Microbiome structure variation and soybean's defense responses during flooding stress and elevated CO2

Abstract

Introduction: With current trends in global climate change, both flooding episodes and higher levels of CO₂ have been key factors to impact plant growth and stress tolerance. Very little is known about how both factors can influence the microbiome diversity and function, especially in tolerant soybean cultivars. This work aims to (i) elucidate the impact of flooding stress and increased levels of CO₂ on the plant defenses and (ii) understand the microbiome diversity during flooding stress and elevated CO₂ (eCO₂).

Methods: We used next-generation sequencing and bioinformatic methods to show the impact of natural flooding and eCO₂ on the microbiome architecture of soybean plants' below- (soil) and above-ground organs (root and shoot). We used high throughput rhizospheric extra-cellular enzymes and molecular analysis of plant defense-related genes to understand microbial diversity in plant responses during eCO₂ and flooding.

Results: Results revealed that bacterial and fungal diversity was substantially higher in combined flooding and eCO₂ treatments than in non-flooding control. Microbial diversity was soil>root>shoot in response to flooding and eCO₂. We found that sole treatment of eCO₂ and flooding had significant abundances of Chitinophaga, Clostridium, and Bacillus. Whereas the combination of flooding and eCO2 conditions showed a significant abundance of Trichoderma and Gibberella. Rhizospheric extra-cellular enzyme activities were significantly higher in eCO₂ than flooding or its combination with eCO₂. Plant defense responses were significantly regulated by the oxidative stress enzyme activities and gene expression of Elongation factor 1 and Alcohol dehydrogenase 2 in floodings and eCO₂ treatments in soybean plant root or shoot parts.

Conclusion: This work suggests that climatic-induced changes in eCO₂ and submergence can reshape microbiome structure and host defenses, essential in plant breeding and developing stress-tolerant crops. This work can help in identifying core-microbiome species that are unique to flooding stress environments and increasing eCO₂.

Keywords: climatic CO2; diversity; flooding stress; gene expression; microbiome; oxidative stress; soybean.

Figure 1

Influence of eCO₂ and flooding on the oxidative stress-related enzymes and biochemicals. PPO, SOD, CAT, and Glut were assessed from the leaf and root parts of the soybean plants treated with eCO₂, flooding, and eCO₂ + flooding and compared with non-flooded control plants. The values in the bar are the mean values of three replicates and show standard deviation. The bars showing *, **, and **** are significantly different (p<0.05) in their content compared with the control as analyzed by two-way ANOVA.

Figure 2

The microbiome diversity indices of soybean plants are treated with flooding stress with or without exposure to eCO₂. The results are compared with non-flooded control soybean plants, represented in blue. Treatment with eCO₂, flooding with eCO₂, and flooding are represented with red, green, and yellow, respectively. (A, B) The bacterial (16S) and fungal (ITS) Shannon diversity indices of rhizospheric soil across treatments compared with the control. (C, D) The bacterial and fungal diversity of root parts of soybean plants treated with flooding stress and eCO₂. (E, F) The bacterial and fungal diversity of shoot parts of soybean plants exposed to flooding and eCO₂ compared with control plants. The data analyzed represent three replicates for each treatment (control, floodings, eCO₂, and flooding + eCO₂).

Figure 3

Bacterial biome diversity and phyla abundance across different treatments. The Bray–Curtis statistical analysis was used to determine bacterial microbiome variation during flooding, eCO₂, and flooding + eCO₂ and compared with the control. The bacterial biome of the host organ in terms of rhizosphere and endosphere was analyzed.

Figure 4

Fungal biome diversity and phyla abundance across different treatments. The Bray–Curtis statistical analysis was used to determine bacterial microbiome variation during flooding, eCO₂, and flooding + eCO₂ and compared with the control. The bacterial biome of the host organ in terms of rhizosphere and endosphere was analyzed.

Figure 5

Genus-level microbiome diversity and abundance during flooding and eCO₂ treatments. The heatmap shows the top 20 microbiome species in the rhizosphere (soil) and endosphere (root and shoot).

Figure 6

Phylogenetic clustering and interaction of different microbiome players from key phyla, their distribution during flooding, and eCO₂ treatments. (A) shows the bacterial and (B) shows fungal phylogenetic clustering. The color distribution depicts the abundance pattern of OTUs across different treatments and their interactions. The outer circle shows the abundance levels (from light yellow to dark green), and the inner circle shows the dominance of specific microbiome players in different conditions.

Figure 7

Extracellular enzymatic activities in rhizospheric soil of soybean plants treated with flooding and eCO₂. The treatments were compared with the control (non-flooding). The values represent the mean values of three replicates and show standard deviation. The bars showing *, **, *** and **** are significantly different (p<0.05) in their content compared with the control as analyzed by two-way ANOVA analysis. “ns” shows that values are insignificant compared with control treatments.

Figure 8

mRNA gene expression related to oxidative stress (A), flooding (B), and eCO₂ (C) of soybean plants treated with flooding and eCO₂. The treatments were compared with the control (non-flooding). The values represent the mean values of three replicates and show the standard deviation of relative expression to housekeeping genes and control. The bars showing * and ** are significantly different (p<0.05) in their content compared with the control as analyzed by two-way ANOVA analysis. “ns” shows that values are insignificant compared with control treatments.