Author contributions L.X. and A.M contributed equally to this study. S.M., E.M. and A.B. planned the study, with input from M.P.S. and J.W. S.M. and E.M. performed the reprogramming experiments, and analysed and interpreted data. S.M., E.M. and L.X. wrote the manuscript with the help of A.B. S.M. generated, processed and analysed bulk and single-cell RNA-seq datasets, analysed the metabolomics data, and performed most THY1-related and conditioned medium experiments. E.M. generated and propagated transgene-free iPS cell lines. All other studies were done by both E.M and S.M., unless otherwise noted. A.M. and S.M. performed wound healing experiments under the supervision of M.T.L. L.X. helped with reprogramming, FACS, and immunofluorescence experiments. F.J. generated the in vitro single-cell RNA-seq data under the supervision of M.P.S. R.S. generated the ChIP-seq libraries under the supervision of J.W. K.H. helped with statistics and PAGODA analysis. X.L. performed metabolomics experiments and helped with metabolomics data analysis and validation under the supervision of M.P.S. K.D. helped with reprogramming and western blotting experiments. L.P. helped with reprogramming and RT-qPCR experiments. C.E.A. and Y.S. performed the induced neuron reprogramming experiment under the supervision of M.W. B.A.B. helped with analysis of the epigenomic data. A.L.S.C. identified and collected the human samples. All authors discussed the results and commented on the manuscript. Data availabilityAll raw sequencing reads for population RNA-seq, ChIP-seq and single-cell RNA-seq data can be found under BioProject PRJNA316110. The command and configuration files, in addition to a list of all versioned dependencies present in the running environment, are available on the Github repository for this paper (https://github.com/brunetlab/Mahmoudi_et_al_2018) (except for the code for the processing of metabolomics data, which is available upon request).

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The diversity of cell types is a challenge for quantifying aging and its reversal. Here we develop ‘aging clocks’ based on single-cell transcriptomics to characterize cell-type-specific aging and rejuvenation. We generated single-cell transcriptomes from the subventricular zone neurogenic region of 28 mice, tiling ages from young to old. We trained single-cell-based regression models to predict chronological age and biological age (neural stem cell proliferation capacity). These aging clocks are generalizable to independent cohorts of mice, other regions of the brains, and other species. To determine if these aging clocks could quantify transcriptomic rejuvenation, we generated single-cell transcriptomic datasets of neurogenic regions for two interventions—heterochronic parabiosis and exercise. Aging clocks revealed that heterochronic parabiosis and exercise reverse transcriptomic aging in neurogenic regions, but in different ways. This study represents the first development of high-resolution aging clocks from single-cell transcriptomic data and demonstrates their application to quantify transcriptomic rejuvenation.

Bax-Inhibitor-1 (BI-1) is an evolutionarily conserved cytoprotective protein that resides in membranes of the endoplasmic reticulum (ER). BI-1’s cytoprotective activity is manifested in the context of ER stress, with previous studies showing that BI-1 modulates several ER-associated functions, including Unfolded Protein Response (UPR) signaling. Here we investigated the role of BI-1 in neuroprotection by generating transgenic mice in which BI-1 was constitutively expressed from a neuronal-specific promoter. Cultured primary cortical neurons from BI-1 transgenic mouse embryos exhibited greater resistance to cell death induced by agents known to cause ER stress compared to their non-transgenic counterparts. While brain morphology and vasculature of BI-1 mice appeared to be unchanged from normal non-transgenic mice, BI-1 transgenic mice showed reduced brain/lesion volumes and better performance in motoric tests, compared with non-transgenic littermates, in two models of acute brain injury – stroke caused by middle cerebral artery occlusion (MCAO) and traumatic brain injury (TBI) caused by controlled cortical impact. Furthermore, brain tissue from BI-1 transgenic mice showed reduced levels of apoptotic cells and reduced induction of markers of ER stress after brain injury, including CHOP protein expression. In summary, our findings demonstrate that enforced neuronal expression of BI-1 reduces ER stress and provides protection from acute brain injury, suggesting that strategies for enhancing BI-1 expression or activity should be considered for development of new therapies for counteracting the consequences of stroke and acute brain trauma.

Aging manifests as progressive dysfunction culminating in death. The diversity of cell types is a challenge to the precise quantification of aging and its reversal. Here we develop a suite of 'aging clocks' based on single cell transcriptomic data to characterize cell type-specific aging and rejuvenation strategies. The subventricular zone (SVZ) neurogenic region contains many cell types and provides an excellent system to study cell-level tissue aging and regeneration. We generated 21,458 single-cell transcriptomes from the neurogenic regions of 28 mice, tiling ages from young to old. With these data, we trained a suite of single cell-based regression models (aging clocks) to predict both chronological age (passage of time) and biological age (fitness, in this case the proliferative capacity of the neurogenic region). Both types of clocks perform well on independent cohorts of mice. Genes underlying the single cell-based aging clocks are mostly cell-type specific, but also include a few shared genes in the interferon and lipid metabolism pathways. We used these single cell-based aging clocks to measure transcriptomic rejuvenation, by generating single cell RNA-seq datasets of SVZ neurogenic regions for two interventions - heterochronic parabiosis (young blood) and exercise. Interestingly, the use of aging clocks reveals that both heterochronic parabiosis and exercise reverse transcriptomic aging in the niche, but in different ways across cell types and genes. This study represents the first development of high-resolution aging clocks from single cell transcriptomic data and demonstrates their application to quantify transcriptomic rejuvenation.