Fermentation Analytical Technology (FAT): Monitoring industrial E. coli fermentations using absolute quantitative 1H NMR spectroscopy.

BACKGROUND: To perform fast, reproducible, and absolute quantitative measurements in an automated manner has become of paramount importance when monitoring industrial processes, including fermentations. Due to its numerous advantages - including its inherent quantitative nature - Proton Nuclear Magnetic Resonance (1H NMR) spectroscopy provides an ideal tool for the time-resolved monitoring of fermentations. However, analytical conditions, including non-automated sample preparation and long relaxation times (T1) of some metabolites, can significantly lengthen the experimental time and make implementation in an industrial set up unfeasible. RESULTS: We present a high throughput method based on Standard Operating Procedures (SOPs) and 1H NMR, which lays the foundation for what we call Fermentation Analytical Technology (FAT). Our method was developed for the accurate absolute quantification of metabolites produced during Escherichia coli industrial fermentations. The method includes: (1) a stopped flow system for non-invasive sample collection followed by sample quenching, (2) automatic robot-assisted sample preparation, (3) fast 1H NMR measurements, (4) metabolites quantification using multivariate curve resolution (MCR), and (5) metabolites absolute quantitation using a novel correction factor (k) to compensate for the short recycle delay (D1) employed in the 1H NMR measurements. The quantification performance was tested using two sample types: buffer solutions of chemical standards and real fermentation samples. Five metabolites - glucose, acetate, alanine, phenylalanine and betaine - were quantified. Absolute quantitation ranged between 0.64 and 3.40 mM in pure buffer, and 0.71-7.76 mM in real samples. SIGNIFICANCE: The proposed method is generic and can be straight forward implemented to other types of fermentations, such as lactic acid, ethanol and acetic acid fermentations. It provides a high throughput automated solution for monitoring fermentation processes and for quality control through absolute quantification of key metabolites in fermentation broth. It can be easily implemented in an at-line industrial setting, facilitating the optimization of the manufacturing process towards higher yields and more efficient and sustainable use of resources.

Towards on-line cheese monitoring: Exploration of semi-hard cheeses using NIR and 1H NMR spectroscopy.

This study aims to investigate the potential of using advanced spectroscopies for cheese quality monitoring. For this purpose, six semi-hard cheeses manufactured using lactic acid bacteria (LAB) and/or propionic acid bacteria (PAB) were explored using near-infrared spectroscopy (NIRS) and Proton Nuclear Magnetic Resonance (1H NMR) spectroscopy. The spectral data were analyzed using principal component analysis for extraction of possible discriminative patterns in quality parameters. The results show that the green analytical, but primarily bulk-sensitive, NIRS method was able to discriminate the cheese varieties primarily due to differences in the first overtone CH stretching region between 1650 and 1720 nm, in particular by the lactate methylene absorption at 1674 nm. A total of 25 metabolites were identified in the 1H NMR spectra of the cheese extracts, several of which were associated with the LAB and PAB metabolic pathways. PAB-associated metabolites include propionate, acetate, and glutamate, while LAB-associated metabolites include lactate and acetoin among others.

The legacy of terrestrial plant evolution on cell wall fine structure.

The evolution of land flora was an epochal event in the history of planet Earth. The success of plants, and especially flowering plants, in colonizing all but the most hostile environments required multiple mechanisms of adaptation. The mainly polysaccharide-based cell walls of flowering plants, which are indispensable for water transport and structural support, are one of the most important adaptations to life on land. Thus, development of vasculature is regarded as a seminal event in cell wall evolution, but the impact of further refinements and diversification of cell wall compositions and architectures on radiation of flowering plant families is less well understood. We approached this from a glyco-profiling perspective and, using carbohydrate microarrays and monoclonal antibodies, studied the cell walls of 287 plant species selected to represent important evolutionary dichotomies and adaptation to a variety of habitats. The results support the conclusion that radiation of flowering plant families was indeed accompanied by changes in cell wall fine structure and that these changes can obscure earlier evolutionary events. Convergent cell wall adaptations identified by our analyses do not appear to be associated with plants with similar lifestyles but that are taxonomically distantly related. We conclude that cell wall structure is linked to phylogeny more strongly than to habitat or lifestyle and propose that there are many approaches of adaptation to any given ecological niche.

New insight into pectic fractions of cell wall: Impact of extraction on pectin structure and in vitro gut fermentation.

Pectic polysaccharides modulate gut fermentation ability, which is determined by structural characteristics. In this work, apple pectins were extracted by HCl (HAEP), NaOH (AEP), cellulase (EAEP), and in parallel cell wall pectic fractions were sequentially extracted by water (WEP), chelator (CEP) and NaOH (NEP). The aim is to comprehensively compare the impact of extraction on pectin structure and gut fermentation behavior. Results showed that high content of galacturonic acid (90.65 mol%) and large molecular weight (675 kg/mol) were detected in the HAEP. Molecular morphology of the HAEP presented high linearity, while AEP, EAEP and WEP exhibited compact filamentous structures with highly branched patterns. The AEP was characterized by high yield (33.1 g/100 g d.b.), moderate molecular weight (304 kg/mol) and large extent of rhamnogalacturonan-I region (24.88 %) with low degree of branching (1.77). After in vitro simulated gut fermentation for 24 h, total content of short-chain fatty acid (SCFA) generated with the AEP supplement increased to 36.8 mmol/L, followed by EAEP, HAEP and WEP (25.2, 24.2 and 20.3 mmol/L, respectively). Meanwhile, WEP simultaneously produced the highest ammonia content (22.4 mmol/L). This investigation suggests that the fermentation of AEP produces more beneficial SCFA and less ammonia, thus indicating a better gut fermentation property.

On-Line Monitoring of Enzymatic Degumming of Soybean Oil Using Near-Infrared Spectroscopy.

Degumming is an oil refinement process in which the naturally occurring phospholipids in crude vegetable oils are removed. Enzymatic degumming results in higher oil yield and more cost-efficient processing compared to traditional degumming processes using only water or acid. Phospholipase C hydrolyses phospholipids into diglycerides and phosphate groups during degumming. The diglyceride content can therefore be considered a good indicator of the state of the enzymatic reaction. This study investigates the use of near-infrared (NIR) spectroscopy and chemometrics to monitor the degumming process by quantifying diglycerides in soybean oil in both off-line and on-line settings. Fifteen enzymatic degumming lab scale batches originating from a definitive screening design (with varying water, acid, and enzyme dosages) were investigated with the aim to develop a NIR spectroscopy prediction method. By applying tailored preprocessing and variable selection methods, the diglyceride content can be predicted with a root mean square error of prediction of 0.06% (w/w) for the off-line set-up and 0.07% (w/w) for the on-line set-up. The results show that the diglyceride content is a good indicator of the enzyme performance and that NIR spectroscopy is a suitable analytical technique for robust real-time diglyceride quantification.

Predicting weight loss success on a new Nordic diet: an untargeted multi-platform metabolomics and machine learning approach.

Background and aim: Results from randomized controlled trials indicate that no single diet performs better than other for all people living with obesity. Regardless of the diet plan, there is always large inter-individual variability in weight changes, with some individuals losing weight and some not losing or even gaining weight. This raises the possibility that, for different individuals, the optimal diet for successful weight loss may differ. The current study utilized machine learning to build a predictive model for successful weight loss in subjects with overweight or obesity on a New Nordic Diet (NND). Methods: Ninety-one subjects consumed an NND ad libitum for 26 weeks. Based on their weight loss, individuals were classified as responders (weight loss ≥5%, n = 46) or non-responders (weight loss <2%, n = 24). We used clinical baseline data combined with baseline urine and plasma untargeted metabolomics data from two different analytical platforms, resulting in a data set including 2,766 features, and employed symbolic regression (QLattice) to develop a predictive model for weight loss success. Results: There were no differences in clinical parameters at baseline between responders and non-responders, except age (47 ± 13 vs. 39 ± 11 years, respectively, p = 0.009). The final predictive model for weight loss contained adipic acid and argininic acid from urine (both metabolites were found at lower levels in responders) and generalized from the training (AUC 0.88) to the test set (AUC 0.81). Responders were also able to maintain a weight loss of 4.3% in a 12 month follow-up period. Conclusion: We identified a model containing two metabolites that were able to predict the likelihood of achieving a clinically significant weight loss on an ad libitum NND. This work demonstrates that models based on an untargeted multi-platform metabolomics approach can be used to optimize precision dietary treatment for obesity.

Human blood plasma biomarkers of diet and weight loss among centrally obese subjects in a New Nordic Diet intervention.

Scope: The New Nordic Diet (NND) has been shown to promote weight loss and lower blood pressure amongst obese people. This study investigates blood plasma metabolite and lipoprotein biomarkers differentiating subjects who followed Average Danish Diet (ADD) or NND. The study also evaluates how the individual response to the diet is reflected in the metabolic differences between NND subjects who lost or maintained their pre-intervention weight. Methods: Centrally obese Danes (BMI >25) followed NND (90 subjects) or ADD (56 subjects) for 6 months. Fasting blood plasma samples, collected at three time-points during the intervention, were screened for metabolites and lipoproteins (LPs) using proton nuclear magnetic resonance spectroscopy. In total, 154 metabolites and 65 lipoproteins were analysed. Results: The NND showed a relatively small but significant effect on the plasma metabolome and lipoprotein profiles, with explained variations ranging from 0.6% for lipoproteins to 4.8% for metabolites. A total of 38 metabolites and 11 lipoproteins were found to be affected by the NND. The primary biomarkers differentiating the two diets were found to be HDL-1 cholesterol, apolipoprotein A1, phospholipids, and ketone bodies (3-hydroxybutyric acid, acetone, and acetoacetic acid). The increased levels of ketone bodies detected in the NND group inversely associated with the decrease in diastolic blood pressure of the NND subjects. The study also showed that body weight loss among the NND subjects was weakly associated with plasma levels of citrate. Conclusion: The main plasma metabolites associated with NND were acetate, methanol and 3-hydroxybutyrate. The metabolic changes associated with the NND-driven weight loss are mostly pronounced in energy and lipid metabolism.

Effect of 1-year daily protein supplementation and physical exercise on muscle protein synthesis rate and muscle metabolome in healthy older Danes: a randomized controlled trial.

BACKGROUND: The skeletal muscle mass decreases with age and the responsiveness of aging muscles' protein synthesis rate (MPS) to protein intake seems to deteriorate. OBJECTIVE: This study investigated the impact of 12 months of protein supplementation with or without physical exercise training on the basal and postprandial MPS and the skeletal muscle metabolome of healthy older Danes (> 65 years, 29 females/37 males). METHODS: Subjects were randomized to follow one of five intervention groups: (1) carbohydrate, (2) collagen protein, (3) whey protein, (4) home-based light resistance training with whey protein, and (5) center-based heavy-load resistance training with whey protein. Before and after the intervention, a tracer infusion trial was conducted to measure basal and postprandial MPS in response to intake of a cocktail consisting of 20 g whey hydrolysate + 10 g glucose. In addition, the skeletal muscle metabolome was measured using gas chromatography-mass spectrometry (GC-MS) at basal state and 4 h after the intake of the cocktail. RESULTS: One year of daily protein or carbohydrate supplementation did not alter the basal and protein-stimulated postprandial muscle protein synthesis rate or the muscle metabolome of healthy older Danes. Basal MPS (%/h) at baseline for all subjects were 0.0034 ± 0,011 (mean ± SD). In contrast to previous studies, no difference was observed in basal MPS between males and females (p = 0.75). With the developed untargeted GC-MS methodology, it was possible to detect and tentatively annotate > 70 metabolites from the human skeletal muscle samples. CONCLUSION: One year of protein supplementation in comparison to an isocaloric-control supplement seems to affect neither the MPS at basal or postprandial state nor the skeletal muscle metabolome. CLINICAL TRIAL REGISTRY: Number: NCT02115698, clinicaltrials.gov/ct2/show/NCT02115698.

Associations between sheep meat intake frequency and blood plasma levels of metabolites and lipoproteins in healthy Uzbek adults.

INTRODUCTION: Uzbekistan is one of the countries with the highest number of diet-related chronic diseases, which is believed to be associated with high animal fat intake. Sheep meat is high in fats (~ 5% in muscle), including saturated and monounsaturated fatty acids, and it contains nearly twice the higher amounts of n-3 polyunsaturated fatty acids and conjugated linoleic acids compared to beef. Nevertheless, sheep meat is considered health promoting by the locals in Uzbekistan and it accounts for around 1/3 of red meat intake in the country. OBJECTIVES: The aim of this study was to apply a metabolomics approach to investigate if sheep meat intake frequency (SMIF) is associated with alterations in fasting blood plasma metabolites and lipoproteins in healthy Uzbek adults. METHODS: The study included 263 subjects, 149 females and 114 males. For each subject a food intake questionnaire, including SMIF, was recorded and fasting blood plasma samples were collected for metabolomics. Blood plasma metabolites and lipoprotein concentrations were determined using 1H NMR spectroscopy. RESULTS AND CONCLUSION: The results showed that SMIF was confounded by nationality, sex, body mass index (BMI), age, intake frequency of total meat and fish in ascending order (p < 0.01). Multivariate and univariate data analyses showed differences in the levels of plasma metabolites and lipoproteins with respect to SMIF. The effect of SMIF after statistical adjustment by nationality, sex, BMI, age, intake frequency of total meat and fish decreased but remained significant. Pyruvic acid, phenylalanine, ornithine, and acetic acid remained significantly lower in the high SMIF group, whereas choline, asparagine, and dimethylglycine showed an increasing trend. Levels of cholesterol, apolipoprotein A1, as well as low- and high-density lipoprotein subfractions all displayed a decreasing trend with increased SMIF although the difference were not significant after FDR correction.

Dietary Fish Meal Level and a Package of Choline, ß-Glucan, and Nucleotides Modulate Gut Function, Microbiota, and Health in Atlantic Salmon (Salmo salar, L.).

Steatosis and inflammation have been common gut symptoms in Atlantic salmon fed plant rich diets. Choline has recently been identified as essential for salmon in seawater, and ß-glucan and nucleotides are frequently used to prevent inflammation. The study is aimed at documenting whether increased fishmeal (FM) levels (8 levels from 0 to 40%) and supplementation (Suppl) with a mixture of choline (3.0 g/kg), ß-glucan (0.5 g/kg), and nucleotides (0.5 g/kg) might reduce the symptoms. Salmon (186 g) were fed for 62 days in 16 saltwater tanks before samples were taken from 12 fish per tank for observation of biochemical, molecular, metabolome, and microbiome indicators of function and health. Steatosis but no inflammation was observed. Lipid digestibility increased and steatosis decreased with increasing FM levels and supplementation, seemingly related to choline level. Blood metabolites confirmed this picture. Genes in intestinal tissue affected by FM levels are mainly involved in metabolic and structural functions. Only a few are immune genes. The supplement reduced these FM effects. In gut digesta, increasing FM levels increased microbial richness and diversity, and changed the composition, but only for unsupplemented diets. An average choline requirement of 3.5 g/kg was indicated for Atlantic salmon at the present life stage and under the present condition.

Alterations of NMR-Based Lipoprotein Profile Distinguish Unstable Angina Patients with Different Severity of Coronary Lesions.

Non-invasive detection of unstable angina (UA) patients with different severity of coronary lesions remains challenging. This study aimed to identify plasma lipoproteins (LPs) that can be used as potential biomarkers for assessing the severity of coronary lesions, determined by the Gensini score (GS), in UA patients. We collected blood plasma from 67 inpatients with angiographically normal coronary arteries (NCA) and 230 UA patients, 155 of them with lowGS (GS ≤ 25.4) and 75 with highGS (GS > 25.4), and analyzed it using proton nuclear magnetic resonance spectroscopy to quantify 112 lipoprotein variables. In a logistic regression model adjusted for four well-known risk factors (age, sex, body mass index and use of lipid-lowering drugs), we tested the association between each lipoprotein and the risk of UA. Combined with the result of LASSO and PLS-DA models, ten of them were identified as important LPs. The discrimination with the addition of selected LPs was evaluated. Compared with the basic logistic model that includes four risk factors, the addition of these ten LPs concentrations did not significantly improve UA versus NCA discrimination. However, thirty-two selected LPs showed notable discrimination power in logistic regression modeling distinguishing highGS UA patients from NCA with a 14.9% increase of the area under the receiver operating characteristics curve. Among these LPs, plasma from highGS patients was enriched with LDL and VLDL subfractions, but lacked HDL subfractions. In summary, we conclude that blood plasma lipoproteins can be used as biomarkers to distinguish UA patients with severe coronary lesions from NCA patients.

Effects of functional ingredients on gut inflammation in Atlantic salmon (Salmo salar L).

Functional feed ingredients are frequently used in feeds for Atlantic salmon, often claimed to improve immune functions in the intestine and reduce severity of gut inflammation. However, documentation of such effects is, in most cases, only indicative. In the present study effects of two packages of functional feed ingredients commonly used in salmon production, were evaluated employing two inflammation models. One model employed soybean meal (SBM) as inducer of a severe inflammation, the other a mixture of corn gluten and pea meal (CoPea) inducing mild inflammation. The first model was used to evaluate effects of two packages of functional ingredients: P1 containing butyrate and arginine, and P2 containing ß-glucan, butyrate, and nucleotides. In the second model only the P2 package was tested. A high marine diet was included in the study as a control (Contr). The six diets were fed to salmon (average weight of 177g) in saltwater tanks (57 fish per tank), in triplicate, for 69 days (754 ddg). Feed intake was recorded. The growth rate of the fish was high, highest for the Contr (TGC: 3.9), lowest for SBM fed fish (TGC: 3.4). Fish fed the SBM diet showed severe symptoms of inflammation in the distal intestine as indicated by histological, biochemical, molecular, and physiological biomarkers. The number of differently expressed genes (DEG) between the SBM and Contr fed fish was 849 and comprised genes indicating alteration in immune functions, cellular and oxidative stress, and nutrient digestion, and transport functions. Neither P1 nor P2 altered the histological and functional symptoms of inflammation in the SBM fed fish importantly. Inclusion of P1 altered expression of 81 genes, inclusion of P2 altered 121 genes. Fish fed the CoPea diet showed minor signs of inflammation. Supplementation with P2 did not change these signs. Regarding composition of the microbiota in digesta from the distal intestine, clear differences regarding beta-diversity and taxonomy between Contr, SBM, and CoPea fed fish were observed. In the mucosa the microbiota differences were less clear. The two packages of functional ingredients altered microbiota composition of fish fed the SBM and the CoPea diet towards that of fish fed the Contr diet.

Screening of non-protein nitrogen compounds in lactose refining streams from industrial whey permeate processing.

The NPN compounds from dairy processing side-streams are a promising source for new products. In this study, the NPN profile of lactose production samples was screened using GC-MS and 1H NMR spectroscopy. These analytical platforms allowed the identification of 35 NPN compounds including, amino acids and derivatives, amino alcohols, organic acids, and other classes. Quantification of the NPN compounds revealed their attenuation by unit operations during a trial lactose production. Urea, ammonia, glycerophosphocholine, creatine, creatinine, orotic acid and choline were the most dominant compounds. Mother liquor concentrate had the highest concentration of NPN, whereas lactose powder had substantial relative amounts of N-acetylglucosamine, phosphocholine and orotic acid. The NPN compounds added up to 57-99% of the total nitrogen, depending on the sample type. The highest nitrogen recovery was found for the reverse osmosis retentate, mother liquid concentrate, wash water and reverse osmosis permeate, whereas the lowest was found for lactose powder.

1-2 Drinks Per Day Affect Lipoprotein Composition after 3 Weeks-Results from a Cross-Over Pilot Intervention Trial in Healthy Adults Using Nuclear Magnetic Resonance-Measured Lipoproteins and Apolipoproteins.

Alcohol consumption ranging from 1−2 drinks/day associates with a lower risk of coronary heart disease in some studies. The underlying mechanisms are unclear. The Metabolic Imprints of Alcoholic Beverages (MetAl) trial aimed to explore the short-term effects of moderate alcohol consumption on cardiovascular biomarkers. A 2 × 3-week cross-over single-blinded intervention trial investigating the effect of 1−2 drinks/day (~12−24 g) compared with abstention on 1H Nuclear Magnetic Resonance-measured main lipoproteins and subfractions was performed in 26 healthy adults. Volunteers were classified as occasional or habitual drinkers based on their habitual alcohol intakes (<2 or ≥2 drinks/week). Compared with abstention, 1−2 drinks/day increased HDL2a-C (p = 0.004), HDL3-C (p = 0.008), and HDL non-significantly (p = 0.19). Total apoA1 and apoA1 in HDL and its subfractions increased (p < 0.05). Novel findings were a decreased apoB/apoA1 ratio (p = 0.02), and increased HDL2a phospholipid content (p = 0.04). In women alone, the results were similar but attenuated, and LDL-P decreased. Thus, changes in apoA1- and HDL-related biomarkers occur within weeks in moderate drinkers. Compared with abstention, 1−2 drinks/day increased total apoA1 more strongly than HDL-C and increased the cholesterol, apoA1, and phospholipid content of several HDL subfractions. Whether this provides a cardiovascular benefit requires further study. Clinicaltrials.gov: NCT03384147.

Effects of Water Stress, Defoliation and Crop Thinning on Vitis vinifera L. cv. Solaris Must and Wine Part II: 1H NMR Metabolomics.

Proton nuclear magnetic resonance (1H NMR) metabolomics was employed to investigate the impact of water deficit, defoliation, and crop thinning on the chemical composition of must and wines from the cool-climate white grape variety Solaris. The obtained results show that viticultural practices (defoliation and crop thinning) affected the amino acid and sugar content of Solaris must and thereby the quality of the final wine­mainly in terms of compounds normally related to fruity aroma (i.e., isopentanol), non-sugar sweetness (i.e., proline and glycerol), and alcohol content. The content of tyrosol, a natural phenolic antioxidant with a high bioavailability, was increased in the final wine by a combination of defoliation and crop thinning. The results of the metabolomics analysis performed on the must and wine samples from the water stress experiment showed that short-term water deficit significantly affected the concentration of several flavor-related compounds, including glutamate, butyrate and propanol, of the organic acids lactate and fumarate, and of the phenolic compounds caffeic acid and p-coumaric acid. ANOVA simultaneous component analysis showed that the effect of water deficit accounted for 11% (p < 0.001) and 8% (p < 0.001) of the variability in the metabolite concentrations in must and wines, respectively, while viticultural practices accounted for 38% (p < 0.001) and 30% (p < 0.001) of the metabolite variability in must and wines, respectively.

Effects of Water Stress, Defoliation and Crop Thinning on Vitis vinifera L. cv. Solaris: Part I: Plant Responses, Fruit Development and Fruit Quality.

Viticultural practices and irrigation have a major impact on fruit development and yield, and ultimately on must quality. The effects of water deficit (WD), defoliation (Def), and crop-thinning (CT) on Solaris plants and fruit development, as well as on the chemical composition of grape juice were investigated. WD was induced at three periods during fruit development (pre-veraison, veraison, and ripening) in pot-grown plants, while Def and CT were carried out on field-grown plants. Environmental and vegetative parameters were monitored during the experiments. The bulk chemical composition of the fruits was determined in juice by Fourier Transform-Infrared (FT-IR) spectroscopy throughout fruit ripening and at final harvest. The results showed that WD reduced soil water content and leaf water status. CT significantly reduced yield per vine, but increased cluster size. Mid to late WD reduced soluble solids by 1%. CT increased sugar content in juice, while Def decreased sugar accumulation. Total acids were higher in the juice from the field vines. Yet, CT lowered malic and tartaric acids. Def increased tartaric acid. Ammonia and alpha amino nitrogen were higher in the juice from pot-grown vines, while pH was lowered by Def and raised by CT. It is concluded that Solaris has a remarkable ability to tolerate and recover from WD. CT and Def significantly affected the bulk chemical composition of grapes in terms of total acidity and sugar accumulation, with CT grapes having the highest sugar content and the lowest total acidity and Def the opposite.

Non-volatile molecular composition and discrimination of single grape white of chardonnay, riesling, sauvignon blanc and silvaner using untargeted GC-MS analysis.

This study developed and applied a GC-MS method aiming at molecular fingerprinting of 120 commercial single grape white wines (Chardonnay, Riesling, Sauvignon Blanc and Silvaner) for possible authentication according to grape variety. The method allowed detection of 372 peaks and tentative identification of 146 metabolites including alcohols, organic acids, esters, amino acids and sugars. The grape variety effect explained 8.3% of the total metabolite variation. Univariate tests showed two-thirds of the metabolites being different between grape varieties. Partial least squares-discriminant analysis based classification models were developed for each grape variety and a panel of classifiers (42 metabolites) was established. All the classification models for grape variety showed a high certainty (>91%) for an independent test set. Riesling contained the highest relative concentrations of sugars and organic acids, while concentrations of hydroxytyrosol and gallic acid, common antioxidants in wine, decreased in the order of Chardonnay > Riesling > Sauvignon Blanc > Silvaner.

Human Blood Lipoprotein Predictions from 1H NMR Spectra: Protocol, Model Performances, and Cage of Covariance.

Lipoprotein subfractions are biomarkers for the early diagnosis of cardiovascular diseases. The reference method, ultracentrifugation, for measuring lipoproteins is time-consuming, and there is a need to develop a rapid method for cohort screenings. This study presents partial least-squares regression models developed using 1H nuclear magnetic resonance (NMR) spectra and concentrations of lipoproteins as measured by ultracentrifugation on 316 healthy Danes. This study explores, for the first time, different regions of the 1H NMR spectrum representing signals of molecules in lipoprotein particles and different lipid species to develop parsimonious, reliable, and optimal prediction models. A total of 65 lipoprotein main and subfractions were predictable with high accuracy, Q2 of >0.6, using an optimal spectral region (1.4-0.6 ppm) containing methylene and methyl signals from lipids. The models were subsequently tested on an independent cohort of 290 healthy Swedes with predicted and reference values matching by up to 85-95%. In addition, an open software tool was developed to predict lipoproteins concentrations in human blood from standardized 1H NMR spectral recordings.

Human Fecal Metabolome Reflects Differences in Body Mass Index, Physical Fitness, and Blood Lipoproteins in Healthy Older Adults.

This study investigated how body mass index (BMI), physical fitness, and blood plasma lipoprotein levels are related to the fecal metabolome in older adults. The fecal metabolome data were acquired using proton nuclear magnetic resonance spectroscopy and gas chromatography-mass spectrometry on 163 healthy older adults (65-80 years old, 80 females and 83 males). Overweight and obese subjects (BMI ≥ 27) showed higher levels of fecal amino acids (AAs) (valine, alanine, and phenylalanine) compared to normal-weight subjects (BMI ≤ 23.5). Adults classified in the high-fitness group displayed slightly lower concentrations of fecal short-chain fatty acids, propionic acid, and AAs (methionine, leucine, glutamic acid, and threonine) compared to the low-fitness group. Subjects with lower levels of cholesterol in low-density lipoprotein particles (LDLchol, ≤2.6 mmol/L) displayed higher fecal levels of valine, glutamic acid, phenylalanine, and lactic acid, while subjects with a higher level of cholesterol in high-density lipoprotein particles (HDLchol, ≥2.1 mmol/L) showed lower fecal concentration of isovaleric acid. The results from this study suggest that the human fecal metabolome, which primarily represents undigested food waste and metabolites produced by the gut microbiome, carries important information about human health and should be closely integrated to other omics data for a better understanding of the role of the gut microbiome and diet on human health and metabolism.

On-Line Real-Time Monitoring of a Rapid Enzymatic Oil Degumming Process: A Feasibility Study Using Free-Run Near-Infrared Spectroscopy.

Enzymatic degumming is a well established process in vegetable oil refinement, resulting in higher oil yield and a more stable downstream processing compared to traditional degumming methods using acid and water. During the reaction, phospholipids in the oil are hydrolyzed to free fatty acids and lyso-phospholipids. The process is typically monitored by off-line laboratory measurements of the free fatty acid content in the oil, and there is a demand for an automated on-line monitoring strategy to increase both yield and understanding of the process dynamics. This paper investigates the option of using Near-Infrared spectroscopy (NIRS) to monitor the enzymatic degumming reaction. A new method for balancing spectral noise and keeping the chemical information in the spectra obtained from a rapid changing chemical process is suggested. The effect of a varying measurement averaging window width (0 to 300 s), preprocessing method and variable selection algorithm is evaluated, aiming to obtain the most accurate and robust calibration model for prediction of the free fatty acid content (% (w/w)). The optimal Partial Least Squares (PLS) model includes eight wavelength variables, as found by rPLS (recursive PLS) calibration, and yields an RMSECV (Root Mean Square Error of Cross Validation) of 0.05% (w/w) free fatty acid using five latent variables.