Quantitative prediction of integrase inhibitor resistance from genotype through consensus linear regression modeling.

BACKGROUND: Integrase inhibitors (INI) form a new drug class in the treatment of HIV-1 patients. We developed a linear regression modeling approach to make a quantitative raltegravir (RAL) resistance phenotype prediction, as Fold Change in IC50 against a wild type virus, from mutations in the integrase genotype. METHODS: We developed a clonal genotype-phenotype database with 991 clones from 153 clinical isolates of INI naïve and RAL treated patients, and 28 site-directed mutants.We did the development of the RAL linear regression model in two stages, employing a genetic algorithm (GA) to select integrase mutations by consensus. First, we ran multiple GAs to generate first order linear regression models (GA models) that were stochastically optimized to reach a goal R2 accuracy, and consisted of a fixed-length subset of integrase mutations to estimate INI resistance. Secondly, we derived a consensus linear regression model in a forward stepwise regression procedure, considering integrase mutations or mutation pairs by descending prevalence in the GA models. RESULTS: The most frequently occurring mutations in the GA models were 92Q, 97A, 143R and 155H (all 100%), 143G (90%), 148H/R (89%), 148K (88%), 151I (81%), 121Y (75%), 143C (72%), and 74M (69%). The RAL second order model contained 30 single mutations and five mutation pairs (p < 0.01): 143C/R&97A, 155H&97A/151I and 74M&151I. The R2 performance of this model on the clonal training data was 0.97, and 0.78 on an unseen population genotype-phenotype dataset of 171 clinical isolates from RAL treated and INI naïve patients. CONCLUSIONS: We describe a systematic approach to derive a model for predicting INI resistance from a limited amount of clonal samples. Our RAL second order model is made available as an Additional file for calculating a resistance phenotype as the sum of integrase mutations and mutation pairs.

Development and performance of conventional HIV-1 phenotyping (Antivirogram®) and genotype-based calculated phenotyping assay (virco®TYPE HIV-1) on protease and reverse transcriptase genes to evaluate drug resistance.

OBJECTIVES: A wide array of monitoring tests is commercially available to gauge HIV-1 disease progression and the overall health status of an HIV-1-infected patient. Viral load tests provide a picture of viral activity, while CD4 cell counts shed light on the immune status and can help physicians to prevent the development of opportunistic infections in patients. On the other hand, genotypic and phenotypic resistance testing and therapeutic drug monitoring help to optimize HIV-1 antiretroviral therapy. Resistance testing is currently recommended within the standard of care guidelines to aid the choice of new drug regimens following treatment failure(s). METHODS: Genotypic testing described here is based on the amplification and sequencing of an HIV-1 protease (PR) and reverse transcriptase (RT) region from a patient sample to identify resistance mutations associated with PR and RT inhibitor resistance. A genotypic test takes a week to perform and the results are reported as a list of detected mutations. The virco®TYPE HIV-1 report uses genotypic data to predict phenotypic susceptibility by linear regression modeling that uses a large correlative database of genotype-phenotype pairs. Phenotypic testing measures the ability of the virus to replicate in the presence of a drug and provides a direct measurement of drug susceptibility in vitro. Since phenotypic analysis is laborious and time consuming (28 days), genotypic resistance testing is currently the standard reference method used for HIV-1 resistance testing. However, a phenotypic test is important when a patient harbors virus with complex genetic patterns, or when the mutational resistance profile for a particular drug is not well-characterized. RESULTS AND CONCLUSIONS: Some of the currently used resistance tests are partially automated enabling laboratories to increase overall efficiency. However, maximum automation and standardization of the process, instruments and software that we have described here can overcome many of the problems encountered with current tests and aims at having a compliant, high-throughput, diagnostic laboratory, which can guarantee sample integrity from sample reception to result reporting. We also describe in detail the development and performance of virco®TYPE HIV-1 (genotype) and Antivirogram® (phenotype) assay on PR and RT genes to evaluate antiretroviral resistance.

Quantitative polymerase chain reaction in the bioanalytical laboratory and technical and scientific considerations for nonclinical and clinical assay characterization, validation and sample analysis.

In this manuscript, the European Bioanalysis Forum reports back on their discussions on practical and scientific considerations related to bioanalytical applications of quantitative polymerase chain reaction. This publication follows an earlier publication in which the European Bioanalysis Forum recommends to consider principles of context of use when defining assay acceptance criteria for method validation criteria and sample analysis.

Reliable and Scalable SARS-CoV-2 qPCR Testing at a High Sample Throughput: Lessons Learned from the Belgian Initiative.

We present our approach to rapidly establishing a standardized, multi-site, nation-wide COVID-19 screening program in Belgium. Under auspices of a federal government Task Force responsible for upscaling the country's testing capacity, we were able to set up a national testing initiative with readily available resources, putting in place a robust, validated, high-throughput, and decentralized qPCR molecular testing platform with embedded proficiency testing. We demonstrate how during an acute scarcity of equipment, kits, reagents, personnel, protective equipment, and sterile plastic supplies, we introduced an approach to rapidly build a reliable, validated, high-volume, high-confidence workflow based on heterogeneous instrumentation and diverse assays, assay components, and protocols. The workflow was set up with continuous quality control monitoring, tied together through a clinical-grade information management platform for automated data analysis, real-time result reporting across different participating sites, qc monitoring, and making result data available to the requesting physician and the patient. In this overview, we address challenges in optimizing high-throughput cross-laboratory workflows with minimal manual intervention through software, instrument and assay validation and standardization, and a process for harmonized result reporting and nation-level infection statistics monitoring across the disparate testing methodologies and workflows, necessitated by a rapid scale-up as a response to the pandemic.

Applying context of use to quantitative polymerase chain reaction method validation and analysis: a recommendation from the European Bioanalysis Forum.

Polymerase chain reaction (PCR) is widely used in various fields of laboratory testing, ranging from forensic, molecular biology, medical and diagnostic applications to a wide array of basic research purposes. COVID-19 infection testing has brought the three-letter PCR abbreviation into the vocabulary of billions of people, making it likely the most well-known laboratory test worldwide. With new modalities and translational medicine gaining importance in pharmaceutical research and development, PCR or more specifically, quantitative PCR (qPCR) is now becoming a standard tool in the (regulated) bioanalytical laboratory, driving the bioanalytical community to define best practices for method development, characterization and validation. In absence of specific guidance from health authorities, qPCR may be vulnerable to scope creep from pharmacokinetics (PK) assay validation as defined in bioanalytical method validation guidance/guidelines. In this manuscript, the European Bioanalysis Forum builds a rationale for applying context of use principles when defining requirements for qPCR assay performance and validation criteria.

Resistance-associated mutations to etravirine (TMC-125) in antiretroviral-naïve patients infected with non-B HIV-1 subtypes.

Susceptibility to etravirine (ETR), an expanded-spectrum nonnucleoside reverse transcriptase inhibitor (NNRTI), is dependent on the type and number of NNRTI resistance-associated mutations (RAMs). Studies have shown that some HIV-1 subtypes may have natural polymorphisms described as ETR RAMs. This study addresses the prevalence of ETR RAMs in treatment-naïve patients infected with HIV-1 non-B subtypes and its potential impact on ETR susceptibility. The prevalence of ETR RAMs in 726 antiretroviral-naïve patients infected with non-B HIV-1 subtypes was studied. ETR genotypic resistance was interpreted according to Agence Nationale de Recherches sur le SIDA and Stanford algorithms. NNRTI phenotypic susceptibilities of samples with at least one ETR RAM were measured. Overall, 75 (10.3%) of 726 sequences harbored at least one ETR RAM: sequences from 72 patients (10%) each had one ETR RAM, and sequences from 3 patients (0.4%) each had two ETR RAMs (V90I and Y181C in one case and V90I and A98G in two cases). None of the viruses had three or more ETR RAMs, and none were consequently classified as resistant to ETR. All sequences with two ETR RAMs belonged to subtype CRF02_AG. The presence of one ETR RAM was statistically more frequent in subtype CRF02_AG than in other non-B subtypes (P=0.004). Three new mutation profiles (E138A and V179I, Y181C and H221Y, and V90I and Y181C) showing decreased ETR phenotypic susceptibility were identified. In conclusion, although the prevalence of ETR RAMs in treatment-naïve patients infected with non-B HIV-1 subtypes was 10%, in most cases this had no significant impact on ETR susceptibility. However, the transmission of drug-resistant viruses with Y181C in a non-B genetic background has a potential for impact on ETR susceptibility.

Susceptibility of human immunodeficiency virus type 1 to the maturation inhibitor bevirimat is modulated by baseline polymorphisms in Gag spacer peptide 1.

In this study, we evaluated baseline susceptibility to bevirimat (BVM), the first in a new class of antiretroviral agents, maturation inhibitors. We evaluated susceptibility to BVM by complete gag genotypic and phenotypic testing of 20 patient-derived human immunodeficiency virus type 1 isolates and 20 site-directed mutants. We found that reduced BVM susceptibility was associated with naturally occurring polymorphisms at positions 6, 7, and 8 in Gag spacer peptide 1.

HIV-1 genotyping of the protease-reverse transcriptase and integrase genes to detect mutations that confer antiretroviral resistance.

Major advances in antiretroviral (ARV) therapy during the last decade have made HIV-1 infections a chronic, manageable disease. In spite of these significant advancements, ARV drug resistance remains a hurdle for HIV-infected patients who are committed to lifelong treatments. Several commercially marketed and/or laboratory-developed tests (LDT) are available to detect resistance-associated mutations (RAMs) in HIV-1, by genotyping. These genotyping tests mainly comprise polymerase chain reaction (PCR)-amplification and population, nucleotide sequencing (Sanger methodology) of a large part of the protease (PR), reverse transcriptase (RT), and integrase (IN) genes. In this chapter, we describe HIV-1 PR, RT, and IN genotyping on clinical samples (plasma), using the LDT methodology performed at Janssen Diagnostics BVBA, Belgium (JDx), where the PR-RT genotyping is used as input, to generate a CE-marked vircoTYPE™ HIV-1 report while the IN genotyping is performed as a research-use-only (RUO) assay. The complete HIV-1 PR gene (297 bp; 99 amino acids) and a large part of the RT gene (the first 1,200 bp; 400 amino acids) are amplified and sequenced as a single 1,497 bp fragment. Genotyping of the IN gene is performed by amplification and sequencing of the RT-IN region (the last 459 bp; 153 amino acids of RT with the complete 867 bp; 289 amino acids of IN). This methodology allows identification of nucleoside/-nucleotide reverse transcriptase, non-nucleoside reverse transcriptase, protease, and integrase inhibitor (NRTI, NtRTI, NNRTI, PI, INI) RAMs in the PR-RT and IN genes, which allows to predict viral response against current ARV regimens.

Cell-free synthesis of poliovirus: 14S subunits are the key intermediates in the encapsidation of poliovirus RNA.

In a cell-free system of uninfected HeLa cells, programmed with poliovirus RNA, extraneous radiolabelled 14S subunits assembled with endogenous 14S subunits and interacted with newly synthesized RNA to form virions (160S). This result suggests that 14S subunits are the key intermediates in the encapsidation of poliovirus RNA.