The presentation deals with the problem of traditional proteomics like strong sequence polymorphism or poorly conserved protein families.
The worklow of this technique is displayed in detail and involves MS/MS analysis as well as data base research.
Table of Contents
1. Problems of ‚traditional‘ proteomics
2. Workflow similarity-driven proteomics
3. Evaluate borderline hits
4. Filtering against background library
5. Protein Identification of D. Salina
6. Proteomics-genomics approach: workflow
7. 2D-Gel electrophoresis of soluble fraction
8. Edman degradation and IPCR
9. Identification of ORF
10. Summary
Research Objectives and Topics
The work focuses on overcoming the limitations of traditional proteomics when analyzing organisms for which the genome sequence is unknown, specifically addressing the challenge of species with high phylogenetic distance or poorly conserved protein families.
- Application of similarity-driven proteomics
- Workflow strategies for cross-species identification
- Integration of proteomics and genomics methods
- Identification of membrane proteins and ORFs
- Use of Edman degradation and IPCR for sequence determination
Excerpt from the Book
Filtering against background library
Background spectra recorded with blank LC-MS/MS runs
Background proteins mainly keratins, trypsins, and serine proteases
De novo interpretation of spectra leads to redundant sequences
MASCOT very stringent and therefore not affected
MS BLAST leads to multiple hits -> unfavourable
Chapter Summary
Problems of ‚traditional‘ proteomics: This chapter outlines the inherent limitations in analyzing organisms with poor genomic data, such as sequence polymorphism and distant phylogenetic relationships.
Workflow similarity-driven proteomics: Introduces a methodical approach for peptide identification that relies on sequence similarity when standard database searches yield low confidence.
Evaluate borderline hits: Discusses techniques for interpreting ambiguous results from MASCOT searches, including de novo interpretation and MS BLAST.
Filtering against background library: Explains the necessity of removing background contaminants like keratins and trypsins to improve the accuracy of de novo sequencing.
Protein Identification of D. Salina: Presents a practical application of the proposed methods to identify 55 unique proteins in the organism D. salina.
Proteomics-genomics approach: workflow: Describes the integration of N-terminal sequencing and genomics to characterize proteins without prior gene sequence knowledge.
2D-Gel electrophoresis of soluble fraction: Visualizes the separation of protein fractions under different environmental conditions, demonstrating the influence of phosphite.
Edman degradation and IPCR: Details the experimental steps to link specific protein spots to their underlying DNA sequences via degenerate primer design.
Identification of ORF: Concludes the analysis by confirming the identity of a specific epimerase/dehydratase protein through DNA sequence evaluation.
Summary: Provides an overview of the benefits of the presented methodologies, emphasizing that high-resolution equipment is not always required for successful identification.
Keywords
Proteomics, Unknown Genome, MASCOT, MS BLAST, Edman degradation, IPCR, D. salina, D. phosphitoxidans, membrane proteins, peptide sequencing, genomics, bioinformatics, protein identification, 2D-Gel electrophoresis, mass spectrometry.
Frequently Asked Questions
What is the core focus of this research?
The research addresses the identification of proteins in organisms where no genome sequence is currently available.
Which specific themes are investigated?
Key themes include similarity-driven proteomics, cross-species identification, integration of genomics, and overcoming technical limitations in mass spectrometry.
What is the primary goal of the study?
The primary goal is to establish workflows that allow for accurate protein identification despite the lack of complete genomic background information.
Which scientific methods are utilized?
Methodologies include 2D-Gel electrophoresis, MASCOT database searching, MS BLAST, de novo peptide sequencing, N-terminal Edman sequencing, and IPCR.
What topics are covered in the main part of the work?
The main part covers data filtering strategies, the evaluation of borderline results, and the integration of genomic data to identify specific ORFs.
Which keywords define this work?
Key terms include Proteomics, Unknown Genome, MASCOT, MS BLAST, Edman degradation, IPCR, and protein identification.
How is the "background library" used in the workflow?
It is used to filter out common contaminants like keratins and trypsins, which are introduced during sample processing, to ensure that only relevant signals are analyzed.
What role does Edman degradation play in this context?
It is used to obtain the N-terminal sequence of proteins, which then guides the design of degenerate primers for downstream genomic investigation.
How is the identification of proteins in D. salina achieved?
The identification is achieved by combining MASCOT searches with MS BLAST for cross-species protein identification.
- Quote paper
- Manuel Langer (Author), 2015, Unknown Genome Proteomics, Munich, GRIN Verlag, https://www.grin.com/document/337836
