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

High-resolution transcriptional dissection of in vivo Atoh1-mediated hair cell conversion in mature cochleae identifies Isl1 as a co-reprogramming factor.

In vivo direct conversion of differentiated cells holds promise for regenerative medicine; however, improving the conversion efficiency and producing functional target cells remain challenging. Ectopic Atoh1 expression in non-sensory supporting cells (SCs) in mouse cochleae induces their partial conversion to hair cells (HCs) at low efficiency. Here, we performed single-cell RNA sequencing of whole mouse sensory epithelia harvested at multiple time points after conditional overexpression of Atoh1. Pseudotemporal ordering revealed that converted HCs (cHCs) are present along a conversion continuum that correlates with both endogenous and exogenous Atoh1 expression. Bulk sequencing of isolated cell populations and single-cell qPCR confirmed 51 transcription factors, including Isl1, are differentially expressed among cHCs, SCs and HCs. In transgenic mice, co-overexpression of Atoh1 and Isl1 enhanced the HC conversion efficiency. Together, our study shows how high-resolution transcriptional profiling of direct cell conversion can identify co-reprogramming factors required for efficient conversion

Isl1 synergistically enhances Atoh1-mediated SC-to-HC conversion <i>ex vivo</i> and <i>in vivo</i>.

<p>(A-D) Immunofluorescence staining of GFP (green) and Myo6 (red) in cultured cochlear explants 7 days after transfection. The explants were prepared from mice at P0 and transfected by electroporation with IRES-GFP alone (A and A’), Atoh1-IRES-GFP (Atoh1, B and B’), Isl1-IRES-GFP (Isl1, C and C’), or Atoh1-IRES-GFP and Isl1-IRES-GFP (Atoh1+Isl1, D and D’). GFP+ cells indicate transfected cells, and Myo6a is a HC marker. White arrows indicate nonconverted GFP-transfected GER cells, and white arrowheads indicate converted HCs that are positive for GFP and Myo6. The white boxes in panels A-D are enlarged in panels A’-D’, respectively. Scale bars represent 100 μm in A-D and 50 μm in A’-D’. (E, F) Scatter plots showing the conversion rates (E) as defined by the number of GFP+/Myo6+ double-positive cells divided by the number of GFP+ cells and the transfection rates (F) as defined by the number of GFP+ GER cells of corresponding explants. Each dot represents a sample; lines indicate mean values. ***P < 0.001 by Student’s t-test. (G-H) Immunofluorescence staining of HA (green), mCherry (red), and parvalbumin (blue) in the HC layer of cochlear wholemounts of Fgfr3-iCreER; Atoh1-HA (Atoh1-HA, G-G”‘) and Fgfr3-iCreER; Atoh1-HA; Isl1-IRES-mCherry (Atoh1-HA; Isl1, H-H”‘) mice. The mice that received tamoxifen injection at P12 and P13 were analyzed at P33. Scale bars represent 10 μm. (I) Quantification of conversion rate (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007552#sec012" target="_blank">Methods</a> for the calculation) in Fgfr3-iCreER; tdTomato (Ctrl), Atoh1-HA, Fgfr3-iCreER; Isl1-IRES-mCherry (Isl1), and Atoh1-HA; Isl1 mice. Data are presented as average ± SEM. ***P < 0.001 by Student’s t-test.</p

A polygenic score for acute vaso-occlusive pain in pediatric sickle cell disease

Polygenic Risk Scores is from the Pain study described below: Recurrent acute pain, or vaso-occlusive pain crisis (VOP), is the most common complication of sickle cell disease and correlates strongly with increased hospital visits and early mortality PMID: 1710777. While the genetics of VOP in sickle cell patients has been studied (PMID: 29205277, 27883292, 25102390, 30079801, 22925497, 29531649, 29620434, 19468207, 20172753, 22576309, 30031848, 24136375, 27603703, 29559808), it is not fully understood. Using WGS, we interrogated the a-thalassemia deletion -a3.7 and 133 candidate risk single nucleotide polymorphisms (SNPs) across an additional 65 genes for association with VOP: 11 SNPs in 3 gene regions associated with fetal hemoglobin (HbF) and 122 additional SNPs in 62 genes previously reported to be associated with pain due to SCD and/or other etiologies. We then constructed unweighted polygenic risk scores (PGSs) by counting the total number of risk alleles per individual across the 11 HbF SNPs (PGSHbF) and the 5 SNPs in COMT (PGSCOMT), where COMT is the gene previously associated with SCD pain (PMID: 29559808, 15537663). We also defined a final PGS comprised of these 16 SNPs plus another 5 internally-validated candidate SNPs (PGSHbF+COMT+5snps), which was more strongly associated with acute VOP than any individual variant. Additionally, patients with the highest 5% of scores had 3-fold more pain events than the bottom 5% but were 5 times more likely to be on hydroxyurea, indicating that patients with high scores might benefit from a second drug

Resolving medulloblastoma cellular architecture by single-cell genomics

Medulloblastoma is a malignant childhood cerebellar tumour type that comprises distinct molecular subgroups. Whereas genomic characteristics of these subgroups are well defined, the extent to which cellular diversity underlies their divergent biology and clinical behaviour remains largely unexplored. Here we used single-cell transcriptomics to investigate intra- and intertumoral heterogeneity in 25 medulloblastomas spanning all molecular subgroups. WNT, SHH and Group 3 tumours comprised subgroup-specific undifferentiated and differentiated neuronal-like malignant populations, whereas Group 4 tumours consisted exclusively of differentiated neuronal-like neoplastic cells. SHH tumours closely resembled granule neurons of varying differentiation states that correlated with patient age. Group 3 and Group 4 tumours exhibited a developmental trajectory from primitive progenitor-like to more mature neuronal-like cells, the relative proportions of which distinguished these subgroups. Cross-species transcriptomics defined distinct glutamatergic populations as putative cells-of-origin for SHH and Group 4 subtypes. Collectively, these data provide insights into the cellular and developmental states underlying subtype-specific medulloblastoma biology