Advances in analytical tools and current statistical methods used in ultra-high-performance liquid chromatography-mass spectrometry of glycero-, glycerophospho- and sphingolipids

Avela, Henri F.; Sirén, Heli M. M.

doi:10.1016/j.ijms.2020.116408

Cited by 7 publications

(8 citation statements)

References 133 publications

(319 reference statements)

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“…LC-MS is the most frequently used tandem of analytical techniques used in lipid analysis, especially in lipidomics [21]. Previously, thin-layer chromatography (TLC) or high-performance thin-layer chromatography (HPTLC) were also used, but nowadays, high-performance liquid chromatography (HPLC) or ultra-high-performance liquid chromatography (UHPLC) utilizing capillary or nano-columns are the most commonly used platforms of LC [127,128]. In LC/MS spectra, data can be collected in positive or negative ESI ionization modes, or more rarely polarity switching ionization mode.…”

Section: Lc-msmentioning

confidence: 99%

“…Nowadays, it is typical to use hybrid mass analyzers such as Orbitrap, QTOF or even combined quadrupole with Orbitrap (Q-Orbitrap). Development of these analyzers greatly improves the identification [127,129]. In the case of quantitative analysis of lipids, use of QqQ is typical [67].…”

Section: Lc-msmentioning

confidence: 99%

“…Separations are preferably performed in reversed-phase (RP) mode utilizing a stationary phase with different alkyl chains (C8, C18, C30, etc. ), which is suitable for the majority of lipid classes [25,56,127]. Composition of mobile phase is an important factor in lipid analysis.…”

Section: Lc-msmentioning

confidence: 99%

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Recent Analytical Methodologies in Lipid Analysis

Gerhardtova,

Jankech,

Majerova

et al. 2024

IJMS

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Lipids represent a large group of biomolecules that are responsible for various functions in organisms. Diseases such as diabetes, chronic inflammation, neurological disorders, or neurodegenerative and cardiovascular diseases can be caused by lipid imbalance. Due to the different stereochemical properties and composition of fatty acyl groups of molecules in most lipid classes, quantification of lipids and development of lipidomic analytical techniques are problematic. Identification of different lipid species from complex matrices is difficult, and therefore individual analytical steps, which include extraction, separation, and detection of lipids, must be chosen properly. This review critically documents recent strategies for lipid analysis from sample pretreatment to instrumental analysis and data interpretation published in the last five years (2019 to 2023). The advantages and disadvantages of various extraction methods are covered. The instrumental analysis step comprises methods for lipid identification and quantification. Mass spectrometry (MS) is the most used technique in lipid analysis, which can be performed by direct infusion MS approach or in combination with suitable separation techniques such as liquid chromatography or gas chromatography. Special attention is also given to the correct evaluation and interpretation of the data obtained from the lipid analyses. Only accurate, precise, robust and reliable analytical strategies are able to bring complex and useful lipidomic information, which may contribute to clarification of some diseases at the molecular level, and may be used as putative biomarkers and/or therapeutic targets.

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Section: Lc-msmentioning

confidence: 99%

Section: Lc-msmentioning

confidence: 99%

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Recent Analytical Methodologies in Lipid Analysis

Gerhardtova,

Jankech,

Majerova

et al. 2024

IJMS

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“…Today, although many new algorithms have appeared for mass spectra from direct analysis in real time-mass spectrometry (DART-MS) , and MS/MS data, ,− the most widely used mass spectral comparison algorithm for GC–MS data is probably the NIST similarity search algorithm, which is an adaptation of the simple dot product, r , or cosine angle between two spectra r false( dot product false) = A · B ∥ italicA ∥ ∥ italicAB ∥ = ∑ i = 1 n A i B i ∑ i = 1 n A i 2 ∑ i = 1 n B i 2 where A and B are n -dimensional vectors of spectral abundances, A i is the i th element of vector A , and B i is the i th element of vector B . Typically, A and B have dimensionality defined by the number of selected m / z values in the spectra, and they take values of normalized abundances between 0 and 100.…”

Section: Introductionmentioning

confidence: 99%

Expert Algorithm for Substance Identification Using Mass Spectrometry: Application to the Identification of Cocaine on Different Instruments Using Binary Classification Models

Mehnert

Davidson

Adeoye

et al. 2023

J. Am. Soc. Mass Spectrom.

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This is the second of two manuscripts describing how general linear modeling (GLM) of a selection of the most abundant normalized fragment ion abundances of replicate mass spectra from one laboratory can be used in conjunction with binary classifiers to enable specific and selective identifications with reportable error rates of spectra from other laboratories. Here, the proof-of-concept uses a training set of 128 replicate cocaine spectra from one crime laboratory as the basis of GLM modeling. GLM models for the 20 most abundant fragments of cocaine were then applied to 175 additional test/validation cocaine spectra collected in more than a dozen crime laboratories and 716 known negative spectra, which included 10 spectra of three diastereomers of cocaine. Spectral similarity and dissimilarity between the measured and predicted abundances were assessed using a variety of conventional measures, including the mean absolute residual and NIST's spectral similarity score. For each spectral measure, GLM predictions were compared to the traditional exemplar approach, which used the average of the cocaine training set as the consensus spectrum for comparisons. In unsupervised models, EASI provided better than a 95% true positive rate for cocaine with a 0% false positive rate. A supervised binary logistic regression model provided 100% accuracy and no errors using EASI-predicted abundances of only four peaks at m/z 152, 198, 272, and 303. Regardless of the measure of spectral similarity, error rates for identifications using EASI were superior to the traditional exemplar/consensus approach. As a supervised binary classifier, EASI was more reliable than using Mahalanobis distances.

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“…Fast separation results in high operating pressure, which places a massive load on HPLC instrumentation [ 1 ]. Furthermore, higher selectivity and sensitivity are advantages of using UHPLC in analytical chromatography [ 2 ]. Unfortunately, the use of UHPLC is counteracted by some of its limitations such as low peak area repeatability values due to the small injection volumes, high difficulty in packing of the tiny sub-2 µm particle columns, and the short column lifetime, which may be attributed to the high back pressure [ 3 , 4 ].…”

Section: Introductionmentioning

confidence: 99%

Development and Validation of a Chiral Liquid Chromatographic Assay for Enantiomeric Separation and Quantification of Verapamil in Rat Plasma: Stereoselective Pharmacokinetic Application

et al. 2021

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A novel, fast and sensitive enantioselective HPLC assay with a new core–shell isopropyl carbamate cyclofructan 6 (superficially porous particle, SPP) chiral column (LarihcShell-P, LSP) was developed and validated for the enantiomeric separation and quantification of verapamil (VER) in rat plasma. The polar organic mobile phase composed of acetonitrile/methanol/trifluoroacetic acid/triethylamine (98:2:0.05: 0.025, v/v/v/v) and a flow rate of 0.5 mL/min was applied. Fluorescence detection set at excitation/emission wavelengths 280/313 nm was used and the whole analysis process was within 3.5 min, which is 10-fold lower than the previous reported HPLC methods in the literature. Propranolol was selected as the internal standard. The S-(−)- and R-(+)-VER enantiomers with the IS were extracted from rat plasma by utilizing Waters Oasis HLB C18 solid phase extraction cartridges without interference from endogenous compounds. The developed assay was validated following the US-FDA guidelines over the concentration range of 1–450 ng/mL (r2 ≥ 0.997) for each enantiomer (plasma) and the lower limit of quantification was 1 ng/mL for both isomers. The intra- and inter-day precisions were not more than 11.6% and the recoveries of S-(−)- and R-(+)-VER at all quality control levels ranged from 92.3% to 98.2%. The developed approach was successfully applied to the stereoselective pharmacokinetic study of VER enantiomers after oral administration of 10 mg/kg racemic VER to Wistar rats. It was found that S-(−)-VER established higher Cmax and area under the concentration-time curve (AUC) values than the R-(+)-enantiomer. The newly developed approach is the first chiral HPLC for the enantiomeric separation and quantification of verapamil utilizing a core–shell isopropyl carbamate cyclofructan 6 chiral column in rat plasma within 3.5 min after solid phase extraction (SPE).

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Advances in analytical tools and current statistical methods used in ultra-high-performance liquid chromatography-mass spectrometry of glycero-, glycerophospho- and sphingolipids

Abstract: Advances in analytical tools and current statistical methods used in ultra-highperformance liquid chromatography-mass spectrometry of glycero-, glycerophosphoand sphingolipids

Cited by 7 publications

References 133 publications

Recent Analytical Methodologies in Lipid Analysis

Recent Analytical Methodologies in Lipid Analysis

Expert Algorithm for Substance Identification Using Mass Spectrometry: Application to the Identification of Cocaine on Different Instruments Using Binary Classification Models

Development and Validation of a Chiral Liquid Chromatographic Assay for Enantiomeric Separation and Quantification of Verapamil in Rat Plasma: Stereoselective Pharmacokinetic Application

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