Back

Multimodal mass spectrometry imaging reveals single-cell metabolic states in mammalian liver

Tian, H.; Rajbhandari, P. R.; Tarolli, J.; Decker, A. M.; Neelakantan, T. V.; Angerer, T.; Zandkarimi, F.; Daniels, J.; Remotti, H. R.; Frache, G.; Winograd, N.; Stockwell, B. R.

2022-09-28 cell biology
10.1101/2022.09.26.508878 bioRxiv
Show abstract

We have developed a powerful workflow to imaging endogenous metabolism in single cells on frozen tissue, allowing us to discover new cell subtypes in human liver. Performing spatially integrated multiomics in single cells within tissues is at the leading frontier in biology but has been prevented by technological challenges. We developed a critical new technology, cryogenic water cluster ion beam secondary ion mass spectrometry imaging ((H2O)n>28K-GCIB-SIMS)) at 1 {micro}m single-cell resolution. This allowed us to perform multi-modal mass spectrometry imaging (MSI) to detect metabolites, lipids, and proteins in single cells within functional liver zones and diverse cell types in the native tissue state. Our workflow utilizes the desorption electrospray ionization (DESI) mass spectrometry imaging (MSI) to build a reference map of metabolic heterogeneity and zonation across liver functional units. Then cryogenic (H2O)n>28K-GCIB-SIMS and C60-SIMS integrated metabolomics, lipidomic and proteomics, - characterizing the metabolic state in single cells on the same tissue section. We found for the first time that lipids and metabolites can classify liver metabolic zones and liver cell types beyond histological and protein-marker annotation. This provides a multi-modal workflow to define single-cell states in normal physiology and disease in mammalian tissue.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.