CRISPR screen for protein inclusion formation uncovers a role for SRRD in the regulation of intermediate filament dynamics and aggresome assembly.

The presence of large protein inclusions is a hallmark of neurodegeneration, and yet the precise molecular factors that contribute to their formation remain poorly understood. Screens using aggregation-prone proteins have commonly relied on downstream toxicity as a readout rather than the direct formation of aggregates. Here, we combined a genome-wide CRISPR knockout screen with Pulse Shape Analysis, a FACS-based method for inclusion detection, to identify direct modifiers of TDP-43 aggregation in human cells. Our screen revealed both canonical and novel proteostasis genes, and unearthed SRRD, a poorly characterized protein, as a top regulator of protein inclusion formation. APEX biotin labeling reveals that SRRD resides in proximity to proteins that are involved in the formation and breakage of disulfide bonds and to intermediate filaments, suggesting a role in regulation of the spatial dynamics of the intermediate filament network. Indeed, loss of SRRD results in aberrant intermediate filament fibrils and the impaired formation of aggresomes, including blunted vimentin cage structure, during proteotoxic stress. Interestingly, SRRD also localizes to aggresomes and unfolded proteins, and rescues proteotoxicity in yeast whereby its N-terminal low complexity domain is sufficient to induce this affect. Altogether this suggests an unanticipated and broad role for SRRD in cytoskeletal organization and cellular proteostasis.

Pooled tagging and hydrophobic targeting of endogenous proteins for unbiased mapping of unfolded protein responses.

System-level understanding of proteome organization and function requires methods for direct visualization and manipulation of proteins at scale. We developed an approach enabled by high-throughput gene tagging for the generation and analysis of complex cell pools with endogenously tagged proteins. Proteins are tagged with HaloTag to enable visualization or direct perturbation. Fluorescent labeling followed by in situ sequencing and deep learning-based image analysis identifies the localization pattern of each tag, providing a bird's-eye-view of cellular organization. Next, we use a hydrophobic HaloTag ligand to misfold tagged proteins, inducing spatially restricted proteotoxic stress that is read out by single cell RNA sequencing. By integrating optical and perturbation data, we map compartment-specific responses to protein misfolding, revealing inter-compartment organization and direct crosstalk, and assigning proteostasis functions to uncharacterized genes. Altogether, we present a powerful and efficient method for large-scale studies of proteome dynamics, function, and homeostasis.

Model for Interpreting Surface Crystallization Using Quartz Crystal Microbalance: Theory and Experiments.

Surface crystallization of calcium sulfate was investigated using a dissipation crystal quartz microbalance (QCM-D) together with microscopy to understand the mechanical property changes occurring during the growth process. The use of optical microscopy and SEM revealed that needle-shaped crystals grow as clusters on the QCM sensor's surface, not in uniform layers. As crystallization growth progressed, QCM-D revealed inversions between negative and positive frequency shifts. This behavior, a function of the growth of crystals in clusters, is not adequately predicted by existing models. As such, a new mass-to-frequency conversion model is proposed herein to explain the observed frequency inversions. This model is derived from a lumped element approach with point-contact loading and Mason equivalent circuit theory. Critically, the physical phenomena occurring form the basis of the model, particularly addressing the three sources of impedance. When a crystal nucleates and grows, its inertial impedance is considered along with a Kelvin-Voigt link with a hydration layer. A comparison between the proposed model and experimental data, of both frequency and dissipation data for the first four harmonics, shows good agreement for the supersaturations (S = C/C*) of S = 3.75, S = 3.48, and S = 3.22. Additionally, significant improvements over existing models for the case of surface crystallization are observed. The proposed model was therefore able to explain that frequency inversions are caused by a shift from inertia-dominated to elastic-dominated impedance, occurring as a result of crystal growth. Using the nucleation induction time and nucleation rates, determined with imaging, an additional understanding of the crystals' mechanical properties (stiffness and dampening) was obtained.