nanoRAPIDS as an analytical pipeline for the discovery of novel bioactive metabolites in complex culture extracts at the nanoscale.

Microbial natural products form the basis of most of the antibiotics used in the clinic. The vast majority has not yet been discovered, among others because the hidden chemical space is obscured by previously identified (and typically abundant) antibiotics in culture extracts. Efficient dereplication is therefore key to the discovery of our future medicines. Here we present an analytical platform for the efficient identification and prioritization of low abundance bioactive compounds at nanoliter scale, called nanoRAPIDS. NanoRAPIDS encompasses analytical scale separation and nanofractionation of natural extracts, followed by the bioassay of interest, automated mass spectrometry identification, and Global Natural Products Social molecular networking (GNPS) for dereplication. As little as 10 µL crude extract is fractionated into 384 fractions. First, bioactive congeners of iturins and surfactins were identified in Bacillus, based on their bioactivity. Subsequently, bioactive molecules were identified in an extensive network of angucyclines elicited by catechol in cultures of Streptomyces sp. This allowed the discovery of a highly unusual N-acetylcysteine conjugate of saquayamycin, despite low production levels in an otherwise abundant molecular family. These data underline the utility and broad application of the technology for the prioritization of minor bioactive compounds in complex extracts.

Capillary electrophoresis-mass spectrometry for creatinine analysis in residual clinical plasma samples and comparison with gold standard assay.

When hospitalized, infants, particularly preterm, are often subjected to multiple painful needle procedures to collect sufficient blood for metabolic screening or diagnostic purposes using standard clinical tests. For example, at least 100 µL of whole blood is required to perform one creatinine plasma measurement with enzymatic colorimetric assays. As capillary electrophoresis-mass spectrometry (CE-MS) utilizing a sheathless porous tip interface only requires limited amounts of sample for in-depth metabolic profiling studies, the aim of this work was to assess the utility of this method for the determination of creatinine in low amounts of plasma using residual blood samples from adults and infants. By using a starting amount of 5 µL of plasma and an injection volume of only 6.7 nL, a detection limit (S/N = 3) of 30 nM could be obtained for creatinine, and intra- and interday precisions (for peak area ratios) were below 3.2%. To shorten the electrophoretic separation time, a multi-segment injection (MSI) strategy was employed to analyze up to seven samples in one electrophoretic run. The findings obtained by CE-MS for creatinine in pretreated plasma were compared with the values acquired by an enzymatic colorimetric assay typically used in clinical laboratories for this purpose. The comparison revealed that CE-MS could be used in a reliable way for the determination of creatinine in residual plasma samples from infants and adults. Nevertheless, to underscore the clinical efficacy of this method, a subsequent investigation employing an expanded pool of plasma samples is imperative. This will not only enhance the method's diagnostic utility but also contribute to minimizing both the amount and frequency of blood collection required for diagnostic purposes.

Association of Altered Plasma Lipidome with Disease Severity in COVID-19 Patients.

The severity of COVID-19 is linked to an imbalanced immune response. The dysregulated metabolism of small molecules and bioactive lipids has also been associated with disease severity. To promote understanding of the disease biochemistry and provide targets for intervention, we applied a range of LC-MS platforms to analyze over 100 plasma samples from patients with varying COVID-19 severity and with detailed clinical information on inflammatory responses (>30 immune markers). This is the third publication in a series, and it reports the results of comprehensive lipidome profiling using targeted LC-MS/MS. We identified 1076 lipid features across 25 subclasses, including glycerophospholipids, sterols, glycerolipids, and sphingolipids, among which 531 lipid features were dramatically changed in the plasma of intensive care unit (ICU) patients compared to patients in the ward. Patients in the ICU showed 1.3-57-fold increases in ceramides, (lyso-)glycerophospholipids, diglycerides, triglycerides, and plasmagen phosphoethanolamines, and 1.3-2-fold lower levels of a cyclic lysophosphatidic acid, sphingosine-1-phosphates, sphingomyelins, arachidonic acid-containing phospholipids, lactosylceramide, and cholesterol esters compared to patients in the ward. Specifically, phosphatidylinositols (PIs) showed strong fatty acid saturation-dependent behavior, with saturated fatty acid (SFA)- and monosaturated fatty acid (MUFA)-derived PI decreasing and polystaturated (PUFA)-derived PI increasing. We also found ~4000 significant Spearman correlations between lipids and multiple clinical markers of immune response with |R| ≥ 0.35 and FDR corrected Q < 0.05. Except for lysophosphatidic acid, lysophospholipids were positively associated with the CD4 fraction of T cells, and the cytokines IL-8 and IL-18. In contrast, sphingosine-1-phosphates were negatively correlated with innate immune markers such as CRP and IL-6. Further indications of metabolic changes in moderate COVID-19 disease were demonstrated in recovering ward patients compared to those at the start of hospitalization, where 99 lipid species were altered (6 increased by 30-62%; 93 decreased by 1.3-2.8-fold). Overall, these findings support and expand on early reports that dysregulated lipid metabolism is involved in COVID-19.

A comprehensive UHPLC-MS/MS method for metabolomics profiling of signaling lipids: Markers of oxidative stress, immunity and inflammation.

Signaling lipids (SLs) play a crucial role in various signaling pathways, featuring diverse lipid backbone structures. Emerging evidence showing the biological significance and biomedical values of SLs has strongly spurred the advancement of analytical approaches aimed at profiling SLs. Nevertheless, the dramatic differences in endogenous abundances across lipid classes as well as multiple isomers within the same lipid class makes the development of a generic analytical method challenging. A better analytical method that combines comprehensive coverage and high sensitivity is needed to enable us to gain a deeper understanding of the biochemistry of these molecules in health and disease. In this study, we developed a fast and comprehensive targeted ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method for profiling SLs. The platform enables analyses of 260 metabolites covering oxylipins (isoprostanes, prostaglandins and other oxidized lipids), free fatty acids, lysophospholipids, sphingoid bases (C16, C18), platelet activating factors (C16, C18), endocannabinoids and bile acids. Various validation parameters including linearity, limit of detection, limit of quantification, extraction recovery, matrix effect, intra-day and inter-day precision were used to characterize this method. Metabolite quantitation was successfully achieved in both NIST Standard Reference Material for human plasma (NIST SRM 1950) and pooled human plasma, with 109 and 144 metabolites quantitated. The quantitation results in NIST SRM 1950 plasma demonstrated good correlations with certified or previously reported values in published literature. This study introduced quantitative data for 37 SLs for the first time. Metabolite concentrations measured in NIST SRM 1950 will serve as essential reference data for facilitating interlaboratory comparisons. The methodology established here will be the cornerstone for in-depth profiling of signaling lipids across diverse biological samples and contexts.

Longitudinal metabolite profiling of Streptococcus pneumoniae-associated community-acquired pneumonia.

INTRODUCTION: Longitudinal biomarkers in patients with community-acquired pneumonia (CAP) may help in monitoring of disease progression and treatment response. The metabolic host response could be a potential source of such biomarkers since it closely associates with the current health status of the patient. OBJECTIVES: In this study we performed longitudinal metabolite profiling in patients with CAP for a comprehensive range of metabolites to identify potential host response biomarkers. METHODS: Previously collected serum samples from CAP patients with confirmed Streptococcus pneumoniae infection (n = 25) were used. Samples were collected at multiple time points, up to 30 days after admission. A wide range of metabolites was measured, including amines, acylcarnitines, organic acids, and lipids. The associations between metabolites and C-reactive protein (CRP), procalcitonin, CURB disease severity score at admission, and total length of stay were evaluated. RESULTS: Distinct longitudinal profiles of metabolite profiles were identified, including cholesteryl esters, diacyl-phosphatidylethanolamine, diacylglycerols, lysophosphatidylcholines, sphingomyelin, and triglycerides. Positive correlations were found between CRP and phosphatidylcholine (34:1) (cor = 0.63) and negative correlations were found for CRP and nine lysophosphocholines (cor = - 0.57 to - 0.74). The CURB disease severity score was negatively associated with six metabolites, including acylcarnitines (tau = - 0.64 to - 0.58). Negative correlations were found between the length of stay and six triglycerides (TGs), especially TGs (60:3) and (58:2) (cor = - 0.63 and - 0.61). CONCLUSION: The identified metabolites may provide insight into biological mechanisms underlying disease severity and may be of interest for exploration as potential treatment response monitoring biomarker.

A comparison between different human hepatocyte models reveals profound differences in net glucose production, lipid composition and metabolism in vitro.

Hepatocytes are responsible for maintaining a stable blood glucose concentration during periods of nutrient scarcity. The breakdown of glycogen and de novo synthesis of glucose are crucial metabolic pathways deeply interlinked with lipid metabolism. Alterations in these pathways are often associated with metabolic diseases with serious clinical implications. Studying energy metabolism in human cells is challenging. Primary hepatocytes are still considered the golden standard for in vitro studies and have been instrumental in elucidating key aspects of energy metabolism found in vivo. As a result of several limitations posed by using primary cells, a multitude of alternative hepatocyte cellular models emerged as potential substitutes. Yet, there remains a lack of clarity regarding the precise applications for which these models accurately reflect the metabolic competence of primary hepatocytes. In this study, we compared primary hepatocytes, stem cell-derived hepatocytes, adult donor-derived liver organoids, immortalized Upcyte-hepatocytes and the hepatoma cell line HepG2s in their response to a glucose production challenge. We observed the highest net glucose production in primary hepatocytes, followed by organoids, stem-cell derived hepatocytes, Upcyte-hepatocytes and HepG2s. Glucogenic gene induction was observed in all tested models, as indicated by an increase in G6PC and PCK1 expression. Lipidomic analysis revealed considerable differences across the models, with organoids showing the closest similarity to primary hepatocytes in the common lipidome, comprising 347 lipid species across 19 classes. Changes in lipid profiles as a result of the glucose production challenge showed a variety of, and in some cases opposite, trends when compared to primary hepatocytes.

Development of an Untargeted LC-MS Metabolomics Method with Postcolumn Infusion for Matrix Effect Monitoring in Plasma and Feces.

Untargeted metabolomics based on reverse phase LC-MS (RPLC-MS) plays a crucial role in biomarker discovery across physiological and disease states. Standardizing the development process of untargeted methods requires paying attention to critical factors that are under discussed or easily overlooked, such as injection parameters, performance assessment, and matrix effect evaluation. In this study, we developed an untargeted metabolomics method for plasma and fecal samples with the optimization and evaluation of these factors. Our results showed that optimizing the reconstitution solvent and sample injection amount was critical for achieving the balance between metabolites coverage and signal linearity. Method validation with representative stable isotopically labeled standards (SILs) provided insights into the analytical performance evaluation of our method. To tackle the issue of the matrix effect, we implemented a postcolumn infusion (PCI) approach to monitor the overall absolute matrix effect (AME) and relative matrix effect (RME). The monitoring revealed distinct AME and RME profiles in plasma and feces. Comparing RME data obtained for SILs through postextraction spiking with those monitored using PCI compounds demonstrated the comparability of these two methods for RME assessment. Therefore, we applied the PCI approach to predict the RME of 305 target compounds covered in our in-house library and found that targets detected in the negative polarity were more vulnerable to the RME, regardless of the sample matrix. Given the value of this PCI approach in identifying the strengths and weaknesses of our method in terms of the matrix effect, we recommend implementing a PCI approach during method development and applying it routinely in untargeted metabolomics.

Targeted proteomics and metabolomics for biomarker discovery in abdominal aortic aneurysm and post-EVAR sac volume.

BACKGROUND AND AIMS: Abdominal aortic aneurysm (AAA) patients undergo uniform surveillance programs both leading up to, and following surgery. Circulating biomarkers could play a pivotal role in individualizing surveillance. We applied a multi-omics approach to identify relevant biomarkers and gain pathophysiological insights. MATERIALS AND METHODS: In this cross-sectional study, 108 AAA patients and 200 post-endovascular aneurysm repair (post-EVAR) patients were separately investigated. We performed partial least squares regression and ingenuity pathway analysis on circulating concentrations of 96 proteins (92 Olink Cardiovascular-III panel, 4 ELISA-assays) and 199 metabolites (measured by LC-TQMS), and their associations with CT-based AAA/sac volume. RESULTS: The median (25th-75th percentile) maximal diameter was 50.0 mm (46.0, 53.0) in the AAA group, and 55.4 mm (45.0, 64.2) in the post-EVAR group. Correcting for clinical characteristics in AAA patients, the aneurysm volume Z-score differed 0.068 (95 %CI: (0.042, 0.093)), 0.066 (0.047, 0.085) and -0.051 (-0.064, -0.038) per Z-score valine, leucine and uPA, respectively. After correcting for clinical characteristics and orthogonalization in the post-EVAR group, the sac volume Z-score differed 0.049 (0.034, 0.063) per Z-score TIMP-4, -0.050 (-0.064, -0.037) per Z-score LDL-receptor, -0.051 (-0.062, -0.040) per Z-score 1-OG/2-OG and -0.056 (-0.066, -0.045) per Z-score 1-LG/2-LG. CONCLUSIONS: The branched-chain amino acids and uPA were related to AAA volume. For post-EVAR patients, LDL-receptor, monoacylglycerols and TIMP-4 are potential biomarkers for sac volume. Additionally, distinct markers for sac change were identified.

Cold-induced changes in plasma signaling lipids are associated with a healthier cardiometabolic profile independently of brown adipose tissue.

Cold exposure activates brown adipose tissue (BAT) and potentially improves cardiometabolic health through the secretion of signaling lipids by BAT. Here, we show that 2 h of cold exposure in young adults increases the levels of omega-6 and omega-3 oxylipins, the endocannabinoids (eCBs) anandamide and docosahexaenoylethanolamine, and lysophospholipids containing polyunsaturated fatty acids. Contrarily, it decreases the levels of the eCBs 1-LG and 2-LG and 1-OG and 2-OG, lysophosphatidic acids, and lysophosphatidylethanolamines. Participants overweight or obese show smaller increases in omega-6 and omega-3 oxylipins levels compared to normal weight. We observe that only a small proportion (∼4% on average) of the cold-induced changes in the plasma signaling lipids are slightly correlated with BAT volume. However, cold-induced changes in omega-6 and omega-3 oxylipins are negatively correlated with adiposity, glucose homeostasis, lipid profile, and liver parameters. Lastly, a 24-week exercise-based randomized controlled trial does not modify plasma signaling lipid response to cold exposure.

Development of targeted hydrophilic interaction liquid chromatography-tandem mass spectrometry method for acyl-Coenzyme A covering short- to long-chain species in a single analytical run.

Acyl-CoAs play a significant role in numerous physiological and metabolic processes making it important to assess their concentration levels for evaluating metabolic health. Considering the important role of acyl-CoAs, it is crucial to develop an analytical method that can analyze these compounds. Due to the structural variations of acyl-CoAs, multiple analytical methods are often required for comprehensive analysis of these compounds, which increases complexity and the analysis time. In this study, we have developed a method using a zwitterionic HILIC column that enables the coverage of free CoA and short- to long-chain acyl-CoA species in one analytical run. Initially, we developed the method using an LC-QTOF instrument for the identification of acyl-CoA species and optimizing their chromatography. Later, a targeted HILIC-MS/MS method was created in scheduled multiple reaction monitoring mode using a QTRAP MS detector. The performance of the method was evaluated based on various parameters such as linearity, precision, recovery and matrix effect. This method was applied to identify the difference in acyl-CoA profiles in HepG2 cells cultured in different conditions. Our findings revealed an increase in levels of acetyl-CoA, medium- and long-chain acyl-CoA while a decrease in the profiles of free CoA in the starved state, indicating a clear alteration in the fatty acid oxidation process.

Integrative multi-omics analysis of genomic, epigenomic, and metabolomics data leads to new insights for Attention-Deficit/Hyperactivity Disorder.

The evolving field of multi-omics combines data and provides methods for simultaneous analysis across several omics levels. Here, we integrated genomics (transmitted and non-transmitted polygenic scores [PGSs]), epigenomics, and metabolomics data in a multi-omics framework to identify biomarkers for Attention-Deficit/Hyperactivity Disorder (ADHD) and investigated the connections among the three omics levels. We first trained single- and next multi-omics models to differentiate between cases and controls in 596 twins (cases = 14.8%) from the Netherlands Twin Register (NTR) demonstrating reasonable in-sample prediction through cross-validation. The multi-omics model selected 30 PGSs, 143 CpGs, and 90 metabolites. We confirmed previous associations of ADHD with glucocorticoid exposure and the transmembrane protein family TMEM, show that the DNA methylation of the MAD1L1 gene associated with ADHD has a relation with parental smoking behavior, and present novel findings including associations between indirect genetic effects and CpGs of the STAP2 gene. However, out-of-sample prediction in NTR participants (N = 258, cases = 14.3%) and in a clinical sample (N = 145, cases = 51%) did not perform well (range misclassification was [0.40, 0.57]). The results highlighted connections between omics levels, with the strongest connections between non-transmitted PGSs, CpGs, and amino acid levels and show that multi-omics designs considering interrelated omics levels can help unravel the complex biology underlying ADHD.

A monoacylglycerol lipase inhibitor showing therapeutic efficacy in mice without central side effects or dependence.

Monoacylglycerol lipase (MAGL) regulates endocannabinoid 2-arachidonoylglycerol (2-AG) and eicosanoid signalling. MAGL inhibition provides therapeutic opportunities but clinical potential is limited by central nervous system (CNS)-mediated side effects. Here, we report the discovery of LEI-515, a peripherally restricted, reversible MAGL inhibitor, using high throughput screening and a medicinal chemistry programme. LEI-515 increased 2-AG levels in peripheral organs, but not mouse brain. LEI-515 attenuated liver necrosis, oxidative stress and inflammation in a CCl4-induced acute liver injury model. LEI-515 suppressed chemotherapy-induced neuropathic nociception in mice without inducing cardinal signs of CB1 activation. Antinociceptive efficacy of LEI-515 was blocked by CB2, but not CB1, antagonists. The CB1 antagonist rimonabant precipitated signs of physical dependence in mice treated chronically with a global MAGL inhibitor (JZL184), and an orthosteric cannabinoid agonist (WIN55,212-2), but not with LEI-515. Our data support targeting peripheral MAGL as a promising therapeutic strategy for developing safe and effective anti-inflammatory and analgesic agents.

Application of a capillary electrophoresis-mass spectrometry metabolomics workflow in zebrafish larvae reveals new effects of cortisol.

In contemporary biomedical research, the zebrafish (Danio rerio) is increasingly considered a model system, as zebrafish embryos and larvae can (potentially) fill the gap between cultured cells and mammalian animal models, because they can be obtained in large numbers, are small and can easily be manipulated genetically. Given that capillary electrophoresis-mass spectrometry (CE-MS) is a useful analytical separation technique for the analysis of polar ionogenic metabolites in biomass-limited samples, the aim of this study was to develop and assess a CE-MS-based analytical workflow for the profiling of (endogenous) metabolites in extracts from individual zebrafish larvae and pools of small numbers of larvae. The developed CE-MS workflow was used to profile metabolites in extracts from pools of 1, 2, 4, 8, 12, 16, 20, and 40 zebrafish larvae. For six selected endogenous metabolites, a linear response (R2  > 0.98) for peak areas was obtained in extracts from these pools. The repeatability was satisfactory, with inter-day relative standard deviation values for peak area of 9.4%-17.7% for biological replicates (n = 3 over 3 days). Furthermore, the method allowed the analysis of over 70 endogenous metabolites in a pool of 12 zebrafish larvae, and 29 endogenous metabolites in an extract from only 1 zebrafish larva. Finally, we applied the optimized CE-MS workflow to identify potential novel targets of the mineralocorticoid receptor in mediating the effects of cortisol.

Higher plasma levels of endocannabinoids and analogues correlate with a worse cardiometabolic profile in young adults.

BACKGROUND AND AIM: The endocannabinoid system is a signalling system composed of endocannabinoids (eCBs), their receptors, and the enzymes involved in their synthesis and metabolism. Alterations in the ECS are linked to the development of cardiometabolic diseases. Here, we investigated the relationship between plasma levels of eCBs and their analogues with body composition and cardiometabolic risk factors. METHODS: The study included 133 young adults (age 22.1 ± 2.2 years, 67% women). Fasting plasma levels of eCBs and their analogues were measured using liquid chromatography-tandem mass spectrometry. Body composition, brown adipose tissue (BAT) volume, glucose uptake, and traditional cardiometabolic risk factors were measured. RESULTS: Plasma levels of eCBs and several eCB analogues were positively correlated with adiposity and traditional cardiometabolic risk factors (e.g., serum insulin and triacylglycerides levels, all r ≥ 0.17 and p ≤ 0.045). Plasma levels of 2-AG and PDEA were negatively correlated with BAT volume and glucose uptake (all r ≤ -0.17 and P ≤ 0.047). We observed that the plasma levels of eCBs and their analogues were higher in metabolically unhealthy overweight-obese participants than in metabolically healthy overweight-obese participants. CONCLUSION: Our findings show that the plasma levels of eCBs and their analogues are related to higher levels of adiposity and worse cardiometabolic profile.

Cardinality optimization in constraint-based modelling: application to human metabolism.

MOTIVATION: Several applications in constraint-based modelling can be mathematically formulated as cardinality optimization problems involving the minimization or maximization of the number of nonzeros in a vector. These problems include testing for stoichiometric consistency, testing for flux consistency, testing for thermodynamic flux consistency, computing sparse solutions to flux balance analysis problems and computing the minimum number of constraints to relax to render an infeasible flux balance analysis problem feasible. Such cardinality optimization problems are computationally complex, with no known polynomial time algorithms capable of returning an exact and globally optimal solution. RESULTS: By approximating the zero-norm with nonconvex continuous functions, we reformulate a set of cardinality optimization problems in constraint-based modelling into a difference of convex functions. We implemented and numerically tested novel algorithms that approximately solve the reformulated problems using a sequence of convex programs. We applied these algorithms to various biochemical networks and demonstrate that our algorithms match or outperform existing related approaches. In particular, we illustrate the efficiency and practical utility of our algorithms for cardinality optimization problems that arise when extracting a model ready for thermodynamic flux balance analysis given a human metabolic reconstruction. AVAILABILITY AND IMPLEMENTATION: Open source scripts to reproduce the results are here https://github.com/opencobra/COBRA.papers/2023_cardOpt with general purpose functions integrated within the COnstraint-Based Reconstruction and Analysis toolbox: https://github.com/opencobra/cobratoolbox.

Opportunities and challenges for sample preparation and enrichment in mass spectrometry for single-cell metabolomics.

Single-cell heterogeneity in metabolism, drug resistance and disease type poses the need for analytical techniques for single-cell analysis. As the metabolome provides the closest view of the status quo in the cell, studying the metabolome at single-cell resolution may unravel said heterogeneity. A challenge in single-cell metabolome analysis is that metabolites cannot be amplified, so one needs to deal with picolitre volumes and a wide range of analyte concentrations. Due to high sensitivity and resolution, MS is preferred in single-cell metabolomics. Large numbers of cells need to be analysed for proper statistics; this requires high-throughput analysis, and hence automation of the analytical workflow. Significant advances in (micro)sampling methods, CE and ion mobility spectrometry have been made, some of which have been applied in high-throughput analyses. Microfluidics has enabled an automation of cell picking and metabolite extraction; image recognition has enabled automated cell identification. Many techniques have been used for data analysis, varying from conventional techniques to novel combinations of advanced chemometric approaches. Steps have been set in making data more findable, accessible, interoperable and reusable, but significant opportunities for improvement remain. Herein, advances in single-cell analysis workflows and data analysis are discussed, and recommendations are made based on the experimental goal.

Development of a targeted hydrophilic interaction liquid chromatography-tandem mass spectrometry based lipidomics platform applied to a coronavirus disease severity study.

The importance of lipids seen in studies of metabolism, cancer, the recent COVID-19 pandemic and other diseases has brought the field of lipidomics to the forefront of clinical research. Quantitative and comprehensive analysis is required to understand biological interactions among lipid species. However, lipidomic analysis is often challenging due to the various compositional structures, diverse physicochemical properties, and wide dynamic range of concentrations of lipids in biological systems. To study the comprehensive lipidome, a hydrophilic interaction liquid chromatography-tandem mass spectrometry (HILIC-MS/MS)-based screening method with 1200 lipid features across 19 (sub)classes, including both nonpolar and polar lipids, has been developed. HILIC-MS/MS was selected due to its class separation property and fatty acyl chain level information. 3D models of class chromatographic retention behavior were established and evaluations of cross-class and within-class interferences were performed to avoid over-reporting these features. This targeted HILIC-MS/MS method was fully validated, with acceptable analytical parameters in terms of linearity, precision, reproducibility, and recovery. The accurate quantitation of 608 lipid species in the SRM 1950 NIST plasma was achieved using multi-internal standards per class and post-hoc correction, extending current databases by providing lipid concentrations resolved at fatty acyl chain level. The overall correlation coefficients (R2) of measured concentrations with values from literature range from 0.64 to 0.84. The applicability of the developed targeted lipidomics method was demonstrated by discovering 520 differential lipid features related to COVID-19 severity. This high coverage and targeted approach will aid in future investigations of the lipidome in various disease contexts.

Effect of bariatric surgery on NAFLD/NASH: a single-centre observational prospective cohort study.

INTRODUCTION: The prevalence of non-alcoholic fatty liver disease (NAFLD) ranges from 25% in the general population to 90% in patients with obesity scheduled for bariatric surgery. NAFLD can progress towards non-alcoholic steatohepatitis (NASH) associated with complications such as cirrhosis, hepatocellular carcinoma and cardiovascular disease. To date, losing weight and lifestyle modifications are the best known treatments for NASH. Bariatric surgery significantly improves NAFLD/NASH in the short term. However, the extent of this improvement is not yet clear and long-term data on the natural course of NAFLD/NASH after bariatric surgery are lacking. The factors involved in NAFLD/NASH regression after bariatric surgery have not been elucidated. METHODS AND ANALYSIS: This is an observational prospective cohort study including patients scheduled for bariatric surgery. Extensive metabolic and cardiovascular analyses will be carried out including measurements of carotid intima media thickness and pulse wave velocity. Genomic, proteomic, lipidomic and metabolomic studies will be done. Microbioma analyses before and 1 year after surgery will be done. Transient elastography measurements will be performed before and at 1, 3 and 5 years after surgery. For those with an elevated preoperative transient elastography measurement by Fibroscan, a laparoscopic liver biopsy will be performed during surgery. Primary outcome measures are the change of steatosis and liver fibrosis 5 years after surgery. Secondary outcome measure is the comparison of the transient elastography measurements with the NAFLD Activity Score from the biopsies. ETHICS AND DISSEMINATION: The protocol has been approved by the Medical Research Ethics Committees United, Nieuwegein, on 1 March 2022 (registration code R21.103/NL79423.100.21). The study results will be submitted for publication in peer-reviewed journals and data will be presented at scientific meetings. TRIAL REGISTRATION NUMBER: NCT05499949.

Microfluidics and Organoids, the Power Couple of Developmental Biology and Oncology Studies.

Organoids are an advanced cell model that hold the key to unlocking a deeper understanding of in vivo cellular processes. This model can be used in understanding organ development, disease progression, and treatment efficacy. As the scientific world embraces the model, it must also establish the best practices for cultivating organoids and utilizing them to the greatest potential in assays. Microfluidic devices are emerging as a solution to overcome the challenges of organoids and adapt assays. Unfortunately, the various applications of organoids often depend on specific features in a device. In this review, we discuss the options and considerations for features and materials depending on the application and development of the organoid.

Single-cell metabolomics by mass spectrometry: ready for primetime?

Single-cell metabolomics (SCMs) is a powerful tool for studying cellular heterogeneity by providing insight into the differences between individual cells. With the development of a set of promising SCMs pipelines, this maturing technology is expected to be widely used in biomedical research. However, before SCMs is ready for primetime, there are some challenges to overcome. In this review, we summarize the trends and challenges in the development of SCMs. We also highlight the latest methodologies, applications, and sketch the perspective for integration with other omics and imaging approaches.