[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.

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.

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.

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.

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.