Evidence map›Paper›PMID 33899069›Full record

ArticleThe Analyst2021

Facile syringe filter-enabled bacteria separation, enrichment, and buffer exchange for clinical isolation-free digital detection and characterization of bacterial pathogens in urine.

Pengfei Zhang, Aniruddha M Kaushik, Kathleen E Mach, Kuangwen Hsieh, Joseph C Liao, Tza-Huei Wang

Abstract read
In one paragraph

Article in The Analyst, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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.

Pengfei ZhangDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA. thwang@jhu.edu.ORCID http://orcid.org/0000-0002-8578-8305
Aniruddha M KaushikDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA.
Kathleen E MachDepartment of Urology, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-1197-4073
Kuangwen HsiehDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA.
Joseph C LiaoDepartment of Urology, Stanford University School of Medicine, Stanford, CA, USA.
Tza-Huei WangDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA. thwang@jhu.edu and Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA.

Funding

A Droplet-based single cell platform for pathogen identification and ASTR01AI117032 · NIAID · JOHNS HOPKINS UNIVERSITY · PI LIAO, JOSEPH C, WANG, TZA-HUEI JEFF · 2015 to 2019
$5.7M
Technology development for point-of-care detection and antimicrobial susceptibility testing of Neisseria gonorrhoeaeR01AI138978 · NIAID · JOHNS HOPKINS UNIVERSITY · PI WANG, TZA-HUEI JEFF · 2018 to 2021
$5.1M
NIAID NIH HHS R01 AI117032NIAID NIH HHS R01 AI138978
6 · The paper itself

Abstract

The development of accelerated methods for pathogen identification (ID) and antimicrobial susceptibility testing (AST) for infectious diseases is necessary to facilitate evidence-based antibiotic therapy and reduce clinical overreliance on broad-spectrum antibiotics. Towards this end, droplet-based microfluidics has unlocked remarkably rapid diagnostic assays with single-cell and single-molecule resolution. Yet, droplet platforms invariably rely on testing purified bacterial samples that have been clinically isolated after lengthy (>16 h) plating. While plating-based clinical isolation is important for enriching and separating out bacteria from background in clinical samples and also facilitating buffer exchange, it creates a diagnostic bottleneck that ultimately precludes droplet-based methods from achieving significantly accelerated times-to-result. To alleviate this bottleneck, we have developed facile syringe filter-enabled strategies for bacterial separation, enrichment, and buffer exchange from urine samples. By selecting appropriately sized filter membranes, we separated bacterial cells from background particulates in urine samples and achieved up to 91% bacterial recovery after such 1-step filtration. When interfaced with droplet-based detection of bacterial cells, 1-step filtration improved the limit of detection for bacterial ID and quantification by over an order of magnitude. We also developed a facile buffer exchange strategy to prepare bacteria in urine samples for droplet-based AST that achieved up to 10-fold bacterial enrichment during buffer exchange. Our filtration strategies, can be easily integrated into droplet workflows, enable clinical isolation-free sample-to-answer ID and AST, and significantly accelerate the turnaround of standard infectious disease diagnostic workflows.

Indexed as

BacteriaSyringesAnti-Bacterial AgentsMicrobial Sensitivity TestsMicrofluidicsAnti-Bacterial Agents

Identifiers

PMID33899069
PMCPMC10697054

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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.