Download Absorption, hepatic metabolism and mammary

EUROPEAN MASTER IN SUSTAINABLE ANIMAL NUTRITION AND FEEDING
The lactating sow
Absorption, hepatic and mammary metabolism and
utilization of dietary nutrients in lactating sows
L.M.G. (Lisanne) Verschuren
8/31/2015
1
SUPERVISORS
Dr. P.K. (Peter) Theil
Senior Researcher
Department of Animal Science
Subdivision Molecular nutrition and cell biology
Aarhus University
Dr. Ir. W.J.J. (Walter) Gerrits
Assistant Professor
Animal Sciences Group
Subdivision Animal Nutrition
Wageningen University
i
Preface
This thesis was completed in partial fulfilment of the requirements for the European Master of Sustainable
Animal Nutrition and Feeding (EM-SANF). This is an European program coordinated by Wageningen University
in a consortium with Aarhus University, Debrecen University and EI Purpan. A full scholarship for the two years
of study was funded by Erasmus Mundus scholarship.
The overall objective of this Master’s thesis was to determine the absorption, hepatic and mammary
metabolism and utilization of dietary nutrients in lactating sows. This was done by means of an animal
experiment and the development of a model. The experimental work was carried out at the Department of
Animal Nutrition and Environment, Research Centre Foulum, Aarhus University.
I would like to thank my supervisors Peter Theil and Walter Gerrits for their guidance and support during the
process. Especially the discussions with Peter regarding the different metabolic processes and his enthusiasm
for finding the right pieces to fit the puzzle helped me a lot to understand the underlying processes and to find
energy and motivation to complete this thesis.
Special thanks to the amazing people I met during this EM-SANF course. The last two years have been the best
time of my life and I am convinced that the formed friendships are going to last forever. The EM-SANF family
made any place in the world feel like home, because home is where the heart is.
Thank you also to my best friend Sasha and my family back in the Netherlands, who have never doubted my
abilities and have always supported my choices, even though it meant that I was seldom at home. Many thanks
to my dad, who guided me through the emotional rollercoaster of life as only he can.
Foulum, August 2015
Lisanne Verschuren
ii
List of tables
Table 1. Apparent total tract digestibility of 77 foodstuffs in dry sows ............................................................... 7
Table 2. Range of digestibility of nutrients in ileum and total tract of sows fed low-fiber, high-fiber and highfiber................................................................................................................................................................... 8
Table 3. Difference in plasma concentrations between the mesenteric artery and portal vein, and absorption in
sows fed low fiber, high soluble fiber, or high insoluble fiber ............................................................................. 9
Table 4. Energy sources for ATP production in the TCA cycle in the liver of lactating sows. .............................. 28
Table 5. Glucose utilization and metabolism in the mammary gland in lactating sows. ..................................... 28
Table 6. Energy sources for ATP production in the TCA cycle in the mammary gland of lactating sows. ............ 29
Table 7. Fatty acid and glycerol synthesis in the mammary gland of lactating sows. ......................................... 29
Table 8. Distribution of dietary glucose uptake by several organs in the lactating sow ..................................... 31
Table 9. Distribution of dietary energy uptake by several organs in the lactating sow ...................................... 32
Table 10. Sensitivity analysis of milk characteristics on glucose distribution in the mammary gland of lactating
sows ................................................................................................................................................................ 32
Table 11 Dietary ingredients and chemical composition of the diet .................................................................. 42
Table 12 Feed and water intake, digestibility and milk production of sows....................................................... 43
Table 13 Arterial variables ............................................................................................................................... 44
Table 14 Portal variables .................................................................................................................................. 45
Table 15 Hepatic variables ............................................................................................................................... 46
Table 16 Blood and plasma flows ..................................................................................................................... 47
Table 17 Mammary extraction ......................................................................................................................... 47
Table 18. Arterial variables .............................................................................................................................. 48
Table 19. Abbreviations used in the model ...................................................................................................... 49
Table 20. Main names and formulas used in the model for several nutrients ................................................... 50
Table 21. Name of the flows and formulas used to calculate nutrient metabolism and utilisation in the liver and
mammary gland............................................................................................................................................... 51
Table 22. Parameters and their value as used in the model .............................................................................. 55
List of figures
Figure 1. Ratio of individual SCFA against total SCFA at basal conditions and reduced buffer SCFA concentration
........................................................................................................................................................................ 10
Figure 2. Glycolysis, gluconeogenesis and tricarboxylic acid cycle..................................................................... 13
Figure 3. Fatty acid metabolism ....................................................................................................................... 14
Figure 4. Net portal and net hepatic fluxes of amino acids in growing pigs ....................................................... 15
Figure 5. Comparison of lactation curves with changing litter gain and litter size ............................................. 18
Figure 6. Flow diagram of the liver fluxes ......................................................................................................... 24
Figure 7. Flow diagram of the fluxes in the mammary gland ............................................................................. 26
Figure 8. Non esterified fatty acid flows and arterial concentration in the lactating sow at d 17 ....................... 30
Figure 9. Relationship between arterial non esterified fatty acidconcentration and mammary uptake of NEFA 30
Figure 10. Glucose flows in the lactating sow at d 17 ....................................................................................... 31
iii
List of abbreviations
Adenosine triphosphate
Amino acid
Apparent ileal digestibility
β-Hydroxybutyrate
Coenzyme-A
Crude protein
Ether extract
Flavin adenine dinucleotide
Gastro intestinal tract
Long chain fatty acid
Neutral detergent fiber
Nicotinamide adenine dinucleotide
Non starch polysaccharide
Organic matter
p-aminohippuric acid
Short chain fatty acid
Standardized ileal digestibility
Tricarboxylic acid cycle
ATP
AA
AID
BHBA
CoA
CP
EE
FADH
GIT
LCFA
NDF
NADH
NSP
OM
pAH
SCFA
SID
TCA cycle
iv
Table of Contents
1.
Abstract ..................................................................................................................................................... 3
2.
General introduction .................................................................................................................................. 4
3.
Literature review........................................................................................................................................ 6
3.1.
Introduction ....................................................................................................................................... 6
3.2.
Nutrient digestion and absorption across the GIT ............................................................................... 7
3.2.1.
Ileal digestibility .......................................................................................................................... 7
3.2.2.
Hindgut fermentation ................................................................................................................. 8
3.2.3.
Absorption dynamics .................................................................................................................. 8
3.3.
3.3.1.
Blood and plasma flow.............................................................................................................. 10
3.3.2.
Glucose and glycogenic substances ........................................................................................... 11
3.3.3.
Fat ............................................................................................................................................ 12
3.3.4.
Amino acids .............................................................................................................................. 14
3.4.
Mammary metabolism and utilisation .............................................................................................. 15
3.4.1.
Blood and plasma flow.............................................................................................................. 15
3.4.2.
Nutrient uptake ........................................................................................................................ 16
3.4.3.
Nutrient utilization ................................................................................................................... 16
3.4.4.
Milk secretion ........................................................................................................................... 18
3.5.
4.
Hepatic metabolism and utilization .................................................................................................. 10
Conclusion........................................................................................................................................ 19
Materials and Methods ............................................................................................................................ 20
4.1.
Experiment ....................................................................................................................................... 20
4.1.1.
Animals and surgery ................................................................................................................. 20
4.1.2.
Recovery, housing and feeding ................................................................................................. 20
4.1.3.
Blood and milk sampling of sows .............................................................................................. 21
4.1.4.
Sow performance registrations ................................................................................................. 21
4.1.5.
Analytical Procedures ............................................................................................................... 22
4.1.6.
Calculations and statistical analysis ........................................................................................... 23
4.2.
Model .............................................................................................................................................. 23
4.2.1.
GIT ............................................................................................................................................ 23
4.2.2.
Liver ......................................................................................................................................... 23
1
5.
4.2.3.
Mammary gland ....................................................................................................................... 25
4.2.4.
Sensitivity analysis .................................................................................................................... 25
4.2.5.
Validation ................................................................................................................................. 26
Results ..................................................................................................................................................... 27
5.1.
5.1.1.
Sow performance ..................................................................................................................... 27
5.1.2.
Metabolites in plasma/blood .................................................................................................... 27
5.2.
6.
Experiment ....................................................................................................................................... 27
Model .............................................................................................................................................. 27
5.2.1.
GIT ............................................................................................................................................ 27
5.2.2.
Liver ......................................................................................................................................... 28
5.2.3.
Mammary gland ....................................................................................................................... 28
5.2.4.
Post prandial changes ............................................................................................................... 30
5.2.5.
Utilization of dietary starch and energy..................................................................................... 31
5.2.6.
Sensitivity analysis .................................................................................................................... 32
5.2.7.
Validation ................................................................................................................................. 32
Discussion ................................................................................................................................................ 33
6.1.
Reliability and accuracy model ......................................................................................................... 33
6.2.
Hepatic and mammary oxidation ...................................................................................................... 33
6.3.
Post prandial changes ....................................................................................................................... 34
6.4.
Mammary plasma/blood flow .......................................................................................................... 34
6.5.
Mammary de novo fat synthesis ....................................................................................................... 35
6.6.
Milk composition .............................................................................................................................. 36
6.7.
Utilization of dietary starch and energy ............................................................................................ 36
7.
Conclusion ............................................................................................................................................... 37
8.
References ............................................................................................................................................... 38
Appendix A ...................................................................................................................................................... 42
Appendix B ...................................................................................................................................................... 43
Appendix C ...................................................................................................................................................... 44
Appendix D ...................................................................................................................................................... 48
Appendix E ...................................................................................................................................................... 49
2
Abstract
Due to large litters, high growth rate and low body fat % the milk production load on lactating sows has
increased over the years. Knowledge of nutrient utilization and metabolism is highly important to sustain a
proper milk production. Therefore, the objective of this study was to determine the absorption, hepatic and
mammary metabolism and utilization of dietary nutrients in lactating sows, by means of developing a dynamic
model based on results of animal experiments. Four second parity sows (Danish Landrace x Yorshire) were
fitted with catheters in an artery, the portal vein, the hepatic vein and the mesenteric vein (for infusion). Blood
was collected at d -10, -3, 3 and 17 to parturition. With the results of this experiment a model was built in
SMART©, having 18 state variables and 17 zero pools, representing nutrient pools in the 3 sub models of the
GIT, liver, and mammary gland. The assumptions made were based on common knowledge and information
available in literature. The mammary gland utilizes 54% of dietary glucose and 59% of dietary energy. In
contrast the liver is the main organ providing energetic sources for the rest of the body, mostly in the form of
lactate (89 mmol/h). The liver mainly oxidizes NEFA (41%), whereas the mammary gland mainly oxidizes
glucose (65%). Mammary de novo fatty acid synthesis was 24% and combined with the cost of de novo fatty
acid synthesis it utilized 37% of the mammary extracted glucose. All in all, glucose is the main energy source
for lactating sows and an adequate starch intake is important for proper milk production.
3
General introduction
The world is expected to continue to grow and with that pork consumption will grow too (FAO, 2009). Together
with the increasing concern about obesity, the demand for lean pork meat is expected to increase. This
resulted in the pig industries focus on large litters, high average daily gain and low back fat (LEI Wageningen
UR, 2015; The Danish Pig Research Centre, 2015). However, as milk yield is positively correlated to litter size
and average daily gain (Toner et al., 1996; Auldist et al., 1998; Nielsen et al., 2002b; Hansen et al., 2012;
Vadmand et al., 2015) and backfat thickness of the sow is genetically correlated to the backfat thickness of
grower finishers (Bergsma, 2011), this leads to an increased milk demand from the sow with less body fat
reserves to sustain this high milk production. From a nutritional point of view, dietary provision of nutrients
and the utilization of these nutrients determine the mobilization of body reserves and the amount of available
substrates for milk production.
One of the first steps in nutrient provision is the digestion of the diet in the gastro intestinal tract (GIT). Ileal
starch digestibility ranges from 91 to 96 % (Jørgensen et al., 2007; Serena et al., 2008), apparent ileal
digestibility (AID) of protein from 61 to 68% (Serena et al., 2008) and ileal fat digestion from 71 to 74% (Serena
et al., 2008). The nutrients not digested in the ileum transfer to the large intestine to be fermented by the
microbes. Acetate is the main product of fermentation (54-65%), followed by propionate (25-34%) and
butyrate (6-7%)(Sappok et al., 2013). The enterocytes of the small intestine primarily use glutamine as their
energy source (Vaugelade et al., 1994), whereas the enterocytes of the large intestine primarily use butyrate
for their energy provision (Herrmann et al., 2011).
When the nutrients are absorbed across the GIT they reach the liver. The liver is an important organ for
homeostasis of glucose, fat and AA. It receives a large share of the cardiac blood output, even though it is only
a relatively small organ(Brendemuhl et al., 1989; Kim and Easter, 2001). Glucose homeostasis is mainly
maintained by glycogen formation and degradation, and the liver uses energy sources other than glucose to
sustain its own function (Kristensen et al., 2009; Theil et al., 2013). Propionate is most likely the most
important energy source for the liver (Ingerslev et al., 2014). Fat homeostasis is especially important during
lactation, as a lot of NEFA are released into the bloodstream (Kraetz et al., 1998). NEFA can be broken down for
ATP production, and unlike in other high milk producing mammals, sows do not produce a lot of ketone bodies
(Theil et al., 2013). This is because of low mitochondrial HMG-CoA synthase activity (Barrero et al., 2001). AA
are also utilized, but the liver mainly produces ketoacids for the rest of the body (Kristensen and Wu, 2012).
In order to quantify the nutrient uptake by the mammary gland, mammary blood/plasma flow has to be
estimated. However, mammary blood and plasma flow are difficult to measure due to the anatomy of the sow
mammary gland (Trottier et al., 1995), but plasma flow is expected to range between 4000 and 7000 L/d
(Farmer et al., 2008). Mammary uptake of nutrients is fairly constant for glucose (Linzell et al., 1969; Spincer et
al., 1969; Spincer and Rook, 1971; Renaudeau et al., 2003) and essential AA (Linzell et al., 1969; Spincer et al.,
1969; Spincer and Rook, 1971; Trottier et al., 1997; Renaudeau et al., 2003), but NEFA uptake depends on the
time after feeding (Dourmad et al., 2000). 53% of the glucose taken up from the blood by the mammary gland
is used for lactose production and the rest of the glucose is used for oxidation and fatty acid synthesis (Linzell
et al., 1969). Nutrients metabolized in the mammary gland are excreted in the milk. Milk yield is highly
influenced by litter size and litter gain, but the milk composition is fairly constant later on in lactation (Hansen
et al., 2012). The methods for estimating milk yield are not ideal, but a combined analysis gives a fairly reliable
result (Hansen et al., 2012).
4
The most recent research estimating nutrient utilization in the mammary gland of lactating sows was by Theil
et al. (2012) through the development of a model based on literature. However, the most recent study
experimentally quantifying nutrient metabolism and utilization dates back to 1971 (Spincer and Rook, 1971). To
the authors knowledge there is not yet research published about the nutrient utilization and metabolism in the
liver, let alone a study combining the knowledge of mammary and hepatic nutrient flows. With the increasing
demand on lactating sows, it is important to quantify the allocation of nutrients within the sows’ body.
Therefore, the objective of this study was to determine the absorption, hepatic and mammary metabolism and
utilization of dietary nutrients in lactating sows, by means of developing a dynamic model based on results of
animal experiments.
5
Literature review
1.1. Introduction
It is expected that the world population will continue to grow, with estimates of 9.6 billion people in 2050
(United Nations, 2013). The main growth will come from developing countries, while the growth in developed
countries is expected to stagnate (United Nations, 2013). Combined with the expectation of growing income
and urbanization in developing countries, is it predicted that there will be an increase in meat demand of 200
million tonnes (FAO, 2009). Worldwide pork production was 109 million tonnes in 2010 and accounted for a
36.9% of total meat production (FAO, 2013). However, in 2007 the share in pork consumption was 38.9% of
total meat consumption (Alexandratos and Bruinsma, 2012). If the distribution of meat consumption remains
the same, this will result in a need for more than 180 million tonnes of pork in 2050. At the same time, obesity
is of increasing concern all over the world, but especially in western countries. Therefore, consumers are
increasingly aware of fat consumption and demand lean meat.
The need for more and leaner pork with less input drove the pig industry to higher efficiencies. Piglets
produced per sow per year (sows), average daily gain (grower-finishers), and lean meat percentages (grower
finishers) are the most important traits. Both the Netherlands and Denmark have improved these three traits
during the last decade. In the Netherlands, piglets produced per sow per year was increased by 5.9 units from
2002 to 2014 (LEI Wageningen UR, 2015) and in Denmark this was 7.3 units from 1994 to 2013 (The Danish Pig
Research Centre, 2015). Average daily gain was improved by 33 units over the last 12 years in the Netherlands
(LEI Wageningen UR, 2015) and also in Denmark the average daily gain increased (The Danish Pig Research
Centre, 2015). In Denmark, the average genetic progress in lean meat of Duroc, Landrace and Yorkshire was
0.10% during the last 4 years (The Danish Pig Research Centre, 2015), whereas in the Netherlands, the lean
meat percentage of fatteners was increased by 2.9% in the last 10 years (LEI Wageningen UR, 2015). In the
future an improved litter size (part of piglets produced per sow per year), average daily gain and lean meat
percentage are to be expected at least due to genetic progress (The Danish Pig Research Centre, 2015).
The increased litter size, improved average daily gain and decreased fat content in pigs influences milk
production in sows. Milk yield and colostrum yield are positively correlated to litter size (Toner et al., 1996;
Auldist et al., 1998; Nielsen et al., 2002b; Vadmand et al., 2015). However, in early lactation milk yield is mostly
related to litter size and later in lactation litter gain becomes the main predictor for this trait (Hansen et al.,
2012). Therefore, the increase in litter size and average daily gain over the years increased the demand for milk
production in the sows. During lactation, sows mobilize body reserves to sustain this milk production, as feed
intake is not sufficient to cover nutrient requirements in high lactating sows. Due to the genetic trend of
increased lean meat percentage in grower-finishers sows have a decreased fat reserve too, as the backfat
thickness in grower-finishers is genetically correlated to the fat mass of the sow (Bergsma, 2011). Sows with a
high genetic capacity for lean tissue growth mobilize less fat during lactation compared to sows with a low
genetic capacity (Sauber et al., 1998; Cameron et al., 2002). As a result, they mobilize more protein to sustain
milk production (Sauber et al., 1998; Kim and Easter, 2001). Overall, the lactating sow has changed a lot over
the years and is challenged increasingly during production. From a nutritional point of view, dietary provision
of nutrients and the utilization of these nutrients determine the mobilization of body reserves and the amount
of substrates available for milk production. Therefore, the objective of this literature review was to determine
the absorption, hepatic and mammary metabolism and utilization of dietary nutrients in lactating sows, with
the main focus on glucose.
6
1.2. Nutrient digestion and absorption across the GIT
1.2.1. Ileal digestibility
Most of the dietary nutrients are digested and absorbed in the ileum. In sows, dietary recommendations are
based on the ratio between protein and energy. As the amino acid (AA) content and ratio varies in protein,
feed recommendations are given on the basis of ileal AA digestibility. However, due to endogenous losses
measured dietary AA digestibility appears lower than was actually true and, therefore, there is a distinction
between AID, which does not correct for endogenous losses, and standardized ileal digestibility (SID), which
does correct for endogenous losses. Table 1 shows the average apparent total tract digestibility of 77
foodstuffs measured in dry sows. In the same research, a regression analysis of the 77 foodstuff digestibilities
in sows revealed that ether extract (EE) digestibility was influenced by fat content and neutral detergent fiber
(NDF) content; NDF digestibility by NDF content only; crude protein (CP) digestibility by CP, NDF and ash
content; organic matter (OM) digestibility by NDF and ash; and energy digestibility by NDF and ash (Le Goff and
Noblet, 2001). As NDF influenced all digestibilities, it appears to be a major component in feed digestion.
Research comparing 2 levels of fiber (high versus low) and 2 solubilities of fiber (soluble versus insoluble) found
that higher fiber levels caused lower ileal digestibility of AA, carbohydrates, starch and NSP and higher
solubility caused better CP digestibility (Serena et al., 2008). Table 2 shows the range of ileal and total tract
nutrient digestibility as found in this research.
Dietary carbohydrates are the main glucose providers in sows and ileal digestibilities of starch and sugar range
between 91 to 96% (Jørgensen et al., 2007; Serena et al., 2008). In sows, non-starch polysaccharide (NSP)
fermentation already starts in the small intestine and 23 to 41% of the NSP has disappeared at the terminal
ileum (Jørgensen et al., 2007; Serena et al., 2008). AID of protein varies between 61 and 68% (Table 2), but can
depend on the metabolic stage. Stein et al. (1999) found that lactating sows have a lower AID of protein
compared to gestating sows when fed canola meal and corn based diets, but there was no difference when
averaged over all 6 diets tested (Stein et al., 1999). When nonspecific endogenous losses are taken into
account, metabolic stages affect protein digestibility even more, as SID of protein is lower in lactating than
gestating sows (77.8 and 86.7% respectively) when averaged over all 6 different diets examined (Stein et al.,
2001). Ileal digestibility of fat is 71 to 74% (Table 2) and is unaffected by fiber level or solubility. However, total
tract digestibility is increased by increased fiber solubility and ranges between 67 to 71% (Serena et al., 2008).
In contrast, Le Goff and Noblet (2001) found an average fat digestibility of 37.1% (Table 1), but this difference
might be explained by the low fat content, as the fat digestibility increased with increasing fat content.
Table 1. Apparent total tract digestibility (AID) (% of intake) of 77 foodstuffs in dry sows (Le Goff and Noblet, 2001)
Chemical analysis
Organic matter
Crude protein
Ether extract
Crude fiber
Nitrogen-free extract
NDF
ADF
Fiber
Energy
AID (%)
87.6
84.9
37.1
51.7
92.3
64.4
48.9
59.5
85.2
7
Table 2. Range of digestibility (% of intake) of nutrients in ileum and total tract of sows fed low-fiber, high-fiber (soluble NSP) and
high-fiber (insoluble NSP) diets (Serena et al., 2008)
Item
Ash
Organic matter
Crude protein
Fat
Carbohydrates
Starch
Total non-starch polysaccharides
Cellulose
Non-cellulosic polysaccharides
Soluble non-starch polysaccharides
Ileum (%)
- 35 - -23
51 - 75
61 - 68
71 -74
51 - 84
91 - 96
23 - 41
4 - 11
34 - 50
32 - 67
Total tract (%)
12 - 29
72 - 84
68 - 82
67 - 71
79 - 89
97 - 99.9
48 - 78
9 - 72
60 - 82
-
1.2.2. Hindgut fermentation
Nondigested carbohydrates and protein reach the large intestine and become available to microbes for
fermentation. Overall carbohydrate disappearance is 79 to 89 %, depending on the fiber level (Table 2). Of this,
almost all nondigested starch disappears fully in the large intestine independently of fiber level. In contrast,
NSP fermentation is highly variable and increases with increased fiber level (Jørgensen et al., 2007; Serena et
al., 2008). Similarly to the ileal digestibility, total tract protein disappearance is only affected by solubility of the
fiber and ranges between 68 and 82% (Table 2). This is in contrast to the findings of Le Goff and Noblet (2001),
who found an average of 84.9% over 77 foodstuffs measured (Table 1).
Short chain fatty acids (SCFA) are the main products of microbial fermentation and total in vitro SCFA
production ranges from 645 to 751 mg per gram AA in pure fiber sources. Acetate is the main product of
fermentation (54-65%), followed by propionate (25-34%) and butyrate (6-7%) (Sappok et al., 2013). Fiber
composition influences the balance between the SCFA, as arabinoxylans and resistant starch stimulate butyrate
production (Van der Meulen et al., 1997; Knudsen et al., 2005; Rideout et al., 2008), β-glucan stimulates
propionate production (Theil et al., 2011b) and cellulose stimulates acetate production (Giusi-Perier et al.,
1989). Overall SCFA production is also influenced by availability of protein for fermentation and source of
protein influences fermentability of the protein in vitro (Cone et al., 2005).
1.2.3. Absorption dynamics
At the apical brush border, glucose is transported into the intestinal epithelial cell by SGLT-1 (Wright and Turk,
2004; Cottrell et al., 2006) and fructose is transported by GLUT5 and/or GLUT2 (Cottrell et al., 2006), whereas
transport at the basolateral membrane of both is facilitated by GLUT2 (Thorens, 1996). As with glucose, most
AA are co-transported with sodium across the small intestinal wall, albeit by different transporters (Solberg and
Diamond, 1987; Rhoads et al., 1990; Grøndahl and Skadhauge, 1997). According to the model of Chillarón et al.
(1996), neutral AA absorption from the intestinal lumen is driven by a Na+ gradient and the gradient of neutral
AA is used to drive cationic AA uptake (Van Winkle, 2000). Peptide absorption at the brush border plays an
important role in AA absorption, as most AA in the form of peptides have a higher absorption than free AA
(Rerat et al., 1992; Morales et al., 2015). PEPT1 is the main peptide transporter and
8
Table 3. Difference in plasma concentrations (0 to 10 h post feeding) between the mesenteric artery and portal vein, and absorption
(AV difference x blood flow) in sows fed low fiber (LF), high soluble fiber (HFS), or high insoluble fiber (HFI). Adapted from (Serena et
al., 2009)
Item
AV difference
Total SCFA (µmol/L)
Acetate (% of total SCFA)
Propionate (% of total SCFA)
Butyrate (% of total SCFA)
Valerate (% of total SCFA)
Caprionate (% of total SCFA)
LF
HFS
HFI
575
54
30
10
2
0
1258
60
26
9
2
1
984
62
26
8
2
1
Absorption (mmol/h)
Glucose
SCFA
Lactate
419
133
49
124
321
44
189
218
43
only transports di- and tri- peptides (Winckler et al., 1999; Klang et al., 2005). Free fatty acids and 2-monoglycerides are combined with phospholipids and cholesterol to form mixed micelles and are absorbed from the
micelles by the enterocyte by passive diffusion (Green and Riley, 1981; Ling et al., 1989) or active transport
(Stremmel, 1988; HOWARD, 1993; Abumrad et al., 1998) by FATP4, CD36 and LACS (Stahl et al., 2001; Hansen
et al., 2003). In the enterocyte, fatty acids are reesterified to form triglycerides, packaged into chylomicrons,
released into the lymph system and drained into the blood stream at the thoracic duct (Tso and Balint, 1986;
Thomson et al., 1989).
An average of 124 to 419 mmol/h of glucose is absorbed across the intestinal wall (Table 3) and absorption is
highly depended upon time and diet (Serena et al., 2009). 93% of mucosal absorbed glucose is released into the
portal blood (Lang et al., 1999). However, glutamine is the main energy source for ileal enterocytes, as
contribution of glutamine to ATP production is two to three times higher than glucose (Vaugelade et al., 1994).
In the enterocytes lactate and pyruvate are produced from glucose and released into the portal blood. During
the first hour after feeding, lactate and pyruvate released from the intestinal muscle tissue were four times
higher than that produced by enterocytes (Vaugelade et al., 1994). The combined intestinal glycolysis results in
an average intestinal lactate absorption of 43 to 49 mmol/h (Table 3). Next to glutamine oxidation, several
other AA are metabolized, as there is an ammonia production of 0.92 nmol/min/[106 cells] unexplained by
glutamine oxidation and a total net production of glutamate, aspartate and alanine (Vaugelade et al., 1994).
Steendam et al. (2004) estimated that 0-6% of dietary N is retained in the portal drained viscera and individual
AA absorption is very variable, since the absorption of essential AA after enzymic milk-protein hydrolysate
infusion ranges from 4 to 43% (mean 34%) and for nonessential AA from 1 to 41% (mean 17%) (Rerat et al.,
1992). In rats, absorption of long chain fatty acids (LCFAs) is 22 to 83% (average 56%), and 28 to 79% (average
56%) of absorbed LCFA are transported through the lymphatic system, but both absorption and portal vein
transport decreases at increasing infusion rates (McDonald et al., 1980). Fatty acid absorption is higher when
the fatty acids have a shorter chain length (Tomarelli et al., 1968), higher unsaturation (Tomarelli et al., 1968)
and sn-2 position on the triglyceride (Tomarelli et al., 1968; Christensen et al., 1995; Innis and Dyer, 1997; Innis
et al., 1997).
9
Figure 1. Ratio of individual SCFA against total SCFA at basal conditions (mucosal pH 7.4 and 80 mmol/L SCFA) and reduced buffer
SCFA concentration. Significant variances between individual SCFA are indicated by (*) for P≤0.05, (**) for P≤0.01 and (***) for
P≤0.001. (Herrmann et al., 2011)
SCFA are present in ionic and non-ionic forms and are absorbed by SCFA-/HCO3- exchange and diffusion
respectively (Von Engelhardt et al., 1995). An average of 133 to 321 mmol/h of SCFA are absorbed across the
intestinal wall and total SCFA absorption depends on dietary fiber level and solubility (Table 3)(Serena et al.,
2009). Acetate is absorbed and released by the intestinal cells at the highest amounts, followed by propionate
and butyrate (Figure 1 and Table 3). However, butyrate is the main energy source for the duodenal cells, as 20
to 30% of the mucosal absorbed butyrate is released at the serosal site, whereas for acetate this is 41 to 45%
and for propionate 34 to 37% (Herrmann et al., 2011). The luminal SCFA concentration influenced the relative
ratio of serosal release between acetate, propionate and butyrate only in comparison to butyrate, which
further shows the demand of the duodenal cell for butyrate (Figure 1) (Herrmann et al., 2011).
In short, ileal nutrient digestibilities are highly variable and are mainly affected by fiber source and level.
Hindgut fermentation is also highly affected by fiber, as it is the main source for fermentation. Acetate,
propionate, and butyrate are the SCFAs produced most, in ratio of 5:3:1. Glucose and AA are absorbed across
the intestinal wall mostly by active transport and are released into the portal blood, whereas fatty acids are
passively transported across enterocytes to be released into the lymph system. For the enterocytes in the small
intestine glutamate is the main energy source, and for the large intestinal cells butyrate is the main energy
provider.
1.3. Hepatic metabolism and utilization
1.3.1. Blood and plasma flow
The liver is a highly active organ and produces 31% of the heat in lactating sows even though it only weights 1
to 2 % of total live weight (Brendemuhl et al., 1989; Kim and Easter, 2001). Blood is supplied to the liver by the
portal vein and the hepatic artery and the liver is drained by the hepatic vein. In growing pigs (60 kg) the liver
blood flow is approximately 3 L/min (Ingerslev et al., 2014). 85 % of the afferent blood is accounted for by the
portal vein, whereas the other 15 % is coming from the hepatic artery (Kristensen et al., 2009). The liver
receives 31 % of the cardiac output (Upton, 2008) and receives oxygen through both the portal vein and
hepatic artery, as only 30% of the oxygen is used by the portal drained viscera (Kristensen et al., 2009). In the
10
liver, hepatocytes take up the nutrients and either utilize them for their own energy expenditure or metabolize
and excrete them for utilization by the rest of the body.
1.3.2. Glucose and glycogenic substances
In cells, the main precursor for energy generation is glucose. One glucose molecule is catalyzed into two
pyruvate molecules during glycolysis in the cytosol of the hepatocyte. Figure 2 shows the process of glycolysis.
During the glycolysis of glucose into pyruvate two adenosine triphosphate (ATP) and two nicotinamide adenine
dinucleotide (NADH) are formed. ATP can directly be used as an energy source by the cells, but NADH has to be
transformed into ATP in the mitochondria. Every NADH from the cytosol consumes ½ an oxygen and produces
3 ATP, but 1 ATP is lost during the transport across the mitochondrial membrane. After glycolysis the two
pyruvate molecules are transported across the mitochondrial membrane and in the mitochondria the pyruvate
is transformed into Acetyl Coenzyme-A (CoA), releasing one CO2 and one NADH per pyruvate molecule. Acetyl
CoA enters the tricarboxylic acid cycle (TCA) cycle (see Figure 2), producing 2 CO2, 3 NADH and 1 flavin adenine
dinucleotide (FADH). NADH and FADH in the mitochondria produce 3 ATP and consume half an O2 per
molecule. The overall reaction of glucose oxidation is:
C6H12O6 +10 NAD+ +2 UQ +2 ADP +2 Pi +2 GDP + 2 Pi + 4 H2O → 6 CO2 + 10 NADH + 10 H++2 UQH2+2 ATP+2 GTP
However, in lactating sows the net hepatic uptake of glucose is small (Flummer et al., 2012). Glucose is not the
only source that can be oxidized in the TCA cycle, as glycerol, lactate, AA and propionate can enter the
pathways at different points too. Glycerol enters the pathway as dihydroxyacetone phosphate, which produces
1 NADH, and is metabolized into pyruvate to enter the TCA cycle. Glycerol is a C-3 molecule and produces a
total of 2 ATP, 6 NADH, 1 FADH and 3 CO2. Lactate is transformed into pyruvate, which is catalyzed by the
enzyme lactate dehydrogenase (EC 1.1.1.27) while protonating NAD+ to NADH (Everse and Kaplan, 1973;
Stryer, 1988). Total oxidation of lactate therefore results in 5 NADH, 1 FADH and 3 CO2. The AA have three
pathways to produce energy, either by being transformed into pyruvate or Acetyl CoA or by entering the TCA
cycle as intermediates. The AA transformed into pyruvate or that enter the TCA cycle as intermediates are
called glycogenic, the ones giving Acetyl CoA are called ketogenic. Only Lysine and Leucine are strictly ketogenic
(Bender, 2014). The AA entering the TCA cycle as intermediate of the TCA cycle only add to the pool of
intermediates and in order to generate ATP oxaloacetate is removed from the cycle and transformed into
pyruvate. Propionate enters the TCA cycle at succinyl CoA and follows the same path as AA added to the TCA
cycle.
During lactation the sow’s plasma glucose is increased compared to before parturition (Theil et al., 2013; Loisel
et al., 2014). Plasma glucose is either coming from the diet or is produced in the liver through gluconeogenesis,
which is reversed glycolysis except for 4 distinct enzymes. Figure 2 shows the process of gluconeogenesis.
There are four sources for gluconeogenesis: lactate, glycerol, glycogenic AA and propionate. These molecules
for gluconeogenesis enter at the same point as for oxidation, except that now they are used to produce
glucose. In this way, two C-3 molecules produce one glucose molecule. The glycogenic AA have two pathways
to produce glucose. Six AA can be transformed directly into pyruvate (Serine, Cystein, Alanin, Glycine,
Methionin and Tryptophan), while other glycogenic AA enter the TCA cycle and produce glucose through the
transformation to oxaloacetate (Berg et al., 2002). Two lactate molecules produce one glucose molecule, but
as the plasma lactate level is increased during lactation in sows (Theil et al., 2013) and also in grower pigs, a net
lactate production is found (Kristensen et al., 2009), it is unlikely that lactate is used for glucose production.
11
Propionate in grower finishers is almost fully extracted at 94% (Ingerslev et al., 2014), and is most likely an
important energy source in the liver.
The liver is the main organ regulating blood glucose levels, which is done by storing glucose in the form of
glycogen. In new born piglets, the liver stores 9.6 g/100 g liver (Theil et al., 2011a), but as new born piglets rely
more on glycogen storage than adult sows it is expected that this will be less in lactating sows. Right after
feeding, glucose levels are high and glucose is stored in the form of glycogen. In contrast, during fasting the
glucose levels are low and glycogen is mobilized. For glycogen synthesis, glucose is combined with UTP to form
UDP-glucose. UDP-glucose is then added to the non-reducing terminal residues of glycogen, increasing the
length of the glycogen molecules and leaving UDP as a product. Glycogen breakdown is facilitated by four
enzymes, one degrading the glycogen, two remodeling the glycogen so that it remains a substrate for
degradation, and one converting the breakdown product. The result, glucose 6-phosphate, is hydrolyzed to
free glucose by glucose 6-phosphatase (EC 3.1.3.9), an enzyme absent from most other tissues. The synthesis
and breakdown of glycogen are reciprocally regulated by glucagon and epinephrine, preventing synthesis and
breakdown from occurring at the same time (Berg et al., 2002).
1.3.3. Fat
The lactating sow mobilizes fat from body reserves, causing fat in the form of non-esterified fatty acids (NEFA)
to be released in the blood (Kraetz et al., 1998). As lactation progresses plasma concentrations of NEFA
increase and higher demands result in higher NEFA concentrations (Kraetz et al., 1998). However Theil et al.
(2013) found that the NEFA concentration was only elevated during the first days after parturition, most likely
because they are fed high fat diets having a higher metabolizable energy content than the diets used by Kraetz
et al. (1998), and the energy balance is most negative during the first days. The liver is the main organ
metabolizing fat products.
As the porcine liver has very low activities of the enzymes for de novo synthesis of fatty acids, this is not a
major pathway in pigs (Kristensen and Wu, 2012). However, NEFA absorbed by the liver can still be used for fat
synthesis. For the synthesis of fat, or triaglycerol, three fatty acids are esterified with a glycerol molecule. In
every reaction one fatty acid, in the form of fatty acyl CoA, is esterified with glycerol. The formation of fatty
acyl CoA from the fatty acid costs one ATP. Three of the enzymes involved in this reaction chain are on both
the outer mitochondrial membrane and endoplasmic reticulum membrane, but one enzyme is only present on
the endoplasmic reticulum membrane (Bender, 2014). The triaglycerols are either stored in the cytosol as lipid
droplets of hepatocytes or excreted to the blood in the form of very low density lipoproteins (VLDL) formed in
the lumen of the endoplasmic reticulum (Berg et al., 2002). VLDL contain next to triaglycerol also cholesterol,
phospholipid and protein. The first week of lactation the protein content increases while the other VLDL
components, which were increased during the last week prior to farrowing, decreased to pre-pregnancy values
(Wright et al., 1995).
Fatty acids can be used as an energy source, even though they cannot be transformed into glucose. In the
absence of malonyl CoA, an intermediate in fatty acid synthesis, fatty acids are transported from the cytosol to
the mitochondrial matrix and oxidized through β-oxidation. Every cycle one Acetyl CoA is produced and the
chain is shortened by two C atoms (Berg et al., 2002). During every cycle 1 NADH and 1 FADH2 are produced, as
can be seen in Figure 3. Butyrate and acetate are also precursors for acetyl CoA production in the cell cytosol
(Berg et al., 2002). Acetyl CoA can enter the TCA cycle, and be transformed into ketone bodies or into acetate.
In lactating sows, β-Hydroxybutyrate (BHBA) is the most important ketone body as plasma BHBA levels are
between 34 and 38 µM and acetoacetate and acetone together are between 15 and 18 µM (Theil et al., 2013).
12
Figure 2. Glycolysis, gluconeogenesis and tricarboxylic acid cycle (TCA) cycle. Text in purple releases energy sources, in red O2
consuming energy sources. Red arrows are pathways requiring different enzymes and substrates for gluconeogenesis compared to
glycolysis. Modified figure from Nicholson (2002)
13
Figure 3. Fatty acid metabolism. Text in purple releases energy sources, in red O2 consuming energy sources, in blue produced in the
pentose phosphate pathway. Modified figure from Bender (2014)
The production of acetate is higher than ketone bodies, since plasma acetate levels are 5 times higher than
BHBA levels (Theil et al., 2013). Other contributors for acetate are the peroxisomes, which have a membrane
permeable to fatty acids. In here fatty acids are oxidized into acetate by formation of H 2O2 and at the cost of
NADH and ½ an O2 molecule (Stryer, 1988; Ingvartsen, 2006). However, not all acetate in plasma is produced by
the liver as acetate is the main product of hindgut fermentation. When compared to other species the pig liver
produces only minor amounts of ketone bodies, because of low mitochondrial HMG-CoA synthase activity
(Barrero et al., 2001).
1.3.4. Amino acids
The liver is an important organ in the metabolism of AA, as notable amounts of non-essential AA are
synthesized in the liver, nitrogen and carbon metabolism are linked by AA catabolism, and α-ketoacids of all
essential AA are converted to AA (Kristensen and Wu, 2012). Figure 4 shows the net portal and hepatic AA
fluxes in grower finishers (60 kg). Except for aspartate, glutamate, isoleucine, threonine, and valine, all AA have
a net hepatic absorption. The absorbed AA may be used to synthesize other AA or glucose, oxidized to produce
ATP, or released as their respective ketoacid. When AA are used to produce other AA the amino-group of the
donor AA is transferred onto the enzyme leaving the respective ketoacid of the donor AA. The acceptor, a
different ketoacid, receives the amino group from the enzyme resulting in a new AA. This process is called
transamination, which is also important when AA are oxidized, used for gluconeogenesis, or excreted as
ketoacids. In this case the acceptor ketoacid is α-ketoglutarate, forming the AA glutamate. However, glutamate
is deaminated to form ammonium and α-ketoglutarate. Every nitrogen atom from this deamination is bound to
another nitrogen atom, derived from free ammonia, and a carbon atom, derived from hydrated CO 2, to form
urea. Only some AA can be directly oxidized (Bender, 2014). The resulting ketoacid from the donor AA is then
entering the TCA cycle or is released to the blood.
In grower finishers there is a net urea production (Kristensen et al., 2009) and in lactating sows there is a small
net disappearance of branched-chain AA in late gestation (Flummer et al., 2012), indicating either oxidation of
AA, gluconeogenesis, or excretion of ketoacids by the liver of pigs. Alanine, glutamine and glycine are taken up
by the liver in the highest amounts, whereas glutamate is excreted (Figure 4). In grower-finishers, the dietary
uptake of aspartate, glutamate, glutamine, proline, arginine, and glycine is not ideal for protein deposition,
requiring the liver to produce glutamate from either other AA or from glucose and urea
14
Figure 4. Net portal (open bars) and net hepatic (filled bars) fluxes of amino acids in growing pigs (60 kg BW). A positive flux denotes
net release and a negative flux net uptake across the tissues (Kristensen and Wu, 2012)
(Kristensen and Wu, 2012), since glutamate is the amino group donor for most AA (Berg et al., 2002).
However, the AA requirement for lactating sows is different from grower-finisher AA requirement, as lactating
sows use their AA mainly for milk synthesis and mobilize body protein (NCR, 2012). Therefore, it can be
expected that hepatic AA metabolism and utilization in lactating sows shows a different pattern than in
grower-finishers.
In brief, the liver is an important organ for homeostasis of glucose, fat and AA. It receives a large share of the
cardiac blood output, even though it is only a relatively small organ. Glucose homeostasis is mainly kept by
glycogen formation and degradation, and the liver uses other energy sources than glucose to sustain its own
functioning. Propionate is most likely the most important energy source for the liver. Fat homeostasis is
especially important during lactation, as a lot of NEFA are released into the bloodstream. NEFA can be broken
down for ATP production, and unlike in other high milk producing mammals, in sows there are not a lot of
ketone bodies produced. AA are also utilized, but the liver mainly produces ketoacids for the rest of the body.
1.4. Mammary metabolism and utilization
1.4.1. Blood and plasma flow
Measurement of mammary blood and plasma flow in sows is quite complicated, as the blood is supplied by
arteries at both the anterior and posterior side, the total mammary system is drained by two different veins,
and each individual gland is supplied by several arteries and drained by several veins (Trottier et al., 1995).
Therefore, there is not one direction of blood flow and mixing of blood occurs, making quantification of the
blood and plasma flow difficult. There are several methods proposed to measure blood and/or plasma flow.
Quantification of the plasma flow by means of an internal marker is used by most of the researches (Trottier et
15
al., 1997; Guan et al., 2002; Nielsen et al., 2002a; Nielsen et al., 2002b; Renaudeau et al., 2002; Guan et al.,
2004a; Guan et al., 2004b; Manjarin et al., 2012). In this method it is assumed that the excretion of the internal
marker in the milk is equal to the mammary uptake from the blood. Plasma flow is than explained by the ratio
between the arterial venous differences and the mammary uptake of the marker. Lysine, methionine,
phenylalanine, tyrosine and calcium were used in previous studies and the plasma flow ranged between 2.8
and 4.9 L/min, but the large variation in plasma flow measurements indicate errors in the used estimation
technique (Farmer et al., 2008). External markers can also be used, but they only give results on a daily basis
(Linzell et al., 1969). Renaudeau et al. (2002) used an ultrasonic blood flow probe to estimate blood flow in the
external pubic artery, resulting in a measurement of 4984 L/d. Infusion with p-aminohippuric acid (pAH) was
used for blood flow measurements in the hepatic and portal veins (Kristensen et al., 2009; Flummer et al.,
2012) and a study successfully using indocyanine green in the mammary veins to measure blood flow (Gannon
et al., 1997) indicates the possibility to use pAH as a marker for mammary blood flow measurement. However,
because of the complexity of the mammary vascular system it is difficult to extrapolate these direct
measurements of a couple of mammary glands to the complete mammary system of the sow.
1.4.2. Nutrient uptake
AV differences for glucose range from 0.198 to 0.375 g/L and mammary extraction efficiency is approximately
25 to 31% (Linzell et al., 1969; Spincer et al., 1969; Spincer and Rook, 1971). However, AV differences are
higher after a meal than when animals are starved (Dourmad et al., 2000). The mammary gland contains GLUT
1 transporters, which have a Km value of 1 to 4 mM (Bell et al., 1990). Onset of lactation is marked with a vast
upregulation of GLUT 1 mRNA expression (Theil et al., 2012). Due to its low Km value, glucose is favored for
mammary gland uptake, as arterial glucose concentrations in sows range between 3.5 and 7 mM (Dourmad et
al., 2000). AV differences for AA range from 0.084 to 0.151 g/L (Linzell et al., 1969; Spincer et al., 1969; Spincer
and Rook, 1971; Trottier et al., 1997; Renaudeau et al., 2003), but is highly dependent on the AA, as mammary
uptake of leucine is 65 μmol/L and only 9.9 μmol/L for tryptophan (Trottier et al., 1997). AV differences for TAG
range from 0.045 to 0.102 g/L (Linzell et al., 1969; Spincer et al., 1969; Renaudeau et al., 2003). Average NEFA
AV differences are 0.032 g/L (Renaudeau et al., 2003), but after feeding the mammary gland excretes NEFA to
the blood (9 g/L), whereas during starvation it takes up NEFA (264 g/L) (Dourmad et al., 2000). NEFA uptake
seems to follow the availability, as arterial NEFA concentrations decrease significantly after feeding (Dourmad
et al., 2000).
1.4.3. Nutrient utilization
53% of the glucose taken up is assumed to be used for lactose synthesis (Linzell et al., 1969). As glucose cannot
be produced through gluconeogenesis in the cow mammary gland, since its glucose-6-phosphatase is very low,
all glucose used for lactose synthesis is coming from the blood (Scott et al., 1976). However, in research in sows
it was estimated that only 59 - 70% of the lactose is from plasma glucose (Linzell et al., 1969; Spincer and Rook,
1971) and glucose-6-phosphatase activity has not been measured in lactating sows. Most likely this is explained
by the difference in glucose origin, as most glucose in the cow is produced by the liver through
gluconeogenesis, whereas in sows most glucose has a dietary origin. Lactose is produced in the Golgi apparatus
and for every lactose molecule 2 glucose molecules are needed. One glucose molecule is transformed into
galactose by UDP-galactose 4’-epimerase (EC 5.1.3.2.) in the cytosol of the cell, actively transported into the
Golgi apparatus and is then bound to a glucose molecule to form lactose (Kuhn et al., 1980). The glucose
molecules are transported across the Golgi membrane by GLUT 1 transporters, which are only present on the
Golgi membrane of mammary cells (Nemeth et al., 2000). In the mouse, the onset of lactation is marked with
16
an increase in GLUT 1 expression on the Golgi membrane and after weaning GLUT 1 transporters disappeared
completely again (Nemeth et al., 2000), indicating the need of suckling for lactose synthesis.
As in the liver, AA can be used to generate energy. Mammary excretion of essential AA in protein roughly
resembles the AA concentration and AV differences of these AA (Trottier et al., 1997). However, there is a net
urea production (results were not shown) during lactation and of the essential AA, 25% of the taken up AA are
retained in the mammary gland (Trottier et al., 1997), either for nonessential AA production, structural protein
synthesis or for glycogenic utilization. Also Linzell et al. (1969) found a higher uptake than output of valine and
arginine. Therefore, AA might contribute to lactose synthesis, fatty acid synthesis or ATP production in the TCA
cycle. Also lactate, propionate and glycerol can be used for glycogenic purposes in the mammary gland as well
as in the liver.
In the mammary gland, de novo synthesis from glucose contributes to 38% of the glycerol in milk (Spincer and
Rook, 1971). Radioactivity studies suggest a low de novo fatty acid synthesis of 2 – 12 % coming from glucose
(Linzell et al., 1969; Spincer and Rook, 1971). Though, the same studies found a large fatty acid pool available in
the mammary gland (Linzell et al., 1969; Spincer and Rook, 1971), causing a low turnover rate of the fatty acids
and therefore a supposed underestimation of de novo fatty acid synthesis from glucose. This is in line with an
AV difference study, which suggests higher de novo synthesis of fatty acids (Spincer et al., 1969). Fat is
synthesized de novo from Acetyl CoA, see Figure 3. At the start of the synthesis one Acetyl CoA molecule is
transformed into Malonyl CoA, which is an irreversible reaction, and 1 Acetyl CoA molecule is transformed into
Acetyl ACP. Malonyl CoA and Acetyl ACP condense to form one Acetoacetyl ACP and CO2. In the consequent
steps 2 NADPH molecules are reduced, one water molecule released and the cycle starts over again until the
fatty acid has a certain length. In every cycle, one Malonyl ACP (coming from Acetyl CoA) is added to the chain,
resulting in an elongation of two 2 C atoms per cycle. In the case of a C16 fatty acid this means that 8 Acetyl
CoA and 14 NADPH were used to produce one fatty acid. Also acetate, butyrate and BHBA can be used for
chain elongation, and in the lactating sow acetate contributes from 2 to 15% of the saturated fatty acids
produced (Linzell et al., 1969).
Fat synthesis takes place in the cytosol of cells, but Acetyl CoA is produced from pyruvate in the mitochondria.
Therefore, mitochondrial Acetyl CoA has to be transported across the membrane as citrate by the citratemalate shuttle. In the cytosol the citrate is cleaved by ATP-citrate lyase (EC 2.3.3.8) at the cost of 1 ATP.
Oxaloacetate is transformed into pyruvate and pyruvate reenters the mitochondria. The pyruvate formation is
catalyzed by two enzymes, first malate dehydrogenase (EC 1.1.1.37) followed by NADP+-malate dehydrogenase
(EC 1.1.1.82) resulting in the production of 1 NADPH per Acetyl CoA transported across the membrane (Berg et
al., 2002). However, sows have low activity of NADP+-malate dehydrogenase (1 nmoles/mg cytosol
protein/minute), while NAD-malate has a high activity (1871 nmoles/mg cytosol protein/minute) (Bauman et
al., 1970). As a result, the transportation of Acetyl-CoA across the mitochondrial membrane in sows most likely
does not produce NADPH. In this way, all 14 (in case of a C16 fatty acid) of the NADPH necessary for fatty acid
synthesis have to be generated in the pentose phosphate pathway.
Pentose phosphate pathway
The pentose phosphate pathway, or also called pentose shunt, uses glucose to generate NADPH and ribose 5phosphate. Depending on the requirements of the tissue, there are four scenarios possible. If there is much
more ribose 5-phosphate required than NADPH, all glucose is used to produce ribose 5-phosphate at the cost
of ATP. If there is a balanced need for ribose 5-phosphate and NADPH there is one ribose 5-phosphate and 2
NADPH produced per glucose molecule, with one molecule of CO 2 produced too. If much more NADPH is
17
required than ribose 5-phospate, all glucose is transformed into NADPH and results in 12 NADPH molecules and
6 CO2 molecules. If both NADPH and ATP are required, glucose is used to produce pyruvate, CO2, NADPH, NADH
and ATP (Berg et al., 2002).
1.4.4. Milk secretion
When recent literature (1980 till 2012) on milk yield in lactating sows was compared and used in a Bayesian
model, average peak lactation occurred at d 18.7 after parturition and milk yield was 9.23 kg (Hansen et al.,
2012). However, with the tendency of increasing litter sizes and litter gain, lactation curves have changed
(Figure 5). When litter size was increased from 8 to 12 piglets, time to peak lactation was decreased from 21 to
15 days and milk yield at peak lactation was increased. In contrast, litter gain mainly affected milk yield. In the
same research milk composition was evaluated. Average protein, lactose and fat contents were estimated at
5.22, 5.41 and 7.32 % respectively (Hansen et al., 2012). However, as lactation progresses, milk protein and
lactose content are increased, and milk fat content decreased (Hansen et al., 2012).
There are several methods to determine the milk yield in sows of which weight-suckle-weight (WSW) and
deuterium oxide (D2O) are the most commonly accepted approaches. The WSW method gives the piglets a
certain amount of bouts to feed, with weighing the piglets directly before and after suckling. The piglets are
either weighed separately or in groups, but in groups is preferred due to measurement errors (Den Hartog et
al., 1984; Theil et al., 2002). In the D2O method, piglets are injected with a diluted D2O solution, blood samples
taken when equilibrium is reached and a couple of days later blood samples are taken again to calculated the
water turnover during the days between injection and last blood sample taken (Theil et al., 2002). WSW
underestimates the milk yield by 29 % on d5, 24 % on d20 and 27 % on d30 (Hansen et al., 2012), most likely
caused by weight losses through evaporation, glycogen utilization, urination, defecation, and salivary left overs
on teats(Klaver et al., 1981; Den Hartog et al., 1984; Theil et al., 2002). However, the model developed by
Hansen et al. (2012) gives a good estimate of milk yield based on liter size and litter gain.
Figure 5. Comparison of lactation curves with changing litter gain (LG) and litter size (LS) (Hansen et al., 2012).
18
In summary, mammary blood and plasma flow are difficult to estimate, but plasma flow is expected to range
between 4000 and 7000 L/d. Mammary uptake of nutrients is fairly constant for glucose and essential AA, but
NEFA uptake depends on the time after feeding. Most of the glucose taken up from the blood by the mammary
gland is used for lactose production and the rest of the glucose is used for oxidation and fatty acid synthesis.
Milk yield is highly influenced by litter size and litter gain, but the milk composition is fairly constant later on in
lactation. The methods for estimating milk yield are not ideal, but a combined analysis gives a fairly reliable
approximation.
1.5. Conclusion
The objective of this literature review was to determine the absorption, hepatic and mammary metabolism and
utilization of dietary nutrients in lactating sows, with the main focus on glucose. The lactating sow is a highly
productive animal and there is not a lot known about the physiological details of nutrient metabolism and
utilization in especially the liver and mammary gland. Absorption of dietary nutrients is highly variable, mainly
influenced by dietary fiber characteristics and inclusion level. However, starch digestion is almost complete and
carbohydrates not digested are fermented in the hindgut. Glucose is the main energy source for the small
intestinal cells and butyrate for the large intestinal cells. The liver keeps a constant blood glucose level by
forming and breaking down glycogen without using a lot of glucose itself. Also for AA and fat the liver plays an
important regulatory role. The mammary gland is a high glucose utilizer and a great part of the glucose taken
up is used for lactose production. However, fat production is also really important in the mammary gland and
part of it is de novo synthesized from glycogenic sources. Most of the AA are directly used for protein synthesis
without being altered. All this is done to sustain a proper milk production, which is important with the still
growing trend of increased litter size and litter gain.
19
Materials and Methods
1.6. Experiment
The present experiment complied with Danish law on the humane care and use of experimental animals (The
Danish Ministry of Justice, 2011). The Danish Animal Experimentation Inspectorate approved the study
protocols and supervised the experiment. The health of the animals was observed and animals were treated
accordingly in case of illness. One sow was culled on d 11 after parturition due to ligation of the uterus with the
abdominal catheters.
1.6.1. Animals and surgery
Four second parity sows (Danish Landrace x Yorshire), were bought from a commercial pig production (Rahbek,
Lem, Denmark) on approximately d 75 of gestation and housed in an intensive care facility at Reseach Center
Foulum, Faculty of Science and Technology, Aarhus University, Denmark. On d 79 ± 3 of gestation sows were
implanted with 4 permanent indwelling catheters in an artery, the portal vein, the hepatic vein and the
mesenteric vein (for infusion), as described by (Kristensen et al., 2009). Catheters were made of Tygon (S 54 HL,
1.02 mm i.d. x 1.78 mm o.d., Buch & Holm A/S, Herlev, Denmark). Sows were placed under general
anaesthesia, maintained with isoflurane (Isoba Vet., Intervet International BV, Boxmeer, The Netherlands).
An incision was made in the left medial lobe of the liver to place the portal and hepatic catheters (Olesen et al,
1989). A portal vein branch was identified by passing a wire guide (THSF-25-145 and THSF-32-210, Cook
Danmark, Bjæverskov, Denmark) from the incision through to the portal vein, where it was identified by
palpation and another guide wire was passed into a hepatic vein. Correct placement of the catheters was
confirmed by visual difference in colour, (hepatic blood darker than portal) and substantial difference in O 2
partial pressure. Catheters were fixed by sutures through the liver parenchyma. The portal catheter tip was
placed at porta hepatica and the hepatic catheter tip in the hepatic vein, before the bifurcation with vena cava.
The mesenteric catheter was placed in the cranial vena mesenterica through a small incision, which was closed
by a purse string suture. The tip of the mesenteric catheter was placed 10 cm from the insertion point and the
distance between the mesenteric catheter tip and the portal catheter was sufficient to allow thorough mixing
of blood and infusate. The femoral arterial catheter was placed through a 7 cm incision in the right hind leg.
The catheter was placed in the tibial branch of the saphenous artery, using a wire guide. The catheter tip was
35 cm from the point of insertion. All catheters were exteriorized on the back of the sow using long stainless
needles. At the end of surgery, catheters were filled with a saline solution containing heparin (100 IU/ml,
Heparin LEO, LEO Pharma A/S, Ballerup, Denmark), benzyl alcohol (0.1%, Benzylalcohol +99%, Sigma-Aldrich,
St. Louis, MO), and benzyl penicillin (0.2%, Benzylpenicillin, Panpharma, NordMedica A/S, Copenhagen,
Denmark).
Correct placement of the arterial, portal, and hepatic catheters were confirmed by necropsy at the end of the
experiment on d 28 of lactation. The distance between the mesenteric and the portal catheter was between 20
and 42 cm.
1.6.2. Recovery, housing and feeding
Sows were treated with antibiotics (Oxytetracyclin, Engemycin Vet., Intervet International BV, Boxmeer, The
Netherlands) for 5 d post-surgery and analgesics (Meloxicam, Metacam vet., Boehringer Ingelheim,
Copenhagen, Denmark; and Buprenorphin, Temgesic, Reckitt Benckiser Healthcare, Berkshire, Egnland) for 3 d
20
post-surgery, unless it was deemed necessary to prolong treatment. Catheter exteriorization points were
cleaned and dripped daily with antibiotics (Benzylpenicilin and Dihydrosteptomycin, Streptocillin vet.,
Boehringer Ingelheim Danmark A/S, Copenhagen, Denmark) to prevent inflammation.
Sows were kept in individual pens (2.0 x 2.7 m) during the entire experimental period and were kept loose from
insertion, until 14 d prior to expected parturition. At this time farrowing rails were installed in the pens, so that
sows were confined during sampling and also during parturition and lactation. The flooring consisted of
approximately ½ of plastic slats opposing the trough and the remaining was covered with rubber mat. Wood
shavings were provided as bedding up until 3 d before the first sampling and again from the day after the last
sampling. Sows were trained to human contact before the experiment.
Sows returned to normal feed intake within 10 d after surgery. At d -15 relative to expected parturition sows
changed from a standard gestation diet to a standard lactation diet (Table 11), which was given to all sows
during the entire experimental period in equal portions at 0800, 1600 and 2400 h. Feed allowance was in
accordance with Danish recommendations (Jørgensen and Tybirk, 2005) and sows were fed restrictedly during
gestation and semi ad libitum during lactation. Feed and water leftovers were recorded and removed daily
between 0800 and 1600, except on sampling days, where leftovers from the night were removed before the
first sampling and leftovers from the morning meal were removed 30 min after feeding.
1.6.3. Blood and milk sampling of sows
Blood sampling was done on d -10 ± 2 and d -3 ± 2 relative to expected parturition (corresponding to d 105 and
112 of gestation, respectively) and on d 3 ± 0 and d 17 ± 2 relative to parturition. On sampling days, continuous
infusion of pAH was initiated at 0630 h to obtain a steady level of pAH. The pAH infusate, containing 175
mmol/L of pAH, was adjusted to pH 7.4, sterile filtered (0.22 µm, FPE 214-500, JET Bio-Filtration Products Co.,
Ltd., Guangzhou, China), and autoclaved. Blood samples were taken as described by (Kristensen et al., 2009), at
hourly intervals for 8 h staring at 0730 h, and sows were fed at 0800 h. Prior to sampling 5 mL of blood was
collected from each catheter and discarded. Then arterial, portal, and hepatic blood were simultaneously
collected in 2 mL heparinized syringes (PICO50, Radiometer A/S, Copenhagen, Denmark) for blood gas
measurements, followed by collection of 18 mL immediately transferred into 2 x 9 mL heparinised tubes. Blood
samples were placed on ice and plasma was harvested after centrifugation at 3,000 x g for 20 min at 4 °C.
Plasma samples were divided and stored at -20 °C or -80 °C until analysis.
Milk samples were obtained by hand milking from two to three middle positioned glands (teat nos. 2-5).
Mammary secreta were obtained at the same days as blood sampling was done (d 3 ± 0 and d 17 ± 2 relative to
parturition), filtered through gauze, and 50 mL was stored at -20 °C until analysis. An intramuscular injection of
2.0 mL oxytocin (10 IU mL-1; Løvens Kemiske Fabrik, Ballerup, Denmark) was used to facilitate milk letdown.
1.6.4. Sow performance registrations
Backfat thickness at P2 (65 mm from the midline at the level of the last rib) of the sows was recorded on d -15,
d 2 and d 28 relative to parturition, as the average of 3 measurements by ultrasound using a 7.5-MHz Linear
Intraoperative Probe Aloka (UST-555I/7.5, Simonsen & Weel, Vallensbæk Strand, Denmark). The sows were
weighed the day before surgery and then once every week from d -10 until weaning. Spontaneous feces
samples were collected on blood sampling days and frozen at -20 °C for later analysis.
21
At parturition, the birth order of piglets was recorded, all piglets were weighed before they suckled (after
drying, ear tagging, and shortening of the umbilical cord to 15 cm), and weighed again 24 h after birth of the
first piglet for determination of colostrum yield. Individual weight on d 2, 4, 7, 11, 14, 18, 21, 15, and 28 after
parturition were also recorded for determination of milk yield. The piglets did not receive any feed, but had
free access to water at all times. At 24 to 36 h after birth of first piglet, the litters were equalized to 12 piglets
and piglets with a birth weight below 0.8 kg were euthanized. Hereafter no piglets were replaced or moved
between sows. On d 4 piglets received 1.2 mL of iron dextran (Hyofer 20% Vet, Salfarm Danmark A/S, Kolding,
Denmark) by subcutaneous injection in the inguinal region and male piglets were castrated. Piglets were
provided with a heating lamp in the pen, until d 14 of lactation.
1.6.5. Analytical Procedures
Diet and feces. DM content was measured by drying to constant weight (approximately 20 h) at 103 °C, and
ash was analysed according to the AOAC (2000) method no 942.05. Nitrogen content was measured by the
Kjeldahl method (Kjeltec 2400, Foss, Hillerød, Denmark) and protein was calculated as N x 6.25. Fat was
extracted with diethyl ether after HCl hydrolysis according to the Stoldt procedure (Stoldt, 1952). Contents of
starch were analysed as described by (Knudsen, 1997). Chromic oxide in feed and feces was measured
spectrophotometrically after oxidation to chromate (Schürch et al., 1950). AA in the diet were quantified after
hydrolysis for 23 h at 110 °C with or without performic acid oxidation using ion exchange chromatography and
photometric detection after ninhydrin reaction (European Commission, 1998).
Whole blood. Haematocrit was determined by centrifugation in capillary tubes at 13,000 x g for 6 min at
ambient temperature in arterial blood samples. Oxygen and carbon dioxide in blood were measured using an
ABL700 Blood Gas Analyser (Radiometer, Copenhagen, Denmark) immediately after collection.
Plasma. For pAH determination, plasma was deproteinized by combining with an equal volume of 20%
trichloroacetic acid (wt/vol) and the supernatant incubated at 100 °C for 1 h. Then it was deacetylated, as
described by Harvey and Brothers (1962), and plasma pAH was determined using a continuous flow analyser
(Autoanalyzer 3, method US-216-75 Rev. 1, Seal Analytical Ltd., Burgess Hill, UK). The concentration of urea
was determined as described by Marsh et al. (1965) using a continuous flow analyser (method G-373-07 Rev.
1). Plasma samples were analysed for AA by Ethyl Chlorformat (ECF) derivatization followed by gas
chromatography- mass spectrometry analysis (GC-MS; Finnigan trace GC ultra, CTC analytics). For each AA,
established internal standards for the individual AA was used for the GC-MS. Glucose and lactate was
determined using D-glucose oxidase and L-lactate oxidase, respectively (YSI 7100, YSI inc., Yellowstone Springs,
OH). Plasma samples were analysed for VFA by 2 Chlor-Ethyl-Chloroformat derivatization, followed by gas
chromatography-mass spectrometry analysis (GC-MS; Finnigan trace GC ultra, CTC analytics; Kristensen, (2000),
and NEFA was analysed using a kit (ref. no FA115, Randox laboratories Ltd., Crumlin, United Kingdom) for
Cobas Mira autoanalyser (Triolab A/S, Brøndby, Denmark). Blood plasma triacylglycerids (TAG) were
determined according to standard procedures (Siemens Diagnostics® Clinical Methods for ADVIA 1650). Plasma
BHBA analyses were performed using an autoanalyzer, ADVIA 1800  Chemistry System (Siemens Medical
Solutions, Tarrytown, NY 10591, USA).
Milk. Milk samples were analyzed as such (in triplicate) for fat, lactose, protein and DM content with infrared
spectroscopy using a Milkoscan FT2 instrument (Foss MilkoScan, Hillerød, Denmark). The Foss analyzer was
calibrated for bovine milk according to the protocol supplied by the manufacturer. Results were verified for
protein (N_6.38) by Dumas analysis (R2 between Foss analyzer and Dumas_0.997) and DM content determined
by drying to constant weight (R2 between Foss analyzer and DM analysis_0.997).
22
1.6.6. Calculations and statistical analysis
The daily milk yield was estimated according to Hansen et al. (2012) and used to derive the mean daily yield at
d17. The portal plasma flow was calculated as: infusion rate of pAH [mmol/h]/(portal plasma pAH
concentration [mmol/L] – arterial plasma pAH concentration [mmol/L]), and the hepatic plasma flow was
calculated as: Infusion rate of pAH [mmol/h]/(hepatic plasma pAH concentration [mmol/L] – arterial plasma
pAH concentration [mmol/L]). If the hepatic plasma flow was lower than portal plasma flow, the hepatic artery
plasma flow was calculated as the difference between hepatic plasma flow and portal plasma flow. Whole
blood flows were calculated as: plasma flow/[1-(haematocrit/100)].
Sow feed and water intake data, as well as production data were analyzed statistically using a Mixed Linear
Model (SAS 9.3, SAS Institute Inc., Cary, NC, United States) with fixed effects of days in milk (DIM) and sow as
random component. Blood and plasma flow were analyzed statistically using a Mixed Linear Model with fixed
effects of DIM and blood sampling time (Time) and the DIM x Time interaction. Sow was included as a random
component and Time was a repeated measure in the model described as an autoregressive process of first
order. Data are presented as Least Square Means ± SE of day 17, as only data of day 17 was used for building
the model. NEFA arterial concentrations were log-transformed and presented with a 95% confidence interval.
1.7. Model
The model was built in SMART© and is based on a system of dynamic, deterministic, nonlinear differential
equations. It consist of 18 state variables and 17 zero pools, representing nutrient pools in the 2 sub models of
the liver (L), and mammary gland (MG). The integration method used was Euler and the integration steps were
0.01 hour. Simulation begun at 0.0 hour and 8 hours were simulated. The results of the experiment described
and results of the experiment of Krogh, et al. (2015, unpublished), presented in Table 17, were used to
parameterize the model. In the case of missing information, data from literature was used. As a model is based
on a lot of assumptions, the assumptions made are based The assumptions made to build the model were
based merely on biochemical processes described in the books of (Berg et al., 2002) and (Bender, 2014). The
formulas used to build the model are given in Appendix E.
1.7.1. GIT
There was no separate model developed for utilization and metabolism in the GIT, solely the nutrient intake,
digestibility and absorption were added to the overall model to calculate the amount of nutrients used by the
GIT and the amount of nutrients available for the rest of the body.
1.7.2. Liver
Figure 6 shows the flow diagram of the liver. Nutrient inflow was calculated as the sum of supply of nutrients
by the portal vein (portal flux) and the hepatic artery (arterial flux), which in turn was calculated by multiplying
the nutrient concentration with the blood flow in case of oxygen and carbon dioxide and with plasma flow in
the case of all other nutrients. Nutrient outflow of the liver (hepatic flux) was calculated as the nutrient
concentration in the hepatic vein times the hepatic blood/plasma flow. Net hepatic flux was calculated as the
hepatic flux – (portal flux + arterial flux).
It was assumed that the net disappearance of glucose between meals was made into pyruvate, at the cost of
one oxygen molecule giving rise to 2 pyruvate molecules (Berg et al., 2002), whereas all other glucose
molecules were stored as glycogen when net hepatic flux of glucose was negative and excreted when net
23
hepatic flux of glucose was positive. Also all net hepatic uptakes of glycerol, alanine, proline, and glycine were
assumed to give rise to pyruvate at the cost of one oxygen molecule(Berg et al., 2002). The total amount of AA
oxidized was assumed to be equal to the urea produced. Pyruvate was assumed to be used for lactate
production, as there was a positive net hepatic flux for lactate. The rest of the pyruvate was assumed to flow
into Acetyl CoA, at the cost of ½ O2 and producing one CO2 per pyruvate molecule (Berg et al., 2002). The
Acetyl CoA pool received, next to pyruvate, inflow from butyrate and NEFA. It was assumed that Acetyl CoA
was used for BHBA and acetate synthesis (Berg et al., 2002), with remainder of the Acetyl CoA used for
oxidation in the TCA cycle. There was a large amount of NEFA absorbed by the liver and the amount of NEFA
transformed into Acetyl CoA was based on the Acetyl CoA needed to balance for oxygen consumption in the
TCA cycle. The NEFA absorption was higher than the Acetyl CoA needed, so storage of NEFA in the liver was
accounted for. Net hepatic triglyceride flux changed between negative and positive, so when negative NEFA
and glycerol were produced, positive NEFA and glycerol were utilized for TAG production
With the model, the utilization and metabolism of glucose were calculated as a percentage of the total glucose
taken up by liver and of the total digested starch. Also, the net contribution of other energy sources to liver
oxidation was calculated as a part of total oxidation happening.
Figure 6. Flow diagram of the liver fluxes. In red the zero pools, in black the state variables. Gluco=glucose, lact=lactate, gly=glycine,
ala=alanine,
pro=proline,
glyc=glycerol,
pyr=pyruvate,
TCA
cycle=tricarboxylic
acid
cycle,
pr=propionate,
bhba=betahydroxybutyricacid, ac=acetate, bu=butyrate, Acetyl CoA=Acetyl CoA, nefa=non esterified fatty acid, tag=triglyceride
24
1.7.3. Mammary gland
Figure 7 shows the flow diagram of the mammary gland. Nutrient uptake (NMF) was calculated as arterial
concentration (anutrient) (Appendix C Table 13) x mammary plasma flow (Mflow) x extraction efficiency (Enutrient)
(Table 17). Mammary plasma flow was calculated by the sum of all excreted carbon atoms to the milk divided
by the sum of all absorbed and excreted carbon atoms from and to the blood. Milk excretion was based on
analyzed milk composition (Appendix B Table 12) x the milk yield (Appendix B Table 12), divided by the
molecular weight of the molecules, and was assumed to be constant during the 8 hours between meals.
Glucose used for lactose production was two times the hourly lactose excretion (Berg et al., 2002). Glucose
used for the PPP was calculated as the amount of NADPH needed for fat synthesis. As there is a large need for
NADPH, every glucose produced 12 NADPH and 6 CO2 (Berg et al., 2002). An additional glucose utilization for
PPP was estimated, based on the overflow of Acetyl CoA. The whole pool of glucose (MGgluco) was said to flow
into pyruvate, costing one O2 molecule and giving 2 pyruvate molecules per glucose (Berg et al., 2002). All
lactate is assumed to flow into pyruvate, at the cost half an oxygen molecule (Berg et al., 2002). The AA used in
oxidation were assumed to be branched chain AA and were therefore assumed to be transformed into
pyruvate (Bender, 2014). The amount of AA oxidized is estimated as the net amount of urea produced. For
every urea produced, one CO2 molecule is used (Berg et al., 2002). The whole pool of pyruvate is said to flow
into Acetyl CoA. For every Acetyl CoA coming from pyruvate, half an oxygen molecule is used and one carbon
dioxide is produced (Berg et al., 2002). All butyrate, acetate and BHBA are assumed to be transformed into
Acetyl CoA. Acetyl CoA is used for fatty acid production. On average, fatty acids are assumed to be 17 C , which
costs 8.5 Acetyl CoA to produce (Berg et al., 2002). The amount of fatty acids synthesized the novo is estimated
as the difference between TAG excreted in the milk, and the TAG and NEFA absorbed from the blood. Every
TAG contains 3 NEFA. Glycerol used as backbone for TAG production was either coming from absorption from
the blood or was synthesized from pyruvate. The amount of Acetyl CoA used in the TCA cycle was assumed to
be equal to the oxygen pool divided by two, as every cycle consumes two O 2 molecules (Berg et al., 2002). In
the TCA cycle every cycle produces 2 CO2 molecules (Berg et al., 2002). Propionate was assumed to be oxidized
in the TCA cycle trough pyruvate production.’
With the model, the utilization and metabolism of glucose was calculated as a percentage of the total glucose
taken up by the mammary gland and of the total digested starch. Also, the net contribution of other energy
sources to mammary oxidation was calculated as a part of total oxidation happening. Additionally, the total
contribution of de novo fatty acid synthesis tot milk fat was calculated.
1.7.4. Sensitivity analysis
Sensitivity analysis was done by increasing every input value by 10%, as the milk yield, lactose and fat content
of the milk. Blood/plasma flow in the mammary gland was corrected for the change in input values. Response
in glucose utilization and metabolism was used as a measure to determine the effect of changing input
parameters on nutrient flows in the mammary gland. Due to the dynamic input for blood/plasma concentration
values, it was not possible to estimate the effect of the arterial values on the mammary sub model. Neither
was it possible to estimate the effect on the liver model.
25
Figure 7. Flow diagram of the fluxes in the mammary gland. In red the zero pools, in black the state variables. Gluco=glucose,
lac=lactose, lact=lactate, aa=amino acid, glyc=glycerol, pyr=pyruvate, TCA cycle=tricarboxylic acid cycle, pr=propionate,
bhba=betahydroxybutyricacid, ac=acetate, bu=butyrate, Acetyl CoA=Acetyl CoA, nefa=non esterified fatty acid, tag=triglyceride
1.7.5. Validation
Validation of the mammary gland sub model was executed by using the arterial values of the same research as
used for the extraction efficiencies of Krogh, et al. (2015, unpublished), presented in Table 18 in Appendix C.
Milk yield was estimated to be 14.05 kg/d, with a fat % of 6.37 and lactose % of 5.19. There was no research
available to compare the liver sub model, as this is the first known research in lactating sows regarding liver
metabolism.
26
Results
1.8. Experiment
1.8.1. Sow performance
Feed intake corrected for leftovers at the morning meal on the sampling day was 2170 g, resulting in a starch
intake of approximately 1007 g (Appendix B Table 12). Correspondingly, the fiber intake was 389 g, protein
intake 383 g and fat intake 109 g. Sows had an average LW of 245 kg after parturition and lost on average 16 kg
LW (P=0.075) and 3 mm backfat from d 2 to d 28 (P=0.06). Parturition was between d 117 and d 120 of
gestation. Sows produced 11.7 kg/d of milk at d 17 of lactation, with fat, protein and lactose percentages of
5.77, 4.28 and 5.38 respectively. Sows had an average litter size of 18.8 live born piglets, with a mean birth
weight of 1.25 kg. Litter sizes were equalized to 12 piglets on d 1, and on average 11.7 piglets were weaned on
d 18, with mean weight of 7.64 kg. The daily piglet weight gain increased from 168 g/d in the first week of
lactation to 237 g/d in the third week (P=0.042).
1.8.2. Metabolites in plasma/blood
The average arterial hematocrit level was 26% (Appendix C
Table 13). Average O2 concentration was 5.8 mmol/L and CO2 was 28.7 mmol/L. In the plasma, urea and
glucose had the highest concentrations, with 6.5 and 5.6 mmol/L respectively. Propionate and butyrate were
least abundant. The portal blood values (Table 14) show a lower O2 and a higher CO2 concentration, being 3.7
and 31.0 mmol/L respectively. Glucose is most abundant in the portal plasma, at 7.4 mmol/L, but urea
concentration is roughly the same as in arterial plasma. Acetate levels are higher in portal plasma than in
arterial plasma (1.4 versus 0.5 mmol/L). Portal glucose concentrations are highest 0.5 hours after feeding and
slowly decrease to before feeding levels during the successive 8 hours. Hepatic blood is even more depleted in
oxygen, having a concentration of 2.2 mmol/h, whereas the CO 2 concentration is much the same as portal
blood (Table 15). Average concentration of glucose in hepatic plasma is lower than in portal plasma (6.8 versus
7.4 mmol/L). The rise in glucose concentrations after feeding is less in hepatic plasma, but is still present. NEFA
concentrations are lower in hepatic plasma than in portal plasma, whereas TAG levels are roughly the same.
Urea concentration is elevated in hepatic plasma and ammonia concentrations are lower when compared to
portal plasma. Hepatic blood and plasma flows were 509 and 374 L/h respectively and portal blood/plasma
supply were 71% of the total liver supply.
1.9. Model
1.9.1. GIT
The starch intake in the sows was calculated based on feed intake and dietary composition, leading to an
average starch intake of 6530 mmol/meal. 98% of the starch is digested in the small intestine, and of the
digested starch 60% is present in the portal blood when it reaches the liver. This means that 40% of the
digested starch is used by the GIT and associated organs. A total of 753 mmol lactate was absorbed per meal.
The SCFA propionate, butyrate and acetate were absorbed with 748, 345 and 1927 mmol/meal respectively.
There was a net urea uptake by the GIT and associated organs of 212 mmol/meal, whereas there was an
excretion of 696 mmol of ammonia per meal.
27
1.9.2. Liver
The net hepatic uptake of glucose was on average 36.84 mmol/h. Table 4 shows the sources for ATP production
in the liver. NEFA provide most of the carbon for oxidation in the TCA cycle (41%) and after that propionate,
butyrate and AA are the main energy sources, providing 46% of the Acetyl CoA molecules. Glucose contributes
to 10% of the energy and glycerol and acetate oxidation are negligible. At peak glycogen formation, there was a
total of 511 mmol glycogen accumulated, which was estimated to happen at t=3.58. 40% of the NEFA was
stored in the liver, which is equal to a total of 259 mmol NEFA per day or approximately 70 grams per day.
Lactate production from pyruvate was 89 mmol/h and BHBA production was 7 mmol/h. There was a total of
12.7 mmol/h CO2 accumulated in the liver CO2 pool, but this is only 2% of the total CO2 produced by the liver.
Table 4. Energy sources for ATP production in the TCA cycle in the liver of lactating sows.
Item
Acetyl CoA oxidized
Glucose
NEFA
Amino Acids
Glycerol
Propionate
Butyrate
Acetate
Amount (mmol/h)
306.2
32.1
126.5
49.0
2.2
38.9
52.0
5.4
1.9.3. Mammary gland
The mammary plasma flow as calculated by the model was 294.14 L/h, resulting in on average a blood flow of
406.45 L/h. Table 5 shows the glucose utilization and metabolism in the mammary gland. Most of the taken up
glucose is used for lactose production (39%), whereas de novo fatty acid synthesis takes the second position
with 26%. However, part of the glucose going into the pentose phosphate pathway is directly needed for the
de novo fatty acid synthesis, which in this model was estimated to be 49 mmol/h. This results in a total of 37 %
of the glucose taken up by the mammary gland to be used for de novo fatty acid synthesis. Only a minor part of
the glucose is actually used for oxidation (13%).
Table 5. Glucose utilization and metabolism in the mammary gland in lactating sows.
Item
Glucose taken up
Lactose
De novo fatty acid synthesis
Glycerol
TCA cycle
Pentose phosphate pathway
Fatty acid synthesis
Amount (mmol/h)
433.0
168.4
111.6
5.4
54.4
93.3
49.0
28
For oxidation, glucose is the main source of energy as it takes care of 65% of the energy supply, which in total
comes down to 163 mmol Acetyl CoA per hour (Table 6). Together the SCFA and lactate contribute 32% to
oxidation, whereas the AA oxidation is not really important, supplying roughly 2%.
Table 6. Energy sources for ATP production in the TCA cycle in the mammary gland of lactating sows.
Item
Acetyl CoA oxidized
Glucose
Lactate
Amino Acids
NEFA
Acetate
Butyrate
BHBA
Propionate
Amount (mmol/h)
162.6
105.2
21.6
3.0
2.4
24.8
2.7
2.7
0.1
By definition of equal distribution of the molecules in the pool, the same ratio between sources for de novo
fatty acid synthesis occurs. The total amount of acetyl CoA going into de novo fatty acid synthesis is 333
mmol/h (not accounting for the glucose needed for NADPH production in the PPP)(Table 7). Of the fatty acids
and glycerol secreted in the milk 35% and 89% were de novo synthesized, respectively. 81% of the de novo
synthesized glycerol and 65% of de novo synthesized fatty acids originated from glucose. TAG contributed 59%
to the total fat excreted in milk. Due to the oxidation of NEFA and excretion of NEFA to the blood, overall de
novo fatty acid synthesis is higher than that excreted in the milk (314 mmol/h synthesis, 307 mmol/h excreted
in milk). There was a total of 5 mmol/h CO2 not accounted for, but this is only 0.4% of the total CO2 produced
by the mammary gland (measured in the blood).
Table 7. Fatty acid and glycerol synthesis in the mammary gland of lactating sows.
Item
Fatty acid excreted
De novo synthesized
Glucose
Acetate
Butyrate
BHBA
NEFA
TAG
Glycerol excreted
De novo synthesized
Glucose
Amount (mmol/h)
108.5
38.3
24.8
5.8
0.4
0.1
6.3
63.9
14.9
13.3
10.8
29
1.9.4. Post prandial changes
During the whole 8 hours between feedings the liver took up NEFA from the blood. The mammary gland, on
the other hand, took up NEFA until t=0.78 and releases NEFA until t=4.38. During this time, NEFA uptake from
the liver was lower when compared to before feeding times. Arterial concentration of NEFA decreased from
half an hour before feeding until 1.5 hours after feeding, after which the plasma concentration gradually
increased again.
Figure 8. Non esterified fatty acid flows and arterial concentration in the lactating sow at d 17. Feeding occurred at arrow
Figure 9 shows the relationship between arterial NEFA concentration and mammary uptake of NEFA. The trend
line crosses the x-axis at 0.226 mmol/L and R2 is 0.974.
Mammary uptake NEFA [mmol/h]
60
50
40
30
20
10
0
-10
-20
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Arterial concentration NEFA [mmol/L]
2
Figure 9. Relationship between arterial non esterified fatty acid (NEFA) concentration and mammary uptake of NEFA (R =0.974)
30
1.9.5. Utilization of dietary starch and energy
On average, there is an available glucose source in the intestinal lumen of 800 mmol/h (Table 8). Of this, 40% of
the available glucose is utilized and metabolized by the GIT and its associated organs. 5% of the digested
glucose is utilized and metabolized in the liver, but the main part of dietary glucose is used for the mammary
gland, as the mammary gland takes up 54% of the digested glucose. This leaves only 2% of the digested glucose
available for the rest of the body.
Table 8. Distribution of dietary glucose uptake by several organs in the lactating sow
Item
Digested glucose
GIT
Liver
Mammary gland
Rest
Amount (mmol/h)
800.1
317.3
36.8
433.1
12.8
The liver mirrors the absorption flow of glucose, whereas the mammary uptake of glucose is fairly constant
(Figure 10). Glucose absorption peaks at half an hour after feeding and decreases gradually until the next meal.
On average there is an energy source in the intestinal lumen available of 7211 mmol/h (Table 8). 40% of the
available energy is utilized and metabolized by the GIT and its associated organs. 13% of the digested energy is
utilized and metabolized in the liver, but the main part of dietary energy is used for the mammary gland, as the
mammary gland takes up 59% of the digested glucose. Since the energetic utilization for the GIT, liver and
mammary gland are more than taken up from the diet, the body has to mobilize energy, equal to 12% of the
dietary energy intake.
Figure 10. Glucose flows in the lactating sow at d 17. Feeding occurred at the arrow
31
Table 9. Distribution of dietary energy uptake by several organs in the lactating sow
Item
Digested C
GIT
Liver
Mammary gland
Rest
Amount (mmol/h)
7210.8
2863.8
967.2
4262.1
-882.36
1.9.6. Sensitivity analysis
The results of the sensitivity analysis of the mammary gland sub model are presented in Table 10. Increase in
all milk characteristics resulted in an increased plasma flow, and therefore an increased mammary glucose
uptake. The glucose distribution was not really affected by the change in milk yield, only the amount of glucose
going into PPP was 1% lower. An increase in fat % resulted in more glucose being allocated to de novo fatty
acid synthesis (28% compared to 26%) and PPP (1% increase), whereas the amount going into lactose and
oxidation were decreased with 2 and 1 % respectively. The change in milk lactose content had the highest
effect on glucose allocation in the mammary gland. Here, 41% of the glucose was used for lactose synthesis,
and only 24% was used for de novo fatty acid synthesis. The amount of glucose used for PPP decreased by 1%.
Table 10. Sensitivity analysis (10% increase) of milk characteristics on glucose distribution in the mammary gland of lactating sows.
dnFA=de novo synthesized fatty acids, TCA cycle=tricarboxylic acid cycle, PPP=pentose phosphate pathway
Glucose distribution (mmol/h)
Reference
Milk
Yield (kg/d)
Fat (%)
Lactose (%)
Plasma flow
(L/h)
294.14
323.55
313.52
304.18
Total
Lactose
dnFA
TCA cycle
PPP
Glycerol
3467
1348
893
436
747
43
3798
3673
3593
1483
1348
1483
984
1031
845
477
449
463
806
794
761
48
51
40
1.9.7. Validation
The mammary plasma flow was calculated to be 357 L/h based on the C balance in the mammary gland. There
was a total CO2 accumulation in the mammary gland, which was 46 mmol/h, but this is only 3% of the total CO 2
produced in the mammary gland. There was also a total Acetyl CoA disappearance of 14 mmol/h, but this was
only 2% of the total Acetyl CoA produced. Overall, the model appears to work for this data set.
32
Discussion
1.10. Reliability and accuracy model
The model was based on an animal experiment on lactating sows. As with all animal experiments and lab
analyses, data found are prone to contain small errors. These small individual measurement errors are
accumulated in the model developed and will therefore lead to larger total mistakes in the model. As the
model included dynamic inputs, the changes in pools were most prominent in the last pools in the whole
model, CO2 and Acetyl CoA, and measurement errors in the animal experiment would accumulate in these two
pools. However, in both the liver and the mammary gland sub model the accumulated error was only minor
(2% in the liver model and 0.4% in the mammary gland model).
The sensitivity analysis shows that the mammary sub model is most sensitive to lactose content changes when
looking at the glucose allocation, but this only resulted in changes of maximum 2 %. However, mammary blood
flow is changed drastically when milk yield, fat % and lactose % were increased. Due to the inherent calculation
of mammary plasma flow in the model, the sensitivity in changes in plasma flow were not calculated, but as
plasma flow determines the total amount of nutrients available for the organ it is expected to influence the
model if one would have wanted to use measured plasma flows. The validation of the model could only be
done with data from the same dataset as was used for the calculation of mammary extraction efficiencies.
Therefore, the validation is only partly valid and ideally a completely new dataset should be used to validate
the model, but this dataset was not available. However, the fact that two completely different experiments
mixed to develop the model result in approximately the same accumulated mistakes in the model indicates
that the model is valid for at least sows with these particular diets fed (normal Danish lactation diets) and these
production results (12 vs 14 piglets).
1.11. Hepatic and mammary oxidation
The liver mainly oxidizes NEFA, and the SCFA butyrate and propionate, whereas the mammary gland mainly
oxidizes glucose and the SCFA acetate. In this study it was found that 13 % of the mammary extracted glucose
was used for oxidation, which is lower than the 34 % estimated by Linzell et al. (1969). In this model there was
an assumption that all NADH produced is used for ATP production, consuming O2 in the process. However, this
is not always the case, as many processes in cells require NADH (Berg et al., 2002). As the amount of Acetyl
CoA used for oxidation was directly linked to the amount of O2 extracted, a decrease in O2 consumption for ATP
production through NADH would increase the oxidation of Acetyl CoA and, therefore, the overall glucose
oxidation. Linzell et al. (1969) also estimated that 54 % of the mammary CO2 produced originated from glucose,
which was found to be 69 % in this study. The milk fat % in the sows used by Linzell et al. (1969) was on average
lower than that in the sows used in this study and the de novo fatty acid synthesis was estimated to be lower
too. As a big part of the CO2 production from glucose is through the PPP, which is linked to the de novo fatty
acid synthesis. It is likely that the difference in these studies originates from different PPP contributions.
The mammary gland also uses lactate for oxidation, which originates from the liver. It was found that 79 % of
the hepatic released lactate is extracted by the mammary gland. In time, the mammary lactate uptake roughly
follows the GIT absorbed lactate and hepatic lactate production, except for time points 2.5 and 5.5 where
mammary lactate absorption is higher than hepatic release. From t=5.5 onwards, mammary lactate uptake is
higher than GIT absorbed lactate, but hepatic lactate release is higher than mammary uptake until t=7. Overall
33
NEFA excretion by the mammary gland is 30 mmol in the 8 hours studied, whereas NEFA extraction by the liver
is 227 mmol. Thus, 13 % of the NEFA used for oxidation in the liver is actually produced by the mammary gland.
1.12. Post prandial changes
The mammary uptake of all nutrients was fairly constant and was either positive or negative, except for NEFA.
The mammary gland excreted NEFA during 3.6 hours from t=0.78 till t=4.36. Dourmad et al. (2000) found a
similar trend in lactating sows at d14 and contributed this effect to the larger uptake of glycogenic sources.
However, in this study the mammary uptake of the main glycogenic source, glucose, is actually decreased
during the time points of NEFA release by the mammary gland. The mammary NEFA uptake/release seems to
follow the arterial NEFA concentration. As there is a high correlation between arterial NEFA concentration and
mammary uptake of NEFA (R2=0.974), it is most likely that mammary NEFA uptake is mass action driven.
Consequently, it might be the case that the mammary gland is de novo synthesizing NEFA at a constant rate,
independent of the arterial NEFA concentration. It is suggested that membranes fatty acid binding proteins
may play a role in NEFA uptake, but the precise mechanism has still to be elucidated (Shennan and Peaker,
2000). The liver extracted NEFA from the blood at all times. However, the NEFA uptake by the liver seems to
mirror the NEFA uptake by the mammary gland from t=5.5 till the next feeding, and NEFA concentrations in the
arterial blood were also higher during these hours, which indicates a larger body fat mobilization during these
hours. This is in agreement with the negative effect of insulin, released by the body as a response to high
glucose levels, on NEFA excretion (Berg et al., 2002). Therefore, the release of NEFA by the mammary gland
might be an indirect effect of insulin.
1.13. Mammary plasma/blood flow
The calculated mammary plasma flow was 7060 L/d. This is in agreement with the results found by Guan et al.
(2002). Most other studies found values below the ones found in this study, but these studies either had a
lower litter size and milk yield, or a comparable litter size but a lower milk yield (Linzell et al., 1969; Trottier et
al., 1997; Nielsen et al., 2002a; Nielsen et al., 2002b; Renaudeau et al., 2002; Guan et al., 2004a; Guan et al.,
2004b). As mammary plasma flow linearly increases with increasing litter size (Nielsen et al., 2002b), an
increased litter size increases milk yield (Hansen et al., 2012), and mammary plasma flow is not affected by day
of lactation (Nielsen et al., 2002b), the results found in this study seem valid. However, blood flow is decreased
for 25 minutes after a meal and suckling causes an increased mammary blood flow (Renaudeau et al., 2002).
The arterial concentrations and extraction efficiencies of the mammary gland in lactating sows are not constant
over time, as seen in the data used for building the model, and a decrease in plasma flow after a meal will
result in lower uptake of nutrients by the mammary gland directly after a meal. As the most abundant
glycogenic nutrients, glucose and lactate, have an approximately 1.5 and 1.8 times higher arterial
concentration after feeding and their extraction efficiencies are decreased 1.8 and 1.2 times respectively,
overall uptake of glucose is most likely lower than calculated in the model and the mistake made in lactate
uptake depends on the amount decreased plasma flow after feeding. Also, the sows in this experiment were
injected with oxytocin for milk collection, and oxytocin injection decreases blood flow to the mammary gland
for 12 minutes (Renaudeau et al., 2002). However, as measuring blood and plasma flow in the mammary gland
is very difficult (Trottier et al., 1995) and still under development, the results of this study are currently the best
available option.
34
1.14. Mammary de novo fat synthesis
The mammary de novo fatty acid synthesis was estimated to be 24%, which is higher than the 2 - 12%
estimated before through radioactive glucose addition (Linzell et al., 1969; Spincer and Rook, 1971), higher
than the 2.4 and 6.4% estimated through the development of a model (Theil et al., 2012), in the range
predicted of 18 to 63% in a feeding trail ((Theil et al., 2004) as interpreted by Theil et al. (2012) and below the
limit of 50% predicted by (Boyd and Kensinger, 1998). The results of Linzell et al. (1969) and Spincer and Rook
(1971) are fairly old studies and had sows in lactation for more than 4 weeks, which is unconventional now.
Also, they had either removed the piglets, which resulted in a rapid decrease of milk production (Spincer and
Rook, 1971), or had very small litter sizes (Linzell et al., 1969). As the studies were based on radioactivity of the
measured molecules, steady state of the milk constituents is important, but was not achieved (Spincer and
Rook, 1971).
However, the findings of Spincer and Rook (1971) about relative contribution are still very applicable. As in this
research there seemed to be an accumulation of carbon atoms at the end of the 8 hours and since fat synthesis
requires a big part of the carbon atoms, it is likely that there is a large fatty acid pool in the mammary gland
having a slow turnover rate, causing de novo the fatty acid production to be unrelated to actual excretion of fat
(Linzell et al., 1969). Linzell et al. (1969) found that glucose contributes more to fatty acid synthesis than
acetate, as total glucose uptake was higher than acetate and it still had twice as much representation in the
milk fat. In this study, the glucose contribution to fatty acid was estimated at 65 %, whereas the acetate
contribution was estimated at 15%. The total contribution of SCFA to fatty acid synthesis was 6.4 mmol/h, but
the contribution of BHBA is questionable, as the BHBA dehydrogenase activity is low in mammary mitochondria
(Bauman et al., 1970). The total contribution of BHBA to fatty acid synthesis was only 2 % in this study and the
mistake made by this assumption is consequently minor.
Theil et al. (2012) developed a model based on literature studies and had 2 scenarios, assuming either a
glucose allocation of 53 % for lactose, 34 % for oxidation, half of the glycerol production, and the rest for de
novo fatty acid synthesis; or a glucose allocation of 70 % for lactose, 5 % for de novo fatty acid synthesis, and
half of the glycerol production, and additionally assuming 5 % oxidation of blood extracted fatty acids and a 17
g/L milk NEFA uptake. In this study, however, the glucose allocation for lactose was estimated at 39 % and
there was no model development necessary to calculate this value. Therefore, the main assumption for both
scenarios of Theil et al. (2012) is already not valid for this study. In addition, estimated milk yield was higher in
this study, fat concentrations were 1% lower and dietary fat consumption was lower.
Spincer and Rook (1971) found that when plasma TAG made of either palmitic acid or stearic acid are infused,
respectively 51- 62 and 42-71 % of the fatty acids found in milk originated from the infused fatty acids. This
shows that there is a large part of the most abundant milk fatty acids directly taken up from the blood, which in
this study was found to be 59%. However, TAG have a higher variation in fatty acid composition than milk fat
(Linzell et al., 1969) and it is most likely that the shorter chain fatty acids from TAG are elongated in the
mammary gland (Spincer and Rook, 1971). Therefore, the assumption of direct transfer of all TAG to milk fat
might be questionable, but if TAG was to be elongated even more glucose was used for fatty acid synthesis.
The 26% of blood extracted glucose allocated to de novo fatty acid synthesis does not account for the
associated costs of de novo fatty acid synthesis. The glucose used for NADPH production for de novo fatty acid
synthesis was 11%, leading to a total of 37% of glucose used for de novo fatty acid synthesis. However, as sows
have an appreciable amount of fatty acid desaturase activity and as the enzyme can use both NADH and
35
NADPH as reducing agents (Bickerstaffe and Annison, 1970), it is likely that part of the produced NADPH is used
for desaturation of fatty acids. For the synthesis of fat, glycerol is a necessity. According to Spincer and Rook
(1971) 38% of the glycerol in milk is de novo synthesized in the mammary gland from glucose, which is lower
than the 81% found in this study. As milk yield and composition are unknown from the study of Spincer and
Rook (1971), it might be explained by an overall lower fat yield in the sows used in their experiment.
1.15. Milk composition
The high increase in Acetyl CoA near the end of the 8 hour period might be explained by a slow turnover of
fatty acids, as explained before, or by having wrong assumptions about milk composition. In this experiment
the milk samples were taken once per day and it was assumed that the composition found on that one point in
time is representative for the whole milk production. However, in goats the milk composition changes after
feeding, with lactose excretion being really low after feeding and increasing until 21 hours after feeding, and
milk fat content decreasing after feeding until 21 h hours and after that increasing again (Linzell, 1967). Glucose
availability was directly related to lactose production when glucose was infused, but milk fat was unaffected
(Linzell, 1967). Also in humans there is a diurnal variation in fat content of milk and this was unrelated to feed
intake (Hall, 1979). In sows, (Linzell et al., 1969) found that the concentration of milk fat rose over time during
the mammary perfusion. Therefore, there could be an effect of feeding or time on nutrient composition of the
milk. The combined NEFA and TAG uptake by the mammary gland in this study was higher than the fat
excretion to the milk from t=7.06 till t=7.8. In this model it was assumed that the excess NEFA is oxidized, but
an increase in milk fat concentration as time progresses could also explain the vast increase in milk fat
precursors near the end of the 8 h period.
1.16. Utilization of dietary starch and energy
The GIT was estimated to utilize 40% of the digested glucose from the GIT. However, diet might affect the
amount of glucose utilized by the GIT with specifically fiber having an influence. Fiber level and source doesn’t
affect glucose, lactate and SCFA portal vein values, but overall absorption of glucose is approximately 30%
higher with low fiber diet, even though the glucose disappearance in the GIT is only 7% higher and SCFA
appearance is only approximately 20% higher in high fiber diets (individual SCFA not affected) (Bach Knudsen et
al., 2000). The liver on average utilized 5% of the glucose from the diet and the highest extraction of glucose
was 311 mmol/h, which occurred at the same time point as maximal glucose was absorbed from the GIT. In
grower-finisher pigs there was a net release of glucose during the 8 hours after feeding (Kristensen et al.,
2009). The discrepancy between net glucose release or absorption by the liver might be explained by the
amount of NEFA that the sow has to deal with. The overall CO2 production in sows is higher than in grower
finishers (684 vs 41 mmol/h) (Kristensen et al., 2009), and in order to keep the TCA cycle running oxaloacetate
should be produced, which has to come from pyruvate (Berg et al., 2002). Therefore, it is likely that the glucose
absorbed by the liver in lactating sows at d 17 is used to keep the TCA cycle running. The mammary gland
utilized 54% of the digested dietary glucose and 59% of the digested energy. Noblet and Etienne (1987) found a
similar result of 57% of ME being excreted in milk. Theil et al. (2004) found a value of 50.1%, whereas
Verstegen et al. (1985) found 67%. In this study the sows lost on average 16 kg of LW, which is higher than the
average weight loss of the sows in the experiment of Verstegen et al. (1985) but lower than in the experiment
of Theil et al. (2004). As a higher weight loss indicates more NEFA available for milk fat synthesis, the relative
contribution of dietary energy decreases, especially since NEFA is energy dense.
36
Conclusion
The objective of this study was to determine the absorption, hepatic and mammary metabolism and utilization
of dietary nutrients in lactating sows. This was done by combining results of two animal trials and the
development of a model. The model developed in this experiment seems valid for the current production
results of lactating sows. The mammary gland is the main utilizer of dietary glucose and energy, whereas the
liver is the main organ providing energetic sources for the rest of the body. The liver mainly oxidizes NEFA,
butyrate and propionate to excrete lactate. In contrast, the mammary gland mainly oxidizes glucose, acetate
and lactate. The mammary plasma flow was calculated according to counting C atoms and gave an average of
294 L/h, which was within the limits found in literature. Mammary de novo fatty acid synthesis was 24% and
combined with the cost of de novo fatty acid synthesis it utilized 37% of the mammary extracted glucose. The
model showed a slight accumulation of Acetyl CoA near the end of the 8 hours of the experiment, which might
be explained by a non-constant milk composition. All in all, glucose is the main energy source for lactating sows
and an adequate starch intake is important for proper milk production.
37
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41
Appendix A
Table 11. Dietary ingredients and chemical composition of the diet
Item
Ingredients, (as fed)
Barley
Wheat
Soybean meal, toasted
Animal fat
Monocalcium phosphate
Calcium carbonate
Sodium chloride
Vitamin-mineral premix
Chemical composition
DM, g/kg
Starch
Dietary fiber
Crude fat
Crude protein
Alanine
Arginine
Aspartic acid
Cystine
Glutamic acid
Glycine
Histidine
Isoleucine
Leucine
Lysine
Methionine
Phenylalanine
Proline
Serine
Threonine
Valine
Chromic oxide
g/kg
400
356
181
30
12
16
4
2
g/kg DM
912
510
197
55
194
8.1
12.1
16.5
3.6
44.1
8.3
4.8
8.5
14.4
9.2
2.9
10.1
15.4
9.7
6.8
9.9
2.3
42
Appendix B
Table 12. Feed and water intake, digestibility and milk production of sows
Item
Consumption
Feed intake, kg/meal
Water intake, L/d
Ingested starch during sampling, g
Ingested fiber during sampling, g
Ingested protein during sampling, g
Ingested fat during sampling, g
6.83
45.9
1007
389
383
109
Digestibility (%)
DM
N
Fat
Energy
DF
81.6
81.4
57.7
81.1
66.0
Milk
Yield, kg/d
Fat, %
Protein, %
Lactose, %
12.87
5.77
4.28
5.38
43
Appendix C
Table 13. Arterial variables (mmol/L unless otherwise noted)
Item
Whole blood
Hematocrit, %
O2
CO2
Plasma
Glucose
Lactate
Urea
NH3
Alanine
Glycine
TAG
NEFA
95% conf. intv.
Glycerol
Acetate
Propionate
Butyrate
BHBA
Sampling time
2.5
3.5
Mean
-0.5
0.5
1.5
25.57
5.80
28.69
25.54
6.91
26.94
26.95
6.01
28.68
24.70
5.64
29.51
25.04
5.97
29.98
5.59
1.15
6.50
0.12
0.43
0.75
0.24
0.25
[0.13 ;
0.48]
0.10
0.45
0.00
0.02
0.13
4.71
0.91
6.73
0.10
0.32
0.71
0.71
0.60
[0.31 ;
1.16]
0.71
7.08
1.68
6.52
0.10
0.42
0.71
0.18
0.30
[0.15 ;
0.58]
0.01
0.47
0.01
0.02
0.14
5.78
1.40
6.44
0.11
0.47
0.70
0.14
0.13
[0.07 ;
0.25]
0.00
5.99
0.95
6.44
0.14
0.46
0.76
0.16
0.17
[0.09 ;
0.32]
0.01
0.35
0.00
0.02
0.13
0.13
0.13
4.5
5.5
6.5
SEM
25.79
5.34
28.41
26.45
5.54
28.04
24.45
5.64
28.91
25.62
5.34
29.04
1.10
0.42
0.62
5.67
1.17
6.41
0.15
0.49
0.85
0.15
0.17
[0.09 ;
0.34]
0.00
5.38
1.00
6.48
0.14
0.45
0.80
0.20
0.21
[0.11 ;
0.41]
0.02
0.46
0.01
0.02
0.14
5.17
1.10
6.52
0.12
0.41
0.75
0.19
0.26
[0.14 ;
0.51]
0.02
4.93
1.02
6.42
0.11
0.40
0.73
0.22
0.37
[0.19 ;
0.71]
0.01
0.50
0.00
0.02
0.13
0.30
0.12
0.28
0.01
0.04
0.04
0.05
0.14
0.14
0.01
0.03
0.00
0.00
0.01
44
Table 14. Portal variables (mmol/L unless otherwise noted)
Item
Whole blood
O2
CO2
Plasma
Glucose
Lactate
Urea
NH3
Alanine
Glycine
TAG
NEFA
95% conf. intv.
Glycerol
Acetate
Propionate
Butyrate
BHBA
Sampling time
2.5
3.5
Mean
-0.5
0.5
1.5
3.73
31.03
4.29
30.00
4.49
30.30
3.29
32.23
3.55
32.23
7.40
1.51
6.40
0.45
0.59
0.89
0.18
0.25
[0.15 ;
0.43]
0.02
1.35
0.35
0.18
0.14
5.58
1.12
6.56
0.43
0.42
0.85
0.20
0.60
[0.35 ;
1.03]
0.05
9.85
2.27
6.41
0.42
0.59
0.79
0.20
0.29
[0.17 ;
0.49]
0.02
1.23
0.31
0.16
0.14
8.13
1.74
6.38
0.41
0.67
0.82
0.14
0.13
[0.07 ;
0.22]
0.00
8.30
1.32
6.38
0.47
0.65
0.90
0.17
0.18
[0.11 ;
0.31]
0.01
1.11
0.30
0.14
0.14
0.13
0.14
4.5
5.5
6.5
SEM
3.62
30.67
3.65
30.53
3.52
31.43
3.45
30.87
0.29
0.63
7.80
1.61
6.25
0.49
0.69
1.02
0.15
0.20
[0.12 ;
0.34]
0.01
7.25
1.39
6.39
0.49
0.62
0.97
0.18
0.21
[0.12 ;
0.36]
0.01
1.44
0.39
0.19
0.14
6.45
1.40
6.49
0.41
0.53
0.92
0.18
0.26
[0.15 ;
0.45]
0.01
5.82
1.21
6.31
0.45
0.51
0.87
0.20
0.36
[0.21 ;
0.62]
0.02
1.61
0.43
0.23
0.14
0.41
0.13
0.28
0.03
0.05
0.05
0.05
0.14
0.13
0.01
0.09
0.04
0.02
0.01
45
Table 15. Hepatic variables (mmol/L unless otherwise noted)
Item
Whole blood
O2
CO2
Plasma
Glucose
Lactate
Urea
NH3
Alanine
Glycine
TAG
NEFA
95% conf. intv.
Glycerol
Acetate
Propionate
Butyrate
BHBA
Sampling time
2.5
3.5
Mean
-0.5
0.5
1.5
2.17
31.69
2.66
30.00
2.59
31.10
2.03
32.70
1.79
33.34
6.78
1.64
6.72
0.10
0.44
0.75
0.18
0.18
[0.10 ;
0.32]
0.00
1.11
0.02
0.06
0.15
5.58
1.11
6.75
0.09
0.31
0.69
0.19
0.47
[0.26 ;
0.84]
0.03
8.22
2.47
6.64
0.09
0.42
0.66
0.21
0.21
[0.12 ;
0.39]
0.00
0.98
0.01
0.06
0.15
6.78
1.89
6.65
0.10
0.46
0.70
0.15
0.09
[0.05 ;
0.16]
0.00
7.31
1.32
6.77
0.10
0.47
0.78
0.16
0.12
[0.07 ;
0.22]
0.00
0.83
0.01
0.04
0.14
0.14
0.14
4.5
5.5
6.5
SEM
1.96
31.70
1.99
31.14
2.09
32.17
2.23
31.34
0.36
0.67
7.05
1.80
6.51
0.12
0.54
0.87
0.15
0.11
[0.06 ;
0.20]
0.00
7.05
1.61
6.74
0.10
0.47
0.81
0.18
0.15
[0.08 ;
0.28]
0.00
1.29
0.02
0.08
0.15
6.06
1.50
6.82
0.09
0.42
0.76
0.19
0.20
[0.11 ;
0.37]
0.00
6.16
1.47
6.93
0.09
0.40
0.75
0.20
0.26
[0.14 ;
0.47]
0.00
1.34
0.02
0.07
0.15
0.34
0.20
0.30
0.01
0.05
0.05
0.05
0.15
0.14
0.01
0.12
0.00
0.01
0.01
46
Table 16. Blood and plasma flows (L/h)
Item
whole blood
Portal vein
Hepatic vein
Hepatic artery
plasma
Portal vein
Hepatic vein
Hepatic artery
Sampling time
2.5
3.5
Mean
-0.5
0.5
1.5
358.7
508.6
147.7
381.0
578.5
164.6
397.9
634.2
238.4
403.0
564.6
164.6
355.8
504.7
151.9
266.9
374.7
109.0
282.5
418.4
119.1
290.6
455.0
171.4
303.4
423.5
123.8
266.5
377.6
114.7
4.5
5.5
6.5
SEM
357.9
515.7
160.8
322.0
404.7
85.7
340.7
481.8
148.2
311.5
384.6
67.0
19.4
53.0
48.8
266.5
382.4
119.5
236.8
296.0
62.8
257.3
362.6
111.8
231.8
282.2
48.7
14.5
40.7
36.0
4.5
5.5
6.5
SEM
Table 17 Mammary extraction (%). Adapted from Krogh, et al. (2015, unpublished)
Item
Whole blood
O2
CO2
Plasma
Glucose
Lactate
Urea
TAG
NEFA
Acetate
Propionate
Butyrate
Sampling time
2.5
3.5
Mean
-0.5
0.5
1.5
34.5
-12.2
31.13
-15.32
24.14
-11.12
32.37
-12.17
39.34
-10.76
27.21
-9.85
43.20
-13.49
38.98
-11.43
39.67
-13.40
7.55
1.96
26.7
20.7
-0.5
40.2
-0.9
59.6
33.1
70.9
36.50
25.19
-1.05
39.34
28.47
23.37
22.53
-1.85
39.04
14.10
61.21
38.49
73.91
21.53
17.99
-0.34
45.69
-37.81
23.37
16.55
0.18
53.56
-23.27
60.48
38.85
71.83
21.21
18.92
-0.71
32.74
-20.34
27.86
18.81
0.30
38.39
2.54
54.73
24.09
66.11
28.26
24.38
-0.52
42.90
2.82
31.33
21.59
-0.07
30.11
26.39
62.01
31.07
71.66
2.84
4.54
0.91
8.35
13.25
5.55
13.09
4.84
47
Appendix D
Table 18. Arterial variables (mmol/L unless otherwise noted). Adapted from Krogh, et al. (2015, unpublished)
Item
Whole blood
Hematocrit, %
O2
CO2
Plasma
Glucose
Lactate
Urea
TAG
NEFA
Acetate
Propionate
Butyrate
Sampling time
2.5
3.5
Mean
-0.5
0.5
1.5
28.14
6.12
28.53
28.99
6.17
26.60
28.83
5.59
28.03
30.62
6.46
29.60
26.84
5.95
31.39
5.89
1.56
3.45
0.13
0.28
0.37
0.01
0.02
4.57
1.33
3.56
0.18
0.56
7.54
1.97
3.46
0.12
0.31
0.37
0.01
0.02
7.56
2.07
3.41
0.12
0.13
6.36
1.76
3.43
0.11
0.12
0.31
0.01
0.02
4.5
5.5
6.5
SEM
27.26
5.67
29.25
27.70
5.92
28.60
27.30
5.92
27.35
27.55
7.27
27.40
1.20
0.42
0.83
6.65
1.63
3.39
0.12
0.13
4.83
1.20
3.48
0.12
0.23
0.35
0.01
0.02
4.86
1.22
3.45
0.15
0.28
4.76
1.28
3.40
0.16
0.44
0.42
0.01
0.02
0.07
0.14
0.33
0.06
0.29
45.52
1.17
2.33
48
Appendix E
Auxiliary variables
De formula’s used to build the model were based on biochemical processes described in the books of (Berg et
al., 2002) and (Bender, 2014), unless mentioned otherwise. Abbreviations used in the model are given in Table
19. The main names and formulas used for several nutrients are given in Table 20. In the flows describing the
metabolism and utilization by the organ (Table 21), the first letter(s) before the underscore indicate the organ
(L=liver, MG=mammary gland), the letters between the first and second underscore indicate the source of the
flow (either directly from the blood or from another pool), and the letters after the second underscore indicate
the destination of the flow (either a pool, the TCA cycle or the milk). If the there is a third underscore after
which a 2 appears, this indicates a different value for outflow from one pool from inflow to another pool. If
there is O2 written behind the third underscore this indicates the O2 utilized during this flow and if there is a
CO2 this indicates CO2 released during this flow.
Table 19. Abbreviations used in the model
Abbreviation
NEFA
Pr
Bu
Ac
TAG
Lact
Glyc
Gluco
HC
Lac
non esterified fatty acid
propionate
butyrate
acetate
triglycerides
lactate
glycerol
glucose
haematocrit
lactose
49
Table 20. Main names and formulas used in the model for several nutrients
Name in model
aflow
pflow
hflow
mflow
Formula or source
Table 16
Table 16
Table 16
∑(((17*anefa*Enefa + 3*apr*Epr+ 4*abohb*Ebohb + 4*abu*Ebu +
2*aac*Eac + 54*aTAG*ETAG + 3*alact*Elact + 3*aglyc*Eglyc +
6*agluco*Egluco) - (-1*((aHC/100)+1)*atco2*Eco2 1*deaurea*Eurea))/100 )/ (12*MFlac + 54*MFfat)
anutrient
Table 13
pnutrient
Table 14
hnutrient
Table 15
Enutrient
Table 17
HFnutrient
hflow*hnutrient
AFnutrient
aflow*anutrient
PFnutrient
pflow*pnutrient
NHFnutrient
HFnutrient-(AFnutrient+PFnutrient)
ABnutrient
PFnutrient-APFnutrient
APFnutrient
anutrient*pflow
MFnutrient
anutrient*mflow
NMFnutrient
MFnutrient*Enutrient/100
Diet composition
FI
Digestibilities
Table 11
Table 12
Table 12
50
Table 21. Name of the flows and formulas used to calculate nutrient metabolism and utilization in the liver and mammary gland
Name flow
Diet
FI_N
FI_fat
FI_starch
DIG_fat
DIG_N
DIG_gluco
Metabolism liver
L_NEFA_storage
L_pr_pyr
L_AA_pyr
L_pyr_ketoAA
L_AA_urea
L_Gluco_pyr_co2
L_bu_ACOA
L_AA_pyr_o2
L_pr_pyr_o2
L_NEFA_ACOA_o2
L_AC_acoa
L_ACOA_ac
L_Pyr_lact
L_glyc_pyr
L_glyc_pyr_o2
L_TAG_glyc
L_NEFA_TAG
L_TAG_NEFA
L_NEFA_ACOA
Condition
Formula
FI*(DM/1000)*(CP/1000)
FI*(DM/1000)*(CFAT/1000)
FI* (DM/1000)* (Starch/1000)
(FIfat/24/ufat)*1000*(CFatdig/100)
(FIN/24/uprot)*1000*(Ndig/100)
(FIstarch/24/ugluco_starch)*1000*(starchdig/100)
Condition-1:
Formula-1:
Condition-2:
Formula-2:
Condition-1:
Formula-1:
Condition-2:
Formula-2:
Condition-1:
Formula-1:
Condition-2:
Formula-2:
Condition-1:
Formula-1:
Condition-2:
Formula-2:
NEFA_storage_eff*LNEFA
(PFpr+AFpr)-HFpr
L_gly_pyr + L_ala_pyr + L_restAA_pyr
L_AA_pyr
L_AA_pyr
L_gluco_pyr
(AFbu+PFbu-HFbu)*2
L_AA_pyr
L_pr_pyr
L_NEFA_ACOA * (17/2 -1)
<default>
0
HFac - (AFac+PFac) <0
(AFac+PFac)-HFac
<default>
HFac - (AFac+PFac)
HFac - (AFac+PFac) <0
0
HFlact-(AFlact+PFlact)
Lglyc
L_glyc_pyr*(1/2)
NHFTAG
<default>
3*NHFtag
NHFtag<0
0
<default>
0
NHFtag<0
-NHFtag*3
LNEFA* (1-NEFA_storage_eff)
51
L_NEFA_ACOA_2
L_ACOA_ox_co2
L_ACOA_ox_o2
L_pyr_ACOA
L_pyr_ACOA_o2
L_pyr_ACOA_co2
L_ACOA_ox
L_restAA_pyr
L_ala_pyr
L_gly_pyr
L_ACOA_BOHB
L_gluco_pyr2
L_gluco_pyr_o2
L_gluco_glyco
L_glyco_gluco
Condition-1:
Formula-1:
Condition-2:
Formula-2:
Condition-3:
Formula-3:
Condition-1:
Formula-1:
Condition-2:
Formula-2:
Condition-3:
Formula-3:
L_gluco_pyr
L_NH3_urea
L_co2_urea
Metabolism Mammary Gland
MG_GLUCO_lac
MG_GLUCO_pyr_2
MG_PYR_acoa
MG_GLUCO_pyr
MG_GLUCO_ppp
MG_PYR_glyc
MG_LAC_pyr
MG_AA_pyr
MG_FATsyn
MG_FA_fat
MG_FAsyn
L_NEFA_ACOA * (17/2)
L_ACOA_ox_2*2
Lo2
Lpyr
L_pyr_ACOA * (1/2)
L_pyr_ACOA
L_ACOA_ox_o2/2
L_NH3_urea-L_gly_pyr-L_ala_pyr
Lala
Lgly
(HFBOHB - (AFBOHB+PFBOHB))*2
L_gluco_pyr*2
L_gluco_pyr
NHFgluco< 0
-NHFgluco-L_gluco_pyr
LGluco<0
0
<otherwise>
0
NHFgluco>0
NHFgluco+L_gluco_pyr
LGlycogen <0
0
<otherwise>
0
36.838375
HFurea-(AFurea+PFurea)
L_AA_urea
MFlac*2
MG_GLUCO_pyr*2
MGpyr
MGgluco
(MG_FAsyn*15)/12+MG_Gluco_extrareducingpower
Condition-1:
MG_FATglycsyn
NMFlac
-NMFurea
MFfat-NMFtrigl
MGnefa
<default>
52
Formula-1:
Condition-2:
Formula-2:
MG_BOHB_acoa
MG_BU_acoa
MG_AC_acoa
MG_ACOA_fa_2
MG_NEFA_acoa
MG_Gluc_extrareducingpower
MG_NEFA_acoa_2
MG_NEFA_acoa_o2
MG_ACOA_fa
MG_PYR_glyc_o2
MG_GLUCO_pyr_o2
MG_PYR_acoa_o2
MG_PYR_acoa_co2
MG_PR_pyr_o2
MG_PR_pyr
MG_LAC_pyr_o2
MG_urea_co2
MG_urea_o2
MG_ACOA_tca
MG_O2_TCA
MG_CO2_TCA
MG_PPP_co2
Condition-1:
Formula-1:
Condition-2:
Formula-2:
Condition-1:
MG_FATsyn*3 -NMFnefa
MG_FATsyn*3 < NMFnefa
0
NMFbohb*2
NMFbu*2
NMFac
MG_FAsyn
<default>
0
MG_FAsyn=0
- (MG_FATsyn*3-NMFnefa)
(MG_PYR_acoa - MG_ACOA_fa - MG_ACOA_tca +
MG_AC_acoa + MG_BU_acoa +
MG_NEFA_acoa_2)>0
Formula-1:
(MG_PYR_acoa - MG_ACOA_fa - MG_ACOA_tca +
MG_AC_acoa + MG_BU_acoa +
MG_NEFA_acoa_2)/2
Condition-2:
Formula-2:
Condition-1:
Formula-1:
Condition-2:
Formula-2:
<otherwise>
0
<default>
0
MG_FAsyn=0
- (MG_FATsyn*3-NMFnefa) * (17/2)
MG_NEFA_acoa * ((17/2)-1)
<default>
MG_FAsyn *(17/2)
MG_FAsyn=0
0
MG_PYR_glyc
MG_GLUCO_pyr
MG_PYR_acoa/2
MG_PYR_acoa
MG_PR_pyr
NMFpr
MG_LAC_pyr/2
-NMFurea
-NMFurea/2
MG_O2_TCA/2
MGo2
MG_O2_TCA
MG_GLUCO_ppp*6
Condition-1:
Formula-1:
Condition-2:
Formula-2:
53
MG_FATglycsyn
Milk
MYlac
MFlac
MYfat
MFfat
MG_FATsyn-NMFglyc
MY*Mlac/100*1000
(MYlac/ulac)*1000/24
MY*Mfat/100*1000
(MYfat/ufat)*1000/24
54
Constants and parameters
The constants and parameters used to build the model are given in Table 22.
Table 22. Parameters and their value as used in the model
Parameter
Extraction Efficiencies
Eglyc
Ebohb
Mole mass
Ufat
Uprot
Ulac
uprot_milk
ugluco_starch
Other
NEFA_storage_eff
Maxglycogen
Value
29.8 % (Theil et al., 2012)
11 % (Theil et al., 2012)
855.468 g/mol
128.569 g/mol
342.29648 g/mol
143.44263 g/mol
162.1549 g/mol
0.4
890.6132 mmol
55