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Algal synthetic communities in industrial wastewater treatment: hurdles and opportunities

  • Vikas Kumar Patel,
  • Ritu Kumari,
  • Anima Das,
  • Priya Kumari,
  • Sachin Kajla

摘要

Synthetic ecology encompasses the designer community of numerous species with varying innate metabolic features. Scientists are focusing on a unique process technology for industrial wastewater treatment, combining characteristics of microbial ecology. However, this technology has disadvantages, such as unpredictable behaviour of constituent members due to inherent metabolic interactions and the detrimental impacts of wastewater contaminants. Recognizing these limitations is crucial for developing a viable treatment strategy for managing large volumes of industrial wastewater on a large scale. It includes inlet water profile of different rejects from diverse plants. We have emphasized on current ecological engineering approaches for building synthetic consortia of photosynthetic algae and cyanobacteria in this study. The durability of algae–cyanobacteria consortia for industrial wastewater has been thoroughly explored using instances from the synthetic ecology and biotechnology public database to illustrate new ideas. These connections include interactions between chemical pollutants of wastewater and consortia members, as well as the consequences of reciprocal and non-reciprocal ecological crosstalk through inherent secretary chemical interactions among the constituent species. We also investigated the factors that influence the synergistic presence of algae and cyanobacteria in industrial wastewater treatment from diverse industries involved in steel-making process. Since, wastewater from steel industries have a diverse pollutant’s profile, a careful evaluation of algae-based treatment technology is required. A critical discussion has taken place about the creation of synthetic consortia of algae and cyanobacteria, their large-scale adoption for improved water quality. This topic covers current ecological techniques and the importance of biophysical factors, and stoichiometric modelling of intrinsic metabolism.

Graphical abstract