The vacuolar kinase Yck3 maintains organelle fragmentation by regulating the HOPS tethering complex

The regulation of cellular membrane flux is poorly understood. Yeast respond to hypertonic stress by fragmentation of the normally large, low copy vacuole. We used this phenomenon as the basis for an in vivo screen to identify regulators of vacuole membrane dynamics. We report here that maintenance of the fragmented phenotype requires the vacuolar casein kinase I Yck3: when Yck3 is absent, salt-stressed vacuoles undergo fission, but reassemble in a SNARE-dependent manner, suggesting that vacuole fusion is disregulated. Accordingly, when Yck3 is deleted, in vitro vacuole fusion is increased, and Yck3 overexpression blocks fusion. Morphological and functional studies show that Yck3 modulates the Rab/homotypic fusion and vacuole protein sorting complex (HOPS)-dependent tethering stage of vacuole fusion. Intriguingly, Yck3 mediates phosphorylation of the HOPS subunit Vps41, a bi-functional protein involved in both budding and fusion during vacuole biogenesis. Because Yck3 also promotes efficient vacuole inheritance, we propose that tethering complex phosphorylation is a part of a general, switch-like mechanism for driving changes in organelle architecture

ATP-independent Control of Vac8 Palmitoylation by a SNARE Subcomplex on Yeast Vacuoles

Yeast vacuole fusion requires palmitoylated Vac8. We previously showed that Vac8 acylation occurs early in the fusion reaction, is blocked by antibodies against Sec18 (yeast N-ethylmaleimide-sensitive fusion protein (NSF)), and is mediated by the R-SNARE Ykt6. Here we analyzed the regulation of this reaction on purified vacuoles. We show that Vac8 acylation is restricted to a narrow time window, is independent of ATP hydrolysis by Sec18, and is stimulated by the ion chelator EDTA. Analysis of vacuole protein complexes indicated that Ykt6 is part of a complex distinct from the second R-SNARE, Nyv1. We speculate that during vacuole fusion, Nyv1 is the classical R-SNARE, whereas the Ykt6-containing complex has a novel function in Vac8 palmitoylation

High-throughput ultrastructure screening using electron microscopy and fluorescent barcoding.

Genetic screens using high-throughput fluorescent microscopes have generated large datasets, contributing many cell biological insights. Such approaches cannot tackle questions requiring knowledge of ultrastructure below the resolution limit of fluorescent microscopy. Electron microscopy (EM) reveals detailed cellular ultrastructure but requires time-consuming sample preparation, limiting throughput. Here we describe a robust method for screening by high-throughput EM. Our approach uses combinations of fluorophores as barcodes to uniquely mark each cell type in mixed populations and correlative light and EM (CLEM) to read the barcode of each cell before it is imaged by EM. Coupled with an easy-to-use software workflow for correlation, segmentation, and computer image analysis, our method, called "MultiCLEM," allows us to extract and analyze multiple cell populations from each EM sample preparation. We demonstrate several uses for MultiCLEM with 15 different yeast variants. The methodology is not restricted to yeast, can be scaled to higher throughput, and can be used in multiple ways to enable EM to become a powerful screening technique.This work was financially supported by grants from the Deutsche Forschungsgemeinschaft (SFB1129 Z2 to J.A.G. Briggs), EMBL (to J.A.G. Briggs), the Medical Research Council (MC_UP_1201/16 to J.A.G. Briggs), and the German Ministry of Education and Research (031A605 to K.R. Patil). The Schuldiner laboratory is supported by the European Research Council CoG 646604 Peroxisystem, the Deutsche Forschungsgemeinschaft (grant SFB1190 and a Deutsch-Israelische Projektkooperation [DIP] collaborative grant). N. Gabrielli was supported by the EMBL interdisciplinary postdoctoral program. M. Schuldiner is an incumbent of the Dr. Gilbert Omenn and Martha Darling Professorial Chair in Molecular Genetics

The yeast Batten disease orthologue Btn1 controls endosome–Golgi retrograde transport via SNARE assembly

Btn1 controls endosome–Golgi retrograde sorting by regulating SNARE phosphorylation and assembly

Phosphorylation of a membrane curvature–sensing motif switches function of the HOPS subunit Vps41 in membrane tethering

An AP-3–binding site required for vesicle–vacuole fusion is masked when Vps41 is associated with highly curved membranes, such as endosomes, but is exposed at membranes with lower curvature, such as vacuoles, because of phosphorylation of the membrane-binding motif

A tethering complex drives the terminal stage of SNARE-dependent membrane fusion.

Membrane fusion in eukaryotic cells mediates the biogenesis of organelles, vesicular traffic between them, and exo- and endocytosis of important signalling molecules, such as hormones and neurotransmitters. Distinct tasks in intracellular membrane fusion have been assigned to conserved protein systems. Tethering proteins mediate the initial recognition and attachment of membranes, whereas SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) protein complexes are considered as the core fusion engine. SNARE complexes provide mechanical energy to distort membranes and drive them through a hemifusion intermediate towards the formation of a fusion pore. This last step is highly energy-demanding. Here we combine the in vivo and in vitro fusion of yeast vacuoles with molecular simulations to show that tethering proteins are critical for overcoming the final energy barrier to fusion pore formation. SNAREs alone drive vacuoles only into the hemifused state. Tethering proteins greatly increase the volume of SNARE complexes and deform the site of hemifusion, which lowers the energy barrier for pore opening and provides the driving force. Thereby, tethering proteins assume a crucial mechanical role in the terminal stage of membrane fusion that is likely to be conserved at multiple steps of vesicular traffic. We therefore propose that SNAREs and tethering proteins should be considered as a single, non-dissociable device that drives fusion. The core fusion machinery may then be larger and more complex than previously thought

Selecting appropriate reinforcement-learning algorithms for robot manipulation domains

This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 73-78).Engineering reinforcement learning agents for application on a particular target domain requires making decisions such as the learning algorithm and state representation. We empirically study the performance of three reference implementations of model-free reinforcement learning algorithms: Covariance Matrix Adaptation Evolution Strategy, Deep Deterministic Policy Gradients, and Proximal Policy Optimization. We compare their performance on various target domains to measure quantitatively their dependence on varied features of the environment. We study the effect of actuation noise, observation noise, reward sparsity and task horizon. Then, we explore automatically generated state encodings for learning using a lower-dimensional encoding from high dimensional sensor data. A proof-of- concept end-to-end system for scooping beads of different sizes in the real world generates, uses, then follows force traces along with a positional controller to execute a scoop.by Alex Licari LaGrassa.M. Eng.M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienc