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Balasubramanian, L.

Publications and source records attributed to Balasubramanian, L..

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Quantifying punctate morphology in mesenchymal stem cells from single cell images provides a definitive quality assessment pipeline for direct correlation to osteogenic lineage differentiation

Mesenchymal stem cells (MSCs) exhibit unique immunological properties and are classified as multipotent stem cells. Considering their immunosuppressive and immunoenhancing properties, they have been used adequately for tissue regeneration across allogeneic barriers. MSCs are propagated mainly using in vitro methods of cell culture and thereby exhibit heterogeneity in a wide spectrum. Such stem cell heterogeneity can arise due to donor, tissue and cellular variability. Studies have shown that functional variances in MSCs derived from the same tissue source across different donors may be influenced by age, gender, and physiological condition. In contrast to their mature counterparts, mesenchymal stem cells exhibit a relative resilience to cellular senescence; yet they remain vulnerable to both intrinsic and extrinsic stress. Cellular senescence can be induced by exposure to cellular stress or a reduction in replicative capacity. Cellular structure, telomere length, and senescence-associated {beta}-galactosidase (SA-{beta}-gal) activity are some of the hallmark observations signifying the onset of senescence in cells. Such a biological state in mesenchymal stem cells diminishes the overall effectiveness of the cells as candidates for biotherapeutics. Although MSCs towards their later passages are known to show drop in proliferative properties and in their regenerative potential, direct correlation of passage related onset of cellular senescence and lineage differentiation at the single cell precision remains largely unexplored. To close this gap in stem cell research, we have developed a single cell image-based pipeline exclusively for human MSCs, which addresses immune-heterogeneity features using both the bright field and fluorescence-based images of stem cells. The MSCProfiler or the single cell image-based pipeline can analyze and quantify feature descriptors of the MSCs, across tissues and passages in vitro. We have extrapolated the pipeline to address a critical biological state like senescence in MSCs to quantify this multi-variable property of stem cells and check the correlation with cellular differentiation, if any. To address the properties of replicative senescence and study it at the single cell level, we wanted to study the senescence-associated {beta}-galactosidase activity in human dental pulp derived MSCs (hDPSCs). Further to these analyses, we wanted to assess if quantifying the punctate morphology in single stem cells can establish any direct correlation of senescence with osteogenic lineage differentiation in case of the hDPSCs. To achieve our hypothesis, we used the MSCProfiler and extended the pipeline to incorporate the expression profiles of senescence-associated {beta}-galactosidase across the early, mid and late passages of hDPSCs. The pipeline was modified to incorporate bright field image features such as cell size, shape and eccentricity and fluorescence images from the SA- {beta}-galactosidase-substrate reactions. We classified the puncta morphology across passages of hDPSCs and checked for osteogenic lineage differentiation abilities in these MSCs. This could prove to be definitive quality assessment pipeline to assess the biological state of all types of MSCs before their use in allogenic transplantations.

cell biology↗

MSCProfiler: An image processing workflow to investigate Mesenchymal Stem Cell heterogeneity using imaging flow cytometry data.

Single-cell immuno-heterogeneity has always been the forerunner of any change in homeostasis of cellular functions in the body. Mesenchymal stem cells represent a viable source for the development of cell-based therapies. Multiple conditions giving rise to inter, and intra-population variations result in heterogeneity and multipotent differentiation ability of these cells of stromal origin. Cell surface markers which are important members of membrane proteins, ion channels, transporter, adhesion, and signaling molecules generally differentiate between stromal cells of different origin. However, existing analytical tools cannot always model a pattern of their surface distribution in successive generations of growth and proliferation. In this study, we have developed a post-acquisition image analysis pipeline for human mesenchymal stromal cells obtained from exfoliated deciduous teeth (hSHEDs). Using the open-source image processing software CellProfiler, a pipeline has been developed to extract cellular features from 50,000-100,000 single-cell images. We made use of the image flow cytometry technology to explore the morphometric properties of hSHEDs, along with their surface marker distribution. This unbiased pipeline can extract cellular, geometrical and texture features such as shape, size, eccentricity, entropy, intensities as a measure of cellular heterogeneity. For the first time, we have described an automated, unbiased image assessment protocol implemented in a validated open-source software, leveraging the suite of image-based measurements to develop the prototype named as MSCProfiler. The hallmark of this screening workflow has been the identification and removal of image-based aberrations to identify the single-cell bright field and fluorescent images of mesenchymal stem cells.

cell biology↗