This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research
Sergio Morales
Department of Microbiology and Immunology, University of Otago, PO Box 56, Dunedin 9054, New Zealand
Corresponding Author
ORCiD: https://orcid.org/0000-0002-5862-0726
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background
Agriculture is fundamental for food production, and microbiomes support agricultural through multiple essential ecosystem services. Despite the importance of individual (i.e. niche specific) agricultural microbiomes, microbiome interactions across niches are not well-understood. To observe the linkages between nearby agricultural microbiomes, multiple approaches (16S, 18S, and ITS) were used to inspect a broad coverage of niche microbiomes. Here we examined agricultural microbiome responses to 3 different nitrogen treatments (0 kg/ha/yr, 150kg/ha/yr and 300kg/ha/yr) in soil and tracked linked responses in other neighbouring farm niches (rumen, faecal, white clover leaf, white clover root, rye grass leaf, rye grass root)
Results
Nitrogen treatment had little impact on microbiome structure or composition across niches, but drastically reduced the microbiome network connectivity in soil. Networks of 16S microbiomes were the most sensitive to nitrogen treatment across amplicons, where ITS microbiome networks were the least responsive.
Conclusions
Nitrogen enrichment in soil altered soil and the neighbouring microbiome networks, supporting our hypotheses that nitrogen treatment in soil altered microbiomes in soil and in nearby niches. This suggested that agricultural microbiomes across farm niches are ecologically interactive. Therefore, knock-on effects on neighbouring niches should to be considered when management is applied to a single agricultural niche.
Keywords
Agricultural microbiomes, 16S, 18S, ITS, amplicon sequencing, Microbiome networks
Figure 1
Figure 2
Figure 3
Figure 4
This is a list of supplementary files associated with this preprint. Click to download.
- Table1.xlsx
Table 1 Beta-diversity statistics for 16S, 18S and ITS microbiomes. ANOSIM and Adonis (Bray-Curtis dissimilarity matrix) are used for determine nitrogen treatment effects for individual niche. Significant data are showing in bold.
- FIgS4ITS.pdf
Fig. S4 Microbiome frequency and occupancy plot (ITS), illustrating the different number of populations occupying different number of samples at each niche. X-axis illustrates number of sample sites panelled by each individual niche. Y-axis illustrates accumulated number of present ASV in certain number of samples.
- FigS1016S.pdf
Fig. S10 Presence-absence heatmap (16S) showing the existence of N-responsive ASVs across multiple niches. The x-axis represents the N-treatment for all samples (there are multiple samples under the same treatment). The y-axis represents the taxonomy classification of individual N-responsive ASV.
- FigS1118S.pdf
Fig. S1 18S Microbiome diversities and composition comparisons across farm niches under three levels of nitrogen treatments (0, 150N/ha/yr, 300N/ha/yr). A) Microbiome richness based on number of observed ASVs are shaped by nitrogen treatments. Open circle 〇, plus symbol ＋ and closed triangle ▲ represent 0, 150N/ha/yr and 300N/ha/yr nitrogen managements respectively. Statistical significances shown in figure were calculated with Kruskal-Wallis test. B) Relative abundance of microbiome taxa across farm niches coloured at Phylum level. C) NMDS plot using Bray-Curtis distance coloured by niches and shaped by treatment levels. (ANOSIM: p<0.01, R=0.246 and ADONIS: p<0.01, R2=0.248).
- FigS12ITS.pdf
Fig. S12 Presence-absence heatmap (ITS) showing the existence of N-responsive ASVs across multiple niches. The x-axis represents the N-treatment for all samples (there are multiple samples under the same treatment). The y-axis represents the taxonomy classification of individual N-responsive ASV.
- FigS1318Snetworks.pdf
Fig. S13 Microbiome networks (18S) across niche and N treatments. Pair-wise Spearman correlation is calculated for each ASV pair. Only strong significant correlations with r >0.8 were kept. Each dot represent an ASV, coloured by phylum. Purple edges represent negative correlation, olive yellow edges represent positive correlation.
- FigS14ITSnetworks.pdf
Fig. S14 Microbiome networks (ITS) across niche and N treatments. Pair-wise Spearman correlation is calculated for each ASV pair. Only strong significant correlations with r >0.8 were kept. Each dot represent an ASV, coloured by phylum. Purple edges represent negative correlation, olive yellow edges represent positive correlation.
- FigS118S.pdf
Fig. S11 Presence-absence heatmap (18S) showing the existence of N-responsive ASVs across multiple niches. The x-axis represents the N-treatment for all samples (there are multiple samples under the same treatment). The y-axis represents the taxonomy classification of individual N-responsive ASV.
- FigS2ITS.pdf
Fig. S2 ITS Microbiome diversities and composition comparisons across farm niches under three levels of nitrogen treatments (0, 150N/ha/yr, 300N/ha/yr). A) Microbiome richness based on number of observed ASVs are shaped by nitrogen treatments. Open circle 〇, plus symbol ＋ and closed triangle ▲ represent 0, 150N/ha/yr and 300N/ha/yr nitrogen managements respectively. Statistical significances shown in figure were calculated with Kruskal-Wallis test. B) Relative abundance of microbiome taxa across farm niches coloured at Phylum level. C) NMDS plot using Bray-Curtis distance coloured by niches and shaped by treatment levels. (ANOSIM: p<0.01, R=0.647, ADONIS: p<0.01, R2=0.325)
- FigS318S.pdf
Fig. S3 Microbiome frequency and occupancy plot (18S), illustrating the different number of populations occupying different number of samples at each niche. X-axis illustrates number of sample sites panelled by each individual niche. Y-axis illustrates accumulated number of present ASV in certain number of samples.
- OLWstattablesum.xlsx
Table S1 Sample metadata table. Table S2 For each amplicon type (16S, 18S and ITS microbiomes), statistical summary on number of observed ASVs for each niche type across treatments. The mean, median and standard deviation values are rounded to one decimal place. Table S3a-c Relative abundance table summarised at Phylum level. Minor phylum (relative abundance <0.01) are not showing in the table. a) Phylum relative abundance at for 16S; b) Phylum relative abundance at for 18S ; c) Phylum relative abundance at for ITS Table S4a-c Exact tests results for all N-responsive ASV. For each N-responsive ASV, taxonomy classification, Log fold change (LogFC), log counts per million (logCPM), p-value, adjusted p-value (FDR), data comparisons between which two nitrogen treatments, and niche type are showed in different columns. Adjusted p-values are used for determining significance of ASV responses to nitrogen treatments. Table S5a-c ASV table (absolute abundance) showing all chosen N-responsive ASVs for network analyses across niches. a) Abundance table of chosen ASV for 16S; b) Abundance table of chosen ASV for 18S ; c) Abundance table of chosen ASV for ITS Table S6a-c Network analyses results on Spearman rank correlation coefficient test across niches and nitrogen treatments. Analyses results for each amplicon is displayed in individual spreadsheet (a: 16S, b: 18S, and c: ITS), Table S7 Summary of network details across amplicons, niches, and nitrogen treatments. Number of nodes and edges, average number of edges per nodes, and the standard deviations are provided in the table.
- FigS518S.pdf
Fig. S5 Dot plot of N-responsive ASV across niches. 18S ASVs with more than 2-fold change in abundance responsive to nitrogen treatments. Each differentially abundant ASV is shown as a dot coloured by phylum. Dot sizes illustrate the absolute fold change. The x-axis represents the niche type, namely faecal and rumen. The y-axis represents the taxonomy classification of individual N-responsive ASV.
- FigS6ITS.pdf
Fig S6 Dot plot of N-responsive ASV across niches. ITS ASVs with more than 2-fold change in abundance responsive to nitrogen treatments. Each differentially abundant ASV is shown as a dot coloured by phylum. Dot sizes illustrate the absolute fold change. The x-axis represents the niche type, namely faecal and rumen. The y-axis represents the taxonomy classification of individual N-responsive ASV.
- FigS716S.pdf
Fig. S7 Volcano plot (16S) showing details on ASVs with more than 2-fold change in abundance responsive to nitrogen treatments across niches and N treatments. Each N-responsive ASV is shown as a dot coloured by phylum. Positive or negative responses in log fold change for each N-responsive ASV is illustrated by the x-axis. The y-axis represents the -log10 adjusted p-value (p<- 0.05 across all ASVs showed in the figure).
- FigS818S.pdf
Fig. S8 Volcano plot (18S) showing details on ASVs with more than 2-fold change in abundance responsive to nitrogen treatments across niches and N treatments. Each N-responsive ASV is shown as a dot coloured by phylum. Positive or negative responses in log fold change for each N-responsive ASV is illustrated by the x-axis. The y-axis represents the -log10 adjusted p-value (p<- 0.05 across all ASVs showed in the figure). NA means the ASV is N-responsive but unclassified at phylum level.
- FigS9ITS.pdf
Fig. S9 Volcano plot (ITS) showing details on ASVs with more than 2-fold change in abundance responsive to nitrogen treatments across niches and N treatments. Each N-responsive ASV is shown as a dot coloured by phylum. Positive or negative responses in log fold change for each N-responsive ASV is illustrated by the x-axis. The y-axis represents the -log10 adjusted p-value (p<- 0.05 for all ASVs in the figure). NA means the ASV is N-responsive but unclassified at phylum level
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research
Sergio Morales
Department of Microbiology and Immunology, University of Otago, PO Box 56, Dunedin 9054, New Zealand
Corresponding Author
ORCiD: https://orcid.org/0000-0002-5862-0726
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 13 Jan, 2021
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
General Microbiology
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background
Agriculture is fundamental for food production, and microbiomes support agricultural through multiple essential ecosystem services. Despite the importance of individual (i.e. niche specific) agricultural microbiomes, microbiome interactions across niches are not well-understood. To observe the linkages between nearby agricultural microbiomes, multiple approaches (16S, 18S, and ITS) were used to inspect a broad coverage of niche microbiomes. Here we examined agricultural microbiome responses to 3 different nitrogen treatments (0 kg/ha/yr, 150kg/ha/yr and 300kg/ha/yr) in soil and tracked linked responses in other neighbouring farm niches (rumen, faecal, white clover leaf, white clover root, rye grass leaf, rye grass root)
Results
Nitrogen treatment had little impact on microbiome structure or composition across niches, but drastically reduced the microbiome network connectivity in soil. Networks of 16S microbiomes were the most sensitive to nitrogen treatment across amplicons, where ITS microbiome networks were the least responsive.
Conclusions
Nitrogen enrichment in soil altered soil and the neighbouring microbiome networks, supporting our hypotheses that nitrogen treatment in soil altered microbiomes in soil and in nearby niches. This suggested that agricultural microbiomes across farm niches are ecologically interactive. Therefore, knock-on effects on neighbouring niches should to be considered when management is applied to a single agricultural niche.
Figure 1
Figure 2
Figure 3
Figure 4
This is a list of supplementary files associated with this preprint. Click to download.
- Table1.xlsx
Table 1 Beta-diversity statistics for 16S, 18S and ITS microbiomes. ANOSIM and Adonis (Bray-Curtis dissimilarity matrix) are used for determine nitrogen treatment effects for individual niche. Significant data are showing in bold.
- FIgS4ITS.pdf
Fig. S4 Microbiome frequency and occupancy plot (ITS), illustrating the different number of populations occupying different number of samples at each niche. X-axis illustrates number of sample sites panelled by each individual niche. Y-axis illustrates accumulated number of present ASV in certain number of samples.
- FigS1016S.pdf
Fig. S10 Presence-absence heatmap (16S) showing the existence of N-responsive ASVs across multiple niches. The x-axis represents the N-treatment for all samples (there are multiple samples under the same treatment). The y-axis represents the taxonomy classification of individual N-responsive ASV.
- FigS1118S.pdf
Fig. S1 18S Microbiome diversities and composition comparisons across farm niches under three levels of nitrogen treatments (0, 150N/ha/yr, 300N/ha/yr). A) Microbiome richness based on number of observed ASVs are shaped by nitrogen treatments. Open circle 〇, plus symbol ＋ and closed triangle ▲ represent 0, 150N/ha/yr and 300N/ha/yr nitrogen managements respectively. Statistical significances shown in figure were calculated with Kruskal-Wallis test. B) Relative abundance of microbiome taxa across farm niches coloured at Phylum level. C) NMDS plot using Bray-Curtis distance coloured by niches and shaped by treatment levels. (ANOSIM: p<0.01, R=0.246 and ADONIS: p<0.01, R2=0.248).
- FigS12ITS.pdf
Fig. S12 Presence-absence heatmap (ITS) showing the existence of N-responsive ASVs across multiple niches. The x-axis represents the N-treatment for all samples (there are multiple samples under the same treatment). The y-axis represents the taxonomy classification of individual N-responsive ASV.
- FigS1318Snetworks.pdf
Fig. S13 Microbiome networks (18S) across niche and N treatments. Pair-wise Spearman correlation is calculated for each ASV pair. Only strong significant correlations with r >0.8 were kept. Each dot represent an ASV, coloured by phylum. Purple edges represent negative correlation, olive yellow edges represent positive correlation.
- FigS14ITSnetworks.pdf
Fig. S14 Microbiome networks (ITS) across niche and N treatments. Pair-wise Spearman correlation is calculated for each ASV pair. Only strong significant correlations with r >0.8 were kept. Each dot represent an ASV, coloured by phylum. Purple edges represent negative correlation, olive yellow edges represent positive correlation.
- FigS118S.pdf
Fig. S11 Presence-absence heatmap (18S) showing the existence of N-responsive ASVs across multiple niches. The x-axis represents the N-treatment for all samples (there are multiple samples under the same treatment). The y-axis represents the taxonomy classification of individual N-responsive ASV.
- FigS2ITS.pdf
Fig. S2 ITS Microbiome diversities and composition comparisons across farm niches under three levels of nitrogen treatments (0, 150N/ha/yr, 300N/ha/yr). A) Microbiome richness based on number of observed ASVs are shaped by nitrogen treatments. Open circle 〇, plus symbol ＋ and closed triangle ▲ represent 0, 150N/ha/yr and 300N/ha/yr nitrogen managements respectively. Statistical significances shown in figure were calculated with Kruskal-Wallis test. B) Relative abundance of microbiome taxa across farm niches coloured at Phylum level. C) NMDS plot using Bray-Curtis distance coloured by niches and shaped by treatment levels. (ANOSIM: p<0.01, R=0.647, ADONIS: p<0.01, R2=0.325)
- FigS318S.pdf
Fig. S3 Microbiome frequency and occupancy plot (18S), illustrating the different number of populations occupying different number of samples at each niche. X-axis illustrates number of sample sites panelled by each individual niche. Y-axis illustrates accumulated number of present ASV in certain number of samples.
- OLWstattablesum.xlsx
Table S1 Sample metadata table. Table S2 For each amplicon type (16S, 18S and ITS microbiomes), statistical summary on number of observed ASVs for each niche type across treatments. The mean, median and standard deviation values are rounded to one decimal place. Table S3a-c Relative abundance table summarised at Phylum level. Minor phylum (relative abundance <0.01) are not showing in the table. a) Phylum relative abundance at for 16S; b) Phylum relative abundance at for 18S ; c) Phylum relative abundance at for ITS Table S4a-c Exact tests results for all N-responsive ASV. For each N-responsive ASV, taxonomy classification, Log fold change (LogFC), log counts per million (logCPM), p-value, adjusted p-value (FDR), data comparisons between which two nitrogen treatments, and niche type are showed in different columns. Adjusted p-values are used for determining significance of ASV responses to nitrogen treatments. Table S5a-c ASV table (absolute abundance) showing all chosen N-responsive ASVs for network analyses across niches. a) Abundance table of chosen ASV for 16S; b) Abundance table of chosen ASV for 18S ; c) Abundance table of chosen ASV for ITS Table S6a-c Network analyses results on Spearman rank correlation coefficient test across niches and nitrogen treatments. Analyses results for each amplicon is displayed in individual spreadsheet (a: 16S, b: 18S, and c: ITS), Table S7 Summary of network details across amplicons, niches, and nitrogen treatments. Number of nodes and edges, average number of edges per nodes, and the standard deviations are provided in the table.
- FigS518S.pdf
Fig. S5 Dot plot of N-responsive ASV across niches. 18S ASVs with more than 2-fold change in abundance responsive to nitrogen treatments. Each differentially abundant ASV is shown as a dot coloured by phylum. Dot sizes illustrate the absolute fold change. The x-axis represents the niche type, namely faecal and rumen. The y-axis represents the taxonomy classification of individual N-responsive ASV.
- FigS6ITS.pdf
Fig S6 Dot plot of N-responsive ASV across niches. ITS ASVs with more than 2-fold change in abundance responsive to nitrogen treatments. Each differentially abundant ASV is shown as a dot coloured by phylum. Dot sizes illustrate the absolute fold change. The x-axis represents the niche type, namely faecal and rumen. The y-axis represents the taxonomy classification of individual N-responsive ASV.
- FigS716S.pdf
Fig. S7 Volcano plot (16S) showing details on ASVs with more than 2-fold change in abundance responsive to nitrogen treatments across niches and N treatments. Each N-responsive ASV is shown as a dot coloured by phylum. Positive or negative responses in log fold change for each N-responsive ASV is illustrated by the x-axis. The y-axis represents the -log10 adjusted p-value (p<- 0.05 across all ASVs showed in the figure).
- FigS818S.pdf
Fig. S8 Volcano plot (18S) showing details on ASVs with more than 2-fold change in abundance responsive to nitrogen treatments across niches and N treatments. Each N-responsive ASV is shown as a dot coloured by phylum. Positive or negative responses in log fold change for each N-responsive ASV is illustrated by the x-axis. The y-axis represents the -log10 adjusted p-value (p<- 0.05 across all ASVs showed in the figure). NA means the ASV is N-responsive but unclassified at phylum level.
- FigS9ITS.pdf
Fig. S9 Volcano plot (ITS) showing details on ASVs with more than 2-fold change in abundance responsive to nitrogen treatments across niches and N treatments. Each N-responsive ASV is shown as a dot coloured by phylum. Positive or negative responses in log fold change for each N-responsive ASV is illustrated by the x-axis. The y-axis represents the -log10 adjusted p-value (p<- 0.05 for all ASVs in the figure). NA means the ASV is N-responsive but unclassified at phylum level
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