Influence of iron deprivation and sub-inhibitory concentrations of antifungal antibiotics on surface antigens of candida albicans yeast cells

This study examined the effect of iron deprivation and sub-inhibitory concentrations of antifungal agents on yeast cell surface antigen recognition by antibodies from patients with Candida infections. Separation of cell wall surface proteins by sodium dodecyl-polyacrylamide gel electrophoresis (SDS-PAGE) and immunological detection by immunoblotting, revealed that antigenic profiles of yeasts were profoundly influenced by the growth environment. Cells grown under iron-depleted conditions expressed several iron-regulated proteins that were recognized by antibodies from patient sera. An attempt to characterize these proteins by lectin blotting with concanavalin A revealed that some could be glycoprotein in nature. Furthermore, these proteins which were located within cell walls and on yeast surfaces, were barely or not expressed in yeasts cultivated under iron-sufficient conditions. The magnitude and heterogeneity of human antibody responses to these iron-regulated proteins were dependent on the type of Candida infection, serum antibody class and yeast strain. Hydroxamate-type siderophores were also detected in supernatants of iron depleted yeast cultures. This evidence suggests that Candida albicans expresses iron-regulated proteins/glycoproteins in vitro which may play a role in siderophore-mediated iron uptake in Candida albicans. Sequential monitoring of IgG antibodies directed against yeast surface antigens during immunization of rabbits revealed that different antigens were recognized particularly during early and later stages of immunization in iron-depleted cells compared to iron-sufficient cells. In vitro and in vivo adherence studies demonstrated that growth phase, yeast strain and growth conditions affect adhesion mechanisms. In particular, growth under iron-depletion in the presence of sub-inhibitory concentrations of polyene and azole antifungals enhanced the hydrophobicity of C.albicans. Growth conditions also influenced MICs of antifungals, notably that of ketoconazole. Sub-inhibitory concentrations of amphotericin B and fluconazole had little effect on surface antigens, whereas nystatin induced profound changes in surface antigens of yeast cells. The effects of such drug concentrations on yeast cells coupled with host defence mechanisms may have a significant affect on the course of Candida infections.

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.

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.

A novel multilocus sequence typing scheme for the opportunistic pathogen Propionibacterium acnes and characterisation of type 1 cell surface-associated antigens

We have developed a novel multilocus sequence typing (MLST) scheme and database (http://pubmlst.org/pacnes/) for Propionibacterium acnes based on the analysis of seven core housekeeping genes. The scheme, which was validated against previously described antibody, single locus and random amplification of polymorphic DNA typing methods, displayed excellent resolution and differentiated 123 isolates into 37 sequence types (STs). An overall clonal population structure was detected with six eBURST groups representing the major clades I, II and III, along with two singletons. Two highly successful and global clonal lineages, ST6 (type IA) and ST10 (type IB1), representing 64?% of this current MLST isolate collection were identified. The ST6 clone and closely related single locus variants, which comprise a large clonal complex CC6, dominated isolates from patients with acne, and were also significantly associated with ophthalmic infections. Our data therefore support an association between acne and P. acnes strains from the type IA cluster and highlight the role of a widely disseminated clonal genotype in this condition. Characterization of type I cell surface-associated antigens that are not detected in ST10 or strains of type II and III identified two dermatan-sulphate-binding proteins with putative phase/antigenic variation signatures. We propose that the expression of these proteins by type IA organisms contributes to their role in the pathophysiology of acne and helps explain the recurrent nature of the disease. The MLST scheme and database described in this study should provide a valuable platform for future epidemiological and evolutionary studies of P. acnes.

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.

Chapter Six – The Increase of Exotic Zoonotic Helminth Infections: The Impact of Urbanization, Climate Change and Globalization

Zoonotic parasitic diseases are increasingly impacting human populations due to the effects of globalization, urbanization and climate change. Here we review the recent literature on the most important helminth zoonoses, including reports of incidence and prevalence. We discuss those helminth diseases which are increasing in endemic areas and consider their geographical spread into new regions within the framework of globalization, urbanization and climate change to determine the effect these variables are having on disease incidence, transmission and the associated challenges presented for public health initiatives, including control and elimination.