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Viral but not bacterial community successional patterns reflect extreme turnover shortly after rewetting dry soils

Nature Ecology & Evolution volume 7, pages 1809–1822 (2023)Cite this article

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Abstract

As central members of soil trophic networks, viruses have the potential to drive substantial microbial mortality and nutrient turnover. Pinpointing viral contributions to terrestrial ecosystem processes remains a challenge, as temporal dynamics are difficult to unravel in the spatially and physicochemically heterogeneous soil environment. In Mediterranean grasslands, the first rainfall after seasonal drought provides an ecosystem reset, triggering microbial activity during a tractable window for capturing short-term dynamics. Here, we simulated precipitation in microcosms from four distinct dry grassland soils and generated 144 viromes, 84 metagenomes and 84 16S ribosomal RNA gene amplicon datasets to characterize viral, prokaryotic and relic DNA dynamics over 10 days. Vastly different viral communities in each soil followed remarkably similar successional trajectories. Wet-up triggered a significant increase in viral richness, followed by extensive compositional turnover. Temporal succession in prokaryotic communities was much less pronounced, perhaps suggesting differences in the scales of activity captured by viromes (representing recently produced, ephemeral viral particles) and total DNA. Still, differences in the relative abundances of Actinobacteria (enriched in dry soils) and Proteobacteria (enriched in wetted soils) matched those of their predicted phages, indicating viral predation of dominant bacterial taxa. Rewetting also rapidly depleted relic DNA, which subsequently reaccumulated, indicating substantial new microbial mortality in the days after wet-up, particularly of the taxa putatively under phage predation. Production of abundant, diverse viral particles via microbial host cell lysis appears to be a conserved feature of the early response to soil rewetting, and results suggest the potential for ‘Cull-the-Winner’ dynamics, whereby viruses infect and cull but do not decimate dominant host populations.

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Fig. 1: Dataset overview.
Fig. 2: Richness and viromic DNA yields over the time series.
Fig. 3: Successional patterns across the four soil types for viral compared with prokaryotic communities.
Fig. 4: Temporal trait-based and taxonomic patterns in viral and prokaryotic responses to wet-up across soils.
Fig. 5: Relic DNA abundance and composition over time.

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Data availability

A detailed version of the viromics laboratory protocol is available at https://protocols.io/view/soil-viromics-protocol-emerson-lab-v1-b7nyrmfw. Raw sequences are available from the NCBI Sequence Read Archive (BioProject PRJNA859194). The databases of dereplicated vOTUs and MAGs are available at https://doi.org/10.5281/zenodo.7510627.

Code availability

Code and processed files needed to replicate the statistical analyses can be found at https://github.com/cmsantosm/WetupViromes.

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Acknowledgements

This work was predominantly supported by an award from the US Department of Energy, Office of Science, Office of Biological and Environmental Research, Genomic Science Program, no. DE-SC0020163 (grant to J.P.R., M.K.F. and J.B.E.). Additional support was provided by the US Department of Energy, Office of Science, Office of Biological and Environmental Research, Genomic Science Program, award no. DE-SC0021198 (grant to J.B.E.). Research at Lawrence Livermore National Laboratory was conducted under the auspices of Department of Energy contract DE-AC52-07NA27344. Shotgun metagenomic library construction and high-throughput sequencing were performed by the DNA Technologies and Expression Analysis Core at the UC Davis Genome Center, supported by National Institutes of Health Shared Instrumentation Grant 1S10OD010786-01. We thank the University of California Natural Reserves site directors and staff, including S. Waddell, C. Koehler, J. Clary and J. Bailey, for facilitating access to field sites and associated site information.

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Authors and Affiliations

  1. Department of Plant Pathology, University of California, Davis, CA, USA

    Christian Santos-Medellín & Joanne B. Emerson

  2. Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA, USA

    Steven J. Blazewicz & Jennifer Pett-Ridge

  3. Life & Environmental Sciences Department, University of California, Merced, CA, USA

    Jennifer Pett-Ridge

  4. Innovative Genomics Institute, University of California, Berkeley, CA, USA

    Jennifer Pett-Ridge

  5. Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA, USA

    Mary K. Firestone

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  1. Christian Santos-Medellín
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Contributions

C.S.-M. and J.B.E. conceived and designed the study with input from S.J.B., J.P.-R. and M.K.F. C.S.-M. performed research and analysed data. C.S.-M. and J.B.E. wrote the paper and all authors reviewed it and approved the final version.

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Correspondence to Joanne B. Emerson.

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Extended data

Extended Data Fig. 1 Soil abiotic profiles and precipitation records.

(a) Hierarchical clustering of soil types based on their abiotic properties. The heatmap shows the z-transformed values of the edaphic variables included in the analysis. (b) Daily precipitation at each of the three field sites preceding, during, and after soil harvesting. Dotted vertical lines mark the dates of soil sample collection. (c) Gravimetric soil moisture content over time across soil types. Points correspond to individual microcosms, and trend lines represent the mean moisture content at each time point. Color indicates whether replicates underwent rewetting or remained dry.

Extended Data Fig. 2 Compositional patterns of prokaryotic communities based on ASV profiles of the 16S rRNA gene from total DNA.

(a) Unconstrained analysis of principal coordinates performed on Bray-Curtis dissimilarities. Colors indicate soil type. (b) Community richness measured as the number of ASVs recovered from soil microcosms: colored points correspond to replicates and colored trend lines represent the mean richness at each collection time point. (c) Unconstrained analyses of principal coordinates performed ASV Bray-Curtis dissimilarities. Analyses were performed independently for each soil type (facets). Colors indicate the collection time point and soil status (dry or wet). (d) Linear regressions between Bray-Curtis similarities and temporal distances in post-wet-up time points for viral (vOTUs in viromes) and prokaryotic (ASVs in total DNA) communities. Points represent pairs of samples, trend lines show the least squares linear regression model, and facets correspond to soil types.

Extended Data Fig. 3 Detection patterns of vOTUs and MAGs identified in this study.

(a-b) Euler diagrams showing the intersections between the sets of (a) vOTUs and (b) MAGs detected in each profiling method.

Extended Data Fig. 4 Viral response to rewetting in Hopland soils collected in different years.

(a) Viral community richness in a complementary viromic survey of dry and rewetted (336 hrs after a laboratory simulation of wet-up) soils harvested from the Hopland site at the end of the 2019 dry season (approximately one year prior to sample collection for the main microcosm experiment in this study). Facets correspond to DNase-treated and untreated viromic profiles. Box boundaries correspond to the 25th and 75th percentile and whiskers indicate the ±1.5x interquartile range. For each time point, we collected samples from n = 3 microcosms. DNase-treated profiles from dry soils could not be generated due to low DNA yields. (b) Daily precipitation at the Hopland site between 2018 and 2021. Dotted vertical lines mark the dates of soil sample collection for the main (2020) and complementary (2019) wet-up experiments reported in this study, as well as the wet-up experiment from 2018 reported in Nicolas et al., 2022. Black horizontal lines highlight the period since the most recent ≥ 5 mm rainfall event preceding each soil sample collection time point. Gaps in the trend line between 2018 and 2019 indicate missing data from the weather station.

Extended Data Fig. 5 Abundance of temperate phages in soil viromes.

(a) Euler diagram displaying the distribution of genomic traits used to identify the set of 1146 vOTUs predicted to be temperate phages. (b, c) Temporal trends of predicted temperate phages (phages putatively capable of lysogeny) and phages not predicted to be temperate in viral communities by soil type. Trends for all vOTUs are separated according to their temperate phage prediction (true = predicted temperate phage, false = not predicted to be temperate). For each time point, panel (b) shows aggregated vOTU relative abundances (based on read mapping-derived coverage), and panel (c) shows the percentage of total vOTUs detected. Points are individual samples, and trend lines track the mean values among replicates.

Extended Data Fig. 6 Differences in temporal turnover of viral and prokaryotic communities.

a) Percentage of MAGs (left) and vOTUs (right) detected at each occupancy level (number of post-wet-up time points) in total metagenomes and viromes, respectively. (b) Pairwise Jaccard similarities of MAG communities profiled in total metagenomes (left) and vOTU communities profiled in DNase-treated and untreated viromes (right). The x-axis and y-axis are the same, such that the diagonal from lower left to upper right for each facet indicates pairwise community similarity among technical replicates, and other comparisons are between microcosms at different time points.

Extended Data Fig. 7 Abundance of temporally dynamic vOTUs in soil viromes.

(a) Changes in the aggregated abundances of vOTUs in each trend group. (b) Upset plot displaying the temporal groups assigned to vOTUs detected as differentially abundant across multiple soils: light gray vertical bars correspond to vOTUs displaying the same temporal trend across soil types, while dark gray vertical bars correspond to vOTUs displaying different temporal trends across soil types.

Extended Data Fig. 8 Viral taxonomic network analyses.

(a) Distribution of local network neighborhoods with a significant overrepresentation (blue points) or underrepresentation (red points) of vOTUs assigned to a particular trend group (adjusted p-value < 0.05, hypergeometric test). Each colored point denotes the center of a significant local neighborhood, and the color gradient indicates the extent of the significance of the overrepresentation or underrepresentation of the temporal group in that neighborhood. (b) Distribution of predicted hosts in the gene-sharing network. For each vOTU (node), the predicted host phylum is indicated. For (a, b), the network layout was constructed with the Fruchterman-Reingold algorithm, based on pairs of vOTUs (nodes) with a significant overlap in their predicted protein content. (c) Distribution of predicted host phyla in each of three vOTU temporal groups. For the subset of vOTUs with an assigned host, cell color indicates percentage of vOTUs classified as infecting a particular phylum in each temporal trait group. (d) Set of predicted host phyla significantly overrepresented or underrepresented in each vOTU temporal group (adjusted p-value < 0.05, hypergeometric test).

Extended Data Fig. 9 Taxonomic trends displayed by the set of temporally dynamic MAGs.

(a) Taxonomic composition of MAG temporal groups. (b) Set of MAG phyla significantly overrepresented or underrepresented in each MAG temporal group (adjusted p-value < 0.05, hypergeometric test).

Extended Data Fig. 10 Taxonomic trends displayed by the set of temporally dynamic ASVs.

(a) Temporal trends in the abundances of differentially abundant ASVs in total DNA profiles from all four soils. Colored trend lines represent the z-transformed mean abundances of single ASVs across time points, bold black trend lines correspond to the mean abundances. (b) Taxonomic composition of ASVs temporal groups. (c) Set of ASV phyla significantly overrepresented or underrepresented in each ASV temporal group (adjusted p-value < 0.05, hypergeometric test).

Supplementary information

Supplementary Information

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Supplementary Tables

Supplementary Tables 1–9.

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Santos-Medellín, C., Blazewicz, S.J., Pett-Ridge, J. et al. Viral but not bacterial community successional patterns reflect extreme turnover shortly after rewetting dry soils. Nat Ecol Evol 7, 1809–1822 (2023). https://doi.org/10.1038/s41559-023-02207-5

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