Chronic lung allograft dysfunction (CLAD) is the leading cause of death in lung transplant recipients. CLAD is characterized clinically by a persistent decline in pulmonary function and histologically by the development of airway-centered fibrosis known as bronchiolitis obliterans. There are no approved therapies to treat CLAD, and the mechanisms underlying its development remain poorly understood. We performed single-cell RNA-Seq and spatial transcriptomic analysis of explanted tissues from human lung recipients with CLAD, and we performed independent validation studies to identify an important role of Janus kinase–signal transducer and activator of transcription (JAK-STAT) signaling in airway epithelial cells that contributes to airway-specific alloimmune injury. Specifically, we established that activation of JAK-STAT signaling leads to upregulation of major histocompatibility complex 1 (MHC-I) in airway basal cells, an important airway epithelial progenitor population, which leads to cytotoxic T cell–mediated basal cell death. This study provides mechanistic insight into the cell-to-cell interactions driving airway-centric alloimmune injury in CLAD, suggesting a potentially novel therapeutic strategy for CLAD prevention or treatment.

A promising strategy to cure HIV infected individuals is to use latency reversing agents (LRAs) to reactivate latent viruses, followed by host clearance of infected reservoir cells. However, reactivation of latent proviruses within infected cells is heterogeneous and often incomplete. This fact limits strategies to cure HIV which may require complete elimination of viable virus from all cellular reservoirs. For this reason, understanding the mechanism(s) of reactivation of HIV within cellular reservoirs is critical to achieve therapeutic success. Methodologies enabling temporal tracking of single cells as they reactivate followed by sorting and molecular analysis of those cells are urgently needed. To this end, microraft arrays were adapted to image T-lymphocytes expressing mCherry under the control of the HIV long terminal repeat (LTR) promoter, in response to the application of various LRAs (prostratin, iBET151, and SAHA). In response to prostratin, iBET151, and SAHA, 30.5 %, 11.2 %, and 12.1 % percentage of cells respectively, reactivated similar to that observed in other experimental systems. The arrays enabled large numbers of single cells (>25,000) to be imaged over time. mCherry fluorescence quantification identified cell subpopulations with differing reactivation kinetics. Significant heterogeneity was observed at the single cell level between different LRAs in terms of time to reactivation, rate of mCherry fluorescence increase upon reactivation, and peak fluorescence attained. In response to prostratin, subpopulations of T lymphocytes with slow and fast reactivation kinetics were identified. Single T-lymphocytes that were either fast or slow reactivators were sorted, and single-cell RNA-sequencing was performed. Different genes associated with inflammation, immune activation, and cellular and viral transcription factors were found. These results advance our conceptual understanding of HIV reactivation dynamics at the single-cell level toward a cure for HIV.

A promising strategy to cure HIV‐infected individuals is to use latency reversing agents (LRAs) to reactivate latent viruses, followed by host clearance of infected reservoir cells. However, reactivation of latent proviruses within infected cells is heterogeneous and often incomplete. This fact limits strategies to cure HIV which may require complete elimination of viable virus from all cellular reservoirs. For this reason, understanding the mechanism(s) of reactivation of HIV within cellular reservoirs is critical to achieve therapeutic success. Methodologies enabling temporal tracking of single cells as they reactivate followed by sorting and molecular analysis of those cells are urgently needed. To this end, microraft arrays were adapted to image T‐lymphocytes expressing mCherry under the control of the HIV long terminal repeat (LTR) promoter, in response to the application of LRAs (prostratin, iBET151, and SAHA). In response to prostratin, iBET151, and SAHA, 30.5%, 11.2%, and 12.1% percentage of cells, respectively. The arrays enabled large numbers of single cells (>25,000) to be imaged over time. mCherry fluorescence quantification identified cell subpopulations with differing reactivation kinetics. Significant heterogeneity was observed at the single‐cell level between different LRAs in terms of time to reactivation, rate of mCherry fluorescence increase upon reactivation, and peak fluorescence attained. In response to prostratin, subpopulations of T lymphocytes with slow and fast reactivation kinetics were identified. Single T‐lymphocytes that were either fast or slow reactivators were sorted, and single‐cell RNA‐sequencing was performed. Different genes associated with inflammation, immune activation, and cellular and viral transcription factors were found.