Bioinformatics Analysis Of Data Research Articles

Screening of the key genes and signaling pathways for schizophrenia using bioinformatics and next generation sequencing data analysis

Schizophrenia is thought to be the most prevalent chronic psychiatric disorder. Researchers have identified numerous proteins associated with the occurrence and development of schizophrenia. This study aimed to identify potential core genes and pathways involved in schizophrenia through exhaustive bioinformatics and next generation sequencing (NGS) data analyses using GSE106589 NGS data of neural progenitor cells and neurons obtained from healthy controls and patients with schizophrenia. The NGS data were downloaded from the Gene Expression Omnibus database. NGS data was processed by the DESeq2 package in R software, and the differentially expressed genes (DEGs) were identified. Gene ontology (GO) enrichment analysis and REACTOME pathway enrichment analysis were carried out to identify potential biological functions and pathways of the DEGs. Protein-protein interaction network, module, micro-RNA (miRNA)-hub gene regulatory network, transcription factor (TF)-hub gene regulatory network, and drug-hub gene interaction network analysis were performed to identify the hub genes, miRNA, TFs, and drug molecules. Potential hub genes were analyzed using receiver operating characteristic curves in the R package. In this investigation, an overall 955 DEGs were identified: 478 genes were remarkably upregulated and 477 genes were distinctly downregulated. These genes were enriched for GO terms and pathways mainly involved in the multicellular organismal process, G protein-coupled receptor ligand binding, regulation of cellular processes, and amine ligand-binding receptors. MYC, FN1, CDKN2A, EEF1G, CAV1, ONECUT1, SYK, MAPK13, TFAP2A, and BTK were considered the potential hub genes. The MiRNA-hub gene regulatory network, TF-hub gene regulatory network, and drug-hub gene interaction network were constructed successfully and predicted key miRNAs, TFs, and drug molecules for schizophrenia diagnosis and treatment. On the whole, the findings of this investigation enhance our understanding of the potential molecular mechanisms of schizophrenia and provide potential targets for further investigation.

Beyond Single Clones: High-Throughput Sequencing in Antibody Discovery.

Antibody repertoire sequencing and display library screening are powerful approaches for antibody discovery and engineering that can connect DNA sequence with antibody function. Antibody display and screening studies have made a tremendous impact on immunology and biotechnology over the last decade, accelerated by technological advances in high-throughput DNA sequencing techniques. Indeed, bioinformatic analysis of antibody DNA library data has now taken a central role in modern antibody drug discovery, and is also critical for many ongoing studies of human immune development. Here, we describe current trends in antibody DNA library screening and analysis, and introduce a selection of protocols describing fundamental bioinformatic techniques to enable scientists to efficiently study antibody DNA libraries.

YAP1 preserves tubular mitochondrial quality control to mitigate diabetic kidney disease

Renal tubule cells act as a primary site of injury in diabetic kidney disease (DKD), with dysfunctional mitochondrial quality control (MQC) closely associated with progressive kidney dysfunction in this context. Our investigation delves into the observed inactivation of yes-associated protein 1 (YAP1) and consequential dysregulation of MQC within renal tubule cells among DKD subjects through bioinformatic analysis of transcriptomics data from the Gene Expression Omnibus (GEO) dataset. Receiver operating characteristic curve analysis unequivocally underscores the robust diagnostic accuracy of YAP1 and MQC-related genes for DKD. Furthermore, we observed YAP1 inactivation, accompanied by perturbed MQC, within cultured tubule cells exposed to high glucose (HG) and palmitic acid (PA). This pattern was also evident in the tubulointerstitial compartment of kidney sections from biopsy-approved DKD patients. Additionally, renal tubule cell-specific Yap1 deletion exacerbated kidney injury in diabetic mice. Mechanistically, Yap1 deletion disrupted MQC, leading to mitochondrial aberrations in mitobiogenesis and mitophagy within tubule cells, ultimately culminating in histologic tubular injury. Notably, Yap1 deletion-induced renal tubule injury promoted the secretion of C-X-C motif chemokine ligand 1 (CXCL1), potentially augmenting M1 macrophage infiltration within the renal microenvironment. These multifaceted events were significantly ameliorated by administrating the YAP1 activator XMU-MP-1 in DKD mice. Consistently, bioinformatic analysis of transcriptomics data from the GEO dataset revealed a noteworthy upregulation of tubule cells-derived chemokine CXCL1 associated with macrophage infiltration among DKD patients. Crucially, overexpression of YAP1 via adenovirus transfection sustained mitochondrial membrane potential, mtDNA copy number, oxygen consumption rate, and activity of mitochondrial respiratory chain complex, but attenuated mitochondrial ROS production, thereby maintaining MQC and subsequently suppressing CXCL1 generation within cultured tubule cells exposed to HG and PA. Collectively, our study establishes a pivotal role of tubule YAP1 inactivation-mediated MQC dysfunction in driving DKD progression, at least in part, facilitated by promoting M1 macrophage polarization through a paracrine-dependent mechanism.

RNA-Binding Protein Hnrnpa1 Triggers Daughter Cardiomyocyte Formation by Promoting Cardiomyocyte Dedifferentiation and Cell Cycle Activity in a Post-Transcriptional Manner.

Stimulating cardiomyocyte (CM) dedifferentiation and cell cycle activity (DACCA) is essential for triggering daughter CM formation. In addition to transcriptional processes, RNA-binding proteins (RBPs) are emerging as crucial post-transcriptional players in regulating CM DACCA. However, whether post-transcriptional regulation of CM DACCA by RBPs could effectively trigger daughter CM formation remains unknown. By performing integrated bioinformatic analysis of snRNA-seq data from neonatal and adult hearts, this study identified Hnrnpa1 as a potential RBP regulating CM DACCA. Hnrnpa1 expression decreased significantly during postnatal heart development. With the use of α-MHC-H2B-mCh/CAG-eGFP-anillin transgenic mice, Hnrnpa1 overexpression promoted CM DACCA, thereby triggering daughter CM formation and enhancing cardiac repair after myocardial infarction (MI). In contrast, CRISPR/Cas9 technology is used to generate CM-specific Hnrnpa1 knockout mice. Hnrnpa1 knockout inhibited cardiac regeneration and worsened cardiac function in the neonatal MI model. Nanopore RNA sequencing, RIP assay, IP-MS, MeRIP-qPCR, PAR-CLIP and luciferase reporter experiments showed that Hnrnpa1 induced Mettl3 post-transcriptional splicing to inhibit m6A-dependent Pbx1 and E2F1 degradation, thereby increasing Runx1, Ccne1, Cdk2 and Ccnb2 expression to promote CM DACCA. In conclusion, Hnrnpa1 triggered daughter CM formation by promoting CM DACCA in a post-transcriptional manner, indicating that Hnrnpa1 might serve as a promising target in cardiac repair post-MI.

DeLTa-Seq: High-Throughput Targeted RNA-Seq of Rice Leaves Without RNA Purification.

DeLTa-seq is a high-throughput RNA-seq library preparation method that enables quantification of the expression of hundreds of arbitrarily selected genes without RNA purification. This method involves direct reverse transcription using rice leaf lysate and targeted RNA-seq library preparation. DeLTa-seq enables the precise quantification of gene expression with a small number of sequencing reads. This chapter provides detailed information on the design of gene-specific primers, sampling of rice leaves, preparation of lysates, direct-lysate reverse transcription, targeted RNA-seq library preparation, and bioinformatic analysis of DeLTa-seq data.

SARS-CoV-2 nucleocapsid protein interaction with YBX1 displays oncolytic properties through PKM mRNA destabilization

BackgroundSARS-CoV-2, a highly contagious coronavirus, is responsible for the global pandemic of COVID-19 in 2019. Currently, it remains uncertain whether SARS-CoV-2 possesses oncogenic or oncolytic potential in influencing tumor progression. Therefore, it is important to evaluate the clinical and functional role of SARS-CoV-2 on tumor progression.MethodsHere, we integrated bioinformatic analysis of COVID-19 RNA-seq data from the GEO database and performed functional studies to explore the regulatory role of SARS-CoV-2 in solid tumor progression, including lung, colon, kidney and liver cancer.ResultsOur results demonstrate that infection with SARS-CoV-2 is associated with a decreased expression of genes associated with cancer proliferation and metastasis in lung tissues from patients diagnosed with COVID-19. Several cancer proliferation or metastasis related genes were frequently downregulated in SARS-CoV-2 infected intestinal organoids and human colon carcinoma cells. In vivo and in vitro studies revealed that SARS-CoV-2 nucleocapsid (N) protein inhibits colon and kidney tumor growth and metastasis through the N-terminal (NTD) and the C-terminal domain (CTD). The molecular mechanism indicates that the N protein of SARS-CoV-2 interacts with YBX1, resulting in the recruitment of PKM mRNA into stress granules mediated by G3BP1. This process ultimately destabilizes PKM expression and suppresses glycolysis.ConclusionOur study reveals a new function of SARS-CoV-2 nucleocapsid protein on tumor progression.

AI-Assisted Identification of Primary and Secondary Metabolomic Markers for Postoperative Delirium.

Despite considerable investigative efforts, the molecular mechanisms of postoperative delirium (POD) remain unresolved. The present investigation employs innovative methodologies for identifying potential primary and secondary metabolic markers of POD by analyzing serum metabolomic profiles utilizing the genetic algorithm and artificial neural networks. The primary metabolomic markers constitute a combination of metabolites that optimally distinguish between POD and non-POD groups of patients. Our analysis revealed L-lactic acid, inositol, and methylcysteine as the most salient primary markers upon which the prediction accuracy of POD manifestation achieved AUC = 99%. The secondary metabolomic markers represent metabolites that exhibit perturbed correlational patterns within the POD group. We identified 54 metabolites as the secondary markers of POD, incorporating neurotransmitters such as gamma-aminobutyric acid (GABA) and serotonin. These findings imply a systemic disruption in metabolic processes in patients with POD. The deployment of gene network reconstruction techniques facilitated the postulation of hypotheses describing the role of established genomic POD markers in the molecular-genetic mechanisms of metabolic pathways dysregulation, and involving the identified primary and secondary metabolomic markers. This study not only expands the understanding of POD pathogenesis but also introduces a novel technology for the bioinformatic analysis of metabolomic data that could aid in uncovering potential primary and secondary markers in diverse research domains.

Identification of Genes Associated with Familial Focal Segmental Glomerulosclerosis Through Transcriptomics and In Silico Analysis, Including RPL27, TUBB6, and PFDN5.

Focal segmental glomerulosclerosis (FSGS) is a major cause of nephrotic syndrome and often leads to progressive kidney failure. Its varying clinical presentation suggests potential genetic diversity, requiring further molecular investigation. This study aims to elucidate some of the genetic and molecular mechanisms underlying FSGS. The study focuses on the use of bioinformatic analysis of gene expression data to identify genes associated with familial FSGS. A comprehensive in silico analysis was performed using the GSE99340 data set from Gene Expression Omnibus (GEO) comparing gene expression in glomerular and tubulointerstitial tissues from FSGS patients (n = 10) and Minimal Change Disease (MCD) patients (n = 8). These findings were validated using transcriptomics data obtained using RNA sequencing from FSGS (n = 3) and control samples (n = 3) from the UAE. Further validation was conducted using qRT-PCR on an independent FFPE cohort (FSGS, n = 6; MCD, n = 7) and saliva samples (FSGS, n = 3; Control, n = 7) from the UAE. Three genes (TUBB6, RPL27, and PFDN5) showed significant differential expression (p < 0.01) when comparing FSGS and MCD with healthy controls. These genes are associated with cell junction organization and synaptic pathways of the neuron, supporting the link between FSGS and the neural system. These genes can potentially be useful as diagnostic biomarkers for FSGS and to develop new treatment options.

Chromatin remodeling by the histone methyltransferase SETD2 drives cardiometabolic heart failure with preserved ejection fraction

Abstract Background Cardiometabolic heart failure with preserved ejection fraction (cHFpEF) is highly prevalent and associates with a poor outcome. Pathological gene expression in heart failure is accompanied by changes in active histone marks without major alterations in DNA methylation. Histone 3 trimethylation at lysine 36 (H3k36me3) - a chromatin signature induced by the histone methyltransferase SETD2 – has shown a strong correlation with changes in gene expression in the human failing heart; however its role in cardiac disease is poorly understood. The present study investigates the role of SETD2/ H3k36me3 in cHFpEF. Purpose To investigate the role of chromatin remodelling in obese HFpEF (obHFpEF). Methods Mice with cardiomyocyte-specific deletion of SETD2 (c-SETD2-/-) were generated and subjected to high fat diet feeding and L-NAME treatment for 15 weeks to induce cHFpEF. Cardiac function and exercise tolerance were assessed by echocardiography and Treadmill exhaustion test, respectively. ChIP-Seq datasets were employed to determine the biological pathways regulated by H3k36me3, whereas chromatin immunoprecipitation assays (ChIP) were performed to investigate SETD2/H3k36me3 enrichment on gene promoters. SETD2 gain- and loss-of-function experiments were performed in cultured cardiomyocytes (CMs) exposed to metabolic stress (palmitic acid). SETD2/H3k36me3 axis was also investigated in left ventricular (LV) myocardial specimens from patients with cHFpEF and control donors. Moreover, pharmacological inhibition of SETD2 was performed in skinned CMs from cHFpEF patients. Results Bioinformatic analysis of ChIP-Seq data in mouse CMs showed a strong involvement of SETD2/H3k36me3 in lipid-related pathways. Specifically, SETD2 and H3k36me3 were upregulated in cHFpEF vs. control mouse hearts and were highly enriched on the promoter of sterol regulatory element-binding transcription factor 1 (SREBP1) gene. SETD2 activation in cHFpEF led to SREBP1 upregulation, myocardial triglyceride accumulation and lipotoxic damage. In cHFpEF mice, cardiomyocyte-specific deletion of SETD2 prevented hypertrophic remodeling, diastolic dysfunction and lung congestion while improving exercise tolerance. Mechanistically, SETD2 deletion blunted H3K36me3 enrichment on SREBP1 promoter thus preventing SREBP1-driven lipid accumulation and leading to a significant rewiring of the cardiac lipidome. These findings were associated with restoration of autophagic flux in the cHFpEF myocardium. In CMs exposed to palmitic acid, SETD2 depletion prevented SREBP1 upregulation, whereas SETD2 overexpression recapitulated lipotoxic damage. Finally, SETD2 was upregulated in LV myocardial samples from cHFpEF patients and its pharmacological inhibition attenuated CM stiffness. Conclusions SETD2 is a new molecular target implicated in the pathophysiology of cHFpEF.

Identification and interaction analysis of molecular markers in myocardial infarction by bioinformatics and next-generation sequencing data analysis

BackgroundCardiovascular diseases are prevalent worldwide with any age, and it is characterized by sudden blockage of blood flow to heart and permanent damage to the heart muscle, whose cause and underlying molecular mechanisms are not fully understood. This investigation aimed to explore and identify essential genes and signaling pathways that contribute to the progression of MI.MethodsThe aim of this investigation was to use bioinformatics and next-generation sequencing (NGS) data analysis to identify differentially expressed genes (DEGs) with diagnostic and therapeutic potential in MI. NGS dataset (GSE132143) was downloaded from the Gene Expression Omnibus (GEO) database. DEGs between MI and normal control samples were identified using the DESeq2 R bioconductor tool. The gene ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed using g:Profiler. Next, four kinds of algorithms in the protein–protein interaction (PPI) were performed to identify potential novel biomarkers. Next, miRNA-hub gene regulatory network analysis and TF-hub gene regulatory network were constructed by miRNet and NetworkAnalyst database, and Cytoscape software. Finally, the diagnostic effectiveness of hub genes was predicted by receiver operator characteristic curve (ROC) analysis and AUC more than 0.800 was considered as having the capability to diagnose MI with excellent specificity and sensitivity.ResultsA total of 958 DEGs were identified, consisting of 480 up-regulated genes and 478 down-regulated genes. The enriched GO terms and pathways of the DEGs include immune system, neuronal system, response to stimulus and multicellular organismal process. Ten hub genes (namely cftr, cdk1, rps13, rps15a, rps27, notch1, mrpl12, nos2, ccdc85b and atn1) were obtained via protein–protein interaction analysis results. MiRNA-hub gene regulatory network and TF-hub gene regulatory network showed that hsa-mir-409-3p, hsa-mir-3200-3p, creb1 and tp63 might play an important role in the MI.ConclusionsAnalysis of next-generation sequencing dataset combined with global network information and validation presents a successful approach to uncover the risk hub genes and prognostic markers of MI. Our investigation identified four risk- and prognostic-related gene signatures, including cftr, cdk1, rps13, rps15a, rps27, notch1, mrpl12, nos2, ccdc85b and atn1. This gene sets contribute a new perspective to improve the diagnostic, prognostic, and therapeutic outcomes of MI.

Screening and identification of key biomarkers associated with endometriosis using bioinformatics and next-generation sequencing data analysis

BackgroundEndometriosis is a common cause of endometrial-type mucosa outside the uterine cavity with symptoms such as painful periods, chronic pelvic pain, pain with intercourse and infertility. However, the early diagnosis of endometriosis is still restricted. The purpose of this investigation is to identify and validate the key biomarkers of endometriosis.MethodsNext-generation sequencing dataset GSE243039 was obtained from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) between endometriosis and normal control samples were identified. After screening of DEGs, gene ontology (GO) and REACTOME pathway enrichment analyses were performed. Furthermore, a protein–protein interaction (PPI) network was constructed and modules were analyzed using the Human Integrated Protein–Protein Interaction rEference database and Cytoscape software, and hub genes were identified. Subsequently, a network between miRNAs and hub genes, and network between TFs and hub genes were constructed using the miRNet and NetworkAnalyst tool, and possible key miRNAs and TFs were predicted. Finally, receiver operating characteristic curve analysis was used to validate the hub genes.ResultsA total of 958 DEGs, including 479 upregulated genes and 479 downregulated genes, were screened between endometriosis and normal control samples. GO and REACTOME pathway enrichment analyses of the 958 DEGs showed that they were mainly involved in multicellular organismal process, developmental process, signaling by GPCR and muscle contraction. Further analysis of the PPI network and modules identified 10 hub genes, including vcam1, snca, prkcb, adrb2, foxq1, mdfi, actbl2, prkd1, dapk1 and actc1. Possible target miRNAs, including hsa-mir-3143 and hsa-mir-2110, and target TFs, including tcf3 (transcription factor 3) and clock (clock circadian regulator), were predicted by constructing a miRNA-hub gene regulatory network and TF-hub gene regulatory network.ConclusionsThis investigation used bioinformatics techniques to explore the potential and novel biomarkers. These biomarkers might provide new ideas and methods for the early diagnosis, treatment and monitoring of endometriosis.

HPV16 E6-induced M2 macrophage polarization in the cervical microenvironment via exosomal miR-204-5p

The persistent infection of high-risk human papillomavirus (HPV) and the progression of cervical cancer necessitate the involvement of microenvironmental immunity. As cervical lesions advance, there is an observed increase in the infiltration of type 2 (M2) macrophages. However, the precise mechanism driving this increased infiltration of M2 macrophages remains unclear. In this study, we investigated the role of exosomes in polarising M2 macrophages in cervical lesions associated with HPV E6. Through the analysis of bioinformatics data and clinical specimens, we discovered a positive correlation between HPV E6/E7 mRNA copy number and the level of M2 macrophage infiltration. Exosomes derived from HPV E6 overexpressed (HPV E6+) cervical squamous cell carcinoma (CESC) cells were found to induce the polarisation of macrophages towards M2 type. Specifically, miR-204-5p, enriched in HPV E6 + CESC exosomes, was transported into macrophages and triggered M2 macrophage polarisation by inhibiting JAK2. The clinical relevance of exosomal miR-204-5p in the progression of cervical lesions was validated through serum samples from 35 cases. Exosomal miR-204-5p emerges as a critical factor influencing M2 macrophage polarisation and is correlated with the severity of cervical lesions. Consequently, miR-204-5p could be used as a potential treatment and a candidate biomarker for cervical lesions.

Inflammatory profile of eosinophils in asthma-COPD overlap and eosinophilic COPD: a multi-omics study.

Elevated blood eosinophil levels in patients with chronic obstructive pulmonary disease (COPD) with or without asthma are linked to increased exacerbations and the effectiveness of inhaled corticosteroid treatment. This study aimed to delineate the inflammatory cellular properties of eosinophils in patients with asthma-COPD overlap (ACO) and eosinophilic COPD (eCOPD). Eosinophils were isolated from the peripheral blood of healthy volunteers, patients with non-eCOPD, and those with ACO/eCOPD. Multi-omics analysis involving transcriptomics, proteomics, and lipidomics was performed, followed by bioinformatic data analyses. In vitro experiments using eosinophils from healthy volunteers were conducted to investigate the molecular mechanisms underlying cellular alterations in eosinophils. Proteomics and transcriptomics analyses revealed cellular characteristics in overall COPD patients represented by viral infection (elevated expression of sterol regulatory element-binding protein-1) and inflammatory responses (elevated levels of IL1 receptor-like 1, Fc epsilon receptor Ig, and transmembrane protein 176B). Cholesterol metabolism enzymes were identified as ACO/eCOPD-related factors. Gene Ontology and pathway enrichment analyses demonstrated the key roles of antiviral responses, cholesterol metabolism, and inflammatory molecules-related signaling pathways in ACO/eCOPD. Lipidomics showed the impaired synthesis of cyclooxygenase-derived mediators including prostaglandin E2 (PGE2) in ACO/eCOPD. In vitro assessment confirmed that IL-33 or TNF-α stimulation combined with IL-5 and IFN-γ stimulation induced cellular signatures in eosinophils in ACO/eCOPD. Atorvastatin, dexamethasone, and PGE2 differentially modulated these inflammatory changes. ACO/eCOPD is associated with viral infection and an inflammatory milieu. Therapeutic strategies using statins and inhaled corticosteroids are recommended to control these pathogenic changes.

Identification of Pathogenic Copy Number Variants in Mexican Patients With Inherited Retinal Dystrophies Applying an Exome Sequencing Data-Based Read-Depth Approach.

Retinal dystrophies (RDs) are the most common cause of inherited blindness worldwide and are caused by genetic defects in about 300 different genes. While targeted next-generation sequencing (NGS) has been demonstrated to be a reliable and efficient method to identify RD disease-causing variants, it doesn't routinely identify pathogenic structural variant as copy number variations (CNVs). Targeted NGS-based CNV detection has become a crucial step for RDs molecular diagnosis, particularly in cases without identified causative single nucleotide or Indels variants. Herein, we report the exome sequencing (ES) data-based read-depth bioinformatic analysis in a group of 30 unrelated Mexican RD patients with a negative or inconclusive genetic result after ES. CNV detection was performed using ExomeDepth software, an R package designed to detect CNVs using exome data. Bioinformatic validation of identified CNVs was conducted through a commercially available CNV caller. All identified candidate pathogenic CNVs were orthogonally verified through quantitative PCR assays. Pathogenic or likely pathogenic CNVs were identified in 6 out of 30 cases (20%), and of them, a definitive molecular diagnosis was reached in 5 cases, for a final diagnostic rate of ~17%. CNV-carrying genes included CLN3 (2 cases), ABCA4 (novel deletion), EYS, and RPGRIP1. Our results indicate that bioinformatic analysis of ES data is a reliable method for pathogenic CNV detection and that it should be incorporated in cases with a negative or inconclusive molecular result after ES.

SULF1 expression is increased and promotes fibrosis through the TGF-β1/SMAD pathway in idiopathic pulmonary fibrosis

BackgroundIdiopathic pulmonary fibrosis (IPF) is a chronic and progressive interstitial lung disease of unknown etiology. Despite the increasing global incidence and poor prognosis, the exact pathogenic mechanisms remain elusive. Currently, effective therapeutic targets and treatment methods for this disease are still lacking. This study tried to explore the pathogenic mechanisms of IPF. We found elevated expression of SULF1 in lung tissues of IPF patients compared to normal control lung tissues. SULF1 is an enzyme that modifies heparan sulfate chains of heparan sulfate proteoglycans, playing a critical role in biological regulation. However, the effect of SULF1 in pulmonary fibrosis remains incompletely understood. Our study aimed to investigate the impact and mechanisms of SULF1 in fibrosis.MethodsWe collected lung specimens from IPF patients for transcriptome sequencing. Validation of SULF1 expression in IPF patients was performed using Western blotting and RT-qPCR on lung tissues. ELISA experiments were employed to detect SULF1 concentrations in IPF patient plasma and TGF-β1 levels in cell culture supernatants. We used lentiviral delivery of SULF1 shRNA to knock down SULF1 in HFL1 cells, evaluating its effects on fibroblast secretion, activation, proliferation, migration, and invasion capabilities. Furthermore, we employed Co-Immunoprecipitation (Co-IP) to investigate the regulatory mechanisms involved.ResultsThrough bioinformatic analysis of IPF transcriptomic sequencing data (HTIPF) and datasets GSE24206, and GSE53845, we identified SULF1 may potentially play a crucial role in IPF. Subsequently, we verified that SULF1 was upregulated in IPF and predominantly increased in fibroblasts. Furthermore, SULF1 expression was induced in HFL1 cells following exposure to TGF-β1. Knockdown of SULF1 suppressed fibroblast secretion, activation, proliferation, migration, and invasion under both TGF-β1-driven and non-TGF-β1-driven conditions. We found that SULF1 catalyzes the release of TGF-β1 bound to TGFβRIII, thereby activating the TGF-β1/SMAD pathway to promote fibrosis. Additionally, TGF-β1 induces SULF1 expression through the TGF-β1/SMAD pathway, suggesting a potential positive feedback loop between SULF1 and the TGF-β1/SMAD pathway.ConclusionsOur findings reveal that SULF1 promotes fibrosis through the TGF-β1/SMAD pathway in pulmonary fibrosis. Targeting SULF1 may offer a promising therapeutic strategy against IPF.

Investigating age-related dynamics and transcriptional signatures of CD8+HLA-DR+ regulatory T lymphocytes: perspectives in understanding immune system aging

The ability of the CD8+HLA-DR+ regulatory T lymphocytes population to regulate the immune response was first described several years ago. It is known that the suppressive effects of these cells depend on intercellular interactions and are mediated by the expression of checkpoint inhibitor molecules such as CTLA-4, TIM-3, PD-1 and LAG-3. The CD8+HLA-DR+ regulatory T cells also share some properties with conventional CD4+ regulatory T lymphocytes. Nevertheless, the characteristics and function of this subpopulation remain poorly understood. Furthermore, studying the properties of CD8+HLA-DR+ regulatory T cells becomes relevant in the light of general age-associated changes in the human immune system and the increased sensitivity of CD8+T lymphocytes to these changes. Therefore, the aim of this study was to investigate the age dynamics and search for transcriptional signatures of the CD8+HLA-DR+ regulatory T cells. For this purpose, flow cytometric analysis of peripheral blood mononuclear cells from 18 donors aged 21 to 85 years was performed. Bioinformatic analysis of single-cell RNA sequencing data was carried out to search for signatures. It was found that CD8+HLA-DR+ regulatory T cells accumulate with age. The transcriptional signatures of this population consist of genes involved in antigen presentation and cytotoxicity, along with a decrease in the expression of genes encoding proteins of activating protein 1 complex. These data suggest mechanisms of suppressor function of CD8+HLA-DR+ regulatory T lymphocytes associated with the ability of these cells to present antigens and perform cytotoxic activity against effector T lymphocytes. The accumulation of the studied cells may imply a potential influence of CD8+HLA-DR+ regulatory T lymphocytes on the efficiency of adaptive immune response in the aging. Further studies of this population may provide insights into its role in age-related changes in the immune system and develop strategies to improve the immune response in the elderly.

Proteomic analysis of the SMN complex reveals conserved and etiologic connections to the proteostasis network.

Molecular chaperones and co-chaperones are highly conserved cellular components that perform a variety of duties related to the proper three-dimensional folding of the proteome. The web of factors that carries out this essential task is called the proteostasis network (PN). Ribonucleoproteins (RNPs) represent an underexplored area in terms of the connections they make with the PN. The Survival Motor Neuron (SMN) complex is an assembly chaperone and serves as a paradigm for studying how specific RNAs are identified and paired with their client substrate proteins to form RNPs. SMN is the eponymous component of a large complex, required for the biogenesis of uridine-rich small nuclear ribonucleoproteins (U-snRNPs), that localizes to distinct membraneless organelles in both the nucleus and cytoplasm of animal cells. SMN protein forms the oligomeric core of this complex, and missense mutations in the human SMN1 gene are known to cause Spinal Muscular Atrophy (SMA). The basic framework for understanding how snRNAs are assembled into U-snRNPs is known. However, the pathways and mechanisms used by cells to regulate their biogenesis are poorly understood. Given the importance of these processes to normal development as well as neurodegenerative disease, we set out to identify and characterize novel SMN binding partners. We carried out affinity purification mass spectrometry (AP-MS) of Drosophila SMN complexes using fly lines exclusively expressing either wildtype or SMA-causing missense alleles. Bioinformatic analyses of the pulldown data, along with comparisons to proximity labeling studies carried out in human cells, revealed conserved connections to at least two other major chaperone systems including heat shock folding chaperones (HSPs) and histone/nucleosome assembly chaperones. Notably, we found that heat shock cognate protein Hsc70-4 and other HspA family members preferentially associated with SMA-causing alleles of SMN. Hsc70-4 is particularly interesting because its mRNA is aberrantly sequestered by a mutant form of TDP-43 in mouse and Drosophila ALS (Amyotrophic Lateral Sclerosis) disease models. Most important, a missense allele of Hsc70-4 (HspA8 in mammals) was recently identified as a bypass suppressor of the SMA phenotype in mice. Collectively, these findings suggest that chaperone-related dysfunction lies at the etiological root of both ALS and SMA.

NR2F2 regulation of interstitial to fetal Leydig cell differentiation in the testis: insights into differences of sex development.

Testicular fetal Leydig cells are a specialized cell type responsible for embryo masculinization. Fetal Leydig cells produce androgens, that induce the differentiation of male reproductive system and sexual characteristics. Deficiencies in Leydig cell differentiation leads to various disorders of sex development and male reproductive defects such as ambiguous genitalia, hypospadias, cryptorchidism, and infertility. Fetal Leydig cells are thought to originate from proliferating progenitor cells in the testis interstitium, marked by genes like Arx , Pdgfra , Tcf21 and Wnt5a . However, the precise mechanisms governing the transition from interstitial cells to fetal Leydig cells remain elusive. Through integrated approaches involving mouse models and single-nucleus multiomic analyses, we discovered that fetal Leydig cells originate from a Nr2f2 -positive non-steroidogenic interstitial cell population. Embryonic deletion of Nr2f2 in mouse testes resulted in disorders of sex development, including dysgenic testes, Leydig cell hypoplasia, cryptorchidism, and hypospadias. We found that NR2F2 promotes the progenitor cell fate while suppresses Leydig cell differentiation by directly and indirectly controlling a cohort of transcription factors and downstream genes. Bioinformatic analyses of single-nucleus ATAC-seq and NR2F2 ChIP-seq data revealed putative transcription factors co-regulating the process of interstitial to Leydig cell differentiation. Collectively, our findings not only highlight the critical role of Nr2f2 in orchestrating the transition from interstitial cells to fetal Leydig cells, but also provide molecular insight into the disorders of sex development as a result of Nr2f2 mutations.

CLONAL HEMATOPOIESIS AND ITS ROLE IN THE DEVELOPMENT OF CARDIOVASCULAR DISEASES

Clonal hematopoiesis (CH) is the increase in somatic clones carrying mutations in hematopoietic stem cells. This biological condition can lead to cancer and is implicated in the development of atherosclerosis and cardiovascular diseases. CH of indeterminate potential (CHIP) refers to somatic mutations in genes that are associated with the development of Coronary heart disease (CHD) and leukemia. Now, with next-generation sequencing, we can detect mutations even if they are present in only a small number of cells in the tissue sample being studied. Consequently, numerous studies have shown that mutations in the DNMT3A, TET2, ASXL1, and JAK2 genes found in the blood are associated with coronary heart disease. The purpose of our study is to detect a genetic variant of genes in Kazakh patients with atherosclerosis, which will further allow us to study the role of CHIP in increasing the risk of developing coronary microvascular dysfunction and CHD. We perform high-throughput whole-exome sequencing in patients with atherosclerosis. The object of the study is samples delivered from the clinic “National Scientific Cardiac Surgery Center” in Astana. The study is carried out in accordance with the principles of the Declaration of Helsinki of the World Medical Association. Genomic DNA extraction was performed on 245 samples using the Illustra Blood Kit (Cytiva, USA). Qualitative and quantitative assessment of the extracted genomic DNA was conducted using the NanoDrop 2000 (Thermo Scientific) and Qubit 2.0 (Thermo Fisher Scientific). Subsequently, DNA library preparation was carried out using the Illumina DNA Prep with Exome 2.5 Enrichment kit. Quality control of the resulting DNA libraries was conducted on a 2100 Bioanalyzer system using the Agilent DNA 1000 Kit and High Sensitivity DNA kit (Agilent Technologies). Following assessment of the DNA library concentration on Qubit 2.0, they were loaded onto the high-performance sequencer NovaSeq 6000 (Illumina, USA) following the manufacturer’s protocol. We conducted human whole-exome sequencing on 245 samples to identify somatic clones in the peripheral blood of patients with atherosclerosis. Patients were divided into three groups – low risk, middle, and high risk of atherosclerotic complications. Bioinformatic analysis of sequence data were performed. We created list of genes associated with CH to deep analysis and to interpreter the data in patient groups. Subsequently, DNA extraction from the remaining samples is performed, followed by sequencing on the NovaSeq 6000 platform. Analysis of the resulting sequenced data is currently underway. Further research and monitoring of CHIP will enable us to understand the mechanisms underlying the development of cardiovascular diseases and to devise a comprehensive management plan for patients with this pathology. Supported by Committee of Science of the Ministry of Science and Higher Education of Republic of Kazakhstan (AP14869903), (BR21881970) and Nazarbayev University CRP (211123CRP1608).

The role of KLF5 in gut microbiota and lung adenocarcinoma: unveiling programmed cell death pathways and prognostic biomarkers

Lung adenocarcinoma (LUAD) is the most important subtype of lung cancer. It is well known that the gut microbiome plays an important role in the pathophysiology of various diseases, including cancer, but little research has been done on the intestinal microbiome associated with LUAD. Utilizing bioinformatics tools and data analysis, we identified novel potential prognostic biomarkers for LUAD. To integrate differentially expressed genes and clinical significance modules, we used a weighted correlation network analysis system. According to the Peryton database and the gutMGene database, the composition and structure of gut microbiota in LUAD patients differed from those in healthy individuals. LUAD was associated with 150 gut microbiota and 767 gut microbiota targets, with Krüppel-like factor 5 (KLF5) being the most closely related. KLF5 was associated with immune status and correlated well with the prognosis of LUAD patients. The identification of KLF5 as a potential prognostic biomarker suggests its utility in improving risk stratification and guiding personalized treatment strategies for LUAD patients. Altogether, KLF5 could be a potential prognostic biomarker in LUAD.Graphical