Background/Objectives: Bacterial outer membrane vesicles (OMVs) play a role in bacterial communication, virulence, antimicrobial resistance, and host-pathogen interaction. OMV isolation is a key step for studying these particles' functions; nevertheless, isolation procedures can greatly influence the yield, purity, and structural integrity of OMVs, thereby affecting downstream biological analyses and functional interpretation. Methods: In this study, we compared the efficacy of two OMV isolation techniques, differential ultracentrifugation (dUC) and size-exclusion chromatography (SEC), in separating and concentrating vesicles produced by two Escherichia coli strains belonging to uropathogenic (UPEC) and Shiga toxin-producing (STEC) pathotypes. The isolated OMVs were characterized using a multi-analytical approach including transmission and scanning electron microscopy (TEM, SEM), nanoparticle tracking analysis (NTA), dynamic light scattering (DLS), ζ-potential measurement, and protein quantification to assess the purity of the preparations. Results: Samples obtained by dUC exhibited higher total protein content, broader particle size distributions, and more pronounced contamination by non-vesicular material. In contrast, SEC yielded morphologically homogeneous and structurally well-preserved vesicles, higher particle-to-protein ratios, and lower total protein content, reflecting reduced co-isolation of protein aggregates. NTA and DLS analyses revealed polydisperse populations in samples obtained with both isolation methods, with DLS measurements highlighting the contribution of larger or transient aggregates. ζ-potential values were close to neutrality for all samples, consistent with limited electrostatic repulsion and with the aggregation tendencies observed in some preparations. Conclusions: This study describes features of OMV produced by two relevant E. coli strains considering two isolation strategies which exert method- and strain-dependent effects on vesicle properties, including size distribution and surface charge, and emphasizes the trade-offs between yield, purity, and vesicle integrity.

Hemolytic uremic syndrome associated with Shiga toxin-producing Escherichia coli (STEC-HUS) infection is a major individual and public health challenge, and the leading cause of acute kidney injury in children. In Western countries, HUS complicates about 15

Abstract 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. Impact statement [ This lay summary of your article should be no more than 200 words, and should a) provide a perspective of how this article adds to the literature in the field; b) identify breadth of interest/utility; and c) state the significance of output (incremental or step), in terms of relevance .] This study is based on the establishment of a One Health STEC genomes database, including sequences from isolates of different sources. Most of the isolates had been isolated in the ten-years’ time span 2010-2020, in 11 different countries, for surveillance and monitoring activities or specific surveys and research purposes. The final dataset included the whole genome sequencing of 3,418 STEC isolates, mainly from human cases of infections. The metadata included the host symptoms, where available, for human STEC strains and the animal source the strains had been isolated from. We set up a pipeline for the harmonized analysis of STEC WGS, called Discover, made available though ARIES webserver or GitHub. The analysis allowed a deep characterization of STEC strains circulating in Europe. We used this resource to assess STEC population structure and to investigate potential associations between genomic features, host reservoirs, and various symptoms associated with STEC infection by PCoA. This analysis highlighted the presence of subpopulation of human STEC associated with specific features. We provide new information useful for risk characterization, as well as a large dataset genome database and associated metadata compiled from STEC strains, representing a valuable resource for the scientific community, enabling further investigations into STEC diversity, evolution, source attribution and public health relevance. Data summary The authors confirm all supporting data, including sequence data accession numbers, code and protocols have been provided within the article or through supplementary data files. One supplementary method and five supplementary tables are available with the online version of this article

Surface-enhanced Raman spectroscopy (SERS) combined with machine learning (ML) has emerged as a powerful strategy for intelligent and automated biosensing. In this study, we present an in-house fabricated and data-driven SERS platform for automated discrimination of multiple experimental states within a nanostructured biosensor system. The sensing architecture was developed using reproducible gold nanoparticle-coated silicon substrates (Au NPs), synthesized and assembled in-house, followed by functionalization with a Raman reporter molecule (4-mercaptobenzoic acid, 4-MBA) or three biologically relevant targets: Escherichia coli, OC43 coronavirus, and Shiga toxin 2. The classification task was formulated as a six-class problem corresponding to distinct experimental sensor states: bare silicon substrate, Au NP-coated plasmonic substrate, 4-MBA-plasmonic functionalized surface, and plasmonic substrates functionalized with each biological target. Raman spectral data were processed through an automated analytical pipeline and evaluated using principal component analysis, linear discriminant analysis, support vector machines, random forest, and a one-dimensional convolutional neural network (1D-CNN). Among the evaluated models, the 1D-CNN achieved superior performance, providing the highest classification accuracy and robust discrimination across all six experimental classes. The results demonstrate that deep learning applied directly to normalized spectral vectors enhances feature extraction and class separability compared to conventional approaches. This work highlights the potential of integrating in-house engineered SERS nanoplatforms with automated ML frameworks for comprehensive sensor-state discrimination and next-generation intelligent biosensor development. Received: 29 December 2025 | Revised: 20 February 2026 | Accepted: 28 February 2026 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement The clean data that support the findings of this study are openly available in public repositories: https://github.com/BryanGuilcapi/Machine-Learning-Enhanced-SERS-on-Silicon-Gold-Sensors-for-Ultra-High-Throughput-Pathogen-Detection. The original database is accessible by requesting the corresponding author. Author Contribution Statement Bryan Guilcapi: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Data curation, Writing - original draft, Writing - review & editing, Visualization, Supervision. Alessia Milano: Software, Validation, Investigation, Data curation, Writing - review & editing. Amalia D' Avino: Investigation, Writing - review & editing. Domenico Sagnelli: Validation, Investigation. Massimo Rippa: Investigation. Valentina Marchesano: Investigation. Ivan Salvatore Perrotta: Investigation. Rosa Luisa Ambrosio: Investigation. Giovanna Fusco: Investigation. Maurizio Brigotti: Investigation, Writing - review & editing. Stefano Morabito: Resources. Lucia Petti: Resources, Writing - review & editing, Supervision, Project administration, Funding acquisition.

Yersinia enterocolitica and Yersinia pseudotuberculosis have been identified as microbiological factors in the multifactorial pathophysiology of inflammatory bowel disease (IBD). Although conventionally associated with self-limiting gastroenteritis, Yersinia has been increasingly investigated for its potential role in IBD, particularly in genetically predisposed individuals. Whether this reflects causality, opportunistic colonization, or secondary enrichment within inflamed tissue, however, remains unresolved. Polymerase chain reaction (PCR)-based studies have detected Yersinia DNA in the intestinal tissues of patients with IBD, and epidemiological studies have suggested an association between prior Yersinia infection and an increased long-term risk of disease. However, because most evidence is based on PCR detection, with limited culture-based confirmation of viable organisms and infrequent sequencing of PCR amplicons, these findings do not establish active infection or a causal relationship. These pathogens exploit abnormalities in the epithelial barrier and compromised mucosal immunity through type III/VI secretion systems to disrupt host responses, activate inflammasomes, and induce pyroptosis. Polymorphisms in autophagy-related genes, such as NOD2 and ATG16L1, impair pathogen clearance and increase susceptibility. While antibiotics continue to be effective against invasive diseases, the rise of resistance highlights the necessity for alternatives. Probiotic-based strategies have demonstrated immunomodulatory, antimicrobial, and barrier-protective effects in preclinical models, although their therapeutic efficacy in IBD requires further clinical validation. Comprehending Yersinia-host genetic interactions could facilitate precision diagnostics and microbiota-targeted treatments in IBD.

Top soil improvers (TSIs) and reused water from municipal wastewater treatment plants (WWTPs) represent useful and sustainable sources of organic carbon and nutrients for agriculture. However, from their regular use, emerging Escherichia coli enterophatotypes, particularly Shiga toxin-producing E. coli (STEC), were responsible for severe foodborne outbreaks from contaminated ready-to-eat vegetables. We report the hazard characterization of 31 top soil improvers (TSIs) and 15 irrigation water samples of different origins, sampled at the farm level. The increased PCR signals of the marker virulence genes stx1, stx2, aggR, aaiC, ipaH, lt, stp, and sth for enteropathogenic, enteroaggregative, enteroinvasive, enterotoxigenic, and Shiga toxin-producing E. coli from post-enrichment samples were considered proof of the presence of viable bacteria. Despite positive signals from TSI-enriched samples, we isolated one enteropathogenic and one enterotoxigenic strain from the same pig slurry sample and one STEC strain carrying the enterotoxigenic heat-stable enterotoxin from bovine slurry. From irrigation water samples, the most detected genes were stx1, stx2, and eae, followed by aggR, aaiC, ipaH, lt, stp, and sth, leading to one STEC (stx1+) isolation. E. coli pathotype virulotyping could be proposed to assess if combined TSI and water inputs would potentially lead to hybrid strains with shuffled virulence features to support safe and sustainable ready-to-eat vegetable production.

Shiga toxin-producing Escherichia coli (STEC) is responsible for severe human infections, including hemolytic uremic syndrome (HUS). Rapid and precise detection of Shiga toxins (Stxs) is crucial for timely diagnosis and treatment. In this study, we developed a nanostructured biosensor based on Surface-Enhanced Raman Spectroscopy (SERS) for the sensitive detection and differentiation of Stx1a, Stx2a, and its cleaved form (Stx2a-cl). The sensor utilizes a plasmonic metasurface featuring a hexagonal array of asymmetric nanocavities (NCs) in a gold film, designed to maximize near-field enhancement and SERS signal amplification. Specific antibodies were immobilized on the sensor surface, enabling selective binding of the target toxins. Principal Component Analysis (PCA) was applied to the acquired SERS spectra, demonstrating clear spectral differentiation among the toxins, including Stx2a and its cleaved form. The PCA results, with an explained variance exceeding 80%, confirm the sensor's high discrimination capability. These findings highlight the potential of the developed biosensor as a potential powerful diagnostic tool for the rapid and accurate detection of STEC infections in clinical and environmental settings.

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.

Hemolytic uremic syndrome (HUS), the main cause of acute renal failure in early childhood, is associated with infections by Escherichia coli strains producing Shiga toxin 2 (Stx2). The microangiopathic injuries caused by the toxin occur mainly in the renal microvasculature when the glycolipid receptor globotriaosylceramide (Gb3Cer) is targeted. Before entering the kidney, Stx2 binds to circulating cells through Gb3Cer and Toll-like receptor 4 (TLR4) and is subsequently delivered in extracellular vesicles to target cells. Here, we have found a specific inhibitor of the Stx2/TLR4 interaction, the preclinical polymyxin B derivative NAB815. The compound impairs the formation of Stx2-containing extracellular vesicles produced by leukocytes and platelets and also reduces their toxic effects in cellular (Vero cells) and animal models (CD-1 mice). NAB815 would represent a useful tool in preventing HUS and is effective at sub-bactericidal concentrations, thus overcoming the concern that antibiotics are harmful to patients infected with Stx2-producing E. coli.

Biosolids and reclaimed waters are valuable resources for reintroducing organic matter into agricultural soils and reducing the water footprint of intensive agricultural food system. While the circular economy is a sustainable practice, it may introduce vulnerabilities in the food chain, by exposing crops to zoonotic agents and antimicrobial resistance determinants. This option is far from being a speculation and evidence start to accumulate indicating that the risk is tangible. This study provides further evidence that the circular economy practices of reusing biomass and reclaimed waters in agricultural setting may be vectors for the spreading of antibiotic resistance genes (ARGs) targeting molecules used to treat human bacterial infections. We screened biosolid and water samples for ARGs presence using shotgun metagenomic sequencing. We demonstrated that the identified ARGs are present in live bacterial organisms, harbouring multidrug-resistant gene clusters, confirmed through phenotypic testing and whole-genome sequencing of isolated bacteria. Additionally, we observed that most of the antibiotic-resistant bacteria identified belonged to environmentally widespread species, which were not expected to be exposed to the antimicrobials, suggesting that inter-species transfer of resistance genes.

Plasmonic biosensors are powerful platforms for detecting various types of analytes. Specifically, surface-enhanced Raman spectroscopy (SERS) can enable label-free and selective detection. Shiga toxin-producing Escherichia coli (STEC) represents zoonotic pathogens that cause severe diseases, such as hemolytic uremic syndrome (HUS), the most important cause of acute renal failure in children. To date, there are no effective therapies for STEC infection, and the available diagnostic methods are complex and inconclusive. Here, a novel nanopattern fabricated by electron beam lithography with remarkable plasmonic properties is employed as SERS substrate for realizing the specific recognition of Stx1a, Stx2a, and of a third variation of the latter. A limit of detection (LOD) of 6.8 pM for Stx1a and 2 pM for Stx2a was achieved. Our approach supported using the principal component analysis (PCA) appears to be a valid alternative to conventional methods, allowing real-time and fast in situ analysis.

Shiga toxin (Stx)-producing Escherichia coli (STEC) harboring virulence determinants of Extraintestinal pathogenic E. coli (ExPEC) are currently emerging in Europe as a cause of severe disease. Among the ExPEC features identified in STEC, the gene hlyF is associated with an augmented production of Outer Membrane Vesicles (OMV). OMVs produced by E. coli strains have been shown to deliver toxins and small RNAs, but information on the latter genetic component is still scanty. We investigated the small RNAs contained in the OMVs produced by two hlyF-positive STEC strains producing Stx2 belonging to O26:H11 and O80:H2 serotypes, isolated from a human case of Hemolytic Uraemic Syndrome (HUS) and from a milk sample, respectively. The OMVs were purified from overnight cultures using two sequential ultracentrifugation steps at 100.000 and 200.000 x g of 2h each. The OMVs collected were analyzed by Nanoparticle Tracking Analysis (NTA) and Electron Microscopy (EM) to define their morphology, size and concentration. The whole genome sequences of the two test strains and three additional hlyF-positive STEC strains were analyzed to identify sequences of small RNAs. Specific Real Time PCR assays were deployed to detect the small RNAs within OMVs. The EM and NTA characterization confirmed the presence of spherical particles, and showed that a cleaner preparation was obtained after the second step of ultracentrifugation (200.000 x g). We identified the sequences of 27 putative small RNAs present in the genome of hlyF-positive STEC strains and absent in that of a non-pathogenic E. coli. Nine of them were identified and quantified in the OMVs produced by the two test strains. A regulatory role in bacterial DNA replication, integration and in stress-response was hypothesized for the identified small RNAs, some of which encompassing all the domains of life. STnc_100 was the only small RNA identified in the OMVs produced by both strains. Interestingly, a copy of STnc_100 sequence is harbored downstream the stx2 operon carried by Stx2-encoding phages in both the strains and has a complementarity region for stxB gene, suggesting a modulation in Stx production or release. Our results indicate that OMVs release may exert regulatory functions, putatively influencing the crosstalk with the host and the gut microbiota during the infection process.

IntroductionFree-living amoebae (FLA) are widespread protozoa that can host bacterial pathogens, promoting their persistence in the environment. Yersinia enterocolitica, a foodborne zoonotic pathogen, has been detected within amoebae, but its intracellular dynamics remain unclear.MethodsIn this study, we explored the interaction between three Y. enterocolitica strains—differing in biotype and virulence gene profile—and two Acanthamoeba spp.—a reference strain and a wild environmental isolate.Results and discussionAll strains were internalized and survived up to 8 days in the collection strain and 16 days in the wild isolate. Intracellular persistence did not affect amoebal integrity or bacterial virulence profiles. Whole genome sequencing (WGS) revealed high genomic stability across strains, though specific mutations—such as in the igaA gene, involved in stress response—emerged after persistence in the collection strain. These findings suggest that Acanthamoeba spp. not only shields Y. enterocolitica from environmental stress but may also influence its genome and adaptive potential. This work expands the current understanding of Y. enterocolitica biology and highlights the role of FLA as reservoirs and potential drivers of bacterial evolution. Their contribution to the bacteria persistence and gene exchange warrants further investigation, particularly in the context of antimicrobial resistance and food safety.

Shiga toxins-producing Escherichia coli (STEC) are zoonotic pathogens causing severe diseases such as hemorrhagic colitis (HC) and hemolytic uremic syndrome (HUS). Infections caused by STEC represent a public health concern due to the severity of the possible outcome and acute mortality. The early diagnosis of the infection is pivotal to driving a correct therapeutic protocol to limit the severity of the symptoms. The diagnosis is quite cumbersome, requires specialized approaches, and thus is rarely performed in the hospital, being managed by the relevant national reference laboratory, delaying the administration of the appropriate supportive care. In this context, the demand for affordable diagnostic tests to be carried out at the bedside is crucial for providing high-value healthcare. In this study, for the first time to the best of our knowledge, we developed and optimized a highly sensitive SERS-based platform that can detect and identify the two main Shiga toxin variants (Stx1 and Stx2a) as well as the cleaved form of Stx2a in human blood serum at extremely low concentrations with limits of detection reaching 0.007 ng/mL (0.1 pM). This method uses affordable, sensitive, and very efficient SERS substrates based on gold nanoparticle films, made with a cost-effective bottom-up approach, which are much cheaper than those typically found in the literature. Our results show that the platform works well in complex biological samples, offering high sensitivity and specificity. Moreover, integrating machine learning algorithms, such as principal component analysis (PCA), enables accurate identification of toxin types, overcoming the limitations of conventional diagnostic methods. This innovative approach represents a significant step toward accessible, rapid, and scalable clinical diagnostics, potentially transforming the early detection and management of STEC-related infections and preventing life-threatening complications.

Whole-genome sequencing (WGS) is increasingly used as the primary typing method for foodborne disease surveillance. It offers high-resolution cluster analysis, interoperability, and comprehensive pathogen characterization. However, implementing WGS-based foodborne surveillance also poses challenges. This paper outlines these challenges and provides practical recommendations. It requires a business plan that details the financial, technical and human resources needed, since setting up WGS-based surveillance requires substantial initial investments. During the initial phase, the per sample costs of WGS are likely higher than with traditional typing method. However, this will align or even go below that when fully transitioned to WGS-based surveillance because WGS data can be used for multiple purposes such as (sero)typing and antimicrobial and virulence characterization. It is advisable to start with a single pathogen to establish a solid foundation, with the aim of having one institutional sequencing facility. Validating accuracy and consistency of results is crucial before expanding to other pathogens. While cross-disciplinary collaboration has always played an important role in foodborne surveillance, the complexity of WGS results now makes it essential for transforming findings into effective interventions. Despite its challenges, advancements in technology and computation capabilities have made it increasingly accessible, ultimately improving public health surveillance and response.

This study investigates the plasmid sequences of porcine O139:H1 Shiga toxin-producing Escherichia coli (STEC) responsible for Edema Disease (ED). Whole-genome analysis reveals significant similarities between these strains and known plasmids, notably pW1316-2, which harbors key virulence genes like hemolysin (hlyA, hlyB) and adhesion factors (aidA-I, faeE). These genes contribute to the cytotoxicity and host colonization associated with ED. Additionally, similarities to plasmids from Shigella flexneri 2a highlight potential associations in virulence gene regulation, particularly via the Hha-H-NS complex. The identification of sequences resembling plasmid pB71 raises serious concerns about the emergence of highly pathogenic strains, as it includes tetracycline resistance genes (tetA, tetC, tetR). This research emphasizes the role of plasmid-like sequences in ED pathogenesis, indicating important implications for swine industry management and public health.

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 application of a One Health approach recognizes that human health, animal health, plant health and ecosystem health are intrinsically connected. Tackling complex challenges associated with foodborne zoonoses, antimicrobial resistance, and emerging threats is imperative. Therefore, the One Health European Joint Programme was established within the European Union research programme Horizon 2020. The One Health European Joint Programme activities were based on the development and harmonization of a One Health science-based framework in the European Union (EU) and involved public health, animal health and food safety institutes from almost all EU Member States, the UK and Norway, thus strengthening the cooperation between public, medical and veterinary organizations in Europe. Activities including 24 joint research projects, 6 joint integrative projects and 17 PhD projects, and a multicountry simulation exercise facilitated harmonization of laboratory methods and surveillance, and improved tools for risk assessment. The provision of sustainable solutions is integral to a One Health approach. To ensure the legacy of the work of the One Health European Joint Programme, focus was on strategic communication and dissemination of the outputs and engagement of stakeholders at the national, European and international levels.

BACKGROUND:Due to the diversity of Shiga toxin-producing Escherichia coli (STEC) isolates, detecting highly pathogenic strains in foodstuffs is challenging. Currently, reference protocols for STEC rely on the molecular detection of eae and the stx1 and/or stx2 genes, followed by the detection of serogroup-specific wzx or wzy genes related to the top 7 serogroups. However, these screening methods do not distinguish between samples in which a STEC possessing both determinants are present and those containing two or more organisms, each containing one of these genes. This study aimed to evaluate ecf1, Z2098, Z2099, and nleA genes as single markers and their combinations (ecf1/Z2098, ecf1/Z2099, ecf1/nleA, Z2098/Z2099, Z2098/nleA, and Z2099/nleA) as genetic markers to detect potentially pathogenic STEC by the polymerase chain reaction (PCR) in 96 animal samples, as well as in 52 whole genome sequences of human samples via in silico PCR analyses. RESULTS:In animal isolates, Z2098 and Z2098/Z2099 showed a strong association with the detected top 7 isolates, with 100% and 69.2% of them testing positive, respectively. In human isolates, Z2099 was detected in 95% of the top 7 HUS isolates, while Z2098/Z2099 and ecf1/Z2099 were detected in 87.5% of the top 7 HUS isolates. CONCLUSIONS:Overall, using a single gene marker, Z2098, Z2099, and ecf1 are sensitive targets for screening the top 7 STEC isolates, and the combination of Z2098/Z2099 offers a more targeted initial screening method to detect the top 7 STEC isolates. Detecting non-top 7 STEC in both animal and human samples proved challenging due to inconsistent characteristics associated with the genetic markers studied.