Abstract
AbstractMicrobial iron and sulfate reduction are the primary drivers of coastal acid sulfate soil (CASS) passive bioremediation schemes. Microbial sulfate reduction is the limiting step for pyrite formation, a desirable endpoint for CASS remediation. Little is known, however, about the impacts of microbial activity or species interaction on long-term iron and sulfur cycling in CASS ecosystems. Using a combination of molecular biology, geochemical speciation and artificial intelligence-powered computational modeling, we deduced from microbial activity patterns (RNA-based) and geochemical measurements a best-fit equation for predicting biogeochemical pyrite formation in a model CASS ecosystem. In addition to the time-dependent activities of key sulfate-reducing prokaryotic taxa (e.g. Desulfobacteraceae), this equation required methylotrophs (Methylobacteriaceae) and bacterial predators (Bacteriovorax) for best-fitting, suggesting that specific microbial interactions exert meaningful influences on CASS bioremediation efficiency. Our findings confirmed that CASS microorganisms act as an assemblage in response to rewetting by tidewater. Accurate predictions of long-term CASS bioremediation efficiency require modelling of complex and interdependent relationships between geochemical speciation and microbial activity.HighlightsCoastal acid sulfate soil (CASS) is a global environmental issue.Microbial activity can be modelled quantitatively to predict CASS remediation.Sulfate-reducing prokaryotes (SRP) play a key role in CASS remediation.Predation on SRP with cultured representatives occurred during early wet-up.The above mechanism leads to increased activity among uncultured SRP.
Publisher
Cold Spring Harbor Laboratory