High variation of fluorescence protein maturation times in closely related Escherichia coli strains.

Fluorescent proteins (FPs) are widely used in biochemistry, biology and biophysics. For quantitative analysis of gene expression FPs are often used as marking molecules. Therefore, sufficient knowledge of maturation times and their affecting factors is of high interest. Here, we investigate the maturation process of the FPs GFP and mCherry expressed by the three closely related Escherichia coli strains of the Colicin E2 system, a model system for colicinogenic interaction. One strain, the C strain produces Colicin, a toxin to which the S strain is sensitive, and against which the R strain is resistant. Under the growth conditions used in this study, the S and R strain have similar growth rates, as opposed to the C strain whose growth rate is significantly reduced due to the toxin production. In combination with theoretical modelling we studied the maturation kinetics of the two FPs in these strains and could confirm an exponential and sigmoidal maturation kinetic for GFP and mCherry, respectively. Our subsequent quantitative experimental analysis revealed a high variance in maturation times independent of the strain studied. In addition, we determined strain dependent maturation times and maturation behaviour. Firstly, FPs expressed by the S and R strain mature on similar average time-scales as opposed to FPs expressed by the C strain. Secondly, dependencies of maturation time with growth conditions are most pronounced in the GFP expressing C strain: Doubling the growth rate of this C strain results in an increased maturation time by a factor of 1.4. As maturation times can vary even between closely related strains, our data emphasize the importance of profound knowledge of individual strains' maturation times for accurate interpretation of gene expression data.

Immediate and heterogeneous response of the LiaFSR two-component system of Bacillus subtilis to the peptide antibiotic bacitracin.

BACKGROUND: Two-component signal transduction systems are one means of bacteria to respond to external stimuli. The LiaFSR two-component system of Bacillus subtilis consists of a regular two-component system LiaRS comprising the core Histidine Kinase (HK) LiaS and the Response Regulator (RR) LiaR and additionally the accessory protein LiaF, which acts as a negative regulator of LiaRS-dependent signal transduction. The complete LiaFSR system was shown to respond to various peptide antibiotics interfering with cell wall biosynthesis, including bacitracin. METHODOLOGY AND PRINCIPAL FINDINGS: Here we study the response of the LiaFSR system to various concentrations of the peptide antibiotic bacitracin. Using quantitative fluorescence microscopy, we performed a whole population study analyzed on the single cell level. We investigated switching from the non-induced 'OFF' state into the bacitracin-induced 'ON' state by monitoring gene expression of a fluorescent reporter from the RR-regulated liaI promoter. We found that switching into the 'ON' state occurred within less than 20 min in a well-defined switching window, independent of the bacitracin concentration. The switching rate and the basal expression rate decreased at low bacitracin concentrations, establishing clear heterogeneity 60 min after bacitracin induction. Finally, we performed time-lapse microscopy of single cells confirming the quantitative response as obtained in the whole population analysis for high bacitracin concentrations. CONCLUSION: The LiaFSR system exhibits an immediate, heterogeneous and graded response to the inducer bacitracin in the exponential growth phase.

Discrimination of Escherichia coli strains using glycan cantilever array sensors.

Carbohydrate-based sensors, that specifically detect sugar binding molecules or cells, are increasingly important in medical diagnostic and drug screening. Here we demonstrate that cantilever arrays functionalized with different mannosides allow the real-time detection of several Escherichia coli strains in solution. Cantilever deflection is thereby dependent on the bacterial strain studied and the glycan used as the sensing molecule. The cantilevers exhibit specific and reproducible deflection with a sensitivity range over four orders of magnitude.

MicroRNA circuits for transcriptional logic.

One of the longstanding challenges in synthetic biology is rational design of complex regulatory circuitry with multiple biological inputs, complex internal processing, and physiologically active outputs. We have previously proposed how to address this challenge in the case of transcription factor inputs. Here we describe the methods used to construct these synthetic circuits, capable of performing logic integration of transcription factor inputs using microRNA expression vectors and RNA interference (RNAi). The circuits operate in mammalian cells and they can serve as starting point for more complex synthetic information processing networks in these cells.

The mode of cell wall growth in selected archaea is similar to the general mode of cell wall growth in bacteria as revealed by fluorescent dye analysis.

The surfaces of 8 bacterial and 23 archaeal species, including many hyperthermophilic Archaea, could be stained using succinimidyl esters of fluorescent dyes. This allowed us for the first time to analyze the mode of cell wall growth in Archaea by subculturing stained cells. The data obtained show that incorporation of new cell wall material in Archaea follows the pattern observed for Bacteria: in the coccoid species Pyrococcus furiosus incorporation was in the region of septum formation while for the rod-shaped species Methanopyrus kandleri and Methanothermus sociabilis, a diffuse incorporation of cell wall material over the cell length was observed. Cell surface appendages like fimbriae/pili, fibers, or flagella were detectable by fluorescence staining only in a very few cases although their presence was proven by electron microscopy. Our data in addition prove that Alexa Fluor dyes can be used for in situ analyses at temperatures up to 100°C.

Rationally designed logic integration of regulatory signals in mammalian cells.

Molecular-level information processing is essential for 'smart' in vivo nanosystems. Natural molecular computing, such as the regulation of messenger RNA (mRNA) synthesis by special proteins called transcription factors, has inspired engineered systems that can control the levels of mRNA with certain combinations of transcription factors. Here, we show an alternative approach to achieving general-purpose control of mRNA and protein levels by logic integration of transcription factor input signals in mammalian cells. The transcription factors regulate synthetic genes coding for small regulatory RNAs (called microRNAs), which, in turn, control the mRNA of interest (the output) via an RNA interference pathway. The simplicity of these modular interactions makes it possible, in theory, to implement any arbitrary logic relation between the transcription factors and the output. We construct, test and optimize increasingly complex circuits with up to three transcription factor inputs, establishing a platform for in vivo molecular computing.

Kinetics of genetic switching into the state of bacterial competence.

Nonlinear amplification of gene expression of master regulators is essential for cellular differentiation. Here we investigated determinants that control the kinetics of the genetic switching process from the vegetative state (B-state) to the competent state (K-state) of Bacillus subtilis, explicitly including the switching window which controls the probability for competence initiation in a cell population. For individual cells, we found that after initiation of switching, the levels of the master regulator [ComK](t) increased with sigmoid shape and saturation occurred at two distinct levels of [ComK]. We analyzed the switching kinetics into the state with highest [ComK] and found saturation after a switching period of length 1.4 +/- 0.3 h. The duration of the switching period was robust against variations in the gene regulatory network of the master regulator, whereas the saturation levels showed large variations between individual isogenic cells. We developed a nonlinear dynamics model, taking into account low-number stochastic effects. The model quantitatively describes the probability and timescale of switching at the single cell level and explains why the ComK level in the K-state is highly sensitive to extrinsic parameter variations. Furthermore, the model predicts a transition from stochastic to deterministic switching at increased production rates of ComK in agreement with experimental data.

Stochastic switching to competence.

Distinct modes of gene expression enable isogenic populations of bacteria to maintain a diversity of phenotypes and to rapidly adapt to environmental changes. Competence development for DNA transformation in Bacillus subtilis has become a paradigm for a multimodal system which implements a genetic switch through a nonlinear positive feedback of a transcriptional master regulator. Recent advances in quantitative analysis at the single cell level in conjunction with mathematical modeling allowed a molecular level understanding of the switching probability between the noncompetent state and the competent state. It has been discovered that the genetic switching probability may be tuned by controlling noise in the transcription of the master regulator of competence, by timing of its expression, and by rewiring of the control circuit.

Basal expression rate of comK sets a 'switching-window' into the K-state of Bacillus subtilis.

Bacillus subtilis cell population divides into a competent fraction and a non-competent fraction in the stationary phase. The transition from the non-competent state (with basal ComK concentration) to the K-state (with high ComK concentration) behaves like a bistable switch. To better understand the mechanism that sets the fraction of cells that switch into the K-state (K-fraction), we characterized the basal comK expression in individual non-competent cells and found a large cell-to-cell variation. Basal expression rate increased exponentially, reached a maximum and decreased towards zero in the stationary phase. Concomitantly, the intrinsic switching rate increased and decreased with a time lag. When switching was induced prematurely by reduction of ComK proteolysis, the K-fraction increased strongly. Our data support a model in which the average basal level of ComK raises during late exponential phase and due to noise in basal comK expression only those cells that are on the high end of comK expression trigger the autocatalytic feedback for ComK transcription. We show that a subsequent shut-down of basal expression rate sets a 'time-window' for switching and is thus involved in determining the K-fraction in the bimodal population.