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Mereu, E.

Publications and source records attributed to Mereu, E..

At least 19 recordsLinked to original sources

Dual inhibition of the nonsense mediated mRNA decay enhances tumour immunogenicity, drives immunoediting, and potentiates checkpoint blockade

Immune checkpoint blockade has transformed cancer therapy, but current biomarkers such as tumour mutation burden often fail to reliably predict clinical benefit. One proposed reason for this discrepancy is the activity of nonsense-mediated mRNA decay (NMD), a cellular quality-control pathway that degrades mutant transcripts, potentially reducing the presentation of neoantigens that would otherwise stimulate anti-tumour immunity. To address this, we identified publicly available small-molecule inhibitors targeting the NMD factors SMG5 and SMG7 (NMDi), which we have prioritise as the NMD components most strongly associated with NMD efficiency across TCGA tumours, and evaluated their therapeutic potential in vivo. In a syngeneic, DNA repair deficient mouse model of lung adenocarcinoma, NMDi treatment alone substantially reduced tumour burden, and its combination with anti-PD-1 therapy led to additive benefit either treatment alone. These effects were immune-dependent and specifically required CD8{square} T cells. Transcriptomic and single-cell analyses revealed that NMDi reprograms the tumour immune microenvironment, enriching for clonally expanded, cytotoxic CD8{square} T cells and altering macrophage states toward those associated with tumour regression. Whole-genome sequencing of tumours revealed that NMDi also promotes immunoediting, leading to negative selection against immunogenic mutations and coding indels, with selective pressure comparable to or greater than that induced by anti-PD-1 treatment. Guided by these results, we generated a new protein language model trained on tumour mutations that can identify neopeptides with immunogenic properties, revealing that the NMDi tumour landscape provides a rich genomic and immunopeptidomic setting for exposing neoantigens that evade immunoediting. Together, these pre-clinical and integrative genomic-transcriptomic insights position NMD inhibition as a promising immunostimulatory strategy that can potentiate immune checkpoint blockade efficacy in tumours.

cancer biology↗

Latent plasticity of the human pancreas across development, health, and disease.

The pancreas plays a central role in major human diseases, yet our understanding of its cellular diversity and plasticity remains incomplete. Here, we present a single-cell multiomics atlas of the human pancreas, profiling over four million cells and nuclei from 57 donors across fetal development, adult homeostasis, and type 2 diabetes (T2D). Integrating sc/snRNA-seq, snATAC-seq, VASA-seq, spatial transcriptomics (Xenium), and multiplexed proteomics (CODEX), we resolve gene expression, chromatin accessibility, and spatial organization at high resolution. We identify transcriptionally plastic centroacinar-like cells (pCACs) in adults with fetal-like features, delineate endocrine and exocrine lineage trajectories during development, and uncover HNF1A-defined beta cell epigenetic states. In T2D, we observe shifts in beta cell subtypes and altered regulatory programs. Glucose perturbation of healthy islets reveals cell-type-specific adaptation and stress responses. This atlas provides a foundational framework to understand pancreas biology and the role of cellular plasticity in regeneration and disease.

genomics↗

Bedaquiline Amplifies Proteasome Inhibitor Efficacy and Overcomes Resistance in Multiple Myeloma

Proteasome inhibitors (PIs) are cornerstone therapies for multiple myeloma (MM), yet resistance remains a major barrier to durable responses. To identify druggable vulnerabilities that enhance PIs efficacy, we performed a small-molecule chemical screen in the presence of carfilzomib (CFZ). We identified bedaquiline (BDQ), an FDA-approved antimycobacterial agent, as a potent synergistic partner. BDQ and its fumarate salt (BDQ-F) significantly amplified CFZ-induced cytotoxicity in PI-sensitive and PI-resistant MM cells, in AL amyloidosis and other B-cell malignancies, with minimal toxicity toward normal cells. Mechanistic studies confirmed that BDQ specifically targets the ATP5F1C subunit of mitochondrial ATP synthase. BDQ-CFZ combination triggered extensive apoptosis, exacerbating proteotoxic stress and proteasome-associated pathways. BDQ specifically enhanced CFZs inhibition of the proteasomes chymotrypsin-like activity. Importantly, BDQ synergized with multiple proteasome and ubiquitin-activating enzyme inhibitors, but not with other standard MM agents, underscoring its selective interaction with the UPS pathway. BDQ-CFZ co-treatment markedly reduced MM cell viability and tumor burden in patient-derived cells and zebrafish xenograft models. These findings support the therapeutic repurposing of BDQ to potentiate PIs efficacy and overcome resistance in MM and related B-cell malignancies. KEY POINTSO_LIBedaquiline synergizes with proteasome inhibitors in MM and other hematologic malignancies, sparing normal cells C_LIO_LIBedaquiline targets ATP synthase {gamma} and boosts carfilzomib by enhancing chymotrypsin-like proteasome inhibition C_LI NOVELTYWe identify the antimicrobial bedaquiline and its fumarate salt as potent enhancers of proteasome inhibitor efficacy in multiple myeloma and other B-cell malignancies. By inhibiting ATP synthase {gamma}, bedaquiline amplifies chymotrypsin-like proteasome inhibition and overcomes drug resistance. This study reveals a mitochondria- proteasome vulnerability and proposes a clinically actionable strategy to restore sensitivity and reduce toxicity of proteasome-based therapies. VISUAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=135 SRC="FIGDIR/small/661768v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@339391org.highwire.dtl.DTLVardef@1d3271org.highwire.dtl.DTLVardef@daa0faorg.highwire.dtl.DTLVardef@17eb4eb_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

Patient-derived liver biopsy organoids enable precision alcohol-associated liver disease modeling

Background & AimsAlcohol-associated liver disease (ALD) is a major cause of liver disease worldwide with scarce therapeutic options. Animal models poorly recapitulate advanced ALD precluding the development of new treatments. Organoids have emerged as a powerful human-based preclinical tool. However, current patient-derived liver organoids fail to recapitulate the epithelial heterogeneity and its generation requires liver surgical resections, thus limiting personalized disease modeling. Here, we report the development of organoids from liver needle biopsies (b-Orgs) from patients with ALD. Methodsb-Orgs were generated from tru-cut biopsies from patients at early (n=28) and advanced (n=34) stages of ALD. b-Orgs were characterized by immunofluorescence, bulk and single cell RNA-sequencing and compared to parental tissues. b-Orgs were used to model ALD progression, identify pathogenic drivers, induce alcohol-associated hepatitis (AH) and evaluate response to prednisolone. ResultsPhenotypic and functional analysis of b-Orgs showed hepatocyte- enriched features. Single-cell RNA-sequencing revealed a heterogeneous cell composition comprising hepatocyte, biliary and progenitor populations, mirroring the epithelial landscape found in patients with advanced ALD. Moreover, b-Orgs preserved disease-stage features and allowed to identify the association of ELF3 with cell plasticity and disease progression. Finally, stimulation of b-Orgs with drivers of ALD induced pathophysiological features of alcohol-associated hepatitis, including ROS production, lipid accumulation, inflammation and decreased cell proliferation, which were mitigated in response to prednisolone. Conclusions Overall, we provide a human-based model that recapitulates epithelial complexity and patient specific features, allowing to identify drivers of cell plasticity and expanding organoid-based liver disease modeling for personalized medicine. Impact and implications Here, we describe the generation of biopsy-derived organoids (b-Orgs) from patients with liver disease. b-Orgs reproduce the liver epithelial cell composition found in patients liver tissue and are efficiently generated from different stages of the disease, providing a platform for patient- tailored disease modeling and drug testing.

cell biology↗

Systematic evaluation of single-cell multimodal data integration for comprehensive human reference atlas.

The integration of multimodal single-cell data enables comprehensive organ reference atlases, yet its impact remains largely unexplored, particularly in complex tissues. We generated a benchmarking dataset for the renal cortex by integrating 3 and 5 scRNA-seq with joint snRNA-seq and snATAC-seq, profiling 119,744 high-quality nuclei/cells from 19 donors. To align cell identities and enable consistent comparisons, we developed the interpretable machine learning tool scOMM (single-cell Omics Multimodal Mapping) and systematically assessed integration strategies. "Horizontal" integration of scRNA and snRNA-seq improved cell-type identification, while "vertical" integration of snRNA-seq and snATAC-seq had an additive effect, enhancing resolution in homogeneous populations and difficult-to-identify states. Global integration was especially effective in identifying adaptive states and rare cell types, including WFDC2-expressing Thick Ascending Limb and Norn cells, previously undetected in kidney atlases. Our work establishes a robust framework for multimodal reference atlas generation, advancing single-cell analysis and extending its applicability to diverse tissues.

genomics↗

The Multiomics Blueprint of Extreme Human Lifespan

The indexed individual, from now on termed M116, was the worlds oldest verified living person from January 17th 2023 until her passing on August 19th 2024, reaching the age of 117 years and 168 days (https://www.supercentenarian.com/records.html). She was a Caucasian woman born on March 4th 1907 in San Francisco, USA, from Spanish parents and settled in Spain since she was 8. A timeline of her life events and her genealogical tree are shown in Supplementary Fig. 1a-b. Although centenarians are becoming more common in the demographics of human populations, the so-called supercentenarians (over 110 years old) are still a rarity. In Catalonia, the historic nation where M116 lived, the life-expectancy for women is 86 years, so she exceeded the average by more than 30 years (https://www.idescat.cat). In a similar manner to premature aging syndromes, such as Hutchinson-Gilford Progeria and Werner syndrome, which can provide relevant clues about the mechanisms of aging, the study of supercentenarians might also shed light on the pathways involved in lifespan. To unfold the biological properties exhibited by such a remarkable human being, we developed a comprehensive multiomics analysis of her genomic, transcriptomic, metabolomic, proteomic, microbiomic and epigenomic landscapes in different tissues, as depicted in Fig. 1a, comparing the results with those observed in non-supercentenarian populations. The picture that emerges from our study shows that extremely advanced age and poor health are not intrinsically linked and that both processes can be distinguished and dissected at the molecular level. O_FIG O_LINKSMALLFIG WIDTH=156 HEIGHT=200 SRC="FIGDIR/small/639740v1_fig1.gif" ALT="Figure 1"> View larger version (63K): org.highwire.dtl.DTLVardef@1705be6org.highwire.dtl.DTLVardef@1a16e4borg.highwire.dtl.DTLVardef@15005f1org.highwire.dtl.DTLVardef@b6297b_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 1C_FLOATNO Chromosomes and genes.a, Schematic representation of all -omics studied in the supercentenarian. b, Telomeres marked with Cy3 (yellow) in nuclei stained with DAPI (blue) observed in HT-qFISH from M116 and younger womens PBMCs. Scale bars: 20 {micro}m. c, Telomere length (Kb) calculation (left) and percentage of extremely short telomeres (below the 20th percentile) (right) in M116 (orange) using standard curve from samples previously analyzed (black) and control women (blue) (Online Methods). d, Circos plot with chromosomal alterations detected through optical genome mapping in supercentenarian. e, Variants of interest (VOI)-harboring genes found in supercentenarians genomic DNA contributing to immune function, cardiovascular health, neuroprotection, metabolism, and DNA dynamics. f, Significantly enriched functions of VOI-harboring genes in the supercentenarian. g, VOI-harbouring genes significantly contributing to enriched functions. h, VOI-harboring genes found in supercentenarians genomic and mitochondrial DNA contributing to mitochondrial function. i, Mean fluorescence intensity of TMRE (a marker of mitochondrial membrane potential) and SOX (a marker of mitochondrial superoxide ion) in PBMCs from the supercentenarian (orange) and healthy controls across various ages (gray). Unpaired t-test was used to statistically compare M116 to the mean of all control women. *p < 0.05. C_FIG

genomics↗

Discovery and evaluation of novel biomarkers reveal dasatinib as a potential treatment for a specific subtype of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) represents the most heterogeneous and aggressive subtype of breast carcinomas, characterized by the absence of clinical biomarkers (ER, PR, and HER2) and the lack of targeted therapies. In this regard, several clinical trials have consistently failed to effectively stratify patients and identify specific treatments that elicit substantial responses. This study aims to pinpoint biomarkers expressed exclusively in the basal mammary epithelial compartment, facilitating a refined subclassification of this breast cancer subtype. Using computational analyses of single-cell RNA sequencing data, we have identified a list of genes associated with basal identity (BC-markers). Histological validation in 137 human samples has enabled us to categorize TNBC patients into BC-positive and BC-negative TNBC subtypes. Significantly, the presence of these markers correlates with a poorer prognosis in TNBC patients. Functional analyses have revealed a pivotal role for TAGLN in cell migration, likely influencing tumor aggressiveness. Further, we discovered that BC-marker expression is associated with the mesenchymal phenotype and increased sensitivity to the tyrosine kinase inhibitor dasatinib, particularly in BC-positive TNBC, suggesting novel therapeutic avenues. In our study, TAGLN emerged as a potential predictive biomarker for dasatinib responsiveness, offering new directions for personalized therapy for TNBC patients.

cancer biology↗

Integrative single-cell multi-omics of CD19CARpos and CARneg T cells suggest drivers of immunotherapy response in B-cell neoplasias

How phenotypic, clonal, and functional heterogeneity of CAR-T-cells impact clinical outcomes remain understudied. Here, we integrated clonal kinetics with transcriptomic heterogeneity resolved by single-cell omics to explore cellular dynamics response of both non-transduced (CARneg) and transduced (CARpos)T-cells. CARneg and CARposT-cells were longitudinally interrogated in the manufactured infusion product (IP) and in-vivo at CAR-T cell expansion peak in five B-ALL patients treated with CD19CAR-T-cells (varni-cel). Significant differences were found in the cellular dynamics between CARpos and CARnegT-cells in response to therapy. CARposT-cells in the IP exhibited a significant higher CD4:CD8 ratio than CARnegT-cells, and the CD4:CD8 CARposT-cell composition impacted therapy outcome as confirmed in a larger cohort of 24 varni-cel-treated B-ALL patients. Conversely, an inverted trend in the CD4:CD8 CARposT-cell ratio was consistently observed at the expansion peak, with clonally expanding CD8+ effector memory and cytotoxic T-cells being the most abundant populations. Expanded cytotoxic CARpos{gamma}{delta}T cells emerged at the expansion peak, and the extent of their in-vivo expansion positively correlated with treatment efficacy, which was validated in a large cohort of B-ALL patients (n=18) treated with varni-cell and B-cell lymphoma patients (n=58) treated with either lisa-cel or axi-cel. Our data provide insights into the complexity and diversity of T-cell responses following CAR-T cell therapy and suggest drivers of immunotherapy response.

immunology↗

The Human Microglia Atlas (HuMicA) Unravels Changes in Homeostatic and Disease-Associated Microglia Subsets across Neurodegenerative Conditions

Dysregulated microglia activation, leading to neuroinflammation, is crucial in neurodegenerative disease development and progression. The initial M1/M2 dual activation classification for microglia is outdated. Even the disease-associated microglia (DAM) phenotype, firstly described in mice, falls short in representing the diverse microglia phenotypes in pathology. In this study, we have constructed a transcriptomic atlas of human brain immune cells by integrating single-nucleus (sn)RNA-seq datasets from multiple neurodegenerative conditions. Sixteen datasets were included, comprising 295 samples from patients with Alzheimers disease, autism spectrum disorder, epilepsy, multiple sclerosis, Lewy body diseases, COVID-19, and healthy controls. The integrated Human Microglia Atlas (HuMicA) dataset included 60,557 nuclei and revealed 11 microglial subpopulations distributed across all pathological and healthy conditions. Among these, we identified four different homeostatic clusters as well as pathological phenotypes. These included two stages of early and late activation of the DAM phenotype and the disease-inflammatory macrophage (DIM) phenotype, which was recently described in mice, and is also present in human microglia, as indicated by our analysis. The high versatility of microglia is evident through changes in subset distribution across various pathologies, suggesting their contribution in shaping pathological phenotypes. Our analysis showed overall depletion of four substates of homeostatic microglia, and expansion of niche subpopulations within the DAM and DIM spectrum across distinct neurodegenerative pathologies. The HuMicA is invaluable in advancing the study of microglia biology in both healthy and disease settings.

neuroscience↗

Macrophage and neutrophil heterogeneity at single-cell spatial resolution in inflammatory bowel disease

Ulcerative colitis (UC) and Crohns disease (CD) are chronic inflammatory intestinal diseases that show a perplexing heterogeneity in manifestations and response to treatment. The molecular basis for this heterogeneity remains uncharacterized. We applied single-cell RNA sequencing and CosMx Spatial Molecular Imaging to human colon and found the highest diversity in cellular composition in the myeloid compartment of UC and CD patients. Besides resident macrophage subsets (M0 and M2), patients showed a variety of activated macrophages including classical (M1 CXCL5 and M1 ACOD1) and new inflammation-dependent alternative (IDA) macrophages. In addition, we captured intestinal neutrophils in three transcriptional states. Subepithelial IDA macrophages expressed NRG1, which promotes epithelial differentiation. In contrast, NRG1low IDA macrophages were expanded within the submucosa and in granulomas, in proximity to abundant inflammatory fibroblasts, which we suggest may promote macrophage activation. We conclude that macrophages sense and respond to unique tissue microenvironments, potentially contributing to patient-to-patient heterogeneity.

immunology↗

IκBα controls dormancy induction in Hematopoietic stem cell development via retinoic acid

Recent findings are challenging the classical hematopoietic model in which long-term hematopoietic stem cells (LT-HSC) are the base of the hematopoietic system. Clonal dynamics analysis of the hematopoietic system indicate that LT-HSC are not the main contributors of normal hemapoiesis in physiological conditions and the hematopoietic system is mainly maintained by multipotent progenitors (MPPs, hereafter HPC) and LT-HSCs are mostly in a non-active state. The first HSCs emerge from the aorta-gonad and mesonephros (AGM) region along with hematopoietic progenitors (HPC) within hematopoietic clusters. Molecular pathways that determine the HSC fate instead of HPC are still unknown, although inflammatory signaling, including NF-{kappa}B has been implicated in the development of HSCs. Here, we identify a chromatin binding function for I{kappa}B (also known as the inhibitor of NF-{kappa}B) that is Polycomb repression complex 2 (PRC2)-dependent and specifically determines dormant vs proliferating HSCs from the onset of their emergence in the AGM. We find a specific reduction of LT-HSCs in the I{kappa}B knockout new-born pups. This defect is manifested at the FL stage already, and traceable to the first emerging HSCs in the E11.5 AGM, without affecting the general HPC population. I{kappa}B deficient LT-HSCs express dormancy signature genes, are less proliferative and can robustly respond to activation stimuli such as in vitro culture and serial transplantation. At the molecular level, we find decreased PRC2-dependent H3K27me3 at the promoters of several retinoic acid signaling elements in the I{kappa}B - deficient aortic endothelium and E14.5 FL LT-HSCs. Additionally, I{kappa}B binding itself is found in the promoters of retinoic acid receptors rar in the AGM, and rar{gamma} in the LT-HSC of FL. Overall, we demonstrate that the retinoic acid pathway is over-activated in the hematopoietic clusters of I{kappa}B-deficient AGMs leading to premature dormancy of LT-HSCs that persists in the FL LT-HSCs.

cell biology↗

Local IL-17 orchestrates skin aging

Skin aging is characterized by structural and functional changes that lead to slower wound healing and higher rate of infections, which contribute to age-associated frailty. This likely depends on synergy between alterations in the local microenvironment and stem cell-intrinsic changes, underscored by pro-inflammatory microenvironments that drive pleotropic changes. To date, little is known about the precise nature and origin of the proposed age-associated inflammatory cues, or how they affect different tissue resident cell types. Based on deep single-cell RNA-sequencing of the entire dermal compartment, we now provide a comprehensive understanding of the age-associated changes in all skin cell types. We show a previously unreported skew towards an IL-17-expressing phenotype of Th cells, {gamma}{delta} T cells and innate lymphoid cells in aged skin. Aberrant IL-17 signaling is common to many autoimmune (e.g., rheumatoid arthritis and psoriasis) and chronic inflammatory diseases. Importantly, in vivo blockade of IL-17-triggered signaling during the aging process reduces the pro-inflammatory state by affecting immune and non-immune skin cells of both dermis and epidermis. Strikingly, IL-17 neutralization significantly delays the appearance of age-related traits, such as decreased epidermal thickness, increased cornified layer thickness and ameliorated hair follicle stem cell activation and hair shaft regeneration. Our results indicate that the aged skin shows chronic and persistent signs of inflammation, and that age-associated increased IL-17 signaling could be targeted as a strategy to prevent age-associated skin ailments in elderly.

cell biology↗

Glioblastoma cell fate is differentially regulated by the microenvironments of the tumour bulk and infiltrative margin

Glioblastoma recurrence originates from invasive cells at the tumour margin that escape surgical debulking, but their biology remains poorly understood. Here we generated three somatic mouse models recapitulating the main glioblastoma driver mutations to characterise margin cells. We find that, regardless of genetics, tumours converge on a common set of neural- like cellular states. However, bulk and margin display distinct neurogenic patterns and immune microenvironments. The margin is immune-cold and preferentially follows developmental-like trajectories to produce astrocyte-like cells. In contrast, injury-like programmes dominate in the bulk, are associated with immune infiltration and generate lowly-proliferative injured neural progenitor-like (iNPCs) cells. In vivo label-retention approaches further demonstrate that iNPCs account for a significant proportion of dormant glioblastoma cells and are induced by interferon signalling within T-cell niches. These findings indicate that tumour region is a major determinant of glioblastoma cell fate and therapeutic vulnerabilities identified in bulk may not extend to the margin residuum.

cancer biology↗

A Single-Cell Tumor Immune Atlas for Precision Oncology

The tumor immune microenvironment is a main contributor to cancer progression and a promising therapeutic target for oncology. However, immune microenvironments vary profoundly between patients and biomarkers for prognosis and treatment response lack precision. A comprehensive compendium of tumor immune cells is required to pinpoint predictive cellular states and their spatial localization. We generated a single-cell tumor immune atlas, jointly analyzing >500,000 cells from 217 patients and 13 cancer types, providing the basis for a patient stratification based on immune cell compositions. Projecting immune cells from external tumors onto the atlas facilitated an automated cell annotation system for a harmonized interpretation. To enable in situ mapping of immune populations for digital pathology, we applied SPOTlight, combining single-cell and spatial transcriptomics data and identifying striking spatial immune cell patterns in tumor sections. We expect the tumor immune cell atlas, together with our versatile toolbox for precision oncology, to advance currently applied stratification approaches for prognosis and immuno-therapy.

cancer biology↗

SPOTlight:Seeded NMF regression to Deconvolute Spatial Transcriptomics Spots with Single-Cell Transcriptomes

The integration of orthogonal data modalities greatly supports the interpretation of transcriptomic landscapes in complex tissues. In particular, spatially resolved gene expression profiles are key to understand tissue organization and function. However, spatial transcriptomics (ST) profiling techniques lack single-cell resolution and require a combination with single-cell RNA sequencing (scRNA-seq) information to deconvolute the spatially indexed datasets. Leveraging the strengths of both data types, we developed SPOTlight, a computational tool that enables the integration of ST with scRNA-seq data to infer the location of cell types and states within a complex tissue. SPOTlight is centered around a seeded non-negative matrix factorization (NMF) regression, initialized using cell-type marker genes, and non-negative least squares (NNLS) to subsequently deconvolute ST capture locations (spots). Using synthetic spots, simulating varying reference quantities and qualities, we confirmed high prediction accuracy also with shallowly sequenced or small-sized scRNA-seq reference datasets. We trained the NMF regression model with sample-matched or external datasets, resulting in accurate and sensitive spatial predictions. SPOTlight deconvolution of the mouse brain correctly mapped subtle neuronal cell states of the cortical layers and the defined architecture of the hippocampus. In human pancreatic cancer, we successfully segmented patient sections into healthy and cancerous areas, and further fine-mapped normal and neoplastic cell states. Trained on an external pancreatic tumor immune reference, we charted the localization of clinical-relevant and tumor-specific immune cell states. Using SPOTlight to detect regional enrichment of immune cells and their co-localization with tumor and adjacent stroma provides an illustrative example in its flexible application spectrum and future potential in digital pathology.

bioinformatics↗

Robustness and applicability of functional genomics tools on scRNA-seq data

Many tools have been developed to extract functional and mechanistic insight from bulk transcriptome profiling data. With the advent of single-cell RNA sequencing (scRNA-seq), it is in principle possible to do such an analysis for single cells. However, scRNA-seq data has characteristics such as drop-out events, low library sizes and a comparatively large number of samples/cells. It is thus not clear if functional genomics tools established for bulk sequencing can be applied to scRNA-seq in a meaningful way. To address this question, we performed benchmark studies on in silico and in vitro single-cell RNA-seq data. We included the bulk-RNA tools PROGENy, GO enrichment and DoRothEA that estimate pathway and transcription factor (TF) activities, respectively, and compared them against the tools AUCell and metaVIPER, designed for scRNA-seq. For the in silico study we simulated single cells from TF/pathway perturbation bulk RNA-seq experiments. Our simulation strategy guarantees that the information of the original perturbation is preserved while resembling the characteristics of scRNA-seq data. We complemented the in silico data with in vitro scRNA-seq data upon CRISPR-mediated knock-out. Our benchmarks on both the simulated and real data revealed comparable performance to the original bulk data. Additionally, we showed that the TF and pathway activities preserve cell-type specific variability by analysing a mixture sample sequenced with 13 scRNA-seq different protocols. Our analyses suggest that bulk functional genomics tools can be applied to scRNA-seq data, outperforming dedicated single cell tools. Furthermore we provide a benchmark for further methods development by the community.

bioinformatics↗

Benchmarking Single-Cell RNA Sequencing Protocols for Cell Atlas Projects

Single-cell RNA sequencing (scRNA-seq) is the leading technique for charting the molecular properties of individual cells. The latest methods are scalable to thousands of cells, enabling in-depth characterization of sample composition without prior knowledge. However, there are important differences between scRNA-seq techniques, and it remains unclear which are the most suitable protocols for drawing cell atlases of tissues, organs and organisms. We have generated benchmark datasets to systematically evaluate techniques in terms of their power to comprehensively describe cell types and states. We performed a multi-center study comparing 13 commonly used single-cell and single-nucleus RNA-seq protocols using a highly heterogeneous reference sample resource. Comparative and integrative analysis at cell type and state level revealed marked differences in protocol performance, highlighting a series of key features for cell atlas projects. These should be considered when defining guidelines and standards for international consortia, such as the Human Cell Atlas project.

genomics↗

matchSCore: Matching Single-Cell Phenotypes Across Tools and Experiments

Single-cell transcriptomics allows the identification of cellular types, subtypes and states through cell clustering. In this process, similar cells are grouped before determining co-expressed marker genes for phenotype inference. The performance of computational tools is directly associated to their marker identification accuracy, but the lack of an optimal solution challenges a systematic method comparison. Moreover, phenotypes from different studies are challenging to integrate, due to varying resolution, methodology and experimental design. In this work we introduce matchSCore (https://github.com/elimereu/matchSCore), an approach to match cell populations fast across tools, experiments and technologies. We compared 14 computational methods and evaluated their accuracy in clustering and gene marker identification in simulated data sets. We further used matchSCore to project cell type identities across mouse and human cell atlas projects. Despite originating from different technologies, cell populations could be matched across data sets, allowing the assignment of clusters to reference maps and their annotation.

bioinformatics↗