Uncovering a Macrophage Transcriptional Program by Integrating Evidence from Motif Scanning and Expression Dynamics

Macrophages are versatile immune cells that can detect a variety of pathogen-associated molecular patterns through their Toll-like receptors (TLRs). In response to microbial challenge, the TLR-stimulated macrophage undergoes an activation program controlled by a dynamically inducible transcriptional regulatory network. Mapping a complex mammalian transcriptional network poses significant challenges and requires the integration of multiple experimental data types. In this work, we inferred a transcriptional network underlying TLR-stimulated murine macrophage activation. Microarray-based expression profiling and transcription factor binding site motif scanning were used to infer a network of associations between transcription factor genes and clusters of co-expressed target genes. The time-lagged correlation was used to analyze temporal expression data in order to identify potential causal influences in the network. A novel statistical test was developed to assess the significance of the time-lagged correlation. Several associations in the resulting inferred network were validated using targeted ChIP-on-chip experiments. The network incorporates known regulators and gives insight into the transcriptional control of macrophage activation. Our analysis identified a novel regulator (TGIF1) that may have a role in macrophage activation

Computational Identification of Transcriptional Regulators in Human Endotoxemia

One of the great challenges in the post-genomic era is to decipher the underlying principles governing the dynamics of biological responses. As modulating gene expression levels is among the key regulatory responses of an organism to changes in its environment, identifying biologically relevant transcriptional regulators and their putative regulatory interactions with target genes is an essential step towards studying the complex dynamics of transcriptional regulation. We present an analysis that integrates various computational and biological aspects to explore the transcriptional regulation of systemic inflammatory responses through a human endotoxemia model. Given a high-dimensional transcriptional profiling dataset from human blood leukocytes, an elementary set of temporal dynamic responses which capture the essence of a pro-inflammatory phase, a counter-regulatory response and a dysregulation in leukocyte bioenergetics has been extracted. Upon identification of these expression patterns, fourteen inflammation-specific gene batteries that represent groups of hypothetically ‘coregulated’ genes are proposed. Subsequently, statistically significant cis-regulatory modules (CRMs) are identified and decomposed into a list of critical transcription factors (34) that are validated largely on primary literature. Finally, our analysis further allows for the construction of a dynamic representation of the temporal transcriptional regulatory program across the host, deciphering possible combinatorial interactions among factors under which they might be active. Although much remains to be explored, this study has computationally identified key transcription factors and proposed a putative time-dependent transcriptional regulatory program associated with critical transcriptional inflammatory responses. These results provide a solid foundation for future investigations to elucidate the underlying transcriptional regulatory mechanisms under the host inflammatory response. Also, the assumption that coexpressed genes that are functionally relevant are more likely to share some common transcriptional regulatory mechanism seems to be promising, making the proposed framework become essential in unravelling context-specific transcriptional regulatory interactions underlying diverse mammalian biological processes

Human Monoclonal Antibody Reactivity With Human Leukocyte Antigen Class I Epitopes Defined by Pairs of Mismatched Eplets and Self-Eplets

Aim. Humoral sensitization affects transplant outcome, and it is now apparent that human leukocyte antigen (HLA) antibodies are specific for epitopes rather than antigens. Such epitopes can be structurally defined by HLAMatchmaker, an algorithm that considers eplets as critical elements of epitopes recognized by alloantibodies. This study addressed the question how mismatched HLA antigens induce specific antibodies in context with eplet differences with the antibody producer. Methods. HLA class I-specific human monoclonal antibodies derived from women sensitized during pregnancy were tested in Luminex assays with single allele panels. Their epitope specificity was determined from reactivity patterns and eplet differences between immunizing antigen and the antibody producer. Results. This study focuses on the reactivity patterns of 10 monoclonal antibodies specific for epitopes defined by a mismatched eplet paired with a self-eplet shared between immunizing HLA antigens and HLA antigens of the antibody producer. The eplets in these pairs are between 7 and 16 angstrom apart, a sufficient distance for contact by two separate complementarity-determining regions of antibody. Conclusions. These findings demonstrate that immunizing antigens have mismatched eplets that can form antibody-reactive epitopes with self-configurations on the molecular surface. They seem to suggest that HLA antibodies can be produced by autoreactive B cells that have undergone receptor editing to accommodate the recognition of nonself-eplets, the driving force of the humoral alloresponse. This concept enhances our understanding of structural epitope immunogenicity and the interpretation of antibody reactivity patterns with HLA panels.Transplantation and autoimmunit

Human monoclonal antibody reactivity with HLA class I epitopes defined by pairs of mismatched eplets and self eplets

Transplantation and autoimmunit

Structural aspects of human leukocyte antigen class I epitopes detected by human monoclonal antibodies

Transplantation and autoimmunit

The biologic properties of leukemias arising from BCR/ABL-mediated transformation vary as a function of developmental origin and activity of the p19ARF gene

Recent reports have shown that upon expression of appropriate oncogenes, both stem cells and more differentiated progenitor populations can serve as leukemia-initiating cells. These studies suggest that oncogenic mutations subvert normal development and induce reacquisition of stem-like features. However, no study has described how specific mutations influence the ability of differentiating cell subsets to serve as leukemia-initiating cells and if varying such cellular origins confers a functional difference. We have examined the role of the tumor suppressor gene p19ARF in a murine model of acute lymphoblastic leukemia and found that loss of p19ARF changes the spectrum of cells capable of tumor initiation. With intact p19ARF, only hematopoietic stem cells (HSCs) can be directly transformed by BCR/ABL expression. In a p19ARF-null genetic background expression of the BCR/ABL fusion protein renders functionally defined HSCs, common lymphoid progenitors (CLP), and precursor B-lymphocytes competent to generate leukemia stem cells. Furthermore, we show that leukemias arising from p19ARF-null HSC versus pro-B cells differ biologically, including relative response to drug insult. Our observations elucidate a unique mechanism by which heterogeneity arises in tumor populations harboring identical genetic lesions and show that activity of p19ARF profoundly influences the nature of tumor-initiating cells during BCR/ABL-mediated leukemogenesis