Supplementation of carbohydrate enzymes plus protease to the diet of finishing pigs containing 2 protein levels on the effects of growth performance, toxic gas emissions, meat quality, and colonic microbiota community

doi:10.21203/rs.3.rs-2218425/v1

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Research Article

Supplementation of carbohydrate enzymes plus protease to the diet of finishing pigs containing 2 protein levels on the effects of growth performance, toxic gas emissions, meat quality, and colonic microbiota community

https://doi.org/10.21203/rs.3.rs-2218425/v1

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Background

Dietary supplementation with exogenous enzymes may positively affect the traits of finishing pigs. The present study investigated the effects of different protein levels and exogenous carbohydrate enzymes plus protease on growth performance, meat quality, toxic gas emissions, and the structure and function of colonic microbiota in finishing pigs.

Pigs need adequate crude protein (CP) to maintain normal metabolism and promote growth. Recent swine nutrition research has focused on a protein-restricted diet for growing and finishing pigs due to rising soybean meal prices. Some studies indicate that a 1–3% reduction of CP in diets without supernumerary essential amino acids tends to limit the growth speed of finishing pigs and piglets [1, 2]. In contrast, other authors argue that reducing 2% CP in the diet has no effect on the growth performance of finishing pigs [3, 4]. Nevertheless, 1.8-3% increases in CP improve gain-to-feed ratio (G/F) and average daily gain (ADG) in growing-finishing pigs [1, 5, 6]. The low-CP diet not only impacts animal growth but also affects meat quality. Approximately 2% reduction in dietary CP results in deeper backfat and higher muscle intramuscular fat (IMF) content by upregulating lipid gene expression [7, 8]. Moreover, 2–3% reduction in dietary CP modulates the microbial community and corresponding metabolites in finishing pigs [9, 10]. The changed microorganism may reflect that protein components flow into the hindgut and continue biochemical reactions.

For pigs weighing more than 60 kg, enhancing nutrient digestibility of pigs is an imperative issue to control feeding costs. Maize and soybean are major ingredients in swine production for energy, starch, and protein sources. Inevitably, non-starch polysaccharides (NSPs) in the plant cell wall, mainly consisting of arabinoxylan, β-glucan, mannan, and cellulose, can’t be hydrolyzed by endogenous enzymes in monogastric animals but could be partially fermented by hindgut microbes [11]. For example, rapeseed meal results in lower protein digestibility than soybean meal due to high levels of mannans and arabinoxylans [12]. Corn distillers dried grains with solubles (DDGS) has preferable proteins and fat contents, but it also contains a high level of cellulose and oligosaccharides that obstruct nutrient absorption than corn [13]. Also, glycinin and β-conglycinin in the soybean resist hydrolysis by endogenous enzymes due to disulfide bonds. In livestock and poultry, exogenous carbohydrate-active enzymes are widely accepted. β-glucanase, one of the carbohydrate-active enzymes, breaks down β-1,3 − 1,4 glycosidic bonds into oligosaccharides and glucose that can be directly absorbed by small intestinal epithelial cells [14]. Although finishing pigs have a mature enzyme secretion system such as pepsin, trypsin, and chymotrypsin for protein digestion, soybean contains at least 10% anti-nutritional elements, which are resistant to degradation by endogenous protease [15]. The anti-nutritional factors could be weakened by exogenous protease and NSPs enzymes. For corn and corn DDGS, their availability can be improved by supplementation of exogenous α-amylase in broilers fed corn-soybean meal diet [16]. Supplementation of exogenous carbohydrase and protease improved the ADG and G/F by improving nutrient absorption [17, 18]. The additional benefits of exogenous enzymes in diets are higher β-glucan and xylo-oligosaccharides from decomposed cell walls which act as prebiotics for hindgut microbes [19].

Nevertheless, there is limited research on the effects of protein levels and exogenous enzymes on finishing pigs. Therefore, this study aimed to explore the effects of high and middle-high CP levels, the compound-enzyme of α-amylase, protease, and β-glucanase on growth performance, meat quality, toxic gas, nutrient digestibility, and colonic microbiota community and their metabolites of finishing pigs using a 2×2 factorial arrangement.

Experimental and animal management procedures were implemented according to the Guide of Laboratory Animals provided by the Institutional Animal Care Advisory Committee for Dankook University, South Korea (Protocol number: DK-1-2121).

Animals, design, and housing

Two hundred Duroc × (Landrace × Yorkshire) finishing pigs (100 gilts: 100 boars) weighing 68.03 (_SD 3.57) kg were selected and randomly allocated to 1 of 4 diet groups. Every treatment group consisted of 10 repetition pens, each of which had 5 piglets (3 gilts:2 boars or 2 gilts:3 boars). The diets, shown in Table 1, were formulated using corn-soybean meal and isoenergy diet with 2 different protein levels, 16.73% CP (HP) and 14.73% CP (MP). We also analyzed the chemical composition of the feed as shown in Table 2. This 49-d experiment was carried out using a 2×2 factorial design: HP diet and MP diet were supplemented with (+) or without (-) 1g/kg multi-enzymes (ENZs) containing feed activity concentrations of 100 U/kg of protease, 2,500 U/kg of α-amylase, and 10,000 U/kg of endo-1,3(6)-β-glucanase. Diets met the standardized ileal digestible Lys, Met + Cys, Thr, Trp, and NE recommended by NRC (2012) [20] for finishing pigs. Machine ventilation was used to control the temperature and humidity of the pig house (20–22°C and 55–60%). Additionally, all diets contained 0.05% phytase (5,000 U per gram of feed). In the experimental phase, pigs obtained feed and water via a semi-self-feeding machine and a nipple drinker in each pen. To keep the feed fresh, the diets were mixed through a blender (DDK-801F; Daedong Tech, Korea) every week.

Table 1

The ingredient composition for the finishing phase (as-fed basis, %)
Items	High protein	Medium-high protein
Cron	63.76	68.03
Soybean meal	19.84	12.71
Rapeseed meal	3.00	4.00
DDGS (corn)	5.00	7.00
Animal fat	3.40	3.20
Molasses	2.00	2.00
Limestone	1.24	1.27
Di-calcium phosphate	0.53	0.36
Salt	0.30	0.30
DL-Methonine (99%)	0.04	0.01
L-Lysine ·H₂SO₄ (78%)	0.41	0.46
L-Threonine (98%)	0.06	0.07
L-Tryptophan (10%)	0.17	0.34
Vitamin¹–mineral premix²	0.20	0.20
Phytase	0.05	0.05
Total	100.00	100.00
Calculated nutrient composition (%)
Net energy (kcal/kg)³	2450	2452
Dry matter	80.56	80.55
Crude protein	16.74	14.73
Calcium	0.69	0.66
Total phosphorus	0.42	0.38
Crude fiber	2.95	2.92
NSP	120.55	117.28
Crude ash	5.07	4.75
Ether extract	5.71	5.71
Neutral detergent fiber	10.17	10.78
Acid detergent fiber	2.98	3.11
Lysine	1.0164	0.8826
Methionine	0.3241	0.2765
Threonine	0.6729	0.5985
Typtophan	0.1961	0.1825
Met + Cys	0.6204	0.5507
Standardized ideal digestible amino acids⁴, %
Met + Cys	0.6204	0.5507
Lys	0.8610	0.7365
Met	0.2803	0.2334
Thr	0.5162	0.4492
Trp	0.1534	0.1420
¹Vitamin premix provided the followings per kg of basic diets: Vitamin A, 8,000 IU; Vitamin D3, 3,000 IU; Vitamin E, 25 IU; Vitamin K, 3 mg; Vitamin B1, 3 mg; Vitamin B2, 4.8 mg; Vitamin B6,3.6 mg; Vitamin B12, 9 µg; Niacin, 30 mg; Pantothenic, 7.5 mg; Folic acid, 1.5 mg; Biotin, 0.15 mg ²Mineral premix provided the followings per kg of basic diets: Se 0.15 mg, I 0.14 mg, Zn 50 mg, Cu 3 mg, Fe 50 mg, Mn 2 mg.

Table 2

Analyzed chemical composition of experimental diet (%, DM)
Items	High-protein diet	Medium-high protein diet
Dry matter	82.23	82.16
Crude protein	16.92	14.85
Calcium	0.71	0.69
Total phosphorus	0.52	0.41
Crude fiber	3.04	2.98
Crude ash	5.25	4.83
Lys	1.1364	0.9826
Met	0.4541	0.3965
Thr	0.7529	0.6983
Typ	0.2361	0.2025
Met + Cys	0.7004	0.5567

Determination of exogenous enzyme activity in the feed samples

The multi-enzymes were provided by Korea Fermentation Co., Ltd (Gyeonggi-do, South Korea). The protease, α-amylase, and β-glucanase were produced by Bacillus licheniformis, Bacillus licheniformis, and Trichoderma reesei, respectively. We measured enzyme activity in feed samples (500 g). The β-glucanase activity was assayed using the K-MBGL Kit (Megazyme, Bray, Ireland) in duplicate. One unit is the amount of β-glucanase that hydrolyzes barley β-glucan to produce 1 µmol of reducing sugar (calculated as glucose)/min at 50°C and pH 4.8. One unit of α-amylase (MAK009, Sigma-Aldrich, Korea) corresponds to the amount of enzyme that liberates 1 µmol of glucosidic linkage from a water-insoluble cross-linked starch polymer substrate per min at pH 6.5 and 37°C. One unit of protease (A2765, Sigma-Aldrich, Korea) is defined as the amount of enzyme that releases 1.0 µg of phenolic compounds, expressed by a casein substrate per min (pH 7.5 and 40°C). Table 3 shows the measured enzyme values.

Table 3

Analyzed exogenous enzyme activity in each diet.
Items	HP	HP	MP	MP
Items	-ENZs	+ENZs	-ENZs	+ENZs
Protease, U /kg	19	174	21	182
α-amylase, U /kg	35	2623	29	2631
β-glucanase, U /kg	87	10464	83	10426

At the end of weeks 3 and 7, the fasted body weights (BWs) were weighed, respectively without feed consumption overnight. Consumed feed was calculated in each pen. According to the BW gain and feed consumption of each pen, the ADG, ADFI, and G/F were calculated. When the feeding trial was ended, 1 fasting female was randomly chosen from each pen for blood sampling. Blood taken from the anterior vena cava was put in K₃EDTA evacuated tubes (3 mL; Greiner Bio-One, Kramsmenster, Austria) and centrifuged at 3,500 ×g for 10 min. The serum was frozen at -20°C for further analysis of serum total protein, serum urea nitrogen, triglycerides, and total cholesterol using an automatic blood analyzer (HITACHI 747, Japan).

In week 1, week 3, and week 7, of the trial period, chromium trioxide (Cr₂O_3, 2.5 g/kg) as an endogenous indicator was mixed in the feed for 7 days. Fresh feces were collected from the rectum of randomly chosen 2 pigs per pen by stimulating the pig’s anal sphincter to induce defecation after a 4-day transition period. The 3-day feces within an individual pen were pooled equably and frozen at -20 ℃ for further analyses. The baking and grinding of feces followed our previous description [21]. Dry matter was assayed by baking the weighted diet and fecal at 105 ℃ overnight. Nitrogen was measured by Kjelec8100 (Foss, Denmark). Gross energy was represented as the heat of combustion in the feed and fecal, respectively, using a Parr 6100 oxygen bomb calorimeter (Parr Instrument Co., Moline, IL, USA). Crude fat was determined by extracting it in petroleum ether using a Soxhlet apparatus (method 934.01, AOAC 2002) [22]. Apparent total tract apparent digestibility (ATTD) of nutrients was calculated: ATTD (%) = [1 − {(Nf × Cr₂O₃d) ∕(Nd × Cr₂O₃f )}] × 100.

Measurement of toxic gas in feces

Simultaneously 100 g of fresh feces collected from the rectum and 100 g of urine collected by bucket per pen from the same pigs used for nutrient digestibility were put into a 2.6 L plastic crisper and fermented at 25 ℃ for 24 h. The specific method was described in our previous study [23]. The concentration assay of H₂S, NH₃, and methyl mercaptan was conducted using Gastec detector tubes (GV-100; Gastec Corp., Kanagawa, Japan; Gastec detector tube No. 3L, No. 4LT, and No. 70L).

Assessment of meat quality

At the end of the trial, 8 pigs/treatment groups with BW closest to the mean weight of the group were transported to a local commercial slaughterhouse without fasting. Pigs were executed by electrical corona and exsanguination, followed by depilation and removing viscera. The intestinal lumen was rapidly dissected and the intestines were separated. Every colonic digesta was aseptically collected in a sterilized tube and quickly frozen in ˗80 ℃ liquid nitrogen for further 16S metagenome sequencing and short-chain fatty acids.

Each carcass was symmetrically divided into two halves. Backfat thickness was obtained as the mean of the first-rib, last-rib, and last-lumbar fat thickness, using a vernier caliper. The eye muscle area was calculated by height × width × 0.7, where the height and width of longissimus dorsi muscle (LM) were taken between the 10th and 11th ribs of the left half carcass according to the description of Xu et al. [24]. After that, the LM was chilled at 4 ℃ for 24 h for the evaluation of meat quality. After 24 h postmortem, the pH of LM was measured as the mean value of measurements at 3 different sites, using a pH meter (Opto-Star, Matthaus, Germany). Four professional judges evaluated color scores at the grade of 1 to 5 (1 = pale, 2 = light pale, 3 = bright red, 4 = deep red, 5 = dark red) and marbling referring to the criterion of the National Pork Producer Council (NPPC 1999) [25]. The meat color indices, like L* (lightness), a* (redness), and b* (yellowness) were assessed with the average of three random readings of CR410 (Minolta, Japan) calibrated against a standard white plate (8 mm diameter aperture, d/0 illumination system).

Drip loss was evaluated as described previously [23]. Briefly, about 40 g of cubit meat obtained in triplicate from each meat sample was hung at 4 ℃ for 24 h, 72 h, and 96 h. The drip loss = (original cubit weight - cubit weight 24 h/72 h/96 h)/original cubit weight. For cooking loss, approximately 100 g of weighed cubic meat was steamed for 40 min, followed by cooling for 20 min and reweighing. After 24 h of slaughter, 1 cm slices were cut from the LM and weighed. Thereafter, they were compressed by a pressurizer for 5 min to remove water and weighed again. Water loss rate = [(original splice weight-compressed splice weight)]/original splice weight ×100, while water holding capacity = 1- (water loss rate/moisture content of meat).

Approximately 40 g of muscle sliced and weighed, was placed in the freeze dryer (Daihan Scientific, Korea) at -50 ℃ until the weight difference between the initial and final was less than 0.05 g. The difference in weight of the muscle sample represented the water content in the muscle. After that, the dried muscle samples were ground into powder and used for the measurement of crude protein (Method 981.10) and crude ash (Method 942.05) following AOAC (2000) [26]. Intramuscular fat (IMF) was determined using the Soxtec 2055 fat extraction system (Foss Tecator AB, Box 70, S-26321; Höganäs, Sweden) as previously described [22].

Individual metagenomic DNA (mDNA) from 32 colonic digesta samples was extracted with the QIAamp PowerFecal Kit (Qiagen, Germany). The purity and concentration of the extracted mDNA were checked via a Bioanalyzer (Agilent 2100, USA) equipment at the center for Bio-medical Engineering Core Facility (Dankook University, South Korea). The forward primer (314F) and reverse primer (805R) of the 16S V3-V4 hyper-variable region were 5' - TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG − 3' and 5' - GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG − 3', respectively. Polymerase chain reaction products were purified with AMPure XP beads (Beckman Coulter, USA). Optimization of DNA concentration (100 ng) of final amplicon products was normalized by Qubit fluorometric quantification. High-throughput amplicon sequencing was conducted on the MiSeq™ platform (Illumina, San Diego, CA, USA), using paired-end sequence.

All raw sequences (length > 100 bp) were used to create the amplicon sequence variants (ASVs) data using the divisive amplicon denoising algorithm 2 (DADA2). Data (.fasta format) were converted to QIIME2 artifacts (.qza format) for QIIME2 pipeline compatibility, which detects and corrects amplicon errors and filters out PhiX chimeric sequences (Table S1). Sequence data quality control and feature table construction were completed using DADA2 in the QIIME 2 plugin. After the denoising step, the microbial diversity analysis (alpha and beta) was performed with the diversity' algorithm in the QIIME2 plugin. Beta diversity analysis to confirm the dissimilarity of microbial composition between each comparison group was measured by principal coordinate analysis (PCoA) of unweighted_UniFrac and Bray-Curtis distance matrices. Bacterial classification results were created using the Silva database (v.138, https://www.arb-silva.de/search/). All visualization data to explain our microbiome analysis results were created using the ggraph pakage of R Studio (3.6.3).

In terms of short-chain fatty acid (SCFA: acetic acid, propionic acid, and butyric acid) and branched-chain fatty acids assay (BCFA: isovaleric acid and isobutyric acid), one gram of thawed digesta sample was diluted with distilled water (1w:2v), vortexed, and then centrifuged at 15,000 × g at 4°C for 10 min. One mL of supernatant was transferred to a 2-mL centrifuge tube, mixed with 200 µL of 25% (w/v) metaphosphoric acid and 23.3 µL of 210 mmol/L crotonic acid, vortexed, and kept at 4°C for 30 min, followed by centrifugation for 10 min at 15,000 × g. The new supernatant was collected, mixed with carbinol with a volume ratio of 1:3, and filtered through a 0.22-µm polytetrafluoroethylene syringe filter. Finally, 1µL of the filtrate was injected into a 1,260 high-performance liquid chromatography (HPLC) system (Agilent, USA) with a 300 × 7.8 mm Aminex HPX-87H column (Bio-Rad, USA) and refractive index and ultra-violet detectors (λ = 210 nm).

Statistical analysis

The data were statistically analyzed by GLIMMIX procedure of 2×2 factorial arrangement, with CP and ENZs as fixed effects, and pigs as a random effect in the SAS system (SAS 9.4, Institute Inc., Cary, NC, USA). For the analysis of growth performance, ATTD, toxic gas, and blood traits, each pen was the statistical unit. The slaughtered pigs were used as experimental units for the analysis of meat quality and colonic microorganisms. Tukey’s multiple comparisons test was used to separate means when interactive effects were significantly different. The results in Tables were visualized as means and pooled SEM, from least-square means. The Kruskal-Wallis was used to compare the alpha-diversity analysis (Table S2). Permutational multivariate analysis of variance (PERMANOVA) non-parametric statistical test was used to confirm the statistical significance of distance dissimilarity (Bray-Curtis and unweighted_ UniFrac distance matrices) of microbial composition between each comparison group (Table S3). Spearman’s correlation was visualized with “Hmisc” and “heatmap” packages of R 3.6, respectively.

Growth performance and apparent total tract digestibility of finishing pigs

No interactive effects of CP level and ENZs on the final BW, ADG, or ADFI of finishing pigs were found (Table 4). Dietary HP supplementation numerically boosted the ADG per period (P < 0.05) and appeared to boost the G/F ratio (P < 0.1) during weeks 1–3 and weeks 4–7 compared to the MP diet. Additionally, ENZs tended to augment the ADG (P = 0.067) during weeks 1–3 and improved it during weeks 4–7 and overall period (P < 0.05), and tended to improve G/F ratio during weeks 4–7 (P = 0.076) compared with no-ENZs groups.

Table 4

Effect of dietary ENZs on growth performance of finishing pigs fed HP or MP diet1
CP levels	HP	MP			CP × ENZs				Pooled SEM	P-value
ENZs			-	+	HP-	HP+	MP-	MP+	Pooled SEM	CP	ENZs	Interaction
Body weight, kg
Initial	68.04	68.03	68.03	68.04	68.03	68.04	68.03	68.03	1.18	0.995	0.998	0.993
Week 3	85.34	84.85	84.87	85.31	85.04	85.64	84.71	84.98	1.28	0.704	0.736	0.899
Week7	110.78	109.48	109.55	110.71	110.10	111.45	109.01	109.96	1.47	0.387	0.439	0.889
Week 1–3
ADG, g/d	824^a	798^b	801	821	810	88	791	905	11	0.020	0.061	0.489
ADFI, g/d	2379	2369	2370	2377	2371	2387	2370	2368	20	0.590	0.707	0.636
G/F	0.347	0.338	0.339	0.345	0.343	0.350	0.336	0.340	0.005	0.091	0.230	0.731
Week 4–7
ADG, g/d	909^a	880^b	881^b	907^a	895	922	868	892	12	0.023	0.040	0.897
ADFI, g/d	2925	2903	2913	2914	2923	2916	2903	2904	21	0.325	0.953	0.921
G/F	0.311	0.302	0.302	0.301	0.307	0.315	0.298	0.307	0.005	0.089	0.076	0.896
Overall
ADG, g/d	872^a	846^b	847^b	870^a	858	886	836	856	11	0.028	0.049	0.729
ADFI, g/d	2680	2673	2677	2685	2685	2693	2668	2677	16	316	598	944
G/F	0.324	0.317	0.317	0.324	0.320	0.329	0.314	0.320	0.005	0.105	0.110	0.698
¹Each value represents the means of 10 replicate pens. ^{a, b} Represents a row that differs significantly (P < 0.05). Abbreviation: HP, 16.73% protein level, MP, 14.73% protein level; ENZs: the combination of 2,500 U/kg α-amylase, 100 U/kg protease, and 10,000 U/kg β-glucanase.

Table 5 shows that dietary HP improved the ATTD of dry matter during week 3 and the ATTD of nitrogen in week 7 (P < 0.05) whereas the MP diet tended to improve crude fat digestibility during weeks 3 and 7 (P < 0.1). Additionally, ENZs intervention induced higher ATTD of gross energy in week 3 and dry matter and gross energy in week 7, compared with groups without ENZs supplements (P < 0.05).

Table 5

Effect of dietary ENZs on nutrient digestibility of finishing pigs fed HP or MP diet1 (%)
CP levels	HP	MP			CP × ENZs				Pooled SEM	P-value
ENZs			+	-	HP-	HP+	MP-	MP+	Pooled SEM	CP	ENZs	Interaction
Initial
Dry matter	77.15	78.98	77.66	77.57	77.22	77.08	78.10	78.05	0.65	0.162	0.888	0.945
Nitrogen	75.83	75.09	75.54	75.38	75.93	75.73	74.83	75.36	0.66	0.271	0.808	0.589
Gross energy	76.61	76.04	76.65	75.99	76.03	77.19	75.97	76.11	0.88	0.523	0.473	0573
Crude fat	68.41	68.85	58.81	68.45	69.06	67.75	68.56	69.14	0.60	0.462	0.543	0.120
Week 3
Dry matter	74.68^a	73.57^b	74.26	73.99	74.55	74.81	73.42	73.71	0.46	0.021	0.558	0.694
Nitrogen	71.94	71.16	72.02	71.08	71.31	72.57	70.86	71.47	0.55	0.173	0.100	0.562
Gross energy	74.34	73.93	74.76^a	73.31^b	73.26	75.43	73.36	74.49	0.80	0.608	0.048	0.520
Crude fat	63.50	64.41	64.26	63.65	63.07	63.93	64.23	64.60	0.46	0.055	0.190	0.600
Week 7
Dry matter	71.23	70.89	71.54	70.58	70.68	71.78	70.47	71.30	0.39	0.387	0.019	0.730
Nitrogen	69.54	68.77	69.17	69.14	69.47	69.61	68.82	68.73	0.37	0.044	0.944	0.759
Gross energy	69.06	68.25	69.61	68.70	68.18	69.94	67.23	69.28	0.74	0.387	0.019	0.730
Crude fat	58.26	59.11	58.52	58.85	58.64	57.88	59.06	59.16	0.45	0.065	0.471	0.344
¹Each value represents the means of 10 replicate pens. ^{a, b} Represents a row that differs significantly (P < 0.05). Abbreviation: HP, 16.73% protein level, MP, 14.73% protein level; ENZs: the combination of 2,500 U/kg α-amylase, 100 U/kg protease, and 10,000 U/kg β-glucanase.

The pigs fed the HP diet had higher serum urea nitrogen concentration while those fed the MP diet had higher concentration of triglycerides (P < 0.05) in Figs. 1a and 1c, respectively.

Table 6 shows an interaction (P < 0.05) for meat color. The LM from HP + ENZs group was scored lower than that from MP + ENZs group. Dietary HP decreased the marbling score while the MP diet contributed to higher IMF in the meat (P < 0.001), shown in Fig. 2d. Dietary ENZs tended to increase CP content in the LM (Fig. 2c). An interaction of CP with ENZs (P = 0.019) was observed. The addition of ENZs to the MP diet enhanced IMF content in the LM, but reduced it in the HP diet group.

Table 6

Effect of dietary ENZs on meat quality of finishing pigs fed HP or MP diet1
CP levels	HP	MP			CP × ENZs				Pooled SEM	P-value
ENZs			+	-	HP-	HP+	MP-	MP+	Pooled SEM	CP	ENZs	Interaction
Backfat thickness, mm	23.98	23.61	23.73	23.85	23.85	24.10	23.62	23.59	0.36	0.323	0.761	0.702
pH _24h	5.05	5.07	5.06	5.06	5.05	5.06	5.08	5.15	0.08	0.451	0.622	0.482
Eye muscle area, mm²	7646	7524	7487	7683	7563.87	7729.09	7410.88	7636.45	117.48	0.305	0.107	0.799
Water holding capacity, %	46.59	48.22	47.80	47.02	46.62	46.56	48.98	47.47	1.09	0.147	0.482	0.513
Color traits
L*(lightness)	51.65	52.42	52.47	51.59	51.93	51.38	53.02	51.82	0.57	0.185	0.135	0.581
a*(redness)	14.57	15.54	14.47	14.64	14.55	14.60	14.40	14.70	0.21	0.891	0.415	0.563
b*(yellowness)	5.84	5.94	5.84	5.93	5.77	5.91	5.92	5.96	0.10	0.307	0.337	0.596
Cooking loss, %	33.95	34.83	34.15	34.62	33.90	33.99	34.41	35.55	1.08	0.347	0.573	0.633
Drip loss, %
D1	3.82	3.65	3.35	3.31	3.63	4.00	3.78	3.52	0.42	0.693	0.890	0.458
D3	12.69	12.90	3.35	3.28	12.08	13.31	12.91	12.89	0.84	0.803	0.477	0.460
D5	19.44	18.75	3.26	3.18	18.62	20.25	19.07	18.43	0.71	0.339	0.492	0.118
Subjective color score	3.30	3.36	3.35	3.31	3.45^a	3.14^b	3.25^ab	3.47^a	0.10	0.509	0.639	0.011
Marbling score	3.22^b	3.40^a	3.35	3.28	3.26	3.18	3.44	3.39	0.059	0.003	0.247	0.776
¹Each value represents the means of 8 replicate pens ^{a, b} Represents a row that differs significantly (P < 0.05). Abbreviation: HP, 16.73% protein level, MP, 14.73% protein level; ENZs: the combination of 2,500 U/kg α-amylase, 100 U/kg protease, and 10,000 U/kg β-glucanase.

Table 7 exhibits that produced levels of methyl mercaptans, NH_3, and H₂S were similar among groups at the begging of this trial. During weeks 3 and 7, the emissions of NH₃ and H₂S in the feces of pigs fed on the HP diet were significantly augmented (P < 0.05). Meanwhile, the interactive effect between HP and ENZs released more NH₃ (P = 0.008).

Table 7

Effect of dietary ENZs on nutrient digestibility of finishing pigs fed HP or MP diet1 (ppm)
CP levels	HP	MP			CP × ENZs				Pooled SEM	P-value
ENZs			+	-	HP-	HP+	MP-	MP+	Pooled SEM	CP	ENZs	Interaction
Initial
Methyl mercaptans	4.94	5.05	5.11	4.88	4.84	5.04	4.93	5.17	0.21	0.595	0.286	0.927
NH₃	3.99	3.77	3.80	3.96	4.05	3.93	3.87	3.67	0.21	0.305	0.466	0.836
H₂S	2.66	2.61	2.66	2.60	2.61	2.70	2.59	2.62	0.066	0.429	0.355	0.667
Week 3
Methyl mercaptans	5.13	4.98	5.09	5.02	5.28	4.98	4.90	5.06	0.20	0.464	0.745	0.267
NH₃	4.70^a	4.04^b	4.25	4.49	5.01^a	4.39^ab	3.97^b	4.11^b	0.15	< 0.001	0.124	0.016
H₂S	2.87^a	2.71^b	2.85	2.73	2.84	2.90	2.63	2.79	0.07	0.040	0.133	0.520
Week 7
Methyl mercaptans	5.86	5.62	5.62	5.85	5.70	6.02	5.55	5.69	0.15	0.119	0.129	0.552
NH₃	5.41^a	4.78^b	5.19	5.00	5.10^b	5.72^a	4.90^b	4.66^b	0.15	< 0.001	0.228	0.008
H₂S	2.87	2.69	2.83	2.73	2.98	2.76	2.68	2.70	0.08	0.053	0.271	0.180
¹Each value represents the means of 10 replicate pens ^{a, b} Represents a row that differs significantly (P < 0.05). Abbreviation: HP, 16.73% protein level, MP, 14.73% protein level; ENZs: the combination of 2,500 U/kg α-amylase, 100 U/kg protease, and 10,000 U/kg β-glucanase.

In total, 3,110,414 raw reads were detected in 32 sequenced chyme samples. After splicing, filtering, and removing chimeras, non-chimeric reads were clustered into ASVs using Silva (v138) with standard > 70% (default). Sequencing depth, like rarefaction curves (Fig. S1), reflected the total microbial species richness. In Figs. 3a-e, the HP diet boosted higher richness in α-diversity, as revealed by higher observed-ASVs (P = 0.013) and Chao1 (P = 0.024) than the MP diet. While in Figs. 3c-3e, the interaction indicated that the addition of ENZs to the HP diet induced higher Shannon index and Pielou's evenness whereas decreased Shannon index in the MP diet (P < 0.05). Moreover, the interactive effect of MP and ENZs tended to reduce the Simpson index (P = 0.077).

A PERMANOVA analysis (Table S2) including Bray-Curtis and unweighted_ UniFrac indicated that the microbial community was separated among four groups, as visualized in Figs. 4a-d.

Figures 5a-j display the top 10 phyla. The MP diet promoted the growth of Firmicutes in the colon (P = 0.014) while the HP diet enhanced the abundance of Spirochaetota, Verrucomicrobiota, Desulfobacterota, and Fibrobacterota (P < 0.05). By supplementing ENZs in the diet, colonic Actinobacteriota and Desulfobacterota abundance were elevated while Verrucomicrobiota abundance was lowered (P < 0.05) compared with the no-ENZs groups. The interaction between HP and ENZs reduced the abundance of Firmicutes but increased that of Bacteroidetes and Desulfobacterota abundance compared with the interactive effect of MP and ENZs (P < 0.05).

Figures 6a-j show the top 10 bacteria at the family level. Compared to the MP diet, the HP diet increased the abundance of Lactobacillaceae, Oscillospiraceae, Muribaculaceae, and Spirochaetaceae (P < 0.01). Meanwhile, the MP diet prompted higher abundance of Clostridiaceae and Selenomonadaceae (P < 0.01). The ENZs intervention impaired the growth of Clostridiaceae and Peptostreptococcaceae but enriched Lactobacillaceae abundance (P < 0.01). The interactions revealed that when ENZs was added to HP and MP diets, Lactobacillaceae and Muribaculaceae abundance were increased, while Peptostreptococcaceae and Selenomonadaceae abundance were just lowered in the HP diet (P < 0.001).

The top 30 genera were listed in Table 8. Dietary HP boosted the abundance of Lactobacillus, Muribaculaceae, Romboutsia, Treponema, Rikenellaceae_RC9_gut_group, Oscillospiraceae-NK4A214_group, Streptococcus, Turicibacter, [Eubacterium]_coprostanoligenes_group, Ruminococcus, and UCG-010 (P < 0.05), compared with the MP diet. On the other hand, the MP diet increased the abundance of Clostridium_sensu_stricto_1, Terrisporobacter, Prevotellaceae_NK3B31_group, Ruminococcaceae-undifitened, Selenomonadaceae-unculture, and Shuttleworthia. Dietary ENZs enriched the abundance of Lactobacillus, Rikenellaceae_RC9_gut_group, Oscillospiraceae-UCG-002, Megasphaera, Coprococcus, and Succinivibrio abundance whereas lowered that of Clostridium_sensu_stricto_1, Terrisporobacter, Oscillospiraceae-UCG-005, Prevotellaceae_NK3B31_group, Romboutsia, and Turicibacter, compared with groups without ENZs. There were interactions between CP levels and ENZs at the genus level. The ENZs supplement to the HP diet lowered Clostridium_sensu_stricto_1, Terrisporobacter, Romboutsia, and Turicibacter abundance but enriched Lactobacillus, Muribaculaceae, Ruminococcaceae-undifitened, Rikenellaceae_RC9_gut_group, and Blautia abundance. Differently, ENZs addition to the MP diet increased Lactobacillus but lowered Muribaculaceae abundance.

Table 8

Effect of dietary ENZs on genera in colonic digesta of finishing pigs (%)1
CP levels	HP	MP			CP × ENZs				Pooled SEM	P-value
ENZs			+	-	HP-	HP+	MP-	MP+	Pooled SEM	CP	ENZs	Interaction
Clostridium-sensu-stricto-1	27.51^b	42.27^a	26.27^b	43.51^a	45.83^a	9.19^b	41.19^a	43.35^a	2.24	< 0.001	< 0.001	< 0.001
Lactobacillus	17.70^a	6.46^b	21.72^a	2.43^b	2.13^c	33.26^a	2.73^c	10.19^b	1.35	< 0.001	< 0.001	< 0.001
Terrisporobacter	4.30^b	5.93a	3.52^b	6.72^a	7.36^a	1.25^b	6.08^a	5.79^a	0.57	0.008	< 0.001	< 0.001
Oscillospiraceae-UCG-005	3.83	2.93	2.52^b	4.24^a	4.74	2.92	3.73	2.12	0.45	0.052	0.001	0.812
Prevotella	2.86	3.59	4.23	2.19	1.64	4.07	2.74	4.44	1.14	0.527	0.081	0.753
Muribaculaceae	2.75^a	1.32^b	2.24	1.83	2.24^b	3.27^a	1.43^bc	1.21^c	0.25	< 0.001	0.117	0.020
Prevotellaceae-NK3B31-group	1.09^b	2.62^a	1.03^b	2.68^a	0.85^b	1.33^b	4.51^a	0.72^b	0.65	0.026	0.017	0.003
Ruminococcaceae- undifitened	0.51^a	0.37^b	0.40^b	0.47^a	0.37^b	0.65^a	0.44^b	0.30^b	0.05	0.008	0.170	< 0.001
Romboutsia	2.05^a	1.29^b	0.83^b	2.51^a	3.83^a	0.26^c	1.18^b	1.40^b	0.09	< 0.001	< 0.001	< 0.001
Treponema	2.75^a	0.44^b	1.27	1.92	2.31	3.20	0.24	0.64	0.63	0.001	0.317	0.705
Unidentified	0.21	0.10	0.08^b	0.24^a	0.05^c	0.38^a	0.11^b	0.10^b	0.07	0.100	0.031	0.019
Roseburia	1.12	1.59	1.27	1.45	0.40^b	1.85^a	2.51^a	0.69^b	0.24	0.064	0.464	< 0.001
Christensenellaceae-R-7-group	1.24	0.82	1.27	0.79	1.27	1.21	0.31	1.34	0.37	0.276	0.212	0.156
Rikenellaceae-RC9-gut-group	1.52^a	0.49^b	1.31^a	0.73^b	0.89^b	2.16^a	0.57^b	0.47^b	0.20	< 0.001	0.006	0.002
Oscillospiraceae-UCG-002	1.24	0.79	1.32^a	0.71^b	0.87	1.60	0.55	1.03	0.22	0.053	0.011	0.582
Megasphaera	0.99	1.01	1.66^a	0.34^b	0.87	1.60	0.55	1.03	0.22	0.948	0.001	0.077
Coprococcus	0.73	0.96	1.06^a	0.64^b	0.405	1.06	0.87	1.05	0.131	0.097	0.004	0.077
Oscillospiraceae-NK4A214-group	1.06^a	0.58^b	0.94	0.70	0.97	1.15	0.44	0.72	0.14	0.001	0.194	0.904
Blautia	0.79	0.84	0.94	0.69	0.38^c	1.20^a	1.00^ab	0.67^bc	0.17	0.796	0.149	0.002
Turicibacter	1.00^a	0.57^b	0.44^b	1.13^a	1.86^a	0.14^c	0.40^bc	0.75^b	0.13	0.002	< 0.001	< 0.001
Phascolarctobacterium	0.78	0.74	0.87	0.65	0.60	0.97	0.70	0.78	0.12	0.709	0.072	0.231
Streptococcus	1.21^a	0.28^b	0.65	0.85	1.66^a	0.76^ab	0.04^b	0.53^ab	0.31	0.005	0.524	0.032
[Eubacterium]-coprostanoligenes-group	0.99^a	0.45^b	0.80	0.64	0.93	1.04	0.34	0.55	0.16	0.002	0.336	0.746
Succinivibrio	0.77	0.62	1.02^a	0.37^b	0.22	1.32	0.51	0.72	0.23	0.493	0.008	0.059
Ruminococcus	0.85^a	0.44^b	0.73	0.56	0.70	1.00	0.42	0.45	0.08	< 0.001	0.052	0.110
Anaerovibrio	0.41	0.83	0.66	0.59	0.35	0.47	0.82	0.85	0.23	0.077	0.757	0.844
UCG-010	0.81^a	0.43^b	0.67	0.57	0.67	0.95	0.46	0.39	0.13	0.007	0.429	0.205
Selenomonadaceae-uncultured	0.53^b	2.88^a	2.02	1.38	0.13^c	0.93^bc	1.84^b	3.92^a	0.33	< 0.001	0.063	< 0.001
Shuttleworthia	0.06^b	0.98^a	0.67	1.37	0	0.12	0.75	1.21	0.24	0.001	0.228	0.484
Acetitomaculum	0.51^a	0.13^b	0.47^a	0.16^b	0.73^a	0.28^b	0.21^b	0.04^c	0.04	< 0.001	< 0.001	0.001
¹Each value represents the means of 8 replicate pens ^{a, b} Represents a row that differs significantly (P < 0.05). Abbreviation: HP, 16.73% protein level, MP, 14.73% protein level; ENZs: the combination of 2,500 U/kg α-amylase,100 U/kg protease, and 10,000 U/kg β-glucanase.

Short chain fatty acid concentrations in the colonic digesta.

As shown in Table 9, HP contributed to higher SCFA and acetate concentrations and tended to increase isobutyric acid concentration, compared to the MP diet (P < 0.001). The interactive effect of HP and ENZs resulted in higher SCFA and acetate concentrations (P ≤ 0.05) and had the tendency to increase butyrate concentration (P = 0.087).

Table 9

The effects of dietary CP levels and multi-enzyme complex on the VFA of finishing pigs (umoL/ g dry feces)1
CP levels	HP	MP			CP × ENZs				Pooled SEM	P-value
ENZs			+	-	HP-	HP+	MP-	MP+	Pooled SEM	CP	ENZs	Interaction
SCFA	91.08^a	83.52^b	87.75	86.84	89.44^ab	92.71^a	84.25^bc	82.79^c	1.15	< 0.001	0.439	0.050
Acetate	36.14^a	29.67^b	32.75	33.06	35.07^a	37.21^a	30.44^b	28.91^b	0.76	< 0.001	0.694	0.023
Propionate	22.50	21.94	21.95	22.49	22.16	22.85	21.75	22.13	0.56	0.325	0.347	0.778
Butyrate	11.16	10.81	10.84	11.13	10.82	11.51	10.86	10.76	0.22	0.129	0.204	0.087
Isovaleric acid	15.40	15.01	15.49	4.96	15.78	15.01	15.20	14.90	0.37	0.358	0.160	0.539
Isovaleric acid	5.91	6.23	5.94	6.20	5.68	6.13	6.19	6.27	0.17	0.070	0.133	0.279
BCFA	21.30	21.28	21.15	21.43	21.46	21.39	21.39	21.16	0.44	0.952	0.541	0.922
¹Each value represents the means of 8 replicate pens ^{a b} Represents a row that differs significantly (P < 0.05) Abbreviation: HP, 16.73% protein level, MP, 14.73% protein level; ENZs: the combination of 2,500 U/kg α-amylase, 100 U/kg protease, and 10,000 U/kg β-glucanase.

The spearman’s correlation analysis for short-chain fatty acids and colonic microbiota at the genus level.

Figure 7 shows that acetate concentration was positively correlated with the abundance of Lactobacillus, Muribaculaceae, Rikenellaceae_RC9_gut_group, Oscillospiraceae-NK4A214_group, Ruminococcus, UCG-010, and [Eubacterium]_coprostanoligenes_group, but negatively correlated with Clostridium_sensu_stricto_1, Shuttleworthia, Terrisporobacter, and Anaerovibrio abundance. Christensenellaceae_R-7_group, Rikenellaceae_RC9_gut_group, Oscillospiraceae-NK4A214_group, Oscillospiraceae-UCG-002, and UCG-010. Butyrate production was positively related to Lactobacillus, Muribaculaceae, Rikenellaceae_RC9_gut_group, and Oscillospiraceae-NK4A214_group abundance, but Clostridium_sensu_stricto_1 played the contrary function to produce butyrate. Isovaleric acid was associated with the abundance of Muribaculaceae.

Growth performance

Protein level maintains the normal life activities of pigs and is closely related to their growth. One of the previous studies reported that a 2% increment in dietary CP level resulted in similar growth performance of growing-finishing pigs [4], compared with the standard CP level diet recommended by NRC (2012) [20]. Another study found that 14.8% and 16.8% CP in growing-finishing pigs’ diets fail to affect growth performance [27]. In contrast to the result, other studies found that 16.28% and 15.5% CP induced higher ADG and G/F ratio in the growing-finishing period by improving nutrient digestibility of dry matter, gross energy, and nitrogen [6, 28]. Hence, the effect of CP level on the growth of growing-finishing pigs has been inconsistent among different studies. The present study found that 16.73% CP diet on finishing pigs augmented ADG and G/F ratio. It may be associated with the increasing tendency of G/F ratio by promoting dry matter and nitrogen nutrient digestibility. The higher crude fat digestibility in the MP diet group may reflect the positive lipid regulation by low protein [29]. Additionally, serum urea nitrogen, as the primary end-product of protein metabolism in the liver, was positively related to excessive protein supply in the 16.73% CP diet group [4, 5, 6, 27].

As expected, ENZs led to higher ADG of pigs fed corn-soybean meal during weeks 4–7 and the overall period. This may result from an improvement in nutrient digestibility of gross energy and dry matter utilization, revealed by the increasing tendency of G/F ratio in response to the exogenous compound enzymes, as reported previously in finishing pigs [17]. Complex enzymes including protease, amylase, and xylanase effectively augmented the nutrient digestibility of dry matter, CP, starch, neutral detergent fiber, and acid detergent fiber in T-cannula of piglets and in vitro [30]. Likewise, multi-carbohydrase plus protease was able to degrade DDGS in vitro [31]. Specifically, endo-β-1,4-glucanase decompose 1,4 glycosidic bonds in the cell wall of cereal endosperm and exposes the constrained protein, starch, and minerals to enzymes [32]. Mechanistically, protease can help pepsin to break down dietary proteins into amino acids and peptides [33] and diminish antinutritional factors in soybean by degrading glycinin, beta-conglycinin, and soybean trypsin [34]. Moreover, α-amylase hydrolyzes α-1,4 glycosidic bonds of starch to release maltose and glucose, which, in turn, prompts more energy release [18]. Besides, compound enzymes including protease and NSPs enzymes improved the ATTD of dry matte, gross energy, and CP, compared to the effect of mono-enzyme, resulting in greater ADG in growing pigs and broilers [17, 18, 35, 36].

Meat quality is an essential economic characteristic of finishing pigs and determines flavor and shelf time, as reflected by pH, color, drip loss, fat content, and protein composition [6]. But in this study, these parameters, except IMF content, were not affected by CP levels or ENZs supplement. This result is similar to the result of Alonso et al. [7], that 14.92% CP diet led to higher IMF in the LM of finishing pigs than 17.0% CP diet. Reportedly, 2 or 3% of reduction in protein level stimulated the activation of lipogenic-related genes, leading to elevated IMF content in the LM of growing or fattening pigs [1, 7, 37, 38]. Differently, the increased IMF in a 3%-reduction of CP diet in fattening pigs was demonstrated by converting muscle glycolytic fibers to oxidative fibers as the lower glycolytic enzymes induced by lower-CP levels [5]. Higher triglyceride concentrations and crude fat absorption in the 14.73% CP group suggests that the lower CP level could accelerate lipid synthesis and deposition. It is possible that greater marbling in the MH group might result from a concurrent increase in IMF [37].

In addition, the interaction between 14.73% CP and ENZs increased IMF content, compared to the interactive effect of 16.73% CP with ENZs because of the main effect, 14.73% CP. In short, A higher IMF content in meat with a better taste is preferred by consumers [37]. The present study proposes that 14.73% CP benefited the more IMF content in finishing pigs.

Reducing dietary CP levels is an effective strategy to decrease NH₃ emissions [39] as monogastric animals have unabsorbed 60–70% of fecal and urinary nitrogen [4]. Decomposed NH₃ mainly from poultry and swine excrement is a key air pollutant as it makes up the particulates in the atmosphere [40]. Consequently, the excretion from HP-treated pigs released more NH₃ and H₂S. It was similar to the results of previous studies on the effect of high protein diets on NH₃ release [4, 10, 39, 41]. The majority of NH4⁺ in the excrete would be hydrolyzed by urease from the microbiota, releasing NH₃ [42]. Sequentially, toxic H₂S are produced by cysteine decomposition and metabolic activity of colonic sulfate-reducing bacteria in mammals [43]. The Met + Cys percentage was higher in the 16.73% CP group than in the 14.73% CP group, which may partially explain the higher H₂S in the 16.73% CP diet group. Although ENZs had no impact on NH₃ emissions, the interaction between ENZs and HP produced more NH₃. Previous reports found that protease plus non-starch polysaccharide enzymes had no influence on NH₃ production [44]. A plausible explanation would be that NSPs-enzymes stimulated microbial activity to utilize more ammonia [45], which in turn caused less ammonia production. As hindgut was the major gas-producing zone, we suspected that dietary CP level and ENZs may impact colonic microbes and their gas production. Hence, we further assayed colonic microbes through 16S ribosomal RNA sequencing.

Based on the MiSeq™ platform, alpha diversity that describes the biodiversity (Shannon and Simpson), the richness (Chao1 and observed _OTUs), and the evenness (Pielou’s evenness) in a sample is calculated at the same sequencing depth. The result found that dietary HP contributed to the elevated microbial richness (Observed_ ASVs and Chao1). This result was consistent with the study conducted by Fan et al. [9], that α-diversity was reduced along with the decreasing CP level from 16–10%. Microbial richness is a crucial parameter for host-microbe symbiosis, the overall health, and the productivity of animals [46]. The interaction between HP and ENZs led to higher microbial diversity (Shannon and Pielou’s evenness) whereas the interactive effect of MP with ENZs lowered the Shannon index, suggesting that the interaction between HP with ENZs enhanced the microbial community diversity and stability. Regarding beta diversity, dietary CP level, ENZs supplements, and the interaction of these two factors changed bacterial community composition. Hence, we further analyzed the microbiota at the phyla, family, and genus levels.

The result found that the HP diet was detrimental to phylum Firmicutes but was advantageous for cellulolytic bacteria, such as Spirochaetota, Verrucomicrobiota, and Fibrobacterota, that mainly break down polysaccharides and cellulose, producing more sugars and SCFAs in the gastrointestinal tract of calves [47–49,]. However, Fan et al. [9] and Zhao et al. [10] showed that the abundance of Firmicutes in the pigs' gut decreased along with decreasing CP levels, contrary to this result. Reportedly, glycinin, β-conglycinin, and lectins as anti-nutritional elements in soybean meal are detrimental to Firmicutes [50]. It could explain the lower Firmicutes abundance in the HP + ENZs group than in the MP + ENZs because the dietary ENZs failed to affect Firmicutes. Higher abundance of Verrucomicrobia in rumen and Spirochaetota in growing pigs, in response to the HP diet in this study, was reported by Qiu et al. [51]. As dietary protein levels increase, more N-containing substances enter the hindgut, prompting the proliferation of N metabolism-associated bacteria [10]. Proteobacteria and Bacteroidetes are the two major N-metabolizing microbiota that can be related to NH₃ production in the HP + ENZs group [10]. Desulfobacterota mainly deacidifies sulfate and ferments pyruvate [52]. Supplementation of ENZs increased the above-mentioned three bacteria in HP diets, suggesting that ENZs decomposed proteins and more nitrogenous compounds reached the hindgut. Additionally, Desulfobacterota is H₂S-producing bacteria and its abundance may be more closely associated with sulfur in the content of Met + Cys in the HP diet. Of note, more H₂S in the HP diet group may be due to it. Interestingly, Verrucomicrobiota producing the most carbohydrate-degrading enzymes was reduced but Actinobacteriota linked to respiratory disease in pigs was increased [9] under ENZs intervention. In the present study, the fixed factors, ENZs, CP, and ENZs × CP elevated Lactobacillus abundance. This microbe consumes various carbohydrates, has antimicrobial activity, and reduces fecal cadaverine [53]. Its high abundance may be due to the increase in available carbohydrates along the gastrointestinal tract since dietary α-amylase and β-glucanase help to decompose carbohydrates into oligosaccharides, stimulating the growth of Lactobacilli [54] in ENZs groups and interaction groups. The abundant Lactobacillus in the HP diet was supported by Zhou et al. [55]. Prevotellaceae_NK3B31_group, a fiber-degrading bacteria, was enriched in the colon by the MP diet, which was consistent with the findings of Zhao et al. [10]. However, the bacteria were abundant in the no-ENZs treatments. We suspected that ENZs intervention promoted the vast majority of cellulolytic bacteria such as Coprococcus, Rikenellaceae_RC9_gut_group, Megasphaera, and Lactobacillus, but this is not absolute.

Blautia, a dominant flora in mammals, was enriched in the HP + ENZs group, maintaining environmental homeostasis by preventing inflammatory diseases and attending to metabolic diseases [56]. Muribaculaceae having a similar function to Blautia, was also abundant in the HP groups [57]. Interestingly, the diets of HP, ENZs, and HP × ENZs lowered the pathogenic bacteria Clostridium_sensu_stricto_1 that was adverse for metabolism, including glutathione and amino acids in intrauterine growth restriction of newborns [58], and positively correlated with epithelial inflammation [59]. Additionally, the abundance of Peptostreptococcaceae and its derivative Terrisporobacter was reduced in the HP + ENZs group, which were both positively associated with oxidative stress [60]. It was found that the HP diet promoted the growth of protein-fermenting bacteria, including pathogenic Streptococcus [61]. This may explain the higher NH₃ emissions found in the HP diet group in this study because Streptococcus secretes more urease that mainly decomposes NH4⁺ [62]. Moreover, other urease-producing bacteria such as [Eubacterium]_coprostanoligenes_group, Peptostreptococcaceae, and Selenomonadaceae were enriched in the HP diet groups [42]. In general, the interaction of HP and ENZs had a profound influence on colonic microbes, compared with a single diet, either HP or ENZs.

Spearman correlation analysis for short-chain fatty acids and microbiota

Gut microorganisms are major SCFA producers, targeting the undigested proteins and fiber in monogastric animals owing to their NSPs enzymes. Therefore, alterations in microbiota properties may affect their metabolites [63]. The result of the present study suggests that the HP diet was partially responsible for the increased abundance of saccharolytic bacteria and carbohydrate fermenting bacteria. Family Oscillospiral and its subordinates, Oscillospiraceae-UCG-002, Oscillospiraceae-UCG-005, and Oscillospiraceae-NK4A214_group, degrade starch and oligosaccharides [64] This role was also found in Ruminococcus [65]. Spirochaetaceae, and its derivative Treponema, both abundant in HP groups, digest cellulose [66]. There was also polysaccharide-degrading bacterium with higher abundance induced by the interactive effect of CP levels and ENZs supplements, like Lachnospiraceae [10, 67]. Additionally, fermentation-associated bacteria were also altered, in the HP diet and HP + ENZs diet, producing high SCFA and acetate concentrations. This increment suggested that microbial activity was enhanced by a high-protein diet as previously proved [9]. According to Spearman correlation analysis, Lactobacillus, Muribaculaceae, Rikenellaceae_RC9_gut_group, Ruminococcus_UCG_010, Eubacterium_ coprostanoligenes_ group positively contributed to the acetate production in this study possibly due to the producing-SCFA capacity [53, 67, 68]. As well-known, acetate could decline obesity by improving liver metabolism and the matrix for synthesis of butyric acid via acetyl CoA [69]. Besides, HP tended to induce higher isobutyric acid produced by microbiota fermenting undigestible proteins, suggesting that more undigested proteins flowed into the hindgut. The interaction between HP and ENZs contributed to higher butyrate, a primary energy source for colon epithelial cells [39]. This result can be attributed to enriched Lactobacillus, Muribaculaceae, and Rikenellaceae_RC9_gut_group in the HP + ENZs group based on Spearman analysis. Microorganism not only metabolize proteins but amino acids to produce SCFA. For example, they metabolize glycine, alanine, threonine, glutamate, lysine, and aspartate to produce acetic acid, glutamate and lysine to produce butyric acid, and valine to produce iso-butyric acid [70].

In summary, 16.73% CP diet and dietary ENZs promoted higher ADG probably by improving nutrient digestibility of nitrogen, dry matter, and gross energy. Dietary 14.73% CP may lead to high meat taste with higher IMF ascribing more crude fat absorption of finishing pigs, but 16.73% CP diet was detrimental to the environment by causing more emissions of NH₃ and H₂S in the feces. The present study found that, based on Chao1 and observed-ASVs, 16.73% CP induced higher microbial richness in colonic microbiota and prompted a higher abundance of carbohydrate-decomposing bacteria, producing a higher acetate concentration. Although the interactive effect of HP and ENZs had no impact on growth performance and toxic gas emission, it elevated higher microbial diversity in Shannon index and Pielou's evenness, and increased the abundance of Bacteroidota but lowered that of Firmicutes and Clostridium_sensu_stricto_1. Besides, dietary ENZs intervention primarily modulated Actinobacteriota, Desulfobacterota, Clostridium_sensu_stricto_1, Lactobacillus, and Rikenellaceae_RC9_gut_group.

16.73% crude protein

14.73% crude protein

crude protein

ENZs:

Declarations

Competing interests

There was the absence of any conflict of interest agreed by all authors.

Funding

This research was supported by Basic Science Research Capacity Enhancement Project through Korea Basic Science Institute (National Research Facilities and Equipment Center) grant funded by the Ministry of Education (Grant No. 2019R1A6C1010033) (K.H.).

Authors' contributions

QZ: conducted experiment and sample collection, writing-original draft; SC: supervision, conceptualization, and methodology; JS: measured the nutrient digestibility, blood parameters, and meat quality; JJ, MY, and MS: conducted the microbial 16S sequencing and analysis; KH: Funding acquisition and writing-review; IK: Experimental design. All authors revised and approved the final manuscript.

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Two hundred finishing pigs were randomly allocated to 4 treatments. The experiment was designed in a 2 × 2 factorial arrangement. Grouping was based on 4 diets: 16.73% crude protein (CP, HP) and 14.73% crude protein (MP) diet supplemented with or without 1g/kg multi-enzymes (ENZs, including protease, α-amylase, and β-glucanase).

Compound-enzymes of carbohydrase plus protease; ADG: average daily gain; ADFI: average daily feed intake; G/F: gain to feed ratio; BW: body weight; NSPs: non-starch polysaccharides; DDGS: Corn distillers dried grains with solubles; SCFA: short-chain fatty acids; BCFA: branched chain fatty acids; LM; longissimus dorsi muscle; IMF: Intramuscular fat; ATTD: apparent total tract digestibility

Acknowledement

The Department of Animal Resource & Science was supported through the Research-Focused Department Promotion & Interdisciplinary Convergence Research Projects as a part of the University Innovation Support Program for Dankook University in 2022.

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Supplementation of carbohydrate enzymes plus protease to the diet of finishing pigs containing 2 protein levels on the effects of growth performance, toxic gas emissions, meat quality, and colonic microbiota community

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Abstract

Background

Introduction

Materials and methods

Animals, design, and housing

Determination of exogenous enzyme activity in the feed samples

Sampling and analysis

Assay of apparent total tract digestibility

Measurement of toxic gas in feces

Assessment of meat quality

Muscle chemical analysis

Illumina library construction and 16S V3-V4 metagenome sequencing

The measurement of short chain fatty acids

Statistical analysis

Results

Growth performance and apparent total tract digestibility of finishing pigs

Serum parameters

Meat quality traits and sensory analysis

Toxic gas in the excrement

Colonic microbiota community

Discussion

Growth performance

Meat quality

Toxic gas emissions

Conclusion

Abbreviations

Declarations

Declarations

Funding

Authors' contributions

References

Unsectioned Paragraphs

Supplementary Files

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