Nuno Rodrigues Faria

Zika virus in the Americas: Early epidemiological and genetic findings

Zika virus genomes from Brazil The Zika virus outbreak is a major cause for concern in Brazil, where it has been linked with increased reports of otherwise rare birth defects and neuropathology. In a phylogenetic analysis, Faria et al. infer a single introduction of Zika to the Americas and estimated the introduction date to be about May to December 2013—some 12 months earlier than the virus was reported. This timing correlates with major events in the Brazilian cultural calendar associated with increased traveler numbers from areas where Zika virus has been circulating. A correlation was also observed between incidences of microcephaly and week 17 of pregnancy. Science, this issue p. 345 Virus sequencing indicates that Zika arrived in Brazil during the middle of 2013, coincident with a surge in air travelers. Brazil has experienced an unprecedented epidemic of Zika virus (ZIKV), with ~30,000 cases reported to date. ZIKV was first detected in Brazil in May 2015, and cases of microcephaly potentially associated with ZIKV infection were identified in November 2015. We performed next-generation sequencing to generate seven Brazilian ZIKV genomes sampled from four self-limited cases, one blood donor, one fatal adult case, and one newborn with microcephaly and congenital malformations. Results of phylogenetic and molecular clock analyses show a single introduction of ZIKV into the Americas, which we estimated to have occurred between May and December 2013, more than 12 months before the detection of ZIKV in Brazil. The estimated date of origin coincides with an increase in air passengers to Brazil from ZIKV-endemic areas, as well as with reported outbreaks in the Pacific Islands. ZIKV genomes from Brazil are phylogenetically interspersed with those from other South American and Caribbean countries. Mapping mutations onto existing structural models revealed the context of viral amino acid changes present in the outbreak lineage; however, no shared amino acid changes were found among the three currently available virus genomes from microcephaly cases. Municipality-level incidence data indicate that reports of suspected microcephaly in Brazil best correlate with ZIKV incidence around week 17 of pregnancy, although this correlation does not demonstrate causation. Our genetic description and analysis of ZIKV isolates in Brazil provide a baseline for future studies of the evolution and molecular epidemiology of this emerging virus in the Americas.

The early spread and epidemic ignition of HIV-1 in human populations

The hidden history of the HIV pandemic Rail and river transport in 1960s Congo, combined with the sexual revolution and changes in health care practices, primed the HIV pandemic. Faria et al. unpick the circumstances surrounding the ascendancy of HIV from its origins before 1920 in chimpanzee hunters in the Cameroon to amplification in Kinshasa. Around 1960, rail links promoted the spread of the virus to mining areas in southeastern Congo and beyond. Ultimately, HIV crossed the Atlantic in Haitian teachers returning home. From those early events, a pandemic was born. Science, this issue p. 56 The early history of HIV centered on Kinshasa before accelerating in 1960 as a result of seismic social change after independence. Thirty years after the discovery of HIV-1, the early transmission, dissemination, and establishment of the virus in human populations remain unclear. Using statistical approaches applied to HIV-1 sequence data from central Africa, we show that from the 1920s Kinshasa (in what is now the Democratic Republic of Congo) was the focus of early transmission and the source of pre-1960 pandemic viruses elsewhere. Location and dating estimates were validated using the earliest HIV-1 archival sample, also from Kinshasa. The epidemic histories of HIV-1 group M and nonpandemic group O were similar until ~1960, after which group M underwent an epidemiological transition and outpaced regional population growth. Our results reconstruct the early dynamics of HIV-1 and emphasize the role of social changes and transport networks in the establishment of this virus in human populations.

Emergence and potential for spread of Chikungunya virus in Brazil

BackgroundIn December 2013, an outbreak of Chikungunya virus (CHIKV) caused by the Asian genotype was notified in the Caribbean. The outbreak has since spread to 38 regions in the Americas. By September 2014, the first autochthonous CHIKV infections were confirmed in Oiapoque, North Brazil, and in Feira de Santana, Northeast Brazil.MethodsWe compiled epidemiological and clinical data on suspected CHIKV cases in Brazil and polymerase-chain-reaction-based diagnostic was conducted on 68 serum samples from patients with symptom onset between April and September 2014. Two imported and four autochthonous cases were selected for virus propagation, RNA isolation, full-length genome sequencing, and phylogenetic analysis. We then followed CDC/PAHO guidelines to estimate the risk of establishment of CHIKV in Brazilian municipalities.ResultsWe detected 41 CHIKV importations and 27 autochthonous cases in Brazil. Epidemiological and phylogenetic analyses indicated local transmission of the Asian CHIKV genotype in Oiapoque. Unexpectedly, we also discovered that the ECSA genotype is circulating in Feira de Santana. The presumed index case of the ECSA genotype was an individual who had recently returned from Angola and developed symptoms in Feira de Santana. We estimate that, if CHIKV becomes established in Brazil, transmission could occur in 94% of municipalities in the country and provide maps of the risk of importation of each strain of CHIKV in Brazil.ConclusionsThe etiological strains associated with the early-phase CHIKV outbreaks in Brazil belong to the Asian and ECSA genotypes. Continued surveillance and vector mitigation strategies are needed to reduce the future public health impact of CHIKV in the Americas.

Improving Bayesian population dynamics inference: a coalescent-based model for multiple loci

Effective population size is fundamental in population genetics and characterizes genetic diversity. To infer past population dynamics from molecular sequence data, coalescent-based models have been developed for Bayesian nonparametric estimation of effective population size over time. Among the most successful is a Gaussian Markov random field (GMRF) model for a single gene locus. Here, we present a generalization of the GMRF model that allows for the analysis of multilocus sequence data. Using simulated data, we demonstrate the improved performance of our method to recover true population trajectories and the time to the most recent common ancestor (TMRCA). We analyze a multilocus alignment of HIV-1 CRF02_AG gene sequences sampled from Cameroon. Our results are consistent with HIV prevalence data and uncover some aspects of the population history that go undetected in Bayesian parametric estimation. Finally, we recover an older and more reconcilable TMRCA for a classic ancient DNA data set.

Unifying Viral Genetics and Human Transportation Data to Predict the Global Transmission Dynamics of Human Influenza H3N2

Information on global human movement patterns is central to spatial epidemiological models used to predict the behavior of influenza and other infectious diseases. Yet it remains difficult to test which modes of dispersal drive pathogen spread at various geographic scales using standard epidemiological data alone. Evolutionary analyses of pathogen genome sequences increasingly provide insights into the spatial dynamics of influenza viruses, but to date they have largely neglected the wealth of information on human mobility, mainly because no statistical framework exists within which viral gene sequences and empirical data on host movement can be combined. Here, we address this problem by applying a phylogeographic approach to elucidate the global spread of human influenza subtype H3N2 and assess its ability to predict the spatial spread of human influenza A viruses worldwide. Using a framework that estimates the migration history of human influenza while simultaneously testing and quantifying a range of potential predictive variables of spatial spread, we show that the global dynamics of influenza H3N2 are driven by air passenger flows, whereas at more local scales spread is also determined by processes that correlate with geographic distance. Our analyses further confirm a central role for mainland China and Southeast Asia in maintaining a source population for global influenza diversity. By comparing model output with the known pandemic expansion of H1N1 during 2009, we demonstrate that predictions of influenza spatial spread are most accurate when data on human mobility and viral evolution are integrated. In conclusion, the global dynamics of influenza viruses are best explained by combining human mobility data with the spatial information inherent in sampled viral genomes. The integrated approach introduced here offers great potential for epidemiological surveillance through phylogeographic reconstructions and for improving predictive models of disease control.

The HIV-1 reservoir in eight patients on long-term suppressive antiretroviral therapy is stable with few genetic changes over time

Significance Identifying the source and dynamics of persistent HIV-1 during combinational antiretroviral therapy (cART) is crucial for understanding the barriers to curing HIV infection. Through genetic characterization of HIV-1 DNA in infected cells from peripheral blood and gut-associated lymphoid tissue from patients after long-term suppressive cART, our study reveals that the primary barrier to a cure is a remarkably stable pool of infected memory CD4+ T cells. Through in-depth phylogenetic analyses, we determined that the HIV-1 reservoir in these cells from eight patients is kept stable during long-term cART and, with little evidence of viral replication, this population could be maintained by homeostatic cell proliferation or other processes. The source and dynamics of persistent HIV-1 during long-term combinational antiretroviral therapy (cART) are critical to understanding the barriers to curing HIV-1 infection. To address this issue, we isolated and genetically characterized HIV-1 DNA from naïve and memory T cells from peripheral blood and gut-associated lymphoid tissue (GALT) from eight patients after 4–12 y of suppressive cART. Our detailed analysis of these eight patients indicates that persistent HIV-1 in peripheral blood and GALT is found primarily in memory CD4+ T cells [CD45RO+/CD27(+/−)]. The HIV-1 infection frequency of CD4+ T cells from peripheral blood and GALT was higher in patients who initiated treatment during chronic compared with acute/early infection, indicating that early initiation of therapy results in lower HIV-1 reservoir size in blood and gut. Phylogenetic analysis revealed an HIV-1 genetic change between RNA sequences isolated before initiation of cART and intracellular HIV-1 sequences from the T-cell subsets after 4–12 y of suppressive cART in four of the eight patients. However, evolutionary rate analyses estimated no greater than three nucleotide substitutions per gene region analyzed during all of the 4–12 y of suppressive therapy. We also identified a clearly replication-incompetent viral sequence in multiple memory T cells in one patient, strongly supporting asynchronous cell replication of a cell containing integrated HIV-1 DNA as the source. This study indicates that persistence of a remarkably stable population of infected memory cells will be the primary barrier to a cure, and, with little evidence of viral replication, this population could be maintained by homeostatic cell proliferation or other processes.

Automated subtyping of HIV-1 genetic sequences for clinical and surveillance purposes: Performance evaluation of the new REGA version 3 and seven other tools

BACKGROUND To investigate differences in pathogenesis, diagnosis and resistance pathways between HIV-1 subtypes, an accurate subtyping tool for large datasets is needed. We aimed to evaluate the performance of automated subtyping tools to classify the different subtypes and circulating recombinant forms using pol, the most sequenced region in clinical practice. We also present the upgraded version 3 of the Rega HIV subtyping tool (REGAv3). METHODOLOGY HIV-1 pol sequences (PR+RT) for 4674 patients retrieved from the Portuguese HIV Drug Resistance Database, and 1872 pol sequences trimmed from full-length genomes retrieved from the Los Alamos database were classified with statistical-based tools such as COMET, jpHMM and STAR; similarity-based tools such as NCBI and Stanford; and phylogenetic-based tools such as REGA version 2 (REGAv2), REGAv3, and SCUEAL. The performance of these tools, for pol, and for PR and RT separately, was compared in terms of reproducibility, sensitivity and specificity with respect to the gold standard which was manual phylogenetic analysis of the pol region. RESULTS The sensitivity and specificity for subtypes B and C was more than 96% for seven tools, but was variable for other subtypes such as A, D, F and G. With regard to the most common circulating recombinant forms (CRFs), the sensitivity and specificity for CRF01_AE was ~99% with statistical-based tools, with phylogenetic-based tools and with Stanford, one of the similarity based tools. CRF02_AG was correctly identified for more than 96% by COMET, REGAv3, Stanford and STAR. All the tools reached a specificity of more than 97% for most of the subtypes and the two main CRFs (CRF01_AE and CRF02_AG). Other CRFs were identified only by COMET, REGAv2, REGAv3, and SCUEAL and with variable sensitivity. When analyzing sequences for PR and RT separately, the performance for PR was generally lower and variable between the tools. Similarity and statistical-based tools were 100% reproducible, but this was lower for phylogenetic-based tools such as REGA (~99%) and SCUEAL (~96%). CONCLUSIONS REGAv3 had an improved performance for subtype B and CRF02_AG compared to REGAv2 and is now able to also identify all epidemiologically relevant CRFs. In general the best performing tools, in alphabetical order, were COMET, jpHMM, REGAv3, and SCUEAL when analyzing pure subtypes in the pol region, and COMET and REGAv3 when analyzing most of the CRFs. Based on this study, we recommend to confirm subtyping with 2 well performing tools, and be cautious with the interpretation of short sequences.

Establishment and cryptic transmission of Zika virus in Brazil and the Americas

Transmission of Zika virus (ZIKV) in the Americas was first confirmed in May 2015 in northeast Brazil. Brazil has had the highest number of reported ZIKV cases worldwide (more than 200,000 by 24 December 2016) and the most cases associated with microcephaly and other birth defects (2,366 confirmed by 31 December 2016). Since the initial detection of ZIKV in Brazil, more than 45 countries in the Americas have reported local ZIKV transmission, with 24 of these reporting severe ZIKV-associated disease. However, the origin and epidemic history of ZIKV in Brazil and the Americas remain poorly understood, despite the value of this information for interpreting observed trends in reported microcephaly. Here we address this issue by generating 54 complete or partial ZIKV genomes, mostly from Brazil, and reporting data generated by a mobile genomics laboratory that travelled across northeast Brazil in 2016. One sequence represents the earliest confirmed ZIKV infection in Brazil. Analyses of viral genomes with ecological and epidemiological data yield an estimate that ZIKV was present in northeast Brazil by February 2014 and is likely to have disseminated from there, nationally and internationally, before the first detection of ZIKV in the Americas. Estimated dates for the international spread of ZIKV from Brazil indicate the duration of pre-detection cryptic transmission in recipient regions. The role of northeast Brazil in the establishment of ZIKV in the Americas is further supported by geographic analysis of ZIKV transmission potential and by estimates of the basic reproduction number of the virus.

Single Cell Analysis of Lymph Node Tissue from HIV-1 Infected Patients Reveals that the Majority of CD4+ T-cells Contain One HIV-1 DNA Molecule

Genetic recombination contributes to the diversity of human immunodeficiency virus (HIV-1). Productive HIV-1 recombination is, however, dependent on both the number of HIV-1 genomes per infected cell and the genetic relationship between these viral genomes. A detailed analysis of the number of proviruses and their genetic relationship in infected cells isolated from peripheral blood and tissue compartments is therefore important for understanding HIV-1 recombination, genetic diversity and the dynamics of HIV-1 infection. To address these issues, we used a previously developed single-cell sequencing technique to quantify and genetically characterize individual HIV-1 DNA molecules from single cells in lymph node tissue and peripheral blood. Analysis of memory and naïve CD4+ T cells from paired lymph node and peripheral blood samples from five untreated chronically infected patients revealed that the majority of these HIV-1-infected cells (>90%) contain only one copy of HIV-1 DNA, implying a limited potential for productive recombination in virus produced by these cells in these two compartments. Phylogenetic analysis revealed genetic similarity of HIV-1 DNA in memory and naïve CD4+ T-cells from lymph node, peripheral blood and HIV-1 RNA from plasma, implying exchange of virus and/or infected cells between these compartments in untreated chronic infection.

Simultaneously reconstructing viral cross- species transmission history and identifying the underlying constraints

The factors that determine the origin and fate of cross-species transmission events remain unclear for the majority of human pathogens, despite being central for the development of predictive models and assessing the efficacy of prevention strategies. Here, we describe a flexible Bayesian statistical framework to reconstruct virus transmission between different host species based on viral gene sequences, while simultaneously testing and estimating the contribution of several potential predictors of cross-species transmission. Specifically, we use a generalized linear model extension of phylogenetic diffusion to perform Bayesian model averaging over candidate predictors. By further extending this model with branch partitioning, we allow for distinct host transition processes on external and internal branches, thus discriminating between recent cross-species transmissions, many of which are likely to result in dead-end infections, and host shifts that reflect successful onwards transmission in the new host species. Our approach corroborates genetic distance between hosts as a key determinant of both host shifts and cross-species transmissions of rabies virus in North American bats. Furthermore, our results indicate that geographical range overlap is a modest predictor for cross-species transmission, but not for host shifts. Although our evolutionary framework focused on the multi-host reservoir dynamics of bat rabies virus, it is applicable to other pathogens and to other discrete state transition processes.