Evidence map›Paper›PMID 35941237›Full record

ArticleNature chemical biology2022

Programmable DARPin-based receptors for the detection of thrombotic markers.

Tobias Strittmatter, Yidan Wang, Adrian Bertschi, Leo Scheller, Patrick C Freitag, Preetam Guha Ray, Pascal Stuecheli, Jonas V Schaefer, Thomas Reinberg, Dimitrios Tsakiris and 3 more

Open access · hybridAbstract read
In one paragraph

Article in Nature chemical biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.7field-weighted citation impact, top 10% of its field
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

14 citing papers in PubMed, 19 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Skin-Integrated Electrogenetic Regulation of Vasculature for Accelerated Wound Healing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
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  7. Synthetic Gene Circuits for Regulation of Next-Generation Cell-Based Therapeutics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Engineering transmembrane signal transduction in synthetic membranes using two-component systems.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  13. Article
  14. 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

13 authors at 7 institutions in 3 countries.

Tobias StrittmatterDepartment of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Yidan WangShanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, People's Republic of China.
Adrian BertschiDepartment of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.ORCID http://orcid.org/0000-0002-1981-1618
Leo SchellerDepartment of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.ORCID http://orcid.org/0000-0003-2490-4015
Patrick C FreitagDepartment of Biochemistry, University of Zurich, Zürich, Switzerland.
Preetam Guha RayDepartment of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Pascal StuecheliJohnson & Johnson, Allschwil, Switzerland.
Jonas V SchaeferDepartment of Biochemistry, University of Zurich, Zürich, Switzerland.ORCID http://orcid.org/0000-0002-8332-4371
Thomas ReinbergDepartment of Biochemistry, University of Zurich, Zürich, Switzerland.
Dimitrios TsakirisDiagnostic Hematology, University Hospital Basel, Basel, Switzerland.
Andreas PlückthunDepartment of Biochemistry, University of Zurich, Zürich, Switzerland.ORCID http://orcid.org/0000-0003-4191-5306
Haifeng YeShanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, People's Republic of China.ORCID http://orcid.org/0000-0002-5482-8116
Martin FusseneggerDepartment of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland. fussenegger@bsse.ethz.ch.ORCID http://orcid.org/0000-0001-8545-667X
ETH Zurich · CHUniversity of Zurich · CHEast China Normal University · CNJohnson & Johnson (Switzerland) · CHNovartis (Switzerland) · CHUniversity Hospital of Basel · CHUniversity of Basel · CH

Funding

European Research Council 785800
6 · The paper itself

Abstract

Cellular therapies remain constrained by the limited availability of sensors for disease markers. Here we present an integrated target-to-receptor pipeline for constructing a customizable advanced modular bispecific extracellular receptor (AMBER) that combines our generalized extracellular molecule sensor (GEMS) system with a high-throughput platform for generating designed ankyrin repeat proteins (DARPins). For proof of concept, we chose human fibrin degradation products (FDPs) as markers with high clinical relevance and screened a DARPin library for FDP binders. We built AMBERs equipped with 19 different DARPins selected from 160 hits, and found 4 of them to be functional as heterodimers with a known single-chain variable fragments binder. Tandem receptors consisting of combinations of the validated DARPins are also functional. We demonstrate applications of these AMBER receptors in vitro and in vivo by constructing designer cell lines that detect pathological concentrations of FDPs and respond with the production of a reporter and a therapeutic anti-thrombotic protein.

Indexed as

Ankyrin RepeatSingle-Chain AntibodiesCarrier ProteinsDesigned Ankyrin Repeat ProteinsFibrin Fibrinogen Degradation ProductsHumansProtein BindingCarrier ProteinsDesigned Ankyrin Repeat ProteinsFibrin Fibrinogen Degradation ProductsSingle-Chain Antibodies

Identifiers

PMID35941237
PMCPMC9512699
OpenAlexW4290673597

What OpenQuestion holds

Textmetadata
LicenceTDM
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.