- Email: [email protected]
Rapid profiling method for mammalian feces short chain fatty acids by GC-MS
Accepted Manuscript Rapid profiling method for mammalian feces short chain fatty acids by GC-MS Takeshi Furuhashi, Kuniyo Sugitate, Takashi Nakai, Yusuke Jikumaru, Genki Ishihara PII:
S0003-2697(17)30494-3
DOI:
10.1016/j.ab.2017.12.001
Reference:
YABIO 12859
To appear in:
Analytical Biochemistry
Received Date: 22 September 2017 Revised Date:
29 November 2017
Accepted Date: 4 December 2017
Please cite this article as: T. Furuhashi, K. Sugitate, T. Nakai, Y. Jikumaru, G. Ishihara, Rapid profiling method for mammalian feces short chain fatty acids by GC-MS, Analytical Biochemistry (2018), doi: 10.1016/j.ab.2017.12.001. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT
Technical Notes
Rapid profiling method for mammalian feces short
SC
RI PT
chain fatty acids by GC-MS
M AN U
Takeshi Furuhashia, Kuniyo Sugitateb, Takashi Nakaib, Yusuke Jikumarub, Genki Ishiharaa
a Anicom Specialty Medical Institute Inc., 8-17-1, Nishi Shinjuku, Shinjuku-ku,
TE D
Tokyo, Japan
EP
b Agilent Technologies Japan, Ltd. 9-1, Takakuramachi, Hachioji-shi, Tokyo, Japan
Correspondence: Takeshi Furuhashi, Anicom Specialty Medical Institute Inc., 8-17-1,
AC C
Nishi Shinjuku, Shinjuku-ku, Tokyo, Japan
Email: [email protected]
1
ACCEPTED MANUSCRIPT
ABSTRACT
Short chain fatty acids (SCFAs) are key feces metabolites generated by gut bacteria
RI PT
fermentation. Despite the importance of profiling feces SCFAs, technical difficulties in analysis
remain due to their volatility and hydrophilicity. We improve previous protocols to
profile SCFAs and optimize the metabolite profiling platform for mammalian feces
SC
samples.
In this study, we investigated feces as biological samples using gas
M AN U
chromatography-mass spectrometry (GC-MS). Isobutyl chloroformate was used for a derivatization in aqueous solution without drying out the samples. Ultimately, we envisage being able to determine the way in which gut bacteria fermentation influences host gut condition by using our rapid metabolite profiling methods.
TE D
Keywords: SCFA (short chain fatty acids), GC-MS, Gut bacteria, Fermentation
Abbreviations: CE, capillary electrophoresis; EI, electron ionization; EIC, extracted
EP
ion chromatogram; GC-MS, gas chromatography mass spectrometry; LC, liquid chromatography; ODS, octadecyl-silica; SCFAs, short chain fatty acids; SPME,
AC C
solid-phase microextraction; TIC, total ion counting; TMS, trimethylsilyl.
2
ACCEPTED MANUSCRIPT
In fermentation processes, bacteria convert degraded food into gases, alcohol and small fatty acids under anaerobic conditions [1]. Mammalian vertebrates, especially herbivores, possess long and large digestive systems [2]. Gut bacteria are responsible
RI PT
for fermentation in the gut (e.g., foregut and hindgut). Food sources that are not completely digested by host animals (e.g., cellulose) can also be digested by gut bacteria and eventually converted into energy [3].
Among the compounds generated in the fermentation process, short chain fatty acids
SC
(SCFAs) are one of the most important products. SCFAs refer to fatty acids whose
carbon number is between one (e.g., formic acid) and six (e.g., hexanoic acid). Indeed,
M AN U
SCFAs are important for the gut barrier system and modulate the immune system of host animals [4]. They are also related to obesity and inflammation [5, 6]. Changes in SCFA quantity and proportion can be influenced by the food type as well as by the complex gut bacteria community itself (i.e., its diversity) [7]. Genomics data provide information on the relative proportion of bacteria species, but not on quantities of
TE D
specific bacteria species. Accordingly, genomics approaches solely indicate bacteria presence in the gut, but cannot shed light on functional changes (i.e., metabolite changes). Conversely, information about bacteria genomics does not yield information
AC C
SCFAs.
EP
on actual fermentation processes. This requires metabolomics approaches, especially for
Although SCFA profiling has been a major topic in gut bacteria studies [8, 9], many researchers have encountered technical difficulties. This is mainly attributable to the highly volatile and hydrophilic characteristics of SCFAs. In particular, biological materials such as feces are complex, making it necessary to separate SCFAs chromatographically. Nonetheless, because of their hydrophilic characteristics, the conventional liquid chromatography (LC) mobile phase – which is water-acetonitrile with formic acid – cannot be applied. Firstly, the LC-MS system based on ODS column separation does not give reasonable chromatographic separation with such a mobile 3
ACCEPTED MANUSCRIPT
phase. Secondly, it is not possible to use formic acid and acetic acid to enhance atmosphere ionization (i.e., ESI and APCI) because these are also present in samples as SCFAs. Ion exclusion chromatography can also be applied, but due to the eluent (e.g.,
reduces the accuracy of SCFA identification and sensitivity.
RI PT
sulfuric acid) [10] it normally cannot be hyphenated with mass spectrometry. This
GC-MS can be a suitable technique for volatile compounds analysis. GC-MS offers
SC
several approaches for volatile compounds: headspace and/or solid phase micro
extraction [11, 12], and derivatization [13]. Despite their volatility, SCFAs in the gas
M AN U
phase from biological samples often have a low concentration for headspace analysis. SPME (solid-phase microextraction) can contain organic acids and concentrate target metabolites. SPMEs, however, are difficult to quantify due to variations in partition equilibria between sample and gas, and between gas and SPME fibers (14). Derivatization can involve silylation (i.e., TMS (trimethylsilyl)) [15], alkylation [16],
TE D
and esterification [17]. Many derivatization protocols require non-aqueous conditions, calling for removing water from biological samples prior to the derivatization reaction. Here, SCFAs can evaporate and disappear during the drying process. In previous studies,
EP
esterification using chloroformate was applied for derivatization under aqueous solutions [18]. Nonetheless, it remains difficult to profile certain SCFAs which overlap
AC C
with the injection peak. As both headspace and SPME are not always suitable for large numbers of samples or for preservation, it would be advantageous to pursue an improved derivatization protocol. The above technical issues call for improving the SCFA profiling methods. We focus on improving the GC-MS derivatization protocol because of the identification potential and sensitivity of mass spectrometry. Here, we introduce a SCFA profiling platform for mammalian feces samples.
4
ACCEPTED MANUSCRIPT
For SCFA standard analysis, we prepared 15 SCFAs standard mix (500pmole-10µmole of each SCFA present in a reaction solution were tested) (Supplementary Table 1). Add 125 µL 20 mM NaOH, 100 µL pyridine and alcohol solution (150 µL 1-propanol
RI PT
with 275µL water, or 70µL isobutanol with 355µL water or make up 650µL with 1-butanol saturated water). One boiling stone was placed into the tube to avoid bumping, and then solution was derivatized with 50 µL of chloroformate (propyl/
isobutyl/1-butyl-). The lid was kept open for 1 min to release generated gases. The lid
SC
was then closed and the sample vortexed. The tube was spun down, 150 µL hexane was added, followed by centrifuging at 21,000 g for 2 min. Thereafter, the upper hexane
or split (1:50) into GC-MS.
M AN U
phase was transferred into a GC vial. Then, we injected either 1 µL with splitless mode
Freshly collected feces (human/dog/cat; 50-100 mg fresh weight) are placed into 2 mL screw cap tubes with ceramic beads (KT03961-1; Bertin Technologies, France). We then added 1 mL 10% isobutanol and homogenized mechanically (Precellys Evolution;
TE D
Bertin Technologies, France) at 6000 rpm for 20 s twice with a 30 s interval. The sample was then centrifuged at 21,000g for 5 min and 675 µL supernatant was transferred to a new tube. We then added 20 µg 3-Methyl pentanoate as internal
EP
standard [19]. The chloroformate derivatization protocol is modified after Zheng et al. (2013) [18]. 125 µL 20 mM NaOH solution and 400 µL chloroform was then added.
AC C
The tube was vortexed and centrifuged at 21,000 g for 2 min. 400 µL upper aqueous phase was transferred into a new tube. Alcohol (70 µL isobutanol) and 100 µL pyridine was then added. Ultra-high quality water was added to make up 650 µL total volume. A boiling stone was placed into the tube to avoid bumping. Samples can be frozen at this stage prior to the derivatization process. We then carefully added 50 µL of isobutyl chloroformate. The lid was kept open for 1 min to release generated gases. The lid was then closed and the sample vortexed. The tube was spun down, 150 µL hexane was added, followed by centrifuging at 21,000 g
5
ACCEPTED MANUSCRIPT
for 2 min. Thereafter, the upper hexane-isobutanol phase was transferred into a GC vial. Then, we injected either 1 µL with splitless mode or split (1:50) into GC-MS. For SCFA quantification, GC-MS measurements were carried out on a single
RI PT
quadrupole mass spectrometer (5977B-MSD; Agilent Technologies, Santa Clara, CA, USA) equipped with 7890B GC (Agilent Technologies, Santa Clara, CA, USA) and
7693 auto sampler (Agilent Technologies, Santa Clara, CA, USA). The temperature of the GC-MS ion source and the transfer line for the samples was 250°C.
SC
HP-5MS 30 m, 0.25 mm, 0.25 µm (19091S-433, Agilent, USA) was used as a GC
column. The oven temperature gradient for the samples was as follows. After a 5 min,
M AN U
50oC isotherm period, the oven was programmed to rise to 150oC at a rate of 5oC min-1, then rise to 330oC at a rate of 40oC min-1, held at 330oC for 1 min. The temperature of both the GC-MS ion source and transfer line was set at 250oC. The scan range was between m/z 30-600.
To quantify SCFAs, we calculated the peak areas of a conventional 70eV EI mode
TE D
(Extractor ion source; Agilent Technologies, Santa Clara, CA, USA) extracted ion chromatogram using software (Mass Hunter; Agilent Technologies, Santa Clara, CA, USA). The chosen m/z and retention time for quantification is described in
EP
Supplementary Table 1. Formic acid, acetic acid, propionic acid, isobutyric acid, and butanoic acid were quantified with split mode. Others were quantified with splitless
AC C
mode.
Several factors can affect esterification, namely solvents (i.e., alcohol), catalysts as well as contaminants (i.e., matrix effect). In this study, we compared a combination of alcohol and chloroformate (1-propanol, 1-butanol, isobutanol, 2-butanol). Changing alcohol together with chloroformate not only shifted the retention time shift, but also influenced the solubility, sensitivity and byproduct peak. Firstly, esters were eluted from propyl ester (1-propanol with propyl chloroformate), isobutyl ester (isobutanol with
6
ACCEPTED MANUSCRIPT
isobutyl chloroformate) and then 1-butyl esters (1-butanol with butyl chloroformate) (Supplementary Table 1). The solubility of 2-butanol in water is high, while the solubility of isobutanol is about
RI PT
10% in water and that of 1-butanol is clearly less than 10%. Due to the solubility of SCFAs in aqueous solution, 2-butanol was previously considered as a candidate solvent. Nevertheless, derivatization with 2-butanol showed a low derivatization efficiency, possibly because the branch structure caused a steric hindrance of the Sn2 reaction.
SC
Consistent with this, when 2-butanol solvent mixed with propyl chloroformate was
applied, both propyl ester and 2-butyl ester were produced at peaks of almost the same
suitable for butyl esterification.
M AN U
height (Supplementary Fig. 1A). Accordingly, we conclude that 2-butanol is not
Formate, acetate and propionate, however, were near the solvent (injection peak) and those peaks were poorly resolved in splitless mode. Split mode can be applied to deconvolute the solvent and SCFA peaks (Supplementary Fig. 1B-C). In the case of
TE D
formic acid and acetic acid, both SCFAs required a split (i.e., split ratio 50) in all tested solvents. Regarding propyl ester derivatized with 1-propanol, propyl esters showed good sensitivity but the formate propyl ester peak was still very close to solvent peaks.
EP
As such, butyl esterification is suggested particularly for formate analysis. The low solubility of 1-butyl ester in water can lead to phase separation, when excess (>
AC C
10%) 1-butanol was added into solution. In this study, we used a 1-butanol saturated water solution. The standard curve of SCFAs derivatized with 1-butanol as well as isobutanol showed good linearity. The solubility of isobutanol (10% isobutanol was applied in this study) is moderate and useful. In general, it is important to profile acetate, propionate, butyrate, valerate and caproate in many biological materials. Isobutyl ester is a good first choice. Reproducibility and stability of esterification was confirmed by calculating calibration curves (Supplementary Fig. 2), showing R2>0.99 in all SCFAs.
7
ACCEPTED MANUSCRIPT
In a previous study, we used NaOH as a base. In the present experiment, we tested another base, NH3, but its byproduct peak (e.g., carbamate) was very broad and overlapped many of the SCFAs (Supplementary Fig. 1D-F). Pyridine as a catalyst was
RI PT
necessary in all cases. We confirmed that NaOH and pyridine are inevitable in this derivatization process, as previously described [18].
The reaction of chloroformate was severe, generating gases in all tested combinations of alcohol. It often caused a bumping of the sample solution when the sample is vortexed.
SC
We improved this by adding a boiling stone prior to addition of chloroformate. This
avoided bumping completely: the reaction proceeded at a constant rate and the reaction
M AN U
appeared to be almost complete within 3 min after adding chloroformate (i.e., the bubbling ceased).
We tested the feces samples of humans and cats (Fig. 1A-B, Supplementary Table2). We commonly detected C2 (i.e., acetic acid), C3 (e.g., propionic acid), and C4 (e.g., butanoic acid) in all tested samples. Acetate was the dominant SCFA among all feces.
TE D
Formic acid was not detected in cat feces in this study, and longer chain SCFAs (i.e., hexanoic acid) were recorded in cat feces. Such profiles could reflect diet differences. Cats are carnivores and the proportion of protein in cat food is generally high (>20%).
EP
Moreover, cats harbor Clostridium in their guts, a bacterium which is typically present in carnivorous mammals and produces hexanoic acid [20].
AC C
Sample pre-treatment is important especially in the case of lipid-rich biological samples such as feces because lipids can influence the derivatization process. It is advantageous to remove the many lipophilic compounds containing carboxylic acid in biological samples (e.g., long chain free fatty acids) by phase separation before the derivatization process. In this study, chloroform was applied for this purpose. This helps to avoid blocking derivatization by too many contaminants and removes the contaminant peaks in the GC chromatogram. The distribution ratio of SCFA in chloroform were not same between SCFAs, and loss by phase separation increased with increase of carbon chain
8
ACCEPTED MANUSCRIPT
length (Supplementary Fig. 3A). Therefore, it is necessary to consider ratio difference in quantification efforts. Another concern for biological samples is the matrix effect. For this reason, stable
RI PT
isotope (deuterium) labelled acetate (D3), propionate (D5), butyrate (D7) were spiked in feces samples and recovery rates were calculated (n=4). The recovery rates of D-acetate and D-propionate were nearly 100%, while that of D-butyrate was around 60%, which was nearly the same value as the distribution ratio during chloroform phase separation.
SC
Hence, chloroform separation needs to be considered as a primary factor for
quantification. To check the reproducibility of feces SCFA quantification, we measured
(Supplementary Table 3).
M AN U
four replicates of cat feces and calculate RSD. RSD was between 0.5 and 9.7
The suggested isobutyl esterification protocol based on chloroformate enables rapid SCFA profiling for various biological samples, especially feces. This is an important
TE D
step forward in investigating gut bacteria fermentation processes. GC-MS helps to identify SCFAs more precisely than LC or CE without connection to MS and can detect small amounts of SCFAs due to its high sensitivity. Compared with the headspace and
EP
thermal desorption protocols, derivatization increases sensitivity as well as peak resolution of SCFAs. In fact, we compared the signal to noise ratio between SPME and
AC C
isobutyl esterification (Supplementary Table 4). In most of the SCFAs, isobutyl esterification showed better s/n ratios than those measured by SPME. In view of sensitivity, isobutyl esterification can detect SCFAs from feces samples that are under the detection limit for SPME. Moreover, the volatility of SCFAs drops when SCFAs are present in aqueous solution. This decreases the sensitivity of SPME measurements. In contrast, our isobutyl esterification protocol is not greatly influenced by aqueous solution. In derivatization, TMS derivatization has also been used in previous studies. In the diethyl ether extraction-TMS derivatization protocol, sensitivity for small SCFAs (e.g., formate and acetate) was low (Supplementary Fig. 3B). In contrast, butyl 9
ACCEPTED MANUSCRIPT
esterified small SCFAs were sensitive enough (unpublished data). Moreover, diethyl ether solution is difficult to handle (pipette) precisely; its high volatility is also disadvantageous for quantification and derivatization processes.
RI PT
As opposed to all other GC-MS protocols, esterification by chloroformate can be conducted in aqueous solutions at room temperature. Compared with esterification in
non-aqueous solutions (e.g., BF3 or H2SO4 in methanol) [17], the protocol is very useful and practical.
SC
Adding boiling stones enabled operators to conduct experiments without bumping
incidents. As our approach can be combined with an auto sampler, automation of the
M AN U
derivatization step can be achieved. Accordingly, this protocol has a high potential for being applied in clinical purposes, e.g., the diagnosis of chronic intestinal disease.
Acknowledgement
We thank Mr Suzuki, Dr Oi, and Mr Ukawa for giving us feces samples and kind encouragement. Dr
AC C
EP
TE D
Stachowitsch improved the English of an early draft.
10
ACCEPTED MANUSCRIPT
References
[1] Zeikus, J. G., Chemical and fuel production by anaerobic bacteria. Ann. Rev.
RI PT
Microbiol 1980, 34, 423-64.
[2] Kararli, T. T. Comparison of the gastrointestinal anatomy, physiology, and
biochemistry of humans and commonly used laboratory animals. Biopharmaceutics &
SC
Drug Disposition 1995, 16, 351-380.
M AN U
[3] den Besten, G., van Eunen, K., Groen, A. K., Venema, K., Reijngoud, D. J., Bakker, B. M., The role of short-chain fatty acids in the interplay between diet, gut microbiota, and host energy metabolism. Journal of Lipid Research 2013, 54, 2325-2340.
[4] Khan, M. T., Duncan, S. H., Stams, A. J. M., van Dijl, J. M., Flint, H. J., Harmsen,
TE D
H. J. M. The gut anaerobe Faecalibacterium prausnitzii uses an extracellular electron shuttle to grow at oxic–anoxic interphases. The ISME Journal 2012, 6, 1578–1585.
EP
[5] Ley, R. E., Bäckhed, F. Turnbaugh, P., Lozupone, C. A., Knight, R. D. Gordon, J. I.
AC C
Obesity alters gut microbial ecology. PNAS 2005, 102(31), 11070–11075.
[6] Patrice D. Cani, P. D., Bibiloni, R., Knauf, C., Waget, A., Neyrinck, A. M., Delzenne, N. M., Burcelin, R. Changes in Gut Microbiota Control Metabolic Endotoxemia-Induced Inflammation in High-Fat Diet–Induced Obesity and Diabetes in Mice. Diabetes 2008, 57, 1470-1481．
[7] Dowd, S. E., Callaway, T. R., Wolcott, R. D., Sun, Y., McKeehan, T., Hagevoort, R. G., Edrington, T. S. Evaluation of the bacterial diversity in the feces of cattle using 16S rDNA bacterial tag-encoded FLX amplicon pyrosequencing (bTEFAP). BMC 11
ACCEPTED MANUSCRIPT
Microbiology 2008, 8(125), 1-8.
[8] Matsumoto, M., Kibe, R, Ooga, T., Aiba, Y., Kurihara, S., Sawaki, E., Koga, Y.,
RI PT
Benno, Y. Impact of intestinal microbiota on intestinal luminal metabolome. Scientific reports 2012, 2(233), 1-10.
[9] Primec, M., Mičetić-Turk, D., Langerholc, T. Analysis of short-chain fatty acids in
SC
human feces: A scoping review. Analytical Biochemistry 2017, 526, 9-21.
M AN U
[10] Niven, S. J., Beal, J. D., Brooks, P. H., The simultaneous determination of short chain fatty acid, monosaccharides and ethanol in fermented liquid pig diets. Animal Feed Science and Technology 2004, 117, 339-345.
[11] Batista, R. B., Grimm, C. C. Semiquantitative Determination of Short-Chain Fatty
TE D
Acids in Cane and Beet Sugars. Journal of Chromatographic Science 2002, 40,127-132.
[12] Caroprese, A., Gabbanini, S., Beltramini, C., Lucchi, E., Valgimigli, L.
EP
HS-SPME-GC-MS analysis of body odor to test the efficacy of foot deodorant
AC C
formulations. Skin Research and Technology 2009, 15, 503-510.
[13] Goto, A. S., Korenaga, T., Chikaraishi, Y. Methyl and ethyl chloroformate derivatization for compound specific stable isotope analysis (CSIA) of fatty acids. Researches in Organic Geochemistry 2011, 27, 91-95.
[14] Savary, B. J., Nuñez, A. Gas chromatography–mass spectrometry method for determining the methanol and acetic acid contents of pectin using headspace solid-phase microextraction and stable isotope dilution. Journal of Chromatography A 2003, 1017, 151-159. 12
ACCEPTED MANUSCRIPT
[15] Olsen, M. A.; Mathiesen, S. D.; Production rates of volatile fatty acids in the minke whale (Balaenoptera acutorostrata) forestomach. British Journal of Nutrition 1996, 75,
RI PT
21-31.
[16] Pons, A., Richet, C., Robbe, C., Herrmann, A., Timmerman, P., Huet, G., Leroy,
Y., Carlstedt, I., Capon, C., Zanetta, J. P. Sequential GC/MS Analysis of Sialic Acids,
SC
Monosaccharides, and Amino Acids of Glycoproteins on a Single Sample as
M AN U
Heptafluorobutyrate Derivatives. Biochemistry 2003, 42, 8342-8353.
[17] Hallmann, C., van Aarssen, B. G. K., Grice, K., Relative efficiency of free fatty acid butyl esterification. Choice of catalyst and derivatization Procedure. Journal of Chromatography A 2008, 1198–1199, 14-20.
TE D
[18] Zheng, X., Qiu, Y., Zhong, W., Baxter, S., Su, M., Li, Q., Xie, G., Ore, B. M., Qiao, S., Spencer, M. D., Zeisel, S. H., A targeted metabolomic protocol for short-chain fatty
EP
acids and branched-chain amino acids. Metabolomics 2013, 9(4), 818-827.
[19] Mellon, A. F.; , Deshpande, S. A.; Mathers, J, C.; Bartlett, K.; Effect of oral
AC C
antibiotics on intestinal production of propionic acid. Arch Dis Child 2000, 82, 169– 172.
[20] Zhu, X.; Tao, Y.; Liang, C.; Li, X.; Wei, N.; Zhang, W.; Zhou, Y.; Yang, Y.; Bo, T.; The synthesis of n-caproate from lactate: a new efficient process for medium-chain carboxylates production. Scientific Reports 2015, 5, 1-9.
13
ACCEPTED MANUSCRIPT
Figure captions
GC chromatogram (split 50 mode) of the feces short
RI PT
Fig. 1.
chain fatty acid isobutyl ester. (A) Human feces
sample, from top to bottom, TIC (total ion counting), EIC (extracted ion chromatogram) m/z 85, EIC m/z
SC
99. Eight short chain fatty acids (from formic acid to pentanoic acid) were profiled. (B) Cat feces sample,
M AN U
from top to bottom, TIC, EIC m/z 85, EIC m/z 99. Nine short chain fatty acids (from acetic acid to
Supplementary Fig. 1.
TE D
hexanoic acid) were profiled.
GC chromatogram (A-E) and mass spectrum (F) of
short chain fatty acids. GC chromatogram is in
AC C
EP
splitless mode at A, others were split in 50 mode. (A) Butanoic acid derivatized with 50µL propyl chloroformate and 150µL 2-butanol. Butanoic acid as well as byproduct showed both propyl ester and 2-butyl ester. (B) SCFA standard mix derivatized with propyl chloroformate and 1-propanol. (C) SCFA standard mix derivatized with isobutyl chloroformate and isobutanol. (D) SCFA standard mix isobutyl ester derivatized with NaOH. (E) SCFA standard mix isobutyl ester derivatized with NH3. (F) Mass spectrum of byproduct peak at E, which was 14
ACCEPTED MANUSCRIPT
apparently carbamate. Supplementary Fig. 2.
Calibration curves of short chain fatty acids (isobutyl esters form). Y-axis indicates EIC peak area of each
RI PT
standard and X-axis indicates concentration of each SCFA. Replication was four times (n=4). Linearity was shown between 50nmole to 1µmole among
formic acid, acetic acid, propionic acid, isobutanoic
SC
acid and butanoic acid (quantification was done with split 50 mode). The value of other SCFAs were
M AN U
between 0.5-50nmole (quantification was done with splitless mode). All calibration curves showed R2>0.99.
Supplementary Fig. 3.
(A) Recovery rate (percentage) of short chain fatty
TE D
acids (isobutyl esters form), indicating loss of SCFAs during chloroform phase separation. Recovery rate was calculated as 100 x (EIC peak
AC C
EP
area of chloroform treated SCFAs / EIC peak area of SCFA without chloroform phase separation). Recovery rate was nearly 100% from C1 (formic acid) to C3 (propionic acid). In contrast, loss by phase separation was observed in accordance with carbon number increase. Between C1-C6, RSD was < 30. (B) GC chromatogram of short chain fatty acid-TMS derivatives (EIC, m/z 75). SCFA was
extracted with diethyl ether and derivatized by MSTFA. Formic acid-TMS and acetic acid-TMS showed particularly small peaks, which was probably 15
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
due to poor solubility into diethyl ether.
16
AC C
EP
TE D
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT
S0003-2697(17)30494-3
DOI:
10.1016/j.ab.2017.12.001
Reference:
YABIO 12859
To appear in:
Analytical Biochemistry
Received Date: 22 September 2017 Revised Date:
29 November 2017
Accepted Date: 4 December 2017
Please cite this article as: T. Furuhashi, K. Sugitate, T. Nakai, Y. Jikumaru, G. Ishihara, Rapid profiling method for mammalian feces short chain fatty acids by GC-MS, Analytical Biochemistry (2018), doi: 10.1016/j.ab.2017.12.001. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT
Technical Notes
Rapid profiling method for mammalian feces short
SC
RI PT
chain fatty acids by GC-MS
M AN U
Takeshi Furuhashia, Kuniyo Sugitateb, Takashi Nakaib, Yusuke Jikumarub, Genki Ishiharaa
a Anicom Specialty Medical Institute Inc., 8-17-1, Nishi Shinjuku, Shinjuku-ku,
TE D
Tokyo, Japan
EP
b Agilent Technologies Japan, Ltd. 9-1, Takakuramachi, Hachioji-shi, Tokyo, Japan
Correspondence: Takeshi Furuhashi, Anicom Specialty Medical Institute Inc., 8-17-1,
AC C
Nishi Shinjuku, Shinjuku-ku, Tokyo, Japan
Email: [email protected]
1
ACCEPTED MANUSCRIPT
ABSTRACT
Short chain fatty acids (SCFAs) are key feces metabolites generated by gut bacteria
RI PT
fermentation. Despite the importance of profiling feces SCFAs, technical difficulties in analysis
remain due to their volatility and hydrophilicity. We improve previous protocols to
profile SCFAs and optimize the metabolite profiling platform for mammalian feces
SC
samples.
In this study, we investigated feces as biological samples using gas
M AN U
chromatography-mass spectrometry (GC-MS). Isobutyl chloroformate was used for a derivatization in aqueous solution without drying out the samples. Ultimately, we envisage being able to determine the way in which gut bacteria fermentation influences host gut condition by using our rapid metabolite profiling methods.
TE D
Keywords: SCFA (short chain fatty acids), GC-MS, Gut bacteria, Fermentation
Abbreviations: CE, capillary electrophoresis; EI, electron ionization; EIC, extracted
EP
ion chromatogram; GC-MS, gas chromatography mass spectrometry; LC, liquid chromatography; ODS, octadecyl-silica; SCFAs, short chain fatty acids; SPME,
AC C
solid-phase microextraction; TIC, total ion counting; TMS, trimethylsilyl.
2
ACCEPTED MANUSCRIPT
In fermentation processes, bacteria convert degraded food into gases, alcohol and small fatty acids under anaerobic conditions [1]. Mammalian vertebrates, especially herbivores, possess long and large digestive systems [2]. Gut bacteria are responsible
RI PT
for fermentation in the gut (e.g., foregut and hindgut). Food sources that are not completely digested by host animals (e.g., cellulose) can also be digested by gut bacteria and eventually converted into energy [3].
Among the compounds generated in the fermentation process, short chain fatty acids
SC
(SCFAs) are one of the most important products. SCFAs refer to fatty acids whose
carbon number is between one (e.g., formic acid) and six (e.g., hexanoic acid). Indeed,
M AN U
SCFAs are important for the gut barrier system and modulate the immune system of host animals [4]. They are also related to obesity and inflammation [5, 6]. Changes in SCFA quantity and proportion can be influenced by the food type as well as by the complex gut bacteria community itself (i.e., its diversity) [7]. Genomics data provide information on the relative proportion of bacteria species, but not on quantities of
TE D
specific bacteria species. Accordingly, genomics approaches solely indicate bacteria presence in the gut, but cannot shed light on functional changes (i.e., metabolite changes). Conversely, information about bacteria genomics does not yield information
AC C
SCFAs.
EP
on actual fermentation processes. This requires metabolomics approaches, especially for
Although SCFA profiling has been a major topic in gut bacteria studies [8, 9], many researchers have encountered technical difficulties. This is mainly attributable to the highly volatile and hydrophilic characteristics of SCFAs. In particular, biological materials such as feces are complex, making it necessary to separate SCFAs chromatographically. Nonetheless, because of their hydrophilic characteristics, the conventional liquid chromatography (LC) mobile phase – which is water-acetonitrile with formic acid – cannot be applied. Firstly, the LC-MS system based on ODS column separation does not give reasonable chromatographic separation with such a mobile 3
ACCEPTED MANUSCRIPT
phase. Secondly, it is not possible to use formic acid and acetic acid to enhance atmosphere ionization (i.e., ESI and APCI) because these are also present in samples as SCFAs. Ion exclusion chromatography can also be applied, but due to the eluent (e.g.,
reduces the accuracy of SCFA identification and sensitivity.
RI PT
sulfuric acid) [10] it normally cannot be hyphenated with mass spectrometry. This
GC-MS can be a suitable technique for volatile compounds analysis. GC-MS offers
SC
several approaches for volatile compounds: headspace and/or solid phase micro
extraction [11, 12], and derivatization [13]. Despite their volatility, SCFAs in the gas
M AN U
phase from biological samples often have a low concentration for headspace analysis. SPME (solid-phase microextraction) can contain organic acids and concentrate target metabolites. SPMEs, however, are difficult to quantify due to variations in partition equilibria between sample and gas, and between gas and SPME fibers (14). Derivatization can involve silylation (i.e., TMS (trimethylsilyl)) [15], alkylation [16],
TE D
and esterification [17]. Many derivatization protocols require non-aqueous conditions, calling for removing water from biological samples prior to the derivatization reaction. Here, SCFAs can evaporate and disappear during the drying process. In previous studies,
EP
esterification using chloroformate was applied for derivatization under aqueous solutions [18]. Nonetheless, it remains difficult to profile certain SCFAs which overlap
AC C
with the injection peak. As both headspace and SPME are not always suitable for large numbers of samples or for preservation, it would be advantageous to pursue an improved derivatization protocol. The above technical issues call for improving the SCFA profiling methods. We focus on improving the GC-MS derivatization protocol because of the identification potential and sensitivity of mass spectrometry. Here, we introduce a SCFA profiling platform for mammalian feces samples.
4
ACCEPTED MANUSCRIPT
For SCFA standard analysis, we prepared 15 SCFAs standard mix (500pmole-10µmole of each SCFA present in a reaction solution were tested) (Supplementary Table 1). Add 125 µL 20 mM NaOH, 100 µL pyridine and alcohol solution (150 µL 1-propanol
RI PT
with 275µL water, or 70µL isobutanol with 355µL water or make up 650µL with 1-butanol saturated water). One boiling stone was placed into the tube to avoid bumping, and then solution was derivatized with 50 µL of chloroformate (propyl/
isobutyl/1-butyl-). The lid was kept open for 1 min to release generated gases. The lid
SC
was then closed and the sample vortexed. The tube was spun down, 150 µL hexane was added, followed by centrifuging at 21,000 g for 2 min. Thereafter, the upper hexane
or split (1:50) into GC-MS.
M AN U
phase was transferred into a GC vial. Then, we injected either 1 µL with splitless mode
Freshly collected feces (human/dog/cat; 50-100 mg fresh weight) are placed into 2 mL screw cap tubes with ceramic beads (KT03961-1; Bertin Technologies, France). We then added 1 mL 10% isobutanol and homogenized mechanically (Precellys Evolution;
TE D
Bertin Technologies, France) at 6000 rpm for 20 s twice with a 30 s interval. The sample was then centrifuged at 21,000g for 5 min and 675 µL supernatant was transferred to a new tube. We then added 20 µg 3-Methyl pentanoate as internal
EP
standard [19]. The chloroformate derivatization protocol is modified after Zheng et al. (2013) [18]. 125 µL 20 mM NaOH solution and 400 µL chloroform was then added.
AC C
The tube was vortexed and centrifuged at 21,000 g for 2 min. 400 µL upper aqueous phase was transferred into a new tube. Alcohol (70 µL isobutanol) and 100 µL pyridine was then added. Ultra-high quality water was added to make up 650 µL total volume. A boiling stone was placed into the tube to avoid bumping. Samples can be frozen at this stage prior to the derivatization process. We then carefully added 50 µL of isobutyl chloroformate. The lid was kept open for 1 min to release generated gases. The lid was then closed and the sample vortexed. The tube was spun down, 150 µL hexane was added, followed by centrifuging at 21,000 g
5
ACCEPTED MANUSCRIPT
for 2 min. Thereafter, the upper hexane-isobutanol phase was transferred into a GC vial. Then, we injected either 1 µL with splitless mode or split (1:50) into GC-MS. For SCFA quantification, GC-MS measurements were carried out on a single
RI PT
quadrupole mass spectrometer (5977B-MSD; Agilent Technologies, Santa Clara, CA, USA) equipped with 7890B GC (Agilent Technologies, Santa Clara, CA, USA) and
7693 auto sampler (Agilent Technologies, Santa Clara, CA, USA). The temperature of the GC-MS ion source and the transfer line for the samples was 250°C.
SC
HP-5MS 30 m, 0.25 mm, 0.25 µm (19091S-433, Agilent, USA) was used as a GC
column. The oven temperature gradient for the samples was as follows. After a 5 min,
M AN U
50oC isotherm period, the oven was programmed to rise to 150oC at a rate of 5oC min-1, then rise to 330oC at a rate of 40oC min-1, held at 330oC for 1 min. The temperature of both the GC-MS ion source and transfer line was set at 250oC. The scan range was between m/z 30-600.
To quantify SCFAs, we calculated the peak areas of a conventional 70eV EI mode
TE D
(Extractor ion source; Agilent Technologies, Santa Clara, CA, USA) extracted ion chromatogram using software (Mass Hunter; Agilent Technologies, Santa Clara, CA, USA). The chosen m/z and retention time for quantification is described in
EP
Supplementary Table 1. Formic acid, acetic acid, propionic acid, isobutyric acid, and butanoic acid were quantified with split mode. Others were quantified with splitless
AC C
mode.
Several factors can affect esterification, namely solvents (i.e., alcohol), catalysts as well as contaminants (i.e., matrix effect). In this study, we compared a combination of alcohol and chloroformate (1-propanol, 1-butanol, isobutanol, 2-butanol). Changing alcohol together with chloroformate not only shifted the retention time shift, but also influenced the solubility, sensitivity and byproduct peak. Firstly, esters were eluted from propyl ester (1-propanol with propyl chloroformate), isobutyl ester (isobutanol with
6
ACCEPTED MANUSCRIPT
isobutyl chloroformate) and then 1-butyl esters (1-butanol with butyl chloroformate) (Supplementary Table 1). The solubility of 2-butanol in water is high, while the solubility of isobutanol is about
RI PT
10% in water and that of 1-butanol is clearly less than 10%. Due to the solubility of SCFAs in aqueous solution, 2-butanol was previously considered as a candidate solvent. Nevertheless, derivatization with 2-butanol showed a low derivatization efficiency, possibly because the branch structure caused a steric hindrance of the Sn2 reaction.
SC
Consistent with this, when 2-butanol solvent mixed with propyl chloroformate was
applied, both propyl ester and 2-butyl ester were produced at peaks of almost the same
suitable for butyl esterification.
M AN U
height (Supplementary Fig. 1A). Accordingly, we conclude that 2-butanol is not
Formate, acetate and propionate, however, were near the solvent (injection peak) and those peaks were poorly resolved in splitless mode. Split mode can be applied to deconvolute the solvent and SCFA peaks (Supplementary Fig. 1B-C). In the case of
TE D
formic acid and acetic acid, both SCFAs required a split (i.e., split ratio 50) in all tested solvents. Regarding propyl ester derivatized with 1-propanol, propyl esters showed good sensitivity but the formate propyl ester peak was still very close to solvent peaks.
EP
As such, butyl esterification is suggested particularly for formate analysis. The low solubility of 1-butyl ester in water can lead to phase separation, when excess (>
AC C
10%) 1-butanol was added into solution. In this study, we used a 1-butanol saturated water solution. The standard curve of SCFAs derivatized with 1-butanol as well as isobutanol showed good linearity. The solubility of isobutanol (10% isobutanol was applied in this study) is moderate and useful. In general, it is important to profile acetate, propionate, butyrate, valerate and caproate in many biological materials. Isobutyl ester is a good first choice. Reproducibility and stability of esterification was confirmed by calculating calibration curves (Supplementary Fig. 2), showing R2>0.99 in all SCFAs.
7
ACCEPTED MANUSCRIPT
In a previous study, we used NaOH as a base. In the present experiment, we tested another base, NH3, but its byproduct peak (e.g., carbamate) was very broad and overlapped many of the SCFAs (Supplementary Fig. 1D-F). Pyridine as a catalyst was
RI PT
necessary in all cases. We confirmed that NaOH and pyridine are inevitable in this derivatization process, as previously described [18].
The reaction of chloroformate was severe, generating gases in all tested combinations of alcohol. It often caused a bumping of the sample solution when the sample is vortexed.
SC
We improved this by adding a boiling stone prior to addition of chloroformate. This
avoided bumping completely: the reaction proceeded at a constant rate and the reaction
M AN U
appeared to be almost complete within 3 min after adding chloroformate (i.e., the bubbling ceased).
We tested the feces samples of humans and cats (Fig. 1A-B, Supplementary Table2). We commonly detected C2 (i.e., acetic acid), C3 (e.g., propionic acid), and C4 (e.g., butanoic acid) in all tested samples. Acetate was the dominant SCFA among all feces.
TE D
Formic acid was not detected in cat feces in this study, and longer chain SCFAs (i.e., hexanoic acid) were recorded in cat feces. Such profiles could reflect diet differences. Cats are carnivores and the proportion of protein in cat food is generally high (>20%).
EP
Moreover, cats harbor Clostridium in their guts, a bacterium which is typically present in carnivorous mammals and produces hexanoic acid [20].
AC C
Sample pre-treatment is important especially in the case of lipid-rich biological samples such as feces because lipids can influence the derivatization process. It is advantageous to remove the many lipophilic compounds containing carboxylic acid in biological samples (e.g., long chain free fatty acids) by phase separation before the derivatization process. In this study, chloroform was applied for this purpose. This helps to avoid blocking derivatization by too many contaminants and removes the contaminant peaks in the GC chromatogram. The distribution ratio of SCFA in chloroform were not same between SCFAs, and loss by phase separation increased with increase of carbon chain
8
ACCEPTED MANUSCRIPT
length (Supplementary Fig. 3A). Therefore, it is necessary to consider ratio difference in quantification efforts. Another concern for biological samples is the matrix effect. For this reason, stable
RI PT
isotope (deuterium) labelled acetate (D3), propionate (D5), butyrate (D7) were spiked in feces samples and recovery rates were calculated (n=4). The recovery rates of D-acetate and D-propionate were nearly 100%, while that of D-butyrate was around 60%, which was nearly the same value as the distribution ratio during chloroform phase separation.
SC
Hence, chloroform separation needs to be considered as a primary factor for
quantification. To check the reproducibility of feces SCFA quantification, we measured
(Supplementary Table 3).
M AN U
four replicates of cat feces and calculate RSD. RSD was between 0.5 and 9.7
The suggested isobutyl esterification protocol based on chloroformate enables rapid SCFA profiling for various biological samples, especially feces. This is an important
TE D
step forward in investigating gut bacteria fermentation processes. GC-MS helps to identify SCFAs more precisely than LC or CE without connection to MS and can detect small amounts of SCFAs due to its high sensitivity. Compared with the headspace and
EP
thermal desorption protocols, derivatization increases sensitivity as well as peak resolution of SCFAs. In fact, we compared the signal to noise ratio between SPME and
AC C
isobutyl esterification (Supplementary Table 4). In most of the SCFAs, isobutyl esterification showed better s/n ratios than those measured by SPME. In view of sensitivity, isobutyl esterification can detect SCFAs from feces samples that are under the detection limit for SPME. Moreover, the volatility of SCFAs drops when SCFAs are present in aqueous solution. This decreases the sensitivity of SPME measurements. In contrast, our isobutyl esterification protocol is not greatly influenced by aqueous solution. In derivatization, TMS derivatization has also been used in previous studies. In the diethyl ether extraction-TMS derivatization protocol, sensitivity for small SCFAs (e.g., formate and acetate) was low (Supplementary Fig. 3B). In contrast, butyl 9
ACCEPTED MANUSCRIPT
esterified small SCFAs were sensitive enough (unpublished data). Moreover, diethyl ether solution is difficult to handle (pipette) precisely; its high volatility is also disadvantageous for quantification and derivatization processes.
RI PT
As opposed to all other GC-MS protocols, esterification by chloroformate can be conducted in aqueous solutions at room temperature. Compared with esterification in
non-aqueous solutions (e.g., BF3 or H2SO4 in methanol) [17], the protocol is very useful and practical.
SC
Adding boiling stones enabled operators to conduct experiments without bumping
incidents. As our approach can be combined with an auto sampler, automation of the
M AN U
derivatization step can be achieved. Accordingly, this protocol has a high potential for being applied in clinical purposes, e.g., the diagnosis of chronic intestinal disease.
Acknowledgement
We thank Mr Suzuki, Dr Oi, and Mr Ukawa for giving us feces samples and kind encouragement. Dr
AC C
EP
TE D
Stachowitsch improved the English of an early draft.
10
ACCEPTED MANUSCRIPT
References
[1] Zeikus, J. G., Chemical and fuel production by anaerobic bacteria. Ann. Rev.
RI PT
Microbiol 1980, 34, 423-64.
[2] Kararli, T. T. Comparison of the gastrointestinal anatomy, physiology, and
biochemistry of humans and commonly used laboratory animals. Biopharmaceutics &
SC
Drug Disposition 1995, 16, 351-380.
M AN U
[3] den Besten, G., van Eunen, K., Groen, A. K., Venema, K., Reijngoud, D. J., Bakker, B. M., The role of short-chain fatty acids in the interplay between diet, gut microbiota, and host energy metabolism. Journal of Lipid Research 2013, 54, 2325-2340.
[4] Khan, M. T., Duncan, S. H., Stams, A. J. M., van Dijl, J. M., Flint, H. J., Harmsen,
TE D
H. J. M. The gut anaerobe Faecalibacterium prausnitzii uses an extracellular electron shuttle to grow at oxic–anoxic interphases. The ISME Journal 2012, 6, 1578–1585.
EP
[5] Ley, R. E., Bäckhed, F. Turnbaugh, P., Lozupone, C. A., Knight, R. D. Gordon, J. I.
AC C
Obesity alters gut microbial ecology. PNAS 2005, 102(31), 11070–11075.
[6] Patrice D. Cani, P. D., Bibiloni, R., Knauf, C., Waget, A., Neyrinck, A. M., Delzenne, N. M., Burcelin, R. Changes in Gut Microbiota Control Metabolic Endotoxemia-Induced Inflammation in High-Fat Diet–Induced Obesity and Diabetes in Mice. Diabetes 2008, 57, 1470-1481．
[7] Dowd, S. E., Callaway, T. R., Wolcott, R. D., Sun, Y., McKeehan, T., Hagevoort, R. G., Edrington, T. S. Evaluation of the bacterial diversity in the feces of cattle using 16S rDNA bacterial tag-encoded FLX amplicon pyrosequencing (bTEFAP). BMC 11
ACCEPTED MANUSCRIPT
Microbiology 2008, 8(125), 1-8.
[8] Matsumoto, M., Kibe, R, Ooga, T., Aiba, Y., Kurihara, S., Sawaki, E., Koga, Y.,
RI PT
Benno, Y. Impact of intestinal microbiota on intestinal luminal metabolome. Scientific reports 2012, 2(233), 1-10.
[9] Primec, M., Mičetić-Turk, D., Langerholc, T. Analysis of short-chain fatty acids in
SC
human feces: A scoping review. Analytical Biochemistry 2017, 526, 9-21.
M AN U
[10] Niven, S. J., Beal, J. D., Brooks, P. H., The simultaneous determination of short chain fatty acid, monosaccharides and ethanol in fermented liquid pig diets. Animal Feed Science and Technology 2004, 117, 339-345.
[11] Batista, R. B., Grimm, C. C. Semiquantitative Determination of Short-Chain Fatty
TE D
Acids in Cane and Beet Sugars. Journal of Chromatographic Science 2002, 40,127-132.
[12] Caroprese, A., Gabbanini, S., Beltramini, C., Lucchi, E., Valgimigli, L.
EP
HS-SPME-GC-MS analysis of body odor to test the efficacy of foot deodorant
AC C
formulations. Skin Research and Technology 2009, 15, 503-510.
[13] Goto, A. S., Korenaga, T., Chikaraishi, Y. Methyl and ethyl chloroformate derivatization for compound specific stable isotope analysis (CSIA) of fatty acids. Researches in Organic Geochemistry 2011, 27, 91-95.
[14] Savary, B. J., Nuñez, A. Gas chromatography–mass spectrometry method for determining the methanol and acetic acid contents of pectin using headspace solid-phase microextraction and stable isotope dilution. Journal of Chromatography A 2003, 1017, 151-159. 12
ACCEPTED MANUSCRIPT
[15] Olsen, M. A.; Mathiesen, S. D.; Production rates of volatile fatty acids in the minke whale (Balaenoptera acutorostrata) forestomach. British Journal of Nutrition 1996, 75,
RI PT
21-31.
[16] Pons, A., Richet, C., Robbe, C., Herrmann, A., Timmerman, P., Huet, G., Leroy,
Y., Carlstedt, I., Capon, C., Zanetta, J. P. Sequential GC/MS Analysis of Sialic Acids,
SC
Monosaccharides, and Amino Acids of Glycoproteins on a Single Sample as
M AN U
Heptafluorobutyrate Derivatives. Biochemistry 2003, 42, 8342-8353.
[17] Hallmann, C., van Aarssen, B. G. K., Grice, K., Relative efficiency of free fatty acid butyl esterification. Choice of catalyst and derivatization Procedure. Journal of Chromatography A 2008, 1198–1199, 14-20.
TE D
[18] Zheng, X., Qiu, Y., Zhong, W., Baxter, S., Su, M., Li, Q., Xie, G., Ore, B. M., Qiao, S., Spencer, M. D., Zeisel, S. H., A targeted metabolomic protocol for short-chain fatty
EP
acids and branched-chain amino acids. Metabolomics 2013, 9(4), 818-827.
[19] Mellon, A. F.; , Deshpande, S. A.; Mathers, J, C.; Bartlett, K.; Effect of oral
AC C
antibiotics on intestinal production of propionic acid. Arch Dis Child 2000, 82, 169– 172.
[20] Zhu, X.; Tao, Y.; Liang, C.; Li, X.; Wei, N.; Zhang, W.; Zhou, Y.; Yang, Y.; Bo, T.; The synthesis of n-caproate from lactate: a new efficient process for medium-chain carboxylates production. Scientific Reports 2015, 5, 1-9.
13
ACCEPTED MANUSCRIPT
Figure captions
GC chromatogram (split 50 mode) of the feces short
RI PT
Fig. 1.
chain fatty acid isobutyl ester. (A) Human feces
sample, from top to bottom, TIC (total ion counting), EIC (extracted ion chromatogram) m/z 85, EIC m/z
SC
99. Eight short chain fatty acids (from formic acid to pentanoic acid) were profiled. (B) Cat feces sample,
M AN U
from top to bottom, TIC, EIC m/z 85, EIC m/z 99. Nine short chain fatty acids (from acetic acid to
Supplementary Fig. 1.
TE D
hexanoic acid) were profiled.
GC chromatogram (A-E) and mass spectrum (F) of
short chain fatty acids. GC chromatogram is in
AC C
EP
splitless mode at A, others were split in 50 mode. (A) Butanoic acid derivatized with 50µL propyl chloroformate and 150µL 2-butanol. Butanoic acid as well as byproduct showed both propyl ester and 2-butyl ester. (B) SCFA standard mix derivatized with propyl chloroformate and 1-propanol. (C) SCFA standard mix derivatized with isobutyl chloroformate and isobutanol. (D) SCFA standard mix isobutyl ester derivatized with NaOH. (E) SCFA standard mix isobutyl ester derivatized with NH3. (F) Mass spectrum of byproduct peak at E, which was 14
ACCEPTED MANUSCRIPT
apparently carbamate. Supplementary Fig. 2.
Calibration curves of short chain fatty acids (isobutyl esters form). Y-axis indicates EIC peak area of each
RI PT
standard and X-axis indicates concentration of each SCFA. Replication was four times (n=4). Linearity was shown between 50nmole to 1µmole among
formic acid, acetic acid, propionic acid, isobutanoic
SC
acid and butanoic acid (quantification was done with split 50 mode). The value of other SCFAs were
M AN U
between 0.5-50nmole (quantification was done with splitless mode). All calibration curves showed R2>0.99.
Supplementary Fig. 3.
(A) Recovery rate (percentage) of short chain fatty
TE D
acids (isobutyl esters form), indicating loss of SCFAs during chloroform phase separation. Recovery rate was calculated as 100 x (EIC peak
AC C
EP
area of chloroform treated SCFAs / EIC peak area of SCFA without chloroform phase separation). Recovery rate was nearly 100% from C1 (formic acid) to C3 (propionic acid). In contrast, loss by phase separation was observed in accordance with carbon number increase. Between C1-C6, RSD was < 30. (B) GC chromatogram of short chain fatty acid-TMS derivatives (EIC, m/z 75). SCFA was
extracted with diethyl ether and derivatized by MSTFA. Formic acid-TMS and acetic acid-TMS showed particularly small peaks, which was probably 15
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
due to poor solubility into diethyl ether.
16
AC C
EP
TE D
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT