Developing an efficient expression system for phytase-like proteins to unveil marine phytoplankton adaptations to phosphorus scarcity

Abstract

[eng] Marine phytoplankton, such as Prochlorococcus and the diatom Phaeodactylum tricornutum, play a vital role as primary producers in oligotrophic oceanic regions. Their ability to thrive in nutrient-poor environments, particularly phosphorus-depleted waters, is crucial for sustaining marine productivity. Phosphorus is a key nutrient that often limits phytoplankton growth, prompting the need for unique adaptive mechanisms. Despite the recognized importance of phosphorus, the precise molecular tools employed by these microorganisms to cope with phosphorus scarcity are not well understood. Among the myriad known unknown proteins found in databases, the highly abundant secreted phytase-like enzymes from Prochlorococcus MED4 and Phaeodactylum tricornutum stand out as intriguing and ecologically significant niche-specific genes. This research endeavors to enhance an expression system to produce recombinant proteins utilizing Pichia pastoris as the host organism. Critical optimizations encompassed the linearization of DNA, transformation procedures, purification protocols, PCR cycling conditions, and expression parameters. The outcomes of this investigation reveal that these phytase-like proteins are highly expressed in phosphorus-depleted marine environments, such as the Mediterranean Sea and the North Atlantic Ocean, as determined through the interrogation of TARA Oceans metagenomic and transcriptomic datasets with Hidden Markov Model (HMM) profiles. Additionally, initial structural and functional characterizations were performed using the AlphaFold AI tool, yielding valuable insights into their potential biological roles. Deciphering the functions of these phytase-like genes is pivotal for elucidating the cellular responses of marine phytoplankton to phosphorus stress. Furthermore, the robust expression system that has been implemented and optimized during this work will enable future functional analyses required to characterize the extensive array of predicted proteins, potentially aiding in the unravelling of ecologically relevant genes.