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At least 1,189 records · Page 66

Manufacturing Large Membrane Mirrors at Low Cost

Relatively inexpensive processes have been developed for manufacturing lightweight, wide-aperture mirrors that consist mainly of reflectively coated, edge-supported polyimide membranes. The polyimide and other materials in these mirrors can withstand the environment of outer space, and the mirrors have other characteristics that make them attractive for use on Earth as well as in outer space: With respect to the smoothness of their surfaces and the accuracy with which they retain their shapes, these mirrors approach the optical quality of heavier, more expensive conventional mirrors. Unlike conventional mirrors, these mirrors can be stowed compactly and later deployed to their full sizes. In typical cases, deployment would be effected by inflation. Potential terrestrial and outer-space applications for these mirrors include large astronomical telescopes, solar concentrators for generating electric power and thermal power, and microwave reflectors for communication, radar, and short-distance transmission of electric power. The relatively low cost of manufacturing these mirrors stems, in part, from the use of inexpensive tooling. Unlike in the manufacture of conventional mirrors, there is no need for mandrels or molds that have highly precise surface figures and highly polished surfaces. The surface smoothness is an inherent property of a polyimide film. The shaped area of the film is never placed in contact with a mold or mandrel surface: Instead the shape of a mirror is determined by a combination of (1) the shape of a fixture that holds the film around its edge and (2) control of manufacturing- process parameters. In a demonstration of this manufacturing concept, spherical mirrors having aperture diameters of 0.5 and 1.0 m were fabricated from polyimide films having thicknesses ranging from <20 m to 150 m. These mirrors have been found to maintain their preformed shapes following deployment.

FROM↗

Predicting Initial Trans-Membrane Pressure for Optimized Operations in UF Unit Using Random Forest

With the growing scarcity of freshwater, innovative process design mechanisms like Ultra-filtration(UF) units are increasingly gaining attention among water treatment utilities to address the rising demand. Ensuring reliable water production necessitates efficient resource utilization, minimizing downtime in UF systems. Recent advancements in machine learning (ML) have enabled the development of accurate data-driven models for Model Predictive Control (MPC), often requiring minimal prior knowledge of underlying physical processes. In this study, we present predictive regression models based on Random Forest (RF) and Auto-Regressive (AR) approaches to forecast the initial Trans-Membrane Pressure (TMP) for each filtration cycle in data generated by Direct Potable Reuse (DPR) systems. The proposed RF-based model demonstrates superior performance compared to baseline methods, including historical mean, Last Observation Carried Forward (LOCF), and naïve AR models, across various forecasting horizons in terms of root mean square (RMSE) metric. Accurate prediction of initial TMP is critical for optimizing CCRO operations, as it enables the development of robust modelling frameworks that enhance process efficiency and reliability. The demonstrated efficacy of the RF-based approach highlights its potential as a tool for real-time decision-making in water treatment systems, paving the way for advanced process optimization and sustainable water resource management.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗

Methanol tolerance of atomically dispersed single metal site catalysts: mechanistic understanding and high-performance direct methanol fuel cells

Proton-exchange membrane fuel cells (PEMFCs) and direct methanol fuel cells (DMFCs) are promising power sources from portable electronic devices to vehicles. The high-cost issue of these low-temperature fuel cells can be primarily addressed by using platinum-group metal (PGM)-free oxygen reduction reaction (ORR) catalysts, in particular atomically dispersed metal–nitrogen–carbon (M–N–C, M = Fe, Co, Mn). Furthermore, a significant advantage of M–N–C catalysts is their superior methanol tolerance over Pt, which can mitigate the methanol cross-over effect and offer great potential of using a higher concentration of methanol in DMFCs. In this work, we investigated the ORR catalytic properties of M–N–C catalysts in methanol-containing acidic electrolytes via experiments and density functional theory (DFT) calculations. FeN 4 sites demonstrated the highest methanol tolerance ability when compared to metal-free pyridinic N, CoN 4 , and MnN 4 active sites. The methanol adsorption on MN 4 sites is even strengthened when electrode potentials are applied during the ORR. The negative influence of methanol adsorption becomes significant for methanol concentrations higher than 2.0 M. However, the methanol adsorption does not affect the 4e - ORR pathway or chemically destroy the FeN 4 sites. The understanding of the methanol-induced ORR activity loss guides the design of promising M–N–C cathode catalyst in DMFCs. Accordingly, we developed a dual-metal site Fe/Co–N–C catalyst through a combined chemical-doping and adsorption strategy. Instead of generating a possible synergistic effect, the introduced Co atoms in the first doping step act as “scissors” for Zn removal in metal–organic frameworks (MOFs), which is crucial for modifying the porosity of the catalyst and providing more defects for stabilizing the active FeN 4 sites generated in the second adsorption step. The Fe/Co–N–C catalyst significantly improved the ORR catalytic activity and delivered remarkably enhanced peak power densities (i.e., 502 and 135 mW cm -2 ) under H 2 –air and methanol–air conditions, respectively, representing the best performance for both types of fuel cells. Notably, the fundamental understanding of methanol tolerance, along with the encouraging DMFC performance, will open an avenue for the potential application of atomically dispersed M–N–C catalysts in other direct alcohol or ammonia fuel cells.

25 ENERGY STORAGE↗

Reversible Reactions, Mesh Size, and Segmental Dynamics Control Penetrant Diffusion in Ethylene Vitrimers

The diffusion of two aromatic dyes with nearly identical sizes was measured in ethylene vitrimers with precise linker lengths and borate ester cross-links using fluorescence recovery after photobleaching (FRAP). One dye possessed a reactive hydroxyl group, while the second was inert. The reaction of the hydroxyl group with the network is slow relative to the hopping times of the dye, resulting in a large slowdown by a factor of 50 for a reactive probe molecule. A kinetic model was fit to the fluorescence intensity data to determine rate constants for the reversible reaction of the dye from the network, which confirms the role of slow reaction kinetics. A second network cross-linker was also investigated with a substituted boronic ester showing ∼10,000 times faster exchange kinetics. In this system, the two dyes show the same diffusion coefficient, as the reaction is no longer the rate-limiting step. The role of dense meshes on small and large dyes is also discussed in the context of the existing theories. Finally, these results highlight the potential of dynamic networks to control penetrant transport through synergistic effects of the mesh size, dynamic bond kinetics, and penetrant–network interactions.

confinement↗

Development of a Next-Generation Membrane-Integrated Adsorption Processor for CO2 Removal and Compression for Closed-Loop Air Revitalization Systems

The current CO2 removal technology of NASA is very energy intensive and contains many non-optimized subsystems. This paper discusses the concept of a next-generation, membrane integrated, adsorption processor for CO2 removal nd compression in closed-loop air revitalization systems. This processor will use many times less power than NASA's current CO2 removal technology and will be capable of maintaining a lower CO2 concentration in the cabin than that can be achieved by the existing CO2 removal systems. The compact, consolidated, configuration of gas dryer, CO2 separator, and CO2 compressor will allow continuous recycling of humid air in the cabin and supply of compressed CO2 to the reduction unit for oxygen recovery. The device has potential application to the International Space Station and future, long duration, transit, and planetary missions.

Mulloth, Lila↗

Identification of a specific exporter that enables high production of aconitic acid in Aspergillus pseudoterreus

Aconitic acid is an unsaturated tricarboxylic acid that is attractive for its potential use in the manufacture of biodegradable and biocompatible polymers, plasticizers, and surfactants. Previously Aspergillus pseudoterreus was engineered as a platform to produce aconitic acid by deleting the cadA (cis-aconitic acid decarboxylase) gene in the itaconic acid biosynthetic pathway. In this study aconitic acid transporter gene (aexA) was identified using comparative global discovery proteomics analysis between the wild-type and cadA deletion strains. Deletion of aexA almost eliminated aconitic acid secretion, while its overexpression led to a significant increase in aconitic acid production. Transportation of aconitic acid across the plasma membrane is a key limiting step. In vitro proteoliposome transport assay further validated AexA’s function and its substrate specificity. This research provides new approaches to efficiently pinpoint and characterize exporters of fungal organic acids and accelerate the metabolic engineering to improve secretion capability and lower cost for bioproduction.

59 BASIC BIOLOGICAL SCIENCES↗

One-Step Facile Synthesis of High-Activity Nitrogen-Doped PtNiN Oxygen Reduction Catalyst

PtM alloy electrocatalysts (M = Fe, Co, Ni) have been the subject of many investigations aimed at increasing their attractive properties, in particular oxygen reduction reaction (ORR) activity, while reducing total platinum-group-metal content and improving durability. Despite some success, these catalysts still have relatively high Pt content and lack the necessary durability as M metals leach out from the alloys during potential cycling. Previously, we synthesized nitrogen (N)-doped PtMN/C catalysts consisting of thin Pt shells on M nitride cores by a two-step method, which showed higher ORR activity and stability than their PtM counterparts. In the present work, we developed a facile one-step synthesis method, which comprises a single thermal annealing process of the N-doped PtNiN/C alloy. The ORR performance of the one-step synthesized PtNiN/C catalyst is much higher than that of the two-step synthesized PtNiN/C, as revealed by rotating disk electrode measurements. Membrane electrode assembly fuel cell testing demonstrated superb durability and high activity. Formation of Pt monolayer shells on the nitrided (Pt x Ni 1-x ) 4 N cores was confirmed by in situ X-ray absorption spectroscopy. The origins of the enhanced activity and stability of the one-step synthesized PtNiN/C catalyst are elucidated based on density functional theory calculations together with the experimental results.

30 DIRECT ENERGY CONVERSION↗

Molecular determinants of pH sensing in the proton-activated chloride channel

In response to acidic pH, the widely expressed proton-activated chloride (PAC) channel opens and conducts anions across cellular membranes. By doing so, PAC plays an important role in both cellular physiology (endosome acidification) and diseases associated with tissue acidosis (acid-induced cell death). Despite the available structural information, how proton binding in the extracellular domain (ECD) leads to PAC channel opening remains largely unknown. Here, through comprehensive mutagenesis and electrophysiological studies, we identified several critical titratable residues, including two histidine residues (H130 and H131) and an aspartic acid residue (D269) at the distal end of the ECD, together with the previously characterized H98 at the transmembrane domain–ECD interface, as potential pH sensors for human PAC. Mutations of these residues resulted in significant changes in pH sensitivity. Some combined mutants also exhibited large basal PAC channel activities at neutral pH. By combining molecular dynamics simulations with structural and functional analysis, we further found that the β12 strand at the intersubunit interface and the associated “joint region” connecting the upper and lower ECDs allosterically regulate the proton-dependent PAC activation. Our studies suggest a distinct pH-sensing and gating mechanism of this new family of ion channels sensitive to acidic environment.

59 BASIC BIOLOGICAL SCIENCES↗

FCET Solid Oxide Fuel Cell Testing and Development: CRADA 526 [Abstract only]

The purpose of the proposed project is for PNNL to test the performance of prototype solid oxide fuel cells (SOFCs) created by FCET. Such testing will provide FCET with independent performance data that can be communicated to potential clients and/or investors. Additionally, PNNL will collaborate with FCET on design changes to improve fuel cell performance. Intellectual property developed in this way will benefit FCET with improved products to market, and PNNL through royalty revenue. The key technology held by FCET is a process to deposit extremely thin layers of oxide materials, from 10-50 nm in thickness. The range of possible materials that can be deposited with their method is broad, but this project will focus on the yttria-stabilized zirconia (YSZ) electrolytes for SOFCs. Thin, gas tight YSZ membranes have been a long-sought target in SOFC research. The thinner the YSZ, the lower the cell resistance, and the higher performance of the cell (or the lower the operating temperature). 10-50 nm would be a major step change in YSZ thickness from the state of the art. PNNL can team with FCET on future R&D projects and push this technology forward to improve energy efficiency and reduce carbon emissions.

30 DIRECT ENERGY CONVERSION↗

Advances in Computational Approaches for Estimating Passive Permeability in Drug Discovery

Passive permeation of cellular membranes is a key feature of many therapeutics. The relevance of passive permeability spans all biological systems as they all employ biomembranes for compartmentalization. A variety of computational techniques are currently utilized and under active development to facilitate the characterization of passive permeability. These methods include lipophilicity relations, molecular dynamics simulations, and machine learning, which vary in accuracy, complexity, and computational cost. This review briefly introduces the underlying theories, such as the prominent inhomogeneous solubility diffusion model, and covers a number of recent applications. Various machine-learning applications, which have demonstrated good potential for high-volume, data-driven permeability predictions, are also discussed. Due to the confluence of novel computational methods and next-generation exascale computers, we anticipate an exciting future for computationally driven permeability predictions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stability Analysis of Substituted Cobaltocenium [Bis(cyclopentadienyl)cobalt(III)] Employing Chemistry-Informed Neural Networks

Cobaltocenium derivatives are promising components of the anion exchange membranes due to their excellent thermal and alkaline stability under the operating conditions of a fuel cell. Here we present an efficient modeling approach of assessing the chemical stability of substituted cobaltocenium CoCp 2 + based on the computed electronic structure enhanced by machine learning techniques. Within the aqueous environment, the positive charge of the metal cation is balanced by the hydroxide anion through formation of the CoCp 2 + OH¯ complexes, whose dissociation is studied within the implicit solvent employing density functional theory. The data set of about 118 species based on 42 substituent groups characterized by a range of electron- donating (ED) and electron-withdrawing (EW) properties is constructed and analyzed. Given 12 carefully chosen chemistry-informed descriptors of the complexes and relevant fragments, the stability of the complexes is found to strongly correlate with the energies of the highest occupied and lowest unoccupied molecular orbitals, modulated by a switching function of the Hirshfeld charge. The latter is used as a measure of the electron withdrawing-donating character of the substituents. Based on this observation from the conventional regression analysis, two fully connected, feed-forward neural network (FNN) models with different unit structures, called the chemistry-informed (CINN) and the quadratic (QNN) neural networks, are developed. Both models predict the bond dissociation energies of the cobaltocenium complexes with mean relative errors less than 5.40% and average absolute errors less than 0.94 kcal/mol. The results show the potential of QNN to efficiently capture more complex relationships. Here, the concept of incorporating the domain (chemical) knowledge/insight into the neural network structure paves the way to applications of machine learning techniques with small data sets, ultimately leading to better predictive models compared to the conventional regression analysis.

36 MATERIALS SCIENCE↗

Accessing a high‐voltage nonaqueous hybrid flow battery with a sodium‐methylphenothiazine chemistry and a sodium‐ion solid electrolyte

Abstract The development of redox flow batteries (RFBs) with nonaqueous electrolytes offers the possibility of accessing a high cell‐operation voltage (no restrain of hydrogen evolution and oxygen evolution potentials) and a low operation temperature (can be operated below the freezing point of water). Therefore, nonaqueous RFBs have recently garnered increasing attention. However, the cross‐mixing of liquid electrode/electrolyte materials has been plaguing the progress of the nonaqueous RFBs. Herein, we present a crossover‐free, high voltage nonaqueous hybrid flow battery (HFB) with a novel sodium‐methylphenothiazine (MPT) chemistry and a single‐ion solid‐electrolyte separator. The Na‐MPT redox couple delivers a high voltage of ~2.6 V when the cell was operated at a medium current density. A NASICON‐type solid electrolyte membrane (Na 3 Zr 2 Si 2 PO 12 ) could circumvent the crossover of the liquids between the positive and negative electrodes, and meanwhile could maintain a single‐ion (Na + ‐ion) conduction between the two electrodes to sustain the electrochemical reactions. Under such an electrochemical mechanism, the nonaqueous Na‐MPT HFB shows remarkable cycling performance.

Yu, Xingwen↗

Engineered extracellular vesicle mimetics from macrophage promotes hair growth in mice and promotes human hair follicle growth

Recent studies clearly show that cell-derived extracellular vesicles (EVs, including exosomes) can promote hair growth. However, large-scale production of EVs remains a big hurdle. Recently, extracellular vesicle mimetics (EMs) engineered by extrusion through various membranes are emerging as a complementary approach for large-scale production. In this study, to investigate their ability to induce hair growth, we generated macrophage-engineered EMs (MAC-EMs) that activated the human dermal papilla (DP) cells in vitro. MAC-EMs intradermally injected into the skin of C57BL/6 mice were retained for up to 72 h. Microscopy imaging revealed that MAC-EMs were predominately internalized into hair follicles. The MAC-EMs treatment induced hair regrowth in mice and hair shaft elongation in a human hair follicle, suggesting the potential of MAC-EMs as an alternative to EVs to overcome clinical limitation.

60 APPLIED LIFE SCIENCES↗

Electric Power System Technology Options for Lunar Surface Missions

In 2004, the President announced a 'Vision for Space Exploration' that is bold and forward-thinking, yet practical and responsible. The vision explores answers to longstanding questions of importance to science and society and will develop revolutionary technologies and capabilities for the future, while maintaining good stewardship of taxpayer dollars. One crucial technology area enabling all space exploration is electric power systems. In this paper, the author evaluates surface power technology options in order to identify leading candidate technologies that will accomplish lunar design reference mission three (LDRM-3). LDRM-3 mission consists of multiple, 90-day missions to the lunar South Pole with 4-person crews starting in the year 2020. Top-level power requirements included a nominal 50 kW continuous habitat power over a 5-year lifetime with back-up or redundant emergency power provisions and a nominal 2-kW, 2-person unpressurized rover. To help direct NASA's technology investment strategy, this lunar surface power technology evaluation assessed many figures of merit including: current technology readiness levels (TRLs), potential to advance to TRL 6 by 2014, effectiveness of the technology to meet the mission requirements in the specified time, mass, stowed volume, deployed area, complexity, required special ground facilities, safety, reliability/redundancy, strength of industrial base, applicability to other LDRM-3 elements, extensibility to Mars missions, costs, and risks. For the 50-kW habitat module, dozens of nuclear, radioisotope and solar power technologies were down-selected to a nuclear fission heat source with Brayton, Stirling or thermoelectric power conversion options. Preferred energy storage technologies included lithium-ion battery and Proton Exchange Membrane (PEM) Regenerative Fuel Cells (RFC). Several AC and DC power management and distribution architectures and component technologies were defined consistent with the preferred habitat power generation technology option and the overall lunar surface mission. For rover power, more than 20 technology options were down-selected to radioisotope Stirling, liquid lithium-ion battery, PEM RFC, or primary fuel cell options. The author discusses various conclusions that can be drawn from the findings of this surface power technologies evaluation.

Kerslake, Thomas W.↗

Anion Selectivities in Zwitterion Grafted Nanopores: Effect of Zwitterion Architecture

The separation of ions of similar charge is a crucial challenge in many applications, from water treatment to precious metal recovery. Membranes with cross-linked zwitterionic amphiphilic copolymer (ZAC-X) selective layers, which feature self-assembled, zwitterion-lined nanodomains for permeation, offer unique permselectivity between monovalent anions (e.g. $\mathrm{Cl^-}$/$\mathrm{F^-}$). This has motivated studies on the mechanisms of transport and selectivity in this family of materials. In this study, we conducted molecular dynamics simulations of aqueous salt solutions within zwitterion-functionalized nanopores to elucidate the influence of dipole orientation of the ZI ligands on anion diffusivities, partitioning, and permeabilities. Here, our model compares systems with contrasting ZI organization: surface-cation-anion ($\mathrm{S\text{-}ZI^{+}\text{-}ZI^{-}}$, Motif A) and surface-anion-cation ($\mathrm{S\text{-}ZI^{-}\text{-}ZI^{+}}$, Motif B). Our results reveal that Motif A exhibits less pronounced ion pairing due to a spatial separation in the radial profiles of cations and anions. Motif B demonstrates prominent ion pairing for smaller anions owing to their overlap with cation distributions. Further, our potential of mean force profiles reveal that anion partitioning increases with anion size in both ligand motifs, whereas Motif B exhibits significantly higher partitioning selectivity towards larger anions compared to Motif A. Our results for ion diffusivities show that the self-diffusivities of both anions and cations are lower for Motif B compared to Motif A. Such trends in anion partitioning and diffusivities can be explained by differences in the interactions and steric hindrance experienced by the anionic species in Motifs A and B. Finally, our results for anion permselectivity, obtained by combining partitioning and diffusivity, indicate that partitioning trends dominate over diffusivity trends. Consequently, anion permeability increases with anion size, and ligand Motif B yields much higher permselectivity towards larger anions compared to ligand Motif A.

anions↗

Proton Selective Nanoporous Atomically Thin Graphene Membranes for Vanadium Redox Flow Batteries

Angstrom-scale proton-selective pores in atomically thin 2D materials present fundamentally new opportunities for advancing proton exchange membranes (PEMs). Vanadium Redox Flow Batteries (VRFBs) for grid-scale energy storage require PEMs with high areal proton conductance (>1 S cm −2 ) and minimal vanadium ion (VO 2+ ) crossover. However, state-of-the-art Nafion 212 membranes (N212 ≈50 µm thick), suffer from persistent VO 2+ crossover reducing performance and efficiency. Here, a layered PEM is demonstrated, comprising monolayer CVD graphene with Angstrom-scale proton-selective pores introduced via Ar plasma, integrated with an ultra-thin ≈300 nm polybenzimidazole (PBI) layer and sandwiched between two Nafion 211 (25 µm thick) layers. The layered architecture facilitates scalable membrane fabrication by mitigating defects while processing and facile stacking of graphene layers allows stochastic non-selective defect isolation enabling exceptionally low VO 2+ crossover (selectivity (H + areal conductance / VO 2+ permeability) ≈6709 × 10 6 S min cm −4 ), with proton conductance >8 S cm −2 . Systematic transport experiments supported by resistance-based transport modelling elucidate the role of defect size, defect isolation, and sealing, as well as layering/stacking, to enable orders of magnitude (>671× over N212) improvements in selectivity, along with areal proton conductance >8 S cm −2 . This work highlights the potential of atomic-scale proton-selective defect engineering in 2D materials, in conjunction with facile stacking and layering of materials as strategies for scalable, high-performance advances in PEMs for energy, electrochemical, and separation applications beyond VRFBs.

Chaturvedi, Pavan [Vanderbilt Univ., Nashville, TN↗

Crystal structure of the CoV-Y domain of SARS-CoV-2 nonstructural protein 3

Abstract Replication of the coronavirus genome starts with the formation of viral RNA-containing double-membrane vesicles (DMV) following viral entry into the host cell. The multi-domain nonstructural protein 3 (nsp3) is the largest protein encoded by the known coronavirus genome and serves as a central component of the viral replication and transcription machinery. Previous studies demonstrated that the highly-conserved C-terminal region of nsp3 is essential for subcellular membrane rearrangement, yet the underlying mechanisms remain elusive. Here we report the crystal structure of the CoV-Y domain, the most C-terminal domain of the SARS-CoV-2 nsp3, at 2.4 Å-resolution. CoV-Y adopts a previously uncharacterized V-shaped fold featuring three distinct subdomains. Sequence alignment and structure prediction suggest that this fold is likely shared by the CoV-Y domains from closely related nsp3 homologs. NMR-based fragment screening combined with molecular docking identifies surface cavities in CoV-Y for interaction with potential ligands and other nsps. These studies provide the first structural view on a complete nsp3 CoV-Y domain, and the molecular framework for understanding the architecture, assembly and function of the nsp3 C-terminal domains in coronavirus replication. Our work illuminates nsp3 as a potential target for therapeutic interventions to aid in the on-going battle against the COVID-19 pandemic and diseases caused by other coronaviruses.

36 MATERIALS SCIENCE↗

A molecular conveyor belt-associated protein controls the rotational direction of the bacterial type 9 secretion system

ABSTRACT Many bacteria utilize the type 9 secretion system (T9SS) for gliding motility, surface colonization, and pathogenesis. This dual-function motor supports both gliding motility and protein secretion, where rotation of the T9SS plays a central role. Fueled by the energy of the stored proton motive force and transmitted through the torque of membrane-anchored stator units, the rotary T9SS propels an adhesin-coated conveyor belt along the bacterial outer membrane like a molecular snowmobile, thereby enabling gliding motion. However, the mechanisms controlling the rotational direction and gliding motility of T9SS remain elusive. Shedding light on this mechanism, we find that in the gliding bacteriumFlavobacterium johnsoniae, deletion of the C-terminus of the conveyor belt-associated protein GldJ controls and, in fact, reverses the rotational direction of T9SS from counterclockwise (CCW) to clockwise (CW). This suggests that the interface between the conveyor belt-associated protein GldJ and the T9SS ring protein GldK plays an important role in controlling the directionality of T9SS, potentially by modulating its interaction with the stator complex GldLM, which drives motor rotation. Combined with MD simulation of the T9SS stator units GldLM, we suggest a “tri-component gearset” model where GldJ controls the rotational direction of its driver, the T9SS, thus providing adaptive sensory feedback to influence the motility of the gliding bacterium. IMPORTANCE The type 9 secretion system (T9SS) is fundamental to bacterial gliding motility, pathogenesis, and surface colonization. Our findings reveal that the C-terminal region of the conveyor belt-associated protein GldJ functions as a molecular switch which is capable of reversing the rotational direction of T9SS. Through the coordinated actions of the T9SS stator units (akin to a driving motor), the GldK ring (the gear that converts rotational energy into linear movement), and GldJ, this machinery forms a smart conveyor belt system reminiscent of flexible or cognitive mechanical conveyors. Such advanced conveyors can alter their direction to adapt to shifting demands. Here, we show that the bacterial T9SS similarly adjusts its rotational bias based on feedback from the conveyor belt-associated protein GldJ. This dual-role feedback mechanism underscores an evolved, controllable biological snowmobile, offering new avenues for studying how bacteria fine-tune motility in dynamic environments.

Microbiology↗