Centrosomes consist of a centriole pair surrounded by pericentriolar material (PCM). Previous work suggested that centrioles are required to organize PCM to form a structurally stable organelle. Here, we characterize SAS-4, a centriole component in Caenorhabditis elegans. Like tubulin, SAS-4 is incorporated into centrioles during their duplication and remains stably associated thereafter. In the absence of SAS-4, centriole duplication fails. Partial depletion of SAS-4 results in structurally defective centrioles that contain reduced levels of SAS-4 and organize proportionally less PCM. Thus, SAS-4 is a centriole-associated component whose amount dictates centrosome size. These results provide novel insight into the poorly understood role of centrioles as centrosomal organizers.

Centrosomes are non-membrane-bound compartments that nucleate microtubule arrays. They consist of nanometer-scale centrioles surrounded by a micron-scale, dynamic assembly of protein called the pericentriolar material (PCM). To study how PCM forms a spherical compartment that nucleates microtubules, we reconstituted PCM-dependent microtubule nucleation in vitro using recombinant C. elegans proteins. We found that macromolecular crowding drives assembly of the key PCM scaffold protein SPD-5 into spherical condensates that morphologically and dynamically resemble in vivo PCM. These SPD-5 condensates recruited the microtubule polymerase ZYG-9 (XMAP215 homolog) and the microtubule-stabilizing protein TPXL-1 (TPX2 homolog). Together, these three proteins concentrated tubulin ∼4-fold over background, which was sufficient to reconstitute nucleation of microtubule asters in vitro. Our results suggest that in vivo PCM is a selective phase that organizes microtubule arrays through localized concentration of tubulin by microtubule effector proteins.

High-content screening for gene profiling has generally been limited to single cells. Here, we explore an alternative approach-profiling gene function by analyzing effects of gene knockdowns on the architecture of a complex tissue in a multicellular organism. We profile 554 essential C. elegans genes by imaging gonad architecture and scoring 94 phenotypic features. To generate a reference for evaluating methods for network construction, genes were manually partitioned into 102 phenotypic classes, predicting functions for uncharacterized genes across diverse cellular processes. Using this classification as a benchmark, we developed a robust computational method for constructing gene networks from high-content profiles based on a network context-dependent measure that ranks the significance of links between genes. Our analysis reveals that multi-parametric profiling in a complex tissue yields functional maps with a resolution similar to genetic interaction-based profiling in unicellular eukaryotes-pinpointing subunits of macromolecular complexes and components functioning in common cellular processes.

Cells sense elevated temperatures and mount an adaptive heat shock response that involves changes in gene expression, but the underlying mechanisms, particularly on the level of translation, remain unknown. Here we report that, in budding yeast, the essential translation initiation factor Ded1p undergoes heat-induced phase separation into gel-like condensates. Using ribosome profiling and an in vitro translation assay, we reveal that condensate formation inactivates Ded1p and represses translation of housekeeping mRNAs while promoting translation of stress mRNAs. Testing a variant of Ded1p with altered phase behavior as well as Ded1p homologs from diverse species, we demonstrate that Ded1p condensation is adaptive and fine-tuned to the maximum growth temperature of the respective organism. We conclude that Ded1p condensation is an integral part of an extended heat shock response that selectively represses translation of housekeeping mRNAs to promote survival under conditions of severe heat stress.

The organization of a cell emerges from the interactions in protein networks. The interactome is critically dependent on the strengths of interactions and the cellular abundances of the connected proteins, both of which span orders of magnitude. However, these aspects have not yet been analyzed globally. Here, we have generated a library of HeLa cell lines expressing 1,125 GFP-tagged proteins under near-endogenous control, which we used as input for a next-generation interaction survey. Using quantitative proteomics, we detect specific interactions, estimate interaction stoichiometries, and measure cellular abundances of interacting proteins. These three quantitative dimensions reveal that the protein network is dominated by weak, substoichiometric interactions that play a pivotal role in defining network topology. The minority of stable complexes can be identified by their unique stoichiometry signature. This study provides a rich interaction dataset connecting thousands of proteins and introduces a framework for quantitative network analysis.

Understanding the in vivo dynamics of protein localization and their physical interactions is important for many problems in biology. To enable systematic protein function interrogation in a multicellular context, we built a genome-scale transgenic platform for in vivo expression of fluorescent- and affinity-tagged proteins in Caenorhabditis elegans under endogenous cis regulatory control. The platform combines computer-assisted transgene design, massively parallel DNA engineering, and next-generation sequencing to generate a resource of 14,637 genomic DNA transgenes, which covers 73% of the proteome. The multipurpose tag used allows any protein of interest to be localized in vivo or affinity purified using standard tag-based assays. We illustrate the utility of the resource by systematic chromatin immunopurification and automated 4D imaging, which produced detailed DNA binding and cell/tissue distribution maps for key transcription factor proteins.

Microtubule behavior changes during the cell cycle and during spindle assembly. However, it remains unclear how these changes are regulated and coordinated. We describe a complex that targets the Protein Phosphatase 2A holoenzyme (PP2A) to centrosomes in C. elegans embryos. This complex includes Regulator of Spindle Assembly 1 (RSA-1), a targeting subunit for PP2A, and RSA-2, a protein that binds and recruits RSA-1 to centrosomes. In contrast to the multiple functions of the PP2A catalytic subunit, RSA-1 and RSA-2 are specifically required for microtubule outgrowth from centrosomes and for spindle assembly. The centrosomally localized RSA-PP2A complex mediates these functions in part by regulating two critical mitotic effectors: the microtubule destabilizer KLP-7 and the C. elegans regulator of spindle assembly TPXL-1. By regulating a subset of PP2A functions at the centrosome, the RSA complex could therefore provide a means of coordinating microtubule outgrowth from centrosomes and kinetochore microtubule stability during mitotic spindle assembly.

Stressed cells shut down translation, release mRNA molecules from polysomes, and form stress granules (SGs) via a network of interactions that involve G3BP. Here we focus on the mechanistic underpinnings of SG assembly. We show that, under non-stress conditions, G3BP adopts a compact auto-inhibited state stabilized by electrostatic intramolecular interactions between the intrinsically disordered acidic tracts and the positively charged arginine-rich region. Upon release from polysomes, unfolded mRNAs outcompete G3BP auto-inhibitory interactions, engendering a conformational transition that facilitates clustering of G3BP through protein-RNA interactions. Subsequent physical crosslinking of G3BP clusters drives RNA molecules into networked RNA/protein condensates. We show that G3BP condensates impede RNA entanglement and recruit additional client proteins that promote SG maturation or induce a liquid-to-solid transition that may underlie disease. We propose that condensation coupled to conformational rearrangements and heterotypic multivalent interactions may be a general principle underlying RNP granule assembly.

P granules are non-membrane-bound RNA-protein compartments that are involved in germline development in C. elegans. They are liquids that condense at one end of the embryo by localized phase separation, driven by gradients of polarity proteins such as the mRNA-binding protein MEX-5. To probe how polarity proteins regulate phase separation, we combined biochemistry and theoretical modeling. We reconstitute P granule-like droplets in vitro using a single protein PGL-3. By combining in vitro reconstitution with measurements of intracellular concentrations, we show that competition between PGL-3 and MEX-5 for mRNA can regulate the formation of PGL-3 droplets. Using theory, we show that, in a MEX-5 gradient, this mRNA competition mechanism can drive a gradient of P granule assembly with similar spatial and temporal characteristics to P granule assembly in vivo. We conclude that gradients of polarity proteins can position RNP granules during development by using RNA competition to regulate local phase separation.

Many protein-protein interactions are mediated through independently folding modular domains. Proteome-wide efforts to model protein-protein interaction or "interactome" networks have largely ignored this modular organization of proteins. We developed an experimental strategy to efficiently identify interaction domains and generated a domain-based interactome network for proteins involved in C. elegans early-embryonic cell divisions. Minimal interacting regions were identified for over 200 proteins, providing important information on their domain organization. Furthermore, our approach increased the sensitivity of the two-hybrid system, resulting in a more complete interactome network. This interactome modeling strategy revealed insights into C. elegans centrosome function and is applicable to other biological processes in this and other organisms.

Proteins such as FUS phase separate to form liquid-like condensates that can harden into less dynamic structures. However, how these properties emerge from the collective interactions of many amino acids remains largely unknown. Here, we use extensive mutagenesis to identify a sequence-encoded molecular grammar underlying the driving forces of phase separation of proteins in the FUS family and test aspects of this grammar in cells. Phase separation is primarily governed by multivalent interactions among tyrosine residues from prion-like domains and arginine residues from RNA-binding domains, which are modulated by negatively charged residues. Glycine residues enhance the fluidity, whereas glutamine and serine residues promote hardening. We develop a model to show that the measured saturation concentrations of phase separation are inversely proportional to the product of the numbers of arginine and tyrosine residues. These results suggest it is possible to predict phase-separation properties based on amino acid sequences.

Single-cell (sc)RNA-seq, together with RNA velocity and metabolic labeling, reveals cellular states and transitions at unprecedented resolution. Fully exploiting these data, however, requires kinetic models capable of unveiling governing regulatory functions. Here, we introduce an analytical framework dynamo (https://github.com/aristoteleo/dynamo-release), which infers absolute RNA velocity, reconstructs continuous vector fields that predict cell fates, employs differential geometry to extract underlying regulations, and ultimately predicts optimal reprogramming paths and perturbation outcomes. We highlight dynamo's power to overcome fundamental limitations of conventional splicing-based RNA velocity analyses to enable accurate velocity estimations on a metabolically labeled human hematopoiesis scRNA-seq dataset. Furthermore, differential geometry analyses reveal mechanisms driving early megakaryocyte appearance and elucidate asymmetrical regulation within the PU.1-GATA1 circuit. Leveraging the least-action-path method, dynamo accurately predicts drivers of numerous hematopoietic transitions. Finally, in silico perturbations predict cell-fate diversions induced by gene perturbations. Dynamo, thus, represents an important step in advancing quantitative and predictive theories of cell-state transitions.

Negative-stranded RNA viruses can establish long-term persistent infection in the form of large intracellular inclusions in the human host and cause chronic diseases. Here, we uncover how cellular stress disrupts the metastable host-virus equilibrium in persistent infection and induces viral replication in a culture model of mumps virus. Using a combination of cell biology, whole-cell proteomics, and cryo-electron tomography, we show that persistent viral replication factories are dynamic condensates and identify the largely disordered viral phosphoprotein as a driver of their assembly. Upon stress, increased phosphorylation of the phosphoprotein at its interaction interface with the viral polymerase coincides with the formation of a stable replication complex. By obtaining atomic models for the authentic mumps virus nucleocapsid, we elucidate a concomitant conformational change that exposes the viral genome to its replication machinery. These events constitute a stress-mediated switch within viral condensates that provide an environment to support upregulation of viral replication.

Functional genomics efforts face tradeoffs between number of perturbations examined and complexity of phenotypes measured. We bridge this gap with Perturb-seq, which combines droplet-based single-cell RNA-seq with a strategy for barcoding CRISPR-mediated perturbations, allowing many perturbations to be profiled in pooled format. We applied Perturb-seq to dissect the mammalian unfolded protein response (UPR) using single and combinatorial CRISPR perturbations. Two genome-scale CRISPR interference (CRISPRi) screens identified genes whose repression perturbs ER homeostasis. Subjecting ∼100 hits to Perturb-seq enabled high-precision functional clustering of genes. Single-cell analyses decoupled the three UPR branches, revealed bifurcated UPR branch activation among cells subject to the same perturbation, and uncovered differential activation of the branches across hits, including an isolated feedback loop between the translocon and IRE1α. These studies provide insight into how the three sensors of ER homeostasis monitor distinct types of stress and highlight the ability of Perturb-seq to dissect complex cellular responses.