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

Abstract

Inthecellularcontext,proteinsparticipateincommunitiestoperformtheirfunction.Thedetectionandidentificationofthesecommunitiesaswellasin-communityinter-actionshaslongbeenthesubjectofinvestigation,mainlythroughproteomicsanalysiswithmassspectrometry.Withtheadventofcryogenicelectronmicroscopyandthe“resolutionrevolution,”theirvisualizationhasrecentlybeenmadepossible,evenincomplex, native samples. The advances in both fields have resulted in the genera-tionoflargeamountsofdata,whoseanalysisrequiresadvancedcomputation,oftenemployingmachinelearningapproachestoreachthedesiredoutcome.Inthiswork,wefirstperformedarobustproteomicsanalysisofmassspectrometry(MS)dataderivedfromayeastnativecellextractandusedthisinformationtoidentifyproteincommu-nitiesandinter-proteininteractions.Cryo-EManalysisofthecellextractprovidedareconstructionofabiomoleculeatmediumresolution(∼8Å(FSC=0.143)).Utiliz-ingMS-derivedproteomicsdataandsystematicfittingofAlphaFold-predictedatomicmodels, this density was assigned to the 2.6 MDa complex of yeast fatty acid syn-thase.OurproposedworkflowidentifiesproteincomplexesinnativecellextractsfromSaccharomyces cerevisiaeby combining proteomics, cryo-EM, and AI-guided proteinstructureprediction.