Maximizing Explanatory Power in Stereological Data Collection: A Protocol for Reliably Integrating Optical Fractionator and Multiple Immunofluorescence Techniques - Anna Kreutz; Nicole Barger; Nicole Barger (Frontiers Media S.A., 2018)
With the promise of greater reliability and replicability of estimates, stereological techniques have revolutionized data collection in the neurosciences. At the same time, improvements in immunohistochemistry and fluorescence imaging technologies have facilitated easy application of immunofluorescence protocols, allowing for isolation of multiple target proteins in one tissue sample. Combining multiple immunofluorescence labeling with stereological data collection can provide a powerful tool to maximize explanatory power and efficiency, while minimizing tissue use. Multiple cell classes, subtypes of larger populations, or different cell states can be quantified in one case and even in one sampling run. Here, we present a protocol integrating stereological data collection and multiple immunofluorescence using commonly employed widefield epifluorescence filter sets, optimized for blue (DAPI), green (FITC), and far red (CY5) channels. Our stereological protocol has been designed to accommodate the challenges of fluorescence imaging to overcome limitations like fixed filter sets, photobleaching, and uneven immunolabeling. To enhance fluorescence signal for stereological sampling, our immunolabeling protocol utilizes both high temperature antigen retrieval to improve primary antibody binding and secondary antibodies conjugated to optimally stable fluorophores. To illustrate the utility of this approach, we estimated the number of Ctip2 immunoreactive subcerebral projection neurons and NeuN immunoreactive neurons in rat cerebral cortex at postnatal day 10. We used DAPI (blue) to define the neocortex, anti-NeuN (far red) to identify neurons, and co-labeling of anti-Ctip2 (green) and anti-NeuN (far red) to isolate only subcerebral projection neurons. Our protocol resulted in estimates with low sampling error (CE < 0.05) and high intrarater reliability (ICC > 0.98) that fall within the range of published values, attesting to its efficacy. We show our immunofluorescence techniques can be used to reliably identify other cell types, e.g., different glial cell classes, to highlight the broader applications of our approach. The flexibility of the technique, increasingly reduced costs of fluorescence technologies, and savings in experimental time and tissue use make this approach valuable for neuroscientists interested in incorporating stereology to ask precise neurophysiological and neuroanatomical questions.