Influences of biofluid sample collection and handling procedures on GC–MS based metabolomic studies Kiyoko Bando, 1,2 Rui Kawahara, 1 Takeshi Kunimatsu, 2 Jun Sakai, 3 Juki Kimura, 2 Hitoshi Funabashi, 2 Takaki Seki, 2 Takeshi Bamba, 1 and Eiichiro Fukusaki 1, ⁎ Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1Yamadaoka, Suita, Osaka 565-0871, Japan 1 Safety Research Laboratories, Dainippon Sumitomo Pharma. Co., Ltd., 3-1-98 Kasugade-naka, Konohana-ku, Osaka 554-0022, Japan 2 and Genomic Science Laboratories, Dainippon Sumitomo Pharma. Co., Ltd., 3-1-98 Kasugade-naka, Konohana-ku, Osaka 554-0022, Japan 3 Received 7 December 2009; accepted 23 April 2010 Available online 18 June 2010 Sample collection procedures of pharmacology and toxicology studies might have a great impact on interpretation of metabolomic study results. Characterization of range variation among sample collection methods is necessary to prevent misinterpretation, as is use of optimal methods in animal experiments to minimize biological/technical variation. Here, we investigated the influence of urine and plasma sample collection and handling procedures on GC–MS based metabolomic studies as follows: for urine, pooling period and tube conditions during collection; for plasma, sampling sites, anesthesia and anticoagulants. Metabolic profiles of urine varied dramatically depending on urine pooling period and tube conditions, underscoring the importance of determining appropriate sampling periods in consideration of diurnal effects and targets of effect/toxicity, and suggesting it would be preferable to keep tubes in metabolic cages under iced conditions for urine sampling. Metabolic profiles of plasma differed depending on blood sampling sites. Anesthesia was not effective in reducing individual variation, although the anesthesia was beneficial in reducing discomfort in rats. In GC–MS based metabolomic studies, we recommend that EDTA be used as anticoagulant in plasma sample preparation, because peaks derived from heparin might overlap with endogenous metabolites, which may induce inter-sample variation. The present study demonstrated that biofluid sample collection and handling procedures provide great impact on metabolic profiles, at the very least for minimizing biological/technical variation, sampling period for urine collection should not be set as a short period, and the use of EDTA is recommended as anticoagulant in preparing plasma for analysis by GC–MS. © 2010, The Society for Biotechnology, Japan. All rights reserved. [Key words: Metabolomics; Urine; Plasma; Sample collection; GC–MS] Metabolomic investigations attempt to detect and profile changes in metabolites, which reflect changes in metabolic pathways and may provide information concerning a disease state or the biological stress of an organism (1,2). Metabolomics is increasingly being applied to pharmacology and toxicology studies. In many cases, animal experi- ments are designed, and biofluid (e.g. urine and plasma) samples are collected from animals and analyzed. An important requirement in animal-based pharmacology or toxicology studies is minimization of variation in control animals relative to the changes induced by drugs. However, various physiological factors (e.g. genetic drift, age, dietary variation, and estrus cycle) can markedly affect metabolic profiles of biofluids (3–8), and thus it is sometimes difficult to distinguish between pathophysiological responses and biological/technical variation. Like- wise, there is concern that biofluid sample collection procedures might have a great impact on metabolic profiles. Therefore, it is necessary to characterize the range of variation among different methods of sample collection so as to prevent misinterpretation, and to use optimal methods in animal experiments so as to minimize biological/technical variation. From the 1970s, gas chromatography–mass spectrometry (GC–MS) has became popular for metabolite profiling and is still used for the detection of many metabolic disorders (9). Advantages of GC–MS include high resolution and reproducibility, as well as the availability of Electron Impact (EI) spectral libraries for structural identification (10). The majority of metabolic profiling studies using combined GC–MS and chemometric techniques reside in the field of plant metabolomics (10–12). The application of GC–MS metabolic profiling in the area of pharmacology/toxicology is relatively underdeveloped as compared to NMR and LC-MS; however, GC–MS has great advantages for analyzing organic acids and amino acids, which are often targets in efficacy and/or toxicity studies. Accordingly, metabolic profiling using GC–MS has potential as a powerful tool in toxicological evaluations, providing a comprehensive understanding of the response of biological systems to xenobiotic intervention (9,13). Journal of Bioscience and Bioengineering VOL. 110 No. 4, 491 – 499, 2010 www.elsevier.com/locate/jbiosc The study represents a portion of the dissertation submitted by Kiyoko Bando to Osaka University in partial fulfillment of the requirement for her PhD. ⁎ Corresponding author. Tel./fax: +81 6 6879 7424. E-mail address: fukusaki@bio.eng.osaka-u.ac.jp (E. Fukusaki). 1389-1723/$ - see front matter © 2010, The Society for Biotechnology, Japan. All rights reserved. doi:10.1016/j.jbiosc.2010.04.010