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The objective of this study was to examine the impact of stage of lactation (early, mid and late) and proportion of pasture in the cows diet (high: GRS, medium: PMR and no: TMR) on the composition and quality of Cheddar cheese. Triplicate trials were carried out in each stage of lactation, and milk protein and fat contents were standardized for Cheddar cheese manufacture at pilot scale. As cheese milks were standardized for milk fat and protein contents, gross composition did not differ as a result of diet. Fatty acid profiles of GRS cheese were significantly different from TMR, while PMR profiles were less distinct and more similar to both GRS and TMR profiles, as illustrated by partial least squares discriminatory analysis. Fatty acids including CLA C18:2 cis-9, trans-11, C22:1 n-9 and C18:3 n-3 were most influential in this separation of profiles. Fatty acid profiling revealed that GRS derived cheese contained higher proportions of nutrients considered beneficial for human health including higher proportions of unsaturated fatty acids and omega-3 fatty acids. A biomarker model utilizing the proportions of 5 fatty acids was constructed and was effective at distinguishing between cheese of GRS, TMR and PMR feeding systems. Proportions of ρ-κ-casein, αs2-casein and αs1-casein in cheese also differed between diets while proportions of ρ-κ-casein, αs1-casein and ß-casein were lowest in late lactation cheese. The impact of diet was less influential compared with that of stage of lactation on the ripening characteristics of cheese. An index of primary proteolysis was highest in late lactation cheese. The peptides derived from the proteolysis of κ-casein and ß-casein and levels of secondary proteolysis, in particular, the proportions of 12 free amino acids were most influenced by stage of lactation. Overall this study demonstrated the effects of increasing pasture allowance and stage of lactation on the nutritional quality and ripening properties of Cheddar cheese.
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The high throughput in genome sequencing and metabolic model (MM) reconstruction has democratised bioinformatics approaches such as flux balance analysis. Fluxes' prediction accuracy greatly relates to the deepness of the MM curation for a specific organism starting from the cell composition. One component is the cell wall, which is a functional barrier (cell shape, exchanges) with the environment. The bacterial cell wall (BCW), including its thickness, structure, and composition, has been extensively studied in Escherichia coli but poorly described for other organisms. The peptidoglycan (PG) layer composing the BCW is usually thinner in Gram- bacteria than in Gram+ bacteria. In both bacteria groups, PG is a polymeric mesh-like structure of amino acids and sugars, including N-acetylglucosamine, N-acetylmuramic acid, and amino acids. In this study, we propose a high-throughput method to characterise and quantify PG in Gram-positive and Gram-negative bacteria using acidic hydrolysis and hydrophilic interaction liquid chromatography coupled with mass spectrometry (HILIC-MS). The method showed a relatively short time frame (11 min analytical run), low inter- and intraday variability (3.2% and 4%, respectively), and high sensitivity and selectivity (limits of quantification in the sub mg/L range). The method was successfully applied on two Gram-negative bacteria (Escherichia coli K12 MG1655, Bacteroides thetaiotaomicron DSM 2079) and one Gram-positive bacterium (Streptococcus salivarius ssp. thermophilus DSM20259). The PG concentration ranged from 1.6% w/w to 14% w/w of the dry cell weight. The results were in good correlation with previously published results. With further development, the PG concentration provided by this newly developed method could reinforce the curation of MM.
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In the present study, an oat drink, a plant-based alternative to dairy products, was developed by fermenting the oat base with different vegan starter cultures. The desired pH below 4.2 was achieved in 12 h, regardless of starter culture used. Metagenomic sequencing revealed that S. thermophilus was the dominating species, ranging from 38% to 99% of the total microbial consortia. At lower pH values, population of L. acidophilus, L. plantarum and L. paracasei continued to increase in fermented oat drinks. Lactic acid was produced between 1.6 and 2.8 g/L. The sensory panel showed that all fermented oat drinks had a sour odor and taste. The volatile compounds identified belonged to the ketone, alcohol, aldehyde, acids, and furan classes. The concentration of the most preferred volatile components, such as diacetyl and acetoin, increased during fermentation. However, sensory evaluation showed that all samples were associated with cereals and not dairy in terms of taste and odor. Rheological analysis showed the formation of weak gel-like structures in fermented oat drinks. Overall, fermentation improved flavor and texture of the product. This study provides a broad overview of the oat drink fermentation process from the perspectives of starter culture growth, microbial consortium dynamics, lactic acid bacteria metabolism, and sensory profile formation.
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This work presents the sample extraction methods for solid and liquid sample matrices for simultaneous quantification of oat (Avena sativa L.) and pea (Pisum sativum L.) saponins: avenacoside A, avenacoside B, 26-desglucoavenacoside A, and saponin B and 2,3-dihydro-2,5-dihydroxy-6-methyl-4H-pyran-4-one (DDMP) saponin, respectively. The targeted saponins were identified and quantified using a hydrophilic interaction liquid chromatography with mass spectrometric detection (HILIC-MS) method. The simple and high-throughput extraction procedure was developed for solid oat- and pea-based food samples. In addition, a very simple extraction procedure for liquid samples, without the need to use lyophilisation, was also implemented. Oat seed flour (U-13C-labelled) and soyasaponin Ba were used as internal standards for avenacoside A and saponin B, respectively. Other saponins were relatively quantified based on avenacoside A and saponin B standard responses. The developed method was tested and successfully validated using oat and pea flours, protein concentrates and isolates, as well as their mixtures, and plant-based drinks. With this method, the saponins from oat- and pea-based products were separated and quantified simultaneously within 6 min. The use of respective internal standards derived from U-13C-labelled oat and soyasaponin Ba ensured high accuracy and precision of the proposed method.
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Saccharides are the most common carbon source for Streptococcus thermophilus, which is a widely used bacterium in the production of fermented dairy products. The performance of the strain is influenced by the consumption of different saccharides during fermentation. Therefore, a precise measurement of the concentrations of saccharides in the fermentation media is essential. An 18-min long method with limits of quantitation in the range of 0.159-0.704 mg/L and with 13C labelled internal standards employing hydrophilic interaction chromatography coupled to mass spectrometric detection-(HILIC-LC-MS) allowed for simultaneous quantification of five saccharides: fructose, glucose, galactose, sucrose, and lactose in the fermentation samples. The method included a four-step sample preparation protocol, which could be easily applied to high-throughput analysis. The developed method was validated and applied to the fermentation samples produced by Streptococcus thermophilus.
Assuntos
Cromatografia Líquida/métodos , Fermentação/fisiologia , Espectrometria de Massas em Tandem/métodos , Dissacarídeos/química , Dissacarídeos/metabolismo , Frutose/metabolismo , Galactose/metabolismo , Glucose/metabolismo , Lactose/metabolismo , Monossacarídeos/química , Monossacarídeos/metabolismo , Streptococcus thermophilus/metabolismo , Sacarose/metabolismoRESUMO
Until now, cheese peptidomics approaches have been criticised for their lower throughput. Namely, analytical gradients that are most commonly used for mass spectrometric detection are usually over 60 or even 120 min. We developed a cheese peptide mapping method using nano ultra-high-performance chromatography data-independent acquisition high-resolution mass spectrometry (nanoUHPLC-DIA-HRMS) with a chromatographic gradient of 40 min. The 40 min gradient did not show any sign of compromise in milk protein coverage compared to 60 and 120 min methods, providing the next step towards achieving higher-throughput analysis. Top 150 most abundant peptides passing selection criteria across all samples were cross-referenced with work from other publications and a good correlation between the results was found. To achieve even faster sample turnaround enhanced DIA methods should be considered for future peptidomics applications.