EasySep™ Mouse Streptavidin RapidSpheres™ Isolation Kit

Immunomagnetic negative selection cell isolation kit

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From: 389 USD


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Immunomagnetic negative selection cell isolation kit
From: 389 USD

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The EasySep™ Mouse Streptavidin RapidSpheres™ Isolation Kit is designed for the depletion of single or multiple unwanted cell types labeled with biotinylated antibodies. Labeled cells from mouse splenocytes or other tissues are targeted for removal by Streptavidin RapidSpheres™ and separated without the use of columns using an EasySep™ magnet. Desired cells are untouched and poured off into a new tube.
• Fast and easy-to-use
• No columns required
• Untouched, viable cells
  • EasySep™ Mouse Streptavidin RapidSpheres™ Isolation Kit (Catalog #19860)
    • EasySep™ Streptavidin RapidSpheres™ 50001, 1 mL
    • Normal Rat Serum, 2 mL
    • RoboSep™ Empty Vial
  • RoboSep™ Mouse Streptavidin RapidSpheres™ Isolation Kit (Catalog #19860RF)
    • EasySep™ Streptavidin RapidSpheres™ 50001, 1 mL
    • Normal Rat Serum, 2 mL
    • RoboSep™ Empty Vial
    • RoboSep™ Buffer (Catalog #20104)
    • RoboSep™ Filter Tips (Catalog #20125)
Magnet Compatibility:
• EasySep™ Magnet (Catalog #18000)
• “The Big Easy” EasySep™ Magnet (Catalog #18001)
• RoboSep™-S (Catalog #21000)
Cell Isolation Kits
Cell Type:
B Cells; Dendritic Cells; Granulocytes and Subsets; Hematopoietic Stem and Progenitor Cells; Macrophages; Marrow Stromal Cells; Mesenchymal Stem and Progenitor Cells; Monocytes; Mononuclear Cells; Myeloid Cells; NK Cells; Other; Plasma Cells; T Cells
Sample Source:
Other; Spleen
Selection Method:
Depletion; Negative
Cell Isolation
EasySep; RoboSep
Area of Interest:

Scientific Resources

Educational Materials


Data and Publications


Typical Mouse Streptavidin Rapidspheres™ CD4 (CD3+CD8-) Depletion Profile

Figure 1. Typical Mouse Streptavidin Rapidspheres™ CD4 (CD3+CD8-) Depletion Profile

Typical Mouse Streptavidin Rapidspheres™ CD8 (CD3+CD4-) Depletion Profile

Figure 2. Typical Mouse Streptavidin Rapidspheres™ CD8 (CD3+CD4-) Depletion Profile

Typical Mouse Streptavidin Rapidspheres™ CD19 (CD19+CD45+) Depletion Profile

Figure 3. Typical Mouse Streptavidin Rapidspheres™ CD19 (CD19+CD45+) Depletion Profile


Cell reports 2020 jun

Complete Topological Mapping of a Cellular Protein Interactome Reveals Bow-Tie Motifs as Ubiquitous Connectors of Protein Complexes.

K. Niss et al.


The network topology of a protein interactome is shaped by the function of each protein, making it a resource of functional knowledge in tissues and in single cells. Today, this resource is underused, as complete network topology characterization has proved difficult for large protein interactomes. We apply a matrix visualization and decoding approach to a physical protein interactome of a dendritic cell, thereby characterizing its topology with no prior assumptions of structure. We discover 294 proteins, each forming topological motifs called bow-ties" that tie together the majority of observed protein complexes. The central proteins of these bow-ties have unique network properties display multifunctional capabilities are enriched for essential proteins and are widely expressed in other cells and tissues. Collectively the bow-tie motifs are a pervasive and previously unnoted topological trend in cellular interactomes. As such these results provide fundamental knowledge on how intracellular protein connectivity is organized and operates."
Nature medicine 2020 jul

Systemic dysfunction and plasticity of the immune macroenvironment in cancer models.

B. M. Allen et al.


Understanding of the factors governing immune responses in cancer remains incomplete, limiting patient benefit. In this study, we used mass cytometry to define the systemic immune landscape in response to tumor development across five tissues in eight mouse tumor models. Systemic immunity was dramatically altered across models and time, with consistent findings in the peripheral blood of patients with breast cancer. Changes in peripheral tissues differed from those in the tumor microenvironment. Mice with tumor-experienced immune systems mounted dampened responses to orthogonal challenges, including reduced T cell activation during viral or bacterial infection. Antigen-presenting cells (APCs) mounted weaker responses in this context, whereas promoting APC activation rescued T cell activity. Systemic immune changes were reversed with surgical tumor resection, and many were prevented by interleukin-1 or granulocyte colony-stimulating factor blockade, revealing remarkable plasticity in the systemic immune state. These results demonstrate that tumor development dynamically reshapes the composition and function of the immune macroenvironment.
Cancer cell 2019 aug

Mechanisms of Progression of Myeloid Preleukemia to Transformed Myeloid Leukemia in Children with Down Syndrome.

M. Labuhn et al.


Myeloid leukemia in Down syndrome (ML-DS) clonally evolves from transient abnormal myelopoiesis (TAM), a preleukemic condition in DS newborns. To define mechanisms of leukemic transformation, we combined exome and targeted resequencing of 111 TAM and 141 ML-DS samples with functional analyses. TAM requires trisomy 21 and truncating mutations in GATA1; additional TAM variants are usually not pathogenic. By contrast, in ML-DS, clonal and subclonal variants are functionally required. We identified a recurrent and oncogenic hotspot gain-of-function mutation in myeloid cytokine receptor CSF2RB. By a multiplex CRISPR/Cas9 screen in an in vivo murine TAM model, we tested loss-of-function of 22 recurrently mutated ML-DS genes. Loss of 18 different genes produced leukemias that phenotypically, genetically, and transcriptionally mirrored ML-DS.
Nature 2018 FEB

Population snapshots predict early haematopoietic and erythroid hierarchies.

B. K. Tusi et al.


The formation of red blood cells begins with the differentiation of multipotent haematopoietic progenitors. Reconstructing the steps of this differentiation represents a general challenge in stem-cell biology. Here we used single-cell transcriptomics, fate assays and a theory that allows the prediction of cell fates from population snapshots to demonstrate that mouse haematopoietic progenitors differentiate through a continuous, hierarchical structure into seven blood lineages. We uncovered coupling between the erythroid and the basophil or mast cell fates, a global haematopoietic response to erythroid stress and novel growth factor receptors that regulate erythropoiesis. We defined a flow cytometry sorting strategy to purify early stages of erythroid differentiation, completely isolating classically defined burst-forming and colony-forming progenitors. We also found that the cell cycle is progressively remodelled during erythroid development and during a sharp transcriptional switch that ends the colony-forming progenitor stage and activates terminal differentiation. Our work showcases the utility of linking transcriptomic data to predictive fate models, and provides insights into lineage development in vivo.
Nature communications 2017 DEC

Alternative activation generates IL-10 producing type 2 innate lymphoid cells.

C. R. Seehus et al.


Type 2 innate lymphoid cells (ILC2) share cytokine and transcription factor expression with CD4+ Th2 cells, but functional diversity of the ILC2 lineage has yet to be fully explored. Here, we show induction of a molecularly distinct subset of activated lung ILC2, termed ILC210. These cells produce IL-10 and downregulate some pro-inflammatory genes. Signals that generate ILC210 are distinct from those that induce IL-13 production, and gene expression data indicate that an alternative activation pathway leads to the generation of ILC210. In vivo, IL-2 enhances ILC210 generation and is associated with decreased eosinophil recruitment to the lung. Unlike most activated ILC2, the ILC210 population contracts after cessation of stimulation in vivo, with maintenance of a subset that can be recalled by restimulation, analogous to T-cell effector cell and memory cell generation. These data demonstrate the generation of a previously unappreciated IL-10 producing ILC2 effector cell population.