Evidence map›Paper›PMID 39020032›Full record

ArticleCommunications biology2024

High-throughput screening for cell binding and repulsion peptides on multifunctionalized surfaces.

Steffen J Sonnentag, Felix Jenne, Véronique Orian-Rousseau, Alexander Nesterov-Mueller

Abstract read
In one paragraph

Article in Communications biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

Steffen J Sonnentag *Institute of Biological and Chemical Systems - Functional Molecular Systems, Karlsruhe Institute of Technology, Kaiserstraße 12, 76131, Karlsruhe, Germany.
Felix Jenne *Institute of Microstructure Technology, Karlsruhe Institute of Technology, Kaiserstraße 12, 76131, Karlsruhe, Germany.
Véronique Orian-RousseauInstitute of Biological and Chemical Systems - Functional Molecular Systems, Karlsruhe Institute of Technology, Kaiserstraße 12, 76131, Karlsruhe, Germany. veronique.orian-rousseau@kit.edu.ORCID 0000-0003-2939-9257
Alexander Nesterov-MuellerInstitute of Microstructure Technology, Karlsruhe Institute of Technology, Kaiserstraße 12, 76131, Karlsruhe, Germany. alexander.nesterov-mueller@kit.edu.ORCID 0000-0001-8446-2728

Funding

Deutsche Forschungsgemeinschaft (German Research Foundation) AOBJ655892
6 · The paper itself

Abstract

The adhesion of cells to the extracellular matrix engages cell surface receptors such as integrins, proteoglycans and other types of cell adhesion molecules such as CD44. To closely examine the determinants of cell adhesion, herein we describe the generation of high-density peptide arrays and test the growth of cells on these multifunctionalized surfaces. The peptide library used consists of over 11,000 different sequences, either random or derived from existing proteins. By applying this screen to SW620 mCherry colorectal cancer cells, we select for peptides with both maximum cell adhesion and maximum cell repulsion. All of these extreme properties are based on unique combinations of amino acids. Here, we identify peptides with maximum cell repulsion on secreted frizzled- and Dickkopf-related proteins. Peptides with strong cell repulsion are found at the poles of the TNF-alpha homotrimer. The formation of cellular patterns on alternating highly repulsive and adhesive peptides are examined. Our screen allows the identification of peptides suitable for biomedical and tissue engineering applications.

Indexed as

Cell AdhesionHigh-Throughput Screening AssaysPeptide LibraryPeptidesCell Line, TumorHumansSurface PropertiesPeptide LibraryPeptides

Identifiers

PMID39020032
PMCPMC11255233

What OpenQuestion holds

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Registered trials

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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.