scholarly journals Single-cell RNA sequencing analysis reveals alginate oligosaccharides preventing chemotherapy-induced mucositis

2020 ◽  
Vol 13 (3) ◽  
pp. 437-448 ◽  
Author(s):  
Yong Zhao ◽  
Yanni Feng ◽  
Ming Liu ◽  
Liang Chen ◽  
Qingshi Meng ◽  
...  
Keyword(s):  
Small Intestine ◽  
Gastrointestinal Tract ◽  
Single Cell ◽  
Rna Sequencing ◽  
Functional Enrichment ◽  
Sequencing Analysis ◽  
Intestinal Function ◽  
Alginate Oligosaccharides ◽  
Single Cell Rna Sequencing ◽  
Small Intestinal

AbstractWorldwide the incidence of cancer has been continuing increasing. Mucositis of the gastrointestinal tract is a common side effect in patients under chemotherapy. Anticancer drug busulfan, used for treating chronic myeloid leukemia especially in pediatric patients, causes mucositis of the gastrointestinal tract. Alginate oligosaccharides (AOS) are natural products with attractive pharmaceutical potentials. We aimed to investigate, at the single-cell level, AOS preventing small intestine mucositis induced by busulfan. We found that busulfan disturbed the endoplasmic reticulum and mitochondria of cells in the small intestine, damaged cell membranes especially cell junctions, and disrupted microvilli; all of which were rescued by AOS. Single-cell RNA sequencing analysis and functional enrichment analysis showed that AOS could recover small intestinal function. Deep analysis found that AOS improved the expression of transcriptional factors which explained AOS regulating gene expression to improve small intestine function. Further investigation in IPEC-J2 cells found that AOS acts its function through mannose receptor signaling pathway. Moreover, the improved blood metabolome confirmed small intestinal function was recovered by AOS. As a natural product with many advantages, AOS could be developed to assist in the recovery of intestinal functions in patients undergoing anticancer chemotherapy or other treatments.

scholarly journals Relative Abundance of SARS-CoV-2 Entry Genes in the Enterocytes of the Lower Gastrointestinal Tract

Genes ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 645 ◽  
Author(s):  
Jaewon J. Lee ◽  
Scott Kopetz ◽  
Eduardo Vilar ◽  
John Paul Shen ◽  
Ken Chen ◽  
...  
Keyword(s):  
Small Intestine ◽  
Gastrointestinal Tract ◽  
Severe Acute Respiratory Syndrome ◽  
Single Cell ◽  
Rna Sequencing ◽  
Relative Abundance ◽  
Lower Gastrointestinal Tract ◽  
Gi Tract ◽  
Single Cell Rna Sequencing

There is increasing evidence of gastrointestinal (GI) infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We surveyed the co-expression of SARS-CoV-2 entry genes ACE2 and TMPRSS2 throughout the GI tract to assess potential sites of infection. Publicly available and in-house single-cell RNA-sequencing datasets from the GI tract were queried. Enterocytes from the small intestine and colonocytes showed the highest proportions of cells co-expressing ACE2 and TMPRSS2. Therefore, the lower GI tract represents the most likely site of SARS-CoV-2 entry leading to GI infection.

scholarly journals Single-cell RNA sequencing analysis of SARS-CoV-2 conventional and moonlighting receptors in human organoids

2020 ◽  
Author(s):  
Rajasekaran Mahalingam ◽  
Prakash Dharmalingam ◽  
Abirami Santhanam ◽  
Gangarao Davuluri ◽  
Harry Karmouty Quintana ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Sequencing Analysis ◽  
Single Cell Rna Sequencing

scholarly journals Single-Cell RNA Sequencing Analysis of the Immunometabolic Rewiring and Immunopathogenesis of Coronavirus Disease 2019

2021 ◽  
Vol 12 ◽  
Author(s):  
Furong Qi ◽  
Wenbo Zhang ◽  
Jialu Huang ◽  
Lili Fu ◽  
Jinfang Zhao
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Mononuclear Cells ◽  
Plasma Cells ◽  
Severe Disease ◽  
Sequencing Analysis ◽  
Sequencing Data ◽  
Metabolic Remodeling ◽  
Single Cell Rna Sequencing ◽  
Antibody Secretion

Although immune dysfunction is a key feature of coronavirus disease 2019 (COVID-19), the metabolism-related mechanisms remain elusive. Here, by reanalyzing single-cell RNA sequencing data, we delineated metabolic remodeling in peripheral blood mononuclear cells (PBMCs) to elucidate the metabolic mechanisms that may lead to the progression of severe COVID-19. After scoring the metabolism-related biological processes and signaling pathways, we found that mono-CD14+ cells expressed higher levels of glycolysis-related genes (PKM, LDHA and PKM) and PPP-related genes (PGD and TKT) in severe patients than in mild patients. These genes may contribute to the hyperinflammation in mono-CD14+ cells of patients with severe COVID-19. The mono-CD16+ cell population in COVID-19 patients showed reduced transcription levels of genes related to lysine degradation (NSD1, KMT2E, and SETD2) and elevated transcription levels of genes involved in OXPHOS (ATP6V1B2, ATP5A1, ATP5E, and ATP5B), which may inhibit M2-like polarization. Plasma cells also expressed higher levels of the OXPHOS gene ATP13A3 in COVID-19 patients, which was positively associated with antibody secretion and survival of PCs. Moreover, enhanced glycolysis or OXPHOS was positively associated with the differentiation of memory B cells into plasmablasts or plasma cells. This study comprehensively investigated the metabolic features of peripheral immune cells and revealed that metabolic changes exacerbated inflammation in monocytes and promoted antibody secretion and cell survival in PCs in COVID-19 patients, especially those with severe disease.

scholarly journals Single‐cell RNA sequencing analysis of SARS‐CoV‐2 entry receptors in human organoids

2020 ◽  
Author(s):  
Rajasekaran Mahalingam ◽  
Prakash Dharmalingam ◽  
Abirami Santhanam ◽  
Sivareddy Kotla ◽  
Gangarao Davuluri ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Sequencing Analysis ◽  
Single Cell Rna Sequencing

scholarly journals A single-cell RNA-sequencing training and analysis suite using the Galaxy framework

GigaScience ◽  
2020 ◽  
Vol 9 (10) ◽  
Author(s):  
Mehmet Tekman ◽  
Bérénice Batut ◽  
Alexander Ostrovsky ◽  
Christophe Antoniewski ◽  
Dave Clements ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cell Biology ◽  
High Performance ◽  
Learning Experience ◽  
Sequencing Analysis ◽  
Teaching Resources ◽  
Single Cell Rna Sequencing ◽  
The Galaxy ◽  
Downstream Analysis

Abstract Background The vast ecosystem of single-cell RNA-sequencing tools has until recently been plagued by an excess of diverging analysis strategies, inconsistent file formats, and compatibility issues between different software suites. The uptake of 10x Genomics datasets has begun to calm this diversity, and the bioinformatics community leans once more towards the large computing requirements and the statistically driven methods needed to process and understand these ever-growing datasets. Results Here we outline several Galaxy workflows and learning resources for single-cell RNA-sequencing, with the aim of providing a comprehensive analysis environment paired with a thorough user learning experience that bridges the knowledge gap between the computational methods and the underlying cell biology. The Galaxy reproducible bioinformatics framework provides tools, workflows, and trainings that not only enable users to perform 1-click 10x preprocessing but also empower them to demultiplex raw sequencing from custom tagged and full-length sequencing protocols. The downstream analysis supports a range of high-quality interoperable suites separated into common stages of analysis: inspection, filtering, normalization, confounder removal, and clustering. The teaching resources cover concepts from computer science to cell biology. Access to all resources is provided at the singlecell.usegalaxy.eu portal. Conclusions The reproducible and training-oriented Galaxy framework provides a sustainable high-performance computing environment for users to run flexible analyses on both 10x and alternative platforms. The tutorials from the Galaxy Training Network along with the frequent training workshops hosted by the Galaxy community provide a means for users to learn, publish, and teach single-cell RNA-sequencing analysis.

scholarly journals Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Noa Bossel Ben-Moshe ◽  
Shelly Hen-Avivi ◽  
Natalia Levitin ◽  
Dror Yehezkel ◽  
Marije Oosting ◽  
...  
Keyword(s):  
Bacterial Infection ◽  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cells ◽  
Sequencing Analysis ◽  
Single Cell Rna Sequencing ◽  
Human Immune
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