Alzheimer’s Disease (AD) is the most common cause of dementia affecting the elderly population worldwide. We have performed a comprehensive transcriptome profiling of Late-Onset AD (LOAD) patients using second generation sequencing technologies, identifying 2,064 genes, 47 lncRNAs and 4 miRNAs whose expression is specifically deregulated in the hippocampal region of LOAD patients. Moreover, analyzing the hippocampal, temporal and frontal regions from the same LOAD patients, we identify specific sets of deregulated miRNAs for each region, and we confirm that the miR-132/212 cluster is deregulated in each of these regions in LOAD patients, consistent with these miRNAs playing a role in AD pathogenesis. Notably, a luciferase assay indicates that miR-184 is able to target the 3’UTR NR4A2 - which is known to be involved in cognitive functions and long-term memory and whose expression levels are inversely correlated with those of miR-184 in the hippocampus. Finally, RNA editing analysis reveals a general RNA editing decrease in LOAD hippocampus, with 14 recoding sites significantly and differentially edited in 11 genes. Our data underline specific transcriptional changes in LOAD brain and provide an important source of information for understanding the molecular changes characterizing LOAD progression.

The ATP-gated ionotropic P2X7 receptor regulates T follicular helper (Tfh) cell abundance in the Peyer's patches (PPs) of the small intestine; deletion of P2rx7, encoding for P2X7, in Tfh cells results in enhanced IgA secretion and binding to commensal bacteria. Here, we show that Tfh cell activity is important for generating a diverse bacterial community in the gut and that sensing of microbiota-derived extracellular ATP via P2X7 promotes the generation of a proficient gut ecosystem for metabolic homeostasis. The results of this study indicate that Tfh cells play a role in host-microbiota mutualism beyond protecting the intestinal mucosa by induction of affinity-matured IgA and suggest that extracellular ATP constitutes an inter-kingdom signaling molecule important for selecting a beneficial microbial community for the host via P2X7-mediated regulation of B cell help.

Metagenomics is providing an unprecedented access to the environmental microbial diversity. The amplicon-based metagenomics approach involves the PCR-targeted sequencing of a genetic locus fitting different features. Namely, it must be ubiquitous in the taxonomic range of interest, variable enough to discriminate between different species but flanked by highly conserved sequences, and of suitable size to be sequenced through next-generation platforms. The internal transcribed spacers 1 and 2 (ITS1 and ITS2) of the ribosomal DNA operon and one or more hyper-variable regions of 16S ribosomal RNA gene are typically used to identify fungal and bacterial species, respectively. In this context, reliable reference databases and taxonomies are crucial to assign amplicon sequence reads to the correct phylogenetic ranks. Several resources provide consistent phylogenetic classification of publicly available 16S ribosomal DNA sequences, whereas the state of ribosomal internal transcribed spacers reference databases is notably less advanced. In this review, we aim to give an overview of existing reference resources for both types of markers, highlighting strengths and possible shortcomings of their use for metagenomics purposes. Moreover, we present a new database, ITSoneDB, of well annotated and phylogenetically classified ITS1 sequences to be used as a reference collection in metagenomic studies of environmental fungal communities. ITSoneDB is available for download and browsing at http://itsonedb.ba.itb.cnr.it/.

Metagenomics, Metabolomics, and Metaproteomics have significantly advanced our knowledge of microbial communities by providing culture-independent insights into their composition and functional potential. However, a critical challenge in this field is the lack of standard and comprehensive metadata associated with raw data, hindering the ability to perform robust data stratifications and consider confounding factors. In this comprehensive review, we categorize publicly available microbiome data into five types: shotgun sequencing, amplicon sequencing, metatranscriptomic, metabolomic, and metaproteomic data. We explore the importance of metadata for data reuse and address the challenges in collecting standardized metadata. We also, assess the limitations in metadata collection of existing public repositories collecting metagenomic data. This review emphasizes the vital role of metadata in interpreting and comparing datasets and highlights the need for standardized metadata protocols to fully leverage metagenomic data's potential. Furthermore, we explore future directions of implementation of Machine Learning (ML) in metadata retrieval, offering promising avenues for a deeper understanding of microbial communities and their ecological roles. Leveraging these tools will enhance our insights into microbial functional capabilities and ecological dynamics in diverse ecosystems. Finally, we emphasize the crucial metadata role in ML models development.