Acute kidney injury is a common complication of sepsis, and its mechanism is very complicated. The purpose of this study was to investigate the mechanism of key differentially expressed proteins and their related signaling pathways in the occurrence and development of acute kidney injury in sepsis through proteomics. Acute kidney injury was induced by intraperitoneal injection of lipopolysaccharide at 10 mg/kg. Renal tissues were analyzed by TMT quantitative proteomic analysis. Differentially expressed proteins (DEPs) were screened. Gene Ontology (GO) function analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein-protein interaction (PPI) network analysis were performed. We obtained 530 DEPs. GO analysis showed that the biological process of DEPs was mainly stress response. The molecular functions of DEPs mainly focus on catalytic activity. The cellular components of DEPs were mainly located in the intracellular and cytoplasm. KEGG analysis showed that DEPs were mainly involved in metabolic pathways. Ten key proteins with interaction degree, such as Isg15, Irf7, Oasl2, Ifit3, Apob, Oasl, Ube2l6, Ifit2, Ifih1 and Ifit1 were identified. Irf7 was significantly up-regulated in rat kidney tissues. The upregulation of Irf7 plays an important role in the mechanism of acute renal injury induced by sepsis.
Metabolomics, a burgeoning field within systems biology, focuses on the comprehensive study of small molecules present in biological systems. Mass spectrometry (MS) has emerged as a powerful tool for metabolomic analysis due to its high sensitivity, resolution, and ability to characterize a wide range of metabolites thus offering deep insights into the metabolic profiles of living systems. This review provides an overview of the methodologies, workflows, strategies, data analysis techniques, and applications associated with mass spectrometry-based metabolomics. We discuss workflows, key strategies, experimental procedures, data analysis techniques, and diverse applications of metabolomics in various research domains. Nuances of sample preparation, metabolite extraction, separation using chromatographic techniques, mass spectrometry analysis, and data processing are elaborated. Moreover, standards, quality controls, metabolite annotation, software for statistical and pathway analysis are also covered. In conclusion, this review aims to facilitate the understanding and adoption of mass spectrometry-based metabolomics by newcomers and researchers alike by providing a foundational understanding and insights into the current state and future directions of this dynamic field.
The risk of cardiovascular disease (CVD) in patients with rheumatoid arthritis (RA) is much higher than that in the general population. As its etiology is not fully understood, we performed a pilot study using a shotgun proteomic approach to investigate whether the plasma signature in RA patients with CVD might show an altered profile. Subjects with RA were compared to a group of RA patients with a previous cardiovascular event (CVE). The cohort consisted of an RA control group (n = 10) and a group (n = 10) of RA patients with a history of CVD. Samples were collected at least 6 months before the CVE and 3–6 months after the CVE. All subjects were matched to controls for age, sex, and medication use. Plasma depletion of the 14 most abundant proteins was followed by bottom-up shotgun proteomics analysis (LC‒MS/MS). Relative changes in protein/peptide abundance were investigated using classical statistical analyses with Perseus and XG-Boost machine learning to compare between groups and to determine the relative importance of identified proteins, respectively. Principal component analysis (PCA) revealed no difference in the global protein and peptide signatures between the control and CVE groups. A total of 150, 239 and 74 protein ID’s showed in comparison between Post Event vs. controls, Event vs. no Event and Pre event vs. Post Event respectively a statistically difference in relative abundance (p < 0.05). Remarkedly a total of 236 proteins ID’s showed a statistical significant difference in relative abundance in the PRE-Event group compared to the control group which could also be confirmed by XGboost machine learning. Here, we demonstrated potential differences in the plasma proteome signature of rheumatic patients with cardiovascular events. Interestingly, this signature may be present prior to CVE’s. However the conclusions must be drawn with caution, since this is a pilot study and further investigation with larger cohorts is warranted to identify potential risk markers that may predict the relative risk of CVEs in rheumatic diseases.
Heart failure with preserved ejection fraction (HFpEF) is a complex syndrome that currently lacks effective biomarkers for early diagnosis and treatment. This study seeks to identify new potential biomarkers for HFpEF using proteomics and machine learning. Plasma samples were collected from 20 patients newly diagnosed age, sex, BMI matched HFpEF and 20 healthy controls (HCs). Proteomic analysis was performed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in data-independent acquisition mode. Differentially expressed proteins (DEPs) were identified and analyzed through enrichment analyses and protein–protein interaction (PPI) network construction. Machine learning methods, including LASSO regression and the Boruta algorithm were used to select candidate biomarkers. The diagnostic value of these proteins was assessed using receiver operating characteristic (ROC) curves and nomogram construction. Expression of candidate proteins was analyzed in immune cells and tissues. Finally, enzyme-linked immunosorbent assay (ELISA) was used to validate the plasma levels of selected proteins. A total of 34 DEPs were identified between HFpEF patients and HCs. Enrichment analyses revealed involvement in acute-phase response and immune pathways. PPI network analysis identified nine hub proteins. Machine learning methods narrowed the candidates to four potential biomarkers: SERPINA1, AFM, SERPINA3, and ITIH4. Among these, SERPINA3 showed the highest diagnostic value with an area under the ROC curve (AUC) of 0.835. ELISA validation confirmed that plasma SERPINA3 levels were significantly elevated in HFpEF patients compared to HCs (p < 0.0001). Our findings suggest that SERPINA3 could serve as a biomarker for HFpEF, Elevated plasma levels of SERPINA3 in HFpEF patients suggest its utility in early diagnosis and may provide insights into the disease’s pathogenesis.
Lysine crotonylation (Kcr) is a novel post-translational modification that is important in functional studies. However, our understanding of Kcr in the developing human fetus brain, heart, kidney, liver, and lung remains restricted. In this study, we used high-resolution LC-MS/MS and high-sensitivity immunoaffinity purification to analyze Kcr in the brain, heart, kidney, liver, and lung of 17-week fetus. A total of 24,947 Kcr modification sites were identified in 5,102 proteins, resulting in the most diverse Kcr proteome of fetus organs ever reported. We investigated the universality and specificity of Kcr during the development of several organs in 17-week fetus using bioinformatics analysis. Kcr proteins were found to be closely associated with the synthesis, transcription and translation of genetic material, energy production and metabolic processes. Importantly, the expression of Kcr proteins in each organ was closely related to the organs’ developmental functions. Furthermore, several highly modified Kcr proteins may be important targets during fetus organ development. This discovery advances our understanding of fetus organ development and establishes the groundwork for future research into the regulatory mechanisms of crotonylation in fetus organ development.
BACKGROUND:Diabetic encephalopathy (DE) is considered as one of the complications of diabetes,which is associated with cognitive impairment in the pathological process of development. Up to now, phospholipid phosphatase related 4 (Plppr4), also known as plasticity related gene 1 (PRG-1) has been revealed its important role in neuroplasticity. However, the underlying mechanisms of Plppr4 on the basis of diabetic-induced cognitive dysfunction (DCD) are still unknown. The aim of current study was to provide insight into molecular mechanism and cellular heterogeneity underlying DCD, and investigate the functional role of PRG-1 involved in this process. METHODS:Combined Single-cell RNA sequencing (scRNA-seq) and RNA transcriptome analysis, the distinct sub-populations, functional heterogeneity as well as potential enriched signaling pathways of hippocampal cells could be elucidated. RESULTS:We identified the sub-cluster of type I spiral ganglion neurons expressed marker gene as Amigo2 in cluster8 and Cnr1 in cluster 9 of hippocampal cells from DCD and the effect of those on neuronal cells interaction. We also found that PRG-1 was involved in the synaptic plasticity regulation of hippocampus via NGF\BDNF-Trkb signaling pathway. In high glucose induced HT22 cells injury model in vitro, we investigated that down-regulated PRG-1 along with down-regulated BDNF and also decreased expression of synapsin-1, PSD-95, SYN which are related to synaptic plasticity; Meanwhile, the Prg-1 targeted miR-18a-LncRNA NONRATG-022419 pairs related with significantly down-regulated expression of PRG-1. CONCLUSION:This study revealed the synaptic plasticity regulation of PRG-1 in DCD, and might provide the therapeutic target and potential biomarkers for early interventions in DCD patients.
Abstract Objective The study aimed to explore the role of metabolism-related proteins and their correlation with clinical data in predicting the prognosis of polycystic ovary syndrome (PCOS). Methods This research involves a secondary analysis of proteomic data derived from endometrial samples collected from our study group, which includes 33 PCOS patients and 7 control subjects. A comprehensive identification and analysis of 4425 proteins were conducted to screened differentially expressed proteins (DEPs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were subsequently performed on the DEPs. To identify independent prognostic metabolism-related proteins, univariate Cox regression and LASSO regression were applied. The expression levels of these proteins were then used to develop a prognostic model, with their predictive accuracy evaluated through receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration curves. Furthermore, we also investigate the correlation between clinical data and prognostic proteins. Results The study identified 285 DEPs between the PCOS and control groups. GO enrichment analysis revealed significant involvement in metabolic processes, while KEGG pathway analysis highlighted pathways such as glycolysis/gluconeogenesis and glucagon signaling. Ten key metabolism-related proteins (ACSL5, ANPEP, CYB5R3, ENOPH1, GLS, GLUD1, LDHB, PLCD1, PYCR2, and PYCR3) were identified as significant predictors of PCOS prognosis. Patients were separated into high and low-risk groups according to the risk score. The ROC curves for predicting outcomes at 6, 28, and 37 weeks demonstrated excellent predictive performance, with AUC values of 0.98, 1.0, and 1.0, respectively. The nomogram constructed from these proteins provided a reliable tool for predicting pregnancy outcomes. DCA indicated a net benefit of the model across various risk thresholds, and the calibration curve confirmed the model’s accuracy. Additionally, we also found BMI exhibited a significant negative correlation with the expression of GLS (r =-0.44, p = 0.01) and CHO showed a significant positive correlation with the expression of LDHB (r = 0.35, p = 0.04). Conclusion The identified metabolism-related proteins provide valuable insights into the prognosis of PCOS. The protein based prognostic model offers a robust and reliable tool for risk stratification and personalized management of PCOS patients.
Tuberculosis drug resistance contributes to the spread of tuberculosis. Immunotherapy is an effective strategy for treating tuberculosis, with the regulation of macrophage-mediated anti-tuberculosis immunity being crucial. Norcantharidin (NCTD), a drug used in tumor immunotherapy, has significant immunomodulatory effects. Thus, NCTD may have an anti-tuberculosis role by regulating immunity. Understanding how NCTD affects the proteome of Mtb-infected macrophages can provide valuable insights into potential treatments. This study aimed to investigate the impact of NCTD (10 μg/mL) on the proteome of macrophages infected with Mtb H37Ra using liquid chromatography-tandem mass spectrometry (LC–MS/MS) analysis. A total of 69 differentially regulated proteins (DRPs) were identified, with 28 up-regulated and 41 down-regulated in the NCTD-treated group. Validation of six DRPs (CLTCL1, VAV1, SP1, TRIM24, MYO1G, and WDR70) by Western blot analysis confirmed the accuracy of the LC–MS/MS method used in this study. NCTD modulates various protein expressions involved in chromatin-modifying enzymes, RHO GTPases activating PAKs, Fc gamma R-mediated phagocytosis, T cell receptor signaling pathway, and antigen processing and presentation. Overall, the research provides new insights into the effects of NCTD on the proteome of Mtb-infected macrophages. The identified changes highlight potential targets for future therapeutic interventions aimed at enhancing host immunity against Mtb infection or developing new anti-TB drugs based on these findings.
INTRODUCTION:Hypertensive intracerebral hemorrhage (HICH) stands out as a critical complication of primary hypertension. Consequently, investigating messenger RNA (mRNA) biomarkers becomes imperative, offering potential targets. This study is conducted for elucidating the expression profile of blood mRNA biomarkers in HICH. METHODS:Twenty-five HICH patients were constituted the HICH group.Twenty-two healthy volunteers recruited and comprised the control group. Peripheral blood cells were extracted to identify candidate mRNA. The identified differential expressions of genes between the two groups were validated, and the potential associations between these differentially expressed genes and adverse events were analyzed. GO and KEGG enrichment of DEGs, Weighted Gene Co-expression Network and Protein Interaction Network were established. target mRNA was screened. RESULTS:The study identified 3163 differentially expressed genes in HICH. 8 candidate mRNA (SPI1, HK3, HCK, SYK, CD14, FCER1G, CYBB, FGR) were pinpointed. Associations with pathways affecting HICH development included HIF-1 signaling, NF-kappa B signaling, and C-type lectin receptor signaling. In the HICH group, higher expressions of HK3, HCK, SYK, CD14, FCER1G, CYBB, and FGR, and lower SPI1 expression compared to the control group. HICH patients experienced high rates of complications: pulmonary infection (84%), epilepsy (16%), enlarged hematoma (20%), gastrointestinal bleeding (48%), malnutrition (84%), and lower limb deep vein thrombosis (DVT) (12%). Factors contributing to pulmonary infection included age and elevated expression of HCK, SYK, CD14, and FGR. SPI1 was associated with epilepsy, while its lower expression correlated with hematoma enlargement. Gastrointestinal bleeding was linked to increased cerebral hemorrhage. Malnutrition was associated with higher age, and expressions of HK3, HCK, SYK, CD14, FCER1G, CYBB, and FGR. Patients with lower limb DVT had elevated expressions of the identified genes. CONCLUSION:In hypertensive intracerebral hemorrhage, there are elevated expressions of HK3, HCK, SYK, CD14, FCER1G, CYBB, and FGR, along with reduced expression of SPI1. Furthermore, age, along with elevated expressions of HCK, SYK, CD14, and FGR, serves as influencing factors contributing to pulmonary infection in patients.
BACKGROUND:The complexity of delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH) may require the simultaneous analysis of variant types of protein biomarkers to describe it more accurately. In this study, we analyzed for the first time the alterations of cerebrospinal fluid (CSF) proteins in patients with aSAH by multi-targeted Olink proteomics, aiming to reveal the pathophysiology of DCI and provide insights into the diagnosis and treatment of aSAH. METHODS:Six aSAH patients and six control patients were selected, and CSF samples were analyzed by Olink Proteomics (including 96-neurology panel and 96-inflammation panel) based on Proximity Extension Assay (PEA). Differentially expressed proteins (DEPs) were acquired and bioinformatics analysis was performed. RESULTS:PCA analysis revealed better intra- and inter-group reproducibility of CSF samples in the control and aSAH groups. 23 neurology-related and 31 inflammation-relevant differential proteins were identified. In the neurology panel, compared to controls, the up-regulated proteins in the CSF of SAH patients predominantly included macrophage scavenger receptor 1 (MSR1), siglec-1, siglec-9, cathepsin C (CTSC), cathepsin S (CTSS), etc. Meanwhile, in the inflammation group, the incremental proteins mainly contained interleukin-6 (IL-6), MCP-1, CXCL10, CXCL-9, TRAIL, etc. Cluster analysis exhibited significant differences in differential proteins between the two groups. GO function enrichment analysis hinted that the differential proteins pertinent to neurology in the CSF of SAH patients were mainly involved in the regulation of defense response, vesicle-mediated transport and regulation of immune response; while the differential proteins related to inflammation were largely connected with the cellular response to chemokine, response to chemokine and chemokine-mediated signaling pathway. Additionally, in the neurology panel, KEGG enrichment analysis indicated that the differential proteins were significantly enriched in the phagosome, apoptosis and microRNAs in cancer pathway. And in the inflammation panel, the differential proteins were mainly enriched in the chemokine signaling pathway, viral protein interaction with cytokine and cytokine receptor and toll-like receptor signaling pathway. CONCLUSIONS:These identified differential proteins reveal unique pathophysiological characteristics secondary to aSAH. Further characterization of these proteins and aberrant pathways in future research could enable their application as potential therapeutic targets and biomarkers for DCI after aSAH.
BACKGROUND:Dirigent (DIR) genes play a key role in the development of organic products in plants. They confer conformational influence on processes that lack stereoselectivity and regioselectivity through processes that are mostly understood. They are required to produce lignans, which are a unique and widely distributed family of plant secondary metabolites with intriguing pharmacological characteristics and potential role in plant development. DIR genes are implicated in the process of lignification and protect plants from environmental stresses, including biotic and abiotic stresses. Nevertheless, no research has been performed on the DIR gene family in Solanum lycopersicum. This study provides detailed information on the DIR gene family in S. lycopersicum. METHODS AND RESULTS:The conserved domain analysis, phylogenetic analysis, evolutionary adaptation, cis-acting elements, proteomic analysis, signal peptide detection, transmembrane potential analysis, sequence identity and similarity analysis, gene assembly, genomic localization, duplication of gene analysis, and evolutionary linkage of 31 potential DIR genes were studied. All these analyses provide a deep understanding of DIR genes in the S. lycopersicum genome that will provide a useful reference for further functional analysis of the DIR genes in S. lycopersicum. CONCLUSION:This research provides an in-depth and comprehensive explanation of the detailed process and structural characterization of DIR genes in the genome of S. lycopersicum, laying the groundwork for future plant genetic engineering and crop development exploration. This work will provide valuable information for identifying DIR genes in higher plants and support future research on the DIR gene family.
Diabetic nephropathy affects a significant proportion of individuals with diabetes, and its progression often leads to cardiovascular disease and infections before the need for renal replacement therapy arises. Empagliflozin has been shown to have various protective effects in cardiovascular disease studies, such as improving diabetic myocardial structure and function, and reducing myocardial oxidative stress. However, the impact of empagliflozin on cardiac protein expression and signaling pathways has not been comprehensively analyzed. To address this gap, we conducted proteome analysis to identify specific protein markers in cardiac tissue from the diabetes model group, including Myh7, Wdr37, Eif3k, Acot1, Acot2, Cat, and Scp2, in cardiac tissue from the diabetes model group. In our drug model, empagliflozin primarily modulates the fat-related metabolic signaling pathway within the heart. Empagliflozin downregulated the protein expression levels of ACOX1, ACADVL and CPT1A in the model group. Overall, our findings demonstrate that empagliflozin provides cardiac protection by targeting metabolic signaling pathways, particularly those related to fat metabolism. Moreover, the identification of cardiac biomarkers in a mouse model of diabetic nephropathy lays the foundation for further exploration of disease biomarkers in cardiac tissue.
NEK10, a serine/threonine/tyrosine kinase belonging to the NEK (NIMA-related kinases) family, has been associated with diverse cellular processes. However, no specific target pathways have been identified. Our previous work knocking down NEK10 in HeLa cells suggested a functional association with mitochondria, as we observed altered mitochondrial morphology, mitochondrial oxygen consumption, mtDNA integrity, and reactive oxygen species levels. To better understand this association, we studied human HAP1 cells fully knockout for NEK10 and confirmed that NEK10 has an important role in mitochondrial homeostasis. We performed the study of mitochondrial respiration, mitochondrial morphology, mitochondrial mass, and mtDNA analysis. Additionally, we showed proteome and phosphoproteome data of crude mitochondrial fraction of Parental and NEK10 KO cells using liquid chromatography-mass spectrometry (LC–MS/MS). In the absence of NEK10 several mitochondrial functions were disturbed. Moreover, proteome and phosphoproteome analyses of mitochondrial fractions showed that NEK10 alters the threonine phosphorylation status of several mitochondrial/endoplasmic reticulum components, including HSP60, NDUFB4, and TOM20. These changes impacted the steady-state levels of a larger group of proteins, preferentially involving respiratory complexes and autophagy pathways. We concluded that NEK10 plays a key role in mitochondrial function, possibly by modulating the phosphorylation status of mitochondrial proteins.
Spatial proteomics is a multidimensional technique that studies the spatial distribution and function of proteins within cells or tissues across both spatial and temporal dimensions. This field multidimensionally reveals the complex structure of the human proteome, including the characteristics of protein spatial distribution, dynamic protein translocation, and protein interaction networks. Recently, as a crucial method for studying protein spatial localization, spatial proteomics has been applied in the clinical investigation of various diseases. This review summarizes the fundamental concepts and characteristics of tissue-level spatial proteomics, its research progress in common human diseases such as cancer, neurological disorders, cardiovascular diseases, autoimmune diseases, and anticipates its future development trends. The aim is to highlight the significant impact of spatial proteomics on understanding disease pathogenesis, advancing diagnostic methods, and developing potential therapeutic targets in clinical research.
Objective The aim of this work was to investigate the immunological effect of MENK by analyzing the protein spectrum and bioinformatics of macrophage RAW264.7, and to explore the relationship between macrophage and ferroptosis. Result We employed proteomic analysis to identify differentially expressed proteins (DEPs) between macrophages and macrophages intervened by MENK. A total of 208 DEPs were identified. Among these, 96 proteins had upregulated expression and 112 proteins had downregulated expression. Proteomic analysis revealed a significant enrichment of DEPs associated with iron metabolism. The identification of hub genes was conducted using KEGG pathway diagrams and protein-protein interaction (PPI) analysis. The hub genes identified in this study include HMOX1 and Ferritin (FTH and FTL). A correlation was established between HMOX1, FTH, and FTL in the GO and KEGG databases. The results of PCR, WB and immunofluorescence showed that MENK downregulated the level of HMOX1 and FTH. Conclusion MENK had the potential to become an adjuvant chemotherapy drug by regulating iron metabolism in macrophages, reducing levels of HMOX1 and ferritin. We proposed an innovative research direction on the therapeutic potential of MENK, focusing on the relationship between ferroptosis and macrophage activity.
BACKGROUND:Patients with immunodeficiency virus-1 (HIV-1) infection are challenging to be cured completely due to the existence of HIV-1 latency reservoirs. However, the knowledge of the mechanisms and biomarkers associated with HIV-1 latency is limited. Therefore, identifying proteins related to HIV-1 latency could provide new insights into the underlying mechanisms of HIV-1 latency, and ultimately contribute to the eradication of HIV reservoirs.METHODS:An Isobaric Tags for Relative and Absolute Quantification (iTRAQ)-labeled subcellular proteomic study was performed on an HIV-1 latently infected cell model (U1, a HIV-1-integrated U937 cell line) and its control (U937). Differentially expressed proteins (DEPs) were analyzed using STRING-DB. Selected DEPs were further evaluated by western blotting and multiple reaction monitoring technology in both cell model and patient-derived cluster of differentiation 4 (CD4)+ T cells. Finally, we investigated the relationship between a specific DEP lysosome-associated membrane glycoprotein 2 (LAMP2) and HIV-1 reactivation by panobinostat or lysosome regulation by a lysosomotropic agent hydroxychloroquine in U1 and U937 cells.RESULTS:In total, 110 DEPs were identified in U1 cells comparing to U937 control cells. Bioinformatics analysis suggested associations of the altered proteins with the immune response and endosomal/lysosomal pathway. LAMP2, leukocyte surface antigen CD47, CD55, and ITGA6 were downregulated in HIV-1 latent cells. Downregulated LAMP2 was further confirmed in resting CD4+ T cells from patients with latent HIV-1 infection. Furthermore, both HIV-1 reactivation by panobinostat and stimulation with hydroxychloroquine upregulated LAMP2 expression.CONCLUSIONS:Our results indicated the involvement of the endosomal/lysosomal pathway in HIV-1 latency in macrophage cell model. The down-modulation of LAMP2 was associated with HIV latency, and the restoration of LAMP2 expression accompanied the transition of viral latency to active infection. This study provides new insights into the mechanism of HIV-1 latency and potential strategies for eradicating HIV-1 reservoirs by targeting LAMP2 expression.
Background Tepary bean ( Phaseolus acutifolius A. Gray) is one of the five species domesticated from the genus Phaseolus with genetic resistance to biotic and abiotic stress. To understand the mechanisms underlying drought responses in seed storage proteins germinated on water and polyethylene glycol (PEG-6000) at -0.49 MPa, we used a proteomics approach to identify potential molecular target proteins associated with the low water potential stress response. Methods Storage proteins from cotyledons of Tepary bean seeds germinated at 24, 48 and 72 h on water and PEG-6000 at -0.49 MPa were analyzed by one-dimensional electrophoresis (DE) with 2-DE analysis and shotgun mass spectrometry. Using computational database searching and bioinformatics analyses, we performed Gene Ontology (GO) and protein interactome (functional protein association network) String analyses. Results Comparative analysis showed that the effect of PEG-6000 on root growth was parallel to that on germination. Based on the SDS‒PAGE protein banding patterns and 2-DE analysis, ten differentially abundant seed storage proteins showed changes in storage proteins, principally in the phaseolin and lectin fractions. We found many proteins that are recognized as drought stress-responsive proteins, and several of them are predicted to be intrinsically related to abiotic stress. The shotgun analysis searched against UniProt’s legume database, and Gene Ontology (GO) analysis indicated that most of the seed proteins were cytosolic, with catalytic activity and associated with carbohydrate metabolism. The protein‒protein interaction networks from functional enrichment analysis showed that phytohemagglutinin interacts with proteins associated with the degradation of storage proteins in the cotyledons of common bean during germination. Conclusion These findings suggest that Tepary bean seed proteins provide valuable information with the potential to be used in genetic improvement and are part of the drought stress response, making our approach a potentially useful strategy for discovering novel drought-responsive proteins in other plant models.
Hair is an advantageous biological sample due to its recordable, collectable, and storable nature. Hair's primary components are keratin and keratin-associated proteins. Owing to its abundance of cystine, keratin possesses impressive mechanical strength and chemical stability, formed by creating disulfide bonds as crosslinks within the protein peptide chain. Furthermore, keratin is cross-linked with keratin-associated proteins to create a complex network structure that provides the hair with strength and rigidity. Protein extraction serves as the foundation for hair analysis research. Bleaching hair causes damage to the structure between keratin and keratin-associated proteins, resulting in texture issues and hair breakage. This article outlines various physical treatment methods and lysate analysis that enhance the efficiency of hair protein extraction. The PLEE method achieves a three-fold increase in hair protein extraction efficiency when using a lysis solution containing SDS and combining high temperatures with intense shaking, compared to previous methods found in literature. We utilized the PLEE method to extract hair from both normal and damaged groups. Normal samples identified 156-157 proteins, including 51 keratin and keratin-associated proteins. The damaged group consisted of 155-158 identified proteins, of which 48-50 were keratin and keratin-associated proteins. Bleaching did not cause any notable difference in the protein identification of hair. However, it did reduce coverage of keratin and keratin-associated proteins significantly. Our hair protein extraction method provides extensive coverage of the hair proteome. Our findings indicate that bleaching damage results in subpar hair quality due to reduced coverage of protein primary sequences in keratin and keratin-associated proteins.
Background The role of platelets in disease progression as well as the function of platelets as part of the haemostatic and immunological system in patients with liver cirrhosis is only incompletely understood. This is partly due to difficulties in assessing platelet function. Proteome analyses of platelets have been used to further investigate the role of platelets in other diseases. Aim To assess possible changes in the platelet proteome during different stages of alcohol induced liver cirrhosis compared to healthy donors. Patients and methods A 45 ml blood sample was drawn from 18 participants aged 18–80 years evenly divided into three groups of healthy donors, patients with less advanced alcohol induced liver cirrhosis (Child-Pugh < 7) and patients with advanced liver cirrhosis (Child-Pugh > 10). The blood was processed to isolate platelets and perform subsequent two-dimensional gel-electrophoresis using a SYPRO™ Ruby dye. After computational analysation significantly in- or decreased protein spots (defined as a two-fold abundance change between different study cohorts and ANOVA < 0.05) were identified via liquid chromatography–mass spectrometry (LCMS) and searching against human protein databases. Results The comparative analysis identified four platelet proteins with progressively decreased protein expression in patients with liver cirrhosis. More specifically Ras-related protein Rab-7a (Rab-7a), Ran-specific binding protein 1 (RANBP1), Rho GDP-dissociation inhibitor 1 (RhoGDI1), and 14–3-3 gamma. Conclusion There is significant change in protein expression in the platelet proteome throughout the disease progression of alcohol induced liver cirrhosis. The identified proteins are possibly involved in haemostatic and immunoregulatory function of platelets.
Objective Numerous evidence has highlighted the differences between primary tumors and metastases. Nonetheless, the differences in exosomal proteins derived from primary tumor and metastases remain elusive. Here, we aimed to identify differentially expressed exosomal proteins from primary canine mammary gland tumor and metastases to understand how they shape their own tumor microenvironment. Methods We clearly distinguished primary canine mammary gland tumors (CHMp) from metastases (CHMm) and profiled the proteins within their secreted exosomes using LC–MS/MS. Moreover, the abundance of glycolysis enzymes (GPI, LDHA) in CHMp exosome was verified with Western blotting, To broaden the scope, we extended to human colorectal cancer-derived exosomes (SW480 vs. SW620) for comparison. Results We identified significant differences in 87 and 65 proteins derived from CHMp and CHMm, respectively. Notably, glycolysis enzymes (GPI, LDHA, LDHB, TPI1, and ALDOA) showed specific enrichment in exosomes from the primary tumor. Conclusion We observed significant differences in the cellular proteome between primary tumors and metastases, and intriguingly, we identified a parallel heterogeneity the protein composition of exosomes. Specifically, we reported that glycolysis enzymes were significantly enriched in CHMp exosomes compared to CHMm exosomes. We further demonstrated that this quantitative difference in glycolysis enzymes persisted across primary and metastases, extending to human colorectal cancer-derived exosomes (SW480 vs. SW620). Our findings of the specific enrichment of glycolysis enzymes in primary tumor-derived exosomes contribute to a better understanding of tumor microenvironment modulation and heterogeneity between primary tumors and metastases.
