CROI 2016 Abstract eBook

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Poster Abstracts

Nup358 has already been shown in previous studies to be an adaptor protein for trafficking by the microtubule motor KIF5B . We therefor asked if KIF5B exerts its effect on viral uncoating through Nup358In this study. Methods: We utilized fluorescent microscopy, including colocalization and Proximity Ligation Assay, to measure the association of the viral core with Nup358 in primary macrophages. We also utilized viral CA mutants which are known to enter the nucleus independently of NUP358 (P90A, N74D) to determine the role of KIF5B in the nuclear import of the viral genome, using quantitative PCR. Results: We show here that depletion of the kinesin-1 motor causes a change in viral capsid and Nup358 localization. Also we show here Nup358 has a dispersed cytoplasmic staining in infected macrophages, a natural target cell type for HIV-1, and these Nup358 signal colocalize with viral capsid in the cytoplasm. This Nup358 relocalization and capsid colocalization was absent in N74D and P90A capsid mutants. Finally we show that kinesin-1 and Nup358 are important determinants for the nuclear import of wildtype virus and not for N74D and P90A. Conclusions: Taken together, our data reveal that the cooperative activities of KIF5B and Nup358 are required for the normal uncoating and nuclear import of the HIV-1 genome during infection. In addition to identifying a key player in HIV-1 infection, these studies may reveal new opportunities to prevent the nuclear import of the viral genome and thereby trigger the antiviral response induced by the accumulation of viral DNA in the cytoplasm. 210 Phylogenetic Analysis of HIV Full Genomes in London, UK: Initial Results From ICONIC Background: The ICONIC (InfeCtion respONse through vIrus genomiCs) project applies whole genome sequencing (WGS) to guide clinical management, infection control and public health approaches of viral diseases including HIV. It has developed an automated high-throughput pipeline that rapidly generates HIV clinical genomes (from gag to nef) from large amounts of short read data. Methods: The pipeline was applied to 420 HIV samples from antiretroviral-naive patients, collected at University College London Hospital and Barts Health NHS Trust (London) and sequenced using an Illumina MiSeq at the Wellcome Trust Sanger Institute (Cambridge). The consensus genomes were subtyped using COMET and Rega, and unique recombinants were studied with jpHMM and SimPlot. Maximum-likelihood phylogenetic trees were constructed (RAxML) to identify transmission networks using the Cluster Picker. Drug- resistance mutations (DRMs) and co-receptor usage were analysed using the Stanford HIVdb and Geno2pheno tools, respectively. Results: The pipeline generated genomes for 375/420 samples (89%), with a median length (7.4Kb) that covered 86% of the clinical genome. The most frequent HIV strains were subtypes B (n=153, 41%) and C (n=80, 21%) and CRF02_AG (n=33, 9%). In total, we found 14 different CRFs (n=68, 18%) and multiple URFs (n=32, 8%) that involved recombination between 11 different subtypes/CRFs. The most frequent URFs were A1/D, B/C, B/CRF01 and B/CRF02 (3 cases each). Half (54%) of the URFs lacked breakpoints in PR/ RT, rendering them undetectable if only that was sequenced. Major DRMs were found in 29 (8.3%) PR/RT and 2 (0.8%) integrase sequences. Accessory DRMs were found in 36 (15%) integrase sequences. Usage of X4 co-receptor, which confers resistance to entry inhibitors, was detected in 21 (7%) samples. We detected 21 sequence clusters: 19 pairs (mostly subtypes B and C) and 2 triplets (both CRF02_AG). Conclusions: The initial analysis of genome sequences detected substantial hidden variability in the London HIV epidemic. Analysing full genome sequences, as opposed to only PR/RT, detected DRMs in all target genes (including integrase and env), and identified previously undetected recombinants. It provides a more reliable description of CRFs (that would be otherwise misclassified) and transmission clusters. Further analyses will study intra-sample minority viral populations. ICONIC-HIV will generate thousands of additional genomes that will help to determine whether WGS should be implemented routinely in clinical care. 211 Comparing Three HIV-1 Subtyping Tools and a Novel Phylogenetic-Based Method William Switzer 1 ; Neeraja Saduvala 2 ;Tianchi Zhang 2 ; Angela L. Hernandez 1 ; Pieter Libin 3 ; Daniel Struck 4 ;Tulio de Oliveira 5 ; Anne-MiekeVandamme 6 ; Joel O.Wertheim 7 ; Alexandra M. Oster 1 1 CDC, Atlanta, GA, USA; 2 ICF Intl, Atlanta, GA, USA; 3 Vrije Universiteit Brussel, Brussels, Belgium; 4 Luxembourg Inst of Hlth, Luxembourg, Luxembourg; 5 Univ of KwaZulu-Natal, Durban, South Africa; 6 Katholieke Universiteit Leuven, Leuven, Belgium; 7 Univ of California San Diego, San Diego, CA, USA Background: HIV-1 evolves rapidly, increasing its genetic diversity and complexity, with group M containing >80 subtypes and circulating recombinant forms (CRFs). Subtype determination is important epidemiologically and can impact treatment and vaccine development. Multiple automated subtyping tools are available; however, differences in their subtype/CRF assignments in a predominantly subtype B setting or with large surveillance data have not been fully evaluated. Methods: We included polymerase sequences ≥500-bp in length reported to the U.S. National HIV Surveillance System for HIV-1-infected persons (one sequence/person). We assigned HIV-1 subtype or CRF using COMET (COntext-based Modeling for Expeditious Typing), REGA V3, and SCUEAL (Subtype Classification Using Evolutionary ALgorithms). For sequences not classified as subtype B by all three methods (including those classified as non-B), we performed phylogenetic analysis using a fast, novel method (phylopartitioning) that combined FastTree approximate maximum likelihood inference using 2,864 curated reference sequences with cluster analysis to identify subtype using Phylopart. We compared results of these subtyping approaches. Results: Of 71,659 sequences, subtype B classification varied by method (COMET:94.8%; REGA:91.6%; SCUEAL:89.6%, p<0.0001). In all, 95.7%were determined to be subtype B by at least one method, and 85.6%were classified as subtype B by all three methods. Of 67,973 sequences assigned as subtype B by COMET, 99.3%were assigned to subtype B by REGA, SCUEAL, or both. Of 6,624 sequences assigned to subtype B by COMET that were not subtype B by all three tools, 3,798 (57.3%) were B by REGA but not SCUEAL, 2,319 (35.0%) were B by SCUEAL but not REGA, and 475 (7.2%) were not B by either REGA or SCUEAL. Of these 6,624, 6,580 (99.3%) were subtype B by phylopartitioning. For non-B subtypes/ CRFs, agreement between the three methods also varied, with almost 90% of COMET and REGA assignments, but only 65.4% of SCUEAL assignments, matching results from phylopartitioning. REGA and SCUEAL identified a higher percentage of all sequences as unique recombinants than COMET (REGA: 4.4%; SCUEAL: 6.7%; COMET: 1.2%). Conclusions: In a setting dominated by subtype B, overall results varied by subtyping method. REGA and SCUEAL reported a high number of unique recombinants. COMET and phylopartitioning, on the other hand, identified a larger number of subtype B sequences. 212 Identification of Rare HIV-1 Group N and HTLV-3 Strains in Rural South Cameroon Ana S. Vallari 1 ; Mary A. Rodgers 1 ;Vera Holzmayer 1 ; JulieYamaguchi 1 ; Jules Kenmegne 2 ; Bih Awazi 2 ; Lazare Kaptue 3 ; Dora Mbanya 2 ; Gavin A. Cloherty 1 ; Nicaise Ndembi 4 1 Abbott Lab, Abbott Park, IL, USA; 2 Univ of Yaoundé, Yaoundé, Cameroon; 3 Univ of Montagnes, Bangangte, Cameroon; 4 Inst of Human Virology, Abuja, Nigeria Background: South Cameroon is a hot spot for newly emerging strains of HIV and HTLV, making this region a critical location for monitoring circulating variants that have the potential to spread globally. In this study we aim to monitor the prevalence and diversity of HIV and HTLV, as well as detect emerging viral strains by conducting surveillance of HIV/ HTLV in South Cameroon, which can inform diagnostics and research. Methods: Study participants, recruited in 7 towns in South Cameroon, were screened for HIV infection using the national algorithm from 2010-2015. All collected specimens from 2010 were selected for further testing; however, in 2011-2015 the selection was weighted to include 30-40% HIV positive specimens. All selected specimens were tested with ARCHITECT HIV Ag/Ab Combo assay (Abbott Diagnostics), and a subset with remaining volume was tested with ARCHITECT rHTLV I/II assay. HIV serotype was determined by a peptide multiplex immunoassay, which classified infections as either HIV-1 group M, N, O or HIV-2. Molecular characterization was performed on a subset of reactive HIV and HTLV specimens. Results: In 2010, the prevalence of HIV in South Cameroon was 8.5% amongst study participants. The serotype immunoassay identified the majority of HIV infections in 2010-2015 as group M (99%); group O (n=22) and group N infections (n=2) were also identified and confirmed by sequence classification of env gp41 or pol -integrase regions. Based on env Gonzalo Yebra 1 ; Dan Frampton 2 ;Tiziano Gallo Cassarino 2 ; Zisis Kozlakidis 2 ; Paul Kellam 3 ; Andrew Leigh Brown 1 1 Univ of Edinburgh, Edinburgh, UK; 2 Univ Coll London, London, UK; 3 Wellcome Trust Sanger Inst, Hinxton, UK

Poster Abstracts

81

CROI 2016