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The case studies below showcase various studies that were performed using Chenomx technology and services.
Analyzing the Metabolic Effects of Acetaminophen
Developing Biomarkers for Adverse Drug Responses
Pathways From Serological Metabolite Profiles
Acetaminophen is the most common identifiable cause of acute liver failure, and is an excellent model compound for studying liver toxicity. Acetaminophen toxicity has thus become a very active area of research. Identifying and quantifying metabolites associated with acetaminophen toxicity is an integral part of this research, and Chenomx is uniquely equipped to extract this information from biofluid samples.
Drug-induced liver injury is the leading reason that drug candidates fail. Identifying a suite of toxicity biomarkers for use in preclinical screening of drug candidates will allow drugs with harmful side effects to be identified earlier. Biomarkers that can be used to monitor or stage diseases will also offer insight into the net metabolic effect of a drug and can provide information for developing new drugs or adjusting treatment. Chenomx software offers powerful tools to aid in identifying these biomarkers.
Metabolomic data sets obtained using Chenomx NMR Suite often require additional analysis to place them in proper context. The GeneGo pathway analysis platform can help establish this context. In this note, we present an example analysis using serological metabolic profiles from Chenomx NMR Suite, known inflammatory markers from prior studies of the K/BxN mouse model and the GeneGo platform to generate a mechanistic hypothesis for the K/BxN mouse model.
Accurate CSI Quantification for Targeted Profiling
Accurately quantifying metabolites using targeted profiling in Chenomx NMR Suite requires using a chemical shape and shift indicator (CSI) of known concentration. As a result, the accuracy of the CSI concentration has a significant influence on quantification accuracy using this technique. Measuring ratios of the CSI peak area with that of a second, commercially available standard under optimal acquisition conditions offers a simple method of accurately measuring the concentration of the CSI.
Optimizing Spectra for Metabolomics
Chenomx Processor allows you to work with NMR spectra from a variety of sources, helping you apply phasing and baseline correction through manual and semi-automated tools, and offering advanced lineshape correction through reference deconvolution. Processor also allows you to define chemical shape indicator (CSI) parameters and determine sample pH via indicator compounds. These are necessary prerequisites to analyzing your spectra with Chenomx Profiler.
Targeted Profiling of Common Metabolites in Saliva
Saliva is an excellent biofluid for analysis by targeted profiling. It is easily collected by individuals with minimal training, using noninvasive techniques. Targeted profiling of saliva samples can provide identification and quantification of many of the small molecule metabolites commonly found in saliva, and may allow the development of simple screening procedures for a variety of diseases. In this note we present a list of common metabolites found in human saliva, and techniques for targeted profiling of saliva spectra with Chenomx NMR Suite.
Metabolites in Blood Serum and Plasma
Blood serum and plasma are biofluids that are increasingly important in NMR-based metabolomics analysis. In this note we discuss several approaches to the analysis of serum using Chenomx NMR Suite, focusing on relaxation-edited NMR (CPMG) and physical separation of protein and metabolites using ultrafiltration. The CPMG method is simpler to apply, but the spectra are easier to analyze when protein is removed from a sample.
Targeted Profiling of Common Metabolites in Urine
Urine is a readily-collected, information-rich biofluid that can provide insight into the metabolic state of an organism. As a result, urine is often a focus in metabolomics investigations using NMR and MRI spectroscopy, in both diagnostic and monitoring applications. Targeted profiling is a powerful tool that can drive such studies, providing direct identification and quantification of a variety of metabolites. In this note we present a list of common metabolites found in many NMR spectra of human urine and several strategies for approaching targeted profiling of such spectra with Chenomx NMR Suite.
Identifying Metabolites in Biofluids
In this note we present a rapid, efficient method for identifying metabolites in biofluid NMR spectra using targeted profiling. Conventional techniques for identifying and quantifying metabolites in such spectra are labor-intensive and error-prone, as positions and linewidths of peaks can vary widely with changes in pH and other solution matrix effects. The length of time and level of operator skill needed to analyze large numbers of these complex spectra are significant barriers to the widespread application of NMR in metabolomics.
Statistical Analysis of Targeted Profiling Data
Analysis of 1H NMR spectra in metabolomics studies often requires multivariate pattern recognition techniques to extract meaningful results. Targeted profiling offers the ability to analyze spectra based directly on the identity and quantities of individual compounds. Profiles created using targeted profiling in Chenomx NMR Suite can be used as input in statistical software packages such as Umetrics SIMCA-P. Performing PCA on Chenomx targeted profiles yields information-rich results that allow rapid biological interpretation, since group separation can be directly correlated to variations in specific metabolite concentrations.
Correcting Lineshapes in NMR Spectra
In this note we present a method for removing lineshape distortions from nuclear magnetic resonance (NMR) spectra prior to more detailed analysis. Reference deconvolution is a method of reconstructing an ideal spectrum by removing lineshape distortions caused by field inhomogeneity. Applying reference deconvolution has been found to improve the quality of fit of a spectrum using targeted profiling in Chenomx NMR Suite. However, successful application of reference deconvolution to a spectrum requires some preprocessing and the presence of an appropriate reference peak.
Statistical Analysis of Spectral Binning Data
Analysis of 1H NMR spectra in metabolomics studies often requires multivariate pattern recognition techniques to extract meaningful results. Spectral binning is an effective data reduction technique commonly used to prepare spectra for multivariate analysis. Spectral binning output from the Profiler module of Chenomx NMR Suite can readily be analyzed with multivariate analysis software packages like Umetrics SIMCA-P.