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Rational domestication of a plant-based recombinant expression system expands its biosynthetic range

Cite this dataset

Gilding, Edward et al. (2022). Rational domestication of a plant-based recombinant expression system expands its biosynthetic range [Dataset]. Dryad.


Plant molecular farming aims to provide a green, flexible, and rapid alternative to conventional recombinant expression systems, capable of producing complex biologics such as enzymes, vaccines, and antibodies. Historically, the recombinant expression of therapeutic peptides in plants has proven difficult, largely due to their small size and instability. However, some plant species harbour the capacity for peptide backbone cyclization, a feature inherent in stable therapeutic peptides. One obstacle to realizing the potential of plant-based therapeutic peptide production is the proteolysis of the precursor before it is matured into its final stabilized form. Here we demonstrate the rational domestication of Nicotiana benthamiana within two generations to endow this plant molecular farming host with an expanded repertoire of peptide sequence space. The in planta production of molecules including an insecticidal peptide, a prostate cancer therapeutic lead and an orally active analgesic are demonstrated.


Data were collected using MALDI-TOF -TOF methods described in the manuscript. Chromatogram data was produced as a service by the Australian Genome Research Foundation in Brisbane, QLD, Australia.

Usage notes

Data are presented as MALDI-TOF-TOF trace values exported from AB Sciex software as unitless values with internal and relative controls for relative representation and quantification. Chromatograms are included which were used to produce supplementary figure alignments. RNA-seq data relevant to this manuscript are not stored in Dryad but have been uploaded to NCBI-SRA (PRJNA784697).


Australian Research Council, Award: DP150100443

Australian Research Council, Award: DP200101299

Australian Research Council, Award: FL150100146

Australian Research Council, Award: CE200100012