Multi-pronged approach to human mesenchymal stromal cells senescence quantification with a focus on label-free methods.

Human mesenchymal stromal cells (hMSCs) have demonstrated, in various preclinical settings, consistent ability in promoting tissue healing and improving outcomes in animal disease models. However, translation from the preclinical model into clinical practice has proven to be considerably more difficult. One key challenge being the inability to perform in situ assessment of the hMSCs in continuous culture, where the accumulation of the senescent cells impairs the culture's viability, differentiation potential and ultimately leads to reduced therapeutic efficacies. Histochemical [Formula: see text]-galactosidase staining is the current standard for measuring hMSC senescence, but this method is destructive and not label-free. In this study, we have investigated alternatives in quantification of hMSCs senescence, which included flow cytometry methods that are based on a combination of cell size measurements and fluorescence detection of SA-[Formula: see text]-galactosidase activity using the fluorogenic substrate, C[Formula: see text]FDG; and autofluorescence methods that measure fluorescence output from endogenous fluorophores including lipopigments. For identification of senescent cells in the hMSC batches produced, the non-destructive and label-free methods could be a better way forward as they involve minimum manipulations of the cells of interest, increasing the final output of the therapeutic-grade hMSC cultures. In this work, we have grown hMSC cultures over a period of 7 months and compared early and senescent hMSC passages using the advanced flow cytometry and autofluorescence methods, which were benchmarked with the current standard in [Formula: see text]-galactosidase staining. Both the advanced methods demonstrated statistically significant values, (r = 0.76, p [Formula: see text] 0.001 for the fluorogenic C[Formula: see text]FDG method, and r = 0.72, p [Formula: see text] 0.05 for the forward scatter method), and good fold difference ranges (1.120-4.436 for total autofluorescence mean and 1.082-6.362 for lipopigment autofluorescence mean) between early and senescent passage hMSCs. Our autofluroescence imaging and spectra decomposition platform offers additional benefit in label-free characterisation of senescent hMSC cells and could be further developed for adoption for future in situ cellular senescence evaluation by the cell manufacturers.

Autofluorescence spectroscopy in redox monitoring across cell confluencies.

Patient-specific therapies require that cells be manufactured in multiple batches of small volumes, making it a challenge for conventional modes of quality control. The added complexity of inherent variability (even within batches) necessitates constant monitoring to ensure comparable end products. Hence, it is critical that new non-destructive modalities of cell monitoring be developed. Here, we study, for the first time, the use of optical spectroscopy in the determination of cellular redox across cell confluencies by exploiting the autofluorescence properties of molecules found natively within cells. This was achieved through a simple retrofitting of a standard inverted fluorescence microscope with a spectrometer output and an appropriate fluorescence filter cube. Through spectral decomposition on the acquired autofluorescence spectra, we are able to further discern the relative contributions of the different molecules, namely flavin adenine dinucleotide (FAD) and reduced nicotinamide adenine dinucleotide (NADH). This is then quantifiable as redox ratios (RR) that represent the extent of oxidation to reduction based upon the optically measured quantities of FAD and NADH. Results show that RR decreases with increasing cell confluency, which we attribute to several inter-related cellular processes. We validated the relationship between RR, metabolism and cell confluency through bio-chemical and viability assays. Live-dead and DNA damage studies were further conducted to substantiate that our measurement process had negligible effects on the cells. In this study, we demonstrate that autofluorescence spectroscopy-derived RR can serve as a rapid, non-destructive and label-free surrogate to cell metabolism measurements. This was further used to establish a relationship between cell metabolism and cellular redox across cell confluencies, and could potentially be employed as an indicator of quality in cell therapy manufacturing.

Identification of senescent cells in multipotent mesenchymal stromal cell cultures: Current methods and future directions.

Regardless of their tissue of origin, multipotent mesenchymal stromal cells (MSCs) are commonly expanded in vitro for several population doublings to achieve a sufficient number of cells for therapy. Prolonged MSC expansion has been shown to result in phenotypical, morphological and gene expression changes in MSCs, which ultimately lead to the state of senescence. The presence of senescent cells in therapeutic MSC batches is undesirable because it reduces their viability, differentiation potential and trophic capabilities. Additionally, senescent cells acquire senescence-activated secretory phenotype, which may not only induce apoptosis in the neighboring host cells following MSC transplantation, but also trigger local inflammatory reactions. This review outlines the current and promising new methodologies for the identification of senescent cells in MSC cultures, with a particular emphasis on non-destructive and label-free methodologies. Technologies allowing identification of individual senescent cells, based on new surface markers, offer potential advantage for targeted senescent cell removal using new-generation senolytic agents, and subsequent production of therapeutic MSC batches fully devoid of senescent cells. Methods or a combination of methods that are non-destructive and label-free, for example, involving cell size and spectroscopic measurements, could be the best way forward because they do not modify the cells of interest, thus maximizing the final output of therapeutic-grade MSC cultures. The further incorporation of machine learning methods has also recently shown promise in facilitating, automating and enhancing the analysis of these measured data.

Single-cell analysis of CD4+ T-cell differentiation reveals three major cell states and progressive acceleration of proliferation.

BACKGROUND: Differentiation of lymphocytes is frequently accompanied by cell cycle changes, interplay that is of central importance for immunity but is still incompletely understood. Here, we interrogate and quantitatively model how proliferation is linked to differentiation in CD4+ T cells. RESULTS: We perform ex vivo single-cell RNA-sequencing of CD4+ T cells during a mouse model of infection that elicits a type 2 immune response and infer that the differentiated, cytokine-producing cells cycle faster than early activated precursor cells. To dissect this phenomenon quantitatively, we determine expression profiles across consecutive generations of differentiated and undifferentiated cells during Th2 polarization in vitro. We predict three discrete cell states, which we verify by single-cell quantitative PCR. Based on these three states, we extract rates of death, division and differentiation with a branching state Markov model to describe the cell population dynamics. From this multi-scale modelling, we infer a significant acceleration in proliferation from the intermediate activated cell state to the mature cytokine-secreting effector state. We confirm this acceleration both by live imaging of single Th2 cells and in an ex vivo Th1 malaria model by single-cell RNA-sequencing. CONCLUSION: The link between cytokine secretion and proliferation rate holds both in Th1 and Th2 cells in vivo and in vitro, indicating that this is likely a general phenomenon in adaptive immunity.