Novel Peak Shift Correction Method Based on the Retention Index for Peak Alignment in Untargeted Metabolomics.

Peak alignment is a crucial step in liquid chromatography-mass spectrometry (LC-MS)-based large-scale untargeted metabolomics workflows, as it enables the integration of metabolite peaks across multiple samples, which is essential for accurate data interpretation. Slight differences or fluctuations in chromatographic separation conditions, however, can cause the chromatographic retention time (RT) shift between consecutive analyses, ultimately affecting the accuracy of peak alignment between samples. Here, we introduce a novel RT shift correction method based on the retention index (RI) and apply it to peak alignment. We synthesized a series of N-acyl glycine (C2-C23) homologues via the amidation reaction between glycine with normal saturated fatty acids (C2-C23) as calibrants able to respond proficiently in both mass spectrometric positive- and negative-ion modes. Using these calibrants, we established an N-acyl glycine RI system. This RI system is capable of covering a broad chromatographic space and addressing chromatographic RT shift caused by variations in flow rate, gradient elution, instrument systems, and LC separation columns. Moreover, based on the RI system, we developed a peak shift correction model to enhance peak alignment accuracy. Applying the model resulted in a significant improvement in the accuracy of peak alignment from 15.5 to 80.9% across long-term data spanning a period of 157 days. To facilitate practical application, we developed a Python-based program, which is freely available at https://github.com/WHU-Fenglab/RI-based-CPSC.

Uncovering the Carboxylated Metabolome in Gut Microbiota-Host Co-metabolism: A Chemical Derivatization-Molecular Networking Approach.

Gut microbiota-host co-metabolites serve as essential mediators of communication between the host and gut microbiota. They provide nutrient sources for host cells and regulate gut microenvironment, which are associated with a variety of diseases. Analysis of gut microbiota-host co-metabolites is of great significance to explore the host-gut microbiota interaction. In this study, we integrated chemical derivatization, liquid chromatography-mass spectrometry, and molecular networking (MN) to establish a novel CD-MN strategy for the analysis of carboxylated metabolites in gut microbial-host co-metabolism. Using this strategy, 261 carboxylated metabolites from mouse feces were detected, which grouped to various classes including fatty acids, bile acids, N-acyl amino acids, benzoheterocyclic acids, aromatic acids, and other unknown small-scale molecular clusters in MN. Based on the interpretation of the bile acid cluster, a novel type of phenylacetylated conjugates of host bile acids was identified, which were mediated by gut microbiota and exhibited a strong binding ability to Farnesoid X receptor and Takeda G protein-coupled receptor 5. Our proposed strategy offers a promising platform for uncovering carboxylated metabolites in gut microbial-host co-metabolism.

Alternating Dual-Collision Energy Scanning Mass Spectrometry Approach: Discovery of Novel Microbial Bile-Acid Conjugates.

Bile acids (BAs) are a type of gut microbiota-host cometabolites with abundant structural diversity, and they play critical roles in maintaining host-microbiota homeostasis. In this study, we developed a new N-(4-aminomethylphenyl) pyridinium (AMPP) derivatization-assisted alternating dual-collision energy scanning mass spectrometry (AMPP-dual-CE MS) method for the profiling of BAs derived from host-gut microbiota cometabolism in mice. Using the proposed method, we discovered two new types of amino acid conjugations (alanine conjugation and proline conjugation) and acetyl conjugation with host BAs, for the first time, from mouse intestine contents and feces. Additionally, we also determined and identified nine new leucine- and phenylalanine-conjugated BAs. These findings broaden our knowledge of the composition of the BA pool and provide insight into the mechanism of host-gut microbiota cometabolism of BAs.

Rapid and Economical Chemoselective Metabolomics Using Boronate Ester Formation on a Monolithic Substrate.

Although chemoselective labeling strategies show great potential in in-depth description of metabolomics, the associated time and expense limit applications in high-throughput and routine analysis. We report a fast and effective chemoselective labeling strategy based on multifunctionalized monolithic probes. A rapid pH-responsive boronate ester reaction was employed to immobilize and release probe molecules from substrate in 5 min. The mesoporous surface and hierarchically porous channels of the substrate allowed for accelerated labeling reactions. Moreover, the discernible boron beacons allowed for recognition of labeled metabolites with no need for expensive isotopic encoding. This new strategy has been successfully used for submetabolome analysis of yeast cells, serum, and faeces samples, with improved sensitivity for short chain fatty acids up to 1 600 times compared with non-labeled liquid chromatography-mass spectrometry (LC-MS) methods.

Screening and Identification of Epoxy/Dihydroxy-Oxylipins by Chemical Labeling-Assisted Ultrahigh-Performance Liquid Chromatography Coupled with High-Resolution Mass Spectrometry.

Epoxy/dihydroxy-oxylipins are important biologically active compounds that are mainly formed from polyunsaturated fatty acids (PUFAs) in the reactions catalyzed by the cytochrome P450 (CYP 450) enzyme. The analysis of epoxy/dihydroxy-oxylipins would be helpful to gain insights into their landscape in living organisms and provide a reference for the biological studies of these compounds. In this work, we employed chemical labeling-assisted liquid chromatography (LC) coupled with high-resolution mass spectrometry (CL-LC-HRMS) to establish a highly sensitive and specific method for screening and annotating epoxy/dihydroxy-oxylipins in biological samples. The isotope reagents 2-dimethylaminoethylamine (DMED) and DMED-d4 were employed to label epoxy/dihydroxy-oxylipins containing carboxyl groups so as to improve the analysis selectivity and MS detection sensitivity of epoxy/dihydroxy-oxylipins. Based on a pair of diagnostic ions with a mass-to-charge ratio (m/z) difference of 15.995 originating from the fragmentation of derivatives via high-energy collision dissociation (HCD), the potential epoxy/dihydroxy-oxylipins were rapidly screened from the complex matrix. Furthermore, the epoxy/dihydroxy groups could be readily localized by the diagnostic ion pairs, which enabled us to accurately annotate the epoxy/dihydroxy-oxylipins detected in biological samples. The applicability of our method was demonstrated by profiling epoxy/dihydroxy-oxylipins in human serum and heart samples from mice with high-fat diet (HFD). By the proposed method, a total of 32 and 62 potential epoxy/dihydroxy-oxylipins including 42 unreported ones were detected from human serum and the mice heart sample, respectively. Moreover, the relative quantitative results showed that most of the potential epoxy/dihydroxy-oxylipins, especially the oxidation products of linoleic acid (LA) or α-linolenic acid (ALA), were significantly decreased in the heart of mice with HFD. Our developed method is of high specificity and sensitivity and thus is a promising tool for the identification of novel epoxy/dihydroxy-oxylipins in biological samples.

Boron Isotope Tag-Assisted Ultrahigh-Performance Liquid Chromatography Coupled with High-Resolution Mass Spectrometry for Discovery and Annotation of cis-Diol-Containing Metabolites.

cis-Diol-containing metabolites are widely distributed in living organisms, and they participate in the regulation of various important biological activities. The profiling of cis-diol-containing metabolites could help us in fully understanding their functions. In this work, based on the characteristic isotope pattern of boron, we employed a boronic acid reagent as the isotope tag to establish a sensitive and selective liquid chromatography-high-resolution mass spectrometry method for the screening and annotation of cis-diol-containing metabolites in biological samples. Boronic acid reagent 2-methyl-4-phenylaminomethylphenylboronic acid was used to label the cis-diol-containing metabolites in biological samples to improve the selectivity and MS sensitivity of cis-diol-containing metabolites. Based on the characteristic 0.996 Da mass difference of precursor ions and the peak intensity ratio of 1:4 originating from 10B and 11B natural isotopes, the potential cis-diol-containing metabolites were rapidly screened from biological samples. Potential cis-diol-containing metabolites were annotated by database searching and analysis of fragmentation patterns obtained by multistage MS (MSn) via collision-induced dissociation. Importantly, the cis-diol position could be readily resolved by the MS3 spectrum. With this method, a total of 45 cis-diol-containing metabolites were discovered in rice, including monoglycerides, polyhydroxy fatty acids, fatty alcohols, and so forth. Furthermore, the established method showed superiority in avoiding false-positive results in profiling cis-diol-containing metabolites.

Integration of Chemical Derivatization and in-Source Fragmentation Mass Spectrometry for High-Coverage Profiling of Submetabolomes.

In-source fragmentation-based high-resolution mass spectrometry (ISF-HRMS) is a potential analytical technique, which is usually used to profile some specific compounds that can generate diagnostic neutral loss (NL) or fragment ion (FI) in ion source inherently. However, the ISF-HRMS method does not work for those compounds that cannot inherently produce diagnostic NL or FI in ion source. In this study, a derivatization-based in-source fragmentation-information-dependent acquisition (DISF-IDA) strategy was proposed for profiling the metabolites with easily labeled functional groups (submetabolomes) by liquid chromatography-electrospray ionization-quadrupole time-of-flight mass spectrometry (LC-ESI-Q-TOF MS). As a proof-of-concept study, 36 carboxylated compounds labeled with N,N-dimethylethylenediamine (DMED) were selected as model compounds to examine performance of DISF-IDA strategy in screening the carboxylated metabolites and acquiring their MSn spectra. In ESI source, the DEMD-derived carboxylated compounds were fragmented to produce characteristic neutral losses of 45.0578, 63.0684, and/or 88.1000 Da that were further used as diagnostic features for screening the carboxylated metabolites by DISF-IDA-based LC-Q-TOF MS. Furthermore, high-resolution MSn spectra of the model compounds were also obtained within a single run of DISF-IDA-based LC-Q-TOF MS analysis, which contributed to the improvement of the annotation confidence. To further verify its applicability, DISF-IDA strategy was used for profiling carboxylated submetabolome in mice feces. Using this strategy, a total of 351 carboxylated metabolites were detected from mice feces, of which 178 metabolites (51% of the total) were positively or putatively identified. Moreover, DISF-IDA strategy was also demonstrated to be applicable for profiling other submetabolomes with easily labeled functional groups such as amino, carbonyl, and cis-diol groups. Overall, our proposed DISF-IDA strategy is a promising technique for high-coverage profiling of submetabolomes with easily labeled functional groups in biological samples.

In-Depth Annotation Strategy of Saturated Hydroxy Fatty Acids Based on Their Chromatographic Retention Behaviors and MS Fragmentation Patterns.

Hydroxy fatty acids are a class of bioactive compounds in a variety of organisms. The identification of hydroxy fatty acids in biological samples has still been a challenge because of their low abundance, high structural similarity, and limited availability of authentic hydroxy fatty acid standards. Here, we present a strategy for the annotation of saturated monohydroxyl fatty acids (OH-FAs) based on the integration of chromatographic retention rules and MS2 fragmentation patterns. Thirty-nine authentic OH-FA standards were used to investigate their retention behavior on a reversed-phase stationary phase (C18) of liquid chromatography, and we found that their retention simultaneously follows two kinds of "carbon number rules". Using the "carbon number rules", the retention index (RI) of all OH-FAs that contain carbon numbers from 8 to 18 (C8-18) can be predicted. Additionally, by studying the MS2 fragmentation of OH-FAs under collision-induced dissociation, we found that the intensity ratio (IR) of the characteristic fragment ions ([M + H]+-63 and [M + H]+-45) is closely related to the position of the hydroxyl group on the OH-FA structure, which is helpful to further identify and confirm the OH-FA isomers. As a result, 97 of 107 potential OH-FAs detected in honey, human serum, and rice seedling by chemical isotope labeling-assisted liquid chromatography-mass spectrometry were annotated upon the RI matching and IR confirming. Furthermore, in order to simplify the annotation process of OH-FAs, we constructed an OH-FA library to facilitate the annotation of OH-FAs. Overall, this study provides a new and promising tool for the in-depth annotation of OH-FA isomers.

In-Silico-Generated Library for Sensitive Detection of 2-Dimethylaminoethylamine Derivatized FAHFA Lipids Using High-Resolution Tandem Mass Spectrometry.

Fatty acid esters of hydroxy fatty acids (FAHFAs) are a family of recently discovered lipids with important physiological functions in mammals and plants. However, low detection sensitivity in negative ionization mode mass spectrometry makes low-abundance FAHFA challenging to analyze. A 2-dimethylaminoethylamine (DMED) based chemical derivatization strategy was recently reported to improve the MS sensitivity of FAHFAs by labeling FAHFAs with a positively ionizable tertiary amine group. To facilitate reliable, high-throughput, and automatic annotation of these compounds, a DMED-FAHFA in silico library containing 4290 high-resolution tandem mass spectra covering 264 different FAHFA classes was developed. The construction of the library was based on the heuristic information from MS/MS fragmentation patterns of DMED-FAHFA authentic standards, and then, the patterns were applied to computer-generated DMED-FAHFAs. The developed DMED-FAHFA in silico library was demonstrated to be compatible with library search software NIST MS Search and the LC-MS/MS data processing tool MS-DIAL to guarantee high-throughput and automatic annotations. Applying the in silico library in Arabidopsis thaliana samples for profiling FAHFAs by high-resolution LC-MS/MS enabled the annotation of 19 DMED-FAHFAs from 16 families, including 3 novel compounds. Using the in silico library largely decreased the false-positive annotation rate in comparison to low-resolution LC-MS/MS. The developed library, MS/MS spectra, and development templates are freely available for commercial and noncommercial use at https://zenodo.org/record/3606905.

Method to Calculate the Retention Index in Hydrophilic Interaction Liquid Chromatography Using Normal Fatty Acid Derivatives as Calibrants.

Hydrophilic interaction liquid chromatography-mass spectrometry (HILIC-MS) is a complementary technique to reversed-phase liquid chromatography-mass spectrometry (RPLC-MS) and has been widely used to expand the coverage of the metabolome in MS-based metabolomics. However, the use of HILIC retention time (HILIC RT) in metabolites annotation is quite limited because of its poor reproducibility. Here, we developed a method to calculate the retention index in HILIC (HILIC RI) for calibration of HILIC RT. In this method, a mixture of 2-dimethylaminoethylamine (DMED)-labeled fatty acid standards with carbon chain length from C2 to C22 were selected as calibrants to establish a linear calibration equation between HILIC RT and carbon number for the calculation of HILIC RI. The calculated HILIC RIs based on a regression equation could efficiently calibrate the retention time shifts for 28 DMED-labeled carboxyl standards and DMED-labeled carboxyl metabolites in rat urine, serum and feces on a HILIC column with different gradient elution conditions. Furthermore, the developed HILIC RI strategy was applied to RT calibration of screened metabolites, the annotation of isomers in HILIC-MS-based metabolomics analysis for real samples, and the correction of isotope effects in chemical isotope labeling HILIC-MS analysis. Taken together, the resulting HILIC RI strategy is a promising analytical technique to improve the accuracy of metabolite annotation; it would be widely used in HILIC-MS-based metabolome analysis.

Comprehensive Screening and Identification of Fatty Acid Esters of Hydroxy Fatty Acids in Plant Tissues by Chemical Isotope Labeling-Assisted Liquid Chromatography-Mass Spectrometry.

Fatty acid esters of hydroxy fatty acids (FAHFAs) are a new class of lipid mediators with promising anti-diabetic and anti-inflammatory properties. Comprehensive screening and identification of FAHFAs in biological samples would be beneficial to the discovery of new FAHFAs and enable greater understanding of their biological functions. Here, we report the comprehensive screening of FAHFAs in rice and  Arabidopsis thaliana by chemical isotope labeling-assisted liquid chromatography-mass spectrometry (CIL-LC-MS). Multiple reaction monitoring (MRM) was used for screening of FAHFAs. With the proposed method, we detected 49 potential FAHFA families, including 262 regioisomers, in tissues of rice and Arabidopsis thaliana, which greatly extends our knowledge of known FAHFAs. In addition, we proposed a strategy to identify FAHFA regioisomers based on their retention on a reversed-phase LC column. Using the proposed identification strategy, we identified 71 regioisomers from 11 FAHFA families based on commercial standards and characteristic chromatographic retention behaviors. The screening technique could allow for the discovery of new FAHFAs in biological samples. The new FAHFAs identified in this work will contribute to the in-depth study of the functions of FAHFAs.

Establishment of Liquid Chromatography Retention Index Based on Chemical Labeling for Metabolomic Analysis.

Chemical labeling (CL) in combination with liquid chromatography-mass spectrometry (LC-MS) analysis has been demonstrated to be a promising technology in metabolomic analysis. However, identification of chemically labeled metabolites remains to be challenging. Retention time (RT) is one of the most important parameters for the identification of metabolites, but it could vary greatly in LC-MS analysis. In this work, we developed a chemical labeling-based HPLC retention index (CL-HPLC RI) strategy to facilitate the identification of metabolites. In this CL-HPLC RI strategy, a series of 2-dimethylaminoethylamine (DMED)-labeled fatty acids were used as calibrants to establish RIs for DMED-labeled carboxylated compounds and a series of 4-( N, N-dimethylamino)phenyl isothiocyanate (DMAP)-labeled fatty amines were used as calibrants for DMAP-labeled amine compunds. To calculate the RIs, the whole LC chromatogram was divided into 24 time intervals by 23 DMED-labeled fatty acid standards or 15 time intervals by 14 DMAP-labeled fatty amine standards. Then, we established the RIs of 854 detected DMED-labeled carboxylated metabolites and 1057 DMAP-labeled amine metabolites in fecal samples and demonstrated that RIs were highly reproducible under different elution gradients, columns, and instrument systems. Finally, we applied this strategy to the identification of metabolites in human serum. Using RIs, 267 DMED-labeled carboxylated metabolites and 273 DMAP-labeled amine metabolites in human serum matched well with the fecal metabolome database. Taken together, the developed CL-HPLC RI strategy was demonstrated to be a promising method to facilitate the identification of metabolites in metabolomic analysis.

Comprehensive Profiling of Fecal Metabolome of Mice by Integrated Chemical Isotope Labeling-Mass Spectrometry Analysis.

Gut microbiota plays important roles in the host health. The host and symbiotic gut microbiota coproduce a large number of metabolites during the metabolism of food and xenobiotics. The analysis of fecal metabolites can provide a noninvasive manner to study the outcome of the host-gut microbiota interaction. Herein, we reported the comprehensive profiling of fecal metabolome of mice by an integrated chemical isotope labeling combined with liquid chromatography-mass spectrometry (CIL-LC-MS) analysis. The metabolites are categorized into several submetabolomes based on the functional moieties (i.e., carboxyl, carbonyl, amine, and thiol) and then analysis of the individual submetabolome was performed. The combined data from the submetabolome form the metabolome with relatively high coverage. To this end, we synthesized stable isotope labeling reagents to label metabolites with different groups, including carboxyl, carbonyl, amine, and thiol groups. We detected 2302 potential metabolites, among which, 1388 could be positively or putatively identified in feces of mice. We then further confirmed 308 metabolites based on our established library of chemically labeled standards and tandem mass spectrometry analysis. With the identified metabolites in feces of mice, we established mice fecal metabolome database, which can be used to readily identify metabolites from feces of mice. Furthermore, we discovered 211 fecal metabolites exhibited significant difference between Alzheimer's disease (AD) model mice and wild type (WT) mice, which suggests the close correlation between the fecal metabolites and AD pathology and provides new potential biomarkers for the diagnosis of AD.

[Alignment method for metabolite chromatographic peaks using an N-acyl glycine retention index system].

Peak alignment is a crucial data-processing step in untargeted metabolomics analysis that aims to integrate metabolite data from multiple liquid chromatography-mass spectrometry (LC-MS) batches for enhanced comparability and reliability. However, slight variations in the chromatographic separation conditions can result in retention time (RT) shifts between consecutive analyses, adversely affecting peak alignment accuracy. In this study, we present a retention index (RI)-based chromatographic peak-shift correction (CPSC) strategy to address RT shifts and align chromatographic peaks for metabolomics studies. A series of N-acyl glycine homologues (C2-C23) was synthesized as calibrants, and an LC RI system was established. This system effectively corrected RT shifts arising from variations in flow rate, gradient elution, instrument systems, and chromatographic columns. Leveraging the RI system, we successfully adjusted the RT of raw data to mitigate RT shifts and then implemented the Joint Aligner algorithm for peak alignment. We assessed the accuracy of the RI-based CPSC strategy using pooled human fecal samples as a test model. Notably, the application of the RI-based CPSC strategy to a long-term dataset spanning 157 d as an illustration revealed a significant enhancement in peak alignment accuracy from 15.5% to 80.9%, indicating its ability to substantially improve peak-alignment precision in multibatch LC-MS analyses.

Metabolomic Analysis Reveals Association between Decreased Ovarian Reserve and In Vitro Fertilization Outcomes.

In vitro fertilization (IVF) is a highly effective treatment for infertility; however, it poses challenges for women with decreased ovarian reserve (DOR). Despite the importance of understanding the impact of DOR on IVF outcomes, limited research has explored this relationship, particularly using omics approaches. Hence, we conducted a study to investigate the association between DOR and IVF outcomes, employing a metabolomic approach. We analyzed serum samples from 207 women undergoing IVF treatment, including 89 with DOR and 118 with normal ovarian reserve (NOR). Our findings revealed that DOR was significantly associated with unfavorable IVF outcomes, characterized by a reduced oocyte count, lower embryo quality, and decreased rates of pregnancy and live births. Furthermore, we identified 82 metabolites that displayed significant alterations in DOR patients, impacting diverse metabolic pathways. Notably, a distinct panel of metabolites, including palmitic acid, stearic acid, LysoPC(9:0(CHO)/0:0), PC(18:0/9:0(CHO)), and PC(16:0/9:0(CHO)), exhibited discriminatory power between the DOR and NOR groups, showcasing a strong correlation with IVF outcomes. These findings emphasize the crucial role of metabolomic disruptions in influencing IVF outcomes among women with DOR.

Determination of vitamin D metabolites in various biological samples through an improved chemical derivatization assisted liquid chromatography-tandem mass spectrometry approach.

Vitamin D (VD) metabolites are involved in a variety of important metabolic processes and physiological effects in organisms. Profiling of VD metabolites favors a deep understanding of the physiological role of VD. However, VD metabolites are difficult to detect due to their high chemical structural rigidity, structural similarity, and low sensitivities under liquid chromatography-tandem mass spectrometry (LC-MS). Herein, we present a chemical derivatization assisted LC-MS/MS strategy for the detection of VDs, in which 4-phenyl-1,2,4-triazoline-3,5-dione (PTAD) is employed to derivatize the conjugated diene of VD metabolites and provides sensitizing reporters for MS detection. After PTAD derivatization, the sensitivities of seven VD metabolites increased by 24-276 folds, with the limits of detection ranging from 3 to 20 pg mL-1. Using this method, we achieved a sensitive and accurate quantification of 7 VD metabolites (vitamin D2, vitamin D3, 25-hydroxyvitamin D2, 25-hydroxyvitamin D3, 1,25-dihydroxyvitamin D2, 1,25-dihydroxyvitamin D3, and 1,24,25-trihydroxyvitamin D3) of the VD metabolic pathway in different trace biological samples, including human serum, mouse tissues (namely liver, kidney, lung, and spleen), and cells. We believe that the present method can provide a promising tool for an in-depth analysis of VD metabolism.

A dataset of branched fatty acid esters of hydroxy fatty acids diversity in foods.

Branched fatty acid esters of hydroxy fatty acids (FAHFAs) are a class of bioactive lipids that show therapeutic potential for diabetes, anti-cancer and inflammation. These FAHFAs can be obtained through dietary intake, potentially improving human health. However, there is currently inadequate knowledge regarding the presence and variety of FAHFAs in different foods. Herein, we profile FAHFAs from 12 typical food samples and 4 medicinal food samples with the aid of our previous established chemical isotope labeling-assisted liquid chromatography-mass spectrometry method and build a comprehensive dataset of FAHFA diversity. The dataset comprised a total of 1207 regioisomers belonging to 298 different families, with over 100 families being newly discovered for the first time. Therefore, our findings contribute valuable insights into the molecular diversity and presence of FAHFA in a range of foods. This dataset serves as a foundation for further exploration of the nutritional and medicinal functions of FAHFAs.

Chemical isotope labeling assisted liquid chromatography-mass spectrometry method for simultaneous analysis of central carbon metabolism intermediates.

Central carbon metabolism pathway (CCM) is one of the most important metabolic pathways in all living organisms and play crucial function in aspect of organism life. However, the simultaneous detection of CCM intermediates remains challenging. Here, we developed a chemical isotope labeling combined with LC-MS method for simultaneous determination of CCM intermediates with high coverage and accuracy. By chemical derivatization with 2-(diazo-methyl)-N-methyl-N-phenyl-benzamide (2-DMBA) and d5-2-DMBA, all CCM intermediates obtain better separation and accurate quantification at a single LC-MS run. The obtained limits of detection of CCM intermediates ranged from 5 to 36 pg/mL. Using this method, we achieved simultaneous and accurate quantification of 22 CCM intermediates in different biological samples. Take account of the high detection sensitivity of the developed method, this method was further applied to the quantification of CCM intermediates at single-cell level. Finally, 21 CCM intermediates were detected in 1000 HEK-293T cells and 9 CCM intermediates were detected in mouse kidney glomeruli optical slice samples (10∼100 cells).

A strategy for screening and identification of new amino acid-conjugated bile acids with high coverage by liquid chromatography-mass spectrometry.

Bile acids (BAs) are a class of vital gut microbiota-host cometabolites, and they play an important role in maintaining gut microbiota-host metabolic homeostasis. Very recently, a new mechanism of BA anabolic metabolism mediated by gut microbiota (BA-amino acid conjugation) has been revealed, which provides a perspective for the research on BA metabolism and gut metabolome. In this study, we established a polarity-switching multiple reaction monitoring mass spectrometry-based screening method to mine amino acid-conjugated bile acids (AA-BAs) derived from host-gut microbiota co-metabolism. In addition, a retention time-based annotation strategy was further proposed to identify the AA-BA isomers and epimers. Using the developed methods, we successfully screened 118 AA-BA conjugates from mouse and human feces, 28 of them were confirmed by standards, and 62 putatively identified based on their predicted retention times. Moreover, we observed that the levels of most AA-BAs were significantly downregulated in the feces of chronic sleep deprivation mice, suggesting that the AA-BA metabolism was closely related to the physiological state of the host.

In-depth profiling of di(2-ethylhexyl) phthalate metabolic footprints in rats using click chemistry-mass spectrometry probes.

Di(2-ethylhexyl) phthalate (DEHP), the most widely used plasticizers in the world, has been regarded as an endocrine disrupting chemical with serious adverse health outcomes. Accumulating evidence strongly suggests that the undesirable biological effects of DEHP are meditated by its metabolites rather than itself. However, the metabolic footprints of DEHP in vivo are still unclear. Here we developed a click chemistry-assisted mass spectrometry (CC-MS) strategy for in-depth profiling DEHP metabolites in rats. An alkyne-modified DEHP analogue (alkyne-DEHP) was synthesized as a tracer for in vivo tracing, and a pair of MS probes (4-azido-nphenylbenzamide, 4-ANPA, and its deuterated reagent d5-4-ANPA) were prepared to specifically label the alkyne-DEHP metabolites, and prominently improve their detection sensitivity and selectivity. Using the CC-MS strategy, we successfully screened 247 alkyne-DEHP metabolites from rat urine, feces, and serum, including many unrevealed metabolites, such as oxidized phthalate diester metabolites and glucuronides of phthalate monoester metabolites. The discovery of new DEHP metabolites provides additional insights for understanding the metabolism of DEHP, which may be beneficial in exploring the mechanism underlying DEHP induced-toxicity in the future.