Time and phenotype-dependent transcriptome analysis in AAV-TGFβ1 and Bleomycin-induced lung fibrosis models

Let-7 restrains an oncogenic epigenetic circuit in AT2 cells to prevent ectopic formation of fibrogenic transitional cell intermediates and pulmonary fibrosis

Analysis of lung alveolar type 2 (AT2) progenitor stem cells has highlighted fundamental mechanisms that direct their differentiation into alveolar type 1 cells (AT1s) in lung repair and disease. However, microRNA (miRNA) mediated post-transcriptional mechanisms which govern this nexus remain understudied. We show here that the let-7 miRNA family serves a homeostatic role in governance of AT2 quiescence, specifically by preventing the uncontrolled accumulation of AT2 transitional cells and by promoting AT1 differentiation to safeguard the lung from spontaneous alveolar destruction and fibrosis. Using mice and organoid models with genetic ablation of let-7a1/let-7f1/let-7d cluster (let-7afd) in AT2 cells, we demonstrate prevents AT1 differentiation and results in aberrant accumulation of AT2 transitional cells in progressive pulmonary fibrosis. Integration of enhanced AGO2 UV-crosslinking and immunoprecipitation sequencing (AGO2-eCLIP) with RNA-sequencing from AT2 cells uncovered the induction of direct targets of let-7 in an oncogene feed-forward regulatory network including BACH1/EZH2 which drives an aberrant fibrotic cascade. Additional analyses by CUT&RUN-sequencing revealed loss of let-7afd hampers AT1 differentiation by eliciting aberrant histone EZH2 methylation which prevents the exit of AT2 transitional cells into terminal AT1s. This study identifies let-7 as a key gatekeeper of post-transcriptional and epigenetic chromatin signals to prevent AT2-driven pulmonary fibrosis.

An agent-based modeling approach for lung fibrosis in response to COVID-19

The severity of the COVID-19 pandemic has created an emerging need to investigate the long-term effects of infection on patients. Many individuals are at risk of suffering pulmonary fibrosis due to the pathogenesis of lung injury and impairment in the healing mechanism. Fibroblasts are the central mediators of extracellular matrix (ECM) deposition during tissue regeneration, regulated by anti-inflammatory cytokines including transforming growth factor beta (TGF-β). The TGF-β-dependent accumulation of fibroblasts at the damaged site and excess fibrillar collagen deposition lead to fibrosis. We developed an open-source, multiscale tissue simulator to investigate the role of TGF-β sources in the progression of lung fibrosis after SARS-CoV-2 exposure, intracellular viral replication, infection of epithelial cells, and host immune response. Using the model, we predicted the dynamics of fibroblasts, TGF-β, and collagen deposition for 15 days post-infection in virtual lung tissue. Our results showed variation in collagen area fractions between 2% and 40% depending on the spatial behavior of the sources (stationary or mobile), the rate of activation of TGF-β, and the duration of TGF-β sources. We identified M2 macrophages as primary contributors to higher collagen area fraction. Our simulation results also predicted fibrotic outcomes even with lower collagen area fraction when spatially-localized latent TGF-β sources were active for longer times. We validated our model by comparing simulated dynamics for TGF-β, collagen area fraction, and macrophage cell population with independent experimental data from mouse models. Our results showed that partial removal of TGF-β sources changed the fibrotic patterns; in the presence of persistent TGF-β sources, partial removal of TGF-β from the ECM significantly increased collagen area fraction due to maintenance of chemotactic gradients driving fibroblast movement. The computational findings are consistent with independent experimental and clinical observations of collagen area fractions and cell population dynamics not used in developing the model. These critical insights into the activity of TGF-β sources may find applications in the current clinical trials targeting TGF-β for the resolution of lung fibrosis.

Transcriptomic and Proteomic Changes Driving Pulmonary Fibrosis Resolution in Young and Old Mice

Bleomycin-induced pulmonary fibrosis in mice mimics major hallmarks of idiopathic pulmonary fibrosis. Yet in this model, it spontaneously resolves over time. We studied molecular mechanisms of fibrosis resolution and lung repair, focusing on transcriptional and proteomic signatures and the effect of aging. Old mice showed incomplete and delayed lung function recovery 8 weeks after bleomycin instillation. This shift in structural and functional repair in old bleomycin-treated mice was reflected in a temporal shift in gene and protein expression. We reveal gene signatures and signaling pathways that underpin the lung repair process. Importantly, the downregulation of WNT, BMP, and TGFβ antagonists Frzb, Sfrp1, Dkk2, Grem1, Fst, Fstl1, and Inhba correlated with lung function improvement. Those genes constitute a network with functions in stem cell pathways, wound, and pulmonary healing. We suggest that insufficient and delayed downregulation of those antagonists during fibrosis resolution in old mice explains the impaired regenerative outcome. Together, we identified signaling pathway molecules with relevance to lung regeneration that should be tested in-depth experimentally as potential therapeutic targets for pulmonary fibrosis.

Dynamic atlas of immune cells reveals multiple functional features of macrophages associated with progression of pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial lung disease with a high mortality rate and unclarified aetiology. Immune response is elaborately regulated during the progression of IPF, but immune cells subsets are complicated which has not been detailed described during IPF progression. Therefore, in the current study, we sought to investigate the role of immune regulation by elaborately characterize the heterogeneous of immune cells during the progression of IPF. To this end, we performed single-cell profiling of lung immune cells isolated from four stages of bleomycin-induced pulmonary fibrosis-a classical mouse model that mimics human IPF. The results revealed distinct components of immune cells in different phases of pulmonary fibrosis and close communication between macrophages and other immune cells along with pulmonary fibrosis progression. Enriched signals of SPP1, CCL5 and CXCL2 were found between macrophages and other immune cells. The more detailed definition of the subpopulations of macrophages defined alveolar macrophages (AMs) and monocyte-derived macrophages (mo-Macs)-the two major types of primary lung macrophages-exhibited the highest heterogeneity and dynamic changes in expression of profibrotic genes during disease progression. Our analysis suggested that Gpnmb and Trem2 were both upregulated in macrophages and may play important roles in pulmonary fibrosis progression. Additionally, the metabolic status of AMs and mo-Macs varied with disease progression. In line with the published data on human IPF, macrophages in the mouse model shared some features regarding gene expression and metabolic status with that of macrophages in IPF patients. Our study provides new insights into the pathological features of profibrotic macrophages in the lung that will facilitate the identification of new targets for disease intervention and treatment of IPF.

ClearF++: Improved Supervised Feature Scoring Using Feature Clustering in Class-Wise Embedding and Reconstruction

Feature selection methods are essential for accurate disease classification and identifying informative biomarkers. While information-theoretic methods have been widely used, they often exhibit limitations such as high computational costs. Our previously proposed method, ClearF, addresses these issues by using reconstruction error from low-dimensional embeddings as a proxy for the entropy term in the mutual information. However, ClearF still has limitations, including a nontransparent bottleneck layer selection process, which can result in unstable feature selection. To address these limitations, we propose ClearF++, which simplifies the bottleneck layer selection and incorporates feature-wise clustering to enhance biomarker detection. We compare its performance with other commonly used methods such as MultiSURF and IFS, as well as ClearF, across multiple benchmark datasets. Our results demonstrate that ClearF++ consistently outperforms these methods in terms of prediction accuracy and stability, even with limited samples. We also observe that employing the Deep Embedded Clustering (DEC) algorithm for feature-wise clustering improves performance, indicating its suitability for handling complex data structures with limited samples. ClearF++ offers an improved biomarker prioritization approach with enhanced prediction performance and faster execution. Its stability and effectiveness with limited samples make it particularly valuable for biomedical data analysis.

Insights on the mechanism of bleomycin to induce lung injury and associated in vivo models: A review

Acute lung injury leads to the development of chronic conditions such as idiopathic pulmonary fibrosis (IPF), chronic obstructive pulmonary disease (COPD), asthma as well as alveolar sarcoma. Various investigations are being performed worldwide to understand the pathophysiology of these diseases, develop novel bioactive compounds and inhibitors to target the ailment. Generally, in vivo models are used to understand the disease outcome and therapeutic suppressing effects for which the animals are chemically or physically induced to mimic the onset of definite disease conditions. Amongst the chemical inducing agents, Bleomycin (BLM) is the most successful inducer. It is reported to target various receptors and activate inflammatory pathways, cellular apoptosis, epithelial mesenchymal transition leading to the release of inflammatory cytokines, and proteases. Mice is one of the most widely used animal model for BLM induced pulmonary associated studies apart from rat, rabbit, sheep, pig, and monkey. Although, there is considerable variation amongst in vivo studies for BLM induction which suggests a detailed study on the same to understand the mechanism of action of BLM at molecular level. Hence, herein we have reviewed various chemical inducers, mechanism of action of BLM in inducing lung injury in vivo, its advantages and disadvantages. Further, we have also discussed the rationale behind various in vivo models and recent development in BLM induction for various animals.

Changes in lung sialidases in male and female mice after bleomycin aspiration

Aim of the study: Sialidases, also called neuraminidases, are enzymes that cleave terminal sialic acids from glycoconjugates. In humans and mice, lung fibrosis is associated with desialylation of glycoconjugates and upregulation of sialidases. There are four mammalian sialidases, and it is unclear when the four mammalian sialidases are elevated over the course of inflammatory and fibrotic responses, whether tissue resident and inflammatory cells express different sialidases, and if sialidases are differentially expressed in male and females. Materials and Methods: To determine the time course of sialidase expression and the identity of sialidase expressing cells, we used the bleomycin model of pulmonary fibrosis in mice to examine levels of sialidases during inflammation (days 3 - 10) and fibrosis (days 10 - 21). Results: Bleomycin aspiration increased sialidase NEU1 at days 14 and 21 in male mice and day 10 in female mice. NEU2 levels increased at day 7 in male and day 10 in female mice. NEU3 appears to have a biphasic response in male mice with increased levels at day 7 and then at days 14 and 21, whereas in female mice NEU3 levels increased over 21 days. In control mice, the sialidases were mainly expressed by EpCAM positive epithelial cells, but after bleomycin, epithelial cells, CD45 positive immune cells, and alveolar cells expressed NEU1, NEU2, and NEU3. Sialidase expression was higher in male compared to female mice. There was little expression of NEU4 in murine lung tissue. Conclusions: These results suggest that sialidases are dynamically expressed following bleomycin, that sialidases are differentially expressed in male and females, and that of the four sialidases only NEU3 upregulation is associated with fibrosis in both male and female mice.