Presentation at the DSM Feed Enzymes Seminar 2014, The Netherlands

1. Protein digestion in poultry – the value
of an exogenous protease
Aaron Cowieson
Principal Scientist, DSM
Professor of Poultry Nutrition, University of Sydney

2. Page
Presentation Overview
• Introduction and key concepts in protein digestion
• Endogenous and exogenous sources of protein in the intestine
• Factors that influence protein/amino acid digestion
• Optimising the use of exogenous protease and the importance of
benchmarking raw material quality
• Conclusions
1

3. Page
Introduction
• Protein/amino acids are among the most expensive nutrients to deliver in
poultry nutrition
• The digestibility of protein in poultry is typically incomplete by the
terminal ileum
• Undigested protein that leaves the ileum is from both exogenous (diet)
and endogenous (bird) sources
• Understanding the digestion of dietary proteins and the recovery of
endogenous proteins is important and can provide a basis for the use of
exogenous proteases
2

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Key Concepts - background
• Substantial input of endogenous protein into the lumen during digestion
• Endogenous proteins are not fully recovered by the terminal ileum (estimates
around 80-90%, Souffrant et al., 1993)
• Endogenous proteolysis requires co-operative effort from several peptidases
• Most (80%) amino acids are recovered from the lumen as di- and tri-peptides,
not as free amino acids (Ganapathy et al., 1994)
• Cytostolic peptidases have limited capacity to hydrolyse tetrapeptides (Sterchi
& Woodley, 1980)
• Dietary protein is generally well recovered and amino acids that exit the
intestine are largely of endogenous origin
• Ileal measurements are more meaningful (microbial synth/metab.)
3

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Low (1980)
4

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Endogenous loss (Moughan & Rutherfurd,
2012)
• Sources of endogenous loss
Pancreatic and gastric enzymes
Mucin
Bile
Acids
Bicarbonate
Intestinal cells
(Microbial protein)
Saliva
• ‘Loss’ defined when an endogenous secretion
leaves the ileum (amino acid cost to the animal)
where there will be no further reasorption
BALANCE OF
SECRETION
AND
ABSORPTION!

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Amino acid profile of endogenous proteins
0
2
4
6
8
10
12
Asp
Thr
Ser
G
lu
Pro
G
ly
Ala
Val
Ile
Leu
Tyr
Phe
H
is
Lys
Arg
C
ys
M
et
%ofaminoacid
• amino acids of most significance, overall, are ser, gly, leu, pro, val, thr, as
• of least significance are met and his
Mean = 5.3%
• mean amino acid profile of 8 sources of endogenous protein

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Energy associated with amino acids
2000
2500
3000
3500
4000
4500
5000
5500
6000
6500
7000
Asp Thr Ser Glu Pro Gly Ala Val Ile Leu Tyr Phe His Lys Arg Cys Met
GE(kcal/kgofaminoacid)
• All amino acids have associated energy – ranges from 2891kcal/kg
for aspartic acid to 6739kcal/kg for phenylalanine
• The energetic consequence of the ingestion of an antinutrient
will depend on the profile of amino acid response (AA profile of
lost protein) & synthesis energy requirements
Mean = 4954kcal/kg

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Adaptation to new diets – Corring (1980)
• GIT physiology is fluid and adapts readily to changing diet composition.
8

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Recovery of endogenous protein
• Whilst much (perhaps 85%) of the endogenous protein is recovered and
retained, some is lost and either excreted or modified by the hind gut
microflora
• Some endogenous protein sources are more readily recovered than others
• Hydrophobic and/or refractory proteins are poorly recovered
• Approximately 70% of endogenous protein is secreted distally from the
stomach/gizzard and so does not readily undergo gastric digestion (Fuller &
Reeds, 1998)
• Glycosylated domains of mucin (rich in Ser, Thr, Pro) are poorly recovered
(Forstner & Forstner, 1994)
• Can we assist the bird with recovery of endogenous protein and/or reduce (in
an appropriate way) endogenous secretion?
9

11. Page
Fuller & Reeds, 1994
• Suggest that approx 1g of endogenous protein is secreted into the GIT for
every 2g of dietary protein ingested
• Dietary protein recovery is approximately 93% complete (on a ‘true’ basis)
• Endogenous protein recovery is approximately 89% complete
• Which endogenous proteins should be the ‘target’ for next generation
exogenous enzymes?
10

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Exogenous enzymes and endogenous
secretion
• Reduced antinutritive effects of e.g. phytate and fibre via exogenous enzymes
– reduced endogenous loss
• Supplementation with exogenous enzymes can directly influence endogenous
production e.g. Jiang et al. (2008) – amylase mRNA
2,250mg/kg of supplementary amylase reduced pancreatic amylase
mRNA by around 20%
• Exogenous enzymes can alter GIT length and improve net energy e.g.
Cowieson et al. (2003), Pirgozliev et al. (2009, 2010)
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• Effect of added fat (canola oil) on amino acid digestibility in piglets
Li & Sauer (1994)
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Fat removal may compromise
digestibility of AA
-6
-5
-4
-3
-2
-1
0
1
2
3
4
Thr
S
er
Ile
C
ys
A
sp
V
al
G
ly
Lys
H
is
P
ro
Leu
A
rg
A
la
Tyr
G
lu
Phe
M
etM
E
AN
%changeinilealdigestibilityfromPCtoNC
d21 d42
Cowieson et al., 2010: 2% fat removed (PC to NC)

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Phytase and protease?
• Bohn et al. (2007) phytate/protein globoids
• The protein shell makes these resistant to phytases
• Leske & Coon (1999) – phytate susceptibility differs in different
raw materials – protease may help (xylanase appears not to)
14

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Bye et al. (2013)
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• Prof. Franz Hofmeister (1850-1922)
• Born in Prague, 1850
• Pharmaceutical chemistry
• Proposer of the ‘Hofmeister Series’ ionic
grouping based on their ability to influence
protein solubility
Franz Hofmeister

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• Effect of ions on protein solubility
CO3
2- > SO4
2- > HPO4
2- > OH- > F- > HCOO- > CH3COO- > Cl- > Br-
> NO3
- > I- > SCN- > ClO4
-
• Fig. 1 Representation of Hofmeister anions with
increasing chaotropic potency from left to right (adapted
from Leontidis, 2002; Zhang & Cremer, 2006).
Cs+ > Rb+ > NH4
+ > K+ > Na+ > Li+ > Mg+ > Sr2+ > Ca2+
• Fig. 2 Representation of Hofmeister cations with
increasing chaotropic potency from left to right (adapted
from Hess & van der Vegt, 2009)
Hofmeister Series

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• Effect of 1M ion salts on soy protein solubility (%):
Damodaran & Kinsella (1982)
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0
10
20
30
40
50
60
70
80
NaI NaCl Na2SO4

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Huang et al. (2005) British Poultry Science
• Wheat/Canola – overall a decrease in AA digestibility d14-42
• Corn/Soy – overall an increase in AA digestibility d14-42

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Importance of benchmarking
• Enzymes act on substrates – substrate type and concentration is clearly
important e.g. phytate, fibre, refractory proteins and starch
• Enzymes can degrade antinutrients such as trypsin inhibitors and phytate
• INHERENT DIGESTIBILITY OF FOCAL NUTRIENTS is absolutely central to the
magnitude and consistency of enzyme effects (Cowieson, 2010)
– Xylanase, protease and phytase all follow this rule
• So, how do we integrate these thoughts in order to optimise the use of
enzymes in our diets?
• Meta-analysis of large databases to show key leverage terms that promote
enzyme efficacy
20

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Methodology
• Digestibility meta-analysis included 804 datapoints from 25 independent
experiments
• Performance meta-analysis included 673 datapoints from 63 independent
experiments
• Data were generated from experiments run between 2006 and 2013
• Most trials were conducted in EU, US and Brazil
• Models were constructed using the statistical software ‘R’
– trials nested in region and ProAct treatment nested in trial
– compared with the appropriate control
• Predictors were assessed based on degree of statistical significance and
biological relevance
21

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Digestibility
• Mean response to ProAct was
around 4% ranging from 5.6% for
Thr to 2.7% for Glu
• AME was significantly increased by
49 Kcal/kg and fat dig by 1%
• Inherent digestibility in the control
diet explained around 47% of the
variance in response (Fig above)
• Pattern of response is correlated
with the AA profile of intestinal
mucin (Fig below)
• We need to be able to predict
control digestibility to better
predict ProAct effect
22
y = 3.3192x - 6.239
R² = 0.3515
0
2
4
6
8
10
12
14
16
18
2.5 3 3.5 4 4.5 5 5.5 6
Aminoacidprofileofintestinal
mucin(%)
Change in amino acid digestibility with protease (%)

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Performance Modelling
• Considered 93 separate leverage terms
• Significance set at P < 0.05
• Non-significant terms re-introduced once a
beta-model was in place to confirm lack of
importance
• Heat mapping used to check for co-linearity
23

25. Page
Performance Model: key terms that
influence effect of protease
SUBJECTIVE
1. Relative performance of control birds (index Ross standard)
OBJECTIVE
1. Diet CP, %
2. Diet AME, kcal/kg
3. dLys, %
4. Limestone inclusion, %
5. AME:dLys ratio
6. CP:dThr ratio
7. AME:dSAA ratio
8. dLys:dThr ratio
24

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Models – Grower/Finisher
25

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Models – Grower/Finisher
26
LOWER VALUE OF PROACT:
- High CP
- Low AME
- Good bird performance
- High limestone
- Inappropriate AA balance:
- LOW dLys:dSAA
- HIGH dLys:dThr
- LOW CP:dThr
- HIGH AME:dSAA
HIGH VALUE OF PROACT:
- Low CP
- High AME
- Poor bird performance
- Low limestone
- Appropriate AA balance:
- HIGH dLys:dSAA
- LOW dLys:dThr
- HIGH CP:dThr
- LOW AME:dSAA

28. Page
Grower/Finisher Model – how this may be
applied in future
27
DIET INPUTS MODEL TERMS MEAN IN DATABASE 0% 5% 10% 25% 50% 75% 90% 95% 100%
CP, % 19.13 19.13 15.18 16.30 17.01 18.00 19.00 20.10 22.00 22.00 23.13
AME, kcal, kg 3107 3107.00 2900.00 2979.00 3004.40 3035.00 3107.00 3179.00 3200.00 3247.90 3275.00
dLys, % 1.05 1.05 0.81 0.85 0.90 0.96 1.00 1.12 1.23 1.26 1.40
dSAA, % 0.75 0.75 0.59 0.62 0.64 0.69 0.75 0.80 0.87 0.92 1.04
dThr, % 0.71 0.71 0.55 0.55 0.60 0.64 0.69 0.78 0.83 0.87 0.96
Limestone, % 0.8 0.80 0.00 0.24 0.35 0.53 0.63 1.13 1.51 1.60 2.00
DIET RATIOS
dLys:dSAA 1.40 1.25 1.28 1.29 1.32 1.37 1.44 1.56 1.62 1.67
AME:dSAA 4142.67 3238.04 3425.67 3661.21 3891.03 4254.67 4565.22 4822.72 5042.02 5411.67
CP:dThr 26.94 22.94 24.34 25.22 25.64 26.59 28.86 29.64 30.40 31.82
dLys:dThr 1.48 1.30 1.32 1.37 1.41 1.47 1.53 1.61 1.65 1.86
BIRD INPUTS
Relative Performance, % lifetime dif to breeder target 1.2 1.20 -69.80 -29.74 -17.62 -11.59 4.10 14.11 22.34 28.65 35.91
OUTPUT
Predicted ProAct Effect (% FCE/BWG change) 2.8

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Application in the future
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30. Page
Application in the future
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31. Page
Where do the performance effects of
ProAct come from?
• Mechanisms responsible for the ‘extra-proteinaceous’ effects of ProAct
may include:
– Gut health
– Mucosal integrity
– Tight junction integrity
– Collagen structure
– Mucin and enzyme flow
– Litter quality
30

32. Page
Future application of ProAct
• Articulated
– Digestibility effects may be further optimised via raw material quality
assessment
– Additional performance benefits may be delivered through meta-
analysis model application
• How may a raw material assessment tool be developed?
• A case study on corn
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33. Page
Corn Quality
• Hydration is a pre-requisite for digestion
• Composition is not an adequate predictor of
AME or protein quality
- Corns with identical starch, protein and fat contents may not
have the same AME
- Different starch and protein solubility can lead to different
ileal digestibilities and thus undigested fractions
- Solubility of corn starch and protein can be
estimated in vitro
- A laboratory has developed a method to estimate starch and
protein quality (starch industry) and also feeding value

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Salt Soluble Protein
Usefulness for predicting quality
• Nutritional value of corn is well correlated with chemical composition and
solubility of protein
• Several trials have demonstrated these correlations:
– Gehring et al. (2013) Worlds Poultry Science Journal
– Gehring et al. (2013) Poultry Science
– Gehring et al. (2012) Poultry Science
– Kaczmarek et al. (2007) ESPN
– Kaczmarek et al. (2013) Animal Production Science
– Metayer et al. (2009) Worlds Poultry Science Journal
• And more generally in other species
– Malumba et al. (2009) Journal of Food Engineering
– Malumba et al. (2008) Food Chemistry
– Malumba et al. (2010) Carbohydrate Polymers
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CORN QUALITY ASSESSMENT
- to scale enzyme response
34
• Mean = 46.4% - relative to albumin standard
• N = 93
• SD = 11.23
• Min/Max = 19.1-65.9

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Undried Corn Starch
Source: University of Poznan, Poland

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Dried Corn Starch
Source: University of Poznan, Poland

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Trial at University of Auburn
Gehring et al. (2013) Poultry Science
Sample Quality
Saline
Protein
Solubility
(%)
Vitreousness
(%)
Starch
(%)
Protein
(%)
Oil
(%)
Crude
fiber
(%)
Predicted
AMEn
(kcal/kg)
1 High 49.2 58.5 74.83 8.36 3.72 2.67 3,274
2 High 46.6 59.8 74.63 9.91 3.45 2.79 3,295
3 Moderate 39.4 59.2 75.54 8.12 3.72 2.62 3,236
4 Moderate 33.4 59.7 74.51 8.17 3.79 2.65 3,174
5 Low 26.9 60.0 74.92 8.17 3.72 2.59 3,143
6 Low 25.7 57.8 75.88 8.01 3.69 2.58 3,159

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Apparent Ileal N Digestibility
NRC
3843
NRC
4025
NRC
8405
72.0
73.0
74.0
75.0
76.0
77.0
78.0
1 2 3 4 5 6
77.15
75.87
75.06 75.04
74.09 74.04
%
High
1
High
2
Moderate
3
Moderate
4
Low
5
Low
6
P = 0.57
SEM = 1.44

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Ileal Digestible Energy
NRC
3843
NRC
4025
NRC
8405
3,150
3,200
3,250
3,300
3,350
3,400
3,450
1 2 3 4 5 6
3,408
3,358
3,316 3,322
3,248
3,287
kcal/kg
High
1
High
2
Moderate
3
Moderate
4
Low
5
Low
6
1 and 2 vs. 5 and 6 P = 0.001
1 vs. 6 P = 0.014
SEM = 34

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Vitreousness
• Indication of endosperm hardness (protein/starch matrix & density)
• (A) High Vitreousness (starch imbedded in prolamin-protein matrix)
• (B) Low Vitreousness (floury starch) – from Gibson et al., 2003
• High vitreousness = poorer digestibility of protein and starch

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CORN QUALITY ASSESSMENT
- to scale enzyme response
41
• Mean = 61.4%
• N = 93
• SD = 2.43
• Min/Max = 52.5-66.5

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Implications
• ProAct is currently widely used to reduce feed cost and does so very
successfully
• DSM are currently working on further enhancement of the application of
ProAct to deliver additional value through:
– Possible further feed cost savings linked to raw material quality
– Improved performance of birds via diet balance (meta-analysis)
42

44. Page
Conclusions
• Protein digestion in poultry (and other animals) is a complex process of
hydrolysis of incoming proteins, absorption, further processing and the
concurrent secretion and recovery of endogenous protein
• Endogenous proteins are often less well recovered that exogenous proteins
and ProAct may assist the animals with digestion of both fractions
• Though ProAct currently delivers substantial value through the CP/AA
matrices and/or DIF values and the focus of use is feed cost saving there
may be additional advantages in performance in the future
• Work is ongoing to further explore the mechanisms responsible for the
effect of ProAct on gut health, litter quality, performance etc.
• In the future the value of ProAct may extend beyond feed cost savings to
offer performance enhancement
43