AbstractThe burgeoning interest in in situ multiplexed gene expression profiling technologies has opened new avenues for understanding cellular behavior and interactions. In this study, we present a comparative benchmark analysis of six in situ gene expression profiling methods, including both commercially available and academically developed methods, using publicly accessible mouse brain datasets. We find that standard sensitivity metrics, such as the number of unique molecules detected per cell, are not directly comparable across datasets due to substantial differences in the incidence of off-target molecular artifacts impacting specificity. To address these challenges, we explored various potential sources of molecular artifacts, developed novel metrics to control for them, and utilized these metrics to evaluate and compare different in situ technologies. Finally, we demonstrate how molecular false positives can seriously confound spatially-aware differential expression analysis, requiring caution in the interpretation of downstream results. Our analysis provides guidance for the selection, processing, and interpretation of in situ spatial technologies. <<<

AbstractSeveral computational methods have recently been developed for characterizing molecular tissue regions in spatially resolved transcriptomics (SRT) data. However, each method fundamentally relies on spatially smoothing transcriptomic features across neighboring cells. Here, we demonstrate that smoothing increases autocorrelation between neighboring cells, causing latent space to encode physical adjacency rather than spatial transcriptomic patterns. We find that randomly sub-sampling neighbors before smoothing mitigates autocorrelation, improving the performance of existing methods and further enabling a simpler, more efficient approach that we callspatialintegration (SPIN). SPIN leverages the conventional single-cell toolkit, yielding spatial analogies to each tool: clustering identifies molecular tissue regions; differentially expressed gene analysis calculates region marker genes; trajectory inference reveals continuous, molecularly defined ana tomical axes; and integration allows joint analysis across multiple SRT datasets, regardless of tissue morphology, spatial resolution, or experimental technology. We apply SPIN to SRT datasets from mouse and marmoset brains to calculate shared and species-specific region marker genes as well as a molecularly defined neocortical depth axis along which several genes and cell types differ across species. <<<

An essential prerequisite for evolution by natural selection is variation among individuals in traits that affect fitness. The ability of a system to produce selectable variation, known as evolvability, thus markedly affects the rate of evolution. Although the immune system is among the fastest-evolving components in mammals, the sources of variation in immune traits remain largely unknown. Here we show that an important determinant of the immune system's evolvability is its organization into interacting modules represented by different immune cell types. By profiling immune cell variation in bone marrow of 54 genetically diverse mouse strains from the Collaborative Cross, we found that variation in immune cell frequencies is polygenic and that many associated genes are involved in homeostatic balance through cell-intrinsic functions of proliferation, migration and cell death. However, we also found genes associated with the frequency of a particular cell type that are expressed in a different cell type, exerting their effect in what we term cyto-trans. The vertebrate evolutionary record shows that genes associated in cyto-trans have faced weaker negative selection, thus increasing the robustness and hence evolvability of the immune system. This phenomenon is similarly observable in human blood. Our findings suggest that interactions between different components of the immune system provide a phenotypic space in which mutations can produce variation with little detriment, underscoring the role of modularity in the evolution of complex systems. <<<

Chenfei Wang, Dongqing Sun, Xin Huang, Changxin Wan, Ziyi Li, Ya Han, Qian Qin, Jingyu Fan, Xintao Qiu, Yingtian Xie, Clifford A Meyer, Myles Brown, Ming Tang, Henry Long, Tao Liu, X Shirley Liu <<<

We present Model-based AnalysEs of Transcriptome and RegulOme (MAESTRO), a comprehensive open-source computational workflow ( http://github.com/liulab-dfci/MAESTRO ) for the integrative analyses of single-cell RNA-seq (scRNA-seq) and ATAC-seq (scATAC-seq) data from multiple platforms. MAESTRO provides functions for pre-processing, alignment, quality control, expression and chromatin accessibility quantification, clustering, differential analysis, and annotation. By modeling gene regulatory potential from chromatin accessibilities at the single-cell level, MAESTRO outperforms the existing methods for integrating the cell clusters between scRNA-seq and scATAC-seq. Furthermore, MAESTRO supports automatic cell-type annotation using predefined cell type marker genes and identifies driver regulators from differential scRNA-seq genes and scATAC-seq peaks. <<<

Ioannis Sarropoulos, Mari Sepp, Robert Frömel, Kevin Leiss, Nils Trost, Evgeny Leushkin, Konstantin Okonechnikov, Piyush Joshi, Peter Giere, Lena M Kutscher, Margarida Cardoso-Moreira, Stefan M Pfister, Henrik Kaessmann <<<

Organ development is orchestrated by cell- and time-specific gene regulatory networks. In this study, we investigated the regulatory basis of mouse cerebellum development from early neurogenesis to adulthood. By acquiring snATAC-seq (single-nucleus assay for transposase accessible chromatin using sequencing) profiles for ~90,000 cells spanning 11 stages, we mapped cerebellar cell types and identified candidate cisregulatory elements (CREs). We detected extensive spatiotemporal heterogeneity among progenitor cells and a gradual divergence in the regulatory programs of cerebellar neurons during differentiation. Comparisons to vertebrate genomes and snATAC-seq profiles for ∼20,000 cerebellar cells from the marsupial opossum revealed a shared decrease in CRE conservation during development and differentiation as well as differences in constraint between cell types. Our work delineates the developmental and evolutionary dynamics of gene regulation in cerebellar cells and provides insights into mammalian organ development. <<<

Christina Koupourtidou, Veronika Schwarz, Hananeh Aliee, Simon Frerich, Judith Fischer-Sternjak, Riccardo Bocchi, Tatiana Simon-Ebert, Xianshu Bai, Swetlana Sirko, Frank Kirchhoff, Martin Dichgans, Magdalena Götz, Fabian J Theis, Jovica Ninkovic <<<

Traumatic brain injury leads to a highly orchestrated immune- and glial cell response partially responsible for long-lasting disability and the development of secondary neurodegenerative diseases. A holistic understanding of the mechanisms controlling the responses of specific cell types and their crosstalk is required to develop an efficient strategy for better regeneration. Here, we combine spatial and single-cell transcriptomics to chart the transcriptomic signature of the injured male murine cerebral cortex, and identify specific states of different glial cells contributing to this signature. Interestingly, distinct glial cells share a large fraction of injury-regulated genes, including inflammatory programs downstream of the innate immune-associated pathways Cxcr3 and Tlr1/2. Systemic manipulation of these pathways decreases the reactivity state of glial cells associated with poor regeneration. The functional relevance of the discovered shared signature of glial cells highlights the importance of our resource enabling comprehensive analysis of early events after brain injury. <<<

Bolun Zhou, Wei Guo, Lei Guo, Yong Li, Zhigang Zheng, Qilin Huai, Fengwei Tan, Yin Li, Qi Xue, Jianming Ying, Liang Zhao, Shugeng Gao, Jie He <<<

Esophageal squamous cell carcinoma (ESCC) is invasive cancer and the complex mechanisms underlying carcinogenesis remain unclear. Extracellular vesicles (EVs), secreted by most cell types, serve as a critical factor in tumorigenesis via intercellular communications. Our study aims to investigate the cellular origin of EVs in ESCC, and unveil the unknown molecular and cellular mechanisms underlying cell-cell communications. Six ESCC patients were enrolled and single-cell RNA sequencing (scRNA-seq) analyses were conducted to screen different cell subpopulations. The genetic origin of EVs was tracked using the supernatant from different cellular extracts. Nanoparticle tracking analysis (NTA), western blot analysis, and transmission electron microscopy (TEM) were performed for validation. Using scRNA-seq analysis, eleven cell subpopulations were identified in ESCC. Differences in gene expression in EVs between malignant and non-malignant esophageal tissues were found. Our findings demonstrated that epithelial cells releasing EVs were the most prevalent in malignant tissues, while endothelial cells and fibroblasts releasing EVs were predominant in non-malignant tissues. Furthermore, the high levels of gene expression in EVs released from these cells were correlated significantly with a worse prognosis. Our findings revealed the genetic origin of EVs in malignant and non-malignant esophageal tissues and provided a comprehensive overview of the associated cell-cell interactions in ESCC. <<<

The recent development of experimental methods for measuring chromatin state at single-cell resolution has created a need for computational tools capable of analyzing these datasets. Here we developed Signac, a comprehensive toolkit for the analysis of single-cell chromatin data. Signac enables an end-to-end analysis of single-cell chromatin data, including peak calling, quantification, quality control, dimension reduction, clustering, integration with single-cell gene expression datasets, DNA motif analysis and interactive visualization. Through its seamless compatibility with the Seurat package, Signac facilitates the analysis of diverse multimodal single-cell chromatin data, including datasets that co-assay DNA accessibility with gene expression, protein abundance and mitochondrial genotype. We demonstrate scaling of the Signac framework to analyze datasets containing over 700,000 cells. <<<

Double-negative T (DNT) cells are a rare and unconventional T-lymphocyte subpopulation lacking both CD4 and CD8 markers. Their immunopathological roles and clinical relevance have yet to be elucidated. Beyond autoimmune lymphoproliferative syndrome (ALPS), these cells may also play a role in rheumatic disorders, including systemic lupus erythematosus (SLE); indeed, these two diseases share several autoimmune manifestations (including nephritis). Moreover, one of the main experimental murine models used to investigate lupus, namely the MRL/lpr mouse, is characterized by an expansion of DNT cells, which can support the production of pathogenic autoantibodies and/or modulate the immune response in this context. However, lupus murine models are not completely consistent with their human SLE counterpart, of course. In this mini review, we summarize and analyze the most relevant clinical studies investigating the DNT cell population in SLE patients. Overall, based on the present literature review and analysis, DNT cell homeostasis seems to be altered in patients with SLE. Indeed, most of the available clinical studies (which include both adults and children) reported an increased DNT cell percentage in SLE patients, especially during the active phases, even though no clear correlation with disease activity and/or inflammatory parameters has been clearly established. Well-designed, standardized, and longitudinal clinical studies focused on DNT cell population are needed, in order to further elucidate the actual contribution of these cells in SLE pathogenesis and their interactions with other immune cells (also implicated and/or altered in SLE, such as basophils), and clarify whether their expansion and/or immunophenotypic aspects may have any immunopathological relevance (and, then, represent potential disease markers and, in perspective, even therapeutic targets) or are just an unspecific epiphenomenon of autoimmunity. <<<

Small extracellular vesicles (sEVs) are emerging as pivotal players in a wide range of physiological and pathological processes. However, a pressing challenge has been the lack of high-throughput techniques capable of unraveling the intricate heterogeneity of sEVs and decoding the underlying cellular behaviors governing sEV secretion. Here we leverage droplet-based single-cell RNA sequencing (scRNA-seq) and introduce an algorithm, SEVtras, to identify sEV-containing droplets and estimate the sEV secretion activity (ESAI) of individual cells. Through extensive validations on both simulated and real datasets, we demonstrate SEVtras' efficacy in capturing sEV-containing droplets and characterizing the secretion activity of specific cell types. By applying SEVtras to four tumor scRNA-seq datasets, we further illustrate that the ESAI can serve as a potent indicator of tumor progression, particularly in the early stages. With the increasing importance and availability of scRNA-seq datasets, SEVtras holds promise in offering valuable extracellular insights into the cell heterogeneity. <<<

The cancer-immunity cycle provides a framework to understand the series of events that generate anti-cancer immune responses. It emphasizes the iterative nature of the response where the killing of tumor cells by T cells initiates subsequent rounds of antigen presentation and T cell stimulation, maintaining active immunity and adapting it to tumor evolution. Any step of the cycle can become rate-limiting, rendering the immune system unable to control tumor growth. Here, we update the cancer-immunity cycle based on the remarkable progress of the past decade. Understanding the mechanism of checkpoint inhibition has evolved, as has our view of dendritic cells in sustaining anti-tumor immunity. We additionally account for the role of the tumor microenvironment in facilitating, not just suppressing, the anti-cancer response, and discuss the importance of considering a tumor's immunological phenotype, the "immunotype". While these new insights add some complexity to the cycle, they also provide new targets for research and therapeutic intervention. <<<

Double-negative (DN) T cells are present at relatively low frequencies in human peripheral blood, and are characterized as expressing the alpha-beta or gamma-delta T-cell receptor (TCR), but not the CD4 nor the CD8 co-receptors. Despite their low frequencies, these cells are potent producers of cytokines and, thus, are key orchestrators of immune responses. DN T cells were initially associated with induction of peripheral immunological tolerance and immunomodulatory activities related to disease prevention. However, other studies demonstrated that these cells can also display effector functions associated with pathology development. This apparent contradiction highlighted the heterogeneity of the DN T-cell population. Here, we review phenotypic and functional characteristics of DN T cells, emphasizing their role in human diseases. The need for developing biomarkers to facilitate the translation of studies from animal models to humans will also be discussed. Finally, we will examine DN T cells as promising therapeutic targets to prevent or inhibit human disease development. <<<

Lian Narunsky-Haziza, Gregory D. Sepich-Poore, Ilana Livyatan, Omer Asraf, Cameron Martino, Deborah Nejman, Nancy Gavert, Jason E. Stajich, Guy Amit, Antonio González, Stephen Wandro, Gili Perry, Ruthie Ariel, Arnon Meltser, Justin P. Shaffer, Qiyun Zhu, Nora Balint-Lahat, Iris Barshack, Maya Dadiani, Einav N. Gal-Yam, Sandip Pravin Patel, Amir Bashan, Austin D. Swafford, Yitzhak Pilpel, Rob Knight, Ravid Straussman <<<

Inflammation predisposes to the development of cancer and promotes all stages of tumorigenesis. Cancer cells, as well as surrounding stromal and inflammatory cells, engage in well-orchestrated reciprocal interactions to form an inflammatory tumor microenvironment (TME). Cells within the TME are highly plastic, continuously changing their phenotypic and functional characteristics. Here, we review the origins of inflammation in tumors, and the mechanisms whereby inflammation drives tumor initiation, growth, progression, and metastasis. We discuss how tumor-promoting inflammation closely resembles inflammatory processes typically found during development, immunity, maintenance of tissue homeostasis, or tissue repair and illuminate the distinctions between tissue-protective and pro-tumorigenic inflammation, including spatiotemporal considerations. Defining the cornerstone rules of engagement governing molecular and cellular mechanisms of tumor-promoting inflammation will be essential for further development of anti-cancer therapies. <<<

Avishai Gavish, Michael Tyler, Alissa C Greenwald, Rouven Hoefflin, Dor Simkin, Roi Tschernichovsky, Noam Galili Darnell, Einav Somech, Chaya Barbolin, Tomer Antman, Daniel Kovarsky, Thomas Barrett, L Nicolas Gonzalez Castro, Debdatta Halder, Rony Chanoch-Myers, Julie Laffy, Michael Mints, Adi Wider, Rotem Tal, Avishay Spitzer, Toshiro Hara, Maria Raitses-Gurevich, Chani Stossel, Talia Golan, Amit Tirosh, Mario L Suvà, Sidharth V Puram, Itay Tirosh <<<

Each tumour contains diverse cellular states that underlie intratumour heterogeneity (ITH), a central challenge of cancer therapeutics. Dozens of recent studies have begun to describe ITH by single-cell RNA sequencing, but each study typically profiled only a small number of tumours and provided a narrow view of transcriptional ITH. Here we curate, annotate and integrate the data from 77 different studies to reveal the patterns of transcriptional ITH across 1,163 tumour samples covering 24 tumour types. Among the malignant cells, we identify 41 consensus meta-programs, each consisting of dozens of genes that are coordinately upregulated in subpopulations of cells within many tumours. The meta-programs cover diverse cellular processes including both generic (for example, cell cycle and stress) and lineage-specific patterns that we map into 11 hallmarks of transcriptional ITH. Most meta-programs of carcinoma cells are similar to those identified in non-malignant epithelial cells, suggesting that a large fraction of malignant ITH programs are variable even before oncogenesis, reflecting the biology of their cell of origin. We further extended the meta-program analysis to six common non-malignant cell types and utilize these to map cell-cell interactions within the tumour microenvironment. In summary, we have assembled a comprehensive pan-cancer single-cell RNA-sequencing dataset, which is available through the Curated Cancer Cell Atlas website, and leveraged this dataset to carry out a systematic characterization of transcriptional ITH. <<<

Tapsi Kumar, Kevin Nee, Runmin Wei, Siyuan He, Quy H Nguyen, Shanshan Bai, Kerrigan Blake, Maren Pein, Yanwen Gong, Emi Sei, Min Hu, Anna K Casasent, Aatish Thennavan, Jianzhuo Li, Tuan Tran, Ken Chen, Benedikt Nilges, Nachiket Kashikar, Oliver Braubach, Bassem Ben Cheikh, Nadya Nikulina, Hui Chen, Mediget Teshome, Brian Menegaz, Huma Javaid, Chandandeep Nagi, Jessica Montalvan, Tatyana Lev, Sharmila Mallya, Delia F Tifrea, Robert Edwards, Erin Lin, Ritesh Parajuli, Summer Hanson, Sebastian Winocour, Alastair Thompson, Bora Lim, Devon A Lawson, Kai Kessenbrock, Nicholas Navin <<<

The adult human breast is comprised of an intricate network of epithelial ducts and lobules that are embedded in connective and adipose tissue. Although most previous studies have focused on the breast epithelial system, many of the non-epithelial cell types remain understudied. Here we constructed the comprehensive Human Breast Cell Atlas (HBCA) at single-cell and spatial resolution. Our single-cell transcriptomics study profiled 714,331 cells from 126 women, and 117,346 nuclei from 20 women, identifying 12 major cell types and 58 biological cell states. These data reveal abundant perivascular, endothelial and immune cell populations, and highly diverse luminal epithelial cell states. Spatial mapping using four different technologies revealed an unexpectedly rich ecosystem of tissue-resident immune cells, as well as distinct molecular differences between ductal and lobular regions. Collectively, these data provide a reference of the adult normal breast tissue for studying mammary biology and diseases such as breast cancer. <<<

The system physiology approaches that emerge in western countries in recent years echo the holistic view of ancient Traditional Chinese Medicine (TCM) practices that deal with the root, rather than only the symptoms of diseases. Particularly, TCM practices, including acupuncture, emphasize the mobilization of self-healing mechanisms to bring back body homeostasis. Acupuncture has been practiced for over two thousand years to modulate body physiology stimulation at specific body regions (acupoints). With the development of various research on acupuncture therapy, its regulatory effect on the immune system has been gradually recognized, especially on immunological diseases, including infectious and allergic diseases. In this study, we reviewed the immunomodulatory mechanism of acupuncture and systematically integrates existing research to respectively elucidate the modulatory mechanisms of acupuncture on the innate immune system, adaptive immune system, and well-known neuroanatomical mechanisms, including intact somatosensory-autonomic reflex pathway. With the advances made in recent systems physiology studies, we now have a great opportunity to gain insight into how acupuncture modulates immunity, and subsequently improves its efficacy. <<<

David Ochoa, Andrew Hercules, Miguel Carmona, Daniel Suveges, Asier Gonzalez-Uriarte, Cinzia Malangone, Alfredo Miranda, Luca Fumis, Denise Carvalho-Silva, Michaela Spitzer, Jarrod Baker, Javier Ferrer, Arwa Raies, Olesya Razuvayevskaya, Adam Faulconbridge, Eirini Petsalaki, Prudence Mutowo, Sandra Machlitt-Northen, Gareth Peat, Elaine McAuley, Chuang Kee Ong, Edward Mountjoy, Maya Ghoussaini, Andrea Pierleoni, Eliseo Papa, Miguel Pignatelli, Gautier Koscielny, Mohd Karim, Jeremy Schwartzentruber, David G Hulcoop, Ian Dunham, Ellen M McDonagh <<<

The Open Targets Platform (https://www.targetvalidation.org/) provides users with a queryable knowledgebase and user interface to aid systematic target identification and prioritisation for drug discovery based upon underlying evidence. It is publicly available and the underlying code is open source. Since our last update two years ago, we have had 10 releases to maintain and continuously improve evidence for target-disease relationships from 20 different data sources. In addition, we have integrated new evidence from key datasets, including prioritised targets identified from genome-wide CRISPR knockout screens in 300 cancer models (Project Score), and GWAS/UK BioBank statistical genetic analysis evidence from the Open Targets Genetics Portal. We have evolved our evidence scoring framework to improve target identification. To aid the prioritisation of targets and inform on the potential impact of modulating a given target, we have added evaluation of post-marketing adverse drug reactions and new curated information on target tractability and safety. We have also developed the user interface and backend technologies to improve performance and usability. In this article, we describe the latest enhancements to the Platform, to address the fundamental challenge that developing effective and safe drugs is difficult and expensive. <<<

Maxime Dhainaut, Samuel A Rose, Guray Akturk, Aleksandra Wroblewska, Sebastian R Nielsen, Eun Sook Park, Mark Buckup, Vladimir Roudko, Luisanna Pia, Robert Sweeney, Jessica Le Berichel, C Matthias Wilk, Anela Bektesevic, Brian H Lee, Nina Bhardwaj, Adeeb H Rahman, Alessia Baccarini, Sacha Gnjatic, Dana Pe'er, Miriam Merad, Brian D Brown <<<

While CRISPR screens are helping uncover genes regulating many cell-intrinsic processes, existing approaches are suboptimal for identifying extracellular gene functions, particularly in the tissue context. Here, we developed an approach for spatial functional genomics called Perturb-map. We applied Perturb-map to knock out dozens of genes in parallel in a mouse model of lung cancer and simultaneously assessed how each knockout influenced tumor growth, histopathology, and immune composition. Moreover, we paired Perturb-map and spatial transcriptomics for unbiased analysis of CRISPR-edited tumors. We found that in Tgfbr2 knockout tumors, the tumor microenvironment (TME) was converted to a fibro-mucinous state, and T cells excluded, concomitant with upregulated TGFβ and TGFβ-mediated fibroblast activation, indicating that TGFβ-receptor loss on cancer cells increased TGFβ bioavailability and its immunosuppressive effects on the TME. These studies establish Perturb-map for functional genomics within the tissue at single-cell resolution with spatial architecture preserved and provide insight into how TGFβ responsiveness of cancer cells can affect the TME. <<<