Tight junction membrane proteins regulate the mechanical resistance of the apical junctional complex.

Epithelia must be able to resist mechanical force to preserve tissue integrity. While intercellular junctions are known to be important for the mechanical resistance of epithelia, the roles of tight junctions (TJs) remain to be established. We previously demonstrated that epithelial cells devoid of the TJ membrane proteins claudins and JAM-A completely lack TJs and exhibit focal breakages of their apical junctions. Here, we demonstrate that apical junctions fracture when claudin/JAM-A-deficient cells undergo spontaneous cell stretching. The junction fracture was accompanied by actin disorganization, and actin polymerization was required for apical junction integrity in the claudin/JAM-A-deficient cells. Further deletion of CAR resulted in the disruption of ZO-1 molecule ordering at cell junctions, accompanied by severe defects in apical junction integrity. These results demonstrate that TJ membrane proteins regulate the mechanical resistance of the apical junctional complex in epithelial cells.

FBP17-mediated finger-like membrane protrusions in cell competition between normal and RasV12-transformed cells.

At the initial stage of carcinogenesis, cell competition often occurs between newly emerging transformed cells and the neighboring normal cells, leading to the elimination of transformed cells from the epithelial layer. For instance, when RasV12-transformed cells are surrounded by normal cells, RasV12 cells are apically extruded from the epithelium. However, the underlying mechanisms of this tumor-suppressive process still remain enigmatic. We first show by electron microscopic analysis that characteristic finger-like membrane protrusions are projected from both normal and RasV12 cells at their interface. In addition, FBP17, a member of the F-BAR proteins, accumulates in RasV12 cells, as well as surrounding normal cells, which plays a positive role in the formation of finger-like protrusions and apical elimination of RasV12 cells. Furthermore, cdc42 acts upstream of these processes. These results suggest that the cdc42/FBP17 pathway is a crucial trigger of cell competition, inducing "protrusion to protrusion response" between normal and RasV12-transformed cells.

3DeeCellTracker, a deep learning-based pipeline for segmenting and tracking cells in 3D time lapse images.

Despite recent improvements in microscope technologies, segmenting and tracking cells in three-dimensional time-lapse images (3D + T images) to extract their dynamic positions and activities remains a considerable bottleneck in the field. We developed a deep learning-based software pipeline, 3DeeCellTracker, by integrating multiple existing and new techniques including deep learning for tracking. With only one volume of training data, one initial correction, and a few parameter changes, 3DeeCellTracker successfully segmented and tracked ~100 cells in both semi-immobilized and 'straightened' freely moving worm's brain, in a naturally beating zebrafish heart, and ~1000 cells in a 3D cultured tumor spheroid. While these datasets were imaged with highly divergent optical systems, our method tracked 90-100% of the cells in most cases, which is comparable or superior to previous results. These results suggest that 3DeeCellTracker could pave the way for revealing dynamic cell activities in image datasets that have been difficult to analyze.

Microscopes have been used to decrypt the tiny details of life since the 17th century. Now, the advent of 3D microscopy allows scientists to build up detailed pictures of living cells and tissues. In that effort, automation is becoming increasingly important so that scientists can analyze the resulting images and understand how bodies grow, heal and respond to changes such as drug therapies. In particular, algorithms can help to spot cells in the picture (called cell segmentation), and then to follow these cells over time across multiple images (known as cell tracking). However, performing these analyses on 3D images over a given period has been quite challenging. In addition, the algorithms that have already been created are often not user-friendly, and they can only be applied to a specific dataset gathered through a particular scientific method. As a response, Wen et al. developed a new program called 3DeeCellTracker, which runs on a desktop computer and uses a type of artificial intelligence known as deep learning to produce consistent results. Crucially, 3DeeCellTracker can be used to analyze various types of images taken using different types of cutting-edge microscope systems. And indeed, the algorithm was then harnessed to track the activity of nerve cells in moving microscopic worms, of beating heart cells in a young small fish, and of cancer cells grown in the lab. This versatile tool can now be used across biology, medical research and drug development to help monitor cell activities.

Adaptive Optical Two-Photon Microscopy for Surface-Profiled Living Biological Specimens.

We developed adaptive optical (AO) two-photon excitation microscopy by introducing a spatial light modulator (SLM) in a commercially available microscopy system. For correcting optical aberrations caused by refractive index (RI) interfaces at a specimen's surface, spatial phase distributions of the incident excitation laser light were calculated using 3D coordination of the RI interface with a 3D ray-tracing method. Based on the calculation, we applied a 2D phase-shift distribution to a SLM and achieved the proper point spread function. AO two-photon microscopy improved the fluorescence image contrast in optical phantom mimicking biological specimens. Furthermore, it enhanced the fluorescence intensity from tubulin-labeling dyes in living multicellular tumor spheroids and allowed successful visualization of dendritic spines in the cortical layer V of living mouse brains in the secondary motor region with a curved surface. The AO approach is useful for observing dynamic physiological activities in deep regions of various living biological specimens with curved surfaces.

Nonmuscle myosin IIA and IIB differently suppress microtubule growth to stabilize cell morphology.

Precise regulation of cytoskeletal dynamics is important in many fundamental cellular processes such as cell shape determination. Actin and microtubule (MT) cytoskeletons mutually regulate their stability and dynamics. Nonmuscle myosin II (NMII) is a candidate protein that mediates the actin-MT crosstalk. NMII regulates the stability and dynamics of actin filaments to control cell morphology. Additionally, previous reports suggest that NMII-dependent cellular contractility regulates MT dynamics, and MTs also control cell morphology; however, the detailed mechanism whereby NMII regulates MT dynamics and the relationship among actin dynamics, MT dynamics and cell morphology remain unclear. The present study explores the roles of two well-characterized NMII isoforms, NMIIA and NMIIB, on the regulation of MT growth dynamics and cell morphology. We performed RNAi and drug experiments and demonstrated the NMII isoform-specific mechanisms-NMIIA-dependent cellular contractility upregulates the expression of some mammalian diaphanous-related formin (mDia) proteins that suppress MT dynamics; NMIIB-dependent inhibition of actin depolymerization suppresses MT growth independently of cellular contractility. The depletion of either NMIIA or NMIIB resulted in the increase in cellular morphological dynamicity, which was alleviated by the perturbation of MT dynamics. Thus, the NMII-dependent control of cell morphology significantly relies on MT dynamics.

Expression, purification and characterization of the recombinant cysteine-rich antimicrobial peptide snakin-1 in Pichia pastoris.

Snakin-1 (SN-1) is a small cysteine-rich plant antimicrobial peptide with broad spectrum antimicrobial activity which was isolated from potato (Solanum tuberosum). Here, we carried out the expression of a recombinant SN-1 in the methylotrophic yeast Pichia pastoris, along with its purification and characterization. A DNA fragment encoding the mature SN-1 was cloned into pPIC9 vector and introduced into P. pastoris. A large amount of pure recombinant SN-1 (approximately 40 mg/1L culture) was obtained from a fed-batch fermentation culture after purification with a cation exchange column followed by RP-HPLC. The identity of the recombinant SN-1 was verified by MALDI-TOF MS, CD and (1)H NMR experiments. All these data strongly indicated that the recombinant SN-1 peptide had a folding with six disulfide bonds that was identical to the native SN-1. Our findings showed that SN-1 exhibited strong antimicrobial activity against test microorganisms and produced very weak hemolysis of mammalian erythrocytes. The mechanism of its antimicrobial action against Escherichia coli was investigated by both outer membrane permeability assay and cytoplasmic membrane depolarization assay. These assays demonstrated that SN-1 is a membrane-active antimicrobial peptide which can disrupt both outer and cytoplasmic membrane integrity. This is the first report on the recombinant expression and purification of a fully active SN-1 in P. pastoris.