Indan Journal of Medical Research Indan Journal of Medical Research Indan Journal of Medical Research Indan Journal of Medical Research
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ORIGINAL ARTICLE
Year : 2014  |  Volume : 140  |  Issue : 6  |  Page : 770-777

MALDI-TOF mass spectrometry proteomic based identification of clinical bacterial isolates


1 Department of Microbiology, All India Institute of Medical Sciences, New Delhi, India
2 Department of Biophysics, All India Institute of Medical Sciences, New Delhi, India

Correspondence Address:
Jyotish C Samantaray
Department of Microbiology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi 110 029
India
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Source of Support: None, Conflict of Interest: None


PMID: 25758576

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Background & objectives: Pathogenic bacteria often cause life threatening infections especially in immunocompromised individuals. Therefore, rapid and reliable species identification is essential for a successful treatment and disease management. We evaluated a rapid, proteomic based technique for identification of clinical bacterial isolates by protein profiling using matrix-assisted laser desorption-ionization time - of - flight mass spectrometry (MALDI-TOF MS). Methods: Freshly grown bacterial isolates were selected from culture plates. Ethanol/formic acid extraction procedure was carried out, followed by charging of MALDI target plate with the extract and overlaying with α-cyano-4 hydroxy-cinnamic acid matrix solution. Identification was performed using the MALDI BioTyper 1.1, software for microbial identification (Bruker Daltonik GmbH, Bremen, Germany). Results: A comparative analysis of 82 clinical bacterial isolates using MALDI -TOF MS and conventional techniques was carried out. Amongst the clinical isolates, the accuracy at the species level for clinical isolates was 98.78%. One out of 82 isolates was not in accordance with the conventional assays because MALDI-TOF MS established it as Streptococcus pneumoniae and conventional methods as Streptococcus viridans. Interpretation & conclusions: MALDI - TOF MS was found to be an accurate, rapid, cost-effective and robust system for identification of clinical bacterial isolates. This innovative approach holds promise for earlier therapeutic intervention leading to better patient care.


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