In vertebrates, the anterior pituitary plays a crucial role in regulating several essential physiological processes via the secretion of at least seven peptide hormones by different endocrine cell types. Comparative and comprehensive knowledge of the spatial distribution of those endocrine cell types is required to better understand their physiological functions. Using medaka as a model and several combinations of multi-color fluorescence in situ hybridization, we present the first 3D atlas revealing the gland-wide distribution of seven endocrine cell populations: lactotropes, thyrotropes, Lh and Fsh gonadotropes, somatotropes, and pomca-expressing cells (corticotropes and melanotropes) in the anterior pituitary of a teleost fish. By combining in situ hybridization and immunofluorescence techniques, we deciphered the location of corticotropes and melanotropes within the pomca-expressing cell population. The 3D localization approach reveals sexual dimorphism of tshba-, pomca-, and lhb-expressing cells in the adult medaka pituitary. Finally, we show the existence of bi-hormonal cells co-expressing lhb-fshb, fshb-tshba and lhb-sl using single-cell transcriptomics analysis and in situ hybridization. This study offers a solid basis for future comparative studies of the teleost pituitary and its functional plasticity.

Sodium dodecyl sulfate (SDS) is widely used for protein solubilization and for separation of proteins by SDS polyacrylamide gel electrophoresis (SDS-PAGE). However, SDS interferes with other techniques used for characterization of proteins, such as mass spectrometry (MS) and amino acid sequencing. In this paper, we have compared three procedures to remove SDS from proteins, including chloroform/methanol/water extraction (C/M/W), cold acetone extraction and desalting columns, in order to find a rapid and reproducible procedure that provides sufficient reduction of SDS and high recovery rates for proteins prior to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS). A 1000-fold reduction of SDS concentration and a protein recovery at approximately 50% were obtained with the C/M/W procedure. The cold acetone procedure gave a 100-fold reduction of SDS and a protein recovery of approximately 80%. By using desalting columns, the removal of SDS was 100-fold, with a protein recovery of nearly 50%. Both the C/M/W and the cold acetone methods provided sufficient reduction of SDS, high recovery rates of protein and allowed the acquisition of MALDI spectra. The use of n-octyl-beta-D-glucopyranoside in the protein sample preparation enhanced the MALDI signal for protein samples containing more than 2 10(-4)% SDS, after the C/M/W extraction. Following the cold acetone procedure, the use of n-octylglucoside was found to be necessary in order to obtain spectra, but they were of lower quality than those obtained with the C/M/W method, probably due to higher residual amounts of SDS.

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Registration of data to a common frame of reference is an essential step in the analysis and integration of diverse neuroscientific data modalities. To this end, volumetric brain atlases enable histological datasets to be spatially registered and analysed, yet accurate registration remains expertise-dependent and slow. We have trained a neural network, DeepSlice, to register mouse brain histology to the Allen Brain Atlas, retaining accuracy while improving speed by >1000 fold.

Brain atlases are widely used in neuroscience as resources for conducting experimental studies, and for integrating, analyzing, and reporting data from animal models. A variety of atlases are available, and it may be challenging to find the optimal atlas for a given purpose and to perform efficient atlas-based data analyses. Comparing findings reported using different atlases is also not trivial, and represents a barrier to reproducible science. With this perspective article, we provide a guide to how mouse and rat brain atlases can be used for analyzing and reporting data in accordance with the FAIR principles that advocate for data to be findable, accessible, interoperable, and re-usable. We first introduce how atlases can be interpreted and used for navigating to brain locations, before discussing how they can be used for different analytic purposes, including spatial registration and data visualization. We provide guidance on how neuroscientists can compare data mapped to different atlases and ensure transparent reporting of findings. Finally, we summarize key considerations when choosing an atlas and give an outlook on the relevance of increased uptake of atlas-based tools and workflows for FAIR data sharing.