Next week, @andrewleduc.bsky.social will present at the CSHL Systems Biology: Global Regulation of Gene Expression meeting.
His talk will focus on in vivo protein regulation in single cells, including results from this preprint:
www.biorxiv.org/content/10.1...
Yeah, I really agree, it doesnt fully make sense to me. Maybe its not detrimental to the cell but ends up being a problem for the organ or something like that
Also I dont get why not just base edit the mutation causing the early stop
I think upon reading it more closely, the thing that i misunderstood was that even a very small rate of fixing the early stop proteins recovered function, maybe in this context it makes sense
We are doing similar experiments right now and our results are so different from all the things you would need to be true for any of this to make sense.
Yeah I mean or the ribosomes some how have other ways of filtering... but this is inconsistent, it really doesnt make sense in so many ways.
Also, if you point edit change some of the natural tRNA, it must be bad to lose those copies for normal case, and how can the dosing be even close to correct
I really dont understand how this sup-tRNA works, how can this possibly work as a therapy without extending natural proteins everywhere
These 3-L bottles contain one million tiny colored spheres each.
One sphere is black (1 ppm).
Finding the black sphere is comparable to detecting a protein present at ~ 6,000 copies in the proteome of a human cell.
Quantifying the protein requires analyzing multiple jars.
Also the cells are sorted by growth rate so idk some meaning to the ordering
When designing antibodies for cell surface proteins, how much do the PTMs (glycosilation specifically) affect how well proteins can bind. Presumably these things are not possible to model with current approaches so I am surprised they apparently work so well
Yeah its not great, it just made comparisons of the different modalities a bit easier to visualize than when we plotted a scatter but will revisit. Thanks for feedback!
Check out our recent work interpreting the contribution of transcription, translation, and protein clearance on regulating protein abundance across cell types and single cells from a mammalian tissue!
I have admittedly been on the non-PI side of this only to realize how true this must be after receiving a blank stare ๐
Some proteins are primarily regulated by one mechanism: RNA abundance, translation, or clearance.
The regulation of most proteins is dominated by different regulatory mechanisms across cell types.
Gratifyingly, this complex regulation defines simple rules โฌ๏ธ
www.biorxiv.org/content/10.1...
We quantified mRNA abundance, translation, protein abundance, protein degradation and cell growth across thousands of single cells from a mammalian tissue.
The results revealed ๐๐จ๐ฆ๐ฉ๐ฅ๐๐ฑ regulation & ๐ฌ๐ข๐ฆ๐ฉ๐ฅ๐ organizing principles:
www.biorxiv.org/content/10.1...
๐งต
Trust me, its better than whatever harm "doing their jobs" will cause...
What about predictions that involve many proteins interacting together?
Yeah, for sure not true but also probably looking under the lamp post effect as well!
What is the best way to compute the correlation of two transcripts across single cells?
Help me build a virtual version of my apartment by training a hugeee (like so huge) neural network on temperature data from my stove.
Call to action from the community to achive this ambitious goal!
* Transcript abundance predictor model
Once you have a certain level of aggregation, it does become hard to imagine removing it easily. What if the aggregate is too large to fit in a lysosome? I dont know I guess what the size scales are
Is it well appreciated that droplet mRNA seq methods massively under-captures nuclear encoded mitochondrial transcripts?
They are essentially entirely unquantified by 10x sample preparation, probably because cell lysis is not sufficiently strong.
What do you use to measure blood sugar?
Anyone out there working on single cell ribo seq, this is potentially an interesting alternative/complementary approach.
There are some differences in the information they give and would be interesting to explore.
The aspiration to directly measure the ๐ซ๐๐ญ๐๐ฌ of protein synthesis and degradation and control mechanisms of gene expression in the individual cells comprising mammalian tissues has always been a significant motivating factor for me to develop single-cell proteomic technologies.
1/n
How do different cell types regulate protein concentrations? Transcription is only part of the story!
Our project focuses on better understanding the regulation of protein abundance by measuring transcription, translation, and protein clearance in single cells.
The talk by @andrewleduc.bsky.social at #SCP2025 is on YouTube:
๐๐ฎ๐๐ง๐ญ๐ข๐๐ข๐๐๐ญ๐ข๐จ๐ง ๐จ๐ ๐ ๐๐ง๐ ๐๐ฑ๐ฉ๐ซ๐๐ฌ๐ฌ๐ข๐จ๐ง ๐๐จ๐ง๐ญ๐ซ๐จ๐ฅ ๐ข๐ง ๐ ๐ฆ๐๐ฆ๐ฆ๐๐ฅ๐ข๐๐ง ๐ญ๐ข๐ฌ๐ฌ๐ฎ๐ ๐๐ญ ๐ฌ๐ข๐ง๐ ๐ฅ๐ ๐๐๐ฅ๐ฅ ๐ซ๐๐ฌ๐จ๐ฅ๐ฎ๐ญ๐ข๐จ๐ง
youtu.be/adkY6txDyqs?...
All ideas != create equal ๐
You ever just flip through genes for a while reading the functions on uniprot and just think,
Wow cells do so much stuff
Yes, testis are special but not the only tissues in which we see substantial discrepancies.
We have seen them in all tissues that we have analyzed, and @andrewleduc.bsky.social has even more compelling examples from mouse trachea ... soon to be published!
