Identification of serum biomarkers to predict pemetrexed/platinum chemotherapy efficacy for advanced lung adenocarcinoma patients by data-independent acquisition (DIA) mass spectrometry analysis with parallel reaction monitoring (PRM) verification

Comparative proteomics reveals that fatty acid metabolism is involved in myocardial adaptation to chronic hypoxic injury

Congenital heart disease (CHD) is the most serious form of heart disease, and chronic hypoxia is the basic physiological process underlying CHD. Some patients with CHD do not undergo surgery, and thus, they remain susceptible to chronic hypoxia, suggesting that some protective mechanism might exist in CHD patients. However, the mechanism underlying myocardial adaptation to chronic hypoxia remains unclear. Proteomics was used to identify the differentially expressed proteins in cardiomyocytes cultured under hypoxia for different durations. Western blotting assays were used to verify protein expression. A Real-Time Cell Analyzer (RTCA) was used to analyze cell growth. In this study, 3881 proteins were identified by proteomics. Subsequent bioinformatics analysis revealed that proteins were enriched in regulating oxidoreductase activity. Functional similarity cluster analyses showed that chronic hypoxia resulted in proteins enrichment in the mitochondrial metabolic pathway. Further KEGG analyses found that the proteins involved in fatty acid metabolism, the TCA cycle and oxidative phosphorylation were markedly upregulated. Moreover, knockdown of CPT1A or ECI1, which is critical for fatty acid degradation, suppressed the growth of cardiomyocytes under chronic hypoxia. The results of our study revealed that chronic hypoxia activates fatty acid metabolism to maintain the growth of cardiomyocytes.

Phosphoproteomic analysis of APP/PS1 mice of Alzheimer's disease by DIA based mass spectrometry analysis with PRM verification

Traditional Chinese medicine has been utilized in China for approximately thousands of years in clinical settings to prevent Alzheimer's disease (AD) and enhance memory, despite the lack of a systematic exploration of its biological underpinnings. Exciting research has corroborated the beneficial effects of tetrahydroxy stilbene glycoside (TSG), an extract derived from Polygonum multiflorum, in delaying learning and memory impairment in a model that mimics AD. Therefore, the primary objective of this study is to investigate the major function of TSG upon protein regulation in AD. Herein, a novel approach, encompassing data independent acquisition (DIA), DIA phosphorylated proteomics, and parallel reaction monitoring (PRM), was utilized to integrate quantitative proteomic data collected from APP/PS1 mouse model exhibiting toxic intracellular aggregation of Aβ. Initially, we deliberated upon both single and multi-dimensional data pertaining to AD model mice. Furthermore, we authenticated disparities in protein phosphorylation quantity and expression, phosphorylation function, and ultimately phosphorylation kinase analysis. In order to validate the results, we utilized PRM ion monitoring technology to identify potential protein or peptide biomarkers. In the mixed samples, targeted detection of 50 target proteins revealed that 26 to 33 target proteins were stably detected by PRM. In summary, our findings provide new candidates for AD biomarker, which have been identified and validated through protein researches conducted on mouse brains. This offers a wealth of potential resources for extensive biomarker validation in neurodegenerative diseases. SIGNIFICANCE: DIA phosphorylated proteomics technique was used to detect and analyze phosphorylated proteins in brain tissues of mice with AD. Data were analyzed by various bioinformatics tools to explore the phosphorylation events and characterize them related to TSG. The results of DIA were further verified by PRM. Besides, we mapped the major metabolite classes emerging from the analyses to key biological pathways implicated in AD to understand the potential roles of the molecules and the interactions in triggering symptom onset and progression of AD. Meanwhile, we clarified that in the context of AD onset and TSG intervention, the changes in proteins, protein phosphorylation, phosphorylation kinases, and the internal connections.

Reveal the kernel dehydration mechanisms in maize based on proteomic and metabolomic analysis

BACKGROUND

Kernel dehydration is an important factor for the mechanized harvest in maize. Kernel moisture content (KMC) and kernel dehydration rate (KDR) are important indicators for kernel dehydration. Although quantitative trait loci and genes related to KMC have been identified, where most of them only focus on the KMC at harvest, these are still far from sufficient to explain all genetic variations, and the relevant regulatory mechanisms are still unclear. In this study, we tried to reveal the key proteins and metabolites related to kernel dehydration in proteome and metabolome levels. Moreover, we preliminarily explored the relevant metabolic pathways that affect kernel dehydration combined proteome and metabolome. These results could accelerate the development of further mechanized maize technologies.

RESULTS

In this study, three maize inbred lines (KB182, KB207, and KB020) with different KMC and KDR were subjected to proteomic analysis 35, 42, and 49 days after pollination (DAP). In total, 8,358 proteins were quantified, and 2,779 of them were differentially expressed proteins in different inbred lines or at different stages. By comparative analysis, K-means cluster, and weighted gene co-expression network analysis based on the proteome data, some important proteins were identified, which are involved in carbohydrate metabolism, stress and defense response, lipid metabolism, and seed development. Through metabolomics analysis of KB182 and KB020 kernels at 42 DAP, 18 significantly different metabolites, including glucose, fructose, proline, and glycerol, were identified.

CONCLUSIONS

In sum, we inferred that kernel dehydration could be regulated through carbohydrate metabolism, antioxidant systems, and late embryogenesis abundant protein and heat shock protein expression, all of which were considered as important regulatory factors during kernel dehydration process. These results shed light on kernel dehydration and provide new insights into developing cultivars with low moisture content.

Proteomics-driven noninvasive screening of circulating serum protein panels for the early diagnosis of hepatocellular carcinoma

Early diagnosis of hepatocellular carcinoma (HCC) lacks highly sensitive and specific protein biomarkers. Here, we describe a staged mass spectrometry (MS)-based discovery-verification-validation proteomics workflow to explore serum proteomic biomarkers for HCC early diagnosis in 1002 individuals. Machine learning model determined as P4 panel (HABP2, CD163, AFP and PIVKA-II) clearly distinguish HCC from liver cirrhosis (LC, AUC 0.979, sensitivity 0.925, specificity 0.915) and healthy individuals (HC, AUC 0.992, sensitivity 0.975, specificity 1.000) in an independent validation cohort, outperforming existing clinical prediction strategies. Furthermore, the P4 panel can accurately predict LC to HCC conversion (AUC 0.890, sensitivity 0.909, specificity 0.877) with predicting HCC at a median of 11.4 months prior to imaging in prospective external validation cohorts (No.: Keshen 2018_005_02 and NCT03588442). These results suggest that proteomics-driven serum biomarker discovery provides a valuable reference for the liquid biopsy, and has great potential to improve early diagnosis of HCC.

4D DIA-PRM proteomic study identifying modulated pathways and biomarkers associated with pelvic organ prolapse

Pelvic organ prolapse (POP) is a highly disabling condition that negatively affects the quality of life of millions of women worldwide. However, the underlying mechanisms associated with the development and progression of the disease remain poorly understood. Here, an untargeted four-dimensional data-independent acquisition (4D DIA)-based proteomics approach was applied to vaginal wall tissue samples from POP (n = 19) and control (n = 8) patients to identify potential diagnostic biomarker(s) for POP and examine the molecular mechanisms underlying the disease. Of the 5713 tissue proteins that were detected, 1957 proteins were significantly changed in POP patients. Further bioinformatics analysis revealed that multiple biological processes including protein digestion & absorption, retrograde endocannabinoid signaling, tyrosine metabolism, and nucleotide metabolism were significantly enriched and associated with the pathogenesis of POP. Interestingly, 16 of these differentially expressed proteins associated with four pathways were also identified by targeted parallel reaction monitoring (PRM) proteomics analysis on the same 27 tissue samples. Changes in 94 % (15/16) of these proteins were consistent with the 4D DIA data. Furthermore, most proteins displayed good diagnostic accuracy with high area under the curve (AUC) values (AUC＞0.8). Specifically, five proteins including ELN, COL6A2, ENTPD1, AOC3, and COX7A2 distinguished between POP and control patients with very high accuracy (AUC ≥ 0.95) in both 4D DIA and PRM analyses, and may therefore be potential diagnostic biomarkers for POP. In summary, the present study not only provided several potential biomarker(s) for effective POP diagnosis, but extended our knowledge of the key regulatory pathways associated with the disease.

Liver transcriptomic and proteomic analyses provide new insight into the pathogenesis of liver fibrosis in mice

BACKGROUND

Liver fibrosis (LF) is a kind of progressive liver injury reaction. The goal of this study was to achieve a more detailed understanding of the molecular changes in response to CCl4-induced LF through the identification of a differentially expressed liver transcriptomic and proteomic.

RESULTS

A total of 1224 differentially expressed genes (DEGs) and 302 differentially expressed proteins (DEPs) were significantly identified at the transcriptomic and proteomic level, respectively, and 69 genes (hereafter "cor-DEGs-DEPs" genes) were detected at both levels. Pathway enrichment analysis showed that these cor-DEGs-DEPs genes were significantly enriched in 133 pathways. Importantly, among the cor-DEGs-DEPs genes, Gstm1, Gstm3, Ephx1 and Gstp1 were shown to be associated with metabolic pathways, and confirmed by RT-qPCR and parallel reaction monitoring (PRM) verification.

CONCLUSIONS

Through the combined analysis of transcriptomic and proteomic data, this study provides valuable insights into the potential mechanism of the pathogenesis of LF, and lays a theoretical foundation for the further development of targeted therapy for LF.

Proteomics-Guided Mining and Characterization of Epoxidase Involved in Camptothecin Biosynthesis from Camptotheca acuminata

The detailed metabolic map for camptothecin (CPT) biosynthesis in Camptotheca acuminata has been proposed according to our combined omics results. However, the CYP450-mediated epoxidation step in CPT biosynthesis remains unexplored. A proteomics-guided approach was used to identify and annotate the proteins enriched during the vigorous CPT metabolism period in mature C. acuminata and seedlings. Comparative analyses revealed that the CPT and flavonoid biosyntheses were vigorous in stems and all of the samples except the leaves, respectively. The CYP71BE genes were screened based on their enrichment patterns at the transcriptomic-proteomic level and biochemically characterized in Saccharomyces cerevisiae WAT11. Four CYP71BE proteins exhibited in vitro isoliquiritigenin epoxidase activity. Additionally, CYP71BE206 showed epoxidase activity toward strictosamide, the critical precursor for CPT biosynthesis, both in vitro and in Nicotiana benthamiana. In planta functional verification suggested that CYP71BE206 is involved in CPT biosynthesis. Their catalytic conditions were optimized, and the enzymatic parameters were determined. This study provides valuable insight into the CYP71BE-mediated epoxidation step for CPT biosynthesis and offers evidence to verify that the newly characterized epoxidase (CYP71BE206) is simultaneously responsible for the biosynthesis of CPT and the flavonoid in this plant. An evolution event probably happened on ancestral CYP71BE, resulting in the neofunctionalization of CYP71BE206.

Quantitative phosphoproteomic analysis of mice with liver fibrosis by DIA mass spectrometry analysis with PRM verification

Liver fibrosis (LF), commonly associated with chronic liver diseases, is a major public health problem worldwide. Protein phosphorylation is not only an important form of protein modification in organisms but also the most important mechanism to regulate and control the activity and function of proteins, affecting the occurrence and development of many diseases. However, comprehensive phosphoproteomic profiling in LF has not been fully elucidated. In this study, data-independent acquisition (DIA) was used to analyse the phosphoproteomics of mice with LF. A total of 553 phosphopeptides (representing 440 phosphoproteins) had significant phosphorylation levels. Among these phosphoproteins, 49 were upregulated and 401 were downregulated, and 5 phosphoserine (P-Ser) motifs and 2 phosphothreonine (P-Thr) motifs were conserved in LF. GO and KEGG pathway enrichment analyses identified 769 significant GO terms and 49 significant KEGG pathways. Four phosphorylated proteins were selected for parallel reaction monitoring (PRM) verification, and the results were consistent with DIA data. Together, there were significantly different phosphoproteomic profiles in LF, suggesting that protein phosphorylation was related to the occurrence and progression of LF, which could pave the way for further investigation into the related regulatory mechanisms. SIGNIFICANCE: LF is a necessary stage in the development of chronic liver disease to liver cirrhosis and has attracted wide attention. To the best of our knowledge, there are few reports on the phosphorylated proteomics of LF. In this study, DIA and PRM techniques were used to study the liver tissue of mice induced by CCl₄. The results showed that phosphorylation had a significant effect on the activity and function of proteins, and the PRM results were consistent with the trend observed in DIA analysis. This study will help to better reveal the relationship of phosphorylated proteins in LF and lay a foundation for further study of related regulatory mechanisms.

Integrative proteomic profiling of lung tissues and blood in acute respiratory distress syndrome

Introduction

Acute respiratory distress syndrome and acute lung injury (ARDS/ALI) still lack a recognized diagnostic test and pharmacologic treatments that target the underlying pathology.

Methods

To explore the sensitive non-invasive biomarkers associated with pathological changes in the lung of direct ARDS/ALI, we performed an integrative proteomic analysis of lung and blood samples from lipopolysaccharide (LPS)-induced ARDS mice and COVID-19-related ARDS patients. The common differentially expressed proteins (DEPs) were identified based on combined proteomic analysis of serum and lung samples in direct ARDS mice model. The clinical value of the common DEPs was validated in lung and plasma proteomics in cases of COVID-19-related ARDS.

Results

We identified 368 DEPs in serum and 504 in lung samples from LPS-induced ARDS mice. Gene ontology (GO) classification and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that these DEPs in lung tissues were primarily enriched in pathways, including IL-17 and B cell receptor signaling pathways, and the response to stimuli. In contrast, DEPs in the serum were mostly involved in metabolic pathways and cellular processes. Through network analysis of protein-protein interactions (PPI), we identified diverse clusters of DEPs in the lung and serum samples. We further identified 50 commonly upregulated and 10 commonly downregulated DEPs in the lung and serum samples. Internal validation with a parallel-reacted monitor (PRM) and external validation in the Gene Expression Omnibus (GEO) datasets further showed these confirmed DEPs. We then validated these proteins in the proteomics of patients with ARDS and identified six proteins (HP, LTA4H, S100A9, SAA1, SAA2, and SERPINA3) with good clinical diagnostic and prognostic value.

Discussion

These proteins can be viewed as sensitive and non-invasive biomarkers associated with lung pathological changes in the blood and could potentially serve as targets for the early detection and treatment of direct ARDS especially in hyperinflammatory subphenotype.

The Plasma DIA-Based Quantitative Proteomics Reveals the Pathogenic Pathways and New Biomarkers in Cervical Cancer and High Grade Squamous Intraepithelial Lesion

OBJECTIVE

The process of normal cervix changing into high grade squamous intraepithelial lesion (HSIL) and invasive cervical cancer is long and the mechanisms are still not completely clear. This study aimed to reveal the protein profiles related to HSIL and cervical cancer and find the diagnostic and prognostic molecular changes.

METHODS

Data-independent acquisition (DIA) analysis was performed to identify 20 healthy female volunteers, 20 HSIL and 20 cervical patients in a cohort to screen differentially expressed proteins (DEPs) for the HSIL and cervical cancer. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used for functional annotation of DEPs; the protein-protein interaction (PPI) and weighted gene co-expression network analysis (WGCNA) were performed for detection of key molecular modules and hub proteins. They were validated using the Enzyme-Linked Immunosorbent Assay (ELISA).

RESULTS

A total of 243 DEPs were identified in the study groups. GO and KEGG analysis showed that DEPs were mainly enriched in the complement and coagulation pathway, cholesterol metabolism pathway, the IL-17 signaling pathway as well as the viral protein interaction with cytokine and cytokine receptor pathway. Subsequently, the WGCNA analysis showed that the green module was highly correlated with the cervical cancer stage. Additionally, six interesting core DEPs were verified by ELISA, APOF and ORM1, showing nearly the same expression pattern with DIA. The area under the curve (AUC) of 0.978 was obtained by using ORM1 combined with APOF to predict CK and HSIL+CC, and in the diagnosis of HSIL and CC, the AUC can reach to 0.982. The high expression of ORM1 is related to lymph node metastasis and the clinical stage of cervical cancer patients as well as the poor prognosis.

CONCLUSION

DIA-ELSIA combined analysis screened and validated two previously unexplored but potentially useful biomarkers for early diagnosis of HSIL and cervical cancer, as well as possible new pathogenic pathways and therapeutic targets.

Serum Proteomic Analysis Identifies SAA1, FGA, SAP, and CETP as New Biomarkers for Eosinophilic Granulomatosis With Polyangiitis

Background

Eosinophilic granulomatosis with polyangiitis (EGPA) is characterized by asthma-like attacks in its early stage, which is easily misdiagnosed as severe asthma. Therefore, new biomarkers for the early diagnosis of EGPA are needed, especially for differentiating the diagnosis of asthma.

Objectives

To identify serum biomarkers that can be used for early diagnosis of EGPA and to distinguish EGPA from severe asthma.

Method

Data-independent acquisition (DIA) analysis was performed to identify 45 healthy controls (HC), severe asthma (S-A), and EGPA patients in a cohort to screen biomarkers for early diagnosis of EGPA and to differentiate asthma diagnosis. Subsequently, parallel reaction monitoring (PRM) analysis was applied to a validation cohort of 71 HC, S-A, and EGPA patients.

Result

Four candidate biomarkers were identified from DIA and PRM analysis-i.e., serum amyloid A1 (SAA1), fibrinogen-α (FGA), and serum amyloid P component (SAP)-and were upregulated in the EGPA group, while cholesteryl ester transfer protein (CETP) was downregulated in the EGPA group compared with the S-A group. Receiver operating characteristics analysis shows that, as biomarkers for early diagnosis of EGPA, the combination of SAA1, FGA, and SAP has an area under the curve (AUC) of 0.947, a sensitivity of 82.35%, and a specificity of 100%. The combination of SAA1, FGA, SAP, and CETP as biomarkers for differential diagnosis of asthma had an AUC of 0.921, a sensitivity of 78.13%, and a specificity of 100%, which were all larger than single markers. Moreover, SAA1, FGA, and SAP were positively and CETP was negatively correlated with eosinophil count.

Conclusion

DIA-PRM combined analysis screened and validated four previously unexplored but potentially useful biomarkers for early diagnosis of EGPA and differential diagnosis of asthma.

Integrating SWATH-MS proteomics and transcriptome analysis to preliminarily identify three DEGs as biomarkers for proliferative diabetic retinopathy

PURPOSE

We intended to preliminarily find differentially expressed proteins that play crucial roles in proliferative diabetic retinopathy (PDR), and lay the foundation for subsequent further research on the mechanism.

EXPERIMENTAL DESIGN

Here, we developed a new strategy integrated the sequential windowed acquisition of all theoretical fragment ion (SWATH) mass spectra (MS) with multi-dataset joint analysis to screen for the PDR plasma biomarker. The annotation of the given gene list was performed with ClueGO function analysis. Additionally, the protein-protein interaction relationship was also revealed by the STRING database.

RESULTS

In SWATH-MS assays, we identified 23 upregulated and 13 downregulated proteins in PDR plasma. In the mRNA database analysis, 375 genes were identified as differentially expressed genes in GSE102485. Only three genes (FCGR3A, DPEP2, and ADGRF5) were characterized as upregulated in both the dataset and the SWATH-MS list. The area under the ROC curve (AUC) of FCGR3A, DPEP2, and ADGRF5 in distinguishing PDR from others was 0.739, 0.770, and 0.739.

CONCLUSIONS AND CLINICAL RELEVANCE

We provide a novel strategy for biomarker screening and identified plasma FCGR3A, DPEP2, and ADGRF5 as potential biomarkers for patients with PDR. Identifying the key molecules of the disease is essential for the development of new therapeutic molecules and new uses of existing drugs.

Proteomic and lipidomic analyses reveal saturated fatty acids, phosphatidylinositol, phosphatidylserine, and associated proteins contributing to intramuscular fat deposition

Intramuscular fat (IMF) content is an important factor in porcine meat quality. Previous studies have screened multiple candidate genes related to IMF deposition, but the lipids that affect IMF deposition and their lipid-protein network remain unknown. In this study, we performed proteomic and lipidomic analyses of the longissimus dorsi (LD) muscle from high-IMF (IMFH) and low-IMF (IMF-L) groups of Xidu black pigs. Eighty-eight proteins and 143 lipids were differentially abundant between the groups. The differentially abundant proteins were found to be involved in cholesterol metabolism, the PPAR signaling pathway, and ferroptosis. The triacylglycerols (TAGs) upregulated in the IMF-H group were mainly shown to be synthesized by saturated fatty acids (SFAs), while the downregulated TAGs were mainly synthesized by polyunsaturated fatty acids (PUFAs). All differentially abundant phosphatidylinositols (PIs) and phosphatidylserines (PSs) were found to be upregulated in the IMF-H group. A correlation analysis of the proteomic and lipidomic revealed candidate proteins (APOA4, VDAC3, PRNP, CTSB, GSPT1) related to TAG, PI, and PS lipids. These results revealed differences in proteins and lipids between the IMF-H and IMF-L groups, which represent new candidate proteins and lipids that should be investigated to determine the molecular mechanisms controlling IMF deposition in pigs. SIGNIFICANCE: Intramuscular fat (IMF) is a key factor affecting meat quality, and meat with a higher IMF content can have a better flavor. In this study, proteomic results show that the ferroptosis pathway, including the PRNP, VDAC3 and CP proteins, affects IMF deposition. Lipid composition is the key factor affecting IMF deposition, but there are few reports on this. In this study, through lipidomic analysis, we suggest that saturated fatty acid (SFA), phosphatidylinositol (PI), and phosphatidylserine (PS) may contribute to IMF deposition. A correlation analysis reveals the potential regulatory network between lipids and proteins. This study clarifies the difference in protein and lipid compositions in longissimus dorsi (LD) muscle with high and low IMF contents. This information suggests that it would be beneficial to increase the intramuscular fat content of pork not only from a genetic perspective but also from a nutritional perspective.