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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.)