Dissecting BCR-ABL Variant Signaling Pathways Using Novel Interactome Identification Strategies

Cell signaling is an essential function of cells and tissues. Understanding cell signaling necessitates technologies that can identify protein-protein interactions as well as post translational modifications to proteins within protein complexes. The goals of this study are (1) to understand how BCR-ABL variants differentially signal to produce different clinical/experimental phenotypes and (2) to develop novel interactome detection strategies to understand signaling. This dissertation describes an integrated approach of the use of proximity dependent labeling protein-protein interaction analysis assays coupled with global phosphorylation analysis to investigate the differences in signaling between two variants the oncogenic fusion protein, BCR-ABL. Two major types of leukemogenic BCR-ABL fusion proteins are p190BCR-ABL and p210BCR-ABL. Although the two fusion proteins are closely related, they can lead to different clinical outcomes. A thorough understanding of the signaling programs employed by these two fusion proteins is necessary to explain these clinical differences. Our findings suggest that p190BCR-ABL and p210BCR-ABL differentially activate important signaling pathways, such as JAK-STAT, and engage with molecules that indicate interaction with different subcellular compartments. In the case of p210BCR-ABL, we observed an increased engagement of molecules active proximal to the membrane and in the case of p190BCR-ABL, an engagement of molecules of the cytoskeleton. These differences in signaling could underlie the distinct leukemogenic process induced by these two protein variants. Additionally, this dissertation also describes the development of a novel interactome detection strategy, called Biotinylation Site Identification Technology (BioSITe), which increases the sensitivity and specificity of proximity dependent biotin labeling technologies. When applied to BCR-ABL variants, BioSITe provides structural information about BCR-ABL interacting proteins and the degree of proximity these proteins are to BCR-ABL. Finally, this thesis demonstrates the use of isotopically labeled biotin for quantitative BioSITe experiments, applied to BCR-ABL variants, simplifies differential interactome analysis

Developmental partitioning of SYK and ZAP70 prevents autoimmunity and cancer

Even though SYK and ZAP70 kinases share high sequence homology and serve analogous functions, their expression in B and T cells is strictly segregated throughout evolution. Here, we identified aberrant ZAP70 expression as a common feature in a broad range of B cell malignancies. We validated SYK as the kinase that sets the thresholds for negative selection of autoreactive and premalignant clones. When aberrantly expressed in B cells, ZAP70 competes with SYK at the BCR signalosome and redirects SYK from negative selection to tonic PI3K signaling, thereby promoting B cell survival. In genetic mouse models for B-ALL and B-CLL, conditional expression of Zap70 accelerated disease onset, while genetic deletion impaired malignant transformation. Inducible activation of Zap70 during B cell development compromised negative selection of autoreactive B cells, resulting in pervasive autoantibody production. Strict segregation of the two kinases is critical for normal B cell selection and represents a central safeguard against the development of autoimmune disease and B cell malignancies.acceptedVersionPeer reviewe

Dissecting BCR-ABL Variant Signaling Pathways Using Novel Interactome Identification Strategies

Cell signaling is an essential function of cells and tissues. Understanding cell signaling necessitates technologies that can identify protein-protein interactions as well as post translational modifications to proteins within protein complexes. The goals of this study are (1) to understand how BCR-ABL variants differentially signal to produce different clinical/experimental phenotypes and (2) to develop novel interactome detection strategies to understand signaling. This dissertation describes an integrated approach of the use of proximity dependent labeling protein-protein interaction analysis assays coupled with global phosphorylation analysis to investigate the differences in signaling between two variants the oncogenic fusion protein, BCR-ABL. Two major types of leukemogenic BCR-ABL fusion proteins are p190BCR-ABL and p210BCR-ABL. Although the two fusion proteins are closely related, they can lead to different clinical outcomes. A thorough understanding of the signaling programs employed by these two fusion proteins is necessary to explain these clinical differences. Our findings suggest that p190BCR-ABL and p210BCR-ABL differentially activate important signaling pathways, such as JAK-STAT, and engage with molecules that indicate interaction with different subcellular compartments. In the case of p210BCR-ABL, we observed an increased engagement of molecules active proximal to the membrane and in the case of p190BCR-ABL, an engagement of molecules of the cytoskeleton. These differences in signaling could underlie the distinct leukemogenic process induced by these two protein variants. Additionally, this dissertation also describes the development of a novel interactome detection strategy, called Biotinylation Site Identification Technology (BioSITe), which increases the sensitivity and specificity of proximity dependent biotin labeling technologies. When applied to BCR-ABL variants, BioSITe provides structural information about BCR-ABL interacting proteins and the degree of proximity these proteins are to BCR-ABL. Finally, this thesis demonstrates the use of isotopically labeled biotin for quantitative BioSITe experiments, applied to BCR-ABL variants, simplifies differential interactome analysis

BioSITe: A Method for Direct Detection and Quantitation of Site-Specific Biotinylation

Biotin-based labeling strategies are widely employed to study protein-protein interactions, subcellular proteomes and post-translational modifications, as well as, used in drug discovery. While the high affinity of streptavidin for biotin greatly facilitates the capture of biotinylated proteins, it still presents a challenge, as currently employed, for the recovery of biotinylated peptides. Here we describe a strategy designated Biotinylation Site Identification Technology (BioSITe) for the capture of biotinylated peptides for LC–MS/MS analyses. We demonstrate the utility of BioSITe when applied to proximity-dependent labeling methods, APEX and BioID, as well as biotin-based click chemistry strategies for identifying O-GlcNAc-modified sites. We demonstrate the use of isotopically labeled biotin for quantitative BioSITe experiments that simplify differential interactome analysis and obviate the need for metabolic labeling strategies such as SILAC. Our data also highlight the potential value of site-specific biotinylation in providing spatial and topological information about proteins and protein complexes. Overall, we anticipate that BioSITe will replace the conventional methods in studies where detection of biotinylation sites is important

A multi-omic analysis of human naïve CD4+ T cells

Background: Cellular function and diversity are orchestrated by complex interactions of fundamental biomolecules including DNA, RNA and proteins. Technological advances in genomics, epigenomics, transcriptomics and proteomics have enabled massively parallel and unbiased measurements. Such high-throughput technologies have been extensively used to carry out broad, unbiased studies, particularly in the context of human diseases. Nevertheless, a unified analysis of the genome, epigenome, transcriptome and proteome of a single human cell type to obtain a coherent view of the complex interplay between various biomolecules has not yet been undertaken. Here, we report the first multi-omic analysis of human primary naïve CD4+ T cells isolated from a single individual. Results: Integrating multi-omics datasets allowed us to investigate genome-wide methylation and its effect on mRNA/protein expression patterns, extent of RNA editing under normal physiological conditions and allele specific expression in naïve CD4+ T cells. In addition, we carried out a multi-omic comparative analysis of naïve with primary resting memory CD4+ T cells to identify molecular changes underlying T cell differentiation. This analysis provided mechanistic insights into how several molecules involved in T cell receptor signaling are regulated at the DNA, RNA and protein levels. Phosphoproteomics revealed downstream signaling events that regulate these two cellular states. Availability of multi-omics data from an identical genetic background also allowed us to employ novel proteogenomics approaches to identify individual-specific variants and putative novel protein coding regions in the human genome. Conclusions: We utilized multiple high-throughput technologies to derive a comprehensive profile of two primary human cell types, naïve CD4+ T cells and memory CD4+ T cells, from a single donor. Through vertical as well as horizontal integration of whole genome sequencing, methylation arrays, RNA-Seq, miRNA-Seq, proteomics, and phosphoproteomics, we derived an integrated and comparative map of these two closely related immune cells and identified potential molecular effectors of immune cell differentiation following antigen encounter

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