Durign the last few months several members of LabBCES have participated of Conferences and other events sharing their research results.

ISMB2022

ISMB is the largest conference on Bioinformatics, this year the group participated remotely, with some posters.

Experiences of the Brazilian Python Workshop for Biological Data in 2022

Authors: Renato Augusto Corrêa Dos Santos, University of São Paulo (USP), Brazil; Gustavo Schiavone Crestana, ESALQ, University of São Paulo (USP), Brazil; Michelli Inácio Gonçalves Funnicelli, São Paulo State University (UNESP), School of Agricultural and Veterinarian Sciences, Brazil; Ubiratan da Silva Batista, Federal University of Ouro Preto (UFOP), Brazil; Raissa Melo de Sousa, Federal University of Pará (UFPA), Brazil; Pedro Henrique Narciso Ferreira, Federal University of São Carlos (UFSCar), Brazil; Matheus Scaketti, University of Campinas (UNICAMP), Brazil; Leonardo André Mumbach da Silva, University of Vale do Rio dos Sinos (UNISINOS), Brazil; Vinícius Franceschini-Santos, University of São Paulo (USP), Brazil; Larissa Graciano Braga, São Paulo State University (UNESP), School of Agricultural and Veterinarian Sciences, Brazil; Diego Mauricio Riaño-Pachón, CENA, University of São Paulo (USP), Brazil; Claudia Barros Monteiro Vitorello, ESALQ, University of São Paulo (USP), Brazil

Abstract

To improve training of life sciences researchers in Brazil, we conceived the Brazilian Python Workshop for Biological Data in 2017, organized by undergraduate and graduate students, and supported by researchers in computational biology, data science, and life sciences. We previously described our workshop, based on the 2020 edition, which started to be organized in a virtual format due to the COVID-19 pandemic. Since then, we have increased our activity on Instagram (mainly) and on Twitter, extending our impact beyond the course week and workshop attendees. Since 2021, we have implemented a short event inspired by the Train the Trainers from EMBL-EBI and Australian universities, that aims to encourage the exchange of experiences between previous and the current organization committee. We also included a lecture with focus on computational reproducibility and programming good practices. This year, we have implemented a code club for the organizers, to help them become familiar with Python and teaching practices. Additionally, we plan to allow donations from attendees, which we expect will benefit organizations with focus on inclusion, diversity, and programming in science. Finally, we are working with the Human Research Ethics Committee to do qualitative research during and after the workshop.

Identification of potentially new CAZymes acting on mannan and xylan polysaccharides

Authors: Diego Mauricio Riaño-Pachón, Center for Nuclear Energy in Agriculture, University of São Paulo, Brazil; Beatiz R. Estevam, Laboratory of Computational, Evolutionary, and Systems Biology - CENA/USP, Brazil; Danilo B. Rocha, Laboratory of Computational, Evolutionary, and Systems Biology - CENA/USP, Brazil

Abstract

Renewable energy from biomass has potential to contribute to the solutions of the growing energy demand. However an important fraction of that energy is stored in compounds that are not readily available. Carbohydrate-degrading enzymes, as some CAZymes, can be applied to release that energy from polysaccharides. Mannan and Xylan are important hemicellulosic polysaccharides in monocots, and there is interest in finding novel CAZymes that can break them into mono or oligosaccharides. The continuously decreasing cost of genome sequencing, and the genomes deposited in public repositories can be mined for potentially novel enzymes. We aimed to identify CAZymes by doing phylogenetic analyses and selecting sequences from less-studied and well-diverse clades that have a potential to break mannan or xylan. To reach this we a) made the prediction, using dbCAN2, of approximately 1 million CAZymes related to mannan and 800 thousand related to xylan present in bacteria, fungi and Archaea groups from 380,522 genomes deposited on NCBI b) we extracted from CAZy website those sequences that had information about structure or functional characterization; and c) we build phylogenies, using IQ-tree, for the families of interest; d) finally we identified clades that have been poorly explored in structural and functional studies.