Meta-analysis: explicit value of mono-component proteases in monogastric diets

Meta-analysis: explicit value of mono-component proteases in monogastric diets ABSTRACT A meta-analysis was conducted to investigate the effect of mono-component proteases on performance and apparent ileal amino acid digestibility (AIAAD, %) in monogastrics. A total of 67 experimental trials were included in the meta-analysis from published and internal reports, contributing 467 lines of data. Poultry and swine data accounted for 81 and 19% of the dataset, respectively. Forty-four different proteases were included in the meta-analysis, accounting for commercial and non-commercial products. Mixed Model analysis was used to assess protease effect and the influence of inherent characteristics of the control on protease response. The mean performance response to protease was a reduction in feed conversion ratio (FCR) for poultry (1%, P < 0.05) and swine (4%, P > 0.05). The mean relative effect of protease on AIAAD over the control was 1.6 ± 0.3%, ranging from 1.2% for Arg, Phe and Trp to 2.6% for Cys. For the majority of amino acids, inherent AIAAD of control diets influenced (P < 0.05) the magnitude of the protease response such that, as inherent digestibility increased, the effect of protease on amino acid digestibility decreased. The dataset was subsequently divided into 2 subgroups: diets with and without other enzymes, namely non-starch polysaccharide degrading enzymes (NSPase) and phytase. Addition of protease in diets containing no other enzymes significantly (P < 0.05) increased AIAAD for the majority of amino acids and tended (P < 0.10) to improve Met, Trp, Pro, Gly, and Tyr. However, when other enzymes were included in the experiment, the beneficial effect of protease on AIAAD was lost (P > 0.05). These findings suggest that when other enzymes are already included in the diet, addition of protease requires further justification for use in monogastric diets. INTRODUCTION Historically, exogenous proteases have been incorporated into enzyme cocktails to improve animal performance (Kocher et al., 2002; Omogbenigun et al., 2004; Cowieson and Adeola, 2005), with minimal evidence that this enzyme provides any explicit value. More recently, mono-component proteases have made their way into the market, with concurrently more research into this area. With rising costs of protein sources, such as soybean meal (SBM), considerable attention is being given to reduce the protein content of animal feed without hindrance to animal performance (Vieira et al., 2016). This concept involves assigning a matrix value for amino acids to the exogenous protease and consequently reducing the amino acid density of the diet (Romero et al., 2013; Olukosi et al., 2015). This is a similar strategy to that employed with phytases, whereby a mineral matrix is applied to the enzyme and inorganic phosphate sources consequently removed. While phytase acts specifically on phytate in the feed, protease is exposed to a vast array of protein substrates of different amino acid composition and molecular weight. Due to substrate variably, the efficacy of a specific protease can be somewhat inconsistent (Acamovic, 2001). An alternative use of exogenous proteases is to enable the substitution of SBM with less digestible and cheaper sources of protein, including animal by-product meal or canola meal (Shahir et al., 2016; Mahmood et al., 2017b). A broad range of endogenous proteases are synthesized and secreted into the digestive tract of monogastric animals, in order to sufficiently utilize dietary protein (Le Huerou-Luron et al., 1993; Nir et al., 1993). However, reduced growth and performance of animals fed poorer digestible protein sources (Qaisrani et al., 2014) indicate the possible inadequacies of endogenous proteases already present in the gastrointestinal tract, particularly in the young animal (Noy and Sklan, 1995; Hedemann and Jensen, 2004). This promotes the idea that exogenous proteases can be used to enhance digestion of dietary proteins that may be unfavorable substrates for endogenous proteases. Nonetheless, the varying nutrient profiles of ingredients can result in an inconsistent protease value. This can make choosing a suitable protease particularly difficult, as the type of protease required will differ depending on the ingredients being fed. Meta-analysis refers to the compiling of results from a number of individual studies for statistical analysis, thereby allowing findings to be integrated and broader interpretations to be made (Glass, 1976). A previous meta-analysis of the literature by Cowieson and Roos (2014) explored the effect of a specific protease (Ronozyme® ProAct) on apparent ileal amino acid digestibility (AIAAD, %) in monogastrics. On further review of the publications included in the meta-analysis, it was noted that a number of experiments presented total excreta amino acid digestibilities rather than ileal (Carvalho et al., 2009; Bertechini et al., 2009a; Bertechini et al., 2009b). Differences between measurements of ileal and excreta digestibilities (Ten Doeschate et al., 1993), as a result of protein turnover by microbes in the hind gut, signify that digestibilities determined in the terminal ileum are more accurate than those measured in the excreta (Ravindran et al., 1999). Therefore, it would not be appropriate to combine ileal and excreta digestibilities and consequently, the 3 aforementioned studies were not included in the current meta-analysis. The objective of this meta-analysis was to combine peer reviewed published work with internal experiments to obtain a more comprehensive understanding of the effectiveness of exogenous proteases in monogastric animals. This report does not focus on one specific protease, but includes a range of proteases to give a better overview of the current situation with the vast choice of products available. MATERIALS AND METHODS A total of 67 experimental animal trials from the years 1955 to 2017 were included in the meta-analysis, contributing 467 lines of data representing treatment averages. These experiments included publications (Lewis et al., 1955; Simbaya et al., 1996; Marsman et al., 1997; Naveed et al., 1998; Rooke et al., 1998; O’Doherty and Forde, 1999; Ghazi et al., 2002; Ghazi et al., 2003; Odetallah et al., 2003; Yin et al., 2004; Odetallah et al., 2005; Yadav and Sah, 2005; Wang et al., 2006; Yu et al., 2007; Wang et al., 2008; Vieira et al., 2009; Angel et al., 2011; Freitas et al., 2011; Fru-Nji et al., 2011; Wang et al., 2011; Guggenbuhl et al., 2012; Barekatain et al., 2013; Liu et al., 2013; Selle et al., 2013; Vieira et al., 2013; Giannenas et al., 2014; O'Shea et al., 2014; Stephenson et al., 2014; Kamel et al., 2015; Zuo et al., 2015; Ding et al., 2016; Pan et al., 2016; Rada et al., 2016; Selle et al., 2016; Shahir et al., 2016; Upadhaya et al., 2016; Yu et al., 2016; Carvalho et al., 2017; dos Santos et al., 2017; Pan et al., 2017; Xu et al., 2017; Yuan et al., 2017; Mahmood et al., 2017a; Mahmood et al., 2017c) and 6 unpublished research trials (Walk et al., Marlborough, UK, personal communication). The unpublished research trials were conducted between October 2014 and October 2016 to evaluate several protease enzymes supplied by AB Enzymes. These trials were conducted at universities or a contract trial site in the United States and UK. Where available, all data on husbandry, diet, performance parameters, and AIAAD from these experiments were collected and utilized in the meta-analysis. Data was filtered such that only experiments that included a mono-component protease were included in the meta-analysis, of which reported performance and/or amino acid digestibility for each treatment. Publications reporting more than one experiment were assigned a specific trial code to each experiment. In some circumstances, other enzymes were included in the treatment alongside protease; however, these were only included in the dataset when an appropriate control comprising these additional enzymes without protease was present. Overall, 44 different protease products (Figure 1) were incorporated into the meta-analysis, with non-commercial proteases used in internal research trials being named protease 1 through 12. Protease inclusion rate varied from 150 to 20,000 mg/kg depending on the protease product, with 4% missing data on dosage. Units for protease activity were only specified in 62% of the dataset. Other enzymes, such as phytase and non-starch polysaccharide degrading enzymes (NSPases) were included in approximately 25% of the experiments, contributing 116 lines of data. Figure 1. View largeDownload slide Tree map showing contribution of protease products in meta-analysis. Figure 1. View largeDownload slide Tree map showing contribution of protease products in meta-analysis. In this meta-analysis, broiler, turkey, and swine experiments represented 76, 5, and 19% of the dataset, respectively. Due to the relatively small number of turkey experiments, these were combined with broiler experiments to give a poultry dataset. The range of dietary ingredients and husbandry practices for poultry and swine are shown in Table 1. Performance data was reported in 61 out of 67 experiments included in the meta-analysis. Due to obvious differences in performance parameters between poultry and swine, these variables were always analyzed as separate datasets. However, poultry and swine datasets were combined for AIAAD analysis. A total of 12 experiments within the meta-analysis dataset presented AIAAD values, with 13 and 87% of this dataset being represented by swine and poultry, respectively. Of these experiments, 9 were from published papers and 3 from internal experiments, contributing 77 lines of data representing treatment averages. Table 1. Main variables included in the dataset for poultry and swine experiments. Poultry Swine Min Max Min Max Ingredient, g/kg Wheat 0.0 706.7 0.0 350.0 Corn 0.0 687.2 0.0 677.8 Barley 0.0 0.0 0.0 442.5 Soybean meal 0.0 450.0 56.1 300.6 DDGS 0.0 300.0 0.0 300.0 Animal protein* 0.0 80.0 0.0 75.0 Vegetable fat 0.0 54.4 0.0 37.0 Phosphate 0.0 36.2 0.0 39.5 Limestone 0.9 20.0 0.0 14.0 Na bicarbonate 0.0 6.0 0.0 0.0 NaCl 0.0 5.8 0.0 5.8 Husbandry Trial duration, days 7 48 7 131 Animals/pen 4 160 1 26 Replicates per treatment 3 24 1 15 Poultry Swine Min Max Min Max Ingredient, g/kg Wheat 0.0 706.7 0.0 350.0 Corn 0.0 687.2 0.0 677.8 Barley 0.0 0.0 0.0 442.5 Soybean meal 0.0 450.0 56.1 300.6 DDGS 0.0 300.0 0.0 300.0 Animal protein* 0.0 80.0 0.0 75.0 Vegetable fat 0.0 54.4 0.0 37.0 Phosphate 0.0 36.2 0.0 39.5 Limestone 0.9 20.0 0.0 14.0 Na bicarbonate 0.0 6.0 0.0 0.0 NaCl 0.0 5.8 0.0 5.8 Husbandry Trial duration, days 7 48 7 131 Animals/pen 4 160 1 26 Replicates per treatment 3 24 1 15 *Fishmeal, meat and bone meal or poultry by-product. View Large Table 1. Main variables included in the dataset for poultry and swine experiments. Poultry Swine Min Max Min Max Ingredient, g/kg Wheat 0.0 706.7 0.0 350.0 Corn 0.0 687.2 0.0 677.8 Barley 0.0 0.0 0.0 442.5 Soybean meal 0.0 450.0 56.1 300.6 DDGS 0.0 300.0 0.0 300.0 Animal protein* 0.0 80.0 0.0 75.0 Vegetable fat 0.0 54.4 0.0 37.0 Phosphate 0.0 36.2 0.0 39.5 Limestone 0.9 20.0 0.0 14.0 Na bicarbonate 0.0 6.0 0.0 0.0 NaCl 0.0 5.8 0.0 5.8 Husbandry Trial duration, days 7 48 7 131 Animals/pen 4 160 1 26 Replicates per treatment 3 24 1 15 Poultry Swine Min Max Min Max Ingredient, g/kg Wheat 0.0 706.7 0.0 350.0 Corn 0.0 687.2 0.0 677.8 Barley 0.0 0.0 0.0 442.5 Soybean meal 0.0 450.0 56.1 300.6 DDGS 0.0 300.0 0.0 300.0 Animal protein* 0.0 80.0 0.0 75.0 Vegetable fat 0.0 54.4 0.0 37.0 Phosphate 0.0 36.2 0.0 39.5 Limestone 0.9 20.0 0.0 14.0 Na bicarbonate 0.0 6.0 0.0 0.0 NaCl 0.0 5.8 0.0 5.8 Husbandry Trial duration, days 7 48 7 131 Animals/pen 4 160 1 26 Replicates per treatment 3 24 1 15 *Fishmeal, meat and bone meal or poultry by-product. View Large Data were statistically analyzed by Mixed Model using JMP Pro v.13 software (SAS Institute Inc, Cary, NC), with significance being accepted at P < 0.05. In all analysis, experiment was included in the model as a random factor, to account for the inevitable study-to-study variation (Sauvant et al., 2008). The effect of protease on performance and AIAAD was assessed by including protease (yes/no) as a fixed factor in the model. To model the response of protease as a function of control performance or digestibility, control data was included as a fixed factor. As stated previously, a number of experiments in this meta-analysis also included other enzymes, such as phytase and NSPases, in the treatment and associated control. Therefore, the dataset was also separated into 2 subgroups to examine the effect of diets with and without other enzymes on AIAAD response to protease separately. In this Mixed Model, protease (yes/no) was included as a fixed factor, with least square means being presented. RESULTS AND DISCUSSION Considering poultry and swine data separately, performance response to protease was measured as relative differences in feed intake, body weight gain (BWG) and feed conversion ratio (FCR) from the control (Table 2). The relative mean response to protease was marginally positive (0.49%) for feed intake in poultry and negative (–0.78%) in swine. For both poultry and swine, the relative mean response to protease was an increase in BWG (1.38 and 4.10%) and a reduction in FCR (–0.92 and –4.12%), respectively, indicating that protease can improve performance in poultry and swine. However, protease only had a significant positive effect (P = 0.04) on FCR in poultry and appears to be influenced (P < 0.001) by control animal performance, such that protease gave greater improvements when FCR is inherently higher. This suggests that it may be more difficult to see a protease response in poultry when birds are already performing well. While protease response in swine may not be dependent on control animal performance, which might explain why we can see much greater relative changes in BWG and FCR with protease in swine than in poultry, although it should be noted that the number of contributing experiments was fewer for swine than poultry (78 vs. 373 lines of data), thereby giving greater variability within the dataset. Table 2. Protease response and the influence of inherent performance on the relative response to protease in poultry and swine. Effect of control on protease response Protease response Species Performance parameter Control (g) SEM P-value Relative protease response over control (%) SEM P-value1 Poultry FI 1975 133.6 0.767 0.49 0.374 0.998 BWG 1153 70.3 0.845 1.38 0.423 0.774 FCR 1.65 0.027 <0.001 −0.92 0.240 0.036 Swine FI 66,837 13,459.6 0.609 −0.78 1.102 0.828 BWG 25,878 4777.9 0.203 4.10 2.147 0.873 FCR 2.25 0.095 0.863 −4.12 1.345 0.423 Effect of control on protease response Protease response Species Performance parameter Control (g) SEM P-value Relative protease response over control (%) SEM P-value1 Poultry FI 1975 133.6 0.767 0.49 0.374 0.998 BWG 1153 70.3 0.845 1.38 0.423 0.774 FCR 1.65 0.027 <0.001 −0.92 0.240 0.036 Swine FI 66,837 13,459.6 0.609 −0.78 1.102 0.828 BWG 25,878 4777.9 0.203 4.10 2.147 0.873 FCR 2.25 0.095 0.863 −4.12 1.345 0.423 SEM, standard error of the mean; RMSE, root mean square error. 1Significance tested between protease treatment mean and control. View Large Table 2. Protease response and the influence of inherent performance on the relative response to protease in poultry and swine. Effect of control on protease response Protease response Species Performance parameter Control (g) SEM P-value Relative protease response over control (%) SEM P-value1 Poultry FI 1975 133.6 0.767 0.49 0.374 0.998 BWG 1153 70.3 0.845 1.38 0.423 0.774 FCR 1.65 0.027 <0.001 −0.92 0.240 0.036 Swine FI 66,837 13,459.6 0.609 −0.78 1.102 0.828 BWG 25,878 4777.9 0.203 4.10 2.147 0.873 FCR 2.25 0.095 0.863 −4.12 1.345 0.423 Effect of control on protease response Protease response Species Performance parameter Control (g) SEM P-value Relative protease response over control (%) SEM P-value1 Poultry FI 1975 133.6 0.767 0.49 0.374 0.998 BWG 1153 70.3 0.845 1.38 0.423 0.774 FCR 1.65 0.027 <0.001 −0.92 0.240 0.036 Swine FI 66,837 13,459.6 0.609 −0.78 1.102 0.828 BWG 25,878 4777.9 0.203 4.10 2.147 0.873 FCR 2.25 0.095 0.863 −4.12 1.345 0.423 SEM, standard error of the mean; RMSE, root mean square error. 1Significance tested between protease treatment mean and control. View Large Due to the vast range of proteases included in this meta-analysis, it is also necessary to take into account performance response differences when specific protease products are included. As can be seen in Figure 2, individual protease products have a diverse effect on performance in both poultry (Figure 2A) and swine (Figure 2B). Rooke et al. (1998) and Ghazi et al. (2002) compared different proteases, derived from either bacterial or fungal species, and found conflicting growth responses. These differences, due to varying specificities against the protein source, may explain some of the inconsistent findings in response to proteases. Other differences may be found between how the protease is applied to the diet. Some studies use a pre-treatment approach whereby the protein source, SBM for example, is incubated with the protease product under optimal pH and temperature conditions for the enzyme prior to being incorporated into the diet (Rooke et al., 1998; Ghazi et al., 2002; Ghazi et al., 2003). Others simply add the enzyme to the feed, where its activation begins following ingestion and exposure to the appropriate digestive tract environment. Moreover, the presence of a coating material over the protease product, to protect the enzyme from sub-optimal conditions within the digestive tract, may also evoke a different response to protease supplementation (Pan et al., 2016; Yu et al., 2016; Pan et al., 2017; Xu et al., 2017). It is also important to note the vast range in units (note there is no standard) of enzyme used between studies, in addition to the large quantity of studies where no measurement of activity was reported. With the broad spectrum of protease products with inherent and acquired differences eliciting varying performance responses it is challenging to fully comprehend animal response to protease supplementation. Figure 2. View largeDownload slide Performance response to a specific protease product. Data show the effects of individual protease products fed to poultry (A) and swine (B) on the relative change in BWG (i) and FCR (ii), compared to control animals. Markers represent individual data points for treatment averages. Figure 2. View largeDownload slide Performance response to a specific protease product. Data show the effects of individual protease products fed to poultry (A) and swine (B) on the relative change in BWG (i) and FCR (ii), compared to control animals. Markers represent individual data points for treatment averages. Table 3. Protease response and the effect of inherent apparent ileal amino acid digestibility (AIAAD, %) on the relative change in AIAAD with protease. Effect of control on protease response Protease response Amino acid Control digestibility (%) SEM P-value Relative protease response over control (% points) SEM P-value1 Arg 84.60 1.136 0.025 1.22 0.274 0.014 Ile 78.16 1.413 <0.001 1.63 0.341 0.004 Leu 78.16 1.584 <0.001 1.57 0.350 0.005 Lys 83.68 1.355 0.680 1.44 0.263 0.003 Met 85.40 1.637 <0.001 1.80 0.292 0.003 Phe 79.34 1.326 <0.001 1.23 0.341 0.007 Thr 71.79 1.876 0.034 1.95 0.403 0.006 Val 76.68 1.977 0.011 1.83 0.373 0.010 Ala 74.19 1.760 <0.001 1.66 0.387 0.016 His 78.78 1.469 <0.001 1.38 0.340 0.012 Asp 76.51 2.035 0.010 1.71 0.372 0.021 Cys 71.15 3.844 0.068 2.64 0.764 0.002 Glu 81.65 1.706 <0.001 1.55 0.288 0.008 Ser 75.91 1.782 0.01 1.85 0.345 0.006 Trp 79.00 3.920 0.676 1.16 0.276 0.079 Pro 75.46 2.184 0.010 1.33 0.361 0.124 Gly 72.97 2.141 0.102 1.48 0.426 0.118 Tyr 76.21 2.190 0.026 2.28 0.435 0.006 Effect of control on protease response Protease response Amino acid Control digestibility (%) SEM P-value Relative protease response over control (% points) SEM P-value1 Arg 84.60 1.136 0.025 1.22 0.274 0.014 Ile 78.16 1.413 <0.001 1.63 0.341 0.004 Leu 78.16 1.584 <0.001 1.57 0.350 0.005 Lys 83.68 1.355 0.680 1.44 0.263 0.003 Met 85.40 1.637 <0.001 1.80 0.292 0.003 Phe 79.34 1.326 <0.001 1.23 0.341 0.007 Thr 71.79 1.876 0.034 1.95 0.403 0.006 Val 76.68 1.977 0.011 1.83 0.373 0.010 Ala 74.19 1.760 <0.001 1.66 0.387 0.016 His 78.78 1.469 <0.001 1.38 0.340 0.012 Asp 76.51 2.035 0.010 1.71 0.372 0.021 Cys 71.15 3.844 0.068 2.64 0.764 0.002 Glu 81.65 1.706 <0.001 1.55 0.288 0.008 Ser 75.91 1.782 0.01 1.85 0.345 0.006 Trp 79.00 3.920 0.676 1.16 0.276 0.079 Pro 75.46 2.184 0.010 1.33 0.361 0.124 Gly 72.97 2.141 0.102 1.48 0.426 0.118 Tyr 76.21 2.190 0.026 2.28 0.435 0.006 SEM, standard error of the mean; RMSE, root mean square error. 1Significance tested between protease treatment mean and control. View Large Table 3. Protease response and the effect of inherent apparent ileal amino acid digestibility (AIAAD, %) on the relative change in AIAAD with protease. Effect of control on protease response Protease response Amino acid Control digestibility (%) SEM P-value Relative protease response over control (% points) SEM P-value1 Arg 84.60 1.136 0.025 1.22 0.274 0.014 Ile 78.16 1.413 <0.001 1.63 0.341 0.004 Leu 78.16 1.584 <0.001 1.57 0.350 0.005 Lys 83.68 1.355 0.680 1.44 0.263 0.003 Met 85.40 1.637 <0.001 1.80 0.292 0.003 Phe 79.34 1.326 <0.001 1.23 0.341 0.007 Thr 71.79 1.876 0.034 1.95 0.403 0.006 Val 76.68 1.977 0.011 1.83 0.373 0.010 Ala 74.19 1.760 <0.001 1.66 0.387 0.016 His 78.78 1.469 <0.001 1.38 0.340 0.012 Asp 76.51 2.035 0.010 1.71 0.372 0.021 Cys 71.15 3.844 0.068 2.64 0.764 0.002 Glu 81.65 1.706 <0.001 1.55 0.288 0.008 Ser 75.91 1.782 0.01 1.85 0.345 0.006 Trp 79.00 3.920 0.676 1.16 0.276 0.079 Pro 75.46 2.184 0.010 1.33 0.361 0.124 Gly 72.97 2.141 0.102 1.48 0.426 0.118 Tyr 76.21 2.190 0.026 2.28 0.435 0.006 Effect of control on protease response Protease response Amino acid Control digestibility (%) SEM P-value Relative protease response over control (% points) SEM P-value1 Arg 84.60 1.136 0.025 1.22 0.274 0.014 Ile 78.16 1.413 <0.001 1.63 0.341 0.004 Leu 78.16 1.584 <0.001 1.57 0.350 0.005 Lys 83.68 1.355 0.680 1.44 0.263 0.003 Met 85.40 1.637 <0.001 1.80 0.292 0.003 Phe 79.34 1.326 <0.001 1.23 0.341 0.007 Thr 71.79 1.876 0.034 1.95 0.403 0.006 Val 76.68 1.977 0.011 1.83 0.373 0.010 Ala 74.19 1.760 <0.001 1.66 0.387 0.016 His 78.78 1.469 <0.001 1.38 0.340 0.012 Asp 76.51 2.035 0.010 1.71 0.372 0.021 Cys 71.15 3.844 0.068 2.64 0.764 0.002 Glu 81.65 1.706 <0.001 1.55 0.288 0.008 Ser 75.91 1.782 0.01 1.85 0.345 0.006 Trp 79.00 3.920 0.676 1.16 0.276 0.079 Pro 75.46 2.184 0.010 1.33 0.361 0.124 Gly 72.97 2.141 0.102 1.48 0.426 0.118 Tyr 76.21 2.190 0.026 2.28 0.435 0.006 SEM, standard error of the mean; RMSE, root mean square error. 1Significance tested between protease treatment mean and control. View Large Table 4. Effect of protease supplementation, in diets with or without inclusion of other enzymes, on apparent ileal amino acid digestibility (AIAAD, %).1 Diets without other enzymes Diets with other enzymes Amino acid Protease (−) Protease (+) P-value RMSE Protease (−) Protease (+) P-value RMSE Arg 85.21 87.16 0.007 1.540 85.75 86.11 0.578 1.552 Ile 77.52 80.32 0.007 2.185 81.94 82.53 0.450 1.845 Leu 78.52 81.23 0.016 2.428 81.18 81.95 0.334 1.910 Lys 84.21 86.37 0.002 1.385 84.01 84.05 0.917 1.043 Met 86.20 88.52 0.055 2.715 84.01 84.05 0.079 1.797 Phe 79.24 81.52 0.007 1.803 82.26 82.69 0.516 1.591 Thr 72.09 75.32 0.004 2.322 75.15 75.57 0.630 2.061 Val 77.57 80.03 0.022 2.356 77.42 78.23 0.314 1.923 Ala 73.16 76.32 0.017 2.896 78.39 78.93 0.617 2.440 His 77.87 80.79 0.013 2.546 82.12 82.21 0.906 1.677 Asp 76.79 79.42 0.017 2.391 79.89 80.14 0.769 1.922 Cys 68.24 72.99 0.006 2.748 74.59 76.10 0.287 2.530 Glu 81.04 83.21 0.031 2.228 85.59 86.37 0.302 1.710 Ser 75.22 78.00 0.003 1.943 80.26 80.75 0.563 1.953 Trp 70.94 73.53 0.099 2.588 87.71 88.59 0.203 0.917 Pro 70.56 72.99 0.078 2.801 83.64 83.60 0.961 2.062 Gly 70.70 72.73 0.084 2.383 77.29 77.58 0.753 2.116 Tyr 78.75 81.29 0.102 2.577 79.71 80.91 0.219 2.209 Diets without other enzymes Diets with other enzymes Amino acid Protease (−) Protease (+) P-value RMSE Protease (−) Protease (+) P-value RMSE Arg 85.21 87.16 0.007 1.540 85.75 86.11 0.578 1.552 Ile 77.52 80.32 0.007 2.185 81.94 82.53 0.450 1.845 Leu 78.52 81.23 0.016 2.428 81.18 81.95 0.334 1.910 Lys 84.21 86.37 0.002 1.385 84.01 84.05 0.917 1.043 Met 86.20 88.52 0.055 2.715 84.01 84.05 0.079 1.797 Phe 79.24 81.52 0.007 1.803 82.26 82.69 0.516 1.591 Thr 72.09 75.32 0.004 2.322 75.15 75.57 0.630 2.061 Val 77.57 80.03 0.022 2.356 77.42 78.23 0.314 1.923 Ala 73.16 76.32 0.017 2.896 78.39 78.93 0.617 2.440 His 77.87 80.79 0.013 2.546 82.12 82.21 0.906 1.677 Asp 76.79 79.42 0.017 2.391 79.89 80.14 0.769 1.922 Cys 68.24 72.99 0.006 2.748 74.59 76.10 0.287 2.530 Glu 81.04 83.21 0.031 2.228 85.59 86.37 0.302 1.710 Ser 75.22 78.00 0.003 1.943 80.26 80.75 0.563 1.953 Trp 70.94 73.53 0.099 2.588 87.71 88.59 0.203 0.917 Pro 70.56 72.99 0.078 2.801 83.64 83.60 0.961 2.062 Gly 70.70 72.73 0.084 2.383 77.29 77.58 0.753 2.116 Tyr 78.75 81.29 0.102 2.577 79.71 80.91 0.219 2.209 RMSE, root mean square error. 1Least square means are presented. View Large Table 4. Effect of protease supplementation, in diets with or without inclusion of other enzymes, on apparent ileal amino acid digestibility (AIAAD, %).1 Diets without other enzymes Diets with other enzymes Amino acid Protease (−) Protease (+) P-value RMSE Protease (−) Protease (+) P-value RMSE Arg 85.21 87.16 0.007 1.540 85.75 86.11 0.578 1.552 Ile 77.52 80.32 0.007 2.185 81.94 82.53 0.450 1.845 Leu 78.52 81.23 0.016 2.428 81.18 81.95 0.334 1.910 Lys 84.21 86.37 0.002 1.385 84.01 84.05 0.917 1.043 Met 86.20 88.52 0.055 2.715 84.01 84.05 0.079 1.797 Phe 79.24 81.52 0.007 1.803 82.26 82.69 0.516 1.591 Thr 72.09 75.32 0.004 2.322 75.15 75.57 0.630 2.061 Val 77.57 80.03 0.022 2.356 77.42 78.23 0.314 1.923 Ala 73.16 76.32 0.017 2.896 78.39 78.93 0.617 2.440 His 77.87 80.79 0.013 2.546 82.12 82.21 0.906 1.677 Asp 76.79 79.42 0.017 2.391 79.89 80.14 0.769 1.922 Cys 68.24 72.99 0.006 2.748 74.59 76.10 0.287 2.530 Glu 81.04 83.21 0.031 2.228 85.59 86.37 0.302 1.710 Ser 75.22 78.00 0.003 1.943 80.26 80.75 0.563 1.953 Trp 70.94 73.53 0.099 2.588 87.71 88.59 0.203 0.917 Pro 70.56 72.99 0.078 2.801 83.64 83.60 0.961 2.062 Gly 70.70 72.73 0.084 2.383 77.29 77.58 0.753 2.116 Tyr 78.75 81.29 0.102 2.577 79.71 80.91 0.219 2.209 Diets without other enzymes Diets with other enzymes Amino acid Protease (−) Protease (+) P-value RMSE Protease (−) Protease (+) P-value RMSE Arg 85.21 87.16 0.007 1.540 85.75 86.11 0.578 1.552 Ile 77.52 80.32 0.007 2.185 81.94 82.53 0.450 1.845 Leu 78.52 81.23 0.016 2.428 81.18 81.95 0.334 1.910 Lys 84.21 86.37 0.002 1.385 84.01 84.05 0.917 1.043 Met 86.20 88.52 0.055 2.715 84.01 84.05 0.079 1.797 Phe 79.24 81.52 0.007 1.803 82.26 82.69 0.516 1.591 Thr 72.09 75.32 0.004 2.322 75.15 75.57 0.630 2.061 Val 77.57 80.03 0.022 2.356 77.42 78.23 0.314 1.923 Ala 73.16 76.32 0.017 2.896 78.39 78.93 0.617 2.440 His 77.87 80.79 0.013 2.546 82.12 82.21 0.906 1.677 Asp 76.79 79.42 0.017 2.391 79.89 80.14 0.769 1.922 Cys 68.24 72.99 0.006 2.748 74.59 76.10 0.287 2.530 Glu 81.04 83.21 0.031 2.228 85.59 86.37 0.302 1.710 Ser 75.22 78.00 0.003 1.943 80.26 80.75 0.563 1.953 Trp 70.94 73.53 0.099 2.588 87.71 88.59 0.203 0.917 Pro 70.56 72.99 0.078 2.801 83.64 83.60 0.961 2.062 Gly 70.70 72.73 0.084 2.383 77.29 77.58 0.753 2.116 Tyr 78.75 81.29 0.102 2.577 79.71 80.91 0.219 2.209 RMSE, root mean square error. 1Least square means are presented. View Large Reported crude protein (CP) and amino acid digestibilities indicate that variable quantities can escape digestion and absorption (Lemme et al., 2004). Undigested protein may be fermented in the ceca and have a detrimental effect on the animal (Apajalahti and Vienola, 2016) or contribute to nitrogen pollution through excretion (Nahm, 2002). Therefore, the benefits to optimizing protein digestion are not only reducing costs in terms of feed, but also for health and environmental reasons (Oxenboll et al., 2011). It may be more appropriate, therefore, to consider the principle purpose of protease enzymes is to improve nitrogen efficiency, which is determined through assessment of amino acid digestibility as a result of protein degradation. A previous meta-analysis by Cowieson and Roos (2014) consisted of 25 experimental trials, 9 of which were from the literature, giving 804 individual data points for amino acid digestibility in monogastrics. However, it should be recalled that 3 of these studies presented total amino acid digestibilities instead of ileal amino acid digestibility, signifying a potential limitation to the usability of the results. In the current study, 12 experiments in monogastrics were included with AIAAD results, 9 of which were from the literature, giving 1,301 individual AIAAD data points (77 lines representing treatment averages). The mean AIAAD of control diets across all 12 experiments was 77.9 ± 1.5% (Table 3). Met had the highest digestibility (85.4%) with Cys having the lowest (71.2%). The mean improvement in AIAAD associated with protease supplementation was 1.6 ± 0.3%. For the majority of amino acids, protease supplementation increased (P < 0.05) AIAAD above that of the control; ranging from 1.2% for Arg, Phe, and Trp to 2.6% for Cys. However, this increase was not significant for Trp, Pro, and Gly. For a number of amino acids, with the exception of Lys, Cys, Trp, and Gly, control digestibility had a significant influence (P < 0.05) on the magnitude of the protease response. This effect is accredited to the fact that as inherent digestibility increases, the effect of protease on amino acid digestibility decreases. Studies have demonstrated that the higher the inherent digestibility of a feed the poorer the response to an enzyme (Cowieson and Bedford, 2009). For example, the relatively poor response for Arg and higher response for Tyr can be explained by the high and low inherent digestibility of these amino acids, respectively, in the corresponding controls. A number of factors can influence control animal characteristics, such as age, species, sex, husbandry practices, and basal diet. In accordance with the latter, 25% of the whole dataset was represented by diets that contained other enzymes, namely phytases and NSPases. It was therefore assessed whether the presence of other enzymes in the basal and treatment diets could influence the response to protease. The use of phytases and NSPases in monogastric feed is widespread, and it would be uncommon for protease to be supplemented without the addition of at least one of these other enzymes. Therefore, it can be difficult to determine the explicit value of exogenous proteases when applied as part of an enzyme cocktail. To address how other exogenous enzymes may influence animal response to proteases, the dataset was divided into two subgroups: diets with and without other enzymes, specifically NSPase and phytase (116 vs. 351 lines of data, respectively). Considering experiments reporting AIAAD data, diets without other enzymes contributed less than half (413 vs 888) the number of individual AIAAD data points than experiments with diets containing other enzymes. The effect of supplementing protease in diets with and without other enzymes on AIAAD was then determined. Results in Table 4 suggest that adding protease to diets that contain no phytases or NSPases increases (P < 0.05) AIAAD for the majority of amino acids, with Met, Trp, Pro, Gly, and Tyr tending (P < 0.10) to improve with protease supplementation. However, supplementing protease into diets already containing other enzymes gives no improvement (P > 0.05) in AIAAD for any of the measured amino acids. This may be explained by the fact that control digestibility was higher in diets already supplemented with other enzymes and thus the response to protease would be less (Cowieson and Bedford, 2009). A study by Sultan et al. (2010) demonstrated that when protease was added to a sorghum-based diet, it increased (P < 0.05) ileal protein digestibility compared to the control, and to a similar extent as addition of a phytase. When phytase and protease were supplemented together, this did not give any further benefit on digestibly than when these enzymes were included individually. It is suggested that phytase improves amino acid digestibility through inhibition of protein-phytate complexes via degradation of phytate (Selle et al., 2006). Therefore, phytase is acting indirectly to improve protein digestion by making protein more available to endogenous proteases. Other studies have also demonstrated the ability of NSPases to improve AIAAD (Cowieson and Bedford, 2009; Cowieson et al., 2010). These findings suggest that when other enzymes, such as NSPases or phytase, are added to the diet, as is currently done almost universally, then including a protease may offer no additional value. Therefore, including protease as part of an enzyme program may not be necessary, since the benefits could already be provided by the other exogenous enzymes present. 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This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Poultry Science Oxford University Press

Meta-analysis: explicit value of mono-component proteases in monogastric diets

Poultry Science , Volume Advance Article (6) – Feb 14, 2018

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Oxford University Press
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© 2018 Poultry Science Association Inc.
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0032-5791
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1525-3171
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10.3382/ps/pey042
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Abstract

ABSTRACT A meta-analysis was conducted to investigate the effect of mono-component proteases on performance and apparent ileal amino acid digestibility (AIAAD, %) in monogastrics. A total of 67 experimental trials were included in the meta-analysis from published and internal reports, contributing 467 lines of data. Poultry and swine data accounted for 81 and 19% of the dataset, respectively. Forty-four different proteases were included in the meta-analysis, accounting for commercial and non-commercial products. Mixed Model analysis was used to assess protease effect and the influence of inherent characteristics of the control on protease response. The mean performance response to protease was a reduction in feed conversion ratio (FCR) for poultry (1%, P < 0.05) and swine (4%, P > 0.05). The mean relative effect of protease on AIAAD over the control was 1.6 ± 0.3%, ranging from 1.2% for Arg, Phe and Trp to 2.6% for Cys. For the majority of amino acids, inherent AIAAD of control diets influenced (P < 0.05) the magnitude of the protease response such that, as inherent digestibility increased, the effect of protease on amino acid digestibility decreased. The dataset was subsequently divided into 2 subgroups: diets with and without other enzymes, namely non-starch polysaccharide degrading enzymes (NSPase) and phytase. Addition of protease in diets containing no other enzymes significantly (P < 0.05) increased AIAAD for the majority of amino acids and tended (P < 0.10) to improve Met, Trp, Pro, Gly, and Tyr. However, when other enzymes were included in the experiment, the beneficial effect of protease on AIAAD was lost (P > 0.05). These findings suggest that when other enzymes are already included in the diet, addition of protease requires further justification for use in monogastric diets. INTRODUCTION Historically, exogenous proteases have been incorporated into enzyme cocktails to improve animal performance (Kocher et al., 2002; Omogbenigun et al., 2004; Cowieson and Adeola, 2005), with minimal evidence that this enzyme provides any explicit value. More recently, mono-component proteases have made their way into the market, with concurrently more research into this area. With rising costs of protein sources, such as soybean meal (SBM), considerable attention is being given to reduce the protein content of animal feed without hindrance to animal performance (Vieira et al., 2016). This concept involves assigning a matrix value for amino acids to the exogenous protease and consequently reducing the amino acid density of the diet (Romero et al., 2013; Olukosi et al., 2015). This is a similar strategy to that employed with phytases, whereby a mineral matrix is applied to the enzyme and inorganic phosphate sources consequently removed. While phytase acts specifically on phytate in the feed, protease is exposed to a vast array of protein substrates of different amino acid composition and molecular weight. Due to substrate variably, the efficacy of a specific protease can be somewhat inconsistent (Acamovic, 2001). An alternative use of exogenous proteases is to enable the substitution of SBM with less digestible and cheaper sources of protein, including animal by-product meal or canola meal (Shahir et al., 2016; Mahmood et al., 2017b). A broad range of endogenous proteases are synthesized and secreted into the digestive tract of monogastric animals, in order to sufficiently utilize dietary protein (Le Huerou-Luron et al., 1993; Nir et al., 1993). However, reduced growth and performance of animals fed poorer digestible protein sources (Qaisrani et al., 2014) indicate the possible inadequacies of endogenous proteases already present in the gastrointestinal tract, particularly in the young animal (Noy and Sklan, 1995; Hedemann and Jensen, 2004). This promotes the idea that exogenous proteases can be used to enhance digestion of dietary proteins that may be unfavorable substrates for endogenous proteases. Nonetheless, the varying nutrient profiles of ingredients can result in an inconsistent protease value. This can make choosing a suitable protease particularly difficult, as the type of protease required will differ depending on the ingredients being fed. Meta-analysis refers to the compiling of results from a number of individual studies for statistical analysis, thereby allowing findings to be integrated and broader interpretations to be made (Glass, 1976). A previous meta-analysis of the literature by Cowieson and Roos (2014) explored the effect of a specific protease (Ronozyme® ProAct) on apparent ileal amino acid digestibility (AIAAD, %) in monogastrics. On further review of the publications included in the meta-analysis, it was noted that a number of experiments presented total excreta amino acid digestibilities rather than ileal (Carvalho et al., 2009; Bertechini et al., 2009a; Bertechini et al., 2009b). Differences between measurements of ileal and excreta digestibilities (Ten Doeschate et al., 1993), as a result of protein turnover by microbes in the hind gut, signify that digestibilities determined in the terminal ileum are more accurate than those measured in the excreta (Ravindran et al., 1999). Therefore, it would not be appropriate to combine ileal and excreta digestibilities and consequently, the 3 aforementioned studies were not included in the current meta-analysis. The objective of this meta-analysis was to combine peer reviewed published work with internal experiments to obtain a more comprehensive understanding of the effectiveness of exogenous proteases in monogastric animals. This report does not focus on one specific protease, but includes a range of proteases to give a better overview of the current situation with the vast choice of products available. MATERIALS AND METHODS A total of 67 experimental animal trials from the years 1955 to 2017 were included in the meta-analysis, contributing 467 lines of data representing treatment averages. These experiments included publications (Lewis et al., 1955; Simbaya et al., 1996; Marsman et al., 1997; Naveed et al., 1998; Rooke et al., 1998; O’Doherty and Forde, 1999; Ghazi et al., 2002; Ghazi et al., 2003; Odetallah et al., 2003; Yin et al., 2004; Odetallah et al., 2005; Yadav and Sah, 2005; Wang et al., 2006; Yu et al., 2007; Wang et al., 2008; Vieira et al., 2009; Angel et al., 2011; Freitas et al., 2011; Fru-Nji et al., 2011; Wang et al., 2011; Guggenbuhl et al., 2012; Barekatain et al., 2013; Liu et al., 2013; Selle et al., 2013; Vieira et al., 2013; Giannenas et al., 2014; O'Shea et al., 2014; Stephenson et al., 2014; Kamel et al., 2015; Zuo et al., 2015; Ding et al., 2016; Pan et al., 2016; Rada et al., 2016; Selle et al., 2016; Shahir et al., 2016; Upadhaya et al., 2016; Yu et al., 2016; Carvalho et al., 2017; dos Santos et al., 2017; Pan et al., 2017; Xu et al., 2017; Yuan et al., 2017; Mahmood et al., 2017a; Mahmood et al., 2017c) and 6 unpublished research trials (Walk et al., Marlborough, UK, personal communication). The unpublished research trials were conducted between October 2014 and October 2016 to evaluate several protease enzymes supplied by AB Enzymes. These trials were conducted at universities or a contract trial site in the United States and UK. Where available, all data on husbandry, diet, performance parameters, and AIAAD from these experiments were collected and utilized in the meta-analysis. Data was filtered such that only experiments that included a mono-component protease were included in the meta-analysis, of which reported performance and/or amino acid digestibility for each treatment. Publications reporting more than one experiment were assigned a specific trial code to each experiment. In some circumstances, other enzymes were included in the treatment alongside protease; however, these were only included in the dataset when an appropriate control comprising these additional enzymes without protease was present. Overall, 44 different protease products (Figure 1) were incorporated into the meta-analysis, with non-commercial proteases used in internal research trials being named protease 1 through 12. Protease inclusion rate varied from 150 to 20,000 mg/kg depending on the protease product, with 4% missing data on dosage. Units for protease activity were only specified in 62% of the dataset. Other enzymes, such as phytase and non-starch polysaccharide degrading enzymes (NSPases) were included in approximately 25% of the experiments, contributing 116 lines of data. Figure 1. View largeDownload slide Tree map showing contribution of protease products in meta-analysis. Figure 1. View largeDownload slide Tree map showing contribution of protease products in meta-analysis. In this meta-analysis, broiler, turkey, and swine experiments represented 76, 5, and 19% of the dataset, respectively. Due to the relatively small number of turkey experiments, these were combined with broiler experiments to give a poultry dataset. The range of dietary ingredients and husbandry practices for poultry and swine are shown in Table 1. Performance data was reported in 61 out of 67 experiments included in the meta-analysis. Due to obvious differences in performance parameters between poultry and swine, these variables were always analyzed as separate datasets. However, poultry and swine datasets were combined for AIAAD analysis. A total of 12 experiments within the meta-analysis dataset presented AIAAD values, with 13 and 87% of this dataset being represented by swine and poultry, respectively. Of these experiments, 9 were from published papers and 3 from internal experiments, contributing 77 lines of data representing treatment averages. Table 1. Main variables included in the dataset for poultry and swine experiments. Poultry Swine Min Max Min Max Ingredient, g/kg Wheat 0.0 706.7 0.0 350.0 Corn 0.0 687.2 0.0 677.8 Barley 0.0 0.0 0.0 442.5 Soybean meal 0.0 450.0 56.1 300.6 DDGS 0.0 300.0 0.0 300.0 Animal protein* 0.0 80.0 0.0 75.0 Vegetable fat 0.0 54.4 0.0 37.0 Phosphate 0.0 36.2 0.0 39.5 Limestone 0.9 20.0 0.0 14.0 Na bicarbonate 0.0 6.0 0.0 0.0 NaCl 0.0 5.8 0.0 5.8 Husbandry Trial duration, days 7 48 7 131 Animals/pen 4 160 1 26 Replicates per treatment 3 24 1 15 Poultry Swine Min Max Min Max Ingredient, g/kg Wheat 0.0 706.7 0.0 350.0 Corn 0.0 687.2 0.0 677.8 Barley 0.0 0.0 0.0 442.5 Soybean meal 0.0 450.0 56.1 300.6 DDGS 0.0 300.0 0.0 300.0 Animal protein* 0.0 80.0 0.0 75.0 Vegetable fat 0.0 54.4 0.0 37.0 Phosphate 0.0 36.2 0.0 39.5 Limestone 0.9 20.0 0.0 14.0 Na bicarbonate 0.0 6.0 0.0 0.0 NaCl 0.0 5.8 0.0 5.8 Husbandry Trial duration, days 7 48 7 131 Animals/pen 4 160 1 26 Replicates per treatment 3 24 1 15 *Fishmeal, meat and bone meal or poultry by-product. View Large Table 1. Main variables included in the dataset for poultry and swine experiments. Poultry Swine Min Max Min Max Ingredient, g/kg Wheat 0.0 706.7 0.0 350.0 Corn 0.0 687.2 0.0 677.8 Barley 0.0 0.0 0.0 442.5 Soybean meal 0.0 450.0 56.1 300.6 DDGS 0.0 300.0 0.0 300.0 Animal protein* 0.0 80.0 0.0 75.0 Vegetable fat 0.0 54.4 0.0 37.0 Phosphate 0.0 36.2 0.0 39.5 Limestone 0.9 20.0 0.0 14.0 Na bicarbonate 0.0 6.0 0.0 0.0 NaCl 0.0 5.8 0.0 5.8 Husbandry Trial duration, days 7 48 7 131 Animals/pen 4 160 1 26 Replicates per treatment 3 24 1 15 Poultry Swine Min Max Min Max Ingredient, g/kg Wheat 0.0 706.7 0.0 350.0 Corn 0.0 687.2 0.0 677.8 Barley 0.0 0.0 0.0 442.5 Soybean meal 0.0 450.0 56.1 300.6 DDGS 0.0 300.0 0.0 300.0 Animal protein* 0.0 80.0 0.0 75.0 Vegetable fat 0.0 54.4 0.0 37.0 Phosphate 0.0 36.2 0.0 39.5 Limestone 0.9 20.0 0.0 14.0 Na bicarbonate 0.0 6.0 0.0 0.0 NaCl 0.0 5.8 0.0 5.8 Husbandry Trial duration, days 7 48 7 131 Animals/pen 4 160 1 26 Replicates per treatment 3 24 1 15 *Fishmeal, meat and bone meal or poultry by-product. View Large Data were statistically analyzed by Mixed Model using JMP Pro v.13 software (SAS Institute Inc, Cary, NC), with significance being accepted at P < 0.05. In all analysis, experiment was included in the model as a random factor, to account for the inevitable study-to-study variation (Sauvant et al., 2008). The effect of protease on performance and AIAAD was assessed by including protease (yes/no) as a fixed factor in the model. To model the response of protease as a function of control performance or digestibility, control data was included as a fixed factor. As stated previously, a number of experiments in this meta-analysis also included other enzymes, such as phytase and NSPases, in the treatment and associated control. Therefore, the dataset was also separated into 2 subgroups to examine the effect of diets with and without other enzymes on AIAAD response to protease separately. In this Mixed Model, protease (yes/no) was included as a fixed factor, with least square means being presented. RESULTS AND DISCUSSION Considering poultry and swine data separately, performance response to protease was measured as relative differences in feed intake, body weight gain (BWG) and feed conversion ratio (FCR) from the control (Table 2). The relative mean response to protease was marginally positive (0.49%) for feed intake in poultry and negative (–0.78%) in swine. For both poultry and swine, the relative mean response to protease was an increase in BWG (1.38 and 4.10%) and a reduction in FCR (–0.92 and –4.12%), respectively, indicating that protease can improve performance in poultry and swine. However, protease only had a significant positive effect (P = 0.04) on FCR in poultry and appears to be influenced (P < 0.001) by control animal performance, such that protease gave greater improvements when FCR is inherently higher. This suggests that it may be more difficult to see a protease response in poultry when birds are already performing well. While protease response in swine may not be dependent on control animal performance, which might explain why we can see much greater relative changes in BWG and FCR with protease in swine than in poultry, although it should be noted that the number of contributing experiments was fewer for swine than poultry (78 vs. 373 lines of data), thereby giving greater variability within the dataset. Table 2. Protease response and the influence of inherent performance on the relative response to protease in poultry and swine. Effect of control on protease response Protease response Species Performance parameter Control (g) SEM P-value Relative protease response over control (%) SEM P-value1 Poultry FI 1975 133.6 0.767 0.49 0.374 0.998 BWG 1153 70.3 0.845 1.38 0.423 0.774 FCR 1.65 0.027 <0.001 −0.92 0.240 0.036 Swine FI 66,837 13,459.6 0.609 −0.78 1.102 0.828 BWG 25,878 4777.9 0.203 4.10 2.147 0.873 FCR 2.25 0.095 0.863 −4.12 1.345 0.423 Effect of control on protease response Protease response Species Performance parameter Control (g) SEM P-value Relative protease response over control (%) SEM P-value1 Poultry FI 1975 133.6 0.767 0.49 0.374 0.998 BWG 1153 70.3 0.845 1.38 0.423 0.774 FCR 1.65 0.027 <0.001 −0.92 0.240 0.036 Swine FI 66,837 13,459.6 0.609 −0.78 1.102 0.828 BWG 25,878 4777.9 0.203 4.10 2.147 0.873 FCR 2.25 0.095 0.863 −4.12 1.345 0.423 SEM, standard error of the mean; RMSE, root mean square error. 1Significance tested between protease treatment mean and control. View Large Table 2. Protease response and the influence of inherent performance on the relative response to protease in poultry and swine. Effect of control on protease response Protease response Species Performance parameter Control (g) SEM P-value Relative protease response over control (%) SEM P-value1 Poultry FI 1975 133.6 0.767 0.49 0.374 0.998 BWG 1153 70.3 0.845 1.38 0.423 0.774 FCR 1.65 0.027 <0.001 −0.92 0.240 0.036 Swine FI 66,837 13,459.6 0.609 −0.78 1.102 0.828 BWG 25,878 4777.9 0.203 4.10 2.147 0.873 FCR 2.25 0.095 0.863 −4.12 1.345 0.423 Effect of control on protease response Protease response Species Performance parameter Control (g) SEM P-value Relative protease response over control (%) SEM P-value1 Poultry FI 1975 133.6 0.767 0.49 0.374 0.998 BWG 1153 70.3 0.845 1.38 0.423 0.774 FCR 1.65 0.027 <0.001 −0.92 0.240 0.036 Swine FI 66,837 13,459.6 0.609 −0.78 1.102 0.828 BWG 25,878 4777.9 0.203 4.10 2.147 0.873 FCR 2.25 0.095 0.863 −4.12 1.345 0.423 SEM, standard error of the mean; RMSE, root mean square error. 1Significance tested between protease treatment mean and control. View Large Due to the vast range of proteases included in this meta-analysis, it is also necessary to take into account performance response differences when specific protease products are included. As can be seen in Figure 2, individual protease products have a diverse effect on performance in both poultry (Figure 2A) and swine (Figure 2B). Rooke et al. (1998) and Ghazi et al. (2002) compared different proteases, derived from either bacterial or fungal species, and found conflicting growth responses. These differences, due to varying specificities against the protein source, may explain some of the inconsistent findings in response to proteases. Other differences may be found between how the protease is applied to the diet. Some studies use a pre-treatment approach whereby the protein source, SBM for example, is incubated with the protease product under optimal pH and temperature conditions for the enzyme prior to being incorporated into the diet (Rooke et al., 1998; Ghazi et al., 2002; Ghazi et al., 2003). Others simply add the enzyme to the feed, where its activation begins following ingestion and exposure to the appropriate digestive tract environment. Moreover, the presence of a coating material over the protease product, to protect the enzyme from sub-optimal conditions within the digestive tract, may also evoke a different response to protease supplementation (Pan et al., 2016; Yu et al., 2016; Pan et al., 2017; Xu et al., 2017). It is also important to note the vast range in units (note there is no standard) of enzyme used between studies, in addition to the large quantity of studies where no measurement of activity was reported. With the broad spectrum of protease products with inherent and acquired differences eliciting varying performance responses it is challenging to fully comprehend animal response to protease supplementation. Figure 2. View largeDownload slide Performance response to a specific protease product. Data show the effects of individual protease products fed to poultry (A) and swine (B) on the relative change in BWG (i) and FCR (ii), compared to control animals. Markers represent individual data points for treatment averages. Figure 2. View largeDownload slide Performance response to a specific protease product. Data show the effects of individual protease products fed to poultry (A) and swine (B) on the relative change in BWG (i) and FCR (ii), compared to control animals. Markers represent individual data points for treatment averages. Table 3. Protease response and the effect of inherent apparent ileal amino acid digestibility (AIAAD, %) on the relative change in AIAAD with protease. Effect of control on protease response Protease response Amino acid Control digestibility (%) SEM P-value Relative protease response over control (% points) SEM P-value1 Arg 84.60 1.136 0.025 1.22 0.274 0.014 Ile 78.16 1.413 <0.001 1.63 0.341 0.004 Leu 78.16 1.584 <0.001 1.57 0.350 0.005 Lys 83.68 1.355 0.680 1.44 0.263 0.003 Met 85.40 1.637 <0.001 1.80 0.292 0.003 Phe 79.34 1.326 <0.001 1.23 0.341 0.007 Thr 71.79 1.876 0.034 1.95 0.403 0.006 Val 76.68 1.977 0.011 1.83 0.373 0.010 Ala 74.19 1.760 <0.001 1.66 0.387 0.016 His 78.78 1.469 <0.001 1.38 0.340 0.012 Asp 76.51 2.035 0.010 1.71 0.372 0.021 Cys 71.15 3.844 0.068 2.64 0.764 0.002 Glu 81.65 1.706 <0.001 1.55 0.288 0.008 Ser 75.91 1.782 0.01 1.85 0.345 0.006 Trp 79.00 3.920 0.676 1.16 0.276 0.079 Pro 75.46 2.184 0.010 1.33 0.361 0.124 Gly 72.97 2.141 0.102 1.48 0.426 0.118 Tyr 76.21 2.190 0.026 2.28 0.435 0.006 Effect of control on protease response Protease response Amino acid Control digestibility (%) SEM P-value Relative protease response over control (% points) SEM P-value1 Arg 84.60 1.136 0.025 1.22 0.274 0.014 Ile 78.16 1.413 <0.001 1.63 0.341 0.004 Leu 78.16 1.584 <0.001 1.57 0.350 0.005 Lys 83.68 1.355 0.680 1.44 0.263 0.003 Met 85.40 1.637 <0.001 1.80 0.292 0.003 Phe 79.34 1.326 <0.001 1.23 0.341 0.007 Thr 71.79 1.876 0.034 1.95 0.403 0.006 Val 76.68 1.977 0.011 1.83 0.373 0.010 Ala 74.19 1.760 <0.001 1.66 0.387 0.016 His 78.78 1.469 <0.001 1.38 0.340 0.012 Asp 76.51 2.035 0.010 1.71 0.372 0.021 Cys 71.15 3.844 0.068 2.64 0.764 0.002 Glu 81.65 1.706 <0.001 1.55 0.288 0.008 Ser 75.91 1.782 0.01 1.85 0.345 0.006 Trp 79.00 3.920 0.676 1.16 0.276 0.079 Pro 75.46 2.184 0.010 1.33 0.361 0.124 Gly 72.97 2.141 0.102 1.48 0.426 0.118 Tyr 76.21 2.190 0.026 2.28 0.435 0.006 SEM, standard error of the mean; RMSE, root mean square error. 1Significance tested between protease treatment mean and control. View Large Table 3. Protease response and the effect of inherent apparent ileal amino acid digestibility (AIAAD, %) on the relative change in AIAAD with protease. Effect of control on protease response Protease response Amino acid Control digestibility (%) SEM P-value Relative protease response over control (% points) SEM P-value1 Arg 84.60 1.136 0.025 1.22 0.274 0.014 Ile 78.16 1.413 <0.001 1.63 0.341 0.004 Leu 78.16 1.584 <0.001 1.57 0.350 0.005 Lys 83.68 1.355 0.680 1.44 0.263 0.003 Met 85.40 1.637 <0.001 1.80 0.292 0.003 Phe 79.34 1.326 <0.001 1.23 0.341 0.007 Thr 71.79 1.876 0.034 1.95 0.403 0.006 Val 76.68 1.977 0.011 1.83 0.373 0.010 Ala 74.19 1.760 <0.001 1.66 0.387 0.016 His 78.78 1.469 <0.001 1.38 0.340 0.012 Asp 76.51 2.035 0.010 1.71 0.372 0.021 Cys 71.15 3.844 0.068 2.64 0.764 0.002 Glu 81.65 1.706 <0.001 1.55 0.288 0.008 Ser 75.91 1.782 0.01 1.85 0.345 0.006 Trp 79.00 3.920 0.676 1.16 0.276 0.079 Pro 75.46 2.184 0.010 1.33 0.361 0.124 Gly 72.97 2.141 0.102 1.48 0.426 0.118 Tyr 76.21 2.190 0.026 2.28 0.435 0.006 Effect of control on protease response Protease response Amino acid Control digestibility (%) SEM P-value Relative protease response over control (% points) SEM P-value1 Arg 84.60 1.136 0.025 1.22 0.274 0.014 Ile 78.16 1.413 <0.001 1.63 0.341 0.004 Leu 78.16 1.584 <0.001 1.57 0.350 0.005 Lys 83.68 1.355 0.680 1.44 0.263 0.003 Met 85.40 1.637 <0.001 1.80 0.292 0.003 Phe 79.34 1.326 <0.001 1.23 0.341 0.007 Thr 71.79 1.876 0.034 1.95 0.403 0.006 Val 76.68 1.977 0.011 1.83 0.373 0.010 Ala 74.19 1.760 <0.001 1.66 0.387 0.016 His 78.78 1.469 <0.001 1.38 0.340 0.012 Asp 76.51 2.035 0.010 1.71 0.372 0.021 Cys 71.15 3.844 0.068 2.64 0.764 0.002 Glu 81.65 1.706 <0.001 1.55 0.288 0.008 Ser 75.91 1.782 0.01 1.85 0.345 0.006 Trp 79.00 3.920 0.676 1.16 0.276 0.079 Pro 75.46 2.184 0.010 1.33 0.361 0.124 Gly 72.97 2.141 0.102 1.48 0.426 0.118 Tyr 76.21 2.190 0.026 2.28 0.435 0.006 SEM, standard error of the mean; RMSE, root mean square error. 1Significance tested between protease treatment mean and control. View Large Table 4. Effect of protease supplementation, in diets with or without inclusion of other enzymes, on apparent ileal amino acid digestibility (AIAAD, %).1 Diets without other enzymes Diets with other enzymes Amino acid Protease (−) Protease (+) P-value RMSE Protease (−) Protease (+) P-value RMSE Arg 85.21 87.16 0.007 1.540 85.75 86.11 0.578 1.552 Ile 77.52 80.32 0.007 2.185 81.94 82.53 0.450 1.845 Leu 78.52 81.23 0.016 2.428 81.18 81.95 0.334 1.910 Lys 84.21 86.37 0.002 1.385 84.01 84.05 0.917 1.043 Met 86.20 88.52 0.055 2.715 84.01 84.05 0.079 1.797 Phe 79.24 81.52 0.007 1.803 82.26 82.69 0.516 1.591 Thr 72.09 75.32 0.004 2.322 75.15 75.57 0.630 2.061 Val 77.57 80.03 0.022 2.356 77.42 78.23 0.314 1.923 Ala 73.16 76.32 0.017 2.896 78.39 78.93 0.617 2.440 His 77.87 80.79 0.013 2.546 82.12 82.21 0.906 1.677 Asp 76.79 79.42 0.017 2.391 79.89 80.14 0.769 1.922 Cys 68.24 72.99 0.006 2.748 74.59 76.10 0.287 2.530 Glu 81.04 83.21 0.031 2.228 85.59 86.37 0.302 1.710 Ser 75.22 78.00 0.003 1.943 80.26 80.75 0.563 1.953 Trp 70.94 73.53 0.099 2.588 87.71 88.59 0.203 0.917 Pro 70.56 72.99 0.078 2.801 83.64 83.60 0.961 2.062 Gly 70.70 72.73 0.084 2.383 77.29 77.58 0.753 2.116 Tyr 78.75 81.29 0.102 2.577 79.71 80.91 0.219 2.209 Diets without other enzymes Diets with other enzymes Amino acid Protease (−) Protease (+) P-value RMSE Protease (−) Protease (+) P-value RMSE Arg 85.21 87.16 0.007 1.540 85.75 86.11 0.578 1.552 Ile 77.52 80.32 0.007 2.185 81.94 82.53 0.450 1.845 Leu 78.52 81.23 0.016 2.428 81.18 81.95 0.334 1.910 Lys 84.21 86.37 0.002 1.385 84.01 84.05 0.917 1.043 Met 86.20 88.52 0.055 2.715 84.01 84.05 0.079 1.797 Phe 79.24 81.52 0.007 1.803 82.26 82.69 0.516 1.591 Thr 72.09 75.32 0.004 2.322 75.15 75.57 0.630 2.061 Val 77.57 80.03 0.022 2.356 77.42 78.23 0.314 1.923 Ala 73.16 76.32 0.017 2.896 78.39 78.93 0.617 2.440 His 77.87 80.79 0.013 2.546 82.12 82.21 0.906 1.677 Asp 76.79 79.42 0.017 2.391 79.89 80.14 0.769 1.922 Cys 68.24 72.99 0.006 2.748 74.59 76.10 0.287 2.530 Glu 81.04 83.21 0.031 2.228 85.59 86.37 0.302 1.710 Ser 75.22 78.00 0.003 1.943 80.26 80.75 0.563 1.953 Trp 70.94 73.53 0.099 2.588 87.71 88.59 0.203 0.917 Pro 70.56 72.99 0.078 2.801 83.64 83.60 0.961 2.062 Gly 70.70 72.73 0.084 2.383 77.29 77.58 0.753 2.116 Tyr 78.75 81.29 0.102 2.577 79.71 80.91 0.219 2.209 RMSE, root mean square error. 1Least square means are presented. View Large Table 4. Effect of protease supplementation, in diets with or without inclusion of other enzymes, on apparent ileal amino acid digestibility (AIAAD, %).1 Diets without other enzymes Diets with other enzymes Amino acid Protease (−) Protease (+) P-value RMSE Protease (−) Protease (+) P-value RMSE Arg 85.21 87.16 0.007 1.540 85.75 86.11 0.578 1.552 Ile 77.52 80.32 0.007 2.185 81.94 82.53 0.450 1.845 Leu 78.52 81.23 0.016 2.428 81.18 81.95 0.334 1.910 Lys 84.21 86.37 0.002 1.385 84.01 84.05 0.917 1.043 Met 86.20 88.52 0.055 2.715 84.01 84.05 0.079 1.797 Phe 79.24 81.52 0.007 1.803 82.26 82.69 0.516 1.591 Thr 72.09 75.32 0.004 2.322 75.15 75.57 0.630 2.061 Val 77.57 80.03 0.022 2.356 77.42 78.23 0.314 1.923 Ala 73.16 76.32 0.017 2.896 78.39 78.93 0.617 2.440 His 77.87 80.79 0.013 2.546 82.12 82.21 0.906 1.677 Asp 76.79 79.42 0.017 2.391 79.89 80.14 0.769 1.922 Cys 68.24 72.99 0.006 2.748 74.59 76.10 0.287 2.530 Glu 81.04 83.21 0.031 2.228 85.59 86.37 0.302 1.710 Ser 75.22 78.00 0.003 1.943 80.26 80.75 0.563 1.953 Trp 70.94 73.53 0.099 2.588 87.71 88.59 0.203 0.917 Pro 70.56 72.99 0.078 2.801 83.64 83.60 0.961 2.062 Gly 70.70 72.73 0.084 2.383 77.29 77.58 0.753 2.116 Tyr 78.75 81.29 0.102 2.577 79.71 80.91 0.219 2.209 Diets without other enzymes Diets with other enzymes Amino acid Protease (−) Protease (+) P-value RMSE Protease (−) Protease (+) P-value RMSE Arg 85.21 87.16 0.007 1.540 85.75 86.11 0.578 1.552 Ile 77.52 80.32 0.007 2.185 81.94 82.53 0.450 1.845 Leu 78.52 81.23 0.016 2.428 81.18 81.95 0.334 1.910 Lys 84.21 86.37 0.002 1.385 84.01 84.05 0.917 1.043 Met 86.20 88.52 0.055 2.715 84.01 84.05 0.079 1.797 Phe 79.24 81.52 0.007 1.803 82.26 82.69 0.516 1.591 Thr 72.09 75.32 0.004 2.322 75.15 75.57 0.630 2.061 Val 77.57 80.03 0.022 2.356 77.42 78.23 0.314 1.923 Ala 73.16 76.32 0.017 2.896 78.39 78.93 0.617 2.440 His 77.87 80.79 0.013 2.546 82.12 82.21 0.906 1.677 Asp 76.79 79.42 0.017 2.391 79.89 80.14 0.769 1.922 Cys 68.24 72.99 0.006 2.748 74.59 76.10 0.287 2.530 Glu 81.04 83.21 0.031 2.228 85.59 86.37 0.302 1.710 Ser 75.22 78.00 0.003 1.943 80.26 80.75 0.563 1.953 Trp 70.94 73.53 0.099 2.588 87.71 88.59 0.203 0.917 Pro 70.56 72.99 0.078 2.801 83.64 83.60 0.961 2.062 Gly 70.70 72.73 0.084 2.383 77.29 77.58 0.753 2.116 Tyr 78.75 81.29 0.102 2.577 79.71 80.91 0.219 2.209 RMSE, root mean square error. 1Least square means are presented. View Large Reported crude protein (CP) and amino acid digestibilities indicate that variable quantities can escape digestion and absorption (Lemme et al., 2004). Undigested protein may be fermented in the ceca and have a detrimental effect on the animal (Apajalahti and Vienola, 2016) or contribute to nitrogen pollution through excretion (Nahm, 2002). Therefore, the benefits to optimizing protein digestion are not only reducing costs in terms of feed, but also for health and environmental reasons (Oxenboll et al., 2011). It may be more appropriate, therefore, to consider the principle purpose of protease enzymes is to improve nitrogen efficiency, which is determined through assessment of amino acid digestibility as a result of protein degradation. A previous meta-analysis by Cowieson and Roos (2014) consisted of 25 experimental trials, 9 of which were from the literature, giving 804 individual data points for amino acid digestibility in monogastrics. However, it should be recalled that 3 of these studies presented total amino acid digestibilities instead of ileal amino acid digestibility, signifying a potential limitation to the usability of the results. In the current study, 12 experiments in monogastrics were included with AIAAD results, 9 of which were from the literature, giving 1,301 individual AIAAD data points (77 lines representing treatment averages). The mean AIAAD of control diets across all 12 experiments was 77.9 ± 1.5% (Table 3). Met had the highest digestibility (85.4%) with Cys having the lowest (71.2%). The mean improvement in AIAAD associated with protease supplementation was 1.6 ± 0.3%. For the majority of amino acids, protease supplementation increased (P < 0.05) AIAAD above that of the control; ranging from 1.2% for Arg, Phe, and Trp to 2.6% for Cys. However, this increase was not significant for Trp, Pro, and Gly. For a number of amino acids, with the exception of Lys, Cys, Trp, and Gly, control digestibility had a significant influence (P < 0.05) on the magnitude of the protease response. This effect is accredited to the fact that as inherent digestibility increases, the effect of protease on amino acid digestibility decreases. Studies have demonstrated that the higher the inherent digestibility of a feed the poorer the response to an enzyme (Cowieson and Bedford, 2009). For example, the relatively poor response for Arg and higher response for Tyr can be explained by the high and low inherent digestibility of these amino acids, respectively, in the corresponding controls. A number of factors can influence control animal characteristics, such as age, species, sex, husbandry practices, and basal diet. In accordance with the latter, 25% of the whole dataset was represented by diets that contained other enzymes, namely phytases and NSPases. It was therefore assessed whether the presence of other enzymes in the basal and treatment diets could influence the response to protease. The use of phytases and NSPases in monogastric feed is widespread, and it would be uncommon for protease to be supplemented without the addition of at least one of these other enzymes. Therefore, it can be difficult to determine the explicit value of exogenous proteases when applied as part of an enzyme cocktail. To address how other exogenous enzymes may influence animal response to proteases, the dataset was divided into two subgroups: diets with and without other enzymes, specifically NSPase and phytase (116 vs. 351 lines of data, respectively). Considering experiments reporting AIAAD data, diets without other enzymes contributed less than half (413 vs 888) the number of individual AIAAD data points than experiments with diets containing other enzymes. The effect of supplementing protease in diets with and without other enzymes on AIAAD was then determined. Results in Table 4 suggest that adding protease to diets that contain no phytases or NSPases increases (P < 0.05) AIAAD for the majority of amino acids, with Met, Trp, Pro, Gly, and Tyr tending (P < 0.10) to improve with protease supplementation. However, supplementing protease into diets already containing other enzymes gives no improvement (P > 0.05) in AIAAD for any of the measured amino acids. This may be explained by the fact that control digestibility was higher in diets already supplemented with other enzymes and thus the response to protease would be less (Cowieson and Bedford, 2009). A study by Sultan et al. (2010) demonstrated that when protease was added to a sorghum-based diet, it increased (P < 0.05) ileal protein digestibility compared to the control, and to a similar extent as addition of a phytase. When phytase and protease were supplemented together, this did not give any further benefit on digestibly than when these enzymes were included individually. It is suggested that phytase improves amino acid digestibility through inhibition of protein-phytate complexes via degradation of phytate (Selle et al., 2006). Therefore, phytase is acting indirectly to improve protein digestion by making protein more available to endogenous proteases. Other studies have also demonstrated the ability of NSPases to improve AIAAD (Cowieson and Bedford, 2009; Cowieson et al., 2010). These findings suggest that when other enzymes, such as NSPases or phytase, are added to the diet, as is currently done almost universally, then including a protease may offer no additional value. Therefore, including protease as part of an enzyme program may not be necessary, since the benefits could already be provided by the other exogenous enzymes present. CONCLUSIONS In summary of this meta-analysis, it can be concluded that supplementing an exogenous protease has the potential to improve animal performance as well as amino acid digestibility. Increasing the inherent amino acid digestibility of a diet reduces the response to protease. Moreover, when other enzymes, such as phytase or NSPases, are included in the diet, the beneficial effect of protease on AIAAD is removed. These findings indicate that the explicit value of exogenous proteases when incorporated into an enzyme cocktail along with other routinely used enzymes may be considered negligible. REFERENCES Acamovic T. 2001 . Commercial application of enzyme technology for poultry production . World. Poult. Sci. J. 57 : 225 – 242 . Google Scholar CrossRef Search ADS Angel C. R. , Saylor W. , Vieira S. L. , Ward N. . 2011 . Effects of a monocomponent protease on performance and protein utilization in 7- to 22-day-old broiler chickens . Poult. Sci. 90 : 2281 – 2286 . 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Poultry ScienceOxford University Press

Published: Feb 14, 2018

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