Ubiquitination-mediated protein degradation and modification： an emerging theme in plant-microbe interactions

Post-translational modification is central to protein stability and to the naodulation of protein activity.Various types ofprotein modification,such as phosphorylation,methylation,acetylation,myristoylation,glycosylation,and ubiquitina-tion,have been reported.Among them,ubiquitination distinguishes itself from others in that most of the ubiquitinatedproteins are targeted to the 26S proteasome for degradation.The ubiquitin/26S proteasome system constitutes the majorprotein degradation pathway in the cell.In recent years,the importance of the ubiquitination machinery in the controlof numerous eukaryotic cellular functions has been increasingly appreciated.Increasing number of E3 ubiquitin ligasesand their substrates,including a variety of essential cellular regulators have been identified.Studies in the past severalyears have revealed that the ubiquitination system is important for a broad range of plant developmental processes andresponses to abiotic and biotic stresses.This review discusses recent advances in the functional analysis of ubiquitina-tion-associated proteins from plants and pathogens that play important roles in plant-microbe interactions.     

A Bipartite Network-based Method for Prediction of Long Non-coding RNA–protein Interactions

As one large class of non-coding RNAs(nc RNAs), long nc RNAs(lncRNAs) have gained considerable attention in recent years. Mutations and dysfunction of lnc RNAs have been implicated in human disorders. Many lnc RNAs exert their effects through interactions with the corresponding RNA-binding proteins. Several computational approaches have been developed, but only few are able to perform the prediction of these interactions from a network-based point of view. Here,we introduce a computational method named lnc RNA–protein bipartite network inference(LPBNI). LPBNI aims to identify potential lnc RNA–interacting proteins, by making full use of the known lnc RNA–protein interactions. Leave-one-out cross validation(LOOCV) test shows that LPBNI significantly outperforms other network-based methods, including random walk(RWR)and protein-based collaborative filtering(Pro CF). Furthermore, a case study was performed to demonstrate the performance of LPBNI using real data in predicting potential lnc RNA–interacting proteins.     

GoldCLIP: Gel-omitted Ligation-dependent CLIP

Protein–RNA interaction networks are essential to understand gene regulation control.Identifying binding sites of RNA-binding proteins(RBPs) by the UV-crosslinking and immunoprecipitation(CLIP) represents one of the most powerful methods to map protein–RNA interactions in vivo. However, the traditional CLIP protocol is technically challenging, which requires radioactive labeling and suffers from material loss during PAGE-membrane transfer procedures. Here we introduce a super-efficient CLIP method(Gold CLIP) that omits all gel purification steps. This nonisotopic method allows us to perform highly reproducible CLIP experiments with polypyrimidine tract-binding protein(PTB), a classical RBP in human cell lines. In principle, our method guarantees sequencing library constructions, providing the protein of interest can be successfully crosslinked to RNAs in living cells. Gold CLIP is readily applicable to diverse proteins to uncover their endogenous RNA targets.     

Computational approaches to understanding protein aggregation in neurodegeneration

The generation of toxic non-native protein conformers has emerged as a unifying thread among disorders such as Alzheimer＇s disease, Parkinson＇s disease, and amyotrophic lateral sclerosis. Atomic-level detail regarding dynamical changes that facilitate protein aggre- gation, as well as the structural features of large-scale ordered aggregates and soluble non-native oligomers, would contribute signifi- cantly to current understanding of these complex phenomena and offer potential strategies for inhibiting formation of cytotoxic species. However, experimental limitations often preclude the acquisition of high-resolution structural and mechanistic information for aggregating systems. Computational methods, particularly those combine both aU-atom and coarse-grained simulations to cover a wide range of time and length scales, have thus emerged as crucial tools for investigating protein aggregation. Here we review the current state of computational methodology for the study of protein self-assembly, with a focus on the application of these methods toward understanding of protein aggregates in human neurodegenerative disorders.     

Global signatures of protein binding on structured RNAs in Saccharomyces cerevisiae

Protein binding is essential to the transport,decay and regulation of almost all RNA molecules.However,the structural preference of protein binding on RNAs and their cellular functions and dynamics upon changing environmental conditions are poorly understood.Here,we integrated various high-throughput data and introduced a computational framework to describe the global interactions between RNA binding proteins(RBPs)and structured RNAs in yeast at single-nucleotide resolution.We found that on average,in terms of percent total lengths,~15%of mRNA untranslated regions(UTRs),~37%of canonical non-coding RNAs(ncRNAs)and~11%of long ncRNAs(lncRNAs)are bound by proteins.The RBP binding sites,in general,tend to occur at single-stranded loops,with evolutionarily conserved signatures,and often facilitate a specific RNA structure conformation in vivo.We found that four nucleotide modifications of tRNA are significantly associated with RBP binding.We also identified various structural motifs bound by RBPs in the UTRs of mRNAs,associated with localization,degradation and stress responses.Moreover,we identified>200 novel lncRNAs bound by RBPs,and about half of them contain conserved secondary structures.We present the first ensemble pattern of RBP binding sites in the structured non-coding regions of a eukaryotic genome,emphasizing their structural context and cellular functions.     

The Pendulum Model for Genome Compositional Dynamics:from the Four Nucleotides to the Twenty Amino Acids

The genetic code serves as one of the natural links for life’s two conceptual frameworks-the informational and operational tracks- bridging the nucleotide sequence of DNA and RNA to the amino acid sequence of protein and thus its structure and function.On the informational track,DNA and its four building blocks have four basic variables:order,length,GC and purine contents;the latter two exhibit unique characteristics in prokaryotic genomes where protein-coding sequences dominate.Bridging the two tracks,tRNAs and their aminoacyl tRNA synthases that interpret each codon-nucleotide triplet,together with ribosomes,form a complex machinery that translates genetic information encoded on the messenger RNAs into proteins.On the operational track,proteins are selected in a context of cellular and organismal functions constantly.The principle of such a functional selection is to minimize the damage caused by sequence alteration in a seemingly random fashion at the nucleotide level and its function-altering consequence at the protein level;the principle also suggests that there must be complex yet sophisticated mechanisms to protect molecular interactions and cellular processes for cells and organisms from the damage in addition to both immediate or short-term eliminations and long-term selections.The twocentury study of selection at species and population levels has been leading a way to understand rules of inheritance and evolution at molecular levels along the informational track,while ribogenomics,epigenomics and other operationally-defined omics(such as the metabolite-centric metabolomics) have been ushering biologists into the new millennium along the operational track.     

Identification of Semaphorin 5A Interacting Protein by Applying Apriori Knowledge and Peptide Complementarity Related to Protein Evolution and Structure

In the post-genomic era, various computational methods that predict proteinprotein interactions at the genome level are available; however, each method has its own advantages and disadvantages, resulting in false predictions. Here we developed a unique integrated approach to identify interacting partner（s） of Semaphorin 5A （SEMA5A）, beginning with seven proteins sharing similar ligand interacting residues as putative binding partners. The methods include Dwyer and Root- Bernstein/Dillon theories of protein evolution, hydropathic complementarity of protein structure, pattern of protein functions among molecules, information on domain-domain interactions, co-expression of genes and protein evolution. Among the set of seven proteins selected as putative SEMA5A interacting partners, we found the functions of Plexin B3 and Neuropilin-2 to be associated with SEMA5A. We modeled the semaphorin domain structure of Plexin B3 and found that it shares similarity with SEMA5A. Moreover, a virtual expression database search and RT-PCR analysis showed co-expression of SEMA5A and Plexin B3 and these proteins were found to have co-evolved. In addition, we confirmed the interaction of SEMA5A with Plexin B3 in co-immunoprecipitation studies. Overall, these studies demonstrate that an integrated method of prediction can be used at the genome level for discovering many unknown protein binding partners with known ligand binding domains.     

Structure prediction of membrane proteins

There is a large gap between the number of membrane protein (MP) sequences and that of their decoded 3D structures, especially high-resolution structures, due to difficulties in crystal preparation of MPs. However, detailed knowledge of the 3D structure is required for the fundamental understanding of the function of an MP and the interactions between the protein and its inhibitors or activators. In this paper, some computational approaches that have been used to predict MP structures are discussed and compared.     

Genome-wide identification of protein binding sites on RNAs in mammalian cells

RNA-binding proteins (RBPs) are proteins that bind to the RNA and participate in forming ribonucleoprotein complexes. They have crucial roles in various biological processes such as RNA splicing, editing, transport, maintenance, degradation, intracellular localization and translation. The RBPs bind RNA with different RNA-sequence specificities and affinities, thus, identification of protein binding sites on RNAs (R-PBSs) will deeper our understanding of RNA-protein interactions. Currently, high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP, also known as CLIP-Seq) is one of the most powerful methods to map RNA-protein binding sites or RNA modification sites. However, this method is only used for identification of single known RBPs and antibodies for RBPs are required. Here we developed a novel method, called capture of protein binding sites on RNAs (RPBS-Cap) to identify genome-wide protein binding sites on RNAs without using antibodies. Double click strategy is used for the RPBS-Cap assay. Proteins and RNAs are UV-crosslinked in vivo first, then the proteins are crosslinked to the magnetic beads. The RNA elements associated with proteins are captured, reverse transcribed and sequenced. Our approach has potential applications for studying genome-wide RNA-protein interactions.     

Organic phase separation opens up new opportunities to interrogate the RNA-binding proteome

Protein–RNA interactions regulate all aspects of RNA metabolism and are crucial to the function of catalytic ribonucleoproteins. Until recently, the available technologies to capture RNA-bound proteins have been biased toward poly(A) RNA-binding proteins (RBPs) or involve molecular labeling, limiting their application. With the advent of organic–aqueous phase separation–based methods, we now have technologies that efficiently enrich the complete suite of RBPs and enable quantification of RBP dynamics. These flexible approaches to study RBPs and their bound RNA open up new research avenues for systems-level interrogation of protein–RNA interactions.     

New approaches to target RNA binding proteins

RNA binding proteins (RBPs) are a large and diverse class of proteins that regulate all aspects of RNA biology. As RBP dysregulation has been implicated in a number of human disorders, including cancers and neurodegenerative disease, small molecule chemical probes that target individual RBPs represent useful tools for deciphering RBP function and guiding the production of new therapeutics. While RBPs are often thought of as tough-to-drug, the discovery of a number of small molecules that target RBPs has spurred considerable recent interest in new strategies for RBP chemical probe discovery. Here we review current and emerging technologies for high throughput RBP-small molecule screening that we expect will help unlock the full therapeutic potential of this exciting protein class.     

mRNPs take shape by CLIPPING and PAIRING

The interaction of RNA-binding proteins (RBPs) with RNA is a crucial aspect of normal cellular metabolism. Yet, the diverse number of RBPs and RNA motifs to which they bind, the wide range of interaction strengths and the fact that RBPs associate in dynamic complexes have made it challenging to determine whether a particular RNA-binding protein binds a particular RNA. Recent work by three different laboratories has led to the development of new tools to query such interactions in the more physiological environs of cultured cells. The use of these methods has led to insights into (1) the networks of RNAs regulated by a particular protein, (2) the identification of new protein partners within messenger ribonucleoprotein particles and (3) the flux of RNA-binding proteins on an mRNA throughout its lifecycle. Here, I examine these new methods and discuss their relative strengths and current limitations.     

Insights into RNA biology from an atlas of mammalian mRNA-binding proteins

RNA-binding proteins (RBPs) determine RNA fate from synthesis to decay. Employing two complementary protocols for covalent UV crosslinking of RBPs to RNA, we describe a systematic, unbiased, and comprehensive approach, termed "interactome capture," to define the mRNA interactome of proliferating human HeLa cells. We identify 860 proteins that qualify as RBPs by biochemical and statistical criteria, adding more than 300 RBPs to those previously known and shedding light on RBPs in disease, RNA-binding enzymes of intermediary metabolism, RNA-binding kinases, and RNA-binding architectures. Unexpectedly, we find that many proteins of the HeLa mRNA interactome are highly intrinsically disordered and enriched in short repetitive amino acid motifs. Interactome capture is broadly applicable to study mRNA interactome composition and dynamics in varied biological settings.     

紫外交联合并串联亲和纯化高效鉴定蛋白复合物组分的RNA结合活性

RNA结合蛋白在RNA的生成与代谢中发挥着重要作用.我们在近年报道的PAR-CLIP(photoactivatableribonucleoside-enhanced crosslinking and immunoprecipitation)技术的基础上建立了一套快速、有效鉴定RNA结合蛋白的实验方法:以串联亲和纯化替代一步免疫沉淀获得高纯度蛋白-RNA复合物;将Sypro Ruby蛋白染色与RNA放射自显影相结合判断复合物中哪种或哪些组分为RNA结合蛋白,该方法命名为紫外交联合并的串联亲和纯化(cross-linkingand tandem affinity purification,CLiTAP).运用该方法对布氏锥虫的三种锌指蛋白ZC3H7、ZC3H34和ZC3H5进行分析,发现ZC3H7作为帽结合蛋白复合物的核心组分具有很强的RNA结合能力;ZC3H34结合RNA能力较弱,但其互作蛋白具有强的RNA结合活性;相比之下,ZC3H5及其复合物组分皆无RNA结合活性.这些结果表明,CLiTAP与蛋白质鉴定方法相结合,能够有效鉴定靶蛋白复合物中的RNA结合蛋白种类,也为进一步定位RNA结合位点、研究RNA结合蛋白的结构及作用机制奠定了基础.     

High throughput platform to explore RNA–protein interactomes

RNA binding proteins (RBPs) and RNA interaction is an emerging topic in molecular biology. Many reports showed that such interactions contribute to many cellular processes as well as disease development. Several standard in vitro and in vivo methods were developed to fulfill the needs of this RBP–RNA interaction study to explore their biological functions. However, these methods have their limitations in terms of throughput. In this review, we emphasize two important high throughput methods to studying RBP–RNA interactions, affinity purification and protein microarray. These methods have recently become robust techniques regarding their efficiency in systematically analyzing RBP–RNA interactions. Here, we provide technique overviews, strategies and applications of these methods during biological research. Although these technologies are just beginning to be explored, they will be most important methods in this study.