Evidence map›Paper›PMID 39087463›Full record

ArticleAngewandte Chemie (International ed. in English)2024

High-Throughput Absorbance-Activated Droplet Sorting for Engineering Aldehyde Dehydrogenases.

Ankit Jain, Mariko Teshima, Tomas Buryska, Dennis Romeis, Magdalena Haslbeck, Manuel Döring, Volker Sieber, Stavros Stavrakis, Andrew de Mello

Abstract read
In one paragraph

Article in Angewandte Chemie (International ed. in English), 2024. 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. Confocal Absorbance-Activated Droplet Sorting (cAADS) for Enzyme Engineering.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  4. Article
  5. Article
  6. 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

9 authors.

Ankit JainInstitute for Chemical and Bioengineering, Department of Chemistry & Applied Biosciences, ETH Zürich, Vladimir Prelog Weg 1, 8093, Zürich, Switzerland.
Mariko TeshimaChemistry of Biogenic Resources, Technical University of Munich, Campus Straubing for Biotechnology and Sustainability, Schulgasse 16, 94315, Straubing, Germany.
Tomas BuryskaInstitute for Chemical and Bioengineering, Department of Chemistry & Applied Biosciences, ETH Zürich, Vladimir Prelog Weg 1, 8093, Zürich, Switzerland.
Dennis RomeisChemistry of Biogenic Resources, Technical University of Munich, Campus Straubing for Biotechnology and Sustainability, Schulgasse 16, 94315, Straubing, Germany.
Magdalena HaslbeckChemistry of Biogenic Resources, Technical University of Munich, Campus Straubing for Biotechnology and Sustainability, Schulgasse 16, 94315, Straubing, Germany.
Manuel DöringChemistry of Biogenic Resources, Technical University of Munich, Campus Straubing for Biotechnology and Sustainability, Schulgasse 16, 94315, Straubing, Germany.
Volker SieberChemistry of Biogenic Resources, Technical University of Munich, Campus Straubing for Biotechnology and Sustainability, Schulgasse 16, 94315, Straubing, Germany.
Stavros StavrakisInstitute for Chemical and Bioengineering, Department of Chemistry & Applied Biosciences, ETH Zürich, Vladimir Prelog Weg 1, 8093, Zürich, Switzerland.ORCID 0000-0002-0888-5953
Andrew de MelloInstitute for Chemical and Bioengineering, Department of Chemistry & Applied Biosciences, ETH Zürich, Vladimir Prelog Weg 1, 8093, Zürich, Switzerland.

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 205321/176011/1
6 · The paper itself

Abstract

Recent decades have seen a dramatic increase in the commercial use of biocatalysts, transitioning from energy-intensive traditional chemistries to more sustainable methods. Current enzyme engineering techniques, such as directed evolution, require the generation and testing of large mutant libraries to identify optimized variants. Unfortunately, conventional screening methods are unable to screen such large libraries in a robust and timely manner. Droplet-based microfluidic systems have emerged as a powerful high-throughput tool for library screening at kilohertz rates. Unfortunately, almost all reported systems are based on fluorescence detection, restricting their use to a limited number of enzyme types that naturally convert fluorogenic substrates or require the use of surrogate substrates. To expand the range of enzymes amenable to evolution using droplet-based microfluidic systems, we present an absorbance-activated droplet sorter that allows droplet sorting at kilohertz rates without the need for optical monitoring of the microfluidic system. To demonstrate the utility of the sorter, we rapidly screen a 10

Indexed as

Aldehyde DehydrogenaseHigh-Throughput Screening AssaysProtein EngineeringMicrofluidic Analytical TechniquesAldehyde Dehydrogenase

Identifiers

PMID39087463
PMCPMC11586695

What OpenQuestion holds

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LicenceCC BY-NC
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.