Analyzing microbial disease at high resolution: following the fate of the bacterium during infection

Crimmins, Gregory T.; Isberg, Ralph R.

doi:10.1016/j.mib.2011.11.005

Cited by 11 publications

(9 citation statements)

References 15 publications

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“…Thanks to recent technological developments in microbiology, and pushed by growing concern over antimicrobial resistance and the need for new vaccines, the last decade has witnessed rapid progress in the quantification of in vivo dynamics of bacterial infection in animal models. Two experimental approaches in particular have shown great promise across multiple pathogen species: isogenic tagging, the focus of this report, and fluorescence dilution, a term encompassing several techniques from which bacterial replication can be inferred [ 2 ]. Isogenic tagging (IT) consists in generating an arbitrary number of sub-clones of a given bacterial strain, each defined by a unique genetic tag (a predetermined nucleotide sequence) inserted in a non-coding region of the chromosome.…”

Section: Introductionmentioning

confidence: 99%

An efficient moments-based inference method for within-host bacterial infection dynamics

Price¹,

Breuzé²,

Dybowski³

et al. 2017

PLoS Comput Biol

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Over the last ten years, isogenic tagging (IT) has revolutionised the study of bacterial infection dynamics in laboratory animal models. However, quantitative analysis of IT data has been hindered by the piecemeal development of relevant statistical models. The most promising approach relies on stochastic Markovian models of bacterial population dynamics within and among organs. Here we present an efficient numerical method to fit such stochastic dynamic models to in vivo experimental IT data. A common approach to statistical inference with stochastic dynamic models relies on producing large numbers of simulations, but this remains a slow and inefficient method for all but simple problems, especially when tracking bacteria in multiple locations simultaneously. Instead, we derive and solve the systems of ordinary differential equations for the two lower-order moments of the stochastic variables (mean, variance and covariance). For any given model structure, and assuming linear dynamic rates, we demonstrate how the model parameters can be efficiently and accurately estimated by divergence minimisation. We then apply our method to an experimental dataset and compare the estimates and goodness-of-fit to those obtained by maximum likelihood estimation. While both sets of parameter estimates had overlapping confidence regions, the new method produced lower values for the division and death rates of bacteria: these improved the goodness-of-fit at the second time point at the expense of that of the first time point. This flexible framework can easily be applied to a range of experimental systems. Its computational efficiency paves the way for model comparison and optimal experimental design.

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Section: Introductionmentioning

confidence: 99%

An efficient moments-based inference method for within-host bacterial infection dynamics

Price¹,

Breuzé²,

Dybowski³

et al. 2017

PLoS Comput Biol

View full text Add to dashboard Cite

show abstract

“…Alterations in growth and division may not necessarily manifest in changes to colony-forming units (CFU), the most common measurement of bacterial replication outside of broth culture (Crimmins and Isberg, 2012; Helaine and Holden, 2013; Manina and McKinney, 2013). Enumeration of the total bacterial burden can undercount quiescent organisms as well as those that are growing but not dividing.…”

Section: Introductionmentioning

confidence: 99%

Host Actin Polymerization Tunes the Cell Division Cycle of an Intracellular Pathogen

et al. 2015

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SUMMARY Growth and division are two of the most fundamental capabilities of a bacterial cell. While they are well described for model organisms growing in broth culture, very little is known about the cell division cycle of bacteria replicating in more complex environments. Using a D-alanine reporter strategy, we found that intracellular Listeria monocytogenes (Lm) spend a smaller proportion of their cell cycle dividing compared to Lm growing in broth culture. This alteration to the cell division cycle is independent of bacterial doubling time. Instead, polymerization of host-derived actin at the bacterial cell surface extends the non-dividing elongation period and compresses the division period. By decreasing the relative proportion of dividing Lm, actin polymerization biases the population towards cells with the highest propensity to form actin tails. Thus, there is a positive feedback loop between the Lm cell division cycle and a physical interaction with the host cytoskeleton.

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“…One way to overcome the limitations of classical infection experiments is to perform co-infections with tagged pathogens and to apply probabilistic models. Such approaches offer unprecedented insights into the dynamics of bacterial populations and may change fundamentally our understanding of bacterial infections [13], [14]. However, so far the potential of such approaches has not been fully exploited.…”

Section: Introductionmentioning

confidence: 99%

Independent Bottlenecks Characterize Colonization of Systemic Compartments and Gut Lymphoid Tissue by Salmonella

et al. 2014

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Vaccination represents an important instrument to control typhoid fever in humans and protects mice from lethal infection with mouse pathogenic serovars of Salmonella species. Mixed infections with tagged Salmonella can be used in combination with probabilistic models to describe the dynamics of the infection process. Here we used mixed oral infections with tagged Salmonella strains to identify bottlenecks in the infection process in naïve and vaccinated mice. We established a next generation sequencing based method to characterize the composition of tagged Salmonella strains which offers a fast and reliable method to characterise the composition of genome-tagged Salmonella strains. We show that initial colonization of Salmonella was distinguished by a non-Darwinian selection of few bacteria setting up the infection independently in gut associated lymphoid tissue and systemic compartments. Colonization of Peyer's patches fuels the sustained spread of bacteria into mesenteric lymph nodes via dendritic cells. In contrast, infection of liver and spleen originated from an independent pool of bacteria. Vaccination only moderately reduced invasion of Peyer's patches but potently uncoupled bacterial populations present in different systemic compartments. Our data indicate that vaccination differentially skews the capacity of Salmonella to colonize systemic and gut immune compartments and provide a framework for the further dissection of infection dynamics.

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Analyzing microbial disease at high resolution: following the fate of the bacterium during infection

Cited by 11 publications

References 15 publications

An efficient moments-based inference method for within-host bacterial infection dynamics

An efficient moments-based inference method for within-host bacterial infection dynamics

Host Actin Polymerization Tunes the Cell Division Cycle of an Intracellular Pathogen

Independent Bottlenecks Characterize Colonization of Systemic Compartments and Gut Lymphoid Tissue by Salmonella

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