Biology subjects

Akiyama, Y.

Publications and source records attributed to Akiyama, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Structural and functional insights into multiple BAM-bound conformations of BepA enabling substrate triage at the outer membrane

The outer membrane (OM) of Gram-negative bacteria acts as a selective permeability barrier against toxic compounds, and for this function, requires proper assembly of outer membrane proteins (OMPs) by the {beta}-barrel assembly machinery (BAM) complex. A periplasmic metalloprotease BepA promotes maturation of LptD, an essential OMP, while degrades LptD intermediates aberrantly stalled at BAM. However, how BepA switches between these functions remains unclear. Here, we report cryo-EM structures of BAM- BepA complexes that capture multiple BepA conformations. In vivo crosslinking and cysteine-accessibility analyses show that possible regulatory elements, 6- and 9-loops that cover the proteolytic active site, can assume open conformations in living cells. Functional analyses reveal that 6-loop opening supports substrate interaction, degradation, and membrane association, whereas 9-loop opening is required for proteolytic activation and stabilizes BAM association. These findings provide insights into how distinct loop rearrangements regulate BepA-mediated substrate triage at BAM.

molecular biology↗

bioRxiv2026

Ribonuclease L Regulates Antiviral Responsiveness through Cleavage of XBP1 mRNA

During viral infection, viral replication perturbs endoplasmic reticulum (ER) homeostasis and triggers the unfolded protein response (UPR). XBP1s, a transcription factor generated by one branch of the UPR, is known to potentiate both innate and adaptive immunity, but its role in antiviral responses remains incompletely understood beyond its ability to augment type I interferon (IFN) mRNA induction. Here, we show that XBP1s positively regulates the RIG-I-like receptors (RLRs), ribonuclease L (RNase L), and protein kinase R (PKR) pathways, indicating that it enhances all three major antiviral response pathways. We further show that RNase L activation rapidly decreases XBP1 mRNA levels in an RNase activity-dependent manner, leading to a prompt reduction in XBP1s expression. Consistent with this, RNase L deletion significantly increased both thapsigargin-mediated XBP1s induction and XBP1s expression following Japan encephalitis virus infection. Poly(I:C)-induced IFNB mRNA expression was significantly enhanced in RNase L-knockout cells. This enhancement was completely abolished by RNase L reconstitution. XBP1 knockdown also significantly attenuated IFNB mRNA expression in RNase L-knockout cells. These findings suggest a negative-feedback loop in which RNase L suppresses XBP1s, thereby fine-tuning antiviral responsiveness during viral infection. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/713401v1_ufig1.gif" ALT="Figure 1000"> View larger version (19K): org.highwire.dtl.DTLVardef@112d312org.highwire.dtl.DTLVardef@df79a9org.highwire.dtl.DTLVardef@1ac571borg.highwire.dtl.DTLVardef@18ac610_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2026

Respiratory suppression enhances voluntary control of human action

Athletes often regulate their breathing to optimize motor performance, suggesting a close link between respiration and movement control. Previous studies have shown that respiration modulates neuronal oscillations and influences behavior. However, how respiratory control directly affects motor behavior remains unclear. Here, we demonstrate that breath holding during the preparatory period facilitates voluntary movement. We examined respiratory patterns while participants performed two types of eye movement tasks: pro-saccade and anti-saccade tasks. In the anti-saccade task, participants were required to suppress a reflexive saccade toward a visual target and instead generate a voluntary saccade in the opposite direction. To assess whether motivation modulates respiratory control, the tasks were conducted under two motivational conditions. Most participants suppressed their breath during the anticipatory period preceding saccade initiation, regardless of task type, and this tendency was more pronounced under high motivation. In the anti-saccade task, stronger respiratory adjustments were associated with shorter reaction times, whereas no such relationship was observed in the pro-saccade task. Moreover, intentional breath holding during the preparatory period selectively reduced reaction times in the anti-saccade task. These findings indicate that individuals spontaneously hold their breath to facilitate voluntary actions in highly motivated situations, and that this effect can be reproduced through intentional breath holding. We propose that anticipatory breath holding may play a functional role in proactively modulating neural processes underlying voluntary movement control.

neuroscience↗

bioRxiv2025

COFFEE-PRESC: A fast pre-screening method using compound retrieval by pairwise positional relationship of representative fragments

Protein-ligand docking is one of the most widely used methods in structure-based virtual screening in the early stages of drug discovery. Its calculations require approximately one minute per compound, making exhaustive evaluation of ultra-large libraries containing billions of molecules computationally impractical. In this study, we propose COFFEE-PRESC (COmpound Filtering by Fragment pair-based Efficient Evaluation for PRE-SCreening), a fast, fragment-based pre-screening method. COFFEE-PRESC first docks fragments in a pre-constructed fragment set to the target protein and enumerates multiple favorable protein-fragment docking poses and then pairs them to consider pairwise positional relationship. The fragment set is composed of a small number of representative fragments that exhibit high similarity to many other fragments, enabling coverage of a large and diverse chemical space. Compounds that contain stuructures similar to fragment pairs are then retrieved through similarity-based searches. This retrieval methodology guarantees that the mutual positional relationship of the two matched fragments does not spatially collide. Finally, the retrieved compounds are evaluated using docking scores of the representative fragments and similarity values between the representative and individual fragments matched in the compound retrieval process. COFFEE-PRESC was 32-fold faster while higher accuracy than Spresso, a existing pre-screening tool, highlighting its potential for application to ultra-large compound library screening. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/692874v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@c9a5eborg.highwire.dtl.DTLVardef@abeddcorg.highwire.dtl.DTLVardef@18d0bfdorg.highwire.dtl.DTLVardef@10e1e33_HPS_FORMAT_FIGEXP M_FIG TOC Graphic C_FIG

bioinformatics↗

bioRxiv2025

Hit or Miss: Understanding Emergence and Absence of Homo-oligomeric Contacts in Protein Language Models

Many proteins function not as isolated molecules but as symmetrical assemblies of identical subunits, from ion channels that gate cellular signals to metabolic enzymes that catalyze lifes essential reactions. Here, we reveal that single-sequence protein language models (pLMs), trained solely on individual protein sequences, implicitly learn the interface contacts of homo-oligomeric assemblies. As models grow larger, their ability to predict inter-subunit contacts continues to improve, whereas the accuracy for single-chain predictions shows only minimal gains. The largest ESM2 model can accurately distinguish genuine biological interfaces from crystallographic artifacts. MSA Pairformer and ESM2-15B perform comparably when broad sets of homologs are used, but restricting alignments to closer evolutionary neighbors reveals a clear difference: MSA Pairformer reaches an interface contact recovery rate of 0.44 compared with 0.33 for ESM2-15B. We hypothesized that one contributing factor is how models implicitly cluster homologous proteins. Comparing evolutionary constraints extracted from pLMs, we find correlation between homologs decrease as model size increases, consistent with larger models partitioning families into finer-grained subclusters and better separating distinct oligomeric interfaces. When models fail to detect known interfaces, these discrepancies may reflect annotation errors, proteins that adopt multiple assembly conformations, or intrinsic model limitations. Overall, our findings show that statistical patterns learned by pLMs encode key aspects of homo-oligomeric assembly organization and provide a basis for understanding how such interfaces diversify across evolution, even though structure is conserved over large evolutionary distances, oligomeric assembly may not be.

biophysics↗

bioRxiv2025

Scaling down protein language modeling with MSA Pairformer

Recent efforts in protein language modeling have focused on scaling single-sequence models and their training data, requiring vast compute resources that limit accessibility. Although models that use multiple sequence alignments (MSA), such as MSA Transformer, offer parameter-efficient alternatives by extracting evolutionary information directly from homologous sequences rather than storing it in parameters, they generally underperform compared to single-sequence-based language due to memory inefficiencies that limit the number of sequences and averaging evolutionary signals across the MSA. We address these challenges with MSA Pairformer, a 111M parameter memory-efficient MSA-based protein language model that extracts evolutionary signals most relevant to a query sequence through bi-directional updates of sequence and pairwise representations. MSA Pairformer achieves state-of-the-art performance in unsupervised contact prediction, outperforming ESM2-15B by 6% points while using two orders of magnitude fewer parameters. In predicting contacts at protein-protein interfaces, MSA Pair-former substantially outperforms all methods with a 24% point increase over MSA Transformer. Unlike single-sequence models that deteriorate in variant effect prediction as they scale, MSA Pairformer maintains strong performance in both tasks. Ablation studies reveal triangle operations remove indirect correlations, and unlike MSA Transformer, MSA Pairformer does not hallucinate contacts after removing covariance, enabling reliable screening of interacting sequence pairs. Overall, our work presents an alternative to the current scaling paradigm in protein language modeling, enabling efficient adaptation to rapidly expanding sequence databases and opening new directions for biological discovery.

biophysics↗

bioRxiv2025

Protocol for Membrane Permeability Prediction of Cyclic Peptides using Descriptors Obtained from Extended Ensemble Molecular Dynamics Simulations and Chemical Structures

Improving membrane permeability is crucial in cyclic peptide drug discovery. Although the approach based on molecular dynamics (MD) simulation is widely used, it is computationally expensive. Alternatively, machine learning can predict membrane permeability at negligible cost, but it requires a larger dataset. There are only 7991 experimental values of membrane permeability available at the newly developed database. Another challenge in predicting membrane permeability using machine learning arises from the unique stable conformation of each cyclic peptide, which is strongly related to membrane permeability but difficult to predict from chemical structure. Therefore, we developed a machine learning protocol using 3D descriptors obtained from MD simulations in addition to 2D descriptors obtained from chemical structure of cyclic peptides, respectively, to generate a universal model with a realistic computational cost. We targeted 252 peptides across four datasets and, to calculate their 3D descriptors, predicted their conformation outside the membrane, at the water/membrane interface, and in the membrane by MD simulations based on the replica exchange with solute tempering/replica exchange umbrella sampling method using 16 replicas. For machine learning, six different algorithms were used, ranging from simple methods such as ridge regression to more sophisticated methods such as XGBoost. The best prediction performance was obtained using XGBoost, with a Pearsons correlation coefficient R = 0.77 and root mean square error (RMSE) = 0.62. The important descriptors included those that describe the hydrophilicity and hydrophobicity of the peptide, conformational differences between inside and outside the membrane, and the degree of freedom of the peptide. We confirm the models ability to predict the membrane permeability of peptides that differ in chemical structure from the training data by predicting the external data consisting of 24 peptides and obtained R = 0.76, RMSE = 1.14. Furthermore, we extracted one of the four datasets of the training data, re-trained the model, and performed the prediction of the permeability coefficients of the extracted dataset. The results showed the models generic nature with R = 0.61 and RMSE = 0.74, when using position-specific (PS) 3D, and 2D descriptors. In such situations descriptors based on conformations obtained from MD are essential for the prediction.

biophysics↗

bioRxiv2025

Sustained visual signals in the primate cerebellar dentate nucleus drive associative learning

A number of studies have suggested that the cerebellum has cognitive functions; however, the underlying neuronal mechanisms remain unclear. In this study, we demonstrated that sustained visual signals in the cerebellar dentate nucleus represent the visuomotor associative information. We recorded neural activity from the dentate nucleus when monkeys performed a learning task involving the association between visual objects and saccade directions. We found that sustained visual activity was greater in the region during learning than during memory retrieval. This enhancement disappeared under the uncertain reward condition, wherein the monkey did not perform the heuristic learning strategy. Furthermore, sustained visual signals changed the response to visual objects depending on the associated saccade direction. This direction selectivity was positively correlated with modulation during learning. These results suggest that sustained visual signals in the dentate nucleus reflect learning motivation and drive learning by increasing the strength of discrimination among visual objects.

physiology↗

bioRxiv2025

Cleavage cascade of the sigma regulator FecR orchestrates TonB-dependent signal transduction

TonB-dependent signal transduction is a versatile mechanism observed in gram-negative bacteria, integrating energy-dependent substrate transport with signal relay. In Escherichia coli, the TonB-ExbBD motor complex energizes the TonB-dependent transporter FecA, facilitating ferric citrate import. FecA also functions as a sensor, transmitting signals to the cytoplasmic membrane protein FecR. We previously demonstrated that FecR undergoes a three-step cleavage process, culminating in the activation of the cytoplasmic sigma factor FecI, which drives fec gene transcription. Here, we describe the complete mechanism of FecR cleavage-mediated ferric citrate signaling involving FecA and TonB. The cleavage cascade begins with FecR autoproteolysis prior to membrane integration. The soluble C-terminal domain (CTD) fragment of FecR is co-translocated with the N-terminal domain (NTD) fragment through a Tat system-mediated process. In the periplasm, the interaction between the CTD and NTD fragments prevents further cleavage. This inhibition is lifted by TonB-mediated motor function, which releases the CTD, allowing the cleavage cascade to proceed. This process is essential for ferric citrate signal-induced activation of fec gene expression. Our findings reveal that the regulation of FecR cleavage, relying on the TonB-FecA axis, plays a central role in bacterial response to ferric citrate signals. Significance StatementScarcity of iron, an essential element for life, has driven bacteria to evolve intricate acquisition systems, yet the molecular basis of their signal transduction mechanisms remains elusive. Unlike conventional pathways, iron transport systems employ outer membrane receptors that mediate signal transduction across both the outer and cytoplasmic membranes, powered by TonB. Using the Escherichia coli Fec system, we uncovered the mechanism by which FecRs cleavage cascade orchestrates ferric citrate signaling through TonB-mediated energy transfer. These findings shed light on similar mechanisms in gram-negative bacteria and have significant implications for understanding bacterial adaptation and pathogenesis.

immunology↗

bioRxiv2024

Repurposing tRNA isodecoders for non-canonical functions via tRNA cleavage

Transfer RNAs (tRNAs) are the key adaptor molecules aiding protein synthesis. Hundreds of tRNA genes are found in the human genome but the biological significance of this genetic excess is still enigmatic. The tRNA repertoires are variable between tissues and cells as well as during development. Such variations can only be partially explained by the correlation to the physiological needs in protein production, e.g. by changes in the expression of tRNA isoacceptor sets (tRNAs charged with the same amino acid but bearing different anticodons). However, changes in the expression levels of individual isodecoders (tRNAs with the same anticodon) are less understood. Besides canonical functions in mRNA translation, tRNAs are implicated in non-canonical functions unrelated to protein synthesis. tRNAs are rich source of small non-protein coding RNAs called tRNA-derived RNAs (tDRs), which include tRNA-derived stress-induced RNAs (tiRNAs) formed in response to stress. Here, we show that tiRNAs derived from isodecoders different in a single nucleotide can also differ in their activities. Specifically, we show that isodecoder sets for tRNAHis-GTG, tRNAGly-GCC and tRNACys-GCA are cleaved by ribonucleases to yield 5-tiRNAs showing differential activity towards mRNA reporter translation. Our data propose a model where cleavage repurposes specific tRNA isodecoders for non-canonical functions. Significance StatementThe human genome encodes hundreds of transfer RNA (tRNA) genes to decode 61 codons. The basis for such genetic redundancy is unclear but the increase in the number of tRNA genes goes in concert with the complexity of an organism. While changes in the expression of isoacceptor tRNA pools can reflect adaptation to demanding protein synthesis needs and/or codon usage, the variations in the expression of the individual tRNA isodecoders are documented but poorly understood. Such expression variations are hypothesized to contribute to non-canonical tRNA functions, yet physiological relevance remains ambiguous. We report here that specific tRNA isodecoders can be functionally repurposed through cleavage that produces tRNA-derived RNAs (tDRs). The repurposing employs nucleotide variations in isodecoders leading to the production of distinct sets of tDRs with variable bioactivities.

molecular biology↗

bioRxiv2023

CycPeptMP: Enhancing Membrane Permeability Prediction of Cyclic Peptides with Multi-Level Molecular Features and Data Augmentation

Cyclic peptides are versatile therapeutic agents with many excellent properties, such as high binding affinity, minimal toxicity, and the potential to engage challenging protein targets. However, the pharmaceutical utilities of cyclic peptides are limited by their low membrane permeability--an essential indicator of oral bioavailability and intracellular targeting. Current machine learning-based models of cyclic peptide permeability show variable performance due to the limitations of experimental data. Furthermore, these methods use features derived from the whole molecule which are used to predict small molecules and ignore the unique structural properties of cyclic peptides. This study presents CycPeptMP: an accurate and efficient method for predicting the membrane permeability of cyclic peptides. We designed features for cyclic peptides at the atom-, monomer-, and peptide-levels, and seamlessly integrated these into a fusion model using state-of-the-art deep learning technology. Using the latest data, we applied various data augmentation techniques to enhance model training efficiency. The fusion model exhibited excellent prediction performance, with root mean squared error of 0.503 and correlation coefficient of 0.883. Ablation studies demonstrated that all feature levels were essential for predicting membrane permeability and confirmed the effectiveness of augmentation to improve prediction accuracy. A comparison with a molecular dynamics-based method showed that CycPeptMP accurately predicted the peptide permeability, which is otherwise difficult to predict using simulations.

bioinformatics↗

bioRxiv2023

Regulating Cell Orientation with a Femtosecond Laser-Induced Macro Stripe Design on Metallic Culture Surfaces

Controlling cell orientation is paramount in bioengineering processes. While several surface modification techniques have emerged to guide cell alignment, they often involve complex, repetitive procedures for each experiment. A streamlined approach for cell orientation is thus necessary. In this study, we present a reusable metallic culture surface that induces an anisotropic cell orientation, attributed to its unique geometric morphology. By employing a femtosecond laser, periodic nanostructures were produced on the metallic culture surface, leading to a distinctive macro-stripe design composed of both laser-treated and mirrored areas. Myoblast cells cultured on this surface displayed a pronounced orientation. Initial random cell adherence was followed by migration towards the mirror surface, culminating in the desired orientation. This shift can be credited to the mirrored sections offering superior cell adhesion and reduced wettability compared to the laser-treated sections. This innovative culture surface holds significant potential for advancing bioengineering endeavors, especially in the realm of tissue engineering.

bioengineering↗

bioRxiv2022

Noninvasive method for monitoring breathing patterns in monkeys

Respiration is strongly linked to internal states such as arousal, emotion, and even cognitive processes and provides objective biological information to estimate these states in humans and animals. However, the measurement of respiration has not been established in macaque monkeys that have been widely used as model animals for understanding various higher brain functions. In the present study, we developed a method to monitor the respiration of behaving monkeys. We first measured the temperature of their nasal breathing, which changes between inspiration and expiration phases, in an anesthetized condition and estimated the respiration pattern. We compared the estimated pattern with that obtained by a conventional chest band method that has been used in humans and applies to anesthetized, but not behaving, monkeys. These respiration patterns matched well, suggesting that the measurement of nasal air temperature can be used to monitor the respiration of monkeys. Furthermore, we confirmed that the respiration frequency in behaving monkeys monitored by the measurement of nasal air temperature was not affected by the orofacial movement of licking to obtain the liquid reward. We next examined the frequency of respiration when they listened to music or white noise. The respiratory frequency was higher when the monkeys listened to music than the noise. This result is consistent with a phenomenon in humans and indicates the accuracy of our monitoring method. These data suggest that the measurement of nasal air temperature enables us to monitor the respiration of behaving monkeys and thereby estimate their internal states. Significance StatementWhile respiration is linked with internal processing, such as emotional and cognitive states, methods have not been established for physiological research on monkeys. We developed a novel method that obtained respiration signals by measuring the nasal air temperatures of behaving monkeys. Our method was able to continuously track the respiration pattern without distortions evoked by orofacial movements to lick the liquid reward. The respiratory frequency increased while listening to music than when listening to white noise for all monkeys. These results demonstrate that nasal air temperature measurements can be used to monitor the respiration patterns of aroused monkeys, allowing us to understand their internal state. This will be useful for investigating the underlying neuronal mechanism of neuropsychiatric disorders using monkeys.

neuroscience↗

bioRxiv2022

Cytoplasmic processing of human transfer RNAs

Biogenesis of different classes of eukaryotic RNAs proceeds via different pathways that require strict spatiotemporal resolution. The intracellular organization has evolved to provide order for RNA processing to coordinate different maturation steps with specific enzymatic reaction. In higher eukaryotes, processing of transfer RNAs (tRNAs) is postulated to be almost entirely intranuclear, while in lower eukaryotes like yeast, tRNA maturation is both nuclear and cytoplasmic. Here, we show that tRNA processing is largely cytosolic event in human cells. After transcription, unprocessed precursors of tRNAs (pre-tRNAs) bound by La protein are exported from the nucleus into the cytoplasm. Using cell fractionation analysis and pre-tRNA-specific fluorescence in situ hybridization (FISH) protocol, we show tRNA splicing/ligation and end-processing takes place in the cytoplasm where majority of processing enzymes is also located. We propose here a model where processing of intron-less and intron-containing pre-tRNAs is cytoplasmic similarly to the observed in lower eukaryotes, although tRNA splicing precedes 5- and 3-end processing in human cells unlike in yeast.

molecular biology↗

bioRxiv2022

Integrative Analysis of Checkpoint Blockade Response in Advanced Non-Small Cell Lung Cancer

Anti-PD-1/PD-L1 agents have transformed the treatment landscape of advanced non-small cell lung cancer (NSCLC). While our understanding of the biology underlying immune checkpoint blockade in NSCLC is still incomplete, studies to date have established predictive roles for PD-L1 tumor expression and tumor mutational burden (TMB). To expand our understanding of the molecular features underlying response to checkpoint inhibitors in NSCLC, we describe here the first joint analysis of the Stand Up 2 Cancer - Mark Foundation (SU2C-MARK) Cohort, a resource of whole exome and/or RNA sequencing from 393 patients with NSCLC treated with anti-PD-(L)1 therapy, along with matched clinical response annotation. We identify a number of associations between molecular features and outcome, including: 1) favorable (e.g., ATM altered), and unfavorable (e.g., TERT amplified) genomic subgroups, 2) distinct immune infiltration signatures associated with wound healing (unfavorable) and immune activation (favorable), and 3) a novel de-differentiated tumor-intrinsic subtype characterized by expression of endodermal lineage genes, immune activation, and enhanced response rate. Taken together, results from this cohort extend our understanding of NSCLC-specific predictors, providing a rich set of molecular and immunologic hypotheses with which to further our understanding of the biology of checkpoint blockade in NSCLC.

genomics↗

bioRxiv2022

Mechanistic insights into intramembrane proteolysis by E. coli site-2 protease homolog RseP

Site-2 proteases are a conserved family of intramembrane proteases that cleave transmembrane substrates to regulate signal transduction and maintain proteostasis. Here, we elucidated crystal structures of inhibitor-bound forms of bacterial site-2 proteases including E. coli RseP. Our observations are consistent with a rearrangement of the RseP domains surrounding the active center to expose the substrate-binding site where a conserved electrostatic linkage between the transmembrane and membrane-associated domains mediates the conformational changes, suggesting that RseP has a gating mechanism to regulate substrate entry. Mutational analysis also supports that the substrate transmembrane helix is unwound by strand addition to the intramembrane {beta} sheet and is clamped at the active center for efficient cleavage. Furthermore, this substrate accommodation mechanism appears to be common across distinct intramembrane proteases.

biochemistry↗

bioRxiv2021

tiRNA signaling via stress-regulated vesicle transfer in the hematopoietic niche

Extracellular vesicles transfer complex biologic material between cells, whose role in in-vivo organismal physiology is poorly defined. Here, we demonstrate that osteoblastic cells in the bone marrow elaborate extracellular vesicles that are taken up by hematopoietic progenitor cells in vivo. Genotoxic or infectious stress rapidly increased stromal-derived extracellular vesicle transfer to granulocyte-monocyte progenitors. Stimulating osteoblastic cells with parathyroid hormone or activating its receptor enhanced extracellular vesicle transfer, myeloid recovery post radiation and improved animal survival from Candida sepsis. The extracellular vesicles contained tiRNAs known to modulate protein translation. 5-ti-Pro-CGG-1 was preferentially abundant in osteoblast-derived extracellular vesicles and when transferred to granulocyte macrophage progenitors, increased protein translation, cell proliferation and myeloid differentiation. Therefore, EV-mediated tiRNA transfer provides a stress modulated signaling axis distinct from conventional cytokine-driven stress responses. One sentence summaryStress regulated tiRNA transfer alters hematopoiesis

cell biology↗

bioRxiv2021

Edge strand of Escherichia coli BepA interacts with immature LptD on the β-barrel assembly machine to direct it to on- and off-pathways

The outer membrane (OM) of gram-negative bacteria functions as a selective permeability barrier. Escherichia coli periplasmic Zn-metallopeptidase BepA contributes to the maintenance of OM integrity through its involvement in the biogenesis and degradation of LptD, a {beta}-barrel protein component of the lipopolysaccharide translocon. BepA either promotes the maturation of LptD when it is on the normal assembly pathway (on-pathway) or degrades it when its assembly is compromised (off-pathway). BepA performs these functions probably on the {beta}-barrel assembly machinery (BAM) complex. However, how BepA recognizes and directs an immature LptD to different pathways remains unclear. Here, we explored the interactions among BepA, LptD, and the BAM complex. We found that the interaction of the BepA edge-strand located adjacent to the active site with LptD was crucial not only for proteolysis but also, unexpectedly, for assembly promotion of LptD. Site-directed crosslinking analyses indicated that the unstructured N-terminal half of the {beta}-barrel-forming domain of an immature LptD contacts with the BepA edge-strand. Furthermore, the C-terminal region of the {beta}-barrel-forming domain of the BepA-bound LptD intermediate interacted with a "seam" strand of BamA, suggesting that BepA recognized LptD assembling on the BAM complex. Our findings provide important insights into the functional mechanism of BepA.

biochemistry↗