Identification of 2-oxohistidine Interacting Proteins Using E. coli Proteome Chips
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Cellular proteins are constantly damaged by reactive oxygen species generated by cellular respiration. Because of its metal-chelating property, the histidine residue is easily oxidized in the presence of Cu/Fe ions and H2O2 via metal-catalyzed oxidation, usually converted to 2-oxohistidine. We hypothesized that cells may have evolved antioxidant defenses against the generation of 2-oxohistidine residues on proteins, and therefore there would be cellular proteins which specifically interact with this oxidized side chain. Using two chemically synthesized peptide probes containing 2-oxohistidine, high-throughput interactome screening was conducted using the E. coli K12 proteome microarray containing >4200 proteins. Ten interacting proteins were identified, and successfully validated using a third peptide probe, fluorescence polarization assays, as well as binding constant measurements. We discovered that 9 out of 10 identified proteins seemed to be involved in redox-related cellular functions. We also built the functional interaction network to reveal their interacting proteins. The network showed that our interacting proteins were enriched in oxido-reduction processes, ion binding, and carbon metabolism. A consensus motif was identified among these 10 bacterial interacting proteins based on bioinformatic analysis, which also appeared to be present on human S100A1 protein. Besides, we found that the consensus binding motif among our identified proteins, including bacteria and human, were located within α-helices and faced the outside of proteins. The combination of chemically engineered peptide probes with proteome microarrays proves to be an efficient discovery platform for protein interactomes of unusual post-translational modifications, and sensitive enough to detect even the insertion of a single oxygen atom in this case. Cellular proteins are constantly damaged by reactive oxygen species generated by cellular respiration. Because of its metal-chelating property, the histidine residue is easily oxidized in the presence of Cu/Fe ions and H2O2 via metal-catalyzed oxidation, usually converted to 2-oxohistidine. We hypothesized that cells may have evolved antioxidant defenses against the generation of 2-oxohistidine residues on proteins, and therefore there would be cellular proteins which specifically interact with this oxidized side chain. Using two chemically synthesized peptide probes containing 2-oxohistidine, high-throughput interactome screening was conducted using the E. coli K12 proteome microarray containing >4200 proteins. Ten interacting proteins were identified, and successfully validated using a third peptide probe, fluorescence polarization assays, as well as binding constant measurements. We discovered that 9 out of 10 identified proteins seemed to be involved in redox-related cellular functions. We also built the functional interaction network to reveal their interacting proteins. The network showed that our interacting proteins were enriched in oxido-reduction processes, ion binding, and carbon metabolism. A consensus motif was identified among these 10 bacterial interacting proteins based on bioinformatic analysis, which also appeared to be present on human S100A1 protein. Besides, we found that the consensus binding motif among our identified proteins, including bacteria and human, were located within α-helices and faced the outside of proteins. The combination of chemically engineered peptide probes with proteome microarrays proves to be an efficient discovery platform for protein interactomes of unusual post-translational modifications, and sensitive enough to detect even the insertion of a single oxygen atom in this case. The complexity of the proteome arises in a large part because of the hundreds of post-translational modifications (PTMs) 1The abbreviations used are:PTMpost-translational modificationMCOmetal-catalyzed oxidationRAGEreceptors for advanced glycation end-productsAβamyloid betaADAlzheimer's diseaseGOGene OntologyKEGGKyoto Encyclopedia of Genes and GenomesBSAbovine serum albuminTBSTTris-buffered saline with Tween 20Kddissociation constantAG peptideAGAQVAHGNEVAG, SE peptideSEAGVNHGSAGQAIA peptideIAVENVHAQGLAOxo-AG peptide, AG peptide with 2-oxohistidine residueOxo-SE peptideSE peptide with 2-oxohistidine residueOxo-IA peptideIA peptide with 2-oxohistidine residueNADPHdihydronicotinamide-adenine dinucleotide phosphate. already discovered. Many PTMs are enzyme-catalyzed, such as phosphorylation, glycosylation, or ubiquitination (1.Wold F. In vivo chemical modification of proteins (post-translational modification).Annu. Rev. 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For instance, 14-3-3 family protein can recognize protein phosphorylation motifs (5.Morrison D.K. The 14-3-3 proteins: integrators of diverse signaling cues that impact cell fate and cancer development.Trends Cell Biol. 2009; 19: 16-23Abstract Full Text Full Text PDF PubMed Scopus (490) Google Scholar) and various lectins can recognize protein glycosylation (6.Kilpatrick D.C. Animal lectins: a historical introduction and overview.Biochim. Biophys. Acta. 2002; 1572: 187-197Crossref PubMed Scopus (373) Google Scholar). However, recognition factors may also exist for nonenzymatic PTMs, such as receptor for advanced glycation end-products (RAGE) (7.Sparvero L.J. Asafu-Adjei D. Kang R. Tang D. Amin N. Im J. Rutledge R. Lin B. Amoscato A.A. Zeh H.J. Lotze M.T. RAGE (Receptor for Advanced Glycation Endproducts), RAGE ligands, and their role in cancer and inflammation.J. Transl. Med. 2009; 7: 17Crossref PubMed Scopus (446) Google Scholar). In this study we seek to uncover cellular binding factors for 2-oxohistidine, the oxidized product of histidine, which is an important but little-understood nonenzymatic PTM. post-translational modification metal-catalyzed oxidation receptors for advanced glycation end-products amyloid beta Alzheimer's disease Gene Ontology Kyoto Encyclopedia of Genes and Genomes bovine serum albumin Tris-buffered saline with Tween 20 dissociation constant AGAQVAHGNEVAG, SE peptide IA peptide Oxo-AG peptide, AG peptide with 2-oxohistidine residue SE peptide with 2-oxohistidine residue IA peptide with 2-oxohistidine residue dihydronicotinamide-adenine dinucleotide phosphate. The generation of ROS is an unavoidable consequence of cellular respiration, which leads to the oxidation of proteins, lipids, and nucleic acids (4.Davies M.J. The oxidative environment and protein damage.Biochim. Biophys. Acta. 2005; 1703: 93-109Crossref PubMed Scopus (1097) Google Scholar, 8.Muller F.L. Lustgarten M.S. Jang Y. Richardson A. Van Remmen H. Trends in oxidative aging theories.Free Radic. Biol. Med. 2007; 43: 477-503Crossref PubMed Scopus (845) Google Scholar). ROS play regulatory roles in cellular signaling pathways under low levels (9.Ray P.D. Huang B.W. Tsuji Y. Reactive oxygen species (ROS) homeostasis and redox regulation in cellular signaling.Cell Signal. 2012; 24: 981-990Crossref PubMed Scopus (2799) Google Scholar), but high levels of ROS are cytotoxic and lead to the accumulation of damaged cellular components (10.Martin K.R. Barrett J.C. Reactive oxygen species as double-edged swords in cellular processes: low-dose cell signaling versus high-dose toxicity.Hum. Exp. Toxicol. 2002; 21: 71-75Crossref PubMed Scopus (284) Google Scholar, 11.Jang Y.Y. Sharkis S.J. A low level of reactive oxygen species selects for primitive hematopoietic stem cells that may reside in the low-oxygenic niche.Blood. 2007; 110: 3056-3063Crossref PubMed Scopus (652) Google Scholar). The reactions of proteins with ROS may lead to almost 100 types of side chain modifications (12.Shacter E. Quantification and significance of protein oxidation in biological samples.Drug Metab. Rev. 2000; 32: 307-326Crossref PubMed Scopus (658) Google Scholar, 13.Xu G. Chance M.R. Hydroxyl radical-mediated modification of proteins as probes for structural proteomics.Chem. Rev. 2007; 107: 3514-3543Crossref PubMed Scopus (539) Google Scholar). Histidine is highly susceptible to ROS damage, because it has strong metal chelation affinity and often constitutes the binding site for metal ions (14.Tainer J.A. Roberts V.A. Getzoff E.D. Metal-binding sites in proteins.Curr. Opin. Biotechnol. 1991; 2: 582-591Crossref PubMed Scopus (120) Google Scholar, 15.Regan L. The design of metal-binding sites in proteins.Annu. Rev. Biophys. Biomol. Struct. 1993; 22: 257-287Crossref PubMed Scopus (145) Google Scholar). The presence of H2O2 and redox-active metals (Cu and Fe) can lead to metal-catalyzed oxidation (MCO, also called Fenton-type chemistry), which converts histidine side chain to 2-oxohistidine (16.Uchida K. Kawakishi S. Identification of oxidized histidine generated at the active site of Cu, Zn-superoxide dismutase exposed to H2O2. Selective generation of 2-oxo-histidine at the histidine 118.J. Biol. Chem. 1994; 269: 2405-2410Abstract Full Text PDF PubMed Google Scholar, 17.Lewisch S.A. Levine R.L. Determination of 2-oxohistidine by amino acid analysis.Anal. Biochem. 1995; 231: 440-446Crossref PubMed Scopus (56) Google Scholar). The conversion of histidine to 2-oxohistidine alters its charge state, hydrogen bonding property, and metal chelation affinity, and hence may have serious impacts on protein structure and function. The net reaction is oxygen insertion (+16 Da), which makes it an irreversible PTM. It is unclear if cells simply tolerate such damages on histidines or employ active mechanisms to recognize them and use them as redox sensors or as damage markers for promoting protein degradation. The only known biological function of 2-oxohistidine is to serve as a redox sensor on bacterial transcription factor PerR (18.Traore D.A. El Ghazouani A. Jacquamet L. Borel F. Ferrer J.L. Lascoux D. Ravanat J.L. Jaquinod M. Blondin G. Caux-Thang C. Duarte V. Latour J.M. Structural and functional characterization of 2-oxo-histidine in oxidized PerR protein.Nat. Chem. Biol. 2009; 5: 53-59Crossref PubMed Scopus (91) Google Scholar), whereas other studies have used 2-oxohistidine as a stable marker of protein damage during oxidative stress (12.Shacter E. Quantification and significance of protein oxidation in biological samples.Drug Metab. Rev. 2000; 32: 307-326Crossref PubMed Scopus (658) Google Scholar, 19.Davies M.J. Fu S. Wang H. Dean R.T. Stable markers of oxidant damage to proteins and their application in the study of human disease.Free Radic. Biol. Med. 1999; 27: 1151-1163Crossref PubMed Scopus (416) Google Scholar). Judging by the potential biological significance of 2-oxohistidine modification, we hypothesized that there may be cellular factors to recognize it. Previous research on 2-oxohistidine had been impeded by the difficulty in generating this side chain with reasonable yields. Recently, we managed to greatly improve the yield of 2-oxohistidine conversion by optimizing MCO reaction conditions using the copper/ascorbate system (20.Huang C.F. Liu Y.H. Tai H.C. Synthesis of peptides containing 2-oxohistidine residues and their characterization by liquid chromatography-tandem mass spectrometry.J. Pept. Sci. 2015; 21: 114-119Crossref PubMed Scopus (1) Google Scholar), allowing us to synthesize and purify peptide probes containing 100% 2-oxohistidine for this study. Here, we used 2-oxohistidine-containing peptides to mimic the oxidative conversion of histidine residues on native proteins. Then, we utilized the Escherichia coli (E. coli) K12 proteome chip to identify 2-oxohistidine-interacting proteins via high-throughput screening, and the interactors turned out to be largely involved redox-related metabolism. From the bacterial interactors we predicted a consensus binding motif, which could be validated across different species and correctly predicted S100A1 as a human binding factor for 2-oxohistidine. Thus, recognition of 2-oxohistidine appears to be an evolutionarily conserved capacity from bacteria to human. The high throughput protein expression, protein purification, and protein printing were modified from the previous study (21.Chen C.S. Korobkova E. Chen H. Zhu J. Jian X. Tao S.C. He C. Zhu H. A proteome chip approach reveals new DNA damage recognition activities in Escherichia coli.Nat. Methods. 2008; 5: 69-74Crossref PubMed Scopus (101) Google Scholar). Briefly, we expressed and purified E. coli K12 proteins in 96-well plate format and subsequently printed the proteome microarray. All purified proteins were spotted in duplicate on each aldehyde slide (BaiO, Shanghai, China) by SmartArrayer 136 (CapitalBio, Beijing, China) at 4 °C. After printing proteins, the proteome microarray chips were kept at 4 °C for protein immobilization on the slides for 12 h. The chips were stored at −80 °C before probing with samples. Solutions containing 1 mm peptide, 5 mm Cu2+ and 200 mm sodium ascorbate were exposed to air with gentle shaking at 37 °C for 24 h (AG and SE peptide) or 6 h (IA peptide). The oxidation reaction was quenched with 20 mm EDTA and analyzed by reverse-phase high-performance liquid chromatography (HPLC) (10–30% acetonitrile and 0.1% TFA in water, C18 column from Dr. Maisch, Ammerbuch, Germany) to determine the reaction yield. For liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis of crude reaction mixtures and HPLC fractions, 10 μl samples were acidified with 2 μl 10% TFA and desalted with ZipTip (Millipore, Billerica, MA) following manufacturer's protocols. Oxidized peptides were purified by semi-preparative HPLC (C18 column, Dr. Maisch). LC-MS/MS experiments were conducted under previously reported conditions (20.Huang C.F. Liu Y.H. Tai H.C. Synthesis of peptides containing 2-oxohistidine residues and their characterization by liquid chromatography-tandem mass spectrometry.J. Pept. Sci. 2015; 21: 114-119Crossref PubMed Scopus (1) Google Scholar). Oxidized and nonoxidized peptides were dissolved in 50 mm sodium borate buffer at pH 7.5 and analyzed by HPLC to determine peptide concentration by 210 nm absorbance. DyLight-conjugated NHS esters (Thermo, Waltham, MA) were dissolved in anhydrous DMF to 10 mg/ml and added to peptide solutions for 1 h incubation at room temperature, at the following fluorophore/peptide ratios: DyLight 650/AG = 3:1, DyLight 650/SE = 5:1, DyLight 650/oxo-IA = 1.5:1; DyLight 550/oxo-AG = 5:1, DyLight 550/oxo-SE = 7:1, DyLight 550/IA = 3:1. Labeled peptides were analyzed and purified by HPLC as described above. Labeled products were verified by LC-MS/MS, and quantified by absorbance measurements based on known fluorophore properties. The chips were first blocked with 3% bovine serum albumin (BSA) (Sigma, St. Louis, MO) for 5 min. DyLight 550-conjugated 2-oxohistidine peptide and DyLight 650-conjugated nonoxidized peptide (10 μm each) were probed together onto the chip with LifterSlips (Thermo) at room temperature for 45 min. Finally, the chips were washed by Tris-buffered saline-Tween 20 (TBST) on an orbital shaker three times and 5 min each time. The chip was dried by centrifugation and then scanned with a LuxScan microarray scanner (CapitalBio). Signal intensities, defined as foreground median subtracted by background median, were acquired and analyzed using GenePix Pro 6.0 software. Then, we used quantile normalization to normalize the signal intensity from both 2-oxohistidine containing probes and nonoxidized probes. To identify positive 2-oxohistidine interacting proteins, four cutoff criteria were set: (1) The signal from experimental group was >1.5 standard deviations above the mean for all experimental groups. (2) To identify large signal differences between experimental groups and negative controls, the delta, defined as signal difference between experimental group and control group, was >1.5 standard deviations above the mean for all deltas. (3) To exclude the nonspecific binding to 2-oxohistidine residue, the signal from the negative control was >1.5 standard deviations below the mean for all control groups. (4) To remove irreproducible hits among triplicate chip assays, the student's t test p values between experimental groups and negative controls were less than 0.05. The R programming language (22.Team R.C. R: A Language and Environment for Statistical Computing.R Foundation for Statistical Computing. 2015; Google Scholar) was used to display heat map. The data was presented by the signal intensity of foreground subtracted by background. The gplots package (23.Warnes G.R. Bolker B. Bonebakker L. Gentleman R. Huber W. Liaw A. Lumley T. Maechler M. Magnusson A. Moeller S. gplots: Various R programming tools for plotting data. 2009; (R package Version 2)Google Scholar) was used for classifying 2-oxohistidine containing peptides and nonoxidized peptides in hierarchy. The identified proteins were used for functional interaction analyses by using EcID (24.Andres Leon E. Ezkurdia I. Garcia B. Valencia A. Juan D. EcID. A database for the inference of functional interactions in E. coli.Nucleic Acids Res. 2009; 37: D629-D635Crossref PubMed Scopus (25) Google Scholar) and Cytoscape (25.Shannon P. Markiel A. Ozier O. Baliga N.S. Wang J.T. Ramage D. Amin N. Schwikowski B. Ideker T. Cytoscape: a software environment for integrated models of biomolecular interaction networks.Genome Res. 2003; 13: 2498-2504Crossref PubMed Scopus (25321) Google Scholar). Briefly, the files of EcID entities and EcID pairs were downloaded from EcID database. Before mapping identified proteins to their EcID entities and EcID pairs, we removed the pairs that were based on the prediction mode, such as phylogenetic profiles, gene neighborhood, mirror tree, in silico two-hybrid, or context mirror. After mapping, we used Cytoscape to generate the functional interaction network, and visualized the identified proteins and their interacting proteins. Subsequently, we used AmiGO 2 (26.Carbon S. Ireland A. Mungall C.J. Shu S. Marshall B. 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KEGG: kyoto encyclopedia of genes and genomes.Nucleic Acids Res. 2000; 28: 27-30Crossref PubMed Scopus (17971) Google Scholar) results, respectively. After blocking the 96-well black plate (Thermo) with 1% BSA at room temperature for 1 h, the identified proteins were added to the plate. The concentrations of 10 identified proteins (ThrS, YqjG, YajL, HemE, IlvA, PrpD, Zwf, Eda, Gor, and PqqL) were 12.0, 25.7, 10.7, 15.6, 3.4, 18.6, 19.5, 11.8, 26.1, and 5.9 μm, respectively. The concentrations of BSA, as a negative control, were identical to the protein being compared with. A 10 nm solution of DyLight 550-conjugated 2-oxohistidine peptide was incubated with target protein or BSA in a Micromixer MX4 (FINEPCR, Gunpo, Korea) at room temperature for 1 h. After incubation, the degree of polarization of each well was detected by a Synergy 2 (BioTek, Winooski, VT), using an excitation wavelength of 540 nm and an emission wavelength of 590 nm with a dichroic mirror of 570 nm. Identified proteins and S100A1 (Abnova, Taipei, Taiwan) were printed on aldehyde chips in a multiple-well format. After printing, the chips were immobilized at 4 °C for 12 h and then stored at −80 °C. The printed chips were blocked at room temperature for 5 min with 3% BSA. Two-fold serial-diluted DyLight 550-conjugated 2-oxohistidine peptides, DyLight 650-conjugated nonoxidized peptides, and quenched fluorescent dyes were added into the chip wells individually with Multi-Well Microarray Hybridization Cassettes (Arrayit, Sunnyvale, CA), and incubated at room temperature for 45 min. The fluorescent dyes, NHS esters of DyLight 550 and DyLight 650, were already quenched by Tris-HCl (Bionovas, Toronto, Canada). To check whether calcium affects interaction between S100A1 and 2-oxohistidine, 1 mm CaCl2 was added in the assay buffer. After several washes with TBST, the chips were dried by centrifugation and then scanned with a microarray scanner. The Kd value was calculated by double-reciprocal plot analysis, in which y is one divided by fluorescence intensity, and x is one divided by peptide concentration. We set the regression line formula in the form of y = ax, where “a” is the slope of regression line. The Kd value will be “a” multiplied by the concentration of identified protein. All identified proteins were converted to FASTA format and analyzed by Gapped Local Alignment of Motifs (GLAM2) (30.Frith M.C. Saunders N.F. Kobe B. Bailey T.L. Discovering sequence motifs with arbitrary insertions and deletions.PLoS Comput. Biol. 2008; 4: e1000071Crossref PubMed Scopus (235) Google Scholar) for surveying consensus motif. The parameters of GLAM2 were set as default. The resultant motif was then searched in entire E. coli K12 proteome and human proteome by GLAM2SCAN (30.Frith M.C. Saunders N.F. Kobe B. Bailey T.L. Discovering sequence motifs with arbitrary insertions and deletions.PLoS Comput. 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To identify proteins which may bind specifically to 2-oxohistidine residue, we devised an experimental strategy illustrated in Fig. 1. First, we fabricated the E. coli K12 proteome chip, generated the 2-oxohistidine containing peptides, and probed these peptides with E. coli K12 proteome chips. After identifying the positive hits, we used fluorescence polarization assays to validate the interactions and measured the binding affinity by dose-response measurements. Then, we surveyed the consensus motif among these identified proteins and applied to human proteome to look for possible human 2-oxohistidine interacting proteins. Finally, we used the functional interaction network to find out the possible interacting proteins and used GO and KEGG to figure out related processes and pathways (Fig. 1). To synthesize peptide probes, histidine residues were placed in the middle of 12-mer or 13-mer peptides to eliminate possible charge effects at N terminus and C terminus, creating a context similar to proteins. Easily oxidized amino acids, such as methionine, cysteine, tyrosine, tryptophan, phenylalanine, lysine, and arginine, were avoided. Three peptides containing a single histidine residue and random selections of other residues, namely AGAQVAHGNEVAG (AG), SEAGVNHGSAGQA (SE), and IAVENVHGGLA (IA), were used for chip assays. We carried out MCO reactions using the copper/ascorbate/air system shown in Fig. 2 to convert them to 2-oxohistidine containing peptides (Oxo-AG, Oxo-SE, Oxo-IA). The HPLC yield of peptides Oxo-AG and Oxo-SE were around 10%, and for Oxo-IA peptide around 20% (Fig. 2). The site of oxidative modification was confirmed by LC-MS/MS for all peptides (supplemental Fig. S1). To investigate 2-oxohistidine interacting proteins, AGAQVAH*GNEVAG (Oxo-AG peptide) and SEAGVNH*GSAGQA (Oxo-SE peptide) were conjugated to DyLight 550 fluoKeywords:
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Abstract The group of inborn errors of metabolism (IEM) displays a marked heterogeneity and IEM can affect virtually all functions and organs of the human organism; however, IEM share that their associated proteins function in metabolism. Most proteins carry out cellular functions by interacting with other proteins, and thus are organized in biological networks. Therefore, diseases are rarely the consequence of single gene mutations but of the perturbations caused in the related cellular network. Systematic approaches that integrate multi‐omics and database information into biological networks have successfully expanded our knowledge of complex disorders but network‐based strategies have been rarely applied to study IEM. We analyzed IEM on a proteome scale and found that IEM‐associated proteins are organized as a network of linked modules within the human interactome of protein interactions, the IEM interactome. Certain IEM disease groups formed self‐contained disease modules, which were highly interlinked. On the other hand, we observed disease modules consisting of proteins from many different disease groups in the IEM interactome. Moreover, we explored the overlap between IEM and non‐IEM disease genes and applied network medicine approaches to investigate shared biological pathways, clinical signs and symptoms, and links to drug targets. The provided resources may help to elucidate the molecular mechanisms underlying new IEM, to uncover the significance of disease‐associated mutations, to identify new biomarkers, and to develop novel therapeutic strategies.
Interactome
Human proteome project
Proteome
Human genetics
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Protein-protein interactions are a critical element of biological systems, and the analysis of interaction partners can provide valuable hints about unknown functions of a protein. In recent years, several large-scale protein interaction studies have begun to unravel the complex networks through which plant proteins exert their functions. Two major classes of experimental approaches are used for protein interaction mapping: analysis of direct interactions using binary methods such as yeast two-hybrid or split ubiquitin, and analysis of protein complexes through affinity purification followed by mass spectrometry. In addition, bioinformatics predictions can suggest interactions that have evaded detection by other methods or those of proteins that have not been investigated. Here we review the major approaches to construct, analyze, use, and carry out quality control on plant protein interactome networks. We present experimental and computational approaches for large-scale mapping, methods for validation or smaller-scale functional studies, important bioinformatics resources, and findings from recently published large-scale plant interactome network maps.
Interactome
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Abstract To understand how proteins function to control cellular processes, their interactions with other proteins must be identified and characterised. The yeast two‐hybrid system is a simple and efficient assay for protein interactions. In a yeast two‐hybrid assay, the two proteins to be tested are expressed in a yeast nucleus with each protein fused to one‐half of a transcription activator. If the two‐hybrid proteins interact, the transcription activator is reconstituted and turns on reporter genes that can be easily detected. This assay has been used to identify tens of thousands of protein interactions, to map protein interaction domains and to characterise mutant variants of proteins. A variety of related assays have been developed, all based on the ability of two interacting hybrid proteins to activate a reporter system. These assays along with the original yeast two‐hybrid assay contribute to the characterisation of the protein interactions – or protein interactome – for humans and a wide range of other organisms. Key Concepts The function of most proteins involves interacting with one or more other proteins. A binary interaction is a direct physical interaction between two proteins. Understanding a protein's function requires charting its binary interactions. The interactome is all of the protein interactions for a particular cell or an entire organism. Two‐hybrid assays detect binary protein interactions by expressing the two test proteins in cells as hybrids fused to protein moieties that when brought into proximity via the protein interaction produce a detectable signal. In a yeast two‐hybrid assay, the two proteins to be tested for interaction are fused to the two halves of a transcription factor in yeast. Two‐hybrid assays, like all protein interaction assays, can produce false positives, which are interactions that are detected in the assay even though they do not occur under normal conditions in vivo . Two‐hybrid and other protein interaction assays can also result in missed interactions or false negatives. Use of multiple different protein interaction assays can reduce the number of false negatives and provide cross‐validation to rule out false positives.
Interactome
Two-hybrid screening
Protein-fragment complementation assay
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Abstract Complex biological processes in cells are embedded in the interactome, representing the complete set of protein-protein interactions. Mapping and analyzing the protein structures are essential to fully comprehending these processes’ molecular details. Therefore, knowing the structural coverage of the interactome is essential to show the current limitations. Structural modeling of protein-protein interactions requires accurate protein structures. In this study, we mapped all experimental structures to the reference human proteome. Later, we found the enrichment in structural coverage when complementary methods such as homology modeling and deep learning (AlphaFold) are included. We then collected the interactions from the literature and databases to form the reference human interactome resulting in 117,897 non-redundant interactions. When we analyzed the structural coverage of the interactome, we found that the number of experimentally determined protein complex structures is scarce, corresponding to 3.95% of all binary interactions. We also analyzed known and modeled structures to potentially construct the structural interactome with a docking method. Our analysis showed that 12.97% of the interactions from HuRI, 73.62%, and 32.94% from the filtered versions of STRING and HIPPIE could potentially be modeled with a high structural coverage or accuracy, respectively. Overall, this paper provides an overview of the current state of structural coverage of the human proteome and interactome. Significance Statement We gathered binary protein-protein interactions from three prominent interactome databases to create a comprehensive human reference interactome. We quantified the structural coverage of the human interactome using already available structural data from four different sources. We further evaluate the percentage of interactions that can be accurately predicted using docking methods.
Interactome
Human proteome project
Proteome
Structural bioinformatics
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Interactome
Identification
Two-hybrid screening
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Citations (5)
The analysis of protein-protein interactions (PPIs) is essential for the understanding of cellular signaling. Besides probing PPIs with immunoprecipitation-based techniques, peptide pull-downs are an alternative tool specifically useful to study interactome changes induced by post-translational modifications. Peptides for pull-downs can be chemically synthesized and thus offer the possibility to include amino acid exchanges and post-translational modifications (PTMs) in the pull-down reaction. The combination of peptide pull-down and analysis of the binding partners with mass spectrometry offers the direct measurement of interactome changes induced by PTMs or by amino acid exchanges in the interaction site. The possibility of large-scale peptide synthesis on a membrane surface opened the possibility to systematically analyze interactome changes for mutations of many proteins at the same time. Short linear motifs (SLiMs) are amino acid patterns that can mediate protein binding. A significant number of SLiMs are located in regions of proteins, which are lacking a secondary structure, making the interaction motifs readily available for binding reactions. Peptides are particularly well suited to study protein interactions, which are based on SLiM-mediated binding. New technologies using arrayed peptides for interaction studies are able to identify SLIM-based interaction and identify the interaction motifs.
Interactome
Immunoprecipitation
Protein Array Analysis
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Abstract To understand how proteins function to control cellular processes, their interactions with other proteins must be identified and characterised. The yeast two‐hybrid system is a simple and efficient assay for protein–protein interactions. In a yeast two‐hybrid assay, two proteins are expressed in a yeast nucleus with each protein fused to one‐half of a transcription activator. If the two hybrid proteins interact, the transcription activator is reconstituted and turns on easily detectable reporter genes. This assay has been used to identify tens of thousands of protein interactions, to map protein interaction domains and to characterise mutant variants of proteins. A variety of related assays have been developed, all based on the ability of two interacting hybrid proteins to activate a reporter system. These assays along with the original two‐hybrid assay are contributing to the characterisation of the protein interactions – or protein interactome – for humans and several model organisms. Key Concepts: The role that most proteins play in cells involves interacting with one or more proteins. A binary interaction is a physical interaction between two proteins. Understanding a protein's function requires charting its binary interactions. Interactome is a term used to refer to all of the protein interactions for a particular cell or an entire organism. Two‐hybrid assays are assays for binary protein interactions, where two test proteins are expressed in cells as hybrids fused to protein moieties that when brought into proximity via the protein interaction produces a detectable signal. In a yeast two‐hybrid assay, the two proteins to be tested for interaction are fused to the two halves of a transcription factor in yeast, which activates reporter genes if the proteins interact. In a protein complementation assay, the two proteins are fused to separate halves of a reporter protein like an enzyme, which will be reconstituted if the two halves are brought into close proximity via the protein–protein interaction. False positives are interactions that are detected in the assay even though they do not occur under normal conditions in vivo . Protein interaction assays can also result in missed interactions or false negatives. Use of multiple different protein interaction assays can reduce the number of false negatives and provide cross‐validation to rule out false positives.
Interactome
Two-hybrid screening
Protein-fragment complementation assay
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Citations (1)