Potential biases from data sources
The meta-analysis relies on published 16S rRNA amplicon sequencing data, which can be influenced by various factors such as sequencing platforms, primer selection, and experimental methodologies. These variations might introduce biases and affect the overall results.
Limitations of predictive tools
The study uses predictive tools like FAPROTAX and PICRUSt2 to infer functional potentials and dormancy strategies, but predictions may not fully reflect the actual functional capabilities of the microorganisms.
Context-dependent effects
While the study provides a global perspective on rhizosphere bacteriome characteristics, specific environmental factors such as soil type, plant species, and climate may exert considerable influence on the microbial community structure and function. More research is needed to understand how these factors interact and modulate the observed patterns.
Limited scope of microbial community
The study focuses primarily on bacteria, while other members of the rhizosphere microbiome, such as fungi, archaea, and protists, also play important roles in ecosystem functioning. Further investigations encompassing the entire rhizosphere community are essential for a more holistic understanding.