{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T09:00:06Z","timestamp":1788512406739,"version":"build-2803163510"},"reference-count":41,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,5,30]],"date-time":"2025-05-30T00:00:00Z","timestamp":1748563200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["426335750"],"award-info":[{"award-number":["426335750"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Bioeng. Biotechnol."],"abstract":"<jats:p>The rapid identification of bacterial pathogens is critical for the early diagnosis of severe clinical conditions, such as sepsis or implant-associated infections, and for the initiation of timely, targeted therapies. This need is particularly acute within the complex oral microbiome, where diverse opportunistic pathogens contribute to a range of local and systemic diseases. While techniques such as phenotypic systems and MALDI-TOF-MS offer faster results, they remain limited by costs, and operational constraints. To address these challenges and cater to the need for rapid identification of bacteria, we present a system for identification and classification of anaerobic bacteria as a first example. This system combines a pyrolyzer, a gas chromatograph and a highly sensitive ion mobility spectrometer. The ion mobility spectrometer has been optimized for coupling with the gas chromatograph and offers simultaneously recording of ion mobility spectra in both ion polarities during one gas chromatographic separation by using two drift tubes arranged in axial configuration. Feasibility has been demonstrated by building a database of fingerprints of eleven isolated reference samples of anaerobic bacteria with clinical relevance. Preliminary experiments have demonstrated that pattern recognition algorithms can predict the genus of isolated bacteria with a precision of up to 97%.<\/jats:p>","DOI":"10.3389\/fbioe.2025.1582565","type":"journal-article","created":{"date-parts":[[2025,5,30]],"date-time":"2025-05-30T05:47:28Z","timestamp":1748584048000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Identification of anaerobic bacterial strains by pyrolysis-gas chromatography-ion mobility spectrometry"],"prefix":"10.3389","volume":"13","author":[{"given":"Tim","family":"Kobelt","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonas","family":"Klose","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rumjhum","family":"Mukherjee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martin","family":"Lippmann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Szymon P.","family":"Szafranski","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meike","family":"Stiesch","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefan","family":"Zimmermann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,5,30]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1038\/s41579-023-00963-6","article-title":"The oral microbiome: diversity, biogeography and human health","volume":"22","author":"Baker","year":"2024","journal-title":"Nat. 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