Global landscape of cell envelope protein complexes in Escherichia coli

Abstract

Bacterial cell envelope protein (CEP) complexes mediate a range of processes, including membrane assembly, antibiotic resistance and metabolic coordination. However, only limited characterization of relevant macromolecules has been reported to date. Here we present a proteomic survey of 1,347 CEPs encompassing 90% inner- and outer-membrane and periplasmic proteins of Escherichia coli. After extraction with non-denaturing detergents, we affinity-purified 785 endogenously tagged CEPs and identified stably associated polypeptides by precision mass spectrometry. The resulting high-quality physical interaction network, comprising 77% of targeted CEPs, revealed many previously uncharacterized heteromeric complexes. We found that the secretion of autotransporters requires translocation and the assembly module TamB to nucleate proper folding from periplasm to cell surface through a cooperative mechanism involving the β-barrel assembly machinery. We also establish that an ABC transporter of unknown function, YadH, together with the Mla system preserves outer membrane lipid asymmetry. This E. coli CEP ‘interactome’ provides insights into the functional landscape governing CE systems essential to bacterial growth, metabolism and drug resistance.

Profiling the E. coli Membrane Interactome Captured in Peptidisc Libraries

“…This is to be expected, since M3D expression correlation was used as a feature in our machine learning classifier (see Methods), meaning high M3D correlation was a criterion on which our peptidisc interactions were selected. However, we also note that protein pairs in our peptidisc interactome had higher expression than protein pairs in the E. coli CE interactome (Babu et al 2018). Therefore, as expected, protein pairs in the peptidisc interactome were well-correlated as measured by M3D, and the level of correlation is higher than the benchmark CE interactome.…”

“…These indicators compare favorably with validating interactomes identified by low-throughput AP/MS, which generally have relatively few false positives ( Fig. 5; Babu et al 2018).…”

“…Therefore, to further estimate the biological plausibility of our peptidisc interactome, we determined whether predicted interacting pairs were more likely than non-interacting pairs to be enriched for three measures of biological association: shared GO terms, positively correlated stress phenotypes, and shared binding domains (Erickson et al 2017;Mosca et al 2014). Further, these enrichment values allowed us to benchmark our interactome against the E. coli cell envelope (CE) interactome recently published by Babu and collaborators (Babu et al 2018).…”

“…While many perform their functions independently, the majority of proteins interact with others to achieve their full biological activity. Characterizing protein-protein interaction networks (the interactome) has traditionally been accomplished by methods such as affinity purification coupled to identification by mass spectrometry (AP/MS) (Arifuzzaman et al 2006;Hu et al 2009;Babu et al 2012Babu et al , 2018, protein fragment complementation assays (Rochette et al 2015;Tarassov et al 2008), or yeast two-hybrid screening (Y2H) (Rajagopala et al 2014). While highthroughput, these methods are quite often limited in their scope by poor scalability because bait proteins must be independently tagged.…”

Global Landscape of Native Protein Complexes inSynechocystissp. PCC 6803

“…The high-throughput methods developed for systematically determining PPIs have led to global molecular interaction maps for model organisms, including E.coli, yeast, 4 worm, fly, and human [18], [19], [20], [21]. Several approaches have been developed for the identification of protein complexes at proteome scale, e.g., Yeast two-hybrid (Y2H), affinity purification followed by mass spectrometry (AP-MS), and cofractionation coupled with mass spectrometry (CoFrac-MS).…”