Biology subjects

Santos, R. A. C.

Publications and source records attributed to Santos, R. A. C..

4 recordsLinked to original sources

bioRxiv2024

Bridging the Python Training Gap for Bioscientists in Brazil: Improvements and Challenges

The rapid evolution of high-throughput technologies in biosciences has generated diverse and voluminous datasets, requiring bioscientists to develop data manipulation and analysis skills. Python, known for its versatility and powerful libraries, has become a crucial tool for managing these datasets. However, there is a significant lack of programming training for bioscientists in many countries. To address this knowledge gap among scientists in Brazil, the Brazilian Python Workshop for Biological Data was introduced several years ago, focusing on basic programming concepts and data handling techniques using popular Python libraries. Despite the progress and positive feedback from earlier editions, challenges persisted, necessitating continuous adaptation and improvement to meet the evolving needs of bioscientists.This work describes the advancements made in the 2021 and 2022 editions of the workshop and discusses new suggestions for its ongoing enhancement. Key innovations were introduced in the workshop structure and coordination, including the creation of new committees and the establishment of a code of conduct. Feedback forms were updated to enable real-time adjustments during the event, improving its overall effectiveness. The workshop also expanded its reach by increasing geographical diversity among participants. New didactic strategies, such as pair-teaching, code clubs, and the integration of information and communication technologies (ICTs), were implemented to enhance learning outcomes. Programming best practices and scientific reproducibility were emphasized through talks and hands-on activities, guided by PEP8 conventions. Furthermore, efforts to enhance scientific dissemination were intensified, with an increased presence on social media and participation in international scientific events and communication networks. Finally, we present updated recommendations for students, researchers, and educators interested in organizing and promoting similar events, building on those previously described.

scientific communication and education↗

bioRxiv2020

Genomic and phenotypic analysis of COVID-19-associated pulmonary aspergillosis isolates of Aspergillus fumigatus

The ongoing global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the coronavirus disease 2019 (COVID-19) first described from Wuhan, China. A subset of COVID-19 patients has been reported to have acquired secondary infections by microbial pathogens, such as fungal opportunistic pathogens from the genus Aspergillus. To gain insight into COVID-19 associated pulmonary aspergillosis (CAPA), we analyzed the genomes and characterized the phenotypic profiles of four CAPA isolates of Aspergillus fumigatus obtained from patients treated in the area of North Rhine-Westphalia, Germany. By examining the mutational spectrum of single nucleotide polymorphisms, insertion-deletion polymorphisms, and copy number variants among 206 genes known to modulate A. fumigatus virulence, we found that CAPA isolate genomes do not exhibit major differences from the genome of the Af293 reference strain. By examining virulence in an invertebrate moth model, growth in the presence of osmotic, cell wall, and oxidative stressors, and the minimum inhibitory concentration of antifungal drugs, we found that CAPA isolates were generally, but not always, similar to A. fumigatus reference strains Af293 and CEA17. Notably, CAPA isolate D had more putative loss of function mutations in genes known to increase virulence when deleted (e.g., in the FLEA gene, which encodes a lectin recognized by macrophages). Moreover, CAPA isolate D was significantly more virulent than the other three CAPA isolates and the A. fumigatus reference strains tested. These findings expand our understanding of the genomic and phenotypic characteristics of isolates that cause CAPA.

microbiology↗

bioRxiv2020

Investigating Feedforward Neural Networks for Classification of Transposon-Derived piRNAs

PIWI-Interacting RNAs (piRNAs) form an important class of non-coding RNAs that play a key role in the genome integrity through the silencing of transposable elements. However, despite their importance and the large application of deep learning in computational biology for classification tasks, there are few studies of deep learning and neural networks for piRNAs prediction. Therefore, this paper presents an investigation on deep feedforward networks models for classification of transposon-derived piRNAs. We analyze and compare the results of the neural networks in different hyperparameters choices, such as number of layers, activation functions and optimizers, clarifying the advantages and disadvantages of each configuration. From this analysis, we propose a model for human piRNAs classification and compare our method with the state-of-the-art deep neural network for piRNA prediction in the literature and also traditional machine learning algorithms, such as Support Vector Machines and Random Forests, showing that our model has achieved a great performance with an F-measure value of 0.872, outperforming the state-of-the-art method in the literature.

bioinformatics↗

bioRxiv2020

Genomic and phenotypic heterogeneity of clinical isolates of the human pathogens Aspergillus fumigatus, Aspergillus lentulus and Aspergillus fumigatiaffinis

Fungal pathogens are a global threat to human health. For example, fungi from the genus Aspergillus cause a spectrum of diseases collectively known as aspergillosis. Most of the >200,000 life-threatening aspergillosis infections per year worldwide are caused by Aspergillus fumigatus. Recently, molecular typing techniques have revealed that aspergillosis can also be caused by organisms that are phenotypically similar to A. fumigatus but genetically distinct, such as Aspergillus lentulus and Aspergillus fumigatiaffinis. Importantly, some of these so-called cryptic species exhibit different virulence and drug susceptibility profiles than A. fumigatus, however, our understanding of their biology and pathogenic potential has been stymied by the lack of genome sequences and phenotypic profiling. To fill this gap, we phenotypically characterized the virulence and drug susceptibility of 15 clinical strains of A. fumigatus, A. lentulus, and A. fumigatiaffinis from Spain and sequenced their genomes. We found heterogeneity in virulence and drug susceptibility across species and strains. Genes known to influence drug susceptibility (cyp51A and fks1) vary in paralog number and sequence among these species and strains and correlate with differences in drug susceptibility. Similarly, genes known to be important for virulence in A. fumigatus showed variability in number of paralogs across strains and across species. Characterization of the genomic similarities and differences of clinical strains of A. lentulus, A. fumigatiaffinis, and A. fumigatus that vary in disease-relevant traits will advance our understanding of the variance in pathogenicity between Aspergillus species and strains that are collectively responsible for the vast majority of aspergillosis infections in humans.

microbiology↗