David Fange

Noise-Induced Min Phenotypes in E. coli

The spatiotemporal oscillations of the Escherichia coli proteins MinD and MinE direct cell division to the region between the chromosomes. Several quantitative models of the Min system have been suggested before, but no one of them accounts for the behavior of all documented mutant phenotypes. We analyzed the stochastic reaction-diffusion kinetics of the Min proteins for several E. coli mutants and compared the results to the corresponding deterministic mean-field description. We found that wild-type (wt) and filamentous (ftsZ −) cells are well characterized by the mean-field model, but that a stochastic model is necessary to account for several of the characteristics of the spherical (rodA−) and phospathedylethanolamide-deficient (PE−) phenotypes. For spherical cells, the mean-field model is bistable, and the system can get trapped in a non-oscillatory state. However, when the intrinsic noise is considered, only the experimentally observed oscillatory behavior remains. The stochastic model also reproduces the change in oscillation directions observed in the spherical phenotype and the occasional gliding of the MinD region along the inner membrane. For the PE− mutant, the stochastic model explains the appearance of randomly localized and dense MinD clusters as a nucleation phenomenon, in which the stochastic kinetics at low copy number causes local discharges of the high MinDATP to MinDADP potential. We find that a simple five-reaction model of the Min system can explain all documented Min phenotypes, if stochastic kinetics and three-dimensional diffusion are accounted for. Our results emphasize that local copy number fluctuation may result in phenotypic differences although the total number of molecules of the relevant species is high.

Stochastic reaction-diffusion kinetics in the microscopic limit

Quantitative analysis of biochemical networks often requires consideration of both spatial and stochastic aspects of chemical processes. Despite significant progress in the field, it is still computationally prohibitive to simulate systems involving many reactants or complex geometries using a microscopic framework that includes the finest length and time scales of diffusion-limited molecular interactions. For this reason, spatially or temporally discretized simulations schemes are commonly used when modeling intracellular reaction networks. The challenge in defining such coarse-grained models is to calculate the correct probabilities of reaction given the microscopic parameters and the uncertainty in the molecular positions introduced by the spatial or temporal discretization. In this paper we have solved this problem for the spatially discretized Reaction-Diffusion Master Equation; this enables a seamless and physically consistent transition from the microscopic to the macroscopic frameworks of reaction-diffusion kinetics. We exemplify the use of the methods by showing that a phosphorylation-dephosphorylation motif, commonly observed in eukaryotic signaling pathways, is predicted to display fluctuations that depend on the geometry of the system.

Single-particle tracking reveals that free ribosomal subunits are not excluded from the Escherichia coli nucleoid

Significance Single-particle tracking in living cells provides a way to identify a particles binding state based on how it moves. In this work, we track fluorescently labeled ribosomal subunits in bacterial cells. We show that translating ribosomes move much slower than free subunits. More importantly, we show that it is only translating ribosomes that are excluded from the bacterial nucleoid, whereas free subunits have full access to the nucleoid. This finding is important because several gene-regulation mechanisms require that ribosomes are able to initiate translation as soon as the RNA polymerase has initiated transcription, and it has been difficult to reconcile such a requirement with the observation that ribosomes are nucleoid-excluded. Biochemical and genetic data show that ribosomes closely follow RNA polymerases that are transcribing protein-coding genes in bacteria. At the same time, electron and fluorescence microscopy have revealed that ribosomes are excluded from the Escherichia coli nucleoid, which seems to be inconsistent with fast translation initiation on nascent mRNA transcripts. The apparent paradox can be reconciled if translation of nascent mRNAs can start throughout the nucleoid before they relocate to the periphery. However, this mechanism requires that free ribosomal subunits are not excluded from the nucleoid. Here, we use single-particle tracking in living E. coli cells to determine the fractions of free ribosomal subunits, classify individual subunits as free or mRNA-bound, and quantify the degree of exclusion of bound and free subunits separately. We show that free subunits are not excluded from the nucleoid. This finding strongly suggests that translation of nascent mRNAs can start throughout the nucleoid, which reconciles the spatial separation of DNA and ribosomes with cotranscriptional translation. We also show that, after translation inhibition, free subunit precursors are partially excluded from the compacted nucleoid. This finding indicates that it is active translation that normally allows ribosomal subunits to assemble on nascent mRNAs throughout the nucleoid and that the effects of translation inhibitors are enhanced by the limited access of ribosomal subunits to nascent mRNAs in the compacted nucleoid.

Direct measurement of transcription factor dissociation excludes a simple operator occupancy model for gene regulation

Transcription factors mediate gene regulation by site-specific binding to chromosomal operators. It is commonly assumed that the level of repression is determined solely by the equilibrium binding of a repressor to its operator. However, this assumption has not been possible to test in living cells. Here we have developed a single-molecule chase assay to measure how long an individual transcription factor molecule remains bound at a specific chromosomal operator site. We find that the lac repressor dimer stays bound on average 5 min at the native lac operator in Escherichia coli and that a stronger operator results in a slower dissociation rate but a similar association rate. Our findings do not support the simple equilibrium model. The discrepancy with this model can, for example, be accounted for by considering that transcription initiation drives the system out of equilibrium. Such effects need to be considered when predicting gene activity from transcription factor binding strengths.

Transcription-factor binding and sliding on DNA studied using micro- and macroscopic models.

Significance Transcription factors (TFs) are the major regulators of gene expression. We have used a combination of computer simulations and theoretical methods to explore the atomic details for how a model TF, the lac repressor, moves on DNA in search for its specific binding site. We find that it slides along the DNA along a helical path, which allows it to probe for specific binding in a major groove. The uniqueness in the study lies in that the fully atomistic molecular dynamics model allows us to estimate the microscopic interaction energies from the TF-DNA structure and that we have developed a theoretical tool to derive macroscopic, experimentally testable, predictions for DNA residence time and sliding lengths from the microscopic interaction energies. Transcription factors search for specific operator sequences by alternating rounds of 3D diffusion with rounds of 1D diffusion (sliding) along the DNA. The details of such sliding have largely been beyond direct experimental observation. For this purpose we devised an analytical formulation of umbrella sampling along a helical coordinate, and from extensive and fully atomistic simulations we quantified the free-energy landscapes that underlie the sliding dynamics and dissociation kinetics for the LacI dimer. The resulting potential of mean force distributions show a fine structure with an amplitude of 1 kBT for sliding and 12 kBT for dissociation. Based on the free-energy calculations the repressor slides in close contact with DNA for 8 bp on average before making a microscopic dissociation. By combining the microscopic molecular-dynamics calculations with Brownian simulation including rotational diffusion from the microscopically dissociated state we estimate a macroscopic residence time of 48 ms at the same DNA segment and an in vitro sliding distance of 240 bp. The sliding distance is in agreement with previous in vitro sliding-length estimates. The in vitro prediction for the macroscopic residence time also compares favorably to what we measure by single-molecule imaging of nonspecifically bound fluorescently labeled LacI in living cells. The investigation adds to our understanding of transcription-factor search kinetics and connects the macro-/mesoscopic rate constants to the microscopic dynamics.

Lost in presumption: stochastic reactions in spatial models

Physical modeling is increasingly important for generating insights into intracellular processes. We describe situations in which combined spatial and stochastic aspects of chemical reactions are needed to capture the relevant dynamics of biochemical systems.

Drug efflux pump deficiency and drug target resistance masking in growing bacteria

Recent experiments have shown that drug efflux pump deficiency not only increases the susceptibility of pathogens to antibiotics, but also seems to “mask” the effects of mutations, that decrease the affinities of drugs to their intracellular targets, on the growth rates of drug-exposed bacteria. That is, in the presence of drugs, the growth rates of drug-exposed WT and target mutated strains are the same in a drug efflux pump deficient background, but the mutants grow faster than WT in a drug efflux pump proficient background. Here, we explain the mechanism of target resistance masking and show that it occurs in response to drug efflux pump inhibition among pathogens with high-affinity drug binding targets, low cell-membrane drug-permeability and insignificant intracellular drug degradation. We demonstrate that target resistance masking is fundamentally linked to growth-bistability, i.e., the existence of 2 different steady state growth rates for one and the same drug concentration in the growth medium. We speculate that target resistance masking provides a hitherto unknown mechanism for slowing down the evolution of target resistance among pathogens.

MesoRD 1.0

SUMMARY MesoRD is a tool for simulating stochastic reaction-diffusion systems as modeled by the reaction diffusion master equation. The simulated systems are defined in the Systems Biology Markup Language with additions to define compartment geometries. MesoRD 1.0 supports scale-dependent reaction rate constants and reactions between reactants in neighbouring subvolumes. These new features make it possible to construct physically consistent models of diffusion-controlled reactions also at fine spatial discretization. AVAILABILITY MesoRD is written in C++ and licensed under the GNU general public license (GPL). MesoRD can be downloaded at http://mesord.sourceforge.net. The MesoRD homepage, http://mesord.sourceforge.net, contains detailed documentation and news about recently implemented features. CONTACT johan.elf@icm.uu.se.

In situ genotyping of a pooled strain library after characterizing complex phenotypes

In this work, we present a proof‐of‐principle experiment that extends advanced live cell microscopy to the scale of pool‐generated strain libraries. We achieve this by identifying the genotypes for individual cells in situ after a detailed characterization of the phenotype. The principle is demonstrated by single‐molecule fluorescence time‐lapse imaging of Escherichia coli strains harboring barcoded plasmids that express a sgRNA which suppresses different genes in the E. coli genome through dCas9 interference. In general, the method solves the problem of characterizing complex dynamic phenotypes for diverse genetic libraries of cell strains. For example, it allows screens of how changes in regulatory or coding sequences impact the temporal expression, location, or function of a gene product, or how the altered expression of a set of genes impacts the intracellular dynamics of a labeled reporter.

Simulated single molecule microscopy with SMeagol

Abstract Summary: SMeagol is a software tool to simulate highly realistic microscopy data based on spatial systems biology models, in order to facilitate development, validation and optimization of advanced analysis methods for live cell single molecule microscopy data. Availability and implementation: SMeagol runs on Matlab R2014 and later, and uses compiled binaries in C for reaction–diffusion simulations. Documentation, source code and binaries for Mac OS, Windows and Ubuntu Linux can be downloaded from http://smeagol.sourceforge.net. Contact: johan.elf@icm.uu.se Supplementary information: Supplementary data are available at Bioinformatics online.