Dual reporter genes enabling cell tracing with viable and reliable selection of various cell types

Although several modes of reprogramming have been reported in different cell types during iPSC induction, the molecular mechanism regarding the selection of different modes of action is still mostly unknown. The present study examined the molecular events that participate in the selection of such processes at the onset of somatic reprogramming. The activity of STAT3 versus that of Erk1/2 reversibly determines the reprogramming mode entered; a lower activity ratio favors the deterministic process and vice versa. Additionally, extraneous E-cadherin facilitates the early events of somatic reprogramming, potentially by stabilizing the LIF/gp130 and EGFR/ErbB2 complexes to promote entry into the deterministic process. Our current findings demonstrated that manipulating the pSTAT3/pErk1/2 activity ratio in the surrounding milieu can drive different modes of action toward either the deterministic or the stochastic process in the context of OSKM-mediated somatic reprogramming.

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The Notch pathway helps to pattern the tips of the Drosophila tracheal branches by selecting cell fates

Development ◽

10.1242/dev.126.11.2355 ◽

1999 ◽

Vol 126 (11) ◽

pp. 2355-2364 ◽

Cited By ~ 9

Author(s):

M. Llimargas

Keyword(s):

Notch Pathway ◽

Cell Types ◽

Notch Signalling ◽

Branching Pattern ◽

Cell Fates ◽

Tracheal System ◽

Notch Signalling Pathway ◽

Tracheal Cell ◽

Mutant Phenotypes ◽

Selection Of

The Drosophila tracheal system consists of a stereotyped network of epithelial tubes formed by several tracheal cell types. By the end of embryogenesis, when the general branching pattern is established, some specialised tracheal cells then mediate branch fusion while others extend fine terminal branches. Here evidence is presented that the Notch signalling pathway acts directly in the tracheal cells to distinguish individual fates within groups of equivalent cells. Notch helps to single out those tracheal cells that mediate branch fusion by blocking their neighbours from adopting the same fate. This function of Notch would require the restricted activation of the pathway in specific cells. In addition, and probably later, Notch also acts in the selection of those tracheal cells that extend the terminal branches. Both the localised expression and the mutant phenotypes of Delta, a known ligand for Notch, suggest that Delta may activate Notch to specify cell fates at the tips of the developing tracheal branches.

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On-the-fly selection of cell-specific enhancers, genes, miRNAs and proteins across the human body using SlideBase

Database ◽

10.1093/database/baw144 ◽

2016 ◽

Vol 2016 ◽

Cited By ~ 10

Author(s):

Hans Ienasescu ◽

Kang Li ◽

Robin Andersson ◽

Morana Vitezic ◽

Sarah Rennie ◽

...

Keyword(s):

Human Body ◽

Individual Cell ◽

Cell Types ◽

Large Datasets ◽

Human Tissues ◽

Web Tool ◽

Expression Of Genes ◽

Micro Rnas ◽

Human Protein Atlas ◽

Selection Of

Genomics consortia have produced large datasets profiling the expression of genes, micro-RNAs, enhancers and more across human tissues or cells. There is a need for intuitive tools to select subsets of such data that is the most relevant for specific studies. To this end, we present SlideBase, a web tool which offers a new way of selecting genes, promoters, enhancers and microRNAs that are preferentially expressed/used in a specified set of cells/tissues, based on the use of interactive sliders. With the help of sliders, SlideBase enables users to define custom expression thresholds for individual cell types/tissues, producing sets of genes, enhancers etc. which satisfy these constraints. Changes in slider settings result in simultaneous changes in the selected sets, updated in real time. SlideBase is linked to major databases from genomics consortia, including FANTOM, GTEx, The Human Protein Atlas and BioGPS. Database URL: http://slidebase.binf.ku.dk

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A Simple and Efficient CRISPR Technique for Protein Tagging

Cells ◽

10.3390/cells9122618 ◽

2020 ◽

Vol 9 (12) ◽

pp. 2618

Author(s):

Fanning Zeng ◽

Valerie Beck ◽

Sven Schuierer ◽

Isabelle Garnier ◽

Carole Manneville ◽

...

Keyword(s):

Live Cell Imaging ◽

Cell Imaging ◽

Fluorescent Protein ◽

Cell Types ◽

Luciferase Assay ◽

Primary Cells ◽

Homology Directed Repair ◽

Independent Gene ◽

Protein Tagging ◽

Selection Of

Genetic knock-in using homology-directed repair is an inefficient process, requiring the selection of few modified cells and hindering its application to primary cells. Here, we describe Homology independent gene Tagging (HiTag), a method to tag a protein of interest by CRISPR in up to 66% of transfected cells with one single electroporation. The technique has proven effective in various cell types and can be used to knock in a fluorescent protein for live cell imaging, to modify the cellular location of a target protein and to monitor the levels of a protein of interest by a luciferase assay in primary cells.

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CD90- (Thy-1-) High Selection Enhances Reprogramming Capacity of Murine Adipose-Derived Mesenchymal Stem Cells

Disease Markers ◽

10.1155/2013/392578 ◽

2013 ◽

Vol 35 ◽

pp. 573-579 ◽

Cited By ~ 9

Author(s):

Koichi Kawamoto ◽

Masamitsu Konno ◽

Hiroaki Nagano ◽

Shimpei Nishikawa ◽

Yoshito Tomimaru ◽

...

Keyword(s):

Stem Cells ◽

Mesenchymal Stem Cells ◽

Stem Cell ◽

Cell Therapy ◽

Tolerance Induction ◽

Cell Types ◽

Effective Strategy ◽

Cell Sorter ◽

High Selection ◽

Selection Of

Background. Mesenchymal stem cells (MSCs), including adipose tissue-derived mesenchymal stem cells (ADSC), are multipotent and can differentiate into various cell types possessing unique immunomodulatory features. Several clinical trials have demonstrated the safety and possible efficacy of MSCs in organ transplantation. Thus, stem cell therapy is promising for tolerance induction. In this study, we assessed the reprogramming capacity of murine ADSCs and found that CD90 (Thy-1), originally discovered as a thymocyte antigen, could be a useful marker for cell therapy.Method. Murine ADSCs were isolated from B6 mice, sorted using a FACSAria cell sorter by selection ofCD90HiorCD90Lo, and then transduced with four standard factors (4F; Oct4, Sox2, Klf4, and c-Myc).Results. Unsorted,CD90Hi-sorted, andCD90Lo-sorted murine ADSCs were reprogrammed using standard 4F transduction.CD90HiADSCs showed increased numbers of alkaline phosphatase-positive colonies compared withCD90LoADSCs. The relative reprogramming efficiencies of unsorted,CD90Hi-sorted, andCD90Lo-sorted ADSCs were 100%, 116.5%, and 74.7%, respectively.CD90Hicells were more responsive to reprogramming.Conclusion.CD90HiADSCs had greater reprogramming capacity thanCD90LoADSCs, suggesting that ADSCs have heterogeneous subpopulations. Thus,CD90Hiselection presents an effective strategy to isolate a highly suppressive subpopulation for stem cell-based tolerance induction therapy.

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Engineering Craniofacial Structures: Facing the Challenge

Journal of Dental Research ◽

10.1177/0022034509349926 ◽

2009 ◽

Vol 88 (12) ◽

pp. 1077-1091 ◽

Cited By ~ 60

Author(s):

S.H. Zaky ◽

R. Cancedda

Keyword(s):

Tissue Engineering ◽

Growth Factors ◽

Progenitor Cells ◽

Cell Types ◽

Future Treatment ◽

Current Review ◽

Regenerative Ability ◽

Selection Of ◽

Irreparable Damage

The human innate regenerative ability is known to be limited by the intensity of the insult together with the availability of progenitor cells, which may cause certain irreparable damage. It is only recently that the paradigm of tissue engineering found its way to the treatment of irreversibly affected body structures with the challenge of reconstructing the lost part. In the current review, we underline recent trials that target engineering of human craniofacial structures, mainly bone, cartilage, and teeth. We analyze the applied engineering strategies relative to the selection of cell types to lay down a specific targeted tissue, together with their association with an escorting scaffold for a particular engineered site, and discuss their necessity to be sustained by growth factors. Challenges and expectations for facial skeletal engineering are discussed in the context of future treatment.

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Inhibins Tune the Thymocyte Selection Process by Regulating Thymic Stromal Cell Differentiation

Journal of Immunology Research ◽

10.1155/2015/837859 ◽

2015 ◽

Vol 2015 ◽

pp. 1-15 ◽

Cited By ~ 4

Author(s):

Ebzadrel Carbajal-Franco ◽

Marisol de la Fuente-Granada ◽

Germán R. Alemán-Muench ◽

Eduardo A. García-Zepeda ◽

Gloria Soldevila

Keyword(s):

Cell Differentiation ◽

Mhc Class Ii ◽

Stromal Cell ◽

Selection Process ◽

Cell Types ◽

Smad Proteins ◽

Thymocyte Differentiation ◽

And Function ◽

T Cell Selection ◽

Selection Of

Inhibins and Activins are members of the TGF-βsuperfamily that regulate the differentiation of several cell types. These ligands were initially identified as hormones that regulate the hypothalamus-pituitary-gonadal axis; however, increasing evidence has demonstrated that they are key regulators in the immune system. We have previously demonstrated that Inhibins are the main Activin ligands expressed in the murine thymus and that they regulate thymocyte differentiation, promoting the DN3-DN4 transition and the selection of SP thymocytes. As Inhibins are mainly produced by thymic stromal cells, which also express Activin receptors and Smad proteins, we hypothesized that Inhibins might play a role in stromal cell differentiation and function. Here, we demonstrate that, in the absence of Inhibins, thymic conventional dendritic cells display reduced levels of MHC Class II (MHCII) and CD86. In addition, the ratio between cTECs and mTECs was affected, indicating that mTEC differentiation was favoured and cTEC diminished in the absence of Inhibins. These changes appeared to impact thymocyte selection leading to a decreased selection of CD4SP thymocytes and increased generation of natural regulatory T cells. These findings demonstrate that Inhibins tune the T cell selection process by regulating both thymocyte and stromal cell differentiation.

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Design of Solar Powered Charging Backpack

International Journal of Power Electronics and Drive Systems (IJPEDS) ◽

10.11591/ijpeds.v9.i2.pp848-858 ◽

2018 ◽

Vol 9 (2) ◽

pp. 848 ◽

Cited By ~ 1

Author(s):

Jonas Taverne ◽

Firdaus Muhammad-Sukki ◽

Ahmad Syahir Ayub ◽

Nazmi Sellami ◽

Siti Hawa Abu-Bakar ◽

...

Keyword(s):

Solar Cell ◽

Mobile Phone ◽

Power Dissipation ◽

Cell Types ◽

Step Process ◽

Charging System ◽

Linear Regulator ◽

Solar Powered ◽

The Cost ◽

Selection Of

This paper demonstrated a step by step process in designing a solar powered charging backpack that is capable of charging a mobile phone efficiently. A selection of existing products available on the market were reviewed and compared to ascertain the cost, size, and output capabilities. Next, the solar cell types and regulators were compared and their respective merits were also investigated. The charging system was then designed and tested before being integrated with the backpack. The results clearly showed that the system managed to charge the mobile phone. However, it was found that the excessive power dissipation has caused the linear regulator to generate significant heat.

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ACE: Explaining cluster from an adversarial perspective

10.1101/2021.02.08.428881 ◽

2021 ◽

Author(s):

Yang Young Lu ◽

Timothy C. Yu ◽

Giancarlo Bonora ◽

William Stafford Noble

Keyword(s):

Recognition Task ◽

Cell Types ◽

Marker Genes ◽

Rna Seq ◽

Step Procedure ◽

Latent Space ◽

Frame Work ◽

Gene Panels ◽

Nonlinear Embedding ◽

Selection Of

AbstractA common workflow in single-cell RNA-seq analysis is to project the data to a latent space, cluster the cells in that space, and identify sets of marker genes that explain the differences among the discovered clusters. A primary drawback to this three-step procedure is that each step is carried out independently, thereby neglecting the effects of the nonlinear embedding and inter-gene dependencies on the selection of marker genes. Here we propose an integrated deep learning frame-work, Adversarial Clustering Explanation (ACE), that bundles all three steps into a single workflow. The method thus moves away from the notion of “marker genes” to instead identify a panel of explanatory genes. This panel may include genes that are not only enriched but also depleted relative to other cell types, as well as genes that exhibit differences between closely related cell types. Empirically, we demonstrate that ACE is able to identify gene panels that are both highly discriminative and nonredundant, and we demonstrate the applicability of ACE to an image recognition task.

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