Telomere-to-mitochondria signalling by ZBP1 mediates replicative crisis.

Cancers arise through the accumulation of genetic and epigenetic alterations that enable cells to evade telomere-based proliferative barriers and achieve immortality. One such barrier is replicative crisis-an autophagy-dependent program that eliminates checkpoint-deficient cells with unstable telomeres and other cancer-relevant chromosomal aberrations1,2. However, little is known about the molecular events that regulate the onset of this important tumour-suppressive barrier. Here we identified the innate immune sensor Z-DNA binding protein 1 (ZBP1) as a regulator of the crisis program. A crisis-associated isoform of ZBP1 is induced by the cGAS-STING DNA-sensing pathway, but reaches full activation only when associated with telomeric-repeat-containing RNA (TERRA) transcripts that are synthesized from dysfunctional telomeres. TERRA-bound ZBP1 oligomerizes into filaments on the outer mitochondrial membrane of a subset of mitochondria, where it activates the innate immune adapter protein mitochondrial antiviral-signalling protein (MAVS). We propose that these oligomerization properties of ZBP1 serve as a signal amplification mechanism, where few TERRA-ZBP1 interactions are sufficient to launch a detrimental MAVS-dependent interferon response. Our study reveals a mechanism for telomere-mediated tumour suppression, whereby dysfunctional telomeres activate innate immune responses through mitochondrial TERRA-ZBP1 complexes to eliminate cells destined for neoplastic transformation.

Mass-spectrometry-based draft of the Arabidopsis proteome.

Plants are essential for life and are extremely diverse organisms with unique molecular capabilities1. Here we present a quantitative atlas of the transcriptomes, proteomes and phosphoproteomes of 30 tissues of the model plant Arabidopsis thaliana. Our analysis provides initial answers to how many genes exist as proteins (more than 18,000), where they are expressed, in which approximate quantities (a dynamic range of more than six orders of magnitude) and to what extent they are phosphorylated (over 43,000 sites). We present examples of how the data may be used, such as to discover proteins that are translated from short open-reading frames, to uncover sequence motifs that are involved in the regulation of protein production, and to identify tissue-specific protein complexes or phosphorylation-mediated signalling events. Interactive access to this resource for the plant community is provided by the ProteomicsDB and ATHENA databases, which include powerful bioinformatics tools to explore and characterize Arabidopsis proteins, their modifications and interactions.

The effects of local interventions on global technological change through spillovers: A modeling framework and application to the road-freight sector.

To address global sustainability challenges, (public) policy interventions are needed to induce or accelerate technological change. While most policy interventions occur on the local level, their innovation effects can spill over to other jurisdictions, potentially having global impact. These spillovers can increase or reduce the incentive for interventions. Lacking to date are computational models that capture these spillover dynamics. Here, we devise a conceptual and methodological approach to quantify ex ante the effects of local demand-side interventions on global competition between incumbent and novel technologies. We introduce two factors that moderate global spillovers-relative size of selection environments and relative innovation potential of competing technologies. Our approach incorporates both factors in a techno-economic discrete choice model that evaluates technology competition over time through endogenized technological learning. We apply this modeling framework to the case of road freight. Different demand-pull interventions and shocks are modeled to assess spillover effects. In the case of road freight, electric vehicles experience growth in most application segments but can still be accelerated substantially through public policy intervention-spillovers occur if strong public interventions are introduced in large regions or in multiple combined regions under club policy interventions. These findings are discussed in the context of club policy interventions and a modeled geopolitical shock in China. A full sensitivity analysis of model input parameters and intervention or shock dynamics reveals high model robustness. Finally, we discuss the implications of the road-freight case study as it might inform the progress of other niche technologies in transitioning sectors.

Subclass-switched anti-spike IgG3 oligoclonal cocktails strongly enhance Fc-mediated opsonization.

Antibodies play a central role in the immune defense against SARS-CoV-2. Emerging evidence has shown that nonneutralizing antibodies are important for immune defense through Fc-mediated effector functions. Antibody subclass is known to affect downstream Fc function. However, whether the antibody subclass plays a role in anti-SARS-CoV-2 immunity remains unclear. Here, we subclass-switched eight human IgG1 anti-spike monoclonal antibodies (mAbs) to the IgG3 subclass by exchanging their constant domains. The IgG3 mAbs exhibited altered avidities to the spike protein and more potent Fc-mediated phagocytosis and complement activation than their IgG1 counterparts. Moreover, combining mAbs into oligoclonal cocktails led to enhanced Fc- and complement receptor-mediated phagocytosis, superior to even the most potent single IgG3 mAb when compared at equivalent concentrations. Finally, in an in vivo model, we show that opsonic mAbs of both subclasses can be protective against a SARS-CoV-2 infection, despite the antibodies being nonneutralizing. Our results suggest that opsonic IgG3 oligoclonal cocktails are a promising idea to explore for therapy against SARS-CoV-2, its emerging variants, and potentially other viruses.

Mass spectrometry-based draft of the mouse proteome.

The laboratory mouse ranks among the most important experimental systems for biomedical research and molecular reference maps of such models are essential informational tools. Here, we present a quantitative draft of the mouse proteome and phosphoproteome constructed from 41 healthy tissues and several lines of analyses exemplify which insights can be gleaned from the data. For instance, tissue- and cell-type resolved profiles provide protein evidence for the expression of 17,000 genes, thousands of isoforms and 50,000 phosphorylation sites in vivo. Proteogenomic comparison of mouse, human and Arabidopsis reveal common and distinct mechanisms of gene expression regulation and, despite many similarities, numerous differentially abundant orthologs that likely serve species-specific functions. We leverage the mouse proteome by integrating phenotypic drug (n > 400) and radiation response data with the proteomes of 66 pancreatic ductal adenocarcinoma (PDAC) cell lines to reveal molecular markers for sensitivity and resistance. This unique atlas complements other molecular resources for the mouse and can be explored online via ProteomicsDB and PACiFIC.

Human Monocytes Engage an Alternative Inflammasome Pathway.

Interleukin-1ß (IL-1ß) is a cytokine whose bioactivity is controlled by activation of the inflammasome. However, in response to lipopolysaccharide, human monocytes secrete IL-1ß independently of classical inflammasome stimuli. Here, we report that this constituted a species-specific response that is not observed in the murine system. Indeed, in human monocytes, lipopolysaccharide triggered an "alternative inflammasome" that relied on NLRP3-ASC-caspase-1 signaling, yet was devoid of any classical inflammasome characteristics including pyroptosome formation, pyroptosis induction, and K(+) efflux dependency. Genetic dissection of the underlying signaling pathway in a monocyte transdifferentiation system revealed that alternative inflammasome activation was propagated by TLR4-TRIF-RIPK1-FADD-CASP8 signaling upstream of NLRP3. Importantly, involvement of this signaling cascade was limited to alternative inflammasome activation and did not extend to classical NLRP3 activation. Because alternative inflammasome activation embraces both sensitivity and promiscuity of TLR4, we propose a pivotal role for this signaling cascade in TLR4-driven, IL-1ß-mediated immune responses and immunopathology in humans.

eIF4A1-dependent mRNAs employ purine-rich 5'UTR sequences to activate localised eIF4A1-unwinding through eIF4A1-multimerisation to facilitate translation.

Altered eIF4A1 activity promotes translation of highly structured, eIF4A1-dependent oncogene mRNAs at root of oncogenic translational programmes. It remains unclear how these mRNAs recruit and activate eIF4A1 unwinding specifically to facilitate their preferential translation. Here, we show that single-stranded RNA sequence motifs specifically activate eIF4A1 unwinding allowing local RNA structural rearrangement and translation of eIF4A1-dependent mRNAs in cells. Our data demonstrate that eIF4A1-dependent mRNAs contain AG-rich motifs within their 5'UTR which specifically activate eIF4A1 unwinding of local RNA structure to facilitate translation. This mode of eIF4A1 regulation is used by mRNAs encoding components of mTORC-signalling and cell cycle progression, and renders these mRNAs particularly sensitive to eIF4A1-inhibition. Mechanistically, we show that binding of eIF4A1 to AG-rich sequences leads to multimerization of eIF4A1 with eIF4A1 subunits performing distinct enzymatic activities. Our structural data suggest that RNA-binding of multimeric eIF4A1 induces conformational changes in the RNA resulting in an optimal positioning of eIF4A1 proximal to the RNA duplex enabling efficient unwinding. Our data proposes a model in which AG-motifs in the 5'UTR of eIF4A1-dependent mRNAs specifically activate eIF4A1, enabling assembly of the helicase-competent multimeric eIF4A1 complex, and positioning these complexes proximal to stable localised RNA structure allowing ribosomal subunit scanning.

Pain quality patterns in delayed onset muscle soreness of the lower back suggest sensitization of fascia rather than muscle afferents: a secondary analysis study.

Delayed onset muscle soreness (DOMS) of the lower back is considered a surrogate for acute low back pain (aLBP) in experimental studies. Of note, it is often unquestioningly assumed to be muscle pain. To date, there has not been a study analyzing lumbar DOMS in terms of its pain origin, which was the aim of this study. Sixteen healthy individuals (L-DOMS) were enrolled for the present study and matched to participants from a previous study (n = 16, L-PAIN) who had undergone selective electrical stimulation of the thoracolumbar fascia and the multifidus muscle. DOMS was induced in the lower back of the L-DOMS group using eccentric trunk extensions performed until exhaustion. On subsequent days, pain on palpation (100-mm analogue scale), pressure pain threshold (PPT), and the Pain Sensation Scale (SES) were used to examine the sensory characteristics of DOMS. Pain on palpation showed a significant increase 24 and 48 h after eccentric training, whereas PPT was not affected (p > 0.05). Factor analysis of L-DOMS and L-PAIN sensory descriptors (SES) yielded a stable three-factor solution distinguishing superficial thermal ("heat pain ") from superficial mechanical pain ("sharp pain") and "deep pain." "Heat pain " and "deep pain" in L-DOMS were almost identical to sensory descriptors from electrical stimulation of fascial tissue (L-PAIN, all p > 0.679) but significantly different from muscle pain (all p < 0.029). The differences in sensory description patterns as well as in PPT and self-reported DOMS for palpation pain scores suggest that DOMS has a fascial rather than a muscular origin.

Anomaly detection in mixed high-dimensional molecular data.

MOTIVATION: Mixed molecular data combines continuous and categorical features of the same samples, such as OMICS profiles with genotypes, diagnoses, or patient sex. Like all high-dimensional molecular data, it is prone to incorrect values that can stem from various sources for example the technical limitations of the measurement devices, errors in the sample preparation, or contamination. Most anomaly detection algorithms identify complete samples as outliers or anomalies. However, in most cases, not all measurements of those samples are erroneous but only a few one-dimensional features within the samples are incorrect. These one-dimensional data errors are continuous measurements that are either located outside or inside the normal ranges of their features but in both cases show atypical values given all other continuous and categorical features in the sample. Additionally, categorical anomalies can occur for example when the genotype or diagnosis was submitted wrongly. RESULTS: We introduce ADMIRE (Anomaly Detection using MIxed gRaphical modEls), a novel approach for the detection and correction of anomalies in mixed high-dimensional data. Hereby, we focus on the detection of single (one-dimensional) data errors in the categorical and continuous features of a sample. For that the joint distribution of continuous and categorical features is learned by mixed graphical models, anomalies are detected by the difference between measured and model-based estimations and are corrected using imputation. We evaluated ADMIRE in simulation and by screening for anomalies in one of our own metabolic datasets. In simulation experiments, ADMIRE outperformed the state-of-the-art methods of Local Outlier Factor, stray, and Isolation Forest. AVAILABILITY AND IMPLEMENTATION: All data and code is available at https://github.com/spang-lab/adadmire. ADMIRE is implemented in a Python package called adadmire which can be found at https://pypi.org/project/adadmire.

G protein-coupled estrogen receptor (GPER)/GPR30 forms a complex with the ß1-adrenergic receptor, a membrane-associated guanylate kinase (MAGUK) scaffold protein, and protein kinase A anchoring protein (AKAP) 5 in MCF7 breast cancer cells.

G protein-coupled receptor 30 (GPR30), also named G protein-coupled estrogen receptor (GPER), and the ß1-adrenergic receptor (ß1AR) are G protein-coupled receptors (GPCR) that are implicated in breast cancer progression. Both receptors contain PSD-95/Discs-large/ZO-1 homology (PDZ) motifs in their C-terminal tails through which they interact in the plasma membrane with membrane-associated guanylate kinase (MAGUK) scaffold proteins, and in turn protein kinase A anchoring protein (AKAP) 5. GPR30 constitutively and PDZ-dependently inhibits ß1AR-mediated cAMP production. We hypothesized that this inhibition is a consequence of a plasma membrane complex of these receptors. Using co-immunoprecipitation, confocal immunofluorescence microscopy, and bioluminescence resonance energy transfer (BRET), we show that GPR30 and ß1AR reside in close proximity in a plasma membrane complex when transiently expressed in HEK293. Deleting the GPR30 C-terminal PDZ motif (-SSAV) does not interfere with the receptor complex, indicating that the complex is not PDZ-dependent. MCF7 breast cancer cells express GPR30, ß1AR, MAGUKs, and AKAP5 in the plasma membrane, and co-immunoprecipitation revealed that these proteins exist in close proximity also under native conditions. Furthermore, expression of GPR30 in MCF7 cells constitutively and PDZ-dependently inhibits ß1AR-mediated cAMP production. AKAP5 also inhibits ß1AR-mediated cAMP production, which is not additive with GPR30-promoted inhibition. These results argue that GPR30 and ß1AR form a PDZ-independent complex in MCF7 cells through which GPR30 constitutively and PDZ-dependently inhibits ß1AR signaling via receptor interaction with MAGUKs and AKAP5.

A Conserved Histidine in the RNA Sensor RIG-I Controls Immune Tolerance to N1-2'O-Methylated Self RNA.

The cytosolic helicase retinoic acid-inducible gene-I (RIG-I) initiates immune responses to most RNA viruses by detecting viral 5'-triphosphorylated RNA (pppRNA). Although endogenous mRNA is also 5'-triphosphorylated, backbone modifications and the 5'-ppp-linked methylguanosine ((m7)G) cap prevent immunorecognition. Here we show that the methylation status of endogenous capped mRNA at the 5'-terminal nucleotide (N1) was crucial to prevent RIG-I activation. Moreover, we identified a single conserved amino acid (H830) in the RIG-I RNA binding pocket as the mediator of steric exclusion of N1-2'O-methylated RNA. H830A alteration (RIG-I(H830A)) restored binding of N1-2'O-methylated pppRNA. Consequently, endogenous mRNA activated the RIG-I(H830A) mutant but not wild-type RIG-I. Similarly, knockdown of the endogenous N1-2'O-methyltransferase led to considerable RIG-I stimulation in the absence of exogenous stimuli. Studies involving yellow-fever-virus-encoded 2'O-methyltransferase and RIG-I(H830A) revealed that viruses exploit this mechanism to escape RIG-I. Our data reveal a new role for cap N1-2'O-methylation in RIG-I tolerance of self-RNA.

ProteomicsDB: toward a FAIR open-source resource for life-science research.

ProteomicsDB (https://www.ProteomicsDB.org) is a multi-omics and multi-organism resource for life science research. In this update, we present our efforts to continuously develop and expand ProteomicsDB. The major focus over the last two years was improving the findability, accessibility, interoperability and reusability (FAIR) of the data as well as its implementation. For this purpose, we release a new application programming interface (API) that provides systematic access to essentially all data in ProteomicsDB. Second, we release a new open-source user interface (UI) and show the advantages the scientific community gains from such software. With the new interface, two new visualizations of protein primary, secondary and tertiary structure as well an updated spectrum viewer were added. Furthermore, we integrated ProteomicsDB with our deep-neural-network Prosit that can predict the fragmentation characteristics and retention time of peptides. The result is an automatic processing pipeline that can be used to reevaluate database search engine results stored in ProteomicsDB. In addition, we extended the data content with experiments investigating different human biology as well as a newly supported organism.

Influence of 8-weeks of supervised static stretching or resistance training of pectoral major muscles on maximal strength, muscle thickness and range of motion.

OBJECTIVES: Current research suggests static stretch-induced maximal strength increases and muscle hypertrophy with potential to substitute resistance-training routines. However, most studies investigated the plantar flexors. This study explored the effects of a static stretching program on maximal strength, hypertrophy and flexibility of the pectoralis major and compared the effects with those of traditional resistance training. METHODS: Eighty-one (81) active participants were allocated to either a static stretching, strength-training or control group. Pectoralis stretching was applied 15 min/day, 4 days per week for 8 weeks, while resistance training trained 3 days per week, 5 × 12 repetitions. RESULTS: There was an increase in all parameters (strength: p < 0.001, ƞ2 = 0.313, muscle thickness: p < 0.001, ƞ2 = 0.157-0.264, flexibility: p < 0.001, ƞ2 = 0.316) and a time*group interaction (strength: p = 0.001, ƞ2 = 0.154, muscle thickness: p = 0.008-0.001, ƞ2 = 0.117-0.173, flexibility: p < 0.001, ƞ2 = 0.267). Post-hoc testing showed no difference between both intervention groups regarding maximal strength and muscle thickness (p = 0.905-0.983, d = 0.036-0.087), while flexibility increased in the stretching group (p = 0.001, d = 0.789). CONCLUSION: Stretching showed increases in maximal strength and hypertrophy, which were comparable with commonly used resistance training. Based on current literature, the influence of mechanical tension as the underlying mechanism is discussed. Furthermore, as equipment and comparatively long stretching durations are requested to induce meaningful strength increases in recreationally active participants, practical application seems limited to special circumstances.

Capillary leak syndrome was associated with more severe multisystem inflammatory syndrome in children during the COVID-19 pandemic.

AIM: This population-based study investigated the occurrence of capillary leak syndrome (CLS) in children with multisystem inflammatory syndrome in children (MIS-C), associated with COVID-19. We also examined associations between CLS and MIS-C disease severity. METHODS: All eligible individuals aged 0-18 years, who were diagnosed with MIS-C in Skåne, southern Sweden, from 1 April 2020 to 31 July 2021, were studied. They were all included in the Pediatric Rheumatology Quality Register and clinical and laboratory data were compared between patients with and without CLS. RESULTS: We included 31 patients (61% male) with MIS-C in the study. The median age at diagnosis was 10.6 years (range 1.99-17.15) and 45% developed CLS. All six patients who required intensive care had CLS. Patients with CLS also had a higher incidence of reduced cardiac function, measured as low ejection fraction. The CLS group exhibited significantly higher C-reactive protein values (p < 0.001) and N-terminal pro-B-type natriuretic peptide levels (p < 0.001), as well as lower platelet counts (p = 0.03), during the first week of treatment. Individuals with CLS also received more intense immunosuppression. CONCLUSION: CLS was a common complication of MIS-C in our study and these patients had a more severe disease course that required more intensive treatment.

Estimating experienced racial segregation in US cities using large-scale GPS data.

We estimate a measure of segregation, experienced isolation, that captures individuals' exposure to diverse others in the places they visit over the course of their days. Using Global Positioning System (GPS) data collected from smartphones, we measure experienced isolation by race. We find that the isolation individuals experience is substantially lower than standard residential isolation measures would suggest but that experienced isolation and residential isolation are highly correlated across cities. Experienced isolation is lower relative to residential isolation in denser, wealthier, more educated cities with high levels of public transit use and is also negatively correlated with income mobility.

ProteomicsML: An Online Platform for Community-Curated Data sets and Tutorials for Machine Learning in Proteomics.

Data set acquisition and curation are often the most difficult and time-consuming parts of a machine learning endeavor. This is especially true for proteomics-based liquid chromatography (LC) coupled to mass spectrometry (MS) data sets, due to the high levels of data reduction that occur between raw data and machine learning-ready data. Since predictive proteomics is an emerging field, when predicting peptide behavior in LC-MS setups, each lab often uses unique and complex data processing pipelines in order to maximize performance, at the cost of accessibility and reproducibility. For this reason we introduce ProteomicsML, an online resource for proteomics-based data sets and tutorials across most of the currently explored physicochemical peptide properties. This community-driven resource makes it simple to access data in easy-to-process formats, and contains easy-to-follow tutorials that allow new users to interact with even the most advanced algorithms in the field. ProteomicsML provides data sets that are useful for comparing state-of-the-art machine learning algorithms, as well as providing introductory material for teachers and newcomers to the field alike. The platform is freely available at https://www.proteomicsml.org/, and we welcome the entire proteomics community to contribute to the project at https://github.com/ProteomicsML/ProteomicsML.

Toward an Integrated Machine Learning Model of a Proteomics Experiment.

In recent years machine learning has made extensive progress in modeling many aspects of mass spectrometry data. We brought together proteomics data generators, repository managers, and machine learning experts in a workshop with the goals to evaluate and explore machine learning applications for realistic modeling of data from multidimensional mass spectrometry-based proteomics analysis of any sample or organism. Following this sample-to-data roadmap helped identify knowledge gaps and define needs. Being able to generate bespoke and realistic synthetic data has legitimate and important uses in system suitability, method development, and algorithm benchmarking, while also posing critical ethical questions. The interdisciplinary nature of the workshop informed discussions of what is currently possible and future opportunities and challenges. In the following perspective we summarize these discussions in the hope of conveying our excitement about the potential of machine learning in proteomics and to inspire future research.

Antiviral activity of human OASL protein is mediated by enhancing signaling of the RIG-I RNA sensor.

Virus infection is sensed in the cytoplasm by retinoic acid-inducible gene I (RIG-I, also known as DDX58), which requires RNA and polyubiquitin binding to induce type I interferon (IFN) and activate cellular innate immunity. We show that the human IFN-inducible oligoadenylate synthetases-like (OASL) protein has antiviral activity and mediates RIG-I activation by mimicking polyubiquitin. Loss of OASL expression reduced RIG-I signaling and enhanced virus replication in human cells. Conversely, OASL expression suppressed replication of a number of viruses in a RIG-I-dependent manner and enhanced RIG-I-mediated IFN induction. OASL interacted and colocalized with RIG-I, and through its C-terminal ubiquitin-like domain specifically enhanced RIG-I signaling. Bone-marrow-derived macrophages from mice deficient for Oasl2 showed that among the two mouse orthologs of human OASL, Oasl2 is functionally similar to human OASL. Our findings show a mechanism by which human OASL contributes to host antiviral responses by enhancing RIG-I activation.

ATP-dependent effector-like functions of RIG-I-like receptors.

The vertebrate antiviral innate immune system is often considered to consist of two distinct groups of proteins: pattern recognition receptors (PRRs) that detect viral infection and induce the interferon (IFN) signaling, and effectors that directly act against viral replication. Accordingly, previous studies on PRRs, such as RIG-I and MDA5, have primarily focused on their functions in viral double-stranded RNA (dsRNA) detection and consequent antiviral signaling. We report here that both RIG-I and MDA5 efficiently displace viral proteins pre-bound to dsRNA in a manner dependent on their ATP hydrolysis, and that this activity assists a dsRNA-dependent antiviral effector protein, PKR, and allows RIG-I to promote MDA5 signaling. Furthermore, truncated RIG-I/MDA5 lacking the signaling domain, and hence the IFN stimulatory activity, displaces viral proteins and suppresses replication of certain viruses in an ATP-dependent manner. Thus, this study reveals novel "effector-like" functions of RIG-I and MDA5 that challenge the conventional view of PRRs.

The mTOR regulated RNA-binding protein LARP1 requires PABPC1 for guided mRNA interaction.

The mammalian target of rapamycin (mTOR) is a critical regulator of cell growth, integrating multiple signalling cues and pathways. Key among the downstream activities of mTOR is the control of the protein synthesis machinery. This is achieved, in part, via the co-ordinated regulation of mRNAs that contain a terminal oligopyrimidine tract (TOP) at their 5'ends, although the mechanisms by which this occurs downstream of mTOR signalling are still unclear. We used RNA-binding protein (RBP) capture to identify changes in the protein-RNA interaction landscape following mTOR inhibition. Upon mTOR inhibition, the binding of LARP1 to a number of mRNAs, including TOP-containing mRNAs, increased. Importantly, non-TOP-containing mRNAs bound by LARP1 are in a translationally-repressed state, even under control conditions. The mRNA interactome of the LARP1-associated protein PABPC1 was found to have a high degree of overlap with that of LARP1 and our data show that PABPC1 is required for the association of LARP1 with its specific mRNA targets. Finally, we demonstrate that mRNAs, including those encoding proteins critical for cell growth and survival, are translationally repressed when bound by both LARP1 and PABPC1.