{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T05:06:02Z","timestamp":1793163962722,"version":"4.5.0"},"reference-count":19,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T00:00:00Z","timestamp":1771286400000},"content-version":"vor","delay-in-days":47,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004329","name":"The Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["J7-2594"],"award-info":[{"award-number":["J7-2594"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Recent studies utilizing 16S rRNA amplicon sequencing have challenged the notion of urine sterility, yet urine is a low-biomass specimen in which apparent community profiles can be strongly influenced by background signal from reagents and processing. To address this interpretability gap, we integrate culture-independent absolute 16S rRNA gene quantification with urinary 16S amplicon sequencing in a negative-control-anchored workflow. Bacterial load provides a biomass-aware quality control gate that defines interpretable low-biomass thresholds and objective exclusion criteria. As a pilot application, we compared midstream urine collected prior to instrumentation from healthy volunteers and newly diagnosed bladder cancer (BC) patients, quality filtering retained 29 controls and 5 BC cases. Samples &amp;gt;\u00a0106 copies\/ml typically produced\u00a0&amp;gt;\u00a010\u2009000 reads; near 105 copies\/ml read counts dropped sharply yet remained distinguishable from background. Thirteen negative controls (V3\u2013V4 PCR and stabilization buffer; median 90, mean 124 reads) supported excluding samples with\u00a0&amp;lt;\u00a01000 reads. Median bacterial load was lower in BC than in controls (7.0\u2009\u2009\u00d7\u2009103\u00a0vs 1.07\u00a0\u00d7\u00a0106 copies\/ml), although not significant in this underpowered cohort (P\u00a0=\u00a00.07). This cohort-size-independent framework enables load-based triage for sequencing, reduces background-driven over-interpretation in low-biomass urine datasets, and supports modeling bacterial load as a covariate or stratifier in future studies of the bladder cancer microbiome.<\/jats:p>","DOI":"10.1093\/femsle\/fnag020","type":"journal-article","created":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T12:30:24Z","timestamp":1771331424000},"source":"Crossref","is-referenced-by-count":1,"title":["Negative-control-anchored urinary microbiome profiling with absolute 16S quantification: a pilot study in newly diagnosed, treatment-naive bladder cancer and healthy individuals"],"prefix":"10.1093","volume":"373","author":[{"given":"Toma\u017e","family":"Accetto","sequence":"first","affiliation":[{"name":"Department of Microbiology, Biotechnical Faculty, University of Ljubljana , SI-1000 Ljubljana 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