Solid organ transplantation and gut microbiota: a review of the potential immunomodulatory properties of short-chain fatty acids in graft maintenance

Transplantation is the treatment of choice for several end-stage organ defects: it considerably improves patient survival and quality of life. However, post-transplant recipients may experience episodes of rejection that can favor or ultimately lead to graft loss. Graft maintenance requires a complex and life-long immunosuppressive treatment. Different immunosuppressive drugs (i.e., calcineurin inhibitors, glucocorticoids, biological immunosuppressive agents, mammalian target of rapamycin inhibitors, and antiproliferative or antimetabolic agents) are used in combination to mitigate the immune response against the allograft. Unfortunately, the use of these antirejection agents may lead to opportunistic infections, metabolic (e.g., post-transplant diabetes mellitus) or cardiovascular (e.g., arterial hypertension) disorders, cancer (e.g., non-Hodgkin lymphoma) and other adverse effects. Lately, immunosuppressive drugs have also been associated with gut microbiome alterations, known as dysbiosis, and were shown to affect gut microbiota-derived short-chain fatty acids (SCFA) production. SCFA play a key immunomodulatory role in physiological conditions, and their impairment in transplant patients could partly counterbalance the effect of immunosuppressive drugs leading to the activation of deleterious pathways and graft rejection. In this review, we will first present an overview of the mechanisms of graft rejection that are prevented by the immunosuppressive protocol. Next, we will explain the dynamic changes of the gut microbiota during transplantation, focusing on SCFA. Finally, we will describe the known functions of SCFA in regulating immune-inflammatory reactions and discuss the impact of SCFA impairment in immunosuppressive drug treated patients.

Metabolomics Meets Clinics: A Multivariate Analysis of Plasma and Urine Metabolic Signatures in Pulmonary Arterial Hypertension

Pulmonary arterial hypertension (PAH) is a severe, multifactorial, and frequently misdiagnosed disorder. The aim of this observational study was to compare the plasma and urine metabolomic profiles of PAH patients and healthy control subjects. Plasma and urine metabolomic profiles were analyzed using the GC-MS technique. Correlations between metabolite levels and clinical parameters among PAH patients, as well as the between-group differences, were evaluated. The linear discriminant analysis model, which allows for subject classification in terms of PAH with the highest possible precision, was developed and proposed. Plasma pyruvic acid, cholesterol, threonine, urine 3-(3-hydroxyphenyl)-3-hydroxypropanoic acid, butyric acid, 1,2-benzenediol, glucoheptonic acid, and 2-oxo-glutaric acid were found to build a relatively accurate classification model for PAH patients. The model reached an accuracy of 91% and significantly improved subject classification (OR = 119 [95% CI: 20.3-698.3], p < 0.0001). Five metabolites were detected in urine that provide easily available and noninvasive tests as compared to right heart catheterization. The selected panel of metabolites has potential for early recognition of patients with dyspnea and faster referral to a reference center.

Trimethylamine N-Oxide Concentration and Blood Pressure in Young Healthy Men and Women: A Replicated Crossover Study

Trimethylamine N-oxide (TMAO), a gut-derived metabolite and marker of gut dysbiosis, has been linked to hypertension. Blood pressure is proposed to be elevated in hormonal contraceptive users and males compared to age-matched eumenorrheic females, but the extent to which TMAO differs between these populations has yet to be investigated. Peripheral and central blood pressure were measured, with the latter determined via applanation tonometry, and plasma TMAO concentration was assessed using liquid chromatography-tandem mass spectrometry. The following variables were assessed on two occasions in each of the following conditions: the early follicular phase (EFP) and mid-luteal phase (MLP) in eumenorrheic women (n = 13), and the pill-free interval (INACTIVE) and pill consumption days (ACTIVE) in women using oral contraceptive pills (n = 12), and in men (n = 22). Briefly, 17-β-estradiol and progesterone concentrations were quantified via ELISA in all females. There were no differences in TMAO concentration between EFP (2.9 ± 1.7 μmol/L) and MLP (3.2 ± 1.1 μmol/L), between INACTIVE (3.3 ± 2.9 μmol/L) and ACTIVE (2.3 ± 1.1 μmol/L) days, or between men (3.0 ± 1.8 μmol/L), eumenorrheic women (3.0 ± 1.3 μmol/L) and contraceptive users (2.8 ± 1.4 μmol/L). Blood pressure was consistent across the menstrual cycle and pill days, but brachial systolic blood pressure was higher in males than females. There were no differences in brachial diastolic blood pressure or central blood pressure between the sexes. Repeated measures of TMAO, blood pressure, 17-β-estradiol and progesterone were consistent in all populations. These findings suggest that the link between TMAO and blood pressure is limited in healthy young adults.

Untargeted metabolomics of pulmonary tuberculosis patient serum reveals potential prognostic markers of both latent infection and outcome

Currently, there are no particularly effective biomarkers to distinguish between latent tuberculosis infection (LTBI) and active pulmonary tuberculosis (PTB) and evaluate the outcome of TB treatment. In this study, we have characterized the changes in the serum metabolic profiles caused by Mycobacterium tuberculosis (Mtb) infection and standard anti-TB treatment with isoniazid-rifampin-pyrazinamide-ethambutol (HRZE) using GC-MS and LC-MS/MS. Seven metabolites, including 3-oxopalmitic acid, akeboside ste, sulfolithocholic acid, 2-decylfuran (4,8,8-trimethyldecahydro-1,4-methanoazulen-9-yl)methanol, d-(+)-camphor, and 2-methylaminoadenosine, were identified to have significantly higher levels in LTBI and untreated PTB patients (T0) than those in uninfected healthy controls (Un). Among them, akeboside Ste and sulfolithocholic acid were significantly decreased in PTB patients with 2-month HRZE (T2) and cured PTB patients with 2-month HRZE followed by 4-month isoniazid-rifampin (HR) (T6). Receiver operator characteristic curve analysis revealed that the combined diagnostic model showed excellent performance for distinguishing LT from T0 and Un. By analyzing the biochemical and disease-related pathways, we observed that the differential metabolites in the serum of LTBI or TB patients, compared to healthy controls, were mainly involved in glutathione metabolism, ascorbate and aldarate metabolism, and porphyrin and chlorophyll metabolism. The metabolites with significant differences between the T0 group and the T6 group were mainly enriched in niacin and nicotinamide metabolism. Our study provided more detailed experimental data for developing laboratory standards for evaluating LTBI and cured PTB.

Mass spectrometry in the clinical laboratory. A short journey through the contribution to the scientific literature by CCLM

Mass spectrometry (MS) has been a gold standard in the clinical laboratory for decades. Although historically refined to limited areas of study such as neonatal screening and steroid analysis, technological advancements in the field have resulted in MS becoming more powerful, versatile, and user-friendly than ever before. As such, the potential for the technique in clinical chemistry has exploded. The past two decades have seen advancements in biomarker detection for disease diagnostics, new methods for protein measurement, improved methodologies for reliable therapeutic drug monitoring, and novel technologies for automation and high throughput. Throughout this time, Clinical Chemistry and Laboratory Medicine has embraced the rapidly developing field of mass spectrometry, endeavoring to highlight the latest techniques and applications that have the potential to revolutionize clinical testing. This mini review will highlight a selection of these critical contributions to the field.

Optimization of a GC-MS method for the profiling of microbiota-dependent metabolites in blood samples: An application to type 2 diabetes and prediabetes

Changes in serum or plasma metabolome may reflect gut microbiota dysbiosis, which is also known to occur in patients with prediabetes and type 2 diabetes (T2DM). Thus, developing a robust method for the analysis of microbiota-dependent metabolites (MDMs) is an important issue. Gas chromatography with mass spectrometry (GC–MS) is a powerful approach enabling detection of a wide range of MDMs in biofluid samples with good repeatability and reproducibility, but requires selection of a suitable solvents and conditions. For this reason, we conducted for the first time the study in which, we demonstrated an optimisation of samples preparation steps for the measurement of 75 MDMs in two matrices. Different solvents or mixtures of solvents for MDMs extraction, various concentrations and volumes of derivatizing reagents as well as temperature programs at methoxymation and silylation step, were tested. The stability, repeatability and reproducibility of the 75 MDMs measurement were assessed by determining the relative standard deviation (RSD). Finally, we used the developed method to analyse serum samples from 18 prediabetic (PreDiab group) and 24 T2DM patients (T2DM group) from our 1000PLUS cohort. The study groups were homogeneous and did not differ in age and body mass index. To select statistically significant metabolites, T2DM vs. PreDiab comparison was performed using multivariate statistics. Our experiment revealed changes in 18 MDMs belonging to different classes of compounds, and seven of them, based on the SVM classification model, were selected as a panel of potential biomarkers, able to distinguish between patients with T2DM and prediabetes.

Simple, high-throughput measurement of gut-derived short-chain fatty acids in clinically relevant biofluids using gas chromatography-mass spectrometry

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A high-throughput assay for measurement of short-chain fatty acids in biofluids.

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A simple, time efficient liquid–liquid extraction protocol with no derivatization.

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Recommend use of lithium heparin plasma or clotting activator serum collection.

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Clinical applicability demonstrated by measurement of kidney disease patient samples.

Introduction

The quantitative measurement of circulating gut bacteria-derived metabolites has increased in recent years due to their associations with health and disease. While much of the previous attention has been placed on metabolites considered as deleterious to health, a shift to the investigation of short-chain fatty acids (SCFAs) as potential health promotors has been observed.

Objectives

To develop a simple, high-throughput and quantitative assay to measure gut-derived SCFAs in clinically relevant biofluids using gas chromatography-mass spectrometry (GC–MS).

Methods

A short (7.5 min) GC–MS assay was optimized for measurement of seven straight- and branched-chain SCFAs and their deuterated isotopes using a wax-based column for analysis without prior derivatization. The assay was validated using routine criteria to assess precision, accuracy, matrix effects, recovery, and extraction reproducibility. Assay applicability was tested in cohorts of healthy individuals and kidney disease patients.

Results

The assay was demonstrated to be precise, accurate and reproducible with acceptable levels of matrix effect and analyte recovery. Lower limits of detection and quantitation were in the low ng/mL range. An investigation into different blood collection tube chemistries demonstrated that lithium heparin plasma and serum clotting activator tubes are recommended for use in future cross-study comparisons. Kidney disease patient analyses demonstrated variable differences across SCFAs when comparing hemodialysis to earlier stages of chronic kidney disease, demonstrating the suitability of the assay for translation to clinical analyses.

Conclusion

The assay has been validated and identified as reliable for use in larger-scale studies for the analysis of SCFAs in human plasma and serum.

Breathomics profiling of metabolic pathways affected by major depression: Possibilities and limitations

BACKGROUND

Major depressive disorder (MDD) is one of the most common psychiatric disorders with multifactorial etiologies. Metabolomics has recently emerged as a particularly potential quantitative tool that provides a multi-parametric signature specific to several mechanisms underlying the heterogeneous pathophysiology of MDD. The main purpose of the present study was to investigate possibilities and limitations of breath-based metabolomics, breathomics patterns to discriminate MDD patients from healthy controls (HCs) and identify the altered metabolic pathways in MDD.

METHODS

Breath samples were collected in Tedlar bags at awakening, 30 and 60 min after awakening from 26 patients with MDD and 25 HCs. The non-targeted breathomics analysis was carried out by proton transfer reaction mass spectrometry. The univariate analysis was first performed by T-test to rank potential biomarkers. The metabolomic pathway analysis and hierarchical clustering analysis (HCA) were performed to group the significant metabolites involved in the same metabolic pathways or networks. Moreover, a support vector machine (SVM) predictive model was built to identify the potential metabolites in the altered pathways and clusters. The accuracy of the SVM model was evaluated by receiver operating characteristics (ROC) analysis.

RESULTS

A total of 23 differential exhaled breath metabolites were significantly altered in patients with MDD compared with HCs and mapped in five significant metabolic pathways including aminoacyl-tRNA biosynthesis (p = 0.0055), branched chain amino acids valine, leucine and isoleucine biosynthesis (p = 0.0060), glycolysis and gluconeogenesis (p = 0.0067), nicotinate and nicotinamide metabolism (p = 0.0213) and pyruvate metabolism (p = 0.0440). Moreover, the SVM predictive model showed that butylamine (p = 0.0005, p_FDR=0.0006), 3-methylpyridine (p = 0.0002, p_FDR = 0.0012), endogenous aliphatic ethanol isotope (p = 0.0073, p_FDR = 0.0174), valeric acid (p = 0.005, p_FDR = 0.0162) and isoprene (p = 0.038, p_FDR = 0.045) were potential metabolites within identified clusters with HCA and altered pathways, and discriminated between patients with MDD and non-depressed ones with high sensitivity (0.88), specificity (0.96) and area under curve of ROC (0.96).

CONCLUSION

According to the results of this study, the non-targeted breathomics analysis with high-throughput sensitive analytical technologies coupled to advanced computational tools approaches offer completely new insights into peripheral biochemical changes in MDD.

The Athlete and Gut Microbiome: Short-chain Fatty Acids as Potential Ergogenic Aids for Exercise and Training

Short-chain fatty acids (SCFAs) are metabolites produced in the gut via microbial fermentation of dietary fibers referred to as microbiota-accessible carbohydrates (MACs). Acetate, propionate, and butyrate have been observed to regulate host dietary nutrient metabolism, energy balance, and local and systemic immune functions. In vitro and in vivo experiments have shown links between the presence of bacteria-derived SCFAs and host health through the blunting of inflammatory processes, as well as purported protection from the development of illness associated with respiratory infections. This bank of evidence suggests that SCFAs could be beneficial to enhance the athlete's immunity, as well as act to improve exercise recovery via anti-inflammatory activity and to provide additional energy substrates for exercise performance. However, the mechanistic basis and applied evidence for these relationships in humans have yet to be fully established. In this narrative review, we explore the existing knowledge of SCFA synthesis and the functional importance of the gut microbiome composition to induce SCFA production. Further, changes in gut microbiota associated with exercise and various dietary MACs are described. Finally, we provide suggestions for future research and practical applications, including how these metabolites could be manipulated through dietary fiber intake to optimize immunity and energy metabolism.

Surface-Enhanced Raman Spectroscopy of Bacterial Metabolites for Bacterial Growth Monitoring and Diagnosis of Viral Infection

Bacterial metabolites are intermediate products of bacterial metabolism and their production reflects metabolic activity. Herein, we report the use of surface-enhanced Raman spectroscopy (SERS) for detection of both volatile and nonvolatile metabolites and the application of this approach for bacterial growth quantification and diagnosis of viral infection. The time-dependent SERS signal of the volatile metabolite dimethyl disulfide in the headspace above bacteria growing on an agar plate was detected and quantified. In addition, SERS signals arising from the plate reflected nutrient consumption and production of nonvolatile metabolites. The measurement of metabolite accumulation can be used for bacterial quantification. In the presence of bacteriophage virus, bacterial metabolism is suppressed, and the relative decrease in SERS intensity reflects the initial virus concentration. Using multivariate analysis, we detect viral infection with a prediction accuracy of 93%. Our SERS-based approach for metabolite production monitoring provides new insights toward viral infection diagnosis.