Dysregulated bile acid (BA) metabolism has been linked to steatosis, inflammation, and fibrosis in nonalcoholic fatty liver disease (NAFLD).

Background Bile acids (BAs) are signaling molecules that regulate numerous metabolic processes in metabolic dysfunction-associated (MAFLD) and chronic kidney disease (CKD). Whether BAs are also associated with early abnormalities in renal function in MAFLD is uncertain. Methods We quantitatively measured plasma BA concentrations in biopsy-proven MAFLD patients with or without abnormal albuminuria (defined as albumin-to-creatinine ratio ≥ 30 mg/g) and in healthy controls, by using ultraperformance liquid chromatography coupled to tandem mass spectrometry. Results Plasma BA profiles (conjugated BAs, glycine-conjugated BAs, glycine-conjugated primary BAs, total conjugated primary BAs, and glycine-conjugated primary BAs) were up-regulated in MAFLD patients with abnormal albuminuria compared to their counterparts with normal albuminuria and healthy controls. In particular, we identified a distinct individual BA, i.e., norcholic acid (NorCA) that was markedly upregulated in MAFLD patients with abnormal albuminuria, and that was also positively correlated with albuminuria. Moreover, the combination of NorCA, tauro-deoxycholic acid, tauro-lithocholic acid and cholic acid, improved identification of abnormal albuminuria in MAFLD patients in a predictive model, that also included diabetes, hypertension, body mass index, and serum alanine aminotransferase levels (AUC = 0.80, 95%CI 0.740–0.863). Conclusion BA biomarkers are increased in patients with MAFLD and abnormal albuminuria and further investigation of their role in renal function is warranted.

Background: Adaptive support ventilation (ASV) is an intelligent mode of mechanical ventilation protocol which uses a closed-loop control between breaths. The algorithm states that for a given level of alveolar ventilation, there is a particular respiratory rate and tidal volume which achieve a lower work of breathing. The mode allows the clinician to set a desired minute ventilation percentage (MV%) while the ventilator automatically selects the target ventilatory pattern base on these inputs and feedback from the ventilator monitoring system. The goal is to minimize the work of breathing and reduce complications by allowing the ventilator to adjust the breath delivery taking into account the patient’s respiratory mechanics (Resistance, and Compliance). In this study we examine the effect of patients’ respiratory effort on target tidal volume (VT) and Minute Ventilation (V̇e) during ASV using breathing simulator. Methods: A bench study was performed by using the ASL 5000 breathing simulator to compare the target ventilator to actual VT and V̇e value in simulated patients with various level of respiratory effort during ASV on the Hamilton G5 ventilator. The clinical scenario involves simulated adult male with IBW 70kg and normal lung mechanics: respiratory compliance of 70 mL/cm H2O, and airway resistance of 9 cm H2O/L/s. Simulated patients were subjected to five different level of muscle pressure (Pmus): 0 (Passive), -5, -10, -15, -25 (Active) cm H2O at a set respiratory rate of 10 (below targeted VT) set at three different levels of minute ventilation goals: 100%, 200%, and 300%, with a PEEP of 5 cm H2O. Fifty breaths were analyzed in every experiment. Means and standard deviations (SD) of variables were calculated. One way analysis of variants was done to compare the values. Pearson correlation coefficient test was used to calculate the correlation between the respiratory effort and the VT, V̇e, and peak inspiratory pressure (PIP). Results: The targeted VT and V̇e were not significant in the passive patient when no effort was present, however were significantly higher in the active states at all levels of Pmus on the 100%, 200% and the 300 MV%. The VT and V̇e increase correlated with the muscle effort in the 100 and 200 MV% but did not in the 300%. Conclusions: Higher inspiratory efforts resulted in significantly higher VT and V̇e than targeted ones. Estimating patients’ effort is important during setting ASV. Keywords: Mechanical ventilation, ASV, InteliVent, Pmus, tidal volume, percent minute ventilation

BACKGROUND:Heart failure with midrange ejection fraction (HFmrEF) has been recently acknowledged as a separate phenotype, but metabolomics evaluation of this subtype remains largely unexamined. METHODS:A quantitative metabolomics study on amino acids and acylcarnitines was performed to characterize different states of heart failure (HF) in 628 participants. Both multivariate orthogonal partial least squares- discriminant analysis and univariate Mann-Whitney U test were used to explore reliable metabolic profiles associated with different HF states. The resulting metabolites were further refined to obtain diagnostic metabolite scores (DMSs) with the use of ordinal logistic regression. Lasso-penalized regression was applied to produce a survival-associated prognostic metabolite score (PMS). The Cox proportional hazards model, Kaplan-Meier curves, and time-dependent receiver operating characteristics were used for a comprehensive assessment of prognostic value using PMS versus traditional clinical biomarkers. RESULTS:The optimized models identified a panel of 15 differential metabolites that were shared across different HF states, whereas some metabolites were associated with a specific state. PMS consisting of 9 metabolites demonstrated an appreciably better prognostic value (hazard ratio [HR] 1.62, 95% confidence interval [CI] 1.25-2.1) vs the natural logarithm of N-terminal pro-B-type natriuretic peptide (Ln[NT-proBNP]; HR 1.23, 95% CI 0.94-1.61; P < 0.001). The overall area under the receiver operating characteristic curve value of PMS was superior to that of Ln(NT-proBNP) in risk prediction for patients with HFmrEF and HF with reduced ejection fraction (HFrEF) subtypes (P < 0.001). CONCLUSIONS:Targeted metabolomics has provided a novel understanding of the molecular mechanism underlying HF. Both DMS and PMS clearly demonstrated HFmrEF as a distinct phenotype between a mild HF with preserved ejection fraction state and a severe HFrEF state. PMS exhibited superior prognostic value than Ln(NT-proBNP). Further investigation is needed with independent large-scale validation.

Additional file 17:Table S6. Untargeted metabolomic characteristics of human serum sample in this study. Metabolites in yellow are the identified differential metabolites in this study (P_value <0.05 & VIP >1).

Background Gut microbiome alterations are closely related to human health and linked to a variety of diseases. Although great efforts have been made to understand the risk factors for multiple myeloma (MM), little is known about the role of the gut microbiome and alterations of its metabolic functions in the development of MM. Results Here, in a cohort of newly diagnosed patients with MM and healthy controls (HCs), significant differences in metagenomic composition were discovered, for the first time, with higher bacterial diversity in MM. Specifically, nitrogen-recycling bacteria such as Klebsiella and Streptococcus were significantly enriched in MM. Also, the bacteria enriched in MM were significantly correlated with the host metabolome, suggesting strong metabolic interactions between microbes and the host. In addition, the MM-enriched bacteria likely result from the regulation of urea nitrogen accumulated during MM progression. Furthermore, by performing fecal microbiota transplantation (FMT) into 5TGM1 mice, we proposed a mechanistic explanation for the interaction between MM-enriched bacteria and MM progression via recycling urea nitrogen. Further experiments validated that Klebsiella pneumoniae promoted MM progression via de novo synthesis of glutamine in mice and that the mice fed with glutamine-deficient diet exhibited slower MM progression. Conclusions Overall, our findings unveil a novel function of the altered gut microbiome in accelerating the malignant progression of MM and open new avenues for novel treatment strategies via manipulation of the intestinal microbiota of MM patients.

It was recently disclosed that CYP3A is responsible for the tertiary stereoselective oxidations of deoxycholic acid (DCA), which becomes a continuum mechanism of the host-gut microbial cometabolism of bile acids (BAs) in humans. This work aims to investigate the species differences of BA redox metabolism and clarify whether the tertiary metabolism of DCA is a conserved pathway in preclinical animals. With quantitative determination of the total unconjugated BAs in urine and fecal samples of humans, dogs, rats, and mice, it was confirmed that the tertiary oxidized metabolites of DCA were found in all tested animals, whereas DCA and its oxidized metabolites disappeared in germ-free mice. The in vitro metabolism data of DCA and the other unconjugated BAs in liver microsomes of humans, monkeys, dogs, rats, and mice showed consistencies with the BA-profiling data, confirming that the tertiary oxidation of DCA is a conserved pathway. In liver microsomes of all tested animals, however, the oxidation activities toward DCA were far below the murine-specific 6β-oxidation activities toward chenodeoxycholic acid (CDCA), ursodeoxycholic acid, and lithocholic acid (LCA), and 7-oxidation activities toward murideoxycholic acid and hyodeoxycholic acid came from the 6-hydroxylation of LCA. These findings provided further explanations for why murine animals have significantly enhanced downstream metabolism of CDCA compared with humans. In conclusion, the species differences of BA redox metabolism disclosed in this work will be useful for the interspecies extrapolation of BA biology and toxicology in translational researches. SIGNIFICANCE STATEMENT: It is important to understand the species differences of bile acid metabolism when deciphering biological and hepatotoxicology findings from preclinical studies. However, the species differences of tertiary bile acids are poorly understood compared with primary and secondary bile acids. This work confirms that the tertiary oxidation of deoxycholic acid is conserved among preclinical animals and provides deeper understanding of how and why the downstream metabolism of chenodeoxycholic acid dominates that of cholic acid in murine animals compared with humans.

This work aims to investigate how the bile acid metabolism of newborns differs from that of adults along the axis of primary, secondary, and tertiary bile acids (BAs). The total unconjugated BA profiles were quantitatively determined by enzyme digestion techniques in urine of 21 newborns born by cesarean section, 29 healthy parturient women, 30 healthy males, and 28 healthy nonpregnant females. As expected, because of a lack of developed gut microbiota, newborns exhibited poor metabolism of secondary BAs. Accordingly, the tertiary BAs contributed limitedly to the urinary excretion of BAs in newborns despite their tertiary-to-secondary ratios significantly increasing. As a result, the primary BAs of newborns underwent extensive oxidative metabolism, resulting in elevated urinary levels of some fetal-specific BAs, including 3-dehydroCA, 3β,7α,12α-trihydroxy-5β-cholan-24-oic acid, 3α,12-oxo-hydroxy-5β-cholan-24-oic acid, and nine tetrahydroxy-cholan-24-oic acids (Tetra-BAs). Parturient women had significantly elevated urinary levels of tertiary BAs and fetal-specific BAs compared with female control, indicating that they may be excreted into amniotic fluid for maternal disposition. An in vitro metabolism assay in infant liver microsomes showed that four Tetra-BAs and 3-dehydroCA were hydroxylated metabolites of cholate, glycocholate, and particularly taurocholate. However, the recombinant cytochrome P450 enzyme assay found that the fetal-specific CYP3A7 did not contribute to these oxidation metabolisms as much as expected compared with CYP3A4. In conclusion, newborns show a BA metabolism pattern predominated by primary BA oxidations due to immaturity of secondary BA metabolism. Translational studies following this finding may bring new ideas and strategies for both pediatric pharmacology and diagnosis and treatment of perinatal cholestasis-associated diseases. SIGNIFICANCE STATEMENT: The prenatal BA disposition is different from adults because of a lack of gut microbiota. However, how the BA metabolism of newborns differs from that of adults along the axis of primary, secondary, and tertiary BAs remains poorly defined. This work demonstrated that the urinary BA profiles of newborns born by cesarean section are characterized by oxidative metabolism of primary BAs, in which the fetal-specific CYP3A7 plays a limited role in the downstream oxidation metabolism of cholate.

ObjectiveBile acids (BAs) are important molecules in the progression of nonalcoholic fatty liver disease. This study aimed to investigate BA profile alterations in Chinese nonalcoholic steatohepatitis (NASH) patients.MethodsBA profiles in serum and liver tissues were determined by ultraperformance liquid chromatography coupled to tandem mass spectrometry in patients from two different clinical centers.ResultsA total of 134 participants were enrolled in this study to serve as the training (n = 87) and validation (n = 47) cohorts. The ratio of circulating conjugated chenodeoxycholic acids to muricholic acids (P = 0.001) was elevated from healthy controls to non‐NASH individuals to NASH individuals in a stepwise manner in the training cohort and was positively associated with the histological severity of NASH: steatosis (R2 = 0.12), lobular inflammation (R2 = 0.12), ballooning (R2 = 0.11), and fibrosis stage (R2 = 0.18). The ratio was elevated in the validation cohort of NASH patients (P < 0.001), and it was able to predict NASH (area under the receiver operating characteristic curve: 75%) and significant fibrosis (area under the receiver operating characteristic curve: 71%) in these two cohorts. Moreover, this elevated ratio and impaired farnesoid X receptor signaling were found in the NASH liver.ConclusionsAltered BA profile in NASH is closely associated with the severity of liver lesions, and it has the potential for predicting NASH development.

The gut microbiota modifies endogenous primary bile acids (BAs) to produce exogenous secondary BAs, which may be further metabolized by cytochrome P450 enzymes (P450s). Our primary aim was to examine how the host adapts to the stress of microbe-derived secondary BAs by P450-mediated oxidative modifications on the steroid nucleus. Five unconjugated tri-hydroxyl BAs that were structurally and/or biologically associated with deoxycholate (DCA) were determined in human biologic samples by liquid chromatography-tandem mass spectrometry in combination with enzyme-digestion techniques. They were identified as DCA-19-ol, DCA-6β-ol, DCA-5β-ol, DCA-6α-ol, DCA-1β-ol, and DCA-4β-ol based on matching in-laboratory synthesized standards. Metabolic inhibition assays in human liver microsomes and recombinant P450 assays revealed that CYP3A4 and CYP3A7 were responsible for the regioselective oxidations of both DCA and its conjugated forms, glycodeoxycholate (GDCA) and taurodeoxycholate (TDCA). The modification of secondary BAs to tertiary BAs defines a host liver (primary BAs)-gut microbiota (secondary BAs)-host liver (tertiary BAs) axis. The regioselective oxidations of DCA, GDCA, and TDCA by CYP3A4 and CYP3A7 may help eliminate host-toxic DCA species. The 19- and 4β-hydroxylation of DCA species demonstrated outstanding CYP3A7 selectivity and may be useful as indicators of CYP3A7 activity.

The primary bile acids (BAs) synthesized from cholesterol in the liver are converted to secondary BAs by gut microbiota. It was recently disclosed that the major secondary BA, deoxycholate (DCA) species, is stereoselectively oxidized to tertiary BAs exclusively by CYP3A enzymes. This work subsequently investigated the in vitro oxidation kinetics of DCA at C-1β, C-3β, C-4β, C-5β, C-6α, C-6β, and C-19 in recombinant CYP3A enzymes and naive enzymes in human liver microsomes (HLMs). The stereoselective oxidation of DCA fit well with Hill kinetics at 1-300 μM in both recombinant CYP3A enzymes and pooled HLMs. With no contributions or trace contributions from CYP3A5, CYP3A7 favors oxidation at C-19, C-4β, C-6α, C-3β, and C-1β, whereas CYP3A4 favors the oxidation at C-5β and C-6β compared with each other. Correlation between DCA oxidation and testosterone 6β-hydroxylation in 14 adult single-donor HLMs provided proof-of-concept evidence that DCA 19-hydroxylation is an in vitro marker reaction for CYP3A7 activity, whereas oxidation at other sites represents mixed indicators for CYP3A4 and CYP3A7 activities. Deactivation caused by DCA-induced cytochrome P450-cytochrome P420 conversion, as shown by the spectral titrations of isolated CYP3A proteins, was observed when DCA levels were near or higher than the critical micelle concentration (about 1500 μM). Unlike CYP3A4, CYP3A7 showed abnormally elevated activities at 500 and 750 μM, which might be associated with an altered affinity for DCA multimers. The disclosed kinetic and functional roles of CYP3A isoforms in disposing of the gut bacteria-derived DCA may help in understanding the structural and functional mechanisms of CYP3A.

SCOPE Flexitarian dieting is increasingly associated with health benefits. The study of postprandial metabolic response to vegan and animal diets is essential to decipher how specific diet components may mediate metabolic changes. METHODS AND RESULTS A randomized, crossover, controlled vegan versus animal diet challenge is conducted on 21 healthy participants. Postprandial metabolic measurements are conducted at seven timepoints. Area under the curve analysis of the vegan diet response demonstrates higher glucose (EE 0.35), insulin (EE 0.38), triglycerides (EE 0.72), and nine amino acids at breakfast (EE 4.72-209.32); and six lower health-promoting fatty acids at lunch (EE -0.1035 to -0.13) (p < 0.05). CONCLUSIONS Glycemic and lipid parameters vary irrespective of diet type, demonstrating that vegan and animal meals contain health-promoting and suboptimal nutrient combinations. The vegan breakfast produces the same pattern of elevated branched chain amino acids, insulin, and glucose as the animal diet from the fasting results, reflecting the low protein load in the animal and the higher branched-chain amino acid load of the vegan breakfast. Liberalization of the vegan menu to vegetarian and the animal menu to a Nordic-based diet can result in optimal metabolic signatures for both flexitarian diet strategies in future research.

SCOPEThe objective of this study is to develop a new methodology to identify the relationship between dietary patterns and metabolites indicative of food intake and metabolism.METHODS AND RESULTSPlasma and urine samples from healthy Swiss subjects (n = 89) collected over two time points are analyzed for a panel of host-microbial metabolites using GC- and LC-MS. Dietary intake is evaluated using a validated food frequency questionnaire. Dietary pattern clusters and relationships with metabolites are determined using Non-Negative Matrix Factorization (NNMF) and Sparse Generalized Canonical Correlation Analysis (SGCCA). Use of NNMF allows detection of latent diet clusters in this population, which describes a high intake of meat or vegetables. SGCCA associates these clusters to i) diet-host microbial and lipid associated bile acid metabolism, and ii) essential amino acid metabolism.CONCLUSIONThis novel application of NNMF and SGCCA allows detection of distinct metabotypes for meat and vegetable dietary patterns in a heterogeneous population. As many of the metabolites associated with meat or vegetable intake are the result of host-microbiota interactions, the findings support a role for microbiota mediating the metabolic imprinting of different dietary choices.

Abstract E-mail: wenzhou@csu.edu.cn Background: Metabolism reprogramming is one of ten features in cancer. It is well known that metabolites in tumor microenvironment contribute to the survival and proliferation of cancer cells. Currently, a lack of detailed information about the metabolites profiling in bone marrow microenvironment limits us to understand the roles of metabolites associated with multiple myeloma(MM) and its diagnosis and treatment. Here we report a serum untargeted metabolomics study of MM patients, together with healthy donors(HD), with the aim of discovering metabolite markers associated with MM. Materials and Methods: Gas chromatography-time-of-flight mass spectrometry (GC-TOFMS)-based metabolomics was used to analyze 140 serum subjects, including 81 bone marrow subjects(22 HD, 59 MM patients) and 59 peripheral blood subjects(27 HD, 32 MM patients). The bone marrow subjects were divided into training set(11 HD, 32 MM patients) and testing set(11 HD, 27 MM patients). SIMCA-14.1 software package was used to visualize the metabolite alterations between MM patient and HD through Principal component analysis (PCA) and orthogonal projection to latent structures discriminant analysis (OPLS-DA). Both the T-test and the receiver operating characteristic curve(ROC) analysis were performed by SPSS software. Metabolites in serum with higher fold change(FC) and variable importance in the projection(VIP) value(VIP > 1.5, P < 0.05 and FC > 1.5, P < 0.05, FDR < 0.05) were considered as biomarker candidates. Results: A total of 117 and 123 metabolites were annotated from the detected spectral features in bone marrow serum subjects derived from training set and testing set, respectively. Based on multivariate statistical analysis(PCA and OPLS-DA) and univariate statistical analysis(T-test), a panel of 6 and 10 metabolites were identified as differential metabolites(VIP > 1.5, P < 0.05 and FC > 1.5, P < 0.05, FDR < 0.05) between MM patients and HD in training set and testing set, respectively, among of which 5 metabolites were found significantly altered in both sets. Creatinine and glycine were significantly elevated in MM patients compared with HD, while fatty acid consists of palmitic acid, petroselinic acid and stearic acida were found decreased in MM patients compared with HD. ROC analysis of these 5 metabolites resulted in an area under the receiver operating characteristic curve (AUC) of 0.922(95% confidence interval=0.748-1) in the training set and 0.923(95% confidence interval=0.853-1) in the testing set. Furthermore, the diagnostic potential of the metabolite signatures was assessed in peripheral blood subjects. Consistent with bone marrow subjects, metabolite signatures were significantly changed(VIP > 1.5, P < 0.05 and FC > 1.5, P < 0.05, FDR < 0.05) in peripheral blood subjects derived from MM patients compared with HD. The AUC of this metabolites signatures was 0.901(95% confidence interval=0.748-1) in peripheral blood subjects, implying that this panel of metabolites could be of potential clinical significance for the diagnosis of MM. Conclusion: We conclude that a panel of 5 metabolites, including creatinine, glycine, palmitic acid, petroselinic acid and stearic acid, in serum has great potential in discriminating MM patient from HD. This metabolite signatures provides a novel and promising molecular diagnostic approach for the detection of MM. Disclosures No relevant conflicts of interest to declare.

SCOPE:Research is limited on diet challenges to improve health. A short-term, vegan protein diet regimen nutritionally balanced in macronutrient composition compared to an omnivorous diet is hypothesized to improve metabolic measurements of blood sugar regulation, blood lipids, and amino acid metabolism.METHODS AND RESULTS:This randomized, cross-over, controlled vegan versus animal diet challenge is conducted on 21 (11 female,10 male) healthy participants. Fasting plasma is measured during a 3 d diet intervention for clinical biochemistry and metabonomics. Intervention diet plans meet individual caloric needs. Meals are provided and supervised. Diet compliance is monitored.CONCLUSIONS:The vegan diet lowers triglycerides, insulin and homeostatic model assessment (HOMA-IR), bile acids, elevated magnesium levels, and changed branched-chain amino acids (BCAAs) metabolism (p < 0.05), potentiating insulin and blood sugar control after 48 h. Cholesterol control improves significantly in the vegan versus omnivorous diets. Plasma amino acid and magnesium concentrations positively correlate with dietary amino acids. Polyunsaturated fatty acids and dietary fiber inversely correlate with insulin, HOMA-IR, and triglycerides. Nutritional biochemistries, BCAAs, insulin, and HOMA-IR are impacted by sexual dimorphism. A health-promoting, BCAA-associated metabolic signature is produced from a short-term, healthy, controlled, vegan diet challenge when compared with a healthy, controlled, omnivorous diet.

Polycystic kidney disease is characterized by the progressive development of kidney cysts and declining renal function with frequent development of cysts in other organs including the liver. The polycystic kidney (PCK) rat is a rodent model of polycystic liver disease that has been used to study hepatorenal disease progression and evaluate pharmacotherapeutic interventions. Biomarkers that describe the cyst progression, liver impairment, and/or hepatic cyst burden could provide clinical utility for this disease. In the present study, hepatic cyst volume was measured by magnetic resonance imaging in PCK rats at 12, 16, and 20 weeks. After 20 weeks, Sprague Dawley (n = 4) and PCK (n = 4) rats were sacrificed and 42 bile acids were analyzed in the liver, bile, serum, and urine by liquid chromatography coupled to tandem mass spectrometry. Bile acid profiling revealed significant increases in total bile acids (molar sum of all measured bile acids) in the liver (13-fold), serum (6-fold), and urine (3-fold) in PCK rats, including those speciated bile acids usually associated with hepatotoxicity. Total serum bile acids correlated with markers of liver impairment (liver weight, total liver bile acids, total hepatotoxic liver bile acids, and cyst volume [ r > 0.75; P < 0.05]). Based on these data, serum bile acids may be useful biomarkers of liver impairment in polycystic hepatorenal disease.

Missing values exist widely in mass-spectrometry (MS) based metabolomics data. Various methods have been applied for handling missing values, but the selection can significantly affect following data analyses. Typically, there are three types of missing values, missing not at random (MNAR), missing at random (MAR), and missing completely at random (MCAR). Our study comprehensively compared eight imputation methods (zero, half minimum (HM), mean, median, random forest (RF), singular value decomposition (SVD), k-nearest neighbors (kNN), and quantile regression imputation of left-censored data (QRILC)) for different types of missing values using four metabolomics datasets. Normalized root mean squared error (NRMSE) and NRMSE-based sum of ranks (SOR) were applied to evaluate imputation accuracy. Principal component analysis (PCA)/partial least squares (PLS)-Procrustes analysis were used to evaluate the overall sample distribution. Student's t-test followed by correlation analysis was conducted to evaluate the effects on univariate statistics. Our findings demonstrated that RF performed the best for MCAR/MAR and QRILC was the favored one for left-censored MNAR. Finally, we proposed a comprehensive strategy and developed a public-accessible web-tool for the application of missing value imputation in metabolomics ( https://metabolomics.cc.hawaii.edu/software/MetImp/ ).

Host-gut microbiota metabolic interactions are closely associated with health and disease. A manifestation of such co-metabolism is the vast structural diversity of bile acids (BAs) involving both oxidative stereochemistry and conjugation. Herein, we describe the development and validation of a LC-MS-based method for the analysis of human C24 BA metabolome in serum and urine. The method has high throughput covering the discrimination of oxidative stereochemistry of unconjugated species in a 15-min analytical cycle. The validated quantitative performance provided an indirect way to ascertain the conjugation patterns of BAs via enzyme-digestion protocols that incorporated the enzymes, sulfatase, β-glucuronidase, and choloylglycine hydrolase. Application of the method has led to the detection of at least 70 unconjugated BAs including 27 known species and 43 newly found species in the post-prandial serum and urine samples from 7 nonalcoholic steatohepatitis patients and 13 healthy volunteers. Newly identified unconjugated BAs included 3α, 12β-dihydroxy-5β-cholan-24-oic acid, 12α-hydroxy-3-oxo-5β-cholan-24-oic acid, and 3α, 7α, 12β-trihydroxy-5β-cholan-24-oic acid. High-definition negative fragment spectra of the other major unknown species were acquired to facilitate future identification endeavors. An extensive conjugation pattern is the major reason for the “invisibility” of the newly found BAs to other common analytical methods. Metabolomic analysis of the total unconjugated BA profile in combination with analysis of their conjugation patterns and urinary excretion tendencies have provided substantial insights into the interconnected roles of host and gut microbiota in maintaining BA homeostasis. It was proposed that the urinary total BA profile may serve as an ideal footprint for the functional status of the host-gut microbial BA co-metabolism. In summary, this work provided a powerful tool for human C24 BA metabolome analysis that bridges the gap between GC-MS techniques in the past age and LC-MS techniques currently prevailing in biomedical researches. Further applications of the present method in clinical, translational research, and other biomedical explorations will continue to boost the construction of a host-gut microbial co-metabolism network of BAs and thus facilitate the decryption of BA-mediated host-gut microbiota crosstalk in health and diseases.

Objective To establish a method for the determination of praziquantel residues in feed and bovine serum by liquid chromatography-tandem mass spectrometric (LC-MS/MS).Methods Samples were extracted with acetonitrile and ultrapure water,and then purified by solid-phase extraction column.The praziquantel residues in the extracts were separated on a reversed phase column using a gradient elution program of 0.1％ formic acid aqueous solution and acetonitrile.Using LC-MS/MS with multiple reactions monitoring (MRM),identification of the praziquantel residues was performed based upon the intensities of fragments.Results Separation and analysis of target compounds could achieved within 8 min.The recoveries were 75.0％～99.0％ for praziquantel residues with 3 spiked levels of 0.05,0.1 and 0.5 ng/mL.The relative standard deviations (RSD) were less than 5.4％ (n=6).Conclusion The proposed method is fast,accurate and sensitive,which is suitable for detecting praziquantel residues in food and feed samples.