| Chapter title |
Defining Diagnostic Biomarkers Using Shotgun Proteomics and MALDI-TOF Mass Spectrometry
|
|---|---|
| Chapter number | 6 |
| Book title |
Diagnostic Bacteriology
|
| Published in |
Methods in molecular biology, June 2017
|
| DOI | 10.1007/978-1-4939-7037-7_6 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7035-3, 978-1-4939-7037-7
|
| Authors |
Jean Armengaud |
| Editors |
Kimberly A. Bishop-Lilly |
| Abstract |
Whole-cell MALDI-TOF has become a robust and widely used tool to quickly identify any pathogen. In addition to being routinely used in hospitals, it is also useful for low cost dereplication in large scale screening procedures of new environmental isolates for environmental biotechnology or taxonomical applications. Here, I describe how specific biomarkers can be defined using shotgun proteomics and whole-cell MALDI-TOF mass spectrometry. Based on MALDI-TOF spectra recorded on a given set of pathogens with internal calibrants, m/z values of interest are extracted. The proteins which contribute to these peaks are deduced from label-free shotgun proteomics measurements carried out on the same sample. Quantitative information based on the spectral count approach allows ranking the most probable candidates. Proteogenomic approaches help to define whether these proteins give the same m/z values along the whole taxon under consideration or result in heterogeneous lists. These specific biomarkers nicely complement conventional profiling approaches and may help to better define groups of organisms, for example at the subspecies level. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 2 | 17% |
| Student > Ph. D. Student | 2 | 17% |
| Student > Master | 2 | 17% |
| Professor | 1 | 8% |
| Lecturer | 1 | 8% |
| Other | 2 | 17% |
| Unknown | 2 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Immunology and Microbiology | 2 | 17% |
| Environmental Science | 1 | 8% |
| Biochemistry, Genetics and Molecular Biology | 1 | 8% |
| Veterinary Science and Veterinary Medicine | 1 | 8% |
| Agricultural and Biological Sciences | 1 | 8% |
| Other | 3 | 25% |
| Unknown | 3 | 25% |