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.

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.

Discriminating antigen and non-antigen using proteome dissimilarity III:tumour and parasite antigens

Computational genome analysis enables systematic identification of potential immunogenic proteins within a pathogen. Immunogenicity is a system property that arises through the interaction of host and pathogen as mediated through the medium of a immunogenic protein. The overt dissimilarity of pathogenic proteins when compared to the host proteome is conjectured by some to be the determining principal of immunogenicity. Previously, we explored this idea in the context of Bacterial, Viral, and Fungal antigen. In this paper, we broaden and extend our analysis to include complex antigens of eukaryotic origin, arising from tumours and from parasite pathogens. For both types of antigen, known antigenic and non-antigenic protein sequences were compared to human and mouse proteomes. In contrast to our previous results, both visual inspection and statistical evaluation indicate a much wider range of homologues and a significant level of discrimination; but, as before, we could not determine a viable threshold capable of properly separating non-antigen from antigen. In concert with our previous work, we conclude that global proteome dissimilarity is not a useful metric for immunogenicity for presently available antigens arising from Bacteria, viruses, fungi, parasites, and tumours. While we see some signal for certain antigen types, using dissimilarity is not a useful approach to identifying antigenic molecules within pathogen genomes.

Discriminating antigen and non-antigen using proteome dissimilarity II:viral and fungal antigens

Immunogenicity arises via many synergistic mechanisms, yet the overall dissimilarity of pathogenic proteins versus the host proteome has been proposed as a key arbiter. We have previously explored this concept in relation to Bacterial antigens; here we extend our analysis to antigens of viral and fungal origin. Sets of known viral and fungal antigenic and non-antigenic protein sequences 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 could not determine a threshold able meaningfully to separate non-antigen from antigen. We conclude that viral and fungal antigens cannot be predicted from pathogen genomes based solely on their dissimilarity to mammalian genomes.

VaxiJen:a server for prediction of protective antigens, tumour antigens and subunit vaccines

Background - Vaccine development in the post-genomic era often begins with the in silico screening of genome information, with the most probable protective antigens being predicted rather than requiring causative microorganisms to be grown. Despite the obvious advantages of this approach – such as speed and cost efficiency – its success remains dependent on the accuracy of antigen prediction. Most approaches use sequence alignment to identify antigens. This is problematic for several reasons. Some proteins lack obvious sequence similarity, although they may share similar structures and biological properties. The antigenicity of a sequence may be encoded in a subtle and recondite manner not amendable to direct identification by sequence alignment. The discovery of truly novel antigens will be frustrated by their lack of similarity to antigens of known provenance. To overcome the limitations of alignment-dependent methods, we propose a new alignment-free approach for antigen prediction, which is based on auto cross covariance (ACC) transformation of protein sequences into uniform vectors of principal amino acid properties. Results - Bacterial, viral and tumour protein datasets were used to derive models for prediction of whole protein antigenicity. Every set consisted of 100 known antigens and 100 non-antigens. The derived models were tested by internal leave-one-out cross-validation and external validation using test sets. An additional five training sets for each class of antigens were used to test the stability of the discrimination between antigens and non-antigens. The models performed well in both validations showing prediction accuracy of 70% to 89%. The models were implemented in a server, which we call VaxiJen. Conclusion - VaxiJen is the first server for alignment-independent prediction of protective antigens. It was developed to allow antigen classification solely based on the physicochemical properties of proteins without recourse to sequence alignment. The server can be used on its own or in combination with alignment-based prediction methods.