Identification and characterization of fish oil supplements based on fatty acid analysis combined with a hierarchical clustering algorithm

Dietary L-carnitine supplementation changes lipid metabolism and glucose utilization of Rhynchocypris lagowskii fed diets with different lipid sources

The widely available crop oil is an effective alternative to the increasingly scarce marine fish oil. However, simple alternative strategies have led to declining growth and the edible value of farmed fish. It is worthwhile to explore the effects of micro supplements in diets to improve the tolerance of fish to different dietary lipid sources, which finally optimizes the feeding strategies. This study aimed to investigate the regulation of L-carnitine and dietary oil conditions on nutrient composition, lipid metabolism, and glucose regulation of Rhynchocypris lagowskii. Four diets were prepared according to fish oil, fish oil supplemented with L-carnitine, corn oil, and corn oil supplemented with L-carnitine, and FO, LCFO, CO, and LCCO were labeled, respectively. R. lagowskii was fed experimental diets for 8 weeks, and the glucose tolerance test was performed. The CO diet significantly resulted in higher crude lipid content in muscle but a lower level of serum lipid parameters of R. lagowskii than the FO diet. However, dietary L-carnitine supplementation significantly reduced the crude lipid content in the hepatopancreas and muscle of the fish fed with the CO diet yet increased the serum lipid parameters. Additionally, the crude lipid content of muscle was reduced in the fish fed with an FO diet supplemented with L-carnitine. Compared with the FO diet, the CO diet significantly reduced the ratio of n3/n6 polyunsaturated fatty acid in the hepatopancreas and muscle of R.lagowskii. Dietary L-carnitine supplementation significantly reduced the contents of total saturated fatty acids and total monounsaturated fatty acids in hepatopancreas under both dietary lipid sources. The CO diet significantly up-regulated the expression of genes related to lipid uptake and adipogenesis in hepatopancreas, including lipoprotein lipase (lpl), acetyl-coenzyme A carboxylase alpha (accα), and sterol regulatory element binding protein-1 (srebp1), compared with the FO diet. While dietary L-carnitine supplementation significantly down-regulated the expressions of lpl, accα, srebp1, and fatty acid synthase in hepatopancreas and muscle of fish under both dietary lipid sources, along with up-regulated expression of carnitine palmitoyltransferase 1 in hepatopancreas. Moreover, the fish fed with a CO diet significantly increased the expression of glucose uptake and clearance and significantly down-regulated the expressions of glucose regulation-related genes, including glucose transporter 1, glycogen synthase 1, and phosphofructokinase in hepatopancreas and muscle, resulting in slower glucose uptake and clearance than fish fed with FO diet. Nevertheless, dietary L-carnitine supplementation up-regulated the expression of gluconeogenesis-related genes, including glucose-6-phosphatase and phosphoenolpyruvate carboxykinase in the hepatopancreas of R. lagowskii under both dietary lipid sources. In conclusion, a higher dietary n6 PUFA resulted in lipid deposition, decreased serum lipid parameters, and limited serum glucose utilization of R. lagowskii. While the regulatory effect of L-carnitine on lipid metabolism and glucose utilization of R. lagowskii varies with dietary lipid sources and tissues.

Authentication of fish oil (omega-3) supplements using class-oriented chemometrics and comprehensive two-dimensional gas chromatography coupled to mass spectrometry

Food supplement authentication is an important concern worldwide due to the ascending consumption related to health benefits and its lack of effective regulation in underdeveloped countries, making it a target of fraudulent activities. In this context, this study evaluated fish oil supplements by comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GC×GC-MS) to obtain fingerprints, which were used to build predictive models for automated authentication of the most popular products sold in Brazil. The authentication process relied on a one-class classifier model using data-driven soft independent modeling of class analogy (DD-SIMCA). The output of the model was a binary classifier: certified IFOS fish oils and non-certified ones - regardless of the source of adulteration. The compositional analysis showed a significant variation in the samples, which validated the need for reliable statistical models. The DD-SIMCA algorithm is still incipient in GC×GC studies, but it proved to be an excellent tool for authenticity purposes, achieving a chemometric model with a sensitivity of 100%, specificity of 98.6%, and accuracy of 99.0% for fish oil authentication. Finally, orthogonalized partial least square discriminant analysis (OPLS-DA) was used to identify the features that distinguished the groups, which ascertained the results of the DD-SIMCA model that IFOS-certified oils are positively correlated to omega-3 fatty acids, including eicosapentaenoic acid (EPA, C20:5 n-3) and docosahexaenoic acid (DHA, C22:6 n-3).

UPLC-ESI-MRM/MS for Absolute Quantification and MS/MS Structural Elucidation of Six Specialized Pyranonaphthoquinone Metabolites From Ventilago harmandiana

Pyranonaphthoquinones (PNQs) are important structural scaffolds found in numerous natural products. Research interest in these specialized metabolites lies in their natural occurrence and therapeutic activities. Nonetheless, research progress has thus far been hindered by the lack of analytical standards and analytical methods for both qualitative and quantitative analysis. We report here that various parts of Ventilago harmandiana are rich sources of PNQs. We developed an ultraperformance liquid chromatography-electrospray ionization multiple reaction monitoring/mass spectrometry method to quantitatively determine six PNQs from leaves, root, bark, wood, and heartwood. The addition of standards in combination with a stable isotope of salicylic acid-D₆ was used to overcome the matrix effect with average recovery of 82% ± 1% (n = 15). The highest concentration of the total PNQs was found in the root (11,902 μg/g dry weight), whereas the lowest concentration was found in the leaves (28 μg/g dry weight). Except for the root, PNQ-332 was found to be the major compound in all parts of V. harmandiana, accounting for ∼48% of the total PNQs quantified in this study. However, PNQ-318A was the most abundant PNQ in the root sample, accounting for 27% of the total PNQs. Finally, we provide novel MS/MS spectra of the PNQs at different collision induction energies: 10, 20, and 40 eV (POS and NEG). For structural elucidation purposes, we propose complete MS/MS fragmentation pathways of PNQs using MS/MS spectra at collision energies of 20 and 40 eV. The MS/MS spectra along with our discussion on structural elucidation of these PNQs should be very useful to the natural products community to further exploring PNQs in V. harmandiana and various other sources.

Accounting for biological variation with linear mixed-effects modelling improves the quality of clinical metabolomics data

Metabolite profiles from biological samples suffer from both technical variations and subject-specific variants. To improve the quality of metabolomics data, conventional data processing methods can be employed to remove technical variations. These methods do not consider sources of subject variation as separate factors from biological factors of interest. This can be a significant issue when performing quantitative metabolomics in clinical trials or screening for a potential biomarker in early-stage disease, because changes in metabolism or a desired-metabolite signal are small compared to the total metabolite signals. As a result, inter-individual variability can interfere subsequent statistical analyses. Here, we propose an additional data processing step using linear mixed-effects modelling to readjust an individual metabolite signal prior to multivariate analyses. Published clinical metabolomics data was used to demonstrate and evaluate the proposed method. We observed a substantial reduction in variation of each metabolite signal after model fitting. A comparison with other strategies showed that our proposed method contributed to improved classification accuracy, precision, sensitivity and specificity. Moreover, we highlight the importance of patient metadata as it contains rich information of subject characteristics, which can be used to model and normalize metabolite abundances. The proposed method is available as an R package lmm2met.

Metabolomics and Integrative Omics for the Development of Thai Traditional Medicine

In recent years, interest in studies of traditional medicine in Asian and African countries has gradually increased due to its potential to complement modern medicine. In this review, we provide an overview of Thai traditional medicine (TTM) current development, and ongoing research activities of TTM related to metabolomics. This review will also focus on three important elements of systems biology analysis of TTM including analytical techniques, statistical approaches and bioinformatics tools for handling and analyzing untargeted metabolomics data. The main objective of this data analysis is to gain a comprehensive understanding of the system wide effects that TTM has on individuals. Furthermore, potential applications of metabolomics and systems medicine in TTM will also be discussed.

Comparison of fatty acid intakes assessed by a cardiovascular-specific food frequency questionnaire with red blood cell membrane fatty acids in hyperlipidaemic Australian adults: a validation study

BACKGROUND/OBJECTIVES

Limited dietary intake tools have been validated specifically for hyperlipidaemic adults. The Australian Eating Survey (AES) Food Frequency Questionnaire (FFQ) was adapted to include foods with cardio-protective properties (CVD-AES). The aims were to estimate dietary fatty acid (FA) intakes derived from the CVD-AES and AES and compare them with red blood cell (RBC) membrane FA content.

SUBJECTS/METHODS

Dietary intake was measured using the semi-quantitative 120-item AES and 177-item CVD-AES. Nutrient intakes were calculated using AUSNUT 2011-2013. Fasting RBC membrane FAs were assessed using gas chromatography. Extent of agreement between intakes estimated by AES or CVD-AES and RBC membrane composition (% of total FAs) for linoleic acid (LA), alpha-linolenic acid (ALA), eicosapentanoic acid (EPA), docosapentaenoic acid (DPA) and docosahexaenoic acid (DHA) were assessed using Spearman's correlation coefficients, adjusted linear regressions and Kappa statistics.

RESULTS

Data from 39 participants (72% female, 59.3±11.1 years) indicate stronger positive correlations between RBC membrane FAs and CVD-AES dietary estimates compared with the AES. Significant (P<0.05) moderate-strong correlations were found between CVD-AES FAs and FA proportions in RBC membranes for EPA (r=0.62), DHA (r=0.53) and DPA (r=0.42), with a moderate correlation for LA (r=0.39) and no correlation with ALA. Significant moderate correlations were found with the AES for DHA (r=0.39), but not for LA, ALA, EPA or DPA.

CONCLUSIONS

The CVD-AES provides a more accurate estimate of long chain FA intakes in hyperlipidaemic adults, compared with AES estimates. This indicates that a CVD-specific FFQ should be used when evaluating FA intakes in this population.

Improved quantification of farnesene during microbial production from Saccharomyces cerevisiae in two-liquid-phase fermentations

Organic solvents are widely used in microbial fermentations to reduce gas stripping effects and capture hydrophobic or toxic compounds. Reliable quantification of biochemical products in these overlays is highly challenging and practically difficult. Here, we present a significant improvement of identification and quantification methods for farnesene produced by Saccharomyces cerevisiae in two-liquid-phase fermentations using GC-MS and GC-FID. By increasing the polarity of the stationary phase introducing a ZB-50 column (50%-phenyl-50%-dimethylsiloxane) peak intensity could be increased and solvent carryover could be minimized. Direct quantification of farnesene in dodecane was achieved by GC-FID whereas GC-MS demonstrated to be an excellent technique for identification of known and unknown metabolites. The GC-FID is a suitable technique for direct quantification of farnesene in complex matrices as shown by the good calibration curve (R(2)>0.998, N=5) within the tested concentration range of 1-50 µg/mL and the reproducibility of the intensity (intraday; <10% RSD at each concentration; N=5). The limit of detection (LOD) and limit of quantification (LOQ) of the method were 0.24 and 0.80 µg/mL, respectively. Furthermore, the FID method proved to be highly stable with regard to the intensity of the calibration (N=6) when the measurements were performed across 250 samples that were derived from a dodecane overlay.