Single passage in mouse organs enhances the survival and spread of Salmonella enterica

Intravenous inoculation of Salmonella enterica serovar Typhimurium into mice is a prime experimental model of invasive salmonellosis. The use of wild-type isogenic tagged strains (WITS) in this system has revealed that bacteria undergo independent bottlenecks in the liver and spleen before establishing a systemic infection. We recently showed that those bacteria that survived the bottleneck exhibited enhanced growth when transferred to naive mice. In this study, we set out to disentangle the components of this in vivo adaptation by inoculating mice with WITS grown either in vitro or in vivo. We developed an original method to estimate the replication and killing rates of bacteria from experimental data, which involved solving the probability-generating function of a non-homogeneous birth–death–immigration process. This revealed a low initial mortality in bacteria obtained from a donor animal. Next, an analysis of WITS distributions in the livers and spleens of recipient animals indicated that in vivo-passaged bacteria started spreading between organs earlier than in vitro-grown bacteria. These results further our understanding of the influence of passage in a host on the fitness and virulence of Salmonella enterica and represent an advance in the power of investigation on the patterns and mechanisms of host–pathogen interactions.

[1]  Ward Whitt,et al.  An Introduction to Numerical Transform Inversion and Its Application to Probability Models , 2000 .

[2]  I. Hautefort,et al.  Single-Copy Green Fluorescent Protein Gene Fusions Allow Accurate Measurement of Salmonella Gene Expression In Vitro and during Infection of Mammalian Cells , 2003, Applied and Environmental Microbiology.

[3]  F. Feroz,et al.  MultiNest: an efficient and robust Bayesian inference tool for cosmology and particle physics , 2008, 0809.3437.

[4]  Ward Whitt,et al.  Numerical inversion of probability generating functions , 1992, Oper. Res. Lett..

[5]  Ward Whitt,et al.  The Fourier-series method for inverting transforms of probability distributions , 1992, Queueing Syst. Theory Appl..

[6]  A. Bäumler,et al.  How To Become a Top Model: Impact of Animal Experimentation on Human Salmonella Disease Research , 2011, Infection and Immunity.

[7]  S. Clare,et al.  Enhanced Virulence of Salmonella enterica Serovar Typhimurium after Passage through Mice , 2010, Infection and Immunity.

[8]  J. Skilling Nested sampling for general Bayesian computation , 2006 .

[9]  Brendon J. Brewer,et al.  Diffusive nested sampling , 2009, Stat. Comput..

[10]  L. Smith,et al.  Bacterial Contamination of Blood Components , 2003, American Society for Clinical Laboratory Science.

[11]  Young Eun Kim,et al.  Burden of typhoid fever in low-income and middle-income countries: a systematic, literature-based update with risk-factor adjustment. , 2014, The Lancet. Global health.

[12]  D. Maskell,et al.  Dynamics of bacterial growth and distribution within the liver during Salmonella infection , 2003, Cellular microbiology.

[13]  Roland R. Regoes,et al.  Lymph Node Colonization Dynamics after Oral Salmonella Typhimurium Infection in Mice , 2013, PLoS pathogens.

[14]  B. Stocker,et al.  Aromatic-dependent Salmonella typhimurium are non-virulent and effective as live vaccines , 1981, Nature.

[15]  D. Kendall Applied Probability , 1958, Nature.

[16]  Olivier Restif,et al.  Modelling within-Host Spatiotemporal Dynamics of Invasive Bacterial Disease , 2008, PLoS biology.

[17]  R. Isberg,et al.  Analyzing microbial disease at high resolution: following the fate of the bacterium during infection. , 2012, Current opinion in microbiology.

[18]  Richard Dybowski,et al.  The Effects of Vaccination and Immunity on Bacterial Infection Dynamics In Vivo , 2014, PLoS pathogens.

[19]  Roland R. Regoes,et al.  Cecum Lymph Node Dendritic Cells Harbor Slow-Growing Bacteria Phenotypically Tolerant to Antibiotic Treatment , 2014, PLoS biology.