A comprehensive Plasmodium falciparum protein interaction map reveals a distinct architecture of a core interactome

We derive a map of protein interactions in the parasite Plasmodium falciparum from conserved interactions in Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, and Escherichia coli and pool them with experimental interaction data. The application of a clique‐percolation algorithm allows us to find overlapping clusters, strongly correlated with yeast specific conserved protein complexes. Such clusters contain core activities that govern gene expression, largely dominated by components of protein production and degradation processes as well as RNA metabolism. A critical role of protein hubs in the interactome of P. falciparum is supported by their appearance in multiple clusters and the tendencies of their interactions to reach into many distinct protein clusters. Parasite proteins with a human ortholog tend to appear in single complexes. Annotating each protein with the stage where it is maximally expressed we observe a high level of cluster integrity in the ring stage. While we find no signal in the trophozoite phase, expression patterns are reversed in the schizont phase, implying a preponderance of parasite specific functions in this late, invasive schizont stage. As such, the inference of potential protein interactions and their analysis contributes to our understanding of the parasite, indicating basic pathways and processes as unique targets for therapeutic intervention.     

A PopZ‐linked apical recruitment assay for studying protein–protein interactions in the bacterial cell envelope

Most bacteria are surrounded by a complex cell envelope. As with many biological processes, studies of envelope assembly have benefited from cell‐based assays for detecting protein–protein interactions. These assays use simple readouts and lack a protein purification requirement, making them ideal for early stage investigations. The most widely used two‐hybrid interaction assay for proteins involved in envelope biogenesis is based on the reconstitution of adenylate cyclase activity from a split enzyme. Because adenylate cyclase is only functional in the cytoplasm, both protein fusions used in the assay must have a terminus located in this compartment. However, many envelope assembly factors are wholly extracytoplasmic. Detecting interactions involving such proteins using two‐hybrid systems has therefore been problematic. To address this issue, we developed a cytological assay in Escherichia coli based on PopZ from Caulobacter crescentus. Here, we demonstrate the utility of this PopZ‐Linked Apical Recruitment (POLAR) method for detecting interactions between proteins located in different cellular compartments. Additionally, we report that recruitment of an active peptidoglycan synthase to the cell pole is detrimental for E. coli and that interactions between proteins in the inner and outer membranes of the Gram‐negative envelope may provide a mechanism for recruiting protein complexes to subpolar sites.     

The IDL of E. coli SSB links ssDNA and protein binding by mediating protein–protein interactions

The E. coli single strand DNA binding protein (SSB) is essential to viability where it functions in two seemingly disparate roles: it binds to single stranded DNA (ssDNA) and to target proteins that comprise the SSB interactome. The link between these roles resides in a previously under‐appreciated region of the protein known as the intrinsically disordered linker (IDL). We present a model wherein the IDL is responsible for mediating protein–protein interactions critical to each role. When interactions occur between SSB tetramers, cooperative binding to ssDNA results. When binding occurs between SSB and an interactome partner, storage or loading of that protein onto the DNA takes place. The properties of the IDL that facilitate these interactions include the presence of repeats, a putative polyproline type II helix and, PXXP motifs that may facilitate direct binding to the OB‐fold in a manner similar to that observed for SH3 domain binding of PXXP ligands in eukaryotic systems.     

J-domain Proteins form Binary Complexes with Hsp90 and Ternary Complexes with Hsp90 and Hsp70

Hsp90 and Hsp70 are highly conserved molecular chaperones that help maintain proteostasis by participating in protein folding, unfolding, remodeling and activation of proteins. Both chaperones are also important for cellular recovery following environmental stresses. Hsp90 and Hsp70 function collaboratively for the remodeling and activation of some client proteins. Previous studies using E. coli and S. cerevisiae showed that residues in the Hsp90 middle domain directly interact with a region in the Hsp70 nucleotide binding domain, in the same region known to bind J-domain proteins. Importantly, J-domain proteins facilitate and stabilize the interaction between Hsp90 and Hsp70 both in E. coli and S. cerevisiae. To further explore the role of J-domain proteins in protein reactivation, we tested the hypothesis that J-domain proteins participate in the collaboration between Hsp90 and Hsp70 by simultaneously interacting with Hsp90 and Hsp70. Using E. coli Hsp90, Hsp70 (DnaK), and a J-domain protein (CbpA), we detected a ternary complex containing all three proteins. The interaction involved the J-domain of CbpA, the DnaK binding region of E. coli Hsp90, and the J-domain protein binding region of DnaK where Hsp90 also binds. Additionally, results show that E. coli Hsp90 interacts with E. coli J-domain proteins, DnaJ and CbpA, and that yeast Hsp90, Hsp82, interacts with a yeast J-domain protein, Ydj1. Together these results suggest that the complexes may be transient intermediates in the pathway of collaborative protein remodeling by Hsp90 and Hsp70.     

Binding of the S7 Protein with Fragment 926–986/1219–1393 of the 16S rRNA As a Key Step in the Assembly of the Small Subunit of Prokaryotic Ribosomes

Both structural and thermodynamic studies are necessary to understand the ribosome assembly. An initial step was made in studying the interaction between a 16S rRNA fragment and S7, a key protein in assembling the prokaryotic ribosome small subunit. The apparent dissociation constant was obtained for complexes of recombinant Escherichia coliandThermus thermophilusS7 with a fragment of the 3" domain of the E. coli16S rRNA. Both proteins showed high rRNA-binding activity, which was not observed earlier. Since RNA and proteins are conformationally labile, their folding must be considered to correctly describe the RNA–protein interactions.     

SCOWLP classification: Structural comparison and analysis of protein binding regions

Background  

Detailed information about protein interactions is critical for our understanding of the principles governing protein recognition mechanisms. The structures of many proteins have been experimentally determined in complex with different ligands bound either in the same or different binding regions. Thus, the structural interactome requires the development of tools to classify protein binding regions. A proper classification may provide a general view of the regions that a protein uses to bind others and also facilitate a detailed comparative analysis of the interacting information for specific protein binding regions at atomic level. Such classification might be of potential use for deciphering protein interaction networks, understanding protein function, rational engineering and design.     

Information Flow Analysis of Interactome Networks

Recent studies of cellular networks have revealed modular organizations of genes and proteins. For example, in interactome networks, a module refers to a group of interacting proteins that form molecular complexes and/or biochemical pathways and together mediate a biological process. However, it is still poorly understood how biological information is transmitted between different modules. We have developed information flow analysis, a new computational approach that identifies proteins central to the transmission of biological information throughout the network. In the information flow analysis, we represent an interactome network as an electrical circuit, where interactions are modeled as resistors and proteins as interconnecting junctions. Construing the propagation of biological signals as flow of electrical current, our method calculates an information flow score for every protein. Unlike previous metrics of network centrality such as degree or betweenness that only consider topological features, our approach incorporates confidence scores of protein–protein interactions and automatically considers all possible paths in a network when evaluating the importance of each protein. We apply our method to the interactome networks of Saccharomyces cerevisiae and Caenorhabditis elegans. We find that the likelihood of observing lethality and pleiotropy when a protein is eliminated is positively correlated with the protein's information flow score. Even among proteins of low degree or low betweenness, high information scores serve as a strong predictor of loss-of-function lethality or pleiotropy. The correlation between information flow scores and phenotypes supports our hypothesis that the proteins of high information flow reside in central positions in interactome networks. We also show that the ranks of information flow scores are more consistent than that of betweenness when a large amount of noisy data is added to an interactome. Finally, we combine gene expression data with interaction data in C. elegans and construct an interactome network for muscle-specific genes. We find that genes that rank high in terms of information flow in the muscle interactome network but not in the entire network tend to play important roles in muscle function. This framework for studying tissue-specific networks by the information flow model can be applied to other tissues and other organisms as well.     

Roles for the two-hybrid system in exploration of the yeast protein interactome

Comprehensive analysis of protein-protein interactions is a challenging endeavor of functional proteomics and has been best explored in the budding yeast. The yeast protein interactome analysis was achieved first by using the yeast two-hybrid system in a proteome-wide scale and next by large-scale mass spectrometric analysis of affinity-purified protein complexes. While these interaction data have led to a number of novel findings and the emergence of a single huge network containing thousands of proteins, they suffer many false signals and fall short of grasping the entire interactome. Thus, continuous efforts are necessary in both bioinformatics and experimentation to fully exploit these data and to proceed another step forward to the goal. Computational tools to integrate existing biological knowledge buried in literature and various functional genomic data with the interactome data are required for biological interpretation of the huge protein interaction network. Novel experimental methods have to be developed to detect weak, transient interactions involving low abundance proteins as well as to obtain clues to the biological role for each interaction. Since the yeast two-hybrid system can be used for the mapping of the interaction domains and the isolation of interaction-defective mutants, it would serve as a technical basis for the latter purpose, thereby playing another important role in the next phase of protein interactome research.     

The Modular Organization of Protein Interactions in Escherichia coli

Escherichia coli serves as an excellent model for the study of fundamental cellular processes such as metabolism, signalling and gene expression. Understanding the function and organization of proteins within these processes is an important step towards a ‘systems’ view of E. coli. Integrating experimental and computational interaction data, we present a reliable network of 3,989 functional interactions between 1,941 E. coli proteins (∼45% of its proteome). These were combined with a recently generated set of 3,888 high-quality physical interactions between 918 proteins and clustered to reveal 316 discrete modules. In addition to known protein complexes (e.g., RNA and DNA polymerases), we identified modules that represent biochemical pathways (e.g., nitrate regulation and cell wall biosynthesis) as well as batteries of functionally and evolutionarily related processes. To aid the interpretation of modular relationships, several case examples are presented, including both well characterized and novel biochemical systems. Together these data provide a global view of the modular organization of the E. coli proteome and yield unique insights into structural and evolutionary relationships in bacterial networks.     

Computational detection of protein complexes in AP-MS experiments

Protein complex identification is an important goal of protein-protein interaction analysis. To date, development of computational methods for detecting protein complexes has been largely motivated by genome-scale interaction data sets from high-throughput assays such as yeast two-hybrid or tandem affinity purification coupled with mass spectrometry (TAP-MS). However, due to the popularity of small to intermediate-scale affinity purification-mass spectrometry (AP-MS) experiments, protein complex detection is increasingly discussed in local network analysis. In such data sets, protein complexes cannot be detected using binary interaction data alone because the data contain interactions with tagged proteins only and, as a result, interactions between all other proteins remain unobserved, limiting the scope of existing algorithms. In this article, we provide a pragmatic review of network graph-based computational algorithms for protein complex analysis in global interactome data, without requiring any computational background. We discuss the practical gap in applying these algorithms to recently surging small to intermediate-scale AP-MS data sets, and review alternative clustering algorithms using quantitative proteomics data and their limitations.     

A proteome-wide protein interaction map for Campylobacter jejuni

Background

Data from large-scale protein interaction screens for humans and model eukaryotes have been invaluable for developing systems-level models of biological processes. Despite this value, only a limited amount of interaction data is available for prokaryotes. Here we report the systematic identification of protein interactions for the bacterium Campylobacter jejuni, a food-borne pathogen and a major cause of gastroenteritis worldwide.

Results

Using high-throughput yeast two-hybrid screens we detected and reproduced 11,687 interactions. The resulting interaction map includes 80% of the predicted C. jejuni NCTC11168 proteins and places a large number of poorly characterized proteins into networks that provide initial clues about their functions. We used the map to identify a number of conserved subnetworks by comparison to protein networks from Escherichia coli and Saccharomyces cerevisiae. We also demonstrate the value of the interactome data for mapping biological pathways by identifying the C. jejuni chemotaxis pathway. Finally, the interaction map also includes a large subnetwork of putative essential genes that may be used to identify potential new antimicrobial drug targets for C. jejuni and related organisms.

Conclusion

The C. jejuni protein interaction map is one of the most comprehensive yet determined for a free-living organism and nearly doubles the binary interactions available for the prokaryotic kingdom. This high level of coverage facilitates pathway mapping and function prediction for a large number of C. jejuni proteins as well as orthologous proteins from other organisms. The broad coverage also facilitates cross-species comparisons for the identification of evolutionarily conserved subnetworks of protein interactions.     

Identification and biochemical characterization of the SLC9A7 interactome

Organellar and cytosolic pH homeostasis is central to most cellular processes, including vesicular trafficking, post-translational modification/processing of proteins, and receptor-ligand interactions. SLC9A7 (NHE7) was identified as a unique (Na⁺, K⁺)/H⁺ exchanger that dynamically cycles between the trans-Golgi network (TGN), endosomes and the plasma membrane. Here we have used mass spectrometry to explore the affinity-captured interactome of NHE7, leading to the identification of cytoskeletal proteins, cell adhesion molecules, membrane transporters, and signaling molecules. Among these binding proteins, calcium-calmodulin, but not apo-calmodulin, binds to NHE7 and regulates the organellar transporter activity. Vimentin was co-immunoprecipitated with endogenous NHE7 protein in human breast cancer MDA-MB-231 cells. A sizable population of NHE7 relocalized to focal complexes in migrating cells and showed colocalization with vimentin and actin in focal complexes. Among the NHE7-binding proteins identified, CD44, a cell surface glycoprotein receptor for hyaluronate and other ligands, showed regulated interaction with NHE7. Pretreatment of the cells with phorbol ester facilitated the NHE7-CD44 interaction and the lipid raft association of CD44. When lipid rafts were chemically disrupted, the NHE7-CD44 interaction was markedly reduced. These results suggest potential dual roles of NHE7 in intracellular compartments and subdomains of cell-surface membranes.     

Artificial septal targeting of Bacillus subtilis cell division proteins in Escherichia coli: an interspecies approach to the study of protein-protein interactions in multiprotein complexes

Bacterial cell division is mediated by a set of proteins that assemble to form a large multiprotein complex called the divisome. Recent studies in Bacillus subtilis and Escherichia coli indicate that cell division proteins are involved in multiple cooperative binding interactions, thus presenting a technical challenge to the analysis of these interactions. We report here the use of an E. coli artificial septal targeting system for examining the interactions between the B. subtilis cell division proteins DivIB, FtsL, DivIC, and PBP 2B. This technique involves the fusion of one of the proteins (the “bait”) to ZapA, an E. coli protein targeted to mid-cell, and the fusion of a second potentially interacting partner (the “prey”) to green fluorescent protein (GFP). A positive interaction between two test proteins in E. coli leads to septal localization of the GFP fusion construct, which can be detected by fluorescence microscopy. Using this system, we present evidence for two sets of strong protein-protein interactions between B. subtilis divisomal proteins in E. coli, namely, DivIC with FtsL and DivIB with PBP 2B, that are independent of other B. subtilis cell division proteins and that do not disturb the cytokinesis process in the host cell. Our studies based on the coexpression of three or four of these B. subtilis cell division proteins suggest that interactions among these four proteins are not strong enough to allow the formation of a stable four-protein complex in E. coli in contrast to previous suggestions. Finally, our results demonstrate that E. coli artificial septal targeting is an efficient and alternative approach for detecting and characterizing stable protein-protein interactions within multiprotein complexes from other microorganisms. A salient feature of our approach is that it probably only detects the strongest interactions, thus giving an indication of whether some interactions suggested by other techniques may either be considerably weaker or due to false positives.     

SLIDE, the Protein Interacting Domain of Imitation Switch Remodelers, Binds DDT-Domain Proteins of Different Subfamilies in Chromatin Remodeling Complexes

The Imitation Switch (ISWI) type adenosine triphosphate (ATP)-dependent chromatin remodeling factors are conserved proteins in eukaryotes, and some of them are known to form stable remodeling complexes...     

Interactome disassembly during apoptosis occurs independent of caspase cleavage

Protein–protein interaction networks (interactomes) define the functionality of all biological systems. In apoptosis, proteolysis by caspases is thought to initiate disassembly of protein complexes and cell death. Here we used a quantitative proteomics approach, protein correlation profiling (PCP), to explore changes in cytoplasmic and mitochondrial interactomes in response to apoptosis initiation as a function of caspase activity. We measured the response to initiation of Fas‐mediated apoptosis in 17,991 interactions among 2,779 proteins, comprising the largest dynamic interactome to date. The majority of interactions were unaffected early in apoptosis, but multiple complexes containing known caspase targets were disassembled. Nonetheless, proteome‐wide analysis of proteolytic processing by terminal amine isotopic labeling of substrates (TAILS) revealed little correlation between proteolytic and interactome changes. Our findings show that, in apoptosis, significant interactome alterations occur before and independently of caspase activity. Thus, apoptosis initiation includes a tight program of interactome rearrangement, leading to disassembly of relatively few, select complexes. These early interactome alterations occur independently of cleavage of these protein by caspases.     

Conserved abundance and topological features in chromatin‐remodeling protein interaction networks

The study of conserved protein interaction networks seeks to better understand the evolution and regulation of protein interactions. Here, we present a quantitative proteomic analysis of 18 orthologous baits from three distinct chromatin‐remodeling complexes in Saccharomyces cerevisiae and Homo sapiens. We demonstrate that abundance levels of orthologous proteins correlate strongly between the two organisms and both networks have highly similar topologies. We therefore used the protein abundances in one species to cross‐predict missing protein abundance levels in the other species. Lastly, we identified a novel conserved low‐abundance subnetwork further demonstrating the value of quantitative analysis of networks.