scholarly journals Vero Cells Gain Renal Tubule Markers in Low-calcium and Magnesium Chemically Defined Media

2021 ◽  
Author(s):  
Megan Logan ◽  
Karsten Rinas ◽  
Brendan McConkey ◽  
Marc G. Aucoin
Keyword(s):  
Cell Types ◽  
Vero Cells ◽  
Renal Tubules ◽  
Rna Seq ◽  
Media Formulation ◽  
Low Calcium ◽  
Calcium And Magnesium ◽  
Free Media ◽  
Animal Component ◽  
Similar Gene

Abstract In this study, a chemically defined, animal component-free media was developed to promote Vero growth in suspension. Key media compounds were screened using Plackett-Burman styled experiments to create a media formulation to support suspension growth. Vero cells remained viable in suspension, but their growth rate was extremely low, conversely, other cell types such as CHO-K1, MDCK and HEK293T were able to grow in single cell suspension in the same media. To investigate the slow growth of Vero cells, RNA-seq analysis was conducted. Vero cells were cultured in three different conditions: adherently in serum-containing medium, adherently in in-house medium, and in suspension in low calcium and magnesium in-house medium. This study illustrates that adherent cells maintain similar gene expression, while the suspension phenotype tends to overexpress genes related to renal tubules.

scholarly journals Vero cells gain renal tubule markers in low-calcium and magnesium chemically defined media

2021 ◽  
Author(s):  
Megan Logan ◽  
Karsten Rinas ◽  
Brendan McConkey ◽  
Marc Aucoin
Keyword(s):  
Cell Types ◽  
Vero Cells ◽  
Renal Tubules ◽  
Rna Seq ◽  
Media Formulation ◽  
Low Calcium ◽  
Calcium And Magnesium ◽  
Free Media ◽  
Animal Component ◽  
Similar Gene

In this study, a chemically defined, animal component-free media was developed to promote Vero growth in suspension. Key media compounds were screened using Plackett-Burman styled experiments to create a media formulation to support suspension growth. Vero cells remained viable in suspension, but their growth rate was extremely low, conversely, other cell types such as CHO-K1, MDCK and HEK293T were able to grow in single cell suspension in the same media. To investigate the slow growth of Vero cells, RNA-Seq analysis was conducted. Vero cells were cultured in three different conditions: adherently in serum-containing medium, adherently in in-house medium, and in suspension in low calcium and magnesium in-house medium. This study illustrates that adherent cells maintain similar gene expression, while the suspension phenotype tends to overexpress genes related to renal tubules.

scholarly journals Transcriptional and morphological profiling of parvalbumin interneuron subpopulations in the mouse hippocampus

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Lin Que ◽  
David Lukacsovich ◽  
Wenshu Luo ◽  
Csaba Földy
Keyword(s):  
Large Scale ◽  
Cell Types ◽  
Rna Seq ◽  
Neuronal Identity ◽  
Parvalbumin Interneurons ◽  
Different Types ◽  
Parvalbumin Interneuron ◽  
Cam Profile ◽  
Developmental Domains

AbstractThe diversity reflected by >100 different neural cell types fundamentally contributes to brain function and a central idea is that neuronal identity can be inferred from genetic information. Recent large-scale transcriptomic assays seem to confirm this hypothesis, but a lack of morphological information has limited the identification of several known cell types. In this study, we used single-cell RNA-seq in morphologically identified parvalbumin interneurons (PV-INs), and studied their transcriptomic states in the morphological, physiological, and developmental domains. Overall, we find high transcriptomic similarity among PV-INs, with few genes showing divergent expression between morphologically different types. Furthermore, PV-INs show a uniform synaptic cell adhesion molecule (CAM) profile, suggesting that CAM expression in mature PV cells does not reflect wiring specificity after development. Together, our results suggest that while PV-INs differ in anatomy and in vivo activity, their continuous transcriptomic and homogenous biophysical landscapes are not predictive of these distinct identities.

scholarly journals treeclimbR pinpoints the data-dependent resolution of hierarchical hypotheses

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ruizhu Huang ◽  
Charlotte Soneson ◽  
Pierre-Luc Germain ◽  
Thomas S.B. Schmidt ◽  
Christian Von Mering ◽  
...  
Keyword(s):  
Single Cell ◽  
Synthetic Data ◽  
Cell Types ◽  
Data Driven ◽  
Rna Seq ◽  
Hierarchical Trees

AbstracttreeclimbR is for analyzing hierarchical trees of entities, such as phylogenies or cell types, at different resolutions. It proposes multiple candidates that capture the latent signal and pinpoints branches or leaves that contain features of interest, in a data-driven way. It outperforms currently available methods on synthetic data, and we highlight the approach on various applications, including microbiome and microRNA surveys as well as single-cell cytometry and RNA-seq datasets. With the emergence of various multi-resolution genomic datasets, treeclimbR provides a thorough inspection on entities across resolutions and gives additional flexibility to uncover biological associations.

scholarly journals Transcriptomic Changes of Murine Visceral Fat Exposed to Intermittent Hypoxia at Single Cell Resolution

2020 ◽  
Vol 22 (1) ◽  
pp. 261
Author(s):  
Abdelnaby Khalyfa ◽  
Wesley Warren ◽  
Jorge Andrade ◽  
Christopher A. Bottoms ◽  
Edward S. Rice ◽  
...  
Keyword(s):  
Intermittent Hypoxia ◽  
Cell Types ◽  
Cellular Level ◽  
Cellular Heterogeneity ◽  
Transcriptional Networks ◽  
Metabolic Dysfunction ◽  
Rna Seq ◽  
Obstructive Sleep ◽  
Differential Expressed Gene ◽  
Key Aspects

Intermittent hypoxia (IH) is a hallmark of obstructive sleep apnea (OSA) and induces metabolic dysfunction manifesting as inflammation, increased lipolysis and insulin resistance in visceral white adipose tissues (vWAT). However, the cell types and their corresponding transcriptional pathways underlying these functional perturbations are unknown. Here, we applied single nucleus RNA sequencing (snRNA-seq) coupled with aggregate RNA-seq methods to evaluate the cellular heterogeneity in vWAT following IH exposures mimicking OSA. C57BL/6 male mice were exposed to IH and room air (RA) for 6 weeks, and nuclei from vWAT were isolated and processed for snRNA-seq followed by differential expressed gene (DEGs) analyses by cell type, along with gene ontology and canonical pathways enrichment tests of significance. IH induced significant transcriptional changes compared to RA across 14 different cell types identified in vWAT. We identified cell-specific signature markers, transcriptional networks, metabolic signaling pathways, and cellular subpopulation enrichment in vWAT. Globally, we also identify 298 common regulated genes across multiple cellular types that are associated with metabolic pathways. Deconvolution of cell types in vWAT using global RNA-seq revealed that distinct adipocytes appear to be differentially implicated in key aspects of metabolic dysfunction. Thus, the heterogeneity of vWAT and its response to IH at the cellular level provides important insights into the metabolic morbidity of OSA and may possibly translate into therapeutic targets.

Development of an In Situ Detachment Protocol of Vero Cells Grown on Cytodex1 Microcarriers Under Animal Component-Free Conditions in Stirred Bioreactor

2013 ◽  
Vol 170 (7) ◽  
pp. 1724-1737 ◽  
Author(s):  
Samia Rourou ◽  
Nesrine Riahi ◽  
Samy Majoul ◽  
Khaled Trabelsi ◽  
Héla Kallel
Keyword(s):  
Vero Cells ◽  
Stirred Bioreactor ◽  
Animal Component

scholarly journals Annotating cell types in human single-cell RNA-seq data with CellO

2021 ◽  
Vol 2 (3) ◽  
pp. 100705
Author(s):  
Matthew N. Bernstein ◽  
Colin N. Dewey
Keyword(s):  
Single Cell ◽  
Cell Types ◽  
Rna Seq

scholarly journals Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Tracy M. Yamawaki ◽  
Daniel R. Lu ◽  
Daniel C. Ellwanger ◽  
Dev Bhatt ◽  
Paolo Manzanillo ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Immune Cell ◽  
Cell Types ◽  
Data Interpretation ◽  
Detection Sensitivity ◽  
Rna Seq ◽  
Cell Recovery

Abstract Background Elucidation of immune populations with single-cell RNA-seq has greatly benefited the field of immunology by deepening the characterization of immune heterogeneity and leading to the discovery of new subtypes. However, single-cell methods inherently suffer from limitations in the recovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropout events. This issue is often compounded by limited sample availability and limited prior knowledge of heterogeneity, which can confound data interpretation. Results Here, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluated methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. We observed higher mRNA detection sensitivity with the 10x Genomics 5′ v1 and 3′ v3 methods. We demonstrate that these methods have fewer dropout events, which facilitates the identification of differentially-expressed genes and improves the concordance of single-cell profiles to immune bulk RNA-seq signatures. Conclusion Overall, our characterization of immune cell mixtures provides useful metrics, which can guide selection of a high-throughput single-cell RNA-seq method for profiling more complex immune-cell heterogeneity usually found in vivo.

scholarly journals Plasma IL-6 levels following corticosteroid therapy as an indicator of ICU length of stay in critically ill COVID-19 patients

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Samir Awasthi ◽  
Tyler Wagner ◽  
A. J. Venkatakrishnan ◽  
Arjun Puranik ◽  
Matthew Hurchik ◽  
...  
Keyword(s):  
Distress Syndrome ◽  
Cell Types ◽  
Specific Cell ◽  
Cytokine Release ◽  
Cytokine Release Syndrome ◽  
Rna Seq ◽  
Future Studies ◽  
Icu Length Of Stay ◽  
Potential Association ◽  
Clinical Trial Results

AbstractIntensive care unit (ICU) admissions and mortality in severe COVID-19 patients are driven by “cytokine storms” and acute respiratory distress syndrome (ARDS). Interim clinical trial results suggest that the corticosteroid dexamethasone displays better 28-day survival in severe COVID-19 patients requiring ventilation or oxygen. In this study, 10 out of 16 patients (62.5%) that had an average plasma IL-6 value over 10 pg/mL post administration of corticosteroids also had worse outcomes (i.e., ICU stay >15 days or death), compared to 8 out of 41 patients (19.5%) who did not receive corticosteroids (p-value = 0.0024). Given this potential association between post-corticosteroid IL-6 levels and COVID-19 severity, we hypothesized that the glucocorticoid receptor (GR or NR3C1) may be coupled to IL-6 expression in specific cell types that govern cytokine release syndrome (CRS). Examining single-cell RNA-seq data from BALF of severe COVID-19 patients and nearly 2 million cells from a pan-tissue scan shows that alveolar macrophages, smooth muscle cells, and endothelial cells co-express NR3C1 and IL-6, motivating future studies on the links between the regulation of NR3C1 function and IL-6 levels.

scholarly journals RNA-Seq Data-Mining Allows the Discovery of Two Long Non-Coding RNA Biomarkers of Viral Infection in Humans

2020 ◽  
Vol 21 (8) ◽  
pp. 2748 ◽  
Author(s):  
Ruth Barral-Arca ◽  
Alberto Gómez-Carballa ◽  
Miriam Cebey-López ◽  
María José Currás-Tuala ◽  
Sara Pischedda ◽  
...  
Keyword(s):  
Gene Expression ◽  
Viral Infections ◽  
Umbilical Vein ◽  
Cell Types ◽  
Dermal Fibroblasts ◽  
Learning Approaches ◽  
Rna Seq ◽  
Wide Range ◽  
Healthy Control ◽  
Umbilical Vein Endothelial Cells

There is a growing interest in unraveling gene expression mechanisms leading to viral host invasion and infection progression. Current findings reveal that long non-coding RNAs (lncRNAs) are implicated in the regulation of the immune system by influencing gene expression through a wide range of mechanisms. By mining whole-transcriptome shotgun sequencing (RNA-seq) data using machine learning approaches, we detected two lncRNAs (ENSG00000254680 and ENSG00000273149) that are downregulated in a wide range of viral infections and different cell types, including blood monocluclear cells, umbilical vein endothelial cells, and dermal fibroblasts. The efficiency of these two lncRNAs was positively validated in different viral phenotypic scenarios. These two lncRNAs showed a strong downregulation in virus-infected patients when compared to healthy control transcriptomes, indicating that these biomarkers are promising targets for infection diagnosis. To the best of our knowledge, this is the very first study using host lncRNAs biomarkers for the diagnosis of human viral infections.

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