Andrew Leduc

@andrewleduc.bsky.social

Post-doc Slavov Lab https://andrew-leduc.github.io/ Studying how variation in protein half-life leads to variation in protein levels

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.

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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

Arc Institute@arcinstitute.org · 11mo ago

In another preprint from the @brianhie.bsky.social Lab and @synbiogaolab.bsky.social, they introduce Germinal, a generative AI system for de novo antibody design. Germinal produces functional nanobodies in just dozens of tests, making custom antibody design more accessible than ever before.

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!

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.

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.

Slavov Laboratory@slavovlab.bsky.social · last yr.

The talk by @andrewleduc.bsky.social at #SCP2025 is on YouTube: 𝐐𝐮𝐚𝐧𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐠𝐞𝐧𝐞 𝐞𝐱𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧 𝐜𝐨𝐧𝐭𝐫𝐨𝐥 𝐢𝐧 𝐚 𝐦𝐚𝐦𝐦𝐚𝐥𝐢𝐚𝐧 𝐭𝐢𝐬𝐬𝐮𝐞 𝐚𝐭 𝐬𝐢𝐧𝐠𝐥𝐞 𝐜𝐞𝐥𝐥 𝐫𝐞𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧 youtu.be/adkY6txDyqs?...

The aspiration to directly measure the 𝐫𝐚𝐭𝐞𝐬 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

Slavov Laboratory@slavovlab.bsky.social · last yr.

The talk by @andrewleduc.bsky.social at #SCP2025 is on YouTube: 𝐐𝐮𝐚𝐧𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐠𝐞𝐧𝐞 𝐞𝐱𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧 𝐜𝐨𝐧𝐭𝐫𝐨𝐥 𝐢𝐧 𝐚 𝐦𝐚𝐦𝐦𝐚𝐥𝐢𝐚𝐧 𝐭𝐢𝐬𝐬𝐮𝐞 𝐚𝐭 𝐬𝐢𝐧𝐠𝐥𝐞 𝐜𝐞𝐥𝐥 𝐫𝐞𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧 youtu.be/adkY6txDyqs?...

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.

Slavov Laboratory@slavovlab.bsky.social · last yr.

The talk by @andrewleduc.bsky.social at #SCP2025 is on YouTube: 𝐐𝐮𝐚𝐧𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐠𝐞𝐧𝐞 𝐞𝐱𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧 𝐜𝐨𝐧𝐭𝐫𝐨𝐥 𝐢𝐧 𝐚 𝐦𝐚𝐦𝐦𝐚𝐥𝐢𝐚𝐧 𝐭𝐢𝐬𝐬𝐮𝐞 𝐚𝐭 𝐬𝐢𝐧𝐠𝐥𝐞 𝐜𝐞𝐥𝐥 𝐫𝐞𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧 youtu.be/adkY6txDyqs?...

The talk by @andrewleduc.bsky.social at #SCP2025 is on YouTube: 𝐐𝐮𝐚𝐧𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐠𝐞𝐧𝐞 𝐞𝐱𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧 𝐜𝐨𝐧𝐭𝐫𝐨𝐥 𝐢𝐧 𝐚 𝐦𝐚𝐦𝐦𝐚𝐥𝐢𝐚𝐧 𝐭𝐢𝐬𝐬𝐮𝐞 𝐚𝐭 𝐬𝐢𝐧𝐠𝐥𝐞 𝐜𝐞𝐥𝐥 𝐫𝐞𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧 youtu.be/adkY6txDyqs?...

Quantification of gene expression control in a mammalian tissue at single cell resolution | SCP2025

YouTube video by Nikolai Slavov

youtu.be

📊 Using stable isotopes of C/N/O, PSMtags increased protein datapoints from 4,340 (label-free) to 28,359 in the same time. We demonstrate 240 samples per day, but over 1,000 are possible with shorter runs. That’s millions of protein data points per day.

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We are excited to introduce ‘time’ as a new domain for proteomics multiplexing! It enables: -Label-free multiplexing -Combinatorial multiplexing with plexDIA Using combined 9-plexDIA and 3-timePlex we demonstrate 27-plex DIA 🚀

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