bims-metlip 2021-11-14 papers

bims-metlip

Biomed News

on Methods and protocols in metabolomics and lipidomics

Issue of 2021–11–14
thirteen papers selected by
Sofia Costa, Icahn School of Medicine at Mount Sinai

Development and Validation of a LC-MS/MS Technique for the Analysis of Short Chain Fatty Acids in Tissues and Biological Fluids without Derivatisation Using Isotope Labelled Internal Standards.
Enantioselective metabolomics by liquid chromatography-mass spectrometry.
Mining plant metabolomes: Methods, applications, and perspectives.
Enhanced On-Tissue Chemical Derivatization with Hydrogel Assistance for Mass Spectrometry Imaging.
High-resolution imaging and identification of biomolecules using Nano-DESI coupled to ion mobility spectrometry.
Extraction of small molecule from human plasma by prototyping 3D printed sorbent through extruded filament for LC-MS/MS analysis.
Practical aspect of dimer adduct formation in small-molecule drug analysis with LC-MS/MS.
A developed HPLC-MS/MS method to quantitate 5 steriod hormones in clinical human serum by using PBS as the surrogate matrix.
Structural Characterization of Unusual Fatty Acid Methyl Esters with Double and Triple Bonds Using HPLC/APCI-MS2 with Acetonitrile In-Source Derivatization.
Quantitative Hydrogen/Deuterium Exchange Mass Spectrometry.
Development and evaluation of a simultaneous strategy for pyrimidine metabolome quantification in multiple biological samples.
Improved Metabolite Prediction Using Microbiome Data-Based Elastic Net Models.
Development of simultaneous quantitative analysis of tricarboxylic acid cycle metabolites to identify specific metabolites in cancer cells by targeted metabolomic approach.

Molecules. 2021 Oct 26. pii: 6444. [Epub ahead of print]26(21):

Development and Validation of a LC-MS/MS Technique for the Analysis of Short Chain Fatty Acids in Tissues and Biological Fluids without Derivatisation Using Isotope Labelled Internal Standards.

Shikha Saha, Priscilla Day-Walsh, Emad Shehata, Paul Anthony Kroon.

  The gut microbiota is critical to the maintenance of physiological homeostasis and as such is implicated in a range of diseases such as colon cancer, ulcerative colitis, diabetes, cardiovascular diseases, and neurodegenerative diseases. Short chain fatty acids (SCFAs) are key metabolites produced by the gut microbiota from the fermentation of dietary fibre. Here we present a novel, sensitive, and direct LC-MS/MS technique using isotopically labelled internal standards without derivatisation for the analysis of SCFAs in different biological matrices. The technique has significant advantages over the current widely used techniques based on sample derivatization and GC-MS analysis, including fast and simple sample preparation and short LC runtime (10 min). The technique is specific and sensitive for the quantification of acetate, butyrate, isobutyrate, isovalerate, lactate, propionate and valerate. The limits of detection were all 0.001 mM except for acetate which was 0.003 mM. The calibration curves for all the analytes were linear with correlation coefficients r2 > 0.998. The intra- and inter-day precisions in three levels of known concentrations were <12% and <20%, respectively. The quantification accuracy ranged from 92% to 120%. The technique reported here offers a valuable analytical tool for use in studies of SCFA production in the gut and their distribution to host tissues.

Keywords:  acetate; butyrate; cardiovascular; diabetes; gut microbiota; kidney; lactate; milk; neurodegenerative; plasma; propionate

DOI:  https://doi.org/10.3390/molecules26216444
J Pharm Biomed Anal. 2022 Jan 05. pii: S0731-7085(21)00541-0. [Epub ahead of print]207 114430

Enantioselective metabolomics by liquid chromatography-mass spectrometry.

Carlos Calderón, Michael Lämmerhofer.

  Metabolomics strives to capture the entirety of the metabolites in a biological system by comprehensive analysis, often by liquid chromatography hyphenated to mass spectrometry. A particular challenge thereby is the differentiation of structural isomers. Common achiral targeted and untargeted assays do not distinguish between enantiomers. This may lead to information loss. An increasing number of publications demonstrate that the enantiomeric ratio of certain metabolites can be meaningful biomarkers of certain diseases emphasizing the importance of introducing enantioselective analytical procedures in metabolomics. In this work, the state-of-the-art in the field of LC-MS based metabolomics is summarized with focus on developments in the recent decade. Methodologies, tagging strategies, workflows and general concepts are outlined. Selected biological applications in which enantioselective metabolomics has documented its usefulness are briefly discussed. In general, targeted enantioselective metabolomics assays are often based on a direct approach using chiral stationary phases (CSP) with polysaccharide derivatives, macrocyclic antibiotics, chiral crown ethers, chiral ion exchangers, donor-acceptor phases as chiral selectors. Rarely, these targeted assays focus on more than 20 analytes and usually are restricted to a certain metabolite class. In a variety of cases, pre-column derivatization of metabolites has been performed, especially for amino acids, to improve separation and detection sensitivity. Triple quadrupole instruments are the detection methods of first choice in targeted assays. Here, issues like matrix effect, absence of blank matrix impair accuracy of results. In selected applications, multiple heart cutting 2D-LC (RP followed by chiral separation) has been pursued to overcome this problem and alleviate bias due to interferences. Non-targeted assays, on the other hand, are based on indirect approach involving tagging with a chiral derivatizing agent (CDA). Besides classical CDAs numerous innovative reagents and workflows have been proposed and are discussed. Thereby, a critical issue for the accuracy is often neglected, viz. the validation of the enantiomeric impurity in the CDA. The majority of applications focus on amino acids, hydroxy acids, oxidized fatty acids and oxylipins. Some potential clinical applications are highlighted.

Keywords:  Amino acid; Chiral derivatizing agent; Chiral separation; Chiral stationary phase; Mass tag; Oxylipin

DOI:  https://doi.org/10.1016/j.jpba.2021.114430
Plant Commun. 2021 Sep 13. 2(5): 100238

Mining plant metabolomes: Methods, applications, and perspectives.

Aimin Ma, Xiaoquan Qi.

  Plants produce a variety of metabolites that are essential for plant growth and human health. To fully understand the diversity of metabolites in certain plants, lots of methods have been developed for metabolites detection and data processing. In the data-processing procedure, how to effectively reduce false-positive peaks, analyze large-scale metabolic data, and annotate plant metabolites remains challenging. In this review, we introduce and discuss some prominent methods that could be exploited to solve these problems, including a five-step filtering method for reducing false-positive signals in LC-MS analysis, QPMASS for analyzing ultra-large GC-MS data, and MetDNA for annotating metabolites. The main applications of plant metabolomics in species discrimination, metabolic pathway dissection, population genetic studies, and some other aspects are also highlighted. To further promote the development of plant metabolomics, more effective and integrated methods/platforms for metabolite detection and comprehensive databases for metabolite identification are highly needed. With the improvement of these technologies and the development of genomics and transcriptomics, plant metabolomics will be widely used in many fields.

Keywords:  application; data-processing methods; metabolites; plant metabolomics

DOI:  https://doi.org/10.1016/j.xplc.2021.100238
Anal Chem. 2021 Nov 08.

Enhanced On-Tissue Chemical Derivatization with Hydrogel Assistance for Mass Spectrometry Imaging.

Qingce Zang, Manjiangcuo Wang, Ying Zhu, Lingzhi Wang, Zhigang Luo, Xin Li, Jiuming He, Ruiping Zhang, Zeper Abliz.

The improvement of on-tissue chemical derivatization for mass spectrometry imaging (MSI) of low-abundance and/or poorly ionizable functional molecules in biological tissue without delocalization is challenging. Here, we developed a novel hydrogel-assisted chemical derivatization (HCD) approach coupled with airflow-assisted desorption electrospray ionization (AFADESI)-MSI, allowing for enhanced visualization of inaccessible molecules in biological tissues. The derivatization reagent Girard's P (GP) reagent was creatively packaged into a hydrogel to form HCD blocks that have reactivity to carbonyl compounds as well as the feasibility of "cover/uncover" contact mode with tissue sections. The HCD blocks provided a favorable liquid microenvironment for the derivatization reaction and reduced matrix effects from derivatization reagents and tissue without obvious molecular migration, thus improving the derivatization efficiency. With this methodology, unusual carbonyl metabolites, including 166 fatty aldehydes (FALs) and 100 oxo fatty acids (FAs), were detected and visualized in rat brain, kidney, and liver tissue. This study provides a new approach to enhance chemical labeling for in situ tissue submetabolome profiling and improves our knowledge of the molecular histology and complex metabolism of biological tissues.

DOI: https://doi.org/10.1021/acs.analchem.1c03118
Anal Chim Acta. 2021 Nov 22. pii: S0003-2670(21)00911-9. [Epub ahead of print]1186 339085

High-resolution imaging and identification of biomolecules using Nano-DESI coupled to ion mobility spectrometry.

Daisy Unsihuay, Ruichuan Yin, Daniela Mesa Sanchez, Manxi Yang, Yingju Li, Xiaofei Sun, Sudhansu K Dey, Julia Laskin.

  Simultaneous spatial localization and structural characterization of molecules in complex biological samples currently represents an analytical challenge for mass spectrometry imaging (MSI) techniques. In this study, we describe a novel experimental platform, which substantially expands the capabilities and enhances the depth of chemical information obtained in high spatial resolution MSI experiments performed using nanospray desorption electrospray ionization (nano-DESI). Specifically, we designed and constructed a portable nano-DESI MSI platform and coupled it with a drift tube ion mobility (IM) spectrometer-mass spectrometer. We demonstrate imaging of drift time-separated ions with a high spatial resolution of better than ∼25 μm using uterine tissues on day 4 of pregnancy in mice. Collision cross-section measurements provide unique molecular descriptors of molecules observed in nano-DESI-IM-MSI necessary for their unambiguous identification by comparison with databases. Meanwhile, isomer-specific imaging reveals variations in the isomeric composition across the tissue. Furthermore, IM separation efficiently eliminates isobaric and isomeric interferences originating from solvent peaks, overlapping isotopic peaks of endogenous molecules extracted from the tissue, and products of in-source fragmentation, which is critical to obtaining accurate concentration gradients in the sample using MSI. The structural information provided by the IM separation substantially expands the molecular specificity of high-resolution MSI necessary for unraveling the complexity of biological systems.

Keywords:  Collision cross section; Ion mobility spectrometry; Isomeric separation; Lipidomics; Mass spectrometry imaging

DOI:  https://doi.org/10.1016/j.aca.2021.339085
Anal Chim Acta. 2021 Dec 01. pii: S0003-2670(21)00968-5. [Epub ahead of print]1187 339142

Extraction of small molecule from human plasma by prototyping 3D printed sorbent through extruded filament for LC-MS/MS analysis.

Daya Raju Adye, Srikanth Ponneganti, Tushar Kanti Malakar, Pullapanthula Radhakrishnanand, Upadhyayula Suryanarayana Murty, Subham Banerjee, Roshan M Borkar.

  Analytical sample preparation techniques are regarded as crucial steps for analyzing compounds from different biological matrices. The development of new extraction techniques is a modern trend in the bioanalytical sciences. 3D printed techniques have emerged as a valuable technology for prototyping devices in customized shapes for a cost-effective way to advance analytical sample preparation techniques. The present study aims to fabricate customized filaments through the hot-melt extrusion (HME) technique followed by fused deposition modeling mediated 3D printing process for rapid prototyping of 3D printed sorbents to extract a sample from human plasma. Thus, we fabricated our own indigenous filament using poly (vinyl alcohol), Eudragit® RSPO, and tri-ethyl citrate through HME to prototype the fabricated filament into a 3D printed sorbent for the extraction of small molecules. The 3D sorbent was applied to extract hydrocortisone from human plasma and analyzed using a validated LC-MS/MS method. The extraction procedure was optimized, and the parameters influencing the sorbent extraction were systematically investigated. The extraction recovery of hydrocortisone was found to be >82% at low, medium, and high quality control samples, with a relative standard deviation of <2%. The intra-and inter-day precisions for hydrocortisone ranged from 1.0% to 12% and 2.0%-10.0%, respectively, whereas the intra-and inter-day accuracy for hydrocortisone ranged from 93.0% to 111.0% and 92.0% to 110.0%, respectively. The newly customizable size and shape of the 3D printed sorbent opens new possibilities for extracting small molecules from human plasma.

Keywords:  3D printed sorbent; Extruded filament; Fused-deposition modeling; LC-MS/MS

DOI:  https://doi.org/10.1016/j.aca.2021.339142
Bioanalysis. 2021 Nov;13(22): 1671-1679

Practical aspect of dimer adduct formation in small-molecule drug analysis with LC-MS/MS.

Marek Dziadosz, Michael Klintschar, Jörg Teske.

  Aim: Since the MS/MS based detection of small-molecule drugs with poor or even no ion fragmentation is a challenge in bioanalysis, alternative MS/MS detection strategies were in focus of this study and applied in the field of forensic toxicology. Material & methods: Analyte quantification with liquid chromatography-tandem mass spectrometry of problematic drugs was studied by the application of dimer adduct formation and valproic acid (VPA) was used as a model drug. VPA adduct ions could be identified during infusion experiments and the VPA dimer adduct ion was optimized for the detection. Conclusion: Dimer adduct ion formation can be used as an effective way of VPA quantification in human serum. Further, the parallel detection of dimer adduct ions with other adduct ion types can be stated as advantage in LC-MS/MS analysis of problematic drugs.

Keywords:  LC-MS/MS; adduct formation; adduct fragmentation; adduct quantification; dimer formation; quadratic calibration; valproic acid

DOI:  https://doi.org/10.4155/bio-2021-0165
J Chromatogr B Analyt Technol Biomed Life Sci. 2021 Oct 26. pii: S1570-0232(21)00483-9. [Epub ahead of print]1186 123002

A developed HPLC-MS/MS method to quantitate 5 steriod hormones in clinical human serum by using PBS as the surrogate matrix.

Dongke Liu, Rusong Zhao, Shigang Zhao, Zhaobao Wang, Ruichen Liu, Fengshan Wang, Yanhui Gao.

  Steroid hormones play an essential role in regulating physiological and reproductive development throughout the lifetime of an individual. One of the difficulties in determining endogenous substances is the lack of a blank matrix. Especially when the level of analytes is lower than the level in the so-called blank matrix. In the present study, an optimized HPLC-MS/MS method was developed and validated to quantify androstenedione (ASD), testosterone (Ts), dehydroepiandrosterone (DHEA), 5α-dihydrotestosterone (DHT), and progesterone (P) in serum samples from healthy people using PBS (pH = 7.4) as the blank surrogate matrix. Simultaneously, the method investigated the characteristics of NaCl, bull serum albumin, pure water as surrogate matrices for the analysis of steroid hormones. The data showed that the matrix effects of ASD, Ts, DHEA, DHT, and P in the same groups were not significantly different between PBS and twice charcoal-stripped serum (CS2S) as a blank surrogate matrix. Furthermore, the LLOQ using PBS as the blank matrix was up to 0.005 ng/mL for ASD, Ts, and P and 0.05 ng/mL for DHEA and DHT. The reference ranges of concentration (CPBS) of 5 steroid hormones were provided. Compared to the concentration with CS2S (CCSS) as the blank surrogate matrix, the relative biases (RBs) of Ts, DHT, P, and DHEA were finally stabilized at approximately -0.7%, -15%, -1.2%, and 9.2%, respectively. The results suggest that, in the cases of special required, the developed HPLC-MS/MS method can be used to determine the absolute concentration of 5 hormones in biological samples with PBS as the blank surrogate matrix.

Keywords:  HPLC-MS/MS; Human serum; PBS; Quantitation; Steroid hormones; Surrogate matrix

DOI:  https://doi.org/10.1016/j.jchromb.2021.123002
Molecules. 2021 Oct 26. pii: 6468. [Epub ahead of print]26(21):

Structural Characterization of Unusual Fatty Acid Methyl Esters with Double and Triple Bonds Using HPLC/APCI-MS2 with Acetonitrile In-Source Derivatization.

Petra Horká, Vladimír Vrkoslav, Jiří Kindl, Karolina Schwarzová-Pecková, Josef Cvačka.

  Double and triple bonds have significant effects on the biological activities of lipids. Determining multiple bond positions in their molecules by mass spectrometry usually requires chemical derivatization. This work presents an HPLC/MS method for pinpointing the double and triple bonds in fatty acids. Fatty acid methyl esters were separated by reversed-phase HPLC with an acetonitrile mobile phase. In the APCI source, acetonitrile formed reactive species, which added to double and triple bonds to form [M + C3H5N]+• ions. Their collisional activation in an ion trap provided fragments helpful in localizing the multiple bond positions. This approach was applied to fatty acids with isolated, cumulated, and conjugated double bonds and triple bonds. The fatty acids were isolated from the fat body of early-nesting bumblebee Bombus pratorum and seeds or seed oils of Punicum granatum, Marrubium vulgare, and Santalum album. Using the method, the presence of the known fatty acids was confirmed, and new ones were discovered.

Keywords:  acetonitrile-related adducts; acetylenic lipids; double and triple bond localization; in-source derivatization; mass spectrometry

DOI:  https://doi.org/10.3390/molecules26216468
J Am Soc Mass Spectrom. 2021 Nov 08.

Quantitative Hydrogen/Deuterium Exchange Mass Spectrometry.

Yoshitomo Hamuro.

  This Account describes considerations for the data generation, data analysis, and data interpretation of a hydrogen/deuterium exchange-mass spectrometry (HDX-MS) experiment to have a quantitative argument. Although HDX-MS has gained its popularity as a biophysical tool, the argument from its data often remains qualitative. To generate HDX-MS data that are more suitable for a quantitative argument, the sequence coverage and sequence resolution should be optimized during the feasibility stage, and the time window coverage and time window resolution should be improved during the HDX stage. To extract biophysically meaningful values for a certain perturbation from medium-resolution HDX-MS data, there are two major ways: (i) estimating the area between the two deuterium buildup curves using centroid values with and without the perturbation when plotted against log time scale and (ii) dissecting into multiple single-exponential curves using the isotope envelopes. To have more accurate arguments for an HDX-MS perturbation study, (i) false negatives due to sequence coverage, (ii) false negatives due to time window coverage, (iii) false positives due to sequence resolution, and (iv) false positives due to allosteric effects should be carefully examined.

Keywords:  hydrogen/deuterium exchange; isotope envelope; mass spectrometry; quantitative

DOI:  https://doi.org/10.1021/jasms.1c00216
Food Chem. 2021 Oct 14. pii: S0308-8146(21)02411-0. [Epub ahead of print]373(Pt A): 131405

Development and evaluation of a simultaneous strategy for pyrimidine metabolome quantification in multiple biological samples.

Feng Xu, Yuanyuan Pang, Qixing Nie, Zhipeng Zhang, Chuan Ye, Changtao Jiang, Yuan Wang, Huiying Liu.

  Pyrimidines are critical nutrients and key biomolecules in nucleic acid biosynthesis and carbohydrate and lipid metabolism. Here, we proposed the concept of the pyrimidine metabolome, which covers 14 analytes in pyrimidine de novo and salvage synthetic pathways, and established a novel analytical strategy with ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) to efficiently illustrate pyrimidine transient distribution and dynamic balance. The lower limits of quantification (LLOQs) of all analytes were less than 10 ng/mL. Acceptable inter- and intra-day relative deviation (<15%) was detected, and good stability was obtained under different storage conditions. Metabolomics analysis revealed pyrimidine metabolic diversity in the plasma and brain among species, and a visualization strategy exhibited that pyrimidine biosynthetic metabolism is quite active in brain. Distinct metabolic features were also observed in cells with pyrimidine metabolomic disorders during proliferation and apoptosis. Absolute concentrations of pyrimidine metabolites in different bio-samples offered reference data for future pyrimidine studies.

Keywords:  Absolute quantification strategy; Cell proliferation and apoptosis; De novo pyrimidine biosynthesis; LC-MS/MS; Pyrimidine metabolome; Species difference

DOI:  https://doi.org/10.1016/j.foodchem.2021.131405
Front Cell Infect Microbiol. 2021 ;11 734416

Improved Metabolite Prediction Using Microbiome Data-Based Elastic Net Models.

Jialiu Xie, Hunyong Cho, Bridget M Lin, Malvika Pillai, Lara H Heimisdottir, Dipankar Bandyopadhyay, Fei Zou, Jeffrey Roach, Kimon Divaris, Di Wu.

  Microbiome data are becoming increasingly available in large health cohorts, yet metabolomics data are still scant. While many studies generate microbiome data, they lack matched metabolomics data or have considerable missing proportions of metabolites. Since metabolomics is key to understanding microbial and general biological activities, the possibility of imputing individual metabolites or inferring metabolomics pathways from microbial taxonomy or metagenomics is intriguing. Importantly, current metabolomics profiling methods such as the HMP Unified Metabolic Analysis Network (HUMAnN) have unknown accuracy and are limited in their ability to predict individual metabolites. To address this gap, we developed a novel metabolite prediction method, and we present its application and evaluation in an oral microbiome study. The new method for predicting metabolites using microbiome data (ENVIM) is based on the elastic net model (ENM). ENVIM introduces an extra step to ENM to consider variable importance (VI) scores, and thus, achieves better prediction power. We investigate the metabolite prediction performance of ENVIM using metagenomic and metatranscriptomic data in a supragingival biofilm multi-omics dataset of 289 children ages 3-5 who were participants of a community-based study of early childhood oral health (ZOE 2.0) in North Carolina, United States. We further validate ENVIM in two additional publicly available multi-omics datasets generated from studies of gut health. We select gene family sets based on variable importance scores and modify the existing ENM strategy used in the MelonnPan prediction software to accommodate the unique features of microbiome and metabolome data. We evaluate metagenomic and metatranscriptomic predictors and compare the prediction performance of ENVIM to the standard ENM employed in MelonnPan. The newly developed ENVIM method showed superior metabolite predictive accuracy than MelonnPan when trained with metatranscriptomics data only, metagenomics data only, or both. Better metabolite prediction is achieved in the gut microbiome compared with the oral microbiome setting. We report the best-predictable compounds in all these three datasets from two different body sites. For example, the metabolites trehalose, maltose, stachyose, and ribose are all well predicted by the supragingival microbiome.

Keywords:  elastic net; metabolome; metagenomics; metatranscriptome; microbiome; prediction; random forest

DOI:  https://doi.org/10.3389/fcimb.2021.734416
Biochem Biophys Res Commun. 2021 Nov 05. pii: S0006-291X(21)01495-9. [Epub ahead of print]584 53-59

Development of simultaneous quantitative analysis of tricarboxylic acid cycle metabolites to identify specific metabolites in cancer cells by targeted metabolomic approach.

Tetsushi Yamamoto, Kanta Sato, Masafumi Yamaguchi, Kuniko Mitamura, Atsushi Taga.

  The tricarboxylic acid (TCA) cycle is one of the most important pathways of energy metabolism, and the profiles of its components are influenced by factors such as diseases and diets. Therefore, the differences in metabolic profile of TCA cycle between healthy and cancer cells have been the focus of studies to understand pathological conditions. In this study, we developed a quantitative method to measure TCA cycle metabolites using LC-MS/MS to obtain useful metabolic profiles for development of diagnostic and therapeutic methods for cancer. We successfully analyzed 11 TCA cycle metabolites by LC MS/MS with high reproducibility by using a PFP column with 0.5% formic acid as a mobile phase. Next, we analyzed the concentration of TCA cycle metabolites in human cell lines (HaCaT: normal skin keratinocytes; A431: skin squamous carcinoma cells; SW480: colorectal cancer cells). We observed reduced concentration of succinate and increased concentration of citrate, 2-hydroxyglutarate, and glutamine in A431 cells as compared with HaCaT cells. On the other hand, decreased concentration of isocitrate, fumarate, and α-ketoglutarate and increased concentration of malate, glutamine, and glutamate in A431 cells were observed in comparison with SW480 cells. These findings suggested the possibility of identifying disease-specific metabolites and/or organ-specific metabolites by using this targeted metabolomic analysis.

Keywords:  Cancer; Energy metabolism; LC-MS; TCA cycle; Targeted metabolomics

DOI:  https://doi.org/10.1016/j.bbrc.2021.10.072