Single-molecule dynamics of enhanceosome assembly in embryonic stem cells.

Enhancer-binding pluripotency regulators (Sox2 and Oct4) play a seminal role in embryonic stem (ES) cell-specific gene regulation. Here, we combine in vivo and in vitro single-molecule imaging, transcription factor (TF) mutagenesis, and ChIP-exo mapping to determine how TFs dynamically search for and assemble on their cognate DNA target sites. We find that enhanceosome assembly is hierarchically ordered with kinetically favored Sox2 engaging the target DNA first, followed by assisted binding of Oct4. Sox2/Oct4 follow a trial-and-error sampling mechanism involving 84-97 events of 3D diffusion (3.3-3.7 s) interspersed with brief nonspecific collisions (0.75-0.9 s) before acquiring and dwelling at specific target DNA (12.0-14.6 s). Sox2 employs a 3D diffusion-dominated search mode facilitated by 1D sliding along open DNA to efficiently locate targets. Our findings also reveal fundamental aspects of gene and developmental regulation by fine-tuning TF dynamics and influence of the epigenome on target search parameters.

Multiview confocal super-resolution microscopy.

Confocal microscopy1 remains a major workhorse in biomedical optical microscopy owing to its reliability and flexibility in imaging various samples, but suffers from substantial point spread function anisotropy, diffraction-limited resolution, depth-dependent degradation in scattering samples and volumetric bleaching2. Here we address these problems, enhancing confocal microscopy performance from the sub-micrometre to millimetre spatial scale and the millisecond to hour temporal scale, improving both lateral and axial resolution more than twofold while simultaneously reducing phototoxicity. We achieve these gains using an integrated, four-pronged approach: (1) developing compact line scanners that enable sensitive, rapid, diffraction-limited imaging over large areas; (2) combining line-scanning with multiview imaging, developing reconstruction algorithms that improve resolution isotropy and recover signal otherwise lost to scattering; (3) adapting techniques from structured illumination microscopy, achieving super-resolution imaging in densely labelled, thick samples; (4) synergizing deep learning with these advances, further improving imaging speed, resolution and duration. We demonstrate these capabilities on more than 20 distinct fixed and live samples, including protein distributions in single cells; nuclei and developing neurons in Caenorhabditis elegans embryos, larvae and adults; myoblasts in imaginal disks of Drosophila wings; and mouse renal, oesophageal, cardiac and brain tissues.

Cell division machinery drives cell-specific gene activation during differentiation in Bacillus subtilis.

When faced with starvation, the bacterium Bacillus subtilis transforms itself into a dormant cell type called a "spore". Sporulation initiates with an asymmetric division event, which requires the relocation of the core divisome components FtsA and FtsZ, after which the sigma factor σF is exclusively activated in the smaller daughter cell. Compartment-specific activation of σF requires the SpoIIE phosphatase, which displays a biased localization on one side of the asymmetric division septum and associates with the structural protein DivIVA, but the mechanism by which this preferential localization is achieved is unclear. Here, we isolated a variant of DivIVA that indiscriminately activates σF in both daughter cells due to promiscuous localization of SpoIIE, which was corrected by overproduction of FtsA and FtsZ. We propose that the core components of the redeployed cell division machinery drive the asymmetric localization of DivIVA and SpoIIE to trigger the initiation of the sporulation program.

Incorporating the image formation process into deep learning improves network performance.

We present Richardson-Lucy network (RLN), a fast and lightweight deep learning method for three-dimensional fluorescence microscopy deconvolution. RLN combines the traditional Richardson-Lucy iteration with a fully convolutional network structure, establishing a connection to the image formation process and thereby improving network performance. Containing only roughly 16,000 parameters, RLN enables four- to 50-fold faster processing than purely data-driven networks with many more parameters. By visual and quantitative analysis, we show that RLN provides better deconvolution, better generalizability and fewer artifacts than other networks, especially along the axial dimension. RLN outperforms classic Richardson-Lucy deconvolution on volumes contaminated with severe out of focus fluorescence or noise and provides four- to sixfold faster reconstructions of large, cleared-tissue datasets than classic multi-view pipelines. We demonstrate RLN's performance on cells, tissues and embryos imaged with widefield-, light-sheet-, confocal- and super-resolution microscopy.

Real-time imaging of drug-induced trapping of cellular topoisomerases and poly(ADP-ribose) polymerase 1 at the single-molecule level.

Topoisomerases (TOP1, TOP2α, and ß) are nuclear enzymes crucial for virtually all aspects of DNA metabolisms. They also are the targets of important anti-tumor chemotherapeutics that act by trapping the otherwise reversible topoisomerase-DNA covalent complex intermediates (TOPccs) that are formed during their catalytic reactions, resulting in long-lived topoisomerase DNA-protein crosslinks (TOP-DPCs) that interfere with DNA transactions. The Poly(ADP-ribose) polymerase (PARP) family protein PARP1 is activated by DNA damage to recruit DNA repair proteins, and PARP inhibitors are another class of commonly used chemotherapeutics, which bind and trap PARP molecules on DNA. To date, the trapping of TOPccs and PARP by their respective inhibitors can only be measured by immune-biochemical methods in cells. Here, we developed an imaging-based approach enabling real-time monitoring of drug-induced trapping of TOPccs and PARP1 in live cells at the single-molecule level. Capitalizing on this approach, we calculated the fraction of self-fluorescence tag-labeled topoisomerases and PARP single-molecules that are trapped by their respective inhibitors in real time. This novel technique should help elucidate the molecular processes that repair TOPcc and PARP trapping and facilitate the development of novel topoisomerase and PARP inhibitor-based therapies.

Three-dimensional residual channel attention networks denoise and sharpen fluorescence microscopy image volumes.

We demonstrate residual channel attention networks (RCAN) for the restoration and enhancement of volumetric time-lapse (four-dimensional) fluorescence microscopy data. First we modify RCAN to handle image volumes, showing that our network enables denoising competitive with three other state-of-the-art neural networks. We use RCAN to restore noisy four-dimensional super-resolution data, enabling image capture of over tens of thousands of images (thousands of volumes) without apparent photobleaching. Second, using simulations we show that RCAN enables resolution enhancement equivalent to, or better than, other networks. Third, we exploit RCAN for denoising and resolution improvement in confocal microscopy, enabling ~2.5-fold lateral resolution enhancement using stimulated emission depletion microscopy ground truth. Fourth, we develop methods to improve spatial resolution in structured illumination microscopy using expansion microscopy data as ground truth, achieving improvements of ~1.9-fold laterally and ~3.6-fold axially. Finally, we characterize the limits of denoising and resolution enhancement, suggesting practical benchmarks for evaluation and further enhancement of network performance.

The HIV-1 Viral Protease Is Activated during Assembly and Budding Prior to Particle Release.

HIV-1 encodes a viral protease that is essential for the maturation of infectious viral particles. While protease inhibitors are effective antiretroviral agents, recent studies have shown that prematurely activating, rather than inhibiting, protease function leads to the pyroptotic death of infected cells, with exciting implications for efforts to eradicate viral reservoirs. Despite 40 years of research into the kinetics of protease activation, it remains unclear exactly when protease becomes activated. Recent reports have estimated that protease activation occurs minutes to hours after viral release, suggesting that premature protease activation is challenging to induce efficiently. Here, monitoring viral protease activity with sensitive techniques, including nanoscale flow cytometry and instant structured illumination microscopy, we demonstrate that the viral protease is activated within cells prior to the release of free virions. Using genetic mutants that lock protease into a precursor conformation, we further show that both the precursor and mature protease have rapid activation kinetics and that the activity of the precursor protease is sufficient for viral fusion with target cells. Our finding that HIV-1 protease is activated within producer cells prior to release of free virions helps resolve a long-standing question of when protease is activated and suggests that only a modest acceleration of protease activation kinetics is required to induce potent and specific elimination of HIV-infected cells. IMPORTANCE HIV-1 protease inhibitors have been a mainstay of antiretroviral therapy for more than 2 decades. Although antiretroviral therapy is effective at controlling HIV-1 replication, persistent reservoirs of latently infected cells quickly reestablish replication if therapy is halted. A promising new strategy to eradicate the latent reservoir involves prematurely activating the viral protease, which leads to the pyroptotic killing of infected cells. Here, we use highly sensitive techniques to examine the kinetics of protease activation during and shortly after particle formation. We found that protease is fully activated before virus is released from the cell membrane, which is hours earlier than recent estimates. Our findings help resolve a long-standing debate as to when the viral protease is initially activated during viral assembly and confirm that prematurely activating HIV-1 protease is a viable strategy to eradicate infected cells following latency reversal.

Visualizing the translation and packaging of HIV-1 full-length RNA.

HIV-1 full-length RNA (HIV-1 RNA) plays a central role in viral replication, serving as a template for Gag/Gag-Pol translation and as a genome for the progeny virion. To gain a better understanding of the regulatory mechanisms of HIV-1 replication, we adapted a recently described system to visualize and track translation from individual HIV-1 RNA molecules in living cells. We found that, on average, half of the cytoplasmic HIV-1 RNAs are being actively translated at a given time. Furthermore, translating and nontranslating RNAs are well mixed in the cytoplasm; thus, Gag biogenesis occurs throughout the cytoplasm without being constrained to particular subcellular locations. Gag is an RNA binding protein that selects and packages HIV-1 RNA during virus assembly. A long-standing question in HIV-1 gene expression is whether Gag modulates HIV-1 RNA translation. We observed that despite its RNA-binding ability, Gag expression does not alter the proportion of translating HIV-1 RNA. Using single-molecule tracking, we found that both translating and nontranslating RNAs exhibit dynamic cytoplasmic movement and can reach the plasma membrane, the major HIV-1 assembly site. However, Gag selectively packages nontranslating RNA into the assembly complex. These studies illustrate that although HIV-1 RNA serves two functions, as a translation template and as a viral genome, individual RNA molecules carry out only one function at a time. These studies shed light on previously unknown aspects of HIV-1 gene expression and regulation.

A 2-dimensional ratchet model describes assembly initiation of a specialized bacterial cell surface.

Bacterial spores are dormant cells that are encased in a thick protein shell, the "coat," which participates in protecting the organism's DNA from environmental insults. The coat is composed of dozens of proteins that assemble in an orchestrated fashion during sporulation. In Bacillus subtilis, 2 proteins initiate coat assembly: SpoVM, which preferentially binds to micron-scale convex membranes and marks the surface of the developing spore as the site for coat assembly; and SpoIVA, a structural protein recruited by SpoVM that uses ATP hydrolysis to drive its irreversible polymerization around the developing spore. Here, we describe the initiation of coat assembly by SpoVM and SpoIVA. Using single-molecule fluorescence microscopy in vivo in sporulating cells and in vitro on synthetic spores, we report that SpoVM's localization is primarily driven by a lower off-rate on membranes of preferred curvature in the absence of other coat proteins. Recruitment and polymerization of SpoIVA results in the entrapment of SpoVM on the forespore surface. Using experimentally derived reaction parameters, we show that a 2-dimensional ratchet model can describe the interdependent localization dynamics of SpoVM and SpoIVA, wherein SpoVM displays a longer residence time on the forespore surface, which favors recruitment of SpoIVA to that location. Localized SpoIVA polymerization in turn prevents further sampling of other membranes by prelocalized SpoVM molecules. Our model therefore describes the dynamics of structural proteins as they localize and assemble at the correct place and time within a cell to form a supramolecular complex.

Single-shot super-resolution total internal reflection fluorescence microscopy.

We combined instant structured illumination microscopy (iSIM) with total internal reflection fluorescence microscopy (TIRFM) in an approach referred to as instant TIRF-SIM, thereby improving the lateral spatial resolution of TIRFM to 115 ± 13 nm without compromising speed, and enabling imaging frame rates up to 100 Hz over hundreds of time points. We applied instant TIRF-SIM to multiple live samples and achieved rapid, high-contrast super-resolution imaging close to the coverslip surface.

Gas chromatography-mass spectrometry based metabolomics profile of hippocampus and cerebellum in mice after chronic arsenic exposure.

Intake of arsenic (As) via drinking water has been a serious threat to global public health. Though there are numerous reports of As neurotoxicity, its pathogenesis mechanisms remain vague especially its chronic effects on metabolic network. Hippocampus is a renowned area in relation to learning and memory, whilst recently, cerebellum is argued to be involved with process of cognition. Therefore, the study aimed to explore metabolomics alternations in these two areas after chronic As exposure, with the purpose of further illustrating details of As neurotoxicity. Twelve 3-week-old male C57BL/6J mice were divided into two groups, receiving deionized drinking water (control group) or 50 mg/L of sodium arsenite (via drinking water) for 24 weeks. Learning and memory abilities were tested by Morris water maze (MWM) test. Pathological and morphological changes of hippocampus and cerebellum were captured via transmission electron microscopy (TEM). Metabolic alterations were analyzed by gas chromatography-mass spectrometry (GC-MS). MWM test confirmed impairments of learning and memory abilities of mice after chronic As exposure. Metabolomics identifications indicated that tyrosine increased and aspartic acid (Asp) decreased simultaneously in both hippocampus and cerebellum. Intermediates (succinic acid) and indirect involved components of tricarboxylic acid cycle (proline, cysteine, and alanine) were found declined in cerebellum, indicating disordered energy metabolism. Our findings suggest that these metabolite alterations are related to As-induced disorders of amino acids and energy metabolism, which might therefore, play an important part in mechanisms of As neurotoxicity.

A general method to improve fluorophores for live-cell and single-molecule microscopy.

Specific labeling of biomolecules with bright fluorophores is the keystone of fluorescence microscopy. Genetically encoded self-labeling tag proteins can be coupled to synthetic dyes inside living cells, resulting in brighter reporters than fluorescent proteins. Intracellular labeling using these techniques requires cell-permeable fluorescent ligands, however, limiting utility to a small number of classic fluorophores. Here we describe a simple structural modification that improves the brightness and photostability of dyes while preserving spectral properties and cell permeability. Inspired by molecular modeling, we replaced the N,N-dimethylamino substituents in tetramethylrhodamine with four-membered azetidine rings. This addition of two carbon atoms doubles the quantum efficiency and improves the photon yield of the dye in applications ranging from in vitro single-molecule measurements to super-resolution imaging. The novel substitution is generalizable, yielding a palette of chemical dyes with improved quantum efficiencies that spans the UV and visible range.

Whole-cell, multicolor superresolution imaging using volumetric multifocus microscopy.

Single molecule-based superresolution imaging has become an essential tool in modern cell biology. Because of the limited depth of field of optical imaging systems, one of the major challenges in superresolution imaging resides in capturing the 3D nanoscale morphology of the whole cell. Despite many previous attempts to extend the application of photo-activated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM) techniques into three dimensions, effective localization depths do not typically exceed 1.2 µm. Thus, 3D imaging of whole cells (or even large organelles) still demands sequential acquisition at different axial positions and, therefore, suffers from the combined effects of out-of-focus molecule activation (increased background) and bleaching (loss of detections). Here, we present the use of multifocus microscopy for volumetric multicolor superresolution imaging. By simultaneously imaging nine different focal planes, the multifocus microscope instantaneously captures the distribution of single molecules (either fluorescent proteins or synthetic dyes) throughout an ∼ 4-µm-deep volume, with lateral and axial localization precisions of ∼ 20 and 50 nm, respectively. The capabilities of multifocus microscopy to rapidly image the 3D organization of intracellular structures are illustrated by superresolution imaging of the mammalian mitochondrial network and yeast microtubules during cell division.

Fast multicolor 3D imaging using aberration-corrected multifocus microscopy.

Conventional acquisition of three-dimensional (3D) microscopy data requires sequential z scanning and is often too slow to capture biological events. We report an aberration-corrected multifocus microscopy method capable of producing an instant focal stack of nine 2D images. Appended to an epifluorescence microscope, the multifocus system enables high-resolution 3D imaging in multiple colors with single-molecule sensitivity, at speeds limited by the camera readout time of a single image.

Single-molecule tools elucidate H2A.Z nucleosome composition.

Although distinct epigenetic marks correlate with different chromatin states, how they are integrated within single nucleosomes to generate combinatorial signals remains largely unknown. We report the successful implementation of single molecule tools constituting fluorescence correlation spectroscopy (FCS), pulse interleave excitation-based Förster resonance energy transfer (PIE-FRET) and fluorescence lifetime imaging-based FRET (FLIM-FRET) to elucidate the composition of single nucleosomes containing histone variant H2A.Z (Htz1p in yeast) in vitro and in vivo. We demonstrate that yeast nucleosomes containing Htz1p are primarily composed of H4 K12ac and H3 K4me3 but not H3 K36me3 and that these patterns are conserved in mammalian cells. Quantification of epigenetic modifications in nucleosomes will provide a new dimension to epigenetics research and lead to a better understanding of how these patterns contribute to the targeting of chromatin-binding proteins and chromatin structure during gene regulation.

Modulation of Biophysical Properties of Nucleocapsid Protein in the Mutant Spectrum of SARS-CoV-2.

Genetic diversity is a hallmark of RNA viruses and the basis for their evolutionary success. Taking advantage of the uniquely large genomic database of SARS-CoV-2, we examine the impact of mutations across the spectrum of viable amino acid sequences on the biophysical phenotypes of the highly expressed and multifunctional nucleocapsid protein. We find variation in the physicochemical parameters of its extended intrinsically disordered regions (IDRs) sufficient to allow local plasticity, but also exhibiting functional constraints that similarly occur in related coronaviruses. In biophysical experiments with several N-protein species carrying mutations associated with major variants, we find that point mutations in the IDRs can have nonlocal impact and modulate thermodynamic stability, secondary structure, protein oligomeric state, particle formation, and liquid-liquid phase separation. In the Omicron variant, distant mutations in different IDRs have compensatory effects in shifting a delicate balance of interactions controlling protein assembly properties, and include the creation of a new protein-protein interaction interface in the N-terminal IDR through the defining P13L mutation. A picture emerges where genetic diversity is accompanied by significant variation in biophysical characteristics of functional N-protein species, in particular in the IDRs.

Modulation of biophysical properties of nucleocapsid protein in the mutant spectrum of SARS-CoV-2.

Genetic diversity is a hallmark of RNA viruses and the basis for their evolutionary success. Taking advantage of the uniquely large genomic database of SARS-CoV-2, we examine the impact of mutations across the spectrum of viable amino acid sequences on the biophysical phenotypes of the highly expressed and multifunctional nucleocapsid protein. We find variation in the physicochemical parameters of its extended intrinsically disordered regions (IDRs) sufficient to allow local plasticity, but also observe functional constraints that similarly occur in related coronaviruses. In biophysical experiments with several N-protein species carrying mutations associated with major variants, we find that point mutations in the IDRs can have nonlocal impact and modulate thermodynamic stability, secondary structure, protein oligomeric state, particle formation, and liquid-liquid phase separation. In the Omicron variant, distant mutations in different IDRs have compensatory effects in shifting a delicate balance of interactions controlling protein assembly properties, and include the creation of a new protein-protein interaction interface in the N-terminal IDR through the defining P13L mutation. A picture emerges where genetic diversity is accompanied by significant variation in biophysical characteristics of functional N-protein species, in particular in the IDRs.

Like other types of RNA viruses, the genetic material of SARS-CoV-2 (the agent responsible for COVID-19) is formed of an RNA molecule which is prone to accumulating mutations. This gives SARS-CoV-2 the ability to evolve quickly, and often to remain one step ahead of treatments. Understanding how these mutations shape the behavior of RNA viruses is therefore crucial to keep diseases such as COVID-19 under control. The gene that codes for the protein that 'packages' the genetic information inside SARS-CoV-2 is particularly prone to mutations. This nucleocapsid (N) protein participates in many key processes during the life cycle of the virus, including potentially interfering with the immune response. Exactly how the physical properties of the N-Protein are impacted by the mutations in its genetic sequence remains unclear. To investigate this question, Nguyen et al. predicted the various biophysical properties of different regions of the N-protein based on a computer-based analysis of SARS-CoV-2 genetic databases. This allowed them to determine if specific protein regions were positively or negatively charged in different mutants. The analyses showed that some domains exhibited great variability in their charge between protein variants ­ reflecting the fact that the corresponding genetic sequences showed high levels of plasticity. Other regions remained conserved, however, including across related coronaviruses. Nguyen et al. also conducted biochemical experiments on a range of N-proteins obtained from clinically relevant SARS-CoV-2 variants. Their results highlighted the importance of protein segments with no fixed three-dimensional structure. Mutations in the related sequences created high levels of variation in the physical properties of these 'intrinsically disordered' regions, which had wide-ranging consequences. Some of these genetic changes even gave individual N-proteins the ability to interact with each other in a completely new way. These results shed new light on the relationship between genetic mutations and the variable physical properties of RNA virus proteins. Nguyen et al. hope that this knowledge will eventually help to develop more effective treatments for viral infections.

Convolutional Neural Network Transformer (CNNT) for Fluorescence Microscopy image Denoising with Improved Generalization and Fast Adaptation.

Deep neural networks have been applied to improve the image quality of fluorescence microscopy imaging. Previous methods are based on convolutional neural networks (CNNs) which generally require more time-consuming training of separate models for each new imaging experiment, impairing the applicability and generalization. Once the model is trained (typically with tens to hundreds of image pairs) it can then be used to enhance new images that are like the training data. In this study, we proposed a novel imaging-transformer based model, Convolutional Neural Network Transformer (CNNT), to outperform the CNN networks for image denoising. In our scheme we have trained a single CNNT based "backbone model" from pairwise high-low SNR images for one type of fluorescence microscope (instance structured illumination, iSim). Fast adaption to new applications was achieved by fine-tuning the backbone on only 5-10 sample pairs per new experiment. Results show the CNNT backbone and fine-tuning scheme significantly reduces the training time and improves the image quality, outperformed training separate models using CNN approaches such as - RCAN and Noise2Fast. Here we show three examples of the efficacy of this approach on denoising wide-field, two-photon and confocal fluorescence data. In the confocal experiment, which is a 5×5 tiled acquisition, the fine-tuned CNNT model reduces the scan time form one hour to eight minutes, with improved quality.

Altruistic feeding and cell-cell signaling during bacterial differentiation actively enhance phenotypic heterogeneity.

Starvation triggers bacterial spore formation, a committed differentiation program that transforms a vegetative cell into a dormant spore. Cells in a population enter sporulation non-uniformly to secure against the possibility that favorable growth conditions, which puts sporulation-committed cells at a disadvantage, may resume. This heterogeneous behavior is initiated by a passive mechanism: stochastic activation of a master transcriptional regulator. Here, we identify a cell-cell communication pathway that actively promotes phenotypic heterogeneity, wherein Bacillus subtilis cells that start sporulating early utilize a calcineurin-like phosphoesterase to release glycerol, which simultaneously acts as a signaling molecule and a nutrient to delay non-sporulating cells from entering sporulation. This produced a more diverse population that was better poised to exploit a sudden influx of nutrients compared to those generating heterogeneity via stochastic gene expression alone. Although conflict systems are prevalent among microbes, genetically encoded cooperative behavior in unicellular organisms can evidently also boost inclusive fitness.

Three-dimensional spatio-angular fluorescence microscopy with a polarized dual-view inverted selective-plane illumination microscope (pol-diSPIM).

Polarized fluorescence microscopy is a valuable tool for measuring molecular orientations, but techniques for recovering three-dimensional orientations and positions of fluorescent ensembles are limited. We report a polarized dual-view light-sheet system for determining the three-dimensional orientations and diffraction-limited positions of ensembles of fluorescent dipoles that label biological structures, and we share a set of visualization, histogram, and profiling tools for interpreting these positions and orientations. We model our samples, their excitation, and their detection using coarse-grained representations we call orientation distribution functions (ODFs). We apply ODFs to create physics-informed models of image formation with spatio-angular point-spread and transfer functions. We use theory and experiment to conclude that light-sheet tilting is a necessary part of our design for recovering all three-dimensional orientations. We use our system to extend known two-dimensional results to three dimensions in FM1-43-labelled giant unilamellar vesicles, fast-scarlet-labelled cellulose in xylem cells, and phalloidin-labelled actin in U2OS cells. Additionally, we observe phalloidin-labelled actin in mouse fibroblasts grown on grids of labelled nanowires and identify correlations between local actin alignment and global cell-scale orientation, indicating cellular coordination across length scales.