Production of an anti-Candidapeptide via fed batch and ion exchange chromatography

Artificial Intelligence in Functional Food Ingredient Discovery and Characterisation: A Focus on Bioactive Plant and Food Peptides

Scientific research consistently demonstrates that diseases may be delayed, treated, or even prevented and, thereby, health may be maintained with health-promoting functional food ingredients (FFIs). Consumers are increasingly demanding sound information about food, nutrition, nutrients, and their associated health benefits. Consequently, a nutrition industry is being formed around natural foods and FFIs, the economic growth of which is increasingly driven by consumer decisions. Information technology, in particular artificial intelligence (AI), is primed to vastly expand the pool of characterised and annotated FFIs available to consumers, by systematically discovering and characterising natural, efficacious, and safe bioactive ingredients (bioactives) that address specific health needs. However, FFI-producing companies are lagging in adopting AI technology for their ingredient development pipelines for several reasons, resulting in a lack of efficient means for large-scale and high-throughput molecular and functional ingredient characterisation. The arrival of the AI-led technological revolution allows for the comprehensive characterisation and understanding of the universe of FFI molecules, enabling the mining of the food and natural product space in an unprecedented manner. In turn, this expansion of bioactives dramatically increases the repertoire of FFIs available to the consumer, ultimately resulting in bioactives being specifically developed to target unmet health needs.

Recombinant peptide fusion construction for protein-templated catalytic palladium nanoparticles

Although peptide-enabled synthesis of nanostructures has garnered considerable interest for use in catalytic applications, it has so far been achieved mostly via Fmoc based solid phase peptide synthesis. Consequently, the potential of longer peptides in nanoparticle synthesis have not been explored largely due to the complexities and economic constraints of this chemical synthesis route. This study examines the potential of a 45-amino acid long peptide expressed as fusion to green fluorescence protein (GFPuv) in Escherichia coli for use in palladium nanoparticle synthesis. Fed-batch fermentation with E. coli harboring an arabinose-inducible plasmid produced a product containing three copies of Pd4 peptide fused to N-terminus of GFPuv ((Pd4)₃ -GFPuv). Using the intrinsic fluorescence of GFPuv, expression and enrichment of the fusion product was easily monitored. Crude lysate, desalted lysate, and an ion-exchange enriched fraction containing (Pd4)₃ -GFPuv were used to test the hypothesis that high purity of the biologic material used as the nanoparticle synthesis template may not be necessary. Nanoparticles were characterized using a variety of material science techniques and used to catalyze a model Suzuki-Miyaura coupling reaction. Results demonstrated that palladium nanoparticles can be synthesized using the soluble cell extract containing (Pd4)₃ -GFPuv without extensive purification or cleavage steps, and as a catalyst the crude mixture is functional.