Sara Jabbari

A systems biology approach to investigate the effect of pH-induced gene regulation on solvent production by Clostridium acetobutylicum in continuous culture.

BackgroundClostridium acetobutylicum is an anaerobic bacterium which is known for its solvent-producing capabilities, namely regarding the bulk chemicals acetone and butanol, the latter being a highly efficient biofuel. For butanol production by C. acetobutylicum to be optimized and exploited on an industrial scale, the effect of pH-induced gene regulation on solvent production by C. acetobutylicum in continuous culture must be understood as fully as possible.ResultsWe present an ordinary differential equation model combining the metabolic network governing solvent production with regulation at the genetic level of the enzymes required for this process. Parameterizing the model with experimental data from continuous culture, we demonstrate the influence of pH upon fermentation products: at high pH (pH 5.7) acids are the dominant product while at low pH (pH 4.5) this switches to solvents. Through steady-state analyses of the model we focus our investigations on how alteration in gene expression of C. acetobutylicum could be exploited to increase butanol yield in a continuous culture fermentation.ConclusionsIncorporating gene regulation into the model of solvent production by C. acetobutylicum enables an accurate representation of the pH-induced switch to solvent production to be obtained and theoretical investigations of possible synthetic-biology approaches to be pursued. Steady-state analyses suggest that, to increase butanol yield, alterations in the expression of single solvent-associated genes are insufficient; a more complex approach targeting two or more genes is required.

Hepatitis C Virus Envelope Glycoprotein Fitness Defines Virus Population Composition following Transmission to a New Host

ABSTRACT Genetic variability is a hallmark of RNA virus populations. However, transmission to a new host often results in a marked decrease in population diversity. This genetic bottlenecking is observed during hepatitis C virus (HCV) transmission and can arise via a selective sweep or through the founder effect. To model HCV transmission, we utilized chimeric SCID/Alb-uPA mice with transplanted human hepatocytes and infected them with a human serum HCV inoculum. E1E2 glycoprotein gene sequences in the donor inoculum and recipient mice were determined following single-genome amplification (SGA). In independent experiments, using mice with liver cells grafted from different sources, an E1E2 variant undetectable in the source inoculum was selected for during transmission. Bayesian coalescent analyses indicated that this variant arose in the inoculum pretransmission. Transmitted variants that established initial infection harbored key substitutions in E1E2 outside HVR1. Notably, all posttransmission E1E2s had lost a potential N-linked glycosylation site (PNGS) in E2. In lentiviral pseudoparticle assays, the major posttransmission E1E2 variant conferred an increased capacity for entry compared to the major variant present in the inoculum. Together, these data demonstrate that increased envelope glycoprotein fitness can drive selective outgrowth of minor variants posttransmission and that loss of a PNGS is integral to this improved phenotype. Mathematical modeling of the dynamics of competing HCV variants indicated that relatively modest differences in glycoprotein fitness can result in marked shifts in virus population composition. Overall, these data provide important insights into the dynamics and selection of HCV populations during transmission.

Bacterial fitness shapes the population dynamics of antibiotic-resistant and -susceptible bacteria in a model of combined antibiotic and anti-virulence treatment.

Bacterial resistance to antibiotic treatment is a huge concern: introduction of any new antibiotic is shortly followed by the emergence of resistant bacterial isolates in the clinic. This issue is compounded by a severe lack of new antibiotics reaching the market. The significant rise in clinical resistance to antibiotics is especially problematic in nosocomial infections, where already vulnerable patients may fail to respond to treatment, causing even greater health concern. A recent focus has been on the development of anti-virulence drugs as a second line of defence in the treatment of antibiotic-resistant infections. This treatment, which weakens bacteria by reducing their virulence rather than killing them, should allow infections to be cleared through the body׳s natural defence mechanisms. In this way there should be little to no selective pressure exerted on the organism and, as such, a predominantly resistant population should be less likely to emerge. However, before the likelihood of resistance to these novel drugs emerging can be predicted, we must first establish whether such drugs can actually be effective. Many believe that anti-virulence drugs would not be powerful enough to clear existing infections, restricting their potential application to prophylaxis. We have developed a mathematical model that provides a theoretical framework to reveal the circumstances under which anti-virulence drugs may or may not be successful. We demonstrate that by harnessing and combining the advantages of antibiotics with those provided by anti-virulence drugs, given infection-specific parameters, it is possible to identify treatment strategies that would efficiently clear bacterial infections, while preventing the emergence of antibiotic-resistant subpopulations. Our findings strongly support the continuation of research into anti-virulence drugs and demonstrate that their applicability may reach beyond infection prevention.

Mathematical modelling of the agr operon in Staphylococcus aureus.

Staphylococcus aureus is a pathogenic bacterium that utilises quorum sensing (QS), a cell-to-cell signalling mechanism, to enhance its ability to cause disease. QS allows the bacteria to monitor their surroundings and the size of their population, and S. aureus makes use of this to regulate the production of virulence factors. Here we describe a mathematical model of this QS system and perform a detailed time-dependent asymptotic analysis in order to clarify the roles of the distinct interactions that make up the QS process, demonstrating which reactions dominate the behaviour of the system at various timepoints. We couple this analysis with numerical simulations and are thus able to gain insight into how a large population of S. aureus shifts from a relatively harmless state to a highly virulent one, focussing on the need for the three distinct phases which form the feedback loop of this particular QS system.

pH-induced gene regulation of solvent production by Clostridium acetobutylicum in continuous culture: Parameter estimation and sporulation modelling

Highlights ► Metabolic ODE system as previously derived is underdetermined from the data. ► Inclusion of spore fraction post-pH shift in experiments improves the fit. ► Assuming approximately 75% of culture sporulates further improves the fit. ► Assays of acetyl-CoA, butyryl-CoA and spores will validate model.

Cross-Strain Quorum Sensing Inhibition by Staphylococcus Aureus. Part 2: A Spatially Inhomogeneous Model

Staphylococcus aureus uses quorum sensing (QS) to enhance its pathogenicity. An intriguing aspect of this is that different strains are capable of inactivating the QS systems of opposing strains. In Part 1 of this study, we presented a model of this phenomenon in a well-mixed environment; here, we incorporate spatial structure. Two competitive strains occupying adjacent habitats with freely diffusing QS signal molecules (QSSMs) are considered. We investigate the effect of the QSSM diffusion coefficient and the relative size of the two populations on the ability of one population to dominate the other. Regarding population size, a larger population is generally at an advantage (initial conditions permitting), while the implications of different diffusivities are more complex and depend upon the sizes of the populations.

Analysis of occludin trafficking, demonstrating continuous endocytosis, degradation, recycling and biosynthetic secretory trafficking.

Tight junctions (TJs) link adjacent cells and are critical for maintenance of apical-basolateral polarity in epithelial monolayers. The TJ protein occludin functions in disparate processes, including wound healing and Hepatitis C Virus infection. Little is known about steady-state occludin trafficking into and out of the plasma membrane. Therefore, we determined the mechanisms responsible for occludin turnover in confluent Madin-Darby canine kidney (MDCK) epithelial monolayers. Using various biotin-based trafficking assays we observed continuous and rapid endocytosis of plasma membrane localised occludin (the majority internalised within 30 minutes). By 120 minutes a significant reduction in internalised occludin was observed. Inhibition of lysosomal function attenuated the reduction in occludin signal post-endocytosis and promoted co-localisation with the late endocytic system. Using a similar method we demonstrated that ∼20% of internalised occludin was transported back to the cell surface. Consistent with these findings, significant co-localisation between internalised occludin and recycling endosomal compartments was observed. We then quantified the extent to which occludin synthesis and transport to the plasma membrane contributes to plasma membrane occludin homeostasis, identifying inhibition of protein synthesis led to decreased plasma membrane localised occludin. Significant co-localisation between occludin and the biosynthetic secretory pathway was demonstrated. Thus, under steady-state conditions occludin undergoes turnover via a continuous cycle of endocytosis, recycling and degradation, with degradation compensated for by biosynthetic exocytic trafficking. We developed a mathematical model to describe the endocytosis, recycling and degradation of occludin, utilising experimental data to provide quantitative estimates for the rates of these processes.

Mathematical modelling reveals properties of TcdC required for it to be a negative regulator of toxin production in Clostridium difficile

The role of the protein TcdC in pathogenicity of the bacterium Clostridium difficile is currently unclear: conflicting reports suggest it is either a negative regulator of toxin production or, on the other hand, has no effect on virulence at all. We exploit a theoretical approach by taking what is known about the network of proteins surrounding toxin production by C. difficile and translating this into a mathematical model. From there it is possible to investigate a range of possible interactions (using numerical and asymptotic analyses), identifying properties of TcdC which would make it a realistic candidate as a toxin inhibitor. Our findings imply that if TcdC is really an inhibitor of toxin production then TcdC production should be at least as fast as that of the protein TcdR and TcdC should remain in the cells throughout growth. These are experimentally-testable hypotheses and are equally applicable to alternative candidates for toxin production inhibition.

The putative influence of the agr operon upon survival mechanisms used by Clostridium acetobutylicum

The bacterium Clostridium acetobutylicum produces acids as an energy-yielding process during exponential growth. An acidic environment, however, is toxic to the cells and two survival mechanisms are in place to prevent them from dying. Firstly, during a solventogenesis phase, the cells take up these acids and convert them to solvents, thus raising the environmental pH. Secondly, the cells undergo sporulation to form highly resistant spores capable of surviving extreme conditions. One possible regulatory mechanism for these processes is the accessory gene regulatory (agr) quorum-sensing system, which is thought to coordinate cell population density with cell phenotype. We model this system to monitor its putative effect upon solventogenesis and the sporulation-initiation network responsible for triggering spore formation. We demonstrate that a high population density should be able to induce both solventogenesis and sporulation, with variations to the parameter set allowing sporulation alone to be triggered; additional distinct signals are capable of restoring the solventogenic response. We compare the agr system of C. acetobutylicum with that of Staphylococcus aureus in order to investigate why the differences in feedback between the two systems may have evolved. Our findings indicate that, depending upon the mechanism of interaction between the agr system and the sporulation-initiation network, the clostridial agr circuitry may be in place either to moderate the number of spores that are formed (in order for this number to reflect the urgency of the situation), or simply as an energy-saving strategy.

The Essential Genome of Escherichia coli K-12

ABSTRACT Transposon-directed insertion site sequencing (TraDIS) is a high-throughput method coupling transposon mutagenesis with short-fragment DNA sequencing. It is commonly used to identify essential genes. Single gene deletion libraries are considered the gold standard for identifying essential genes. Currently, the TraDIS method has not been benchmarked against such libraries, and therefore, it remains unclear whether the two methodologies are comparable. To address this, a high-density transposon library was constructed in Escherichia coli K-12. Essential genes predicted from sequencing of this library were compared to existing essential gene databases. To decrease false-positive identification of essential genes, statistical data analysis included corrections for both gene length and genome length. Through this analysis, new essential genes and genes previously incorrectly designated essential were identified. We show that manual analysis of TraDIS data reveals novel features that would not have been detected by statistical analysis alone. Examples include short essential regions within genes, orientation-dependent effects, and fine-resolution identification of genome and protein features. Recognition of these insertion profiles in transposon mutagenesis data sets will assist genome annotation of less well characterized genomes and provides new insights into bacterial physiology and biochemistry. IMPORTANCE Incentives to define lists of genes that are essential for bacterial survival include the identification of potential targets for antibacterial drug development, genes required for rapid growth for exploitation in biotechnology, and discovery of new biochemical pathways. To identify essential genes in Escherichia coli, we constructed a transposon mutant library of unprecedented density. Initial automated analysis of the resulting data revealed many discrepancies compared to the literature. We now report more extensive statistical analysis supported by both literature searches and detailed inspection of high-density TraDIS sequencing data for each putative essential gene for the E. coli model laboratory organism. This paper is important because it provides a better understanding of the essential genes of E. coli, reveals the limitations of relying on automated analysis alone, and provides a new standard for the analysis of TraDIS data. IMPORTANCE Incentives to define lists of genes that are essential for bacterial survival include the identification of potential targets for antibacterial drug development, genes required for rapid growth for exploitation in biotechnology, and discovery of new biochemical pathways. To identify essential genes in Escherichia coli, we constructed a transposon mutant library of unprecedented density. Initial automated analysis of the resulting data revealed many discrepancies compared to the literature. We now report more extensive statistical analysis supported by both literature searches and detailed inspection of high-density TraDIS sequencing data for each putative essential gene for the E. coli model laboratory organism. This paper is important because it provides a better understanding of the essential genes of E. coli, reveals the limitations of relying on automated analysis alone, and provides a new standard for the analysis of TraDIS data.