Effects of yeast culture supplementation and the ratio of non-structural carbohydrate to fat on rumen fermentation parameters and bacterial-community composition in sheep

Animal Feed Science and Technology 249 (2019) 62–75

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Effects of yeast culture supplementation and the ratio of nonstructural carbohydrate to fat on rumen fermentation parameters and bacterial-community composition in sheep

T

Yang-zhi Liua, Xue Chena,b, Wei Zhaoa,b, Min Langa, Xue-feng Zhanga,b, Tao Wanga,b, ⁎ ⁎ Mohammed Hamdy Farouka,c,d, Yu-guo Zhena,b, , Gui-xin Qina,c, a Department of Animal Nutrition and Feed Science, College of Animal Science and Technology, Jilin Agricultural University, Changchun, 130118, PR China b JLAU-Borui Dairy Science and Technology R&D Center of Jilin Agricultural University, Changchun, 130118, PR China c Key Laboratory of Animal Production, Product Quality and Security, Ministry of Education, Jilin Agricultural University, Changchun, PR China d Animal Production Department, Faculty of Agriculture, Al-Azhar University, Nasr City, Cairo, 11884, Egypt

A R T IC LE I N F O

ABS TRA CT

Keywords: Bacterial-community composition Ratio of non-structural carbohydrate to fat Rumen fermentation parameters Sheep Yeast culture

This study aimed to evaluate the effects of yeast culture (YC) supplementation and the ratio of non-structural carbohydrate to fat (NSCFR) on rumen fermentation parameters (RFPs) and bacterial-community composition (BCC) using 6 ruminally cannulated sheep in a 2 × 3 factorial experiment. We formulated 6 dietary treatments with 3 levels of YC supplementation (0, 0.8 and 2.3 g/kg of dietary dry matter) and 2 dietary NSCFRs (17.02 and 5.60). Each animal was fed 1 of 6 diets in a 6 × 6 Latin square arrangement during the experiment. Ruminal liquid was sampled at 0, 2, 4, 6, 8, and 12 h after morning feeding on days 16 and 17 (last 2 days) in all 6 of the Latin square periods. The concentrations of acetic acid, butyric acid and total volatile fatty acid (TVFA) were significantly (p < 0.05) increased and the pH values were significantly (p < 0.05) decreased when the animals fed on high-NSCFR diet (H diet) with 2.3 g/kg of YC at 2 h after feeding compared with that on the low-NSCFR diet (L diet). However, the concentrations of ammonia nitrogen (NH3-N) were higher (p < 0.05) in all H groups than that in L groups. The relative abundances of Prevotella_1 were higher in all L groups (p < 0.05), while Lachnospiraceae_NK3A20 and Olsenella were higher in H groups (p < 0.05). Compared with L groups, the relative abundances of Candidatus_Saccharimonas and [Ruminococcus]_gauvreauii of H groups were increased when supplemented with YC (2.3 g/kg; p < 0.05). A significant increased relative abundance of Butyrivibrio_2 was observed in the L group (2.3 g/kg YC). Overall, the RFPs and BCC were influenced by both dietary NSCFR and YC supplementation. There was significant interaction between dietary NSCFR and YC supplementation in the aspects of VFAs, NH3-N and all genera of BCC.

Abbreviations: A/P, acetic to propionic acid; BCC, bacterial-community composition; BUN, blood urine nitrogen; CCA, canonical correspondence analysis; CP, crude protein; DM, dry matter; H diet, high ratio of non-structural carbohydrate to fat diet (17.02, 32.5 NSC, 1.91 fat); L diet, low ratio of non-structural carbohydrate to fat diet (5.60, 23.5 NSC, 4.51 fat); NDF, neutral detergent fiber; NH3-N, ammonia nitrogen; NSC, non-structural carbohydrate; NSCFR, ratio of non-structural carbohydrate-fat; PCR, polymerase chain reaction; PVC, polyvinyl chloride; RDP, ribosomal database project; RFPs, rumen fermentation parameters; TVFA, total volatile fatty acid; VFAs, volatile fatty acids; YC, yeast culture ⁎ Corresponding authors at: Department of Animal Nutrition and Feed Science, College of Animal Science and Technology, Jilin Agricultural University, Changchun, 130118, PR China. E-mail addresses: [email protected] (Y.-g. Zhen), [email protected] (G.-x. Qin). https://doi.org/10.1016/j.anifeedsci.2019.02.003 Received 5 February 2018; Received in revised form 2 February 2019; Accepted 9 February 2019 0377-8401/ © 2019 Elsevier B.V. All rights reserved.

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1. Introduction Yeast culture (YC) has been widely used as an additive in ruminant animal nutrition for several decades. It is thought that YC enhances ruminal fermentation (Mohamed et al., 2009), improves the ruminal bacterial community (Mullins et al., 2013; Jiang et al., 2016), and promotes animal performance (Haddad and Goussous, 2005; Dias et al., 2017). YC is a type of prebiotic produced through aerobic proliferation and anaerobic metabolism of yeast cell on specific culture media. It is mainly composed of yeast extracellular metabolites including peptide, alcohols, esters, organic acids, and a small amount of inactive yeast cell (Shurson, 2018; Sun, 2018). Explanations for the mechanisms by which YC positively adjusts ruminant metabolism vary. Nisbet and Martin (1991) noted that the organic acids and saccharides contained in YC benefited the growth and metabolism of microorganisms such as S. ruminatium and M. elsdenii in the rumen. Some researchers have demonstrated that inactivated yeast (Saccharomyces cerevisiae) cells contain bioactive compounds that can modify ruminal bacterial-community composition (BCC), improve nutrient digestibility and ruminal health (Girard and Dawson, 1994). Results of YC used as a nutritional additive in ruminant animals vary greatly by study. YC supplementation significantly modified ruminal pH value when animals were fed a diet with a high level of concentrate (70%; Andrighetto et al., 1993). However, no significant differences in pH value were observed between supplemental YC and control group when the animals were fed a diet with lower concentrate level (30%; García et al., 2000; Can et al., 2007). Deaville and Galbraith (1992) conducted a YC supplementation experiment with different dietary-protein levels and found a significant improvement in liveweight gain in the high-protein-diet (18%) group only. Effects of YC supplementation on dry matter intake, milk yield and milk fat content are inconsistent between the diets with higher-forage neutral detergent fiber (NDF; 21%) and lower-forage NDF (17%; Wang et al., 2001). It can be speculated, based on the above mentioned mechanisms and research results that the effects of YC supplementation may vary with nutritional supplementation. In order to clarify the interaction between YC supplementation and dietary ratio of nonstructural carbohydrate to fat (NSCFR) in their effects on rumen fermentation parameters (RFPs) and bacterial-community composition (BCC) in sheep, a 2 × 3 factorial experiment was conducted with 2 dietary NSCFRs and 3 levels of YC supplementation. 2. Material and methods 2.1. Animals, diets, and experimental design Six male small-tailed Han sheep (body weight 30 ± 2 kg; age 12 ± 1 months) were fitted with ruminal fistula and randomly assigned to 1 of the 6 experimental treatments during 6 experimental periods in a 6 × 6 Latin square design. Each period consisted of 15 days of adaptation to the diets and 2 days of sampling. The arrangement of the experimental animals is presented in Table S1. The dietary treatments were as follows: (1) Hh: high-NSCFR diet (H diet, 17.02; 32.5 NSC: 1.91 fat) with high level of YC (2.3 g/kg of dietary dry matter [DM]); (2) Hl: H diet (17.02; 32.5 NSC: 1.91 fat) with low level of YC (0.8 g/kg of dietary DM); (3) Hc: H diet (17.02; 32.5 NSC: 1.91 fat) with no YC supplementation; (4) Lh: low-NSCFR diet (L diet, 5.60; 25.3 NSC: 4.51 fat) with high level of YC (2.3 g/kg of dietary DM); (5) Ll: L diet (5.60; 25.3 NSC: 4.51 fat) with low level of YC (0.8 g/kg of dietary DM); and (6) Lc: L diet (5.60; 25.3 NSC: 4.51 fat) with no YC supplementation. The ingredients and chemical composition of the diets are presented in Table 1. Chemical composition of the ingredients was determined as proposed by AOAC: Official Methods of Analysis, 15th ed. (1990). YC was prepared in JLAU-Borui Dairy Science and Technology R&D Center, College of Animal Science & Technology, Jilin Agricultural University, Changchun, China. Animals were kept in individual rearing cages and limited them to feedings of 1.1 kg/day of diet DM (Ranjhan, 1998) twice daily at 7:00 a.m. and 7:00 p.m., with free access to clean water. All of the experimental procedures were in accordance with the Guidelines for the Care and Use of Experimental Animals of Jilin Agricultural University. Using a polyvinyl chloride (PVC) tube, ruminal fluid was collected (40 mL) into 50 mL sterile centrifuge tubes via ruminal cannula at 0, 2, 4, 6, 8, and 12 h after morning feeding. The samples were filtered through 4 layers of gauze (120 meshes), then divided in half. One half was used for analyzing concentrations of volatile fatty acids (VFAs) and NH3-N; the other was preserved in liquid nitrogen at -196 °C for BCC analysis. 2.2. Ruminal -fluid pH, VFAs and NH3-N Ruminal pH was determined using a Sanxin MP523-04 pH meter (Shanghai Sanxin Instrumentation, Inc., Shanghai, China) per manufacturer’s guidelines. Metaphosphoric acid (200 μL) was mixed with 1 mL of thawed ruminal fluid and centrifuged at 11,000 ×g for 15 min at 4 °C. The supernatant was used to analyze acetic acid, propionic acid, butyric acid, and total volatile fatty acid (TVFA) by an Agilent 7890 A Gas Chromatography (Agilent Technologies, Santa Clara, California, USA) with a 50 m (internal diameter 0.32 mm) CP-Wax Chrompack silica-fused capillary column (Varian, Palo Alto, California, US) per Isac et al. (1994). Nitrogen was used as the carrier gas, and the oven initial and final temperatures were 65 °C and 195 °C, respectively. Detector and injector temperatures were set at 250 °C, and injector volume was 1 μL. NH3-N was determined per the method established by Chaney and Marbach (1962) using a Shimadzu UV-1201 spectrophotometer (Shimadzu, Kyoto, Japan). 2.3. DNA extraction, polymerase chain reaction (PCR) amplification and high-throughput sequencing Next-generation sequencing (NGS), including library preparations, were conducted at Genewiz, Inc. (Suzhou, China) using an 63

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Table 1 Ingredients and chemical composition of the experimental diets (% of dry matter). Item Ingredients Leymus chinensis Corn Beam pulp Premixa Salt Corn bran Rumen bypass fat Molasses Chemical composition Dry matter MEb, MJ/kg Crude protein Starch Sugar Non-structural carbohydrate Fat Nonfiberous carbohydrate Neutral detergent fiber Acid detergent fiber Calcium Phosphorus Rumen undegradable protein Rumen degradable protein

Hc diet

L diet

40.00 43.00 15.40 0.60 1.00 – – –

48.00 24.20 15.00 0.52 1.00 6.00 2.24 3.00

90.10 8.51 13.50 27.82 4.73 32.50 1.91 41.03 30.02 17.10 0.35 0.37 5.32 6.27

89.98 8.45 13.80 18.41 6.88 25.30 4.51 33.01 36.04 20.31 0.38 0.37 5.72 5.94

a Premix composition (per kilogram): FeSO4 8453 mg, CuSO4•5H2O 1480 mg, MnSO4 13,241 mg, ZnSO4•5H2O 8294 mg, CoCl2 16 mg, KI 30 mg, Na2SeO3 (1% Se) 377 mg, Vitamin A 755 IU, Vitamin D 113 IU, Vitamin E 887 IU. b Calculated according to NRC (2003). c H diet: high ratio of non-structural carbohydrate to fat diet (17.02; 32.5 NSC : 1.91 fat); L diet: low ratio of non-structural carbohydrate to fat diet (5.60; 25.3 NSC : 4.51 fat).

Table 2 Effects of yeast culture (YC) supplementation in H and L diets on ruminal pH, NH3-N concentration (mg/100 mL). Item

Treatments Hh1

pH value 0h 6.78 2h 5.49a 4h 5.74a 6h 6.10 8h 6.40 12 h 6.58 NH3-N (mg/100 mL) 0h 7.96c 2h 8.70cd 4h 6.56c 6h 6.18c 8h 6.60b 12 h 6.90c

SEM Hl

Hc

Lh

Ll

Lc

6.80 5.51a 5.79a 6.27 6.42 6.53

6.87 5.75b 5.83ab 6.10 6.34 6.53

6.85 5.88bc 5.92ab 6.12 6.45 6.75

6.78 5.99c 6.01b 6.28 6.41 6.61

6.69 5.84bc 6.00b 6.23 6.45 6.63

8.79d 9.43e 6.56c 7.79d 7.14b 7.51c

6.80b 7.90b 7.14cd 7.87d 8.32c 6.15b

6.93b 6.95a 4.17a 4.47a 5.32a 5.47ab

6.90b 8.12bc 5.67b 5.34b 4.74a 5.93ab

5.53a 8.95de 7.60d 6.84c 6.66b 5.22a

p-Value Diets

YC

Time

D × YC

0.07 0.06 0.06 0.10 0.06 0.14

< 0.01

0.83

< 0.01

0.68

0.26 0.27 0.36 0.31 0.28 0.26

< 0.01

< 0.01

< 0.01

< 0.05

a,b,c,d,e

Means in the same row with different superscripts are significantly different (p < 0.05). Hh: Diet of high ratio of non-structural carbohydrate to fat with high-dose of yeast culture; Hl: Diet of high ratio of non-structural carbohydrate to fat with low-dose of yeast culture; Hc: Diet of high ratio of non-structural carbohydrate to fat without YC; Lh: Diet of low ratio of non-structural carbohydrate to fat with high-dose YC; Ll: Diet of low ratio of non-structural carbohydrate to fat with low-dose YC; Lc: Diet of low ratio of nonstructural carbohydrate to fat without YC. 1

Illumina MiSeq (Illumina, San Diego, California, US). DNA (30–50 ng) was extracted using TIANGEN DP336 genomic-DNA extraction kits (TIANGEN Biotech [Beijing] Co. Ltd., Beijing, China) and quantified with a Qubit 2.0 Fluorometer (Invitrogen, Carlsbad, California, US) to generate amplicons (400–450 bp) using a MetaVx Library Preparation Kit (Genewiz, South Plainfield, New Jersey, US). For each 40 ng sample of DNA, V3, V4, and V5 hypervariable regions of prokaryotic 16S ribosomal RNA (rRNA) were selected for generating amplicons, following taxonomic analysis. Genewiz has designed a panel of proprietary primers aimed at relatively 64

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Table 3 Effects of yeast culture (YC) supplementation and the ratio of dietary non-structural carbohydrate: fat on ruminal volatile fatty acids (VFAs) concentration (mmol/L) and the ratio of acetic acid to propionic acid (A/P). Item

Treatments 1

Hh

Acetic acid 0h 24.8b 2h 58.2d 4h 45.3bc 6h 38.4c 8h 31.0b 12 h 23.1a Propionic acid 0h 9.9a 2h 24.4cd 4h 19.8bc 6h 19.1cd 8h 15.5ab 12 h 11.4a Butyric acid 0h 6.05ab 2h 14.47d 4h 11.33b 6h 10.00abc 8h 7.80a 12 h 5.28a TVFA 0h 41.2b 2h 97.0d 4h 76.4ab 6h 67.6b 8h 54.4b 12 h 39.8a A/P ratio 0h 2.56bc 2h 2.57c 4h 2.58b 6h 2.25 8h 2.13 12 h 1.97ab

SEM Hl

Hc

Lh

Ll

Lc

19.6a 54.2c 47.0c 31.7a 25.5a 26.9b

17.8a 45.0ab 43.9b 38.4c 33.1b 28.6bc

25.4b 47.6b 39.3a 37.1bc 33.8b 23.3a

24.8b 42.7a 40.3a 33.7ab 34.8b 30.4c

25.7b 44.5ab 44.2bc 40.6c 31.5b 28.7bc

8.9a 22.2bc 20.4bc 15.1ab 12.9a 13.8abc

9.4a 20.9b 19.1ab 17.8bc 16.3c 14.3c

12.7b 24.9d 19.8bc 20.4cd 18.2c 11.6ab

9.8b 18.5a 16.9a 14.7a 15.4ab 13.1abc

5.50a 13.13cd 12.02b 8.63a 7.10a 6.71bc

4.85a 10.80ab 11.84b 11.14c 9.25b 7.95cd

5.65ab 11.02ab 9.49a 9.85abc 7.96a 4.81a

34.1a 89.5c 79.6b 55.4a 45.5a 47.4b

31.9a 76.7ab 74.9ab 67.3b 58.7b 50.8b

2.36abc 2.49c 2.45ab 2.23 2.14 2.09ab

2.24ab 2.17abc 2.45ab 2.26 2.14 2.16ab

p-Value Diets

YC

Time

D × YC

0.72 1.51 0.94 1.20 1.35 1.06

0.66

0.13

< 0.01

< 0.05

12.7b 24.7cd 22.0c 21.3d 17.4c 14.1bc

0.54 0.84 0.69 0.75 0.95 0.80

< 0.05

< 0.01

< 0.01

< 0.05

6.77b 12.03bc 11.99b 10.12bc 9.42b 9.07d

5.97ab 9.73a 10.08a 9.48ab 7.34a 5.85ab

0.38 0.48 0.36 0.46 0.32 0.43

0.07

< 0.05

< 0.01

< 0.01

43.8b 85.2c 68.8a 67.3b 60.0b 39.8a

41.4b 73.2a 69.1a 58.5a 59.5b 52.7b

44.4b 80.4b 78.6b 71.4b 56.3b 48.7b

2.00 1.66 2.52 1.60 2.03 2.02

0.63

< 0.05

< 0.01

0.11

2.10a 1.97ab 2.05a 1.86 1.92 2.08ab

2.62c 2.32bc 2.38ab 2.29 2.35 2.35b

2.09a 1.86a 2.07a 1.99 1.91 2.06a

0.12 0.13 0.15 0.18 0.16 0.10

< 0.05

< 0.05

< 0.01

0.05

a,b,c,d

Means in the same row with different superscripts are significantly different (p < 0.05). Hh: Diet of high ratio of non-structural carbohydrate to fat with high-dose of yeast culture; Hl: Diet of high ratio of non-structural carbohydrate to fat with low-dose of yeast culture; Hc: Diet of high ratio of non-structural carbohydrate to fat without YC; Lh: Diet of low ratio of non-structural carbohydrate to fat with high-dose YC; Ll: Diet of low ratio of non-structural carbohydrate to fat with low-dose YC; Lc: Diet of low ratio of nonstructural carbohydrate to fat without YC. 1

conserved regions bordering the V3, V4, and V5 hypervariable regions of bacteria and Archaea16S rDNA (if eukaryotic DNA was contaminated, only the V3 and V4 regions were amplified). V3 and V4 regions were amplified using forward primers containing the sequence CCTACGGRRBGCASCAGKVRVGAAT and reverse primers containing the sequence GGACTACNVGGGTWTCTAATCC, the V4 and V5 regions were amplified using forward primers containing the sequence GTGYCAGCMGCCGCGGTAA and reverse primers containing the sequence CTTGTGCGGKCCCCCGYCAATTC. First-round PCR products were used as templates for second-round amplicon enrichment PCR. At the same time, indexed adapters were added to the ends of the 16S rDNA amplicons to generate indexed libraries ready for downstream NGS on the Illumina MiSeq per Quast et al. (2013). DNA libraries were validated using an Agilent 2100 Bioanalyzer (Agilent Technologies), quantified by Qubit 2.0 Fluorometer (Invitrogen), multiplexed and loaded onto the Illumina MiSeq as per manufacturer’s instructions. NGS was performed using a 2 × 300 paired-end (PE) configuration (Li et al., 2017a, 2017b) and image analysis was conducted and base calling with the MiSeq Control Software (MCS) embedded in the MiSeq instrument (Yilmaz et al., 2014). The amplicon sequence data was deposited with the National Center for Biotechnology Information (Accession Nos. SRR2579284 and ERS2011824). 2.4. Sequence analysis Quantitative Insights Into Microbial Ecology (QIIME) data analysis software was used to analyse 16S rRNA data (Caporaso et al., 2010). Quality filtering was performed on raw sequences as per Bokulich et al. (2013), as well as on joined sequences. Any sequence that did not fulfill the criteria of sequence length < 200 bp, no ambiguous bases and mean quality score ≥ 20 was discarded. The forward and reverse reads were joined and assigned to samples based on barcode and truncated by cutting off the barcode and 65

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Table 4 Effects of yeast culture (YC) supplementation on alpha diversity of ruminal bacterial communities in sheep fed the diets with different NSCFR. Item

ACE 0 2 4 6 12 Chao1 0 2 4 6 12 Shannon 0 2 4 6 12 Simpson 0 2 4 6 12

Treatments

SEM

Hh1

Hl

Hc

Lh

Ll

Lc

756a 711a 860b 779a 889b

848b 764b 739a 819a 751a

892b 830c 881b 918b 946c

1071d 994e 992c 1069c 989cd

990c 1029e 984c 947b 1001d

867b 883d 904b 927b 880b

749a 721a 869b 788a 909bc

850b 766a 752a 827a 759a

890b 847b 869b 943b 954c

1082c 1006d 994c 1087c 1015d

999c 1038d 1003c 957b 1014d

5.94a 5.37a 5.96a 5.35a 6.40ab

6.12ab 5.91b 5.68a 5.29a 5.40a

6.23ab 6.12b 6.20ab 6.37b 6.58bcd

7.35bc 7.00c 6.74bc 7.21c 6.99d

0.95ab 0.90a 0.94a 0.90a 0.96ab

0.95ab 0.95ab 0.93a 0.91ab 0.92a

0.95ab 0.94ab 0.95ab 0.96bc 0.96ab

0.98b 0.97c 0.96ab 0.96bc 0.97b

p-Value Diets

YC

Time

D×YC

19.2 20.4 16.9 17.3 15.7

< 0.01

0.32

< 0.05

< 0.01

882b 909c 910b 938b 893b

21.4 21.1 16.3 17.9 16.3

< 0.01

0.38

< 0.01

< 0.01

6.81c 7.13c 7.05c 6.64b 6.80cd

6.12a 6.92c 6.91c 6.75b 6.19b

0.13 0.13 0.12 0.13 0.10

0.26

< 0.01

0.56

< 0.01

0.94b 0.98c 0.98b 0.98c 0.97b

0.87a 0.97c 0.98b 0.97c 0.93ab

0.01 0.01 0.01 0.01 0.01

< 0.01

0.81

0.62

0.07

a,b,c,d,e

Means in the same row with different superscripts are significantly different (p < 0.05). Hh: Diet of high ratio of non-structural carbohydrate to fat with high-dose of yeast culture; Hl: Diet of high ratio of non-structural carbohydrate to fat with low-dose of yeast culture; Hc: Diet of high ratio of non-structural carbohydrate to fat without YC; Lh: Diet of low ratio of non-structural carbohydrate to fat with high-dose YC; Ll: Diet of low ratio of non-structural carbohydrate to fat with low-dose YC; Lc: Diet of low ratio of nonstructural carbohydrate to fat without YC. 1

primer sequence. The obtained sequences where compared with the reference database (Ribosomal Database Project [RDP] Gold database) using the UCHIME algorithm (Edgar et al., 2011) to detect chimeric sequences, the chimeric sequences were removed. The effective sequences were used in the final analysis. Sequences were grouped into operational taxonomic units (OTUs) and preclustered at 97% sequence identity using the clustering program VSEARCH version 1.9.6 (Rognes et al., 2016) against the SILVA 119 database. The RDP classifier was used to assign taxonomic categories to all of the OTUs at a confidence threshold of 0.8, as per Crawford et al. (2009). The RDP classifier uses the SILVA 119 database, which has taxonomic categories predicted to the species level. Sequences were rarefied prior to calculation of alpha and beta diversity statistics. Alpha diversity indices were calculated in QIIME from rarefied samples using the Shannon index for diversity and the Chao1 index for richness (Chao, 1984; Chao and Lee, 1992). Beta diversity was calculated using weighted and unweighted UniFrac and principal-component analysis (PCA; Hamady et al., 2010). Unweighted Pair Group Method with Arithmetic mean (UPGMA) tree from beta diversity distance matrix was built. 2.5. Statistical analysis Based on the beta diversity distance matrix and on environmental-factor data, the canonical correspondence analysis (CCA) between RFPs and BCC were integrated by the R-language software application (R Core Team, 2018). All data was analysed by 2-way (YC and diet) analysis of variance (ANOVA) using the General Linear Model Repeated Measure of SAS software version 9.3 (SAS Institute Inc., Cary, North Carolina, US). Duncan contrasts were used to test the significance level for the effects of diet compositions, YC supplementation, and their interactions (diet × YC), with p < 0.05 indicating a significant difference. 3. Results 3.1. Rumen fermentation parameters The effects of YC supplementation and dietary NSCFR on RFPs are presented in Tables 2 and 3. NH3-N was affected by diet (p < 0.01), YC (p < 0.01), and their interaction (diet × YC; p < 0.05; Table 2). The concentrations of NH3-N were higher (p < 0.05) in H groups (0.8 and 2.3 g/kg YC) than that in L groups (Table 2). Ruminal pH was affected by diet (p < 0.01), and it was significantly lower in H diet supplemented with YC (0.8 and 2.3 g/kg) than in L diet at 2 h after feeding (p < 0.05; Table 2). Acetic acid was only affected by diet × YC interaction (p < 0.05; Table 3). Propionic acid and the ratio of acetic to propionic acid (A/P ratio) were affected by all factors (p ≤ 0.05; Table 3). Butyric acid was affected by both YC (p < 0.05) and diet×YC interaction (p < 0.01; Table 3). In 66

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Table 5 Composition of ruminal bacterial communities at phylum level (%). Phylum

Treatments Hh1

Bacteroidetes 0h 40.7a 2h 37.2a 4h 37.5ab 6h 32.2a 12 h 44.4a Firmicutes 0h 46.7c 2h 48.4b 4h 54.4c 6h 41.3cd 12 h 39.6bc Saccharibacteria 0h 6.37d 2h 4.25b 4h 6.04c 6h 3.02c 12 h 2.14b Actinobacteria 0h 3.77c 2h 3.29b 4h 12.73b 6h 8.55b 12 h 3.21b Proteobacteria 0h 0.75a 2h 0.72a 4h 0.77a 6h 0.57a 12 h 1.53bc Synergistetes 0h 0.43 2h 0.50a 4h 0.26a 6h 0.35a 12 h 0.51a

SEM Hl

Hc

Lh

Ll

Lc

49.4b 37.6a 32.9ab 41.3ab 56.1bc

52.5b 35.1a 45.4c 41.8ab 57.4bc

64.3c 52.2b 58.6d 57.6c 61.0c

52.5b 35.3a 38.6ab 52.5bc 50.7ab

53.8b 38.0a 28.7a 41.0ab 48.0ab

40.8b 50.8b 43.1ab 47.5de 35.6ab

35.8b 45.6b 36.2a 29.9a 33.0ab

27.6a 34.3a 34.6a 31.9ab 29.8a

38.1b 48.3b 35.9a 38.9bc 35.3a

2.28b 4.17b 4.29b 0.65a 2.63b

1.36a 3.20ab 5.69bc 3.75d 0.77a

0.96a 2.13a 2.26a 1.52b 1.42ab

4.20c 8.07c 11.63b 12.50c 3.84b

2.96b 13.57d 13.56b 11.92c 8.76c

2.16c 2.66b 1.87b 0.94a 1.17b 0.66 0.66ab 0.47ab 0.38ab 0.29a

p-Value Diets

YC

Time

D × YC

1.54 1.62 2.25 2.09 1.52

< 0.01

0.12

< 0.01

< 0.01

38.4b 49.7b 48.2bc 53.2e 44.7c

1.23 1.47 1.72 1.64 1.25

0.07

0.06

< 0.01

< 0.01

3.77c 8.06c 14.3d 5.55e 8.46d

4.05c 8.80c 14.4d 7.7e 4.05c

0.31 0.45 0.83 0.41 0.44

< 0.01

< 0.01

< 0.01

< 0.01

0.79a 1.18a 1.30a 1.80a 0.58a

0.57a 0.61a 0.81a 0.79a 0.34a

0.50a 0.26a 0.42a 0.36a 0.35a

0.27 0.84 1.05 0.89 0.52

< 0.01

< 0.01

< 0.01

< 0.01

2.62d 4.41c 2.64c 3.24c 1.89c

2.16c 3.15b 3.70d 2.14b 3.85d

1.23b 2.81b 2.97c 1.67b 0.47a

0.63a 1.02a 1.44b 0.81a 0.76a

0.14 0.22 0.18 0.18 0.19

0.64

0.26

< 0.01

< 0.01

0.73 0.91b 0.83c 0.31a 0.25a

0.54 1.86d 1.15d 0.52b 0.42a

0.59 1.49c 0.67bc 1.03c 1.86b

0.17 0.68ab 0.66bc 0.36ab 0.31a

0.04 0.09 0.06 0.05 0.10

< 0.01

< 0.01

< 0.01

< 0.01

a,b,c,d,e

Means in the same row with different superscripts are significantly different (p < 0.05). Hh: Diet of high ratio of non-structural carbohydrate to fat with high-dose of yeast culture; Hl: Diet of high ratio of non-structural carbohydrate to fat with low-dose of yeast culture; Hc: Diet of high ratio of non-structural carbohydrate to fat without YC; Lh: Diet of low ratio of non-structural carbohydrate to fat with high-dose YC; Ll: Diet of low ratio of non-structural carbohydrate to fat with low-dose YC; Lc: Diet of low ratio of nonstructural carbohydrate to fat without YC. 1

addition, the concentration of TVFA was only affected by YC (p < 0.05; Table 3). H group supplemented with YC (2.3 g/kg) had a significant (p < 0.05) increase in the concentrations of acetic acid, butyric acid and TVFA compared with L group at 2 h after feeding (Table 3). 3.2. Ruminal-bacterial diversity and community structure 3.2.1. DNA sequencing In this study, all ruminal-liquid samples (n = 180) produced 32,896,250 original sequences. After sequence cleanup, 16,448,125 total high-quality bacterial sequences (average 91,378 sequences per sample) were obtained. The rarefaction curve showed that the patterns of bacterial diversity appeared to be sufficient to estimate BCC (Fig. S1). 3.2.2. Alpha diversity Table 4 showed that indices of ACE and Chao1 were significantly affected by diet and diet × YC interaction (p < 0.01), while Shannon index was affected by YC and diet × YC interaction (p < 0.01). All these three indices were lower in H diet than in L diet (p < 0.05). Simpson was only significantly affected by diet (p < 0.01). 3.2.3. Bacterial-community composition The BCC was affected by diet × YC interaction at the phylum level (p < 0.01; Table 5). A diet effect was observed on Bacteroidetes, while both diet and YC had effects on Saccharibacteria, Actinobacteria and Synergistetes (p < 0.01; Table 5). Bacteroidetes, Firmicutes, 67

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Fig. 1. Percentage relative abundance of bacterial phyla. Hh: Diet of high ratio of non-structural carbohydrate to fat with high-dose of yeast culture; Hl: Diet of high ratio of non-structural carbohydrate to fat with low-dose of yeast culture; Hc: Diet of high ratio of non-structural carbohydrate to fat without YC; Lh: Diet of low ratio of non-structural carbohydrate to fat with high-dose YC; Ll: Diet of low ratio of non-structural carbohydrate to fat with low-dose YC; Lc: Diet of low ratio of non-structural carbohydrate to fat without YC. “Unclassified” refers to sequences that could not be assigned to phylum level.

and Saccharibacteria were the prominent phyla in all groups, and Actinobacteria was distinguished as a prominent phylum in H diet (Table 5; Fig.1). The relative abundance of Bacteroidetes was also affected by diet (p < 0.05; Table 5). In addition, Saccharibacteria and Actinobacteria were affected by both diet and YC (p < 0.01; Table 5). The BCC at the genus level was affected by all factors (p < 0.01) except for Ruminococcus_1 (diet, p = 0.49) and Succiniclasticum (diet, p = 0.76; Table 6). Prominent genus of all groups were Prevotella_1, Ruminococcus_2, Ruminococcaceae_UCG-014, Ruminococcus_1, Rikenellaceae_RC9, Candidatus_ Saccharimonas, and Christensenellaceae_R-7 (Table 6; Fig.2). Meanwhile the relative abundances of Prevotella_1 were significantly higher in L groups than in H groups (p < 0.05). H diet with YC supplementation (2.3 g/kg) increased the relative abundance of Candidatus_Saccharimonas compared with L diet. [Eubacterium]_coprostanoligenes, Lachnospiraceae_NK3A20, Pseudoscardovia, Olsenella and [Ruminococcus]_gauvreauii were the dominant genera in the H groups, while Saccharofermentans was the dominant genus in the L groups (Table 6; Fig.2). Especially, the relative abundances of Olsenella and Lachnospiraceae_NK3A20 were increased in H groups compared with L groups (p < 0.05). H diet with YC supplementation (0.8 and 2.3 g/kg) increased the relative abundance of [Ruminococcus]_gauvreauii (p < 0.05), whereas Butyrivibrio_2 was increased in L diet (2.3 g/kg YC). 3.2.4. Beta diversity Patterns of variation in BCC were observed over time among the different diets and YC levels using PCA (Fig. 3). PCA plots between groups at each periods showed that bacterial clusters in the H and L groups receiving YC treatment were distinct from those in their respective control groups at 2 and 4 h, respectively, after morning feeding. Meanwhile, there were many overlaps in ruminal BCC between all groups at 0, 6 and 12 h. 3.2.5. Correlations of ruminal BCC with RFPs by canonical correspondence analysis (CCA) The arrows demonstrate the lengths and angles between explanatory and response variables and reflect their degrees of correlation. Samples from different treatment groups are labeled with different colors and shapes (Fig. 4). When the angle between 2 environmental factors was acute, there was a positive correlation between these factors; an obtuse angle indicated a negative 68

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Table 6 Composition of ruminal bacterial communities at genus level in each group (%). Genus

Treatments Hh1

SEM Hl

Prevotella _1 0h 17.8b 11.0a 9.26b 2h 12.2b 4h 8.79a 8.94a 6h 6.18a 11.2b 12h 17.7c 8.32a Ruminococcus_2 0h 15.1d 2.81a 2h 23.6c 2.71a 3.44b 4h 10.6c 6h 24.6d 3.29a 12h 5.21c 1.78a Ruminococcaceae_UCG-014 0h 2.43c 1.43b 2h 1.24a 1.24a 4h 2.57a 1.81a 6h 1.95b 2.20b 12h 2.80c 1.57b Ruminococcus_1 0h 2.51a 6.76c 2h 3.01a 11.9d 4h 1.80a 9.09c 6h 2.41a 3.84b 12h 2.98a 4.63b [Eubacterium]_coprostanoligenes 0h 3.31c 1.09b 2h 1.73c 1.52c 4h 1.99d 2.61e 6h 1.90d 1.52c 12h 0.82a 0.88a Rikenellaceae_RC9 0h 8.69a 10.20a 2h 5.07a 4.42a 4h 5.92a 5.01a 6h 5.07a 16.5c 12h 9.8b 13.7c Candidatus_Saccharimonas 0h 7.19d 2.28b 2h 4.59b 4.00b 4h 6.04b 5.62b 6h 3.02b 3.75b 12h 1.97b 2.63b Christensenellaceae_R-7 0h 1.60b 0.87a 2h 1.27b 0.85a 4h 1.40b 1.01a 6h 0.85a 0.58a 12h 1.95d 0.50a Lachnospiraceae_NK3A20 0h 1.34c 2.35d 2h 1.33c 4.06e 4h 3.49c 3.29c 6h 3.62d 4.06d 12h 1.71b 0.56b Pseudoscardovia 0h 1.45c 0.98b 2h 1.89c 0.46a 4h 2.56b 3.02c 6h 2.10b 3.93c 12h 1.08c 0.58b Olsenella 0h 2.47c 1.59b 2h 5.23c 2.22b 4h 9.48c 7.73b 6h 7.43d 6.17c 12h 2.00b 2.84c

Hc

Lh

Ll

Lc

9.23a 4.43a 10.1a 14.4b 12.5b

37.0d 26.0d 33.3c 29.5d 32.9e

25.0c 11.0b 14.3b 28.5d 25.7d

25.9c 15.2c 14.5b 24.4c 23.8d

5.51c 8.79b 1.38a 5.91b 3.49b

3.53b 4.07a 3.42b 8.61c 4.94c

3.70b 2.84a 1.26a 2.83a 2.99a

0.65a 0.78a 1.74a 0.73a 0.71a

1.29b 2.76b 3.17b 3.05c 1.39b

3.93b 5.10b 3.73b 4.25c 5.71c

p-Value Diets

YC

Time

D×YC

1.74 1.25 1.54 1.58 1.62

< 0.01

< 0.01

< 0.01

< 0.01

1.52a 2.69a 3.53b 7.13b 8.64d

0.84 1.50 0.55 1.28 0.41

< 0.01

< 0.01

< 0.01

< 0.01

1.50b 4.30c 7.33c 4.76d 4.17d

3.97d 3.69c 8.15c 6.58e 2.68c

0.19 0.24 0.46 0.35 0.29

< 0.01

< 0.01

< 0.05

< 0.01

2.21a 4.00a 4.57b 3.13a 4.09a

2.62a 5.32b 4.78b 3.38a 3.90a

3.77b 9.95c 10.4c 6.20d 5.22b

0.29 0.57 0.54 0.24 0.22

0.49

< 0.01

< 0.01

< 0.01

1.14b 1.58c 1.58c 1.34b 1.22b

0.55a 0.56a 0.77a 0.78a 0.57a

1.10b 1.48c 1.13b 1.07a 0.81a

0.67a 0.83b 1.35b 1.32b 0.86a

0.16 0.08 0.11 0.08 0.05

< 0.01

< 0.05

< 0.01

< 0.01

22.3c 12.2c 20.5c 15.2c 15.6c

13.5b 9.54b 8.04b 8.06b 10.3b

13.6b 12.0c 8.67b 10.4b 10.54b

9.43a 8.61b 4.47a 4.79a 5.54a

0.87 0.58 0.96 0.86 0.65

< 0.01

< 0.01

< 0.01

< 0.01

1.36a 3.54a 4.29b 0.65a 0.68a

0.96a 2.26a 2.26a 1.51a 1.42a

3.77c 7.06c 12.3c 5.72c 8.46d

4.05c 8.80c 13.2c 7.69d 4.05c

0.37 0.45 0.83 0.42 0.46

< 0.01

< 0.01

< 0.01

< 0.01

0.68a 1.99c 1.83c 2.31d 1.25b

1.81b 1.83c 1.24a 1.66c 1.58c

2.05c 1.43b 1.83c 1.15a 0.97b

1.61b 1.95c 1.50b 1.67c 1.68d

0.10 0.08 0.07 0.11 0.10

< 0.01

< 0.01

< 0.05

< 0.01

0.90b 2.55d 2.82b 2.31c 2.15c

0.21a 0.58b 0.34b 0.76b 0.20a

0.27a 0.31a 0.33a 0.28a 0.13a

0.13a 0.17a 0.10a 0.15a 0.11a

0.14 0.24 0.26 0.27 0.14

< 0.01

< 0.01

< 0.01

< 0.01

0.80b 0.51b 3.95d 3.64c 2.22a

0.08a 0.03a 0.10a 0.57a 0.11a

0.03a 0.05a 0.07a 0.09a 0.02a

0.04a 0.01a 0.06a 0.03a 0.03a

0.10 0.13 0.28 0.28 0.14

< 0.01

0.06

< 0.01

< 0.05

2.53c 8.67d 7.51b 6.71c 5.38d

0.36a 0.19a 0.56a 1.09b 0.32a

0.43a 0.21a 0.81a 0.49a 0.18a

0.35a 0.12a 0.23a 0.23a 0.19a

0.43 1.43 1.75 1.39 0.84

< 0.01

< 0.01

< 0.01

< 0.01

(continued on next page) 69

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Table 6 (continued) Genus

Treatments Hh1

SEM Hl

Succiniclasticum 0h 0.34a 1.43d 2h 0.29a 1.05b 4h 0.29a 1.31d 6h 0.47b 1.16c 12h 0.76c 0.65b Pseudobutyrivibrio 0h 0.12a 0.17b 2h 0.13a 0.22b 0.18a 4h 0.19a 6h 0.11a 0.08a 12h 0.16a 0.21a Saccharofermentans 0h 0.48a 0.66b 2h 0.36a 0.41a 4h 1.05b 0.51a 6h 0.35b 0.09a 12h 1.20c 0.25a [Ruminococcus]_gauvreauii 0h 2.14c 1.09b 2h 1.49d 0.85c 4h 2.53c 1.80b 6h 3.64d 2.06c 12h 1.76c 1.49c Butyrivibrio_2 0h 0.05a 0.15a 2h 0.05a 0.07a 4h 0.07a 0.05a 6h 0.07a 0.08a 12h 0.09a 0.32a

p-Value

Hc

Lh

Ll

Lc

Diets

YC

Time

0.14a 0.35a 0.24a 0.18a 0.69b

1.06c 1.11b 0.89c 0.49b 0.82c

0.33a 0.46a 0.16a 0.41b 0.35a

0.74a 1.03b 0.46b 0.32a 0.51a

0.10 0.07 0.08 0.06 0.04

0.76

< 0.01

< 0.05

< 0.01

0.06a 0.21b 0.39b 0.31b 0.52b

0.88d 0.75e 0.74c 0.59c 0.80c

1.12e 0.48d 1.13d 2.31a 1.64d

0.58c 0.35c 0.34b 0.42b 0.61a

0.07 0.04 0.06 0.13 0.09

< 0.01

< 0.01

< 0.01

< 0.01

0.24a 0.84b 0.94b 0.76c 0.88b

1.54c 1.52c 1.17b 0.99d 1.12c

4.87d 2.88d 2.65d 2.18e 3.35e

0.77b 1.29c 1.36c 1.30e 1.35d

0.27 0.15 0.12 0.12 0.16

< 0.01

< 0.01

< 0.01

< 0.01

0.35a 0.65b 0.38a 0.72b 0.90b

0.29a 0.44a 0.43a 0.59b 0.30a

0.27a 0.33a 0.40a 0.30a 0.12a

0.26a 0.21a 0.15a 0.14a 0.23a

0.12 0.08 0.15 0.23 0.12

< 0.01

< 0.01

0.21a 0.17a 0.18a 0.21a 0.46b

1.63c 0.64c 0.48c 1.42c 1.34c

0.61b 0.29b 0.20b 0.51b 0.35a

0.27a 0.28b 0.11a 0.14a 0.31a

0.10 0.04 0.03 0.09 0.08

< 0.01

< 0.01

< 0.01

< 0.01

D×YC

< 0.01

< 0.01

a,b,c,d,e

Means in the same row with different superscripts are significantly different (p < 0.05). Hh: Diet of high ratio of non-structural carbohydrate to fat with high-dose of yeast culture; Hl: Diet of high ratio of non-structural carbohydrate to fat with low-dose of yeast culture; Hc: Diet of high ratio of non-structural carbohydrate to fat without YC; Lh: Diet of low ratio of non-structural carbohydrate to fat with high-dose YC; Ll: Diet of low ratio of non-structural carbohydrate to fat with low-dose YC; Lc: Diet of low ratio of nonstructural carbohydrate to fat without YC. 1

correlation. The H groups are distinct from the L groups in the CCA plot (Fig. 4). The results indicated that BCC in Hh group was positively associated with VFAs, NH3-N, and A/P ratio but negatively associated with ruminal-liquid pH value. There was a large overlap in clustering among the Lc, Ll and Lh groups. The functions of ruminal microorganisms in the L groups were negatively correlated with VFAs, NH3-N and A/P but positively correlated with ruminal pH value. Weak relationships were observed between BCC and RFPs. A positive correlation was observed between ruminal NH3-N concentration and the relative abundance of Prevotella_1 (Fig. S2). Ruminal pH values were negatively correlated with Candidatus_Saccharimonas (Fig. S3) and Olsenella (Fig. S4) but positively correlated with Rikenellaceae_RC9 (Fig. S5). 4. Discussion 4.1. Ruminal fermentation Ruminal pH, NH3-N, and VFAs are important indicators of ruminal function and the stability of the ruminal microecosystem (Li et al., 2017a, 2017b). Different responses of ruminal fermentation resulting from feeding animals different substrates can be attributed to different responses of ruminal BCC (Golder et al., 2012). In the current study, the levels of propionic acid and total VFA in different doses of supplemental YC corresponded with the findings of Dias et al. (2017), whose study was conducted with high-starch and low-starch diets in dairy cow. Additionally, Soren et al. (2013) observed a decrease in ruminal pH and an increase in NH3-N concentration with YC supplementation on lambs fed high-grain diet. Such ruminal pH results are in accordance with those for the Hh and Hl groups in our study at 2 h after feeding. Thrune et al. (2009) reported that YC supplementation increased ruminal pH but decreased total VFA in a low-starch diet (16% corn). These results were in accordance with those for the Ll group at 2 and 4 h after feeding in our study. This could be related to the interaction between YC and diet composition. Despite rumen pH values in the H groups were decreased to 5.49 at 2 h after feeding, that values recovered to the level that stay away from the risk of subacute ruminal acidosis (Krause and Combs, 2003) after 4 h. These results indicated that experimental diets supplemented with YC had no deleterious effect on the ability of the rumen to regulate itself (AlZahal et al., 2007; Kleen et al., 2003). A similar trend for NH3-N concentration was observed in both diet treatment groups, which was higher than in their respective control group at 2 and 4 h post70

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Fig. 2. Percentage relative abundance of bacterial genus. Hh: Diet of high ratio of non-structural carbohydrate to fat with high-dose of yeast culture; Hl: Diet of high ratio of non-structural carbohydrate to fat with low-dose of yeast culture; Hc: Diet of high ratio of non-structural carbohydrate to fat without YC; Lh: Diet of low ratio of non-structural carbohydrate to fat with high-dose YC; Ll: Diet of low ratio of non-structural carbohydrate to fat with low-dose YC; Lc: Diet of low ratio of non-structural carbohydrate to fat without YC. “Unclassified” refers to sequences that could not be assigned to genus level.

feeding but lower after 4 h. Such results may be ascribed to the functions of YC, which can stimulate the growth of protein-degrading bacteria and increase the activities of NH3-N utilization bacteria (Vohra et al., 2016). In the herein study, the concentrations of ruminal NH3-N, acetic, propionic, and butyric acids were affected by the diet × YC interaction. The effects of YC supplementation were closely depended on diet compositions. The concentrations of VFAs in ruminal ingesta were increased with the increasing of YC supplementation level when the animals fed on the H diet compared with that on the L diet. However, the influences of the YC supplementation on NH3-N level were more evident in the animals fed on L diet than that fed on high NSCFR diet. Probably, this results were related to those interaction effects on fiber-degrading bacteria (Hu et al., 2004), proteolytic bacteria(Reilly et al., 2002), and amylolytic bacteria (Therion et al., 1982).

4.2. Ruminal bacterial-community composition The rumen is colonized by several facultative anaerobic-bacterial communities (Vohra et al., 2016), which play important roles in fermenting and digesting nutrients to provide energy and protein resources (Vymazal and Kröpfelová, 2013), maintaining major biological activities, and promoting growth and performances (Morgavi et al., 2015). Moreover, these bacterial communities are living in a dynamic environment that can be affected by many other factors, such as diurnal variations, diet structure, and feed additives (Guan et al., 2008; Menezes et al., 2011). Therefore, we objectively estimated the effects of dietary NSCFR and YC supplementation on BCC by logging the data at bi-hourly intervals after the morning feeding. The present results indicated that compositional differences existed among the BCCs in H and L groups receiving YC treatment when ruminal-metabolism activity was vigorous. Previous studies have demonstrated that greater populations of ruminal microorganisms can improve resistance to external stress, stabilize the ruminal microecosystem, and enhance production performance (McCann, 2000; Cani and Delzenne, 2009). In the current study, indices of BCC alpha diversity decreased as the pH decreased, which could be attributed to some gram-negative bacteria decreasing in a low-pH environment (Khafipour et al., 2009). This result is in contrast to that of Jiang et al. (2016), who found that alpha diversity was not affected by YC supplementation. The difference was likely related to the different combinations of 71

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Fig. 3. Principal component analysis (PCA) plots of ruminal bacterial-community composition at (A) 0 h (B) 2 h (C) 4 h (D) 6 h (E) 12 h after morning feeding of sheep fed the diets with different energy structures supplemented with yeast culture. Hh: Diet of high ratio of non-structural carbohydrate to fat with high-dose of yeast culture; Hl: Diet of high ratio of non-structural carbohydrate to fat with low-dose of yeast culture; Hc: Diet of high ratio of non-structural carbohydrate to fat without YC; Lh: Diet of low ratio of non-structural carbohydrate to fat with high-dose YC; Ll: Diet of low ratio of non-structural carbohydrate to fat with low-dose YC; Lc: Diet of low ratio of non-structural carbohydrate to fat without YC. Each point represents different samples plotted on a 2-dimensional graph according to their OTU composition and abundance. A greater distance between 2 points implies a lower similarity between them, whereas samples with a more similar bacterial composition and abundance are clustered closer together.

YC levels and dietary compositions. In the current study, Bacteroidetes (H groups, 32.2%-57.4%; L groups, 28.7%-61.0%) and Firmicutes (H groups, 29.9%-54.4%; L groups, 27.6%-53.2%) were the most abundant phyla in all groups. It is well known that dietary composition is the most important factor that can affect BCC (Liu et al., 2013; Mullins et al., 2013; Golder et al., 2014; Mao et al., 2015). Similarly, Li et al. (2017a); (2017b) found that Bacteroidetes (43.58%) and Firmicutes (41.97%) were respectively the most dominant and second dominant in lambs fed a high-starch diet. Furthermore, Mao et al. (2015) observed lower relative abundance of Bacteroidetes and higher relative

72

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Fig. 4. Ordination plots by the canonical correspondence analysis (CCA) used to explore the relationships between the ruminal bacterial-community composition (BCC) and ruminal fermentation parameters. Hh: Diet of high ratio of non-structural carbohydrate to fat with high-dose of yeast culture; Hl: Diet of high ratio of non-structural carbohydrate to fat with low-dose of yeast culture; Hc: Diet of high ratio of non-structural carbohydrate to fat without YC; Lh: Diet of low ratio of non-structural carbohydrate to fat with high-dose YC; Ll: Diet of low ratio of non-structural carbohydrate to fat with low-dose YC; Lc: Diet of low ratio of non-structural carbohydrate to fat without YC.

abundance of Firmicutes as dietary grain level increased. This also might be attributed to different pH levels caused by different diets. In ruminants, Prevotella is the genus of phylum Bacteroidetes with the highest relative abundance (Huo et al., 2014). Prevotella can secrete the enzyme xylanase, which aids polysaccharide degradation (Krause et al., 2003). Some species of Prevotella participate in the utilization processes of fiber, hemicellulose, pectin, and protein (Matsui, 2010; Koike and Kobayashi, 2001). Mao et al. (2015) suggested that low pH in the ruminal environment caused by subacute ruminal acidosis reduces Prevotella’s relative abundance. Similarly, our data showed that relative abundance of Prevotella_1 had a weak negative correlation with NH3-N concentration and a positive correlation with YC supplementation. This may be due to the abundant nutrients in YC (e.g., lactose and glycine), which can be used by Prevotella_1 and other gram-negative bacteria (Shah and Collins, 1990), thus improving utilization of nitrogenous substances in the rumen and subsequently promoting protein synthesis. A weak positive correlation was observed between Rikenellaceae_RC9 and pH value, but only few recent studies of Huang et al. (2018) and Zhang et al. (2018) have mentioned the genus Rikenellaceae_RC9, and the description of its function is not exhaustive. Ruminococcus and Lachnospiraceae belong to phylum Firmicutes, which can use cellulose and hemicellulose as substrates to produce VFAs (Liu et al., 2015). Sun (2018) found that the metabolites of YC containing D-glucose, D-galactose, D-fructose, D-ribose. [Ruminococcus]_gauvreauii can use these metabolites to produce acetic acid (Domingo et al., 2008). Moreover, the low-pH environment caused by the H diet seemed to be more conducive to the growth of [Ruminococcus]_gauvreauii. This may be why the relative abundances of [Ruminococcus]_gauvreauii were increased with YC supplementation in H groups, which further to decrease the pH value. This might explain why pH levels in H groups were much lower than in L groups with YC supplementation. Soren et al. (2013) and Kholif et al. (2017) obtained similar results for high-grain diets. Candidatus_Saccharimonas is the predominant genus in phylum Saccharibacteria (formerly TM7) which can use glucose, oleic acid, amino acid, and butyric acid (Kindaichi et al., 2016). Killer et al. (2013) reported that Pseudoscardovia can activate the limiting enzyme of glycolysis and the end product of glycolysis is lactic acid (Rye and Lamarr, 2015). Kraatz et al. (2011) suggested that Olsenella is the member of Actinobacteria that can use carbohydrate to produce lactic acid (Ricaboni et al., 2017). Saccharofermentans can use hexose, hydrolysis polysaccharides, alcohols, sucrose, and aesculin as fermentative substrates (Chen et al., 2010). Previous studies reported that Christensenellaceae_R-7 can use different sugars to produce acetic acid (Zhang et al., 2016; Han et al., 2017). The end products of the above 5 mentioned genera are acids. The higher relative abundances of Candidatus_Saccharimonas, Pseudoscardovia and Olsenella in H groups may lead to decrease in their pH values.

5. Conclusions In conclusion, the ruminal predominant genera and rumen fermentation were effectively influenced by the interaction of diet composition and YC. Diet composition may play a more important role in terms of modifying ruminal pH values, NH3-N. There was significant interaction between diet composition and YC supplementation in the aspects of VFAs, NH3-N and all genera of BCC. Therefore, the effects of YC supplementation were largely depended on the diet compositions. 73

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Conflict of interest The authors state that they have no conflict of interest. Acknowledgments This study was supportedby the Jilin Province Major Scientific & Technological Achievement Transformation Project (20160301003NY) and Jilin Province Feed Engineering and Technology Research Center (20170623075TC). Appendix A. Supplementary data Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.anifeedsci. 2019.02.003. References Alzahal, O., Kebreab, E., France, J., Mcbride, B.W., 2007. A mathematical approach to predicting biological values from ruminal pH measurements. J. Dairy Sci. 90, 3777–3785. Andrighetto, I., Bailoni, L., Cozzi, G., Berzaghi, P., 1993. Effects of yeast culture addition on digestion in sheep fed a high concentrate diet. Small Rumin. Res. 12, 27–34. AOAC, 1990. Association of Analytical Communities, Official Methods of Analysis. Association of Official Agricultural Chemists (U. S.), Washington, DC. 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