力学生物学

Time-lapse into immunofluorescence (TL into IF) imaging combines the wealth of information acquired during live-cell imaging with ease of access for static immunofluorescence markers. In the field of mechanobiology, connecting live and static imaging to visualize cell biology dynamics is often troublesome. For instance, nuclear blebs are deformations of the nucleus that often rupture spontaneously, leading to changes in the molecular composition of the nucleus and the nuclear bleb. Current techniques to connect cellular dynamics and their downstream effects via live-cell imaging, followed by immunofluorescence, often require third-party analysis programs or stage position measurements to accurately track cells. This protocol simplifies the connection between live and static imaging by utilizing a gridded imaging dish. In our protocol, cells are plated on a dish with an engraved coordinate plane. Individual cells are then matched from when the time-lapse ends to the immunofluorescence images simply by their known coordinate location. Overall, TL into IF offers a straightforward method for connecting dynamic live-cell with static immunofluorescence imaging, in an easy and accessible tool for cell biologists.

This protocol describes a reproducible workflow for modeling in vitro impact-induced traumatic brain injury (TBI) using a mechanical stretch system applied to differentiated SH-SY5Y human neuroblastoma cells cultured on polydimethylsiloxane (PDMS) substrates. The protocol integrates three primary components: (1) fabrication and surface modification of deformable PDMS chambers to support cellular adhesion, (2) partial differentiation of SH-SY5Y cells using retinoic acid, and (3) induction of controlled mechanical strain to simulate mild to moderate TBI. The stretch-induced injury model enables quantitative assessment of cellular viability and recovery following mechanical insult. This approach provides a versatile platform for studying cellular and molecular mechanisms of TBI, screening neuroprotective compounds, and exploring mechanobiological responses in neural cells under controlled strain magnitudes and rates.

Efficient and nontoxic delivery of foreign cargo into cells is a critical step in many biological studies and cell engineering workflows with applications in areas such as biomanufacturing and cell-based therapeutics. However, effective molecular delivery into cells involves optimizing several experimental parameters. In the case of electroporation-based intracellular delivery, there is a need to optimize parameters like pulse voltage, duration, buffer type, and cargo concentration for each unique application. Here, we present the protocol for fabricating and utilizing a high-throughput multi-well localized electroporation device (LEPD) assisted by deep learning–based image analysis to enable rapid optimization of experimental parameters for efficient and nontoxic molecular delivery into cells. The LEPD and the optimization workflow presented herein are relevant to both adherent and suspended cell types and different molecular cargo (DNA, RNA, and proteins). The workflow enables multiplexed combinatorial experiments and can be adapted to cell engineering applications requiring in vitro delivery.

When focusing on quick movements in the analysis of animal behavior, a high-speed camera can be used as a powerful tool. There are many options for high-speed cameras to record movement. In recent years, the quality and sophistication of videos captured on cell phones have evolved so much that the iPhone’s slow-motion video system can function as a tool for behavior analysis. Here, we describe a method to analyze the movement of the ankle joint and jump speed during the jumping action of mice, using an iPhone.