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Individualized lipid profile in urine-derived extracellular vesicles from clinical patients with Mycobacterium tuberculosis infections.
Lyu, Lingna; Jia, Hongyan; Liu, Qiuyue; Ma, Wenxia; Li, Zihui; Pan, Liping; Zhang, Xiuli.
Afiliación
  • Lyu L; Department of Gastroenterology and Hepatology, Beijing You'an Hospital Affiliated to Capital Medical University, Beijing, China.
  • Jia H; Beijing Key Laboratory for Drug Resistant Tuberculosis Research, Beijing Chest Hospital Affiliated to Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China.
  • Liu Q; Beijing Key Laboratory for Drug Resistant Tuberculosis Research, Beijing Chest Hospital Affiliated to Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China.
  • Ma W; Beijing Key Laboratory for Drug Resistant Tuberculosis Research, Beijing Chest Hospital Affiliated to Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China.
  • Li Z; Department of Gastroenterology and Hepatology, Beijing You'an Hospital Affiliated to Capital Medical University, Beijing, China.
  • Pan L; Beijing Key Laboratory for Drug Resistant Tuberculosis Research, Beijing Chest Hospital Affiliated to Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China.
  • Zhang X; Beijing Key Laboratory for Drug Resistant Tuberculosis Research, Beijing Chest Hospital Affiliated to Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China.
Front Microbiol ; 15: 1409552, 2024.
Article en En | MEDLINE | ID: mdl-38873163
ABSTRACT

Background:

Lipids are a key nutrient source for the growth and reproduction of Mycobacterium tuberculosis (Mtb). Urine-derived extracellular vesicles (EVs), because of its non-invasive sampling, lipid enrichment, and specific sorting character, have been recognized as a promising research target for biomarker discovery and pathogenesis elucidation in tuberculosis (TB). We aim to profile lipidome of Mtb-infected individuals, offer novel lipid signatures for the development of urine-based TB testing, and provide new insights into the lipid metabolism after Mtb infection.

Methods:

Urine-derived extracellular vesicles from 41 participants (including healthy, pulmonary tuberculosis, latent tuberculosis patients, and other lung disease groups) were isolated and individually detected using targeted lipidomics and proteomics technology platforms. Biomarkers were screened by multivariate and univariate statistical analysis and evaluated by SPSS software. Correlation analyses were performed on lipids and proteins using the R Hmisc package.

Results:

Overall, we identified 226 lipids belonging to 14 classes. Of these, 7 potential lipid biomarkers for TB and 6 for latent TB infection (LTBI) were identified, all of which were classified into diacylglycerol (DAG), monoacylglycerol (MAG), free fatty acid (FFA), and cholesteryl ester (CE). Among them, FFA (201) was the most promising biomarker target in diagnosing TB/LTBI from other compared groups and also have great diagnostic performance in distinguishing TB from LTBI with AUC of 0.952. In addition, enhanced lipolysis happened as early as individuals got latent Mtb infection, and ratio of raft lipids was gradually elevated along TB progression.

Conclusion:

This study demonstrated individualized lipid profile of urinary EVs in patients with Mtb infection, revealed novel potential lipid biomarkers for TB/LTBI diagnosis, and explored mechanisms by which EV lipid raft-dependent bio-processes might affect pathogenesis. It lays a solid foundation for the subsequent diagnosis and therapeutic intervention of TB.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Microbiol Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Microbiol Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza