Isodeoxycholic Acid
(Synonyms: isoDCA) 目录号 : GC47464
A bile acid
Cas No.:566-17-6
Sample solution is provided at 25 µL, 10mM.
;)
,-1-7$$$37316672.jpg');)
;)
;)
$$$36806353.jpg');)
;33(7)%EF%BC%9A546-561$$$37156877.jpg');)
;)
;)
;)
%201124-1138.$$$35908550.jpg');)
%20766-780.$$$37100057.jpg');)
%20418-432.$$$36893736.jpg');)
%EF%BC%9A-240-255.$$$35108512.jpg');)
533-545$$$36543525.jpg');)
%201-13.$$$36600053.jpg');)
;)
Quality Control & SDS
- View current batch:
- Purity: >95.00%
- COA (Certificate Of Analysis)
- SDS (Safety Data Sheet)
- Datasheet
Isodeoxycholic acid is a bile acid that is formed via epimerization of deoxycholic acid by intestinal bacteria.[1] It has a greater critical micelle concentration than DCA, indicating reduced detergent activity, and is less active than DCA in inhibiting growth in a panel of seven gut commensal bacteria species. Isodeoxycholic acid (0.1%) inhibits spore germination induced by taurocholic acid in several C. difficile strains, as well as decreases the cytotoxicity of C. difficile culture supernatants to Vero cells.[2] Plasma levels of isodeoxycholic acid are decreased in a rat model of high-fat diet-induced obesity compared with rats fed a normal diet.[3]
Reference:
[1].Devlin, A.S., and Fischbach, M.A.A biosynthetic pathway for a prominent class of microbiota-derived bile acidsNat. Chem. Biol.11(9)685-690(2018)
[2].Thanissery, R., Winston, J.A., and Theriot, C.M.Inhibition of spore germination, growth, and toxin activity of clinically relevant C. difficile strains by gut microbiota derived secondary bile acidsAnaerobe4586-100(2017)
[3].Lin, H., An, Y., Tang, H., et al.Alterations of bile acids and gut microbiota in obesity induced by high fat diet in rat modelJ. Agric. Food Chem.67(13)3624-3632(2019)
| Cas No. | 566-17-6 | SDF | |
| 别名 | isoDCA | ||
| 化学名 | (5β,7α,12α)-7,12-dihydroxy-cholan-24-oic acid | ||
| Canonical SMILES | C[C@@]12[C@@](C[C@@H](O)[C@]3([H])[C@]2([H])C[C@H](O)[C@@]4(C)[C@@]3([H])CC[C@]4([H])[C@H](C)CCC(O)=O)([H])CCCC1 | ||
| 分子式 | C24H40O4 | 分子量 | 392.6 |
| 溶解度 | DMF: 30mg/mL,DMF:PBS (pH 7.2) (1:1): 0.5mg/mL,DMSO: 20mg/mL,Ethanol: 20mg/mL | 储存条件 | Store at -20°C |
| General tips | 请根据产品在不同溶剂中的溶解度选择合适的溶剂配制储备液；一旦配成溶液，请分装保存，避免反复冻融造成的产品失效。 储备液的保存方式和期限：-80°C 储存时，请在 6 个月内使用，-20°C 储存时，请在 1 个月内使用。 为了提高溶解度，请将管子加热至37℃，然后在超声波浴中震荡一段时间。 |
||
| Shipping Condition | 评估样品解决方案：配备蓝冰进行发货。所有其他可用尺寸：配备RT，或根据请求配备蓝冰。 | ||
| 制备储备液 | |||
 |
1 mg | 5 mg | 10 mg |
| 1 mM | 2.5471 mL | 12.7356 mL | 25.4712 mL |
| 5 mM | 0.5094 mL | 2.5471 mL | 5.0942 mL |
| 10 mM | 0.2547 mL | 1.2736 mL | 2.5471 mL |
| 第一步：请输入基本实验信息（考虑到实验过程中的损耗，建议多配一只动物的药量） | ||||||||||
| 给药剂量 | mg/kg |  |
动物平均体重 | g | |
每只动物给药体积 | ul | |
动物数量 | 只 |
| 第二步：请输入动物体内配方组成（配方适用于不溶于水的药物；不同批次药物配方比例不同，请联系GLPBIO为您提供正确的澄清溶液配方） | ||||||||||
| % DMSO % % Tween 80 % saline | ||||||||||
| 计算重置 | ||||||||||
计算结果:
工作液浓度： mg/ml；
DMSO母液配制方法： mg 药物溶于 μL DMSO溶液（母液浓度 mg/mL，
体内配方配制方法：取 μL DMSO母液，加入 μL PEG300，混匀澄清后加入μL Tween 80，混匀澄清后加入 μL saline，混匀澄清。
1. 首先保证母液是澄清的；
2.
一定要按照顺序依次将溶剂加入，进行下一步操作之前必须保证上一步操作得到的是澄清的溶液，可采用涡旋、超声或水浴加热等物理方法助溶。
3. 以上所有助溶剂都可在 GlpBio 网站选购。
Intrauterine growth retardation affects liver bile acid metabolism in growing pigs: effects associated with the changes of colonic bile acid derivatives
J Anim Sci Biotechnol 2022 Nov 2;13(1):117.PMID:36320049DOI:10.1186/s40104-022-00772-6.
Background: Intrauterine growth retardation (IUGR) is associated with severely impaired nutrient metabolism and intestinal development of pigs. Our previous study found that IUGR altered intestinal microbiota and metabolites in the colon. However, the consequences of IUGR on bile acid metabolism in pigs remained unclear. The present study aimed to investigate the bile acid metabolism in the liver and the profile of bile acid derivatives in the colon of growing pigs with IUGR using bile acid targeted metabolomics. Furthermore, we determined correlations between colonic microbiota composition and metabolites of IUGR and normal birth weight (NBW) pigs at different growth stages that were 7, 21, and 28-day-old, and the average body weight (BW) of 25, 50, and 100 kg of the NBW pigs. Results: The results showed that the plasma total bile acid concentration was higher (P < 0.05) at the 25 kg BW stage and tended to increase (P = 0.08) at 28-day-old in IUGR pigs. The hepatic gene expressions related to bile acid synthesis (CYP7A1, CYP27A1, and NTCP) were up-regulated (P < 0.05), and the genes related to glucose and lipid metabolism (ATGL, HSL, and PC) were down-regulated (P < 0.05) at the 25 kg BW stage in IUGR pigs when compared with the NBW group. Targeted metabolomics analysis showed that 29 bile acids and related compounds were detected in the colon of pigs. The colonic concentrations of dehydrolithocholic acid and apocholic acid were increased (P < 0.05), while Isodeoxycholic Acid and 6,7-diketolithocholic acid were decreased (P < 0.05) in IUGR pigs, when compared with the NBW pigs at the 25 kg BW stage. Moreover, Spearman's correlation analysis revealed that colonic Unclassified_[Mogibacteriaceae], Lachnospira, and Slackia abundances were negatively correlated (P < 0.05) with dehydrolithocholic acid, as well as the Unclassified_Clostridiaceae abundance with 6,7-diketolithocholic acid at the 25 kg BW stage. Conclusions: These findings suggest that IUGR could affect bile acid and glucolipid metabolism in growing pigs, especially at the 25 kg BW stage, these effects being paralleled by a modification of bile acid derivatives concentrations in the colonic content. The plausible links between these modified parameters are discussed.
Characterization of long-chain fatty acid-linked bile acids: a major conjugation form of 3β-hydroxy bile acids in feces
J Lipid Res 2022 Oct;63(10):100275.PMID:36089004DOI:10.1016/j.jlr.2022.100275.
Although most bile acids (BAs) in feces are present in noncovalent forms that can be extracted with ethanol, non-negligible amounts of saponifiable BAs are also present. It is a major concern that such saponifiable BAs are routinely omitted from fecal BA measurements. We compared the BA profiles of healthy stools that were obtained with/without alkaline hydrolysis and found that as much as 29.7% (2.1-67.7%) of total BAs were saponifiable. Specifically, alkaline treatment led to significant elevations of Isodeoxycholic Acid (isoDCA) and isolithocholic acid (isoLCA) concentrations, suggesting that considerable proportions of isoDCA and isoLCA were esterified. Precursor ion scan data from LC/MS suggested the presence of long-chain FA-linked BAs. We chemically synthesized a series of fatty acid 3β-acyl conjugates of isoDCA and isoLCA as analytical standards and analyzed their fecal profiles from newborns to adults (n = 64) by LC/MS. FA-conjugated isobile acids (FA-isoBAs) were constantly present from 2 years of age to adulthood. C16- and C18-chain FA-isoBA esters were predominantly found regardless of age, but small amounts of acetic acid esters were also found. FA-isoBA concentrations were not correlated to fecal FA concentrations. Interestingly, there were some adults who did not have FA-isoBAs. Gut bacteria involved in the production of FA-isoBAs have not been identified yet. The present study provides insight into the establishment of early gut microbiota and the interactive development of esterified BAs.The contribution of FA-isoBAs to gut physiology and their role in pathophysiologic conditions such as inflammatory bowel disease are currently under investigation.
A dynamic multiple reaction monitoring strategy to develop and optimize targeted metabolomics methods: Analyzing bile acids in capecitabine-induced diarrhea
J Pharm Biomed Anal 2022 Sep 20;219:114938.PMID:35850015DOI:10.1016/j.jpba.2022.114938.
Objective: We sought to develop and optimize a targeted bile acids (BAs) metabolomics method based on a dynamic multiple reaction monitoring (dMRM) strategy and explored the dynamic alterations of BAs in diarrhea induced by capecitabine in a mouse model. Method: The targeted metabolomics method was developed using an Agilent 6460A triple quadrupole mass spectrometer, and 41 types of BAs were monitored in negative ionization mode. The mass spectrometer detection was optimized using dMRM to enhance the responses, separation, and peak shape and to shorten the analysis time. A mouse model of diarrhea was established by multiple administration of capecitabine, and plasma samples were collected at baseline and the end of drug administration for subsequent BAs analysis. Results: The targeted BA metabolomics method achieved shorter chromatographic separation time (10 min) for 41 BAs, with good peak shapes and response increases of 3- to 10-fold after application of dMRM. The mouse model of capecitabine-induced diarrhea was established, and the three BAs 23-norcholic acid, isolithocholic acid, and Isodeoxycholic Acid in the baseline samples contributed the most to differentiating mice with diarrhea from those without diarrhea. For mice that ultimately developed diarrhea, apocholic acid, Isodeoxycholic Acid, and 7-ketodeoxycholic acid exhibited the largest change in concentrations compared with their baseline concentrations. Conclusion: The dMRM strategy has obvious advantages compared with common MRM. The results in model mice showed that a differentiated profile of BAs in the baseline may indicate biomarkers of diarrhea induced by capecitabine, and disturbed homeostasis may explain the metabolomic mechanism of diarrhea occurrence.
A Novel Gene Alignment in Dorea sp. AM58-8 Produces 7-Dehydroxy-3β Bile Acids from Primary Bile Acids
Biochemistry 2022 Dec 20;61(24):2870-2878.PMID:36130198DOI:10.1021/acs.biochem.2c00264.
Bile acids are essential metabolites and signaling molecules in mammals. Primary bile acids are synthesized from cholesterol in the liver. At the same time, the microbiota in the mammalian gut has many interactions with bile acid, including various biotransformation processes such as 7-dehydroxylation and 3-epimerization. 7-Dehydroxylation is mediated by a bile acid-inducible (bai) operon, while 7-dehydroxylation and 3-epimerization are independently observed in only a few strains. Herein, we describe a novel microbe, Dorea sp. AM58-8, that can accomplish a two-step transformation and turn primary bile acids into both 3α secondary bile acids like deoxycholic acid and lithocholic acid, and 3β secondary bile acids like Isodeoxycholic Acid and isolithocholic acid. We subsequently characterized BaiA, BaiB, BaiE, and their substrate profiles biochemically. The potential bai gene clusters in the metagenomes were further mined. Their evolution, potential functions, and possible regulatory pathways were predicted using bioinformatics based on our understanding of the 7-dehydroxylation pathway in Dorea sp. AM58-8. This study of Dorea sp. AM58-8 also helps us distinguish the inactive bacteria that seem to have the 7-dehydroxylation pathway proteins and discover the 7-dehydroxylation pathway in other mammalian gut microbes.
A single-injection targeted metabolomics profiling method for determination of biomarkers to reflect tripterygium glycosides efficacy and toxicity
Toxicol Appl Pharmacol 2020 Jan 15;389:114880.PMID:31945383DOI:10.1016/j.taap.2020.114880.
Metabolomics is a powerful tool for studying physiological state of the system. In this study, we proposed a single-injection targeted metabolomics method to identify reliable tripterygium glycosides efficacy and toxicity related biomarkers based on ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Through careful optimization of the UHPLC-MS/MS conditions, a total of 289 metabolites can be quantified in single-injection of 27 min using both positive and negative scanning modes with rapid polarity switching. Tripterygium glycosides is widely used in clinical for its excellent anti-inflammatory and immunosuppressive functions. However, it is the most common drug that can cause hepatotoxicity. In this study, the established metabolomics method was used for determination of biomarkers to reflect tripterygium glycosides efficacy and toxicity. Two different dosages were designed in the animal experiment, including therapeutic dosage and toxic dosage. Statistical analysis based on metabolite concentrations showed that the glutathione metabolism and pyrimidine metabolism were the obvious interfering pathways. This was highly consistent with previous studies. A total of 22 and 47 metabolites were screened as potential biomarkers related to the efficacy and hepatotoxicity of tripterygium glycosides, respectively. Receiver operating characteristic curve (ROC) analysis showed that ten metabolites, including cytosine, 5-methyluridine, deoxyuridine, 5-methylcytidine, deoxycytidine triphosphate (DCTP), keto-glutarate, d-ribose, dihydrofolate, nordeoxycholic acid and Isodeoxycholic Acid possessed area under the curve (AUC) of 1. The metabolites filtered here can better distinguish tripterygium glycosides treated rats from the control rats compared with the traditional blood indicators of liver function.