Unlocking sustainability: Integrating omics for advanced wastewater treatment

Owing to the urgent and escalating environmental crisis of water pollution through anthropogenic wastewater generated from various sources, the development of novel and innovative bioremediation strategies that are equally sustainable is highly necessitated. The present study embarks on an integrated omics-based exploration, complemented by a thorough literature synthesis, to critically evaluate and enhance hybrid algal-bacterial systems for effective wastewater treatment. Drawing on case studies and research from diverse geographic regions, we explore how these technologies inform the design and optimization of both engineered and natural treatment systems. The review emphasizes the integration of multi-omics data to support sustainable, targeted bioremediation strategies and underscores the cross-disciplinary convergence of environmental engineering, molecular biology, and systems ecology. This global and holistic perspective positions omics as a cornerstone for advancing the next generation of wastewater treatment solutions. Comprehensive analyses of the efficacies of different treatment methods used to remediate organic pollutants, heavy metals, nutrients, and contaminants of emerging concern (CECs), including antibiotic resistance genes (ARGs), were carried out, thus underscoring the pivotal role of microbial diversity and metabolic activity in the complex process of contaminant elimination. While prior research has predominantly focused on isolated components, the current study presents a holistic approach, merging state-of-the-art high-throughput metagenomics and transcriptomics techniques. This innovative combination illuminates the functional dynamics of microbial communities operating within the hybrid system under a range of operational conditions. The primary critical findings reveal significant shifts in microbial community structure and gene expression patterns, which are intricately linked to enhanced efficiencies in nutrient uptake and contaminant removal. In addition, the study also situates these findings within the expansive framework of omics-based bioremediation research, providing a clear and structured pathway for identifying prevailing knowledge gaps and directing future optimization efforts. Collectively, these contributions not only deepen our understanding of microbial community functions but also pave the way for designing next-generation bio-based wastewater treatment systems driven by the intricate interplay of microbial dynamics.