{"title":"利用单细胞技术了解HIV潜伏期模型。","authors":"Julia S Huff, Edward P Browne","doi":"10.1097/COH.0000000000000959","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose of review: </strong>This review outlines current model systems of HIV latency and their analysis with single-cell omics technologies. Previous studies have used bulk analyses of infected cell cultures to determine mechanisms of HIV transcription and to identify targets associated with HIV latency in vitro . However, heterogeneity in cell populations creates a barrier to the effectiveness of latency reversing agents. Single cell approaches promise to accelerate our understanding of how the host cell environment regulates complex behaviors of the HIV provirus.</p><p><strong>Recent findings: </strong>Several recent papers have applied cutting edge single cell omics methods to model systems of HIV latency, including scRNAseq and scATACseq, as well as multiomic methods such as DOGMAseq and ECCITEseq. These papers have revealed complex heterogeneity in latently infected cells but have also led to the identification of several new host cell genes that regulate HIV latency.</p><p><strong>Summary: </strong>Single-cell technologies provide sensitive detection of cellular subpopulations that contribute to proviral reactivation and latency, making them advantageous to apply to widely used cell line and primary cell models of HIV latency. These studies have increased our understanding of HIV latency model systems and generated novel hypotheses which can be tested in clinical samples from people with HIV.</p>","PeriodicalId":93966,"journal":{"name":"Current opinion in HIV and AIDS","volume":" ","pages":"488-492"},"PeriodicalIF":4.0000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12321199/pdf/","citationCount":"0","resultStr":"{\"title\":\"Using single cell technologies to understand HIV latency models.\",\"authors\":\"Julia S Huff, Edward P Browne\",\"doi\":\"10.1097/COH.0000000000000959\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose of review: </strong>This review outlines current model systems of HIV latency and their analysis with single-cell omics technologies. Previous studies have used bulk analyses of infected cell cultures to determine mechanisms of HIV transcription and to identify targets associated with HIV latency in vitro . However, heterogeneity in cell populations creates a barrier to the effectiveness of latency reversing agents. Single cell approaches promise to accelerate our understanding of how the host cell environment regulates complex behaviors of the HIV provirus.</p><p><strong>Recent findings: </strong>Several recent papers have applied cutting edge single cell omics methods to model systems of HIV latency, including scRNAseq and scATACseq, as well as multiomic methods such as DOGMAseq and ECCITEseq. These papers have revealed complex heterogeneity in latently infected cells but have also led to the identification of several new host cell genes that regulate HIV latency.</p><p><strong>Summary: </strong>Single-cell technologies provide sensitive detection of cellular subpopulations that contribute to proviral reactivation and latency, making them advantageous to apply to widely used cell line and primary cell models of HIV latency. These studies have increased our understanding of HIV latency model systems and generated novel hypotheses which can be tested in clinical samples from people with HIV.</p>\",\"PeriodicalId\":93966,\"journal\":{\"name\":\"Current opinion in HIV and AIDS\",\"volume\":\" \",\"pages\":\"488-492\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2025-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12321199/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.0000000000000959\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/7/11 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current opinion in HIV and AIDS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1097/COH.0000000000000959","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/11 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Using single cell technologies to understand HIV latency models.
Purpose of review: This review outlines current model systems of HIV latency and their analysis with single-cell omics technologies. Previous studies have used bulk analyses of infected cell cultures to determine mechanisms of HIV transcription and to identify targets associated with HIV latency in vitro . However, heterogeneity in cell populations creates a barrier to the effectiveness of latency reversing agents. Single cell approaches promise to accelerate our understanding of how the host cell environment regulates complex behaviors of the HIV provirus.
Recent findings: Several recent papers have applied cutting edge single cell omics methods to model systems of HIV latency, including scRNAseq and scATACseq, as well as multiomic methods such as DOGMAseq and ECCITEseq. These papers have revealed complex heterogeneity in latently infected cells but have also led to the identification of several new host cell genes that regulate HIV latency.
Summary: Single-cell technologies provide sensitive detection of cellular subpopulations that contribute to proviral reactivation and latency, making them advantageous to apply to widely used cell line and primary cell models of HIV latency. These studies have increased our understanding of HIV latency model systems and generated novel hypotheses which can be tested in clinical samples from people with HIV.