A group leader decided that his lab would share the fluorescent dyes they create, for free and without authorship requirements. Nearly 12,000 aliquots later, he reveals what has happened since.

Correlative light and electron microscopy (CLEM) combines the power of electron microscopy, with its excellent resolution and contrast, with that of fluorescence imaging, which allows the staining of specific molecules, organelles, and cell populations. Fluorescence imaging is also readily compatible with live cells and behaving animals, facilitating real-time visualization of cellular processes, potentially followed by electron microscopic reconstruction. Super-resolution single-molecule localization microscopy is a relatively new modality that harnesses the ability of some fluorophores to photoconvert, through which localization precision better than Abbe’s diffraction limit is achieved through iterative high-resolution localization of single-molecule emitters. Here we describe our lab’s recent progress in the development of reagents and techniques for super-resolution single-molecule localization CLEM and their applications to biological problems.

Intracellular signaling processes are frequently based on direct interactions between proteins and organelles. A fundamental strategy to elucidate the physiological significance of such interactions is to utilize optical dimerization tools. These tools are based on the use of small proteins or domains that interact with each other upon light illumination. Optical dimerizers are particularly suitable for reproducing and interrogating a given protein‐protein interaction and for investigating a protein's intracellular role in a spatially and temporally precise manner. Described in this article are genetic engineering strategies for the generation of modular light‐activatable protein dimerization units and instructions for the preparation of optogenetic applications in mammalian cells. Detailed protocols are provided for the use of light‐tunable switches to regulate protein recruitment to intracellular compartments, induce intracellular organellar membrane tethering, and reconstitute protein function using enhanced Magnets (eMags), a recently engineered optical dimerization system. © 2021 Wiley Periodicals LLC.

To truly understand biological systems, one must possess the ability to selectively manipulate their parts and observe the outcome. (For purposes of this review, we refer mostly to targets of neuroscience; however, the principles covered here largely extend to myriad samples from microbes to plants to the intestine, etc.).

Drugs are the most commonly employed way of introducing such perturbations, but they act on endogenous proteins that frequently exist in multiple cell types, complicating the interpretation of experiments. Whatever the applied stimulus, it is best to introduce optimized exogenous reagents into the systems under studydenabling manipulations to be targeted to speci!c cells and pathways. (It is also possible to target manipulations through other means, such as drugs that acquire cell-type speci!city through targeting via antibodies and/or cell surface receptor ligands, but as far as we are aware, existing reagents fall short in terms of necessary speci!city.) Many types of perturbations are useful in living systems and can be divided into rough categories such as the following: depolarize or hyperpolarize cells, induce or repress the activity of a speci!c pathway, induce or inhibit expression of a particular gene, activate or repress a speci!c protein, degrade a speci!c protein, etc. User-supplied triggers for such manipulations to occur include the following: addition of a small molecule (“chemogenetics”dideally inert on endogenous proteins) [1], sound waves (“sonogenetics”) [2], alteration of temperature (“thermogenetics”d almost exclusively used for small invertebrates) [3], and light (“optogenetics”). There are reports of using magnetic !elds (“magnetogenetics”) [4], but there is no evidence that such effects are reproducible or even physically possible [5,6]. Of these, the most commonly used, for multiple reasons, is light.

Many factors make light an ideal user-controlled stimulus for the manipulation of samples. Light is quickly delivered, and most light-sensitive proteins and other molecules respond quickly to light stimuli, making many optogenetic systems relatively rapid in comparison to, for instance, drug-modulated systems. Light is also quite easy to deliver in localized patterns, allowing for targeted stimulation. Multiple wavelengths can be delivered separately to distinct (or overlapping) regions, potentially allowing combinatorial control of diverse components. Finally, light can be delivered to shallow brain regions (and peripheral sites) relatively noninvasively, and to deeper brain regions with some effort.

However, there are also a number of shortcomings of using light for control. Robust and uniform penetration of light into the sample is the most signi!cant concern. For systems requiring modulation of many cells, particularly at depth, the use of systems controlled by small molecule drugs would generally be recommended instead of optogenetic approaches. When light is delivered through the use of !bers, lenses, or other optical devices, such interventions can produce signi!- cant cellular death, scar formation, and biofouling. The foreign-body response of tissue to objects triggers substantial molecular alterations, the implications of which are incompletely de!ned, but can involve reactive astrogliosis, oxidative stress, and perturbed vascularization. Head-mounted lightdelivery devices can be heavy and/or restrictive, and thus perturb behavior, particularly for small animals (e.g., mouse behavior is much more disrupted than rat behavior). More generally, all light causes tissue heating, which can have dramatic effects on cell health, physiology, and animal behavior. This is most concerning for tiny animals such as "ies. Light itself also damages tissue, most obviously through photochemistry (e.g., oxidation and radicalization) and photobleaching of critical endogenousmolecules. Furthermore, of course, light is ubiquitous, meaning that the sample is never completely unstimulated, despite precautions. Light passes through the eyes into the brain with surprising ease, and even through the skull with modest ef!cacy [7]dwhich can disrupt animal behavior (as can the converse: stimulating light in the brain perceived as a visual stimulus through the back of the eyes.) Light-responsive proteins exist in all samples, particularly in the eyes but to some extent in all tissuesdnotably, deep-brain photoreceptors [8].

The use of optogenetic tools has accelerated research on many fronts in disparate !elds. Additional, perhaps most, limitations on the utility of optogenetics must, however, be placed squarely on the shortcomings of the current suite of tools (and potential inherent limits in their performance.) The vast majority of optogenetic effectors are gated by blue light, which has signi!cant penetration issues and can be phototoxic under high intensity; redder wavelengths would in general be preferred. Furthermore, multiplexing requires tools making use of other parts of the visible spectrum (and redder wavelengths). A related issue is that most chromophores for optogenetic reagents have very broad action spectra (w250 nm bandwidth for retinal; w200 nm bandwidth for "avin), complicating both multiplexing and their use alongside many optical imaging reagentsdnarrower action spectra would be preferred for effectors in most situations. More generally, the current classes of optogenetic effectors are few, mostly limited to (1) channels and pumps (most with poor ion selectivity), (2) dimerizers, and (3) a handful of enzymes. The number of optogenetic tools that perform a very speci!c function in cells is small. Although progress has undeniably been made, much additional research and engineering will be required to dramatically expand the optogenetic toolkit.

Rather than providing a survey of research !ndings, this review covers general considerations of optogenetics experiments, and then focuses largely on molecular tools: the existing suite, their features and limitations, and goals for the creation and validation of additional reagents.

Fold-switching proteins challenge the one-sequence-one-structure paradigm by adopting multiple stable folds. Nevertheless, it is uncertain whether fold switchers are naturally pervasive or rare exceptions to the well-established rule. To address this question, we developed a predictive method and applied it to the NusG superfamily of >15,000 transcription factors. We predicted that a substantial population (25%) of the proteins in this family switch folds. Circular dichroism and nuclear magnetic resonance spectroscopies of 10 sequence-diverse variants confirmed our predictions. Thus, we leveraged family-wide predictions to determine both conserved contacts and taxonomic distributions of fold-switching proteins. Our results indicate that fold switching is pervasive in the NusG superfamily and that the single-fold paradigm significantly biases structure-prediction strategies.

COVID-19 has severely impacted socioeconomically disadvantaged populations. To support pandemic control strategies, geographically weighted negative binomial regression (GWNBR) mapped COVID-19 risk related to epidemiological and socioeconomic risk factors using South Korean incidence data (January 20, 2020 to July 1, 2020). We constructed COVID-19-specific socioeconomic and epidemiological themes using established social theoretical frameworks and created composite indexes through principal component analysis. The risk of COVID-19 increased with higher area morbidity, risky health behaviours, crowding, and population mobility, and with lower social distancing, healthcare access, and education. Falling COVID-19 risks and spatial shifts over three consecutive time periods reflected effective public health interventions. This study provides a globally replicable methodological framework and precision mapping for COVID-19 and future pandemics.

3D snapshot microscopy enables fast volumetric imaging by capturing a 3D volume in a single 2D camera image and performing computational reconstruction. Fast volumetric imaging has a variety of biological applications such as whole brain imaging of rapid neural activity in larval zebrafish. The optimal microscope design for this optical 3D-to-2D encoding is both sample- and task-dependent, with no general solution known. Deep learning based decoders can be combined with a differentiable simulation of an optical encoder for end-to-end optimization of both the deep learning decoder and optical encoder. This technique has been used to engineer local optical encoders for other problems such as depth estimation, 3D particle localization, and lensless photography. However, 3D snapshot microscopy is known to require a highly non-local optical encoder which existing UNet-based decoders are not able to engineer. We show that a neural network architecture based on global kernel Fourier convolutional neural networks can efficiently decode information from multiple depths in a volume, globally encoded across a 3D snapshot image. We show in simulation that our proposed networks succeed in engineering and reconstructing optical encoders for 3D snapshot microscopy where the existing state-of-the-art UNet architecture fails. We also show that our networks outperform the state-of-the-art learned reconstruction algorithms for a computational photography dataset collected on a prototype lensless camera which also uses a highly non-local optical encoding.

Expansion microscopy (ExM) is a method to expand biological specimens ~fourfold in each dimension by embedding in a hyper-swellable gel material. The expansion is uniform across observable length scales, enabling imaging of structures previously too small to resolve. ExM is compatible with any microscope and does not require expensive materials or specialized software, offering effectively sub-diffraction-limited imaging capabilities to labs that are not equipped to use traditional super-resolution imaging methods. Expanded specimens are ~99% water, resulting in strongly reduced optical scattering and enabling imaging of sub-diffraction-limited structures throughout specimens up to several hundred microns in (pre-expansion) thickness.

Modern morphological and structural studies are coming to a new level by incorporating the latest methods of three-dimensional electron microscopy (3D-EM). One of the key problems for the wide usage of these methods is posed by difficulties with sample preparation, since the methods work poorly with heterogeneous (consisting of tissues different in structure and in chemical composition) samples and require expensive equipment and usually much time. We have developed a simple protocol allows preparing heterogeneous biological samples suitable for 3D-EM in a laboratory that has a standard supply of equipment and reagents for electron microscopy. This protocol, combined with focused ion-beam scanning electron microscopy, makes it possible to study 3D ultrastructure of complex biological samples, e.g., whole insect heads, over their entire volume at the cellular and subcellular levels. The protocol provides new opportunities for many areas of study, including connectomics.

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.