Evidence map›Paper›PMID 42251288›Full record

ArticleBMC microbiology2026

Impact of sample processing method and volume on 16 S rRNA profiling of the urobiome.

Sophie C Ramirez, Zachary J Lewis, Vanessa L Hale, Emily L Coffey

Abstract read
In one paragraph

Article in BMC microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sophie C Ramirez *University of Minnesota, College of Veterinary Medicine, Veterinary Medical Center, 1352 Boyd Avenue, Saint Paul, MN, 55108, USA.
Zachary J Lewis *Cornell University, College of Veterinary Medicine, 602 Tower Road, Ithaca, NY, 14853, USA.
Vanessa L HaleThe Ohio State University College of Veterinary Medicine, Columbus, OH, 43210, USA.
Emily L CoffeyUniversity of Minnesota, College of Veterinary Medicine, Veterinary Medical Center, 1352 Boyd Avenue, Saint Paul, MN, 55108, USA. coffe099@umn.edu.

Funding

CTSA K12 Program at University of MinnesotaK12TR004373 · NCATS · UNIVERSITY OF MINNESOTA · PI David H Ingbar · 2024 to 2026
$3.2M
Bladders and biomes: Environmental compounds as modifiers of microbiomes, metabolomes, and urotheliumK08ES034821 · NIEHS · OHIO STATE UNIVERSITY · PI Vanessa L Hale · 2023 to 2026
$668k
Veterinary Summer Scholars in Comparative MedicineT35OD011118 · OD · UNIVERSITY OF MINNESOTA · PI EDWARD E PATTERSON · 2012 to 2026
$601k
NCATS NIH HHS K12 TR004373NIEHS NIH HHS K08 ES034821NIH HHS 1K08ES034821-01A1NIH HHS K12TR004373NIH HHS T35 OD011118NIH HHS T35OD011118
6 · The paper itself

Abstract

backgroundThe urinary microbiome (urobiome) plays important roles in both human and animal urogenital tract health. Characterization of these microbial communities presents several technical challenges, largely due to the low microbial biomass of urine. Whereas other low biomass liquid systems, such as aquatic samples, frequently employ small-pore vacuum filtration for microbial DNA concentration, urobiome studies have traditionally relied on centrifugation and pelleting of smaller volumes. Therefore, this study compared the effects of processing method (vacuum filtration versus pelleting) and sample volume on bacterial DNA yield, contaminant burden, and microbial diversity in canine urine.

resultsA total of 50 urine aliquots were obtained across samples. Urine from 15 healthy dogs was pooled into five unique batches and divided into duplicate aliquots at volumes of 1, 3, 10, 30, and 50 mL. One aliquot was pelleted and one filtered (0.2 μm pore filter) prior to DNA extraction of the pellet or filter, respectively, and 16 S rRNA gene (V4) sequencing. Three aliquots ≥ 30 mL could not be filtered due to clogging. Sequence depth, DNA recovery, contaminant abundance, and microbial diversity were similar across urine volumes. Filtered samples contained a higher proportion of reads classified as contaminants (𝑃 = 0.002). Although beta diversity differed between methods (Bray-Curtis PERMANOVA, P = 0.007), the effect size was small (R

conclusionsThese findings indicate that interindividual variation predominates over methodological effects. Higher urine volumes (≥ 30 mL) were associated with technical challenges in filtered samples, whereas moderate urine volumes (1-10 mL) appear sufficient for urobiome characterization. Similar microbial recovery, increased contaminant signal, and occasional clogging with filtration suggests that pelleting remains an appropriate approach for urobiome characterization.

Indexed as

BacteriaMicrobiotaRNA, Ribosomal, 16SSpecimen HandlingUrinary TractUrineAnimalsDNA, BacterialDogsFemaleFiltrationSequence Analysis, DNADNA, BacterialRNA, Ribosomal, 16SCanineFiltrationMicrobiomeUrinary MicrobiomeUrobiome

Identifiers

PMID42251288
PMCPMC13445789

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.