Improved LC-MS identification of short homologous peptides using sequence-specific retention time predictors.

Peptides are an important group of compounds contributing to the desired, as well as the undesired taste of a food product. Their taste impressions can include aspects of sweetness, bitterness, savoury, umami and many other impressions depending on the amino acids present as well as their sequence. Identification of short peptides in foods is challenging. We developed a method to assign identities to short peptides including homologous structures, i.e. peptides containing the same amino acids with a different sequence order, by accurate prediction of the retention times during reversed phase separation. To train the method, a large set of well-defined short peptides with systematic variations in the amino acid sequence was prepared by a novel synthesis strategy called 'swapped-sequence synthesis'. Additionally, several proteins were enzymatically digested to yield short peptides. Experimental retention times were determined after reversed phase separation and peptide MS2 data was acquired using a high-resolution mass spectrometer operated in data-dependent acquisition mode (DDA). A support vector regression model was trained using a combination of existing sequence-independent peptide descriptors and a newly derived set of selected amino acid index derived sequence-specific peptide (ASP) descriptors. The model was trained and validated using the experimental retention times of the 713 small food-relevant peptides prepared. Whilst selecting the most useful ASP descriptors for our model, special attention was given to predict the retention time differences between homologous peptide structures. Inclusion of ASP descriptors greatly improved the ability to accurately predict retention times, including retention time differences between 157 homologous peptide pairs. The final prediction model had a goodness-of-fit (Q2) of 0.94; moreover for 93% of the short peptides, the elution order was correctly predicted.

Identification of plant polysaccharides by MALDI-TOF MS fingerprinting after periodate oxidation and thermal hydrolysis.

An autoclave treatment at 121 °C on periodate-oxidized plant polysaccharides and mixes thereof was investigated for the release of oligosaccharides to obtain a generic polysaccharide depolymerization method for polysaccharides fingerprinting. Matrix-Assisted Laser Desorption Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) analysis of the oligosaccharides released showed that each polysaccharide had a unique oligosaccharides profile, even the same type of polysaccharide derived from different sources and/or having different fine structures (e.g. class of (arabino)xylans, galactomannans, glucans, or pectic materials). Various polysaccharide classes present in a polysaccharide mix could be identified based on significantly different (p < 0.05) marker m/z values present in the mass spectrum. Principal component analysis and hierarchical cluster analysis of the obtained MALDI-TOF MS data highlighted the structural heterogeneity of the polysaccharides studied, and clustered polysaccharide samples with resembling oligosaccharide profiles. Our approach represents a step further towards a generic and accessible identification of plant polysaccharides individually or in a mixture.

Impact of Xylanase and Glucanase on Oligosaccharide Formation, Carbohydrate Fermentation Patterns, and Nutrient Utilization in the Gastrointestinal Tract of Broilers.

This study aimed at determining how the degradation of cereal non-starch polysaccharides (NSP) by dietary enzymes during feed digestion can influence nutrient digestibility and NSP fermentability in broilers. Ninety-six one-day-old male broilers were assigned to 4 different treatments: control and enzyme-supplemented wheat-based (WC, WE) or maize-based (MC, ME) treatments. Enzyme supplementation with endo-xylanase and endo-glucanase occurred from day 20 onwards. On day 28, digesta samples were collected. Nutrient digestibility, NSP recovery, oligosaccharide profile, and short-chain fatty acids (SCFA) content were determined. Enzyme supplementation in WE resulted in a higher starch (3%; p = 0.004) and protein (5%; p = 0.002) digestion in the ileum compared to WC. Xylanase activity in WE led to in situ formations of arabinoxylan-oligosaccharides consisting of 5 to 26 pentose units in the ileum. This coincided with decreased arabinose (p = 0.059) and xylose (p = 0.036) amounts in the ceca and higher acetate (p = 0.014) and butyrate (p = 0.044) formation in WE compared to WC. Conversely, complete total tract recovery of arabinoxylan in MC and ME suggested poor maize NSP fermentability. Overall, enzyme action improved nutrient digestibility and arabinoxylan fermentability in the wheat-based diet. The lower response of the maize-based diet to enzyme treatment may be related to the recalcitrance of maize arabinoxylan as well as to the high nutritive value of maize.

LC-MS based plant metabolic profiles of thirteen grassland species grown in diverse neighbourhoods.

In plants, secondary metabolite profiles provide a unique opportunity to explore seasonal variation and responses to the environment. These include both abiotic and biotic factors. In field experiments, such stress factors occur in combination. This variation alters the plant metabolic profiles in yet uninvestigated ways. This data set contains trait and mass spectrometry data of thirteen grassland species collected at four time points in the growing season in 2017. We collected above-ground vegetative material of seven grass and six herb species that were grown in plant communities with different levels of diversity in the Jena Experiment. For each sample, we recorded visible traits and acquired shoot metabolic profiles on a UPLC-ESI-Qq-TOF-MS. We performed the raw data pre-processing in Galaxy-W4M and prepared the data for statistical analysis in R by applying missing data imputation, batch correction, and validity checks on the features. This comprehensive data set provides the opportunity to investigate environmental dynamics across diverse neighbourhoods that are reflected in the metabolomic profile.

Revealing the main factors and two-way interactions contributing to food discolouration caused by iron-catechol complexation.

Fortification of food with iron is considered to be an effective approach to counter the global health problem caused by iron deficiency. However, reactivity of iron with the catechol moiety of food phenolics leads to discolouration and impairs bioavailability. In this study, we investigated the interplay between intrinsic and extrinsic factors on food discolouration caused by iron-catechol complexation. To this end, a three-level fractional factorial design was implemented. Absorbance spectra were analysed using statistical methods, including PCA, HCA, and ANOVA. Furthermore, a direct link between absorbance spectra and stoichiometry of the iron-catechol complexes was confirmed by ESI-Q-TOF-MS. All statistical methods confirm that the main effects affecting discolouration were type of iron salt, pH, and temperature. Additionally, several two-way interactions, such as type of iron salt × pH, pH × temperature, and type of iron salt × concentration significantly affected iron-catechol complexation. Our findings provide insight into iron-phenolic complexation-mediated discolouration, and facilitate the design of iron-fortified foods.

Reciprocal cybrids reveal how organellar genomes affect plant phenotypes.

Assessment of the impact of variation in chloroplast and mitochondrial DNA (collectively termed the plasmotype) on plant phenotypes is challenging due to the difficulty in separating their effect from nuclear-derived variation (the nucleotype). Haploid-inducer lines can be used as efficient plasmotype donors to generate new plasmotype-nucleotype combinations (cybrids)1. We generated a panel comprising all possible cybrids of seven Arabidopsis thaliana accessions and extensively phenotyped these lines for 1,859 phenotypes under both stable and fluctuating conditions. We show that natural variation in the plasmotype results in both additive and epistatic effects across all phenotypic categories. Plasmotypes that induce more additive phenotypic changes also cause more epistatic effects, suggesting a possible common basis for both additive and epistatic effects. On average, epistatic interactions explained twice as much of the variance in phenotypes as additive plasmotype effects. The impact of plasmotypic variation was also more pronounced under fluctuating and stressful environmental conditions. Thus, the phenotypic impact of variation in plasmotypes is the outcome of multi-level nucleotype-plasmotype-environment interactions and, as such, the plasmotype is likely to serve as a reservoir of variation that is predominantly exposed under certain conditions. The production of cybrids using haploid inducers is a rapid and precise method for assessment of the phenotypic effects of natural variation in organellar genomes. It will facilitate efficient screening of unique nucleotype-plasmotype combinations to both improve our understanding of natural variation in these combinations and identify favourable combinations to enhance plant performance.

Biomarkers for grain yield stability in rice under drought stress.

Crop yield stability requires an attenuation of the reduction of yield losses caused by environmental stresses such as drought. Using a combination of metabolomics and high-throughput colorimetric assays, we analysed central metabolism and oxidative stress status in the flag leaf of 292 indica rice (Oryza sativa) accessions. Plants were grown in the field and were, at the reproductive stage, exposed to either well-watered or drought conditions to identify the metabolic processes associated with drought-induced grain yield loss. Photorespiration, protein degradation, and nitrogen recycling were the main processes involved in the drought-induced leaf metabolic reprogramming. Molecular markers of drought tolerance and sensitivity in terms of grain yield were identified using a multivariate model based on the values of the metabolites and enzyme activities across the population. The model highlights the central role of the ascorbate-glutathione cycle, particularly dehydroascorbate reductase, in minimizing drought-induced grain yield loss. In contrast, malondialdehyde was an accurate biomarker for grain yield loss, suggesting that drought-induced lipid peroxidation is the major constraint under these conditions. These findings highlight new breeding targets for improved rice grain yield stability under drought.

Application of Volatile Organic Compound Analysis in a Nutritional Intervention Study: Differential Responses during Five Hours Following Consumption of a High- and a Low-Fat Dairy Drink.

SCOPE: Exhaled volatile organic compounds (VOCs) are a possible relevant target for noninvasive assessment of metabolic responses. Using a breathomics approach, it is aimed to explore whether lipid intake influences VOC profiles in exhaled air, and to obtain insight in intra- and interindividual variations. METHODS AND RESULTS: Three human interventions are performed. In the first, 12 males consume a high-fat drink on three study days. In the second, 12 males receive a high- and a low-fat drink on 6 days. In the third, three volunteers consume the high-fat drink again for tentative compound identification. Participants are asked to exhale, for 5 h postprandial with 15-20 min intervals, into a proton-transfer-reaction mass spectrometer, and VOCs in exhaled air are measured. Consumption of a drink alters the VOC profile, with considerable interindividual variation and quantitative intraindividual differences between days. Consumption of two different drinks results in a distinct VOC profile, caused by several specific m/z values. Most of these compounds are identified as being related to ketone body formation and lipid oxidation, showing an increase in high- versus low-fat drink. CONCLUSION: Exhaled VOCs have the potential to assess differences in metabolic responses induced by nutrition, especially when day-to-day variation can be minimized.

Variability of Serum Proteins in Chinese and Dutch Human Milk during Lactation.

To better understand the variability of the type and level of serum proteins in human milk, the milk serum proteome of Chinese mothers during lactation was investigated using proteomic techniques and compared to the milk serum proteome of Dutch mothers. This showed that total milk serum protein concentrations in Chinese human milk decreased over a 20-week lactation period, although with variation between mothers in the rate of decrease. Variation was also found in the composition of serum proteins in both colostrum and mature milk, although immune-active proteins, enzymes, and transport proteins were the most abundant for all mothers. These three protein groups account for many of the 15 most abundant proteins, with these 15 proteins covering more than 95% of the total protein concentrations, in both the Chinese and Dutch milk serum proteome. The Dutch and Chinese milk serum proteome were also compared based on 166 common milk serum proteins, which showed that 22% of the 166 serum proteins differed in level. These differences were observed mainly in colostrum and concern several highly abundant proteins. This study also showed that protease inhibitors, which are highly correlated to immune-active proteins, are present in variable amounts in human milk and could be relevant during digestion.

Transcriptome Analysis of CHO Cell Size Increase During a Fed-Batch Process.

In a Chinese Hamster Ovary (CHO) cell fed-batch process, arrest of cell proliferation and an almost threefold increase in cell size occurred, which is associated with an increase in cell-specific productivity. In this study, transcriptome analysis is performed to identify the molecular mechanisms associated with this. Cell cycle analysis reveals that the cells are arrested mainly in the G0 /G1 phase. The cell cycle arrest is associated with significant up-regulation of cyclin-dependent kinases inhibitors (CDKNs) and down-regulation of cyclin-dependent kinases (CDKs) and cyclins. During the cell size increase phase, the gene expression of the upstream pathways of mechanistic target of rapamycin (mTOR), which is related to the extracellular growth factor, cytokine, and amino acid conditions, shows a strongly synchronized pattern to promote the mTOR activity. The downstream genes of mTOR also show a synchronized pattern to stimulate protein translation and lipid synthesis. The results demonstrate that cell cycle inhibition and stimulated mTOR activity at the transcriptome level are related to CHO cell size increase. The cell size increase is related to the extracellular nutrient conditions through a number of cascade pathways, indicating that by rational design of media and feeds, CHO cell size can be manipulated during culture processes, which may further improve cell growth and specific productivity.

QSAR of 1,4-benzoxazin-3-one antimicrobials and their drug design perspectives.

Synthetic derivatives of 1,4-benzoxazin-3-ones have been shown to possess promising antimicrobial activity, whereas their natural counterparts were found lacking in this respect. In this work, quantitative structure-activity relationships (QSAR) of natural and synthetic 1,4-benzoxazin-3-ones as antimicrobials were established. Data published in literature were curated into an extensive dataset of 111 compounds. Descriptor selection was performed by a genetic algorithm. QSAR models revealed differences in requirements for activity against fungi, gram-positive and gram-negative bacteria. Shape, VolSurf, and H-bonding property descriptors were frequently picked in all models. The models obtained for gram-positive and gram-negative bacteria showed good predictive power (Q2Ext 0.88 and 0.85, respectively). Based on the models generated, an additional set of 1,4-benzoxazin-3-ones, for which no antimicrobial activity had been determined in literature, were evaluated in silico. Additionally, newly designed lead compounds with a 1,4-benzoxazin-3-one scaffold were generated in silico by varying the positions and combinations of substituents. Two of these were predicted to be up to 5 times more active than any of the compounds in the current dataset. The 1,4-benzoxazin-3-one scaffold was concluded to possess potential for the design of new antimicrobial compounds with potent antibacterial activity, a multitarget mode of action, and possibly reduced susceptibility to gram negatives' efflux pumps.

Transcriptome analysis for the scale-down of a CHO cell fed-batch process.

Transcriptome and metabolism analysis were performed to evaluate the scale-down of a CHO cell fed-batch process from a 10 L bioreactor to an ambr 15® (ambr) system. Two different agitation scale-down principles were applied, resulting in two different agitation rates in the ambr system: 1300 RPM based on the agitator tip speed, and 800 rpm based on the volumetric power input (P/V). Culture performance including cell growth, product titer, glycosylation, and specific consumption/production rates of metabolites was the same for both agitation rates in the ambr and was comparable to that of the 10 L system. The initial variation in gene expression between the inocula for the ambr and 10 L system was no longer present after three days of culture, indicating comparable culture conditions in both systems. Based on principal component analysis, changes in gene expression over time were similar between both scales with less than 6% variation. 2455 genes were uniquely regulated in the ambr system compared to 1604 genes in the 10 L system. Functional analysis of these genes did not reveal their relations with scale or cellular function. This study further strengthens that the ambr system gives representative culture performance for the 10 L bench-scale bioreactor.

A Multidisciplinary Phenotyping and Genotyping Analysis of a Mapping Population Enables Quality to Be Combined with Yield in Rice.

In this study a mapping population (F8) of ca 200 progeny from a cross between the commercial rice varieties Apo and IR64 has been both genotyped and phenotyped. A genotyping-by-sequencing approach was first used to identify 2,681 polymorphic SNP markers which gave dense coverage of the genome with a good distribution across all 12 chromosomes. The coefficient of parentage was also low, at 0.13, confirming that the parents are genetically distant from each other. The progeny, together with both parents, were grown under irrigated and water restricted conditions in a randomised block design. All grain was harvested to determine variation in yield across the population. The grains were then polished following standard procedures prior to performing the phenotyping analyses. A Gas Chromatography-Mass Spectrometry approach was used to determine the volatile biochemical profiles of each line and after data curation and processing, discriminatory metabolites were putatively identified based on in-house and commercial spectral libraries. These data were used to predict the potential role of these metabolites in determining differences in aroma between genotypes. A number of QTLs for yield and for individual metabolites have been identified. Following these combined multi-disciplinary analyses, it proved possible to identify a number of lines which appeared to combine the favourable aroma attributes of IR64 with the favourable (higher) yield potential of Apo. As such, these lines are excellent candidates to assess further as potential genotypes to work up into a new variety of rice which has both good yield and good quality, thus meeting the needs of both farmer and consumer alike.

Improved batch correction in untargeted MS-based metabolomics.

INTRODUCTION: Batch effects in large untargeted metabolomics experiments are almost unavoidable, especially when sensitive detection techniques like mass spectrometry (MS) are employed. In order to obtain peak intensities that are comparable across all batches, corrections need to be performed. Since non-detects, i.e., signals with an intensity too low to be detected with certainty, are common in metabolomics studies, the batch correction methods need to take these into account. OBJECTIVES: This paper aims to compare several batch correction methods, and investigates the effect of different strategies for handling non-detects. METHODS: Batch correction methods usually consist of regression models, possibly also accounting for trends within batches. To fit these models quality control samples (QCs), injected at regular intervals, can be used. Also study samples can be used, provided that the injection order is properly randomized. Normalization methods, not using information on batch labels or injection order, can correct for batch effects as well. Introducing two easy-to-use quality criteria, we assess the merits of these batch correction strategies using three large LC-MS and GC-MS data sets of samples from Arabidopsis thaliana. RESULTS: The three data sets have very different characteristics, leading to clearly distinct behaviour of the batch correction strategies studied. Explicit inclusion of information on batch and injection order in general leads to very good corrections; when enough QCs are available, also general normalization approaches perform well. Several approaches are shown to be able to handle non-detects-replacing them with very small numbers such as zero seems the worst of the approaches considered. CONCLUSION: The use of quality control samples for batch correction leads to good results when enough QCs are available. If an experiment is properly set up, batch correction using the study samples usually leads to a similar high-quality correction, but has the advantage that more metabolites are corrected. The strategy for handling non-detects is important: choosing small values like zero can lead to suboptimal batch corrections.

Changes over lactation in breast milk serum proteins involved in the maturation of immune and digestive system of the infant.

Here we provide data from shot-gun proteomics, using filtered-aided sample preparation (FASP), dimethyl labeling and LC-MS/MS, to quantify the changes in the repertoire of human milk proteins over lactation. Milk serum proteins were analyzed at week 1, 2, 3 4, 8, 16, and 24 in milk from four individual mothers. A total of 247 proteins were identified, of which 200 proteins were quantified. The data supplied in this article supports the accompanying publication (Zhang et al., 2006) [1]. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (Vizcaíno et al., 2016) [2] via the PRIDE partner repository with the dataset identifier PXD003465.

Changes over lactation in breast milk serum proteins involved in the maturation of immune and digestive system of the infant.

UNLABELLED: To objective of this study was to better understand the biological functions of breast milk proteins in relation to the growth and development of infants over the first six months of life. Breast milk samples from four individual women collected at seven time points in the first six months after delivery were analyzed by filter aided sample preparation and dimethyl labeling combined with liquid chromatography tandem mass spectrometry. A total of 247 and 200 milk serum proteins were identified and quantified, respectively. The milk serum proteome showed a high similarity (80% overlap) on the qualitative level between women and over lactation. The quantitative changes in milk serum proteins were mainly caused by three groups of proteins, enzymes, and transport and immunity proteins. Of these 21 significantly changed proteins, 30% were transport proteins, such as serum albumin and fatty acid binding protein, which are both involved in transporting nutrients to the infant. The decrease of the enzyme bile salt-activated lipase as well as the immunity proteins immunoglobulins and lactoferrin coincide with the gradual maturation of the digestive and immune system of infants. The human milk serum proteome didn't differ qualitatively but it did quantitatively, both between mothers and as lactation advanced. The changes of the breast milk serum proteome over lactation corresponded with the development of the digestive and immune system of infants. BIOLOGICAL SIGNIFICANCE: Breast milk proteins provide nutrition, but also contribute to healthy development of infants. Despite the previously reported large number of identified breast milk proteins and their changes over lactation, less is known on the changes of these proteins in individual mothers. This study is the first to determine the qualitative and quantitative changes of milk proteome over lactation between individual mothers. The results indicate that the differences in the milk proteome between individual mothers are more related to the quantitative level than qualitative level. The correlation between the changes of milk proteins and the gradual maturation of the gastrointestinal tract and immune system in infants, contributes to a better understanding of the biological functions of human milk proteins for the growth and development of infants.

Perspective on calf and mammary gland development through changes in the bovine milk proteome over a complete lactation.

Milk contains all the nutrients for the growth and development of the neonate. However, milk composition is not constant during lactation. To study the changes of the milk proteome over lactation, filter-aided sample preparation combined with dimethyl labeling followed by liquid chromatography tandem mass spectrometry was used to identify and quantify milk proteins from 4 cows. A total of 229 proteins were identified, of which 219 were quantified. An 80% overlap was found in identified and quantified proteins between the 4 individual cows during lactation. Over lactation, the number of quantified proteins changed slightly (less than 10%), whereas the concentration of proteins changed considerably. Transport proteins involved in lipid synthesis (fatty acid-binding protein, perilipin-2, butyrophilin) increased, whereas proteins related to cholesterol transport (apolipoprotein E) decreased. The changes of lipid synthesis proteins are in accordance with the increased milk fat yield over lactation, indicating the increase of de novo mammary fatty acid synthesis as lactation advances. The high abundance of immune-related proteins in early lactation indicates the important role of these proteins for immune system development of calves. The increase in immune-related proteins (immunoglobulins, osteopontin, lactoferrin) and the decrease of proteins related to milk component synthesis (α-lactalbumin, ß-lactoglobulin, fatty acid-binding protein, perilipin-2, butyrophilin) in late lactation can be associated with the protection of the mammary gland. In conclusion, the changes of proteins with different biological functions reflect not only the changing needs of calves but also the development and protection of the mammary gland over lactation.

Bovine milk proteome in the first 9 days: protein interactions in maturation of the immune and digestive system of the newborn.

In order to better understand the milk proteome and its changes from colostrum to mature milk, samples taken at seven time points in the first 9 days from 4 individual cows were analyzed using proteomic techniques. Both the similarity in changes from day 0 to day 9 in the quantitative milk proteome, and the differences in specific protein abundance, were observed among four cows. One third of the quantified proteins showed a significant decrease in concentration over the first 9 days after calving, especially in the immune proteins (as much as 40 fold). Three relative high abundant enzymes (XDH, LPL, and RNASE1) and cell division and proliferation protein (CREG1) may be involved in the maturation of the gastro-intestinal tract. In addition, high correlations between proteins involved in complement and blood coagulation cascades illustrates the complex nature of biological interrelationships between milk proteins. The linear decrease of protease inhibitors and proteins involved in innate and adaptive immune system implies a protective role for protease inhibitor against degradation. In conclusion, the results found in this study not only improve our understanding of the role of colostrum in both host defense and development of the newborn calf but also provides guidance for the improvement of infant formula through better understanding of the complex interactions between milk proteins.

Simplivariate models: uncovering the underlying biology in functional genomics data.

One of the first steps in analyzing high-dimensional functional genomics data is an exploratory analysis of such data. Cluster Analysis and Principal Component Analysis are then usually the method of choice. Despite their versatility they also have a severe drawback: they do not always generate simple and interpretable solutions. On the basis of the observation that functional genomics data often contain both informative and non-informative variation, we propose a method that finds sets of variables containing informative variation. This informative variation is subsequently expressed in easily interpretable simplivariate components.We present a new implementation of the recently introduced simplivariate models. In this implementation, the informative variation is described by multiplicative models that can adequately represent the relations between functional genomics data. Both a simulated and two real-life metabolomics data sets show good performance of the method.

Comparative analysis of transcriptome and fitness profiles reveals general and condition-specific cellular functions involved in adaptation to environmental change in Saccharomyces cerevisiae.

The transcriptional responses of yeast cells to a wide variety of stress conditions have been studied extensively. In addition, deletion mutant collections have been widely used to measure the combined effect of gene loss and stress on growth (fitness). Here we present a comparative analysis of 1,095 publicly available transcription and genome-wide fitness profiles in yeast, from different laboratories and experimental platforms. We analyzed these data, using T-profiler, to describe the correlation in behavior of a priori defined functional groups. Two-mode clustering analysis of the fitness T-profiles revealed that functional groups involved in regulating ribosome biogenesis and translation offer general stress resistance. These groups are closely related to growth rate and nutrient availability. General stress sensitivity was found in deletion mutant groups functioning in intracellular vesicular transport, actin cytoskeleton organization, and cell polarity, indicating that they play an key role in maintaining yeast adaptability. Analysis of the phenotypic and transcriptional variability of our a priori defined functional groups showed that the quantitative effect on fitness of both resistant and sensitive groups is highly condition-dependent. Finally, we discuss the implications of our results for combinatorial drug design.