Starting on proteomics: What’s mass spectrometry and how can it help unravel the proteome

Proteomics is an interdisciplinary science that allows the exploration of the proteome from different perspectives: the composition levels of proteins, their structure, their biological activity… Understanding the proteome is understanding the building blocks that make life happen.

To study this interesting part of the fundaments of life, we need to bring to the table powerful techniques that allow us to unravel as much as possible the information contained in these complex macromolecules. Mass spectrometry is the golden standard because it allows the study of proteomes in large sample-sets (millions of cells) but also on single cell samples with the same resolution.

Mass spectrometry is based on the principle of vaporising the sample, disrupting it to peptides, and ionize those peptides creating ions that the mass spectrometer would separate based on mass and charge in a detector source. With that data yielded, there are mainly two types of analysis to run on mass spectrometry, both of which have their own strong points and their own differences, these are: data dependent and data independent analysis.

Data dependent

This type of analysis is the perfect for absence/ presence analysis where a target protein is studied within the sample-set. This type of analysis is based on targeting the protein to study, so it has easier BI analysis and uses a database-dependent algorithm to do the analysis, providing faster results. The only thing to consider with it is the existing knowledge of the protein, since the more complete databases (the more know is the protein) the more information the analysis will yield.

Data independent

This type of analysis is a de novo kind. Meaning that we don’t need to worry about what’s in the sample (what to target). The proteomics study will be run with everything present on the sample, meaning it will also be more demanding of computational resources and will have a more complex data analysis.

Proteomics is a field with lots of history and future development related to the advance of computer models that allow us, not only to yield more data, but also to analyse the existent datasets with a different perspective. It’s expected these types of analyses blend in the future to give place to a new way of approach knowledge, but for now, the best step we can give in that direction is to identify the needs of the experiment choosing the appropriate analysis.