Differential mobility spectrometry classification of bacteria

Lauri Hokkinen, Artturi Kesti, Jaakko Lepomäki, O Anttalainen, Anton Kontunen, Markus Karjalainen, Janne Aittoniemi, Risto Vuento, Terho Lehtimäki, Niku Oksala, Antti Roine

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)


<p>Aim: Rapid identification of bacteria would facilitate timely initiation of therapy and improve cost-effectiveness of treatment. Traditional methods (culture, PCR) require reagents, consumables and hours to days to complete the identification. In this study, we examined whether differential mobility spectrometry could classify most common bacterial species, genera and between Gram status within minutes. Materials & methods: Cultured bacterial sample gaseous headspaces were measured with differential mobility spectrometry and data analyzed using k-nearest-neighbor and leave-one-out cross-validation. Results: Differential mobility spectrometry achieved a correct classification rate 70.7% for all bacterial species. For bacterial genera, the rate was 77.6% and between Gram status, 89.1%. Conclusion: Largest difficulties arose in distinguishing bacteria of the same genus. Future improvement of the sensor characteristics may improve the classification accuracy.</p>
Original languageEnglish
Pages (from-to)233-240
Number of pages8
JournalFuture Microbiology
Issue number4
Publication statusPublished - 2020
Publication typeA1 Journal article-refereed


  • DMS
  • IMS
  • bacteria
  • differential mobility spectrometry
  • eNose
  • ion mobility spectrometry

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