Proximal immune-epithelial progenitor interactions drive chronic tissue sequelae post COVID-19.

The long-term physiological consequences of SARS-CoV-2, termed Post-Acute Sequelae of COVID-19 (PASC), are rapidly evolving into a major public health concern. The underlying cellular and molecular etiology remain poorly defined but growing evidence links PASC to abnormal immune responses and/or poor organ recovery post-infection. Yet, the precise mechanisms driving non-resolving inflammation and impaired tissue repair in the context of PASC remain unclear. With insights from three independent clinical cohorts of PASC patients with abnormal lung function and/or viral infection-mediated pulmonary fibrosis, we established a clinically relevant mouse model of post-viral lung sequelae to investigate the pathophysiology of respiratory PASC. By employing a combination of spatial transcriptomics and imaging, we identified dysregulated proximal interactions between immune cells and epithelial progenitors unique to the fibroproliferation in respiratory PASC but not acute COVID-19 or idiopathic pulmonary fibrosis (IPF). Specifically, we found a central role for lung-resident CD8+ T cell-macrophage interactions in maintaining Krt8hi transitional and ectopic Krt5+ basal cell progenitors, thus impairing alveolar regeneration and driving fibrotic sequelae after acute viral pneumonia. Mechanistically, CD8+ T cell derived IFN-γ and TNF stimulated lung macrophages to chronically release IL-1ß, resulting in the abnormal accumulation of dysplastic epithelial progenitors and fibrosis. Notably, therapeutic neutralization of IFN-γ and TNF, or IL-1ß after the resolution of acute infection resulted in markedly improved alveolar regeneration and restoration of pulmonary function. Together, our findings implicate a dysregulated immune-epithelial progenitor niche in driving respiratory PASC. Moreover, in contrast to other approaches requiring early intervention, we highlight therapeutic strategies to rescue fibrotic disease in the aftermath of respiratory viral infections, addressing the current unmet need in the clinical management of PASC and post-viral disease.

Proximal immune-epithelial progenitor interactions drive chronic tissue sequelae post COVID-19.

The long-term physiological consequences of SARS-CoV-2, termed Post-Acute Sequelae of COVID-19 (PASC), are rapidly evolving into a major public health concern. The underlying cellular and molecular etiology remain poorly defined but growing evidence links PASC to abnormal immune responses and/or poor organ recovery post-infection. Yet, the precise mechanisms driving non-resolving inflammation and impaired tissue repair in the context of PASC remain unclear. With insights from three independent clinical cohorts of PASC patients with abnormal lung function and/or viral infection-mediated pulmonary fibrosis, we established a clinically relevant mouse model of post-viral lung sequelae to investigate the pathophysiology of respiratory PASC. By employing a combination of spatial transcriptomics and imaging, we identified dysregulated proximal interactions between immune cells and epithelial progenitors unique to the fibroproliferation in respiratory PASC but not acute COVID-19 or idiopathic pulmonary fibrosis (IPF). Specifically, we found a central role for lung-resident CD8+ T cell-macrophage interactions in maintaining Krt8hi transitional and ectopic Krt5+ basal cell progenitors, thus impairing alveolar regeneration and driving fibrotic sequelae after acute viral pneumonia. Mechanistically, CD8+ T cell derived IFN-γ and TNF stimulated lung macrophages to chronically release IL-1ß, resulting in the abnormal accumulation of dysplastic epithelial progenitors and fibrosis. Notably, therapeutic neutralization of IFN-γ and TNF, or IL-1ß after the resolution of acute infection resulted in markedly improved alveolar regeneration and restoration of pulmonary function. Together, our findings implicate a dysregulated immune-epithelial progenitor niche in driving respiratory PASC. Moreover, in contrast to other approaches requiring early intervention, we highlight therapeutic strategies to rescue fibrotic disease in the aftermath of respiratory viral infections, addressing the current unmet need in the clinical management of PASC and post-viral disease.

Ectopic Tcf1 expression instills a stem-like program in exhausted CD8+ T cells to enhance viral and tumor immunity.

Exhausted CD8+ T (Tex) cells are dysfunctional due to persistent antigen exposure in chronic viral infection and tumor contexts. A stem cell-like Tex (Tex-stem) subset can self-renew and differentiate into terminally exhausted (Tex-term) cells. Here, we show that ectopic Tcf1 expression potently promoted the generation of Tex-stem cells in both a chronic viral infection and preclinical tumor models. Tcf1 overexpression diminished coinhibitory receptor expression and enhanced polycytokine-producing capacity while retaining a heightened responses to checkpoint blockade, leading to enhanced viral and tumor control. Mechanistically, ectopically expressed Tcf1 exploited existing and novel chromatin accessible sites as transcriptional enhancers or repressors and modulated the transcriptome by enforcing pre-existing expression patterns in Tex-stem cells, such as enhanced suppression of Blimp1 and Bim and acquisition of new downstream genes, including Mx1, Tox2, and Runx3. These findings reveal a pronounced impact of ectopic Tcf1 expression on Tex functional restoration and highlight the therapeutic potential of harnessing Tcf1-enforced transcriptional programs.

High-dimensional genomic data bias correction and data integration using MANCIE.

High-dimensional genomic data analysis is challenging due to noises and biases in high-throughput experiments. We present a computational method matrix analysis and normalization by concordant information enhancement (MANCIE) for bias correction and data integration of distinct genomic profiles on the same samples. MANCIE uses a Bayesian-supported principal component analysis-based approach to adjust the data so as to achieve better consistency between sample-wise distances in the different profiles. MANCIE can improve tissue-specific clustering in ENCODE data, prognostic prediction in Molecular Taxonomy of Breast Cancer International Consortium and The Cancer Genome Atlas data, copy number and expression agreement in Cancer Cell Line Encyclopedia data, and has broad applications in cross-platform, high-dimensional data integration.

Refined DNase-seq protocol and data analysis reveals intrinsic bias in transcription factor footprint identification.

Sequencing of DNase I hypersensitive sites (DNase-seq) is a powerful technique for identifying cis-regulatory elements across the genome. We studied the key experimental parameters to optimize performance of DNase-seq. Sequencing short fragments of 50-100 base pairs (bp) that accumulate in long internucleosome linker regions was more efficient for identifying transcription factor binding sites compared to sequencing longer fragments. We also assessed the potential of DNase-seq to predict transcription factor occupancy via generation of nucleotide-resolution transcription factor footprints. In modeling the sequence-specific DNase I cutting bias, we found a strong effect that varied over more than two orders of magnitude. This indicates that the nucleotide-resolution cleavage patterns at many transcription factor binding sites are derived from intrinsic DNase I cleavage bias rather than from specific protein-DNA interactions. In contrast, quantitative comparison of DNase I hypersensitivity between states can predict transcription factor occupancy associated with particular biological perturbations.