The two-component signal transduction protein Chk1p regulates quorum sensing in Candida albicans

Regulation of hyphal morphogenesis in Candida albicans can occur through quorum sensing (QS). A QS signal, farnesol, is produced during high-density growth and inhibits morphogenesis. However, the signal transduction pathway that regulates QS is unknown. Here, we show that a C. albicans mutant lacking Chk1p but not either the Sln1p or the Nik1p histidine kinase is refractory to the inhibitory effect of farnesol both in cell suspension and during the formation of a biofilm. This study is the first to demonstrate a role for a two-component signal transduction protein in QS by a eukaryotic organism.     

Developing next generation antimicrobials by intercepting AI-2 mediated quorum sensing

Bacteria have been evolving antibiotic resistance since their discovery in the early twentieth century. Most new antibiotics are derivatives of older generations and there are now bacteria that are virtually resistant to almost all antibiotics. This poses a global threat to human health and has been classified as a clinical “super-challenge”, which has necessitated research into new antimicrobials that inhibit bacterial virulence while minimizing selective pressures that lead to the emergence of resistant strains. Quorum sensing (QS), the process of population dependent bacterial cell-cell signaling, can accelerate bacterial virulence and is an increasingly interesting target for developing next generation antimicrobials. Most QS inhibitors target species-specific signals, such as acylhomoserine lactones (AHLs) and oligopeptides. Methodologies for intercepting the cross-species signal, autoinducer-2 (AI-2), have only recently emerged. We review these strategies to prevent the relay of the AI-2 signal amongst pathogens, including Escherichia coli, Salmonella enterica serovar Typhimurium, Vibrio cholerae and Pseudomonas aeruginosa. Inhibition mechanisms are categorized based on the target (i.e., enzymes for signal generation, the signal molecule itself, or the various components of the signal transduction process). The universal nature of the AI-2 signal imparts on its inhibitors the potential for broad spectrum use.     

AI-2 analogs and antibiotics: a synergistic approach to reduce bacterial biofilms

Quorum sensing (QS), the process of autoinducer-mediated cell–cell signaling among bacteria, facilitates biofilm formation, virulence, and many other multicellular phenotypes. QS inhibitors are being investigated as antimicrobials because of their potential to reduce symptoms of infectious disease while slowing the emergence of resistant strains. Autoinducer-2 (AI-2) analogs have been shown to inhibit genotypic QS responses among many bacteria. We demonstrate for the first time, the ability of C1-alkyl AI-2 analog, isobutyl-DPD, to significantly inhibit the maturation of Escherichia coli biofilms grown in vitro. Using a novel microfluidic device that incorporates dynamic, real-time measurements of biofilm density, we also show that a combinatorial approach wherein isobutyl-DPD ((S)-4,5-dihydroxy-2,3-pentanedione) is used with the antibiotic gentamicin is quite effective in rendering near complete clearance of pre-existing E. coli biofilms. Similarly, another AI-2 analog, phenyl-DPD, also used in combination with near MIC levels of gentamicin, resulted in clearance of preformed Pseudomonas aeruginosa biofilms. Clearance of pre-existing biofilms has remained a significant health care challenge; these results warrant consideration of a new approach based on the combination of “quenching” QS signal transduction processes with traditional antibiotic treatment.     

Rational design of ‘controller cells’ to manipulate protein and phenotype expression

Coordination between cell populations via prevailing metabolic cues has been noted as a promising approach to connect synthetic devices and drive phenotypic or product outcomes. However, there has been little progress in developing ‘controller cells’ to modulate metabolic cues and guide these systems. In this work, we developed ‘controller cells’ that manipulate the molecular connection between cells by modulating the bacterial signal molecule, autoinducer-2, that is secreted as a quorum sensing (QS) signal by many bacterial species. Specifically, we have engineered Escherichia coli to overexpress components responsible for autoinducer uptake (lsrACDB), phosphorylation (lsrK), and degradation (lsrFG), thereby attenuating cell–cell communication among populations. Further, we developed a simple mathematical model that recapitulates experimental data and characterizes the dynamic balance among the various uptake mechanisms. This study revealed two controller ‘knobs’ that serve to increase AI-2 uptake: overexpression of the AI-2 transporter, LsrACDB, which controls removal of extracellular AI-2, and overexpression of the AI-2 kinase, LsrK, which increases the net uptake rate by limiting secretion of AI-2 back into the extracellular environment. We find that the overexpression of lsrACDBFG results in an extraordinarily high AI-2 uptake rate that is capable of completely silencing QS-mediated gene expression among wild-type cells. We demonstrate utility by modulating naturally occurring processes of chemotaxis and biofilm formation. We envision that ‘controller cells’ that modulate bacterial behavior by manipulating molecular communication, will find use in a variety of applications, particularly those employing natural or synthetic bacterial consortia.     

Insightful directed evolution of Escherichia coli quorum sensing promoter region of the lsrACDBFG operon: a tool for synthetic biology systems and protein expression

Quorum sensing (QS) regulates many natural phenotypes (e.q. virulence, biofilm formation, antibiotic resistance), and its components, when incorporated into synthetic genetic circuits, enable user-directed phenotypes. We created a library of Escherichia coli lsr operon promoters using error-prone PCR (ePCR) and selected for promoters that provided E. coli with higher tetracycline resistance over the native promoter when placed upstream of the tet(C) gene. Among the fourteen clones identified, we found several mutations in the binding sites of QS repressor, LsrR. Using site-directed mutagenesis we restored all p-lsrR-box sites to the native sequence in order to maintain LsrR repression of the promoter, preserving the other mutations for analysis. Two promoter variants, EP01rec and EP14rec, were discovered exhibiting enhanced protein expression. In turn, these variants retained their ability to exhibit the LsrR-mediated QS switching activity. Their sequences suggest regulatory linkage between CytR (CRP repressor) and LsrR. These promoters improve upon the native system and exhibit advantages over synthetic QS promoters previously reported. Incorporation of these promoters will facilitate future applications of QS-regulation in synthetic biology and metabolic engineering.     

Linking Molecular and Population Processes in Mathematical Models of Quorum Sensing

Many bacteria alter their behaviors as a function of population density, via a process known as quorum sensing (QS). QS is achieved by the synthesis and detection of diffusible signal molecules, often involving complex signal transduction pathways and regulatory networks. Mathematical models have been developed to investigate a number of aspects of QS, resulting in a wide range of model structures; many have focused on either the molecular or the population scale. In this paper, I show that many published models fail to satisfy physical constraints (such as conservation of matter) or rely on a priori assumptions that may not be valid. I present new, simple models of canonical Gram-negative and Gram-positive QS systems, in both well-mixed and biofilm populations, focusing on the interaction between molecular and population processes. I show that this interaction may be crucial for several important features of QS, including bistability and the localization of QS in space. The results highlight the need to link molecular and population processes carefully in QS models, provide a general framework for understanding the behavior of complex system-specific models, and suggest new directions for both theoretical and experimental work.     

Inhibitors of the Pseudomonas aeruginosa quorum‐sensing regulator,QscR

QscR is a quorum‐sensing (QS) signal receptor that controls expression of virulence genes in the prevalent opportunistic pathogen, Pseudomonas aeruginosa. Unlike the previously reported LuxR‐type QS receptor proteins, that is, LasR and TraR, QscR can be obtained as an apo‐protein that can reversibly form an active complex in vitro with its cognate signal molecule, 3‐oxododecanoyl‐homoserine lactone (3OC12‐HSL), and subsequently bind to target promoter DNA sequences. To search for potential QS inhibitors, an in vitro gel retardation assay was developed using the purified QscR. Both the in vitro assay and the in vivo cell‐based assay using QscR‐overproducing recombinant strains were applied in the screening process. Furanones were chosen for testing the activity as QS inhibitors because they have been reported to strongly inhibit expression of QS‐related genes in Agrobacterium tumefaciens. Among more than a hundred furanones tested, three compounds showed strong and dose‐dependent inhibitory effects on QscR in both assays. One compound in particular, designated as F2, could completely inhibit the 3OC12‐HSL‐dependent QscR activity in vitro at a concentration of 50‐fold molar excess over 3OC12‐HSL. However, with the furanones F3 and F4, which are structurally similar to F2 but with a nitro group instead of the amine moiety, significantly decreased activities were observed. These results suggest that (i) the in vitro assay is a sensitive and reliable tool for screening QS inhibitors, and (ii) furanones are potentially important QS inhibitors for many LuxR‐type receptor proteins. Biotechnol. Bioeng. 2010; 106: 119–126. © 2010 Wiley Periodicals, Inc.     

Molecular cloning and characterization of mitogen-activated protein kinase 2 in Trypanosoma cruzi

Mitogen-activated protein kinase (MAPK) pathways are major signal transduction systems by which eukaryotic cells convert environmental cues to intracellular events such as proliferation and differentiation. We have identified a Trypanosoma cruzi homologue of the MAPK family that we have called TcMAPK2. Sequence analyses demonstrates TcMAPK2 has high homology with lower eukaryotic ERK2 but has significant differences from mammalian ERK2. Enzymatic assays of both recombinant TcMAPK2 and native protein obtained by immunoprecipitation using anti-TcMAPK2 demonstrated that both preparations of TcMAPK2 were catalytically active. Immunofluorescence analysis of the subcellular localization of TcMAPK2 determined it is mainly cytoplasmic in epimastigotes, along the flagella in trypomastigotes and on the plasma membrane of intracellular amastigotes. Phosphorylated TcMAPK2 was highest in trypomastigotes and lowest in amastigotes. Recombinant TcMAPK2 was able to phosphorylate the recombinant protein of a cAMP specific phosphodiesterase. Overexpression of TcMAPK2 in epimastigotes inhibited growth and development leading to death. TcMAPK2 has an important role in the stress response of the parasite and may be important in regulating proliferation and differentiation.Key words: Trypanosoma cruzi, mitogen-activated protein kinase, phosphorylation     

Analysing phosphorylation-based signalling networks by phospho flow cytometry

Analysis of signalling events by classical biochemical approaches is limited as the outcome is an averaged readout for protein activation of a single protein within a cell population. This is a clear restriction when addressing signalling events in mixed populations or subpopulations of cells. By combining flow cytometry with a panel of phosphospecific antibodies against several signal molecules simultaneously in a multi-parameter phospho flow cytometry analysis it is possible to obtain a higher level of understanding of the signal transduction dynamics at a single cell level. In addition, analysis of mixed cell populations makes it possible to study cells ex vivo in a state more closely resembling the in vivo situation. The multimeric analysis yields information on combinations of signals turned on and off in specific settings such as disease (signal nodes) that can be used for biomarker analysis and for development of drug screening strategies. Prostaglandin E₂ (PGE₂) is known to signal through four G-protein coupled transmembrane receptors, EP1-4, activating a multitude of potential signalling pathways. The analysis of the PGE₂ signalling network elicited by activation of the four EP receptors in lymphoid cells revealing several signalling nodes is reviewed as an example.     

LsrR quorum sensing "switch" is revealed by a bottom-up approach

Quorum sensing (QS) enables bacterial multicellularity and selective advantage for communicating populations. While genetic "switching" phenomena are a common feature, their mechanistic underpinnings have remained elusive. The interplay between circuit components and their regulation are intertwined and embedded. Observable phenotypes are complex and context dependent. We employed a combination of experimental work and mathematical models to decipher network connectivity and signal transduction in the autoinducer-2 (AI-2) quorum sensing system of E. coli. Negative and positive feedback mechanisms were examined by separating the network architecture into sub-networks. A new unreported negative feedback interaction was hypothesized and tested via a simple mathematical model. Also, the importance of the LsrR regulator and its determinant role in the E. coli QS "switch", normally masked by interfering regulatory loops, were revealed. Our simple model allowed mechanistic understanding of the interplay among regulatory sub-structures and their contributions to the overall native functioning network. This "bottom up" approach in understanding gene regulation will serve to unravel complex QS network architectures and lead to the directed coordination of emergent behaviors.     

BRET-monitoring of the dynamic changes of inositol lipid pools in living cells reveals a PKC-dependent PtdIns4P increase upon EGF and M3 receptor activation

Deciphering many roles played by inositol lipids in signal transduction and membrane function demands experimental approaches that can detect their dynamic accumulation with subcellular accuracy and exquisite sensitivity. The former criterion is met by imaging of fluorescence biosensors in living cells, whereas the latter is facilitated by biochemical measurements from populations. Here, we introduce BRET-based biosensors able to detect rapid changes in inositol lipids in cell populations with both high sensitivity and subcellular resolution in a single, convenient assay. We demonstrate robust and sensitive measurements of PtdIns4P, PtdIns(4,5)P₂ and PtdIns(3,4,5)P₃ dynamics, as well as changes in cytoplasmic Ins(1,4,5)P₃ levels. Measurements were made during either experimental activation of lipid degradation, or PI 3-kinase and phospholipase C mediated signal transduction. Our results reveal a previously unappreciated synthesis of PtdIns4P that accompanies moderate activation of phospholipase C signaling downstream of both EGF and muscarinic M3 receptor activation. This signaling-induced PtdIns4P synthesis relies on protein kinase C, and implicates a feedback mechanism in the control of inositol lipid metabolism during signal transduction.     

Population Model of Quorum Sensing with Multiple Parallel Pathways

Quorum sensing (QS) is a bacterial communication mechanism that uses signal-receptor binding to regulate gene expression based on cell density, resulting in group behaviors such as biofilm formation, bioluminescence and stress response. In certain bacterial species such as Vibrio harveyi, several parallel QS signaling pathways drive a single phosphorylation–dephosphorylation cycle, which in turn regulates QS target genes. In this paper, we investigate the possible role of parallel signaling pathways by developing a mathematical model of QS in V. harveyi at both the single-cell and population levels. First we explore how signal integration may be achieved at the single-cell level, and how different model parameters influence the process. We then consider two examples of signal integration at the population level: a one-population model responding to two environmental cues (cell density and mass transfer), and a two-population model with distinct cell densities. In each case, we use contraction analysis to reduce the population model to an effective single-cell model.     

Directed assembly of a bacterial quorum

Many reports have elucidated the mechanisms and consequences of bacterial quorum sensing (QS), a molecular communication system by which bacterial cells enumerate their cell density and organize collective behavior. In few cases, however, the numbers of bacteria exhibiting this collective behavior have been reported, either as a number concentration or a fraction of the whole. Not all cells in the population, for example, take on the collective phenotype. Thus, the specific attribution of the postulated benefit can remain obscure. This is partly due to our inability to independently assemble a defined quorum, for natural and most artificial systems the quorum itself is a consequence of the biological context (niche and signaling mechanisms). Here, we describe the intentional assembly of quantized quorums. These are made possible by independently engineering the autoinducer signal transduction cascade of Escherichia coli (E. coli) and the sensitivity of detector cells so that upon encountering a particular autoinducer level, a discretized sub-population of cells emerges with the desired phenotype. In our case, the emergent cells all express an equivalent amount of marker protein, DsRed, as an indicator of a specific QS-mediated activity. The process is robust, as detector cells are engineered to target both large and small quorums. The process takes about 6 h, irrespective of quorum level. We demonstrate sensitive detection of autoinducer-2 (AI-2) as an application stemming from quantized quorums. We then demonstrate sub-population partitioning in that AI-2-secreting cells can ‘call'' groups neighboring cells that ‘travel'' and establish a QS-mediated phenotype upon reaching the new locale.