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Boschin, M.

Publications and source records attributed to Boschin, M..

2 recordsLinked to original sources

An AI-driven pipeline for the discovery of hidden peptides in plant proteomes: the CLE family as a case study

Plant proteomes contain evolutionarily conserved peptides with poorly conserved primary sequences, often hindering their identification and classification into families. Homology-based approaches and conventional annotation pipelines frequently fail to detect these family members, particularly in poorly characterized, but agronomically relevant plant species. CLE peptides (CLAVATA3/EMBRYO SURROUNDING REGION-related peptides) constitute a large and evolutionarily conserved family of plant signaling molecules, yet their characterization remains incomplete. Beyond a limited number of well-studied members, a substantial number of CLE peptides remain uncharacterized due to functional redundancy and the intrinsic features of CLE genes, which encode short pre-propeptides with only a small 12-residue conserved motif. Here, we present a novel framework leveraging state-of-the-art Protein Language Models (pLMs) to discover CLE peptides directly from 13 plant proteomes. By coupling sequence embeddings trained on large evolutionary datasets (ESM2 and ProtT5) with supervised machine learning, our dual-model approach captures deep semantic features of the CLE family that are missed by traditional alignment methods. The pipeline demonstrated robust generalization, achieving high classification accuracy (98.9-99.4%) on a held-out set of CLE peptides not used during training. Consequently, we identified a set of high-confidence, previously unannotated CLE candidates prioritized through a stringent consensus-based filtering strategy. This work demonstrates how AI-driven proteome analysis can overcome the limitations of homology-based methods and provides a scalable strategy for uncovering previously unidentified peptide-mediated signaling molecules across plant lineages. HighlightLeveraging Protein Language Models, our AI framework uncovers "hidden" signaling peptides missed by standard tools, revealing the elusive diversity of CLE regulators across plant proteomes.

plant biology↗

Physcomitrium patens flavodiiron proteins form a redox-dependent heterocomplex.

Flavodiiron proteins (FLVs) catalyze the reduction of oxygen to water by exploiting electrons from Photosystem I (PSI). In several photosynthetic organisms such as cyanobacteria, green algae, mosses and gymnosperms, FLV-dependent electron flow protects PSI from over-reduction and consequent damage especially under fluctuating light conditions. In this work we investigated biochemical and structural properties of FLVA and FLVB from the model moss Physcomitrium patens. The two proteins, expressed and purified from Escherichia coli, bind both iron and flavin cofactors and show NAD(P)H oxidase activity as well as oxygen reductase capacities. Moreover, the co-expression of both FLVA and FLVB, coupled to a tandem affinity purification procedure with two different affinity tags, enabled the isolation of the stable and catalytically active FLVA/B hetero multimer protein complex, that has never been isolated and characterized so far. The multimeric organization was shown to be stabilized by inter-subunit disulfide bonds. This investigation provides valuable new information on the biochemical properties of FLVs, with new insights into their in vivo role and regulation.

plant biology↗