In order to improve clinical care for chronic lung diseases, particularly personalised therapies, model systems that capture the complex cellular ecosystem of lung tissue, where diverse immune cell populations interact with stromal cells and targets such as cancer cells, viruses, or bacteria within the alveolar architecture [1, 2], are eagerly awaited. Human tissue-based approaches such as precision-cut lung slices (PCLS) from surgically resected tumour lesions retain key features of the lung tissue microenvironment, including its architecture, mechanical properties, and diverse resident cell populations [3–5] making them suitable to test novel therapeutic agents [2, 6–8]. Further development of such technologies may contribute to the advancement of understanding the underlying disease mechanisms and improving therapeutic options for the treatment of chronic lung disease patients.

Osteogenesis imperfecta (OI) and Ehlers–Danlos syndrome (EDS) are inherited connective tissue disorders caused by diverse genetic defects, many of which affect collagen biosynthesis. However, the identified genetic variants do not always fully explain the clinical heterogeneity observed in patients, highlighting the need for advanced models and imaging techniques to assess collagen structure and fibroblast behavior at the microscopic level. In this study, we employed 5-week three-dimensional (3D) dermal fibroblast cultures derived from patients with haploinsufficient (HI) and dominant-negative (DN) OI, EDS, and healthy controls. Using label-free higher harmonic generation microscopy (HHGM), we visualized and quantified secreted collagen fibers and fibroblast morphology in situ. We analyzed fibroblast 3D orientation, collagen fiber diameter, collagen amount per cell, and the spatial alignment between fibroblasts and collagen fibers. HI OI fibroblasts secreted significantly less collagen than both control and EDS-derived cells, while EDS samples exhibited thinner collagen fibers compared to controls. Across all groups, collagen fiber orientation was strongly correlated with fibroblast alignment, in line with the role of fibroblasts in matrix organization. In healthy controls and HI OI samples, we observed a depth-dependent, counterclockwise rotation in fibroblast orientation from the culture bottom to the surface—a pattern that was less prominent in DN OI and EDS samples, potentially reflecting altered matrix guidance in diseased tissues. Overall, the quantity and quality of collagen, as well as fibroblast morphology and organization, were markedly altered in the OI and EDS model systems. These alterations may mirror tissue-level manifestations of the diseases, demonstrating the physiological relevance of patient-derived 3D fibroblast models for OI and EDS, as well as the power of harmonic generation microscopy in probing the cellular and extracellular consequences of disease-related gene defects in collagen or its biosynthetic pathways. Extensions of this methodological approach provide a way towards deeper understanding of tissue-level manifestations of collagen dysregulation in connective tissue disorders.

Current methods to study patient-specific disease processes rely on a variety of ex vivo techniques, like static histological analysis or tissue cultures with static endpoints, that provide limited insight into how the tissue microenvironment behaves in real time. Yet, dynamic features, such as immune cell infiltration and extracellular matrix remodeling, are crucial predictors of therapy response, be it in cancer or fibrotic diseases. At present, no label-free and clinically viable assay exists that can capture these behaviors in live human tissue. We propose an innovative platform that provides metrics on cell density, cell dynamics and microstructure of the extracellular matrix for the characterization of treatment response. The platform integrates fully label-free, time-lapse 3D higher harmonic generation microscopy to visualize both cells and the extracellular matrix, and a stage-top incubator in which tissue slices are cultured during time-lapse measurements. Here, we demonstrate the viability of the tissue slices during imaging and the ability to resolve endogenous immune cell and seeded monocyte dynamics, in the context of healthy alveolar structures. Time-lapse dynamics were recorded in 3D for up to 59 hours during a total culture period of 90 hours, and the migration of endogenous smaller cells and seeded monocytes was tracked and analyzed. This platform is relatively simple to operate and has potential for studies on drug development and patient-specific treatment response prediction in the context of human lung disease.