CNKSR2 interactome analysis indicates its association with the centrosome/microtubule system

The protein connector enhancer of kinase suppressor of Ras 2(CNKSR2),present in both the postsynaptic density and cytoplasm of neurons,is a scaffolding protein with several protein-binding domains.Variants of the CNKSR2 gene have been implicated in neurodevelopmental disorders,particularly intellectual disability,although the precise mechanism involved has not yet been fully understood.Research has demonstrated that CNKSR2 plays a role in facilitating the localization of postsynaptic density protein complexes to the membrane,thereby influencing synaptic signaling and the morphogenesis of dendritic spines.However,the function of CNKSR2 in the cytoplasm remains to be elucidated.In this study,we used immunoprecipitation and high-resolution liquid chromatography-mass spectrometry to identify the interactors of CNKSR2.Through a combination of bioinformatic analysis and cytological experiments,we found that the CNKSR2 interactors were significantly enriched in the proteome of the centrosome.We also showed that CNKSR2 interacted with the microtubule protein DYNC1H1 and with the centrosome marker CEP290.Subsequent colocalization analysis confirmed the centrosomal localization of CNKSR2.When we downregulated CNKSR2 expression in mouse neuroblastoma cells(Neuro 2A),we observed significant changes in the expression of numerous centrosomal genes.This manipulation also affected centrosome-related functions,including cell size and shape,cell proliferation,and motility.Furthermore,we found that CNKSR2 interactors were highly enriched in de novo variants associated with intellectual disability and autism spectrum disorder.Our findings establish a connection between CNKSR2 and the centrosome,and offer new insights into the underlying mechanisms of neurodevelopmental disorders.

Spastin and alsin protein interactome analyses begin to reveal key canonical pathways and suggest novel druggable targets

Developing effective and long-term treatment strategies for rare and complex neurodegenerative diseases is challenging. One of the major roadblocks is the extensive heterogeneity among patients. This hinders understanding the underlying disease-causing mechanisms and building solutions that have implications for a broad spectrum of patients. One potential solution is to develop personalized medicine approaches based on strategies that target the most prevalent cellular events that are perturbed in patients. Especially in patients with a known genetic mutation, it may be possible to understand how these mutations contribute to problems that lead to neurodegeneration. Protein–protein interaction analyses offer great advantages for revealing how proteins interact, which cellular events are primarily involved in these interactions, and how they become affected when key genes are mutated in patients. This line of investigation also suggests novel druggable targets for patients with different mutations. Here, we focus on alsin and spastin, two proteins that are identified as “causative” for amyotrophic lateral sclerosis and hereditary spastic paraplegia, respectively, when mutated. Our review analyzes the protein interactome for alsin and spastin, the canonical pathways that are primarily important for each protein domain, as well as compounds that are either Food and Drug Administration–approved or are in active clinical trials concerning the affected cellular pathways. This line of research begins to pave the way for personalized medicine approaches that are desperately needed for rare neurodegenerative diseases that are complex and heterogeneous.

The BLOC Interactomes Form a Network in Endosomal Transport

With the identification of more than a dozen novel Hermansky-Pudlak Syndrome （HPS） proteins in vesicle trafficking in higher eukaryotes, a new class of trafficking pathways has been described. It mainly consists of three newly-defined protein com- plexes, BLOC-l, -2, and -3. Compelling evidence indicates that these complexes together with two other well-known complexes, AP3 and HOPS, play important roles in endosomal transport. The interactions between these complexes form a network in protein trafficking via endosomes and cytoskeleton. Each node of this network has intra-complex and extra-complex interactions. These complexes are connected by direct interactions between the subunits from different complexes or by indirect interactions through coupling nodes that interact with two or more subunits from different complexes. The dissection of this network facilitates the understanding of a dynamic but elaborate transport machinery in protein/membrane trafficking. The disruption of this network may lead to abnormal trafficking or defective organellar development as described in patients with Hermansky-Pudlak syndrome.

Mapping the human protein interactome

Interactions are the essence of all biomolecules because they cannot fulfill their roles without interacting with other molecules. Hence, mapping the interactions of biomolecules can be useful for understanding their roles and functions. Furthermore, the development of molecular based systems biology requires an understanding of the biomolecular interactions. In recent years, the mapping of protein-protein interactions in different species has been reported, but few reports have focused on the large-scale mapping of protein-protein interactions in human. Here, we review the developments in protein interaction mapping and we discuss issues and strategies for the mapping of the human protein interactome.

The cellular interactome for glycoprotein 5 of the Chinese highly pathogenic porcine reproductive and respiratory syndrome virus

supported by the Earmarked Fund for Modern Agro-industry Technology Research System of China （CARS-36） from the Ministry of Agriculture of China;the National Natural Science Foundation of China （31572549）;the National Key Technology R＆D Program of China （2015BAD12B01-2） from the Ministry of Science and Technology of China

Strategies for translating proteomics discoveries into drug discovery for dementia

Tauopathies,diseases characterized by neuropathological aggregates of tau including Alzheimer's disease and subtypes of fro ntotemporal dementia,make up the vast majority of dementia cases.Although there have been recent developments in tauopathy biomarkers and disease-modifying treatments,ongoing progress is required to ensure these are effective,economical,and accessible for the globally ageing population.As such,continued identification of new potential drug targets and biomarkers is critical."Big data"studies,such as proteomics,can generate information on thousands of possible new targets for dementia diagnostics and therapeutics,but currently remain underutilized due to the lack of a clear process by which targets are selected for future drug development.In this review,we discuss current tauopathy biomarkers and therapeutics,and highlight areas in need of improvement,particularly when addressing the needs of frail,comorbid and cognitively impaired populations.We highlight biomarkers which have been developed from proteomic data,and outline possible future directions in this field.We propose new criteria by which potential targets in proteomics studies can be objectively ranked as favorable for drug development,and demonstrate its application to our group's recent tau interactome dataset as an example.

Potential role of the protein interactome in translating TCM theory and clinical practice into modern biomedical knowledge

With the awarding of the 2015 Nobel Prize in Physiology or Medicine to Chinese pharmacologist Tu Youyou,and the significant contributions of traditional Chinese medicine(TCM)for coronavirus disease 2019(COVID-19),TCM has garnered increasing attention and interest globally.Although advanced research progress has been made in the efficacy research,mechanism elucidation and target prediction of TCM in recent years[1].

动态加权蛋白质相互作用网络构建及其应用研究

一个蛋白质可能在不同条件或不同时刻与不同的蛋白质发生相互作用,这称为蛋白质的动态特性.蛋白质在分子处理的不同阶段参与到不同的模块,与其他的蛋白质共同完成某项功能.因此,动态蛋白质相互作用的研究有助于提高蛋白质功能预测的准确率.结合蛋白质相互作用网络和时间序列基因表达数据,构建动态蛋白质相互作用网络.为降低PPI网络中假阴性对功能预测产生的负面影响,结合结构域信息和复合物信息,预测和产生新的相互作用,并对相互作用加权.基于构建的动态加权网络,提出一种功能预测方法 D-PIN(Dynamic protein interaction networks).基于三个不同的酵母相互作用网络实验结果表明,D-PIN方法的综合性能比现有方法提高了14%以上.结果验证了构建的动态加权蛋白质相互网络的有效性.

网络药理学研究中的网络构建技术

网络构建技术是网络药理学研究中的基础技术,也是核心技术。通过整合来源于实验、数据库和计算预测等的包含药物、疾病及生物分子等在内的用于网络构建的相关数据,采用复杂网络构建技术进行药物作用相关、疾病相关和生物分子相关的网络模型构建,尤其对于以阿尔茨海默病为代表的复杂疾病分子网络的构建,为进一步重要靶标的辨识、发病机制和药物作用机制的阐释、指导药物开发,以及药物重定位等打下基础。本文就网络药理学研究相关的药物组网络、疾病组网络和分子相互作用组网络等的构建及其可视化技术进行综述。

病毒-宿主相互作用的系统生物学与宿主靶向抗病毒策略

以病毒蛋白为靶的抗病毒药物面临易产生耐药、抗病毒谱较窄等诸多问题,宿主分子靶向已经成目前抗病毒药物研究的重要策略,宿主靶标的辨识是宿主靶向药物设计的关键。病毒-宿主相互作用的系统生物学研究将成为抗病毒药物宿主靶标辨识和宿主-病毒联合靶向治疗策略设计提供有力工具。近年来通过蛋白质组学、大规模基因沉默、基因芯片等实验得到了大量的病毒感染相关宿主分子和病毒-宿主分子相互作用关系,为在病毒-宿主分子网络水平揭示病毒生存策略奠定了基础。整合病毒感染基因表达谱和人蛋白相互作用网络可以构建病毒感染激活网络,进而通过网络分析获得关键的宿主因子。正在发展的动态蛋白质组学和动态网络分析技术将为建立更加真实的病毒-宿主分子网络模型,进而辨识有效的宿主靶标提供有力工具。

蛋白质相互作用数据库

随着"蛋白质组学"的蓬勃发展和人类对生物大分子功能机制的知识积累,涌现出海量的蛋白质相互作用数据。随之,研究者开发了300多个蛋白质相互作用数据库,用于存储、展示和数据的重利用。蛋白质相互作用数据库是系统生物学、分子生物学和临床药物研究的宝贵资源。本文将数据库分为3类:(1)综合蛋白质相互作用数据库;(2)特定物种的蛋白质相互作用数据库;(3)生物学通路数据库。重点介绍常用的蛋白质相互作用数据库,包括BioGRID、STRING、IntAct、MINT、DIP、IMEx、HPRD、Reactome和KEGG等。

大规模的酵母双杂交系统在蛋白质相互作用组图谱中的应用

蛋白质-蛋白质之间的相互作用是蛋白质发挥其功能的重要途径之一。通过研究蛋白质组中所有蛋白质之间的相互作用做出蛋白质相互作用对图谱是功能基因组时代许多科学家关注的问题,而大规模的酵母双杂交系统是蛋白质相互作用对图谱的研究中应用较为广泛的策略。近两年来该策略最具代表的实例是用它进行酵母中所有蛋白之间相互作用的检查。但是巨大的蛋白质网络比我们想象要大得多,单一的双杂交系统不能解决所有问题,需要同其它的方法有效地结合。

细胞动力学研究进展与展望

细胞是生命活动的最小单元,其功能可塑性及动力学特征是维系生命个体健康及物种繁衍的重要保证.在分子水平,细胞可塑性与动力学特征受遗传学及表观遗传学的调控.随着基因组计划的顺利完成及我们对细胞增殖重要蛋白质作用网络生物化学特征研究的成功实施,揭示细胞重要生命活动过程中功能分子的动力学特征及其调控机制显得日益重要.组建中国科学技术大学细胞动力学实验室旨在纳米尺度揭示细胞重要生命活动全过程的详尽全息分子调控机制.在过去的几年中,已取得了动点蛋白质网络研究的阶段性进展,在动点蛋白复合物组分剖析、功能评估、蛋白质作用动力学及可塑性研究等方面均取得了具有特色的成绩.目前,拟在纳米尺度评估动点组装的时空动力学调控机制.相信在未来的日子里,细胞动力学实验室的创新性成果能够综合集成,并为人口与健康领域的重大命题提供相关的解答方案与技术平台.

RNA结合蛋白与RNA相互作用鉴定技术

RNA结合蛋白(RNA binding proteins,RBPs)通过与RNA相互作用,广泛参与到RNA的剪切、转运、编辑、胞内定位及翻译调控等过程中。RNA领域尤其是非编码RNA(non-coding RNA,ncRNA)研究的快速发展,催生了多种RBPs-RNAs相互作用鉴定技术。这些技术反之又推动了RNA领域的研究进程。本文对紫外交联免疫沉淀(ultraviolet crosslinking and immunoprecipitation,CLIP),CLIP cDNA文库高通量测序(high-throughput sequencing of CLIP cDNA library,HITS-CLIP),光活化核苷增强的CLIP(photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation,PAR-CLIP),单核苷酸分离CLIP(individual nucleotide resolution CLIP,i CLIP),TRIBE(targets of RNA-binding protein identified by editing),RNA标记,相互作用组捕获(interactome capture,IC)和Ser IC(serial RNA interactome capture)等RBPs-RNAs相互作用鉴定技术的基本原理和优缺点以及应用进行综述。

Early steps in the DNA base excision/single-strand interruption repair pathway in mammalian cells

Base excision repair （BER） is an evolutionarily conserved process for maintaining genomic integrity by eliminating several dozen damaged （oxidized or aikylated） or inappropriate bases that are generated endogenously or induced by genotoxicants, predominantly, reactive oxygen species （ROS）. BER involves 4-5 steps starting with base excision by a DNA glycosylase, followed by a common pathway usually involving an AP-endonuclease （APE） to generate 3＇ OH terminus at the damage site, followed by repair synthesis with a DNA polymerase and nick sealing by a DNA iigase. This pathway is also responsible for repairing DNA single-strand breaks with blocked termini directly generated by ROS. Nearly all glycosylases, far fewer than their substrate lesions particularly for oxidized bases, have broad and overlapping substrate range, and could serve as back-up enzymes in vivo. In contrast, mammalian cells encode only one APE, APEI, unlike two APEs in lower organisms. In spite of overall similarity, BER with distinct subpathways in the mammals is more complex than in E. coli. The glycosylases form complexes with downstream proteins to carry out efficient repair via distinct subpathways one of which, responsible for repair of strand breaks with 3＇ phosphate termini generated by the NEIL family glycosylases or by ROS, requires the phosphatase activity of polynucleotide kinase instead of APE1. Different complexes may utilize distinct DNA polymerases and iigases. Mammalian glycosylases have nonconserved extensions at one of the termini, dispensable for enzymatic activity but needed for interaction with other BER and non-BER proteins for complex formation and organeile targeting. The mammalian enzymes are sometimes covalently modified which may affect activity and complex formation. The focus of this review is on the early steps in mammalian BER for oxidized damage.

Computational Identification of Protein-Protein Interactions in Rice Based on the Predicted Rice Interactome Network

Plant protein-protein interaction networks have not been identified by large-scale experiments. In order to better understand the protein interactions in rice, the Predicted Rice Interactome Network （PRIN; http：//bis.zju.edu.cn/ prin/） presented 76,585 predicted interactions involving 5,049 rice proteins. After mapping genomic features of rice （GO annotation, subcellular localizationprediction, and gene expression）, we found that a well-annotated and biologically significant network is rich enough to capture many significant functional linkages within higher-order biological systems, such as pathways and biological processes. Furthermore, we took MADS-box do- main-containing proteins and circadian rhythm signaling pathways as examples to demonstrate that functional protein complexes and biological pathways could be effectively expanded in our predicted network. The expanded molecular network in PRIN has considerably improved the capability of these analyses to integrate existing knowledge and provide novel insights into the function and coordination of genes and gene networks.

蛋白质互作组学技术及其在植物研究中的应用进展

蛋白质互作组学技术是一门鉴定和量化蛋白质与其他代谢物或蛋白质等分子相互作用的前沿技术,已成为研究植物系统生物学和多组学研究的重要组成部分。近年来,基于质谱的组学技术迅速发展,也促进蛋白质-代谢物相互作用(Protein-metabolite interaction,PMI)、蛋白质-蛋白质相互作用(Protein-protein interaction,PPI)的发现和验证方法取得巨大进步,这些蛋白质互作组学技术在功能基因组和功能代谢组研究中逐渐展示出巨大的应用潜力。系统总结了过去10年不同蛋白质互作组学技术(主要包括PMI和PPI)的分析策略,并详细分析了它们各自的优缺点和适用的相互作用类型,综述了蛋白质互作组学技术在植物研究领域的应用进展,对植物蛋白质互作组学技术的应用策略和需要攻克的关键技术瓶颈进行了总结。蛋白质互作组学技术的不断发展将进一步推动植物胞内信号转导及代谢调控通路的解析,而精准解析信号网络中关键相互作用将为植物自身生长发育以及适应外界环境等机制研究提供重要的信息。

Using Interactome Big Data to Crack Genetic Mysteries and Enhance Future Crop Breeding

The functional genes underlying phenotypic variation and their interactions represent“genetic mysteries”.Understanding and utilizing these genetic mysteries are key solutions for mitigating the current threats to agriculture posed by population growth and individual food preferences.Due to advances in highthroughput multi-omics technologies,we are stepping into an Interactome Big Data era that is certain to revolutionize genetic research.In this article,we provide a brief overview of current strategies to explore genetic mysteries.We then introduce the methods for constructing and analyzing the Interactome Big Data and summarize currently available interactome resources.Next,we discuss how Interactome Big Data can be used as a versatile tool to dissect genetic mysteries.We propose an integrated strategy that could revolutionize genetic research by combining Interactome Big Data with machine learning,which involves mining information hidden in Big Data to identify the genetic models or networks that control various traits,and also provide a detailed procedure for systematic dissection of genetic mysteries,Finally,we discuss three promising future breeding strategies utilizing the Interactome Big Data to improve crop yields and quality.

Integrate Omics Data and Molecular Dynamics Simulations toward Better Understanding of Human 14-3-3 Interactomes and Better Drugs for Cancer Therapy

The 14-3-3 protein family is among the most extensively studied, yet still largely mysterious protein families in mammals to date. As they are well recognized for their roles in apoptosis, cell cycle regulation, and proliferation in healthy cells, aberrant 14-3-3 expression has unsurprisingly emerged as instrumentalin the development of many cancers and in prognosis. Interestingly, while the seven known 14-3-3 isoforms in humans have many similar functions across cell types, evidence of isoform-specific functions and localization has been observed in both healthy and diseased cells The strikingly high similarity among 14-3-3 isoforms has made it difficult to delineate isoform-specific functions and for isoform-specific targeting. Here, we review our knowledge of 14-3-3 interactome（s） generated by high- throughput techniques, bioinformatics, structural genomics and chemical genornics and point out that integrating the information with molecular dynamics （MD） simulations may bring us new opportunity to the design of isoform-specific inhibitors, which can not only be used as powerful research tools for delineating distinct interactomes of individual 14-3-3 isoforms, but also can serve as potential new anti-cancer drugs that selectively target aberrant 14-3-3 isoform.

Systems-Based Interactome Analysis for Hematopoiesis Effect of Angelicae sinensis Radix: Regulated Network of Cell Proliferation towards Hemopoiesis

Objective: To explore the molecular-level mechanism on the hematopoiesis effect of Angelicae sinensis Radix(ASR) with systems-based interactome analysis. Methods: This systems-based interactome analysis was designed to enforce the workflow of "ASR(herb)→compound→target protein→internal protein actions→ending regulated protein for hematopoiesis". This workflow was deployed with restrictions on regulated proteins expresses in bone marrow and anemia disease and futher validated with experiments. Results: The hematopoiesis mechanism of ASR might be accomplished through regulating pathways of cell proliferation towards hemopoiesis with cross-talking agents of spleen tyrosine kinase(SYK), Janus kinase 2(JAK2), and interleukin-2-inducible T-cell kinase(ITK). The hematopoietic function of ASR was also validated by colonyforming assay performed on mice bone marrow cells. As a result, SYK, JAK2 and ITK were activated. Conclusion: This study provides a new approach to systematically study and predict the therapeutic mechanism for ASR based on interactome analysis towards biological process with experimental validations.