TISSUE: uncertainty-calibrated prediction of single-cell spatial transcriptomics improves downstream analyses.

Whole-transcriptome spatial profiling of genes at single-cell resolution remains a challenge. To address this limitation, spatial gene expression prediction methods have been developed to infer the spatial expression of unmeasured transcripts, but the quality of these predictions can vary greatly. Here we present Transcript Imputation with Spatial Single-cell Uncertainty Estimation (TISSUE) as a general framework for estimating uncertainty for spatial gene expression predictions and providing uncertainty-aware methods for downstream inference. Leveraging conformal inference, TISSUE provides well-calibrated prediction intervals for predicted expression values across 11 benchmark datasets. Moreover, it consistently reduces the false discovery rate for differential gene expression analysis, improves clustering and visualization of predicted spatial transcriptomics and improves the performance of supervised learning models trained on predicted gene expression profiles. Applying TISSUE to a MERFISH spatial transcriptomics dataset of the adult mouse subventricular zone, we identified subtypes within the neural stem cell lineage and developed subtype-specific regional classifiers.

Single-cell analysis reveals T cell infiltration in old neurogenic niches.

The mammalian brain contains neurogenic niches that comprise neural stem cells and other cell types. Neurogenic niches become less functional with age, but how they change during ageing remains unclear. Here we perform single-cell RNA sequencing of young and old neurogenic niches in mice. The analysis of 14,685 single-cell transcriptomes reveals a decrease in activated neural stem cells, changes in endothelial cells and microglia, and an infiltration of T cells in old neurogenic niches. T cells in old brains are clonally expanded and are generally distinct from those in old blood, which suggests that they may experience specific antigens. T cells in old brains also express interferon-γ, and the subset of neural stem cells that has a high interferon response shows decreased proliferation in vivo. We find that T cells can inhibit the proliferation of neural stem cells in co-cultures and in vivo, in part by secreting interferon-γ. Our study reveals an interaction between T cells and neural stem cells in old brains, opening potential avenues through which to counteract age-related decline in brain function.

Spatiotemporal transcriptomic profiling and modeling of mouse brain at single-cell resolution reveals cell proximity effects of aging and rejuvenation.

Old age is associated with a decline in cognitive function and an increase in neurodegenerative disease risk1. Brain aging is complex and accompanied by many cellular changes2-20. However, the influence that aged cells have on neighboring cells and how this contributes to tissue decline is unknown. More generally, the tools to systematically address this question in aging tissues have not yet been developed. Here, we generate spatiotemporal data at single-cell resolution for the mouse brain across lifespan, and we develop the first machine learning models based on spatial transcriptomics ('spatial aging clocks') to reveal cell proximity effects during brain aging and rejuvenation. We collect a single-cell spatial transcriptomics brain atlas of 4.2 million cells from 20 distinct ages and across two rejuvenating interventions-exercise and partial reprogramming. We identify spatial and cell type-specific transcriptomic fingerprints of aging, rejuvenation, and disease, including for rare cell types. Using spatial aging clocks and deep learning models, we find that T cells, which infiltrate the brain with age, have a striking pro-aging proximity effect on neighboring cells. Surprisingly, neural stem cells have a strong pro-rejuvenating effect on neighboring cells. By developing computational tools to identify mediators of these proximity effects, we find that pro-aging T cells trigger a local inflammatory response likely via interferon-γ whereas pro-rejuvenating neural stem cells impact the metabolism of neighboring cells possibly via growth factors (e.g. vascular endothelial growth factor) and extracellular vesicles, and we experimentally validate some of these predictions. These results suggest that rare cells can have a drastic influence on their neighbors and could be targeted to counter tissue aging. We anticipate that these spatial aging clocks will not only allow scalable assessment of the efficacy of interventions for aging and disease but also represent a new tool for studying cell-cell interactions in many spatial contexts.

Identification of protein aggregates in the aging vertebrate brain with prion-like and phase-separation properties.

Protein aggregation, which can sometimes spread in a prion-like manner, is a hallmark of neurodegenerative diseases. However, whether prion-like aggregates form during normal brain aging remains unknown. Here, we use quantitative proteomics in the African turquoise killifish to identify protein aggregates that accumulate in old vertebrate brains. These aggregates are enriched for prion-like RNA-binding proteins, notably the ATP-dependent RNA helicase DDX5. We validate that DDX5 forms aggregate-like puncta in the brains of old killifish and mice. Interestingly, DDX5's prion-like domain allows these aggregates to propagate across many generations in yeast. In vitro, DDX5 phase separates into condensates. Mutations that abolish DDX5 prion propagation also impair the protein's ability to phase separate. DDX5 condensates exhibit enhanced enzymatic activity, but they can mature into inactive, solid aggregates. Our findings suggest that protein aggregates with prion-like properties form during normal brain aging, which could have implications for the age-dependency of cognitive decline.

TISSUE: uncertainty-calibrated prediction of single-cell spatial transcriptomics improves downstream analyses.

Whole-transcriptome spatial profiling of genes at single-cell resolution remains a challenge. To address this limitation, spatial gene expression prediction methods have been developed to infer the spatial expression of unmeasured transcripts, but the quality of these predictions can vary greatly. Here we present TISSUE (Transcript Imputation with Spatial Single-cell Uncertainty Estimation) as a general framework for estimating uncertainty for spatial gene expression predictions and providing uncertainty-aware methods for downstream inference. Across eleven benchmark datasets, TISSUE provides well-calibrated prediction intervals for predicted expression values. Moreover it consistently reduces false discovery rates for differential gene expression analysis, improves clustering and visualization of predicted spatial transcriptomics, and improves the performance of supervised learning models trained on predicted gene expression profiles. Applying TISSUE to a MERFISH spatial transcriptomics dataset of the adult mouse subventricular zone, we identified subtypes within the neural stem cell lineage and developed subtype-specific regional classifiers. TISSUE is publicly available as a flexible wrapper method for existing spatial gene expression prediction methods to assist researchers with implementing uncertainty-aware analyses of spatial transcriptomics data.

Chromatin accessibility dynamics of neurogenic niche cells reveal defects in neural stem cell adhesion and migration during aging.

The regenerative potential of brain stem cell niches deteriorates during aging. Yet the mechanisms underlying this decline are largely unknown. Here we characterize genome-wide chromatin accessibility of neurogenic niche cells in vivo during aging. Interestingly, chromatin accessibility at adhesion and migration genes decreases with age in quiescent neural stem cells (NSCs) but increases with age in activated (proliferative) NSCs. Quiescent and activated NSCs exhibit opposing adhesion behaviors during aging: quiescent NSCs become less adhesive, whereas activated NSCs become more adhesive. Old activated NSCs also show decreased migration in vitro and diminished mobilization out of the niche for neurogenesis in vivo. Using tension sensors, we find that aging increases force-producing adhesions in activated NSCs. Inhibiting the cytoskeletal-regulating kinase ROCK reduces these adhesions, restores migration in old activated NSCs in vitro, and boosts neurogenesis in vivo. These results have implications for restoring the migratory potential of NSCs and for improving neurogenesis in the aged brain.

Aging and Rejuvenation of Neural Stem Cells and Their Niches.

Aging has a profound and devastating effect on the brain. Old age is accompanied by declining cognitive function and enhanced risk of brain diseases, including cancer and neurodegenerative disorders. A key question is whether cells with regenerative potential contribute to brain health and even brain "rejuvenation." This review discusses mechanisms that regulate neural stem cells (NSCs) during aging, focusing on the effect of metabolism, genetic regulation, and the surrounding niche. We also explore emerging rejuvenating strategies for old NSCs. Finally, we consider how new technologies may help harness NSCs' potential to restore healthy brain function during physiological and pathological aging.

The WDR11 complex facilitates the tethering of AP-1-derived vesicles.

Vesicluar transport of proteins from endosomes to the trans-Golgi network (TGN) is an essential cellular pathway, but much of its machinery is still unknown. A screen for genes involved in endosome-to-TGN trafficking produced two hits, the adaptor protein-1 (AP-1 complex), which facilitates vesicle budding, and WDR11. Here we demonstrate that WDR11 forms a stable complex with two other proteins, which localises to the TGN region and does not appear to be associated with AP-1, suggesting it may act downstream from budding. In a vesicle tethering assay, capture of vesicles by golgin-245 was substantially reduced in WDR11-knockout cells. Moreover, structured illumination microscopy and relocation assays indicate that the WDR11 complex is initially recruited onto vesicles rather than the TGN, where it may in turn recruit the golgin binding partner TBC1D23. We propose that the complex acts together with TBC1D23 to facilitate the golgin-mediated capture of vesicles that were generated using AP-1.

Contribution of the clathrin adaptor AP-1 subunit µ1 to acidic cluster protein sorting.

Acidic clusters act as sorting signals for packaging cargo into clathrin-coated vesicles (CCVs), and also facilitate down-regulation of MHC-I by HIV-1 Nef. To find acidic cluster sorting machinery, we performed a gene-trap screen and identified the medium subunit (µ1) of the clathrin adaptor AP-1 as a top hit. In µ1 knockout cells, intracellular CCVs still form, but acidic cluster proteins are depleted, although several other CCV components were either unaffected or increased, indicating that cells can compensate for long-term loss of AP-1. In vitro experiments showed that the basic patch on µ1 that interacts with the Nef acidic cluster also contributes to the binding of endogenous acidic cluster proteins. Surprisingly, µ1 mutant proteins lacking the basic patch and/or the tyrosine-based motif binding pocket could rescue the µ1 knockout phenotype completely. In contrast, these mutants failed to rescue Nef-induced down-regulation of MHC class I, suggesting a possible mechanism for attacking the virus while sparing the host cell.

Tensor-based morphometry and stereology reveal brain pathology in the complexin1 knockout mouse.

Complexins (Cplxs) are small, soluble, regulatory proteins that bind reversibly to the SNARE complex and modulate synaptic vesicle release. Cplx1 knockout mice (Cplx1(-/-)) have the earliest known onset of ataxia seen in a mouse model, although hitherto no histopathology has been described in these mice. Nevertheless, the profound neurological phenotype displayed by Cplx1(-/-) mutants suggests that significant functional abnormalities must be present in these animals. In this study, MRI was used to automatically detect regions where structural differences were not obvious when using a traditional histological approach. Tensor-based morphometry of Cplx1(-/-) mouse brains showed selective volume loss from the thalamus and cerebellum. Stereological analysis of Cplx1(-/-) and Cplx1(+/+) mice brain slices confirmed the volume loss in the thalamus as well as loss in some lobules of the cerebellum. Finally, stereology was used to show that there was loss of cerebellar granule cells in Cplx1(-/-) mice when compared to Cplx1(+/+) animals. Our study is the first to describe pathological changes in Cplx1(-/-) mouse brain. We suggest that the ataxia in Cplx1(-/-) mice is likely to be due to pathological changes in both cerebellum and thalamus. Reduced levels of Cplx proteins have been reported in brains of patients with neurodegenerative diseases. Therefore, understanding the effects of Cplx depletion in brains from Cplx1(-/-) mice may also shed light on the mechanisms underlying pathophysiology in disorders in which loss of Cplx1 occurs.