Evolutionary Genomics Suggests That CheV Is an Additional Adaptor for Accommodating Specific Chemoreceptors within the Chemotaxis Signaling Complex

Escherichia coli and Salmonella enterica are models for many experiments in molecular biology including chemotaxis, and most of the results obtained with one organism have been generalized to another. While most components of the chemotaxis pathway are strongly conserved between the two species, Salmonella genomes contain some chemoreceptors and an additional protein, CheV, that are not found in E. coli. The role of CheV was examined in distantly related species Bacillus subtilis and Helicobacter pylori, but its role in bacterial chemotaxis is still not well understood. We tested a hypothesis that in enterobacteria CheV functions as an additional adaptor linking the CheA kinase to certain types of chemoreceptors that cannot be effectively accommodated by the universal adaptor CheW. Phylogenetic profiling, genomic context and comparative protein sequence analyses suggested that CheV interacts with specific domains of CheA and chemoreceptors from an orthologous group exemplified by the Salmonella McpC protein. Structural consideration of the conservation patterns suggests that CheV and CheW share the same binding spot on the chemoreceptor structure, but have some affinity bias towards chemoreceptors from different orthologous groups. Finally, published experimental results and data newly obtained via comparative genomics support the idea that CheV functions as a “phosphate sink” possibly to off-set the over-stimulation of the kinase by certain types of chemoreceptors. Overall, our results strongly suggest that CheV is an additional adaptor for accommodating specific chemoreceptors within the chemotaxis signaling complex

MiST: a microbial signal transduction database

Signal transduction pathways control most cellular activities in living cells ranging from regulation of gene expression to fine-tuning enzymatic activity and controlling motile behavior in response to extracellular and intracellular signals. Because of their extreme sequence variability and extensive domain shuffling, signal transduction proteins are difficult to identify, and their current annotation in most leading databases is often incomplete or erroneous. To overcome this problem, we have developed the microbial signal transduction (MiST) database (), a comprehensive library of the signal transduction proteins from completely sequenced bacterial and archaeal genomes. By searching for domain profiles that implicate a particular protein as participating in signal transduction, we have systematically identified 69 270 two- and one-component proteins in 365 bacterial and archaeal genomes. We have designed a user-friendly website to access and browse the predicted signal transduction proteins within various organisms. Further capabilities include gene/protein sequence retrieval, visualized domain architectures, interactive chromosomal views for exploring gene neighborhood, advanced querying options and cross-species comparison. Newly available, complete genomes are loaded into the database each month. MiST is the only comprehensive and up-to-date electronic catalog of the signaling machinery in microbial genomes

Aquerium: A web application for comparative exploration of domain-based protein occurrences on the taxonomically clustered genome tree: Architecture Querying Podium

Gene duplication and loss are major driving forces in evolution. While many important genomic resources provide information on gene presence, there is a lack of tools giving equal importance to presence and absence information as well as web platforms enabling easy visual comparison of multiple domain-based protein occurences at once. Here, we present Aquerium, a platform for visualizing genomic presence and absence of biomolecules with a focus on protein domain architectures. The web server offers advanced domain organization querying against the database of pre-computed domains for ~26000 organisms and it can be utilized for identification of evolutionary events, such as fusion, disassociation, duplication and shuffling of protein domains. The tool also allows alternative inputs of custom entries or BLASTP results for visualization. Aquerium will be a useful tool for biologists who perform comparative genomic and evolutionary analyses. The web server is freely accessible at http://aquerium.utk.edu

Dynamics of domain coverage of the protein sequence universe

Background The currently known protein sequence space consists of millions of sequences in public databases and is rapidly expanding. Assigning sequences to families leads to a better understanding of protein function and the nature of the protein universe. However, a large portion of the current protein space remains unassigned and is referred to as its “dark matter”. Results Here we suggest that true size of “dark matter” is much larger than stated by current definitions. We propose an approach to reducing the size of “dark matter” by identifying and subtracting regions in protein sequences that are not likely to contain any domain. Conclusions Recent improvements in computational domain modeling result in a decrease, albeit slowly, in the relative size of “dark matter”; however, its absolute size increases substantially with the growth of sequence data

MiST 3.0: an updated microbial signal transduction database with an emphasis on chemosensory systems

Bacteria and archaea employ dedicated signal transduction systems that modulate gene expression, second-messenger turnover, quorum sensing, biofilm formation, motility, host-pathogen and beneficial interactions. The updated MiST database provides a comprehensive classification of microbial signal transduction systems. This update is a result of a substantial scaling to accommodate constantly growing microbial genomic data. More than 125 000 genomes, 516 million genes and almost 100 million unique protein sequences are currently stored in the database. For each bacterial and archaeal genome, MiST 3.0 provides a complete signal transduction profile, thus facilitating theoretical and experimental studies on signal transduction and gene regulation. New software infrastructure and distributed pipeline implemented in MiST 3.0 enable regular genome updates based on the NCBI RefSeq database. A novel MiST feature is the integration of unique profile HMMs to link complex chemosensory systems with corresponding chemoreceptors in bacterial and archaeal genomes. The data can be explored online or via RESTful API (freely available at https://mistdb.com)

MiST 3.0: an updated microbial signal transduction database with an emphasis on chemosensory systems

Bacteria and archaea employ dedicated signal transduction systems that modulate gene expression, second-messenger turnover, quorum sensing, biofilm formation, motility, host-pathogen and beneficial interactions. The updated MiST database provides a comprehensive classification of microbial signal transduction systems. This update is a result of a substantial scaling to accommodate constantly growing microbial genomic data. More than 125 000 genomes, 516 million genes and almost 100 million unique protein sequences are currently stored in the database. For each bacterial and archaeal genome, MiST 3.0 provides a complete signal transduction profile, thus facilitating theoretical and experimental studies on signal transduction and gene regulation. Newsoftware infrastructure and distributed pipeline implemented in MiST 3.0 enable regular genome updates based on the NCBI RefSeq database. A novel MiST feature is the integration of unique profile HMMs to link complex chemosensory systems with corresponding chemoreceptors in bacterial and archaeal genomes

Interdimer zipping in the chemoreceptor signaling domain revealed by molecular dynamics simulations

Chemoreceptors are principal components of the bacterial sensory system that modulates cellular motility. They detect changes in the environment and transmit information to CheA histidine kinase, which ultimately controls cellular flagellar motors. The prototypical Tsr chemoreceptor in E. coli is a homodimer containing two principal functional modules: (i) a periplasmic ligand-binding domain and (ii) a cytoplasmic signaling domain. Chemoreceptor dimers are arranged into a trimer of dimers at the tip of the signaling domain comprising a minimal physical unit essential for enhancing the CheA activity several hundredfold. Trimers of dimers are arranged into highly ordered hexagon arrays at the cell pole; however, the mechanism underlying the trimer-of-dimer and higher order array formation remains unclear. Furthermore, molecular mechanisms of signal transduction that are likely to involve inter-dimer interactions are not fully understood. Here we apply all-atom, microsecond-time scale molecular dynamics simulations of the Tsr trimer of dimers atomic model in order to obtain further insight into potential interactions within the chemoreceptor signaling unit. We show extensive interactions between homodimers at the hairpin tip of the signaling domain, where strong hydrophobic interactions maintain binding. A subsequent zipping of homodimers is facilitated by electrostatic interactions, in particular by polar solvation energy and salt bridges that stabilize the final compact structure, which extends beyond the kinase interacting subdomain. Our study provides evidence that interdimer interactions within the chemoreceptor signaling domain are more complex than previously thought

Assigning chemoreceptors to chemosensory pathways in Pseudomonas aeruginosa

In contrast to Escherichia coli, a model organism for chemotaxis that has 5 chemoreceptors and a single chemosensory pathway, Pseudomonas aeruginosa PAO1 has a much more complex chemosensory network, which consists of 26 chemoreceptors feeding into four chemosensory pathways. While several chemoreceptors were rigorously linked to specific pathways in a series of experimental studies, for most of them this information is not available. Thus, we addressed the problem computationally. Protein–protein interaction network prediction, coexpression data mining, and phylogenetic profiling all produced incomplete and uncertain assignments of chemoreceptors to pathways. However, comparative sequence analysis specifically targeting chemoreceptor regions involved in pathway interactions revealed conserved sequence patterns that enabled us to unambiguously link all 26 chemoreceptors to four pathways. Placing computational evidence in the context of experimental data allowed us to conclude that three chemosensory pathways in P. aeruginosa utilize one chemoreceptor per pathway, whereas the fourth pathway, which is the main system controlling chemotaxis, utilizes the other 23 chemoreceptors. Our results show that while only a very few amino acid positions in receptors, kinases, and adaptors determine their pathway specificity, assigning receptors to pathways computationally is possible. This requires substantial knowledge about interacting partners on a molecular level and focusing comparative sequence analysis on the pathway-specific regions. This general principle should be applicable to resolving many other receptor–pathway interactions