Sunday, 20 May 2018

Common proteomic technologies, applications, and their limitations.

Protein separation
Relative quantitative
Poor separation of acidic, basis, hydrophobic and low abundant proteins.
Quantitative expression profiling
PTM information.

Relative quantitative
Protein separation
PTM information
Proteins without lysine cannot be labelled Requires special equipment for visualization and fluorophores are very expensive
Quantitative expression profiling
High sensitivity
Reduction of intergel variability

Chemical isotope labelling for quantitative proteomics
Sensitive and reproducible
Proteins without cysteine residues and acidic proteins are not detected
Detect peptides with low expression levels.

Direct isotope labelling of cells
Degree of labelling is very high
SILAC labelling of tissue samples is not possible
Differential expression pattern
Quantitation is straightforward

Isobaric tagging of peptides
Multiplex several samples
Increases sample complexity
Relative quantification High-throughput
Require fractionation of peptides before MS.

Identification of protein-protein interactions
High separation
Not quantitative
Large protein complexes identification
Difficulty in analysing the huge data set
Deconvolve complex sets of proteins
Difficult to identify isoforms

Protein array
Quantitate specific proteins used in diagnostics (biomarkers or antibody detection) and discovery research
Limited protein production
Highly sensitive
Poor expression methods
Low sample consumption
Availability of the antibodies
Accessing very large numbers of affinity reagents.

Mass spectrometry
Primary tool for protein identification and characterization
High sensitivity and specificity. High-throughput. Qualitative and quantitative
No individual method to identify all proteins. Not sensitive enough to identify minor or weak spots. MALDI and ESI do not favour identification of hydrophobic peptides and basic peptides
PTM information

Analysis of qualitative and quantitative proteomic data
Functional analysis, data mining, and knowledge discovery from mass spectrometric data
No integrated pipeline for processing and analysis of complex data. Search engines do not yield identical results

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