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A long-standing question in the field of signal transduction is how distinct signaling pathways interact with each other to control cell behavior. Growth factor receptors and G protein-coupled receptors (GPCRs) are the two major signaling hubs in eukaryotes. Given that the mechanisms by which they signal independently have been extensively characterized, we investigated how they may cross-talk with each other. Using linear ion trap mass spectrometry and cell-based biophysical, biochemical, and phenotypic assays, we found at least three distinct ways in which epidermal growth factor affected canonical G protein signaling by the Gi-coupled GPCR CXCR4 through the phosphorylation of Gαi. Phosphomimicking mutations in two residues in the αE helix of Gαi (tyrosine-154/tyrosine-155) suppressed agonist-induced Gαi activation while promoting constitutive Gβγ signaling. Phosphomimicking mutations in the P loop (serine-44, serine-47, and threonine-48) suppressed Gi activation entirely, thus completely segregating growth factor and GPCR pathways. As expected, most of the phosphorylation events appeared to affect intrinsic properties of Gαi proteins, including conformational stability, nucleotide binding, and the ability to associate with and to release Gβγ. However, one phosphomimicking mutation, targeting the carboxyl-terminal residue tyrosine-320, promoted mislocalization of Gαi from the plasma membrane, a previously uncharacterized mechanism of suppressing GPCR signaling through G protein subcellular compartmentalization. Together, these findings elucidate not only how growth factor and chemokine signals cross-talk through the phosphorylation-dependent modulation of Gαi but also how such cross-talk may generate signal diversity.

BackgroundAnti-MDA5 (Melanoma differentiation-associated protein-5) positive dermatomyositis (MDA5+-DM) is characterised by rapidly progressive interstitial lung disease (ILD) and high mortality. MDA5 is an RNA sensor and a key pattern recognition receptor for the SARS-CoV-2 virus.MethodsThis is a retrospective observational study of a surge in MDA5 autoimmunity, as determined using a 15 muscle-specific autoantibodies (MSAs) panel, between Janurary 2018 and December 2022 in Yorkshire, UK. MDA5-positivity was correlated with clinical features and outcome, and regional SARS-CoV-2 positivity and vaccination rates. Gene expression patterns in COVID-19 were compared with autoimmune lung disease and idiopathic pulmonary fibrosis (IPF) to gain clues into the genesis of the observed MDA5+-DM outbreak.FindingsSixty new anti-MDA5+, but not other MSAs surged between 2020 and 2022, increasing from 0.4% in 2019 to 2.1% (2020), 4.8% (2021) and 1.7% (2022). Few (8/60) had a prior history of confirmed COVID-19, peak rates overlapped with regional SARS-COV-2 community positivity rates in 2021, and 58% (35/60) had received anti-SARS-CoV-2 vaccines. 25/60 cases developed ILD which rapidly progression with death in 8 cases. Among the 35/60 non-ILD cases, 14 had myositis, 17 Raynaud phenomena and 10 had dermatomyositis spectrum rashes. Transcriptomic studies showed strong IFIH1 (gene encoding for MDA5) induction in COVID-19 and autoimmune-ILD, but not IPF, and IFIH1 strongly correlated with an IL-15-centric type-1 interferon response and an activated CD8+ T cell signature that is an immunologic hallmark of progressive ILD in the setting of systemic autoimmune rheumatic diseases. The IFIH1 rs1990760TT variant blunted such response.InterpretationA distinct pattern of MDA5-autoimmunity cases surged contemporaneously with circulation of the SARS-COV-2 virus during COVID-19. Bioinformatic insights suggest a shared immunopathology with known autoimmune lung disease mechanisms.FundingThis work was supported in part by the National Institute for Health Research (NIHR) Leeds Biomedical Research Centre (BRC), and in part by the National Institutes of Health (NIH) grant R01-AI155696 and pilot awards from the UC Office of the President (UCOP)-RGPO (R00RG2628, R00RG2642 and R01RG3780) to P.G. S.S was supported in part by R01-AI141630 (to P.G) and in part through funds from the American Association of Immunologists (AAI) Intersect Fellowship Program for Computational Scientists and Immunologists.

Self-sufficiency (autonomy) in growth signaling, the earliest recognized hallmark of cancer, is fueled by the tumor cell's ability to "secrete-and-sense" growth factors (GFs); this translates into cell survival and proliferation that is self-sustained by autocrine/paracrine secretion. A Golgi-localized circuitry comprised of two GTPase switches has recently been implicated in the orchestration of growth signaling autonomy. Using breast cancer cells that are either endowed or impaired (by gene editing) in their ability to assemble the circuitry for growth signaling autonomy, here we define the transcriptome, proteome, and phenome of such an autonomous state, and unravel its role during cancer progression. We show that autonomy is associated with enhanced molecular programs for stemness, proliferation, and epithelial-mesenchymal plasticity. Autonomy is both necessary and sufficient for anchorage-independent GF-restricted proliferation and resistance to anticancer drugs and is required for metastatic progression. Transcriptomic and proteomic studies show that autonomy is associated, with a surprising degree of specificity, with self-sustained epidermal growth factor receptor (EGFR)/ErbB signaling. Derivation of a gene expression signature for autonomy revealed that growth signaling autonomy is uniquely induced in circulating tumor cells (CTCs), the harshest phase in the life of tumor cells when it is deprived of biologically available epidermal growth factor (EGF). We also show that autonomy in CTCs tracks therapeutic response and prognosticates outcome. These data support a role for growth signaling autonomy in multiple processes essential for the blood-borne dissemination of human breast cancer.

Macrophages clear infections by engulfing and digesting pathogens within phagolysosomes. Pathogens escape this fate by engaging in a molecular arms race; they use WxxxE motif-containing "effector" proteins to subvert the host cells they invade and seek refuge within protective vacuoles. Here, we define the host component of the molecular arms race as an evolutionarily conserved polar "hot spot" on the PH domain of ELMO1 (Engulfment and Cell Motility protein 1), which is targeted by diverse WxxxE effectors. Using homology modeling and site-directed mutagenesis, we show that a lysine triad within the "patch" directly binds all WxxxE effectors tested: SifA (Salmonella), IpgB1 and IpgB2 (Shigella), and Map (enteropathogenic Escherichia coli). Using an integrated SifA-host protein-protein interaction network, in silico network perturbation, and functional studies, we show that the major consequences of preventing SifA-ELMO1 interaction are reduced Rac1 activity and microbial invasion. That multiple effectors of diverse structure, function, and sequence bind the same hot spot on ELMO1 suggests that the WxxxE effector(s)-ELMO1 interface is a convergence point of intrusion detection and/or host vulnerability. We conclude that the interface may represent the fault line in coevolved molecular adaptations between pathogens and the host, and its disruption may serve as a therapeutic strategy.

Estrogen receptor-positive (ER+) breast cancer commonly disseminates to bone marrow, where interactions with mesenchymal stromal cells (MSCs) shape disease trajectory. We modeled these interactions with tumor-MSC co-cultures and used an integrated transcriptome-proteome-network-analyses workflow to identify a comprehensive catalog of contact-induced changes. Conditioned media from MSCs failed to recapitulate genes and proteins, some borrowed and others tumor-intrinsic, induced in cancer cells by direct contact. Protein-protein interaction networks revealed the rich connectome between 'borrowed' and 'intrinsic' components. Bioinformatics prioritized one of the borrowed components, CCDC88A/GIV, a multi-modular metastasis-related protein that has recently been implicated in driving a hallmark of cancer, growth signaling autonomy. MSCs transferred GIV protein to ER+ breast cancer cells (that lack GIV) through tunnelling nanotubes via connexin (Cx)43-facilitated intercellular transport. Reinstating GIV alone in GIV-negative breast cancer cells reproduced approximately 20% of both the borrowed and the intrinsic gene induction patterns from contact co-cultures; conferred resistance to anti-estrogen drugs; and enhanced tumor dissemination. Findings provide a multiomic insight into MSC [right arrow] tumor cell intercellular transport and validate how transport of one such candidate, GIV, from the haves (MSCs) to have-nots (ER+ breast cancer) orchestrates aggressive disease states., Introduction Estrogen receptor-positive (ER+) breast cancer, the most common subtype, preferentially disseminates to bone and bone marrow (1, 2). Bone metastases remain incurable and cause debilitating symptoms, e.g., pain, fractures, [...]

BackgroundSingle-cell transcriptomic studies have greatly improved organ-specific insights into macrophage polarization states are essential for the initiation and resolution of inflammation in all tissues; however, such insights are yet to translate into therapies that can predictably alter macrophage fate.MethodUsing machine learning algorithms on human macrophages, here we reveal the continuum of polarization states that is shared across diverse contexts. A path, comprised of 338 genes accurately identified both physiologic and pathologic spectra of "reactivity" and "tolerance", and remained relevant across tissues, organs, species, and immune cells (>12,500 diverse datasets).FindingsThis 338-gene signature identified macrophage polarization states at single-cell resolution, in physiology and across diverse human diseases, and in murine pre-clinical disease models. The signature consistently outperformed conventional signatures in the degree of transcriptome-proteome overlap, and in detecting disease states; it also prognosticated outcomes across diverse acute and chronic diseases, e.g., sepsis, liver fibrosis, aging, and cancers. Crowd-sourced genetic and pharmacologic studies confirmed that model-rationalized interventions trigger predictable macrophage fates.InterpretationThese findings provide a formal and universally relevant definition of macrophage states and a predictive framework (http://hegemon.ucsd.edu/SMaRT) for the scientific community to develop macrophage-targeted precision diagnostics and therapeutics.FundingThis work was supported by the National Institutes for Health (NIH) grant R01-AI155696 (to P.G, D.S and S.D). Other sources of support include: R01-GM138385 (to D.S), R01-AI141630 (to P.G), R01-DK107585 (to S.D), and UG3TR003355 (to D.S, S.D, and P.G). D.S was also supported by two Padres Pedal the Cause awards (Padres Pedal the Cause/RADY #PTC2017 and San Diego NCI Cancer Centers Council (C3) #PTC2017). S.S, G.D.K, and D.D were supported through The American Association of Immunologists (AAI) Intersect Fellowship Program for Computational Scientists and Immunologists. We also acknowledge support from the Padres Pedal the Cause #PTC2021 and the Torey Coast Foundation, La Jolla (P.G and D.S). D.S, P.G, and S.D were also supported by the Leona M. and Harry B. Helmsley Charitable Trust.

Cancers represent complex autonomous systems, displaying self-sufficiency in growth signaling. Autonomous growth is fueled by a cancer cell's ability to "secrete-and-sense" growth factors (GFs): a poorly understood phenomenon. Using an integrated computational and experimental approach, here we dissect the impact of a feedback-coupled GTPase circuit within the secretory pathway that imparts secretion-coupled autonomy. The circuit is assembled when the Ras-superfamily monomeric GTPase Arf1, and the heterotrimeric GTPase Giαβγ and their corresponding GAPs and GEFs are coupled by GIV/Girdin, a protein that is known to fuel aggressive traits in diverse cancers. One forward and two key negative feedback loops within the circuit create closed-loop control, allow the two GTPases to coregulate each other, and convert the expected switch-like behavior of Arf1-dependent secretion into an unexpected dose-response alignment behavior of sensing and secretion. Such behavior translates into cell survival that is self-sustained by stimulus-proportionate secretion. Proteomic studies and protein-protein interaction network analyses pinpoint GFs (e.g., the epidermal GF) as key stimuli for such self-sustenance. Findings highlight how the enhanced coupling of two biological switches in cancer cells is critical for multiscale feedback control to achieve secretion-coupled autonomy of growth factors.

BackgroundIn the aftermath of Covid-19, some patients develop a fibrotic lung disease, i.e., post-COVID-19 lung disease (PCLD), for which we currently lack insights into pathogenesis, disease models, or treatment options.MethodsUsing an AI-guided approach, we analyzed > 1000 human lung transcriptomic datasets associated with various lung conditions using two viral pandemic signatures (ViP and sViP) and one covid lung-derived signature. Upon identifying similarities between COVID-19 and idiopathic pulmonary fibrosis (IPF), we subsequently dissected the basis for such similarity from molecular, cytopathic, and immunologic perspectives using a panel of IPF-specific gene signatures, alongside signatures of alveolar type II (AT2) cytopathies and of prognostic monocyte-driven processes that are known drivers of IPF. Transcriptome-derived findings were used to construct protein-protein interaction (PPI) network to identify the major triggers of AT2 dysfunction. Key findings were validated in hamster and human adult lung organoid (ALO) pre-clinical models of COVID-19 using immunohistochemistry and qPCR.FindingsCOVID-19 resembles IPF at a fundamental level; it recapitulates the gene expression patterns (ViP and IPF signatures), cytokine storm (IL15-centric), and the AT2 cytopathic changes, e.g., injury, DNA damage, arrest in a transient, damage-induced progenitor state, and senescence-associated secretory phenotype (SASP). These immunocytopathic features were induced in pre-clinical COVID models (ALO and hamster) and reversed with effective anti-CoV-2 therapeutics in hamsters. PPI-network analyses pinpointed ER stress as one of the shared early triggers of both diseases, and IHC studies validated the same in the lungs of deceased subjects with COVID-19 and SARS-CoV-2-challenged hamster lungs. Lungs from tg-mice, in which ER stress is induced specifically in the AT2 cells, faithfully recapitulate the host immune response and alveolar cytopathic changes that are induced by SARS-CoV-2.InterpretationLike IPF, COVID-19 may be driven by injury-induced ER stress that culminates into progenitor state arrest and SASP in AT2 cells. The ViP signatures in monocytes may be key determinants of prognosis. The insights, signatures, disease models identified here are likely to spur the development of therapies for patients with IPF and other fibrotic interstitial lung diseases.FundingThis work was supported by the National Institutes for Health grants R01- GM138385 and AI155696 and funding from the Tobacco-Related disease Research Program (R01RG3780).

Global modeling of aerosol‐particle number and size is important for understanding aerosol effects on Earth's climate and air quality. Fine‐resolution global models are desirable for representing nonlinear aerosol‐microphysical processes, their nonlinear interactions with dynamics and chemistry, and spatial heterogeneity. However, aerosol‐microphysical simulations are computationally demanding, which can limit the achievable global horizontal resolution. Here, we present the first coupling of the TwO‐Moment Aerosol Sectional (TOMAS) microphysics scheme with the High‐Performance configuration of the GEOS‐Chem model of atmospheric composition (GCHP), a coupling termed GCHP‐TOMAS. GCHP's architecture allows massively parallel GCHP‐TOMAS simulations including on the cloud, using hundreds of computing cores, faster runtimes, more memory, and finer global horizontal resolution (e.g., 25 km × 25 km, 7.8 × 105 model columns) versus the previous single‐node capability of GEOS‐Chem‐TOMAS (tens of cores, 200 km × 250 km, 1.3 × 104 model columns). GCHP‐TOMAS runtimes have near‐ideal scalability with computing‐core number. Simulated global‐mean number concentrations increase (dominated by free‐tropospheric over‐ocean sub‐10‐nm‐diameter particles) toward finer GCHP‐TOMAS horizontal resolution. Increasing the horizontal resolution from 200 km × 200–50 km × 50 km increases the global monthly mean free‐tropospheric total particle number by 18.5%, and over‐ocean sub‐10‐nm‐diameter particles by 39.8% at 4‐km altitude. With a cascade of contributing factors, free‐tropospheric particle‐precursor concentrations increase (32.6% at 4‐km altitude) with resolution, promoting new‐particle formation and growth that outweigh coagulation changes. These nonlinear effects have the potential to revise current understanding of processes controlling global aerosol number and aerosol impacts on Earth's climate and air quality. Plain Language Summary: Small particles in the air have important effects on Earth's climate and air quality. Representing the number and size of these particles in global models is challenging because their processes are complex. This factor has often limited global‐model horizontal resolution because fine global resolution models (e.g., 25 km × 25 km or smaller) generally ran too slowly but would be useful for representing details missed at traditional coarse resolution (e.g., 200 km × 250 km). We start with a detailed particle scheme that previously only ran at coarse global resolution because fine resolution would take too long. We present the initial use of this scheme in an updated model version, with a structure allowing a fast‐running, high‐memory model with fine resolution, by using hundreds to thousands of computer cores. In the updated structure, model speed increases with the number of cores used. We find that the total number of particles in the model is more with fine compared to coarse model resolution. These increases are most in Earth's remote regions and for particles which come from gas. Using fine model resolution globally when representing particles could change our understanding of how they impact Earth's climate and air quality. Key Points: We couple aerosol microphysics with GEOS‐Chem's High‐Performance configuration for fine (25 km × 25 km) global‐resolution capabilityGlobal‐mean aerosol number increases with model resolution, dominated by particles smaller than 10 nm in the over‐ocean free troposphereToward finer horizontal resolution, enhanced particle precursor loading in the free troposphere promotes particle formation and growth [ABSTRACT FROM AUTHOR]

A long-standing question in the field of signal transduction is how distinct signaling pathways interact with each other to control cell behavior. Growth factor receptors and G protein–coupled receptors (GPCRs) are the two major signaling hubs in eukaryotes. Given that the mechanisms by which they signal independently have been extensively characterized, we investigated how they may cross-talk with each other. Using linear ion trap mass spectrometry and cell-based biophysical, biochemical, and phenotypic assays, we found at least three distinct ways in which epidermal growth factor affected canonical G protein signaling by the Gi-coupled GPCR CXCR4 through the phosphorylation of Gαi. Phosphomimicking mutations in two residues in the αE helix of Gαi (tyrosine-154/tyrosine-155) suppressed agonist-induced Gαi activation while promoting constitutive Gβγ signaling. Phosphomimicking mutations in the P loop (serine-44, serine-47, and threonine-48) suppressed Gi activation entirely, thus completely segregating growth factor and GPCR pathways. As expected, most of the phosphorylation events appeared to affect intrinsic properties of Gαi proteins, including conformational stability, nucleotide binding, and the ability to associate with and to release Gβγ. However, one phosphomimicking mutation, targeting the carboxyl-terminal residue tyrosine-320, promoted mislocalization of Gαi from the plasma membrane, a previously uncharacterized mechanism of suppressing GPCR signaling through G protein subcellular compartmentalization. Together, these findings elucidate not only how growth factor and chemokine signals cross-talk through the phosphorylation-dependent modulation of Gαi but also how such cross-talk may generate signal diversity. Editor's summary: In addition to being activated by GPCRs, heterotrimeric G proteins can be transactivated by receptor tyrosine kinases, including epidermal growth factor receptor (EGFR). Roy et al. investigated mechanisms of cross-talk between the GPCR CXCR4 and EGFR. Mass spectrometry analysis identified Gαi residues that were phosphorylated in response to EGF. Studies of Gαi proteins mutated at these sites showed that Gαi phosphorylation prevented it from subsequently coupling to CXCR4, in one case because of the cytosolic mislocalization of Gαi. Together, these findings suggest that cross-talk between growth factor receptors and GPCRs may be mediated at the level of Gαi phosphorylation. —John F. Foley [ABSTRACT FROM AUTHOR]