Molecular Biology of the Cell最新文献

Phenotypic heterogeneity-distinct molecular and behavioral variations within a population-significantly influences collective invasion and tumor progression. Here, we use a molecular approach to explore how the underlying metabolic heterogeneity in non-small cell lung cancer (NSCLC) influences invasion and pack patterning. Assessment of  three-dimensional (3D) pack patterning revealed invasive heterogeneity across NSCLC cell lines and patient-derived samples. Flow cytometry identified IL13RA2 as a biomarker for invasive potential, enabling isolation of subpopulations with distinct invasive characteristics. By integrating a cell surface biomarker (IL13RA2±) with mitochondrial membrane potential (TMRM), we identified and isolated three distinct subpopulations. Two-dimensional (2D) analyses revealed differences in mitochondrial polarity and transcriptional programs associated with migration and oxygensensitivity. In 3D, these subpopulations invaded with distinct patterns, from contiguous circular packs to structured chains. Assessments under varied oxygen tension demonstrated that oxygen availability and subpopulation metabolism together influence collective invasion patterning. When recombined at ratios recapitulating the original population, both stochastic and opportunistic cooperative dynamics emerged, dependent on subpopulation composition and oxygen levels. Our molecular approach, integrating cell surface and metabolic characteristics, enables the isolation of unique subpopulations and demonstrates that phenotypic and metabolic heterogeneity, population composition, and oxygen availability collectively pattern invasion packs and drive collective invasion.

Actomyosin rings are specializations of the nonmuscle actomyosin cytoskeleton that drive cell shape changes during division, wound healing, and other events. Contractile rings throughout phylogeny and in a range of cellular contexts are built from conserved components, including nonmuscle myosin II, actin filaments, and cross-linking proteins. To explore whether diverse actomyosin rings generate contractile force and close via a common mechanism, we studied three instances of ring closure within the continuous cytoplasm of the Caenorhabditis elegans syncytial oogenic germline: mitotic cytokinesis of germline stem cells, apoptosis of meiotic compartments, and cellularization of oocytes. The three ring types exhibited distinct closure kinetics and component protein abundance dynamics. We formulated a physical model to relate measured closure speed and molecular composition dynamics to ring active stress and viscosity. We conclude that these ring intrinsic factors vary among the ring types. Our model suggests that motor and nonmotor cross-linkers' abundance and distribution along filaments are important to recapitulate observed closure dynamics. Thus, our findings suggest that across ring closure contexts, fundamental contractile mechanics are conserved, and the magnitude of contractile force is tuned via regulation of ring component abundance and distribution. These results motivate testable hypotheses about cytoskeletal regulation, architecture, and remodeling.

Cell size is strongly correlated with several biological processes, including the cell cycle and growth. Here, we investigated the regulation of stem cell size during Drosophila central nervous system (CNS) development and its association with cell fate. We note that neural stem cells (NSC) in different regions of the ventral nerve cord increase their size at different rates. Thoracic NSCs grow at a faster rate compared with those in the abdominal region during larval development. We show that in addition to the known role in apoptosis and nervous system remodeling, larval expression of abdA is crucial in regulating the rate of postembryonic NSCs size increase, their timely exit from G₂ phase and mitotic rate. We demonstrate that when abdA expression is lost in abdominal NSCs, their size increases, they exhibit a shorter G₂ phase, enter mitosis earlier, and divide more rapidly. Conversely, the introduction of abdA in thoracic NSCs slows their growth and delays their entry into mitosis. We demonstrate that abdA-mediated NSC size regulation acts downstream of their nutrition-induced activation, thereby fine-tuning the stem cell potential spatiotemporally. This study highlights the instructive role of abdA in regulating various fates of larval NSCs during CNS patterning.

At the end of the 19th century, Rayleigh and Plateau explained the physical principle behind the fragmentation of a liquid jet into regular droplets. The classical Rayleigh-Plateau instability concerns liquid jets governed by inertia and surface tension, whereas biological tubes are membrane-bounded and inertia-free. We therefore refer to the process observed here as a pearling instability, formally analogous to Rayleigh-Plateau but dominated by membrane mechanics. Although pearling-type instabilities have long been recognized in lipid tubes and some biological systems, a clear physiological example remained elusive. Here, we present results showing that pearling instability occurs during the physiological process of platelet formation. Platelets are formed from megakaryocytes by the extension of long protrusions, called proplatelets. As they extend in the bloodstream, proplatelets become pearled and detach, circulating in the peripheral blood before their fragmentation into calibrated platelets. We propose that this pearling, by creating regular constrictions along proplatelets, is key to the process of proplatelet fragmentation into individual platelets of calibrated size. Pearling instability thus acts as a mechanobiological regulator allowing local delivery of the right size platelets to the right place at the right time. Our observations quantitatively match parameter-free theoretical predictions for membrane pearling, supporting a unified physical picture.

Mitochondrial networks exhibit remarkable dynamics that are driven in part by fission and fusion events. However, there are other reorganizations of the network that do not involve fission and fusion. One such exception is the elusive "beads-on-a-string" morphological transition of mitochondria. During such transitions, the cylindrical tubes of the mitochondrial membrane transiently undergo shape changes to a string of "pearls" connected along thin tubes. These dynamics have been observed in many contexts and given disparate explanations. Here, we unify these observations by proposing a common underlying mechanism based on the biophysical properties of tubular fluid membranes, for which it is known that, under particular regimes of tension and pressure, membranes reach an instability and undergo a shape transition to a string of connected pearls. First, we use high-speed light-sheet microscopy to show that transient, short-lived pearling events occur spontaneously in the mitochondrial network in every cell type we have examined, including during T-cell activation, neuronal firing, and replicative senescence. This high-temporal data reveals two distinct classes of spontaneous pearling, triggered either by ionic flux or cytoskeleton tension. We then induce pearling with chemical, genetic, and mechanical perturbations and establish three main physical causes of mitochondrial pearling: 1) ionic flux producing internal osmotic pressure, 2) membrane packing lowering bending elasticity, and 3) external mechanical force increasing membrane tension. Pearling dynamics thereby reveal a fundamental biophysical facet of mitochondrial biology. We suggest that pearling should take its place beside fission and fusion as a key process of mitochondrial dynamics, with implications for physiology, disease, and aging.

Alternative splicing expands proteomic diversity and is tightly regulated by splicing factors, including the serine/arginine-rich (SR) protein family. Here, we analyze the poorly characterized protein SRSF12. Although SRSF12 is conserved across vertebrates, it is lowly expressed in most mammals, and we find that SRSF12 knockout mice do not display overt physiological or transcriptomic alterations. In contrast, SRSF12 is more highly expressed in primates, where it is predominantly transcribed in the testes, oocytes, and brain. SRSF12 colocalizes with other splicing components to nuclear speckles and interacts with splicing regulatory factors in cultured human cells. Strikingly, ectopic expression of SRSF12 in human cells induces widespread transcriptional changes, activating meiosis-, testis-, and brain-specific genes. SRSF12 overexpression also leads to mitotic arrest and cell death, phenotypes that require both its structured RNA recognition motif and intrinsically disordered arginine/serine-rich C-terminal domain. Together, our results suggest that SRSF12 has evolved primate-specific expression to regulate testis- and brain-specific genes.

Membrane organelles are dynamic structures that depend on fluid membranes for their integrity and function, with the fluidity primarily derived from loosely packed unsaturated lipids. We investigated how cells respond to lipid saturation and its effect on nuclear dynamics in the budding yeast Saccharomyces cerevisiae. We found that the lipid desaturase mutant ole1-20 upregulates various genes, including OLE1, primarily through the lipid saturation-sensing transcription factor Mga2. The ole1-20 mutant displays prolonged anaphase and impaired nuclear membrane expansion, which can be rescued by the membrane fluidizer glycerol and by enhanced glycerophospholipid synthesis. However, deleting MGA2 or inhibiting de novo glycerophospholipid synthesis exacerbates mitotic phenotypes in ole1-20, leading to mitotic spindle bending, unequal nuclear division, and transient nuclear leakage. Our study underscores the importance of lipid unsaturation in nuclear dynamics during mitosis and highlights the crucial role of Mga2-mediated gene regulation in maintaining glycerophospholipid homeostasis necessary for proper nuclear membrane expansion and division in response to lipid saturation.

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.