Multipartite genomes, consisting of more than one replicon, have been found in approximately 10 % of bacteria, many of which belong to the phylum Proteobacteria. Many aspects of their origin and evolution, and the possible advantages related to this type of genome structure, remain to be elucidated. Here, we performed a systematic analysis of the presence and distribution of multipartite genomes in the class Gammaproteobacteria, which includes several genera with diverse lifestyles. Within this class, multipartite genomes are mainly found in the order Alteromonadales (mostly in the genus Pseudoalteromonas ) and in the family Vibrionaceae . Our data suggest that the emergence of secondary replicons in Gammaproteobacteria is rare and that they derive from plasmids. Despite their multiple origins, we highlighted the presence of evolutionary trends such as the inverse proportionality of the genome to chromosome size ratio, which appears to be a general feature of bacteria with multipartite genomes irrespective of taxonomic group. We also highlighted some functional trends. The core gene set of the secondary replicons is extremely small, probably limited to essential genes or genes that favour their maintenance in the genome, while the other genes are less conserved. This hypothesis agrees with the idea that the primary advantage of secondary replicons could be to facilitate gene acquisition through horizontal gene transfer, resulting in replicons enriched in genes associated with adaptation to different ecological niches. Indeed, secondary replicons are enriched both in genes that could promote adaptation to harsh environments, such as those involved in antibiotic, biocide and metal resistance, and in functional categories related to the exploitation of environmental resources (e.g. carbohydrates), which can complement chromosomal functions.

Advances in Next Generation Sequencing technologies allow us to inspect and unlock the genome to a level of detail that was unimaginable only a few decades ago. Omics-based studies are casting a light on the patterns and determinants of disease conditions in populations, as well as on the influence of microbial communities on human health, just to name a few. Through increasing volumes of sequencing information, for example, it is possible to compare genomic features and analyze the modulation of the transcriptome under different environmental stimuli. Although protocols for NGS preparation are intended to leave little to no space for contamination of any kind, a noticeable fraction of sequencing reads still may not uniquely represent what was intended to be sequenced in the first place. If a natural consequence of a sequencing sample is to assess the presence of features of interest by mapping the obtained reads to a genome of reference, sometimes it is useful to determine the fraction of those that do not map, or that map discordantly, and store this information to a new file for subsequent analyses. Here we propose a new mapper, which we called Squid, that among other accessory functionalities finds and returns sequencing reads that match or do not match to a reference sequence database in any orientation. We encourage the use of Squid prior to any quantification pipeline to assess, for instance, the presence of contaminants, especially in RNA-Seq experiments.

Human oral microbiome harbours hundreds of bacterial species, which, during evolution, assembled in different niches, such as the microbiome of saliva, tongue, hard palate, gingiva and dental plaque. Among these, saliva has been the most studied ecological niche of the oral microbiome. In this frame, scientific research has demonstrated that several factors concur to determine the saliva microbial composition, including diet, systemic diseases and drugs. However, the influence of such variables on other oral niches, such as the dental calculus, a calcified derivative of dental plaque, is still unexplored. During the last decade, dental calculus has become the primary target for evolutionary microbiome studies because of its ability to keep both bacterial DNA and dietary molecules (i.e., proteins and starch). As a consequence, dental calculus is now considered a powerful tool for obtaining information about oral microbiome composition, diet and individual health status in past populations, making it also appealing for clinical research. Here, we provide the first clinical study, to our knowledge, assessing the inter-variability of dental calculus microbiome in 40 patients. Samples were collected during routine dental inspection and analysed through 16S amplicon sequencing. In addition, we investigated the relationship between oral microbiome and host. Specifically, we tested the influence of Mediterranean diet style on the composition and functional pathways of oral bacteria, with the aim to test the dental calculus as a clinical bio-marker for diet impact and health status.

Environmental microbial exposures are hypothesized to drive immune profile differences across rural-urban gradients, yet direct evidence linking exposures to immune phenotypes remains limited. Here, we employed phage-displayed immunoprecipitation sequencing (PhIP-seq) to profile antibody repertoires against 357,192 epitopes from >700 organisms in 62 age-matched healthy adults from rural Senegal (n=29), urban Senegal (n=20), and urban Netherlands (n=13). PhIP-Seq analysis identified two major patterns of antibody repertoire variation: geographically restricted signatures distinguishing Senegal from the Netherlands, and a trajectory associated with rural-urban gradients spanning from rural Senegal to urban Netherlands. Integration of PhIP-seq data with high-dimensional immunological profiling revealed immune signatures correlated with the rural-urban antibody repertoire trajectory. Our findings demonstrate that antibody repertoire profiling captures distinct microbial exposure histories across both geographic regions and rural-urban gradients and correlates with variation in immune signatures. This work establishes PhIP-seq as a powerful tool for linking environmental exposure histories to population-level immune landscapes and provides insights into immune adaptation across diverse environments.

The emergence and rapid spread of the SARS-CoV-2 virus has highlighted the importance of genomic epidemiology in understanding the evolution of pathogens and for guiding public health interventions. In particular, the Omicron variant underscored the role of epistasis in the evolution of lineages with both higher infectivity and immune escape, and therefore the necessity to update surveillance pipelines to detect them as soon as they emerge. In this study we applied a method based on mutual information (MI) between positions in a multiple sequence alignment (MSA), which is capable of scaling up to millions of samples. We showed how it could reliably predict known experimentally validated epistatic interactions, even when using as little as 10,000 sequences, which opens the possibility of making it a near real-time prediction system. We tested this possibility by modifying the method to account for sample collection date and applied it retrospectively to MSAs for each month between March 2020 and March 2023. We could detect a cornerstone epistatic interaction in the Spike protein between codons 498 and 501 as soon as 6 samples with a double mutation were present in the dataset, thus demonstrating the method’s sensitivity. Lastly we provide examples of predicted interactions between genes, which are harder to test experimentally and therefore more likely to be overlooked. This method could become part of continuous surveillance systems tracking present and future pathogen outbreaks.