Enterohaemorrhagic Escherichia coli (EHEC) infections in humans are an important public health concern and are commonly acquired via contact with ruminant faeces. Cattle are a key control point however cross-protective vaccines for the control of EHEC in the bovine reservoir do not yet exist. The EHEC serogroups that are predominantly associated with human infection in Europe and North America are O157 and O26. Intimin and EHEC factor for adherence (Efa-1) play important roles in intestinal colonisation of cattle by EHEC and are thus attractive candidates for the development of subunit vaccines. Immunisation of calves with the cell-binding domain of intimin subtypes β or γ via the intramuscular route induced antigen-specific serum IgG1 and, in some cases salivary IgA responses, but did not reduce the magnitude or duration of faecal excretion of EHEC O26:H- (Int280-β) or EHEC O157:H7 (Int280-γ) upon subsequent experimental challenge. Similarly, immunisation of calves via the intramuscular route with the truncated Efa-1 protein (Efa-1′) from EHEC O157:H7 or a mixture of the amino-terminal and central thirds of the full-length protein (Efa-1-N and M) did not protect against intestinal colonisation by EHEC O157:H7 (Efa-1′) or EHEC O26:H- (Efa-1-N and M) despite the induction of humoral immunity. A portion of the serum IgG1 elicited by the truncated recombinant antigens in calves was confirmed to recognise native protein exposed on the bacterial surface. Calves immunised with a mixture of Int280-γ and Efa-1′ or an EHEC O157:H7 bacterin via the intramuscular route then boosted via the intranasal route with the same antigens using cholera toxin B subunit as an adjuvant were also not protected against intestinal colonisation by EHEC O157:H7. These studies highlight the need for further studies to develop and test novel vaccines or treatments for control of this important foodborne pathogen.

DNA microarrays offer the possibility of testing for the presence of thousands of micro-organisms in a single experiment. However, there is a lack of reliable bioinformatics tools for the analysis of such data. We have developed DetectiV, a package for the statistical software R. DetectiV offers powerful yet simple visualization, normalization and significance testing tools. We show that DetectiV performs better than previously published software on a large, publicly available dataset. RationaleOne of the key applications of metagenomics is the identification and quantification of species within a clinical or environmental sample. Microarrays are particularly attractive for the recognition of pathogens in clinical material since current diagnostic assays are typically restricted to the detection of single targets by real-time PCR or immunological assays. Furthermore, molecular characterization and phylogenetic analysis of these signatures can require downstream sequencing of genomic regions. Many microarrays have already been produced with the aim of characterizing the spectrum of microorganisms present in a sample, including detection of known viruses [1][2][3][4][5], assessment of bioterrorism [6,7] and monitoring food quality [8].However, the use of DNA microarrays for routine applications produces many challenges for bioinformatics. Firstly, probe selection is a difficult and time consuming process. There are a huge number of diverse species in nature, of which we have sequence information for only a tiny fraction. This makes it difficult to find oligonucleotides, either alone or in combination, that uniquely identify species of interest. Oligos may have homology to multiple species, which results in a complex and noisy hybridization pattern. Secondly, each nucleic acid sample tested will typically contain a mixture of DNA and RNA from the organism of interest, the host and from a variety of contaminants, which may all contribute to the resulting microarray profile. Furthermore, this may be complicated by the presence of multiple, possibly related, pathogen species, making it difficult to separate patterns due to cross-hybridization from a true positive result.Urisman et al. [9] have previously reported E-Predict, a computational strategy for species identification based on observed microarray hybridization patterns. E-Predict uses a matrix of theoretical hybridization energy profiles calculated by BLAST-ing completely sequenced viral genomes against the oligos on their array, and calculating a free energy of hybridization. Observed hybridization profiles are then compared to the theoretical profiles using a similarity metric, and a p value calculated using a set of experimentally obtained null probability distributions. E-Predict has been shown to

Enteropathogenic Escherichia coli contain a large chromosomal gene (lifA) that encodes lymphostatin, a predicted 365 kDa protein that inhibits the mitogen-activated proliferation of peripheral blood lymphocytes and lamina propria mononuclear cells and the synthesis of proinflammatory cytokines. Non-O157 serotypes of enterohaemorrhagic E. coli (EHEC) contain a highly homologous gene, designated efa1 (EHEC factor for adherence), which influences adherence to epithelial cells in vitro and intestinal colonization in calves. Serotype O157:H7 EHEC strains contain a truncated version of this gene (efa1') and a pO157-encoded homologue of lifA/efa1 (toxB). Here we report for the first time that efa1 inhibits mitogen-activated proliferation of bovine peripheral blood lymphocytes by EHEC O103:H2, but that E. coli K-12 strains expressing the N-terminal and central portions of the protein lack activity. While a Shiga toxin-negative E. coli O157:H7 strain was shown to possess lymphostatin-like activity, deletion of efa1' or toxB, singly or in combination, failed to significantly relieve the inhibitory effect.

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