Molecular-Level Dysregulation of Insulin Pathways and Inflammatory Processes in Peripheral Blood Mononuclear Cells by Circadian Misalignment.

Circadian misalignment due to night work has been associated with an elevated risk for chronic diseases. We investigated the effects of circadian misalignment using shotgun protein profiling of peripheral blood mononuclear cells taken from healthy humans during a constant routine protocol, which was conducted immediately after participants had been subjected to a 3-day simulated night shift schedule or a 3-day simulated day shift schedule. By comparing proteomic profiles between the simulated shift conditions, we identified proteins and pathways that are associated with the effects of circadian misalignment and observed that insulin regulation pathways and inflammation-related proteins displayed markedly different temporal patterns after simulated night shift. Further, by integrating the proteomic profiles with previously assessed metabolomic profiles in a network-based approach, we found key associations between circadian dysregulation of protein-level pathways and metabolites of interest in the context of chronic metabolic diseases. Endogenous circadian rhythms in circulating glucose and insulin differed between the simulated shift conditions. Overall, our results suggest that circadian misalignment is associated with a tug of war between central clock mechanisms controlling insulin secretion and peripheral clock mechanisms regulating insulin sensitivity, which may lead to adverse long-term outcomes such as diabetes and obesity. Our study provides a molecular-level mechanism linking circadian misalignment and adverse long-term health consequences of night work.

Macrophage-derived MLKL in alcohol-associated liver disease: Regulation of phagocytosis.

BACKGROUND AND AIMS: Mixed lineage kinase domain-like pseudokinase (MLKL), a key terminal effector of necroptosis, also plays a role in intracellular vesicle trafficking that is critical for regulating liver inflammation and injury in alcohol-associated liver disease (ALD). Although receptor interacting protein kinase 3 (Rip3)-/- mice are completely protected from ethanol-induced liver injury, Mlkl-/- mice are only partially protected. Therefore, we hypothesized that cell-specific functions of MLKL may contribute to ethanol-induced injury. APPROACH AND RESULTS: Bone marrow transplants between Mlkl-/- mice and littermates were conducted to distinguish the role of myeloid versus nonmyeloid Mlkl in the Gao-binge model of ALD. Ethanol-induced hepatic injury, steatosis, and inflammation were exacerbated in Mlkl-/- →wild-type (WT) mice, whereas Mlkl deficiency in nonmyeloid cells (WT→ Mlkl-/- ) had no effect on Gao-binge ethanol-induced injury. Importantly, Mlkl deficiency in myeloid cells exacerbated ethanol-mediated bacterial burden and accumulation of immune cells in livers. Mechanistically, challenging macrophages with lipopolysaccharide (LPS) induced signal transducer and activator of transcription 1-mediated expression and phosphorylation of MLKL, as well as translocation and oligomerization of MLKL to intracellular compartments, including phagosomes and lysosomes but not plasma membrane. Importantly, pharmacological or genetic inhibition of MLKL suppressed the phagocytic capability of primary mouse Kupffer cells (KCs) at baseline and in response to LPS with/without ethanol as well as peripheral monocytes isolated from both healthy controls and patients with alcohol-associated hepatitis. Further, in vivo studies revealed that KCs of Mlkl-/- mice phagocytosed fewer bioparticles than KCs of WT mice. CONCLUSION: Together, these data indicate that myeloid MLKL restricts ethanol-induced liver inflammation and injury by regulating hepatic immune cell homeostasis and macrophage phagocytosis.

Integrated Transcriptomic and Proteomic Analysis Identifies Plasma Biomarkers of Hepatocellular Failure in Alcohol-Associated Hepatitis.

Alcohol-associated hepatitis (AH) is a form of liver failure with high short-term mortality. Recent studies have shown that defective function of hepatocyte nuclear factor 4 alpha (HNF4a) and systemic inflammation are major disease drivers of AH. Plasma biomarkers of hepatocyte function could be useful for diagnostic and prognostic purposes. Herein, an integrative analysis of hepatic RNA sequencing and liquid chromatography-tandem mass spectrometry was performed to identify plasma protein signatures for patients with mild and severe AH. Alcohol-related liver disease cirrhosis, nonalcoholic fatty liver disease, and healthy subjects were used as comparator groups. Levels of identified proteins primarily involved in hepatocellular function were decreased in patients with AH, which included hepatokines, clotting factors, complement cascade components, and hepatocyte growth activators. A protein signature of AH disease severity was identified, including thrombin, hepatocyte growth factor α, clusterin, human serum factor H-related protein, and kallistatin, which exhibited large abundance shifts between severe and nonsevere AH. The combination of thrombin and hepatocyte growth factor α discriminated between severe and nonsevere AH with high sensitivity and specificity. These findings were correlated with the liver expression of genes encoding secreted proteins in a similar cohort, finding a highly consistent plasma protein signature reflecting HNF4A and HNF1A functions. This unbiased proteomic-transcriptome analysis identified plasma protein signatures and pathways associated with disease severity, reflecting HNF4A/1A activity useful for diagnostic assessment in AH.

Targeted Quantification of Protein Phosphorylation and Its Contributions towards Mathematical Modeling of Signaling Pathways.

Post-translational modifications (PTMs) are key regulatory mechanisms that can control protein function. Of these, phosphorylation is the most common and widely studied. Because of its importance in regulating cell signaling, precise and accurate measurements of protein phosphorylation across wide dynamic ranges are crucial to understanding how signaling pathways function. Although immunological assays are commonly used to detect phosphoproteins, their lack of sensitivity, specificity, and selectivity often make them unreliable for quantitative measurements of complex biological samples. Recent advances in Mass Spectrometry (MS)-based targeted proteomics have made it a more useful approach than immunoassays for studying the dynamics of protein phosphorylation. Selected reaction monitoring (SRM)-also known as multiple reaction monitoring (MRM)-and parallel reaction monitoring (PRM) can quantify relative and absolute abundances of protein phosphorylation in multiplexed fashions targeting specific pathways. In addition, the refinement of these tools by enrichment and fractionation strategies has improved measurement of phosphorylation of low-abundance proteins. The quantitative data generated are particularly useful for building and parameterizing mathematical models of complex phospho-signaling pathways. Potentially, these models can provide a framework for linking analytical measurements of clinical samples to better diagnosis and treatment of disease.

Tandem Mass Tag Labeling Facilitates Reversed-Phase Liquid Chromatography-Mass Spectrometry Analysis of Hydrophilic Phosphopeptides.

Protein phosphorylation is a critical post-translational modification (PTM). Despite recent technological advances in reversed-phase liquid chromatography (RPLC)-mass spectrometry (MS)-based proteomics, comprehensive phosphoproteomic coverage in complex biological systems remains challenging, especially for hydrophilic phosphopeptides with enriched regions of serines, threonines, and tyrosines that often orchestrate critical biological functions. To address this issue, we developed a simple, easily implemented method to introduce a commonly used tandem mass tag (TMT) to increase peptide hydrophobicity, effectively enhancing RPLC-MS analysis of hydrophilic peptides. Different from conventional TMT labeling, this method capitalizes on using a nonprimary amine buffer and TMT labeling occurring before C18-based solid phase extraction. Through phosphoproteomic analyses of MCF7 cells, we have demonstrated that this method can greatly increase the number of identified hydrophilic phosphopeptides and improve MS detection signals. We applied this method to study the peptide QPSSSR, a very hydrophilic tryptic peptide located on the C-terminus of the G protein-coupled receptor (GPCR) CXCR3. Identification of QPSSSR has never been reported, and we were unable to detect it by traditional methods. We validated our TMT labeling strategy by comparative RPLC-MS analyses of both a hydrophilic QPSSSR peptide library as well as common phosphopeptides. We further confirmed the utility of this method by quantifying QPSSSR phosphorylation abundances in HEK 293 cells under different treatment conditions predicted to alter QPSSSR phosphorylation. We anticipate that this simple TMT labeling method can be broadly used not only for decoding GPCR phosphoproteome but also for effective RPLC-MS analysis of other highly hydrophilic analytes.

Mitotic protein kinase CDK1 phosphorylation of mRNA translation regulator 4E-BP1 Ser83 may contribute to cell transformation.

Mammalian target of rapamycin (mTOR)-directed eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1) phosphorylation promotes cap-dependent translation and tumorigenesis. During mitosis, cyclin-dependent kinase 1 (CDK1) substitutes for mTOR and fully phosphorylates 4E-BP1 at canonical sites (T37, T46, S65, and T70) and the noncanonical S83 site, resulting in a mitosis-specific hyperphosphorylated δ isoform. Colocalization studies with a phospho-S83 specific antibody indicate that 4E-BP1 S83 phosphorylation accumulates at centrosomes during prophase, peaks at metaphase, and decreases through telophase. Although S83 phosphorylation of 4E-BP1 does not affect general cap-dependent translation, expression of an alanine substitution mutant 4E-BP1.S83A partially reverses rodent cell transformation induced by Merkel cell polyomavirus small T antigen viral oncoprotein. In contrast to inhibitory mTOR 4E-BP1 phosphorylation, these findings suggest that mitotic CDK1-directed phosphorylation of δ-4E-BP1 may yield a gain of function, distinct from translation regulation, that may be important in tumorigenesis and mitotic centrosome function.

Global Proteomic Analysis Reveals an Exclusive Role of Thylakoid Membranes in Bioenergetics of a Model Cyanobacterium.

Cyanobacteria are photosynthetic microbes with highly differentiated membrane systems. These organisms contain an outer membrane, plasma membrane, and an internal system of thylakoid membranes where the photosynthetic and respiratory machinery are found. This existence of compartmentalization and differentiation of membrane systems poses a number of challenges for cyanobacterial cells in terms of organization and distribution of proteins to the correct membrane system. Proteomics studies have long sought to identify the components of the different membrane systems in cyanobacteria, and to date about 450 different proteins have been attributed to either the plasma membrane or thylakoid membrane. Given the complexity of these membranes, many more proteins remain to be identified, and a comprehensive catalogue of plasma membrane and thylakoid membrane proteins is needed. Here we describe the identification of 635 differentially localized proteins in Synechocystis sp. PCC 6803 by quantitative iTRAQ isobaric labeling; of these, 459 proteins were localized to the plasma membrane and 176 were localized to the thylakoid membrane. Surprisingly, we found over 2.5 times the number of unique proteins identified in the plasma membrane compared with the thylakoid membrane. This suggests that the protein composition of the thylakoid membrane is more homogeneous than the plasma membrane, consistent with the role of the plasma membrane in diverse cellular processes including protein trafficking and nutrient import, compared with a more specialized role for the thylakoid membrane in cellular energetics. Thus, our data clearly define the two membrane systems with distinct functions. Overall, the protein compositions of the Synechocystis 6803 plasma membrane and thylakoid membrane are quite similar to that of the plasma membrane of Escherichia coli and thylakoid membrane of Arabidopsis chloroplasts, respectively. Synechocystis 6803 can therefore be described as a Gram-negative bacterium with an additional internal membrane system that fulfills the energetic requirements of the cell.

The landscape of viral proteomics and its potential to impact human health.

INTRODUCTION: Advances in mass spectrometry-based proteomic technologies are enhancing studies of viral pathogenesis. Identification and quantification of host and viral proteins and modifications in cells and extracellular fluids during infection provides useful information about pathogenesis, and will be critical for directing clinical interventions and diagnostics. AREAS COVERED: Herein we review and discuss a broad range of global proteomic studies conducted during viral infection, including those of cellular responses, protein modifications, virion packaging, and serum proteomics. We focus on viruses that impact human health and focus on experimental designs that reveal disease processes and surrogate markers. Expert commentary: Global proteomics is an important component of systems-level studies that aim to define how the interaction of humans and viruses leads to disease. Viral-community resource centers and strategies from other fields (e.g., cancer) will facilitate data sharing and platform-integration for systems-level analyses, and should provide recommended standards and assays for experimental designs and validation.

Proteome-wide light/dark modulation of thiol oxidation in cyanobacteria revealed by quantitative site-specific redox proteomics.

Reversible protein thiol oxidation is an essential regulatory mechanism of photosynthesis, metabolism, and gene expression in photosynthetic organisms. Herein, we present proteome-wide quantitative and site-specific profiling of in vivo thiol oxidation modulated by light/dark in the cyanobacterium Synechocystis sp. PCC 6803, an oxygenic photosynthetic prokaryote, using a resin-assisted thiol enrichment approach. Our proteomic approach integrates resin-assisted enrichment with isobaric tandem mass tag labeling to enable site-specific and quantitative measurements of reversibly oxidized thiols. The redox dynamics of ∼2,100 Cys-sites from 1,060 proteins under light, dark, and 3-(3,4-dichlorophenyl)-1,1-dimethylurea (a photosystem II inhibitor) conditions were quantified. In addition to relative quantification, the stoichiometry or percentage of oxidation (reversibly oxidized/total thiols) for ∼1,350 Cys-sites was also quantified. The overall results revealed broad changes in thiol oxidation in many key biological processes, including photosynthetic electron transport, carbon fixation, and glycolysis. Moreover, the redox sensitivity along with the stoichiometric data enabled prediction of potential functional Cys-sites for proteins of interest. The functional significance of redox-sensitive Cys-sites in NADP-dependent glyceraldehyde-3-phosphate dehydrogenase, peroxiredoxin (AhpC/TSA family protein Sll1621), and glucose 6-phosphate dehydrogenase was further confirmed with site-specific mutagenesis and biochemical studies. Together, our findings provide significant insights into the broad redox regulation of photosynthetic organisms.

Advancing the high throughput identification of liver fibrosis protein signatures using multiplexed ion mobility spectrometry.

Rapid diagnosis of disease states using less invasive, safer, and more clinically acceptable approaches than presently employed is a crucial direction for the field of medicine. While MS-based proteomics approaches have attempted to meet these objectives, challenges such as the enormous dynamic range of protein concentrations in clinically relevant biofluid samples coupled with the need to address human biodiversity have slowed their employment. Herein, we report on the use of a new instrumental platform that addresses these challenges by coupling technical advances in rapid gas phase multiplexed ion mobility spectrometry separations with liquid chromatography and MS to dramatically increase measurement sensitivity and throughput, further enabling future high throughput MS-based clinical applications. An initial application of the liquid chromatography--ion mobility spectrometry-MS platform analyzing blood serum samples from 60 postliver transplant patients with recurrent fibrosis progression and 60 nontransplant patients illustrates its potential utility for disease characterization.

Morphine produces immunosuppressive effects in nonhuman primates at the proteomic and cellular levels.

Morphine has long been known to have immunosuppressive properties in vivo, but the molecular and immunologic changes induced by it are incompletely understood. To explore how these changes interact with lentiviral infections in vivo, animals from two nonhuman primate species (African green monkeys and pigtailed macaques) were provided morphine and studied using a systems biology approach. Biological specimens were obtained from multiple sources (e.g. lymph node, colon, cerebrospinal fluid, and peripheral blood) before and after the administration of morphine (titrated up to a maximum dose of 5 mg/kg over a period of 20 days). Cellular immune, plasma cytokine, and proteome changes were measured and morphine-induced changes in these parameters were assessed on an interorgan, interindividual, and interspecies basis. In both species, morphine was associated with decreased levels of Ki-67(+) T-cell activation but with only minimal changes in overall T-cell counts, neutrophil counts, and NK cell counts. Although changes in T-cell maturation were observed, these varied across the various tissue/fluid compartments studied. Proteomic analysis revealed a morphine-induced suppressive effect in lymph nodes, with decreased abundance of protein mediators involved in the functional categories of energy metabolism, signaling, and maintenance of cell structure. These findings have direct relevance for understanding the impact of heroin addiction and the opioids used to treat addiction as well as on the potential interplay between opioid abuse and the immunological response to an infective agent.

Longitudinal analysis of host protein serum signatures of treatment and recovery in pulmonary tuberculosis.

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.

Identification of integrated proteomics and transcriptomics signature of alcohol-associated liver disease using machine learning.

Distinguishing between alcohol-associated hepatitis (AH) and alcohol-associated cirrhosis (AC) remains a diagnostic challenge. In this study, we used machine learning with transcriptomics and proteomics data from liver tissue and peripheral mononuclear blood cells (PBMCs) to classify patients with alcohol-associated liver disease. The conditions in the study were AH, AC, and healthy controls. We processed 98 PBMC RNAseq samples, 55 PBMC proteomic samples, 48 liver RNAseq samples, and 53 liver proteomic samples. First, we built separate classification and feature selection pipelines for transcriptomics and proteomics data. The liver tissue models were validated in independent liver tissue datasets. Next, we built integrated gene and protein expression models that allowed us to identify combined gene-protein biomarker panels. For liver tissue, we attained 90% nested-cross validation accuracy in our dataset and 82% accuracy in the independent validation dataset using transcriptomic data. We attained 100% nested-cross validation accuracy in our dataset and 61% accuracy in the independent validation dataset using proteomic data. For PBMCs, we attained 83% and 89% accuracy with transcriptomic and proteomic data, respectively. The integration of the two data types resulted in improved classification accuracy for PBMCs, but not liver tissue. We also identified the following gene-protein matches within the gene-protein biomarker panels: CLEC4M-CLC4M, GSTA1-GSTA2 for liver tissue and SELENBP1-SBP1 for PBMCs. In this study, machine learning models had high classification accuracy for both transcriptomics and proteomics data, across liver tissue and PBMCs. The integration of transcriptomics and proteomics into a multi-omics model yielded improvement in classification accuracy for the PBMC data. The set of integrated gene-protein biomarkers for PBMCs show promise toward developing a liquid biopsy for alcohol-associated liver disease.

Proteomics identifies complement protein signatures in patients with alcohol-associated hepatitis.

Diagnostic challenges continue to impede development of effective therapies for successful management of alcohol-associated hepatitis (AH), creating an unmet need to identify noninvasive biomarkers for AH. In murine models, complement contributes to ethanol-induced liver injury. Therefore, we hypothesized that complement proteins could be rational diagnostic/prognostic biomarkers in AH. Here, we performed a comparative analysis of data derived from human hepatic and serum proteome to identify and characterize complement protein signatures in severe AH (sAH). The quantity of multiple complement proteins was perturbed in liver and serum proteome of patients with sAH. Multiple complement proteins differentiated patients with sAH from those with alcohol cirrhosis (AC) or alcohol use disorder (AUD) and healthy controls (HCs). Serum collectin 11 and C1q binding protein were strongly associated with sAH and exhibited good discriminatory performance among patients with sAH, AC, or AUD and HCs. Furthermore, complement component receptor 1-like protein was negatively associated with pro-inflammatory cytokines. Additionally, lower serum MBL associated serine protease 1 and coagulation factor II independently predicted 90-day mortality. In summary, meta-analysis of proteomic profiles from liver and circulation revealed complement protein signatures of sAH, highlighting a complex perturbation of complement and identifying potential diagnostic and prognostic biomarkers for patients with sAH.

Proteome and computational analyses reveal new insights into the mechanisms of hepatitis C virus-mediated liver disease posttransplantation.

UNLABELLED: Liver transplant tissues offer the unique opportunity to model the longitudinal protein abundance changes occurring during hepatitis C virus (HCV)-associated liver disease progression in vivo. In this study, our goal was to identify molecular signatures, and potential key regulatory proteins, representative of the processes influencing early progression to fibrosis. We performed global protein profiling analyses on 24 liver biopsy specimens obtained from 15 HCV(+) liver transplant recipients at 6 and/or 12 months posttransplantation. Differentially regulated proteins associated with early progression to fibrosis were identified by analysis of the area under the receiver operating characteristic curve. Analysis of serum metabolites was performed on samples obtained from an independent cohort of 60 HCV(+) liver transplant patients. Computational modeling approaches were applied to identify potential key regulatory proteins of liver fibrogenesis. Among 4,324 proteins identified, 250 exhibited significant differential regulation in patients with rapidly progressive fibrosis. Patients with rapid fibrosis progression exhibited enrichment in differentially regulated proteins associated with various immune, hepatoprotective, and fibrogenic processes. The observed increase in proinflammatory activity and impairment in antioxidant defenses suggests that patients who develop significant liver injury experience elevated oxidative stresses. This was supported by an independent study demonstrating the altered abundance of oxidative stress-associated serum metabolites in patients who develop severe liver injury. Computational modeling approaches further highlight a potentially important link between HCV-associated oxidative stress and epigenetic regulatory mechanisms impacting on liver fibrogenesis. CONCLUSION: Our proteome and metabolome analyses provide new insights into the role for increased oxidative stress in the rapid fibrosis progression observed in HCV(+) liver transplant recipients. These findings may prove useful in prognostic applications for predicting early progression to fibrosis.

The Mycobacterium tuberculosis protein O-phosphorylation landscape.

Bacterial phosphosignalling has been synonymous with two-component systems and their histidine kinases, but many bacteria, including Mycobacterium tuberculosis (Mtb), also code for Ser/Thr protein kinases (STPKs). STPKs are the main phosphosignalling enzymes in eukaryotes but the full extent of phosphorylation on protein Ser/Thr and Tyr (O-phosphorylation) in bacteria is untested. Here we explored the global signalling capacity of the STPKs in Mtb using a panel of STPK loss-of-function and overexpression strains combined with mass spectrometry-based phosphoproteomics. A deep phosphoproteome with >14,000 unique phosphosites shows that O-phosphorylation in Mtb is a vastly underexplored protein modification that affects >80% of the proteome and extensively interfaces with the transcriptional machinery. Mtb O-phosphorylation gives rise to an expansive, distributed and cooperative network of a complexity that has not previously been seen in bacteria and that is on par with eukaryotic phosphosignalling networks. A resource of >3,700 high-confidence direct substrate-STPK interactions and their transcriptional effects provides signalling context for >80% of Mtb proteins and allows the prediction and assembly of signalling pathways for mycobacterial physiology.

Coupling microdroplet-based sample preparation, multiplexed isobaric labeling, and nanoflow peptide fractionation for deep proteome profiling of tissue microenvironment.

There is increasing interest in developing in-depth proteomic approaches for mapping tissue heterogeneity at a cell-type-specific level to better understand and predict the function of complex biological systems, such as human organs. Existing spatially resolved proteomics technologies cannot provide deep proteome coverages due to limited sensitivity and poor sample recovery. Herein, we seamlessly combined laser capture microdissection with a low-volume sample processing technology that includes a microfluidic device named microPOTS (Microdroplet Processing in One pot for Trace Samples), the multiplexed isobaric labelling, and a nanoflow peptide fractionation approach. The integrated workflow allowed to maximize proteome coverage of laser-isolated tissue samples containing nanogram proteins. We demonstrated the deep spatial proteomics can quantify more than 5,000 unique proteins from a small-sized human pancreatic tissue pixel (∼60,000 µm2) and reveal unique islet microenvironments.

Phosphorylation barcodes direct biased chemokine signaling at CXCR3.

G protein-coupled receptor (GPCR) biased agonism, the activation of some signaling pathways over others, is thought to largely be due to differential receptor phosphorylation, or "phosphorylation barcodes." At chemokine receptors, ligands act as "biased agonists" with complex signaling profiles, which contributes to the limited success in pharmacologically targeting these receptors. Here, mass spectrometry-based global phosphoproteomics revealed that CXCR3 chemokines generate different phosphorylation barcodes associated with differential transducer activation. Chemokine stimulation resulted in distinct changes throughout the kinome in global phosphoproteomic studies. Mutation of CXCR3 phosphosites altered ß-arrestin conformation in cellular assays and was confirmed by molecular dynamics simulations. T cells expressing phosphorylation-deficient CXCR3 mutants resulted in agonist- and receptor-specific chemotactic profiles. Our results demonstrate that CXCR3 chemokines are non-redundant and act as biased agonists through differential encoding of phosphorylation barcodes and lead to distinct physiological processes.

Phosphorylation barcodes direct biased chemokine signaling at CXCR3.

G protein-coupled receptor (GPCR)-biased agonism, selective activation of certain signaling pathways relative to others, is thought to be directed by differential GPCR phosphorylation "barcodes." At chemokine receptors, endogenous chemokines can act as "biased agonists", which may contribute to the limited success when pharmacologically targeting these receptors. Here, mass spectrometry-based global phosphoproteomics revealed that CXCR3 chemokines generate different phosphorylation barcodes associated with differential transducer activation. Chemokine stimulation resulted in distinct changes throughout the kinome in global phosphoproteomics studies. Mutation of CXCR3 phosphosites altered ß-arrestin 2 conformation in cellular assays and was consistent with conformational changes observed in molecular dynamics simulations. T cells expressing phosphorylation-deficient CXCR3 mutants resulted in agonist- and receptor-specific chemotactic profiles. Our results demonstrate that CXCR3 chemokines are non-redundant and act as biased agonists through differential encoding of phosphorylation barcodes, leading to distinct physiological processes.

Predicting chronic postsurgical pain: current evidence and a novel program to develop predictive biomarker signatures.

ABSTRACT: Chronic pain affects more than 50 million Americans. Treatments remain inadequate, in large part, because the pathophysiological mechanisms underlying the development of chronic pain remain poorly understood. Pain biomarkers could potentially identify and measure biological pathways and phenotypical expressions that are altered by pain, provide insight into biological treatment targets, and help identify at-risk patients who might benefit from early intervention. Biomarkers are used to diagnose, track, and treat other diseases, but no validated clinical biomarkers exist yet for chronic pain. To address this problem, the National Institutes of Health Common Fund launched the Acute to Chronic Pain Signatures (A2CPS) program to evaluate candidate biomarkers, develop them into biosignatures, and discover novel biomarkers for chronification of pain after surgery. This article discusses candidate biomarkers identified by A2CPS for evaluation, including genomic, proteomic, metabolomic, lipidomic, neuroimaging, psychophysical, psychological, and behavioral measures. Acute to Chronic Pain Signatures will provide the most comprehensive investigation of biomarkers for the transition to chronic postsurgical pain undertaken to date. Data and analytic resources generatedby A2CPS will be shared with the scientific community in hopes that other investigators will extract valuable insights beyond A2CPS's initial findings. This article will review the identified biomarkers and rationale for including them, the current state of the science on biomarkers of the transition from acute to chronic pain, gaps in the literature, and how A2CPS will address these gaps.