Slavov Laboratory

Parallel Squared Technology Institute aims to scale the throughput of sensitive proteomics without compromising quantitative accuracy, depth or specificity. Today, we share a step in this direction: 🔹 A workflow supporting the analysis of 1,130 single-cell samples per day (SPD) while preserving depth and quantitative accuracy. 1/ biorxiv.org/content/10.1101/…

Proteomics has long faced a choice: Go deep, or go fast. Deep, high-confidence coverage of protein sequences has traditionally required extensive chromatographic fractionation, large sample inputs and data acquisition times too long to be practical for analyzing human cohort scale samples. Scalable data-independent acquisition (DIA) workflows handle many samples quickly, but detect less of each protein and with lower confidence. Our new preprint introduces multiDIA: It gets more from each sample without fractionation. 1/ doi.org/10.64898/2026.10.16.…

Congratulations to Luke Khoury on the successful defense of his dissertation. Working, learning and growing together has been fun. I am proud of his scientific growth. Our research has opened a fresh perspective on peripheral immune cells: doi.org/10.64898/2026.09.11.…

The regulatory variation within a cell type is remarkably informative and interesting.

This gets particularly interesting in single cells from the same cell type. Working at the cell type level misses much of the action. 2/ biorxiv.org/content/10.1101/…

Do you need an intro to analyzing (prote)omics data? This series of lectures may be helpful. We aimed to make them short & accessible. Enjoy watching & learning ! youtube.com/playlist?list=PL…

Read the methods before reading the results Read the methods before reading the conclusions Read the methods before evaluating the conclusions Read the methods before making conclusions Read the methods!

A video summary of our recent preprint biorxiv.org/content/10.64898…

How much data would it take to describe human biology ? A very crude description of molecular abundance requires 1,000× more bites than all digital data humanity stores. We need more than scale to close the gap. blog.slavovlab.net/2026/09/2…

Using single-cell proteomics, we discovered protein (and functional) symmetry breaking in early mammalian embryos influencing cell fates. These proteomic asymmetries are detectable at the zygote stage, intensify by the 2-cell and 4-cell stage, and correlate with the sperm entry site, pointing to fertilization as a symmetry-breaking event. The clear protein differences allowed us to define two types of blastomeres, termed alpha and beta. ⬛ These differences predict the developmental potential of the blastomeres. Similar clustering and protein enrichment patterns found in human 2-cell embryos suggest this early asymmetry might be conserved. 1/

Beyond heterogeneity, single-cell analysis can reveal functional coherence. Coherence, regularity and principles advance science. Full recording: youtube.com/watch?v=z0dIhG4C…

Millions of PBMCs have been analyzed by scRNA-seq. Have we seen it all ? We profiled thousands of single PBMCs — proteomes and transcriptomes side by side — and uncovered functional coordination undetectable in the deepest scRNA-seq we could perform. biorxiv.org/content/10.64898… 1/

Among the numerous metrics evaluating academics, one stands out for me: Our intellectual heritage reflected in our students and colleagues, and their intellectual growth. That amplifies the initial sparks and bears more fruit than any one of us could have produced.

Some of the most important scientific results were initially rejected before they became important milestones of scientific progress. 🔷 If you have great results, this is one of the most effective ways to help them succeed: blog.slavovlab.net/2024/02/1… 1/

Nature just published a tech feature on single-cell proteomics. It highlights our journey from skepticism to robust technology and biological discoveries. I love that the feature starts with a biological discovery enabled by the technology: cell.com/cell/fulltext/S0092… 1/