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Fantini, M.

Publications and source records attributed to Fantini, M..

2 recordsLinked to original sources

New Techniques for Ancient Proteins: Direct Coupling Analysis Applied on Proteins involved in Iron Sulfur Cluster Biogenesis

Direct coupling analysis (DCA) is a powerful tool based on protein evolution and introduced to predict protein fold and protein-protein interactions which has been applied also to the prediction of entire interactomes. We have used DCA to analyse three proteins of the iron-sulfur biogenesis machine, an essential metabolic pathway conserved in all organisms. We show that, although based on a relatively small number of sequences due to its distribution in genomes, we can correctly recapitulate all the features of the fold of the CyaY/frataxin family, a protein involved in the human disease Friedreichs ataxia. This result gave us confidence in the use of this tool. Application of DCA to the iron-sulfur cluster scaffold protein IscU, which has been suggested to function both as an ordered and a disordered form, allows us to clearly distinguish evolutionary traces of the structured species, suggesting that, if present in the cell, the disordered form has not left any evolutionary imprinting. We observe instead, for the first time, direct indications of how the protein can dimerize head-to-head and bind 4Fe4S clusters. Analysis of the alternative scaffold protein IscA provides strong support to a coordination of the cluster mediated by a dimeric rather than a tetrameric form as previously suggested. Our analysis also suggests the presence in solution of a mixture of monomeric and dimeric species and guide us to the prevalent one. Finally, we used DCA to analyse protein-protein interactions between some of these proteins and discuss the potentialities and the limitations of the method.

bioinformatics

Assessment of Antibody Library Diversity through Next Generation Sequencing and Technical Error Compensation.

Antibody libraries are important resources to derive antibodies to be used for a wide range of applications, from structural and functional studies to intracellular protein interference studies to developing new diagnostics and therapeutics. Whatever the goal, the key parameter for an antibody library is its diversity, i.e. the number of distinct elements in the collection, which directly reflects the probability of finding in the library an antibody against a given antigen, of sufficiently high affinity. Quantitative evaluation of antibody library diversity and quality has been for a long time inadequately addressed, due to the high similarity and length of the sequences of the library. Diversity was usually inferred by the transformation efficiency and tested either by fingerprinting and/or sequencing of a few hundred random library elements. Inferring diversity from such a small sample is, however, very rudimental and gives limited information about the real complexity, because complexity does not scale linearly with sample size. Next-generation sequencing (NGS) has opened new ways to tackle the antibody library diversity quality assessment. However, much remains to be done to fully exploit the potential of NGS for the quantitative analysis of antibody repertoires and to overcome current limitations. To obtain a more reliable antibody library complexity estimate here we show a new, PCR-free, NGS approach to sequence antibody libraries on Illumina platform, coupled to a new bioinformatic analysis and software (Diversity Estimator of Antibody Library, DEAL) that allows to reliably estimate the diversity, taking in consideration the sequencing error.

bioinformatics