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<metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>Negative-control-anchored urinary microbiome profiling with absolute 16S quantification</dc:title><dc:creator>Accetto,	Tomaž	(Avtor)
	</dc:creator><dc:creator>Strašek Smrdel,	Katja	(Avtor)
	</dc:creator><dc:creator>Taskovska,	Milena	(Avtor)
	</dc:creator><dc:creator>Starčič Erjavec,	Marjanca	(Avtor)
	</dc:creator><dc:creator>Smrkolj,	Tomaž	(Avtor)
	</dc:creator><dc:creator>Seme,	Katja	(Avtor)
	</dc:creator><dc:creator>Erdani-Kreft,	Mateja	(Avtor)
	</dc:creator><dc:subject>bladder cancer</dc:subject><dc:subject>midstream urine</dc:subject><dc:subject>microbiota</dc:subject><dc:subject>urinary tract infection</dc:subject><dc:subject>next-generation sequencing</dc:subject><dc:subject>nonmetric multidimensional scaling</dc:subject><dc:subject>absolute quantification</dc:subject><dc:subject>negative controls</dc:subject><dc:subject>low biomass</dc:subject><dc:description>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 &gt; 106 copies/ml typically produced &gt; 10 000 reads; near 105 copies/mlread counts dropped sharply yetremained distinguishable from background. Thirteen negative controls (V3–V4 PCR and stabilization buffer; median 90, mean 124 reads) supported excluding samples with &lt; 1000 reads. Median bacterial load was lower in BC than in controls (7.0 × 103 vs 1.07 × 106 copies/ml), although not significant in this underpowered cohort (P = 0.07). This cohort-size-independent framework enables load-based triage for sequencing, reduces backgrounddriven 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.</dc:description><dc:date>2026</dc:date><dc:date>2026-07-30 12:41:54</dc:date><dc:type>Članek v reviji</dc:type><dc:identifier>185282</dc:identifier><dc:identifier>UDK: 579:616.6</dc:identifier><dc:identifier>ISSN pri članku: 0378-1097</dc:identifier><dc:identifier>DOI: 10.1093/femsle/fnag020</dc:identifier><dc:identifier>COBISS_ID: 272226819</dc:identifier><dc:language>sl</dc:language></metadata>
