Evaluation and Optimization of Sample Handling Methods for

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Evaluation and optimization of sample handling methods for quantification of short-chain fatty acids in human fecal samples by GC-MS Ya-Lin Hsu, Chieh-Chang Chen, Ya-Ting Lin, Wei-Kai Wu, LinChau Chang, Chang-Hao Lai, Ming-Shiang Wu, and Ching-Hua Kuo J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.8b00536 • Publication Date (Web): 21 Mar 2019 Downloaded from http://pubs.acs.org on March 21, 2019

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Journal of Proteome Research

Evaluation and optimization of sample handling methods for quantification of short-chain fatty acids in human fecal samples by GC-MS Ya-Lin Hsu,†,‡,§ Chieh-Chang Chen, ,§ Ya-Ting Lin,†,‡ Wei-Kai Wu, ,∞ Lin-Chau Chang, ∥

Chang-Hao Lai, Ming-Shiang Wu, and Ching-Hua Kuo*,†,‡,⊥ ∥

†

†

#

∥

School of Pharmacy, College of Medicine, National Taiwan University, Taiwan.

‡

The Metabolomics Core Laboratory, Center of Genomic Medicine, National Taiwan University, Taiwan.

∥

Departments of Internal Medicine, National Taiwan University Hospital, National

Taiwan University College of Medicine, Taipei, Taiwan. #

Department of Internal Medicine, National Taiwan University Hospital Bei-Hu Branch, Taipei, Taiwan

∞

Institute of Food Science and Technology, National Taiwan University, Taipei, Taiwan

⊥

Department of Pharmacy, National Taiwan University Hospital, Taiwan.

§These authors contributed equally.

*Corresponding Author Ching-Hua Kuo Address: School of Pharmacy, College of Medicine, National Taiwan University, Rm. 418, 4F., No.33, Linsen S. Rd., Chongsheng Dist., Taipei City 100, Taiwan (R.O.C.) Tel: +886.2.33668766 Fax: +886.2.23919098 E-mail: kuoch@ ntu.edu.tw 1

ACS Paragon Plus Environment

Journal of Proteome Research 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Abstract The gut microbiota has attracted a great deal of interest in recent years due to its association with many diseases. Short-chain fatty acids (SCFAs), the end products of dietary fiber fermentation by the intestinal microbiota, are among the most frequently discussed gut metabolites. As the sample handling method greatly affects the integrity of data, this study investigated the most important parameters that affect the bias of SCFA comparisons in human fecal studies. An accurate gas chromatography-mass spectrometry (GC-MS) method was first established and validated for quantifying six SCFAs, including acetic, propionic, butyric, isobutyric, isovaleric, and valeric acids. To remove interfering species, we used butanol to extract SCFAs from acidified fecal suspensions. The validated quantification method was then applied to evaluate fecal sample handling protocols. We found that lyophilization of fecal samples can not only minimize bias due to the water content but also provide better stability of SCFAs. Six SCFAs were stable and that their recoveries were higher than 90% after lyophilization. Lyophilization of a large fecal sample is extremely time-consuming, and 1 g of fecal sample is suggested for lyophilization to minimize sampling bias. The inter-individual difference was significantly higher than the intra-individual difference when using 1 g of fecal sample to study SCFAs. Finally, an effective protocol from sample collection to GC-MS analysis was proposed. As SCFAs have been shown to play an important role in health maintenance and disease development, the proposed protocol is anticipated to be applicable to clinical studies to delineate the biological functions of each SCFA.

Key words: Short-chain fatty acids, GC-MS, gut microbiota, lyophilization 2


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1. Introduction Recently, there has been a growing interest in the influence of the gut microbiota on human health.1, 2 Considered to be a forgotten organ,3 the gut microbiota exerts beneficial effects on the intestinal mucosa, ranging from protecting against infection to immune system development, and also plays an important role in the regulation of multiple host metabolic pathways.4, 5 The gut microbiota produces a diverse range of metabolites that may affect human health. Short-chain fatty acids (SCFAs), the end products of the fermentation of dietary fibers by the intestinal microbiota, are among the most frequently discussed gut metabolites. Many of SCFAs have been shown to play important roles in health maintenance or disease development.6, 7 SCFAs are monocarboxylic acids that consist of one to six carbons. The most abundant SCFAs in the colon are acetate (C2), propionate (C3) and butyrate (C4), whereas isobutyrate (i-C4), valerate (C5), and isovalerate (i-C5) which contribute to more than 90% of the total SCFA in human feces. Hexanoate (C6), lactic acid and other minor SCFAs constitute only 5–10% of the total SCFAs.8 Previous studies have indicated that SCFAs act as substrates or signaling molecules in various tissues and are involved in the regulation of host energy metabolisms, including lipid, glucose, and cholesterol.9 In addition to the roles of SCFAs in metabolic functions, there is growing evidence that SCFAs contribute to reducing colonic inflammation, preventing colon carcinogenesis, and promoting mucosal healing.10 Changes in the fecal SCFA concentrations can reflect the balance between the production and absorption of SCFA in the colon, and fecal samples are the most frequently used specimens for studying the correlation between the SCFA concentration and disease.11-13 Different levels of fecal SCFAs have been observed in 3



patients with colorectal cancer14 and inflammatory bowel disease.15, 16 As the health effects of the gut microbiota have drawn much attention in recent years and the measurement of SCFA in human feces has been used to study many diseases, it is essential to develop an accurate quantification method and a standard sample handling protocol to improve data quality. Several analytical methods have been proposed to quantify SCFAs. However, a systematic study of sample handling protocols for studying SCFAs in human feces is still lacking. Among all of the equipment used to determine SCFAs, GC is the most widely used for SCFAs analysis due to the volatility of these compounds. Moreover, the combination with mass spectrometer (MS) provides better sensitivity and selectivity compared to flame ionization.17 Although many GC-MS methods include a derivatization step to improve sample volatility and detection sensitivity, SCFAs show good volatility and direct analysis after sample extraction was widely applied for most SCFA analytical methods.18-20 To extract SCFAs from a complex matrix, different sample pretreatment procedures have been reported. Adding a acidification step to fecal sample extraction has been demonstrated to improve extraction efficiency and the peak shape of SCFAs.18 Formic acid and phosphoric acid both have been used as the acidification agents in fecal extraction. García-Villalba et al. indicated that the two acids gave similar yields, but an interfering peak appeared when using formic acid for acidification.20 Because direct injection of complex samples into the GC apparatus may lead to a shorter column lifespan due to the contamination of nonvolatile compounds, liquid-liquid extraction (LLE) was generally employed after the acidification step.19-21 Solid phase microextraction (SPME), a solvent-less extraction technique, has also been

4


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applied to extract volatile SCFAs.22 However, fibers are relatively expensive and fragile, and it also requires additional devices for automated analysis. The study of the gut microbiota began with an investigation of microbial DNA and gradually moved to studies of gut metabolites. Many SCFA analysis studies use a sampling protocol to study microbial DNA, but this may not be the ideal protocol for studying gut metabolites.23, 24 Special attention should be paid to minimize comparison bias in gut metabolite studies. Wide water content variations may cause a concentration comparison bias; the use of lyophilization has been suggested to minimize the comparison bias caused by the water content. Since SCFAs are volatile compounds, the potential loss of SCFAs was discussed in one study.25 As lyophilization is the most straightforward approach to minimize water content-caused comparison bias, it is essential to more thoroughly investigate the effect of this preparation procedure. Unlike other specimens, such as urine and plasma, fecal samples are heterogeneous, and thus, spot sampling may result in high variations.26 The amount sampled varies from several milligrams to grams in different studies, and whether this subsample is representative of the study subject has not been investigated. Another critical issue that may cause comparison bias is sample stability. Since feces contain numerous microbes, appropriate methods for collecting, transporting, and storing samples after defecation are necessary to prevent SCFA transformation.12 Previous stability studies have mainly focused on analyzing the fecal metabolome and have suggested extracting fecal samples within 24 h and storing fecal water at < -20°C to avoid sample degradation. One review article regarding SCFA analysis suggested maintaining fecal samples at -20°C or -80°C without discussing the form of fecal samples being stored.27

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Considering the importance of SCFAs in gut microbiota studies, it is essential to develop a standard protocol for handling human fecal samples. To evaluate factors in the sample handling procedure that may cause SCFA concentration changes, we developed a LLE method combined with GC-MS analysis to quantify SCFA in fecal samples. The quantification method was used to investigate the potential biases due to sampling amounts and lyophilization. SCFA stability in different storage forms was also investigated. The final aim of this study is to propose a standard sample handling protocol for studying SCFA in human fecal samples and to provide more accurate results for investigating their effects on human health.

2. Material and methods 2.1 Chemicals Short-chain fatty acids standards, including propionic acid, butyric acid, isobutyric acid, isovaleric acid, and valeric acid, were purchased from Sigma-Aldrich (St. Louis, MO, USA). Acetic acid and orthophosphoric acid were obtained from Merck (Darmstadt, Germany). 1-butanol (ACS reagent grade, ≥ 99.5%) was purchased from Sigma-Aldrich (St. Louis, MO, USA). Sodium acetate-d3 (99% D) and sodium propionate-d5 (98% D) were purchased from CDN Isotopes (Pointe-Claire, Quebec, Canada).

2.2 Fecal sample collection and experimental design The collection of human fecal samples was approved by the Research Ethics Committee

of

National

Taiwan

University

Hospital

(NTUH

REC

No:

201809014RINC). Fecal samples were collected in a plastic box and transported to the 6


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laboratory on ice within 24 h after collection. One gram of fecal sample was placed in a 5 mL centrifuge tube, and the weighed sample was subjected to lyophilization. After lyophilization, the samples were stored at -80°C until extraction and GC-MS analysis. The fecal samples should be kept at a temperature equal to, or lower than 4°C after collection and before lyophylization. Figure 1 shows the experimental design of this study. To consider individual differences, fecal samples from five healthy volunteers were used to optimize the sampling amounts and to study the effect of lyophilization. To evaluate the effect of sampling amount, we compared the concentration differences of SCFAs in fecal samples obtained from different sampling positions (the middle and both ends) for sample amounts from 60 mg, 500 mg and 1 g. The sampling location didn’t exactly reflect its location in the original stool, and the design was to have samples apart from each other to evaluate the SCFA concentration difference between different locations of the fecal samples. To evaluate the effect of lyophilization and the stability difference between different storage forms, we used homogenized fecal samples to minimize the confounding errors due to the heterogeneity of the fecal samples. Because using 1 g of fecal sample was demonstrated to be effective in minimizing sampling errors, we used 1 g of homogenized fecal samples which were subjected to different treatments (e.g., with or without lyophilization; different storage temperature). For each tested condition, we used three homogenized fecal samples to study the factor effect. To study stability differences between different storage forms, crude feces, lyophilized feces and fecal extracts (extracted by 0.5% H3PO4) were placed in 5 mL centrifugation tube and stored under 4 or -20°C for the stated time period (7 days or 30 days). The crude feces were 7



additionally tested for the stability of SCFAs at 1 h, 6 h and 24 h at room temperature. To avoid stability caused errors, all samples used for studying sample handling procedures were immediately extracted after subjected treatment and stored at -80°C before GC-MS analysis.

Figure 1. Experimental design for the evaluation of the sample handling protocol for studying SCFAs in human feces.

2.3 Sample extraction and GC-TOF analysis 2.3.1 Sample extraction and GC-TOF analysis One gram of crude feces was subjected to lyophilization, and the fecal sample was re-weighted after lyophilization. Sample weight after lyophilization was used for calculation of SCFA contain. The lyophilized samples were suspended in 5 mL of a 0.5% phosphoric acid solution containing 50 μg ml-1 sodium acetate-d3 (internal standard 1; IS1) and extracted with a Geno/Grinder 2010 (SPEX, Metuchen, NJ, US) at 100 RCF for 2 min, followed by sonication for 5 min. After centrifugation at 3000 8


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RCF for 10 min, 60 μL of the supernatant was transferred into a 1.5 mL centrifuge tube and diluted with 240 μL of a 0.5% phosphoric acid aqueous solution. An aliquot of 300 μL of butanol was subsequently added to the solution for liquid-liquid extraction (LLE) of SCFAs, and the mixture was extracted by the Geno/Grinder 2010 for 2 min, followed by centrifugation at 18000 RCF for 10 min. Then, 180 μL of the upper organic layer was transferred into a new tube and 20 μL of butanol containing sodium propionate-d5 was added as internal standards (ISs) at a final concentration of 50 g mL-1. The resulting mixture was filtered with 0.2 μm PP membrane filters (RC-4, Sartorius, Göttingen, Germany) and transferred into a glass insert prior to analysis. All samples were frozen at -80°C until analysis. IS1 was used to monitor the recovery of the extraction process. Any sample with IS1 deviation larger than 15% should be reanalyzed.

All analyses were carried out on an Agilent 7890A gas chromatograph equipped with a MultiPurpose Sampler MPS (GERSTEL, Mülheim an der Ruhr, Germany) that was coupled to a Pegasus GC -TOFMS system (Leco Corporation, St. Joseph, MI, USA). A polar VF-WAXms capillary column (30 m x 0.25 mm i.d. x 0.25 m film thickness) (Agilent Technologies, Santa Clara, CA) was utilized for the separation. The helium carrier gas flow rate was set at 1 mL min-1. One microliter of the sample was injected in the split mode at a ratio of 1:10. The oven temperature was initially held at 70°C for 1 min and then increased to 170°C at a rate of 10°C min-1, to 240°C at a rate of 25°C min-1, and finally maintained at 240°C for 2 min (total run time 15.8 min). The temperatures of the front inlet, transfer line, and ion source were set at 250°C, 250°C, and 240°C, respectively. The filament OFF segment was set from 0 to 5.8 min. The 9



electron impact ionization was 70 eV, and the data were acquired in full scan mode with a mass range of m/z 40–550. The identification of each SCFA was confirmed by comparing the mass spectra and retention times. The acquired tandem mass spectra were matched against the NIST Standard reference database 1A. All compounds were assigned by the ChromaTOF software and the similarity scores should be above 850 for identification. The quantifier for acetic acid, propionic acid, butyric acid, isobutyric acid, valeric acid, isovaleric acid, acetate d3 (ISTD) and propionate d5 (ISTD) were m/z 60, 74, 60, 73, 60, 60, 63, 79.

2.3.2 Analytical method validation Method validation was performed using a standard mixture of SCFAs dissolved in 0.5% H3PO4. Stock solutions of the six SCFAs were prepared in methanol/0.5% H3PO4 (1:1) at a concentration of 10000 g mL-1. Aliquot of the stock solutions were further diluted with 0.5% H3PO4 containing 50 μg ml-1 IS1 to make the final volume of 5 mL. The diluted standard solution was subjected to LLE as described in the sample extraction section (sec 2.3.1) except for the 5 fold dilution of the phosphate solution. In this study,sodium acetate-d3 was used as an IS for acetate, and sodium propionate-d5 was used for the other five SCFAs. For extraction recovery, a standard mixture of six SCFAs was added into the pooled human fecal suspension at three concentration levels, followed by extraction with butanol. Three independent samples were prepared at each concentration, and the recoveries were calculated using the following formula: Recovery % =

peak area of SCFA in the pre − extraction spiked fecal sample × 100% peak area of SCFA in the post − extraction spiked fecal sample 10


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To evaluate linearity, calibration curves of the six SCFAs were constructed with six concentration levels by plotting the peak area ratio of each SCFA to IS versus concentration. Concentrations of 6 calibrators for acetic acid, propionic acid and butyric acid were 10, 20, 50, 100, 200, 300 μg ml-1. Concentrations of 6 calibrators for isobutyric acid, isovaleric acid and valeric acid were 1, 5, 10, 20, 25, 30 μg ml-1. All concentrations were analyzed in triplicate. The repeatability, intermediate precision, and accuracy for the six SCFAs were evaluated by analyzing three independent replicates at low, medium, and high concentrations on three different days. The precision was expressed as the % relative standard deviation (RSD), and the accuracy of the intra- and inter-day measurements were determined by calculating the recoveries of the six SCFA using the constructed calibration curves. The Limit of detection (LOD) was defined as the level at which the SCFA could be detected and identified by the library. The Limit of quantification (LOQ) was defined as the level where the lowest amount of SCFA that can be determined with precision lower than 20% RSD and accuracy within 80-120%.

2.4 Data analysis Data acquisition and data processing were carried out using LECO’s ChromaTOF® software (Leco Corporation, St. Joseph, MI, USA). The peak area of each SCFA was calculated using the unique mass defined by ChromaTOF® . Principle component analysis (PCA) was performed using the web-based metabolomics dataprocessing

tool

MetaboAnalyst

3.0

(Canada)

http://www.metaboanalyst.ca).28 11


(accessible

at


3. Results 3.1 Quantification of SCFAs in fecal samples by GC-MS This study first tested six different organic solvents including methanol, acetonitrile, acetone, chloroform, ethanol, and hexane to extract the SCFAs from fecal samples. Among all, methanol showed the best extraction efficiency and minimal interferences with acetic acid compared to the rest of the solvents. However, the direct injection of methanol extracts was found to cause damage to the inlet liner due to the accumulation of non-volatile compounds from fecal matrix. Therefore, liquid/liquid extraction (LLE) is necessary to clean up fecal samples. Ethyl acetate, methyl tert-butyl ether (MTBE) and chloroform have been used as extraction solvents for the LLE method in previous studies,19-21 and were tested for their extraction performance. A significant acetic acid signal was observed in blank ethyl acetate solvent from several commercial sources and was therefore excluded as the extraction solvent. Although chloroform and MTBE provided a clean background, the extraction recoveries for acetic acid and propionic acid were poor for chloroform and MTBE showed poor recovery for acetic acid. Compared to chloroform and MTBE, butanol provided comparable recoveries for valeric acid and butyric and better recoveries for acetic acid and propionic acid. The background was clean in the butanol solvent blank. Butanol was therefore selected as the LLE extraction solvent. We also compared single extraction with double extraction for six SCFAs29. The results indicated that using double extraction was not able to further improve the extraction recovery for the six SCFAs, and single extraction was therefore applied for SCFA analysis. Table 1 shows the recoveries of the six SCFAs. The recoveries of isobutyric 12


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(i-C4), butyric (C4), isovaleric (i-C5), and valeric acid (C5) ranged from 82 to 97%. The recoveries of acetic (C2) and propionic (C3) acid were comparatively low, with recoveries of 63% and 73%, respectively, when spiked at a high concentration (300 g ml-1) (Table 1). Figure S1 shows the chromatograms obtained from a standard mixture of the six SCFAs and human fecal samples using the optimal extraction procedure.

3.2 Method validation The method developed was validated in terms of linearity, precision, and accuracy using a standard mixture of SCFAs. The linearity, precision, and accuracy results are summarized in Table1. The ranges were designed according to the reported SCFA concentrations in human feces. All of the calibration curves showed good linearity with a high correlation coefficient (greater than 0.99) within the test range. The RSD values for repeatability and intermediate precision were below 10.5 %, and the accuracy of the six SCFAs at three concentrations was in the range of 87.9–110.9% (include the LOQ level). The filter effect was also tested at three concentrations, and the recoveries were in the range of 95.1-105.0%. The LOD and LOQ are shown in Table 2. These results suggest that optimized GC-MS methods can provide accurate and reliable quantification of SCFAs in human feces within the range tested.

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Table 1. The extraction recovery of six SCFAs and internal standards (n = 3). Compound

Concentration

Recovery (%)* 86.7 ± 0.9

Acetic acid (C2)

20 (4 g) (g ml-1) 100 (20 g) 300 (60 g)

63.2 ± 0.9

20 (4 g)

91.8 ± 0.9

100 (20 g)

88.5 ± 1.0

300 (60 g)

73.1 ± 0.8

2 (0.4 g)

95.5 ± 0.9

10 (2 g)

90.8 ± 0.7

30 (6 g)

87.9 ± 1.0

20 (4 g)

93.9 ± 0.4

100 (20 g)

93.1 ± 2.0

300 (60 g)

82.1 ± 1.5

2 (0.4 g)

94.2 ± 1.0

10 (2 g)

89.5 ± 1.6

30 (6 g)

83.5 ± 1.7

2 (0.4 g)

97.4 ± 0.2

10 (2 g)

91.6 ± 3.1

30 (6 g)

85.8 ± 1.2

IS1

50

56.62 ± 3.6

IS2

50

71.82 ± 1.8

Propionic acid (C3)

Isobutyric acid (i-C4)

Butyric acid (C4)

Isovaleric acid (i-C5)

Valeric acid (C5)

*Mean ± SD

14


73.9 ± 1.4

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Table 2. Calibration curve, repeatability (n = 3), intermediate precision (n = 9), and accuracy of six SCFAs. Linearity SCFA

a

Rangea

Calibration curve

R2

LOD

a

LOQ

Acetic acid

10–300

y = 0.016x - 0.057

0.999

0.05

0.5

Propionic acid

1–300

y = 0.023x - 0.098

0.999

0.05

1.0

Isobutyric acid

1-30

y = 0.024x - 0.003

0.999

0.1

0.5

Butyric acid

10–300

y = 0.075x - 0.347

0.999

0.05

1.0

Isovaleric acid

1–30

y = 0.074x - 0.016

0.999

0.1

0.5

Valeric acid

1–30

y = 0.075x - 0.030

0.998

0.1

0.5

a

Conc.

a

20 100 300 20 100 300 2 10 30 20 100 300 2 10 30 2 10 30

g ml-1

b

Mean ± Standard deviation

15


Intra-day Precision (RSD %)

Inter-day Precision (RSD %)

Accuracyb (%)

2.8 3.6 3.2 2.9 6.1 2.4 3.0 7.0 2.5 2.8 7.8 2.9 2.5 7.2 3.1 4.0 7.1 3.1

4.9 4.7 2.7 2.9 6.1 2.2 8.5 8.3 6.0 4.7 6.4 3.0 8.5 8.9 6.8 9.7 8.1 6.5

110.0 ± 4.1 92.9 ± 4.0 96.7 ± 2.7 103.2 ± 2.4 88.0 ± 5.1 100.9 ± 2.3 100.2 ± 7.1 93.3 ± 7.3 102.9 ± 5.4 110.5 ± 3.8 93.8 ± 6.1 110.9 ± 3.3 102.3 ± 6.8 96.2 ± 8.0 109.4 ± 6.6 101.9 ± 7.1 87.9 ± 6.6 98.1 ± 5.6


3.3 Evaluation and optimization of the sample handling methods Heterogeneity, water content variation and compound stability are major factors that may cause comparison bias when studying SCFAs concentrations in fecal samples. To propose a reliable sample handling protocol for studying SCFAs, this study evaluated several generally used handling approaches and optimized the amount of samples used. We first optimized the sample amounts to minimize sampling bias in subsequent studies. The optimized sample amount was used to study the effect of lyophilization and the stability of SCFAs in different storage forms.

3.4 Optimization of the sampling amount Unlike other specimens, such as urine and plasma, fecal samples are heterogeneous; therefore, spot sampling may result in high metabolic variations.26 Previous studies have suggested homogenization of fecal samples before analysis. However, homogenization of fecal samples is not user-friendly in many laboratories. Therefore, this study investigated whether sampling bias can be minimized by optimizing the sample amount to make the subsample more representative of the feces as a whole. In our literature survey, the amounts of feces used for metabolite analyses generally ranged between milligrams and grams. Therefore, we compared the concentration differences of SCFAs in fecal samples obtained from different sampling positions (the middle and both ends) for sample amounts from 60 mg, 500 mg and 1 g. To optimize the sampling amounts, we collected fecal samples from 5 healthy volunteers. Three-point sampling was performed for each fecal sample. Subsamples were extracted and quantified via the previously mentioned optimized analytical method. Figure 2 shows a comparison of principal component plots obtained from 60 16


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mg, 500 mg and 1 g samples. When the sample amount was 60 mg, subsamples obtained from the same subject could not be clustered. In addition, an intra-individual variance larger than the inter-individual difference was observed in subject 3 and subject 5. When the sample amount was increased to 500 mg, we still observed significant intra-individual variance, especially in subject 1, 3, and 5. Figure 2c indicates that when using 1 g of feces to analyze SCFAs, subsamples obtained from the same subject could be successfully clustered. This result indicated that when using the 1 g fecal sample, the inter-individual difference was obviously larger than intraindividual variance.

Figure 2. The principal component analysis (PCA) scores plot showing clustering of the SCFA compositions in (a) 60 mg and (b) 500 mg and (c) 1 g fecal samples. Different colors and symbols represent fecal samples obtained from different subjects. Fecal samples were obtained from three different locations for each subject (n = 5).

Table S1 shows concentrations of 6 SCFA obtained from the three different sampling positions for the 5 test individuals when using 1 g of sample. The concentration variations between the different sampling positions varied between each test individual and each SCFA. The relative standard deviation of the 6 SCFAs obtained from the 3 different sampling positions for the 5 test individuals was between 2 to 28%. 17



Isobutyric acid and isovaleric acid showed the highest concentration variation in subject 1 and 2, whereas acetic acid showed the highest concentration variation in subject 3. The differences are assumed to be caused by the different compositions of the gut microbiota between the test individuals. Although slightly higher than 20% RSD was found for isobutyric acid and isovaleric acid in subject 1, the intra-individual variation was still well below the inter-individual variation. Based on these results, one gram of fecal sample is suggested for SCFA analysis.

3.5 Stability of SCFA between different storage forms Since SCFAs are volatile compounds, particular attention should be paid to the storage of fecal samples. It has been suggested that samples be stored as fecal water when studying the fecal metabolome due to improved stability,26 but little is known about the stability of SCFAs in different forms of fecal samples. The three most common storage forms of fecal samples are lyophilized feces, crude feces and fecal water; the sample stability for these storage forms was investigated in this study. The experimental design for studying SCFA stability in the different storage forms is shown in Figure 1. Fecal samples from the same healthy volunteer were subjected to lyophilization or acid water extraction. The lyophilized products, fecal water and crude feces were storage at 4°C or -20°C for the stability study. The results shown in Figure 3 indicate that the recoveries of the 6 SCFAs were higher than 85% for all of the storage forms and at all of the storage temperatures tested over 7 days of storage. However, significant loss was observed when the sample was stored as crude feces at 4°C for 30 days. It was found that valeric acid was slightly decreased when stored as fecal water for 30 days at both temperatures, with recoveries of 86%. We concluded that SCFAs in 18


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the lyophilized form were the most stable. Lyophilized fecal samples were further studied for their freeze-thaw stability, and the results indicated that the target SCFAs were stable after three freeze-thaw cycles with recoveries within 104.1-106.6% . To consider the early time period after fecal sample collection and before sample shipment for analysis, we additionally studied the stability of SCFAs in crude feces after 1 h, 6 h and 24 h of storage at room temperature. The results are shown in Figure 3 (g). Acetic acid gradually increased with the increase of the storage time, and the other five SCFAs were relatively stable with recoveries > 80% after 24 h of storage at room temperature. Compared to t0 (immediate analysis after sample collection), acetic acid levels showed an increase of 78.8%.

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Figure 3. Stability of SCFAs in lyophilized feces (a)(b), crude feces (c)(d) and fecal extract (e)(f) stored at 4℃ (a)(c)(e), -20℃ (b)(d)(f) for 30 days after sampling. Figure (g) shows the stability of SCFAs in crude feces stored at room temperature for 24 h. Data were normalized to the concentration at day 0 and expressed as recoveries (%) (n=3).

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3.6 Evaluation the effect of lyophilization on the measurement of SCFAs Lyophilization is a common sample pretreatment procedure for fecal samples that is performed to minimize the comparison bias caused by different water contents. We also found that an additional advantage of processing a lyophilized sample was improved stability. However, whether the lyophilization process will cause a loss of SCFAs remains a concern. Therefore, we investigated the effect of the lyophilization procedure on each SCFA concentration in fecal samples. To evaluate whether there was a loss of SCFAs during lyophilization, fecal samples from the same healthy volunteers were first homogenized, and then, two 1 g fecal samples were processed with or without lyophilization, followed by sample extraction. The comparison of the concentrations of the six SCFAs from fecal samples processed with or without lyophilization is shown in Figure 4. The recoveries of the six SCFAs in fecal samples processed without lyophilization were set as 100% and were used to compare those obtained after lyophilization to investigate the potential loss of SCFAs during lyophilization. Figure 4 indicates that the recoveries of the six SCFA from lyophilized samples were generally within 90% to 115%. A slightly higher variation of acetic acid was observed for S03, which is assumed to be due to sampling bias, as discussed in the previous section. We concluded that the lyophilization procedure does not cause a significant loss of SCFAs.

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Figure 4. Comparison of the recoveries of the 6 SCFAs obtained from fecal samples processed with or without lyophilization from 5 subjects. C2 = acetic acid, C3 = propionic acid, C4 = butyric acid, i-C4 = isobutyric acid, i-C5 = isovaleric acid, C5 = valeric acid. 3.7 Suggest sample handling protocol for analyzing SCFAs in human feces This study investigated the sample handling parameters that may affect SCFA comparison bias in human fecal studies. We found that acetic acid gradually increased with the increase of storage time when stored at room temperature. Therefore, fecal samples should be kept at a temperature equal to or lower than 4°C after sample collection, and also during shipment. The stability study indicated that the recoveries were higher than 85% for the six SCFAs in crude feces, but were significantly reduced at 30 days if the samples were stored at 4°C. As a result, sample transportation to the analytical lab is suggested to be completed within 7 days after collection. We found 22


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that lyophilization of fecal samples can not only minimize the bias caused by the water content but also provide better SCFA stability. Although previous studies had concerns about the potential loss of SCFAs during lyophilization, this study demonstrated that the six SCFAs were stable and that their recoveries were higher than 90% after lyophilization. Lyophilization was therefore suggested as the best sample storage form before GC-MS analysis. Lyophilization of a large amount of fecal sample is extremely time consuming, so 1 g of fecal sample was suggested for lyophilization to minimize sampling bias. The proposed sample handling protocol is shown in Figure 5.

Figure 5. Suggested protocol for studying SCFAs in human feces.

4. Discussion Due to its association with various diseases, study of the gut microbiota has been a hot topic in recent years. Studying the gut microbiota mainly began with an investigation of microbial DNA and gradually moved to the gut metabolites. Unlike microbial DNA studies, which mainly focus on investigating the species of microbe, 23



metabolites are compared for their concentrations. For urine metabolomic studies, a concentration adjustment for the creatinine concentration or osmolality is generally applied before statistical analysis.30, 31 However, concentration adjustments have been less discussed in fecal metabolomic studies. To provide a fair comparison for metabolite concentrations, adjusting for the water content is essential for human fecal studies due to the high water content variations between individuals. SCFAs are among the most frequently studied gut metabolites due to their biological importance. Most of the current SCFA analysis studies use a sampling protocol designed for microbial DNA studies without considering the special concerns for metabolite concentration comparisons.23, 24 Though a few studies have considered water content variations and used lyophilisates in SCFA studies, the sample amounts varied substantially or were not mentioned.32 As the sample handling method greatly affects the integrity of data, this study investigated the most important parameters that may affect the SCFA comparison bias in human fecal studies. We also developed an accurate GC-MS method to quantify SCFAs. The LLE method was applied to extract SCFA and also minimize fecal interferences. Although ethyl acetate was the most frequently used extraction solvent, we found a significant acetic acid signal in blank ethyl acetate solvent in several commercial sources. This study used butanol as the extraction solvent which could provide a much cleaner background compared to ethyl acetate. Although the recovery was around 70% at high concentration for acetic (C2) and propionic (C3) acid when using butanol as the extraction solvent, it was constant during the analysis. We therefore were able to get good precision and accuracy for six SCFAs.

24


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Gratton et al recently proposed a sample handling strategy for metabolic profiling of human feces and suggested using fecal water samples with a representative amount (∼ 15 g) of homogenized stool sample. Because their method targeted a large set of metabolites with a wide dynamic range, a significantly large amount of fecal sample was suggested to minimize sampling error. Compared to their study, in the present study, a 1 g fecal sample was shown to be sufficiently representative of the SCFA profile in our test subjects. Although the relative standard deviation of a few SCFAs was slightly higher than 20% between samples obtained from different fecal locations in the same subject, the inter-individual differences were still larger than the intra-individual differences. In addition to differences in the sampling amount, we suggest lyophilizing fecal samples before analysis. We found that the lyophilization procedure does not cause a significant loss of SCFAs. Different to our results, Saric et al. have indicated the potential loss of SCFAs during lyophilization25. Jacobs et al. found that the loss of SCFA can be minimized if the fecal extract is pre-adjusted to pH≥733. The reason for different observations in SCFA loss with our study could be explained by the different analytical methods being used. Both of the previous two studies claimed the potential loss of SCFA targeted on fecal metabolome and used water as the extraction solution followed by NMR analysis. Solubility of SCFAs in water is lower than in the organic solvent used in our study. The relatively low amount of SCFA in fecal extract makes them more easily be affected by the lyophilization procedure. This study used butanol extraction followed by GC-MS to quantify SCFA in human feces. Validation results indicated that the method could provide good quantification accuracy for SCFA in fecal samples. With the accurate quantification method, we found that lyophilization 25



procedure does not cause a significant loss of SCFAs. We also demonstrated that SCFAs in lyophilisates showed the best stability. Most importantly, lyophilization can minimize the water content bias, which is especially important for comparing fecal metabolite concentrations. This study also found acetic acid gradually increased if stored at room temperature which is assumed to be due to the production by microbes in feces. To minimize the activity of microbes, fecal samples should immediately be kept at 4°C after collection. With understanding the factors that may cause bias in analyzing SCFAs in human feces, we have established a sample handling protocol that could more closely reflect SCFA concentrations in study subjects.

5. Conclusion The gut microbiota has become one of the most important scientific fields. The study of gut metabolites began by studying microbial DNA, so the sample handling protocol was mainly adapted from DNA studies. However, special precautions that should be taken when comparing metabolite concentrations were rarely considered in designing sample handling protocols. SCFAs are among most frequently discussed gut metabolites. As the sample handling method greatly affects the integrity of data, we investigated the most relevant parameters that may affect the SCFA comparison bias in human fecal studies. We developed a LLE method combined with GC-MS analysis to quantify SCFA, and the method was applied to study sample handling protocol for analyzing SCFAs in human feces. We found that lyophilization of fecal samples can not only minimize the bias caused by the water content but can also provide better stability of SCFAs. We also found that using a 1 g fecal sample was sufficiently 26


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representative of the SCFA profile in the study subject and was suggested as the sampling amount to minimize sampling bias. As SCFAs have been shown to play an important role in the maintenance of health or the development of disease, the proposed protocol is anticipated to be applicable to clinical studies for delineating the biological functions of SCFAs.

Supporting information The following supporting information is available free of charge at ACS website. Figure S1. Extracted ion chromatogram of each SCFA (including internal standards) in standard mixture (a) to (h) and fecal sample(i) to (p). (a)(i) acetic acid; (b)(j) propionic acid ; (c)(k) isobutyric acid; (d)(l) butyric acid; (e)(m) isovaleric acid; (f)(n) valeric acid; (g)(o) IS1, sodium acetate-d3; (h)(p) sodium propionate-d5. The concentration of the standards and ISs are 50 g mL-1. Table S1. Concentrations of 6 SCFA obtained from the three different sampling positions for the 5 test individuals (n=3 with independent preparations).

Acknowledgements This study was supported by the Ministry of Science and Technology of Taiwan (MOST

106-2113-M-002-006;

106-2314-B-002-227),

and the

Program

for

Translational Innovation of Biopharmaceutical Development - Technology Supporting Platform Axis (Grant No. 106-0210-01-10-01 ; 107-0210-01-19-04 ) for funding support.

27



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30. Wagner, B. D.; Accurso, F. J.; Laguna, T. A., The applicability of urinary creatinine as a method of specimen normalization in the cystic fibrosis population. Journal of Cystic Fibrosis 2010, 9, (3), 212-216. 31. Gyamlani, G. G.; Bergstralh, E. J.; Slezak, J. M.; Larson, T. S., Urinary albumin to osmolality ratio predicts 24-hour urine albumin excretion in diabetes mellitus. American Journal of Kidney Diseases 2003, 42, (4), 685-692. 32. Unger, M. M.; Spiegel, J.; Dillmann, K. U.; Grundmann, D.; Philippeit, H.; Burmann, J.; Fassbender, K.; Schwiertz, A.; Schafer, K. H., Short chain fatty acids and gut microbiota differ between patients with Parkinson's disease and agematched controls. Parkinsonism & Related Disorders 2016, 32, 66-72. 33. Jacobs, D. M.; Deltimple, N.; van Velzen, E.; van Dorsten, F. A.; Bingham, M.; Vaughan, E. E.; van Duynhoven, J., H-1 NMR metabolite profiling of feces as a tool to assess the impact of nutrition on the human microbiome. Nmr in Biomedicine 2008, 21, (6), 615-626.

Figures legends Figure 1. Experimental design for evaluation of the sample handling protocol for studying SCFAs in human feces. Figure 2. The principal component analysis (PCA) scores plot showing clustering of the SCFA compositions in (a) 60 mg, (b) 500 mg and (c) 1 g fecal samples. Different colors and symbols represent fecal samples obtained from different subjects. Fecal samples were obtained from three different locations for each subject (n = 5). Figure 3. Stability of SCFAs in lyophilized feces (a)(b), crude feces (c)(d) and fecal extract (e)(f) stored at 4℃ (a)(c)(e) and -20℃ (b)(d)(f) for 30 days after sampling. Figure (g) shows the stability of SCFAs in crude feces stored at room temperature for 24 h. Data were normalized to the concentration at day 0 and expressed as recoveries (%) (n=3). Figure 4. Comparison of the recoveries of the 6 SCFAs obtained from fecal samples processed with or without lyophilization from 5 subjects. C2 = acetic acid, C3 = propionic acid, C4 = butyric acid, i-C4 = isobutyric acid, i-C5 = isovaleric acid, C5 = valeric acid. Figure 5. Suggested protocol for studying SCFAs in human feces. 30


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For TOC only

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Figure 1 295x178mm (150 x 150 DPI)


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Figure 2 296x100mm (150 x 150 DPI)



Figure 3 295x357mm (150 x 150 DPI)


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Figure 4 254x169mm (150 x 150 DPI)



Figure 5 109x128mm (150 x 150 DPI)


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Graphic abstract 130x155mm (150 x 150 DPI)


Evaluation and Optimization of Sample Handling Methods for

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