Drug resistance in B and non-B subtypes amongst subjects recently diagnosed as primary/recent or chronic HIV-infected over the period 2013–2016: Impact on susceptibility to first-line strategies including integrase strand-transfer inhibitors

Objectives To characterize the prevalence of transmitted drug resistance mutations (TDRMs) by plasma analysis of 750 patients at the time of HIV diagnosis from January 1, 2013 to November 16, 2016 in the Veneto region (Italy), where all drugs included in the recommended first line therapies were prescribed, included integrase strand transfer inhibitors (InNSTI). Methods TDRMs were defined according to the Stanford HIV database algorithm. Results Subtype B was the most prevalent HIV clade (67.3%). A total of 92 patients (12.3%) were expected to be resistant to one drug at least, most with a single class mutation (60/68–88.2% in subtype B infected subjectsand 23/24–95.8% in non-B subjects) and affecting mainly NNRTIs. No significant differences were observed between the prevalence rates of TDRMs involving one or more drugs, except for the presence of E138A quite only in patients with B subtype and other NNRTI in subjects with non-B infection. The diagnosis of primary/recent infection was made in 73 patients (9.7%): they had almost only TDRMs involving a single class. Resistance to InSTI was studied in 484 subjects (53 with primary-recent infection), one patient had 143C in 2016, a total of thirteen 157Q mutations were detected (only one in primary/recent infection). Conclusions Only one major InSTI-TDRM was identified but monitoring of TDRMs should continue in the light of continuing presence of NNRTI-related mutation amongst newly diagnosed subjects, sometime impacting also to modern NNRTI drugs recommended in first-line therapy

HIV-1 tropism determination using a phenotypic Env recombinant viral assay highlights overestimation of CXCR4-usage by genotypic prediction algorithms for CRRF01_AE and CRF02_AG

Background: Human Immunodeficiency virus type-1 (HIV) entry into target cells involves binding of the viral envelope (Env) to CD4 and a coreceptor, mainly CCR5 or CXCR4. The only currently licensed HIV entry inhibitor, maraviroc, targets CCR5, and the presence of CXCX4-using strains must be excluded prior to treatment. Co-receptor usage can be assessed by phenotypic assays or through genotypic prediction. Here we compared the performance of a phenotypic Env-Recombinant Viral Assay (RVA) to the two most widely used genotypic prediction algorithms, Geno2Pheno([coreceptor]) and webPSSM. Methods: Co-receptor tropism of samples from 73 subtype B and 219 non-B infections was measured phenotypically using a luciferase-tagged, NL4-3-based, RVA targeting Env. In parallel, tropism was inferred genotypically from the corresponding V3-loop sequences using Geno2Pheno([coreceptor]) (5-20% FPR) and webPSSM-R5X4. For discordant samples, phenotypic outcome was retested using co-receptor antagonists or the validated Trofile (R) Enhanced-Sensitivity-Tropism-Assay. Results: The lower detection limit of the RVA was 2.5% and 5% for X4 and R5 minority variants respectively. A phenotype/genotype result was obtained for 210 samples. Overall, concordance of phenotypic results with Geno2Pheno([coreceptor]) was 85.2% and concordance with webPSSM was 79.5%. For subtype B, concordance with Geno2pheno([coreceptor]) was 94.4% and concordance with webPSSM was 79.6%. High concordance of genotypic tools with phenotypic outcome was seen for subtype C (90% for both tools). Main discordances involved CRF01_AE and CRF02_AG for both algorithms (CRF01_AE: 35.9% discordances with Geno2Pheno([coreceptor]) and 28.2% with webPSSM; CRF02_AG: 20.7% for both algorithms). Genotypic prediction overestimated CXCR4-usage for both CRFs. For webPSSM, 40% discordance was observed for subtype A. Conclusions: Phenotypic assays remain the most accurate for most non-B subtypes and new subtype-specific rules should be developed for non-B subtypes, as research studies more and more draw conclusions from genotypically-inferred tropism, and to avoid unnecessarily precluding patients with limited treatment options from receiving maraviroc or other entry inhibitors

RegaDB: Community-driven data management and analysis for infectious diseases

Summary: RegaDB is a free and open source data management and analysis environment for infectious diseases. RegaDB allows clinicians to store, manage and analyse patient data, including viral genetic sequences. Moreover, RegaDB pr

The HIV-1 Subtype C Epidemic in South America Is Linked to the United Kingdom

Background: The global spread of HIV-1 has been accompanied by the emergence of genetically distinct viral strains. Over the past two decades subtype C viruses, which predominate in Southern and Eastern Africa, have spread rapidly throughout parts of South America. Phylogenetic studies indicate that subtype C viruses were introduced to South America through a single founder event that occurred in Southern Brazil. However, the external route via which subtype C viruses spread to the South American continent has remained unclear.Methodology/Principal Findings: We used automated genotyping to screen 8,309 HIV-1 subtype C pol gene sequences sampled within the UK for isolates genetically linked to the subtype C epidemic in South America. Maximum likelihood and Bayesian approaches were used to explore the phylogenetic relationships between 54 sequences identified in this screen, and a set of globally sampled subtype C reference sequences. Phylogenetic trees disclosed a robustly supported relationship between sequences from Brazil, the UK and East Africa. A monophyletic cluster comprised exclusively of sequences from the UK and Brazil was identified and dated to approximately the early 1980s using a Bayesian coalescent-based method. A sub-cluster of 27 sequences isolated from homosexual men of UK origin was also identified and dated to the early 1990s.Conclusions: Phylogenetic, demographic and temporal data support the conclusion that the UK was a crucial staging post in the spread of subtype C from East Africa to South America. This unexpected finding demonstrates the role of diffuse international networks in the global spread of HIV-1 infection, and the utility of globally sampled viral sequence data in revealing these networks. Additionally, we show that subtype C viruses are spreading within the UK amongst men who have sex with men

Database resources of the National Center for Biotechnology Information

In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data retrieval systems and computational resources for the analysis of data in GenBank and other biological data made available through NCBI's website. NCBI resources include Entrez, Entrez Programming Utilities, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs), Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheritance in Man (OMIM), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD) and the Conserved Domain Architecture Retrieval Tool (CDART). Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized datasets. All of the resources can be accessed through the NCBI home page at http://www.ncbi.nlm.nih.gov

Recent trends in molecular diagnostics of yeast infections : from PCR to NGS

The incidence of opportunistic yeast infections in humans has been increasing over recent years. These infections are difficult to treat and diagnose, in part due to the large number and broad diversity of species that can underlie the infection. In addition, resistance to one or several antifungal drugs in infecting strains is increasingly being reported, severely limiting therapeutic options and showcasing the need for rapid detection of the infecting agent and its drug susceptibility profile. Current methods for species and resistance identification lack satisfactory sensitivity and specificity, and often require prior culturing of the infecting agent, which delays diagnosis. Recently developed high-throughput technologies such as next generation sequencing or proteomics are opening completely new avenues for more sensitive, accurate and fast diagnosis of yeast pathogens. These approaches are the focus of intensive research, but translation into the clinics requires overcoming important challenges. In this review, we provide an overview of existing and recently emerged approaches that can be used in the identification of yeast pathogens and their drug resistance profiles. Throughout the text we highlight the advantages and disadvantages of each methodology and discuss the most promising developments in their path from bench to bedside

A standardized framework for accurate, high-throughput genotyping of recombinant and non-recombinant viral sequences

Human immunodeficiency virus type-1 (HIV-1), hepatitis B and C and other rapidly evolving viruses are characterized by extremely high levels of genetic diversity. To facilitate diagnosis and the development of prevention and treatment strategies that efficiently target the diversity of these viruses, and other pathogens such as human T-lymphotropic virus type-1 (HTLV-1), human herpes virus type-8 (HHV8) and human papillomavirus (HPV), we developed a rapid high-throughput-genotyping system. The method involves the alignment of a query sequence with a carefully selected set of pre-defined reference strains, followed by phylogenetic analysis of multiple overlapping segments of the alignment using a sliding window. Each segment of the query sequence is assigned the genotype and sub-genotype of the reference strain with the highest bootstrap (>70%) and bootscanning (>90%) scores. Results from all windows are combined and displayed graphically using color-coded genotypes. The new Virus-Genotyping Tools provide accurate classification of recombinant and non-recombinant viruses and are currently being assessed for their diagnostic utility. They have incorporated into several HIV drug resistance algorithms including the Stanford (http://hivdb.stanford.edu) and two European databases (http://www.umcutrecht.nl/subsite/spread-programme/ and http://www.hivrdb.org.uk/) and have been successfully used to genotype a large number of sequences in these and other databases. The tools are a PHP/JAVA web application and are freely accessible on a number of servers including

In-house human immunodeficiency virus-1 genotype resistance testing to determine highly active antiretroviral therapy resistance mutations in Hong Kong

Objective To determine the frequency of highly active antiretroviral therapy resistance mutations in the viral pol gene of human immunodeficiency virus-1 (HIV-1) genotypes that circulate in Hong Kong, by means of an in-house HIV-1 genotyping system. Design Retrospective study. Setting Two HIV clinics in Hong Kong. Patients A modified in-house genotyping resistance test was used to sequence the partial pol gene in 1165 plasma samples from 965 patients. The performance of our test was cross-compared with the US Food and Drug Administration-approved ViroSeq HIV-1 genotyping system. The results of genotyping were submitted to the Stanford HIV-1 drug resistance database for analysis. Results The cost-effective in-house genotypic resistance test (US$40) demonstrated comparable performance to the US Food and Drug Administration-approved ViroSeq system. The detection limit of this in-house genotypic resistance test could reach 400 copies/mL for both HIV-1 subtype B and CRF01_AE, which were the predominant genotypes in Hong Kong. Drug resistance mutations were detected only in post-treatment samples from treatment-failure patients. However, there was no significant difference in the frequency of drug resistance mutations between subtype B and CRF01_AE. Conclusion Our cost-effective in-house genotypic resistance test detected no significant difference in drug resistance-related mutations frequencies between HIV-1 subtype B and CRF01_AE in Hong Kong. A drug resistance-related mutations database for different HIV-1 genotypes should be established in Hong Kong to augment guidance for HIV treatment.published_or_final_versio