RESUMEN
The absence of quantitative in vitro cell-extracellular matrix models represents an important bottleneck for basic research and human health. Randomness of cellular distributions provides an opportunity for the development of a quantitative in vitro model. However, quantification of the randomness of random cell distributions is still lacking. In this paper, we have imaged cellular distributions in an alginate matrix using a multiview light sheet microscope and developed quantification metrics of randomness by modeling it as a Poisson process, a process that has constant probability of occurring in space or time. We imaged fluorescently labeled human mesenchymal stem cells embedded in an alginate matrix of thickness greater than 5 mm with axial resolution, the mean full width at half maximum of the axial intensity profiles of fluorescent particles. Simulated randomness agrees well with the experiments. Quantification of distributions and validation by simulations will enable quantitative study of cell-matrix interactions in tissue models.
Asunto(s)
Matriz Extracelular , Imagenología Tridimensional/métodos , Microscopía/métodos , Alginatos , Humanos , Imagenología Tridimensional/instrumentación , Rayos Láser , Luz , Células Madre Mesenquimatosas/citología , Microscopía Fluorescente/métodos , Tamaño de la PartículaRESUMEN
MMP1 is an essential enzyme for tissue remodeling both in normal and pathological states. We report a method of purifying activated human MMP1 in E. coli without using urea or 4-Aminophenylmercuric acetate (APMA). Instead, a non-ionic detergent, Triton X-100, was used in the lysis buffer to solubilize MMP1 followed by the protease activities of both trypsin and MMP1 to digest E. coli proteins and activate pro-MMP1. Identity of activated MMP1 was confirmed by Western blot using anti-human MMP1 antibodies, whereas the mass was determined to be 43 kD using matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI TOF-MS). Collagen and gelatin degradation by purified MMP1 were confirmed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS PAGE) of degraded FITC-labeled type-1 collagen and gelatin zymogram. Broad-spectrum protease activity of purified MMP1 was also confirmed by lysis of native E. coli proteins. Inexpensive high throughput purification of recombinant human MMP1 in E. coli will enable easier MMP1 production for diverse applications.
Asunto(s)
Metaloproteinasa 1 de la Matriz/química , Metaloproteinasa 1 de la Matriz/aislamiento & purificación , Proteínas Recombinantes/química , Proteínas Recombinantes/aislamiento & purificación , Colágeno/química , Electroforesis en Gel de Poliacrilamida , Escherichia coli/genética , Gelatina/química , Humanos , Metaloproteinasa 1 de la Matriz/genética , Proteolisis , Proteínas Recombinantes/genética , Espectrometría de Masa por Láser de Matriz Asistida de Ionización DesorciónRESUMEN
Studying individual biomolecules at the single-molecule level has proved very insightful recently. Single-molecule experiments allow us to probe both the equilibrium and nonequilibrium properties as well as make quantitative connections with ensemble experiments and equilibrium thermodynamics. However, it is important to be careful about the analysis of single-molecule data because of the noise present and the lack of theoretical framework for processes far away from equilibrium. Biomolecular motion, whether it is free in solution, on a substrate, or under force, involves thermal fluctuations in varying degrees, which makes the motion noisy. In addition, the noise from the experimental setup makes it even more complex. The details of biologically relevant interactions, conformational dynamics, and activities are hidden in the noisy single-molecule data. As such, extracting biological insights from noisy data is still an active area of research. In this review, we will focus on analyzing both fluorescence-based and force-based single-molecule experiments and gaining biological insights at the single-molecule level. Inherently nonequilibrium nature of biological processes will be highlighted. Simulated trajectories of biomolecular diffusion will be used to compare and validate various analysis techniques.