RESUMO
The biophysical features of a cell can provide global insights into diverse molecular changes, especially in processes like the dedifferentiation of chondrocytes. Key biophysical markers of chondrocyte dedifferentiation include flattened cellular morphology and increased stress-fiber formation. During cartilage regeneration procedures, dedifferentiation of chondrocytes during in vitro expansion presents a critical limitation to the successful repair of cartilage tissue. Our study investigates how biophysical changes of chondrocytes during dedifferentiation influence the nuclear mechanics and gene expression of structural proteins located at the nuclear envelope. Through an experimental model of cell stretching and a detailed spatial intranuclear strain quantification, we identified that strain is amplified and the distribution of strain within the chromatin is altered under tensile loading in the dedifferentiated state. Further, using a confocal microscopy image-based finite element model and simulation of cell stretching, we found that the cell shape is the primary determinant of the strain amplification inside the chondrocyte nucleus in the dedifferentiated state. Additionally, we found that nuclear envelope proteins have lower gene expression in the dedifferentiated state. This study highlights the role of cell shape in nuclear mechanics and lays the groundwork to design biophysical strategies for the maintenance and enhancement of the chondrocyte phenotype during cell expansion with a goal of successful cartilage tissue engineering.
Assuntos
Cartilagem Articular , Condrócitos , Núcleo Celular , Proliferação de Células , Engenharia Tecidual/métodosRESUMO
Structural heterogeneity is a hallmark of living cells that drives local mechanical properties and dynamic cellular responses. However, the robust quantification of intracellular mechanics is lacking from conventional methods. Here, we describe the development of deformation microscopy, which leverages conventional imaging and an automated hyperelastic warping algorithm to investigate strain history, deformation dynamics, and changes in structural heterogeneity within the interior of cells and cell nuclei. Using deformation microscopy, we found that partial or complete disruption of LINC complexes in cardiomyocytes in vitro and lamin A/C deficiency in myocytes in vivo abrogate dominant tensile loading in the nuclear interior. We also found that cells cultured on stiff substrates or in hyperosmotic conditions displayed abnormal strain burden and asymmetries at interchromatin regions, which are associated with active transcription. Deformation microscopy represents a foundational approach toward intracellular elastography, with the potential utility to provide mechanistic and quantitative insights in diverse mechanobiological applications.
Assuntos
Citoesqueleto/metabolismo , Miócitos Cardíacos/citologia , Matriz Nuclear/metabolismo , Imagem Óptica/métodos , Estresse Mecânico , Algoritmos , Animais , Fenômenos Biomecânicos , Células Cultivadas , Condrócitos/citologia , Cromatina/química , Elasticidade , Laminas/química , Limite de Detecção , Masculino , Camundongos , Imagem Óptica/normas , Pressão Osmótica , Resistência à TraçãoRESUMO
Nuclear structure and mechanics play a critical role in diverse cellular functions, such as organizing direct access of chromatin to transcriptional regulators. Here, we use a new, to our knowledge, hybrid method, based on microscopy and hyperelastic warping, to determine three-dimensional strain distributions inside the nuclei of single living cells embedded within their native extracellular matrix. During physiologically relevant mechanical loading to tissue samples, strain was transferred to individual nuclei, resulting in submicron distributions of displacements, with compressive and tensile strain patterns approaching a fivefold magnitude increase in some locations compared to tissue-scale stimuli. Moreover, nascent RNA synthesis was observed in the interchromatin regions of the cells studied and spatially corresponded to strain patterns. Our ability to measure large strains in the interchromatin space, which reveals that movement of chromatin in the nucleus may not be due to random or biochemical mechanisms alone, but may result from the transfer of mechanical force applied at a distant tissue surface.
Assuntos
Cartilagem Articular/citologia , Núcleo Celular/genética , Núcleo Celular/metabolismo , RNA/biossíntese , Estresse Mecânico , Animais , Cartilagem Articular/fisiologia , Bovinos , Microambiente Celular , Cromatina/genética , Cromatina/metabolismo , Matriz Extracelular/metabolismo , Análise de Célula Única , Suporte de CargaRESUMO
Cells remarkably are capable of large deformations during motility and when subjected to mechanical force. Measurement of mechanical deformation (i.e. displacements, strain) is critical to understand functional changes in cells and biological tissues following disease, and to elucidate basic relationships between applied force and cellular biosynthesis. Microscopy-based imaging modalities provide the ability to noninvasively visualize small cell or tissue structures and track their motion over time, often using two-dimensional (2D) digital image (texture) correlation algorithms. For the measurement of complex and nonlinear motion in cells and tissues, implementation of texture correlation algorithms with high order approximations of displacement mapping terms are needed to minimize error. Here, we extend a texture correlation algorithm with up to third-order approximation of displacement mapping terms for the measurement of cell and tissue deformation. We additionally investigate relationships between measurement error and image texture, defined by subset entropy. Displacement measurement error is significantly reduced when the order of displacement mapping terms in the texture correlation algorithm matches or exceeds the order of the deformation observed. Displacement measurement error is also inversely proportional to subset entropy, with well-defined cell and tissue structures leading to high entropy and low error. For cell and tissue studies where complex or nonlinear displacements are expected, texture correlation algorithms with high order terms are required to best characterize the observed deformation.