Context. Activated sludge process, which is a biological wastewater treatment process, has a history of over 100 years, and has been also applied for the treatment of coke-oven wastewater discharged from steelmaking industry. Recent advances in molecular approach such as next-generation sequencing technology have revealed the presence of the complex and diverse microbial community in the process.
Gap. However, the relationship between the performance of activated sludge process and microorganisms has not been specified yet due to the complex community, so called "big-data". Thus, the microorganisms responsible for the wastewater treatment have been regarded as a black box, which is one of the reasons for the instability of the process.
Aim. Therefore, we developed a statistical method for identification of microorganisms responsible for wastewater treatment
Methods. By applying a transdisciplinary approach integrating microbiology and mathematics, the novel statistical method was developed. The method has been validated by using water quality and microbial community data obtained from a laboratory-scale moving bed biological reactor fed with synthetic coke-oven wastewater.
Findings. We developed a novel statistical method in combination with least absolute shrinkage and selection operator (LASSO) and the bootstrap method. The method successfully identified important microorganism responsible for laboratory-scale wastewater treatment process.
Utilization. This method is expected to contribute to the further stabilization and efficiency of biological wastewater treatment processes.
