Summary Cellular lipid requirements are achieved through a combination of biosynthesis and import programs. Using isotope tracer analysis, we show that type I interferon (IFN) signaling shifts the balance of these programs by decreasing synthesis and increasing import of cholesterol and long chain fatty acids. Genetically enforcing this metabolic shift in macrophages is sufficient to render mice resistant to viral challenge, demonstrating the importance of reprogramming the balance of these two metabolic pathways in vivo. Unexpectedly, mechanistic studies reveal that limiting flux through the cholesterol biosynthetic pathway spontaneously engages a type I IFN response in a STING-dependent manner. The upregulation of type I IFNs was traced to a decrease in the pool size of synthesized cholesterol, and could be inhibited by replenishing cells with free cholesterol. Taken together, these studies delineate a metabolic-inflammatory circuit that links perturbations in cholesterol biosynthesis with activation of innate immunity.

The diffuse-type gastric cancer (DGC) is a subtype of gastric cancer with the worst prognosis and few treatment options. Here we present a dataset from 84 DGC patients, composed of a proteome of 11,340 gene products and mutation information of 274 cancer driver genes covering paired tumor and nearby tissue. DGC can be classified into three subtypes (PX1–3) based on the altered proteome alone. PX1 and PX2 exhibit dysregulation in the cell cycle and PX2 features an additional EMT process; PX3 is enriched in immune response proteins, has the worst survival, and is insensitive to chemotherapy. Data analysis revealed four major vulnerabilities in DGC that may be targeted for treatment, and allowed the nomination of potential immunotherapy targets for DGC patients, particularly for those in PX3. This dataset provides a rich resource for information and knowledge mining toward altered signaling pathways in DGC and demonstrates the benefit of proteomic analysis in cancer molecular subtyping.

As a circadian organ, liver executes diverse functions in different phase of the circadian clock. This process is believed to be driven by a transcription program. Here, we present a transcription factor (TF) DNA-binding activity-centered multi-dimensional proteomics landscape of the mouse liver, which includes DNA-binding profiles of different TFs, phosphorylation, and ubiquitylation patterns, the nuclear sub-proteome, the whole proteome as well as the transcriptome, to portray the hierarchical circadian clock network of this tissue. The TF DNA-binding activity indicates diurnal oscillation in four major pathways, namely the immune response, glucose metabolism, fatty acid metabolism, and the cell cycle. We also isolate the mouse liver Kupffer cells and measure their proteomes during the circadian cycle to reveal a cell-type resolved circadian clock. These comprehensive data sets provide a rich data resource for the understanding of mouse hepatic physiology around the circadian clock.

Plasma membranes of animal cells are enriched for cholesterol. Cholesterol-dependent cytolysins (CDCs) are pore forming toxins secreted by bacteria that target membrane cholesterol for their effector function. Phagocytes are essential for clearance of CDC-producing bacteria; however, mechanisms these cells use to evade the deleterious effects of CDCs are largely unknown. Here, we report that interferon (IFN) signals convey resistance to CDC-induced pores on macrophages Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms

Transcription factors (TFs) drive various biological processes ranging from embryonic development to carcinogenesis. Here, we employ a recently developed concatenated tandem array of consensus TF response elements (catTFRE) approach to profile the activated TFs in 24 adult and 8 fetal mouse tissues on proteome scale. A total of 941 TFs are quantitatively identified, representing over 60% of the TFs in the mouse genome. Using an integrated omics approach, we present a TF network in the major organs of the mouse, allowing data mining and generating knowledge to elucidate the roles of TFs in various biological processes, including tissue type maintenance and determining the general features of a physiological system. This study provides a landscape of TFs in mouse tissues that can be used to elucidate transcriptional regulatory specificity and programming and as a baseline that may facilitate understanding diseases that are regulated by TFs.

Highlights d A quantitative profiling of the mouse macrophage lipidome activated by immune stimuli d Macrophages alter lipid composition in a TLR-specific manner d MyD88-dependent TLRs alter lipid composition by increasing de novo MUFA synthesis d Inhibiting MUFA synthesis increases inflammation generated by MyD88-dependent TLRs

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