Evidence map›Paper›PMID 32824984›Full record

ArticleSensors (Basel, Switzerland)2020

Rapid Detection of β-Lactamase-Producing Bacteria Using the Integrated Comprehensive Droplet Digital Detection (IC 3D) System.

Yiyan Li, Hemanth Cherukury, Louai Labanieh, Weian Zhao, Dong-Ku Kang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Biosensors-on-Chip: An Up-to-Date Review.Molecules (Basel, Switzerland) · 2020
    Review
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.

Yiyan LiDepartment of Physics and Engineering, Fort Lewis College, Durango, CO 81301, USA.ORCID 0000-0002-1682-1108
Hemanth CherukuryDepartment of Pharmaceutical Sciences, University of California Irvine, Irvine, CA 92697, USA.
Louai LabaniehDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Weian ZhaoDepartment of Pharmaceutical Sciences, University of California Irvine, Irvine, CA 92697, USA.
Dong-Ku KangDepartment of Chemistry, Incheon National University, Incheon 22012, Korea.ORCID 0000-0003-1261-6446

Funding

Integrated Comprehensive Droplet Digital Detection (IC 3D) system for rapid detection of bacteria andantimicrobial resistanceR01AI117061 · NIAID · UNIVERSITY OF CALIFORNIA-IRVINE · PI ZHAO, WEIAN · 2015 to 2019
$5.1M
NIAID NIH HHS R01 AI117061Research Foundation of Korea (NRF) NRF2016R1A5A1010148Research Foundation of Korea (NRF) NRF-2017R1A6A1A06015181
6 · The paper itself

Abstract

Antibiotic-resistant bacteria have emerged as an imminent global threat. The lack of rapid and sensitive diagnostic techniques leaves health care providers with inadequate resources for guiding therapy and risks the lives of patients. The traditional plate culturing methods for identifying antibiotic-resistant bacteria is laborious and time-consuming. Bulk PCR (Polymerase Chain Reaction) and qPCR are limited by poor detection sensitivity, which is critical for the early-stage detection of bloodstream infections. In this study, we introduce a technique for detecting β-lactamase-producing bacteria at single-cell sensitivity based on a commercial β-lactamase sensor (Fluorocillin), droplet microfluidics, and a custom 3D particle counter. Bacteria-containing samples were encapsulated within picoliter-sized droplets at the single-cell level and cultured within water-in-oil droplets containing antibiotics and the Fluorocillin sensor. Then, fluorescent droplets were digitally quantified with the 3D particle counter, which is capable of analyzing milliliter-scale volumes of collected droplets within 10 min. The fluorescence signal from single-colony droplets was detectable in less than 5 h, and the 3D scanning was performed in less than 10 min, which was significantly faster than conventional culture-based methods. In this approach, the limit of detection achieved was about 10 bacterial cells per mL of sample, and the turnaround time from sample to result was less than 6 h. This study demonstrates a promising strategy for the detection of β-lactamase-producing bacteria using the recently developed IC 3D system.

Indexed as

Bacteriabeta-LactamasesSepsisBiosensing TechniquesHumansMicrofluidicsPolymerase Chain Reactionbeta-Lactamasesdigital quantificationdroplet microfluidicsIC 3D

Identifiers

PMID32824984
PMCPMC7506896

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.