Influence of feed efficiency and physiological state on rumen VFA and microbial profiles in cattle

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1 2 3 4 Influence of feed efficiency and physiological state on rumen VFA and microbial profiles in cattle S Lam 1, J Munro 2, J Cant 1, L Guan 3, M Steele 3, F Schenkel 1, S Miller 1,4, Y Montanholi 2

Outline Introduction Hypothesis Objectives Materials and methods Grain-fed study Grass-fed study Results and discussion Conclusion Acknowledgements 2

Introduction: Industry challenges 30-50% agriculture GHG 3

Introduction: Industry challenges 30-50% agriculture GHG Feed costs $ Herd cost variation 4

Introduction: Feed efficiency Feed Efficiency 5

Introduction: Feed efficiency Feed Efficiency 6

Introduction: Feed efficiency Milk and colostrum composition (Montanholi et al. 2013) Feed Efficiency Blood metabolites and hormones (Kelly et al. 2011, Gonano et al. 2014) Fertility traits (Awda et al. 2013, Fontoura et al. 2015) Cardiac physiology (Munro et al. 2016) 7

Introduction: Rumen metabolism % 10% of the biological variation of RFI due to digestibility (Richardson and Herd 2004) Rumen and reticulum = 75% total digestive tract (Baldwin 1980) Large energetic sink with high energy demand (Hungate 1960) Area of energy absorption - 75% total VFA (Bergman 1990) 8

Introduction: Microbiology Bacteria (10 11 cells/ml) 75% feed particle digestion Fungi (10 3-10 4 cells/ml) Fibrolytic particle digestion Methanogens (10 4-10 6 cells/ml) Methanogen ecology associated with methane emissions Protozoa (10 4-10 6 cells/ml) Ciliate species digesting suspended and colonized feed particles Feed efficiency (Guan et al. 2008, Zhou et al. 2009, Hernandez et al. 2012, Carberry et al. 2014) 9

Introduction: Volatile fatty acids (VFA) 75% energy requirements Feed efficiency (Guan et al. 2008, Hernandez-Sanabria 2012) 10 (Briggs et al. 1957, Bergman et al. 1990)

Introduction: Rumen microstructure Sheep papillae microstructure Low energy diet: High energy diet: Stratum corneum thickness Energy in diet (Steele et al. 2012) 11

Introduction: Rumen ph ph = 14 alkaline ph = 7 neutral acidic ph = 0 (Kimura et al. 2016) 12

Hypothesis Feed efficiency is associated with energetic processes and the rumen is a highly metabolically active organ. Therefore, the variability in rumen metabolism across feed efficiency phenotypes and dietary treatments may be featured through rumen functional and structural assessments. 13

Objectives Microbiology Papillae epithelium Volatile fatty acids (VFA) 100x Rumen ph 14

Objectives Microbiology Efficient Papillae epithelium vs Inefficient Grain-fed animals Grass-fed animals Volatile fatty acids (VFA) 100x Rumen ph 15

Materials: Experimental conditions Feedlot study 48 crossbred cattle Trial length: 112 d 16 Steers Overall breed composition 15.7% 39.4% 44.9% Elora Beef Research Centre 16 Steers BW = 506 + 72 kg Average BW = 536 + 43 kg 16 Bulls BW = 531 + 57 kg 16

Materials: Experimental conditions Grass-fed study Overall breed composition 141 crossbred cattle 23.6% Trial length: 124 d 55.2% 21.2% 107 heifer calves 36 pregnant heifers BW = 253 ± 38 kg Age = 403 ± 27 d BW = 406 ± 42 kg Age = 594 ± 95 d Maritime Beef Test Station 17

Methods: Diet INSENTEC feeding system Chemical Composition Dry Basis (%) Dry Matter 53.8 Crude Protein 13.9 Acid Detergent Fibre 10.9 Neutral Detergent Fibre 22.2 Starch 45.0 Total Digestible Nutrients 86.0 Ingredient Composition Dry Basis (%) High-moisture corn 52.5 Haylage 42.3 Soybean meal 3.5 Premix* 1.7 18 *Contains 40% of calcium phosphate, 60% trace mineralized salt

Methods: Diet Chemical Composition Dry Basis (%) Dry matter 36.1 Crude Protein 15.5 Acid Detergent Fibre 29.6 Neutral Detergent Fibre 53.7 Starch 6.5 Total Digestible Nutrients 70.3 Ingredient Composition Dry Basis (%) Haylage 99.5 GROWSAFE feeding system Premix* 0.5 *Contains 37.4% of calcium phosphate, 62.7% trace mineralized salt 19

Methods: RFI models Grain-fed (R 2 = 0.74): Fatness Body Size Rate of Gain Leanness Feed intake = [μ + (β 1 x body weight)] + (β 2 *ADG) - (β 3 *ribeye area) + (β 4 *back fat) (β 5 *marbling) + subpopulation + RFI Grass-fed (R 2 = 0.61): Fatness Body Size Rate of Gain Leanness Feed intake = [μ + (β 1 *body weight)] + (β 2 *ADG) - (β 3 *ribeye area) + (β 4 *rump fat) (β 5 *age) + subpopulation + RFI 20

Methods: Sample collection 5.5+1 d prior slaughter End of performance test ph logger insertion Rumen fluid Rumen tissue 21

Methods: Logger insertion Rumen ph loggers T9 LRCpH Data Logger Dascor Method: esophageal tubing Logger sensor Recording: 5 minute intervals (~2,600 data points/animal) 22

Methods: Rumen fluid collection Method: Oro-ruminal probe with suction Evaluating: Microbiology Volatile fatty acid profiles 23

Methods: Microbiology Method: Rumen fluid DNA isolation RT-qPCR Ruminal fluid DNA analysis: Bacteria Protozoa Fungi Methanogen Evaluating: 10 um 24 (Doddema 1978; Mathers and Miller 1980; Godfried 1980)

Methods: VFA Evaluated: VFA molar concentrations Acetate Propionate Butyrate Valerate Isovalerate Isobutyrate Caproate Method: VFA sample processing Total VFA concentration Bruker, CP-8400 Autosampler 25

Methods: Rumen tissue collection Method: Tissue collection Processed for histomorphology dorsal blind Evaluating: Papillae epithelial thickness ventral ventral blind 26

Methods: Histomorphometry Histology traits: Stratum corneum Papillae width Tip Middle piece Base 27

Rumen ph Methods: ph measurements 7.6 7.4 7.2 7 6.8 6.6 6.4 6.2 High-RFI- Predicted ph High-RFI- Observed ph 6 0:00 2:24 4:48 7:12 9:36 12:00 14:24 16:48 19:12 21:36 0:00 28 Time (hh:mm)

Methods: Statistical analysis Univariate Normality Procedure Skewness, Kurtosis, Anderson-Darling Test Transformations logarithm squared GLM Select procedure Determine model effects General Linear Model (GLM) Procedure Rumen traits Partial Least Square procedure Determine % contribution to RFI + - 50% Efficient vs. 50% Inefficient Y ijkl = μ + efficiency group i + subpopulation j + breeds k + ϵ ijkl 29

Results: Physiological status Trait (%/total VFA) Heifer calves Pregnant heifers P-value Acetate 71.68 74.62 <0.01 Propionate 18.30 16.53 <0.01 Isobutyrate 0.97 0.89 0.051 Butyrate 7.29 6.47 <0.01 Isovalerate 0.90 0.90 0.952 Valerate 0.58 0.41 <0.01 Caproate 0.28 0.18 <0.01 Total VFA (µmol/ml) 43.52 37.39 <0.01 30

Results: Physiological status Trait (%/total VFA) Heifer calves Pregnant heifers P-value Acetate 71.68 74.62 <0.01 Propionate 18.30 16.53 <0.01 Isobutyrate 0.97 0.89 0.051 Butyrate 7.29 6.47 <0.01 Isovalerate 0.90 0.90 0.952 Valerate 0.58 0.41 <0.01 Caproate 0.28 0.18 <0.01 Total VFA (µmol/ml) 43.52 37.39 <0.01 Pregnant heifers Bacteria population Metabolic activity throughout gestation VFA metabolism and energy demand (Church, 1988; Drackley et al. 2001) 31

Results: RFI Microbial profiles Trait (16s rrna copy/ml) Inefficient Efficient P-value Total bacteria 4.3x10 11 7.6x10 11 <0.05 Methanogen 4.9x10 9 2.3x10 9 <0.05 Protozoa 4.3x10 7 1.5x10 7 0.18 Fungi 6.3x10 4 3.8x10 4 0.37 Trait (16s rrna copy/ml) Inefficient Efficient P-value Total bacteria 6.0x10 10 5.3x10 10 0.16 Methanogen 2.6x10 7 3.1x10 7 <0.05 Protozoa 1.2x10 5 1.6x10 5 0.30 Fungi 1.3x10 5 1.9x10 5 <0.05

Results: RFI VFA profiles Trait (%/total VFA) Inefficient Efficient P-value Inefficient Efficient P-value Acetate 54.4 54.5 0.97 73.48 72.95 0.55 Propionate 29.0 29.3 0.89 17.25 17.45 0.38 Isobutyrate 1.2 1.0 0.11 0.90 0.95 <0.10 Butyrate 8.9 8.6 0.75 6.81 6.91 0.44 Isovalerate 3.0 2.7 0.41 0.87 0.94 <0.05 Valerate 2.6 2.9 0.29 0.47 0.49 0.43 Caproate 0.4 0.5 0.40 0.22 0.22 0.87 Total VFA (µmol/ml) 78.0 80.3 0.66 38.94 41.83 <0.10 33

Results: Variance analysis 32.5% 21.5% 34

Results: Variance analysis 44.3% 25.5% 24.5% Bacteria 25.1% 25.1% Methanogen 24.1% 25.8% Protozoa Fungi 24.9% 24.9% 10.0% 32.5% 21.5% 35

Results: Variance analysis 44.3% 25.5% 24.5% Bacteria 25.1% 25.1% Methanogen 24.1% 25.8% Protozoa Fungi 24.9% 24.9% 10.0% 32.5% 21.5% 55.7% 0.9% 9.8% 19.0% 36.2% 16.5% 15.3% 18.8% 12.5% 90.0% 5.5% 19.9% 8.6% 7.6% 15.3% 14.0% 36

Results: Papillae histomorphometry ventral blind Papillae width Papillae area Inefficient Efficient P (µm) Base 110.1 113.4 0.39 Middle 119.5 139.4 <0.05 Tip 125.0 148.4 <0.01 37

Results: Predicted rumen ph curves Rumen ph Feed intake (kg) 7.4 7.2 7.0 6.8 6.6 6.4 6.2 0.18 0.16 0.14 0.12 0.10 0.08 0.06 0.04 0.02 6.0 0.00 0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 38 Time of day (hh:min)

Rumen ph Feed intake (kg) Results: Predicted rumen ph curves 7.4 * * = P < 0.05 0.18 7.2 7.0 6.8 6.6 6.4 6.2 * * * * * * * * * * * 0.16 0.14 0.12 0.10 0.08 0.06 0.04 0.02 6.0 0.00 0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 39 Time of day (hh:min)

Rumen ph Feed intake (kg) Results: Predicted rumen ph curves 7.4 7.2 7.0 6.8 6.6 6.4 6.2 * * * * * * 93% * * * * = P < 0.05 * 5.6 < ph < 6.0 * Inefficient 4.4% vs Efficient 8.5% P = 0.02 * 0.18 0.16 0.14 0.12 0.10 0.08 0.06 0.04 0.02 6.0 0.00 0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 40 Time of day (hh:min)

Summary Bacteria population Feed Efficiency 41

Summary Bacteria population Methanogen population Feed Efficiency Methanogen population 42

Summary Bacteria population Methanogen population Feed Efficiency Methanogen population Total and specific VFA 43

Summary Bacteria population Methanogen population Feed Efficiency Papillae width Circadian ph Methanogen population Total and specific VFA 44

Conclusions Rumen microbiology, functional and structural parameters are important in assessing the underlying digestive biology of feed efficiency Dietary treatment has an impact on the relevance of rumen parameters used for indicating feed efficiency 45

Acknowledgements Advisor: Dr. Yuri Montanholi Colleagues and volunteers Technical staff Yanhong Chen Tim Caldwell Elora beef research centre Maritime beef testing station 46