Disorder is a critical component of lipoprotein sorting in Gram-negative bacteria.

Gram-negative bacteria express structurally diverse lipoproteins in their cell envelope. Here, we find that approximately half of lipoproteins destined to the Escherichia coli outer membrane display an intrinsically disordered linker at their N terminus. Intrinsically disordered regions are common in proteins, but establishing their importance in vivo has remained challenging. As we sought to unravel how lipoproteins mature, we discovered that unstructured linkers are required for optimal trafficking by the Lol lipoprotein sorting system, whereby linker deletion re-routes three unrelated lipoproteins to the inner membrane. Focusing on the stress sensor RcsF, we found that replacing the linker with an artificial peptide restored normal outer-membrane targeting only when the peptide was of similar length and disordered. Overall, this study reveals the role played by intrinsic disorder in lipoprotein sorting, providing mechanistic insight into the biogenesis of these proteins and suggesting that evolution can select for intrinsic disorder that supports protein function.

Detecting Lipoproteins Sneaking Out of the Lipopolysaccharide Leaflet.

The envelope of Gram-negative bacteria is an essential compartment which is in direct contact with the environment; the envelope maintains cellular integrity and functions as a permeability barrier protecting the cell from toxic compounds. The outer layer of the envelope is an asymmetric membrane whose external leaflet is mainly composed of lipopolysaccharide molecules. Recently, there has been growing evidence that lipoproteins (i.e., soluble proteins anchored to a membrane by a lipid moiety) decorate the lipopolysaccharide leaflet in the model bacterium Escherichia coli, challenging the current paradigm that lipoproteins remain in the periplasm in this organism. However, assessing the surface exposure of lipoproteins is challenging. Here, we describe an optimized and reproducible dotblot protocol to assess the presence of lipoproteins at the surface of E. coli and other bacterial models. We added all necessary controls to reduce the possibility of artifacts giving rise to false-positive results. We selected the stress sensor RcsF as a model lipoprotein to illustrate the method, which can be used for any other lipoprotein.