Proteomics turns functional

Integrative analysis of network pharmacology and proteomics reveal the protective effect of Xiaoqinglong Decotion on neutrophilic asthma

ETHNOPHARMACOLOGICAL RELEVANCE

Xiaoqinglong Decotion (XQLD) is a commonly used Chinese herbal formula in clinical practice, especially for allergic diseases such as asthma. However, its intrinsic mechanism for the treatment of neutrophilic asthma (NA) remains unclear.

AIM OF THE STUDY

The aim of this study was to evaluate the efficacy and potential mechanisms of XQLD on NA using network pharmacology and in vivo experiments.

MATERIALS AND METHODS

First, the active compounds, potential targets and mechanisms of XQLD against NA were initially elucidated by network pharmacology. Then, OVA/CFA-induced NA mice were treated with XQLD to assess its efficacy. Proteins were then analyzed and quantified using a Tandem Mass Tags approach for differentially expressed proteins (DEPs) to further reveal the mechanisms of NA treatment by XQLD. Finally, the hub genes, critical DEPs and potential pathways were validated.

RESULTS

176 active compounds and 180 targets against NA were identified in XQLD. Protein-protein interaction (PPI) network revealed CXCL10, CX3CR1, TLR7, NCF1 and FABP4 as hub genes. In vivo experiments showed that XQLD attenuated inflammatory infiltrates, airway mucus secretion and remodeling in the lungs of NA mice. Moreover, XQLD significantly alleviated airway neutrophil inflammation in NA mice by decreasing the expression of IL-8, MPO and NE. XQLD also reduced the levels of CXCL10, CX3CR1, TLR7, NCF1 and FABP4, which are closely associated with neutrophil inflammation. Proteomics analysis identified 28 overlapping DEPs in the control, NA and XQLD groups, and we found that XQLD inhibited ferroptosis signal pathway (elevated GPX4 and decreased ASCL3) as well as the expression of ARG1, MMP12 and SPP1, while activating the Rap1 signaling pathway.

CONCLUSION

This study revealed that inhibition of ARG1, MMP12 and SPP1 expression as well as ferroptosis pathways, and activation of the Rap1 signaling pathway contribute to the therapeutic effect of XQLD on NA.

Blueberry extract and its bioactive compounds mitigate oxidative stress and suppress human lung cancer cell (A549) growth by modulating the expression of p53/EGFR/STAT3/IL6-mediated signaling molecules

Bioactive phytocompounds are crucial components in all plants. Since the time of traditional medicine, the utilization of plants has been grounded in the potential of these bioactive compounds to treat or manage specific illnesses. These natural bioactive compounds have sparked growing interest in employing medicinal plants for addressing various conditions, such as inflammatory diseases, diabetes, and cancer. This study focuses on assessing the qualitative phytochemical composition, antioxidant potential, and cytotoxic effects of blueberry (Vaccinium sect. Cyanococcus) extract using three different solvents, namely water, ethanol, and methanol. The extract exhibited notable antioxidant activities, as evidenced by DPPH and H2O2 free radical scavenging assays. The cell viability assay also demonstrated cell growth inhibition in A549 cells. Furthermore, nine specific phytocompounds sourced from existing literature were selected for molecular docking studies against CDK6 and, AMPK key protein kinases which enhance the cancer progression. The molecular docking results also revealed favorable binding scores, with a high score of -9.5 kcal/mol in CDK6 protein and a maximum score of AMPK with targets of -8.8 kcal/mol. The selected phytocompounds' pharmacodynamic properties such as ADMET also supported the study. Furthermore, rutin stated that pre-dominantly present in blueberry plants shows a potent cytotoxicity effect in A549 cells. Functional annotations by bioinformatic analysis for rutin also revealed the strong enrichment in the involvement of PI3K/AKT1/STAT, and p53 signaling pathways. Based on this analysis, the identified rutin and other compounds hold a promising anticancer activity. Overall, the comprehensive evaluation of both in vitro and in silico data suggests that the Vaccinium sect. Cyanococcus extract could serve as a valuable source of pharmaceutical agents and may prove effective in future therapeutic applications.

From the outer space to the inner cell: deconvoluting the complexity of Bacillus subtilis disulfide stress responses by redox state and absolute abundance quantification of extracellular, membrane, and cytosolic proteins

Understanding cellular mechanisms of stress management relies on omics data as a valuable resource. However, the lack of absolute quantitative data on protein abundances remains a significant limitation, particularly when comparing protein abundances across different cell compartments. In this study, we aimed to gain deeper insights into the proteomic responses of the Gram-positive model bacterium Bacillus subtilis to disulfide stress. We determined proteome-wide absolute abundances, focusing on different sub-cellular locations (cytosol and membrane) as well as the extracellular medium, and combined these data with redox state determination. To quantify secreted proteins in the culture medium, we developed a simple and straightforward protocol for the absolute quantification of extracellular proteins in bacteria. We concentrated extracellular proteins, which are highly diluted in the medium, using StrataClean beads along with a set of standard proteins to determine the extent of the concentration step. The resulting data set provides new insights into protein abundances in different sub-cellular compartments and the extracellular medium, along with a comprehensive proteome-wide redox state determination. Our study offers a quantitative understanding of disulfide stress management, protein production, and secretion in B. subtilis.

IMPORTANCE

Stress responses play a crucial role in bacterial survival and adaptation. The ability to quantitatively measure protein abundances and redox states in different cellular compartments and the extracellular environment is essential for understanding stress management mechanisms. In this study, we addressed the knowledge gap regarding absolute quantification of extracellular proteins and compared protein concentrations in various sub-cellular locations and in the extracellular medium under disulfide stress conditions. Our findings provide valuable insights into the protein production and secretion dynamics of B. subtilis, shedding light on its stress response strategies. Furthermore, the developed protocol for absolute quantification of extracellular proteins in bacteria presents a practical and efficient approach for future studies in the field. Overall, this research contributes to the quantitative understanding of stress management mechanisms and protein dynamics in B. subtilis, which can be used to enhance bacterial stress tolerance and protein-based biotechnological applications.

Integrative multi-omics characterization reveals sex differences in glioblastoma

BACKGROUND

Glioblastoma (GBM) is the most common and lethal primary brain tumor in adults, with limited treatment modalities and poor prognosis. Recent studies have highlighted the importance of considering sex differences in cancer incidence, prognosis, molecular disparities, and treatment outcomes across various tumor types, including colorectal adenocarcinoma, lung adenocarcinoma, and GBM.

METHODS

We performed comprehensive analyses of large-scale multi-omics data (genomic, transcriptomic, and proteomic data) from TCGA, GLASS, and CPTAC to investigate the genetic and molecular determinants that contribute to the unique clinical properties of male and female GBM patients.

RESULTS

Our results revealed several key differences, including enrichments of MGMT promoter methylation, which correlated with increased overall and post-recurrence survival and improved response to chemotherapy in female patients. Moreover, female GBM exhibited a higher degree of genomic instability, including aneuploidy and tumor mutational burden. Integrative proteomic and phosphor-proteomic characterization uncovered sex-specific protein abundance and phosphorylation activities, including EGFR activation in males and SPP1 hyperphosphorylation in female patients. Lastly, the identified sex-specific biomarkers demonstrated prognostic significance, suggesting their potential as therapeutic targets.

CONCLUSIONS

Collectively, our study provides unprecedented insights into the fundamental modulators of tumor progression and clinical outcomes between male and female GBM patients and facilitates sex-specific treatment interventions. Highlights Female GBM patients were characterized by increased MGMT promoter methylation and favorable clinical outcomes compared to male patients. Female GBMs exhibited higher levels of genomic instability, including aneuploidy and TMB. Each sex-specific GBM is characterized by unique pathway dysregulations and molecular subtypes. EGFR activation is prevalent in male patients, while female patients are marked by SPP1 hyperphosphorylation.

Shu: visualization of high-dimensional biological pathways

SUMMARY

Shu is a visualization tool that integrates diverse data types into a metabolic map, with a focus on supporting multiple conditions and visualizing distributions. The goal is to provide a unified platform for handling the growing volume of multi-omics data, leveraging the metabolic maps developed by the metabolic modeling community. In addition, shu offers a streamlined python API, based on the Grammar of Graphics, for easy integration with data pipelines.

AVAILABILITY AND IMPLEMENTATION

Freely available at https://github.com/biosustain/shu under MIT/Apache 2.0 license. Binaries are available in the release page of the repository and the web application is deployed at https://biosustain.github.io/shu.

Personalized Drug Therapy: Innovative Concept Guided With Proteoformics

Personalized medicine can reduce adverse effects, enhance drug efficacy, and optimize treatment outcomes, which represents the essence of personalized medicine in the pharmacy field. Protein drugs are crucial in the field of personalized drug therapy and are currently the mainstay, which possess higher target specificity and biological activity than small-molecule chemical drugs, making them efficient in regulating disease-related biological processes, and have significant potential in the development of personalized drugs. Currently, protein drugs are designed and developed for specific protein targets based on patient-specific protein data. However, due to the rapid development of two-dimensional gel electrophoresis and mass spectrometry, it is now widely recognized that a canonical protein actually includes multiple proteoforms, and the differences between these proteoforms will result in varying responses to drugs. The variation in the effects of different proteoforms can be significant and the impact can even alter the intended benefit of a drug, potentially making it harmful instead of lifesaving. As a result, we propose that protein drugs should shift from being targeted through the lens of protein (proteomics) to being targeted through the lens of proteoform (proteoformics). This will enable the development of personalized protein drugs that are better equipped to meet patients' specific needs and disease characteristics. With further development in the field of proteoformics, individualized drug therapy, especially personalized protein drugs aimed at proteoforms as a drug target, will improve the understanding of disease mechanisms, discovery of new drug targets and signaling pathways, provide a theoretical basis for the development of new drugs, aid doctors in conducting health risk assessments and making more cost-effective targeted prevention strategies conducted by artificial intelligence/machine learning, promote technological innovation, and provide more convenient treatment tailored to individualized patient profile, which will benefit the affected individuals and society at large.

Quantitative Proteomics Reveals Manganese Alleviates Heat Stress of Broiler Myocardial Cells via Regulating Nucleic Acid Metabolism

Heat stress threatens severely cardiac function by caused myocardial injury in poultry. Our previous study has showed that manganese (Mn) has a beneficial effect on heat-stress resistance of broiler. Therefore, we tried to confirm the alleviation mechanism through proteomic analysis after heat stress exposure to primary broiler myocardial cells pretreated with Mn. The experiment was divided into four groups: CON group (37 °C, cells without any treatment), HS group (43 °C, cells treatment with heat stress for 4 h), HS+MnCl2 group (cells treated with 20 μM MnCl2 before heat stress), and HS+Mn-AA group (cells treated with 20 μM Mn compound amino acid complex before heat stress). Proteome analysis using DIA identified 300 differentially expressed proteins (DEPs) between CON group and HS group; 93 and 121 DEPs were identified in inorganic manganese treatment group and organic manganese treatment group, respectively; in addition, there were 53 DEPs identified between inorganic and organic manganese group. Gene Ontology (GO) analysis showed that DEPs were mainly involved in binding, catalytic activity, response to stimulus, and metabolic process. DEPs of manganese pretreatment involved in a variety of biological regulatory pathways, and significantly influenced protein processing and repair in endoplasmic reticulum, apoptosis, and DNA replication and repair. These all seem to imply that manganese may help to resist cell damage induced by heat stress by regulating key node proteins. These findings contribute to a better understanding of the effects of manganese on overall protein changes during heat-stress and the possible mechanisms, as well as how to better use manganese to protect heart function in high temperature.

Label-free proteomic comparison reveals ciliary and nonciliary phenotypes of IFT-A mutants

DIFFRAC is a powerful method for systematically comparing proteome content and organization between samples in a high-throughput manner. By subjecting control and experimental protein extracts to native chromatography and quantifying the contents of each fraction using mass spectrometry, it enables the quantitative detection of alterations to protein complexes and abundances. Here, we applied DIFFRAC to investigate the consequences of genetic loss of Ift122, a subunit of the intraflagellar transport-A (IFT-A) protein complex that plays a vital role in the formation and function of cilia and flagella, on the proteome of Tetrahymena thermophila. A single DIFFRAC experiment was sufficient to detect changes in protein behavior that mirrored known effects of IFT-A loss and revealed new biology. We uncovered several novel IFT-A-regulated proteins, which we validated through live imaging in Xenopus multiciliated cells, shedding new light on both the ciliary and non-ciliary functions of IFT-A. Our findings underscore the robustness of DIFFRAC for revealing proteomic changes in response to genetic or biochemical perturbation.

Designed Nanomaterials-Assisted Proteomics and Metabolomics Analysis for In Vitro Diagnosis

In vitro diagnosis (IVD) is pivotal in modern medicine, enabling early disease detection and treatment optimization. Omics technologies, particularly proteomics and metabolomics, offer profound insights into IVD. Despite its significance, omics analyses for IVD face challenges, including low analyte concentrations and the complexity of biological environments. In addition, the direct omics analysis by mass spectrometry (MS) is often hampered by issues like large sample volume requirements and poor ionization efficiency. Through manipulating their size, surface charge, and functionalization, as well as the nanoparticle-fluid incubation conditions, nanomaterials have emerged as a promising solution to extract biomolecules and enhance the desorption/ionization efficiency in MS detection. This review delves into the last five years of nanomaterial applications in omics, focusing on their role in the enrichment, separation, and ionization analysis of proteins and metabolites for IVD. It aims to provide a comprehensive update on nanomaterial design and application in omics, highlighting their potential to revolutionize IVD.

Proteomics provides insights into the theranostic potential of extracellular vesicles

Extracellular vesicles (EVs) encompass a diverse range of membranous structures derived from cells, including exosomes and microvesicles. These vesicles are present in biological fluids and play vital roles in various physiological and pathological processes. They facilitate intercellular communication by enabling the exchange of proteins, lipids, and genetic material between cells. Understanding the cellular processes that govern EV biology is essential for unraveling their physiological and pathological functions and their potential clinical applications. Despite significant advancements in EV research in recent years, there is still much to learn about these vesicles. The advent of improved mass spectrometry (MS)-based techniques has allowed for a deeper characterization of EV protein composition, providing valuable insights into their roles in different physiological and pathological conditions. In this chapter, we provide an overview of proteomics studies conducted to identify the protein contents of EVs, which contribute to their therapeutic and pathological features. We also provided evidence on the potential of EV proteome contents as biomarkers for early disease diagnosis, progression, and treatment response, as well as factors that influence their composition. Additionally, we discuss the available databases containing information on EV proteome contents, and finally, we highlight the need for further research to pave the way toward their utilization in clinical settings.

Quantitative proteomics reveals plasma protein profile and potential pathways in pulmonary tuberculosis patients with and without diabetes

BACKGROUND

The coexistence of pulmonary tuberculosis (PTB) and diabetes mellitus (DM) has emerged as a significant global public health concern. Patients with DM are at higher risk of developing PTB, and PTB is one of the important factors that exacerbate the development of DM. However, the impact of DM on the protein profile and underlying pathways in PTB patients is unclear.

METHODS

We systematically used data-independent acquisition (DIA)-based liquid chromatography - tandem mass spectrometry (LC-MS/MS) to identify differentially expressed proteins (DEPs) in plasma samples from PTB patients, DM combined with PTB patients, and healthy controls. Then these DEPs were analyzed by bioinformatics.

RESULTS

Our analysis identified 268 proteins, the results indicated that DEPs in the PTB group as well as in the DM-PTB group were mainly involved in immune responses, complement and coagulation cascade and cholesterol metabolic pathways compared to healthy controls.

CONCLUSIONS

We analyzed the plasma protein profiles of PTB, DM-PTB, and HC groups using proteomics techniques and identified potential pathways for PTB patients with and without DM. This provides valuable clues to explore the impact of DM on PTB.

Cell and tissue imaging by secondary ion mass spectrometry

This Tutorial focuses on the use of secondary ion mass spectrometry for the analysis of cellular and tissue samples. The Tutorial aims to cover the considerations in sample preparation analytical set up and some specific aspects of data interpretation associated with such analysis.

Combining proteomic markers to construct a logistic regression model for polycystic ovary syndrome

Introduction

Proteomics technology has been used in various fields in recent years for the Q6 exploration of novel markers and the study of disease pathogenesis, and has become one of the most important tools for researchers to explore unknown areas. However, there are fewer studies related to the construction of clinical models using proteomics markers.

Methods

In our previous study we used DIA proteomics to screen for proteins that were significant in 31 PCOS patients compared to women of normal reproductive age. In this study, we used logistic regression among these protein markers to screen out variables with diagnostic value and constructed logistic regression models.

Results

We constructed a logistic model using these protein markers, where HIST1H4A (OR=1.037) was an independent risk factor for polycystic ovary syndrome and TREML1 (OR=0.976) were protective factors for the disease. The logistic regression model equation is: Logit (PCOS) =0.036*[HIST1H4A]-0.024*[TREML1]-16.368. The ROC curve analyzing the diagnostic value of the model has an AUC value of 0.977 and a Youden index of0.903, which gives a cutoff value of 0.518 at this point. The model has a sensitivity of 93.5% and a specificity of 96.8%. Calibration curves show fair consistency of the model.

Discussion

Our study is the first to use proteomic results with clinical biochemical data to construct a logistic regression model, and the model is consistent. However, our study still needs a more complete sample to confirm our findings.

Study on the Relationship Between Differentially Expressed Proteins in Breast Cancer and Lymph Node Metastasis

INTRODUCTION

Lymph node metastasis is a cause of poor prognosis in breast cancer. Mass spectrometry-based proteomics aims to map the protein landscapes of biological samples and profile tumors more comprehensively. Here, proteomics was employed to identify differentially expressed proteins (DEPs) that were associated with lymph node metastasis.

METHODS

Tandem mass tag (TMT) quantitative proteomic approaches were applied for extensive profiling of conditioned medium of MDA-MB-231 and MCF7 cell lines and serums of patients who did or did not have lymph node metastasis, and DEPs were analyzed by bioinformatics. Furthermore, potential secreted or membrane proteins MUC5AC, ITGB4, CTGF, EphA2, S100A4, PRDX2, and PRDX6 were selected for verification in 114 tissue microarray samples of breast cancer using the immunohistochemical method. The relevant data was analyzed and processed by independent sample t test, chi-square test, or Fisher's exact test using SPSS 22.0 software.

RESULTS

In the conditioned medium of MDA-MB-231 cell lines, 154 proteins were upregulated, while 136 were downregulated compared to those of MCF7. In the serum of patients with breast cancer and lymph node metastasis, 17 proteins were upregulated, and 5 proteins were downregulated compared to those without lymph node metastasis. Furthermore, according to tissue verification, CTGF, EphA2, S100A4, and PRDX2 were associated with breast cancer lymph node metastasis.

CONCLUSION

Our study provides a new perspective for the understanding of the role of DEPs (especially CTGF, EphA2, S100A4, and PRDX2) in the development and metastasis of breast cancer. They could become potential diagnostic and prognostic biomarkers and therapeutic targets.

Metabolomic and proteomic analyses of primary Sjogren's syndrome

The pathogenesis of primary Sjogren's syndrome (pSS) has not been fully elucidated. We explored differentially expressed proteins and metabolic pathways in pSS using proteomics and metabolomics. 456 named proteins in total were identified, among which 50 were significantly changed in the pSS. Altered proteins were significantly associated with signaling pathways such as antigen processing and presentation, human immunodeficiency virus 1 infection, and FC gamma R-mediated phagocytosis. Meanwhile, 12 proteins, such as SH3BGRL3, TPM4, and CA1, can be used as potential clinical molecular markers. Moreover, 128 metabolites were significantly expressed in the pSS group. A total of 96 pathways were significantly enriched including central carbon metabolism in cancer, taurine and hypotaurine metabolism, and ABC transporters. Notably, both proteomics and metabolomics enriched glycolysis/gluconeogenesis metabolism, pentose phosphate pathway, and glutathione metabolism pathways. In this study, the progression mechanism of pSS was analyzed and novel biomarkers were identified by proteomics and metabolomics.

Vinculin Identified as a Potential Biomarker in Hand-Arm Vibration Syndrome Based on iTRAQ and LC-MS/MS-Based Proteomic Analysis

Local vibration can induce vascular injuries, one example is the hand-arm vibration syndrome (HAVS) caused by hand-transmitted vibration (HTV). Little is known about the molecular mechanism of HAVS-induced vascular injuries. Herein, the iTRAQ (isobaric tags for relative and absolute quantitation) followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomics approach was applied to conduct the quantitative proteomic analysis of plasma from specimens with HTV exposure or HAVS diagnosis. Overall, 726 proteins were identified in iTRAQ. 37 proteins upregulated and 43 downregulated in HAVS. Moreover, 37 upregulated and 40 downregulated when comparing severe HAVS and mild HAVS. Among them, Vinculin (VCL) was found to be downregulated in the whole process of HAVS. The concentration of vinculin was further verified by ELISA, and the results suggested that the proteomics data was reliable. Bioinformative analyses were used, and those proteins mainly engaged in specific biological processes like binding, focal adhesion, and integrins. The potential of vinculin application in HAVS diagnosis was validated by the receiver operating characteristic curve.

Characterization of Xenobiotic and Steroid Disposition Potential of Human Placental Tissue and Cell Lines (BeWo, JEG-3, JAR, and HTR-8/SVneo) by Quantitative Proteomics

The placenta is a fetal organ that performs critical functions to maintain pregnancy and support fetal development, including metabolism and transport of xenobiotics and steroids between the maternal-fetal unit. In vitro placenta models are used to study xenobiotic and steroid disposition, but how well these models recapitulate the human placenta is not well understood. We first characterized the abundance of proteins involved in xenobiotic and steroid disposition in human placental tissue. In pooled human placenta, the following xenobiotic and steroid disposition proteins were detected (highest to lowest), 1) enzymes: glutathione S-transferase P, carbonyl reductase 1, aldo-keto reductase 1B1, hydroxysteroid dehydrogenases (HSD3B1 and HSD11B1), aromatase, epoxide hydrolase 1 (EPHX1) and steryl-sulfatase, and 2) transporters: monocarboxylate transporters (MCT1 and 4), organic anion transporting polypeptide 2B1, organic anion transporter 4, and breast cancer resistance protein (BCRP). Then, the tissue proteomics data were compared with four placental cell lines (BeWo, JEG-3, JAR, and HTR-8/SVneo). The differential global proteomics analysis revealed that the tissue and cell lines shared 1420 cytosolic and 1186 membrane proteins. Although extravillous trophoblast and cytotrophoblast marker proteins were detected in all cell lines, only BeWo and JEG-3 cells expressed the syncytiotrophoblast marker, chorionic somatomammotropin hormone 1. BeWo and JEG-3 cells expressed most target proteins including aromatase, HSDs, EPHX1, MCT1, and BCRP. JEG-3 cells treated with commonly detected phthalates in human biofluids showed dysregulation of steroid pathways. The data presented here show that BeWo and JEG-3 cells are closer to the placental tissue for studying xenobiotic and steroid disposition. SIGNIFICANCE STATEMENT: This is the first study to compare proteomics data of human placental tissue and cell lines (BeWo, JAR, JEG-3, and HTR-8/SVneo). The placental cell line and tissue proteomes are vastly different, but BeWo and JEG-3 cells showed greater resemblance to the tissue in the expression of xenobiotic and steroid disposition proteins. These data will assist researchers to select an optimum cell model for mechanistic investigations on xenobiotic and steroid disposition in the placenta.

Modulation of pulmonary desmosomes by inhaler therapy in preterm-born children with bronchopulmonary dysplasia

Despite evidence demonstrating persistent lung function deficits in preterm-born children, especially in those who had bronchopulmonary dysplasia (BPD) in infancy, the underlying biological mechanisms explaining these lung function deficits remain poorly understood. We characterised the exhaled breath condensate (EBC) proteome in preterm-born children, with and without BPD; and before and after inhaler treatment. EBC from children aged 7-12 years, from the Respiratory Health Outcomes in Neonates (RHiNO) study, were analysed by Nano-LC Mass Spectrometry with Tandem Mass Tag labelling. Children with percent predicted forced expiratory volume in 1 second ≤ 85% were enrolled to a 12-week blinded randomised trial of inhaled corticosteroids alone (ICS) or with long-acting β₂-agonist (ICS/LABA) or placebo. EBC was analysed from 218 children at baseline, and 46 children received randomised inhaled therapy. 210 proteins were detected in total. For the 19 proteins present in every sample, the desmosome proteins: desmoglein-1, desmocollin-1 and plakoglobin were significantly decreased, and cytokeratin-6A was increased in preterm-born children with BPD when compared to preterm- and term-born controls. ICS/LABA treatment significantly increased abundance of desmoglein-1, desmocollin-1 and plakoglobin in the BPD group with low lung function, and significantly increased plakoglobin in those without BPD. No differences were noted after ICS treatment. Exploratory analyses of proteins not detected in all samples suggested decreased abundance of several antiproteases. This study provides proteomic evidence of ongoing pulmonary structural changes with decreased desmosomes in school-aged preterm-born children with BPD and low lung function, which was reversed with combined inhaled corticosteroids and long-acting β₂-agonists therapy.

Inter- and intratumoral proteomics and glycosaminoglycan characterization of ALK rearranged lung adenocarcinoma tissues: a pilot study

Lung cancer is one of the most common types of cancer with limited therapeutic options, therefore a detailed understanding of the underlying molecular changes is of utmost importance. In this pilot study, we investigated the proteomic and glycosaminoglycan (GAG) profile of ALK rearranged lung tumor tissue regions based on the morphological classification, mucin and stromal content. Principal component analysis and hierarchical clustering revealed that both the proteomic and GAG-omic profiles are highly dependent on mucin content and to a lesser extent on morphology. We found that differentially expressed proteins between morphologically different tumor types are primarily involved in the regulation of protein synthesis, whereas those between adjacent normal and different tumor regions take part in several other biological processes (e.g. extracellular matrix organization, oxidation-reduction processes, protein folding) as well. The total amount and the sulfation profile of heparan sulfate and chondroitin sulfate showed small differences based on morphology and larger differences based on mucin content of the tumor, while an increase was observed in both the total amount and the average rate of sulfation in tumors compared to adjacent normal regions.

Comparative proteomics analysis of adult Haemonchus contortus isolates from Ovis ammon

Haemonchus contortus is an important parasite that causes disease that seriously endangers ruminant animals cattle, sheep, goat, and camel. Here, we compared the proeomics analysis of three adult Haemonchus contortus isolates from mouflons (Ovis ammon). A total of 1,299 adult worm proteins were identified, and 461 proteins were quantified, of which 82 (108), 83 (97), and 97 (86) significantly upregulated (downregulated) differentially expressed proteins (DEPs) were detected among pairwise comparisons (1-vs.-3, 2-vs.-3, and 2-vs.-1). Liquid chromatography–tandem mass spectrometry (LC−MS/MS) and bioinformatic analysis indicated that these DEPs are mainly concentrated in cellular composition, molecular function, biological function, and catabolism pathways. In addition, Gene Ontology (GO) classification and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were carried out to screen the DEPs. The main biological processes involved were nucleotide, nucleotide phosphate, ribonucleotide, purine-containing compound, purine ribonucleotide, single-organism, oxoacid, organic, carboxylic, oxoacid metabolic processes and single-organism catabolic processes. The majority of KEGG pathways were found to be related to metabolic pathways, biosynthesis of secondary metabolites, biosynthesis of antibiotics, carbon metabolism, and microbial metabolism in diverse environments. Moreover, we also found differences in the expression of some important or novel regulatory proteases, such as serine hydroxymethyl transferase (SHMT), dihydrolipoyl dehydrogenase (DLD), and transket pyr domain-containing protein (TKPD). In summary, label-free proteomic analysis of adult H. contortus worms displayed significant differences in three different individual isolates, which helps to improve our understanding of the growth and metabolic mechanisms of H. contortus in different individuals and relative natural environments and provides novel drug targets for the treatment of parasitic diseases.

Label-free proteomic comparison reveals ciliary and non-ciliary phenotypes of IFT-A mutants

DIFFRAC is a powerful method for systematically comparing proteome content and organization between samples in a high-throughput manner. By subjecting control and experimental protein extracts to native chromatography and quantifying the contents of each fraction using mass spectrometry, it enables the quantitative detection of alterations to protein complexes and abundances. Here, we applied DIFFRAC to investigate the consequences of genetic loss of Ift122, a subunit of the intraflagellar transport-A (IFT-A) protein complex that plays a vital role in the formation and function of cilia and flagella, on the proteome of Tetrahymena thermophila . A single DIFFRAC experiment was sufficient to detect changes in protein behavior that mirrored known effects of IFT-A loss and revealed new biology. We uncovered several novel IFT-A-regulated proteins, which we validated through live imaging in Xenopus multiciliated cells, shedding new light on both the ciliary and non-ciliary functions of IFT-A. Our findings underscore the robustness of DIFFRAC for revealing proteomic changes in response to genetic or biochemical perturbation.

Neurodegenerative disorders: From clinicopathology convergence to systems biology divergence

Neurodegenerative diseases are multifactorial. This means that several genetic, epigenetic, and environmental factors contribute to their emergence. Therefore, for the future management of these highly prevalent diseases, it is necessary to change perspective. If a holistic viewpoint is assumed, the phenotype (the clinicopathological convergence) emerges from the perturbation of a complex system of functional interactions among proteins (systems biology divergence). The systems biology top-down approach starts with the unbiased collection of sets of data generated through one or more -omics techniques and has the aim to identify the networks and the components that participate in the generation of a phenotype (disease), often without any available a priori knowledge. The principle behind the top-down method is that the molecular components that respond similarly to experimental perturbations are somehow functionally related. This allows the study of complex and relatively poorly characterized diseases without requiring extensive knowledge of the processes under investigation. In this chapter, the use of a global approach will be applied to the comprehension of neurodegeneration, with a particular focus on the two most prevalent ones, Alzheimer's and Parkinson's diseases. The final purpose is to distinguish disease subtypes (even with similar clinical manifestations) to launch a future of precision medicine for patients with these disorders.

A quantitative proteomic analyses of primary myocardial cell injury induced by heat stress in chicken embryo

In this study, the model of heat stress was constructed in primary chick embryonic myocardial cells at 42 °C for 4 h. Proteome analysis using DIA identified 245 differentially expressed proteins (DEPs) (Q-value <0.05, fold change >1.5), of which 63 proteins were up-regulated and 182 proteins were down-regulated. Many were related to metabolism, oxidative stress, oxidative phosphorylation and apoptosis. Gene Ontology (GO) analysis showed that many DEPs under heat stress were involved in regulating metabolites and energy, cellular respiration, catalytic activity and stimulation. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that DEPs were enriched in metabolic pathways, oxidative phosphorylation, citrate cycle (TCA cycle), cardiac muscle contraction, and carbon metabolism. The results could help understanding of the effect of heat stress on myocardial cells and even the heart and possible action mechanism at the protein level.

The Need for Biomarkers in the ALS-FTD Spectrum: A Clinical Point of View on the Role of Proteomics

Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) are severely debilitating and progressive neurodegenerative disorders. A distinctive pathological feature of several neurodegenerative diseases, including ALS and FTD, is the deposition of aberrant protein inclusions in neuronal cells, which leads to cellular dysfunction and neuronal damage and loss. Despite this, to date, the biological process behind developing these protein inclusions must be better clarified, making the development of disease-modifying treatment impossible until this is done. Proteomics is a powerful tool to characterize the expression, structure, functions, interactions, and modifications of proteins of tissue and biological fluid, including plasma, serum, and cerebrospinal fluid. This protein-profiling characterization aims to identify disease-specific protein alteration or specific pathology-based mechanisms which may be used as markers of these conditions. Our narrative review aims to highlight the need for biomarkers and the potential use of proteomics in clinical practice for ALS-FTD spectrum disorders, considering the emerging rationale in proteomics for new drug development. Certainly, new data will emerge in the near future in this regard and support clinicians in the development of personalized medicine.

The biomarkers discovery of hyperuricemia and gout: proteomics and metabolomics

Background

Hyperuricemia and gout are a group of disorders of purine metabolism. In recent years, the incidence of hyperuricemia and gout has been increasing, which is a severe threat to people's health. Several studies on hyperuricemia and gout in proteomics and metabolomics have been conducted recently. Some literature has identified biomarkers that distinguish asymptomatic hyperuricemia from acute gout or remission of gout. We summarize the physiological processes in which these biomarkers may be involved and their role in disease progression.

Methodology

We used professional databases including PubMed, Web of Science to conduct the literature review. This review addresses the current landscape of hyperuricemia and gout biomarkers with a focus on proteomics and metabolomics.

Results

Proteomic methods are used to identify differentially expressed proteins to find specific biomarkers. These findings may be suggestive for the diagnosis and treatment of hyperuricemia and gout to explore the disease pathogenesis. The identified biomarkers may be mediators of the link between hyperuricemia, gout and kidney disease, metabolic syndrome, diabetes and hypertriglyceridemia. Metabolomics reveals the main influential pathways through small molecule metabolites, such as amino acid metabolism, lipid metabolism, or other characteristic metabolic pathways. These studies have contributed to the discovery of Chinese medicine. Some traditional Chinese medicine compounds can improve the metabolic disorders of the disease.

Conclusions

We suggest some possible relationships of potential biomarkers with inflammatory episodes, complement activation, and metabolic pathways. These biomarkers are able to distinguish between different stages of disease development. However, there are relatively few proteomic as well as metabolomic studies on hyperuricemia and gout, and some experiments are only primary screening tests, which need further in-depth study.

Top-Down Proteomics and Comparative 2D-DIGE Analysis

The combination of large-scale protein separation techniques, sophisticated mass spectrometry, and systems bioinformatics has led to the establishment of proteomics as a distinct discipline within the wider field of protein biochemistry. Both discovery proteomics and targeted proteomics are widely used in biological and biomedical research, whereby the analytical approaches can be broadly divided into proteoform-centric top-down proteomics versus peptide-centric bottom-up proteomics. This chapter outlines the scientific value of top-down proteomics and describes how fluorescence two-dimensional difference gel electrophoresis can be combined with the systematic analysis of crucial post-translational modifications. The concept of on-membrane digestion following the electrophoretic transfer of proteins and the usefulness of comparative two-dimensional immunoblotting are discussed.

Proteomics-based molecular and functional characteristic profiling of muscle tissue in Triploid crucian carp

Triploid crucian carp (TCC) is a kind of artificially bred fish with huge economic value to China. It has several excellent characteristics, such as fast growth, strong disease resistance and delicious taste. However, as a regionally specific fish, the underlying molecular mechanisms of these characteristics are largely unknown. In this study, we performed quantitative proteomics on the muscle tissues of TCC and its parents, allotetraploid (♂), red crucian carp (♀) and common carp. Combined with multiple bioinformatic analysis, we found that the taste of TCC can be mainly attributed to umami amino acid-enriched proteins such as PURBA, PVALBI and ATP5F1B, and that its rapid growth can be mainly ascribed to the high expression and regulation of metabolism-related proteins such as NDUFS1, ENO1A and CS. These play significant roles in substrate and energy metabolism, as well as in bias transformation. Subsequently, we identified several proteins, including MDH1AA, GOT1 and DLAT, that may serve as potential regulators of innate immunity by regulating the biosynthesis and transformation of significant antibiotics and antimicrobial peptides. In conclusion, this study can serve as a significant reference for similar investigations and shed light on the molecular and biological functions of individual proteins in TCC muscle tissue.

Effects of dehydroabietic acid on nontarget lipidomics and proteomics of HepG2

Objective: Studies of the effects of dehydroabietic acid on the multiomics of HepG2 hepatoma carcinoma cells are currently lacking. In this study, the molecular mechanism of the influence of dehydroabietic acid on HepG2 cells was disclosed by studying lipidomics and proteomics. Correlations among multiomics conjoint analysis results were verified. Methods: First, proteomics analysis of HepG2 cells was carried out using dehydroabietic acid. Differentially expressed proteins were screened and analyzed. Pathway enrichment analyses of differential proteins were compared, and the molecular mechanism was disclosed. Second, lipidomics analysis of HepG2 cells was conducted using dehydroabietic acid. The influence of dehydroabietic acid on HepG2 cells was determined on the lipid molecular level. Finally, a conjoint analysis of data related to differentially expressed proteins of ferroptosis and differentially changing lipid molecules was implemented. Results: A total of 260 upregulated and 961 downregulated proteins were screened in the proteomics analysis. The top five significantly enriched pathways included ferroptosis, oxidative phosphorylation, and protein processing in the endoplasmic reticulum. In the lipidomics analysis, 30 significantly differential metabolites with upregulated and downregulated expression were identified, and differentially expressed lipids were mainly related to the metabolism of glyceryl phosphatide. According to the comprehensive multiomics analysis results, real-time quantitative PCR and the enzyme-linked immunosorbent assay (ELISA), ACSL3 participated in cardiolipin metabolism. Conclusion: Dehydroabietic acid influences HepG2 cells through the above biological pathways.

Endothelin-1, over-expressed in SOD1G93A mice, aggravates injury of NSC34-hSOD1G93A cells through complicated molecular mechanism revealed by quantitative proteomics analysis

Endothelin-1 (ET-1), a secreted signaling peptide, is suggested to be involved in multiple actions in various tissues including the brain, but its role in amyotrophic lateral sclerosis (ALS) remains unknown. In this study, we detected the expression changes as well as the cellular localization of ET-1, endothelin A (ET-A) and endothelin B (ET-B) receptors in spinal cord of transgenic SOD1-G93A (TgSOD1-G93A) mice, which showed that the two ET receptors (ET-Rs) expressed mainly on neurons and decreased as the disease progressed especially ET-B, while ET-1 expression was up-regulated and primarily localized on astrocytes. We then explored the possible mechanisms underlying the effect of ET-1 on cultured NSC34-hSOD1G93A cell model. ET-1 showed toxic effect on motor neurons (MNs), which can be rescued by the selective ET-A receptor antagonist BQ-123 or ET-B receptor antagonist BQ-788, suggesting that clinically used ET-Rs pan-antagonist could be a potential strategy for ALS. Using proteomic analysis, we revealed that 110 proteins were differentially expressed in NSC34-hSOD1G93A cells after ET-1 treatment, of which 54 were up-regulated and 56 were down-regulated. Bioinformatic analysis showed that the differentially expressed proteins (DEPs) were primarily enriched in hippo signaling pathway-multiple species, ABC transporters, ErbB signaling pathway and so on. These results provide further insights on the potential roles of ET-1 in ALS and present a new promising therapeutic target to protect MNs of ALS.

Clinical applications of plasma proteomics and peptidomics: Towards precision medicine

In the context of precision medicine, disease treatment requires individualized strategies based on the underlying molecular characteristics to overcome therapeutic challenges posed by heterogeneity. For this purpose, it is essential to develop new biomarkers to diagnose, stratify, or possibly prevent diseases. Plasma is an available source of biomarkers that greatly reflects the physiological and pathological conditions of the body. An increasing number of studies are focusing on proteins and peptides, including many involving the Human Proteome Project (HPP) of the Human Proteome Organization (HUPO), and proteomics and peptidomics techniques are emerging as critical tools for developing novel precision medicine preventative measures. Excitingly, the emerging plasma proteomics and peptidomics toolbox exhibits a huge potential for studying pathogenesis of diseases (e.g., COVID-19 and cancer), identifying valuable biomarkers and improving clinical management. However, the enormous complexity and wide dynamic range of plasma proteins makes plasma proteome profiling challenging. Herein, we summarize the recent advances in plasma proteomics and peptidomics with a focus on their emerging roles in COVID-19 and cancer research, aiming to emphasize the significance of plasma proteomics and peptidomics in clinical applications and precision medicine.

The use of mass spectrometry in a proteome-centered multiomics study of human pituitary adenomas

A pituitary adenoma (PA) is a common intracranial neoplasm, and is a complex, chronic, and whole-body disease with multicausing factors, multiprocesses, and multiconsequences. It is very difficult to clarify molecular mechanism and treat PAs from the single-factor strategy model. The rapid development of multiomics and systems biology changed the paradigms from a traditional single-factor strategy to a multiparameter systematic strategy for effective management of PAs. A series of molecular alterations at the genome, transcriptome, proteome, peptidome, metabolome, and radiome levels are involved in pituitary tumorigenesis, and mutually associate into a complex molecular network system. Also, the center of multiomics is moving from structural genomics to phenomics, including proteomics and metabolomics in the medical sciences. Mass spectrometry (MS) has been extensively used in phenomics studies of human PAs to clarify molecular mechanisms, and to discover biomarkers and therapeutic targets/drugs. MS-based proteomics and proteoform studies play central roles in the multiomics strategy of PAs. This article reviews the status of multiomics, multiomics-based molecular pathway networks, molecular pathway network-based pattern biomarkers and therapeutic targets/drugs, and future perspectives for personalized, predeictive, and preventive (3P) medicine in PAs.

Clinlabomics: leveraging clinical laboratory data by data mining strategies

The recent global focus on big data in medicine has been associated with the rise of artificial intelligence (AI) in diagnosis and decision-making following recent advances in computer technology. Up to now, AI has been applied to various aspects of medicine, including disease diagnosis, surveillance, treatment, predicting future risk, targeted interventions and understanding of the disease. There have been plenty of successful examples in medicine of using big data, such as radiology and pathology, ophthalmology cardiology and surgery. Combining medicine and AI has become a powerful tool to change health care, and even to change the nature of disease screening in clinical diagnosis. As all we know, clinical laboratories produce large amounts of testing data every day and the clinical laboratory data combined with AI may establish a new diagnosis and treatment has attracted wide attention. At present, a new concept of radiomics has been created for imaging data combined with AI, but a new definition of clinical laboratory data combined with AI has lacked so that many studies in this field cannot be accurately classified. Therefore, we propose a new concept of clinical laboratory omics (Clinlabomics) by combining clinical laboratory medicine and AI. Clinlabomics can use high-throughput methods to extract large amounts of feature data from blood, body fluids, secretions, excreta, and cast clinical laboratory test data. Then using the data statistics, machine learning, and other methods to read more undiscovered information. In this review, we have summarized the application of clinical laboratory data combined with AI in medical fields. Undeniable, the application of Clinlabomics is a method that can assist many fields of medicine but still requires further validation in a multi-center environment and laboratory.

Current Insights on Neurodegeneration by the Italian Proteomics Community

The growing number of patients affected by neurodegenerative disorders represents a huge problem for healthcare systems, human society, and economics. In this context, omics strategies are crucial for the identification of molecular factors involved in disease pathobiology, and for the discovery of biomarkers that allow early diagnosis, patients’ stratification, and treatment response prediction. The integration of different omics data is a required step towards the goal of personalized medicine. The Italian proteomics community is actively developing and applying proteomics approaches to the study of neurodegenerative disorders; moreover, it is leading the mitochondria-focused initiative of the Human Proteome Project, which is particularly important given the central role of mitochondrial impairment in neurodegeneration. Here, we describe how Italian research groups in proteomics have contributed to the knowledge of many neurodegenerative diseases, through the elucidation of the pathobiology of these disorders, and through the discovery of disease biomarkers. In particular, we focus on the central role of post-translational modifications analysis, the implementation of network-based approaches in functional proteomics, the integration of different omics in a systems biology view, and the development of novel platforms for biomarker discovery for the high-throughput quantification of thousands of proteins at a time.

Network Pharmacology of Adaptogens in the Assessment of Their Pleiotropic Therapeutic Activity

The reductionist concept, based on the ligand–receptor interaction, is not a suitable model for adaptogens, and herbal preparations affect multiple physiological functions, revealing polyvalent pharmacological activities, and are traditionally used in many conditions. This review, for the first time, provides a rationale for the pleiotropic therapeutic efficacy of adaptogens based on evidence from recent gene expression studies in target cells and where the network pharmacology and systems biology approaches were applied. The specific molecular targets and adaptive stress response signaling mechanisms involved in nonspecific modes of action of adaptogens are identified.

Ischemic preconditioning/ischemic postconditioning alleviates anoxia/reoxygenation injury via the Notch1/Hes1/VDAC1 axis

Ischemic preconditioning (IPC), and ischemic postconditioning (IPost) have a significant protective effect on myocardial ischemia/reperfusion (MI/R) injury by alleviating oxidative stress and mitochondrial disturbances, although the underlying molecular mechanisms are unclear. The study was to demonstrate that cardioprotection against anoxia/reoxygenation (A/R) injury is transduced via the Notch1/Hes1/VDAC1 signaling pathway. Using mass spectrometry and tandem affinity purification (TAP), to screen for differentially expressed proteins associated with Hes1, followed by standard bioinformatics analysis. The co-immunoprecipitation (Co-IP) assay confirmed an interaction between Hes1 and VDAC1 proteins. H9c2 cells were transfected with Hes1 adenoviral N-terminal TAP vector (AD-NTAP/Hes1) and Hes1-short hairpin RNA adenoviral vector (AD-Hes1-shRNA) to establish A/R injury, IPC, and IPost models, respectively. The expression of Hes1 and VDAC1 proteins were measured by western blot analysis, while the levels of reactive oxygen species (ROS), mitochondrial membrane potential (ΔΨm), and apoptosis were evaluated by flow cytometry. AD-NTAP/Hes1 can activate the exogenous protein expression of Hes1, thus decreasing creatine phosphokinase (CPK) and lactate dehydrogenase (LDH) activity and promoting cell viability. The study found that VDAC1 was a potential target protein for Hes1 and the overexpression of Hes1 protein expression downregulated protein expression levels of VDAC1, reduced ROS production, stabilized ΔΨm, and inhibited apoptosis in H9c2 cells. Additionally, downregulation of Hes1 protein expression also upregulated VDAC1 protein expression, increased ROS production, imbalanced ΔΨm, promoted cell apoptosis, and attenuated the cardioprotection afforded by IPC and IPost. The Notch1/Hes1 signaling pathway activated by IPC/IPost can directly downregulate the protein expression of VDAC1 and consequently relieve A/R injury.

TMT-based proteomics analysis of the cerebral cortex of TauT knockout rats

Background

Taurine serves a variety of nutritional and physiological roles, and it is mostly transported in cells via taurine transporter (TauT). The effect of taurine transporter in cerebral cortex is still unknown. We employed TMT label-based proteomics to find differences in proteins in the cerebral cortex of TauT knockout rats in this investigation. The goal of this research was to see how TauT deletion affected protein alterations in brain tissue and to see if there was a new research area for TauT.

Methods

The cerebral cortex of TauT knockout rats and wild-type control rats were analyzed using TMT-based proteomics, and differentially expressed proteins were analyzed by bioinformatics analysis means such as GO and KEGG, the association between the proteins was found by PPI, and biologically significant and interesting proteins were selected for verification by WB and immunohistochemistry.

Results

There were total of 8275 proteins found, but only 35 differentially expressed proteins were identified (27 up-regulated and 8 down-regulated), and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to predict the biological pathways and functional classification of the proteins. The results show that these differentially expressed proteins are mainly enriched in lysine degradation, cell cycle, chronic myeloid leukemia, and longevity regulating pathways-multiple species, renal cell carcinoma, pathways in cancer, etc. To verify the proteomic data, we analyzed the expression of Annexin6 and Pik3r2 by western blotting and immunofluorescence. The results are consistent with proteomics, which proves the reliability of our proteomics data.

Conclusion

Through TMT-based proteomics, we have a comprehensive understanding of the effect of TauT knockout on the changes of other proteins in the cerebral cortex, providing new evidence for further understanding the function of TauT.

Muti-omics integration analysis revealed molecular network alterations in human nonfunctional pituitary neuroendocrine tumors in the framework of 3P medicine

Nonfuctional pituitary neuroendocrine tumor (NF-PitNET) is highly heterogeneous and generally considered a common intracranial tumor. A series of molecules are involved in NF-PitNET pathogenesis that alter in multiple levels of genome, transcriptome, proteome, and metabolome, and those molecules mutually interact to form dynamically associated molecular-network systems. This article reviewed signaling pathway alterations in NF-PitNET based on the analyses of the genome, transcriptome, proteome, and metabolome, and emphasized signaling pathway network alterations based on the integrative omics, including calcium signaling pathway, cGMP-PKG signaling pathway, mTOR signaling pathway, PI3K/AKT signaling pathway, MAPK (mitogen-activated protein kinase) signaling pathway, oxidative stress response, mitochondrial dysfunction, and cell cycle dysregulation, and those signaling pathway networks are important for NF-PitNET formation and progression. Especially, this review article emphasized the altered signaling pathways and their key molecules related to NF-PitNET invasiveness and aggressiveness that are challenging clinical problems. Furthermore, the currently used medication and potential therapeutic agents that target these important signaling pathway networks are also summarized. These signaling pathway network changes offer important resources for insights into molecular mechanisms, discovery of effective biomarkers, and therapeutic targets for patient stratification, predictive diagnosis, prognostic assessment, and targeted therapy of NF-PitNET.

Looking at COVID-19 from a Systems Biology Perspective

The sudden outbreak and worldwide spread of the SARS-CoV-2 pandemic pushed the scientific community to find fast solutions to cope with the health emergency. COVID-19 complexity, in terms of clinical outcomes, severity, and response to therapy suggested the use of multifactorial strategies, characteristic of the network medicine, to approach the study of the pathobiology. Proteomics and interactomics especially allow to generate datasets that, reduced and represented in the forms of networks, can be analyzed with the tools of systems biology to unveil specific pathways central to virus-human host interaction. Moreover, artificial intelligence tools can be implemented for the identification of druggable targets and drug repurposing. In this review article, we provide an overview of the results obtained so far, from a systems biology perspective, in the understanding of COVID-19 pathobiology and virus-host interactions, and in the development of disease classifiers and tools for drug repurposing.

Exploring the Mechanism of Edaravone for Oxidative Stress in Rats with Cerebral Infarction Based on Quantitative Proteomics Technology

Objective

To explore the mechanism of edaravone in the treatment of oxidative stress in rats with cerebral infarction based on quantitative proteomics technology.

Method

The modified Zea Longa intracavitary suture blocking method was utilized to make rat CI model. After modeling, the rat was intragastrically given edaravone for 7 days, once a day. After the 7-day intervention, the total proteins of serum were extracted. After proteomics analysis, the differentially expressed proteins are analyzed by bioinformatics. Then chemoinformatics methods were used to explore the biomolecular network of edaravone intervention in CI.

Result

The neurological scores and pathological changes of rats were improved after the intervention of edaravone. Proteomics analysis showed that in the model/sham operation group, 90 proteins in comparison group were upregulated, and 26 proteins were downregulated. In the edaravone/model group, 21 proteins were upregulated, and 41 proteins were downregulated. Bioinformatics analysis and chemoinformatics analysis also show that edaravone is related to platelet activation and aggregation, oxidative stress, intercellular adhesion, glycolysis and gluconeogenesis, iron metabolism, hypoxia, inflammatory chemokines, their mediated signal transduction, and so on.

Conclusion

The therapeutic mechanism of edaravone in the treatment of CI may involve platelet activation and aggregation, oxidative stress, intercellular adhesion, glycolysis and gluconeogenesis, iron metabolism, hypoxia, and so on. This study revealed the serum protein profile of edaravone in the treatment of cerebral infarction rats through serum TMT proteomics and discovered the relevant mechanism of edaravone regulating iron metabolism in cerebral infarction, which provides new ideas for the study of edaravone intervention in cerebral infarction and also provides reference information for future research on the mechanism of edaravone intervention in iron metabolism-related diseases.

Advances in functional proteomics to study plant-pathogen interactions

Pathogen infection triggers complex signaling networks in plant cells that ultimately result in either susceptibility or resistance. We have made substantial progress in dissecting many of these signaling events, and it is becoming clear that changes in proteome composition and protein activity are major drivers of plant-microbe interactions. Here, we highlight different approaches to analyze the functional proteomes of hosts and pathogens and discuss how they have been used to further our understanding of plant disease. Global proteome profiling can quantify the dynamics of proteins, posttranslational modifications, and biological pathways that contribute to immune-related outcomes. In addition, emerging techniques such as enzyme activity-based profiling, proximity labeling, and kinase-substrate profiling are being used to dissect biochemical events that operate during infection. Finally, we discuss how these functional approaches can be integrated with other profiling data to gain a mechanistic, systems-level view of plant and pathogen signaling.

CIMAGE2.0: An Expanded Tool for Quantitative Analysis of Activity-Based Protein Profiling (ABPP) Data

Activity-based protein profiling (ABPP) is a powerful chemical proteomic method for studying protein activity, modifications, and interactions in a high-throughput manner. In ABPP experiments, accurate quantification is crucial to determine the extent of probe labeling at the level of either target proteins or specific amino acid side chains. CIMAGE has been developed as an in-house quantification software specifically designed for ABPP data analysis that incorporates (1) a relaxed peak extraction algorithm and (2) stringent post-quantification checks for efficient and accurate quantification. It also can generate table and image data for users to conveniently visualize their results. Here we provide a retrospective introduction of the software and describe our recent upgrade efforts to enable (1) interfacing with different database search engines as input, (2) triplex quantification of ABPP data by reductive dimethylation, and (3) envelope checking for chemical elements with special isotopic distributions. We show that the updated CIMAGE can maintain its ability to quantify ABPP data with dramatic depth and high accuracy, and it also has similar quantification performance in benchmarked SILAC data as compared with MaxQuant. We believe that CIMAGE2.0 will continue to serve as a powerful analytical tool for ABPP studies.

Quantitative Proteomic Analysis of Synovial Tissue Reveals That Upregulated OLFM4 Aggravates Inflammation in Rheumatoid Arthritis

Tandem mass tag (TMT)-coupled liquid chromatography coupled with tandem mass spectrometry is a powerful method to investigate synovial tissue protein profiles in patients with rheumatoid arthritis (RA) and osteoarthritis (OA). Protein was isolated from synovial tissue samples of 22 patients and labeled with a TMT kit. Over 500 proteins were identified as the differential expression protein on comparing RA and OA synovial tissue, including 239 upregulated and 271 downregulated proteins. Data are available via ProteomeXchange with identifier PXD027703. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed that the majority participated in the developmental processes and protein processing in the endoplasmic reticulum. Olfactomedin 4 (OLFM4), a secreted glycoprotein, in joint inflammation of RA was explored. OLFM4 was upregulated in RA synovial tissue samples. In fibroblast-like synoviocytes (FLS), inflammation cytokines, TNF-α, interleukin (IL)-1β, and LPS can upregulate OLFM4. After OLFM4 knockdown under TNF-α stimulation, RA FLS proliferation was inhibited and the expression of CXCL9, CXCL11, and MMP-1 was decreased. Overall, the RA synovial tissue protein expression profile by proteomic analysis shows some unique targets in RA pathophysiology, and OLFM4 in FLS plays an important role in RA joint inflammation. OLFM4 can be a promising therapeutic target in RA synovial tissue.

iTRAQ-based proteome analysis of porcine group A rotavirus-infected porcine IPEC-J2 intestinal epithelial cells

Porcine rotavirus (PoRV), particularly group A, is one of the most important swine pathogens, causing substantial economic losses in the animal husbandry industry. To improve understanding of host responses to PoRV infection, we applied isobaric tags for relative and absolute quantification (iTRAQ) labeling coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to quantitatively identify the differentially expressed proteins in PoRV-infected IPEC-J2 cells and confirmed the differentially accumulated proteins (DAPs) expression differences by performing RT-qPCR and Western blot analysis. Herein, in PoRV- and mock-infected IPEC-J2 cells, relative quantitative data were identified for 4724 proteins, 223 of which were DAPs (125 up-accumulated and 98 down-accumulated). Bioinformatics analyses further revealed that a majority of the DAPs are involved in numerous crucial biological processes and signaling pathways, such as metabolic process, immune system process, amino acid metabolism, energy metabolism, immune system, MHC class I peptide loading complex, Hippo signaling pathway, Th1 and Th2 cell differentiation, antigen processing and presentation, and tubule bicarbonate reclamation. The cellular localization prediction analysis indicated that these DAPs may be located in the Golgi apparatus, nucleus, peroxisomal, cytoplasm, mitochondria, extracellular, plasma membrane, and endoplasmic reticulum (ER). Expression levels of three up-accumulated (VAMP4, IKBKE, and TJP3) or two down-accumulated (SOD3 and DHX9) DAPs upon PoRV infection, were further validated by RT-qPCR and Western blot analysis. Collectively, this work is the first time to investigate the protein profile of PoRV-infected IPEC-J2 cells using quantitative proteomics; these findings provide valuable information to better understand the mechanisms underlying the host responses to PoRV infection in piglets. SIGNIFICANCE: The proteomics analysis of this study uncovered the target associated with PoRV-induced innate immune response or cellular damage, and provided relevant insights into the molecular functions, biological processes, and signaling pathway in these targets. Out of these 223 DAPs, the expression levels of three up-accumulated (VAMP4, IKBKE, and TJP3) and two down-accumulated (SOD3 and DHX9) DAPs upon PoRV infection, have been further validated using RT-qPCR and Western blot analysis. These outcomes could uncover how PoRV manipulated the cellular machinery, which could further our understanding of PoRV pathogenesis in piglets.

Integrated Proteomics and Metabolomics Link Acne to the Action Mechanisms of Cryptotanshinone Intervention

The label-free methods of proteomic combined with metabolomics were applied to explore the mechanisms of Cryptotanshinone (CPT) intervention in rats with acne. The model group consisted of rats given oleic acid (MC), then treated with CPT, while control groups did not receive treatment. The skin samples were significantly different between control, model and CPT-treated groups in hierarchical clustering dendrogram. Obvious separations of the skin metabolic profiles from the three groups were found through PCA scoring. In total, 231 and 189 differentially expressed proteins (DEPs) were identified in MC and CPT groups, respectively. By the KEGG analysis, five protein and metabolite pathways were found to be significantly altered. These played important roles in response to oleic acid-induced acne and drug treatment. CPT could negatively regulate glycolysis/gluconeogenesis and histidine metabolisms to decrease keratinocyte differentiation and improve excessive keratinization and cellular barrier function. CPT could down-regulate the IL-17 signaling pathway and regulate the acne-driven immune response of sebum cells. The biosynthesis of unsaturated fatty acids metabolism, glycerophospholipid metabolism and linoleic acid pathways could significantly alter sebum production and control sebaceous gland secretion after CPT treatment. The gap junction was up-regulated after CPT treatment and the skin barrier turned back to normal. Krt 14, Krt 16 and Krt 17 were significantly down-regulated, decreasing keratinization, while inflammatory cell infiltration was improved by down-regulation of Msn, up-regulation of linoleic acid and estrogen pathways after CPT treatment. These results propose action mechanisms for the use of CPT in acne, as a safe and potential new drug.

Deconvoluting complex protein interaction networks through reductionist strategies in peptide biochemistry: Modern approaches and research questions

Following the decoding of the first human genome, researchers have vastly improved their understanding of cell biology and its regulation. As a result, it has become clear that it is not merely genetic information, but the aberrant changes in the functionality and connectivity of its encoded proteins that drive cell response to periods of stress and external cues. Therefore, proper utilization of refined methods that help to describe protein signalling or regulatory networks (i.e., functional connectivity), can help us understand how change in the signalling landscape effects the cell. However, given the vast complexity in 'how and when' proteins communicate or interact with each other, it is extremely difficult to define, characterize, and understand these interaction networks in a tangible manner. Herein lies the challenge of tackling the functional proteome; its regulation is encoded in multiple layers of interaction, chemical modification and cell compartmentalization. To address and refine simple research questions, modern reductionist strategies in protein biochemistry have successfully used peptide-based experiments; their summation helping to simplify the overall complexity of these protein interaction networks. In this way, peptides are powerful tools used in fundamental research that can be readily applied to comparative biochemical research. Understanding and defining how proteins interact is one of the key aspects towards understanding how the proteome functions. To date, reductionist peptide-based research has helped to address a wide range of proteome-related research questions, including the prediction of enzymes substrates, identification of posttranslational modifications, and the annotation of protein interaction partners. Peptide arrays have been used to identify the binding specificity of reader domains, which are able to recognise the posttranslational modifications; forming dynamic protein interactions that are dependent on modification state. Finally, representing one of the fastest growing classes of inhibitor molecules, peptides are now begin explored as "disruptors" of protein-protein interactions or enzyme activity. Collectively, this review will discuss the use of peptides, peptide arrays, peptide-oriented computational biochemistry as modern reductionist strategies in deconvoluting the functional proteome.

Research status and prospects of biomarkers for nasopharyngeal carcinoma in the era of high‑throughput omics (Review)

As a malignant tumor type, nasopharyngeal carcinoma (NPC) is characterized by distinct geographical, ethnic and genetic differences; presenting a major threat to human health in many countries, especially in Southern China. At present, no accurate and effective methods are available for the early diagnosis, efficacious evaluation or prognosis prediction for NPC. As such, a large number of patients have locoregionally advanced NPC at the time of initial diagnosis. Many patients show toxic reactions to overtreatment and have risks of cancer recurrence and distant metastasis owing to insufficient treatment. To solve these clinical problems, high‑throughput '‑omics' technologies are being used to screen and identify specific molecular biomarkers for NPC. Because of the lack of comprehensive descriptions regarding NPC biomarkers, the present study summarized the research progress that has been made in recent years to discover NPC biomarkers, highlighting the existing problems that require exploration. In view of the lack of authoritative reports at present, study design factors that affect the screening of biomarkers are also discussed here and prospects for future research are proposed to provide references for follow‑up studies of NPC biomarkers.

Gene Set Enrichment Analysis of Interaction Networks Weighted by Node Centrality

Gene set enrichment analysis (GSEA) is a powerful tool to associate a disease phenotype to a group of genes/proteins. GSEA attributes a specific weight to each gene/protein in the input list that depends on a metric of choice, which is usually represented by quantitative expression data. However, expression data are not always available. Here, GSEA based on betweenness centrality of a protein–protein interaction (PPI) network is described and applied to two cases, where an expression metric is missing. First, personalized PPI networks were generated from genes displaying alterations (assessed by array comparative genomic hybridization and whole exome sequencing) in four probands bearing a 16p13.11 microdeletion in common and several other point variants. Patients showed disease phenotypes linked to neurodevelopment. All networks were assembled around a cluster of first interactors of altered genes with high betweenness centrality. All four clusters included genes known to be involved in neurodevelopmental disorders with different centrality. Moreover, the GSEA results pointed out to the evidence of “cell cycle” among enriched pathways. Second, a large interaction network obtained by merging proteomics studies on three neurodegenerative disorders was analyzed from the topological point of view. We observed that most central proteins are often linked to Parkinson’s disease. The selection of these proteins improved the specificity of GSEA, with “Metabolism of amino acids and derivatives” and “Cellular response to stress or external stimuli” as top-ranked enriched pathways. In conclusion, betweenness centrality revealed to be a suitable metric for GSEA. Thus, centrality-based GSEA represents an opportunity for precision medicine and network medicine.

Functional proteomic analysis reveals roles for PKCδ in regulation of cell survival and cell death: Implications for cancer pathogenesis and therapy

Protein Kinase C-δ (PKCδ), regulates a broad group of biological functions and disease processes, including well-defined roles in immune function, cell survival and apoptosis. PKCδ primarily regulates apoptosis in normal tissues and non-transformed cells, and genetic disruption of the PRKCD gene in mice is protective in many diseases and tissue damage models. However pro-survival/pro-proliferative functions have also been described in some transformed cells and in mouse models of cancer. Recent evidence suggests that the contribution of PKCδ to specific cancers may depend in part on the oncogenic context of the tumor, consistent with its paradoxical role in cell survival and cell death. Here we will discuss what is currently known about biological functions of PKCδ and potential paradigms for PKCδ function in cancer. To further understand mechanisms of regulation by PKCδ, and to gain insight into the plasticity of PKCδ signaling, we have used functional proteomics to identify pathways that are dependent on PKCδ. Understanding how these distinct functions of PKCδ are regulated will be critical for the logical design of therapeutics to target this pathway.

Molecular biological methods in environmental engineering

Microbes are sensitive to environmental changes and can respond in a short time. Genomics, proteomics, transcriptomics, metabolomics, and multigroup association are used to characterize the composition, function, and metabolism of microorganisms, and to evaluate the environment according to the changes in microorganisms, which has important reference and guiding significance of environmental monitoring, management, and repair. In this paper, the application of molecular biological methods to study environmental microorganisms in the fields of wastewater treatment, pollution control, soil improvement, and environmental monitoring in 2019 is reviewed.