scholarly journals Biomolecular phenotyping and heterogeneity assessment of mesenchymal stromal cells using label-free Raman spectroscopy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
R. A. Rocha ◽  
J. M. Fox ◽  
P. G. Genever ◽  
Y. Hancock

AbstractEasy, quantitative measures of biomolecular heterogeneity and high-stratified phenotyping are needed to identify and characterise complex disease processes at the single-cell level, as well as to predict cell fate. Here, we demonstrate how Raman spectroscopy can be used in the difficult-to-assess case of clonal, bone-derived mesenchymal stromal cells (MSCs) to identify MSC lines and group these according to biological function (e.g., differentiation capacity). Biomolecular stratification is achieved using high-precision measures obtained from representative statistical sampling that also enable quantified heterogeneity assessment. Application to primary MSCs and human dermal fibroblasts shows use of these measures as a label-free assay to classify cell sub-types within complex heterogeneous cell populations, thus demonstrating the potential for therapeutic translation, and broad application to the phenotypic characterisation of other cells.

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Weichao Zhai ◽  
Jerome Tan ◽  
Tobias Russell ◽  
Sixun Chen ◽  
Dennis McGonagle ◽  
...  

AbstractHuman 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 $$\upbeta $$ β -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-$$\upbeta $$ β -galactosidase activity using the fluorogenic substrate, C$${_{12}}$$ 12 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 $$\upbeta $$ β -galactosidase staining. Both the advanced methods demonstrated statistically significant values, (r = 0.76, p $$\le $$ ≤ 0.001 for the fluorogenic C$${_{12}}$$ 12 FDG method, and r = 0.72, p $$\le $$ ≤ 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.


2014 ◽  
Vol 111 (38) ◽  
pp. 13954-13959 ◽  
Author(s):  
J. Leijten ◽  
N. Georgi ◽  
L. Moreira Teixeira ◽  
C. A. van Blitterswijk ◽  
J. N. Post ◽  
...  

2019 ◽  
Vol 20 (15) ◽  
pp. 3639 ◽  
Author(s):  
Giorgia Maroni ◽  
Daniele Panetta ◽  
Raffaele Luongo ◽  
Indira Krishnan ◽  
Federica La Rosa ◽  
...  

Molecular mechanisms governing cell fate decision events in bone marrow mesenchymal stromal cells (MSC) are still poorly understood. Herein, we investigated the homeobox gene Prep1 as a candidate regulatory molecule, by adopting Prep1 hypomorphic mice as a model to investigate the effects of Prep1 downregulation, using in vitro and in vivo assays, including the innovative single cell RNA sequencing technology. Taken together, our findings indicate that low levels of Prep1 are associated to enhanced adipogenesis and a concomitant reduced osteogenesis in the bone marrow, suggesting Prep1 as a potential regulator of the adipo-osteogenic differentiation of mesenchymal stromal cells. Furthermore, our data suggest that in vivo decreased Prep1 gene dosage favors a pro-adipogenic phenotype and induces a “browning” effect in all fat tissues.


2019 ◽  
Vol 7 (3) ◽  
pp. 1088-1100 ◽  
Author(s):  
Febriyani F. R. Damanik ◽  
Gabriele Spadolini ◽  
Joris Rotmans ◽  
Silvia Farè ◽  
Lorenzo Moroni

Controlling chemical and structural properties of electrospun scaffolds provide cues to regulate cell fate and migration.


2020 ◽  
Vol 6 (10) ◽  
pp. eaaw7853 ◽  
Author(s):  
Sébastien Sart ◽  
Raphaël F.-X. Tomasi ◽  
Antoine Barizien ◽  
Gabriel Amselem ◽  
Ana Cumano ◽  
...  

Organoids that recapitulate the functional hallmarks of anatomic structures comprise cell populations able to self-organize cohesively in 3D. However, the rules underlying organoid formation in vitro remain poorly understood because a correlative analysis of individual cell fate and spatial organization has been challenging. Here, we use a novel microfluidics platform to investigate the mechanisms determining the formation of organoids by human mesenchymal stromal cells that recapitulate the early steps of condensation initiating bone repair in vivo. We find that heterogeneous mesenchymal stromal cells self-organize in 3D in a developmentally hierarchical manner. We demonstrate a link between structural organization and local regulation of specific molecular signaling pathways such as NF-κB and actin polymerization, which modulate osteo-endocrine functions. This study emphasizes the importance of resolving spatial heterogeneities within cellular aggregates to link organization and functional properties, enabling a better understanding of the mechanisms controlling organoid formation, relevant to organogenesis and tissue repair.


2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15513-e15513
Author(s):  
Miaomiao Li ◽  
Xiaochuan Chen ◽  
Ting Lin ◽  
Zongwei Huang ◽  
Shihong Wu ◽  
...  

e15513 Background: To explore the metabolic alterations of nasopharyngeal carcinoma (NPC) cells after treated with chemodrugs, the Raman profiles were characterized with laser tweezer Raman spectroscopy. Methods: Two NPC cell lines (CNE2 and C666-1) were treated with gemcitabine, cisplatin, and paclitaxel, respectively. The high-quality Raman spectra of cells without or with treatments were recorded at the single-cell level with label-free laser tweezers Raman spectroscopy (LTRS) and analyzed for the differences of alterations of Raman profiles. Results: Tentative assignments of Raman peaks indicated that the cellular specific biomolecular changes associated with drug treatment, including changes in protein structure (e.g. 1655 cm−1), changes in DNA content and structure (e.g. 830 cm−1), destruction of DNA base pairs (e.g. 785 cm−1), and reduction in lipids (e.g. 970 cm−1). Besides, both principal components analysis (PCA) combined with linear discriminant analysis (LDA) and the classification and regression trees (CRT) algorithms were employed to further analyze and classify the spectral data between control group and treated group, with the best discriminant accuracy of 96.7% and 90.0% for CNE2 and C666-1 group treated with paclitaxel, respectively. Conclusions: This exploratory work demonstrated that LTRS technology combined with multivariate statistical analysis has promising potential to be a novel analytical strategy at the single-cell level for the evaluation of NPC-related chemotherapeutic drugs.


PLoS ONE ◽  
2013 ◽  
Vol 8 (5) ◽  
pp. e65438 ◽  
Author(s):  
Pei-San Hung ◽  
Yi-Chun Kuo ◽  
He-Guei Chen ◽  
Hui-Hua Kenny Chiang ◽  
Oscar Kuang-Sheng Lee

2019 ◽  
Author(s):  
Sébastien Sart ◽  
Raphaël F.-X. Tomasi ◽  
Antoine Barizien ◽  
Gabriel Amselem ◽  
Ana Cumano ◽  
...  

AbstractOrganoids that recapitulate the functional hallmarks of anatomic structures comprise cell populations able to self-organize cohesively in 3D. However, the rules underlying organoid formation in vitro remain poorly understood because a correlative analysis of individual cell fate and spatial organization has been challenging. Here, we use a novel microfluidics platform to investigate the mechanisms determining the formation of organoids by human mesenchymal stromal cells that recapitulate the early steps of condensation initiating bone repair in vivo. We find that heterogeneous mesenchymal stromal cells self-organize in 3D in a developmentally hierarchical manner. We demonstrate a link between structural organization and local regulation of specific molecular signaling pathways such as NF-κB and actin polymerization, which modulate osteo-endocrine functions. This study emphasizes the importance of resolving spatial heterogeneities within cellular aggregates to link organization and functional properties, enabling a better understanding of the mechanisms controlling organoid formation, relevant to organogenesis and tissue repair.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sara Imboden ◽  
Xuanqing Liu ◽  
Brandon S. Lee ◽  
Marie C. Payne ◽  
Cho-Jui Hsieh ◽  
...  

AbstractMesenchymal stromal cells (MSCs) are multipotent cells that have great potential for regenerative medicine, tissue repair, and immunotherapy. Unfortunately, the outcomes of MSC-based research and therapies can be highly inconsistent and difficult to reproduce, largely due to the inherently significant heterogeneity in MSCs, which has not been well investigated. To quantify cell heterogeneity, a standard approach is to measure marker expression on the protein level via immunochemistry assays. Performing such measurements non-invasively and at scale has remained challenging as conventional methods such as flow cytometry and immunofluorescence microscopy typically require cell fixation and laborious sample preparation. Here, we developed an artificial intelligence (AI)-based method that converts transmitted light microscopy images of MSCs into quantitative measurements of protein expression levels. By training a U-Net+ conditional generative adversarial network (cGAN) model that accurately (mean $$r_s$$ r s = 0.77) predicts expression of 8 MSC-specific markers, we showed that expression of surface markers provides a heterogeneity characterization that is complementary to conventional cell-level morphological analyses. Using this label-free imaging method, we also observed a multi-marker temporal-spatial fluctuation of protein distributions in live MSCs. These demonstrations suggest that our AI-based microscopy can be utilized to perform quantitative, non-invasive, single-cell, and multi-marker characterizations of heterogeneous live MSC culture. Our method provides a foundational step toward the instant integrative assessment of MSC properties, which is critical for high-throughput screening and quality control in cellular therapies.


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