First Steps toward the Giant Panda Metabolome Database: Untargeted Metabolomics of Feces, Urine, Serum, and Saliva by 1H NMR

Spinal muscular atrophy (SMA) is a genetically heterogeneous group of rare neuromuscular diseases and was until recently the most common genetic cause of death in children. The effects of 2-month nusinersen therapy on urine, serum, and liquor 1H-NMR metabolomes in SMA males and females were not explored yet, especially not in comparison to the urine 1H-NMR metabolomes of matching male and female cohorts. In this prospective, single-centered study, urine, serum, and liquor samples were collected from 25 male and female pediatric patients with SMA before and after 2 months of nusinersen therapy and urine samples from a matching healthy cohort (n = 125). Nusinersen intrathecal application was the first therapy for the treatment of SMA by the Food and Drug Administration (FDA) and the European Medicines Agency (EMA). Metabolomes were analyzed using targeted metabolomics utilizing 600 MHz 1H-NMR, parametric and nonparametric multivariate statistical analyses, machine learning, and modeling. Medical assessment before and after nusinersen therapy showed significant improvements of movement, posture, and strength according to various medical tests. No significant differences were found in metabolomes before and after nusinersen therapy in urine, serum, and liquor samples using an ensemble of statistical and machine learning approaches. In comparison to a healthy cohort, 1H-NMR metabolomes of SMA patients contained a reduced number and concentration of urine metabolites and differed significantly between males and females as well. Significantly larger data scatter was observed for SMA patients in comparison to matched healthy controls. Machine learning confirmed urinary creatinine as the most significant, distinguishing SMA patients from the healthy cohort. The positive effects of nusinersen therapy clearly preceded or took place devoid of significant rearrangements in the 1H-NMR metabolomic makeup of serum, urine, and liquor. Urine creatinine was successful at distinguishing SMA patients from the matched healthy cohort, which is a simple systemic novelty linking creatinine and SMA to the physiology of inactivity and diabetes, and it facilitates the monitoring of SMA disease in pediatric patients through non-invasive urine collection.

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Effects of the Chiral Fungicides Metalaxyl and Metalaxyl-M on the Earthworm Eisenia fetida as Determined by 1H-NMR-Based Untargeted Metabolomics

Molecules ◽

10.3390/molecules24071293 ◽

2019 ◽

Vol 24 (7) ◽

pp. 1293 ◽

Cited By ~ 6

Author(s):

Renke Zhang ◽

Zhiqiang Zhou

Keyword(s):

Nuclear Magnetic Resonance ◽

Citric Acid ◽

Magnetic Resonance ◽

1H Nmr ◽

Eisenia Fetida ◽

Tricarboxylic Acid ◽

Untargeted Metabolomics ◽

1H Nuclear Magnetic Resonance ◽

Endogenous Metabolites ◽

Arginine Aspartate

Although metalaxyl and metalaxyl-M are widely used fungicides, very little is known about their subacute and enantiospecific effects on the earthworm metabolome. In this study, Eisenia fetida were exposed to metalaxyl and metalaxyl-M at three concentrations (0.5, 5 and 50 mg/kg) for seven days. 1H nuclear magnetic resonance (1H-NMR)-based untargeted metabolomics showed that metalaxyl and metalaxyl-M exposure disturbed earthworms’ metabolism at all three concentrations. Endogenous metabolites, such as succinate, arginine, aspartate, urea, asparagine, alanine, trimethylamine, taurine, cysteine, serine, threonine, histidine, lysine, glucose, choline, carnitine, citric acid, alpha-ketoisovaleric acid, fumaric acid and so on, were significantly changed. These results indicate that metalaxyl and metalaxyl-M produce different, enantiospecific disturbances in the earthworm metabolism, particularly in the tricarboxylic acid (TCA) and urea cycles. The application of untargeted metabolomics thus provides more information for evaluating the toxic risks of metalaxyl and metalaxyl-M.

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Monitoring the Transition Period in Dairy Cows through 1H NMR-Based Untargeted Metabolomics

Dairy ◽

10.3390/dairy2030028 ◽

2021 ◽

Vol 2 (3) ◽

pp. 356-366

Author(s):

Andrés López Radcenco ◽

María de Lourdes Adrien ◽

Gretel Ruprechter ◽

Elena de Torres ◽

Ana Meikle ◽

...

Keyword(s):

Dairy Cows ◽

Milk Production ◽

1H Nmr ◽

Metabolic Diseases ◽

Transition Period ◽

Principal Component ◽

Partial Least Square ◽

Least Square ◽

Untargeted Metabolomics ◽

The Impact

The metabolic alterations associated with the increase in milk production make the transition period critical to the health of dairy cows, usually leading to a higher incidence of disease in periparturient animals. In this manuscript, we describe the use of NMR-based untargeted metabolomics to follow how these changes impact the serum metabolome in a group of 28 transition dairy cows with no initial clinical diseases. Principal component analysis (PCA) of serum 1H NMR data from four weeks before calving to 8 weeks after parturition allowed us to clearly identify four stages during the transition period. Pairwise comparisons using orthogonal partial least square discriminant analysis (OPLS-DA) and univariate data analysis led to the identification of 18 metabolites that varied significantly through these stages. Species such as acetate, betaine, and creatine are observed early after calving, while other markers of metabolic stress, including acetone, β-hydroxybutyrate (BHB), and choline, accumulate significantly at the height of milk production. Furthermore, marked variations in the levels of lactate, allantoin, alanine, and other amino acids reveal the activation of different gluconeogenic pathways following parturition. Concomitant with a return to homeostasis, a gradual normalization of the serum metabolome occurs 8 weeks after calving. Correlations of metabolite levels with dietary and metabolic adaptations based on animal parity could also be identified. Overall, these results show that NMR-based chemometric methods are ideally suited to monitor manifestations of metabolic diseases throughout the transition period and to assess the impact of nutritional management schemes on the metabolism of dairy cows.

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