Intraspecies characterization of bacteria via evolutionary modeling of protein domains.

The ability to detect and characterize bacteria within a biological sample is crucial for the monitoring of infections and epidemics, as well as for the study of human health and its relationship with commensal microorganisms. To this aim, a commonly used technique is the 16S rRNA gene targeted sequencing. PCR-amplified 16S sequences derived from the sample of interest are usually clustered into the so-called Operational Taxonomic Units (OTUs) based on pairwise similarities. Then, representative OTU sequences are compared with reference (human-made) databases to derive their phylogeny and taxonomic classification. Here, we propose a new reference-free approach to define the phylogenetic distance between bacteria based on protein domains, which are the evolving units of proteins. We extract the protein domain profiles of 3368 bacterial genomes and we use an ecological approach to model their Relative Species Abundance distribution. Based on the model parameters, we then derive a new measurement of phylogenetic distance. Finally, we show that such model-based distance is capable of detecting differences between bacteria in cases in which the 16S rRNA-based method fails, providing a possibly complementary approach , which is particularly promising for the analysis of bacterial populations measured by shotgun sequencing.

DNA methylation correlation structure of chromosome 21 in Down syndrome.

DNA methylation studies usually focus on the groups of CpG sites. Neighbouring CpG sites are analyzed together due to their group behaviour. However, this approach ignores the possible interaction between more distant CpG sites. In this work, we investigate the complete methylation correlation structure of chromosome 21. Two data sets were used for the correlation analysis, smaller data set with methylation measurements from Down syndrome patients and their family members and larger data set with healthy subjects. This allowed us to examine the general properties of the methylation correlation structure as well as its modifications in presence of an extra copy of the chromosome. We observed that the CpG sites work in small highly correlated groups. While some groups coincided with CpG islands, other groups contained CpG sites scattered across the whole chromosome. Groups of highly correlated CpG sites remained preserved in the case of Down syndrome. Moreover, the methylome of a Down syndrome patient had newly formed correlations between CpG sites suggesting that the methylation correlation structure in Down syndrome is stronger than in case of an unaffected individual.

Small extracellular vesicles deliver miR-21 and miR-217 as pro-senescence effectors to endothelial cells.

The role of epigenetics in endothelial cell senescence is a cutting-edge topic in ageing research. However, little is known of the relative contribution to pro-senescence signal propagation provided by microRNAs shuttled by extracellular vesicles (EVs) released from senescent cells. Analysis of microRNA and DNA methylation profiles in non-senescent (control) and senescent (SEN) human umbilical vein endothelial cells (HUVECs), and microRNA profiling of their cognate small EVs (sEVs) and large EVs demonstrated that SEN cells released a significantly greater sEV number than control cells. sEVs were enriched in miR-21-5p and miR-217, which target DNMT1 and SIRT1. Treatment of control cells with SEN sEVs induced a miR-21/miR-217-related impairment of DNMT1-SIRT1 expression, the reduction of proliferation markers, the acquisition of a senescent phenotype and a partial demethylation of the locus encoding for miR-21. MicroRNA profiling of sEVs from plasma of healthy subjects aged 40-100 years showed an inverse U-shaped age-related trend for miR-21-5p, consistent with senescence-associated biomarker profiles. Our findings suggest that miR-21-5p/miR-217 carried by SEN sEVs spread pro-senescence signals, affecting DNA methylation and cell replication.