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The antidepressant effects of ketamine and esketamine are well-documented. Nonetheless, most of the underlying molecular mechanisms have to be uncovered yet. In the last decade, metabolomics has emerged as a useful means to investigate the metabolic phenotype associated with depression as well as changes induced by antidepressant treatments. This mini-review aims at summarizing the main findings from preclinical and clinical studies that used metabolomics to investigate the metabolic effects of subanesthetic, antidepressant doses of ketamine and esketamine and their relationship with clinical response. Both animal and human studies report alterations in several metabolic pathways - including the tricarboxylic acid cycle, glycolysis, the pentose phosphate pathway, lipid metabolism, amino acid metabolism, the kynurenine pathway, and the urea cycle - following the administration of ketamine or its enantiomers. Although more research is needed to clarify commonalities and differences in molecular mechanisms of action between the racemic compound and its enantiomers, these findings comprehensively support an influence of ketamine and esketamine on mitochondrial and cellular energy production, membrane homeostasis, neurotransmission, and signaling. Metabolomics may thus represent a promising strategy to clarify molecular mechanisms underlying treatment-resistant depression and related markers of clinical response to ketamine and esketamine. This body of preclinical and clinical evidence, if further substantiated, has the potential to guide clinicians towards personalized approaches, contributing to new paradigms in the clinical management of depression.

Mass spectrometry imaging (MSI) is an emerging technology that is capable of mapping various biomolecules within their native spatial context, and performing spatial multiomics on formalin-fixed paraffin-embedded (FFPE) tissues may further increase the molecular characterization of pathological states. Here we present a novel workflow which enables the sequential MSI of lipids, N- glycans, and tryptic peptides on a single FFPE tissue section and highlight the enhanced molecular characterization that is offered by combining the multiple spatial omics data sets. In murine brain and clear cell renal cell carcinoma (ccRCC) tissue, the three molecular levels provided complementary information and characterized differ- ent histological regions. Moreover, when the spatial omics data was integrated, the different histopathological regions of the ccRCC tissue could be better discriminated with respect to the imaging data set of any single omics class. Taken together, these promising findings demonstrate the capability to more comprehensively map the molecular complexity within pathological tissue.

Lipid-lowering therapies are widely used to prevent the development of atherosclerotic cardiovascular disease (ASCVD) and related mortality worldwide. "Omics" technologies have been successfully applied in recent decades to investigate the mechanisms of action of these drugs, their pleiotropic effects, and their side effects, aiming to identify novel targets for future personalized medicine with an improvement of the efficacy and safety associated with the treatment. Pharmacometabolomics is a branch of metabolomics that is focused on the study of drug effects on metabolic pathways that are implicated in the variation of response to the treatment considering also the influences from a specific disease, environment, and concomitant pharmacological therapies. In this review, we summarized the most significant metabolomic studies on the effects of lipid-lowering therapies, including the most commonly used statins and fibrates to novel drugs or nutraceutical approaches. The integration of pharmacometabolomics data with the information obtained from the other "omics" approaches could help in the comprehension of the biological mechanisms underlying the use of lipid-lowering drugs in view of defining a precision medicine to improve the efficacy and reduce the side effects associated with the treatment.

Volumetric absorptive microsampling (VAMS) is a recently developed sample collection method that enables single-drop blood collection in a minimally invasive manner. Blood biomolecules can then be extracted and processed for analysis using several analytical platforms. The integration of VAMS with conventional mass spectrometry (MS)-based metabolomics approaches is an attractive solution for human studies representing a less-invasive procedure compared to phlebotomy with the additional potential for remote sample collection. However, as we recently demonstrated, VAMS samples require long-term storage at −80 °C. This study investigated the stability of VAMS samples during short-term storage and compared the metabolome obtained from capillary blood collected from the fingertip to those of plasma and venous blood from 22 healthy volunteers. Our results suggest that the blood metabolome collected by VAMS samples is stable at room temperature only for up to 6 h requiring subsequent storage at −80 °C to avoid significant changes in the metabolome. We also demonstrated that capillary blood provides better coverage of the metabolome compared to plasma enabling the analysis of several intracellular metabolites presented in red blood cells. Finally, this work demonstrates that with the appropriate pre-analytical protocol capillary blood can be successfully used for untargeted metabolomics studies.

Arrhythmogenic cardiomyopathy (ACM) is a genetic disease associated with sudden cardiac death and cardiac fibro-fatty replacement. Over the last years, several works have demonstrated that different epigenetic enzymes can affect not only gene expression changes in cardiac diseases but also cellular metabolism. Specifically, the histone acetyltransferase GCN5 is known to facilitate adipogenesis and modulate cardiac metabolism in heart failure. Our group previously demonstrated that human primary cardiac stromal cells (CStCs) contribute to adipogenesis in the ACM pathology. Thus, this study aims to evaluate the role of GCN5 in ACM intracellular lipid accumulation. To do so, CStCs were obtained from right ventricle biopsies of ACM patients and from samples of healthy cadaveric donors (CTR). GCN5 expression was increased both in ex vivo and in vitro ACM samples compared to CTR. When GCN5 expression was silenced or pharmacologically inhibited by the administration of MB-3, we observed a reduction in lipid accumulation and a mitigation of reactive oxygen species (ROS) production in ACM CStCs. In agreement, transcriptome analysis revealed that the presence of MB-3 modified the expression of pathways related to cellular redox balance. Altogether, our findings suggest that GCN5 inhibition reduces fat accumulation in ACM CStCs, partially by modulating intracellular redox balance pathways.

Metabolites are intermediates or end products of biochemical processes involved in both health and disease. Here, we take advantage of the well-characterized Cooperative Health Research in South Tyrol (CHRIS) study to perform an exome-wide association study (ExWAS) on absolute concentrations of 175 metabolites in 3294 individuals. To increase power, we imputed the identified variants into an additional 2211 genotyped individuals of CHRIS. In the resulting dataset of 5505 in-dividuals, we identified 85 single-variant genetic associations, of which 39 have not been reported previously. Fifteen associations emerged at ten variants with >5-fold enrichment in CHRIS compared to non-Finnish Europeans reported in the gnomAD database. For example, the CHRIS-enriched ETFDH stop gain variant p.Trp286Ter (rs1235904433-hexanoylcarnitine) and the MCCC2 stop lost variant p.Ter564GlnextTer3 (rs751970792-carnitine) have been found in patients with glutaric acidemia type II and 3-methylcrotonylglycinuria, respectively, but the loci have not been associated with the respective metabolites in a genome-wide association study (GWAS) previously. We further identified three gene-trait associations, where multiple rare variants contribute to the signal. These results not only provide further evidence for previously described associations, but also describe novel genes and mechanisms for diseases and disease-related traits.

The aim of this study was to determine alterations of the metabolome in blood plasma in response to concentric-eccentric leg exercise performed at a simulated altitude of 3,500 m. To do so, we recruited 11 well-trained subjects and performed an untargeted metabolomics analysis of plasma samples obtained before, 20 min after as well as on day 8 after five sets of maximal, concentric-eccentric leg exercises that lasted 90 s each. We identified and annotated 115 metabolites through untargeted liquid chromatography-mass spectrometry metabolomics and used them to further calculate 20 sum/ratio of metabolites. A principal component analysis (PCA) revealed differences in-between the overall metabolome at rest and immediately after exercise. Interestingly, some systematic changes of relative metabolite concentrations still persisted on day 8 after exercise. The first two components of the PCA explained 34% of the relative concentrations of all identified metabolites analyzed together. A volcano plot indicates that 35 metabolites and two metabolite ratios were significantly changed directly after exercise, such as metabolites related to carbohydrate and TCA metabolism. Moreover, we observed alterations in the relative concentrations of amino acids (e.g., decreases of valine, leucine and increases in alanine) and purines (e.g., increases in hypoxanthine, xanthine and uric acid). In summary, high intensity concentric-eccentric exercise performed at simulated altitude systematically changed the blood metabolome in trained athletes directly after exercise and some relative metabolite concentrations were still changed on day 8. The importance of that persisting metabolic alterations on exercise performance should be studied further.

Researchers worldwide are taking advantage of novel, commercially available, technologies, such as ion mobility mass spectrometry (IM-MS), for metabolomics and lipidomics applications in a variety of fields including life, biomedical, and food sciences. IM-MS provides three main technical advantages over traditional LC-MS workflows. Firstly, in addition to mass, IM-MS allows collision cross-section values to be measured for metabolites and lipids, a physicochemical identifier related to the chemical shape of an analyte that increases the confidence of identification. Second, IM-MS increases peak capacity and the signal-to-noise, improving fingerprinting as well as quantification, and better defining the spatial localization of metabolites and lipids in biological and food samples. Third, IM-MS can be coupled with various fragmentation modes, adding new tools to improve structural characterization and molecular annotation. Here, we review the state-of-the-art in IM-MS technologies and approaches utilized to support metabolomics and lipidomics applications and we assess the challenges and opportunities in this growing field.

What’s brewing? Mapping the distribution of bioactive compounds in green C. arabica coffee beans through MS-driven spatial metabolomics

Triple-negative breast cancer (TNBC) is a very aggressive disease even in its early stages and is characterized by a severe prognosis. Neoadjuvant chemotherapy is one of the milestones of treatment, and paclitaxel (PTX) is among the most active drugs used in this setting. However, despite its efficacy, peripheral neuropathy occurs in approximately 20-25% of cases and represents the dose-limiting toxicity of this drug. New deliverable strategies to ameliorate drug delivery and reduce side effects are keenly awaited to improve patients' outcomes. Mesenchymal stromal cells (MSCs) have recently been demonstrated as promising drug delivery vectors for cancer treatment. The aim of the present preclinical study is to explore the possibility of a cell therapy approach based on the use of MSCs loaded with PTX to treat TNBC-affected patients. For this purpose, we in vitro evaluated the viability, migration and colony formation of two TNBC cell lines, namely, MDA-MB-231 and BT549, treated with MSC-PTX conditioned medium (MSC-CM PTX) in comparison with both CM of MSCs not loaded with PTX (CTRL) and free PTX. We observed stronger inhibitory effects on survival, migration and tumorigenicity for MSC-CM PTX than for CTRL and free PTX in TNBC cell lines. Further studies will provide more information about activity and potentially open the possibility of using this new drug delivery vector in the context of a clinical study.

Predicting the prognosis of colorectal cancer (CRC) patients remains challenging and a characterisation of the tumour immune environment represents one of the most crucial avenues when attempting to do so. For this reason, molecular approaches which are capable of classifying the immune environments associated with tumour infiltrating lymphocytes (TILs) are being readily investigated. In this proof of concept study, we aim to explore the feasibility of using spatial lipidomics by MALDI-MSI to distinguish CRC tissue based upon their TIL content. Formalin-fixed paraffin-embedded tissue from human thymus and tonsil was first analysed by MALDI-MSI to obtain a curated mass list from a pool of single positive T lymphocytes, whose putative identities were annotated using an LC-MS-based lipidomic approach. A CRC tissue microarray (TMA, n = 30) was then investigated to determine whether these cases could be distinguished based upon their TIL content in the tumour and its microenvironment. MALDI-MSI from the pool of mature T lymphocytes resulted in the generation of a curated mass list containing 18 annotated m/z features. Initially, subsets of T lymphocytes were then distinguished based on their state of maturation and differentiation in the human thymus and tonsil tissue. Then, when applied to a CRC TMA containing differing amounts of T lymphocyte infiltration, those cases with a high TIL content were distinguishable from those with a lower TIL content, especially within the tumour microenvironment, with three lipid signals being shown to have the greatest impact on this separation (p < 0.05). On the whole, this preliminary study represents a promising starting point and suggests that a lipidomics MALDI-MSI approach could be a promising tool for subtyping the diverse immune environments in CRC.

Arrhythmogenic cardiomyopathy (ACM) is a genetic-based cardiac disease accompanied by severe ventricular arrhythmias and a progressive substitution of the myocardium with fibro-fatty tissue. ACM is often associated with sudden cardiac death. Due to the reduced penetrance and variable expressivity, the presence of a genetic defect is not conclusive, thus complicating the diagnosis of ACM. Recent studies on human induced pluripotent stem cells-derived cardiomyocytes (hiPSC-CMs) obtained from ACM individuals showed a dysregulated metabolic status, leading to the hypothesis that ACM pathology is characterized by an impairment in the energy metabolism. However, despite efforts having been made for the identification of ACM specific biomarkers, there is still a substantial lack of information regarding the whole metabolomic profile of ACM patients. The aim of the present study was to investigate the metabolic profiles of ACM patients compared to healthy controls (CTRLs). The targeted Biocrates AbsoluteIDQ® p180 assay was used on plasma samples. Our analysis showed that ACM patients have a different metabolome compared to CTRLs, and that the pathways mainly affected include tryptophan metabolism, arginine and proline metabolism and beta oxidation of fatty acids. Altogether, our data indicated that the plasma metabolomes of arrhythmogenic cardiomyopathy patients show signs of endothelium damage and impaired nitric oxide (NO), fat, and energy metabolism.

With the author(s)’ decision to opt for Open Choice the copyright of the article changed on 10 June, 2021 to © The Author(s).

OBJECTIVES: To provide evidence-based recommendations for vaccination against influenza virus and S. pneumoniae in patients with autoimmune rheumatic diseases (ARDs). METHODS: A Consensus Committee including physicians with expertise in rheumatic and infectious diseases was established by two Italian scientific societies, Società Italiana di Reumatologia (SIR) and Società Italiana di Malattie Infettive e Tropicali (SIMIT). The experts were invited to develop evidence-based recommendations concerning vaccinations in ARDs patients, based on their clinical status before and after undergoing immunosuppressive treatments. Key clinical questions were formulated for the systematic literature reviews, based on the clinical pathway. A search was made in Medline (via PubMed) according to the original MeSH strategy from October 2009 and a keyword strategy from January 2016 up to December 2017, updating existing EULAR recommendations. Specific recommendations were separately voted and scored from 0 (no agreement with) to 100 (maximal agreement) and supporting evidence graded. The mean and standard deviation of the scores were calculated to determine the level of agreement among the experts' panel for each recommendation. Total cumulative agreement ≥70 defined consensus for each statement. RESULTS: Nine recommendations, based on 6 key clinical questions addressed by the expert committee, were proposed. The aim of this work is to integrate the 2011 EULAR recommendations on vaccination against influenza and S. pneumoniae in ARDs patients. An implementation plan was proposed to improve the vaccination status of these patients and their safety during immunosuppressive treatments. CONCLUSIONS: Influenza and pneumococcus vaccinations are effective and safe in patients with ARDs. More efforts should be made to translate the accumulated evidence into practice.

Mass spectrometry imaging (MSI) is an emerging technology that is capable of mapping various biomolecules within their native spatial context, and performing spatial multiomics on formalin-fixed paraffin-embedded (FFPE) tissues may further increase the molecular characterization of pathological states. Here we present a novel workflow which enables the sequential MSI of lipids, N-glycans, and tryptic peptides on a single FFPE tissue section and highlight the enhanced molecular characterization that is offered by combining the multiple spatial omics data sets. In murine brain and clear cell renal cell carcinoma (ccRCC) tissue, the three molecular levels provided complementary information and characterized different histological regions. Moreover, when the spatial omics data was integrated, the different histopathological regions of the ccRCC tissue could be better discriminated with respect to the imaging data set of any single omics class. Taken together, these promising findings demonstrate the capability to more comprehensively map the molecular complexity within pathological tissue.

The European Food Safety Authority asked for novel approaches for identifying mechanically separated meat (MSM) in meat products, due to food safety concern. In this study, a novel approach based on multivariate analysis of 43 trace elements in meat products is described. Overall, 27 trace elements and 16 rare earth elements were determined by using ICP-MS after sample mineralization of 100 meat samples, composed of different percentages of MSM, obtained at low and high pressure, and without MSM. After development and optimization, the multivariate approach was validated by analyzing and then classifying 10 “blind” meat samples, obtaining method accuracy equal to 90%. Thus, the applicability of this new analytical approach was demonstrated. The method represents a significant improvement for this type of determination, especially when MSM is obtained at low pressure, since this product is characterized by chemical characteristics very similar to fresh meat.

Mass spectrometry (MS)-based metabolomics approaches have been used for characterizing the metabolite content and composition of biological samples in drug discovery and development, as well as in metabolic engineering, and food and plant sciences applications. Here, we describe a protocol routinely used in our laboratory to conduct a metabolic profiling of small polar metabolites from biological samples. Metabolites can be extracted from each sample using a methanol-based single-phase extraction procedure. The combination of LC-based hydrophilic interaction liquid chromatography (HILIC) and a hybrid quadrupole–time of flight (Q-ToF) mass spectrometer allows the comprehensive analysis of small polar metabolites including sugars, phosphorylated compounds, purines and pyrimidines, nucleotides, nucleosides, acylcarnitines, carboxylic acids, hydrophilic vitamins and amino acids. Retention times and accurate masses of metabolites involved in key metabolic pathways are annotated for routine high-throughput screening in both untargeted and targeted metabolomics analyses.

Neural tissue has high metabolic requirements. Following spinal cord injury (SCI), the damaged tissue suffers from a severe metabolic impairment, which aggravates axonal degeneration and neuronal loss. Impaired cellular energetic, tricarboxylic acid (TCA) cycle and oxidative phosphorylation metabolism in neuronal cells has been demonstrated to be a major cause of neural tissue death and regeneration failure following SCI. Therefore, rewiring the spinal cord cell metabolism may be an innovative therapeutic strategy for the treatment of SCI. In this study, we evaluated the therapeutic effect of the recovery of oxidative metabolism in a mouse model of severe contusive SCI. Oral administration of TCA cycle intermediates, co-factors, essential amino acids, and branched-chain amino acids was started 3 days post-injury and continued until the end of the experimental procedures. Metabolomic, immunohistological, and biochemical analyses were performed on the injured spinal cord sections. Administration of metabolic precursors enhanced spinal cord oxidative metabolism. In line with this metabolic shift, we observed the activation of the mTORC1 anabolic pathway, the increase in mitochondrial mass, and ROS defense which effectively prevented the injury-induced neural cell apoptosis in treated animals. Consistently, we found more choline acetyltransferase (ChAT)-expressing motor neurons and increased neurofilament-positive corticospinal axons in the spinal cord parenchyma of the treated mice. Interestingly, oral administration of the metabolic precursors increased the number of activated microglia expressing the CD206 marker suggestive of a pro-resolutive, M2-like phenotype. These molecular and histological modifications observed in treated animals ultimately led to a significant, although partial, improvement of the motor functions. Our data demonstrate that rewiring the cellular metabolism can represent an effective strategy to treat SCI.

Ion mobility (IM) spectrometry can separate gas-phase ions according to their charge, molecular shape, and size. In recent years, several IM technologies have been integrated with mass spectrometry (MS) and launched as commercially available instrumentation for metabolomics analysis. The addition of IM to MS-based metabolomics workflows provides an additional degree of separation to chromatography and MS resolving power, improving peak capacity and signal-to-noise ratio. Moreover, it makes possible to experimentally derive collision cross section (CCS), which can be used as an additional coordinate for metabolite identification, together with accurate mass and fragmentation information. The addition of CCS to current metabolome database would allow to filter and score molecules based on their CCS values, adding more confidence in the identification process during metabolomics experiments. In this chapter, we present procedures for the integration of travelling-wave (TW)-IM into traditional MS-based metabolomics workflows.

Background: Lipids are increasingly involved in cardiovascular risk prediction as potential proarrhythmic influencers. However, knowledge is limited about the specific mechanisms connecting lipid alterations with atrial conduction. Methods: To shed light on this issue, we conducted a broad assessment of 151 sphingo- and phospholipids, measured using mass spectrometry, for association with atrial conduction, measured by P wave duration (PWD) from standard electrocardiograms, in the MICROS study (Microisolates in South Tyrol) (n=839). Causal pathways involving lipidomics, body mass index (BMI), and PWD were assessed using 2-sample Mendelian randomization analyses based on published genome-wide association studies of lipidomics (n=4034) and BMI (n=734 481), and genetic association analysis of PWD in 5 population-based studies (n=24 236). Results: We identified an association with relative phosphatidylcholine 38:3 (%PC 38:3) concentration, which was replicated in the ORCADES (Orkney Complex Disease Study; n=951), with a pooled association across studies of 2.59 (95% CI, 1.3-3.9; P=1.1×10-4) ms PWD per mol% increase. While being independent of cholesterol, triglycerides, and glucose levels, the %PC 38:3-PWD association was mediated by BMI. Results supported a causal effect of BMI on both PWD (P=8.3×10-5) and %PC 38:3 (P=0.014). Conclusions: Increased %PC 38:3 levels are consistently associated with longer PWD, partly because of the confounding effect of BMI. The causal effect of BMI on PWD reinforces evidence of BMI's involvement into atrial electrical activity.

The aim of this study was to obtain a longitudinal evaluation of the exposure to chlorpyrifos (CP) and chlorpyrifos-methyl (CPM) in agricultural workers in South Tyrol and in a residential group living in the same area. CP and CPM are widely used pesticides in agriculture. Biological monitoring of CP and CPM exposure in humans can be achieved by analyzing urinary levels of 3,5,6-trichloro-2-pyridinol (TCPy). TCPy a metabolite of CP and CPM which is produced by a two-step metabolic transformation. Between May 14th, 2014 and March 16th, 2015 we conducted a longitudinal study on 28 farmers actively working in spray pesticide treatment and 43 non-farmers living in the same agricultural area of South Tyrol (Italy). Urine samples were collected at two time points: during the pesticide treatment period and in a temporally distant season that should guarantee metabolite clearance. We developed and validated a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the determination of urinary TCPy levels. During the treatment season, both farmers and residents showed higher TCPy levels (median = 6.8 and 6.73 ug/g creatinine, respectively) than during the non-treatment season (median = 2.54 and 3.22 ug/g creatinine, respectively), suggesting a similar effect of the pesticide spraying on both groups. However, the observed TCPy levels resulted in a daily CP and CPM intake well below the limits recommended by FAO/WHO. During the non-treatment season, non-farmers showed higher TCPy levels values than farmers, suggesting the existence of TCPy of other unmeasured sources of exposure not considered in this study. This suggests that, for a comprehensive evaluation of the risks associated with TCPy exposure, additional sources should be identified in addition to CP and CPM pesticides.

Mass spectrometry (MS)-based lipidomics and metabolomics approaches have been used to discover new diagnostic and therapeutic targets of neurodegenerative disorders. Here, we describe a protocol to conduct an integrated metabolomics and lipidomics profiling of postmortem brains of frozen tissue samples from clinically characterized patients and age-matched controls. Metabolites and lipids can be extracted from each brain tissue sample, using a biphasic liquid/liquid extraction method. An unbiased liquid chromatography MS-based lipidomics and metabolomics workflows allows to screen for the content and composition of lipids and polar metabolites for each brain tissue. Data processing and statistical analysis are then used to compare the molecular content of all the samples, grouping them into cluster based on molecular similarities. The final results highlight classes of metabolites and biochemical pathways that are altered in brain samples from diseased brains compared to those from healthy subjects, helping to generate novel hypotheses on their mechanistic and functional significance.

Platelets (PLTs) deteriorate over time when stored within blood banks through a biological process known as PLT storage lesion (PSL). Here, we describe the refinement of the biochemical model of PLT metabolism, iAT-PLT-636, and its application to describe and investigate changes in metabolism during PLT storage. Changes in extracellular acetate and citrate were measured in buffy coat and apheresis PLT units over 10 days of storage in the PLT additive solution T-Sol. Metabolic network analysis of these data was performed alongside our prior metabolomics data to describe the metabolism of fresh (days 1–3), intermediate (days 4–6), and expired (days 7–10) PLTs. Changes in metabolism were studied by comparing metabolic model flux predictions of iAT-PLT-636 between stages and between collection methods. Extracellular acetate and glucose contribute most to central carbon metabolism in PLTs. The anticoagulant citrate is metabolized in apheresis-stored PLTs and is converted into aconitate and, to a lesser degree, malate. The consumption of nutrients changes during storage and reflects altered PLT activation profiles following their collection. Irrespective of the collection method, a slowdown in oxidative phosphorylation takes place, consistent with mitochondrial dysfunction during PSL. Finally, the main contributors to intracellular ammonium and NADPH are highlighted. Future optimization of flux through these pathways provides opportunities to address intracellular pH changes and reactive oxygen species, which are both of importance to PSL. The metabolic models provide descriptions of PLT metabolism at steady state and represent a platform for future PLT metabolic research.

The recent hyphenation of ion mobility spectrometry (IMS) with high resolution mass spectrometry (HRMS) has risen as a powerful technique for both targeted and non-targeted screening, reducing background noise and allowing separation of isomeric and isobaric compounds. Nevertheless, such an approach remains largely unexplored in food safety applications, such as mycotoxin analysis. To implement ion mobility in routinely MS-based mycotoxin workflows, searchable databases with collusion cross section (CCS) values and accurate mass-values are required. This paper provides for the first time a traveling-wave IMS (TWIMS)-derived CCS database for mycotoxins, including more than 100 CCS values. The measurements showed high reproducibility (RSD < 2%) across different instrumental conditions as well as several complex cereal matrices, showing a mean inter-matrix precision of RSD <0.9%. As a proof of concept, the database was applied to the analysis of several spiked as well as naturally incurred cereal-based samples. In addition, the effect of adducts on the drift time was studied in a series of mycotoxins in order to understand potential deviations from expected drift time behaviors. Overall, our study confirmed that CCS values represent a physicochemical property that can be used alongside the traditional molecular identifiers of precursor ion accurate mass, fragment ions, isotopic pattern, and retention time.

Background: Plasma and serum are the most widely used matrices in clinical studies. However, some variability in absolute concentrations of metabolites are likely to be observed in these collection tubes matrices. Methods: We analyzed 189 metabolites using the same protocol for quantitative targeted metabolomics (LC-MS/MS AbsoluteIDQ p180 Kit Biocrates) in three types of samples, serum, plasma EDTA and citrate, of 80 subjects from the Cooperative Health Research In South Tyrol cohort (40 healthy elderly and 40 healthy young). Results: The concentration levels were higher in serum than citrate and EDTA, in particular for amino acids and biogenic amines. The average Pearson's correlation coefficients were however always higher than 0.7 for these two classes of metabolites. We could also demonstrate that blank EDTA vacutainer tubes contain a significant amount of sarcosine. Finally, we compared the metabolome of young people against elderly subjects and found that the highest number of metabolites significantly changing with age was detected in serum. Conclusion: Serum samples provide higher sensitivity for biomarker discovery studies. Due to the presence of spurious amount of sarcosine in vacutainer EDTA tubes, plasma EDTA is not suitable for studies requiring accurate quantification of sarcosine.

Ion mobility (IM) is a post ionization tool that can be used to separate lipid ions in the gas phase according to their charge, shape and size. IM can be combined with mass spectrometry (MS), adding three main benefits to traditional approaches for lipid analysis. First, IM allows determination of the collision cross section of a lipid molecule, a physicochemical property related to the conformational structure, which facilitates lipid identification. Second, IM improves the peak capacity and the signal-to-noise ratio, allowing the separation of interfering isobaric lipid species. Third, IM allows a new set of hybrid fragmentation experiments that combine collision-induced dissociation with gas phase separation, improving the specificity of the tandem MS-based approaches. Here, we review the current applications of IM-MS for lipid analysis.

Formalin-fixed paraffin-embedded (FFPE) tissue represents the primary source of clinical tissue and is routinely used in MALDI-MSI studies. However, it is not particularly suitable for lipidomics imaging given that many species are depleted during tissue processing. Irrespective, a number of solvent-resistant lipids remain, but their extraction may be hindered by the cross-link between proteins. Therefore, an antigen retrieval step could enable the extraction of a greater number of lipids and may provide information that is complementary to that which can be obtained from other biomolecules, such as proteins. In this short communication, we aim to address the effect of performing antigen retrieval prior to MALDI-MSI of lipids in FFPE tissue. As a result, an increased number of lipid signals could be detected and may have derived from lipid species that are known to be implicated in the lipid-protein cross-linking that is formed as a result of formalin fixation. Human renal cancer tissue was used as a proof of concept to determine whether using these detected lipid signals were also able to highlight the histopathological regions that were present. These preliminary findings may highlight the potential to enhance the clinical relevance of the lipidomic information obtained from FFPE tissue.