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The Bayesian regularization method for high-throughput differential analysis, described in Baldi and Long (A Bayesian framework for the analysis of microarray expression data: regularized t-test and statistical inferences of gene changes. Bioinformatics 2001: 17: 509-519) and implemented in the Cyber-T web server, is one of the most widely validated. Cyber-T implements a t-test using a Bayesian framework to compute a regularized variance of the measurements associated with each probe under each condition. This regularized estimate is derived by flexibly combining the empirical measurements with a prior, or background, derived from pooling measurements associated with probes in the same neighborhood. This approach flexibly addresses problems associated with low replication levels and technology biases, not only for DNA microarrays, but also for other technologies, such as protein arrays, quantitative mass spectrometry and next-generation sequencing (RNA-seq). Here we present an update to the Cyber-T web server, incorporating several useful new additions and improvements. Several preprocessing data normalization options including logarithmic and (Variance Stabilizing Normalization) VSN transforms are included. To augment two-sample t-tests, a one-way analysis of variance is implemented. Several methods for multiple tests correction, including standard frequentist methods and a probabilistic mixture model treatment, are available. Diagnostic plots allow visual assessment of the results. The web server provides comprehensive documentation and example data sets. The Cyber-T web server, with R source code and data sets, is publicly available at http://cybert.ics.uci.edu/.

The development of an effective malaria vaccine remains a global public health priority. Less than 0.5% of the Plasmodium falciparum genome has been assessed as potential vaccine targets and candidate vaccines have been based almost exclusively on single antigens. It is possible that the failure to develop a malaria vaccine despite decades of effort might be attributed to this historic focus. To advance malaria vaccine development, we have fabricated protein microarrays representing 23% of the entire P. falciparum proteome and have probed these arrays with plasma from subjects with sterile protection or no protection after experimental immunization with radiation attenuated P. falciparum sporozoites. A panel of 19 pre-erythrocytic stage antigens was identified as strongly associated with sporozoite-induced protective immunity; 16 of these antigens were novel and 85% have been independently identified in sporozoite and/or liver stage proteomic or transcriptomic data sets. Reactivity to any individual antigen did not correlate with protection but there was a highly significant difference in the cumulative signal intensity between protected and not protected individuals. Functional annotation indicates that most of these signature proteins are involved in cell cycle/DNA processing and protein synthesis. In addition, 21 novel blood-stage specific antigens were identified. Our data provide the first evidence that sterile protective immunity against malaria is directed against a panel of novel P. falciparum antigens rather than one antigen in isolation. These results have important implications for vaccine development, suggesting that an efficacious malaria vaccine should be multivalent and targeted at a select panel of key antigens, many of which have not been previously characterized.

Chlamydia trachomatis infections can lead to severe chronic complications, including trachoma, ectopic pregnancy, and infertility. The only effective approach to disease control is vaccination. The goal of this work was to identify new potential vaccine candidates through a proteomics approach. We constructed a protein chip array (Antigen Discovery, Inc.) by expressing the open reading frames (ORFs) from C. trachomatis mouse pneumonitis (MoPn) genomic and plasmid DNA and tested it with serum samples from MoPn-immunized mice. Two groups of BALB/c female mice were immunized either intranasally or intravaginally with live elementary bodies (EB). Another two groups were immunized by a combination of the intramuscular and subcutaneous routes with UV-treated EB (UV-EB), using either CpG and Montanide as adjuvants to favor a Th1 response or alum to elicit a Th2 response. Serum samples collected at regular intervals postimmunization were tested in the proteome array. The microarray included the expression products of 909 proteins from a total of 921 ORFs of the Chlamydia MoPn genome and plasmid. A total of 185 immunodominant proteins elicited an early and sustained antibody response in the mice immunized with live EB, and of these, 71 were also recognized by the sera from mice immunized with UV-EB. The reactive antigens included some proteins that were previously described as immunogenic, such as the major outer membrane protein, OmpB, Hsp60, and IncA and proteins from the type III secretion system. In addition, we identified in mice several new immunogens, including 75 hypothetical proteins. In summary, we have identified a new group of immunodominant chlamydial proteins that can be tested for their ability to induce protection.

Motivation: Discovery of novel protective antigens is fundamental to the development of vaccines for existing and emerging pathogens. Most computational methods for predicting protein antigenicity rely directly on homology with previously characterized protective antigens; however, homology-based methods will fail to discover truly novel protective antigens. Thus, there is a significant need for homology-free methods capable of screening entire proteomes for the antigens most likely to generate a protective humoral immune response., Results: Here we begin by curating two types of positive data: (i) antigens that elicit a strong antibody response in protected individuals but not in unprotected individuals, using human immunoglobulin reactivity data obtained from protein microarray analyses; and (ii) known protective antigens from the literature. The resulting datasets are used to train a sequence-based prediction model, ANTIGENpro, to predict the likelihood that a protein is a protective antigen. ANTIGENpro correctly classifies 82% of the known protective antigens when trained using only the protein microarray datasets. The accuracy on the combined dataset is estimated at 76% by cross-validation experiments. Finally, ANTIGENpro performs well when evaluated on an external pathogen proteome for which protein microarray data were obtained after the initial development of ANTIGENpro., Availability: ANTIGENpro is integrated in the SCRATCH suite of predictors available at http://scratch.proteomics.ics.uci.edu., Contact: pfbaldi@ics.uci.edu

Abs are central to malaria immunity, which is only acquired after years of exposure to Plasmodium falciparum (Pf). Despite the enormous worldwide burden of malaria, the targets of protective Abs and the basis of their inefficient acquisition are unknown. Addressing these knowledge gaps could accelerate malaria vaccine development. To this end, we developed a protein microarray containing approximately 23% of the Pf 5,400-protein proteome and used this array to probe plasma from 220 individuals between the ages of 2-10 years and 18-25 years in Mali before and after the 6-month malaria season. Episodes of malaria were detected by passive surveillance over the 8-month study period. Ab reactivity to Pf proteins rose dramatically in children during the malaria season; however, most of this response appeared to be short-lived based on cross-sectional analysis before the malaria season, which revealed only modest incremental increases in Ab reactivity with age. Ab reactivities to 49 Pf proteins measured before the malaria season were significantly higher in 8-10-year-old children who were infected with Pf during the malaria season but did not experience malaria (n = 12) vs. those who experienced malaria (n = 29). This analysis also provided insight into patterns of Ab reactivity against Pf proteins based on the life cycle stage at which proteins are expressed, subcellular location, and other proteomic features. This approach, if validated in larger studies and in other epidemiological settings, could prove to be a useful strategy for better understanding fundamental properties of the human immune response to Pf and for identifying previously undescribed vaccine targets.

Candida albicans in the immunocompetent host is a benign member of the human microbiota. Though, when host physiology is disrupted, this commensal-host interaction can degenerate and lead to an opportunistic infection. Relatively little is known regarding the dynamics of C. albicans colonization and pathogenesis. We developed a C. albicans cell surface protein microarray to profile the immunoglobulin G response during commensal colonization and candidemia. The antibody response from the sera of patients with candidemia and our negative control groups indicate that the immunocompetent host exists in permanent host-pathogen interplay with commensal C. albicans. This report also identifies cell surface antigens that are specific to different phases (i.e. acute, early and mid convalescence) of candidemia. We identified a set of thirteen cell surface antigens capable of distinguishing acute candidemia from healthy individuals and uninfected hospital patients with commensal colonization. Interestingly, a large proportion of these cell surface antigens are involved in either oxidative stress or drug resistance. In addition, we identified 33 antigenic proteins that are enriched in convalescent sera of the candidemia patients. Intriguingly, we found within this subset an increase in antigens associated with heme-associated iron acquisition. These findings have important implications for the mechanisms of C. albicans colonization as well as the development of systemic infection.

Understanding the way in which the immune system responds to infection is central to the development of vaccines and many diagnostics. To provide insight into this area, we fabricated a protein microarray containing 1,205 Burkholderia pseudomallei proteins, probed it with 88 melioidosis patient sera, and identified 170 reactive antigens. This subset of antigens was printed on a smaller array and probed with a collection of 747 individual sera derived from 10 patient groups including melioidosis patients from Northeast Thailand and Singapore, patients with different infections, healthy individuals from the USA, and from endemic and nonendemic regions of Thailand. We identified 49 antigens that are significantly more reactive in melioidosis patients than healthy people and patients with other types of bacterial infections. We also identified 59 cross-reactive antigens that are equally reactive among all groups, including healthy controls from the USA. Using these results we were able to devise a test that can classify melioidosis positive and negative individuals with sensitivity and specificity of 95% and 83%, respectively, a significant improvement over currently available diagnostic assays. Half of the reactive antigens contained a predicted signal peptide sequence and were classified as outer membrane, surface structures or secreted molecules, and an additional 20% were associated with pathogenicity, adaptation or chaperones. These results show that microarrays allow a more comprehensive analysis of the immune response on an antigen-specific, patient-specific, and population-specific basis, can identify serodiagnostic antigens, and contribute to a more detailed understanding of immunogenicity to this pathogen.

Humans and other animals with Lyme borreliosis produce antibodies to a number of components of the agent Borrelia burgdorferi, but a full accounting of the immunogens during natural infections has not been achieved. Employing a protein array produced in vitro from 1,292 DNA fragments representing approximately 80% of the genome, we compared the antibody reactivities of sera from patients with early or later Lyme borreliosis to the antibody reactivities of sera from controls. Overall, approximately 15% of the open reading frame (ORF) products (Orfs) of B. burgdorferi in the array detectably elicited an antibody response in humans with natural infections. Among the immunogens, 103 stood out on the basis of statistical criteria. The majority of these Orfs were also immunogenic with sera obtained from naturally infected Peromyscus leucopus mice, a major reservoir. The high-ranking set included several B. burgdorferi proteins hitherto unrecognized as immunogens, as well as several proteins that have been established as antigens. The high-ranking immunogens were more likely than nonreactive Orfs to have the following characteristics: (i) plasmid-encoded rather than chromosome-encoded proteins, (ii) a predicted lipoprotein, and (iii) a member of a paralogous family of proteins, notably the Bdr and Erp proteins. The newly discovered antigens included Orfs encoded by several ORFs of the lp36 linear plasmid, such as BBK07 and BBK19, and proteins of the flagellar apparatus, such as FliL. These results indicate that the majority of deduced proteins of B. burgdorferi do not elicit antibody responses during infection and that the limited sets of immunogens are similar for two different host species.