Non-Invasive Multi-Dimensional Two-Photon Microscopy enables optical fingerprinting (TPOF) of immune cells

Label-free multiphoton microscopy enables histopathological assessment of colorectal liver metastases and supports automated classification of neoplastic tissue

As the state of resection margins is an important prognostic factor after extirpation of colorectal liver metastases, surgeons aim to obtain negative margins, sometimes elaborated by resections of the positive resection plane after intraoperative frozen sections. However, this is time consuming and results sometimes remain unclear during surgery. Label-free multimodal multiphoton microscopy (MPM) is an optical technique that retrieves morpho-chemical information avoiding all staining and that can potentially be performed in real-time. Here, we investigated colorectal liver metastases and hepatic tissue using a combination of three endogenous nonlinear signals, namely: coherent anti-Stokes Raman scattering (CARS) to visualize lipids, two-photon excited fluorescence (TPEF) to visualize cellular patterns, and second harmonic generation (SHG) to visualize collagen fibers. We acquired and analyzed over forty thousand MPM images of metastatic and normal liver tissue of 106 patients. The morphological information with biochemical specificity produced by MPM allowed discriminating normal liver from metastatic tissue and discerning the tumor borders on cryosections as well as formalin-fixed bulk tissue. Furthermore, automated tissue type classification with a correct rate close to 95% was possible using a simple approach based on discriminant analysis of texture parameters. Therefore, MPM has the potential to increase the precision of resection margins in hepatic surgery of metastases without prolonging surgical intervention.

Touch-free optical technologies to streamline the production of T cell therapies

Currently approved adoptive T cell therapy relies on autologous (obtained from the same patient) T cells, which often suffer from poor quality that diminishes treatment efficacy. Due to the heterogeneous nature of T cell quality between and within patients, significant efforts are aimed at optimizing cell manipulation and growth conditions for potent T cell products. We believe that touch-free imaging and sensing technologies are critical to monitor single-cell features during T cell manufacturing to ensure consistent and optimally timed methods for cell manipulation and growth. Here, we discuss emerging label-free optical imaging and sensing methods, along with machine learning techniques that could enable in-line feedback to optimize T cell quality at multiple stages during manufacturing. These methods have the potential to streamline current workflow, accelerate the manufacture of safe high-quality T cell therapies, and improve our understanding of the dynamic, heterogeneous processes of T cell manufacturing.

Label-free analysis of inflammatory tissue remodeling in murine lung tissue based on multiphoton microscopy, Raman spectroscopy and machine learning

Inflammatory fibrotic tissue remodeling can lead to severe morbidity. Histopathology grading requires extraction of biopsies and elaborate tissue processing. Label-free optical technologies can provide diagnostic readout without preparation and artificial stainings and show potential for in vivo applications. Here, we present an integration of Raman spectroscopy (RS) and multiphoton microscopy for joint investigation of the bio-chemical composition and morphological features related to cellular components and connective tissue. Both modalities show that collagen signatures were significantly increased in a murine fibrosis model. Furthermore, autofluorescence signatures assigned to immune cells show high correlation with disease severity. RS indicates increased levels of elastin and lipids. Further, we investigated the effect of joint data sets on prediction performance in machine learning models. Although binary classification did not benefit from adding more features, multi-class classification was improved by integrated data sets.

Natural NADH and FAD Autofluorescence as Label-Free Biomarkers for Discriminating Subtypes and Functional States of Immune Cells

Immune cell activity is a major factor for disease progression in inflammatory bowel diseases (IBD). Classifying the type and functional state of immune cells is therefore crucial in clinical diagnostics of IBD. Label-free optical technologies exploiting NADH and FAD autofluorescence, such as multiphoton microscopy, have been used to describe tissue morphology in healthy and inflamed colon samples. Nevertheless, a strategy for the identification of single immune cell subtypes within the tissue is yet to be developed. This work aims to initiate an understanding of autofluorescence changes depending on immune cell type and activation state. For this, NADH and FAD autofluorescence signals of different murine immune cell subtypes under native conditions, as well as upon in vitro stimulation and cell death, have been evaluated. Autofluorescence was assessed using flow cytometry and multiphoton microscopy. Our results reveal significantly increased NADH and FAD signals in innate immune cells compared to adaptive immune cells. This allowed identification of relative amounts of neutrophils and CD4+ T cells in mixed cell suspensions, by using NADH signals as a differentiation marker. Furthermore, in vitro stimulation significantly increased NADH and FAD autofluorescence in adaptive immune cells and macrophages. Cell death induced a significant drop in NADH autofluorescence, while FAD signals were hardly affected. Taken together, these results demonstrate the value of autofluorescence as a tool to characterize immune cells in different functional states, paving the way to the label-free clinical classification of IBD in the future.

Autofluorescence multiphoton microscopy for visualization of tissue morphology and cellular dynamics in murine and human airways

The basic understanding of inflammatory airway diseases greatly benefits from imaging the cellular dynamics of immune cells. Current imaging approaches focus on labeling specific cells to follow their dynamics but fail to visualize the surrounding tissue. To overcome this problem, we evaluated autofluorescence multiphoton microscopy for following the motion and interaction of cells in the airways in the context of tissue morphology. Freshly isolated murine tracheae from healthy mice and mice with experimental allergic airway inflammation were examined by autofluorescence multiphoton microscopy. In addition, fluorescently labeled ovalbumin and fluorophore-labeled antibodies were applied to visualize antigen uptake and to identify specific cell populations, respectively. The trachea in living mice was imaged to verify that the ex vivo preparation reflects the in vivo situation. Autofluorescence multiphoton microscopy was also tested to examine human tissue from patients in short-term tissue culture. Using autofluorescence, the epithelium, underlying cells, and fibers of the connective tissue, as well as blood vessels, were identified in isolated tracheae. Similar structures were visualized in living mice and in the human airway tissue. In explanted murine airways, mobile cells were localized within the tissue and we could follow their migration, interactions between individual cells, and their phagocytic activity. During allergic airway inflammation, increased number of eosinophil and neutrophil granulocytes were detected that moved within the connective tissue and immediately below the epithelium without damaging the epithelial cells or connective tissues. Contacts between granulocytes were transient lasting 3 min on average. Unexpectedly, prolonged interactions between granulocytes and antigen-uptaking cells were observed lasting for an average of 13 min. Our results indicate that autofluorescence-based imaging can detect previously unknown immune cell interactions in the airways. The method also holds the potential to be used during diagnostic procedures in humans if integrated into a bronchoscope.