bLactococcin 972 (Lcn972) is a cell wall-active bacteriocin that inhibits cell wall biosynthesis in Lactococcus lactis. In this work, the transcriptomes of the Lcn972-resistant (Lcn r ) mutant L. lactis D1 and its parent strain were compared to identify factors involved in Lcn972 resistance. Upregulated genes included members of the cell envelope stress (CesSR) regulon, the penicillinbinding protein pbpX gene and gene llmg2447, which may encode a putative extracytoplasmic function (ECF) anti-sigma factor. The gene llmg2447 is located downstream of the nonfunctional ECF gene sigX pseudo . Nisin-controlled expression of llmg2447 led to high Lcn972 resistance in L. lactis, with no cross-resistance to other cell wall-active antimicrobials. Upregulation of llmg2447 in L. lactis D1 (Lcn r ) was linked to the integration of insertion element IS981 into the llmg2447 promoter region, replacing the native ؊35 box and activating the otherwise silent promoter P 2447 . This is the first example of an orphan ECF anti-sigma factor involved in bacteriocin resistance. This new role in neutralizing cell wall-active compounds (e.g., Lcn972) could have evolved from a putative primary function of Llmg2447 in sensing cell envelope stress.

RATIONALE: Patients can be allergic to multiple substances due to IgEmediated recognition of similar epitopes on proteins from different sources. We applied cluster-detection techniques to food-allergic patient data to detect groups of cross-reactive allergens. Such groupings will be useful for patient-classification, diagnosis, treatment and discovery. METHODS: Skin prick test (SPT) results were obtained for confirmed food-allergic patients, for allergens common to Mediterranean areas. Patients/allergens with much missing data were excluded. Cluster analysis was performed using R/Cytoscape. Similarity was calculated using binary distance metrics. Patient self-reporting data was also obtained. RESULTS: Following exclusion, 525 participants and 45 agents were analysed. The allergens giving rise to the most positive SPT results were olive pollen, peach, tree-nuts/peanuts, grasses and house-dust mites. Cluster analysis found that similar allergen-sources tended to group together, including fruits, mites, nuts, dander, trees, weeds and grasses. Comparison with self-reported previous reactions showed high overlap, albeit with notable exceptions including lentils and sesame seeds. The choice of distance metric and clustering method influenced cluster-building. CONCLUSIONS: SPT analysis reveals patterns of co-reactivity between allergens. This information can aid diagnosis and suggest which allergensources to avoid. It can also guide studies of panallergens and epitope mapping. However, the choice of metric to calculate similarity is important: given the predominance of negative data, assymetric metrics are advised. Future work will investigate other geographical areas and patient IgE levels.

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