Influence of iron on bacterial infections in leukaemia

The influence of iron metabolism, both on the invading bacterial pathogen and in the host is widespread and often appears to be crucial in determining the outcome of an infection. This study involved the investigation of leukaemia, a clinical disease where abnormal availability of iron may play a part in predisposing patients to bacterial infection. The iron status throughout a Gram-negative septicaemia and in 20 random, newly diagnosed leukaemic patients was assessed. The results revealed that the majority of the patients exhibited high serum iron levels and serum transferrin saturation often at 100%, with an inability to reduce the latter to within normal values during an infection episode. The antibody response to P.aeruginosa, E.coli and K.pneumoniae outer membrane protein (OMP) antigens were investigated by immunoblotting with sequential serum samples during infection in the leukaemic host. Antibodies to all the major OMPs, were observed, although recognition of iron-regulated membrane proteins (IRMPs) was in many cases weak. Results from the enzyme-linked immunosorbent assay indicated that in all patients antibody titre in response to infection was poor. Sub-MICs of mitomycin C significantly altered the surface characteristics of P.aeruginosa. The silver-stained SDS-PAGE gels of proteinase K digested whole cell lysates of strains PAO1, 6750, M7 and PAJ indicated that core LPS was affected in the presence of mitomycin C. In contrast, the rough strain AK1012 showed no observable differences. Results obtained using quantitative gas-liquid chromatographic analysis showed the amount of LPS fatty acids to be unaffected, however, the KDO and carbohydrate content in strains PAO1, 6750 and M7 under Fe+ and Fe- growth conditions were decreased by up to 4-fold in the presence of mitomycin C, indicating perturbed expression of LPS. The cell surface became significantly more hydrophobic in the P.aeruginosa strains, except AK1012 which was comparatively unaffected. The induction of protein G (OprG) in P.aeruginosa was found to be a sensitive indicator of media iron. The data indicated that expression of OprG can be modulated by growth rate/phase, availability of iron and by the presence of ciprofloxacin in the growth medium.

Spirochaetes and other bacterial species associated with bovine digital dermatitis

The 16S rRNA genes from spirochaetes associated with digital dermatitis of British cattle were amplified by polymerase chain reaction from digital dermatitis lesion biopsies using one universal and one treponeme-specific primer. Two treponemal sequences were identified both of which shared a high degree of homology with the oral pathogen Treponema denticola (98%). Two further 16S rRNA gene sequences were obtained and shared similarity to Bacteroides levii (99%) and Mycoplasma hyopharyngis (98%). Polymerase chain reaction with T. denticola-specific primers amplified a potential virulence gene from digital dermatitis lesions which shared a high degree of homology to the 46-kDa haemolysin gene of T. denticola. The significance of the presence of organisms in digital dermatitis lesions of the bovine foot which are closely related to oral pathogens is discussed.

Discriminating antigen and non-antigen using proteome dissimilarity:bacterial antigens

It has been postulated that immunogenicity results from the overall dissimilarity of pathogenic proteins versus the host proteome. We have sought to use this concept to discriminate between antigens and non-antigens of bacterial origin. Sets of 100 known antigenic and nonantigenic peptide sequences from bacteria were compared to human and mouse proteomes. Both antigenic and non-antigenic sequences lacked human or mouse homologues. Observed distributions were compared using the non-parametric Mann-Whitney test. The statistical null hypothesis was accepted, indicating that antigen and non-antigens did not differ significantly. Likewise, we were unable to determine a threshold able to separate meaningfully antigen from non-antigen. Thus, antigens cannot be predicted from pathogen genomes based solely on their dissimilarity to the human genome.