Identifying Unique Material Binding Peptides Using a High Throughput Method
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University of Dayton / OhioLINK
2016
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| Online Access: | http://rave.ohiolink.edu/etdc/view?acc_num=dayton1467888412 |
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ndltd-OhioLink-oai-etd.ohiolink.edu-dayton14678884122021-08-03T06:37:20Z Identifying Unique Material Binding Peptides Using a High Throughput Method Krabacher, Rachel M. Biochemistry Bioinformatics Chemical Engineering Materials Science Carbon nanotubes phage display peptide immobilization high throughput sequencing bioinformatics peptide binding biotic-abiotic interaction Through biotic-abiotic interactions, it has been shown that peptides can recognize and selectively bind to a wide variety of materials dependent on both their surface properties and the environment. Better understanding of these peptides and the materials to which they bind can be beneficial in the development of biofunctionalization approaches for creating hybrid materials and sensors. Several research groups have identified material binding peptides using biopanning with phage or cell peptide display libraries. However, limitations with sequence diversity of traditional bacteriophage (phage) display libraries and loss of unique phage clones during the amplification cycles results in a smaller pool of peptide sequences identified. In order to overcome some of the limitations of traditional biopanning methodology, a modified method using phage display along with high-throughput next generation sequencing to select for unique peptides specific for different classes of single wall carbon nanotubes has been devised. The process, analysis and characterization of peptide sequences identified using the modified method is described and compared to peptides identified using the traditional methods. Selected sequences from this study were immobilized on surfaces and used in site-specific capture of metallic and/or semiconducting carbon nanotubes. A dispersion experiment was carried out to identify chiral specific peptides. From this research, successful methods have been identified to select and confirm binding peptides specific to various materials. Knowledge of chiral specific recognizing peptides can allow for the potential purification and separation of specific chirality carbon nanotubes, thus opening the door for a number of carbon nanotube applications which had been previously hindered by mixed carbon nanotube samples. 2016-09-08 English text University of Dayton / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=dayton1467888412 http://rave.ohiolink.edu/etdc/view?acc_num=dayton1467888412 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws. |
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NDLTD |
| language |
English |
| sources |
NDLTD |
| topic |
Biochemistry Bioinformatics Chemical Engineering Materials Science Carbon nanotubes phage display peptide immobilization high throughput sequencing bioinformatics peptide binding biotic-abiotic interaction |
| spellingShingle |
Biochemistry Bioinformatics Chemical Engineering Materials Science Carbon nanotubes phage display peptide immobilization high throughput sequencing bioinformatics peptide binding biotic-abiotic interaction Krabacher, Rachel M. Identifying Unique Material Binding Peptides Using a High Throughput Method |
| author |
Krabacher, Rachel M. |
| author_facet |
Krabacher, Rachel M. |
| author_sort |
Krabacher, Rachel M. |
| title |
Identifying Unique Material Binding Peptides Using a High Throughput Method |
| title_short |
Identifying Unique Material Binding Peptides Using a High Throughput Method |
| title_full |
Identifying Unique Material Binding Peptides Using a High Throughput Method |
| title_fullStr |
Identifying Unique Material Binding Peptides Using a High Throughput Method |
| title_full_unstemmed |
Identifying Unique Material Binding Peptides Using a High Throughput Method |
| title_sort |
identifying unique material binding peptides using a high throughput method |
| publisher |
University of Dayton / OhioLINK |
| publishDate |
2016 |
| url |
http://rave.ohiolink.edu/etdc/view?acc_num=dayton1467888412 |
| work_keys_str_mv |
AT krabacherrachelm identifyinguniquematerialbindingpeptidesusingahighthroughputmethod |
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1719440104558166016 |