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.

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.

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.

The Power of LC-MS Based Multiomics: Exploring Adipogenic Differentiation of Human Mesenchymal Stem/Stromal Cells.

The molecular study of fat cell development in the human body is essential for our understanding of obesity and related diseases. Mesenchymal stem/stromal cells (MSC) are the ideal source to study fat formation as they are the progenitors of adipocytes. In this work, we used human MSCs, received from surgery waste, and differentiated them into fat adipocytes. The combination of several layers of information coming from lipidomics, metabolomics and proteomics enabled network analysis of the biochemical pathways in adipogenesis. Simultaneous analysis of metabolites, lipids, and proteins in cell culture is challenging due to the compound's chemical difference, so most studies involve separate analysis with unimolecular strategies. In this study, we employed a multimolecular approach using a two-phase extraction to monitor the crosstalk between lipid metabolism and protein-based signaling in a single sample (~105 cells). We developed an innovative analytical workflow including standardization with in-house produced 13C isotopically labeled compounds, hyphenated high-end mass spectrometry (high-resolution Orbitrap MS), and chromatography (HILIC, RP) for simultaneous untargeted screening and targeted quantification. Metabolite and lipid concentrations ranged over three to four orders of magnitude and were detected down to the low fmol (absolute on column) level. Biological validation and data interpretation of the multiomics workflow was performed based on proteomics network reconstruction, metabolic modelling (MetaboAnalyst 4.0), and pathway analysis (OmicsNet). Comparing MSCs and adipocytes, we observed significant regulation of different metabolites and lipids such as triglycerides, gangliosides, and carnitine with 113 fully reprogrammed pathways. The observed changes are in accordance with literature findings dealing with adipogenic differentiation of MSC. These results are a proof of principle for the power of multimolecular extraction combined with orthogonal LC-MS assays and network construction. Considering the analytical and biological validation performed in this study, we conclude that the proposed multiomics workflow is ideally suited for comprehensive follow-up studies on adipogenesis and is fit for purpose for different applications with a high potential to understand the complex pathophysiology of diseases.

A Novel Lipidomics Workflow for Improved Human Plasma Identification and Quantification Using RPLC-MSn Methods and Isotope Dilution Strategies.

Lipid identification and quantification are essential objectives in comprehensive lipidomics studies challenged by the high number of lipids, their chemical diversity, and their dynamic range. In this work, we developed a tailored method for profiling and quantification combining (1) isotope dilution, (2) enhanced isomer separation by C30 fused-core reversed-phase material, and (3) parallel Orbitrap and ion trap detection by the Orbitrap Fusion Lumos Tribid mass spectrometer. The combination of parallelizable ion analysis without time loss together with different fragmentation techniques (HCD/CID) and an inclusion list led to higher quality in lipid identifications exemplified in human plasma and yeast samples. Moreover, we used lipidome isotope-labeling of yeast (LILY)-a fast and efficient in vivo labeling strategy in Pichia pastoris-to produce (nonradioactive) isotopically labeled eukaryotic lipid standards in yeast. We integrated the 13C lipids in the LC-MS workflow to enable relative and absolute compound-specific quantification in yeast and human plasma samples by isotope dilution. Label-free and compound-specific quantification was validated by comparison against a recent international interlaboratory study on human plasma SRM 1950. In this way, we were able to prove that LILY enabled quantification leads to accurate results, even in complex matrices. Excellent analytical figures of merit with enhanced trueness, precision and linearity over 4-5 orders of magnitude were observed applying compound-specific quantification with 13C-labeled lipids. We strongly believe that lipidomics studies will benefit from incorporating isotope dilution and LC-MSn strategies.

Merging metabolomics and lipidomics into one analytical run.

A novel integrated metabolomics/lipidomics workflow is introduced enabling high coverage of polar metabolites and non-polar lipids within one analytical run. Dual HILIC and RP chromatography were combined to high-resolution mass spectrometry. As a major advantage, only one data file per sample was obtained by fully automated simultaneous analysis of two extracts per sample. Hence, the unprecedented high coverage without compromise on analytical throughput was not only obtained by the orthogonality of the chromatographic separations, but also by the implementation of dedicated sample preparation procedures resulting in optimum extraction efficiency for both sub-omes. Thus, the method addressed completely hydrophilic sugars and organic acids next to water-insoluble triglycerides. As for the timing of the dual chromatography setup, HILIC and RP separation were performed consecutively. However, re-equilibration of the HILIC column during elution of RP compounds and vice versa reduced the overall analysis time by one third to 32 min. Application to the Standard Reference Material SRM 1950 - Metabolites in Frozen Human Plasma resulted in >100 metabolite and >380 lipid identifications based on accurate mass implementing fast polarity switching and acquiring data dependent MS2 spectra with the use of automated exclusion lists. Targeted quantification based on external calibrations and 13C labeled yeast internal standards was successfully accomplished for 59 metabolites. Moreover, the potential for lipid quantification was shown integrating non-endogenous lipids as internal standards. In human plasma, concentrations ranging over 4 orders of magnitude (low nM to high µM) were assessed.

Simultaneous non-polar and polar lipid analysis by on-line combination of HILIC, RP and high resolution MS.

Given the chemical diversity of lipids and their biological relevance, suitable methods for lipid profiling and quantification are demanded to reduce sample complexity and analysis times. In this work, we present a novel on-line chromatographic method coupling hydrophilic interaction liquid chromatography (HILIC) dedicated to class-specific separation of polar lipid to reversed-phase chromatography (RP) for non-polar lipid analysis. More specifically, the void volume of the HILIC separation-consisting of non-polar lipids- is transferred to the orthogonal RP column enabling the on-line combination of HILIC with RP without any dilution in the second dimension. In this setup the orthogonal HILIC and RP separations were performed in parallel and the effluents of both columns were combined prior to high-resolution MS detection, offering the full separation space in one analytical run. Rapid separation for both polar and non-polar lipids within only 15 min (including reequilibration time) was enabled using sub-2 µm particles and UHPLC. The method proved to be robust with excellent retention time stability (RSDs < 1%) and LODs in the fmol to pmol (absolute on column) range even in the presence of complex biological matrix such as human plasma. The presented high-resolution LC-MS/MS method leads to class-specific separation of polar lipids and separation of non-polar lipids which is lost in conventional HILIC separations. HILIC-RP-MS is a promising tool for targeted and untargeted lipidomics workflows as three interesting features are combined namely (1) the decreased run time of state of the art shotgun MS methods, (2) the elevated linear dynamic range inherent to chromatographic separation and (3) increased level of identification by separation of polar and non-polar lipid classes.

Scrutinizing different ionization responses of polar lipids in a reversed-phase gradient by implementing a counter-gradient.

Lipidomics studies strive for a comprehensive identification and quantification of lipids. While reversed phase (RP) liquid chromatography (LC) coupled to high resolution mass spectrometry (MS) offers unrivalled selectivity and thus is the preferred method for lipid identification, accurate lipid quantification remains challenging. The widely adopted one-point lipid class specific quantification (one internal standard per lipid class) suffers from the fact that ionization of internal standard and target lipid occurs under different solvent composition as a consequence of chromatographic separation. To address this issue, we established a dual flow injection and chromatography setup that allows to control solvent conditions during ionization enabling isocratic ionization while running a RP gradient through the use of a counter-gradient. Using this dual LC pump platform, we investigated the impact of solvent conditions within a RP gradient on ionization response and arising quantification biases. Our results confirmed that changing solvent composition significantly influences ionization response. Quantification of human plasma (SRM 1950) lipids under gradient and isocratic ionization conditions further confirmed these findings as significant differences between the two conditions were found for the majority of lipids. While the quantity of sphingomyelins with >40 C atoms was consistently overestimated under gradient ionization, isocratic ionization improved their recovery compared to consensus values. However, the limitation of consensus values was demonstrated as overall only small changes in z-score were observed because of high uncertainties of the consensus values. Furthermore, we observed a trueness bias between gradient and isocratic ionization when quantifying a panel of lipid species standards which is highly dependent on lipid class and ionization mode. Uncertainty calculations under consideration of the trueness bias as RP gradient uncertainty revealed that especially ceramides with >40 C atoms had a high bias leading to total combined uncertainties of up to 54%. The assumption of isocratic ionization significantly decreases total measurement uncertainty and highlights the importance of studying the trueness bias introduced by a RP gradient to reduce quantification uncertainty.

Benchmarking Non-Targeted Metabolomics Using Yeast-Derived Libraries.

Non-targeted analysis by high-resolution mass spectrometry (HRMS) is an essential discovery tool in metabolomics. To date, standardization and validation remain a challenge. Community-wide accepted cost-effective benchmark materials are lacking. In this work, we propose yeast (Pichia pastoris) extracts derived from fully controlled fermentations for this purpose. We established an open-source metabolite library of >200 identified metabolites based on compound identification by accurate mass, matching retention times, and MS/MS, as well as a comprehensive literature search. The library includes metabolites from the classes of (1) organic acids and derivatives (2) nucleosides, nucleotides, and analogs, (3) lipids and lipid-like molecules, (4) organic oxygen compounds, (5) organoheterocyclic compounds, (6) organic nitrogen compounds, and (7) benzoids at expected concentrations ranges of sub-nM to µM. As yeast is a eukaryotic organism, key regulatory elements are highly conserved between yeast and all annotated metabolites were also reported in the human metabolome database (HMDB). Orthogonal state-of-the-art reversed-phase (RP-) and hydrophilic interaction chromatography mass spectrometry (HILIC-MS) non-targeted analysis and authentic standards revealed that 104 out of the 206 confirmed metabolites were reproducibly recovered and stable over the course of three years when stored at -80 °C. Overall, 67 out of these 104 metabolites were identified with comparably stable areas over all three yeast fermentation and are the ideal starting point for benchmarking experiments. The provided yeast benchmark material enabled not only to test for the chemical space and coverage upon method implementation and developments but also allowed in-house routines for instrumental performance tests. Transferring the quality control strategy of proteomics workflows based on the number of protein identification in HeLa extracts, metabolite IDs in the yeast benchmarking material can be used as metabolomics quality control. Finally, the benchmark material opens new avenues for batch-to-batch corrections in large-scale non-targeted metabolomics studies.

Robust Analytical Methods for the Accurate Quantification of the Total Biomass Composition of Mammalian Cells.

Biomass composition is an important input for genome-scale metabolic models and has a big impact on their predictive capabilities. However, researchers often rely on generic data for biomass composition, e.g. collected from similar organisms. This leads to inaccurate predictions, because biomass composition varies between different cell lines, conditions, and growth phases. In this chapter we present protocols for the determination of the biomass composition of Chinese Hamster Ovary (CHO) cells. These methods can easily be adapted to other types of mammalian cells. The protocols include the quantification of cell dry mass and of the main biomass components, namely protein, lipid, DNA, RNA, and carbohydrates. Cell dry mass is determined gravimetrically by weighing a defined number of cells. Amino acid composition and protein content are measured by gas chromatography mass spectrometry. Lipids are quantified by shotgun mass spectrometry, which provides quantities for the different lipid classes and also the distribution of fatty acids. RNA is purified and then quantified spectrophotometrically. The methods for DNA and carbohydrates are simple fluorometric and colorimetric assays adapted to a 96-well plate format. To ensure quantitative results, internal standards or spike-in controls are used in all methods, e.g. to account for possible matrix effects or loss of material. Finally, the last section provides a guide on how to convert the measured data into biomass equations, which can then be integrated into a metabolic model.