Metagenomic Analyses of Plant Growth-Promoting and Carbon-Cycling Genes in Maize Rhizosphere Soils with Distinct Land-Use and Management Histories

Abstract

Many studies have shown that the maize rhizosphere comprises several plant growth-promoting microbes, but there is little or no study on the effects of land-use and management histories on microbial functional gene diversity in the maize rhizosphere soils in Africa. Analyzing microbial genes in the rhizosphere of plants, especially those associated with plant growth promotion and carbon cycling, is important for improving soil fertility and crop productivity. Here, we provide a comparative analysis of microbial genes present in the rhizosphere samples of two maize fields with different agricultural histories using shotgun metagenomics. Genes involved in the nutrient mobilization, including nifA, fixJ, norB, pstA, kefA and B, and ktrB were significantly more abundant (α = 0.05) in former grassland (F1) rhizosphere soils. Among the carbon-cycling genes, the abundance of 12 genes, including all those involved in the degradation of methane were more significant (α = 0.05) in the F1 soils, whereas only five genes were significantly more abundant in the F2 soils. α-diversity indices were different across the samples and significant differences were observed in the β diversity of plant growth-promoting and carbon-cycling genes between the fields (ANOSIM, p = 0.01 and R = 0.52). Nitrate-nitrogen (N-NO3) was the most influential physicochemical parameter (p = 0.05 and contribution = 31.3%) that affected the distribution of the functional genes across the samples. The results indicate that land-use and management histories impact the composition and diversity of plant growth-promoting and carbon-cycling genes in the plant rhizosphere. The study widens our understanding of the effects of anthropogenic activities on plant health and major biogeochemical processes in soils.

Role of Agricultural Management in the Provision of Ecosystem Services in Warm Climate Vineyards: Functional Prediction of Genes Involved in Nutrient Cycling and Carbon Sequestration

“…There is also strong evidence for the relationship between nitrogen fixation and sustainable agriculture [ 41 ], including lower numbers of nif genes and free-living nitrogen-fixing bacteria under inorganic N fertilization and no tillage [ 42 , 43 , 44 ]. In the present study, organic inputs from both cover vegetation and organic amendments did not improve the number of predicted genes involved in N fixation.…”

Response of bacterial community characteristics in the rhizosphere soil of Stellera chamaejasme L. to its expansion on the Qinghai‐Tibet Plateau

“…This may be why the Proteobacteria, particularly the genus associated with nutrient cycling and promoting plant growth, are identified as a biomarker. Microbacteriaceae is characterized by their ability to colonize the plant rhizosphere and mobilize soil nutrients, promoting nutrient absorption and plant growth (Chukwuneme et al, 2021).…”

Bioinformatics approaches and applications in plant biotechnology

“…Through metagenomics approaches, the soil microorganism community that contributed to plant growth may provide a great genomic insight into physiology and pathology [50][51][52][53]. In metagenomics approaches, the overall genetic materials obtained from soil are sequenced and advancing to microbial community analysis via data analytics [53][54][55]. The extracted genetic materials from the soil were subjected to high-throughput metagenomics analysis via various NGS approaches such as 16S rRNA sequencing, shotgun metagenomic sequencing, MiSeq sequencing [54][55][56] for microbial species identification, functional genomics study, and structural metagenomic analysis.…”

“…In metagenomics approaches, the overall genetic materials obtained from soil are sequenced and advancing to microbial community analysis via data analytics [53][54][55]. The extracted genetic materials from the soil were subjected to high-throughput metagenomics analysis via various NGS approaches such as 16S rRNA sequencing, shotgun metagenomic sequencing, MiSeq sequencing [54][55][56] for microbial species identification, functional genomics study, and structural metagenomic analysis. A NGS produces huge genomics data for each study; thus, application of bioinformatics tools would add value in the metagenomics analysis as the target genes identified could advance into elucidation of plant growth, plant disease, soil contamination, and microbial taxonomy [52].…”