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Bellinzona, G.

Publications and source records attributed to Bellinzona, G..

4 recordsLinked to original sources

How to measure bacterial genome plasticity? A novel time-integrated index helps gather insights on pathogens

Genome plasticity can be defined as the capacity of a bacterial population to swiftly gain or lose genes. The time factor plays a fundamental role for the evolutionary success of microbes, particularly when considering pathogens and their tendency to gain antimicrobial resistance factors under the pressure of the extensive use of antibiotics. Multiple metrics have been proposed to provide insights into the gene content repertoire, yet they overlook the temporal component, which has a critical role in determining the adaptation and survival of a bacterial strain. In this study, we introduce a novel index that incorporates the time dimension to assess the rate at which bacteria exchange genes, thus fitting the definition of plasticity. Opposite to available indexes, our method also takes into account the possibility of contiguous genes being transferred together in one single event. We applied our novel index to measure plasticity in three widely studied bacterial species: Klebsiella pneumoniae, Staphylococcus aureus, and Escherichia coli. Our results highlight distinctive plasticity patterns in specific sequence types and clusters, suggesting a possible correlation between heightened genome plasticity and globally recognized high-risk clones. Our approach holds promise as an index for predicting the emergence of strains of potential clinical concern, possibly allowing for timely and more effective interventions. Impact statementHow quickly bacterial populations can acquire new functions is the key to their evolutionary success. This speed, called genome plasticity, is particularly relevant for human pathogens, especially when considering the acquisition of antimicrobial resistance. Today, the availability of large numbers of genomes from public databases makes it possible to develop a way to measure plasticity. However, none is currently available, besides indexes of gene content variability, which do not take into account the rate at which such gene content changes. In this work, we developed a plasticity index, called Flux Of Gene Segments (FOGS), and we tested it on large datasets of bacterial pathogen genomes. Interestingly, the subpopulations of the selected species that showed higher FOGS correspond to globally emerging high-risk clones. Therefore, we suggest that our index might be used not only to detect but also to predict emerging strains of human health concern. Data summaryThe authors confirm that all supporting data, code and protocols have been provided within the article or through supplementary data files.

genomics↗

Comparative genomics reveals the emergence of an outbreak-associated Cryptosporidium parvum population in Europe and its spread to the USA

The zoonotic parasite Cryptosporidium parvum is a global cause of gastrointestinal disease in humans and ruminants. Sequence analysis of the highly polymorphic gp60 gene enabled the classification of C. parvum isolates into multiple groups (e.g. IIa, IIc, Id) and a large number of subtypes. In Europe, subtype IIaA15G2R1 is largely predominant and has been associated with many water-and food-borne outbreaks. In this study, we generated new whole genome sequence (WGS) data from 123 human-and ruminant-derived isolates collected in 13 European countries and included other available WGS data from Europe, Egypt, China and the USA (n=72) in the largest comparative genomics study to date. We applied rigorous filters to exclude mixed infections and analysed a dataset from 141 isolates from the zoonotic groups IIa (n=119) and IId (n=22). Based on 28,047 high quality, biallelic genomic SNPs, we identified three distinct and strongly supported populations: isolates from China (IId) and Egypt (IIa and IId) formed population 1, a minority of European isolates (IIa and IId) formed population 2, while the majority of European (IIa, including all IIaA15G2R1 isolates) and all isolates from the USA (IIa) clustered in population 3. Based on analyses of the population structure, population genetics and recombination, we show that population 3 has recently emerged and expanded throughout Europe to then, possibly from the UK, reach the USA where it also expanded. In addition, genetic exchanges between different populations led to the formation of mosaic genomes. The reason(s) for the successful spread of population 3 remained elusive, although genes under selective pressure uniquely in this population were identified.

genomics↗

P-DOR, an easy-to-use pipeline to reconstruct outbreaks using pathogen genomics

Bacterial Healthcare Associated Infections (HAIs) are a major threat worldwide, which can be counteracted by establishing effective infection control measures, guided by constant surveillance and timely epidemiological investigations. Genomics is crucial in modern epidemiology but lacks standard methods and user-friendly software, accessible to users without a strong bioinformatics proficiency. To overcome these issues we developed P-DOR, a novel tool for rapid bacterial outbreak characterization. P-DOR accepts genome assemblies as input, it automatically selects a background of publicly available genomes using k-mer distances and adds it to the analysis dataset before inferring a SNP-based phylogeny. Epidemiological clusters are identified considering the phylogenetic tree topology and SNP distances. By analyzing the SNP-distance distribution, the user can gauge the correct threshold. Patient metadata can be inputted as well, to provide a spatio-temporal representation of the outbreak. The entire pipeline is fast and scalable and can be also run on low-end computers. Availability and implementationP-DOR is implemented in Python3 and R and can be installed using conda environments. It is available from GitHub https://github.com/SteMIDIfactory/P-DOR under the GPL-3.0 license.

microbiology↗

Host association and intracellularity evolved multiple times independently in the Rickettsiales

The order Rickettsiales (Alphaproteobacteria) encompasses multiple diverse lineages of host-associated bacteria, including pathogens, reproductive manipulators, and mutualists. In order to understand how intracellularity and host association originated in this order, and whether they are ancestral or convergently evolved characteristics, we built an unprecedentedly large and phylogenetically-balanced dataset that includes de novo sequenced genomes and an accurate selection of published genomic and metagenomic assemblies. We performed detailed functional reconstructions that clearly indicated "late" and parallel evolution of obligate host-association and intracellularity in different Rickettsiales lineages. According to the depicted scenario, multiple independent series of horizontal acquisitions of transporters led to the progressive loss of biosynthesis of nucleotides, amino acids and other metabolites, producing distinct conditions of host-dependence. Coherently, each clade experienced a different pattern of evolution of the ancestral arsenal of interaction apparatuses, including development of specialised effectors involved in the lineage-specific mechanisms of host cell adhesion/invasion and intracellularity.

microbiology↗