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The μ-opioid receptor (μOR) represents an important target of therapeutic and abused drugs. So far, most understanding of μOR activity has focused on a subset of known signal transducers and regulatory molecules. Yet μOR signaling is coordinated by additional proteins in the interaction network of the activated receptor, which have largely remained invisible given the lack of technologies to interrogate these networks systematically. Here we describe a proteomics and computational approach to map the proximal proteome of the activated μOR and to extract subcellular location, trafficking and functional partners of G-protein-coupled receptor (GPCR) activity. We demonstrate that distinct opioid agonists exert differences in the μOR proximal proteome mediated by endocytosis and endosomal sorting. Moreover, we identify two new μOR network components, EYA4 and KCTD12, which are recruited on the basis of receptor-triggered G-protein activation and might form a previously unrecognized buffering system for G-protein activity broadly modulating cellular GPCR signaling.

Meningiomas are associated with inactivation of NF2/Merlin, but approximately one-third of meningiomas with favorable clinical outcomes retain Merlin expression. Biochemical mechanisms underlying Merlin-intact meningioma growth are incompletely understood, and non-invasive biomarkers that may be used to guide treatment de-escalation or imaging surveillance are lacking. Here, we use single-cell RNA sequencing, proximity-labeling proteomic mass spectrometry, mechanistic and functional approaches, and magnetic resonance imaging (MRI) across meningioma xenografts and patients to define biochemical mechanisms and an imaging biomarker that underlie Merlin-intact meningiomas. We find Merlin serine 13 (S13) dephosphorylation drives meningioma Wnt signaling and tumor growth by attenuating inhibitory interactions with β-catenin and activating the Wnt pathway. MRI analyses show Merlin-intact meningiomas with S13 phosphorylation and favorable clinical outcomes are associated with high apparent diffusion coefficient (ADC). These results define mechanisms underlying a potential imaging biomarker that could be used to guide treatment de-escalation or imaging surveillance for patients with Merlin-intact meningiomas.

To facilitate our understanding of proteome dynamics during signaling events, robust workflows affording fast time resolution without confounding factors are essential. We present Surface-exposed protein Labeling using PeroxidaSe, H2O2, and Tyramide-derivative (SLAPSHOT) to label extracellularly exposed proteins in a rapid, specific, and sensitive manner. Simple and flexible SLAPSHOT utilizes recombinant soluble APEX2 protein applied to cells, thus circumventing the engineering of tools and cells, biological perturbations, and labeling biases. We applied SLAPSHOT and quantitative proteomics to examine the TMEM16F-dependent plasma membrane remodeling in WT and TMEM16F KO cells. Time-course data ranging from 1 to 30 min of calcium stimulation revealed co-regulation of known protein families, including the integrin and ICAM families, and identified proteins known to reside in intracellular organelles as occupants of the freshly deposited extracellularly exposed membrane. Our data provide the first accounts of the immediate consequences of calcium signaling on the extracellularly exposed proteome.

Owing to its roles in cellular signal transduction, protein phosphorylation plays critical roles in myriad cell processes. That said, detecting and quantifying protein phosphorylation has remained a challenge. We describe the use of a novel mass spectrometer (Orbitrap Astral) coupled with data-independent acquisition (DIA) to achieve rapid and deep analysis of human and mouse phosphoproteomes. With this method, we map approximately 30,000 unique human phosphorylation sites within a half-hour of data collection. The technology is benchmarked to other state-of-the-art MS platforms using both synthetic peptide standards and with EGF-stimulated HeLa cells. We apply this approach to generate a phosphoproteome multi-tissue atlas of the mouse. Altogether, we detect 81,120 unique phosphorylation sites within 12 hours of measurement. With this unique dataset, we examine the sequence, structural, and kinase specificity context of protein phosphorylation. Finally, we highlight the discovery potential of this resource with multiple examples of phosphorylation events relevant to mitochondrial and brain biology.

Protein-protein interactions (PPIs) are fundamental to understanding biological systems as protein complexes are the active molecular modules critical for carrying out cellular functions. Dysfunctional PPIs have been associated with various diseases including cancer. Systems-wide PPI analysis not only sheds light on pathological mechanisms, but also represents a paradigm in identifying potential therapeutic targets. In recent years, cross-linking mass spectrometry (XL-MS) has emerged as a powerful tool for defining endogenous PPIs of cellular networks. While proteome-wide studies have been performed in cell lysates, intact cells and tissues, applications of XL-MS in clinical samples have not been reported. In this study, we adopted a DSBSO-based in vivo XL-MS platform to map interaction landscapes from two breast cancer patient-derived xenograft (PDX) models. As a result, we have generated a PDX interaction network comprising 2,557 human proteins and identified interactions unique to breast cancer subtypes. Interestingly, most of the observed differences in PPIs correlated well with protein abundance changes determined by TMT-based proteome quantitation. Collectively, this work has demonstrated the feasibility of XL-MS analysis in clinical samples, and established an analytical workflow for tissue cross-linking that can be generalized for mapping PPIs from patient samples in the future to dissect disease-relevant cellular networks.

Protein-protein interactions (PPIs) are at the heart of the molecular landscape permeating life. Proteomics studies can explore this protein interaction landscape using mass spectrometry (MS). Thanks to their high sensitivity, mass spectrometers can easily identify thousands of proteins within a single sample, but that same sensitivity generates tangled spiderwebs of data that hide biologically relevant findings. So, what does a researcher do when she finds herself walking into spiderwebs? In a field focused on discovery, MS data require rigor in their analysis, experimental validation, or a combination of both. In this Review, we provide a brief primer on MS-based experimental methods to identify PPIs. We discuss approaches to analyze the resulting data and remove the proteomic background. We consider the advantages between comprehensive and targeted studies. We also discuss how scoring might be improved through AI-based protein structure information. Women have been essential to the development of proteomics, so we will specifically highlight work by women that has made this field thrive in recent years.

Proximity labeling (PL) via biotinylation coupled with mass spectrometry (MS) captures spatial proteomes in cells. Large-scale processing requires a workflow minimizing hands-on time and enhancing quantitative reproducibility. We introduced a scalable PL pipeline integrating automated enrichment of biotinylated proteins in a 96-well plate format. Combining this with optimized quantitative MS based on data-independent acquisition (DIA), we increased sample throughput and improved protein identification and quantification reproducibility. We applied this pipeline to delineate subcellular proteomes across various compartments. Using the 5HT2A serotonin receptor as a model, we studied temporal changes of proximal interaction networks induced by receptor activation. In addition, we modified the pipeline for reduced sample input to accommodate CRISPR-based gene knockout, assessing dynamics of the 5HT2A network in response to perturbation of selected interactors. This PL approach is universally applicable to PL proteomics using biotinylation-based PL enzymes, enhancing throughput and reproducibility of standard protocols.

The identification and quantification of misfolded proteins from complex mixtures is important for biological characterization and disease diagnosis, but remains a major bioanalytical challenge. We have developed Hsp40 Affinity Profiling as a bioanalytical approach to profile protein stability in response to cellular stress. In this assay, we ectopically introduce the Hsp40 FlagDNAJB8H31Q into cells and use quantitative proteomics to determine how protein affinity for DNAJB8 changes in the presence of cellular stress, without regard for native clients. Herein, we evaluate potential approaches to improve the performance of this bioanalytical assay. We find that although intracellular crosslinking increases recovery of protein interactors, this is not enough to overcome the relative drop in DNAJB8 recovery. While the J-domain promotes Hsp70 association, it does not affect the yield of protein association with DNAJB8 under basal conditions. By contrast, crosslinking and J-domain ablation both substantially increase relative protein interactor recovery with the structurally distinct Class B Hsp40 DNAJB1 but are completely compensated by poorer yield of DNAJB1 itself. Cellular thermal stress promotes increased affinity between DNAJB8H31Q and interacting proteins, as expected for interactions driven by recognition of misfolded proteins. DNAJB8WT does not demonstrate such a property, suggesting that under stress misfolded proteins are handed off to Hsp70. Hence, we find that DNAJB8H31Q is still our most effective recognition element for the recovery of destabilized client proteins following cellular stress.

Standard single-cell (sc) proteomics of disease states inferred from multicellular organs or organoids cannot currently be related to single-cell physiology. Here, a scPatch-Clamp/Proteomics platform is developed on single neurons generated from hiPSCs bearing an Alzheimer's disease (AD) genetic mutation and compares them to isogenic wild-type controls. This approach provides both current and voltage electrophysiological data plus detailed proteomics information on single-cells. With this new method, the authors are able to observe hyperelectrical activity in the AD hiPSC-neurons, similar to that observed in the human AD brain, and correlate it to ≈1400 proteins detected at the single neuron level. Using linear regression and mediation analyses to explore the relationship between the abundance of individual proteins and the neuron's mutational and electrophysiological status, this approach yields new information on therapeutic targets in excitatory neurons not attainable by traditional methods. This combined patch-proteomics technique creates a new proteogenetic-therapeutic strategy to correlate genotypic alterations to physiology with protein expression in single-cells.

While the primary sequences of human proteins have been cataloged for over a decade, determining how these are organized into a dynamic collection of multiprotein assemblies, with structures and functions spanning biological scales, is an ongoing venture. Systematic and data-driven analyses of these higher-order structures are emerging, facilitating the discovery and understanding of cellular phenotypes. At present, knowledge of protein localization and function has been primarily derived from manual annotation and curation in resources such as the Gene Ontology, which are biased toward richly annotated genes in the literature. Here, we envision a future powered by data-driven mapping of protein assemblies. These maps can capture and decode cellular functions through the integration of protein expression, localization, and interaction data across length scales and timescales. In this review, we focus on progress toward constructing integrated cell maps that accelerate the life sciences and translational research.

In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.

Archived patient-derived tissue specimens play a central role in understanding disease and developing therapies. To address specificity and sensitivity shortcomings of existing single-cell resolution proteoform analysis tools, we introduce a hybrid microfluidic platform (DropBlot) designed for proteoform analyses in chemically fixed single cells. DropBlot serially integrates droplet-based encapsulation and lysis of single fixed cells, with on-chip microwell-based antigen retrieval, with single-cell western blotting of target antigens. A water-in-oil droplet formulation withstands the harsh chemical (SDS, 6 M urea) and thermal conditions (98 °C, 1-2 hr) required for effective antigen retrieval, and supports analysis of retrieved protein targets by single-cell electrophoresis. We demonstrate protein-target retrieval from unfixed, paraformaldehyde-fixed (PFA), and methanol-fixed cells. Key protein targets (HER2, GAPDH, EpCAM, Vimentin) retrieved from PFA-fixed cells were resolved and immunoreactive. Relevant to biorepositories, DropBlot profiled targets retrieved from human-derived breast tumor specimens archived for six years, offering a workflow for single-cell protein-biomarker analysis of sparing biospecimens.

Bone marrow aspirate concentrate (BMAC) and adipose-derived stromal vascular fraction (ADSVF) are the most marketed stem cell therapies to treat a variety of conditions in the general population and elite athletes. Both tissues have been used interchangeably clinically even though their detailed composition, heterogeneity, and mechanisms of action have neither been rigorously inventoried nor compared. This lack of information has prevented investigations into ideal dosages and has facilitated anecdata and misinformation. Here, we analyzed single-cell transcriptomes, proteomes, and flow cytometry profiles from paired clinical-grade BMAC and ADSVF. This comparative transcriptional atlas challenges the prevalent notion that there is one therapeutic cell type present in both tissues. We also provide data of surface markers that may enable isolation and investigation of cell (sub)populations. Furthermore, the proteome atlas highlights intertissue and interpatient heterogeneity of injected proteins with potentially regenerative or immunomodulatory capacities. An interactive webtool is available online.

MOTIVATION: Spatial proteomics can reveal the spatial organization of immune cells in the tumor immune microenvironment. Relating measures of spatial clustering, such as Ripleys K or Besags L, to patient outcomes may offer important clinical insights. However, these measures require pre-specifying a radius in which to quantify clustering, yet no consensus exists on the optimal radius which may be context-specific. RESULTS: We propose a SPatial Omnibus Test (SPOT) which conducts this analysis across a range of candidate radii. At each radius, SPOT evaluates the association between the spatial summary and outcome, adjusting for confounders. SPOT then aggregates results across radii using the Cauchy combination test, yielding an omnibus P-value characterizing the overall degree of association. Using simulations, we verify that the type I error rate is controlled and show SPOT can be more powerful than alternatives. We also apply SPOT to ovarian and lung cancer studies. AVAILABILITY AND IMPLEMENTATION: An R package and tutorial are provided at https://github.com/sarahsamorodnitsky/SPOT.

BACKGROUND: Pulmonary hypertension (PH) represents an important phenotype in heart failure with preserved ejection fraction (HFpEF). However, management of PH-HFpEF is challenging because mechanisms involved in the regulation of PH-HFpEF remain unclear. METHODS: We used a mass spectrometry-based comparative plasma proteomics approach as a sensitive and comprehensive hypothesis-generating discovery technique to profile proteins in patients with PH-HFpEF and control subjects. We then validated and investigated the role of one of the identified proteins using in vitro cell cultures, in vivo animal models, and independent cohort of human samples. RESULTS: Plasma proteomics identified high protein abundance levels of B2M (β2-microglobulin) in patients with PH-HFpEF. Interestingly, both circulating and skeletal muscle levels of B2M were increased in mice with skeletal muscle SIRT3 (sirtuin-3) deficiency or high-fat diet-induced PH-HFpEF. Plasma and muscle biopsies from a validation cohort of PH-HFpEF patients were found to have increased B2M levels, which positively correlated with disease severity, especially pulmonary capillary wedge pressure and right atrial pressure at rest. Not only did the administration of exogenous B2M promote migration/proliferation in pulmonary arterial vascular endothelial cells but it also increased PCNA (proliferating cell nuclear antigen) expression and cell proliferation in pulmonary arterial vascular smooth muscle cells. Finally, B2m deletion improved glucose intolerance, reduced pulmonary vascular remodeling, lowered PH, and attenuated RV hypertrophy in mice with high-fat diet-induced PH-HFpEF. CONCLUSIONS: Patients with PH-HFpEF display higher circulating and skeletal muscle expression levels of B2M, the magnitude of which correlates with disease severity. Our findings also reveal a previously unknown pathogenic role of B2M in the regulation of pulmonary vascular proliferative remodeling and PH-HFpEF. These data suggest that circulating and skeletal muscle B2M can be promising targets for the management of PH-HFpEF.

The B cell receptor (BCR) signals together with a multi-component co-receptor complex to initiate B cell activation in response to antigen binding. Here, we take advantage of peroxidase-catalyzed proximity labeling combined with quantitative mass spectrometry to track co-receptor signaling dynamics in Raji cells from 10 s to 2 h after BCR stimulation. This approach enables tracking of 2,814 proximity-labeled proteins and 1,394 phosphosites and provides an unbiased and quantitative molecular map of proteins recruited to the vicinity of CD19, the signaling subunit of the co-receptor complex. We detail the recruitment kinetics of signaling effectors to CD19 and identify previously uncharacterized mediators of B cell activation. We show that the glutamate transporter SLC1A1 is responsible for mediating rapid metabolic reprogramming and for maintaining redox homeostasis during B cell activation. This study provides a comprehensive map of BCR signaling and a rich resource for uncovering the complex signaling networks that regulate activation.

BACKGROUND: There is a need for novel noninvasive markers for metabolic dysfunction-associated steatotic liver disease (MASLD) to stratify patients at high risk for liver-related events including liver cancer and decompensation. In the present study, we used proteomic analysis of proteins in extracellular vesicles (EVs) to identify new biomarkers that change with fibrosis progression and can predict the development of liver-related events. METHODS: We analyzed serum EVs from 50 patients with MASLD assessed for liver fibrosis by biopsy and identified proteins that altered with advanced fibrosis. A further evaluation was conducted on another cohort of 463 patients with MASLD with biopsy. RESULTS: Eight candidate proteins were identified by proteomic analysis of serum EVs. Among them, serum levels of Fibulin-3, Fibulin-1, and Ficolin 1 correlated with their EV levels. In addition, serum Fibulin-3 and serum Fibulin-1 levels changed significantly with advanced fibrosis. Using another cohort with biopsy, we found that the serum Fibulin-3 concentration was significantly greater in those with advanced fibrosis but that the serum Fibulin-1 concentration was not significantly different. Multivariate Cox proportional hazards analysis revealed that a higher Fibrosis-4 (FIB-4) index and higher serum Fibulin-3 concentration were independent risk factors for liver-related events. When the cutoff value for the serum Fibulin-3 concentration was 6.0 µg/mL according to the Youden index of AUROCs, patients with high serum Fibulin-3 significantly more frequently developed liver-related events than did other patients. Validation using another cohort of 226 patients with clinically diagnosed MASLD confirmed that high serum Fibulin-3 levels are associated with a greater frequency of liver-related events. CONCLUSIONS: Serum Fibulin-3 was identified as a biomarker for predicting liver-related events in patients with MASLD.

The multifaceted nature of multiple sclerosis requires quantitative biomarkers that can provide insights related to diverse physiological pathways. To this end, proteomic analysis of deeply-phenotyped serum samples, biological pathway modeling, and network analysis were performed to elucidate inflammatory and neurodegenerative processes, identifying sensitive biomarkers of multiple sclerosis disease activity. Here, we evaluated the concentrations of > 1400 serum proteins in 630 samples from three multiple sclerosis cohorts for association with clinical and radiographic new disease activity. Twenty proteins were associated with increased clinical and radiographic multiple sclerosis disease activity for inclusion in a custom assay panel. Serum neurofilament light chain showed the strongest univariate correlation with gadolinium lesion activity, clinical relapse status, and annualized relapse rate. Multivariate modeling outperformed univariate for all endpoints. A comprehensive biomarker panel including the twenty proteins identified in this study could serve to characterize disease activity for a patient with multiple sclerosis.

Regular exercise promotes whole-body health and prevents disease, but the underlying molecular mechanisms are incompletely understood1-3. Here, the Molecular Transducers of Physical Activity Consortium4 profiled the temporal transcriptome, proteome, metabolome, lipidome, phosphoproteome, acetylproteome, ubiquitylproteome, epigenome and immunome in whole blood, plasma and 18 solid tissues in male and female Rattus norvegicus over eight weeks of endurance exercise training. The resulting data compendium encompasses 9,466 assays across 19 tissues, 25 molecular platforms and 4 training time points. Thousands of shared and tissue-specific molecular alterations were identified, with sex differences found in multiple tissues. Temporal multi-omic and multi-tissue analyses revealed expansive biological insights into the adaptive responses to endurance training, including widespread regulation of immune, metabolic, stress response and mitochondrial pathways. Many changes were relevant to human health, including non-alcoholic fatty liver disease, inflammatory bowel disease, cardiovascular health and tissue injury and recovery. The data and analyses presented in this study will serve as valuable resources for understanding and exploring the multi-tissue molecular effects of endurance training and are provided in a public repository ( https://motrpac-data.org/ ).

We describe deep analysis of the human proteome in less than 1 h. We achieve this expedited proteome characterization by leveraging state-of-the-art sample preparation, chromatographic separations, and data analysis tools, and by using the new Orbitrap Astral mass spectrometer equipped with a quadrupole mass filter, a high-field Orbitrap mass analyzer, and an asymmetric track lossless (Astral) mass analyzer. The system offers high tandem mass spectrometry acquisition speed of 200 Hz and detects hundreds of peptide sequences per second within data-independent acquisition or data-dependent acquisition modes of operation. The fast-switching capabilities of the new quadrupole complement the sensitivity and fast ion scanning of the Astral analyzer to enable narrow-bin data-independent analysis methods. Over a 30-min active chromatographic method consuming a total analysis time of 56 min, the Q-Orbitrap-Astral hybrid MS collects an average of 4319 MS1 scans and 438,062 tandem mass spectrometry scans per run, producing 235,916 peptide sequences (1% false discovery rate). On average, each 30-min analysis achieved detection of 10,411 protein groups (1% false discovery rate). We conclude, with these results and alongside other recent reports, that the 1-h human proteome is within reach.

Psychosis risk prediction is one of the leading challenges in psychiatry. Previous investigations have suggested that plasma proteomic data may be useful in accurately predicting transition to psychosis in individuals at clinical high risk (CHR). We hypothesized that an a priori-specified proteomic prediction model would have strong predictive accuracy for psychosis risk and aimed to replicate longitudinal associations between plasma proteins and transition to psychosis. This study used plasma samples from participants in 3 CHR cohorts: the North American Prodrome Longitudinal Studies 2 and 3, and the NEURAPRO randomized control trial (total n = 754). Plasma proteomic data were quantified using mass spectrometry. The primary outcome was transition to psychosis over the study follow-up period. Logistic regression models were internally validated, and optimism-corrected performance metrics derived with a bootstrap procedure. In the overall sample of CHR participants (age: 18.5, SD: 3.9; 51.9% male), 20.4% (n = 154) developed psychosis within 4.4 years. The a priori-specified model showed poor risk-prediction accuracy for the development of psychosis (C-statistic: 0.51 [95% CI: 0.50, 0.59], calibration slope: 0.45). At a group level, Complement C8B, C4B, C5, and leucine-rich α-2 glycoprotein 1 (LRG1) were associated with transition to psychosis but did not surpass correction for multiple comparisons. This study did not confirm the findings from a previous proteomic prediction model of transition from CHR to psychosis. Certain complement proteins may be weakly associated with transition at a group level. Previous findings, derived from small samples, should be interpreted with caution.

The OMICs cascade describes the hierarchical flow of information through biological systems. The epigenome sits at the apex of the cascade, thereby regulating the RNA and protein expression of the human genome and governs cellular identity and function. Genes that regulate the epigenome, termed epigenes, orchestrate complex biological signaling programs that drive human development. The broad expression patterns of epigenes during human development mean that pathogenic germline mutations in epigenes can lead to clinically significant multi-system malformations, developmental delay, intellectual disabilities, and stem cell dysfunction. In this review, we refer to germline developmental disorders caused by epigene mutation as chromatinopathies. We curated the largest number of human chromatinopathies to date and our expanded approach more than doubled the number of established chromatinopathies to 179 disorders caused by 148 epigenes. Our study revealed that 20.6% (148/720) of epigenes cause at least one chromatinopathy. In this review, we highlight key examples in which OMICs approaches have been applied to chromatinopathy patient biospecimens to identify underlying disease pathogenesis. The rapidly evolving OMICs technologies that couple molecular biology with high-throughput sequencing or proteomics allow us to dissect out the causal mechanisms driving temporal-, cellular-, and tissue-specific expression. Using the full repertoire of data generated by the OMICs cascade to study chromatinopathies will provide invaluable insight into the developmental impact of these epigenes and point toward future precision targets for these rare disorders.

BACKGROUND: Alcohol-associated hepatitis (AH) is one of the clinical presentations of alcohol-associated liver disease. AH has poor prognosis, and corticosteroids remain the mainstay of drug therapy. However, ~40% of patients do not respond to this treatment, and the mechanisms underlying the altered response to corticosteroids are not understood. The current study aimed to identify changes in hepatic protein expression associated with responsiveness to corticosteroids and prognosis in patients with AH. METHODS: Patients with AH were enrolled based on the National Institute on Alcohol Abuse and Alcoholism inclusion criteria for acute AH and further confirmed by a diagnostic liver biopsy. Proteomic analysis was conducted on liver samples acquired from patients with AH grouped as nonresponders (AH-NR, n = 7) and responders (AH-R, n = 14) to corticosteroids, and nonalcohol-associated liver disease controls (n = 10). The definition of responders was based on the clinical prognostic model, the Lille Score, where a score < 0.45 classified patients as AH-R and a score > 0.45 as AH-NR. Primary outcomes used to assess steroid response were Lille Score (eg, improved liver function) and survival at 24 weeks. RESULTS: Reduced levels of the glucocorticoid receptor and its transcriptional co-activator, glucocorticoid modulatory element-binding protein 2, were observed in the hepatic proteome of AH-NR versus AH-R. The corticosteroid metabolizing enzyme, 11-beta-hydroxysteroid dehydrogenase 1, was increased in AH-NR versus AH-R along with elevated mitochondrial DNA repair enzymes, while several proteins of the heat shock pathway were reduced. Analysis of differentially expressed proteins in AH-NR who survived 24 weeks relative to AH-NR nonsurvivors revealed several protein expression changes, including increased levels of acute phase proteins, elevated coagulation factors, and reduced mast cell markers. CONCLUSIONS: This study identified hepatic proteomic changes that may predict responsiveness to corticosteroids and mortality in patients with AH.

Circulating levels of the soluble ligand-binding ectodomain of the LDL receptor (sLDLR) that is proteolytically cleaved from the cell surface have been shown to correlate with plasma triglycerides, but the lipid and lipoprotein effects of longitudinal changes in sLDLR have not been examined. We sought to assess associations between changes in sLDLR and detailed lipoprotein measurements between baseline and 6 months in participants in the DIETFITS (Diet Intervention Examining The Factors Interacting with Treatment Success) weight loss trial who were randomly assigned to the low-fat (n = 225) or low-carbohydrate (n = 236) diet arms. sLDLR was assayed using a proteomic procedure, lipids and apoprotein (apo) B and apoAI were measured by standard assays, and lipoprotein particle subfractions were quantified by ion mobility methodology. Changes in sLDLR were significantly positively associated with changes in plasma cholesterol, triglycerides, apoB, large-sized and medium-sized VLDL, and small and very small LDL, and inversely with changes in large LDL and HDL. The lipoprotein subfraction associations with sLDLR were independent of age, sex, diet, and BMI, but all except for large LDL were reduced to insignificance when adjusted for triglyceride change. Principal component analysis identified three independent clusters of changes in lipoprotein subfractions that accounted for 78% of their total variance. Change in sLDLR was most strongly correlated with change in the principal component that was loaded positively with large VLDL and small and very small LDL and negatively with large LDL and HDL. In conclusion, sLDLR is a component of a cluster of lipids and lipoproteins that are characteristic of atherogenic dyslipidemia.

INTRODUCTION: The chromosome 22q11.2 deletion syndrome (22q11.2DS) is characterized by a well-defined microdeletion and is associated with a wide range of brain-related phenotypes including schizophrenia spectrum disorders (SCZ), autism spectrum disorders (ASD), anxiety disorders and attention deficit disorders (ADHD). The typically deleted region in 22q11.2DS contains multiple genes which haploinsufficiency has the potential of altering the protein and the metabolic profiles. OBJECTIVES: Alteration in metabolic processes and downstream protein pathways during the early brain development may help to explain the increased prevalence of the observed neurodevelopmental phenotypes in 22q11.2DS. However, relatively little is known about the correlation of dysregulated protein/metabolite expression and neurobehavioral impairments in individuals who developed them over time. METHODS: In this study, we performed untargeted metabolic and proteomic analysis in plasma samples derived from 30 subjects including 16 participants with 22q11.2DS and 14 healthy controls (TD) enrolled in a longitudinal study, aiming to identify a metabolic and protein signature informing about the underlying mechanisms involved in disease development and progression. The metabolic and proteomic profiles were also compared between the participants with 22q11.2DS with and without various comorbidities, such as medical involvement, psychiatric conditions, and autism spectrum disorder (ASD) to detect potential changes among multiple specimens, collected overtime, with the aim to understand the basic underlying mechanisms involved in disease development and progression. RESULTS: We observed a large number of statistically significant differences in metabolites between the two groups. Among them, the levels of taurine and arachidonic acid were significantly lower in 22q11.2DS compared to the TD group. In addition, we identified 16 proteins that showed significant changes in expression levels (adjusted P

Biofilms are matrix-encased microbial communities that increase the environmental fitness and infectivity of many human pathogens including Vibrio cholerae. Biofilm matrix assembly is essential for biofilm formation and function. Known components of the V. cholerae biofilm matrix are the polysaccharide Vibrio polysaccharide (VPS), matrix proteins RbmA, RbmC, Bap1, and extracellular DNA, but the majority of the protein composition is uncharacterized. This study comprehensively analyzed the biofilm matrix proteome and revealed the presence of outer membrane proteins (OMPs). Outer membrane vesicles (OMVs) were also present in the V. cholerae biofilm matrix and were associated with OMPs and many biofilm matrix proteins suggesting that they participate in biofilm matrix assembly. Consistent with this, OMVs had the capability to alter biofilm structural properties depending on their composition. OmpU was the most prevalent OMP in the matrix, and its absence altered biofilm architecture by increasing VPS production. Single-cell force spectroscopy revealed that proteins critical for biofilm formation, OmpU, the matrix proteins RbmA, RbmC, Bap1, and VPS contribute to cell-surface adhesion forces at differing efficiency, with VPS showing the highest efficiency whereas Bap1 showing the lowest efficiency. Our findings provide new insights into the molecular mechanisms underlying biofilm matrix assembly in V. cholerae, which may provide new opportunities to develop inhibitors that specifically alter biofilm matrix properties and, thus, affect either the environmental survival or pathogenesis of V. cholerae.IMPORTANCECholera remains a major public health concern. Vibrio cholerae, the causative agent of cholera, forms biofilms, which are critical for its transmission, infectivity, and environmental persistence. While we know that the V. cholerae biofilm matrix contains exopolysaccharide, matrix proteins, and extracellular DNA, we do not have a comprehensive understanding of the majority of biofilm matrix components. Here, we discover outer membrane vesicles (OMVs) within the biofilm matrix of V. cholerae. Proteomic analysis of the matrix and matrix-associated OMVs showed that OMVs carry key matrix proteins and Vibrio polysaccharide (VPS) to help build biofilms. We also characterize the role of the highly abundant outer membrane protein OmpU in biofilm formation and show that it impacts biofilm architecture in a VPS-dependent manner. Understanding V. cholerae biofilm formation is important for developing a better prevention and treatment strategy framework.

BackgroundPostoperative delirium is prevalent in older adults and has been shown to increase the risk of long-term cognitive decline. Plasma biomarkers to identify the risk for postoperative delirium and the risk of Alzheimer's disease and related dementias are needed.MethodsThis biomarker discovery case-control study aimed to identify plasma biomarkers associated with postoperative delirium. Patients aged ≥65 years undergoing major elective noncardiac surgery were recruited. The preoperative plasma proteome was interrogated with SOMAmer-based technology targeting 1433 biomarkers.ResultsIn 40 patients (20 with vs. 20 without postoperative delirium), a preoperative panel of 12 biomarkers discriminated patients with postoperative delirium with an accuracy of 97.5%. The final model of five biomarkers delivered a leave-one-out cross-validation accuracy of 80%. Represented biological pathways included lysosomal and immune response functions.ConclusionIn older patients who have undergone major surgery, plasma SOMAmer proteomics may provide a relatively non-invasive benchmark to identify biomarkers associated with postoperative delirium.

Infectious diseases are a significant burden in global healthcare. Pathogens engage with different host defense mechanisms. However, it is currently unknown if there are disease-specific immune signatures and/or if different pathogens elicit common immune-associated molecular entities to common therapeutic interventions. We studied patients enrolled through the Human Immunology Project Consortium (HIPC), which focuses on immune responses to various infections. Blood samples were collected and analyzed from patients during infection and follow-up time points at the convalescent stage. The study included samples from patients with Lyme disease (LD), tuberculosis (TB), malaria (MLA), dengue virus (DENV), and West Nile virus (WNV), as well as kidney transplant patients with cytomegalovirus (CMV) and polyomavirus (BKV) infections. Using an antibody-based assay, we quantified ~ 350 cell surface markers, cytokines, and chemokines involved in inflammation and immunity. Unique protein signatures were identified specific to the acute phase of infection irrespective of the pathogen type, with significant changes during convalescence. In addition, tumor necrosis factor receptor superfamily member 6 (TNR6), C-C Motif Chemokine Receptor 7 (CCR7), and C-C motif chemokine ligand-1 (CCL1) were increased in the acute and convalescent phases across all viral, bacterial, and protozoan compared to blood from healthy donors. Furthermore, despite the differences between pathogens, proteins were enriched in common biological pathways such as cell surface receptor signaling pathway and response to external stimulus. In conclusion, we demonstrated that irrespective of the pathogen type, there are common immunoregulatory and proinflammatory signals.

Multi-omics approaches have been successfully applied to investigate pregnancy and health outcomes at a molecular and genetic level in several studies. As omics technologies advance, research areas are open to study further. Here we discuss overall trends and examples of successfully using omics technologies and techniques (e.g., genomics, proteomics, metabolomics, and metagenomics) to investigate the molecular epidemiology of pregnancy. In addition, we outline omics applications and study characteristics of pregnancy for understanding fundamental biology, causal health, and physiological relationships, risk and prediction modeling, diagnostics, and correlations.

Lupus nephritis (LN) is a pathologically heterogenous autoimmune disease linked to end-stage kidney disease and mortality. Better therapeutic strategies are needed as only 30%-40% of patients completely respond to treatment. Noninvasive biomarkers of intrarenal inflammation may guide more precise approaches. Because urine collects the byproducts of kidney inflammation, we studied the urine proteomic profiles of 225 patients with LN (573 samples) in the longitudinal Accelerating Medicines Partnership in RA/SLE cohort. Urinary biomarkers of monocyte/neutrophil degranulation (i.e., PR3, S100A8, azurocidin, catalase, cathepsins, MMP8), macrophage activation (i.e., CD163, CD206, galectin-1), wound healing/matrix degradation (i.e., nidogen-1, decorin), and IL-16 characterized the aggressive proliferative LN classes and significantly correlated with histological activity. A decline of these biomarkers after 3 months of treatment predicted the 1-year response more robustly than proteinuria, the standard of care (AUC: CD206 0.91, EGFR 0.9, CD163 0.89, proteinuria 0.8). Candidate biomarkers were validated and provide potentially treatable targets. We propose these biomarkers of intrarenal immunological activity as noninvasive tools to diagnose LN and guide treatment and as surrogate endpoints for clinical trials. These findings provide insights into the processes involved in LN activity. This data set is a public resource to generate and test hypotheses and validate biomarkers.

BackgroundBiological age may be estimated by proteomic aging clocks (PACs). Previous published PACs were constructed either in smaller studies or mainly in white individuals, and they used proteomic measures from only one-time point. In this study, we created de novo PACs and compared their performance to published PACs at 2 different time points in the Atherosclerosis Risk in Communities (ARIC) study of white and black participants (around 75% white and 25% black).Medthods and findingsA total of 4,712 plasma proteins were measured using SomaScan in blood samples collected in 1990 to 1992 from 11,761 midlife participants (aged 46 to 70 years) and in 2011 to 2013 from 5,183 late-life participants (aged 66 to 90 years). The de novo ARIC PACs were constructed by training them against chronological age using elastic net regression in two-thirds of healthy participants in midlife and late life and validated in the remaining one-third of healthy participants at the corresponding time point. We also computed 3 published PACs. We estimated age acceleration for each PAC as residuals after regressing each PAC on chronological age. We also calculated the change in age acceleration from midlife to late life. We examined the associations of age acceleration and change in age acceleration with mortality through 2019 from all-cause, cardiovascular disease (CVD), cancer, and lower respiratory disease (LRD) using Cox proportional hazards regression in participants (irrespective of health) after excluding the training set. The model was adjusted for chronological age, smoking, body mass index (BMI), and other confounders. We externally validated the midlife PAC using the Multi-Ethnic Study of Atherosclerosis (MESA) Exam 1 data. The ARIC PACs had a slightly stronger correlation with chronological age than published PACs in healthy participants at each time point. Associations with mortality were similar for the ARIC PACs and published PACs. For late-life and midlife age acceleration for the ARIC PACs, respectively, hazard ratios (HRs) per 1 standard deviation were 1.65 and 1.38 (both p < 0.001) for all-cause mortality, 1.37 and 1.20 (both p < 0.001) for CVD mortality, 1.21 (p = 0.028) and 1.04 (p = 0.280) for cancer mortality, and 1.68 and 1.36 (both p < 0.001) for LRD mortality. For the change in age acceleration, HRs for all-cause, CVD, and LRD mortality were comparable to the HRs for late-life age acceleration. The association between the change in age acceleration and cancer mortality was not significant. The external validation of the midlife PAC in MESA showed significant associations with mortality, as observed for midlife participants in ARIC. The main limitation is that our PACs were constructed in midlife and late-life participants. It is unknown whether these PACs could be applied to young individuals.ConclusionsIn this longitudinal study, we found that the ARIC PACs and published PACs were similarly associated with an increased risk of mortality. These findings suggested that PACs show promise as biomarkers of biological age. PACs may be serve as tools to predict mortality and evaluate the effect of anti-aging lifestyle and therapeutic interventions.

A hallmark of Parkinsons disease is the specific degeneration of dopaminergic neurons in the substantia nigra pars compacta. Interestingly, not all of these neurons are affected to the same extent. Studies revealed that neurons located more ventrally within the substantia nigra pars compacta have a higher prevalence to degenerate than those located in the dorsal tier. The underlying reasons for this selective neuronal vulnerability are still unknown. The aim of the present study was to gain a better understanding of molecular differences between these two neuronal subpopulations that may explain the selective neuronal vulnerability within the human substantia nigra. For this purpose, the neurons from the ventral as well as dorsal tier of the substantia nigra were specifically isolated out of neuropathologically unremarkable human substantia nigra sections with laser microdissection. Following, their proteome was analyzed by data independent acquisition mass spectrometry. The samples were analysed donor-specifically and not pooled for this purpose. A total of 5,391 proteins were identified in the substantia nigra. Of these, 2,453 proteins could be quantified in 100% of the dorsal tier samples. 1,629 could be quantified in 100% of the ventral tier samples. Nine proteins were differentially regulated with a log2 value ≥0.5 and a Qvalue ≤0.05. Of these 7 were higher abundant in the dorsal tier and 2 higher in the ventral tier. These proteins are associated with the cytoskeleton, neuronal plasticity, or calcium homeostasis. With these findings a deeper understanding can be gained of the selective neuronal vulnerability within the substantia nigra and of protective mechanisms against neurodegeneration in specific neuronal subpopulations.

INTRODUCTION: Staphylococcus aureus bacteremia (SAB) is a life-threatening infection particularly involving methicillin-resistant S. aureus (MRSA). In contrast to resolving MRSA bacteremia (RB), persistent MRSA bacteremia (PB) blood cultures remain positive despite appropriate antibiotic treatment. Host immune responses distinguishing PB vs. RB outcomes are poorly understood. Here, integrated transcriptomic, IL-10 cytokine levels, and genomic analyses sought to identify signatures differentiating PB vs. RB outcomes. METHODS: Whole-blood transcriptomes of propensity-matched PB (n=28) versus RB (n=30) patients treated with vancomycin were compared in one independent training patient cohort. Gene expression (GE) modules were analyzed and prioritized relative to host IL-10 cytokine levels and DNA methyltransferase-3A (DNMT3A) genotype. RESULTS: Differential expression of T and B lymphocyte gene expression early in MRSA bacteremia discriminated RB from PB outcomes. Significant increases in effector T and B cell signaling pathways correlated with RB, lower IL-10 cytokine levels and DNMT3A heterozygous A/C genotype. Importantly, a second PB and RB patient cohort analyzed in a masked manner demonstrated high predictive accuracy of differential signatures. DISCUSSION: Collectively, the present findings indicate that human PB involves dysregulated immunity characterized by impaired T and B cell responses associated with excessive IL-10 expression in context of the DNMT3A A/A genotype. These findings reveal distinct immunologic programs in PB vs. RB outcomes, enable future studies to define mechanisms by which host and/or pathogen drive differential signatures and may accelerate prediction of PB outcomes. Such prognostic assessment of host risk could significantly enhance early anti-infective interventions to avert PB and improve patient outcomes.

BACKGROUND: A better understanding of treatment progression and recovery in pulmonary tuberculosis (TB) infectious disease is crucial. This study analyzed longitudinal serum samples from pulmonary TB patients undergoing interventional treatment to identify surrogate markers for TB-related outcomes. METHODS: Serum that was collected at baseline and 8, 17, 26, and 52 weeks from 30 TB patients experiencing durable cure were evaluated and compared using a sensitive LC-MS/MS proteomic platform for the detection and quantification of differential host protein signatures relative to timepoint. The global proteome signature was analyzed for statistical differences across the time course and between disease severity and treatment groups. RESULTS: A total of 676 proteins showed differential expression in the serum over these timepoints relative to baseline. Comparisons to understand serum protein dynamics at 8 weeks, treatment endpoints at 17 and 26 weeks, and post-treatment at 52 weeks were performed. The largest protein abundance changes were observed at 8 weeks as the initial effects of antibiotic treatment strongly impacted inflammatory and immune modulated responses. However, the largest number of proteome changes was observed at the end of treatment time points 17 and 26 weeks respectively. Post-treatment 52-week results showed an abatement of differential proteome signatures from end of treatment, though interestingly those proteins uniquely significant at post-treatment were almost exclusively downregulated. Patients were additionally stratified based upon disease severity and compared across all timepoints, identifying 461 discriminating proteome signatures. These proteome signatures collapsed into discrete expression profiles with distinct pathways across immune activation and signaling, hemostasis, and metabolism annotations. Insulin-like growth factor (IGF) and Integrin signaling maintained a severity signature through 52 weeks, implying an intrinsic disease severity signature well into the post-treatment timeframe. CONCLUSION: Previous proteome studies have primarily focused on the 8-week timepoint in relation to culture conversion status. While this study confirms previous observations, it also highlights some differences. The inclusion of additional end of treatment and post-treatment time points offers a more comprehensive assessment of treatment progression within the serum proteome. Examining the expression dynamics at these later time periods will help in the investigation of relapse patients and has provided indicative markers of response and recovery.

Despite advancements in cancer immunotherapy, solid tumors remain formidable challenges. In glioma, profound inter- and intra-tumoral heterogeneity of antigen landscape hampers therapeutic development. Therefore, it is critical to consider alternative sources to expand the repertoire of targetable (neo-)antigens and improve therapeutic outcomes. Accumulating evidence suggests that tumor-specific alternative splicing (AS) could be an untapped reservoir of antigens. In this study, we investigated tumor-specific AS events in glioma, focusing on those predicted to generate major histocompatibility complex (MHC)-presentation-independent, cell-surface antigens that could be targeted by antibodies and chimeric antigen receptor-T cells. We systematically analyzed bulk RNA-sequencing datasets comparing 429 tumor samples (from The Cancer Genome Atlas) and 9166 normal tissue samples (from the Genotype-Tissue Expression project), and identified 13 AS events in 7 genes predicted to be expressed in more than 10% of the patients, including PTPRZ1 and BCAN, which were corroborated by an external RNA-sequencing dataset. Subsequently, we validated our predictions and elucidated the complexity of the isoforms using full-length transcript amplicon sequencing on patient-derived glioblastoma cells. However, analyses of the RNA-sequencing datasets of spatially mapped and longitudinally collected clinical tumor samples unveiled remarkable spatiotemporal heterogeneity of the candidate AS events. Furthermore, proteomics analysis did not reveal any peptide spectra matching the putative antigens. Our investigation illustrated the diverse characteristics of the tumor-specific AS events and the challenges of antigen exploration due to their notable spatiotemporal heterogeneity and elusive nature at the protein levels. Redirecting future efforts toward intracellular, MHC-presented antigens could offer a more viable avenue.

Ulcerative colitis (UC) is driven by immune and stromal subsets, culminating in epithelial injury. Vedolizumab (VDZ) is an anti-integrin antibody that is effective for treating UC. VDZ is known to inhibit lymphocyte trafficking to the intestine, but its broader effects on other cell subsets are less defined. To identify the inflammatory cells that contribute to colitis and are affected by VDZ, we perform single-cell transcriptomic and proteomic analyses of peripheral blood and colonic biopsies in healthy controls and patients with UC on VDZ or other therapies. Here we show that VDZ treatment is associated with alterations in circulating and tissue mononuclear phagocyte (MNP) subsets, along with modest shifts in lymphocytes. Spatial multi-omics of formalin-fixed biopsies demonstrates trends towards increased abundance and proximity of MNP and fibroblast subsets in active colitis. Spatial transcriptomics of archived specimens pre-treatment identifies epithelial-, MNP-, and fibroblast-enriched genes related to VDZ responsiveness, highlighting important roles for these subsets in UC.

Respiratory distress (RD) has been reported in SARS-CoV-2 exposed uninfected (SEU) term neonates. Prior studies suggest that prenatal exposure to Coronavirus Disease 19 (COVID-19) may activate an inflammatory cascade in the newborn airway. In this study, we examine the relationship between maternal COVID-19 vaccination and neonatal RD using a longitudinal cohort of mother-infant pairs in Los Angeles, CA. Two-hundred and twenty-one mothers with laboratory confirmed SARS-CoV-2 during pregnancy and 227 exposed fetuses are enrolled in our study. Maternal disease severity and neonatal RD variables were defined based on current accepted clinical criteria. To explore the multifactorial associations between maternal COVID-19 parameters and infant RD, we utilize a multivariable logistic regression model and a proteomic sub-analysis to propose a pathway for the development of RD following in utero exposure to SARS-CoV-2. Unusually high rates of RD are observed in SEU infants (17%). The odds ratio of RD is 3.06 (95% CI:1.08-10.21) in term neonates born to unvaccinated individuals versus those born to individuals vaccinated prior to maternal infection. Proteomic analysis reveals a robust inflammatory response associated with ciliary dysregulation and enhanced IgE production among SEU neonates with RD. Maternal vaccination against COVID-19 reduces the frequency of neonatal RD.

PURPOSE: VitreoDx is an experimental device enabling push-button collection of a neat vitreous liquid biopsy incidental to an intravitreal injection. We explored the ability of the device to collect a sample usable for proteomic biomarker discovery and testing. DESIGN: Pilot study using ex vivo human eyes. METHODS: Non-vitrectomized, human eyes from nine donors 75-91 years of age were refrigerated in BSS and used within 5 days of death. Four VitreoDx devices fitted with 25G needles, and four staked needle insulin syringes with 30G needles, were inserted at equal intervals through the pars plana of each eye and held in place by a fixture. The sampling mode of each VitreoDx device was triggered to attempt to acquire a liquid biopsy up to 70 μL. The plunger of each insulin syringe was retracted to attempt to obtain a liquid biopsy with a maximum volume of 50 μL. Samples acquired with the VitreoDx were extracted to polypropylene cryovials, refrigerated to -80 ºC, and sent for offsite proteomic analysis by proximity extension assay with a focus on panels containing approved and pipelined drug targets for neovascular disease and inflammatory factors. RESULTS: Of the attempted liquid biopsies with the novel 25G VitreoDx, 92% (66 of 72) resulted in successful acquisition (>25 μL) while 89% (64 of 72) attempted by a traditional 30G needle resulted in a successful acquisition. Sample volume sufficient for proteomics array analysis was acquired by the VitreoDx for every eye. Detectable protein was found for 151 of 166 unique proteins assayed in at least 25% of eyes sampled by VitreoDx. CONCLUSIONS: The high acquisition rate achieved by the prototype was similar to that achieved in previous clinical studies where a standard syringe was used with a 25G needle to biopsy vitreous fluid directly prior to standard intravitreal injection. Successful aspiration rates were likewise high for 30G needles. Together, these suggest that it is possible to routinely acquire liquid vitreous biopsies from patients who typically receive intravitreal injections with an injection device using a standard size needle without a vitreous cutter. Protein analysis shows that proteins of interest survive the sampling mechanism and may have potential to direct care in the future.

Cornified envelopes (CEs) of human epidermis ordinarily consist of transglutaminase-mediated cross-linked proteins and are essential for skin barrier function. However, in addition to enzyme-mediated isopeptide bonding, protein cross-linking could also arise from oxidative damage. Our group recently demonstrated abnormal incorporation of cellular proteins into CEs by pro-oxidants in woodsmoke. In this study, we focused on 2,3-dimethoxy-1,4-naphthoquinone (DMNQ), mesquite liquid smoke (MLS), and 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), to further understand the mechanisms through which environmental pro-oxidants induce CE formation and alter the CE proteome. CEs induced by the ionophore X537A were used for comparison. Similar to X537A, DMNQ- and MLS-induced CE formation was associated with membrane permeabilization. However, since DMNQ is non-adduct forming, its CEs were similar in protein profile to those from X537A. By contrast, MLS, rich in reactive carbonyls that can form protein adducts, caused a dramatic change in the CE proteome. TCDD-CEs were found to contain many CE precursors, such as small proline-rich proteins and late cornified envelope proteins, encoded by the epidermal differentiation complex. Since expression of these proteins is mediated by the aryl hydrocarbon receptor (AhR), and its well-known downstream protein, CYP1A1, was exclusively present in the TCDD group, we suggest that TCDD alters the CE proteome through persistent AhR activation. This study demonstrates the potential of environmental pro-oxidants to alter the epidermal CE proteome and indicates that the cellular redox state has an important role in CE formation.

Biallelic mutations in the gene that encodes the enzyme N-glycanase 1 (NGLY1) cause a rare disease with multi-symptomatic features including developmental delay, intellectual disability, neuropathy, and seizures. NGLY1s activity in human neural cells is currently not well understood. To understand how NGLY1 gene loss leads to the specific phenotypes of NGLY1 deficiency, we employed direct conversion of NGLY1 patient-derived induced pluripotent stem cells (iPSCs) to functional cortical neurons. Transcriptomic, proteomic, and functional studies of iPSC-derived neurons lacking NGLY1 function revealed several major cellular processes that were altered, including protein aggregate-clearing functionality, mitochondrial homeostasis, and synaptic dysfunctions. These phenotypes were rescued by introduction of a functional NGLY1 gene and were observed in iPSC-derived mature neurons but not astrocytes. Finally, laser capture microscopy followed by mass spectrometry provided detailed characterization of the composition of protein aggregates specific to NGLY1-deficient neurons. Future studies will harness this knowledge for therapeutic development.

Most uveal melanoma cases harbor activating mutations in either GNAQ or GNA11. Despite activation of the mitogen-activated protein kinase (MAPK) signaling pathway downstream of Gαq/11, there are no effective targeted kinase therapies for metastatic uveal melanoma. The human genome encodes numerous understudied kinases, also called the dark kinome. Identifying additional kinases regulated by Gαq/11 may uncover novel therapeutic targets for uveal melanoma. In this study, we treated GNAQ-mutant uveal melanoma cell lines with a Gαq/11 inhibitor, YM-254890, and conducted a kinase signaling proteomic screen using multiplexed-kinase inhibitors followed by mass spectrometry. We observed downregulated expression and/or activity of 22 kinases. A custom siRNA screen targeting these kinases demonstrated that knockdown of microtubule affinity regulating kinase 3 (MARK3) and serine/threonine kinase 10 (STK10) significantly reduced uveal melanoma cell growth and decreased expression of cell cycle proteins. Additionally, knockdown of MARK3 but not STK10 decreased ERK1/2 phosphorylation. Analysis of RNA-sequencing and proteomic data showed that Gαq signaling regulates STK10 expression and MARK3 activity. Our findings suggest an involvement of STK10 and MARK3 in the Gαq/11 oncogenic pathway and prompt further investigation into the specific roles and targeting potential of these kinases in uveal melanoma.

Transgenic T-cell receptor (TCR) T cell-based adoptive cell therapies for solid tumors are associated with dramatic initial response rates, but there remain many instances of treatment failure and disease relapse. The association of infusion product cytokine profiles with clinical response has not been explored in the context of TCR T-cell therapy products. Single-cell antigen-dependent secretomic and proteomic analysis of preinfusion clinical TCR T-cell therapy products revealed that TNFα cytokine functionality of CD8+ T cells and phospho-STAT3 signaling in these cells were both associated with superior clinical responsiveness to therapy. By contrast, CD4+ T-helper 2 cell cytokine profiles were associated with inferior clinical responses. In parallel, preinfusion levels of IL15, Flt3-L, and CX3CL1 were all found to be associated with clinical response to therapy. These results have implications for the development of therapeutic biomarkers and identify potential targets for enrichment in the design of transgenic TCR T-cell therapies for solid tumors.

Arboleda-Tham Syndrome (ARTHS) is a rare genetic disorder caused by heterozygous, de novo mutations in Lysine(K) acetyltransferase 6A (KAT6A). ARTHS is clinically heterogeneous and characterized by several common features, including intellectual disability, developmental and speech delay, and hypotonia, and affects multiple organ systems. KAT6A is the enzymatic core of a histone-acetylation protein complex; however, the direct histone targets and gene regulatory effects remain unknown. In this study, we use ARTHS patient (n = 8) and control (n = 14) dermal fibroblasts and perform comprehensive profiling of the epigenome and transcriptome caused by KAT6A mutations. We identified differential chromatin accessibility within the promoter or gene body of 23% (14/60) of genes that were differentially expressed between ARTHS and controls. Within fibroblasts, we show a distinct set of genes from the posterior HOXC gene cluster (HOXC10, HOXC11, HOXC-AS3, HOXC-AS2, and HOTAIR) that are overexpressed in ARTHS and are transcription factors critical for early development body segment patterning. The genomic loci harboring HOXC genes are epigenetically regulated with increased chromatin accessibility, high levels of H3K23ac, and increased gene-body DNA methylation compared to controls, all of which are consistent with transcriptomic overexpression. Finally, we used unbiased proteomic mass spectrometry and identified two new histone post-translational modifications (PTMs) that are disrupted in ARTHS: H2A and H3K56 acetylation. Our multi-omics assays have identified novel histone and gene regulatory roles of KAT6A in a large group of ARTHS patients harboring diverse pathogenic mutations. This work provides insight into the role of KAT6A on the epigenomic regulation in somatic cell types.

Remodeling of the cellular endomembrane system by viruses allows for efficient and coordinated replication of the viral genome in distinct subcellular compartments termed replication organelles. As a critical step in the viral life cycle, replication organelle formation is an attractive target for therapeutic intervention, but factors central to this process are only partially understood. In this study, we corroborate that two viral proteins, nsp3 and nsp4, are the major drivers of membrane remodeling in SARS-CoV-2 infection. We further report a number of host cell factors interacting with these viral proteins and supporting the viral replication cycle, some of them by contributing to the formation of the SARS-CoV-2 replication organelle.

Covalent chemistry represents an attractive strategy for expanding the ligandability of the proteome, and chemical proteomics has revealed numerous electrophile-reactive cysteines on diverse human proteins. Determining which of these covalent binding events affect protein function, however, remains challenging. Here we describe a base-editing strategy to infer the functionality of cysteines by quantifying the impact of their missense mutation on cancer cell proliferation. The resulting atlas, which covers more than 13,800 cysteines on more than 1,750 cancer dependency proteins, confirms the essentiality of cysteines targeted by covalent drugs and, when integrated with chemical proteomic data, identifies essential, ligandable cysteines in more than 160 cancer dependency proteins. We further show that a stereoselective and site-specific ligand targeting an essential cysteine in TOE1 inhibits the nuclease activity of this protein through an apparent allosteric mechanism. Our findings thus describe a versatile method and valuable resource to prioritize the pursuit of small-molecule probes with high function-perturbing potential.

ObjectiveAmyotrophic lateral sclerosis (ALS) is a heterogeneous disease with a complex etiology that lacks biomarkers predicting disease progression. The objective of this study was to use longitudinal cerebrospinal fluid (CSF) samples to identify biomarkers that distinguish fast progression (FP) from slow progression (SP) and assess their temporal response.MethodsWe utilized mass spectrometry (MS)-based proteomics to identify candidate biomarkers using longitudinal CSF from a discovery cohort of SP and FP ALS patients. Immunoassays were used to quantify and validate levels of the top biomarkers. A state-transition mathematical model was created using the longitudinal MS data that also predicted FP versus SP.ResultsWe identified a total of 1148 proteins in the CSF of all ALS patients. Pathway analysis determined enrichment of pathways related to complement and coagulation cascades in FPs and synaptogenesis and glucose metabolism in SPs. Longitudinal analysis revealed a panel of 59 candidate markers that could segregate FP and SP ALS. Based on multivariate analysis, we identified three biomarkers (F12, RBP4, and SERPINA4) as top candidates that segregate ALS based on rate of disease progression. These proteins were validated in the discovery and a separate validation cohort. Our state-transition model determined that the overall variance of the proteome over time was predictive of the disease progression rate.InterpretationWe identified pathways and protein biomarkers that distinguish rate of ALS disease progression. A mathematical model of the CSF proteome determined that the change in entropy of the proteome over time was predictive of FP versus SP.

Epithelial and stromal/mesenchymal limbal stem cells contribute to corneal homeostasis and cell renewal. Extracellular vesicles (EVs), including exosomes (Exos), can be paracrine mediators of intercellular communication. Previously, we described cargos and regulatory roles of limbal stromal cell (LSC)-derived Exos in non-diabetic (N) and diabetic (DM) limbal epithelial cells (LECs). Presently, we quantify the miRNA and proteome profiles of human LEC-derived Exos and their regulatory roles in N- and DM-LSC. We revealed some miRNA and protein differences in DM vs. N-LEC-derived Exos cargos, including proteins involved in Exo biogenesis and packaging that may affect Exo production and ultimately cellular crosstalk and corneal function. Treatment by N-Exos, but not by DM-Exos, enhanced wound healing in cultured N-LSCs and increased proliferation rates in N and DM LSCs vs. corresponding untreated (control) cells. N-Exos-treated LSCs reduced the keratocyte markers ALDH3A1 and lumican and increased the MSC markers CD73, CD90, and CD105 vs. control LSCs. These being opposite to the changes quantified in wounded LSCs. Overall, N-LEC Exos have a more pronounced effect on LSC wound healing, proliferation, and stem cell marker expression than DM-LEC Exos. This suggests that regulatory miRNA and protein cargo differences in DM- vs. N-LEC-derived Exos could contribute to the disease state.

The molecular mechanisms and evolutionary changes accompanying synapse development are still poorly understood1,2. Here we generate a cross-species proteomic map of synapse development in the human, macaque and mouse neocortex. By tracking the changes of more than 1,000 postsynaptic density (PSD) proteins from midgestation to young adulthood, we find that PSD maturation in humans separates into three major phases that are dominated by distinct pathways. Cross-species comparisons reveal that human PSDs mature about two to three times slower than those of other species and contain higher levels of Rho guanine nucleotide exchange factors (RhoGEFs) in the perinatal period. Enhancement of RhoGEF signalling in human neurons delays morphological maturation of dendritic spines and functional maturation of synapses, potentially contributing to the neotenic traits of human brain development. In addition, PSD proteins can be divided into four modules that exert stage- and cell-type-specific functions, possibly explaining their differential associations with cognitive functions and diseases. Our proteomic map of synapse development provides a blueprint for studying the molecular basis and evolutionary changes of synapse maturation.

BACKGROUND: Although Kawasaki disease is commonly regarded as a single disease entity, variability in clinical manifestations and disease outcome has been recognised. We aimed to use a data-driven approach to identify clinical subgroups. METHODS: We analysed clinical data from patients with Kawasaki disease diagnosed at Rady Childrens Hospital (San Diego, CA, USA) between Jan 1, 2002, and June 30, 2022. Patients were grouped by hierarchical clustering on principal components with k-means parcellation based on 14 variables, including age at onset, ten laboratory test results, day of illness at the first intravenous immunoglobulin infusion, and normalised echocardiographic measures of coronary artery diameters at diagnosis. We also analysed the seasonality and Kawasaki disease incidence from 2002 to 2019 by subgroup. To explore the biological underpinnings of identified subgroups, we did differential abundance analysis on proteomic data of 6481 proteins from 32 patients with Kawasaki disease and 24 healthy children, using linear regression models that controlled for age and sex. FINDINGS: Among 1016 patients with complete data in the final analysis, four subgroups were identified with distinct clinical features: (1) hepatobiliary involvement with elevated alanine transaminase, gamma-glutamyl transferase, and total bilirubin levels, lowest coronary artery aneurysm but highest intravenous immunoglobulin resistance rates (n=157); (2) highest band neutrophil count and Kawasaki disease shock rate (n=231); (3) cervical lymphadenopathy with high markers of inflammation (erythrocyte sedimentation rate, C-reactive protein, white blood cell, and platelet counts) and lowest age-adjusted haemoglobin Z scores (n=315); and (4) young age at onset with highest coronary artery aneurysm but lowest intravenous immunoglobulin resistance rates (n=313). The subgroups had distinct seasonal and incidence trajectories. In addition, the subgroups shared 211 differential abundance proteins while many proteins were unique to a subgroup. INTERPRETATION: Our data-driven analysis provides insight into the heterogeneity of Kawasaki disease, and supports the existence of distinct subgroups with important implications for clinical management and research design and interpretation. FUNDING: US National Institutes of Health and the Irving and Francine Suknow Foundation.

Although many novel gene-metabolite and gene-protein associations have been identified using high-throughput biochemical profiling, systematic studies that leverage human genetics to illuminate causal relationships between circulating proteins and metabolites are lacking. Here, we performed protein-metabolite association studies in 3,626 plasma samples from three human cohorts. We detected 171,800 significant protein-metabolite pairwise correlations between 1,265 proteins and 365 metabolites, including established relationships in metabolic and signaling pathways such as the protein thyroxine-binding globulin and the metabolite thyroxine, as well as thousands of new findings. In Mendelian randomization (MR) analyses, we identified putative causal protein-to-metabolite associations. We experimentally validated top MR associations in proof-of-concept plasma metabolomics studies in three murine knockout strains of key protein regulators. These analyses identified previously unrecognized associations between bioactive proteins and metabolites in human plasma. We provide publicly available data to be leveraged for studies in human metabolism and disease.