Sebastian Pechmann

Evolutionary conservation of codon optimality reveals hidden signatures of cotranslational folding

The choice of codons can influence local translation kinetics during protein synthesis. Whether codon preference is linked to cotranslational regulation of polypeptide folding remains unclear. Here, we derive a revised translational efficiency scale that incorporates the competition between tRNA supply and demand. Applying this scale to ten closely related yeast species, we uncover the evolutionary conservation of codon optimality in eukaryotes. This analysis reveals universal patterns of conserved optimal and nonoptimal codons, often in clusters, which associate with the secondary structure of the translated polypeptides independent of the levels of expression. Our analysis suggests an evolved function for codon optimality in regulating the rhythm of elongation to facilitate cotranslational polypeptide folding, beyond its previously proposed role of adapting to the cost of expression. These findings establish how mRNA sequences are generally under selection to optimize the cotranslational folding of corresponding polypeptides.

The Ribosome as a Hub for Protein Quality Control

Cells face a constant challenge as they produce new proteins. The newly synthesized polypeptides must be folded properly to avoid aggregation. If proteins do misfold, they must be cleared to maintain a functional and healthy proteome. Recent work is revealing the complex mechanisms that work cotranslationally to ensure protein quality control during biogenesis at the ribosome. Indeed, the ribosome is emerging as a central hub in coordinating these processes, particularly in sensing the nature of the nascent protein chain, recruiting protein folding and translocation components, and integrating mRNA and nascent chain quality control. The tiered and complementary nature of these decision-making processes confers robustness and fidelity to protein homeostasis during protein synthesis.

The Molecular Architecture of the Eukaryotic Chaperonin TRiC/CCT

TRiC/CCT is a highly conserved and essential chaperonin that uses ATP cycling to facilitate folding of approximately 10% of the eukaryotic proteome. This 1 MDa hetero-oligomeric complex consists of two stacked rings of eight paralogous subunits each. Previously proposed TRiC models differ substantially in their subunit arrangements and ring register. Here, we integrate chemical crosslinking, mass spectrometry, and combinatorial modeling to reveal the definitive subunit arrangement of TRiC. In vivo disulfide mapping provided additional validation for the crosslinking-derived arrangement as the definitive TRiC topology. This subunit arrangement allowed the refinement of a structural model using existing X-ray diffraction data. The structure described here explains all available crosslink experiments, provides a rationale for previously unexplained structural features, and reveals a surprising asymmetry of charges within the chaperonin folding chamber.

Principles of Cotranslational Ubiquitination and Quality Control at the Ribosome

Achieving efficient cotranslational folding of complex proteomes poses a challenge for eukaryotic cells. Nascent polypeptides that emerge vectorially from the ribosome often cannot fold stably and may be susceptible to misfolding and degradation. The extent to which nascent chains are subject to cotranslational quality control and degradation remains unclear. Here, we directly and quantitatively assess cotranslational ubiquitination and identify, at a systems level, the determinants and factors governing this process. Cotranslational ubiquitination occurs at very low levels and is carried out by a complex network of E3 ubiquitin ligases. Ribosome-associated chaperones and cotranslational folding protect the majority of nascent chains from premature quality control. Nonetheless, a number of nascent chains whose intrinsic properties hinder efficient cotranslational folding remain susceptible for cotranslational ubiquitination. We find that quality control at the ribosome is achieved through a tiered system wherein nascent polypeptides have a chance to fold before becoming accessible to ubiquitination.

The Cotranslational Function of Ribosome-Associated Hsp70 in Eukaryotic Protein Homeostasis

In eukaryotic cells a molecular chaperone network associates with translating ribosomes, assisting the maturation of emerging nascent polypeptides. Hsp70 is perhaps the major eukaryotic ribosome-associated chaperone and the first reported to bind cotranslationally to nascent chains. However, little is known about the underlying principles and function of this interaction. Here, we use a sensitive and global approach to define the cotranslational substrate specificity of the yeast Hsp70 SSB. We find that SSB binds to a subset of nascent polypeptides whose intrinsic properties and slow translation rates hinder efficient cotranslational folding. The SSB-ribosome cycle and substrate recognition is modulated by its ribosome-bound cochaperone, RAC. Deletion of SSB leads to widespread aggregation of newly synthesized polypeptides. Thus, cotranslationally acting Hsp70 meets the challenge of folding the eukaryotic proteome by stabilizing its longer, more slowly translated, and aggregation-prone nascent polypeptides.

Defining the specificity of cotranslationally acting chaperones by systematic analysis of mRNAs associated with ribosome-nascent chain complexes.

Polypeptides exiting the ribosome must fold and assemble in the crowded environment of the cell. Chaperones and other protein homeostasis factors interact with newly translated polypeptides to facilitate their folding and correct localization. Despite the extensive efforts, little is known about the specificity of the chaperones and other factors that bind nascent polypeptides. To address this question we present an approach that systematically identifies cotranslational chaperone substrates through the mRNAs associated with ribosome-nascent chain-chaperone complexes. We here focused on two Saccharomyces cerevisiae chaperones: the Signal Recognition Particle (SRP), which acts cotranslationally to target proteins to the ER, and the Nascent chain Associated Complex (NAC), whose function has been elusive. Our results provide new insights into SRP selectivity and reveal that NAC is a general cotranslational chaperone. We found surprising differential substrate specificity for the three subunits of NAC, which appear to recognize distinct features within nascent chains. Our results also revealed a partial overlap between the sets of nascent polypeptides that interact with NAC and SRP, respectively, and showed that NAC modulates SRP specificity and fidelity in vivo. These findings give us new insight into the dynamic interplay of chaperones acting on nascent chains. The strategy we used should be generally applicable to mapping the specificity, interplay, and dynamics of the cotranslational protein homeostasis network.

Local slowdown of translation by nonoptimal codons promotes nascent-chain recognition by SRP in vivo

The genetic code allows most amino acids a choice of optimal and nonoptimal codons. We report that synonymous codon choice is tuned to promote interaction of nascent polypeptides with the signal recognition particle (SRP), which assists in protein translocation across membranes. Cotranslational recognition by the SRP in vivo is enhanced when mRNAs contain nonoptimal codon clusters 35–40 codons downstream of the SRP-binding site, the distance that spans the ribosomal polypeptide exit tunnel. A local translation slowdown upon ribosomal exit of SRP-binding elements in mRNAs containing these nonoptimal codon clusters is supported experimentally by ribosome profiling analyses in yeast. Modulation of local elongation rates through codon choice appears to kinetically enhance recognition by ribosome-associated factors. We propose that cotranslational regulation of nascent-chain fate may be a general constraint shaping codon usage in the genome.

Interplay between chaperones and protein disorder promotes the evolution of protein networks.

Evolution is driven by mutations, which lead to new protein functions but come at a cost to protein stability. Non-conservative substitutions are of interest in this regard because they may most profoundly affect both function and stability. Accordingly, organisms must balance the benefit of accepting advantageous substitutions with the possible cost of deleterious effects on protein folding and stability. We here examine factors that systematically promote non-conservative mutations at the proteome level. Intrinsically disordered regions in proteins play pivotal roles in protein interactions, but many questions regarding their evolution remain unanswered. Similarly, whether and how molecular chaperones, which have been shown to buffer destabilizing mutations in individual proteins, generally provide robustness during proteome evolution remains unclear. To this end, we introduce an evolutionary parameter λ that directly estimates the rate of non-conservative substitutions. Our analysis of λ in Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens sequences reveals how co- and post-translationally acting chaperones differentially promote non-conservative substitutions in their substrates, likely through buffering of their destabilizing effects. We further find that λ serves well to quantify the evolution of intrinsically disordered proteins even though the unstructured, thus generally variable regions in proteins are often flanked by very conserved sequences. Crucially, we show that both intrinsically disordered proteins and highly re-wired proteins in protein interaction networks, which have evolved new interactions and functions, exhibit a higher λ at the expense of enhanced chaperone assistance. Our findings thus highlight an intricate interplay of molecular chaperones and protein disorder in the evolvability of protein networks. Our results illuminate the role of chaperones in enabling protein evolution, and underline the importance of the cellular context and integrated approaches for understanding proteome evolution. We feel that the development of λ may be a valuable addition to the toolbox applied to understand the molecular basis of evolution.

Improvement of the memory function of a mutual repression network in a stochastic environment by negative autoregulation

Background Cellular memory is a ubiquitous function of biological systems. By generating a sustained response to a transient inductive stimulus, often due to bistability, memory is central to the robust control of many important biological processes. However, our understanding of the origins of cellular memory remains incomplete. Stochastic fluctuations that are inherent to most biological systems have been shown to hamper memory function. Yet, how stochasticity changes the behavior of genetic circuits is generally not clear from a deterministic analysis of the network alone. Here, we apply deterministic rate equations, stochastic simulations, and theoretical analyses of Fokker-Planck equations to investigate how intrinsic noise affects the memory function in a mutual repression network. Results We find that the addition of negative autoregulation improves the persistence of memory in a small gene regulatory network by reducing stochastic fluctuations. Our theoretical analyses reveal that this improved memory function stems from an increased stability of the steady states of the system. Moreover, we show how the tuning of critical network parameters can further enhance memory. Conclusions Our work illuminates the power of stochastic and theoretical approaches to understanding biological circuits, and the importance of considering stochasticity to designing synthetic circuits with memory function.Cellular memory is a ubiquitous function of biological systems. By generating a sustained response to a transient inductive stimulus, often due to bistability, memory is central to the robust control of many important biological functions. However, our understanding of the mechanistic basis of cellular memory remains incomplete. Specifically, stochastic fluctuations that are inherent to most biological systems have been shown to hamper memory function. Yet, how stochasticity changes the behavior of genetic circuits is generally not clear from a deterministic analysis of the network alone. Here, we apply deterministic, stochastic, and theoretical analyses to investigate how intrinsic noise affects the memory function in a mutual repression network. We find that the addition of negative autoregulation improves the persistence of memory by reducing stochastic fluctuations. Our theoretical analyses reveal that this improved memory function stems from an increased stability of the steady states of the system. Moreover, we show how the tuning of critical network parameters can further enhance memory. Our work highlights the power of stochastic and theoretical approaches to understanding biological circuits, and the importance of considering stochasticity to designing synthetic circuits with memory function.

Coping with stress by regulating tRNAs

Codon usage regulates translation in response to stress conditions (Torrent et al., in 4 September 2018 issue). Stress conditions curtail the energetically costly process of messenger RNA translation. In this issue of Science Signaling, Torrent et al. report key evidence for a direct link between codon usage and translation regulation in response to stress.