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INTRODUCTION
Growing-finishing pigs are considered as a main cause of environmental problems such as eutrophication and acidification due to nitrogen emissions [1,2]. Over-supplementation of diets with nutrients is a major factor contributing to the excretion of nutrients into feces and urine and emissions of nitrogen (N) [3]. Therefore, researchers are constantly attempting to reduce N emission from feces and urine by reducing dietary protein and energy levels in pig diets [4,5]. Researchers have reported that reducing dietary protein concentration to be under 4% [6-9] and reducing dietary energy (150 kcal) can decrease N emission [10,11].
However, the most concerning challenge of reducing dietary protein and energy is a decrease in growth performance [4,12-14]. When dietary protein and energy levels are reduced in feeds at growing-finishing periods, pigs attempt to maintain energy consumption by eating more feed [11,15]. Reduction of dietary protein and energy levels can also lead to extension of feeding term for growing-finishing pigs to reach market weights due to poor growth performance [16-18]. Consequently, reduction of dietary protein and energy could increase feed consumption, which might cause poor profitability to swine producers.
Dietary nutrient density could affect feed consumption of pigs. Previous studies have reported feed intake is decreased when dietary nutrient density is increased [19,20]. It means that uptake of exogenous protease might be influenced by nutrient density. However, few studies have evaluated the relationship between protease and nutrient density.
Exogenous protease known to hydrolyze proteins to peptides, is being widely used to enhance growth performance and improve protein digestion [21-24]. Several studies have reported that improved digestion and absorption of crude protein (CP) might reduce losses of nutrients associated with strategies to reduce N emissions [25,26]. Furthermore, supplementation of exogenous protease to high protein diets can reduce N excretion into urine in growing pigs [27]. Therefore, supplementation of exogenous protease could be an ideal strategy to reduce N emissions when pigs are fed with high protein diets during growing-finishing periods. Many studies have reported effects of protease based on Bacillus licheniformis, Aspergillus and Peniophora [28,29], while there are few studies on effects of exogenous protease based on Streptomyces sps. We hypothesized that increased nutrient density diets and supplementation of exogenous protease would positively affect growth performance and nutrient digestibility without increasing excretion of residual nutrients, which could negatively cause environmental impacts. Thus, the objective of this study was to investigate the effects of nutrient density and protease on growth performance, nutrient digestibility, blood profiles, gas emissions, and fecal microflora.
MATERIALS AND METHODS
The protocol for this study was reviewed and approved by the Institutional Animal Care and Use Committee of Chungbuk National University, Cheongju, Korea (approval no. CBNUA-1740-22-02).
The protease A (PTA) enzyme was supported by a commercial company. According to the supplier, PTA, an alkaline serine endopeptidase produced by a fermentation process by a Streptomyces bacterial strain at optimal pH 8.5, was purified from a crude solution produced by a Streptomyces sps. PTA contains 60,000 protease units/g produced by a Streptomyces sps. PTB commercial product, containing 75,000 protease units/g derived from Nocardiopsis prasina produced in Bacillus licheniformis.
A total of one hundred-eight crossbred growing pigs ([Landrace × Yorkshire] × Duroc) with an initial body weight (BW; 18.74 ± 3.46 kg) were used for 15 weeks. Pigs were randomly assigned to six dietary treatments with 6 replicates of 3 pigs per pen in a 3 × 2 factorial through arrangement: three groups of protease (1, Basal diets; 2, PTA: 125 mg/kg protease derived from Streptomyces sps; 3, PTB: 100 mg/kg protease derived from Bacillus licheniformis) at two different nutrient density diets (1; Basal requirement 2; 0.94%–0.98% higher than requirement in dietary protein and 50 kcal/kg in energy). Feeds were provided by Woosung (Daejeon, Korea). The feed was formulated to meet or exceed the nutritional requirements of pigs according to NRC (Table 1) [3]. Each pigs had ad libitum access to water. A single-sided stainless-steel feeder and nipple drinker were placed with each pen.
1) Provided per kilogram of complete diet: vitamin A, 11,025 U; vitamin D3,1103 U; vitamin E, 44 U; vitamin K, 4.4 mg; riboflavin, 8.3 mg; niacin,50 mg; thiamine, 4 mg; d-pantothenic, 29 mg; choline, 166 mg; and vitamin B12, 33 µg; Cu (as CuSO4 · 5H2O), 12 mg; Zn (as ZnSO4), 85 mg; Mn (as MnO2), 8 mg; I (as KI), 0.28 mg; and selenium (as Na2SeO3 · 5H2O), 0.15 mg.
High, high nutrient density diet; Basal, basal nutrient density diet; DDGS, distiller’s dried grains with solubles; MDCP, monodicalcium phosphate; NE, net energy; AA, amino acids; Arg, arginine; Ile, isoleucine; Leu, leucine; Lys, lysine; Met, methionine; Cys, cysteine; Thr, tryptophan; Val, valine; AID, apparent ileal digestibility.
BW, and feed consumption were measured at initial, 2, 4, 6, 9, 13 and 15 weeks to calculate average daily gain (ADG), average daily feed intake (ADFI), and feed conversion ratio (FCR).
In experiment periods, fresh fecal samples from each treatment are collected by rectal massage at weeks 6 and 13 from 3 pigs in a pen. Fresh fecal samples were transferred to the laboratory in an icebox for analysis. Diets and feces were analyzed for dry matter (DM), CP, and gross energy (GE) using AOAC methods [30]. We analyzed the GE of the diets and feces using an adiabatic oxygen bomb calorimeter (Parr Instruments, Moline, IL, USA). To evaluate the apparent total tract digestibility (ATTD) of CP, DM, and GE, 0.2% chromium oxide (Cr2O3) was analyzed immediately as an indigestible marker that added in pig’s diet. Using a spectrophotometer, the acid digestion method was used to determine Cr2O3.
Nf =nutrient concentration in feces (DM%), Nd = nutrient concentration in diet (DM%), Cd =chromium concentration in diet (DM%), and Cf = chromium concentration in feces (DM%).
At 6 and 13 weeks, blood samples from the anterior vena cava of 6 pigs per treatment were collected to evaluate the levels of total protein and blood urea nitrogen (BUN). Blood samples were collected into both nonheparinized tubes and vacuum tubes containing K3EDTA (Becton, Dickinson and CO., Franklin Lakes, NJ, USA) to obtain serum and whole blood. After collection, serum samples were centrifuged (3,000 rpm) for 20 min at 4°C. BUN (Urease GLDH, Roche, Mannheim, Germany) and total protein concentration (Colorimetric assay, Roche) were analyzed using a blood analyzer (Cobas C702, Roche).
To analysis fecal ammonia (NH3), and hydrogen sulfide (H2S) concentration, feces were collected at weeks 6, 13. The feces (300 g) that collected for each treatment were stored in a plastic box with small holes, and the holes were sealed with plaster. Feces were fermented for 24 hours and 48 hours in room temperature (25°C). Before the measurement, feces with plastic boxes are shaken 20s to break down any crust formation. NH3, and H2S concentrations were determined in the ranges of 50.0 to 100.0 ppm (Gastec, Gastec detector tube No. 3La for NH3; No. 4LK for H2S and No. 81L for acetic acid, detector tube, Gastec, Kanagawa, Japan).
Fresh fecal samples from each treatment are collected by rectal massage at weeks 6 and 13 from 3 pigs in a pen. Fresh fecal samples were transferred to the laboratory in an icebox for analysis. For counting bacterial colonies, the pour plate method was used. To count the number of Lactobacillus and Escherichia coli (E. coli), de Man, Rogosa and Sharpe (MRS) agar for Lactobacillus, and MacConkey agar for E. coli were used, and E. coli was cultured at 37°C for 24 h, and Lactobacillus was cultured for 48 h.
Data for effects of two types of feedstuffs (High nutrient diet [HN], basal nutrient diet [BN]) added with three different types (CON, PTA and PTB) of protease on growth performance, nutrient digestibility, blood profiles and fecal microflora of pigs were conducted with two-way ANOVA, with different nutrient density, different types of proteases, and their interactions as main effects and litter as a covariate. All data was analyzed with the general linear model procedure of SAS (Version 9.4, 2013, SAS, Cary, NC, USA). Differences between treatment groups was considered by using Duncan’s multiple range test. Statistical significance and tendency were determined at p < 0.05 and 0.05 ≤ p < 0.10.
RESULTS
As shown in Table 2, BW was significantly increased (p < 0.05) in PTA added treatment compared with CON at weeks 4. Also, at weeks 6, BW was significantly increased (p < 0.01) in PTA and PTB added treatment compared with CON. From weeks 2 to 4, ADG was significantly increased (p < 0.05) in PTA added treatment compared with CON. From weeks 0 to 6, ADG was significantly increased (p < 0.01) in PTA and PTB added treatment compared with CON. From weeks 0 to 2, 4 to 6 and 0 to 6, ADG was significantly increased (p < 0.05) in HN treatment than for BN treatment. There was an interaction (p < 0.05) between nutrient density of diets and protease in FCR at weeks 4 to 6. Pigs supplemented with BN, and no additive had higher FCR levels compared to pigs supplemented with HN and no additive. From weeks 13 to 15, ADG was higher (p < 0.05) HN treatment than for BN treatment. From weeks 9 to 13 and 6 to 15, ADG was significantly increased (p < 0.05) in PTA added treatment compared with PTB. From weeks 13 to 15, ADG was significantly increased (p < 0.05) in PTA and PTB added treatment compared with CON. From weeks 9 to 13, FCR was less (p < 0.05) for PTB added treatment than PTA added treatment. From weeks 6 to 9, ADFI showed a tendency to increase (p < 0.10) when the BN diets were supplied. Also, from weeks 0 to 15, FCR showed a tendency to increase (p < 0.10) when the BN diets were supplied.
1) High nutrient density is 0.94%–0.98% higher than requirement in dietary protein and 50 kcal/kg in energy than basal nutrient density.
High, high nutrient density diet; Basal, basal nutrient density diet; Den, different nutrient density diet; Pro, supplementation of protease; CON, basal diet; PTA, CON + 0.0125% protease A; PTB, CON + 0.010% protease B; Den × Pro, different nutrient density diet × supplementation of protease; BW, body weight; ADG, average daily gain; ADFI, average daily feed intake; FCR, feed conversion ratio.
As shown in Table 3, pigs supplemented with HN showed higher (p < .0001) levels of CP digestion compared to BN at weeks 6. Also, CP digestion was significantly increased (p < 0.05) in supplementation of PTA protease compared to CON at weeks 6. Supplementation of PTA diets showed significant increase of GE (p < 0.05) than CON diets at weeks 13. However, there was no significant difference in DM at weeks 13. Pigs supplemented with BN showed higher (p < 0.001) CP digestion levels compared to HN at weeks 13. Also, supplementation of PTA and PTB showed higher (p < 0.05) levels of CP digestion compared to CON at weeks 13. There was an interaction (p < 0.05) between nutrient density of diets and protease in CP digestibility at weeks 13. Supplementation of PTA showed higher (p < 0.05) concentrations of CP digestibility in HN diets compared to CON and PTA at weeks 13.
1) High nutrient density is 0.94%–0.98% higher than requirement in dietary protein and 50 kcal/kg in energy than basal nutrient density.
High, high nutrient density diet; Basal, basal nutrient density diet; Den, different nutrient density diet; Pro, supplementation of protease; CON, basal diet; PTA, CON + 0.0125% protease A; PTB, CON + 0.010% protease B; Den × Pro, different nutrient density diet × supplementation of protease; DM, dry matter; CP, crude protein; GE, gross energy.
As shown in Table 4, there was no significant difference between HN and BN diets treatment and supplementation of protease at growing periods. In finishing period, there was significant increased (p < 0.05) in BUN between supplementation of protease. PTA and PTB showed lesser than CON. Total protein was not significantly (p > 0.05) affected by nutrient density of diets and supplementation of protease.
1) High nutrient density is 0.94%–0.98% higher than requirement in dietary protein and 50 kcal/kg in energy than basal nutrient density.
High, high nutrient density diet; Basal, basal nutrient density diet; Den, different nutrient density diet; Pro, supplementation of protease; CON, basal diet; PTA, CON + 0.0125% protease A; PTB, CON + 0.010% protease B; Den × Pro, different nutrient density diet × supplementation of protease; BUN, blood urea nitrogen.
As shown in Table 5, addition of PTA diets showed lesser than CON diets (p < 0.05) NH3 emissions at weeks 6. There was no significant difference (p < 0.05) in H2S emission. At weeks 13, there was significant difference (p < 0.05) in H2S between supplementation of protease. Supplementation of PTA and PTB decreased significantly in H2S emission compared with CON. In NH3, PTA showed lowest (p < 0.05) emissions and CON showed highest emissions.
1) High nutrient density is 0.94%–0.98% higher than requirement in dietary protein and 50 kcal/kg in energy than basal nutrient density.
High, high nutrient density diet; Basal, basal nutrient density diet; Den, different nutrient density diet; Pro, supplementation of protease; CON, basal diet; PTA, CON + 0.0125% protease A; PTB, CON + 0.010% protease B; Den × Pro, different nutrient density diet × supplementation of protease; H2S, hydrogen sulfide; NH3, ammonia.
As shown in Table 6, there was no significant difference (p > 0.05) in E. coli and Lactobacillus concentration in feces between density of diets and supplementation of protease at weeks 6. Likewise, there was no significant difference (p > 0.05) in E. coli and Lactobacillus in feces between density of diets and supplementation of protease at weeks 13.
1) High nutrient density is 0.94%–0.98% higher than requirement in dietary protein and 50 kcal/kg in energy than basal nutrient density.
High, high nutrient density diet; Basal, basal nutrient density diet; Den, different nutrient density diet; Pro, supplementation of protease; CON, basal diet; PTA, CON + 0.0125% protease A; PTB, CON + 0.010% protease B; Den × Pro, different nutrient density diet × supplementation of protease; E. coli, Escherichia coli.
DISCUSSION
The current study focused on the following two mechanisms to assess positive effects of high nutrient density and protease; 1) providing HN diets could improve nutrient digestibility with ADG due to increased dietary protein with energy, and 2) supplementation of protease for hydrolyzing dietary proteins into peptides could increase digestion and absorption.
Pigs in groups with HN diets showed improvement in BW and ADG compared to those in groups with BN diets. These observations are consistent with previous studies showing that providing high dietary protein (0.97% and 1.29%, respectively) and energy levels (100 kcal/kg and143 kcal/kg, respectively) could improve ADG during growing periods [31,32]. Supporting the current study’s results, numerous studies have reported a positive correlation between increased dietary protein with energy, which could improve growth performance [31,33,34]. Thus, the increase of ADG in the present study might be due to the increased nutrient density diets.
During the growing period, we observed increased ATTD of CP in HN diets. Previous studies have reported a positive correlation between improved ATTD of CP and improved ADG [13,32]. Our results were consistent with previous reports, suggesting that providing HN diets could lead to positive correlation between increase of ATTD of CP and increase of ADG.
Dietary energy level is highly related with feed intake and considered as first determinant of ADFI [19,20]. Yan et al. has reported a decrease of ADFI when growing-finishing pig are fed 100 kcal/kg higher energy density diets than basal energy density diets [31]. However, in the present study, we observed decreased ADFI only at weeks 6 to 9. According to Meng et al. [13], HN diets can improve growth performance without affecting ADFI of growing-finishing pigs which might be reasonable of different results in this study.
Supplementation of protease improved BW and ADG compared to non-supplementation protease groups in this study. These results are consistent with a previous study, reporting that 125 mg/kg of protease (Streptomyces sps and Bacillus licheniformis) supplementation could improve ADG [35]. Increase of ADG with ATTD of CP was observed in the present study, which is consistent with results of previous study [13,32]. The improvement in ATTD of CP and ADG by protease supplementation could be due to the effective breakdown of protein molecules into more useable peptides that can be degraded into amino acids by carboxypeptidases [36]. Thus, increased ATTD of CP might be reasonable by using protease which can improve the utilization of dietary proteins, leading to increase of ADG in this study.
BUN is a waste of protein, which produced by mechanism of N digestion in liver and kidney [37]. Several studies have indicated that BUN concentration and total protein in blood can be used as indicators of protein utilizations and N excretion [35,38]. In the present study, we observed the supplementation of protease decreased BUN concentration and improved ATTD of CP during finishing periods. Following the mechanism of BUN, we considered that the current study’s decreased BUN concentration could be explained by effects of protease, which could improve digestion and utilization of dietary protein.
In aspects of nutrient density, HN diets did not show significant effects on BUN in blood, consistent with results of Yan and Kim results [32]. According to previous studies, differences in nutrient density were 1.2% and 2.1% dietary protein, respectively, with 100 kcal/kg energy level [32,39]. However, studies of Yan and Kim [32] and Wang et al. [39] did not show significant difference of BUN level in the blood. Thus, we hypothesized that more difference between dietary protein and energy levels should be considered to demonstrate the effects of nutrient density on blood profiles in this study.
Significant differences of total protein in blood were not observed in the current study. Consistently, Yan et al. [31] have reported that 1% difference in dietary protein does not reduce total protein in blood. Liu et al. [26] have also reported that supplementation of protease, which derived from Pseudoalteromonas arctica can reduce total protein in blood. The potential mechanism of reduced total protein in blood might be due to increased ATTD of CP which can improve utilization of proteins. Thus, concentration of nutrient density and types of proteases should be considered to identify differences of total protein in blood in this study.
According to Ferket et al. [40] and Yan et al. [41], improved nutrient digestibility could result in decreased gas emissions by reducing substrates for microbial fermentation in the large intestine. Previous studies have reported that protease can reduces gas emissions due to improved utilization and absorption of dietary proteins [25,26]. Gas emissions, which occurred by undigested protein, many studies have reported that the increased ATTD of CP by providing HN diets effects in reducing gas emissions [13,32]. Thus, we considered that the reduction of gas emission might be due to improved ATTD of CP by providing HN diets and protease in this study.
Reduction of pathogenic bacterial population in the gastrointestinal tract and improvement of beneficial microbial activity are considered as main factors that decrease gas emissions by improving microbial fermentation [42]. Although decreased gas emissions were observed, there were no significant differences in fecal microflora in this study. In the aspects of nutrient density diets, Zhao et al. [20] have reported that under 80 kcal/kg energy level difference does not show improvement of fecal microflora, consistent with the current study. Many studies have also revealed that supplementation of protease can provide positive effects in weanling period than in growing-finishing periods due to enhanced resistance to intestinal pathogens [43,44]. Thus, higher more concentration of protease and more nutrient density be needed to identify differences in fecal microflora.
In the current study, we observed an interaction between protease and nutrient density diet in FCR and nutrient digestibility. The possible reason for decreased FCR in HN diets without protease could be explained by higher energy concentration. Pigs consume more feeds to meet their energy requirement when a low energy concentration feed is supplied [20]. Due to this explanation, we considered that the decrease of FCR in HN might be due to energy concentration differences between HN and BN diets. Higher improvement in ATTD of CP was observed in the finishing period in response to PTA supplementation with HN diets. When pigs consume HN diets with PTA (Streptomyces sps), they showed greater digestion of CP compared to CON and PTB (Bacillus licheniformis). This result was consistent with a study of Cheng et al. [45] reporting that supplementation of Bacillus licheniformis in diets with different nutrient densities (0.74% differences in CP) did not show significant difference in ATTD of CP. According to results of the present study, providing HN diets with supplementation of PTA produced by Streptomyces sps could be ideal ways to maximize production while reducing environmental pollution.
CONCLUSION
The result of this study coincides with the hypothesis regarding the effect of high-nutrient density diets and exogenous protease supplementation in diets. In this study, our results showed that the supplementation of exogenous protease could improve growth performance, nutrient digestibility, blood profiles, and gas emission. Also, high nutrient density diets showed beneficial effects on growth performance and nutrient digestibility compared to basal nutrient density diets. In addition, we observed a higher ATTD of CP in HN diets with Streptomyces sps compared to Bacillus licheniformis. In conclusion, providing HN diets with PTA could be ideal strategy to reduce environmental pollution with maintaining productivity.
