Phenotypic Heterogeneity in Mycobacterial Stringent Response

A common survival strategy of microorganisms subjected to stress involves the generation of phenotypic heterogeneity in the isogenic microbial population enabling a subset of the population to survive under stress. In a recent study, a mycobacterial population of M. smegmatis was shown to develop phenotypic heterogeneity under nutrient depletion. The observed heterogeneity is in the form of a bimodal distribution of the expression levels of the Green Fluorescent Protein (GFP) as reporter with the gfp fused to the promoter of the rel gene. The stringent response pathway is initiated in the subpopulation with high rel activity.In the present study, we characterize quantitatively the single cell promoter activity of the three key genes, namely, mprA, sigE and rel, in the stringent response pathway with gfp as the reporter. The origin of bimodality in the GFP distribution lies in two stable expression states, i.e., bistability. We develop a theoretical model to study the dynamics of the stringent response pathway. The model incorporates a recently proposed mechanism of bistability based on positive feedback and cell growth retardation due to protein synthesis. Based on flow cytometry data, we establish that the distribution of GFP levels in the mycobacterial population at any point of time is a linear superposition of two invariant distributions, one Gaussian and the other lognormal, with only the coefficients in the linear combination depending on time. This allows us to use a binning algorithm and determine the time variation of the mean protein level, the fraction of cells in a subpopulation and also the coefficient of variation, a measure of gene expression noise.The results of the theoretical model along with a comprehensive analysis of the flow cytometry data provide definitive evidence for the coexistence of two subpopulations with overlapping protein distributions.Comment: 24 pages,8 figures, supplementary information and 5 supplementary figure

Dependence of Bacterial Chemotaxis on Gradient Shape and Adaptation Rate

Simulation of cellular behavior on multiple scales requires models that are sufficiently detailed to capture central intracellular processes but at the same time enable the simulation of entire cell populations in a computationally cheap way. In this paper we present RapidCell, a hybrid model of chemotactic Escherichia coli that combines the Monod-Wyman-Changeux signal processing by mixed chemoreceptor clusters, the adaptation dynamics described by ordinary differential equations, and a detailed model of cell tumbling. Our model dramatically reduces computational costs and allows the highly efficient simulation of E. coli chemotaxis. We use the model to investigate chemotaxis in different gradients, and suggest a new, constant-activity type of gradient to systematically study chemotactic behavior of virtual bacteria. Using the unique properties of this gradient, we show that optimal chemotaxis is observed in a narrow range of CheA kinase activity, where concentration of the response regulator CheY-P falls into the operating range of flagellar motors. Our simulations also confirm that the CheB phosphorylation feedback improves chemotactic efficiency by shifting the average CheY-P concentration to fit the motor operating range. Our results suggest that in liquid media the variability in adaptation times among cells may be evolutionary favorable to ensure coexistence of subpopulations that will be optimally tactic in different gradients. However, in a porous medium (agar) such variability appears to be less important, because agar structure poses mainly negative selection against subpopulations with low levels of adaptation enzymes. RapidCell is available from the authors upon request

Base Pairing Interaction between 5′- and 3′-UTRs Controls icaR mRNA Translation in Staphylococcus aureus

The presence of regulatory sequences in the 3′ untranslated region (3′-UTR) of eukaryotic mRNAs controlling RNA stability and translation efficiency is widely recognized. In contrast, the relevance of 3′-UTRs in bacterial mRNA functionality has been disregarded. Here, we report evidences showing that around one-third of the mapped mRNAs of the major human pathogen Staphylococcus aureus carry 3′-UTRs longer than 100-nt and thus, potential regulatory functions. We selected the long 3′-UTR of icaR, which codes for the repressor of the main exopolysaccharidic compound of the S. aureus biofilm matrix, to evaluate the role that 3′-UTRs may play in controlling mRNA expression. We showed that base pairing between the 3′-UTR and the Shine-Dalgarno (SD) region of icaR mRNA interferes with the translation initiation complex and generates a double-stranded substrate for RNase III. Deletion or substitution of the motif (UCCCCUG) within icaR 3′-UTR was sufficient to abolish this interaction and resulted in the accumulation of IcaR repressor and inhibition of biofilm development. Our findings provide a singular example of a new potential post-transcriptional regulatory mechanism to modulate bacterial gene expression through the interaction of a 3′-UTR with the 5′-UTR of the same mRNA. © 2013 Ruiz de los Mozos et al.Peer Reviewe

Image Processing and Simulation Toolboxes of Microscopy Images of Bacterial Cells

Recent advances in microscopy imaging technology have allowed the characterization of the dynamics of cellular processes at the single-cell and single-molecule level. Particularly in bacterial cell studies, and using the E. coli as a case study, these techniques have been used to detect and track internal cell structures such as the Nucleoid and the Cell Wall and fluorescently tagged molecular aggregates such as FtsZ proteins, Min system proteins, inclusion bodies and all the different types of RNA molecules. These studies have been performed with using multi-modal, multi-process, time-lapse microscopy, producing both morphological and functional images. To facilitate the finding of relationships between cellular processes, from small-scale, such as gene expression, to large-scale, such as cell division, an image processing toolbox was implemented with several automatic and/or manual features such as, cell segmentation and tracking, intra-modal and intra-modal image registration, as well as the detection, counting and characterization of several cellular components. Two segmentation algorithms of cellular component were implemented, the first one based on the Gaussian Distribution and the second based on Thresholding and morphological structuring functions. These algorithms were used to perform the segmentation of Nucleoids and to identify the different stages of FtsZ Ring formation (allied with the use of machine learning algorithms), which allowed to understand how the temperature influences the physical properties of the Nucleoid and correlated those properties with the exclusion of protein aggregates from the center of the cell. Another study used the segmentation algorithms to study how the temperature affects the formation of the FtsZ Ring. The validation of the developed image processing methods and techniques has been based on benchmark databases manually produced and curated by experts. When dealing with thousands of cells and hundreds of images, these manually generated datasets can become the biggest cost in a research project. To expedite these studies in terms of time and lower the cost of the manual labour, an image simulation was implemented to generate realistic artificial images. The proposed image simulation toolbox can generate biologically inspired objects that mimic the spatial and temporal organization of bacterial cells and their processes, such as cell growth and division and cell motility, and cell morphology (shape, size and cluster organization). The image simulation toolbox was shown to be useful in the validation of three cell tracking algorithms: Simple Nearest-Neighbour, Nearest-Neighbour with Morphology and DBSCAN cluster identification algorithm. It was shown that the Simple Nearest-Neighbour still performed with great reliability when simulating objects with small velocities, while the other algorithms performed better for higher velocities and when there were larger clusters present

Study of a Bacillus circulans chitin-binding domain by a green fluorescent protein binding assay and detection of lysozymes by improved zymograms

A fluorescent binding assay was developed to investigate the effects of site-directed mutagenesis on the binding affinity and binding specificity of the chitin-binding domain of chitinase A1 from Bacillus circulans WL-12. The chitin-binding domain (ChBD) was genetically fused to the N-terminus of the green fluorescent protein, GFP. The polyhistidine-tagged hybrid protein was expressed in Escherichia coli under the dose-dependent regulation of the araBAD promoter and purified using metal affinity-, chitin- or ion-exchange chromatography. Residues suggested to be involved in binding from previous three-dimensional studies were mutated and their contributions to binding and substrate specificity were evaluated by depletion assays. Purified fusion proteins were incubated with chitin beads, polysaccharide-protein complexes were removed by centrifugation and the free protein concentration was measured fluorometrically. The experimental binding isotherms were analyzed by non-linear regression using a modified Langmuir equation. Binding affinity and specificity were alternatively studied by affinity electrophoresis under non-denaturing conditions. Non-conservative substitution of tryptophan residue (W687) with alanine abolished chitin-binding affinity. Double mutation E668K/P689A also impaired binding significantly. Other substitutions in the binding site had little effect on overall affinity for chitin. Interestingly, mutation T682A led to a higher specificity towards chitinous substrates than observed for the wild-type. Furthermore, the ChBD-GFP hybrid protein proved to be useful for specifically labeling cell walls of fungi and yeast and for the detection of fungal infections in tissue samples. Additionally, an improved method for detecting cell lytic activity by a colorbased zymogram was developed. Proteins were separated by electrophoresis in SDS-polyacrylamide gels copolymerized with Remazol-brilliant-blue labeled whole cells of Micrococcus lysodeikticus. After electrophoresis, the enzymes were allowed to refold and lyse the blue-labeled cells embedded in the gel, producing clearing zones in an otherwise bluish gel. This improved zymogram method allows the rapid, sensitive and simultaneous determination of cell lytic specificity, relative activity and molecular weight. This assay should be useful for many research disciplines investigating the role of lysozymes and other cell wall hydrolases capable of refolding after SDS treatment

Overcoming Metabolic Burden in Synthetic Biology: a CRISPR interference approach

Synthetic Biology is gaining an increasingly important role in the scientific community and dedicated research centers are rising all over the world. This discipline introduced the engineering principles of abstraction, modularity and standardization in the biology world; the application of these principles is allowing the design of complex biological systems to program living cells, realizing all sorts of desired function in many fields. These systems consist of DNA sequences, rationally combined to program the genetic instructions for cell behavior customization. Each part should behave as a biological brick for the design of complex genetic programs through functional building blocks; each module undergoes an extensive characterization to provide documentation on its functioning, enabling the rational design of complex circuits. Mathematical modeling accompanies all the design procedure as a tool to describe the behavior of each single genetic module, in a bottom-up fashion that should allow the prediction of more complex systems obtained by the interconnection of pre-characterized parts. However, many unpredictability sources hamper the ideally rational design of those synthetic genetic devices, mainly due to the tangled context-dependency behavior of those parts once placed into an intrinsically complex biological living system. Among others, the finite amount of translational resources in prokaryotic cells leads to an effect called metabolic burden, as a result of which hidden interactions between protein synthesis rates arise, leading to unexpected counterintuitive behaviors. To face this issue, two actions have been proposed in this study: firstly, a recently proposed mathematical modeling solution that included a description of the metabolic load exerted by the expression of recombinant genes have been applied on a case study, highlighting its worth of use and working boundaries; second, a CRISPR interference-based architecture have been developed to be used as an alternative to high resource usage transcriptional protein regulators, studying the underlying mechanism in several circuital configurations and optimizing each forming part in order to achieve the desired specifications. In Chapter 1, an introduction on synthetic biology is presented; in the second part, a brief overview on CRISPR technology and the overall aim of the study are reported. In Chapter 2, a case study evaluating the use of mathematical modeling to properly include metabolic burden in rational design of a set of transcriptional regulator cascades is reported. Firstly, the circuits and expected behavior are introduced, along with the discussion about experimental data, dissenting from what initially predicted. Secondly, the comparison between the use of a classical Hill equation-based model and an improved version that explicitly consider the translational load exerted by the expression of recombinant genes is reported. In Chapter 3, the design and deep characterization of a BioBrick$^{TM}$-compatible CRISPR interference-based repression set of modules is shown; expression optimization of the molecular players is reported and its usability as a low-burden alternative is demonstrated with experimental data and mathematical modeling. Working boundaries, peculiar aspects and rooms for improvements are then highlighted. In Chapter 4, preliminary studies aimed to improve the CRISPR interference system are reported and some of its context-dependencies are highlighted. Effects on repression efficiency due to alteration in the sequence of the RNA molecules addressing the CRISPR machinery to the desired target are discussed; evaluation of problems and opportunities related to the expression of more of this RNA guides are then highlighted. Lastly, an example of behavior of the system in presence of a competitor transcriptional regulator is reported. In Chapter 5 the overall conclusions of this thesis work are drawn

Rational Elaborated Common Strategies Employed For The Efficient in Silico Optimization Of An Accesible Synthetically (AMPs) Peptidomimetic-similar To An Amphiphile-Based Pharmacophoric Agent As A Promising Enhanced Therapeutic Antimicrobial Agent

Antimicrobial peptides (AMPs) which predominantly act via membrane active mechanisms haveemerged as an exciting class of antimicrobial agents with tremendous potential to overcome the globalepidemic of antibiotics-resistant infections. The first generation of AMPs derived from natural sources asdiverse as plants, insects and humans has provided a wealth of compositional and structural information todesign novel synthetic AMPs with enhanced antimicrobial potencies and selectivities, reduced cost ofproduction due to shorter sequences and improved stabilities under physiological conditions. As a rationalresult we discovered for the first time the GENEA-Antimamphiler-109 utilizing threading/structure-basedBIOGENETOLIGANDOROLTM Rational Strategies employed for the in silico design and optimization ofsynthetic antimicrobial peptide mimic amphiphile-based pharmacophoric agents with promising enhancedtherapeutic potentials introducing the iview: an interactive WebGL visualizer for protein-ligand complexthrough a subpocket analysis method for fragment-based drug discovery through a KNIME-SharedBiogenetoligandorolTM binding site amino acid predicted similarity subpockets