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mTORC1 is a protein kinase important for metabolism and is regulated by growth factor and nutrient signaling pathways, mediated by the Rheb and Rag GTPases, respectively. Here we provide the first animal model in which both pathways were upregulated through concurrent mutations in their GTPase-activating proteins, Tsc1 and Depdc5. Unlike former models that induced limited mTORC1 upregulation, hepatic deletion of both Tsc1 and Depdc5 (DKO) produced strong, synergistic activation of the mTORC1 pathway and provoked pronounced and widespread hepatocyte damage, leading to externally visible liver failure phenotypes, such as jaundice and systemic growth defects. The transcriptome profile of DKO was different from single knockout mutants but similar to those of diseased human livers with severe hepatitis and mouse livers challenged with oxidative stress-inducing chemicals. In addition, DKO liver cells exhibited prominent molecular pathologies associated with excessive endoplasmic reticulum (ER) stress, oxidative stress, DNA damage and inflammation. Although DKO liver pathologies were ameliorated by mTORC1 inhibition, ER stress suppression unexpectedly aggravated them, suggesting that ER stress signaling is not the major conduit of how hyperactive mTORC1 produces liver damage. Interestingly, superoxide scavengers N-acetylcysteine (NAC) and Tempol, chemicals that reduce oxidative stress, were able to recover liver phenotypes, indicating that mTORC1 hyperactivation induced liver damage mainly through oxidative stress pathways. Our study provides a new model of unregulated mTORC1 activation through concomitant upregulation of growth factor and nutrient signaling axes and shows that mTORC1 hyperactivation alone can provoke oxidative tissue injury.

Spatial barcoding technologies have the potential to reveal histological details of transcriptomic profiles; however, they are currently limited by their low resolution. Here we report Seq-Scope, a spatial barcoding technology with a resolution almost comparable to an optical microscope. Seq-Scope is based on a solid-phase amplification of randomly barcoded single-molecule oligonucleotides using an Illumina sequencing-by-synthesis platform. The resulting clusters annotated with spatial coordinates are processed to expose RNA-capture moiety. These RNA-capturing barcoded clusters define the pixels of Seq-Scope that are approximately 0.5-1 μm apart from each other. From tissue sections, Seq-Scope visualizes spatial transcriptome heterogeneity at multiple histological scales, including tissue zonation according to the portal-central (liver), crypt-surface (colon) and inflammation-fibrosis (injured liver) axes, cellular components including single cell types and subtypes, and subcellular architectures of nucleus, cytoplasm and mitochondria. Seq-scope is quick, straightforward and easy-to-implement, and makes spatial single cell analysis accessible to a wide group of biomedical researchers.

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