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Bizzotto, E.

Publications and source records attributed to Bizzotto, E..

2 recordsLinked to original sources

Inactivation of mitochondrial complex IV in Physcomitrium patens reveals the essential role of respiration in coordinating plants metabolism

Photosynthetic organisms use sunlight as energy source but rely on respiration during the night and in non-photosynthetic tissues. Respiration is also active in photosynthetically active cells, where its role is still unclear due to a lack of viable mutants. Plants lacking cytochrome c oxidase (complex IV) activity are generally lethal but were here isolated exploiting the possibility of generating knockout lines through vegetative propagation in the moss Physcomitrium patens. The mutants showed severely impaired growth, with an altered composition of the respiratory apparatus and increased electron transfer through the alternative oxidase. The light phase of photosynthesis remained largely unaffected while the efficiency of carbon fixation was moderately reduced. Transcriptomic and metabolomic analyses showed that the disruption of the cytochrome pathway had broad consequences for carbon and nitrogen metabolism. A major alteration in nitrogen assimilation was observed with a general reduction in amino acid abundance. A partial rescue of the growth could be obtained by growing the plants with an external supply of amino acids but not with sugars, demonstrating that respiration in plant photosynthetic cells plays an essential role at the interface between carbon and nitrogen metabolism and a key role in providing carbon skeletons for amino acid biosynthesis.

plant biology↗

Classification of bioactive peptides: a comparative analysis of models and encodings

Bioactive peptides are short amino acid chains possessing biological activity and exerting specific physiological effects relevant to human health, which are increasingly produced through fermentation due to their therapeutic roles. One of the main open problems related to biopeptides remains the determination of their functional potential, which still mainly relies on time-consuming in vivo tests. While bioinformatic tools for the identification of bioactive peptides are available, they are focused on specific functional classes and have not been systematically tested on realistic settings. To tackle this problem, bioactive peptide sequences and functions were collected from a variety of databases to generate a comprehensive collection of bioactive peptides from microbial fermentation. This collection was organized into nine functional classes including some previously studied and some newly defined such as immunomodulatory, opioid and cardiovascular peptides. Upon assessing their native sequence properties, four alternative encoding methods were tested in combination with a multitude of machine learning algorithms, from basic classifiers like logistic regression to advanced algorithms like BERT. By testing a total set of 171 models, it was found that, while some functions are intrinsically easier to detect, no single combination of classifiers and encoders worked universally well for all the classes. For this reason, we unified all the best individual models for each class and generated CICERON (Classification of bIoaCtive pEptides fRom micrObial fermeNtation), a classification tool for the functional classification of peptides. State-of-the-art classifiers were found to underperform on our benchmark dataset compared to the models included in CICERON. Altogether, our work provides a tool for real-world peptide classification and can serve as a benchmark for future model development.

bioinformatics↗