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Protein digestion in poultry – the value of an exogenous protease

Aaron Cowieson Principal Scientist, DSMProfessor of Poultry Nutrition, University of Sydney

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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

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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

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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.)

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Low (1980)

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Endogenous loss (Moughan & Rutherfurd, 2012)

• Sources of endogenous lossPancreatic and gastric enzymesMucinBileAcidsBicarbonateIntestinal 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

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Asp Thr Ser Glu Pro Gly Ala Val Ile Leu Tyr

Phe His Lys

Arg Cys Met

% o

f am

ino

acid

• amino acids of most significance, overall, are ser, gly, leu, pro, val, thr, asp• 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

20002500300035004000450050005500600065007000

Asp Thr Ser Glu Pro Gly Ala Val Ile Leu Tyr Phe His Lys Arg Cys Met

GE

(kca

l/kg

of a

min

o ac

id)

• 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.

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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?

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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?

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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

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-5

-4

-3

-2

-1

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1

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3

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Thr Ser Ile Cys Asp Val Gly Lys His Pro Leu Arg Ala Tyr Glu Phe Met

MEAN

% c

hang

e in

ilea

l dig

estib

ility

from

PC

to N

C

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)

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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

CO32- > SO4

2- > HPO42- > 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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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

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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

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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

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y = 3.3192x - 6.239R² = 0.3515

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2.5 3 3.5 4 4.5 5 5.5 6

Am

ino

acid

pro

file

of in

test

inal

m

ucin

(%)

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

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Performance Model: key terms that influence effect of proteaseSUBJECTIVE1. Relative performance of control birds (index Ross standard)

OBJECTIVE1. Diet CP, %2. Diet AME, kcal/kg3. dLys, %4. Limestone inclusion, % 5. AME:dLys ratio6. CP:dThr ratio7. AME:dSAA ratio8. dLys:dThr ratio

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Models – Grower/Finisher

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Models – Grower/Finisher

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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

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Grower/Finisher Model – how this may be applied in future

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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 23.13AME, kcal, kg 3107 3107.00 2900.00 2979.00 3004.40 3035.00 3107.00 3179.00 3200.00 3247.90 3275.00dLys, % 1.05 1.05 0.81 0.85 0.90 0.96 1.00 1.12 1.23 1.26 1.40dSAA, % 0.75 0.75 0.59 0.62 0.64 0.69 0.75 0.80 0.87 0.92 1.04dThr, % 0.71 0.71 0.55 0.55 0.60 0.64 0.69 0.78 0.83 0.87 0.96Limestone, % 0.8 0.80 0.00 0.24 0.35 0.53 0.63 1.13 1.51 1.60 2.00

DIET RATIOSdLys:dSAA 1.40 1.25 1.28 1.29 1.32 1.37 1.44 1.56 1.62 1.67AME:dSAA 4142.67 3238.04 3425.67 3661.21 3891.03 4254.67 4565.22 4822.72 5042.02 5411.67CP:dThr 26.94 22.94 24.34 25.22 25.64 26.59 28.86 29.64 30.40 31.82dLys:dThr 1.48 1.30 1.32 1.37 1.41 1.47 1.53 1.61 1.65 1.86

BIRD INPUTSRelative 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

OUTPUTPredicted ProAct Effect (% FCE/BWG change) 2.8

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Application in the future

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Application in the future

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Where do the performance effects of ProAct come from?

• Mechanisms responsible for the ‘extra-proteinaceous’ effects of ProActmay include:– Gut health– Mucosal integrity– Tight junction integrity– Collagen structure– Mucin and enzyme flow– Litter quality

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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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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 ProteinUsefulness 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

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• 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 AuburnGehring et al. (2013) Poultry Science

Sample Quality

SalineProtein

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

NRC3843

NRC4025

NRC8405

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

%

High1

High2

Moderate3

Moderate4

Low5

Low6

P = 0.57SEM = 1.44

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Ileal Digestible Energy

NRC3843

NRC4025

NRC8405

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

High1

High2

Moderate3

Moderate4

Low5

Low6

1 and 2 vs. 5 and 6 P = 0.0011 vs. 6 P = 0.014SEM = 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

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• 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)

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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

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