Kasper Hettinga

The Host Defense Proteome of Human and Bovine Milk

Milk is the single source of nutrients for the newborn mammal. The composition of milk of different mammals has been adapted during evolution of the species to fulfill the needs of the offspring. Milk not only provides nutrients, but it also serves as a medium for transfer of host defense components to the offspring. The host defense proteins in the milk of different mammalian species are expected to reveal signatures of evolution. The aim of this study is therefore to study the difference in the host defense proteome of human and bovine milk. We analyzed human and bovine milk using a shot-gun proteomics approach focusing on host defense-related proteins. In total, 268 proteins in human milk and 269 proteins in bovine milk were identified. Of these, 44 from human milk and 51 from bovine milk are related to the host defense system. Of these proteins, 33 were found in both species but with significantly different quantities. High concentrations of proteins involved in the mucosal immune system, immunoglobulin A, CD14, lactoferrin, and lysozyme, were present in human milk. The human newborn is known to be deficient for at least two of these proteins (immunoglobulin A and CD14). On the other hand, antimicrobial proteins (5 cathelicidins and lactoperoxidase) were abundant in bovine milk. The high concentration of lactoperoxidase is probably linked to the high amount of thiocyanate in the plant-based diet of cows. This first detailed analysis of host defense proteins in human and bovine milk is an important step in understanding the function of milk in the development of the immune system of these two mammals.

Predicting bovine milk fat composition using infrared spectroscopy based on milk samples collected in winter and summer

It has recently been shown that Fourier transform infrared spectroscopy has potential for the prediction of detailed milk fat composition, even based on a limited number of observations. Therefore, there seems to be an opportunity for improvement by means of using more observations. The objective of this study was to verify whether the use of more data would add to the accuracy of predicting milk fat composition. In addition, the effect of season on modeling was quantified because large differences in milk fat composition between winter and summer samples exist. We concluded that the use of 3,622 observations does increase predictability of milk fat composition based on infrared spectroscopy. However, for fatty acids with low concentrations, the use of many observations does not increase predictability to a level at which application of the model becomes obvious. Furthermore, the effect of season on validation r-square was limited but was occasionally large on prediction bias. For fatty acids that show large differences in level and standard deviation between winter and summer, a representative sample that includes observations collected in various seasons is critical for unbiased prediction. This research shows that all major fatty acids, combined groups of fatty acids, and the ratio of saturated to unsaturated fatty acids can be predicted accurately.

Filter-aided sample preparation with dimethyl labeling to identify and quantify milk fat globule membrane proteins

Bovine milk is a major nutrient source in many countries and it is produced at an industrial scale. Milk is a complex mixture of proteins, fats, carbohydrates, vitamins and minerals. The composition of the bovine milk samples can vary depending on the genetic makeup of the bovine species as well as environmental factors. It is therefore important to study the qualitative and quantitative differences of bovine milk samples. Proteins in milk can be present in casein micelles, in the serum (the water soluble fraction) or in fat globules. These fat globules have a double membrane layer with proteins being bound to or being incapsulated in the membrane layer. The identification and molecular composition of the milk proteins have gained increased interest in recent years. Proteomic techniques make it now possible to identify up to many thousands of proteins in one sample, however quantification of proteins is as yet not straightforward. We analyzed the proteins of the milk fat globule membrane using dimethyl labeling methods combined with a filter-aided sample preparation protocol. Using these methods, it is now possible to quantitatively study the detailed protein composition of many milk samples in a short period of time.

Influence of different proteolytic strains of Streptococcus thermophilus in co-culture with Lactobacillus delbrueckii subsp. bulgaricus on the metabolite profile of set-yoghurt

Proto-cooperation between Streptococcus thermophilus and Lactobacillus delbrueckii subsp. bulgaricus is one of the key factors that determine the fermentation process and final quality of yoghurt. In this study, the interaction between different proteolytic strains of S. thermophilus and L. delbrueckii subsp. bulgaricus was investigated in terms of microbial growth, acidification and changes in the biochemical composition of milk during set-yoghurt fermentation. A complementary metabolomics approach was applied for global characterization of volatile and non-volatile polar metabolite profiles of yoghurt associated with proteolytic activity of the individual strains in the starter cultures. The results demonstrated that only non-proteolytic S. thermophilus (Prt-) strain performed proto-cooperation with L. delbrueckii subsp. bulgaricus. The proto-cooperation resulted in significant higher populations of the two species, faster milk acidification, significant abundance of aroma volatiles and non-volatile metabolites desirable for a good organoleptic quality of yoghurt. Headspace SPME-GC/MS and (1)H NMR resulted in the identification of 35 volatiles and 43 non-volatile polar metabolites, respectively. Furthermore, multivariate statistical analysis allows discriminating set-yoghurts fermented by different types of starter cultures according to their metabolite profiles. Our finding underlines that selection of suitable strain combinations in yoghurt starters is important for achieving the best technological performance regarding the quality of product.

Detection of Mastitis Pathogens by Analysis of Volatile Bacterial Metabolites

The ability to detect mastitis pathogens based on their volatile metabolites was studied. Milk samples from cows with clinical mastitis, caused by Staphylococcus aureus, coagulase-negative staphylococci, Streptococcus uberis, Streptococcus dysgalactiae, and Escherichia coli were collected. In addition, samples from cows without clinical mastitis and with low somatic cell count (SCC) were collected for comparison. All mastitis samples were examined by using classical microbiological methods, followed by headspace analysis for volatile metabolites. Milk from culture-negative samples contained a lower number and amount of volatile components compared with cows with clinical mastitis. Because of variability between samples within a group, comparisons between pathogens were not sufficient for classification of the samples by univariate statistics. Therefore, an artificial neural network was trained to classify the pathogen in the milk samples based on the bacterial metabolites. The trained network differentiated milk from uninfected and infected quarters very well. When comparing pathogens, Staph. aureus produced a very different pattern of volatile metabolites compared with the other samples. Samples with coagulase-negative staphylococci and E. coli had enough dissimilarity with the other pathogens, making it possible to separate these 2 pathogens from each other and from the other samples. The 2 streptococcus species did not show significant differences between each other but could be identified as a different group from the other pathogens. Five groups can thus be identified based on the volatile bacterial metabolites: Staph. aureus, coagulase-negative staphylococci, streptococci (Strep. uberis and Strep. dysgalactiae as one group), E. coli, and uninfected quarters.

Enteric methane production, rumen volatile fatty acid concentrations, and milk fatty acid composition in lactating Holstein-Friesian cows fed grass silage- or corn silage-based diets

The objective of this study was to determine the effects of replacing grass silage (GS) with corn silage (CS) in dairy cow diets on enteric methane (CH4) production, rumen volatile fatty acid concentrations, and milk fatty acid (FA) composition. A completely randomized block design experiment was conducted with 32 multiparous lactating Holstein-Friesian cows. Four dietary treatments were used, all having a roughage-to-concentrate ratio of 80:20 based on dry matter (DM). The roughage consisted of either 100% GS, 67% GS and 33% CS, 33% GS and 67% CS, or 100% CS (all DM basis). Feed intake was restricted (95% of ad libitum DM intake) to avoid confounding effects of DM intake on CH4 production. Nutrient intake, apparent digestibility, milk production and composition, nitrogen (N) and energy balance, and CH4 production were measured during a 5-d period in climate respiration chambers after adaptation to the diet for 12 d. Increasing CS proportion linearly decreased neutral detergent fiber and crude protein intake and linearly increased starch intake. Milk production and milk fat content (on average 23.4 kg/d and 4.68%, respectively) were not affected by increasing CS inclusion, whereas milk protein content increased quadratically. Rumen variables were unaffected by increasing CS inclusion, except the molar proportion of butyrate, which increased linearly. Methane production (expressed as grams per day, grams per kilogram of fat- and protein-corrected milk, and as a percent of gross energy intake) decreased quadratically with increasing CS inclusion, and decreased linearly when expressed as grams of CH4 per kilogram of DM intake. In comparison with 100% GS, CH4 production was 11 and 8% reduced for the 100% CS diet when expressed per unit of DM intake and per unit fat- and protein-corrected milk, respectively. Nitrogen efficiency increased linearly with increased inclusion of CS. The concentration of trans C18:1 FA, C18:1 cis-12, and total CLA increased quadratically, and iso C16:0, C18:1 cis-13, and C18:2n-6 increased linearly, whereas the concentration of C15:0, iso C15:0, C17:0, and C18:3n-3 decreased linearly with increasing inclusion of CS. No differences were found in short- and medium-straight, even-chain FA concentrations, with the exception of C4:0 which increased linearly with increased inclusion of CS. Replacing GS with CS in a common forage-based diet for dairy cattle offers an effective strategy to decrease enteric CH4 production without negatively affecting dairy cow performance, although a critical level of starch in the diet seems to be needed.

Changes in Milk Proteome and Metabolome Associated with Dry Period Length, Energy Balance, and Lactation Stage in Postparturient Dairy Cows

The early lactation period of dairy cows, which produce high quantities of milk, is normally characterized by an insufficient energy intake to cover milk production and maintenance requirements. Mobilization of body reserves occurs to compensate this negative energy balance (NEB), and probably as a consequence there is a higher susceptibility to diseases and metabolic disorders. There are several diagnostic methods to detect NEB, usually involving ketosis related parameters. Due to the easy availability of milk this is a preferred matrix, but simple and robust predictors of NEB level are missing. To better understand the physiological mechanism of NEB, milk of cows subjected to different dry period lengths, in different energy balance status and lactation stage, were analyzed by untargeted metabolomics and proteomics techniques. Milk of cows in severe NEB showed higher concentrations of acute phase response proteins, unsaturated fatty acids, and galactose-1-phosphate. Improved energy balance (EB) resulted in higher concentration of cholesterol, cholesterol synthesis related proteins, and stomatin. The presence of stomatin and galactose-1-phosphate in milk was strongly dependent on the EB of the cows. These novel and interesting findings warrant more in-depth research to assess their applicability as robust indicators of NEB in milk and to clarify the role of stomatin and galactose-1-phophate in milk of dairy cows in NEB.

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.

Milk Fat Content and DGAT1 Genotype Determine Lipid Composition of the Milk Fat Globule Membrane

During secretion of milk fat globules, triacylglycerol (TAG) droplets are enveloped by a phospholipid (PL) trilayer. Globule size has been found to be related to polar lipid composition and fat content, and milk fat content and fatty acid composition have been associated with the diacylglycerol acyltransferase 1 (DGAT1) K232A polymorphism; however, the association between the DGAT1 polymorphism and fat globule size and polar lipid composition has not been studied. The ratio between polar and neutral lipids as well as the composition of the polar lipids in milk has industrial as well as nutritional and health implications. Understanding phenotypic and genotypic factors influencing these parameters could contribute to improving milk lipid composition for dairy products. The focus of the present study was to determine the effect of both fat content and DGAT1 polymorphism on PL/TAG ratio, as a marker for milk fat globule size, and detailed PL composition. Milk samples were selected from 200 cows such that there were equal numbers of samples for the different fat contents as well as per DGAT1 genotype. Samples were analyzed for neutral and polar lipid concentration and composition. PL/TAG ratio was significantly associated with both fat content and DGAT1 genotype. Phosphatidylinositol and phosphatidylserine concentrations were associated with fat content*DGAT1 genotype with a stronger association for the AA than the KK genotype. Sphingomyelin concentration tended to interact with fat content*DGAT1 genotype. Phosphatidylethanolamine (PE) concentration showed a biphasic response to fat content, suggesting that multiple biological processes influence its concentration. These results provide a new direction for controlling polar lipid concentration and composition in milk through selective breeding of cows.

Endogenous Human Milk Peptide Release Is Greater after Preterm Birth than Term Birth

BACKGROUND Hundreds of naturally occurring milk peptides are present in term human milk. Preterm milk is produced before complete maturation of the mammary gland, which could change milk synthesis and secretion processes within the mammary gland, leading to differences in protein expression and enzymatic activity, thereby resulting in an altered peptide profile. OBJECTIVE This study examined differences in peptides present between milk from women delivering at term and women delivering prematurely. METHODS Nano-LC tandem mass spectrometry was employed to identify naturally occurring peptides and compare their abundances between term and preterm human milk samples at multiple time points over lactation. Term milk samples were collected from 8 mothers and preterm milk was collected from 14 mothers. The 28 preterm and 32 term human milk samples were divided into 4 groups based on day of collection (<14, 14-28, 29-41, and 42-58 d). RESULTS Preterm milk peptide counts, ion abundance, and concentration were significantly higher in preterm milk than term milk. Bioinformatic analysis of the cleavage sites for peptides identified suggested that plasmin was more active in preterm milk than term milk and that cytosol aminopeptidase and carboxypeptidase B2 likely contribute to extensive milk protein breakdown. Many identified milk peptides in both term and preterm milk overlapped with known functional peptides, including antihypertensive, antimicrobial, and immunomodulatory peptides. CONCLUSION The high protein degradation by endogenous proteases in preterm milk might attenuate problems because of the preterm infants immature digestive system. This trial was registered at clinicaltrials.gov as NCT01817127.