Development of a generic sample preparation method using dispersive liquid-liquid microextraction for the monitoring of leachable compounds in hospital pharmacy-prepared prefilled drug products.

Performant sample preparation is mandatory in any leachable study to clean and preconcentrate analytes within the sample to offer the best possible extraction recovery as well the best precision for any given substance. The aim consists in developing a sample preparation method for hospital pharmacy-prepared drug products such as long-term storage prefilled syringes, vials and IV bags for the screening of leachable compounds. The Quality Control Laboratory of the Pharmacy of the Lausanne University Hospital (Switzerland) has developed a time- and cost-effective, highly sensitive, robust, and fast method using liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) for the analysis of 205 plastic additives. An innovative setup, based on postcolumn infusion (PCI) using 2% ammonium hydroxide in methanol was used to boost the signal intensity of the analytes in MS detection. A database for extractable and leachable trace assessment (DELTA) was built to assist in the screening process of 205 plastic packaging-related compounds. The development of the sample preparation was based on 33 plastic additive candidates in different hospital pharmacy compounding solutions, and their extraction recovery rates as well as their relative standard deviation were taken into consideration. In conclusion, the developed DLLME was assigned with ultrasound assistance and triple extraction, which brought about extraction recovery rates between 67% and 92%, a good RSD <10%, and a preconcentration factor of 50×. Therefore, DLLME could be considered suitable for the semiquantitative screening of leachable additives in simple hospital pharmacy-prepared prefilled drug products.

Comprehensive plasma steroidomics reveals subtle alterations of systemic steroid profile in patients at different stages of prostate cancer disease.

The steroid submetabolome, or steroidome, is of particular interest in prostate cancer (PCa) as the dependence of PCa growth on androgens is well known and has been routinely exploited in treatment for decades. Nevertheless, the community is still far from a comprehensive understanding of steroid involvement in PCa both at the tissue and at systemic level. In this study we used liquid chromatography/high resolution mass spectrometry (LC/HRMS) backed by a dynamic retention time database DynaSTI to obtain a readout on circulating steroids in a cohort reflecting a progression of the PCa. Hence, 60 relevant compounds were annotated in the resulting LC/HRMS data, including 22 unknown steroid isomers therein. Principal component analysis revealed only subtle alterations of the systemic steroidome in the study groups. Next, a supervised approach allowed for a differentiation between the healthy state and any of the stages of the disease. Subsequent clustering of steroid metabolites revealed two groups responsible for this outcome: one consisted primarily of the androgens, whereas another contained corticosterone and its metabolites. The androgen data supported the currently established involvement of a hypothalamic-pituitary-gonadal axis in the development of PCa, whereas biological role of corticosterone remained elusive. On top of that, current results suggested a need for improvement in the dynamic range of the analytical methods to better understand the role of low abundant steroids, as the analysis revealed an involvement of estrogen metabolites. In particular, 2-hydroxyestradiol-3-methylether, one of the compounds present in the disease phenotype, was annotated and reported for the first time in men.

Activation of endogenous glucocorticoids by HSD11B1 inhibits the antitumor immune response in renal cancer.

Although immune-based therapies have revolutionized the management of cancer, novel approaches are urgently needed to improve their outcome. We investigated the role of endogenous steroids in the resistance to cancer immunotherapy, as these have strong immunomodulatory functions. Using a publicly available database, we found that the intratumoral expression of 11 beta-hydroxysteroid dehydrogenase type 1 (HSD11B1), which regenerates inactive glucocorticoids into active glucocorticoids, was associated with poor clinical outcome and correlated with immunosuppressive gene signatures in patients with renal cell carcinoma (RCC). HSD11B1 was mainly expressed in tumor-infiltrating immune myeloid cells as seen by immunohistochemistry in RCC patient samples. Using peripheral blood mononuclear cells from healthy donors or immune cells isolated from the tumor of RCC patients, we showed that the pharmacological inhibition of HSD11B1 improved the response to the immune checkpoint inhibitor anti-PD-1. In a subcutaneous mouse model of renal cancer, the combination of an HSD11B1 inhibitor with anti-PD-1 treatment increased the proportion of tumor-infiltrating dendritic cells. In an intrarenal mouse tumor model, HSD11B1 inhibition increased the survival of mice treated with anti-PD-1. In addition, inhibition of HSD11B1 sensitized renal tumors in mice to immunotherapy with resiquimod, a Toll-like receptor 7 agonist. Mechanistically, we demonstrated that HSD11B1 inhibition combined with resiquimod increased T cell-mediated cytotoxicity to tumor cells by stimulating the antigen-presenting capacity of dendritic cells. In conclusion, these results support the use of HSD11B1 inhibitors to improve the outcome of immunotherapy in renal cancer and highlight the role of the endogenous glucocorticoid metabolism in the efficacy of immunotherapy.

Gonadotropin axis and semen quality in young Swiss men after cannabis consumption: Effect of chronicity and modulation by cannabidiol.

BACKGROUND: While cannabis is the most widely used recreational drug in the world, the effects of phytocannabinoids on semen parameters and reproductive hormones remain controversial. Cannabinoid receptors are activated by these compounds at each level of the hypothalamus-pituitary-gonadotropic axis. OBJECTIVES: To assess the impact of the consumption of Δ-9-tetrahydrocannabinol and cannabidiol on semen parameters, as well as on male reproductive hormone and endocannabinoid levels, in a cohort of young Swiss men. MATERIALS AND METHODS: The individuals in a Swiss cohort were divided according to their cannabis consumption. In the cannabis user group, we determined the delay between the last intake of cannabis and sample collection, the chronicity of use and the presence of cannabidiol in the consumed product. Urinary Δ-9-tetrahydrocannabinol metabolites were quantified via gas chromatography-mass spectrometry. Blood phytocannabinoids, endocannabinoids and male steroids were determined via liquid chromatography-mass spectrometry/mass spectrometry, and other hypothalamus-pituitary-gonadotropic axis hormones were determined via immunoassays. Semen parameters such as sperm concentration and motility were recorded using computer-assisted sperm analysis. RESULTS: Anandamide, N-palmitoyl ethanolamide, androgens, estradiol and sex hormone binding globulin levels were all higher in cannabis users, particularly in chronic, recent and cannabidiol-positive consumers. Gonadotropin levels were not significantly different in these user subpopulations, whereas prolactin and albumin concentrations were lower. In addition, cannabis users had a more basic semen pH and a higher percentage of spermatozoa with progressive motility. However, the two latter observations seem to be related to a shorter period of sexual abstinence in this group rather than to the use of cannabis. CONCLUSIONS: Because both cannabidiol and Δ-9-tetrahydrocannabinol are frequently used by men of reproductive age, it is highly relevant to elucidate the potential effects they may have on human reproductive health. This study demonstrates that the mode of cannabis consumption must be considered when evaluating the effect of cannabis on semen quality.

Development of a generic approach for monitoring leachable compounds in hospital pharmacy-prepared prefilled plastic packaging by ultrahigh-performance liquid chromatography coupled to high-resolution mass spectrometry with postcolumn infusion.

Prefilled plastic packaging is time- and cost-effective in hospital pharmacy because it prevents waste, preparation errors, dosage errors, microbial contamination and accidents. This packaging mostly includes prefilled syringes (PFS), intravenous (IV) bags and vials intended for long-term storage that can be used for immediate treatment. There is a rising availability in the market for prefilled drug products due to their practical approach. Leachable compounds could be evaluated in hospital pharmacy-prepared prefilled drug solutions. The Pharmacy Department at the Lausanne University Hospital has developed an innovative, highly sensitive, and generic method by postcolumn infusion based on ultrahigh-performance liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) for the analysis of plastic additives in hospital pharmacies. The postcolumn infusion solution was developed with 2% ammonium hydroxide in methanol on a representative set of 30 candidate compounds with different physical-chemical properties, such as log P and molecular structure, to represent the most important categories of additives. The LODs obtained for all compounds ranged from 0.03 to 7.91 ng/mL with linearity up to 250 ng/mL. Through this screening method, plastic additives can be rapidly identified due to the combined use of retention time, exact mass (including isotopic pattern) and MS/MS spectra. In addition, the users can screen for vast categories of plastic additives, including plasticizers, epoxy monomers, antioxidants, UV stabilizers, and others. The screening is facilitated by assessments of a complex in-house-built database for extractable and leachable trace assessment (DELTA), containing 205 compounds for unambiguous identification. Relative response factors were established for all analytes to obtain a semiquantitation of compounds. Moreover, the database also contains valuable estimative toxicology information, which was obtained through calculating their permissible dose exposure threshold; thus, estimative toxicology assessment can be performed for identified compounds in prefilled drug products. This method and the database were applied to a hospital pharmacy-prepared prefilled vancomycin syringe for paediatric use. Ultrasound-assisted dispersive liquid-liquid microextraction (UA-DLLME) was used to prepare the samples for leachable analysis. As a result, 17 plastic additives were formally identified, and their concentrations were estimated. A toxicology assessment was performed by comparing their concentrations with their theoretical PDE thresholds. In conclusion, the prefilled drug solution released a negligible amount of known leachables that appeared to be safe for use in neonates and children.

Multitargeted Internal Calibration for the Quantification of Chronic Kidney Disease-Related Endogenous Metabolites Using Liquid Chromatography-Mass Spectrometry.

Accurate quantitative analysis in liquid chromatography-mass spectrometry (LC-MS) benefits from calibration curves generated in the same matrix as the study sample. In the case of endogenous compound quantification, as no blank matrix exists, the multitargeted internal calibration (MTIC) is an attractive and straightforward approach to avoid the need for extensive matrix similarity evaluation. Its principle is to take advantage of stable isotope labeled (SIL) standards as internal calibrants to simultaneously quantify authentic analytes using a within sample calibration. An MTIC workflow was developed for the simultaneous quantification of metabolites related to chronic kidney disease (CKD) using a volumetric microsampling device to collect 20 µL of serum or plasma, followed by a single-step extraction with acetonitrile/water and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Since a single concentration of internal calibrant is necessary to calculate the study sample concentration, the instrument response function was investigated to determine the best SIL concentration. After validation, the trueness of 16 endogenous analytes in authentic human serum ranged from 72.2 to 116.0%, the repeatability from 1.9 to 11.3%, and the intermediate precision ranged overall from 2.1 to 15.4%. The proposed approach was applied to plasma samples collected from healthy control participants and two patient groups diagnosed with CKD. Results confirmed substantial concentration differences between groups for several analytes, including indoxyl sulfate and cortisone, as well as metabolite enrichment in the kynurenine and indole pathways. Multitargeted methodologies represent a major step toward rapid and straightforward LC-MS/MS absolute quantification of endogenous biomarkers, which could change the paradigm of MS use in clinical laboratories.

Straightforward quantification of endogenous steroids with liquid chromatography-tandem mass spectrometry: Comparing calibration approaches.

Different calibration strategies are used in liquid chromatography hyphenated to mass spectrometry (LC-MS) bioanalysis. Currently, the surrogate matrix and surrogate analyte represent the most widely used approaches to compensate for the lack of analyte-free matrices in endogenous compounds quantification. In this context, there is a growing interest in rationalizing and simplifying quantitative analysis using a one-point concentration level of stable isotope-labeled (SIL) standards as surrogate calibrants. Accordingly, an internal calibration (IC) can be applied when the instrument response is translated into analyte concentration via the analyte-to-SIL ratio performed directly in the study sample. Since SILs are generally used as internal standards to normalize variability between authentic study sample matrix and surrogate matrix used for the calibration, IC can be calculated even if the calibration protocol was achieved for an external calibration (EC). In this study, a complete dataset of a published and fully validated method to quantify an extended steroid profile in serum was recomputed by adapting the role of SIL internal standards as surrogate calibrants. Using the validation samples, the quantitative performances for IC were comparable with the original method, showing acceptable trueness (79%-115%) and precision (0.8%-11.8%) for the 21 detected steroids. The IC methodology was then applied to human serum samples (n = 51) from healthy women and women diagnosed with mild hyperandrogenism, showing high agreement (R2 > 0.98) with the concentrations obtained using the conventional quantification based on EC. For IC, Passing-Bablok regression showed proportional biases between -15.0% and 11.3% for all quantified steroids, with an average difference of -5.8% compared to EC. These results highlight the reliability and the advantages of implementing IC in clinical laboratories routine to simplify quantification in LC-MS bioanalysis, especially when a large panel of analytes is monitored.

Targeted metabolomic profiling as a tool for diagnostics of patients with non-small-cell lung cancer.

Lung cancer is referred to as the second most common cancer worldwide and is mainly associated with complex diagnostics and the absence of personalized therapy. Metabolomics may provide significant insights into the improvement of lung cancer diagnostics through identification of the specific biomarkers or biomarker panels that characterize the pathological state of the patient. We performed targeted metabolomic profiling of plasma samples from individuals with non-small cell lung cancer (NSLC, n = 100) and individuals without any cancer or chronic pathologies (n = 100) to identify the relationship between plasma endogenous metabolites and NSLC by means of modern comprehensive bioinformatics tools, including univariate analysis, multivariate analysis, partial correlation network analysis and machine learning. Through the comparison of metabolomic profiles of patients with NSCLC and noncancer individuals, we identified significant alterations in the concentration levels of metabolites mainly related to tryptophan metabolism, the TCA cycle, the urea cycle and lipid metabolism. Additionally, partial correlation network analysis revealed new ratios of the metabolites that significantly distinguished the considered groups of participants. Using the identified significantly altered metabolites and their ratios, we developed a machine learning classification model with an ROC AUC value equal to 0.96. The developed machine learning lung cancer model may serve as a prototype of the approach for the in-time diagnostics of lung cancer that in the future may be introduced in routine clinical use. Overall, we have demonstrated that the combination of metabolomics and up-to-date bioinformatics can be used as a potential tool for proper diagnostics of patients with NSCLC.

Low-polarity untargeted metabolomic profiling as a tool to gain insight into seminal fluid.

INTRODUCTION: A decrease in sperm cell count has been observed along the last several decades, especially in the most developed regions of the world. The use of metabolomics to study the composition of the seminal fluid is a promising approach to gain access to the molecular mechanisms underlying this fact. OBJECTIVES: In the present work, we aimed at relating metabolomic profiles of young healthy men to their semen quality parameters obtained from conventional microscopic analysis. METHODS: An untargeted metabolomics approach focusing on low- to mid-polarity compounds was used to analyze a subset of seminal fluid samples from a cohort of over 2700 young healthy men. RESULTS: Our results show that a broad metabolic profiling comprising several families of compounds (including acyl-carnitines, steroids, and other lipids) can contribute to effectively distinguish samples provided by individuals exhibiting low or high absolute sperm counts. CONCLUSION: A number of metabolites involved in sexual development and function, signaling, and energy metabolism were highlighted as being distinctive of samples coming from either group, proving untargeted metabolomics as a promising tool to better understand the pathophysiological processes responsible for male fertility impairment.

A new multimodal paradigm for biomarkers longitudinal monitoring: a clinical application to women steroid profiles in urine and blood.

BACKGROUND: Most current state-of-the-art strategies to generate individual adaptive reference ranges are designed to monitor one clinical parameter at a time. An innovative methodology is proposed for the simultaneous longitudinal monitoring of multiple biomarkers. The estimation of individual thresholds is performed by applying a Bayesian modeling strategy to a multivariate score integrating several biomarkers (compound concentration and/or ratio). This multimodal monitoring was applied to data from a clinical study involving 14 female volunteers with normal menstrual cycles receiving testosterone via transdermal route, as to test its ability to detect testosterone administration. The study samples consisted of urine and blood collected during 4 weeks of a control phase and 4 weeks with a daily testosterone gel application. RESULTS: Integrating multiple biomarkers improved the detection of testosterone gel administration with substantially higher sensitivity compared with the distinct follow-up of each biomarker, when applied to selected urine and serum steroid biomarkers, as well as the combination of both. Among the 175 known positive samples, 38% were identified by the multimodal approach using urine biomarkers, 79% using serum biomarkers and 83% by combining biomarkers from both biological matrices, whereas 10%, 67% and 64% were respectively detected using standard unimodal monitoring. SIGNIFICANCE AND NOVELTY: The detection of abnormal patterns can be improved using multimodal approaches. The combination of urine and serum biomarkers reduced the overall number of false-negatives, thus evidencing promising complementarity between urine and blood sampling for doping control, as highlighted in the case of the use of transdermal testosterone preparations. The generation in a multimodal setting of adaptive and personalized reference ranges opens up new opportunities in clinical and anti-doping profiling. The integration of multiple parameters in a longitudinal monitoring is expected to provide a more complete evaluation of individual profiles generating actionable intelligence to further guide sample collection, analysis protocols and decision-making in clinics and anti-doping.

A unified strategy to rebalance multifactorial designs with unequal group sizes: application to analysis of variance multiblock orthogonal partial least squares.

BACKGROUND: Adequately handling unbalanced groups remains one of the major challenges for the analysis of multivariate data collected from multifactorial experimental designs. While partial least squares-based methods, such as analysis of variance multiblock orthogonal partial least squares (AMOPLS), can offer better discrimination between factor levels, they can be more heavily affected by this issue, and unbalanced designs of experiments may lead to a substantial confusion of the effects. Even state-of-the-art analysis of variance (ANOVA) decomposition methodologies using general linear models (GLM) lack the ability to efficiently disentangle these sources of variation when combined with AMOPLS. RESULTS: A versatile solution developed as an extension of a prior rebalancing strategy is proposed for the first decomposition step based on ANOVA. This approach has the advantage of yielding an unbiased estimation of the parameters and retaining the within-group variation in the rebalanced design, while preserving the orthogonality of effect matrices, even in presence of unequal group sizes. This property is of utmost importance for model interpretation because it avoids mixing sources of variation related to the different effects in the design. A real case study involving metabolomic data from in vitro toxicological experiments was used to demonstrate the potential of this strategy to handle unequal group sizes using a supervised approach. Primary 3D rat neural cell cultures were exposed to trimethyltin following a multifactorial design of experiments involving three fixed effect factors. SIGNIFICANCE AND NOVELTY: The rebalancing strategy was demonstrated as a novel and potent solution to handle unbalanced experimental designs by offering unbiased parameter estimators and orthogonal submatrices, thus avoiding confusion of the effects and facilitating model interpretation. Moreover, it can be combined with any multivariate method used for the analysis of high-dimensional data collected from multifactorial designs.

Extended steroid profiling in H295R cells provides deeper insight into chemical-induced disturbances of steroidogenesis: Exemplified by prochloraz and anabolic steroids.

Human adrenocortical H295R cells have been validated by the OECD Test Guideline 456 to detect chemicals disrupting testosterone and 17ß-estradiol (estradiol) biosynthesis. This study evaluated a novel approach to detect disturbances of steroidogenesis in H295R cells, exemplified by prochloraz and five anabolic steroids. Steroid profiles were assessed by an untargeted LC-MS-based method, providing a relative quantification of 57 steroids annotated according to their accurate masses and retention times. Such a panel of steroids included several mineralocorticoids, glucocorticoids, progestins and adrenal androgens. The coverage of a high number of metabolites in this extended steroid profiling facilitated grouping of chemicals with similar effects and detecting subtler differences between chemicals. It allowed, for example, distinguishing between the effects of turinabol and oxymetholone, supposed to act similarly in a previous characterization including only nine adrenal steroids. Furthermore, the results revealed that product/substrate ratios can provide superior information on altered enzyme activities compared to individual metabolite levels. For example, the 17α-hydroxypregnenolone/pregnenolone ratio was found to be a more sensitive marker for detecting 17α-hydroxylase inhibition by prochloraz than the corresponding individual steroids. These results illustrate that chemical grouping and calculation of product/substrate ratios can provide valuable information on mode-of-action and help prioritizing further experimental work.

Investigation of several chromatographic approaches for untargeted profiling of central carbon metabolism.

Monitoring the central carbon metabolism (CCM) network using liquid chromatography/mass spectrometry (LC-MS) analysis is hampered by the diverse chemical nature of its analytes, which are extremely difficult to analyze using single chromatographic conditions. Furthermore, CCM-related compounds present non-specific adsorption on metal surfaces, causing detrimental chromatographic effects and sensitivity loss. In this study, polar reversed-phase, mixed-mode (MMC), and zwitterionic hydrophilic interaction chromatography (HILIC) featuring low-adsorption hardware were investigated towards untargeted analysis of biological samples with a focus on energy metabolism-related analytes. Best results were achieved with sulfoalkylbetaine HILIC with different supports, where polymeric option featured the highest coverage and inert hybrid silica facilitated best throughput and kinetic performance at a cost of less selectivity for small carboxylic acids. MMC demonstrated excellent performance for strongly anionic analytes such as multiresidue phosphates. The obtained experimental data also suggested that an additional hydrophilic modulation might be necessary to facilitate better resolution of carboxylic acids in zHILIC mode, as found during the application of the developed method to study the effect of two different mutations on the energy metabolism of S. aureus.

From fundamentals in calibration to modern methodologies: A tutorial for small molecules quantification in liquid chromatography-mass spectrometry bioanalysis.

Over the last two decades, liquid chromatography coupled to mass-spectrometry (LC‒MS) has become the gold standard to perform qualitative and quantitative analyses of small molecules. When quantitative analysis is developed, an analyst usually refers to international guidelines for analytical method validation. In this context, the design of calibration curves plays a key role in providing accurate results. During recent years and along with instrumental advances, strategies to build calibration curves have dramatically evolved, introducing innovative approaches to improve quantitative precision and throughput. For example, when a labeled standard is available to be spiked directly into the study sample, the concentration of the unlabeled analog can be easily determined using the isotopic pattern deconvolution or the internal calibration approach, eliminating the need for multipoint calibration curves. This tutorial aims to synthetize the advances in LC‒MS quantitative analysis for small molecules in complex matrices, going from fundamental aspects in calibration to modern methodologies and applications. Different work schemes for calibration depending on the sample characteristics (analyte and matrix nature) are distinguished and discussed. Finally, this tutorial outlines the importance of having international guidelines for analytical method validation that agree with the advances in calibration strategies and analytical instrumentation.

Digoxin Induces Human Astrocyte Reaction In Vitro.

Astrocyte reaction is a complex cellular process involving astrocytes in response to various types of CNS injury and a marker of neurotoxicity. It has been abundantly studied in rodents but relatively poorly in human cells due to limited access to the brain. Astrocytes play important roles in cerebral energy metabolism and are also key players in neuroinflammation. Astroglial metabolic and inflammatory changes have been reported with age, leading to the hypothesis that mitochondrial metabolism and inflammatory responses are interconnected. However, the relationship between energy metabolism and astrocyte reactivity in the context of neurotoxicity is not known. We hypothesized that changes in energy metabolism of astrocytes will be coupled to their activation by xenobiotics. Astrocyte reaction and associated energy metabolic changes were assessed by immunostaining, gene expression, proteomics, metabolomics, and extracellular flux analyses after 24 h of exposure of human ReN-derived astrocytes to digoxin (1-10 µM) or TNFα (30 ng/ml) used as a positive control. Strong astrocytic reaction was observed, accompanied by increased glycolysis at low concentrations of digoxin (0.1 and 0.5 µM) and after TNFα exposure, suggesting that increased glycolysis may be a common feature of reactive astrocytes, independent of the triggering molecule. In conclusion, whether astrocyte activation is triggered by cytokines or a xenobiotic, it is strongly tied to energy metabolism in human ReN-derived astrocytes. Increased glycolysis might be considered as an endpoint to detect astrocyte activation by potentially neurotoxic compounds in vitro. Finally, ReN-derived astrocytes may help to decipher mechanisms of neurotoxicity in ascertaining the ability of chemicals to directly target astrocytes.

Metabolites in the regulatory risk assessment of pesticides in the EU.

A large majority of chemicals is converted into metabolites through xenobiotic-metabolising enzymes. Metabolites may present a spectrum of characteristics varying from similar to vastly different compared with the parent compound in terms of both toxicokinetics and toxicodynamics. In the pesticide arena, the role of metabolism and metabolites is increasingly recognised as a significant factor particularly for the design and interpretation of mammalian toxicological studies and in the toxicity assessment of pesticide/metabolite-associated issues for hazard characterization and risk assessment purposes, including the role of metabolites as parts in various residues in ecotoxicological adversities. This is of particular relevance to pesticide metabolites that are unique to humans in comparison with metabolites found in in vitro or in vivo animal studies, but also to disproportionate metabolites (quantitative differences) between humans and mammalian species. Presence of unique or disproportionate metabolites may underlie potential toxicological concerns. This review aims to present the current state-of-the-art of comparative metabolism and metabolites in pesticide research for hazard and risk assessment, including One Health perspectives, and future research needs based on the experiences gained at the European Food Safety Authority.

Target Metabolome Profiling-Based Machine Learning as a Diagnostic Approach for Cardiovascular Diseases in Adults.

Metabolomics is a promising technology for the application of translational medicine to cardiovascular risk. Here, we applied a liquid chromatography/tandem mass spectrometry approach to explore the associations between plasma concentrations of amino acids, methylarginines, acylcarnitines, and tryptophan catabolism metabolites and cardiometabolic risk factors in patients diagnosed with arterial hypertension (HTA) (n = 61), coronary artery disease (CAD) (n = 48), and non-cardiovascular disease (CVD) individuals (n = 27). In total, almost all significantly different acylcarnitines, amino acids, methylarginines, and intermediates of the kynurenic and indolic tryptophan conversion pathways presented increased (p < 0.05) in concentration levels during the progression of CVD, indicating an association of inflammation, mitochondrial imbalance, and oxidative stress with early stages of CVD. Additionally, the random forest algorithm was found to have the highest prediction power in multiclass and binary classification patients with CAD, HTA, and non-CVD individuals and globally between CVD and non-CVD individuals (accuracy equal to 0.80 and 0.91, respectively). Thus, the present study provided a complex approach for the risk stratification of patients with CAD, patients with HTA, and non-CVD individuals using targeted metabolomics profiling.

Oxidative Stress and Extracellular Matrix Remodeling Are Signature Pathways of Extracellular Vesicles Released upon Morphine Exposure on Human Brain Microvascular Endothelial Cells.

Morphine, a commonly used antinociceptive drug in hospitals, is known to cross the blood-brain barrier (BBB) by first passing through brain endothelial cells. Despite its pain-relieving effect, morphine also has detrimental effects, such as the potential induction of redox imbalance in the brain. However, there is still insufficient evidence of these effects on the brain, particularly on the brain endothelial cells and the extracellular vesicles that they naturally release. Indeed, extracellular vesicles (EVs) are nanosized bioparticles produced by almost all cell types and are currently thought to reflect the physiological state of their parent cells. These vesicles have emerged as a promising source of biomarkers by indicating the functional or dysfunctional state of their parent cells and, thus, allowing a better understanding of the biological processes involved in an adverse state. However, there is very little information on the morphine effect on human brain microvascular endothelial cells (HBMECs), and even less on their released EVs. Therefore, the current study aimed at unraveling the detrimental mechanisms of morphine exposure (at 1, 10, 25, 50 and 100 µM) for 24 h on human brain microvascular endothelial cells as well as on their associated EVs. Isolation of EVs was carried out using an affinity-based method. Several orthogonal techniques (NTA, western blotting and proteomics analysis) were used to validate the EVs enrichment, quality and concentration. Data-independent mass spectrometry (DIA-MS)-based proteomics was applied in order to analyze the proteome modulations induced by morphine on HBMECs and EVs. We were able to quantify almost 5500 proteins in HBMECs and 1500 proteins in EVs, of which 256 and 148, respectively, were found to be differentially expressed in at least one condition. Pathway enrichment analysis revealed that the "cell adhesion and extracellular matrix remodeling" process and the "HIF1 pathway", a pathway related to oxidative stress responses, were significantly modulated upon morphine exposure in HBMECs and EVs. Altogether, the combination of proteomics and bioinformatics findings highlighted shared pathways between HBMECs exposed to morphine and their released EVs. These results put forward molecular signatures of morphine-induced toxicity in HBMECs that were also carried by EVs. Therefore, EVs could potentially be regarded as a useful tool to investigate brain endothelial cells dysfunction, and to a different extent, the BBB dysfunction in patient circulation using these "signature pathways".

Teg58, a small regulatory RNA, is involved in regulating arginine biosynthesis and biofilm formation in Staphylococcus aureus.

Staphylococcus aureus adapts to different environments by sensing and responding to diverse environmental cues. The responses are coordinately regulated by regulatory proteins, and small regulatory RNAs at the transcriptional and translational levels. Here, we characterized teg58, a SarA repressed sRNA, using ChIP-Seq and RNA-Seq analysis of a sarA mutant. Phenotypic and genetic analyses indicated that inactivation of teg58 led to reduced biofilm formation in a process that is independent of SarA, agr, PIA, and PSMs. RNA-Seq analysis of teg58 mutant revealed up-regulation of arginine biosynthesis genes (i.e., argGH) as well as the ability of the mutant to grow in a chemical defined medium (CDM) lacking L-arginine. Exogenous L-arginine or endogenous induction of argGH led to decreased biofilm formation in parental strains. Further analysis in vitro and in vivo demonstrated that the specific interaction between teg58 and the argGH occurred at the post-transcriptional level to repress arginine synthesis. Biochemical and genetic analyses of various arginine catabolic pathway genes demonstrated that the catabolic pathway did not play a significant role in reduced biofilm formation in the teg58 mutant. Overall, results suggest that teg58 is a regulatory sRNA that plays an important role in modulating arginine biosynthesis and biofilm formation in S. aureus.

Evaluation of Prototype CE-MS Interfaces.

Capillary electrophoresis-mass spectrometry (CE-MS) coupling is a powerful analytical solution bringing together the separation power of CE and the wealth of chemical information afforded by MS. Nevertheless, interfaces making the hyphenation of both techniques possible have always been the subject of a quest for improvement by their users in search for more sensitive and robust setups. This fact has led to numerous technical developments and new interface designs claiming to outrival existing approaches in different aspects. Nevertheless, the task of evaluating and comparing a new interface to previous solutions is not always straightforward. Issued from our own experience in the field, we herein propose a protocol to optimize the operation parameters of a new CE-MS interface design, assess its analytical performance, and compare it to a reference interface if desired. Electrospray stability, sensitivity, reproducibility, and robustness are practically evaluated as key elements of the process.