We characterized the effects of crop residue derived biochar on tomato growth, soil microbial diversity, and rhizosphere-level gene expression responses in an organic production system. Shoot fresh biomass and fruit yield were assessed at the end of the growing cycle. The corresponding transcriptomic response of the roots, the soil microbial community profiles, and the active transcripts within the communities were quantified using a metatranscriptomic approach at four different developmental stages of the plant.
Biochar treatment did not impact shoot biomass or fruit production; however, metatranscriptome analysis revealed that the gene expression activity of the tomato rhizosphere changes over time in response to the biochar treatment, with a number of bacteria with known benefits to soil health and plant growth displaying increased gene expression e.
Streptomycetaceae were expressed at the highest levels in the rhizosphere. Biochar seemed to attenuate the expression of this bacteria by the end of the time course, possibly due to the rise in competition for resources driven by the increased activity of other beneficial microbes.
Notably, pathogenic fungi in the soil displayed generally reduced expression in the biochar-amended rhizosphere in comparison with the control. In addition to the assessment of the rhizosphere microbiome, transcriptome analysis and gene ontology analysis of tomato roots revealed functional enrichment of genes associated with nitrogen metabolic processes, regulation of metabolic processes, and production of organic compounds in the biochar treated rhizosphere.
Together, these results suggest that biochar amendment enhances gene expression of beneficial soil microbes, and also impacts gene expression in the plant roots, which may in turn lead to improvements in soil and plant health. The results of this study provide foundations and a methodology for using metatranscriptomic approaches to investigate the impacts of biochar or other soil amendments in different crops, varying soil types, and with greater experimental complexity.
