Santos, R. A. C. | bioRxiv Science

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↗