Discerning amyloid network in plants [article]

Avinash Yashwant Gahane, Nabodita Sinha, Talat Zahra, Ashwani Kumar Thakur
2021 bioRxiv   pre-print
Amyloids are proteinaceous fibrillar structures and are known for their pathogenic and functional roles across the kingdoms. Besides proteinaceous deposits, amyloid-like structures are present in small metabolite assemblies and fibrillar hydrogels. Recent cryoelectron microscopy studies have shed light on the heterogeneous nature of the amyloid structures and their association with carbohydrate or lipid molecules, suggesting that amyloids are not exclusively proteinaceous. The association of
more » ... loids with carbohydrates is further supported because the gold-standard dye of amyloid detection, Congo red, also binds to carbohydrates, probably due to similar stacking interactions. We name the association between amyloids, carbohydrates and other biomolecules as amyloid-network and propose that plants might contain such structures. Specifically, we hypothesize that cereal seeds containing glutamine-repeat-rich granules of storage proteins may have amyloid-like structures. This is because, polyQ repeats are associated with protein aggregation and amyloid formation in humans and are linked to multiple neurodegenerative conditions. Also seed storage proteins and seed cell wall proteins possess carbohydrate affinity. Thus, plant seeds might contain an intercalated network of proteins and carbohydrates, lending strength, stability and dynamics to these structures. In this paper, we show that, plant seeds have a mesh-like network that shows apple-green birefringence on staining with Congo red, a characteristic of amyloids. This congophilic network is more prominent in protein-rich seed sections of wheat and lentils, as compared to starch-rich compartments of potato tuber. The findings suggest an amyloid network in the seeds and might be extended to other plant tissues. Further investigation with mass spectrometry and other techniques would detail the exact compositional analysis of these networks.
doi:10.1101/2021.01.24.427947 fatcat:lxefe2duqraslcc37qg62upj4a