Molecular Biology of the Cell最新文献

The ESCRT machinery mediates membrane remodeling in fundamental cellular processes, including cytokinesis, endosomal sorting, nuclear envelope reformation, and membrane repair. Membrane constriction and scission are driven by the filament-forming ESCRT-III complex and the AAA-ATPase VPS4. Although ESCRT-III-driven membrane scission is generally established, the mechanisms governing the assembly and coordination of its 12 mammalian isoforms in cells remain poorly understood. Here, we examined the spatial organization and interdependence of ESCRT-III subunits during mammalian cytokinetic abscission by depleting CHMP2A, a core ESCRT-III component. Using live cell imaging, structured illumination microscopy (SIM) and correlative light-electron microscopy, we show that CHMP2A knockout cells display a significant delay-but not failure-in abscission, accompanied by distinct mislocalization phenotypes across ESCRT-III subunits. While IST1 and CHMP2B were minimally disrupted, CHMP4B, CHMP3, and CHMP1B display progressively severe organization defects at the abscission site. Dual-protein imaging reveals disrupted coordination between ESCRT-III subunits in individual CHMP2A-deficient cells, supporting an ordered assembly of ESCRT-III subunits in cytokinetic abscission. Together, our findings provide the first in vivo evidence for hierarchical assembly of ESCRT-III subunits during ESCRT-mediated membrane remodeling and identify CHMP2A as a key organizer of ESCRT-III architecture essential for timely membrane abscission.

Deep learning-based segmentation models can accelerate the analysis of high-throughput microscopy data by automatically identifying and classifying cells in images. However, the datasets needed to train these models are typically assembled via laborious hand-annotation. This limits their scale and diversity, which in turn limits model performance. We present Cell-APP (Cellular Annotation and Perception Pipeline), a tool that automates the annotation of high-quality training data for transmitted-light (TL) cell segmentation. Cell-APP uses two inputs-paired TL and nuclear fluorescence images-and operates in two main steps. First, it extracts each cell's location from the nuclear fluorescence channel and provides these locations to promptable deep learning models to generate cell masks. Then, it classifies each cell as mitotic or nonmitotic based on nuclear features. Together, these masks and classifications form the basis for cell segmentation training data. By training vision-transformer-based models on Cell-APP-generated datasets, we demonstrate how Cell-APP enables the creation of both cell line-specific and multi-cell line segmentation models. Cell-APP thus empowers laboratories to tailor cell segmentation models to their needs and outlines a scalable path to creating general models for the research community.

Genome editing has enabled the integration of fluorescent protein coding sequences into genomes, resulting in expression of in-frame fusion proteins under the control of their natural gene regulatory sequences. While this technique overcomes the well-documented artifacts associated with gene overexpression for biological processes sensitive to altered protein stoichiometry, such as clathrin-mediated endocytosis (CME), editing genomes of metazoan cells incurs a significant time cost compared with simpler organisms, such as yeast. Editing two or more genes to express multiple fluorescent fusion proteins in a single cell line has proven to be a powerful strategy for uncovering spatial dynamic, and therefore functional, relationships among different proteins, but it can take many months to edit each gene within the same cell line. Here, by utilizing cell fusions, we quickly generated cells expressing pairwise permutations of fluorescent fusion proteins in genome-edited human cells to reveal previously undetected protein-organelle interactions. We fused human induced pluripotent stem cells (hiPSCs) that express in-frame fusions of CME and actin cytoskeleton proteins with hiPSCs that express fluorescently tagged organelle markers, uncovering novel interactions between CME proteins, branched actin filament networks, and lysosomes.

The parasite Cryptosporidium causes severe diarrheal disease that can be life-threatening, and effective treatments are sorely lacking. Recently, aspartyl proteases (ASP) have emerged as targets with significant therapeutic potential in several related parasites, resulting in the development of multiple potent leads. ASPs are critical to the proteolytic activation and maturation of secretory proteins that parasites rely on to invade, manipulate, and upon completion of their replication cycle, exit the host cells in which they reside. The Cryptosporidium genome encodes five ASPs, which have not been previously studied. Here, we explore two of these enzymes and in genetic experiments find one, CpASP2, to be essential to parasite growth. Conditional deletion of the gene encoding this protease leads to arrest at two distinct points in the lifecycle. Cell biological studies of the mutant phenotype demonstrate that CpASP2 is required for egress of both asexual merozoites and male gametes. Mutant parasites appear to complete intracellular development yet are paralyzed and incapable of responding to stimuli that trigger motility and egress in wild-type. Ablation of CpASP2 in infected mice leads to rapid parasite clearance, highlighting the promise of CpASP2 and likely additional related enzymes as multistage targets of therapy.

Successful cutaneous wound healing requires reepithelialization by keratinocytes using a coordinated migratory process called keratinocyte collective cell migration (KCCM). Environmental stresses such as wounding induce the integrated stress response (ISR) initiated by protein kinases that phosphorylate the α subunit of eIF2 and mitigate translational control to alleviate stress damage. We previously reported that the ISR protein kinase GCN2 (EIF2AK4) facilitates KCCM via sustained phosphorylation of eIF2α and coordinated production of reactive oxygen species and amino acid transport. In this study, we show that a second ISR protein kinase, PERK (EIF2AK3), also contributes to KCCM. PERK promotes KCCM by protein-protein interactions requiring the cytoplasmic portion of PERK but independent of its catalytic functions. To discern these PERK interactions, we used BioID proximity labeling, immunoprecipitation analyses, and immunofluorescence microscopy to show that PERK interacts with multiple cell adhesion and cytoskeletal complexes important for KCCM. PERK engages with the hemidesmosome proteins ITGA6, ITGB4, COLXVII, and the desmosome proteins JUP, DSG2, and DSG3. Loss of PERK disrupts expression and localization of these cell adhesion proteins, which alters keratinocyte morphology and increases cell-substrate and intercellular adhesions. Our results define an underappreciated scaffolding function for PERK involving cell adhesions that are critical for KCCM.

Meiosis is a source of genetic variation in eukaryotes. Meiosis in the eukaryotic fission yeast Schizosaccharomyces pombe leads to the formation of spores that are particularly resistant to environmental stresses. In addition to external factors, internal processes may nevertheless contribute to cellular stress and impact the genome. This study investigates the role of Pnu1 as the major meiotic nuclease in S. pombe. Transcription and cellular expression of Pnu1 are regulated upon specific phases of meiosis, while its mitochondrial localization is also altered during this process. As a result, Pnu1 induces fragmentation of both genomic and mitochondrial DNA in the postmeiotic phase. This sugar-nonspecific endonuclease generates random double-strand breaks across the genome, an activity that appears to be mediated by direct interaction with chromatin. Given the high spore viability (∼95%) and the widespread occurrence of this phenomenon, this fragmentation appears to be physiological rather than apoptotic as observed in mammals. EndoG is the mammalian homologue of Pnu1 and is a caspase-independent apoptotic endonuclease that can allow cell survival. This study further describes the dynamics of Pnu1 action and supports the conclusion that Pnu1 is a major meiotic endonuclease of S. pombe responsible for a transient postmeiotic fragmentation of cellular DNA, potentially contributing to genetic variability.

Neuronal trafficking pathways must operate with high fidelity and speed, adapting to the dynamic demands of synaptic activity to maintain stable functionality. The biogenesis of lysosome-related organelles complex 1 (BLOC-1) is an attractive candidate to stabilize synaptic function during such challenges. BLOC-1 is an evolutionarily conserved protein complex composed of eight subunits involved in vesicle trafficking. In the nervous system, the BLOC-1 is associated with neurodevelopmental diseases and synaptic plasticity. However, the functions of each BLOC-1 component remain enigmatic. Here, we use CRISPR to mutate each Drosophila BLOC-1 gene to investigate roles in synaptic growth, function, and homeostatic plasticity. First, we show that BLOC-1 mutations are viable, with no defects in synaptic growth, morphology, or baseline function. We then demonstrate distinct synaptic localization patterns of BLOC-1 components. Finally, we show that only two of the eight BLOC-1 components, dysbindin and snapin, are necessary for presynaptic homeostatic potentiation. These results indicate separable functions and distinct synaptic localization patterns of BLOC-1 subunits, and a need to reconsider predictions made from biochemical models of BLOC-1.

To enable effective cell migration, local cell protrusion has to be coordinated with local cell attachment. Here, we investigate spatiotemporal activity patterns of key regulators of cell protrusion and adhesion, the small GTPases Rac and Rap, in migrating cells. These analyses show that Rac activity correlates very tightly with instantaneous cell protrusion events, while the Rap activity stays elevated for prolonged time periods after protrusion and is also detectable before cell protrusion. Direct analysis of activity cross-talk in living cells via light-based perturbation methods revealed that Rap can efficiently activate Rac; however, reciprocal cross-talk from Rac to Rap was not detectable. These findings suggest that Rap plays an instructive role in the generation of cell protrusions by its ability to activate Rac. Furthermore, prolonged Rap activity suggests that this molecule also plays a role in maintenance or stabilization of cell protrusions. Indeed, analysis of Rap1-depleted A431 cells revealed a significant reduction of cell attachment, suggesting that Rap-stimulated cell adhesion can stabilize newly formed protrusions. Taken together, our study suggests a mechanism, by which cell protrusion is coupled to cell adhesion via unidirectional cross-talk that connects the activity of the small GTPases Rap and Rac.

Growth is the essential vital process that drives life forward and always occurs within cells. Cell growth fuels the cell divisions that drive proliferation of single-celled organisms and growth of multicellular organisms. Mechanisms that control the extent and location of growth within cells generate the extraordinary diversity of cell sizes and shapes seen across the tree of life and within the human body, and nearly all cancers show profound defects in control of cell growth that lead to severe aberrations in cell size and shape. Yet we know little about how cell growth occurs or how it is controlled. For decades we have known how basic building blocks such as amino acids and lipids are built, but an enormous gap has always remained in our understanding of how these building blocks are used to build out cells of highly diverse sizes and shapes under varying environmental conditions and in diverse developmental contexts. Given the fundamental importance of growth in biology and cancer, our minimal understanding of cell growth is a growing problem. Here, a few of the intriguing and important questions about cell growth are considered.

Electron microscopy is an important technique for the study of synaptic morphology and its relation to synaptic function. The data analysis for this task requires the segmentation of the relevant synaptic structures, such as synaptic vesicles (SV), active zones, mitochondria, presynaptic densities, synaptic ribbons, and synaptic compartments. Previous studies were predominantly based on manual segmentation, which is very time-consuming and prevented the systematic analysis of large datasets. Here, we introduce SynapseNet, a tool for the automatic segmentation and analysis of synapses in electron micrographs. It can reliably segment SVs and other synaptic structures in a wide range of electron microscopy approaches, thanks to a large annotated dataset, which we assembled, and domain adaptation functionality we developed. We demonstrated its capability for (semi-)automatic biological analysis in two applications and made it available as an easy-to-use tool to enable novel data-driven insights into synapse organization and function.