NMR-Based Metabolic Snapshot from Minibronchoalveolar Lavage Fluid: An Approach To Unfold Human Respiratory Metabolomics

Potential of in vitro nuclear magnetic resonance of biofluids and tissues in clinical research

Body fluids, cells, and tissues contain a wide variety of metabolites that consist of a mixture of various low-molecular-weight compounds, including amino acids, peptides, lipids, nucleic acids, and organic acids, which makes comprehensive analysis more difficult. Quantitative nuclear magnetic resonance (NMR) spectroscopy is a well-established analytical technique for analyzing the metabolic profiles of body fluids, cells, and tissues. It enables fast and comprehensive detection, characterization, a high level of experimental reproducibility, minimal sample preparation, and quantification of various endogenous metabolites. In recent times, NMR-based metabolomics has been appreciably utilized in diverse branches of medicine, including microbiology, toxicology, pathophysiology, pharmacology, nutritional intervention, and disease diagnosis/prognosis. In this review, the utility of NMR-based metabolomics in clinical studies is discussed. The significance of in vitro NMR-based metabolomics as an effective tool for detecting metabolites and their variations in different diseases are discussed, together with the possibility of identifying specific biomarkers that can contribute to early detection and diagnosis of disease.

Cluster analysis and profiling of airway fluid metabolites in pediatric acute hypoxemic respiratory failure

Hierarchal clustering of amino acid metabolites may identify a metabolic signature in children with pediatric acute hypoxemic respiratory failure. Seventy-four immunocompetent children, 41 (55.4%) with pediatric acute respiratory distress syndrome (PARDS), who were between 2 days to 18 years of age and within 72 h of intubation for acute hypoxemic respiratory failure, were enrolled. We used hierarchal clustering and partial least squares-discriminant analysis to profile the tracheal aspirate airway fluid using quantitative LC–MS/MS to explore clusters of metabolites that correlated with acute hypoxemia severity and ventilator-free days. Three clusters of children that differed by severity of hypoxemia and ventilator-free days were identified. Quantitative pathway enrichment analysis showed that cysteine and methionine metabolism, selenocompound metabolism, glycine, serine and threonine metabolism, arginine biosynthesis, and valine, leucine, and isoleucine biosynthesis were the top five enriched, impactful pathways. We identified three clusters of amino acid metabolites found in the airway fluid of intubated children important to acute hypoxemia severity that correlated with ventilator-free days < 21 days. Further studies are needed to validate our findings and to test our models.

Respiratory metabolites in bronchoalveolar lavage fluid (BALF) and exhaled breath condensate (EBC) can differentiate horses affected by severe equine asthma from healthy horses

BACKGROUND

The use of an untargeted metabolomic approach to investigate biofluids of respiratory origin is of increasing interest in human and veterinary lung research. Considering the high incidence of equine asthma (> 14%) within horse population and the importance of this animal model for human disease, we aimed to investigate the metabolomic profile of bronchoalveolar lavage fluid (BALF) and exhaled breath condensate (EBC) in healthy and asthmatic horses.

RESULTS

On the basis of clinical, endoscopic and BALF cytology findings, 6 horses with severe asthma (Group A) and 6 healthy horses (Group C) were included in the study. 1H-NMR analysis was used to identified metabolites in BALF and EBC samples. Metabolomic analysis allowed to identify and quantify 12 metabolites in BALF and seven metabolites in EBC. Among respiratory metabolites, myo-inositol, formate, glycerol and isopropanol in BALF, and methanol and ethanol in EBC, differed between groups (p < 0.05).

CONCLUSIONS

The application of metabolomic studies to investigate equine asthma using minimally invasive diagnostic methods, such as EBC metabolomics, provided promising results. According to our research, the study of selective profiles of BALF and EBC metabolites might be useful for identifying molecules like myo-inositol and methanol as possible biomarkers for airways diseases in horses.

An NMR based panorama of the heterogeneous biology of acute respiratory distress syndrome (ARDS) from the standpoint of metabolic biomarkers

Acute respiratory distress syndrome (ARDS), manifested by intricate etiology and pathophysiology, demands careful clinical surveillance due to its high mortality and imminent life support measures. NMR based metabolomics provides an approach for ARDS which culminates from a wide spectrum of illness thereby confounding early manifestation and prognosis predictors. ¹ H NMR with its manifold applications in critical disease settings can unravel the biomarker of ARDS thus holding potent implications by providing surrogate endpoints of clinical utility. NMR metabolomics which is the current apogee platform of omics trilogy is contributing towards the possible panacea of ARDS by subsequent validation of biomarker credential on larger datasets. In the present review, the physiological derangements that jeopardize the whole metabolic functioning in ARDS are exploited and the biomarkers involved in progression are addressed and substantiated. The following sections of the review also outline the clinical spectrum of ARDS from the standpoint of NMR based metabolomics which is an emerging element of systems biology. ARDS is the main premise of intensivists textbook, which has been thoroughly reviewed along with its incidence, progressive stages of severity, new proposed diagnostic definition, and the preventive measures and the current pitfalls of clinical management. The advent of new therapies, the need for biomarkers, the methodology and the contemporary promising approaches needed to improve survival and address heterogeneity have also been evaluated. The review has been stepwise illustrated with potent biometrics employed to selectively pool out differential metabolites as diagnostic markers and outcome predictors. The following sections have been drafted with an objective to better understand ARDS mechanisms with predictive and precise biomarkers detected so far on the basis of underlying physiological parameters having close proximity to diseased phenotype. The aim of this review is to stimulate interest in conducting more studies to help resolve the complex heterogeneity of ARDS with biomarkers of clinical utility and relevance.

Distinct Metabolic Endotype Mirroring Acute Respiratory Distress Syndrome (ARDS) Subphenotype and its Heterogeneous Biology

Predisposing aetiologies in Acute Respiratory Distress Syndrome (ARDS), perpetuates to heterogeneous clinical course hampering therapeutic response. Therefore, physiological variables need to be identified by stratifying ARDS subphenotypes and endotype, to target ARDS heterogeneity. The present study is stimulated by the fact that the ARDS heterogeneity arises from diverse pathophysiological changes leading to distinct ARDS endotypes characterized by perturbed biological mechanism which can be exploited in terms of metabolic profile by metabolomics. Biological endotypes using (n = 464 patients and controls), mBALF and serum samples were identified by high - resolution NMR spectroscopy from two clinically diagnosed ARDS subtypes grouped under mild, moderate and severe ARDS as subphenotype1and pulmonary and extra - pulmonary ARDS as subphenotype2. The identified mBALF endotypes (isoleucine, leucine, valine, lysine/arginine, tyrosine, threonine) and serum endotypes (proline, glutamate, phenylalanine, valine) in both subphenotypes by statistical analysis were tested for their reproducibility and robustness. By combining metabolic endotypes with clinical based mortality score (APACHE and SOFA) added to their predictive performance as ARDS mortality predictors. Thus, a comprehensive set of mBALF endotypes representing compartmentalized lung milieu and serological endotypes representing systemic markers of ARDS subtypes were validated. The interlinked biological pathway of these disease specific endotype further elucidated their role as candidate biomarker in governing ARDS heterogeneous biology.

Comprehensive characterization of in vitro and in vivo metabolites of 2',3',5'‑tri‑O‑acetyl‑N6‑(3‑hydroxyphenyl) adenosine and study of the metabolites distribution in rats by combined methods of HPLC-DAD, off-line cryoNMR, and HPLC-QTOFMS

The compound 2',3',5'‑tri‑O‑acetyl‑N₆‑(3‑hydroxyphenyl) adenosine (also known as IMM-H007) is a new adenosine analogue that displays anti-hyperlipidaemic activity in many preliminary studies. To clarify its biotransformation process, in vitro and in vivo metabolic patterns of IMM-H007 in rat liver microsomes (RLMs), urine, feces, serum, and various tissues were investigated using high-performance liquid chromatography coupled to a diode array detector (HPLC-DAD), off-line cryogenically cooled probe nuclear magnetic resonance (cryoNMR), and high-performance liquid chromatography quadrupole TOF MS (HPLC-QTOFMS) measurements. A total of 21 metabolites were detected and identified based on accurate mass measurements, diagnostic product ions, and 1D and 2D NMR data. All of the 21 metabolites were detected in vivo besides the 7 ones (LM1-3, LM4a-b, LM5, LM6 (M8)) in vitro. Among them, eight metabolites were phase I metabolites composed of the hydrolysis products LM1-3, LM4a, LM4b, LM5 and M7-8, and hydrolysis and hydroxylation products M6. Others were phase II metabolites including glucuronidation products M2, M4, M9, M11a-c, and M12a-c; and sulfation products M3, M5, and M10. Notably, 14 metabolites (LM1-3, LM4a-b, LM5, M9-10, M11a-c, M12a-c) were unreported before and the distribution of IMM-H007 and its all metabolites was reported for the first time. The results revealed IMM-H007 was metabolized mainly in the small intestine and serum, kidney, stomach, small and large intestines were important samples for metabolites presence. This work improves understanding of the metabolism, distribution, and excretion of IMM-H007, and demonstrates the HPLC/HPLC-MS/off-line cryoNMR approach can be applied for detection and identification of metabolites in complex biological matrices.

A Molecular Window into the Biology and Epidemiology of Pneumocystis spp

Pneumocystis, a unique atypical fungus with an elusive lifestyle, has had an important medical history. It came to prominence as an opportunistic pathogen that not only can cause life-threatening pneumonia in patients with HIV infection and other immunodeficiencies but also can colonize the lungs of healthy individuals from a very early age. The genus Pneumocystis includes a group of closely related but heterogeneous organisms that have a worldwide distribution, have been detected in multiple mammalian species, are highly host species specific, inhabit the lungs almost exclusively, and have never convincingly been cultured in vitro, making Pneumocystis a fascinating but difficult-to-study organism. Improved molecular biologic methodologies have opened a new window into the biology and epidemiology of Pneumocystis. Advances include an improved taxonomic classification, identification of an extremely reduced genome and concomitant inability to metabolize and grow independent of the host lungs, insights into its transmission mode, recognition of its widespread colonization in both immunocompetent and immunodeficient hosts, and utilization of strain variation to study drug resistance, epidemiology, and outbreaks of infection among transplant patients. This review summarizes these advances and also identifies some major questions and challenges that need to be addressed to better understand Pneumocystis biology and its relevance to clinical care.

Metabolomics based predictive biomarker model of ARDS: A systemic measure of clinical hypoxemia

Despite advancements in ventilator technologies, lung supportive and rescue therapies, the outcome and prognostication in acute respiratory distress syndrome (ARDS) remains incremental and ambiguous. Metabolomics is a potential insightful measure to the diagnostic approaches practiced in critical disease settings. In our study patients diagnosed with mild and moderate/severe ARDS clinically governed by hypoxemic P/F ratio between 100-300 but with indistinct molecular phenotype were discriminated employing nuclear magnetic resonance (NMR) based metabolomics of mini bronchoalveolar lavage fluid (mBALF). Resulting biomarker prototype comprising six metabolites was substantiated highlighting ARDS susceptibility/recovery. Both the groups (mild and moderate/severe ARDS) showed distinct biochemical profile based on 83.3% classification by discriminant function analysis and cross validated accuracy of 91% using partial least squares discriminant analysis as major classifier. The predictive performance of narrowed down six metabolites were found analogous with chemometrics. The proposed biomarker model consisting of six metabolites proline, lysine/arginine, taurine, threonine and glutamate were found characteristic of ARDS sub-stages with aberrant metabolism observed mainly in arginine, proline metabolism, lysine synthesis and so forth correlating to diseased metabotype. Thus NMR based metabolomics has provided new insight into ARDS sub-stages and conclusively a precise biomarker model proposed, reflecting underlying metabolic dysfunction aiding prior clinical decision making.

NMR Spectroscopy-based Metabolomics of Drosophila Model of Huntington's Disease Suggests Altered Cell Energetics

Huntington's disease (HD) is a neurodegenerative disorder induced by aggregation of the pathological form of Huntingtin protein that has expanded polyglutamine (polyQ) repeats. In the Drosophila model, for instance, expression of transgenes with polyQ repeats induces HD-like pathologies, progressively correlating with the increasing lengths of these repeats. Previous studies on both animal models and clinical samples have revealed metabolite imbalances during HD progression. To further explore the physiological processes linked to metabolite imbalances during HD, we have investigated the 1D ¹H NMR spectroscopy-based metabolomics profile of Drosophila HD model. Using multivariate analysis (PCA and PLS-DA) of metabolites obtained from methanolic extracts of fly heads displaying retinal deformations due to polyQ overexpression, we show that the metabolite imbalance during HD is likely to affect cell energetics. Six out of the 35 metabolites analyzed, namely, nicotinamide adenine dinucleotide (NAD), lactate, pyruvate, succinate, sarcosine, and acetoin, displayed segregation with progressive severity of HD. Specifically, HD progression was seen to be associated with reduction in NAD and increase in lactate-to-pyruvate ratio. Furthermore, comparative analysis of fly HD metabolome with those of mouse HD model and HD human patients revealed comparable metabolite imbalances, suggesting altered cellular energy homeostasis. These findings thus raise the possibility of therapeutic interventions for HD via modulation of cellular energetics.

A discrete Fourier-encoded, diagonal-free experiment to simplify homonuclear 2D NMR correlations

Nuclear magnetic resonance (NMR) spectroscopy has long served as an irreplaceable, versatile tool in physics, chemistry, biology, and materials sciences, owing to its ability to study molecular structure and dynamics in detail. In particular, the connectivity of chemical sites within molecules, and thereby molecular structure, becomes visible by multi-dimensional NMR. Homonuclear correlation experiments are a powerful tool for identifying coupled spins. Generally, diagonal peaks in these correlation spectra display the strongest intensities and do not offer any new information beyond the standard one-dimensional spectrum, whereas weaker, symmetrically placed cross peaks contain most of the coupling information. The cross peaks near the diagonal are often affected by the tails of strong diagonal peaks or even obscured entirely by the diagonal. In this paper, we demonstrate a homonuclear encoding approach based on imparting a discrete phase modulation of the targeted cross peaks and combine it with a site-selective sculpting scheme, capable of simplifying the patterns arising in these 2D correlation spectra. The theoretical principles of the new methods are laid out, and experimental observations are rationalized on the basis of theoretical analyses. The ensuing techniques provide a new way to retrieve 2D coupling information within homonuclear spin systems, with enhanced sensitivity, speed, and clarity.

1H NMR To Evaluate the Metabolome of Bronchoalveolar Lavage Fluid (BALf) in Bronchiolitis Obliterans Syndrome (BOS): Toward the Development of a New Approach for Biomarker Identification

This report describes the application of NMR spectroscopy to the profiling of metabolites in bronchoalveolar lavage fluid (BALf) of lung transplant recipients without bronchiolitis obliterans syndrome (BOS) (stable, S, n = 10), and with BOS at different degrees of severity (BOS 0p, n = 10; BOS I, n = 10). Through the fine-tuning of a number of parameters concerning both sample preparation/processing and variations of spectra acquisition modes, an efficient and reproducible protocol was designed for the screening of metabolites in a pulmonary fluid that should reflect the status of airway inflammation/injury. Exploiting the combination of mono- and bidimensional NMR experiments, 38 polar metabolites, including amino acids, Krebs cycle intermediates, mono- and disaccharides, nucleotides, and phospholipid precursors, were unequivocally identified. To determine which signature could be correlated with the onset of BOS, the metabolites' content of the above recipients was analyzed by multivariate (PCA and OPLS-DA) statistical methods. PCA analysis (almost) totally differentiated S from BOS I, and this discrimination was significantly improved by the application of OPLS-DA, whose model was characterized by excellent fit and prediction values (R² = 0.99 and Q² = 0.88). The analysis of S vs BOS 0p and of BOS 0p vs BOS I samples showed a clear discrimination of considered cohorts, although with a poorer efficiency compared to those measured for S vs BOS I patients. The data shown in this work assess the suitability of the NMR approach in monitoring different pathological lung conditions.

Metabolomics for clinical use and research in chronic kidney disease

Chronic kidney disease (CKD) has a high prevalence in the general population and is associated with high mortality; a need therefore exists for better biomarkers for diagnosis, monitoring of disease progression and therapy stratification. Moreover, very sensitive biomarkers are needed in drug development and clinical research to increase understanding of the efficacy and safety of potential and existing therapies. Metabolomics analyses can identify and quantify all metabolites present in a given sample, covering hundreds to thousands of metabolites. Sample preparation for metabolomics requires a very fast arrest of biochemical processes. Present key technologies for metabolomics are mass spectrometry and proton nuclear magnetic resonance spectroscopy, which require sophisticated biostatistic and bioinformatic data analyses. The use of metabolomics has been instrumental in identifying new biomarkers of CKD such as acylcarnitines, glycerolipids, dimethylarginines and metabolites of tryptophan, the citric acid cycle and the urea cycle. Biomarkers such as c-mannosyl tryptophan and pseudouridine have better performance in CKD stratification than does creatinine. Future challenges in metabolomics analyses are prospective studies and deconvolution of CKD biomarkers from those of other diseases such as metabolic syndrome, diabetes mellitus, inflammatory conditions, stress and cancer.