Saitheja A Pucha, Maddie Hasson, Hanna Solomon, Gail E McColgan, Jennifer L Robinson, Sebastián L Vega, Jay M Patel
{"title":"揭示纤维增强微环境中细胞反应的早期空间模式","authors":"Saitheja A Pucha, Maddie Hasson, Hanna Solomon, Gail E McColgan, Jennifer L Robinson, Sebastián L Vega, Jay M Patel","doi":"10.1089/ten.TEA.2024.0017","DOIUrl":null,"url":null,"abstract":"<p><p>Fiber-reinforcement approaches have been used to replace aligned tissues with engineered constructs after injury or surgical resection, strengthening soft biomaterial scaffolds and replicating anisotropic, load-bearing properties. However, most studies focus on the macroscale aspects of these scaffolds, rarely considering the cell-biomaterial interactions that govern remodeling and extracellular matrix organization toward aligned neo-tissues. As initial cell-biomaterial responses within fiber-reinforced microenvironments likely influence the long-term efficacy of repair and regeneration strategies, here we elucidate the roles of spatial orientation, substrate stiffness, and matrix remodeling on early cell-fiber interactions. Bovine mesenchymal stromal cells (MSCs) were cultured in soft fibrin gels reinforced with a stiff 100 µm polyglycolide-co-caprolactone fiber. Gel stiffness and remodeling capacity were modulated by fibrinogen concentration and aprotinin treatment, respectively. MSCs were imaged at 3 days and evaluated for morphology, mechanoresponsiveness (nuclear Yes-associated protein [YAP] localization), and spatial features including distance and angle deviation from fiber. Within these constructs, morphological conformity decreased as a function of distance from fiber. However, these correlations were weak (<i>R</i><sup>2</sup> = 0.01043 for conformity and <i>R</i><sup>2</sup> = 0.05542 for nuclear YAP localization), illustrating cellular heterogeneity within fiber-enforced microenvironments. To better assess cell-fiber interactions, we applied machine-learning strategies to our heterogeneous dataset of cell-shape and mechanoresponsive parameters. Principal component analysis (PCA) was used to project 23 input parameters (not including distance) onto 5 principal components (PCs), followed by agglomerative hierarchical clustering to classify cells into 3 groups. These clusters exhibited distinct levels of morpho-mechanoresponse (combination of morphological conformity and YAP signaling) and were classified as high response (HR), medium response (MR), and low response (LR) clusters. Cluster distribution varied spatially, with most cells (61%) closest to the fiber (0-75 µm) belonging to the HR cluster, and most cells (55%) furthest from the fiber (225-300 µm) belonging to the LR cluster. Modulation of gel stiffness and fibrin remodeling showed differential effects for HR cells, with stiffness influencing the level of mechanoresponse and remodeling capacity influencing the location of responding cells. Together, these novel findings demonstrate early trends in cellular patterning of the fiber-reinforced microenvironment, showing how spatial orientation, substrate biophysical properties, and matrix remodeling may guide the amplitude and localization of cellular mechanoresponses. These trends may guide approaches to optimize the design of microscale scaffold architecture and substrate properties for enhancing organized tissue assembly at the macroscale.</p>","PeriodicalId":56375,"journal":{"name":"Tissue Engineering Part A","volume":null,"pages":null},"PeriodicalIF":3.5000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Revealing Early Spatial Patterns of Cellular Responsivity in Fiber-Reinforced Microenvironments.\",\"authors\":\"Saitheja A Pucha, Maddie Hasson, Hanna Solomon, Gail E McColgan, Jennifer L Robinson, Sebastián L Vega, Jay M Patel\",\"doi\":\"10.1089/ten.TEA.2024.0017\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Fiber-reinforcement approaches have been used to replace aligned tissues with engineered constructs after injury or surgical resection, strengthening soft biomaterial scaffolds and replicating anisotropic, load-bearing properties. However, most studies focus on the macroscale aspects of these scaffolds, rarely considering the cell-biomaterial interactions that govern remodeling and extracellular matrix organization toward aligned neo-tissues. As initial cell-biomaterial responses within fiber-reinforced microenvironments likely influence the long-term efficacy of repair and regeneration strategies, here we elucidate the roles of spatial orientation, substrate stiffness, and matrix remodeling on early cell-fiber interactions. Bovine mesenchymal stromal cells (MSCs) were cultured in soft fibrin gels reinforced with a stiff 100 µm polyglycolide-co-caprolactone fiber. Gel stiffness and remodeling capacity were modulated by fibrinogen concentration and aprotinin treatment, respectively. MSCs were imaged at 3 days and evaluated for morphology, mechanoresponsiveness (nuclear Yes-associated protein [YAP] localization), and spatial features including distance and angle deviation from fiber. Within these constructs, morphological conformity decreased as a function of distance from fiber. However, these correlations were weak (<i>R</i><sup>2</sup> = 0.01043 for conformity and <i>R</i><sup>2</sup> = 0.05542 for nuclear YAP localization), illustrating cellular heterogeneity within fiber-enforced microenvironments. To better assess cell-fiber interactions, we applied machine-learning strategies to our heterogeneous dataset of cell-shape and mechanoresponsive parameters. Principal component analysis (PCA) was used to project 23 input parameters (not including distance) onto 5 principal components (PCs), followed by agglomerative hierarchical clustering to classify cells into 3 groups. These clusters exhibited distinct levels of morpho-mechanoresponse (combination of morphological conformity and YAP signaling) and were classified as high response (HR), medium response (MR), and low response (LR) clusters. Cluster distribution varied spatially, with most cells (61%) closest to the fiber (0-75 µm) belonging to the HR cluster, and most cells (55%) furthest from the fiber (225-300 µm) belonging to the LR cluster. Modulation of gel stiffness and fibrin remodeling showed differential effects for HR cells, with stiffness influencing the level of mechanoresponse and remodeling capacity influencing the location of responding cells. Together, these novel findings demonstrate early trends in cellular patterning of the fiber-reinforced microenvironment, showing how spatial orientation, substrate biophysical properties, and matrix remodeling may guide the amplitude and localization of cellular mechanoresponses. 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Revealing Early Spatial Patterns of Cellular Responsivity in Fiber-Reinforced Microenvironments.
Fiber-reinforcement approaches have been used to replace aligned tissues with engineered constructs after injury or surgical resection, strengthening soft biomaterial scaffolds and replicating anisotropic, load-bearing properties. However, most studies focus on the macroscale aspects of these scaffolds, rarely considering the cell-biomaterial interactions that govern remodeling and extracellular matrix organization toward aligned neo-tissues. As initial cell-biomaterial responses within fiber-reinforced microenvironments likely influence the long-term efficacy of repair and regeneration strategies, here we elucidate the roles of spatial orientation, substrate stiffness, and matrix remodeling on early cell-fiber interactions. Bovine mesenchymal stromal cells (MSCs) were cultured in soft fibrin gels reinforced with a stiff 100 µm polyglycolide-co-caprolactone fiber. Gel stiffness and remodeling capacity were modulated by fibrinogen concentration and aprotinin treatment, respectively. MSCs were imaged at 3 days and evaluated for morphology, mechanoresponsiveness (nuclear Yes-associated protein [YAP] localization), and spatial features including distance and angle deviation from fiber. Within these constructs, morphological conformity decreased as a function of distance from fiber. However, these correlations were weak (R2 = 0.01043 for conformity and R2 = 0.05542 for nuclear YAP localization), illustrating cellular heterogeneity within fiber-enforced microenvironments. To better assess cell-fiber interactions, we applied machine-learning strategies to our heterogeneous dataset of cell-shape and mechanoresponsive parameters. Principal component analysis (PCA) was used to project 23 input parameters (not including distance) onto 5 principal components (PCs), followed by agglomerative hierarchical clustering to classify cells into 3 groups. These clusters exhibited distinct levels of morpho-mechanoresponse (combination of morphological conformity and YAP signaling) and were classified as high response (HR), medium response (MR), and low response (LR) clusters. Cluster distribution varied spatially, with most cells (61%) closest to the fiber (0-75 µm) belonging to the HR cluster, and most cells (55%) furthest from the fiber (225-300 µm) belonging to the LR cluster. Modulation of gel stiffness and fibrin remodeling showed differential effects for HR cells, with stiffness influencing the level of mechanoresponse and remodeling capacity influencing the location of responding cells. Together, these novel findings demonstrate early trends in cellular patterning of the fiber-reinforced microenvironment, showing how spatial orientation, substrate biophysical properties, and matrix remodeling may guide the amplitude and localization of cellular mechanoresponses. These trends may guide approaches to optimize the design of microscale scaffold architecture and substrate properties for enhancing organized tissue assembly at the macroscale.
期刊介绍:
Tissue Engineering is the preeminent, biomedical journal advancing the field with cutting-edge research and applications that repair or regenerate portions or whole tissues. This multidisciplinary journal brings together the principles of engineering and life sciences in the creation of artificial tissues and regenerative medicine. Tissue Engineering is divided into three parts, providing a central forum for groundbreaking scientific research and developments of clinical applications from leading experts in the field that will enable the functional replacement of tissues.