A second-generation protein-protein interaction network of Helicobacter pylori

The protein interactome of the citrus Huanglongbing pathogen Candidatus Liberibacter asiaticus

The bacterium Candidatus Liberibacter asiaticus (CLas) causes citrus Huanglongbing disease. Our understanding of the pathogenicity and biology of this microorganism remains limited because CLas has not yet been cultivated in artificial media. Its genome is relatively small and encodes approximately 1136 proteins, of which 415 have unknown functions. Here, we use a high-throughput yeast-two-hybrid (Y2H) screen to identify interactions between CLas proteins, thus providing insights into their potential functions. We identify 4245 interactions between 542 proteins, after screening 916 bait and 936 prey proteins. The false positive rate of the Y2H assay is estimated to be 2.9%. Pull-down assays for nine protein-protein interactions (PPIs) likely involved in flagellar function support the robustness of the Y2H results. The average number of PPIs per node in the CLas interactome is 15.6, which is higher than the numbers previously reported for interactomes of free-living bacteria, suggesting that CLas genome reduction has been accompanied by increased protein multi-functionality. We propose potential functions for 171 uncharacterized proteins, based on the PPI results, guilt-by-association analyses, and comparison with data from other bacterial species. We identify 40 hub-node proteins, including quinone oxidoreductase and LysR, which are known to protect other bacteria against oxidative stress and might be important for CLas survival in the phloem. We expect our PPI database to facilitate research on CLas biology and pathogenicity mechanisms.

Defining hierarchical protein interaction networks from spectral analysis of bacterial proteomes

Cellular behaviors emerge from layers of molecular interactions: proteins interact to form complexes, pathways, and phenotypes. We show that hierarchical networks of protein interactions can be defined from the statistical pattern of proteome variation measured across thousands of diverse bacteria and that these networks reflect the emergence of complex bacterial phenotypes. Our results are validated through gene-set enrichment analysis and comparison to existing experimentally derived databases. We demonstrate the biological utility of our approach by creating a model of motility in Pseudomonas aeruginosa and using it to identify a protein that affects pilus-mediated motility. Our method, SCALES (Spectral Correlation Analysis of Layered Evolutionary Signals), may be useful for interrogating genotype-phenotype relationships in bacteria.

Computational Network Inference for Bacterial Interactomics

Since the large-scale experimental characterization of protein–protein interactions (PPIs) is not possible for all species, several computational PPI prediction methods have been developed that harness existing data from other species. While PPI network prediction has been extensively used in eukaryotes, microbial network inference has lagged behind. However, bacterial interactomes can be built using the same principles and techniques; in fact, several methods are better suited to bacterial genomes. These predicted networks allow systems-level analyses in species that lack experimental interaction data. This review describes the current network inference and analysis techniques and summarizes the use of computationally-predicted microbial interactomes to date.

Computationally Reconstructed Interactome of Bradyrhizobium diazoefficiens USDA110 Reveals Novel Functional Modules and Protein Hubs for Symbiotic Nitrogen Fixation

Symbiotic nitrogen fixation is an important part of the nitrogen biogeochemical cycles and the main nitrogen source of the biosphere. As a classical model system for symbiotic nitrogen fixation, rhizobium-legume systems have been studied elaborately for decades. Details about the molecular mechanisms of the communication and coordination between rhizobia and host plants is becoming clearer. For more systematic insights, there is an increasing demand for new studies integrating multiomics information. Here, we present a comprehensive computational framework integrating the reconstructed protein interactome of B. diazoefficiens USDA110 with its transcriptome and proteome data to study the complex protein-protein interaction (PPI) network involved in the symbiosis system. We reconstructed the interactome of B. diazoefficiens USDA110 by computational approaches. Based on the comparison of interactomes between B. diazoefficiens USDA110 and other rhizobia, we inferred that the slow growth of B. diazoefficiens USDA110 may be due to the requirement of more protein modifications, and we further identified 36 conserved functional PPI modules. Integrated with transcriptome and proteome data, interactomes representing free-living cell and symbiotic nitrogen-fixing (SNF) bacteroid were obtained. Based on the SNF interactome, a core-sub-PPI-network for symbiotic nitrogen fixation was determined and nine novel functional modules and eleven key protein hubs playing key roles in symbiosis were identified. The reconstructed interactome of B. diazoefficiens USDA110 may serve as a valuable reference for studying the mechanism underlying the SNF system of rhizobia and legumes.

The Protein Interactome of Glycolysis in Escherichia coli

Glycolysis is regulated by numerous mechanisms including allosteric regulation, post-translational modification or protein-protein interactions (PPI). While glycolytic enzymes have been found to interact with hundreds of proteins, the impact of only some of these PPIs on glycolysis is well understood. Here we investigate which of these interactions may affect glycolysis in E. coli and possibly across numerous other bacteria, based on the stoichiometry of interacting protein pairs (from proteomic studies) and their conservation across bacteria. We present a list of 339 protein-protein interactions involving glycolytic enzymes but predict that ~70% of glycolytic interactors are not present in adequate amounts to have a significant impact on glycolysis. Finally, we identify a conserved but uncharacterized subset of interactions that are likely to affect glycolysis and deserve further study.

Internetwork connectivity of molecular networks across species of life

Molecular interactions are studied as independent networks in systems biology. However, molecular networks do not exist independently of each other. In a network of networks approach (called multiplex), we study the joint organization of transcriptional regulatory network (TRN) and protein-protein interaction (PPI) network. We find that TRN and PPI are non-randomly coupled across five different eukaryotic species. Gene degrees in TRN (number of downstream genes) are positively correlated with protein degrees in PPI (number of interacting protein partners). Gene-gene and protein-protein interactions in TRN and PPI, respectively, also non-randomly overlap. These design principles are conserved across the five eukaryotic species. Robustness of the TRN-PPI multiplex is dependent on this coupling. Functionally important genes and proteins, such as essential, disease-related and those interacting with pathogen proteins, are preferentially situated in important parts of the human multiplex with highly overlapping interactions. We unveil the multiplex architecture of TRN and PPI. Multiplex architecture may thus define a general framework for studying molecular networks. This approach may uncover the building blocks of the hierarchical organization of molecular interactions.

Quantitative proteomics approach to investigate the antibacterial response of Helicobacter pylori to daphnetin, a traditional Chinese medicine monomer

Helicobacter pylori is a Gram-negative bacterium related to the development of peptic ulcers and stomach cancer. An increasing number of infected individuals are found to harbor antibiotic-resistant H. pylori, which results in treatment failure. Daphnetin, a traditional Chinese medicine, has a broad spectrum of antibacterial activity without the development of bacterial resistance. However, the antibacterial mechanisms of daphnetin have not been elucidated entirely. To better understand the mechanisms of daphnetin's effect on H. pylori, a label-free quantitative proteomics approach based on an EASY-nLC 1200 system coupled with an Orbitrap Fusion Lumos mass spectrometer was established to investigate the key protein differences between daphnetin- and non-daphnetin-treated H. pylori. Using the criteria of greater than 1.5-fold changes and adjusted p value <0.05, proteins related to metabolism, membrane structure, nucleic acid and protein synthesis, ion binding, H. pylori colonization and infection, stress reaction, flagellar assembly and so on were found to be changed under daphnetin pressure. And the changes of selected proteins in expression level were confirmed by targeted proteomics. These new data provide us a more comprehensive horizon of the proteome changes in H. pylori that occur in response to daphnetin.

Analysis of the RNA and Protein Complexome by Grad-seq

The complexome of a cell is the entirety of its complexes. Complexome capture studies have mostly focused on protein-protein interactions, which has left a gap in our knowledge of the global interactions of RNAs. To overcome these limitations, we recently introduced gradient profiling by sequencing (Grad-seq), which analyzes in a high-throughput fashion soluble cellular complexes after their separation in a glycerol gradient by fraction-wise RNA-seq and mass spectrometry. Here, we describe a detailed Grad-seq protocol for Streptococcus pneumoniae, which should also be applicable to other bacterial species.

Structural Conservation and Adaptation of the Bacterial Flagella Motor

Many bacteria require flagella for the ability to move, survive, and cause infection. The flagellum is a complex nanomachine that has evolved to increase the fitness of each bacterium to diverse environments. Over several decades, molecular, biochemical, and structural insights into the flagella have led to a comprehensive understanding of the structure and function of this fascinating nanomachine. Notably, X-ray crystallography, cryo-electron microscopy (cryo-EM), and cryo-electron tomography (cryo-ET) have elucidated the flagella and their components to unprecedented resolution, gleaning insights into their structural conservation and adaptation. In this review, we focus on recent structural studies that have led to a mechanistic understanding of flagellar assembly, function, and evolution.

Structural proteomics, electron cryo-microscopy and structural modeling approaches in bacteria-human protein interactions

A central challenge in infection medicine is to determine the structure and function of host-pathogen protein-protein interactions to understand how these interactions facilitate bacterial adhesion, dissemination and survival. In this review, we focus on proteomics, electron cryo-microscopy and structural modeling to showcase instances where affinity-purification (AP) and cross-linking (XL) mass spectrometry (MS) has advanced our understanding of host-pathogen interactions. We highlight cases where XL-MS in combination with structural modeling has provided insight into the quaternary structure of interspecies protein complexes. We further exemplify how electron cryo-tomography has been used to visualize bacterial-human interactions during attachment and infection. Lastly, we discuss how AP-MS, XL-MS and electron cryo-microscopy and -tomography together with structural modeling approaches can be used in future studies to broaden our knowledge regarding the function, dynamics and evolution of such interactions. This knowledge will be of relevance for future drug and vaccine development programs.

Protein isoelectric point distribution in the interactomes across the domains of life

The distribution of the protein isoelectric point (pI) in the protein-protein interaction (PPI) networks across the domains of life has not been investigated yet. This work attempts to correlate the pI with the number of direct interacting partners in the experimentally supported networks involving 226.085 PPIs from 14 various organisms including human, mouse, yeast, bacteria, viruses and 53.606 virus-host interactions. The results showed that the acidic proteins (pI<3) have the highest average number of interactions in eukaryotes, while in bacteria more neutral proteins. On the contrary, the basic proteins (pI>11) have the lowest average number of interactions in human, mouse, yeast, bacteria and human-viral interactomes and the highest average in intraviral interactomes. We examined the correlation of the pI of the interacting partners by calculating the assortativity index of various PPI networks. We found that the interactions between the acidic, neutral and basic proteins have a fairly random mix, implying weak if any association between the acidic and basic proteins. Furthermore, protein features such as biological function, structurally order and disorder, subcellular localization, and homodimerization were classified according to pI in prokaryote and eukaryote proteomes.

Protein-protein complexes as targets for drug discovery against infectious diseases

Antibiotics are therapeutic agents against bacterial infections, however, the emergence of multiple and extremely drug-resistant microbes (Multi-Drug Resistant and Extremely Drug-Resistant) are compromising the effectiveness of the currently available treatment options. The drug resistance is not a novel crisis, the current pace of drug discovery has failed to compete with the growth of MDR and XDR pathogenic strains and therefore, it is highly central to find out novel antimicrobial drugs with unique mechanisms of action which may reduce the burden of MDR and XDR pathogenic strains. Protein-protein interactions (PPIs) are involved in a countless of the physiological and cellular phenomena and have become an attractive target to treat the diseases. Therefore, targeting PPIs in infectious agents may offer a completely novel strategy of intervention to develop anti-infective drugs that may combat the ever-increasing rate of drug resistant strains. This chapter describes how small molecule candidate inhibitors that are capable of disrupting the PPIs in pathogenic microbes and it could be an alternative lead discovery strategy to obtain novel antibiotics. Over the last three decades, there has been increasing efforts focused on the manipulation of PPIs in order to develop novel therapeutic interventions. The diversity and complexity of such a complex and highly dynamic systems pose many challenges in targeting PPIs by drug-like molecules with necessary selectivity and potency. Traditional and novel drug discovery strategies have provided tools for designing and assessing PPI inhibitors against infectious diseases.

Comparative analysis of differential proteome-wide protein-protein interaction network of Methanobrevibacter ruminantium M1

A proteome-wide protein-protein interaction (PPI) network of Methanobrevibacter ruminantium M1 (MRU), a predominant rumen methanogen, was constructed from its metabolic genes using a gene neighborhood algorithm and then compared with closely related rumen methanogens Using proteome-wide PPI approach, we constructed network encompassed 2194 edges and 637 nodes interacting with 634 genes. Network quality and robustness of functional modules were assessed with gene ontology terms. A structure-function-metabolism mapping for each protein has been carried out with efforts to extract experimental PPI concomitant information from the literature. The results of our study revealed that some topological properties of its network were robust for sharing homologous protein interactions across heterotrophic and hydrogenotrophic methanogens. MRU proteome has shown to establish many PPI sub-networks for associated metabolic subsystems required to survive in the rumen environment. MRU genome found to share interacting proteins from its PPI network involved in specific metabolic subsystems distinct to heterotrophic and hydrogenotrophic methanogens. Across these proteomes, the interacting proteins from differential PPI networks were shared in common for the biosynthesis of amino acids, nucleosides, and nucleotides and energy metabolism in which more fractions of protein pairs shared with Methanosarcina acetivorans. Our comparative study expedites our knowledge to understand a complex proteome network associated with typical metabolic subsystems of MRU and to improve its genome-scale reconstruction in the future.

Combination of SAXS and Protein Painting Discloses the Three-Dimensional Organization of the Bacterial Cysteine Synthase Complex, a Potential Target for Enhancers of Antibiotic Action

The formation of multienzymatic complexes allows for the fine tuning of many aspects of enzymatic functions, such as efficiency, localization, stability, and moonlighting. Here, we investigated, in solution, the structure of bacterial cysteine synthase (CS) complex. CS is formed by serine acetyltransferase (CysE) and O-acetylserine sulfhydrylase isozyme A (CysK), the enzymes that catalyze the last two steps of cysteine biosynthesis in bacteria. CysK and CysE have been proposed as potential targets for antibiotics, since cysteine and related metabolites are intimately linked to protection of bacterial cells against redox damage and to antibiotic resistance. We applied a combined approach of small-angle X-ray scattering (SAXS) spectroscopy and protein painting to obtain a model for the solution structure of CS. Protein painting allowed the identification of protein–protein interaction hotspots that were then used as constrains to model the CS quaternary assembly inside the SAXS envelope. We demonstrate that the active site entrance of CysK is involved in complex formation, as suggested by site-directed mutagenesis and functional studies. Furthermore, complex formation involves a conformational change in one CysK subunit that is likely transmitted through the dimer interface to the other subunit, with a regulatory effect. Finally, SAXS data indicate that only one active site of CysK is involved in direct interaction with CysE and unambiguously unveil the quaternary arrangement of CS.

Neglog: Homology-Based Negative Data Sampling Method for Genome-Scale Reconstruction of Human Protein-Protein Interaction Networks

Rapid reconstruction of genome-scale protein-protein interaction (PPI) networks is instrumental in understanding the cellular processes and disease pathogenesis and drug reactions. However, lack of experimentally verified negative data (i.e., pairs of proteins that do not interact) is still a major issue that needs to be properly addressed in computational modeling. In this study, we take advantage of the very limited experimentally verified negative data from Negatome to infer more negative data for computational modeling. We assume that the paralogs or orthologs of two non-interacting proteins also do not interact with high probability. We coin an assumption as "Neglog" this assumption is to some extent supported by paralogous/orthologous structure conservation. To reduce the risk of bias toward the negative data from Negatome, we combine Neglog with less biased random sampling according to a certain ratio to construct training data. L₂-regularized logistic regression is used as the base classifier to counteract noise and train on a large dataset. Computational results show that the proposed Neglog method outperforms pure random sampling method with sound biological interpretability. In addition, we find that independent test on negative data is indispensable for bias control, which is usually neglected by existing studies. Lastly, we use the Neglog method to validate the PPIs in STRING, which are supported by gene ontology (GO) enrichment analyses.

Comparative proteomics of Helicobacter pylori strains reveals geographical features rather than genomic variations

Helicobacter pylori, a pathogen of various gastric diseases, has many genome sequence variants. Thus, the pathogenesis and infection mechanisms of the H. pylori-driven gastric diseases have not been elucidated. Here, we carried out a large-scale proteome analysis to profile the heterogeneity of the proteome expression of 7 H. pylori strains by using an LC/MS/MS-based proteomics approach combined with a customized database consisting of nonredundant tryptic peptide sequences derived from full genome sequences of 52 H. pylori strains. The nonredundant peptide database enabled us to identify more peptides in the database search of MS/MS data compared with a simply merged protein database. Using this approach, we carried out proteome analysis of genome-unknown strains of H. pylori at as large a scale as genome-known ones. Clustering of the H. pylori strains using proteome profiling slightly differed from the genome profiling and more clearly divided the strains into two groups based on the isolated area. Furthermore, we identified phosphorylated proteins and sites of the H. pylori strains and obtained the phosphorylation motifs located in the N-terminus that are commonly observed in bacteria.

Molecular docking, pharmacophore based virtual screening and molecular dynamics studies towards the identification of potential leads for the management of H. pylori

The enzyme pantothenate synthetase panC is one of the potential new antimicrobial drug targets, but it is poorly characterized in H. pylori. H. pylori infection can cause gastric cancer and the management of H. pylori infection is crucial in various gastric ulcers and gastric cancer. The current study describes the use of innovative drug discovery and design approaches like comparative metabolic pathway analysis (Metacyc), exploration of database of essential genes (DEG), homology modelling, pharmacophore based virtual screening, ADMET studies and molecular dynamics simulations in identifying potential lead compounds for the H. pylori specific panC. The top ranked virtual hits STOCK1N-60270, STOCK1N-63040, STOCK1N-44424 and STOCK1N-63231 can act as templates for synthesis of new H. pylori inhibitors and they hold a promise in the management of gastric cancers caused by H. pylori.

Computational approaches such as pharmacophore modeling, virtual screening and MD simulations were explored to find the potential hits as H. pylori specific panC inhibitors for the management of gastric ulcers and gastric cancers.

Protein-protein interactions in bacteria: a promising and challenging avenue towards the discovery of new antibiotics

Antibiotics are potent pharmacological weapons against bacterial infections; however, the growing antibiotic resistance of microorganisms is compromising the efficacy of the currently available pharmacotherapies. Even though antimicrobial resistance is not a new problem, antibiotic development has failed to match the growth of resistant pathogens and hence, it is highly critical to discover new anti-infective drugs with novel mechanisms of action which will help reducing the burden of multidrug-resistant microorganisms. Protein–protein interactions (PPIs) are involved in a myriad of vital cellular processes and have become an attractive target to treat diseases. Therefore, targeting PPI networks in bacteria may offer a new and unconventional point of intervention to develop novel anti-infective drugs which can combat the ever-increasing rate of multidrug-resistant bacteria. This review describes the progress achieved towards the discovery of molecules that disrupt PPI systems in bacteria for which inhibitors have been identified and whose targets could represent an alternative lead discovery strategy to obtain new anti-infective molecules.

Three SpoA-domain proteins interact in the creation of the flagellar type III secretion system in Helicobacter pylori

Bacterial flagella are rotary nanomachines that contribute to bacterial fitness in many settings, including host colonization. The flagellar motor relies on the multiprotein flagellar motor-switch complex to govern flagellum formation and rotational direction. Different bacteria exhibit great diversity in their flagellar motors. One such variation is exemplified by the motor-switch apparatus of the gastric pathogen Helicobacter pylori, which carries an extra switch protein, FliY, along with the more typical FliG, FliM, and FliN proteins. All switch proteins are needed for normal flagellation and motility in H. pylori, but the molecular mechanism of their assembly is unknown. To fill this gap, we examined the interactions among these proteins. We found that the C-terminal SpoA domain of FliY (FliY_C) is critical to flagellation and forms heterodimeric complexes with the FliN and FliM SpoA domains, which are β-sheet domains of type III secretion system proteins. Surprisingly, unlike in other flagellar switch systems, neither FliY nor FliN self-associated. The crystal structure of the FliY_C-FliN_C complex revealed a saddle-shaped structure homologous to the FliN-FliN dimer of Thermotoga maritima, consistent with a FliY-FliN heterodimer forming the functional unit. Analysis of the FliY_C-FliN_C interface indicated that oppositely charged residues specific to each protein drive heterodimer formation. Moreover, both FliY_C-FliM_C and FliY_C-FliN_C associated with the flagellar regulatory protein FliH, explaining their important roles in flagellation. We conclude that H. pylori uses a FliY-FliN heterodimer instead of a homodimer and creates a switch complex with SpoA domains derived from three distinct proteins.

Generating genomic platforms to study Candida albicans pathogenesis

The advent of the genomic era has made elucidating gene function on a large scale a pressing challenge. ORFeome collections, whereby almost all ORFs of a given species are cloned and can be subsequently leveraged in multiple functional genomic approaches, represent valuable resources toward this endeavor. Here we provide novel, genome-scale tools for the study of Candida albicans, a commensal yeast that is also responsible for frequent superficial and disseminated infections in humans. We have generated an ORFeome collection composed of 5099 ORFs cloned in a Gateway™ donor vector, representing 83% of the currently annotated coding sequences of C. albicans. Sequencing data of the cloned ORFs are available in the CandidaOrfDB database at http://candidaorfeome.eu. We also engineered 49 expression vectors with a choice of promoters, tags and selection markers and demonstrated their applicability to the study of target ORFs transferred from the C. albicans ORFeome. In addition, the use of the ORFeome in the detection of protein-protein interaction was demonstrated. Mating-compatible strains as well as Gateway™-compatible two-hybrid vectors were engineered, validated and used in a proof of concept experiment. These unique and valuable resources should greatly facilitate future functional studies in C. albicans and the elucidation of mechanisms that underlie its pathogenicity.

Iron-sulfur protein maturation in Helicobacter pylori: identifying a Nfu-type cluster carrier protein and its iron-sulfur protein targets

Helicobacter pylori is anomalous among non nitrogen-fixing bacteria in containing an incomplete NIF system for Fe-S cluster assembly comprising two essential proteins, NifS (cysteine desulfurase) and NifU (scaffold protein). Although nifU deletion strains cannot be obtained via the conventional gene replacement, a NifU-depleted strain was constructed and shown to be more sensitive to oxidative stress compared to wild-type (WT) strains. The hp1492 gene, encoding a putative Nfu-type Fe-S cluster carrier protein, was disrupted in three different H. pylori strains, indicating that it is not essential. However, Δnfu strains have growth deficiency, are more sensitive to oxidative stress and are unable to colonize mouse stomachs. Moreover, Δnfu strains have lower aconitase activity but higher hydrogenase activity than the WT. Recombinant Nfu was found to bind either one [2Fe-2S] or [4Fe-4S] cluster/dimer, based on analytical, UV-visible absorption/CD and resonance Raman studies. A bacterial two-hybrid system was used to ascertain interactions between Nfu, NifS, NifU and each of 36 putative Fe-S-containing target proteins. Nfu, NifS and NifU were found to interact with 15, 6 and 29 putative Fe-S proteins respectively. The results indicate that Nfu, NifS and NifU play a major role in the biosynthesis and/or delivery of Fe-S clusters in H. pylori.

Proteome Data Improves Protein Function Prediction in the Interactome of Helicobacter pylori

Helicobacter pylori is a common pathogen that is estimated to infect half of the human population, causing several diseases such as duodenal ulcer. Despite one of the first pathogens to be sequenced, its proteome remains poorly characterized as about one-third of its proteins have no functional annotation. Here, we integrate and analyze known protein interactions with proteomic and genomic data from different sources. We find that proteins with similar abundances tend to interact. Such an observation is accompanied by a trend of interactions to appear between proteins of similar functions, although some show marked cross-talk to others. Protein function prediction with protein interactions is significantly improved when interactions from other bacteria are included in our network, allowing us to obtain putative functions of more than 300 poorly or previously uncharacterized proteins. Proteins that are critical for the topological controllability of the underlying network are significantly enriched with genes that are up-regulated in the spiral compared with the coccoid form of H. pylori Determining their evolutionary conservation, we present evidence that 80 protein complexes are identical in composition with their counterparts in Escherichia coli, while 85 are partially conserved and 120 complexes are completely absent. Furthermore, we determine network clusters that coincide with related functions, gene essentiality, genetic context, cellular localization, and gene expression in different cellular states.

Integration of fluorescence imaging with proteomics enables visualization and identification of metallo-proteomes in living cells

Metalloproteins account for nearly one-third of proteins in proteomes. To date, the identification of metalloproteins relies mainly on protein purification and the subsequent characterization of bound metals, which often leads to losses of metal ions bound weakly and transiently. Herein, we developed a strategy to visualize and subsequently identify endogenous metalloproteins and metal-binding proteins in living cells via integration of fluorescence imaging with proteomics. We synthesized a "metal-tunable" fluorescent probe (denoted as Mⁿ⁺-TRACER) that rapidly enters cells to target proteins with 4-40 fold fluorescence enhancements. By using Ni²⁺-TRACER as an example, we demonstrate the feasibility of tracking Ni²⁺-binding proteins in vitro, while cellular small molecules exhibit negligible interference on the labeling. We identified 44 Ni²⁺-binding proteins from microbes using Helicobacter pylori as a showcase. We further applied Cu²⁺-TRACER to mammalian cells and found 54 Cu²⁺-binding proteins. The strategy we report here provides a great opportunity to track various endogenous metallo-proteomes and to mine potential targets of metallodrugs.

Prediction of Host-Pathogen Interactions for Helicobacter pylori by Interface Mimicry and Implications to Gastric Cancer

There is a strong correlation between some pathogens and certain cancer types. One example is Helicobacter pylori and gastric cancer. Exactly how they contribute to host tumorigenesis is, however, a mystery. Pathogens often interact with the host through proteins. To subvert defense, they may mimic host proteins at the sequence, structure, motif, or interface levels. Interface similarity permits pathogen proteins to compete with those of the host for a target protein and thereby alter the host signaling. Detection of host-pathogen interactions (HPIs) and mapping the re-wired superorganism HPI network-with structural details-can provide unprecedented clues to the underlying mechanisms and help therapeutics. Here, we describe the first computational approach exploiting solely interface mimicry to model potential HPIs. Interface mimicry can identify more HPIs than sequence or complete structural similarity since it appears more common than the other mimicry types. We illustrate the usefulness of this concept by modeling HPIs of H. pylori to understand how they modulate host immunity, persist lifelong, and contribute to tumorigenesis. H. pylori proteins interfere with multiple host pathways as they target several host hub proteins. Our results help illuminate the structural basis of resistance to apoptosis, immune evasion, and loss of cell junctions seen in H. pylori-infected host cells.

A protein-protein interaction dictates Borrelial infectivity

Two Borrelia burgdorferi interacting proteins, BB0238 and BB0323, play distinct roles in pathogen biology and infectivity although a significance of their interaction remained enigmatic. Here we identified the polypeptide segment essential for BB0238-BB0323 interaction and examined how it supports spirochete infectivity. We show that the interaction region in BB0323 requires amino acid residues 22-200, suggesting that the binding encompasses discontinuous protein segments. In contrast, the interaction region in BB0238 spans only 11 amino acids, residues 120-130. A deletion of these 11 amino acids neither alters the overall secondary structure of the protein, nor affects its stability or oligomerization property, however, it reduces the post-translational stability of the binding partner, BB0323. Mutant B. burgdorferi isolates producing BB0238 lacking the 11-amino acid interaction region were able to persist in ticks but failed to transmit to mice or to establish infection. These results suggest that BB0238-BB0323 interaction is critical for post-translational stability of BB0323, and that this interaction is important for mammalian infectivity and transmission of B. burgdorferi. We show that saturation or inhibition of BB0238-BB0323 interaction could be studied in a luciferase assay, which could be amenable for future identification of small molecule inhibitors to combat B. burgdorferi infection.

The Protein Interactome of Streptococcus pneumoniae and Bacterial Meta-interactomes Improve Function Predictions

Identification of protein interactions in bacterial species can help define the individual roles that proteins play in cellular pathways and pathogenesis. Very few protein interactions have been identified for the important human pathogen S. pneumoniae. We used an experimental approach to identify over 2,000 new protein interactions for S. pneumoniae, the most extensive interactome data for this bacterium to date. To predict protein function, we used our interactome data augmented with interactions from other closely related bacteria. The combination of the experimental data and meta-interactome data significantly improved the prediction results, allowing us to assign possible functions to a large number of poorly characterized proteins.

The functions of roughly a third of all proteins in Streptococcus pneumoniae, a significant human-pathogenic bacterium, are unknown. Using a yeast two-hybrid approach, we have determined more than 2,000 novel protein interactions in this organism. We augmented this network with meta-interactome data that we defined as the pool of all interactions between evolutionarily conserved proteins in other bacteria. We found that such interactions significantly improved our ability to predict a protein’s function, allowing us to provide functional predictions for 299 S. pneumoniae proteins with previously unknown functions.

IMPORTANCE Identification of protein interactions in bacterial species can help define the individual roles that proteins play in cellular pathways and pathogenesis. Very few protein interactions have been identified for the important human pathogen S. pneumoniae. We used an experimental approach to identify over 2,000 new protein interactions for S. pneumoniae, the most extensive interactome data for this bacterium to date. To predict protein function, we used our interactome data augmented with interactions from other closely related bacteria. The combination of the experimental data and meta-interactome data significantly improved the prediction results, allowing us to assign possible functions to a large number of poorly characterized proteins.

Novel protein interactions with an actin homolog (MreB) of Helicobacter pylori determined by bacterial two-hybrid system

The bacterium Helicobacter pylori infects more than 50% of the world population and causes several gastroduodenal diseases, including gastric cancer. Nevertheless, we still need to explore some protein interactions that may be involved in pathogenesis. MreB, an actin homolog, showed some special characteristics in previous studies, indicating that it could have different functions. Protein functions could be realized via protein-protein interactions. In the present study, the MreB protein from H. pylori 26695 fused with two tags 10×His and GST in tandem was overexpressed and purified from Escherchia coli. The purified recombinant protein was used to perform a pull-down assay with H. pylori 26695 cell lysate. The pulled-down proteins were identified by mass spectrometry (MALDI-TOF), in which the known important proteins related to morphogenesis were absent but several proteins related to pathogenesis process were observed. The bacterial two-hybrid system was further used to evaluate the protein interactions and showed that new interactions of MreB respectively with VacA, UreB, HydB, HylB and AddA were confirmed but the interaction MreB-MreC was not validated. These results indicated that the protein MreB in H. pylori has a distinct interactome, does not participate in cell morphogenesis via MreB-MreC but could be related to pathogenesis.

Bacterial protein meta-interactomes predict cross-species interactions and protein function

Background

Protein-protein interactions (PPIs) can offer compelling evidence for protein function, especially when viewed in the context of proteome-wide interactomes. Bacteria have been popular subjects of interactome studies: more than six different bacterial species have been the subjects of comprehensive interactome studies while several more have had substantial segments of their proteomes screened for interactions. The protein interactomes of several bacterial species have been completed, including several from prominent human pathogens. The availability of interactome data has brought challenges, as these large data sets are difficult to compare across species, limiting their usefulness for broad studies of microbial genetics and evolution.

Results

In this study, we use more than 52,000 unique protein-protein interactions (PPIs) across 349 different bacterial species and strains to determine their conservation across data sets and taxonomic groups. When proteins are collapsed into orthologous groups (OGs) the resulting meta-interactome still includes more than 43,000 interactions, about 14,000 of which involve proteins of unknown function. While conserved interactions provide support for protein function in their respective species data, we found only 429 PPIs (~1% of the available data) conserved in two or more species, rendering any cross-species interactome comparison immediately useful. The meta-interactome serves as a model for predicting interactions, protein functions, and even full interactome sizes for species with limited to no experimentally observed PPI, including Bacillus subtilis and Salmonella enterica which are predicted to have up to 18,000 and 31,000 PPIs, respectively.

Conclusions

In the course of this work, we have assembled cross-species interactome comparisons that will allow interactomics researchers to anticipate the structures of yet-unexplored microbial interactomes and to focus on well-conserved yet uncharacterized interactors for further study. Such conserved interactions should provide evidence for important but yet-uncharacterized aspects of bacterial physiology and may provide targets for anti-microbial therapies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1585-0) contains supplementary material, which is available to authorized users.

BindML/BindML+: Detecting Protein-Protein Interaction Interface Propensity from Amino Acid Substitution Patterns

Prediction of protein-protein interaction sites in a protein structure provides important information for elucidating the mechanism of protein function and can also be useful in guiding a modeling or design procedures of protein complex structures. Since prediction methods essentially assess the propensity of amino acids that are likely to be part of a protein docking interface, they can help in designing protein-protein interactions. Here, we introduce BindML and BindML+ protein-protein interaction sites prediction methods. BindML predicts protein-protein interaction sites by identifying mutation patterns found in known protein-protein complexes using phylogenetic substitution models. BindML+ is an extension of BindML for distinguishing permanent and transient types of protein-protein interaction sites. We developed an interactive web-server that provides a convenient interface to assist in structural visualization of protein-protein interactions site predictions. The input data for the web-server are a tertiary structure of interest. BindML and BindML+ are available at http://kiharalab.org/bindml/ and http://kiharalab.org/bindml/plus/ .

Identification of YbeY-Protein Interactions Involved in 16S rRNA Maturation and Stress Regulation in Escherichia coli

YbeY is part of a core set of RNases in Escherichia coli and other bacteria. This highly conserved endoribonuclease has been implicated in several important processes such as 16S rRNA 3' end maturation, 70S ribosome quality control, and regulation of mRNAs and small noncoding RNAs, thereby affecting cellular viability, stress tolerance, and pathogenic and symbiotic behavior of bacteria. Thus, YbeY likely interacts with numerous protein or RNA partners that are involved in various aspects of cellular physiology. Using a bacterial two-hybrid system, we identified several proteins that interact with YbeY, including ribosomal protein S11, the ribosome-associated GTPases Era and Der, YbeZ, and SpoT. In particular, the interaction of YbeY with S11 and Era provides insight into YbeY's involvement in the 16S rRNA maturation process. The three-way association between YbeY, S11, and Era suggests that YbeY is recruited to the ribosome where it could cleave the 17S rRNA precursor endonucleolytically at or near the 3' end maturation site. Analysis of YbeY missense mutants shows that a highly conserved beta-sheet in YbeY-and not amino acids known to be important for YbeY's RNase activity-functions as the interface between YbeY and S11. This protein-interacting interface of YbeY is needed for correct rRNA maturation and stress regulation, as missense mutants show significant phenotypic defects. Additionally, structure-based in silico prediction of putative interactions between YbeY and the Era-30S complex through protein docking agrees well with the in vivo results.

IMPORTANCE

Ribosomes are ribonucleoprotein complexes responsible for a key cellular function, protein synthesis. Their assembly is a highly coordinated process of RNA cleavage, RNA posttranscriptional modification, RNA conformational changes, and protein-binding events. Many open questions remain after almost 5 decades of study, including which RNase is responsible for final processing of the 16S rRNA 3' end. The highly conserved RNase YbeY, belonging to a core set of RNases essential in many bacteria, was previously shown to participate in 16S rRNA processing and ribosome quality control. However, detailed mechanistic insight into YbeY's ribosome-associated function has remained elusive. This work provides the first evidence that YbeY is recruited to the ribosome through interaction with proteins involved in ribosome biogenesis (i.e., ribosomal protein S11, Era). In addition, we identified key residues of YbeY involved in the interaction with S11 and propose a possible binding mode of YbeY to the ribosome using in silico docking.

In silico identification of essential proteins in Corynebacterium pseudotuberculosis based on protein-protein interaction networks

Background

Corynebacterium pseudotuberculosis (Cp) is a gram-positive bacterium that is classified into equi and ovis serovars. The serovar ovis is the etiological agent of caseous lymphadenitis, a chronic infection affecting sheep and goats, causing economic losses due to carcass condemnation and decreased production of meat, wool, and milk. Current diagnosis or treatment protocols are not fully effective and, thus, require further research of Cp pathogenesis.

Results

Here, we mapped known protein-protein interactions (PPI) from various species to nine Cp strains to reconstruct parts of the potential Cp interactome and to identify potentially essential proteins serving as putative drug targets. On average, we predict 16,669 interactions for each of the nine strains (with 15,495 interactions shared among all strains). An in silico sanity check suggests that the potential networks were not formed by spurious interactions but have a strong biological bias. With the inferred Cp networks we identify 181 essential proteins, among which 41 are non-host homologous.

Conclusions

The list of candidate interactions of the Cp strains lay the basis for developing novel hypotheses and designing according wet-lab studies. The non-host homologous essential proteins are attractive targets for therapeutic and diagnostic proposes. They allow for searching of small molecule inhibitors of binding interactions enabling modern drug discovery. Overall, the predicted Cp PPI networks form a valuable and versatile tool for researchers interested in Corynebacterium pseudotuberculosis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0346-4) contains supplementary material, which is available to authorized users.

Identification of putative Z-ring-associated proteins, involved in cell division in human pathogenic bacteria Helicobacter pylori

Cell division in bacteria is initiated by FtsZ, which forms a Z ring at the middle of the cell, between the nucleoids. The Z ring is stabilized by Z ring-associated proteins (Zaps), which crosslink the FtsZ filaments and provide strength. The deletion of Zaps leads to the elongation phenotype with an abnormal Z ring. The components of cell division in Helicobacter pylori are similar to other gram negative bacteria except for the absence of few components including Zaps. Here, we used HHsearch to identify homologs of the missing cell division proteins and got potential hits for ZapA and ZapB, as well as for few other cell division proteins. We further validated the function of the putative ZapA homolog by genetic complementation, immuno-colocalization and biochemical analysis.

The interactome of Streptococcus pneumoniae and its bacteriophages show highly specific patterns of interactions among bacteria and their phages

Although an abundance of bacteriophages exists, little is known about interactions between their proteins and those of their bacterial hosts. Here, we experimentally determined the phage-host interactomes of the phages Dp-1 and Cp-1 and their underlying protein interaction network in the host Streptococcus pneumoniae. We compared our results to the interaction patterns of E. coli phages lambda and T7. Dp-1 and Cp-1 target highly connected host proteins, occupy central network positions, and reach many protein clusters through the interactions of their targets. In turn, lambda and T7 targets cluster to conserved and essential proteins in E. coli, while such patterns were largely absent in S. pneumoniae. Furthermore, targets in E. coli were mutually strongly intertwined, while targets of Dp-1 and Cp-1 were strongly connected through essential and orthologous proteins in their immediate network vicinity. In both phage-host systems, the impact of phages on their protein targets appears to extend from their network neighbors, since proteins that interact with phage targets were located in central network positions, have a strong topologically disruptive effect and touch complexes with high functional heterogeneity. Such observations suggest that the phages, biological impact is accomplished through a surprisingly limited topological reach of their targets.

Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions

Identifying protein-protein interactions (PPIs) at an acceptable false discovery rate (FDR) is challenging. Previously we identified several hundred PPIs from affinity purification - mass spectrometry (AP-MS) data for the bacteria Escherichia coli and Desulfovibrio vulgaris. These two interactomes have lower FDRs than any of the nine interactomes proposed previously for bacteria and are more enriched in PPIs validated by other data than the nine earlier interactomes. To more thoroughly determine the accuracy of ours or other interactomes and to discover further PPIs de novo, here we present a quantitative tagless method that employs iTRAQ MS to measure the copurification of endogenous proteins through orthogonal chromatography steps. 5273 fractions from a four-step fractionation of a D. vulgaris protein extract were assayed, resulting in the detection of 1242 proteins. Protein partners from our D. vulgaris and E. coli AP-MS interactomes copurify as frequently as pairs belonging to three benchmark data sets of well-characterized PPIs. In contrast, the protein pairs from the nine other bacterial interactomes copurify two- to 20-fold less often. We also identify 200 high confidence D. vulgaris PPIs based on tagless copurification and colocalization in the genome. These PPIs are as strongly validated by other data as our AP-MS interactomes and overlap with our AP-MS interactome for D.vulgaris within 3% of expectation, once FDRs and false negative rates are taken into account. Finally, we reanalyzed data from two quantitative tagless screens of human cell extracts. We estimate that the novel PPIs reported in these studies have an FDR of at least 85% and find that less than 7% of the novel PPIs identified in each screen overlap. Our results establish that a quantitative tagless method can be used to validate and identify PPIs, but that such data must be analyzed carefully to minimize the FDR.

'Modulation of the enzymatic activities of replicative helicase (DnaB) by interaction with Hp0897: a possible mechanism for helicase loading in Helicobacter pylori'

DNA replication in Helicobacter pylori is initiated from a unique site (oriC) on its chromosome where several proteins assemble to form a functional replisome. The assembly of H. pylori replication machinery is similar to that of the model gram negative bacterium Escherichia coli except for the absence of DnaC needed to recruit the hexameric DnaB helicase at the replisome assembly site. In the absence of an obvious DnaC homologue in H. pylori, the question arises as to whether HpDnaB helicase is loaded at the Hp-replication origin by itself or is assisted by other unidentified protein(s). A high-throughput yeast two-hybrid study has revealed two proteins of unknown functions (Hp0897 and Hp0340) that interact with HpDnaB. Here we demonstrate that Hp0897 interacts with HpDnaB helicase in vitro as well as in vivo. Furthermore, the interaction stimulates the DNA binding activity of HpDnaB and modulates its adenosine triphosphate hydrolysis and helicase activities significantly. Prior complex formation of Hp0897 and HpDnaB enhances the binding/loading of DnaB onto DNA. Hp0897, along with HpDnaB, colocalizes with replication complex at initiation but does not move with the replisome during elongation. Together, these results suggest a possible role of Hp0897 in loading of HpDnaB at oriC.

Bacterial Interactomes: Interacting Protein Partners Share Similar Function and Are Validated in Independent Assays More Frequently Than Previously Reported

Numerous affinity purification-mass spectrometry (AP-MS) and yeast two-hybrid screens have each defined thousands of pairwise protein-protein interactions (PPIs), most of which are between functionally unrelated proteins. The accuracy of these networks, however, is under debate. Here, we present an AP-MS survey of the bacterium Desulfovibrio vulgaris together with a critical reanalysis of nine published bacterial yeast two-hybrid and AP-MS screens. We have identified 459 high confidence PPIs from D. vulgaris and 391 from Escherichia coli Compared with the nine published interactomes, our two networks are smaller, are much less highly connected, and have significantly lower false discovery rates. In addition, our interactomes are much more enriched in protein pairs that are encoded in the same operon, have similar functions, and are reproducibly detected in other physical interaction assays than the pairs reported in prior studies. Our work establishes more stringent benchmarks for the properties of protein interactomes and suggests that bona fide PPIs much more frequently involve protein partners that are annotated with similar functions or that can be validated in independent assays than earlier studies suggested.

Prediction and characterization of protein-protein interaction network in Bacillus licheniformis WX-02

In this study, we constructed a protein-protein interaction (PPI) network of B. licheniformis strain WX-02 with interolog method and domain-based method, which contained 15,864 edges and 2,448 nodes. Although computationally predicted networks have relatively low coverage and high false-positive rate, our prediction was confirmed from three perspectives: local structural features, functional similarities and transcriptional correlations. Further analysis of the COG heat map showed that protein interactions in B. licheniformis WX-02 mainly occurred in the same functional categories. By incorporating the transcriptome data, we found that the topological properties of the PPI network were robust under normal and high salt conditions. In addition, 267 different protein complexes were identified and 117 poorly characterized proteins were annotated with certain functions based on the PPI network. Furthermore, the sub-network showed that a hub protein CcpA jointed directly or indirectly many proteins related to γ-PGA synthesis and regulation, such as PgsB, GltA, GltB, ProB, ProJ, YcgM and two signal transduction systems ComP-ComA and DegS-DegU. Thus, CcpA might play an important role in the regulation of γ-PGA synthesis. This study therefore will facilitate the understanding of the complex cellular behaviors and mechanisms of γ-PGA synthesis in B. licheniformis WX-02.

Proteomic analysis of the TerC interactome: Novel links to tellurite resistance and pathogenicity

The tellurite resistance gene operon (ter) is widely spread among bacterial species, particularly pathogenic species. The ter operon has been implicated in tellurite resistance, phage inhibition, colicine resistance, and pathogenicity. The TerC protein represents one of the key proteins in tellurite resistance and shows no significant homology to any protein of known function. So far, there is no experimental evidence for TerC interaction partners. In this study, proteomic-based methods, including blue native electrophoresis and co-immunoprecipitation combined with LC-MS/MS, have been used to identify TerC interaction partners and thus providing indirect evidence for tentative functions of TerC in Escherichia coli. An interactome has been constructed and robust physical interaction of integral membrane protein TerC with TerB, DctA, PspA, HslU, and RplK has been shown. The TerC-TerB complex appears to act as a central unit that may link different functional modules with biochemical activities of C4-dicarboxylate transport, inner membrane stress response (phage shock protein regulatory complex), ATPase/chaperone activity, and proteosynthesis. In previous reports, it was hypothesized that a transmembrane unit formed by TerC protein may interact with the TerD family, but herein neither TerD nor TerE proteins were identified as TerC complex components. We propose that TerD/TerE participates in tellurite resistance through TerC-independent action.

Using host-pathogen protein interactions to identify and characterize Francisella tularensis virulence factors

Background

Francisella tularensis is a select bio-threat agent and one of the most virulent intracellular pathogens known, requiring just a few organisms to establish an infection. Although several virulence factors are known, we lack an understanding of virulence factors that act through host-pathogen protein interactions to promote infection. To address these issues in the highly infectious F. tularensis subsp. tularensis Schu S4 strain, we deployed a combined in silico, in vitro, and in vivo analysis to identify virulence factors and their interactions with host proteins to characterize bacterial infection mechanisms.

Results

We initially used comparative genomics and literature to identify and select a set of 49 putative and known virulence factors for analysis. Each protein was then subjected to proteome-scale yeast two-hybrid (Y2H) screens with human and murine cDNA libraries to identify potential host-pathogen protein-protein interactions. Based on the bacterial protein interaction profile with both hosts, we selected seven novel putative virulence factors for mutant construction and animal validation experiments. We were able to create five transposon insertion mutants and used them in an intranasal BALB/c mouse challenge model to establish 50 % lethal dose estimates. Three of these, ΔFTT0482c, ΔFTT1538c, and ΔFTT1597, showed attenuation in lethality and can thus be considered novel F. tularensis virulence factors. The analysis of the accompanying Y2H data identified intracellular protein trafficking between the early endosome to the late endosome as an important component in virulence attenuation for these virulence factors. Furthermore, we also used the Y2H data to investigate host protein binding of two known virulence factors, showing that direct protein binding was a component in the modulation of the inflammatory response via activation of mitogen-activated protein kinases and in the oxidative stress response.

Conclusions

Direct interactions with specific host proteins and the ability to influence interactions among host proteins are important components for F. tularensis to avoid host-cell defense mechanisms and successfully establish an infection. Although direct host-pathogen protein-protein binding is only one aspect of Francisella virulence, it is a critical component in directly manipulating and interfering with cellular processes in the host cell.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2351-1) contains supplementary material, which is available to authorized users.

Mapping the Protein-Protein Interactome Networks Using Yeast Two-Hybrid Screens

The yeast two-hybrid system (Y2H) is a powerful method to identify binary protein-protein interactions in vivo. Here we describe Y2H screening strategies that use defined libraries of open reading frames (ORFs) and cDNA libraries. The array-based Y2H system is well suited for interactome studies of small genomes with an existing ORFeome clones preferentially in a recombination based cloning system. For large genomes, pooled library screening followed by Y2H pairwise retests may be more efficient in terms of time and resources, but multiple sampling is necessary to ensure comprehensive screening. While the Y2H false positives can be efficiently reduced by using built-in controls, retesting, and evaluation of background activation; implementing the multiple variants of the Y2H vector systems is essential to reduce the false negatives and ensure comprehensive coverage of an interactome.

An improved interolog mapping-based computational prediction of protein–protein interactions with increased network coverage

Automated and efficient methods that map ortholog interactions from several organisms and public databases (pDB) are needed to identify new interactions in an organism of interest (interolog mapping).