Aleksandra Nita-Lazar

Systems Biology in Immunology: A Computational Modeling Perspective*

Systems biology is an emerging discipline that combines high-content, multiplexed measurements with informatic and computational modeling methods to better understand biological function at various scales. Here we present a detailed review of the methods used to create computational models and to conduct simulations of immune function. We provide descriptions of the key data-gathering techniques employed to generate the quantitative and qualitative data required for such modeling and simulation and summarize the progress to date in applying these tools and techniques to questions of immunological interest, including infectious disease. We include comments on what insights modeling can provide that complement information obtained from the more familiar experimental discovery methods used by most investigators and the reasons why quantitative methods are needed to eventually produce a better understanding of immune system operation in health and disease.

Phosphoproteome Profiling of the Macrophage Response to Different Toll-Like Receptor Ligands Identifies Differences in Global Phosphorylation Dynamics

Toll-like receptors (TLRs) are among the first sensors that detect infection and drive immune response. Macrophages encountering a pathogen are usually stimulated not by one TLR, but by a combination of TLRs engaged by distinct microbe ligands. To understand the integrated signaling under complex conditions, we investigated the differences in the phosphoprotein signaling cascades triggered by TLR2, TLR4, and TLR7 ligands using a single responding cell population. We performed a global, quantitative, early poststimulation kinetic analysis of the mouse macrophage phosphoproteome using stable isotope labeling with amino acids coupled to phosphopeptide enrichment and high-resolution mass spectrometry. For each TLR ligand, we found marked elevation of phosphorylation of cytoskeleton components, GTPases of the Rho family, and phospholipase C signaling pathway proteins. Phosphorylation of proteins involved in phagocytosis was only seen in response to TLR2 and TLR4 but not to TLR7 activation. Changes in the phosphorylation of proteins involved in endocytosis were delayed in response to TLR2 as compared to TLR4 ligands. These findings reveal that the phosphoproteomic response to stimulation of distinct TLRs varies both in the major modification targets and the phosphorylation dynamics. These results advance the understanding of how macrophages sense and respond to a diverse set of TLR stimuli.

Quantitative analysis of phosphorylation-based protein signaling networks in the immune system by mass spectrometry

Dynamic modification of cell proteins with phosphate is one of the key regulators of the cellular response to external stimuli. Phosphorylation‐based signaling networks mediate cell proliferation, differentiation, and migration, and their dysregulation is the basis of multiple diseases. However, the transient nature of the regulatory protein phosphorylation and low site occupancy mean that only a fraction of the protein is phosphorylated at a given time, and it is a challenge to measure the degree and dynamics of phosphorylation using traditional biochemical means. Technological advances in the field of mass spectrometry (MS) made it possible to generate large sets of phosphoproteomics data, probing the phosphoproteome with great depth, sensitivity, and accuracy. Therefore, quantitative phosphoproteomics emerged as one of the essential components of the systems biology approach for profiling of complex biological networks. Nowadays, the challenge lies in validation of the information and in its integration into the comprehensive models of cell decision processes. This article reviews the role of phosphoproteomics in systems biology, the MS‐based approach, and technical details of the methods. Recent examples of quantitative measurements and methodologies as well as applications to the studies of the immune system and infectious diseases are presented and discussed. WIREs Syst Biol Med 2011 3 368–376 DOI: 10.1002/wsbm.123

Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification.

Absolute quantification of target proteins within complex biological samples is critical to a wide range of research and clinical applications. This protocol provides step-by-step instructions for the development and application of quantitative assays using selected reaction monitoring (SRM) mass spectrometry (MS). First, likely quantotypic target peptides are identified based on numerous criteria. This includes identifying proteotypic peptides, avoiding sites of posttranslational modification, and analyzing the uniqueness of the target peptide to the target protein. Next, crude external peptide standards are synthesized and used to develop SRM assays, and the resulting assays are used to perform qualitative analyses of the biological samples. Finally, purified, quantified, heavy isotope labeled internal peptide standards are prepared and used to perform isotope dilution series SRM assays. Analysis of all of the resulting MS data is presented. This protocol was used to accurately assay the absolute abundance of proteins of the chemotaxis signaling pathway within RAW 264.7 cells (a mouse monocyte/macrophage cell line). The quantification of Gi2 (a heterotrimeric G-protein α-subunit) is described in detail.

Characterization of functional reprogramming during osteoclast development using quantitative proteomics and mRNA profiling

In addition to forming macrophages and dendritic cells, monocytes in adult peripheral blood retain the ability to develop into osteoclasts, mature bone-resorbing cells. The extensive morphological and functional transformations that occur during osteoclast differentiation require substantial reprogramming of gene and protein expression. Here we employ -omic-scale technologies to examine in detail the molecular changes at discrete developmental stages in this process (precursor cells, intermediate osteoclasts, and multinuclear osteoclasts), quantitatively comparing their transcriptomes and proteomes. The data have been deposited to the ProteomeXchange with identifier PXD000471. Our analysis identified mitochondrial changes, along with several alterations in signaling pathways, as central to the development of mature osteoclasts, while also confirming changes in pathways previously implicated in osteoclast biology. In particular, changes in the expression of proteins involved in metabolism and redirection of energy flow from basic cellular function toward bone resorption appeared to play a key role in the switch from monocytic immune system function to specialized bone-turnover function. These findings provide new insight into the differentiation program involved in the generation of functional osteoclasts.

Targeted Proteomics-Driven Computational Modeling of Macrophage S1P Chemosensing.

Osteoclasts are monocyte-derived multinuclear cells that directly attach to and resorb bone. Sphingosine-1-phosphate (S1P)1 regulates bone resorption by functioning as both a chemoattractant and chemorepellent of osteoclast precursors through two G-protein coupled receptors that antagonize each other in an S1P-concentration-dependent manner. To quantitatively explore the behavior of this chemosensing pathway, we applied targeted proteomics, transcriptomics, and rule-based pathway modeling using the Simmune toolset. RAW264.7 cells (a mouse monocyte/macrophage cell line) were used as model osteoclast precursors, RNA-seq was used to identify expressed target proteins, and selected reaction monitoring (SRM) mass spectrometry using internal peptide standards was used to perform absolute abundance measurements of pathway proteins. The resulting transcript and protein abundance values were strongly correlated. Measured protein abundance values, used as simulation input parameters, led to in silico pathway behavior matching in vitro measurements. Moreover, once model parameters were established, even simulated responses toward stimuli that were not used for parameterization were consistent with experimental findings. These findings demonstrate the feasibility and value of combining targeted mass spectrometry with pathway modeling for advancing biological insight.

Internal modifications in the CENP-A nucleosome modulate centromeric dynamics

BackgroundPosttranslational modifications of core histones are correlated with changes in transcriptional status, chromatin fiber folding, and nucleosome dynamics. However, within the centromere-specific histone H3 variant CENP-A, few modifications have been reported, and their functions remain largely unexplored. In this multidisciplinary report, we utilize in silico computational and in vivo approaches to dissect lysine 124 of human CENP-A, which was previously reported to be acetylated in advance of replication.ResultsComputational modeling demonstrates that acetylation of K124 causes tightening of the histone core and hinders accessibility to its C-terminus, which in turn diminishes CENP-C binding. Additionally, CENP-A K124ac/H4 K79ac containing nucleosomes are prone to DNA sliding. In vivo experiments using a CENP-A acetyl or unacetylatable mimic (K124Q and K124A, respectively) reveal alterations in CENP-C levels and a modest increase in mitotic errors. Furthermore, mutation of K124 results in alterations in centromeric replication timing. Purification of native CENP-A proteins followed by mass spectrometry analysis reveals that while CENP-A K124 is acetylated at G1/S, it switches to monomethylation during early S and mid-S phases. Finally, we provide evidence implicating the histone acetyltransferase (HAT) p300 in this cycle.ConclusionsTaken together, our data suggest that cyclical modifications within the CENP-A nucleosome contribute to the binding of key kinetochore proteins, the integrity of mitosis, and centromeric replication. These data support the paradigm that modifications in histone variants can influence key biological processes.

Proteome and secretome analysis reveals differential post-transcriptional regulation of Toll-like receptor responses

The innate immune system is the organisms first line of defense against pathogens. Pattern recognition receptors (PRRs) are responsible for sensing the presence of pathogen-associated molecules. The prototypic PRRs, the membrane-bound receptors of the Toll-like receptor (TLR) family, recognize pathogen-associated molecular patterns (PAMPs) and initiate an innate immune response through signaling pathways that depend on the adaptor molecules MyD88 and TRIF. Deciphering the differences in the complex signaling events that lead to pathogen recognition and initiation of the correct response remains challenging. Here we report the discovery of temporal changes in the protein signaling components involved in innate immunity. Using an integrated strategy combining unbiased proteomics, transcriptomics and macrophage stimulations with three different PAMPs, we identified differences in signaling between individual TLRs and revealed specifics of pathway regulation at the protein level.

Host-pathogen dynamics through targeted secretome analysis of stimulated macrophages

The pattern recognition receptors (PRRs) facilitate an organisms first line of defense against interlopers and shape the overall innate immune response through sensing and sampling pathogen-associated molecular patterns (PAMPs). The Toll-like receptor (TLR) family is the prototypic PRR family. Upon recognition of PAMPs, TLRs promote MyD88 dependent and independent responses. Understanding how different PAMPs are recognized by their specific TLRs and how pathogen recognition initiates immune activation is an intense area of research. Previously, we have reported the discovery of the temporal changes in signaling cascades of macrophage proteome and secretome post-stimulation with three different PAMPs. To extend our global proteomics approach to targeted protein abundance quantification, we describe the macrophage secretome targeted proteomics assay. We chose three different pathogens that specifically stimulate diverse TLRs (TLR2, TLR4, and TLR7). Using a simple targeted proteomics approach, combining data-dependent acquisition with an inclusion list, an array of cytokines, chemokines, and transcription factors can be profiled for their secretome abundance. This strategy facilitates the profiling and validation of pathogen-specific temporal changes in the macrophage secretome.

Mass Spectrometry-based Structural Analysis and Systems Immunoproteomics Strategies for Deciphering the Host Response to Endotoxin

One cause of sepsis is systemic maladaptive immune response of the host to bacteria and specifically, to Gram-negative bacterial outer-membrane glycolipid lipopolysaccharide (LPS). On the host myeloid cell surface, proinflammatory LPS activates the innate immune system via Toll-like receptor-4/myeloid differentiation factor-2 complex. Intracellularly, LPS is also sensed by the noncanonical inflammasome through caspase-11 in mice and 4/5 in humans. The minimal functional determinant for innate immune activation is the membrane anchor of LPS called lipid A. Even subtle modifications to the lipid A scaffold can enable, diminish, or abolish immune activation. Bacteria are known to modify their LPS structure during environmental stress and infection of hosts to alter cellular immune phenotypes. In this review, we describe how mass spectrometry-based structural analysis of endotoxin helped uncover major determinations of molecular pathogenesis. Through characterization of LPS modifications, we now better understand resistance to antibiotics and cationic antimicrobial peptides, as well as how the environment impacts overall endotoxin structure. In addition, mass spectrometry-based systems immunoproteomics approaches can assist in elucidating the immune response against LPS. Many regulatory proteins have been characterized through proteomics and global/targeted analysis of protein modifications, enabling the discovery and characterization of novel endotoxin-mediated protein translational modifications.