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.

We address the problem of explaining the decision process of deep neural network classifiers on images, which is of particular importance in biomedical datasets where class-relevant differences are not always obvious to a human observer. Our proposed solution, termed quantitative attribution with counterfactuals (QuAC), generates visual explanations that highlight class-relevant differences by attributing the classifier decision to changes of visual features in small parts of an image. To that end, we train a separate network to generate counterfactual images (i.e., to translate images between different classes). We then find the most important differences using novel discriminative attribution methods. Crucially, QuAC allows scoring of the attribution and thus provides a measure to quantify and compare the fidelity of a visual explanation. We demonstrate the suitability and limitations of QuAC on two datasets: (1) a synthetic dataset with known class differences, representing different levels of protein aggregation in cells and (2) an electron microscopy dataset of D. melanogaster synapses with different neurotransmitters, where QuAC reveals so far unknown visual differences. We further discuss how QuAC can be used to interrogate mispredictions to shed light on unexpected inter-class similarities and intra-class differences.

A new generation of direct electron detectors for transmission electron microscopy (TEM) promises significant improvement over previous detectors in terms of their modulation transfer function (MTF) and detective quantum efficiency (DQE). However, the performance of these new detectors needs to be carefully monitored in order to optimize imaging conditions and check for degradation over time. We have developed an easy-to-use software tool, FindDQE, to measure MTF and DQE of electron detectors using images of a microscope’s built-in beam stop. Using this software, we have determined the DQE curves of four direct electron detectors currently available: the Gatan K2 Summit, the FEI Falcon I and II, and the Direct Electron DE-12, under a variety of total dose and dose rate conditions. We have additionally measured the curves for the Gatan US4000 and TVIPS TemCam-F416 scintillator-based cameras. We compare the results from our new method with published curves.

Live imaging of large biological specimens is fundamentally limited by the short optical penetration depth of light microscopes. To maximize physical coverage, we developed the SiMView technology framework for high-speed in vivo imaging, which records multiple views of the specimen simultaneously. SiMView consists of a light-sheet microscope with four synchronized optical arms, real-time electronics for long-term sCMOS-based image acquisition at 175 million voxels per second, and computational modules for high-throughput image registration, segmentation, tracking and real-time management of the terabytes of multiview data recorded per specimen. We developed one-photon and multiphoton SiMView implementations and recorded cellular dynamics in entire Drosophila melanogaster embryos with 30-s temporal resolution throughout development. We furthermore performed high-resolution long-term imaging of the developing nervous system and followed neuroblast cell lineages in vivo. SiMView data sets provide quantitative morphological information even for fast global processes and enable accurate automated cell tracking in the entire early embryo.

High-resolution movies in the Digital Embryo repository
Nature News: "Fruitfly development, cell by cell" by Lauren Gravitz
Nature Methods Technology Feature: "Faster frames, clearer pictures" by Monya Baker
Andor Insight Awards: Life Sciences Winner

Glucose is an essential source of energy for the brain. Recently, the development of genetically encoded fluorescent biosensors has allowed real time visualization of glucose dynamics from individual neurons and astrocytes. A major difficulty for this approach, even for ratiometric sensors, is the lack of a practical method to convert such measurements into actual concentrations in ex vivo brain tissue or in vivo. Fluorescence lifetime imaging provides a strategy to overcome this. In a previous study, we reported the lifetime glucose sensor iGlucoSnFR-TS (then called SweetieTS) for monitoring changes in neuronal glucose levels in response to stimulation. This genetically encoded sensor was generated by combining the Thermus thermophilus glucose-binding protein with a circularly permuted variant of the monomeric fluorescent protein T-Sapphire. Here, we provide more details on iGlucoSnFR-TS design and characterization, as well as pH and temperature sensitivities. For accurate estimation of glucose concentrations, the sensor must be calibrated at the same temperature as the experiments. We find that when the extracellular glucose concentration is in the range 2-10 mM, the intracellular glucose concentration in hippocampal neurons from acute brain slices is ~20% of the nominal external glucose concentration (~0.4-2 mM). We also measured the cytosolic neuronal glucose concentration in vivo, finding a range of ~0.7-2.5 mM in cortical neurons from awake mice.

We describe a fluorescence in situ hybridization method that permits detection of the localization and abundance of single mRNAs (smFISH) in cleared whole-mount adult Drosophila brains. The approach is rapid and multiplexable and does not require molecular amplification; it allows facile quantification of mRNA expression with subcellular resolution on a standard confocal microscope. We further demonstrate single-mRNA detection across the entire brain using a custom Bessel beam structured illumination microscope (BB-SIM).

Neuronal circuit mapping using electron microscopy demands laborious proofreading or reconciliation of multiple independent reconstructions. Here, we describe new methods to apply quantitative arbor and network context to iteratively proofread and reconstruct circuits and create anatomically enriched wiring diagrams. We measured the morphological underpinnings of connectivity in new and existing reconstructions of Drosophila sensorimotor (larva) and visual (adult) systems. Synaptic inputs were preferentially located on numerous small, microtubule-free 'twigs' which branch off a single microtubule-containing 'backbone'. Omission of individual twigs accounted for 96% of errors. However, the synapses of highly connected neurons were distributed across multiple twigs. Thus, the robustness of a strong connection to detailed twig anatomy was associated with robustness to reconstruction error. By comparing iterative reconstruction to the consensus of multiple reconstructions, we show that our method overcomes the need for redundant effort through the discovery and application of relationships between cellular neuroanatomy and synaptic connectivity.

Lysosomes play crucial roles in maintaining cellular homeostasis and promoting organism fitness. The pH of lysosomes is a crucial parameter for their proper function, and it is dynamically influenced by both intracellular and environmental factors. Here, we present a method based on fluorescence lifetime imaging microscopy (FLIM) for quantitatively analyzing lysosomal pH profiles in diverse types of primary mammalian cells and in different tissues of the live organism Caenorhabditis elegans. This FLIM-based method exhibits high sensitivity in resolving subtle pH differences, thereby revealing the heterogeneity of the lysosomal population within a cell and between cell types. The method enables rapid measurement of lysosomal pH changes in response to various environmental stimuli. Furthermore, the FLIM measurement of pH-sensitive dyes circumvents the need for transgenic reporters and mitigates potential confounding factors associated with varying dye concentrations or excitation light intensity. This FLIM approach offers absolute quantification of lysosomal pH and highlights the significance of lysosomal pH heterogeneity and dynamics, providing a valuable tool for studying lysosomal functions and their regulation in various physiological and pathological contexts.

The endo-lysosomal system plays a crucial role in maintaining cellular homeostasis and promoting organism fitness. The pH of its acidic compartments is a crucial parameter for proper function, and it is dynamically influenced by both intracellular and environmental factors. Here, we present a method based on fluorescence lifetime imaging microscopy (FLIM) for quantitatively analyzing the pH profiles of acidic endolysosomal compartments in diverse types of primary mammalian cells and in live organism . This FLIM-based method exhibits high sensitivity in resolving subtle pH differences, thereby revealing heterogeneity within a cell and across cell types. This method enables rapid measurement of pH changes in the acidic endolysosomal system in response to various environmental stimuli. Furthermore, the fast FLIM measurement of pH-sensitive dyes circumvents the need for transgenic reporters and mitigates potential confounding factors associated with varying dye concentrations or excitation light intensity. This FLIM approach offers absolute pH quantification and highlights the significance of pH heterogeneity and dynamics, offering a valuable tool for investigating lysosomal functions and their regulation in various physiological and pathological contexts.

A quantitative understanding of tissue morphogenesis requires description of the movements of individual cells in space and over time. In transparent embryos, such as C. elegans, fluorescently labeled nuclei can be imaged in three-dimensional time-lapse (4D) movies and automatically tracked through early cleavage divisions up to  350 nuclei. A similar analysis of later stages of C. elegans development has been challenging owing to the increased error rates of automated tracking of large numbers of densely packed nuclei. We present Nucleitracker4D, a freely available software solution for tracking nuclei in complex embryos that integrates automated tracking of nuclei in local searches with manual curation. Using these methods, we have been able to track >99% of all nuclei generated in the C. elegans embryo. Our analysis reveals that ventral enclosure of the epidermis is accompanied by complex coordinated migration of the neuronal substrate. We can efficiently track large numbers of migrating nuclei in 4D movies of zebrafish cardiac morphogenesis, suggesting that this approach is generally useful in situations in which the number, packing or dynamics of nuclei present challenges for automated tracking.