High Throughput Method for Analysis of Repeat Number for 28 Phase Variable Loci of Campylobacter jejuni Strain NCTC11168

Lango-Scholey, Lea; Aidley, Jack; Woodacre, Alexandra; Jones, Michael A.; Bayliss, Christopher D.

doi:10.1371/journal.pone.0159634

Cited by 20 publications

(30 citation statements)

References 21 publications

(29 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Individual colonies were picked from the inoculum (60 colonies) and the final population (30 colonies) after five successive bottlenecks. The repeat numbers, expression states, and phasotypes for 28 phase-variable loci of these colonies were determined with the 28-locus PV assay (29). …”

Section: Methodsmentioning

confidence: 99%

Nonselective Bottlenecks Control the Divergence and Diversification of Phase-Variable Bacterial Populations

Aidley

Rajopadhye

Akinyemi

et al. 2017

mBio

Self Cite

View full text Add to dashboard Cite

Phase variation occurs in many pathogenic and commensal bacteria and is a major generator of genetic variability. A putative advantage of phase variation is to counter reductions in variability imposed by nonselective bottlenecks during transmission. Genomes of Campylobacter jejuni, a widespread food-borne pathogen, contain multiple phase-variable loci whose rapid, stochastic variation is generated by hypermutable simple sequence repeat tracts. These loci can occupy a vast number of combinatorial expression states (phasotypes) enabling populations to rapidly access phenotypic diversity. The imposition of nonselective bottlenecks can perturb the relative frequencies of phasotypes, changing both within-population diversity and divergence from the initial population. Using both in vitro testing of C. jejuni populations and a simple stochastic simulation of phasotype change, we observed that single-cell bottlenecks produce output populations of low diversity but with bimodal patterns of either high or low divergence. Conversely, large bottlenecks allow divergence only by accumulation of diversity, while interpolation between these extremes is observed in intermediary bottlenecks. These patterns are sensitive to the genetic diversity of initial populations but stable over a range of mutation rates and number of loci. The qualitative similarities of experimental and in silico modeling indicate that the observed patterns are robust and applicable to other systems where localized hypermutation is a defining feature. We conclude that while phase variation will maintain bacterial population diversity in the face of intermediate bottlenecks, narrow transmission-associated bottlenecks could produce host-to-host variation in bacterial phenotypes and hence stochastic variation in colonization and disease outcomes.

show abstract

Section: Methodsmentioning

confidence: 99%

Nonselective Bottlenecks Control the Divergence and Diversification of Phase-Variable Bacterial Populations

Aidley

Rajopadhye

Akinyemi

et al. 2017

mBio

Self Cite

View full text Add to dashboard Cite

show abstract

“…Furthermore, linking genotype with phenotype in this organism, especially in the context of flagellar biogenesis and modification, is complicated by the presence of phase-variable polynucleotide tracts in genes encoding glycosylation enzymes. This leads to frequent on/off switching of genes (∼1/1,000 generations) due to slipped-strand mispairing during DNA replication (Lango-Scholey et al, 2016). For example, C. jejuni 11168, the first genome-sequenced strain of the species, harbors poly-deoxyguanosine (poly-G) tracts in at least 28 of its genes (Parkhill et al, 2000;Lango-Scholey et al, 2016), 10 of which are found within its ∼50-gene flagellar glycosylation locus (Hitchen et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

“…This leads to frequent on/off switching of genes (∼1/1,000 generations) due to slipped-strand mispairing during DNA replication (Lango-Scholey et al, 2016). For example, C. jejuni 11168, the first genome-sequenced strain of the species, harbors poly-deoxyguanosine (poly-G) tracts in at least 28 of its genes (Parkhill et al, 2000;Lango-Scholey et al, 2016), 10 of which are found within its ∼50-gene flagellar glycosylation locus (Hitchen et al, 2010). Given these challenges, much of the diversity in Campylobacter flagellar glycans, as well as the mechanisms that drive this diversity, remain unknown.…”

Section: Introductionmentioning

confidence: 99%

Binding of Phage-Encoded FlaGrab to Motile Campylobacter jejuni Flagella Inhibits Growth, Downregulates Energy Metabolism, and Requires Specific Flagellar Glycans

et al. 2020

View full text Add to dashboard Cite

Many bacterial pathogens display glycosylated surface structures that contribute to virulence, and targeting these structures is a viable strategy for pathogen control. The foodborne pathogen Campylobacter jejuni expresses a vast diversity of flagellar glycans, and flagellar glycosylation is essential for its virulence. Little is known about why C. jejuni encodes such a diverse set of flagellar glycans, but it has been hypothesized that evolutionary pressure from bacteriophages (phages) may have contributed to this diversity. However, interactions between Campylobacter phages and host flagellar glycans have not been characterized in detail. Previously, we observed that Gp047 (now renamed FlaGrab), a conserved Campylobacter phage protein, binds to C. jejuni flagella displaying the nine-carbon monosaccharide 7-acetamidino-pseudaminic acid, and that this binding partially inhibits cell growth. However, the mechanism of this growth inhibition, as well as how C. jejuni might resist this activity, are not well-understood. Here we use RNA-Seq to show that FlaGrab exposure leads C. jejuni 11168 cells to downregulate expression of energy metabolism genes, and that FlaGrab-induced growth inhibition is dependent on motile flagella. Our results are consistent with a model whereby FlaGrab binding transmits a signal through flagella that leads to retarded cell growth. To evaluate mechanisms of FlaGrab resistance in C. jejuni, we characterized the flagellar glycans and flagellar glycosylation loci of two C. jejuni strains naturally resistant to FlaGrab binding. Our results point toward flagellar glycan diversity as the mechanism of resistance to FlaGrab. Overall, we have further characterized the interaction between this phage-encoded flagellar glycan-binding protein and C. jejuni, both in terms of mechanism of action and mechanism of resistance. Our results suggest that C. jejuni encodes as-yet unidentified mechanisms for generating flagellar glycan diversity, and point to phage proteins as exciting lenses through which to study bacterial surface glycans.

show abstract

“…Hence, by measuring repeat lengths at multiple loci (Lango‐Scholey et al. ) across strains and over time, with sufficient statistical power it may become possible to draw key inferences about the natural evolutionary dynamics of stochastic switches.…”

Section: Discussionmentioning

confidence: 99%

The impact of bottlenecks on microbial survival, adaptation, and phenotypic switching in host-pathogen interactions

Moxon

Kussell

2017

Evolution

View full text Add to dashboard Cite

Microbial pathogens and viruses can often maintain sufficient population diversity to evade a wide range of host immune responses. However, when populations experience bottlenecks, as occurs frequently during initiation of new infections, pathogens require specialized mechanisms to regenerate diversity. We address the evolution of such mechanisms, known as stochastic phenotype switches, which are prevalent in pathogenic bacteria. We analyze a model of pathogen diversification in a changing host environment that accounts for selective bottlenecks, wherein different phenotypes have distinct transmission probabilities between hosts. We show that under stringent bottlenecks, such that only one phenotype can initiate new infections, there exists a threshold stochastic switching rate below which all pathogen lineages go extinct, and above which survival is a near certainty. We determine how quickly stochastic switching rates can evolve by computing a fitness landscape for the evolutionary dynamics of switching rates, and analyzing its dependence on both the stringency of bottlenecks and the duration of within-host growth periods. We show that increasing the stringency of bottlenecks or decreasing the period of growth results in faster adaptation of switching rates. Our model provides strong theoretical evidence that bottlenecks play a critical role in accelerating the evolutionary dynamics of pathogens.

show abstract

High Throughput Method for Analysis of Repeat Number for 28 Phase Variable Loci of Campylobacter jejuni Strain NCTC11168

Cited by 20 publications

References 21 publications

Nonselective Bottlenecks Control the Divergence and Diversification of Phase-Variable Bacterial Populations

Nonselective Bottlenecks Control the Divergence and Diversification of Phase-Variable Bacterial Populations

Binding of Phage-Encoded FlaGrab to Motile Campylobacter jejuni Flagella Inhibits Growth, Downregulates Energy Metabolism, and Requires Specific Flagellar Glycans

The impact of bottlenecks on microbial survival, adaptation, and phenotypic switching in host-pathogen interactions

Contact Info

Product

Resources

About