Check out one of my favorite techniques of the last few years - the NanoSplits paper here!
The first preprint of this study is somewhere on the blog, but the work evolved considerably since we initially saw it.
If you aren't familiar, what this does is label free preparation of REAL NORMAL SIZED SINGLE ONE (1, uno, um, eins, jeden, yski, en siffra, een, ichi) at a time on glass slides using precision robotics.
THEN the lysed cell is split into 2 fractions with most of the protein going one way and more of the little transcripts going the other way. You do single cell proteomics on the fraction with more protein and you can amplify the transcripts in the other fraction for transcriptomics.
BOOM! You get everything! Now, there are obviously some drawbacks here, including that it is really hard to do. You need the precision robotics. This team features some people with serious instrumentation backgrounds but also people with a history of simplifying methods so mortals can eventually do them. We've written 2 grant applications where the technique has been prominently featured. The scSeq people are a whole lot more comfortable with this measuring protein thing if they can get evidence that you aren't just making stuff up!
What's super cool here is that while multiple groups have shown complementary data by doing stuff like single cell proteomics and single cell seq on the same or very similar populations of cells (my group's first study was dosing the same cell line from the same source with the same drug - in a recent study) - here you get a real - Cell A proteomics and transcriptomics fill in a specific pattern. Cell B the same.
The authors are quick to point out that NanoSplits could be a bridge technique to unify findings between more traditional studies where you either do SCP or scSeq or both on the same population. A small number of cells split could explain discrepancies between these 2 data types, or help you truly link 2 populations together.
Seriously - a phenomenal, clever technique with top notch data collection and informatics and when I resubmit a grant in a couple of months I'm sure my reviewers will be excited to see a prominently published paper rather than a link to a preprint.
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