Comparison of Two DNA Labeling Dyes Commonly Used to Detect Metabolically Active Bacteria.

Leena Malayil, Suhana Chattopadhyay, Neha Sripathi, Emmanuel F Mongodin, Amy R Sapkota

Abstract read

In one paragraph

Article in Microorganisms, 2025. 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

5 authors.

Leena MalayilDepartment of Global, Environmental, and Occupational Health, University of Maryland School of Public Health, College Park, MD 20742, USA.ORCID 0000-0002-8864-2678

Suhana ChattopadhyayDepartment of Global, Environmental, and Occupational Health, University of Maryland School of Public Health, College Park, MD 20742, USA.

Neha SripathiDepartment of Global, Environmental, and Occupational Health, University of Maryland School of Public Health, College Park, MD 20742, USA.

Emmanuel F MongodinInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA.ORCID 0000-0003-3833-7437

Amy R SapkotaDepartment of Global, Environmental, and Occupational Health, University of Maryland School of Public Health, College Park, MD 20742, USA.

Funding

National Institute of Health (NIH) and the Food and Drug Administration (FDA); United States Department of Agriculture-National Institute of Food and Agriculture P50-CA-180523-01; 2016-68007-25064the National Science Foundation National Research Traineeship Program 1828910United States Department of Agriculture-National Institute of Food and Agriculture 2016-68007-25064

6 · The paper itself

Abstract

Bacteria are ubiquitous in the environment and critical to human health and disease, yet only a small fraction can be identified through standard culture methods. Advances in next-generation sequencing techniques have improved bacterial identification, but these DNA-based methods cannot distinguish live bacteria from relic DNA. Recently, DNA-labeling dyes (e.g., 5-bromo-2'-deoxyuridine [BrdU] and propidium monoazide [PMA]) have been used to detect metabolically active bacteria in different sample types. Here, we compare BrdU and PMA in combination with 16SrRNA gene sequencing to characterize metabolically active bacteria in two different sample types: (1) manufactured products (

Indexed as

5-bromo-2′-deoxyuridineDNA labelingharvested rainwatermetabolically active bacterianext-generation sequencingpropidium monoazidetobacco products

Identifiers

PMID40431188

DOI10.3390/microorganisms13051015

PMCPMC12114394

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

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.