Capturing actively produced microbial volatile organic compounds from human associated samples with vacuum assisted sorbent extraction

ABSTRACTVolatile organic compounds (VOC) from biological samples have unknown origins. VOCs may originate from the host or different microbial organisms from a microbial community. In order to disentangle the origin of microbial VOCs, we performed volatile headspace analysis of bacterial mono- and co-cultures ofStaphylococcus aureus, Pseudomonas aeruginosa, andAcinetobacter baumannii, and stable isotope probing in biological samples of feces, saliva, sewage, and sputum. We utilized mono- and co-cultures to identify volatile production from individual bacterial species or in combination with stable isotope probing to identify the active metabolism of microbes from the biological samples. To extract the VOCs, we employed vacuum assisted sorbent extraction (VASE). VASE is an easy-to-use commercialized solvent-free headspace extraction method for semi-volatile and volatile compounds. The lack of solvents and the near vacuum conditions used make developing a method relatively easy and fast when compared to other extraction options like tert-butylation and solid phase microextraction. However, VASE does not work on nonvolatile compounds, thus excluding many protein analyses and heavy stable isotope labelling experiments. Using the workflow described here, we identified volatile signatures from mono- and co-cultures indicating there were volatiles specific to certain microbes or co-cultures. Furthermore, analysis of the stable isotope probing of biological samples identified VOCs that were either commonly or uniquely produced from the different human derived biological samples. Here we present the general workflow and experimental considerations of VASE.SUMMARYFrom this protocol, readers will be able to extract volatile organic compounds from a biological sample with the vacuum assisted sorbent extraction method, run samples on a GC-MS with the use of the Entech autosampler, and analyze data.