{"title":"A daisy chain of inferences: the role of single-cell and single-genome proviral sequencing in characterizing HIV-1 reservoirs.","authors":"Guinevere Q Lee","doi":"10.1097/COH.0000000000000964","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose of review: </strong>Understanding and targeting the HIV reservoir requires navigating a hierarchy of inferential assays. Quantitative viral outgrowth assays, FLIP-seq, and intact proviral DNA assays (IPDA) - though methodologically distinct - are all fundamentally single-cell technologies. Each relies on limiting dilution to isolate and interrogate individual proviral genomes derived from single infected cells, offering high-resolution proxies for the outcome of greatest interest: replication competence and the risk of viral rebound. Rather than providing direct measurements, these assays infer one another in a nested framework. This review highlights the importance of critically interpreting assay outputs within this chain of inference to guide cure-directed strategies and reservoir quantification.</p><p><strong>Recent findings: </strong>Recent studies emphasize the complexity and limitations of current assays measuring HIV-1 reservoirs. Key themes include reliance on bioinformatics definitions of genome-intactness to infer replication competence, alongside significant limitations due to viral diversity, PCR amplification length biases, and definitional inconsistencies. Modified assays like subtype-specific IPDA aim to address these issues.</p><p><strong>Summary: </strong>Standardized, subtype-specific single-cell methodologies are crucial for accurate HIV reservoir characterization. Future research should integrate large-scale sequencing with replication competence validation, and should refine bioinformatics approaches to enhance predictive accuracy. Enhanced assay precision is essential to inform effective HIV cure strategies.</p>","PeriodicalId":93966,"journal":{"name":"Current opinion in HIV and AIDS","volume":" ","pages":""},"PeriodicalIF":4.0000,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12313248/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current opinion in HIV and AIDS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1097/COH.0000000000000964","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose of review: Understanding and targeting the HIV reservoir requires navigating a hierarchy of inferential assays. Quantitative viral outgrowth assays, FLIP-seq, and intact proviral DNA assays (IPDA) - though methodologically distinct - are all fundamentally single-cell technologies. Each relies on limiting dilution to isolate and interrogate individual proviral genomes derived from single infected cells, offering high-resolution proxies for the outcome of greatest interest: replication competence and the risk of viral rebound. Rather than providing direct measurements, these assays infer one another in a nested framework. This review highlights the importance of critically interpreting assay outputs within this chain of inference to guide cure-directed strategies and reservoir quantification.
Recent findings: Recent studies emphasize the complexity and limitations of current assays measuring HIV-1 reservoirs. Key themes include reliance on bioinformatics definitions of genome-intactness to infer replication competence, alongside significant limitations due to viral diversity, PCR amplification length biases, and definitional inconsistencies. Modified assays like subtype-specific IPDA aim to address these issues.
Summary: Standardized, subtype-specific single-cell methodologies are crucial for accurate HIV reservoir characterization. Future research should integrate large-scale sequencing with replication competence validation, and should refine bioinformatics approaches to enhance predictive accuracy. Enhanced assay precision is essential to inform effective HIV cure strategies.