MobiLipid: A Tool for Enhancing CCS Quality Control of Ion Mobility-Mass Spectrometry Lipidomics by Internal Standardization.

Ion mobility-mass spectrometry (IM-MS) offers benefits for lipidomics by obtaining IM-derived collision cross sections (CCS), a conditional property of an ion that can enhance lipid identification. While drift tube (DT) IM-MS retains a direct link to the primary experimental method to derive CCS values, other IM technologies rely solely on external CCS calibration, posing challenges due to dissimilar chemical properties between lipids and calibrants. To address this, we introduce MobiLipid, a novel tool facilitating the CCS quality control of IM-MS lipidomics workflows by internal standardization. MobiLipid utilizes a newly established DTCCSN2 library for uniformly (U)13C-labeled lipids, derived from a U13C-labeled yeast extract, containing 377 DTCCSN2 values. This automated open-source R Markdown tool enables internal monitoring and straightforward compensation for CCSN2 biases. It supports lipid class- and adduct-specific CCS corrections, requiring only three U13C-labeled lipids per lipid class-adduct combination across 10 lipid classes without requiring additional external measurements. The applicability of MobiLipid is demonstrated for trapped IM (TIM)-MS measurements of an unlabeled yeast extract spiked with U13C-labeled lipids. Monitoring the CCSN2 biases of TIMCCSN2 values compared to DTCCSN2 library entries utilizing MobiLipid resulted in mean absolute biases of 0.78% and 0.33% in positive and negative ionization mode, respectively. By applying the CCS correction integrated into the tool for the exemplary data set, the mean absolute CCSN2 biases of 10 lipid classes could be reduced to approximately 0%.

Protein production dynamics and physiological adaptation of recombinant Komagataella phaffii at near-zero growth rates.

BACKGROUND: Specific productivity (qP) in yeast correlates with growth, typically peaking at intermediate or maximum specific growth rates (µ). Understanding the factors limiting productivity at extremely low µ might reveal decoupling strategies, but knowledge of production dynamics and physiology in such conditions is scarce. Retentostats, a type of continuous cultivation, enable the well-controlled transition to near-zero µ through the combined retention of biomass and limited substrate supply. Recombinant Komagataella phaffii (syn Pichia pastoris) secreting a bivalent single domain antibody (VHH) was cultivated in aerobic, glucose-limited retentostats to investigate recombinant protein production dynamics and broaden our understanding of relevant physiological adaptations at near-zero growth conditions. RESULTS: By the end of the retentostat cultivation, doubling times of approx. two months were reached, corresponding to µ = 0.00047 h-1. Despite these extremely slow growth rates, the proportion of viable cells remained high, and de novo synthesis and secretion of the VHH were observed. The average qP at the end of the retentostat was estimated at 0.019 mg g-1 h-1. Transcriptomics indicated that genes involved in protein biosynthesis were only moderately downregulated towards zero growth, while secretory pathway genes were mostly regulated in a manner seemingly detrimental to protein secretion. Adaptation to near-zero growth conditions of recombinant K. phaffii resulted in significant changes in the total protein, RNA, DNA and lipid content, and lipidomics revealed a complex adaptation pattern regarding the lipid class composition. The higher abundance of storage lipids as well as storage carbohydrates indicates that the cells are preparing for long-term survival. CONCLUSIONS: In conclusion, retentostat cultivation proved to be a valuable tool to identify potential engineering targets to decouple growth and protein production and gain important insights into the physiological adaptation of K. phaffii to near-zero growth conditions.

Airborne Aluminum as an Underestimated Source of Human Exposure: Quantification of Aluminum in 24 Human Tissue Types Reveals High Aluminum Concentrations in Lung and Hilar Lymph Node Tissues.

Aluminum (Al) is the most abundant metal in the earth's crust, and humans are exposed to Al through sources like food, cosmetics, and medication. So far, no comprehensive data on the Al distribution between and within human tissues were reported. We measured Al concentrations in 24 different tissue types of 8 autopsied patients using ICP-MS/MS (inductively coupled plasma-tandem mass spectrometry) under cleanroom conditions and found surprisingly high concentrations in both the upper and inferior lobes of the lung and hilar lymph nodes. Al/Si ratios in lung and hilar lymph node samples of 12 additional patients were similar to the ratios reported in urban fine dust. Histological analyses using lumogallion staining showed Al in lung erythrocytes and macrophages, indicating the uptake of airborne Al in the bloodstream. Furthermore, Al was continuously found in PM2.5 and PM10 fine dust particles over 7 years in Upper Austria, Austria. According to our findings, air pollution needs to be reconsidered as a major Al source for humans and the environment.

Semiquantitative Analysis for High-Speed Mapping Applications of Biological Samples Using LA-ICP-TOFMS.

Laser ablation (LA) in combination with inductively coupled plasma time-of-flight mass spectrometry (ICP-TOFMS) enables monitoring of elements from the entire mass range for every pixel, regardless of the isotopes of interest for a certain application. This provides nontargeted multi-element (bio-)imaging capabilities and the unique possibility to screen for elements that were initially not expected in the sample. Quantification of a large range of elements is limited as the preparation of highly multiplexed calibration standards for bioimaging applications by LA-ICP-(TOF)MS is challenging. In this study, we have developed a workflow for semiquantitative analysis by LA-ICP-TOFMS based on multi-element gelatin micro-droplet standards. The presented approach is intended for the mapping of biological samples due to the requirement of matrix-matched standards for accurate quantification in LA-ICPMS, a prerequisite that is given by the use of gelatin-based standards. A library of response factors was constructed based on 72 elements for the semiquantitative calculations. The presented method was evaluated in two stages: (i) on gelatin samples with known elemental concentrations and (ii) on real-world samples that included prime examples of bioimaging (mouse spleen and tumor tissue). The developed semiquantification approach was based on 10 elements as calibration standards and provided the determination of 136 nuclides of 63 elements, with errors below 25%, and for half of the nuclides, below 10%. A web application for quantification and semiquantification of LA-ICP(-TOF)MS data was developed, and a detailed description is presented to easily allow others to use the presented method.

Homologue series detection and management in LC-MS data with homologueDiscoverer.

SUMMARY: Untargeted metabolomics data analysis is highly labour intensive and can be severely frustrated by both experimental noise and redundant features. Homologous polymer series is a particular case of features that can either represent large numbers of noise features or alternatively represent features of interest with large peak redundancy. Here, we present homologueDiscoverer, an R package that allows for the targeted and untargeted detection of homologue series as well as their evaluation and management using interactive plots and simple local database functionalities. AVAILABILITY AND IMPLEMENTATION: homologueDiscoverer is freely available at GitHub https://github.com/kevinmildau/homologueDiscoverer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Oral Anticancer Heterobimetallic PtIV -AuI Complexes Show High In Vivo Activity and Low Toxicity.

AuI -carbene and PtIV -AuI -carbene prodrugs display low to sub-µM activity against several cancer cell lines and overcome cisplatin (cisPt) resistance. Linking a cisPt-derived PtIV (phenylbutyrate) complex to a AuI -phenylimidazolylidene complex 2, yielded the most potent prodrug. While in vivo tests against Lewis Lung Carcinoma showed that the prodrug PtIV (phenylbutyrate)-AuI -carbene (7) and the 1 : 1 : 1 co-administration of cisPt: phenylbutyrate:2 efficiently inhibited tumor growth (≈95 %), much better than 2 (75 %) or cisPt (84 %), 7 exhibited only 5 % body weight loss compared to 14 % for 2, 20 % for cisPt and >30 % for the co-administration. 7 was much more efficient than 2 at inhibiting TrxR activity in the isolated enzyme, in cells and in the tumor, even though it was much less efficient than 2 at binding to selenocysteine peptides modeling the active site of TrxR. Organ distribution and laser-ablation (LA)-ICP-TOFMS imaging suggest that 7 arrives intact at the tumor and is activated there.

Power of mzRAPP-Based Performance Assessments in MS1-Based Nontargeted Feature Detection.

When performing chromatography-mass spectrometry-based nontargeted metabolomics, or exposomics, one of the key steps in the analysis is to obtain MS1-based feature tables. Inapt parameter settings in feature detection will result in missing or wrong quantitative values and might ultimately lead to downstream incorrect biological interpretations. However, until recently, no strategies to assess the completeness and abundance accuracy of feature tables were available. Here, we show that mzRAPP enables the generation of benchmark peak lists by using an internal set of known molecules in the analyzed data set. Using the benchmark, the completeness and abundance accuracy of feature tables can be assessed in an automated pipeline. We demonstrate that our approach adds to other commonly applied quality assurance methods such as manual or automatized parameter optimization techniques or removal of false-positive signals. Moreover, we show that as few as 10 benchmark molecules can already allow for representative performance metrics to further improve quantitative biological understanding.

Achieving Absolute Molar Lipid Concentrations: A Phospholipidomics Cross-Validation Study.

Standardization is essential in lipidomics and part of a huge community effort. However, with the still ongoing lack of reference materials, benchmarking quantification is hampered. Here, we propose traceable lipid class quantification as an important layer for the validation of quantitative lipidomics workflows. 31P nuclear magnetic resonance (NMR) and inductively coupled plasma (ICP)-mass spectrometry (MS) can use certified species-unspecific standards to validate shotgun or liquid chromatography (LC)-MS-based lipidomics approaches. We further introduce a novel lipid class quantification strategy based on lipid class separation and mass spectrometry using an all ion fragmentation (AIF) approach. Class-specific fragments, measured over a mass range typical for the lipid classes, are integrated to assess the lipid class concentration. The concept proved particularly interesting as low absolute limits of detection in the fmol range were achieved and LC-MS platforms are widely used in the field of lipidomics, while the accessibility of NMR and ICP-MS is limited. Using completely independent calibration strategies, the introduced validation scheme comprised the quantitative assessment of the complete phospholipid sub-ome, next to the individual lipid classes. Komagataella phaffii served as a prime example, showcasing mass balances and supporting the value of benchmarks for quantification at the lipid species level.

Elemental Mapping of Human Malignant Mesothelioma Tissue Samples Using High-Speed LA-ICP-TOFMS Imaging.

This is the first report of the use of laser ablation-inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-TOFMS) to analyze human malignant pleural mesothelioma (MPM) samples at the cellular level. MPM is an aggressive, incurable cancer associated with asbestos exposure, with a long latency and poor overall survival. Following careful optimization of the laser fluence, the simultaneous ablation of soft biological tissue and hard mineral fibers was possible, allowing the spatial detection of elements such as Si, Mg, Ca, and Fe, which are also present in the glass substrate. A low-dispersion LA setup was employed, which provided the high spatial resolution necessary to identify the asbestos fibers and fiber fragments in the tissue and to characterize the metallome at the cellular level (a pixel size of 2 µm), with a high speed (at 250 Hz). The multielement LA-ICP-TOFMS imaging approach enabled (i) the detection of asbestos fibers/mineral impurities within the MPM tissue samples of patients, (ii) the visualization of the tissue structure with the endogenous elemental pattern at high spatial resolution, and (iii) obtaining insights into the metallome of MPM patients with different pathologies in a single analysis run. Asbestos and other mineral fibers were detected in the lung and pleura tissue of MPM patients, respectively, based on their multielement pattern (Si, Mg, Ca, Fe, and Sr). Interestingly, strontium was detected in asbestos fibers, suggesting a link between this potential toxic element and MPM pathogenesis. Furthermore, monitoring the metallome around the talc deposit regions (characterized by elevated levels of Al, Mg, and Si) revealed significant tissue damage and inflammation caused by talc pleurodesis. LA-ICP-TOFMS results correlated to Perls' Prussian blue and histological staining of the corresponding serial sections. Ultimately, the ultra-high-speed and high-spatial-resolution capabilities of this novel LA-ICP-TOFMS setup may become an important clinical tool for simultaneous asbestos detection, metallome monitoring, and biomarker identification.

mzRAPP: a tool for reliability assessment of data pre-processing in non-targeted metabolomics.

SUMMARY: Reliability assessment of automated pre-processing of liquid chromatography-high resolution mass spectrometry data presents a significant challenge. Here, we present a tool named mzRAPP, which generates and validates a benchmark from user-supplied information and later utilizes it for reliability assessment of data pre-processing. As a result, mzRAPP produces several performance metrics for different steps of the pre-processing workflow, supporting five of the most commonly used pre-processing tools. AVAILABILITY AND IMPLEMENTATION: mzRAPP is implemented in R and can be downloaded from GitHub under GNU GPL v.3.0 licence. Extensive documentation, background and examples are available at (https://github.com/YasinEl/mzRAPP). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Accurate characterization of ß-amyloid (Aß40, Aß42) standards using species-specific isotope dilution by means of HPLC-ICP-MS/MS.

The amyloid ß peptide, as one of the main components in senile plaque, represents a defining pathological feature for Alzheimer's disease, and is therefore commonly used as a biomarker for this disease in clinical analysis. However, the selection of suitable standards is limited here, since only a few are commercially available, and these suffer from varying purity. Hence, the accurate characterization of these standards is of great importance. In this study, we developed a method for the traceable quantification of the peptide content using species-specific isotope dilution and ICP-MS/MS detection. It is based on the separation of the sulfur-containing amino acids methionine and cysteine after oxidation and hydrolysis of the peptide. Using a strong anion exchange column, both amino acids could be separated from each other, as well as from their oxidized forms and sulfate. The sulfur content was determined via ICP-MS/MS using oxygen as reaction gas. Species-specific isotope dilution was enabled by using a 34S-labeled yeast hydrolysate, containing methionine sulfone and cysteic acid with different isotopic composition. The peptide contents of Aß standards (Aß40,42), as well as myoglobin and lysozyme with different degrees of purity, were determined. For validation purposes, the standard reference material NIST 2389a, which contains the amino acids in a similar concentration, was subjected to the developed sample preparation and analysis method. In addition to accounting for errors during sample preparation, high levels of accuracy and precision could be obtained using this method, making it fit-for-purpose for the characterization of peptide standards.

Yeast-based reference materials for quantitative metabolomics.

We introduce a new concept of yeast-derived biological matrix reference material for metabolomics research relying on in vivo synthesis of a defined biomass, standardized extraction followed by absolute quantification with isotope dilution. The yeast Pichia pastoris was grown using full control- and online monitoring fed-batch fermentations followed by fast cold methanol quenching and boiling ethanol extraction. Dried extracts served for the quantification campaign. A metabolite panel of the evolutionarily conserved primary metabolome (amino acids, nucleotides, organic acids, and metabolites of the central carbon metabolism) was absolutely quantified by isotope dilution utilizing uniformly labeled 13C-yeast-based internal standards. The study involved two independent laboratories employing complementary mass spectrometry platforms, namely hydrophilic interaction liquid chromatography-high resolution mass spectrometry (HILIC-HRMS) and gas chromatography-tandem mass spectrometry (GC-MS/MS). Homogeneity, stability tests (on a panel of >70 metabolites over a period of 6 months), and excellent biological repeatability of independent fermentations over a period of 2 years showed the feasibility of producing biological reference materials on demand. The obtained control ranges proved to be fit for purpose as they were either superior or comparable to the established reference materials in the field.

Micro-droplet-based calibration for quantitative elemental bioimaging by LA-ICPMS.

In this work, a novel standardization strategy for quantitative elemental bioimaging is evaluated. More specifically, multi-element quantification by laser ablation-inductively coupled plasma-time-of-flight mass spectrometry (LA-ICP-TOFMS) is performed by multi-point calibration using gelatin-based micro-droplet standards and validated using in-house produced reference materials. Fully automated deposition of micro-droplets by micro-spotting ensured precise standard volumes of 400 ± 5 pL resulting in droplet sizes of around 200 µm in diameter. The small dimensions of the micro-droplet standards and the use of a low-dispersion laser ablation setup reduced the analysis time required for calibration by LA-ICPMS significantly. Therefore, as a key advance, high-throughput analysis (pixel acquisition rates of more than 200 Hz) enabled to establish imaging measurement sequences with quality control- and standardization samples comparable to solution-based quantification exercises by ICP-MS. Analytical figures of merit such as limit of detection, precision, and accuracy of the calibration approach were assessed for platinum and for elements with biological key functions from the lower mass range (phosphorus, copper, and zinc). As a proof-of-concept application, the tool-set was employed to investigate the accumulation of metal-based anticancer drugs in multicellular tumor spheroid models at clinically relevant concentrations. Graphical abstract.

Cisplatin Uptake in Macrophage Subtypes at the Single-Cell Level by LA-ICP-TOFMS Imaging.

A high-throughput laser ablation-inductively coupled plasma-time-of-flight mass spectrometry (LA-ICP-TOFMS) workflow was implemented for quantitative single-cell analysis following cytospin preparation of cells. For the first time, in vitro studies on cisplatin exposure addressed human monocytes and monocyte-derived macrophages (undifferentiated THP-1 monocytic cells, differentiated M0 macrophages, as well as further polarized M1 and M2 phenotypes) at the single-cell level. The models are of particular interest as macrophages comprise the biggest part of immune cells present in the tumor microenvironment and play an important role in modulating tumor growth and progression. The introduced bioimaging workflow proved to be universally applicable to adherent and suspension cell cultures and fit-for-purpose for the quantitative analysis of several hundreds of cells within minutes. Both, cross-validation of the method with single-cell analysis in suspension for THP-1 cells and with LA-ICP-TOFMS analysis of adherent M0 cells grown on chambered glass coverslips, revealed agreeing platinum concentrations at the single-cell level. A high incorporation of cisplatin was observed in M2 macrophages compared to the M0 and M1 macrophage subtypes and the monocyte model, THP-1. The combination with bright-field images and monitoring of highly abundant endogenous elements such as phosphorus and sodium at a high spatial resolution allowed assessing cell size and important morphological cell parameters and thus straightforward control over several cell conditions. This way, apoptotic cells and cell debris as well as doublets or cell clusters could be easily excluded prior to data evaluation without additional staining.

STAT3-dependent analysis reveals PDK4 as independent predictor of recurrence in prostate cancer.

Prostate cancer (PCa) has a broad spectrum of clinical behavior; hence, biomarkers are urgently needed for risk stratification. Here, we aim to find potential biomarkers for risk stratification, by utilizing a gene co-expression network of transcriptomics data in addition to laser-microdissected proteomics from human and murine prostate FFPE samples. We show up-regulation of oxidative phosphorylation (OXPHOS) in PCa on the transcriptomic level and up-regulation of the TCA cycle/OXPHOS on the proteomic level, which is inversely correlated to STAT3 expression. We hereby identify gene expression of pyruvate dehydrogenase kinase 4 (PDK4), a key regulator of the TCA cycle, as a promising independent prognostic marker in PCa. PDK4 predicts disease recurrence independent of diagnostic risk factors such as grading, staging, and PSA level. Therefore, low PDK4 is a promising marker for PCa with dismal prognosis.

A combined flow injection/reversed-phase chromatography-high-resolution mass spectrometry workflow for accurate absolute lipid quantification with 13C internal standards.

We propose a fully automated novel workflow for lipidomics based on flow injection, followed by liquid chromatography-high-resolution mass spectrometry (FI/LC-HRMS). The workflow combined in-depth characterization of the lipidome achieved via reversed-phase LC-HRMS with absolute quantification by using a large number of lipid species-specific and/or retention time (RT)-matched/class-specific calibrants. The lipidome of 13C-labelled yeast (LILY) provided a large panel of cost-effective internal standards (ISTDs) covering triacylglycerols (TG), steryl esters (SE), free fatty acids (FA), diacylglycerols (DG), sterols (ST), ceramides (Cer), hexosyl ceramides (HexCer), phosphatidylglycerols (PG), phosphatidylethanolamines (PE), phosphatidic acids (PA), cardiolipins (CL), phosphatidylinositols (PI), phosphatidylserines (PS), phosphatidylcholines (PC), lysophosphatidylcholines (LPC) and lysophosphatidylethanolamines (LPE). The workflow in combination with the LILY lipid panel enables simultaneous quantification via (1) external multi-point calibration with internal standardization and (2) internal one-point calibration with LILY as a surrogate ISTD, increasing the coverage while keeping the accuracy and throughput high. Extensive measures on quality control allowed us to rank the calibration strategies and to automatically select the calibration strategy of the highest metrological order for the respective lipid species. Overall, the workflow enabled a streamlined analysis, with a limit of detection in the low femtomolar range, and provided validation tools together with absolute concentration values for >350 lipids in human plasma on a species level. Based on the selected standard panel, lipids from 7 classes (LPC, LPE, PC, PE, PI, DG, TG) passed stringent quality filters, which included QC accuracy, a precision and recovery bias of <30% and concentrations within the 99% confidence interval of the international laboratory comparison of SRM 1950, NIST, USA. The quantitative values are independent of common deuterated or non-endogenous ISTDs, thus offering cross-validation of different lipid methods and further standardizing lipidomics.

What CHO is made of: Variations in the biomass composition of Chinese hamster ovary cell lines.

BACKGROUND: Cell line-specific, genome-scale metabolic models enable rigorous and systematic in silico investigation of cellular metabolism. Such models have recently become available for Chinese hamster ovary (CHO) cells. However, a key ingredient, namely an experimentally validated biomass function that summarizes the cellular composition, was so far missing. Here, we close this gap by providing extensive experimental data on the biomass composition of 13 parental and producer CHO cell lines under various conditions. RESULTS: We report total protein, lipid, DNA, RNA and carbohydrate content, cell dry mass, and detailed protein and lipid composition. Furthermore, we present meticulous data on exchange rates between cells and environment and provide detailed experimental protocols on how to determine all of the above. The biomass composition is converted into cell line- and condition-specific biomass functions for use in cell line-specific, genome-scale metabolic models of CHO. Finally, flux balance analysis (FBA) is used to demonstrate consistency between in silico predictions and experimental analysis. CONCLUSIONS: Our study reveals a strong variability of the total protein content and cell dry mass across cell lines. However, the relative amino acid composition is independent of the cell line and condition and thus needs not be explicitly measured for each new cell line. In contrast, the lipid composition is strongly influenced by the growth media and thus will have to be determined in each case. These cell line-specific variations in biomass composition have a small impact on growth rate predictions with FBA, as inaccuracies in the predictions are rather dominated by inaccuracies in the exchange rate spectra. Cell-specific biomass variations only become important if the experimental errors in the exchange rate spectra drop below twenty percent.

An Organometallic Gold(I) Bis-N-Heterocyclic Carbene Complex with Multimodal Activity in Ovarian Cancer Cells.

The organometallic AuI bis-N-heterocyclic carbene complex [Au(9-methylcaffeine-8-ylidene)2 ]+ (AuTMX2 ) was previously shown to selectively and potently stabilise telomeric DNA G-quadruplex (G4) structures. This study sheds light on the molecular reactivity and mode of action of AuTMX2 in the cellular context using mass spectrometry-based methods, including shotgun proteomics in A2780 ovarian cancer cells. In contrast to other metal-based anticancer agents, this organogold compound is less prone to form coordinative bonds with biological nucleophiles and is expected to exert its drug effects mainly by non-covalent interactions. Global protein expression changes of treated cancer cells revealed a multimodal mode of action of AuTMX2 by alterations in the nucleolus, telomeres, actin stress-fibres and stress-responses, which were further supported by pharmacological assays, fluorescence microscopy and cellular accumulation experiments. Proteomic data are available via ProteomeXchange with identifier PXD020560.

Synthesis, Modification, and Biological Evaluation of a Library of Novel Water-Soluble Thiopyridone-Based Organometallic Complexes and Their Unexpected (Biological) Behavior.

A series of 16 dinuclear thiopyridone-based organometallics with excellent water solubility, increased stability and remarkable cytotoxicity were synthesized and characterized. The complexes of this work formed dimeric species featuring a double positive charge in polar protic solvents, accounting for their outstanding solubility in aqueous solution. Most of them displayed higher antiproliferative activity than their parental thiomaltol complex, with unexpected cytotoxicity trends depending on the employed metal center, ligand modification, and cell line. Insights into their behavior in biological systems were gathered by means of amino-acid interaction studies, cytotoxicity tests in 3D spheroid models, laser ablation, cellular accumulation measurements, as well as cell cycle experiments.

Preparative supercritical fluid chromatography for lipid class fractionation-a novel strategy in high-resolution mass spectrometry based lipidomics.

In this work, a lipidomics workflow based on offline semi-preparative lipid class-specific fractionation by supercritical fluid chromatography (SFC) followed by high-resolution mass spectrometry was introduced. The powerful SFC approach offered separation of a wide polarity range for lipids, enabled enrichment (up to 3 orders of magnitude) of lipids, selective fractionation of 14 lipid classes/subclasses, and increased dynamic range enabling in-depth characterization. A significantly increased coverage of low abundant lipids improving lipid identification by numbers and degree (species and molecular level) was obtained in Pichia pastoris when comparing high-resolution mass spectrometry based lipidomics with and without prior fractionation. Proof-of-principle experiments using a standard reference material (SRM 1950, NIST) for human plasma showed that the proposed strategy enabled quantitative lipidomics. Indeed, for 70 lipids, the consensus values available for this sample could be met. Thus, the novel workflow is ideally suited for lipid class-specific purification/isolation from milligram amounts of sample while not compromising on omics type of analysis (identification and quantification). Finally, compared with established fractionation/pre-concentration approaches, semi-preparative SFC is superior in terms of versatility, as it involved only volatile modifiers and salt additives facilitating any follow-up use such as qualitative or quantitate analysis or further purification down to the single lipid species level. Graphical Abstract.