Research in the Cellular Networks Proteomics Unit focuses on understanding the changes that occur in the cell proteome in response to exogenous factors such as pathogen-derived molecules, cytokines, and chemokines, which alter the differentiation state of cells in the immune system or whose production characterizes specific disease states. We are especially interested in large-scale absolute quantitative measurements of immune cell signaling cascade components and in the characterization of post-translational modification (PTM) dynamics on a global scale. We use the resulting large datasets to create predictive models of molecular interactions using the Simmune software generated by the Computational Biology Unit. The predictions of these models will in turn be employed to elucidate biological responses to stimuli at multiple scales of biological organization, including the cell, tissue, and, eventually, whole organism.
We employ mass-spectrometry-based technology together with other proteomic and biochemical methods using state-of-the art equipment and technologies available in our laboratory and at NIH.
The following are examples of our projects:
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Dr. Nita-Lazar received her Ph.D. in biochemistry in 2003 from the University of Basel for studies performed at the Friedrich Miescher Institute for Biomedical Research, where she analyzed protein glycosylation using mass spectrometry methods. After postdoctoral training at Stony Brook University and Massachusetts Institute of Technology, where she continued to investigate post-translational protein modifications and their influence on cell signaling, she joined the Program in Systems Immunology and Infectious Disease Research, now the Laboratory of Systems Biology, in April 2009.
CNPU members 2015, from left to right: (standing) Arthur Nuccio, Marijke Koppenol-Raab, Sebastian Montalvo; (sitting) Nathan Manes, Aleksandra Nita-Lazar, Casey Daniels
Manes NP, Angermann BR, Koppenol-Raab M, An E, Sjoelund VH, Sun J, Ishii M, Germain RN, Meier-Schellersheim M, Nita-Lazar A. Targeted proteomics-driven computational modeling of macrophage S1P chemosensing. Mol Cell Proteomics. 2015 Oct;14(10):2661-81.
Manes NP, Mann JM, Nita-Lazar A. Selected reaction monitoring mass spectrometry for absolute protein quantification. J Vis Exp. 2015 Aug 17;(102):e52959.
An E, Narayanan M, Manes NP, Nita-Lazar A. Characterization of functional reprogramming during osteoclast development using quantitative proteomics and mRNA profiling. Mol Cell Proteomics. 2014 Jul 20.
Sjoelund VH, Smelkinson M, Nita-Lazar A. Phosphoproteome profiling of the macrophage response to different Toll-like receptor ligands identifies differences in global phosphorylation dynamics. J Proteome Res. 2014 Jun 18. Epub ahead of print.
Germain RN, Meier-Schellersheim M, Nita-Lazar A, Fraser ID. Systems biology in immunology: a computational modeling perspective. Annu Rev Immunol. 2011 Apr 23;29:527-85.
Nita-Lazar A. Quantitative analysis of phosphorylation-based protein signaling networks in the immune system by mass spectrometry. Wiley Interdiscip Rev Syst Biol Med. 2011 May-Jun;3(3):368-76.
View complete listing in PubMed.
Last Updated March 21, 2016