Abstract
In recent times, microalgae have been recognized as one of the most potential sources of biomolecules with therapeutic potential. Microalgae are rich sources of polyunsaturated fatty acids, proteins, carbohydrates, carotenoids, and vitamins. These compounds have significant anticancer, antioxidant, anti-aging, antidiabetic, hepatoprotective, and anti-inflammatory potentials. Until now, monoculture of microalgae has been the most preferred way to produce these compounds. However, this method faces the challenge of low biomass and biomolecule production and a high risk of contamination. Controlled symbiotic co-culture of microalgae with suitable microorganisms can overcome these challenges. Therefore, it is crucial to explore the compatibility of microalgae with other microorganisms to develop novel consortia to enhance biomass and biomolecule production. The article comprehensively reviews the strategies for the improvement of bioactive compound production using microalgal consortia (SIBCP-MC) viz. microalgae, fungi, bacteria, and cyanobacteria. It also discusses the mechanisms of their interaction, economic viability, and a comparison of expected revenue generation from different types of microalgal consortia. The review mainly focuses on the therapeutic potentials of microalgae biomolecules and the optimization of different factors, such as the selection of consortium partners, inoculum ratio, cultivation types and modes, temperature, pH, light intensity, and photoperiod, that affect the biomass and biomolecule production of microalgal consortia which in future helps in enhancement in biomass and biomolecules production from microalgae and curing chronic diseases. The review discusses various types of microalgal consortia, aiding in selecting the most suitable consortia for future use. The review compares their biomass and biomolecule production with monoculture, outlining microalgal consortia's advantages, challenges, and prospects. Additionally, it discusses advanced artificial intelligence techniques that could assist in the future in the selection of compatible organisms and predict expected revenue generation.
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