Detecting phenotypically resistant Mycobacterium tuberculosis using wavelength modulated Raman spectroscopy

Vincent O. Baron, Mingzhou Chen, Simon O. Clark, Ann Williams, Kishan Dholakia, Stephen H. Gillespie

Research output: Chapter in Book/Report/Conference proceedingChapter

10 Citations (Scopus)

Abstract

Raman spectroscopy is a non-destructive and label-free technique. Wavelength modulated Raman (WMR) spectroscopy was applied to investigate Mycobacterium tuberculosis cell state, lipid rich (LR) and lipid poor (LP). Compared to LP cells, LR cells can be up to 40 times more resistant to key antibiotic regimens. Using this methodology single lipid rich (LR) from lipid poor (LP) bacteria can be differentiated with both high sensitivity and specificity. It can also be used to investigate experimentally infected frozen tissue sections where both cell types can be differentiated. This methodology could be utilized to study the phenotype of mycobacterial cells in other tissues.

Original languageEnglish
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages41-50
Number of pages10
DOIs
Publication statusPublished - 2018

Publication series

NameMethods in Molecular Biology
Volume1736
ISSN (Print)1064-3745

Bibliographical note

Funding Information:
This work was supported by the PreDiCT-TB consortium [IMI Joint undertaking grant agreement number 115337, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution (www.imi.europa.eu). This work was supported by the Department of Health, UK. The views expressed in this chapter are those of the authors and not necessarily those of the Department of Health. This work was supported by the UK Engineering and Physical Sciences Research Council (Grant code EP/J01771X/1) and a European Union FAMOS project (FP7 ICT, 317744). Authors acknowledge the loan of a laser from M Squared Lasers.

Publisher Copyright:
© 2018, Springer Science+Business Media, LLC.

All Science Journal Classification (ASJC) codes

  • Molecular Biology
  • Genetics

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