中国神经再生研究(英文版) ›› 2018, Vol. 13 ›› Issue (9): 1520-1523.doi: 10.4103/1673-5374.235222

• 综述:脑损伤修复保护与再生 • 上一篇    下一篇

看到树木:改善3D体外大脑切片培养物中胶质细胞的定量

  

  • 收稿日期:2018-06-20 出版日期:2018-09-15 发布日期:2018-09-15

Seeing the wood for the trees: towards improved quantification of glial cells in central nervous system tissue

Sinéad Healy, Jill McMahon, Una FitzGerald   

  1. Galway Neuroscience Centre, School of Natural Sciences, National University of Ireland, Galway, Ireland
  • Received:2018-06-20 Online:2018-09-15 Published:2018-09-15
  • Contact: Una FitzGerald, Ph.D., una.fitzgerald@nuigalway.ie
  • Supported by:

    The work was supported by a grant from Thomas Crawford Hayes Research Fund; the NUI Galway College of Science scholarship to SH; a grant from NUI Galway Foundation Office to JM.

摘要:

orcid:0000-0002-8019-6546(Una FitzGerald)

Abstract:

The following mini-review attempts to guide researchers in the quantification of fluorescently-labelled proteins within cultured thick or chromogenically-stained proteins within thin sections of brain tissue. It follows from our examination of the utility of Fiji ImageJ thresholding and binarization algorithms. Describing how we identified the maximum intensity projection as the best of six tested for two dimensional (2D)-rendering of three-dimensional (3D) images derived from a series of z-stacked micrographs, the review summarises our comparison of 16 global and 9 local algorithms for their ability to accurately quantify the expression of astrocytic glial fibrillary acidic protein (GFAP), microglial ionized calcium binding adapter molecule 1 (IBA1) and oligodendrocyte lineage Olig2 within fixed cultured rat hippocampal brain slices. The application of these algorithms to chromogenically-stained GFAP and IBA1 within thin tissue sections, is also described. Fiji’s BioVoxxel plugin allowed categorisation of algorithms according to their sensitivity, specificity accuracy and relative quality. The Percentile algorithm was deemed best for quantifying levels of GFAP, the Li algorithm was best when quantifying IBA expression, while the Otsu algorithm was optimum for Olig2 staining, albeit with over-quantification of oligodendrocyte number when compared to a stereological approach. Also, GFAP and IBA expression in 3,3’-diaminobenzidine (DAB)/haematoxylin-stained cerebellar tissue was best quantified with Default, Isodata and Moments algorithms. The workflow presented in Figure 1 could help to improve the quality of research outcomes that are based on the quantification of protein with brain tissue.

Key words: organotypic brain slice culture, glial cell quantification, thresholding algorithms, Fiji ImageJ, BioVoxxel plug-in, stereology