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Review
. 2014;32:547-77.
doi: 10.1146/annurev-immunol-032713-120254.

Systems-level Analysis of Innate Immunity

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Free PMC article
Review

Systems-level Analysis of Innate Immunity

Daniel E Zak et al. Annu Rev Immunol. .
Free PMC article

Abstract

Systems-level analysis of biological processes strives to comprehensively and quantitatively evaluate the interactions between the relevant molecular components over time, thereby enabling development of models that can be employed to ultimately predict behavior. Rapid development in measurement technologies (omics), when combined with the accessible nature of the cellular constituents themselves, is allowing the field of innate immunity to take significant strides toward this lofty goal. In this review, we survey exciting results derived from systems biology analyses of the immune system, ranging from gene regulatory networks to influenza pathogenesis and systems vaccinology.

Figures

Figure 1
Figure 1
Omics measurements—more than high throughput. (a) Conventional targeted measurement of mRNA levels—for example, by qRT-PCR—produces a measurement that can be used to make inferences about the levels of the encoded protein. (b) Although genome-level assessment of mRNA levels—for example, by RNA-Seq transcriptomics—may be similarly employed to make inferences about encoded proteins, the unbiased and systematic nature of the transcriptome measurement also allows it to be interpreted as a holistic readout of all gene regulatory activities within the cell. Transcriptomes interpreted in this manner may be interrogated by network analysis to make inferences about the activities of transcription factors, RNA-binding proteins, and miRNAs that result in differential transcriptome patterns across varying conditions.
Figure 2
Figure 2
The iterative cycle of systems biology. Biology dictates what new technology and computational tools must be developed to answer specific questions. In turn, newly developed technologies and tools open new frontiers, revolutionizing biology and generating new fields of inquiry. (Figure adapted from Reference .)
Figure 3
Figure 3
The FOXO3/IRF7 regulatory network fine-tunes the antiviral response. (a) Model of FOXO3 regulation of IRF7-dependent gene expression and implications for fine-tuning of the antiviral response. (b) Hematoxylin and eosin staining of lung tissue sections from wild-type (WT), Foxo3−/−, and Irf7−/− mice 0, 2, and 5 days after intranasal infection with vesicular stomatitis virus serotype Indiana 105 plaque-forming units (p.f.u.). Data are from one experiment representative of three independent experiments (n = 6 mice per group). (Figure adapted from Reference .)
Figure 4
Figure 4
Contextualizing Sharpin within the NF-κB pathway by comparative analysis of mutant transcriptomes. (a) The heat map shows the effects of numerous mutations on 284 genes robustly induced by Pam3 (12 h) in macrophages. Blue indicates impaired gene induction compared to wild type, whereas pink indicates enhanced gene induction compared to wild type. The mutant with the most similar responses to Sharpincpdm was Nemopanr2 (correlation coefficient = 0.82). (b) SHARPIN is an essential adaptor downstream of the branch point defined by the panr2 mutation in NEMO. The signaling responses most strongly impaired by SHARPIN deficiency and NEMO L153P (panr2) are the phosphorylation of p105 and ERK, suggesting that p105 IκB activity and Tpl2 sequestration are dominant regulators of Toll-like receptor 2 (TLR2)-induced proinflammatory cytokine expression (left). The greater deficiency in signaling and proinflammatory cytokine induction observed in panr2 compared with cpdm macrophages may result from SHARPIN-independent interactions between NEMO and the SHARPIN paralog RBCK1, which are also abrogated by NEMO L153P. TLR2-induced IκBα degradation, phosphorylation of p38 and c-Jun terminal kinase (JNK), and Nfkbia gene induction were unimpaired in cpdm macrophages and panr2 mutant macrophages, implying the existence of a branch of NEMO-dependent IκB kinase (IKK) and mitogen-activated protein kinase (MAPK) activity that proceeds independently of SHARPIN and NEMO L153 (right). (Figure adapted from Reference .)
Figure 5
Figure 5
High-throughput chromatin immunoprecipitation coupled to next generation sequencing (ChIP-Seq) systematically maps protein-DNA interactions. Systematically profiling protein-DNA interactions in the innate immune response facilitates the discovery of the hierarchical genome-wide organization of transcription factors. Amit and colleagues (31) discovered that in LPS-stimulated BMDCs, transcription factors can function as differentiation regulators, priming factors for transcriptional induction, and regulators of specific gene programs. (Reproduced with permission from Reference .)
Figure 6
Figure 6
Transcriptional analysis reveals a critical role for neutrophil recruitment in driving lethal influenza infection. Germain and colleagues (73) performed detailed comparative transcriptional analysis of lung tissue during influenza infection and identified a transcriptional module “A-8” that was strongly associated with lethality. Analysis of the A-8 module implicated inflammatory pathways and neutrophils in the pathogenesis of lethal influenza. (a) Inflammatory network indicating signaling components elevated in module A-8 (outline red) and preferential constitutive (green) and/or inducible (yellow) expression in neutrophils. (b) Neutrophil samples exhibit highest expression of downstream genes from inflammatory signaling cascades. (Reproduced with permission from Reference .)
Figure 7
Figure 7
Lipidomic analysis of influenza infection. (a) Lipoxygenase (LOX) metabolism pathway of arachidonic acid. Rectangular boxes represent the enzyme catalyzing the reaction. Circles represent the lipid mediators within the pathway. (b) Stacked bar graph representing the percentages of 5-, 15-, 12-, or 8-LOX-derived metabolites of all lipoxygenase-derived metabolites in mouse and human samples. Each vertical line represents data from a single sample (n = 8–11 per time point or group). (Figure adapted from Reference .)
Figure 8
Figure 8
Systems-level analysis of the Step Study HIV vaccine. (a) MRKAd5/HIV induces interferon response genes and represses lymphoid cell–associated genes. This effect is shown in a gene module (117) radar plot in which the axes indicate the average expression of specific functional gene modules (“M” followed by a number). Responses are attenuated in moderate Ad5 neutralizing antibody (nAb) titer (green lines) compared with low nAb titer (black line) volunteers. (b) As an example, induction of IP-10 (CXCL10) transcript by MRKAd5/HIV was attenuated in moderate Ad5 nAb titer (dark green) compared with low (light green) and zero (gray) titer volunteers. (c) MRKAd5/HIV induces transcriptional responses that involve more genes but are shorter-lived than YF-17D. (d) A subset of MRKAd5/HIV innate immune response genes (72 h postvaccination) are associated with HIV-specific CD8+ T cell responses (1 month postvaccination). For example, CRIP3 is inversely correlated with both MRKAd5/HIV- and YF-17D–induced CD8+ T cell responses. (Figure adapted from Reference .)

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