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Orzechowska, B.

Publications and source records attributed to Orzechowska, B..

2 recordsLinked to original sources

Salmonella Genomic Markers for Risk to Food Safety

Foodborne non-typhoidal Salmonella remains a major public health concern, yet many isolates recovered through food surveillance are not associated with human illness. To investigate whether genomic factors influence infection risk, we analysed whole-genome sequencing data from over 900 food and environmental isolates collected through UK Health Security Agency surveillance. Hierarchical clustering and comparative genomics identified distinct lineages associated with clinical cases, which were further contextualised using the global EnteroBase database. By combining pangenome and genome-wide association analyses, we identified distinct lineages within several serovars that differed in their association with human cases. In Salmonella Agona, all clinical isolates belonged to a single lineage carrying a highly conserved 7 kb marker that was absent from low-risk strains and demonstrated strong sensitivity and specificity across global datasets. This marker was located within a prophage closely related to the well-characterised Fels-2 phage and encodes a DNA invertase previously implicated in phase variation, a mechanism that promotes bacterial adaptability. Our findings indicate that infection risk can be structured at the lineage level and associated with mobile genomic elements, particularly prophages, that may contribute to environmental persistence and host adaptation. This work advances genomic surveillance from retrospective linkage towards mechanistic and predictive risk assessment, with direct relevance for supporting risk-based decision-making during outbreak investigations. IMPORTANCENot all strains found in food pose the same risk to human health, yet current surveillance systems generally treat them as equivalent hazards. We analysed over 900 genomes from food and environmental sources and found that human infection risk can be concentrated within specific genetic lineages rather than distributed across an entire serovar. In Salmonella Agona, we identified a highly conserved prophage-associated marker with strong sensitivity and specificity for infection-associated lineages. This marker was located within a prophage related to the well-characterised Fels-2 phage and encoded a DNA invertase previously associated to bacterial adaptation. These findings show how genome sequencing can move beyond outbreak detection to identify lineages with elevated public health relevance. Incorporating such information into surveillance programmes could improve risk-based decision-making, helping public health agencies prioritise investigations and interventions more effectively.

genomics↗

A unique Tandem RAman Microscopy (TRAM) integrating spontaneous and coherent Raman scattering offers integrated data analysis to improve optical biosensing

We provide Tandem RAman Microscopy (TRAM), a cutting-edge multimodal microscope that integrates the methods of Stimulated Raman Scattering (SRS), Coherent anti-Stokes Raman Scattering (CARS), and spontaneous (Resonance) Raman Scattering ((R)RS). The device facilitates sequential Continuous Wave (CW) driven RS imaging to collect full spectra from every sample location and rapid pulsed-wave-driven SRS-CARS scanning at specific wavenumbers, offering a reliable and efficient analytical tool. The fingerprint spectral region can be included in the spectral imaging capabilities of CARS and SRS. Data collected from a sample area using several techniques can be integrated and analyzed, significantly increasing reliability and predictions. We analyzed the in vitro model of nonadherent leukocytes (LC) to illustrate the capabilities of this unique system, emphasizing the benefits of measuring the same sample with three different Raman techniques without having to transfer it between microscopes. Data fusion allowed for the correct classification of two subtypes of LC based on the partial least squares (PLS) discrimination, increasing the prediction accuracy from approximately 83% in the case of textural and morphological data (SRS) to 100% when combined with spectral data (SRS and RS). We also present RRS images of LC labeled with astaxanthin, and reference data from SRS and CARS microscopy. Additionally, polystyrene beads were investigated as a non-biological material. The advantages of each Raman technique are utilized when (R)RS, SRS, and CARS are combined into a single device. This paves the way for dependable chemical characterization in a wide range of scientific and industrial fields.

biophysics↗