A proteome-wide protein interaction map for Campylobacter jejuni

High molecular/low acetylated chitosans reduce adhesion of Campylobacter jejuni to host cells by blocking JlpA

Infections caused by Campylobacter spp. are a major cause of severe enteritis worldwide. Multifactorial prevention strategies are necessary to reduce the prevalence of Campylobacter. In particular, antiadhesive strategies with specific inhibitors of early host-pathogen interaction are promising approaches to reduce the bacterial load. An in vitro flow cytometric adhesion assay was established to study the influence of carbohydrates on the adhesion of C. jejuni to Caco-2 cells. Chitosans with a high degree of polymerization and low degree of acetylation were identified as potent antiadhesive compounds, exerting significant reduction of C. jejuni adhesion to Caco-2 cells at non-toxic concentrations. Antiadhesive and also anti-invasive effects were verified by confocal laser scanning microscopy. For target identification, C. jejuni adhesins FlpA and JlpA were expressed in Escherichia coli ArcticExpress, and the influence of chitosan on binding to fibronectin and HSP90α, respectively, was investigated. While no effects on FlpA binding were found, a strong inhibition of JlpA-HSP90α binding was observed. To simulate real-life conditions, chicken meat was inoculated with C. jejuni, treated with antiadhesive chitosan, and the bacterial load was quantified. A strong reduction of C. jejuni load was observed. Atomic force microscopy revealed morphological changes of C. jejuni after 2 h of chitosan treatment, indicating disturbance of the cell wall and sacculi formation by electrostatic interaction of positively charged chitosan with the negatively charged cell surface. In conclusion, our data indicate promising antiadhesive and anti-invasive potential of high molecular weight, strongly de-acetylated chitosans for reducing C. jejuni load in livestock and food production. KEY POINTS: • Antiadhesive effects of chitosan with high DP/low DA against C. jejuni to host cells • Specific targeting of JlpA/Hsp90α interaction by chitosan • Meat treatment with chitosan reduces C. jejuni load.

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.

Cj0683 Is a Competence Protein Essential for Efficient Initialization of DNA Uptake in Campylobacter jejuni

C. jejuni is an important food-borne pathogen displaying high genetic diversity, substantially based on natural transformation. The mechanism of DNA uptake from the environment depends on a type II secretion/type IV pilus system, whose components are partially known. Here, we quantified DNA uptake in C. jejuni at the single cell level and observed median transport capacities of approximately 30 kb per uptake location. The process appeared to be limited by the initialization of DNA uptake, was finite, and, finalized within 30 min of contact to DNA. Mutants lacking either the outer membrane pore PilQ or the inner membrane channel ComEC were deficient in natural transformation. The periplasmic DNA binding protein ComE was negligible for DNA uptake, which is in contrast to its proposed function. Intriguingly, a mutant lacking the unique periplasmic protein Cj0683 displayed rare but fully functional DNA uptake events. We conclude that Cj0683 was essential for the efficient initialization of DNA uptake, consistent with the putative function as a competence pilus protein. Unravelling features important in natural transformation might lead to target identification, reducing the adaptive potential of pathogens.

Two-component regulatory systems in Helicobacter pylori and Campylobacter jejuni: Attractive targets for novel antibacterial drugs

Two-component regulatory systems (TCRS) are ubiquitous signal transduction mechanisms evolved by bacteria for sensing and adapting to the constant changes that occur in their environment. Typically consisting of two types of proteins, a membrane sensor kinase and an effector cytosolic response regulator, the TCRS modulate via transcriptional regulation a plethora of key physiological processes, thereby becoming essential for bacterial viability and/or pathogenicity and making them attractive targets for novel antibacterial drugs. Some members of the phylum Campylobacterota (formerly Epsilonproteobacteria), including Helicobacter pylori and Campylobacter jejuni, have been classified by WHO as “high priority pathogens” for research and development of new antimicrobials due to the rapid emergence and dissemination of resistance mechanisms against first-line antibiotics and the alarming increase of multidrug-resistant strains worldwide. Notably, these clinically relevant pathogens express a variety of TCRS and orphan response regulators, sometimes unique among its phylum, that control transcription, translation, energy metabolism and redox homeostasis, as well as the expression of relevant enzymes and virulence factors. In the present mini-review, we describe the signalling mechanisms and functional diversity of TCRS in H. pylori and C. jejuni, and provide an overview of the most recent findings in the use of these microbial molecules as potential novel therapeutic targets for the development of new antibiotics.

ComFC mediates transport and handling of single-stranded DNA during natural transformation

The ComFC protein is essential for natural transformation, a process that plays a major role in the spread of antibiotic resistance genes and virulence factors across bacteria. However, its role remains largely unknown. Here, we show that Helicobacter pylori ComFC is involved in DNA transport through the cell membrane, and is required for the handling of the single-stranded DNA once it is delivered into the cytoplasm. The crystal structure of ComFC includes a zinc-finger motif and a putative phosphoribosyl transferase domain, both necessary for the protein's in vivo activity. Furthermore, we show that ComFC is a membrane-associated protein with affinity for single-stranded DNA. Our results suggest that ComFC provides the link between the transport of the transforming DNA into the cytoplasm and its handling by the recombination machinery.

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.

A large-scale prediction of protein-protein interactions based on random forest and matrix of sequence

Protein-protein interaction (PPIs) is an important part of many life activities in organisms, and the prediction of protein-protein interactions is closely related to protein function, disease occurrence, and disease treatment. In order to optimize the prediction performance of protein interactions, here a RT-MOS model was constructed based on Random Forest (RF) and Matrix of Sequence (MOS) to predict protein-protein interactions. Firstly, MOS is used to encode the protein sequences into a 29-dimensional feature vector; Then, a prediction model RT-MOS is build based on random forest, and the RT-MOS model is optimized and evaluated using the test set; Finally, the optimized model RT-MOS is used for prediction. The experimental results show that the accuracy rates of the RT-MOS model on the benchmark dataset and the non-redundant dataset are 97.18% and 91.34%, respectively, and the accuracies on four external datasets of C.elegans, Drosophila, E.coli and H.sapiens are 96.21%, 97.86%, 97.54% and 97.75%, respectively. Compared with the existing methods, it is found that it is superior to the existing methods. The experimental results show that the model RT-MOS has the advantages of saving time, preventing overfitting and high accuracy, and is suitable for large-scale PPIs prediction.

The Campylobacter jejuni Response Regulator and Cyclic-Di-GMP Binding CbrR Is a Novel Regulator of Flagellar Motility

A leading cause of bacterial gastroenteritis, Campylobacter jejuni is also associated with broad sequelae, including extragastrointestinal conditions such as reactive arthritis and Guillain-Barré Syndrome (GBS). CbrR is a C. jejuni response regulator that is annotated as a diguanylate cyclase (DGC), an enzyme that catalyzes the synthesis of c-di-GMP, a universal bacterial second messenger, from GTP. In C. jejuni DRH212, we constructed an unmarked deletion mutant, cbrR^-, and complemented mutant, cbrR⁺. Motility assays indicated a hyper-motile phenotype associated with cbrR^-, whereas motility was deficient in cbrR⁺. The overexpression of CbrR in cbrR⁺ was accompanied by a reduction in expression of FlaA, the major flagellin. Biofilm assays and scanning electron microscopy demonstrated similarities between DRH212 and cbrR^-; however, cbrR⁺ was unable to form significant biofilms. Transmission electron microscopy showed similar cell morphology between the three strains; however, cbrR⁺ cells lacked flagella. Differential radial capillary action of ligand assays (DRaCALA) showed that CbrR binds GTP and c-di-GMP. Liquid chromatography tandem mass spectrometry detected low levels of c-di-GMP in C. jejuni and in E. coli expressing CbrR. CbrR is therefore a negative regulator of FlaA expression and motility, a critical virulence factor in C. jejuni pathogenesis.

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.

Inactivation of the core cheVAWY chemotaxis genes disrupts chemotactic motility and organised biofilm formation in Campylobacter jejuni

Flagellar motility plays a central role in the bacterial foodborne pathogen Campylobacter jejuni, as flagellar motility is required for reaching the intestinal epithelium and subsequent colonisation or disease. Flagellar proteins also contribute strongly to biofilm formation during transmission. Chemotaxis is the process directing flagellar motility in response to attractant and repellent stimuli, but its role in biofilm formation of C. jejuni is not well understood. Here we show that inactivation of the core chemotaxis genes cheVAWY in C. jejuni strain NCTC 11168 affects both chemotactic motility and biofilm formation. Inactivation of any of the core chemotaxis genes (cheA, cheY, cheV or cheW) impaired chemotactic motility but did not affect flagellar assembly or growth. The ∆cheY mutant swam in clockwise loops, while complementation restored normal motility. Inactivation of the core chemotaxis genes interfered with the ability to form a discrete biofilm at the air-media interface, and the ∆cheY mutant displayed reduced dispersal/shedding of bacteria into the planktonic fraction. This suggests that while the chemotaxis system is not required for biofilm formation per se, it is necessary for organized biofilm formation. Hence interference with the Campylobacter chemotaxis system at any level disrupts optimal chemotactic motility and transmission modes such as biofilm formation.

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.

Assigning a role for chemosensory signal transduction in Campylobacter jejuni biofilms using a combined omics approach

Biofilms of the gastroenteric pathogen C. jejuni may serve an important role in the transmission of infection from reservoirs of infection to humans. Herein, we undertook a combinatorial approach examining differential gene expression and protein abundance during biofilm formation in C. jejuni. Biofilms induced a substantial rearrangement of the C. jejuni transcriptome and proteome, with ~600 genes differentially expressed when compared to planktonic cells. Genes and proteins induced in biofilms were involved in iron metabolism and acquisition, cell division, glycan production and attachment, while those repressed were associated with metabolism, amino acid usage, and large tracts of the chemotaxis pathway. We further examined the role of chemotaxis in C. jejuni biofilm formation by examining isogenic strains with deletions of the cheV and cheW signal transduction genes. Both ∆cheV and ∆cheW exhibited a significant decrease in directed motility when compared to wild-type C. jejuni as well as demonstrating an increase in autoagglutination ability and biofilm formation. A subtle difference was also observed between the phenotypes of ∆cheV and ∆cheW mutants, both in motility and biofilm formation. This suggests roles for CheV and CheW and may present signal transduction as a potential method for modulating C. jejuni biofilm formation.

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.

Protein-Protein Interactions in Candida albicans

Despite being one of the most important human fungal pathogens, Candida albicans has not been studied extensively at the level of protein-protein interactions (PPIs) and data on PPIs are not readily available in online databases. In January 2018, the database called "Biological General Repository for Interaction Datasets (BioGRID)" that contains the most PPIs for C. albicans, only documented 188 physical or direct PPIs (release 3.4.156) while several more can be found in the literature. Other databases such as the String database, the Molecular INTeraction Database (MINT), and the Database for Interacting Proteins (DIP) database contain even fewer interactions or do not even include C. albicans as a searchable term. Because of the non-canonical codon usage of C. albicans where CUG is translated as serine rather than leucine, it is often problematic to use the yeast two-hybrid system in Saccharomyces cerevisiae to study C. albicans PPIs. However, studying PPIs is crucial to gain a thorough understanding of the function of proteins, biological processes and pathways. PPIs can also be potential drug targets. To aid in creating PPI networks and updating the BioGRID, we performed an exhaustive literature search in order to provide, in an accessible format, a more extensive list of known PPIs in C. albicans.

Analysis of protein targets in pathogen-host interaction in infectious diseases: a case study on Plasmodium falciparum and Homo sapiens interaction network

Infection and disease progression is the outcome of protein interactions between pathogen and host. Pathogen, the role player of Infection, is becoming a severe threat to life as because of its adaptability toward drugs and evolutionary dynamism in nature. Identifying protein targets by analyzing protein interactions between host and pathogen is the key point. Proteins with higher degree and possessing some topologically significant graph theoretical measures are found to be drug targets. On the other hand, exceptional nodes may be involved in infection mechanism because of some pathway process and biologically unknown factors. In this article, we attempt to investigate characteristics of host-pathogen protein interactions by presenting a comprehensive review of computational approaches applied on different infectious diseases. As an illustration, we have analyzed a case study on infectious disease malaria, with its causative agent Plasmodium falciparum acting as 'Bait' and host, Homo sapiens/human acting as 'Prey'. In this pathogen-host interaction network based on some interconnectivity and centrality properties, proteins are viewed as central, peripheral, hub and non-hub nodes and their significance on infection process. Besides, it is observed that because of sparseness of the pathogen and host interaction network, there may be some topologically unimportant but biologically significant proteins, which can also act as Bait/Prey. So, functional similarity or gene ontology mapping can help us in this case to identify these proteins.

DNN-PPI: A LARGE-SCALE PREDICTION OF PROTEIN–PROTEIN INTERACTIONS BASED ON DEEP NEURAL NETWORKS

Protein–protein interaction (PPI) is very important for various biological processes and has given rise to a series of prediction-computing methods. In spite of different computing methods in relation to PPI prediction, PPI network projects fail to perform on a large scale. Aiming at ensuring that PPI can be predicted effectively, we used a deep neural network (DNN) for the study of PPI prediction that is based on an amino acid sequence. We present a novel DNN-PPI model with an auto covariance (AC) descriptor and a conjoint triad (CT) descriptor for the prediction of PPI that is based only on the protein sequence information. The 10-fold cross-validation indicated that the best DNN-PPI model with CT achieved 97.65% accuracy, 98.96% recall and a 98.51% area under the curve (AUC). The model exhibits a prediction accuracy of 94.20–97.10% for other external datasets. All of these suggest the high validity of the proposed algorithm in relation to various species.

A Genome-Scale Co-Functional Network of Xanthomonas Genes Can Accurately Reconstruct Regulatory Circuits Controlled by Two-Component Signaling Systems

Bacterial species in the genus Xanthomonas infect virtually all crop plants. Although many genes involved in Xanthomonas virulence have been identified through molecular and cellular studies, the elucidation of virulence-associated regulatory circuits is still far from complete. Functional gene networks have proven useful in generating hypotheses for genetic factors of biological processes in various species. Here, we present a genome-scale co-functional network of Xanthomonas oryze pv. oryzae (Xoo) genes, XooNet (www.inetbio.org/xoonet/), constructed by integrating heterogeneous types of genomics data derived from Xoo and other bacterial species. XooNet contains 106,000 functional links, which cover approximately 83% of the coding genome. XooNet is highly predictive for diverse biological processes in Xoo and can accurately reconstruct cellular pathways regulated by two-component signaling transduction systems (TCS). XooNet will be a useful in silico research platform for genetic dissection of virulence pathways in Xoo.

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.

FliW controls growth-phase expression of Campylobacter jejuni flagellar and non-flagellar proteins via the post-transcriptional regulator CsrA

Campylobacter jejuni is an important human pathogen that causes 96 million cases of acute diarrheal disease worldwide each year. We have shown that C. jejuni CsrA is involved in the post-transcriptional regulation of more than 100 proteins, and altered expression of these proteins is presumably involved in the altered virulence-related phenotypes of a csrA mutant. Mutation of fliW results in C. jejuni cells that have greatly truncated flagella, are less motile, less able to form biofilms, and exhibit a reduced ability to colonize chicks. The loss of FliW results in the altered expression of 153 flagellar and non-flagellar proteins, the majority of which are members of the CsrA regulon. The number of proteins dysregulated in the fliW mutant was greater at mid-log phase (120 proteins) than at stationary phase (85 proteins); 52 proteins showed altered expression at both growth phases. Loss of FliW altered the growth-phase- and CsrA-mediated regulation of FlaA flagellin. FliW exerts these effects by binding to both FlaA and to CsrA, as evidenced by pull-down assays, protein-protein cross-linking, and size-exclusion chromatography. Taken together, these results show that CsrA-mediated regulation of both flagellar and non-flagellar proteins is modulated by direct binding of CsrA to the flagellar chaperone FliW. Changing FliW:CsrA stoichiometries at different growth phases allow C. jejuni to couple the expression of flagellar motility to metabolic and virulence characteristics.

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.

INDEX: Incremental depth extension approach for protein-protein interaction networks alignment

High-throughput methods have provided us with a large amount of data pertaining to protein-protein interaction networks. The alignment of these networks enables us to better understand biological systems. Given the fact that the alignment of networks is computationally intractable, it is important to introduce a more efficient and accurate algorithm which finds as large as possible similar areas among networks. This paper proposes a new algorithm named INDEX for the global alignment of protein-protein interaction networks. INDEX has multiple phases. First, it computes topological and biological scores of proteins and creates the initial alignment based on the proposed matching score strategy. Using networks topologies and aligned proteins, it then selects a set of high scoring proteins in each phase and extends new alignments around them until final alignment is obtained. Proposing a new alignment strategy, detailed consideration of matching scores, and growth of the alignment core has led INDEX to obtain a larger common connected subgraph with a much greater number of edges compared with previous methods. Regarding other measures such as edge correctness, symmetric substructure score, and runtime, the proposed algorithm performed considerably better than existing popular methods. Our results show that INDEX can be a promising method for identifying functionally conserved interactions.

AVAILABILITY

The INDEX executable file is available at https://github.com/a-mir/index/.

ModuleAlign: module-based global alignment of protein-protein interaction networks

MOTIVATION

As an increasing amount of protein-protein interaction (PPI) data becomes available, their computational interpretation has become an important problem in bioinformatics. The alignment of PPI networks from different species provides valuable information about conserved subnetworks, evolutionary pathways and functional orthologs. Although several methods have been proposed for global network alignment, there is a pressing need for methods that produce more accurate alignments in terms of both topological and functional consistency.

RESULTS

In this work, we present a novel global network alignment algorithm, named ModuleAlign, which makes use of local topology information to define a module-based homology score. Based on a hierarchical clustering of functionally coherent proteins involved in the same module, ModuleAlign employs a novel iterative scheme to find the alignment between two networks. Evaluated on a diverse set of benchmarks, ModuleAlign outperforms state-of-the-art methods in producing functionally consistent alignments. By aligning Pathogen-Human PPI networks, ModuleAlign also detects a novel set of conserved human genes that pathogens preferentially target to cause pathogenesis.

AVAILABILITY

http://ttic.uchicago.edu/∼hashemifar/ModuleAlign.html

CONTACT

canzar@ttic.edu or j3xu.ttic.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Importance of Campylobacter jejuni FliS and FliW in Flagella Biogenesis and Flagellin Secretion

Flagella-driven motility enables bacteria to reach their favorable niche within the host. The human foodborne pathogen Campylobacter jejuni produces two heavily glycosylated structural flagellins (FlaA and FlaB) that form the flagellar filament. It also encodes the non-structural FlaC flagellin which is secreted through the flagellum and has been implicated in host cell invasion. The mechanisms that regulate C. jejuni flagellin biogenesis and guide the proteins to the export apparatus are different from those in most other enteropathogens and are not fully understood. This work demonstrates the importance of the putative flagellar protein FliS in C. jejuni flagella assembly. A constructed fliS knockout strain was non-motile, displayed reduced levels of FlaA/B and FlaC flagellin, and carried severely truncated flagella. Pull-down and Far Western blot assays showed direct interaction of FliS with all three C. jejuni flagellins (FlaA, FlaB, and FlaC). This is in contrast to, the sensor and regulator of intracellular flagellin levels, FliW, which bound to FlaA and FlaB but not to FlaC. The FliS protein but not FliW preferred binding to glycosylated C. jejuni flagellins rather than to their non-glycosylated recombinant counterparts. Mapping of the binding region of FliS and FliW using a set of flagellin fragments showed that the C-terminal subdomain of the flagellin was required for FliS binding, whereas the N-terminal subdomain was essential for FliW binding. The separate binding subdomains required for FliS and FliW, the different substrate specificity, and the differential preference for binding of glycosylated flagellins ensure optimal processing and assembly of the C. jejuni flagellins.

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

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.

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.

Cooperation of two distinct coupling proteins creates chemosensory network connections

Although it is appreciated that bacterial chemotaxis systems rely on coupling, also called scaffold, proteins to both connect input receptors with output kinases and build interkinase connections that allow signal amplification, it is not yet clear why many systems use more than one coupling protein. We examined the distinct functions for multiple coupling proteins in the bacterial chemotaxis system of Helicobacter pylori, which requires two nonredundant coupling proteins for chemotaxis: CheW and CheV1, a hybrid of a CheW and a phosphorylatable receiver domain. We report that CheV1 and CheW have largely redundant abilities to interact with chemoreceptors and the CheA kinase, and both similarly activated CheA's kinase activity. We discovered, however, that they are not redundant for formation of the higher order chemoreceptor arrays that are known to form via CheA-CheW interactions. In support of this possibility, we found that CheW and CheV1 interact with each other and with CheA independent of the chemoreceptors. Therefore, it seems that some microbes have modified array formation to require CheW and CheV1. Our data suggest that multiple coupling proteins may be used to provide flexibility in the chemoreceptor array formation.

Protein-protein interaction and molecular dynamics analysis for identification of novel inhibitors in Burkholderia cepacia GG4

The lack of complete treatments and appearance of multiple drug-resistance strains of Burkholderia cepacia complex (Bcc) are causing an increased risk of lung infections in cystic fibrosis patients. Bcc infection is a big risk to human health and demands an urgent need to identify new therapeutics against these bacteria. Network biology has emerged as one of the prospective hope in identifying novel drug targets and hits. We have applied protein-protein interaction methodology to identify new drug-target candidates (orthologs) in Burkhloderia cepacia GG4, which is an important strain for studying the quorum-sensing phenomena. An evolutionary based ortholog mapping approach has been applied for generating the large scale protein-protein interactions in B. Cepacia. As a case study, one of the identified drug targets; GEM_3202, a NH (3)-dependent NAD synthetase protein has been studied and the potential ligand molecules were screened using the ZINC database. The three dimensional structure (NH (3)-dependent NAD synthetase protein) has been predicted from MODELLERv9.11 tool using multiple PDB templates such as 3DPI, 2PZ8 and 1NSY with sequence identity of 76%, 50% and 50% respectively. The structure has been validated with Ramachandaran plot having 100% residues of NadE in allowed region and overall quality factor of 81.75 using ERRAT tool. High throughput screening and Vina resulted in two potential hits against NadE such as ZINC83103551 and ZINC38008121. These molecules showed lowest binding energy of -5.7kcalmol^-1 and high stability in the binding pockets during molecular dynamics simulation analysis. The similar approach for target identification could be applied for clinical strains of other pathogenic microbes.

Cell-free Determination of Binary Complexes That Comprise Extended Protein-Protein Interaction Networks of Yersinia pestis

Binary protein interactions form the basic building blocks of molecular networks and dynamic assemblies that control all cellular functions of bacteria. Although these protein interactions are a potential source of targets for the development of new antibiotics, few high-confidence data sets are available for the large proteomes of most pathogenic bacteria. We used a library of recombinant proteins from the plague bacterium Yersinia pestis to probe planar microarrays of immobilized proteins that represented ∼85% (3552 proteins) of the bacterial proteome, resulting in >77,000 experimentally determined binary interactions. Moderate (K_D ∼μm) to high-affinity (K_D ∼nm) interactions were characterized for >1600 binary complexes by surface plasmon resonance imaging of microarrayed proteins. Core binary interactions that were in common with other gram-negative bacteria were identified from the results of both microarray methods. Clustering of proteins within the interaction network by function revealed statistically enriched complexes and pathways involved in replication, biosynthesis, virulence, metabolism, and other diverse biological processes. The interaction pathways included many proteins with no previously known function. Further, a large assembly of proteins linked to transcription and translation were contained within highly interconnected subregions of the network. The two-tiered microarray approach used here is an innovative method for detecting binary interactions, and the resulting data will serve as a critical resource for the analysis of protein interaction networks that function within an important human pathogen.

Feedback control of Campylobacter jejuni flagellin levels through reciprocal binding of FliW to flagellin and the global regulator CsrA

Bacterial flagella assembly is tightly regulated to ensure a timely and sequential production of the various flagellum constituents. In the pathogen Campylobacter jejuni the hierarchy in flagella biosynthesis is largely determined at the transcriptional level through the activity of the alternative sigma factors sigma⁵⁴ and sigma²⁸ . Here, we report that C. jejuni flagellin levels are also controlled at the post-transcriptional level via the thus far poorly-characterized flagellar assembly factor FliW. Analysis of flagellin synthesis in C. jejuni 81116 and a ΔfliW knock-out mutant showed reduced flagellin protein levels in the mutant strain while ectopic expression of FliW resulted in enhanced levels. Real-time RT-PCR revealed relatively minor changes in flaA and flaB mRNA levels for the recombinant and parent strain consistent with post-transcriptional regulation. Purified FliW was found to bind to FlaA and FlaB flagellin as well as to the global post-transcriptional regulator CsrA. Inactivation of CsrA resulted in increased levels of flagellin translation. An in vitro translation assay confirmed the regulatory role of CsrA in flagellin biosynthesis. We propose that competitive reciprocal binding of FliW to flagellins and the RNA binding protein CsrA serves as a feedback mechanism to control the number of cytosolic flagellin copies at the protein level.

Reconstruction and Application of Protein-Protein Interaction Network

The protein-protein interaction network (PIN) is a useful tool for systematic investigation of the complex biological activities in the cell. With the increasing interests on the proteome-wide interaction networks, PINs have been reconstructed for many species, including virus, bacteria, plants, animals, and humans. With the development of biological techniques, the reconstruction methods of PIN are further improved. PIN has gradually penetrated many fields in biological research. In this work we systematically reviewed the development of PIN in the past fifteen years, with respect to its reconstruction and application of function annotation, subsystem investigation, evolution analysis, hub protein analysis, and regulation mechanism analysis. Due to the significant role of PIN in the in-depth exploration of biological process mechanisms, PIN will be preferred by more and more researchers for the systematic study of the protein systems in various kinds of organisms.

Campylobacter jejuni CsrA Regulates Metabolic and Virulence Associated Proteins and Is Necessary for Mouse Colonization

Campylobacter jejuni infection is a leading bacterial cause of gastroenteritis and a common antecedent leading to Gullian-Barré syndrome. Our previous data suggested that the RNA-binding protein CsrA plays an important role in regulating several important phenotypes including motility, biofilm formation, and oxidative stress resistance. In this study, we compared the proteomes of wild type, csrA mutant, and complemented csrA mutant C. jejuni strains in an effort to elucidate the mechanisms by which CsrA affects virulence phenotypes. The putative CsrA regulon was more pronounced at stationary phase (111 regulated proteins) than at mid-log phase (25 regulated proteins). Proteins displaying altered expression in the csrA mutant included diverse metabolic functions, with roles in amino acid metabolism, TCA cycle, acetate metabolism, and various other cell processes, as well as pathogenesis-associated characteristics such as motility, chemotaxis, oxidative stress resistance, and fibronectin binding. The csrA mutant strain also showed altered autoagglutination kinetics when compared to the wild type. CsrA specifically bound the 5' end of flaA mRNA, and we demonstrated that CsrA is a growth-phase dependent repressor of FlaA expression. Finally, the csrA mutant exhibited reduced ability to colonize in a mouse model when in competition with the wild type, further underscoring the role of CsrA in C. jejuni colonization and pathogenesis.

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.

Structural plasticity of the Salmonella FliS flagellar export chaperone

The Salmonella FliS flagellar export chaperone is a highly α-helical protein. Proteolytic experiments suggest that FliS has a compact core. However, the calorimetric melting profile of FliS does not show any melting transition in the 25-110 °C temperature range. Circular dichroism measurements reveal that FliS is losing its helical structure over a broad temperature range upon heating. These observations indicate that FliS unfolds in a noncooperative way and its native state shows features reminiscent of the molten globule state of proteins possessing substantial structural plasticity. As FliS has several binding partners within the cell, conformational adaptability seems to be an essential requirement to fulfill its multiple roles.

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.

The power of the yeast two-hybrid system in the identification of novel drug targets: building and modulating PPP1 interactomes

Since the description of the yeast two-hybrid (Y2H) method, it has become more and more evident that it is the most commonly used method to identify protein-protein interactions (PPIs). The improvements in the original Y2H methodology in parallel with the idea that PPIs are promising drug targets, offer an excellent opportunity to apply the principles of this molecular biology technique to the pharmaceutical field. Additionally, the theoretical developments in the networks field make PPI networks very useful frameworks that facilitate many discoveries in biomedicine. This review highlights the relevance of Y2H in the determination of PPIs, specifically phosphoprotein phosphatase 1 interactions, and its possible outcomes in pharmaceutical research.

Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery

Precision medicine will revolutionize the way we treat and prevent disease. A major barrier to the implementation of precision medicine that clinicians and translational scientists face is understanding the underlying mechanisms of disease. We are starting to address this challenge through automatic approaches for information extraction, representation and analysis. Recent advances in text and data mining have been applied to a broad spectrum of key biomedical questions in genomics, pharmacogenomics and other fields. We present an overview of the fundamental methods for text and data mining, as well as recent advances and emerging applications toward precision medicine.

Quantifying noise in mass spectrometry and yeast two-hybrid protein interaction detection experiments

Protein interaction networks (PINs) are popular means to visualize the proteome. However, PIN datasets are known to be noisy, incomplete and biased by the experimental protocols used to detect protein interactions. This paper aims at understanding the connection between true protein interactions and the protein interaction datasets that have been obtained using the most popular experimental techniques, i.e. mass spectronomy and yeast two-hybrid. We start from the observation that the adjacency matrix of a PIN, i.e. the binary matrix which defines, for every pair of proteins in the network, whether or not there is a link, has a special form, that we call separable. This induces precise relationships between the moments of the degree distribution (i.e. the average number of links that a protein in the network has, its variance, etc.) and the number of short loops (i.e. triangles, squares, etc.) along the links of the network. These relationships provide powerful tools to test the reliability of datasets and hint at the underlying biological mechanism with which proteins and complexes recruit each other.

Computational analysis of protein interaction networks for infectious diseases

Infectious diseases caused by pathogens, including viruses, bacteria and parasites, pose a serious threat to human health worldwide. Frequent changes in the pattern of infection mechanisms and the emergence of multidrug-resistant strains among pathogens have weakened the current treatment regimen. This necessitates the development of new therapeutic interventions to prevent and control such diseases. To cater to the need, analysis of protein interaction networks (PINs) has gained importance as one of the promising strategies. The present review aims to discuss various computational approaches to analyse the PINs in context to infectious diseases. Topology and modularity analysis of the network with their biological relevance, and the scenario till date about host–pathogen and intra-pathogenic protein interaction studies were delineated. This would provide useful insights to the research community, thereby enabling them to design novel biomedicine against such infectious diseases.

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.

How bacteria maintain location and number of flagella?

Bacteria differ in number and location of their flagella that appear in regular patterns at the cell surface (flagellation pattern). Despite the plethora of bacterial species, only a handful of these patterns exist. The correct flagellation pattern is a prerequisite for motility, but also relates to biofilm formation and the pathogenicity of disease-causing flagellated bacteria. However, the mechanisms that maintain location and number of flagella are far from being understood. Here, we review our knowledge on mechanisms that enable bacteria to maintain their appropriate flagellation pattern. While some peritrichous flagellation patterns might occur by rather simple stochastic processes, other bacterial species appear to rely on landmark systems to define the designated flagellar position. Such landmarks are the Tip system of Caulobacter crescentus or the signal recognition particle (SRP)-GTPase FlhF and the MinD/ParA-type ATPase FlhG (synonyms: FleN, YlxH and MinD2). The latter two proteins constitute a regulatory circuit essential for diverse flagellation patterns in many Gram-positive and negative species. The interactome of FlhF/G (e.g. C-ring proteins FliM, FliN, FliY or the transcriptional regulator FleQ/FlrA) seems evolutionary adapted to meet the specific needs for a respective pattern. This variability highlights the importance of the correct flagellation pattern for motile species.

The yeast two-hybrid system: a tool for mapping protein-protein interactions

Virtually all processes in living cells are dependent on protein-protein interactions (PPIs). Understanding PPI networks is thus essential for molecular biology and disease research. One powerful genetic system for mapping PPIs both at a small scale and in a high-throughput manner is the yeast two-hybrid (Y2H) screen. In Y2H screening, PPIs are detected through the activation of reporter genes responding to a reconstituted transcription factor. In this introduction, we describe library- and array-based Y2H methods and explain their basic theory. We also include the rationale behind different Y2H approaches and strategies for optimizing results.

A directed-overflow and damage-control N-glycosidase in riboflavin biosynthesis

Plants and bacteria synthesize the essential human micronutrient riboflavin (vitamin B2) via the same multi-step pathway. The early intermediates of this pathway are notoriously reactive and may be overproduced in vivo because riboflavin biosynthesis enzymes lack feedback controls. In the present paper, we demonstrate disposal of riboflavin intermediates by COG3236 (DUF1768), a protein of previously unknown function that is fused to two different riboflavin pathway enzymes in plants and bacteria (RIBR and RibA respectively). We present cheminformatic, biochemical, genetic and genomic evidence to show that: (i) plant and bacterial COG3236 proteins cleave the N-glycosidic bond of the first two intermediates of riboflavin biosynthesis, yielding relatively innocuous products; (ii) certain COG3236 proteins are in a multi-enzyme riboflavin biosynthesis complex that gives them privileged access to riboflavin intermediates; and (iii) COG3236 action in Arabidopsis thaliana and Escherichia coli helps maintain flavin levels. COG3236 proteins thus illustrate two emerging principles in chemical biology: directed overflow metabolism, in which excess flux is diverted out of a pathway, and the pre-emption of damage from reactive metabolites.

MinD-like ATPase FlhG effects location and number of bacterial flagella during C-ring assembly

The number and location of flagella, bacterial organelles of locomotion, are species specific and appear in regular patterns that represent one of the earliest taxonomic criteria in microbiology. However, the mechanisms that reproducibly establish these patterns during each round of cell division are poorly understood. FlhG (previously YlxH) is a major determinant for a variety of flagellation patterns. Here, we show that FlhG is a structural homolog of the ATPase MinD, which serves in cell-division site determination. Like MinD, FlhG forms homodimers that are dependent on ATP and lipids. It interacts with a complex of the flagellar C-ring proteins FliM and FliY (also FliN) in the Gram-positive, peritrichous-flagellated Bacillus subtilis and the Gram-negative, polar-flagellated Shewanella putrefaciens. FlhG interacts with FliM/FliY in a nucleotide-independent manner and activates FliM/FliY to assemble with the C-ring protein FliG in vitro. FlhG-driven assembly of the FliM/FliY/FliG complex is strongly enhanced by ATP and lipids. The protein shows a highly dynamic subcellular distribution between cytoplasm and flagellar basal bodies, suggesting that FlhG effects flagellar location and number during assembly of the C-ring. We describe the molecular evolution of a MinD-like ATPase into a flagellation pattern effector and suggest that the underappreciated structural diversity of the C-ring proteins might contribute to the formation of different flagellation patterns.