Data-independent Acquisition Proteomics Research Articles

Proteo-transcriptomic profiles reveal key regulatory pathways and functions of LDHA in the ovulation of domestic chickens (Gallus gallus)

BackgroundIn poultry, the smooth transition of follicles from the preovulatory-to-postovulatory phase impacts egg production in hens and can benefit the poultry industry. However, the regulatory mechanism underlying follicular ovulation in avians is a complex biological process that remains unclear.ResultsCritical biochemical events involved in ovulation in domestic chickens (Gallus gallus) were evaluated by transcriptomics, proteomics, and in vitro assays. Comparative transcriptome analyses of the largest preovulatory follicle (F1) and postovulatory follicle (POF1) in continuous laying (CL) and intermittent laying (IL) chickens indicated the greatest difference between CL_F1 and IL_F1, with 950 differentially expressed genes (DEGs), and the smallest difference between CL_POF1 and IL_POF1, with 14 DEGs. Additionally, data-independent acquisition proteomics revealed 252 differentially abundant proteins between CL_F1 and IL_F1. Perivitelline membrane synthesis, steroid biosynthesis, lysosomes, and oxidative phosphorylation were identified as pivotal pathways contributing to ovulation regulation. In particular, the regulation of zona pellucida sperm-binding protein 3, plasminogen activator, cathepsin A, and lactate dehydrogenase A (LDHA) was shown to be essential for ovulation. Furthermore, the inhibition of LDHA decreased cell viability and promoted apoptosis of ovarian follicles in vitro.ConclusionsThis study reveals several important biochemical events involved in the process of ovulation, as well as crucial role of LDHA. These findings improve our understanding of ovulation and its regulatory mechanisms in avian species.

Bioinformation Analysis of Differential Expression Proteins in Different Processes of COVID-19.

COVID-19 is a highly infectious respiratory disease whose progression has been associated with multiple factors. From SARS-CoV-2 infection to death, biomarkers capable of predicting different disease processes are needed to help us further understand the molecular progression of COVID-19 disease. The aim is to find differentially expressed proteins that are associated with the progression of COVID-19 disease or can be potential biomarkers, and to provide a reference for further understanding of the molecular mechanisms of COVID-19 occurrence, progression, and treatment. Data-independent Acquisition (DIA) proteomics to obtain sample protein expression data, using R language screening differentially expressed proteins. Gene Ontology and Kyoto Encyclopedia for Genes and Genomes analysis was performed on differential proteins and protein-protein interaction (PPI) network was constructed to screen key proteins. A total of 47 differentially expressed proteins were obtained from COVID-19 incubation patients and healthy population (L/H), mainly enriched in platelet-related functions, and complement and coagulation cascade reaction pathways, such as platelet degranulation and platelet aggregation. A total of 42 differential proteins were obtained in clinical and latent phase patients (C/L), also mainly enriched in platelet-related functions and in complement and coagulation cascade reactions, platelet activation pathways. A total of 10 differential proteins were screened in recovery and clinical phase patients (R/C), mostly immune-related proteins. The differentially expressed proteins in different stages of COVID-19 are mostly closely associated with coagulation, and key differential proteins, such as FGA, FGB, FGG, ACTB, PFN1, VCL, SERPZNCL, APOC3, LTF, and DEFA1, have the potential to be used as early diagnostic markers.

SLC34A2 Targets in Calcium/Phosphorus Homeostasis of Mammary Gland and Involvement in Development of Clinical Mastitis in Dairy Cows.

The type II Na/Pi co-transporter (NaPi2b), encoded by the solute carrier (SLC) transporter 34A2 (SLC34A2), is responsible for calcium (Ca) and phosphorus (P) homeostasis. Unbalanced Ca/P metabolism induces mastitis in dairy cows. However, the specific role of SLC34A2 in regulating this imbalance in Holstein cows with clinical mastitis (CM) remains unclear. The aim of this study was to investigate the role of SLC34A2 and identify differentially expressed proteins (DEPs) that interact with SLC34A2 and are associated with Ca/P metabolism in dairy cows with CM. Immunohistochemical and immunofluorescence staining results showed that SLC34A2 was located primarily in the mammary epithelial cells of the mammary alveoli in both the control (healthy cows, Con/C) and CM groups. Compared to the Con/C group, the relative expression of the SLC34A2 gene and protein were significantly downregulated in the CM group. We identified 12 important DEPs included in 11 GO terms and two pathways interacting with SLC34A2 using data-independent acquisition proteomics. The PPI (protein-and-protein interaction) network results suggested that these DEPs were associated with ion metabolism and homeostasis, especially SLC34A2. These results demonstrate that SLC34A2 downregulation is negatively correlated with the occurrence and development of CM in Holstein cows, providing a basis for exploring the function and regulatory mechanism of SLC34A2 in Ca/P metabolism and homeostasis in Holstein cows with CM.

Proteomic study of left ventricle and cortex in rats after myocardial infarction

Myocardial infarction (MI) induces neuroinflammation indirectly, chronic neuroinflammation may cause neurodegenerative diseases. Changes in the proteomics of heart and brain tissue after MI may shed new light on the mechanisms involved in neuroinflammation. This study explored brain and heart protein changes after MI with a data-independent acquisition (DIA) mode proteomics approach. Permanent ligation of the left anterior descending coronary artery (LAD) was performed in the heart of rats, and the immunofluorescence of microglia in the brain cortex was performed at 1d, 3d, 5d, and 7d after MI to detect the neuroinflammation. Then proteomics was accomplished to obtain the vital proteins in the heart and brain post-MI. The results show that the number of microglia was significantly increased in the Model-1d group, the Model-3d group, the Model-5d group, and the Model-7d group compared to the Sham group. Various proteins were obtained through DIA proteomics. Linking to key targets of brain disease, 14 proteins were obtained in the brain cortex. Among them, elongation of very long chain fatty acids protein 5 (ELOVL5) and ATP-binding cassette subfamily G member 4 (ABCG4) were verified through western blotting (WB). The results of WB were consistent with the proteomics results. Therefore, these proteins may be related to the pathogenesis of neuroinflammation after MI.

Integrative proteomics and metabolomics data analysis exploring the mechanism of brain injury after cardiac surgery in chronic stress rats

ObjectivePreoperative chronic stress (CS) is associated with postoperative brain injury in patients undergoing open heart cardiac surgery. This research is to explore the potential molecular biological mechanisms of brain damage following cardiac surgery in preoperative CS rats by the analyses combining proteomics and metabolomics.MethodsWe constructed the chronic unpredictable stress (CUS) and cardiac surgery models in adult rats. We proved the brain injury in CUS cardiac surgery rats by Hematoxylin–Eosin (H&E) staining, followed by separating the hippocampal tissue and investigating the potential mechanisms of brain injury by the methods of data-independent acquisition proteomics and untargeted metabolomics.ResultsThe signaling pathways of glycoproteins and metabolism of amino acids were the main possible mechanisms of brain injury in CUS rats following cardiac surgery according to the proteomics and metabolomics. In addition, the pathways of animo acids metabolism such as the pathways of lysine degradation and β-alanine metabolism may be the main mechanism of cardiac surgery related brain injury in preoperative CUS rats.ConclusionsThe pathways of animo acids metabolism such as lysine degradation and β-alanine metabolism may be the potential mechanisms of brain injury in CUS rats following cardiac surgery. We should focus on the varieties of bioproteins and metabolites in these pathways, and related changes in other signaling pathways induced by the two pathways.

Synthetic Circular RNA for microRNA-1269a Suppresses Tumor Progression in Oral Squamous Cell Carcinoma.

microRNAs (miRs) function in cancer progression as post-transcriptional regulators. We previously reported that endogenous circular RNAs (circRNAs) function as efficient miR sponges and could act as novel gene regulators in oral squamous cell carcinoma (OSCC). In this study, we carried out cellular and luciferase reporter assays to examine competitive inhibition of miR-1269a, which is upregulated expression in several cancers, by circRNA-1269a, a synthetic circRNA that contains miR-1269a binding sequences. We also used data-independent acquisition (DIA) proteomics and in silico analyses to determine how circRNA-1269a treatment affects molecules downstream of miR-1269a. First, we confirmed the circularization of the linear miR-1269a binding site sequence using RT-PCR with divergent/convergent primers and direct sequencing of the head-to-tail circRNA junction point. In luciferase reporter and cellular functional assays, circRNA-1269a significantly reduced miR-1269a function, leading to a significant decrease in cell proliferation and migration. DIA proteomics and gene set enrichment analysis of OSCC cells treated with circRNA-1269a indicated high differential expression for 284 proteins that were mainly enriched in apoptosis pathways. In particular, phospholipase C gamma 2 (PLCG2), which is related to OSCC clinical stage and overall survival, was affected by the circRNA-1269a/miR-1269a axis. Taken together, synthetic circRNA-1269a inhibits tumor progression via miR-1269a and its downstream targets, indicating that artificial circRNAs could represent an effective OSCC therapeutic.

Combining FAIMS based glycoproteomics and DIA proteomics reveals widespread proteome alterations in response to glycosylation occupancy changes in Neisseria gonorrhoeae.

Protein glycosylation is increasingly recognized as a common protein modification across bacterial species. Within the Neisseria genus O-linked protein glycosylation is conserved yet closely related Neisseria species express O-oligosaccharyltransferases (PglOs) with distinct targeting activities. Within this work, we explore the targeting capacity of different PglOs using Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) fractionation and Data-Independent Acquisition (DIA) to allow the characterization of the impact of changes in glycosylation on the proteome of Neisseria gonorrhoeae. We demonstrate FAIMS expands the known glycoproteome of wild type N. gonorrhoeae MS11 and enables differences in glycosylation to be assessed across strains expressing different pglO allelic chimeras with unique substrate targeting activities. Combining glycoproteomic insights with DIA proteomics, we demonstrate that alterations within pglO alleles have widespread impacts on the proteome of N. gonorrhoeae. Examination of peptides known to be targeted by glycosylation using DIA analysis supports alterations in glycosylation occupancy occurs independently of changes in protein levels and that the occupancy of glycosylation is generally low on most glycoproteins. This work thus expands our understanding of the N. gonorrhoeae glycoproteome and the roles that pglO allelic variation may play in governing genus-level protein glycosylation.

Data-Independent Acquisition Proteomics and N-Terminomics Methods Reveal Alterations in Mitochondrial Function and Metabolism in Ischemic-Reperfused Hearts.

Myocardial ischemia-reperfusion (IR) (stunning) injury triggers changes in the proteome and degradome of the heart. Here, we utilize quantitative proteomics and comprehensive degradomics to investigate the molecular mechanisms of IR injury in isolated rat hearts. The control group underwent aerobic perfusion, while the IR injury group underwent 20 min of ischemia and 30 min of reperfusion to induce a stunning injury. As MMP-2 activation has been shown to contribute to myocardial injury, hearts also underwent IR injury with ARP-100, an MMP-2-preferring inhibitor, to dissect the contribution of MMP-2 to IR injury. Using data-independent acquisition (DIA) and mass spectroscopy, we quantified 4468 proteins in ventricular extracts, whereby 447 proteins showed significant alterations among the three groups. We then used subtiligase-mediated N-terminomic labeling to identify more than a hundred specific cleavage sites. Among these protease substrates, 15 were identified following IR injury. We identified alterations in numerous proteins involved in mitochondrial function and metabolism following IR injury. Our findings provide valuable insights into the biochemical mechanisms of myocardial IR injury, suggesting alterations in reactive oxygen/nitrogen species handling and generation, fatty acid metabolism, mitochondrial function and metabolism, and cardiomyocyte contraction.

Exploring molecular mechanisms of intra-articular changes in osteonecrosis of femoral head using DIA proteomics and bioinformatics.

This study is aimed to delve into the crucial proteins associated with hormonal osteonecrosis of the femoral head (ONFH) and its intra-articular lesions through data-independent acquisition (DIA) proteomics and bioinformatics analysis. We randomly selected samples from eligible ONFH patients and collected samples from the necrotic area of the femoral head and load-bearing cartilage. The control group comprised specimens from the same location in patients with femoral neck fractures. With DIA proteomics, we quantitatively and qualitatively tested both groups and analyzed the differentially expressed proteins (DEPs) between groups. Additionally, we enriched the analysis of DEP functions using gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways and verified the key proteins in ONFH through Western blot. Proteomics experiment uncovered 937 common DEPs (422 upregulated and 515 downregulated) between the two groups. These DEPs mainly participate in biological processes such as hidden attributes, catalytic activity, molecular function regulators, and structural molecule activity, and in pathways such as starch and sucrose metabolism, ECM-receptor interaction, PI3K-Akt signaling, complement and coagulation cascades, IL-17 signaling, phagosome, transcriptional misregulation in cancers, and focal adhesion. Through protein-protein interaction network target gene analysis and Western blot validation, we identified C3, MMP9, APOE, MPO, LCN2, ELANE, HPX, LTF, and THBS1 as key proteins in ONFH. With DIA proteomics and bioinformatics analysis, this study reveals the molecular mechanisms of intra-articular lesions in ONFH. A correlation in the necrotic area and load-bearing cartilage of ONFH at ARCO stages IIIB-IV as well as potential key regulatory proteins was identified. These findings will help more deeply understand the pathogenesis of ONFH and may provide important clues for seeking more effective treatment strategies.

Acquisition and Analysis of DIA-Based Proteomic Data: A Comprehensive Survey in 2023

Data-independent acquisition (DIA) mass spectrometry (MS) has emerged as a powerful technology for high-throughput, accurate, and reproducible quantitative proteomics. This review provides a comprehensive overview of recent advances in both the experimental and computational methods for DIA proteomics, from data acquisition schemes to analysis strategies and software tools. DIA acquisition schemes are categorized based on the design of precursor isolation windows, highlighting wide-window, overlapping-window, narrow-window, scanning quadrupole-based, and parallel accumulation-serial fragmentation–enhanced DIA methods. For DIA data analysis, major strategies are classified into spectrum reconstruction, sequence-based search, library-based search, de novo sequencing, and sequencing-independent approaches. A wide array of software tools implementing these strategies are reviewed, with details on their overall workflows and scoring approaches at different steps. The generation and optimization of spectral libraries, which are critical resources for DIA analysis, are also discussed. Publicly available benchmark datasets covering global proteomics and phosphoproteomics are summarized to facilitate performance evaluation of various software tools and analysis workflows. Continued advances and synergistic developments of versatile components in DIA workflows are expected to further enhance the power of DIA-based proteomics.

DIA-based quantitative proteomic analysis of porcine endometrium in the peri-implantation phase

The 12th day of gestation is a critical period for embryo loss and the beginning of imminent implantation in sows. Data independent acquisition (DIA) technology is one of the high-throughput, high-resolution and reproducible proteomics technologies for large-scale digital qualitative and quantitative research. The aim of this study was to identify and characterize the protein abundance landscape of Yorkshire pig endometrium on the 12th day of pregnancy (P12) and estrous cycle (C12) using DIA proteomics. A total of 1251 differentially abundant proteins (DAPs) were identified, of which 882 were up-regulated and 369 were down-regulated at P12. Functional enrichment analysis showed that the identified proteins were related to metabolism, biosynthesis and signaling pathways. Three proteins were selected for Western blot (WB) validation and the results were consistent with the DIA data. Further combined with transcriptome data, fibrinogen like 2 (FGL2) and S100 calcium binding protein A8 (S100A8) were verified to be highly abundant in the P12 endometrial epithelium. In summary, there were significantly different abundance of proteome profiles in C12 and P12 endometrium, suggesting that DAPs are associated with changes in endometrial receptivity, which laid the foundation for further research on related regulatory mechanisms. SignificanceThe 12th day of gestation is an important point in the peri-implantation period of pigs, when the endometrium presents a receptive state under the stimulation of estrogen. DIA proteomics technology is an emerging protein identification technology in recent years, which can obtain protein information through comprehensive and unbiased scanning. In this study, DIA technology was used to characterize endometrial proteins in pigs during the peri-implantation period. The results showed that higher protein abundance was detected using the DIA technique, and some of these DAPs may be involved in regulating embryo implantation. This study will help to better reveal the related proteins involved in embryo implantation, and lay a foundation for further research on the mechanism of endometrial regulation of embryo implantation. Significance of the studyThe 12th day of gestation is an important point in the peri-implantation period of pigs, when the endometrium presents a receptive state under the stimulation of estrogen. DIA proteomics technology is an emerging protein identification technology in recent years, which can obtain protein information through comprehensive and unbiased scanning. In this study, DIA technology was used to characterize endometrial proteins in pigs during the peri-implantation period. The results showed that higher protein abundance was detected using the DIA technique, and some of these DAPs may be involved in regulating embryo implantation. This study will help to better reveal the related proteins involved in embryo implantation, and lay a foundation for further research on the mechanism of endometrial regulation of embryo implantation.

Analysis of the Differentially Expressed Proteins in Donkey Milk in Different Lactation Stages.

Proteins in donkey milk (DM) have special biological activities. However, the bioactive proteins and their expression regulation in donkey milk are still unclear. Thus, the differentially expressed proteins (DEPs) in DM in different lactation stages were first investigated by data-independent acquisition (DIA) proteomics. A total of 805 proteins were characterized in DM. The composition and content of milk proteins varied with the lactation stage. A total of 445 candidate DEPs related to biological processes and molecular functions were identified between mature milk and colostrum. The 219 down-regulated DEPs were mainly related to complement and coagulation cascades, staphylococcus aureus infection, systemic lupus erythematosus, prion diseases, AGE-RAGE signaling pathways in diabetic complications, and pertussis. The 226 up-regulated DEPs were mainly involved in metabolic pathways related to nutrient (fat, carbohydrate, nucleic acid, and vitamin) metabolism. Some other DEPs in milk from the lactation period of 30 to 180 days also had activities such as promoting cell proliferation, promoting antioxidant, immunoregulation, anti-inflammatory, and antibacterial effects, and enhancing skin moisture. DM can be used as a nutritional substitute for infants, as well as for cosmetic and medical purposes. Our results provide important insights for understanding the bioactive protein differences in DM in different lactation stages.

Data-independent acquisition proteomics of cerebrospinal fluid implicates endoplasmic reticulum and inflammatory mechanisms in amyotrophic lateral sclerosis.

While unbiased proteomics of human cerebrospinal fluid (CSF) has been used successfully to identify biomarkers of amyotrophic lateral sclerosis (ALS), high-abundance proteins mask the presence of lower abundance proteins that may have diagnostic and prognostic value. However, developments in mass spectrometry (MS) proteomic data acquisition methods offer improved protein depth. In this study, MS with library-free data-independent acquisition (DIA) was used to compare the CSF proteome of people with ALS (n = 40), healthy (n = 15) and disease (n = 8) controls. Quantified protein groups were subsequently correlated with clinical variables. Univariate analysis identified 7 proteins, all significantly upregulated in ALS versus healthy controls, and 9 with altered abundance in ALS versus disease controls (FDR < 0.1). Elevated chitotriosidase-1 (CHIT1) was common to both comparisons and was proportional to ALS disability progression rate (Pearson r = 0.41, FDR-adjusted p = 0.035) but not overall survival. Ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCHL1; upregulated in ALS versus healthy controls) was proportional to disability progression rate (Pearson r = 0.53, FDR-adjusted p = 0.003) and survival (Kaplan Meier log-rank p = 0.013) but not independently in multivariate proportional hazards models. Weighted correlation network analysis was used to identify functionally relevant modules of proteins. One module, enriched for inflammatory functions, was associated with age at symptom onset (Pearson r = 0.58, FDR-adjusted p = 0.005) and survival (Hazard Ratio = 1.78, FDR = 0.065), and a second module, enriched for endoplasmic reticulum proteins, was negatively correlated with disability progression rate (r = -0.42, FDR-adjusted p = 0.109). DIA acquisition methodology therefore strengthened the biomarker candidacy of CHIT1 and UCHL1 in ALS, while additionally highlighted inflammatory and endoplasmic reticulum proteins as novel sources of prognostic biomarkers.

A pilot study of S100A4, S100A8/A9, and S100A12 in dilated cardiomyopathy: novel biomarkers for diagnosis or prognosis?

Circulating biomarkers can provide important information for the diagnosis and prognosis of dilated cardiomyopathy (DCM). We explored novel biomarkers for the diagnosis and prognosis of DCM to improve clinical decision-making. A total of 238 DCM patients and 65 control were consecutively enrolled at Zhongshan Hospital between January 2017 and January 2019. In the screening set, four DCM patients and four controls underwent measurements of serum proteomic analysis. Seventy-six differentially expressed circulating proteins were screened by data-independent acquisition proteomics, and three of these proteins (S100A4, S100A8/A9, and S100A12) were validated by multiple-reaction monitoring-mass spectrometry. In the validation set, subsequently, a total of 234 DCM patients and 61 control subjects were evaluated by enzyme-linked immunosorbent assay. Circulating S100A4, S100A8/A9, and S100A12 were significantly increased in DCM patients (P<0.001). These three proteins were significant positively correlated with other parameters, such as Lg (NT-proBNP), IL-1β, TGF-β, CRP, left ventricular end-diastolic diameter, and left ventricular end-systolic diameter, whereas they were negatively correlated with left ventricular ejection fraction, respectively (P<0.05). The receiver operator characteristic curve showed the combination of S100A4, S100A8/A9, and S100A12 [area under curve (AUC) 0.88, 95% confidence interval (CI) 0.84-0.93] was better than single S100A4 (AUC 0.74, 95% CI 0.68-0.81), S100A8/A9 (AUC 0.82, 95% CI 0.77-0.88), or S100A12 (AUC 0.80, 95% CI 0.72-0.88) in the diagnosis of DCM (P<0.01). After a median follow-up period of 33.5months, 110 patients (47.01%) experienced major adverse cardiac events (MACEs), including 46 who had cardiac deaths and 64 who had heart failure rehospitalizations. Kaplan-Meier analysis indicated that the DCM patients with ≥75th percentile level of S100A4 had a significantly higher incidence of MACEs than those with <75th percentile level of S100A4 (61.40% vs. 42.37%, P<0.05). There were no significant differences of MACE rate among DCM patients with different concentrations of S100A8/A9 and S100A12 (P>0.05). Cox proportional hazards regression analysis revealed that S100A4 [≥75th percentile vs. <75th percentile: hazard ratio (HR) 1.65; 95% CI 1.11-2.45] remained significant independent predictors for MACEs (P<0.05); however, S100A8/A9 and S100A12 were not independent factors for predicting MACE (P≥0.05). S100A4, S100A8/A9, and S100A12 may be additional diagnostic tools for human DCM recognition, and the combination of these three indicators helped to improve the accuracy of a single index to diagnose DCM. Additionally, S100A4 was identified as a significant predictor of prognosis in patients with DCM.

Plasma proteomics-based biomarkers for predicting response to mesenchymal stem cell therapy in severe COVID-19

BackgroundThe objective of this study was to identify potential biomarkers for predicting response to MSC therapy by pre-MSC treatment plasma proteomic profile in severe COVID-19 in order to optimize treatment choice.MethodsA total of 58 patients selected from our previous RCT cohort were enrolled in this study. MSC responders (n = 35) were defined as whose resolution of lung consolidation ≥ 51.99% (the median value for resolution of lung consolidation) from pre-MSC to 28 days post-MSC treatment, while non-responders (n = 23) were defined as whose resolution of lung consolidation < 51.99%. Plasma before MSC treatment was detected using data-independent acquisition (DIA) proteomics. Multivariate logistic regression analysis was used to identify pre-MSC treatment plasma proteomic biomarkers that might distinguish between responders and non-responders to MSC therapy.ResultsIn total, 1101 proteins were identified in plasma. Compared with the non-responders, the responders had three upregulated proteins (CSPG2, CTRB1, and OSCAR) and 10 downregulated proteins (ANXA1, AGRG6, CAPG, DDX55, KV133, LEG10, OXSR1, PICAL, PTGDS, and S100A8) in plasma before MSC treatment. Using logistic regression model, lower levels of DDX55, AGRG6, PICAL, and ANXA1 and higher levels of CTRB1 pre-MSC treatment were predictors of responders to MSC therapy, with AUC of the ROC at 0.910 (95% CI 0.818–1.000) in the training set. In the validation set, AUC of the ROC was 0.767 (95% CI 0.459–1.000).ConclusionsThe responsiveness to MSC therapy appears to depend on baseline level of DDX55, AGRG6, PICAL, CTRB1, and ANXA1. Clinicians should take these factors into consideration when making decision to initiate MSC therapy in patients with severe COVID-19.

Identification of plasma proteomic signatures associated with the progression of cardia gastric cancer and precancerous lesions

ObjectiveConsidering that there are no effective biomarkers for the screening of cardia gastric cancer (CGC), we developed a noninvasive diagnostic approach, employing data-independent acquisition (DIA) proteomics to identify candidate protein markers. MethodsPlasma samples were obtained from 40 subjects, 10 each for CGC, cardia high-grade dysplasia (CHGD), cardia low-grade dysplasia (CLGD), and healthy controls. Proteomic profiles were obtained through liquid chromatography-mass spectrometry (LC-MS/MS-based DIA proteomics. Candidate plasma proteins were identified by weighted gene co-expression network analysis (WGCNA) combined with machine learning and further validated by the Human Protein Atlas (HPA) database. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of the biomarker panel. ResultsThere was a clear distinction in proteomic features among CGC, CHGD, CLGD, and the healthy controls. According to the WGCNA, we found 42 positively associated and 164 inversely associated proteins related to CGC progression and demonstrated several canonical cancer-associated pathways. Combined with the results from random forests, LASSO regression, and immunohistochemical results from the HPA database, we identified three candidate proteins (GSTP1, CSRP1, and LY6G6F) that could together distinguish CLGD (AUC = 0.91), CHGD (AUC = 0.99) and CGC (AUC = 0.98) from healthy controls with excellent accuracy. ConclusionsThe panel of protein biomarkers showed promising diagnostic potential for CGC and precancerous lesions. Further validation and a larger-scale study are warranted to assess its potential clinical applications, suggesting a potential avenue for CGC prevention in the future.

Substantial downregulation of mitochondrial and peroxisomal proteins during acute kidney injury revealed by data-independent acquisition proteomics.

Acute kidney injury (AKI) manifests as a major health concern, particularly for the elderly. Understanding AKI-related proteome changes is critical for prevention and development of novel therapeutics to recover kidney function and to mitigate the susceptibility for recurrent AKI or development of chronic kidney disease. In this study, mouse kidneys were subjected to ischemia-reperfusion injury, and the contralateral kidneys remained uninjured to enable comparison and assess injury-induced changes in the kidney proteome. A ZenoTOF 7600 mass spectrometer was optimized for data-independent acquisition (DIA) to achieve comprehensive protein identification and quantification. Short microflow gradients and the generation of a deep kidney-specific spectral library allowed for high-throughput, comprehensive protein quantification. Upon AKI, the kidney proteome was completely remodeled, and over half of the 3945 quantified protein groups changed significantly. Downregulated proteins in the injured kidney were involved in energy production, including numerous peroxisomal matrix proteins that function in fatty acid oxidation, such as ACOX1, CAT, EHHADH, ACOT4, ACOT8, and Scp2. Injured kidneys exhibited severely damaged tissues and injury markers. The comprehensive and sensitive kidney-specific DIA-MS assays feature high-throughput analytical capabilities to achieve deep coverage of the kidney proteome, and will serve as useful tools for developing novel therapeutics to remediate kidney function.

Quantitative Analysis of mRNA and Protein Expression Levels of Aldo-Keto Reductase and Short-Chain Dehydrogenase/Reductase Isoforms in the Human Intestine.

Enzymes catalyzing the reduction reaction of xenobiotics are mainly members of the aldo-keto reductase (AKR) and short-chain dehydrogenase/reductase (SDR) superfamilies. The intestine, together with the liver, is responsible for first-pass effects and is an organ that determines the bioavailability of orally administered drugs. In this study, we evaluated the mRNA and protein expression levels of 12 AKR isoforms (AKR1A1, AKR1B1, AKR1B10, AKR1B15, AKR1C1, AKR1C2, AKR1C3, AKR1C4, AKR1D1, AKR1E2, AKR7A2, and AKR7A3) and 7 SDR isoforms (CBR1, CBR3, CBR4, DCXR, DHRS4, HSD11B1, and HSD17B12) in each region of the human intestine using next-generation sequencing and data-independent acquisition proteomics. At both the mRNA and protein levels, most AKR isoforms were highly expressed in the upper regions of the intestine, namely the duodenum and jejunum, and then declined toward the rectum. Among the members in the SDR superfamily, CBR1 and DHRS4 were highly expressed in the upper regions, whereas the expression levels of the other isoforms were almost uniform in all regions. Significant positive correlations between mRNA and protein levels were observed in AKR1A1, AKR1B1, AKR1B10, AKR1C3, AKR7A2, AKR7A3, CBR1, and CBR3. The mRNA level of AKR1B10 was highest, followed by AKR7A3 and CBR1, each accounting for more than 10% of the sum of all AKR and SDR levels in the small intestine. This expression profile in the human intestine was greatly different from that in the human liver, where AKR1C isoforms are predominantly expressed. SIGNIFICANCE STATEMENT: In this study comprehensively determined the mRNA and protein expression profiles of aldo-keto reductase (AKR) and short-chain dehydrogenase/reductase isoforms involved in xenobiotic metabolism in the human intestine and found that most of them are highly expressed in the upper region, where AKR1B10, AKR7A3, and CBR1 are predominantly expressed. Since the intestine is significantly involved in the metabolism of orally administered drugs, the information provided here is valuable for pharmacokinetic studies in drug development.

Identification of a Non-Invasive Urinary Exosomal Biomarker for Diabetic Nephropathy Using Data-Independent Acquisition Proteomics.

Diabetic nephropathy (DN), as the one of most common complications of diabetes, is generally diagnosed based on a longstanding duration, albuminuria, and decreased kidney function. Some patients with the comorbidities of diabetes and other primary renal diseases have similar clinical features to DN, which is defined as non-diabetic renal disease (NDRD). It is necessary to distinguish between DN and NDRD, considering they differ in their pathological characteristics, treatment regimes, and prognosis. Renal biopsy provides a gold standard; however, it is difficult for this to be conducted in all patients. Therefore, it is necessary to discover non-invasive biomarkers that can distinguish between DN and NDRD. In this research, the urinary exosomes were isolated from the midstream morning urine based on ultracentrifugation combined with 0.22 μm membrane filtration. Data-independent acquisition-based quantitative proteomics were used to define the proteome profile of urinary exosomes from DN (n = 12) and NDRD (n = 15) patients diagnosed with renal biopsy and Type 2 diabetes mellitus (T2DM) patients without renal damage (n = 9), as well as healthy people (n = 12). In each sample, 3372 ± 722.1 proteins were identified on average. We isolated 371 urinary exosome proteins that were significantly and differentially expressed between DN and NDRD patients, and bioinformatic analysis revealed them to be mainly enriched in the immune and metabolic pathways. The use of least absolute shrinkage and selection operator (LASSO) logistic regression further identified phytanoyl-CoA dioxygenase domain containing 1 (PHYHD1) as the differential diagnostic biomarker, the efficacy of which was verified with another cohort including eight DN patients, five NDRD patients, seven T2DM patients, and nine healthy people. Additionally, a concentration above 1.203 μg/L was established for DN based on the ELISA method. Furthermore, of the 19 significantly different expressed urinary exosome proteins selected by using the protein-protein interaction network and LASSO logistic regression, 13 of them were significantly related to clinical indicators that could reflect the level of renal function and hyperglycemic management.

Genome-Wide Association Study for the Genetic Determinants of Thiopurine Methyltransferase Protein Expression in Human Livers and Racial Differences.

Polymorphisms in the Thiopurine S-Methyltransferase (TPMT) gene are associated with decreased TPMT activity, but little is known about their impact on TPMT protein expression in the liver. This project is to conduct a genome-wide association study (GWAS) to identify single nucleotide polymorphisms (SNPs) associated with altered TPMT protein expression in human livers and to determine if demographics affect hepatic TPMT protein expression. Human liver samples (n = 287) were genotyped using a whole genome genotyping panel and quantified for TPMT protein expression using a Data-Independent Acquisition proteomics approach. Thirty-one SNPs were found to be associated with differential expression of TPMT protein in the human livers. Subsequent analysis, conditioning on rs1142345, a SNP associated with the TPMT*3A and TPMT*3C alleles, showed no additional independent signals. Mean TPMT expression is significantly higher in wildtype donors compared to those carrying the known TPMT alleles, including TPMT*3A, TPMT*3C, and TPMT*24 (0.107 ± 0.028 vs. 0.052 ± 0.014pmol/mg total protein, P = 2.2 × 10-16). After removing samples carrying the known TPMT variants, European ancestry donors exhibited significantly higher expression than African ancestry donors (0.109 ± 0.026 vs. 0.090 ± 0.041pmol/mg total protein, P = 0.020). The GWAS identified 31 SNPs associated with TPMT protein expression in human livers. Hepatic TPMT protein expression was significantly lower in subjects carrying the TPMT*3A, TPMT*3C, and TPMT*24 alleles compared to non-carriers. European ancestry was associated with significantly higher hepatic TPMT protein expression than African ancestry, independent of known TPMT variants.