Integrated microRNA–mRNA analysis of coronary artery disease

Although patients with coronary artery disease (CAD) have a high mortality rate, the pathogenesis of CAD is still poorly understood. The purpose of this study was to explore the underlying molecular mechanisms and potential target molecules for CAD. The platelet miRNA (GSE28858) and blood mRNA (GSE42148) expression profiles of patients with CAD and healthy controls were downloaded from Gene Expression Omnibus. Differentially expressed miRNAs and genes (DEGs) were identified by significant analysis of microarray algorithm after data preprocessing. Furthermore, the miRNA-target gene regulatory network was constructed based on miRecords database. The spearman correlation coefficients (ρ) between miRNAs and their target genes were calculated. Six up- (miR-340, miR-545, miR-451, miR454-5p, miR-624 and miR-585) and four down-regulated (miR-199a, miR-17-3p, miR-154 and miR-339) miRNAs were screened. Total 295 target genes of miR-545, miR-451, miR-585 and miR-154 were predicted. Among these 295 target genes, 7 genes were DEGs. Further analysis showed miR-545-TFEC and miR-585-SPOCK1 were highly positively correlated (ρ = 0.808091264; ρ = 0.874680776) in CAD samples. Therefore, differentially expressed miRNAs might participate in the pathogenesis of CAD by regulating their target genes.     

Rational design of microRNA–siRNA chimeras for multifunctional target suppression

MicroRNAs (miRNAs) are involved in a variety of human diseases by simultaneously suppressing many gene targets. Thus, the therapeutic value of miRNAs has been intensely studied. However, there are potential limitations with miRNA-based therapeutics such as a relatively moderate impact on gene target regulation and cellular phenotypic control. To address these issues, we proposed to design new chimeric small RNAs (aiRNAs) by incorporating sequences from both miRNAs and siRNAs. These aiRNAs not only inherited functions from natural miRNAs, but also gained new functions of gene knockdown in an siRNA-like fashion. The improved efficacy of multifunctional aiRNAs was demonstrated in our study by design and testing of an aiRNA that inherited the functions of both miR-200a and an AKT1-targeting siRNA for simultaneous suppression of cancer cell motility and proliferation. The general principles of aiRNA design were further validated by engineering new aiRNAs mimicking another miRNA, miR-9. By regulating multiple cellular functions, aiRNAs could be used as an improved tool over miRNAs to target disease-related genes, thus alleviating our dependency on a limited number of miRNAs for the development of RNAi-based therapeutics.     

Targeted and proteome-wide analysis of metabolite–protein interactions

Understanding the molecular mechanisms of endogenous and environmental metabolites is crucial for basic biology and drug discovery. With the genome, proteome, and metabolome of many organisms being readily available, researchers now have the opportunity to dissect how key metabolites regulate complex cellular pathways in vivo. Nonetheless, characterizing the specific and functional protein targets of key metabolites associated with specific cellular phenotypes remains a major challenge. Innovations in chemical biology are now poised to address this fundamental limitation in physiology and disease. In this review, we highlight recent advances in chemoproteomics for targeted and proteome-wide analysis of metabolite–protein interactions that have enabled the discovery of unpredicted metabolite–protein interactions and facilitated the development of new small molecule therapeutics.     

Novel approaches to map small molecule–target interactions

The quest for small molecule perturbators of protein function or a given cellular process lies at the heart of chemical biology and pharmaceutical research. Bioactive compounds need to be extensively characterized in the context of the modulated protein(s) or process(es) in living systems to unravel and confirm their mode of action. A crucial step in this workflow is the identification of the molecular targets for these small molecules, for which a generic methodology is lacking. Herein we summarize recently developed approaches for target identification spurred by advances in omics techniques and chemo- and bioinformatics analysis.     

Systems for the detection and analysis of protein–protein interactions

The analysis of protein–protein interactions is important for developing a better understanding of the functional annotations of proteins that are involved in various biochemical reactions in vivo. The discovery that a protein with an unknown function binds to a protein with a known function could provide a significant clue to the cellular pathway concerning the unknown protein. Therefore, information on protein–protein interactions obtained by the comprehensive analysis of all gene products is available for the construction of interactive networks consisting of individual protein–protein interactions, which, in turn, permit elaborate biological phenomena to be understood. Systems for detecting protein–protein interactions in vitro and in vivo have been developed, and have been modified to compensate for limitations. Using these novel approaches, comprehensive and reliable information on protein–protein interactions can be determined. Systems that permit this to be achieved are described in this review.K. Kuroda, M. Kato and J. Mima contributed equally to this work.     

Importance of phospholipid bilayer integrity in the analysis of protein–lipid interactions

The integrity of supported phospholipid bilayer membranes is of crucial importance for the investigation of lipid–protein interactions. Therefore we recorded the formation of supported membranes on SiO₂ and mica by quartz crystal microbalance and controlled the integrity by atomic force microscopy. This study aims to analyze how membrane defects affect protein–lipid interactions. The experiments focused on a lipid mixture of POPC/DOPC/Chol/POPS/PI(4,5)P₂ (37:20:20:20:3) and the binding of the peripheral membrane associated protein annexin A2. We found that formation of a continuous undisturbed bilayer is an indispensable precondition for a reliable determination and quantification of lipid–protein-interactions. If membrane defects were present, protein adsorption causes membrane disruption and lipid detachment on a support thus leading to false determination of binding constants. Our results obtained for PI(4,5)P₂ and cholesterol containing supported membranes yield new knowledge to construct functional surfaces that may cover nanoporous substrates, form free standing membranes or may be used for lab-on-a-chip applications.     

Characterisation of aptamer–target interactions by branched selection and high-throughput sequencing of SELEX pools

Nucleic acid aptamer selection by systematic evolution of ligands by exponential enrichment (SELEX) has shown great promise for use in the development of research tools, therapeutics and diagnostics. Typically, aptamers are identified from libraries containing up to 10¹⁶ different RNA or DNA sequences by 5–10 rounds of affinity selection towards a target of interest. Such library screenings can result in complex pools of many target-binding aptamers. New high-throughput sequencing techniques may potentially revolutionise aptamer selection by allowing quantitative assessment of the dynamic changes in the pool composition during the SELEX process and by facilitating large-scale post-SELEX characterisation. In the present study, we demonstrate how high-throughput sequencing of SELEX pools, before and after a single round of branched selection for binding to different target variants, can provide detailed information about aptamer binding sites, preferences for specific target conformations, and functional effects of the aptamers. The procedure was applied on a diverse pool of 2′-fluoropyrimidine-modified RNA enriched for aptamers specific for the serpin plasminogen activator inhibitor-1 (PAI-1) through five rounds of standard selection. The results demonstrate that it is possible to perform large-scale detailed characterisation of aptamer sequences directly in the complex pools obtained from library selection methods, thus without the need to produce individual aptamers.     

Comparative analysis of Leishmania exoproteomes: Implication for host–pathogen interactions

Leishmaniasis is a vector-borne disease caused by the protozoa Leishmania. We have analyzed and compared the sequences of three experimental exoproteomes of Leishmania promastigotes from different species to determine their specific features and to identify new candidate proteins involved in interactions of Leishmania with the host. The exoproteomes differ from the proteomes by a decrease in the average molecular weight per protein, in disordered amino acid residues and in basic proteins. The exoproteome of the visceral species is significantly enriched in sites predicted to be phosphorylated as well as in features frequently associated with molecular interactions (intrinsic disorder, number of disordered binding regions per protein, interaction and/or trafficking motifs) compared to the other species. The visceral species might thus have a larger interaction repertoire with the host than the other species. Less than 10% of the exoproteomes contain heparin-binding and RGD sequences, and ~ 30% the host targeting signal RXLXE/D/Q. These latter proteins might thus be exported inside the host cell during the intracellular stage of the infection. Furthermore we have identified nine protein families conserved in the three exoproteomes with specific combinations of Pfam domains and selected eleven proteins containing at least three interaction and/or trafficking motifs including two splicing factors, phosphomannomutase, 2,3-bisphosphoglycerate-independent phosphoglycerate mutase, the paraflagellar rod protein-1D and a putative helicase. Their role in host–Leishmania interactions warrants further investigation but the putative ATP-dependent DEAD/H RNA helicase, which contains numerous interaction motifs, a host targeting signal and two disordered regions, is a very promising candidate.     

Single-cell genomics-based analysis of virus–host interactions in marine surface bacterioplankton

Viral infections dynamically alter the composition and metabolic potential of marine microbial communities and the evolutionary trajectories of host populations with resulting feedback on biogeochemical cycles. It is quite possible that all microbial populations in the ocean are impacted by viral infections. Our knowledge of virus–host relationships, however, has been limited to a minute fraction of cultivated host groups. Here, we utilized single-cell sequencing to obtain genomic blueprints of viruses inside or attached to individual bacterial and archaeal cells captured in their native environment, circumventing the need for host and virus cultivation. A combination of comparative genomics, metagenomic fragment recruitment, sequence anomalies and irregularities in sequence coverage depth and genome recovery were utilized to detect viruses and to decipher modes of virus–host interactions. Members of all three tailed phage families were identified in 20 out of 58 phylogenetically and geographically diverse single amplified genomes (SAGs) of marine bacteria and archaea. At least four phage–host interactions had the characteristics of late lytic infections, all of which were found in metabolically active cells. One virus had genetic potential for lysogeny. Our findings include first known viruses of Thaumarchaeota, Marinimicrobia, Verrucomicrobia and Gammaproteobacteria clusters SAR86 and SAR92. Viruses were also found in SAGs of Alphaproteobacteria and Bacteroidetes. A high fragment recruitment of viral metagenomic reads confirmed that most of the SAG-associated viruses are abundant in the ocean. Our study demonstrates that single-cell genomics, in conjunction with sequence-based computational tools, enable in situ, cultivation-independent insights into host–virus interactions in complex microbial communities.     

Structural analysis of protein–protein interactions in type I polyketide synthases

Abstract

Polyketide synthases (PKSs) are responsible for synthesizing a myriad of natural products with agricultural, medicinal relevance. The PKSs consist of multiple functional domains of which each can catalyze a specified chemical reaction leading to the synthesis of polyketides. Biochemical studies showed that protein–substrate and protein–protein interactions play crucial roles in these complex regio-/stereo-selective biochemical processes. Recent developments on X-ray crystallography and protein NMR techniques have allowed us to understand the biosynthetic mechanism of these enzymes from their structures. These structural studies have facilitated the elucidation of the sequence–function relationship of PKSs and will ultimately contribute to the prediction of product structure. This review will focus on the current knowledge of type I PKS structures and the protein–protein interactions in this system.     

Current trends in endotoxin detection and analysis of endotoxin–protein interactions

Endotoxin is a type of pyrogen that can be found in Gram-negative bacteria. Endotoxin can form a stable interaction with other biomolecules thus making its removal difficult especially during the production of biopharmaceutical drugs. The prevention of endotoxins from contaminating biopharmaceutical products is paramount as endotoxin contamination, even in small quantities, can result in fever, inflammation, sepsis, tissue damage and even lead to death. Highly sensitive and accurate detection of endotoxins are keys in the development of biopharmaceutical products derived from Gram-negative bacteria. It will facilitate the study of the intermolecular interaction of an endotoxin with other biomolecules, hence the selection of appropriate endotoxin removal strategies. Currently, most researchers rely on the conventional LAL-based endotoxin detection method. However, new methods have been and are being developed to overcome the problems associated with the LAL-based method. This review paper highlights the current research trends in endotoxin detection from conventional methods to newly developed biosensors. Additionally, it also provides an overview of the use of electron microscopy, dynamic light scattering (DLS), fluorescence resonance energy transfer (FRET) and docking programs in the endotoxin–protein analysis.     

An efficiency analysis of high-order combinations of gene–gene interactions using multifactor-dimensionality reduction

Background

Multifactor dimensionality reduction (MDR) is widely used to analyze interactions of genes to determine the complex relationship between diseases and polymorphisms in humans. However, the astronomical number of high-order combinations makes MDR a highly time-consuming process which can be difficult to implement for multiple tests to identify more complex interactions between genes. This study proposes a new framework, named fast MDR (FMDR), which is a greedy search strategy based on the joint effect property.

Results

Six models with different minor allele frequencies (MAFs) and different sample sizes were used to generate the six simulation data sets. A real data set was obtained from the mitochondrial D-loop of chronic dialysis patients. Comparison of results from the simulation data and real data sets showed that FMDR identified significant gene–gene interaction with less computational complexity than the MDR in high-order interaction analysis.

Conclusion

FMDR improves the MDR difficulties associated with the computational loading of high-order SNPs and can be used to evaluate the relative effects of each individual SNP on disease susceptibility. FMDR is freely available at http://bioinfo.kmu.edu.tw/FMDR.rar.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1717-8) contains supplementary material, which is available to authorized users.     

180 Integrating structural and systems biology: structure-based prediction of protein–protein interactions on a genome-wide scale

The genome-wide identification of pairs of interacting proteins is an important step in the elucidation of cell regulatory mechanisms. To date, structural information has had only limited impact on genome-scale efforts to predict protein–protein interactions (PPIs). A new algorithm, PrePPI, will be introduced that combines structural information with nonstructural clues and that is comparable in accuracy to high-throughput experiments. The surprising effectiveness of three-dimensional structural information can be attributed to the use of homology models and the exploitation of both close and remote geometric relationships between proteins. More generally, the “structural BLAST” approach encapsulated in PrePPI significantly expands the range of application of protein structure in the annotation of protein function.     

Avidin–biotin-immobilized liposome column for chromatographic fluorescence on-line analysis of solute–membrane interactions

Unilamellar liposomes with entrapped fluorescent dye calcein were stably immobilized in gel beads by avidin–biotin-binding. The immobilized liposomes remained extremely stable upon storage and chromatographic runs. The immobilized calcein-entrapped liposomes were utilized for fluorescent analysis of solute–membrane interactions, which in some cases are too weak to be detected by chromatographic retardation. A liposome column was used as a sensitive probe to detect the interactions of membranes with pharmaceutical drugs, peptides and proteins. Retardation of the solutes was monitored using a UV detector. Perturbation of the membranes, reflected as leakage of the entrapped calcein by some of the solutes, can thus be detected on-line using a flow-fluorescent detector. For the amphiphilic drugs or synthetic peptides, perturbation of membranes became more pronounced when the retardation (hydrophobicity) of the molecules increased. On the other hand, in the case of positively-charged peptides, polylysine, or partially denatured bovine carbonic anhydrase, significant dye leakage from the liposomes was observed although the retardation was hardly to be measured. Weak protein–membrane interactions can thus be assumed from the large leakage of calcein from the liposomes. This provides additional useful information for solute–membrane interactions, as perturbation of the membranes was also indicated by avidin–biotin-immobilized liposome chromatography (ILC).     

High-efficiency recovery of target cells using improved yeast display system for detection of protein–protein interactions

We constructed a high-throughput screening (HTS) system for target cells based on the detection of protein–protein interactions by flow cytometric sorting due to the improvement in the yeast cell surface display system. Interaction model proteins, which are the ZZ domain derived from Staphylococcus aureus and the Fc part of human immunoglobulin G (IgG), were displayed on the yeast cell surface. We achieved a rapid and enhanced expression of these proteins as a result of adopting an appropriate yeast strain and a suitable promoter. The displayed ZZ domain had an ability to bind to rabbit IgG and the displayed Fc part to protein A. These were confirmed by flow cytometry and fluorescence microscopy. Furthermore, the cells displaying the ZZ domain or Fc part were isolated from the model libraries constructed by mixing the control yeast cells with the target yeast cells. The ratio of the target cells was increased from 0.0001% to more than 70% by two cycles of cell sorting. These results indicate that we can achieve a rapid and highly efficient isolation method for the target cells with FACSCalibur and that this method will further extend the application of flow cytometric sorting to library selections.