N methyl n trimethylsilyl trifluoroacetamide

Manufactured by GL Sciences

Sourced in Japan

N-methyl N-trimethylsilyl-trifluoroacetamide is a chemical reagent used in analytical chemistry. It is commonly used as a derivatizing agent to enhance the volatility and separation of compounds during gas chromatography analysis.

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Lab products found in correlation

2 isopropylmalic acid, by Merck Group (3 mentions) Gcms qp2010 ultra, by Shimadzu (3 mentions) Smart metabolites database, by Shimadzu (3 mentions) Methoxyamine hydrochloride, by Merck Group (2 mentions) Gcms qp2010 system, by Shimadzu (2 mentions) Agilent 6460, by Agilent Technologies (1 mentions) Masshunter workstation data acquisition software, by Agilent Technologies (1 mentions)

Spelling variants of this product

N-methyl-N- (trimethylsilyl) trifluoroacetamide (MSTFA) (6 citations)

5 protocols using n methyl n trimethylsilyl trifluoroacetamide

Serum Metabolomics Analysis by GC/MS

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A serum metabolomics analysis was performed using GC/MS as described previously [24 (link)] with some modifications. In brief, a sample of 50
µl of serum was mixed with 5 µl of 1 mg/ml 2-isopropylmalic acid (Sigma-Aldrich, Tokyo, Japan) in distilled water as an internal
standard, and 250 µl of methanol–chloroform–water (2.5:1:1) mixture. Then samples were lyophilized, and added with 40 µl of 20 mg/mlmethoxyamine hydrochloride (Sigma-Aldrich), dissolved in pyridine for oximation. After mixing, the samples were shaken for 90 min at 30°C. Next 20 µl of N-methyl
N-trimethylsilyl-trifluoroacetamide (GL Science, Tokyo, Japan) was added for trimethylsilylation, and the mixture was incubated at 37°C for 45 min. The sample was subjected to GC/MS (GCMS
QP2010-Ultra; Shimadzu, Kyoto, Japan). The Shimadzu Smart Metabolites Database (Shimadzu) was used to identify metabolites. Samples were normalized by a pooled sample from control group. A
metabolic pathway analysis was performed using MetaboAnalyst [25 (link)]. Metabolites that significantly diffed between two groups were subjected to an
enrichment analysis (http://www.metaboanalyst.ca/faces/upload/EnrichUploadView.xhtml).

PU S., USUDA K., NAGAOKA K, & WATANABE G. (2018). Heat challenge influences serum metabolites concentrations and liver lipid metabolism in Japanese quail (Coturnix japonica). The Journal of Veterinary Medical Science, 81(1), 77-83.

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Serum Metabolomics Analysis by GC/MS

Cited 1 time

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A serum metabolomics analysis was performed using GC/MS as described previously [34 (link)] with some modifications. In brief, a sample of 50 μL of serum was mixed with 5 μL of 1 mg/mL 2-isopropylmalic acid (Sigma-Aldrich, St. Louis, MO, USA) in distilled water as an internal standard, and 250 μL of methanol–chloroform–water (2.5:1:1) mixture. Then samples were lyophilized, and added with 40 μL of 20 mg/mL methoxyamine hydrochloride (Sigma-Aldrich), dissolved in pyridine for oximation. After mixing, the samples were shaken for 90 min at 30 °C. Next, 20 μL of N-methyl N-trimethylsilyl-trifluoroacetamide (GL Science, Tokyo, Japan) was added for trimethylsilylation, and the mixture was incubated at 37 °C for 45 min. The sample was subjected to GC/MS (GCMS QP2010-Ultra; Shimadzu, Kyoto, Japan). The Shimadzu Smart Metabolites Database (Shimadzu) was used to identify metabolites. Samples were normalized by a pooled all sample. All data are presented in Supplementary Tables S1 and S2 [35 (link)]. A metabolic pathway analysis was performed using MetaboAnalyst [36 (link)]. Metabolites that significantly differed between two groups were subjected to an enrichment analysis (http://www.metaboanalyst.ca/faces/upload/EnrichUploadView.xhtml, accessed on 1 June 2021).

Kusama K., Bai R., Matsuno Y., Ideta A., Sakurai T., Nagaoka K., Hori M, & Imakawa K. (2022). Characterization of Serum Metabolome and Proteome Profiles Identifies SNX5 Specific for Pregnancy Failure in Holstein Heifers. Life, 12(2), 309.

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Quantification of Free Amino Acids in Fermentation

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Free amino acids were extracted from supernatants collected from culture broths after 48 h of fermentation, using a modified cold chloroform–methanol method (Putri et al. 2013 (link)). The water phase of the extract (700 µL) was dried under vacuum and stored at − 80 °C until further analysis (Bennett et al. 2008 (link)).
The dried extract samples were thawed on ice and derivatized at 30 °C for 90 min with 100 µL of 20 mg/mL methoxyamine hydrochloride in pyridine, after which 50 µL N-methyl-N-(trimethylsilyl) trifluoroacetamide (GL Sciences, Tokyo, Japan) (Lisec et al. 2006 (link)) was added, followed by incubation at 37 °C for 30 min. The derivatized samples (1 µL) were subjected to gas chromatography–quadrupole–mass spectrometry (GC–Q–MS) using a GCMSQP-2010 system (Shimadzu). The details of the GC–Q–MS operating conditions and procedures were described previously (Kato et al. 2012 (link); Sasaki et al. 2014 (link)). Free amino acid concentrations were measured in triplicate.

Sasaki D., Sasaki K., Kadowaki Y., Aotsuka Y, & Kondo A. (2019). Bifidogenic and butyrogenic effects of young barely leaf extract in an in vitro human colonic microbiota model. AMB Express, 9, 182.

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Serum Metabolomics by GC/MS Analysis

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Serum metabolomics analysis was performed using GC/MS as described previously (Takemoto et al., 2017 (link)) with some modifications. A sample of 50 μL of serum was mixed with 5 μL of 1 mg/mL 2-isopropylmalic acid (Sigma-Aldrich, Tokyo, Japan) in distilled water as an internal standard, and 250 μL of a methanol–chloroform–water (2.5:1:1) mixture. Then, the samples were lyophilized, and 40 μL of 20 mg/mL methoxyamine hydrochloride (Sigma-Aldrich) was dissolved in pyridine for oximation. After mixing, the samples were shaken for 90 min at 30°C. Next, 20 μL of N-methyl N-trimethylsilyl-trifluoroacetamide (GL Science, Tokyo, Japan) was added for trimethylsilylation. The mixture was incubated at 37°C for 45 min. The sample was subjected to GC/MS (GCMS QP2010-Ultra; Shimadzu, Kyoto, Japan). The Shimadzu Smart Metabolites Database (Shimadzu) was used to identify metabolites. Samples were normalized by a pooled sample from the control group. A metabolic pathway analysis was performed using MetaboAnalyst (Xia and Wishart, 2011 (link)). Metabolites that significantly differed between the 2 groups were subjected to an enrichment analysis (http://www.metaboanalyst.ca/faces/upload/EnrichUploadView.xhtml).

Pu S., Usuda K., Nagaoka K., Gore A., Crews D, & Watanabe G. (2020). The relation between liver damage and reproduction in female Japanese quail (Coturnix japonica) exposed to high ambient temperature. Poultry Science, 99(9), 4586-4597.

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Comprehensive metabolomic analysis of cell extracts

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The dried extract samples were thawed on ice, derivatized at 30 °C for 90 min with 100 µL of 20 mg mL⁻¹ methoxyamine hydrochloride in pyridine, after which 50 µL N-methyl-N-(trimethylsilyl) trifluoroacetamide (GL Sciences, Tokyo, Japan) [27 (link)] was added followed by incubation at 37 °C for 30 min. Derivatized samples (1 µL) were subjected to gas chromatography-quadrupole-mass spectrometry (GC-Q-MS) using a GCMSQP-2010 system (Shimadzu) to detect metabolites from the TCA cycle, glutamate, and glucose.
Aliquots of the dried extract samples were also dissolved in 50 µL Milli-Q water and prepared for analysis by liquid chromatography-triple-stage quadrupole-mass spectrometry (LC-QqQ-MS) using an HPLC Agilent 1200 series for LC and Agilent 6460 with Jet Stream Technology for MS (Agilent Technologies, Waldbronn, Germany) controlled by MassHunter Workstation Data Acquisition software (v. B. 04.01; Agilent Technologies). The following compounds were detected: metabolites from the Embden-Meyerhof and pentose phosphate pathways, acetyl-CoA, ATP, ADP, nicotinamide adenine dinucleotide (NADH, NAD⁺), and nicotinamide adenine dinucleotide phosphate (NADPH, NADP⁺) [28 (link)]. Details of the GC-Q-MS and LC-QqQ-MS operating conditions and procedures have been described previously [29 (link), 30 (link)]. Metabolite concentration was measured by triplicate sample injections.

Sasaki D., Sasaki K., Tsuge Y, & Kondo A. (2019). Less biomass and intracellular glutamate in anodic biofilms lead to efficient electricity generation by microbial fuel cells. Biotechnology for Biofuels, 12, 72.

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