To understand how organisms evolve, it is fundamental to study how mutations emerge and establish. Here, we estimated the rate of mutation accumulation of SARS-CoV-2 in vitro and investigated the repeatability of its evolution when facing a new cell type but no immune or drug pressures. We performed experimental evolution with two strains of SARS-CoV-2, one carrying the originally described spike protein (CoV-2-D) and another carrying the D614G mutation that has spread worldwide (CoV-2-G). After 15 passages in Vero cells and whole genome sequencing, we characterized the spectrum and rate of the emerging mutations and looked for evidences of selection across the genomes of both strains. From the frequencies of the mutations accumulated, and excluding the genes with signals of selection, we estimate a spontaneous mutation rate of 1.3 × 10⁻⁶ ± 0.2 × 10⁻⁶ per-base per-infection cycle (mean across both lineages of SARS-CoV-2 ± 2SEM). We further show that mutation accumulation is larger in the CoV-2-D lineage and heterogeneous along the genome, consistent with the action of positive selection on the spike protein, which accumulated five times more mutations than the corresponding genomic average. We also observe the emergence of mutators in the CoV-2-G background, likely linked to mutations in the RNA-dependent RNA polymerase and/or in the error-correcting exonuclease protein. These results provide valuable information on how spontaneous mutations emerge in SARS-CoV-2 and on how selection can shape its genome toward adaptation to new environments. Lay Summary: Each time a virus replicates inside a cell, errors (mutations) occur. Here, via laboratory propagation in cells originally isolated from the kidney epithelium of African green monkeys, we estimated the rate at which the SARS-CoV-2 virus mutates—an important parameter for understanding how it can evolve within and across humans. We also confirm the potential of its Spike protein to adapt to a new environment and report the emergence of mutators—viral populations where mutations occur at a significantly faster rate.

In response to the EFSA call New approaches in identifying and characterizing microbial and chemical hazards, the project INNUENDO (https://sites.google.com/site/theinnuendoproject/) aimed to design an analytical platform and standard procedures for the use of whole‐genome sequencing in surveillance and outbreak investigation of food‐borne pathogens. The project firstly attempted to identify existing flaws and needs, and then to provide applicable cross‐sectorial solutions. The project focused in developing a platform for small countries with limited economical and personnel resources. To achieve these goals, we applied a user‐centered design strategy involving the end‐users, such as microbiologists in public health and veterinary authorities, in every step of the design, development and implementation phases. As a result, we delivered the INNUENDO Platform V1.0 (https://innuendo.readthedocs.io/en/latest/), a stand‐alone, portable, open‐source, end‐to‐end system for the management, analysis, and sharing of bacterial genomic data. The platform uses Nextflow workflow manager to assemble analytical software modules in species‐specific protocols that can be run using a user‐friendly interface. The reproducibility of the process is ensured by using Docker containers and throught the annotation of the whole process using an ontology. Several modules, available at https://github.com/TheInnuendoProject, have been developed including: genome assembly and species confirmation; fast genome clustering; in silico typing; standardized species‐specific phylogenetic frameworks for Campylobacter jejuni, Yersinia enterocolitica, Salmonella enterica and Escherichia coli based on an innovative gene‐by‐gene methodology; quality control measures from raw reads to allele calling; reporting system; a built‐in communication protocols and a strain classification system enabling smooth communication during outbreak investigation. As proof‐of‐concepts, the proposed solutions have been thoroughly tested in simulated outbreak conditions by several public health and veterinary agencies across Europe. The results have been widely disseminated through several channels (web‐sites, scientific publications, organization of workshops). The INNUENDO Platform V1.0 is effectively one of the models for the usage of open‐source software in genomic epidemiology.

The spread of antibiotic resistant bacteria throughout the food chain constitutes a public health concern. To understand the contribution of fresh produce in shaping antibiotic resistance bacteria and integron prevalence in the food chain, 333 antibiotic resistance Gram negative isolates were collected from organic and conventionally produced fruits (pears, apples and strawberries) and vegetables (lettuces, tomatoes and carrots). Although low levels of resistance have been detected, the bacterial genera identified in the assessed fresh produce are often described not only as environmental, but mostly as commensals and opportunistic pathogens. The genomic characterization of integron-harboring isolates revealed a high number of mobile genetic elements and clinically relevant antibiotic resistance genes, of which we highlight the presence of as mcr-1, qnrA1, blaGES-11, mphA and oqxAB. The study of class 1 (n=8), class 2 (n=3) and class 3 (n=1) integrons, harbored by species such as Morganella morganii, Escherichia coli, Klebsiella pneumoniae, led to the identification of different integron promoters (PcW, PcH1, PcS and PcWTNG-10) and cassette arrays (containing drfA, aadA, cmlA, estX, sat and blaGES). In fact, the diverse integron backbones were associated with transposable elements (e.g. Tn402, Tn7, ISCR1, Tn2*, IS26, IS1326 and IS3) that conferred greater mobility. This is also the first appearance of In1258, In1259 and In3-13, which should be monitored to prevent their establishment as successfully dispersed mobile resistance integrons. These results underscore the growing concern about the dissemination of acquired resistance genes by mobile elements in the food chain.

Pathogen genome sequencing during epidemics enhances our ability to identify and understand suspected clusters and investigate their relationships. Here, we combine genomic and epidemiological data of the 2022 mpox outbreak to better understand early viral spread, diversification and transmission dynamics. By sequencing 52% of the confirmed cases in Portugal, we identified the mpox virus sublineages with the highest impact on case numbers and fitted them into a global context, finding evidence that several international sublineages probably emerged or spread early in Portugal. We estimated a 62% infection reporting rate and that 1.3% of the population of men who have sex with men in Portugal were infected. We infer the critical role played by sexual networks and superspreader gatherings, such as sauna attendance, in the dissemination of mpox virus. Overall, our findings highlight genomic epidemiology as a tool for the real-time monitoring and control of mpox epidemics, and can guide future vaccine policy in a highly susceptible population.