The sacrificial adaptor protein Skp functions to remove stalled substrates from the β-barrel assembly machine

The biogenesis of integral β-barrel outer membrane proteins (OMPs) in gram-negative bacteria requires transport by molecular chaperones across the aqueous periplasmic space. Owing in part to the extensive functional redundancy within the periplasmic chaperone network, specific roles for molecular chaperones in OMP quality control and assembly have remained largely elusive. Here, by deliberately perturbing the OMP assembly process through use of multiple folding-defective substrates, we have identified a role for the periplasmic chaperone Skp in ensuring efficient folding of OMPs by the β-barrel assembly machine (Bam) complex. We find that β-barrel substrates that fail to integrate into the membrane in a timely manner are removed from the Bam complex by Skp, thereby allowing for clearance of stalled Bam–OMP complexes. Following the displacement of OMPs from the assembly machinery, Skp subsequently serves as a sacrificial adaptor protein to directly facilitate the degradation of defective OMP substrates by the periplasmic protease DegP. We conclude that Skp acts to ensure efficient β-barrel folding by directly mediating the displacement and degradation of assembly-compromised OMP substrates from the Bam complex.

The cell envelopes of gram-negative bacteria, mitochondria, and chloroplasts all contain an outer membrane (OM) consisting of integral transmembrane proteins that assume a β-barrel conformation (1, 2). In gram-negative bacteria such as Escherichia coli, β-barrel outer membrane proteins (OMPs) contribute to the selective permeability of the OM, protecting the cell from harmful molecules while still allowing for the uptake of nutrients (3). Structurally and functionally diverse OMPs serve a number of roles critical to cell viability, namely the selective passage of small molecules, efflux of toxins, insertion of lipopolysaccharide (LPS) onto the cell surface, and assembly of OMPs themselves (1, 4). Reflective of their importance in maintaining cellular integrity, defects in OMP biogenesis confer sensitivity to a wide array of toxic molecules including detergents, bile salts, and most importantly, antibiotics (5, 6). As such, considerable efforts have been made to identify agents that inhibit essential cellular processes performed by OMPs (7–12), with hopes of hastening the development of novel therapeutics to combat the ever-growing threat of antibiotic-resistant infections caused by gram-negative microbes (13, 14).Ensuring efficient OMP biogenesis is a particularly challenging cellular feat. Newly synthesized OMPs must traverse the aqueous, oxidizing periplasm in an unfolded state, avoid self-aggregation, and subsequently complete proper assembly, all in an environment devoid of cellular energy such as adenosine triphosphate (15). A multitude of molecular chaperones and proteases function to overcome this challenge by minimizing unfolded OMP accumulation and facilitating OMP transport to the OM assembly machinery (16). Although more than a dozen chaperones and proteases with clear implications in OMP biogenesis have been identified (16–18), the most well-characterized and predominant proteins in E. coli are the chaperones SurA and Skp, as well as the chaperone protease DegP. Numerous genetic, biochemical, and proteomic studies have demonstrated that SurA is the primary periplasmic chaperone that facilitates transport of the bulk mass of OMP substrates to the OM (19–24). Skp and DegP, on the other hand, comprise a secondary, partially redundant OMP biogenesis pathway that primarily serves to minimize accumulation of unfolded OMPs, either by rescuing their assembly or promoting their degradation (19, 20).Notably, Skp binds unfolded OMPs with dissociation constants in the low nanomolar range (25, 26), exceeding the binding affinities of either SurA or DegP (27–29), to form highly stable Skp–OMP complexes that display lifetimes on the order of hours (30). Given the substantial stability of Skp–OMP complexes, the precise mechanism of OMP release from Skp remains poorly understood. The rapid conformational dynamics of OMPs bound within the Skp cavity have been proposed to enable local substrate release that is ultimately driven by the recognition and folding of OMPs by the OM assembly machinery (30), thus coupling client release from Skp to the thermodynamic stability provided by OMP integration into a membrane (31). Indeed, substrate release and folding of OMPs from Skp–OMP complexes is enabled in vitro by incubation with OM folding machinery–containing liposomes (28, 32), demonstrating that Skp can facilitate productive OMP assembly. This mechanism of folding-driven substrate release has been similarly observed in genetic and biochemical studies indicating that Skp is capable of directly inserting OMPs into lipid bilayers in vitro (33), as well as the inner membrane in vivo (34), without assistance from the OM assembly machinery.Whether OMPs are capable of being removed from Skp within physiological timescales in the absence of coupled folding, however, is not entirely clear. Under conditions of periplasmic stress, in which the burden of unfolded OMPs exceeds the rate at which they can be assembled, the activities of both Skp and DegP become crucial (19, 20, 24, 35). Given that Skp not only binds substrates with a higher affinity than DegP (29) but also does so several orders of magnitude faster (36), how unfolded OMPs are transferred from Skp to DegP for degradation under stress conditions is not obvious. Indeed, direct transfer of an OMP from Skp to DegP has yet to be demonstrated, and intriguingly, the formation of Skp–DegP–OMP ternary complexes has been reported in such experiments (29, 36).Folding and insertion of nascent OMPs into the OM is catalyzed by the heteropentameric β-barrel assembly machine (Bam) complex, consisting of the BamA β-barrel and four accessory lipoproteins, BamBCDE (37, 38). Recent biochemical and structural studies have provided a relatively clear current model for the mechanism of β-barrel assembly. Following substrate recruitment to BamD (39), BamA catalyzes the sequential addition of β-hairpins in a C-to-N-terminal manner (40), with early folding occurring within the interior of the BamA barrel (41). Folding proceeds until membrane integration occurs, and subsequent stepwise hydrogen-bond formation between N and C substrate termini facilitates barrel closure and substrate release into the membrane (40).One outstanding question concerns the fate of OMP substrates that have stalled while folding on the Bam complex. Protein misfolding in the periplasm, translational error, or impaired Bam complex function can result in substrates arresting on the assembly machinery, a condition that can ultimately be lethal if left unchecked (42–44). Until recently, investigations of stalled OMP substrates have been largely impeded by a lack of structurally defined folding intermediates and the absence of an established general mechanism of OMP assembly. Several studies to date have utilized mutant alleles of the large β-barrel LptD to probe Bam complex assembly (39, 41, 45, 46), and multiple proteases that degrade assembly-compromised LptD within distinct stages of its folding regime have been identified (46, 47). It is unclear, however, whether these stringent quality control mechanisms monitoring assembly of LptD are exerted on all β-barrel substrates or whether LptD represents a unique case given its remarkably complex folding trajectory (48). Given that OMP assembly by the Bam complex has evolved to be incredibly efficient—so efficient that unfolded OMPs cannot be detected at steady state—it stands to reason that quality control mechanisms ensuring the efficient assembly of all β-barrel substrates exist. Recently, it has been shown that extracellular loop deletions within the C-terminal half of the BamA β-barrel cause early folding defects and thus render stalled BamA susceptible to proteolysis by DegP (40). How DegP actively disengages a partially folded, stalled substrate from its folding on BamA, given the relatively weak and slow nature of DegP binding, is not obvious.Here, we have utilized an assembly-defective variant of a slow-folding β-barrel OMP to investigate the fate of substrates that engage the OM assembly machinery but otherwise fail to undergo efficient folding and membrane integration. We identify a specific role for the periplasmic chaperone Skp in facilitating the degradation of defective OMP substrates by the protease DegP, thus imposing an active quality control mechanism that serves to remove assembly-compromised substrates from the Bam complex. Strikingly, we find that Skp is degraded alongside its bound substrate by DegP, thereby functioning as a sacrificial adaptor protein. By evaluating the requirement for Skp in degradation of a series of sequentially stalled β-barrel substrates, we find that Skp is only required to degrade substrates that have initiated folding on the Bam complex. Thus, β-barrel OMPs that have stalled during assembly specifically require Skp for their removal from the Bam complex and subsequent degradation by DegP. We conclude that Skp acts to ensure efficient β-barrel assembly by facilitating both the direct removal and degradation of stalled substrates from the Bam complex.     

Outer membrane β-barrel protein folding is physically controlled by periplasmic lipid head groups and BamA

Outer membrane β-barrel proteins (OMPs) are crucial for numerous cellular processes in prokaryotes and eukaryotes. Despite extensive studies on OMP biogenesis, it is unclear why OMPs require assembly machineries to fold into their native outer membranes, as they are capable of folding quickly and efficiently through an intrinsic folding pathway in vitro. By investigating the folding of several bacterial OMPs using membranes with naturally occurring Escherichia coli lipids, we show that phosphoethanolamine and phosphoglycerol head groups impose a kinetic barrier to OMP folding. The kinetic retardation of OMP folding places a strong negative pressure against spontaneous incorporation of OMPs into inner bacterial membranes, which would dissipate the proton motive force and undoubtedly kill bacteria. We further show that prefolded β-barrel assembly machinery subunit A (BamA), the evolutionarily conserved, central subunit of the BAM complex, accelerates OMP folding by lowering the kinetic barrier imposed by phosphoethanolamine head groups. Our results suggest that OMP assembly machineries are required in vivo to enable physical control over the spontaneously occurring OMP folding reaction in the periplasm. Mechanistic studies further allowed us to derive a model for BamA function, which explains how OMP assembly can be conserved between prokaryotes and eukaryotes.Outer membrane β-barrel proteins (OMPs) are found in the outer membranes of Gram-negative bacteria, mitochondria, and chloroplasts (1). The functions of OMPs are versatile and often essential as they include transport of metabolites and toxins as well as membrane biogenesis (2). Alterations of outer membranes and outer membrane proteins can lead to the development of antibiotic-resistance in pathogenic bacteria, and dysfunction of OMPs in outer membranes of mitochondria plays a role in diabetes and neurodegenerative diseases, among other life-threatening illnesses (3–7). How OMPs attain their native fold in their natural lipid environment is therefore a fundamental question in biological and biomedical research.The biological assembly of outer membrane proteins into bacterial outer membranes requires a functionally conserved protein complex, termed β-barrel assembly machinery (BAM) (8, 9). Previous work suggested that the main subunit of the BAM complex, the OMP BamA, carries out its essential function by providing a structural basis for OMP folding (10–12). However, it has been shown many times that OMPs are capable of spontaneously folding to their native state in model membranes in vitro through an intrinsic folding pathway in the absence of BamA (13–17). Neither the folding in vivo nor in vitro requires an external energy source such as ATP or a redox potential (18, 19).The observation that OMPs can fold to their native states in vitro raises the important question of why OMPs require assembly machineries such as BAM to fold into their cellular outer membranes. To address this question, we developed an experimental strategy that enabled us to monitor the folding kinetics of bacterial OMPs in the absence and presence of prefolded BamA under membrane conditions that mimicked the periplasmic lipid environment. We discovered that native lipid head groups impose a kinetic barrier to folding that is relieved by the catalytic action of BamA. Our findings explain many in vivo observations and allowed us to derive a biophysical model of OMP sorting to the correct cellular membrane followed by its folding into bacterial outer membranes.     

Class-specific interactions between Sis1 J-domain protein and Hsp70 chaperone potentiate disaggregation of misfolded proteins

Protein homeostasis is constantly being challenged with protein misfolding that leads to aggregation. Hsp70 is one of the versatile chaperones that interact with misfolded proteins and actively support their folding. Multifunctional Hsp70s are harnessed to specific roles by J-domain proteins (JDPs, also known as Hsp40s). Interaction with the J-domain of these cochaperones stimulates ATP hydrolysis in Hsp70, which stabilizes substrate binding. In eukaryotes, two classes of JDPs, Class A and Class B, engage Hsp70 in the reactivation of aggregated proteins. In most species, excluding metazoans, protein recovery also relies on an Hsp100 disaggregase. Although intensely studied, many mechanistic details of how the two JDP classes regulate protein disaggregation are still unknown. Here, we explore functional differences between the yeast Class A (Ydj1) and Class B (Sis1) JDPs at the individual stages of protein disaggregation. With real-time biochemical tools, we show that Ydj1 alone is superior to Sis1 in aggregate binding, yet it is Sis1 that recruits more Ssa1 molecules to the substrate. This advantage of Sis1 depends on its ability to bind to the EEVD motif of Hsp70, a quality specific to most of Class B JDPs. This second interaction also conditions the Hsp70-induced aggregate modification that boosts its subsequent dissolution by the Hsp104 disaggregase. Our results suggest that the Sis1-mediated chaperone assembly at the aggregate surface potentiates the entropic pulling, driven polypeptide disentanglement, while Ydj1 binding favors the refolding of the solubilized proteins. Such subspecialization of the JDPs across protein reactivation improves the robustness and efficiency of the disaggregation machinery.

Molecular chaperones are involved in the maintenance of protein homeostasis by aiding correct protein folding (1). Yet severe stress conditions induce excessive protein misfolding and aggregation (2). Upon stress relief, the return to the proteostasis is mediated by the Hsp70 chaperone with cochaperones, including J-domain proteins (JDPs/Hsp40s), which together restore the native state of misfolded polypeptides trapped in aggregates (3–5). The JDP–Hsp70 system acts alone in metazoans or in cooperation with an Hsp100 disaggregase in most other eukaryotes and bacteria (5, 6).Protein disaggregation and refolding starts with a recognition of misfolded polypeptides within an aggregate by a JDP, and then, its J-domain interacts with the nucleotide-binding domain of Hsp70, inducing ATP hydrolysis which triggers the closure of the Hsp70’s substrate-binding domain over the aggregated substrate (7, 8). The aggregate-bound Hsp70 interacts with an Hsp100 disaggregase, and this interaction allosterically activates Hsp100 and tethers it to the aggregate (9–16). Subsequently, in an ATP-driven process, Hsp100 disentangles and translocates polypeptides from aggregates (17–21), which enables their correct refolding, spontaneous or with an assistance of Hsp70 and its cochaperones (22, 23).JDPs are the major regulators of the Hsp70 activity and substrate specificity (3, 24, 25). In yeast Saccharomyces cerevisiae, a general Hsp70 chaperone, Ssa1, is recruited to protein disaggregation by two main cytosolic JDPs, Ydj1 and Sis1, assigned to the Class A and Class B, respectively (3, 4, 26). Both Ydj1 and Sis1 comprise a helical, highly conserved J-domain, a flexible, mostly unstructured G/F region, two beta-barrel peptide-binding domains, CTDI and CTDII, and a C-terminal dimerization domain (27–33). Ydj1 additionally features a Zn-binding domain located in the first part of the CTDI region of the protein, which is distinctive for the Class A JDPs (32, 34).Despite the structural similarities, the two JDPs are functionally nonredundant. Sis1 is essential, and Ydj1 is required for growth above 34 °C (26, 27, 35, 36). Overexpression of Sis1 suppresses the phenotype caused by the deletion of YDJ1, while Ydj1 overexpression is not sufficient to suppress the deletion of SIS1 (26, 27, 35–37). The two JDPs show different specificities toward amorphous and amyloid aggregates (35, 38) and different populations of amorphous aggregates formed in vitro (4, 24).Recent reports shed more light on the JDPs’ divergence. Both JDPs form homodimers, which differ in the structural orientation of the J-domain: In Sis1, the J-domain is restrained from Hsp70 binding by the interaction with the Helix 5 in the G/F region (26, 33, 39–41). Such autoinhibition, which also occurs in most human Class B JDPs, is released through the interaction with the C-terminal EEVD motif of Hsp70 (33, 42). This regulation is important for the disassembly of amyloid fibrils by the human JDP–Hsp70 system (43), but its role in the handling of stress-related, amorphous aggregates is not clear. Despite the breadth of data on Hsp70 mechanisms, we still lack understanding of how the disparate features of the JDPs impact Hsp70 functioning in protein disaggregation.Here, we investigate individual steps of protein disaggregation in the context of functional differences between Sis1 and Ydj1. Using various biochemical approaches, we show that the two JDPs drive different modes of Ssa1 binding to aggregated substrates, which dictate diverse kinetics of their disaggregation by Hsp104. The distinctive performance of Sis1 is associated with its interaction with the C terminus of Hsp70. Our results suggest that the bivalent interaction with the Class B JDP conditions aggregate remodeling by the Hsp70 system, resulting in enhanced Hsp104-dependent protein recovery. Our data indicate a mechanism by which the Class A and B JDPs contribute to the disaggregation efficacy in a complex and divergent manner.     

Protein aggregation can inhibit clathrin-mediated endocytosis by chaperone competition

Protein conformational diseases exhibit complex pathologies linked to numerous molecular defects. Aggregation of a disease-associated protein causes the misfolding and aggregation of other proteins, but how this interferes with diverse cellular pathways is unclear. Here, we show that aggregation of neurodegenerative disease-related proteins (polyglutamine, huntingtin, ataxin-1, and superoxide dismutase-1) inhibits clathrin-mediated endocytosis (CME) in mammalian cells by aggregate-driven sequestration of the major molecular chaperone heat shock cognate protein 70 (HSC70), which is required to drive multiple steps of CME. CME suppression was also phenocopied by HSC70 RNAi depletion and could be restored by conditionally increasing HSC70 abundance. Aggregation caused dysregulated AMPA receptor internalization and also inhibited CME in primary neurons expressing mutant huntingtin, showing direct relevance of our findings to the pathology in neurodegenerative diseases. We propose that aggregate-associated chaperone competition leads to both gain-of-function and loss-of-function phenotypes as chaperones become functionally depleted from multiple clients, leading to the decline of multiple cellular processes. The inherent properties of chaperones place them at risk, contributing to the complex pathologies of protein conformational diseases.Many neurodegenerative diseases are characterized by protein misfolding and aggregation (1–5). Although the underlying disease origins may be genetically inherited or manifest sporadically, as exemplified by Huntington disease and ALS, respectively, the pathologies of these maladies all share the common molecular occurrence of protein aggregation (6). A network of protein folding and clearance mechanisms (the proteostasis network) is proposed to maintain a healthy proteome for normal cellular function (7, 8). Central to the proteostasis network are molecular chaperones and cochaperones, a diverse group of proteins that modulate the synthesis, folding, transport, and degradation of proteins (7). The conformations of aggregation-prone proteins are subject to multiple layers of regulation by the proteostasis network; however, as evidenced by the widespread pathologies of protein conformational diseases, the aggregation propensity of proteins associated with these diseases ultimately overwhelms the proteostasis machineries, thus initiating a cascade of cellular dysfunction (9–11).It is increasingly common for diseases of protein aggregation to be described as the result of gain-of-function toxicity. This toxicity is largely attributed to the dominant appearance of diverse aggregate species and the subsequent aberrant association of various proteostasis network components and other metastable proteins with these aggregates. This position is supported by experiments using immunohistochemical, biochemical, and MS methods on diseased patient tissues, as well as on numerous cellular and animal model systems (12–16). Some of these molecular interactions, such as those between aggregates and proteasomal subunits, appear irreversible, suggesting a permanent sequestration of these proteins. The association of molecular chaperones with aggregates, on the other hand, appears transient (17, 18), indicating that chaperones may be functionally recognizing aggregates as substrates for potential disaggregation and refolding (19).Beyond refolding of toxic misfolded proteins, chaperones are also essential for the folding of endogenous metastable client proteins, as well as in the assembly and disassembly of functional protein complexes. Thus, chaperones regulate a wide range of essential cellular processes, including gene expression, vesicular trafficking, and signal transduction (20–25). This dual role of chaperones suggests that a “competition” may arise between aggregates and endogenous protein clients for finite chaperone resources in situations where aggregates have accumulated. It has been proposed that such an imbalance may trigger the onset of many neurodegenerative diseases (10, 26), and recent studies report that polyglutamine (polyQ)-based aggregates can sequester and inhibit the function of a low-abundance cochaperone, Sis1p/DNAJB1, in protein degradation (27).Here, we show that diverse disease-associated aggregates sequester the highly abundant major chaperone heat shock cognate protein 70 (HSC70) to the point of functional collapse of an essential cellular process, clathrin-mediated endocytosis (CME). Importantly, aggregate-driven CME inhibition is reversible and can be rescued by nominally increasing HSC70 levels. Aggregate-driven chaperone depletion may help explain the phenotypic complexities displayed in protein conformational diseases.     

High-throughput suppressor screen demonstrates that RcsF monitors outer membrane integrity and not Bam complex function

The regulator of capsule synthesis (Rcs) is a complex signaling cascade that monitors gram-negative cell envelope integrity. The outer membrane (OM) lipoprotein RcsF is the sensory component, but how RcsF functions remains elusive. RcsF interacts with the β-barrel assembly machinery (Bam) complex, which assembles RcsF in complex with OM proteins (OMPs), resulting in RcsF’s partial cell surface exposure. Elucidating whether RcsF/Bam or RcsF/OMP interactions are important for its sensing function is challenging because the Bam complex is essential, and partial loss-of-function mutations broadly compromise the OM biogenesis. Our recent discovery that, in the absence of nonessential component BamE, RcsF inhibits function of the central component BamA provided a genetic tool to select mutations that specifically prevent RcsF/BamA interactions. We employed a high-throughput suppressor screen to isolate a collection of such rcsF and bamA mutants and characterized their impact on RcsF/OMP assembly and Rcs signaling. Using these mutants and BamA inhibitors MRL-494 and darobactin, we provide multiple lines of evidence against the model in which RcsF senses Bam complex function. We show that Rcs activation in bam mutants results from secondary OM and lipopolysaccharide defects and that RcsF/OMP assembly is required for this activation, supporting an active role of RcsF/OMP complexes in sensing OM stress.

The bacterial cell envelope is an essential structure, acting as a first line of defense against environmental assault. The gram-negative cell envelope is complex, consisting of an inner (IM) and outer (OM) membrane that encloses the cell wall in an aqueous periplasmic space (1). The OM is asymmetric, with phospholipids and lipopolysaccharides (LPS) in the inner and outer leaflets, respectively. The cation cross-bridged LPS molecules confer extreme resistance to detergents and many antibiotics (2).The regulator of capsule synthesis (Rcs) signaling cascade is one of several envelope stress responses that monitor envelope integrity and biogenesis (Fig. 1) (3). Rcs involves at least six proteins spanning all cellular compartments from the cell surface to the cytoplasm. At the core of this pathway is the RcsCDB Histidine-Aspartate phosphorelay complex consisting of the IM hybrid histidine protein kinase RcsC, the IM phosphotransferase protein RcsD, and the cytoplasmic DNA-binding response regulator RcsB (4–6). The activity of this Rcs phosphorelay is regulated by interactions with two upstream components, IgaA and RcsF. IgaA is a polytopic IM protein with a large periplasmic domain, and it inhibits the phosphorelay through RcsD (7, 8). The OM lipoprotein RcsF is a sensory component of the Rcs cascade, which activates downstream signaling in response to stress by releasing IgaA inhibition (8–12). However, sensing by RcsF and signal transduction to IgaA are poorly understood at a molecular level, in part because many distinct genetic and chemical stimuli can induce Rcs, including defects in lipoprotein biogenesis (13–15), cell wall biogenesis (12, 16–19), and the defects of LPS at the cell surface (as a result of Polymyxin B [PMB] treatment, for example) (19–22).Open in a separate windowFig. 1.Proposed mechanistic models for the Rcs stress response. Rcs components (orange) are shown in the context of the envelope structure and biogenesis pathways. The sensory lipoprotein RcsF and the negative regulator IgaA are central to the regulation of RcsCDB phosphorelay. RcsF is exported to the OM by the Lol pathway; the Bam complex assembles RcsF with partner OMPs, leading to a partially surface-exposed topology. Red arrows represent proposed signaling events in response to stress (red stars) that are not yet fully understood. (A) Proposed model for the OM/LPS sensing by RcsF. Cell surface localization of RcsF NTD enables RcsF to monitor the integrity of the outer leaflet. Upon LPS stress (e.g., PMB treatment), the signal is transduced to the periplasmic CTD through the conformational change in the RcsF/OMP complex stimulating downstream signaling. (B) Proposed model for the Bam complex sensing function of RcsF. Envelope stress by an unknown mechanism inhibits the Bam complex function; as a result, RcsF/BamA interaction is prevented, and RcsF is accumulated in the periplasmic-facing orientation stimulating downstream signaling.At the OM, RcsF forms a complex with β-barrel OM proteins (OMPs) such as OmpA, OmpC, and OmpF, adopting a transmembrane orientation in which RcsF is partially surface exposed (12, 23). The β-barrel assembly machinery (Bam complex) that assembles all OMPs also assembles RcsF/OMP complexes, and RcsF interacts with its central and essential component, BamA (12, 23).Defective lipoprotein biogenesis results in the retention of RcsF at the IM, promoting physical association with IgaA and the constitutive activation of signaling (12, 13). Two hypotheses have been proposed to explain how RcsF signals from the OM (Fig. 1 A and B): the first suggests that the surface-exposed N-terminal domain (NTD) of RcsF in an RcsF/OMP complex monitors the integrity of LPS at the outer leaflet, transmitting the signal to the periplasmic carboxyl-terminal domain (CTD) to induce downstream signaling (19, 23) (Fig. 1A); the second argues that the RcsF/OMP complex plays no active role in signal transduction, with stress signals altering the RcsF/BamA interaction to retain RcsF in a periplasm-facing orientation, allowing downstream signaling (12) (Fig. 1B). This altering of the RcsF/BamA interaction is thought to allow RcsF to monitor Bam complex activity (12). Testing these hypotheses has proven to be challenging, as the Bam complex is essential, and there was no clear path to identifying point mutations that specifically disrupt RcsF/OMP or RcsF/BamA interactions without compromising OMP biogenesis and OM integrity.The Bam complex consists of five components, A through E (24): BamA is a β-barrel with five periplasmic Potra domains that scaffold four regulatory lipoproteins, BamB through E. An essential lipoprotein, BamD, recruits OMP substrates to the Bam complex and activates BamA for OMP folding and insertion into the OM (25–29). Coordination of BamA and BamD activities is essential for the OMP assembly and is mediated by their direct interaction at the Potra 5 interface, for which the salt bridge between BamA E373 and BamD R197 is critically important (29, 30). Previously, we reported that the loss of the nonessential Bam component BamE results in a significant decrease in RcsF/OMP assembly (SI Appendix, Fig. S1) (19). The ΔbamE strain and an assembly-defective rcsF^A55Y mutant strain (SI Appendix, Table S1) are both significantly deficient in the detection of PMB-induced LPS stress, providing the first evidence to support an active role for RcsF/OMP in signaling under conditions of LPS stress (19). In the absence of BamE, BamA binds RcsF but is unable to engage with BamD to complete RcsF/OMP assembly (31) (SI Appendix, Fig. S1). As a result, RcsF accumulates on BamA, preventing it from functioning in OMP assembly (31, 32). This RcsF-dependent “jamming” of BamA is the reason for the synthetic lethal interaction of ΔbamE and various bam mutants, including a bamB null (SI Appendix, Table S1) (31, 32).We exploited the lethal interaction between BamA and RcsF in the bamE bamB double mutant to select for mutations that disrupt this RcsF/BamA interaction. Our characterization of the effects of the rcsF and bamA suppressor mutations identified on Rcs signaling and RcsF/OMP assembly demonstrates that assembly of the RcsF/OMP complex is required for Rcs signaling and argues against the model that proposes that RcsF monitors BamA activity. Moreover, our data suggest that the recently published RcsF/BamA structure corresponds to the "jammed" RcsF-BamA complex and not an assembly intermediate, as suggested (33).     

Mutant libraries reveal negative design shielding proteins from supramolecular self-assembly and relocalization in cells

Understanding the molecular consequences of mutations in proteins is essential to map genotypes to phenotypes and interpret the increasing wealth of genomic data. While mutations are known to disrupt protein structure and function, their potential to create new structures and localization phenotypes has not yet been mapped to a sequence space. To map this relationship, we employed two homo-oligomeric protein complexes in which the internal symmetry exacerbates the impact of mutations. We mutagenized three surface residues of each complex and monitored the mutations’ effect on localization and assembly phenotypes in yeast cells. While surface mutations are classically viewed as benign, our analysis of several hundred mutants revealed they often trigger three main phenotypes in these proteins: nuclear localization, the formation of puncta, and fibers. Strikingly, more than 50% of random mutants induced one of these phenotypes in both complexes. Analyzing the mutant’s sequences showed that surface stickiness and net charge are two key physicochemical properties associated with these changes. In one complex, more than 60% of mutants self-assembled into fibers. Such a high frequency is explained by negative design: charged residues shield the complex from self-interacting with copies of itself, and the sole removal of the charges induces its supramolecular self-assembly. A subsequent analysis of several other complexes targeted with alanine mutations suggested that such negative design is common. These results highlight that minimal perturbations in protein surfaces’ physicochemical properties can frequently drive assembly and localization changes in a cellular context.

Understanding genotype to phenotype relationships is crucial to predict the molecular consequences of mutations (1). At the protein level, alanine scans have revealed how individual residues contribute to protein function, stability, and binding affinity (2–4). More recently, systematic mappings have been widely used to connect sequence variability to changes in protein structure (5, 6), stability (7–9), solubility (10), and functionality (2, 11–14). Similar efforts have been made to map the impact of mutations in protein–ligand (15, 16) and protein–protein interactions (17–21).However, mutations can impact proteins beyond their stability, function, or existing interactions with specific partners or ligands. Sequences can also encode how proteins distribute spatially in cells, either by addressing them to membrane-bound compartments (22) or by inducing their self-assembly into large polymeric structures (23–27) and membraneless compartments (28, 29). While changes in protein self-assembly and localization can serve a functional purpose in adaptation (30–36), they can also lead to disease (37). For example, the supramolecular self-assembly of hemoglobin and γD-crystallin cause sickle-cell disease and cataracts, respectively (38, 39). The mislocalization of nuclear proteins TDP-43 and FUS in the cytosol is associated with amyotrophic lateral sclerosis disease (40, 41), and the mislocalization of Ataxin-3 to the nucleus has been implicated in spinocerebellar ataxia type 3 disease (42). It is therefore critical to characterize principles by which mutations can trigger such supramolecular self-assembly and mislocalization.Symmetry is frequent in proteins (37, 43) and is a crucial property promoting their self-assembly into high-order structures (44–50). Indeed, a strong enrichment in symmetric homo-oligomers among natural filament-forming proteins has been reported (37). Previous work has also shown that point mutations to two hydrophobic amino acids—leucine and tyrosine—frequently led symmetric homo-oligomers to assemble into high-order assemblies. However, whether other types of amino acids would display a similar potential, whether they would do so often, and whether additional phenotypes of assembly and localization could emerge upon mutation remains unknown.Here, we assess the potential of mutations to trigger such changes in protein assembly and localization in vivo. We targeted two homo-oligomeric protein complexes and randomly mutated three neighboring residues at the surface of each complex. We expressed the mutants fused to a fluorescent protein to track their spatial distribution in yeast cells. We found that a vast sequence space led to changes in protein assembly and localization in both proteins with three predominant phenotypes: nuclear localization, the formation of filaments, and the formation of puncta. Sequencing of the mutants revealed that increasing surface stickiness frequently promoted nuclear localization in one of the two proteins. Surprisingly, in the other protein, a loss of negatively charged residues was sufficient to trigger protein self-assembly, with fibers frequently forming regardless of the type of mutation, including to alanine and glycine. We also observed that four out of eight additional complexes analyzed underwent supramolecular self-assembly or a change in cellular localization when surface charges were mutated to alanine, implying that negative design against supramolecular self-assembly and mislocalization is common among symmetric homo-oligomers.     

Conformational dynamics of a crystalline protein from microsecond-scale molecular dynamics simulations and diffuse X-ray scattering

X-ray diffraction from protein crystals includes both sharply peaked Bragg reflections and diffuse intensity between the peaks. The information in Bragg scattering is limited to what is available in the mean electron density. The diffuse scattering arises from correlations in the electron density variations and therefore contains information about collective motions in proteins. Previous studies using molecular-dynamics (MD) simulations to model diffuse scattering have been hindered by insufficient sampling of the conformational ensemble. To overcome this issue, we have performed a 1.1-μs MD simulation of crystalline staphylococcal nuclease, providing 100-fold more sampling than previous studies. This simulation enables reproducible calculations of the diffuse intensity and predicts functionally important motions, including transitions among at least eight metastable states with different active-site geometries. The total diffuse intensity calculated using the MD model is highly correlated with the experimental data. In particular, there is excellent agreement for the isotropic component of the diffuse intensity, and substantial but weaker agreement for the anisotropic component. Decomposition of the MD model into protein and solvent components indicates that protein–solvent interactions contribute substantially to the overall diffuse intensity. We conclude that diffuse scattering can be used to validate predictions from MD simulations and can provide information to improve MD models of protein motions.Proteins explore many conformations while carrying out their functions in biological systems (1–3). X-ray crystallography is the dominant source of information about protein structure; however, crystal structure models usually consist of just a single major conformation and at most a small portion of the model as alternate conformations. Crystal structures therefore are missing many details about the underlying conformational ensemble (4).Proteins assembled in crystalline arrays, like proteins in solution, exhibit rich conformational diversity (4) and often can perform their native functions (5). Many methods have emerged for using Bragg data to model conformational diversity in protein crystals (6–17). The development of these methods has been important as conformational diversity can lead to inaccuracies in protein structure models (9, 18–20). A key limitation of using the Bragg data, however, is that different models of conformational diversity can yield the same mean electron density.Whereas the Bragg scattering only contains information about the mean electron density, diffuse scattering (diffraction resulting in intensity between the Bragg peaks) is sensitive to spatial correlations in electron density variations (21–28) and therefore contains information about the way that atomic positions vary together in protein crystals. Because models that yield the same mean electron density can yield different correlations in electron density variations, diffuse scattering provides a means to increase the accuracy of crystallography for determining protein conformational variations (29). Peter Moore (30) and Mark Wilson (31) have argued that diffuse scattering should be used to test models of conformational diversity in X-ray crystallography.Several pioneering studies used diffuse scattering to reveal insights into correlated motions in proteins (17, 30, 32–49). Some of these studies used diffuse scattering to experimentally validate predictions of correlated motions from molecular-dynamics (MD) simulations (35–37, 40, 42–44). These studies revealed important insights but were limited by inadequate sampling of the conformational ensemble, leading to lack of convergence of the diffuse scattering calculations (35). Microsecond-scale simulations of staphylococcal nuclease were predicted to be adequate for convergence of diffuse scattering calculations (42). Modern simulation algorithms and computer hardware now enable microsecond or longer MD simulations of protein crystals (50).Here, we present calculations of diffuse X-ray scattering using a 1.1-μs MD simulation of crystalline staphylococcal nuclease. The results demonstrate that we have overcome the past limitation of inadequate sampling. We chose staphylococcal nuclease because the experiments of Wall et al. (49) still represent the only complete, high-quality, 3D diffuse scattering data set from a protein crystal. The calculated diffuse intensity is very similar using two independent halves of the trajectory; the results therefore are reproducible and can be meaningfully compared with the experimental data. The MD simulation provides a rich picture of conformational diversity in the energy landscape of a protein crystal, consisting of at least eight metastable states. Like previous MD studies of crystalline staphylococcal nuclease (42–44), the agreement of the simulation with the total experimental diffuse intensity is excellent, supporting the use of MD simulations to model diffuse scattering data. Unlike previous MD studies, we separately compared the more finely structured, anisotropic component of the diffuse intensity with experimental data. The agreement is substantial but weaker than for the isotropic component, indicating there are inaccuracies in the MD models. Our results therefore point toward using diffuse scattering to improve MD models of protein motions.     

Synthesis and folding of a mirror-image enzyme reveals ambidextrous chaperone activity

Mirror-image proteins (composed of d-amino acids) are promising therapeutic agents and drug discovery tools, but as synthesis of larger d-proteins becomes feasible, a major anticipated challenge is the folding of these proteins into their active conformations. In vivo, many large and/or complex proteins require chaperones like GroEL/ES to prevent misfolding and produce functional protein. The ability of chaperones to fold d-proteins is unknown. Here we examine the ability of GroEL/ES to fold a synthetic d-protein. We report the total chemical synthesis of a 312-residue GroEL/ES-dependent protein, DapA, in both l- and d-chiralities, the longest fully synthetic proteins yet reported. Impressively, GroEL/ES folds both l- and d-DapA. This work extends the limits of chemical protein synthesis, reveals ambidextrous GroEL/ES folding activity, and provides a valuable tool to fold d-proteins for drug development and mirror-image synthetic biology applications.All known living organisms use proteins composed of l-amino acids. Mirror-image proteins (composed of d-amino acids) are not found in nature and are promising therapeutic agents due to their resistance to degradation by natural proteases (1, 2). d-peptide inhibitors that target particular protein interfaces can be identified by mirror-image phage display (3, 4), in which a library of phage bearing l-peptides on their surface is screened against a mirror-image (d-) protein target. By symmetry, d-peptide versions of the identified sequences will bind to the natural l-target. Because d-protein targets must be chemically synthesized, this discovery method has thus far been limited to relatively small targets.Through rigorous application of recent advances in chemical protein synthesis (reviewed in ref. 5), the production of larger synthetic d-proteins is becoming increasingly feasible [e.g., 204-residue d-VEGF dimer (6) and 84-residue d-MDM2/MDMX (7)]. However, many proteins are prone to misfolding, especially as their size and complexity increase (8). Molecular chaperones, such as the extensively studied GroEL/ES, mediate folding by preventing aggregation of many cellular proteins (9, 10). GroEL/ES is thought to interact with these diverse substrates via nonspecific hydrophobic interactions, but it is unknown whether it can fold mirror-image proteins. If natural chaperones cannot fold mirror-image proteins, then the folding of large/complex d-proteins into their active conformations will be a major challenge (in the absence of mirror-image chaperones, which are currently inaccessible).The binding of substrates by GroEL is an intriguing instance of promiscuous molecular recognition. GroEL has been shown to interact transiently with ∼250 cytosolic proteins in Escherichia coli under normal growth conditions (8, 11). A subset of these proteins exhibit an absolute requirement for GroEL and its cochaperone GroES to avoid aggregation and fold into their native state (8, 12). Interestingly, sequence analysis of known GroEL/ES obligate substrates reveals no obvious consensus binding sequence (11), although structurally they are enriched in aggregation-prone folds (12).Several lines of evidence suggest the predominant interactions between GroEL/ES and substrate proteins are hydrophobic. Protein substrates trapped in nonnative states have been shown to present hydrophobic surfaces that are otherwise buried in the core of the correctly folded protein, and a hydrophobic binding model is supported by the thermodynamics of binding of these nonnative states to GroEL (13). Additionally, the GroEL apical domain residues implicated in substrate binding are largely hydrophobic (14). Finally, previous studies on the basis of substrate interaction with GroEL using short model peptides have concluded that the most important determinant of substrate binding is the presentation of a cluster of hydrophobic residues (15–17).The only evidence addressing the chiral specificity of GroEL/ES comes from a study that qualitatively demonstrated binding of a short d-peptide to GroEL (16). However, this NMR study required peptide concentrations that greatly exceed physiologic levels and did not localize the interaction to the substrate-binding region of GroEL. Only recently has it become feasible to directly test the stereospecificity of the GroEL/ES folding reaction by synthesizing the mirror-image version of a chaperone-dependent protein.Due to great interest in mirror-image proteins as targets for drug discovery (6, 7, 18, 19) and mirror-image synthetic biology (20, 21), we were intrigued by the possibility that natural (l-) GroEL/ES could assist in the folding of d-proteins. Thus, we synthesized a d-version of a substrate protein and evaluated its folding by GroEL/ES. Furthermore, because most GroEL/ES substrate proteins are large (>250 residues), this project provided an excellent opportunity to demonstrate the power of chemical synthesis methodologies for producing previously inaccessible synthetic proteins.     

Higher-order epistasis and phenotypic prediction

Contemporary high-throughput mutagenesis experiments are providing an increasingly detailed view of the complex patterns of genetic interaction that occur between multiple mutations within a single protein or regulatory element. By simultaneously measuring the effects of thousands of combinations of mutations, these experiments have revealed that the genotype–phenotype relationship typically reflects not only genetic interactions between pairs of sites but also higher-order interactions among larger numbers of sites. However, modeling and understanding these higher-order interactions remains challenging. Here we present a method for reconstructing sequence-to-function mappings from partially observed data that can accommodate all orders of genetic interaction. The main idea is to make predictions for unobserved genotypes that match the type and extent of epistasis found in the observed data. This information on the type and extent of epistasis can be extracted by considering how phenotypic correlations change as a function of mutational distance, which is equivalent to estimating the fraction of phenotypic variance due to each order of genetic interaction (additive, pairwise, three-way, etc.). Using these estimated variance components, we then define an empirical Bayes prior that in expectation matches the observed pattern of epistasis and reconstruct the genotype–phenotype mapping by conducting Gaussian process regression under this prior. To demonstrate the power of this approach, we present an application to the antibody-binding domain GB1 and also provide a detailed exploration of a dataset consisting of high-throughput measurements for the splicing efficiency of human pre-mRNA 5′ splice sites, for which we also validate our model predictions via additional low-throughput experiments.

Understanding the relationship between genotype and phenotype is difficult because the effects of a mutation often depend on which other mutations are already present in the sequence, a phenomenon known as epistasis (1–3). Recent advances in high-throughput mutagenesis and phenotyping have for the first time provided a detailed view of these complex genetic interactions, by allowing phenotypic measurements for the effects of tens of thousands of combinations of mutations within individual proteins (4–18), RNAs (19–24), and regulatory or splicing elements (25–31). Importantly, it has now become clear that the data from these experiments cannot be captured by considering simple pairwise interactions, but rather higher-order genetic interactions between three, four, or even all sites within a functional element are empirically common (2, 12, 32–44) and indeed often expected based on first-principles biophysical considerations (12, 23, 32, 35, 36, 41, 45, 46). However, the enormous number of possible combinations of mutations makes these higher-order interactions both difficult to conceptualize and challenging to incorporate into predictive models.From a very basic perspective, data from combinatorial mutagenesis experiments provide us with observations of phenotypic values for individual genotypes, the effects of specific mutations on specific genetic backgrounds, epistatic coefficients between pairs of mutations on specific backgrounds, etc. The essential problem in modeling data like this then comes down to the question of how to combine these observed quantities to make phenotypic predictions for unobserved genotypes. That is, given that we have already seen the results of a specific mutation in several different genetic backgrounds, how should we combine these observations to predict its effect in a new background?Here we provide an answer to this question based on the intuition that when making these predictions, we should focus on the observed effects of mutations that are nearby in sequence space to the genetic background we are making a prediction for, rather than observations of mutational effects that are more distant. We do this by considering a key comprehensible aspect of higher-order epistasis, namely, the decay in the predictability of mutational effects (12, 47), epistatic coefficients of double mutants, and observed phenotypes (33, 48, 49), as one moves through sequence space.More specifically, we use the observed pattern of decay in phenotypic correlation as a function of genetic distance to estimate the fraction of variance due to each order of interaction in our observed data. Based on these point estimates, we then construct a prior distribution over all possible sequence-to-function mappings where the expected decay in the predictability of mutational effects in the prior matches that observed in the data. Finally, we conduct Bayesian inference under this prior using Gaussian process regression (50) and employ Hamiltonian Monte Carlo (51) to sample from the resulting high-dimensional posterior distribution. The end result is a procedure that automatically weights the contributions of our observations to our predictions in the manner suggested by the type and extent of higher-order epistasis present in the data, while simultaneously accounting for the effects of measurement noise and quantifying the uncertainty in our predictions.We call this method empirical variance component regression (VC regression) because it uses an empirical Bayes (52) prior defined by the variance components. To demonstrate the performance of our method, we apply it to two datasets. The first dataset is derived from a combinatorial mutagenesis experiment for protein G (37), a streptococcal antibody-binding protein that has served as a model system for studies of the genotype–phenotype map in proteins. The second dataset consists of high-throughput measurements of the splicing efficiency of human 5′ splice sites (31), which are RNA sequence elements crucial for the assembly of the spliceosome during pre-mRNA splicing. For this latter dataset, we also present low-throughput validation measurements for our model predictions, as well as a qualitative exploration of the complex patterns of epistasis in splicing efficiency observed in this system.     

Conformational dynamics of a membrane protein chaperone enables spatially regulated substrate capture and release

Membrane protein biogenesis poses enormous challenges to cellular protein homeostasis and requires effective molecular chaperones. Compared with chaperones that promote soluble protein folding, membrane protein chaperones require tight spatiotemporal coordination of their substrate binding and release cycles. Here we define the chaperone cycle for cpSRP43, which protects the largest family of membrane proteins, the light harvesting chlorophyll a/b-binding proteins (LHCPs), during their delivery. Biochemical and NMR analyses demonstrate that cpSRP43 samples three distinct conformations. The stromal factor cpSRP54 drives cpSRP43 to the active state, allowing it to tightly bind substrate in the aqueous compartment. Bidentate interactions with the Alb3 translocase drive cpSRP43 to a partially inactive state, triggering selective release of LHCP’s transmembrane domains in a productive unloading complex at the membrane. Our work demonstrates how the intrinsic conformational dynamics of a chaperone enables spatially coordinated substrate capture and release, which may be general to other ATP-independent chaperone systems.Protein homeostasis is essential for all cells and requires proper control of the folding, localization, and interactions of proteins. The biogenesis of membrane proteins poses a particular challenge to protein homeostasis. Before arrival at the membrane, newly synthesized membrane proteins need to traverse aqueous cellular compartments where they are highly prone to aggregation. Thus, the posttranslational targeting of membrane proteins relies critically on effective molecular chaperones that maintain nascent membrane proteins in translocation competent states. Many examples illustrate the intimate link between chaperone function and membrane protein biogenesis: SecB, Skp, and SurA protect bacterial outer membrane proteins (1–5), and Hsp70 homologs assist the import of mitochondrial or chloroplast proteins (6).Our understanding of membrane protein chaperones lags far behind that for soluble proteins, such as DnaK and GroEL. All chaperones need to switch between “open” and “closed” conformations to allow substrate release and binding, respectively. For many chaperones that promote the folding of soluble proteins, these switches can be driven either by ATPase cycles, such as Hsp70 (7) and GroEL (8), or by changes in environmental conditions, such as the acid-induced HdeA (9, 10) and oxidation-induced Hsp33 (11). In contrast, membrane protein chaperones must regulate their action spatially: they must effectively capture substrate proteins in the aqueous phase, and then facilely and productively release them at the target membrane. With few exceptions (1, 2), how membrane protein chaperones achieve spatiotemporal coordination of their chaperone cycle is not well understood.The light harvesting chlorophyll a/b-binding proteins (LHCPs) provide an excellent model system to address these questions. Like >95% of organellar proteins, LHCPs are initially synthesized in the cytosol and imported across the chloroplast envelope in a largely unfolded state with the assistance of the LHCP translocation defect protein (12). In the stroma, LHCPs are protected in a soluble “transit complex” by the chloroplast signal recognition particle (cpSRP), comprised of cpSRP43 and cpSRP54 (13). Via interactions between the GTPase domains of cpSRP54 and its receptor cpFtsY, LHCPs are delivered to the Alb3 translocase and inserted into the thylakoid membrane (13–17). LHCPs comprise more than 50% of the proteins in the thylakoid membrane and are the most abundant membrane protein family on earth. Their sheer abundance, high aggregation propensity, and crucial roles in energy generation of green plants demand highly effective chaperone(s) during their biogenesis, making this a robust system to understand the function and mechanism of membrane protein chaperones.Previous work showed that the cpSRP43 subunit in cpSRP binds tightly to and quantitatively prevents the aggregation of multiple members of the LHCP family, demonstrating that cpSRP43 is responsible for chaperone function (18, 19). cpSRP43 is comprised of multiple protein-interaction domains: three chromodomains (CDs) and an ankyrin repeat domain (A1–A4) between CD1 and CD2 (Fig. 1A) (14). Biochemical and crystallographic analyses showed that a conserved Tyr204 in the third ankyrin repeat recognizes a FDPLGL motif in L18, a conserved 18-amino acid sequence between TM2 and TM3 of LHCP (20–22). In addition, aromatic cages in CD2 provide binding sites for a conserved RRKR motif in the C terminus of cpSRP54 (23). A recent study found that cpSRP54 can induce compaction of cpSRP43 and enhance L18 peptide binding threefold, suggesting that cpSRP54 could positively regulate cpSRP43 (24). Finally, cpSRP43 also interacts directly with the C-terminal stromal domain of the Alb3 translocase (termed Alb3CT) that mediates the membrane insertion of LHCP (25–29), suggesting a potential mechanism to couple substrate release to the correct localization of LHCP and its imminent membrane insertion (30). The ability of cpSRP43 to directly bind Alb3 may also explain findings in earlier genetic studies that, when both cpSRP54 and cpFtsY are deleted, cpSRP43 by itself can mediate the targeting and insertion of some LHCP family members, albeit less efficiently (30).Open in a separate windowFig. 1.The CD1Ank-BH fragment is necessary and sufficient for the chaperone activity of cpSRP43. (A) Schematic of cpSRP43. CD, chromodomain; A1–A4, ankyrin repeats 1–4; BH, bridging helix; SBD, substrate binding domain. (B) Binding of LHCP to wildtype cpSRP43 (black) and to the CD1Ank (green) and CD1Ank-BH (red) fragments of cpSRP43 were measured by the ability of cpSRP43 to prevent LHCP aggregation (Materials and Methods). The data were fit to Eq. 1 and gave apparent K_d values of 170 and 32 nM for LHCP binding to cpSRP43 and to the CD1Ank-BH fragment, respectively. (C) CD1Ank-BH (red) can reverse LHCP aggregation more efficiently than WT cpSRP43 (black), but the CD1Ank (green) fragment cannot. (D) Binding of HiLyte-Fluor 488–labeled L11 peptide to WT and mutant cpSRP43, detected by fluorescence anisotropy. The data were fit to Eq. 2 and gave K_d values of 25 and 15 nM for the binding of dye-labeled L11 peptide to cpSRP43 (black) and to the CD1Ank-BH (red) fragment, respectively. (E) Binding of the L18 peptide to WT and mutant cpSRP43 was measured using L18 as a competitor of dye-labeled L11. The data were fit to Eq. 3 and gave Kiapp values of 1.1 and 0.5 µM for cpSRP43 (black) and the CD1Ank-BH (red) fragment, respectively. Errors of K_d and Kiapp values were estimated to be ±10% (SD) based on at least two measurements (technical replicates).Nevertheless, the molecular mechanism of cpSRP43’s chaperone function remains elusive. Where is the substrate binding domain of this chaperone located? How does it interact with the targeting (cpSRP54) and translocation (Alb3) machineries to achieve accurate spatiotemporal regulation of its activity? More fundamentally, in the absence of an ATPase module, what propels the substrate binding and release cycle for this chaperone? In this work, a combination of biochemical and solution NMR studies addresses these questions and for the first time, to our knowledge, defines the complete chaperone cycle for a chaperone dedicated to integral membrane proteins. Our results show that cpSRP43 inherently exchanges between three distinct conformations; this allows it to be readily turned “on” by cpSRP54 in the aqueous stroma to enable tight substrate binding and to be readily switched to less active conformations by Alb3 at the membrane to enable facile substrate unloading. Furthermore, we show that Alb3 specifically induces the release of substrate TMDs, but not the L18 motif, from cpSRP43, suggesting a highly productive, stepwise mechanism for handover of the membrane protein substrates to the translocation machinery.     

Spontaneous nucleation and fast aggregate-dependent proliferation of α-synuclein aggregates within liquid condensates at neutral pH

The aggregation of α-synuclein into amyloid fibrils has been under scrutiny in recent years because of its association with Parkinson’s disease. This process can be triggered by a lipid-dependent nucleation process, and the resulting aggregates can proliferate through secondary nucleation under acidic pH conditions. It has also been recently reported that the aggregation of α-synuclein may follow an alternative pathway, which takes place within dense liquid condensates formed through phase separation. The microscopic mechanism of this process, however, remains to be clarified. Here, we used fluorescence-based assays to enable a kinetic analysis of the microscopic steps underlying the aggregation process of α-synuclein within liquid condensates. Our analysis shows that at pH 7.4, this process starts with spontaneous primary nucleation followed by rapid aggregate-dependent proliferation. Our results thus reveal the microscopic mechanism of α-synuclein aggregation within condensates through the accurate quantification of the kinetic rate constants for the appearance and proliferation of α-synuclein aggregates at physiological pH.

Parkinson’s disease is the most common neurodegenerative movement disorder (1, 2). A distinctive pathophysiological signature of this disease is the presence of abnormal intraneuronal protein deposits known as Lewy bodies (3, 4). One of the main components of Lewy bodies is α-synuclein (5), a peripheral membrane protein highly abundant at neuronal synapses (6, 7) and genetically linked with Parkinson’s disease (8, 9). This 140-residue disordered protein can be subdivided into three domains, an amphipathic N-terminal region (amino acids 1 to 60), a central hydrophobic region (non-amyloid-β component, or NAC, amino acids 61 to 95), and an acidic proline-rich C-terminal tail (amino acids 96 to 140) (7). Although α-synuclein aggregation is characteristic of Parkinson’s disease and related synucleinopathies, the corresponding mechanism and its possible pathological role in disease are not yet fully understood.Generally, the aggregation process of proteins proceeds through a series of interconnected microscopic steps, including primary nucleation, elongation, and secondary nucleation (10, 11). During primary nucleation, the self-assembly of proteins from their native, monomeric form leads to the formation of oligomeric species, an event that may occur in solution or on surfaces including biological membranes (12, 13). The formation of these oligomers is typically a slow event governed by high kinetic barriers (10, 11). Once formed, the oligomers may convert into ordered assemblies rich in β structure, which are capable of further growth into fibrillar aggregates (14). In many cases, the surfaces of existing fibrillar aggregates then further catalyze the formation of new oligomers (15, 16). This secondary nucleation process is typically characterized by the assembly of protein monomers on the surface of fibrils that eventually nucleate into new oligomeric species (15, 16). This autocatalytic mechanism generates rapid fibril proliferation (15).In the case of the aggregation process of α-synuclein, several key questions are still open, including two that we are addressing in this study. The first concerns whether there are cellular conditions under which α-synuclein can undergo spontaneous aggregation, and the second whether the proliferation of α-synuclein fibrils by aggregate-dependent feedback processes can take place at physiological pH. These questions are relevant because according to our current knowledge, α-synuclein aggregation does not readily take place spontaneously in the absence of contributing factors such as lipid membranes. Furthermore, secondary nucleation contributes significantly to the aggregation process only at acidic pH (13, 17). It thus remains challenging to rationalize the links between α-synuclein aggregation and Parkinson’s disease.To address this problem, we investigated whether it is possible to leverage the recent finding that α-synuclein can undergo a phase separation process resulting in the formation of dense liquid condensates (18–21). Phase separation has recently emerged as a general phenomenon associated with a wide variety of cellular functions (22–25) and closely linked with human disease (23, 26–29). This process has been reported for a wide range of proteins implicated in neurodegenerative conditions, including tau, fused in sarcoma (FUS), and TAR DNA binding protein 43 (TDP-43) (30–32). Since it has also been shown that protein aggregation can take place within liquid condensates (19, 26, 32–36), we asked whether it is possible to characterize at the microscopic level the condensate-induced aggregation mechanism of α-synuclein by determining the kinetic rate constants of the corresponding microscopic processes.To enable the accurate determination of the rate constants for the microscopic steps in α-synuclein aggregation within condensates, we developed fluorescence-based aggregation assays to monitor both the spontaneous aggregation of α-synuclein and the aggregation in the presence of aggregate seeds. Using these assays within the framework of a kinetic theory of protein aggregation (10, 11, 37), we show that α-synuclein can undergo spontaneous homogenous primary nucleation and fast aggregate-dependent proliferation within condensates at physiological pH.     

Calcium levels in the Golgi complex regulate clustering and apical sorting of GPI-APs in polarized epithelial cells

Glycosylphosphatidylinositol-anchored proteins (GPI-APs) are lipid-associated luminal secretory cargoes selectively sorted to the apical surface of the epithelia where they reside and play diverse vital functions. Cholesterol-dependent clustering of GPI-APs in the Golgi is the key step driving their apical sorting and their further plasma membrane organization and activity; however, the specific machinery involved in this Golgi event is still poorly understood. In this study, we show that the formation of GPI-AP homoclusters (made of single GPI-AP species) in the Golgi relies directly on the levels of calcium within cisternae. We further demonstrate that the TGN calcium/manganese pump, SPCA1, which regulates the calcium concentration within the Golgi, and Cab45, a calcium-binding luminal Golgi resident protein, are essential for the formation of GPI-AP homoclusters in the Golgi and for their subsequent apical sorting. Down-regulation of SPCA1 or Cab45 in polarized epithelial cells impairs the oligomerization of GPI-APs in the Golgi complex and leads to their missorting to the basolateral surface. Overall, our data reveal an unexpected role for calcium in the mechanism of GPI-AP apical sorting in polarized epithelial cells and identify the molecular machinery involved in the clustering of GPI-APs in the Golgi.

Glycosylphosphatidylinositol (GPI)-anchored proteins (GPI-APs) are localized on the apical surface of most epithelia, where they exert their physiological functions, which are regulated by their spatiotemporal compartmentalization.In polarized epithelial cells, the organization of GPI-APs at the apical surface is driven by the mechanism of apical sorting, which relies on the formation of GPI-AP homoclusters in the Golgi apparatus (1, 2). GPI-AP homoclusters (containing a single GPI-AP species) form uniquely in the Golgi apparatus of fully polarized cells (and not in nonpolarized cells) in a cholesterol-dependent manner (1, 3, 4). Once formed, GPI-AP homoclusters become insensitive to cholesterol depletion, suggesting that protein–protein interactions stabilize them (1, 2). At the apical membrane, newly arrived homoclusters coalesce into heteroclusters (containing at least two different GPI-AP species) that are sensitive to cholesterol depletion (1). Of importance, in the absence of homoclustering in the Golgi (e.g., in nonpolarized epithelial cells), GPI-APs remain in the form of monomers and dimers and do not cluster at the cell surface (1, 5). Thus, the organization of GPI-APs at the apical plasma membrane of polarized cells strictly depends on clustering mechanisms in the Golgi apparatus allowing their apical sorting. This is different from what was shown in fibroblasts where clustering of GPI-APs occurs from monomer condensation at the plasma membrane, indicating that distinct mechanisms regulate GPI-AP clustering in polarized epithelial cells and fibroblasts (1, 6, 7). Furthermore, in polarized epithelial cells, the spatial organization of clusters also appears to regulate the biological activity of the proteins (1) so that GPI-APs are fully functional only when properly sorted to the apical surface and less active in the case of missorting to the basolateral domain (1, 8, 9). Understanding the mechanism of GPI-AP apical sorting in the Golgi apparatus is therefore crucial to decipher their organization at the plasma membrane and the regulation of their activity. The determinants for protein apical sorting have been difficult to uncover compared to the ones for basolateral sorting (10–14). Besides a role of cholesterol, the molecular factors regulating the clustering-based mechanism of GPI-AP sorting in polarized epithelial cells are unknown. Here, we analyzed the possible role of the actin cytoskeleton and of calcium levels in the Golgi. The actin cytoskeleton is not only critical for the maintenance of the Golgi structure and its mechanical properties but also provides the structural support favoring carrier biogenesis (15–18). The Golgi exit of various cargoes is altered in cells treated with drugs either depolymerizing or stabilizing actin filaments (19, 20), and the post-Golgi trafficking is affected either by the knockdown of the expression of some actin-binding proteins, which regulate actin dynamics, or by the overexpression of their mutants (12, 21–23), all together revealing the critical role of actin dynamics for protein trafficking. Only few studies have shown the involvement of actin remodeling proteins in polarized trafficking, mostly in selectively mediating the apical and basolateral trafficking of transmembrane proteins [refs. 24–26; and reviewed in ref. 27]; thus, it remains unclear whether actin filaments play a role in protein sorting in polarized cells.On the other hand, the Golgi apparatus exhibits high calcium levels that have been revealed to be essential for protein processing and the sorting of some secreted soluble proteins in nonpolarized cells (28–31). Moreover, a functional interplay between the actin cytoskeleton and Golgi calcium in modulating protein sorting in nonpolarized cells has been shown (22).In this study, we report that in epithelial cells, actin perturbation does not impair GPI-AP clustering capacity in the Golgi and therefore their apical sorting. In contrast, we found that the Golgi organization of GPI-APs is drastically perturbed upon calcium depletion and that the amount of calcium in the Golgi cisternae is critical for the formation of GPI-AP homoclusters. We further show that the TGN calcium/manganese pump, SPCA1 (secretory pathway Ca(2+)-ATPase pump type 1), which controls the Golgi calcium concentration (32), and Cab45, a calcium-binding luminal Golgi resident protein previously described to be involved in the sorting of a subset of soluble cargoes (33, 34), are essential for the formation of GPI-APs homoclusters in the Golgi and for their subsequent apical sorting. Indeed, down-regulation of SPCA1 or Cab45 expression impairs the oligomerization of GPI-APs in the Golgi complex and leads to their missorting to the basolateral surface but does not affect apical or basolateral transmembrane proteins. Overall, our data reveal an unexpected role for calcium in the mechanism of GPI-AP apical sorting in polarized epithelial cells and identify the molecular machinery involved in the clustering of GPI-APs in the Golgi.     

Differential gradients of interaction affinities drive efficient targeting and recycling in the GET pathway

Efficient and accurate localization of membrane proteins requires a complex cascade of interactions between protein machineries. This requirement is exemplified in the guided entry of tail-anchored (TA) protein (GET) pathway, where the central targeting factor Get3 must sequentially interact with three distinct binding partners to ensure the delivery of TA proteins to the endoplasmic reticulum (ER) membrane. To understand the molecular principles that provide the vectorial driving force of these interactions, we developed quantitative fluorescence assays to monitor Get3–effector interactions at each stage of targeting. We show that nucleotide and substrate generate differential gradients of interaction energies that drive the ordered interaction of Get3 with successive effectors. These data also provide more molecular details on how the targeting complex is captured and disassembled by the ER receptor and reveal a previously unidentified role for Get4/5 in recycling Get3 from the ER membrane at the end of the targeting reaction. These results provide general insights into how complex protein interaction cascades are coupled to energy inputs in biological systems.Membrane proteins comprise ∼30% of the proteome; their efficient and accurate localization is crucial for the structure and function of all cells. Although the well-studied cotranslational signal recognition particle pathway delivers numerous endoplasmic reticulum (ER) -destined proteins (1), many membrane proteins use posttranslational targeting pathways with mechanisms that are far less well understood. A salient example is tail-anchored (TA) proteins, which comprise 3–5% of the eukaryotic membrane proteome and play essential roles in numerous processes, including protein translocation, vesicular trafficking, quality control, and apoptosis (2–5). Because their sole transmembrane domain is at the extreme C terminus, TA proteins cannot engage the cotranslational signal recognition particle machinery and instead, must use posttranslational pathways for localization (6).In the guided entry of TA protein (GET) pathway, TA proteins are initially captured by the yeast cochaperone Sgt2 (or mammalian SGTA) (2, 7). The Get4/5 complex then enables loading of the TA substrate from Sgt2 onto Get3 (or mammalian TRC40), the central targeting factor (7–9). The Get3/TA complex binds a receptor complex on the ER membrane comprised of Get1 and Get2, through which the TA protein is released from Get3 and inserted into the membrane (10–12). Dissociation from Get1/2 is then needed to recycle Get3 for additional rounds of targeting (11–13). Knockout of Get3 (or TRC40) confers stress sensitivity in yeast and embryonic lethality in mammals, underscoring its essential role in the proper functioning of the cell (10, 14, 15).TA protein targeting is driven by the ATPase cycle of Get3, a member of the signal recognition particle, MinD and BioD class of nucleotide hydrolases (8, 16). Crystallographic studies revealed that Get3 is an obligate homodimer, in which the ATPase domains bridge the dimer interface and are connected to helical domains (17, 18). Notably, the conformation of Get3 can be tuned by its nucleotide state, the TA substrate, and its binding partners (11, 12, 17, 19). Apo-Get3 is in an open conformation, in which the helical domains are disconnected (18). ATP biases Get3 to more closed structures, in which the helical domains form a contiguous hydrophobic surface implicated in TA protein binding (17, 18, 20). The Get4/5 complex further locks Get3 into an occluded conformation, in which ATP is tightly bound, but its hydrolysis is delayed, priming Get3 into the optimal state to capture the TA substrate (19, 21). TA proteins induce additional association of Get3 dimers to form a closed tetramer, which stimulates rapid ATP hydrolysis and delays ADP release (19, 22). Finally, Get1 strongly binds apo-Get3 in the open conformation (see below), likely at the end of the targeting reaction (11, 12, 23).The GET pathway demands a sequential cascade of interactions of Get3 with three distinct binding partners: the Get4 subunit in the Get4/5 complex and the Get1 and Get2 subunits in the Get1/2 receptor complex. All three partners share overlapping binding sites on Get3 (Fig. S1) (21), raising intriguing questions as to the mechanisms that ensure the high spatial and temporal accuracy of these protein interactions. For example, Get3 must first interact with Get4/5 in the cytosol to facilitate the loading of TA substrate (7, 9). It is unclear what then drives the release of Get3 from Get4/5 and enables its transit to the ER membrane, where it interacts with the Get1/2 receptor instead.Similarly, how Get3 and the Get3/TA complex transit between different subunits of the Get1/2 receptor at the ER membrane remains unclear. Get1/2 (WRB/CAML in mammals) is necessary and sufficient for TA protein insertion at the ER membrane (12, 13, 24, 25). Crystallographic analyses revealed that Get1 binds strongly to apo- or ADP-bound Get3 in the open conformation (11, 12, 23), whereas Get2 can bind Get3 in semiclosed or closed states (11, 12). In vitro reconstitution experiments showed that high concentrations of Get1 but not Get2 can trigger substrate release from Get3 (12). These observations led to the model that Get2 first captures Get3, whereas Get1 is responsible for disassembling the targeting complex (2, 13). Nevertheless, the subunit that is responsible for capturing the Get3/TA targeting complex has not been experimentally addressed, and whether Get1 or Get2 can discriminate different substrate-bound states of Get3 also has not been addressed.At the end of targeting, Get1 is tightly bound to apo-Get3 (11–13). Experiments with the cytosolic domain (CD) of Get1 show that its interaction with Get3 is strongly antagonized by ATP, leading to the current model that ATP drives the recycling of Get3 from the ER membrane (11, 12). However, two observations raise difficulties with this minimal model. In experiments with intact ER membranes or Get1/2 proteoliposomes (PLs), ATP is insufficient to completely release Get3 from the membrane (12, 13). Furthermore, the tight interaction of Get1 with Get3 raises the possibility that their dissociation is slow (11), which could pose potential barriers for subsequent rounds of TA protein targeting.To address these issues, we developed fluorescence assays to report on the interaction of Get3 with its effectors. Quantitative measurements show that both substrate and nucleotide regulate the interaction of Get3 with Get4/5 and Get1/2, generating differential gradients of interaction energies that drive the ordered transit of Get3 from one binding partner to the next. These results also reveal an active role of ATP in displacing Get3 from Get1, which together with Get4/5, ensures the effective recycling of Get3 back to the cytosol.