Performance monitoring of a mammalian cell based bioprocess using Raman spectroscopy

Being able to predict the final product yield at all stages in long-running, industrial, mammalian cell culture processes is vital for both operational efficiency, process consistency, and the implementation of quality by design (QbD) practices. Here we used Raman spectroscopy to monitor (in terms of glycoprotein yield prediction) a fed-batch fermentation from start to finish. Raman data were collected from 12 different time points in a Chinese hamster ovary (CHO) based manufacturing process and across 37 separate production runs. The samples comprised of clarified bioprocess broths extracted from the CHO cell based process with varying amounts of fresh and spent cell culture media. Competitive adaptive reweighted sampling (CoAdReS) and ant colony optimization (ACO) variable selection methods were used to enhance the predictive ability of the chemometric models by removing unnecessary spectral information. Using CoAdReS accurate prediction models (relative error of predictions between 2.1% and 3.3%) were built for the final glycoprotein yield at every stage of the bioprocess from small scale up to the final 5000 L bioreactor. This result reinforces our previous studies which indicate that media quality is one of the most significant factors determining the efficiency of industrial CHO-cell processes. This Raman based approach could thus be used to manage production in terms of selecting which small scale batches are progressed to large-scale manufacture, thus improving process efficiency significantly.     

On the induced‐fit mechanism of substrate‐enzyme binding structures of nylon‐oligomer hydrolase

We present a detailed computational investigation of the induced‐fit motion in a nylon‐oligomer hydrolase (NylB) upon substrate binding. To this aim, we resort on the recently introduced parallel cascade selection molecular dynamics approach, allowing for an accelerated access to the set of conformational changes from an open‐ to a closed‐state structure to form the enzyme‐substrate complex in a specific induce‐fit mechanism. The structural investigation is quantitatively complemented by free energy analyses within the umbrella sampling algorithm accompanied by weighted histogram analysis. We find that the stabilization free energy is about 1.4 kcal/mol, whereas the highest free energy barrier to be overcome is about 2.3 kcal/mol. Conversely, the energetic contribution for the substrate binding is about 20 kcal/mol, as estimated from Generalized Born/Surface Area. This means that the open‐close induced‐fit motion could occur frequently once the substrate binds to the open state of NylB. © 2014 Wiley Periodicals, Inc.     

Comprehensive two‐dimensional gas chromatography coupled with static headspace sampling to analyze volatile compounds: Application to almonds

The hyphenation of static headspace sampling with comprehensive 2D GC equipped with a modulator based on capillary flow technology and a flame ionization detector was used to separate and identify 43 representative target volatile compounds (light hydrocarbons, carbonyls, pyrazines, alcohols, furans, and benzenes) frequently detected in the roasting process of nuts. Five column combinations with differing degrees of orthogonality (one conventional and four inverted phase sets) were tested in order to obtain the best conditions for analyzing these volatile compounds. Optimization of the working conditions for each of the different column combinations was performed by means of a central composite design. The best results in terms of separation and differentiation among the different chemical groups were achieved with a combination of inverted phase columns (first dimension: highly polar, INNOWax; second dimension: mid‐polar, ZB‐35). Additionally, a reference template was developed to provide an effective and rapid analysis of the target compounds. Finally, the proposed method was successfully employed to identify volatile compounds in raw and roasted almond samples from the Spanish cultivar Largueta.     

基于改进免疫遗传算法的近红外光谱变量选择方法

该文在免疫遗传算法（IGA）的基础上,提出一种改进免疫遗传算法（iIGA）用于近红外光谱波长变量的选择。该算法舍去了原算法中固定抗体相似度阈值的思想,取而代之的是抗体相似度阈值自适应,同时引入精英保留策略和贪心算法思想,使得算法朝着正确的方向进行局部性探优。将该算法在玉米的淀粉和蛋白质含量数据集上进行实验测试,建立偏最小二乘（PLS）分析模型,并与IGA、遗传算法（GA）以及全谱方法进行了对比。结果表明,在玉米淀粉含量的预测上,iIGA相较于原IGA算法,预测集均方根误差（RMSEP）从0.312 0降至0.298 0,预测集预测精度提升4.5%;在玉米蛋白质含量的预测上,RMSEP从0.124 4降至0.110 3,预测集预测精度提升11.3%。分别对预测淀粉和蛋白质模型的RMSEP值进行显著性检验,F值分别为165.22和182.05,P值分别为9.5 × 10－23和4.5 × 10－24,P值均小于0.05,因此,iIGA能显著提升模型预测精度。     

A method for C(alpha) direct-detection in protonless NMR

Attempts are made to efficiently decouple (13)C nuclei without significant loss of coherence during the application of the decoupling package. Such attempts are based on the S(3)E spin-state selection method. A newly developed double S(3)E (DS(3)E) is particularly efficient for C(alpha) detection for proteins as large as 480 kDa.     

毛细管电泳法高效筛选8-氧代鸟嘌呤DNA糖基化酶的核酸适配体

8-氧代鸟嘌呤DNA糖基化酶(OGG1)是人体中重要的功能蛋白,在修复DNA氧化性损伤过程中起关键作用。氧化应激等引起的氧化损伤易导致炎症反应的发生,对OGG1的抑制可以一定程度上起到缓解作用;对癌细胞OGG1的抑制有望作为癌症治疗的新方法。目前的研究多集中于小分子对OGG1功能的影响和调控,而OGG1的适配体筛选尚未见报道。作为功能配体,适配体具有合成简单、高亲和力及高特异性等优点。该文筛选了OGG1的核酸适配体,结合毛细管电泳高效快速的优点建立了两种基于毛细管电泳-指数富集进化(CE-SELEX)技术的筛选方法:同步竞争法和多轮筛选法。同步竞争法利用单链结合蛋白(SSB)与核酸库中单链核酸的强结合能力,与目标蛋白OGG1组成竞争体系,并通过增加SSB浓度来增加竞争筛选压力,以去除与OGG1弱结合的核酸序列,一步筛选即可获得与OGG1强结合的核酸序列。多轮筛选法在相同孵育条件和电泳条件下,经3轮筛选获得OGG1的核酸适配体。比较两种筛选方法的筛选结果,筛选结果中频次最高的3条候选核酸适配体序列一致,其解离常数(K_D)值在1.71~2.64 μmol/L之间。分子对接分析结果表明候选适配体1(Apt 1)可能与OGG1中具有修复氧化性损伤功能的活性口袋结合。通过对两种筛选方法的对比,证明同步竞争法更加快速高效,对其他蛋白核酸适配体筛选方法的选择具有一定的指导意义。得到的适配体有望用于OGG1功能调控,以抑制其修复功能。     

电拓扑状态预测有机磷酸酯类化合物的气相色谱保留指数

以原子类型电拓扑状态指数(ETSI)有效表征35个有机磷酸酯类化合物(OP)的分子结构, 应用基于预测的变量选择与模型化(VSMP)方法建立OP化合物在3种不同固定相上的气相色谱保留指数(RI)与分子结构(ETSI)的定量相关模型. 结果表明, 影响不同固定相上OP色谱保留的主要结构因素都是由7个ETSI描述子对应的子结构碎片, 即: ＝CH₂,≡C—, aaC—, ＝O, —O—, Cl和Br. 其中子结构aaC—, ＝O和—O与OP化合物母体骨架密切相关, 而＝CH₂,≡C—, —Cl和—Br反映支链或取代基的变化. 通过多元线性回归法建立OP化合物在三个固定相上的定量结构-保留相关模型(QSRR)发现, 各QSAR模型的估计相关系数均在0.99以上, LOO检验相关系数在0.98以上, 表明模型具有良好估计能力与稳定性. 应用28个OP训练集样本构建的QSRR模型预测外部7个检验集RI结果表明训练集模型具有良好预测能力.     

发夹型荧光分子探针用于DNA甲基化酶的活性分析及其在药物筛选中的应用

报道了一种基于发夹型荧光探针的甲基化酶活性的分析方法, 甲基化酶和相应的限制性内切酶的识别位点被设计在发夹型探针的茎部, 四甲基罗丹明(TAMRA)被连接在探针的5'端, 其荧光被连在3'端的熄灭基团4-(4'-二甲基对胺基偶氮苯)苯甲酸(DABCYL)所熄灭. 限制性内切酶可切割未发生甲基化修饰的探针, 导致探针的发夹结构遭到破坏, 引起TAMRA荧光信号的恢复. 根据荧光信号的恢复程度可实现对甲基化酶活性的分析. 在此基础上, 建立了一种简便、快速分析抗肿瘤药物对DNA甲基化酶活性的影响的方法, 为筛选针对基因甲基化异常引起的恶性肿瘤的治疗药物提供了一种新的思路和方法.     

Diffraction mode selection in planar Bragg resonators of optical and microwave wavelength ranges

Using the coupled waves approach complemented by the time-domain quasi-optical approximation, we solve a 2D diffraction problem which allows to evaluate the eigenfrequencies, quality factors and spatial structures of eigenmodes in planar Bragg resonators with a finite length and width of the corrugated area. We find the values of the Fresnel parameter determined by the geometrical dimensions of the system which allows for efficient transverse mode discrimination due to the larger diffraction losses of the modes with higher transverse numbers.     

Optimization of STEM-HAADF Electron Tomography Reconstructions by Parameter Selection in Compressed Sensing Total Variation Minimization-Based Algorithms

A novel procedure to optimize the 3D morphological characterization of nanomaterials by means of high angle annular dark field scanning-transmission electron tomography is reported and is successfully applied to the analysis of a metal- and halogen-free ordered mesoporous carbon material. The new method is based on a selection of the two parameters (μ and β) which are key in the reconstruction of tomographic series by means of total variation minimization (TVM). The parameter-selected TVM reconstructions obtained using this approach clearly reveal the porous structure of the carbon-based material as consisting of a network of parallel, straight channels of ≈6 nm diameter ordered in a honeycomb-type arrangement. Such an unusual structure cannot be retrieved from a TVM 3D reconstruction using default reconstruction values. Moreover, segmentation and further quantification of the optimized 3D tomographic reconstruction provide values for different textural parameters, such as pore size distribution and specific pore volume that match very closely with those determined by macroscopic physisorption techniques. The approach developed can be extended to other reconstruction models in which the final result is influenced by parameter choice.