Effects of Insect-Resistant Maize HGK60 on Community Diversity of Bacteria and Fungi in Rhizosphere Soil

Abstract

The influence of biotech crops on microbial communities in rhizosphere soil is an important issue in biosafety assessments. The transgenic maize HGK60 harboring the Bt cry1Ah gene enhanced the resistance to lepidopteran pests, while the ecological risk of HGK60 maize on rhizosphere microorganisms is unclear. In this study, we comprehensively analyzed the diversity and composition of bacterial and fungal communities in the rhizosphere soil around Bt maize HGK60 and the near-isogenic non-Bt maize ZD958 at four growth stages via a high-throughput sequencing technique. The results showed that HGK60 maize unleashed temporary effects on the bacterial and fungal diversity and richness during the study plant's development, which would be restored after one cycle of plant cultivation due to the application of the same agricultural management. The differences of bacterial and fungal communities were marked by seasonality, while the different growth stage was the important factor as opposed to the cultivar contributing to the shifts in the bacterial and fungal communities' structure. This study will provide useful information regarding the impact of Bt transgenic maize on the soil microbiome and a theoretical basis for the development of a safety assessment approach for Bt maize in China.

Keywords: bacterial community composition; cry1ah transgenic maize; fungal community composition; illumina novaseq PE250 sequencing; risk assessment.

Figure 1

Rarefaction analysis. The rarefaction curve of the operational taxonomic units (OTUs) obtained from 16S rDNA (A) and ITS (B) amplicon sequencing in the rhizosphere of HGK60 and ZD958. The curves were named in the following form: “growth stage_cultivar_replicate”. HS—heading stage, MS—milk stage, DS—dough stage, PH—post-harvest stage, A—HGK60, and B—ZD958.

Figure 2

The composition of bacterial community in the rhizosphere soil of HGK60 and ZD958. (A) Venn diagram showing variable overlaps between HGK60 and ZD958; (B) Venn diagram showing variable overlaps between four growth stages; (C) relative read abundance of bacterial phyla within the communities. The numbers in (A) and (B) within the circles represent the operational taxonomic units (OTUs) numbers. HS—heading stage, MS—milk stage, DS—dough stage, and PH—post-harvest stage.

Figure 3

The identification of bacterial biomarkers resulting in the difference in composition of rhizosphere bacteria between HGK60 and ZD958 at early stages. (A,B) The bacterial biomarkers of HGK60 and ZD958 at the heading stage and milk stage; (C) the relative abundance of bacterial biomarkers. HS—heading stage, MS—milk stage, DS—dough stage, and PH—post-harvest stage. ** p value < 0.01.

Figure 4

The composition of fungal community in the rhizosphere soil of HGK60 and ZD958. (A) Venn diagram showing variable overlaps between HGK60 and ZD958; (B) Venn diagram showing variable overlaps between four growth stages; (C) relative read abundance of fungal phyla classes within the communities. The numbers in (A,B) within the circles represent the operational taxonomic units (OTUs). HS—heading stage, MS—milk stage, DS—dough stage, and PH—post-harvest stage.

Figure 5

Effects of cultivar and stage on the rhizosphere bacterial and fungal communities. (A,B) Non-metric multidimensional scaling (NMDS) of bacterial and fungal community structures between cultivars, respectively; (C,D) variance-partitioning analysis (VPA) of the effects of cultivar, growth stage, and the interactions among these factors on the bacterial and fungal community structure. Circles show the percentage of variation caused by each factor alone. The unexplained variation is depicted in the squares at the bottom of the figure; (E,F) variance-partitioning analysis (VPA) of the effects of cultivar, growth stage, and the interactions among these factors on the bacterial and fungal community structures, respectively. ** p value < 0.01. * p value < 0.05.

Figure 6

Linear discriminant analysis effect size (LEFSE) was employed based on the 10 compartments of data to identify the bacterial (A) and fungal (B) community biomarkers.