Sugarcane cultivation practices modulate rhizosphere microbial community composition and structure

Abstract

Sugarcane (Saccharum spp.) represents a crop of great economic importance, remarkably relevant in the food industry and energy supply chains from renewable sources. However, its conventional cultivation involves the intensive use of fertilizers, pesticides, and other agrochemical agents whose detrimental effects on the environment are notorious. Alternative systems, such as organic farming, have been presented as an environmentally friendly way of production. Still, the outcomes of different cropping systems on the microbiota associated with sugarcane-whose role in its health and growth is crucial-remain underexplored. Thus, we studied the rhizospheric microbiota of two adjacent sugarcane fields, which differ in terms of the type of farming system. For this, we used the sequencing of taxonomic markers of prokaryotes (gene 16S rRNA, subregions V3-V4) and fungi (Internal transcribed spacer 2) and evaluated the changes caused by the systems. Our results show a well-conserved microbiota composition among farming systems in the highest taxonomic ranks, such as phylum, class, and order. Also, both systems showed very similar alpha diversity indices and shared core taxa with growth-promoting capacities, such as bacteria from the Bacillus and Bradyrhizobium genera and the fungal genus Trichoderma. However, the composition at more specific levels denotes differences, such as the separation of the samples concerning beta diversity and the identification of 74 differentially abundant taxa between the systems. Of these, 60 were fungal taxa, indicating that this microbiota quota is more susceptible to changes caused by farming systems. The analysis of co-occurrence networks also showed the formation of peripheral sub-networks associated with the treatments-especially in fungi-and the presence of keystone taxa in terms of their ability to mediate relationships between other members of microbial communities. Considering that both crop fields used the same cultivar and had almost identical soil properties, we conclude that the observed findings are effects of the activities intrinsic to each system and can contribute to a better understanding of the effects of farming practices on the plant microbiome.

Figure 1

Distribution of the 8 most abundant prokaryotic phyla (A) and distribution of the 15 most abundant bacterial orders in the sugarcane rhizosphere of the organic (ORZ) and conventional (CRZ) farming systems (B).

Figure 2

Distribution of the 5 most abundant fungal phyla (A) and distribution of the 15 most abundant fungal orders in the sugarcane rhizosphere of the organic (ORZ) and conventional (CRZ) farming systems (B).

Figure 3

Alpha diversity indices for the 16S (Bacteria) and ITS (Fungi) datasets of the organic and conventional sugarcane rhizosphere soil. The measures were statistically compared using the Wilcoxon nonparametric test of means, considering a p-value ≤ 0.1. as statistically significant (*).

Figure 4

Dendrogram resulting from the hierarchical grouping of 16S rRNA samples from rhizospheric soil (A). Principal Coordinate Analysis (PCoA), based on the Bray–Curtis index of 16S rRNA samples from rhizospheric soil (B). Distance matrices were used for statistical comparison between the systems by a PERMANOVA analysis, considering a p-value ≤ 0.1.

Figure 5

Dendrogram resulting from the hierarchical grouping of ITS samples of rhizospheric soil (A). Principal Coordinate Analysis (PCoA), based on the Bray–Curtis index of ITS samples of rhizospheric soil (B). Distance matrices were used for statistical comparison between the systems by a PERMANOVA analysis, considering a p-value ≤ 0.1.

Figure 6

Core microbiome analysis of sugarcane rhizosphere. High prevalence prokaryotic taxa (> 90%) in the rhizosphere samples, regardless of the farming system, where the blue color indicates the prevalence of taxa in the samples and the horizontal percentage represents the relative abundance of each taxon in the respective sample. The taxonomic level can be identified by the prefixes: “p” (phylum), “c” (class), “o” (order), “f” (family), and “g” (genus).

Figure 7

Core rhizosphere sugarcane microbiome analysis. High prevalence fungal taxa (> 90%) in the rhizosphere samples, regardless of the farming system, where the blue color indicates the prevalence of taxa in the samples and the horizontal percentage represents the relative abundance of each taxon in the respective sample. The taxonomic level can be identified by the prefixes: “p” (phylum), “c” (class), “o” (order), “f” (family), and “g” (genus).

Figure 8

Differently abundant prokaryotic taxa between conventional (CRZ) and organic (ORZ) farming systems present in the sugarcane rhizosphere microbiota, through statistical verification by the Wald test, considering a p-value ≤ 0.01.

Figure 9

Differently abundant fungal taxa between conventional (CRZ) and organic (ORZ) farming systems present in the sugarcane rhizosphere microbiota, through statistical verification by the Wald test, considering a p-value ≤ 0.01.

Figure 10

Metabolic pathways of prokaryotes, differentially enriched in the sugarcane rhizosphere in the organic versus conventional farming system. The White’s t-test was used for significance evaluation, considering a p-value ≤ 0.05 as statistically significant. The pathways in red represent the conventional system and in green, the organic one.

Figure 11

Metabolic pathways of fungi, differentially enriched in the sugarcane rhizosphere in the organic versus conventional farming system. The White’s t-test was used for significance tests, considering a p-value ≤ 0.05 as statistically significant. The pathways in red represent the conventional system and in green, the organic one.

Figure 12

Co-occurrence network of prokaryotic genera present in conventional and organic farming systems. The circles are proportional to the sums of the relative abundance of each genus. The color indicates the relative abundance in the conventional (red) and organic (green) systems. Gray lines are indicative of positively correlated connections between genera, while blue lines are negatively correlated connections. The measures of centrality of the treatments were statistically compared, using the parameters of minimum correlation =  ± 0.5 and p-value ≤ 0.05.

Figure 13

Co-occurrence network of fungal genera present in conventional and organic farming systems. The circles are proportional to the sums of the relative abundance of each genus. The color indicates the relative abundance in the conventional (red) and organic (green) systems. Gray lines are indicative of positively correlated connections between genera, while blue lines are negatively correlated connections. The measures of centrality of the treatments were statistically compared, using the parameters of minimum correlation =  ± 0.5 and p-value ≤ 0.05.