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177 results for “Campylobacter”
Trial Of Azithromycin In Campylobacter Concisus Patients With Diarrhea
ClinicalTrials.gov study NCT01531218. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Campylobacter Jejuni Challenge Model Development: Assessment of Homologous Protection
ClinicalTrials.gov study NCT01048112. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Campylobacter Enteritis and Post-Infective Bowel Dysfunction (PI-BD): Role of Antibiotics and Microbiota
ClinicalTrials.gov study NCT02040922. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Campylobacter jejuni infection associated with relatively poor condition and low survival in a wild bird
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Data from: Marked host specificity and lack of phylogeographic population structure of Campylobacter jejuni in wild birds
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Contrasting patterns of Campylobacter and Salmonella distribution in wild birds: a comparative analysis
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Data analysis scripts for the publication - Differences in the transcriptomic response of Campylobacter coli and Campylobacter lari to heat stress (Riedel et al.)
<p>Data analysis scripts and data for the publication "Differences in the transcriptomic response of Campylobacter coli and Campylobacter lari to heat stress" by Riedel <em>et al.</em>.</p>
Data from: Cytokine responses in birds challenged with the human food-borne pathogen Campylobacter jejuni implies a Th17 response
Development of process orientated understanding of cytokine interactions within the gastrointestinal tract during an immune response to pathogens requires experimentation and statistical modelling. The immune response against pathogen challenge depends on the specific threat to the host. Here, we show that broiler chickens mount a breed-dependent immune response to Campylobacter jejuni infection in the caeca by analysing experimental data using frequentist and Bayesian structural equation models (SEM). SEM provides a framework by which cytokine interdependencies, based on prior knowledge, can be tested. In both breeds important cytokines including pro-inflammatory interleukin (IL)-1β, , IL-4, IL-17A, interferon (IFN)-γ and anti-inflammatory IL-10 and transforming growth factor (TGF)-β4 were expressed post-challenge. The SEM revealed a putative regulatory pathway illustrating a T helper (Th)17 response and regulation of IL-10, which is breed-dependent. The prominence of the Th17 pathway indicates the cytokine response aims to limit the invasion or colonization of an extracellular bacterial pathogen but the time-dependent nature of the response differs between breeds.
Data from: High throughput method for analysis of repeat number for 28 phase variable loci of Campylobacter jejuni strain NCTC11168
Mutations in simple sequence repeat tracts are a major mechanism of phase variation in several bacterial species including Campylobacter jejuni. Changes in repeat number of tracts located within the reading frame can produce a high frequency of reversible switches in gene expression between ON and OFF states. The genome of C. jejuni strain NCTC11168 contains 29 loci with polyG/polyC tracts of seven or more repeats. This protocol outlines a method—the 28-locus-CJ11168 PV-analysis assay—for rapidly determining ON/OFF states of 28 of these phase-variable loci in a large number of individual colonies from C. jejuni strain NCTC11168. The method combines a series of multiplex PCR assays with a fragment analysis assay and automated extraction of fragment length, repeat number and expression state. This high throughput, multiplex assay has utility for detecting shifts in phase variation states within and between populations over time and for exploring the effects of phase variation on adaptation to differing selective pressures. Application of this method to analysis of the 28 polyG/polyC tracts in 90 C. jejuni colonies detected a 2.5-fold increase in slippage products as tracts lengthened from G8 to G11 but no difference between tracts of similar length indicating that flanking sequence does not influence slippage rates. Comparison of this observed slippage to previously measured mutation rates for G8 and G11 tracts in C. jejuni indicates that PCR amplification of a DNA sample will over-estimate phase variation frequencies by 20-35-fold. An important output of the 28-locus-CJ11168 PV-analysis assay is combinatorial expression states that cannot be determined by other methods. This method can be adapted to analysis of phase variation in other C. jejuni strains and in a diverse range of bacterial species.
Data from: Genome-wide association study identifies vitamin B5 biosynthesis as a host specificity factor in Campylobacter
Genome-wide association studies have the potential to identify causal genetic factors underlying important phenotypes but have rarely been performed in bacteria. We present an association mapping method that takes into account the clonal population structure of bacteria and is applicable to both core and accessory genome variation. Campylobacter is a common cause of human gastroenteritis as a consequence of its proliferation in multiple farm animal species and its transmission via contaminated meat and poultry. We applied our association mapping method to identify the factors responsible for adaptation to cattle and chickens among 192 Campylobacter isolates from these and other host sources. Phylogenetic analysis implied frequent host switching but also showed that some lineages were strongly associated with particular hosts. A seven-gene region with a host association signal was found. Genes in this region were almost universally present in cattle but were frequently absent in isolates from chickens and wild birds. Three of the seven genes encoded vitamin B5 biosynthesis. We found that isolates from cattle were better able to grow in vitamin B5-depleted media and propose that this difference may be an adaptation to host diet.
Data from: Cryptic ecology among host generalist Campylobacter jejuni in domestic animals
Homologous recombination between bacterial strains is theoretically capable of preventing the separation of daughter clusters, and producing cohesive clouds of genotypes in sequence space. However, numerous barriers to recombination are known. Barriers may be essential such as adaptive incompatibility, or ecological, which is associated with the opportunities for recombination in the natural habitat. Campylobacter jejuni is a gut colonizer of numerous animal species and a major human enteric pathogen. We demonstrate that the two major generalist lineages of C. jejuni do not show evidence of recombination with each other in nature, despite having a high degree of host niche overlap and recombining extensively with specialist lineages. However, transformation experiments show that the generalist lineages readily recombine with one another in vitro. This suggests ecological rather than essential barriers to recombination, caused by a cryptic niche structure within the hosts.
Data from: Rapid host switching in generalist Campylobacter strains erodes the signal for tracing human infections
Campylobacter jejuni and Campylobacter coli are the biggest causes of bacterial gastroenteritis in the developed world, with human infections typically arising from zoonotic transmission associated with infected meat. Because Campylobacter is not thought to survive well outside the gut, host-associated populations are genetically isolated to varying degrees. Therefore, the likely origin of most strains can be determined by host-associated variation in the genome. This is instructive for characterizing the source of human infection. However, some common strains, notably isolates belonging to the ST-21, ST-45 and ST-828 clonal complexes, appear to have broad host ranges, hindering source attribution. Here whole-genome sequencing has the potential to reveal fine-scale genetic structure associated with host specificity. We found that rates of zoonotic transmission among animal host species in these clonal complexes were so high that the signal of host association is all but obliterated, estimating one zoonotic transmission event every 1.6, 1.8 and 12 years in the ST-21, ST-45 and ST828 complexes, respectively. We attributed 89% of clinical cases to a chicken source, 10% to cattle and 1% to pig. Our results reveal that common strains of C. jejuni and C. coli infectious to humans are adapted to a generalist lifestyle, permitting rapid transmission between different hosts. Furthermore, they show that the weak signal of host association within these complexes presents a challenge for pinpointing the source of clinical infections, underlining the view that whole-genome sequencing, powerful though it is, cannot substitute for intensive sampling of suspected transmission reservoirs.
Data from: Structure of FlgK reveals the divergence of the bacterial hook-filament junction of Campylobacter
Evolution of a nano-machine consisting of multiple parts, each with a specific function, is a complex process. A change in one part should eventually result in changes in other parts, if the overall function is to be conserved. In bacterial flagella, the filament and the hook have distinct functions and their respective proteins, FliC and FlgE, have different three-dimensional structures. The filament functions as a helical propeller and the hook as a flexible universal joint. Two proteins, FlgK and FlgL, assure a smooth connectivity between the hook and the filament. Here we show that, in Campylobacter, the 3D structure of FlgK differs from that of its orthologs in Salmonella and Burkholderia, whose structures have previously been solved. Docking the model of the FlgK junction onto the structure of the Campylobacter hook provides some clues about its divergence. These data suggest how evolutionary pressure to adapt to structural constraints, due to the structure of Campylobacter hook, causes divergence of one element of a supra-molecular complex in order to maintain the function of the entire flagellar assembly.
Data from: Monitoring chicken flock behaviour provides early warning of infection by human pathogen Campylobacter
Campylobacter is the commonest bacterial cause of gastrointestinal infection in humans and chicken meat is the major source of infection throughout the world. Strict and expensive on-farm biosecurity measures have been largely unsuccessful in controlling infection and are hampered by the time needed to analyze faecal samples with the result that Campylobacter status is often known only after a flock has been processed. Our data demonstrate an alternative approach that monitors the behaviour of live chickens with cameras and analyses the 'optical flow' patterns made by flock movements. Campylobacter-free chicken flocks have higher mean and lower kurtosis of optical flow than those testing positive for Campylobacter by microbiological methods. We show that by monitoring behaviour in this way, flocks likely to become positive can be identified within the first 7-10 days of life, much earlier than conventional on-farm microbiological methods. This early warning has the potential to lead to a more targeted approach to Campylobacter control and also provides new insights into possible sources of infection that could transform the control of this globally important foodborne pathogen.
Figure 4 from: Sundermann EM, Nauta M, Swart A (2021) A ready-to-use dose-response model of Campylobacter jejuni implemented in the FSKX-standard. Food Modelling Journal 2: e63309. https://doi.org/10.3897/fmj.2.63309
Figure 4 The probability of illness and infection for the human population after consumption of Campylobacter jejuni-contaminated food. The probabilities are calculated based on the outbreak dataset with 1000 various mean doses (the so-called OutbreakVarMeanDoses simulation).
Figure 2 from: Sundermann EM, Nauta M, Swart A (2021) A ready-to-use dose-response model of Campylobacter jejuni implemented in the FSKX-standard. Food Modelling Journal 2: e63309. https://doi.org/10.3897/fmj.2.63309
Figure 2 The probability of illness and infection for the human population after consumption of a mean dose of 1 CFU of Campylobacter jejuni-contaminated food. The probabilities are calculated based on the outbreak dataset (the so-called outbreak simulation).
Figure 3 from: Sundermann EM, Nauta M, Swart A (2021) A ready-to-use dose-response model of Campylobacter jejuni implemented in the FSKX-standard. Food Modelling Journal 2: e63309. https://doi.org/10.3897/fmj.2.63309
Figure 3 The probability of illness and infection for the human population after consumption of Campylobacter jejuni-contaminated food. The probabilities are calculated based on the challenge studies dataset with 1000 various mean doses (the so-called ChallengeVarMeanDoses simulation).
Supplementary material 1 from: Sundermann EM, Nauta M, Swart A (2021) A ready-to-use dose-response model of Campylobacter jejuni implemented in the FSKX-standard. Food Modelling Journal 2: e63309. https://doi.org/10.3897/fmj.2.63309
CampylobacterDRM.fskx
Figure 1 from: Sundermann EM, Nauta M, Swart A (2021) A ready-to-use dose-response model of Campylobacter jejuni implemented in the FSKX-standard. Food Modelling Journal 2: e63309. https://doi.org/10.3897/fmj.2.63309
Figure 1 The probability of illness and infection for the human population after consumption of a mean dose of 1 CFU of Campylobacter jejuni contaminated food. The probabilities are calculated based on the challenge studies dataset (the so-called default simulation).
Nucleotide and protein database of Campylobacter virulence-associated genes
<p>Nucleotide and protein databases of 334 <em>Campylobacter</em> virulence-associated genes. The .XLSX file contains detailed information on these genes. It includes data on the strain from which each sequence was derived, as well as the corresponding locus tag, gene and protein lengths, and the classification of each gene by virulence factor category. Additionally, genes exhibiting phase-variation are also indicated. For these genes, the functional version (ON) of the protein is included.</p> <p>The combined use of the two databases for gene searching using BLASTn and tBLASTn for the nucleotide and protein databases, respectively, allows the identification of those genes present that might not be functional, especially those affected by phase-variation.</p>
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Allen Brain Atlas
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