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Background: We introduce TRAM, a triple acquisition strategy on a high-speed quadrupole time-of-flight mass spectrometer for merging non-targeted and targeted metabolomics into one run. TRAM stands for "quasi-simultaneous" acquisition of (1) a full scan MS1, (2) top 30 data-dependent MS2 (DDA), and (3) targeted scheduled MS2 for multiple reaction monitoring (MRM) within measurement cycles of ∼1 s. TRAM combines the selectivity and sensitivity of state-of-the-art targeted MRM-based methods with the full scope of non-targeted analysis enabled by high-resolution mass spectrometry., Results: In this work, we deploy a workflow based on hydrophilic interaction liquid chromatography (HILIC). For a broad panel of metabolites, we provide chromatographic retention times, and optimized conditions as a basis for targeted MRM experiments, listing accurate masses and sum formulas for fragment ions (including fully 13 C labeled analogs). Validation experiments showed that TRAM offered (1) linear working ranges and limits of quantification comparable to MRM-only methods, (2) enabled accurate quantification in SRM 1950 human plasma reference material, and (3) was equivalent to DDA-only approaches in non-targeted metabolomics. Metabolomics in human cerebrospinal fluid showcased the power of the strategy, emphasizing the need for high coverage/high throughput metabolomics in clinical studies., Significance: Acquiring up to 30 data-dependent spectra per MS cycle while still offering gold standard absolute quantification down to low nanomolar concentrations, TRAM allows in-depth profiling and reduces required sample volume, time, cost, and environmental impact., Competing Interests: Declaration of competing interest The authors declare no competing financial interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

The analysis of gangliosides is extremely challenging, given their structural complexity, lack of reference standards, databases, and software solutions. Here, we introduce a fast 6 min high field asymmetric ion mobility spectrometry (FAIMS) shotgun lipidomics workflow, along with a dedicated software solution for ganglioside detection. By ramping FAIMS compensation voltages, ideal ranges for different ganglioside classes were obtained. FAIMS revealed both class- and charge-state separation behavior based on the glycan headgroup moiety. The number of sialic acids attached to the glycan moiety correlates positively with their preferred charge states, i.e., trisialylated gangliosides were mainly present as [M - 3H] 3- ions, whereas [M - 4H] 4- and [M - 5H] 5- ions were observed for GQ1 and GP1. For data evaluation, we developed a shotgun/FAIMS extension for the open-source Lipid Data Analyzer (LDA), enabling automated annotation of gangliosides up to the molecular lipid species level. This extension utilized combined orthogonal fragmentation spectra from CID, HCD, and 213 nm UVPD ion activation methods and covers 29 ganglioside classes, including acetylated and fucosylated modifications. With our new workflow and software extension 117 unique gangliosides species were identified in porcine brain extracts. While conventional shotgun lipidomics favored the observation of singly charged ganglioside species, the utilization of FAIMS made multiply charged lipid species accessible, resulting in an increased number of detected species, primarily due to an improved signal-to-noise ratio arising from FAIMS charge state filtering. Therefore, this FAIMS-driven workflow, complemented by new software capabilities, offers a promising strategy for complex ganglioside and glycosphingolipid characterization in shotgun lipidomics.

microbeMASST, a taxonomically informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbe-derived metabolites and relative producers without a priori knowledge will vastly enhance the understanding of microorganisms' role in ecology and human health., (© 2024. The Author(s).)

Fluorinated carbohydrates are important tools for understanding the deregulation of metabolic fluxes and pathways. Fluorinating specific positions within the sugar scaffold can lead to enhanced metabolic stability and subsequent metabolic trapping in cells. This principle has, however, never been applied to study the metabolism of the rare sugars of the pentose phosphate pathway (PPP). In this study, two fluorinated derivatives of d-sedoheptulose were designed and synthesized: 4-deoxy-4-fluoro-d-sedoheptulose (4DFS) and 3-deoxy-3-fluoro-d-sedoheptulose (3DFS). Both sugars are taken up by human fibroblasts but only 4DFS is phosphorylated. Fluorination of d-sedoheptulose at C-4 effectively halts the enzymatic degradation by transaldolase and transketolase. 4DFS thus has a high potential as a new PPP imaging probe based on the principle of metabolic trapping. Therefore, the synthesis of potential radiolabeling precursors for 4DFS for future radiofluorinations with fluorine-18 is presented., (© 2023 The Authors. Chemistry - A European Journal published by Wiley-VCH GmbH.)

MicrobeMASST, a taxonomically-informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbial-derived metabolites and relative producers, without a priori knowledge, will vastly enhance the understanding of microorganisms' role in ecology and human health., Competing Interests: Disclosures PCD is an advisor to Cybele, consulted for MSD animal health in 2023, and he is a Co-founder and scientific advisor for Ometa Labs, Arome, and Enveda with prior approval by UC San Diego. MW is a Co-founder of Ometa labs. There are no known conflicts of interest in this work by the USDA, Agricultural Research Service, National Center for Agricultural Utilization Research, Mycotoxin Prevention and Applied Microbiology Research Unit. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture.

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier B.V.)

Background: An important goal of modern medicine is the development of products deriving from natural sources to improve environmental sustainability. In this study, humic substances (HS) and compost teas (CTs) extracted from artichoke (ART) and coffee grounds (COF) as recycled biomasses were employed on Ocimum basilicum plants to optimize the yield of specific metabolites with nutraceutical and antibacterial features by applying sustainable strategies., Methods: The molecular characteristics of compost derivates were elucidated by Nuclear Magnetic Resonance spectroscopy to investigate the structure-activity relationship between organic extracts and their bioactive potential. Additionally, combined untargeted and targeted metabolomics workflows were applied to plants treated with different concentrations of compost extracts., Results: The substances HS-ART and CT-COF improved both antioxidant activity (TEAC values between 39 and 55 μmol g -1 ) and the antimicrobial efficacy (MIC value between 3.7 and 1.3 μg mL -1 ) of basil metabolites. The metabolomic approach identified about 149 metabolites related to the applied treatments. Targeted metabolite quantification further highlighted the eliciting effect of HS-ART and CT-COF on the synthesis of aromatic amino acids and phenolic compounds for nutraceutical application., Conclusions: The combination of molecular characterization, biological assays, and an advanced metabolomic approach, provided innovative insight into the valorization of recycled biomass to increase the availability of natural compounds employed in the medical field.

The totality of environmental exposures and lifestyle factors, commonly referred to as the exposome, is poorly understood. Measuring the myriad of chemicals that humans are exposed to is immensely challenging, and identifying disrupted metabolic pathways is even more complex. Here, we present a novel technological approach for the comprehensive, rapid, and integrated analysis of the endogenous human metabolome and the chemical exposome. By combining reverse-phase and hydrophilic interaction liquid chromatography (HILIC) and fast polarity-switching, molecules with highly diverse chemical structures can be analyzed in 15 min with a single analytical run as both column's effluents are combined before analysis. Standard reference materials and authentic standards were evaluated to critically benchmark performance. Highly sensitive median limits of detection (LODs) with 0.04 μM for >140 quantitatively assessed endogenous metabolites and 0.08 ng/mL for the >100 model xenobiotics and human estrogens in solvent were obtained. In matrix, the median LOD values were higher with 0.7 ng/mL (urine) and 0.5 ng/mL (plasma) for exogenous chemicals. To prove the dual-column approach's applicability, real-life urine samples from sub-Saharan Africa (high-exposure scenario) and Europe (low-exposure scenario) were assessed in a targeted and nontargeted manner. Our liquid chromatography high-resolution mass spectrometry (LC-HRMS) approach demonstrates the feasibility of quantitatively and simultaneously assessing the endogenous metabolome and the chemical exposome for the high-throughput measurement of environmental drivers of diseases., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)

Gangliosides are an indispensable glycolipid class concentrated on cell surfaces with a critical role in stem cell differentiation. Nonetheless, owing to the lack of suitable methods for scalable analysis covering the full scope of ganglioside molecular diversity, their mechanistic properties in signaling and differentiation remain undiscovered to a large extent. This work introduces a sensitive and comprehensive ganglioside assay based on liquid chromatography, high-resolution mass spectrometry, and multistage fragmentation. Complemented by an open-source data evaluation workflow, we provide automated in-depth lipid species-level and molecular species-level annotation based on decision rule sets for all major ganglioside classes. Compared to conventional state-of-the-art methods, the presented ganglioside assay offers (1) increased sensitivity, (2) superior structural elucidation, and (3) the possibility to detect novel ganglioside species. A major reason for the highly improved sensitivity is the optimized spectral readout based on the unique capability of two parallelizable mass analyzers for multistage fragmentation. We demonstrated the high-throughput universal capability of our novel analytical strategy by identifying 254 ganglioside species. As a proof of concept, 137 unique gangliosides were annotated in native and differentiated human mesenchymal stem cells including 78 potential cell-state-specific markers and 38 previously unreported gangliosides. A general increase of the ganglioside numbers upon differentiation was observed as well as cell-state-specific clustering based on the ganglioside species patterns. The combination of the developed glycolipidomics assay with the extended automated annotation tool enables comprehensive in-depth ganglioside characterization as shown on biological samples of interest. Our results suggest ganglioside patterns as a promising quality control tool for stem cells and their differentiation products. Additionally, we believe that our analytical workflow paves the way for probing glycolipid-based biochemical processes shedding light on the enigmatic processes of gangliosides and glycolipids in general., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)

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. 31 P 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.

Cellular energy metabolism is reprogrammed in cancer to fuel proliferation. In oncological therapy, treatment resistance remains an obstacle and is frequently linked to metabolic perturbations. Identifying metabolic changes as vulnerabilities opens up novel approaches for the prevention or targeting of acquired therapy resistance. Insights into metabolic alterations underlying ruthenium-based chemotherapy resistance remain widely elusive. In this study, colon cancer HCT116 and pancreatic cancer Capan-1 cells were selected for resistance against the clinically evaluated ruthenium complex sodium trans-[tetrachlorobis(1H-indazole)ruthenate(III)] (BOLD-100). Gene expression profiling identified transcriptional deregulation of carbohydrate metabolism as a response to BOLD-100 and in resistance against the drug. Mechanistically, acquired BOLD-100 resistance is linked to elevated glucose uptake and an increased lysosomal compartment, based on a defect in downstream autophagy execution. Congruently, metabolomics suggested stronger glycolytic activity, in agreement with the distinct hypersensitivity of BOLD-100-resistant cells to 2-deoxy-d-glucose (2-DG). In resistant cells, 2-DG induced stronger metabolic perturbations associated with ER stress induction and cytoplasmic lysosome deregulation. The combination with 2-DG enhanced BOLD-100 activity against HCT116 and Capan-1 cells and reverted acquired BOLD-100 resistance by synergistic cell death induction and autophagy disturbance. This newly identified enhanced glycolytic activity as a metabolic vulnerability in BOLD-100 resistance suggests the targeting of glycolysis as a promising strategy to support BOLD-100 anticancer activity.

Chemotherapy with platinum complexes is essential for clinical anticancer therapy. However, due to side effects and drug resistance, further drug improvement is urgently needed. Herein, we report on triple-action platinum(IV) prodrugs, which, in addition to tumor targeting via maleimide-mediated albumin binding, release the immunomodulatory ligand 1-methyl-d-tryptophan (1-MDT). Unexpectedly, structure-activity relationship analysis showed that the mode of 1-MDT conjugation distinctly impacts the reducibility and thus activation of the prodrugs. This in turn affected ligand release, pharmacokinetic properties, efficiency of immunomodulation, and the anticancer activity in vitro and in a mouse model in vivo . Moreover, we could demonstrate that the design of albumin-targeted multi-modal prodrugs using platinum(IV) is a promising strategy to enhance the cellular uptake of bioactive ligands with low cell permeability (1-MDT) and to improve their selective delivery into the malignant tissue. This will allow tumor-specific anticancer therapy supported by a favorably tuned immune microenvironment.

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.

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.

Glycosyl inositol phospho ceramides (GIPCs) are the major sphingolipids on earth, as they account for a considerable fraction of the total lipids in plants and fungi, which in turn represent a large portion of the biomass on earth. Despite their obvious importance, GIPC analysis remains challenging due to the lack of commercial standards and automated annotation software. In this work, we introduce a novel GIPC glycolipidomics workflow based on reversed-phase ultra-high pressure liquid chromatography coupled to high-resolution mass spectrometry. For the first time, automated GIPC assignment was performed using the open-source software Lipid Data Analyzer (LDA), based on platform-independent decision rules. Four different plant samples (salad, spinach, raspberry, and strawberry) were analyzed and the results revealed 64 GIPCs based on accurate mass, characteristic MS2 fragments and matching retention times. Relative quantification using lactosyl ceramide for internal standardization revealed GIPC t18:1/h24:0 as the most abundant species in all plants. Depending on the plant sample, GIPCs contained mainly amine, N-acetylamine or hydroxyl residues. Most GIPCs revealed a Hex-HexA-IPC core and contained a ceramide part with a trihydroxylated t18:0 or a t18:1 long chain base and hydroxylated fatty acid chains ranging from 16 to 26 carbon atoms in length (h16:0-h26:0). Interestingly, four GIPCs containing t18:2 were observed in the raspberry sample, which was not reported so far. The presented workflow supports the characterization of different plant samples by automatic GIPC assignment, potentially leading to the identification of new GIPCs. For the first time, automated high-throughput profiling of these complex glycolipids is possible by liquid chromatography-high-resolution tandem mass spectrometry and subsequent automated glycolipid annotation based on decision rules.

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.

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.

Tumor spheroids are important model systems due to the capability of capturing in vivo tumor complexity. In this work, the experimental design of metabolomics workflows using three-dimensional multicellular tumor spheroid (3D MTS) models is addressed. Non-scaffold based cultures of the HCT116 colon carcinoma cell line delivered highly reproducible MTSs with regard to size and other key parameters (such as protein content and fraction of viable cells) as a prerequisite. Carefully optimizing the multiple steps of sample preparation, the developed procedure enabled us to probe the metabolome of single MTSs (diameter range 790 ± 22 µm) in a highly repeatable manner at a considerable throughput. The final protocol consisted of rapid washing of the spheroids on the cultivation plate, followed by cold methanol extraction. 13 C enriched internal standards, added upon extraction, were key to obtaining the excellent analytical figures of merit. Targeted metabolomics provided absolute concentrations with average biological repeatabilities of <20% probing MTSs individually. In a proof of principle study, MTSs were exposed to two metal-based anticancer drugs, oxaliplatin and the investigational anticancer drug KP1339 (sodium trans -[tetrachloridobis(1 H -indazole)ruthenate(III)]), which exhibit distinctly different modes of action. This difference could be recapitulated in individual metabolic shifts observed from replicate single MTSs. Therefore, biological variation among single spheroids can be assessed using the presented analytical strategy, applicable for in-depth anticancer drug metabolite profiling.

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 (~10 5 cells). We developed an innovative analytical workflow including standardization with in-house produced 13 C 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.

13 C metabolite tracer and metabolic flux analyses require upfront experimental planning and validation tools. Here, we present a validation scheme including a comparison of different LC methods that allow for customization of analytical strategies for tracer studies with regard to the targeted metabolites. As the measurement of significant changes in labeling patterns depends on the spectral accuracy, we investigate this aspect comprehensively for high-resolution orbitrap mass spectrometry combined with reversed-phase chromatography, hydrophilic interaction liquid chromatography, or anion-exchange chromatography. Moreover, we propose a quality control protocol based on (1) a metabolite containing selenium to assess the instrument performance and on (2) in vivo synthesized isotopically enriched Pichia pastoris to validate the accuracy of carbon isotopologue distributions (CIDs), in this case considering each isotopologue of a targeted metabolite panel. Finally, validation involved a thorough assessment of procedural blanks and matrix interferences. We compared the analytical figures of merit regarding CID determination for over 40 metabolites between the three methods. Excellent precisions of less than 1% and trueness bias as small as 0.01-1% were found for the majority of compounds, whereas the CID determination of a small fraction was affected by contaminants. For most compounds, changes of labeling pattern as low as 1% could be measured. Graphical abstract.

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.

Chromosome segregation depends on sister chromatid cohesion which is established by cohesin during DNA replication. Cohesive cohesin complexes become acetylated to prevent their precocious release by WAPL before cells have reached mitosis. To obtain insight into how DNA replication, cohesion establishment and cohesin acetylation are coordinated, we analysed the interaction partners of 55 human proteins implicated in these processes by mass spectrometry. This proteomic screen revealed that on chromatin the cohesin acetyltransferase ESCO2 associates with the MCM2-7 subcomplex of the replicative Cdc45-MCM-GINS helicase. The analysis of ESCO2 mutants defective in MCM binding indicates that these interactions are required for proper recruitment of ESCO2 to chromatin, cohesin acetylation during DNA replication, and centromeric cohesion. We propose that MCM binding enables ESCO2 to travel with replisomes to acetylate cohesive cohesin complexes in the vicinity of replication forks so that these complexes can be protected from precocious release by WAPL Our results also indicate that ESCO1 and ESCO2 have distinct functions in maintaining cohesion between chromosome arms and centromeres, respectively., (© 2018 The Authors.)

In the version of this article initially published online, the authors used incorrectly defined restraints for specifying the distance between residues when using the HADDOCK portal. Following the publication of a Correspondence by the developers of the HADDOCK portal (Nat. Protoc. https://dx.doi.org/10.1038/s41596-018-0017-6, 2018) and a Reply by the authors of the Protocol (Nat. Protoc. https://dx.doi.org/10.1038/s41596-018-0018-5, 2018), the syntax in step 21 has been corrected. In addition, the input files (available as Supplementary Data 5-7) have been replaced.

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 13 C 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 13 C-labeled lipids. We strongly believe that lipidomics studies will benefit from incorporating isotope dilution and LC-MSn strategies.

This protocol describes a workflow for creating structural models of proteins or protein complexes using distance restraints derived from cross-linking mass spectrometry experiments. The distance restraints are used (i) to adjust preliminary models that are calculated on the basis of a homologous template and primary sequence, and (ii) to select the model that is in best agreement with the experimental data. In the case of protein complexes, the cross-linking data are further used to dock the subunits to one another to generate models of the interacting proteins. Predicting models in such a manner has the potential to indicate multiple conformations and dynamic changes that occur in solution. This modeling protocol is compatible with many cross-linking workflows and uses open-source programs or programs that are free for academic users and do not require expertise in computational modeling. This protocol is an excellent additional application with which to use cross-linking results for building structural models of proteins. The established protocol is expected to take 6-12 d to complete, depending on the size of the proteins and the complexity of the cross-linking data.

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.

In this work, simultaneous targeted metabolic profiling by isotope dilution and non-targeted fingerprinting is proposed for cancer cell studies. The novel streamlined metabolomics workflow was established using anion-exchange chromatography (IC) coupled to high-resolution mass spectrometry (MS). The separation time of strong anion-exchange (2 mm column, flow rate 380 μL min -1 , injection volume 5 μL) could be decreased to 25 min for a target list comprising organic acids, sugars, sugar phosphates, and nucleotides. Internal standardization by fully 13 C labeled Pichia pastoris extracts enabled absolute quantification of the primary metabolites in adherent cancer cell models. Limits of detection (LODs) in the low nanomolar range and excellent intermediate precisions of the isotopologue ratios (on average <5%, N = 5, over 40 h) were observed. As a result of internal standardization, linear dynamic ranges over 4 orders of magnitude (5 nM-50 μM, R 2 > 0.99) were obtained. Experiments on drug-sensitive versus resistant SW480 cancer cells showed the feasibility of merging analytical tasks into one analytical run. Comparing fingerprinting with and without internal standard proved that the presence of the 13 C labeled yeast extract required for absolute quantification was not detrimental to non-targeted data evaluation. Several interesting metabolites were discovered by accurate mass and comparing MS2 spectra (acquired in ddMS2 mode) with spectral libraries. Significant differences revealed distinct metabolic phenotypes of drug-sensitive and resistant SW480 cells.

Quantification is an essential task in comprehensive lipidomics studies challenged by the high number of lipids, their chemical diversity and their dynamic range of the lipidome. In this work, we introduce lipidome isotope labeling of yeast (LILY) in order to produce (non-radioactive) isotopically labeled eukaryotic lipid standards in yeast for normalization and quantification in mass spectrometric assays. More specifically, LILY is a fast and efficient in vivo labeling strategy in Pichia pastoris for the production of 13 C labeled lipid library further paving the way to comprehensive compound-specific internal standardization in quantitative mass spectrometry based assays. More than 200 lipid species (from PA, PC, PE, PG, PI, PS, LysoGP, CL, DAG, TAG, DMPE, Cer, HexCer, IPC, MIPC) were obtained from yeast extracts with an excellent 13 C enrichment >99.5%, as determined by complementary high resolution mass spectrometry based shotgun and high resolution LC-MS/MS analysis. In a first proof of principle study we tested the relative and absolute quantification capabilities of the 13 C enriched lipids obtained by LILY using a parallel reaction monitoring based LC-MS approach. In relative quantification it could be shown that compound specific internal standardization was essential for the accuracy extending the linear dynamic range to four orders of magnitude. Excellent analytical figures of merit were observed for absolute quantification for a selected panel of 5 investigated glycerophospholipids (e.g. LOQs around 5 fmol absolute; typical concentrations ranging between 1 to 10 nmol per 10 8 yeast cell starting material; RSDs <10% (N = 4)).

The HOP2-MND1 heterodimer is essential for meiotic homologous recombination in plants and other eukaryotes and promotes the repair of DNA double-strand breaks. We investigated the conformational flexibility of HOP2-MND1, important for understanding the mechanistic details of the heterodimer, with chemical cross-linking in combination with mass spectrometry (XL-MS). The final XL-MS workflow encompassed the use of complementary cross-linkers, quenching, digestion, size exclusion enrichment, and HCD-based LC-MS/MS detection prior to data evaluation. We applied two different homobifunctional amine-reactive cross-linkers (DSS and BS(2)G) and one zero-length heterobifunctional cross-linker (EDC). Cross-linked peptides of four biological replicates were analyzed prior to 3D structure prediction by protein threading and protein-protein docking for cross-link-guided molecular modeling. Miniaturization of the size-exclusion enrichment step reduced the required starting material, led to a high amount of cross-linked peptides, and allowed the analysis of replicates. The major interaction site of HOP2-MND1 was identified in the central coiled-coil domains, and an open colinear parallel arrangement of HOP2 and MND1 within the complex was predicted. Moreover, flexibility of the C-terminal capping helices of both complex partners was observed, suggesting the coexistence of a closed complex conformation in solution.

Elemental speciation analysis was implemented as an essential tool set addressing optimum fermentation conditions for the production of selenized yeast feed supplements. Accordingly, the study addressed intracellular levels of (1) total selenium and sulfur, (2) seleno methionine (SeMet), (3) cysteine (Cys) and methionine (Met) and (4) selenite and selenate. Dedicated sample preparation- and LC-ICP-MS methods were implemented and validated using the reference material Selm-1. Excellent repeatability precisions <10% (n = 4 biological replicates) could be obtained for all parameters. The study comprised fermentation monitoring over 72 hours (6 different time points) for a Saccharomyces cerevisiae strain under different selenite feed conditions. It was observed that for this strain an increase in the selenium concentration in the fermentation feed by 50% did not result in enhanced selenium accumulation. Fermentation monitoring of three different Saccharomyces cerevisiae strains under the same conditions showed strain specific selenium uptake after 72 hours. The strain with the lowest cell viability of 60% showed the lowest SeMet content. After 47 h of fermentation, all strains reached a critical point, at which seleno methionine accounted for approximately 100% of the total selenium and cell viability started to decrease. This could be explained by sulfur limitation and/or excess of the seleno methionine storage capacity. Strains showing cell viability of approx. 90% after 72 hours of fermentation revealed SeMet concentrations up to 3000 μg g(-1). In the final product, an apparent threshold level for Met/SeMet of approx. 1 was observed for all strains.