Laboratory behavioural tasks are an essential research tool. As questions asked of behaviour and brain activity become more sophisticated, the ability to specify and run richly structured tasks becomes more important. An increasing focus on reproducibility also necessitates accurate communication of task logic to other researchers. To these ends we developed pyControl, a system of open source hardware and software for controlling behavioural experiments comprising; a simple yet flexible Python-based syntax for specifying tasks as extended state machines, hardware modules for building behavioural setups, and a graphical user interface designed for efficiently running high throughput experiments on many setups in parallel, all with extensive online documentation. These tools make it quicker, easier and cheaper to implement rich behavioural tasks at scale. As important, pyControl facilitates communication and reproducibility of behavioural experiments through a highly readable task definition syntax and self-documenting features.

Quality assessment of tree-like structures obtained from a neuron reconstruction algorithm is necessary for evaluating the performance of the algorithm. The lack of user-friendly software for calculating common metrics motivated us to develop a Python toolbox called PyNeval, which is the first open-source toolbox designed to evaluate reconstruction results conveniently as far as we know. The toolbox supports popular metrics in two major categories, geometrical metrics and topological metrics, with an easy way to configure custom parameters for each metric. We tested the toolbox on both synthetic data and real data to show its reliability and robustness. As a demonstration of the toolbox in real applications, we used the toolbox to improve the performance of a tracing algorithm successfully by integrating it into an optimization procedure.

Pyramidal neurons are characterized by their distinct apical and basal dendritic trees and the pyramidal shape of their soma. They are found in several regions of the CNS and, although the reasons for their abundance remain unclear, functional studies--especially of CA1 hippocampal and layer V neocortical pyramidal neurons--have offered insights into the functions of their unique cellular architecture. Pyramidal neurons are not all identical, but some shared functional principles can be identified. In particular, the existence of dendritic domains with distinct synaptic inputs, excitability, modulation and plasticity appears to be a common feature that allows synapses throughout the dendritic tree to contribute to action-potential generation. These properties support a variety of coincidence-detection mechanisms, which are likely to be crucial for synaptic integration and plasticity.

Neurons relevant to a particular behavior are often widely dispersed across the brain. To record activity in groups of individual neurons that might be distributed across large distances, neuroscientists and optical engineers have been developing a new type of microscope called a mesoscope. Mesoscopes have high spatial resolution and a large field of view. This Q&A will discuss this exciting new technology, highlighting a particular instrument, the two-photon random access mesoscope (2pRAM).

BACKGROUND/PURPOSE: To automatically assess hair growth during cosmetic trials, incorporating parameters such as anagen-to-telogen rate, growth rate, and especially hair diameter.

METHODS: We designed and qualified a new and automatic phototrichogram system based on a high-resolution DSLR camera system (theoretical resolution of 2.557 μm/pixel) and modular macrolens system with fixed focus, combined with a trainable pattern recognition software for automated analysis.

RESULTS: We improved the standard routine for dermatological phototrichogram technique to overcome inaccuracy in thickness measurements due to hair swelling by using an alternative immersion fluid, and increased the effective resolution for hair size and thickness measurement to <4 μm. After having qualified manual measurements as gold standard for the determination of hair diameters, we established a new trainable automatic picture analysis software able to locate and measure individual hairs in length and thickness even in picture series taken from the same skin area at different time points. Comparisons between manual and automatic measurements of the same hairs showed a >90% correlation, and by comparing the automatic results with manual measurements of the same images without individual hair annotation, we could find a correlation of at least 80%.

CONCLUSION: According to the results and findings generated in this qualification study, we have a reliable tool now that enables us to test cosmetic products for hair treatment in a highly automated way with a sufficient degree of precision and accuracy to detect even small changes in hair diameter during cosmetic trials.

Post-translational histone modifications are highly correlated with transcriptional activity, but the relative timing of these marks and their dynamic interplay during gene regulation remains controversial. To shed light on this problem and clarify the connections between histone modifications and transcription, we demonstrate how FabLEM (Fab-based Live Endogenous Modification labeling) can be used to simultaneously track histone H3 Lysine 9 acetylation (H3K9ac) together with RNA polymerase II Serine 2 and Serine 5 phosphorylation (RNAP2 Ser2ph/Ser5ph) in single living cells and their progeny. We provide a detailed description of the FabLEM methodology, including helpful tips for preparing and loading fluorescently conjugated antigen binding fragments (Fab) into cells for optimal results. We also introduce simple procedures for analyzing and visualizing FabLEM data, including color-coded scatterplots to track correlations between modifications through the cell cycle and temporal cross-correlation analysis to dissect modification dynamics. Using these methods, we find significant correlations that span cell generations, with a relatively strong correlation between H3K9ac and Ser5ph that appears to peak a few hours before mitosis and may reflect the bookmarking of genes for efficient re-initiation following mitosis. The techniques we have developed are broadly applicable and should help clarify how histone modifications dynamically contribute to gene regulation.

Quantifying molecular dynamics within the context of complex cellular morphologies is essential toward understanding the inner workings and function of cells. Fluorescence recovery after photobleaching (FRAP) is one of the most broadly applied techniques to measure the reaction diffusion dynamics of molecules in living cells. FRAP measurements typically restrict themselves to single-plane image acquisition within a subcellular-sized region of interest due to the limited temporal resolution and undesirable photobleaching induced by 3D fluorescence confocal or widefield microscopy. Here, an experimental and computational pipeline combining lattice light sheet microscopy, FRAP, and numerical simulations, offering rapid and minimally invasive quantification of molecular dynamics with respect to 3D cell morphology is presented. Having the opportunity to accurately measure and interpret the dynamics of molecules in 3D with respect to cell morphology has the potential to reveal unprecedented insights into the function of living cells.

The distinctive distributions of proteins within subcellular compartments both at steady state and during signaling events have essential roles in cell function. Here we describe a method for delineating the complex arrangement of proteins within subcellular structures visualized using point-localization superresolution (PL-SR) imaging. The approach, called pair correlation photoactivated localization microscopy (PC-PALM), uses a pair-correlation algorithm to precisely identify single molecules in PL-SR imaging data sets, and it is used to decipher quantitative features of protein organization within subcellular compartments, including the existence of protein clusters and the size, density and number of proteins in these clusters. We provide a step-by-step protocol for PC-PALM, illustrating its analysis capability for four plasma membrane proteins tagged with photoactivatable GFP (PAGFP). The experimental steps for PC-PALM can be carried out in 3 d and the analysis can be done in ∼6-8 h. Researchers need to have substantial experience in single-molecule imaging and statistical analysis to conduct the experiments and carry out this analysis.

Progressive, technological achievements in the quantitative fluorescence microscopy field are allowing researches from many different areas to start unraveling the dynamic intricacies of biological processes inside living cells. From super-resolution microscopy techniques to tracking of individual proteins, fluorescence microscopy is changing our perspective on how the cell works. Fortunately, a growing number of research groups are exploring single-molecule studies in living cells. However, no clear consensus exists on several key aspects of the technique such as image acquisition conditions, or analysis of the obtained data. Here, we describe a detailed approach to perform single-molecule tracking (SMT) of transcription factors in living cells to obtain key binding characteristics, namely their residence time and bound fractions. We discuss different types of fluorophores, labeling density, microscope, cameras, data acquisition, and data analysis. Using the glucocorticoid receptor as a model transcription factor, we compared alternate tags (GFP, mEOS, HaloTag, SNAP-tag, CLIP-tag) for potential multicolor applications. We also examine different methods to extract the dissociation rates and compare them with simulated data. Finally, we discuss several challenges that this exciting technique still faces.

Pointillistic based super-resolution techniques, such as photoactivated localization microscopy (PALM), involve multiple cycles of sequential activation, imaging, and precise localization of single fluorescent molecules. A super-resolution image, having nanoscopic structural information, is then constructed by compiling all the image sequences. Because the final image resolution is determined by the localization precision of detected single molecules and their density, accurate image reconstruction requires imaging of biological structures labeled with fluorescent molecules at high density. In such image datasets, stochastic variations in photon emission and intervening dark states lead to uncertainties in identification of single molecules. This, in turn, prevents the proper utilization of the wealth of information on molecular distribution and quantity. A recent strategy for overcoming this problem is pair-correlation analysis applied to PALM. Using rigorous statistical algorithms to estimate the number of detected proteins, this approach allows the spatial organization of molecules to be quantitatively described.