Evidence map›Paper›PMID 39579677›Full record

ArticleBiosensors & bioelectronics2025

Cross-kingdom pathogen detection via duplex universal PCR and high-resolution melt.

Pei-Wei Lee, Marissa Totten, Amelia Traylor, Sean X Zhang, Tza-Huei Wang, Kuangwen Hsieh

Abstract read
In one paragraph

Article in Biosensors & bioelectronics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

6 authors.

Pei-Wei LeeDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, United States.
Marissa TottenDivision of Microbiology, Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD, United States.
Amelia TraylorDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, United States.
Sean X ZhangDivision of Microbiology, Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD, United States.
Tza-Huei WangDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, United States; Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, United States. Electronic address: thwang@jhu.edu.
Kuangwen HsiehDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, United States. Electronic address: khsieh4@jhu.edu.

Funding

A "Culture" Shift: Integrated Bacterial Screening and Antibacterial Susceptibility Test on Microfluidic Digital Array for Bloodstream InfectionsR01AI137272 · NIAID · JOHNS HOPKINS UNIVERSITY · PI WANG, TZA-HUEI JEFF, YANG, SAMUEL · 2018 to 2022
$3.6M
T32: Predoctoral and Postdoctoral Training Program in Nanotechnology for Cancer ResearchT32CA153952 · NCI · JOHNS HOPKINS UNIVERSITY · PI Denis Wirtz · 2015 to 2026
$3.5M
Integrated genotype-informed single-cell molecular antibacterial susceptibility testing platform for rapid and actionable diagnosis of bacteremiaR01AI183336 · NIAID · JOHNS HOPKINS UNIVERSITY · PI Tza-Huei Jeff Wang · 2024 to 2026
$2.1M
Streamlined 15-min HIV Viral Load Self-Testing Using Finger-Stick BloodR33AI154628 · NIAID · JOHNS HOPKINS UNIVERSITY · PI HSIEH, YU-HSIANG, MANABE, YUKARI C · 2023 to 2024
$1.5M
NCI NIH HHS T32 CA153952NIAID NIH HHS R01 AI137272NIAID NIH HHS R01 AI183336NIAID NIH HHS R33 AI154628
6 · The paper itself

Abstract

Infectious diseases caused by pathogenic bacteria and fungi continuously pose a significant threat worldwide. The occurrence of polymicrobial infections, including polybacterial, polyfungal or bacteria-fungal co-infections further complicates diagnosis and treatment. Current diagnostic methods, heavily reliant on culture methods, are slow and often inefficient. This inefficiency underscores the urgent need for new diagnostic approaches that can swiftly identify a wide array of pathogens across both the bacterial and fungal kingdoms. In response to this need, our study introduces a duplex universal PCR and high-resolution melt (HRM) method that enables the detection of both bacterial and fungal pathogens within a single PCR-HRM procedure. This method uses two universal primer sets designed to target bacterial and fungal genomic DNA respectively, facilitating broad-range detection of 16 pathogens flagged by the World Health Organization (WHO). Moreover, this assay can be adapted in microfluidic-based digital reaction format and when analyzed via a one-versus-one support vector machine classifier achieved a detection accuracy exceeding 99.9%. This digital duplex PCR-HRM method has the capacity to quantitatively detect co-infections with varying pathogen ratios in simulated samples, demonstrating its versatility and multiplexed capacity. When applied to clinical bronchoalveolar lavage (BAL) samples, digital duplex PCR-HRM successfully identified both monomicrobial and polymicrobial infections. This development marks a significant advancement in the field of infectious disease diagnostics, offering a rapid, accurate, and comprehensive method for identifying a broad spectrum of bacterial and fungal pathogens, thus potentially improving patient management and outcomes.

Indexed as

BacteriaDNA, BacterialFungiBacterial InfectionsBiosensing TechniquesBronchoalveolar Lavage FluidCoinfectionDNA, FungalHumansMycosesPolymerase Chain ReactionDNA, BacterialDNA, Fungal

Identifiers

PMID39579677
PMCPMC11625404

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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.