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The immune system plays a vital role in health and disease, and is regulated through a complex interactive network of many different immune cells and mediators. To understand the complexity of the immune system, we propose to apply a multi-omics approach in immunological research. This review provides a complete overview of available methodological approaches for the different omics data layers relevant for immunological research, including genetics, epigenetics, transcriptomics, proteomics, metabolomics, and cellomics. Thereafter, we describe the various methods for data analysis as well as how to integrate different layers of omics data. Finally, we discuss the possible applications of multi-omics studies and opportunities they provide for understanding the complex regulatory networks as well as immune variation in various immune-related diseases.

Adoptive T-cell therapy has shown remarkable clinical efficacy in treating refractory hematological cancers. However, challenges presented by solid tumors impede the applicability of adoptive T-cell therapy to the majority of cancers. In order to engineer effective T-cell therapies targeting solid tumors, two synergistic design criteria-T-cell therapeutic programs and anti-tumor T-cell chassis-should be taken into consideration. Recent advances in synthetic biology have enabled genetic programming of therapeutic sense-and-respond modalities in T cells. Furthermore, systems-level integration of multi-omics datum have allowed researchers to holistically profile robust anti-tumor T-cell populations. In this review, we feature novel strategies that can be incorporated into adoptive T-cell therapy design-ushering in a new paradigm of solid tumor treatment options.

The complexity of the Plasmodium parasite and its life cycle poses a challenge to our understanding of the host immune response against malaria. Studying human immune responses during natural and experimental Plasmodium infections can enhance our understanding of malaria-protective immunity and inform the design of disease-modifying adjunctive therapies and next-generation malaria vaccines. Systems immunology can complement conventional approaches to facilitate our understanding of the complex immune response to the highly dynamic malaria parasite. In this review, recent studies that used systems-based approaches to evaluate human immune responses during natural and experimental Plasmodium falciparum and Plasmodium vivax infections as well as during immunization with candidate malaria vaccines are summarized and related to each other. The potential for next-generation technologies to address the current limitations of systems-based studies of human malaria are discussed.

T cell receptor (TCR) repertoires are critical for antiviral immunity. Determining the TCR repertoires composition, diversity, and dynamics and how they change during viral infection can inform the molecular specificity of viral infection such as SARS-CoV-2. To determine signatures associated with COVID-19 disease severity, here we performed a large-scale analysis of over 4.7 billion sequences across 2,130 TCR repertoires from COVID-19 patients and healthy donors. TCR repertoire analyses from these data identified and characterized convergent COVID-19 associated CDR3 gene usages, specificity groups, and sequence patterns. T cell clonal expansion was found to be associated with upregulation of T cell effector function, TCR signaling, NF-kB signaling, and Interferon-gamma signaling pathways. Machine learning approaches accurately predicted disease severity for patients based on TCR sequence features, with certain high-power models reaching near-perfect AUROC scores across various predictor permutations. These analyses provided an integrative, systems immunology view of T cell adaptive immune responses to COVID-19.

International audience; The interleukin-12 (IL-12) family comprises the only heterodimeric cytokines mediating diverse functional effects. We previously reported a striking bimodal IL-12p70 response to lipopolysaccharide (LPS) stimulation in healthy donors. Herein, we demonstrate that interferon β (IFNβ) is a major upstream determinant of IL-12p70 production, which is also associated with numbers and activation of circulating monocytes. Integrative modeling of proteomic, genetic, epigenomic, and cellular data confirms IFNβ as key for LPS-induced IL-12p70 and allowed us to compare the relative effects of each of these parameters on variable cytokine responses. Clinical relevance of our findings is supported by reduced IFNβ-IL-12p70 responses in patients hospitalized with acute severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or chronically infected with hepatitis C (HCV). Importantly, these responses are resolved after viral clearance. Our systems immunology approach defines a better understanding of IL-12p70 and IFNβ in healthy and infected persons, providing insights into how common genetic and epigenetic variation may impact immune responses to bacterial infection.

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, including those targeting seasonal influenza, yellow fever, and hepatitis B. These data are made available to the broader scientific community through the ImmuneSpace data portal and analysis engine leveraging the NIH/NIAID ImmPort repository1,2. However, a barrier to progress in this area is that 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 and includes transcriptional profiles and antibody response measurements. 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.

A systems immunology analysis of controlled human malaria infections in Africans who were malaria experienced and Europeans who were malaria naive yields new insights into old questions of malaria immunity.

For a long time, the nervous system and the immune system have been studied as isolated entities, but a growing body of evidence shows that there is an extensive crosstalk between both systems. In fact, neurons and immune cells share certain functional features and reside in close proximity within the tissues, enabling them to effectively communicate. T cells are crucial for mounting and controlling almost any kind of immune response. However, when dysregulated, T cells fail to protect the host from invading pathogens or can cause damage to surrounding tissues, leading to autoimmunity-related pathology. In the first part of this cumulative thesis, we aimed at identifying novel genes regulating CD4 T cell responses and identified VIMP, one of the 25 human proteins containing the 21st amino acid selenocysteine, as a gene having anti-inflammatory functions. Furthermore, T cells express various neurotransmitter receptors allowing the integration of neuronal signal for an appropriate response. In the second part, we showed a CD4-T-cell-intrinsic mechanism through which stress hormones mediate their control over the immune system. We identified a previously unrecognized pathway regulating CD4 T cell differentiation that involves the circadian clock gene Per1 and mTORC1 signalling. Finaly, T cells involvement in different neuropathologies has been reported in the past few decades. Emerging evidence indicates the involvement of the immune system and in particular T cells in the pathogenesis of Parkinson’s disease (PD), the 2nd most common neurodegenerative disease. In the 3rd part of the thesis we systematically characterized the immunological status of early-to-mid stage PD patients and matched healthy controls, and identified a distinct peripheral immunological fingerprint in PD patients, especially in the CD8 T-cell compartment. The findings of the studies described in this cumulative thesis advance our understanding of the regulatory nodes of CD4 T cells during a stress response and fill the knowledge gap on the early involvement of CD8 T cells and other immune subsets in neurodegenerative diseases in the case of PD.

Both vaccine “take” and neutralizing antibody (nAb) titer are historical correlates for vaccine-induced protection from smallpox. We analyzed a subset of samples from a phase 2a trial of three DNA/HIV-1 primes and a recombinant Tiantan vaccinia virus-vectored (rTV)/HIV-1 booster and found that a proportion of participants showed no anti-vaccinia nAb response to the rTV/HIV-1 booster, despite successful vaccine “take.” Using a rich transcriptomic and vaccinia-specific immunological dataset with fine kinetic sampling, we investigated the molecular mechanisms underlying nAb response. Blood transcription module analysis revealed the downregulation of the activator protein 1 (AP-1) pathway in responders, but not in non-responders, and the upregulation of T-cell activation in responders. Furthermore, transcriptional factor network reconstruction revealed the upregulation of AP-1 core genes at hour 4 and day 1 post-rTV/HIV-1 vaccination, followed by a downregulation from day 3 until day 28 in responders. In contrast, AP-1 core and pro-inflammatory genes were upregulated on day 7 in non-responders. We speculate that persistent pro-inflammatory signaling early post-rTV/HIV-1 vaccination inhibits the nAb response.

The field of infectious diseases currently takes a reactive approach and treats infections as they present in patients. Although certain populations are known to be at greater risk of developing infection (eg, immunocompromised), we lack a systems approach to define the true risk of future infection for a patient. Guided by impressive gains in “omics” technologies, future strategies to infectious diseases should take a precision approach to infection through identification of patients at intermediate and high-risk of infection and deploy targeted preventative measures (ie, prophylaxis). The advances of high-throughput immune profiling by multiomics approaches (ie, transcriptomics, epigenomics, metabolomics, proteomics) hold the promise to identify patients at increased risk of infection and enable risk-stratifying approaches to be applied in the clinic. Integration of patient-specific data using machine learning improves the effectiveness of prediction, providing the necessary technologies needed to propel the field of infectious diseases medicine into the era of personalized medicine., Translational systems immunology approaches to infectious diseases will enable the switch from reactive to precision treatment of patients, which will improve clinical outcomes while reducing the use of prophylactic antibiotics and incidence of infection in high-risk individuals.

Intercellular communication mediated by cytokines is critical to the development of immune responses, particularly in the context of infectious and inflammatory diseases. By releasing these small molecular weight peptides, the source cells can influence numerous intracellular processes in the target cells, including the secretion of other cytokines downstream. However, there are no readily available bioinformatic resources that can model cytokine - cytokine interactions. In this effort, we built a communication map between major tissues and blood cells that reveals how cytokine-mediated intercellular networks form during homeostatic conditions. We collated the most prevalent cytokines from literature, and assigned the proteins and their corresponding receptors to source tissue and blood cell types based on enriched consensus RNA-Seq data from the Human Protein Atlas database. To assign more confidence to the interactions, we integrated literature information on cell - cytokine interactions from two systems immunology databases, immuneXpresso and ImmunoGlobe. From the collated information, we defined two metanetworks: a cell-cell communication network connected by cytokines; and a cytokine-cytokine interaction network depicting the potential ways in which cytokines can affect the activity of each other. Using expression data from disease states, we then applied this resource to reveal perturbations in cytokine-mediated intercellular signalling in inflammatory and infectious diseases (ulcerative colitis and COVID-19, respectively). For ulcerative colitis, with CytokineLink we demonstrated a significant rewiring of cytokine-mediated intercellular communication between non-inflamed and inflamed colonic tissues. For COVID-19, we were able to identify inactive cell types and cytokine interactions that may be important following SARS-CoV-2 infection when comparing the cytokine response with other viruses capable of initiating a cytokine storm. Such findings have potential to inform the development of novel, cytokine-targeted therapeutic strategies. CytokineLink is freely available for the scientific community through the NDEx platform and the project github repository (https://github.com/korcsmarosgroup/CytokineLink).

Immune responses rely on a complex adaptive system in which the body and infections interact at multiple scales and in different compartments. We developed a modular model of CD4+ T cells, which uses four modeling approaches to integrate processes at three spatial scales in different tissues. In each cell, signal transduction and gene regulation are described by a logical model, metabolism by constraint-based models. Cell population dynamics are described by an agent-based model and systemic cytokine concentrations by ordinary differential equations. A Monte Carlo simulation algorithm allows information to flow efficiently between the four modules by separating the time scales. Such modularity improves computational performance and versatility and facilitates data integration. We validated our technology by reproducing known experimental results, including differentiation patterns of CD4+ T cells triggered by different combinations of cytokines, metabolic regulation by IL2 in these cells, and their response to influenza infection. In doing so, we added multi-scale insights to single-scale studies and demonstrated its predictive power by discovering switch-like and oscillatory behaviors of CD4+ T cells that arise from nonlinear dynamics interwoven across three scales. We identified the inflamed lymph node’s ability to retain naive CD4+ T cells as a key mechanism in generating these emergent behaviors. We envision our model and the generic framework encompassing it to serve as a tool for understanding cellular and molecular immunological problems through the lens of systems immunology., Author summary CD4+ T cells are a key part of the adaptive immune system. They differentiate into different phenotypes to carry out different functions. They do so by secreting molecules called cytokines to regulate other immune cells. Multi-scale modeling can potentially explain their emergent behaviors by integrating biological phenomena occurring at different spatial (intracellular, cellular, and systemic), temporal, and organizational scales (signal transduction, gene regulation, metabolism, cellular behaviors, and cytokine transport). We built a computational platform by combining disparate modeling frameworks (compartmental ordinary differential equations, agent-based modeling, Boolean network modeling, and constraint-based modeling). We validated the platform’s ability to predict CD4+ T cells’ emergent behaviors by reproducing their differentiation patterns, metabolic regulation, and population dynamics in response to influenza infection. We then used it to predict and explain novel switch-like and oscillatory behaviors for CD4+ T cells. On the basis of these results, we believe that our multi-approach and multi-scale platform will be a valuable addition to the systems immunology toolkit. In addition to its immediate relevance to CD4+ T cells, it also has the potential to become the foundation of a virtual immune system.

T cell stemness and exhaustion coexist as two key contrasting phenomena during chronic antigen stimulation, such as infection, transplant, cancer, and autoimmunity. T cell exhaustion refers to the progressive loss of effector function caused by chronic antigen exposure. Exhausted T (TEX) cells highly express multiple inhibitory receptors and exhibit severe defects in cell proliferation and cytokine production. The term T cell stemness describes the stem cell-like behaviors of T cells, including self-renewal, multipotency, and functional persistence. It is well accepted that naïve and some memory T cell subsets have stem cell-like properties. When investigating the exhaustive differentiation of T cells in chronic infection and cancer, recent studies highlighted the stemness of “precursors of exhausted” T (TPEX) cells prior to their terminal differentiation to TEX cells. Clinically successful checkpoint blockades for cancer treatment appear to invigorate antitumor TPEX cells but not TEX cells. Here we discuss the transcriptional and epigenetic regulations of T cell stemness and exhaustion, with a focus on how systems immunology was and will be utilized to define the molecular basis underlying the transition of TPEX to TEX cells. We suggest a “stepwise model” of T cell stemness and exhaustion, in which loss of stemness and exhaustion progression are gradual multi-step processes. We provide perspectives on the research needed to define T cell stemness and exhaustion in the transplantation setting, in which allogenic T cells are also chronically exposed to alloantigens. A better understanding of T cell stemness and exhaustion will shed light on developing novel strategies for immunotherapies.

The emerging field of long noncoding RNA (lncRNA)-immunity has provided a new perspective on cancer immunity and immunotherapies. The lncRNA modifiers of infiltrating immune cells in the tumor immune microenvironment (TIME) and their impact on tumor behavior and disease prognosis remain largely uncharacterized. In the present study, a systems immunology framework integrating the noncoding transcriptome and immunogenomics profiles of 9549 tumor samples across 30 solid cancer types was used, and 36 lncRNAs were identified as modifier candidates underlying immune cell infiltration in the TIME at the pan-cancer level. These TIME lncRNA modifiers (TIL-lncRNAs) were able to subclassify various tumors into three de novo pan-cancer subtypes characterized by distinct immunological features, biological behaviors, and disease prognoses. Finally, a TIL-lncRNA-derived immune state index (TISI) that was reflective of immunological and oncogenic states but also predictive of patients’ prognosis was proposed. Furthermore, the TISI provided additional prognostic value for existing tumor immunological and molecular subtypes. By applying the TISI to tumors from different clinical immunotherapy cohorts, the TISI was found to be significantly negatively correlated with immune-checkpoint genes and to have the ability to predict the effectiveness of immunotherapy. In conclusion, the present study provided comprehensive resources and insights for future functional and mechanistic studies on lncRNA-mediated cancer immunity and highlighted the potential of the clinical application of lncRNA-based immunotherapeutic strategies in precision immunotherapy.

The immune system plays a vital role in health and disease, and is regulated through a complex interactive network of many different immune cells and mediators. To understand the complexity of the immune system, we propose to apply a multi-omics approach in immunological research. This review provides a complete overview of available methodological approaches for the different omics data layers relevant for immunological research, including genetics, epigenetics, transcriptomics, proteomics, metabolomics, and cellomics. Thereafter, we describe the various methods for data analysis as well as how to integrate different layers of omics data. Finally, we discuss the possible applications of multi-omics studies and opportunities they provide for understanding the complex regulatory networks as well as immune variation in various immune-related diseases.

The immune system is a highly complex and dynamic biological system. It operates through intracellular molecular networks and intercellular (cell-cell) interaction networks. Systems immunology is an emerging discipline that applies systems biology approaches of integrating high-throughput multi-omics measurements with computational network modeling to better understand immunity at various scales. In this review, we summarize key omics technologies and computational approaches used for immunological studies at both population and single-cell levels. We highlight the hidden driver analysis based on data-driven networks and comment on the potential of translating systems immunology discoveries to immunotherapy of cancer and other human diseases.

Bone marrow (BM) stromal cells are important in the development and maintenance of cells of the immune system. Using single cell RNA sequencing, we here explore the functional and phenotypic heterogeneity of individual transcriptomes of 1167 murine BM mesenchymal stromal cells. These cells exhibit a tremendous heterogeneity of gene expression, which precludes the identification of defined subpopulations. However, according to the expression of 108 genes involved in the communication of stromal cells with hematopoietic cells, we have identified 14 non‐overlapping subpopulations, with distinct cytokine or chemokine gene expression signatures. With respect to the maintenance of subsets of immune memory cells by stromal cells, we identified distinct subpopulations expressing Il7, Il15 and Tnfsf13b. Together, this study provides a comprehensive dissection of the BM stromal heterogeneity at the single cell transcriptome level and provides a basis to understand their lifestyle and their role as organizers of niches for the long‐term maintenance of immune cells.

Intercellular communication mediated by cytokines is the main mechanism by which cells of the immune system ‘talk’ to each other. Many aspects of cytokine signaling in the immune system have been explored in great detail at the structural, biophysical, biochemical and cellular levels. However, a systematic understanding of the quantitative rules that govern cytokine-mediated cell-to-cell communication is still lacking. Here, we discuss recent efforts in the field of systems immunology to bring about a quantitative understanding of cytokine-mediated communication between leukocytes and to provide novel insights into the orchestration of immune responses and inflammation.

The therapeutic activation of antitumour immunity by immune checkpoint inhibitors (ICIs) is a significant advance in cancer medicine, not least due to the prospect of long-term remission. However, many patients are unresponsive to ICI therapy and may experience serious side effects; companion biomarkers are urgently needed to help inform ICI prescribing decisions. We present the IMMUNETS networks of gene coregulation in five key immune cell types and their application to interrogate control of nivolumab response in advanced melanoma cohorts. The results evidence a role for each of the IMMUNETS cell types in ICI response and in driving tumour clearance with independent cohorts from TCGA. As expected, ‘immune hot’ status, including T cell proliferation, correlates with response to first-line ICI therapy. Genes regulated in NK, dendritic, and B cells are the most prominent discriminators of nivolumab response in patients that had previously progressed on another ICI. Multivariate analysis controlling for tumour stage and age highlights CIITA and IKZF3 as candidate prognostic biomarkers. IMMUNETS provide a resource for network biology, enabling context-specific analysis of immune components in orthogonal datasets. Overall, our results illuminate the relationship between the tumour microenvironment and clinical trajectories, with potential implications for precision medicine.

B cell related immune protection is complex, involving a large network of processes. These processes may differ with respect to time, space, kind, number and diversity of interacting agents, and take place on various scales. To assemble a map of this network that possesses predictive capacity is one aim of Systems Immunology. Such a map is a crucial element in both vaccine development and infection control. Its implementation requires, in particular, performing multilevel, multiscale studies as well as mining the resulting, integrated knowledge from shared data bases.

In single-cell biology there is an ongoing push toward more and more comprehensive measurements made in individual cells. By combining measurements of proteins, mRNA, genetic, and epigenetic traits, in contexts of cell stimulation or drug treatment, novel single-cell analyses will help understand the determinants of cellular identity, differentiation decisions, and regulatory mechanisms governing cellular function in health and disease. Mass cytometry is a flexible methodology not only developed toward this aim, allowing analyses of cells in suspension such as blood but also extended for the analyses of tissue sections. Here, I will discuss the different measurements possible by mass cytometry and not only discuss its potential but also its limitations now and in the years to come.

Significance Chronic inflammation contributes to morbidity and mortality in aging, but whether similar mechanisms underlie dysfunction in infection-associated chronic inflammation is unclear. Using a multicohort systems immunology approach, we identified signatures of immune dysfunction that are shared in aging and chronic viral infections, namely HIV and hepatitis C virus. We show that these shared dysfunctions persist despite viral clearance, and we describe the changes in functional coordination that occur during viral eradication. Finally, we highlight a partial restoration in interferon-α sensitivity across all major immune cell lineages as viral load drops. Our findings suggest a broad and persistent functional remodeling and deterioration of the human immune system despite removal of a chronic pathogenic burden that shares features of chronic inflammation in aging., Chronic inflammation is thought to be a major cause of morbidity and mortality in aging, but whether similar mechanisms underlie dysfunction in infection-associated chronic inflammation is unclear. Here, we profiled the immune proteome, and cellular composition and signaling states in a cohort of aging individuals versus a set of HIV patients on long-term antiretroviral therapy therapy or hepatitis C virus (HCV) patients before and after sofosbuvir treatment. We found shared alterations in aging-associated and infection-associated chronic inflammation including T cell memory inflation, up-regulation of intracellular signaling pathways of inflammation, and diminished sensitivity to cytokines in lymphocytes and myeloid cells. In the HIV cohort, these dysregulations were evident despite viral suppression for over 10 y. Viral clearance in the HCV cohort partially restored cellular sensitivity to interferon-α, but many immune system alterations persisted for at least 1 y posttreatment. Our findings indicate that in the HIV and HCV cohorts, a broad remodeling and degradation of the immune system can persist for a year or more, even after the removal or drastic reduction of the pathogen load and that this shares some features of chronic inflammation in aging.

COVID-19 exhibits extensive patient-to-patient heterogeneity. To link immune response variation to disease severity and outcome over time, we longitudinally assessed circulating proteins as well as 188 surface protein markers, transcriptome, and T-cell receptor sequence simultaneously in single peripheral immune cells from COVID-19 patients. Conditional-independence network analysis revealed primary correlates of disease severity, including gene expression signatures of apoptosis in plasmacytoid dendritic cells and attenuated inflammation but increased fatty acid metabolism in CD56dimCD16hi NK cells linked positively to circulating IL-15. CD8+ T cell activation was apparent without signs of exhaustion. While cellular inflammation was depressed in severe patients early after hospitalization, it became elevated by days 17-23 post symptom onset, suggestive of a late wave of inflammatory responses. Furthermore, circulating protein trajectories at this time were divergent between and predictive of recovery-fatal outcomes. Our findings stress the importance of timing in the analysis, clinical monitoring, and therapeutic intervention of COVID-19., A multiparameter metric developed by integrating circulating cytokines, multimodal single cell profiling, cell surface protein and immune cell analyses of COVID-19 patients over time, reveals a late wave of diverging inflammatory and host immune responses that predicts recovery versus fatality.

The biology of Plasmodium vivax is markedly different to that of P. falciparum; how this shapes the immune response to infection remains unclear. To address this shortfall, we inoculated human volunteers with a clonal field isolate of P. vivax and tracked their response through infection and convalescence. High dimensional protein and RNA-seq data show that P. vivax triggers an acute phase response that shares remarkable overlap with that of P. falciparum, suggesting a hardwired emergency myeloid response that does not discriminate parasite species. We then used cytometry by time of flight to analyse the fate and function of innate-like and adaptive T cells; these data show that P. vivax can activate up to one quarter of the entire T cell compartment. Heterogeneous effector memory-like CD4+ T cells dominate this extraordinary response and phenotypic analysis reveals unexpected features of terminal differentiation that are normally associated with cytotoxicity and autoinflammatory disease. In line with this observation, we found that CD4+ T cell activation coincides with collateral tissue damage and liver injury. Finally, comparative analyses demonstrate that P. falciparum drives T cell activation far in excess of P. vivax, which may partially explain why falciparum malaria more frequently causes severe disease.

Falciparum malaria is clinically heterogeneous and the relative contribution of parasite and host in shaping disease severity remains unclear. We explored the interaction between inflammation and parasite variant surface antigen (VSA) expression, asking whether this relationship underpins the variation observed in controlled human malaria infection (CHMI). We uncovered marked heterogeneity in the host response to blood challenge; some volunteers remained quiescent, others triggered interferon-stimulated inflammation and some showed transcriptional evidence of myeloid cell suppression. Significantly, only inflammatory volunteers experienced hallmark symptoms of malaria. When we tracked temporal changes in parasite VSA expression to ask whether variants associated with severe disease rapidly expand in naive hosts, we found no transcriptional evidence to support this hypothesis. These data indicate that parasite variants that dominate severe malaria do not have an intrinsic growth or survival advantage; instead, they presumably rely upon infection-induced changes in their within-host environment for selection.