Protein-protein interaction analysis using an affinity peptide tag and hydrophilic polystyrene plate

A sandwich ELISA method using peptide tags showing a specific affinity to a hydrophilic polystyrene surface (PS-tags), PS 19 composed of RAFIASRRIKRP and KPS19R10 of KRAFIASRRIRRP and a hydrophilic polystyrene (phi-PS) plate was used to analyze protein-protein interactions. An Escherichia coli cysteine synthase complex, in which serine acetyltransferase (SAT) interacts with O-acetylserine sulfhydrylase-A (OASS) was used as a model system. When the interaction was detected by the conventional sandwich ELISA method using a hydrophobic polystyrene (pho-PS) plate, for the exclusive use of ELISA, the signal intensity was barely detectable due to conformational change of the ligand protein, OASS in the adsorbed state. On the contrary, when OASS, genetically fused with PS19 (OASS-PS19) or chemically conjugated with KPS19R10 (OASS-KPS19R10), was immobilized on the phi-PS plate, a high signal intensity was detected. Furthermore, by applying the two-step sandwich ELISA, in which OASS-PS19 or OASS-KPS19R10 formed a complex with SAT in the blocking solution before immobilization on the phi-PS plate, the signal intensity was further increased with a much shorter operational time, because SAT in the blocking solution formed a complex with OASS-PS19 or OASS-KPS19R10 without any steric hindrance.     

Modelling molecular interaction pathways using a two-stage identification algorithm

In systems biology, molecular interactions are typically modelled using white-box methods, usually based on mass action kinetics. Unfortunately, problems with dimensionality can arise when the number of molecular species in the system is very large, which makes the system modelling and behavior simulation extremely difficult or computationally too expensive. As an alternative, this paper investigates the identification of two molecular interaction pathways using a black-box approach. This type of method creates a simple linear-in-the-parameters model using regression of data, where the output of the model at any time is a function of previous system states of interest. One of the main objectives in building black-box models is to produce an optimal sparse nonlinear one to effectively represent the system behavior. In this paper, it is achieved by applying an efficient iterative approach, where the terms in the regression model are selected and refined using a forward and backward subset selection algorithm. The method is applied to model identification for the MAPK signal transduction pathway and the Brusselator using noisy data of different sizes. Simulation results confirm the efficacy of the black-box modelling method which offers an alternative to the computationally expensive conventional approach.     

Quantitative analysis of cell surface antigen-antibody interaction using Gaussia princeps luciferase antibody fusion proteins

Cell surface antigen-specific antibodies are of substantial diagnostic and therapeutic importance. The binding properties of such antibodies are usually evaluated by cell-free assays, in particular surface plasmon resonance (SPR) analysis, or flow cytometry. SPR analyses allow the detailed quantitative and dynamic evaluation of the binding properties of antibodies, but need purified, typically recombinantly produced antigens. It can, however, be difficult to produce the required antigen. Furthermore, cellular factors influencing the antigen-antibody interaction are not considered by this method. Flow cytometry-based analyses do not have these limitations, but require elaborated calibration controls for absolute quantification of bound molecules. To overcome the limitations of SRP and flow cytometry in the characterization of cell surface antigen-specific antibodies, we developed Fn14-specific antibody 18D1 as an example of an antibody fusion protein format that includes the luciferase of Gaussia princeps (GpL), which enables very simple and highly sensitive cellular binding studies. We found that GpL-tagging of the C-terminus of the antibody light chain does not affect the interaction of 18D1-IgG1 with its antigen and Fc-gamma receptors (FcγRs). In accordance with this, the GpL_(LC-CT)-18D1-IgG1 antibody fusion protein showed basically the same FcγR-dependent agonistic properties as the parental 18D1 antibody. Similar results were obtained with isotype switch variants of 18D1 and antibodies specific for CD95, LTβR and CD40. In sum, we demonstrate that antibody GpL fusion proteins are easily manageable and versatile tools for the characterization of cell surface antigen-antibody interactions that have the potential to considerably extend the instrumentarium for the evaluation of antibodies.     

Screening and identification of ClpE interaction proteins in Streptococcus pneumoniae by a bacterial two-hybrid system and co-immunoprecipitation

Hsp100/Clp proteins have crucial functions in the protein quality control, stress tolerance, and virulence of many pathogenic bacteria. ClpE is an important virulence factor involved in adherence and invasion in Streptococcus pneumoniae. To explore the underlying mechanism, we screened ClpE interaction proteins using a bacterial two-hybrid system and co-immunoprecipitation. We used ClpE as bait and constructed the pBT-ClpE bait plasmid for two-hybrid screening. Then, we constructed ClpE::GFP fusion for co-immunoprecipitation screening using anti-GFP monoclonal antibody. We obtained eight potential ClpE interaction proteins, including carbamoyl-phosphate synthase, pyruvate oxidase (SpxB), phosphoenolpyruvate-protein phosphotransferase, aminopeptidase N (pepN), L-lactate dehydrogenase, ribosomal protein S4, sensor histidine kinase (SPD_2019), and FtsW (a cell division protein). FtsW, SpxB, pepN, and SPD_2019 were confirmed to interact with ClpE using Bacterial Two-hybrid or Co-immunoprecipitation. Morphologic observations found that ΔclpE strain existed in abnormal division. β-Galactosidase activity assay suggested that ClpE contributed to the degradation of FtsW. Furthermore, FtsW could be induced by heat shock. The results suggested that ClpE might affect cell division by regulating the level of FtsW. These data may provide new insights in studying the role of ClpE in S. pneumoniae.     

Proteomic analysis and identification of Streptococcus pyogenes surface-associated proteins

Streptococcus pyogenes is a gram-positive human pathogen that causes a wide spectrum of disease, placing a significant burden on public health. Bacterial surface-associated proteins play crucial roles in host-pathogen interactions and pathogenesis and are important targets for the immune system. The identification of these proteins for vaccine development is an important goal of bacterial proteomics. Here we describe a method of proteolytic digestion of surface-exposed proteins to identify surface antigens of S. pyogenes. Peptides generated by trypsin digestion were analyzed by multidimensional tandem mass spectrometry. This approach allowed the identification of 79 proteins on the bacterial surface, including 14 proteins containing cell wall-anchoring motifs, 12 lipoproteins, 9 secreted proteins, 22 membrane-associated proteins, 1 bacteriophage-associated protein, and 21 proteins commonly identified as cytoplasmic. Thirty-three of these proteins have not been previously identified as cell surface associated in S. pyogenes. Several proteins were expressed in Escherichia coli, and the purified proteins were used to generate specific mouse antisera for use in a whole-cell enzyme-linked immunosorbent assay. The immunoreactivity of specific antisera to some of these antigens confirmed their surface localization. The data reported here will provide guidance in the development of a novel vaccine to prevent infections caused by S. pyogenes.     

A competitive assay of lipoprotein: proteoglycan interaction using a 96-well microtitration plate

A method for the microassay in vitro of lipoprotein: proteoglycan interactions is described. The wells of a plastic 96-well microtitration plate are coated with low density lipoprotein. A limiting quantity of biotin-conjugated proteoglycan is allowed to bind to each coated well, and the amount of the latter retained in wells is estimated spectrophotometrically through subsequent binding of alkaline phosphatase-conjugated avidin. Many of the incubation parameters (e.g., time, pH, salt concentration, divalent cations), which influence the extent of binding of biotin-conjugated proteoglycan, have been studied and optimized. The effect upon binding of introducing different levels of proteoglycans or lipoproteins at the interaction step can be measured readily. Thus, the orders of increasing relative binding affinities were found to be high density lipoprotein less than Lipoprotein (a) less than low density lipoprotein; rat chondrosarcoma proteoglycan less than bovine nasal cartilage proteoglycan less than human aorta proteoglycan; chondroitin 4-sulfate less than chondroitin 6-sulfate less than dermatan sulfate for lipoproteins, proteoglycans, and glycosaminoglycans, respectively.     

Yeast two-hybrid analysis of the origin recognition complex of Saccharomyces cerevisiae: interaction between subunits and identification of binding proteins

Origin recognition complex (ORC), a six-protein complex (Orc1p-6p), is the most likely initiator of chromosomal DNA replication in eukaryotes. Although ORC of Saccharomyces cerevisiae has been studied extensively from biochemical and genetic perspectives, its quaternary structure remains unknown. Previous studies suggested that ORC has functions other than DNA replication, such as gene silencing, but the molecular mechanisms of these functions have not been determined. In this study, we used yeast two-hybrid analysis to examine the interaction between ORC subunits and to search for ORC-binding proteins. As well as the known Orc4p-Orc5p interaction, we revealed strong interactions between Orc2p and Ord3p (2p-3p), Orc2p and Ord5p (2p-5p), Orc2p and Ord6p (2p-6p) and Orc3p and Ord6p (3p-6p) and weaker interactions between Orc1p and Ord4p (1p-4p), Orc3p and Ord4p (3p-4p), Orc2p and Ord3p (3p-5p) and Orc5p and Ord3p (5p-6p). These results suggest that 2p-3p-6p may form a core complex. Orc2p and Orc6p are phosphorylated in vivo, regulating initiation of DNA replication. However, replacing the phosphorylated amino acid residues with others that cannot be phosphorylated, or that mimic phosphorylation, did not affect subunit interactions. We also identified several proteins that interact with ORC subunits; Sir4p and Mad1p interact with Orc2p; Cac1p and Ykr077wp with Orc3p; Rrm3p and Swi6p with Orc5p; and Mih1p with Orc6p. We discuss roles of these interactions in functions of ORC.     

Virtual identification of essential proteins within the protein interaction network of yeast

Topological analysis of large scale protein-protein interaction networks (PINs) is important for understanding the organizational and functional principles of individual proteins. The number of interactions that a protein has in a PIN has been observed to be correlated with its indispensability. Essential proteins generally have more interactions than the nonessential ones. We show here that the lethality associated with removal of a protein from the yeast proteome correlates with different centrality measures of the nodes in the PIN, such as the closeness of a protein to many other proteins, or the number of pairs of proteins which need a specific protein as an intermediary in their communications, or the participation of a protein in different protein clusters in the PIN. These measures are significantly better than random selection in identifying essential proteins in a PIN. Centrality measures based on graph spectral properties of the network, in particular the subgraph centrality, show the best performance in identifying essential proteins in the yeast PIN. Subgraph centrality gives important structural information about the role of individual proteins, and permits the selection of possible targets for rational drug discovery through the identification of essential proteins in the PIN.     

Blue copper proteins: a comparative analysis of their molecular interaction properties

Blue copper proteins are type-I copper-containing redox proteins whose role is to shuttle electrons from an electron donor to an electron acceptor in bacteria and plants. A large amount of experimental data is available on blue copper proteins; however, their functional characterization is hindered by the complexity of redox processes in biological systems. We describe here the application of a semiquantitative method based on a comparative analysis of molecular interaction fields to gain insights into the recognition properties of blue copper proteins. Molecular electrostatic and hydrophobic potentials were computed and compared for a set of 33 experimentally-determined structures of proteins from seven blue copper subfamilies, and the results were quantified by means of similarity indices. The analysis provides a classification of the blue copper proteins and shows that (I) comparison of the molecular electrostatic potentials provides useful information complementary to that highlighted by sequence analysis; (2) similarities in recognition properties can be detected for proteins belonging to different subfamilies, such as amicyanins and pseudoazurins, that may be isofunctional proteins; (3) dissimilarities in interaction properties, consistent with experimentally different binding specificities, may be observed between proteins belonging to the same subfamily, such as cyanobacterial and eukaryotic plastocyanins; (4) proteins with low sequence identity, such as azurins and pseudoazurins, can have sufficient similarity to bind to similar electron donors and acceptors while having different binding specificity profiles.     

On-chip Escherichia coli culture, purification, and detection of expressed proteins

In a recent study, we reported the results of a rapid high-throughput expression analysis of the affinity-tagged proteins present in total cell lysates, using a surface plasmon resonance (SPR) imaging protein chip system. In this paper, we describe a novel method, which is able to sequentially carry out a recombinant Escherichia coli culture, as well as the detection and purification of the expressed proteins on a single microwell chip, fabricated on a two-dimensional thin gold film. Following the induction of the protein on the microwell chip, the E. coli cells were lysed on the chip via the addition of lysozymes, and the expressed glutathione S-transferase-fused green fluorescent protein (GST–GFP) was then purified on the chip via affinity interaction with the glutathionylated gold surface of the chip. Finally, the expressed protein was directly detected using the surface plasmon resonance (SPR) imaging system. This system saves a substantial amount of time, experimental resources, and labor, by allowing for the complicated and labor-intensive procedures inherent to the production of recombinant proteins to be conducted on a single microwell chip, simply and economically.M. Kim and S. Y. Lee contributed equally to this work.     

Proteome analysis of spermatogonia: identification of a first set of 53 proteins

During spermatogenesis, the various classes of germ cells synthesize proteins necessary for their own functioning and for regulation of the Sertoli cells. However, the nature of these proteins has been little studied, especially in spermatogonia, the germ stem cells. In this study, the electrophoretic patterns of high-resolution, silver-stained, two-dimensional polyacrylamide gels of intracellular spermatogonial protein extracts were studied by computerized gel image analysis. We detected 675 individual spots, some of which we identified by mass spectrometry and database searching. We present here a first set of 53 proteins identified. They include housekeeping proteins never before detected in spermatogonia, ten proteins previously detected in the reproductive tract but not in spermatogonia, including stathmin, a protein previously shown to be involved in cell proliferation and differentiation, and one new testicular protein named translationally controlled tumor protein (TCTP), also known as a growth-related protein. Immunohistochemistry demonstrated that the two latter proteins were indeed highly expressed in spermatogonia in situ, and their possible involvement in spermatogonial division and proliferation is currently under investigation in our laboratory. We conclude that this type of experimental strategy, known as proteomics, is a very powerful way to analyze germ cell proteins comprehensively and should rapidly greatly improve our understanding of spermatogenesis.     

A novel approach for the identification of protein-protein interaction with integral membrane proteins

Protein-protein interaction plays a major role in all biological processes. The currently available genetic methods such as the two-hybrid system and the protein recruitment system are relatively limited in their ability to identify interactions with integral membrane proteins. Here we describe the development of a reverse Ras recruitment system (reverse RRS), in which the bait used encodes a membrane protein. The bait is expressed in its natural environment, the membrane, whereas the protein partner (the prey) is fused to a cytoplasmic Ras mutant. Protein-protein interaction between the proteins encoded by the prey and the bait results in Ras membrane translocation and activation of a viability pathway in yeast. We devised the expression of the bait and prey proteins under the control of dual distinct inducible promoters, thus enabling a rapid selection of transformants in which growth is attributed solely to specific protein-protein interaction. The reverse RRS approach greatly extends the usefulness of the protein recruitment systems and the use of integral membrane proteins as baits. The system serves as an attractive approach to explore novel protein-protein interactions with high specificity and selectivity, where other methods fail.     

Interpreting genotype-by-environment interaction using redundancy analysis

Summary Methods for the interpretation of genotype-by-environment interaction in the presense of explicitly measured environmental variables can be divided into two groups. Firstly, methods that extract environmental characterizations from the data itself, which are subsequently related to measured environmental variables, e.g., regression on the mean or singular value decomposition of the matrix of residuals from additivity, followed by correlation, or regression, methods. Secondly, methods that incorporate measured environmental variables directly into the model, e.g., multiple regression of individual genotypical responses on environmental variables, or factorial regression in which a genotype-by-environment matrix is modelled in terms of concomitant variables for the environmental factor. In this paper a redundancy analysis is presented, which can be derived from the singular-value decomposition of the residuals from additivity by imposing the restriction on the environmental scores of having to be linear combinations of environmental variables. At the same time, redundancy analysis is derivable from factorial regression by rotation of the axes in the space spanned by the fitted values of the factorial regression, followed by a reduction of dimensionality through discarding the least explanatory axes. Redundancy analysis is a member of the second group of methods, and can be an important tool in the interpretation of genotype-by-environment interaction, especially with reference to concomitant environmental information. A theoretical treatise of the method is given, followed by a practical example in which the results of the method are compared to the results of the other methods mentioned.     

Proteomic analysis and identification of aqueous humor proteins with a pathophysiological role in diabetic retinopathy

Diabetic retinopathy (DR) can cause irreversible blindness and is the severest microvascular complication in the eyes of patients with diabetic mellitus (DM). The identification of susceptibility factors contributing to development of DR is helpful for identifying predisposed patients and improving treatment efficacy. Although proteomics analysis is useful for identifying protein markers related to diseases, it has never been used to explore DR-associated susceptibility factors in the aqueous humor (AH). To better understand the pathophysiology of DR and to identify DR-associated risk factors, a gel-based proteomics analysis was performed to compare AH protein profiles of DM patients with and without development of DR. MALDI-TOF MS was then performed to identify protein spots that were differentially expressed between the two groups and western blot analysis was used to validate the expressional change of protein demonstrated by proteomics. Our proteomics and bioinformatics analysis identified 11 proteins differentially expressed between DR and control groups. These proteins are linked to biological networks associated with nutrition transport, microstructure reorganization, angiogenesis, anti-oxidation, and neuroprotection. The data may provide potential AH biomarkers and susceptibility factors for predicting DR development, and provide an insight into the underlying pathophysiological mechanisms of DR. This article is part of a Special Issue entitled: Proteomics: The clinical link.     

De novo identification of mammalian ciliary motility proteins using cryo-EM

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