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Abstract Tryptophan (TRP) and its catabolites have attracted a lot of attention because of their clinical significance to human health. Recently, microbiome-gut-brain axis was found to have links to many diseases based on the imbalance of TRP catabolism. By using ultra-high performance liquid chromatography coupled to electrospray ionization triple quadrupole mass spectrometry, we present a rapid, robust and comprehensive method to determine 31 TRP catabolites covering three major pathways - kynurenic, serotonergic and bacterial degradation - within 5 min. Polarity switching was employed to analyze catabolites in both ionization modes simultaneously for greatly improved analytical throughput. The intra-day and inter-day precision were 0.5–15.8% and 1.5–16.7%, respectively. Accuracy was between 75.8 and 126.9%. The developed method was applied to study the tissue level of TRP catabolites in the liver, ileum, ileal contents, brain and plasma samples from 8 mice, and clear differences in the distribution of TRP catabolites were observed in different tissues. Ratios of key catabolites to TRP were used to evaluate the activities of specific enzyme and pathway in respective tissues. This method has potential in high throughput analysis of TRP catabolites in biological matrices, which can facilitate understanding the influence of TRP catabolites on microbiome-gut-brain axis and on human health. Graphical abstract Image 1 Highlights • Targeted metabolomics assay covers tryptophan and 31 of its catabolites. • Polarity switching UHPLC-SRM-MS enables analysis in just 5 min. • Simple sample preparation ensures high analyte recovery and reproducibility. • Assay was validated in 5 different types of mouse tissues. • Ratios of catabolites to TRP reflect key enzymatic activities in different tissues. [ABSTRACT FROM AUTHOR]

Cellular lipidomic studies have been favored approaches in many biomedical research areas. To provide fair comparisons of the studied cells, it is essential to perform normalization of the determined concentration before lipidomic analysis. This study proposed a cellular lipidomic normalization method by measuring the phosphatidylcholine (PC) and sphingomyelin (SM) contents in cell extracts. To provide efficient analysis of PC and SM in cell extracts, flow injection analysis-electrospray ionization-tandem mass spectrometry (FIA-ESI-MS/MS) with a precursor ion scan (PIS) of m/z 184 was used, and the parameters affecting the performance of the method were optimized. Good linearity could be observed between the cell extract dilution factor and the reciprocal of the total ion chromatogram (TIC) area in the PIS of m/z 184 within the dilution range of 1- to 16-fold (R 2 = 0.998). The calibration curve could be used for concentration adjustment of the unknown concentration of a cell extract. The intraday and intermediate precisions were below 10%. The accuracy ranged from 93.0% to 105.6%. The performance of the new normalization method was evaluated using different numbers of HCT-116 cells. Sphingosine, ceramide (d18:1/18:0), SM (d18:1/18:0) and PC (16:1/18:0) were selected as the representative test lipid species, and the results showed that the peak areas of each lipid species obtained from different cell numbers were within a 20% variation after normalization. Finally, the PIS of 184 normalization method was applied to study ischemia-induced neuron injury using oxygen and glucose deprivation (OGD) on primary neuronal cultured cells. Our results showed that the PIS of 184 normalization method is an efficient and effective approach for concentration normalization in cellular lipidomic studies. [ABSTRACT FROM AUTHOR]

Normalizing the total urine concentration is important for minimizing bias in urinary metabolomics analysis comparisons. In this study, we report a matrix-induced ion suppression (MIIS)-based method to normalize concentration using flow injection analysis coupled with electrospray ionization mass spectrometry (FIA-ESI-MS). An ion suppression indicator (ISI) was spiked into urine samples, and the intensity of the extracted ion chromatogram (EIC) for ISI in a urine matrix was subtracted by the EIC for a blank solution and used to calculate the extent to which the signal was reduced by the urine matrix. A series dilution of pooled urine samples was used to correlate the urine concentration and level of ion suppression for ISI. A regression equation was used to estimate the relative concentration of unknown urine samples. The MIIS method was validated for linearity, precision and accuracy. We obtained a good correlation using a quadratic regression model for 1- to 32-fold urine dilutions ( R 2 = 0.998). The reproducibility ( n = 4) and intermediate precision ( n = 3) were below 5% RSD, and the accuracy ranged from 97.15% to 102.10%. The established method was used to estimate the relative concentrations of 16 urine samples, and the results were compared with commonly used normalization methods. Pearson’s correlation test was used to demonstrate that the MIIS method correlated highly with the creatinine and osmolarity methods; the correlation coefficients were 0.93 and 0.99, respectively. We successfully applied this method to a urinary metabolomics study on breast cancer. This study demonstrated the MIIS method is simple, accurate and can contribute to data integrity in urinary metabolomics studies. [ABSTRACT FROM AUTHOR]

Quantification of endogenous metabolites has enabled the discovery of biomarkers for diagnosis and provided for an understanding of disease etiology. The standard addition and stable isotope labeled-internal standard (SIL-IS) methods are currently the most widely used approaches to quantifying endogenous metabolites, but both have some limitations for clinical measurement. In this study, we developed a new approach for endogenous metabolite quantification by the postcolumn infused-internal standard (PCI-IS) method combined with the matrix normalization factor (MNF) method. MNF was used to correct the difference in MEs between standard solution and biofluids, and PCI-IS additionally tailored the correction of the MEs for individual samples. Androstenedione and testosterone were selected as test articles to verify this new approach to quantifying metabolites in plasma. The repeatability ( n = 4 runs) and intermediate precision ( n = 3 days) in terms of the peak area of androstenedione and testosterone at all tested concentrations were all less than 11% relative standard deviation (RSD). The accuracy test revealed that the recoveries were between 95.72% and 113.46%. The concentrations of androstenedione and testosterone in fifty plasma samples obtained from healthy volunteers were quantified by the PCI-IS combined with the MNF method, and the quantification results were compared with the results of the SIL-IS method. The Pearson correlation test showed that the correlation coefficient was 0.98 for both androstenedione and testosterone. We demonstrated that the PCI-IS combined with the MNF method is an effective and accurate method for quantifying endogenous metabolites. [ABSTRACT FROM AUTHOR]

Highlights: [•] An effective and economic PCI-IS method for MEs correction in LC–ESI-MS. [•] PCI-IS could effectively correct MEs in urine specimens. [•] PCI-IS method resolved the drawbacks of traditional internal standard method. [ABSTRACT FROM AUTHOR]

Liquid chromatography-electrospray ionization mass spectrometry (LC-ESI-MS) has become one of the most widely used methods in pharmaceutical laboratories. Although LC-ESI-MS provides high sensitivity and high specificity for quantifying target analytes in complicated biofluids, the associated severe matrix effects (MEs) generally result in large quantification errors. Here, we propose a novel strategy for correcting MEs in various biofluids using a postcolumn infused-internal standard (PCI-IS) method in combination with matrix normalization factors (MNFs). We used the MNFs to normalize the encountered MEs in various biofluids to the MEs encountered in standard solutions. The use of a postcolumn infused-internal standard also corrects the MEs for individual samples. When using the PCI-IS method in combination with MNFs, the calibration curve generated from standard solutions can be applied to quantify the target analytes in various biofluids. We applied this new approach to quantify etoposide and etoposide catechol in plasma and CSF. The accuracy of the test results showed that over 93% of the data have quantification errors less than 20% and that 99% of the data have quantification errors less than 30%. The successful application of this method to evaluate real clinical samples revealed that our proposed MNFs in combination with the PCI-IS method largely simplifies the entire method development and validation processes, saves a great deal of time and cost without sacrificing quantification accuracy, and provides a simple means of quantifying target analytes in various biofluids. This method will be particularly useful in fields in which the same target analytes need to be quantified in various types of matrices, including bioanalysis, forensic toxicology, environmental studies, and food safety control. [ABSTRACT FROM AUTHOR]