Systems Immunology Approaches to Metabolism.

Over the last decade, immunometabolism has emerged as a novel interdisciplinary field of research and yielded significant fundamental insights into the regulation of immune responses. Multiple classical approaches to interrogate immunometabolism, including bulk metabolic profiling and analysis of metabolic regulator expression, paved the way to appreciating the physiological complexity of immunometabolic regulation in vivo. Studying immunometabolism at the systems level raised the need to transition towards the next-generation technology for metabolic profiling and analysis. Spatially resolved metabolic imaging and computational algorithms for multi-modal data integration are new approaches to connecting metabolism and immunity. In this review, we discuss recent studies that highlight the complex physiological interplay between immune responses and metabolism and give an overview of technological developments that bear the promise of capturing this complexity most directly and comprehensively.

Insights Gained from Single-Cell Analysis of Immune Cells in the Tumor Microenvironment.

Understanding tumor immune microenvironments is critical for identifying immune modifiers of cancer progression and developing cancer immunotherapies. Recent applications of single-cell RNA sequencing (scRNA-seq) in dissecting tumor microenvironments have brought important insights into the biology of tumor-infiltrating immune cells, including their heterogeneity, dynamics, and potential roles in both disease progression and response to immune checkpoint inhibitors and other immunotherapies. This review focuses on the advances in knowledge of tumor immune microenvironments acquired from scRNA-seq studies across multiple types of human tumors, with a particular emphasis on the study of phenotypic plasticity and lineage dynamics of immune cells in the tumor environment. We also discuss several imminent questions emerging from scRNA-seq observations and their potential solutions on the horizon.

Understanding Human Autoimmunity and Autoinflammation Through Transcriptomics.

Transcriptomics, the high-throughput characterization of RNAs, has been instrumental in defining pathogenic signatures in human autoimmunity and autoinflammation. It enabled the identification of new therapeutic targets in IFN-, IL-1- and IL-17-mediated diseases. Applied to immunomonitoring, transcriptomics is starting to unravel diagnostic and prognostic signatures that stratify patients, track molecular changes associated with disease activity, define personalized treatment strategies, and generally inform clinical practice. Herein, we review the use of transcriptomics to define mechanistic, diagnostic, and predictive signatures in human autoimmunity and autoinflammation. We discuss some of the analytical approaches applied to extract biological knowledge from high-dimensional data sets. Finally, we touch upon emerging applications of transcriptomics to study eQTLs, B and T cell repertoire diversity, and isoform usage.

Integrative spatial analysis reveals a multi-layered organization of glioblastoma.

Glioma contains malignant cells in diverse states. Here, we combine spatial transcriptomics, spatial proteomics, and computational approaches to define glioma cellular states and uncover their organization. We find three prominent modes of organization. First, gliomas are composed of small local environments, each typically enriched with one major cellular state. Second, specific pairs of states preferentially reside in proximity across multiple scales. This pairing of states is consistent across tumors. Third, these pairwise interactions collectively define a global architecture composed of five layers. Hypoxia appears to drive the layers, as it is associated with a long-range organization that includes all cancer cell states. Accordingly, tumor regions distant from any hypoxic/necrotic foci and tumors that lack hypoxia such as low-grade IDH-mutant glioma are less organized. In summary, we provide a conceptual framework for the organization of cellular states in glioma, highlighting hypoxia as a long-range tissue organizer.

TULIPs decorate the three-dimensional genome of PFA ependymoma.

Posterior fossa group A (PFA) ependymoma is a lethal brain cancer diagnosed in infants and young children. The lack of driver events in the PFA linear genome led us to search its 3D genome for characteristic features. Here, we reconstructed 3D genomes from diverse childhood tumor types and uncovered a global topology in PFA that is highly reminiscent of stem and progenitor cells in a variety of human tissues. A remarkable feature exclusively present in PFA are type B ultra long-range interactions in PFAs (TULIPs), regions separated by great distances along the linear genome that interact with each other in the 3D nuclear space with surprising strength. TULIPs occur in all PFA samples and recur at predictable genomic coordinates, and their formation is induced by expression of EZHIP. The universality of TULIPs across PFA samples suggests a conservation of molecular principles that could be exploited therapeutically.

Open-ST: High-resolution spatial transcriptomics in 3D.

Spatial transcriptomics (ST) methods unlock molecular mechanisms underlying tissue development, homeostasis, or disease. However, there is a need for easy-to-use, high-resolution, cost-efficient, and 3D-scalable methods. Here, we report Open-ST, a sequencing-based, open-source experimental and computational resource to address these challenges and to study the molecular organization of tissues in 2D and 3D. In mouse brain, Open-ST captured transcripts at subcellular resolution and reconstructed cell types. In primary head-and-neck tumors and patient-matched healthy/metastatic lymph nodes, Open-ST captured the diversity of immune, stromal, and tumor populations in space, validated by imaging-based ST. Distinct cell states were organized around cell-cell communication hotspots in the tumor but not the metastasis. Strikingly, the 3D reconstruction and multimodal analysis of the metastatic lymph node revealed spatially contiguous structures not visible in 2D and potential biomarkers precisely at the 3D tumor/lymph node boundary. All protocols and software are available at https://rajewsky-lab.github.io/openst.

Time-resolved single-cell transcriptomics defines immune trajectories in glioblastoma.

Deciphering the cell-state transitions underlying immune adaptation across time is fundamental for advancing biology. Empirical in vivo genomic technologies that capture cellular dynamics are currently lacking. We present Zman-seq, a single-cell technology recording transcriptomic dynamics across time by introducing time stamps into circulating immune cells, tracking them in tissues for days. Applying Zman-seq resolved cell-state and molecular trajectories of the dysfunctional immune microenvironment in glioblastoma. Within 24 hours of tumor infiltration, cytotoxic natural killer cells transitioned to a dysfunctional program regulated by TGFB1 signaling. Infiltrating monocytes differentiated into immunosuppressive macrophages, characterized by the upregulation of suppressive myeloid checkpoints Trem2, Il18bp, and Arg1, over 36 to 48 hours. Treatment with an antagonistic anti-TREM2 antibody reshaped the tumor microenvironment by redirecting the monocyte trajectory toward pro-inflammatory macrophages. Zman-seq is a broadly applicable technology, enabling empirical measurements of differentiation trajectories, which can enhance the development of more efficacious immunotherapies.

A TCF4-dependent gene regulatory network confers resistance to immunotherapy in melanoma.

To better understand intrinsic resistance to immune checkpoint blockade (ICB), we established a comprehensive view of the cellular architecture of the treatment-naive melanoma ecosystem and studied its evolution under ICB. Using single-cell, spatial multi-omics, we showed that the tumor microenvironment promotes the emergence of a complex melanoma transcriptomic landscape. Melanoma cells harboring a mesenchymal-like (MES) state, a population known to confer resistance to targeted therapy, were significantly enriched in early on-treatment biopsies from non-responders to ICB. TCF4 serves as the hub of this landscape by being a master regulator of the MES signature and a suppressor of the melanocytic and antigen presentation transcriptional programs. Targeting TCF4 genetically or pharmacologically, using a bromodomain inhibitor, increased immunogenicity and sensitivity of MES cells to ICB and targeted therapy. We thereby uncovered a TCF4-dependent regulatory network that orchestrates multiple transcriptional programs and contributes to resistance to both targeted therapy and ICB in melanoma.

Neoadjuvant PARPi or chemotherapy in ovarian cancer informs targeting effector Treg cells for homologous-recombination-deficient tumors.

Homologous recombination deficiency (HRD) is prevalent in cancer, sensitizing tumor cells to poly (ADP-ribose) polymerase (PARP) inhibition. However, the impact of HRD and related therapies on the tumor microenvironment (TME) remains elusive. Our study generates single-cell gene expression and T cell receptor profiles, along with validatory multimodal datasets from >100 high-grade serous ovarian cancer (HGSOC) samples, primarily from a phase II clinical trial (NCT04507841). Neoadjuvant monotherapy with the PARP inhibitor (PARPi) niraparib achieves impressive 62.5% and 73.6% response rates per RECIST v.1.1 and GCIG CA125, respectively. We identify effector regulatory T cells (eTregs) as key responders to HRD and neoadjuvant therapies, co-occurring with other tumor-reactive T cells, particularly terminally exhausted CD8+ T cells (Tex). TME-wide interferon signaling correlates with cancer cells upregulating MHC class II and co-inhibitory ligands, potentially driving Treg and Tex fates. Depleting eTregs in HRD mouse models, with or without PARP inhibition, significantly suppresses tumor growth without observable toxicities, underscoring the potential of eTreg-focused therapeutics for HGSOC and other HRD-related tumors.

The life-saving benefit of dexamethasone in severe COVID-19 is linked to a reversal of monocyte dysregulation.

Dexamethasone is a life-saving treatment for severe COVID-19, yet its mechanism of action is unknown, and many patients deteriorate or die despite timely treatment initiation. Here, we identify dexamethasone treatment-induced cellular and molecular changes associated with improved survival in COVID-19 patients. We observed a reversal of transcriptional hallmark signatures in monocytes associated with severe COVID-19 and the induction of a monocyte substate characterized by the expression of glucocorticoid-response genes. These molecular responses to dexamethasone were detected in circulating and pulmonary monocytes, and they were directly linked to survival. Monocyte single-cell RNA sequencing (scRNA-seq)-derived signatures were enriched in whole blood transcriptomes of patients with fatal outcome in two independent cohorts, highlighting the potential for identifying non-responders refractory to dexamethasone. Our findings link the effects of dexamethasone to specific immunomodulation and reversal of monocyte dysregulation, and they highlight the potential of single-cell omics for monitoring in vivo target engagement of immunomodulatory drugs and for patient stratification for precision medicine approaches.

Molecular and spatial signatures of mouse brain aging at single-cell resolution.

The diversity and complex organization of cells in the brain have hindered systematic characterization of age-related changes in its cellular and molecular architecture, limiting our ability to understand the mechanisms underlying its functional decline during aging. Here, we generated a high-resolution cell atlas of brain aging within the frontal cortex and striatum using spatially resolved single-cell transcriptomics and quantified changes in gene expression and spatial organization of major cell types in these regions over the mouse lifespan. We observed substantially more pronounced changes in cell state, gene expression, and spatial organization of non-neuronal cells over neurons. Our data revealed molecular and spatial signatures of glial and immune cell activation during aging, particularly enriched in the subcortical white matter, and identified both similarities and notable differences in cell-activation patterns induced by aging and systemic inflammatory challenge. These results provide critical insights into age-related decline and inflammation in the brain.

Multimodal charting of molecular and functional cell states via in situ electro-sequencing.

Paired mapping of single-cell gene expression and electrophysiology is essential to understand gene-to-function relationships in electrogenic tissues. Here, we developed in situ electro-sequencing (electro-seq) that combines flexible bioelectronics with in situ RNA sequencing to stably map millisecond-timescale electrical activity and profile single-cell gene expression from the same cells across intact biological networks, including cardiac and neural patches. When applied to human-induced pluripotent stem-cell-derived cardiomyocyte patches, in situ electro-seq enabled multimodal in situ analysis of cardiomyocyte electrophysiology and gene expression at the cellular level, jointly defining cell states and developmental trajectories. Using machine-learning-based cross-modal analysis, in situ electro-seq identified gene-to-electrophysiology relationships throughout cardiomyocyte development and accurately reconstructed the evolution of gene expression profiles based on long-term stable electrical measurements. In situ electro-seq could be applicable to create spatiotemporal multimodal maps in electrogenic tissues, potentiating the discovery of cell types and gene programs responsible for electrophysiological function and dysfunction.

Spatiotemporal insight into early pregnancy governed by immune-featured stromal cells.

Endometrial decidualization connecting embryo implantation and placentation is transient but essential for successful pregnancy, which, however, is not systematically investigated. Here, we use a scStereo-seq technology to spatially visualize and define the dynamic functional decidual hubs assembled by distinct immune, endothelial, trophoblast, and decidual stromal cells (DSCs) in early pregnant mice. We unravel the DSC transdifferentiation trajectory and surprisingly discover a dual-featured type of immune-featured DSCs (iDSCs). We find that immature DSCs attract immune cells and induce decidual angiogenesis at the mesenchymal-epithelial transition hub during decidualization initiation. iDSCs enable immune cell recruitment and suppression, govern vascularization, and promote cytolysis at immune cell assembling and vascular hubs, respectively, to establish decidual homeostasis at a later stage. Interestingly, dysfunctional and spatially disordered iDSCs cause abnormal accumulation of immune cells in the vascular hub, which disrupts decidual hub specification and eventually leads to pregnancy complications in DBA/2-mated CBA/J mice.

SARS-CoV-2 variants evolve convergent strategies to remodel the host response.

SARS-CoV-2 variants of concern (VOCs) emerged during the COVID-19 pandemic. Here, we used unbiased systems approaches to study the host-selective forces driving VOC evolution. We discovered that VOCs evolved convergent strategies to remodel the host by modulating viral RNA and protein levels, altering viral and host protein phosphorylation, and rewiring virus-host protein-protein interactions. Integrative computational analyses revealed that although Alpha, Beta, Gamma, and Delta ultimately converged to suppress interferon-stimulated genes (ISGs), Omicron BA.1 did not. ISG suppression correlated with the expression of viral innate immune antagonist proteins, including Orf6, N, and Orf9b, which we mapped to specific mutations. Later Omicron subvariants BA.4 and BA.5 more potently suppressed innate immunity than early subvariant BA.1, which correlated with Orf6 levels, although muted in BA.4 by a mutation that disrupts the Orf6-nuclear pore interaction. Our findings suggest that SARS-CoV-2 convergent evolution overcame human adaptive and innate immune barriers, laying the groundwork to tackle future pandemics.

Stepwise emergence of the neuronal gene expression program in early animal evolution.

The assembly of the neuronal and other major cell type programs occurred early in animal evolution. We can reconstruct this process by studying non-bilaterians like placozoans. These small disc-shaped animals not only have nine morphologically described cell types and no neurons but also show coordinated behaviors triggered by peptide-secreting cells. We investigated possible neuronal affinities of these peptidergic cells using phylogenetics, chromatin profiling, and comparative single-cell genomics in four placozoans. We found conserved cell type expression programs across placozoans, including populations of transdifferentiating and cycling cells, suggestive of active cell type homeostasis. We also uncovered fourteen peptidergic cell types expressing neuronal-associated components like the pre-synaptic scaffold that derive from progenitor cells with neurogenesis signatures. In contrast, earlier-branching animals like sponges and ctenophores lacked this conserved expression. Our findings indicate that key neuronal developmental and effector gene modules evolved before the advent of cnidarian/bilaterian neurons in the context of paracrine cell signaling.

Self-demixing of mRNA copies buffers mRNA:mRNA and mRNA:regulator stoichiometries.

Cellular homeostasis requires the robust control of biomolecule concentrations, but how do millions of mRNAs coordinate their stoichiometries in the face of dynamic translational changes? Here, we identified a two-tiered mechanism controlling mRNA:mRNA and mRNA:protein stoichiometries where mRNAs super-assemble into condensates with buffering capacity and sorting selectivity through phase-transition mechanisms. Using C. elegans oogenesis arrest as a model, we investigated the transcriptome cytosolic reorganization through the sequencing of RNA super-assemblies coupled with single mRNA imaging. Tightly repressed mRNAs self-assembled into same-sequence nanoclusters that further co-assembled into multiphase condensates. mRNA self-sorting was concentration dependent, providing a self-buffering mechanism that is selective to sequence identity and controls mRNA:mRNA stoichiometries. The cooperative sharing of limiting translation repressors between clustered mRNAs prevented the disruption of mRNA:repressor stoichiometries in the cytosol. Robust control of mRNA:mRNA and mRNA:protein stoichiometries emerges from mRNA self-demixing and cooperative super-assembly into multiphase multiscale condensates with dynamic storage capacity.

Molecular cartography uncovers evolutionary and microenvironmental dynamics in sporadic colorectal tumors.

Colorectal cancer exhibits dynamic cellular and genetic heterogeneity during progression from precursor lesions toward malignancy. Analysis of spatial multi-omic data from 31 human colorectal specimens enabled phylogeographic mapping of tumor evolution that revealed individualized progression trajectories and accompanying microenvironmental and clonal alterations. Phylogeographic mapping ordered genetic events, classified tumors by their evolutionary dynamics, and placed clonal regions along global pseudotemporal progression trajectories encompassing the chromosomal instability (CIN+) and hypermutated (HM) pathways. Integrated single-cell and spatial transcriptomic data revealed recurring epithelial programs and infiltrating immune states along progression pseudotime. We discovered an immune exclusion signature (IEX), consisting of extracellular matrix regulators DDR1, TGFBI, PAK4, and DPEP1, that charts with CIN+ tumor progression, is associated with reduced cytotoxic cell infiltration, and shows prognostic value in independent cohorts. This spatial multi-omic atlas provides insights into colorectal tumor-microenvironment co-evolution, serving as a resource for stratification and targeted treatments.

Mapping the transcriptome: Realizing the full potential of spatial data analysis.

RNA sequencing in situ allows for whole-transcriptome characterization at high resolution, while retaining spatial information. These data present an analytical challenge for bioinformatics-how to leverage spatial information effectively? Properties of data with a spatial dimension require special handling, which necessitate a different set of statistical and inferential considerations when compared to non-spatial data. The geographical sciences primarily use spatial data and have developed methods to analye them. Here we discuss the challenges associated with spatial analysis and examine how we can take advantage of practice from the geographical sciences to realize the full potential of spatial information in transcriptomic datasets.

Spatiotemporal transcriptome atlas reveals the regional specification of the developing human brain.

Different functional regions of brain are fundamental for basic neurophysiological activities. However, the regional specification remains largely unexplored during human brain development. Here, by combining spatial transcriptomics (scStereo-seq) and scRNA-seq, we built a spatiotemporal developmental atlas of multiple human brain regions from 6-23 gestational weeks (GWs). We discovered that, around GW8, radial glia (RG) cells have displayed regional heterogeneity and specific spatial distribution. Interestingly, we found that the regional heterogeneity of RG subtypes contributed to the subsequent neuronal specification. Specifically, two diencephalon-specific subtypes gave rise to glutamatergic and GABAergic neurons, whereas subtypes in ventral midbrain were associated with the dopaminergic neurons. Similar GABAergic neuronal subtypes were shared between neocortex and diencephalon. Additionally, we revealed that cell-cell interactions between oligodendrocyte precursor cells and GABAergic neurons influenced and promoted neuronal development coupled with regional specification. Altogether, this study provides comprehensive insights into the regional specification in the developing human brain.

Pan-cancer analysis of post-translational modifications reveals shared patterns of protein regulation.

Post-translational modifications (PTMs) play key roles in regulating cell signaling and physiology in both normal and cancer cells. Advances in mass spectrometry enable high-throughput, accurate, and sensitive measurement of PTM levels to better understand their role, prevalence, and crosstalk. Here, we analyze the largest collection of proteogenomics data from 1,110 patients with PTM profiles across 11 cancer types (10 from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium [CPTAC]). Our study reveals pan-cancer patterns of changes in protein acetylation and phosphorylation involved in hallmark cancer processes. These patterns revealed subsets of tumors, from different cancer types, including those with dysregulated DNA repair driven by phosphorylation, altered metabolic regulation associated with immune response driven by acetylation, affected kinase specificity by crosstalk between acetylation and phosphorylation, and modified histone regulation. Overall, this resource highlights the rich biology governed by PTMs and exposes potential new therapeutic avenues.