Adult stem cells are essential for tissue maintenance and repair. Although genetic pathways for controlling adult stem cells are extensively investigated in various tissues, much less is known about how mechanosensing could regulate adult stem cells and tissue growth. Here, we demonstrate that shear stress sensing regulates intestine stem cell proliferation and epithelial cell number in adult Drosophila . Ca ²⁺ imaging in ex vivo midguts shows that shear stress, but not other mechanical forces, specifically activates enteroendocrine cells among all epithelial cell types. This activation is mediated by transient receptor potential A1 (TrpA1), a Ca ²⁺ -permeable channel expressed in enteroendocrine cells. Furthermore, specific disruption of shear stress, but not chemical, sensitivity of TrpA1 markedly reduces proliferation of intestinal stem cells and midgut cell number. Therefore, we propose that shear stress may act as a natural mechanical stimulation to activate TrpA1 in enteroendocrine cells, which, in turn, regulates intestine stem cell behavior.

Objectives: Alzheimer's disease (AD) is a well‐known neurodegenerative disease, of which the hallmark is the disposition of β‐amyloid (Aβ) in the form of plaque in the brain. Neprilysin (NEP) is the major enzyme to degrade Aβ and prevent accumulation of Aβ. The present study was undertaken to elucidate the correlation between the NEP gene polymorphisms and AD in Chinese Tibetan population.Methods: Ninety‐nine sporadic AD Tibetan patients and 113 healthy Tibetan controls were enrolled in this study. The genotype frequencies and allele frequencies of multiple NEP gene loci were analyzed using the case–control association analysis.Results: No significant correlation was found between polymorphisms of NEP gene loci (rs9829757, rs1816558, rs6776185, rs3736187, rs701109, rs989692) and the occurrence of AD in Tibetan population. However, allele C of NEP gene locus (rs701109) and allele T of gene locus (rs3736187) were possible risk factors of male AD patients in Tibetan population.Conclusions: NEP gene loci (rs701109, rs989692, rs9829757, rs3736187, rs1816558, rs6776185) were polymorphic in Tibetan population. No difference was found between these loci but for that male gender combined with allele C of NEP gene locus (rs701109) and T of gene locus (rs3736187) might be risk factors for AD in Tibet.

Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease characterized by repetitive alveolar injuries with excessive deposition of extracellular matrix (ECM) proteins. A crucial need in understanding IPF pathogenesis is identifying cell types associated with histopathological regions, particularly local fibrosis centers known as fibroblast foci. To address this, we integrated published spatial transcriptomics and single-cell RNA sequencing (scRNA-seq) transcriptomics and adopted the Query method and the Overlap method to determine cell type enrichments in histopathological regions. Distinct fibroblast cell types are highly associated with fibroblast foci, and transitional alveolar type 2 and aberrant KRT5-/KRT17+ (KRT: keratin) epithelial cells are associated with morphologically normal alveoli in human IPF lungs. Furthermore, we employed laser capture microdissection-directed mass spectrometry to profile proteins. By comparing with another published similar dataset, common differentially expressed proteins and enriched pathways related to ECM structure organization and collagen processing were identified in fibroblast foci. Importantly, cell type enrichment results from innovative spatial proteomics and scRNA-seq data integration accord with those from spatial transcriptomics and scRNA-seq data integration, supporting the capability and versatility of the entire approach. In summary, we integrated spatial multi-omics with scRNA-seq data to identify disease-associated cell types and potential targets for novel therapies in IPF intervention. The approach can be further applied to other disease areas characterized by spatial heterogeneity.

Understanding the heterogeneity of Rheumatoid Arthritis (RA) and identifying therapeutic targets remain challenging using traditional bulk transcriptomics alone, as it lacks the spatial and protein-level resolution needed to fully capture disease and tissue complexities. In this study, we applied Laser Capture Microdissection (LCM) coupled with mass spectrometry-based proteomics to analyze histopathological niches of the RA synovium, enabling the identification of protein expression profiles of the diseased synovial lining and sublining microenvironments compared to their healthy counterparts. In this respect, key pathogenetic RA proteins like membrane proteins (TYROBP, AOC3, SLC16A3, TCIRG1, and NCEH1), and extracellular matrix (ECM) proteins (PLOD2, OGN, and LUM) showed different expression patterns in diseased synovium compartments. To enhance our understanding of cellular dynamics within the dissected regions, we further integrated the proteomic dataset with single-cell RNA sequencing (scRNA-seq), and deduced cell type enrichment, including T cells, fibroblasts, NK cells, myeloid cells, B cells, and synovial endothelial cells. By combining high-resolution spatial proteomics and transcriptomic analyses, we provide novel insights into the molecular mechanisms driving RA, and highlight potential protein targets for therapeutic intervention. This integrative approach offers a more comprehensive view of RA synovial pathology, and mitigates the limitations of traditional bulk transcriptomics in target discovery.

Crohn’s disease (CD) is a subtype of inflammatory bowel disease (IBD) characterized by transmural disease. The concept of transmural healing (TH) has been proposed as an indicator of deep clinical remission of CD and as a predictor of favorable treatment endpoints. Understanding the pathophysiology involved in transmural disease is critical to achieving these endpoints. However, most studies have focused on the intestinal mucosa, overlooking the contribution of the intestinal wall in Crohn’s disease. Multi-omics approaches have provided new avenues for exploring the pathogenesis of Crohn’s disease and identifying potential biomarkers. We aimed to use transcriptomic and proteomic technologies to compare immune and mesenchymal cell profiles and pathways in the mucosal and submucosa/wall compartments to better understand chronic refractory disease elements to achieve transmural healing. The results revealed similarities and differences in gene and protein expression profiles, metabolic mechanisms, and immune and non-immune pathways between these two compartments. Additionally, the identification of protein isoforms highlights the complex molecular mechanisms underlying this disease, such as decreased RTN4 isoforms (RTN4B2 and RTN4C) in the submucosa/wall, which may be related to the dysregulation of enteric neural processes. These findings have the potential to inform the development of novel therapeutic strategies to achieve TH.

Rheumatoid arthritis (RA) is a systemic autoimmune and inflammatory disease. Plasma biomarkers are critical for understanding disease mechanisms, treatment effects, and diagnosis. Mass spectrometry-based proteomics is a powerful tool for unbiased biomarker discovery. However, plasma proteomics is significantly hampered by signal interference from high-abundance proteins, low overall protein coverage, and high levels of missing data from data-dependent acquisition (DDA). To achieve quantitative proteomics analysis for plasma samples with a balance of throughput, performance, and cost, we developed a workflow incorporating plate-based high abundance protein depletion and sample preparation, comprehensive peptide spectral library building, and data-independent acquisition (DIA) SWATH mass spectrometry-based methodology. In this study, we analyzed plasma samples from both RA patients and healthy donors. The results showed that the new workflow performance exceeded that of the current state-of-the-art depletion-based plasma proteomic platforms in terms of both data quality and proteome coverage. Proteins from biological processes related to the activation of systemic inflammation, suppression of platelet function, and loss of muscle mass were enriched and differentially expressed in RA. Some plasma proteins, particularly acute-phase reactant proteins, showed great power to distinguish between RA patients and healthy donors. Moreover, protein isoforms in the plasma were also analyzed, providing even deeper proteome coverage. This workflow can serve as a basis for further application in discovering plasma biomarkers of other diseases.