6. Metabolic profiling of biopsy tissue, cell culture and breath
SPME has also been used for collected biopsy, and, in such cases, HS mode is the most commonly used approach. The profile of VOCs permitted the proposal of candidate biomarkers for melanoma and indicated involvement of the compounds in altering the metabolic profile of the studied tissue [21,47]. Comparative analysis of VOCs secreted from healthy and cancerous stomach tissues showed a significant difference in the extracted amounts of 1-propranolol and carbon disulfide. The profiles were also matched with the HS composition of Helicobacter pylori to verify the bacteria as a pathogen of gastric cancer in the cases investigated [51]. In similar studies, lung tissues collected from patients with lung cancer were cultured in vitro in parallel to three types of lung-cancer cell lines. Their profiles of VOCs were compared with the composition of exhaled breath analyzed in the same patients in order to find the correlation between the studied ma- trices [52]. The analysis of exhaled breath alone was also used for the investigation of the metabolic profile and potential biomarkers, which can serve as a non-invasive diagnostic tool in clinical practice [53–55]. As mentioned above, SPME can be successfully used to obtain signature fingerprints of the HS of cell cultures. This approach was utilized for characterization of fibroblasts during their growth in different media [56] and identification of metabolism changes in colon cancer cells under serum-free and serum-reduced growth conditions [57]. HS-SPME analysis of tissue samples was also employed to dis- criminate human remains from decomposed tissues of animals [58] and characterization of several human-tissue samples of different types and originating from different parts of the body [59]. In both cases, it was proposed to use the method for preparing a mixture
177B. Bojko et al./Trends in Analytical Chemistry 61 (2014) 168–180
of VOCs, which could be used as a training set for the Human Remains Detection and Victim Recovery dogs. HS-SPME-GC was also applied to characterize decomposition of fatty acid in the pericar- dial fat tissue collected from cardiac-surgery patients and piglets [60]. It was hypothesized that lipid deposits in brain microcircu- lation can originate from the alteration of these compounds induced by electrocautery. The emission of volatile compounds by bacteria cultures was also investigated by SPME. One of the studied aspects was detec- tion of contamination of packed food with Salmonella typhimurium [37]. The combination of SPME-GC-MS with a multi-layer perceptron (MLP) neural network with a back-propagation algorithm allowed for the prediction of a number of bacteria in unknown samples. Another study performed with the SPME-GCxGC platform pro- vided comprehensive insight into the volatile fingerprint of Pseudomonas aeruginosa and the enhancement of the existing list of VOCs for this species for 28 new compounds [61]. The auto- mated SPME-GC-MS platform was used for the analysis of the influence of different concentrations of cinnamaldehyde on the growth of E. coli at various growth phases [62]. SPME-GC-MS was also used for rapid determination of microbial contamination in cosmetic products (Fig. 4) [82]. The results showed that some volatiles were common for both bacterial cultures and contami- nated samples, while others were characteristic for the specific product, suggesting the influence of the substrate on the bacterial metabolism.
6. Metabolic profiling of biopsy tissue, cell culture and breath
SPME has also been used for collected biopsy, and, in such cases, HS mode is the most commonly used approach. The profile of VOCs permitted the proposal of candidate biomarkers for melanoma and indicated involvement of the compounds in altering the metabolic profile of the studied tissue [21,47]. Comparative analysis of VOCs secreted from healthy and cancerous stomach tissues showed a significant difference in the extracted amounts of 1-propranolol and carbon disulfide. The profiles were also matched with the HS composition of Helicobacter pylori to verify the bacteria as a pathogen of gastric cancer in the cases investigated [51]. In similar studies, lung tissues collected from patients with lung cancer were cultured in vitro in parallel to three types of lung-cancer cell lines. Their profiles of VOCs were compared with the composition of exhaled breath analyzed in the same patients in order to find the correlation between the studied ma- trices [52]. The analysis of exhaled breath alone was also used for the investigation of the metabolic profile and potential biomarkers, which can serve as a non-invasive diagnostic tool in clinical practice [53–55]. As mentioned above, SPME can be successfully used to obtain signature fingerprints of the HS of cell cultures. This approach was utilized for characterization of fibroblasts during their growth in different media [56] and identification of metabolism changes in colon cancer cells under serum-free and serum-reduced growth conditions [57]. HS-SPME analysis of tissue samples was also employed to dis- criminate human remains from decomposed tissues of animals [58] and characterization of several human-tissue samples of different types and originating from different parts of the body [59]. In both cases, it was proposed to use the method for preparing a mixture
177B. Bojko et al./Trends in Analytical Chemistry 61 (2014) 168–180
of VOCs, which could be used as a training set for the Human Remains Detection and Victim Recovery dogs. HS-SPME-GC was also applied to characterize decomposition of fatty acid in the pericar- dial fat tissue collected from cardiac-surgery patients and piglets [60]. It was hypothesized that lipid deposits in brain microcircu- lation can originate from the alteration of these compounds induced by electrocautery. The emission of volatile compounds by bacteria cultures was also investigated by SPME. One of the studied aspects was detec- tion of contamination of packed food with Salmonella typhimurium [37]. The combination of SPME-GC-MS with a multi-layer perceptron (MLP) neural network with a back-propagation algorithm allowed for the prediction of a number of bacteria in unknown samples. Another study performed with the SPME-GCxGC platform pro- vided comprehensive insight into the volatile fingerprint of Pseudomonas aeruginosa and the enhancement of the existing list of VOCs for this species for 28 new compounds [61]. The auto- mated SPME-GC-MS platform was used for the analysis of the influence of different concentrations of cinnamaldehyde on the growth of E. coli at various growth phases [62]. SPME-GC-MS was also used for rapid determination of microbial contamination in cosmetic products (Fig. 4) [82]. The results showed that some volatiles were common for both bacterial cultures and contami- nated samples, while others were characteristic for the specific product, suggesting the influence of the substrate on the bacterial metabolism.
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