Literature DB >> 28734362

Discrimination of bacteria by rapid sensing their metabolic volatiles using an aspiration-type ion mobility spectrometer (a-IMS) and gas chromatography-mass spectrometry GC-MS.

Ileana Andreea Ratiu1, Victor Bocos-Bintintan2, Adrian Patrut3, Victor Hugo Moll4, Matthew Turner4, C L Paul Thomas4.   

Abstract

The objective of our study was to investigate whether one may quickly and reliably discriminate different microorganism strains by direct monitoring of the headspace atmosphere above their cultures. Headspace samples above a series of in vitro bacterial cultures were directly interrogated using an aspiration type ion mobility spectrometer (a-IMS), which produced distinct profiles ("fingerprints") of ion currents generated simultaneously by the detectors present inside the ion mobility cell. Data processing and analysis using principal component analysis showed net differences in the responses produced by volatiles emitted by various bacterial strains. Fingerprint assignments were conferred on the basis of product ion mobilities; ions of differing size and mass were deflected in a different degree upon their introduction of a transverse electric field, impacting finally on a series of capacitors (denominated as detectors, or channels) placed in a manner analogous to sensor arrays. Three microorganism strains were investigated - Escherichia coli, Bacillus subtilis and Staphylococcus aureus; all strains possess a relatively low pathogenic character. Samples of air with a 5 cm3 volume from the headspace above the bacterial cultures in agar growth medium were collected using a gas-tight chromatographic syringe and injected inside the closed-loop pneumatic circuit of the breadboard a-IMS instrument model ChemPro-100i (Environics Oy, Finland), at a distance of about 1 cm from the ionization source. The resulting chemical fingerprints were produced within two seconds from the moment of injection. The sampling protocol involved to taking three replicate samples from each of 10 different cultures for a specific strain, during a total period of 72 h after the initial incubation - at 24, 48 and 72 h, respectively. Principal component analysis (PCA) was used to discriminate between the IMS fingerprints. PCA was found to successfully discriminate between bacteria at three levels in the experimental campaign: 1) between blank samples from growth medium and samples from bacterial cultures, 2) between samples from different bacterial strains, and 3) between time evolutions of headspace samples from the same bacterial strain over the 3-day sampling period. Consistent classification between growth medium samples and growth medium inoculated with bacteria was observed in both positive and negative detection/ionization modes. In parallel, headspace air samples of 1 dm3 were collected from each bacterial culture and loaded onto Tenax™-Carbograph desorption tubes, using a custom built sampling unit based on a portable sampling pump. One sample was taken for each of 10 different cultures of a strain, at 24, 48 and 72 h after the initial incubation. These adsorption tubes were subsequently analyzed using thermal desorption - gas chromatography - mass spectrometry (TD-GC-MS). This second dataset was intended to produce a qualitative analysis of the volatiles present in the headspace above the bacterial cultures.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Aspiration ion mobility spectrometry a-IMS; Bacterial chemical profile; Bacterial volatile markers; Headspace air samples; Microorganisms discrimination; Principal component analysis; TD-GC-MS

Mesh:

Substances:

Year:  2017        PMID: 28734362     DOI: 10.1016/j.aca.2017.06.031

Source DB:  PubMed          Journal:  Anal Chim Acta        ISSN: 0003-2670            Impact factor:   6.558


  7 in total

1.  Sensing Precursors of Illegal Drugs-Rapid Detection of Acetic Anhydride Vapors at Trace Levels Using Photoionization Detection and Ion Mobility Spectrometry.

Authors:  Victor Bocos-Bintintan; George-Bogdan Ghira; Mircea Anton; Aurel-Vasile Martiniuc; Ileana-Andreea Ratiu
Journal:  Molecules       Date:  2020-04-17       Impact factor: 4.411

Review 2.  Diversity and Distribution of Volatile Secondary Metabolites Throughout Bacillus subtilis Isolates.

Authors:  Marco Kai
Journal:  Front Microbiol       Date:  2020-04-08       Impact factor: 5.640

Review 3.  Sniffing Out Urinary Tract Infection-Diagnosis Based on Volatile Organic Compounds and Smell Profile.

Authors:  Valentin-Mihai Dospinescu; Akira Tiele; James A Covington
Journal:  Biosensors (Basel)       Date:  2020-07-23

4.  Monitoring the volatile language of fungi using gas chromatography-ion mobility spectrometry.

Authors:  Verena Speckbacher; Susanne Zeilinger; Stefan Zimmermann; Christopher A Mayhew; Helmut Wiesenhofer; Veronika Ruzsanyi
Journal:  Anal Bioanal Chem       Date:  2021-03-06       Impact factor: 4.142

5.  A Smartphone Integrated Platform for Ratiometric Fluorescent Sensitive and Selective Determination of Dipicolinic Acid.

Authors:  Xiang Li; Junsong Wu; Huaguang Hu; Fangfang Liu; Jialian Wang
Journal:  Biosensors (Basel)       Date:  2022-08-22

Review 6.  Bacillus for Plant Growth Promotion and Stress Resilience: What Have We Learned?

Authors:  Teboho Tsotetsi; Lerato Nephali; Motumiseng Malebe; Fidele Tugizimana
Journal:  Plants (Basel)       Date:  2022-09-22

7.  Performances and Biosensing Mechanisms of Interdigitated Capacitive Sensors Based on the Hetero-mixture of SnO2 and In2O3.

Authors:  Akhil Chandran Mukkattu Kuniyil; Janez Zavašnik; Željka Cvejić; Sohail Sarang; Mitar Simić; Vladimir V Srdić; Goran M Stojanović
Journal:  Sensors (Basel)       Date:  2020-11-06       Impact factor: 3.576

  7 in total

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