| Literature DB >> 23637626 |
Roy R Chaudhuri1, Eirwen Morgan, Sarah E Peters, Stephen J Pleasance, Debra L Hudson, Holly M Davies, Jinhong Wang, Pauline M van Diemen, Anthony M Buckley, Alison J Bowen, Gillian D Pullinger, Daniel J Turner, Gemma C Langridge, A Keith Turner, Julian Parkhill, Ian G Charles, Duncan J Maskell, Mark P Stevens.
Abstract
Chickens, pigs, and cattle are key reservoirs of Salmonella enterica, a foodborne pathogen of worldwide importance. Though a decade has elapsed since publication of the first Salmonella genome, thousands of genes remain of hypothetical or unknown function, and the basis of colonization of reservoir hosts is ill-defined. Moreover, previous surveys of the role of Salmonella genes in vivo have focused on systemic virulence in murine typhoid models, and the genetic basis of intestinal persistence and thus zoonotic transmission have received little study. We therefore screened pools of random insertion mutants of S. enterica serovar Typhimurium in chickens, pigs, and cattle by transposon-directed insertion-site sequencing (TraDIS). The identity and relative fitness in each host of 7,702 mutants was simultaneously assigned by massively parallel sequencing of transposon-flanking regions. Phenotypes were assigned to 2,715 different genes, providing a phenotype-genotype map of unprecedented resolution. The data are self-consistent in that multiple independent mutations in a given gene or pathway were observed to exert a similar fitness cost. Phenotypes were further validated by screening defined null mutants in chickens. Our data indicate that a core set of genes is required for infection of all three host species, and smaller sets of genes may mediate persistence in specific hosts. By assigning roles to thousands of Salmonella genes in key reservoir hosts, our data facilitate systems approaches to understand pathogenesis and the rational design of novel cross-protective vaccines and inhibitors. Moreover, by simultaneously assigning the genotype and phenotype of over 90% of mutants screened in complex pools, our data establish TraDIS as a powerful tool to apply rich functional annotation to microbial genomes with minimal animal use.Entities:
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Year: 2013 PMID: 23637626 PMCID: PMC3630085 DOI: 10.1371/journal.pgen.1003456
Source DB: PubMed Journal: PLoS Genet ISSN: 1553-7390 Impact factor: 5.917
Figure 1Experimental strategy for TraDIS mutant screens.
An input pool of random transposon insertion mutants is generated, and used to inoculate experimental animals. Output pools of bacteria that are capable of survival and growth in each host are isolated from an appropriate tissue. Massively parallel sequencing of the regions flanking each transposon allow the disrupted genes to be identified, and comparison of the sequence counts derived from the input and output pools allows the relative fitness of each mutant to be assessed.
Figure 2Circular diagrams of the S. Typhimurium SL1344 chromosome and plasmids (not to scale), showing the near random distribution and high density of transposon insertions mapped by TraDIS.
The inner two rings indicate the positions of annotated genes, coloured according to their GC content (blue = low, yellow = intermediate, red = high). The outer ring indicates the number of transposon-flanking sequence reads obtained at each position, with peaks corresponding to the presence of a transposon insertion.
Figure 3Relative fitness scores (defined as log2 fold changes in sequence read counts between input and output pools) for each transposon mutant, plotted against average read coverage (equivalent to an M/A plot, commonly used to display microarray data) for each of the four host species.
Mutants which showed a significant change in abundance in the output relative to the input are highlighted in red. Mutants which had no reads in the output pool are assigned an arbitrary fitness score of −15.
Figure 4Venn diagrams showing the attenutation phenotypes observed in chickens, pigs, and cattle using TraDIS.
A) the numbers of transposon mutants which were significantly attenuated in each host B) the numbers of genes which were disrupted in the TraDIS mutant library, and which are potentially important for colonization (i.e. they had at least one significantly attenuated mutant) in each of the three reservoir hosts.
Competitive indices of defined null mutants of S. Typhimurium lacking candidate virulence-associated loci identified by TraDIS.
| Mutation | Mean CI Day 4 | Mean CI Day 6 | Mean CI Day 10 | Chicken TraDIS |
|
| 0.187 (0.0004) | 0.171 (0.0016) | 0.002 (<0.0001) | −5.43 to −15 (5/5) |
|
| 0.047 (<0.0001) | 0.001 (<0.0001) | −2.36 to −8.11 (4/4) | |
|
| 0.294 (0.0026) | 0.310 (0.0309) | 0.104 (0.0001) | −2.05 to −3.38 (1/2) |
|
| 0.957 (0.9014) | 0.469 (0.0159) | 0.820 (0.2802) | −15 (1/1) |
|
| 0.761 (0.2741) | 0.613 (0.2588) | 0.804 (0.1625) | −3.08 to −15 (4/4) |
| SL1344_0084 | 0.727 (0.0959) | 1.062 (0.7933) | 0.430 (0.0008) | −0.82 to −9.11 (6/7) |
| SL1344_4248 | 0.487 (0.0015) | 1.152 (0.7458) | 1.020 (0.8951) | −3.51 to −5.07 (4/4) |
| SL1344_3128 | 1.267 (0.3367) | 1.001 (0.9963) | 1.204 (0.7051) | −1.02 to −9.20 (7/9) |
|
| 0.003 (<0.0001) | 0.013 (<0.0001) | −3.58 to −8.21 (4/4) | |
|
| 0.347 (0.0024) | 0.638 (0.1336) | 0.416 (0.0038) | −1.48 to −7.05 (3/4) |
|
| 0.184 (<0.0001) | 0.175 (<0.0001) | 0.033 (<0.0001) | 0.44 to −4.38 (2/6) |
|
| 0.592 (0.0015) | 0.581 (0.7458) | 0.522 (0.8951) | −15 (1/1) |
P values are shown in parentheses. The range of TraDIS fitness scores obtained in the chicken experiment is also shown for each gene, with the fraction of significantly attenuated mutants shown in parentheses.