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RNA sequencing analysis reveals quiescent microglia isolation methods from postnatal mouse brains and limitations of BV2 cells

Overview of attention for article published in Journal of Neuroinflammation, May 2018
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Title
RNA sequencing analysis reveals quiescent microglia isolation methods from postnatal mouse brains and limitations of BV2 cells
Published in
Journal of Neuroinflammation, May 2018
DOI 10.1186/s12974-018-1195-4
Pubmed ID
Authors

Yingbo He, Xiang Yao, Natalie Taylor, Yuchen Bai, Timothy Lovenberg, Anindya Bhattacharya

Abstract

Microglia play key roles in neuron-glia interaction, neuroinflammation, neural repair, and neurotoxicity. Currently, various microglial in vitro models including primary microglia derived from distinct isolation methods and immortalized microglial cell lines are extensively used. However, the diversity of these existing models raises difficulty in parallel comparison across studies since microglia are sensitive to environmental changes, and thus, different models are likely to show widely varied responses to the same stimuli. To better understand the involvement of microglia in pathophysiological situations, it is critical to establish a reliable microglial model system. With postnatal mouse brains, we isolated microglia using three general methods including shaking, mild trypsinization, and CD11b magnetic-associated cell sorting (MACS) and applied RNA sequencing to compare transcriptomes of the isolated cells. Additionally, we generated a genome-wide dataset by RNA sequencing of immortalized BV2 microglial cell line to compare with primary microglia. Furthermore, based on the outcomes of transcriptional analysis, we compared cellular functions between primary microglia and BV2 cells including immune responses to LPS by quantitative RT-PCR and Luminex Multiplex Assay, TGFβ signaling probed by Western blot, and direct migration by chemotaxis assay. We found that although the yield and purity of microglia were comparable among the three isolation methods, mild trypsinization drove microglia in a relatively active state, evidenced by high amount of amoeboid microglia, enhanced expression of microglial activation genes, and suppression of microglial quiescent genes. In contrast, CD11b MACS was the most reliable and consistent method, and microglia isolated by this method maintained a relatively resting state. Transcriptional and functional analyses revealed that as compared to primary microglia, BV2 cells remain most of the immune functions such as responses to LPS but showed limited TGFβ signaling and chemotaxis upon chemoattractant C5a. Collectively, we determined the optimal isolation methods for quiescent microglia and characterized the limitations of BV2 cells as an alternative of primary microglia. Considering transcriptional and functional differences, caution should be taken when extrapolating data from various microglial models. In addition, our RNA sequencing database serves as a valuable resource to provide novel insights for appropriate application of microglia as in vitro models.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 130 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 130 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 22%
Student > Master 22 17%
Researcher 19 15%
Student > Bachelor 18 14%
Student > Doctoral Student 6 5%
Other 11 8%
Unknown 25 19%
Readers by discipline Count As %
Neuroscience 45 35%
Biochemistry, Genetics and Molecular Biology 25 19%
Agricultural and Biological Sciences 12 9%
Medicine and Dentistry 5 4%
Pharmacology, Toxicology and Pharmaceutical Science 4 3%
Other 10 8%
Unknown 29 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 May 2018.
All research outputs
#17,964,768
of 23,070,218 outputs
Outputs from Journal of Neuroinflammation
#1,962
of 2,661 outputs
Outputs of similar age
#238,784
of 330,078 outputs
Outputs of similar age from Journal of Neuroinflammation
#53
of 78 outputs
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So far Altmetric has tracked 2,661 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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