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Initial study of three different pathogenic microorganisms by gas chromatography-mass spectrometry

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Background: Diagnoses of respiratory tract infections usually happen in the late phase of the disease and usually result in reduction of the pathogen load after broad-spectrum antibiotic therapy, but not… Click to show full abstract

Background: Diagnoses of respiratory tract infections usually happen in the late phase of the disease and usually result in reduction of the pathogen load after broad-spectrum antibiotic therapy, but not in eradication of the pathogen. The development of a non-invasive, fast, and accurate method to detect pathogens has always been of interest to researchers and clinicians alike. Previous studies have shown that bacteria produce organic gases. The current study aimed to identify the volatile organic compounds (VOCs) produced by three respiratory tract pathogens, including Staphylococcus aureus, Escherichia coli and Candida albicans. Methods: The VOCs produced were identified by gas chromatography–mass spectrometry (GC-MS), with prior collection of microbial volatile compounds using solid phase microextraction (SPME) fiber. The volatile compounds were collected by obtaining bacterial headspace samples. Results: Results showed that these three organisms have various VOCs, which were analyzed under different conditions. By ignoring common VOCs, some species-specific VOCs could be detected. The most important VOC of E. coli was indole, also some important VOCs produced by S. aureus were 2,3-pentandione, cis-dihydro-α-terpinyl acetate, 1-decyne, 1,3-heptadiene, 2,5-dimethyl pyrazine, ethyl butanoate and cyclohexene,4-ethenyl. Furthermore, most of the identified compounds by C. albicans are alcohols. Conclusions: The detection of VOCs produced by infectious agents maybe the key to make a rapid and precise diagnosis of infection, but more comprehensive studies must be conducted in this regard.

Keywords: gas chromatography; mass spectrometry; vocs; study; chromatography mass; vocs produced

Journal Title: F1000Research
Year Published: 2017

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