Kunze-Szikszay, Nils

[["dc.bibliographiccitation.firstpage","6245"],["dc.bibliographiccitation.issue","16-17"],["dc.bibliographiccitation.journal","Applied Microbiology and Biotechnology"],["dc.bibliographiccitation.lastpage","6255"],["dc.bibliographiccitation.volume","105"],["dc.contributor.author","Kunze-Szikszay, Nils"],["dc.contributor.author","Euler, Maximilian"],["dc.contributor.author","Perl, Thorsten"],["dc.date.accessioned","2021-09-01T06:42:43Z"],["dc.date.available","2021-09-01T06:42:43Z"],["dc.date.issued","2021"],["dc.description.abstract","Abstract Diagnosis of bacterial infections until today mostly relies on conventional microbiological methods. The resulting long turnaround times can lead to delayed initiation of adequate antibiotic therapy and prolonged periods of empiric antibiotic therapy (e.g., in intensive care medicine). Therewith, they contribute to the mortality of bacterial infections and the induction of multidrug resistances. The detection of species specific volatile organic compounds (VOCs) emitted by bacteria has been proposed as a possible diagnostic approach with the potential to serve as an innovative point-of-care diagnostic tool with very short turnaround times. A range of spectrometric methods are available which allow the detection and quantification of bacterial VOCs down to a range of part per trillion. This narrative review introduces the application of spectrometric analytical methods for the purpose of detecting VOCs of bacterial origin and their clinical use for diagnosing different infectious conditions over the last decade. Key Points • Detection of VOCs enables bacterial differentiation in various medical conditions. • Spectrometric methods may function as point-of-care diagnostics in near future."],["dc.description.abstract","Abstract Diagnosis of bacterial infections until today mostly relies on conventional microbiological methods. The resulting long turnaround times can lead to delayed initiation of adequate antibiotic therapy and prolonged periods of empiric antibiotic therapy (e.g., in intensive care medicine). Therewith, they contribute to the mortality of bacterial infections and the induction of multidrug resistances. The detection of species specific volatile organic compounds (VOCs) emitted by bacteria has been proposed as a possible diagnostic approach with the potential to serve as an innovative point-of-care diagnostic tool with very short turnaround times. A range of spectrometric methods are available which allow the detection and quantification of bacterial VOCs down to a range of part per trillion. This narrative review introduces the application of spectrometric analytical methods for the purpose of detecting VOCs of bacterial origin and their clinical use for diagnosing different infectious conditions over the last decade. Key Points • Detection of VOCs enables bacterial differentiation in various medical conditions. • Spectrometric methods may function as point-of-care diagnostics in near future."],["dc.identifier.doi","10.1007/s00253-021-11469-7"],["dc.identifier.pii","11469"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/89126"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-455"],["dc.relation.eissn","1432-0614"],["dc.relation.issn","0175-7598"],["dc.title","Identification of volatile compounds from bacteria by spectrometric methods in medicine diagnostic and other areas: current state and perspectives"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","69"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","BMC Microbiology"],["dc.bibliographiccitation.volume","21"],["dc.contributor.author","Kunze-Szikszay, Nils"],["dc.contributor.author","Euler, Maximilian"],["dc.contributor.author","Kuhns, Martin"],["dc.contributor.author","Thieß, Melanie"],["dc.contributor.author","Groß, Uwe"],["dc.contributor.author","Quintel, Michael"],["dc.contributor.author","Perl, Thorsten"],["dc.date.accessioned","2021-04-14T08:28:09Z"],["dc.date.accessioned","2022-08-18T12:35:52Z"],["dc.date.available","2021-04-14T08:28:09Z"],["dc.date.available","2022-08-18T12:35:52Z"],["dc.date.issued","2021-02-28"],["dc.date.updated","2022-07-29T12:07:23Z"],["dc.description.abstract","Abstract\r\n \r\n Background\r\n Hospital-acquired pneumonia (HAP) is a common problem in intensive care medicine and the patient outcome depends on the fast beginning of adequate antibiotic therapy. Until today pathogen identification is performed using conventional microbiological methods with turnaround times of at least 24 h for the first results. It was the aim of this study to investigate the potential of headspace analyses detecting bacterial species-specific patterns of volatile organic compounds (VOCs) for the rapid differentiation of HAP-relevant bacteria.\r\n \r\n \r\n Methods\r\n Eleven HAP-relevant bacteria (Acinetobacter baumanii, Acinetobacter pittii, Citrobacter freundii, Enterobacter cloacae, Escherichia coli, Klebsiella oxytoca, Klebsiella pneumoniae, Pseudomonas aeruginosa, Proteus mirabilis, Staphylococcus aureus, Serratia marcescens) were each grown for 6 hours in Lysogeny Broth and the headspace over the grown cultures was investigated using multi-capillary column-ion mobility spectrometry (MCC-IMS) to detect differences in the VOC composition between the bacteria in the panel. Peak areas with changing signal intensities were statistically analysed, including significance testing using one-way ANOVA or Kruskal-Wallis test (p < 0.05).\r\n \r\n \r\n Results\r\n 30 VOC signals (23 in the positive ion mode and 7 in the negative ion mode of the MCC-IMS) showed statistically significant differences in at least one of the investigated bacteria. The VOC patterns of the bacteria within the HAP panel differed substantially and allowed species differentiation.\r\n \r\n \r\n Conclusions\r\n MCC-IMS headspace analyses allow differentiation of bacteria within HAP-relevant panel after 6 h of incubation in a complex fluid growth medium. The method has the potential to be developed towards a feasible point-of-care diagnostic tool for pathogen differentiation on HAP."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2021"],["dc.identifier.citation","BMC Microbiology. 2021 Feb 28;21(1):69"],["dc.identifier.doi","10.1186/s12866-021-02102-8"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/17742"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/82517"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/112945"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.notes.intern","Merged from goescholar"],["dc.publisher","BioMed Central"],["dc.relation.eissn","1471-2180"],["dc.rights","CC BY 4.0"],["dc.rights.holder","The Author(s)"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.subject","Pneumonia"],["dc.subject","Microbiological techniques"],["dc.subject","Volatile organic compound"],["dc.subject","Metabolite"],["dc.subject","Ion mobility spectrometry"],["dc.title","Headspace analyses using multi-capillary column-ion mobility spectrometry allow rapid pathogen differentiation in hospital-acquired pneumonia relevant bacteria"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","8"],["dc.bibliographiccitation.journal","Antibiotics"],["dc.bibliographiccitation.volume","11"],["dc.contributor.affiliation","Euler, Maximilian; 1Department of Anesthesiology, University Medical Center Göttingen, Robert-Koch-Straße 40, 37075 Göttingen, Germany; isabell.eickel@med.uni-goettingen.de (I.E.); johannes.wieditz@med.uni-goettingen.de (J.W.); konrad.meissner@med.uni-goettingen.de (K.M.); nils.kunze@med.uni-goettingen.de (N.K.-S.)"],["dc.contributor.affiliation","Perl, Thorsten; 2Department of General, Visceral and Pediatric Surgery, University Medical Center Göttingen, Robert-Koch-Straße 40, 37075 Göttingen, Germany; thorsten.perl@med.uni-goettingen.de"],["dc.contributor.affiliation","Eickel, Isabell; 1Department of Anesthesiology, University Medical Center Göttingen, Robert-Koch-Straße 40, 37075 Göttingen, Germany; isabell.eickel@med.uni-goettingen.de (I.E.); johannes.wieditz@med.uni-goettingen.de (J.W.); konrad.meissner@med.uni-goettingen.de (K.M.); nils.kunze@med.uni-goettingen.de (N.K.-S.)"],["dc.contributor.affiliation","Dudakova, Anna; 3Department of Medical Microbiology and Virology, University Medical Center Göttingen, Kreuzbergring 57, 37075 Göttingen, Germany; anna.dudakova@med.uni-goettingen.de (A.D.); esther.maguillarosado@med.uni-goettingen.de (E.M.R.)"],["dc.contributor.affiliation","Maguilla Rosado, Esther; 3Department of Medical Microbiology and Virology, University Medical Center Göttingen, Kreuzbergring 57, 37075 Göttingen, Germany; anna.dudakova@med.uni-goettingen.de (A.D.); esther.maguillarosado@med.uni-goettingen.de (E.M.R.)"],["dc.contributor.affiliation","Drees, Carolin; 4Leibniz-Institute for Analytical Sciences—ISAS—e.V., Bunsen-Kirchhoff-Straße 11, 44139 Dortmund, Germany; drees@medecon.ruhr (C.D.); w.vautz@ion-gas.de (W.V.)"],["dc.contributor.affiliation","Vautz, Wolfgang; 4Leibniz-Institute for Analytical Sciences—ISAS—e.V., Bunsen-Kirchhoff-Straße 11, 44139 Dortmund, Germany; drees@medecon.ruhr (C.D.); w.vautz@ion-gas.de (W.V.)"],["dc.contributor.affiliation","Wieditz, Johannes; 1Department of Anesthesiology, University Medical Center Göttingen, Robert-Koch-Straße 40, 37075 Göttingen, Germany; isabell.eickel@med.uni-goettingen.de (I.E.); johannes.wieditz@med.uni-goettingen.de (J.W.); konrad.meissner@med.uni-goettingen.de (K.M.); nils.kunze@med.uni-goettingen.de (N.K.-S.)"],["dc.contributor.affiliation","Meissner, Konrad; 1Department of Anesthesiology, University Medical Center Göttingen, Robert-Koch-Straße 40, 37075 Göttingen, Germany; isabell.eickel@med.uni-goettingen.de (I.E.); johannes.wieditz@med.uni-goettingen.de (J.W.); konrad.meissner@med.uni-goettingen.de (K.M.); nils.kunze@med.uni-goettingen.de (N.K.-S.)"],["dc.contributor.affiliation","Kunze-Szikszay, Nils; 1Department of Anesthesiology, University Medical Center Göttingen, Robert-Koch-Straße 40, 37075 Göttingen, Germany; isabell.eickel@med.uni-goettingen.de (I.E.); johannes.wieditz@med.uni-goettingen.de (J.W.); konrad.meissner@med.uni-goettingen.de (K.M.); nils.kunze@med.uni-goettingen.de (N.K.-S.)"],["dc.contributor.author","Euler, Maximilian"],["dc.contributor.author","Perl, Thorsten"],["dc.contributor.author","Eickel, Isabell"],["dc.contributor.author","Dudakova, Anna"],["dc.contributor.author","Maguilla Rosado, Esther"],["dc.contributor.author","Drees, Carolin"],["dc.contributor.author","Vautz, Wolfgang"],["dc.contributor.author","Wieditz, Johannes"],["dc.contributor.author","Meissner, Konrad"],["dc.contributor.author","Kunze-Szikszay, Nils"],["dc.date.accessioned","2022-08-04T08:39:16Z"],["dc.date.available","2022-08-04T08:39:16Z"],["dc.date.issued","2022-07-23"],["dc.date.updated","2022-08-03T09:06:01Z"],["dc.description.abstract","(1) Background: Automated blood culture headspace analysis for the detection of volatile organic compounds of microbial origin (mVOC) could be a non-invasive method for bedside rapid pathogen identification. We investigated whether analyzing the gaseous headspace of blood culture (BC) bottles through gas chromatography-ion mobility spectrometry (GC-IMS) enables differentiation of infected and non-infected; (2) Methods: BC were gained out of a rabbit model, with sepsis induced by intravenous administration of E. coli (EC group; n = 6) and control group (n = 6) receiving sterile LB medium intravenously. After 10 h, a pair of blood cultures was obtained and incubated for 36 h. The headspace from aerobic and anaerobic BC was sampled every two hours using an autosampler and analyzed using a GC-IMS device. MALDI-TOF MS was performed to confirm or exclude microbial growth in BCs; (3) Results: Signal intensities (SI) of 113 mVOC peak regions were statistically analyzed. In 24 regions, the SI trends differed between the groups and were considered to be useful for differentiation. The principal component analysis showed differentiation between EC and control group after 6 h, with 62.2% of the data variance described by the principal components 1 and 2. Single peak regions, for example peak region P_15, show significant SI differences after 6 h in the anaerobic environment (p < 0.001) and after 8 h in the aerobic environment (p < 0.001); (4) Conclusions: The results are promising and warrant further evaluation in studies with an extended microbial panel and indications concerning its transferability to human samples."],["dc.description.sponsorship","Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)"],["dc.description.sponsorship","APC support by the Open Access Publication Funds of the Göttingen University"],["dc.description.sponsorship","Open-Access-Publikationsfonds 2022"],["dc.identifier.doi","10.3390/antibiotics11080992"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/112637"],["dc.language.iso","en"],["dc.relation.eissn","2079-6382"],["dc.rights","CC BY 4.0"],["dc.title","Blood Culture Headspace Gas Analysis Enables Early Detection of Escherichia coli Bacteremia in an Animal Model of Sepsis"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]