This study was performed at the Key Laboratory for Dairy Cow Nutrition, College of Animal Science and Technology, Beijing University of Agriculture, Beijing, China. The experimental methods were approved by the Animal Care and Use Committee of Beijing University of Agriculture and were in compliance with the Regulations for the Administration of Affairs Concerning Experimental Animals (The State Science and Technology Commission of P. R. China, 1988). The GSPE (90% procyanidins, which are members of the proanthocyanidin class of flavonoids) was purchased from Tianjin Jianfeng Natural Product R&D Co., Ltd. (Tianjin, China).

This experiment was conducted according to a completely randomized design to identify the effects of GSPE on gas production, fermentation patterns and the archaeal community. There were two treatments: the control group (group A, CON, no GSPE adding; n = 9) and the treatment group (group B, GSPE, 1 mg/bottle GSPE, 2 g/kg dry matter [DM]; n = 9). Fresh ruminal fluid was collected from four cannulated lactating Holstein dairy cows (670±24 kg body weight; 114.6±7.5 days in milk) 2 h after the morning feeding, mixed in equal amounts, and poured into a sterilized bottle such that no headspace remained in the bottle. The bottle was brought to the laboratory within 30 min. The ruminal fluid was extruded into the flask through four layers of gauze, and the flask was filled with CO₂ and placed in a 39°C water bath until use. The fresh ruminal fluid was diluted with buffer solution (1:2 v/v), which was prepared as described by [8]. The incubation progress in vitro was operated as we previously described [9]. Briefly, 75 mL of inoculum-buffer mixture was added to each 120-mL serum bottle, which contained 500 mg of mixed diet DM as fermentation substrates. The composition of the mixed diet is shown in Table 1. The GSPE (1±0.1 mg) was measured in advance using analytical balance (ME204, Mettler Toledo, Uster, Switzerland) and dosed into the treatment group serum bottles. All bottles were sealed with crimp-sealed rubber stoppers to prevent gas leakage and connected with vacuumed air bag (Hedetech, Dalian, China), then affixed to a rotary shaker platform (90 rpm) in a temperature-controlled (39°C±0.5°C) incubator (THZ-C, Taichang, Shijiazhuang, China) for 24 h. This experiment was repeated in three batches, and three units per treatment were arranged in each batch.

The total gas production was measured using a 100-mL calibrated glass syringes (Häberle Labortechnik, Lonsee-Ettlenschieß, Ettlenschiess, Germany). Gas samples (5 mL) were used to detect the concentrations of methane and hydrogen by gas chromatography (7890B, Agilent Technologies, Foster City, CA, USA). The productions of methane and hydrogen were calculated from the methane and hydrogen concentration and total gas production according to ideal gas law (pV = nRT). The pH value of each fermentation fluid was measured with a pH meter (SevenGo TM pH meter SG2, Mettler Toledo, Switzerland). VFA analysis was conducted on 1 mL of each fermentation fluid, which was preserved by adding 0.2 mL of 25% H₃PO₄ by gas chromatography (7890B, Agilent Technologies, USA), as reported by Mao et al [10]. All the samples were stored at −80°C until the analyses. The pre-weighted filter bags (ANKOM Technology, Macedon, NY, USA) were used to filter the fermentation fluid of each serum bottle. Then the filter bags were washed with cold running water until the effluent ran clear. At last, the filter bags were dried at 55°C for 48 h for analysis of the DM digestibility.

Microbial DNA extraction was carried out on the rumen samples with cetyltrimethylammonium bromide and bread-beating methods as previously described by Jin et al [11]. DNA quality was determined by 1% agarose gel electrophoresis containing Goldview TM (Saibaisheng, Shanghai, China). The yield and purity of the extracted DNA were assessed with a NanoDrop 1000 instrument (NanoDrop, Wilmington, DE, USA).

The DNA samples were used as templates to quantify the total bacterial abundance, and the abundances of anaerobic fungi, ciliate protozoa, methanogens, Fibrobacter succinogenes, Ruminococcus albus, and Ruminococcus flavefaciens were assessed. All primers and assay conditions used in this study have been previously published [12]. Each reaction involved 3 duplicates amplified using a Step-One Plus real-time polymerase chain reaction (RT-PCR) system (Applied Biosystems, Foster City, CA, USA) with SYBR Premix Ex Taq (Takara, Dalian, China) and were performed according to previously published methods [13]. Changes in the targeted populations were calculated using a relative quantification calculation, and the total bacterial Ct (cycle threshold) value was used as the reference value: target bacterial population (%) = 100× 2^{−(Ct target – Ct total bacterial)}. Changes in microbial communities due to the addition of GSPE are expressed as a percentage change relative to the control population.

The V3-V4 regions of the archaeal 16S rRNA gene were amplified by PCR (95°C for 3 min; followed by 27 cycles at 95°C for 30 s, 55°C for 30 s, 72°C for 45 s; and a final extension at 72°C for 10 min) using the primers 349F (5′-barcode-GYGC ASCAGKCGMGAAW-3′) and 806R (5′-GGACTACVSGG GTATCTAAT-3′) [14], where the barcode is an eight-base sequence that is unique to each sample. The PCRs were performed in triplicate in a 20-μL mixture containing 4 μL of 5× FastPfu buffer, 2 μL of 2.5 mM dNTPs, 0.8 μL of each primer (5 μM), 0.4 μL of FastPfu polymerase, 0.2 μL of bovine serum albumin and 10 ng of the template DNA. Amplicons were excised from 2% agarose gels, purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA) according to the manufacturer’s instructions, and quantified using a QuantiFluor-ST instrument (Promega, Madison, WI, USA). Finally, purified amplicons were pooled in equimolar ratios and subjected to paired-end sequencing (2×300) on an Illumina MiSeq platform according to standard protocols. The raw reads were deposited into the NCBI Sequence Read Archive database (accession number: SRP139902).

Sequencing data processing and analysis followed our previously described procedures [15]. Briefly, the raw FASTQ files were quality filtered using Trimmomatic software and merged using FLASH with the following criteria: i) the reads were truncated at any site that received an average quality score of <20 over a 50-bp sliding window; ii) sequences with overlapping segments longer than 10 bp were merged according to their overlapping sections with a mismatch of no more than 2 bp; iii) the sequences of each sample were separated based on the barcodes (exactly matched) and primers (allowing 2-nucleotide mismatches), and reads containing ambiguous bases were removed. Subsequently, the average length of all the clean reads was 372 bp and the average sequencing depth was 52,281 clean reads for archaeal community analysis. Operational taxonomic units were clustered at 97% sequence identity using UPARSE [16]. The ribosomal database project was used for the taxonomic classification of the sequence. Simpson, Shannon, Chao, and ACE indices were calculated for each sample. LEfSe analysis was carried out using R-3.2 with the vegan package on the online Majorbio I-Sanger Cloud Platform (http://www.i-sanger.com) according to our previously reported methods [15].

Data for gas production, NH₃-N, DM digestibility, microbial crude protein, CH₄, H₂, ruminal pH, VFA concentrations and the alpha diversity index were analyzed using PROC MIXED of SAS 9.4 (SAS Institute, Inc, Cary, NC, USA), as shown in the following model: Y_ijk = μ+T_i+B_j+TB_ij+e_ijk, where Y_ijk is the dependent variable, μ is the overall mean, T_i is the effect of treatment (GSPE or CON, considered fixed), B_j is the effect of batches (j = 1,2,3, consider fixed), TB_ij is the ineraction between T_i and B_j (considered fixed) and e_ijk is the residual. The archaeal abundance was log 10 (n+1) transformed to ensure normal distribution. Statistical significance is defined when p values are less than 0.05, and a trend was indicated by p<0.10.

The fermentation results with grape seed procyanidin treatment are summarized in Table 2. The DM digestibility, gas production and methane production were significantly decreased by the addition of GSPE. The proportion of propionate significantly increased by the GSPE supplement, while the acetate to propionate ratio was decreased. Compared with the control group, the proportion of acetate exhibited a decreasing tendency. Overall, the results indicate that grape seed procyanidin had a significant impact on the VFA profile, especially on propionate formation.

The RT-PCR results showed that the relative populations of methanogens, ciliate protozoa, and Fibrobacter succinogenes were significantly decreased by 52%, 42%, and 51%, respectively (Table 3). Compared with CON, the population of anaerobic fungi was increased by 50% in the grape seed procyanidin group, while Ruminococcus albus and Ruminococcus flavefaciens were not affected.

The effects of grape seed procyanidin on the alpha diversity of the ruminal archaeal community are summarized in Table 4. No significant differences were observed among the alpha diversity indices upon grape seed procyanidin treatment. The archaeal community was represented by the predominant phylum Euryarchaeota in both the grape seed procyanidin and control groups, comprising an average of 98% of the archaeal community. At the genus level, organisms with a relative abundance of ≥0.1% of the total sequences in at least one of the samples were further analyzed. The top 3 predominant genera were Methanobrevibacter, Methanomicrobium, and Methanomassiliicoccus in both groups (Figure 1). The relative abundance of Methanobrevibacter was lower in the GSPE-treated group than that in the control group (Figure 2). Additionally, the abundances of Methanomicrobium and Methanomassiliicoccus were significantly increased by the GSPE treatment.

The LEfSe analysis combined the rank sum tests and taxonomic information to determine biomarker genera with the largest impact on community structure. In our study, 4 methanogenics were selected as biomarkers for the control group, and 6 methanogenics were selected as biomarkers for the GSPE-treated group. A list of the biomarker genera is shown in Figure 3.

The present study indicated that there was a reduction in methane production after supplementation of grape seed procyanidin, followed by a significant decrease in the relative abundance of Methanobrevibacter and a significant increase in that of Methanomassiliicoccus. There were three major pathways for methanogenesis in rumen: hydrogenotrophic, methylotrophic and acetoclastic pathways. Leahy et al [18] showed that Methanobrevibacter could convert H₂ and/or formate to CH₄ via the hydrogenotrophic methanogen pathway. A similar study reported that Methanobrevibacter ruminantium is a rod-shaped bacterium with variable motility that is able to utilize hydrogen (H₂), carbon dioxide, and formate as substrates for methane production [19]. Furthermore, Methanobrevibacter was reported as the major protozoa-associated methanogen [20]. Ciliate protozoa play an essential role in the interspecies hydrogen transfer and methane formation in rumen, which produce large mounts of H₂ by hydrogenases. Methanomassiliicoccus can use methylamine substrates for methanogenesis by H₂-dependent methylotrophic pathway [21]. It has been reported that Methanomassiliicoccus was 1.5-fold more abundant in low CH₄ emitters than in high CH₄ emitters among dairy cows [22]. Wang et al [9] found that replacement of forage fiber with non-forage fiber sources would reduce methanogenesis in rumen by decreasing the relative abundance of Methanobrevibacter and increasing that of Methanomassiliicoccus. Therefore, the results indicated that grape seed procyanidin has significant effects on the populations of major methanogen communities that are closely associated with methane production.

The changes in VFA production in response to grape seed procyanidin treatment are possibly associated with changes in the microbial population. It is well documented that acetate and butyrate accompany H₂ production, which can be used for the CH₄ formation by the methanogenic archaea, and that CH₄ is positively associated with the acetate to propionate ratio [23]. Janssen [24] reported that increasing propionate formation was strongly associated with a decrease in CH₄ production. In the present study, GSPE caused a significantly increased proportion of propionate, while the proportion of acetate tended to decrease. The RT-PCR results showed that the relative populations of methanogens and Fibrobacter succinogenes were significantly decreased by grape seed procyanidin treatment. Methanogens were the sole producers of methane in rumen, and the number of them was considered as the major driver of methane emission [25]. Fibrobacter succinogenes was the dominant fibrolytic bacteria in rumen, and the decreased relative abundance indicated that the addition of GSPE presented somewhat detrimental effects on the ability of degrading substrate. Protozoa are associated with the abundance of H₂-producing microorganisms, with an important role in methane production [26]. The RT-PCR results also showed a significant decrease in the protozoal population upon the addition of GSPE. Jolazadeh et al [27] found that supplementation with GSPE decreased total protozoal population and improved the growth performance of Holstein bulls, which was in accordance with our results. Protozoa, as the major butyrate producers in the rumen, are positively associated with butyrate production and are also known to contribute to fiber degradation, which might also be responsible for the change in fermentation. Further analysis of the response of protozoa to grape seed procyanidin with regard to the inhibition of methanogens may aid in elucidating the role of this compound in rumen fermentation. Additionally, the pH is known to have a substantial effect on the microbial community structure and diversity in the rumen ecosystem [28]; specifically, the pH was significantly increased by the GSPE treatment in the present study. Moreover, previous studies reported that polymeric procyanidins play an important role in improving rumen metabolism and ruminant nutrition, including reducing protein degradation and inhibiting methanogenesis [29]. Hence, the decrease in methane production may also be explained by the fact that grape seed procyanidin affected the pattern of fermentation by shifts in the microbial populations. However, further research is needed to fully understand the in vivo activity of grape seed procyanidin in rumen microbial ecosystems.