Mass Spectrometry-based Proteomic Profiling Research Articles

Gradient-Elution Nanoflow Liquid Chromatography without a Binary Pump: Smoothed Step Gradients Enable Reproducible, Sensitive, and Low-Cost Separations for Single-Cell Proteomics

Mass spectrometry-based proteome profiling of trace analytes including single cells benefits from liquid chromatography separations operated at low flow rates (e.g., <50 nL/min). However, high-pressure binary pumps needed to achieve such flow rates are not commercially available, and instead require splitting of the gradient flow to achieve low-nanoliter-per-minute flow rates. Gradient flow splitting can waste solvent and lead to flow inconsistencies. To address this, we have developed a method for creating gradients by combining plugs of mobile phase of increasing solvent strength together in a column, and then relying on Taylor dispersion to form the desired smooth gradient profile. Additionally, our method dramatically reduces costs, as only a single isocratic high-pressure pump is required. Following development of gradient profiles for both 10- and 20-min active gradients, we measured 200 pg injections of HeLa digest using a timsTOF mass spectrometer. Finally, we investigated differences in protein expression between single cells originating from two different colonies of ATG-knockout HeLa cells. Thousands of proteins were quantified, and a potential mechanism explaining differential immune responses of these two colonies upon exposure to viral DNA treatment was determined.

Unveiling the role of transgelin as a prognostic and therapeutic target in kidney fibrosis via a proteomic approach

Chronic kidney disease (CKD) progression involves tubulointerstitial fibrosis, a process characterized by excessive extracellular matrix accumulation. To identify potential biomarkers for kidney fibrosis, we performed mass spectrometry-based proteomic profiling of human kidney tubular epithelial cells and kidney tissue from a 5/6 nephrectomy rat model. Multidisciplinary analysis across kidney fibrosis models revealed 351 differentially expressed proteins associated with kidney fibrosis, and they were enriched in processes related to the extracellular matrix, kidney aging, and mitochondrial functions. Network analysis of the selected proteins revealed five crucial proteins, of which transgelin emerged as a candidate protein that interacts with known fibrosis-related proteins. Concordantly, the gene expression of transgelin in the kidney tissue from the 5/6 nephrectomy model was elevated. Transgelin expression in kidney tissue gradually increased from intermediate to advanced fibrosis stages in 5/6 Nx rats and mice with unilateral ureteral obstruction. Subsequent validation in kidney tissue and urine samples from patients with CKD confirmed the upregulation of transgelin, particularly under advanced disease stages. Moreover, we investigated whether blocking TAGLN ameliorated kidney fibrosis and reduced reactive oxygen species levels in cellular models. In conclusion, our proteomic approach identified TAGLN as a potential noninvasive biomarker and therapeutic target for CKD-associated kidney fibrosis, suggesting its role in modulating mitochondrial dysfunction and oxidative stress responses.

Quantitative proteomics reveals serum proteome alterations during metastatic disease progression in breast cancer patients

BackgroundTumor recurrence and metastatic progression remains the leading cause for breast cancer related mortalities. However, the proteomes of patient- matched primary breast cancer (BC) and metastatic lesions have not yet been identified, due to the lack of clinically annotated longitudinal samples. In this study, we evaluated the global-proteomic landscape of BC patients with and without distant metastasis as well as compared the proteome of distant metastatic disease with its corresponding primary BC, within the same patient.MethodsWe performed mass spectrometry-based proteome profiling of 73 serum samples from 51 BC patients. Among the 51 patients with BC, 29 remained metastasis-free (henceforth called non-progressors), and 22 developed metastases (henceforth called progressors). For the 22 progressors, we obtained two samples: one collected within a year of diagnosis, and the other collected within a year before the diagnosis of metastatic disease. MS data were analyzed using intensity-based absolute quantification and normalized before differential expression analysis. Significantly differentially expressed proteins (DEPs; absolute fold-change ≥ 1.5, P-value < 0.05 and 30% abundance per clinical group) were subjected to pathway analyses.ResultsWe identified 967 proteins among 73 serum samples from patients with BC. Among these, 39 proteins were altered in serum samples at diagnosis, between progressors and non-progressors. Among these, 4 proteins were further altered when the progressors developed distant metastasis. In addition, within progressors, 20 proteins were altered in serum collected at diagnosis versus at the onset of metastasis. Pathway analysis showed that these proteins encoded pathways that describe metastasis, including epithelial–mesenchymal transition and focal adhesion that are hallmarks of metastatic cascade.ConclusionsOur results highlight the importance of examining matched samples from distant metastasis with primary BC samples collected at diagnosis to unravel subset of proteins that could be involved in BC progression in serum. This study sets the foundation for additional future investigations that could position these proteins as non-invasive markers for clinically monitoring breast cancer progression in patients.

Inter-alpha-trypsin inhibitor heavy chain H3 is a potential biomarker for disease activity in myasthenia gravis

Myasthenia gravis is a chronic antibody-mediated autoimmune disease disrupting neuromuscular synaptic transmission. Informative biomarkers remain an unmet need to stratify patients with active disease requiring intensified monitoring and therapy; their identification is the primary objective of this study. We applied mass spectrometry-based proteomic serum profiling for biomarker discovery. We studied an exploration and a prospective validation cohort consisting of 114 and 140 anti-acetylcholine receptor antibody (AChR-Ab)-positive myasthenia gravis patients, respectively. For downstream analysis, we applied a machine learning approach. Protein expression levels were confirmed by ELISA and compared to other myasthenic cohorts, in addition to myositis and neuropathy patients. Anti-AChR-Ab levels were determined by a radio receptor assay. Immunohistochemistry and immunofluorescence of intercostal muscle biopsies were employed for validation in addition to interactome studies of inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3). Machine learning identified ITIH3 as potential serum biomarker reflective of disease activity. Serum levels correlated with disease activity scores in the exploration and validation cohort and were confirmed by ELISA. Lack of correlation between anti-AChR-Ab levels and clinical scores underlined the need for biomarkers. In a subgroup analysis, ITIH3 was indicative of treatment responses. Immunostaining of muscle specimens from these patients demonstrated ITIH3 localization at the neuromuscular endplates in myasthenia gravis but not in controls, thus providing a structural equivalent for our serological findings. Immunoprecipitation of ITIH3 and subsequent proteomics lead to identification of its interaction partners playing crucial roles in neuromuscular transmission. This study provides data on ITIH3 as a potential pathophysiological-relevant biomarker of disease activity in myasthenia gravis. Future studies are required to facilitate translation into clinical practice.

The tumour-derived extracellular vesicle proteome varies by endometrial cancer histology and is confounded by an obesogenic environment.

Endometrial cancer, the most common gynaecological cancer worldwide, is closely linked to obesity and metabolic diseases, particularly in younger women. New circulating biomarkers have the potential to improve diagnosis and treatment selections, which could significantly improve outcomes. Our approach focuses on extracellular vesicle (EV) biomarker discovery by directly profiling the proteome of EVs enriched from frozen biobanked endometrial tumours. We analysed nine tissue samples to compare three clinical subgroups-low BMI (Body Mass Index) Endometrioid, high BMI Endometrioid, and Serous (any BMI)-identifying proteins related to histological subtype, BMI, and shared secreted proteins. Using collagenase digestion and size exclusion chromatography, we successfully enriched generous quantities of EVs (range 204.8-1291.0µg protein: 1.38×1011-1.10×1012 particles), characterised by their size (∼150nm), expression of EV markers (CD63/81), and proposed endometrial cancer markers (L1CAM, ANXA2). Mass spectrometry-based proteomic profiling identified 2075 proteins present in at least one of the 18 samples. Compared to cell lysates, EVs were successfully depleted for mitochondrial and blood proteins and enriched for common EV markers and large secreted proteins. Further analysis highlighted significant differences in EV protein profiles between the high BMI subgroup and others, underlining the impact of comorbidities on the EV secretome. Interestingly, proteins differentially abundant in tissue subgroups were largely not also differential in matched EVs. This research identified secreted proteins known to be involved in endometrial cancer pathophysiology and proposed novel diagnostic biomarkers (EIF6, MUC16, PROM1, SLC26A2).

Insights into the differential proteome landscape of a newly isolated Paramecium multimicronucleatum in response to cadmium stress

Employing microbial systems for the bioremediation of contaminated waters represent a potential option, however, limited understanding of the underlying mechanisms hampers the implication of microbial-mediated bioremediation. The omics tools offer a promising approach to explore the molecular basis of the bioremediation process. Here, a mass spectrometry-based quantitative proteome profiling approach was conducted to explore the differential protein levels in cadmium-treated Paramecium multimicronucleatum. The Proteome Discoverer software was used to identify and quantify differentially abundant proteins. The proteome profiling generated 7,416 peptide spectral matches, yielding 2824 total peptides, corresponding to 989 proteins. The analysis revealed that 29 proteins exhibited significant (p ≤ 0.05) differential levels, including a higher abundance of 6 proteins and reduced levels of 23 proteins in Cd2+ treated samples. These differentially abundant proteins were associated with stress response, energy metabolism, protein degradation, cell growth, and hormone processing. Briefly, a comprehensive proteome profile in response to cadmium stress of a newly isolated Paramecium has been established that will be useful in future studies identifying critical proteins involved in the bioremediation of metals in ciliates. SignificanceCiliates are considered a good biological indicator of chemical pollution and relatively sensitive to heavy metal contamination. A prominent ciliate, Paramecium is a promising candidate for the bioremediation of polluted water. The proteins related to metal resistance in Paramecium species are still largely unknown and need further exploration. In order to identify and reveal the proteins related to metal resistance in Paramecia, we have reported differential protein abundance in Paramecium multimicronucleatum in response to cadmium stress. The proteins found in our study play essential roles during stress response, hormone processing, protein degradation, energy metabolism, and cell growth. It seems likely that Paramecia are not a simple sponge for metals but they could also transform them into less toxic derivatives or by detoxification by protein binding. This data will be helpful in future studies to identify critical proteins along with their detailed mechanisms involved in the bioremediation and detoxification of metal ions in Paramecium species.

Abstract 2285: Mass spectrometry-based proteomics profiling reveals differential proteome composition in tumor and normal tissues, with implications for normalization

Abstract The composition of the proteome varies significantly across different tissues and disease states creating a challenge of how best to compare expression levels of each protein across these tissue types. Traditionally, a median approach to normalization has been used, but this could obscure meaningful biological differences between tissues. Here, we present a quantitative proteomic study analyzing proteome composition across tumor and normal tissues in order to assess normalization methods. Human proteomes covering 7 cancer indications (244 samples) and 12 normal tissue organs (370 samples) were analyzed by data-independent acquisition mass spectrometry. On average, over 8,000 proteins were quantified across the study cohorts. Comparison of proteomes revealed an average of 11.4% higher protein identification in tumors compared to matched normal tissues (6 tumor types all p&amp;lt;0.003). Tissue origin strongly influenced proteome composition, most notably in bone marrow, while cancer tissues displayed less proteomic composition variation than normal tissues. Compared to global median normalization, riBAQ and tissue-specific quantile normalization reduced technical variances while maintaining biological differences between tissue types. By revealing tissue-specific proteome signatures as well as systemic proteomic alterations in tumors, this study lays the groundwork for appropriate comparative approaches accounting for tissue origins, and establishes a framework for discovery of tissue-specific biomarkers, which may facilitate the development of novel diagnostic and prognostic tests, and guide therapeutic interventions for cancer. Citation Format: Ying Zheng, Lindsay Olita, McIver Nivens, Abby Chiang, Shreya Ahuja, Matthew Glover, John Bullen, Elaine Hurt, Wenyan Zhong. Mass spectrometry-based proteomics profiling reveals differential proteome composition in tumor and normal tissues, with implications for normalization [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2285.

Mass Spectrometry-Based Proteomic Profiling of Extracellular Vesicle Proteins in Diabetic and Nondiabetic Ischemic Stroke Patients: A Case-Control Study

Mass Spectrometry-Based Proteomic Profiling of Extracellular Vesicle Proteins in Diabetic and Nondiabetic Ischemic Stroke Patients: A Case-Control Study

Mass spectrometry-based proteomic profiling of extracellular vesicle proteins in diabetic and non-diabetic ischemic stroke patients: a case-control study.

Acute ischemic stroke is the most common cause of neurologic dysfunction caused by focal brain ischemia and tissue injury. Diabetes is a major risk factor of stroke, exacerbating disease management and prognosis. Therefore, discovering new diagnostic markers and therapeutic targets is critical for stroke prevention and treatment. Extracellular vesicles (EVs), with their distinctive properties, have emerged as promising candidates for biomarker discovery and therapeutic application. This case-control study utilized mass spectrometry-based proteomics to compare EVs from non-diabetic stroke (nDS = 14), diabetic stroke (DS = 13), and healthy control (HC = 12) subjects. Among 1288 identified proteins, 387 were statistically compared. Statistical comparisons using a general linear model (log2 foldchange ≥0.58 and FDR-p≤0.05) were performed for nDS vs HC, DS vs HC, and DS vs nDS. DS vs HC and DS vs nDS comparisons produced 123 and 149 differentially expressed proteins, respectively. Fibrinogen gamma chain (FIBG), Fibrinogen beta chain (FIBB), Tetratricopeptide repeat protein 16 (TTC16), Proline rich 14-like (PR14L), Inhibitor of nuclear factor kappa-B kinase subunit epsilon (IKKE), Biorientation of chromosomes in cell division protein 1-like 1 (BD1L1), and protein PR14L exhibited significant differences in the DS group. The pathway analysis revealed that the complement system pathways were activated, and blood coagulation and neuroprotection were inhibited in the DS group (z-score ≥2; p ≤ 0.05). These findings underscore the potential of EVs proteomics in identifying biomarkers for stroke management and prevention, warranting further clinical investigation.

C1QA and COMP: plasma-based biomarkers for early diagnosis of pancreatic neuroendocrine tumors

Pancreatic Neuroendocrine tumors (PanNET) are challenging to diagnose and often detected at advanced stages due to a lack of specific and sensitive biomarkers. This study utilized proteomics as a valuable approach for cancer biomarker discovery; therefore, mass spectrometry-based proteomic profiling was conducted on plasma samples from 12 subjects (3 controls; 5 Grade I, 4 Grade II PanNET patients) to identify potential proteins capable of effectively distinguishing PanNET from healthy controls. Data are available via ProteomeXchange with the identifier PXD045045. 13.2% of proteins were uniquely identified in PanNET, while 60% were commonly expressed in PanNET and controls. 17 proteins exhibiting significant differential expression between PanNET and controls were identified with downstream analysis. Further, 5 proteins (C1QA, COMP, HSP90B1, ITGA2B, and FN1) were selected by pathway analysis and were validated using Western blot analysis. Significant downregulation of C1QA (p = 0.001: within groups, 0.03: control vs. grade I, 0.0013: grade I vs. grade II) and COMP (p = 0.011: within groups, 0.019: control vs grade I) were observed in PanNET Grade I & II than in controls. Subsequently, ELISA on 38 samples revealed significant downregulation of C1QA and COMP with increasing disease severity. This study shows the potential of C1QA and COMP in the early detection of PanNET, highlighting their role in the search for early-stage (Grade-I and Grade-II) diagnostic markers and therapeutic targets for PanNET.

The Golgi stacking protein GRASP55 is targeted by the natural compound prodigiosin

BackgroundThe bacterial secondary metabolite prodigiosin has been shown to exert anticancer, antimalarial, antibacterial and immunomodulatory properties. With regard to cancer, it has been reported to affect cancer cells but not non-malignant cells, rendering prodigiosin a promising lead compound for anticancer drug discovery. However, a direct protein target has not yet been experimentally identified.MethodsWe used mass spectrometry-based thermal proteome profiling in order to identify target proteins of prodigiosin. For target validation, we employed a genetic knockout approach and electron microscopy.ResultsWe identified the Golgi stacking protein GRASP55 as target protein of prodigiosin. We show that prodigiosin treatment severely affects Golgi morphology and functionality, and that prodigiosin-dependent cytotoxicity is partially reduced in GRASP55 knockout cells. We also found that prodigiosin treatment results in decreased cathepsin activity and overall blocks autophagic flux, whereas co-localization of the autophagosomal marker LC3 and the lysosomal marker LAMP1 is clearly promoted. Finally, we observed that autophagosomes accumulate at GRASP55-positive structures, pointing towards an involvement of an altered Golgi function in the autophagy-inhibitory effect of this natural compound.ConclusionTaken together, we propose that prodigiosin affects autophagy and Golgi apparatus integrity in an interlinked mode of action involving the regulation of organelle alkalization and the Golgi stacking protein GRASP55.8brCwiZ4E3PVMoFvaLMguTVideo

Integrative multi-omics reveals two biologically distinct groups of pilocytic astrocytoma.

Pilocytic astrocytoma (PA), the most common pediatric brain tumor, is driven by aberrant mitogen-activated protein kinase signaling most commonly caused by BRAF gene fusions or activating mutations. While 5-year overall survival rates exceed 95%, tumor recurrence or progression constitutes a major clinical challenge in incompletely resected tumors. Here, we used similarity network fusion (SNF) analysis in an integrative multi-omics approach employing RNA transcriptomic and mass spectrometry-based proteomic profiling to molecularly characterize PA tissue samples from 62 patients. Thereby, we uncovered that PAs segregated into two molecularly distinct groups, namely, Group 1 and Group 2, which were validated in threenon-overlapping cohorts. Patients with Group 1 tumors were significantly younger and showed worse progression-free survival compared to patients with group 2 tumors. Ingenuity pathways analysis (IPA) and gene set enrichment analysis (GSEA) revealed that Group 1 tumors were enriched for immune response pathways, such as interferon signaling, while Group 2 tumors showed enrichment for action potential and neurotransmitter signaling pathways. Analysis of immune cell-related gene signatures showed an enrichment of infiltrating T Cells in Group 1 versus Group 2 tumors. Taken together, integrative multi-omics of PA identified biologically distinct and prognostically relevant tumor groups that may improve risk stratification of this single pathway driven tumor type.

Blood-based Proteomic Signatures Associated With MEN1-related Duodenopancreatic Neuroendocrine Tumor Progression.

Patients with multiple endocrine neoplasia type 1 (MEN1) are predisposed to develop duodenopancreatic neuroendocrine tumors (dpNETs), and metastatic dpNET is the primary cause of disease-related mortality. Presently, there is a paucity of prognostic factors that can reliably identify patients with MEN1-related dpNETS who are at high risk of distant metastasis. In the current study, we aimed to establish novel circulating molecular protein signatures associated with disease progression. Mass spectrometry-based proteomic profiling was conducted on plasmas procured through an international collaboration between MD Anderson Cancer Center, the National Institutes of Health, and the University Medical Center Utrecht from a cohort of 56 patients with MEN1 [14 with distant metastasis dpNETs (cases) and 42 with either indolent dpNETs or no dpNETs (controls)]. Findings were compared to proteomic profiles generated from serially collected plasmas from a mouse model of Men1-pancreatic neuroendocrine tumors (Men1fl/flPdx1-CreTg) and control mice (Men1fl/fl). A total of 187 proteins were found to be elevated in MEN1 patients with distant metastasis compared to controls, including 9 proteins previously associated with pancreatic cancer and other neuronal proteins. Analyses of mouse plasmas revealed 196 proteins enriched for transcriptional targets of oncogenic MYCN, YAP1, POU5F1, and SMAD that were associated with disease progression in Men1fl/flPdx1-CreTg mice. Cross-species intersection revealed 19 proteins positively associated with disease progression in both human patients and in Men1fl/flPdx1-CreTg mice. Our integrated analyses identified novel circulating protein markers associated with disease progression in MEN1-related dpNET.

Mass spectrometry-based proteomic profiling of sonicate fluid differentiates Staphylococcus aureus periprosthetic joint infection from non-infectious failure: A pilot study.

This pilot study aimed to use proteomic profiling of sonicate fluid samples to compare host response during Staphylococcus aureus-associated periprosthetic joint infection (PJI) and non-infected arthroplasty failure (NIAF) and identify potential novel biomarkers differentiating the two. In this pilot study, eight sonicate fluid samples (four from NIAF and four from S. aureus PJI) were studied. Samples were reduced, alkylated, and trypsinized overnight, followed by analysis using liquid chromatography-tandem mass spectrometry (LC-MS/MS) on a high-resolution Orbitrap Eclipse mass spectrometer. MaxQuant software suite was used for protein identification, filtering, and label-free quantitation. Principal component analysis of the identified proteins clearly separated S. aureus PJI and NIAF samples. Overall, 810 proteins were identified based on their detection in at least three out of four samples from each group; 35 statistically significant differentially abundant proteins (DAPs) were found (two-sample t-test p-values ≤0.05 and log2 fold-change values ≥2 or ≤-2). Gene ontology pathway analysis found that microbial defense responses, specifically those related to neutrophil activation, to be increased in S. aureus PJI compared to NIAF samples. Proteomic profiling of sonicate fluid using LC-MS/MS differentiated S. aureus PJI and NIAF in this pilot study. Further work is needed using a larger sample size and including non-S. aureus PJI and a diversty of NIAF-types.

Proteomic Profiling of Fallopian Tube-Derived Extracellular Vesicles Using a Microfluidic Tissue-on-Chip System.

The human fallopian tube epithelium (hFTE) is the site of fertilization, early embryo development, and the origin of most high-grade serous ovarian cancers (HGSOCs). Little is known about the content and functions of hFTE-derived small extracellular vesicles (sEVs) due to the limitations of biomaterials and proper culture methods. We have established a microfluidic platform to culture hFTE for EV collection with adequate yield for mass spectrometry-based proteomic profiling, and reported 295 common hFTE sEV proteins for the first time. These proteins are associated with exocytosis, neutrophil degranulation, and wound healing, and some are crucial for fertilization processes. In addition, by correlating sEV protein profiles with hFTE tissue transcripts characterized using GeoMx® Cancer Transcriptome Atlas, spatial transcriptomics analysis revealed cell-type-specific transcripts of hFTE that encode sEVs proteins, among which, FLNA, TUBB, JUP, and FLNC were differentially expressed in secretory cells, the precursor cells for HGSOC. Our study provides insights into the establishment of the baseline proteomic profile of sEVs derived from hFTE tissue, and its correlation with hFTE lineage-specific transcripts, which can be used to evaluate whether the fallopian tube shifts its sEV cargo during ovarian cancer carcinogenesis and the role of sEV proteins in fallopian tube reproductive functions.

Magnetic enrichment of immuno-specific extracellular vesicles for mass spectrometry using biofilm-derived iron oxide nanowires.

Immuno-specific enrichment of extracellular vesicles (EVs) can provide important information into cellular pathways underpinning various pathologies and for non-invasive diagnostics, including mass spectrometry-based analyses. Herein, we report an optimised protocol for immuno-magnetic enrichment of specific EV subtypes and their subsequent processing with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Specifically, we conjugated placental alkaline phosphatase (PLAP) antibodies to magnetic iron oxide nanowires (NWs) derived from bacterial biofilms and demonstrated the utility of this approach by enriching placenta-specific EVs (containing PLAP) from cell culture media. We demonstrate efficient PLAP+ve EV enrichment for both NW-PLAP and Dynabeads™-PLAP, with high PLAP protein recovery (83.7 ± 8.9% and 83.2 ± 5.9%, respectively), high particle-to-protein ratio (7.5 ± 0.7 × 109 and 7.1 ± 1.2 × 109, respectively), and low non-specific binding of non-target EVs (7 ± 3.2% and 5.4 ± 2.2%, respectively). Furthermore, our optimized EV enrichment and processing approach identified 2518 and 2545 protein groups with LC-MS/MS for NW-PLAP and Dynabead™-PLAP, respectively, with excellent reproducibility (Pearson correlation 0.986 and 0.988). These findings demonstrate that naturally occurring iron oxide NWs have comparable performance to current gold standard immune-magnetic beads. The optimized immuno-specific EV enrichment for LC-MS/MS method provides a low-cost and highly-scalable yet efficient, high-throughput approach for quality EV proteomic studies.

Protocol for Plasma Extracellular Vesicle and Particle Isolation and Mass Spectrometry-Based Proteomic Identification.

Plasma extracellular vesicles and particles (EVPs) are enriched in biomolecules that reflect individuals' physiological and pathological states. Several studies have demonstrated the potential of human plasma EVPs as a novel liquid biopsy. Here we describe a protocol for human plasma EVPs isolation and proteomic characterization. We isolated human plasma EVPs by the classical ultracentrifugation method and performed mass spectrometry-based proteomic profiling. Using this protocol, researchers can reveal the plasma EVPs proteome and explore the clinical application of plasma EVPs proteins for developing disease biomarkers.

Mass Spectrometry-Based Proteomic and Metabolomic Profiling of Serum Samples for Discovery and Validation of Tuberculosis Diagnostic Biomarker Signature.

Tuberculosis (TB) is a transmissible disease listed as one of the 10 leading causes of death worldwide (10 million infected in 2019). A swift and precise diagnosis is essential to forestall its transmission, for which the discovery of effective diagnostic biomarkers is crucial. In this study, we aimed to discover molecular biomarkers for the early diagnosis of tuberculosis. Two independent cohorts comprising 29 and 34 subjects were assayed by proteomics, and 49 were included for metabolomic analysis. All subjects were arranged into three experimental groups-healthy controls (controls), latent TB infection (LTBI), and TB patients. LC-MS/MS blood serum protein and metabolite levels were submitted to univariate, multivariate, and ROC analysis. From the 149 proteins quantified in the discovery set, 25 were found to be differentially abundant between controls and TB patients. The AUC, specificity, and sensitivity, determined by ROC statistical analysis of the model composed of four of these proteins considering both proteomic sets, were 0.96, 93%, and 91%, respectively. The five metabolites (9-methyluric acid, indole-3-lactic acid, trans-3-indoleacrylic acid, hexanoylglycine, and N-acetyl-L-leucine) that better discriminate the control and TB patient groups (VIP &gt; 1.75) from a total of 92 metabolites quantified in both ionization modes were submitted to ROC analysis. An AUC = 1 was determined, with all samples being correctly assigned to the respective experimental group. An integrated ROC analysis enrolling one protein and four metabolites was also performed for the common control and TB patients in the proteomic and metabolomic groups. This combined signature correctly assigned the 12 controls and 12 patients used only for prediction (AUC = 1, specificity = 100%, and sensitivity = 100%). This multiomics approach revealed a biomarker signature for tuberculosis diagnosis that could be potentially used for developing a point-of-care diagnosis clinical test.

Proteomic Insight into the Role of Exosomes in Proliferative Vitreoretinopathy Development.

Purpose: To characterize vitreous humor (VH) exosomes and to explore their role in the development of proliferative vitreoretinopathy (PVR) using mass spectrometry-based proteome profiling. Methods: Exosomes were isolated from undiluted VH from patients with retinal detachment (RD) with various stages of PVR (n = 9), macular hole (MH; n = 5), or epiretinal membrane (ERM; n = 5) using differential ultracentrifugation. The exosomal size, morphology, and exosome markers were analyzed using a nanoparticle tracking analysis (NTA), transmission electron microscopy (TEM), and an exosome detection antibody array. The tryptic fragment sequencing of exosome-contained proteins was performed using liquid chromatography–tandem mass spectrometry (LC-MS/MS) and a Thermo Lumos Fusion Tribrid Orbitrap mass spectrometer. The pathway analysis of the MS data was performed. Results: The number of exosome particles were significantly increased only in the RD with severe PVR group compared with the control groups and the RD without PVR or with mild PVR groups. Of 724 exosome proteins identified, 382 were differentially expressed (DE) and 176 were uniquely present in PVR. Both DE proteins and exosome proteins that were only present in PVR were enriched in proteins associated with previously known key pathways related to PVR development, including reactive retinal gliosis, pathologic cellular proliferation, inflammation, growth of connective tissues, and epithelial mesenchymal transition (EMT). The SPP1, CLU, VCAN, COL2A1, and SEMA7A that are significantly upregulated in PVR were related to the tissue remodeling. Conclusions: Exosomes may play a key role in mediating tissue remodeling along with a complex set of pathways involved in PVR development.

Mass Spectrometry-Based Proteome Profiling of Extracellular Vesicles Derived from the Cerebrospinal Fluid of Adult Rhesus Monkeys Exposed to Cocaine throughout Gestation.

Cocaine use disorder has been reported to cause transgenerational effects. However, due to the lack of standardized biomarkers, the effects of cocaine use during pregnancy on postnatal development and long-term neurobiological and behavioral outcomes have not been investigated thoroughly. Therefore, in this study, we examined extracellular vesicles (EVs) in adult (~12 years old) female and male rhesus monkeys prenatally exposed to cocaine (n = 11) and controls (n = 9). EVs were isolated from the cerebrospinal fluid (CSF) and characterized for the surface expression of specific tetraspanins, concentration (particles/mL), size distribution, and cargo proteins by mass spectrometry (MS). Transmission electron microscopy following immunogold labeling for tetraspanins (CD63, CD9, and CD81) confirmed the successful isolation of EVs. Nanoparticle tracking analyses showed that the majority of the particles were <200 nm in size, suggesting an enrichment for small EVs (sEV). Interestingly, the prenatally cocaine-exposed group showed ~54% less EV concentration in CSF compared to the control group. For each group, MS analyses identified a number of proteins loaded in CSF-EVs, many of which are commonly listed in the ExoCarta database. Ingenuity pathway analysis (IPA) demonstrated the association of cargo EV proteins with canonical pathways, diseases and disorders, upstream regulators, and top enriched network. Lastly, significantly altered proteins between groups were similarly characterized by IPA, suggesting that prenatal cocaine exposure could be potentially associated with long-term neuroinflammation and risk for neurodegenerative diseases. Overall, these results indicate that CSF-EVs could potentially serve as biomarkers to assess the transgenerational adverse effects due to prenatal cocaine exposure.