Where do the antibiotic resistance genes come from? A modulated analysis of sources and loads of resistances in Lake Maggiore

Antibiotic resistance genes (ARGs) are abundant in aquatic ecosystems affected by human activities. Understanding the fate of ARGs across different ecosystems is essential because of the significant role aquatic environments play in the cycle of antibiotic resistance. We quantified selected ARGs in Lake Maggiore, its main tributaries, and the effluent of the main wastewater treatment plant (WWTP) discharging directly into the lake. We linked their dynamics to the different anthropogenic impacts in each tributary's watershed. The dynamics of tetA in the lake were influenced by those of the rivers and the WWTP effluent, and by the concentration of N-NH4, related to anthropogenic pollution, while sul2 abundance in the lake was not influenced by any water inflow. The dynamics of the different ARGs varied across the different rivers. Rivers with watersheds characterized by high population density, touristic activities, and secondary industries released more ARGs, while ermB correlated with higher numbers of primary industries. This study suggests a limited contribution of treated wastewater in the spread of ARGs, indicating as prevalent origin other sources of pollution, calling for a reconsideration on what are considered the major sources of ARGs into the environment.

A PDZ scaffolding/CaM-mediated pathway in Cryptochrome signaling

Cryptochromes are cardinal constituents of the circadian clock, which orchestrates daily physiological rhythms in living organisms. A growing body of evidence points to their participation in pathways that have not traditionally been associated with circadian clock regulation, implying that cryptochromes may be subject to modulation by multiple signaling mechanisms. In this study, we demonstrate that human CRY2 (hCRY2) forms a complex with the large, modular scaffolding protein known as Multi-PDZ Domain Protein 1 (MUPP1). This interaction is facilitated by the calcium-binding protein Calmodulin (CaM) in a calcium-dependent manner. Our findings suggest a novel cooperative mechanism for the regulation of mammalian cryptochromes, mediated by calcium ions (Ca2+ ) and CaM. We propose that this Ca2+ /CaM-mediated signaling pathway may be an evolutionarily conserved mechanism that has been maintained from Drosophila to mammals, most likely in relation to its potential role in the broader context of cryptochrome function and regulation. Further, the understanding of cryptochrome interactions with other proteins and signaling pathways could lead to a better definition of its role within the intricate network of molecular interactions that govern circadian rhythms.

GOWDL: gene ontology-driven wide and deep learning model for cell typing of scRNA-seq data

Single-cell RNA-sequencing (scRNA-seq) allows for obtaining genomic and transcriptomic profiles of individual cells. That data make it possible to characterize tissues at the cell level. In this context, one of the main analyses exploiting scRNA-seq data is identifying the cell types within tissue to estimate the quantitative composition of cell populations. Due to the massive amount of available scRNA-seq data, automatic classification approaches for cell typing, based on the most recent deep learning technology, are needed. Here, we present the gene ontology-driven wide and deep learning (GOWDL) model for classifying cell types in several tissues. GOWDL implements a hybrid architecture that considers the functional annotations found in Gene Ontology and the marker genes typical of specific cell types. We performed cross-validation and independent external testing, comparing our algorithm with 12 other state-of-the-art predictors. Classification scores demonstrated that GOWDL reached the best results over five different tissues, except for recall, where we got about 92% versus 97% of the best tool. Finally, we presented a case study on classifying immune cell populations in breast cancer using a hierarchical approach based on GOWDL.

Microbial and Qualitative Traits of Quinoa and Amaranth Seeds from Experimental Fields in Southern Italy

Quinoa and amaranth are of special interest since they are increasingly used for the development of new bakery products with enhanced nutritional value. The aim of the study was to evaluate the agronomic, microbiological, and nutritional characteristics of quinoa and amaranth seeds grown in Southern Italy. For this reason, quinoa Titicaca and three amaranth accessions (5, 12, and 14) were cultivated in different experimental fields in the Campania Region and analyzed for the cultivation aspects, chemical composition, and microbiological quality of the seeds. All seeds showed a good adaptability to cultivation in the experimental areas of the Mediterranean basin. Quinoa seeds were characterized by their higher protein, fat, and ash content than the amaranth seeds, which were characterized by their higher value in dietary fiber. All seeds, regardless of the geographical area of production, were contaminated with yeasts, moulds, and spore-forming bacteria, mainly Bacillus cereus, B. licheniformis, B. safensis and B. subtilis, as identified by 16S rRNA sequencing analysis. So, the detection of Bacillus spp. must be strongly monitored, as quinoa and amaranth seeds could be used in bread production, where they can cause ropiness, resulting in great economic losses for the industries.