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ABSTRACT: In this study, differences at the genetic level of 37 Salmonella Enteritidis strains from five phage types (PTs) were compared using comparative genomic hybridization (CGH) to assess differences between PTs. There were approximately 400 genes that differentiated prevalent (4, 6, 8 and 13a) and sporadic (11) PTs, of which 35 were unique to prevalent PTs, including six plasmid-borne genes, pefA, B, C, D, srgC and rck, and four chromosomal genes encoding putative amino acid transporters. Phenotype array studies also demonstrated that strains from prevalent PTs were less susceptible to urea stress and utilized l-histidine, l-glutamine, l-proline, l-aspartic acid, gly-asn and gly-gln more efficiently than PT11 strains. Complementation of a PT11 strain with the transporter genes from PT4 resulted in a significant increase in utilization of the amino acids and reduced susceptibility to urea stress. In epithelial cell association assays, PT11 strains were less invasive than other prevalent PTs. Most strains from prevalent PTs were better biofilm formers at 37 degrees C than at 28 degrees C, whilst the converse was true for PT11 strains. Collectively, the results indicate that genetic and corresponding phenotypic differences exist between strains of the prevalent PTs 4, 6, 8 and 13a and non-prevalent PT11 strains that are likely to provide a selective advantage for strains from the former PTs and could help them to enter the food chain and cause salmonellosis.
Microbiology 08/2009; 155(Pt 10):3200-13. · 3.06 Impact Factor
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Laura E J Searle,
Angus Best,
Alejandro Nunez,
Francisco J Salguero,
Linda Johnson,
Ute Weyer,
Alexandra H Dugdale,
William A Cooley, Ben Carter,
Gareth Jones,
George Tzortzis,
Martin J Woodward,
Roberto M La Ragione
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ABSTRACT: The prebiotic Bimuno is a mixture containing galactooligosaccharide, produced by the galactosyltransferase activity of Bifidobacterium bifidum NCIMB 41171 in the presence of lactose. Previous studies have implicated prebiotics in reducing infections by enteric pathogens, thus it was hypothesized that Bimuno may confer some protection in the murine host from Salmonella enterica serovar Typhimurium (S. Typhimurium) infection. In this study, infection caused by S. Typhimurium SL1344nal(r) in the presence or absence of Bimuno was assessed using tissue culture assays, a murine ligated ileal gut loop model and a murine oral challenge model. In tissue culture adherence and invasion assays with HT-29-16E cells, the presence of approximately 2 mM Bimuno significantly reduced the invasion of S. Typhimurium SL1344nal(r) (P<0.0001). In the murine ligated ileal gut loops, the presence of Bimuno prevented colonization and the associated pathology of S. Typhimurium. In the BALB/c mouse model, the oral delivery of Bimuno prior to challenge with S. Typhimurium resulted in significant reductions in colonization in the five organs sampled, with highly significant reductions being observed in the spleen at 72 and 96 h post-challenge (P=0.0002, <0.0001, respectively). Collectively, the results indicate that Bimuno significantly reduced the colonization and pathology associated with S. Typhimurium infection in a murine model system, possibly by reducing the invasion of the pathogen into host cells.
Journal of Medical Microbiology 01/2009; 58(Pt 1):37-48. · 2.50 Impact Factor
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ABSTRACT: In cattle, the lymphoid rich regions of the rectal-anal mucosa at the terminal rectum are the preferred site for Escherichia coli O157:H7 colonisation. All cattle infected by rectal swab administration demonstrate long-term E. coli O157:H7 colonisation, whereas orally challenged cattle do not demonstrate long-term E. coli O157:H7 colonisation in all animals. Oral, but not rectal challenge of sheep with E. coli O157:H7 has been reported, but an exact site for colonisation in sheep is unknown. To determine if E. coli O157:H7 can effectively colonise the ovine terminal rectum, in vitro organ culture (IVOC) was initiated. Albeit sparsely, large, densely packed E. coli O157:H7 micro-colonies were observed on the mucosa of ovine and control bovine terminal rectum explants. After necropsy of orally inoculated lambs, bacterial enumeration of the proximal and distal gastrointestinal tract did suggest a preference for E. coli O157:H7 colonisation at the ovine terminal rectum, albeit for both lymphoid rich and non-lymphoid sites. As reported for cattle, rectal inoculation studies were then conducted to determine if all lambs would demonstrate persistent colonisation at the terminal rectum. After necropsy of E. coli O157:H7 rectally inoculated lambs, most animals were not colonised at gastrointestinal sites proximal to the rectum, however, large densely packed micro-colonies of E. coli O157:H7 were observed on the ovine terminal rectum mucosa. Nevertheless, at the end point of the study (day 14), only one lamb had E. coli O157:H7 micro-colonies associated with the terminal rectum mucosa. A comparison of E. coli O157:H7 shedding yielded a similar pattern of persistence between rectally and orally inoculated lambs. The inability of E. coli O157:H7 to effectively colonise the terminal rectum mucosa of all rectally inoculated sheep in the long term, suggests that E. coli O157:H7 may colonise this site, but less effectively than reported previously for cattle.
Veterinary Research 11/2008; 40(1):9. · 4.06 Impact Factor
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ABSTRACT: An Escherichia coli oligonucleotide microarray based on three sequenced genomes was validated for comparative genomic microarray hybridization and used to study the diversity of E. coli O157 isolates from human infections and food and animal sources. Among 26 test strains, 24 (including both Shiga toxin [Stx]-positive and -negative strains) were found to be related to the two sequenced E. coli O157:H7 strains, EDL933 and Sakai. However, these strains showed much greater genetic diversity than those reported previously, and most of them could not be categorized as either lineage I or II. Some genes were found more often in isolates from human than from nonhuman sources; e.g., ECs1202 and ECs2976, associated with stx2AB and stx1AB, were in all isolates from human sources but in only 40% of those from nonhuman sources. Some (but not all) lineage I-specific or -dominant genes were also more frequently associated with isolates from human. The results suggested that it might be more effective to concentrate our efforts on finding markers that are directly related to infection rather than those specific to certain lineages. In addition, two Stx-negative O157 cattle isolates (one confirmed to be H7) were significantly different from other Stx-positive and -negative E. coli O157:H7 strains and were more similar to MG1655 in their gene content. This work demonstrates that not all E. coli O157:H7 strains belong to the same clonal group, and those that were similar to E. coli K-12 might be less virulent.
Infection and immunity 03/2008; 76(2):845-56. · 4.21 Impact Factor
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ABSTRACT: Microarray based comparative genomic hybridisation (CGH) experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity.
The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data.
After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.
BMC Genomics 02/2008; 9:53. · 4.07 Impact Factor
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ABSTRACT: Abstract
Background
Microarray based comparative genomic hybridisation (CGH) experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity.
Results
The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data.
Conclusion
After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.
BMC Genomics. 01/2008;
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ABSTRACT: The influence of geographical origin, host animal and presence of the stx gene on the virulence of Escherichia coli O26 strains from ruminants was determined in this study. A clear association was found between the virulence profile and geographical origin of Shiga-toxigenic E. coli (STEC) O26 strains, with UK STEC O26 strains harbouring virtually identical profiles, whilst central European strains showed considerable heterogeneity in plasmid-encoded genes. The former group were also more likely to be non-motile and katP gene positive. Comparison of UK STEC and atypical enteropathogenic E. coli (aEPEC) O26 strains showed that the presence of the stx1 gene was positively correlated with the presence of espP and katP genes and negatively associated with the presence of the yagP-yagT region and with rhamnose fermentation. In contrast to the uniform profiles of STEC O26 strains from ruminants in the UK, aEPEC O26 strains of bovine and ovine origin showed diverse profiles both within and between groups, and could not be separated into discrete groups. These results indicate that the characteristics of UK O26 strains from ruminants are distinct from those of O26 strains from ruminants and humans in other regions in central Europe. Such differences are expected to influence the zoonotic potential of this pathogen and the subsequent incidence of O26-associated human disease.
Journal of Medical Microbiology 12/2007; 56(Pt 11):1431-9. · 2.50 Impact Factor
