Gut microbiota-related metabolome analysis based on chromatography-mass spectrometry

Operationalizing Team Science at the Academic Cancer Center Network to Unveil the Structure and Function of the Gut Microbiome

Oncologists increasingly recognize the microbiome as an important facilitator of health as well as a contributor to disease, including, specifically, cancer. Our knowledge of the etiologies, mechanisms, and modulation of microbiome states that ameliorate or promote cancer continues to evolve. The progressive refinement and adoption of "omic" technologies (genomics, transcriptomics, proteomics, and metabolomics) and utilization of advanced computational methods accelerate this evolution. The academic cancer center network, with its immediate access to extensive, multidisciplinary expertise and scientific resources, has the potential to catalyze microbiome research. Here, we review our current understanding of the role of the gut microbiome in cancer prevention, predisposition, and response to therapy. We underscore the promise of operationalizing the academic cancer center network to uncover the structure and function of the gut microbiome; we highlight the unique microbiome-related expert resources available at the City of Hope of Comprehensive Cancer Center as an example of the potential of team science to achieve novel scientific and clinical discovery.

Ultrasensitive Determination of Amino Acids in Single Cells by Chemical Isotope Labeling with Liquid Chromatography Mass Spectrometry Analysis

Amino acids play multiple critical roles in the regulation of various metabolic pathways and physiological processes in living organisms. Mass spectrometry (MS) has become the most pioneering platform for amino acid analysis. However, the simultaneous and sensitive determination of amino acids is still challenging because of their structural similarity and broad ranges of concentrations. To this end, a pair of isotope labeling reagents, d0/d3-2-((diazomethyl)phenyl)(9-methyl-1,3,4,9-tetrahydro-2H-pyrido[3,4-b]indol-2-yl) methanone (DMPI/d3-DMPI), were applied to label amino acid metabolites. The diazo groups on the pair of isotopomers (DMPI/d3-DMPI) can specifically react with the carboxyl groups on the amino acids. The results showed that the retention on reversed-phase column were enhanced and the detection sensitivities of 19 amino acids were increased benefiting from DMPI labeling strategy that transfers the hydrophobic indole heterocycle group of DMPI to the hydrophilic compounds of amino acids. The obtained limits of detection (LODs) of amino acids were in the range of 0.002-0.082 fmol. With this established method, we achieved the sensitive detection of amino acids in a single HUVE cell. Meanwhile, we found that the contents of amino acids in the serum of premature neonates were higher compared to normal neonates. Overall, this developed method provides great support of detection tool for the clinical metabolomic study of amino acids and the investigation of dynamic changes of amino acid metabolism in single cells.

Discovery-Based Analysis for Chemical Trends in Chromatographic Data Sets Using Alteration Analysis and Two-Dimensional Correlation Analysis

Alteration analysis (ALA), an unsupervised chemometric technique, was evaluated for its ability to discover statistically significant trends in chromatographic data sets. Recently introduced, adoption of ALA has been limited due to uncertainty regarding its sensitivity to minor changes, and there are no rules implementing ALA especially for multivariate data sets such as liquid or gas chromatography coupled to mass spectrometry. Using in-silico data sets, ALA limits of discovery for various signal-to-noises (S/Ns), rates of change across samples, and a number of samples were assessed. For 10 samples, ALA discovered changes of ∼2% across each sample for low S/Ns (15-50), ∼1% change across each sample for moderate S/Ns (65-200), and as little as a 0.1% change at high S/Ns. ALA was also evaluated for unresolved chromatographic peaks, detecting changes down to a resolution of 0.01. In tandem with ALA, two-dimensional correlation analysis (2DCOR), a nonquantitative technique, was employed post-ALA processing to provide unique insights into the relationships between the chemical changes across simulated data sets. Finally, ALA and 2DCOR were applied to the pyrolysis gas chromatography-mass spectrometry (pyGC-MS) of Kraton G1650, a styrene-ethylene-butylene-stryrene (SEBS) polymer, pyrolyzed at temperatures ranging from 350 to 700 °C. A total of 523 statistically significant chemical compounds were discovered. The ALA output was fed into 2DCOR, and a subset of the data was evaluated to understand the relationship between the chemical changes of four selected statistically significant compounds.

Simultaneous Quantification of Carboxylate Enantiomers in Multiple Human Matrices with the Hydrazide-Assisted Ultrahigh-Performance Liquid Chromatography Coupled with Tandem Mass Spectrometry

Many chiral carboxylic acids with α-amino, α-hydroxyl, and α-methyl groups are concurrently present in mammals establishing unique molecular phenotypes and multiple biological functions, especially host-microbiota symbiotic interactions. Their chirality-resolved simultaneous quantification is essential to reveal the biochemical details of physiology and pathophysiology, though challenging with their low abundances in some biological matrices and difficulty in enantiomer resolution. Here, we developed a method of the chirality-resolved metabolomics with sensitivity-enhanced quantitation via probe-promotion (Met-SeqPro) for analyzing these chiral carboxylic acids. We designed and synthesized a hydrazide-based novel chiral probe, (S)-benzoyl-proline-hydrazide (SBPH), to convert carboxylic acids into amide diastereomers to enhance their retention and chiral resolution on common C18 columns. Using the d5-SBPH-labeled enantiomers as internal standards, we then developed an optimized ultrahigh-performance liquid chromatography with tandem mass spectrometry (UHPLC-MS/MS) method for simultaneous quantification of 60 enantiomers of 30 chiral carboxylic acids in one run. This enantiomer-resolved method showed excellent sensitivity (LOD < 4 fmol-on-column), linearity (R2 > 0.992), precision (CV < 15%), accuracy (|RE| < 20%), and recovery (80-120%) in multiple biological matrices. With the method, we then quantified 60 chiral carboxylic acids in human urine, plasma, feces, and A549 cells to define their metabolomic phenotypes. This provides basic data for human phenomics and a promising tool for investigating the mammal-microbiome symbiotic interactions.

Comorbidities confound metabolomics studies of human disease

The co-occurrence of multiple chronic conditions, termed multimorbidity, presents an expanding global health challenge, demanding effective diagnostics and treatment strategies. Chronic ailments such as obesity, diabetes, and cardiovascular diseases have been linked to metabolites interacting between the host and microbiota. In this study, we investigated the impact of co-existing conditions on risk estimations for 1375 plasma metabolites in 919 individuals from population-based Estonian Biobank cohort using liquid chromatography mass spectrometry (LC-MS) method. We leveraged annually linked national electronic health records (EHRs) data to delineate comorbidities in incident cases and controls for the 14 common chronic conditions. Among the 254 associations observed across 13 chronic conditions, we primarily identified disease-specific risk factors (92%, 217/235), with most predictors (93%, 219/235) found to be related to the gut microbiome upon cross-referencing recent literature data. Accounting for comorbidities led to a reduction of common metabolite predictors across various conditions. In conclusion, our study underscores the potential of utilizing biobank-linked retrospective and prospective EHRs for the disease-specific profiling of diverse multifactorial chronic conditions.

The Role of Microbiota-Related Co-Metabolites in MASLD Progression: A Narrative Review

Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a growing health concern due to its increasing prevalence worldwide. Metabolic homeostasis encompasses the stable internal conditions vital for efficient metabolism. This equilibrium extends to the intestinal microbiota, whose metabolic activities profoundly influence overall metabolic balance and organ health. The metabolites derived from the gut microbiota metabolism can be defined as microbiota-related co-metabolites. They serve as mediators between the gut microbiota and the host, influencing various physiological processes. The recent redefinition of the term MASLD has highlighted the metabolic dysfunction that characterize the disease. Metabolic dysfunction encompasses a spectrum of abnormalities, including impaired glucose regulation, dyslipidemia, mitochondrial dysfunction, inflammation, and accumulation of toxic byproducts. In addition, MASLD progression has been linked to dysregulation in the gut microbiota and associated co-metabolites. Short-chain fatty acids (SCFAs), hippurate, indole derivatives, branched-chain amino acids (BCAAs), and bile acids (BAs) are among the key co-metabolites implicated in MASLD progression. In this review, we will unravel the relationship between the microbiota-related metabolites which have been associated with MASLD and that could play an important role for developing effective therapeutic interventions for MASLD and related metabolic disorders.

Metabolomic differences between non-hydrothermal treated water-soluble (WSPs) and hydrothermally treated water-insoluble (WIPs) Maitake polysaccharides fermented by Lactobacillus acidophilus and L. plantarum

Bacterial Metabolite through a fermentation process is a growing trend and a promising alternative for use as functional components. Non-hydrothermal water-soluble (WSPs) and hydrothermally treated water-insoluble (WIPs) Maitake polysaccharides were fermented with Lactobacillus acidophilus (LA) and Lactobacillus plantarum (LP). Chemical composition analysis indicated that Maitake polysaccharides contained 58.22 ± 1.35 % total sugar and 31.46 % β-glucan, essential for metabolites production. 6-glucanase was used to degrade the WIPs, and hydrothermally treated WIP fibers exhibited smooth microstructure. Hence, the LA and LP bacteria investigated the potential fermented metabolic activities and differences between WSPs(Sp1)and WIP(Sp3) Maitake polysaccharides using LC-MS, and 887 metabolites were identified. Using Venn, Partial least squares discriminant analysis (PLS-DA), VIP Metabolites, and other multivariate statistical analysis methods, metabolites were expressed differently in all samples. Due to hydrothermal processing, WIP induced the highest growth of LA and LP, with an abundance of isocitrate metabolites. Furthermore, 50 metabolite correlations were identified, leading to the classification of 6 distinct metabolic groups. Thus, the study offers the initial comprehensive analysis of metabolites in Lactobacillus-fermented Maitake polysaccharides, aiding in understanding its metabolic interactions and facilitating progress in food engineering research.

Profiling Analysis of Tryptophan Metabolites in the Urine of Patients with Parkinson's Disease Using LC-MS/MS

Although Parkinson's disease (PD) is a representative neurodegenerative disorder and shows characteristic motor impediments, the pathophysiological mechanisms and treatment targets for PD have not yet been clearly identified. Since several tryptophan metabolites produced by gut microbiota could pass the blood-brain barrier and, furthermore, might influence the central nervous system, tryptophan metabolites within the indole, kynurenine, and serotonin metabolic pathways might be the most potent targets for PD development. Furthermore, most metabolites are circulated via the blood, play roles in and/or are metabolized via the host organs, and finally are excreted into the urine. Therefore, profiling the overall tryptophan metabolic pathways in urine samples of patients with PD is important to understanding the pathological mechanisms, finding biomarkers, and discovering therapeutic targets for PD. However, the development of profiling analysis based on tryptophan metabolism pathways in human urine samples is still challenging due to the wide physiological ranges, the varied signal response, and the structural diversity of tryptophan metabolites in complicated urine matrices. In this study, an LC-MS/MS method was developed to profile 21 tryptophan metabolites within the indole, kynurenine, and serotonin metabolic pathways in human urine samples using ion-pairing chromatography and multiple reaction monitoring determination. The developed method was successfully applied to urine samples of PD patients (n = 41) and controls (n = 20). Further, we investigated aberrant metabolites to find biomarkers for PD development and therapeutic targets based on the quantitative results. Unfortunately, most tryptophan metabolites in the urine samples did not present significant differences between control and PD patients, except for indole-3-acetic acid. Nonetheless, indole-3-acetic acid was reported for the first time for its aberrant urinary levels in PD patients and tentatively selected as a potential biomarker for PD. This study provides accurate quantitative results for 21 tryptophan metabolites in biological samples and will be helpful in revealing the pathological mechanisms of PD development, discovering biomarkers for PD, and further providing therapeutic targets for various PD symptoms. In the near future, to further investigate the relationship between gut microbial metabolites and PD, we will employ studies on microbial metabolites using plasma and stool samples from control and PD patients.

Mass spectrometry-based analysis of gut microbial metabolites of aromatic amino acids

Small molecules derived from gut microbiota have been increasingly investigated to better understand the functional roles of the human gut microbiome. Microbial metabolites of aromatic amino acids (AAA) have been linked to many diseases, such as metabolic disorders, chronic kidney diseases, inflammatory bowel disease, diabetes, and cancer. Important microbial AAA metabolites are often discovered via global metabolite profiling of biological specimens collected from humans or animal models. Subsequent metabolite identity confirmation and absolute quantification using targeted analysis enable comparisons across different studies, which can lead to the establishment of threshold concentrations of potential metabolite biomarkers. Owing to their excellent selectivity and sensitivity, hyphenated mass spectrometry (MS) techniques are often employed to identify and quantify AAA metabolites in various biological matrices. Here, we summarize the developments over the past five years in MS-based methodology for analyzing gut microbiota-derived AAA. Sample preparation, method validation, analytical performance, and statistical methods for correlation analysis are discussed, along with future perspectives.

Recent Review on Selected Xenobiotics and Their Impacts on Gut Microbiome and Metabolome

As it is well known, the gut is one of the primary sites in any host for xenobiotics, and the many microbial metabolites responsible for the interactions between the gut microbiome and the host. However, there is a growing concern about the negative impacts on human health induced by toxic xenobiotics. Metabolomics, broadly including lipidomics, is an emerging approach to studying thousands of metabolites in parallel. In this review, we summarized recent advancements in mass spectrometry (MS) technologies in metabolomics. In addition, we reviewed recent applications of MS-based metabolomics for the investigation of toxic effects of xenobiotics on microbial and host metabolism. It was demonstrated that metabolomics, gut microbiome profiling, and their combination have a high potential to identify metabolic and microbial markers of xenobiotic exposure and determine its mechanism. Further, there is increasing evidence supporting that reprogramming the gut microbiome could be a promising approach to the intervention of xenobiotic toxicity.

Determination of short-chain fatty acids as putative biomarkers of cancer diseases by modern analytical strategies and tools: a review

Short-chain fatty acids (SCFAs) are the main metabolites produced by bacterial fermentation of non-digestible carbohydrates in the gastrointestinal tract. They can be seen as the major flow of carbon from the diet, through the microbiome to the host. SCFAs have been reported as important molecules responsible for the regulation of intestinal homeostasis. Moreover, these molecules have a significant impact on the immune system and are able to affect inflammation, cardiovascular diseases, diabetes type II, or oncological diseases. For this purpose, SCFAs could be used as putative biomarkers of various diseases, including cancer. A potential diagnostic value may be offered by analyzing SCFAs with the use of advanced analytical approaches such as gas chromatography (GC), liquid chromatography (LC), or capillary electrophoresis (CE) coupled with mass spectrometry (MS). The presented review summarizes the importance of analyzing SCFAs from clinical and analytical perspective. Current advances in the analysis of SCFAs focused on sample pretreatment, separation strategy, and detection methods are highlighted. Additionally, it also shows potential areas for the development of future diagnostic tools in oncology and other varieties of diseases based on targeted metabolite profiling.

Characterization of Bile Acid Isomers and the Implementation of High-Resolution Demultiplexing with Ion Mobility-Mass Spectrometry

Bile acids (BAs) are a complex suite of clinically relevant metabolites that include many isomers. Liquid chromatography coupled to mass spectrometry (LC-MS) is an increasingly popular technique due to its high specificity and sensitivity; nonetheless, acquisition times are generally 10-20 min, and isomers are not always resolved. In this study, the application of ion mobility (IM) spectrometry coupled to MS was investigated to separate, characterize, and measure BAs. A subset of 16 BAs was studied, including three groups of isomers belonging to unconjugated, glycine-conjugated, and taurine-conjugated BA classes. A variety of strategies were explored to increase BA isomer separation such as changing the drift gas, measuring different ionic species (i.e., multimers and cationized species), and enhancing the instrumental resolving power. In general, Ar, N₂, and CO₂ provided the best peak shape, resolving power (R_p), and separation, especially CO₂; He and SF₆ were less preferable. Furthermore, measuring dimers versus monomers improved isomer separation due to enhanced gas-phase structural differences. A variety of cation adducts other than sodium were characterized. Mobility arrival times and isomer separation were affected by the choice of adduct, which was shown to be used to target certain BAs. Finally, a novel workflow that involves high-resolution demultiplexing in combination with dipivaloylmethane ion-neutral clusters was implemented to improve R_p dramatically. A maximum R_p increase was observed with lower IM field strengths to obtain longer drift times, increasing R_p from 52 to 187. A combination of these separation enhancement strategies demonstrates great potential for rapid BA analysis.

Rapid and sustainable HPLC method for the determination of uremic toxins in human plasma samples

Protein-bound uremic toxins, mainly indoxyl sulfate (3-INDS), p-cresol sulfate (pCS), and indole-3-acetic acid (3-IAA) but also phenol (Pol) and p-cresol (pC), are progressively accumulated during chronic kidney disease (CKD). Their accurate measurement in biomatrices is demanded for timely diagnosis and adoption of appropriate therapeutic measures. Multianalyte methods allowing the establishment of a uremic metabolite profile are still missing. Hence, the aim of this work was to develop a rapid and sensitive method based on high-performance liquid chromatography with fluorescence detection for the simultaneous quantification of Pol, 3-IAA, pC, 3-INDS, and pCS in human plasma. Separation was attained in 12 min, using a monolithic C18 column and isocratic elution with acetonitrile and phosphate buffer containing an ion-pairing reagent, at a flow rate of 2 mL min^-1. Standards were prepared in plasma and quantification was performed using the background subtraction approach. LOQ values were ≤ 0.2 µg mL^-1 for all analytes except for pCS (LOQ of 2 µg mL^-1). The method proved to be accurate (93.5-112%) and precise (CV ≤ 14.3%). The multianalyte application of the method, associated to a reduced sample volume (50 µL), a less toxic internal standard (eugenol) in comparison to the previously applied 2,6-dimethylphenol and 4-ethylphenol, and a green extraction solvent (ethanol), resulted in the AGREE score of 0.62 which is in line with the recent trend of green and sustainable analytical chemistry. The validated method was successfully applied to the analysis of plasma samples from control subjects exhibiting normal levels of uremic toxins and CKD patients presenting significantly higher levels of 3-IAA, pC, 3-INDS, and pCS that can be further investigated as biomarkers of disease progression.

Sample preparation and chromatographic methods for the determination of protein-bound uremic retention solutes in human biological samples: An overview

Protein-bound uremic retention solutes, such as indole-3-acetic acid, indoxyl sulfate, p-cresol and p-cresol sulfate, are associated with the development of several pathologies, namely renal, cardiovascular, and bone toxicities, due to their potential accumulation in the human body, thus requiring analytical methods for monitoring and evaluation. The present review addresses conventional and advanced sample treatment procedures for sample handling and the chromatographic analytical methods developed for quantification of these compounds in different biological fluids, with particular focus on plasma, serum, and urine. The sample preparation and chromatographic methods coupled to different detection systems are critically discussed, focusing on the different steps involved for sample treatment, namely elimination of interfering compounds present in the sample matrix, and the evaluation of their environmental impact through the AGREEprep tool. There is a clear trend for the application of liquid-chromatography coupled to tandem mass spectrometry, which requires protein precipitation, solid-phase extraction and/or dilution prior to analysis of biological samples. Furthermore, from a sustainability point of view, miniaturized methods resorting to microplate devices are highly recommended.

Quantification of Gut Microbiota Dysbiosis-Related Organic Acids in Human Urine Using LC-MS/MS

Urine organic acid contains water-soluble metabolites and/or metabolites—derived from sugars, amino acids, lipids, vitamins, and drugs—which can reveal a human’s physiological condition. These urine organic acids—hippuric acid, benzoic acid, phenylacetic acid, phenylpropionic acid, 4-hydroxybenzoic acid, 4-hydroxyphenyl acetic acid, 3-hydroxyphenylpropionic acid, 3,4-dihydroxyphenyl propionic acid, and 3-indoleacetic acid—were the eligible candidates for the dysbiosis of gut microbiota. The aim of this proposal was to develop and to validate a liquid chromatography−tandem mass spectrometry (LC-MS/MS) bioanalysis method for the nine organic acids in human urine. Stable-labeled isotope standard (creatinine-d3) and acetonitrile were added to the urine sample. The supernatant was diluted with deionized water and injected into LC-MS/MS. This method was validated with high selectivity for the urine sample, a low limit of quantification (10−40 ng/mL), good linearity (r > 0.995), high accuracy (85.8−109.7%), and high precision (1.4−13.3%). This method simultaneously analyzed creatinine in urine, which calibrates metabolic rate between different individuals. Validation has been completed for this method; as such, it could possibly be applied to the study of gut microbiota clinically.