Bovine Milk Oligosaccharide Contents Show Remarkable Seasonal

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Bovine milk oligosaccharide contents show remarkable seasonal variation and inter-cow variation Zhiqian Liu, Martin Auldist, Marlie Wright, Benjamin Cocks, and Simone Rochfort J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.6b04098 • Publication Date (Web): 31 Jan 2017 Downloaded from http://pubs.acs.org on February 6, 2017

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Journal of Agricultural and Food Chemistry

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Bovine milk oligosaccharide contents show remarkable seasonal variation

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and inter-cow variation

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Zhiqian Liu1*, Martin Auldist2, Marlie Wright2, Benjamin Cocks1,3 and Simone Rochfort1,3

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Australia

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Victoria 3821, Australia

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Biosciences Research, Agriculture Victoria, AgriBio, 5 Ring Road, Bundoora, Victoria 3083,

Farming Systems Research, Agriculture Victoria, Ellinbank Centre, 1301 Hazeldean Rd, Ellinbank,

School of Applied Systems Biology, La Trobe University, Bundoora , Victoria 3083, Australia

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Corresponding author:

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Email: [email protected]

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Phone: +61-3-9032 7134

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Fax: +61-3-9032 7601

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Table of Contents categories:

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1) Agricultural and Environmental Chemistry

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2) Food and Beverage Chemistry/Biochemistry

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Abstract

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Human milk oligosaccharides (OS) play an important role in protecting the neonate. In

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addition to fructo-oligosaccharides and galacto-oligosaccharides, bovine milk OS have great

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potential to be used in paediatric food products to mimic the functions of human milk OS.

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Currently, little is known about the accumulation of OS in bovine milk in relation to genetic

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and environmental factors. A systematic survey on seasonal variation of 14 major OS was

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thus conducted with 19 cows over the entire milking season using liquid chromatography-

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mass spectrometry technique. This study revealed a number of significant correlations

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between structurally-related and structurally non-related OS, and a substantial individual

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animal difference for all the 14 OS. Most of the 14 OS displayed a remarkable seasonal

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variation in abundance (up to 10 fold change), with the highest abundance observed in April

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and May (i.e. autumn) for the majority of the 19 cows.

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Keywords: milk, oligosaccharides, seasonal variation, liquid chromatography-mass

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spectrometry

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INTRODUCTION

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Milk oligosaccharides (milk OS) are known to exert multiple beneficial functions for neonate

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health, such as selectively promoting the growth of beneficial bifidobacteria in the colon,

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preventing infection by inhibiting the adhesion of pathogenic bacteria to the intestinal

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mucosal surface and enhancing brain development and cognitive function of neonates.1-3 OS

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are a significant component of human milk (7-12 g/L in mature milk) that confer protection

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to infants.4 In the absence of commercial source of the complex structures of human milk OS,

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fructo-oligosaccharides (FOS) derived from plants and galacto-oligosaccharides (GOS)

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enzymatically synthesised are widely used as functional additives in infant formulas.5,6 Both

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FOS and GOS are linear molecules with a very limited varieties of monomers, as opposed to

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human milk OS with both linear and branched structures and more diverse monomers (such

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as fucose, sialic acid, N-acetylglucosamine and N-acetylgalactosamine in addition to

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hexoses), so FOS and GOS may not mimic all the functions of human milk OS.

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Bovine milk OS are structurally closer to human milk OS than are FOS and GOS,7 but

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their concentration is much lower especially in mature milk. Recently, purification of OS

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from whey permeate in dairy streams has been reported,8-11 and this by-product may become

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an important source for valuable OS used in paediatric food products.12

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In order to increase the level of OS in raw milk, understanding how the biosynthesis of

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bovine milk OS is influenced by various genetic and environmental factors is required. Until

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now, the most studied factors relating to milk OS content include cow breed (Jersey versus

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Holstein),13,14 and lactation stage, especially during the first several days postpartum.15-18

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Surprisingly, few reports can be found concerning the effect of feeding regime or diets on OS

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accumulation.19 Although seasonal change of milk composition was the subject of numerous

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investigations, most of them focused on the major components of milk in particular lactose,

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fat and protein.20-23 One single study surveyed the seasonal change of OS, but only five major

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OS were measured in bulked milk samples.13 It has been recognised that seasonal change of

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milk composition could offer opportunities for dairy manufacturers, as exemplified by the

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observation that the spreadability of butter is better when it is produced from summer fat

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compared with winter fat.23 In order to maximise the value of bovine milk OS in paediatric

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food products, a systematic survey on the seasonal change of all major OS is needed.

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Forty to sixty OS have been identified in enriched fraction of bovine milk using various

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techniques.3,24,25 However, our previous study found that in non-enriched milk samples the

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majority of those reported OS were present at a level too low for reliable quantification, and

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only 13 species were consistently detected at a quantifiable level and they were considered as

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major OS species in bovine milk.19 The aims of this study were: 1) conducting a systematic

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survey on the abundance of all the major OS over eight consecutive months spanning the

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entire milking season; 2) evaluating the variation in OS level between individual cows using

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a large number of animals of the same breed, subjected to the same feeding and management

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regime.

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MATERIALS AND METHODS

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Cows, herd management and milk sample collection. Milk samples were collected on a

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monthly basis for eight consecutive months (from October 2013 to May 2014) in Victoria

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(Australia) from 19 seasonally calving multiparous Holstein-Friesian dairy cows (labelled A-

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S), that calved in late winter/early spring. At the time of the first sample collection in

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October, they were 73±24 days in milk. All cows were maintained in the research herd at the

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Department of Economic Development, Jobs, Transport and Resources’ Ellinbank Centre and

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the experimentation was conducted in accordance with the Australian Code of Practice for

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the Care and Use of Animals for Scientific Purposes.26 Cow diet varied through the sampling

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period but the majority of the cows’ nutrient intake was usually derived from grazed pasture

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supplemented with bought in feedstuff fed according to different strategies. This included

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offering cereal grain or pelleted concentrates in the dairy at milking time and/or the provision

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of a mixed ration in a feedpad after milking. On each sampling occasion, the total milk from

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the afternoon and morning milking was collected into test buckets, pooled for each cow and a

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subsample taken for analysis. Milk samples were transported to the laboratory on ice and kept

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at -80 °C before analysis.

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Chemicals. OS standards galactotriose [Gal(β1-4)Gal(β1-4)Gal], 3’-sialyllactose (3’-SL),

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6’-sialyllactose (6’-SL) and 6’-sialyllatosamine (6’-SLN), and internal standard (IS)

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stachyose were purchased from Sigma-Aldrich. Molecular weight cut-off filters (10 kDa,

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Amicon) were obtained from Merck Millipore. Mobile phase solvent (acetonitrile containing

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0.1% formic acid) was from Fisher Scientific and mobile phase additive (ammonium

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formate) from Sigma-Aldrich.

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Sample preparation for oligosaccharide analysis. OS fraction was isolated from diluted

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raw milk using an ultra-filtration method and the filtrate used directly for LC-MS analysis.

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The detailed sample preparation procedure was as previously described.19

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OS analysis by LC-MS. An Agilent 1290 UPLC system coupled to an LTQ-Orbitrap MS

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(Thermo Scientific) was used for OS quantification. Chromatographic separation of OS was

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achieved using a HILIC Kinetex column (150×4.6 mm, 2.6 µm, Phenomenex) maintained at

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30 °C. The mobile phase was composed of 5 mM aqueous ammonium formate (A) and

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acetonitrile containing 0.1% formic acid (B). The flow rate was 0.8 mL/min and the elution

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started with 5% A for the first 3 min and then increased to 30% A from 3 to 17 min. The

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total run time was 26 min for each analysis. MS instrumental settings for OS analysis were as

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previously described.19 All OS and the IS were detected in negative ion mode as their

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deprotonated ions.

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Method validation. Method precision. A bulked milk sample (from 10 random samples)

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was analysed three times. Measurement precision was assessed by the peak area variation

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between repeated analyses for each of the major OS species.

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Method recovery. A mix of four OS standards (galactotriose, stachyose, 6’-SL and 6’-

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SLN) was spiked to the bulked milk sample at two different levels (0.1 and 1 µg in 400 µl of

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milk). The recovery of the authentic standards was calculated using the following formula:

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Recovery (%) = [(total mass in the spiked sample – mass in the non-spiked sample)/mass

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spiked] ×100.

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Quantification of OS in milk samples. Due to the lack of standards for several OS,

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relative quantification was carried out for all the major OS. Peak area (after normalisation by

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the IS) was used as a measure for comparing the abundance of each OS across all samples.

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Statistical analysis of data. OS abundance data across the eight months were subjected

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to ANOVA (XLSTAT, Microsoft Excel); where significant differences were found between

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seasons, a Tukey’s HSD test was conducted for pairwise comparisons.

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RESULTS AND DISCUSSION

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Major OS detected in the bulked milk sample. Fourteen OS were detected without

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sample enrichment in this study; their monomer composition and accurate mass are

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summarised in Table 1. The LC-MS profiles of these 14 OS are shown in Fig.1. Triose,

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present in four isomers in milk,25 was chromatographically separated into two peaks of

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similar intensity in this study, named Triose-a (Tri-a) and Triose-b (Tri-b). An isomer peak of

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much lower intensity was also detected in the case of 6’-SLN, GNL, OS-A, OS-C, OS-E, OS-

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F and OS-G in addition to the dominant peak (Fig. 1).

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Quantification of OS in milk samples. Except for triose and sialyllactose, for which two

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isomers (Tri-a/Tri-b and 3’-SL/6’-SL, respectively) were quantified separately, only the 6 ACS Paragon Plus Environment

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dominant isomer was quantified for other OS, so a total of 14 OS species were measured for

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each sample. The method showed good reproducibility for the measurement of all the OS

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(RSD < 6%) (Table S-1, Supporting Information). The overall recovery of the four

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representative OS standards spiked at two different levels was between 92 and 102% (Table

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S-2, Supporting Information). The whole dataset that contains 1974 measurements (141

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samples × 14 OS) was analysed for correlation between OS, inter-cow variation for each OS

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and seasonal variation for each OS.

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Correlation between OS. Our previous study had identified significant correlation

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between three pairs of OS (6’-SL/6’-SLN, OS-C/GNL and OS-D/OS-G) using a relatively

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small number of samples (n = 32).19 A thorough pair-wise correlation analysis was performed

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in this study with the entire data matrix that contains 141 samples and the abundance of 14

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OS. This allowed us to detect 16 pairs of OS that showed highly significant correlation in

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abundance (R2 > 0.35, P < 0.00001) (Table 2 in bold). The strongest correlation was found

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between OS-B and OS-G (R2 = 0.95), followed by OS-B vs OS-D (R2 = 0.94), and GNL vs

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OS-C (R2 = 0.64). Fig. S-1 (Supporting Information) shows the correlation plot for two

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representative pairs of OS with differing R2 values.

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One pair of OS (6’-SL/6’-SLN) found to be correlated significantly in our previous report

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was not confirmed in this study. Most of the correlated pairs are structurally related. For

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example, in the case of the highly correlated pair OS-B/OS-G, OS-B is the non-sialylated

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analogue of the monosialylated OS-G, suggesting that the former is probably the precursor of

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the latter. The correlation between these two OS can thus be explained by a precursor-product

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relationship. Such a direct precursor-product relationship is likely to be responsible for the

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correlation observed between OS pairs GNL/OS-C and 3’-SL/DSL, because OS-C has one

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extra hexose unit at the non-reducing end of GNL, whereas DSL has one extra unit of sialic

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acid compared with 3’-SL. A second explanation for the correlation between OS is that they

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share a common precursor. This may account for the inter-correlation between OS-A/OS-

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F/DSL, all likely having 3’-SL as the common precursor. However, not all correlations

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between OS can be explained by structural similarity, this is the case for the correlation

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observed between OS-E and 6’-SLN (R2 = 0.51).

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To our best knowledge, the present study is the first to report the correlational relationship

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between the major OS in bovine milk. The fact that four groups of inter-correlated OS (3’-

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SL/OS-A/OS-F/DSL, OS-B/OS-D/OS-G, GNL/OS-C and OS-E/6’-SLN) can be identified

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from the 14 major OS indicates that a complex metabolic network is implicated in the

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biosynthesis of OS in milk. More work is clearly required to fully understand the underlying

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regulatory mechanisms.

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Inter-cow variation. The abundance of all OS showed clear variation between cows but

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the magnitude of variation appeared to be different between OS. Some OS such as GNL, OS-

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B, OS-D and OS-G displayed a huge variation (> 10-fold difference) between cows

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throughout the experimental period (i.e. eight consecutive months), whereas only a moderate

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variation (< 2-fold difference) between cows was observed for the most abundant OS 3’-SL,

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regardless of the sampling time. For all the remaining OS, a cow-to-cow variation between 2-

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10 fold was always recorded despite a slight month-to-month fluctuation (data not shown).

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Fig. 2 shows the abundance of four representative OS (3’-SL, OS-E, OS-C and GNL) with a

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differing level of inter-cow variation (small, moderate, large and huge cow-to-cow variation

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respectively) across the 19 individual animal samples collected in November 2013. While

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Kelly et al.27 identified within the same breed individual cows with concentrations of 3’-SL

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or 6’-SL > 3-fold higher than the mean, this study revealed a remarkable individual animal

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variation in the abundance of most of the 14 major OS.

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An inter-month correlation analysis was also conducted for each of the 14 OS separately.

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Because samples could only be collected from 15 out of the 19 animals for the last month, so

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this analysis was based on the data of the first seven months. Stronger correlations were

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generally observed between consecutive months, especially during the first four months (i.e.

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from October 2013 to January 2014) (results not shown). Seven out of the 14 OS, namely 3’-

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SL, 6’-SL, GNL, OS-C, DSL, OS-F and Tri-a, showed a significant inter-month correlation

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(R2 > 0.25, P < 0.05) across all seven months. For these seven OS, a clear correlation was

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observed even between samples collected five months apart. Fig. 3 shows the highly

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significant correlation (P < 0.01) of four OS (GNL, 6’-SL, OS-C and OS-F) between

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November 2013 and April 2014. This inter-month correlation indicates that some cows

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produce consistently higher or lower OS milk across different sampling months. Because all

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cows were under the same management regime and at a similar lactation stage, genotypic

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difference is likely to be a contributing factor for the inter-cow variation of some OS, which

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could potentially be exploited to increase the abundance of milk OS.

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Seasonal change. Incomplete data obtained from four animals were excluded from

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seasonal variation analysis, so the whole dataset contains eight monthly measurements of 14

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OS species for 15 individual animal samples. These eight months (October 2013 to May

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2014) cover the essential lactation period (July to September being the calving period).

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Overall, OS in milk follow a complex seasonal change pattern during the milking season.

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Depending on OS, four types of seasonal variation were distinguished for the 14 OS:

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(1) The abundance of OS displayed a modest change during the first four months,

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followed by a steady increase, so that the highest abundance was detected at the last sampling

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months (April and May 2014). Seven OS (6’-SLN, OS-B, OS-D, OS-G, OS-A, OS-F and

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DSL) belong to this category and their seasonal evolution is shown in Fig. 4.

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(2) The abundance of OS showed no significant change during the first several months

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and then an increase over the last two months. Again the highest abundance was observed in

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May. Two OS (Tri-a and 6’-SL) followed such a seasonal variation pattern (Fig. 4). The

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overall abundance change of these two OS during the milking season was less pronounced

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compared to the first category of OS.

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(3) The abundance of OS sustained a gradual increase for the whole milking season. This

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is the case observed with 3’-SL and OS-E (Fig. 4). The overall change of abundance over the

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milking season was moderate for 3’-SL, but substantial for OS-E. For these two OS species,

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the highest level was also recoded in May, similar to the first two categories of OS.

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(4) The abundance of OS displayed a steady increase from the start of the milking season,

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that peaked in February and then stayed stagnant over the following months. Only Tri-b

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exhibited such an unusual seasonal variation (Fig. 4).

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It should be pointed out that the aforementioned four types of seasonal change in OS

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abundance were only the overall trend observed with the majority of the 15 cows, because for

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each OS there were a few cows that did not follow completely the same variation pattern

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(results not shown). In addition to the above patterns observed with 12 OS, two remaining OS

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(GNL and OS-C) did not show any clear seasonal change (Fig. 4). Indeed, except for a few

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animals, the abundance of these two OS did not fluctuate much throughout the milking

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season. Interestingly, these two OS also displayed a strong inter-month correlation, i.e.

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animal-specific accumulation feature.

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This systematic study revealed a remarkable increase (up to 10 fold) in abundance for 12

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out of the 14 OS over the eight months’ milking season. This suggests that the overall OS

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level in milk is highly season-dependent and based on the current study, milk produced in

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April and May (i.e. autumn in Australia) contained the highest amount of OS. Our results are

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partially in agreement with the report of McJarrow and van Amelsfort-Schoonbeek,13 who

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surveyed the seasonal variation of five OS (3’-SL, 6’-SL, 6’-SLN, DSL and GNL) in bulked

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raw milk produced in New Zealand and found the 3’-SL concentration increased over the

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milking season (September to April), and 6’-SL dipped at the beginning and increased again

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at the end of the season. However, unlike our observation, they did not observe a clear

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seasonal increase for DSL and 6’-SLN.

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The clear seasonal increase in abundance for most of the major OS is an important

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finding. However, the causative factors for such a variation remains unclear, because several

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factors such as temperature, humidity, feed and even the chemical composition of the same

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pasture were not constant over the season. It has been demonstrated that OS concentration

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decreases along lactation (from colostrum to transitional milk, and further to mature

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milk),16,17 but information on the OS content in mature milk during the entire milking season

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is scarce. Although it has been found that milk fat composition changes when cows switch

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from a silage-based diet to a fresh grass-based diet and back,28,29 and grazing has a significant

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effect on the concentration of total sialic acid and hexose in bovine milk,30 whether milk OS

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level is also prone to be influenced by animal diet remains to be proven. Irrespective of the

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cause, such a seasonal increase in OS level is likely to be a general and reproducible feature,

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since the experiment was conducted following the typical herd management regime of the

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region.

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In conclusion, this is the first comprehensive survey on the seasonal variation of all the

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major OS species in bovine milk. We have demonstrated a number of significant correlation

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between the major OS; the correlated OS are structurally related in some but not all cases.

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The abundance of all OS varies greatly between individual animals, and for some OS this

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cow-to-cow variation may be genetically based. Most OS also show a remarkable seasonal

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variation with the highest level observed in autumn.

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Supporting Information

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Measurement precision for the 14 major OS (Table S-1), recovery (%) of spiked standards

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(Table S-2), and correlation between two pairs of OS (OS-B/OS-G and GNL/OS-C) (Figure

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S-1).

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This material is available free of charge via the Internet at http://pubs.acs.org.

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Neutral and acidic oligosaccharides in Holstein-Friesian colostrum during the first 3 days

317

of lactation measured by high performance liquid chromatography on a microfluidic chip

318

and time-of-flight spectrometry. J. Dairy Sci. 2010, 93, 3940-3949.

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(19) Liu, Z.; Moate, P.; Cocks, B.; Rochfort, S. Simple liquid chromatography-mass

320

spectrometry method for quantification of major free oligosaccharides in bovine milk. J.

321

Agric. Food Chem. 2014, 62, 11568-11574.

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(20) Auldist, M.J.; Walsh, B.J.; Thompson, N.A. Seasonal and lactational influences on bovine milk composition in New Zealand. J. Dairy Res. 1998, 65, 401-411. (21) Lindmark-Manssona, H.; Fonden, R.; Pettersson, H-E. Composition of Swedish dairy milk. Int. Dairy J. 2003, 13, 409-425. (22) Lock, A.L.; Garnsworthy, P.C. Seasonal variation in milk conjugated linoleic acid and delta(9)-desaturase activity in dairy cows. Livest. Prod. Sci. 2003, 79, 47–59.

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(23) Heck, J.L.M.; van Valenberg, H.J.F.; Dijkstra, J.; van Hooijdonk, A.C.M. Seasonal

329

variation in the Dutch bovine raw milk composition. J. Dairy Sci. 2009, 92, 4745-4755.

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(24) Tao, N.; DePeters, E.J.; Freeman, S.; German, J.B.; Grimm, R.; Lebrilla, C.B. Bovine milk glycome. J. Dairy Sci. 2008, 91, 3768-3778.

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(25) Aldredge, D.L.; Geronimo, M.R.; Hua, S.; Nwosu, C.C.; Lebrilla, C.B.; Barile, D.

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Annotation and structural elucidation of bovine milk oligosaccharides and determination

334

of novel fucosylated structures. Glycobiol. 2013, 23, 664-676.

335

(26) Anonymous. Australian Code of Practice for the Care and Use of Animals for Scientific

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Purposes. 2013. 8th edition. http://www.nhmrc.gov.au/publications/synopses/ea16syn.htm.

337

(accessed 24th July 2013).

338

(27) Kelly, V.; Davis, S.; Berry, S.; Melis, J.; Spelman, R.; Snell, R.; Lehnert, K.; Palmer, D.

339

Rapid, quantitative analysis of 3’- and 6’-sialyllactose in milk by flow-injection analysis-

340

mass spectrometry: Screening of milks for naturally elevated sialyllactose concentration.

341

J. Dairy Sci. 2013, 96, 7684-7691.

342

(28) Kelly, M.L.; Kolver, E.S.; Bauman, D.E.; van Amburgh, M.E.; Muller, L.D. Effect of

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intake of pasture on concentration of conjugated linoleic acid in milk of lactating cow. J.

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Dairy Sci. 1998, 81, 1630-1636.

345

(29) Elgersma, A.; Ellen, G.; van der Horst, H.; Boer, H.; Dekker, P.R. Tamminga S. Quick

346

changes in milk fat composition from cows after transition from fresh grass to a silage

347

diet. Anim. Feed Sci. Technol. 2004, 117, 13-27.

348

(30) Asakuma, S.; Ueda, Y.; Akiyama, F.; Uemura, Y.; Miyagi, M.; Nakamura, M.; Murai,

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M.; Urashima, T. Effect of grazing on the concentration of total sialic acid and hexose in

350

bovine milk. J. Dairy Sci. 2010, 93, 4850-4854.

351

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352 353

Figure legend:

354

Figure 1. Extracted ion chromatogram of the 14 major OS surveyed. The deprotonated ion of

355

each compound was extracted using a window of calculated accurate mass (shown in

356

Table 1) ± 0.005 (m/z).

357

Figure 2. Variation of four representative OS (3’-SL, OS-E, OS-C and GNL) across 19

358

individual animal milk samples (labelled A-S) collected in November 2013. The

359

relative abundance of each OS was represented by normalised peak area.

360

Figure 3. Correlation of the relative abundance of four OS (GNL, 6’-SL, OS-C and OS-F)

361

between samples collected in November 2013 and April 2014 from 17 cows. The

362

relative abundance of each OS was represented by normalised peak area.

363

Figure 4. Seasonal variation of the relative abundance of the 14 major OS in bovine milk

364

from October 2013 to May 2014. The relative abundance of each OS was represented

365

by normalised peak area; each column is the mean value of 15 cows. Within the same

366

OS, columns with different letters are significantly different (P < 0.05).

367

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Journal of Agricultural and Food Chemistry

Table 1. Major OS surveyed in this studya Name (abbreviation)

Monomer composition

m/z (calculated)

Triose-a (Tri-a)

3 Hex

503.1612

Triose-b (Tri-b)

3 Hex

503.1612

3’-sialyllactose (3’-SL)

2 Hex, 1 NeuAc

632.2038

6’-sialyllactose (6’-SL)

2 Hex, 1 NeuAc

632.2038

6’-sialyl-N-acetyllactosamine (6’-SLN)

1 Hex, 1 HexNAc, 1 NeuAc

673.2304

Disialyllactose (DSL)

2 Hex, 2 NeuAc

923.2992

N-acetylgalactosaminyllactose (GNL)

2 Hex, 1 HexNAc

544.1878

OS-A

3 Hex, 1 NeuAc

794.2566

OS-B

4 Hex, 1 HexNAc

868.2934

OS-C

3 Hex, 1 HexNAc

706.2406

OS-D

3 Hex, 2 HexNAc

909.3200

OS-E

2 Hex, 1 NeuGc

648.1987

OS-F

2 Hex, 1 HexNAc, 1 NeuAc

835.2832

OS-G

4 Hex, 1 HexNAc, 1 NeuAc

1159.3888

369

a

370

glucose or galactose; HexNAc, N-acetylglucosamine or N-acetylgalactosamine; NeuAc, N-

371

acetylneuraminic acid (sialic acid); and NeuGc, N-glycolylneuraminic acid.

calculated m/z values for deprotonated molecular ions (detected in negative mode); Hex,

372

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373

Page 18 of 24

Table 2. Pairwise correlation (R2) between the abundance of different OS (n = 141) 3'-SL

6'-SL

3'-SL

1.00

6'-SL

0.34

1.00

GNL

0.06

0.04

GNL

OS-A

OS-C

OS-E

DSL

6'-SLN

OS-B

OS-D

OS-F

OS-G

Tri-a

Tri-b

1.00

OS-A

0.47

0.16

0.10

1.00

OS-C

0.01

0.00

0.64

0.05

1.00

OS-E

0.09

0.07

0.05

0.10

0.14

1.00

DSL

0.36

0.18

0.01

0.36

0.00

0.23

1.00

6'-SLN

0.10

0.17

0.00

0.20

0.08

0.51

0.31

1.00

OS-B

0.25

0.09

0.01

0.48

0.00

0.11

0.22

0.36

1.00

OS-D

0.21

0.07

0.00

0.36

0.00

0.07

0.13

0.25

0.94

1.00

OS-F

0.39

0.08

0.00

0.51

0.00

0.27

0.52

0.21

0.31

0.26

1.00

OS-G

0.32

0.09

0.00

0.50

0.00

0.10

0.25

0.34

0.95

0.91

0.35

1.00

Tri-a

0.01

0.05

0.00

0.06

0.04

0.06

0.09

0.31

0.20

0.10

0.00

0.12

1.00

Tri-b

0.32

0.07

0.07

0.24

0.01

0.07

0.21

0.15

0.05

0.02

0.20

0.10

0.01

1.00

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Journal of Agricultural and Food Chemistry

Tri-a

Tri-b

3’-SL

6’-SL

6’-SLN DSL GNL OS-A OS-B OS-C OS-D OS-E OG-F OS-G 12

14

16

18

20

Time (min)

Fig.1

19 ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

6.0E+05

OS-E abundance

3'-SL abundance

1.0E+08 8.0E+07 6.0E+07 4.0E+07 2.0E+07

5.0E+05 4.0E+05 3.0E+05 2.0E+05 1.0E+05 0.0E+00

0.0E+00

A B C D E F G H I J K L MN O P Q R S

A B C D E F G H I J K L M N O P Q R S

Cow ID

Cow ID 1.2E+06

1.0E+07

1.0E+06

8.0E+06

GNL abundance

OS-C abundance

Page 20 of 24

8.0E+05 6.0E+05 4.0E+05 2.0E+05 0.0E+00

6.0E+06 4.0E+06 2.0E+06 0.0E+00

A B C D E F G H I J K L MN O P Q R S

A B C D E F G H I J K L M N O P Q R S

Cow ID

Cow ID

Fig. 2

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Journal of Agricultural and Food Chemistry

3.5E+07 y = 1.0057x + 583365 R² = 0.878 (P < 0.01)

6'-SL abundance (Apr. 2014)

GNL abundance (Apr. 2014)

1.0E+07

8.0E+06

6.0E+06

4.0E+06

2.0E+06

0.0E+00 0.0E+00 2.0E+06 4.0E+06 6.0E+06 8.0E+06 1.0E+07

3.0E+07 2.5E+07 2.0E+07 1.5E+07 1.0E+07 5.0E+06 0.0E+00 0.0E+00

1.0E+06 8.0E+05 6.0E+05 4.0E+05 2.0E+05

3.0E+05

6.0E+05

2.0E+07

3.0E+07

7.0E+05

y = 0.7956x + 177167 R² = 0.5016 (P < 0.01)

OS-F abundance (Apr. 2014)

OS-C abundance (Apr. 2014)

1.4E+06

0.0E+00 0.0E+00

1.0E+07

6'-SL abundance (Nov. 2013)

GNL abundance (Nov. 2013)

1.2E+06

y = 0.9687x + 1E+06 R² = 0.7277 (P < 0.01)

9.0E+05

1.2E+06

6.0E+05

y = 1.1063x + 85915 R² = 0.4541 (P < 0.01)

5.0E+05 4.0E+05 3.0E+05 2.0E+05 1.0E+05 0.0E+00 0.00E+00

1.00E+05

2.00E+05

3.00E+05

4.00E+05

OS-F abundance (Nov. 2013)

OS-C abundance (Nov. 2013)

Fig. 3

21 ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

7.5E+05 a

4.5E+06 3.0E+06 b 1.5E+06 b

b

b

b

b

b

OS-B abundance

6'-SLN abundance

6.0E+06

0.0E+00 Nov Dec

Jan

bc

c c

1.5E+05

c

c

c

Nov

Dec

Jan

Feb

Mar Apr May

1.2E+06 a

2.5E+05 2.0E+05

OS-G abundance

OS-D abundance

3.0E+05

Oct

ab

1.5E+05 bc

bc c

5.0E+04

c

c

c

0.0E+00

a

9.0E+05 ab 6.0E+05 bc 3.0E+05

c c

c

c

c

0.0E+00 Oct

Nov Dec

Jan

Feb Mar Apr May

8.0E+06

Oct

ab 6.0E+06

bc c

4.0E+06

c c

c

c

2.0E+06

Nov Dec

Jan

Feb Mar Apr May

4.0E+05

a

OS-F abundance

OS-A abundance

ab 4.5E+05

Feb Mar Apr May

3.0E+05

a

3.0E+05

ab

ab

Mar

Apr May

bc c 2.0E+05

c

c

c

1.0E+05 0.0E+00

0.0E+00 Oct

Nov Dec

Jan

Feb Mar Apr May

4.0E+06

Oct

Jan

Feb

a

ab 3.0E+06

Nov Dec

1.5E+06

a ab

b b

b

b

b

2.0E+06 1.0E+06

DSL abundance

Tri-a abundance

a

6.0E+05

0.0E+00 Oct

1.0E+05

Page 22 of 24

0.0E+00

1.2E+06 bc

9.0E+05

b

bcd 6.0E+05

d

d

d

cd

3.0E+05 0.0E+00

Oct

Nov Dec

Jan

Feb Mar Apr May

Oct

Nov Dec

Jan

Feb Mar Apr May

Fig. 4.

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Journal of Agricultural and Food Chemistry

3.0E+07

1.0E+08

2.5E+07

3'-SL abundance

6'-SL abundance

a ab 2.0E+07

b

b

b

b

b

b

1.5E+07 1.0E+07 5.0E+06 0.0E+00

8.0E+07 d

d

cd

ab

a

abc

ab

Feb

Mar Apr May

cd

6.0E+07 4.0E+07 2.0E+07 0.0E+00

Oct

Nov

Dec

Jan

Feb Mar

Apr May

Oct

Nov Dec

Jan

bc

ab

Nov Dec

Jan

a 8.0E+05

Tri-b abundance

OS-E abundance

1.0E+06

ab 6.0E+05 4.0E+05

b b

b

b

b

b

2.0E+05 0.0E+00

1.0E+07 a

8.0E+06 6.0E+06 4.0E+06

abc

ab

cd d

2.0E+06 0.0E+00

Oct

Nov

Dec

Jan

Feb

Mar

Apr May

Oct

6.0E+06

Feb Mar Apr May

8.0E+05 a

a

4.0E+06

a

a

a

a

a

a a

2.0E+06

0.0E+00

OS-C abundance

a

GNL abundance

ab

a 6.0E+05

a

a

a

a

a

4.0E+05 2.0E+05 0.0E+00

Oct

Nov

Dec

Jan

Feb

Mar

Apr May

Oct

Nov Dec

Jan

Feb Mar

Apr May

Fig. 4 (continued)

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