The mechanisms of integral membrane protein biogenesis
TL;DR: In this article, the molecular basis of integral membrane protein targeting and insertion has been investigated, with tantalizing new insights into the poorly understood processes of multipass membrane protein biogenesis and multi-subunit protein complex assembly.
Abstract: Roughly one quarter of all genes code for integral membrane proteins that are inserted into the plasma membrane of prokaryotes or the endoplasmic reticulum membrane of eukaryotes. Multiple pathways are used for the targeting and insertion of membrane proteins on the basis of their topological and biophysical characteristics. Multipass membrane proteins span the membrane multiple times and face the additional challenges of intramembrane folding. In many cases, integral membrane proteins require assembly with other proteins to form multi-subunit membrane protein complexes. Recent biochemical and structural analyses have provided considerable clarity regarding the molecular basis of membrane protein targeting and insertion, with tantalizing new insights into the poorly understood processes of multipass membrane protein biogenesis and multi-subunit protein complex assembly.
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TL;DR: In this paper, the authors follow the signal peptide into the endoplasmic reticulum (ER) and discuss the recent insights that structural biology has provided on the governing principles of those interactions.
Abstract: Cleavable endoplasmic reticulum (ER) signal peptides (SPs) and other non-cleavable signal sequences target roughly a quarter of the human proteome to the ER. These short peptides, mostly located at the N-termini of proteins, are highly diverse. For most proteins targeted to the ER, it is the interactions between the signal sequences and the various ER targeting and translocation machineries such as the signal recognition particle (SRP), the protein-conducting channel Sec61, and the signal peptidase complex (SPC) that determine the proteins’ target location and provide translocation fidelity. In this review, we follow the signal peptide into the ER and discuss the recent insights that structural biology has provided on the governing principles of those interactions.
18 citations
TL;DR: In this article , biochemical and structural analysis of intermediates during multipass protein biogenesis showed that the nascent chain is not engaged with Sec61, which is occluded and latched closed by CCDC47.
Abstract: Multipass membrane proteins play numerous roles in biology and include receptors, transporters, ion channels and enzymes1,2. How multipass proteins are co-translationally inserted and folded at the endoplasmic reticulum is not well understood2. The prevailing model posits that each transmembrane domain (TMD) of a multipass protein successively passes into the lipid bilayer through a front-side lateral gate of the Sec61 protein translocation channel3-9. The PAT complex, an intramembrane chaperone comprising Asterix and CCDC47, engages early TMDs of multipass proteins to promote their biogenesis by an unknown mechanism10. Here, biochemical and structural analysis of intermediates during multipass protein biogenesis showed that the nascent chain is not engaged with Sec61, which is occluded and latched closed by CCDC47. Instead, Asterix binds to and redirects the substrate to a location behind Sec61, where the PAT complex contributes to a multipass translocon surrounding a semi-enclosed, lipid-filled cavity11. Detection of multiple TMDs in this cavity after their emergence from the ribosome suggests that multipass proteins insert and fold behind Sec61. Accordingly, biogenesis of several multipass proteins was unimpeded by inhibitors of the Sec61 lateral gate. These findings elucidate the mechanism of an intramembrane chaperone and suggest a new framework for multipass membrane protein biogenesis at the endoplasmic reticulum.
17 citations
TL;DR: In this article , a pre-translocation intermediate with eukaryotic elongation factor 1a (eEF1a) was found to remain associated with the ribosome after GTP hydrolysis during proofreading.
Abstract: Abstract The dynamic ribosome–translocon complex, which resides at the endoplasmic reticulum (ER) membrane, produces a major fraction of the human proteome 1,2 . It governs the synthesis, translocation, membrane insertion, N -glycosylation, folding and disulfide-bond formation of nascent proteins. Although individual components of this machinery have been studied at high resolution in isolation 3–7 , insights into their interplay in the native membrane remain limited. Here we use cryo-electron tomography, extensive classification and molecular modelling to capture snapshots of mRNA translation and protein maturation at the ER membrane at molecular resolution. We identify a highly abundant classical pre-translocation intermediate with eukaryotic elongation factor 1a (eEF1a) in an extended conformation, suggesting that eEF1a may remain associated with the ribosome after GTP hydrolysis during proofreading. At the ER membrane, distinct polysomes bind to different ER translocons specialized in the synthesis of proteins with signal peptides or multipass transmembrane proteins with the translocon-associated protein complex (TRAP) present in both. The near-complete atomic model of the most abundant ER translocon variant comprising the protein-conducting channel SEC61, TRAP and the oligosaccharyltransferase complex A (OSTA) reveals specific interactions of TRAP with other translocon components. We observe stoichiometric and sub-stoichiometric cofactors associated with OSTA, which are likely to include protein isomerases. In sum, we visualize ER-bound polysomes with their coordinated downstream machinery.
16 citations
TL;DR: The constraints and mechanisms governing eukaryotic co- and posttranslational protein folding and assembly are reviewed, including the influence of elongation rate on nascent chain targeting, folding, and chaperone interactions.
Abstract: The formation of protein complexes is crucial to most biological functions. The cellular mechanisms governing protein complex biogenesis are not yet well understood, but some principles of cotranslational and posttranslational assembly are beginning to emerge. In bacteria, this process is favored by operons encoding subunits of protein complexes. Eukaryotic cells do not have polycistronic mRNAs, raising the question of how they orchestrate the encounter of unassembled subunits. Here we review the constraints and mechanisms governing eukaryotic co- and posttranslational protein folding and assembly, including the influence of elongation rate on nascent chain targeting, folding, and chaperone interactions. Recent evidence shows that mRNAs encoding subunits of oligomeric assemblies can undergo localized translation and form cytoplasmic condensates that might facilitate the assembly of protein complexes. Understanding the interplay between localized mRNA translation and cotranslational proteostasis will be critical to defining protein complex assembly in vivo. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
14 citations
TL;DR: In this article , the authors performed an unbiased peptidome stability screen in yeast and identified a large cohort of proteome-derived degrons, some of which exhibited broad E3 ligase specificity.
Abstract: Abstract The eukaryotic proteome undergoes constant surveillance by quality control systems that either sequester, refold, or eliminate aberrant proteins by ubiquitin-dependent mechanisms. Ubiquitin-conjugation necessitates the recognition of degradation determinants, termed degrons, by their cognate E3 ubiquitin-protein ligases. To learn about the distinctive properties of quality control degrons, we performed an unbiased peptidome stability screen in yeast. The search identify a large cohort of proteome-derived degrons, some of which exhibited broad E3 ligase specificity. Consequent application of a machine-learning algorithm establishes constraints governing degron potency, including the amino acid composition and secondary structure propensities. According to the set criteria, degrons with transmembrane domain-like characteristics are the most probable sequences to act as degrons. Similar quality control degrons are present in viral and human proteins, suggesting conserved degradation mechanisms. Altogether, the emerging data indicate that transmembrane domain-like degron features have been preserved in evolution as key quality control determinants of protein half-life.
11 citations
References
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TL;DR: A computer program that progressively evaluates the hydrophilicity and hydrophobicity of a protein along its amino acid sequence has been devised and its simplicity and its graphic nature make it a very useful tool for the evaluation of protein structures.
21,921 citations
TL;DR: A new membrane protein topology prediction method, TMHMM, based on a hidden Markov model is described and validated, and it is discovered that proteins with N(in)-C(in) topologies are strongly preferred in all examined organisms, except Caenorhabditis elegans, where the large number of 7TM receptors increases the counts for N(out)-C-in topologies.
11,453 citations
TL;DR: T tandem affinity purification was used to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae to identify protein–protein interactions, which will help future studies on individual proteins as well as functional genomics and systems biology.
Abstract: Identification of protein-protein interactions often provides insight into protein function, and many cellular processes are performed by stable protein complexes. We used tandem affinity purification to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae. Each preparation was analysed by both matrix-assisted laser desorption/ionization-time of flight mass spectrometry and liquid chromatography tandem mass spectrometry to increase coverage and accuracy. Machine learning was used to integrate the mass spectrometry scores and assign probabilities to the protein-protein interactions. Among 4,087 different proteins identified with high confidence by mass spectrometry from 2,357 successful purifications, our core data set (median precision of 0.69) comprises 7,123 protein-protein interactions involving 2,708 proteins. A Markov clustering algorithm organized these interactions into 547 protein complexes averaging 4.9 subunits per complex, about half of them absent from the MIPS database, as well as 429 additional interactions between pairs of complexes. The data (all of which are available online) will help future studies on individual proteins as well as functional genomics and systems biology.
2,975 citations
TL;DR: It is suggested that an age-related decline in proteostasis capacity allows the manifestation of various protein-aggregation diseases, including Alzheimer's disease and Parkinson's disease, which may spring from a detailed understanding of the pathways underlying proteome maintenance.
Abstract: Most proteins must fold into defined three-dimensional structures to gain functional activity. But in the cellular environment, newly synthesized proteins are at great risk of aberrant folding and aggregation, potentially forming toxic species. To avoid these dangers, cells invest in a complex network of molecular chaperones, which use ingenious mechanisms to prevent aggregation and promote efficient folding. Because protein molecules are highly dynamic, constant chaperone surveillance is required to ensure protein homeostasis (proteostasis). Recent advances suggest that an age-related decline in proteostasis capacity allows the manifestation of various protein-aggregation diseases, including Alzheimer's disease and Parkinson's disease. Interventions in these and numerous other pathological states may spring from a detailed understanding of the pathways underlying proteome maintenance.
2,803 citations
TL;DR: A deep neural network-based approach that improves SP prediction across all domains of life and distinguishes between three types of prokaryotic SPs is presented.
Abstract: Signal peptides (SPs) are short amino acid sequences in the amino terminus of many newly synthesized proteins that target proteins into, or across, membranes. Bioinformatic tools can predict SPs from amino acid sequences, but most cannot distinguish between various types of signal peptides. We present a deep neural network-based approach that improves SP prediction across all domains of life and distinguishes between three types of prokaryotic SPs.
2,732 citations