Enrichments of post‐translational modifications in proteomic studies

More than 300 different protein post‐translational modifications are currently known, but only a few have been extensively investigated because modified proteoforms are commonly present in sub‐stoichiometry amount. For this reason, improvement of specific enrichment techniques is particularly useful for the proteomic characterization of post‐translationally modified proteins. Enrichment proteomic strategies could help the researcher in the challenging issue to decipher the complex molecular cross‐talk existing between the different factors influencing the cellular pathways. In this review the state of art of the platforms applied for the enrichment of specific and most common post‐translational modifications, such as glycosylation and glycation, phosphorylation, sulfation, redox modifications (i.e. sulfydration and nitrosylation), methylation, acetylation, and ubiquitinylation, are described. Enrichments strategies applied to characterize less studied post‐translational modifications are also briefly discussed.     

An overview on enrichment methods for cell surface proteome profiling

Cell surface proteins are essential for many important biological processes, including cell–cell interactions, signal transduction, and molecular transportation. With the characteristics of low abundance, high hydrophobicity, and high heterogeneity, it is difficult to get a comprehensive view of cell surface proteome by direct analysis. Thus, it is important to selectively enrich the cell surface proteins before liquid chromatography with mass spectrometry analysis. In recent years, a variety of enrichment methods have been developed. Based on the separation mechanism, these methods could be mainly classified into three types. The first type is based on their difference in the physicochemical property, such as size, density, charge, and hydrophobicity. The second one is based on the bimolecular affinity interaction with lectin or antibody. And the third type is based on the chemical covalent coupling to free side groups of surface‐exposed proteins or carbohydrate chains, such as primary amines, carboxyl groups, glycan side chains. In addition, metabolic labeling and enzymatic reaction‐based methods have also been employed to selectively isolate cell surface proteins. In this review, we will provide a comprehensive overview of the enrichment methods for cell surface proteome profiling.     

一组新氨基酸描述子用于肽定量构效关系研究

用主成分分析从20种天然氨基酸0D～3D结构信息中收集到的共1369个描述子变量得到了一组新氨基酸描述子(SZOTT), 将其用于血管紧张素转化酶抑制剂和苦味二肽结构表征并以偏最小二乘法建立定量构效关系模型, 得复相关系数R_CU²分别为0.894和0.908, 留一法交互检验的复相关系数R_CV²分别为0.828和0.736, 估计均方根误差RMS分别为0.331和0.195. 研究结果表明, SZOTT描述子含信息量大, 操作简便, 结构表达能力强, 有望在多肽定量构效关系研究中得到进一步推广.     

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.     

分子信标用于p53 mRNA的体外定量检测

根据p53基因的序列设计并合成了能特异性检测p53 mRNA的分子信标(MB), 发展了一种快速定量测定细胞内总RNA提取物中p53 mRNA的方法. 采用鼻咽癌(CNE2)细胞系和经RNA干扰技术降低p53基因表达的CNE2-p53RNAi细胞系, 抽提总RNA并用MB检测, 验证了MB的检测对象是p53 mRNA. 将该方法应用于多种肿瘤细胞内p53基因表达水平的分析, 表达变化趋势与经典的mRNA分析方法RT-PCR检测结果相符. 在此基础上, 用MB对5-氟尿嘧啶(5-Fu)处理的肺腺癌细胞(A549)进行了p53 mRNA的体外定量检测, 结果表明采用MB能够快速地获知该药物对细胞内p53 mRNA表达影响的信息.     

Label-Free Quantitative Proteomics to Explore the Action Mechanism of the Pharmaceutical-Grade Triticum vulgare Extract in Speeding Up Keratinocyte Healing

Plant extracts have shown beneficial properties in terms of skin repair, promoting wound healing through a plethora of mechanisms. In particular, the poly-/oligosaccharidic aqueous extract of Triticum vulgare (TVE), as well as TVE-based products, shows interesting biological assets, hastening wound repair. Indeed, TVE acts in the treatment of tissue regeneration mainly on decubitus and venous leg ulcers. Moreover, on scratched monolayers, TVE prompts HaCat cell migration, correctly modulating the expression of metalloproteases toward a physiological matrix remodeling. Here, using the same HaCat-based in vitro scratch model, the TVE effect has been investigated thanks to an LFQ proteomic analysis of HaCat secretomes and immunoblotting. Indeed, the unbiased TVE effect on secreted proteins has not yet been fully understood, and it could be helpful to obtain a comprehensive picture of its bio-pharmacological profile. It has emerged that TVE treatment induces significant up-regulation of several proteins in the secretome (153 to be exact) whereas only a few were down-regulated (72 to be exact). Interestingly, many of the up-regulated proteins are implicated in promoting wound-healing-related processes, such as modulating cell–cell interaction and communication, cell proliferation and differentiation, and prompting cell adhesion and migration.     

基于改进云推理算法的塔架结构损伤识别

为了解决塔架结构的损伤识别问题,提出了基于应变能和改进云推理算法的损伤识别方法。首先描述了云模型的基本理论和数字特征,并给出了模态应变能的基本公式;然后分析了X条件云发生器和Y条件云发生器的基本算法和运行步骤,借助灰云模型建立相应的前件云和后件云规则,考虑了测量噪声的影响,利用云发生器生成多组云滴,并利用多模式下云滴的确定度和生成值构建了基本云推理算法及其损伤识别指标。基本云推理算法中常会产生不均匀发散的云滴,从而使计算结果产生一定的偏差,为了降低云滴发散产生的偏差影响,提出了基于损伤模式数量加权的云推理改进策略。计算结果表明:云推理算法可以较好地应用于塔架结构的损伤识别,其识别结果明显优于传统的应变能耗散率指标方法;而改进云推理算法进一步提高了识别的精度,优于基本云推理算法。     

Preparation of Highly Stable and Photoluminescent Cadmium-Free InP/GaP/ZnS Core/Shell Quantum Dots and Application to Quantitative Immunoassay

Indium phosphide (InP) quantum dots (QDs) are ideal substitutes for widely used cadmium-based QDs and have great application prospects in biological fields due to their environmentally benign properties and human safety. However, the synthesis of InP core/shell QDs with biocompatibility, high quantum yield (QY), uniform particle size, and high stability is still a challenging subject. Herein, high quality (QY up to 72%) thick shell InP/GaP/ZnS core/shell QDs (12.8 ± 1.4 nm) are synthesized using multiple injections of shell precursor and extension of shell growth time, with GaP serving as the intermediate layer and 1-octanethiol acting as the new S source. The thick shell InP/GaP/ZnS core/shell QDs still keep high QY and photostability after transfer into water. InP/GaP/ZnS core/shell QDs as fluorescence labels to establish QD-based fluorescence-linked immunosorbent assay (QD-FLISA) for quantitative detection of C-reactive protein (CRP), and a calibration curve is established between fluorescence intensity and CRP concentrations (range: 1–800 ng mL⁻¹, correlation coefficient: R² = 0.9992). The limit of detection is 2.9 ng mL⁻¹, which increases twofold compared to previously reported cadmium-free QD-based immunoassays. Thus, InP/GaP/ZnS core/shell QDs as a great promise fluorescence labeling material, provide a new route for cadmium-free sensitive and specific immunoassays in biomedical fields.     

Channel-Supermodular Entropies: Order Theory and an Application to Query Anonymization

This work introduces channel-supermodular entropies, a subset of quasi-concave entropies. Channel-supermodularity is a property shared by some of the most commonly used entropies in the literature, including Arimoto–Rényi conditional entropies (which include Shannon and min-entropy as special cases), k-tries entropies, and guessing entropy. Based on channel-supermodularity, new preorders for channels that strictly include degradedness and inclusion (or Shannon ordering) are defined, and these preorders are shown to provide a sufficient condition for the more-capable and capacity ordering, not only for Shannon entropy but also regarding analogous concepts for other entropy measures. The theory developed is then applied in the context of query anonymization. We introduce a greedy algorithm based on channel-supermodularity for query anonymization and prove its optimality, in terms of information leakage, for all symmetric channel-supermodular entropies.     

Chemometrics: An Excavator in Temperature-Dependent Near-Infrared Spectroscopy

Temperature-dependent near-infrared (NIR) spectroscopy has been developed and taken as a powerful technique for analyzing the structure of water and the interactions in aqueous systems. Due to the overlapping of the peaks in NIR spectra, it is difficult to obtain the spectral features showing the structures and interactions. Chemometrics, therefore, is adopted to improve the spectral resolution and extract spectral information from the temperature-dependent NIR spectra for structural and quantitative analysis. In this review, works on chemometric studies for analyzing temperature-dependent NIR spectra were summarized. The temperature-induced spectral features of water structures can be extracted from the spectra with the help of chemometrics. Using the spectral variation of water with the temperature, the structural changes of small molecules, proteins, thermo-responsive polymers, and their interactions with water in aqueous solutions can be demonstrated. Furthermore, quantitative models between the spectra and the temperature or concentration can be established using the spectral variations of water and applied to determine the compositions in aqueous mixtures.