Enabling cryo‐EM density interpretation from yeast native cell extracts by proteomics data and AlphaFold structures

Abstract

In the cellular context, proteins participate in communities to perform their function. The detection and identification of these communities as well as in‐community interactions has long been the subject of investigation, mainly through proteomics analysis with mass spectrometry. With the advent of cryogenic electron microscopy and the “resolution revolution,” their visualization has recently been made possible, even in complex, native samples. The advances in both fields have resulted in the generation of large amounts of data, whose analysis requires advanced computation, often employing machine learning approaches to reach the desired outcome. In this work, we first performed a robust proteomics analysis of mass spectrometry (MS) data derived from a yeast native cell extract and used this information to identify protein communities and inter‐protein interactions. Cryo‐EM analysis of the cell extract provided a reconstruction of a biomolecule at medium resolution (∼8 Å (FSC = 0.143)). Utilizing MS‐derived proteomics data and systematic fitting of AlphaFold‐predicted atomic models, this density was assigned to the 2.6 MDa complex of yeast fatty acid synthase. Our proposed workflow identifies protein complexes in native cell extracts from Saccharomyces cerevisiae by combining proteomics, cryo‐EM, and AI‐guided protein structure prediction.

Advances in Structural Virology via Cryo-EM in 2022

“…This combination of high-quality images coupled with advanced software running on powerful computers allows new questions to be answered. In addition to improving analyses of classical images, the current software within cryo-electron microscopy enables the separation of multiple conformations that can be adopted by a macromolecular complex [ 3 ] and even the separation of different macromolecular species present in a sample [ 4 ]. If the obtained resolution is still not optimal, the experimental electron density maps can then be combined with three-dimensional (3D) models obtained using structure prediction software such as AlphaFold2 [ 5 , 6 ].…”