Microbial succession during the degradation of bioplastic in coastal marine sediment favors sulfate reducing microorganisms

Marine environments are sinks for many contaminants, including petroleum-based plastic waste. Bioplastics, or biodegradable plastics derived from renewable resources, are considered promising alternatives as numerous studies have demonstrated their degradation in marine environments. However, their rates of degradation vary and microbial consortia responsible for its degradation are not well characterized. Previous research by our group has shown that polyhydroxyalkanoate (PHA) stimulates sulfate reducing microorganisms (SRM), enriches sulfate reduction gene pools, and accumulates antibiotic and metal resistance genes. Here, we quantify the degradation rate of PHA pellets in marine sediment and present the long-term temporal changes in PHA-associated SRM communities over 424 days. For comparative purposes, polyethylene terephthalate (PET) and ceramic served as biofilm controls and the free-living microorganisms in the overlying water column served as a non-biofilm control. PHA experienced a 51% mass loss after 424 days and a generalized additive mixed model predicted that 100% mass loss would require 909 days. Throughout the course of the 424-day exposure, PHA was colonized by a distinct microbial community while PET and ceramic were colonized by similarly structured communities. SRM comprised a larger proportion of the overall community (25 – 40%) in PHA-associated biofilms as compared to PET and ceramic controls across all timepoints. Further, the diversity of SRM was greater within PHA biofilms than PET and ceramic biofilms. This study shows that PHA degrades relatively slowly and promotes a long-term shift in microbial community structure toward sulfate reduction, demonstrating the ability of this manufactured polymer to alter its environment via the disruption of biogeochemical cycling, indicating that PHA rises to the level of pollutant in benthic marine systems.This study was funded by the Texas General Land Office Coastal Management Program (GLO-CMP), the Texas Research and Development Fund (TRDF), Texas Sea Grant (TSG), and the National Sciences and Engineering Research Council of Canada (NSERC). The majority of computational data analysis was performed on TAMU-CC’s high-performance computing cluster, which is funded in part by the National Science Foundation’s CNS MRI Grant (No. 1429518)