Towards comprehensive and quantitative proteomics for diagnosis and therapy of human disease

Proteomics revealed composition- and size-related regulators for hepatic impairments induced by silica nanoparticles

Along with the growing production and application of silica nanoparticles (SiNPs), increased human exposure and ensuing safety evaluation have progressively attracted concern. Accumulative data evidenced the hepatic injuries upon SiNPs inhalation. Still, the understanding of the hepatic outcomes resulting from SiNPs exposure, and underlying mechanisms are incompletely elucidated. Here, SiNPs of two sizes (60 nm and 300 nm) were applied to investigate their composition- and size-related impacts on livers of ApoE-/- mice via intratracheal instillation. Histopathological and biochemical analysis indicated SiNPs promoted inflammation, lipid deposition and fibrosis in the hepatic tissue, accompanied by increased ALT, AST, TC and TG. Oxidative stress was activated upon SiNPs stimuli, as evidenced by the increased hepatic ROS, MDA and declined GSH/GSSG. Of note, these alterations were more dramatic in SiNPs with a smaller size (SiNPs-60) but the same dosage. LC-MS/MS-based quantitative proteomics unveiled changes in mice liver protein profiles, and filtered out particle composition- or size-related molecules. Interestingly, altered lipid metabolism and oxidative damage served as two critical biological processes. In accordance with correlation analysis and liver disease-targeting prediction, a final of 10 differentially expressed proteins (DEPs) were selected as key potential targets attributable to composition- (4 molecules) and size-related (6 molecules) liver impairments upon SiNPs stimuli. Overall, our study provided strong laboratory evidence for a comprehensive understanding of the harmful biological effects of SiNPs, which was crucial for toxicological evaluation to ensure nanosafety.

An Atlas of Dietary Intakes and Medication Uses on Risk of Bladder Cancer: A Wide-Angle Mendelian Randomization Analysis

BACKGROUND

Observational studies suggests that diets and medications affect bladder cancer (BC) development, which are subject to confounding and difficult to make causal inference. Here we aimed to investigate whether those observational associations are causal and determining the potential directions and pathways.

METHODS

We used 2-sample Mendelian randomization (MR) analysis to assess associations of dietary intakes, medication uses and molecules with BC risk. Genetic summary data were derived from participants of predominantly European ancestry with rigorous instruments selection, where univariable MR, mediation MR and multivariable MR were performed.

RESULTS

The results of univariable MR showed 4 dietary intakes and 4 medication uses having a protective effect on BC, while 4 circulating metabolites, 440 circulating proteins and 2 gut microbes were observed to be causally associated with BC risk. Through mediation MR, we found 572 analytes showing consistent mediating effects between dietary intakes or medication uses and BC risk. Furthermore, 9 out of 16 diet-medication pairs showed significant interactions and alterations on BC when consumed jointly.

CONCLUSION

In summary, the findings obtained from the current study have important implications for informing prevention strategies that point to potential lifestyle interventions or medication prescriptions to reduce the risk of developing BC. HighlightsThe current study extends observational literature in showing the importance of diets and medications on bladder cancer prevention.The associations of diets and medications on bladder cancer prevention might be through circulating metabolites, circulating proteins and gut microbiotaOur results provide a new understanding of interactions in certain diet-medication pairs which should be taken into account by both physicians and patients during the development of a treatment strategy.

Proteomic analysis of plasma proteins from patients with cardiac rupture after acute myocardial infarction using TMT-based quantitative proteomics approach

BACKGROUND

Cardiac rupture (CR) is a rare but catastrophic mechanical complication of acute myocardial infarction (AMI) that seriously threatens human health. However, the reliable biomarkers for clinical diagnosis and the underlying signaling pathways insights of CR has yet to be elucidated.

METHODS

In the present study, a quantitative approach with tandem mass tag (TMT) labeling and liquid chromatography-tandem mass spectrometry was used to characterize the differential protein expression profiles of patients with CR. Plasma samples were collected from patients with CR (n = 37), patients with AMI (n = 47), and healthy controls (n = 47). Candidate proteins were selected for validation by multiple reaction monitoring (MRM) and enzyme-linked immunosorbent assay (ELISA).

RESULTS

In total, 1208 proteins were quantified and 958 differentially expressed proteins (DEPs) were identified. The difference in the expression levels of the DEPs was more noticeable between the CR and Con groups than between the AMI and Con groups. Bioinformatics analysis showed most of the DEPs to be involved in numerous crucial biological processes and signaling pathways, such as RNA transport, ribosome, proteasome, and protein processing in the endoplasmic reticulum, as well as necroptosis and leukocyte transendothelial migration, which might play essential roles in the complex pathological processes associated with CR. MRM analysis confirmed the accuracy of the proteomic analysis results. Four proteins i.e., C-reactive protein (CRP), heat shock protein beta-1 (HSPB1), vinculin (VINC) and growth/differentiation factor 15 (GDF15), were further validated via ELISA. By receiver operating characteristic (ROC) analysis, combinations of these four proteins distinguished CR patients from AMI patients with a high area under the curve (AUC) value (0.895, 95% CI, 0.802-0.988, p < 0.001).

CONCLUSIONS

Our study highlights the value of comprehensive proteomic characterization for identifying plasma proteome changes in patients with CR. This pilot study could serve as a valid foundation and initiation point for elucidation of the mechanisms of CR, which might aid in identifying effective diagnostic biomarkers in the future.

Multiomics Reveals Induction of Neuroblastoma SK-N-BE(2)C Cell Death by Mitochondrial Division Inhibitor 1 through Multiple Effects

Mitochondrial division inhibitor 1 (Mdivi-1) is a well-known synthetic compound aimed at inhibiting dynamin-related protein 1 (Drp1) to suppress mitochondrial fission, making it a valuable tool for studying mitochondrial dynamics. However, its specific effects beyond Drp1 inhibition remain to be confirmed. In this study, we employed integrative proteomics and phosphoproteomics to delve into the molecular responses induced by Mdivi-1 in SK-N-BE(2)C cells. A total of 3070 proteins and 1945 phosphorylation sites were identified, with 880 of them represented as phosphoproteins. Among these, 266 proteins and 97 phosphorylation sites were found to be sensitive to the Mdivi-1 treatment. Functional enrichment analysis unveiled their involvement in serine biosynthesis and extrinsic apoptotic signaling pathways. Through targeted metabolomics, we observed that Mdivi-1 enhanced intracellular serine biosynthesis while reducing the production of C24:1-ceramide. Within these regulated phosphoproteins, dynamic dephosphorylation of proteasome subunit alpha type 3 serine 250 (PSMA3-S250) occurred after Mdivi-1 treatment. Further site-directed mutagenesis experiments revealed that the dephosphorylation-deficient mutant PSMA3-S250A exhibited a decreased cell survival. This research confirms that Mdivi-1's inhibition of mitochondrial division leads to various side effects, ultimately influencing cell survival, rather than solely targeting Drp1 inhibition.

Advances in neuroproteomics for neurotrauma: unraveling insights for personalized medicine and future prospects

Neuroproteomics, an emerging field at the intersection of neuroscience and proteomics, has garnered significant attention in the context of neurotrauma research. Neuroproteomics involves the quantitative and qualitative analysis of nervous system components, essential for understanding the dynamic events involved in the vast areas of neuroscience, including, but not limited to, neuropsychiatric disorders, neurodegenerative disorders, mental illness, traumatic brain injury, chronic traumatic encephalopathy, and other neurodegenerative diseases. With advancements in mass spectrometry coupled with bioinformatics and systems biology, neuroproteomics has led to the development of innovative techniques such as microproteomics, single-cell proteomics, and imaging mass spectrometry, which have significantly impacted neuronal biomarker research. By analyzing the complex protein interactions and alterations that occur in the injured brain, neuroproteomics provides valuable insights into the pathophysiological mechanisms underlying neurotrauma. This review explores how such insights can be harnessed to advance personalized medicine (PM) approaches, tailoring treatments based on individual patient profiles. Additionally, we highlight the potential future prospects of neuroproteomics, such as identifying novel biomarkers and developing targeted therapies by employing artificial intelligence (AI) and machine learning (ML). By shedding light on neurotrauma's current state and future directions, this review aims to stimulate further research and collaboration in this promising and transformative field.

Combination of HBA1, TTR, and SERPINF2 in plasma defines phenotype correlated with severe burn outcome

Recent advancements in proteomics allow for the concurrent identification and quantification of multiple proteins. This study aimed to identify proteins associated with severe burn pathology and establish a clinically useful molecular pathology classification. In a retrospective observational study, blood samples were collected from severe burn patients. Proteins were measured using mass spectrometry, and prognosis-related proteins were extracted by comparing survivors and non-survivors. Enrichment and ROC analyses evaluated the extracted proteins, followed by latent class analysis. Measurements were performed on 83 burn patients. In the non-survivor group, ten proteins significantly changing on the day of injury were associated with metabolic processes and toxin responses. ROC analysis identified HBA1, TTR, and SERPINF2 with AUCs > 0.8 as predictors of 28-day mortality. Latent class analysis classified three molecular pathotypes, and plasma mass spectrometry revealed ten proteins associated with severe burn prognosis. Molecular pathotypes based on HBA1, TTR, and SERPINF2 significantly correlated with outcomes.

The application of Aptamer in biomarker discovery

Biomarkers are detectable molecules that can reflect specific physiological states of cells, organs, and organisms and therefore be regarded as indicators for specific diseases. And the discovery of biomarkers plays an essential role in cancer management from the initial diagnosis to the final treatment regime. Practically, reliable clinical biomarkers are still limited, restricted by the suboptimal methods in biomarker discovery. Nucleic acid aptamers nowadays could be used as a powerful tool in the discovery of protein biomarkers. Nucleic acid aptamers are single-strand oligonucleotides that can specifically bind to various targets with high affinity. As artificial ssDNA or RNA, aptamers possess unique advantages compared to conventional antibodies. They can be flexible in design, low immunogenicity, relative chemical/thermos stability, as well as modifying convenience. Several SELEX (Systematic Evolution of Ligands by Exponential Enrichment) based methods have been generated recently to construct aptamers for discovering new biomarkers in different cell locations. Secretome SELEX-based aptamers selection can facilitate the identification of secreted protein biomarkers. The aptamers developed by cell-SELEX can be used to unveil those biomarkers presented on the cell surface. The aptamers from tissue-SELEX could target intracellular biomarkers. And as a multiplexed protein biomarker detection technology, aptamer-based SOMAScan can analyze thousands of proteins in a single run. In this review, we will introduce the principle and workflow of variations of SELEX-based methods, including secretome SELEX, ADAPT, Cell-SELEX and tissue SELEX. Another powerful proteome analyzing tool, SOMAScan, will also be covered. In the second half of this review, how these methods accelerate biomarker discovery in various diseases, including cardiovascular diseases, cancer and neurodegenerative diseases, will be discussed.

Comparative transcriptome and proteome analysis explores the antitumor key regulators of ergosterone in H22 tumor-bearing mice

Ergosterone has been proved to have potential antitumor effect on H22 tumor-bearing mice, but the antitumor mechanism and key regulators are still unclear. The current study was aimed to explore the key regulators responsible for antitumor of ergosterone using whole transcriptome and proteome analysis in H22 tumor-bearing mice model. The model of H22 tumor-bearing mice was constructed according to the histopathological data and biochemical parameters. The isolated tumor tissues of different treatment groups were subjected to transcriptomic and proteomic analysis. Our findings demonstrated that 472 differentially expressed genes and 658 proteins were identified in the tumor tissue of different treatment groups through RNA-Seq and liquid chromatography with tandem mass spectrometry-based proteomic analysis, respectively. The combined omics analysis revealed three critical genes/proteins, including Lars2, Sirpα and Hcls1 that could play a role in antitumor pathways. Furthermore, Lars2, Sirpα and Hcls1 genes/proteins, as key regulators of the antitumor effect of ergosterone, were verified by qRT-PCR and western blotting methods, respectively. In summary, our study provides new insights into analysing the antitumor mechanism of ergosterone from the point of view of gene and protein expression and will encourage further development of the antitumor pharmaceutical industry.

Current Methods for Identifying Plasma Membrane Proteins as Cancer Biomarkers

Plasma membrane proteins are a special class of biomolecules present on the cellular membrane. They provide the transport of ions, small molecules, and water in response to internal and external signals, define a cell's immunological identity, and facilitate intra- and intercellular communication. Since they are vital to almost all cellular functions, their mutants, or aberrant expression is linked to many diseases, including cancer, where they are a part of cancer cell-specific molecular signatures and phenotypes. In addition, their surface-exposed domains make them exciting biomarkers for targeting by imaging agents and drugs. This review looks at the challenges in identifying cancer-related cell membrane proteins and the current methodologies that solve most of the challenges. We classified the methodologies as biased, i.e., search cells for the presence of already known membrane proteins. Second, we discuss the unbiased methods that can identify proteins without prior knowledge of what they are. Finally, we discuss the potential impact of membrane proteins on the early detection and treatment of cancer.

Proteome analysis reveals novel serum biomarkers for Henoch-Schönlein purpura in Chinese children

PURPOSE

Henoch-Schönlein purpura (HSP) is diagnosed based on characteristic skin changes. This study aimed to identify the serum biomarkers of HSP in children.

EXPERIMENTAL DESIGN

We performed proteomic analysis of serum samples from 38 paired pre- and posttherapy HSP patients and 22 healthy controls using a combination of magnetic bead-based weak cation exchange and MALDI-TOF MS. ClinProTools was used to screen the differential peaks. Then, LC-ESI-MS/MS was performed to identify the proteins. ELISA was used to verify the expression of whole protein in the serum of 92 HSP patients, 14 peptic ulcer disease (PUD) patients and 38 healthy controls, which were prospectively collected. Finally, logistic regression analysis was performed to analyze the diagnostic value of the above predictors and existing clinical indicators.

RESULTS

Seven potential HSP serum biomarker peaks (m/z:1228.95, m/z:1781.22, m/z:1468.43, m/z:1619.53, m/z:1868.41, m/z:1694.05, m/z:1743.25) with higher expression in the pretherapy group and one peak (m/z:1947.41) with lower expression in the pretherapy group were all identified as peptide regions of albumin (ALB), complement C4-A precursor (C4A), tubulin beta chain (TUBB), isoform 1 of fibrinogen alpha chain (FGA), and ezrin (EZR). The expression of identified proteins was validated by ELISA. Multivariate logistic regression analysis showed that serum C4A EZR and ALB were independent risk factors for HSP, serum C4A and lgA were independent risk factors for HSPN, and serum D-dimer was an independent risk factor for abdominal HSP.

CONCLUSIONS AND CLINICAL RELEVANCE

These findings revealed the specific etiology of HSP from the perspective of serum proteomics. The identified proteins might serve as potential biomarkers for HSP and HSPN diagnoses.

SIGNIFICANCE

Henoch-Schönlein purpura (HSP) is the most common systemic vasculitis in children, and its diagnosis depends primarily on characteristic skin changes. Early diagnosis of non-rash patients is difficult, especially for abdominal and renal types (Henoch-Schönlein purpura nephritis, HSPN). HSPN has poor outcomes, is diagnosed based on urinary protein and/or haematuria, and cannot be detected early in HSP. Patients with an earlier diagnosis of HSPN appear to have better renal outcomes. Our plasma proteomic analysis of HSP in children revealed that HSP patients could be distinguished from healthy controls and peptic ulcer disease patients using complement C4-A precursor (C4A), ezrin, and albumin. C4A and IgA could distinguish HSPN from HSP in the early stages, and D-dimer was a sensitive index used to distinguish abdominal HSP; identifying these biomarkers could promote the early diagnosis of HSP, especially pediatric HSPN and abdominal HSP, thereby improving precision therapy.

Protective effect of Xingnaojing injection on ferroptosis after cerebral ischemia injury in MCAO rats and SH-SY5Y cells

ETHNOPHARMACOLOGICAL RELEVANCE

Xingnaojing（XNJ）injection is a traditional Chinese medicine injection with neuroprotective effect, which has been widely used in the treatment of stroke for many years.

AIM OF THE STUDY

This study aimed to explore the potential mechanism of XNJ in cerebral ischemia mediated by ferroptosis using proteomics and in vivo and in vitro experiments.

MATERIALS AND METHODS

After the rat model of middle cerebral artery occlusion (MCAO) was successfully established, they were randomly divided into model, XNJ, and deferoxamine (DFO) group. Triphenyl tetrazolium chloride (TTC) staining, Hematoxylin and eosin (H&E), and Nissl staining were used to observe the infarct area, pathological changes and the degree of neuronal apoptosis of rat brain. Proteins extracted from rat brain tissues were analyzed by quantitative proteomics using tandem mass tags (TMT). Western blotting and immunohistochemical assessment were used to measure the expression of ferroptosis-related proteins. In vitro, the SH-SY5Y cells were subjected to hypoxia (37°C/5% CO2/1% O2) for 24 h to observe the survival rate, and detect the reactive oxygen species (ROS) content and ferroptosis-related proteins.

RESULTS

In TTC and H&E experiments, we found that XNJ drug treatment reduced the infarct volume and brain tissue damage in MCAO rats. Nissl staining also showed that compared with MCAO group rats, the Nissl bodies of brain tissue after XNJ drug intervention were clear with a 3.54-fold increased times, suggesting that XNJ improved cerebral infraction, and neurological deficits in MCAO rats. Proteomics identified 101 intersected differentially expressed proteins (DEPs). According to the bioinformatics analysis, these DEPs were closely related to ferroptosis. Further research indicated that MCAO-induced cerebral ischemia was alleviated by upregulating recombinant glutathione peroxidase 4 (GPX4), ferroportin (FPN) expression, Heme oxygenase-1 (HO-1) expression, and downregulating cyclooxygenase-2 (COX-2), transferring receptor (TFR) and divalent metal transporter-1 (DMT1) expression after XNJ treatment. In addition, in vitro experiment indicated that XNJ improved the survival rate of hypoxia-damaged SH-SY5Y cells. XNJ increased the level of GPX4 and inhibited the protein expression of COX-2 and TFR after cell hypoxia. Moreover, different concentrations of XNJ (0.25%, 0.5%, 1%) reduced the ROS content of hypoxic cells, suggesting that XNJ could inhibit hypoxia-induced cell damage by regulating the expression of ferroptosis-related proteins and decreasing the production of ROS.

CONCLUSIONS

XNJ could promote the recovery of neurological function in MCAO rats and hypoxia SH-SY5Y cells by regulating ferroptosis.

Proteomics approaches: A review regarding an importance of proteome analyses in understanding the pathogens and diseases

Proteomics is playing an increasingly important role in identifying pathogens, emerging and re-emerging infectious agents, understanding pathogenesis, and diagnosis of diseases. Recently, more advanced and sophisticated proteomics technologies have transformed disease diagnostics and vaccines development. The detection of pathogens is made possible by more accurate and time-constrained technologies, resulting in an early diagnosis. More detailed and comprehensive information regarding the proteome of any noxious agent is made possible by combining mass spectrometry with various gel-based or short-gun proteomics approaches recently. MALDI-ToF has been proved quite useful in identifying and distinguishing bacterial pathogens. Other quantitative approaches are doing their best to investigate bacterial virulent factors, diagnostic markers and vaccine candidates. Proteomics is also helping in the identification of secreted proteins and their virulence-related functions. This review aims to highlight the role of cutting-edge proteomics approaches in better understanding the functional genomics of pathogens. This also underlines the limitations of proteomics in bacterial secretome research.

pGlycoQuant with a deep residual network for quantitative glycoproteomics at intact glycopeptide level

Large-scale intact glycopeptide identification has been advanced by software tools. However, tools for quantitative analysis remain lagging behind, which hinders exploring the differential site-specific glycosylation. Here, we report pGlycoQuant, a generic tool for both primary and tandem mass spectrometry-based intact glycopeptide quantitation. pGlycoQuant advances in glycopeptide matching through applying a deep learning model that reduces missing values by 19-89% compared with Byologic, MSFragger-Glyco, Skyline, and Proteome Discoverer, as well as a Match In Run algorithm for more glycopeptide coverage, greatly expanding the quantitative function of several widely used search engines, including pGlyco 2.0, pGlyco3, Byonic and MSFragger-Glyco. Further application of pGlycoQuant to the N-glycoproteomic study in three different metastatic HCC cell lines quantifies 6435 intact N-glycopeptides and, together with in vitro molecular biology experiments, illustrates site 979-core fucosylation of L1CAM as a potential regulator of HCC metastasis. We expected further applications of the freely available pGlycoQuant in glycoproteomic studies.

Quantitative Proteomics Based on iTRAQ Reveal that Nitidine Chloride Induces Apoptosis by Activating JNK/c-Jun Signaling in Hepatocellular Carcinoma Cells

The aim of the present study was to investigate the cytotoxic effects and underlying molecular mechanisms of nitidine chloride (NC) in hepatocellular carcinoma cells via quantitative proteomics. MTT assays were used to detect the inhibitory effects of NC in Bel-7402 liver cancer cells, and the number of apoptotic cells was measured by flow cytometry. Quantitative proteomics technology based on iTRAQ was used to discover differential expressed proteins after NC treatment, and bioinformatic techniques were further used to screen potential targets of NC. Molecular docking was applied to evaluate the docking activity of NC with possible upstream proteins, and their expression was detected at the mRNA and protein levels by quantitative reverse transcription PCR and western blotting. NC inhibited the proliferation of Bel-7402 cells after 24 h of treatment and stimulated apoptosis in vitro. The proteomics experiment showed that NC triggers mitochondrial damage in HCC cells and transcription factor AP-1 (c-Jun) may be a potential target of NC (fold change = 4.36 ± 0.23). Molecular docking results revealed the highest docking score of NC with c-Jun N-terminal kinase (JNK), one of the upstream proteins of c-Jun. Moreover, the mRNA and protein expression of c-Jun and JNK were significantly increased after NC treatment (p < 0.05). These findings indicate that NC significantly induced mitochondrial damage in HCC cells, and induced apoptosis by activating JNK/c-Jun signaling.

Advances in the application of proteomics in lung cancer

Although the incidence and mortality of lung cancer have decreased significantly in the past decade, it is still one of the leading causes of death, which greatly impairs people’s life and health. Proteomics is an emerging technology that involves the application of techniques for identifying and quantifying the overall proteins in cells, tissues and organisms, and can be combined with genomics, transcriptomics to form a multi-omics research model. By comparing the content of proteins between normal and tumor tissues, proteomics can be applied to different clinical aspects like diagnosis, treatment, and prognosis, especially the exploration of disease biomarkers and therapeutic targets. The applications of proteomics have promoted the research on lung cancer. To figure out potential applications of proteomics associated with lung cancer, we summarized the role of proteomics in studies about tumorigenesis, diagnosis, prognosis, treatment and resistance of lung cancer in this review, which will provide guidance for more rational application of proteomics and potential therapeutic strategies of lung cancer.

Clinlabomics: leveraging clinical laboratory data by data mining strategies

The recent global focus on big data in medicine has been associated with the rise of artificial intelligence (AI) in diagnosis and decision-making following recent advances in computer technology. Up to now, AI has been applied to various aspects of medicine, including disease diagnosis, surveillance, treatment, predicting future risk, targeted interventions and understanding of the disease. There have been plenty of successful examples in medicine of using big data, such as radiology and pathology, ophthalmology cardiology and surgery. Combining medicine and AI has become a powerful tool to change health care, and even to change the nature of disease screening in clinical diagnosis. As all we know, clinical laboratories produce large amounts of testing data every day and the clinical laboratory data combined with AI may establish a new diagnosis and treatment has attracted wide attention. At present, a new concept of radiomics has been created for imaging data combined with AI, but a new definition of clinical laboratory data combined with AI has lacked so that many studies in this field cannot be accurately classified. Therefore, we propose a new concept of clinical laboratory omics (Clinlabomics) by combining clinical laboratory medicine and AI. Clinlabomics can use high-throughput methods to extract large amounts of feature data from blood, body fluids, secretions, excreta, and cast clinical laboratory test data. Then using the data statistics, machine learning, and other methods to read more undiscovered information. In this review, we have summarized the application of clinical laboratory data combined with AI in medical fields. Undeniable, the application of Clinlabomics is a method that can assist many fields of medicine but still requires further validation in a multi-center environment and laboratory.

Exosome Proteomics Reveals the Deregulation of Coagulation, Complement and Lipid Metabolism Proteins in Gestational Diabetes Mellitus

Exosomes are small extracellular vesicles with a variable protein cargo in consonance with cell origin and pathophysiological conditions. Gestational diabetes mellitus (GDM) is characterized by different levels of chronic low-grade inflammation and vascular dysfunction; however, there are few data characterizing the serum exosomal protein cargo of GDM patients and associated signaling pathways. Eighteen pregnant women were enrolled in the study: 8 controls (CG) and 10 patients with GDM. Blood samples were collected from patients, for exosomes’ concentration. Protein abundance alterations were demonstrated by relative mass spectrometric analysis and their association with clinical parameters in GDM patients was performed using Pearson’s correlation analysis. The proteomics analysis revealed 78 significantly altered proteins when comparing GDM to CG, related to complement and coagulation cascades, platelet activation, prothrombotic factors and cholesterol metabolism. Down-regulation of Complement C3 (C3), Complement C5 (C5), C4-B (C4B), C4b-binding protein beta chain (C4BPB) and C4b-binding protein alpha chain (C4BPA), and up-regulation of C7, C9 and F12 were found in GDM. Our data indicated significant correlations between factors involved in the pathogenesis of GDM and clinical parameters that may improve the understanding of GDM pathophysiology. Data are available via ProteomeXchange with identifier PXD035673.

Network Pharmacology of Adaptogens in the Assessment of Their Pleiotropic Therapeutic Activity

The reductionist concept, based on the ligand–receptor interaction, is not a suitable model for adaptogens, and herbal preparations affect multiple physiological functions, revealing polyvalent pharmacological activities, and are traditionally used in many conditions. This review, for the first time, provides a rationale for the pleiotropic therapeutic efficacy of adaptogens based on evidence from recent gene expression studies in target cells and where the network pharmacology and systems biology approaches were applied. The specific molecular targets and adaptive stress response signaling mechanisms involved in nonspecific modes of action of adaptogens are identified.

Semen Ziziphi Spinosae attenuates blood-brain barrier dysfunction induced by lipopolysaccharide by targeting the FAK-DOCK180-Rac1-WAVE2-Arp3 signaling pathway

Semen Ziziphi Spinosae (SZS) has been extensively used in the daily diet as a functional food for neuroprotective health-benefit in China for many years. However, the neuroprotective mechanism of SZS associated with blood–brain barrier (BBB) integrity remains unexplored. The present study suggests SZS could protect against lipopolysaccharide (LPS)-induced BBB dysfunction. Proteomics indicate that 135 proteins in rat brain are significantly altered by SZS. These differentially expressed proteins are mainly clustered into cell–cell adhesion and adherens junctions, which are closely related with BBB integrity. SZS reversed LPS-induces BBB breakdown by activating the FAK-DOCK180-Rac1-WAVE2-Arp3 pathway. Molecular docking between signaling pathway proteins and identified SZS components in rat plasma reveals that 6”‘-feruloylspinosin, spinosin, and swertisin strongly binds to signaling proteins at multiple amino acid sites. These novel findings suggest a health benefit of SZS in prevention of cerebral diseases and contributes to the further application of SZS as a functional food.

Proteomic and Morphological Profiling of Mice Ocular Tissue During High-altitude Acclimatization Process: An Animal Study at Lhasa

Purpose

High-altitude environment mainly with hypobaric hypoxia could induce pathological alterations in ocular tissue. Previous studies have mostly focused on sporadic case reports and simulated high-altitude hypoxia experiments. This aim of this study was to explore the proteomic and morphological changes of ocular tissue in mice at real altitude environment.

Methods

In this study, mice were flown from Chengdu (elevation: 500 m) to Lhasa (elevation: 3600 m). After exposure for 1day, 3, 6, 10, 20, 30, and 40days, the mice were euthanatized to obtain blood and ocular tissue. Serological tests, ocular pathological examinations, integral ocular proteomics analysis, and Western blot were conducted.

Results

We focused on acute phase (1–3 days) and chronic phase (>30 days) during high-altitude acclimatization. Serum interleukin-1 was increased at 3 days, while superoxide dismutase, interleukin-6, and tumor necrosis factor-α showed no statistical changes. H&E staining demonstrated that the cornea was edematous at 3 days and exhibited slower proliferation at 30 days. The choroid showed a consistently significant thickening, while there existed no noticeable changes in retinal thickness. Overall, 4073 proteins were identified, among which 71 and 119 proteins were detected to have significant difference at 3 days and 40 days when compared with the control group. Functional enrichment analysis found the differentiated proteins at 3 days exposure functionally related with response to radiation, dephosphorylation, negative regulation of cell adhesion, and erythrocyte homeostasis. Moreover, the differential profiles of the proteins at 40 days exposure exhibited changes of regulation of complement activation, regulation of protein activation cascade, regulation of humoral immune response, second-messenger-mediated signaling, regulation of leukocyte activation, and cellular iron homeostasis. Interestingly, we found the ocular proteins with lactylation modification were increased along high-altitude adaptation.

Conclusion

This is the first work reporting the ocular proteomic and morphological changes at real high-altitude environment. We expect it would deep the understanding of ocular response during altitude acclimatization.

Forsythiaside A Regulates Activation of Hepatic Stellate Cells by Inhibiting NOX4-Dependent ROS

Hepatic stellate cells (HSCs) activation is an important step in the process of hepatic fibrosis. NOX4 and reactive oxygen species expressed in HSCs play an important role in liver fibrosis. Forsythiaside A (FA), a phenylethanoid glycoside extracted and isolated from Forsythiae Fructus, has significant antioxidant activities. However, it is not clear whether FA can play a role in inhibiting the HSCs activation through regulating NOX4/ROS pathway. Therefore, our purpose is to explore the effect and mechanism of FA on HSCs activation to alleviate liver fibrosis. LX2 cells were activated by TGF-β1 in vitro. MTT assay and Wound Healing assay were used to investigate the effect of FA on TGF-β1-induced LX2 cell proliferation and migration. Elisa kit was used to measure the expression of MMP-1 and TIMP-1. Western blot and RT-qPCR were used to investigate the expression of fibrosis-related COLI, α-SMA, MMP-1 and TIMP-1, and inflammation-related TNF-α, IL-6 and IL-1β. The hydroxyproline content was characterized using a biochemical kit. The mechanism of FA to inhibit HSCs activation and apoptosis was detected by DCF-DA probe, RT-qPCR, western blot and flow cytometry. NOX4 siRNA was used to futher verify the effect of FA on NOX4/ROS pathway. The results showed that FA inhibited the proliferation and migration of LX2 cells and adjusted the expression of MMP-1, TIMP-1, COLI, α-SMA, TNF-α, IL-6 and IL-1β as well as promoted collagen metabolism to show potential in anti-hepatic fibrosis. Mechanically, FA down-regulated NOX4/ROS signaling pathway to improve oxidation imbalances, and subsequently inhibited PI3K/Akt pathway to suppress proliferation. FA also promoted the apoptosis of LX2 cells by Bax/Bcl2 pathway. Furthermore, the effects of FA on TGF-β1-induced increased ROS levels and α-SMA and COLI expression were weaken by silencing NOX4. In conclusion, FA had potential in anti-hepatic fibrosis at least in part by remolding of extracellular matrix and improving oxidation imbalances to inhibit the activation of HSCs and promote HSCs apoptosis.

Protein Lipidation Types: Current Strategies for Enrichment and Characterization

Post-translational modifications regulate diverse activities of a colossal number of proteins. For example, various types of lipids can be covalently linked to proteins enzymatically or non-enzymatically. Protein lipidation is perhaps not as extensively studied as protein phosphorylation, ubiquitination, or glycosylation although it is no less significant than these modifications. Evidence suggests that proteins can be attached by at least seven types of lipids, including fatty acids, lipoic acids, isoprenoids, sterols, phospholipids, glycosylphosphatidylinositol anchors, and lipid-derived electrophiles. In this review, we summarize types of protein lipidation and methods used for their detection, with an emphasis on the conjugation of proteins with polyunsaturated fatty acids (PUFAs). We discuss possible reasons for the scarcity of reports on PUFA-modified proteins, limitations in current methodology, and potential approaches in detecting PUFA modifications.

Clinical identification of expressed proteins in adrenal medullary hyperplasia detected with hypertension

BACKGROUND

Hypertension remains a challenging public health problem worldwide, and adrenal gland-related diseases are one class of the major causes for secondary hypertension. Among them, one relatively rare pattern is adrenal hyperplastic hypertension caused by adrenal medullary hyperplasia (AMH), leading to excessive secretion of autonomic catecholamine. Given that the pathological changes of adrenal medulla are not well correlated to the onset and even severity of secondary hypertension, the molecular basis why some AMH patients are accompanied with hypertension remains unclear and is worth exploring.

AIMS

For this reason, this study aims at investigating differentially expressed proteins in clinical AMH tissue, with special focus on the potential contribution of these differentially expressed proteins to AMH development, in order to have a better understanding of mechanisms how AMH leads to secondary hypertension to some extent.

METHODS AND RESULTS

To this end, AMH specimens were successfully obtained and verified through computed tomography (CT) and haematoxylin-eosin (HE) staining. Proteomic analyses of AMH and control tissues revealed 782 kinds of differentially expressed proteins. Compared with the control tissue, there were 357 types of upregulated proteins and 425 types of downregulated proteins detected in AMH tissue. Of interest, these differentially expressed proteins were significantly enriched in 60 gene ontology terms (P < 0.05), including 28 biological process terms, 14 molecular function terms, and 18 cellular component terms. Pathway analysis further indicated that 306 proteins exert their functions in at least one Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Western blotting showed enhanced expression of phenylethanolamine N- methyltransferase (PNMT), myelin protein zero (MPZ), and Ras-related protein Rab-3C (RAB3C), and reduced expression of cluster of differentiation 36 (CD36) observed in AMH tissue in comparison with controls.

CONCLUSIONS

Clinical AMH specimens display a different proteomic profile compared to control tissue. Of note, PNMT, MPZ, RAB3C, and CD36 are found to differentially expressed and can be potential targets for AMH, providing a theoretical basis for mechanistic exploration of AMH along with hypertension.

Proteomic profiling of carbonic anhydrase CA3 in skeletal muscle

INTRODUCTION

Carbonic anhydrase (CA) is a key enzyme that mediates the reversible hydration of carbon dioxide. Skeletal muscles contain high levels of the cytosolic isoform CA3. This enzyme has antioxidative function and plays a crucial role in the maintenance of intracellular pH homeostasis.

AREAS COVERED

Since elevated levels of serum CA3, often in combination with other muscle-specific proteins, are routinely used as a marker of general muscle damage, it was of interest to examine recent analyses of this enzyme carried out by modern proteomics. This review summarizes the mass spectrometry-based identification and evaluation of CA3 in normal, adapting, dystrophic, and aging skeletal muscle tissues.

EXPERT OPINION

The mass spectrometric characterization of CA3 confirmed this enzyme as a highly useful marker of both physiological and pathophysiological alterations in skeletal muscles. Cytosolic CA3 is clearly enriched in slow-twitching type I fibers, which makes it an ideal marker for studying fiber type shifting and muscle adaptations. Importantly, neuromuscular diseases feature distinct alterations in CA3 in skeletal muscle tissues versus biofluids, such as serum. Characteristic changes of CA3 in age-related muscle wasting and dystrophinopathy established this enzyme as a suitable biomarker candidate for differential diagnosis and monitoring of disease progression and therapeutic impact.

CRISPR/Cas9 genome-wide screening identifies LUC7L2 that promotes radioresistance via autophagy in nasopharyngeal carcinoma cells

Radioresistance emerges as the major obstacle to nasopharyngeal carcinoma (NPC) treatment, further understanding of underlying mechanisms is necessary to overcome the radioresistance and improve the therapeutic effect. In this study, we first identified a candidate radioresistant-related gene LUC7L2 via CRISPR/Cas9 high-throughput screening and quantitative proteomic approach. Overexpression of LUC7L2 in NPC cells promoted cell viability following exposure to ionizing radiation (IR), while knockdown of LUC7L2 significantly slowed down the DNA replication and impaired cell survival, sensitized NPC-radioresistant cells to IR. Using immunoprecipitation assay, we found SQSTM1, an autophagy receptor, was a potential binding partner of LUC7L2. Down-regulation of LUC7L2 in NPC-radioresistant cells led to reduction of SQSTM1 expression and enhancement of autophagy level. Furthermore, LUC7L2 knockdown in combination with autophagy inhibitor, chloroquine (CQ), resulted in more NPC-radioresistant cell death. Besides, LUC7L2 was obviously distributed in NPC tissues, and high LUC7L2 expression correlated with shorter survival in NPC patients. Our data suggest that LUC7L2 plays a huge part in regulating radioresistance of NPC cells, and serves as a promising therapeutic target in re-sensitizing NPC to radiotherapy.

Proteomics Analysis of Serum Proteins in Gestational Diabetes

OBJECTIVE

The purpose of this study was to screen serum proteins for biomarkers of gestational diabetes mellitus (GDM) and to investigate its pathogenesis by analyzing the differences in serum proteomics between pregnant women with GDM and healthy pregnant women.

METHODS

Patients who were admitted to the First Affiliated Hospital of Fujian Medical University from June 2019 to January 2020 were included. According to the medical history and the results of the 75 g oral glucose tolerance test (OGTT), they were divided into the normal pregnant women group and GDM pregnant women group. The serum of two groups of patients was collected. High performance liquid chromatography-mass spectrometry was used to identify differentially expressed serum proteins between pregnant women with GDM and healthy pregnant women, and bioinformatics analysis was then performed on the identified proteins.

RESULTS

A total of 1152 quantifiable proteins were detected; among them, 15 were upregulated in serum of GDM pregnant women, while 26 were downregulated. The subsequent parallel reaction monitoring (PRM) assay validated the expression levels of 12 out of 41 differentially expressed proteins. Moreover, bioinformatics analysis revealed that the differentially expressed proteins are involved in multiple biological processes and signaling pathways related to the lipid metabolism, glycan degradation, immune response, and platelet aggregation.

CONCLUSIONS

This study identified 41 serum proteins with differential expression between pregnant women with GDM and healthy pregnant women, providing new candidate molecules for elucidating GDM pathogenesis and screening therapeutic targets.

An Introduction to Advanced Targeted Acquisition Methods

Targeted proteomics via selected reaction monitoring (SRM) or parallel reaction monitoring (PRM) enables fast and sensitive detection of a preselected set of target peptides. However, the number of peptides that can be monitored in conventional targeting methods is usually rather small. Recently, a series of methods has been described that employ intelligent acquisition strategies to increase the efficiency of mass spectrometers to detect target peptides. These methods are based on one of two strategies. First, retention time adjustment-based methods enable intelligent scheduling of target peptide retention times. These include Picky, iRT, as well as spike-in free real-time adjustment methods such as MaxQuant.Live. Second, in spike-in triggered acquisition methods such as SureQuant, Pseudo-PRM, TOMAHAQ, and Scout-MRM, targeted scans are initiated by abundant labeled synthetic peptides added to samples before the run. Both strategies enable the mass spectrometer to better focus data acquisition time on target peptides. This either enables more sensitive detection or a higher number of targets per run. Here, we provide an overview of available advanced targeting methods and highlight their intrinsic strengths and weaknesses and compatibility with specific experimental setups. Our goal is to provide a basic introduction to advanced targeting methods for people starting to work in this field.

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Advanced acquisition methods improve focus of mass spectrometers on target peptides.

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This review discusses existing methods based on two strategies.

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Retention time adjustment-based methods enable intelligent scheduling of peptide RTs.

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In spike-in triggered acquisition methods targeted scans are initiated by spike-ins.

Evaluating the Performance of 193 nm Ultraviolet Photodissociation for Tandem Mass Tag Labeled Peptides

Despite the successful application of tandem mass tags (TMT) for peptide quantitation, missing reporter ions in higher energy collisional dissociation (HCD) spectra remains a challenge for consistent quantitation, especially for peptides with labile post-translational modifications. Ultraviolet photodissociation (UVPD) is an alternative ion activation method shown to provide superior coverage for sequencing of peptides and intact proteins. Here, we optimized and evaluated 193 nm UVPD for the characterization of TMT-labeled model peptides, HeLa proteome, and N-glycopeptides from model proteins. UVPD yielded the same TMT reporter ions as HCD, at m/z 126–131. Additionally, UVPD produced a wide range of fragments that yielded more complete characterization of glycopeptides and less frequent missing TMT reporter ion channels, whereas HCD yielded a strong tradeoff between characterization and quantitation of TMT-labeled glycopeptides. However, the lower fragmentation efficiency of UVPD yielded fewer peptide identifications than HCD. Overall, 193 nm UVPD is a valuable tool that provides an alternative to HCD for the quantitation of large and highly modified peptides with labile PTMs. Continued development of instrumentation specific to UVPD will yield greater fragmentation efficiency and fulfil the potential of UVPD to be an all-in-one spectrum ion activation method for broad use in the field of proteomics.

TMT-Based proteomics analysis of LPS-induced acute lung injury

PURPOSE

The proteome during lipopolysaccharide (LPS)-induced acute lung injury (ALI) in mice is unclear.

MATERIALS AND METHODS

In this study, eight-week-old male C57BL/6 mice were intraperitoneally injected with LPS and sacrificed 18 hours after LPS administration to identify protein expression levels in lung tissue using tandem mass tag (TMT) analysis for relative quantification. Hematoxylin-eosin (HE) staining was used to evaluate lung injury in mice. Immunohistochemical staining was used to calculate the production of myeloperoxidase (MPO) and TUNEL staining was performed to detect apoptosis. GO functional clustering and KEGG pathway enrichment analyses were performed to determine functions of differentially expressed proteins (DEPs) and transduction pathways. Domain annotation and subcellular localization analysis of the DEPs were also performed. Furthermore, parallel reaction monitoring (PRM) analysis was used to verify the top 30 DEPs.

RESULTS

A total of 5188 proteins were found to be expressed in lung tissues from LPS- and saline-treated mice. Among these proteins, 293 were differentially expressed between the two groups; 255 proteins were upregulated in the LPS-treated ALI mice, while 38 were downregulated. GO analysis showed that the DEPs are mainly extracellular, and KEGG analysis suggested that the DEPs are mainly enriched in the NOD-like receptor signaling pathway, complement and coagulation cascades and natural killer cell-mediated cytotoxicity. Enrichment of the DEPs is mainly peptidase S1A, serine proteases, peptidase S1, and the serpin domain. 26.6% of the DEPs are in the nucleus, 24.6% are in the cytosol, 19.1% are in the extracellular space, and 18.8% are in the plasma membrane. PRM validation showed that the trend of 30 DEPs was same with TMT analysis. Among these, Cytochrome b-245 heavy chain (Cybb), Monocyte differentiation antigen CD14 (Cd14) and Neutrophil gelatinase-associated lipocalin (NGAL) were the most obvious change.

CONCLUSIONS

Our results may help to identify markers and therapeutic targets for LPS-induced ALI.

In-Cell Labeling and Mass Spectrometry for Systems-Level Structural Biology

Biological systems have evolved to utilize proteins to accomplish nearly all functional roles needed to sustain life. A majority of biological functions occur within the crowded environment inside cells and subcellular compartments where proteins exist in a densely packed complex network of protein-protein interactions. The structural biology field has experienced a renaissance with recent advances in crystallography, NMR, and CryoEM that now produce stunning models of large and complex structures previously unimaginable. Nevertheless, measurements of such structural detail within cellular environments remain elusive. This review will highlight how advances in mass spectrometry, chemical labeling, and informatics capabilities are merging to provide structural insights on proteins, complexes, and networks that exist inside cells. Because of the molecular detection specificity provided by mass spectrometry and proteomics, these approaches provide systems-level information that not only benefits from conventional structural analysis, but also is highly complementary. Although far from comprehensive in their current form, these approaches are currently providing systems structural biology information that can uniquely reveal how conformations and interactions involving many proteins change inside cells with perturbations such as disease, drug treatment, or phenotypic differences. With continued advancements and more widespread adaptation, systems structural biology based on in-cell labeling and mass spectrometry will provide an even greater wealth of structural knowledge.

Personalized Therapy and Liquid Biopsy-A Focus on Colorectal Cancer

(1) Background: Resistance mechanisms represent a barrier to anti-cancer therapies. Liquid biopsies would allow obtaining additional information in order to develop targeted therapies to thwart the resistance phenomena but also to follow in time real response to treatment and be able to adapt it the most quickly possible way in case of resistance. (2) Methods: herein we summarize the different liquid biopsies which are currently under research; we then review the literature and focalize on one of their potential roles: the theranostic one and especially in the cases of colorectal cancers. (3) Results: few studies targeting liquid biopsy as a potential tool to adapt cancer treatments are present in the literature and encompass few patients. (4) Conclusions: further research is needed to prove the efficiency of LB. Indeed, it seems a promising tool to guide treatment by targeting actionable mutations with detection of resistant mutations.

Tianlongkechuanling Inhibits Pulmonary Fibrosis Through Down-Regulation of Arginase-Ornithine Pathway

Background: Pulmonary Fibrosis (PF) is an interstitial lung disease characterized by excessive accumulation of extracellular matrix in the lungs, which disrupts the structure and gas exchange of the alveoli. There are only two approved therapies for PF, nintedanib (Nib) and pirfenidone. Therefore, the use of Chinese medicine for PF is attracting attention. Tianlongkechuanling (TL) is an effective Chinese formula that has been applied clinically to alleviate PF, which can enhance lung function and quality of life.

Purpose: The potential effects and specific mechanisms of TL have not been fully explored, yet. In the present study, proteomics was performed to explore the therapeutic protein targets of TL on Bleomycin (BLM)-induced Pulmonary Fibrosis.

Method: BLM-induced PF mice models were established. Hematoxylineosin staining and Masson staining were used to analyze histopathological changes and collagen deposition. To screen the differential proteins expression between the Control, BLM, BLM + TL and BLM + Nib (BLM + nintedanib) groups, quantitative proteomics was performed using tandem mass tag (TMT) labeling with nanoLC-MS/MS [nano liquid chromatographymass spectrometry]). Changes in the profiles of the expressed proteins were analyzed using the bioinformatics tools Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The protein–protein interactions (PPI) were established by STRING. Expressions of α-smooth muscle actin (α-SMA), Collagen I (Col1a1), Fibronectin (Fn1) and enzymes in arginase-ornithine pathway were detected by Western blot or RT-PCR.

Result: TL treatments significantly ameliorated BLM-induced collagen deposition in lung tissues. Moreover, TL can inhibit the protein expressions of α-SMA and the mRNA expressions of Col1a1 and Fn1. Using TMT technology, we observed 253 differentially expressed proteins related to PPI networks and involved different KEGG pathways. Arginase-ornithine pathway is highly significant. The expression of arginase1 (Arg1), carbamoyltransferase (OTC), carbamoy-phosphate synthase (CPS1), argininosuccinate synthase (ASS1), ornithine aminotransferase (OAT) argininosuccinate lyase (ASL) and inducible nitric oxide synthase (iNOS) was significantly decreased after TL treatments.

Conclusion: Administration of TL in BLM-induced mice resulted in decreasing pulmonary fibrosis. Our findings propose that the down regulation of arginase-ornithine pathway expression with the reduction of arginase biosynthesis is a central mechanism and potential treatment for pulmonary fibrosis with the prevention of TL.

Advances in Aptamer-Based Biomarker Discovery

The discovery and identification of biomarkers promote the rational and fast development of medical diagnosis and therapeutics. Clinically, the application of ideal biomarkers still is limited due to the suboptimal technology in biomarker discovery. Aptamers are single-stranded deoxyribonucleic acid or ribonucleic acid molecules and can selectively bind to varied targets with high affinity and specificity. Compared with antibody, aptamers have desirable advantages, such as flexible design, easy synthesis and convenient modification with different functional groups. Currently, different aptamer-based technologies have been developed to facilitate biomarker discovery, especially CELL-SELEX and SOMAScan technology. CELL-SELEX technology is mainly used to identify cell membrane surface biomarkers of various cells. SOMAScan technology is an unbiased biomarker detection method that can analyze numerous and even thousands of proteins in complex biological samples at the same time. It has now become a large-scale multi-protein biomarker discovery platform. In this review, we introduce the aptamer-based biomarker discovery technologies, and summarize and highlight the discovered emerging biomarkers recently in several diseases.

LC-MS/MS-Based Quantitative Proteomics Analysis of Different Stages of Non-Small-Cell Lung Cancer

Lung cancer has a higher incidence rate and mortality rate than all other cancers. Early diagnosis and treatment of lung cancer remain a major challenge, and the 5-year survival rate of its patients is only 15%. Basic and clinical research, especially the discovery of biomarkers, is crucial for improving the diagnosis and treatment of lung cancer patients. To identify novel biomarkers for lung cancer, we used the iTRAQ8-plex labeling technology combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to analyze the serum and urine of patients with different stages of lung adenocarcinoma and healthy individuals. A total of 441 proteins were identified in the serum, and 1,161 proteins were identified in the urine. The levels of elongation factor 1-alpha 2, proteasome subunit alpha type, and spermatogenesis-associated protein increased significantly in the serum of patients with lung cancer compared with those in healthy controls. The levels of transmembrane protein 143, cadherin 5, fibronectin 1, and collectin-11 decreased significantly in the serum of patients with metastases compared with those of nonmetastatic lung cancer patients. In the urine of stage III and IV lung cancer patients, the prostate-specific antigen and prostatic acid phosphatase decreased significantly, whereas neutrophil defensin 1 increased significantly. The results of LC-MS/MS were confirmed by enzyme-linked immunosorbent assay (ELISA) for transmembrane protein 143, cadherin 5, fibronectin 1, and collectin-11 in the serum. These proteins may be a potential early diagnosis and metastasis biomarkers for lung adenocarcinoma. Furthermore, the relative content of these markers in the serum and urine could be used to determine the progression of lung adenocarcinoma and achieve accurate staging and diagnosis.

iTRAQ-based proteomic profiling reveals protein alterations after traumatic brain injury and supports thyroxine as a potential treatment

Traumatic brain injury (TBI) is a primary cause of disability and death across the world. Previously, RNA analysis was widely used to study the pathophysiological mechanisms underlying TBI; however, the relatively low correlation between the transcriptome and proteome revealed that RNA transcription abundance does not reliably predict protein abundance, which led to the emergence of proteomic research. In this study, an iTRAQ proteomics approach was applied to detect protein alterations after TBI on a large scale. A total of 3937 proteins were identified, and 146 proteins were significantly changed after TBI. Moreover, 23 upregulated proteins were verified by parallel reaction monitoring (PRM), and fold changes in 16 proteins were consistent with iTRAQ outcomes. Transthyretin (Ttr) upregulation has been demonstrated at the transcriptional level, and this study further confirmed this at the protein level. After treatment with thyroxine (T4), which is transported by Ttr, the effects of T4 on neuronal histopathology and behavioral performance were determined in vivo (TBI + T4 group). Brain edema was alleviated, and the integrity of the blood brain barrier (BBB) improved. Escape latency in the Morris water maze (MWM) declined significantly compared with the group without T4 treatment. Modified neurological severity scores (mNSS) of the TBI + T4 group decreased from day 1 to day 7 post-TBI compared with the TBI + saline group. These results indicate that T4 treatment has potential to alleviate pathologic and behavioral abnormalities post-TBI. Protein alterations after T4 treatment were also detected by iTRAQ proteomics. Upregulation of proteins like Lgals3, Gfap and Apoe after TBI were reversed by T4 treatment. GO enrichment showed T4 mainly affected intermediate filament organization, cholesterol transportation and axonal regeneration. In summary, iTRAQ proteomics provides information about the impact of TBI on protein alterations and yields insight into underlying mechanisms and pathways involved in TBI and T4 treatment. Finally, Ttr and other proteins identified by iTRAQ may become potential novel treatment targets post-TBI.

Genomic data mining approaches for the discovery of anticancer peptides from Ganoderma sinense

Drug discovery from traditional Chinese medicine (TCM) typically involves the extraction of active ingredients from natural products with high biological activity and function from the vast repertoire of traditional Chinese medicine. This strategy cannot fully exploit the vast resources of TCM. Known as the longevity mushroom, Ganoderma spp. has been used as medicine for thousands of years. Recent studies have demonstrated its anticancer activity. While most research on Ganoderma spp. has focused on their polysaccharides or small molecules as potential anticancer components, possible anticancer peptides (ACPs) or proteins have been neglected. In this study, genomic data mining approaches were used to discover potential ACPs from Ganoderma sinense. A search against known ACPs identified 477 proteins in the G. sinense proteome that possess putative ACP sequences and that thus may serve as parent proteins. After in silico digestion by trypsin, 34 G. sinense proteins were predicted to release putative ACPs (by the mACPpred program). A subsequent sequence similarity comparison against known ACPs identified 15 trypsin-digested fragments as possible ACPs, of which 3 sequences were identical to known ACPs. The results indicated that ACPs may be involved in the anticancer activity of G. sinense and that genomic mining approaches can be effective strategies for discovering active components in TCM resources. The accumulation of genomic and proteomic data will undoubtedly accelerate drug discovery from TCM resources.

Influence of Warfarin Therapy on Prothrombin Production and Its Posttranslational Modifications

BACKGROUND

Protein induced by vitamin K absence-II (PIVKA-II) is produced by the liver during hepatoma and upon warfarin administration. Those patients have disturbed protein synthesis and glycosylation in the liver. This decreases the number of γ-carboxyglutamyl (Gla) residues on prothrombin, converting prothrombin into PIVKA-II. The mechanism of this conversion, however, is not clearly understood.

METHODS

Prothrombin was isolated from healthy and warfarin-treated individuals whose liver function of protein production was quantitatively normal. Glycan structures in the purified prothrombin containing PIVKA-II were qualitatively analyzed by high performance liquid chromatography after labeling the glycan with fluorophore 2-aminobenzamide.

RESULTS

The concentration of PIVKA-II was significantly higher in the warfarin-treated individuals than in the healthy individuals (P< 0.001). Although protein production in the liver was normal in both groups, the concentration of prothrombin was lower in the warfarin-treated individuals than in the healthy individuals (P < 0.001). The main glycan was A2 in the healthy and warfarin-treated individuals (86.6 ± 4.4% and 85.6 ± 3.4%, respectively). Eight types of glycan were characterized in both groups, although generation of PIVKA-II in the warfarin-treated individuals did not lead to variation in glycosylation of prothrombin.

CONCLUSIONS

Warfarin therapy leads to lower amounts of prothrombin and Gla residues within prothrombin without exerting qualitative and quantitative change in glycan profile and protein synthetic function in the liver.

Quantitative proteomics identified 3 oxidative phosphorylation genes with clinical prognostic significance in gastric cancer

The aim of the present study was to explore the underlying mechanisms involved in gastric cancer (GC) formation using data-independent acquisition (DIA) quantitative proteomics analysis. We identified the differences in protein expression and related functions involved in biological metabolic processes in GC. Totally, 745 differentially expressed proteins (DEPs) were found in GC tissues vs. gastric normal tissues. Despite enormous complexity in the details of the underlying regulatory network, we find that clusters of proteins from the DEPs were mainly involved in 38 pathways. All of the identified DEPs involved in oxidative phosphorylation were down-regulated. Moreover, GC possesses significantly altered biological metabolic processes, such as NADH dehydrogenase complex assembly and tricarboxylic acid cycle, which is mostly consistent with that in KEGG analysis. Furthermore the higher expression of UQCRQ, NDUFB7 and UQCRC2 were positively correlated with a better prognosis, implicating these proteins may as novel candidate diagnostic and prognostic biomarkers.

Differential proteomics mass spectrometry of melanosis coli

This study aims to reveal the biological relevancy between melanosis coli (MC) with colon cancer by analyzing the proteomics differences of tissues of melanosis coli, colon cancer, and normal ones to probe into the causes and development mechanisms of MC from the perspective of biomolecules. Fourteen differential protein spots were found in the study after using two-dimensional gel electrophoresis (2-DE) and bio-mass spectrometry (MALDI-TOF/TOF-MS). Specifically, six and eight differential protein spots in the melanosis coli tissues were detected, respectively, compared with the normal tissues and colon cancer tissues. Eight kinds of proteins, including keratin 8 (KRT8), keratin 18 (KRT18), fibrinogen beta chain isoform 2 preproprotein (FGB), catalase (CAT), 26s protease regulatory subunit 10b (PSMC6), isoform 1 of tropomyosin alpha-4 chain (TPM4), carbonic anhydrase 1 (CA1), isoform of prelammin-A/C (LMNA), were retrieved through the mass spectral database, which could be deemed as associated proteins of MC and colon cancer. The different expressions in the disease tissues indicate that these proteins may be connected with the carcinogenesis of MC as well as the malignant proliferation, development, differentiation, and diffusion of cancer cells.

Plasma Proteomic Analysis Reveals Age-Specific Changes in Platelet- and Endothelial Cell-Derived Proteins and Regulators of Plasma Coagulation and Fibrinolysis

This post hoc study of a plasma proteomic database investigated hemostatic proteins in the context of developmental hemostasis. Twenty-seven hemostatic proteins changed expression with age, and the hemostatic profile of neonates was unique. Appreciating developmental hemostasis through proteomics may lead to more personalized medicine for hospitalized children.

Label-free quantitative proteomics identifies transforming growth factor β1 (TGF-β1) as an inhibitor of adipogenic transformation in OP9-DL1 cells and primary thymic stromal cells

Background

Adipocyte accumulation is a predominant feature of age-related thymic involution, but the mechanisms responsible for thymic adipogenesis remain to be elucidated. The aim of this study was to identify key regulators in thymic adipogenesis. We used rosiglitazone, a potent peroxisome proliferator-activated receptor γ (PPARγ) agonist, to induce adipogenic differentiation of OP9-DL1 cells, and investigated the differentially expressed proteins during adipogenic differentiation by using label-free quantitative proteomics. Furthermore, the effects of transforming growth factor β1 (TGF-β1) on rosiglitazone-induced adipogenic differentiation of OP9-DL1 cells as well as the underlying mechanisms were also investigated.

Results

Proteomic analysis identified 139 proteins differed significantly in rosiglitazone-treated cells compared with dimethyl sulphoxide (DMSO)-treated cells. Rosiglitazone-induced adipogenic differentiation was inhibited by TGF-β1 treatment in OP9-DL1 cells and primary thymic stromal cells. Real-time PCR analysis showed significant increases in PPARγ and fatty acid binding protein 4 mRNA levels in rosiglitazone-treated cells, which were inhibited by TGF-β1 treatment. TGF-β1 down-regulated PPARγ expression at both mRNA and protein levels in OP9-DL1 cells. Chromatin immunoprecipitation analysis demonstrated that TGF-β1 enhanced the binding of Smad2/3 and histone deacetylase 1, but reduced the binding of H3K14ac to the promoter of PPARγ gene. TGF-β1 partially reversed the inhibitory effects of rosiglitazone on the expression of Axin2 and β-catenin protein levels. TGF-β1 inhibited rosiglitazone-induced adipogenic transformation in OP9-DL1 cells by down-regulation of PPARγ and activation of the canonical Wnt/β-catenin signaling pathway.

Conclusion

Taken together, activation of TGF-β pathway may serve as a useful strategy to prevent thymic adiposity in age-related thymic involution.

Electronic supplementary material

The online version of this article (10.1186/s13578-019-0311-1) contains supplementary material, which is available to authorized users.

SWATH-MS Proteomic Analysis of Oxygen-Induced Retinopathy Reveals Novel Potential Therapeutic Targets

Purpose

Oxygen-induced retinopathy (OIR) is the most widely used model for ischemic retinopathies such as retinopathy of prematurity (ROP), proliferative diabetic retinopathy (PDR), and retinal vein occlusion (RVO). The purpose of this study was to perform the most comprehensive characterization of OIR by a recently developed technique, sequential window acquisition of all theoretical mass spectra (SWATH-MS) proteomics.

Methods

Control and OIR retina samples collected from various time points were subjected to SWATH-MS and detailed data analysis. Immunohistochemistry from mouse retinas as well as neovascular membranes from human PDR and RVO patients were used for the detection of the localization of the proteins showing altered expression in the retina and to address their relevance to human ischemic retinopathies.

Results

We report the most extensive proteomic profiling of OIR to date by quantifying almost 3000 unique proteins and their expression differences between control and OIR retinas. Crystallins were the most prominent proteins induced by hypoxia in the retina, while angiogenesis related proteins such as Filamin A and nonmuscle myosin IIA stand out at the peak of angiogenesis. Majority of the changes in protein expression return to normal at P42, but there is evidence to suggest that proteins involved in neurotransmission remain at reduced level.

Conclusions

The results reveal new potential therapeutic targets to address hypoxia-induced pathological angiogenesis taking place in number of retinal diseases. The extensive proteomic profiling combined with pathway analysis also identifies novel molecular networks that could contribute to the pathogenesis of retinal diseases.

Serum Proteomics in African American Female Patients With Irritable Bowel Syndrome: An Exploratory Study

Background

Sex and subtype differences within patients with irritable bowel syndrome (IBS) complicate the understanding of disorder pathogenesis and hinder the design of efficacious, therapeutic interventions.

Objectives

The aims of this study were to harness the power of shotgun proteomic analysis, identify circulating proteins that differentiate African American female patients with IBS from healthy controls (HC), and gain biological insight on symptomatology.

Methods

Serum proteome analysis was performed upon a cohort of overweight, African American female participants with constipation predominant IBS symptoms (n = 5) and HC (n = 5), matched on age, sex, years of education, body mass index, and 11 physiological markers. Tandem mass tags for multiplexed proteomic analysis were performed, incorporating reverse-phase liquid chromatography and liquid chromatography-tandem mass spectrometry.

Results

Participants with IBS did not differ from HC in demographics, clinical characteristics, or initial proteomic analysis. Nested case control analysis of six samples (IBS: n = 3, HC: n = 3), hierarchically clustered into two main groups, with 12 out of 1,317 proteins significantly different in levels of expression: TGFβ1, PF4V1, PF4, APP, MMP9, PPBP, CTGF, SRGN, THBS1, WRN, LTBP1 (Isoform 3), and IGLV5-48. Top associations of identified proteins in DAVID and STRING resources (upregulated in HC vs. IBS) involve platelet alpha granule lumen, platelet activation/degranulation, extracellular region, and secretion by cell.

Discussion

Differentially expressed proteins between participants with IBS and HC involving platelet-related associations prompt inquiry as to differences in serotonergic signaling, inflammatory or immunomodulatory mechanisms underlying IBS symptomatology. Although preliminary and requiring validation in larger cohorts, these findings bear relevance to understanding pathogenic processes of IBS and biological effects of the disorder.

Analysis of Comparative Proteomic and Potent Targets of Peniciketal A in Human Acute Monocytic Leukemia

BACKGROUND

Peniciketal A (Pe-A), a spiroketal compound, shows potent anticancer activities in human acute monocytic leukemia. However, the detailed mechanisms and potent targets of Pe-A remain largely unexplored. Here, we investigated the differentially expressed proteins between the Pe-A-treated group and the control group on human acute monocytic leukemia cell line THP-1.

METHODS

The DEPs were analyzed by the liquid chromatography-tandem mass spectrometry (LC-MS/MS) with TMT label. The function and feature of the identified proteins were analyzed by the bioinformatic analysis. Western blotting was used to evaluate protein expression.

RESULTS

The DEPs were primarily sub located in the cytoplasm and the nucleus by regulating 21 pathways enriched through the Kyoto Encyclopedia of Genes and Genomes (KEGG). Moreover, we preliminarily demonstrated that glucose-6-phosphate 1-dehydrogenase (G6PD), prolow-density lipoprotein receptor-related protein 1 (LRP1) and Calreticulin (CALR) might be the potent targets of Pe-A on death induction of THP-1 cells.

CONCLUSION

Collectively, this study not only provides a global proteomic profile as the supplementary data of our previous studies but also provides interesting information that Pe-A may exert more bio-activities.

Application of Proteomics to Inflammatory Bowel Disease Research: Current Status and Future Perspectives

Inflammatory bowel disease (IBD) is a chronic relapsing/remitting inflammatory illness of the gastrointestinal tract of unknown aetiology. Despite recent advances in decoding the pathophysiology of IBD, many questions regarding disease pathogenesis remain. Genome-wide association studies (GWAS) and knockout mouse models have significantly advanced our understanding of genetic susceptibility loci and inflammatory pathways involved in IBD pathogenesis. Despite their important contribution to a better delineation of the disease process in IBD, these genetic findings have had little clinical impact to date. This is because the presence of a given gene mutation does not automatically correspond to changes in its expression or final metabolic or structural effect(s). Furthermore, the existence of these gene susceptibility loci in the normal population suggests other driving prerequisites for the disease manifestation. Proteins can be considered the main functional units as almost all intracellular physiological functions as well as intercellular interactions are dependent on them. Proteomics provides methods for the large-scale study of the proteins encoded by the genome of an organism or a cell, to directly investigate the proteins and pathways involved. Understanding the proteome composition and alterations yields insights into IBD pathogenesis as well as identifying potential biomarkers of disease activity, mucosal healing, and cancer progression. This review describes the state of the art in the field with respect to the study of IBD and the potential for translation from biomarker discovery to clinical application.

Enhanced Molecular Appreciation of Psychiatric Disorders Through High-Dimensionality Data Acquisition and Analytics

The initial diagnosis, molecular investigation, treatment, and posttreatment care of major psychiatric disorders (schizophrenia and bipolar depression) are all still significantly hindered by the current inability to define these disorders in an explicit molecular signaling manner. High-dimensionality data analytics, using large datastreams from transcriptomic, proteomic, or metabolomic investigations, will likely advance both the appreciation of the molecular nature of major psychiatric disorders and simultaneously enhance our ability to more efficiently diagnose and treat these debilitating conditions. High-dimensionality data analysis in psychiatric research has been heterogeneous in aims and methods and limited by insufficient sample sizes, poorly defined case definitions, methodological inhomogeneity, and confounding results. All of these issues combine to constrain the conclusions that can be extracted from them. Here, we discuss possibilities for overcoming methodological challenges through the implementation of transcriptomic, proteomic, or metabolomics signatures in psychiatric diagnosis and offer an outlook for future investigations. To fulfill the promise of intelligent high-dimensionality data-based differential diagnosis in mental disease diagnosis and treatment, future research will need large, well-defined cohorts in combination with state-of-the-art technologies.

Identification of candidate serum biomarkers of childhood-onset growth hormone deficiency using SWATH-MS and feature selection

A typical clinical manifestation of growth hormone deficiency (GHD) is a short stature resulting from delayed growth, but GHD affects bone health, cardiovascular function and metabolic profile and therefore quality of life. Although early GH treatment during childhood has been shown to improve outcomes, no single biochemical parameter is currently available for the accurate diagnosis of GHD in children. There is hence a need for non-invasive biomarkers. In this study, the relative abundance of serum proteins from GHD children and healthy controls was measured by next-generation proteomics SWATH-MS technology. The data generated was analysed by machine-learning feature-selection algorithms in order to discover the minimum number of protein biomarkers that best discriminate between both groups. The analysis of serum proteins by a SWATH-MS approach yielded a useful method for discovering potential biomarkers of GHD in children. A total of 263 proteins were confidently detected and quantified in each sample. Pathway analysis indicated an effect on tissue/organ structure and morphogenesis. The top ten serum protein biomarker candidates were identified after applying feature-selection data analysis. The combination of three proteins - apolipoprotein A-IV, complement factor H-related protein 4 and platelet basic protein - demonstrated the best classification performance for our data. In addition, the apolipoprotein group resulted in strong over-representation, thus highlighting these proteins as an additional promising biomarker panel.

SIGNIFICANCE

Currently there is no single biochemical parameter available for the accurate diagnosis of growth hormone (GH) deficiency (GHD) in children. Simple GH measurements are not an option: because GH is released in a pulsatile action, its blood levels fluctuate throughout the day and remain nearly undetectable for most of that time. This makes measurements of GH in a single blood sample useless for assessing GH deficiency. Actually, the diagnosis of GHD includes a combination of direct and indirect non-accurate measurements, such as taking several body measurements, testing GH levels in multiple blood samples after provocative tests (GH peak <7.3ng/mL, using radioimmunoassay), and conducting magnetic resonance imaging (MRI), among others. Therefore, there is a need for simple, non-invasive, accurate and cost-effective biomarkers. Here we report a case-control study, where relative abundance of serum proteins were measured by next-generation proteomics SWATH-MS technology in 15 GHD children and 15healthy controls matched by age, sex, and not receiving any treatment. Data generated was analysed by machine learning feature selection algorithms. 263 proteins could be confidently detected and quantified on each sample. The top 10 serum protein biomarker candidates could be identified after applying a feature selection data analysis. The combination of three proteins, apolipoprotein A-IV, complement factor H-related protein 4 and platelet basic protein, showed the best classification performance for our data. In addition, the fact that the pathway and GO analysis we performed pointed to the apolipoproteins as over-represented highlights this protein group as an additional promising biomarker panel for the diagnosis of GHD and for treatment evaluation.

The Scope of Big Data in One Medicine: Unprecedented Opportunities and Challenges

Advances in high-throughput molecular biology and electronic health records (EHR), coupled with increasing computer capabilities have resulted in an increased interest in the use of big data in health care. Big data require collection and analysis of data at an unprecedented scale and represents a paradigm shift in health care, offering (1) the capacity to generate new knowledge more quickly than traditional scientific approaches; (2) unbiased collection and analysis of data; and (3) a holistic understanding of biology and pathophysiology. Big data promises more personalized and precision medicine for patients with improved accuracy and earlier diagnosis, and therapy tailored to an individual’s unique combination of genes, environmental risk, and precise disease phenotype. This promise comes from data collected from numerous sources, ranging from molecules to cells, to tissues, to individuals and populations—and the integration of these data into networks that improve understanding of heath and disease. Big data-driven science should play a role in propelling comparative medicine and “one medicine” (i.e., the shared physiology, pathophysiology, and disease risk factors across species) forward. Merging of data from EHR across institutions will give access to patient data on a scale previously unimaginable, allowing for precise phenotype definition and objective evaluation of risk factors and response to therapy. High-throughput molecular data will give insight into previously unexplored molecular pathophysiology and disease etiology. Investigation and integration of big data from a variety of sources will result in stronger parallels drawn at the molecular level between human and animal disease, allow for predictive modeling of infectious disease and identification of key areas of intervention, and facilitate step-changes in our understanding of disease that can make a substantial impact on animal and human health. However, the use of big data comes with significant challenges. Here we explore the scope of “big data,” including its opportunities, its limitations, and what is needed capitalize on big data in one medicine.

Serial-omics of P53-/-, Brca1-/- Mouse Breast Tumor and Normal Mammary Gland

This study demonstrates a liquid-liquid extraction for the sequential tandem mass spectrometry (LC-MS/MS) analysis of non-polar lipids, polar metabolites, proteins and phosphorylation sites from a single piece of tissue. Extraction of 10 mg BRCA-/-, p53-/- breast tumor tissue or normal mammary gland tissue with methyl-tert-butyl ether (MTBE) results in three phases: an upper non-polar phase containing 1,382 lipids, a lower polar phase with 805 metabolites and a precipitated protein pellet with 4,792 proteins with 1,072 phosphorylation sites. Comparative analysis revealed an activated AKT-mTOR pathway in tumors. Tumors also showed a reduction of phosphorylation sites involved in transcription and RNA splicing and decreased abundance of enzymes in lipid synthesis. Analysis of polar metabolites revealed a reduction in glycolysis, pentose phosphate pathway, polyamines and nucleotides, but an increase in TCA and urea cycle intermediates. Analysis of lipids revealed a shift from high triglycerides in mammary gland to high phospholipid levels in tumors. The data were integrated into a model showing breast tumors exhibit features on the proteomic, lipidomic and metabolomic level that are distinct from normal breast tissue. Our integrative technique lends itself to samples such as tumor biopsies, dried blood spots and fluids including urine and CSF to develop biomarkers of disease.

Mass spectrometric identification of dystrophin, the protein product of the Duchenne muscular dystrophy gene, in distinct muscle surface membranes

Supramolecular membrane complexes of low abundance are difficult to study by routine bioanalytical techniques. The plasmalemmal complex consisting of sarcoglycans, dystroglycans, dystrobrevins and syntrophins, which is closely associated with the membrane cytoskeletal protein dystrophin, represents such a high‑molecular‑mass protein assembly in skeletal muscles. The almost complete loss of the dystrophin isoform Dp427‑M and concomitant reduction in the dystrophin‑associated glycoprotein complex is the underlying cause of the highly progressive neuromuscular disorder named Duchenne muscular dystrophy. This gives the detailed characterization of the dystrophin complex considerable pathophysiological importance. In order to carry out a comprehensive mass spectrometric identification of the dystrophin‑glycoprotein complex, in this study, we used extensive subcellular fractionation and enrichment procedures prior to subproteomic analysis. Mass spectrometry identified high levels of full‑length dystrophin isoform Dp427‑M, α/β‑dystroglycans, α/β/γ/δ‑sarcoglycans, α1/β1/β2‑syntrophins and α/β‑dystrobrevins in highly purified sarcolemma vesicles. By contrast, lower levels were detected in transverse tubules and no components of the dystrophin complex were identified in triads. For comparative purposes, the presence of organellar marker proteins was studied in crude surface membrane preparations vs. enriched fractions from the sarcolemma, transverse tubules and triad junctions using gradient gel electrophoresis and on‑membrane digestion. This involved the subproteomic assessment of various ion‑regulatory proteins and excitation‑contraction coupling components. The comparative profiling of skeletal muscle fractions established a relatively restricted subcellular localization of the dystrophin‑glycoprotein complex in the muscle fibre periphery by proteomic means and clearly demonstrated the absence of dystrophin from triad junctions by sensitive mass spectrometric analysis.