Trigeminal ganglion neurons are directly activated by influx of CSF solutes in a migraine model.

Classical migraine patients experience aura, which is transient neurological deficits associated with cortical spreading depression (CSD), preceding headache attacks. It is not currently understood how a pathological event in cortex can affect peripheral sensory neurons. In this study, we show that cerebrospinal fluid (CSF) flows into the trigeminal ganglion, establishing nonsynaptic signaling between brain and trigeminal cells. After CSD, ~11% of the CSF proteome is altered, with up-regulation of proteins that directly activate receptors in the trigeminal ganglion. CSF collected from animals exposed to CSD activates trigeminal neurons in naïve mice in part by CSF-borne calcitonin gene-related peptide (CGRP). We identify a communication pathway between the central and peripheral nervous system that might explain the relationship between migrainous aura and headache.

Spatial Proteomics of Single Hepatocytes with Multiplexed Data-Independent Acquisition (mDIA).

Spatially resolved mass spectrometry-based proteomics at single-cell resolution promises to provide insights into biological heterogeneity. We describe a protocol based on multiplexed data-independent acquisition (mDIA) with dimethyl labeling to enhance proteome depth, accuracy, and throughput while minimizing costs. It enables high-quality proteome analysis of single isolated hepatocytes and utilizes liver zonation for single-cell proteomics benchmarking. This adaptable, modular protocol will promote the use of single-cell proteomics in spatial biology.

Spaceflight on the ISS changed the skeletal muscle proteome of two astronauts.

Skeletal muscle undergoes atrophy and loss of force during long space missions, when astronauts are persistently exposed to altered gravity and increased ionizing radiation. We previously carried out mass spectrometry-based proteomics from skeletal muscle biopsies of two astronauts, taken before and after a mission on the International Space Station. The experiments were part of an effort to find similarities between spaceflight and bed rest, a ground-based model of unloading, focused on proteins located at the costameres. We here extend the data analysis of the astronaut dataset and show compartment-resolved changes in the mitochondrial proteome, remodeling of the extracellular matrix and of the antioxidant response. The astronauts differed in their level of onboard physical exercise, which correlated with their respective preservation of muscle mass and force at landing in previous analyses. We show that the mitochondrial proteome downregulation during spaceflight, particularly the inner membrane and matrix, was dramatic for both astronauts. The expression of autophagy regulators and reactive oxygen species scavengers, however, showed partially opposite expression trends in the two subjects, possibly correlating with their level of onboard exercise. As mitochondria are primarily affected in many different tissues during spaceflight, we hypothesize that reactive oxygen species (ROS) rather than mechanical unloading per se could be the primary cause of skeletal muscle mitochondrial damage in space. Onboard physical exercise might have a strong direct effect on the prevention of muscle atrophy through mechanotransduction and a subsidiary effect on mitochondrial quality control, possibly through upregulation of autophagy and anti-oxidant responses.

Proteomic profiling reveals diagnostic signatures and pathogenic insights in multisystem inflammatory syndrome in children.

Multisystem inflammatory syndrome in children (MIS-C) is a severe disease that emerged during the COVID-19 pandemic. Although recognized as an immune-mediated condition, the pathogenesis remains unresolved. Furthermore, the absence of a diagnostic test can lead to delayed immunotherapy. Using state-of-the-art mass-spectrometry proteomics, assisted by artificial intelligence (AI), we aimed to identify a diagnostic signature for MIS-C and to gain insights into disease mechanisms. We identified a highly specific 4-protein diagnostic signature in children with MIS-C. Furthermore, we identified seven clusters that differed between MIS-C and controls, indicating an interplay between apolipoproteins, immune response proteins, coagulation factors, platelet function, and the complement cascade. These intricate protein patterns indicated MIS-C as an immunometabolic condition with global hypercoagulability. Our findings emphasize the potential of AI-assisted proteomics as a powerful and unbiased tool for assessing disease pathogenesis and suggesting avenues for future interventions and impact on pediatric disease trajectories through early diagnosis.

Nivolumab reaches brain lesions in patients with recurrent glioblastoma and induces T-cell activity and upregulation of checkpoint pathways.

Glioblastoma (GBM) is an aggressive brain tumor with poor prognosis. Although immunotherapy is being explored as a potential treatment option for patients with GBM, it is unclear whether systemic immunotherapy can reach and modify the tumor microenvironment in the brain. We evaluated immune characteristics in patients receiving the anti-PD1 immune checkpoint inhibitor Nivolumab one week prior to surgery, compared to control patients receiving salvage resection without prior Nivolumab treatment. We observed saturating levels of Nivolumab bound to intratumorally- and tissue-resident T cells in the brain, implicating saturating levels of Nivolumab reaching brain tumors. Following Nivolumab treatment, significant changes in T-cell activation and proliferation were observed in the tumor resident T-cell population, and peripheral T cells upregulated chemokine receptors related to brain homing. A strong Nivolumab-driven upregulation in compensatory checkpoint inhibition molecules, TIGIT, LAG-3, TIM-3 and CTLA-4 was observed, potentially counteracting the treatment effect. Finally, tumor-reactive tumor-infiltrating lymphocytes (TILs) were found in a subset of Nivolumab-treated patients with prolonged survival, and neoantigen-reactive T cells were identified in both TILs and blood. This indicates a systemic response towards GBM in a subset of patients, which was further boosted by Nivolumab, with T-cell responses towards tumor-derived neoantigens. Our study demonstrates that Nivolumab does reach the GBM tumor lesion and enhances antitumor T-cell responses both intratumorally and systemically. However, various anti-inflammatory mechanisms mitigate the clinical efficacy of the anti-PD1 treatment.

Imputation of label-free quantitative mass spectrometry-based proteomics data using self-supervised deep learning.

Imputation techniques provide means to replace missing measurements with a value and are used in almost all downstream analysis of mass spectrometry (MS) based proteomics data using label-free quantification (LFQ). Here we demonstrate how collaborative filtering, denoising autoencoders, and variational autoencoders can impute missing values in the context of LFQ at different levels. We applied our method, proteomics imputation modeling mass spectrometry (PIMMS), to an alcohol-related liver disease (ALD) cohort with blood plasma proteomics data available for 358 individuals. Removing 20 percent of the intensities we were able to recover 15 out of 17 significant abundant protein groups using PIMMS-VAE imputations. When analyzing the full dataset we identified 30 additional proteins (+13.2%) that were significantly differentially abundant across disease stages compared to no imputation and found that some of these were predictive of ALD progression in machine learning models. We, therefore, suggest the use of deep learning approaches for imputing missing values in MS-based proteomics on larger datasets and provide workflows for these.

Proteomic Characterization of Undifferentiated Small Round Cell Sarcomas With EWSR1 and CIC::DUX4 Translocations Reveals Diverging Tumor Biology and Distinct Diagnostic Markers.

Undifferentiated small round cell sarcomas (USRS) of bone and soft tissue are a group of tumors with heterogenic genomic alterations sharing similar morphology. In the present study, we performed a comparative large-scale proteomic analysis of USRS (n = 42) with diverse genomic translocations including classic Ewing sarcomas with EWSR1::FLI1 fusions (n = 24) or EWSR1::ERG fusions (n = 4), sarcomas with an EWSR1 rearrangement (n = 2), CIC::DUX4 fusion (n = 8), as well as tumors classified as USRS with no genetic data available (n = 4). Proteins extracted from formalin-fixed, paraffin-embedded pretherapeutic biopsies were analyzed qualitatively and quantitatively using shotgun mass spectrometry (MS). More than 8000 protein groups could be quantified using data-independent acquisition. Unsupervised hierarchical cluster analysis based on proteomic data allowed stratification of the 42 cases into distinct groups reflecting the different molecular genotypes. Protein signatures that significantly correlated with the respective genomic translocations were identified and used to generate a heatmap of all 42 sarcomas with assignment of cases with unknown molecular genetic data to either the EWSR1- or CIC-rearranged groups. MS-based prediction of sarcoma subtypes was molecularly confirmed in 2 cases where next-generation sequencing was technically feasible. MS also detected proteins routinely used in the immunohistochemical approach for the differential diagnosis of USRS. BCL11B highly expressed in Ewing sarcomas, and BACH2 as well as ETS-1 highly expressed in CIC::DUX4-associated sarcomas, were among proteins identified by the present proteomic study, and were chosen for immunohistochemical confirmation of MS data in our study cohort. Differential expressions of these 3 markers in the 2 genetic groups were further validated in an independent cohort of n = 34 USRS. Finally, our proteomic results point toward diverging signaling pathways in the different USRS subgroups.

Non-canonical substrate recognition by the human WDR26-CTLH E3 ligase regulates prodrug metabolism.

The yeast glucose-induced degradation-deficient (GID) E3 ubiquitin ligase forms a suite of complexes with interchangeable receptors that selectively recruit N-terminal degron motifs of metabolic enzyme substrates. The orthologous higher eukaryotic C-terminal to LisH (CTLH) E3 complex has been proposed to also recognize substrates through an alternative subunit, WDR26, which promotes the formation of supramolecular CTLH E3 assemblies. Here, we discover that human WDR26 binds the metabolic enzyme nicotinamide/nicotinic-acid-mononucleotide-adenylyltransferase 1 (NMNAT1) and mediates its CTLH E3-dependent ubiquitylation independently of canonical GID/CTLH E3-family substrate receptors. The CTLH subunit YPEL5 inhibits NMNAT1 ubiquitylation and cellular turnover by WDR26-CTLH E3, thereby affecting NMNAT1-mediated metabolic activation and cytotoxicity of the prodrug tiazofurin. Cryoelectron microscopy (cryo-EM) structures of NMNAT1- and YPEL5-bound WDR26-CTLH E3 complexes reveal an internal basic degron motif of NMNAT1 essential for targeting by WDR26-CTLH E3 and degron mimicry by YPEL5's N terminus antagonizing substrate binding. Thus, our data provide a mechanistic understanding of how YPEL5-WDR26-CTLH E3 acts as a modulator of NMNAT1-dependent metabolism.

Noncanonical assembly, neddylation and chimeric cullin-RING/RBR ubiquitylation by the 1.8 MDa CUL9 E3 ligase complex.

Ubiquitin ligation is typically executed by hallmark E3 catalytic domains. Two such domains, 'cullin-RING' and 'RBR', are individually found in several hundred human E3 ligases, and collaborate with E2 enzymes to catalyze ubiquitylation. However, the vertebrate-specific CUL9 complex with RBX1 (also called ROC1), of interest due to its tumor suppressive interaction with TP53, uniquely encompasses both cullin-RING and RBR domains. Here, cryo-EM, biochemistry and cellular assays elucidate a 1.8-MDa hexameric human CUL9-RBX1 assembly. Within one dimeric subcomplex, an E2-bound RBR domain is activated by neddylation of its own cullin domain and positioning from the adjacent CUL9-RBX1 in trans. Our data show CUL9 as unique among RBX1-bound cullins in dependence on the metazoan-specific UBE2F neddylation enzyme, while the RBR domain protects it from deneddylation. Substrates are recruited to various upstream domains, while ubiquitylation relies on both CUL9's neddylated cullin and RBR domains achieving self-assembled and chimeric cullin-RING/RBR E3 ligase activity.

Inhibition of mammalian mtDNA transcription acts paradoxically to reverse diet-induced hepatosteatosis and obesity.

The oxidative phosphorylation system1 in mammalian mitochondria plays a key role in transducing energy from ingested nutrients2. Mitochondrial metabolism is dynamic and can be reprogrammed to support both catabolic and anabolic reactions, depending on physiological demands or disease states. Rewiring of mitochondrial metabolism is intricately linked to metabolic diseases and promotes tumour growth3-5. Here, we demonstrate that oral treatment with an inhibitor of mitochondrial transcription (IMT)6 shifts whole-animal metabolism towards fatty acid oxidation, which, in turn, leads to rapid normalization of body weight, reversal of hepatosteatosis and restoration of normal glucose tolerance in male mice on a high-fat diet. Paradoxically, the IMT treatment causes a severe reduction of oxidative phosphorylation capacity concomitant with marked upregulation of fatty acid oxidation in the liver, as determined by proteomics and metabolomics analyses. The IMT treatment leads to a marked reduction of complex I, the main dehydrogenase feeding electrons into the ubiquinone (Q) pool, whereas the levels of electron transfer flavoprotein dehydrogenase and other dehydrogenases connected to the Q pool are increased. This rewiring of metabolism caused by reduced mtDNA expression in the liver provides a principle for drug treatment of obesity and obesity-related pathology.

Opportunities and barriers in omics-based biomarker discovery for steatotic liver diseases.

The rising prevalence of liver diseases related to obesity and excessive use of alcohol is fuelling an increasing demand for accurate biomarkers aimed at community screening, diagnosis of steatohepatitis and significant fibrosis, monitoring, prognostication and prediction of treatment efficacy. Breakthroughs in omics methodologies and the power of bioinformatics have created an excellent opportunity to apply technological advances to clinical needs, for instance in the development of precision biomarkers for personalised medicine. Via omics technologies, biological processes from the genes to circulating protein, as well as the microbiome - including bacteria, viruses and fungi, can be investigated on an axis. However, there are important barriers to omics-based biomarker discovery and validation, including the use of semi-quantitative measurements from untargeted platforms, which may exhibit high analytical, inter- and intra-individual variance. Standardising methods and the need to validate them across diverse populations presents a challenge, partly due to disease complexity and the dynamic nature of biomarker expression at different disease stages. Lack of validity causes lost opportunities when studies fail to provide the knowledge needed for regulatory approvals, all of which contributes to a delayed translation of these discoveries into clinical practice. While no omics-based biomarkers have matured to clinical implementation, the extent of data generated has enabled the hypothesis-free discovery of a plethora of candidate biomarkers that warrant further validation. To explore the many opportunities of omics technologies, hepatologists need detailed knowledge of commonalities and differences between the various omics layers, and both the barriers to and advantages of these approaches.

Epigenetic control over the cell-intrinsic immune response antagonizes self-renewal in acute myeloid leukemia.

ABSTRACT: Epigenetic modulation of the cell-intrinsic immune response holds promise as a therapeutic approach for leukemia. However, current strategies designed for transcriptional activation of endogenous transposons and subsequent interferon type-I (IFN-I) response, show limited clinical efficacy. Histone lysine methylation is an epigenetic signature in IFN-I response associated with suppression of IFN-I and IFN-stimulated genes, suggesting histone demethylation as key mechanism of reactivation. In this study, we unveil the histone demethylase PHF8 as a direct initiator and regulator of cell-intrinsic immune response in acute myeloid leukemia (AML). Site-specific phosphorylation of PHF8 orchestrates epigenetic changes that upregulate cytosolic RNA sensors, particularly the TRIM25-RIG-I-IFIT5 axis, thereby triggering the cellular IFN-I response-differentiation-apoptosis network. This signaling cascade largely counteracts differentiation block and growth of human AML cells across various disease subtypes in vitro and in vivo. Through proteome analysis of over 200 primary AML bone marrow samples, we identify a distinct PHF8/IFN-I signature in half of the patient population, without significant associations with known clinically or genetically defined AML subgroups. This profile was absent in healthy CD34+ hematopoietic progenitor cells, suggesting therapeutic applicability in a large fraction of patients with AML. Pharmacological support of PHF8 phosphorylation significantly impairs the growth in samples from patients with primary AML. These findings provide novel opportunities for harnessing the cell-intrinsic immune response in the development of immunotherapeutic strategies against AML.

AlphaPept: a modern and open framework for MS-based proteomics.

In common with other omics technologies, mass spectrometry (MS)-based proteomics produces ever-increasing amounts of raw data, making efficient analysis a principal challenge. A plethora of different computational tools can process the MS data to derive peptide and protein identification and quantification. However, during the last years there has been dramatic progress in computer science, including collaboration tools that have transformed research and industry. To leverage these advances, we develop AlphaPept, a Python-based open-source framework for efficient processing of large high-resolution MS data sets. Numba for just-in-time compilation on CPU and GPU achieves hundred-fold speed improvements. AlphaPept uses the Python scientific stack of highly optimized packages, reducing the code base to domain-specific tasks while accessing the latest advances. We provide an easy on-ramp for community contributions through the concept of literate programming, implemented in Jupyter Notebooks. Large datasets can rapidly be processed as shown by the analysis of hundreds of proteomes in minutes per file, many-fold faster than acquisition. AlphaPept can be used to build automated processing pipelines with web-serving functionality and compatibility with downstream analysis tools. It provides easy access via one-click installation, a modular Python library for advanced users, and via an open GitHub repository for developers.

Mustn1 is a smooth muscle cell-secreted microprotein that modulates skeletal muscle extracellular matrix composition.

OBJECTIVE: Skeletal muscle plasticity and remodeling are critical for adapting tissue function to use, disuse, and regeneration. The aim of this study was to identify genes and molecular pathways that regulate the transition from atrophy to compensatory hypertrophy or recovery from injury. Here, we have used a mouse model of hindlimb unloading and reloading, which causes skeletal muscle atrophy, and compensatory regeneration and hypertrophy, respectively. METHODS: We analyzed mouse skeletal muscle at the transition from hindlimb unloading to reloading for changes in transcriptome and extracellular fluid proteome. We then used qRT-PCR, immunohistochemistry, and bulk and single-cell RNA sequencing data to determine Mustn1 gene and protein expression, including changes in gene expression in mouse and human skeletal muscle with different challenges such as exercise and muscle injury. We generated Mustn1-deficient genetic mouse models and characterized them in vivo and ex vivo with regard to muscle function and whole-body metabolism. We isolated smooth muscle cells and functionally characterized them, and performed transcriptomics and proteomics analysis of skeletal muscle and aorta of Mustn1-deficient mice. RESULTS: We show that Mustn1 (Musculoskeletal embryonic nuclear protein 1, also known as Mustang) is highly expressed in skeletal muscle during the early stages of hindlimb reloading. Mustn1 expression is transiently elevated in mouse and human skeletal muscle in response to intense exercise, resistance exercise, or injury. We find that Mustn1 expression is highest in smooth muscle-rich tissues, followed by skeletal muscle fibers. Muscle from heterozygous Mustn1-deficient mice exhibit differences in gene expression related to extracellular matrix and cell adhesion, compared to wild-type littermates. Mustn1-deficient mice have normal muscle and aorta function and whole-body glucose metabolism. We show that Mustn1 is secreted from smooth muscle cells, and that it is present in arterioles of the muscle microvasculature and in muscle extracellular fluid, particularly during the hindlimb reloading phase. Proteomics analysis of muscle from Mustn1-deficient mice confirms differences in extracellular matrix composition, and female mice display higher collagen content after chemically induced muscle injury compared to wild-type littermates. CONCLUSIONS: We show that, in addition to its previously reported intracellular localization, Mustn1 is a microprotein secreted from smooth muscle cells into the muscle extracellular space. We explore its role in muscle ECM deposition and remodeling in homeostasis and upon muscle injury. The role of Mustn1 in fibrosis and immune infiltration upon muscle injury and dystrophies remains to be investigated, as does its potential for therapeutic interventions.

Purification of time-resolved insulin granules reveals proteomic and lipidomic changes during granule aging.

Endocrine cells employ regulated exocytosis of secretory granules to secrete hormones and neurotransmitters. Secretory granule exocytosis depends on spatiotemporal variables such as proximity to the plasma membrane and age, with newly generated granules being preferentially released. Despite recent advances, we lack a comprehensive view of the molecular composition of insulin granules and associated changes over their lifetime. Here, we report a strategy for the purification of insulin secretory granules of distinct age from insulinoma INS-1 cells. Tagging the granule-resident protein phogrin with a cleavable CLIP tag, we obtain intact fractions of age-distinct granules for proteomic and lipidomic analyses. We find that the lipid composition changes over time, along with the physical properties of the membrane, and that kinesin-1 heavy chain (KIF5b) as well as Ras-related protein 3a (RAB3a) associate preferentially with younger granules. Further, we identify the Rho GTPase-activating protein (ARHGAP1) as a cytosolic factor associated with insulin granules.

Comparative Quantitative Proteomic Analysis of Melanoma Subtypes, Nevus-Associated Melanoma, and Corresponding Nevi.

A substantial part of cutaneous malignant melanomas develops from benign nevi. However, the precise molecular events driving the transformation from benign to malignant melanoma are not well-understood. We used laser microdissection and mass spectrometry to analyze the proteomes of melanoma subtypes, including superficial spreading melanomas (n = 17), nodular melanomas (n = 17), and acral melanomas (n = 15). Furthermore, we compared the proteomes of nevi cells with those of melanoma cells within the same specimens (nevus-associated melanoma (n = 14)). In total, we quantified 7935 proteins. Despite the genomic and clinical differences of the melanoma subtypes, our analysis revealed relatively similar proteomes, except for the upregulation of proteins involved in immune activation in nodular melanomas versus acral melanomas. Examining nevus-associated melanoma versus nevi, we found 1725 differentially expressed proteins (false discovery rate < 0.05). Among these proteins were 140 that overlapped with cancer hallmarks, tumor suppressors, and regulators of metabolism and cell cycle. Pathway analysis indicated aberrant activation of the phosphoinositide 3-kinase-protein kinase B-mTOR pathways and the Hippo-YAP pathway. Using a classifier, we identified six proteins capable of distinguishing melanoma from nevi samples. Our study represents a comprehensive comparative analysis of the proteome in melanoma subtypes and associated nevi, offering insights into the biological behavior of these distinct entities.

Full Mass Range ΦSDM Orbitrap Mass Spectrometry for DIA Proteome Analysis.

Optimizing data-independent acquisition methods for proteomics applications often requires balancing spectral resolution and acquisition speed. Here, we describe a real-time full mass range implementation of the phase-constrained spectrum deconvolution method (ΦSDM) for Orbitrap mass spectrometry that increases mass resolving power without increasing scan time. Comparing its performance to the standard enhanced Fourier transformation signal processing revealed that the increased resolving power of ΦSDM is beneficial in areas of high peptide density and comes with a greater ability to resolve low-abundance signals. In a standard 2 h analysis of a 200 ng HeLa digest, this resulted in an increase of 16% in the number of quantified peptides. As the acquisition speed becomes even more important when using fast chromatographic gradients, we further applied ΦSDM methods to a range of shorter gradient lengths (21, 12, and 5 min). While ΦSDM improved identification rates and spectral quality in all tested gradients, it proved particularly advantageous for the 5 min gradient. Here, the number of identified protein groups and peptides increased by >15% in comparison to enhanced Fourier transformation processing. In conclusion, ΦSDM is an alternative signal processing algorithm for processing Orbitrap data that can improve spectral quality and benefit quantitative accuracy in typical proteomics experiments, especially when using short gradients.

The NSP3 protein of SARS-CoV-2 binds fragile X mental retardation proteins to disrupt UBAP2L interactions.

Viruses interact with numerous host factors to facilitate viral replication and to dampen antiviral defense mechanisms. We currently have a limited mechanistic understanding of how SARS-CoV-2 binds host factors and the functional role of these interactions. Here, we uncover a novel interaction between the viral NSP3 protein and the fragile X mental retardation proteins (FMRPs: FMR1, FXR1-2). SARS-CoV-2 NSP3 mutant viruses preventing FMRP binding have attenuated replication in vitro and reduced levels of viral antigen in lungs during the early stages of infection. We show that a unique peptide motif in NSP3 binds directly to the two central KH domains of FMRPs and that this interaction is disrupted by the I304N mutation found in a patient with fragile X syndrome. NSP3 binding to FMRPs disrupts their interaction with the stress granule component UBAP2L through direct competition with a peptide motif in UBAP2L to prevent FMRP incorporation into stress granules. Collectively, our results provide novel insight into how SARS-CoV-2 hijacks host cell proteins and provides molecular insight into the possible underlying molecular defects in fragile X syndrome.