Selection of substrate recognition sequence of protein kinase with ferric chelation affinity chromatography

Protein kinase substrate phage (PKS phage) was constructed by fusing the substrate recognition consensus sequence of cAMP-dependent protein kinase (cAPK) with bacteriophage minor coat protein g3p and by dis-playing it on the surface of filamentous bacteriophage fd. Phosphorylation in vitro by cAPK showed a unique labelled band of approximately 60 ku, which was consistent with the molecular weight of the PKS-g3p fusion protein. Some weakly phosphorylated bands for both PKS phage and wild-type phage were also observed. Phage display random 15-mer peptide library phosphorylated by cAPK was selected with ferric (Fe3 ) chelalion affinity resin. After 4 rounds of screening, phage clones were picked out to determine the displayed peptide sequences by DNA sequencing. The results showed that 5 of 14 sequenced phages displayed the cAPK recognition sequence motif (R)RXS/T. Their in vitro phosphorylation analyses revealed the specific labelled bands corresponding to the positive PKS phages with and without the typ     

Metagenomic Surveys of Gut Microbiota

Gut microbiota of higher vertebrates is host-specific. The number and diversity of the organisms residing within the gut ecosystem are defined by physiological and environmental factors,such as host genotype, habitat, and diet. Recently, culture-independent sequencing techniques have added a new dimension to the study of gut microbiota and the challenge to analyze the large volume of sequencing data is increasingly addressed by the development of novel computational tools and methods. Interestingly, gut microbiota maintains a constant relative abundance at operational taxonomic unit(OTU) levels and altered bacterial abundance has been associated with complex diseases such as symptomatic atherosclerosis, type 2 diabetes, obesity, and colorectal cancer. Therefore, the study of gut microbial population has emerged as an important field of research in order to ultimately achieve better health. In addition, there is a spontaneous, non-linear, and dynamic interaction among different bacterial species residing in the gut. Thus, predicting the influence of perturbed microbe–microbe interaction network on health can aid in developing novel therapeutics. Here, we summarize the population abundance of gut microbiota and its variation in different clinical states,computational tools available to analyze the pyrosequencing data, and gut microbe–microbe interaction networks.     

Study on interaction between microtubule associated protein tau and prion protein

Microtubule-associated protein tau is considered to play roles in many neurodegenera-tive diseases including some transmissible spongiform encephalopathies.To address the possible molecular linkage of prion protein(PrP) and tau,a GST-fusion segment of human tau covering the three-repeat region and various PrP segments was used in the tests of GST pull-down and immuno-precipitation.We found tau protein interacted with various style prion proteins such as native prion protein(PrPC) or protease-resistant isoform(PrPSc) .Co-localization signals of tau and PrP were found in the CHO cell tranfected with both PrP and tau gene.The domain of interaction with tau was located at N-terminal of PrP(residues 23 to 91) .The evidence of molecular interactions between PrP and tau protein highlights a potential role of tau in the biological function of PrP and the pathogenesis of TSEs.     

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.     

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.     

Interactome Mapping: Using Protein Microarray Technology to Reconstruct Diverse Protein Networks

A major focus of systems biology is to characterize interactions between cellular components, in order to develop an accurate picture of the intricate networks within biological systems. Over the past decade, protein microarrays have greatly contributed to advances in proteomics and are becoming an important platform for systems biology. Protein microarrays are highly flexible, ranging from large-scale proteome microarrays to smaller customizable microarrays, making the technology amenable for detection of a broad spectrum of biochemical properties of proteins. In this article, we will focus on the numerous studies that have utilized protein microarrays to reconstruct biological networks including protein-DNA interactions, posttranslational protein modifications (PTMs), lectin-glycan recognition, pathogen-host interactions and hierarchical signaling cascades. The diversity in applications allows for integration of interaction data from numerous molecular classes and cellular states, providing insight into the structure of complex biological systems. We will also discuss emerging applications and future directions of protein microarray technology in the global frontier.     

DGMP: Identifying Cancer Driver Genes by Jointing DGCN and MLP from Multi-omics Genomic Data

Identification of cancer driver genes plays an important role in precision oncology research, which is helpful to understand cancer initiation and progression. However, most existing computational methods mainly used the protein–protein interaction(PPI) networks, or treated the directed gene regulatory networks(GRNs) as the undirected gene–gene association networks to identify the cancer driver genes, which will lose the unique structure regulatory information in the directed GRNs, and then affe...     

Identification of interaction between HIV-1 glycoprotein 41 and integrase

Human immunodeficiency virus-1(HIV-1) encodes 15 viral proteins. Protein-protein interactions play a large role in the function of these proteins. In this study, we attempted to identify novel interactions between the HIV-1 proteins to better understand the role played by viral protein-protein interactions in the life cycle of HIV-1. Genes encoding the 15 viral proteins from the HIV-1 strain AD8 were inserted into the plasmids of a yeast two-hybrid system. By screening 120 pairs of proteins, interactions between seven pairs were found. This led to the discovery of an interaction between the HIV-1 proteins integrase(IN) and glycoprotein 41(gp41), which was confirmed by both co-immunoprecipitation(Co-IP) assays and fluorescence resonance energy transfer(FRET)imaging in live cells. In addition, it was found that the amino acids at positions 76–100 of gp41 are required for it to bind to IN. Deletion of this region from gp41 prevented its interaction with IN and reduced the production of HIV-1 in 293 T cells. This study provides new information on HIV-1protein-protein interactions which improves the understanding of the biological functions of gp41 and IN during the virus life cycle.     

Vaccination against very virulent infectious bursal disease virus using recombinant T4 bacteriophage displaying viral protein VP2

In order to develop a desirable inexpensive, effective and safe vaccine against the very virulent infectious bursal disease virus （vvIBDV）, we tried to take advantage of the emerging T4 bacteriophage surface protein display system. The major immunogen protein VP2 from the vvIBDV strain HK46 was fused to the nonessential T4 phage surface capsid protein, a small outer capsid （SOC） protein, resulting in the 49 kDa SOC-VP2 fusion protein, which was verified by sodium dodecylsulfate polyacrylamide gel electrophoresis and Western blot. Immunoelectromicroscopy showed that the recombinant VP2 protein was successfully displayed on the surface of the T4 phage. The recombinant VP2 protein is antigenic and showed reactivities to various monoclonal antibodies （mAbs） against IBDV, whereas the wild-type phage T4 could not react to any mAb. In addition, the recombinant VP2 protein is immunogenic and elicited specific antibodies in immunized specific pathogen free （SPF） chickens. More significantly, immunization of SPF chickens with the recombinant T4-VP2 phage protected them from infection by the vvIBDV strain HK46. When challenged with the vvIBDV strain HK46 at a dose of 100 of 50% lethaldose （LD50） per chicken 4 weeks after the booster was given, the group vaccinated with the T4-VP2 recombinant phage showed no clinical signs of disease or death, whereas the unvaccinated group and the group vaccinated with the wild-type T4 phage exhibited 100% clinical signs of disease and bursal damages, and 30%-40% mortality. Collectively, the data herein showed that the T4-displayed VP2 protein might be an inexpensive, effective and safe vaccine candidate against vvIBDV.     

Rearrangement of Actin Cytoskeleton by Zika Virus Infection Facilitates Blood–Testis Barrier Hyperpermeability

In recent years,various serious diseases caused by Zika virus (ZIKV) have made it impossible to be ignored.Confirmed existence of ZIKV in semen and sexually transmission of ZIKV suggested that it can break the blood–testis barrier (BTB),or Sertoli cell barrier (SCB).However,little is known about the underlying mechanism.In this study,interaction between actin,an important component of the SCB,and ZIKV envelope (E) protein domain Ⅲ (EDⅢ) was inferred from coimmunoprecipitation (Co-IP) liquid chromatography–tandem mass spectrometry (LC–MS/MS) analysis.Confocal microscopy confirmed the role of actin filaments (F-actin) in ZIKV infection,during which part of the stress fibers,the bundles that constituted by paralleled actin filaments,were disrupted and presented in the cell periphery.Colocalization of E and reorganized actin filaments in the cell periphery of transfected Sertoli cells suggests a participation of ZIKV E protein in ZIKV-induced F-actin rearrangement.Perturbation of F-actin by cytochalasin D (CytoD) or Jasplakinolide (Jas)enhanced the infection of ZIKV.More importantly,the transepithelial electrical resistance (TEER) of an in vitro mouse SCB (mSCB) model declined with the progression of ZIKV infection or overexpression of E protein.Co-IP and confocal microscopy analyses revealed that the interaction between F-actin and tight junction protein ZO-1 was reduced after ZIKV infection or E protein overexpression,highlighting the role of E protein in ZIKV-induced disruption of the BTB.We conclude that the interaction between ZIKV E and F-actin leads to the reorganization of F-actin network,thereby compromising BTB integrity.     

The Ti-TAN plasmid toolbox for TurboID-based proximity labeling assays in Nicotiana benthamiana

<正>Protein–protein interactions and the formation of protein complexes play a central role in the regulation of virtually all aspects of life. The identification and characterization of interactions between proteins is the basis of our understanding of protein function and the biological processes they enable. These molecular interactions, however, can display different degrees of strength and stability and,     

An Integrated Systems Biology Approach Identifies ZIKV and DENV Replication

The Zika virus(ZIKV) and dengue virus(DENV) flaviviruses exhibit similar replicative processes but have distinct clinical outcomes. A systematic understanding of virus–host protein–protein interaction networks can reveal cellular pathways critical to viral replication and disease pathogenesis. Here we employed three independent systems biology approaches toward this goal. First,protein array analysis of direct interactions between individual ZIKV/DENV viral proteins and20,240 human proteins revealed multiple conserved cellular pathways and protein complexes,including proteasome complexes. Second, an RNAi screen of 10,415 druggable genes identified the host proteins required for ZIKV infection and uncovered that proteasome proteins were crucial in this process. Third, high-throughput screening of 6016 bioactive compounds for ZIKV inhibition yielded 134 effective compounds, including six proteasome inhibitors that suppress both ZIKV and DENV replication. Integrative analyses of these orthogonal datasets pinpoint proteasomes as critical host machinery for ZIKV/DENV replication. Our study provides multi-omics datasets for further studies of flavivirus–host interactions, disease pathogenesis, and new drug targets.     

Identification of Risk Pathways and Functional Modules for Coronary Artery Disease Based on Genome-wide SNP Data

Coronary artery disease(CAD) is a complex human disease, involving multiple genes and their nonlinear interactions, which often act in a modular fashion. Genome-wide single nucleotide polymorphism(SNP) profiling provides an effective technique to unravel these underlying genetic interplays or their functional involvements for CAD. This study aimed to identify the susceptible pathways and modules for CAD based on SNP omics. First, the Wellcome Trust Case Control Consortium(WTCCC) SNP datasets of CAD and control samples were used to assess the jointeffect of multiple genetic variants at the pathway level, using logistic kernel machine regression model. Then, an expanded genetic network was constructed by integrating statistical gene–gene interactions involved in these susceptible pathways with their protein–protein interaction(PPI)knowledge. Finally, risk functional modules were identified by decomposition of the network. Of 276 KEGG pathways analyzed, 6 pathways were found to have a significant effect on CAD. Other than glycerolipid metabolism, glycosaminoglycan biosynthesis, and cardiac muscle contraction pathways, three pathways related to other diseases were also revealed, including Alzheimer's disease, non-alcoholic fatty liver disease, and Huntington's disease. A genetic epistatic network of 95 genes was further constructed using the abovementioned integrative approach. Of 10 functional modules derived from the network, 6 have been annotated to phospholipase C activity and cell adhesion molecule binding, which also have known functional involvement in Alzheimer's disease.These findings indicate an overlap of the underlying molecular mechanisms between CAD and Alzheimer's disease, thus providing new insights into the molecular basis for CAD and its molecular relationships with other diseases.     

LSL1 controls cell death and grain production by stabilizing chloroplast in rice

Lesion mutants can be valuable tools to reveal the interactions between genetic factors and environmental signals and to improve grain production. Here we identified a rice(Oryza sativa) mutant, lesion spotleaf1(lsl1), which produces necrotic leaf lesions throughout its life cycle. LSL1 encodes a protein of unknown function and belongs to a grass-specific clade. The lesion phenotype of the lsl1 mutant was sharply induced by shading, and its detached leaves incubated in 6-benzylamino purine simil...     

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 localization prediction, 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.     

Construction of a chloroplast protein interaction network and functional mining of photosynthetic proteins in Arabidopsis thaliana

Chloroplast is a typical plant cell organelle where photosynthesis takes place. In this study, a total of 1 808 chloroplast core proteins in Arabidopsis thaliana were reliably identified by combining the results of previously published studies and our own predictions. We then constructed a chloroplast protein interaction network primarily based on these core protein interactions. The network had 22 925 protein interaction pairs which involved 2 214 proteins. A total of 160 previously uncharacterized proteins were annotated in this network. The subunits of the photosynthetic complexes were modularized, and the functional relationships among photosystem Ⅰ （PSI）, photosystem Ⅱ （PSII）, light harvesting complex of photosystem Ⅰ （LHC Ⅰ） and light harvesting complex of photosystem Ⅰ （LHC Ⅱ） could be deduced from the predicted protein interactions in this network. We further confirmed an interaction between an unknown protein AT1G52220 and a photosynthetic subunit PSI-D2 by yeast two-hybrid analysis. Our chloroplast protein interaction network should be useful for functional mining of photosynthetic proteins and investigation of chloroplast-related functions at the systems biology level in Arabidopsis.     

Bayesian Peak Picking for NMR Spectra

Protein structure determination is a very important topic in structural genomics,which helps people to understand varieties of biological functions such as protein-protein interactions,protein–DNA interactions and so on.Nowadays,nuclear magnetic resonance(NMR) has often been used to determine the three-dimensional structures of protein in vivo.This study aims to automate the peak picking step,the most important and tricky step in NMR structure determination.We propose to model the NMR spectrum by a mixture of bivariate Gaussian densities and use the stochastic approximation Monte Carlo algorithm as the computational tool to solve the problem.Under the Bayesian framework,the peak picking problem is casted as a variable selection problem.The proposed method can automatically distinguish true peaks from false ones without preprocessing the data.To the best of our knowledge,this is the first effort in the literature that tackles the peak picking problem for NMR spectrum data using Bayesian method.     

The Functional Motif of SARS-CoV S Protein Involved in the Interaction with ACE2

SARS-CoV is a newly discovery pathogen causing severe acute respiratory problems. It has been established that the S protein in this pathogen plays an important rule in the adsorption and penetration of SARS-CoV into the host cell by interaction with the ACE2 receptor. To determinant which functional motif of the S protein was involved in the interaction with ACE2, seven truncated S proteins deleted from the N or C terminal were obtained by an E.coli expression system and purified by column chroma-tography to homogeneity. Each truncated S protein was fixed on to the well of an ELISA plate and an interaction was initiated with the ACE2 protein. The adsorption were quantified by ELISA, and the results indicated that amino acids from 388 to 496 of the S protein was responsible for the interaction with the ACE2 receptor, and the interaction could be completely disrupted by an antibody specific to these amino acids. Deletions adjacent to this domain did not appear to have a significant impact on the interaction with ACE2, suggesting that the S protein of SARS-CoV could be developed as a vaccine to prevent the spread of SARS-CoV.