Single-cell profiling reveals immunometabolic remodeling with T-cell dysfunction in HIV-1 infected people

Abstract Background: Immunometabolism plays a vital role in the immunopathogenesis of people living with human immunodeficiency virus type 1 (HIV-1) (PLWH). However, the precise relationship between metabolic profiles and T-cell dysfunction in this population remains unclear. This study aims to investigate the metabolic reprogramming and underlying mechanisms contributing to T-cell dysfunction in PLWH. Methods: This study re-analyzed single-cell RNA sequencing data from the Genome Sequence Archive of the Beijing Institute of Genomics Data Center, Chinese Academy of Sciences. The dataset comprised samples from healthy donors (HD), HIV-1-infected treatment-naive patients (TN), and patients undergoing antiviral therapy. Various analytical approaches—including functional analysis, transcription factor analysis, network analysis, and enrichment analysis—were performed to assess T-cell functional and metabolic characteristics, as well as to identify potential targets within metabolic-epigenetic or non-epigenetic regulatory axes involved in T-cell dysfunction. Results: By analyzing the transcriptional profiles, a total of 58,752 CD4 + T cell subsets and 68,907 CD8 + T cell subsets were identified and annotated. Among these, the naive subset CD8-CCR7 was significantly reduced in TN patients compared to HD ( P < 0.05), whereas CD4-CCR7 showed a decreasing trend. Conversely, the effector subset CD8+ activated effector/memory T cells (CD8-EMRA) were significantly increased in TN patients ( P < 0.05), while cytolytic CD4+ T cells (CD4-CTL) displayed an increasing trend. ART did not effectively restore these alterations. Additionally, naive subsets and CD8-EMRA cells were associated with disease progression. Further analysis revealed that naive subsets exhibited hyper-activation and increased differentiation, whereas effector subsets showed excessive activation and a strong interferon (IFN) response in PLWH compared to HD ( P < 0.05). Intriguingly, we observed substantial metabolic alterations linked to immune dysfunction within the four T-cell subsets. Specifically, elevated levels of the methyltransferases absent, small, or homeotic-like 1 (ASH1L) and SET domain containing the 1B gene (SETD1B) may promote the differentiation and exhaustion of the CD4-CCR7 subset via the ASH1L/SETD1B-H3K4me3-FOXP1 axis. These enzymes are also associated with the exhaustion of CD8-CCR7 cells in TN patients through ASH1L/SETD1B-H3K4me3 axis. Additionally, isocitrate dehydrogenase 2 (IDH2)-mediated production of α-ketoglutarate (α-KG) may contribute to the dysfunction of CD8-CCR7 cells by activating janus kinase (JAK)-signal transducer and activator of transcription (STAT)3-dependent interferon signaling during HIV-1 infection. Conversely, increased activity of SET domain containing protein 2 methyltransferase is closely linked to hyperactivation, a strong type I interferon response, and cellular senescence in CD4-CTL cells from TN patients. Furthermore, heightened expression of solute carrier family 7 member 5 correlates with exhaustion of effector subsets in TN individuals. The IDH2-STAT1 axis may also play a crucial role in driving the over-activation and exhaustion of CD8-EMRA cells through interferon signaling pathways. Conclusion: These findings indicate amino acid- and IDH2-related metabolism may cause the dysfunction of both naive and effector subsets by metabolic-epigenetic or non-epigenetic regulatory axes in PLWH.

Authors

Institutions

Publication Details

Journal
Infectious Diseases & Immunity
Published
2025-10-27
DOI
https://doi.org/10.1097/id9.0000000000000189
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Single-cell profiling reveals immunometabolic remodeling with T-cell dysfunction in HIV-1 infected people

Hui-Huang Huang, Xin Zhang, Fu‐Sheng Wang, Ming‐Ju Zhou et al.
Infectious Diseases & Immunity
Single-cell and spatial transcriptomics
article

Single-cell profiling reveals immunometabolic remodeling with T-cell dysfunction in HIV-1 infected people

Hui-Huang Huang, Xin Zhang, Fu‐Sheng Wang, Ming‐Ju Zhou, Zhen Cheng, Xing Fan, Yongbing Sun, Jin‐Wen Song, Chao Zhang, You-Yuan Wang, Jinfang Zhao, Yan-Mei Jiao, Tian-Jun Jiang
article en

Abstract

Abstract Background: Immunometabolism plays a vital role in the immunopathogenesis of people living with human immunodeficiency virus type 1 (HIV-1) (PLWH). However, the precise relationship between metabolic profiles and T-cell dysfunction in this population remains unclear. This study aims to investigate the metabolic reprogramming and underlying mechanisms contributing to T-cell dysfunction in PLWH. Methods: This study re-analyzed single-cell RNA sequencing data from the Genome Sequence Archive of the Beijing Institute of Genomics Data Center, Chinese Academy of Sciences. The dataset comprised samples from healthy donors (HD), HIV-1-infected treatment-naive patients (TN), and patients undergoing antiviral therapy. Various analytical approaches—including functional analysis, transcription factor analysis, network analysis, and enrichment analysis—were performed to assess T-cell functional and metabolic characteristics, as well as to identify potential targets within metabolic-epigenetic or non-epigenetic regulatory axes involved in T-cell dysfunction. Results: By analyzing the transcriptional profiles, a total of 58,752 CD4 + T cell subsets and 68,907 CD8 + T cell subsets were identified and annotated. Among these, the naive subset CD8-CCR7 was significantly reduced in TN patients compared to HD ( P < 0.05), whereas CD4-CCR7 showed a decreasing trend. Conversely, the effector subset CD8+ activated effector/memory T cells (CD8-EMRA) were significantly increased in TN patients ( P < 0.05), while cytolytic CD4+ T cells (CD4-CTL) displayed an increasing trend. ART did not effectively restore these alterations. Additionally, naive subsets and CD8-EMRA cells were associated with disease progression. Further analysis revealed that naive subsets exhibited hyper-activation and increased differentiation, whereas effector subsets showed excessive activation and a strong interferon (IFN) response in PLWH compared to HD ( P < 0.05). Intriguingly, we observed substantial metabolic alterations linked to immune dysfunction within the four T-cell subsets. Specifically, elevated levels of the methyltransferases absent, small, or homeotic-like 1 (ASH1L) and SET domain containing the 1B gene (SETD1B) may promote the differentiation and exhaustion of the CD4-CCR7 subset via the ASH1L/SETD1B-H3K4me3-FOXP1 axis. These enzymes are also associated with the exhaustion of CD8-CCR7 cells in TN patients through ASH1L/SETD1B-H3K4me3 axis. Additionally, isocitrate dehydrogenase 2 (IDH2)-mediated production of α-ketoglutarate (α-KG) may contribute to the dysfunction of CD8-CCR7 cells by activating janus kinase (JAK)-signal transducer and activator of transcription (STAT)3-dependent interferon signaling during HIV-1 infection. Conversely, increased activity of SET domain containing protein 2 methyltransferase is closely linked to hyperactivation, a strong type I interferon response, and cellular senescence in CD4-CTL cells from TN patients. Furthermore, heightened expression of solute carrier family 7 member 5 correlates with exhaustion of effector subsets in TN individuals. The IDH2-STAT1 axis may also play a crucial role in driving the over-activation and exhaustion of CD8-EMRA cells through interferon signaling pathways. Conclusion: These findings indicate amino acid- and IDH2-related metabolism may cause the dysfunction of both naive and effector subsets by metabolic-epigenetic or non-epigenetic regulatory axes in PLWH.

Infectious Diseases & Immunity
Peking University (CN), Chinese PLA General Hospital (CN), Peking University People's Hospital (CN)
Openalex Percentile: Top 71%
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.