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Phages recognizing the Indium Nitride semiconductor surface via their peptides.

Identifieur interne : 001222 ( Main/Exploration ); précédent : 001221; suivant : 001223

Phages recognizing the Indium Nitride semiconductor surface via their peptides.

Auteurs : RBID : pubmed:21234986

English descriptors

Abstract

Considerable advances in materials science are expected via the use of selected or designed peptides to recognize material, control their growth, or to assemble them into elaborate novel devices. Identifying specific peptides for a number of technologically useful materials has been the challenge of many research groups in recent years. This can be accomplished by using affinity-based bio-panning methods such as phage display technologies. In this work, a combinatorial library including billions of clones of genetically engineered M13 bacteriophage was used to select peptides that could recognize improved indium nitride (InN) semiconductor (SC) material. Several rounds of biopanning were necessary to select the phage with the higher affinity from the low variant library. The DNA of this specific phage was extracted and sequenced to set up the related specific adherent peptide. Atomic force microscopy (AFM) is used to demonstrate the real affinity of a selected phage for the InN surface. Due to the possibility of its functionalization with biomolecules and its important physical properties, InN is a promising candidate for developing affinity-based optical and electrical biosensors and/or for biomimetic applications.

DOI: 10.1002/psc.1315
PubMed: 21234986

Links toward previous steps (curation, corpus...)


Le document en format XML

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<name sortKey="Martin, Marta" uniqKey="Martin M">Marta Martin</name>
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<name sortKey="Larroque, Christian" uniqKey="Larroque C">Christian Larroque</name>
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<name sortKey="Cuisinier, Frederic J G" uniqKey="Cuisinier F">Frédéric J G Cuisinier</name>
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<name sortKey="Briot, Olivier" uniqKey="Briot O">Olivier Briot</name>
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<name sortKey="Ruffenach, Sandra" uniqKey="Ruffenach S">Sandra Ruffenach</name>
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<name sortKey="Moret, Matthieu" uniqKey="Moret M">Matthieu Moret</name>
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<name sortKey="Gergely, Csilla" uniqKey="Gergely C">Csilla Gergely</name>
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<div type="abstract" xml:lang="en">Considerable advances in materials science are expected via the use of selected or designed peptides to recognize material, control their growth, or to assemble them into elaborate novel devices. Identifying specific peptides for a number of technologically useful materials has been the challenge of many research groups in recent years. This can be accomplished by using affinity-based bio-panning methods such as phage display technologies. In this work, a combinatorial library including billions of clones of genetically engineered M13 bacteriophage was used to select peptides that could recognize improved indium nitride (InN) semiconductor (SC) material. Several rounds of biopanning were necessary to select the phage with the higher affinity from the low variant library. The DNA of this specific phage was extracted and sequenced to set up the related specific adherent peptide. Atomic force microscopy (AFM) is used to demonstrate the real affinity of a selected phage for the InN surface. Due to the possibility of its functionalization with biomolecules and its important physical properties, InN is a promising candidate for developing affinity-based optical and electrical biosensors and/or for biomimetic applications.</div>
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