Unser 10. Leibniz Plant Biochemistry Symposium am 7. und 8. Mai war ein großer Erfolg. Thematisch ging es in diesem Jahr um neue Methoden und Forschungsansätze der Naturstoffchemie. Die exzellenten Vorträge über Wirkstoffe…
Omanische Heilpflanze im Fokus der Phytochemie IPB-Wissenschaftler und Partner aus Dhofar haben jüngst die omanische Heilpflanze Terminalia dhofarica unter die phytochemische Lupe genommen. Die Pflanze ist reich an…
Geschmack ist vorhersagbar: Mit FlavorMiner. FlavorMiner heißt das Tool, das IPB-Chemiker und Partner aus Kolumbien jüngst entwickelt haben. Das Programm kann, basierend auf maschinellem Lernen (KI), anhand der…
In plant cells, plastids form elongated extensions called stromules, the regulation and purposes of which remain unclear. Here, we quantitatively explore how different stromule structures serve to enhance the ability of a plastid to interact with other organelles: increasing the effective space for interaction and biomolecular exchange between organelles. Interestingly, electron microscopy and confocal imaging showed that the cytoplasm in Arabidopsis thaliana and Nicotiana benthamiana epidermal cells is extremely thin (around 100 nm in regions without organelles), meaning that inter-organelle interactions effectively take place in 2D. We combine these imaging modalities with mathematical modeling and new in planta experiments to demonstrate how different stromule varieties (single or multiple, linear or branching) could be employed to optimize different aspects of inter-organelle interaction capacity in this 2D space. We found that stromule formation and branching provide a proportionally higher benefit to interaction capacity in 2D than in 3D. Additionally, this benefit depends on optimal plastid spacing. We hypothesize that cells can promote the formation of different stromule architectures in the quasi-2D cytoplasm to optimize their interaction interface to meet specific requirements. These results provide new insight into the mechanisms underlying the transition from low to high stromule numbers, the consequences for interaction with smaller organelles, how plastid access and plastid to nucleus signaling are balanced and the impact of plastid density on organelle interaction.
Publikation
Cabas-Mora, G.; Daza, A.; Soto-García, N.; Garrido, V.; Alvarez, D.; Navarrete, M. A.; Sarmiento-Varón, L.; Sepúlveda-Yañez, J.; Davari, M. D.; Cadet, F.; Olivera-Nappa, A.; Uribe-Paredes, R.; Medina-Ortiz, D.;Peptipedia v2.0: a peptide sequence database and user-friendly web platform. A major updateDatabase2024baae113(2024)DOI: 10.1093/database/baae113
In recent years, peptides have gained significant relevance due to their therapeutic properties. The surge in peptide production and synthesis has generated vast amounts of data, enabling the creation of comprehensive databases and information repositories. Advances in sequencing techniques and artificial intelligence have further accelerated the design of tailor-made peptides. However, leveraging these techniques requires versatile and continuously updated storage systems, along with tools that facilitate peptide research and the implementation of machine learning for predictive systems. This work introduces Peptipedia v2.0, one of the most comprehensive public repositories of peptides, supporting biotechnological research by simplifying peptide study and annotation. Peptipedia v2.0 has expanded its collection by over 45% with peptide sequences that have reported biological activities. The functional biological activity tree has been revised and enhanced, incorporating new categories such as cosmetic and dermatological activities, molecular binding, and antiageing properties. Utilizing protein language models and machine learning, more than 90 binary classification models have been trained, validated, and incorporated into Peptipedia v2.0. These models exhibit average sensitivities and specificities of 0.877±0.0530 and 0.873±0.054, respectively, facilitating the annotation of more than 3.6 million peptide sequences with unknown biological activities, also registered in Peptipedia v2.0. Additionally, Peptipedia v2.0 introduces description tools based on structural and ontological properties and user-friendly machine learning tools to facilitate the application of machine learning strategies to study peptide sequences.
Database URL: https://peptipedia.cl/