Network Theory Analysis of Antibody-Antigen Reactivity Data: The Immune Trees at Birth and Adulthood

Motivation: New antigen microarray technology enables parallel recording of antibody reactivities with hundreds of antigens. Such data affords system level analysis of the immune system’s organization using methods and approaches from network theory. Here we measured the reactivity of 290 antigens (for both the IgG and IgM isotypes) of 10 healthy mothers and their term newborns. We constructed antigen correlation networks (or immune networks) whose nodes are the antigens and the edges are the antigen-antigen reactivity correlations, and we also computed their corresponding minimum spanning trees (MST) – maximal information reduced sub-graphs. We quantify the network organization (topology) in terms of the network theory divergence rate measure and rank the antigen importance in the full antigen correlation networks by the eigen-value centrality measure. This analysis makes possible the characterization and comparison of the IgG and IgM immune networks at birth (newborns) and adulthood (mothers) in terms of topology and node importance. Results: Comparison of the immune network topology at birth and adulthood revealed partial conservation of the IgG immune network topology, and significant reorganization of the IgM immune networks. Inspection of the antigen importance revealed some dominant (in terms of high centrality) antigens in the IgG and IgM networks at birth, which retain their importance at adulthood

Functional immunomics: Microarray analysis of IgG autoantibody repertoires predicts the future response of NOD mice to an inducer of accelerated diabetes

One's present repertoire of antibodies encodes the history of one's past immunological experience. Can the present autoantibody repertoire be consulted to predict resistance or susceptibility to the future development of an autoimmune disease? Here we developed an antigen microarray chip and used bioinformatic analysis to study a model of type 1 diabetes developing in non-obese diabetic (NOD) male mice in which the disease was accelerated and synchronized by exposing the mice to cyclophosphamide at 4 weeks of age. We obtained sera from 19 individual mice, treated the mice to induce cyclophosphamide-accelerated diabetes (CAD), and found, as expected, that 9 mice became severely diabetic while 10 mice permanently resisted diabetes. We again obtained serum from each mouse afterCAD induction. We then analyzed the patterns of antibodies in the individualmice to 266 different antigens spotted on the antigen chip. We identified a select panel of 27 different antigens (10% of the array) that revealed a pattern of IgG antibody reactivity in the pre-CAD serathat discriminated between the mice resistant or susceptible to CAD with 100% sensitivity and 82% specificity (p=0.017). Surprisingly, the set of IgG antibodies that was informative before CAD induction did not separate the resistant and susceptible groups after the onset of CAD; new antigens became criticalfor post-CAD repertoire discrimination. Thus, at least for a model disease, present antibody repertoires can predict future disease; predictive and diagnostic repertoires can differ; and decisive information about immune system behavior can be mined by bioinformatic technology. Repertoires matter.Comment: See Advanced Publication on the PNAS website for final versio

A proteomic approach for the identification of novel lysine methyltransferase substrates

<p>Abstract</p> <p>Background</p> <p>Signaling via protein lysine methylation has been proposed to play a central role in the regulation of many physiologic and pathologic programs. In contrast to other post-translational modifications such as phosphorylation, proteome-wide approaches to investigate lysine methylation networks do not exist.</p> <p>Results</p> <p>In the current study, we used the ProtoArray^®platform, containing over 9,500 human proteins, and developed and optimized a system for proteome-wide identification of novel methylation events catalyzed by the protein lysine methyltransferase (PKMT) SETD6. This enzyme had previously been shown to methylate the transcription factor RelA, but it was not known whether SETD6 had other substrates. By using two independent detection approaches, we identified novel candidate substrates for SETD6, and verified that all targets tested <it>in vitro </it>and in cells were genuine substrates.</p> <p>Conclusions</p> <p>We describe a novel proteome-wide methodology for the identification of new PKMT substrates. This technological advance may lead to a better understanding of the enzymatic activity and substrate specificity of the large number (more than 50) PKMTs present in the human proteome, most of which are uncharacterized.</p

Autoantibodies to αS1-Casein Are Induced by Breast-Feeding

BACKGROUND: The generation of antibodies is impaired in newborns due to an immature immune system and reduced exposure to pathogens due to maternally derived antibodies and placental functions. During nursing, the immune system of newborns is challenged with multiple milk-derived proteins. Amongst them, caseins are the main constituent. In particular, human αS1-casein (CSN1S1) was recently shown to possess immunomodulatory properties. We were thus interested to determine if auto-antibodies to CSN1S1 are induced by breast-feeding and may be sustained into adulthood. METHODS: 62 sera of healthy adult individuals who were (n = 37) or were not (n = 25) breast-fed against human CSN1S1 were investigated by a new SD (surface display)-ELISA. For cross-checking, these sera were tested for anti Epstein-Barr virus (EBV) antibodies by a commercial ELISA. RESULTS: IgG-antibodies were predominantly detected in individuals who had been nursed. At a cut-off value of 0.4, the SD-ELISA identified individuals with a history of having been breast-fed with a sensitivity of 80% and a specificity of 92%. Under these conditions, 35 out of 37 sera from healthy donors, who where breast-fed, reacted positively but only 5 sera of the 25 donors who were not breast-fed. The duration of breast-feeding was of no consequence to the antibody reaction as some healthy donors were only short term breast-fed (5 days minimum until 6 weeks maximum), but exhibited significant serum reaction against human CSN1S1 nonetheless. CONCLUSION: We postulate that human CSN1S1 is an autoantigen. The antigenicity is orally determined, caused by breast-feeding, and sustained into adulthood

HSP60 as a Target of Anti-Ergotypic Regulatory T Cells

The 60 kDa heat shock protein (HSP60) has been reported to influence T-cell responses in two ways: as a ligand of toll-like receptor 2 signalling and as an antigen. Here we describe a new mechanism of T-cell immuno-regulation focused on HSP60: HSP60 is up-regulated and presented by activated T cells (HSP60 is an ergotope) to regulatory (anti-ergotypic) T cells. Presentation of HSP60 by activated T cells was found to be MHC-restricted and dependent on accessory molecules - CD28, CD80 and CD86. Anti-ergotypic T cells responded to T-cell HSP60 by proliferation and secreted IFNγ and TGFβ1. In vitro, the anti-ergotypic T cells inhibited IFNγ production by their activated T-cell targets. In vivo, adoptive transfer of an anti-ergotypic HSP60-specific T-cell line led to decreased secretion of IFNγ by arthritogenic T cells and ameliorated adjuvant arthritis (AA). Thus, the presentation of HSP60 by activated T cells turns them into targets for anti-ergotypic regulatory T cells specific for HSP60. However, the direct interaction between the anti-ergotypic T regulators (anti-HSP60) and the activated T cells also down-regulated the regulators. Thus, by functioning as an ergotope, HSP60 can control both the effector T cells and the regulatory HSP60-specific T cells that control them

Structural insights into the catalysis and regulation of E3 ubiquitin ligases

Covalent attachment (conjugation) of one or more ubiquitin molecules to protein substrates governs numerous eukaryotic cellular processes, including apoptosis, cell division and immune responses. Ubiquitylation was originally associated with protein degradation, but it is now clear that ubiquitylation also mediates processes such as protein–protein interactions and cell signalling depending on the type of ubiquitin conjugation. Ubiquitin ligases (E3s) catalyse the final step of ubiquitin conjugation by transferring ubiquitin from ubiquitin-conjugating enzymes (E2s) to substrates. In humans, more than 600 E3s contribute to determining the fates of thousands of substrates; hence, E3s need to be tightly regulated to ensure accurate substrate ubiquitylation. Recent findings illustrate how E3s function on a structural level and how they coordinate with E2s and substrates to meticulously conjugate ubiquitin. Insights regarding the mechanisms of E3 regulation, including structural aspects of their autoinhibition and activation are also emerging

A Bioinformatics Filtering Strategy for Identifying Radiation Response Biomarker Candidates

The number of biomarker candidates is often much larger than the number of clinical patient data points available, which motivates the use of a rational candidate variable filtering methodology. The goal of this paper is to apply such a bioinformatics filtering process to isolate a modest number (<10) of key interacting genes and their associated single nucleotide polymorphisms involved in radiation response, and to ultimately serve as a basis for using clinical datasets to identify new biomarkers. In step 1, we surveyed the literature on genetic and protein correlates to radiation response, in vivo or in vitro, across cellular, animal, and human studies. In step 2, we analyzed two publicly available microarray datasets and identified genes in which mRNA expression changed in response to radiation. Combining results from Step 1 and Step 2, we identified 20 genes that were common to all three sources. As a final step, a curated database of protein interactions was used to generate the most statistically reliable protein interaction network among any subset of the 20 genes resulting from Steps 1 and 2, resulting in identification of a small, tightly interacting network with 7 out of 20 input genes. We further ranked the genes in terms of likely importance, based on their location within the network using a graph-based scoring function. The resulting core interacting network provides an attractive set of genes likely to be important to radiation response