Biochemical and Genetic Analysis Identify CSLD3 as a beta-1,4-Glucan Synthase That Functions during Plant Cell Wall Synthesis.

In plants, changes in cell size and shape during development fundamentally depend on the ability to synthesize and modify cell wall polysaccharides. The main classes of cell wall polysaccharides produced by terrestrial plants are cellulose, hemicelluloses, and pectins. Members of the cellulose synthase (CESA) and cellulose synthase-like (CSL) families encode glycosyltransferases that synthesize the ß-1,4-linked glycan backbones of cellulose and most hemicellulosic polysaccharides that comprise plant cell walls. Cellulose microfibrils are the major load-bearing component in plant cell walls and are assembled from individual ß-1,4-glucan polymers synthesized by CESA proteins that are organized into multimeric complexes called CESA complexes, in the plant plasma membrane. During distinct modes of polarized cell wall deposition, such as in the tip growth that occurs during the formation of root hairs and pollen tubes or de novo formation of cell plates during plant cytokinesis, newly synthesized cell wall polysaccharides are deposited in a restricted region of the cell. These processes require the activity of members of the CESA-like D subfamily. However, while these CSLD polysaccharide synthases are essential, the nature of the polysaccharides they synthesize has remained elusive. Here, we use a combination of genetic rescue experiments with CSLD-CESA chimeric proteins, in vitro biochemical reconstitution, and supporting computational modeling and simulation, to demonstrate that Arabidopsis (Arabidopsis thaliana) CSLD3 is a UDP-glucose-dependent ß-1,4-glucan synthase that forms protein complexes displaying similar ultrastructural features to those formed by CESA6.

Advantages of a distant cellulase catalytic base.

The inverting glycoside hydrolase Trichoderma reesei (Hypocrea jecorina) Cel6A is a promising candidate for protein engineering for more economical production of biofuels. Until recently, its catalytic mechanism had been uncertain: The best candidate residue to serve as a catalytic base, Asp-175, is farther from the glycosidic cleavage site than in other glycoside hydrolase enzymes. Recent unbiased transition path sampling simulations revealed the hydrolytic mechanism for this more distant base, employing a water wire; however, it is not clear why the enzyme employs a more distant catalytic base, a highly conserved feature among homologs across different kingdoms. In this work, we describe molecular dynamics simulations designed to uncover how a base with a longer side chain, as in a D175E mutant, affects procession and active site alignment in the Michaelis complex. We show that the hydrogen bond network is tuned to the shorter aspartate side chain, and that a longer glutamate side chain inhibits procession as well as being less likely to adopt a catalytically productive conformation. Furthermore, we draw comparisons between the active site in Trichoderma reesei Cel6A and another inverting, processive cellulase to deduce the contribution of the water wire to the overall enzyme function, revealing that the more distant catalytic base enhances product release. Our results can inform efforts in the study and design of enzymes by demonstrating how counterintuitive sacrifices in chemical reactivity can have worthwhile benefits for other steps in the catalytic cycle.

The reaction mechanism of the Ideonella sakaiensis PETase enzyme.

Polyethylene terephthalate (PET), the most abundantly produced polyester plastic, can be depolymerized by the Ideonella sakaiensis PETase enzyme. Based on multiple PETase crystal structures, the reaction has been proposed to proceed via a two-step serine hydrolase mechanism mediated by a serine-histidine-aspartate catalytic triad. To elucidate the multi-step PETase catalytic mechanism, we use transition path sampling and likelihood maximization to identify optimal reaction coordinates for the PETase enzyme. We predict that deacylation is likely rate-limiting, and the reaction coordinates for both steps include elements describing nucleophilic attack, ester bond cleavage, and the "moving-histidine" mechanism. We find that the flexibility of Trp185 promotes the reaction, providing an explanation for decreased activity observed in mutations that restrict Trp185 motion. Overall, this study uses unbiased computational approaches to reveal the detailed reaction mechanism necessary for further engineering of an important class of enzymes for plastics bioconversion.

ATESA: An Automated Aimless Shooting Workflow.

Transition path sampling methods are powerful tools for studying the dynamics of rare events in molecular simulations. However, these methods are generally restricted to experts with the knowledge and resources to properly set up and analyze the often hundreds of thousands of simulations that constitute a complete study. Aimless Transition Ensemble Sampling and Analysis (ATESA) is a new open-source software program written in Python that automates a full transition path sampling workflow based on the aimless shooting algorithm, streamlining the process and reducing the barrier to use for researchers new to this approach. This introduction to ATESA includes a demonstration of a complete transition path sampling process flow for an example reaction, including finding an initial transition state, sampling with aimless shooting, building a reaction coordinate with inertial likelihood maximization, verifying that coordinate with committor analysis, and measuring the reaction energy profile with umbrella sampling. We also describe our implementation of a termination criterion for aimless shooting based on the Godambe information calculated during model building with likelihood maximization as well as a novel approach to constraining simulations to the desired rare event pathway during umbrella sampling.

Umbrella-like Helical Structure of α-Synuclein at the Air-Water Interface Observed with Experimental and Theoretical Sum Frequency Generation Spectroscopy.

The misfolding of α-synuclein (αS) into amyloid aggregates is catalyzed by hydrophobic surfaces and associated with severe brain disorders, such as Parkinson's disease. Despite the important role of interfaces, the three-dimensional structure of αS at the interfaces is still not clear. We report interface-specific sum frequency generation (SFG) experiments of monomeric αS binding to the air-water interface, a model system for the important hydrophobic surfaces. We combine the SFG spectra with calculations of theoretical spectra based on molecular dynamics simulations to show that αS, which is an intrinsically disordered protein in solution, folds into a defined, mostly helical secondary structure at the air-water interface. The binding pose resembles an umbrella shape, where the C-terminus protrudes into the water phase, while the N-terminus and the NAC region span the canopy at the interface. In this binding pose, αS is prone to aggregate, which could explain the catalytic effect of hydrophobic interfaces and air bubbles on αS fibrillation.

Quick and Accurate Estimates of Mutation Effects on Transition-State Stabilization of Enzymes from Molecular Simulations with Restrained Transition States.

Data science and machine learning are revolutionizing enzyme engineering; however, high-throughput simulations for screening large libraries of enzyme variants remain a challenge. Here, we present a novel but highly simple approach to comparing enzyme variants with fully atomistic classical molecular dynamics (MD) simulations on a tractable timescale. Our method greatly simplifies the problem by restricting sampling only to the reaction transition state, and we show that the resulting measurements of transition-state stability are well correlated with experimental activity measurements across two highly distinct enzymes, even for mutations with effects too small to resolve with free energy methods. This method will enable atomistic simulations to achieve sampling coverage for enzyme variant prescreening and machine learning model training on a scale that was previously not possible.

Click-Chemistry-Based Free Azide versus Azido Sugar Detection Enables Rapid In Vivo Screening of Glycosynthase Activity.

Engineering of carbohydrate-active enzymes such as glycosynthases to enable chemoenzymatic synthesis of bespoke oligosaccharides has been limited by the lack of suitable ultrahigh-throughput screening methods capable of robustly detecting either starting substrates or end-products of the glycosidic bond formation reaction. Currently, there are limited screening methods available for rapid and highly sensitive single-cell-based screening of glycosynthase enzymes employing azido sugars as activated donor glycosyl substrates. Here, we report a fluorescence-based approach employing click-chemistry for the selective detection of glycosyl azides as substrates versus free inorganic azides as reaction products that facilitated an ultrahigh-throughput in vivo single-cell-based assay of glycosynthase activity. This assay was developed based on the distinct differences observed in relative fluorescence intensity of the triazole-containing fluorophore product formed during the click-chemistry reaction of organic glycosyl azides versus inorganic azides. This discovery formed the basis for proof of concept validation of a directed evolution methodology for screening and sorting glycosynthase mutants capable of synthesis of targeted fucosylated oligosaccharides. Our screening approach facilitated fluorescence-activated cell sorting of an error-prone polymerase chain reaction-based mutant library of fucosynthases expressed in Escherichia coli to identify several novel mutants that showed increased activity for ß-fucosyl azide-activated donor sugars toward desired acceptor sugars (e.g., pNP-xylose and lactose). Finally, we discuss avenues for improving this proof of concept in vivo assay method to identify better glycosynthase mutants and further demonstrate the broader applicability of this screening methodology for synthesis of bespoke glycans.

Second Generation Nanoporous Silicon Nitride Membranes for High Toxin Clearance and Small Format Hemodialysis.

Conventional hemodialysis (HD) uses floor-standing instruments and bulky dialysis cartridges containing ≈2 m2 of 10 micrometer thick, tortuous-path membranes. Portable and wearable HD systems can improve outcomes for patients with end-stage renal disease by facilitating more frequent, longer dialysis at home, providing more physiological toxin clearance. Developing devices with these benefits requires highly efficient membranes to clear clinically relevant toxins in small formats. Here, the ability of ultrathin (<100 nm) silicon-nitride-based membranes to reduce the membrane area required to clear toxins by orders of magnitude is shown. Advanced fabrication methods are introduced that produce nanoporous silicon nitride membranes (NPN-O) that are two times stronger than the original nanoporous nitride materials (NPN) and feature pore sizes appropriate for middle-weight serum toxin removal. Single-pass benchtop studies with NPN-O (1.4 mm2 ) demonstrate the extraordinary clearance potential of these membranes (105 mL min-1 m-2 ), and their intrinsic hemocompatibility. Results of benchtop studies with nanomembranes, and 4 h dialysis of uremic rats, indicate that NPN-O can reduce the membrane area required for hemodialysis by two orders of magnitude, suggesting the performance and robustness needed to enable small-format hemodialysis, a milestone in the development of small-format hemodialysis systems.

ULTRATHIN SILICON MEMBRANES FOR IMPROVING EXTRACORPOREAL BLOOD THERAPIES.

Extracorporeal blood therapies such as hemodialysis and extracorporeal membrane oxygenation supplement or replace organ function by the exchange of molecules between blood and another fluid across a semi-permeable membrane. Traditionally, these membranes are made of polymers with large surface areas and thicknesses on the scale of microns. Therapeutic gas exchange or toxin cleara nce in these devices occurs predominantly by diffusion, a process that is described by an inverse square law relating a distance to the average time a diffusing particle requires to travel that distance. As such, small changes in membrane thickness or other device dimensions can have significant effects on device performance - and large changes can cause dramatic paradigm shifts. In this work, we discuss the application of ultrathin nanoporous silicon membranes (nanomembranes) with thicknesses on the scale of tens of nanometers to diffusion-mediated medical devices. We discuss the theoretical consequences of nanomembrane medical devices for patients, analyzing several notable benefits such as reduced device size (enabling wearability, for instance) and improved clearance specificity. Special attention is paid to computational and analytical models that describe real experimental behavior, and that in doing so provide insights into the relevant parameters governing the devices.

Analytical and Finite Element Modeling of Nanomembranes for Miniaturized, Continuous Hemodialysis.

Hemodialysis involves large, periodic treatment doses using large-area membranes. If the permeability of dialysis membranes could be increased, it would reduce the necessary dialyzer size and could enable a wearable device that administers a continuous, low dose treatment of chronic kidney disease. This paper explores the application of ultrathin silicon membranes to this purpose, by way of analytical and finite element models of diffusive and convective transport of plasma solutes during hemodialysis, which we show to be predictive of experimental results. A proof-of-concept miniature nanomembrane dialyzer design is then proposed and analytically predicted to clear uremic toxins at near-ideal levels, as measured by several markers of dialysis adequacy. This work suggests the feasibility of miniature nanomembrane-based dialyzers that achieve therapeutic levels of uremic toxin clearance for patients with kidney failure.