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Serum sCD14, PGLYRP2 and FGA as potential biomarkers for multidrug-resistant tuberculosis based on data-independent acquisition and targeted proteomics.

ABSTRACT: Multidrug-resistant tuberculosis (MDR-TB), defined as tuberculosis (TB) resistant to at least isoniazid and rifampicin, is a major concern of TB control worldwide. However, the diagnosis of MDR-TB remains a huge challenge to its prevention and control. To identify new diagnostic methods for MDR-TB, a mass spectrometry strategy of data-independent acquisition and parallel reaction monitoring was used to detect and validate differential serum proteins. The bioinformatic analysis showed that the functions of differential serum proteins between the MDR-TB group and the drug-sensitive tuberculosis group were significantly correlated to the complement coagulation cascade, surface adhesion and extracellular matrix receptor interaction, suggesting a disorder of coagulation in TB. Here, we identified three potential candidate biomarkers such as sCD14, PGLYRP2 and FGA, and established a diagnostic model using these three candidate biomarkers with a sensitivity of 81.2%, a specificity of 90% and the area under the curve value of 0.934 in receiver operation characteristics curve to diagnose MDR-TB. Our study has paved the way for a novel method to diagnose MDR-TB and may contribute to elucidate the mechanisms underlying MDR-TB.

SUBMITTER: Chen J

PROVIDER: S-EPMC7686995 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Serum sCD14, PGLYRP2 and FGA as potential biomarkers for multidrug-resistant tuberculosis based on data-independent acquisition and targeted proteomics.

Chen Jing J Han Yu-Shuai YS Yi Wen-Jing WJ Huang Huai H Li Zhi-Bin ZB Shi Li-Ying LY Wei Li-Liang LL Yu Yi Y Jiang Ting-Ting TT Li Ji-Cheng JC

Journal of cellular and molecular medicine 20200923 21

Multidrug-resistant tuberculosis (MDR-TB), defined as tuberculosis (TB) resistant to at least isoniazid and rifampicin, is a major concern of TB control worldwide. However, the diagnosis of MDR-TB remains a huge challenge to its prevention and control. To identify new diagnostic methods for MDR-TB, a mass spectrometry strategy of data-independent acquisition and parallel reaction monitoring was used to detect and validate differential serum proteins. The bioinformatic analysis showed that the fu ...[more]

PMID: 32967043

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Project description:The ultimate aim of proteomics is to fully identify and quantify the entire complement of proteins and post-translational modifications in biological samples of interest. For the last 15 years, liquid chromatography-tandem mass spectrometry (LC-MS/MS) in data-dependent acquisition (DDA) mode has been the standard for proteomics when sampling breadth and discovery were the main objectives; multiple reaction monitoring (MRM) LC-MS/MS has been the standard for targeted proteomics when precise quantification, reproducibility, and validation were the main objectives. Recently, improvements in mass spectrometer design and bioinformatics algorithms have resulted in the rediscovery and development of another sampling method: data-independent acquisition (DIA). DIA comprehensively and repeatedly samples every peptide in a protein digest, producing a complex set of mass spectra that is difficult to interpret without external spectral libraries. Currently, DIA approaches the identification breadth of DDA while achieving the reproducible quantification characteristic of MRM or its newest version, parallel reaction monitoring (PRM). In comparative de novo identification and quantification studies in human cell lysates, DIA identified up to 89% of the proteins detected in a comparable DDA experiment while providing reproducible quantification of over 85% of them. DIA analysis aided by spectral libraries derived from prior DIA experiments or auxiliary DDA data produces identification and quantification as reproducible and precise as that achieved by MRM/PRM, except on low?abundance peptides that are obscured by stronger signals. DIA is still a work in progress toward the goal of sensitive, reproducible, and precise quantification without external spectral libraries. New software tools applied to DIA analysis have to deal with deconvolution of complex spectra as well as proper filtering of false positives and false negatives. However, the future outlook is positive, and various researchers are working on novel bioinformatics techniques to address these issues and increase the reproducibility, fidelity, and identification breadth of DIA.

Dataset Information

Serum sCD14, PGLYRP2 and FGA as potential biomarkers for multidrug-resistant tuberculosis based on data-independent acquisition and targeted proteomics.

Publications

Serum sCD14, PGLYRP2 and FGA as potential biomarkers for multidrug-resistant tuberculosis based on data-independent acquisition and targeted proteomics.

Similar Datasets

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