Innate recognition of non-self nucleic acids

A variety of innate immune system receptors recognize and respond to the nucleic acids of invading pathogens

Emerging Roles of Cellular Metabolism in Regulating Dendritic Cell Subsets and Function

Dendritic cells (DCs) are the bridge between innate and T cell-dependent adaptive immunity and are promising therapeutic targets for cancer and immune-mediated disorders. Upon stimulation by pathogen or danger-sensing receptors, DCs become activated and poised to induce T cell priming. Recent studies have identified critical roles of metabolic pathways, including glycolysis, oxidative phosphorylation, and fatty acid metabolism, in orchestrating DC function. In this review, we discuss the shared and distinct metabolic programs shaping the functional specification of different DC subsets, including conventional DCs, bone marrow-derived DCs, and plasmacytoid DCs. We also briefly discuss the signaling networks that tune metabolic programs in DC subsets

Phosphoinositide 3-Kinase Enhancer Regulates Neuronal Dendritogenesis and Survival in Neocortex

Phosphoinositide 3-kinase enhancer (PIKE) binds and enhances phosphatidylinositol 3-kinase (PI3K)/Akt activities. However, its physiological functions in brain have never been explored. Here we show that PIKE is important in regulating the neuronal survival and development of neocortex. During development, enhanced apoptosis is observed in the ventricular zone of PIKE knock-out $(PIKE^{−/−})$ cortex. Moreover, $PIKE^{−/−}$ neurons show reduced dendritic complexity, dendritic branch length, and soma size. These defects are due to the reduced PI3K/Akt activities in $PIKE^{−/−}$ neurons, as the impaired dendritic arborization can be rescued when PI3K/Akt cascade is augmented in vitro or in $PIKE^{−/−}PTEN^{−/−}$ double-knock-out mice. Interestingly, $PIKE^{−/−}$ mice display behavioral abnormality in locomotion and spatial navigation. Because of the diminished PI3K/Akt activities, $PIKE^{−/−}$ neurons are more vulnerable to glutamate- or stroke-induced neuronal cell death. Together, our data established the critical role of PIKE in regulating neuronal survival and development by substantiating the PI3K/Akt pathway

Deficiency of Phosphoinositide 3-Kinase Enhancer Protects Mice From Diet-Induced Obesity and Insulin Resistance

OBJECTIVE: Phosphoinositide 3-kinase enhancer A (PIKE-A) is a proto-oncogene that promotes tumor growth and transformation by enhancing Akt activity. However, the physiological functions of PIKE-A in peripheral tissues are unknown. Here, we describe the effect of PIKE deletion in mice and explore the role of PIKE-A in obesity development. RESEARCH DESIGN AND METHODS: Whole-body PIKE knockout mice were generated and subjected to high-fat–diet feeding for 20 weeks. The glucose tolerance, tissue-specific insulin sensitivity, adipocyte differentiation, and lipid oxidation status were determined. The molecular mechanism of PIKE in the insulin signaling pathway was also studied. RESULTS: We show that PIKE-A regulates obesity development by modulating AMP-activated protein kinase (AMPK) phosphorylation. PIKE-A is important for insulin to suppress AMPK phosphorylation. The expression of PIKE-A is markedly increased in adipose tissue of obese mice, whereas depletion of PIKE-A inhibits adipocyte differentiation. PIKE knockout mice exhibit a prominent phenotype of lipoatrophy and are resistant to high-fat diet–induced obesity, liver steatosis, and diabetes. PIKE knockout mice also have augmented lipid oxidation, which is accompanied by enhanced AMPK phosphorylation in both muscle and adipose tissue. Moreover, insulin sensitivity is improved in PIKE-A–deficient muscle and fat, thus protecting the animals from diet-induced diabetes. CONCLUSIONS: Our results suggest that PIKE-A is implicated in obesity and associated diabetes development by negatively regulating AMPK activity

Metabolic signaling directs the reciprocal lineage decisions of αβ and γδ T cells

Wiring metabolic signaling circuits in thymocytes Cell differentiation is often accompanied by metabolic changes. Yang et al. report that generation of double-positive (DP) thymocytes from double-negative (DN) cells coincides with dynamic regulation of glycolytic and oxidative metabolism. Given the central role of mechanistic target of rapamycin complex 1 (mTORC1) signaling in regulating metabolic changes, they examined the role of mTORC1 pathway in thymocyte development by conditionally deleting RAPTOR, the key component of the mTORC1 complex, in thymocytes. Loss of RAPTOR impaired the DN-to-DP transition, but unexpectedly also perturbed the balance between αβ and γδ T cells and promoted the generation of γδ T cells. Their studies highlight an unappreciated role for mTORC1-dependent metabolic changes in controlling thymocyte fates. The interaction between extrinsic factors and intrinsic signal strength governs thymocyte development, but the mechanisms linking them remain elusive. We report that mechanistic target of rapamycin complex 1 (mTORC1) couples microenvironmental cues with metabolic programs to orchestrate the reciprocal development of two fundamentally distinct T cell lineages, the αβ and γδ T cells. Developing thymocytes dynamically engage metabolic programs including glycolysis and oxidative phosphorylation, as well as mTORC1 signaling. Loss of RAPTOR-mediated mTORC1 activity impairs the development of αβ T cells but promotes γδ T cell generation, associated with disrupted metabolic remodeling of oxidative and glycolytic metabolism. Mechanistically, we identify mTORC1-dependent control of reactive oxygen species production as a key metabolic signal in mediating αβ and γδ T cell development, and perturbation of redox homeostasis impinges upon thymocyte fate decisions and mTORC1-associated phenotypes. Furthermore, single-cell RNA sequencing and genetic dissection reveal that mTORC1 links developmental signals from T cell receptors and NOTCH to coordinate metabolic activity and signal strength. Our results establish mTORC1-driven metabolic signaling as a decisive factor for reciprocal αβ and γδ T cell development and provide insight into metabolic control of cell signaling and fate decisions. Development of αβ and γδ T cells requires coupling of environmental signals with metabolic and redox regulation by mTORC1. Development of αβ and γδ T cells requires coupling of environmental signals with metabolic and redox regulation by mTORC1

GSDMD is critical for autoinflammatory pathology in a mouse model of Familial Mediterranean Fever

Pyroptosis is an inflammasome-induced lytic cell death mode, the physiological role of which in chronic inflammatory diseases is unknown. Familial Mediterranean Fever (FMF) is the most common monogenic autoinflammatory disease worldwide, affecting an estimated 150,000 patients. The disease is caused by missense mutations in Mefv that activate the Pyrin inflammasome, but the pathophysiologic mechanisms driving autoinflammation in FMF are incompletely understood. Here, we show that Clostridium difficile infection of FMF knock-in macrophages that express a chimeric FMF-associated Mefv(V726A) Pyrin elicited pyroptosis and gasdermin D (GSDMD)-mediated interleukin (IL)-1 beta secretion. Importantly, in vivo GSDMD deletion abolished spontaneous autoinflammatory disease. GSDMD-deficient FMF knock-in mice were fully protected from the runted growth, anemia, systemic inflammatory cytokine production, neutrophilia, and tissue damage that characterize this autoinflammatory disease model. Overall, this work identifies pyroptosis as a critical mechanism of IL-1 beta-dependent autoinflammation in FMF and highlights GSDMD inhibition as a potential antiinflammatory strategy in inflammasome-driven diseases

Nutrient and Metabolic Sensing in T Cell Responses

T cells play pivotal roles in shaping host immune responses in infectious diseases, autoimmunity, and cancer. The activation of T cells requires immune and growth factor-derived signals. However, alterations in nutrients and metabolic signals tune T cell responses by impinging upon T cell fates and immune functions. In this review, we summarize how key nutrients, including glucose, amino acids, and lipids, and their sensors and transporters shape T cell responses. We also briefly discuss regulation of T cell responses by oxygen and energy sensing mechanisms

Two-tiered Online Optimization of Region-wide Datacenter Resource Allocation via Deep Reinforcement Learning

This paper addresses the important need for advanced techniques in continuously allocating workloads on shared infrastructures in data centers, a problem arising due to the growing popularity and scale of cloud computing. It particularly emphasizes the scarcity of research ensuring guaranteed capacity in capacity reservations during large-scale failures. To tackle these issues, the paper presents scalable solutions for resource management. It builds on the prior establishment of capacity reservation in cluster management systems and the two-level resource allocation problem addressed by the Resource Allowance System (RAS). Recognizing the limitations of Mixed Integer Linear Programming (MILP) for server assignment in a dynamic environment, this paper proposes the use of Deep Reinforcement Learning (DRL), which has been successful in achieving long-term optimal results for time-varying systems. A novel two-level design that utilizes a DRL-based algorithm is introduced to solve optimal server-to-reservation assignment, taking into account of fault tolerance, server movement minimization, and network affinity requirements due to the impracticality of directly applying DRL algorithms to large-scale instances with millions of decision variables. The paper explores the interconnection of these levels and the benefits of such an approach for achieving long-term optimal results in the context of large-scale cloud systems. We further show in the experiment section that our two-level DRL approach outperforms the MIP solver and heuristic approaches and exhibits significantly reduced computation time compared to the MIP solver. Specifically, our two-level DRL approach performs 15% better than the MIP solver on minimizing the overall cost. Also, it uses only 26 seconds to execute 30 rounds of decision making, while the MIP solver needs nearly an hour

Identification of Direct Target Engagement Biomarkers for Kinase-Targeted Therapeutics

Pharmacodynamic (PD) biomarkers are an increasingly valuable tool for decision-making and prioritization of lead compounds during preclinical and clinical studies as they link drug-target inhibition in cells with biological activity. They are of particular importance for novel, first-in-class mechanisms, where the ability of a targeted therapeutic to impact disease outcome is often unknown. By definition, proximal PD biomarkers aim to measure the interaction of a drug with its biological target. For kinase drug discovery, protein substrate phosphorylation sites represent candidate PD biomarkers. However, substrate phosphorylation is often controlled by input from multiple converging pathways complicating assessment of how potently a small molecule drug hits its target based on substrate phoshorylation measurements alone. Here, we report the use of quantitative, differential mass-spectrometry to identify and monitor novel drug-regulated phosphorylation sites on target kinases. Autophosphorylation sites constitute clinically validated biomarkers for select protein tyrosine kinase inhibitors. The present study extends this principle to phosphorylation sites in serine/threonine kinases looking beyond the T-loop autophosphorylation site. Specifically, for the 3′-phosphoinositide-dependent protein kinase 1 (PDK1), two phospho-residues p-PDK1Ser410 and p-PDK1Thr513 are modulated by small-molecule PDK1 inhibitors, and their degree of dephosphorylation correlates with inhibitor potency. We note that classical, ATP-competitive PDK1 inhibitors do not modulate PDK1 T-loop phosphorylation (p-PDK1Ser241), highlighting the value of an unbiased approach to identify drug target-regulated phosphorylation sites as these are complementary to pathway PD biomarkers. Finally, we extend our analysis to another protein Ser/Thr kinase, highlighting a broader utility of our approach for identification of kinase drug-target engagement biomarkers