Application of Nylon Affinity Nets to Capture Tuberculosis Extracellular Vesicles and Identify Protein Biomarkers

Authors

  • VIDHI SHARMA Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA
  • MERICA PATRICIA TALLEY Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA
  • Ahana Byne Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA
  • Barbara Birkaya Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA
  • Alessandra Luchini Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA

DOI:

https://doi.org/10.13021/jssr2023.3928

Abstract

Tuberculosis (TB) requires efforts for more efficient diagnostic approaches to combat its impact worldwide. Current diagnostic efforts only identify active disease rather than infection stage and are limited to blood or skin samples, which are difficult to obtain from younger or immunocompromised patients. A promising source for TB diagnosis is the extracellular vesicles (EVs) released by TB bacteria, containing valuable TB biomarkers in many easily accessible biological samples. They provide an accurate distinction between latent TB and TB disease, and thus, can be more informative if captured properly. This study develops a novel method to utilize nylon affinity nets to properly capture EVs from patient urine samples. We used nylon fibers functionalized with synthetic dyes (affinity net) for the capture and concentration of EVs from urine. EVs are examined for protein and DNA content by LC-MS/MS and by identifying the TB genes within EVs using molecular biology techniques (DNA precipitation - ligation mediated amplification, cloning sequencing, and nucleotide blast). Functionalized nylon captured urine EVs contain MTB peptides and nucleic acids, such as LAM, CD81, CD63, CD9, and the rpoB gene (identified by PCR). Identification of various proteins and markers in TB urine could help in sputum-free diagnosis and antibody development. 

Published

2023-10-27

Issue

Section

College of Science: School of Systems Biology

Categories