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Een analyse m.b.v. Raman-spectroscopie van cellen zonder mitochondria (ρ0 cellen) en cellen van ME/CVS-patiënten laat zien dat fenylalanine een hoofdrol speelt in de stofwisseling van beide cellen.

Het lijkt erop dat fenylalanine die rol gaat spelen als de normale stofwisseling ontoereikend is.

Eerder toonden Sarah Myhill, Norman Booth e.a. via een ATP-profiel mitochondriale disfunctie aan.

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

Analyst. 2018 Aug 22. doi: 10.1039/C8AN01437J.

Xu J, Potter M, Tomas C, Elson J, Morten K, Poulton J, Wang N, Jin H, Hou Z, Huang W.

Abstract

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 wild type model and healthy controls.

Remarkably, an increase in intensities of Raman phenylalanine bands

were also observed in CFS patients.

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 relate to mitochondrial/energetic dysfunction in both systems.

Interestingly, phenylalanine can be used as a potential biomarker for 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 machine learning algorithm

therefore has the potential to become a diagnostic tool for CFS.

Keywords:

Raman micro-spectroscopy, single cell, chronic fatigue syndrome, myalgic encephalomyelitis, fatigue, mitochondria, adenosine triphosphate (ATP), phenylalanine, biomarker, oxidative phosphorylation

Met dank aan Manja, die, ondanks haar ziekte, altijd oplettend blijft.