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.

Cell-cycle-dependent structural transitions in the human CENP-A nucleosome in vivo.

In eukaryotes, DNA is packaged into chromatin by canonical histone proteins. The specialized histone H3 variant CENP-A provides an epigenetic and structural basis for chromosome segregation by replacing H3 at centromeres. Unlike exclusively octameric canonical H3 nucleosomes, CENP-A nucleosomes have been shown to exist as octamers, hexamers, and tetramers. An intriguing possibility reconciling these observations is that CENP-A nucleosomes cycle between octamers and tetramers in vivo. We tested this hypothesis by tracking CENP-A nucleosomal components, structure, chromatin folding, and covalent modifications across the human cell cycle. We report that CENP-A nucleosomes alter from tetramers to octamers before replication and revert to tetramers after replication. These structural transitions are accompanied by reversible chaperone binding, chromatin fiber folding changes, and previously undescribed modifications within the histone fold domains of CENP-A and H4. Our results reveal a cyclical nature to CENP-A nucleosome structure and have implications for the maintenance of epigenetic memory after centromere replication.

Recent Advancements in Subcellular Proteomics: Growing Impact of Organellar Protein Niches on the Understanding of Cell Biology.

The mammalian cell is a complex entity, with membrane-bound and membrane-less organelles playing vital roles in regulating cellular homeostasis. Organellar protein niches drive discrete biological processes and cell functions, thus maintaining cell equilibrium. Cellular processes such as signaling, growth, proliferation, motility, and programmed cell death require dynamic protein movements between cell compartments. Aberrant protein localization is associated with a wide range of diseases. Therefore, analyzing the subcellular proteome of the cell can provide a comprehensive overview of cellular biology. With recent advancements in mass spectrometry, imaging technology, computational tools, and deep machine learning algorithms, studies pertaining to subcellular protein localization and their dynamic distributions are gaining momentum. These studies reveal changing interaction networks because of "moonlighting proteins" and serve as a discovery tool for disease network mechanisms. Consequently, this review aims to provide a comprehensive repository for recent advancements in subcellular proteomics subcontexting methods, challenges, and future perspectives for method developers. In summary, subcellular proteomics is crucial to the understanding of the fundamental cellular mechanisms and the associated diseases.

Lipopolysaccharide Regulates the Macrophage RNA-Binding Proteome.

RNA-protein interactions within cellular signaling pathways have significant modulatory effects on RNA binding proteins' (RBPs') effector functions. During the innate immune response, specific RNA-protein interactions have been reported as a regulatory layer of post-transcriptional control. We investigated changes in the RNA-bound proteome of immortalized mouse macrophages (IMM) following treatment with lipopolysaccharide (LPS). Stable isotope labeling by amino acids in cell culture (SILAC) of cells followed by unbiased purification of RNP complexes at two time points after LPS stimulation and bottom-up proteomic analysis by LC-MS/MS resulted in a set of significantly affected RBPs. Global RNA sequencing and LFQ proteomics were used to characterize the correlation of transcript and protein abundance changes in response to LPS at different time points with changes in protein-RNA binding. Il1α, MARCKS, and ACOD1 were noted as RBP candidates involved in innate immune signaling. The binding sites of the RBP and RNA conjugates at amino acid resolution were investigated by digesting the cross-linked oligonucleotide from peptides remaining after elution using Nuclease P1. The combined data sets provide directions for further studies of innate immune signaling regulation by RBP interactions with different classes of RNA.

Omics and systems view of innate immune pathways.

Multiomics approaches to studying systems biology are very powerful techniques that can elucidate changes in the genomic, transcriptomic, proteomic, and metabolomic levels within a cell type in response to an infection. These approaches are valuable for understanding the mechanisms behind disease pathogenesis and how the immune system responds to being challenged. With the emergence of the COVID-19 pandemic, the importance and utility of these tools have become evident in garnering a better understanding of the systems biology within the innate and adaptive immune response and for developing treatments and preventative measures for new and emerging pathogens that pose a threat to human health. In this review, we focus on state-of-the-art omics technologies within the scope of innate immunity.

Less Severe Sepsis in Cecal Ligation and Puncture Models with and without Lipopolysaccharide in Mice with Conditional Ezh2-Deleted Macrophages (LysM-Cre System).

Despite a previous report on less inflammatory responses in mice with an absence of the enhancer of zeste homologue 2 (Ezh2), a histone lysine methyltransferase of epigenetic regulation, using a lipopolysaccharide (LPS) injection model, proteomic analysis and cecal ligation and puncture (CLP), a sepsis model that more resembles human conditions was devised. As such, analysis of cellular and secreted protein (proteome and secretome) after a single LPS activation and LPS tolerance in macrophages from Ezh2 null (Ezh2flox/flox; LysM-Crecre/-) mice (Ezh2 null) and the littermate control mice (Ezh2fl/fl; LysM-Cre-/-) (Ezh2 control) compared with the unstimulated cells from each group indicated fewer activities in Ezh2 null macrophages, especially by the volcano plot analysis. Indeed, supernatant IL-1ß and expression of genes in pro-inflammatory M1 macrophage polarization (IL-1ß and iNOS), TNF-α, and NF-κB (a transcription factor) were lower in Ezh2 null macrophages compared with the control. In LPS tolerance, downregulated NF-κB compared with the control was also demonstrated in Ezh2 null cells. In CLP sepsis mice, those with CLP alone and CLP at 2 days after twice receiving LPS injection, representing sepsis and sepsis after endotoxemia, respectively, symptoms were less severe in Ezh2 null mice, as indicated by survival analysis and other biomarkers. However, the Ezh2 inhibitor improved survival only in CLP, but not LPS with CLP. In conclusion, an absence of Ezh2 in macrophages resulted in less severe sepsis, and the use of an Ezh2 inhibitor might be beneficial in sepsis.

Less Severe Lipopolysaccharide-Induced Inflammation in Conditional mgmt-Deleted Mice with LysM-Cre System: The Loss of DNA Repair in Macrophages.

Despite the known influence of DNA methylation from lipopolysaccharide (LPS) activation, data on the O6-methylguanine-DNA methyltransferase (MGMT, a DNA suicide repair enzyme) in macrophages is still lacking. The transcriptomic profiling of epigenetic enzymes from wild-type macrophages after single and double LPS stimulation, representing acute inflammation and LPS tolerance, respectively, was performed. Small interfering RNA (siRNA) silencing of mgmt in the macrophage cell line (RAW264.7) and mgmt null (mgmtflox/flox; LysM-Crecre/-) macrophages demonstrated lower secretion of TNF-α and IL-6 and lower expression of pro-inflammatory genes (iNOS and IL-1ß) compared with the control. Macrophage injury after a single LPS dose and LPS tolerance was demonstrated by reduced cell viability and increased oxidative stress (dihydroethidium) compared with the activated macrophages from littermate control mice (mgmtflox/flox; LysM-Cre-/-). Additionally, a single LPS dose and LPS tolerance also caused mitochondrial toxicity, as indicated by reduced maximal respiratory capacity (extracellular flux analysis) in the macrophages of both mgmt null and control mice. However, LPS upregulated mgmt only in LPS-tolerant macrophages but not after the single LPS stimulation. In mice, the mgmt null group demonstrated lower serum TNF-α, IL-6, and IL-10 than control mice after either single or double LPS stimulation. Suppressed cytokine production resulting from an absence of mgmt in macrophages caused less severe LPS-induced inflammation but might worsen LPS tolerance.

Dynamic ADP-Ribosylome, Phosphoproteome, and Interactome in LPS-Activated Macrophages.

We have used mass spectrometry (MS) to characterize protein signaling in lipopolysaccharide (LPS)-stimulated macrophages from human blood, human THP1 cells, mouse bone marrow, and mouse Raw264.7 cells. Protein ADP-ribosylation was truncated down to phosphoribose, allowing for enrichment and identification of the resulting phosphoribosylated peptides alongside phosphopeptides. Size exclusion chromatography-MS (SEC-MS) was used to separate proteoforms by size; protein complexes were then identified by weighted correlation network analysis (WGCNA) based on their correlated movement into or out of SEC fractions following stimulation, presenting an analysis method for SEC-MS that does not rely on established databases. We highlight two modules of interest: one linked to the apoptosis signal-regulating kinase (ASK) signalosome and the other containing poly(ADP-ribose) polymerase 9 (PARP9). Finally, PARP inhibition was used to perturb the characterized systems, demonstrating the importance of ADP-ribosylation for the global interactome. All post-translational modification (PTM) and interactome data have been aggregated into a meta-database of 6729 proteins, with ADP-ribosylation characterized on 2905 proteins and phosphorylation characterized on 2669 proteins. This database-titled MAPCD, for Macrophage ADP-ribosylation, Phosphorylation, and Complex Dynamics-serves as an invaluable resource for studying crosstalk between the ADP-ribosylome, phosphoproteome, and interactome.

Approaching complexity: systems biology and ms-based techniques to address immune signaling.

INTRODUCTION: Studying immune signaling has been critical for our understanding of immunology, pathogenesis, cancer, and homeostasis. To enhance the breadth of the analysis, high throughput methods have been developed to survey multiple areas simultaneously, including transcriptomics, reporter assays, and ELISAs. While these techniques have been extremely informative, mass-spectrometry-based technologies have been gaining momentum and starting to be widely used in the studies of immune signaling and systems immunology. AREAS COVERED: We present established proteomic methods that have been used to address immune signaling and discuss the new mass-spectrometry- based techniques of interest to the expanding field of systems immunology. Established and new proteomic methods and their applications discussed here include post-translational modification analysis, protein quantification, secretome analysis, and interactomics. In addition, we present developments in small molecule and metabolite analysis, mass spectrometry imaging, and single cell analysis. Finally, we discuss the role of multi-omic integration in aiding leading edge investigation. EXPERT OPINION: In science, available techniques enhance the breadth and depth of the studies. By incorporating proteomic techniques and their innovative use, it will be possible to expand the current studies and to address novel questions at the forefront of scientific discovery.

Proteome and Secretome Analysis Reveals Differential Post-transcriptional Regulation of Toll-like Receptor Responses.

The innate immune system is the organism's 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.

Decreased Protein Kinase C-ß Type II Associated with the Prominent Endotoxin Exhaustion in the Macrophage of FcGRIIb-/- Lupus Prone Mice is Revealed by Phosphoproteomic Analysis.

Dysfunction of FcGRIIb, the only inhibitory receptor of the FcGR family, is commonly found in the Asian population and is possibly responsible for the extreme endotoxin exhaustion in lupus. Here, the mechanisms of prominent endotoxin (LPS) tolerance in FcGRIIb-/- mice were explored on bone marrow-derived macrophages using phosphoproteomic analysis. As such, LPS tolerance decreased several phosphoproteins in the FcGRIIb-/- macrophage, including protein kinase C-ß type II (PRKCB), which was associated with phagocytosis function. Overexpression of PRKCB attenuated LPS tolerance in RAW264.7 cells, supporting the role of this gene in LPS tolerance. In parallel, LPS tolerance in macrophages and in mice was attenuated by phorbol 12-myristate 13-acetate (PMA) administration. This treatment induced several protein kinase C families, including PRKCB. However, PMA attenuated the severity of mice with cecal ligation and puncture on LPS tolerance preconditioning in FcGRIIb-/- but not in wild-type cells. The significant reduction of PRKCB in the FcGRIIb-/- macrophage over wild-type cell possibly induced the more severe LPS-exhaustion and increased the infection susceptibility in FcGRIIb-/- mice. PMA induced PRKCB, improved LPS-tolerance, and attenuated sepsis severity, predominantly in FcGRIIb-/- mice. PRKCB enhancement might be a promising strategy to improve macrophage functions in lupus patients with LPS-tolerance from chronic infection.

The development of SRM assays is transforming proteomics research.

Bottom-up targeted proteomics using SRM is a powerful analytical technology, but it requires the development of SRM assays, which is a complex procedure. Whereas proteome-wide SRM assays have recently been developed for a small number of species, this is not so for the mouse. In this issue, Percy et al. report the development of hundreds of mouse SRM assays. Their development required shotgun MS to identify proteotypic peptides, synthesis, and LC-MS characterization of peptide standards, and interlaboratory SRM to robustly assess the quality of the assays. The resulting SRM assays are intended to be used to analyze mouse plasma and cardiac tissue, primarily for cardiovascular disease and cancer research.

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.

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.

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.

Rumi functions as both a protein O-glucosyltransferase and a protein O-xylosyltransferase.

Mutations in rumi result in a temperature-sensitive loss of Notch signaling in Drosophila. Drosophila Rumi is a soluble, endoplasmic reticulum-retained protein with a CAP10 domain that functions as a protein O-glucosyltransferase. In human and mouse genomes, three potential Rumi homologues exist: one with a high degree of identity to Drosophila Rumi (52%), and two others with lower degrees of identity but including a CAP10 domain (KDELC1 and KDELC2). Here we show that both mouse and human Rumi, but not KDELC1 or KDELC2, catalyze transfer of glucose from UDP-glucose to an EGF repeat from human factor VII. Similarly, human Rumi, but not KDELC1 or KDELC2, rescues the Notch phenotypes in Drosophila rumi clones. During characterization of the Rumi enzymes, we noted that, in addition to protein O-glucosyltransferase activity, both mammalian and Drosophila Rumi also showed significant protein O-xylosyltransferase activity. Rumi transfers Xyl or glucose to serine 52 in the O-glucose consensus sequence ( ) of factor VII EGF repeat. Surprisingly, the second serine (S53) facilitates transfer of Xyl, but not glucose, to the EGF repeat by Rumi. EGF16 of mouse Notch2, which has a diserine motif in the consensus sequence ( ), is also modified with either O-Xyl or O-glucose glycans in cells. Mutation of the second serine (S590A) causes a loss of O-Xyl but not O-glucose at this site. Altogether, our data establish dual substrate specificity for the glycosyltransferase Rumi and provide evidence that amino acid sequences of the recipient EGF repeat significantly influence which donor substrate (UDP-glucose or UDP-Xyl) is used.

The Legionella pneumophila effector DenR hijacks the host NRas proto-oncoprotein to downregulate MAPK signaling.

Small GTPases of the Ras subfamily are best known for their role as proto-oncoproteins, while their function during microbial infection has remained elusive. Here, we show that Legionella pneumophila hijacks the small GTPase NRas to the Legionella-containing vacuole (LCV) surface. A CRISPR interference screen identifies a single L. pneumophila effector, DenR (Lpg1909), required for this process. Recruitment is specific for NRas, while its homologs KRas and HRas are excluded from LCVs. The C-terminal hypervariable tail of NRas is sufficient for recruitment, and interference with either NRas farnesylation or S-acylation sites abrogates recruitment. Intriguingly, we detect markers of active NRas signaling on the LCV, suggesting it acts as a signaling platform. Subsequent phosphoproteomics analyses show that DenR rewires the host NRas signaling landscape, including dampening of the canonical mitogen-activated protein kinase pathway. These results provide evidence for L. pneumophila targeting NRas and suggest a link between NRas GTPase signaling and microbial infection.

Human ESCRT-I and ALIX function as scaffolding helical filaments in vivo.

The Endosomal Sorting Complex Required for Transport (ESCRT) is an evolutionarily conserved machinery that performs reverse-topology membrane scission in cells universally required from cytokinesis to budding of enveloped viruses. Upstream acting ESCRT-I and ALIX control these events and link recruitment of viral and cellular partners to late-acting ESCRT-III CHMP4 through incompletely understood mechanisms. Using structure-function analyses combined with super-resolution imaging, we show that ESCRT-I and ALIX function as distinct helical filaments in vivo . Together, they are essential for optimal structural scaffolding of HIV-1 nascent virions, the retention of viral and human genomes through defined functional interfaces, and recruitment of CHMP4 that itself assembles into corkscrew-like filaments intertwined with ESCRT-I or ALIX helices. Disruption of filament assembly or their conformationally clustered RNA binding interfaces in human cells impaired membrane abscission, resulted in major structural instability and leaked nucleic acid from nascent virions and nuclear envelopes. Thus, ESCRT-I and ALIX function as helical filaments in vivo and serve as both nucleic acid-dependent structural scaffolds as well as ESCRT-III assembly templates. Significance statement: When cellular membranes are dissolved or breached, ESCRT is rapidly deployed to repair membranes to restore the integrity of intracellular compartments. Membrane sealing is ensured by ESCRT-III filaments assembled on the inner face of membrane; a mechanism termed inverse topology membrane scission. This mechanism, initiated by ESCRT-I and ALIX, is universally necessary for cytokinesis, wound repair, budding of enveloped viruses, and more. We show ESCRT-I and ALIX individually oligomerize into helical filaments that cluster newly discovered nucleic acid-binding interfaces and scaffold-in genomes within nascent virions and nuclear envelopes. These oligomers additionally appear to serve as ideal templates for ESCRT-III polymerization, as helical filaments of CHMP4B were found intertwined ESCRT-I or ALIX filaments in vivo . Similarly, corkscrew-like filaments of ALIX are also interwoven with ESCRT-I, supporting a model of inverse topology membrane scission that is synergistically reinforced by inward double filament scaffolding.

EnsMOD: A Software Program for Omics Sample Outlier Detection.

Detection of omics sample outliers is important for preventing erroneous biological conclusions, developing robust experimental protocols, and discovering rare biological states. Two recent publications describe robust algorithms for detecting transcriptomic sample outliers, but neither algorithm had been incorporated into a software tool for scientists. Here we describe Ensemble Methods for Outlier Detection (EnsMOD) which incorporates both algorithms. EnsMOD calculates how closely the quantitation variation follows a normal distribution, plots the density curves of each sample to visualize anomalies, performs hierarchical cluster analyses to calculate how closely the samples cluster with each other, and performs robust principal component analyses to statistically test if any sample is an outlier. The probabilistic threshold parameters can be easily adjusted to tighten or loosen the outlier detection stringency. EnsMOD can be used to analyze any omics dataset with normally distributed variance. Here it was used to analyze a simulated proteomics dataset, a multiomic (proteome and transcriptome) dataset, a single-cell proteomics dataset, and a phosphoproteomics dataset. EnsMOD successfully identified all of the simulated outliers, and subsequent removal of a detected outlier improved data quality for downstream statistical analyses.