1. Quantification of the modification dynamics in TLR signaling pathways. The TLRs are a family of pathogen recognition receptors that alert the host to the presence of pathogens by recognizing molecular signatures, termed pathogen-associated molecular patterns (PAMPs). These sensors act as the first step in the induction of protective innate and adaptive immune responses. There are 11 human TLR homologues and they are each activated by one or more PAMP ligands. TLRs are all transmembrane proteins and their signaling is mediated by association of their internal domains with intracellular components. Classically, the TLR signaling cascade involves the myeloid differentiation primary response gene 88 (MyD88), interleukin-1 receptor-activated kinase (IRAK), and tumor-necrosis factor receptor-associated factor 6 (TRAF6), leading to the activation of Nuclear Factor kappaB (NF-kB). Among the most important genes to be regulated by TLR signaling are those encoding cytokines. Given the key role of cytokines in the orchestration of the inflammatory response, mechanisms of modulating their production has garnered substantial interest, in particular in the area of the development of therapies for the treatment of chronic inflammatory diseases. A clearer understanding of the TLR pathway leading to the cytokine production is required for a successful pharmacological intervention. A) We investigated differences in the phosphoprotein signaling cascades triggered by TLR2, TLR4, and TLR7 ligands using as a responding population a well-characterized murine macrophage cell line. We performed a global, quantitative, early post-stimulation kinetic analysis of the global mouse macrophage phosphoproteome using stable isotope labeling with amino acids coupled to phosphopeptide enrichment and high-resolution mass spectrometry. These results advanced our understanding of how macrophages sense and respond to a diverse set of TLR stimuli (1). We are characterizing the changes in tyrosine phosphorylation in the same conditions and obtained quantitative mass spectrometry data showing changes in tyrosine phosphorylation following LPS stimulation. We are studying the changes in phosphorylation-dependent signaling in cells where the TLR signaling pathway components (MyD88, IRAK family proteins, CD14) are knocked down or knocked out. We currently use the phosphorylation datasets as well as datasets quantifying other PTMs (ADP-ribosylation, ubiquitination) as additional constraints for a computational model of the TLR signaling network (project AI001085-07). The candidate proteins whose phosphorylation changed significantly during the investigated time course are being further examined in biological experiments. We have characterized the changes in phosphorylation of specific sites of MARCKS upon LPS stimulation and we are now exploring the biological significance of these sites. We have performed site-directed mutagenesis of the individual sites and the mutant MARCKS has been expressed in the cells where we knocked out the wild-type protein using CRISPR technology, and characterized by mass spectrometry. We are applying dimethyl labeling to studies of the PTMs in the TLR pathway in primary murine macrophages and human elutriated monocytes. B). We have conducted parallel studies of the proteome and secretome changes using the same cells and ligands as for the phosphoproteome analysis, but collecting data after longer periods of time to allow for changes in protein expression and secretion (2). We have validated the data using ELISA-based assays of cytokine production and targeted proteomics. We have performed data correlation with the transcriptome (in collaboration with Iain Fraser). We identified differences in signaling between individual TLRs and revealed specifics of pathway regulation at the protein level (3, 4). The data will provide more stringent constraints for the TLR signaling model. C). We are studying the dynamics of the MyD88-associated protein complex (myddosome) following the stimulation of mouse macrophages with pathogen-derived molecules. Our initial results indicate that MyD88 exists in macrophages in a complex with inhibitory molecules which are released after LPS stimulation, allowing the proteins activating the inflammatory response to interact with MyD88 and initiate the inflammatory signaling cascade. We have shown that the dynamics of the myddosome is proteolysis-dependent. 2. In collaboration with Dr. Yamini Dalal (NCI) we are conducting the analysis of post-translational modifications of CENP-A. In eukaryotes DNA is packaged into chromatin by essential histone proteins. Specialized histone variants such as centromere-specific histone H3 (CENP-A) provide a structural and epigenetic basis for chromosome segregation by marking centromeres. To maintain centromere parity after replication, CENP-A must segregate equally to nascent daughter DNA strands. How cells prevent unequal distribution of CENP-A to daughter strands after replication fork passage is unknown. We have characterized novel modifications within the histone fold domains of CENP-A and H4 that occur at G1-S cell cycle transition, which coincide with loss of the chaperone HJURP binding, suggesting a mechanistic basis for CENP-A structural conversion. We are continuing the detailed characterization of the modification states of CENP-A dependent on the cell cycle stage. We have recently demonstrated that while native CENP-A K124 is acetylated at G1/S, it switches to monomethylation during early S and mid-S phases (4). We are now using TAU gels for the optimal separation of histone variants to obtain comprehensive modification map of CENP-A in the primary tumor cells. The TAU gels and mass spectrometry are a novel combination of methods for histone post-translational modification analysis (5). 3. We have performed a quantitative analysis of the proteome of the cells from the terminal ileum (chosen as a site of intense host-microbe interactions) of germ-free and normal mice (collaboration with Drs. Natalia Shulzhenko and Andrey Morgun). The data showed large changes in the immune processes-related protein expression and in certain metabolic pathways. The correlation of the proteome and transcriptome data revealed several differentially regulated pathways and significant transcriptome-proteome discordance in the adaptation of the host to the microbiota. This discovery leads to a definite conclusion that transcript level analysis is not sufficient to predict protein levels and their influence on the function of many specific cellular pathways, so only the combination of the quantitative data at different levels will lead to the complete understanding of the complex relationships between the host and the microbiota (7). References: 1. Sjoelund V, Smelkinson M, and Nita-Lazar A. (2014) J Proteome Res. 2014 Nov 7;13(11):5185-97. 2. Koppenol-Raab M, Sjoelund V, Manes NP, Gottschalk RA, Dutta B, Benet ZL, Fraser ID, Nita-Lazar A. (2017) Mol Cell Proteomics 16(4 suppl 1):S172-S186. 3. Koppenol-Raab M., and Nita-Lazar A. (2017) Methods Mol Biol. 1636:301-312 4. Khan, M. M., Koppenol-Raab, M., Kuriakose, M., Manes, N. P., Goodlett, D. R., and Nita-Lazar, A. (2018) Host-pathogen dynamics through targeted secretome analysis of stimulated macrophages. J. Proteomics pii: S1874-3919(18)30111-8. 5. Bui M, Pitman M, Nuccio A, Roque S, Donlin-Asp PG,Nita-LazarA, Papoian GA, Dalal Y.(2017) Epigenetics Chromatin 10:17. 6. Nuccio A., Bui M., Dalal Y., and Nita-Lazar A. (2017) Methods Enzymol. 586:275-290 7. Manes, N.P., Shulzhenko, N., Nuccio, A.G., Azeem, S., Morgun, A,. and Nita-Lazar, A. (2017):Multi-omics comparative analysis reveals multiple layers of host signaling pathway regulation by the gut microbiota. mSystems. 2(5). pii: e00107-17.
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