Dysregulation of the adaptive immune system is a key feature of aging and is associated with age-related chronic diseases and mortality. Here, we find that T cell aging, especially in the CD4 subset, is controlled by B cells. B cells contributed to the age-related reduction of naive CD4 T cells, their differentiation toward immunosenescent T cell subsets, and age-associated T cell receptor clonal restriction. Concurrently, mice lacking B cells displayed improvements in health span and life span. We uncovered a role for B cell-intrinsic insulin receptor signaling in influencing age-related B cell phenotypes that in turn induces CD4 T cell dysfunction, a process that is in part driven by major histocompatibility complex class II. These results identify B cells as critical mediators driving age-associated adaptive immune dysfunction and health-span outcomes and suggest previously unrecognized modalities to manage aging and related health decline.

Treatment resistance in glioblastoma (GBM) is largely driven by the extensive multi-level heterogeneity that typifies this disease. Despite significant progress toward elucidating GBM's genomic and transcriptional heterogeneity, a critical knowledge gap remains in defining this heterogeneity at the spatial level. To address this, we employed spatial transcriptomics to map the architecture of the GBM ecosystem. This revealed tumor cell states that are jointly defined by gene expression and spatial localization, and multicellular niches whose composition varies along the tumor core-edge axis. Ligand-receptor interaction analysis uncovered a complex network of intercellular communication, including niche- and region-specific interactions. Finally, we found that CD8 positive GZMK positive T cells colocalize with LYVE1 positive CD163 positive myeloid cells in vascular regions, suggesting a potential mechanism for immune evasion. These findings provide novel insights into the GBM tumor microenvironment, highlighting previously unrecognized patterns of spatial organization and intercellular interactions, and novel therapeutic avenues to disrupt tumor-promoting interactions and overcome immune resistance.

While non-mammalian embryos often rely on spatial pre-patterning, mammalian development has long been thought to begin with equivalent blastomeres. However, emerging evidence challenges this. Here, using multiplexed and label-free single-cell proteomics, we identify over 300 asymmetrically abundant proteins-many involved in protein degradation and transport-dividing mouse 2-cell-stage blastomeres into two distinct clusters, which we term alpha and beta. These proteomic asymmetries are detectable as early as the zygote stage, intensify by the 4-cell stage, and correlate with the sperm entry site, implicating fertilization as a symmetry-breaking event. Splitting 2-cell-stage embryos into halves reveals that beta blastomeres possess greater developmental potential than alpha blastomeres. Similar clustering and protein enrichment patterns found in human 2-cell embryos suggest this early asymmetry might be conserved. These findings uncover a previously unrecognized proteomic pre-patterning triggered by fertilization in mammalian embryos, with important implications for understanding totipotency and early lineage bias.

Genomic and epigenetic profiling, particularly DNA methylation analysis, have refined the molecular classification of meningiomas and revealed marked intratumoral heterogeneity. To further characterize heterogeneity within and between patients, we analyzed meningiomas using single-cell RNA sequencing (n=11), whole-exome sequencing (n=9), and spatial transcriptomics (n=3). Single-cell analysis revealed six transcriptionally distinct tumor cell states that corresponded to unique biological processes. Integration of the single-cell data with published exome and bulk RNA sequencing data from a large cohort revealed significant associations among somatic variants, tumor cell states, and immunological signatures. Notably, NF2-altered tumors were enriched for an epithelial-to-mesenchymal transition (EMT) cell state and immune cells, whereas NF2-intact tumors were enriched for a sterol metabolism cell state. Spatial transcriptomic analysis confirmed co-localization of immune cells and EMT tumor cells. Comparisons with immune cells from other brain tumors and peripheral tissues highlighted immunological cell states specific to meningioma. Collectively, these findings refine our genetic and molecular understanding of meningioma heterogeneity and underscore the link between genotype and molecular phenotype.

The "gut-brain axis" is an emerging target in Alzheimer's disease (AD), although its immunological features remain poorly understood. Using single-cell RNA sequencing, coupled to extensive spectral-tuning flow cytometry validation of the colon immune compartment in the 5XFAD amyloid-β mouse model, we found several AD-associated changes including in B/plasma cell activity. Notably, levels of CXCR4+ antibody-secreting cells are reduced in 5XFAD colons. This change corresponds with accumulating CXCR4+ B cells and gut-specific IgA+ cells in the brain and dura mater, respectively. Consistently, a chemokine ligand for CXCR4, CXCL12, is expressed at higher levels in the 5XFAD brain and in in silico-analyzed human AD brain studies, supporting altered neuroimmune trafficking. An inulin prebiotic fiber diet could expand gut IgA+ cells, rescue peripheral Treg levels, reduce dysbiosis, improve serum microbial metabolite levels, and attenuate overall AD-associated frailty. Our study reveals key aspects of the gut-brain axis and highlights potential targets against AD.

Gene markers for Xenium in situ cell type identification.

Abstract We integrated single-cell RNA-sequencing, Visium spatial transcriptomic, and Xenium in situ transcriptomic data to identify differences in cell composition between the tumor core and infiltrating edge in IDHWT glioblastoma (GBM). Using CellTrek, an algorithm that maps single cells to their most-likely locations in spatial transcriptomic data, we identified extensive spatial organization in GBM. Cell mapping revealed distinct regions enriched for tumor, immune, endothelial, neuronal, and glial cells. These were associated with the location of the tissue sample – edge regions were enriched for neurons and glia (as expected), while core regions were enriched for tumor cells and infiltrating immune cells, particularly macrophages. Within the core samples, the tumor and immune cells tended to occupy distinct spatial niches. Spatial clustering of mapped tumor cells across all samples revealed five spatially segregated tumor cell states, each associated with specific biological processes, including (1) histone methylation, (2) proliferation, (3) wound-healing, EMT, and antigen presentation, (4) hypoxia response, and (5) stem cell differentiation. These tumor cell states exhibited preferential colocalization with specific non-malignant cell types. For instance, antigen-presenting/wound-healing tumor cells tended to colocalize with diverse immune cells, while stem-like tumor cells tended to reside in neuron-rich regions at the tumor edge. Next, to identify ligand-receptor interactions governing this spatial organization, we analyzed known ligand-receptor pairs within all three data types. This revealed known and novel mediators of tumor cell interactions with vasculature, lymphoid cells, myeloid cells, neurons, and glia. While some interactions were shared across all tumor cell states (e.g. all tumor cell states interacted with myeloid cells via APP/CD74 interactions), others were specific to particular tumor cell states (e.g. wound-healing/antigen-presenting tumor cells interacted with macrophages via CSF1/CSF1R, while proliferating and stem-like tumor cells interacted with neurons through multiple known NRXN/NLGN interactions). These interactions suggest potential targets for clinical disruption of the tumor ecosystem.

Analysis of RNA Tirosh exhaustion and inhibitory scores expressed by T cells from cohort 1.

Patient demographics and sample characteristics.

Single-cell proteomics by mass spectrometry (MS) allows quantifying proteins with high specificity and sensitivity. To increase its throughput, we developed nPOP, a method for parallel preparation of thousands of single cells in nanoliter volume droplets deposited on glass slides. Here, we describe its protocol with emphasis on its flexibility to prepare samples for different multiplexed MS methods. An implementation with plexDIA demonstrates accurate quantification of about 3,000 - 3,700 proteins per human cell. The protocol is implemented on the CellenONE instrument and uses readily available consumables, which should facilitate broad adoption. nPOP can be applied to all samples that can be processed to a single-cell suspension. It takes 1 or 2 days to prepare over 3,000 single cells. We provide metrics and software for quality control that can support the robust scaling of nPOP to higher plex reagents for achieving reliable high-throughput single-cell protein analysis.

Single-cell tissue atlases commonly use RNA abundances as surrogates for protein abundances. Yet, protein abundance also depends on the regulation of protein synthesis and degradation rates. To estimate the contributions of such post transcriptional regulation, we quantified the proteomes of 5,883 single cells from human testis using 3 distinct mass spectrometry methods (SCoPE2, pSCoPE, and plexDIA). To distinguish between biological and technical factors contributing to differences between protein and RNA levels, we developed BayesPG, a Bayesian model of transcript and protein abundance that systematically accounts for technical variation and infers biological differences. We use BayesPG to jointly model RNA and protein data collected from 29,709 single cells across different methods and datasets. BayesPG estimated consensus mRNA and protein levels for 3,861 gene products and quantified the relative protein-to-mRNA ratio (rPTR) for each gene across six distinct cell types in samples from human testis. About 28% of the gene products exhibited significant differences at protein and RNA levels and contributed to about 1, 500 significant GO groups. We observe that specialized and context specific functions, such as those related to spermatogenesis are regulated after transcription. Among hundreds of detected post translationally modified peptides, many show significant abundance differences across cell types. Furthermore, some phosphorylated peptides covary with kinases in a cell-type dependent manner, suggesting cell-type specific regulation. Our results demonstrate the potential of inferring protein regulation in from single-cell proteogenomic data and provide a generalizable model, BayesPG, for performing such analyses.

Vestibular schwannomas (VS) are benign tumors that lead to significant neurologic and otologic morbidity. How VS heterogeneity and the tumor microenvironment (TME) contribute to VS pathogenesis remains poorly understood. In this study, we perform scRNA-seq on 15 VS, with paired scATAC-seq ( n = 6) and exome sequencing ( n = 12). We identify diverse Schwann cell (SC), stromal, and immune populations in the VS TME and find that repair-like and MHC-II antigen-presenting SCs are associated with myeloid cell infiltrate, implicating a nerve injury-like process. Deconvolution analysis of RNA-expression data from 175 tumors reveals Injury-like tumors are associated with larger tumor size, and scATAC-seq identifies transcription factors associated with nerve repair SCs from Injury-like tumors. Ligand-receptor analysis and in vitro experiments suggest that Injury-like VS-SCs recruit myeloid cells via CSF1 signaling. Our study indicates that Injury-like SCs may cause tumor growth via myeloid cell recruitment and identifies molecular pathways that may be therapeutically targeted.

Physiological processes, such as the epithelial-mesenchymal transition (EMT), are mediated by changes in protein interactions. These changes may be better reflected in protein covariation within a cellular cluster than in the temporal dynamics of cluster-average protein abundance. To explore this possibility, we quantified proteins in single human cells undergoing EMT. Covariation analysis of the data revealed that functionally coherent protein clusters dynamically changed their protein-protein correlations without concomitant changes in the cluster-average protein abundance. These dynamics of protein-protein correlations were monotonic in time and delineated protein modules functioning in actin cytoskeleton organization, energy metabolism, and protein transport. These protein modules are defined by protein covariation within the same time point and cluster and, thus, reflect biological regulation masked by the cluster-average protein dynamics. Thus, protein correlation dynamics across single cells offers a window into protein regulation during physiological transitions.

Abstract Recent clinical trials have highlighted the limited efficacy of T cell–based immunotherapy in patients with glioblastoma (GBM). To better understand the characteristics of tumor-infiltrating lymphocytes (TIL) in GBM, we performed cellular indexing of transcriptomes and epitopes by sequencing and single-cell RNA sequencing with paired V(D)J sequencing, respectively, on TILs from two cohorts of patients totaling 15 patients with high-grade glioma, including GBM or astrocytoma, IDH-mutant, grade 4 (G4A). Analysis of the CD8+ TIL landscape reveals an enrichment of clonally expanded GZMK+ effector T cells in the tumor compared with matched blood, which was validated at the protein level. Furthermore, integration with other cancer types highlights the lack of a canonically exhausted CD8+ T-cell population in GBM TIL. These data suggest that GZMK+ effector T cells represent an important T-cell subset within the GBM microenvironment and may harbor potential therapeutic implications. Significance: To understand the limited efficacy of immune-checkpoint blockade in GBM, we applied a multiomics approach to understand the TIL landscape. By highlighting the enrichment of GZMK+ effector T cells and the lack of exhausted T cells, we provide a new potential mechanism of resistance to immunotherapy in GBM. This article is featured in Selected Articles from This Issue, p. 897

Pre-patterning of the embryo, driven by spatially localized factors, is a common feature across several non-mammalian species 1-4 . However, mammals display regulative development and thus it was thought that blastomeres of the embryo do not show such pre-patterning, contributing randomly to the three lineages of the blastocyst: the epiblast, primitive endoderm and trophectoderm that will generate the new organism, the yolk sac and placenta respectively 4-6 . Unexpectedly, early blastomeres of mouse and human embryos have been reported to have distinct developmental fates, potential and heterogeneous abundance of certain transcripts 7-12 . Nevertheless, the extent of the earliest intra-embryo differences remains unclear and controversial. Here, by utilizing multiplexed and label-free single-cell proteomics by mass-spectrometry 13 , we show that 2-cell mouse and human embryos contain an alpha and a beta blastomere as defined by differential abundance of hundreds of proteins exhibiting strong functional enrichment for protein synthesis, transport, and degradation. Such asymmetrically distributed proteins include Gps1 and Nedd8, depletion or overexpression of which in one blastomere of the 2-cell embryo impacts lineage segregation. These protein asymmetries increase at 4-cell stage. Intriguingly, halved mouse zygotes display asymmetric protein abundance that resembles alpha and beta blastomeres, suggesting differential proteome localization already within zygotes. We find that beta blastomeres give rise to a blastocyst with a higher proportion of epiblast cells than alpha blastomeres and that vegetal blastomeres, which are known to have a reduced developmental potential, are more likely to be alpha. Human 2-cell blastomeres also partition into two clusters sharing strong concordance with clusters found in mouse, in terms of differentially abundant proteins and functional enrichment. To our knowledge, this is the first demonstration of intra-zygotic and inter-blastomere proteomic asymmetry in mammals that has a role in lineage segregation.

TCR landscape of ex vivo expanded TIL does not recapitulate the initial TCR landscape.

DEGs of various T cell populations

Antibody markers and respective clone numbers.

Gene markers for cell type identification and gene signatures.