Dataset Information

Dissecting the specificity of protein-protein interaction in bacterial two-component signaling: orphans and crosstalks.

ABSTRACT: Predictive understanding of the myriads of signal transduction pathways in a cell is an outstanding challenge of systems biology. Such pathways are primarily mediated by specific but transient protein-protein interactions, which are difficult to study experimentally. In this study, we dissect the specificity of protein-protein interactions governing two-component signaling (TCS) systems ubiquitously used in bacteria. Exploiting the large number of sequenced bacterial genomes and an operon structure which packages many pairs of interacting TCS proteins together, we developed a computational approach to extract a molecular interaction code capturing the preferences of a small but critical number of directly interacting residue pairs. This code is found to reflect physical interaction mechanisms, with the strongest signal coming from charged amino acids. It is used to predict the specificity of TCS interaction: Our results compare favorably to most available experimental results, including the prediction of 7 (out of 8 known) interaction partners of orphan signaling proteins in Caulobacter crescentus. Surveying among the available bacterial genomes, our results suggest 15?25% of the TCS proteins could participate in out-of-operon "crosstalks". Additionally, we predict clusters of crosstalking candidates, expanding from the anecdotally known examples in model organisms. The tools and results presented here can be used to guide experimental studies towards a system-level understanding of two-component signaling.

SUBMITTER: Procaccini A

PROVIDER: S-EPMC3090404 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Dissecting the specificity of protein-protein interaction in bacterial two-component signaling: orphans and crosstalks.

Procaccini Andrea A Lunt Bryan B Szurmant Hendrik H Hwa Terence T Weigt Martin M

PloS one 20110509 5

Predictive understanding of the myriads of signal transduction pathways in a cell is an outstanding challenge of systems biology. Such pathways are primarily mediated by specific but transient protein-protein interactions, which are difficult to study experimentally. In this study, we dissect the specificity of protein-protein interactions governing two-component signaling (TCS) systems ubiquitously used in bacteria. Exploiting the large number of sequenced bacterial genomes and an operon struct ...[more]

PMID: 21573011

Similar Datasets

Project description:The prevalent paradigm governing bacterial two-component signaling systems (TCSs) is specificity, wherein the histidine kinase (HK) of a TCS exclusively activates its cognate response regulator (RR). Cross talk, where HKs activate noncognate RRs, is considered evolutionarily disadvantageous because it can compromise adaptive responses by leaking signals. Yet cross talk is observed in several bacteria. Here, to resolve this paradox, we propose an alternative paradigm where cross talk can be advantageous. We envisioned programmed environments, wherein signals appear in predefined sequences. In such environments, cross talk that primes bacteria to upcoming signals may improve adaptive responses and confer evolutionary benefits. To test this hypothesis, we employed mathematical modeling of TCS signaling networks and stochastic evolutionary dynamics simulations. We considered the comprehensive set of bacterial phenotypes, comprising thousands of distinct cross talk patterns competing in varied signaling environments. Our simulations predicted that in programmed environments phenotypes with cross talk facilitating priming would outcompete phenotypes without cross talk. In environments where signals appear randomly, bacteria without cross talk would dominate, explaining the specificity widely seen. Additionally, a testable prediction was that the phenotypes selected in programmed environments would display one-way cross talk, ensuring priming to future signals. Interestingly, the cross talk networks we deduced from available data on TCSs of Mycobacterium tuberculosis all displayed one-way cross talk, which was consistent with our predictions. Our study thus identifies potential evolutionary underpinnings of cross talk in bacterial TCSs, suggests a reconciliation of specificity and cross talk, makes testable predictions of the nature of cross talk patterns selected, and has implications for understanding bacterial adaptation and the response to interventions. IMPORTANCE Bacteria use two-component signaling systems (TCSs) to sense and respond to environmental changes. The prevalent paradigm governing TCSs is specificity, where signal flow through TCSs is insulated; leakage to other TCSs is considered evolutionarily disadvantageous. Yet cross talk between TCSs is observed in many bacteria. Here, we present a potential resolution of this paradox. We envision programmed environments, wherein stimuli appear in predefined sequences. Cross talk that primes bacteria to upcoming stimuli could then confer evolutionary benefits. We demonstrate this benefit using mathematical modeling and evolutionary simulations. Interestingly, we found signatures of predicted cross talk patterns in Mycobacterium tuberculosis. Furthermore, specificity was selected in environments where stimuli occurred randomly, thus reconciling specificity and cross talk. Implications follow for understanding bacterial evolution and for interventions.

Project description:Bacteria use two-component signaling systems to adapt and respond to their competitors and changing environments. For instance, competitor bacteria may produce antibiotics and other bioactive metabolites and sequester nutrients. To survive, some species of bacteria escape competition through antibiotic production, biofilm formation, or motility. Specialized metabolite production and biofilm formation are relatively well understood for bacterial species in isolation. How bacteria control these functions when competitors are present is not well studied. To address fundamental questions relating to the competitive mechanisms of different species, we have developed a model system using two species of soil bacteria, Bacillus subtilis and Streptomyces sp. strain Mg1. Using this model, we previously found that linearmycins produced by Streptomyces sp. strain Mg1 cause lysis of B. subtilis cells and degradation of colony matrix. We identified strains of B. subtilis with mutations in the two-component signaling system yfiJK operon that confer dual phenotypes of specific linearmycin resistance and biofilm morphology. We determined that expression of the ATP-binding cassette (ABC) transporter yfiLMN operon, particularly yfiM and yfiN, is necessary for biofilm morphology. Using transposon mutagenesis, we identified genes that are required for YfiLMN-mediated biofilm morphology, including several chaperones. Using transcriptional fusions, we found that YfiJ signaling is activated by linearmycins and other polyene metabolites. Finally, using a truncated YfiJ, we show that YfiJ requires its transmembrane domain to activate downstream signaling. Taken together, these results suggest coordinated dual antibiotic resistance and biofilm morphology by a single multifunctional ABC transporter promotes competitive fitness of B. subtilisIMPORTANCE DNA sequencing approaches have revealed hitherto unexplored diversity of bacterial species in a wide variety of environments that includes the gastrointestinal tract of animals and the rhizosphere of plants. Interactions between different species in bacterial communities have impacts on our health and industry. However, many approaches currently used to study whole bacterial communities do not resolve mechanistic details of interspecies interactions, including how bacteria sense and respond to their competitors. Using a competition model, we have uncovered dual functions for a previously uncharacterized two-component signaling system involved in specific antibiotic resistance and biofilm morphology. Insights gleaned from signaling within interspecies interaction models build a more complete understanding of gene functions important for bacterial communities and will enhance community-level analytical approaches.

Dataset Information

Dissecting the specificity of protein-protein interaction in bacterial two-component signaling: orphans and crosstalks.

Publications

Dissecting the specificity of protein-protein interaction in bacterial two-component signaling: orphans and crosstalks.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets