Machine learning interpretable models of cell mechanics from protein images.

Cellular form and function emerge from complex mechanochemical systems within the cytoplasm. Currently, no systematic strategy exists to infer large-scale physical properties of a cell from its molecular components. This is an obstacle to understanding processes such as cell adhesion and migration. Here, we develop a data-driven modeling pipeline to learn the mechanical behavior of adherent cells. We first train neural networks to predict cellular forces from images of cytoskeletal proteins. Strikingly, experimental images of a single focal adhesion (FA) protein, such as zyxin, are sufficient to predict forces and can generalize to unseen biological regimes. Using this observation, we develop two approaches-one constrained by physics and the other agnostic-to construct data-driven continuum models of cellular forces. Both reveal how cellular forces are encoded by two distinct length scales. Beyond adherent cell mechanics, our work serves as a case study for integrating neural networks into predictive models for cell biology.

Isthmus progenitor cells contribute to homeostatic cellular turnover and support regeneration following intestinal injury.

The currently accepted intestinal epithelial cell organization model proposes that Lgr5+ crypt-base columnar (CBC) cells represent the sole intestinal stem cell (ISC) compartment. However, previous studies have indicated that Lgr5+ cells are dispensable for intestinal regeneration, leading to two major hypotheses: one favoring the presence of a quiescent reserve ISC and the other calling for differentiated cell plasticity. To investigate these possibilities, we studied crypt epithelial cells in an unbiased fashion via high-resolution single-cell profiling. These studies, combined with in vivo lineage tracing, show that Lgr5 is not a specific ISC marker and that stemness potential exists beyond the crypt base and resides in the isthmus region, where undifferentiated cells participate in intestinal homeostasis and regeneration following irradiation (IR) injury. Our results provide an alternative model of intestinal epithelial cell organization, suggesting that stemness potential is not restricted to CBC cells, and neither de-differentiation nor reserve ISC are drivers of intestinal regeneration.

Thiolase: A Versatile Biocatalyst Employing Coenzyme A-Thioester Chemistry for Making and Breaking C-C Bonds.

Thiolases are CoA-dependent enzymes that catalyze the thiolytic cleavage of 3-ketoacyl-CoA, as well as its reverse reaction, which is the thioester-dependent Claisen condensation reaction. Thiolases are dimers or tetramers (dimers of dimers). All thiolases have two reactive cysteines: (a) a nucleophilic cysteine, which forms a covalent intermediate, and (b) an acid/base cysteine. The best characterized thiolase is the Zoogloea ramigera thiolase, which is a bacterial biosynthetic thiolase belonging to the CT-thiolase subfamily. The thiolase active site is also characterized by two oxyanion holes, two active site waters, and four catalytic loops with characteristic amino acid sequence fingerprints. Three thiolase subfamilies can be identified, each characterized by a unique sequence fingerprint for one of their catalytic loops, which causes unique active site properties. Recent insights concerning the thiolase reaction mechanism, as obtained from recent structural studies, as well as from classical and recent enzymological studies, are addressed, and open questions are discussed.

Hallmarks of neurodegenerative diseases.

Decades of research have identified genetic factors and biochemical pathways involved in neurodegenerative diseases (NDDs). We present evidence for the following eight hallmarks of NDD: pathological protein aggregation, synaptic and neuronal network dysfunction, aberrant proteostasis, cytoskeletal abnormalities, altered energy homeostasis, DNA and RNA defects, inflammation, and neuronal cell death. We describe the hallmarks, their biomarkers, and their interactions as a framework to study NDDs using a holistic approach. The framework can serve as a basis for defining pathogenic mechanisms, categorizing different NDDs based on their primary hallmarks, stratifying patients within a specific NDD, and designing multi-targeted, personalized therapies to effectively halt NDDs.

A neural circuit for male sexual behavior and reward.

Male sexual behavior is innate and rewarding. Despite its centrality to reproduction, a molecularly specified neural circuit governing innate male sexual behavior and reward remains to be characterized. We have discovered a developmentally wired neural circuit necessary and sufficient for male mating. This circuit connects chemosensory input to BNSTprTac1 neurons, which innervate POATacr1 neurons that project to centers regulating motor output and reward. Epistasis studies demonstrate that BNSTprTac1 neurons are upstream of POATacr1 neurons, and BNSTprTac1-released substance P following mate recognition potentiates activation of POATacr1 neurons through Tacr1 to initiate mating. Experimental activation of POATacr1 neurons triggers mating, even in sexually satiated males, and it is rewarding, eliciting dopamine release and self-stimulation of these cells. Together, we have uncovered a neural circuit that governs the key aspects of innate male sexual behavior: motor displays, drive, and reward.

Transcription factor networks directing the development, function, and evolution of innate lymphoid effectors.

Mammalian lymphoid immunity is mediated by fast and slow responders to pathogens. Fast innate lymphocytes are active within hours after infections in mucosal tissues. Slow adaptive lymphocytes are conventional T and B cells with clonal antigen receptors that function days after pathogen exposure. A transcription factor (TF) regulatory network guiding early T cell development is at the core of effector function diversification in all innate lymphocytes, and the kinetics of immune responses is set by developmental programming. Operational units within the innate lymphoid system are not classified by the types of pathogen-sensing machineries but rather by discrete effector functions programmed by regulatory TF networks. Based on the evolutionary history of TFs of the regulatory networks, fast effectors likely arose earlier in the evolution of animals to fortify body barriers, and in mammals they often develop in fetal ontogeny prior to the establishment of fully competent adaptive immunity.

Control of Tissue Development by Morphogens.

Intercellular signaling molecules, known as morphogens, act at a long range in developing tissues to provide spatial information and control properties such as cell fate and tissue growth. The production, transport, and removal of morphogens shape their concentration profiles in time and space. Downstream signaling cascades and gene regulatory networks within cells then convert the spatiotemporal morphogen profiles into distinct cellular responses. Current challenges are to understand the diverse molecular and cellular mechanisms underlying morphogen gradient formation, as well as the logic of downstream regulatory circuits involved in morphogen interpretation. This knowledge, combining experimental and theoretical results, is essential to understand emerging properties of morphogen-controlled systems, such as robustness and scaling.

A modular master regulator landscape controls cancer transcriptional identity.

Despite considerable efforts, the mechanisms linking genomic alterations to the transcriptional identity of cancer cells remain elusive. Integrative genomic analysis, using a network-based approach, identified 407 master regulator (MR) proteins responsible for canalizing the genetics of individual samples from 20 cohorts in The Cancer Genome Atlas (TCGA) into 112 transcriptionally distinct tumor subtypes. MR proteins could be further organized into 24 pan-cancer, master regulator block modules (MRBs), each regulating key cancer hallmarks and predictive of patient outcome in multiple cohorts. Of all somatic alterations detected in each individual sample, >50% were predicted to induce aberrant MR activity, yielding insight into mechanisms linking tumor genetics and transcriptional identity and establishing non-oncogene dependencies. Genetic and pharmacological validation assays confirmed the predicted effect of upstream mutations and MR activity on downstream cellular identity and phenotype. Thus, co-analysis of mutational and gene expression profiles identified elusive subtypes and provided testable hypothesis for mechanisms mediating the effect of genetic alterations.

An atlas of protein-protein interactions across mouse tissues.

Cellular processes arise from the dynamic organization of proteins in networks of physical interactions. Mapping the interactome has therefore been a central objective of high-throughput biology. However, the dynamics of protein interactions across physiological contexts remain poorly understood. Here, we develop a quantitative proteomic approach combining protein correlation profiling with stable isotope labeling of mammals (PCP-SILAM) to map the interactomes of seven mouse tissues. The resulting maps provide a proteome-scale survey of interactome rewiring across mammalian tissues, revealing more than 125,000 unique interactions at a quality comparable to the highest-quality human screens. We identify systematic suppression of cross-talk between the evolutionarily ancient housekeeping interactome and younger, tissue-specific modules. Rewired proteins are tightly regulated by multiple cellular mechanisms and are implicated in disease. Our study opens up new avenues to uncover regulatory mechanisms that shape in vivo interactome responses to physiological and pathophysiological stimuli in mammalian systems.

A phosphate starvation response-centered network regulates mycorrhizal symbiosis.

To secure phosphorus (P) from soil, most land plants use a direct phosphate uptake pathway via root hairs and epidermis and an indirect phosphate uptake pathway via mycorrhizal symbiosis. The interaction between these two pathways is unclear. Here, we mapped a network between transcription factors and mycorrhizal symbiosis-related genes using Y1H. Intriguingly, this gene regulatory network is governed by the conserved P-sensing pathway, centered on phosphate starvation response (PHR) transcription factors. PHRs are required for mycorrhizal symbiosis and regulate symbiosis-related genes via the P1BS motif. SPX-domain proteins suppress OsPHR2-mediated induction of symbiosis-related genes and inhibit mycorrhizal infection. In contrast, plants overexpressing OsPHR2 show improved mycorrhizal infection and are partially resistant to P-mediated inhibition of symbiosis. Functional analyses of network nodes revealed co-regulation of hormonal signaling and mycorrhizal symbiosis. This network deciphers extensive regulation of mycorrhizal symbiosis by endogenous and exogenous signals and highlights co-option of the P-sensing pathway for mycorrhizal symbiosis.

NLRP3 cages revealed by full-length mouse NLRP3 structure control pathway activation.

The NACHT-, leucine-rich-repeat- (LRR), and pyrin domain-containing protein 3 (NLRP3) is emerging to be a critical intracellular inflammasome sensor of membrane integrity and a highly important clinical target against chronic inflammation. Here, we report that an endogenous, stimulus-responsive form of full-length mouse NLRP3 is a 12- to 16-mer double-ring cage held together by LRR-LRR interactions with the pyrin domains shielded within the assembly to avoid premature activation. Surprisingly, this NLRP3 form is predominantly membrane localized, which is consistent with previously noted localization of NLRP3 at various membrane organelles. Structure-guided mutagenesis reveals that trans-Golgi network dispersion into vesicles, an early event observed for many NLRP3-activating stimuli, requires the double-ring cages of NLRP3. Double-ring-defective NLRP3 mutants abolish inflammasome punctum formation, caspase-1 processing, and cell death. Thus, our data uncover a physiological NLRP3 oligomer on the membrane that is poised to sense diverse signals to induce inflammasome activation.

Deciphering cell signaling networks with massively multiplexed biosensor barcoding.

Genetically encoded fluorescent biosensors are powerful tools for monitoring biochemical activities in live cells, but their multiplexing capacity is limited by the available spectral space. We overcome this problem by developing a set of barcoding proteins that can generate over 100 barcodes and are spectrally separable from commonly used biosensors. Mixtures of barcoded cells expressing different biosensors are simultaneously imaged and analyzed by deep learning models to achieve massively multiplexed tracking of signaling events. Importantly, different biosensors in cell mixtures show highly coordinated activities, thus facilitating the delineation of their temporal relationship. Simultaneous tracking of multiple biosensors in the receptor tyrosine kinase signaling network reveals distinct mechanisms of effector adaptation, cell autonomous and non-autonomous effects of KRAS mutations, as well as complex interactions in the network. Biosensor barcoding presents a scalable method to expand multiplexing capabilities for deciphering the complexity of signaling networks and their interactions between cells.

Dual proteome-scale networks reveal cell-specific remodeling of the human interactome.

Thousands of interactions assemble proteins into modules that impart spatial and functional organization to the cellular proteome. Through affinity-purification mass spectrometry, we have created two proteome-scale, cell-line-specific interaction networks. The first, BioPlex 3.0, results from affinity purification of 10,128 human proteins-half the proteome-in 293T cells and includes 118,162 interactions among 14,586 proteins. The second results from 5,522 immunoprecipitations in HCT116 cells. These networks model the interactome whose structure encodes protein function, localization, and complex membership. Comparison across cell lines validates thousands of interactions and reveals extensive customization. Whereas shared interactions reside in core complexes and involve essential proteins, cell-specific interactions link these complexes, "rewiring" subnetworks within each cell's interactome. Interactions covary among proteins of shared function as the proteome remodels to produce each cell's phenotype. Viewable interactively online through BioPlexExplorer, these networks define principles of proteome organization and enable unknown protein characterization.

A single-embryo, single-cell time-resolved model for mouse gastrulation.

Mouse embryonic development is a canonical model system for studying mammalian cell fate acquisition. Recently, single-cell atlases comprehensively charted embryonic transcriptional landscapes, yet inference of the coordinated dynamics of cells over such atlases remains challenging. Here, we introduce a temporal model for mouse gastrulation, consisting of data from 153 individually sampled embryos spanning 36 h of molecular diversification. Using algorithms and precise timing, we infer differentiation flows and lineage specification dynamics over the embryonic transcriptional manifold. Rapid transcriptional bifurcations characterize the commitment of early specialized node and blood cells. However, for most lineages, we observe combinatorial multi-furcation dynamics rather than hierarchical transcriptional transitions. In the mesoderm, dozens of transcription factors combinatorially regulate multifurcations, as we exemplify using time-matched chimeric embryos of Foxc1/Foxc2 mutants. Our study rejects the notion of differentiation being governed by a series of binary choices, providing an alternative quantitative model for cell fate acquisition.

Low-frequency stimulation enhances ensemble co-firing and dexterity after stroke.

Electrical stimulation is a promising tool for modulating brain networks. However, it is unclear how stimulation interacts with neural patterns underlying behavior. Specifically, how might external stimulation that is not sensitive to the state of ongoing neural dynamics reliably augment neural processing and improve function? Here, we tested how low-frequency epidural alternating current stimulation (ACS) in non-human primates recovering from stroke interacted with task-related activity in perilesional cortex and affected grasping. We found that ACS increased co-firing within task-related ensembles and improved dexterity. Using a neural network model, we found that simulated ACS drove ensemble co-firing and enhanced propagation of neural activity through parts of the network with impaired connectivity, suggesting a mechanism to link increased co-firing to enhanced dexterity. Together, our results demonstrate that ACS restores neural processing in impaired networks and improves dexterity following stroke. More broadly, these results demonstrate approaches to optimize stimulation to target neural dynamics.

Rigidity percolation uncovers a structural basis for embryonic tissue phase transitions.

Embryo morphogenesis is impacted by dynamic changes in tissue material properties, which have been proposed to occur via processes akin to phase transitions (PTs). Here, we show that rigidity percolation provides a simple and robust theoretical framework to predict material/structural PTs of embryonic tissues from local cell connectivity. By using percolation theory, combined with directly monitoring dynamic changes in tissue rheology and cell contact mechanics, we demonstrate that the zebrafish blastoderm undergoes a genuine rigidity PT, brought about by a small reduction in adhesion-dependent cell connectivity below a critical value. We quantitatively predict and experimentally verify hallmarks of PTs, including power-law exponents and associated discontinuities of macroscopic observables. Finally, we show that this uniform PT depends on blastoderm cells undergoing meta-synchronous divisions causing random and, consequently, uniform changes in cell connectivity. Collectively, our theoretical and experimental findings reveal the structural basis of material PTs in an organismal context.

TCR+/BCR+ dual-expressing cells and their associated public BCR clonotype are not enriched in type 1 diabetes.

Ahmed and colleagues recently described a novel hybrid lymphocyte expressing both a B and T cell receptor, termed double expresser (DE) cells. DE cells in blood of type 1 diabetes (T1D) subjects were present at increased numbers and enriched for a public B cell clonotype. Here, we attempted to reproduce these findings. While we could identify DE cells by flow cytometry, we found no association between DE cell frequency and T1D status. We were unable to identify the reported public B cell clone, or any similar clone, in bulk B cells or sorted DE cells from T1D subjects or controls. We also did not observe increased usage of the public clone VH or DH genes in B cells or in sorted DE cells. Taken together, our findings suggest that DE cells and their alleged public clonotype are not enriched in T1D. This Matters Arising paper is in response to Ahmed et al. (2019), published in Cell. See also the response by Ahmed et al. (2021), published in this issue.

Modularity and robustness of frontal cortical networks.

Neural activity underlying short-term memory is maintained by interconnected networks of brain regions. It remains unknown how brain regions interact to maintain persistent activity while exhibiting robustness to corrupt information in parts of the network. We simultaneously measured activity in large neuronal populations across mouse frontal hemispheres to probe interactions between brain regions. Activity across hemispheres was coordinated to maintain coherent short-term memory. Across mice, we uncovered individual variability in the organization of frontal cortical networks. A modular organization was required for the robustness of persistent activity to perturbations: each hemisphere retained persistent activity during perturbations of the other hemisphere, thus preventing local perturbations from spreading. A dynamic gating mechanism allowed hemispheres to coordinate coherent information while gating out corrupt information. Our results show that robust short-term memory is mediated by redundant modular representations across brain regions. Redundant modular representations naturally emerge in neural network models that learned robust dynamics.

RTN4/NoGo-receptor binding to BAI adhesion-GPCRs regulates neuronal development.

RTN4-binding proteins were widely studied as "NoGo" receptors, but their physiological interactors and roles remain elusive. Similarly, BAI adhesion-GPCRs were associated with numerous activities, but their ligands and functions remain unclear. Using unbiased approaches, we observed an unexpected convergence: RTN4 receptors are high-affinity ligands for BAI adhesion-GPCRs. A single thrombospondin type 1-repeat (TSR) domain of BAIs binds to the leucine-rich repeat domain of all three RTN4-receptor isoforms with nanomolar affinity. In the 1.65 Å crystal structure of the BAI1/RTN4-receptor complex, C-mannosylation of tryptophan and O-fucosylation of threonine in the BAI TSR-domains creates a RTN4-receptor/BAI interface shaped by unusual glycoconjugates that enables high-affinity interactions. In human neurons, RTN4 receptors regulate dendritic arborization, axonal elongation, and synapse formation by differential binding to glial versus neuronal BAIs, thereby controlling neural network activity. Thus, BAI binding to RTN4/NoGo receptors represents a receptor-ligand axis that, enabled by rare post-translational modifications, controls development of synaptic circuits.

A Human IgSF Cell-Surface Interactome Reveals a Complex Network of Protein-Protein Interactions.

Cell-surface protein-protein interactions (PPIs) mediate cell-cell communication, recognition, and responses. We executed an interactome screen of 564 human cell-surface and secreted proteins, most of which are immunoglobulin superfamily (IgSF) proteins, using a high-throughput, automated ELISA-based screening platform employing a pooled-protein strategy to test all 318,096 PPI combinations. Screen results, augmented by phylogenetic homology analysis, revealed ∼380 previously unreported PPIs. We validated a subset using surface plasmon resonance and cell binding assays. Observed PPIs reveal a large and complex network of interactions both within and across biological systems. We identified new PPIs for receptors with well-characterized ligands and binding partners for "orphan" receptors. New PPIs include proteins expressed on multiple cell types and involved in diverse processes including immune and nervous system development and function, differentiation/proliferation, metabolism, vascularization, and reproduction. These PPIs provide a resource for further biological investigation into their functional relevance and may offer new therapeutic drug targets.