Protein-protein Interaction Map Research Articles

PhoXplex: Combining Phospho-enrichable Cross-Linking with Isobaric Labeling for Quantitative Proteome-Wide Mapping of Protein Interfaces.

Integrating cross-linking mass spectrometry (XL-MS) into structural biology workflows provides valuable information about the spatial arrangement of amino acid stretches, which can guide elucidation of protein assembly architecture. Additionally, the combination of XL-MS with peptide quantitation techniques is a powerful approach to delineate protein interface dynamics across diverse conditions. While XL-MS is increasingly effective with isolated proteins or small complexes, its application to whole-cell samples poses technical challenges related to analysis depth and throughput. The use of enrichable cross-linkers has greatly improved the detectability of protein interfaces in a proteome-wide scale, facilitating global protein-protein interaction mapping. Therefore, bringing together enrichable cross-linking and multiplexed peptide quantification is an appealing approach to enable comparative characterization of structural attributes of proteins and protein interactions. Here, we combined phospho-enrichable cross-linking with TMT labeling to develop a streamline workflow (PhoXplex) for the detection of differential structural features across a panel of cell lines in a global scale. We achieved deep coverage with quantification of over 9000 cross-links and long loop-links in total including potentially novel interactions. Overlaying AlphaFold predictions and disorder protein annotations enables exploration of the quantitative cross-linking data set, to reveal possible associations between mutations and protein structures. Lastly, we discuss current shortcomings and perspectives for deep whole-cell profiling of protein interfaces at large-scale.

Hippocampal tau-induced GRIN3A deficiency in Alzheimer's disease.

Alzheimer's disease (AD) is characterized by significant alterations in hippocampal function and structure, but the molecular mechanisms underlying the hippocampal region remain elusive. We integrated multiple transcriptome datasets including human or rat hippocampus (GSE173955, GSE129051, GSE84422) to identify candidate genes. Subsequent analyses including gene ontology analysis and protein-protein interaction mapping were performed to identify key genes and pathways. We found that glutamate ionotropic receptor NMDA-type subunit 3A (GRIN3A) and glutamate metabotropic receptor 8 (GRM8), which are related to the glutamatergic system, were the top two annotated genes and directly related to MAPT, which encodes a tau protein. Since there is no direct evidence of interaction between tauopathy and these genes in AD, further transcriptomic data(GSE125957, GSE56772) from tau transgenic mice and experimental validations through primary rat hippocampal neurons and induced pluripotent stem cell (iPSC)-derived brain organoids were performed. Interestingly, we identified that decreased NR3A (encoded by GRIN3A) and mGluR8 (encoded by GRM8) are correlated with tauopathy and loss of postsynaptic function in AD. Taken together, our results identified a novel tauopathy biomarker GRIN3A in AD. Furthermore, our findings suggest that an integrated approach combining public databases and diverse experimental validations can contribute to the advancement of precision medicine therapies.

Navigating the microalgal maze: a comprehensive review of recent advances and future perspectives in biological networks.

PPI analysis deepens our knowledge in critical processes like carbon fixation and nutrient sensing. Moreover, signaling networks, including pathways like MAPK/ERK and TOR, provide valuable information in how microalgae respond to environmental changes and stress. Additionally, species-species interaction networks for microalgae provide a comprehensive understanding of how different species interact within their environments. This review examines recent advancements in the study of biological networks within microalgae, with a focus on the intricate interactions that define these organisms. It emphasizes how network biology, an interdisciplinary field, offers valuable insights into microalgae functions through various methodologies. Crucial approaches, such as protein-protein interaction (PPI) mapping utilizing yeast two-hybrid screening and mass spectrometry, are essential for comprehending cellular processes and optimizing functions, such as photosynthesis and fatty acid biosynthesis. The application of advanced computational methods and information mining has significantly improved PPI analysis, revealing networks involved in critical processes like carbon fixation and nutrient sensing. The review also encompasses transcriptional networks, which play a role in gene regulation and stress responses, as well as metabolic networks represented by genome-scale metabolic models (GEMs), which aid in strain optimization and the prediction of metabolic outcomes. Furthermore, signaling networks, including pathways like MAPK/ERK and TOR, are crucial for understanding how microalgae respond to environmental changes and stress. Additionally, species-species interaction networks for microalgae provide a comprehensive understanding of how different species interact within their environments. The integration of these network biology approaches has deepened our understanding of microalgal interactions, paving the way for more efficient cultivation and new industrial applications.

The major vault protein integrates adhesion-driven signals to regulate collagen remodeling

DDR1 interacts with fibrillar collagen and can affect β1 integrin-dependent signaling, but the mechanism that mediates functional interactions between these two different receptors is not defined. We searched for molecules that link DDR1 and β1 integrin-dependent signaling in response to collagen binding. The activation of DDR1 by binding to fibrillar collagen reduced by 5-fold, β1 integrin-dependent ERK phosphorylation that leads to MMP1 expression. In contrast, pharmacological inhibition of DDR1 or culturing cells on fibronectin restored ERK phosphorylation and MMP1 expression mediated by the β1 integrin. A phospho-site screen indicated that collagen-induced DDR1 activation inhibited β1 integrin-dependent ERK signaling by regulating autophosphorylation of focal adhesion kinase (FAK). Immunoprecipitation, mass spectrometry, and protein-protein interaction mapping showed that while DDR1 and FAK do not interact directly, the major vault protein (MVP) binds DDR1 and FAK depending on the substrate. MVP associated with DDR1 in cells expressing β1 integrin that were cultured on collagen. Knockdown of MVP restored ERK activation and MMP1 expression in DDR1-expressing cells cultured on collagen. Immunostaining of invasive cancers in human colon showed colocalization of DDR1 with MVP. These data indicate that MVP interactions with DDR1 and FAK contribute to the regulation of β1 integrin-dependent signaling pathways that drive collagen degradation.

Effects and Mechanisms of Andrographolide for COVID-19: A Network Pharmacology-Based and Experimentally Validated Study

Objective: This study aimed to elucidate the therapeutic effects and underlying mechanisms of andrographolide against COVID-19 through a network pharmacology approach and experimental validation. Methods: Network pharmacology approaches were employed to elucidate potential targets of andrographolide, investigating their overlap with proteins implicated in SARS-CoV-2 infection. The identified targets underwent further analysis through protein-protein interaction (PPI) mapping, gene ontology (GO) categorization, and pathway enrichment within the framework of the Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequent molecular docking studies provided insights into the binding dynamics between andrographolide and the relevant protein targets. To validate these findings, a series of experimental procedures were conducted, including cytotoxicity assays, quantitative PCR analyses, and the deployment of a SARS-CoV-2 pseudovirus system, using BEAS-2B lung epithelial cells as a model. Results: Bioinformatics analysis revealed that andrographolide potentially modulates proinflammatory cytokines, JAK-STAT signaling, and antiviral immunity pathways in COVID-19. Molecular docking showed favorable binding interactions between andrographolide and its putative targets. In vitro studies confirmed that andrographolide suppressed the mRNA expression of IL-6, TNF-α, IL-1β, and STAT3 and inhibited pseudovirus entry and infection at pharmacologically relevant concentrations. Conclusion: The findings suggest that andrographolide could be a promising candidate for the treatment of COVID-19 due to its capacity to both inhibit SARS-CoV-2 and modulate harmful inflammation. Our findings highlight the potential therapeutic value of andrographolide in treating COVID-19, warranting further exploration in clinical trials.

Large-scale map of RNA-binding protein interactomes across the mRNA life cycle

mRNAs interact with RNA-binding proteins (RBPs) throughout their processing and maturation. While efforts have assigned RBPs to RNA substrates, less exploration has leveraged protein-protein interactions (PPIs) to study proteins in mRNA life-cycle stages. We generated an RNA-aware, RBP-centric PPI map across the mRNA life cycle in human cells by immunopurification-mass spectrometry (IP-MS) of ∼100 endogenous RBPs with and without RNase, augmented by size exclusion chromatography-mass spectrometry (SEC-MS). We identify 8,742 known and 20,802 unreported interactions between 1,125 proteins and determine that 73% of the IP-MS-identified interactions are RNA regulated. Our interactome links many proteins, some with unknown functions, to specific mRNA life-cycle stages, with nearly half associated with multiple stages. We demonstrate the value of this resource by characterizing the splicing and export functions of enhancer of rudimentary homolog (ERH), and by showing that small nuclear ribonucleoprotein U5 subunit 200 (SNRNP200) interacts with stress granule proteins and binds cytoplasmic RNA differently during stress.

Exploring potential ion channel targets for rheumatoid arthritis: combination of network analysis and gene expression analysis.

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic inflammation of the synovial membrane that leads to the destruction of cartilage and bone. Currently, pharmacological targeting of ion channels is being increasingly recognized as an attractive and feasible strategy for the treatment of RA. The present work employs a network analysis approach to predict the most promising ion channel target for potential RA-treating drugs. A protein-protein interaction map was generated for 343 genes associated with inflammation in RA and ion channel genes using Search Tool for the Retrieval of Interacting Genes and visualized using Cytoscape. Based on the betweenness centrality and traffic values as key topological parameters, 17 hub nodes were identified, including FOS (9800.85), tumor necrosis factor (3654.60), TGFB1 (3305.75), and VEGFA (3052.88). The backbone network constructed with these 17 hub genes was intensely analyzed to identify the most promising ion channel target using network analyzer. Calcium permeating ion channels, especially store-operated calcium entry channels, and their associated regulatory proteins were found to highly interact with RA inflammatory hub genes. This significant ion channel target for RA identified by theoretical and statistical studies was further validated by a pilot case-control gene expression study. Experimental verification of the above findings in 75 RA cases and 25 controls showed increased ORAI1 expression. Thus, with a combination of network analysis approach and gene expression studies, we have explored potential targets for RA treatment.

Mapping protein-protein interactions by mass spectrometry.

Protein-protein interactions (PPIs) are essential for numerous biological activities, including signal transduction, transcription control, and metabolism. They play a pivotal role in the organization and function of the proteome, and their perturbation is associated with various diseases, such as cancer, neurodegeneration, and infectious diseases. Recent advances in mass spectrometry (MS)-based protein interactomics have significantly expanded our understanding of the PPIs in cells, with techniques that continue to improve in terms of sensitivity, and specificity providing new opportunities for the study of PPIs in diverse biological systems. These techniques differ depending on the type of interaction being studied, with each approach having its set of advantages, disadvantages, and applicability. This review highlights recent advances in enrichment methodologies for interactomes before MS analysis and compares their unique features and specifications. It emphasizes prospects for further improvement and their potential applications in advancing our knowledge of PPIs in various biological contexts.

Characterization of lymphocyte-rich hepatocellular carcinoma and the prognostic role of tertiary lymphoid structures.

Lymphocyte-rich hepatocellular carcinoma (LR-HCC) is largely unknown and a rare subtype of HCC with immune-rich stroma. Tertiary lymphoid structures (TLS), frequently observed in LR-HCC, are known to be prognostically significant in various malignancies; however, their significance in HCC remains unevaluated. Clinicopathologic data of 191 cases of surgically resected conventional HCC (C-HCC, n = 160) and LR-HCC (n = 31) were retrieved. Immunohistochemistry, multiplex immunofluorescence staining, RNA sequencing and proteomic analysis were conducted. Differences between the subtypes were statistically evaluated. LR-HCC was significantly correlated to larger tumour size, higher Edmondson-Steiner grade, presence of TLS and higher CD3-, CD8- and FOXP3-positive T cell, high PD-1 and PD-L1 expression (p < .001 for all) compared to C-HCC. Patients with LR-HCC exhibited significantly better overall survival (OS) (p = .044) and recurrence-free survival (RFS) (p = .025) than C-HCC. LR-HCC demonstrated TLS signatures with significantly higher proteomic-based immune scores in 14 of 17 types of tumour-infiltrating immune cells. Furthermore, C-HCC with secondary follicles, the most mature form of TLS, exhibited significantly better OS (p = .031) and RFS (p = .033) than those without. Across the global proteome, LR-HCC was well-differentiated from C-HCC and a map of protein-protein interactions between tumour-infiltrating lymphocytes and HCC in tumour microenvironment was completed. LR-HCC is clinicopathologically and molecularly distinct and shows better prognosis compared to C-HCC. Also, the presence of secondary follicle can be an important prognostic marker for better prognosis in both LR-HCC and C-HCC.

Mycobacterium tuberculosis-THP-1 like macrophages protein-protein interaction map revealed through dual RNA-seq analysis and a computational approach.

Introduction. Infection caused by Mycobacterium tuberculosis (M. tb) is still a leading cause of mortality worldwide with estimated 1.4 million deaths annually.Hypothesis/Gap statement. Despite macrophages' ability to kill bacterium, M. tb can grow inside these innate immune cells and the exploration of the infection has traditionally been characterized by a one-sided relationship, concentrating solely on the host or examining the pathogen in isolation.Aim. Because of only a handful of M. tb-host interactions have been experimentally characterized, our main goal is to predict protein-protein interactions during the early phases of the infection.Methodology. In this work, we performed an integrative computational approach that exploits differentially expressed genes obtained from Dual RNA-seq analysis combined with known domain-domain interactions.Results. A total of 2381 and 7214 genes were identified as differentially expressed in M. tb and in THP-1-like macrophages, respectively, revealing different transcriptional profiles in response to infection. Over 48 h of infection, the host-pathogen network revealed 25 016 PPIs. Analysis of the resulting predicted network based on cellular localization information of M. tb proteins, indicated the implication of interacting nodes including the bacterial PE/PPE/PE_PGRS family. In addition, M. tb proteins interacted with host proteins involved in NF-kB signalling pathway as well as interfering with the host apoptosis ability via the potential interaction of M. tb TB16.3 with human TAB1 and M. tb GroEL2 with host protein kinase C delta, respectively.Conclusion. The prediction of the full range of interactions between M. tb and host will contribute to better understanding of the pathogenesis of this bacterium and may provide advanced approaches to explore new therapeutic targets against tuberculosis.

Mapping Protein-Protein Interactions at Birth: Single-Particle Cryo-EM Analysis of a Ribosome-Nascent Globin Complex.

Interactions between ribosome-bound nascent chains (RNCs) and ribosomal components are critical to elucidate the mechanism of cotranslational protein folding. Nascent protein-ribosome contacts within the ribosomal exit tunnel were previously assessed mostly in the presence of C-terminal stalling sequences, yet little is known about contacts taking place in the absence of these strongly interacting motifs. Further, there is nearly no information about ribosomal proteins (r-proteins) interacting with nascent chains within the outer surface of the ribosome. Here, we combine chemical cross-linking, single-particle cryo-EM, and fluorescence anisotropy decays to determine the structural features of ribosome-bound apomyoglobin (apoMb). Within the ribosomal exit tunnel core, interactions are similar to those identified in previous reports. However, once the RNC enters the tunnel vestibule, it becomes more dynamic and interacts with ribosomal RNA (rRNA) and the L23 r-protein. Remarkably, on the outer surface of the ribosome, RNCs interact mainly with a highly conserved nonpolar patch of the L23 r-protein. RNCs also comprise a compact and dynamic N-terminal region lacking contact with the ribosome. In all, apoMb traverses the ribosome and interacts with it via its C-terminal region, while N-terminal residues sample conformational space and form a compact subdomain before the entire nascent protein sequence departs from the ribosome.

Comparative interactome analysis of α-arrestin families in human and Drosophila.

The α-arrestins form a large family of evolutionally conserved modulators that control diverse signaling pathways, including both G-protein-coupled receptor (GPCR)-mediated and non-GPCR-mediated pathways, across eukaryotes. However, unlike β-arrestins, only a few α-arrestin targets and functions have been characterized. Here, using affinity purification and mass spectrometry, we constructed interactomes for 6 human and 12 Drosophila α-arrestins. The resulting high-confidence interactomes comprised 307 and 467 prey proteins in human and Drosophila, respectively. A comparative analysis of these interactomes predicted not only conserved binding partners, such as motor proteins, proteases, ubiquitin ligases, RNA splicing factors, and GTPase-activating proteins, but also those specific to mammals, such as histone modifiers and the subunits of V-type ATPase. Given the manifestation of the interaction between the human α-arrestin, TXNIP, and the histone-modifying enzymes, including HDAC2, we undertook a global analysis of transcription signals and chromatin structures that were affected by TXNIP knockdown. We found that TXNIP activated targets by blocking HDAC2 recruitment to targets, a result that was validated by chromatin immunoprecipitation assays. Additionally, the interactome for an uncharacterized human α-arrestin ARRDC5 uncovered multiple components in the V-type ATPase, which plays a key role in bone resorption by osteoclasts. Our study presents conserved and species-specific protein-protein interaction maps for α-arrestins, which provide a valuable resource for interrogating their cellular functions for both basic and clinical research.

A Semiquantitative Protein-Fragment Complementation Assay to Study Protein-Protein Interactions of the Polymerase Complex in Cellula.

Protein-fragment complementation assays (PCAs) are powerful tools to investigate protein-protein interactions in a cellular context. These are especially useful to study unstable proteins and weak interactions that may not resist protein isolation or purification. The PCA based on the reconstitution of the Gaussia princeps luciferase (split-luc) is a sensitive approach allowing the mapping of protein-protein interactions and the semiquantitative measurement of binding affinity. Here, we describe the split-luc protocol we used to map the viral interactome of measles virus polymerase complex.

Proteomic Analyses of the Mouse Brain.

Proteomics is a scientific field that aims to identify and characterize all proteins within a biological system, including their posttranslational modifications (PTMs), quantitative changes, and protein-protein interactions. Over the last two decades, proteomic approaches have been widely used in neuroscience research, providing multidimensional insights into the biology and pathology of the brain.Here, we present a basic protocol for profiling protein expression in the mouse brain, which involves total protein extraction, fractionation, digestion, and identification through liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). This method is compatible with many prevalent techniques used for protein quantitation, PTM analysis, and protein-protein interaction mapping.

Structure-based prediction of protein-protein interaction network in rice.

Comprehensive protein-protein interaction (PPI) maps are critical for understanding the functional organization of the proteome, but challenging to produce experimentally. Here, we developed a computational method for predicting PPIs based on protein docking. Evaluation of performance on benchmark sets demonstrated the ability of the docking-based method to accurately identify PPIs using predicted protein structures. By employing the docking-based method, we constructed a structurally resolved PPI network consisting of 24,653 interactions between 2,131 proteins, which greatly extends the current knowledge on the rice protein-protein interactome. Moreover, we mapped the trait-associated single nucleotide polymorphisms (SNPs) to the structural interactome, and computationally identified 14 SNPs that had significant consequences on PPI network. The protein structural interactome map provided a resource to facilitate functional investigation of PPI-perturbing alleles associated with agronomically important traits in rice.

TK1 expression influences pathogenicity by cell cycle progression, cellular migration, and cellular survival in HCC 1806 breast cancer cells.

Breast cancer is the most common cancer diagnosis worldwide accounting for 1 out of every 8 cancer diagnoses. The elevated expression of Thymidine Kinase 1 (TK1) is associated with more aggressive tumor grades, including breast cancer. Recent studies indicate that TK1 may be involved in cancer pathogenesis; however, its direct involvement in breast cancer has not been identified. Here, we evaluate potential pathogenic effects of elevated TK1 expression by comparing HCC 1806 to HCC 1806 TK1-knockdown cancer cells (L133). Transcriptomic profiles of HCC 1806 and L133 cells showed cell cycle progression, apoptosis, and invasion as potential pathogenic pathways affected by TK1 expression. Subsequent in-vitro studies confirmed differences between HCC 1806 and L133 cells in cell cycle phase progression, cell survival, and cell migration. Expression comparison of several factors involved in these pathogenic pathways between HCC 1806 and L133 cells identified p21 and AKT3 transcripts were significantly affected by TK1 expression. Creation of a protein-protein interaction map of TK1 and the pathogenic factors we evaluated predict that the majority of factors evaluated either directly or indirectly interact with TK1. Our findings argue that TK1 elevation directly increases HCC 1806 cell pathogenicity and is likely occurring by p21- and AKT3-mediated mechanisms to promote cell cycle arrest, cellular migration, and cellular survival.

Skin benefits of postbiotics derived from Micrococcus luteus derived from human skin: an untapped potential for dermatological health.

The skin microbiome, a diverse community of microorganisms, plays a crucial role in maintaining skin health. Among these microorganisms, the gram-positive bacterium Micrococcus luteus exhibits potential for promoting skin health. This study focuses on postbiotics derived from M. luteus YM-4, a strain isolated from human skin. Our objective is to explore the beneficial effects of YM-4 culture filtrate on dermatological health, including enhancing barrier function, modulating immune response, and aiding recovery from environmental damage. The effects of the YM-4 culture filtrate were tested on human keratinocytes and fibroblasts under various conditions using real-time PCR for gene expression analysis and fibroblast migration assays. A dehydration-simulated model was employed to prepare RNA-Seq samples from HaCaT cells treated with the YM-4 culture filtrate. Differentially expressed genes were identified and functionally classified through k-means clustering, gene ontology terms enrichment analyses, and protein-protein interactions mapping. The YM-4 culture filtrate enhanced the expression of genes involved in skin hydration, hyaluronic acid synthesis, barrier function, and cell proliferation. It also reduced inflammation markers in keratinocytes and fibroblasts under stress conditions. It mitigated UVB-induced collagen degradation while promoted collagen synthesis, suggesting anti-aging properties, and accelerated wound healing processes by promoting cell proliferation and migration. RNA sequencing analysis revealed that the YM-4 culture filtrate could reverse dehydration-induced transcriptional changes towards a state similar to untreated cells. M. luteus YM-4 culture filtrate exhibits significant therapeutic potential for dermatological applications.

Interactome profiling of Crimean-Congo hemorrhagic fever virus glycoproteins

Crimean-Congo hemorrhagic fever virus (CCHFV) is a biosafety level-4 pathogen requiring urgent research and development efforts. The glycoproteins of CCHFV, Gn and Gc, are considered to play multiple roles in the viral life cycle by interactions with host cells; however, these interactions remain largely unclear to date. Here, we analyzed the cellular interactomes of CCHFV glycoproteins and identified 45 host proteins as high-confidence Gn/Gc interactors. These host molecules are involved in multiple cellular biological processes potentially associated with the physiological actions of the viral glycoproteins. Then, we elucidated the role of a representative cellular protein, HAX1. HAX1 interacts with Gn by its C-terminus, while its N-terminal region leads to mitochondrial localization. By the strong interaction, HAX1 sequestrates Gn to mitochondria, thus depriving Gn of its normal Golgi localization that is required for functional glycoprotein-mediated progeny virion packaging. Consistently, the inhibitory activity of HAX1 against viral packaging and hence propagation was further elucidated in the contexts of pseudotyped and authentic CCHFV infections in cellular and animal models. Together, the findings provide a systematic CCHFV Gn/Gc-cell protein-protein interaction map, but also unravel a HAX1/mitochondrion-associated host antiviral mechanism, which may facilitate further studies on CCHFV biology and therapeutic approaches.

The REEP5/TRAM1 complex binds SARS-CoV-2 NSP3 and promotes virus replication.

Generation of virus-host protein-protein interactions (PPIs) maps may provide clues to uncover SARS-CoV-2-hijacked cellular processes. However, these PPIs maps were created by expressing each viral protein singularly, which does not reflect the life situation in which certain viral proteins synergistically interact with host proteins. Our results reveal the host-viral protein-protein interactome of SARS-CoV-2 NSP3, NSP4, and NSP6 expressed individually or in combination. Furthermore, REEP5/TRAM1 complex interacts with NSP3 at ROs and promotes viral replication. The significance of our research is identifying virus-host interactions that may be targeted for therapeutic intervention.

Bioinformatic analysis of CHEK1 as a marker of glomerular epithelial cell injury in diabetic nephropathy.

Diabetic nephropathy (DN) is considered to be a kidney disease caused by diabetes. In recent years, the incidence of DN has been on the rise, which is also a major challenge in the treatment and prognosis of the disease. Therefore, the search for new biomarkers of DN is urgent and has important clinical significance for reducing the morbidity and mortality of DN. In this study, two datasets GSE1009 and GSE142153 were selected to extract expression profile-based data from DN glomerular samples, and 238 differentially expressed genes (DEGs) were screened. Then, through enrichment analysis, the biological function of DEGs involved in DN disease was preliminarily explored. Subsequently, the STRING website was used to construct a protein-protein interaction map (PPI) to find 10 key genes (CHEK1, ITGB3, COL4A2, COL4A5, COL4A3, COL4A4, CCNB2, CCNB1, TPX2, KIF11), Which play an important role in the progression of DN disease and are closely related to other genes. CHEK1 was the focus of this study, and the expression level of CHEK1 in glomerular epithelial cell models was verified by qRT-PCR. Our results suggest that CHEK1 is a potential biomarker of the degree of damage to DN glomerular epithelial cells.