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Hemi-pyocyanin (HPC) is a heterocyclic nitrogenous compound with some reported potential medical effects. The current report aimed to investigate the potential use of organic industrial waste for the production of HPC via microbial fermentation. The novel antidiabetic activity of HPC was also accessed and reported in this work. A peanut oil processing by-product (groundnut cake) was screened as the best substrate for Pseudomonas aeruginosa TUN03 conversion to obtain high-yield HPC. This compound was further produced in a 14 L bioreactor system on a large scale (6 L per pilot) and reached higher productivity (35.1 μg/mL) in a shorter time course of cultivation (8 h) compared to fermentation on a small scale in flasks (19.5 μg/mL; 3 days of fermentation). On assessing its activity, HPC demonstrated potent inhibition against α-glucosidase, an antidiabetic enzyme, with a low IC50 value (0.572 mg/mL) and a maximum inhibition rate of 100%. In an in silico study, HPC was found to inhibit α-glucosidase with a good binding energy score (−9.0 kcal/mol) via interaction with amino acids Lys156, Leu313, and Arg315 at the active site, and three bonds (1 H-acceptor and 2 pi-H) were generated. The data from five Lipkin’s rules and ADMET-based pharmacokinetics and pharmacology revealed that HPC possesses drug-like properties and good ADMET properties within the required allotted limitations. The data obtained in the current work highlighted the potential application of groundnut cakes for the eco-friendly and scaled-up production of HPC, a new anti-α-glucosidase agent that should be further investigated for type 2 diabetes management.

Biological nitrogen removal (BNR) technologies are the most effective approaches for the remediation of environmental nitrogen pollutants from wastewater treatment plants (WWTPs). Presently, research is going on to elucidate the structure and function of BNR microbial communities and optimizing BNR treatment systems to enhance nitrogen removal efficiency. The literature on BNR microbial communities and experimental datasets is not unified across various repositories, while a uniform resource for the collection, annotation, and structuring of these BNR datasets is still unavailable. Herein, we present the Biological Nitrogen Removal Database (BNRdb), an integrated resource containing various manually curated BNR-related data. At present, BNRdb contains 23,308 microbial strains, 46 gene families, 24 enzymes, 18 reactions, 301 BNR treatment datasets, 860 BNR-associated next-generation sequencing datasets, and 6 common BNR bioreactor systems. BNRdb provides a user-friendly interface enabling interactive data browsing. To our knowledge, BNRdb is the first BNR data resource that systematically integrates BNR data from archaeal, bacterial, and fungal communities. We believe that BNRdb will contribute to a better understanding of BNR process and nitrogen bioremediation research.