Approximately 10% of fractures will not heal without intervention. Current treatments can be marginally effective, costly, and some have adverse effects. A safe and manufacturable mimic of anabolic bone is the primary goal of bone engineering, but achieving this is challenging. Mesenchymal stem cells (MSCs), are excellent candidates for engineering bone, but lack reproducibility due to donor source and culture methodology. The need for a bioactive attachment substrate also hinders progress. Herein, we describe a highly osteogenic MSC line generated from induced pluripotent stem cells that generates high yields of an osteogenic cell-matrix (ihOCM) in vitro. In mice, the intrinsic osteogenic activity of ihOCM surpasses bone morphogenic protein 2 (BMP2) driving healing of calvarial defects in 4 weeks by a mechanism mediated in part by collagen VI and XII. We propose that ihOCM may represent an effective replacement for autograft and BMP products used commonly in bone tissue engineering.
Human mesenchymal stem cells (hMSCs) are effective in treating disorders resulting from an inflammatory or heightened immune response. The hMSCs derived from induced pluripotent stem cells (ihMSCs) share the characteristics of tissue derived hMSCs but lack challenges associated with limited tissue sources and donor variation. To meet the expected future demand for ihMSCs, there is a need to develop scalable methods for their production at clinical yields while retaining immunomodulatory efficacy. Herein, we describe a platform for the scalable expansion and rapid harvest of ihMSCs with robust immunomodulatory activity using degradable gelatin methacryloyl (GelMA) microcarriers. GelMA microcarriers were rapidly and reproducibly fabricated using a custom microfluidic step emulsification device at relatively low cost. Using vertical wheel bioreactors, 8.8 to 16.3-fold expansion of ihMSCs was achieved over 8 days.Complete recovery by 5-minute digestion of the microcarriers with standard cell dissociation reagents resulted in >95% viability. The ihMSCs matched or exceeded immunomodulatory potential in vitro when compared with ihMSCs expanded on monolayers. This is the first description of a robust, scalable, and cost-effective method for generation of immunomodulatory ihMSCs, representing a significant contribution to their translational potential.
Purpose: Mesenchymal stem cells (MSCs) have demonstrated clinically relevant therapeutic effects for treatment of trauma and chronic diseases. The proliferative potential, immunomodulatory characteristics, and multipotentiality of MSCs in monolayer culture is reflected by their morphological phenotype. Standard techniques to evaluate culture viability are subjective, destructive, or time-consuming. We present an image analysis approach to objectively determine morphological phenotype of MSCs for prediction of culture efficacy.Approach: The algorithm was trained using phase-contrast micrographs acquired during the early and mid-logarithmic stages of MSC expansion. Cell regions are localized using edge detection, thresholding, and morphological operations, followed by cell marker identification using Hminima transform within each region to differentiate individual cells from cell clusters. Clusters are segmented using marker-controlled watershed to obtain single cells. Morphometric and textural features are extracted to classify cells based on phenotype using machine learning.Results: Algorithm performance was validated using an independent test dataset of 186 MSCs in 36 culture images. Results show 88% sensitivity and 86% precision for overall cell detection and a mean Sorensen-Dice coefficient of 0.849 AE 0.106 for segmentation per image. The algorithm exhibited an area under the curve of 0.816 (CI 95 ¼ 0.769 to 0.886) and 0.787 (CI 95 ¼ 0.716 to 0.851) for classifying MSCs according to their phenotype at early and mid-logarithmic expansion, respectively. Conclusions:The proposed method shows potential to segment and classify low and moderately dense MSCs based on phenotype with high accuracy and robustness. It enables quantifiable and consistent morphology-based quality assessment for various culture protocols to facilitate cytotherapy development.
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