Toggle Main Menu Toggle Search

Open Access padlockePrints

A new approach to find biomarkers in chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) by single-cell Raman micro-spectroscopy

Lookup NU author(s): Dr Cara Tomas, Dr Joanna Elson

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


Abstract

© 2019 The Royal Society of Chemistry. Chronic fatigue syndrome (CFS), also called myalgic encephalomyelitis (ME), is a debilitating disorder characterized by physical and mental exhaustion. Mitochondrial and energetic dysfunction has been investigated in CFS patients due to a hallmark relationship with fatigue; however, no consistent conclusion has yet been achieved. Single-cell Raman spectra (SCRS) are label-free biochemical profiles, indicating phenotypic fingerprints of single cells. In this study, we applied a new approach using single-cell Raman microspectroscopy (SCRM) to examine ρ0 cells that lack mitochondrial DNA (mtDNA), and peripheral blood mononuclear cells (PBMCs) from CFS patients and healthy controls. The experimental results show that Raman bands associated with phenylalanine in ρ0 cells and CFS patient PBMCs were significantly higher than those of the wild-type model and healthy controls. As similar changes were observed in the ρ0 cell model with a known deficiency in the mitochondrial respiratory chain as well as in CFS patients, our results suggest that the increase in cellular phenylalanine may be related to mitochondrial/energetic dysfunction in both systems. Interestingly, phenylalanine can be used as a potential biomarker for the diagnosis of CFS by SCRM. A machine learning classification model achieved an accuracy rate of 98% correctly assigning Raman spectra to either the CFS group or the control group. SCRM combined with a machine learning algorithm therefore has the potential to become a diagnostic tool for CFS.


Publication metadata

Author(s): Xu J, Potter M, Tomas C, Elson JL, Morten KJ, Poulton J, Wang N, Jin H, Hou Z, Huang WE

Publication type: Article

Publication status: Published

Journal: Analyst

Year: 2019

Volume: 144

Issue: 3

Pages: 913-920

Print publication date: 07/02/2019

Online publication date: 22/08/2018

Acceptance date: 21/08/2018

ISSN (print): 0003-2654

ISSN (electronic): 1364-5528

Publisher: Royal Society of Chemistry

URL: https://doi.org/10.1039/c8an01437j

DOI: 10.1039/c8an01437j

PubMed id: 30207334


Altmetrics

Altmetrics provided by Altmetric


Share