Acyl-CoA Identification in Mouse Liver Samples Using the In Silico CoA-Blast Tandem Mass Spectral Library

Enzyme Catalyzed Formation of CoA Adducts of Fluorinated Hexanoic Acid Analogues using a Long-Chain acyl-CoA Synthetase from Gordonia sp. Strain NB4-1Y

Per and polyfluoroalkyl substances (PFAS) are a large family of anthropogenic fluorinated chemicals of increasing environmental concern. Over recent years, numerous microbial communities have been found to be capable of metabolizing some polyfluoroalkyl substances, generating a range of low-molecular-weight PFAS metabolites. One proposed pathway for the microbial breakdown of fluorinated carboxylates includes β-oxidation, this pathway is initiated by the formation of a CoA adduct. However, until recently no PFAS-CoA adducts had been reported. In a previous study, we were able to use a bacterial medium-chain acyl-CoA synthetase (mACS) to form CoA adducts of fluorinated adducts of propanoic acid and pentanoic acid but were not able to detect any products of fluorinated hexanoic acid analogues. Herein, we expressed and purified a long-chain acyl-CoA synthetase (lACS) and a A461K variant of mACS from the soil bacterium Gordonia sp. strain NB4-1Y and performed an analysis of substrate scope and enzyme kinetics using fluorinated and nonfluorinated carboxylates. We determined that lACS can catalyze the formation of CoA adducts of 1:5 fluorotelomer carboxylic acid (FTCA), 2:4 FTCA and 3:3 FTCA, albeit with generally low turnover rates (<0.02 s-1) compared with the nonfluorinated hexanoic acid (5.39 s-1). In addition, the A461K variant was found to have an 8-fold increase in selectivity toward hexanoic acid compared with wild-type mACS, suggesting that Ala-461 has a mechanistic role in selectivity toward substrate chain length. This provides further evidence to validate the proposed activation step involving the formation of CoA adducts in the enzymatic breakdown of PFAS.

An 8-(Diazomethyl) Quinoline Derivatized Acyl-CoA in Silico Mass Spectral Library Reveals the Landscape of Acyl-CoA in Aging Mouse Organs

Acyl-Coenzyme As (acyl-CoAs) are essential intermediates to incorporate carboxylic acids into the bioactive metabolic network across all species, which play important roles in lipid remodeling, fatty acids, and xenobiotic carboxylic metabolism. However, due to the poor liquid chromatographic behavior, the relatively low mass spectrometry (MS) sensitivity, and lack of authentic standards for annotation, the in-depth untargeted profiling of acyl-CoAs is challenging. We developed a chemical derivatization strategy of acyl-CoAs by employing 8-(diazomethyl) quinoline (8-DMQ) as the labeling reagent, which increased the detection sensitivity by 625-fold with good peak shapes. By applying the MS/MS fragmentation rules learned from the MS/MS spectra of 8-DMQ-acyl-CoA authentic standards, an 8-DMQ-acyl-CoA in silico mass spectral library containing 33,344 high-resolution tandem mass spectra of 8,336 acyl-CoA species was created. The in silico library facilitated the high-throughput and automatic annotation of acyl-CoA using multiple metabolomic data processing tools, such as NIST MS Search and MSDIAL. The feasibility of the in silico library in a complex sample was demonstrated by profiling endogenous acyl-CoAs in multiple organs of an aging mouse. 53 acyl-CoA species were annotated, including 12 oxidized fatty acyl-CoAs and 3 novel nonfatty acyl-CoAs. False positive annotations were further screened by developing an eXtreme Gradient Boosting (XGBoost) based retention time prediction model. The organ distribution and the aging dynamics of acyl-CoAs in a mouse model were discussed for the first time, which helped to elucidate the organ-specific function of acyl-CoAs and the role of different acyl-CoA species during aging.

Formation of CoA Adducts of Short-Chain Fluorinated Carboxylates Catalyzed by Acyl-CoA Synthetase from Gordonia sp. Strain NB4-1Y

Perfluoroalkyl and polyfluoroalkyl substances (PFAS) make up a group of anthropogenic chemicals with a myriad of applications. However, some PFAS have been shown to negatively impact human health and the environment, leading to increased regulation, with some countries making efforts to phase out their use. PFAS fate in the environment is driven by physical, chemical, and biological processes, with microbial communities in matrices such as soil and sewage sludge being known to generate a range of low-molecular-weight PFAS metabolites. Proposed metabolic intermediates for both mixed and pure microbial cultures include fluorinated carboxylates that may be activated by CoA prior to β-oxidation and defluorination, although thus far, no PFAS-CoA adducts have been reported. Herein, we expressed and purified acyl-CoA synthetase (ACS) from the soil bacterium Gordonia sp. strain NB4-1Y and performed an analysis of substrate scope and enzyme kinetics using fluorinated and nonfluorinated carboxylates. We determined that ACS was able to catalyze the formation of CoA adducts of 3,3,3-trifluoropropionic acid, 5,5,5-trifluoropentanoic acid, 4,5,5-trifluoropent-4-enoic acid, and 4,4,5,5,5-pentafluoropentanoic acid. Kinetic analysis revealed a 90-98% decrease in kcat between nonfluorinated carboxylates and their fluorinated analogues. This provides evidence to validate proposed enzymatic pathways for microbial PFAS metabolism that proceed via an activation step involving the formation of CoA adducts.

Integration of semi-empirical MS/MS library with characteristic features for the annotation of novel amino acid-conjugated bile acids

Recently, amino acids other than glycine and taurine were found to be conjugated with bile acids by the gut microbiome in mouse and human. As potential diagnostic markers for inflammatory bowel disease and farnesoid X receptor agonists, their physiological effects and mechanisms, however, remain to be elucidated. A tool for the rapid and comprehensive annotation of such new metabolites is required. Thus, we developed a semi-empirical MS/MS library for bile acids conjugated with 18 common amino acids, including alanine, arginine, asparagine, aspartate, glutamine, glutamate, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, proline, serine, threonine, tryptophan, tyrosine, and valine. To investigate their fragmentation rules, these amino acids were chemically conjugated with lithocholic acid, deoxycholic acid, and cholic acid, and their accurate-mass MS/MS spectra were acquired. The common fragmentation patterns from the amino acid moieties were combined with 10 general bile acid skeletons to generate a semi-empirical MS/MS library of 180 structures. Software named BAFinder 2.0 was developed to combine the semi-empirical library in negative mode and the characteristic fragments in positive mode for automatic unknown identification. As a proof of concept, this workflow was applied to the LC-MS/MS analysis of the feces of human, beagle dogs, and rats. In total, 171 common amino acid-conjugated bile acids were annotated and 105 of them were confirmed with the retention times of synthesized compounds. To explore other potential bile acid conjugates, user-defined small molecules were in-silico conjugated with bile acids and searched in the fecal dataset. Four novel bile acid conjugates were discovered, including D-Ala-D-Ala, Lys(iso)-Gly, L-2-aminobutyric acid, and ornithine.

Comprehensive Profiling of Phosphomonoester Metabolites in Saccharomyces cerevisiae by the Chemical Isotope Labeling-LC-MS Method

Phosphomonoesters are important biosynthetic and energy metabolism intermediates in microorganisms. A comprehensive analysis of phosphomonoester metabolites is of great significance for the understanding of their metabolic phosphorylation process and inner mechanism. In this study, we established a pair of isotope reagent d₀/d₅-2-diazomethyl-N-methyl-phenyl benzamide-labeling-based LC-MS method for the comprehensive analysis of phosphomonoester metabolites. By this method, the labeled phosphomonoester metabolites specifically produced characteristic isotope paired peaks with an m/z difference of 5.0314 in the MS¹ spectra and a pair of diagnostic ions (m/z 320.0693/325.1077) in the MS² spectra. Based on this, a diagnostic ion-based strategy was established for the rapid screening, identification, and relative quantification of phosphomonoester metabolites. Using this strategy, 42 phosphomonoester metabolites were highly accurately identified fromSaccharomyces cerevisiae (S. cerevisiae). Notably, two phosphomonoesters were first detected fromS. cerevisiae. The relative quantification results indicated that the contents of nine phosphomonoester metabolites including two intermediates (Ru5P and S7P) in the pentose phosphate pathway (PPP) were significantly different between lycopene-producible and wild-type S. cerevisiae. A further enzyme assay indicated that the activity of the PPP was closely related to the production of lycopene. Our findings provide new perspectives for the related mechanism study and valuable references for making informed microbial engineering decisions.

Strategies for structure elucidation of small molecules based on LC–MS/MS data from complex biological samples

LC–MS/MS is a major analytical platform for metabolomics, which has become a recent hotspot in the research fields of life and environmental sciences. By contrast, structure elucidation of small molecules based on LC–MS/MS data remains a major challenge in the chemical and biological interpretation of untargeted metabolomics datasets. In recent years, several strategies for structure elucidation using LC–MS/MS data from complex biological samples have been proposed, these strategies can be simply categorized into two types, one based on structure annotation of mass spectra and for the other on retention time prediction. These strategies have helped many scientists conduct research in metabolite-related fields and are indispensable for the development of future tools. Here, we summarized the characteristics of the current tools and strategies for structure elucidation of small molecules based on LC–MS/MS data, and further discussed the directions and perspectives to improve the power of the tools or strategies for structure elucidation.