HIV-1 subtype-specific drug resistance on dolutegravir-based antiretroviral therapy: protocol for a multicentre longitudinal study (DTG RESIST).

Introduction: HIV drug resistance poses a challenge to the United Nation's goal of ending the HIV/AIDS epidemic. The integrase strand transfer inhibitor (InSTI) dolutegravir, which has a higher resistance barrier, was endorsed by the World Health Organization in 2019 for first-, second-, and third-line antiretroviral therapy (ART). This multiplicity of roles of dolutegravir in ART may facilitate the emergence of dolutegravir resistance. Methods and analysis: DTG RESIST is a multicentre longitudinal study of adults and adolescents living with HIV in sub-Saharan Africa, Asia, and South and Central America who experienced virologic failure on dolutegravir-based ART. At the time of virologic failure whole blood will be collected and processed to prepare plasma or dried blood spots. Laboratories in Durban, Mexico City and Bangkok will perform genotyping. Analyses will focus on (i) individuals who experienced virologic failure on dolutegravir, and (ii) on those who started or switched to such a regimen and were at risk of virologic failure. For population (i), the outcome will be any InSTI drug resistance mutations, and for population (ii) virologic failure defined as a viral load >1000 copies/mL. Phenotypic testing will focus on non-B subtype viruses with major InSTI resistance mutations. Bayesian evolutionary models will explore and predict treatment failure genotypes. The study will have intermediate statistical power to detect differences in resistance mutation prevalence between major HIV-1 subtypes; ample power to identify risk factors for virologic failure and limited power for analysing factors associated with individual InSTI drug resistance mutations. Ethics and dissemination: The research protocol was approved by the Biomedical Research Ethics Committee at the University of KwaZulu-Natal, South Africa, and the Ethics Committee of the Canton of Bern, Switzerland. All sites participate in IeDEA and have obtained ethics approval from their local ethics committee to conduct the additional data collection. Registration: NCT06285110. Strengths and limitations of this study: - DTG RESIST is a large international study to prospectively examine emergent dolutegravir resistance in diverse settings characterised by different HIV-1 subtypes, provision of ART, and guidelines on resistance testing. - Embedded within the International epidemiology Databases to Evaluate AIDS (IeDEA), DTG RESIST will benefit from harmonized clinical data across participating sites and expertise in clinical, epidemiological, biological, and computational fields. - Procedures for sequencing and assembling genomes from different HIV-1 strains will be developed at the heart of the HIV epidemic, by the KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), in Durban, South Africa. Phenotypic testing, Genome Wide Association Study (GWAS) methods and Bayesian evolutionary models will explore and predict treatment failure genotypes. - A significant limitation is the absence of genotypic resistance data from participants before they started dolutegravir treatment, as collecting and bio-banking pre-treatment samples was not feasible at most IeDEA sites. Consistent and harmonized data on adherence to treatment are also lacking. - The distribution of HIV-1 subtypes across different sites is uncertain, which may limit the statistical power of the study in analysing patterns and risk factors for dolutegravir resistance. The results from GWAS and Bayesian modelling analyses will be preliminary and hypothesis-generating.

HIV-1 subtype-specific drug resistance on dolutegravir-based antiretroviral therapy: protocol for a multicentre study (DTG RESIST).

INTRODUCTION: HIV drug resistance poses a challenge to the United Nation's goal of ending the HIV/AIDS epidemic. The integrase strand transfer inhibitor (InSTI) dolutegravir, which has a higher resistance barrier, was endorsed by the WHO in 2019 for first-line, second-line and third-line antiretroviral therapy (ART). This multiplicity of roles of dolutegravir in ART may facilitate the emergence of dolutegravir resistance. METHODS AND ANALYSIS: Nested within the International epidemiology Databases to Evaluate AIDS (IeDEA), DTG RESIST is a multicentre study of adults and adolescents living with HIV in sub-Saharan Africa, Asia, and South and Central America who experienced virological failure on dolutegravir-based ART. At the time of virological failure, whole blood will be collected and processed to prepare plasma or dried blood spots. Laboratories in Durban, Mexico City and Bangkok will perform genotyping. Analyses will focus on (1) individuals who experienced virological failure on dolutegravir and (2) those who started or switched to such a regimen and were at risk of virological failure. For population (1), the outcome will be any InSTI drug resistance mutations, and for population (2) virological failure is defined as a viral load >1000 copies/mL. Phenotypic testing will focus on non-B subtype viruses with major InSTI resistance mutations. Bayesian evolutionary models will explore and predict treatment failure genotypes. The study will have intermediate statistical power to detect differences in resistance mutation prevalence between major HIV-1 subtypes; ample power to identify risk factors for virological failure and limited power for analysing factors associated with individual InSTI drug resistance mutations. ETHICS AND DISSEMINATION: The research protocol was approved by the Biomedical Research Ethics Committee at the University of KwaZulu-Natal, South Africa and the Ethics Committee of the Canton of Bern, Switzerland. All sites participate in International epidemiology Databases to Evaluate AIDS and have obtained ethics approval from their local ethics committee to collect additional data. TRIAL REGISTRATION NUMBER: NCT06285110.

High-throughput flow cytometry-based assay to identify apoptosis-inducing proteins.

After sequencing the human genome, the challenge ahead is to systematically analyze the functions and disease relation of the proteins encoded. Here the authors describe the application of a flow cytometry-based high-throughput assay to screen for apoptosis-activating proteins in transiently transfected cells. The assay is based on the detection of activated caspase-3 with a specific antibody, in cells overexpressing proteins tagged C- or N-terminally with yellow fluorescent protein. Fluorescence intensities are measured using a flow cytometer integrated with a high-throughput autosampler. The applicability of this screen has been tested in a pilot screen with 200 proteins. The candidate proteins were all verified in an independent microscopy-based nuclear fragmentation assay, finally resulting in the identification of 6 apoptosis inducers.

Functional profiling: from microarrays via cell-based assays to novel tumor relevant modulators of the cell cycle.

Cancer transcription microarray studies commonly deliver long lists of "candidate" genes that are putatively associated with the respective disease. For many of these genes, no functional information, even less their relevance in pathologic conditions, is established as they were identified in large-scale genomics approaches. Strategies and tools are thus needed to distinguish genes and proteins with mere tumor association from those causally related to cancer. Here, we describe a functional profiling approach, where we analyzed 103 previously uncharacterized genes in cancer relevant assays that probed their effects on DNA replication (cell proliferation). The genes had previously been identified as differentially expressed in genome-wide microarray studies of tumors. Using an automated high-throughput assay with single-cell resolution, we discovered seven activators and nine repressors of DNA replication. These were further characterized for effects on extracellular signal-regulated kinase 1/2 (ERK1/2) signaling (G1-S transition) and anchorage-independent growth (tumorigenicity). One activator and one inhibitor protein of ERK1/2 activation and three repressors of anchorage-independent growth were identified. Data from tumor and functional profiling make these proteins novel prime candidates for further in-depth study of their roles in cancer development and progression. We have established a novel functional profiling strategy that links genomics to cell biology and showed its potential for discerning cancer relevant modulators of the cell cycle in the candidate lists from microarray studies.

Statistical methods and software for the analysis of highthroughput reverse genetic assays using flow cytometry readouts.

Highthroughput cell-based assays with flow cytometric readout provide a powerful technique for identifying components of biologic pathways and their interactors. Interpretation of these large datasets requires effective computational methods. We present a new approach that includes data pre-processing, visualization, quality assessment, and statistical inference. The software is freely available in the Bioconductor package prada. The method permits analysis of large screens to detect the effects of molecular interventions in cellular systems.

From ORFeome to biology: a functional genomics pipeline.

As several model genomes have been sequenced, the elucidation of protein function is the next challenge toward the understanding of biological processes in health and disease. We have generated a human ORFeome resource and established a functional genomics and proteomics analysis pipeline to address the major topics in the post-genome-sequencing era: the identification of human genes and splice forms, and the determination of protein localization, activity, and interaction. Combined with the understanding of when and where gene products are expressed in normal and diseased conditions, we create information that is essential for understanding the interplay of genes and proteins in the complex biological network. We have implemented bioinformatics tools and databases that are suitable to store, analyze, and integrate the different types of data from high-throughput experiments and to include further annotation that is based on external information. All information is presented in a Web database (http://www.dkfz.de/LIFEdb). It is exploited for the identification of disease-relevant genes and proteins for diagnosis and therapy.