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研究生:吳煜鈞
研究生(外文):Yu-Jun Wu
論文名稱:第一部分:開發以LC-MS定量芳香族胺基酸衍生之腸道菌代謝物的分析方法並應用於帕金森氏症;第二部分:開發以LC-MS定量人類糞便腸道菌代謝物的方法
論文名稱(外文):Part I : Development of an LC-MS Method to Quantify Aromatic Amino Acid-derived Gut Microbial Metabolites in Human Plasma and Its Application in Studying Parkinson’s Disease; Part II : Development of a Liquid Chromatography-Mass Spectrometry Method to Quantify Gut Microbial Metabolites in Human Feces
指導教授:郭錦樺郭錦樺引用關係
指導教授(外文):Ching-Hua Kuo
口試委員:林靜嫻謝建台賴建成
口試委員(外文):Chin-Hsien LinJentaie ShieaChien-Chen Lai
口試日期:2023-07-21
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:藥學研究所
學門:醫藥衛生學門
學類:藥學學類
論文種類:學術論文
論文出版年:2023
畢業學年度:111
論文頁數:83
中文關鍵詞:腸道菌代謝物芳香族胺基酸液相層析串聯質譜帕金森氏症吲哚膽酸糞便檢體
外文關鍵詞:gut microbial metabolitesaromatic amino acidsliquid chromatography-mass spectrometryParkinson's diseaseindolebile acidsfecal samples
DOI:10.6342/NTU202302703
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人體的腸道菌落複雜且多樣,會隨著飲食習慣與疾病狀態而變化。腸道菌代謝物(Gut microbial metabolites)不僅存在於人體的腸道中,也會分布於人體的血液循環。過去的研究發現腸道菌的組成與它們的代謝產物常常與疾病的發展有關,也因此越來越多的研究利用液相層析串聯質譜儀(Liquid Chromatography-Mass Spectrometry, LC-MS)分析人體血液與糞便中的腸道菌代謝物。
苯乙醯谷氨醯胺(Phenylacetylglutamine, PAGln)與對甲酚(Para-cresol, p-C)分別是苯丙胺酸(Phenylalanine)與酪胺酸(Tyrosine)的下游代謝物,過去被報導是帕金森氏症(Parkinson’s disease)的危險因子。但是這類非標靶代謝體學(Untargeted metabolomics)的研究無法針對特定代謝物做準確定量,亦無法聚焦於特定的代謝途徑做機轉研究。由於過去未有針對芳香族胺基酸(Aromatic amino acid, AAA)代謝途徑與帕金森氏症的研究,因此在本論文的第一部分,我們開發了定量分析血漿中苯丙胺酸、酪胺酸以及色胺酸(Tryptophan)之代謝產物的LC-MS方法。因為芳香族胺基酸代謝物的結構類似,在層析上會需要使用添加物(Additives)來增加分離效果,但添加物的存在又會對苯乙酸(Phenylacetic acid)、苯丙酸(Phenylpropionic acid)以及對甲酚這三種代謝物造成強烈的離子抑制(Ion suppression)。為了解決上述問題我們藉由調整移動相組成和梯度來最佳化層析效果。在一系列的確效後,我們將此方法應用於測量250位帕金森氏症病人的血漿代謝物濃度,並發現苯丙胺酸到苯乙醯谷氨醯胺的整個代謝途徑皆與帕金森氏症相關,更進一步發現苯乙醯谷氨醯胺與葡萄糖醛對甲酚(Para-cresol glucuronide, p-CG)與帕金森氏症病人的動作障礙嚴重度有顯著正相關。基於我們的研究發現,未來將有利於對帕金森氏症機轉的探討。
吲哚(Indole)與膽酸(Bile acids)是過去最常被討論的腸道菌代謝物之一。腸道菌代謝物於腸道中被製造卻會隨著血液循環去影響人體的各個部位,過去也有許多研究顯示同一種代謝物於血漿與糞便中的分布截然不同。由於過去已有定量血漿中吲哚與膽酸的方法,因此在本論文的第二部分,我們開發了同時定量分析人類糞便中的吲哚代謝物以及膽酸的LC-MS方法。糞便是不均質檢體且糞便中代謝物的濃度差異非常大,這對樣品前處理造成了非常大的挑戰。另外腸道菌的存在使得糞便檢體中的代謝物會持續反應,讓檢體的保存更加不易。為了克服以上困難,我們評估了糞便檢體的乾濕型態、取樣量、稀釋倍數與取樣誤差,做了一系列的最佳化後得出一個標準化的糞便前處理流程。我們利用凍乾法去除糞便水分,不但能校正不同檢體間的水分影響,也更容易讓檢體均質化。20毫克的糞便乾粉足以在一次分析中定量高濃度與大部分低濃度的代謝物,省去了二次稀釋上機的時間,並且不會有太大的取樣誤差。我們的安定性試驗顯示原始糞便必須在一小時內儲存於-20度C以降低定量誤差。
總結本論文開發了定量血漿芳香族胺基酸代謝物的方法,並應用於帕金森氏症的臨床研究;本論文更進一步最佳化糞便檢體的前處理與保存運送流程,讓未來的研究者於定量糞便中的吲哚代謝物以及膽酸時能有一個比較基準。
The human gut microbiota is complex and diverse, and it undergoes changes based on dietary habits and disease states. Gut microbial metabolites exist in the intestinal tract and distribute in the bloodstream. Previous studies have shown that the composition of gut microbiota and their metabolites are often associated with disease development. Therefore, an increasing number of studies have utilized liquid chromatography-mass spectrometry (LC-MS) to analyze gut microbial metabolites in human blood and feces.
Phenylacetylglutamine (PAGln) and para-cresol (p-C) are downstream metabolites of phenylalanine and tyrosine, respectively, and have been reported as risk factors for Parkinson's disease (PD). However, untargeted metabolomics studies cannot accurately quantify specific metabolites or investigate specific metabolic pathways. Since there has been limited research on the aromatic amino acid (AAA) metabolic pathway in relation to PD, the first part of this thesis focuses on developing an LC-MS method for the quantitative analysis of phenylalanine, tyrosine, and tryptophan metabolites in human plasma. The structural similarity of AAA metabolites requires additives for enhanced separation; however, these additives can cause strong ion suppression for phenylacetic acid, phenylpropionic acid, and para-cresol. To address this issue, we optimized the chromatographic conditions by adjusting the mobile phase composition and gradient. Following a series of validation experiments, we applied the method to measure the concentrations of AAA metabolites in the plasma of 250 PD patients. We found that the entire pathway from phenylalanine to PAGln is associated with PD, and further analysis showed significant positive correlations between PAGln and para-cresol glucuronide (p-CG) with the severity of motor dysfunction in PD patients. Based on our findings, future studies can further explore the mechanisms of PD.
Indole and bile acids are among the most discussed gut microbial metabolites. While these metabolites are produced in the intestine, they can impact various parts of the human body through the bloodstream. Previous studies have shown distinct differences in the distribution of the same metabolites between plasma and feces. As quantitative methods for indole and bile acids in plasma have already been established, the second part of this thesis focuses on developing an LC-MS method for the simultaneous quantification of indole metabolites and bile acids in human feces. Fecal samples pose challenges due to their heterogeneous nature and significant variations in metabolite concentrations. The presence of gut microbiota leads to continuous reactions of metabolites in fecal samples, such as dihydroxylation, oxidation, and epimerization, making sample storage more difficult. To overcome these challenges, we evaluated the effects of sample types (wet or dry), sampling weight, dilution factors, and sampling errors, and developed a standardized fecal sample preparation process. By using lyophilization to remove water in feces, we were able to correct for variations in water content between samples and achieve better sample homogenization. A 20 mg aliquot of lyophilized fecal powder was sufficient for the quantitative analysis of high and most low concentration metabolites in a single run, eliminating the need for second dilution and minimizing sampling errors. Our stability test showed that the crude wet feces must be stored at -20°C within one hour to minimize quantitative errors.
In summary, this thesis developed a quantitative method for analyzing plasma AAA metabolites and applied it to clinical research in PD. It further optimized the sample preparation, storage, and transportation processes for fecal samples, providing a protocol for future researchers quantifying indole metabolites and bile acids in feces.
誌謝 I
中文摘要 II
Abstract IV
Contents VII
Figure contents IX
Table contents XI
Part I : Development of an LC-MS Method to Quantify Aromatic Amino Acid-derived Gut Microbial Metabolites in Human Plasma and Its Application in Studying Parkinson’s Disease
1 Introduction 2
2 Materials and Methods 4
2.1. Chemicals 4
2.2. Preparation of standard stocks 5
2.3. Analysis of plasma concentrations of AAA-derived gut microbial metabolites 6
2.4. Method validation 8
2.4.1. Linearity 8
2.4.2. Accuracy and extraction recovery 9
2.4.3. Intra-day and inter-day precisions 10
2.5. Clinical application 10
2.5.1. Participants and clinical evaluation 10
2.5.2. Samples collection 11
2.6. Data analysis 12
3 Results 13
3.1. Optimization of LC conditions 13
3.2. Method validation 16
3.2.1. Linearity 16
3.2.2. Accuracy and extraction recovery 17
3.2.3. Intra-day and inter-day precisions 17
3.3. Clinical application 18
4 Discussion 20
5 Conclusion 24
6 Figures 26
7 Tables 34
Part II : Development of a Liquid Chromatography-Mass Spectrometry Method to Quantify Gut Microbial Metabolites in Human Feces
8 Introduction 41
9 Materials and Methods 43
9.1. Chemicals 43
9.2. Preparation of standard stocks 45
9.3. Preparation of fecal samples 46
9.4. UHPLC-MS condition 46
9.5. Optimization of fecal sample preparation 48
9.5.1. Selection of wet and dry fecal samples 48
9.5.2. Optimization of sampling weight of fecal samples 49
9.6. Method validation 50
9.6.1. Linearity 50
9.6.2. Accuracy, extraction recovery, and matrix effect 50
9.6.3. Intra-day and inter-day precisions 52
9.7. Evaluation of stability 52
9.7.1. Stability of crude wet feces 53
9.7.2. Stability of lyophilized fecal powders and fecal extracts 53
9.8. Data analysis 54
10 Results 54
10.1. Establishing a sample preparation protocol 54
10.1.1. The effect of lyophilization 54
10.1.2. Selection of the sampling weight 55
10.2. Method validation 57
10.3. Evaluation of stability 58
10.3.1. Stability of metabolites in different sample types and different storage conditions 58
10.3.2. Suggested human fecal sample preparation and handling protocol 59
11 Discussion 60
12 Conclusion 64
13 Figures 65
14 Tables 70
References 78
1.Klingelhoefer, L. and H. Reichmann, Pathogenesis of Parkinson disease—the gut–brain axis and environmental factors. Nature Reviews Neurology, 2015. 11(11): p. 625-636.
2Cryan, J.F., et al., The Microbiota-Gut-Brain Axis. Physiological Reviews, 2019. 99(4): p. 1877-2013.
3Liu, J., et al., Gut Microbiota Approach-A New Strategy to Treat Parkinson's Disease. Frontiers in Cellular and Infection Microbiology, 2020.
4Bartl, M., et al., Evidence for immune system alterations in peripheral biological fluids in Parkinson's disease. Neurobiology of Disease, 2022. 170: p. 105744.
5Metta, V., et al., Gastrointestinal dysfunction in Parkinson’s disease: molecular pathology and implications of gut microbiome, probiotics, and fecal microbiota transplantation. Journal of Neurology, 2022. 269(3): p. 1154-1163.
6Konjevod, M., et al., Metabolomics analysis of microbiota-gut-brain axis in neurodegenerative and psychiatric diseases. Journal of Pharmaceutical and Biomedical Analysis, 2021. 194: p. 113681.
7Canfora, E.E., et al., Gut microbial metabolites in obesity, NAFLD and T2DM. Nature Reviews Endocrinology, 2019. 15(5): p. 261-273.
8Chen, S.-J., et al., Association of Fecal and Plasma Levels of Short-Chain Fatty Acids With Gut Microbiota and Clinical Severity in Patients With Parkinson Disease. Neurology, 2022. 98(8): p. e848.
9Sampson, T.R., et al., Gut Microbiota Regulate Motor Deficits and Neuroinflammation in a Model of Parkinson’s Disease. Cell, 2016. 167(6): p. 1469-1480.e12.
10Tran, S.M. and M.H. Mohajeri The Role of Gut Bacterial Metabolites in Brain Development, Aging and Disease. Nutrients, 2021. 13, DOI: 10.3390/nu13030732.
11Cirstea, M.S., et al., Microbiota Composition and Metabolism Are Associated With Gut Function in Parkinson's Disease. Movement Disorders, 2020. 35(7): p. 1208-1217.
12Shao, Y., et al., Comprehensive metabolic profiling of Parkinson’s disease by liquid chromatography-mass spectrometry. Molecular Neurodegeneration, 2021. 16(1): p. 4.
13Sankowski, B., et al., Higher cerebrospinal fluid to plasma ratio of p-cresol sulfate and indoxyl sulfate in patients with Parkinson’s disease. Clinica Chimica Acta, 2020. 501: p. 165-173.
14Gacias, M., et al., Microbiota-driven transcriptional changes in prefrontal cortex override genetic differences in social behavior. eLife, 2016. 5: p. e13442.
15Pascucci, T., et al. P-cresol Alters Brain Dopamine Metabolism and Exacerbates Autism-Like Behaviors in the BTBR Mouse. Brain Sciences, 2020. 10, DOI: 10.3390/brainsci10040233.
16Nemet, I., et al., A Cardiovascular Disease-Linked Gut Microbial Metabolite Acts via Adrenergic Receptors. Cell, 2020. 180(5): p. 862-877.e22.
17Yeh, Y.-C., et al., Indoxyl sulfate, not p-cresyl sulfate, is associated with cognitive impairment in early-stage chronic kidney disease. NeuroToxicology, 2016. 53: p. 148-152.
18Adesso, S., et al., Indoxyl Sulfate Affects Glial Function Increasing Oxidative Stress and Neuroinflammation in Chronic Kidney Disease: Interaction between Astrocytes and Microglia. 2017(1663-9812 (Print)).
19Dou, L., et al., The uremic solute indoxyl sulfate induces oxidative stress in endothelial cells. Journal of Thrombosis and Haemostasis, 2007. 5(6): p. 1302-1308.
20Guideline, I.H.T. validation of analytical procedures Q2 (R1).
21Vashist, S.K. and J.H.T. Luong, Chapter 4 - Bioanalytical Requirements and Regulatory Guidelines for Immunoassays, in Handbook of Immunoassay Technologies, S.K. Vashist and J.H.T. Luong, Editors. 2018, Academic Press. p. 81-95.
22F. T. Peters, J., et al. APPENDIX B To the GTFCh Guidelines for quality assurance in forensic-toxicological analyses Requirements for the validation of analytical methods. 2015.
23Hughes, A.J., et al., Accuracy of clinical diagnosis of idiopathic Parkinson's disease: a clinico-pathological study of 100 cases. Journal of Neurology, Neurosurgery, and Psychiatry, 1992. 55(3): p. 181.
24Zeng, Y., et al., Targeted metabolomics analysis of aromatic amino acids and their gut microbiota–host cometabolites in rat serum and urine by liquid chromatography coupled with tandem mass spectrometry. Journal of Separation Science, 2017. 40(16): p. 3221-3230.
25Tang, K., J.S. Page, and R.D. Smith, Charge competition and the linear dynamic range of detection in electrospray ionization mass spectrometry. Journal of the American Society for Mass Spectrometry, 2004. 15(10): p. 1416-1423.
26Tang, Y., et al., Analysis of two intestinal bacterial metabolites (trimethylamine N-oxide and phenylacetylglutamine) in human serum samples of patients with T2DM and AMI using a liquid chromatography tandem mass spectrometry method. Clinica Chimica Acta, 2022. 536: p. 162-168.
27Ntranos, A., et al., Bacterial neurotoxic metabolites in multiple sclerosis cerebrospinal fluid and plasma. Brain, 2022. 145(2): p. 569-583.
28Diémé, B., et al., Metabolomics Study of Urine in Autism Spectrum Disorders Using a Multiplatform Analytical Methodology. Journal of Proteome Research, 2015. 14(12): p. 5273-5282.
29Kuligowski, J., et al., Metabolomic Analysis of Gastric Cancer Progression within the Correa’s Cascade Using Ultraperformance Liquid Chromatography–Mass Spectrometry. Journal of Proteome Research, 2016. 15(8): p. 2729-2738.
30Roager, H.M., et al., Colonic transit time is related to bacterial metabolism and mucosal turnover in the gut. Nature Microbiology, 2016. 1(9): p. 16093.
31Liu, Y., et al., Gut Microbial Metabolites of Aromatic Amino Acids as Signals in Host-Microbe Interplay. Trends in Endocrinology & Metabolism, 2020. 31(11): p. 818-834.
32Dodd, D., et al., A gut bacterial pathway metabolizes aromatic amino acids into nine circulating metabolites. Nature, 2017. 551(7682): p. 648-652.
33Seguella, L., G. Sarnelli, and G. Esposito, Leaky gut, dysbiosis, and enteric glia activation: the trilogy behind the intestinal origin of Parkinson's disease. (1673-5374 (Print)).
34Blachier, F. and M. Andriamihaja, Effects of the l-tyrosine-derived bacterial metabolite p-cresol on colonic and peripheral cells. Amino Acids, 2022. 54(3): p. 325-338.
35Sirich, T.L., et al., Prominent Accumulation in Hemodialysis Patients of Solutes Normally Cleared by Tubular Secretion. Journal of the American Society of Nephrology, 2014. 25(3).
36Diether, N.E. and B.P. Willing Microbial Fermentation of Dietary Protein: An Important Factor in Diet–Microbe–Host Interaction. Microorganisms, 2019. 7, DOI: 10.3390/microorganisms7010019.
37Wong, X., et al., Deleterious Effect of p-Cresol on Human Colonic Epithelial Cells Prevented by Proanthocyanidin-Containing Polyphenol Extracts from Fruits and Proanthocyanidin Bacterial Metabolites. Journal of Agricultural and Food Chemistry, 2016. 64(18): p. 3574-3583.
38Stachulski, A.V., et al., A host–gut microbial amino acid co-metabolite, p-cresol glucuronide, promotes blood–brain barrier integrity in vivo. Tissue Barriers, 2023. 11(1): p. 2073175.
39Zhu, S., Y. Rong, and T.K.L. Kiang Effects of p-Cresol on Oxidative Stress, Glutathione Depletion, and Necrosis in HepaRG Cells: Comparisons to Other Uremic Toxins and the Role of p-Cresol Glucuronide Formation. Pharmaceutics, 2021. 13, DOI: 10.3390/pharmaceutics13060857.
40Falconi, C.A., et al., Uremic Toxins: An Alarming Danger Concerning the Cardiovascular System. Frontiers in Physiology, 2021. 12.
41Przedborski, S., Inflammation and Parkinson's disease pathogenesis. Movement Disorders, 2010. 25(S1): p. S55-S57.
42Dodiya, H.B., et al., Chronic stress-induced gut dysfunction exacerbates Parkinson's disease phenotype and pathology in a rotenone-induced mouse model of Parkinson's disease. Neurobiology of Disease, 2020. 135: p. 104352.
43Nicholson, J.K., et al., Host-Gut Microbiota Metabolic Interactions. Science, 2012. 336(6086): p. 1262-1267.
44Tremaroli, V. and F. Bäckhed, Functional interactions between the gut microbiota and host metabolism. Nature, 2012. 489(7415): p. 242-249.
45Belkaid, Y. and Timothy W. Hand, Role of the Microbiota in Immunity and Inflammation. Cell, 2014. 157(1): p. 121-141.
46Schmidt, T.S.B., J. Raes, and P. Bork, The Human Gut Microbiome: From Association to Modulation. Cell, 2018. 172(6): p. 1198-1215.
47Lee, J.-Y., R.M. Tsolis, and A.J. Bäumler, The microbiome and gut homeostasis. Science. 377(6601): p. eabp9960.
48Woo, V. and T. Alenghat, Epigenetic regulation by gut microbiota. Gut Microbes, 2022. 14(1): p. 2022407.
49Davila, A.-M., et al., Intestinal luminal nitrogen metabolism: Role of the gut microbiota and consequences for the host. Pharmacological Research, 2013. 68(1): p. 95-107.
50van de Wouw, M., et al., Microbiota-Gut-Brain Axis: Modulator of Host Metabolism and Appetite. The Journal of Nutrition, 2017. 147(5): p. 727-745.
51Zuo, T. and S.C. Ng, The Gut Microbiota in the Pathogenesis and Therapeutics of Inflammatory Bowel Disease. Frontiers in Microbiology, 2018. 9.
52Wang, Z. and Y. Zhao, Gut microbiota derived metabolites in cardiovascular health and disease. Protein & Cell, 2018. 9(5): p. 416-431.
53Quigley, E.M.M., Microbiota-Brain-Gut Axis and Neurodegenerative Diseases. Current Neurology and Neuroscience Reports, 2017. 17(12): p. 94.
54Vivarelli, S., et al. Gut Microbiota and Cancer: From Pathogenesis to Therapy. Cancers, 2019. 11, DOI: 10.3390/cancers11010038.
55Feng, Q., W.-D. Chen, and Y.-D. Wang, Gut Microbiota: An Integral Moderator in Health and Disease. Frontiers in Microbiology, 2018. 9.
56Gasaly, N., P. de Vos, and M.A. Hermoso, Impact of Bacterial Metabolites on Gut Barrier Function and Host Immunity: A Focus on Bacterial Metabolism and Its Relevance for Intestinal Inflammation. Frontiers in Immunology, 2021. 12.
57Kanemitsu, Y., et al., Comprehensive and semi-quantitative analysis of carboxyl-containing metabolites related to gut microbiota on chronic kidney disease using 2-picolylamine isotopic labeling LC-MS/MS. Scientific Reports, 2019. 9(1): p. 19075.
58Roager, H.M. and T.R. Licht, Microbial tryptophan catabolites in health and disease. Nature Communications, 2018. 9(1): p. 3294.
59Guzior, D.V. and R.A. Quinn, Review: microbial transformations of human bile acids. Microbiome, 2021. 9(1): p. 140.
60Hisamatsu, T., et al., Novel, Objective, Multivariate Biomarkers Composed of Plasma Amino Acid Profiles for the Diagnosis and Assessment of Inflammatory Bowel Disease. PLOS ONE, 2012. 7(1): p. e31131.
61Gupta, N.K., et al., Serum Analysis of Tryptophan Catabolism Pathway: Correlation With Crohn's Disease Activity. Inflammatory Bowel Diseases, 2012. 18(7): p. 1214-1220.
62Jansson, J., et al., Metabolomics Reveals Metabolic Biomarkers of Crohn's Disease. PLOS ONE, 2009. 4(7): p. e6386.
63Rosas, H.D., et al., A systems-level “misunderstanding”: the plasma metabolome in Huntington's disease. Annals of Clinical and Translational Neurology, 2015. 2(7): p. 756-768.
64Sehgal, R., et al. Indole-3-Propionic Acid, a Gut-Derived Tryptophan Metabolite, Associates with Hepatic Fibrosis. Nutrients, 2021. 13, DOI: 10.3390/nu13103509.
65Marksteiner, J., et al., Bile acid quantification of 20 plasma metabolites identifies lithocholic acid as a putative biomarker in Alzheimer’s disease. Metabolomics, 2017. 14(1): p. 1.
66Kamano, T., et al., Ratio of primary and secondary bile acids in feces: Possible marker for colorectal cancer? Diseases of the Colon & Rectum, 1999. 42(5).
67Kakiyama, G., et al., Modulation of the fecal bile acid profile by gut microbiota in cirrhosis. Journal of Hepatology, 2013. 58(5): p. 949-955.
68Xu, H., et al., Gut microbiota-derived metabolites in inflammatory diseases based on targeted metabolomics. Frontiers in Pharmacology, 2022. 13.
69Shafaei, A., et al., Extraction and quantitative determination of bile acids in feces. Analytica Chimica Acta, 2021. 1150: p. 338224.
70Szu-Ju, C., et al., Association of Fecal and Plasma Levels of Short-Chain Fatty Acids With Gut Microbiota and Clinical Severity in Patients With Parkinson Disease. Neurology, 2022. 98(8): p. e848.
71Karu, N., et al., A review on human fecal metabolomics: Methods, applications and the human fecal metabolome database. Analytica Chimica Acta, 2018. 1030: p. 1-24.
72Kakiyama, G., et al., A simple and accurate HPLC method for fecal bile acid profile in healthy and cirrhotic subjects: validation by GC-MS and LC-MS[S]. Journal of Lipid Research, 2014. 55(5): p. 978-990.
73Alemán, J.O., et al., Fecal microbiota and bile acid interactions with systemic and adipose tissue metabolism in diet-induced weight loss of obese postmenopausal women. Journal of Translational Medicine, 2018. 16(1): p. 244.
74Reiter, S., et al., Development of a Highly Sensitive Ultra-High-Performance Liquid Chromatography Coupled to Electrospray Ionization Tandem Mass Spectrometry Quantitation Method for Fecal Bile Acids and Application on Crohn’s Disease Studies. Journal of Agricultural and Food Chemistry, 2021. 69(17): p. 5238-5251.
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