An inflection point in high-throughput proteomics with Orbitrap Astral: analysis of biofluids, cells, and tissues.

This technical note presents a comprehensive proteomics workflow for the new combination of Orbitrap and Astral mass analyzers across biofluids, cells, and tissues. Central to our workflow is the integration of Adaptive Focused Acoustics (AFA) technology for cells and tissue lysis, to ensure robust and reproducible sample preparation in a high-throughput manner. Furthermore, we automated the detergent-compatible single-pot, solid-phase-enhanced sample Preparation (SP3) method for protein digestion, a technique that streamlines the process by combining purification and digestion steps, thereby reducing sample loss and improving efficiency. The synergy of these advanced methodologies facilitates a robust and high-throughput approach for cells and tissue analysis, an important consideration in translational research. This work disseminates our platform workflow, analyzes the effectiveness, demonstrates reproducibility of the results, and highlights the potential of these technologies in biomarker discovery and disease pathology. For cells and tissues (heart, liver, lung, and intestine) proteomics analysis by data-independent acquisition mode, identifications exceeding 10,000 proteins can be achieved with a 24-minute active gradient. In 200ng injections of HeLa digest across multiple gradients, an average of more than 80% of proteins have a CV less than 20%, and a 45-minute run covers ∼90% of the expressed proteome. In plasma samples including naive, depleted, perchloric acid precipitated, and Seer nanoparticle captured, all with a 24-minute gradient length, we identified 87, 108, 96 and 137 out of 216 FDA approved circulating protein biomarkers, respectively. This complete workflow allows for large swaths of the proteome to be identified and is compatible across diverse sample types.

HIC1 interacts with FOXP3 multi protein complex: Novel pleiotropic mechanisms to regulate human regulatory T cell differentiation and function.

Transcriptional repressor, hypermethylated in cancer 1 (HIC1) participates in a range of important biological processes, such as tumor repression, immune suppression, embryonic development and epigenetic gene regulation. Further to these, we previously demonstrated that HIC1 provides a significant contribution to the function and development of regulatory T (Treg) cells. However, the mechanism by which it regulates these processes was not apparent. To address this question, we used affinity-purification mass spectrometry to characterize the HIC1 interactome in human Treg cells. Altogether 61 high-confidence interactors were identified, including IKZF3, which is a key transcription factor in the development of Treg cells. The biological processes associated with these interacting proteins include protein transport, mRNA processing, non-coding (ncRNA) transcription and RNA metabolism. The results revealed that HIC1 is part of a FOXP3-RUNX1-CBFB protein complex that regulates Treg signature genes thus improving our understanding of HIC1 function during early Treg cell differentiation.

Serum APOC1 levels are decreased in young autoantibody positive children who rapidly progress to type 1 diabetes.

Better understanding of the early events in the development of type 1 diabetes is needed to improve prediction and monitoring of the disease progression during the substantially heterogeneous presymptomatic period of the beta cell damaging process. To address this concern, we used mass spectrometry-based proteomics to analyse longitudinal pre-onset plasma sample series from children positive for multiple islet autoantibodies who had rapidly progressed to type 1 diabetes before 4 years of age (n = 10) and compared these with similar measurements from matched children who were either positive for a single autoantibody (n = 10) or autoantibody negative (n = 10). Following statistical analysis of the longitudinal data, targeted serum proteomics was used to verify 11 proteins putatively associated with the disease development in a similar yet independent and larger cohort of children who progressed to the disease within 5 years of age (n = 31) and matched autoantibody negative children (n = 31). These data reiterated extensive age-related trends for protein levels in young children. Further, these analyses demonstrated that the serum levels of two peptides unique for apolipoprotein C1 (APOC1) were decreased after the appearance of the first islet autoantibody and remained relatively less abundant in children who progressed to type 1 diabetes, in comparison to autoantibody negative children.

Cardiovascular-related proteomic changes in ECFCs exposed to the serum of COVID-19 patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection significantly affects the cardiovascular system, causing vascular damage and thromboembolic events in critical patients. Endothelial dysfunction represents one of the first steps in response to COVID-19 that might lead to cardiovascular complications and long-term sequelae. However, despite the enormous efforts in the last two years, the molecular mechanisms involved in such processes remain poorly understood. Herein, we analyzed the protein changes taking place in endothelial colony forming cells (ECFCs) after the incubation with the serum from individuals infected with COVID-19, whether asymptomatic or critical patients, by application of a label free-quantitative proteomics approach. Specifically, ECFCs from healthy individuals were incubated ex-vivo with the serum of either COVID-19 negative donors (PCR-/IgG-, n:8), COVID-19 asymptomatic donors at different infective stages (PCR+/ IgG-, n:8and PCR-/IgG+, n:8), or hospitalized critical COVID-19 patients (n:8), followed by proteomics analysis. In total, 590 proteins were differentially expressed in ECFCs in response to all infected serums. Predictive analysis highlighted several proteins like CAPN5, SURF4, LAMP2 or MT-ND1, as highly discriminating features between the groups compared. Protein changes correlated with viral infection, RNA metabolism or autophagy, among others. Remarkably, the angiogenic potential of ECFCs in response to the infected serums was impaired, and many of the protein alterations in response to the serum of critical patients were associated with cardiovascular-related pathologies.

A systematic comparison of FOSL1, FOSL2 and BATF-mediated transcriptional regulation during early human Th17 differentiation.

Th17 cells are essential for protection against extracellular pathogens, but their aberrant activity can cause autoimmunity. Molecular mechanisms that dictate Th17 cell-differentiation have been extensively studied using mouse models. However, species-specific differences underscore the need to validate these findings in human. Here, we characterized the human-specific roles of three AP-1 transcription factors, FOSL1, FOSL2 and BATF, during early stages of Th17 differentiation. Our results demonstrate that FOSL1 and FOSL2 co-repress Th17 fate-specification, whereas BATF promotes the Th17 lineage. Strikingly, FOSL1 was found to play different roles in human and mouse. Genome-wide binding analysis indicated that FOSL1, FOSL2 and BATF share occupancy over regulatory regions of genes involved in Th17 lineage commitment. These AP-1 factors also share their protein interacting partners, which suggests mechanisms for their functional interplay. Our study further reveals that the genomic binding sites of FOSL1, FOSL2 and BATF harbour hundreds of autoimmune disease-linked SNPs. We show that many of these SNPs alter the ability of these transcription factors to bind DNA. Our findings thus provide critical insights into AP-1-mediated regulation of human Th17-fate and associated pathologies.

HDL proteome remodeling associates with COVID-19 severity.

BACKGROUND: Besides the well-accepted role in lipid metabolism, high-density lipoprotein (HDL) also seems to participate in host immune response against infectious diseases. OBJECTIVE: We used a quantitative proteomic approach to test the hypothesis that alterations in HDL proteome associate with severity of Coronavirus disease 2019 (COVID-19). METHODS: Based on clinical criteria, subjects (n=41) diagnosed with COVID-19 were divided into two groups: a group of subjects presenting mild symptoms and a second group displaying severe symptoms and requiring hospitalization. Using a proteomic approach, we quantified the levels of 29 proteins in HDL particles derived from these subjects. RESULTS: We showed that the levels of serum amyloid A 1 and 2 (SAA1 and SAA2, respectively), pulmonary surfactant-associated protein B (SFTPB), apolipoprotein F (APOF), and inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4) were increased by more than 50% in hospitalized patients, independently of sex, HDL-C or triglycerides when comparing with subjects presenting only mild symptoms. Altered HDL proteins were able to classify COVID-19 subjects according to the severity of the disease (error rate 4.9%). Moreover, apolipoprotein M (APOM) in HDL was inversely associated with odds of death due to COVID-19 complications (odds ratio [OR] per 1-SD increase in APOM was 0.27, with 95% confidence interval [CI] of 0.07 to 0.72, P=0.007). CONCLUSION: Our results point to a profound inflammatory remodeling of HDL proteome tracking with severity of COVID-19 infection. They also raise the possibility that HDL particles could play an important role in infectious diseases.

Interactome Networks of FOSL1 and FOSL2 in Human Th17 Cells.

Dysregulated function of Th17 cells has implications in immunodeficiencies and autoimmune disorders. Th17 cell differentiation is orchestrated by a complex network of transcription factors, including several members of the activator protein (AP-1) family. Among the latter, FOSL1 and FOSL2 modulate the effector functions of Th17 cells. However, the molecular mechanisms underlying these effects are unclear, owing to the poorly characterized protein interaction networks of FOSL factors. Here, we establish the first interactomes of FOSL1 and FOSL2 in human Th17 cells, using affinity purification-mass spectrometry analysis. In addition to the known JUN proteins, we identified several novel binding partners of FOSL1 and FOSL2. Gene ontology analysis found a significant fraction of these interactors to be associated with RNA-binding activity, which suggests new mechanistic links. Intriguingly, 29 proteins were found to share interactions with FOSL1 and FOSL2, and these included key regulators of Th17 fate. We further validated the binding partners identified in this study by using parallel reaction monitoring targeted mass spectrometry and other methods. Our study provides key insights into the interaction-based signaling mechanisms of FOSL proteins that potentially govern Th17 cell differentiation and associated pathologies.

Quantitative Proteomics Reveals the Dynamic Protein Landscape during Initiation of Human Th17 Cell Polarization.

Th17 cells contribute to the pathogenesis of inflammatory and autoimmune diseases and cancer. To reveal the Th17 cell-specific proteomic signature regulating Th17 cell differentiation and function in humans, we used a label-free mass spectrometry-based approach. Furthermore, a comprehensive analysis of the proteome and transcriptome of cells during human Th17 differentiation revealed a high degree of overlap between the datasets. However, when compared with corresponding published mouse data, we found very limited overlap between the proteins differentially regulated in response to Th17 differentiation. Validations were made for a panel of selected proteins with known and unknown functions. Finally, using RNA interference, we showed that SATB1 negatively regulates human Th17 cell differentiation. Overall, the current study illustrates a comprehensive picture of the global protein landscape during early human Th17 cell differentiation. Poor overlap with mouse data underlines the importance of human studies for translational research.

Serum Proteomic Profiling to Identify Biomarkers of Premature Carotid Atherosclerosis.

To evaluate the presence of serum protein biomarkers associated with the early phases of formation of carotid atherosclerotic plaques, label-free quantitative proteomics analyses were made for serum samples collected as part of The Cardiovascular Risk in Young Finns Study. Samples from subjects who had an asymptomatic carotid artery plaque detected by ultrasound examination (N = 43, Age = 30-45 years) were compared with plaque free controls (N = 43) (matched for age, sex, body weight and systolic blood pressure). Seven proteins (p < 0.05) that have been previously linked with atherosclerotic phenotypes were differentially abundant. Fibulin 1 proteoform C (FBLN1C), Beta-ala-his-dipeptidase (CNDP1), Cadherin-13 (CDH13), Gelsolin (GSN) and 72 kDa type IV collagenase (MMP2) were less abundant in cases, whereas Apolipoproteins C-III (APOC3) and apolipoprotein E (APOE) were more abundant. Using machine learning analysis, a biomarker panel of FBLN1C, APOE and CDH13 was identified, which classified cases from controls with an area under receiver-operating characteristic curve (AUROC) value of 0.79. Furthermore, using selected reaction monitoring mass spectrometry (SRM-MS) the decreased abundance of FBLN1C was verified. In relation to previous associations of FBLN1C with atherosclerotic lesions, the observation could reflect its involvement in the initiation of the plaque formation, or represent a particular risk phenotype.

Quantitative proteomic characterization and comparison of T helper 17 and induced regulatory T cells.

The transcriptional network and protein regulators that govern T helper 17 (Th17) cell differentiation have been studied extensively using advanced genomic approaches. For a better understanding of these biological processes, we have moved a step forward, from gene- to protein-level characterization of Th17 cells. Mass spectrometry-based label-free quantitative (LFQ) proteomics analysis were made of in vitro differentiated murine Th17 and induced regulatory T (iTreg) cells. More than 4,000 proteins, covering almost all subcellular compartments, were detected. Quantitative comparison of the protein expression profiles resulted in the identification of proteins specifically expressed in the Th17 and iTreg cells. Importantly, our combined analysis of proteome and gene expression data revealed protein expression changes that were not associated with changes at the transcriptional level. Our dataset provides a valuable resource, with new insights into the proteomic characteristics of Th17 and iTreg cells, which may prove useful in developing treatment of autoimmune diseases and developing tumor immunotherapy.

Analysis of the plasma proteome using iTRAQ and TMT-based Isobaric labeling.

Over the past decade, chemical labeling with isobaric tandem mass tags, such as isobaric tags for relative and absolute quantification reagents (iTRAQ) and tandem mass tag (TMT) reagents, has been employed in a wide range of different clinically orientated serum and plasma proteomics studies. In this review the scope of these works is presented with attention to the areas of research, methods employed and performance limitations. These applications have covered a wide range of diseases, disorders and infections, and have implemented a variety of different preparative and mass spectrometric approaches. In contrast to earlier works, which struggled to quantify more than a few hundred proteins, increasingly these studies have provided deeper insight into the plasma proteome extending the numbers of quantified proteins to over a thousand.

Mass Spectrometry-Based Serum Proteomics for Biomarker Discovery and Validation.

Blood protein measurements are used frequently in the clinic in the assessment of patient health. Nevertheless, there remains the need for new biomarkers with better diagnostic specificities. With the advent of improved technology for bioanalysis and the growth of biobanks including collections from specific disease risk cohorts, the plasma proteome has remained a target of proteomics research toward the characterization of disease-related biomarkers. The following protocol presents a workflow for serum/plasma proteomics including details of sample preparation both with and without immunoaffinity depletion of the most abundant plasma proteins and methodology for selected reaction monitoring mass spectrometry validation.

Serum proteomes distinguish children developing type 1 diabetes in a cohort with HLA-conferred susceptibility.

We determined longitudinal serum proteomics profiles from children with HLA-conferred diabetes susceptibility to identify changes that could be detected before seroconversion and positivity for disease-associated autoantibodies. Comparisons were made between children who seroconverted and progressed to type 1 diabetes (progressors) and those who remained autoantibody negative, matched by age, sex, sample periodicity, and risk group. The samples represented the prediabetic period and ranged from the age of 3 months to 12 years. After immunoaffinity depletion of the most abundant serum proteins, isobaric tags for relative and absolute quantification were used for sample labeling. Quantitative proteomic profiles were then measured for 13 case-control pairs by high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). Additionally, a label-free LC-MS/MS approach was used to analyze depleted sera from six case-control pairs. Importantly, differences in abundance of a set of proteins were consistently detected before the appearance of autoantibodies in the progressors. Based on top-scoring pairs analysis, classification of such progressors was observed with a high success rate. Overall, the data provide a reference of temporal changes in the serum proteome in healthy children and children progressing to type 1 diabetes, including new protein candidates, the levels of which change before clinical diagnosis.

Proteome wide reduction in AGE modification in streptozotocin induced diabetic mice by hydralazine mediated transglycation.

The non-enzymatic reaction between glucose and protein can be chemically reversed by transglycation. Here we report the transglycation activity of hydralazine using a newly developed MALDI-TOF-MS based assay. Hydralazine mediated transglycation of HbA1c, plasma proteins and kidney proteins was demonstrated in streptozotocin (STZ) induced diabetic mice, as evidenced by decrease in protein glycation, as well as presence of hydralazine-glucose conjugate in urine of diabetic mice treated with hydralazine. Hydralazine down regulated the expression of Receptor for Advanced Glycation End products (RAGE), NADPH oxidase (NOX), and super oxide dismutase (SOD). These findings will provide a new dimension for developing intervention strategies for the treatment of glycation associated diseases such as diabetes complications, atherosclerosis, and aging.

"Zoom-ln"--A targeted database search for identification of glycation modifications analyzed by untargeted tandem mass spectrometry.

Post-translational modifications (PTMs) are very important to biological function, however their identification and characterization is technically challenging. In this study, we have identified glycation modifications by nano LC-MSE, a data independent acquisition work flow, followed by database search using the Protein Lynx Global Server (PLGSJ). PLGS search with a complete human protein database hardly identified glycation modifications in a glycated human serum albumin (HSA), which was detected to be glycated by western blotting with advanced glycation end products (AGE) antibody and fluorescence spectroscopy. To overcome this difficulty, "Zoom-In" approach, a targeted database search was used to identify glycation modifications in a glycated HSA, which were further manually validated. This approach was useful for identification of glycation modifications from untargeted tandem mass spectrometryworkflow such as MSE, but may require the development of a new algorithm or an upgrade of the existing software.

Comparative and chemical proteomic approaches reveal gatifloxacin deregulates enzymes involved in glucose metabolism.

Gatifloxacin has been associated with increased risks of hypoglycemic and hyperglycemic side effects. In order to understand the molecular mechanism of gatifloxacin induced deregulation of glucose metabolism, a combination of comparative and chemical proteomic approaches were employed using yeast as a model system. Differential protein expression studies using two dimensional electrophoresis and mass spectrometry reveal that gatifloxacin deregulates the expression of key enzymes involved in glucose metabolism. Furthermore, affinity chromatography and LC-MS(E) analysis led to identification of enolase, as one of the key gatifloxacin binding proteins. Fluorescence spectrometric studies confirmed that the gatifloxacin indeed binds to enolase. Role of enolase in regulation of gatifloxacin induced dysglycemic effect is discussed.