Establishing the networks of phosphorus cycling microbes in California agriculture: A metagenomic investigation
Establishing the networks of phosphorus cycling microbes in California agriculture: A metagenomic investigation

Most agricultural soils have depleted pools of plant-available phosphorus (Pav) or are saturated with occluded forms of phosphorus (P) due to excessive use of inorganic P fertilizers to meet the demands of plant growth and development. The inefficacy of common P fertilizers, compounded with shifting geopolitical P markets and dwindling P reserves, necessitates strategies to increase Pav and phosphorus use efficiency (PUE) to improve resource management. Although promising, biostimulants containing single-strain phosphorus-solubilizing microbes (PSM) have shown variable to poor efficacy in-field, raising questions about the ecological relevance of a high solubilizing capacity. Microbial mechanisms for transforming occluded P extend far beyond the solubilization of inorganic P, and recent advancements in metagenomics and high-resolution technology have revealed the diverse complexity of phosphorus cycling microbes (PCM) Hence, we aim to investigate PCM community structure, P-species distribution, and differential energy investment strategies of PCM at key spatial gradients of depth and root association in two commercial almond orchards in California. Our goal is to identify the parameters that inform the relevance and utility of specific P-cycling genes (PCGs), which have the potential to be used downstream in biostimulant research and development. Using next-generation metagenomic sequencing along with the most current and robust PCG databases available, and total reflection X-ray spectrometry (TXRF) for P-speciation, our continuing research aims to address the following hypotheses: H1: PCG family abundance will proportionally co-occur with the abundance of P-species found along each spatial gradient, but PCG diversity will reflect the broader microbial community's differential energy strategies. H2: Energy investment strategies will follow the spatial root-association gradient. Specifically, extracellular metabolic traits will increase with distance from the root, while intracellular metabolic traits will decrease.