Literature DB >> 33686954

Long non-coding RNAs ENST00000429730.1 and MSTRG.93125.4 are associated with metabolic activity in tuberculosis lesions of sputum-negative tuberculosis patients.

Lin Wang1, Zilu Wen1,2, Hui Ma2, Liwei Wu1, Hui Chen1, Yijun Zhu1, Liangfei Niu2, Qihang Wu1,2, Hongwei Li1, Lei Shi1, Leilei Li1, Leiyi Wan1, Jun Wang1, Ka-Wing Wong2, Yanzheng Song1.   

Abstract

Accurate diagnosis of complete inactivation of tuberculosis lesions is still a challenge with respect to sputum-negative tuberculosis. RNA-sequencing was conducted to uncover potential lncRNA indicators of metabolic activity in tuberculosis lesions. Lung tissues with high metabolic activity and low metabolic activity demonstrated by fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography were collected from five sputum-negative tuberculosis patients for RNA-sequencing. Differentially-expressed mRNAs and lncRNAs were identified. Their correlations were evaluated to construct lncRNA-mRNA co-expression network, in which lncRNAs and mRNAs with high degrees were confirmed by quantitative real-time PCR using samples collected from 11 patients. Prediction efficiencies of lncRNA indicators were assessed by receiver operating characteristic curve analysis. Bioinformatics analysis was performed for potential lncRNAs. 386 mRNAs and 44 lncRNAs were identified to be differentially expressed. Differentially-expressed mRNAs in lncRNA-mRNA co-expression network were significantly associated with fibrillar collagen, platelet-derived growth factor binding, and leukocyte migration involved in inflammatory response. Seven mRNAs (C1QB, CD68, CCL5, CCL19, MMP7, HLA-DMB, and CYBB) and two lncRNAs (ENST00000429730.1 and MSTRG.93125.4) were validated to be significantly up-regulated. The area under the curve of ENST00000429730.1 and MSTRG.93125.4 was 0.750 and 0.813, respectively. Two lncRNAs ENST00000429730.1 and MSTRG.93125.4 might be considered as potential indicators of metabolic activity in tuberculosis lesions for sputum-negative tuberculosis.

Entities:  

Keywords:  RNA-sequencing; lncRNA; sputum-negative tuberculosis

Year:  2021        PMID: 33686954     DOI: 10.18632/aging.202634

Source DB:  PubMed          Journal:  Aging (Albany NY)        ISSN: 1945-4589            Impact factor:   5.682


  4 in total

Review 1.  Long Non-coding RNAs in Tuberculosis: From Immunity to Biomarkers.

Authors:  Xianyi Zhang; Chan Chen; Yuzhong Xu
Journal:  Front Microbiol       Date:  2022-05-11       Impact factor: 6.064

Review 2.  Non-Coding RNAs in the Etiology and Control of Major and Neglected Human Tropical Diseases.

Authors:  Ousman Tamgue; Cybelle Fodieu Mezajou; Natacha Njike Ngongang; Charleine Kameni; Jubilate Afuoti Ngum; Ulrich Stephane Fotso Simo; Fabrice Junior Tatang; Mazarin Akami; Annie Ngane Ngono
Journal:  Front Immunol       Date:  2021-10-19       Impact factor: 7.561

3.  Comprehensive Genetic Analysis of Tuberculosis and Identification of Candidate Biomarkers.

Authors:  Zilu Wen; Liwei Wu; Lin Wang; Qinfang Ou; Hui Ma; Qihang Wu; Shulin Zhang; Yanzheng Song
Journal:  Front Genet       Date:  2022-03-07       Impact factor: 4.599

4.  Identification of Key CircRNAs Related to Pulmonary Tuberculosis Based on Bioinformatics Analysis.

Authors:  Qin Yuan; Zilu Wen; Ke Yang; Shulin Zhang; Ning Zhang; Yanzheng Song; Fuxue Chen
Journal:  Biomed Res Int       Date:  2022-04-04       Impact factor: 3.411

  4 in total

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