We examined microbiomes using 3 approaches focusing on specific microbiome subpopulations, namely prokaryotes (16S rRNA), eukaryotes (18S rRNA) and fungi (ITS rRNA). Next-generation sequencing data were captured from 7 farm niches, specifically 2 animal-associated niches (Rumen [R] and Faecal [F]), 3 below-ground niches (WhiteCloverRoot [WCR], RyeGrassRoot [RGR], and Bulk Soil [BS]), and 2 above-ground niches (WhiteCloverLeaf [WCL] and RyeGrassLeaf [RGL]). For each of these microbiomes, community responses were compared across 3 different soil nitrogen treatments (control or no-nitrogen [0 N kg/ha/yr], medium-nitrogen [150 N kg/ha/yr], and high-nitrogen [300 N kg/ha/yr]).
Microbial richness and composition were distinct acrossniches, but shared similar responses to soil nitrogen treatment.
To compare the microbiome richness across niches and nitrogen treatment, Alpha diversities were calculated and analysed across niche microbiomes with ASVs (amplicon sequence variants). For all 3 amplicons, richness of microbiomes were distinct across farm niches (p<0.001, Kruskal-Wallis rank sum test) (Table 1 and S2), but were not significantly differentiated between nitrogen treatments (Fig. 1A, S1A-S2A, and Table S2). In general, leaf microbiomes were the least diverse where BS microbiomes richness under no-nitrogen were the highest across amplicons, with an average of 788, 357 and 385 observed ASVs from 16S, 18S and ITS respectively. In contrast, phyllosphere microbiomes richness were relatively low. For instance WCL microbiome richness under no-nitrogen were low across amplicons, with an average of 36, 20 and 149 observed ASVs from 16S, 18S and ITS respectively. Nitrogen treatment did not alter microbiome richness except for ITS of below-ground niche WCR (Fig. S2A), where microbiome richness was decreased with soil nitrogen treatment (p=0.045, Kruskal-Wallis rank sum test).
Taxonomic compositions were distinct across niches, but did not change in response to soil nitrogen treatment (Fig. 1B, S1B-2B, Table S3a-c). For 16S communities, regardless of nitrogen treatment, the phyllosphere microbiomes in both RGL and WCL were dominated by Proteobacteria (82% and 79% on average respectively). Similarly in soil and rhizosphere niches (BS, RGR, and WCR), Proteobacteria dominated at 28%, 36% and 47% on average respectively. Animal-associated microbiomes R and F were both dominated by Bacteroidetes and Firmicutes (Table S3a). Trends (i.e. changes across niches, with no treatment effects) were similar for 18S and ITS microbiomes (Fig. S1B-2B, Table S3b-c) with a couple of exceptions. For 18S, Phragmoplastophyta dominated in all phyllosphere and rhizosphere niches, while Cilliophora dominated the 2 animal-associated niches (Fig. S1 and Table S3b). For ITS, Ascomycota dominated across all niches except for R, where Neocallimastigomycota was the most abundant (Fig. S2 and Table S3c).
Bray-Curtis distances were calculated and plotted with NMDS ordinations to examine microbiome beta diversities across niches. Significant differences in community composition were observed across niche microbiomes (16S: ANOSIM: R=0.758 and ADONIS: R2=0.505. 18S: ANOSIM: R=0.246 and ADONIS: R2=0.248. ITS: ANOSIM: R=0.647, ADONIS: R2=0.325, p<0.01 for all cases), but not in response to nitrogen treatment (Fig. 1C, S1c-2c, and Table 1) except for WCR (16S community) and R (18S community). For 16S, animal-associated microbiomes were more distinct compared with other niches (Fig. 1C). Samples from the rhizosphere were clustered primarily by niches, but partial overlaps were observed between BS, RGR,RGL, WCR and WCL microbiomes. Microbiome compositions for 18S and ITS were also significantly different across niches, but broad overlaps across niches were found. Nitrogen treatment had minimal impact on microbiome compositions within each individual niche except for 16S microbiomes in WCR (ANOSIM p=0.004, R=0.317 and ADONIS p=0.01, R2=0.189), and for 18S microbiomes in R (ANOSIM p=0.027, R=0.043 and ADONIS p=0.048, R2=0.056).
To compliment the microbiome compositional and structural change in response to nitrogen treatment, microbiome structural dynamics were also measured for each amplicon across niches with frequency and occupancy plots (Fig. 2 and S3-4). Microbiomes occupancy-frequency distributions across amplicons in both of the phyllosphere niches showed similar skewed patterns. The number of shared ASV declined with increasing number of samples within niche, followed by an increase in species occupying all or most sites, illustrating a core-satellite pattern [59, 60]. Compared to the phyllosphere microbiomes, rhizosphere microbiomes showed variations in distribution dynamics across amplicons. Core-satellite patterns were found in ITS and 18S communities, but not in 16S, suggesting variations in community assembly mechanisms and selective pressure across sub-populations and niches.
Nitrogen treatment affected ASV abundance, but only for certain taxa in animal associated niches.
To identify changes in ASV abundance in response to nitrogen treatment, an Exact test was performed for each niche between two nitrogen treatment pairs: no-nitrogen verses medium-nitrogen, or no-nitrogen versus high-nitrogen. For each niche, responsive ASVs (Exact test with logFC >= 2 or logFC <= -2, and BH adjusted p<0.05) (defined as N-responsive ASVs) were identified. Scattered plots were used to illustrate abundance changes of N-responsive ASV across niches (Fig. 3, Fig. S5-6). Volcano plots (Fig. S7-9) and heatmaps (Fig. S10-12) were used to provide complementary details on foldchanges of N-responsive ASVs across niches and nitrogen treatments.
All N-responsive ASVs were linked with animal-associated niches (Fig. 3, Fig. S5-6), but their presences were detected in other niches (Fig. S10-12). In 16S communities for example, 126 ASV were originally identified as N-responsive in animal-associated niches (Table S4a, Fig. 3), but none in other niches. Interestingly, over one third (47 out of 126) of N-responsive 16S ASVs were classified under the genus Prevotella. Moreover, all of the N-responsive Prevotella ASVs had positive foldchanges under medium- or high-nitrogen (Table S4a). Similarly in 18S and ITS communities, the majority of N-responsive ASVs of (18S: 1692 out of 1694, ITS: 139 out of 140) were only responsive in animal-associated niches (Fig. S8-9, Table S4b-c). Surprisingly, no ASV from BS niche was N-responsive across amplicons. In addition, close to a third of 18S N-responsive ASVs (495 out of 1694) were unclassified, suggesting a lack of reference sequences for N-responsive18S sequences.
Nitrogen treatment drastically reduced microbial network connectivity in soil but the knock-on effects on other niches were random.
To investigate microbiome network changes in response to nitrogen treatment across niches, network analyses were performed for each niche individually with a pool of unique ASVs. The ASV pool was formed by a conjunction of N-responsive ASVs and the 200 most abundant ASVs (Table S5) from each niche. Pairwise Spearman correlations were conducted between selected ASVs (i.e. ASVs found in ASV pool) to calculate their correlations. Only strong correlations (r>=0.8 or r<=-0.8, p<=0.05, defined as connections) were included in the networks (Table S6). Networks in each niche were formed by all connections found with each nitrogen treatment, each network connection was formed by two ASVs (i.e. nodes) and a line (i.e. edge) in between. Overall, microbiome networks were responsive to nitrogen treatment across niches, but responses were inconsistent between niches and across amplicons.
Nitrogen treatment drastically reduced or eliminated network connections in BS across amplicons (Fig. 4, Fig. S13-14 and Table S7). On average, BS networks had 4.94, 9.43 and 16.21 edges per node in 16S, 18S and ITS respectively under no-nitrogen. BS network connections were drastically reduced for ITS under medium- and high-nitrogen (2.86 and 3.03 edges per node respectively), and were eradicated for 16S and 18S under medium- and high-nitrogen.
Nitrogen treatment had knock-on effects on other microbiome networks, but resulted in random changes across niches and amplicons (Fig. 4, Fig. S13-14). For 16S, faecal networks under medium-nitrogen (108 nodes and 149 edges) were the most dense compared to networks under no- or high-nitrogen (no-nitrogen: 22 nodes and 20 edges; high-nitrogen: 76 nodes and 59 edges. Fig. 4 and Table S7). Similar trends were noted in the other 16S animal-associated networks, but not for other amplicons (Fig. S13-14 and Table S7). Rhizosphere networks responded to nitrogen treatment differently between niches and amplicons. Network connections of WCR in both 16S (18 nodes and 24 edges ) and ITS (94 nodes and 700 edges) under high-nitrogen were the most dense compared to that under no- or medium-nitrogen (Fig. 4, Fig. S14, and Table S7). In contrast, RGR networks only showed notable changes in 18S, where networks (39 nodes and 55 edges) under medium-nitrogen were the most dense (Fig. S13). Phyllosphere microbiome networks across amplicons showed no response to nitrogen treatment.