Resolving the proteome with single-cell and spatial proteomics.
Single-cell and spatial proteomics: a more refined future.
Proteomics is the study of all of the proteins produced by our cells.
This includes how they interact with one another and how all of those proteins collaborate to create the numerous tissues that make up multicellular organisms!
But, proteomics has the same exact problem that most omics approaches have as it relates to how we collect and analyze samples.
Until recently, omics studies were done on bulk material, meaning we collect a blood sample or take a tissue biopsy and then grind up all of those cells.
We then throw them on an instrument to detect everything that’s in there.
The problem with this approach is that blood (and tissues) contain many millions of cells and not all of them are the same!
What happens when you measure a sample in bulk is that all of those cells and the proteins/RNA/DNA in them get mixed with all of those things from the other cells in the sample.
This has the effect of averaging out all of the signals, meaning, you’re likely only going to be able to detect big changes within the population of cells you sampled!
Unfortunately, you might be really interested in small changes, or changes that happen gradually over time.
Because, it’s the activities of individual cells working together (but differently) that makes us who we are!
It’s also small populations of misbehaving cells in things like cancer that can cause big problems later, and it’d be super nice to detect those signals sooner rather than later!
Wouldn’t it be swell if we could do proteomics on individual cells?
Thankfully, we’re in luck!
The explosion of the field of single-cell and spatial transcriptomics (looking at RNA) has also led to methods that allow us to look at proteins at the same time.
You might be wondering why we'd care about proteins if we’re already able to look at RNA.
And that’s because RNA expression doesn’t always correlate directly with protein abundance!
So, you can have lots of an mRNA in a cell, and a little of its translated protein, or vice versa depending on what a cell is doing at any given time!
This means that the two techniques are very complementary, and if you’re already doing transcriptomics, most methods allow you to throw in a bunch (50-100) of antibodies to also detect proteins you might be interested in.
But, what if you want to GET ALL OF THE PROTEINS?!?!?!
If you’re a proteomics Cookie Monster, you’re also in luck!
We also have LCMS based methods that take an unbiased approach to protein detection.
And when paired with fancy new separation and capture techniques, we can use LCMS to detect and quantify all of the proteins in single cells or within a tissue section.
Read the full issue of Omic.ly Premium 15
Brian Krueger