Dataset Information

Identification of serum microRNA biomarkers for tuberculosis using RNA-seq.

ABSTRACT: Tuberculosis (TB) remains a significant human health issue. More effective biomarkers for use in tuberculosis prevention, diagnosis, and treatment, including markers that can discriminate between healthy individuals and those with latent infection, are urgently needed. To identify a set of such markers, we used Solexa sequencing to examine microRNA expression in the serum of patients with active disease, healthy individuals with latent TB, and those with or without prior BCG inoculation. We identified 24 microRNAs that are up-regulated (2.85-1285.93 fold) and 6 microRNAs that are down-regulated (0.003-0.11 fold) (P<0.05) in patients with active TB relative to the three groups of healthy controls. In addition, 75 microRNAs were up-regulated (2.05-2454.58 fold) and 11 were down-regulated (0.001-0.42 fold) (P<0.05) in latent-TB infected individuals relative to BCG- inoculated individuals. Of interest, 134 microRNAs were differentially-expressed in BCG-inoculated relative to un-inoculated individuals (18 up-regulated 2.9-499.29 fold, 116 down-regulated 0.0002-0.5 fold), providing insights into the effects of BCG inoculation at the microRNA level. Target prediction of differentially-expressed microRNAs by microRNA-Gene Network analysis and analysis of pathways affected suggest that regulation of the host immune system by microRNAs is likely to be one of the main factors in the pathogenesis of tuberculosis. qRT-PCR validation indicated that hsa-miR-196b and hsa-miR-376c have potential as markers for active TB disease. The microRNA differential-expression profiles generated in this study provide a good foundation for the development of markers for TB diagnosis, and for investigations on the role of microRNAs in BCG-inoculated and latent-infected individuals.

SUBMITTER: Zhang H

PROVIDER: S-EPMC3930592 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Identification of serum microRNA biomarkers for tuberculosis using RNA-seq.

Zhang Hongtai H Sun Zhaogang Z Wei Wenjing W Liu Zhonghui Z Fleming Joy J Zhang Shuai S Lin Nan N Wang Ming M Chen Maoshan M Xu Yuhui Y Zhou Jie J Li Chuanyou C Bi Lijun L Zhou Guangming G

PloS one 20140220 2

Tuberculosis (TB) remains a significant human health issue. More effective biomarkers for use in tuberculosis prevention, diagnosis, and treatment, including markers that can discriminate between healthy individuals and those with latent infection, are urgently needed. To identify a set of such markers, we used Solexa sequencing to examine microRNA expression in the serum of patients with active disease, healthy individuals with latent TB, and those with or without prior BCG inoculation. We iden ...[more]

PMID: 24586438

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Project description:BackgroundCell lines form the cornerstone of cell-based experimentation studies into understanding the underlying mechanisms of normal and disease biology including cancer. However, it is commonly acknowledged that contamination of cell lines is a prevalent problem affecting biomedical science and available methods for cell line authentication suffer from limited access as well as being too daunting and time-consuming for many researchers. Therefore, a new and cost effective approach for authentication and quality control of cell lines is needed.ResultsWe have developed a new RNA-seq based approach named CeL-ID for cell line authentication. CeL-ID uses RNA-seq data to identify variants and compare with variant profiles of other cell lines. RNA-seq data for 934 CCLE cell lines downloaded from NCI GDC were used to generate cell line specific variant profiles and pair-wise correlations were calculated using frequencies and depth of coverage values of all the variants. Comparative analysis of variant profiles revealed that variant profiles differ significantly from cell line to cell line whereas identical, synonymous and derivative cell lines share high variant identity and are highly correlated (ρ > 0.9). Our benchmarking studies revealed that CeL-ID method can identify a cell line with high accuracy and can be a valuable tool of cell line authentication in biomedical science. Finally, CeL-ID estimates the possible cross contamination using linear mixture model if no perfect match was detected.ConclusionsIn this study, we show the utility of an RNA-seq based approach for cell line authentication. Our comparative analysis of variant profiles derived from RNA-seq data revealed that variant profiles of each cell line are distinct and overall share low variant identity with other cell lines whereas identical or synonymous cell lines show significantly high variant identity and hence variant profiles can be used as a discriminatory/identifying feature in cell authentication model.

Dataset Information

Identification of serum microRNA biomarkers for tuberculosis using RNA-seq.

Publications

Identification of serum microRNA biomarkers for tuberculosis using RNA-seq.

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