Evidence map›Paper›PMID 39320273›Full record

ArticleAnalytical chemistry2024

Passive Droplet Microfluidic Platform for High-Throughput Screening of Microbial Proteolytic Activity.

Luca Potenza, Lukasz Kozon, Lukasz Drewniak, Tomasz S Kaminski

Abstract read
In one paragraph

Article in Analytical chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Detection of Single Cell Contamination ofFood safety (Tokyo, Japan) · 2025
    Article
  4. Innovative Advances in Droplet Microfluidics.Research (Washington, D.C.) · 2025
    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

4 authors.

Luca PotenzaDepartment of Molecular Biology, Institute of Biochemistry, Faculty of Biology, University of Warsaw, Miecznikowa 1, Warsaw 02-096, Poland.
Lukasz KozonDepartment of Molecular Biology, Institute of Biochemistry, Faculty of Biology, University of Warsaw, Miecznikowa 1, Warsaw 02-096, Poland.
Lukasz DrewniakDepartment of Environmental Microbiology and Biotechnology, Institute of Microbiology, Faculty of Biology, University of Warsaw, Miecznikowa 1, Warsaw 02-096, Poland.
Tomasz S KaminskiDepartment of Molecular Biology, Institute of Biochemistry, Faculty of Biology, University of Warsaw, Miecznikowa 1, Warsaw 02-096, Poland.ORCID 0000-0001-5124-4548

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditional bacterial isolation methods are often costly, have limited throughput, and may not accurately reflect the true microbial community composition. Consequently, identifying rare or slow-growing taxa becomes challenging. Over the past decade, a new approach has been proposed to replace traditional flasks or multiwell plates with ultrahigh-throughput droplet microfluidic screening assays. In this study, we present a novel passive droplet-based method designed for isolating proteolytic microorganisms, which are crucial in various biotechnology industries. Following the encapsulation of single cells in gelatin microgel compartments and their subsequent clonal cultivation, microcultures are passively sorted at high throughput based on the deformability of droplets. Our novel chip design offers a 50-fold improvement in throughput compared to a previously developed deformability-based droplet sorter. This method expands an array of droplet-based microbial enrichment assays and significantly reduces the time and resources required to isolate proteolytic bacteria strains.

Indexed as

High-Throughput Screening AssaysMicrofluidic Analytical TechniquesProteolysisBacteria

Identifiers

PMID39320273
PMCPMC11465220

What OpenQuestion holds

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LicenceCC BY
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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.