Featured Publication:

Metabolic and Immunological Effects of Intermittent Fasting on a Ketogenic Diet Containing Medium-Chain Triglycerides in Healthy Dogs.

Leung YB, Cave NJ, Heiser A, Edwards PJB, Godfrey AJR, Wester T Front. Vet. Sci. (2020)

View 2019 — 2006 Publications 

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1) López‐Garrido L, Bañuelos‐Hernández AE, Pérez‐Hernández E, et al. Metabolic profiling of serum in patients with cartilage tumours using 1H‐NMR spectroscopy: A pilot study. Magn Reson Chem. (2020)

2) Zhong X, Gu L, Xiong W, Wang H, Lian D, Zheng Y, Zhou S, Zhou W, Gu J, Shen J, Wang J, Zhang G, Liu X. 1H NMR spectroscopy-based metabolic profiling of Ophiocordyceps sinensis and Cordyceps militaris in water-boiled and 50% ethanol-soaked extracts. Journal of Pharmaceutical and Biomedical Analysis (2020)

3) McClorry S, Slupsky C, Lind T, Åkeson P, Hernell O, Öhlund I. Effectiveness of vitamin D supplementation in Swedish children may be negatively impacted by BMI and serum fructose. The Journal of Nutritional Biochemistry (2020)

4) Choi Y, Lee S, Kim H, Eom J, Kim D, Lee S. The potential nutritive value of Sargassum fulvellum as a feed ingredient for ruminants. Algal Research (2020)

5) Kim S, Kim E, Shin B, Seo J, Kim Y, Lee D, Choi H. NMR-based metabolic profiling discriminates the geographical origin of raw sesame seeds. Food Control (2020)

6) Eymann C., Götze S., Bock C. et al. Thermal performance of the European flat oyster, Ostrea edulis (Linnaeus, 1758)—explaining ecological findings under climate change. Mar Biol (2020)

7) Kumari S., Goyal V., Kumaran S.S. et al. Quantitative metabolomics of saliva using proton NMR spectroscopy in patients with Parkinson’s disease and healthy controls. Neurol Sci (2020)

8) Lu Z, Wang S, Ji C, Shan X, Wu H. Evaluation of metal pollution-induced biological effects in Chinese shrimp Fenneropenaeus chinensis by NMR-based metabolomics. Marine Pollution Bulletin (2020)

9) Chen L, Zhao X, Wu J, Liu Q, Pang X, Yang H. Metabolic characterisation of eight Escherichia coli strains including "Big Six" and acidic responses of selected strains revealed by NMR spectroscopy. Food Microbiology (2020)

10) Chien C, Lin T, Chi C, Liu C. Probiotic, Bacillus subtilis E20 alters the immunity of white shrimp, Litopenaeus vannamei via glutamine metabolism and hexosamine biosynthetic pathway. Fish & Shellfish Immunology (2020)

11) Hee Chun B, Kim K, Jeong S, Jeon C. The effect of salt concentrations on the fermentation of doenjang, a traditional Korean fermented soybean paste. Food Microbiology (2020)

12) Blakebrough-Hall C., Dona A., D’occhio M.J. et al. Diagnosis of Bovine Respiratory Disease in feedlot cattle using blood 1H NMR metabolomics. Sci Rep (2020)

13) Cropotova J, Mozuraityte R, Standal I, Ojha S, Rustad T, Brijesh Tiwari. Influence of high-pressure processing on quality attributes of haddock and mackerel minces during frozen storage, and fishcakes prepared thereof. Innovative Food Science & Emerging Technologies (2020)

14) Thøgersen R, Gray N, Kuhnle G, Van Hecke T, De Smet S, Young J, Sundekilde U, Hansen A, Bertram H. Inulin-fortification of a processed meat product attenuates formation of nitroso compounds in the gut of healthy rats. Food Chemistry (2020)

15) Gao P, Wang L, Yang N, Wen J, Zhao M, Su G, Zhang J, Weng D. Peroxisome proliferator-activated receptor gamma (PPARγ) activation and metabolism disturbance induced by bisphenol A and its replacement analog bisphenol S using in vitro macrophages and in vivo mouse models. Environment International (2020)

16) Bao W., Huang X., Liu J., Han B., Chen, J. Influence of Lactobacillus brevis on metabolite changes in bacteria‐fermented sufu. Journal of Food Science (2020)

17) Liang R, Shao X, Shi Y, Jiang L, Han G. Antioxidant defenses and metabolic responses of blue mussels (Mytilus edulis) exposed to various concentrations of erythromycin. Science of The Total Environment (2020)

18) Alinaghi M, Nguyen D.N., Sangild P.T., Bertram H.C., Direct Implementation of Intestinal Permeability Test in NMR Metabolomics for Simultaneous Biomarker Discovery—A Feasibility Study in a Preterm Piglet Model. Metabolites (2020)

19) Muhialdin B, Kadum H, Zarei M, Hussin A. Effects of metabolite changes during lacto-fermentation on the biological activity and consumer acceptability for dragon fruit juice. LWT (2020)

20) Hong, X, Mat Isa, N, Fakurazi, S, Safinar Ismail, I. Phytochemical and anti‐inflammatory properties of Scurrula ferruginea (Jack) Danser parasitising on three different host plants elucidated by NMR‐based metabolomics. Phytochemical Analysis (2020)

21) Kim S, Kim A, Ma S, Lee W, Lee S, Yoon D, Kim D H, Kim S. Glutathione Injection Alleviates the Fluctuation of Metabolic Response under Thermal Stress in Olive Flounder. Paralichthys olivaceus. Metabolites (2020)

22) Lin C, Dong J, Wei Z, Cheng K, Li J, You S, Liu Y, Wang X, Chen Z. 1H-NMR based metabolic profiles delineate the anticancer effect of vitamin C and oxaliplatin on hepatocellular carcinoma cells. Journal of Proteome Research (2020)

23) Li A, Zhang W, Zhang L, Liu Y, Li K, Du G, Qin X. Elucidating the time-dependent changes in the urinary metabolome under doxorubicin-induced nephrotoxicity. Toxicology Letters (2020)

24) Ferdausi A, Chang X, Hall A, Jones M. Galanthamine production in tissue culture and metabolomic study on Amaryllidaceae alkaloids in Narcissus pseudonarcissus cv. Carlton. Industrial Crops and Products (2020)

25) Djukovic D, Raftery D, Gowda N. Chapter 16 - Mass spectrometry and NMR spectroscopy based quantitative metabolomics. Proteomic and Metabolomic Approaches to Biomarker Discovery (Second Edition). Academic Press (2020)

26) Lopes T, de Moraes F, Arni R, Rahal P, Calmon M. Berberine associated photodynamic therapy promotes autophagy and apoptosis via ROS generation in renal carcinoma cells. Biomedicine & Pharmacotherapy (2020)

27) Luise D, Picone G, Balzani A, Capozzi F, Bertocchi M, Salvarani C, Bosi P, Edwards S, Trevisi P. Investigation of the Defatted Colostrum 1H-NMR Metabolomics Profile of Gilts and Multiparous Sows and Its Relationship with Litter Performance. Animals (2020)

28) Zheng H, Dong B, Ning J, Shao X, Zhao L, Jiang Q, Ji H, Cai A, Xue W, Gao H. NMR-based metabolomics analysis identifies discriminatory metabolic disturbances in tissue and biofluid samples for progressive prostate cancer. Clinica Chimica Acta (2020)

29) Teng S, Aziz N, Mustafa M, Laboh R, Ismail I, Devi S. Preliminary study on the effect of endogeic earthworm on metabolic changes of blood-disease-infected banana. Archives of Phytopathology and Plant Protection (2020)

30) Rahimi R, Hajirezaee S, Pordanjani H. A 1HNMR-based molecular study of anesthesia in fish. Aquaculture (2020)

31) Leung YB, Cave NJ, Heiser A, Edwards PJB, Godfrey AJR, Wester T Metabolic and Immunological Effects of Intermittent Fasting on a Ketogenic Diet Containing Medium-Chain Triglycerides in Healthy Dogs. Front. Vet. Sci. (2020)

32) Xia J, Hu X, Huang C et al. Metabolic profiling of cold adaptation of a deep-sea psychrotolerant Microbacterium sediminis to prolonged low temperature under high hydrostatic pressure. Appl Microbiol Biotechnol (2020)

33) Hansen B, Sørensen L, Størseth T, Altin D, Gonzalez S, Skancke J, Rønsberg M, Nordtug T. The use of PAH, metabolite and lipid profiling to assess exposure and effects of produced water discharges on pelagic copepods. Science of The Total Environment (2020)

34) Kumar U, Jain A, Guleria A, Kumar V, Misra D, Goel R, Danda D, Misra R, Kumar D. Circulatory Glutamine/Glucose ratio for evaluating disease activity in Takayasu arteritis: A NMR based serum metabolomics study. Journal of Pharmaceutical and Biomedical Analysis (2020)

35) Bianchi L, Laghi L, Correani V, Schifano E, Landi C, Uccelletti D, Mattei B. A Combined Proteomics, Metabolomics and In Vivo Analysis Approach for the Characterization of Probiotics in Large-Scale Production. Biomolecules (2020)

36) Burton KJ, Krüger R, Scherz V, Münger L.H, Picone G, Vionnet N, Bertelli C, Greub G, Capozzi F, Vergères G. Trimethylamine-N-Oxide Postprandial Response in Plasma and Urine Is Lower After Fermented Compared to Non-Fermented Dairy Consumption in Healthy Adults. Nutrients (2020)

37) Gramatyka M, Boguszewicz, Ciszek M, Gabryś D, Kulik R, Sokół M. Metabolic changes in mice cardiac tissue after low-dose irradiation revealed by 1H NMR spectroscopy. Journal of Radiation Research (2020)

38) Awin T, Mediani A, Faudzi S, Maulidiani, Leong S, Shaari K, Abas F. Identification of α-glucosidase inhibitory compounds from Curcuma mangga fractions, International Journal of Food Properties (2020)

39) Gao J, Bai P, Li Y, Li J, Jia C, Wang T, Zhao H, Si Y, Chen J. Metabolomic Profiling of the Synergistic Effects of Ginsenoside Rg1 in Combination with Neural Stem Cell Transplantation in Ischemic Stroke Rats. Journal of Proteome Research (2020)

40) Hsu WH, Wang S.-J., Chao Y.-M., Chen C.-J., Wang Y.-F., Fuh J.-L, Lin Y.-L. Urine metabolomics signatures in reversible cerebral vasoconstriction syndrome. Cephalalgia. (2020)


42) Okumu D, Aponte-Collazo L, Dewar B, Cox N, East M, Tech K, McDonald I, Tikunov A, Holmuhamedov E, Macdonald J, Graves L. Lyn regulates creatine uptake in an imatinib-resistant CML cell line. Biochimica et Biophysica Acta (2020)

43) Zolkeflee NKZ, Isamail NA, Maulidiani M, et al. Metabolite variations and antioxidant activity of Muntingia calabura leaves in response to different drying methods and ethanol ratios elucidated by NMR‐based metabolomics. Phytochemical Analysis. (2020)

44) Ten-Doménech I, Ramos-Garcia V, Piñeiro-Ramos J.D, Gormaz M, Parra-Llorca A, Vento M, Kuligowski J, Quintás G. Current Practice in Untargeted Human Milk Metabolomics. Metabolites (2020)

45) van Schadewijk R., Krug J.R., Shen D. et al. Magnetic Resonance Microscopy at Cellular Resolution and Localised Spectroscopy of Medicago truncatula at 22.3 Tesla. Sci Rep 10, 971 (2020)

46) Guirro M, Gual-Grau A, Gibert-Ramos A, Alcaide-Hidalgo J.M., Canela N.; Arola L., Mayneris-Perxachs J. Metabolomics Elucidates Dose-Dependent Molecular Beneficial Effects of Hesperidin Supplementation in Rats Fed an Obesogenic Diet. Antioxidants (2020)

47) Pathmasiri W., Kay K., McRitchie S., Sumner S. Analysis of NMR Metabolomics Data. In: Li S. (eds) Computational Methods and Data Analysis for Metabolomics. Methods in Molecular Biology (2020)

Case Studies

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.

Application Notes


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.

Sample Types

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

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.