Fructose-sweetened liquid consumption is associated with fatty liver and oxidative stress. In rodent models of fructose-mediated fatty liver, protein consumption is decreased. Additionally, decreased sulfur amino acid intake is known to cause oxidative stress. Studies were designed to test whether oxidative stress in fructose-sweetened liquid-induced fatty liver is caused by decreased ad libitum solid food intake with associated inadequate sulfur amino acid intake. C57BL6 mice were grouped as: control (ad libitum water), fructose (ad libitum 30% fructose-sweetened liquid), glucose (ad libitum 30% glucose-sweetened water) and pair-fed (ad libitum water and sulfur amino acid intake same as the fructose group). Hepatic and plasma thiol-disulfide antioxidant status were analyzed after five weeks. Fructose- and glucose-fed mice developed fatty liver. The mitochondrial antioxidant protein, thioredoxin-2, displayed decreased abundance in the liver of fructose and glucose-fed mice compared to controls. Glutathione/glutathione disulfide redox potential (E hGSSG) and abundance of the cytoplasmic antioxidant protein, peroxiredoxin-2, were similar among groups. We conclude that both fructose and glucose-sweetened liquid consumption results in fatty liver and upregulated thioredoxin-2 expression, consistent with mitochondrial oxidative stress; however, inadequate sulfur amino acid intake was not the cause of this oxidative stress.
An alcohol use disorder (AUD) is associated with an increased susceptibility to respiratory infection and injury and, upon hospitalization, higher mortality rates. Studies in model systems show effects of alcohol on mitochondrial function, lipid metabolism and antioxidant systems. The present study applied high-resolution metabolomics to test for these changes in bronchoalveolar lavage fluid (BALF) of subjects with an AUD. Smokers were excluded to avoid confounding effects and compliance was verified by cotinine measurements. Statistically significant metabolic features, differentially expressed by control and AUD subjects, were identified by statistical and bioinformatic methods. The results show that fatty acid and acylcarnitine concentrations were increased in AUD subjects, consistent with perturbed mitochondrial and lipid metabolism. Decreased concentrations of methyl-donor compounds suggest altered one-carbon metabolism and oxidative stress. An accumulation of peptides suggests proteolytic activity, which could reflect altered epithelial barrier function. Two metabolites of possible microbial origin suggest subclinical bacterial infection. Furthermore, increased diacetylspermine suggests additional metabolic perturbations, which could contribute to dysregulated alveolar macrophage function and vulnerability to infection. Together, the results show an extended metabolic consequence of AUD in the bronchoalveolar space.
Nutritional metabolomics is rapidly maturing to use small molecule chemical profiling to support integration of diet and nutrition in complex biosystems research. These developments are critical to facilitate transition of nutritional sciences from population-based to individual-based criteria for nutritional research, assessment and management. This review addresses progress in making these approaches manageable for nutrition research. Important concept developments concerning the exposome, predictive health and complex pathobiology, serve to emphasize the central role of diet and nutrition in integrated biosystems models of health and disease. Improved analytic tools and databases for targeted and non-targeted metabolic profiling, along with bioinformatics, pathway mapping and computational modeling, are now used for nutrition research on diet, metabolism, microbiome and health associations. These new developments enable metabolome-wide association studies (MWAS) and provide a foundation for nutritional metabolomics, along with genomics, epigenomics and health phenotyping, to support integrated models required for personalized diet and nutrition forecasting.
Objective: Oxidation of plasma cysteine/cystine (Cys/CySS) redox potential (EhCySS) has been associated with risk factors for cardiovascular disease in humans. Cys and CySS are derived from dietary sulfur amino acids (SAA), but the specific effects of SAA depletion and repletion on Cys/CySS redox indices are unknown. The present study examined the effect of dietary SAA intake level on free Cys, free CySS and EhCySS in human plasma under fasting conditions.
Research Methods and Procedures: Healthy individuals aged 18–36 y (n=13) were equilibrated to foods providing the RDA for SAA and then fed chemically defined diets without SAA (0 mg·kg−1·d−1; n=13) followed by SAA at levels approximating the mean (56 mg·kg−1·d−1; n=8) or 99th percentile (117 mg·kg−1·d−1; n=5) intake levels of Americans. Fasting plasma samples were collected daily during 4-d study periods and analyzed for free Cys, free CySS and the EhCySS.
Results: The SAA-free diet significantly (p<0.05) decreased plasma free Cys concentrations and oxidized EhCySS values after 4 days of SAA depletion. With SAA repletion at 56 mg·kg−1·d− 1, plasma free Cys increased significantly and values for EhCySS became more reducing. Administration of a diet providing a higher dose of SAA (117 mg·kg−1·d−1) resulted in a significantly higher level of free Cys and a more reducing EhCySS.
Conclusions: These results show that free Cys and Cys/CySS redox potential (EhCySS) in fasting plasma are affected by dietary SAA intake level in humans. Significant changes occur slowly over 4 days with insufficient SAA intake, but rapidly (after 1 day) with repletion.
Background: Current available malaria diagnostic methods each have some limitations to meet the need for real-time and large-scale screening of asymptomatic and low density malaria infection at community level. It was proposed that malaria parasite-specific low molecular-weight metabolites could be used as biomarkers for the development of a malaria diagnostic tool aimed to address this diagnostic challenge. In this study, high resolution metabolomics (HRM) was employed to identify malaria parasite-specific metabolites in Plasmodium falciparum in vitro culture samples. Methods: Supernatants were collected at 12 hours interval from 3% haematocrit in vitro 48-hour time-course asynchronized culture system of P. falciparum. Liquid chromatography coupled with high resolution mass spectrometry was applied to discover potential parasite-specific metabolites in the cell culture supernatant. A metabolome-wide association study was performed to extract metabolites using Manhattan plot with false discovery rate (FDR) and hierarchical cluster analysis. The significant metabolites based on FDR cutoff were annotated using Metlin database. Standard curves were created using corresponding chemical compounds to accurately quantify potential Plasmodium-specific metabolites in culture supernatants. Results: The number of significant metabolite features was 1025 in the supernatant of the Plasmodium infected culture based on Manhattan plot with FDR q=0.05. A two way hierarchical cluster analysis showed a clear segregation of the metabolic profile of parasite infected supernatant from non-infected supernatant at four time points during the 48 hour culture. Among the 1025 annotated metabolites, the intensities of four molecules were significantly increased with culture time suggesting a positive association between the quantity of these molecules and level of parasitaemia: i) 3-methylindole, a mosquito attractant, ii) succinylacetone, a haem biosynthesis inhibitor, iii) S-methyl-L-thiocitrulline, a nitric oxide synthase inhibitor, and iv) O-arachidonoyl glycidol, a fatty acid amide hydrolase inhibitor, The highest concentrations of 3-methylindole and succinylacetone were 178 ± 18.7 pmoles at 36 hours and 157±30.5 pmoles at 48 hours respectively in parasite infected supernatant. Conclusion: HRM with bioinformatics identified four potential parasite-specific metabolite biomarkers using in vitro culture supernatants. Further study in malaria infected human is needed to determine presence of the molecules and its relationship with parasite densities.
Progression of Parkinson’s disease (PD) is highly variable, indicating that differences between slow and rapid progression forms could provide valuable information for improved early detection and management. Unfortunately, this represents a complex problem due to the heterogeneous nature of humans in regards to demographic characteristics, genetics, diet, environmental exposures and health behaviors. In this pilot study, we employed high resolution mass spectrometry-based metabolic profiling to investigate the metabolic signatures of slow versus rapidly progressing PD present in human serum. Archival serum samples from PD patients obtained within 3 years of disease onset were analyzed via dual chromatography-high resolution mass spectrometry, with data extraction by xMSanalyzer and used to predict rapid or slow motor progression of these patients during follow-up. Statistical analyses, such as false discovery rate analysis and partial least squares discriminant analysis, yielded a list of statistically significant metabolic features and further investigation revealed potential biomarkers. In particular, N8-acetyl spermidine was found to be significantly elevated in the rapid progressors compared to both control subjects and slow progressors. Our exploratory data indicate that a fast motor progression disease phenotype can be distinguished early in disease using high resolution mass spectrometry-based metabolic profiling and that altered polyamine metabolism may be a predictive marker of rapidly progressing PD.
The concept of multifractality is currently used to describe self-similar and complex scaling properties observed in numerous biological signals. Fractals are geometric objects or dynamic variations which exhibit some degree of similarity (irregularity) to the original object in a wide range of scales. This approach determines irregularity of biologic signal as an indicator of adaptability, the capability to respond to unpredictable stress, and health. In the present work, we propose the application of multifractal analysis of wavelet-transformed proton nuclear magnetic resonance (1H NMR) spectra of plasma to determine nutritional insufficiency. For validation of this method on 1H NMR signal of human plasma, standard deviation from classical statistical approach and Hurst exponent (H), left slope and partition function from multifractal analysis were extracted from 1H NMR spectra to test whether multifractal indices could discriminate healthy subjects from unhealthy, intensive care unit patients. After validation, the multifractal approach was applied to spectra of plasma from a modified crossover study of sulfur amino acid insufficiency and tested for associations with blood lipids. The results showed that standard deviation and H, but not left slope, were significantly different for sulfur amino acid sufficiency and insufficiency. Quadratic discriminant analysis of H, left slope and the partition function showed 78% overall classification accuracy according to sulfur amino acid status. Triglycerides and apolipoprotein C3 were significantly correlated with a multifractal model containing H, left slope, and standard deviation, and cholesterol and high-sensitivity C-reactive protein were significantly correlated to H. In conclusion, multifractal analysis of 1H NMR spectra provides a new approach to characterize nutritional status.
Mitochondrial phenotype is complex and difficult to define at the level of individual cell types. Newer metabolic profiling methods provide information on dozens of metabolic pathways from a relatively small sample. This pilot study used “top-down” metabolic profiling to determine the spectrum of metabolites present in liver mitochondria. High resolution mass spectral analyses and multivariate statistical tests provided global metabolic information about mitochondria and showed that liver mitochondria possess a significant phenotype based on gender and genotype. The data also show that mitochondria contain a large number of unidentified chemicals.
The concept of multifractality is currently used to describe self-similar and complex scaling properties observed in numerous biological signals. Fractals are geometric objects or dynamic variations which exhibit some degree of similarity (irregularity) to the original object in a wide range of scales. This approach determines irregularity of biologic signal as an indicator of adaptability, the capability to respond to unpredictable stress, and health. In the present work, we propose the application of multifractal analysis of wavelet-transformed proton nuclear magnetic resonance (1H NMR) spectra of plasma to determine nutritional insufficiency. For validation of this method on 1H NMR signal of human plasma, standard deviation from classical statistical approach and Hurst exponent (H), left slope and partition function from multifractal analysis were extracted from 1H NMR spectra to test whether multifractal indices could discriminate healthy subjects from unhealthy, intensive care unit patients. After validation, the multifractal approach was applied to spectra of plasma from a modified crossover study of sulfur amino acid insufficiency and tested for associations with blood lipids. The results showed that standard deviation and H, but not left slope, were significantly different for sulfur amino acid sufficiency and insufficiency. Quadratic discriminant analysis of H, left slope and the partition function showed 78% overall classification accuracy according to sulfur amino acid status. Triglycerides and apolipoprotein C3 were significantly correlated with a multifractal model containing H, left slope, and standard deviation, and cholesterol and high-sensitivity C-reactive protein were significantly correlated to H. In conclusion, multifractal analysis of 1H NMR spectra provides a new approach to characterize nutritional status.