scholarly journals Single-Cell RNA Sequencing in Human Retinal Degeneration Reveals Distinct Glial Cell Populations

Cells ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 438 ◽  
Author(s):  
Andrew P. Voigt ◽  
Elaine Binkley ◽  
Miles J. Flamme-Wiese ◽  
Shemin Zeng ◽  
Adam P. DeLuca ◽  
...  

Degenerative diseases affecting retinal photoreceptor cells have numerous etiologies and clinical presentations. We clinically and molecularly studied the retina of a 70-year-old patient with retinal degeneration attributed to autoimmune retinopathy. The patient was followed for 19 years for progressive peripheral visual field loss and pigmentary changes. Single-cell RNA sequencing was performed on foveal and peripheral retina from this patient and four control patients, and cell-specific gene expression differences were identified between healthy and degenerating retina. Distinct populations of glial cells, including astrocytes and Müller cells, were identified in the tissue from the retinal degeneration patient. The glial cell populations demonstrated an expression profile consistent with reactive gliosis. This report provides evidence that glial cells have a distinct transcriptome in the setting of human retinal degeneration and represents a complementary clinical and molecular investigation of a case of progressive retinal disease.

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Erik Johansson ◽  
Hiroo Ueno

AbstractThe advances in oral cancer research and therapies have not improved the prognosis of patients with tongue cancer. The poor treatment response of tongue cancer may be attributed to the presence of heterogeneous tumor cells exhibiting stem cell characteristics. Therefore, there is a need to develop effective molecular-targeted therapies based on the specific gene expression profiles of these cancer stem-like cell populations. In this study, the characteristics of normal and cancerous organoids, which are convenient tools for screening anti-cancer drugs, were analyzed comparatively. As organoids are generally generated by single progenitors, they enable the exclusion of normal cell contamination from the analyses. Single-cell RNA sequencing analysis revealed that p53 signaling activation and negative regulation of cell cycle were enriched characteristics in normal stem-like cells whereas hypoxia-related pathways, such as HIF-1 signaling and glycolysis, were upregulated in cancer stem-like cells. The findings of this study improved our understanding of the common features of heterogeneous cell populations with stem cell properties in tongue cancers, that are different from those of normal stem cell populations; this will enable the development of novel molecular-targeted therapies for tongue cancer.


Author(s):  
Qi Qiu ◽  
Peng Hu ◽  
Kiya W. Govek ◽  
Pablo G. Camara ◽  
Hao Wu

ABSTRACTSingle-cell RNA sequencing offers snapshots of whole transcriptomes but obscures the temporal dynamics of RNA biogenesis and decay. Here we present single-cell new transcript tagging sequencing (scNT-Seq), a method for massively parallel analysis of newly-transcribed and pre-existing RNAs from the same cell. This droplet microfluidics-based method enables high-throughput chemical conversion on barcoded beads, efficiently marking metabolically labeled newly-transcribed RNAs with T-to-C substitutions. By simultaneously measuring new and old transcriptomes, scNT-Seq reveals neuronal subtype-specific gene regulatory networks and time-resolved RNA trajectories in response to brief (minutes) versus sustained (hours) neuronal activation. Integrating scNT-Seq with genetic perturbation reveals that DNA methylcytosine dioxygenases may inhibit stepwise transition from pluripotent embryonic stem cell state to intermediate and totipotent two-cell-embryo-like (2C-like) states by promoting global RNA biogenesis. Furthermore, pulse-chase scNT-Seq enables transcriptome-wide measurements of RNA stability in rare 2C-like cells. Time-resolved single-cell transcriptomic analysis thus opens new lines of inquiry regarding cell-type-specific RNA regulatory mechanisms.


2020 ◽  
Author(s):  
Emmi Helle ◽  
Minna Ampuja ◽  
Alexandra Dainis ◽  
Laura Antola ◽  
Elina Temmes ◽  
...  

AbstractRationaleCell-cell interactions are crucial for the development and function of the organs. Endothelial cells act as essential regulators of tissue growth and regeneration. In the heart, endothelial cells engage in delicate bidirectional communication with cardiomyocytes. The mechanisms and mediators of this crosstalk are still poorly known. Furthermore, endothelial cells in vivo are exposed to blood flow and their phenotype is greatly affected by shear stress.ObjectiveWe aimed to elucidate how cardiomyocytes regulate the development of organotypic phenotype in endothelial cells. In addition, the effects of flow-induced shear stress on endothelial cell phenotype were studied.Methods and resultsHuman induced pluripotent stem cell (hiPSC) -derived cardiomyocytes and endothelial cells were grown either as a monoculture or as a coculture. hiPS-endothelial cells were exposed to flow using the Ibidi-pump system. Single-cell RNA sequencing was performed to define cell populations and to uncover the effects on their transcriptomic phenotypes. The hiPS-cardiomyocyte differentiation resulted in two distinct populations; atrial and ventricular. Coculture had a more pronounced effect on hiPS-endothelial cells compared to hiPS-cardiomyocytes. Coculture increased hiPS-endothelial cell expression of transcripts related to vascular development and maturation, cardiac development, and the expression of cardiac endothelial cell -specific genes. Exposure to flow significantly reprogrammed the hiPS-endothelial cell transcriptome, and surprisingly, promoted the appearance of both venous and arterial clusters.ConclusionsSingle-cell RNA sequencing revealed distinct atrial and ventricular cell populations in hiPS-cardiomyocytes, and arterial and venous-like cell populations in flow exposed hiPS-endothelial cells. hiPS-endothelial cells acquired cardiac endothelial cell identity in coculture. Our study demonstrated that hiPS-cardiomoycytes and hiPS-endothelial cells readily adapt to coculture and flow in a consistent and relevant manner, indicating that the methods used represent improved physiological cell culturing conditions that potentially are more relevant in disease modelling. In addition, novel cardiomyocyte-endothelial cell crosstalk mediators were revealed.


2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Rabah Dabouz ◽  
Colin W. H. Cheng ◽  
Pénélope Abram ◽  
Samy Omri ◽  
Gael Cagnone ◽  
...  

Abstract Background Inflammation and particularly interleukin-1β (IL-1β), a pro-inflammatory cytokine highly secreted by activated immune cells during early AMD pathological events, contribute significantly to retinal neurodegeneration. Here, we identify specific cell types that generate IL-1β and harbor the IL-1 receptor (IL-1R) and pharmacologically validate IL-1β’s contribution to neuro-retinal degeneration using the IL-1R allosteric modulator composed of the amino acid sequence rytvela (as well as the orthosteric antagonist, Kineret) in a model of blue light–induced retinal degeneration. Methods Mice were exposed to blue light for 6 h and sacrificed 3 days later. Mice were intraperitoneally injected with rytvela, Kineret, or vehicle twice daily for 3 days. The inflammatory markers F4/80, NLRP3, caspase-1, and IL-1β were assessed in the retinas. Single-cell RNA sequencing was used to determine the cell-specific expression patterns of retinal Il1b and Il1r1. Macrophage-induced photoreceptor death was assessed ex vivo using retinal explants co-cultured with LPS-activated bone marrow–derived macrophages. Photoreceptor cell death was evaluated by the TUNEL assay. Retinal function was assessed by flash electroretinography. Results Blue light markedly increased the mononuclear phagocyte recruitment and levels of inflammatory markers associated with photoreceptor death. Co-localization of NLRP3, caspase-1, and IL-1β with F4/80+ mononuclear phagocytes was clearly detected in the subretinal space, suggesting that these inflammatory cells are the main source of IL-1β. Single-cell RNA sequencing confirmed the immune-specific expression of Il1b and notably perivascular macrophages in light-challenged mice, while Il1r1 expression was found primarily in astrocytes, bipolar, and vascular cells. Retinal explants co-cultured with LPS/ATP-activated bone marrow–derived macrophages displayed a high number of TUNEL-positive photoreceptors, which was abrogated by rytvela treatment. IL-1R antagonism significantly mitigated the inflammatory response triggered in vivo by blue light exposure, and rytvela was superior to Kineret in preserving photoreceptor density and retinal function. Conclusion These findings substantiate the importance of IL-1β in neuro-retinal degeneration and revealed specific sources of Il1b from perivascular MPs, with its receptor Ilr1 being separately expressed on surrounding neuro-vascular and astroglial cells. They also validate the efficacy of rytvela-induced IL-1R modulation in suppressing detrimental inflammatory responses and preserving photoreceptor density and function in these conditions, reinforcing the rationale for clinical translation.


2018 ◽  
Vol 9 ◽  
Author(s):  
Akira Nguyen ◽  
Weng Hua Khoo ◽  
Imogen Moran ◽  
Peter I. Croucher ◽  
Tri Giang Phan

2021 ◽  
Vol 4 (6) ◽  
pp. e202000935
Author(s):  
Samantha B Kemp ◽  
Nina G Steele ◽  
Eileen S Carpenter ◽  
Katelyn L Donahue ◽  
Grace G Bushnell ◽  
...  

Pancreatic ductal adenocarcinoma (PDA) is accompanied by reprogramming of the local microenvironment, but changes at distal sites are poorly understood. We implanted biomaterial scaffolds, which act as an artificial premetastatic niche, into immunocompetent tumor-bearing and control mice, and identified a unique tumor-specific gene expression signature that includes high expression of C1qa, C1qb, Trem2, and Chil3. Single-cell RNA sequencing mapped these genes to two distinct macrophage populations in the scaffolds, one marked by elevated C1qa, C1qb, and Trem2, the other with high Chil3, Ly6c2 and Plac8. In mice, expression of these genes in the corresponding populations was elevated in tumor-associated macrophages compared with macrophages in the normal pancreas. We then analyzed single-cell RNA sequencing from patient samples, and determined expression of C1QA, C1QB, and TREM2 is elevated in human macrophages in primary tumors and liver metastases. Single-cell sequencing analysis of patient blood revealed a substantial enrichment of the same gene signature in monocytes. Taken together, our study identifies two distinct tumor-associated macrophage and monocyte populations that reflects systemic immune changes in pancreatic ductal adenocarcinoma patients.


2017 ◽  
Author(s):  
Belinda Phipson ◽  
Luke Zappia ◽  
Alicia Oshlack

AbstractSingle cell RNA sequencing (scRNA-seq) has rapidly gained popularity for profiling transcriptomes of hundreds to thousands of single cells. This technology has led to the discovery of novel cell types and revealed insights into the development of complex tissues. However, many technical challenges need to be overcome during data generation. Due to minute amounts of starting material, samples undergo extensive amplification, increasing technical variability. A solution for mitigating amplification biases is to include Unique Molecular Identifiers (UMIs), which tag individual molecules. Transcript abundances are then estimated from the number of unique UMIs aligning to a specific gene and PCR duplicates resulting in copies of the UMI are not included in expression estimates. Here we investigate the effect of gene length bias in scRNA-Seq across a variety of datasets differing in terms of capture technology, library preparation, cell types and species. We find that scRNA-seq datasets that have been sequenced using a full-length transcript protocol exhibit gene length bias akin to bulk RNA-seq data. Specifically, shorter genes tend to have lower counts and a higher rate of dropout. In contrast, protocols that include UMIs do not exhibit gene length bias, and have a mostly uniform rate of dropout across genes of varying length. Across four different scRNA-Seq datasets profiling mouse embryonic stem cells (mESCs), we found the subset of genes that are only detected in the UMI datasets tended to be shorter, while the subset of genes detected only in the full-length datasets tended to be longer. We briefly discuss the role of these genes in the context of differential expression testing and GO analysis. In addition, despite clear differences between UMI and full-length transcript data, we illustrate that full-length and UMI data can be combined to reveal underlying biology influencing expression of mESCs.


2021 ◽  
Vol 12 ◽  
Author(s):  
Melanie A. Brennan ◽  
Adam Z. Rosenthal

Clonal bacterial populations exhibit various forms of heterogeneity, including co-occurrence of cells with different morphological traits, biochemical properties, and gene expression profiles. This heterogeneity is prevalent in a variety of environments. For example, the productivity of large-scale industrial fermentations and virulence of infectious diseases are shaped by cell population heterogeneity and have a direct impact on human life. Due to the need and importance to better understand this heterogeneity, multiple methods of examining single-cell heterogeneity have been developed. Traditionally, fluorescent reporters or probes are used to examine a specific gene of interest, providing a useful but inherently biased approach. In contrast, single-cell RNA sequencing (scRNA-seq) is an agnostic approach to examine heterogeneity and has been successfully applied to eukaryotic cells. Unfortunately, current extensively utilized methods of eukaryotic scRNA-seq present difficulties when applied to bacteria. Specifically, bacteria have a cell wall which makes eukaryotic lysis methods incompatible, bacterial mRNA has a shorter half-life and lower copy numbers, and isolating an individual bacterial species from a mixed community is difficult. Recent work has demonstrated that these technical hurdles can be overcome, providing valuable insight into factors influencing microbial heterogeneity. This perspective describes the emerging microbial scRNA-seq toolkit. We outline the benefit of these new tools in elucidating numerous scientific questions in microbiological studies and offer insight about the possible rules that govern the segregation of traits in individual microbial cells.


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