The dynamics of Mycobacterium tuberculosis phagosome and the fate of infection

Zhang, Q; Ma, Shaying; Li, Peibo; Xie, Jianping

doi:10.1016/j.cellsig.2023.110715

Cited by 5 publications

(4 citation statements)

References 102 publications

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“…8F). Given the well-documented association of these pathways with immunity 17,18,19 , these ndings suggest a potential involvement of AGPAT3 in the pathogenesis of CESC through immune regulation.…”

Section: Function Enrichment Analysis Of Agpat3 In Cescmentioning

confidence: 65%

AGPAT Family in Cervical Cancer: A Multi-Omics Perspective on Prognosis and Function

liang,

Chen,

Qin

et al. 2024

Preprint

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Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) are the primary histological subtypes of cervical cancer. The AGPAT gene family has been implicated in disease processes across different cancer types, but its specific role and prognostic relevance in cervical cancer remain unclear. This study emphasizes the AGPAT family as a potential biomarker and therapeutic target in cervical cancer due to its significant impact on the disease's development and outcomes. Gene expression data from the AGPAT family and clinical information from 306 CESC cases and 3 control cases were collected from The Cancer Genome Atlas (TCGA) database. These data were analyzed for mRNA expression, prognostic and diagnostic value, clinical correlations, function enrichment, and ESTIMATE score. The study revealed that AGPAT2, AGPAT3, and AGPAT5 mRNA expression was elevated, while AGPAT1 and AGPAT4 expression was reduced in cervical cancer tissues. Particularly, increased levels of AGPAT3 and AGPAT4 expression were associated with a poorer prognosis in cervical cancer patients. Additionally, higher DNA methyl-ation levels of AGPAT3 were observed in CESC tissues compared to normal samples, and specific CpGs within AGPAT3 showed a strong correlation with prognosis. Moreover, AGPAT3 expression was linked to the presence of various tumor-infiltrating immune cells. Experimental evidence demonstrated that inhibiting the AGPAT3 gene led to a significant decrease in the proliferation and migration abilities of the Hela cervical cancer cell line. These results suggest that AGPAT3 could be a valuable biomarker and a promising therapeutic target for predicting the prognosis of individuals with cervical cancer.

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Section: Function Enrichment Analysis Of Agpat3 In Cescmentioning

confidence: 65%

AGPAT Family in Cervical Cancer: A Multi-Omics Perspective on Prognosis and Function

liang,

Chen,

Qin

et al. 2024

Preprint

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“…UBE2L6, an E2 ubiquitin-conjugating enzyme, has been identified as a biomarker for active tuberculosis, displaying heightened expression in the whole blood of tuberculosis patients (Gao et al, 2021). UBE2L6 can also influence the tuberculosis immune response by post-translationally modifying phagosomeassociated proteins through ubiquitination (Zhang et al, 2023), suggesting potential regulation by methylation. Enrichment analysis results reveal that differentially methylated positions in this gene are enriched in the ubiquitin-like protein ligase binding pathway, with 63 genes in this pathway displaying significant hypomethylation.…”

Section: Discussionmentioning

confidence: 99%

Exploring TSPAN4 promoter methylation as a diagnostic biomarker for tuberculosis

Zhang,

Chen,

Zhang

et al. 2024

Front. Genet.

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Background:Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is a persistent infectious disease threatening human health. The existing diagnostic methods still have significant shortcomings, including a low positivity rate in pathogen-based diagnoses and the inability of immunological diagnostics to detect active TB. Hence, it is urgent to develop new techniques to detect TB more accurate and earlier. This research aims to scrutinize and authenticate DNA methylation markers suitable for tuberculosis diagnosis. Concurrently, Providing a new approach for tuberculosis diagnosis.Methods:Blood samples from patients with newly diagnosed tuberculosis and healthy controls (HC) were utilized in this study. Examining methylation microarray data from 40 whole blood samples (22TB + 18HC), we employed two procedures: signature gene methylated position analysis and signature region methylated position analysis to pinpoint distinctive methylated positions. Based on the screening results, diagnostic classifiers are constructed through machine learning, and validation was conducted through pyrosequencing in a separate queue (22TB + 18HC). Culminating in the development of a new tuberculosis diagnostic method via quantitative real-time methylation specific PCR (qMSP).Results:The combination of the two procedures revealed a total of 10 methylated positions, all of which were located in the promoter region. These 10 signature methylated positions facilitated the construction of a diagnostic classifier, exhibiting robust diagnostic accuracy in both cross-validation and external test sets. The LDA model demonstrated the best classification performance, achieving an AUC of 0.83, specificity of 0.8, and sensitivity of 0.86 on the external test set. Furthermore, the validation of signature methylated positions through pyrosequencing demonstrated high agreement with screening outcomes. Additionally, qMSP detection of 2 potential hypomethylated positions (cg04552852 and cg12464638) exhibited promising results, yielding an AUC of 0.794, specificity of 0.720, and sensitivity of 0.816.Conclusion:Our study demonstrates that the validated signature methylated positions through pyrosequencing emerge as plausible biomarkers for tuberculosis diagnosis. The specific methylation markers in the TSPAN4 gene, identified in whole blood samples, hold promise for improving tuberculosis diagnosis. This approach could significantly enhance diagnostic accuracy and speed, offering a new avenue for early detection and treatment.

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“…Phagosome is a cellular substructure formed by phagocytes in the process of immunity [31] . With the development and maturation, phagosome participates in the process of oxidative stress and affects the survival, proliferation and death of cells [32] . The NF-κB signaling pathway is considered a classical pro-in ammatory signaling pathway, and its dysregulation is associated with in ammation and autoimmunity [33] .…”

Section: Discussionmentioning

confidence: 99%

Identification of the susceptible genes of systemic lupus erythematosus and sepsis: based on immune and oxidative stress-related genes

Ye,

He,

Jin

et al. 2023

Preprint

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Background: Systemic lupus erythematosus (SLE) is an autoimmune inflammatory connective tissue disease involving multiple organs. As one of the serious complications of SLE, sepsis (SEP) has a high risk of death. Here, the goal of this study was to identify vulnerable biomarkers that could be used to diagnose SLE and SEP. Methods: We used the Limma R software tool and the Gene Expression Omnibus (GEO) database to find differentially expressed genes (DEGs) in SLE. Additionally, genes associated with oxidative stress and immune system function were chosen from the MSigDB database and the Genecard database, respectively. Weighted gene Coexpression network analysis (WGCNA) was used to identify the important module genes associated with SEP. With the help of WGCNA, machine learning, and logistic regression, immunological and oxidative stress-related hub genes were discovered and validated by an external validation set. The analysis was put to the test using consensus clustering. Immune cell infiltration was investigated in SLE and SEP patients. Results: We obtained 957 genes from the GSE6163 dataset and 2559 genes from the significant module of WGCNA, which yielded 46 genes after taking intersection with immune and oxidative stress-related genes. According to the enrichment analysis's findings, the two diseases share a lot of similar immunological and inflammation-related pathways. Machine learning was utilized to pick 11 hub genes, and ROC was employed to evaluate the diagnostic effectiveness. Furthermore, the expression profiles of the hub genes revealed by logistic regression modeling have a significant diagnostic value. Moreover, consensus clustering revealed a favorable correlation between the severity of immunological and oxidative stress and disease activity in SLE and SEP. Analysis of immune infiltration revealed a more consistent immune cell infiltration behavior between SLE and SEP. Conclusion: In this study, the expression of 11 potential hub genes, including TLR2, IL1RN, IRF9, ISG20, TXK, SH2D1A, IL7R, CD28, ITK, CD3E, and CCR7, were thoroughly analyzed using bioinformatics. An efficient logistic regression model was created, and it was possible to identify a correlation between the progression of SLE and SEP disease and the expression of immunological and oxidative stress by consensus clustering. In addition, there is a similar immunoinvasive behavior between the two diseases. It is helpful to identify the biological markers with potential diagnostic value.

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The dynamics of Mycobacterium tuberculosis phagosome and the fate of infection

Cited by 5 publications

References 102 publications

AGPAT Family in Cervical Cancer: A Multi-Omics Perspective on Prognosis and Function

AGPAT Family in Cervical Cancer: A Multi-Omics Perspective on Prognosis and Function

Exploring TSPAN4 promoter methylation as a diagnostic biomarker for tuberculosis

Identification of the susceptible genes of systemic lupus erythematosus and sepsis: based on immune and oxidative stress-related genes

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