H3K4 methylation regulates development, DNA repair, and virulence in Mucorales

Mucorales are basal fungi that opportunistically cause a potentially fatal infection known as mucormycosis (black fungus disease), which poses a significant threat to human health due to its high mortality rate and its recent association with SARS-CoV-2 infections. On the other hand, histone methylation is a regulatory mechanism with pleiotropic effects, including the virulence of several pathogenic fungi. However, the role of epigenetic changes at the histone level never has been studied in Mucorales. Here, we dissected the functional role of Set1, a histone methyltransferase that catalyzes the methylation of H3K4, which is associated with the activation of gene transcription and virulence. A comparative analysis of the Mucor lusitanicus genome (previously known as Mucor circinelloides f. lusitanicus) identified only one homolog of Set1 from Candida albicans and Saccharomyces cerevisiae that contains the typical SET domain. Knockout strains in the gene set1 lacked H3K4 monomethylation, dimethylation, and trimethylation enzymatic activities. These strains also showed a significant reduction in vegetative growth and sporulation. Additionally, set1 null strains were more sensitive to SDS, EMS, and UV light, indicating severe impairment in the repair process of the cell wall and DNA lesions and a correlation between Set1 and these processes. During pathogen-host interactions, strains lacking the set1 gene exhibited shortened polar growth within the phagosome and attenuated virulence both in vitro and in vivo. Our findings suggest that the histone methyltransferase Set1 coordinates several cell processes related to the pathogenesis of M. lusitanicus and may be an important target for future therapeutic strategies against mucormycosis.

A wavelet neural control scheme for a quadrotor unmanned aerial vehicle

Wavelets are designed to have compact support in both time and frequency, giving them the ability to represent a signal in the two-dimensional time-frequency plane. The Gaussian, the Mexican hat and the Morlet wavelets are crude wavelets that can be used only in continuous decomposition. The Morlet wavelet is complex-valued and suitable for feature extraction using the continuous wavelet transform. Continuous wavelets are favoured when high temporal and spectral resolution is required at all scales. In this paper, considering the properties from the Morlet wavelet and based on the structure of a recurrent high-order neural network model, a novel wavelet neural network structure, here called a recurrent Morlet wavelet neural network, is proposed in order to achieve a better identification of the behaviour of dynamic systems. The effectiveness of our proposal is explored through the design of a decentralized neural backstepping control scheme for a quadrotor unmanned aerial vehicle. The performance of the overall neural identification and control scheme is verified via simulation and real-time results.This article is part of the theme issue 'Redundancy rules: the continuous wavelet transform comes of age'.