Literature DB >> 33974116

Rapid in vitro differentiation of bacteria by ion mobility spectrometry.

Isabel Steppert1,2, Jessy Schönfelder3,4, Carolyn Schultz1, Dirk Kuhlmeier1,5.   

Abstract

Rapid screening of infected people plays a crucial role in interrupting infection chains. However, the current methods for identification of bacteria are very tedious and labor intense. Fast on-site screening for pathogens based on volatile organic compounds (VOCs) by ion mobility spectrometry (IMS) could help to differentiate between healthy and potentially infected subjects. As a first step towards this, the feasibility of differentiating between seven different bacteria including resistant strains was assessed using IMS coupled to multicapillary columns (MCC-IMS). The headspace above bacterial cultures was directly drawn and analyzed by MCC-IMS after 90 min of incubation. A cluster analysis software and statistical methods were applied to select discriminative VOC clusters. As a result, 63 VOC clusters were identified, enabling the differentiation between all investigated bacterial strains using canonical discriminant analysis. These 63 clusters were reduced to 7 discriminative VOC clusters by constructing a hierarchical classification tree. Using this tree, all bacteria including resistant strains could be classified with an AUC of 1.0 by receiver-operating characteristic analysis. In conclusion, MCC-IMS is able to differentiate the tested bacterial species, even the non-resistant and their corresponding resistant strains, based on VOC patterns after 90 min of cultivation. Although this result is very promising, in vivo studies need to be performed to investigate if this technology is able to also classify clinical samples. With a short analysis time of 5 min, MCC-IMS is quite attractive for a rapid screening for possible infections in various locations from hospitals to airports.Key Points• Differentiation of bacteria by MCC-IMS is shown after 90-min cultivation.• Non-resistant and resistant strains can be distinguished.• Classification of bacteria is possible based on metabolic features.

Entities:  

Keywords:  Antibiotic resistance; Bacteria identification; Diagnostic; Infection; Ion mobility spectrometry (IMS); Volatile organic compounds (VOC)

Year:  2021        PMID: 33974116     DOI: 10.1007/s00253-021-11315-w

Source DB:  PubMed          Journal:  Appl Microbiol Biotechnol        ISSN: 0175-7598            Impact factor:   4.813


  24 in total

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3.  Current developments in ion mobility spectrometry.

Authors:  Gérard Hopfgartner
Journal:  Anal Bioanal Chem       Date:  2019-07-30       Impact factor: 4.142

4.  Canine scent detection as a tool to distinguish meticillin-resistant Staphylococcus aureus.

Authors:  M Koivusalo; C Vermeiren; J Yuen; C Reeve; S Gadbois; K Katz
Journal:  J Hosp Infect       Date:  2017-03-09       Impact factor: 3.926

5.  The changing culture of the microbiology laboratory.

Authors:  Kevin B Laupland; Louis Valiquette
Journal:  Can J Infect Dis Med Microbiol       Date:  2013       Impact factor: 2.471

6.  From pests to tests: training rats to diagnose tuberculosis.

Authors:  Lena Fiebig; Negussie Beyene; Robert Burny; Cynthia D Fast; Christophe Cox; Georgies F Mgode
Journal:  Eur Respir J       Date:  2020-03-20       Impact factor: 16.671

7.  GC-IMS headspace analyses allow early recognition of bacterial growth and rapid pathogen differentiation in standard blood cultures.

Authors:  Carolin Drees; Wolfgang Vautz; Sascha Liedtke; Christopher Rosin; Kirsten Althoff; Martin Lippmann; Stefan Zimmermann; Tobias J Legler; Duygu Yildiz; Thorsten Perl; Nils Kunze-Szikszay
Journal:  Appl Microbiol Biotechnol       Date:  2019-10-30       Impact factor: 4.813

Review 8.  Review on ion mobility spectrometry. Part 1: current instrumentation.

Authors:  R Cumeras; E Figueras; C E Davis; J I Baumbach; I Gràcia
Journal:  Analyst       Date:  2015-03-07       Impact factor: 4.616

9.  Ion mobility spectrometry for microbial volatile organic compounds: a new identification tool for human pathogenic bacteria.

Authors:  Melanie Jünger; Wolfgang Vautz; Martin Kuhns; Lena Hofmann; Siobhán Ulbricht; Jörg Ingo Baumbach; Michael Quintel; Thorsten Perl
Journal:  Appl Microbiol Biotechnol       Date:  2012-02-12       Impact factor: 4.813

10.  Detection and validation of volatile metabolic patterns over different strains of two human pathogenic bacteria during their growth in a complex medium using multi-capillary column-ion mobility spectrometry (MCC-IMS).

Authors:  Nils Kunze; Julia Göpel; Martin Kuhns; Melanie Jünger; Michael Quintel; Thorsten Perl
Journal:  Appl Microbiol Biotechnol       Date:  2013-03-07       Impact factor: 4.813

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  4 in total

1.  Susceptibility Testing by Volatile Organic Compound Detection Direct from Positive Blood Cultures: A Proof-of-Principle Laboratory Study.

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Journal:  Antibiotics (Basel)       Date:  2022-05-24

2.  Blood Culture Headspace Gas Analysis Enables Early Detection of Escherichia coli Bacteremia in an Animal Model of Sepsis.

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Journal:  Antibiotics (Basel)       Date:  2022-07-23

3.  Rapid detection of Staphylococcus aureus and Streptococcus pneumoniae by real-time analysis of volatile metabolites.

Authors:  Alejandro Gómez-Mejia; Kim Arnold; Julian Bär; Kapil Dev Singh; Thomas C Scheier; Silvio D Brugger; Annelies S Zinkernagel; Pablo Sinues
Journal:  iScience       Date:  2022-09-06

4.  Machine Learning Approaches to Identify Discriminative Signatures of Volatile Organic Compounds (VOCs) from Bacteria and Fungi Using SPME-DART-MS.

Authors:  Mehak Arora; Stephen C Zambrzycki; Joshua M Levy; Annette Esper; Jennifer K Frediani; Cassandra L Quave; Facundo M Fernández; Rishikesan Kamaleswaran
Journal:  Metabolites       Date:  2022-03-08
  4 in total

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