Background: Immunosignaturing is a new peptide microarray based technology for profiling of humoral immune responses. Despite new challenges, immunosignaturing gives us the opportunity to explore new and fundamentally different research questions. In addition to classifying samples based on disease status, the complex patterns and latent factors underlying immunosignatures, which we attempt to model, may have a diverse range of applications.

Methods: We investigate the utility of a number of statistical methods to determine model performance and address challenges inherent in analyzing immunosignatures. Some of these methods include exploratory and confirmatory factor analyses, classical significance testing, structural equation and mixture modeling.

Results: We demonstrate an ability to classify samples based on disease status and show that immunosignaturing is a very promising technology for screening and presymptomatic screening of disease. In addition, we are able to model complex patterns and latent factors underlying immunosignatures. These latent factors may serve as biomarkers for disease and may play a key role in a bioinformatic method for antibody discovery.

Conclusion: Based on this research, we lay out an analytic framework illustrating how immunosignatures may be useful as a general method for screening and presymptomatic screening of disease as well as antibody discovery.

Background: High-throughput technologies such as DNA, RNA, protein, antibody and peptide microarrays are often used to examine differences across drug treatments, diseases, transgenic animals, and others. Typically one trains a classification system by gathering large amounts of probe-level data, selecting informative features, and classifies test samples using a small number of features. As new microarrays are invented, classification systems that worked well for other array types may not be ideal. Expression microarrays, arguably one of the most prevalent array types, have been used for years to help develop classification algorithms. Many biological assumptions are built into classifiers that were designed for these types of data. One of the more problematic is the assumption of independence, both at the probe level and again at the biological level. Probes for RNA transcripts are designed to bind single transcripts. At the biological level, many genes have dependencies across transcriptional pathways where co-regulation of transcriptional units may make many genes appear as being completely dependent. Thus, algorithms that perform well for gene expression data may not be suitable when other technologies with different binding characteristics exist. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides. It relies on many-to-many binding of antibodies to the random sequence peptides. Each peptide can bind multiple antibodies and each antibody can bind multiple peptides. This technology has been shown to be highly reproducible and appears promising for diagnosing a variety of disease states. However, it is not clear what is the optimal classification algorithm for analyzing this new type of data.

Results: We characterized several classification algorithms to analyze immunosignaturing data. We selected several datasets that range from easy to difficult to classify, from simple monoclonal binding to complex binding patterns in asthma patients. We then classified the biological samples using 17 different classification algorithms. Using a wide variety of assessment criteria, we found ‘Naïve Bayes’ far more useful than other widely used methods due to its simplicity, robustness, speed and accuracy.

Conclusions: ‘Naïve Bayes’ algorithm appears to accommodate the complex patterns hidden within multilayered immunosignaturing microarray data due to its fundamental mathematical properties.

The field of cyanobacterial biofuel production is advancing rapidly, yet we know little of the basic biology of these organisms outside of their photosynthetic pathways. We aimed to gain a greater understanding of how the cyanobacterium Synechocystis PCC 6803 (Synechocystis, hereafter) modulates its cell surface. Such understanding will allow for the creation of mutants that autoflocculate in a regulated way, thus avoiding energy intensive centrifugation in the creation of biofuels. We constructed mutant strains lacking genes predicted to function in carbohydrate transport or synthesis. Strains with gene deletions of slr0977 (predicted to encode a permease component of an ABC transporter), slr0982 (predicted to encode an ATP binding component of an ABC transporter) and slr1610 (predicted to encode a methyltransferase) demonstrated flocculent phenotypes and increased adherence to glass. Upon bioinformatic inspection, the gene products of slr0977, slr0982, and slr1610 appear to function in O-antigen (OAg) transport and synthesis. However, the analysis provided here demonstrated no differences between OAg purified from wild-type and mutants. However, exopolysaccharides (EPS) purified from mutants were altered in composition when compared to wild-type. Our data suggest that there are multiple means to modulate the cell surface of Synechocystis by disrupting different combinations of ABC transporters and/or glycosyl transferases. Further understanding of these mechanisms may allow for the development of industrially and ecologically useful strains of cyanobacteria. Additionally, these data imply that many cyanobacterial gene products may possess as-yet undiscovered functions, and are meritorious of further study.

Avian pathogenic Escherichia coli (APEC) strains cause systemic and localized infections in poultry, jointly termed colibacillosis. Avian colibacillosis is responsible for significant economic losses to the poultry industry due to disease treatment, decrease in growth rate and egg production, and mortality. APEC are also considered a potential zoonotic risk for humans. Fully elucidating the virulence and zoonotic potential of APEC is key for designing successful strategies against their infections and their transmission. Herein, we investigated the prevalence of a newly discovered E. coli common pilus (ECP) for the subunit protein of the ECP pilus (ecpA) and ECP expression amongst APEC strains as well as the role of ECP in virulence. A PCR-based ecpA survey of a collection of 167 APEC strains has shown that 76% (127/167) were ecpA+. An immunofluorescence assay using anti-EcpA antibodies, revealed that among the ecpA+ strains, 37.8% (48/127) expressed ECP when grown in DMEM +0.5% Mannose in contact with HeLa cells at 37°C and/or in biofilm at 28°C; 35.4% (17/48) expressed ECP in both conditions and 64.6% (31/48) expressed ECP in biofilm only. We determined that the ecp operon in the APEC strain χ7122 (ecpA+, ECP-) was not truncated; the failure to detect ECP in some strains possessing non-truncated ecp genes might be attributed to differential regulatory mechanisms between strains that respond to specific environmental signals. To evaluate the role of ECP in the virulence of APEC, we generated ecpA and/or ecpD-deficient mutants from the strain χ7503 (ecpA+, ECP+). Deletion of ecpA and/or ecpD abolished ECP synthesis and expression, and reduced biofilm formation and motility in vitro and virulence in vivo. All together our data show that ecpA is highly prevalent among APEC isolates and its expression could be differentially regulated in these strains, and that ECP plays a role in the virulence of APEC.

Natural killer (NK) cells are a critical part of the innate immune defense against viral infections and for the control of tumors. Much less is known about how NK cells contribute to anti-bacterial immunity. NK cell-produced interferon gamma (IFN-γ) contributes to the control of early exponential replication of bacterial pathogens, however the regulation of these events remains poorly resolved. Using a mouse model of invasive Salmonellosis, here we report that the activation of the intracellular danger sensor NLRC4 by Salmonella-derived flagellin within CD11c⁺ cells regulates early IFN-γ secretion by NK cells through the provision of interleukin 18 (IL-18), independently of Toll-like receptor (TLR)-signaling. Although IL18-signalling deficient NK cells improved host protection during S. Typhimurium infection, this increased resistance was inferior to that provided by wild-type NK cells. These findings suggest that although NLRC4 inflammasome-driven secretion of IL18 serves as a potent activator of NK cell mediated IFN-γ secretion, IL18-independent NK cell-mediated mechanisms of IFN-γ secretion contribute to in vivo control of Salmonella replication.

Immunosignaturing shows promise as a general approach to diagnosis. It has been shown to detect immunological signs of infection early during the course of disease and to distinguish Alzheimer’s disease from healthy controls. Here we test whether immunosignatures correspond to clinical classifications of disease using samples from people with brain tumors. Blood samples from patients undergoing craniotomies for therapeutically naïve brain tumors with diagnoses of astrocytoma (23 samples), Glioblastoma multiforme (22 samples), mixed oligodendroglioma/astrocytoma (16 samples), oligodendroglioma (18 samples), and 34 otherwise healthy controls were tested by immunosignature. Because samples were taken prior to adjuvant therapy, they are unlikely to be perturbed by non-cancer related affects. The immunosignaturing platform distinguished not only brain cancer from controls, but also pathologically important features about the tumor including type, grade, and the presence or absence of O⁶-methyl-guanine-DNA methyltransferase methylation promoter (MGMT), an important biomarker that predicts response to temozolomide in Glioblastoma multiformae patients.

Background: Salmonella has been employed to deliver therapeutic molecules against cancer and infectious diseases. As the carrier for target gene(s), the cargo plasmid should be stable in the bacterial vector. Plasmid recombination has been reduced in E. coli by mutating several genes including the recA, recE, recF and recJ. However, to our knowledge, there have been no published studies of the effect of these or any other genes that play a role in plasmid recombination in Salmonella enterica.

Results: The effect of recA, recF and recJ deletions on DNA recombination was examined in three serotypes of Salmonella enterica. We found that (1) intraplasmid recombination between direct duplications was RecF-independent in Typhimurium and Paratyphi A, but could be significantly reduced in Typhi by a ΔrecA or ΔrecF mutation; (2) in all three Salmonella serotypes, both ΔrecA and ΔrecF mutations reduced intraplasmid recombination when a 1041 bp intervening sequence was present between the duplications; (3) ΔrecA and ΔrecF mutations resulted in lower frequencies of interplasmid recombination in Typhimurium and Paratyphi A, but not in Typhi; (4) in some cases, a ΔrecJ mutation could reduce plasmid recombination but was less effective than ΔrecA and ΔrecF mutations. We also examined chromosome-related recombination. The frequencies of intrachromosomal recombination and plasmid integration into the chromosome were 2 and 3 logs lower than plasmid recombination frequencies in Rec[superscript +] strains. A ΔrecA mutation reduced both intrachromosomal recombination and plasmid integration frequencies.

Conclusions: The ΔrecA and ΔrecF mutations can reduce plasmid recombination frequencies in Salmonella enterica, but the effect can vary between serovars. This information will be useful for developing Salmonella delivery vectors able to stably maintain plasmid cargoes for vaccine development and gene therapy.

Salmonella enterica serovar Typhimurium strains belonging to sequence type ST313 are a major cause of fatal bacteremia among HIV-infected adults and children in sub-Saharan Africa. Unlike “classical” non-typhoidal Salmonella (NTS), gastroenteritis is often absent during ST313 infections and isolates are most commonly recovered from blood, rather than from stool. This is consistent with observations in animals, in which ST313 strains displayed lower levels of intestinal colonization and higher recovery from deeper tissues relative to classic NTS isolates. A better understanding of the key environmental factors regulating these systemic infections is urgently needed. Our previous studies using dynamic Rotating Wall Vessel (RWV) bioreactor technology demonstrated that physiological levels of fluid shear regulate virulence, gene expression, and stress response profiles of classic S. Typhimurium. Here we provide the first demonstration that fluid shear alters the virulence potential and pathogenesis-related stress responses of ST313 strain D23580 in a manner that differs from classic NTS.

There is an increasing awareness that health care must move from post-symptomatic treatment to presymptomatic intervention. An ideal system would allow regular inexpensive monitoring of health status using circulating antibodies to report on health fluctuations. Recently, we demonstrated that peptide microarrays can do this through antibody signatures (immunosignatures). Unfortunately, printed microarrays are not scalable. Here we demonstrate a platform based on fabricating microarrays (~10 M peptides per slide, 330,000 peptides per assay) on silicon wafers using equipment common to semiconductor manufacturing. The potential of these microarrays for comprehensive health monitoring is verified through the simultaneous detection and classification of six different infectious diseases and six different cancers. Besides diagnostics, these high-density peptide chips have numerous other applications both in health care and elsewhere.

Extraintestinal pathogenic Escherichia coli (ExPEC) strains are important pathogens that cause diverse diseases in humans and poultry. Some E. coli isolates from chicken feces contain ExPEC-associated virulence genes, so appear potentially pathogenic; they conceivably could be transmitted to humans through handling and/or consumption of contaminated meat. However, the actual extraintestinal virulence potential of chicken-source fecal E. coli is poorly understood. Here, we assessed whether fecal E. coli isolates from healthy production chickens could cause diseases in a chicken model of avian colibacillosis and three rodent models of ExPEC-associated human infections. From 304 E. coli isolates from chicken fecal samples, 175 E. coli isolates were screened by PCR for virulence genes associated with human-source ExPEC or avian pathogenic E. coli (APEC), an ExPEC subset that causes extraintestinal infections in poultry. Selected isolates genetically identified as ExPEC and non-ExPEC isolates were assessed in vitro for virulence-associated phenotypes, and in vivo for disease-causing ability in animal models of colibacillosis, sepsis, meningitis, and urinary tract infection. Among the study isolates, 13% (40/304) were identified as ExPEC; the majority of these were classified as APEC and uropathogenic E. coli, but none as neonatal meningitis E. coli. Multiple chicken-source fecal ExPEC isolates resembled avian and human clinical ExPEC isolates in causing one or more ExPEC-associated illnesses in experimental animal infection models. Additionally, some isolates that were classified as non-ExPEC were able to cause ExPEC-associated illnesses in animal models, and thus future studies are needed to elucidate their mechanisms of virulence. These findings show that E. coli isolates from chicken feces contain ExPEC-associated genes, exhibit ExPEC-associated in vitro phenotypes, and can cause ExPEC-associated infections in animal models, and thus may pose a health threat to poultry and consumers.