Arnold Knijn

Shiga toxin-producing Escherichia coli (STEC) are important foodborne pathogens, able to cause severe disease in humans. In the DiSCoVeR project (https://onehealthejp.eu/jrp-discover/) a STEC inventory from human and non-human sources from 11 European countries was set up and ≥ 3500 strains were sequenced to perform comparative genomics analysis. We used this dataset to assess STEC population structure and to investigate potential associations between genomic features, host reservoirs and symptoms. Most STEC isolates analysed by Whole Genome Sequencing (WGS) in this study were collected between years 2010-2020. An ad hoc pipeline was deployed for a harmonised characterization of the STEC in the database, allowing the determination of serotyping, stx gene subtyping, 7-loci MLST, virulotyping and cgMLST. The results were analysed with Principal Component Analysis (PCoA) in relation with isolation source to assess clustering of STEC subpopulations. When human STEC data were analysed, the PCoA revealed three distinct human STEC subpopulations (STEC_1, STEC_2 and STEC_3), which were further analysed for associations between genomic features, symptoms and variance. The non-human STEC showed a more dispersed distribution, except for one subpopulation with genes linked to specific host species, and some virulence profiles overlapping with the STEC_1 population. In conclusion, our analysis identified distinct STEC subpopulations from human cases, each characterized by specific genetic features and associated with varying proportions of severe disease outcomes. These findings provide novel insights supporting the risk assessment of STEC.

Whole-genome sequence (WGS) analysis was used in this study to characterize Shiga toxin-producing Escherichia coli (STEC) isolates in free-ranging red deer from the central Italian Alps. Fecal samples from 92 hunted red deer collected between September and December 2022 were analyzed for the presence of STEC. Single E. coli colonies positive by PCR for stx genes were analyzed by WGS. STEC were isolated from eleven (12%) samples, showing eight stx2b, one stx2a, two stx1c, and one stx1a subtypes. Different serotypes and sequence types were identified (n = 8 each). Three isolates of O27:H30 serotype and ST753 showed no correlation in the cgMLST analysis (AD range 44–98). All strains harbored additional virulence factors. The only isolate harboring stx2a also possessed the eae gene and belonged to serotype O26:H11. Some isolates displayed shuffled virulence features of more than one E. coli pathotype. The high genetic diversity of strains circulating in the red deer population living in the central Italian Alps, including the STEC O26:H11 strain associated with STEC from severe disease in humans, confirms red deer as STEC reservoirs and highlights the need for monitoring the presence of these pathogens in wild ruminants.

In this work, we studied the selective pressure and evolutionary analysis on the SARS-CoV-2 BF.7 and BQ.1.1 lineages circulating in Italy from July to December 2022. Two different datasets were constructed: the first comprised 694 SARS-CoV-2 BF.7 lineage sequences and the second comprised 734 BQ.1.1 sequences, available in the Italian COVID-19 Genomic (I-Co-Gen) platform and GISAID (last access date 15 December 2022). Alignments were performed with MAFFT v.7 under the Galaxy platform. The HYPHY software was used to study the selective pressure. Four positively selected sites (two in nsp3 and two in the spike) were identified in the BF.7 dataset, and two (one in ORF8 and one in the spike gene) were identified in the BQ.1.1 dataset. Mutation analysis revealed that R408S and N440K are very common in the spike of the BF.7 genomes, as well as L452R among BQ.1.1. N1329D and Q180H in nsp3 were found, respectively, at low and rare frequencies in BF.7, while I121L and I121T were found to be rare in ORF8 for BQ.1.1. The positively selected sites may have been driven by the selection for increased viral fitness, under circumstances of defined selective pressure, as well by host genetic factors.

The SARS-CoV-2 Delta variant of concern (VOC) was often associated with serious clinical course of the COVID-19 disease. Herein, we investigated the selective pressure, gene flow and evaluation on the frequencies of mutations causing amino acid substitutions in the Delta variant in three Italian regions. A total of 1500 SARS-CoV-2 Delta genomes, collected in Italy from April to October 2021 were investigated, including a subset of 596 from three Italian regions. The selective pressure and the frequency of amino acid substitutions and the prediction of their possible impact on the stability of the proteins were investigated. Delta variant dataset, in this study, identified 68 sites under positive selection: 16 in the spike (23.5%), 11 in nsp2 (16.2%) and 10 in nsp12 (14.7%) genes. Three of the positive sites in the spike were located in the receptor-binding domain (RBD). In Delta genomes from the three regions, 6 changes were identified as very common (>83.7%), 4 as common (>64.0%), 21 at low frequency (2.1%–25.0%) and 29 rare (≤2.0%). The detection of positive selection on key mutations may represent a model to identify recurrent signature mutations of the virus.

Pathogen genomics is transforming surveillance of infectious diseases, deepening our understanding of evolution and diffusion of etiological agents, host-pathogen interactions and antimicrobial resistance. This discipline is playing an important role in the development of One Health Surveillance with public health experts of various disciplines integrating methods applied to pathogen research, monitoring, management and prevention of outbreaks. Especially with the notion that foodborne diseases may not be transmitted by food only, the ARIES Genomics project aimed to deliver an Information System for the collection of genomic and epidemiological data to enable genomics-based surveillance of infectious epidemics, foodborne outbreaks and diseases at the animal-human interface. Keeping in mind that the users of the system comprised persons with expertise in a wide variety of domains, the system was expected to be used with a low learning curve directly by the persons target of the analyses' results, keeping the information exchange chains as short as possible. As a result, the IRIDA-ARIES platform (https://irida.iss.it/) provides an intuitive web-based interface for multisectoral data collection and bioinformatic analyses. In practice, the user creates a sample and uploads the Next-generation sequencing reads, then an analysis pipeline is launched automatically performing a series of typing and clustering operations fueling the information flow. Instances of IRIDA-ARIES host the Italian national surveillance system for infections by Listeria monocytogenes (Lm) and the surveillance system for infections by Shigatoxin-producing Escherichia coli (STEC). As of today, the platform does not provide tools to manage epidemiological investigations but serves as an instrument of aggregation for risk monitoring, capable of triggering alarms on possible critical situations that might go unnoticed otherwise.

Background: Since its first appearance in December 2019, the novel Severe Acute Respiratory Syndrome Coronavirus type 2 (SARS-CoV-2), spread worldwide causing an increasing number of cases and deaths (35,537,491 and 1,042,798, respectively at the time of writing, https://covid19.who.int ). Similarly, the number of complete viral genome sequences produced by Next Generation Sequencing (NGS), increased exponentially. NGS enables a rapid accumulation of a large number of sequences. However, bioinformatics analyses are critical and require combined approaches for data analysis, which can be challenging for non-bioinformaticians. Results: A user-friendly and sequencing platform-independent bioinformatics pipeline, named SARS-CoV-2 RECoVERY (REconstruction of CoronaVirus gEnomes & Rapid analYsis) has been developed to build SARS-CoV-2 complete genomes from raw sequencing reads and to investigate variants. The genomes built by SARS-CoV-2 RECoVERY were compared with those obtained using other software available and revealed comparable or better performances of SARS–CoV2 RECoVERY. Depending on the number of reads, the complete genome reconstruction and variants analysis can be achieved in less than one hour. The pipeline was implemented in the multi-usage open-source Galaxy platform allowing an easy access to the software and providing computational and storage resources to the community. Conclusions: SARS-CoV-2 RECoVERY is a piece of software destined to the scientific community working on SARS-CoV-2 phylogeny and molecular characterisation, providing a performant tool for the complete reconstruction and variants’ analysis of the viral genome. Additionally, the simple software interface and the ability to use it through a Galaxy instance without the need to implement computing and storage infrastructures, make SARS-CoV-2 RECoVERY a resource also for virologists with little or no bioinformatics skills. Availability and implementation: The pipeline SARS-CoV-2 RECoVERY (REconstruction of COronaVirus gEnomes & Rapid analYsis) is implemented in the Galaxy instance ARIES ( https://aries.iss.it ).

Enteroinvasive Escherichia coli (EIEC) cause intestinal illness through the same pathogenic mechanism used by Shigella spp. The latter species can be typed through genomic and phenotypic methods used for E. coli and have been proposed for reclassification within E. coli species. Recently the first appearance of a highly pathogenic EIEC O96:H19 was described in Europe as the causative agent of two large outbreaks that occurred in Italy and in the United Kingdom. In contrast to Shigella spp and to the majority of EIEC strains, EIEC O96:H19 fermented lactose, lacked pathoadaptive mutations, and showed good fitness in extracellular environment, similarly to non-pathogenic E. coli, suggesting they have emerged following acquisition of the invasion plasmid by a non-pathogenic E. coli. Here we describe the whole genome comparison of two EIEC O96:H19 strains isolated from severe cases of diarrhea in Uruguay in 2014 with the sequences of EIEC O96:H19 available in the public domain. The phylogenetic comparison grouped all the O96:H19 strains in a single cluster, while reference EIEC strains branched into different clades with Shigella strains occupying apical positions. The comparison of the virulence plasmids showed the presence of a complete conjugation region in at least one O96:H19 EIEC. Reverse Transcriptase Real Time PCR experiments confirmed in this strain the expression of the pilin-encoding gene and conjugation experiments suggested its ability to mobilize an accessory plasmid in a recipient strain. Noteworthy, the tra region was comprised between two reversely oriented IS600 elements, which were also found as remnants in another EIEC O96:H19 plasmid lacking the tra locus. We hypothesize that an IS-mediated recombination mechanism may have caused the loss of the conjugation region commonly observed in EIEC and Shigella virulence plasmids. The results of this study support the hypothesis of EIEC originating from non-pathogenic E. coli through the acquisition of the virulence plasmid via conjugation. Remarkably, this study showed the ability of a circulating EIEC strain to mobilize plasmids through conjugation, suggesting a mechanism for the emergence of novel EIEC clones.

Background: With the introduction of Next Generation Sequencing (NGS) and Whole-Genome Sequencing (WGS) in microbiology and molecular epidemiology, the development of an information system for the collection of genomic and epidemiological data and subsequent transparent and reproducible data analysis became indispensable. Further requirements for the system included accessibility and ease of use by bioinformatics as well as command line profane scientists. Findings: The ARIES (Advanced Research Infrastructure for Experimentation in genomicS, https://aries.iss.it ) platform has been implemented in 2015 as an instance of the Galaxy framework specific for use of WGS in molecular epidemiology. Here, the experience with ARIES is reported. Conclusions: During its five years existence, ARIES has grown into a well-established reality not only as a web service but as well as a workflow engine for the Integrated Rapid Infectious Disease Analysis (IRIDA) platform. In fact, an environment has been created with the implementation of complex bioinformatic tools in an easy-to-use context allowing scientists to concentrate on what to do instead of how to do it.