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

Drees, Carolin; Vautz, Wolfgang; Liedtke, Sascha; Rosin, Christopher; Althoff, Kirsten; Lippmann, Martin; Zimmermann, Stefan; Legler, Tobias J.; Yildiz, Duygu; Perl, Thorsten; Kunze-Szikszay, Nils

doi:10.1007/s00253-019-10181-x

Cited by 39 publications

(44 citation statements)

References 32 publications

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“…For the differentiation of 15 different human pathogenic bacteria after 24 h of incubation, Jünger et al ( 2012 ) required the negative ion mode in addition to the positive one. Our restriction to positive ion mode is in line with the study of Drees et al ( 2019 ) where only one VOC in negative ion mode could be detected for E. coli within the first 8 h of incubation. This aspect could be confirmed by an earlier study (Steppert 2013 ) in which the negative ion mode rarely delivered information compared to the positive ion mode.…”

Section: Discussionsupporting

confidence: 84%

“…Only few studies used IMS to explore the feasibility of fast bacteria identification. Drees et al ( 2019 ) investigated VOCs emitted by E. coli , S. aureus , and P. aeruginosa in headspace of blood cultures using GC-IMS hourly for up to 8 h of incubation. Their results revealed that the best differentiation could be achieved after 6 h of incubation.…”

Section: Discussionmentioning

confidence: 99%

“…It can be assumed that a higher concentration of bacteria may lead to an earlier occurrence of VOCs and therefore to an earlier differentiation by headspace analysis with IMS. Unfortunately, Drees et al ( 2019 ) and Kunze et al ( 2013 ) did not specify the start concentration of the bacteria cultures, although it is apparent that both studies used an initial bacteria suspension with a much lower OD. Therefore, the differentiation in such an early stage in our study might be due to the high initial bacteria concentrations.…”

Section: Discussionmentioning

confidence: 99%

“…While many studies on infection- or pathogen-related VOCs were performed with mass spectrometry technologies, only a few studies have been conducted with ion mobility spectrometry. A differentiation between different bacterial strains and controls in headspace above cultures could be achieved from 2 up to 24 h of incubation (Jünger et al 2012 ; Kunze et al 2013 ; Steppert 2013 ; Drees et al 2019 ). Slowly growing mycobacteria could be detected with differential ion mobility spectrometry (DMS) after 1 week of cultivation.…”

Section: Introductionmentioning

confidence: 99%

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Rapid in vitro differentiation of bacteria by ion mobility spectrometry

Steppert

Schönfelder

Schultz

et al. 2021

Appl Microbiol Biotechnol

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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.

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Section: Discussionsupporting

confidence: 84%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Rapid in vitro differentiation of bacteria by ion mobility spectrometry

Steppert

Schönfelder

Schultz

et al. 2021

Appl Microbiol Biotechnol

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“…The headspace of E. coli, P. aeruginosa, K. pneumoniae, and S. aureus from inoculated artificial sputum medium or nutrient broth was tested with GC-TOF-MS [117]. Similarly, GC-IMS has been deployed to analyse the headspace of blood cultures containing E. coli, S. aureus and P. aeruginosa [118]. A study involving 210 samples of bronchoalveolar lavages found volatile fatty acids in the headspace of Candida alibicans, Enterococcus faecalis, Pseudomonas aeruginosa, K. pneumoniae, Proteus species, S. aureus, and other bacteria [119].…”

Section: Detection Of Urinary Tract Infection Using Volatile Organic mentioning

confidence: 99%

Sniffing Out Urinary Tract Infection—Diagnosis Based on Volatile Organic Compounds and Smell Profile

2020

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Current available methods for the clinical diagnosis of urinary tract infection (UTI) rely on a urine dipstick test or culturing of pathogens. The dipstick test is rapid (available in 1–2 min), but has a low positive predictive value, while culturing is time-consuming and delays diagnosis (24–72 h between sample collection and pathogen identification). Due to this delay, broad-spectrum antibiotics are often prescribed immediately. The over-prescription of antibiotics should be limited, in order to prevent the development of antimicrobial resistance. As a result, there is a growing need for alternative diagnostic tools. This paper reviews applications of chemical-analysis instruments, such as gas chromatography–mass spectrometry (GC-MS), selected ion flow tube mass spectrometry (SIFT-MS), ion mobility spectrometry (IMS), field asymmetric ion mobility spectrometry (FAIMS) and electronic noses (eNoses) used for the diagnosis of UTI. These methods analyse volatile organic compounds (VOCs) that emanate from the headspace of collected urine samples to identify the bacterial pathogen and even determine the causative agent’s resistance to different antibiotics. There is great potential for these technologies to gain wide-spread and routine use in clinical settings, since the analysis can be automated, and test results can be available within minutes after sample collection. This could significantly reduce the necessity to prescribe broad-spectrum antibiotics and allow the faster and more effective use of narrow-spectrum antibiotics.

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