scholarly journals A New Gene Set Identifies Senescent Cells and Predicts Senescence-Associated Pathways Across Tissues

2021 ◽  
Author(s):  
Dominik Saul ◽  
Robyn Laura Kosinsky ◽  
Elizabeth J Atkinson ◽  
Madison L. Doolittle ◽  
Xu Zhang ◽  
...  
Keyword(s):  
Single Cell ◽  
Mesenchymal Cells ◽  
Senescent Cell ◽  
Single Cell Level ◽  
Cell Level ◽  
Gene Set ◽  
Age Related ◽  
Cell Clearance ◽  
Bone Biopsies

AbstractAlthough cellular senescence is increasingly recognized as driving multiple age-related co-morbidities through the senescence-associated secretory phenotype (SASP), in vivo senescent cell identification, particularly in bulk or single cell RNA-sequencing (scRNA-seq) data remains challenging. Here, we generated a novel gene set (SenMayo) and first validated its enrichment in bone biopsies from two aged human cohorts. SenMayo also identified senescent cells in aged murine brain tissue, demonstrating applicability across tissues and species. For direct validation, we demonstrated significant reductions in SenMayo in bone following genetic clearance of senescent cells in mice, with similar findings in adipose tissue from humans in a pilot study of pharmacological senescent cell clearance. In direct comparisons, SenMayo outperformed all six existing senescence/SASP gene sets in identifying senescent cells across tissues and in demonstrating responses to senescent cell clearance. We next used SenMayo to identify senescent hematopoietic or mesenchymal cells at the single cell level from publicly available human and murine bone marrow/bone scRNA-seq data and identified monocytic and osteolineage cells, respectively, as showing the highest levels of senescence/SASP genes. Using pseudotime and cellular communication patterns, we found senescent hematopoietic and mesenchymal cells communicated with other cells through common pathways, including the Macrophage Migration Inhibitory Factor (MIF) pathway, which has been implicated not only in inflammation but also in immune evasion, an important property of senescent cells. Thus, SenMayo identifies senescent cells across tissues and species with high fidelity. Moreover, using this senescence panel, we were able to characterize senescent cells at the single cell level and identify key intercellular signaling pathways associated with these cells, which may be particularly useful for evolving efforts to map senescent cells (e.g., SenNet). In addition, SenMayo represents a potentially clinically applicable panel for monitoring senescent cell burden with aging and other conditions as well as in studies of senolytic drugs.

scholarly journals A New Gene Set Identifies Senescent Cells and Predicts Senescence-Associated Pathways Across Tissues

2021 ◽  
Author(s):  
Sundeep Khosla ◽  
Dominik Saul ◽  
Robyn Laura Kosinsky ◽  
Elizabeth Atkinson ◽  
Madison Doolittle ◽  
...  
Keyword(s):  
Single Cell ◽  
Mesenchymal Cells ◽  
Senescent Cell ◽  
Single Cell Level ◽  
Cell Level ◽  
Gene Set ◽  
Age Related ◽  
Cell Clearance ◽  
Bone Biopsies

Abstract Although cellular senescence is increasingly recognized as driving multiple age-related co-morbidities through the senescence-associated secretory phenotype (SASP), in vivo senescent cell identification, particularly in bulk or single cell RNA-sequencing (scRNA-seq) data remains challenging. Here, we generated a novel gene set (SenMayo) and first validated its enrichment in bone biopsies from two aged human cohorts. SenMayo also identified senescent cells in aged murine brain tissue, demonstrating applicability across tissues and species. For direct validation, we demonstrated significant reductions in SenMayo in bone following genetic clearance of senescent cells in mice, with similar findings in adipose tissue from humans in a pilot study of pharmacological senescent cell clearance. In direct comparisons, SenMayo outperformed all six existing senescence/SASP gene sets in identifying senescent cells across tissues and in demonstrating responses to senescent cell clearance. We next used SenMayo to identify senescent hematopoietic or mesenchymal cells at the single cell level from publicly available human and murine bone marrow/bone scRNA-seq data and identified monocytic and osteolineage cells, respectively, as showing the highest levels of senescence/SASP genes. Using pseudotime and cellular communication patterns, we found senescent hematopoietic and mesenchymal cells communicated with other cells through common pathways, including the Macrophage Migration Inhibitory Factor (MIF) pathway, which has been implicated not only in inflammation but also in immune evasion, an important property of senescent cells. Thus, SenMayo identifies senescent cells across tissues and species with high fidelity. Moreover, using this senescence panel, we were able to characterize senescent cells at the single cell level and identify key intercellular signaling pathways associated with these cells, which may be particularly useful for evolving efforts to map senescent cells (e.g., SenNet). In addition, SenMayo represents a potentially clinically applicable panel for monitoring senescent cell burden with aging and other conditions as well as in studies of senolytic drugs.

scholarly journals Quantification of Unintegrated HIV-1 DNA at the Single Cell Level In Vivo

PLoS ONE ◽  
2012 ◽  
Vol 7 (5) ◽  
pp. e36246 ◽  
Author(s):  
Rodolphe Suspène ◽  
Andreas Meyerhans
Keyword(s):  
Single Cell ◽  
Single Cell Level ◽  
Cell Level ◽  
Hiv 1

scholarly journals The iSplit GFP assay detects intracellular recombinant proteins in Bacillus subtilis

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Patrick Lenz ◽  
Fabienne Hilgers ◽  
Alina Burmeister ◽  
Leonie Zimmermann ◽  
Kristina Volkenborn ◽  
...  
Keyword(s):  
Bacillus Subtilis ◽  
Recombinant Protein ◽  
Single Cell ◽  
Recombinant Protein Production ◽  
Protein Production ◽  
Online Monitoring ◽  
Protein Detection ◽  
Single Cell Level ◽  
Cell Level

Abstract Background Bacillus subtilis is one of the most important microorganisms for recombinant protein production. It possesses the GRAS (generally recognized as safe) status and a potent protein secretion capacity. Secretory protein production greatly facilitates downstream processing and thus significantly reduces costs. However, not all heterologous proteins are secreted and intracellular production poses difficulties for quantification. To tackle this problem, we have established a so-called intracellular split GFP (iSplit GFP) assay in B. subtilis as a tool for the in vivo protein detection during expression in batch cultures and at a single-cell level. For the iSplit GFP assay, the eleventh β-sheet of sfGFP is fused to a target protein and can complement a detector protein consisting of the respective truncated sfGFP (GFP1-10) to form fluorescent holo-GFP. Results As proof of concept, the GFP11-tag was fused C-terminally to the E. coli β-glucuronidase GUS, resulting in fusion protein GUS11. Variable GUS and GUS11 production levels in B. subtilis were achieved by varying the ribosome binding site via spacers of increasing lengths (4–12 nucleotides) for the GUS-encoding gene. Differences in intracellular enzyme accumulation were determined by measuring the GUS11 enzymatic activity and subsequently by adding the detector protein to respective cell extracts. Moreover, the detector protein was co-produced with the GUS11 using a two-plasmid system, which enabled the in vivo detection and online monitoring of glucuronidase production. Using this system in combination with flow cytometry and microfluidics, we were able to monitor protein production at a single-cell level thus yielding information about intracellular protein distribution and culture heterogeneity. Conclusion Our results demonstrate that the iSplit GFP assay is suitable for the detection, quantification and online monitoring of recombinant protein production in B. subtilis during cultivation as well as for analyzing production heterogeneity and intracellular localization at a single-cell level. Graphic abstract

scholarly journals Single-Cell Gene Expression Analysis and Evaluation of the Therapeutic Function of Murine Adipose-Derived Stromal Cells (ASCs) from the Subcutaneous and Visceral Compartment

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Dominik Pförringer ◽  
Matthias M. Aitzetmüller ◽  
Elizabeth A. Brett ◽  
Khosrow S. Houschyar ◽  
Richard Schäfer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Wound Healing ◽  
Single Cell ◽  
Stromal Cells ◽  
Single Cell Level ◽  
Cell Level ◽  
Adipose Derived Stromal Cells ◽  
Wound Healing Model ◽  
Healing Model

Introduction. Adipose-derived stromal cells (ASCs) are a promising resource for wound healing and tissue regeneration because of their multipotent properties and cytokine secretion. ASCs are typically isolated from the subcutaneous fat compartment, but can also be obtained from visceral adipose tissue. The data on their equivalence diverges. The present study analyzes the cell-specific gene expression profiles and functional differences of ASCs derived from the subcutaneous (S-ASCs) and the visceral (V-ASCs) compartment. Material and Methods. Subcutaneous and visceral ASCs were obtained from mouse inguinal fat and omentum. The transcriptional profiles of the ASCs were compared on single-cell level. S-ASCs and V-ASCs were then compared in a murine wound healing model to evaluate their regenerative functionality. Results. On a single-cell level, S-ASCs and V-ASCs displayed distinct transcriptional profiles. Specifically, significant differences were detected in genes associated with neoangiogenesis and tissue remodeling (for example, Ccl2, Hif1α, Fgf7, and Igf). In addition, a different subpopulation ecology could be identified employing a cluster model. Nevertheless, both S-ASCs and V-ASCs induced accelerated healing rates and neoangiogenesis in a mouse wound healing model. Conclusion. With similar therapeutic potential in vivo, the significantly different gene expression patterns of ASCs from the subcutaneous and visceral compartments suggest different signaling pathways underlying their efficacy. This study clearly demonstrates that review of transcriptional results in vivo is advisable to confirm the tentative effect of cell therapies.

scholarly journals Dynamic Imaging of Marrow-Resident Granulocytes Interacting with Human Mesenchymal Stem Cells upon Systemic Lipopolysaccharide Challenge

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Jay T. Myers ◽  
Deborah S. Barkauskas ◽  
Alex Y. Huang
Keyword(s):  
Stem Cells ◽  
Mesenchymal Stem Cells ◽  
Single Cell ◽  
Human Mesenchymal Stem Cells ◽  
Dynamic Imaging ◽  
Whole Body ◽  
Whole Body Imaging ◽  
Single Cell Level ◽  
Cell Level

Human mesenchymal stem cells (hMSCs) have gained intense research interest due to their immune-modulatory, tissue differentiating, and homing properties to sites of inflammation. Despite evidence demonstrating the biodistribution of infused hMSCs in target organs using static fluorescence imaging or whole-body imaging techniques, surprisingly little is known about how hMSCs behave dynamically within host tissues on a single-cell levelin vivo. Here, we infused fluorescently labeled clinical-grade hMSCs into immune-competent mice in which neutrophils and monocytes express a second fluorescent marker under the lysozyme M (LysM) promoter. Using intravital two-photon microscopy (TPM), we were able for the first time to capture dynamic interactions between hMSCs and LysM+granulocytes in the calvarium bone marrow of recipient mice during systemic LPS challenge in real time. Interestingly, many of the infused hMSCs remained intact despite repeated cellular contacts with host neutrophils. However, we were able to observe the destruction and subsequent phagocytosis of some hMSCs by surrounding granulocytes. Thus, our imaging platform provides opportunities to gain insight into the biology and therapeutic mechanisms of hMSCsin vivoat a single-cell level within live hosts.

In vivo MRI of cancer cell fate at the single-cell level in a mouse model of breast cancer metastasis to the brain

2006 ◽  
Vol 56 (5) ◽  
pp. 1001-1010 ◽  
Author(s):  
Chris Heyn ◽  
John A. Ronald ◽  
Soha S. Ramadan ◽  
Jonatan A. Snir ◽  
Andrea M. Barry ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Mouse Model ◽  
Single Cell ◽  
Cell Fate ◽  
Cancer Metastasis ◽  
Breast Cancer Metastasis ◽  
Single Cell Level ◽  
Cell Level ◽  
The Brain
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