Targeting low levels of MIF expression as a potential therapeutic strategy for ALS.

Mutations in SOD1 cause amyotrophic lateral sclerosis (ALS), a neurodegenerative disease characterized by motor neuron (MN) loss. We previously discovered that macrophage migration inhibitory factor (MIF), whose levels are extremely low in spinal MNs, inhibits mutant SOD1 misfolding and toxicity. In this study, we show that a single peripheral injection of adeno-associated virus (AAV) delivering MIF into adult SOD1G37R mice significantly improves their motor function, delays disease progression, and extends survival. Moreover, MIF treatment reduces neuroinflammation and misfolded SOD1 accumulation, rescues MNs, and corrects dysregulated pathways as observed by proteomics and transcriptomics. Furthermore, we reveal low MIF levels in human induced pluripotent stem cell-derived MNs from familial ALS patients with different genetic mutations, as well as in post mortem tissues of sporadic ALS patients. Our findings indicate that peripheral MIF administration may provide a potential therapeutic mechanism for modulating misfolded SOD1 in vivo and disease outcome in ALS patients.

Paradigm shift in biomarker translation: a pipeline to generate clinical grade biomarker candidates from DIA-MS discovery.

Clinical biomarker development has been stymied by inaccurate protein quantification from mass spectrometry (MS) discovery data and a prolonged validation process. To mitigate these issues, we created the Targeted Extraction Assessment of Quantification (TEAQ) software package. This innovative tool uses the discovery cohort analysis to select precursors, peptides, and proteins that adhere to established targeted assay criteria. TEAQ was applied to Data-Independent Acquisition MS data from plasma samples acquired on an Orbitrap™ Astral™ MS. Identified precursors were evaluated for linearity, specificity, repeatability, reproducibility, and intra-protein correlation from 11-point loading curves under three throughputs, to develop a resource for clinical-grade targeted assays. From a clinical cohort of individuals with inflammatory bowel disease (n=492), TEAQ successfully identified 1116 signature peptides for 327 quantifiable proteins from 1180 identified proteins. Embedding stringent selection criteria adaptable to targeted assay development into the analysis of discovery data will streamline the transition to validation and clinical studies.

A novel micropeptide, Slitharin, exerts cardioprotective effects in myocardial infarction.

PURPOSE: Micropeptides are an emerging class of proteins that play critical roles in cell signaling. Here, we describe the discovery of a novel micropeptide, dubbed slitharin (Slt), in conditioned media from Cardiosphere-derived cells (CDCs), a therapeutic cardiac stromal cell type. EXPERIMENTAL DESIGN: We performed mass spectrometry of peptide-enriched fractions from the conditioned media of CDCs and a therapeutically inert cell type (human dermal fibrobasts). We then evaluated the therapeutic capacity of the candidate peptide using an in vitro model of cardiomyocyte injury and a rat model of myocardial infarction. RESULTS: We identified a novel 24-amino acid micropeptide (dubbed Slitharin [Slt]) with a non-canonical leucine start codon, arising from long intergenic non-coding (LINC) RNA 2099. Neonatal rat ventricular myocytes (NRVMs) exposed to Slt were protected from hypoxic injury in vitro compared to a vehicle or scrambled control. Transcriptomic analysis of cardiomyocytes exposed to Slt reveals cytoprotective capacity, putatively through regulation of stress-induced MAPK-ERK. Slt also exerted cardioprotective effects in rats with myocardial infarction as shown by reduced infarct size 48 h post-injury. Conclusions and clinical relavance: Thus, Slt is a non-coding RNA-derived micropeptide, identified in the extracellular space, with a potential cardioprotective function.

Treatment of human cardiac fibroblasts with the protein arginine deiminase inhibitor BB-Cl-amidine activates the Nrf2/HO-1 signaling pathway.

BACKGROUND: Cardiac fibrosis contributes to end-stage extracellular matrix remodeling and heart failure (HF). Cardiac fibroblasts (CFs) differentiate into myofibroblasts (myoFbs) to preserve the structural integrity of the heart; however, the molecular mechanisms regulating CF transdifferentiation remain poorly understood. Protein arginine deiminase (PAD), which converts arginine to citrulline, has been shown to play a role in myocardial infarction, fibrosis, and HF. This study aimed to investigate the role of PAD in CF differentiation to myoFbs and identify the citrullinated proteins that were associated with phenotypic changes in CFs. RESULTS: Gene expression analysis showed that PAD1 and PAD2 isoforms, but not PAD4 isoforms, were abundant in both CFs and myoFbs, and PAD1 was significantly upregulated in myoFbs. The pan-PAD inhibitor BB-Cl-amidine (BB-Cl) downregulated the mRNA expression of PAD1 and PAD2 as well as the protein expression of the fibrosis marker COL1A1 in CFs and myoFbs. Interestingly, a proteomic approach pointed to the activation of the Nrf2/HO-1 signaling pathway upon BB-Cl treatment in CFs and myoFbs. BB-Cl administration resulted in the upregulation of HO-1 at both the gene and protein levels in CFs and myoFbs. Importantly, the protein citrullination landscape of CFs consisting of 86 novel citrullination sites associated with focal adhesion (FN1(R1054)), inflammation (TAGLN(R12)) and DNA replication (EEF2(R767)) pathways was identified. CONCLUSIONS: In summary, we revealed that BB-Cl treatment resulted in increased HO-1 expression via the Nrf2 pathway, which could prevent excessive tissue damage, thereby leading to substantial clinical benefits for the treatment of cardiac fibrosis.

Peptidyl arginine deiminase inhibition alleviates angiotensin II-induced fibrosis.

OBJECTIVES: The conversion of protein arginine residues to citrulline by calcium-dependent peptidyl arginine deiminases (PADs) has been implicated in the pathogenesis of several diseases, indicating that PADs are therapeutic targets. A recent study indicated that PAD4 regulates age-related organ fibrosis and dysfunction; however, the specific role of this PAD and its citrullination substrate remains unclear. We investigated whether pharmacological inhibition of PAD activity could affect the progression of fibrosis and restore heart function. METHODS: Cardiac hypertrophy was induced by chronic infusion of angiotensin (Ang) II. After 2 weeks of AngII infusion, a PAD inhibitor (Cl-amidine hydrochloride) or vehicle (saline) was injected every other day for the next 14 days together with the continued administration of AngII for a total of up to 28 days. Cardiac fibrosis and remodeling were evaluated by quantitative heart tissue histology, echocardiography, and mass spectrometry. RESULTS: A reverse AngII-induced effect was observed in PAD inhibitor-treated mice (n=6) compared with AngII vehicle-treated mice, as indicated by a significant reduction in the heart/body ratio (AngII: 6.51±0.8 mg/g vs. Cl-amidine: 5.27±0.6 mg/g), a reduction in fibrosis (AngII: 2.1-fold increased vs. Cl-amidine: 1.8-fold increased), and a reduction in left ventricular posterior wall diastole (LWVPd) (AngII: 1.1±0.04 vs. Cl-amidine: 0.78±0.02 mm). Label-free quantitative proteomics analysis of heart tissue indicated that proteins involved in fibrosis (e.g., periostin), cytoskeleton organization (e.g., transgelin), and remodeling (e.g., myosin light chain, carbonic anhydrase) were normalized by Cl-amidine treatment. CONCLUSION: Our findings demonstrate that pharmacological inhibition of PAD may be an effective strategy to attenuate cardiac fibrosis.

Hyperphosphorylation of hepatic proteome characterizes nonalcoholic fatty liver disease in S-adenosylmethionine deficiency.

Methionine adenosyltransferase 1a (MAT1A) is responsible for hepatic S-adenosyl-L-methionine (SAMe) biosynthesis. Mat1a -/- mice have hepatic SAMe depletion, develop nonalcoholic steatohepatitis (NASH) which is reversed with SAMe administration. We examined temporal alterations in the proteome/phosphoproteome in pre-disease and NASH Mat1a -/- mice, effects of SAMe administration, and compared to human nonalcoholic fatty liver disease (NAFLD). Mitochondrial and peroxisomal lipid metabolism proteins were altered in pre-disease mice and persisted in NASH Mat1a -/- mice, which exhibited more progressive alterations in cytoplasmic ribosomes, ER, and nuclear proteins. A common mechanism found in both pre-disease and NASH livers was a hyperphosphorylation signature consistent with casein kinase 2α (CK2α) and AKT1 activation, which was normalized by SAMe administration. This was mimicked in human NAFLD with a metabolomic signature (M-subtype) resembling Mat1a -/- mice. In conclusion, we have identified a common proteome/phosphoproteome signature between Mat1a -/- mice and human NAFLD M-subtype that may have pathophysiological and therapeutic implications.

BIRCH: An Automated Workflow for Evaluation, Correction, and Visualization of Batch Effect in Bottom-Up Mass Spectrometry-Based Proteomics Data.

Recent surges in large-scale mass spectrometry (MS)-based proteomics studies demand a concurrent rise in methods to facilitate reliable and reproducible data analysis. Quantification of proteins in MS analysis can be affected by variations in technical factors such as sample preparation and data acquisition conditions leading to batch effects, which adds to noise in the data set. This may in turn affect the effectiveness of any biological conclusions derived from the data. Here we present Batch-effect Identification, Representation, and Correction of Heterogeneous data (BIRCH), a workflow for analysis and correction of batch effect through an automated, versatile, and easy to use web-based tool with the goal of eliminating technical variation. BIRCH also supports diagnosis of the data to check for the presence of batch effects, feasibility of batch correction, and imputation to deal with missing values in the data set. To illustrate the relevance of the tool, we explore two case studies, including an iPSC-derived cell study and a Covid vaccine study to show different context-specific use cases. Ultimately this tool can be used as an extremely powerful approach for eliminating technical bias while retaining biological bias, toward understanding disease mechanisms and potential therapeutics.

A panel of blood biomarkers unique to sudden cardiac arrest.

BACKGROUND: The identification of circulating biomarkers specific for sudden cardiac arrest (SCA) could enhance risk prediction. Of particular interest are biomarkers specific to SCA, independent of coronary artery disease (CAD). OBJECTIVE: The purpose of this study was to identify biomarkers of SCA obtained close to the SCA event. METHODS: Twenty cases (survivors of SCA) and 40 age- and sex-matched controls were compared, with a replication analysis of 29 cases matched to 57 controls. A secondary analysis compared 20 SCA cases to 20 controls with CAD. Blood samples were obtained from SCA survivors at a median of 11 months after the SCA event. Proteins were analyzed on a mass spectrometer using data-independent acquisition; a subset of cytokines were analyzed using immunoassays; and 1153 lipids (13 classes) were analyzed. A false discovery rate P value of <.05 identified associated proteins. RESULTS: Patients had a mean age of 58 years (range 25-87 years), and 70% were male. A total of 26 protein biomarkers associated with SCA when cases were compared with controls, of which 20 differentiated SCA from CAD. The replication analysis identified 8 of 26 biomarkers, of which 6 were not overlapping with CAD. The top identified biological processes involved the extracellular matrix, coagulation cascades, and platelet activation. Lipids in the lysophosphatidylcholine class were implicated in SCA through the CAD pathway. CONCLUSION: We identified a panel of novel blood biomarkers specifically associated with SCA, including several that may be involved outside the CAD pathway. These biomarkers could have mechanistic significance and the potential to enhance clinical prediction of SCA.

Protein arginine deiminase 2 (PAD2) modulates the polarization of THP-1 macrophages to the anti-inflammatory M2 phenotype.

BACKGROUND: Macrophages are effector cells of the innate immune system that undergo phenotypical changes in response to organ injury and repair. These cells are most often classified as proinflammatory M1 and anti-inflammatory M2 macrophages. Protein arginine deiminase (PAD), which catalyses the irreversible conversion of protein-bound arginine into citrulline, is expressed in macrophages. However, the substrates of PAD and its role in immune cells remain unclear. This study aimed to investigate the role of PAD in THP-1 macrophage polarization to the M1 and M2 phenotypes and identify the citrullinated proteins and modified arginines that are associated with this biological switch using mass spectrometry. RESULTS: Our study showed that PAD2 and, to a lesser extent, PAD1 and PAD4 were predominantly expressed in M1 macrophages. We showed that inhibiting PAD expression with BB-Cl-amidine decreased macrophage polarization to the M1 phenotype (TNF-α, IL-6) and increased macrophage polarization to the M2 phenotype (MRC1, ALOX15). This process was mediated by the downregulation of proteins involved in the NF-κß pathway. Silencing PAD2 confirmed the activation of M2 macrophages by increasing the antiviral innate immune response and interferon signalling. A total of 192 novel citrullination sites associated with inflammation, cell death and DNA/RNA processing pathways were identified in M1 and M2 macrophages. CONCLUSIONS: We showed that inhibiting PAD activity using a pharmacological inhibitor or silencing PAD2 with PAD2 siRNA shifted the activation of macrophages towards the M2 phenotype, which can be crucial for designing novel macrophage-mediated therapeutic strategies. We revealed a major citrullinated proteome and its rearrangement following macrophage polarization, which after further validation could lead to significant clinical benefits for the treatment of inflammation and autoimmune diseases.

Answer ALS, a large-scale resource for sporadic and familial ALS combining clinical and multi-omics data from induced pluripotent cell lines.

Answer ALS is a biological and clinical resource of patient-derived, induced pluripotent stem (iPS) cell lines, multi-omic data derived from iPS neurons and longitudinal clinical and smartphone data from over 1,000 patients with ALS. This resource provides population-level biological and clinical data that may be employed to identify clinical-molecular-biochemical subtypes of amyotrophic lateral sclerosis (ALS). A unique smartphone-based system was employed to collect deep clinical data, including fine motor activity, speech, breathing and linguistics/cognition. The iPS spinal neurons were blood derived from each patient and these cells underwent multi-omic analytics including whole-genome sequencing, RNA transcriptomics, ATAC-sequencing and proteomics. The intent of these data is for the generation of integrated clinical and biological signatures using bioinformatics, statistics and computational biology to establish patterns that may lead to a better understanding of the underlying mechanisms of disease, including subgroup identification. A web portal for open-source sharing of all data was developed for widespread community-based data analytics.

pH/Acetonitrile-Gradient Reversed-Phase Fractionation of Enriched Hyper-Citrullinated Library in Combination with LC-MS/MS Analysis for Confident Identification of Citrullinated Peptides.

Citrullination, the Ca2+-driven enzymatic conversion of arginine residues to citrulline, is a posttranslational modification, implicated in several physiological and pathological processes. Several methods to detect citrullinated proteins have been developed, including color development reagent, fluorescence, phenylglyoxal, and antibody-based methods. These methods yet suffer from limitations in sensitivity, specificity, or citrullinated site determination. Mass spectrometry (MS)-based proteomic analysis has emerged as a promising method to resolve these problems. However, due to low abundance of citrullinated proteins and similar MS features to deamidation of asparagine and glutamine, confident identification of citrullinated proteome is challenging. Here, we present a systematic approach to identify a compendium of steps to enhance the number of detected citrullinated residue and implement diagnostic MS feature that allow the confidence of MS-based identifications. Our method is based on the concept of generation of hyper-citrullinated library with high-pH reversed-phase peptide fractionation that allows to enrich in low abundance citrullinated peptides and amplify the effect of charge loss upon citrullination. Application of our approach to complex global citrullino-proteome datasets demonstrates the confident assessment of citrullinated peptides, thereby enhancing the size and functional interpretation of citrullinated proteomes.

Gene and protein expression in human megakaryocytes derived from induced pluripotent stem cells.

BACKGROUND: There is interest in deriving megakaryocytes (MKs) from pluripotent stem cells (iPSC) for biological studies. We previously found that genomic structural integrity and genotype concordance is maintained in iPSC-derived MKs. OBJECTIVE: To establish a comprehensive dataset of genes and proteins expressed in iPSC-derived MKs. METHODS: iPSCs were reprogrammed from peripheral blood mononuclear cells (MNCs) and MKs were derived from the iPSCs in 194 healthy European American and African American subjects. mRNA was isolated and gene expression measured by RNA sequencing. Protein expression was measured in 62 of the subjects using mass spectrometry. RESULTS AND CONCLUSIONS: MKs expressed genes and proteins known to be important in MK and platelet function and demonstrated good agreement with previous studies in human MKs derived from CD34+ progenitor cells. The percent of cells expressing the MK markers CD41 and CD42a was consistent in biological replicates, but variable across subjects, suggesting that unidentified subject-specific factors determine differentiation of MKs from iPSCs. Gene and protein sets important in platelet function were associated with increasing expression of CD41/42a, while those related to more basic cellular functions were associated with lower CD41/42a expression. There was differential gene expression by the sex and race (but not age) of the subject. Numerous genes and proteins were highly expressed in MKs but not known to play a role in MK or platelet function; these represent excellent candidates for future study of hematopoiesis, platelet formation, and/or platelet function.

PINE: An Automation Tool to Extract and Visualize Protein-Centric Functional Networks.

Recent surges in mass spectrometry-based proteomics studies demand a concurrent rise in speedy and optimized data processing tools and pipelines. Although several stand-alone bioinformatics tools exist that provide protein-protein interaction (PPI) data, we developed Protein Interaction Network Extractor (PINE) as a fully automated, user-friendly, graphical user interface application for visualization and exploration of global proteome and post-translational modification (PTM) based networks. PINE also supports overlaying differential expression, statistical significance thresholds, and PTM sites on functionally enriched visualization networks to gain insights into proteome-wide regulatory mechanisms and PTM-mediated networks. To illustrate the relevance of the tool, we explore the total proteome and its PTM-associated relationships in two different nonalcoholic steatohepatitis (NASH) mouse models to demonstrate different context-specific case studies. The strength of this tool relies in its ability to (1) perform accurate protein identifier mapping to resolve ambiguity, (2) retrieve interaction data from multiple publicly available PPI databases, and (3) assimilate these complex networks into functionally enriched pathways, ontology categories, and terms. Ultimately, PINE can be used as an extremely powerful tool for novel hypothesis generation to understand underlying disease mechanisms.

Genetic heterogeneity within collective invasion packs drives leader and follower cell phenotypes.

Collective invasion, the coordinated movement of cohesive packs of cells, has become recognized as a major mode of metastasis for solid tumors. These packs are phenotypically heterogeneous and include specialized cells that lead the invasive pack and others that follow behind. To better understand how these unique cell types cooperate to facilitate collective invasion, we analyzed transcriptomic sequence variation between leader and follower populations isolated from the H1299 non-small cell lung cancer cell line using an image-guided selection technique. We now identify 14 expressed mutations that are selectively enriched in leader or follower cells, suggesting a novel link between genomic and phenotypic heterogeneity within a collectively invading tumor cell population. Functional characterization of two phenotype-specific candidate mutations showed that ARP3 enhances collective invasion by promoting the leader cell phenotype and that wild-type KDM5B suppresses chain-like cooperative behavior. These results demonstrate an important role for distinct genetic variants in establishing leader and follower phenotypes and highlight the necessity of maintaining a capacity for phenotypic plasticity during collective cancer invasion.

Proteome-wide Structural Analysis of PTM Hotspots Reveals Regulatory Elements Predicted to Impact Biological Function and Disease.

Post-translational modifications (PTMs) regulate protein behavior through modulation of protein-protein interactions, enzymatic activity, and protein stability essential in the translation of genotype to phenotype in eukaryotes. Currently, less than 4% of all eukaryotic PTMs are reported to have biological function - a statistic that continues to decrease with an increasing rate of PTM detection. Previously, we developed SAPH-ire (Structural Analysis of PTM Hotspots) - a method for the prioritization of PTM function potential that has been used effectively to reveal novel PTM regulatory elements in discrete protein families (Dewhurst et al., 2015). Here, we apply SAPH-ire to the set of eukaryotic protein families containing experimental PTM and 3D structure data - capturing 1,325 protein families with 50,839 unique PTM sites organized into 31,747 modified alignment positions (MAPs), of which 2010 (∼6%) possess known biological function. Here, we show that using an artificial neural network model (SAPH-ire NN) trained to identify MAP hotspots with biological function results in prediction outcomes that far surpass the use of single hotspot features, including nearest neighbor PTM clustering methods. We find the greatest enhancement in prediction for positions with PTM counts of five or less, which represent 98% of all MAPs in the eukaryotic proteome and 90% of all MAPs found to have biological function. Analysis of the top 1092 MAP hotspots revealed 267 of truly unknown function (containing 5443 distinct PTMs). Of these, 165 hotspots could be mapped to human KEGG pathways for normal and/or disease physiology. Many high-ranking hotspots were also found to be disease-associated pathogenic sites of amino acid substitution despite the lack of observable PTM in the human protein family member. Taken together, these experiments demonstrate that the functional relevance of a PTM can be predicted very effectively by neural network models, revealing a large but testable body of potential regulatory elements that impact hundreds of different biological processes important in eukaryotic biology and human health.

iTAP: integrated transcriptomics and phenotype database for stress response of Escherichia coli and Saccharomyces cerevisiae.

BACKGROUND: Organisms are subject to various stress conditions, which affect both the organism's gene expression and phenotype. It is critical to understand microbial responses to stress conditions and uncover the underlying molecular mechanisms. To this end, it is necessary to build a database that collects transcriptomics and phenotypic data of microbes growing under various stress factors for in-depth systems biology analysis. Despite of numerous databases that collect gene expression profiles, to our best knowledge, there are few, if any, databases that collect both transcriptomics and phenotype data simultaneously. In light of this, we have developed an open source, web-based database, namely integrated transcriptomics and phenotype (iTAP) database, that records and links the transcriptomics and phenotype data for two model microorganisms, Escherichia coli and Saccharomyces cerevisiae in response to exposure of various stress conditions. RESULTS: To collect the data, we chose relevant research papers from the PubMed database containing all the necessary information for data curation including experimental conditions, transcriptomics data, and phenotype data. The transcriptomics data, including the p value and fold change, were obtained through the comparison of test strains against control strains using Gene Expression Omnibus's GEO2R analyzer. The phenotype data, including the cell growth rate and the productivity, volumetric rate, and mass-based yield of byproducts, were calculated independently from charts or graphs within the reference papers. Since the phenotype data was never reported in a standardized format, the curation of correlated transcriptomics-phenotype datasets became extremely tedious and time-consuming. Despite the challenges, till now, we successfully correlated 57 and 143 datasets of transcriptomics and phenotype for E. coli and S. cerevisiae, respectively, and applied a regression model within the iTAP database to accurately predict over 93 and 73 % of the growth rates of E. coli and S. cerevisiae, respectively, directly from the transcriptomics data. CONCLUSION: This is the first time that transcriptomics and phenotype data are categorized and correlated in an open-source database. This allows biologists to access the database and utilize it to predict the phenotype of microorganisms from their transcriptomics data. The iTAP database is freely available at https://sites.google.com/a/vt.edu/biomolecular-engineering-lab/software .