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Aleksandra Nita-Lazar, Ph.D.

Photo of Aleksandra Nita-Lazar, Ph.D. 

Chief, Cellular Networks Proteomics Unit

Tenure Track Investigator

Laboratory of Systems Biology

Major Areas of Research

  • Protein modifications involved in cell signaling
  • Absolute quantification of molecular representation and interaction

Program Description

Research in the Cellular Networks Proteomics Unit focuses on understanding the changes that occur in the cell proteome in response to various stimuli such as cytokines or pathogen-derived molecules, which alter the differentiation state of cells in the immune system or whose production characterizes various disease states. We are especially interested in large-scale absolute quantitative measurements of components in immune cell signaling networks. We will use the resulting large datasets, combined with the data generated by the high-throughput screening efforts of the Signaling Systems Unit and the microarray/next-generation sequencing data from the Systems Genomics and Bioinformatics Unit and Lymphocyte Biology Section, to create predictive models of molecular interactions using the software generated by the Computational Biology Unit. The predictions of these models will in turn be employed to better understand biological responses at multiple scales of biological organization, including the cell, tissue, and, eventually, whole organism.

Our primary experimental approach to generating the necessary datasets is mass spectrometry, which we will employ together with other proteomic methods using state-of-the art equipment and technologies available in our laboratory and at the National Institutes of Health.

The following are examples of our projects:

  • Protein modifications involved in cell signaling: Because dynamic post-translational modifications (PTMs) are essential for the regulation of cell signaling, it is crucial to quantify the PTMs of proteins involved in signaling cascades. Examples of our interests include Toll-like receptor (TLR) signaling in macrophages or T-cell antigen receptor (TCR) signaling.
  • Absolute quantification of molecular representation and interaction: Mathematical modeling of biological events is most reliable when the absolute quantities of molecules are known and used to set parameters in the simulations. Therefore, we are interested in absolute quantification of protein expression and protein-protein interactions, e.g., in the lipid-induced signaling pathways involving the S1P1 and S1P2 receptors in osteoclast precursors that control cell mobilization at bone surfaces (Ishii M et al., Nature 458, 2009).

Special Interest Groups

  • Proteomics
  • Mass Spectrometry
  • Immunology
  • Systems Biology

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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.

Research Group

CNPU members 2015, from left to right: (standing) Arthur Nuccio, Marijke Koppenol-Raab, Sebastian Montalvo; (sitting) Nathan Manes, Aleksandra Nita-Lazar, Casey Daniels

CNPU members 2015, from left to right: (standing) Arthur Nuccio, Marijke Koppenol-Raab, Sebastian Montalvo; (sitting) Nathan Manes, Aleksandra Nita-Lazar, Casey Daniels

Selected Publications

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.

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Last Updated November 17, 2015