Proteomics Flashcards
What does omics refer to?
Informally refers to genomics, proteomics or metabolomics
What is -ome used for?
To address the objects of study of such field, such as the genome, proteome or metabolome respectively.
What are the aims of omics?
The collective characterization and quantification of pools of biological molcules that translate into the structure, function and dynamics of an organism or organisms
What is the proteome?
All the proteins expressed at any one time
In which aspect relevant to omic technologies are proteins and DNA different?
DNA is specific to a certain species or individuals
Proteins can be specific at many levels - population, person, tissue, cell, organelle
What information can you get from the genome?
Functional information only
What information can you get from the proteome?
How much there is
Activated or not
State of activation
How much variation is there in the genome?
Little compared to the proteome
Arises only from the combinations of 4 nucleotides
How much variation is there in the proteome?
A lot
Arises from combination of up to 20 amino acids
Increased further by the post-transcriptional modification
How many genes are there in the genome?
Around 25 000
How many proteins are there in the proteome?
More than 1 million
Modification and splice variants increase the amount
The genome encompasses a —- code, whereas the proteomic code is highly —-
Static
Dynamic
What are prepro regions?
Proteins are often made as precursors or pro-proteins
Not active until they have undergone some form of post translational modification
They also contain a signalling peptide (pre-pro peptide) to signal the cell whether or not they should be secreted or incorporates into the plasma membrane
This is a cleavable peptide that must be removed before the protein is activated
What are examples of post translational modification?
Posphorylation
Acylation
Methylation
Ubiquitination
Glycolysation
Give an example where proteomics was used clinically
Ovarian cancer patients
Bioinformatics was combined with proteomics
This showed clusters identifying key genes involved, including Ubiquitin C and FGF4
Also showed gene outliers, which could be specific to the type of cancer
Which gene is specific and used clinically to diagnose ovarian cancer?
Mucin16
What type of field is bioinformatics?
Very multidisciplinary
What professions are involved in bioinformatics?
Biologists
Computer scientists
Mathematicians
Chemists
Statisticians
Physicists
What does bioinformatics entail?
The study of biological information with a computer
What information can bioinformatics provide us with regarding the proteome?
Structural
Find networks
Quantify a protein
Generate models: how changes in environment can affect protein modulation
What 3 tools can be used for bioinformatics?
BLAST
GO
Panther
Describe the BLAST bioinformatic tool
Takes a sequence and searches it
Compares the sequence to sequences in the database
Can be a protein or a gene
Uses this to guess the protein it is
Uses the conserved region of a protein to accurately predict its function
Can also give you the phylogeny information regarding that protein
Describe the GO bioinformatic tool
Gene ontology
Associates the function of a protein with a word
Creates a library of these proteins regarding their functions
Clusters proteins with similar functions together
Describe the Panther bioinformatic tool
Looks at a list of proteins described by GO and returns the average most enriched processes
Cancer cells: apoptotic processes, immune cells
Give an example of bioinformatic analysis done on a patient cohort
Asthma patients
Grouped patients into eosinophilic, neutrophilic and non-allergic
Showed that neutrophilic asthma formed 2-3 subgroups, where the effect of treatment and disease type were different
Identified groups which shared genes
What, in terms of hypotheses testing, are omic technologies useful for?
Omics are good for generating hypotheses
What are prescriptive vs non-prescriptive approaches in proteomics?
Prescriptive approaches have defined targets
Non-prescriptive approaches have unknown targets
What type of approach is used in protein arrays?
Prescriptive
Used to identify a predefined set of proteins
What technique are protein arrays based on?
Antibody recognition
Are protein arrays classified as omic technologies?
Not yet
We don’t have all the antibodies for all the proteins
Almost omic for yeasts
What type of approach is used in mass sectromertry ?
Non-prescriptive
Identifies all the detectable proteins in a sample
What are mass spectrometry results based on?
Peptide m/z values
Are mass spectrometers classified as omic technologies?
Yes
What are the two proteomic technologies used?
Protein arrays
Mass spectrometry
What is proteomic characterisation?
The characterisation and quantification of all polypeptide components present in a biological compartment
What are the three levels by which proteins are characterised?
Primary
Secondary and tertiary
Quarternary
What is the primary structure of proteins?
Amino acid sequence
What is the quarternary structure of proteins?
Protein-protein interactions
Interactome
What are the questioned addressed by proteomics?
Which proteins are translated from the genome/transcriptome?
Where are the proteins found?
Which proteins do the proteins bind to?
Are the proteins post-transcriptionally modified?
Does the protein concentration/localization/ interaction/ modification differ between samples?
What are the pros of mRNA profiling?
Fairly omic
Quick
Relatively cheap
What are the pros of proteomics?
Good for looking at ECM and fluids such as CSF, plasma, serum and urine
More informative and more accurate to focus on the active entities rather than their biosynthetic template to asses abundance, modification, turnover and localisation
What are the cons of mRNA profiling?
Bad at looking at certain ECM and fluids
What are the cons of proteomics?
Difficult to perform
Expensive
Not truly comprehensive
Do proteomes and mRNA profiles always correlate?
Some correlate well, some don’t
What are the two reasons for why we need sample fractionation?
Dynamic range
Complexity