{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T13:59:26Z","timestamp":1785419966089,"version":"3.56.0"},"reference-count":104,"publisher":"American Society for Microbiology","issue":"6","license":[{"start":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T00:00:00Z","timestamp":1781049600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T00:00:00Z","timestamp":1781049600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.asm.org\/non-commercial-tdm-license"}],"funder":[{"DOI":"10.13039\/100012774","name":"Innovationsfonden","doi-asserted-by":"publisher","award":["1045-00022A"],"award-info":[{"award-number":["1045-00022A"]}],"id":[{"id":"10.13039\/100012774","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100013467","name":"Association of Avian Veterinarians","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100013467","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100020229","name":"Loro Parque Fundaci\u00f3n","doi-asserted-by":"publisher","award":["PP-230\/LPF"],"award-info":[{"award-number":["PP-230\/LPF"]}],"id":[{"id":"10.13039\/100020229","id-type":"DOI","asserted-by":"publisher"}]},{"name":"H.P. Olsen og Hustrus Mindefond","award":["13518-001"],"award-info":[{"award-number":["13518-001"]}]},{"DOI":"10.13039\/501100007438","name":"Familien Hede Nielsens Fond","doi-asserted-by":"publisher","award":["2022-1394"],"award-info":[{"award-number":["2022-1394"]}],"id":[{"id":"10.13039\/501100007438","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007469","name":"Alfred Benzon Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100007469","id-type":"DOI","asserted-by":"publisher"}]},{"name":"European Association of Avian Veterinarians"}],"content-domain":{"domain":["journals.asm.org"],"crossmark-restriction":true},"short-container-title":["J Clin Microbiol"],"published-print":{"date-parts":[[2026,6,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title\/>\n                    <jats:p>\n                      Avian aspergillosis, caused by\n                      <jats:italic toggle=\"yes\">Aspergillus fumigatus<\/jats:italic>\n                      (\n                      <jats:italic toggle=\"yes\">Af<\/jats:italic>\n                      ), lacks sensitive antemortem diagnostics. Existing microbial cell-free DNA (cfDNA) tests are prone to contamination and require a high pathogen load. We hypothesized that infection-induced tissue damage in chickens creates differentially methylated regions (DMRs) in host cfDNA, enabling machine learning (ML) diagnostics. Serum cfDNA samples (\n                      <jats:italic toggle=\"yes\">n<\/jats:italic>\n                      = 124) were obtained from broiler chickens (\n                      <jats:italic toggle=\"yes\">n<\/jats:italic>\n                      = 76) with\n                      <jats:italic toggle=\"yes\">Af<\/jats:italic>\n                      and non-\n                      <jats:italic toggle=\"yes\">Af<\/jats:italic>\n                      infections (\n                      <jats:italic toggle=\"yes\">Escherichia coli<\/jats:italic>\n                      or\n                      <jats:italic toggle=\"yes\">Gallibacterium anatis<\/jats:italic>\n                      ) and controls. Oxford Nanopore sequencing enabled DMR detection and ML training. Performance was evaluated using an independent set (\n                      <jats:italic toggle=\"yes\">n<\/jats:italic>\n                      = 49) and 10-repeat Monte Carlo cross-validation (CV) (\n                      <jats:italic toggle=\"yes\">n<\/jats:italic>\n                      = 490 evaluations per test) as quality control. A High Accuracy test (93 DMRs, neural network) achieved 98.0% accuracy (sensitivity 95%, specificity 100%, AUC 0.974, PR-AUC 0.928) in the independent set, with CV accuracy 92.0% [95% CI: 89.7%\u201394.4%]. A Fast test (35 DMRs, SVM) achieved 81.6% accuracy and CV accuracy 79.6% [74.9%\u201384.3%]. An\n                      <jats:italic toggle=\"yes\">In Situ<\/jats:italic>\n                      test (5 DMRs, random forest) designed for field deployment achieved 71.4% accuracy and CV accuracy 62.9% [58.7%\u201367.0%]. Stratified CV accuracy showed 84.6% [65.1%\u201395.6%] correct classifications for\n                      <jats:italic toggle=\"yes\">E. coli<\/jats:italic>\n                      and 100% [80.5%\u2013100%] for\n                      <jats:italic toggle=\"yes\">G. anatis<\/jats:italic>\n                      . Markers showed high bootstrap stability and predominantly overlapped EMARs and enhancers. In conclusion, we present MethylSense (\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/markusdrag\/MethylSense\" xlink:type=\"simple\">https:\/\/github.com\/markusdrag\/MethylSense<\/jats:ext-link>\n                      ), an automated open-source software. The High Accuracy test achieved 92.0% [89.7%\u201394.4%] CV accuracy (CV sensitivity 94.5% [91.4%\u201397.6%], CV specificity 90.3% [87.8%\u201392.9%]). While validated in chickens, MethylSense is adaptable to other species and pathogens, offering scalable, contamination-resilient diagnostics for veterinary and conservation applications.\n                    <\/jats:p>\n                    <jats:sec>\n                      <jats:title>IMPORTANCE<\/jats:title>\n                      <jats:p>\n                        MethylSense is an automated software for training machine learning diagnostics using differentially methylated regions (DMRs) in cell-free DNA from Oxford Nanopore sequencing. We applied MethylSense to develop three\n                        <jats:italic toggle=\"yes\">Aspergillus fumigatus<\/jats:italic>\n                        tests for chickens, each optimized for different clinical scenarios. The High Accuracy test (93 DMRs, neural network) demonstrated 98.0% accuracy, in a blinded test set (\n                        <jats:italic toggle=\"yes\">n<\/jats:italic>\n                        = 49) with sensitivity 95%, specificity 100%, ROC-AUC 0.974, and PR-AUC 0.928. Stratified 10-repeat Monte Carlo cross-validation (\n                        <jats:italic toggle=\"yes\">n<\/jats:italic>\n                        = 490) showed correct classifications of 84.6% [CI: 65.1%\u201395.6%]\n                        <jats:italic toggle=\"yes\">Escherichia coli<\/jats:italic>\n                        and 100% [80.5%\u2013100%]\n                        <jats:italic toggle=\"yes\">Gallibacterium anatis<\/jats:italic>\n                        infected specificity samples. A Fast test for rapid &lt;1 h sequencing (35 DMRs, support vector machine) achieved 81.6% accuracy (sensitivity 80%, specificity 82.8%). An\n                        <jats:italic toggle=\"yes\">In Situ<\/jats:italic>\n                        test (5 DMRs, random forest) for field deployment via methylation-specific PCR achieved 71.4% accuracy (sensitivity 45%, specificity 89.7%). Bootstrap analysis demonstrated exceptional marker stability (80.6%\u2013100%) with minimal batch effects, confirming robust host-based diagnostics.\n                      <\/jats:p>\n                    <\/jats:sec>\n                  <\/jats:sec>","DOI":"10.1128\/jcm.01054-25","type":"journal-article","created":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T09:10:25Z","timestamp":1777281025000},"update-policy":"https:\/\/doi.org\/10.1128\/asmj-crossmark-policy-page","source":"Crossref","is-referenced-by-count":0,"title":["MethylSense: high accuracy machine learning-based diagnostics for\n                    <i>Aspergillus fumigatus<\/i>\n                    infection in chickens using host cell-free DNA methylation and Nanopore sequencing"],"prefix":"10.1128","volume":"64","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7412-6402","authenticated-orcid":true,"given":"Markus Hodal","family":"Drag","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/019950a73","id-type":"ROR","asserted-by":"publisher"}],"name":"Copenhagen Zoo","place":["Frederiksberg, Denmark"]},{"id":[{"id":"https:\/\/ror.org\/035b05819","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Veterinary and Animal Sciences, University of Copenhagen","place":["Frederiksberg C, Denmark"]},{"id":[{"id":"https:\/\/ror.org\/035b05819","id-type":"ROR","asserted-by":"publisher"}],"name":"Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen","place":["Copenhagen N, Denmark"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7870-6888","authenticated-orcid":true,"given":"Christina","family":"Hvilsom","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/019950a73","id-type":"ROR","asserted-by":"publisher"}],"name":"Copenhagen Zoo","place":["Frederiksberg, Denmark"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0675-1353","authenticated-orcid":true,"given":"Louise Ladefoged","family":"Poulsen","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/035b05819","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Veterinary and Animal Sciences, University of Copenhagen","place":["Frederiksberg C, Denmark"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Henrik Elvang","family":"Jensen","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/035b05819","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Veterinary and Animal Sciences, University of Copenhagen","place":["Frederiksberg C, Denmark"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1036-4898","authenticated-orcid":true,"given":"Stamatios Alan","family":"Tahas","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/019950a73","id-type":"ROR","asserted-by":"publisher"}],"name":"Copenhagen Zoo","place":["Frederiksberg, Denmark"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4241-7018","authenticated-orcid":true,"given":"Christoph","family":"Leineweber","sequence":"additional","affiliation":[{"name":"Laboklin GmbH & Co. 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