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Microscale analysis of soil characteristics and microbiomes reveals potential impacts on plants and fruit: vineyard as a model case study

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Abstract

Aims

Soil microbiome roles in agriculture is becoming more and more important. This importance is also reflected on the way plants are seen: complex organisms formed by the plant itself plus the microbes inhabiting its tissues, including the ones on the surface of every organ and the ones adhered or in proximity to the roots. In addition, as already demonstrated, the microbial community associated with a specific soil is able to predetermine the health status of crops. For all the above mentioned reasons, defining the microbial composition of agricultural soils and the factors driving the assemblage is pivotal to achieve more sustainable agriculture and viticulture.

Methods

We aimed to investigate how the soil geological characteristics influence the microbiome composition associated with close geographically related vineyards. Moreover, we studied both the top (15 cm in depth) and deep (120 cm in depth) soil layers as anthropically influenced and almost-undisturbed soil, respectively.

Results

We observed slightly different microbial communities despite the close geographical proximity of the two vineyards, which is considered one of the main determinants of the soil microbiome composition. In addition, we found that the geological characteristics of the two soils influence both the root distribution and the accumulation of pathogen- and symbiont-related genera. Sensory profiles of the Grillo wines from the two different soils confirmed the tight link between soil origin and wine traits.

Conclusions

In the present study, we highlight that the geological characteristics of soil can influence soil microbial composition and assemblage in close geographically related vineyards, with a potential effect on wine features.

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Data availability

The SRA accession numbers of the NGS reported in this paper are deposited in NCBI under the BioProject PRJNA655455; BioSample SAMN15735114 and SAMN15735115; SRA accession SRR12436974 and SRR12436973.

Code availability

Not applicable.

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Acknowledgements

The Fig. 6 was created with BioRender.com.

Funding

Part of the work was supported by Settesoli winery S.C.A. Menfi (AG) Sicily (IT) and by the BIOPROME in the frame of the DiBio project founded by the Italian Ministry of Agriculture.

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Authors and Affiliations

  1. Council for Agricultural Research and Economics – Research Centre for Viticulture and Enology CREA-VE, Via XXVIII Aprile 26, 31015, Conegliano, TV, Italy

    Luca Nerva, L. Moffa, G. Giudice, D. Tomasi & Walter Chitarra

  2. Institute for Sustainable Plant Protection, CNR, Strada delle Cacce 73, 10135, Torino, Italy

    Luca Nerva & Walter Chitarra

  3. Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, Via delle Scienze 206, 33100, Udine, Italy

    L. Moffa

  4. Department of Agricultural and Environmental Sciences - Production, Landscape, Agroenergy (DiSAA), University of Milano, Via Celoria 2, 20133, Milano, Italy

    G. Giudice

  5. PhD on Earth Science and Professional Geologist, via Francesco Cilea, 97, 90144, Palermo, Italy

    A. Giorgianni

Authors
  1. Luca Nerva
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  2. L. Moffa
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  3. G. Giudice
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  4. A. Giorgianni
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  5. D. Tomasi
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  6. Walter Chitarra
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Contributions

L.N. and W.C. designed the experimental system, carried out the wet lab experiments, analysed data and wrote the manuscript draft. D.T., L.N. and W.C. worked out vine roots system. D.T. analysed wines sensory description. D.T., A.G, L.M. and G.G. helped to design the experiments, contributed to the writing and carefully revised the manuscript.

Corresponding authors

Correspondence to Luca Nerva or Walter Chitarra.

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Responsible Editor: Birgit Mitter.

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D. Tomasi and Walter Chitarra equally contributed as senior authors.

The SRA accession numbers of the NGS reported in this paper are deposited in NCBI under the BioProject PRJNA655455; BioSample SAMN15735114 and SAMN15735115; SRA accession SRR12436974 and SRR12436973.

Supplementary Information

Figure S1.

PCoA representing the four soil samples analysed for 16S sequences (n=3). (PPTX 2244 kb)

Figure S2.

NMDS algorithm based on Bray-Curtis distances matrixes were used to reduce into a bi-dimensional scaling data obtained for bacteria (A), fungi (B) and the overall microbial community (C) (n=3). (PPTX 315 kb)

Figure S3.

Cluster heatmap built using data of both 16S and ITS amplicon sequencing to highlight relationship among samples. (PDF 36 kb)

Figure S4.

Significant co-occurrence network of bacterial communities and interactions among OTUs in soil samples. The nodes are sized according to degree of connection (Supplementary Table 11). Green lines indicate that there are co-occurrence interactions and red lines indicate mutualistic exclusions (n=3). (PPTX 106 kb)

Figure S5.

Significant co-occurrence network of fungal communities and interactions among OTUs in soil samples. The nodes are sized according to degree of connection (Supplementary Table 12). Green lines indicate that there are co-occurrence interactions and red lines indicate mutualistic exclusions (n=3). (PNG 98902 kb)

High Resolution Image (TIF 14783 kb)

Figure S6.

Significant co-occurrence network of both bacterial and fungal communities considered together and interactions among OTUs in soil samples. The nodes are sized according to degree of connection (Supplementary Table 13). Green lines indicate that there are co-occurrence interactions and red lines indicate mutualistic exclusions (n=3). (PNG 207531 kb)

High Resolution Image (TIF 41522 kb)

Figure S7

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Nerva, L., Moffa, L., Giudice, G. et al. Microscale analysis of soil characteristics and microbiomes reveals potential impacts on plants and fruit: vineyard as a model case study. Plant Soil 462, 525–541 (2021). https://doi.org/10.1007/s11104-021-04884-2

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