With the most current AMP PD release that contains both targeted and untargeted proteomics data, I wanted to take a minute to explain the differences between the two and expand a bit on the types of proteomics data one might find in databases.
At the highest level, targeted proteomics, as its name implies, targets specific and known peptides/proteins and untargeted proteomics is a way of doing discovery when you aren’t looking for specific peptides/proteins.
Targeted proteomics data can be affinity based or mass spectrometry based.
Affinity based proteomics uses an antibody or aptamer, depending on the technology, which binds to the protein of interest. Quantity of that protein is related to the signal generated by the bound entity. For example, Olink technology uses a pair of antibodies for each protien of interest that contain specific DNA fragments. When the two antibodies bind to the protien, their DNA sequences can hybridize. After an extension period where more copies of these sequences can be made, Next Gen Sequencing (NGS) is used to determine the relative quantity of the assayed proteins. An example of a company that uses aptamers for targeted proteomics analysis is Somalogic.
Targeted Mass Spectrometry based proteomics uses multiple stages of tandem mass spectrometry for ions with a specific mass and at a specific time during a gradient. Types of Targeted MS based proteomics are SRM (single reaction monitoring), MRM (mulitple reaction monitoring) and DDA (data dependent acquisition).
Untargeted proteomics is widely used for discovery approaches. Data Independent Acquisition (DIA) is used. Unlike targeted methods, DIA methods fragment and analyze all ions within a selected mass/charge ratio in the second stage of tandem mass spectrometry.
One of the main differences between DDA and DIA are the selection of ions in a specific mass/charge ratio. DDA selects a fix number of precursor ions for tandem MS and DIA sends all precuror ions for subsequent tandem MS. Tandem MS refers to the process in which precursor ions are broken into smaller fragments - this allows researchers to computationally identify amino acid sequence by looking at mass differences between these smaller fragments.
When thinking about future experiments or available data sets you wish to utilize for your analyses, it’s important to understand the different types of proteomics data that are availabe, so you can make an informed decision about which type of data will best help you answer your scientific questions.