Comparative analysis of the microbiome composition of artisanal cheeses produced in the Mediterranean area.

In the PRIMA project ArtiSaneFood, the microbiological parameters of several artisanal cheeses produced in the Mediterranean area have been quantified. In this pilot study, we selected four of these artisanal cheese products from Italy, Portugal, Spain, and Morocco to investigate and compare their microbiomes in terms of taxonomic composition, presence of reads of foodborne pathogens, as well as virulence and antimicrobial resistance genes. , and were the most represented genera in the Portuguese and Spanish cheeses, in the Italian cheese, and , , , and in the Moroccan products.

Renal Function Is Associated with Changes in Bone Mineral Density in Postmenopausal Osteoporotic Women Treated with Denosumab: Data From a Retrospective Cohort Study.

: Renal function influences bone metabolism, as kidney failure can increase the risk of fractures. Denosumab is an approved osteoporosis treatment, but its efficacy in relation to renal function has not yet been studied in real-life scenarios. This study aimed to investigate the denosumab-induced change in bone mineral density (BMD) according to kidney function.

Genome-resolved metagenomics revealed novel microbial taxa with ancient metabolism from macroscopic microbial mat structures inhabiting anoxic deep reefs of a Maldivian Blue Hole.

Blue holes are vertical water-filled openings in carbonate rock that exhibit complex morphology, ecology, and water chemistry. In this study, macroscopic microbial mat structures found in complete anoxic conditions in the Faanu Mudugau Blue Hole (Maldives) were studied by metagenomic methods. Such communities have likely been evolutionary isolated from the surrounding marine environment for more than 10,000 years since the Blue Hole formation during the last Ice Age.

Time-series sewage metagenomics distinguishes seasonal, human-derived and environmental microbial communities potentially allowing source-attributed surveillance.

Sewage metagenomics has risen to prominence in urban population surveillance of pathogens and antimicrobial resistance (AMR). Unknown species with similarity to known genomes cause database bias in reference-based metagenomics. To improve surveillance, we seek to recover sewage genomes and develop a quantification and correlation workflow for these genomes and AMR over time.