Mitochondria cannot be generated de novo; they must grow, replicate their genome, and divide in order to be inherited to each daughter cell during mitosis. Mitochondrial division is a structural challenge that requires a massive remodeling of membrane morphology 1–3. Although division factors differ across organisms, the need for multiple constriction steps and a dynamin-related protein (Drp1, Dnm1 in yeast) has been conserved 4–6. In mammalian cells, mitochondrial division has been shown to proceed with at least two sequential constriction steps: 1. endoplasmic reticulum (ER) and actin collaborate to generate constrictions suitable for Drp1 assembly; 2. Drp1 further constricts membranes until fission occurs 2,7–9. However, in vitro experiments argue that Drp1 does not have the dynamic range to complete membrane fission per se 7. In contrast to Drp1, the neuronal-specific classical Dynamin-1 (Dyn1) has been shown to assemble on narrower lipid profiles and facilitates spontaneous membrane fission upon GTP hydrolysis 10,11. Here we discovered that the ubiquitously-expressed classical Dynamin-2 (Dyn2) is a fundamental component of the mitochondrial division machinery. A combination of live-cell and electron microscopy reveals that Dyn2 works in concert with Drp1 to orchestrate sequential constriction events leading up to division. Our work underscores the biophysical limitations of Drp1 and positions Dyn2, which has intrinsic membrane fission properties, at the final step of mitochondrial division.

The endoplasmic reticulum (ER) has a remarkably complex structure, composed of a single bilayer that forms the nuclear envelope, along with a network of sheets and dynamic tubules. Our understanding of the biological significance of the complex architecture of the ER has improved dramatically in the last few years. The identification of proteins and forces required for maintaining ER shape, as well as more advanced imaging techniques, has allowed the relationship between ER shape and function to come into focus. These studies have also revealed unexpected new functions of the ER and novel ER domains regulating alterations in ER dynamics. The importance of ER structure has become evident as recent research has identified diseases linked to mutations in ER-shaping proteins. In this review, we discuss what is known about the maintenance of ER architecture, the relationship between ER structure and function, and diseases associated with defects in ER structure.

Mitochondria are dynamic organelles that undergo constant remodeling through the regulation of two opposing processes, mitochondrial fission and fusion. Although several key regulators and physiological stimuli have been identified to control mitochondrial fission and fusion, the role of mitochondrial morphology in the two processes remains to be determined. To address this knowledge gap, we investigated whether morphological features extracted from time-lapse live-cell images of mitochondria could be used to predict mitochondrial fate. That is, we asked if we could predict whether a mitochondrion is likely to participate in a fission or fusion event based on its current shape and local environment. Using live-cell microscopy, image analysis software, and supervised machine learning, we characterized mitochondrial dynamics with single-organelle resolution to identify features of mitochondria that are predictive of fission and fusion events. A random forest (RF) model was trained to correctly classify mitochondria poised for either fission or fusion based on a series of morphological and positional features for each organelle. Of the features we evaluated, mitochondrial perimeter positively correlated with mitochondria about to undergo a fission event. Similarly mitochondrial solidity (compact shape) positively correlated with mitochondria about to undergo a fusion event. Our results indicate that fission and fusion are positively correlated with mitochondrial morphological features; and therefore, mitochondrial fission and fusion may be influenced by the mechanical properties of mitochondrial membranes.

Secretory cargo is recognized, concentrated and trafficked from endoplasmic reticulum (ER) exit sites (ERES) to the Golgi. Cargo export from the ER begins when a series of highly conserved COPII coat proteins accumulate at the ER and regulate the formation of cargo-loaded COPII vesicles. In animal cells, capturing live de novo cargo trafficking past this point is challenging; it has been difficult to discriminate whether cargo is trafficked to the Golgi in a COPII-coated vesicle. Here, we describe a recently developed live-cell cargo export system that can be synchronously released from ERES to illustrate de novo trafficking in animal cells. We found that components of the COPII coat remain associated with the ERES while cargo is extruded into COPII-uncoated, non-ER associated, Rab1 (herein referring to Rab1a or Rab1b)-dependent carriers. Our data suggest that, in animal cells, COPII coat components remain stably associated with the ER at exit sites to generate a specialized compartment, but once cargo is sorted and organized, Rab1 labels these export carriers and facilitates efficient forward trafficking.This article has an associated First Person interview with the first author of the paper.

Macroautophagy (autophagy) is a cellular recycling program essential for homeostasis and survival during cytotoxic stress. This process, which has an emerging role in disease etiology and treatment, is executed in four stages through the coordinated action of more than 30 proteins. An effective strategy for studying complicated cellular processes, such as autophagy, involves the construction and analysis of mathematical or computational models. When developed and refined from experimental knowledge, these models can be used to interrogate signaling pathways, formulate novel hypotheses about systems, and make predictions about cell signaling changes induced by specific interventions. Here, we present the development of a computational model describing autophagic vesicle dynamics in a mammalian system. We used time-resolved, live-cell microscopy to measure the synthesis and turnover of autophagic vesicles in single cells. The stochastically simulated model was consistent with data acquired during conditions of both basal and chemically-induced autophagy. The model was tested by genetic modulation of autophagic machinery and found to accurately predict vesicle dynamics observed experimentally. Furthermore, the model generated an unforeseen prediction about vesicle size that is consistent with both published findings and our experimental observations. Taken together, this model is accurate and useful and can serve as the foundation for future efforts aimed at quantitative characterization of autophagy.