Detection and estimation of mRNA levels using a nonlinear model in neurons labeled by in situ hybridization histochemistry.
Detection and estimation of mRNA levels using a nonlinear model in neurons labeled by in situ hybridization histochemistry.
复制标题
使用原位杂交组织化学标记的神经元中的非线性模型检测和估计 mRNA 水平。
DOI：
10.1006/nimg.1993.1008
复制
发表时间：
1993
期刊：
影响因子：
5.7
通讯作者：
Kream,RM
中科院分区：
文献类型：
--
作者：
Zaccheo,TS;Gonsalves,RA;Kream,RM
原位杂交组织化学（ISHH）是一种解剖学技术，用于通过检测mRNA的稳态水平来监测细胞水平的基因表达。以前，ISHH产生的放射自显影材料的光密度分析提供了一个相对定量的测量在任何给定的解剖区域分布的特定mRNA的水平。本研究详细介绍了用于自动化ISHH的定量方面的参数建模技术的发展。本文描述的ISHH实验利用了与编码神经肽P物质和相关速激肽的mRNA分子互补的特异性DNA探针。一个非线性模型被用来描述标记神经元的暗场强度模式。模型的参数，然后在检测个别杂交的神经元，并在估计前速激肽原mRNA和相关的细胞面积的水平。通过将模型描述的强度与从14C放射自显影标准品获得的强度相关联来定量总mRNA含量。最后，该算法的性能进行了评估，通过比较这些估计从标记的神经元的手动颗粒计数。总的来说，这里提出的参数模型有利于基于预定的和无偏的形态学标准进行杂交神经元的定量分析的过程。
In situhybridization histochemistry (ISHH) is an anatomical technique used to monitor gene expression at the cellular level via detection of steady-state levels of mRNA. Previously, densitometric analysis of ISHH-generated autoradiographic material has provided a relatively quantitative measure of the level of a specific mRNA distributed in any given anatomical region. The present study details the development of a parametric modeling technique used to automate the quantitative aspects of ISHH. The ISHH experiments described here utilized a specific DNA probe complementary to mRNA molecules encoding the neuropeptide substance P and related tachykinin peptides. A nonlinear model was used to describe the dark-field intensity pattern of labeled neurons. The model's parameters were then employed in detecting individually hybridized neurons and in estimating levels of preprotachykinin mRNA and associated cellular areas. Total mRNA content was quantified by relating the intensities described by the models to those obtained from14C autoradiographic standards. Finally, the algorithm's performance was evaluated by comparing these estimates to those obtained from manual grain counts of labeled neurons. Overall, the parametric model presented here facilitates the process of performing quantitative analysis of hybridized neurons based on predetermined and un-biased morphological criteria.