Chapter title |
Segmental Isotope Labeling of Insoluble Proteins for Solid-State NMR by Protein Trans-Splicing
|
---|---|
Chapter number | 10 |
Book title |
Split Inteins
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-6451-2_10 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6449-9, 978-1-4939-6451-2
|
Authors |
Tobias Schubeis, Madhu Nagaraj, Christiane Ritter, Schubeis, Tobias, Nagaraj, Madhu, Ritter, Christiane |
Abstract |
Solid-state NMR spectroscopy (ssNMR) is uniquely suited for atomic-resolution structural investigations of large protein assemblies, which are notoriously difficult to study due to their insoluble and non-crystalline nature. However, assignment ambiguities because of limited resolution and spectral crowding are currently major hurdles that quickly increase with the length of the polypeptide chain. The line widths of ssNMR signals are independent of proteins size, making segmental isotope labeling a powerful approach to overcome this limitation. It allows a scalable reduction of signal overlap, aids the assignment of repetitive amino acid sequences, and can be easily combined with other selective isotope labeling strategies. Here we present a detailed protocol for segmental isotope labeling of insoluble proteins using protein trans-splicing. Our protocol exploits the ability of many insoluble proteins, such as amyloid fibrils, to fold correctly under in vitro conditions. In combination with the robust trans-splicing efficiency of the intein DnaE from Nostoc punctiforme, this allows for high yields of segmentally labeled protein required for ssNMR analysis. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 14 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 5 | 36% |
Researcher | 4 | 29% |
Other | 2 | 14% |
Student > Master | 1 | 7% |
Unknown | 2 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 5 | 36% |
Agricultural and Biological Sciences | 2 | 14% |
Chemistry | 2 | 14% |
Social Sciences | 1 | 7% |
Unknown | 4 | 29% |