NAD+ metabolism drives astrocyte proinflammatory reprogramming in central nervous system autoimmunity.

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system (CNS). Astrocytes are the most abundant glial cells in the CNS, and their dysfunction contributes to the pathogenesis of MS and its animal model, experimental autoimmune encephalomyelitis (EAE). Recent advances highlight the pivotal role of cellular metabolism in programming immune responses. However, the underlying immunometabolic mechanisms that drive astrocyte pathogenicity remain elusive. Nicotinamide adenine dinucleotide (NAD+) is a vital coenzyme involved in cellular redox reactions and a substrate for NAD+-dependent enzymes. Cellular NAD+ levels are dynamically controlled by synthesis and degradation, and dysregulation of this balance has been associated with inflammation and disease. Here, we demonstrate that cell-autonomous generation of NAD+ via the salvage pathway regulates astrocyte immune function. Inhibition of nicotinamide phosphoribosyltransferase (NAMPT), a key enzyme in the salvage pathway, results in depletion of NAD+, inhibits oxidative phosphorylation, and limits astrocyte inflammatory potential. We identified CD38 as the main NADase up-regulated in reactive mouse and human astrocytes in models of neuroinflammation and MS. Genetic or pharmacological blockade of astrocyte CD38 activity augmented NAD+ levels, suppressed proinflammatory transcriptional reprogramming, impaired chemotactic potential to inflammatory monocytes, and ameliorated EAE. We found that CD38 activity is mediated via calcineurin/NFAT signaling in mouse and human reactive astrocytes. Thus, NAMPT-NAD+-CD38 circuitry in astrocytes controls their ability to meet their energy demands and drives the expression of proinflammatory transcriptional modules, contributing to CNS pathology in EAE and, potentially, MS. Our results identify candidate therapeutic targets in MS.

Cell composition analysis of bulk genomics using single-cell data.

Single-cell RNA sequencing (scRNA-seq) is a rich resource of cellular heterogeneity, opening new avenues in the study of complex tissues. We introduce Cell Population Mapping (CPM), a deconvolution algorithm in which reference scRNA-seq profiles are leveraged to infer the composition of cell types and states from bulk transcriptome data ('scBio' CRAN R-package). Analysis of individual variations in lungs of influenza-virus-infected mice reveals that the relationship between cell abundance and clinical symptoms is a cell-state-specific property that varies gradually along the continuum of cell-activation states. The gradual change is confirmed in subsequent experiments and is further explained by a mathematical model in which clinical outcomes relate to cell-state dynamics along the activation process. Our results demonstrate the power of CPM in reconstructing the continuous spectrum of cell states within heterogeneous tissues.

The host transcriptional response to superinfection by influenza A virus and Streptococcus pneumoniae.

Secondary bacterial challenges during influenza virus infection "superinfection") cause excessive mortality and hospitalization. Here, we present a longitudinal study of bulk gene expression changes in murine lungs during superinfection, with an initial influenza A virus infection and a subsequent Streptococcus pneumoniae infection. In addition to the well-characterized impairment of the host response, we identified superinfection-specific alterations in the global transcriptional program that are linked to the host's ability to resist the pathogens. Particularly, whereas superinfected mice manifested an excessive rapid induction of the resistance-to-infection program, there was a substantial tissue-level rewiring of this program: upon superinfection, interferon-regulated genes were switched from positive to negative correlations with the host's resistance state, whereas genes of fatty acid metabolism switched from negative to positive correlations with resistance states. Thus, the transcriptional resistance state in superinfection is reprogrammed toward repressed interferon signaling and induced fatty acid metabolism. Our findings suggest new insights into a tissue-level remodeling of the host defense upon superinfection, providing promising targets for future therapeutic interventions. IMPORTANCE: Secondary bacterial infections are the most frequent complications during influenza A virus (IAV) pandemic outbreaks, contributing to excessive morbidity and mortality in the human population. Most IAV-related deaths are attributed to Streptococcus pneumoniae (SP) infections, which usually begin within the first week of IAV infection in the respiratory tracts. Here, we focused on longitudinal transcriptional responses during a superinfection model consisting of an SP infection that follows an initial IAV infection, comparing superinfection to an IAV-only infection, an SP-only infection, and control treatments. Our longitudinal data allowed a fine analysis of gene expression changes during superinfection. For instance, we found that superinfected mice exhibited rapid gene expression induction or reduction within the first 12 h after encountering the second pathogen. Cell proliferation and immune response activation processes were upregulated, while endothelial processes, vasculogenesis, and angiogenesis were downregulated, providing promising targets for future therapeutic interventions. We further analyzed the longitudinal transcriptional responses in the context of a previously defined spectrum of the host's resistance state, revealing superinfection-specific reprogramming of resistance states, such as reprogramming of fatty acid metabolism and interferon signaling. The reprogrammed functions are compelling new targets for switching the pathogenic superinfection state into a single-infection state.

Distinct gene programs underpinning disease tolerance and resistance in influenza virus infection.

When challenged with an invading pathogen, the host-defense response is engaged to eliminate the pathogen (resistance) and to maintain health in the presence of the pathogen (disease tolerance). However, the identification of distinct molecular programs underpinning disease tolerance and resistance remained obscure. We exploited transcriptional and physiological monitoring across 33 mouse strains, during in vivo influenza virus infection, to identify two host-defense gene programs-one is associated with hallmarks of disease tolerance and the other with hallmarks of resistance. Both programs constitute generic responses in multiple mouse and human cell types. Our study describes the organizational principles of these programs and validates Arhgdia as a regulator of disease-tolerance states in epithelial cells. We further reveal that the baseline disease-tolerance state in peritoneal macrophages is associated with the pathophysiological response to injury and infection. Our framework provides a paradigm for the understanding of disease tolerance and resistance at the molecular level.

Leveraging the cell lineage to predict cell-type specificity of regulatory variation from bulk genomics.

Recent computational methods have enabled the inference of the cell-type-specificity of eQTLs based on bulk transcriptomes from highly heterogeneous tissues. However, these methods are limited in their scalability to highly heterogeneous tissues and limited in their broad applicability to any cell-type specificity of eQTLs. Here we present and demonstrate Cell Lineage Genetics (CeL-Gen), a novel computational approach that allows inference of eQTLs together with the subsets of cell types in which they have an effect, from bulk transcriptome data. To obtain improved scalability and broader applicability, CeL-Gen takes as input the known cell lineage tree and relies on the observation that dynamic changes in genetic effects occur relatively infrequently during cell differentiation. CeL-Gen can therefore be used not only to tease apart genetic effects derived from different cell types but also to infer the particular differentiation steps in which genetic effects are altered.

Mutated MITF-E87R in Melanoma Enhances Tumor Progression via S100A4.

Melanoma, a melanocyte origin neoplasm, is the most lethal type of skin cancer, and incidence is increasing. Several familial and somatic mutations have been identified in the gene encoding the melanocyte lineage master regulator, MITF; however, the neoplastic mechanisms of these mutant MITF variants are mostly unknown. Here, by performing unbiased analysis of the transcriptomes in cells expressing mutant MITF, we identified calcium-binding protein S100A4 as a downstream target of MITF-E87R. By using wild-type and mutant MITF melanoma lines, we found that both endogenous wild-type and MITF-E87R variants occupy the S100A4 promoter. Remarkably, whereas wild-type MITF represses S100A4 expression, MITF-E87R activates its transcription. The opposite effects of wild-type and mutant MITF result in opposing cellular phenotypes, because MITF-E87R via S100A4 enhanced invasion and reduced adhesion in contrast to wild-type MITF activity. Finally, we found that melanoma patients with altered S100A4 expression have poor prognosis. These data show that a change in MITF transcriptional activity from repression to activation of S100A4 that results from a point mutation in MITF alters melanoma invasive ability. These data suggest new opportunities for diagnosis and treatment of metastatic melanoma.