Biology subjects

Clark, P. L.

Publications and source records attributed to Clark, P. L..

9 recordsLinked to original sources

bioRxiv2026

Autotransporter folding avoids a kinetic trap during vectorial translocation across the bacterial outer membrane

Autotransporter proteins are major virulence factors in Gram-negative pathogens, yet how they fold during secretion remains incompletely understood. A longstanding puzzle is why pertactin folds and is secreted in vivo within minutes but refolds in vitro over hours to days. We introduce BEAM, a multiscale framework that learns slow collective variables from coarse-grained simulations to guide all-atom enhanced sampling. Applied to a C-terminal segment of the pertactin passenger domain from Bordetella pertussis, BEAM achieved four- to six-fold greater conformational coverage than traditional collective-variable-guided adaptive sampling or unbiased molecular dynamics. The resulting free-energy landscape revealed a compact, non-native intermediate accessible in bulk solution but geometrically incompatible with vectorial translocation across the outer membrane. Kinetic simulations show that access to this intermediate slows folding, whereas excluding it produces rapid, in vivo-like kinetics. Together, these results explain how vectorial secretion accelerates pertactin folding by excluding an off-pathway kinetic trap. More broadly, BEAM provides a multiscale strategy for revealing hidden conformational states at atomic resolution.

biophysics↗

bioRxiv2025

Deep Receptor Scanning Reveals General Sequence Constraints on GPCR Biosynthesis

G protein-coupled receptors (GPCRs) mediate a variety of signaling pathways and are the most common pharmacological targets. While advances in structural biochemistry have provided deep functional insights into key receptors, many of the 800+ human GPCRs remain understudied. We introduce a versatile "deep receptor scanning" platform that can be used to experimentally characterize 766 human GPCRs and 174 known GPCR splice variants in parallel. We use this platform to quantitatively characterize the relative abundance of canonical and alternative receptor transcripts, their translational efficiency, and the plasma membrane expression of each receptor in the context of a recombinant pool of HEK293T cells expressing individual GPCRs. We then employ machine learning to identify specific structural features that modulate GPCR expression. This experimental platform and informatic approach are compatible with a variety of assays and can be used to efficiently explore the biochemical and pharmacological properties of the GPCRome.

biochemistry↗

bioRxiv2025

Protein folding success depends on the direction and speed of polypeptide chain appearance

The failure of proteins to fold correctly to their native, functional structures is the molecular basis of many human diseases. Every protein is introduced to the cellular environment from N-to C-terminus as it is synthesized, which can enable the N-terminus to begin folding before the C-terminus appears. Here we show that direction and speed of appearance alone can significantly affect whether a protein will fold to its native structure, versus misfold. This sensitivity demonstrates that folding energy landscapes are sufficiently rugged that conformations adopted by the first portion of the protein to appear can significantly impact subsequent folding steps. Despite high structural similarity, homologous proteins had different sensitivities to vectorial appearance, indicating the native topology is insufficient to determine contours of the energy landscape.

biophysics↗

bioRxiv2024

Discovery of an on-pathway protein folding intermediate illuminates the kinetic competition between folding and misfolding

Our current understanding of protein folding is based predominantly on studies of small (<150 aa) proteins that refold reversibly from a chemically denatured state. As protein length increases, the competition between off-pathway misfolding and on-pathway folding likewise increases, creating a more complex energy landscape. Little is known about how intermediates populated during the folding of larger proteins affect navigation of this more complex landscape. Previously, we reported extremely slow folding rates for the 539 aa {beta}-helical passenger domain of pertactin (P.69T), including conditions that favor the formation of a kinetically trapped, off-pathway partially folded state (PFS). The existence of an on-pathway intermediate for P.69T folding was speculated but its characterization remained elusive. In this work, we exploited the extremely slow kinetics of PFS unfolding to develop a double-jump "denaturant challenge" assay. With this assay, we identified a transient unfolding intermediate, PFS*, that adopts a similar structure to PFS, including C-terminal folded structure and a disordered N-terminus, yet unfolds much more quickly than PFS. Additional experiments revealed that PFS* also functions as an on-pathway intermediate for P.69T folding. Collectively, these results support a two-step, C-to-N-terminal model for P.69T folding: folding initiates in the C-terminus with the rate-limiting formation of the transient on-pathway PFS* intermediate, which sits at the junction of the kinetic competition between folding and misfolding. Notably, processive folding from C-to-N-terminus also occurs during C-to-N-terminal translocation of P.69T across the bacterial outer membrane. These results illuminate the crucial role of kinetics when navigating a complex energy landscape for protein folding.

biophysics↗

bioRxiv2023

A Fit for Purpose Approach to Evaluate Detection of Amino Acid Substitutions in Shotgun Proteomics

Amino acid substitutions (AAS) change a protein from its genome-expected sequence. Accumulation of substitutions in proteins underlie numerous diseases and antibiotic mechanisms. Accurate global detection of substitutions and their frequencies would help characterize these mechanisms. Measurement of AAS using shotgun proteomics is attractive due to its high sensitivity and untargeted acquisition. However, identifying substituted peptide-spectra requires search strategies that extrapolate beyond the genome, which can introduce bias. To characterize this bias, we constructed a "ground-truth" approach using the similarities between the Escherichia coli and Salmonella typhimurium proteomes to effectively model the complexity of distinguishing substitutions from genomic peptides. Shotgun proteomics on combined whole cell lysates from both organisms generated a library representing nearly 100,000 peptide-spectra and 4,161 distinct peptide sequences corresponding to genome-level single AAS with defined stoichiometry. We tested the ability to identify S. typhimurium peptide-spectra using only the E. coli genome in substitution-tolerant database searching. Overall, 64.1% of library peptides were correctly identified. We observed a wide range of identification efficiencies based on the specific AAS, but no inherent bias from stoichiometry of the substitution. Short peptides and substitutions near peptide termini, which require specific diagnostic ions for unambiguous identification, are matched with below-average frequency. We also identified "scissor substitutions" that gain or lose protease cleavage sites. Although scissor substitutions are chemically distinct from the genomic peptide, they had poor identification efficiency. This ground-truth AAS library identifies multiple sources of bias in AAS peptide-spectra identification and sets expectations for the application of shotgun proteomics to testing AAS hypotheses. Significance statementHigh-fidelity decoding of the genome is essential for life. Mistranslation leads to amino acid substitutions, which can disrupt protein folding and function, and impact cell fitness. Detection of mistranslated protein products necessitates robust and non-biased approaches. Proteomics is a promising solution, but identifying non-genomic peptide-spectra is a severe bioinformatics challenge. We created a ground-truth library of substituted amino acid peptides by mixing two closely related bacteria in a single sample. We quantitatively defined the degree to which informatics could correctly distinguish substituted peptides when single-organism databases are present. This approach defines intrinsic and informatics limits in substitution detection in shotgun proteomics and identifies previously overlooked challenges with identifying "scissor substitutions".

bioinformatics↗

bioRxiv2022

Synonymous codon substitutions regulate transcription and translation of an upstream gene

Synonymous codons were originally viewed as interchangeable with no phenotypic consequences. However, over the years a substantial body of evidence has demonstrated that some synonymous substitutions can perturb a variety of gene expression and protein homeostasis mechanisms, including translational efficiency, translational fidelity and co-translational folding of the encoded protein. To date, synonymous codon-derived perturbations have largely focused on effects within a single gene. Here we show that synonymous codon substitutions made far within an E. coli plasmid-encoded protein coding sequence frequently led to significant upregulation of a neighboring, upstream gene. Notably, in four out of nine synonymously recoded sequences, significant upregulation of the upstream gene arose due to cryptic transcription of the anti-sense strand. Surprisingly, cryptic transcription of the upstream gene readily bypassed its native transcriptional repression mechanism. Even more surprisingly, translation of this upstream gene correlates closely with the subset of its mRNA transcribed from the cryptic internal promoter, rather than its total mRNA level. These results suggest that synonymous codons in bacteria may be under selection to both preserve the amino acid sequence of the encoded gene while also avoiding internal sequence elements that significantly perturb transcriptional and translational regulation of neighboring genes.

molecular biology↗

bioRxiv2020

Analysis of computational codon usage models and their association with translationally slow codons

Improved computational modeling of protein translation rates, including better prediction of where translational slowdowns along an mRNA sequence may occur, is critical for understanding co-translational folding. Because codons within a synonymous codon group are translated at different rates, many computational translation models rely on analyzing synonymous codons. Some models rely on genome-wide codon usage bias (CUB), believing that globally rare and common codons are the most informative of slow and fast translation, respectively. Others use the CUB observed only in highly expressed genes, which should be under selective pressure to be translated efficiently (and whose CUB may therefore be more indicative of translation rates). No prior work has analyzed these models for their ability to predict translational slowdowns. Here, we evaluate five models for their association with slowly translated positions as denoted by two independent ribosome footprint (RFP) count experiments from S. cerevisiae, because RFP data is often considered as a "ground truth" for translation rates across mRNA sequences. We show that all five considered models strongly associate with the RFP data and therefore have potential for estimating translational slowdowns. However, we also show that there is a weak correlation between RFP counts for the same genes originating from independent experiments, even when their experimental conditions are similar. This raises concerns about the efficacy of using current RFP experimental data for estimating translation rates and highlights a potential advantage of using computational models to understand translation rates instead.

bioinformatics↗

bioRxiv2019

Synonymous codon substitutions perturb co-translational protein folding and significantly impair cell fitness

In the cell, proteins are synthesized from N- to C-terminus and begin to fold during translation. Co-translational folding mechanisms are therefore linked to elongation rate, which varies as a function of synonymous codon usage. However, synonymous codon substitutions can affect many distinct cellular processes, which has complicated attempts to deconvolve the extent to which synonymous codon usage can promote or frustrate proper protein folding in vivo. Although previous studies have shown that some synonymous changes can lead to different final structures, other substitutions will likely be more subtle, perturbing predominantly the protein folding pathway without radically altering the final structure. Here we show that synonymous codon substitutions encoding a single essential enzyme lead to dramatically slower cell growth. These mutations do not prevent active enzyme formation; instead, they predominantly alter the protein folding mechanism, leading to enhanced degradation in vivo. These results support a model where synonymous codon substitutions can impair cell fitness by significantly perturbing co-translational protein folding mechanisms, despite the chaperoning provided by the cellular protein homeostasis network.\n\nSignificanceMany proteins that are incapable of refolding in vitro nevertheless fold efficiently to their native state in the cell. This suggests that more information than the amino acid sequence is required to properly fold these proteins. Here we show that synonymous mRNA mutations can alter a protein folding mechanism in vivo, leading to changes in cellular fitness. This work demonstrates that synonymous codon selection can play an important role in supporting efficient protein production in vivo.

biochemistry↗

bioRxiv2018

Commonly-used FRET fluorophores promote collapse of an otherwise disordered protein.

The dimensions that unfolded proteins, including intrinsically disordered proteins (IDPs), adopt at low or no denaturant remains controversial. We recently developed an innovative analysis procedure for small-angle X-ray scattering (SAXS) profiles and found that even relatively hydrophobic IDPs remain nearly as expanded as the chemically denatured ensemble, rendering them significantly more expanded than generally inferred using fluorescence resonance energy transfer (FRET) measurements. We show here that fluorophores typical of those employed in FRET can contribute to this discrepancy. Specifically, we find that addition of Alexa488 to a normally expanded IDP causes contraction of its ensemble. In parallel, we also tested the recent suggestion that FRET and SAXS results can be reconciled if, in contrast to homopolymers, the radius of gyration (Rg) of an unfolded protein chain can vary independently from its end-to-end distance (Ree). To do so, we developed an analysis procedure that can accurately extract both Rg and Ree from SAXS profiles even if they are decoupled. Using this procedure, we find that Rg and Ree remain tightly coupled even for heteropolymeric IDPs. We thus conclude that, when combined with improved analysis procedures for both SAXS and FRET, fluorophore-driven interactions are sufficient to explain the preponderance of existing data regarding the nature of polypeptide chains unfolded in the absence of denaturant.

biophysics↗