Monitoring of the Rioja red wine production process by 1 H-NMR spectroscopy.

BACKGROUND: As an inherently quantitative and unbiased analytical technique, proton nuclear magnetic resonance (1 H-NMR) provides an excellent method to monitor the quality of food and beverages, and a sensitive and informative tool to study the winemaking process. RESULTS: By using NMR, it is possible to monitor quantitative changes in wine metabolites (amino acids, organic acids and some phenolic compounds) during the winemaking process, including wine ageing. This study shows an increase in the concentration of the phenols at the beginning of alcoholic fermentation, as well as a stabilization and slight increase in gallic acid and a slight decrease in resveratrol during the oak barrel ageing step. CONCLUSION: This study demonstrates the potential of NMR as a process analytical technology (PAT) tool in the wine industry, by monitoring amino acids, organic acids and three polyphenols - gallic acid, catechin and resveratrol - during the winemaking process. This study of the time course evolution of wine has been conducted in a commercial winery rather than an experimental laboratory, demonstrating the capacity of this technique in commercial winemaking production. © 2021 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Repeatability and reproducibility of lipoprotein particle profile measurements in plasma samples by ultracentrifugation.

Background Characterization of lipoprotein particle profiles (LPPs) (including main classes and subclasses) by means of ultracentrifugation (UC) is highly requested given its clinical potential. However, rapid methods are required to replace the very labor-intensive UC method and one solution is to calibrate rapid nuclear magnetic resonance (NMR)-based prediction models, but the reliability of the UC-response method required for the NMR calibration has been largely overlooked. Methods This study provides a comprehensive repeatability and reproducibility study of various UC-based lipid measurements (cholesterol, triglycerides [TGs], free cholesterol, phospholipids, apolipoprotein [apo]A1 and apoB) in different main classes and subclasses of 25 duplicated fresh plasma samples and of 42 quality control (QC) frozen pooled plasma samples of healthy individuals. Results Cholesterol, apoA1 and apoB measurements were very repeatable in all classes (intraclass correlation coefficient [ICC]: 92.93%-99.54%). Free cholesterol and phospholipid concentrations in main classes and subclasses and TG concentrations in high-density lipoproteins (HDL), HDL subclasses and low-density lipoproteins (LDL) subclasses, showed worse repeatability (ICC: 19.21%-99.08%) attributable to low concentrations, variability introduced during UC and assay limitations. On frozen QC samples, the reproducibility of cholesterol, apoA1 and apoB concentrations was found to be better than for the free cholesterol, phospholipids and TGs concentrations. Conclusions This study shows that for LPPs measurements near or below the limit of detection (LOD) in some of the subclasses, as well as the use of frozen samples, results in worsened repeatability and reproducibility. Furthermore, we show that the analytical assay coupled to UC for free cholesterol and phospholipids have different repeatability and reproducibility. All of this needs to be taken into account when calibrating future NMR-based models.

Toward Reliable Lipoprotein Particle Predictions from NMR Spectra of Human Blood: An Interlaboratory Ring Test.

Lipoprotein profiling of human blood by 1H nuclear magnetic resonance (NMR) spectroscopy is a rapid and promising approach to monitor health and disease states in medicine and nutrition. However, lack of standardization of measurement protocols has prevented the use of NMR-based lipoprotein profiling in metastudies. In this study, a standardized NMR measurement protocol was applied in a ring test performed across three different laboratories in Europe on plasma and serum samples from 28 individuals. Data was evaluated in terms of (i) spectral differences, (ii) differences in LPD predictions obtained using an existing prediction model, and (iii) agreement of predictions with cholesterol concentrations in high- and low-density lipoproteins (HDL and LDL) particles measured by standardized clinical assays. ANOVA-simultaneous component analysis (ASCA) of the ring test spectral ensemble that contains methylene and methyl peaks (1.4-0.6 ppm) showed that 97.99% of the variance in the data is related to subject, 1.62% to sample type (serum or plasma), and 0.39% to laboratory. This interlaboratory variation is in fact smaller than the maximum acceptable intralaboratory variation on quality control samples. It is also shown that the reproducibility between laboratories is good enough for the LPD predictions to be exchangeable when the standardized NMR measurement protocol is followed. With the successful implementation of this protocol, which results in reproducible prediction of lipoprotein distributions across laboratories, a step is taken toward bringing NMR more into scope of prognostic and diagnostic biomarkers, reducing the need for less efficient methods such as ultracentrifugation or high-performance liquid chromatography (HPLC).

POLYS 2.0: An open source software package for building three-dimensional structures of polysaccharides.

This article describes an update of POLYS, the POLYSaccharide builder, for generating three-dimensional structures of polysaccharides and complex carbohydrates (Engelsen et al., Biopolymers 1996, 39, 417-433). POLYS is written in portable ANSI C and is now released under an open source license. Using this software, complex branched carbohydrate structures and polysaccharides can be constructed from their primary structure and the relevant monosaccharides stored in database containing information on optimized glycosidic linkage geometries. The constructed three-dimensional structures are described as Cartesian coordinate files which can be used as input to other molecular modeling software. The new version of POLYS includes a large database of monosaccharides and a helical generator to build and optimize regular single helix or double helix structures. To demonstrate the efficiency of POLYS to build carbohydrate structures, four examples of increasing complexity are presented in the manuscript, from simple alpha glucans over complex starch fragments and the double helical structure of amylopectin to the mega-oligosaccharide RhamnoGalacturonan II.

Batch-wise versus continuous dough mixing of Danish butter cookies. A near infrared hyperspectral imaging study.

The Danish buttered cookie is a famous confectionery product. Its success makes manufacturing of the large volumes required challenging, introducing the need for different strategies to increase production while maintaining a high-quality standard. Two manufacturing lines used are batch-wise and continuous dough mixing. Despite the recipe being the same, the outcome of the two production types differs in texture and external appearance. While this does not infringe on the quality, changes in texture are observable. This manuscript analyses the physicochemical differences of the cookies after baking using Near Infrared hyperspectral imaging and Chemometrics. The study demonstrates that the changes in texture between batch and continuous production are mostly due to the difference in crystalline sucrose emerging in invisible spots on or near the surface of the cookies and a higher tendency of migrated butter-fat spots on the surface of the cookies for the continuous manufacturing procedure.

Gut Microbiome and Its Cofactors Are Linked to Lipoprotein Distribution Profiles.

Increasing evidence indicates that the gut microbiome (GM) plays an important role in dyslipidemia. To date, however, no in-depth characterization of the associations between GM with lipoproteins distributions (LPD) among adult individuals with diverse BMI has been conducted. To determine such associations, we studied blood-plasma LPD, fecal short-chain fatty acids (SCFA) and GM of 262 Danes aged 19-89 years. Stratification of LPD segregated subjects into three clusters displaying recommended levels of lipoproteins and explained by age and body-mass-index. Higher levels of HDL2a and HDL2b were associated with a higher abundance of Ruminococcaceae and Christensenellaceae. Increasing levels of total cholesterol and LDL-1 and LDL-2 were positively associated with Lachnospiraceae and Coriobacteriaceae, and negatively with Bacteroidaceae and Bifidobacteriaceae. Metagenome-sequencing showed a higher abundance of biosynthesis of multiple B-vitamins and SCFA metabolism genes among healthier LPD profiles. Metagenomic-assembled genomes (MAGs) affiliated to Eggerthellaceae and Clostridiales were contributors of these genes and their relative abundance correlated positively with larger HDL subfractions. The study demonstrates that differences in composition and metabolic traits of the GM are associated with variations in LPD among the recruited subjects. These findings provide evidence for GM considerations in future research aiming to shed light on mechanisms of the GM-dyslipidemia axis.

Residue specific hydration of primary cell wall potato pectin identified by solid-state 13C single-pulse MAS and CP/MAS NMR spectroscopy.

Hydration of rhamnogalacturonan-I (RG-I) derived from potato cell wall was analyzed by (13)C single-pulse (SP) magic-angle-spinning (MAS) and (13)C cross-polarization (CP) MAS nuclear magnetic resonance (NMR) and supported by (2)H SP/MAS NMR experiments. The study shows that the arabinan side chains hydrate more readily than the galactan side chains and suggests that the overall hydration properties can be controlled by modifying the ratio of these side chains. Enzymatic modification of native (NA) RG-I provided samples with reduced content of arabinan (sample DA), galactan (sample DG), or both side chains (sample DB). Results of these samples suggested that hydration properties were determined by the length and character of the side chains. NA and DA exhibited similar hydration characteristics, whereas DG and DB were difficult to hydrate because of the less hydrophilic properties of the rhamnose-galacturonic acid (Rha-GalA) backbone in RG-I. Potential food ingredient uses of RG-I by tailoring of its structure are discussed.

The effect of daily protein supplementation, with or without resistance training for 1 year, on muscle size, strength, and function in healthy older adults: A randomized controlled trial.

BACKGROUND: Protein supplementation alone or combined with resistance training has been proposed to be effective in counteracting age-related losses of muscle mass and strength. OBJECTIVES: To investigate the effect of protein supplementation alone or combined with light-intensity or heavy-load resistance exercise on muscle size, strength, and function in older adults. METHODS: In a 1-y randomized controlled trial, 208 healthy older adults (>65 y) were randomly assigned to 1 of 5 interventions: 1) carbohydrate supplementation (CARB); 2) collagen protein supplementation (COLL); 3) whey protein supplementation (WHEY); 4) light-intensity resistance training 3-5 times/wk with whey protein supplementation (LITW); and 5) heavy resistance training 3 times weekly with whey protein supplementation (HRTW). Protein supplements contained 20 g protein + 10 g carbohydrate, whereas CARB contained 30 g of carbohydrates. All intervention groups received the supplement twice daily. The primary outcome was change in the quadriceps cross-sectional area (qCSA). Secondary outcomes included measures of lower extremity strength and power, functional capabilities, and body composition. RESULTS: There were 184 participants who completed the study. COLL and WHEY did not affect any measured parameter compared to CARB. Compared to WHEY, HRTW improved the qCSA size (between-group difference, +1.68 cm2; 95% CI, +0.41 to +2.95 cm2; P = 0.03), as well as dynamic (+18.4 Nm; 95% CI, +10.1 to +26.6 Nm; P < 10-4) and isometric knee extensor strength (+23.9 Nm; 95% CI, +14.2 to +33.6 Nm; P < 10-5). LITW did not improve the qCSA size, but increased dynamic knee extensor strength compared to WHEY (+13.7 Nm; 95% CI, +5.3 and +22.1 Nm; P = 0.01). CONCLUSIONS: Recommending protein supplementation as a stand-alone intervention for healthy older individuals seems ineffective in improving muscle mass and strength. Only HRTW was effective in both preserving muscle mass and increasing strength. Thus, we recommend that future studies investigate strategies to increase long-term compliance to heavy resistance exercise in healthy older adults. This trial was registered at clinicaltrials.gov as NCT02034760.

Three different Fourier-transform mid-infrared sampling techniques to characterize bio-organic samples.

In recent years, there has been a surge in the number of applications of Fourier-transform mid-infrared (FTIR) spectroscopy for the characterization of environmental samples and prediction of some of their properties whose measurement has traditionally involved time-consuming and costly methods. However, there are several different mid-infrared techniques available, and there is a gap in knowledge regarding the best-suited technique for recording informative spectra of different types of environmental samples. This study compared the three most widespread FTIR techniques using solid and liquid samples. A total of 11 environmental samples belonging to four categories were analyzed with attenuated total reflectance (ATR), photoacoustic (PAS), and diffuse reflectance (DR) FTIR spectroscopy. Overall, PAS-FTIR was the best technique, providing a greater amount of information, especially for opaque samples (i.e., organic waste, biochar, and soil), than ATR-FTIR and DR-FTIR spectroscopy. Attenuated total reflectance FTIR provided the best spectra for soft samples, such as plant materials, probably due to their ability to achieve good optical contact with the ATR crystal. Finally, DR-FTIR performed relatively well for most samples but was found to be more sensitive to moisture in the samples, resulting in noise in specific areas, and was less sensitive in bond vibrations related to Si.

Physical fitness in community-dwelling older adults is linked to dietary intake, gut microbiota, and metabolomic signatures.

When humans age, changes in body composition arise along with lifestyle-associated disorders influencing fitness and physical decline. Here we provide a comprehensive view of dietary intake, physical activity, gut microbiota (GM), and host metabolome in relation to physical fitness of 207 community-dwelling subjects aged +65 years. Stratification on anthropometric/body composition/physical performance measurements (ABPm) variables identified two phenotypes (high/low-fitness) clearly linked to dietary intake, physical activity, GM, and host metabolome patterns. Strikingly, despite a higher energy intake high-fitness subjects were characterized by leaner bodies and lower fasting proinsulin-C-peptide/blood glucose levels in a mechanism likely driven by higher dietary fiber intake, physical activity and increased abundance of Bifidobacteriales and Clostridiales species in GM and associated metabolites (i.e., enterolactone). These factors explained 50.1% of the individual variation in physical fitness. We propose that targeting dietary strategies for modulation of GM and host metabolome interactions may allow establishing therapeutic approaches to delay and possibly revert comorbidities of aging.

An exploratory NMR nutri-metabonomic investigation reveals dimethyl sulfone as a dietary biomarker for onion intake.

The metabolome following intake of onion by-products is evaluated. Thirty-two rats were fed a diet containing an onion by-product or one of the two derived onion by-product fractions: an ethanol extract and the residue. A 24 hour urine sample was analyzed using (1)H NMR spectroscopy in order to investigate the effects of onion intake on the rat metabolism. Application of interval extended canonical variates analysis (ECVA) proved to be able to distinguish between the metabolomic profiles from rats consuming normal feed and rats fed with an onion diet. Two dietary biomarkers for onion intake were identified as dimethyl sulfone and 3-hydroxyphenylacetic acid. The same two dietary biomarkers were subsequently revealed by interval partial least squares regression (PLS) to be perfect quantitative markers for onion intake. The best PLS calibration model yielded a root mean square error of cross-validation (RMSECV) of 0.97% (w/w) with only 1 latent variable and a squared correlation coefficient of 0.94. This indicates that urine from rats on the by-product diet, the extract diet, and the residue diet all contain the same dietary biomarkers and it is concluded that dimethyl sulfone and 3-hydroxyphenylacetic acid are dietary biomarkers for onion intake. Being able to detect specific dietary biomarkers is highly beneficial in the control of nutritionally enhanced functional foods.

A novel improved method for analysis of 2D diffusion-relaxation data--2D PARAFAC-Laplace decomposition.

This paper demonstrates how the multi-linear PARAFAC model can with advantage be used to decompose 2D diffusion-relaxation correlation NMR spectra prior to 2D-Laplace inversion to the T(2)-D domain. The decomposition is advantageous for better interpretation of the complex correlation maps as well as for the quantification of extracted T(2)-D components. To demonstrate the new method seventeen mixtures of wheat flour, starch, gluten, oil and water were prepared and measured with a 300 MHz nuclear magnetic resonance (NMR) spectrometer using a pulsed gradient stimulated echo (PGSTE) pulse sequence followed by a Carr-Purcell-Meiboom-Gill (CPMG) pulse echo train. By varying the gradient strength, 2D diffusion-relaxation data were recorded for each sample. From these double exponentially decaying relaxation data the PARAFAC algorithm extracted two unique diffusion-relaxation components, explaining 99.8% of the variation in the data set. These two components were subsequently transformed to the T(2)-D domain using 2D-inverse Laplace transformation and quantitatively assigned to the oil and water components of the samples. The oil component was one distinct distribution with peak intensity at D=3 x 10(-12) m(2) s(-1) and T(2)=180 ms. The water component consisted of two broad populations of water molecules with diffusion coefficients and relaxation times centered around correlation pairs: D=10(-9) m(2) s(-1), T(2)=10 ms and D=3 x 10(-13) m(2) s(-1), T(2)=13 ms. Small spurious peaks observed in the inverse Laplace transformation of original complex data were effectively filtered by the PARAFAC decomposition and thus considered artefacts from the complex Laplace transformation. The oil-to-water ratio determined by PARAFAC followed by 2D-Laplace inversion was perfectly correlated with known oil-to-water ratio of the samples. The new method of using PARAFAC prior to the 2D-Laplace inversion proved to have superior potential in analysis of diffusion-relaxation spectra, as it improves not only the interpretation, but also the quantification.

Long wavelength near-infrared transmission spectroscopy of barley seeds using a supercontinuum laser: Prediction of mixed-linkage beta-glucan content.

A supercontinuum laser was used to perform the first transmission measurements on intact seeds with long wavelength near-infrared spectroscopy. A total of 105 barley seeds from five different barley genotypes (Bomi, lys5.f, lys5.g, lys16 and lys95) were measured from 2275 to 2375 nm. The mixed-linkage (1→3,1→4)-ß-D-glucan (BG) and protein content was measured with wet chemical analysis for each single seed. A partial least squares model correlated the BG % (w/w) with the spectral measurements with a R2CV and R2PRED of 0.83 and 0.90, respectively. The predictive model for BG could be improved by averaging spectra from the same seed and by replacing the individual seed BG content with the average BG of each barley genotype.

Untargeted GC-MS Metabolomics Reveals Changes in the Metabolite Dynamics of Industrial Scale Batch Fermentations of Streptoccoccus thermophilus Broth.

An industrial scale biomass production using batch or fed-batch fermentations usually optimized by selection of bacterial strains, tuning fermentation media, feeding strategy, and temperature. However, in-depth investigation of the biomass metabolome during the production may reveal new knowledge for better optimization. In this study, for the first time, the authors investigated seven fermentation batches performed on five Streptoccoccus thermophilus strains during the biomass production at Chr. Hansen (Denmark) in a real life large scale fermentation process. The study is designed to investigate effects of batch fermentation, fermentation time, production line, and yeast extract brands on the biomass metabolome using untargeted GC-MS metabolomics. Processing of the raw GC-MS data using PARAFAC2 revealed a total of 90 metabolites out of which 64 are identified. Partitioning of the data variance according to the experimental design was performed using ASCA and revealed that batch and fermentation time effects and their interaction term were the most significant effects. The yeast extract brand had a smaller impact on the biomass metabolome, while the production line showed no effect. This study shows that in-depth metabolic analysis of fermentation broth provides a new tool for advanced optimization of high-volume-low-cost biomass production by lowering the cost, increase the yield, and augment the product quality.

Starch phosphorylation: a new front line in starch research.

Starch is the primary energy reserve in higher plants and is, after cellulose, the second most abundant carbohydrate in the biosphere. It is also the most important energy source in the human diet and, being a biodegradable polymer with well-defined chemical properties, has an enormous potential as a versatile renewable resource. The only naturally occurring covalent modification of starch is phosphorylation. Starch phosphate esters were discovered a century ago but were long regarded as a curiosity, receiving little attention. Indeed, the mechanism for starch phosphorylation remained completely unknown until recently. The starch-phosphorylating enzyme is an alpha-glucan water dikinase. It is now known that starch phosphorylation plays a central role in starch metabolism.

Prediction of total fatty acid parameters and individual fatty acids in pork backfat using Raman spectroscopy and chemometrics: Understanding the cage of covariance between highly correlated fat parameters.

This study investigates how Partial Least Squares regression models for predicting individual fatty acids (FAs) and total FA parameters depend on Raman spectral variation associated with the iodine value in pork backfat. The backfat was sampled from pigs, which were fed with different dietary fat sources and levels. Good correlations between the Raman spectra and the total FA composition parameters and most individual FAs were obtained (R(CV)(2)=0.78-0.90). However, the predictions of the individual FAs are indirect and to a high degree depend on co-variance with the total FA parameters. A new procedure was demonstrated for identifying and characterizing such indirect or non-targeted calibrations. This information is very useful when Raman spectroscopy or other vibrational spectroscopic techniques are used to predict non-targeted quality parameters such as individual FAs as they may lead to inaccurate predictions of future sample if the underlying covariance structure is changed e.g. by new dietary regimes or genotypes.

Cooking effects on water distribution in potatoes using nuclear magnetic resonance relaxation.

Continuous low-field (LF) (1)H NMR relaxometry was used to monitor the structural changes during cooking of potatoes with two different dry matter (DM) contents. A principal component analysis of the relaxation decay curves revealed major events related to water mobility during cooking, which occur at 53 and 60 degrees C for potatoes with medium and low DM contents, respectively. Exponential analysis of the relaxation decays reveals two major water populations in the potato: a slow-relaxing (assigned to water in cytoplasm and extracellular cavities) water component, T(22) ( approximately 350-550 ms), and a fast-relaxing component (primarily assigned to water associated with starch and cell walls), T(21) ( approximately 45-65 ms). Significant DM dependent shifts in both the T(21) and T(22) relaxation time constants were observed during cooking, indicating that starch gelatinizes between 53 and 70 degrees C with water exchanging with the hydroxyls of starch (transition in T(21)) and cells start to disrupt with an increase in diffusion volumes at approximately 60 degrees C (transition in T(22)). The study reveals that continuous LF NMR measurement is an excellent and highly sensitive method to study changes in water mobility and water populations during the cooking of potatoes.

Insight into the Functionality of Microbial Exopolysaccharides by NMR Spectroscopy and Molecular Modeling.

Microbial polysaccharides represent an important class of microbial polymers with diverse functions such as biofilm formation, thickening, and gelling properties as well as health-promoting properties. The broad range of exopolysaccharide (EPS) functionalities has sparked a renewed interest in this class of molecules. Chemical, enzymatic as well as genetic modifications by metabolic engineering can be used to create large numbers of analogous EPS variants with respect to EPS functionality. While this top-down approach is effective in finding new candidates for desired functionality, there seems to be a lack of the corresponding bottom-up approach. The molecular mechanisms of the desired functionalities can be established from Nuclear Magnetic Resonance (NMR) and molecular models and it is proposed that these models can be fed back into the biotechnology by using a quantitative structure-property approach. In this way it will be possible to tailor specific functionality within a given design space. This perspective will include two well-known commercial microbial EPS examples namely gellan and diutan and show how even a limited use of multiphase NMR and molecular modeling can increase the insight into their different properties, which are based on only minor structural differences.

Fluorescence spectroscopy in process analytical technology (PAT): simultaneous quantification of two active pharmaceutical ingredients in a tablet formulation.

Many pharmaceuticals include highly potent active pharmaceutical ingredients (API), which only require a small dosage to obtain the desired therapeutic effect. This leads to a challenge for quantification of the API using process analytical technology, since the standard nondestructive measurement technique, near-infrared spectroscopy, is not able to quantify below 1% (weight/weight (w/w)) API content. In formulations with more than one API, this challenge is further increased. The purpose of this study is to scrutinize the potential of fluorescence spectroscopy for the simultaneous quantification of two APIs: flupentixol (FLU) in low dosage (0.208-0.625% w/w free base) and melitracen (MEL) (4.17-12.5% w/w free base) in a tablet formulation. Despite internal quenching between the ingredients and the two APIs, this paper demonstrates that it is possible to establish calibrations using partial least squares (PLS) regression on unfolded fluorescence landscapes with a root mean square error of prediction and relative error of 0.038% (w/w) and 9.1%, for FLU and 0.344% (w/w) and 4.1% for MEL, respectively.

Combining fold recognition and exploratory data analysis for searching for glycosyltransferases in the genome of Mycobacterium tuberculosis.

Fold recognition was applied to the systematic analysis of the all sequences encoded by the genome of Mycoplasma tuberculosis H37Rv in order to identify new putative glycosyltransferases. The search was conducted against a library composed of all known crystal structures of glycosyltransferases and some related proteins. A clear relationship appeared between some sequences and some folds. It appears necessary to complete the fold recognition approach with a statistical approach in order to identify the relevant data above the background noise. Exploratory data analysis was carried out using several methods. Analytical methods confirmed the validity of the approach, while predictive methods, although very preliminary in the present case, allowed for identifying a number of sequences of interest that should be further investigated. This new approach of combining bioinformatics and chemometrics appears to be a powerful tool for analysis of newly sequenced genomes. Its application to glycobiology is of great interest.