Systems Immunology Approaches Research Articles

Systems Immunology Approaches to Understanding Immune Responses in Acute Infection of Yellow Fever Patients.

In the 2018 yellow fever (YF) outbreak in Brazil, we generated new transcriptomic data and combined it with clinical and immunological data to decode the pathogenesis of YF. Analyzing 79 patients, we found distinct gene expression patterns between acute YF, other viral infections, and the milder YF-17D vaccine infection. We identified a critical role for low-density, immature neutrophils in severe outcomes, marked by the downregulation of genes essential for neutrophil migration and maturation, such as PADI4, CSF3R, and ICAM1, in deceased patients. Our study also revealed complex interactions among inflammation-related genes, including increased CXCL10 and IL1R2 expression and decreased IL-1b expression in the acute phase. The diminished expression of HLA class II genes indicates impaired antigen presentation. These findings highlight the delicate balance of immune responses in YF pathogenesis and lay the groundwork for future therapeutic and diagnostic advancements.

An interactive web application for exploring systemic lupus erythematosus blood transcriptomic diversity.

In the field of complex autoimmune diseases such as systemic lupus erythematosus (SLE), systems immunology approaches have proven invaluable in translational research settings. Large-scale datasets of transcriptome profiling have been collected and made available to the research community in public repositories, but remain poorly accessible and usable by mainstream researchers. Enabling tools and technologies facilitating investigators' interaction with large-scale datasets such as user-friendly web applications could promote data reuse and foster knowledge discovery. Microarray blood transcriptomic data from the LUPUCE cohort (publicly available on Gene Expression Omnibus, GSE49454), which comprised 157 samples from 62 adult SLE patients, were analyzed with the third-generation (BloodGen3) module repertoire framework, which comprises modules and module aggregates. These well-characterized samples corresponded to different levels of disease activity, different types of flares (including biopsy-proven lupus nephritis), different auto-antibody profiles and different levels of interferon signatures. A web application was deployed to present the aggregate-level, module-level and gene-level analysis results from LUPUCE dataset. Users can explore the similarities and heterogeneity of SLE samples, navigate through different levels of analysis, test hypotheses and generate custom fingerprint grids and heatmaps, which may be used in reports or manuscripts. This resource is available via this link: https://immunology-research.shinyapps.io/LUPUCE/. This web application can be employed as a stand-alone resource to explore changes in blood transcript profiles in SLE, and their relation to clinical and immunological parameters, to generate new research hypotheses.

The diverse landscape of memory T-cell heterogeneity.

The diverse landscape of memory T-cell heterogeneity.

Prenylcysteine oxidase 1 like protein is required for neutrophil bactericidal activities

The bactericidal function of neutrophils is dependent on a myriad of intrinsic and extrinsic stimuli. Using systems immunology approaches we identify microbiome- and infection-induced changes in neutrophils. We focus on investigating the Prenylcysteine oxidase 1 like (Pcyox1l) protein function. Murine and human Pcyox1l proteins share ninety four percent aminoacid homology revealing significant evolutionary conservation and implicating Pcyox1l in mediating important biological functions. Here we show that the loss of Pcyox1l protein results in significant reductions in the mevalonate pathway impacting autophagy and cellular viability under homeostatic conditions. Concurrently, Pcyox1l CRISPRed-out neutrophils exhibit deficient bactericidal properties. Pcyox1l knock-out mice demonstrate significant susceptibility to infection with the gram-negative pathogen Psuedomonas aeruginosa exemplified through increased neutrophil infiltrates, hemorrhaging, and reduced bactericidal functionality. Cumulatively, we ascribe a function to Pcyox1l protein in modulation of the prenylation pathway and suggest connections beween metabolic responses and neutrophil functionality.

Comparative single-cell transcriptome analysis informs early innate immune response in severe human burns

Abstract Proper wound healing requires a coordinated time-dependent balance of immune pathways to prevent irreversible systemic damage. Given that innate immune cells are first to mobilize to sites of injury, we hypothesize that neutrophils, macrophages, and their interactions are associated with burn severity. To test this, we employed systems immunology and bioinformatics approaches utilizing single-cell transcriptome (scRNA-Seq) in model organisms and large-scale bulk transcriptome of human burns. To this end, we generated the first to-date scRNA-Seq atlas of 6,671 neutrophils and 12,560 macrophages from a time-course zebrafish tail burn model. Our data unveiled transcriptionally distinct subsets that present different dynamics during the wound healing process. We identified the granularity of IL6-IL6R interactions between macrophages and neutrophils, which impair neutrophil recruitment to sterile thermal injury, making the area vulnerable to microbial invasion and subsequent infection. Furthermore, we generated a comprehensive cross-species reference of neutrophils and macrophages in injury models by integrating publicly available mice scRNA-Seq with our zebrafish data. This reference allows us to deconvolute bulk transcriptome data from different published human cohorts and discover signatures of early innate immune cells associated with burn severity in humans. Our discovery demonstrates the power of using comparative bioinformatics approach to better understand the innate immune system during wound healing. In the future, these advances will guide interventional genomics approaches to identify druggable pathways to optimize burn wound healing in human patients.

Systems Immunology Approaches to Metabolism

Over the last decade, immunometabolism has emerged as a novel interdisciplinary field of research and yielded significant fundamental insights into the regulation of immune responses. Multiple classical approaches to interrogate immunometabolism, including bulk metabolic profiling and analysis of metabolic regulator expression, paved the way to appreciating the physiological complexity of immunometabolic regulation in vivo. Studying immunometabolism at the systems level raised the need to transition towards the next-generation technology for metabolic profiling and analysis. Spatially resolved metabolic imaging and computational algorithms for multi-modal data integration are new approaches to connecting metabolism and immunity. In this review, we discuss recent studies that highlight the complex physiological interplay between immune responses and metabolism and give an overview of technological developments that bear the promise of capturing this complexity most directly and comprehensively.

T helper cell subsets: diversification of the field.

Polarized T helper cell (Th cell) responses are important determinants of host protection. Th cell subsets tailor their functional repertoire of cytokines to their cognate antigens to efficiently contribute to their clearance. In contrast, in settings of immune abrogation, these polarized cytokine patterns of Th cells can mediate tissue damage and pathology resulting in allergy or autoimmunity. Recent technological developments in single-cell genomics and proteomics as well as advances in the high-dimensional bioinformatic analysis of complex datasets have challenged the prevailing Th cell subset classification into Th1, Th2, Th17, and other subsets. Additionally, systems immunology approaches have revealed that instructive input from the peripheral tissue microenvironment can have differential effects on the overall phenotype and molecular wiring of Th cells depending on their spatial distribution. Th cells from the blood or secondary lymphoid organs are therefore expected to follow distinct rules of regulation. In this review, the functional heterogeneity of Th cell subsets will be reviewed in the context of new technological developments and T-cell compartmentalization in tissue niches. This work will especially focus on challenges to the traditional boundaries of Th cell subsets and will discuss the underlying regulatory checkpoints, which could reveal new therapeutic strategies for various immune-mediated diseases.

Sex and prior exposure jointly shape innate immune responses to a live herpesvirus vaccine.

Both sex and prior exposure to pathogens are known to influence responses to immune challenges, but their combined effects are not well established in humans, particularly in early innate responses critical for shaping subsequent outcomes. We employed systems immunology approaches to study responses to a replication-defective, herpes simplex virus (HSV) 2 vaccine in men and women either naive or previously exposed to HSV. Blood transcriptomic and cell population profiling showed substantial changes on day 1 after vaccination, but the responses depended on sex and whether the vaccinee was naive or previously exposed to HSV. The magnitude of early transcriptional responses was greatest in HSV naive women where type I interferon (IFN) signatures were prominent and associated negatively with vaccine-induced neutralizing antibody titers, suggesting that a strong early antiviral response reduced the uptake of this replication-defective virus vaccine. While HSV seronegative vaccine recipients had upregulation of gene sets in type I IFN (IFN-α/β) responses, HSV2 seropositive vaccine recipients tended to have responses focused more on type II IFN (IFN-γ) genes. These results together show that prior exposure and sex interact to shape early innate responses that then impact subsequent adaptive immune phenotypes. Intramural Research Program of the NIH, the National Institute of Allergy and Infectious Diseases, and other institutes supporting the Trans-NIH Center for Human Immunology, Autoimmunity, and Inflammation. The vaccine trial was supported through a clinical trial agreement between the National Institute of Allergy and Infectious Diseases and Sanofi Pasteur. Clinical trial number: NCT01915212.

Influenza vaccination reveals sex dimorphic imprints of prior mild COVID-19.

Acute viral infections can have durable functional impacts on the immune system long after recovery, but how they affect homeostatic immune states and responses to future perturbations remain poorly understood1-4. Here we use systems immunology approaches, including longitudinal multimodal single-cell analysis (surface proteins, transcriptome and V(D)J sequences) to comparatively assess baseline immune statuses and responses to influenza vaccination in 33 healthy individuals after recovery from mild, non-hospitalized COVID-19 (mean, 151 days after diagnosis) and 40 age- and sex-matched control individuals who had never had COVID-19. At the baseline and independent of time after COVID-19, recoverees had elevated T cell activation signatures and lower expression of innate immune genesincluding Toll-like receptors in monocytes. Male individuals who had recovered from COVID-19 had coordinately higher innate, influenza-specific plasmablast, and antibody responses after vaccination compared with healthy male individuals and female individuals who had recovered from COVID-19, in part because male recoverees had monocytes with higher IL-15 responses early after vaccination coupled with elevated prevaccination frequencies of 'virtual memory'-like CD8+ T cells poised to produce more IFNγ after IL-15 stimulation. Moreover, the expression of the repressed innate immune genes in monocytes increased by day 1 to day 28 after vaccination in recoverees, therefore moving towards the prevaccination baseline of the healthy control individuals. By contrast, these genes decreased on day 1 and returned to the baseline by day 28 in the control individuals. Our study reveals sex-dimorphic effects of previous mild COVID-19 and suggests that viral infections in humans can establish new immunological set-points that affect future immune responses in an antigen-agnostic manner.

The Immune Signatures data resource, a compendium of systems vaccinology datasets

Vaccines are among the most cost-effective public health interventions for preventing infection-induced morbidity and mortality, yet much remains to be learned regarding the mechanisms by which vaccines protect. Systems immunology combines traditional immunology with modern ‘omic profiling techniques and computational modeling to promote rapid and transformative advances in vaccinology and vaccine discovery. The NIH/NIAID Human Immunology Project Consortium (HIPC) has leveraged systems immunology approaches to identify molecular signatures associated with the immunogenicity of many vaccines. However, comparative analyses have been limited by the distributed nature of some data, potential batch effects across studies, and the absence of multiple relevant studies from non-HIPC groups in ImmPort. To support comparative analyses across different vaccines, we have created the Immune Signatures Data Resource, a compendium of standardized systems vaccinology datasets. This data resource is available through ImmuneSpace, along with code to reproduce the processing and batch normalization starting from the underlying study data in ImmPort and the Gene Expression Omnibus (GEO). The current release comprises 1405 participants from 53 cohorts profiling the response to 24 different vaccines. This novel systems vaccinology data release represents a valuable resource for comparative and meta-analyses that will accelerate our understanding of mechanisms underlying vaccine responses.

Barcode Enabled Antigen Mapping (BEAM) enables next-generation systems immunology analysis of the post-COVID-19 immune landscape

Abstract A more complete understanding of immune responses to disease requires consideration of multiple different cell types across both the innate and adaptive branches of the immune system along with the detection of many different analytes. We used Barcode Enabled Antigen Mapping (BEAM) and Immune Profiling technology to perform simultaneous multimodal profiling at single cell resolution in hundreds of thousands of peripheral blood mononuclear cells (PBMCs) from a human donor following recovery from COVID-19. In addition to measuring gene and protein expression, we generated full-length, paired sequences of the rearranged T- and B-cell receptors while also screening their specificity for a wide range of antigens from SARS-CoV-2 and other viral pathogens. These data provide insights into the entirety of the immune landscape after recovery from acute viral disease. The scale and throughput of our experiments gave us high-resolution data from all cell types from the innate and adaptive immune systems. We identified antigen-specific clones of both B and T lymphocytes, with the high cellular throughput enabling detection of rare clones. Analysis of all PBMC cell types allowed us to place these antigen-specific clones within the overall transcriptional landscape of the post-viral immune system. Experiments such as these will underpin new systems immunology approaches and will continue to reveal the complex interplay between the components of the immune system. We envisage that these methods will be valuable in the analysis of the immune response to vaccination, infectious disease, cancer, allergy, autoimmune conditions, and ageing that can potentially lead to the development of novel diagnostic and therapeutic approaches.

M1 Polarization Markers Are Upregulated in Basal-Like Breast Cancer Molecular Subtype and Associated With Favorable Patient Outcome.

BackgroundBreast cancer heterogeneity is an essential element that plays a role in the therapy response variability and the patient’s outcome. This highlights the need for more precise subtyping methods that focus not only on tumor cells but also investigate the profile of stromal cells as well as immune cells.ObjectivesTo mine publicly available transcriptomic breast cancer datasets and reanalyze their transcriptomic profiling using unsupervised clustering in order to identify novel subsets in molecular subtypes of breast cancer, then explore the stromal and immune cells profile in each subset using bioinformatics and systems immunology approaches.Materials and MethodsTranscriptomic data from 1,084 breast cancer patients obtained from The Cancer Genome Atlas (TCGA) database were extracted and subjected to unsupervised clustering using a recently described, multi-step algorithm called Iterative Clustering and Guide-gene Selection (ICGS). For each cluster, the stromal and immune profile was investigated using ESTIMATE and CIBERSORT analytical tool. Clinical outcomes and differentially expressed genes of the characterized clusters were identified and validated in silico and in vitro in a cohort of 80 breast cancer samples by immunohistochemistry.ResultsSeven unique sub-clusters showed distinct molecular and clinical profiles between the well-known breast cancer subtypes. Those unsupervised clusters identified more homogenous subgroups in each of the classical subtypes with a different prognostic profile. Immune profiling of the identified clusters showed that while the classically activated macrophages (M1) are correlated with the more aggressive basal-like breast cancer subtype, the alternatively activated macrophages (M2) showed a higher level of infiltration in luminal A and luminal B subtypes. Indeed, patients with higher levels of M1 expression showed less advanced disease and better patient outcomes presented as prolonged overall survival. Moreover, the M1 high basal-like breast cancer group showed a higher expression of interferon-gamma induced chemokines and guanylate-binding proteins (GBPs) involved in immunity against microbes.ConclusionAdding immune profiling using transcriptomic data can add precision for diagnosis and prognosis and can cluster patients according to the available modalities of therapy in a more personalized approach.

Understanding immune variation for improved translational medicine.

The goal of translational medicine is to use an improved understanding of human biology to develop new clinical approaches. Immune responses are highly variable from one person to another, with this variability strongly impacting clinical outcome. Variable immunity can determine differential risks for infection, for development of autoimmunity, and for response to therapeutic interventions. Therefore, a better understanding of the causes of such differences has huge potential to improve patient management through precision medicine strategies. Variability in immunity is determined by intrinsic (e.g. age, sex), extrinsic (e.g. environment, diet), and genetic factors. There is a growing consensus that genetics factors account for 20-40% of immune variability between individuals. The remaining unexplained variability is likely due to direct environmental influences, as well as specific gene-environmental interactions, which are more challenging to quantify and study. However, population based cohort studies with systems immunology approaches are now providing new understanding into these associations.

Infinity Flow: comprehensive single-cell protein profiling via massively parallel flow cytometry and machine learning

Abstract Modern flow cytometers can quantify around 20 proteins at the single-cell level. Higher-dimensional alternatives exist, such as mass cytometry, or oligonucleotides-tagged antibodies - but they feature lower cellular throughput, higher cost and are not as widely available. To overcome these limitations, we propose a pipeline which allows the quantification of hundreds of proteins across millions of single cells. Experimentally, cells are stained with a customizable 10–20 “backbone” antibody panel which defines the cellular population structure of the sample. This is followed by aliquoting into hundreds (200–300) of individual wells, each containing a unique “exploratory” antibody. Data acquisition is performed using conventional flow cytometry. Computationally, multivariate non-linear regression models are trained, one for each well. These models learn how to impute an exploratory antibody signal from backbone measurements. The models are each applied to the backbone data to obtain hundreds of imputed measurements across millions of single cells. We applied this workflow cell suspensions from the lungs of C57/B6 mice, resulting in 2,660,000 events with imputed expression levels for 266 proteins. Imputed expression and co-expression patterns are accurate and consensual across regression models, allowing near-exhaustive annotation of both immune and non-immune cells, and finer granularity than dimensionality reduction or clustering. By enabling broad characterization of cellular networks at the protein level, this pipeline is well-suited for systems immunology approaches. Given the wealth of data generated by this pipeline and its accessibility, we anticipate it will be widely adopted.

Deep Phenotyping by Mass Cytometry and Single-Cell RNA-Sequencing Reveals LYN-Regulated Signaling Profiles Underlying Monocyte Subset Heterogeneity and Lifespan

Monocytes are key effectors of the mononuclear phagocyte system, playing critical roles in regulating tissue homeostasis and coordinating inflammatory reactions, including those involved in chronic inflammatory diseases such as atherosclerosis. Monocytes have traditionally been divided into 2 major subsets termed conventional monocytes and patrolling monocytes (pMo) but recent systems immunology approaches have identified marked heterogeneity within these cells, and much of what regulates monocyte population homeostasis remains unknown. We and others have previously identified LYN tyrosine kinase as a key negative regulator of myeloid cell biology; however, LYN's role in regulating specific monocyte subset homeostasis has not been investigated. We sought to comprehensively profile monocytes to elucidate the underlying heterogeneity within monocytes and dissect how Lyn deficiency affects monocyte subset composition, signaling, and gene expression. We further tested the biological significance of these findings in a model of atherosclerosis. Mass cytometric analysis of monocyte subsets and signaling pathway activation patterns in conventional monocytes and pMos revealed distinct baseline signaling profiles and far greater heterogeneity than previously described. Lyn deficiency led to a selective expansion of pMos and alterations in specific signaling pathways within these cells, revealing a critical role for LYN in pMo physiology. LYN's role in regulating pMos was cell-intrinsic and correlated with an increased circulating half-life of Lyn-deficient pMos. Furthermore, single-cell RNA sequencing revealed marked perturbations in the gene expression profiles of Lyn-/- monocytes with upregulation of genes involved in pMo development, survival, and function. Lyn deficiency also led to a significant increase in aorta-associated pMos and protected Ldlr-/- mice from high-fat diet-induced atherosclerosis. Together our data identify LYN as a key regulator of pMo development and a potential therapeutic target in inflammatory diseases regulated by pMos.

Metabolic Control and Systems Immunology in Blood Cell Development

Coordination of metabolic programs with cell fate decisions is a fundamental determinant of hematopoietic cell development and function. Hematopoietic cells at different developmental and activation stages exhibit distinct metabolic signatures. Emerging evidence further highlights the interplay between cell signaling and metabolic programming in these processes. We found that myelopoiesis, including the differentiation of monocytes, macrophages and dendritic cells (DCs), required mechanistic target of rapamycin complex 1 (mTORC1) signaling and anabolic metabolism. Loss of mTORC1 impaired myelopoiesis under steady state and dampened innate immune responses against Listeria monocytogenes infection. Stimulation of hematopoietic progenitors with macrophage colony-stimulating factor (M-CSF) resulted in mTORC1-dependent anabolic metabolism, which in turn promoted expression of M-CSF receptor and transcription factors PU.1 and IRF8, thereby constituting a feed-forward loop for myelopoiesis. Mechanistically, mTORC1 engaged glucose metabolism and initiated a transcriptional program involving glycolysis and sterol biosynthesis after M-CSF stimulation. Integrative metabolomic and genomic profiling further identified one-carbon metabolism as a central node in mTORC1-dependent myelopoiesis. Moreover, we found that differentiation of DCs from bone marrow precursors was associated with dynamic regulation of mTORC1 signaling and cell metabolism. Either reduced or excessive mTORC1 activity was detrimental to DC development, associated with impaired regulation of cell metabolism. Interestingly, in contrast to the obligatory role of mTORC1 in monocyte and DC development, mTORC2 function was dispensable in these processes. Our results demonstrate that the interplay between mTORC1 signaling and bioenergetic and biosynthetic activities constitutes key metabolic checkpoints to orchestrate myelopoiesis. We are currently applying systems immunology approaches to explore metabolic signaling in myelopoiesis. Disclosures No relevant conflicts of interest to declare.

The chromatin accessibility signature of human immune aging stems from CD8+ T cells.

Aging is linked to deficiencies in immune responses and increased systemic inflammation. To unravel the regulatory programs behind these changes, we applied systems immunology approaches and profiled chromatin accessibility and the transcriptome in PBMCs and purified monocytes, B cells, and T cells. Analysis of samples from 77 young and elderly donors revealed a novel and robust aging signature in PBMCs, with simultaneous systematic chromatin closing at promoters and enhancers associated with T cell signaling and a potentially stochastic chromatin opening mostly found at quiescent and repressed sites. Combined analyses of chromatin accessibility and the transcriptome uncovered immune molecules activated/inactivated with aging and identified the silencing of the IL7R gene and the IL-7 signaling pathway genes as potential biomarkers. This signature is borne by memory CD8+ T cells, which exhibited an aging-related loss in binding of NF-κB and STAT factors. Thus, our study provides a unique and comprehensive approach to identifying candidate biomarkers and provides mechanistic insights into aging-associated immunodeficiency.

Petri Net computational modelling of Langerhans cell Interferon Regulatory Factor Network predicts their role in T cell activation

Langerhans cells (LCs) are able to orchestrate adaptive immune responses in the skin by interpreting the microenvironmental context in which they encounter foreign substances, but the regulatory basis for this has not been established. Utilising systems immunology approaches combining in silico modelling of a reconstructed gene regulatory network (GRN) with in vitro validation of the predictions, we sought to determine the mechanisms of regulation of immune responses in human primary LCs. The key role of Interferon regulatory factors (IRFs) as controllers of the human Langerhans cell response to epidermal cytokines was revealed by whole transcriptome analysis. Applying Boolean logic we assembled a Petri net-based model of the IRF-GRN which provides molecular pathway predictions for the induction of different transcriptional programmes in LCs. In silico simulations performed after model parameterisation with transcription factor expression values predicted that human LC activation of antigen-specific CD8 T cells would be differentially regulated by epidermal cytokine induction of specific IRF-controlled pathways. This was confirmed by in vitro measurement of IFN-γ production by activated T cells. As a proof of concept, this approach shows that stochastic modelling of a specific immune networks renders transcriptome data valuable for the prediction of functional outcomes of immune responses.

Disease Mechanisms in Rheumatology—Tools and Pathways: Current Perspectives on Systems Immunology Approaches to Rheumatic Diseases

Disease Mechanisms in Rheumatology—Tools and Pathways: Current Perspectives on Systems Immunology Approaches to Rheumatic Diseases

Systems Scale Interactive Exploration Reveals Quantitative and Qualitative Differences in Response to Influenza and Pneumococcal Vaccines

Systems immunology approaches were employed to investigate innate and adaptive immune responses to influenza and pneumococcal vaccines. These two non-live vaccines show different magnitudes of transcriptional responses at different time points after vaccination. Software solutions were developed to explore correlates of vaccine efficacy measured as antibody titers at day 28. These enabled a further dissection of transcriptional responses. Thus, the innate response, measured within hours in the peripheral blood, was dominated by an interferon transcriptional signature after influenza vaccination and by an inflammation signature after pneumococcal vaccination. Day 7 plasmablast responses induced by both vaccines was more pronounced after pneumococcal vaccination. Together, these results suggest that comparing global immune responses elicited by different vaccines will be critical to our understanding of the immune mechanisms underpinning successful vaccination.