Acinetobacter species assigned to the Acinetobacter calcoaceticus-baumannii (Acb) complex, are Gram-negative bacteria responsible for a large number of human infections. The population structure of Acb has been studied using two 7-gene MLST schemes, introduced by Bartual and coworkers (Oxford scheme) and by Diancourt and coworkers (Pasteur scheme). The schemes have three genes in common but underlie two coexisting nomenclatures of sequence types and clonal complexes, which complicates communication on A. baumannii genotypes. The aim of this study was to compare the characteristics of the two schemes to make a recommendation about their usage. Using genome sequences of 730 strains of the Acb complex, we evaluated the phylogenetic congruence of MLST schemes, the correspondence between sequence types, their discriminative power and genotyping reliability from genomic sequences. In silico ST re-assignments highlighted the presence of a second copy of the Oxford gdhB locus, present in 553/730 genomes that has led to the creation of artefactual profiles and STs. The reliability of the two MLST schemes was tested statistically comparing MLST-based phylogenies to two reference phylogenies (core-genome genes and genome-wide SNPs) using topology-based and likelihood-based tests. Additionally, each MLST gene fragment was evaluated by correlating the pairwise nucleotide distances between each pair of genomes calculated on the core-genome and on each single gene fragment. The Pasteur scheme appears to be less discriminant among closely related isolates, but less affected by homologous recombination and more appropriate for precise strain classification in clonal groups, which within this scheme are more often correctly monophyletic. Statistical tests evaluate the tree deriving from the Oxford scheme as more similar to the reference genome trees. Our results, together with previous work, indicate that the Oxford scheme has important issues: gdhB paralogy, recombination, primers sequences, position of the genes on the genome. While there is no complete agreement in all analyses, when considered as a whole the above results indicate that the Pasteur scheme is more appropriate for population biology and epidemiological studies of A. baumannii and related species and we propose that it should be the scheme of choice during the transition toward, and in parallel with, core genome MLST.

No abstract

Background The rapid identification of pathogen clones is pivotal for effective epidemiological control strategies in hospital settings. High Resolution Melting (HRM) is a molecular biology technique suitable for fast and inexpensive pathogen typing protocols. Unfortunately, the mathematical/informatics skills required to analyse HRM data for pathogen typing likely limit the application of this promising technique in hospital settings. Results MeltingPlot is the first tool specifically designed for epidemiological investigations using HRM data, easing the application of HRM typing to large real-time surveillance and rapid outbreak reconstructions. MeltingPlot implements a graph-based algorithm designed to discriminate pathogen clones on the basis of HRM data, producing portable typing results. The tool also merges typing information with isolates and patients metadata to create graphical and tabular outputs useful in epidemiological investigations and it runs in a few seconds even with hundreds of isolates. Availability: https://skynet.unimi.it/index.php/tools/meltingplot/. Conclusions The analysis and result interpretation of HRM typing protocols can be not trivial and this likely limited its application in hospital settings. MeltingPlot is a web tool designed to help the user to reconstruct epidemiological events by combining HRM-based clustering methods and the isolate/patient metadata. The tool can be used for the implementation of HRM based real time large scale surveillance programs in hospital settings.

MeltingPlot is an open source web tool for pathogen typing and epidemiological investigations using High Resolution Melting (HRM) data. The tool implements a graph-based algorithm designed to discriminate pathogen clones on the basis of HRM data, producing portable typing results. MeltingPlot also merges typing information with isolates and patients metadata to create graphical and tabular outputs useful in epidemiological studies. HRM technique allows pathogen typing in less than 5 hours with ~5 euros per sample. MeltingPlot is the first tool specifically designed for HRM-based epidemiological studies and it can analyse hundreds of isolates in a few seconds. Thus, the use of MeltingPlot makes HRM-based typing suitable for large surveillance programs as well as for rapid outbreak reconstructions.

The SARS-CoV-2 pandemic that we are currently experiencing is exerting a massive toll both in human lives and economic impact. One of the challenges we must face is to try to understand if and how different variants of the virus emerge and change their frequency in time. Such information can be extremely valuable as it may indicate shifts in aggressiveness, and it could provide useful information to trace the spread of the virus in the population. In this work we identified and traced over time 7 amino acid variants that are present with high frequency in Italy and Europe, but that were absent or present at very low frequencies during the first stages of the epidemic in China and the initial reports in Europe. The analysis of these variants helps defining 6 phylogenetic clades that are currently spreading throughout the world with changes in frequency that are sometimes very fast and dramatic. In the absence of conclusive data at the time of writing, we discuss whether the spread of the variants may be due to a prominent founder effect or if it indicates an adaptive advantage.