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The soilborne ascomycete fungus Verticillium dahliae causes destructive vascular wilt disease in hundreds of dicotyledonous plant species. However, our understanding of the early invasion from the epidermis to the vasculature and the prompt proliferation and colonization in the xylem tissues remains poor. To elaborate the detailed infection strategy of V. dahliae in host plants, we traced the whole infection process of V. dahliae by live‐cell imaging combined with high‐resolution scanning electron microscopy. The 4D image series demonstrated that the apex of invading hyphae becomes tapered and directly invades the intercellular space of root epidermal cells at the initial infection. Following successful epidermal invasion, the invading hyphae extend in the intercellular space of the root cortex toward the vascular tissues. Importantly, the high‐resolution microscopic and live‐cell images demonstrated (a) that conidia are formed via budding at the apex of the hyphae in the xylem vessels to promote systemic propagation vertically, and (b) that the hyphae freely cross adjacent xylem vessels through the intertracheary pits to achieve horizontal colonization. Our findings provide a solid cellular basis for future studies on both intracellular invasion and vascular colonization/proliferation during V. dahliae infection and pathogenesis in host plants. High‐resolution scanning electron microscopy and live‐cell images show that Verticillium dahliae hyphae invade the intercellular space of the host root epidermis and differentiate into simple conidiophores to promote systemic propagation in xylem vessels.

Many biological networks respond to various inputs through a common signaling molecule that triggers distinct cellular outcomes. One potential mechanism for achieving specific input–output relationships is to trigger distinct dynamical patterns in response to different stimuli. Here we focused on the dynamics of p53, a tumor suppressor activated in response to cellular stress. We quantified the dynamics of p53 in individual cells in response to UV and observed a single pulse that increases in amplitude and duration in proportion to the UV dose. This graded response contrasts with the previously described series of fixed pulses in response to γ‐radiation. We further found that while γ‐triggered p53 pulses are excitable, the p53 response to UV is not excitable and depends on continuous signaling from the input‐sensing kinases. Using mathematical modeling and experiments, we identified feedback loops that contribute to specific features of the stimulus‐dependent dynamics of p53, including excitability and input‐duration dependency. Our study shows that different stresses elicit different temporal profiles of p53, suggesting that modulation of p53 dynamics might be used to achieve specificity in this network.

The advent of single‐cell methods is paving the way for an in‐depth understanding of the cell cycle with unprecedented detail. Due to its ramifications in nearly all biological processes, the evaluation of cell cycle progression is critical for an exhaustive cellular characterization. Here, we present DeepCycle, a deep learning method for estimating a cell cycle trajectory from unsegmented single‐cell microscopy images, relying exclusively on the brightfield and nuclei‐specific fluorescent signals. DeepCycle was evaluated on 2.6 million single‐cell microscopy images of MDCKII cells with the fluorescent FUCCI2 system. DeepCycle provided a latent representation of cell images revealing a continuous and closed trajectory of the cell cycle. Further, we validated the DeepCycle trajectories by showing its nearly perfect correlation with real time measured from live‐cell imaging of cells undergoing an entire cell cycle. This is the first model able to resolve the closed cell cycle trajectory, including cell division, solely based on unsegmented microscopy data from adherent cell cultures. Synopsis DeepCycle is a deep neural network able to reconstruct a cyclic cell cycle trajectory from unsegmented cell images. The model is validated on cells undergoing a full cell cycle by comparing the progression of the inferred trajectory to real time. The deep learning model DeepCycle reconstructs a cyclic cell cycle trajectory solely from unsegmented images in the Hoescht and Brightfield channels. The model was trained using fluorescently labelled cell cycle markers from the FUCCI2 system. The reconstructed DeepCycle pseudotime was validated by comparing its progression to the measured real cell cycle time of cells undergoing an entire cell cycle. Graphical Abstract DeepCycle is a deep neural network able to reconstruct a cyclic cell cycle trajectory from unsegmented cell images. The model is validated on cells undergoing a full cell cycle by comparing the progression of the inferred trajectory to real time.

Background Tumor metastasis is a leading cause of cancer‐related death, fundamentally dependent on cell motility—a conserved behavior enabling cells to move directionally in response to environmental signals. Eco‐oncology posits that tumors function as cellular ecosystems; however, the individual migration behavior of tumor cells, particularly their potential “foraging” activities, remains poorly understood. Our study observes the biological behavior of independent tumor cells during migration to understand how they utilize available resources to achieve their survival goals, and whether they compete with and interact with “companions” that are also migrating. Methods We used live‐cell dynamic imaging analysis to observe the migration of individual CT26 and A549 tumor cells over time. Cells were cultured at low density, and a subset of CT26 cells was labeled with enhanced green fluorescent protein (EGFP) for visualization. Cell interactions and motility were recorded every 10 min, and cell contact was detected using Wright staining. Results Tumor cells migrated by extending pseudopodia‐like membrane processes, simultaneously undergoing cell division and proliferation. Cells actively migrated to the vicinity of dead cells or cell debris, capturing and absorbing these substances within minutes. Frequent intercellular contact occurred, with stronger cells absorbing the cytoplasm of weaker cells, ultimately leaving only nuclear remnants. Cells also exhibited the ability to cleave and absorb debris from adjacent cellular structures. Conclusions Individual tumor cells exhibit intrinsic, active foraging‐like behavior during migration, including acquiring nutrients from dead cells and competing with neighboring surviving cells. Tumor cell motility should be viewed not only as a mechanistic process but also as a resource‐seeking survival strategy. Tumor cells gradually form pseudopodia, migrate to necrotic cells, make contact with them, and absorb necrotic cell debris. During this migration, small vesicles formed by dying tumor cells also gradually migrate toward living tumor cells. Once the nutrients from the necrotic cells have been completely absorbed, the living tumor cells will leave.

INTRODUCTION Tauopathies involve progressive accumulation of abnormal tau species that disrupt the autophagy‐lysosomal pathway (ALP), critical for degrading intracellular macromolecules and aggregates, leading to toxicity and cell death. This study examines how overexpression of the N‐terminally truncated Tau35 protein affects proteolytic pathways, including autophagy and endo‐lysosomal processes. METHODS Using the Tau35 mouse model and SH‐SY5Y human neuroblastoma cells stably expressing Tau35 or full‐length tau, we assessed protein degradation and lysosomal function via Western blotting, proteomics of lysosome‐enriched brain fractions, cathepsin activity assays, endocytosis/proteolysis assays, and live‐cell imaging using LysoTracker. RESULTS We identified early endo‐lysosomal alterations associated with Tau35 expression, including increased endocytosis, disrupted autophagic flux, proteolytic impairment, and lysosomal motility defects. DISCUSSION These findings extend previous research by elucidating Tau35‐induced dysfunction in intracellular degradation systems and offer mechanistic insight into tauopathy progression. This work provides a foundation for developing targeted therapies to restore acidification, proteostasis, and lysosomal function in tauopathies. Highlights Tau35, an N‐terminally truncated tau fragment, disrupts proteolytic pathways: We show that Tau35 overexpression leads to significant alterations in autophagy and endo‐lysosomal function. Endo‐lysosomal dysfunction is an early pathological event: Our findings demonstrate early‐stage increases in endocytosis, impaired proteolytic activity, altered autophagic flux, and disrupted lysosomal motility in Tau35‐expressing models. In vivo and in vitro models confirm consistent pathogenic signatures: Parallel studies in a Tau35 mouse model and SH‐SY5Y cells reveal converging cellular and molecular dysfunctions. Lysosome‐enriched proteomics reveals novel pathway alterations: Proteomic profiling of lysosomal fractions identifies Tau35‐specific protein dysregulation contributing to disease pathology. Mechanistic insights into tauopathy progression: These results provide a mechanistic understanding of how truncated tau species contribute to neuronal dysfunction, offering a rationale for targeting endo‐lysosomal pathways in therapeutic development.

Cancer's notorious heterogeneity poses significant challenges, as each tumor comprises a unique ecosystem. While single‐cell and spatial transcriptomics advancements have transformed our understanding of spatial diversity within tumors, the temporal dimension remains underexplored. Tumors are dynamic entities that continuously evolve and adapt, and relying solely on static snapshots obscures the intricate interplay between cancer cells and their microenvironment. Here, we advocate for integrating temporal dynamics into cancer research, emphasizing a fundamental shift from traditional endpoint experiments to data‐driven, continuous approaches. This integration involves, for instance, the development of advanced live imaging techniques, innovative temporal omics methodologies, and novel computational tools. This article advocates integrating temporal dynamics into cancer research. Rather than relying on static snapshots, researchers should increasingly consider adopting dynamic methods—such as live imaging, temporal omics, and liquid biopsies—to track how tumors evolve over time. These continuous approaches could reveal hidden patterns in cancer progression and metastasis, paving the way for more effective, personalized treatments.

Membrane microdomains (lipid rafts) are now recognized as critical for proper compartmentalization of insulin signaling. We previously demonstrated that, in adipocytes in a state of TNFα-induced insulin resistance, the inhibition of insulin metabolic signaling and the elimination of insulin receptors (IR) from the caveolae microdomains were associated with an accumulation of the ganglioside GM3. To gain insight into molecular mechanisms behind interactions of IR, caveolin-1 (Cav1), and GM3 in adipocytes, we have performed immunoprecipitations, cross-linking studies of IR and GM3, and live cell studies using total internal reflection fluorescence microscopy and fluorescence recovery after photobleaching techniques. We found that (i) IR form complexes with Cav1 and GM3 independently; (ii) in GM3-enriched membranes the mobility of IR is increased by dissociation of the IR-Cav1 interaction; and (iii) the lysine residue localized just above the transmembrane domain of the IR β-subunit is essential for the interaction of IR with GM3. Because insulin metabolic signal transduction in adipocytes is known to be critically dependent on caveolae, we propose a pathological feature of insulin resistance in adipocytes caused by dissociation of the IR-Cav1 complex by the interactions of IR with GM3 in microdomains.

Alternative splicing is a fundamental mechanism that enhances proteomic diversity and modulates gene function, with its dysregulation being a hallmark of numerous diseases. Despite its biological significance, the real‐time monitoring of spliced mRNA isoforms in living cells remains challenging due to limited specificity and sensitivity in existing methods. Herein, we present a Stringent dUPlex‐activated Error‐Robust (SUPER) platform, an in situ, split‐DNAzyme‐based system enabling precise imaging of mRNA splicing events in live cells. SUPER employs an identical parental DNAzyme reassembled via isoform‐specific intron‐exon junctions, providing high‐fidelity discrimination of closely related splicing variants. Its dual‐site‐activated fluorescence design ensures error‐robust, background‐minimized imaging with spatial colocalization as an intrinsic validation mechanism. Beyond dynamic isoform profiling, the programmable nature of SUPER enables its conversion into a spatially confined catalytic antenna, locally activating therapeutic aptamers without affecting off‐target transcripts. This approach further allows for real‐time tracking of variant integrity and decay by monitoring subtle changes in probe colocalization. Our platform offers a powerful tool for dissecting splicing mechanisms and holds promise for therapeutic intervention in splicing‐associated diseases by enabling isoform‐selective gene regulation while mitigating oligonucleotide toxicity. A Stringent dUPlex‐activated Error Robust (SUPER) DNAzyme system enables real‐time imaging of alternative mRNA splicing (e.g., Bcl‐xL/Bcl‐xS) in living cells via target‐triggered split‐DNAzyme reassembly and dual‐color fluorescence. It also achieves mRNA‐selective knockdown through DNAzyme‐based gene regulation, serving as a versatile tool for splicing dynamics research and RNA‐guided precision medicine.

Incorporating mechanical stretching of cells in tissue culture is crucial for mimicking (patho)‐physiological conditions and understanding the mechanobiological responses of cells, which can have significant implications in areas like tissue engineering and regenerative medicine. Despite the growing interest, most available cell‐stretching devices are not compatible with automated live‐cell imaging, indispensable for characterizing alterations in the dynamics of various important cellular processes. In this work, StretchView is presented, a multi‐axial cell‐stretching platform compatible with automated, time‐resolved live‐cell imaging. Using StretchView, long‐term image acquisition of cells in the relaxed and stretched states is shown for the first time (experimental time of 12 h) without the need for human intervention. Homogeneous and stable strain fields are demonstrated for 18 h of cyclic stretching, highlighting the platform's versatility and robustness. As proof‐of‐principle, the effect of stretching on cell kinematics and spatiotemporal localization of the cell‐cell adhesion protein E‐cadherin is examined for MDCK cells in monolayer. First evidence of a monotonic increase in junctional E‐cadherin localization upon exposure to stretch is presented using live‐cell imaging data acquired during cyclic stretching, suggestive of an increase in barrier integrity of the monolayer. These findings highlight the potential of StretchView in providing insights into cell mechanobiology and beyond. StretchView is presented, a multi‐axial cell‐stretching platform compatible with automated live‐cell imaging during cyclic stretching. Using StretchView, long‐term image acquisition of epithelial cells and fluorescent tracer beads in relaxed and stretched cell culture membrane states is shown. These capabilities position StretchView as a valuable tool for gaining insights into the dynamics of biomechanically regulated cellular processes.

Thermal heating of biological samples allows to reversibly manipulate cellular processes with high temporal and spatial resolution. Manifold heating techniques in combination with live‐cell imaging were developed, commonly tailored to customized applications. They include Peltier elements and microfluidics for homogenous sample heating as well as infrared lasers and radiation absorption by nanostructures for spot heating. A prerequisite of all techniques is that the induced temperature changes are measured precisely which can be the main challenge considering subcellular structures or multicellular organisms as target regions. This article discusses heating and temperature sensing techniques for live‐cell imaging, leading to future applications in cell biology. Thermal modulation in live‐cell imaging with a high spatiotemporal resolution allows the investigation of biomolecular reactions like protein deactivation and unfolding, and cellular processes like calcium signaling. Local changes in temperature are induced via infrared (IR) irradiation of water (direct), magnetic or radiative excitation of absorber material (indirect), or by stage heating and they can be monitored by optical thermometry.