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For a cell to move forward it must convert chemical energy into mechanical propulsion. Force produced by actin polymerization can generate traction across the plasma membrane by transmission through integrins to their ligands. However, the role this force plays in integrin activation is unknown. Here we show that integrin activity and cytoskeletal dynamics are reciprocally linked, where actin-dependent force itself appears to regulate integrin activity. We generated fluorescent tension-sensing constructs of integrin αLβ2 (LFA-1) to visualize intramolecular tension during cell migration. Using quantitative imaging of migrating T cells, we correlate tension in the αL or β2 subunit with cell and actin dynamics. We find that actin engagement produces tension within the β2 subunit to induce and stabilize an active integrin conformational state and that this requires intact talin and kindlin motifs. This supports a general mechanism where localized actin polymerization can coordinate activation of the complex machinery required for cell migration. The role of force in activating integrin cell adhesion receptors is not known. Here the authors develop fluorescent tension sensors for αL and β2 integrins and show that in migrating T cells force is transduced across the β2 integrin, and that this correlates with an active conformational state.

Computational methods have made substantial progress in improving the accuracy and throughput of pathology workflows for diagnostic, prognostic, and genomic prediction. Still, lack of interpretability remains a significant barrier to clinical integration. We present an approach for predicting clinically-relevant molecular phenotypes from whole-slide histopathology images using human-interpretable image features (HIFs). Our method leverages >1.6 million annotations from board-certified pathologists across >5700 samples to train deep learning models for cell and tissue classification that can exhaustively map whole-slide images at two and four micron-resolution. Cell- and tissue-type model outputs are combined into 607 HIFs that quantify specific and biologically-relevant characteristics across five cancer types. We demonstrate that these HIFs correlate with well-known markers of the tumor microenvironment and can predict diverse molecular signatures (AUROC 0.601–0.864), including expression of four immune checkpoint proteins and homologous recombination deficiency, with performance comparable to ‘black-box’ methods. Our HIF-based approach provides a comprehensive, quantitative, and interpretable window into the composition and spatial architecture of the tumor microenvironment. Computational methods have made progress in improving classification accuracy and throughput of pathology workflows, but lack of interpretability remains a barrier to clinical integration. Here, the authors present an approach for predicting clinically-relevant molecular phenotypes from whole-slide histopathology images using human-interpretable image features.

Anatomical and functional analyses reveal the existence of two types of globus pallidus externus neurons that directly control cortex, suggesting a pathway by which dopaminergic drugs used to treat neuropsychiatric disorders may act in the basal ganglia to modulate cortex. Basal ganglia/frontal cortex linkage Current models postulate that the basal ganglia — nerve cells clustered in the caudate nucleus, putamen and globus pallidus at the base of the forebrain in vertebrates — exert their effects on the cerebral cortex indirectly via inhibition of thalamus, and that this circuitry controls movement and reward learning. Bernardo Sabatini and colleagues now describe a previously unrecognized direct anatomical connection from the globus pallidus externus to the frontal cortex, and show that it functionally modulates cortical activity. The activity of this pathway is sensitive to dopamine receptor signalling, suggesting a potentially novel mechanism for the action of dopaminergic drugs used to treat neuropsychiatric disorders. The basal ganglia are phylogenetically conserved subcortical nuclei necessary for coordinated motor action and reward learning 1 . Current models postulate that the basal ganglia modulate cerebral cortex indirectly via an inhibitory output to thalamus, bidirectionally controlled by direct- and indirect-pathway striatal projection neurons (dSPNs and iSPNs, respectively) 2 , 3 , 4 . The basal ganglia thalamic output sculpts cortical activity by interacting with signals from sensory and motor systems 5 . Here we describe a direct projection from the globus pallidus externus (GP), a central nucleus of the basal ganglia, to frontal regions of the cerebral cortex (FC). Two cell types make up the GP–FC projection, distinguished by their electrophysiological properties, cortical projections and expression of choline acetyltransferase (ChAT), a synthetic enzyme for the neurotransmitter acetylcholine (ACh). Despite these differences, ChAT + cells, which have been historically identified as an extension of the nucleus basalis, as well as ChAT − cells, release the inhibitory neurotransmitter GABA (γ-aminobutyric acid) and are inhibited by iSPNs and dSPNs of dorsal striatum. Thus, GP–FC cells comprise a direct GABAergic/cholinergic projection under the control of striatum that activates frontal cortex in vivo . Furthermore, iSPN inhibition of GP–FC cells is sensitive to dopamine 2 receptor signalling, revealing a pathway by which drugs that target dopamine receptors for the treatment of neuropsychiatric disorders can act in the basal ganglia to modulate frontal cortices.

This study identifies SFPQ (splicing factor, poly-glutamine rich) as an RNA binding protein that binds and coassembles multiple mRNAs in axonal transport granules, and thereby promotes neurotrophin-dependent axon survival. These data demonstrate that SFPQ orchestrates spatial gene expression of a newly identified RNA regulon essential for axonal viability. To achieve accurate spatiotemporal patterns of gene expression, RNA-binding proteins (RBPs) guide nuclear processing, intracellular trafficking and local translation of target mRNAs. In neurons, RBPs direct transport of target mRNAs to sites of translation in remote axons and dendrites. However, it is not known whether an individual RBP coordinately regulates multiple mRNAs within these morphologically complex cells. Here we identify SFPQ (splicing factor, poly-glutamine rich) as an RBP that binds and regulates multiple mRNAs in dorsal root ganglion sensory neurons and thereby promotes neurotrophin-dependent axonal viability. SFPQ acts in nuclei, cytoplasm and axons to regulate functionally related mRNAs essential for axon survival. Notably, SFPQ is required for coassembly of LaminB2 ( Lmnb2 ) and Bclw ( Bcl2l2 ) mRNAs in RNA granules and for axonal trafficking of these mRNAs. Together these data demonstrate that SFPQ orchestrates spatial gene expression of a newly identified RNA regulon essential for axonal viability.

Rho GTPases during cell protrusion The Rho GTPase family acts in concert to regulate cyoskeletal dynamics during processes such as cell motility. In this study, Danuser and colleagues study the coordination of RhoA, Rac1 and Cdc42 during cell migration by simultaneously visualizing two molecules using complementary biosensor designs, and by computationally defining the relationships between individual molecules visualized in separate cells. The latter approach demonstrates that different biosensors, imaged separately, can be freely combined to produce maps of relative signalling activities with seconds and single-micron resolution. These technologies pave the way to defining the dynamics of many proteins in large signal transduction networks. The Rho GTPase family is involved in the control of cytoskeleton dynamics, but the spatiotemporal coordination of each element (Rac1, RhoA and Cdc42) remains unknown. Here, GTPase coordination in mouse embryonic fibroblasts is examined both through simultaneous visualization of two GTPase biosensors and using a computational approach. The GTPases Rac1, RhoA and Cdc42 act together to control cytoskeleton dynamics 1 , 2 , 3 . Recent biosensor studies have shown that all three GTPases are activated at the front of migrating cells 4 , 5 , 6 , 7 , and biochemical evidence suggests that they may regulate one another: Cdc42 can activate Rac1 (ref. 8 ), and Rac1 and RhoA are mutually inhibitory 9 , 10 , 11 , 12 . However, their spatiotemporal coordination, at the seconds and single-micrometre dimensions typical of individual protrusion events, remains unknown. Here we examine GTPase coordination in mouse embryonic fibroblasts both through simultaneous visualization of two GTPase biosensors and using a ‘computational multiplexing’ approach capable of defining the relationships between multiple protein activities visualized in separate experiments. We found that RhoA is activated at the cell edge synchronous with edge advancement, whereas Cdc42 and Rac1 are activated 2 μm behind the edge with a delay of 40 s. This indicates that Rac1 and RhoA operate antagonistically through spatial separation and precise timing, and that RhoA has a role in the initial events of protrusion, whereas Rac1 and Cdc42 activate pathways implicated in reinforcement and stabilization of newly expanded protrusions.

Neutrophil swarms protect healthy tissues by sealing off sites of infection. In the absence of swarming, microbial invasion of surrounding tissues can result in severe infections. Recent observations in animal models have shown that swarming requires rapid neutrophil responses and well-choreographed neutrophil migration patterns. However, in animal models, physical access to the molecular signals coordinating neutrophil activities during swarming is limited. Here, we report the development and validation of large microscale arrays of zymosan particle clusters for the study of human neutrophils during swarming ex vivo . We characterized the synchronized swarming of human neutrophils under the guidance of neutrophil-released chemokines, and measured the mediators released at different phases of human-neutrophil swarming against targets simulating infections. We found that the network of mediators coordinating human-neutrophil swarming includes start and stop signals, proteolytic enzymes and enzyme inhibitors, as well as modulators of activation of other immune and non-immune cells. We also show that the swarming behaviour of neutrophils from patients following major trauma is deficient and gives rise to smaller swarms than those of neutrophils from healthy individuals. Large microscale arrays of zymosan particle clusters enable the characterization of human-neutrophil swarming, including the presence of start and stop signals, and the deficient swarming behaviour of neutrophils from patients following major trauma.

The initial steps in the synthesis of leukotrienes are the translocation of 5-lipoxygenase (5-LO) to the nuclear envelope and its subsequent association with its scaffold protein 5-lipoxygenase-activating protein (FLAP). A major gap in our understanding of this process is the knowledge of how the organization of 5-LO and FLAP on the nuclear envelope regulates leukotriene synthesis. We combined single molecule localization microscopy with Clus-DoC cluster analysis, and also a novel unbiased cluster analysis to analyze changes in the relationships between 5-LO and FLAP in response to activation of RBL-2H3 cells to generate leukotriene C4. We identified the time-dependent reorganization of both 5-LO and FLAP into higher-order assemblies or clusters in response to cell activation via the IgE receptor. Clus-DoC analysis identified a subset of these clusters with a high degree of interaction between 5-LO and FLAP that specifically correlates with the time course of LTC4 synthesis, strongly suggesting their role in the initiation of leukotriene biosynthesis.

Assessment of programmed death ligand 1 (PD-L1) expression by immunohistochemistry (IHC) has emerged as an important predictive biomarker across multiple tumor types. However, manual quantitation of PD-L1 positivity can be difficult and leads to substantial inter-observer variability. Although the development of artificial intelligence (AI) algorithms may mitigate some of the challenges associated with manual assessment and improve the accuracy of PD-L1 expression scoring, use of AI-based approaches to oncology biomarker scoring and drug development has been sparse, primarily due to the lack of large-scale clinical validation studies across multiple cohorts and tumor types. We developed AI-powered algorithms to evaluate PD-L1 expression on tumor cells by IHC and compared it with manual IHC scoring in urothelial carcinoma, non-small cell lung cancer, melanoma, and squamous cell carcinoma of the head and neck (prospectively determined during the phase II and III CheckMate clinical trials). 1,746 slides were retrospectively analyzed, the largest investigation of digital pathology algorithms on clinical trial datasets performed to date. AI-powered quantification of PD-L1 expression on tumor cells identified more PD-L1–positive samples compared with manual scoring at cutoffs of ≥1% and ≥5% in most tumor types. Additionally, similar improvements in response and survival were observed in patients identified as PD-L1–positive compared with PD-L1–negative using both AI-powered and manual methods, while improved associations with survival were observed in patients with certain tumor types identified as PD-L1–positive using AI-powered scoring only. Our study demonstrates the potential for implementation of digital pathology-based methods in future clinical practice to identify more patients who would benefit from treatment with immuno-oncology therapy compared with current guidelines using manual assessment.

Advances in biosensor technology have made it possible to simultaneously study the activation of multiple signalling network components in the same cell. This approach has been enhanced by novel computational approaches (referred to as computational multiplexing) that can reveal relationships between network nodes imaged in separate cells. Cellular signal transduction occurs in complex and redundant interaction networks, which are best understood by simultaneously monitoring the activation dynamics of multiple components. Recent advances in biosensor technology have made it possible to visualize and quantify the activation of multiple network nodes in the same living cell. The precision and scope of this approach has been greatly extended by novel computational approaches (referred to as computational multiplexing) that can reveal relationships between network nodes imaged in separate cells.

Clinical trials in metabolic dysfunction-associated steatohepatitis (MASH, formerly known as nonalcoholic steatohepatitis) require histologic scoring for assessment of inclusion criteria and endpoints. However, variability in interpretation has impacted clinical trial outcomes. We developed an artificial intelligence-based measurement (AIM) tool for scoring MASH histology (AIM-MASH). AIM-MASH predictions for MASH Clinical Research Network necroinflammation grades and fibrosis stages were reproducible ( κ  = 1) and aligned with expert pathologist consensus scores ( κ  = 0.62–0.74). The AIM-MASH versus consensus agreements were comparable to average pathologists for MASH Clinical Research Network scores (82% versus 81%) and fibrosis (97% versus 96%). Continuous scores produced by AIM-MASH for key histological features of MASH correlated with mean pathologist scores and noninvasive biomarkers and strongly predicted progression-free survival in patients with stage 3 ( P  < 0.0001) and stage 4 ( P  = 0.03) fibrosis. In a retrospective analysis of the ATLAS trial (NCT03449446), responders receiving study treatment showed a greater continuous change in fibrosis compared with placebo ( P  = 0.02). Overall, these results suggest that AIM-MASH may assist pathologists in histologic review of MASH clinical trials, reducing inter-rater variability on trial outcomes and offering a more sensitive and reproducible measure of patient responses. Using data from MASH clinical trials, an AI model shows comparable performance with respect to individual pathologists in assessing histologic scoring for enrollment criteria and endpoint evaluation