Carbohydrate-binding module O-mannosylation alters binding selectivity to cellulose and lignin

Improved understanding of the effect of protein glycosylation is expected to provide the foundation for the design of protein glycoengineering strategies. In this study, we examine the impact of O-glycosylation on the binding selectivity of a model Family 1 carbohydrate-binding module (CBM), which has been shown to be one of the primary sub-domains responsible for non-productive lignin binding in multi-modular cellulases. Specifically, we examine the relationship between glycan structure and the binding specificity of the CBM to cellulose and lignin substrates. We find that the glycosylation pattern of the CBM exhibits a strong influence on the binding affinity and the selectivity between both cellulose and lignin. In addition, the large set of binding data collected allows us to examine the relationship between binding affinity and the correlation in motion between pairs of glycosylation sites. Our results suggest that glycoforms displaying highly correlated motion in their glycosylation sites tend to bind cellulose with high affinity and lignin with low affinity. Taken together, this work helps lay the groundwork for future exploitation of glycoengineering as a tool to improve the performance of industrial enzymes.

Improved understanding of the effect of protein glycosylation is expected to provide the foundation for the design of protein glycoengineering strategies.

The cell walls of terrestrial plants primarily comprise the polysaccharides cellulose, hemicellulose, and pectin, as well as the heterogeneous aromatic polymer, lignin. In nature, carbohydrates derived from plant polysaccharides provide a massive carbon and energy source for biomass-degrading fungi, bacteria, and archaea, which together are the primary organisms that recycle plant matter and are a critical component of the global carbon cycle. Across the various environments in which these microbes break down lignocellulose, a few known enzymatic and chemical systems have evolved to deconstruct polysaccharides to soluble sugars.^1–6 These natural systems are, in several cases, being evaluated for industrial use to produce sugars for further conversion into renewable biofuels and chemicals.From an industrial perspective, overcoming biomass recalcitrance to cost-effectively produce soluble intermediates, including sugars for further upgrading remains the main challenge in biomass conversion. Lignin, the evolution of which in planta provided a significant advantage for terrestrial plants to mitigate microbial attack, is now widely recognized as a primary cause of biomass recalcitrance.⁷ Chemical and/or biological processing scenarios of lignocellulose have been evaluated⁸ and several approaches have been scaled to industrial biorefineries to date. Many biomass conversion technologies overcome recalcitrance by partially or wholly removing lignin from biomass using thermochemical pretreatment or fractionation. This approach enables easier polysaccharide access for carbohydrate-active enzymes and/or microbes. There are however, several biomass deconstruction approaches that employ enzymes or microbes with whole, unpretreated biomass.^9,10 In most realistic biomass conversion scenarios wherein enzymes or microbes are used to depolymerize polysaccharides, native or residual lignin remains.^11,12 It is important to note that lignin can bind and sequester carbohydrate-active enzymes, which in turn can affect conversion performance.¹³Therefore, efforts aimed at improving cellulose binding selectivity relative to lignin have emerged as major thrusts in cellulase studies.^14–25 Multiple reports in the past a few years have made exciting new contributions to our collective understanding of how fungal glycoside hydrolases, which are among the most well-characterized cellulolytic enzymes given their importance to cellulosic biofuels production, bind to lignin from various pretreatments.^15,17 Taken together, these studies have demonstrated that the Family 1 carbohydrate-binding modules (CBMs) often found in fungal cellulases are the most relevant sub-domains for non-productive binding to lignin,^15,17,20,26 likely due to the hydrophobic face of these CBMs that is known to be also responsible for cellulose binding (Fig. 1).²⁷Open in a separate windowFig. 1Model of glycosylated CBM binding the surface of a cellulose crystal. Glycans are shown in green with oxygen atoms in red, tyrosines known to be critical to binding shown in purple, and disulfide bonds Cys8–Cys25 and Cys19–Cys35 in yellow.Furthermore, several studies have been published recently using protein engineering of Family 1 CBMs to improve CBM binding selectivity to cellulose with respect to lignin. Of particular note, Strobel et al. screened a large library of point mutations in both the Family 1 CBM and the linker connecting the catalytic domain (CD) and CBM.^21,22 These studies demonstrated that several mutations in the CBM and one in the linker led to improved cellulose binding selectivity compared to lignin. The emerging picture is that the CBM-cellulose interaction, which occurs mainly as a result of stacking between the flat, hydrophobic CBM face (which is decorated with aromatic residues) and the hydrophobic crystal face of cellulose I, is also likely the main driving force in the CBM-lignin interaction given the strong potential for aromatic–aromatic and hydrophobic interactions.Alongside amino acid changes, modification of O-glycosylation has recently emerged as a potential tool in engineering fungal CBMs, which Harrison et al. demonstrated to be O-glycosylated.^28–31 In particular, we have revealed that the O-mannosylation of a Family 1 CBM of Trichoderma reesei cellobiohydrolase I (TrCel7A) can lead to significant enhancements in the binding affinity towards bacterial microcrystalline cellulose (BMCC).^30,32,33 This observation, together with the fact that glycans have the potential to form both hydrophilic and hydrophobic interactions with other molecules, led us to hypothesize that glycosylation may have a unique role in the binding selectivity of Family 1 CBMs to cellulose relative to lignin and as such, glycoengineering may be exploited to improve the industrial performance of these enzymes. To test this hypothesis, in the present study, we systematically probed the effects of glycosylation on CBM binding affinity for a variety of lignocellulose-derived cellulose and lignin substrates and investigated routes to computationally predict the binding properties of different glycosylated CBMs.     

交替三线性分解算法与反相高效液相-二极管阵列检测方法相结合同时测定苯二酚的位置异构体

 利用交替三线性分解算法与反相高效液相 二极管阵列检测 (RP HPLC DAD)相结合 ,在洗脱时间为1 0 86min～ 1 399min(间隔 1 / 1 50min)、紫外吸收波长为 2 68nm～ 2 98nm(间隔 1nm)时对苯二酚位置异构体的重叠及光谱体系进行了分辨研究。分辨结果与实际结果一致。同时测定了水溶液中共存的邻苯二酚、间苯二酚和对苯二酚的含量 ,回收率分别为 (1 0 0 1± 1 0 ) % ,(99 4± 1 4) % ,(1 0 0 5± 1 7) %。研究结果表明 :该方法定量快速准确 ,实验操作步骤简单 ,解决了在干扰物存在条件下三者很难同时分辨的问题。     

A Perturbation Approach to Vector Optimization Problems: Lagrange and Fenchel–Lagrange Duality

Journal of Optimization Theory and Applications - In this paper, we study a general minimization vector problem which is expressed in terms of a perturbation mapping defined on a product of locally...     

Unsupervised model-driven neural network based image denoising for transmission line monitoring

With the expansion of smart grid and Internet of things (IoT) technology, edge computing has a wide variety of applications in these domains. The criteria for real-time monitoring and accuracy are particularly high in the field of online real-time monitoring of electricity lines. Based on edge technology, high-quality real-time monitoring can be performed for transmission lines using image processing techniques. Therefore, we propose an image denoising method, which can learn clean images using a stream-based generative model. The stream model uses a two-stage approach in the network to handle the different training periods of denoising separately. Experimental results show that the proposed method has good denoising performance.     

High-Efficiency Organic Solar Cells Enabled by Chalcogen Containing Branched Chain Engineering: Balancing Short-Circuit Current and Open-Circuit Voltage,Enhancing Fill Factor

The elaborate balance between the open-circuit voltage (V_OC) and the short-circuit current density (J_SC) is critical to ensure efficient organic solar cells (OSCs). Herein, the chalcogen containing branched chain engineering is employed to address this dilemma. Three novel nonfullerene acceptors (NFAs), named BTP-2O , BTP-O-S , and BTP-2S , featuring different peripheral chalcogen containing branched chains are synthesized. Compared with symmetric BTP-2O and BTP-2S grafting two alkoxy or alkylthio branched chains, the asymmetric BTP-O-S grafting one alkoxy and one alkylthio branched chains shows mediate absorption range, applicable miscibility, and favorable crystallinity. Benefiting from the enhanced π–π stacking and charge transport, an optimal power conversion efficiency (PCE) of 17.3% is obtained for the PM6: BTP-O-S -based devices, with a good balance between V_OC (0.912 V) and J_SC (24.5 mA cm⁻²), and a high fill factor (FF) of 0.775, which is much higher than those of BTP-2O (16.1%) and BTP-2S -based (16.4%) devices. Such a result represents one of the highest efficiencies among the binary OSCs with V_OC surpassing 0.9 V. Moreover, the BTP-O-S -based devices fabricated by using green solvent yield a satisfactory PCE of 17.1%. This work highlights the synergistic effect of alkoxy and alkylthio branched chains for high-performance OSCs by alleviating voltage loss and enhancing FF.     

Metal Single-Site Molecular Complex–MXene Heteroelectrocatalysts Interspersed Graphene Nanonetwork for Efficient Dual-Task of Water Splitting and Metal–Air Batteries

Development of multifunctional electrocatalysts with high efficiency and stability is of great interest in recent energy conversion technologies. Herein, a novel heteroelectrocatalyst of molecular iron complex (Fe_MC)-carbide MXene (Mo₂TiC₂T_x) uniformly embedded in a 3D graphene-based hierarchical network (GrH) is rationally designed. The coexistence of Fe_MC and MXene with their unique interactions triggers optimum electronic properties, rich multiple active sites, and favorite free adsorption energy for excellent trifunctional catalytic activities. Meanwhile, the highly porous GrH effectively promotes a multichannel architecture for charge transfer and gas/ion diffusion to improve stability. Therefore, the Fe_MC–MXene/GrH results in superb performances towards oxygen reduction reaction (ORR), oxygen evolution reaction (OER), and hydrogen evolution reaction (HER) in alkaline medium. The practical tests indicate that Zn/Al–air batteries derived from Fe_MC–MXene/GrH cathodic electrodes produce high power densities of 165.6 and 172.7 mW cm⁻², respectively. Impressively, the liquid-state Zn–air battery delivers excellent cycling stability of over 1100 h. In addition, the alkaline water electrolyzer induces a low cell voltage of 1.55 V at 10 mA cm⁻² and 1.86 V at 0.4 A cm⁻² in 30 wt.% KOH at 80 °C, surpassing recent reports. The achievements suggest an exciting multifunctional electrocatalyst for electrochemical energy applications.     

基于EMD方法的X波段双偏振雷达衰减订正

针对X波段双偏振雷达信号在降雨路径中的衰减现象,本文提出经验模式分解（Empirical Mode Decomposition,EMD）方法进行X波段双偏振雷达衰减订正,首先对总差分传播相移进行EMD分解得到有限个基本模式分量（Intrinsic Mode Function,IMF）,并基于皮尔逊相关系数准则将IMF分为噪声IMF和信号IMF两类,然后对信号IMF进行有效重构得到差分传播相移,再将差分传播相移通过最小二乘法拟合得到差分传播相移率,最后对求得的差分传播相移与差分传播相移率采用自适应约束方法进行反射率衰减订正。利用EMD方法和其他方法进行对比分析,其结果表明,EMD方法能够有效地消除X波段双偏振雷达回波数据中后向散射的影响,在保留真实的气象信息的同时,有效地抑制差分传播相移的显著波动,进而衰减订正效果更好。     

回波功率筛选与数字地表分类数据辅助的低空风切变风速估计方法

针对非均匀杂波环境下,低空风切变风速估计不准的问题,该文提出一种回波功率筛选与数字地表分类数据(DLCD)辅助的低空风切变风速估计方法.该方法首先利用样本回波功率对训练样本进行初选,然后利用DLCD计算各样本间的相似度,并从功率较大的训练样本中选取样本相似度较高的训练样本估计待测距离单元的杂波协方差矩阵,最后利用广义相邻多波束(GMB)-局域联合处理(JDL)的方法实现低空风切变风速的有效估计.     

Existence results for superlinear semipositone 's

We consider the existence of positive solutions to the BVP

where . Our results extend some of the existing literature on superlinear semipositone problems and singular BVPs. Our proofs are quite simple and are based on fixed point theorems in a cone.