4.7 Article

Rapid detection of bacterial infection and viability assessment with high specificity and sensitivity using Raman microspectroscopy

Journal

ANALYTICAL AND BIOANALYTICAL CHEMISTRY
Volume 412, Issue 11, Pages 2505-2516

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s00216-020-02474-2

Keywords

Mycobacterium tuberculosis; Diagnosis; Raman spectroscopy; Viability assessment

Funding

  1. DST
  2. Department of Science and Technology (DST) [SR/S2/JCB-52/2009]
  3. Department of Biotechnology, Government of India [BT/01/CEIB/09/IV/05]
  4. Department of Biotechnology (DBT), Government of India [BT/PR3260/BRB/10/967/ 2011, BT/PR17357/MED/29/1019/ 2016]
  5. DST-FIST [SR/FST/LS11-036/2014(C)]
  6. UGC-SAP [F.4.13/2018/DRS-III (SAP-II)]
  7. DBT-IISc Partnership Program Phase-II [BT/PR27952-INF/22/212/2018]
  8. Infosys Foundation

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Infectious diseases caused by bacteria still pose major diagnostic challenges in spite of the availability of various molecular approaches. Irrespective of the type of infection, rapid identification of the causative pathogen with a high degree of sensitivity and specificity is essential for initiating appropriate treatment. While existing methods like PCR possess high sensitivity, they are incapable of identifying the viability status of the pathogen and those which can, like culturing, are inherently slow. To overcome these limitations, we developed a diagnostic platform based on Raman microspectroscopy, capable of detecting biochemical signatures from a single bacterium for identification as well as viability assessment. The study also establishes a decontamination protocol for handling live pathogenic bacteria which does not affect identification and viability testing, showing applicability in the analysis of sputum samples containing pathogenic mycobacterial strains. The minimal sample processing along with multivariate analysis of spectroscopic signatures provides an interface for automatic classification, allowing the prediction of unknown samples by mapping signatures onto available datasets. Also, the novelty of the current work is the demonstration of simultaneous identification and viability assessment at a single bacterial level for pathogenic bacteria. Graphical abstract

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