{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T07:03:58Z","timestamp":1784099038522,"version":"3.55.0"},"reference-count":28,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T00:00:00Z","timestamp":1784073600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Microbiol."],"abstract":"<jats:p>\n                    <jats:italic>Salmonella enterica<\/jats:italic>\n                    remains a leading cause of gastrointestinal infections worldwide, requiring rapid and accurate typing for effective outbreak management and clinical treatment. Traditional serological methods, such as the Kauffmann\u2013White scheme, are labor-intensive, time-consuming, and require specialized expertise. This study evaluated the IR Biotyper (IRBT) system, which combines Fourier-transform infrared (FTIR) spectroscopy with machine learning algorithms, for rapid classification of clinical\n                    <jats:italic>Salmonella<\/jats:italic>\n                    isolates at the O-serogroup level and for differentiating\n                    <jats:italic>S<\/jats:italic>\n                    . Typhi from non-typhoidal\n                    <jats:italic>Salmonella<\/jats:italic>\n                    (NTS) in a routine pediatric microbiology setting in the Middle East. A total of 164 clinical isolates from blood and stool cultures were analyzed, generating 1,925 spectra for serogroup classification and 790 spectra for the Typhi vs. NTS classifier. Using the Wellcolex\u2122 Color\n                    <jats:italic>Salmonella<\/jats:italic>\n                    kit as a reference, the IRBT O-group classifier achieved an overall accuracy of 98.2%, correctly identifying 161 of 164 isolates. The system reached 100% accuracy for Groups A (\n                    <jats:italic>n<\/jats:italic>\n                    = 4, 95% CI: 39.8%\u2013100%), A+E\/G (\n                    <jats:italic>n<\/jats:italic>\n                    = 5, 95% CI: 47.8%\u2013100%), B (\n                    <jats:italic>n<\/jats:italic>\n                    = 40, 95% CI: 91.2%\u2013100%), C+D (\n                    <jats:italic>n<\/jats:italic>\n                    = 13, 95% CI: 75.3%\u2013100%), D (\n                    <jats:italic>n<\/jats:italic>\n                    = 49, 95% CI: 92.7%\u2013100%), and isolates expressing the Vi antigen (\n                    <jats:italic>n<\/jats:italic>\n                    = 2, 95% CI: 15.8%\u2013100%), while Group E\/G showed lower accuracy at 89.5%. The Typhi vs. NTS classifier achieved 100% accuracy in both internal validation (\n                    <jats:italic>n<\/jats:italic>\n                    = 34, 95% CI: 89.8%\u2013100%) and independent testing (\n                    <jats:italic>n<\/jats:italic>\n                    = 31, 95% CI: 88.8%\u2013100%), demonstrating complete concordance with the Vi antiserum assay. These results indicate that FTIR spectroscopy offers a rapid, reliable, and user-friendly alternative to conventional serotyping, reducing turnaround time to under 2 h. Integration of this technology into clinical microbiology workflows provides a robust tool for real-time pathogen monitoring and enhanced public health response.\n                  <\/jats:p>","DOI":"10.3389\/fmicb.2026.1847592","type":"journal-article","created":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T06:05:30Z","timestamp":1784095530000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Fourier-transform infrared spectroscopy with machine learning for rapid O-serogrouping and typhi differentiation of clinical Salmonella isolates"],"prefix":"10.3389","volume":"17","author":[{"given":"Mohammed","family":"Suleiman","sequence":"first","affiliation":[{"name":"Department of Pathology, Sidra Medicine","place":["Doha, Qatar"]},{"name":"Department of Biomedical Sciences, Qatar University","place":["Doha, Qatar"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Princess","family":"Morales","sequence":"additional","affiliation":[{"name":"Department of Pathology, Sidra Medicine","place":["Doha, Qatar"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elizabeth","family":"Ilagan","sequence":"additional","affiliation":[{"name":"Department of Pathology, Sidra Medicine","place":["Doha, Qatar"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miriam","family":"Cordovana","sequence":"additional","affiliation":[{"name":"Bruker Daltonics GmbH & Co. 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