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Identifying Dormant Growth State of Mycobacteria by Orthogonal Analytical Approaches on a Single Cell and Ensemble Basis

  • A. C. Neumann
  • , D. Bauer
  • , M. Hoelscher
  • , C. Haisch
  • , A. Wieser
  • University Hospital
  • University of Munich
  • German Center for Infection Research (DZIF), Partner Site Munich
  • Technical University of Munich

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Tuberculosis is currently the single most deadly infectious disease in the world and a public health priority as defined by WHO. Although the disease is in general curable, treatment success is hampered by the necessity of a long and side effect prone treatment. Low treatment efficiency may be partly due to the special growth states that mycobacteria enter to avoid being killed by antibiotics and to persist longer within the host. Such growth states have been recently defined as dormant or persistent. We produced dormant model-organism cultures using an acidification model and characterized those by a multilayered approach using mass spectrometry (MALDI-TOF), microscopy (SEM, Raman), and microbiological techniques (CFU, OD 600 , ATP-levels). With a fast and 96-well-adapted extraction protocol, mycobacteria could be inactivated and extracted for MALDI-TOF analysis. For the first time, we demonstrate growth-state-dependent changes in the mass signatures of the culture, allowing for a reliable differentiation of dormant state and exponential growth. We also demonstrate resuscitation from dormant state back to exponential growth. Viable mycobacteria were immobilized, and single organisms were analyzed individually by Raman microscopy. For single-cell Raman microscopy, Mycobacterium smegmatis cultures were fixed using a new fast and gentle single-step immobilization technique on a hydrophobic glass slide. We were able to distinguish single viable bacteria in the dormant state from their rapidly growing, genetically identical counterparts, identifying the growth state of the culture based on single-organism spectra. This allows for the separation of heterogeneous cultures depending on their growth state using the destruction-free optical method of Raman microscopy.

Original languageEnglish
Pages (from-to)881-887
Number of pages7
JournalAnalytical Chemistry
Volume91
Issue number1
DOIs
StatePublished - 2 Jan 2019

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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