Bleed-through correction for rendering and correlation analysis in multi-colour localization microscopy

A Light in the Dark: Uncovering Wolbachia-Host Interactions Using Fluorescence Imaging

The success of microbial endosymbionts, which reside naturally within a eukaryotic "host" organism, requires effective microbial interaction with, and manipulation of, the host cells. Fluorescence microscopy has played a key role in elucidating the molecular mechanisms of endosymbiosis. For 30 years, fluorescence analyses have been a cornerstone in studies of endosymbiotic Wolbachia bacteria, focused on host colonization, maternal transmission, reproductive parasitism, horizontal gene transfer, viral suppression, and metabolic interactions in arthropods and nematodes. Fluorescence-based studies stand to continue informing Wolbachia-host interactions in increasingly detailed and innovative ways.

Phosphatidylinositol 4,5-Bisphosphate Mediates the Co-Distribution of Influenza A Hemagglutinin and Matrix Protein M1 at the Plasma Membrane

The fully assembled influenza A virus (IAV) has on its surface the highest density of a single membrane protein found in nature-the glycoprotein hemagglutinin (HA) that mediates viral binding, entry, and assembly. HA clusters at the plasma membrane of infected cells, and the HA density (number of molecules per unit area) of these clusters correlates with the infectivity of the virus. Dense HA clusters are considered to mark the assembly site and ultimately lead to the budding of infectious IAV. The mechanism of spontaneous HA clustering, which occurs with or without other viral components, has not been elucidated. Using super-resolution fluorescence photoactivation localization microscopy (FPALM), we have previously shown that these HA clusters are interdependent on phosphatidylinositol 4,5-biphosphate (PIP2). Here, we show that the IAV matrix protein M1 co-clusters with PIP2, visualized using the pleckstrin homology domain. We find that cetylpyridinium chloride (CPC), which is a positively charged quaternary ammonium compound known for its antibacterial and antiviral properties at millimolar concentrations, disrupts M1 clustering and M1-PIP2 co-clustering at micromolar concentrations well below the critical micelle concentration (CMC). CPC also disrupts the co-clustering of M1 with HA at the plasma membrane, suggesting the role of host cell PIP2 clusters as scaffolds for gathering and concentrating M1 and HA to achieve their unusually high cluster densities in the IAV envelope.

Identification of cell types in multiplexed in situ images by combining protein expression and spatial information using CELESTA

Advances in multiplexed in situ imaging are revealing important insights in spatial biology. However, cell type identification remains a major challenge in imaging analysis, with most existing methods involving substantial manual assessment and subjective decisions for thousands of cells. We developed an unsupervised machine learning algorithm, CELESTA, which identifies the cell type of each cell, individually, using the cell's marker expression profile and, when needed, its spatial information. We demonstrate the performance of CELESTA on multiplexed immunofluorescence images of colorectal cancer and head and neck squamous cell carcinoma (HNSCC). Using the cell types identified by CELESTA, we identify tissue architecture associated with lymph node metastasis in HNSCC, and validate our findings in an independent cohort. By coupling our spatial analysis with single-cell RNA-sequencing data on proximal sections of the same specimens, we identify cell-cell crosstalk associated with lymph node metastasis, demonstrating the power of CELESTA to facilitate identification of clinically relevant interactions.

Cetylpyridinium chloride (CPC) reduces zebrafish mortality from influenza infection: Super-resolution microscopy reveals CPC interference with multiple protein interactions with phosphatidylinositol 4,5-bisphosphate in immune function

The COVID-19 pandemic raises significance for a potential influenza therapeutic compound, cetylpyridinium chloride (CPC), which has been extensively used in personal care products as a positively-charged quaternary ammonium antibacterial agent. CPC is currently in clinical trials to assess its effects on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) morbidity. Two published studies have provided mouse and human data indicating that CPC may alleviate influenza infection, and here we show that CPC (0.1 μM, 1 h) reduces zebrafish mortality and viral load following influenza infection. However, CPC mechanisms of action upon viral-host cell interaction are currently unknown. We have utilized super-resolution fluorescence photoactivation localization microscopy to probe the mode of CPC action. Reduction in density of influenza viral protein hemagglutinin (HA) clusters is known to reduce influenza infectivity: here, we show that CPC (at non-cytotoxic doses, 5-10 μM) reduces HA density and number of HA molecules per cluster within the plasma membrane of NIH-3T3 mouse fibroblasts. HA is known to colocalize with the negatively-charged mammalian lipid phosphatidylinositol 4,5-bisphosphate (PIP2); here, we show that nanoscale co-localization of HA with the PIP2-binding Pleckstrin homology (PH) reporter in the plasma membrane is diminished by CPC. CPC also dramatically displaces the PIP2-binding protein myristoylated alanine-rich C-kinase substrate (MARCKS) from the plasma membrane of rat RBL-2H3 mast cells; this disruption of PIP2 is correlated with inhibition of mast cell degranulation. Together, these findings offer a PIP2-focused mechanism underlying CPC disruption of influenza and suggest potential pharmacological use of this drug as an influenza therapeutic to reduce global deaths from viral disease.

Localization-Based Super-Resolution Microscopy Reveals Relationship between SARS-CoV2 Spike and Phosphatidylinositol (4,5)-bisphosphate

Localization microscopy circumvents the diffraction limit by identifying and measuring the positions of numerous subsets of individual fluorescent molecules, ultimately producing an image whose resolution depends on the uncertainty and density of localization, and whose capabilities are compatible with imaging living specimens. Spectral resolution can be improved by incorporating a dichroic or dispersive element in the detection path of a localization microscope, which can be useful for separation of multiple probes imaged simultaneously and for detection of changes in emission spectra of fluorophores resulting from changes in their environment. These methodological advances enable new biological applications, which in turn motivate new questions and technical innovations. As examples, we present fixed-cell imaging of the spike protein SARS-CoV2 (S) and its interactions with host cell components. Results show a relationship between S and the lipid phosphatidylinositol (4,5)-bisphosphate (PIP2). These findings have ramifications for several existing models of plasma membrane organization.

Challenges facing quantitative large-scale optical super-resolution, and some simple solutions

Optical super-resolution microscopy (SRM) has enabled biologists to visualize cellular structures with near-molecular resolution, giving unprecedented access to details about the amounts, sizes, and spatial distributions of macromolecules in the cell. Precisely quantifying these molecular details requires large datasets of high-quality, reproducible SRM images. In this review, we discuss the unique set of challenges facing quantitative SRM, giving particular attention to the shortcomings of conventional specimen preparation techniques and the necessity for optimal labeling of molecular targets. We further discuss the obstacles to scaling SRM methods, such as lengthy image acquisition and complex SRM data analysis. For each of these challenges, we review the recent advances in the field that circumvent these pitfalls and provide practical advice to biologists for optimizing SRM experiments.

CorRelator: Interactive software for real-time high precision cryo-correlative light and electron microscopy

Cryo-correlative light and electron microscopy (CLEM) is a technique that uses the spatiotemporal cues from fluorescence light microscopy (FLM) to investigate the high-resolution ultrastructure of biological samples by cryo-electron microscopy (cryo-EM). Cryo-CLEM provides advantages for identifying and distinguishing fluorescently labeled proteins, macromolecular complexes, and organelles from the cellular environment. Challenges remain on how correlation workflows and software tools are implemented on different microscope platforms to support automated cryo-EM data acquisition. Here, we present CorRelator: an open-source desktop application that bridges between cryo-FLM and real-time cryo-EM/ET automated data collection. CorRelator implements a pixel-coordinate-to-stage-position transformation for flexible, high accuracy on-the-fly and post-acquisition correlation. CorRelator can be integrated into cryo-CLEM workflows and easily adapted to standard fluorescence and transmission electron microscope (TEM) system configurations. CorRelator was benchmarked under live-cell and cryogenic conditions using several FLM and TEM instruments, demonstrating that CorRelator reliably supports real-time, automated correlative cryo-EM/ET acquisition, through a combination of software-aided and interactive alignment. CorRelator is a cross-platform software package featuring an intuitive Graphical User Interface (GUI) that guides the user through the correlation process. CorRelator source code is available at: https://github.com/wright-cemrc-projects/corr.

Fly-QMA: Automated analysis of mosaic imaginal discs in Drosophila

Mosaic analysis provides a means to probe developmental processes in situ by generating loss-of-function mutants within otherwise wildtype tissues. Combining these techniques with quantitative microscopy enables researchers to rigorously compare RNA or protein expression across the resultant clones. However, visual inspection of mosaic tissues remains common in the literature because quantification demands considerable labor and computational expertise. Practitioners must segment cell membranes or cell nuclei from a tissue and annotate the clones before their data are suitable for analysis. Here, we introduce Fly-QMA, a computational framework that automates each of these tasks for confocal microscopy images of Drosophila imaginal discs. The framework includes an unsupervised annotation algorithm that incorporates spatial context to inform the genetic identity of each cell. We use a combination of real and synthetic validation data to survey the performance of the annotation algorithm across a broad range of conditions. By contributing our framework to the open-source software ecosystem, we aim to contribute to the current move toward automated quantitative analysis among developmental biologists.

Navigating challenges in the application of superresolution microscopy

In 2014, the Nobel Prize in Chemistry was awarded to three scientists who have made groundbreaking contributions to the field of superresolution (SR) microscopy (SRM). The first commercial SR microscope came to market a decade earlier, and many other commercial options have followed. As commercialization has lowered the barrier to using SRM and the awarding of the Nobel Prize has drawn attention to these methods, biologists have begun adopting SRM to address a wide range of questions in many types of specimens. There is no shortage of reviews on the fundamental principles of SRM and the remarkable achievements made with these methods. We approach SRM from another direction: we focus on the current practical limitations and compromises that must be made when designing an SRM experiment. We provide information and resources to help biologists navigate through common pitfalls in SRM specimen preparation and optimization of image acquisition as well as errors and artifacts that may compromise the reproducibility of SRM data.

The Continuing Mystery of Lipid Rafts

Since its initial formalization nearly 20 years ago, the concept of lipid rafts has generated a tremendous amount of attention and interest and nearly as much controversy. The controversy is perhaps surprising because the notion itself is intuitive: compartmentalization in time and space is a ubiquitous theme at all scales of biology, and therefore, the partitioning of cellular membranes into lateral subdivision should be expected. Nevertheless, the physicochemical principles responsible for compartmentalization and the molecular mechanisms by which they are functionalized remain nearly as mysterious today as they were two decades ago. Herein, we review recent literature on this topic with a specific focus on the major open questions in the field including: (1) what are the best tools to assay raft behavior in living membranes? (2) what is the function of the complex lipidome of mammalian cells with respect to membrane organization? (3) what are the mechanisms that drive raft formation and determine their properties? (4) how can rafts be modulated? (5) how is membrane compartmentalization integrated into cellular signaling? Despite decades of intensive research, this compelling field remains full of fundamental questions.

Super-Resolution Imaging of Molecular Emission Spectra and Single Molecule Spectral Fluctuations

Localization microscopy can image nanoscale cellular details. To address biological questions, the ability to distinguish multiple molecular species simultaneously is invaluable. Here, we present a new version of fluorescence photoactivation localization microscopy (FPALM) which detects the emission spectrum of each localized molecule, and can quantify changes in emission spectrum of individual molecules over time. This information can allow for a dramatic increase in the number of different species simultaneously imaged in a sample, and can create super-resolution maps showing how single molecule emission spectra vary with position and time in a sample.

Far-red organic fluorophores contain a fluorescent impurity

Far-red organic fluorophores commonly used in traditional and super-resolution localization microscopy are found to contain a fluorescent impurity with green excitation and near-red emission. This near-red fluorescent impurity can interfere with some multicolor stochastic optical reconstruction microscopy/photoactivated localization microscopy measurements in live cells and produce subtle artifacts in chemically fixed cells. We additionally describe alternatives to avoid artifacts in super-resolution localization microscopy.

Progress in quantitative single-molecule localization microscopy

With the advent of single-molecule localization microscopy (SMLM) techniques, intracellular proteins can be imaged at unprecedented resolution with high specificity and contrast. These techniques can lead to a better understanding of cell functioning, as they allow, among other applications, counting the number of molecules of a protein specie in a single cell, studying the heterogeneity in protein spatial organization, and probing the spatial interactions between different protein species. However, the use of these techniques for accurate quantitative measurements requires corrections for multiple inherent sources of error, including: overcounting due to multiple localizations of a single fluorophore (i.e., photoblinking), undercounting caused by incomplete photoconversion, uncertainty in the localization of single molecules, sample drift during the long imaging time, and inaccurate image registration in the case of dual-color imaging. In this paper, we review recent efforts that address some of these sources of error in quantitative SMLM and give examples in the context of photoactivated localization microscopy (PALM).

Simultaneous multicolor imaging of biological structures with fluorescence photoactivation localization microscopy

Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.