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Effects of lifelong exercise and aging on the blood metabolic fingerprint of rats.

Tzimou, Anastasia, et al. Biogerontology (2020)

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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)

Cartilage‐forming lesions include tumours that can vary in severity from benign enchondromas to high‐grade malignant chondrosarcomas. Chondrosarcoma is the second most frequent malignant bone tumour, accounting for 20–30% of all malignant bone neoplasms. Surgery is the standard treatment for cartilage tumours (CTs); however, their incidental diagnosis and the difficult differentiation of low‐grade lesions like chondrosarcoma grade I from benign entities like enchondroma are challenges for clinical management. In this sense, the search for circulating biomarkers for early detection and prognosis is an ongoing interest. Targeted metabolomics is a powerful tool that can propose potential biomarkers in biological fluids as well as help to discover disturbed metabolic pathways to reveal tumour pathogenesis. In this context, the aim of this study was to investigate the 1H nuclear magnetic resonance metabolomic serum profile of patients with CTs contrasted with healthy controls. Forty‐one metabolites were identified and quantified; the multivariate statistical methods principal component analysis and partial least squares discriminant analysis reveal a clear separation of the CT group, that is, the differential metabolites that were involved in two main metabolic pathways: the taurine and hypotaurine metabolism and synthesis and degradation of ketone bodies. Our results represent preliminary work for emergent serum‐based diagnostics or prognostic methods for patients with chondrogenic tumours.

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)

Intake of red and processed meat has been suspected to increase colorectal cancer risk potentially via endogenous formation of carcinogenic N-nitroso compounds or increased lipid and protein oxidation. Here we investigated the effect of inulin fortification of a pork sausage on these parameters. For four weeks, healthy Sprague-Dawley rats (n = 30) were fed one of three diets: inulin-fortified pork sausage, control pork sausage or a standard chow diet. Fecal content of apparent total N-nitroso compounds (ATNC), nitrosothiols and nitrosyl iron compounds (FeNO) were analyzed in addition to liver metabolism and oxidation products formed in liver, plasma and diets. Intriguingly, inulin fortification reduced fecal ATNC (p = 0.03) and FeNO (p = 0.04) concentrations. The study revealed that inulin fortification of processed meat could be a strategy to reduce nitroso compounds formed endogenously after consumption.

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)

48) Duan X, Zhang T, Ou L et al. 1H NMR-based metabolomic study of metabolic profiling for the urine of kidney stone patients. Urolithiasis (2020)

49) Yin X, Gibbons H, Rundle M, Frost G, McNulty B A, Nugent A P, Walton J, Flynn A, Brennan L. The Relationship between Fish Intake and Urinary Trimethylamine‐N‐Oxide. Mol. Nutr. Food Res. (2020)

50) Maulidiani M, Abas F, Rudiyanto R, Kadir N, Zolkeflee N, Lajis N. Analysis of urinary metabolic alteration in type 2 diabetic rats treated with metformin using the metabolomics of quantitative spectral deconvolution 1H NMR spectroscopy. Microchemical Journal (2020)

51) Castellanos L, Naranjo-Gaybor S, Forero A, Morales G, Wilson E, Ramos F, Choi Y. Metabolic fingerprinting of banana passion fruits and its correlation with quorum quenching activity. Phytochemistry (2020)

52) Antonelo D, Cônsolo N, Gómez J, Beline M, Goulart R, Corte R, Colnago L, Schilling M, Gerrard D, Silva S. Metabolite profile and consumer sensory acceptability of meat from lean Nellore and Angus × Nellore crossbreed cattle fed soybean oil. Food Research International (2020)

53) Sakaguchi C A, Nieman D C, Signini E, de Abreu R, Silva C D, Rehder-Santos P, Carosio M G A, Maria R, Dato C C, de Araújo H S S, Venâncio T, Ferreira A G, Catai A M. Chronic Influence of Inspiratory Muscle Training at Different Intensities on the Serum Metabolome. Metabolites (2020).

54) Darius T, Vergauwen M, Smith T et al. Brief O2 uploading during continuous hypothermic machine perfusion is simple yet effective oxygenation method to improve initial kidney function in a porcine autotransplant model. Am J Transplant (2020)

55) Lindqvist H, Rådjursöga M, Torstensson T, Jansson L, Ellegård L, Winkvist A. Urine Metabolite Profiles and Nutrient Intake Based on 4-Day Weighed Food Diary in Habitual Vegans, Vegetarians, and Omnivores, The Journal of Nutrition (2020)

56) He X, Sotelo-Orozco J, Rudolph C, Lönnerdal B and Slupsky CM. The Role of Protein and Free Amino Acids on Intake, Metabolism, and Gut Microbiome: A Comparison Between Breast-Fed and Formula-Fed Rhesus Monkey Infants. Front. Pediatr. (2020)

57) Lee J D, Kim H Y, Kang K et al. Integration of transcriptomics, proteomics and metabolomics identifies biomarkers for pulmonary injury by polyhexamethylene guanidine phosphate (PHMG-p), a humidifier disinfectant, in rats. Arch Toxicol (2020)

58) Morrell A, Tripet B, Eilers B, Tegman M, Thompson D, Copié V, Burkhea d J.Copper modulates sex-specific fructose hepatoxicity in nonalcoholic fatty liver disease (NALFD) Wistar rat models. The Journal of Nutritional Biochemistry (2020)

59) Cônsolo N R B, Silva J, Buarque V L M, Higuera-Padilla A, Barbosa L, Zawadzki A, Colnago L A, Netto A S, Gerrard D E, Silva S. Selection for Growth and Precocity Alters Muscle Metabolism in Nellore Cattle. Metabolites (2020)

60) Alshamleh N, Krause C, Richter N, Kurrle H, Serve U, Günther H, Schwalbe. Real‐Time NMR Spectroscopy for Studying Metabolism Angew. Chem. (2020)

61) Li Z, Du Y, Yuan Y. et al. Integrated quality evaluation strategy for multi-species resourced herb medicine of Qinjiao by metabolomics analysis and genetic comparation. Chin Med (2020).

62) Velásquez-Valle R, Villa-Ruano N, Hidalgo-Martínez D, Zepeda-Vallejo L, Pérez-Hernández N, Reyes-López C, Reyes-Cervantes E, Medina-Melchor D, Becerra-Martínez E. Revealing the 1H NMR metabolome of mirasol chili peppers (Capsicum annuum) infected by Candidatus Phytoplasma trifolii. Food Research International (2020)

63) Murgia F, Corda V, Serrenti M, Usai V, Santoru ML, Hurt KJ, Passaretti M, Monni MC, Atzori L, Monni G. Seminal Fluid Metabolomic Markers of Oligozoospermic Infertility in Humans. Metabolites (2020)

64) Steward KF, Eilers B, Tripet B, Fuchs A, Dorle M, Rawle R, Soriano B, Balasubramanian N, Copié V, Bothner B and Hatzenpichler R. Metabolic Implications of Using BioOrthogonal Non-Canonical Amino Acid Tagging (BONCAT) for Tracking Protein Synthesis. Front. Microbiol(2020)

BioOrthogonal Non-Canonical Amino acid Tagging (BONCAT) is a powerful tool for tracking protein synthesis on the level of single cells within communities and whole organisms. A basic premise of BONCAT is that the non-canonical amino acids (NCAA) used to track translational activity do not significantly alter cellular physiology. If the NCAA would induce changes in the metabolic state of cells, interpretation of BONCAT studies could be challenging. To address this knowledge-gap, we have used a global metabolomics analyses to assess the intracellular effects of NCAA incorporation. Two NCAA were tested: L-azidohomoalanine (AHA) and L-homopropargylglycine (HPG); L-methionine (MET) was used as a minimal stress baseline control. Liquid Chromatography Mass Spectrometry (LC-MS) and Nuclear Magnetic Resonance (NMR) were used to characterize intracellular metabolite profiles of Escherichia coli cultures, with multivariate statistical analysis using XCMS and MetaboAnalyst. Results show that doping with NCAA induces metabolic changes, however, the metabolic impact was not dramatic. A second set of experiments in which cultures were placed under mild stress to simulate real-world environmental conditions showed a more consistent and more robust perturbation. Pathways that changed include amino acid and protein synthesis, choline and betaine, and the TCA cycle. Globally, these changes were statistically minor, indicating that NCAA are unlikely to exert a significant impact on cells during incorporation. Our results are consistent with previous reports of NCAA doping under replete conditions and extend these results to bacterial growth under environmentally relevant conditions. Our work highlights the power of metabolomics studies in detecting cellular response to growth conditions and the complementarity of NMR and LCMS as omics tools.

65) Wu Z, Cheng Y, Yang Y, Gao Y, Sun X, Wang L, Sun Q, Zhang J, Xu X. In vitro and in vivo anti-Listeria effect of Succinoglycan Riclin through regulating MAPK/IL-6 axis and metabolic profiling. International Journal of Biological Macromolecules (2020)

66) Martín-González MZ, Palacios H, Rodríguez MA, Arola L, Aragonès G, Muguerza B. Beneficial Effects of a Low-dose of Conjugated Linoleic Acid on Body Weight Gain and other Cardiometabolic Risk Factors in Cafeteria Diet-fed Rats. Nutrients (2020)

67) Fan Y, Huang X, Chen J, Han B. Formation of a Mixed-Species Biofilm Is a Survival Strategy for Unculturable Lactic Acid Bacteria and Saccharomyces cerevisiae in Daqu, a Chinese Traditional Fermentation Starter. Front. Microbiol(2020)

68) Abdul Majid ND, Abdul Hamid A, Salleh SZ, et al. Metabolomics approach to investigate the ergogenic effect of Morinda citrifolia L. leaf extract on obese Sprague Dawley rats. Phytochemical Analysis. (2020)

69) Kim SH, Lee W, Kwon D, Lee S, Son SW, Seo MS, Kim KS, Lee YH, Kim S, Jung YS. Metabolomic Analysis of the Liver of a Dextran Sodium Sulfate-Induced Acute Colitis Mouse Model: Implications of the Gut–Liver Connection. Cells (2020)

70) Zhang J, Hang C, Shao W, Li W, Lin D. NMR-Based metabolomic analysis of the anticancer effect of metformin on cholangiocarcinoma cells. (2020)

71) Niemuth J N, Harms C A, Macdonald J M, Stoskopf M K. NMR-based metabolomic profile of cold stun syndrome in loggerhead Caretta caretta, green Chelonia mydas and Kemp's ridley Lepidochelys kempii sea turtles in North Carolina, USA. Wildlife Biology(2020).

72) Chaumont M, Tagliatti V, Channan E M, Colet J M, Bernard A, Morra S, Faoro V. Short halt in vaping modifies cardiorespiratory parameters and urine metabolome: a randomized trial. American Journal of Physiology-Lung Cellular and Molecular Physiology (2020)

73) Yang X, Zhao Y, Sun Q, Yang Y, Gao Y, Ge W, Zhang J. Adenosine accumulation causes metabolic disorders in testes and associates with lower testosterone level in obese mice. Molecular Reproduction and Development. (2020)

74) Azizan A, Xin L A, Hamid A, Ashikin N, Maulidiani M, Mediani A, Abas F. Potentially Bioactive Metabolites from Pineapple Waste Extracts and Their Antioxidant and α-Glucosidase Inhibitory Activities by 1H NMR. Foods (2020)

75) Thøgersen R, Rasmussen M K, Sundekilde U K, Goethals S A, Van Hecke T, Vossen E, Bertram H C. Background Diet Influences TMAO Concentrations Associated with Red Meat Intake without Influencing Apparent Hepatic TMAO-Related Activity in a Porcine Model. Metabolites (2020)

76) Dallons M, Schepkens C, Dupuis A, Tagliatti V, Colet J M. New Insights About Doxorubicin-Induced Toxicity to Cardiomyoblast-Derived H9C2 Cells and Dexrazoxane Cytoprotective Effect: Contribution of In Vitro 1H-NMR Metabonomics. Front. Pharmacol (2020)

77) Ijare O B, Sharpe M A, Baskin D S, Pichumani K. Proton Magnetic Resonance Spectroscopy Characterization of Rathke’s Cleft Cysts (RCCs): Relevance to the Differential Diagnosis of Pituitary Adenomas and RCCs. Cancers (2020)

78) Viswan A, Singh C, Kayastha A M, Azim A, Sinha N. An NMR based panorama of the heterogeneous biology of acute respiratory distress syndrome (ARDS) from the standpoint of metabolic biomarkers. NMR in Biomedicine (2020)

79) Watve S, Barrasso K, Jung S A, Davis K J, Hawver L A, Khataokar A, Ng W L. Parallel quorum-sensing system in Vibrio cholerae prevents signal interference inside the host. PLoS pathogens (2020)

80) Rousseau M. Le rôle des métabolites dérivés de la diète sur la santé cardiométabolique: la contribution des acides aminés à chaîne ramifiée et des polyphénols. (2020)

81) Bingol, K., Masucci, J., & Caldwell, G. NMR-Based Amino acid Assay for Human Plasma and Serum. (2020)

82) Ji Y, Su A, Ma G, Tao T, Fang D, Zhao L, Hu Q. Comparison of bioactive constituents and effects on gut microbiota by in vitro fermentation between Ophicordyceps sinensis and Cordyceps militaris. Journal of Functional Foods (2020)

83) Yin X, Gibbons H, Rundle M, Frost G, McNulty B A, Nugent A P, Brennan L.The Relationship between Fish Intake and Urinary Trimethylamine‐N‐Oxide. Molecular Nutrition & Food Research (2020)

84) Barnett B R, Fathi F, Falco Cobra P, Yi S Y, Anderson J M, Eghbalnia H R, Yu J P J. Metabolic Changes in Synaptosomes in an Animal Model of Schizophrenia Revealed by 1H and 1H, 13C NMR Spectroscopy. Metabolites (2020)

Synaptosomes are isolated nerve terminals that contain synaptic components, including neurotransmitters, metabolites, adhesion/fusion proteins, and nerve terminal receptors. The essential role of synaptosomes in neurotransmission has stimulated keen interest in understanding both their proteomic and metabolic composition. Mass spectrometric (MS) quantification of synaptosomes has illuminated their proteomic composition, but the determination of the metabolic composition by MS has been met with limited success. In this study, we report a proof-of-concept application of one- and two-dimensional nuclear magnetic resonance (NMR) spectroscopy for analyzing the metabolic composition of synaptosomes. We utilize this approach to compare the metabolic composition synaptosomes from a wild-type rat with that from a newly generated genetic rat model (Disc1 svΔ2), which qualitatively recapitulates clinically observed early DISC1 truncations associated with schizophrenia. This study demonstrates the feasibility of using NMR spectroscopy to identify and quantify metabolites within synaptosomal fractions.

85) Brugaletta G, De Cesare A, Zampiga, M., Laghi, L., Oliveri, C., Zhu, C., Sirri, F. Effects of Alternative Administration Programs of a Synbiotic Supplement on Broiler Performance, Foot Pad Dermatitis, Caecal Microbiota, and Blood Metabolites. Animals (2020)

86) Yoon, D., Shin, W. C., Lee, Y. S., Kim, S., Baek, N. I., Lee, D. Y. A Comparative Study on Processed Panax ginseng Products Using HR-MAS NMR-Based Metabolomics. Molecules (2020)

87) Lee, J. S., Kim, S. Y., Chun, Y. S., Chun, Y. J., Shin, S. Y., Choi, C. H., & Choi, H. K. Characteristics of fecal metabolic profiles in patients with irritable bowel syndrome with predominant diarrhea investigated using 1H‐NMR coupled with multivariate statistical analysis. Neurogastroenterology & Motility (2020)

88) Jiang, L., Howlett, K., Patterson, K., & Wang, B. Introduction of a New Method for Two-Dimensional NMR Quantitative Analysis in Metabolomics Studies. Analytical Biochemistry (2020)

89) Murgia, F., Lorefice, L., Poddighe, S., Fenu, G., Secci, M. A., Marrosu, M. G., ... & Atzori, L. Multi-Platform Characterization of Cerebrospinal Fluid and Serum Metabolome of Patients Affected by Relapsing–Remitting and Primary Progressive Multiple Sclerosis. Journal of Clinical Medicine (2020)

Background: Multiple sclerosis (MS) is a chronic immunemediated disease of the central nervous system with a highly variable clinical presentation and disease progression. In this study, we investigate the metabolomics profile of patients affected by relapsing–remitting MS (RRMS)and primary progressive MS (PPMS), in order to find potential biomarkers to distinguish between the two forms. Methods: Cerebrospinal Fluid CSF and blood samples of 34 patients (RRMS n = 22, PPMS n = 12) were collected. Nuclear magnetic resonance (1H-NMR) and mass spectrometry (coupled with a gas chromatography and liquid chromatography) were used as analytical techniques. Subsequently, a multivariate statistical analysis was performed; the resulting significant variables underwent U-Mann–Whitney test and correction for multiple comparisons. Receiver Operating Characteristic ROC curves were built and the pathways analysis was conducted. Results: The analysis of the serum and the CSF of the two classes, allowed the identification of several altered metabolites (lipids, biogenic amines, and amino acids). The pathways analysis indicated the following pathways were affected: Glutathione metabolism, nitrogen metabolism, glutamine–glutamate metabolism, arginine–ornithine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis etc. Conclusion: The analysis allowed the identification of a set of metabolites able to classify RRMS and PPMS patients, each of whom express different patterns of metabolites in the two biofluids.

90) Akhbari, Pouya, et al. "Can joint fluid metabolic profiling (or “metabonomics”) reveal biomarkers for osteoarthritis and inflammatory joint disease? A systematic review." Bone & Joint Research 9.3 (2020)

91) Song, Hye Seon, et al. "Microbial niches in raw ingredients determine microbial community assembly during kimchi fermentation." Food Chemistry (2020)

92) Sehlakgwe, Phophi Freda, Namrita Lall, and Gerhard Prinsloo. "1H-NMR Metabolomics and LC-MS Analysis to Determine Seasonal Variation in a Cosmeceutical Plant Leucosidea sericea." Frontiers in Pharmacology 11 (2020)

93) Gu, Jinping, et al. "Analysis of the Different Metabolic Phenotypes of Metalaxyl Enantiomers in Adolescent Rat by Using 1H NMR Based Urinary Metabolomics." Chemical Research in Toxicology (2020).

94) Graça, Gonçalo, Chung-Ho E. Lau, and Luís G. Gonçalves. "Exploring Cancer Metabolism: Applications of Metabolomics and Metabolic Phenotyping in Cancer Research and Diagnostics." Tumor Microenvironment. Springer, Cham,(2020)

95) Zhang, Guanshi, et al. "Urinary Metabolomics Around Parturition Identifies Metabolite Alterations in Dairy Cows Affected Postpartum by Lameness: Preliminary Study." Dairy 1.1 (2020)

96) Xu, Han, et al. "Therapeutic assessment of fractions of Gastrodiae Rhizoma on chronic atrophic gastritis by 1H NMR-based metabolomics." Journal of Ethnopharmacology (2020)

97) Acevedo-Acevedo, Suehelay, Seneca Cox, and Sean P. Palecek. "Lymphatic endothelial cells (LECs) have minor influence on breast cancer metabolism." The metabolic response of cancer cells to chemotherapeutics and the tumor microenvironment (2020)

98) Acevedo-Acevedo, Suehelay, et al. "Copanlisib (Copan) and ABT263 combination therapy induce changes in colorectal cancer (CRC) metabolism." The metabolic response of cancer cells to chemotherapeutics and the tumor microenvironment (2020)

99) Paul, Anup, et al. "Malignancy prediction among tissues from Oral SCC patients including neck invasions: a 1 H HRMAS NMR based metabolomic study." Metabolomics 16.3 (2020)

100) Garcia-Gutierrez, Enriqueta, et al. "Production of multiple bacteriocins, including the novel bacteriocin gassericin M, by Lactobacillus gasseri LM19, a strain isolated from human milk." Applied Microbiology and Biotechnology (2020)

101) Chandradevan, Machap, et al. "1 H NMR-Based Metabolomics Approach in Investigating the Chemical Profile, Antioxidant and Anti-Inflammatory Activities of Gynura procumbens and Cleome gynandra." Plant Foods for Human Nutrition (2020)

102) Zuo, Jian, et al. "Bioactive fractions from Securidaca inappendiculata alleviated collagen‐induced arthritis in rats by regulating metabolism‐related signaling." The Kaohsiung Journal of Medical Sciences (2020)

103) Pomfret, Sarah M., et al. "Metabolomics for biomonitoring: an evaluation of the metabolome as an indicator of aquatic ecosystem health." Environmental Reviews 28.1 (2020)

104) Acevedo-Acevedo, Suehelay, et al. "Breast cancer influences lymphatic endothelial cell metabolism." The metabolic response of cancer cells to chemotherapeutics and the tumor microenvironment (2020)

105) Yang, Changwei, et al. "Brain-Region Specific Metabolic Abnormalities in Parkinson’s Disease and Levodopa-Induced Dyskinesia." Frontiers in Aging Neuroscience 12 (2020)

106) Stimpson, Scott E., et al. "Human CD8+ T-cells Require Glycolysis to Elicit Effector Function." bioRxiv (2020)

107) Merolle, Lucia, et al. "Heparin‐induced lipoprotein precipitation apheresis in dyslipidemic patients: A multiparametric assessment." Journal of Clinical Apheresis (2020)

108) Anderson, James R., et al. "Ex-Vivo Equine Cartilage Explant Osteoarthritis Model-A Metabolomics and Proteomics Study." bioRxiv (2020)

109) Sylvestre, Duncan A., et al. "Untargeted metabolomic analysis of plasma from relapsing-remitting multiple sclerosis patients reveals changes in metabolites associated with structural changes in brain." Brain Research 1732 (2020)

110) Tiemeier, Gesa L., et al. "Lowering the increased intracellular pH of human‐induced pluripotent stem cell‐derived endothelial cells induces formation of mature Weibel‐Palade bodies." Stem cells translational medicine (2020)

111) Ashraf, Azhaar, et al. "Iron dyshomeostasis, lipid peroxidation and perturbed expression of cystine/glutamate antiporter in Alzheimer’s disease: Evidence of ferroptosis." Redox Biology (2020)

112) Barroso-Batista, João, et al. "Specific eco-evolutionary contexts in the mouse gut reveal Escherichia coli metabolic versatility." Current Biology (2020)

113) Chen, Fang-Hsin, et al. "Multimodal imaging reveals transient liver metabolic disturbance and sinusoidal circulation obstruction after a single administration of ketamine/xylazine mixture." Scientific Reports 10.1 (2020)

114) Sundekilde, Ulrik K., et al. "An Integrated Multi-Omics Analysis Defines Key Pathway Alterations in a Diet-Induced Obesity Mouse Model." Metabolites 10.3 (2020)

115)Hardivillé, Stéphan, et al. "TATA-Box Binding Protein O-GlcNAcylation at T114 Regulates Formation of the B-TFIID Complex and Is Critical for Metabolic Gene Regulation." Molecular Cell 77.5 (2020)

116) Myer, Ciara, et al. "Aqueous humor metabolite profile of psuedoexfoliation glaucoma is distinctive." Molecular Omics (2020)

117) SANTORU, MARIA LAURA. "Study of metabolic alterations in inflammatory bowel diseases." (2020)

118) D’Amato, Alfonsina, et al. "Faecal microbiota transplant from aged donor mice affects spatial learning and memory via modulating hippocampal synaptic plasticity-and neurotransmission-related proteins in young recipients." bioRxiv (2020)

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119) Ahmadi, Shokouh, et al. "Metformin reduces aging-related leaky gut and improves cognitive function by beneficially modulating gut microbiome/goblet cell/mucin axis." The Journals of Gerontology: Series A (2020)

120) Belivermiş, Murat, et al. "Effects of variable deoxygenation on trace element bioaccumulation and resulting metabolome profiles in the blue mussel (Mytilus edulis)." Chemosphere (2020)

121) Hellal, Khaoula, et al. "Antioxidant, α-Glucosidase, and Nitric Oxide Inhibitory Activities of Six Algerian Traditional Medicinal Plant Extracts and 1H-NMR-Based Metabolomics Study of the Active Extract." Molecules 25.5 (2020)

122) Beachler, T. M., et al. "Plasma metabolomic profiling of healthy pregnant mares and mares with experimentally induced placentitis." Equine Veterinary Journal (2020)

123) Fang-Hsin, Chen, et al. "Multimodal imaging reveals transient liver metabolic disturbance and sinusoidal circulation obstruction after a single administration of ketamine/xylazine mixture." Scientific Reports (Nature Publisher Group) 10.1 (2020)

124) Yi, Shenghui, et al. "NMR-based metabonomic analysis of HUVEC cells during replicative senescence." Aging (Albany NY) 12.4 (2020)

125) Cunha, Camila P., et al. "Metabolic Regulation and Development of Energy Cane Setts upon Auxin Stimulus." Plant and Cell Physiology 61.3 (2020)
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128) Li, Li, et al. "1H-NMR Metabolomics Analysis of the Effect of Rubusoside on Serum Metabolites of Golden Hamsters on a High-Fat Diet." Molecules 25.6 (2020)

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153) Ji, Chenglong, et al. "Global responses to tris (1-chloro-2-propyl) phosphate (TCPP) in rockfish Sebastes schlegeli using integrated proteomic and metabolomic approach." Science of The Total Environment (2020)

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159) Shi, Yue, et al. "The effect of polysaccharides from Cibotium barometz on enhancing temozolomide–induced glutathione exhausted in human glioblastoma U87 cells, as revealed by 1H NMR metabolomics analysis." International Journal of Biological Macromolecules (2020)

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161) Zhu, Chenglin, et al. "First Insights into the Urinary Metabolome of Captive Giraffes by Proton Nuclear Magnetic Resonance Spectroscopy." Metabolites 10.4 (2020)

162) Song, Shuang, et al. "Biochar for urban agriculture: Impacts on soil chemical characteristics and on Brassica rapa growth, nutrient content and metabolism over multiple growth cycles." Science of The Total Environment (2020)

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164) Roques, Simon, et al. "Integrative Metabolomics for Assessing the Effect of Insect (Hermetia illucens) Protein Extract on Rainbow Trout Metabolism." Metabolites 10.3 (2020)

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176) Jakobsen, Louise, et al. "Metabolic Effects of Bovine Milk Oligosaccharides on Selected Commensals of the Infant Microbiome—Commensalism and Postbiotic Effects." Metabolites 10.4 (2020)

177) Cibecchini, Giulia, et al. "Anti-angiogenic effect of graphene oxide in primary human endothelial cells." ACS Applied Materials & Interfaces (2020)

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207) Tzimou, Anastasia, et al. "Effects of lifelong exercise and aging on the blood metabolic fingerprint of rats." Biogerontology (2020)

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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.