Changes in ruminal community diversity
In total, 417.5 million sequences deriving from 24 samples with an average read length of 155 bp were obtained, with a mean of 17.4 million reads per sample. After removing low quality sequences, 93.7% of reads remained for further processing. After aligning with the rRNA reference databases, 32.6% of sequences were classified as 16S and 18S rRNA, the rest were considered as putative mRNA.
Approximately 63 and 102 bacterial genera were identified in the ruminal liquid and solid fractions (Fig. 1A and Table S2; P < 0.001). A lower pH environment tended to increase numbers of bacterial genera in the liquid fraction compared to normal pH (56 versus 70 bacteria genera; P = 0.09), while there was no difference in the solid fraction (102 versus 101 bacteria genera; P = 0.89). When considering the total number of individual bacterial taxa, Menhinick’s index indicated low pH increased bacterial richness in the liquid fraction (P = 0.02) but did not affect the richness in the solid fraction (P = 0.92) compared to the corresponding Control group. Hill’s ratio indicated the there was no pH effect in either fraction (P = 0.21 and 0.95). The Shannon-Wiener index, a combination of richness and evenness, indicated that low pH increased bacterial community diversity in the solid fraction compared to the liquid fraction at normal pH (P < 0.001), but it had no effect on the solid fraction (P = 0.94). Although the liquid fraction had a greater richness than the solid fraction (P = 0.04), the liquid fraction was less homogenous than the solid fraction (P < 0.001), which contributed to a lesser diversity in the liquid fraction than the solid fraction (P < 0.001).
About 10 and 9 protozoal genera were observed in the liquid and solid fractions (Fig. 1B and Table S1). Ruminal pH did not significantly affect richness, evenness, or diversity. Greater evenness and diversity were observed in the solid fraction than the liquid fraction (P = 0.004 and 0.005) though the liquid and solid fractions had no difference in richness (P = 0.31).
Only 3 archaeal genera were identified in the rumen, and no significant difference was observed in terms of richness, evenness, and diversity between liquid and solid fractions in association with treatment.
Principle Component Analysis of Bacterial Phyla and Protozoal Genera
Principle component analysis was conducted to compare overall composition of bacterial phyla among all samples (Fig. 2). The analyses indicated the first component accounted for 40.4% of the total variation, and the second component accounted for 19.4% of the total variation (Fig. 2A). Loading factors for the first two components (the arrows in Fig. 2A) reveal the contributions of each variable on the first two components. The arrow direction represents negative or positive correlations on the factor map, and the arrow length indicates contribution rates to the principal components. The first component was negatively correlated with Bacteroidetes and Kiritimatiellaeota, and positively correlated with Chloroflexi and Actinobacteria; While the second component was negatively correlated with Firmicutes and Proteobacteria, and positively correlated with Epsilonbacteraeota, and Synergistetes. Although there was an overlap between the Control and LpH group, the second component can separate different ruminal pH treatments (Fig. 2B), and the first component can clearly separate ruminal liquid and solid fractions (Fig. 2C).
Principle component analysis for protozoal genera are displayed in FigureS1. The first component accounted for 35% of the total variation, and the second component accounted for 24.1% of the total variation. The first component was positively correlated with Entodinium, while negatively correlated with Polyplastron and Eudiplodinium (Figure S1A). There was a positive correlation between the second component and Dasytricha and a negative correlation with Diplodinium, Blepharocorys, and Cycloposthium (Figure S1A). Similar to the overall variance structure of bacterial phylum, the second component appeared to sperate different ruminal pH treatments (Figure S1B), and the first component separated different ruminal liquid and solid fractions (Figure S1C).
Changes of taxonomic distribution in the rumen
Overall, there were 19 active bacterial phyla with a relative abundance greater than 0.05% identified in all samples. The most abundant phyla were Firmicutes, Proteobacteria, Bacteroidetes, and Spirochaetes (Fig. 3A). However, their proportions were dependent on treatments or rumen sample fractions. Approximately 15.0% Firmicutes, 41.0% Proteobacteria, 22.7% Bacteroidetes, and 5.0% Spirochaetes were distributed in the liquid fraction of the normal pH group, while there were 21.5% Firmicutes, 24.2% Proteobacteria, 19.9% Bacteroidetes, and 7.7% Spirochaetes in the liquid fraction of the LpH group. The population contained 36.0% Firmicutes, 28.0% Proteobacteria, 11.4% Bacteroidetes, and 13.6% Spirochaetes in the solid fraction of the Control groups, as compared to 30.4% Firmicutes, 27.1% Proteobacteria, 12.0% Bacteroidetes, and 14.6% Spirochaetes in the solid fraction of the LpH group.
Analysis of variance results are presented in and Fig. 3B and Table S3. The ruminal liquid fraction had greater proportions of Bacteroidetes, Cyanobacteria, Elusimicrobia, Kirtimatiellaeota, Lentisphaerae, and Verrucomicrobia than that in ruminal solid fractions (P < 0.001, 0.001, 0.03, < 0.001, < 0.001, and 0.01), but lesser proportions of Actinobacteria, Chloroflexi, Firmicutes, Patescibacteria, and Spirochaetes (P < 0.001, 0.02, 0.002, 0.04, and < 0.001). Compared to normal pH, the low pH treatment increased the proportion of Chloroflexi in the liquid fraction (P = 0.05), and decreased the proportions of Bacteroidetes, Patescibacteria, and Proteobacteria (P < 0.001, 0.03, and < 0.001). However, no significant pH effect was observed in the solid fraction.
Analyses at the bacterial genus level were performed to gain further insights into changes in the taxonomic distributions. In total, 121 bacterial genera were identified in the samples, with 86 having relative abundances greater than 0.05% in all the samples. On average, Succinivibrionaceae_UCG-002, Treponema_2, Fibrobacter, Ruminobacter, Christensenellaceae_R-7_group, Erysipelotrichaceae_UCG-004, Ruminococcus_2, Prevotella_1, Succinivibrionaceae_UCG-001, and CAG-352 were the 10 most abundant genera, accounting for 17.5, 8.9, 4.4, 4.1, 3.6, 3.1, 3.0, 3.9, 2.8, and 3.0% of total bacteria within liquid and solid samples (Fig. 4A). In total, 28 bacterial genera had different proportions between the ruminal liquid and solid samples; 12 bacterial genera were affected by ruminal pH in the liquid fraction; only 2 bacterial genera were affected by pH in the solid fraction (Table S4). Of these, 1 bacterial genus was affected by ruminal pH in both the liquid and solid fractions, and 4 genera were influenced by both ruminal pH in the liquid fraction and by sample fraction.
Regardless of ruminal pH, the solid fraction had a greater proportion of Olsenella (P < 0.001), Prevotellaceae_NK3B31_group (P = 0.02), Prevotellaceae_UCG-001 (P < 0.001), Acetitomaculum (P = 0.01), Butyrivibrio_2 (P < 0.001), Family_XIII_AD3011_group (P < 0.001), Lachnospiraceae_AC2044_group (P < 0.001), Lachnospiraceae_NK3A20_group (P < 0.001), Mogibacterium (P < 0.001), Moryella (P < 0.001), Pseudobutyrivibrio (P = 0.005), Ruminococcus_1 (P < 0.001), Saccharofermentans (P < 0.001), Selenomonas_1 (P = 0.002), Desulfovibrio (P < 0.001), Treponema_2 (P = 0.01), and Pyramidobacter (P = 0.001) than the liquid fraction, and a lesser proportion of Prevotella_1 (P < 0.001), Prevotellaceae_YAB2003_group (P < 0.001), Elusimicrobium (P < 0.001), Asteroleplasma (P = 0.004), Erysipelotrichaceae_UCG-004 (P < 0.001), Ruminococcaceae_UCG-010 (P = 0.01), Horsej-a03 (P = 0.01), Ruminobacter (P = 0.001), Sphaerochaeta (P = 0.004), and Anaeroplasma (P = 0.01).
As displayed in Fig. 4B, compared to normal ruminal pH, low ruminal pH decreased Prevotella_1 (P = 0.04), Prevotella_9 (P = 0.003), Anaerosporobacter (P = 0.002), and Succinimonas (P = 0.003) in the liquid fraction, and increased Flexilinea (P < 0.001), Mogibacterium (P = 0.01), Papillibacter (P = 0.01), Ruminococcaceae_UCG-005 (P = 0.03), Ruminococcaceae_UCG-010 (P = 0.01), Sediminispirochaeta (P = 0.03), Treponema (P = 0.03), and Pyramidobacter (P = 0.02) in the liquid fraction. Finally, low ruminal pH increased Bifidobacterium (P = 0.03) and Prevotella_9 (P = 0.05) in the solid fraction.
In total, 11 protozoal genera were identified through analysis of microbial composition, and 7 of them were observed in all the samples with relative abundances greater than 0.05% of the total population. As displayed in Figure S2, Entodinium, Polyplastron, Isotricha, Eudiplodinium, and Eremoplastron were highly abundant representing 67.9, 11.0, 9.6, 2.7, and 2.9% of the population in all the liquid and solid samples. The ruminal liquid fraction had lesser proportions of Diploplastron and Eudiplodinium than the solid fraction (P = 0.04 and 0.001; Table S5). Low pH decreased the proportion of Entodinium and Isotricha in the liquid samples (P = 0.02 and 0.004; Table S5). However, no significant pH effect was observed in the solid samples.
Candidatus Methanomethylophilus and Methanobrevibacter were the most abundant archaeal genera, accounting for approximately 54.3 and 25.1% of total ruminal archaea. Low ruminal pH did not change archaeal composition in either fraction. However, the ruminal solid fraction had a greater proportion of Methanobrevibacter than the liquid fraction (P = 0.02), and a lesser proportion of Candidatus Methanomethylophilus (P < 0.001; Table S6).
Changes in CAZyme transcripts expressed by rumen microbiota
In total, 97 transcripts encoding CAZyme were identified, and 88 had a relative abundance above 0.05% in all the samples. As displayed in Fig. 5A, genes encoding cellulase, endo-1,4-beta- xylanase, amylase, and alpha-N-arabinofuranosidase were the most abundant transcripts in the liquid and solid fractions, accounting for 12.83, 11.87, 7.72, and 2.75% of the total enzyme transcripts. As shown in Table S7 and Fig. 5B, 8 transcripts were significantly affected by ruminal pH in the liquid fraction; 2 transcripts were influenced by ruminal pH in the solid fraction, and 16 transcripts had different distributions between the liquid and solid fractions. Within them 2 transcripts were affected by both pH effect in the liquid fraction and sample fraction effect, and 1 was affected by ruminal pH effect in both liquid and solid fractions.
The expression of genes encoding glucan phosphorylase, glucosidase Cel1C, pectate lyase, rhamnogalacturonan acetylesterase, and UDP-3-0-acyl N-acetylglucosamine deacetylase were upregulated by lower ruminal pH in the liquid fraction (P = 0.05, 0.01, < 0.001, 0.05, and 0.04), while transcripts of glycosyl hydrolase family 16, putative glycosyl transferase, and sucrose alpha-glucosidase were downregulated (P = 0.02, 0.03, and < 0.001). Compared to the normal pH, the low pH environment decreased expression of genes encoding glycosyl hydrolase family 43 in the solid fraction (P = 0.02), while increased gene expressions of pectate lyase (P < 0.001). The ruminal liquid fraction contained a greater proportion of transcripts of alpha-glucosidase, amylase, beta-galactosidase, cellulase celA, glycosyl hydrolase family 57, penicillin-binding protein 1A, putative 4-alpha-glucanotransferase, putative alpha-xylosidase, putative carbohydrate-active enzyme, and sucrose alpha-glucosidase than the solid fraction (P = 0.003, < 0.001, 0.03, 0.001, 0.01, 0.04, 0.005, 0.03, < 0.001, and 0.01), while lesser transcripts of glucan 1,4-alpha-maltotetraohydrolase, glucan phosphorylase, glycoside hydrolase family 43, glycosyl hydrolase family 51, glycosyltransferase 36, and isoamylase domain/esterase family protein (P = 0.003, 0.01, < 0.001, 0.01, 0.001, and 0.01).
Intake, fiber degradation, and VFA concentrations
Real time pH over the whole experimental period were displayed in Figure S3. As designed, the mean ruminal pH achieved for the Control and LpH treatments were 6.44 and 6.09, respectively. Compared to the Control, DMI was inhibited by decreasing ruminal pH (P = 0.04, Fig. 5A and Table S8).
In situ degradation of dietary DM, hemicellulose, cellulose, and lignin with respect to the rumen incubation time are shown in Figure S4. Although the individual parameters a, b, and kd were not affected by lower ruminal pH (Fig. 5B and Table S8), effective degradabilities of dietary DM, hemicellulose, cellulose, and lignin were decreased (P = 0.06, 0.02, 0.02, and 0.002, Fig. 5C). Decreased DMI and ruminal fiber degradability were associated with decrease of VFA concentrations and presumably production rates. As a result, concentrations of ruminal total VFA, acetate, propionate, butyrate, isobutyrate, valerate, and isovalerate were decreased in response to lower ruminal pH (P = 0.001, 0.001, 0.001, 0.001, 0.001, 0.04, and 0.003; Fig. 5A and Table S8).
Correlations between ruminal microbes and gene expressions of CAZyme
Pairwise correlations between microbes and transcripts encoding CAZyme are displayed in Fig. 7. There were 45 microbes (41 bacterial genera and 4 protozoal genera) and 27 CAZyme transcripts that had at least one correlation coefficient above 0.5 or less than − 0.5 which was the criteria for inclusion in the matrix regardless of ruminal liquid or solid fractions. However, there was no significant correlations identified among archaeal genera and transcripts encoding CAZyme.
Network Analysis of Factors Associated with Fiber Degradation and VFA Production
Network analysis demonstrated that 76 bacterial genera, 4 protozoal genera, and 48 genes encoding CAZyme were associated with fiber degradation and VFA production (Fig. 8). Ruminal pH was strongly correlated with 29 bacterial genera, 4 protozoal genera, and 6 genes encoding CAZyme. Of these, 19 bacterial genera (Clostridium_sensu_stricto_1, Succinivibrionaceae_UCG-002, Lachnoclostridium_1, Anaerosporobacter, CAG-352, M2PT2-76_termite_group, Ruminiclostridium_9, Lachnospiraceae_FE2018_group, Lachnospiraceae_ND3007_group, Z20, Fibrobacter, Victivallis, Ruminococcaceae_UCG-005, Sediminispirochaeta, Ruminococcaceae_UCG-010, Papillibacter, Treponema, Flexilinea, Bifidobacterium), 4 protozoal genera (Blepharocorys, Cycloposthium, Dasytricha, and Isotricha), and 5 genes encoding CAZyme (sucrose alpha-glucosidase, glycosyl hydrolase family 16, glycosyl hydrolase family 31, lacto-N-biosidase, and pectate lyase) participated in metabolic pathways of fiber degradation and VFA production.