scholarly journals Single Cell Sequencing Reveals Glial Specific Responses to Tissue Processing & Enzymatic Dissociation in Mice and Humans

2020 ◽  
Author(s):  
Samuel E. Marsh ◽  
Tushar Kamath ◽  
Alec J. Walker ◽  
Lasse Dissing-Olesen ◽  
Timothy R. Hammond ◽  
...  

AbstractA key aspect of nearly all single cell experiments is the necessity to dissociate intact tissues into single cell suspensions for processing. While many protocols have been optimized for optimal cell yield, they have often overlooked the effects that dissociation can have on ex vivo gene expression changes during this process. Microglia, the brain’s resident macrophages, are a highly dynamic population that are extremely sensitive to their microenvironment and have been shown to dramatically alter their transcriptome upon stimulation. We demonstrate that use of enzymatic dissociation methods on mouse central nervous system (CNS) tissue induces an aberrant gene expression signature in microglia that can significantly confound downstream analysis. To minimize this issue, we developed a flexible protocol, that can be used with existing enzymatic protocols for fresh tissue, to eliminate artifactual gene expression while allowing for increased cell type diversity and yield. We demonstrate efficacy of this protocol in analysis of diverse CNS cell types and sorted myeloid populations while using enzymatic dissociation. Generation of new and reanalysis of previously published human brain single nucleus RNAseq (snRNA-seq) datasets reveal that a similar signature is also present in post-mortem tissue. Through novel snRNA-seq analysis of acutely-resected neurosurgical tissue we demonstrate that this signature can be induced in human tissue due to technical differences in sample processing. These results provide key insight into the potential confounds of enzymatic digestion and provide a solution to allow for enzymatic digestion for scRNA-seq while avoiding ex vivo transcriptional artifacts. Analysis of human tissue reveals potential for artifacts in current and future snRNA-seq datasets that will require deeper analysis and careful consideration to separate true biology from artifacts related to post-mortem processes.

2019 ◽  
Vol 20 (9) ◽  
pp. 2316 ◽  
Author(s):  
Maria Moreno-Villanueva ◽  
Ye Zhang ◽  
Alan Feiveson ◽  
Brandon Mistretta ◽  
Yinghong Pan ◽  
...  

Detrimental health consequences from exposure to space radiation are a major concern for long-duration human exploration missions to the Moon or Mars. Cellular responses to radiation are expected to be heterogeneous for space radiation exposure, where only high-energy protons and other particles traverse a fraction of the cells. Therefore, assessing DNA damage and DNA damage response in individual cells is crucial in understanding the mechanisms by which cells respond to different particle types and energies in space. In this project, we identified a cell-specific signature for radiation response by using single-cell transcriptomics of human lymphocyte subpopulations. We investigated gene expression in individual human T lymphocytes 3 h after ex vivo exposure to 2-Gy gamma rays while using the single-cell sequencing technique (10X Genomics). In the process, RNA was isolated from ~700 irradiated and ~700 non-irradiated control cells, and then sequenced with ~50 k reads/cell. RNA in each of the cells was distinctively barcoded prior to extraction to allow for quantification for individual cells. Principal component and clustering analysis of the unique molecular identifier (UMI) counts classified the cells into three groups or sub-types, which correspond to CD4+, naïve, and CD8+/NK cells. Gene expression changes after radiation exposure were evaluated using negative binomial regression. On average, BBC3, PCNA, and other TP53 related genes that are known to respond to radiation in human T cells showed increased activation. While most of the TP53 responsive genes were upregulated in all groups of cells, the expressions of IRF1, STAT1, and BATF were only upregulated in the CD4+ and naïve groups, but were unchanged in the CD8+/NK group, which suggests that the interferon-gamma pathway does not respond to radiation in CD8+/NK cells. Thus, single-cell RNA sequencing technique was useful for simultaneously identifying the expression of a set of genes in individual cells and T lymphocyte subpopulation after gamma radiation exposure. The degree of dependence of UMI counts between pairs of upregulated genes was also evaluated to construct a similarity matrix for cluster analysis. The cluster analysis identified a group of TP53-responsive genes and a group of genes that are involved in the interferon gamma pathway, which demonstrate the potential of this method for identifying previously unknown groups of genes with similar expression patterns.


2020 ◽  
Author(s):  
Karin D. Prummel ◽  
Helena L. Crowell ◽  
Susan Nieuwenhuize ◽  
Eline C. Brombacher ◽  
Stephan Daetwyler ◽  
...  

AbstractThe mesothelium forms epithelial membranes that line the bodies cavities and surround the internal organs. Mesothelia widely contribute to organ homeostasis and regeneration, and their dysregulation can result in congenital anomalies of the viscera, ventral wall defects, and mesothelioma tumors. Nonetheless, the embryonic ontogeny and developmental regulation of mesothelium formation has remained uncharted. Here, we combine genetic lineage tracing, in toto live imaging, and single-cell transcriptomics in zebrafish to track mesothelial progenitor origins from the lateral plate mesoderm (LPM). Our single-cell analysis uncovers a post-gastrulation gene expression signature centered on hand2 that delineates distinct progenitor populations within the forming LPM. Combining gene expression analysis and imaging of transgenic reporter zebrafish embryos, we chart the origin of mesothelial progenitors to the lateral-most, hand2-expressing LPM and confirm evolutionary conservation in mouse. Our time-lapse imaging of transgenic hand2 reporter embryos captures zebrafish mesothelium formation, documenting the coordinated cell movements that form pericardium and visceral and parietal peritoneum. We establish that the primordial germ cells migrate associated with the forming mesothelium as ventral migration boundary. Functionally, hand2 mutants fail to close the ventral mesothelium due to perturbed migration of mesothelium progenitors. Analyzing mouse and human mesothelioma tumors hypothesized to emerge from transformed mesothelium, we find de novo expression of LPM-associated transcription factors, and in particular of Hand2, indicating the re-initiation of a developmental transcriptional program in mesothelioma. Taken together, our work outlines a genetic and developmental signature of mesothelial origins centered around Hand2, contributing to our understanding of mesothelial pathologies and mesothelioma.


Author(s):  
Astrid M. Alsema ◽  
Qiong Jiang ◽  
Laura Kracht ◽  
Emma Gerrits ◽  
Marissa L. Dubbelaar ◽  
...  

AbstractMicroglia are the tissue-resident macrophages of the central nervous system (CNS). Recent studies based on bulk and single-cell RNA sequencing in mice indicate high relevance of microglia with respect to risk genes and neuro-inflammation in Alzheimer’s disease. Here, we investigated microglia transcriptomes at bulk and single cell level in non-demented elderly and AD donors using acute human post-mortem cortical brain samples. We identified 9 human microglial subpopulations with heterogeneity in gene expression. Notably, gene expression profiles and subcluster composition of microglia did not differ between AD donors and non-demented elderly in bulk RNA sequencing nor in single-cell sequencing.


2019 ◽  
Vol 2 (6) ◽  
pp. e201900561 ◽  
Author(s):  
Dong Seong Cho ◽  
Bolim Lee ◽  
Jason D Doles

Obesity is a serious health concern and is associated with a reduced quality of life and a number of chronic diseases, including diabetes, heart disease, stroke, and cancer. With obesity rates on the rise worldwide, adipose tissue biology has become a top biomedical research priority. Despite steady growth in obesity-related research, more investigation into the basic biology of adipose tissue is needed to drive innovative solutions aiming to curtail the obesity epidemic. Adipose progenitor cells (APCs) play a central role in adipose tissue homeostasis and coordinate adipose tissue expansion and remodeling. Although APCs are well studied, defining and characterizing APC subsets remains ambiguous because of ill-defined cellular heterogeneity within this cellular compartment. In this study, we used single-cell RNA sequencing to create a cellular atlas of APC heterogeneity in mouse visceral adipose tissue. Our analysis identified two distinct populations of adipose tissue–derived stem cells (ASCs) and three distinct populations of preadipocytes (PAs). We identified novel cell surface markers that, when used in combination with traditional ASC and preadipocyte markers, could discriminate between these APC subpopulations by flow cytometry. Prospective isolation and molecular characterization of these APC subpopulations confirmed single-cell RNA sequencing gene expression signatures, and ex vivo culture revealed differential expansion/differentiation capabilities. Obese visceral adipose tissue featured relative expansion of less mature ASC and PA subpopulations, and expression analyses revealed major obesity-associated signaling alterations within each APC subpopulation. Taken together, our study highlights cellular and transcriptional heterogeneity within the APC pool, provides new tools to prospectively isolate and study these novel subpopulations, and underscores the importance of considering APC diversity when studying the etiology of obesity.


2021 ◽  
Vol 17 (7) ◽  
pp. e1009228
Author(s):  
Kaiyi Zhu ◽  
Lingyi Cai ◽  
Chenqian Cui ◽  
Juan R. de los Toyos ◽  
Dimitris Anastassiou

During the last ten years, many research results have been referring to a particular type of cancer-associated fibroblasts associated with poor prognosis, invasiveness, metastasis and resistance to therapy in multiple cancer types, characterized by a gene expression signature with prominent presence of genes COL11A1, THBS2 and INHBA. Identifying the underlying biological mechanisms responsible for their creation may facilitate the discovery of targets for potential pan-cancer therapeutics. Using a novel computational approach for single-cell gene expression data analysis identifying the dominant cell populations in a sequence of samples from patients at various stages, we conclude that these fibroblasts are produced by a pan-cancer cellular transition originating from a particular type of adipose-derived stromal cells naturally present in the stromal vascular fraction of normal adipose tissue, having a characteristic gene expression signature. Focusing on a rich pancreatic cancer dataset, we provide a detailed description of the continuous modification of the gene expression profiles of cells as they transition from APOD-expressing adipose-derived stromal cells to COL11A1-expressing cancer-associated fibroblasts, identifying the key genes that participate in this transition. These results also provide an explanation to the well-known fact that the adipose microenvironment contributes to cancer progression.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 1194-1194
Author(s):  
Philipp Sergeev ◽  
Sadiksha Adhikari ◽  
Juho J. Miettinen ◽  
Maiju-Emilia Huppunen ◽  
Minna Suvela ◽  
...  

Abstract Introduction Melphalan flufenamide (melflufen), is a novel peptide-drug conjugate that targets aminopeptidases and selectively delivers alkylating agents in tumors. Melflufen was recently FDA approved for the treatment of relapsed/refractory multiple myeloma (MM) patients. Considering the challenges in treating this group of patients, and the availability of several new drugs for MM, information that can support treatment selection is urgently needed. To identify potential indicators of response and mechanism of resistance to melflufen, we applied a multiparametric drug sensitivity assay to MM patient samples ex vivo and analyzed the samples by single cell RNA sequencing (scRNAseq). Ex vivo drug testing identified MM samples that were distinctly sensitive or resistant to melflufen, while differential gene expression analysis revealed pathways associated with response. Methods Bone marrow (BM) aspirates from 24 MM patients were obtained after written informed consent following approved protocols in compliance with the Declaration of Helsinki. BM mononuclear cells from 12 newly diagnosed (ND) and 12 relapsed/refractory (RR) patients were used for multi-parametric flow cytometry-based drug sensitivity and resistance testing (DSRT) evaluation to melflufen and melphalan, and for scRNAseq. Based on the results from the DSRT tests and drug sensitivity scores (DSS), we divided the samples into three groups - high sensitivity (HS, DSS > 40 (melflufen) or DSS > 16 (melphalan)), intermediate sensitivity (IS, 31 ≤ DSS ≤ 40 (melflufen) or 10 ≤ DSS ≤ 16 (melphalan)), and low sensitivity (LS, DSS < 31 (melflufen) or DSS < 10 (melphalan)). To identify genes, responsible for the general sensitivity to melphalan-based drugs we conducted differential gene expression (DGE) analyses separately for melphalan and melflufen focusing on the plasma cell populations, comparing gene expression between HS and LS samples for both drugs ("HS vs. LS melphalan" and "HS vs. LS for melflufen", respectively). In addition, to explain the increased sensitivity of RR samples, we conducted the DGE analysis for ND vs. RR samples and searched for similarities between these three datasets. Results DSRT data indicated that samples from RRMM patients were significantly more sensitive to melflufen compared to samples from NDMM (Fig. 1A). In addition, we observed that samples with a gain of 1q (+1q) were more sensitive to melflufen while those with deletion of 13q (del13q) appeared to be less sensitive, although these results lacked significance (Fig. 1A). After separating the samples into different drug sensitivity groups (HS, IS, LS), DGE analysis showed significant downregulation of the drug efflux and multidrug resistance protein family member ABCB9 in the melflufen HS group opposed to the LS group (2.2-fold, p < 0.001). A similar pattern was detected for the melphalan HS vs. LS comparison suggesting that this alteration might be a common indicator of sensitivity to melphalan-based drugs. Furthermore, in the melflufen HS group we observed downregulation of the matrix metallopeptidase inhibitors TIMP1 and TIMP2 (3-fold and 1.6-fold, p < 0.001, respectively), and cathepsin inhibitors CST3 and CSTB (3.2-fold and 1.3-fold, p < 0.001, respectively) (Fig. 1B). This effect was observed in both "ND vs. RR" and "HS vs. LS for melflufen" comparisons, but not for melphalan, suggesting that these changes are associated with disease progression and specific indicators of sensitivity to melflufen. Moreover, gene set enrichment analysis (GSEA) showed activation of pathways related to protein synthesis, as well as amino acid starvation for malignant and normal cell populations in the HS group. Conclusion In summary, our results indicate that melflufen is more active in RRMM compared to NDMM. In addition, samples from MM patients with +1q, which is considered an indicator of high-risk disease, tended to be more sensitive to melflufen. Based on differential GSEA and pathway enrichment, several synergizing mechanisms could potentially explain the higher sensitivity to melflufen, such as decreased drug efflux and increased drug uptake. Although these results indicate potential indicators of response and mechanisms of drug efficacy, further validation of these findings is required using data from melflufen treated patients. Figure 1 Figure 1. Disclosures Slipicevic: Oncopeptides AB: Current Employment. Nupponen: Oncopeptides AB: Consultancy. Lehmann: Oncopeptides AB: Current Employment. Heckman: Orion Pharma: Research Funding; Oncopeptides: Consultancy, Research Funding; Novartis: Research Funding; Celgene/BMS: Research Funding; Kronos Bio, Inc.: Research Funding.


2021 ◽  
Author(s):  
Francisco J. Garcia ◽  
Na Sun ◽  
Hyeseung Lee ◽  
Brianna Godlewski ◽  
Kyriaki Galani ◽  
...  

SummaryDespite the importance of the blood-brain barrier in maintaining normal brain physiology and in understanding neurodegeneration and CNS drug delivery, human cerebrovascular cells remain poorly characterized due to their sparsity and dispersion. Here, we perform the first single-cell characterization of the human cerebrovasculature using both ex vivo fresh-tissue experimental enrichment and post mortem in silico sorting of human cortical tissue samples. We capture 31,812 cerebrovascular cells across 17 subtypes, including three distinct subtypes of perivascular fibroblasts as well as vasculature-coupled neurons and glia. We uncover human-specific expression patterns along the arteriovenous axis and determine previously uncharacterized cell type-specific markers. We use our newly discovered human-specific signatures to study changes in 3,945 cerebrovascular cells of Huntington’s disease patients, which reveal an activation of innate immune signaling in vascular and vasculature-coupled cell types and the concomitant reduction to proteins critical for maintenance of BBB integrity. Finally, our study provides a comprehensive resource molecular atlas of the human cerebrovasculature to guide future biological and therapeutic studies.


Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 3343-3343
Author(s):  
Matteo Maria Naldini ◽  
Gabriele Casirati ◽  
Erika Zonari ◽  
Giacomo Desantis ◽  
Andrea Cammarata ◽  
...  

Abstract Hematopoietic stem and progenitor cell (HSPC) expansion remains an important unmet goal for ex vivo gene therapy based on gene addition and editing to compensate for the negative impact of the gene transfer procedure enabling faster engraftment and less complications. Additionally, ex vivo expansion of corrected cells may improve efficacy at more sustainable manufacturing costs by downscaling transduction. To date, our knowledge of precise mechanisms of action of expansion compounds is limited, and it remains unclear whether cord blood expansion protocols also maintain stemness of mobilized peripheral blood CD34+ cells (mPB), the preferred HSPC source for gene therapy. We performed serial (day 0,4,8) droplet-based single cell RNA sequencing (scRNAseq) on lentivirally transduced mPB expanded with UM171 to dissect cellular heterogeneity, monitor population dynamics over time and identify a transcriptional profile of primitive cells in culture. By associating published HSPC gene expression profiles to our scRNAseq dataset from uncultured mPB, we found that 45% of cells harbored a myelo-lymphoid signature. Smaller cell clusters expressed a shared erythroid (ERY) and megakaryocytic (MK) signature (20%), or a more primitive multipotent HSC-like signature (15%) characterized by enhanced JAK/STAT signaling and expression of HSC associated genes (AVP, HOPX, ID3). Unsupervised ordering of cells within pseudotime separated emerging MK/ERYpoiesis (FCER1A, HBD) from lympho-myelopoiesis (CD52, JUN), with intermediate states of more primitive progenitors located in between. After 4 days in culture, we noted a general increase in nuclear and mitochondrial gene transcription with activation of oxidative metabolism, paralleled by cell cycle activation, as expected from cytokine stimulation. By d8 of culture these changes leveled off but remained higher than uncultured cells. Of note, cells at d8 revealed an activation of cellular stress response pathways (e.g. TNFa, IFNg) hinting towards a compromised culture that may eventually exhaust HSC. Unsupervised clustering of cultured mPB highlighted a dramatic expansion (70-80%) of MK/ERY progenitor cells with high cycling activity with only 20-30% cells showing myelo-lymphoid transcriptional features. In line, pseudotime analysis highlighted a main ERY and MK trajectory separated from that of cells characterized by the expression of HSPC genes (HOPX, SPINK2) and of an emerging myeloid trajectory (MPO). To profile HSC in culture, we sorted and sequenced CD34+90+201+ cells from d4 expansion culture (3% of total cells), which we show to contain >70% of SCID repopulating potential. ScRNAseq revealed transcriptional similarity with the myelo-lymphoid progenitor cluster identified in the unsorted d4 culture. Unsupervised clustering of the CD34+90+201+ population revealed cell cycle dependent heterogeneity, identifying a highly quiescent cluster with expression of HSC-like signatures. This cluster was also characterized by relatively low gene expression, possibly reflecting a non-activated cell state consistent with primitive HSPC. Pseudotime analysis produced a four-branched minimum spanning tree, which retained a clear cell cycle and metabolic effect. Top variable genes included cell cycle, glycolytic, mitochondrial and ribosomal genes, identifying different metabolic modules along the branched trajectory. These results highlight that cell heterogeneity within a purified, HSC-enriched population is driven mainly by metabolic activation and cell cycle status. As a complementary approach, we purified LT-HSC from uncultured mPB (CD34+38-90+45RA-49f+), marked them with CFSE and expanded them in UM171 culture. LT-HSCs expanded on average 3.5 fold in 7 days, with the following distribution: 0 divisions: 3%; 1: 26%; 2: 47%; 3: 21%; 4: 3%. We performed scRNAseq on LT-HSC pre culture and after 7d separating a highly proliferative (≥2 divisions) and quiescent (0 - 1 division) fraction, allowing us to obtain unprecedented insight into the response of engrafting cells to ex vivo culture and set a framework to dissect self-renewal (HSC expansion), HSC maintenance and loss through differentiation as potential culture outcomes. Our combined functional/transcriptomic approach will define new HSC markers in culture and greatly facilitate side-by-side comparison of different expansion protocols towards rapid clinical translation. Disclosures No relevant conflicts of interest to declare.


2019 ◽  
Author(s):  
J. Javier Díaz-Mejía ◽  
Elaine C. Meng ◽  
Alexander R. Pico ◽  
Sonya A. MacParland ◽  
Troy Ketela ◽  
...  

AbstractIdentification of cell type subpopulations from complex cell mixtures using single-cell RNA-sequencing (scRNA-seq) data includes automated computational steps like data normalization, dimensionality reduction and cell clustering. However, assigning cell type labels to cell clusters is still conducted manually by most researchers, resulting in limited documentation, low reproducibility and uncontrolled vocabularies. Two bottlenecks to automating this task are the scarcity of reference cell type gene expression signatures and that some dedicated methods are available only as web servers with limited cell type gene expression signatures. In this study, we benchmarked four methods (CIBERSORT, GSEA, GSVA, and ORA) for the task of assigning cell type labels to cell clusters from scRNA-seq data. We used scRNA-seq datasets from liver, peripheral blood mononuclear cells and retinal neurons for which reference cell type gene expression signatures were available. Our results show that, in general, all four methods show a high performance in the task as evaluated by Receiver Operating Characteristic curve analysis (average AUC = 0.94, sd = 0.036), whereas Precision-Recall curve analyses show a wide variation depending on the method and dataset (average AUC = 0.53, sd = 0.24). CIBERSORT and GSVA were the top two performers. Additionally, GSVA was the fastest of the four methods and was more robust in cell type gene expression signature subsampling simulations. We provide an extensible framework to evaluate other methods and datasets at https://github.com/jdime/scRNAseq_cell_cluster_labeling.


2021 ◽  
Author(s):  
Yongjin Park ◽  
Liang He ◽  
Jose Davila-Velderrain ◽  
Lei Hou ◽  
Shahin Mohammadi ◽  
...  

AbstractThousands of genetic variants acting in multiple cell types underlie complex disorders, yet most gene expression studies profile only bulk tissues, making it hard to resolve where genetic and non-genetic contributors act. This is particularly important for psychiatric and neurodegenerative disorders that impact multiple brain cell types with highly-distinct gene expression patterns and proportions. To address this challenge, we develop a new framework, SPLITR, that integrates single-nucleus and bulk RNA-seq data, enabling phenotype-aware deconvolution and correcting for systematic discrepancies between bulk and single-cell data. We deconvolved 3,387 post-mortem brain samples across 1,127 individuals and in multiple brain regions. We find that cell proportion varies across brain regions, individuals, disease status, and genotype, including genetic variants in TMEM106B that impact inhibitory neuron fraction and 4,757 cell-type-specific eQTLs. Our results demonstrate the power of jointly analyzing bulk and single-cell RNA-seq to provide insights into cell-type-specific mechanisms for complex brain disorders.


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