Single-cell Gene Expression Analysis Research Articles

CACNA1A haploinsufficiency leads to reduced synaptic function and increased intrinsic excitability.

Haploinsufficiency of the CACNA1A gene, encoding the pore-forming α1 subunit of P/Q-type voltage-gated calcium channels, is associated with a clinically variable phenotype ranging from cerebellar ataxia, to neurodevelopmental syndromes with epilepsy and intellectual disability. To understand the pathological mechanisms of CACNA1A loss-of-function variants, we characterized a human neuronal model for CACNA1A haploinsufficiency, by differentiating isogenic induced pluripotent stem cell lines into glutamatergic neurons, and investigated the effect of CACNA1A haploinsufficiency on mature neuronal networks through a combination of electrophysiology, gene expression analysis, and in silico modeling. We observed an altered network synchronization in CACNA1A+/- networks alongside synaptic deficits, notably marked by an augmented contribution of GluA2-lacking AMPA receptors. Intriguingly, these synaptic perturbations coexisted with increased non-synaptically driven activity, as characterized by inhibition of NMDA and AMPA receptors on micro-electrode arrays. Single-cell electrophysiology and gene expression analysis corroborated this increased intrinsic excitability through reduced potassium channel function and expression. Moreover, we observed partial mitigation of the CACNA1A+/- network phenotype by 4-aminopyridine, a therapeutic intervention for episodic ataxia type 2. Positive modulation of KCa2 channels could reverse the CACNA1A+/- network electrophysiological phenotype. In summary, our study pioneers the characterization of a human induced pluripotent stem cell-derived neuronal model for CACNA1A haploinsufficiency, and has unveiled novel mechanistic insights. Beyond showcasing synaptic deficits, this neuronal model exhibited increased intrinsic excitability mediated by diminished potassium channel function, underscoring its potential as a therapeutic discovery platform with predictive validity.

Recipient tissue microenvironment determines developmental path of intestinal innate lymphoid progenitors

Innate lymphoid cells (ILCs) are critical in maintaining tissue homeostasis, and during infection and inflammation. Here we identify, by using combinatorial reporter mice, a rare ILC progenitor (ILCP) population, resident to the small intestinal lamina propria (siLP) in adult mice. Transfer of siLP-ILCP into recipients generates group 1 ILCs (including ILC1 and NK cells), ILC2s and ILC3s within the intestinal microenvironment, but almost exclusively group 1 ILCs in the liver, lung and spleen. Single cell gene expression analysis and high dimensional spectral cytometry analysis of the siLP-ILCPs and ILC progeny indicate that the phenotype of the group 1 ILC progeny is also influenced by the tissue microenvironment. Thus, a local pool of siLP-ILCP can contribute to pan-ILC generation in the intestinal microenvironment but has more restricted potential in other tissues, with a greater propensity than bone marrow-derived ILCPs to favour ILC1 and ILC3 production. Therefore, ILCP potential is influenced by both tissue of origin and the microenvironment during development. This may provide additional flexibility during the tuning of immune reactions.

Areal specializations in the morpho-electric and transcriptomic properties of primate layer 5 extratelencephalic projection neurons

Large-scale analysis of single-cell gene expression has revealed transcriptomically defined cell subclasses present throughout the primate neocortex with gene expression profiles that differ depending upon neocortical region. Here, we test whether the interareal differences in gene expression translate to regional specializations in the physiology and morphology of infragranular glutamatergic neurons by performing Patch-seq experiments in brain slices from the temporal cortex (TCx) and motor cortex (MCx) of the macaque. We confirm that transcriptomically defined extratelencephalically projecting neurons of layer 5 (L5 ET neurons) include retrogradely labeled corticospinal neurons in the MCx and find multiple physiological properties and ion channel genes that distinguish L5 ET from non-ET neurons in both areas. Additionally, while infragranular ET and non-ET neurons retain distinct neuronal properties across multiple regions, there are regional morpho-electric and gene expression specializations in the L5 ET subclass, providing mechanistic insights into the specialized functional architecture of the primate neocortex.

Feature selection followed by a novel residuals-based normalization that includes variance stabilization simplifies and improves single-cell gene expression analysis

Normalization is a crucial step in the analysis of single-cell RNA-sequencing (scRNA-seq) counts data. Its principal objectives are reduction of systematic biases primarily introduced through technical sources and transformation of counts to make them more amenable for the application of established statistical frameworks. In the standard workflows, normalization is followed by feature selection to identify highly variable genes (HVGs) that capture most of the biologically meaningful variation across the cells. Here, we make the case for a revised workflow by proposing a simple feature selection method and showing that we can perform feature selection before normalization by relying on observed counts. We highlight that the feature selection step can be used to not only select HVGs but to also identify stable genes. We further propose a novel variance stabilization transformation inclusive residuals-based normalization method that in fact relies on the stable genes to inform the reduction of systematic biases. We demonstrate significant improvements in downstream clustering analyses through the application of our proposed methods on biological truth-known as well as simulated counts datasets. We have implemented this novel workflow for analyzing high-throughput scRNA-seq data in an R package called Piccolo.

Synergic activity of FGFR2 and MEK inhibitors in the treatment of FGFR2-amplified cancers of unknown primary

Patients with cancer of unknown primary (CUP) carry the double burden of an aggressive disease and reduced access to therapies. Experimental models are pivotal for CUP biology investigation and drug testing. We derived two CUP cell lines (CUP#55 and #96), and corresponding patient-derived xenografts (PDXs), from ascites tumor cells. CUP cell lines and PDXs underwent histological, immune-phenotypical, molecular, and genomic characterization confirming the features of the original tumor. The tissue-of-origin prediction was obtained from the tumor microRNA expression profile and confirmed by single-cell transcriptomics. Genomic testing and FISH analysis identified FGFR2 gene amplification in both models, in the form of homogenously staining region (HSR) in CUP#55 and double minutes in CUP#96. FGFR2 was recognized as the main oncogenic driver and therapeutic target. FGFR2-targeting drug BGJ-398 (infigratinib) in combination with the MEK inhibitor trametinib proved to be synergic and exceptionally active, both in vitro and in vivo. The effects of the combined treatment by single-cell gene expression analysis revealed a remarkable plasticity of tumor cells and the greater sensitivity of cells with epithelial phenotype. This study brings personalized therapy closer to CUP patients and provides the rationale for FGFR2 and MEK targeting in metastatic tumors with FGFR2 pathway activation.

Invariant γδTCR natural killer-like effector T cells in the naked mole-rat

The naked mole-rat (Heterocephalus glaber) is a long-lived rodent species showing resistance to the development of cancer. Although naked mole-rats have been reported to lack natural killer (NK) cells, γδ T cell-based immunity has been suggested in this species, which could represent an important arm of the immune system for antitumor responses. Here, we investigate the biology of these unconventional T cells in peripheral tissues (blood, spleen) and thymus of the naked mole-rat at different ages by TCR repertoire profiling and single-cell gene expression analysis. Using our own TCR annotation in the naked mole-rat genome, we report that the γδ TCR repertoire is dominated by a public invariant Vγ4-2/Vδ1-4 TCR, containing the complementary-determining-region-3 (CDR3)γ CTYWDSNYAKKLF / CDR3δ CALWELRTGGITAQLVF that are likely generated by short-homology-repeat-driven DNA rearrangements. This invariant TCR is specifically found in γδ T cells expressing genes associated with NK cytotoxicity and is generated in both the thoracic and cervical thymus of the naked mole-rat until adult life. Our results indicate that invariant Vγ4-2/Vδ1-4 NK-like effector T cells in the naked mole-rat can contribute to tumor immunosurveillance by γδ TCR-mediated recognition of a common molecular signal.

Low-intensity ultrasound ameliorates brain organoid integration and rescues microcephaly deficits.

Human brain organoids represent a remarkable platform for modeling neurological disorders and a promising brain repair approach. However, the effects of physical stimulation on their development and integration remain unclear. Here, we report that low-intensity ultrasound significantly increases neural progenitor cell proliferation and neuronal maturation in cortical organoids. Histological assays and single-cell gene expression analyses reveal that low-intensity ultrasound improves the neural development in cortical organoids. Following organoid grafts transplantation into the injured somatosensory cortices of adult mice, longitudinal electrophysiological recordings and histological assays reveal that ultrasound-treated organoid grafts undergo advanced maturation. They also exhibit enhanced pain-related gamma-band activity and more disseminated projections into the host brain than the untreated groups. Finally, low-intensity ultrasound ameliorates neuropathological deficits in a microcephaly brain organoid model. Hence, low-intensity ultrasound stimulation advances the development and integration of brain organoids, providing a strategy for treating neurodevelopmental disorders and repairing cortical damage.

Clinical and CSF single-cell profiling of post-COVID-19 cognitive impairment

Natural history and mechanisms for persistent cognitive symptoms ("brain fog") following acute and often mild COVID-19 are unknown. In a large prospective cohort of people who underwent testing a median of 9months after acute COVID-19 in the New York City/New Jersey area, we found that cognitive dysfunction is common; is not influenced by mood, fatigue, or sleepiness; and is correlated with MRI changes in very few people. In a subgroup that underwent cerebrospinal fluid analysis, there are no changes related to Alzheimer's disease or neurodegeneration. Single-cell gene expression analysis in the cerebrospinal fluid shows findings consistent with monocyte recruitment, chemokine signaling, cellular stress, and suppressed interferon response-especially in myeloid cells. Longitudinal analysis shows slow recovery accompanied by key alterations in inflammatory genes and increased protein levels of CXCL8, CCL3L1, and sTREM2. These findings suggest that the prognosis for brain fog following COVID-19 correlates with myeloid-related chemokine and interferon-responsive genes.

SingmiR: a single-cell miRNA alignment and analysis tool.

Single-cell RNA sequencing(RNA-seq) has revolutionized our understanding of cell biology, developmental and pathophysiological molecular processes, paving the way toward novel diagnostic and therapeutic approaches. However, most of the gene regulatory processes on the single-cell level are still unknown, including post-transcriptional control conferred by microRNAs (miRNAs). Like the established single-cell gene expression analysis, advanced computational expertise is required to comprehensively process newly emerging single-cell miRNA-seq datasets. A web server providing a workflow tailored for single-cell miRNA-seq data with a self-explanatory interface is currently not available. Here, we present SingmiR, enabling the rapid (pre-)processing and quantification of human miRNAs from noncoding single-cell samples. It performs read trimming for different library preparation protocols, generates automated quality control reports and provides feature-normalized count files. Numerous standard and advanced analyses such as dimension reduction, clustered feature heatmaps, sample correlation heatmaps and differential expression statistics are implemented. We aim to speed up the prototyping pipeline for biologists developing single-cell miRNA-seq protocols on small to medium-sized datasets. SingmiR is freely available to all users without the need for a login athttps://www.ccb.uni-saarland.de/singmir.

Abstract 7041: Tumor-immune interactions and cisplatin resistance in localized muscle-invasive bladder cancer

Abstract Background: Cisplatin-based chemotherapy followed by radical cystectomy remains the standard-of-care treatment for patient with localized muscle-invasive bladder cancer (MIBC). Neoadjuvant clinical trials studying the combination of cisplatin-based chemotherapy and immune checkpoint blockade (ICB) in MIBC reported encouraging pathologic complete response rates. However, the molecular mechanisms and cellular programs involved in response and resistance to cisplatin and ICB in MIBC remain incompletely characterized. Our goal is to define cellular transcriptional programs and chromatin accessible regions in cancer cells and infiltrating immune cells associated with response and resistance to neoadjuvant systemic therapy. Methods: We performed single-cell Multiome ATAC and Gene expression sequencing (simultaneous identification of gene expression and open chromatin regions within the same cell) of tumors that had a complete response – “responders” – and tumors that had no response or progressed – “non-responders” – through neoadjuvant cisplatin-based chemotherapy (n=15). Single cell suspensions were prepared following the 10x Genomics protocol. Cell Ranger ARC was used for sequence alignment, peak calling, and generation of count matrices. Downstream single-cell gene expression analysis was performed with Scanpy and ATAC-seq with Seurat. Results: We identified two distinct urothelial cell populations in "responders" vs "non-responders" based on single cell gene expression and genome wide chromatin accessibility regions. Cancer cells in “non-responders” preferentially express basal cell gene expression signatures. “Non-responders” were significantly enriched in suppressive tumor-associated macrophages (TAMs). Interestingly, SPP1+ TAMs known to have a pro-tumoral role and promote resistance to ICB were exclusively identified in “non-responders”. Conclusion: Single cell and genome wide chromatin accessibility regions identify heterogenous urothelial cell populations expressing basal cell markers in tumors resistant to neoadjuvant cisplatin-based chemotherapy. “Non-responders” are significantly enriched with TAMs implicated in resistance to ICB. Future studies will better define the implications of these findings in cancer therapeutics for patients with MIBC. Citation Format: Filipe La Fuente De Carvalho, Jihyun Lee, Kevin Bi, Breanna Titchen, Konrad Stawiski, Jihye Park, Amanda Garza, Daniel Michaud, Jennifer Guerriero, Elizabeth Mittendorf, Kent Mouw, Eliezer Van Allen. Tumor-immune interactions and cisplatin resistance in localized muscle-invasive bladder cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7041.

The effector program of human CD8 T cells supports tissue remodeling.

CD8 T lymphocytes are classically viewed as cytotoxic T cells. Whether human CD8 T cells can, in parallel, induce a tissue regeneration program is poorly understood. Here, antigen-specific assay systems revealed that human CD8 T cells not only mediated cytotoxicity but also promoted tissue remodeling. Activated CD8 T cells could produce the epidermal growth factor receptor (EGFR)-ligand amphiregulin (AREG) and sensitize epithelial cells for enhanced regeneration potential. Blocking the EGFR or the effector cytokines IFN-γ and TNF could inhibit tissue remodeling. This regenerative program enhanced tumor spheroid and stem cell-mediated organoid growth. Using single-cell gene expression analysis, we identified an AREG+, tissue-resident CD8 T cell population in skin and adipose tissue from patients undergoing abdominal wall or abdominoplasty surgery. These tissue-resident CD8 T cells showed a strong TCR clonal relation to blood PD1+TIGIT+ CD8 T cells with tissue remodeling abilities. These findings may help to understand the complex CD8 biology in tumors and could become relevant for the design of therapeutic T cell products.

Nasopharyngeal lymphatic plexus is a hub for cerebrospinal fluid drainage.

Cerebrospinal fluid (CSF) in the subarachnoid space around the brain has long been known to drain through the lymphatics to cervical lymph nodes1-17, but the connections and regulation have been challenging to identify. Here, using fluorescent CSF tracers in Prox1-GFP lymphatic reporter mice18, we found that the nasopharyngeal lymphatic plexus is a major hub for CSF outflow to deep cervical lymph nodes. This plexus had unusual valves and short lymphangions but no smooth-muscle coverage, whereas downstream deep cervical lymphatics had typical semilunar valves, long lymphangions and smooth muscle coverage that transported CSF to the deep cervical lymph nodes. α-Adrenergic and nitric oxide signalling in the smooth muscle cells regulated CSF drainage through the transport properties of deep cervical lymphatics. During ageing, the nasopharyngeal lymphatic plexus atrophied, but deep cervical lymphatics were not similarly altered, and CSF outflow could still be increased by adrenergic or nitric oxide signalling. Single-cell analysis of gene expression in lymphatic endothelial cells of the nasopharyngeal plexus of aged mice revealed increased type I interferon signalling and other inflammatory cytokines. The importance of evidence for the nasopharyngeal lymphatic plexus functioning as a CSF outflow hub is highlighted by its regression during ageing. Yet, the ageing-resistant pharmacological activation of deep cervical lymphatic transport towards lymph nodes can still increase CSF outflow, offering an approach for augmenting CSF clearance in age-related neurological conditions in which greater efflux would be beneficial.

Transcriptional profiling of human cartilage endplate cells identifies novel genes and cell clusters underlying degenerated and non-degenerated phenotypes

BackgroundLow back pain is a leading cause of disability worldwide and is frequently attributed to intervertebral disc (IVD) degeneration. Though the contributions of the adjacent cartilage endplates (CEP) to IVD degeneration are well documented, the phenotype and functions of the resident CEP cells are critically understudied. To better characterize CEP cell phenotype and possible mechanisms of CEP degeneration, bulk and single-cell RNA sequencing of non-degenerated and degenerated CEP cells were performed.MethodsHuman lumbar CEP cells from degenerated (Thompson grade ≥ 4) and non-degenerated (Thompson grade ≤ 2) discs were expanded for bulk (N=4 non-degenerated, N=4 degenerated) and single-cell (N=1 non-degenerated, N=1 degenerated) RNA sequencing. Genes identified from bulk RNA sequencing were categorized by function and their expression in non-degenerated and degenerated CEP cells were compared. A PubMed literature review was also performed to determine which genes were previously identified and studied in the CEP, IVD, and other cartilaginous tissues. For single-cell RNA sequencing, different cell clusters were resolved using unsupervised clustering and functional annotation. Differential gene expression analysis and Gene Ontology, respectively, were used to compare gene expression and functional enrichment between cell clusters, as well as between non-degenerated and degenerated CEP samples.ResultsBulk RNA sequencing revealed 38 genes were significantly upregulated and 15 genes were significantly downregulated in degenerated CEP cells relative to non-degenerated cells (|fold change| ≥ 1.5). Of these, only 2 genes were previously studied in CEP cells, and 31 were previously studied in the IVD and other cartilaginous tissues. Single-cell RNA sequencing revealed 11 unique cell clusters, including multiple chondrocyte and progenitor subpopulations with distinct gene expression and functional profiles. Analysis of genes in the bulk RNA sequencing dataset showed that progenitor cell clusters from both samples were enriched in “non-degenerated” genes but not “degenerated” genes. For both bulk- and single-cell analyses, gene expression and pathway enrichment analyses highlighted several pathways that may regulate CEP degeneration, including transcriptional regulation, translational regulation, intracellular transport, and mitochondrial dysfunction.ConclusionsThis thorough analysis using RNA sequencing methods highlighted numerous differences between non-degenerated and degenerated CEP cells, the phenotypic heterogeneity of CEP cells, and several pathways of interest that may be relevant in CEP degeneration.

Dual-Fluorescence Chromosome-Located Labeling System for Accurate In Vivo Single-Cell Gene Expression Analysis in Pseudomonas syringae.

Epigenetic regulation as a means for bacterial adaptation is receiving increasing interest in the last decade. Significant efforts have been directed towards understanding the mechanisms giving raise to phenotypic heterogeneity within bacterial populations and its adaptive relevance. Phenotypic heterogeneity mostly refers to phenotypic variation not linked to genetic differences nor to environmental stimuli. Recent findings on the relevance of phenotypic heterogeneity on some bacterial complex traits are causing a shift from traditional assays where bacterial phenotypes are defined by averaging population-level data, to single-cell analysis that focus on bacterial individual behavior within the population. Fluorescent labeling is a key asset for single-cell gene expression analysis using flow cytometry, fluorescence microscopy, and/or microfluidics.We previously described the generation of chromosome-located transcriptional gene fusions to fluorescent reporter genes using the model bacterial plant pathogen Pseudomonas syringae. These fusions allow researchers to follow variation in expression of the gene(s) of interest, without affecting gene function. In this report, we improve the analytic power of the method by combining such transcriptional fusions with constitutively expressed compatible fluorescent reporter genes integrated in a second, neutral locus of the bacterial chromosome. Constitutively expressed fluorescent reporters allow for the detection of all bacteria comprising a heterogeneous population, regardless of the level of expression of the concurrently monitored gene of interest, thus avoiding the traditional use of stains often incompatible with samples from complex contexts such as the leaf.

FastCAR: fast correction for ambient RNA to facilitate differential gene expression analysis in single-cell RNA-sequencing datasets

Cell type-specific differential gene expression analyses based on single-cell transcriptome datasets are sensitive to the presence of cell-free mRNA in the droplets containing single cells. This so-called ambient RNA contamination may differ between samples obtained from patients and healthy controls. Current ambient RNA correction methods were not developed specifically for single-cell differential gene expression (sc-DGE) analyses and might therefore not sufficiently correct for ambient RNA-derived signals. Here, we show that ambient RNA levels are highly sample-specific. We found that without ambient RNA correction, sc-DGE analyses erroneously identify transcripts originating from ambient RNA as cell type-specific disease-associated genes. We therefore developed a computationally lean and intuitive correction method, Fast Correction for Ambient RNA (FastCAR), optimized for sc-DGE analysis of scRNA-Seq datasets generated by droplet-based methods including the 10XGenomics Chromium platform. FastCAR uses the profile of transcripts observed in libraries that likely represent empty droplets to determine the level of ambient RNA in each individual sample, and then corrects for these ambient RNA gene expression values. FastCAR can be applied as part of the data pre-processing and QC in sc-DGE workflows comparing scRNA-Seq data in a health versus disease experimental design. We compared FastCAR with two methods previously developed to remove ambient RNA, SoupX and CellBender. All three methods identified additional genes in sc-DGE analyses that were not identified in the absence of ambient RNA correction. However, we show that FastCAR performs better at correcting gene expression values attributed to ambient RNA, resulting in a lower frequency of false-positive observations. Moreover, the use of FastCAR in a sc-DGE workflow increases the cell-type specificity of sc-DGE analyses across disease conditions.

Post-Transplant T Cell Clonotype Diversity Is Associated with Survival in Patients with TP53-Mutated Acute Myeloid Leukemia

Background TP53 mutations are associated with unfavorable outcomes in various cancer types and present an obstacle to achieving sustained remission in acute myeloid leukemia (AML). Even with allogeneic hematopoietic stem cell transplantation (HSCT), the risk of relapse approximates 80%, with dismal long-term survival. This could imply methods of immune escape in TP53 mutated leukemias that allow them to evade the graft-versus-leukemia (GVL) effect, which is a critical mechanism of disease control with HSCT. This study investigates the dynamics of immune reconstitution at single-cell resolution in TP53-mutated AML at pre- and multiple post-HSCT timepoints in patients who either remain in long-term remission or relapse following HSCT. Methods We collected 26 longitudinal bone marrow aspirates and 1 peripheral blood sample from 12 patients with TP53-mutated AML who underwent HSCT at the Dana-Farber Cancer Institute between 2015-21. All patients received HLA-matched T-cell replete HSCT in morphologic remission, with standard tacrolimus/methotrexate-based prophylaxis and peripheral blood stem cells. We categorized the patients into two cohorts based on their treatment response: long-term remission (>3.5 years, cohort 1, n=4) or relapse (cohort 2, n=8). We performed paired 5' single-cell RNA and T cell receptor (TCR) sequencing on sorted viable mononuclear from each sample and CD3+ T cells from selected samples using 10x Genomics procedures. In total, we analyzed 44 samples (27 mononuclear, 17 CD3+), resulting in 250,640 high-quality single-cell transcriptomes, including 137,649 T cells and NK cells. Data analysis was performed using Cell Ranger Multi (10x Genomics) and R 4.3 with the tidyverse 2.0, Seurat 5.1, and scRepertoire 1.1 packages. Results We focused our initial analysis on the 2-6-month post-HSCT period that is critical for immune reconstitution. This included eight samples from seven patients in the two cohorts (1: remission, 2: relapse, pink box in Figure 1). Of these 7 patients, 4 were in the relapse cohort, with these relapses occurring >4 months post-HSCT. No significant difference in T-cell chimerism was seen between these 7 patients in this 2-6 month period. Based on canonical gene expression signatures, we annotated cell types and selected T cells for further evaluation (Figure 2). First, we found that the CD4/CD8 ratio differed between the cohorts, indicating a relative CD8+ T cell expansion in the relapse cohort (cohort 1: 1.69, cohort 2: 0.55, P<0.0001). Second, we found lower TCR diversity in the relapse cohort (inverse Simpson index, cohort 1: 234.6, cohort 2: 83.0, P<0.0001). This difference remained significant when subsampling the same number of T cells per patient and when restricting all samples to the 3 to 4-month timepoint. Considering the disparity in CD8 T cell numbers between the cohorts, we also analyzed repertoire diversity, specifically in CD8+ T cells, and found that the observed significance persisted. To further investigate TCR diversity, we overlaid T cell clonotypes (cells that share the same TCR sequence) in a UMAP visualization, which highlighted increased hyperexpanded CD8+ T cells in the relapse cohort (Figure 2). Finally, we found that greater clonotype expansion was correlated with the expression of key T cell genes, including CD8A, CD8B, PRF1, NKG7, and GZMA. These results suggest that cytotoxic CD8+ T cells link lower TCR diversity to the likelihood of disease relapse. Conclusions By performing deep analysis of single-cell gene expression linked to TCR clonotypes, we discover new insights into the biology of hematopoietic reconstitution after HSCT of patients with TP53-mutated AML. Despite having analyzed a limited number of samples, we find that patients who remain in long-term remission have significantly higher CD8+ TCR diversity between 2-6 months post-HSCT, while those who relapsed between 5-18 months post-HSCT showed lower TCR diversity and hyperexpanded CD8+ clones at the same timepoints. This work suggests that early post-HSCT TCR diversity could be a biomarker associated with GVL and warrants further study. In ongoing and future analyses, we will mine the current dataset for further insights into the factors influencing survival in TP53-mutated AML patients. We also plan to extend the measurement of TCR diversity as a predictor of survival for validation in a larger cohort.

A Novel, Probe-Based and Instrument-Free Method for Improved Ultrahigh-Throughput Single-Cell Gene Expression Analysis of Peripheral Blood Mononuclear Cells

Single-cell gene expression assays are critical tools for identifying functional subtypes of immune cells, as well as changes within cells resulting from pathology or treatment. However, most current methods are expensive, low in sample throughput, rely on reverse transcription and lack the sensitivity to consistently measure low expressed genes from single cells - preventing measurements of many key immune biomarkers and molecular pathways. Another problem with existing single-cell sequencing methods is that many of the cell-associated reads either fail to map to transcripts or map to uninformative ribosomal and mitochondrial genes. Some methods also require the use of live cells, which means the single-cell assay has to be carried out at the specific time of treatment or when culture is terminated. The aforementioned limitations have contributed to most single-cell sequencing studies being restricted to small numbers of samples and have prevented their wider scale adoption in biopharma, clinical, translational and applied applications. Here we report on the development and performance of a novel combinatorial split-pool-based workflow, TempO-LINC™, that adds cell-identifying molecular barcodes onto high-sensitivity gene expression probes within fixed cells. Cells can be fixed at the end of a treatment, or when obtained from a patient and stably stored for months until they are ready to be processed with other samples through the TempO-LINC assay. All probes within the same fixed cell receive an identical barcode, enabling the reconstruction of single-cell gene expression profiles across as few as several hundred cells and up to 100,000 cells per run. TempO-LINC simultaneously processes up to 96 fixed cell samples per run, has a simple workflow that is amenable to automation and as we will show, has a higher gene detection rate than existing single-cell platforms. We will also show that TempO-LINC has an observed doublet rate of less than 0.5% for 12,500 cells analyzed. Critically, TempO-LINC reduces sample sequencing costs and although we show the assay accurately profiles the whole transcriptome (23,000 transcripts), it can also be targeted to measure only genes/pathways of interest - dramatically reducing sequencing costs yet further. We applied TempO-LINC to assay PBMCs and a human hepatocyte model for toxicology and demonstrated the ability to correctly identify unique cell states and molecular pathways from these populations. We will also present time course and dose response data from compound treatment of cells. All of these features position TempO-LINC as a potential disruptive technology that hematology researchers, clinicians and drug developers can use for new large-scale applications/studies using single-cell sequencing across thousands of samples while obtaining improved data quality.

ScMuffin: an R package to disentangle solid tumor heterogeneity by single-cell gene expression analysis

IntroductionSingle-cell (SC) gene expression analysis is crucial to dissect the complex cellular heterogeneity of solid tumors, which is one of the main obstacles for the development of effective cancer treatments. Such tumors typically contain a mixture of cells with aberrant genomic and transcriptomic profiles affecting specific sub-populations that might have a pivotal role in cancer progression, whose identification eludes bulk RNA-sequencing approaches. We present scMuffin, an R package that enables the characterization of cell identity in solid tumors on the basis of a various and complementary analyses on SC gene expression data.ResultsscMuffin provides a series of functions to calculate qualitative and quantitative scores, such as: expression of marker sets for normal and tumor conditions, pathway activity, cell state trajectories, Copy Number Variations, transcriptional complexity and proliferation state. Thus, scMuffin facilitates the combination of various evidences that can be used to distinguish normal and tumoral cells, define cell identities, cluster cells in different ways, link genomic aberrations to phenotypes and identify subtle differences between cell subtypes or cell states. We analysed public SC expression datasets of human high-grade gliomas as a proof-of-concept to show the value of scMuffin and illustrate its user interface. Nevertheless, these analyses lead to interesting findings, which suggest that some chromosomal amplifications might underlie the invasive tumor phenotype and the presence of cells that possess tumor initiating cells characteristics.ConclusionsThe analyses offered by scMuffin and the results achieved in the case study show that our tool helps addressing the main challenges in the bioinformatics analysis of SC expression data from solid tumors.

Control of murine brown adipocyte development by GATA6.

Brown adipose tissue (BAT) is a thermogenic organ that protects animals against hypothermia and obesity. BAT derives from the multipotent paraxial mesoderm; however, the identity of embryonic brown fat progenitor cells and regulators of adipogenic commitment are unclear. Here, we performed single-cell gene expression analyses of mesenchymal cells during mouse embryogenesis with a focus on BAT development. We identified cell populations associated with the development of BAT, including Dpp4+ cells that emerge at the onset of adipogenic commitment. Immunostaining and lineage-tracing studies show that Dpp4+ cells constitute the BAT fascia and contribute minorly as adipocyte progenitors. Additionally, we identified the transcription factor GATA6 as a marker of brown adipogenic progenitor cells. Deletion of Gata6 in the brown fat lineage resulted in a striking loss of BAT. Together, these results identify progenitor and transitional cells in the brown adipose lineage and define a crucial role for GATA6 in BAT development.

Using combined single-cell gene expression, TCR sequencing and cell surface protein barcoding to characterize and track CD4+ T cell clones from murine tissues.

Single-cell gene expression analysis using sequencing (scRNA-seq) has gained increased attention in the past decades for studying cellular transcriptional programs and their heterogeneity in an unbiased manner, and novel protocols allow the simultaneous measurement of gene expression, T-cell receptor clonality and cell surface protein expression. In this article, we describe the methods to isolate scRNA/TCR-seq-compatible CD4+ T cells from murine tissues, such as skin, spleen, and lymph nodes. We describe the processing of cells and quality control parameters during library preparation, protocols for multiplexing of samples, and strategies for sequencing. Moreover, we describe a step-by-step bioinformatic analysis pipeline from sequencing data generated using these protocols. This includes quality control, preprocessing of sequencing data and demultiplexing of individual samples. We perform quantification of gene expression and extraction of T-cell receptor alpha and beta chain sequences, followed by quality control and doublet detection, and methods for harmonization and integration of datasets. Next, we describe the identification of highly variable genes and dimensionality reduction, clustering and pseudotemporal ordering of data, and we demonstrate how to visualize the results with interactive and reproducible dashboards. We will combine different analytic R-based frameworks such as Bioconductor and Seurat, illustrating how these can be interoperable to optimally analyze scRNA/TCR-seq data of CD4+ T cells from murine tissues.