investigation. To accomplish this, repeated deep sequencing results were generated using the Roche GS-FLX (454) from a number of sources including a non-homogeneous clinical sample (N = 47 replicates over 18 deep sequencing runs), and a large clinical cohort from the MOTIVATE and A400129 studies (N = 1521). For repeated measurements of a non-homogeneous clinical sample, increasing input copy number both decreased variance in the measured proportion of non-R5 using virus (p<<0.001 and 0.02 for single replicates and triplicates respectively) and increased measured viral diversity (p<0.001; multiple measures). Detection of sequences with a mean abundance less than 1% abundance showed a 2 fold increase in median coefficient of variation (CV) in repeated measurements of a non-homogeneous clinical sample, and a 2.7 fold increase in CV in the MOTIVATE/A400129 dataset compared to sequences with ≥1% abundance. An unexpected source of error included read position, with low accuracy reads occurring more frequently towards the edge of sequencing regions (p<<0.001). Overall, the primary source of variability was sampling error caused by low input copy number/minority species prevalence, though other sources of error including sequence intrinsic, temporal, and read-position related errors were detected.

Unlabelled: A population of human immunodeficiency virus (HIV) within a host often descends from a single transmitted/founder virus. The high mutation rate of HIV, coupled with long delays between infection and diagnosis, make isolating and characterizing this strain a challenge. In theory, ancestral reconstruction could be used to recover this strain from sequences sampled in chronic infection; however, the accuracy of phylogenetic techniques in this context is unknown. To evaluate the accuracy of these methods, we applied ancestral reconstruction to a large panel of published longitudinal clonal and/or single-genome-amplification HIV sequence data sets with at least one intrapatient sequence set sampled within 6 months of infection or seroconversion (n = 19,486 sequences, median [interquartile range] = 49 [20 to 86] sequences/set). The consensus of the earliest sequences was used as the best possible estimate of the transmitted/founder. These sequences were compared to ancestral reconstructions from sequences sampled at later time points using both phylogenetic and phylogeny-naive methods. Overall, phylogenetic methods conferred a 16% improvement in reproducing the consensus of early sequences, compared to phylogeny-naive methods. This relative advantage increased with intrapatient sequence diversity (P < 10(-5)) and the time elapsed between the earliest and subsequent samples (P < 10(-5)). However, neither approach performed well for reconstructing ancestral indel variation, especially within indel-rich regions of the HIV genome. Although further improvements are needed, our results indicate that phylogenetic methods for ancestral reconstruction significantly outperform phylogeny-naive alternatives, and we identify experimental conditions and study designs that can enhance accuracy of transmitted/founder virus reconstruction., Importance: When HIV is transmitted into a new host, most of the viruses fail to infect host cells. Consequently, an HIV infection tends to be descended from a single "founder" virus. A priority target for the vaccine research, these transmitted/founder viruses are difficult to isolate since newly infected individuals are often unaware of their status for months or years, by which time the virus population has evolved substantially. Here, we report on the potential use of evolutionary methods to reconstruct the genetic sequence of the transmitted/founder virus from its descendants at later stages of an infection. These methods can recover this ancestral sequence with an overall error rate of about 2.3%-about 15% more information than if we had ignored the evolutionary relationships among viruses. Although there is no substitute for sampling infections at earlier points in time, these methods can provide useful information about the genetic makeup of transmitted/founder HIV.

HLA-restricted immune escape mutations that persist following HIV transmission could gradually spread through the viral population, thereby compromising host antiviral immunity as the epidemic progresses. To assess the extent and phenotypic impact of this phenomenon in an immunogenetically diverse population, we genotypically and functionally compared linked HLA and HIV (Gag/Nef) sequences from 358 historic (1979-1989) and 382 modern (2000-2011) specimens from four key cities in the North American epidemic (New York, Boston, San Francisco, Vancouver). Inferred HIV phylogenies were star-like, with approximately two-fold greater mean pairwise distances in modern versus historic sequences. The reconstructed epidemic ancestral (founder) HIV sequence was essentially identical to the North American subtype B consensus. Consistent with gradual diversification of a "consensus-like" founder virus, the median "background" frequencies of individual HLA-associated polymorphisms in HIV (in individuals lacking the restricting HLA[s]) were ∼ 2-fold higher in modern versus historic HIV sequences, though these remained notably low overall (e.g. in Gag, medians were 3.7% in the 2000s versus 2.0% in the 1980s). HIV polymorphisms exhibiting the greatest relative spread were those restricted by protective HLAs. Despite these increases, when HIV sequences were analyzed as a whole, their total average burden of polymorphisms that were "pre-adapted" to the average host HLA profile was only ∼ 2% greater in modern versus historic eras. Furthermore, HLA-associated polymorphisms identified in historic HIV sequences were consistent with those detectable today, with none identified that could explain the few HIV codons where the inferred epidemic ancestor differed from the modern consensus. Results are therefore consistent with slow HIV adaptation to HLA, but at a rate unlikely to yield imminent negative implications for cellular immunity, at least in North America. Intriguingly, temporal changes in protein activity of patient-derived Nef (though not Gag) sequences were observed, suggesting functional implications of population-level HIV evolution on certain viral proteins.

A phylogeny is a tree-based model of common ancestry that is an indispensable tool for studying biological variation. Phylogenies play a special role in the study of rapidly evolving populations such as viruses, where the proliferation of lineages is constantly being shaped by the mode of virus transmission, by adaptation to immune systems, and by patterns of human migration and contact. These processes may leave an imprint on the shapes of virus phylogenies that can be extracted for comparative study; however, tree shapes are intrinsically difficult to quantify. Here we present a comprehensive study of phylogenies reconstructed from 38 different RNA viruses from 12 taxonomic families that are associated with human pathologies. To accomplish this, we have developed a new procedure for studying phylogenetic tree shapes based on the 'kernel trick', a technique that maps complex objects into a statistically convenient space. We show that our kernel method outperforms nine different tree balance statistics at correctly classifying phylogenies that were simulated under different evolutionary scenarios. Using the kernel method, we observe patterns in the distribution of RNA virus phylogenies in this space that reflect modes of transmission and pathogenesis. For example, viruses that can establish persistent chronic infections (such as HIV and hepatitis C virus) form a distinct cluster. Although the visibly 'star-like' shape characteristic of trees from these viruses has been well-documented, we show that established methods for quantifying tree shape fail to distinguish these trees from those of other viruses. The kernel approach presented here potentially represents an important new tool for characterizing the evolution and epidemiology of RNA viruses.

Objectives: Using deep sequencing methods, we intensively investigated the selective pressure of maraviroc on the viral population in four patients with dual/mixed HIV-1 experiencing treatment failure., Methods: Patients received maraviroc add-on therapy (n = 4). Tropism was determined by Monogram's Trofile assay and/or 'deep' sequencing. Longitudinal 'deep' sequence analysis used triplicate HIV V3 RT-PCR on plasma samples. Sequences were interpreted using the geno2phenocoreceptor algorithm with a 3.5% false-positive rate (FPR) cut-off., Results: Patients had a median viral load of 4.7 log10 HIV RNA copies/mL with a median of 24% chemokine (C-X-C motif) receptor 4 (CXCR4)-using virus at baseline. Following maraviroc exposure, the chemokine (C-C motif) receptor 5 (CCR5)-using virus (R5) plasma viral load decreased by at least 1 log10, and only non-R5 variants with extremely low FPR values predominated after 21 days. Virus with an FPR ≤1.8% accounted for more than 90% of the circulating virus, having expanded to occupy the 'space' left by the suppression of R5 variants. Population genetic estimates of viral fitness in the presence of maraviroc showed a steep rise around an FPR value of 2%., Conclusions: Longitudinal analysis of independent R5 and non-R5 HIV populations shows that maraviroc selects viruses with an extremely low FPR, implying that the antiviral activity of maraviroc may extend to a broader range of HIV variants than previously suspected.

We applied an efficient method to characterize the relative fitness levels of multiple nonnucleoside reverse transcriptase (NNRTI)-resistant HIV-1 variants by simultaneous competitive culture and 454 deep sequencing. Using this method, we show that the Y181V mutation in the HIV-1 reverse transcriptase in particular confers a clear selective advantage to the virus over 14 other NNRTI resistance mutations in the presence of etravirine in vitro.

HIV-1 tropism can be predicted using V3 genotypic algorithms. The performance of these prediction algorithms for non-B subtypes is poorly characterized. Here, we use these genotypic algorithms to predict viral tropism of HIV-1 subtype A, B, C, and D to find apparent sensitivity, specificity, and concordance against a recombinant phenotypic assay, the original Trofile assay. This is a substudy of an epidemiological study (Pfizer A4001064). Plasma samples were selected to represent a large number of DM/X4 and R5 viruses. The HIV-1 env gene V3 loop was genotyped by Sanger sequencing (N=260) or 454 "deep" sequencing (N=280). Sequences were scored with g2p[coreceptor], PSSM X4/R5, PSSM SI/NSI, and PSSM subtype C matrices. Overall, non-B subtypes tropism prediction had similar concordance and apparent sensitivity and specificity as subtype B in predicting Trofile's results in both population sequencing (81.3%, 65.6%, and 90.5% versus 84.2%, 78.5%, and 88.2%) and 454 "deep" sequencing (82.3%, 80.0%, and 83.6% versus 86.8%, 92.0%, and 82.6%) using g2p[coreceptor]. By population sequencing, subtype A had lower sensitivity, whereas subtype D had lower specificity for non-R5 predictions, both in comparison to subtype B. 454 "deep" sequencing improved subtype A sensitivity but not subtype D. Subtype C had greater concordance than subtype B regardless of sequencing methods. In conclusion, genotypic tropism prediction algorithms may be applied to non-B HIV-1 subtypes with caution. Collective analysis of non-B subtypes revealed a performance similar to subtype B, whereas a subtype-specific analysis revealed overestimation (subtype D) or underestimation (subtype A).

Background: A tropism test is required before administration of the antiretroviral drug maraviroc. However, plasma RNA testing is not possible in patients with undetectable plasma viral loads. Here we assess genotypic testing of cellular human immunodeficiency virus (HIV) DNA from peripheral blood mononuclear cells (PBMCs) to predict virologic responses in treatment-experienced patients beginning maraviroc-containing regimens., Methods: PBMC samples from 181 maraviroc recipients at study entry in MOTIVATE or A4001029 (51% R5 by original Trofile). The V3 loop was amplified in triplicate from cellular HIV DNA, and matching plasma RNA (n = 156). Sequencing was performed using standard population-based methods and next-generation deep sequencing, with tropism assessment as previously defined., Results: Genotypic DNA-based tropism testing from the cellular compartment had 78%-81% sensitivity relative to RNA-based Trofile at the same time point. Cell-based genotypic tropism methods and plasma-based phenotypic and genotypic methods were predictive of virologic response. However, when classifications were discordant, the outcomes favored the plasma predictions over the DNA ones., Conclusions: Genotypic determination of HIV tropism can be performed using cell-derived viral DNA, and is a predictor of virologic success on maraviroc in therapy-experienced patients. However, the PBMC compartment appears to be a suboptimal predictor compared to plasma.

Human immunodeficiency virus type 1 (HIV-1) V3 loop sequence can be used to infer viral coreceptor use. The effect of input copy number on population-based sequencing of the V3 loop of HIV-1 was examined through replicate deep and population-based sequencing of samples with known tropism, a heterogeneous clinical sample (624 population-based sequences and 47 deep-sequencing replicates), and a large cohort of clinical samples from phase III clinical trials of maraviroc including the MOTIVATE/A4001029 studies (n = 1,521). Proviral DNA from two independent samples from each of 101 patients from the MOTIVATE/A4001029 studies was also analyzed. Cumulative technical error occurred at a rate of 3 × 10(-4) mismatches/bp, without observed effect on inferred tropism. Increasing PCR replication increased minority species detection with an ~10% minority population detected in 18% of cases using a single replicate at a viral load of 1,072 copies/ml and in 44% of cases using three replicates. The nucleotide prevalence detected by population-based and deep sequencing were highly correlated (Spearman's ρ, 0.73), and the accuracy increased with increasing input copy number (P < 0.001). Triplicate sequencing was able to predict tropism changes in the MOTIVATE/A4001029 studies for both low (P = 0.05) and high (P = 0.02) viral loads. Sequences derived from independently extracted and processed samples of proviral DNA for the same patient were equivalent to replicates from the same extraction (P = 0.45) and had correlated position-specific scoring matrix scores (Spearman's ρ, 0.75; P << 0.001); however, concordance in tropism inference was only 83%. Input copy number and PCR replication are important factors in minority species detection in samples with significant heterogeneity.

Evidence for ageing in symmetrically dividing bacteria such as Escherichia coli has historically been conflicting. Early work found weak or no evidence. More recent studies found convincing evidence, but negative results are still encountered. Because bacterial ageing is believed to result from non-genetic (e.g. oxidative) damage, we tested the possibility that the negative outcomes resulted from the lack of an extrinsic damage agent. We found that streptomycin, which produces mistranslated proteins that are more vulnerable to oxidation, was able to induce both damage and ageing in bacterial populations. A dosage effect relating the level of damage to the concentration of streptomycin was observed. Our results explain the previous inconsistencies, because all studies that failed to find evidence for bacterial ageing did not use a damage agent. However, all studies that succeeded in finding evidence utilized fluorescent proteins as a visual marker. We suggest that ageing in those studies was induced by the harmful effects of an extrinsic factor, such as the proteins themselves or the excitation light. Thus, all of the earlier studies can be reconciled and bacterial ageing is a real phenomenon. However, the study and observation of bacterial ageing require the addition of an extrinsic damage agent.

Genotypic tropism testing methods are emerging as the first step before prescription of the CCR5 antagonist maraviroc (MVC) to HIV-infected patients in Europe. Studies validating genotypic tests have included other active drugs that could have potentially convoluted the effects of MVC. The maraviroc clinical test (MCT) is an in vivo drug sensitivity test based on the virological response to a short-term exposure to MVC monotherapy. Thus, our aim was to compare the results of genotypic tropism testing methods with the short-term virological response to MVC monotherapy. A virological response in the MCT was defined as a ≥ 1-log(10) decrease in HIV RNA or undetectability after 8 days of drug exposure. Seventy-three patients undergoing the MCT were included in this study. We used both standard genotypic methods (n = 73) and deep sequencing (n = 27) on MCT samples at baseline. For the standard methods, the most widely used genotypic algorithms for analyzing the V3 loop sequence, geno2pheno and PSSM, were used. For deep sequencing, the geno2pheno algorithm was used with a false-positive rate cutoff of 3.5. The discordance rates between the standard genotypic methods and the virological response were approximately 20% (including mostly patients without a virological response). Interestingly, these discordance rates were similar to that obtained from deep sequencing (18.5%). The discordance rates between the genotypic methods (tropism assays predictive of the use of the CCR5 coreceptor) and the MCT (in vivo MVC sensitivity assay) indicate that the algorithms used by genotypic methods are still not sufficiently optimized.

RNA viruses evolve very rapidly, often recombine, and are subject to strong host (immune response) and anthropogenic (antiretroviral drugs) selective forces. Given their compact and extensively sequenced genomes, comparative analysis of RNA viral data can provide important insights into the molecular mechanisms of adaptation, pathogenicity, immune evasion, and drug resistance. In this chapter, we present an example-based overview of recent advances in evolutionary models and statistical approaches that enable screening viral alignments for evidence of adaptive change in the presence of recombination, detecting bursts of directional adaptive evolution associated with the phenotypic changes, and detecting of coevolving sites in viral genes.

At the early stage of infection, human immunodeficiency virus (HIV)-1 predominantly uses the CCR5 coreceptor for host cell entry. The subsequent emergence of HIV variants that use the CXCR4 coreceptor in roughly half of all infections is associated with an accelerated decline of CD4+ T-cells and rate of progression to AIDS. The presence of a 'fitness valley' separating CCR5- and CXCR4-using genotypes is postulated to be a biological determinant of whether the HIV coreceptor switch occurs. Using phylogenetic methods to reconstruct the evolutionary dynamics of HIV within hosts enables us to discriminate between competing models of this process. We have developed a phylogenetic pipeline for the molecular clock analysis, ancestral reconstruction, and visualization of deep sequence data. These data were generated by next-generation sequencing of HIV RNA extracted from longitudinal serum samples (median 7 time points) from 8 untreated subjects with chronic HIV infections (Amsterdam Cohort Studies on HIV-1 infection and AIDS). We used the known dates of sampling to directly estimate rates of evolution and to map ancestral mutations to a reconstructed timeline in units of days. HIV coreceptor usage was predicted from reconstructed ancestral sequences using the geno2pheno algorithm. We determined that the first mutations contributing to CXCR4 use emerged about 16 (per subject range 4 to 30) months before the earliest predicted CXCR4-using ancestor, which preceded the first positive cell-based assay of CXCR4 usage by 10 (range 5 to 25) months. CXCR4 usage arose in multiple lineages within 5 of 8 subjects, and ancestral lineages following alternate mutational pathways before going extinct were common. We observed highly patient-specific distributions and time-scales of mutation accumulation, implying that the role of a fitness valley is contingent on the genotype of the transmitted variant.

The evolution of drug resistance mutations in plasma samples is relatively well-characterized. However, the viral population and diversity in other body compartments such as peripheral blood mononuclear cells (PBMC) remains poorly understood. Previous studies have mostly focused on protease and reverse transcriptase drug resistance mutations (DRMs). In this study, we used 454 "deep" sequencing technology to observe and quantify longitudinally the prevalence of resistance mutations associated with the integrase inhibitor, raltegravir, in plasma versus PBMC samples from a San Francisco-based cohort. Four heavily treatment-experienced subjects were monitored in this study over a median of 1.2 years since the initiation of raltegravir-containing regimens. We observed a consistent discordance in the prevalence of DRMs, but not resistance pathway(s), in the plasma versus PBMC viral populations. In the final paired samples that were tested while the subjects were on a raltegravir-containing regimen, DRM prevalence reached 100% in plasma but remained 1% in PBMC on day 177 post-therapy in Subject 3180 (Q148H/G140S), 100% in plasma and 36% in PBMC on day 224 in Subject 3242 (N155H), 78% in plasma and 11-12% in PBMC on day 338 in Subject 3501 (Q148H/G140S), and 100% in plasma and 0% in PBMC on day 197 in Subject 3508 (Y143R). Furthermore, absolute sequence homology comparison between the two compartments revealed that 21% - 99% of PBMC sequences had no match in plasma, whereas 14% - 100% of plasma sequences had no match in PBMC. Overall, our observations suggested that plasma and PBMC hosted drastically different HIV-1 populations even after a prolonged exposure to raltegravir selection pressure.

Objective: To reconstruct dates of HIV infection by the coalescent analysis of longitudinal next-generation sequencing (NGS) data., Design: The coalescent predicts the time that has elapsed since the most recent common ancestor (MRCA) of a population. Because HIV tends to undergo severe bottlenecks upon transmission, the MRCA may be a good predictor of the time of infection. NGS provides an efficient means for performing large-scale clonal sequencing of HIV populations within patients, and the ideal raw material for coalescent analysis., Methods: Baseline and follow-up plasma samples were obtained from 19 individuals enrolled into the Montréal Primary HIV Infection cohort. Dates of infection were initially estimated at baseline from nongenetic data (clinical and serological markers and patient questionnaires). HIV RNA was extracted and seven regions of the genome were amplified, subjected to parallel-tagged 454 pyrosequencing, and analyzed using the software package BEAST., Results: Mean estimates of the time to the MRCA per patient were significantly correlated with nongenetic estimates (Spearman's ρ = 0.65, P = 4.4 × 10(-3)). The median absolute difference between coalescent and nongenetic date estimates was smallest (median 29.4 days) for highly variable regions of the HIV genome such as env V3, and greater (median 114.9 days) for more conserved regions such as pol., Conclusion: This application of NGS represents an important advancement, not only because accurate estimates of dates of infection can be derived retrospectively from archived specimens, but also because each analysis is patient-specific and, therefore, robust to variation in rates of HIV evolution.

The difference between regional rates of HIV-associated dementia (HAD) in patients infected with different subtypes of HIV suggests that genetic determinants exist within HIV that influence the ability of the virus to replicate in the central nervous system (in Uganda, Africa, subtype D HAD rate is 89%, while subtype A HAD rate is 24%). HIV-1 nef is a multifunctional protein with known toxic effects in the brain compartment. The goal of the current study was to identify if specific three-dimensional nef structures may be linked to patients who developed HAD. HIV-1 nef structures were computationally derived for consensus brain and non-brain sequences from a panel of patients infected with subtype B who died due to varied disease pathologies and consensus subtype A and subtype D sequences from Uganda. Site directed mutation analysis identified signatures in brain structures that appear to change binding potentials and could affect folding conformations of brain-associated structures. Despite the large sequence variation between HIV subtypes, structural alignments confirmed that viral structures derived from patients with HAD were more similar to subtype D structures than to structures derived from patient sequences without HAD. Furthermore, structures derived from brain sequences of patients with HAD were more similar to subtype D structures than they were to their own non-brain structures. The potential finding of a brain-specific nef structure indicates that HAD may result from genetic alterations that alter the folding or binding potential of the protein.

Environmental metagenomics provides snippets of genomic sequences from all organisms in an environmental sample and are an unprecedented resource of information for investigating microbial population genetics. Current analytical methods, however, are poorly equipped to handle metagenomic data, particularly of short, unlinked sequences. A custom analytical pipeline was developed to calculate dN/dS ratios, a common metric to evaluate the role of selection in the evolution of a gene, from environmental metagenomes sequenced using 454 technology of flow-sorted populations of marine Synechococcus, the dominant cyanobacteria in coastal environments. The large majority of genes (98%) have evolved under purifying selection (dN/dS<1). The metagenome sequence coverage of the reference genomes was not uniform and genes that were highly represented in the environment (i.e. high read coverage) tended to be more evolutionarily conserved. Of the genes that may have evolved under positive selection (dN/dS>1), 77 out of 83 (93%) were hypothetical. Notable among annotated genes, ribosomal protein L35 appears to be under positive selection in one Synechococcus population. Other annotated genes, in particular a possible porin, a large-conductance mechanosensitive channel, an ATP binding component of an ABC transporter, and a homologue of a pilus retraction protein had regions of the gene with elevated dN/dS. With the increasing use of next-generation sequencing in metagenomic investigations of microbial diversity and ecology, analytical methods need to accommodate the peculiarities of these data streams. By developing a means to analyze population diversity data from these environmental metagenomes, we have provided the first insight into the role of selection in the evolution of Synechococcus, a globally significant primary producer.

Human immunodeficiency virus type 1 (HIV-1) genomes often carry one or more mutations associated with drug resistance upon transmission into a therapy-naïve individual. We assessed the prevalence and clinical significance of transmitted drug resistance (TDR) in chronically-infected therapy-naïve patients enrolled in a multi-center cohort in North America. Pre-therapy clinical significance was quantified by plasma viral load (pVL) and CD4+ cell count (CD4) at baseline. Naïve bulk sequences of HIV-1 protease and reverse transcriptase (RT) were screened for resistance mutations as defined by the World Health Organization surveillance list. The overall prevalence of TDR was 14.2%. We used a Bayesian network to identify co-transmission of TDR mutations in clusters associated with specific drugs or drug classes. Aggregate effects of mutations by drug class were estimated by fitting linear models of pVL and CD4 on weighted sums over TDR mutations according to the Stanford HIV Database algorithm. Transmitted resistance to both classes of reverse transcriptase inhibitors was significantly associated with lower CD4, but had opposing effects on pVL. In contrast, position-specific analyses of TDR mutations revealed substantial effects on CD4 and pVL at several residue positions that were being masked in the aggregate analyses, and significant interaction effects as well. Residue positions in RT with predominant effects on CD4 or pVL (D67 and M184) were re-evaluated in causal models using an inverse probability-weighting scheme to address the problem of confounding by other mutations and demographic or risk factors. We found that causal effect estimates of mutations M184V/I (-1.7 log₁₀pVL) and D67N/G (-2.1[³√CD4] and 0.4 log₁₀pVL) were compensated by K103N/S and K219Q/E/N/R. As TDR becomes an increasing dilemma in this modern era of highly-active antiretroviral therapy, these results have immediate significance for the clinical management of HIV-1 infections and our understanding of the ongoing adaptation of HIV-1 to human populations.

Initial in vitro studies of bevirimat resistance failed to observe mutations in the clinically significant QVT motif in SP1 of HIV-1 gag. This study presents a novel screening method involving mixed, clinically derived gag-protease recombinant HIV-1 samples to more accurately mimic the selection of resistance seen in vivo. Bevirimat resistance was investigated via population-based sequencing performed with a large, initially antiretroviral-naïve cohort before (n = 805) and after (n = 355) standard HIV therapy (without bevirimat). The prevalence of any polymorphism in the motif comprising Q, V, and T was ∼ 6%, 29%, and 12%, respectively, and did not change appreciably over the course of therapy. From these samples, three groups of 10 samples whose bulk sequences were wild type at the QVT motif were used to generate gag-protease recombinant viruses that captured the existing diversity. Groups were mixed and passaged with various bevirimat concentrations for 9 weeks. gag variations were assessed by amplicon-based "deep" sequencing using a GS FLX sequencer (Roche). Unscreened mutations were present in all groups, and a V370A minority not originally detected by bulk sequencing was present in one group. V370A, occurring together with another preexisting, unscreened resistance mutation, was selected in all groups in the presence of a bevirimat concentration above 0.1 μM. For the two groups with V370A levels below consistent detectability by deep sequencing, the initial selection of V370A required 3 to 4 weeks of exposure to a narrow range of bevirimat concentrations, whereas for the group with the V370A minority, selection occurred immediately. This approach provides quasispecies diversity that facilitates the selection of mutations observed in clinical trials and, coupled with deep sequencing, could represent an efficient in vitro screening method for detecting resistance mutations.

Datamonkey is a popular web-based suite of phylogenetic analysis tools for use in evolutionary biology. Since the original release in 2005, we have expanded the analysis options to include recently developed algorithmic methods for recombination detection, evolutionary fingerprinting of genes, codon model selection, co-evolution between sites, identification of sites, which rapidly escape host-immune pressure and HIV-1 subtype assignment. The traditional selection tools have also been augmented to include recent developments in the field. Here, we summarize the analyses options currently available on Datamonkey, and provide guidelines for their use in evolutionary biology. Availability and documentation: http://www.datamonkey.org.

Rapidly evolving viruses such as HIV-1 display extensive sequence variation in response to host-specific selection, while simultaneously maintaining functions that are critical to replication and infectivity. This apparent conflict between diversifying and purifying selection may be resolved by an abundance of epistatic interactions such that the same functional requirements can be met by highly divergent sequences. We investigate this hypothesis by conducting an extensive characterization of sequence variation in the HIV-1 nef gene that encodes a highly variable multifunctional protein. Population-based sequences were obtained from 686 patients enrolled in the HOMER cohort in British Columbia, Canada, from which the distribution of nonsynonymous substitutions in the phylogeny was reconstructed by maximum likelihood. We used a phylogenetic comparative method on these data to identify putative epistatic interactions between residues. Two interactions (Y120/Q125 and N157/S169) were chosen to further investigate within-host evolution using HIV-1 RNA extractions from plasma samples from eight patients. Clonal sequencing confirmed strong linkage between polymorphisms at these sites in every case. We used massively parallel pyrosequencing (MPP) to reconstruct within-host evolution in these patients. Experimental error associated with MPP was quantified by performing replicates at two different stages of the protocol, which were pooled prior to analysis to reduce this source of variation. Phylogenetic reconstruction from these data revealed correlated substitutions at Y120/Q125 or N157/S169 repeated across multiple lineages in every host, indicating convergent within-host evolution shaped by epistatic interactions.

Over time, natural selection molds every gene into a unique mosaic of sites evolving rapidly or resisting change-an "evolutionary fingerprint" of the gene. Aspects of this evolutionary fingerprint, such as the site-specific ratio of nonsynonymous to synonymous substitution rates (dN/dS), are commonly used to identify genetic features of potential biological interest; however, no framework exists for comparing evolutionary fingerprints between genes. We hypothesize that protein-coding genes with similar protein structure and/or function tend to have similar evolutionary fingerprints and that comparing evolutionary fingerprints can be useful for discovering similarities between genes in a way that is analogous to, but independent of, discovery of similarity via sequence-based comparison tools such as Blast. To test this hypothesis, we develop a novel model of coding sequence evolution that uses a general bivariate discrete parameterization of the evolutionary rates. We show that this approach provides a better fit to the data using a smaller number of parameters than existing models. Next, we use the model to represent evolutionary fingerprints as probability distributions and present a methodology for comparing these distributions in a way that is robust against variations in data set size and divergence. Finally, using sequences of three rapidly evolving RNA viruses (HIV-1, hepatitis C virus, and influenza A virus), we demonstrate that genes within the same functional group tend to have similar evolutionary fingerprints. Our framework provides a sound statistical foundation for efficient inference and comparison of evolutionary rate patterns in arbitrary collections of gene alignments, clustering homologous and nonhomologous genes, and investigation of biological and functional correlates of evolutionary rates.

Background: Most of our knowledge about how antiretrovirals and host immune responses influence the HIV-1 protease gene is derived from studies of subtype B virus. We investigated the effect of protease resistance-associated mutations (PRAMs) and population-based HLA haplotype frequencies on polymorphisms found in CRF01&#95;AE pro., Methods: We used all CRF01&#95;AE protease sequences retrieved from the LANL database and obtained regional HLA frequencies from the dbMHC database. Polymorphisms and major PRAMs in the sequences were identified using the Stanford Resistance Database, and we performed phylogenetic and selection analyses using HyPhy. HLA binding affinities were estimated using the Immune Epitope Database and Analysis., Results: Overall, 99% of CRF01&#95;AE sequences had at least 1 polymorphism and 10% had at least 1 major PRAM. Three polymorphisms (L10 V, K20RMI and I62 V) were associated with the presence of a major PRAM (P < 0.05). Compared to the subtype B consensus, six additional polymorphisms (I13 V, E35D, M36I, R41K, H69K, L89M) were identified in the CRF01&#95;AE consensus; all but L89M were located within epitopes recognized by HLA class I alleles. Of the predominant HLA haplotypes in the Asian regions of CRF01&#95;AE origin, 80% were positively associated with the observed polymorphisms, and estimated HLA binding affinity was estimated to decrease 19-40 fold with the observed polymorphisms at positions 35, 36 and 41., Conclusion: Polymorphisms in CRF01&#95;AE protease gene were common, and polymorphisms at residues 10, 20 and 62 most likely represent selection by use of protease inhibitors, whereas R41K and H69K were more likely attributable to recognition of epitopes by the HLA haplotypes of the host population.

Genetically diverse pathogens (such as Human Immunodeficiency virus type 1, HIV-1) are frequently stratified into phylogenetically or immunologically defined subtypes for classification purposes. Computational identification of such subtypes is helpful in surveillance, epidemiological analysis and detection of novel variants, e.g., circulating recombinant forms in HIV-1. A number of conceptually and technically different techniques have been proposed for determining the subtype of a query sequence, but there is not a universally optimal approach. We present a model-based phylogenetic method for automatically subtyping an HIV-1 (or other viral or bacterial) sequence, mapping the location of breakpoints and assigning parental sequences in recombinant strains as well as computing confidence levels for the inferred quantities. Our Subtype Classification Using Evolutionary ALgorithms (SCUEAL) procedure is shown to perform very well in a variety of simulation scenarios, runs in parallel when multiple sequences are being screened, and matches or exceeds the performance of existing approaches on typical empirical cases. We applied SCUEAL to all available polymerase (pol) sequences from two large databases, the Stanford Drug Resistance database and the UK HIV Drug Resistance Database. Comparing with subtypes which had previously been assigned revealed that a minor but substantial (approximately 5%) fraction of pure subtype sequences may in fact be within- or inter-subtype recombinants. A free implementation of SCUEAL is provided as a module for the HyPhy package and the Datamonkey web server. Our method is especially useful when an accurate automatic classification of an unknown strain is desired, and is positioned to complement and extend faster but less accurate methods. Given the increasingly frequent use of HIV subtype information in studies focusing on the effect of subtype on treatment, clinical outcome, pathogenicity and vaccine design, the importance of accurate, robust and extensible subtyping procedures is clear.

Highly pathogenic avian influenza (HPAI) virus H5N1 infects water and land fowl and can infect and cause mortality in mammals, including humans. However, HPAI H5N1 strains are not equally virulent in mammals, and some strains have been shown to cause only mild symptoms in experimental infections. Since most experimental studies of the basis of virulence in mammals have been small in scale, we undertook a meta-analysis of available experimental studies and used Bayesian graphical models (BGM) to increase the power of inference. We applied text-mining techniques to identify 27 individual studies that experimentally determined pathogenicity in HPAI H5N1 strains comprising 69 complete genome sequences. Amino acid sequence data in all 11 genes were coded as binary data for the presence or absence of mutations related to virulence in mammals or nonconsensus residues. Sites previously implicated as virulence determinants were examined for association with virulence in mammals in this data set, and the sites with the most significant association were selected for further BGM analysis. The analyses show that virulence in mammals is a complex genetic trait directly influenced by mutations in polymerase basic 1 (PB1) and PB2, nonstructural 1 (NS1), and hemagglutinin (HA) genes. Several intra- and intersegment correlations were also found, and we postulate that there may be two separate virulence mechanisms involving particular combinations of polymerase and NS1 mutations or of NS1 and HA mutations.