ArticleThe Journal of infectious diseases2025
Development of a Rapid, Culture-Free, Universal Microbial Identification System Using Internal Transcribed Spacer Targeting Primers.
Article in The Journal of infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
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Who cites it
5 citing papers in PubMed.
- Integrating molecular and conventional diagnostics in native vertebral osteomyelitis: a narrative review.Journal of bone and joint infection · 2026Review
- Impact of FilmArray Gastrointestinal Panel Compared to Standard-of-Care Diagnostic Tests in Clinical Practice of Acute Gastroenteritis in an HIV Reference Center with Limited Resources.Diagnostics (Basel, Switzerland) · 2026Article
- Molecular Typing ofMicroorganisms · 2025Article
- Epidemiology of positive bacterial cultures and the coverage gaps in multiplex PCR diagnostics: a single-center retrospective study.Journal of clinical microbiology · 2025Article
- GenomicGapID: leveraging spatial distribution of conserved genomic sites for broad-spectrum microbial identification.Microbiology spectrum · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
The indiscriminate administration of broad-spectrum antibiotics is a primary contributor to the increasing prevalence of antibiotic resistance. Unfortunately, culture, the gold standard for bacterial identification is a time intensive process. Due to this extended diagnostic period, broad-spectrum antibiotics are generally prescribed to prevent poor outcomes. To overcome the deficits of culture-based methods, we have developed a rapid universal bacterial identification system. The platform uses a unique universal polymerase chain reaction primer set that targets the internal transcribed spacer regions between conserved bacterial genes, creating a distinguishable amplicon signature for every bacterial species. Bioinformatic simulation demonstrates that nearly every bacteria in a set of 45 commonly isolated pathogenic species can be uniquely identified using this approach. We experimentally confirmed these predictions on a representative set of pathogenic bacterial species. We further showed that the system can determine the corresponding concentration of each pathogen. Finally, we validated performance in clinical urinary tract infection samples.
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Registered trials
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.