in this work we present easyprimer, a user-friendly online tool developed to assist pan-pcR and High Resolution Melting (HRM) primer design. The tool finds the most suitable regions for primer design in a gene alignment and returns a clear graphical representation of their positions on the consensus sequence. EasyPrimer is particularly useful in difficult contexts, e.g. on gene alignments of hundreds of sequences and/or on highly variable genes. HRM analysis is an emerging method for fast and cost saving bacterial typing and an HRM scheme of six primer pairs on five Multi-Locus Sequence Type (MLST) genes is already available for Klebsiella pneumoniae. We validated the tool designing a scheme of two HRM primer pairs on the hypervariable gene wzi of Klebsiella pneumoniae and compared the two schemes. the wzi scheme resulted to have a discriminatory power comparable to the HRM MLST scheme, using only one third of primer pairs. then we successfully used the wzi HRM primer scheme to reconstruct a Klebsiella pneumoniae nosocomial outbreak in few hours. the use of hypervariable genes reduces the number of HRM primer pairs required for bacterial typing allowing to perform cost saving, large-scale surveillance programs.Most methods used for the identification and typing of prokaryotes are based on DNA amplification and sequencing. Indeed, the sequence of specific genes can harbour enough information to classify bacteria at species, subspecies or also to a clonal level. For instance, Multi-Locus Sequence Typing (MLST) is one of the most used methods for bacterial typing and it is based on the amplification and sequencing of few housekeeping genes 1 . During the last ten years, the analysis of the entire bacterial genome by Whole Genome Sequencing (WGS) approach revolutionized the field, drastically increasing the typing precision 1 .The reconstruction of nosocomial outbreaks is one of the most important clinical applications of bacterial typing. A nosocomial outbreak occurs when the number of patients infected by a pathogen increases above the expected in a limited time 2 . In these situations, it is fundamental to determine the clonality of bacteria causing disease in the patients to define the proper strategy to handle the emergency. Pulsed-Field Gel Electrophoresis (PFGE), MLST and WGS are the most frequently applied molecular methods in outbreak investigation 1 .During a nosocomial outbreak, clinicians need bacterial typing information in the shortest time possible. Despite the high potential of WGS in outbreak reconstruction, the sequencing of a complete genome requires two to four working days, introducing an important time lag. Similarly, PFGE typing requires five days and also MLST needs few days. During the last years, the High Resolution Melting (HRM) assay has emerged as a low-cost and fast method for bacterial typing, particularly promising for epidemiological applications 3-6 . HRM is a single-step

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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.

High resolution melting (HRM) is a fast closed-tube method for nucleotide variant scanning applicable for bacterial species identification or molecular typing. Recently a novel HRM-based method for Klebsiella pneumoniae typing has been proposed: it consists of an HRM protocol designed on the capsular wzi gene and an HRM-based algorithm of strains clustering. In this study, we evaluated the repeatability and reproducibility of this method by performing the HRM typing of a set of K. pneumoniae strains, on three different instruments and by two different operators. The results showed that operators do not affect melting temperatures while different instruments can. Despite this, we found that strain clustering analysis, performed using MeltingPlot separately on the data from the three instruments, remains almost perfectly consistent. The HRM method under study resulted highly repeatable and thus reliable for large studies, even when several operators are involved. Furthermore, the HRM clusters obtained from the three different instruments were highly conserved, suggesting that this method could be applied in multicenter studies, even if different instruments are used.

The first identification of autochthonous transmission of SARS‐CoV‐2 in Italy was documented by the Laboratory of Clinical Microbiology, Virology and Bioemergencies of L. Sacco Hospital (Milano, Italy) on 20th February 2020 in a 38 years old male patient, who was found positive for pneumonia at the Codogno Hospital. Thereafter Lombardy has reported the highest prevalence of COVID‐19 cases in the country, especially in Milano, Brescia and Bergamo provinces. The aim of this study was to assess the potential presence of different viral clusters belonging to the six main provinces involved in Lombardy COVID‐19 cases in order to highlight peculiar province‐dependent viral characteristics. A phylogenetic analysis was conducted on 20 full length genomes obtained from patients addressing to several Lombard hospitals from February 20th to April 4th, 2020, aligned with 41 Italian viral genome assemblies available on GISAID database as of 30th March, 2020: two main monophyletic clades, containing 8 and 53 isolates, respectively, were identified. Noteworthy, Bergamo isolates mapped inside the small clade harbouring M gene D3G mutation. The molecular clock analysis estimated a cluster divergence approximately one month before the first patient identification, supporting the hypothesis that different SARS‐CoV‐2 strains had spread worldwide at different times, but their presence became evident only in late February along with Italian epidemic emergence. Therefore, this epidemiological reconstruction suggests that virus initial circulation in Lombardy was ascribable to multiple introduction. The phylogenetic reconstruction robustness, however, will be improved when more genomic sequences are available, in order to guarantee a complete epidemiological surveillance. This article is protected by copyright. All rights reserved.