Metabolomics aims to achieve a global quantitation of the pool of metabolites within a biological system. Importantly, metabolite concentrations serve as a sensitive marker of both genomic and phenotypic changes in response to both internal and external stimuli. NMR spectroscopy greatly aids in the understanding of both in vitro and in vivo physiological systems and in the identification of diagnostic and therapeutic biomarkers. Accordingly, NMR is widely utilized in metabolomics and fluxomics studies due to its limited requirements for sample preparation and chromatography, its non‐destructive and quantitative nature, its utility in the structural elucidation of unknown compounds, and, importantly, its versatility in the analysis of in vitro, in vivo, and ex vivo samples. This review provides an overview of the strengths and limitations of in vitro and in vivo experiments for translational research and discusses how ex vivo studies may overcome these weaknesses to facilitate the extrapolation of in vitro insights to an in vivo system. The application of NMR‐based metabolomics to ex vivo samples, tissues, and biofluids can provide essential information that is close to a living system (in vivo) with sensitivity and resolution comparable to those of in vitro studies. The success of this extrapolation process is critically dependent on high‐quality and reproducible data. Thus, the incorporation of robust quality assurance and quality control checks into the experimental design and execution of NMR‐based metabolomics experiments will ensure the successful extrapolation of ex vivo studies to benefit translational medicine.
- Award ID(s):
- 1660921
- NSF-PAR ID:
- 10227342
- Date Published:
- Journal Name:
- Molecules
- Volume:
- 25
- Issue:
- 21
- ISSN:
- 1420-3049
- Page Range / eLocation ID:
- 5128
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
-
Rapid and automated lipid profiling by nuclear magnetic resonance spectroscopy using neural networksmore » « less
Abstract Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for quantitative metabolomics; however, quantification of metabolites from NMR data is often a slow and tedious process requiring user input and expertise. In this study, we propose a neural network approach for rapid, automated lipid identification and quantification from NMR data. Multilayered perceptron (MLP) networks were developed with NMR spectra as the input and lipid concentrations as output. Three large synthetic datasets were generated, each with 55,000 spectra from an original 30 scans of reference standards, by using linear combinations of standards and simulating experimental‐like modifications (line broadening, noise, peak shifts, baseline shifts) and common interference signals (water, tetramethylsilane, extraction solvent), and were used to train MLPs for robust prediction of lipid concentrations. The performances of MLPS were first validated on various synthetic datasets to assess the effect of incorporating different modifications on their accuracy. The MLPs were then evaluated on experimentally acquired data from complex lipid mixtures. The MLP‐derived lipid concentrations showed high correlations and slopes close to unity for most of the quantified lipid metabolites in experimental mixtures compared with ground‐truth concentrations. The most accurate, robust MLP was used to profile lipids in lipophilic hepatic extracts from a rat metabolomics study. The MLP lipid results analyzed by two‐way ANOVA for dietary and sex differences were similar to those obtained with a conventional NMR quantification method. In conclusion, this study demonstrates the potential and feasibility of a neural network approach for improving speed and automation in NMR lipid profiling and this approach can be easily tailored to other quantitative, targeted spectroscopic analyses in academia or industry.
-
Bladder cancer (BC) is frequent cancer affecting the urinary tract and is one of the most prevalent malignancies worldwide. No biomarkers that can be used for effective monitoring of therapeutic interventions for this cancer have been identified to date. This study investigated polar metabolite profiles in urine samples from 100 BC patients and 100 normal controls (NCs) using nuclear magnetic resonance (NMR) and two methods of high- resolution nanoparticle-based laser desorption/ionization mass spectrometry (LDI-MS). Five urine metabolites were identified and quantified using NMR spectroscopy to be potential indicators of bladder cancer. Twenty-five LDI-MS-detected compounds, predominantly peptides and lipids, distinguished urine samples from BC and NCs individuals. Level changes of three characteristic urine metabolites enabled BC tumor grades to be distinguished, and ten metabolites were reported to correlate with tumor stages. Receiver-Operating Characteristics analysis showed high predictive power for all three types of metabolomics data, with the area under the curve (AUC) values greater than 0.87. These findings suggest that metabolite markers identified in this study may be useful for the non-invasive detection and monitoring of bladder cancer stages and grades.more » « less
-
Chromatography is a robust and reliable separation method that can use various stationary phases to separate complex mixtures commonly seen in metabolomics. This review examines the types of chromatography and stationary phases that have been used in targeted or untargeted metabolomics with methods such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. General considerations for sample pretreatment and separations in metabolomics are considered, along with the various supports and separation formats for chromatography that have been used in such work. The types of liquid chromatography (LC) that have been most extensively used in metabolomics will be examined, such as reversed-phase liquid chromatography and hydrophilic liquid interaction chromatography. In addition, other forms of LC that have been used in more limited applications for metabolomics (e.g., ion-exchange, size-exclusion, and affinity methods) will be discussed to illustrate how these techniques may be utilized for new and future research in this field. Multidimensional LC methods are also discussed, as well as the use of gas chromatography and supercritical fluid chromatography in metabolomics. In addition, the roles of chromatography in NMR- vs. MS-based metabolomics are considered. Applications are given within the field of metabolomics for each type of chromatography, along with potential advantages or limitations of these separation methods.more » « less
-
more » « less
Abstract During aging, muscle gradually undergoes sarcopenia, the loss of function associated with loss of mass, strength, endurance, and oxidative capacity. However, the 3D structural alterations of mitochondria associated with aging in skeletal muscle and cardiac tissues are not well described. Although mitochondrial aging is associated with decreased mitochondrial capacity, the genes responsible for the morphological changes in mitochondria during aging are poorly characterized. We measured changes in mitochondrial morphology in aged murine gastrocnemius, soleus, and cardiac tissues using serial block‐face scanning electron microscopy and 3D reconstructions. We also used reverse transcriptase‐quantitative PCR, transmission electron microscopy quantification, Seahorse analysis, and metabolomics and lipidomics to measure changes in mitochondrial morphology and function after loss of mitochondria contact site and cristae organizing system (MICOS) complex genes,
Chchd3 ,Chchd6 , andMitofilin . We identified significant changes in mitochondrial size in aged murine gastrocnemius, soleus, and cardiac tissues. We found that both age‐related loss of the MICOS complex and knockouts of MICOS genes in mice altered mitochondrial morphology. Given the critical role of mitochondria in maintaining cellular metabolism, we characterized the metabolomes and lipidomes of young and aged mouse tissues, which showed profound alterations consistent with changes in membrane integrity, supporting our observations of age‐related changes in muscle tissues. We found a relationship between changes in the MICOS complex and aging. Thus, it is important to understand the mechanisms that underlie the tissue‐dependent 3D mitochondrial phenotypic changes that occur in aging and the evolutionary conservation of these mechanisms betweenDrosophila and mammals.
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/molecules25215128
