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Métodos genotípicos de resistencia a antivirales JOSÉ C. PALOMARES Catedrático Microbiología Jefe de Sección Microbiología Diagnóstica Molecular. H. U.

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Presentation on theme: "Métodos genotípicos de resistencia a antivirales JOSÉ C. PALOMARES Catedrático Microbiología Jefe de Sección Microbiología Diagnóstica Molecular. H. U."— Presentation transcript:

1 Métodos genotípicos de resistencia a antivirales JOSÉ C. PALOMARES Catedrático Microbiología Jefe de Sección Microbiología Diagnóstica Molecular. H. U. Valme

2 Agentes Antiretrovirales (VIH) Nucleoside RTIs Zidovudine Didanosine Zalcitabine Stavudine Lamivudine Abacavir Emtricitabine Tenofovir Nonnucleos(t)ide RTIs Nevirapine Delavirdine Efavirenz Etravirine Rilpivirina Protease Inhibitors Saquinavir Ritonavir Indinavir Nelfinavir Amprenavir Lopinavir/r Atazanavir Fosamprenavir Tipranavir Darunavir Boosters Ritonavir Cobicistat Fusion Inhibitor Enfuvirtide (T-20) CCR5 Antagonist Maraviroc Vicriviroc Integrase Inhibitors Raltegravir Dolutegravir* Elvitegravir

3 Agentes Antivirales: Virus Hepatitis VHB Lamivudine Tenofovir Entecavir Adefobir Telbivudina VHC Clásicos Interferón Ribavirina Antivirales Acción Directa (DAAs) Inhibidores Proteasa Boceprevir Telaprevir Simeprevir Asunaprevir Faldaprevir Inhibidores Replicasa NS5A Daclatasvir Ledipasvir Inhibidores Polimerasa NS5B Sofosbuvir Deleobuvir



6 Detección Fenotípica de Resistencia Phenotypic susceptibility tests measure viral replication in cell culture in the presence of serialARV dilutions. Plotting the inhibition of viral replication at increasing ARV concentrations creates a sigmoidal dose-response curve that is usually summarized by the ARV concentration that inhibits viral replication by 50 % (IC 50 ). The IC 50 of an ARV cannot be translated directly into the in vivo activity of the ARV because the virus inoculum and cells used in a phenotypic assay often do not reflect “in vivo”conditions. Rather, phenotypic susceptibility testing determines the relative antiviral activity of an ARV against a tested HIV-1 isolate versus against a wild-type control virus. Therefore, drug susceptibility results are reported as levels of fold-resistance, which are calculated by dividing the IC 50 of the investigated virus by the IC 50 of a control virus. Plasma HIV-1 RNA levels >1000 copies per mL are generally required for phenotypic susceptibility testing.

7 Detección Genotípica de Resistencia Genotypic resistance testing relies on detecting known drug- resistance mutations in the enzymatic targets of antiviral therapy: protease, reverse transcriptase, and, if specially requested, integrase and glycoprotein (gp)41. The standard approach to genotypic resistance testing is direct polymerase chain reaction (PCR) dideoxynucleotide (Sanger) sequencing.

8 Detección Genotípica de Resistencia Genotypic testing produces a nucleotide sequence usually encompassing the complete 297 nucleotides (or 99 amino acids) of HIV-1 protease, and the 50 polymerase coding region of HIV-1 reverse transcriptase, usually encompassing amino acid positions 40–240, the part of reverse transcriptase containing the vast majority of NRTI- and NNRTI-resistance mutations. Integrase sequencing is usually ordered as a separate test. The sensitivity of genotypic resistance tests ranges from 100 to 1000 plasma HIV-1 RNA copies per mL, depending upon the assay used.At low plasma HIV-1 RNA levels, genotypic resistance testing is likely to be sequencing only a small number of circulating virus variants.

9 Detección Genotípica de Resistencia The nucleotide sequence is then translated to its amino acid sequence. The amino acid sequence is then compared either with the sequence of a wild- type subtype B laboratory strain or to a consensus wild-type subtype B amino acid sequence. The differences between a sequenced clinical virus and the reference wild-type sequence generates a list of mutations. Mutations are reported using a shorthand in which each mutation is denoted by the one-letter code for the wild-type reference amino acid, followed by the amino acid position, followed by the one-letter code for the amino acid mutation found in the sequence.

10 Mutations in the Envelope Gene Associated With Resistance to Entry Inhibitors Enfuvirtide Maraviroc Maraviroc activity is limited to patients with only CCR5 (R5) -using virus detectable; CXCR4 (X4) -CCR5 mixed tropic viruses and X4- using viruses do not respond to maraviroc treatment. Some cases of virologic failure during maraviroc therapy are associated with outgrowth of X4 virus that pre-exists as a minority population below the level of assay detection. Mutations in the HIV-1 gp120 molecule that allow the virus to bind to R5 receptors in the presence of drug have been described in viruses from some patients whose virus remained R5 at the time of virologic failure. A number of such mutations have been identified, and the phenotypic manifestation of this drug resistance is a reduction in the maximal percentage inhibition (MPI) rather than the increase in the 50% inhibitory concentration (IC50; defined by fold increase) that is characteristic of resistance to other classes of antiretrovirals. The resistance profile for maraviroc is too complex to be depicted on the figures. The frequency and rate at which maraviroc resistance mutations emerge are not yet know

11 Mutations Selected by nRTIs Abacavir Didanosine Emtricitabine Lamivudine Stavudine Tenofovir Zidovudine

12 Mutations Selected by NNRTIs Efavirenz Etravirine Nevirapine

13 Mutations in the Integrase Gene Associated With Resistance to Integrase Inhibitors Raltegravir Raltegravir failure was associated with integrase mutations in 2 distinct genetic pathways defined by 2 or more mutations including: (1) a signature (major) mutation at either Q148H/K/R or N155H; and (2) 1 or more minor mutations unique to each pathway. Minor mutations described in the Q148H/K/R pathway include L74M + E138A, E138K, or G140S. The most common mutation pattern in this pathway is Q148H + G140S; this Q148H + G140S pattern exhibits the greatest loss of drug susceptibility. Mutations described in the N155H pathway include this primary mutation plus either L74M, E92Q, T97A, E92Q + T97A, Y143H, G163K/R, V151I, or D232N (Hazuda et al, Antivir Ther, 2007).

14 Mutations Selected by PIs Atazanavir +/-ritonavir Darunavir/ ritonavir Fosamprenavir/ ritonavir Indinavir/ ritonavir Lopinavir/ ritonavir

15 Mutations Selected by PIs (cont) Nelfinavir Saquinavir/ ritonavir Tipranavir /ritonavir

16 Limitaciones de estudios genotípicos y fenotípicos Necesaria una carga viral  1,000 copias/mL Sensibilidad (no detecta poblaciones minoritarias, precisa prevalencia de  20%+) Calidad (ensayo, laboratorio) Problemas con amplificación por PCR (contaminación) Coste

17 Detección de variantes minoritarias Varias técnicas que permiten detección de variantes con prevalencia incluso menor del 1%: RT-PCR alelo específica Oligonucleotido ligation assay (OLA) Detectan mutaciones puntuales LigAmp Secuenciación de genoma único (SGS) o secuenciación clonal Ultra-deep sequencing Multi-genome sequencing (MGS)


19 Existen variados mecanismos de resistencia frente a ARVs. Múltiples mutaciones generan diferentes efectos sobre la sensibilidad a los ARVs. Las resistencias se adquieren al infectarse o se seleccionan con el tratamiento. Una vez establecida la resistencia, evoluciona, se diversifica y se hace irreversible. PERSPECTIVAS

20 Tecnologías de Secuenciación






26 General Sanger Secuenciación 2ª generación: 454 Illumina SOLiD Ion Torrent Secuenciación 3ª generación: PacBio Nanopore

27 Secuenciación Sanger Traditional DNA sequencing method Ideal for small sequencing projects Read length around 600-700 bp Around 5-10$ per reaction 384 reactions in parallel at most Applied Biosystems is the main technological provider

28 Secuenciación Sanger


30 Secuencia y calidad Phred score = - 10 log (prob error)

31 Secuenciación 2ª generación (NGS)

32 454 First NGS platform Pirosequencing based chemistry Long reads (400-1500 bp) Most expensive cost per base Ideal for de novo sequencing projects Owned by Roche ½, ¼ and 1/8 run can be ordered >1 million reads GS FLX+ and GS Junior

33 454



36 Illumina Previously known as Solexa Reversible terminators based sequencing technique Short reads (75 or 250bp depending on the version) Lowest cost per base Ideal for resequencing projects Highest throughput Runs divided in 8 lines up to 3000 million reads Can sequence both ends of the molecules (paired ends) HiSeq2500 and MiSeq


38 Illumina

39 SOLiD Ligation based sequencing chemistry Short reads (35 - 75bp depending on the version) Only for resequencing projects It does not produce nucleotide sequences, but colors 115 or 320 million reads



42 SOLiD

43 Really?

44 Ion Torrent Around 60-80 M reads. 200 pb length. Sequences based on H+ production Error rates lower than other 2nd generation Error pattern similar to 454, with homopolymer problem. Very cheap per run. Belongs to Life technologies (Applied Biosystems)


46 Sanger vs NGS SangerNGS Num. sequences per reaction 1 cloneMillions of molecules Max. parallelization384Several millions Sequence qualityHighLow Sequence length600-800 bp 35-1000 (depends on the platform) ThroughtputLowHigh

47 Sanger vs NGS

48 Comparación

49 Cost per raw Megabase of DNA

50 Secuenciación 3ª generación

51 PacBio 3rd generation platform (single molecule) Polymerase based chemistry (SMRT) Longest NGS reads (more than 1000bp) Very high error rate Ideal for de novo sequencing projects 45000 reads

52 PacBio 3rd generation, single molecule detection. No amplification step required. Nucleotides labeled on the phosphate removed during the polymerization. Sequencing based on the time required by the polymerase to incorporate a nucleotide (Polymerase requires milliseconds versus microseconds for the stochastic diffusion)



55 Nanopore



58 Sequencing technologies Sanger2 nd Generation3 rd Generation Modified from Michael Stromberg

59 Bioinformatic challenges Huge data files handling. Beefy computers required. Software still being developed or missing. Ad-hoc software required during the analysis. Existing software tailored to experienced bioinformaticians. Dollar for dollar rule proposed EDSAC by Computer Laboratory Cambridge

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