Label-free Quantitative Method Research Articles

Label-free quantitative proteomic analysis reveals the characteristics of ovarian development from stage II to III in Chinese sturgeon (Acipenser sinensis)

Chinese sturgeon (Acipenser sinensis) is an endangered anadromous and rare fish. The ovary development from stage II to III is being challenged by captive conditions, which seriously hinders the artificial reproduction of Chinese sturgeon. A comparative proteomic analysis on the ovaries at stage II and stage III of Chinese sturgeon was conducted in this study using the label-free quantitative method to uncover the intricate physiological processes. The findings revealed 200 up-regulated differentially expressed proteins (DEPs) and 150 down-regulated DEPs in the ovary at stage III compared with stage II, and 11 DEPs (including UCHL1, VTG, CTSD, and ZP, etc.) involved in the vitellogenesis and oocyte growth. Moreover, the up-regulated DEPs exhibited significant enrichment in the pathways linked to protein synthesis (ribosome, protein processing in the endoplasmic), metabolism and energy production (valine, leucine and isoleucine degradation, TCA cycle, oxidative phosphorylation, and fatty acid degradation), suggesting more active protein processing and energy metabolism at stage III. Meanwhile, APOB was down-regulated while VTG was up-regulated in stage III ovary, indicating the uptake of yolk protein and lipid through VTG at this stage. The parallel reaction monitoring (PRM) quantification of 16 DEPs solidly validated the outcomes of label-free analysis. This study provided powerful information for understanding the physiological processes of ovarian development in Chinese sturgeon, and potential biomarkers in predicting the vitellogenic stage.

Proteomic analysis of giant panda testicular tissue of different age groups

Background The reproductive ability of male giant pandas has been a major complicating factor in the ex-situ conservation of the species. While it is well known that the testis produces sperm and secretes androgens, a process that requires precise regulation of various proteins, at present, there has been no systematic study on the composition of proteins in the testis of the giant pandas. Therefore, this study aims to apply proteomics to explore the regulation of proteins in the testes of giant pandas. Methods Samples from the testes of three giant pandas (22 years, 18 years, 8 days) were studied to assess the protein’s function. A label-free quantitative method was used to isolate testicular proteins from each male, 139,039 peptides and 11,435 proteins were obtained. Results Gene Ontology (GO) annotates most of the proteins involved in the processes of protein phosphorylation, oxidation-reduction, proteolysis, and signal transduction. KEGG pathway indicated that most of the proteins were involved in the pathway of signal transduction, transport, and catabolism. The protein kinase and WD40 repeats were involved in protein-protein interaction, which in turn regulates gene expression in the testicular tissue of giant pandas. Conclusions This study is the first to conduct an in-depth proteomic analysis of testicular tissue in giant pandas. The results revealed the important role of proteins in testicular tissue on spermatogenesis, testosterone production, and testicular microenvironment, providing clues for further research on male giant panda reproduction.

Site-specific N-glycan alterations on haptoglobin as potential biomarkers for distinguishing intrahepatic cholangiocarcinoma from hepatocellular carcinoma

Intrahepatic cholangiocellular carcinoma (ICC) is a challenging malignancy marked by subtle early symptoms and a high mortality rate, making effective diagnostic markers crucial for early detection and improved patient outcomes. Currently, the conventional diagnosis of ICC is not easily distinguishable from Hepatocellular Carcinoma (HCC) and lacks highly specific and sensitive diagnostic markers. Protein glycosylation, pivotal in biological processes, shows promise for cancer biomarkers due to its association with disease progression. This study aims to develop a novel biomarker discovery framework for ICC utilizing site-specific quantitative N-glycoproteomics to overcome the limitations of existing diagnostic approaches. Employing a tandem mass tag (TMT)-based quantitative analysis, we profiled serum glycoproteins from ICC, HCC, and control cohorts at site-specific glycosylation level. The identified markers underwent further validation in an independent cohort using label-free quantitative methods. Ultimately, we identified five site-specific N-glycans on haptoglobin (HP) as potential biomarkers (AUC > 0.9) for distinguishing ICC from HCC. This finding represents a considerable advance over traditional biomarkers, highlighting the significance of protein glycosylation alterations in ICC pathogenesis. This research, therefore, sets a new precedent for biomarker discovery in ICC, with potential applications in other cancers characterized by glycosylation abnormalities.

Underlying mechanism of Dendrobium huoshanense resistance to lead stress using the quantitative proteomics method

Lead affects photosynthesis and growth and has serious toxic effects on plants. Here, the differential expressed proteins (DEPs) in D. huoshanense were investigated under different applications of lead acetate solutions. Using label-free quantitative proteomics methods, more than 12,000 peptides and 2,449 proteins were identified. GO and KEGG functional annotations show that these differential proteins mainly participate in carbohydrate metabolism, energy metabolism, amino acid metabolism, translation, protein folding, sorting, and degradation, as well as oxidation and reduction processes. A total of 636 DEPs were identified, and lead could induce the expression of most proteins. KEGG enrichment analysis suggested that proteins involved in processes such as homologous recombination, vitamin B6 metabolism, flavonoid biosynthesis, cellular component organisation or biogenesis, and biological regulation were significantly enriched. Nearly 40 proteins are involved in DNA replication and repair, RNA synthesis, transport, and splicing. The effect of lead stress on D. huoshanense may be achieved through photosynthesis, oxidative phosphorylation, and the production of excess antioxidant substances. The expression of 9 photosynthesis-related proteins and 12 oxidative phosphorylation-related proteins was up-regulated after lead stress. Furthermore, a total of 3 SOD, 12 POD, 3 CAT, and 7 ascorbate-related metabolic enzymes were identified. Under lead stress, almost all key enzymes involved in the synthesis of antioxidant substances are up-regulated, which may facilitate the scavenging of oxygen-free radical scavenging. The expression levels of some key enzymes involved in sugar and glycoside synthesis, the phenylpropanoid synthesis pathway, and the terpene synthesis pathway also increased. More than 30 proteins involved in heavy metal transport were also identified. Expression profiling revealed a significant rise in the expression of the ABC-type multidrug resistance transporter, copper chaperone, and P-type ATPase with exposure to lead stress. Our findings lay the basis for research on the response and resistance of D. huoshanense to heavy metal stress.

Proteomic profiling of bronchoalveolar lavage fluid uncovers protein clusters linked to survival in idiopathic forms of interstitial lung disease

BackgroundIdiopathic interstitial pneumonias (IIPs) such as idiopathic pulmonary fibrosis (IPF) and interstitial pneumonia with autoimmune features (IPAF), present diagnostic and therapeutic challenges due to their heterogeneous nature. This study aimed to identify intrinsic molecular signatures within the lung microenvironment of these IIPs through proteomic analysis of bronchoalveolar lavage fluid (BALF).MethodsPatients with IIP (n=23) underwent comprehensive clinical evaluation including pre-treatment bronchoscopy and were compared to controls without lung disease (n=5). Proteomic profiling of BALF was conducted using label-free quantitative methods. Unsupervised cluster analyses identified protein expression profiles which were then analyzed to predict survival outcomes and investigate associated pathways.ResultsProteomic profiling successfully differentiated IIP from controls.k-means clustering, based on protein expression revealed three distinct IIP clusters, which were not associated with age, smoking history, or baseline pulmonary function. These clusters had unique survival trajectories and provided more accurate survival predictions than the Gender Age Physiology (GAP) index (C-index 0.794versus0.709). The cluster with the worst prognosis featured decreased inflammatory signaling and complement activation, with pathway analysis highlighting altered immune response pathways related to immunoglobulin production and B cell-mediated immunity.ConclusionsThe unsupervised clustering of BALF proteomics provided a novel stratification of IIP patients, with potential implications for prognostic and therapeutic targeting. The identified molecular phenotypes underscore the diversity within the IIP classification and the potential importance of personalized treatments for these conditions. Future validation in larger, multi-ethnic cohorts is essential to confirm these findings and to explore their utility in clinical decision-making for patients with IIP.

Proteomic profiling of bronchoalveolar lavage fluid uncovers protein clusters linked to survival in idiopathic forms of interstitial lung disease.

Idiopathic interstitial pneumonias (IIPs) such as idiopathic pulmonary fibrosis (IPF) and interstitial pneumonia with autoimmune features (IPAF), present diagnostic and therapeutic challenges due to their heterogeneous nature. This study aimed to identify intrinsic molecular signatures within the lung microenvironment of these IIPs through proteomic analysis of bronchoalveolar lavage fluid (BALF). Patients with IIP (n=23) underwent comprehensive clinical evaluation including pre-treatment bronchoscopy and were compared to controls without lung disease (n=5). Proteomic profiling of BALF was conducted using label-free quantitative methods. Unsupervised cluster analyses identified protein expression profiles which were then analyzed to predict survival outcomes and investigate associated pathways. Proteomic profiling successfully differentiated IIP from controls. k-means clustering, based on protein expression revealed three distinct IIP clusters, which were not associated with age, smoking history, or baseline pulmonary function. These clusters had unique survival trajectories and provided more accurate survival predictions than the Gender Age Physiology (GAP) index (C-index 0.794 vs. 0.709). The cluster with the worst prognosis featured decreased inflammatory signaling and complement activation, with pathway analysis highlighting altered immune response pathways related to immunoglobulin production and B cell-mediated immunity. The unsupervised clustering of BALF proteomics provided a novel stratification of IIP patients, with potential implications for prognostic and therapeutic targeting. The identified molecular phenotypes underscore the diversity within the IIP classification and the potential importance of personalized treatments for these conditions. Future validation in larger, multi-ethnic cohorts is essential to confirm these findings and to explore their utility in clinical decision-making for patients with IIP.

Proteomic analysis of serum extracellular vesicles from biliary tract infection patients to identify novel biomarkers

Biliary tract infection (BTI), a commonly occurring abdominal disease, despite being extensively studied for its initiation and underlying mechanisms, continues to pose a challenge in the quest for identifying specific diagnostic biomarkers. Extracellular vesicles (EVs), which emanate from diverse cell types, serve as minute biological entities that mirror unique physiological or pathological conditions. Despite their potential, there has been a relatively restricted exploration of EV-oriented methodologies for diagnosing BTI. To uncover potent protein biomarkers for BTI patients, we applied a label-free quantitative proteomic method known for its unbiased and high-throughput nature. Furthermore, 192 differentially expressed proteins surfaced within EVs isolated from individuals afflicted with BTI. Subsequent GO and KEGG analyses pinpointed Carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) and Crumbs homolog 3 (CRB3) as noteworthy biomarkers. Validation via data analysis of plasma-derived EV samples confirmed their specificity to BTI. Our study leveraged an unbiased proteomic tool to unveil CEACAM1 and CRB3 as promising protein biomarkers in serum EVs, presenting potential avenues for the advancement of diagnostic systems for BTI detection.

Pick-up single-cell proteomic analysis for quantifying up to 3000 proteins in a Mammalian cell

The shotgun proteomic analysis is currently the most promising single-cell protein sequencing technology, however its identification level of ~1000 proteins per cell is still insufficient for practical applications. Here, we develop a pick-up single-cell proteomic analysis (PiSPA) workflow to achieve a deep identification capable of quantifying up to 3000 protein groups in a mammalian cell using the label-free quantitative method. The PiSPA workflow is specially established for single-cell samples mainly based on a nanoliter-scale microfluidic liquid handling robot, capable of achieving single-cell capture, pretreatment and injection under the pick-up operation strategy. Using this customized workflow with remarkable improvement in protein identification, 2449–3500, 2278–3257 and 1621–2904 protein groups are quantified in single A549 cells (n = 37), HeLa cells (n = 44) and U2OS cells (n = 27) under the DIA (MBR) mode, respectively. Benefiting from the flexible cell picking-up ability, we study HeLa cell migration at the single cell proteome level, demonstrating the potential in practical biological research from single-cell insight.

Protein expression changes in Tibetan middle-to-long distance runners after the transition from high altitude to low altitude: Implications for enhancing endurance training

The study aims to investigate the differences in protein expressions in Xizang's (Tibetan) middle-to-long distance runners after the transition from high altitude to low altitude and reveal the molecular mechanisms underlying their enhanced middle-to-long distance running performance. In the study, eleven subjects were selected from native Tibetan middle-to-long distance runners to participate in an 8-week pre-competition exercise training program consisting of a 6-week training stage in Kangding City at an altitude of 2 560 meters (m) and a subsequent 2-week training stage in Leshan City at an altitude of 360 ​m. Blood samples were collected twice from the runners before beginning altitude exercise training in Kangding and after going to sea level - Leshan City. Using a label-free quantitative method, peptides in the samples were analyzed by mass spectrometry. Proteomic analysis was performed to identify differentially expressed proteins and predict their biological functions. A total of 846 proteins were identified in the 21 samples, including 719 quantified proteins. In total, 49 significantly differentially expressed proteins (p ​< ​0.05) were identified, including twenty-eight 0.2-fold up-regulated proteins or twenty-one 0.17-fold down-regulated proteins. The up-regulated proteins, including cystic fibrosis transmembrane conductance regulator (CFTR) and carbonic anhydrase I (CAI), were of particular interest due to their role in regulating the oxygen saturation in deep tissues. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that these proteins were mainly involved in regulating actin cytoskeleton, local adhesion, biotin absorption and metabolism, immune system, cancer, and membrane transport processes. In conclusion, Tibetan middle-to-long distance runners who resided in high-altitude areas benefited from repeated plateau-plain alternate training mode during the pre-competition period. The training mode induced positive changes in peripheral blood plasma proteins (CFTR and CAI), the biomarkers associated with aerobic capacity. Among the 11 runners, one female athlete won the gold medal in the 3 000-m running event in this competition, demonstrating that the plateau-plain alternate training mode could enhance the aerobic capacity of athletes.

Data-independent acquisition-based mass spectrometry(DIA-MS) for quantitative analysis of patients with chronic hepatitis B

Chronic hepatitis B is a significant public health problem and complex pathologic process, and unraveling the underlying mechanisms and pathophysiology is of great significance. Data independent acquisition mass spectrometry (DIA-MS) is a label-free quantitative proteomics method that has been successfully applied to the study of a wide range of diseases. The aim of this study was to apply DIA-MS for proteomic analysis of patients with chronic hepatitis B. We performed comprehensive proteomics analysis of protein expression in serum samples from HBV patients and healthy controls by using DIA-MS. Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and protein network analysis were performed on differentially expressed proteins and were further combined with literature analysis. We successfully identified a total of 3786 serum proteins with a high quantitative performance from serum samples in this study. We identified 310 differentially expressed proteins (DEPs) (fold change > 1.5 and P value < 0.05 as the criteria for a significant difference) between HBV and healthy samples. A total of 242 upregulated proteins and 68 downregulated proteins were among the DEPs. Some protein expression levels were significantly elevated or decreased in patients with chronic hepatitis B, indicating a relation to chronic liver disease, which should be further investigated.

Comprehensive proteome, phosphoproteome and kinome characterization of luminal A breast cancer.

Breast cancer is one of the most frequently occurring malignant cancers worldwide. Invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) are the two most common histological subtypes of breast cancer. In this study, we aimed to deeply explore molecular characteristics and the relationship between IDC and ILC subtypes in luminal A subgroup of breast cancer using comprehensive proteomics and phosphoproteomics analysis. Cancer tissues and noncancerous adjacent tissues (NATs) with the luminal A subtype (ER- and PR-positive, HER2-negative) were obtained from paired IDC and ILC patients respectively. Label-free quantitative proteomics and phosphoproteomics methods were used to detect differential proteins and the phosphorylation status between 10 paired breast cancer and NATs. Then, the difference in protein expression and its phosphorylation between IDC and ILC subtypes were explored. Meanwhile, the activation of kinases and their substrates was also revealed by Kinase-Substrate Enrichment Analysis (KSEA). In the luminal A breast cancer, a total of 5,044 high-confidence proteins and 3,808 phosphoproteins were identified from 10 paired tissues. The protein phosphorylation level in ILC tissues was higher than that in IDC tissues. Histone H1.10 was significantly increased in IDC but decreased in ILC, Conversely, complement C4-B and Crk-like protein were significantly decreased in IDC but increased in ILC. Moreover, the increased protein expression of Septin-2, Septin-9, Heterogeneous nuclear ribonucleoprotein A1 and Kinectin but reduce of their phosphorylation could clearly distinguish IDC from ILC. In addition, IDC was primarily related to energy metabolism and MAPK pathway, while ILC was more closely involved in the AMPK and p53/p21 pathways. Furthermore, the kinomes in IDC were primarily significantly activated in the CMGC groups. Our research provides insights into the molecular characterization of IDC and ILC and contributes to discovering novel targets for further drug development and targeted treatment.

Proteomics profiling of vitreous humor reveals complement and coagulation components, adhesion factors, and neurodegeneration markers as discriminatory biomarkers of vitreoretinal eye diseases.

Diabetic retinopathy (DR) and age-related macular degeneration (AMD) are leading causes of visual impairment and blindness in people aged 50 years or older in middle-income and industrialized countries. Anti-VEGF therapies have improved the management of neovascular AMD (nAMD) and proliferative DR (PDR), no treatment options exist for the highly prevalent dry form of AMD. To unravel the biological processes underlying these pathologies and to find new potential biomarkers, a label-free quantitative (LFQ) method was applied to analyze the vitreous proteome in PDR (n=4), AMD (n=4) compared to idiopathic epiretinal membranes (ERM) (n=4). Post-hoc tests revealed 96 proteins capable of differentiating among the different groups, whereas 118 proteins were found differentially regulated in PDR compared to ERM and 95 proteins in PDR compared to dry AMD. Pathway analysis indicates that mediators of complement, coagulation cascades and acute phase responses are enriched in PDR vitreous, whilst proteins highly correlated to the extracellular matrix (ECM) organization, platelet degranulation, lysosomal degradation, cell adhesion, and central nervous system development were found underexpressed. According to these results, 35 proteins were selected and monitored by MRM (multiple reaction monitoring) in a larger cohort of patients with ERM (n=21), DR/PDR (n=20), AMD (n=11), and retinal detachment (n=13). Of these, 26 proteins could differentiate between these vitreoretinal diseases. Based on Partial least squares discriminant and multivariate exploratory receiver operating characteristic (ROC) analyses, a panel of 15 discriminatory biomarkers was defined, which includes complement and coagulation components (complement C2 and prothrombin), acute-phase mediators (alpha-1-antichymotrypsin), adhesion molecules (e.g., myocilin, galectin-3-binding protein), ECM components (opticin), and neurodegeneration biomarkers (beta-amyloid, amyloid-like protein 2).

Label-free quantitative proteomics of arbuscular mycorrhizal Elaeagnus angustifolia seedlings provides insights into salt-stress tolerance mechanisms.

Soil salinization has become one of the most serious environmental issues globally. Excessive accumulation of soluble salts will adversely affect the survival, growth, and reproduction of plants. Elaeagnus angustifolia L., commonly known as oleaster or Russian olive, has the characteristics of tolerance to drought and salt. Arbuscular mycorrhizal (AM) fungi are considered to be bio-ameliorator of saline soils that can enhance the salt tolerance of the host plants. However, there is little information on the root proteomics of AM plants under salt stress. In this study, a label-free quantitative proteomics method was employed to identify the differentially abundant proteins in AM E. angustifolia seedlings under salt stress. The results showed that a total of 170 proteins were significantly differentially regulated in E.angustifolia seedlings after AMF inoculation under salt stress. Mycorrhizal symbiosis helps the host plant E. angustifolia to respond positively to salt stress and enhances its salt tolerance by regulating the activities of some key proteins related to amino acid metabolism, lipid metabolism, and glutathione metabolism in root tissues. Aspartate aminotransferase, dehydratase-enolase-phosphatase 1 (DEP1), phospholipases D, diacylglycerol kinase, glycerol-3-phosphate O-acyltransferases, and gamma-glutamyl transpeptidases may play important roles in mitigating the detrimental effect of salt stress on mycorrhizal E. angustifolia . In conclusion, these findings provide new insights into the salt-stress tolerance mechanisms of AM E. angustifolia seedlings and also clarify the role of AM fungi in the molecular regulation network of E. angustifolia under salt stress.

Differential Serum Proteomic Signatures between Acute Aortic Dissection and Acute Myocardial Infarction.

Acute aortic dissection (AAD) and acute myocardial infarction (AMI) are both severe cardiovascular diseases that may cause sudden death. However, whether serum proteins are differentially expressed between AAD and AMI remains unclear. Here, we aimed to explore serum protein profiles between AAD and AMI patients. A total of 75 serum samples were collected, including AAD patients without AMI (n = 25), AMI patients without AAD (n = 25), and normal subjects (n = 25). Protein identities and expression levels were assessed by LC-MS/MS analysis and a label-free quantitation method, respectively. After depletion of albumin and IgG, a total of 117 proteins with differential expression (fold change ≥2 or ≤-2.0, p &lt; 0.05) were identified, of which 60 were upregulated and 57 were downregulated in AAD sera as compared to AMI sera. Bioinformatic analysis revealed that the differentially expressed serum proteins were mainly derived from exosomes and the extracellular space, and their molecular functions and biological processes were primarily involved in the activity of transporters and complements and the immune response. In addition, the serum level of Cadherin-5, an identified protein with significant regulation in AAD, was further evaluated by ELISA and the results showed that Cadherin-5 in AAD sera was higher that in AMI and healthy sera. Collectively, these findings reveal the differential serum protein profiles between AAD and AMI, which may reflect the divergent pathophysiological progression between the two cardiovascular diseases.

Determination of porcine derived components in gelatin and gelatin-containing foods by high performance liquid chromatography-tandem mass spectrometry

Detection and quantitation of porcine derived components in bovine and donkey gelatins and gelatin-containing foods is required for religious practices and consumer economic interests. In this study, shot-gun proteomics approaches were implemented to identify species-specific peptide biomarkers of three main gelatin origins, including porcine, bovine and donkey. Tryptic gelatin peptides were separated and analyzed with ultra-performance liquid chromatography-tandem high-resolution mass spectrometry (UPLC-HRMS), and 11 peptide biomarkers were selected for porcine, bovine and donkey. The gelatin pretreatment methods in three different food matrixes were optimized, and a label-free quantitative method using the MRM method of the most sensitive biomarker peptides was established. Among them, two porcine gelatin quantitative peptides were confirmed to have good linearity. The method has been successfully applied to the adulteration detection of porcine-derived components in gelatin and the quantification of porcine gelatin in candy and dairy products, with LODs of 0.07, 0.08 and 0.12 mg/kg, respectively. • A strategy for identification of peptide biomarkers of common gelatin species was established and improved with untargeted and targeted proteomics approaches. • Eleven species-specific peptide biomarkers were selected for porcine, bovine and donkey gelatin. • The pretreatment method of gelatin in different food matrixes has been optimized, especially for gelatin in dairy products. • The label-free MRM method is used for quantitative determination of adulterated porcine gelatin in mixed gelatin and gelatin-containing food, with good linearity, specificity, sensitivity and repeatability.

Insight on physicochemical properties governing peptide MS1 response in HPLC-ESI-MS/MS: A deep learning approach

Accurate and absolute quantification of peptides in complex mixtures using quantitative mass spectrometry (MS)-based methods requires foreground knowledge and isotopically labeled standards, thereby increasing analytical expenses, time consumption, and labor, thus limiting the number of peptides that can be accurately quantified. This originates from differential ionization efficiency between peptides and thus, understanding the physicochemical properties that influence the ionization and response in MS analysis is essential for developing less restrictive label-free quantitative methods. Here, we used equimolar peptide pool repository data to develop a deep learning model capable of identifying amino acids influencing the MS1 response. By using an encoder-decoder with an attention mechanism and correlating attention weights with amino acid physicochemical properties, we obtain insight on properties governing the peptide-level MS1 response within the datasets. While the problem cannot be described by one single set of amino acids and properties, distinct patterns were reproducibly obtained. Properties are grouped in three main categories related to peptide hydrophobicity, charge, and structural propensities. Moreover, our model can predict MS1 intensity output under defined conditions based solely on peptide sequence input. Using a refined training dataset, the model predicted log-transformed peptide MS1 intensities with an average error of 9.7 ± 0.5% based on 5-fold cross validation, and outperformed random forest and ridge regression models on both log-transformed and real scale data. This work demonstrates how deep learning can facilitate identification of physicochemical properties influencing peptide MS1 responses, but also illustrates how sequence-based response prediction and label-free peptide-level quantification may impact future workflows within quantitative proteomics.

Docosahexaenoic acid administration improves diabetes-induced cardiac fibrosis through enhancing fatty acid oxidation in cardiac fibroblast

Diabetes mellitus can lead to various complications, including organ fibrosis. Metabolic remodeling often occurs during the development of organ fibrosis. Docosahexaenoic acid (DHA), an essential ω-3 polyunsaturated fatty acid, shows great benefits in improving cardiovascular disease and organ fibrosis, including regulating cellular metabolism. In this study, we investigated whether DHA can inhibit diabetes-induced cardiac fibrosis by regulating the metabolism of cardiac fibroblasts. Type I diabetic mice were induced by streptozotocin and after supplementation with DHA for 16 weeks, clinical indicators of serum and heart were evaluated. DHA administration significantly improved serum lipid levels, cardiac function and cardiac interstitial fibrosis, but not blood glucose levels. Subsequently, immunofluorescences, western blot and label-free quantitative proteomics methods were used to study the mechanism. The results showed that the anti-fibrotic function of DHA was achieved through regulating extracellular matrix homeostasis including ECM synthesis and degradation. Our research demonstrated DHA regulated the energy metabolism of cardiac fibroblasts, especially fatty acid oxidation, and then affected the balance of ECM synthesis and degradation. It suggested that DHA supplementation could be considered an effective adjuvant therapy for cardiac fibrosis caused by hyperglycemia.

4D label-free quantitative proteomics analysis to screen potential drug targets of Jiangu Granules treatment for postmenopausal osteoporotic rats.

Background: Postmenopausal osteoporosis (PMOP) is a disease with a high prevalence in postmenopausal women and is characterized by an imbalance in bone metabolism, reduced bone mass, and increased risk of fracture due to estrogen deficiency. Jiangu granules (JG) is a compound prescription used in traditional Chinese medicine to treat PMOP. However, its definitive mechanism in PMOP is unclear. This study used a 4D label-free quantitative proteomics method to explore the potential therapeutic mechanism of JG in an ovariectomy (OVX) rats' model. Materials and methods: A rat model of PMOP was established by removing the ovaries bilaterally. Nine 3-month-old specific-pathogen-free female SD rats. The nine rats were randomly divided into 3 groups (n = 3 in each group): the sham-operated group (J), the ovariectomy group (NC), and the JG treatment (ZY) group. Proteins extracted from the bone tissue of the lumbar spine (L3, L4) of three groups of rats were analyzed by 4D label-free quantitative proteomics, and proteins differentially expressed after JG treatment and proteins differentially expressed after de-ovulation were intersected to identify proteins associated with the mechanism of PMOP by JG treatment. Result: There were 104 up-regulated and 153 down-regulated differentially expressed proteins (DEPs) in the J group vs. NC group, 107 up-regulated and 113 down-regulated DEPs in the J group vs. ZY group, and 15 up-regulated and 32 down-regulated DEPs in the NC group vs. ZY group. Six potential target proteins for JG regulation of osteoblast differentiation in OVX rats were identified by taking intersections of differential proteins in the J group vs. NC group and NC group vs. ZY group. Conclusion: JG may exert therapeutic effects by modulating the expression levels of target proteins associated with osteoblast differentiation to enhance osteoblast differentiation in OVX rats. These results further uncovered the target proteins and specific mechanisms of JG in treating PMOP, providing an experimental basis for the clinical application of JG in treating PMOP.

A preliminary report of exploration of the exosomal shuttle protein in marine invertebrate Chlamys farreri

Exosomes are extracellular vesicles secreted by diverse cell under normal or abnormal physiological conditions, which could carry a range of bioactive molecules and play significant roles in biological processes, such as intercellular communication and immune response. In the current study, a preliminary study was performed to investigate the exosomal shuttle protein in Chlamys farreri (designated as CfesPro) and to predict the potential function of exosomes in scallop innate immunity. The serum derived exosomes (designated as CfEVs) were obtained from lipopolysaccharide (LPS)-stimulated C. farreri and untreated ones. After confirmation and characterization by transmission electron microscopy (TEM), nano-HPLC-MS/MS spectrometry was performed on CfEVs using a label-free quantitative method. Totally 2481 exosomal shuttle proteins were identified in CfEVs proteomic data, which included many innate immune related proteins. GO and KOG functional annotation showed that CfesPro participated in cellular processes, metabolism reactions, signaling transductions, immune responses and so on. Moreover, 1421 proteins in CfesPro were enriched to 324 pathways by KEGG analysis, including several immune-related pathways, such as autophagy, apoptosis and lysosome pathway. Meanwhile, eight autophagy-related proteins were initially identified in CfesPro, indicating that CfEVs had a potential role with autophagy. All these findings showed that CfEVs were involved in C. farreri innate immune defenses. This research would enrich the protein database of marine exosomes and provide a basis for the exploration of immune defense systems in marine invertebrates.

Segmented MS/MS acquisition of a1 ion-based strategy for in-depth proteome quantitation

In-depth proteome quantitation is of great significance for understanding protein functions, advancing biological, medical, environmental and metabolic engineering research. Herein, benefiting from the high formation efficiencies and intensities of dimethyl-labeled a1 ions for accurate quantitation, we developed an in-depth a1 ion-based proteome quantitation method, named deep-APQ, by a sequential MS/MS acquisition of the high mass range for identification and the low mass range for a1 ion intensity extraction to increase quantitative protein number and sequence coverage. By the analysis of HeLa protein digests, our developed method showed deeper quantitative coverage than our previously reported a1 ion-based quantitation method without mass range segmentation and lower missing values than widely-used label-free quantitation method. It also exhibited excellent accuracy and precision within a 20-fold dynamic range. We further integrated a workflow combining the deep-APQ method with highly efficient sample preparation, high-pH and low-pH reversed-phase separation and high-field asymmetric waveform ion mobility spectrometry (FAIMS) to study E. coli proteome responses under the nutritional conditions of glucose and acetate. A total of 3447 proteins were quantified, representing 82% of protein-coding genes, with the average sequence coverage up to 40%, demonstrating the high coverage of quantitation results. We found that most of the quantified proteins related to chemotaxis were differentially expressed, including the low-abundance proteins such as tap, trg, aer, cheA and cheB, indicating that chemotaxis would play an important role for E. coli cell to survive from acetate toxicity. The above results demonstrated that the deep-APQ method is of great promising to achieve the deep-coverage proteome quantitation with high confidence.