Proteomics

H3ABioNet_high_res

Prepared by:  Samar Kamal Kassim
Module name: Proteomics
Contact hours (to be used as a guide)Total (40 hrs), Theory (50%), Practical (50%)

SPECIFIC OUTCOMES ADDRESSED

This module will focus on cutting-edge proteomic approaches and technologies. Students will gain practical experience in purifying and identifying protein complexes and post-translational modifications. 

By the end of this module, students should have gained the following skills:

General

  • Achieve solid understanding of the scope of proteomics
  •  Understand basic and advanced techniques necessary for analyzing proteomic experiments
  •  Learn how to access new information and how to assimilate it into the whole, in order to continue to learn beyond the limits of this course.

Knowledge and Understanding

  • Students will understand fundamental principles of proteomics
  • Students will think about the range of applications of proteomics to molecular biology, clinical medicine, pharmacology, biotechnology, agriculture, forensic science, drug design and other disciplines
  • Student will know the application of computational methods to interpret proteomic data.

Intellectual Skills

  • Students will understand the language of both experimental biologist and computing scientist, and will be able to bridge the gap between them in the context of proteomics.
  • Studnet will be able to perform basic analyses of proteomics.

 Professional and Practical Skills

  • Students will have obtained basic skills in information retrieval, and calculations with proteomic data, and will have the ability to extend these skills by self-directed ‘field work’ on the web.
  • Students will have computational skills for the use of open-source software tools designed for the analysis, validation, storage and interpretation of data obtained from large-scale quantitative proteomics experiments and methods.
  • Students will have the capacity to interpret multi-dimensional chromatography and tandem mass spectrometry results.

 General and Transferable Skills

  • Students will be able to hold discussions among partners from various academic backgrounds (biologists, statisticians, and computer professions) involved in proteomics problems.
  • Students will know how to use the web and other resources for performing proteomic surveys. 

 

BACKGROUND KNOWLEDGE REQUIRED

H3ABioNet bioinformatics modules as pre-requisites: None.

Additional: None.

 

BOOKS AND OTHER SOURCES USED

Nawin C. MishraGünter Blobel Introduction to Proteomics: Principles and Applications.  ISBN 978-0-471-75402-2

 

COURSE CONTENT

A)   Theory lectures

1. Introduction to mass spectrometry for biological applications.  (10 hours/ 5 lectures)

  • Peptide Mass Spectrometry.
  • Interpretation of Peptide Mass Spectra.
  • Proteolysis and Protein Sequencing.
  • System architecture and analytical strategies for the detection, characterization, and quantitation of proteins.
  • Protein Identification by Mass Spectrometry.

2. Application of proteomics methods to biological problems.    (4 hours/ 2 lectures)            

  • The identification and localization of protein post-translational modifications.
  • Validation and Reporting.

3. Immunoproteomics: Use of antibodies coupled with mass spectrometry to measure proteins in complex biological systems.    (6 hours/3 lectures)

  • 2D gel electrophoresis-based proteomics.
  • Quantitative proteomics.
  • Antibodies and other protein/peptide binders for sample enrichment.

 

B)   Practical component

1. Instruction on using SPC resources such as PeptideAtlasSRMAtlas, and related tools for design of targeted proteomics workflows via selected reaction monitoring (SRM/MRM).   (8 hours)  (Follows lectures 1-5)

  • Top-down and bottom-up immuno-MS methods.
  • SISCAPA methods applied to biomarker validation and clinical assay development.

 2. Using proteomic methodologies to investigate bacterial pathogenesis.  

(8 hours)  (Follows lectures 6-10)          

  • Sample preparation, two-dimensional gels, iTRAQ.
  • detection of post-translational methylations, group projects to analyze iTRAQ and methylation data.
  • Using proteomic methodologies to study ion channel signaling networks in the regulation of neurogenesis Tools for analysis of protein-protein interactions, comparison of 1D gel, 2D gel or gel-free methods for identification of novel protein interactors by MS.

3. Gene ontology tools, interaction validation, functional studies; sample preparation for membrane proteins in neuronal differentiation, iTRAQ review and discussions of questions that can be addressed using iTRAQ.

(4 hours) (follows lecture 6-10)

 

ASSESSMENT ACTIVITIES AND THEIR WEIGHTS

Assessment 1: Midterm exam.                                                      Week 5

Assessment 2: Final exam.                                                            Week 10

Weighting of Assessments

Class-discussion participation                                                      5%

Homework (exercises, reading assignments)                          10%

Practical work                                                                                10%

Individual presentations                                                              15%

Mid-term Examination                                                                  20%

Final-term Examination                                                                 40%

Other types of assessment                                                            0 %

Total                                                                                                100%

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