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Protein Engineering

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Cover of 'Protein Engineering'

Table of Contents

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    Book Overview
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    Chapter 1 Protein Engineering: Past, Present, and Future
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    Chapter 2 Rational and Semirational Protein Design
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    Chapter 3 Computational Analysis of Protein Tunnels and Channels
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    Chapter 4 YASARA: A Tool to Obtain Structural Guidance in Biocatalytic Investigations
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    Chapter 5 A Computational Library Design Protocol for Rapid Improvement of Protein Stability: FRESCO
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    Chapter 6 Directed Evolution of Proteins Based on Mutational Scanning
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    Chapter 7 A Brief Guide to the High-Throughput Expression of Directed Evolution Libraries
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    Chapter 8 Library Growth and Protein Expression: Optimal and Reproducible Microtiter Plate Expression of Recombinant Enzymes in E. coli Using MTP Shakers
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    Chapter 9 Normalized Screening of Protein Engineering Libraries by Split-GFP Crude Cell Extract Quantification
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    Chapter 10 Functional Analysis of Membrane Proteins Produced by Cell-Free Translation
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    Chapter 11 Practical Considerations Regarding the Choice of the Best High-Throughput Assay
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    Chapter 12 High-Throughput Screening Assays for Lipolytic Enzymes
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    Chapter 13 Continuous High-Throughput Colorimetric Assays for α -Transaminases
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    Chapter 14 Colorimetric High-Throughput Screening Assays for the Directed Evolution of Fungal Laccases
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    Chapter 15 Directed Coevolution of Two Cellulosic Enzymes in Escherichia coli Based on Their Synergistic Reactions
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    Chapter 16 Program-Guided Design of High-Throughput Enzyme Screening Experiments and Automated Data Analysis/Evaluation
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    Chapter 17 Solid-Phase Agar Plate Assay for Screening Amine Transaminases
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    Chapter 18 Ultrahigh-Throughput Screening of Single-Cell Lysates for Directed Evolution and Functional Metagenomics
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    Chapter 19 Isolation of pH-Sensitive Antibody Fragments by Fluorescence-Activated Cell Sorting and Yeast Surface Display
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    Chapter 20 Library Generation and Auxotrophic Selection Assays in Escherichia coli and Thermus thermophilus
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    Chapter 21 Erratum to: Functional Analysis of Membrane Proteins Produced by Cell-Free Translation
Attention for Chapter 19: Isolation of pH-Sensitive Antibody Fragments by Fluorescence-Activated Cell Sorting and Yeast Surface Display
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Chapter title
Isolation of pH-Sensitive Antibody Fragments by Fluorescence-Activated Cell Sorting and Yeast Surface Display
Chapter number 19
Book title
Protein Engineering
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7366-8_19
Pubmed ID
Book ISBNs
978-1-4939-7364-4, 978-1-4939-7366-8
Authors

Christian Schröter, Simon Krah, Jan Beck, Doreen Könning, Julius Grzeschik, Bernhard Valldorf, Stefan Zielonka, Harald Kolmar, Schröter, Christian, Krah, Simon, Beck, Jan, Könning, Doreen, Grzeschik, Julius, Valldorf, Bernhard, Zielonka, Stefan, Kolmar, Harald

Abstract

Fluorescence-activated cell sorting (FACS) in combination with yeast surface display (YSD) has proven to be a valuable tool for the engineering of antibodies. It enables the fast and robust identification and isolation of candidates with prescribed characteristics from combinatorial libraries. A novel application for FACS and YSD that has recently evolved addresses the engineering of antibodies toward pH-switchable antigen binding, aiming at reduced binding at acidic pH, compared to neutral pH. Therefore, we give guidance for the incorporation of such pH switches into antibody variable domains using combinatorial histidine scanning libraries. The protocol describes a flow cytometric sorting technique for the enrichment of antigen-specific molecules. Moreover, we provide information on how to screen the obtained antibody pools from initial sorting to isolate and characterize pH-sensitive variants.

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 29%
Student > Ph. D. Student 4 29%
Student > Master 3 21%
Student > Bachelor 1 7%
Professor > Associate Professor 1 7%
Other 0 0%
Unknown 1 7%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 36%
Agricultural and Biological Sciences 3 21%
Engineering 2 14%
Chemical Engineering 1 7%
Chemistry 1 7%
Other 1 7%
Unknown 1 7%