Distinct H3K9me3 heterochromatin maintenance dynamics govern different gene programs and repeats in pluripotent cells.

H3K9me3-heterochromatin, established by lysine methyltransferases (KMTs) and compacted by HP1 isoforms, represses alternative lineage genes and DNA repeats. Our understanding of H3K9me3-heterochromatin stability is presently limited to individual domains and DNA repeats. We engineered Suv39h2 KO mouse embryonic stem cells to degrade remaining two H3K9me3- KMTs within one hour and found that both passive dilution and active removal contribute to H3K9me3 decay within 12-24 hours. We discovered four different H3K9me3 decay rates across the genome and chromatin features and transcription factor binding patterns that predict the stability classes. A "binary switch" governs heterochromatin compaction, with HP1 rapidly dissociating from heterochromatin upon KMTs' depletion and a particular threshold level of HP1 limiting pioneer factor binding, chromatin opening, and exit from pluripotency within 12 hr. Unexpectedly, receding H3K9me3 domains unearth residual HP1ß peaks enriched with heterochromatin-inducing proteins. Our findings reveal distinct H3K9me3-heterochromatin maintenance dynamics governing gene networks and repeats that together safeguard pluripotency.

High-throughput optimized prime editing mediated endogenous protein tagging for pooled imaging of protein localization.

The subcellular organization of proteins carries important information on cellular state and gene function, yet currently there are no technologies that enable accurate measurement of subcellular protein localizations at scale. Here we develop an approach for pooled endogenous protein tagging using prime editing, which coupled with an optical readout and sequencing, provides a snapshot of proteome organization in a manner akin to perturbation-based CRISPR screens. We constructed a pooled library of 17,280 pegRNAs designed to exhaustively tag 60 endogenous proteins spanning diverse localization patterns and explore a large space of genomic and pegRNA design parameters. Pooled measurements of tagging efficiency uncovered both genomic and pegRNA features associated with increased efficiency, including epigenetic states and interactions with transcription. We integrate pegRNA features into a computational model with predictive value for tagging efficiency to constrain the design space of pegRNAs for large-scale peptide knock-in. Lastly, we show that combining in-situ pegRNA sequencing with high-throughput deep learning image analysis, enables exploration of subcellular protein localization patterns for many proteins in parallel following a single pooled lentiviral transduction, setting the stage for scalable studies of proteome dynamics across cell types and environmental perturbations.

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.