Proteomic Bioinformatics Research Articles

Protein phosphatase PP2Cα S-glutathionylation regulates cell migration

Redox signaling is a fundamental mechanism that controls all major biological processes partly via protein cysteine oxidations, including S-glutathionylation. Despite over 2,000 cysteines identified to form S-glutathionylation in databases, the identification of redox cysteines functionally linked to a biological process of interest remains challenging. Here, we demonstrate a strategy combining glutathionylation proteomic database, bioinformatics, and biological screening, which resulted in the identification of S-glutathionylated proteins, including PP2Cα, as redox players of cell migration. We showed that PP2Cα, a prototypical magnesium-dependent serine/threonine phosphatase, is susceptible to S-glutathionylation selectively at non-conserved C314. PP2Cα glutathionylation causes increased migration and invasion of breast cancer cell lines in oxidative stress or upon hydrogen peroxide production. Mechanistically, PP2Cα glutathionylation modulates its protein-protein interactions, activating c-Jun N-terminal kinase (JNK) and extracellular signal-regulated kinase (ERK) pathways to elevate migration and invasion. In addition, PP2Cα glutathionylation occurs in response to epidermal-growth factor, supporting a serine/threonine phosphatase PP2Cα as a new redox player in growth factor signal transduction.

VEGF-B prevents chronic hyperglycemia-induced retinal vascular leakage by regulating the CDC42-ZO1/VE-cadherin pathway.

Non-proliferative diabetic retinopathy (NPDR) is the early stage of diabetic retinopathy (DR) and is a chronic oxidative stress-related ocular disease. Few treatments are approved for early DR. This study aimed to investigate the pathogenic mechanisms underlying the retinal micro-vasculopathy induced by diabetes and to explore an early potential for treating early DR in a mouse model. The mouse model of type 1 diabetes was established by intraperitoneal injection of streptozotocin (STZ, 180 mg/kg), which was used as the early DR model. The body weight and blood glucose mice were measured regularly; The retinal vascular leakage in the early DR mice was determined by whole-mount staining; Label-free quantitative proteomic analysis and bioinformatics were used to explore the target proteins and signaling pathways associated with the retinal tissues of early DR mice; To detect the effects of target protein on endothelial cell proliferation, migration, and tube formation, knockdown and overexpression of VEGF-B were performed in human retinal vascular endothelial cells (HRECs); Western blotting was used to detect the expression of target proteins invitro and invivo; Meanwhile, the therapeutic effect of VEGF-B on vascular leakage has also been evaluated invitro and invivo. The protein expressions of vascular endothelial growth factor (VEGF)-B and the Rho GTPases family member CDC42 were reduced in the retinal tissues of early DR. VEGF-B upregulated the expression of CDC42/ZO1/VE-cadherin and prevented hyperglycemia-induced vascular leakage in HRECs. Standard intravitreal VEGF-B injections improved the retinal vascular leakage and neurovascular response in early DR mice. Our findings demonstrated, for the first time, that in diabetes, the retinal vessels are damaged due to decreased VEGF-B expression through downregulation of CDC42/ZO1/VE-cadherin expression. Therefore, VEGF-B could be used as a novel therapy for early DR.

Abstract 6054: UPPGRADER: a bioinformatics-based novel E3 ligase discovery platform

Abstract In Target Protein Degradation (TPD) field, conventional E3 ligases utilized in the clinic are limited to CRBN and VHL, which opens the need for exploration of novel E3 ligases for the advancement of TPD. To address this, we have developed a proprietary platform, UPPGRADER, for systematic discovery of novel E3 ligases based on -omics data including single cell RNA sequencing (scRNA-seq) and whole genome sequencing (WGS), in conjunction with proteomics data and bioinformatics tools.UPPGRADER enables systematic analyses on alterations occurred in all genomic areas including E3 ligase genes and potential target genes. For example, analyzing Pan-Cancer Analysis of Whole Genomes (PCAWG) data identified amino acid changes into Cysteine or Lysine, which can be targeted by covalent binders with cancer specificity. Through such analysis, we discovered several novel E3 ligases, including but not limited to FBXW7, with the categorization of the findings based on specific cancer types.At the single cell expression level, UPPGRADER provides the capability to assess gene expression levels of E3 ligases and target proteins by proprietary measurements based on gene detection rate. This system also allows assessment of E3 ligase-Target gene co-expression per single cell. In colorectal cancer, UPPGRADER has shown that the co-expression of E3 ligase FBXW7 and well-known colorectal cancer target (KRAS) increases from 1% (4 out of 334) in normal epithelial cells to 17% (2,967 out of 17,458) in cancerous epithelial cells, highlighting a significant change in their simultaneous expression patterns during cancer progression.UPPGRADER also identified E3 ligase X which showed high co-expression level with KRAS gene alongside universal expression properties and high cancer cell dependencies. For E3 ligase X, we developed novel small molecule binders (nM binding affinity) with bioavailability > 20% in animal pharmacokinetics. Bifunctional degraders utilizing these binders displayed BRD4 degradation in more than 20 cell lines with double to triple digit nM DC50 and DC90 values. Other targets (AURKA, CRBN and others) were potently degraded with anticipated mechanism of action (assessed by E3 ligase KO cell line and proteasomal inhibitors).To conclude, UPPGRADER is a comprehensive bioinformatics tool for discovering novel E3 ligases with biological validations. Through recent explosion of scRNA-seq and WGS datasets in different diseases and mechanism-based identification of additional molecular targets, UPPGRADER is poised to advance the field of TPD. Citation Format: Kyungsik Ha, Woojeung Song, Woochang Choi, Gi Bbeum Lee, Soohee Ryu, Jun Kyu Lee, Hwajin Lee. UPPGRADER: a bioinformatics-based novel E3 ligase discovery platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6054.

Quantitative Proteomics Reveal That CB2R Agonist JWH-133 Downregulates NF-κB Activation, Oxidative Stress, and Lysosomal Exocytosis from HIV-Infected Macrophages.

HIV-associated neurocognitive disorders (HAND) affect 15-55% of HIV-positive patients and effective therapies are unavailable. HIV-infected monocyte-derived macrophages (MDM) invade the brain of these individuals, promoting neurotoxicity. We demonstrated an increased expression of cathepsin B (CATB), a lysosomal protease, in monocytes and post-mortem brain tissues of women with HAND. Increased CATB release from HIV-infected MDM leads to neurotoxicity, and their secretion is associated with NF-κB activation, oxidative stress, and lysosomal exocytosis. Cannabinoid receptor 2 (CB2R) agonist, JWH-133, decreases HIV-1 replication, CATB secretion, and neurotoxicity from HIV-infected MDM, but the mechanisms are not entirely understood. We hypothesized that HIV-1 infection upregulates the expression of proteins associated with oxidative stress and that a CB2R agonist could reverse these effects. MDM were isolated from healthy women donors (n = 3), infected with HIV-1ADA, and treated with JWH-133. After 13 days post-infection, cell lysates were labeled by Tandem Mass Tag (TMT) and analyzed by LC/MS/MS quantitative proteomics bioinformatics. While HIV-1 infection upregulated CATB, NF-κB signaling, Nrf2-mediated oxidative stress response, and lysosomal exocytosis, JWH-133 treatment downregulated the expression of the proteins involved in these pathways. Our results suggest that JWH-133 is a potential alternative therapy against HIV-induced neurotoxicity and warrant in vivo studies to test its potential against HAND.

Proteomics analysis techniques and Bioinformatics approaches for biomarkers discovery

Proteomics is the study of all the proteins expressed in the proteome and offer new avenues of research in the biomedical field. The recent development of protein analysis tools has continued to improve, offering a wide range of technologies categorised according to their ability to analyse and identify protein such as MSbased technology. These novels tools have been invaluable to the rise of proteomics and permitted significant progress in the identification of clinically applicable biomarkers and new therapeutic targets although detection of very low abundance proteins remains difficult. Due to the high throughput data generated by proteomic mass spectrometric analysis, automatic biomarker identification requires bioinformatics and database screening. Bioinformatics allows the development of new algorithms and software for the interpretation of mass spectrometry data in order to facilitate the exploitation of the data and the validation of potentially discovered biomarkers. The aim of this paper was to discuss the analytical techniques used in protein biomarker discovery and the usefulness of bioinformatics for the interpretation and validation of the data generated.

Labeled-free quantitative proteomic analysis of cervical squamous cell carcinoma identifies potential protein biomarkers.

Cervical cancer remains a prevalent cancer among women, and reliance on surgical and radio-chemical therapies can irreversibly affect patients' life span and quality of life. Thus, early diagnosis and further exploration into the pathogenesis of cervical cancer are crucial. Mass spectrometry technology is widely applied in clinical practice and can be used to further investigate the protein alterations during the onset of cervical cancer. Employing labeled-free quantitative proteomics technology and bioinformatics tools, we analyzed and compared the differential protein expression profiles between normal cervical squamous cell tissues and cervical squamous cell cancer tissues. GEPIA is an online website for analyzing the RNA sequencing expression data of tumor and normal tissue data from the TCGA and the GTEx databases. This approach aided in identifying qualitative and quantitative changes in key proteins related to the progression of cervical cancer. Compared to normal samples, a total of 562 differentially expressed proteins were identified in cervical cancer samples, including 340 up-regulated and 222 down-regulated proteins. Gene ontology functional annotation, and KEGG pathway, and enrichment analysis revealed that the differentially expressed proteins mainly participated in metabolic pathways, spliceosomes, regulation of the actin cytoskeleton, and focal adhesion signaling pathways. Specifically, desmoplakin (DSP), protein phosphatase 1, regulatory (inhibitor) subunit 13 like (PPP1R13L) and ANXA8 may be involved in cervical tumorigenesis by inhibiting apoptotic signal transmission. Moreover, we used GEPIA database to validate the expression of DSP, PPP1R13L and ANXA8 in human cancers and normal cervix. In this study, we identified 562 differentially expressed proteins, and there were three proteins expressed higher in the cervical cancer tissues. The functions and signaling pathways of these differentially expressed proteins lay a theoretical foundation for elucidating the molecular mechanisms of cervical cancer.

Biological Effects of "Inflammageing" on Human Oral Cells: Insights into a Potential Confounder of Age-Related Diseases.

The term "inflammageing" describes the process of inflammation-induced aging that leads living cells to a state of permanent cell cycle arrest due to chronic antigenic irritation. This in vitro study aimed to shed light on the mechanisms of "inflammageing" on human oral cells. Primary cultures of human gingival fibroblasts (hGFs) were exposed to variable pro-inflammatory stimuli, including lipopolysaccharide (LPS), Tumor Necrosis Factor-alpha (TNFa), and gingival crevicular fluid (GCF) collected from active periodontal pockets of systemically healthy patients. Inflammageing was studied through two experimental models, employing either late-passage ("aged") cells (p. 10) that were exposed to the pro-inflammatory stimuli or early-passage ("young") cells (p. 1) continuously exposed during a period of several passages (up to p. 10) to the above-mentioned stimuli. Cells were evaluated for the expression of beta-galactosidase activity (histochemical staining), senescence-associated genes (qPCR analysis), and biomarkers related to a Senescence-Associated Secretory Phenotype (SASP), through proteome profile analysis and bioinformatics. A significant increase (p < 0.05) in beta-galactosidase-positive cells was observed after exposure to each pro-inflammatory stimulus. The senescence-associated gene expression included upregulation for CCND1 and downregulation for SUSD6, and STAG1, a profile typical for cellular senescence. Overall, pro-inflammatory priming of late-passage cells caused more pronounced effects in terms of senescence than long-term exposure of early-passage cells to these stimuli. Proteomic analysis showed induction of SASP, evidenced by upregulation of several pro-inflammatory proteins (IL-6, IL-10, IL-16, IP-10, MCP-1, MCP-2, M-CSF, MIP-1a, MIP-1b, TNFb, sTNF-RI, sTNF-RII, TIMP-2) implicated in cellular aging and immune responses. The least potent impact on the induction of SASP was provoked by LPS and the most pronounced by GCF. This study demonstrates that long-term exposure of hGFs to various pro-inflammatory signals induced or accelerated cellular senescence with the most pronounced impact noted for the late-passage cells. The outcome of these analyses provides insights into oral chronic inflammation as a potential confounder of age-related diseases.

SYNOVIAL FLUID PROTEOMICS AND BIOINFORMATICS HIGHLIGHTS POTENTIAL MECHANISMS OF UMBILICAL CORD-MSC INDUCED RADIOLOGICAL IMPROVEMENT IN AN OVINE MODEL OF OSTEOARTHRITIS

AbstractObjectivesA promising therapy for early osteoarthritis (OA) is the transplantation of human umbilical cord-derived mesenchymal stromal cells (hUC-MSCs). The synovial fluid (SF) from a pre-clinical ovine model treated with hUC-MSCs has been profiled using proteomics and bioinformatics to elucidate potential mechanisms of therapeutic effect.MethodsFour weeks after a medial meniscus transection surgery, sheep were injected with 107 hUC-MSCs in Phosphate Buffered Saline (PBS) or PBS only (n=7) and sacrificed at 12 weeks. SF was normalised for protein abundance (ProteoMinerTM) and analysed using label-free quantitation proteomics. Bioinformatics analyses (Ingenuity Pathway Analysis (IPA) and STRING) were used to assess differentially regulated functions from the proteomic data. Human orthologues were identified for the ovine proteins using UniProt and DAVID resources and proteins that were ≥±1.3 fold differentially abundant between treatment groups, were included in the bioinformatics analyses.ResultshUC-MSC treated animals demonstrated significantly less joint space narrowing. Nineteen SF proteins were differentially abundant in treated cf. control sheep (FC±2.0; p&lt;0.05). Biglycan (a small leucine-rich proteoglycan of the cartilage extracellular matrix) abundance was increased by 2.1 fold in treated compared to untreated sheep (p=0.024). IPA indicated that lipid synthesis (z-score=1.772; p=0.00267) and immune cell migration pathways (cell movement of mononuclear leukocytes: z-score=1.761; p=0.00259), amongst others, were likely to be activated in the treated sheep. Conversely, tissue damage (z-score=−2; p=0.00019), senescence (z-score=−1.981; p=0.00007) and necrosis (z-score=−1.728; p=0.00829) associated pathways as well as inflammation (z-score=−1.718; p=0.00057) and vascular permeability (z-score=−1.698; p=0.00002) were likely to be inhibited in treated cf. untreated sheep.ConclusionshUC-MSC treatment prevented/delayed OA progression, demonstrated via a reduction in joint space narrowing. SF proteome bioinformatics revealed potential mechanisms of therapeutic action related to immunomodulation and the inhibition of multiple cell death, and tissue damage associated pathways. Further, a potential predicted upregulation in lipid synthesis in treated sheep represents a novel mechanism warranting further investigation. Additional work is required to validate these discovery phase proteomic findings in studies which specifically target and manipulate the proposed mechanisms highlighted.Declaration of Interest(b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project.

Effect of Naoxintong Capsule on Microglia and Proteomics of Cortex After Myocardial Infarction in Rats.

Neuroinflammation caused by microglia in the central nervous system (CNS) is observed after myocardial infarction (MI). However, the inflammatory response mechanism remains unclear. BuChang Naoxintong capsule (NXT) is a Chinese medicine for treating ischemic cardio-cerebrovascular diseases, requiring more studies to understand the pharmacodynamic mechanism. Permanent ligation of the left anterior descending coronary artery (LAD) was performed in rats. Additionally, histopathological staining in the left ventricular (LV) and immunofluorescence within the brain cortex after 1 d and 7 d of MI were performed to determine the NXT pharmacodynamic action and best administration dosage. Proteomics helped obtain the essential proteins related to neuroinflammation and MI in the heart and brain tissue after 7 d of MI. Based on TTC, HE, Masson, and immunofluorescence staining results of CD206 and IBA-1, NXT demonstrated a better pharmacodynamic action towards myocardial injury and neuroinflammation after 7 d of MI. Moreover, the human equivalent dosage of NXT (220 mg/kg) became the best administration dose. The proteome bioinformatics analysis in the LV and brain cortex was performed. Thus, the elongation of very long-chain fatty acids protein 5 (ELOVL5) and ATP-binding cassette subfamily G member 4 (ABCG4) became critical proteins related to MI and neuroinflammation. The western blotting results indicated that ABCG4 expression possessed the same trend as the proteomics results. The auto-dock results revealed that ABCG4 had a good binding ability with Ferulic acid, Paeoniflorin, and Tanshinone II A, the key ingredients of NXT. The cellular thermal shift assay results demonstrated that ABCG4 showed better thermal stability post-NXT treatment. NXT can improve myocardial injury, such as heart infarct size, pathological injury, myocardial fibrosis, and inflammatory cell infiltration. Additionally, brain neuroinflammation induced by microglia after MI affects the expression and structure of ABCG4. Thus, ABCG4 could be the key protein associated with MI and neuroinflammation.

Unveiling the Molecular Footprint: Proteome-Based Biomarkers for Alzheimer's Disease.

Alzheimer's disease (AD) is a devastating neurodegenerative disorder characterized by progressive cognitive decline and memory loss. Early and accurate diagnosis of AD is crucial for implementing timely interventions and developing effective therapeutic strategies. Proteome-based biomarkers have emerged as promising tools for AD diagnosis and prognosis due to their ability to reflect disease-specific molecular alterations. There is of great significance for biomarkers in AD diagnosis and management. It emphasizes the limitations of existing diagnostic approaches and the need for reliable and accessible biomarkers. Proteomics, a field that comprehensively analyzes the entire protein complement of cells, tissues, or bio fluids, is presented as a powerful tool for identifying AD biomarkers. There is a diverse range of proteomic approaches employed in AD research, including mass spectrometry, two-dimensional gel electrophoresis, and protein microarrays. The challenges associated with identifying reliable biomarkers, such as sample heterogeneity and the dynamic nature of the disease. There are well-known proteins implicated in AD pathogenesis, such as amyloid-beta peptides, tau protein, Apo lipoprotein E, and clusterin, as well as inflammatory markers and complement proteins. Validation and clinical utility of proteome-based biomarkers are addressing the challenges involved in validation studies and the diagnostic accuracy of these biomarkers. There is great potential in monitoring disease progression and response to treatment, thereby aiding in personalized medicine approaches for AD patients. There is a great role for bioinformatics and data analysis in proteomics for AD biomarker research and the importance of data preprocessing, statistical analysis, pathway analysis, and integration of multi-omics data for a comprehensive understanding of AD pathophysiology. In conclusion, proteome-based biomarkers hold great promise in the field of AD research. They provide valuable insights into disease mechanisms, aid in early diagnosis, and facilitate personalized treatment strategies. However, further research and validation studies are necessary to harness the full potential of proteome-based biomarkers in clinical practice.

Molecular Mechanism of Male Sterility Induced by 60Co γ-Rays on Plutella xylostella (Linnaeus).

Plutella xylostella (Linnaeus) is one of the notorious pests causing substantial loses to numerous cruciferous vegetables across many nations. The sterile insect technique (SIT) is a safe and effective pest control method, which does not pollute the environment and does not produce drug resistance. We used proteomics technology and bioinformatics analysis to investigate the molecular mechanisms responsible for the effects of different doses of radiation treatment on the reproductive ability of male P. xylostella. A total of 606 differentially expressed proteins (DEPs) were identified in the 200 Gy/CK group, 1843 DEPs were identified in the 400 Gy/CK group, and 2057 DEPs were identified in the 400 Gy/200 Gy group. The results showed that after 200 Gy irradiation, the testes resisted radiation damage by increasing energy supply, amino acid metabolism and transport, and protein synthesis, while transcription-related pathways were inhibited. After 400 Gy irradiation, the mitochondria and DNA in the testis tissue of P. xylostella were damaged, which caused cell autophagy and apoptosis, affected the normal life activities of sperm cells, and greatly weakened sperm motility and insemination ability. Meanwhile, Western blotting showed that irradiation affects tyrosine phosphorylation levels, which gradually decrease with increasing irradiation dose.

Using Proteome Microarray and Gene Expression Omnibus Database to Screen Tumour-Associated Antigens to Construct the Optimal Diagnostic Model of Oesophageal Squamous Cell Carcinoma

AimsAutoantibodies against tumour-associated antigens (TAAs) are promising biomarkers for early immunodiagnosis of cancers. This study was designed to screen and verify autoantibodies against TAAs in sera as diagnostic biomarkers for oesophageal squamous cell carcinoma (ESCC). Materials and methodsThe customised proteome microarray based on cancer driver genes and the Gene Expression Omnibus database were used to identify potential TAAs. The expression levels of the corresponding autoantibodies in serum samples obtained from 243 ESCC patients and 243 healthy controls were investigated by enzyme-linked immunosorbent assay (ELISA). In total, 486 serum samples were randomly divided into the training set and the validation set in the ratio of 2:1. Logistic regression analysis, recursive partition analysis and support vector machine were performed to establish different diagnostic models. ResultsFive and nine candidate TAAs were screened out by proteome microarray and bioinformatics analysis, respectively. Among these 14 anti-TAAs autoantibodies, the expression level of nine (p53, PTEN, GNA11, SRSF2, CXCL8, MMP1, MSH6, LAMC2 and SLC2A1) anti-TAAs autoantibodies in the cancer patient group was higher than that in the healthy control group based on the results from ELISA. In the three constructed models, a logistic regression model including four anti-TAA autoantibodies (p53, SLC2A1, GNA11 and MMP1) was considered to be the optimal diagnosis model. The sensitivity and specificity of the model in the training set and the validation set were 70.4%, 72.8% and 67.9%, 67.9%, respectively. The area under the receiver operating characteristic curve for detecting early patients in the training set and the validation set were 0.84 and 0.85, respectively. ConclusionsThis approach to screen novel TAAs is feasible, and the model including four autoantibodies could pave the way for the diagnosis of ESCC.

Leveraging transformers-based language models in proteome bioinformatics.

In recent years, the rapid growth of biological data has increased interest in using bioinformatics to analyze and interpret this data. Proteomics, which studies the structure, function, and interactions of proteins, is a crucial area of bioinformatics. Using natural language processing (NLP) techniques in proteomics is an emerging field that combines machine learning and text mining to analyze biological data. Recently, transformer-based NLP models have gained significant attention for their ability to process variable-length input sequences in parallel, using self-attention mechanisms to capture long-range dependencies. In this review paper, we discuss the recent advancements in transformer-based NLP models in proteome bioinformatics and examine their advantages, limitations, and potential applications to improve the accuracy and efficiency of various tasks. Additionally, we highlight the challenges and future directions of using these models in proteome bioinformatics research. Overall, this review provides valuable insights into the potential of transformer-based NLP models to revolutionize proteome bioinformatics.

17 Beta-estradiol impedes aortic root dilation and rupture in male Marfan mice

Background: Marfan syndrome causes a hereditary form of TAA with dilation of the aortic root. Male patients with Marfan syndrome are more likely than women to have aortic dilation and dissection and mouse models of Marfan syndrome demonstrate larger aortic roots in males compared to females even after adjustment for body size. In this study we examine the effects of estrogen17 β-estradiol on aortic dilation and rupture in a Marfan mouse model. Methods: Marfan male mice were administered estrogen17 β-estradiol pellets with 60 day release and the growth in aortic root size was measured every 2 weeks for 8 weeks. Aortic root tissue from vehicle and 17 b-estradiol mice were subjected to proteomic analysis and bioinformatics was used to ascertain enriched pathways. Marfan mice with and without 17 b-estradiol were also treated with continuous angiotensin II infusion and survival was determined for 30 days. Results: Male Marfan mice with estrogen17 β-estradiol had a significant reduction in the ratio of aortic diameter 8 weeks after pellet implantation to baseline aortic diameter compared to the same ratio in Marfan mice with sham surgery. Proteomic analysis demonstrated complement C3 and C4 protein upregulation in Marfan mice compared to wild type and Marfan mice treated with 17 b-estradiol. Aortic smooth muscle cells express complement components in vivo and in vitro and expression of these factors are regulated by cytokines and estrogen17 β-estradiol in vitro. Additionally, 17 b-estradiol and female sex protect against aortic rupture when Marfan mice are treated with continuous infusion of angiotensin II and this protection correlates with lower protein levels of C3. Conclusions: Our findings support a protective role of 17 b-estradiol in preventing the dilation and rupture of aortic roots in Marfan male mice and suggest that these therapeutic actions may develop through anti-inflammatory properties. FAER Foundation for Anesthesia Education and Research This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Proteomics analyses of herbicide-tolerant genetically modified, conventionally, and organically farmed soybean seeds

The present study compared genetically modified (GM) crops with crops from different farming practices using high-resolution tandem mass spectrometry (HR-MS) and proteomics bioinformatics tools. In a previously published study, a number of significant differences regarding nutritional and elemental composition between a selection of GM, non-GM conventionally farmed, and organic soybeans have been found. In the present study, the proteome-level equivalence of the same samples was assessed using HR-MS. Direct comparison of tandem mass spectra and bottom-up proteomics bioinformatics indicated that proteomes of all samples investigated were very similar overall, with only a few distinct protein expression clusters obtained for GM and organic samples. Standard bottom-up proteome analyses identified 1025 soy proteins; of these 39 were found to be differentially expressed (p < 0.01) between GM, non-GM conventionally farmed, and organically farmed soybeans. Subsequent bioinformatics analyses of these proteins highlighted several potentially affected biochemical pathways that could contribute to the compositional differences reported earlier. In addition, protein markers separating conventionally, and organically farmed soybean seeds were found and peptide markers for the detection of GM soy in food and feed samples are described. Taken together, the data presented here shows that HR-MS based proteomics approaches can be used for the detection of transgenic events in food and feed grade soy, the differentiation of organically and conventionally farmed plants, and provide mechanistic explanations of effects observed on the phenotypic level of GM plants. HR-MS and proteomic bioinformatics thus should be considered key tools when developing molecular panel approaches for detection and safety assessments of novel crop varieties destined for use in feed and food.

Quantitative proteomics analysis reveals the anthocyanin biosynthetic mechanism in barley

Anthocyanin biosynthesis is complex, and synthetic mechanisms have not been clarified in purple barley. Proteomic techniques and bioinformatics were used to analyse the differences in protein during the three stages (groups A, C, and E). A total of 4185 proteins were identified in three stages of highland barley samples with anthocyanin contents of 0 (group A), 0.17 (group C), and 0.53 mg/g (group E). DEPs associated with photosynthesis, small molecule metabolic processes, generation of precursor metabolites and energy, and anthocyanin biosynthesis. KEGG pathway enrichment revealed that DEPs involved 474 significant metabolic pathways, mainly involved carbon metabolism, amino acid and secondary metabolite biosynthesis. In these significantly correlated anthocyanin synthesis pathways, six key proteins, P51106, M0Y9M3, A0A287WTB9, A0A287RU82, Q8LPD5, and A0A287P1Q6, were likely to participate in regulating anthocyanin synthesis. Proteins P51106 and M0Y9M3 were identified as dihydroflavonol 4-reductase and phenylalanine ammonia-lyase, which were key enzymes for anthocyanin synthesis. Proteins A0A287WTB9 and A0A287RU82 were identified to contain the functional domains of the transcription factors Myb and BHLH, involved in the regulation of anthocyanin synthesis. Q8LPD5 (Glutathione-S-transferase) and A0A287P1Q6 (alpha-1,3-glucosyltransferase) might be involved in anthocyanin transport and glycosidic bond modification, respectively. The PRM results were consistent with the TMT data.

Urinary insulin signaling pathway related proteins may serve as potential biomarkers for monitoring diabetes mellitus without hypertension and hyperlipidemia.

The insulin signaling pathway plays an important role in the development of diabetes mellitus. The expression of insulin signaling pathway related proteins in the urine of diabetic patients has not been reported. The aim of this study was to analyze and verify the expression of insulin signaling pathway related proteins in the urine of diabetic patients without hypertension and hyperlipidemia, and to explore their clinical application value. Based on data-independent acquisition proteomics technology and bioinformatics, the urinary protein expression profile of diabetic patients without hypertension and hyperlipidemia was established. Western blot and enzyme-linked immunoassay were performed to verify the expression of insulin signaling pathway related proteins in the urine of diabetic patients. Sixteen proteins related to the insulin signaling pathway were screened in urine, and 7 of them were differentially expressed in the urine of diabetic patients without hypertension and hyperlipidemia. Further quantitative analysis showed that the downregulation of protein kinase CAMP-dependent type II regulatory subunit α, growth factor receptor bound protein 2, and guanine nucleotide-binding protein G(s) in the urine of diabetic patients without hyperlipidemia and hypertension was consistent with the preliminary screening results. In this exploratory study, we detected the expression of insulin signaling pathway related proteins in the urine of diabetic patients without hypertension and hyperlipidemia. protein kinase CAMP-dependent type II regulatory subunit α, growth factor receptor bound protein 2, and guanine nucleotide-binding protein G(s) in the urine of diabetic patients were downregulated, which was associated with diabetes. They may be promising noninvasive biomarkers for monitoring diabetes.

Multi-omics technology for demystifying herbal medicine

Herbal medicine (HM) is a fruitful source of chemical substances that has contributed greatly to the pharmaceutical industry and novel therapeutics. Natural products derived from HM continue to be a rich source of lead compounds because of their high structural diversity and potent bioactivities. However, despite the success of active ingredients derived from HM in drug discovery, compatibility issues that make huge challenging for extended timelines of effective evaluation, chemical composition identification, active ingredient screening and target confirmation. However, some approaches solely cannot effectively elucidate the overall effect and action mechanism due to complexity muti-components of HM. Thus, integration strategies combining modern analytical techniques with HM are increasingly being developed in the era of big data and omics. The updated mass spectrometry has been used to identify natural product structure and their mode of action on biological processes. Their molecular properties are validated through the use of recent high-throughput multi-omics including transcriptomic, proteomic and metabolomic tools and bio-informatics, molecular docking, network pharmacology techniques that enable to accelerate natural product discovery. We summarized several important omics technical platforms and multi-omics-based integration approach as powerful strategies to demystify HM and discover new bioactive molecules.

Proteomic-Based Approach Reveals the Involvement of Apolipoprotein A-I in Related Phenotypes of Autism Spectrum Disorder in the BTBR Mouse Model

Autism spectrum disorder (ASD) is a neurodevelopmental disorder. Abnormal lipid metabolism has been suggested to contribute to its pathogenesis. Further exploration of its underlying biochemical mechanisms is needed. In a search for reliable biomarkers for the pathophysiology of ASD, hippocampal tissues from the ASD model BTBR T+ Itpr3tf/J (BTBR) mice and C57BL/6J mice were analyzed, using four-dimensional (4D) label-free proteomic analysis and bioinformatics analysis. Differentially expressed proteins were significantly enriched in lipid metabolic pathways. Among them, apolipoprotein A-I (ApoA-I) is a hub protein and its expression was significantly higher in the BTBR mice. The investigation of protein levels (using Western blotting) also confirmed this observation. Furthermore, expressions of SphK2 and S1P in the ApoA-I pathway both increased. Using the SphK inhibitor (SKI-II), ASD core phenotype and phenotype-related protein levels of P-CREB, P-CaMKII, and GAD1 were improved, as shown via behavioral and molecular biology experiments. Moreover, by using SKI-II, we found proteins related to the development and function of neuron synapses, including ERK, caspase-3, Bax, Bcl-2, CDK5 and KCNQ2 in BTBR mice, whose levels were restored to protein levels comparable to those in the controls. Elucidating the possible mechanism of ApoA-I in ASD-associated phenotypes will provide new ideas for studies on the etiology of ASD.

Increased CD34 in pancreatic islet negatively predict islet β-cell decrease in type1 diabetes model.

Islet β-cell biomarkers can reflect changes in the number and function of islet β-cells in the prediabetes or early diabetes stage. CD34 is a commonly used stem cell biomarker; however, its expression and function in pancreatic islets remain unclear. In the present study, double immunofluorescence staining, proteomic bioinformatics analysis, and correlation analysis were used to explore the potential of CD34 as an islet β-cell biomarker. Bioinformatics analysis revealed that the amino acid sequence of CD34 was conserved among multiple species and abundantly expressed on mouse and human pancreatic tissues. Immunofluorescence demonstrated that in the control rat pancreas, CD34 was expressed on glucagon-labeled islet α-cells but not on insulin-labeled islet β-cells. Furthermore, the proportion of CD34-positive cells, which were also positive for glucagon, was significantly increased in alloxan-induced diabetes models. Statistical analysis revealed that the expression of CD34 was negatively correlated with the number of insulin-labeled islet β-cells during diabetes progression in dose-dependent fashion in alloxan-induced diabetes models. Furthermore, the results suggested that the transdifferentiation of islet β-cells into islet α-cells may occur in the process of diabetes. Thus, the present study demonstrated that CD34 is expressed on islet α-cells, and its number is linearly and negatively correlated with the number of islet β-cells, suggesting that CD34 can be used as a prospective biomarker for islet β-cells in the early diagnosis of diabetes. The study also suggests the transformation of β-cells to α-cells in diabetes which provide a potential to be applied towards diabetes mechanism research.