A detailed analysis of 3D subcellular signal localization

A rapid method for quantifying cytoplasmic versus nuclear localization in endogenous peripheral blood leukocytes by conventional flow cytometry

A biochemical system and method have been developed to enable the quantitative measurement of cytoplasmic versus nuclear localization within cells in whole blood. Compared with the analyses of nuclear localization by western blot or fluorescence microscopy, this system saves a lot of time and resources by eliminating the necessity of purification and culturing steps, and generates data that are free from the errors and artifacts associated with using tumor cell lines or calculating nuclear signals from 2D images. This user‐friendly system enables the analysis of cell signaling within peripheral blood cells in their endogenous environment, including measuring the kinetics of nuclear translocation for transcription factors without requiring protein modifications. We first demonstrated the efficiency and specificity of this system for targeting nuclear epitopes, and verified the results by fluorescence microscopy. Next, the power of the technique to analyze LPS‐induced signaling in peripheral blood monocytes was demonstrated. Finally, both FoxP3 localization and IL‐2‐induced STAT5 signaling in regulatory T cells were analyzed. We conclude that this system can be a useful tool for enabling multidimensional molecular‐biological analyses of cell signaling within endogenous peripheral blood cells by conventional flow cytometry. © 2017 The Authors. Cytometry Part A Published by Wiley Periodicals, Inc. on behalf of ISAC.

A novel toolbox to investigate tissue spatial organization applied to the study of the islets of Langerhans

Thanks to the development of new 3D Imaging techniques, volumetric data of thick samples, especially tissues, are commonly available. Several algorithms were proposed to analyze cells or nuclei in tissues, however these tools are limited to two dimensions. Within any given tissue, cells are not likely to be organized randomly and as such have specific patterns of cell-cell interaction forming complex communication networks. In this paper, we propose a new set of tools as an approach to segment and analyze tissues in 3D with single cell resolution. This new tool box can identify and compute the geographical location of single cells and analyze the potential physical interactions between different cell types and in 3D. As a proof-of-principle, we applied our methodology to investigation of the cyto-architecture of the islets of Langerhans in mice and monkeys. The results obtained here are a significant improvement in current methodologies and provides new insight into the organization of alpha cells and their cellular interactions within the islet’s cellular framework.

Regulation of TGF-β receptor hetero-oligomerization and signaling by endoglin

Endoglin is a modulator of TGF-β signaling in endothelial cells. We show that it forms stable homodimers serving as a scaffold for binding TβRII, ALK5, and ALK1. ALK1 and ALK5 bind endoglin differentially, with TβRII recruiting ALK5. Signaling data indicate a role for this receptor complex in balancing TGF-β signaling between Smad1/5/8 and Smad2/3.

Complex formation among transforming growth factor-β (TGF-β) receptors and its modulation by coreceptors represent an important level of regulation for TGF-β signaling. Oligomerization of ALK5 and the type II TGF-β receptor (TβRII) has been thoroughly investigated, both in vitro and in intact cells. However, such studies, especially in live cells, are missing for the endothelial cell coreceptor endoglin and for the ALK1 type I receptor, which enables endothelial cells to respond to TGF-β by activation of both Smad2/3 and Smad1/5/8. Here we combined immunoglobulin G–mediated immobilization of one cell-surface receptor with lateral mobility studies of a coexpressed receptor by fluorescence recovery after photobleaching (FRAP) to demonstrate that endoglin forms stable homodimers that function as a scaffold for binding TβRII, ALK5, and ALK1. ALK1 and ALK5 bind to endoglin with differential dependence on TβRII, which plays a major role in recruiting ALK5 to the complex. Signaling data indicate a role for the quaternary receptor complex in regulating the balance between TGF-β signaling to Smad1/5/8 and to Smad2/3.

TEMPy: a Python library for assessment of three-dimensional electron microscopy density fits

TEMPy is an object-oriented Python library that provides the means to validate density fits in electron microscopy reconstructions. This article highlights several features of particular interest for this purpose and includes some customized examples.

Three-dimensional electron microscopy is currently one of the most promising techniques used to study macromolecular assemblies. Rigid and flexible fitting of atomic models into density maps is often essential to gain further insights into the assemblies they represent. Currently, tools that facilitate the assessment of fitted atomic models and maps are needed. TEMPy (template and electron microscopy comparison using Python) is a toolkit designed for this purpose. The library includes a set of methods to assess density fits in intermediate-to-low resolution maps, both globally and locally. It also provides procedures for single-fit assessment, ensemble generation of fits, clustering, and multiple and consensus scoring, as well as plots and output files for visualization purposes to help the user in analysing rigid and flexible fits. The modular nature of TEMPy helps the integration of scoring and assessment of fits into large pipelines, making it a tool suitable for both novice and expert structural biologists.

Chemical biology-based approaches on fluorescent labeling of proteins in live cells

Recently, significant advances have been made in live cell imaging owing to the rapid development of selective labeling of proteins in vivo. Green fluorescent protein (GFP) was the first example of fluorescent reporters genetically introduced to protein of interest (POI). While GFP and various types of engineered fluorescent proteins (FPs) have been actively used for live cell imaging for many years, the size and the limited windows of fluorescent spectra of GFP and its variants set limits on possible applications. In order to complement FP-based labeling methods, alternative approaches that allow incorporation of synthetic fluorescent probes to target POIs were developed. Synthetic fluorescent probes are smaller than fluorescent proteins, often have improved photochemical properties, and offer a larger variety of colors. These synthetic probes can be introduced to POIs selectively by numerous approaches that can be largely categorized into chemical recognition-based labeling, which utilizes metal-chelating peptide tags and fluorophore-carrying metal complexes, and biological recognition-based labeling, such as (1) specific non-covalent binding between an enzyme tag and its fluorophore-carrying substrate, (2) self-modification of protein tags using substrate variants conjugated to fluorophores, (3) enzymatic reaction to generate a covalent binding between a small molecule substrate and a peptide tag, and (4) split-intein-based C-terminal labeling of target proteins. The chemical recognition-based labeling reaction often suffers from compromised selectivity of metal-ligand interaction in the cytosolic environment, consequently producing high background signals. Use of protein-substrate interactions or enzyme-mediated reactions generally shows improved specificity but each method has its limitations. Some examples are the presence of large linker protein, restriction on the choice of introducible probes due to the substrate specificity of enzymes, and competitive reaction mediated by an endogenous analogue of the introduced protein tag. These limitations have been addressed, in part, by the split-intein-based labeling approach, which introduces fluorescent probes with a minimal size (~4 amino acids) peptide tag. In this review, the advantages and the limitations of each labeling method are discussed.

Robust signal detection in 3D fluorescence microscopy

Robust detection and localization of biomolecules inside cells is of great importance to better understand the functions related to them. Fluorescence microscopy and specific staining methods make biomolecules appear as point-like signals on image data, often acquired in 3D. Visual detection of such point-like signals can be time consuming and problematic if the 3D images are large, containing many, sometimes overlapping, signals. This sets a demand for robust automated methods for accurate detection of signals in 3D fluorescence microscopy. We propose a new 3D point-source signal detection method that is based on Fourier series. The method consists of two parts, a detector, which is a cosine filter to enhance the point-like signals, and a verifier, which is a sine filter to validate the result from the detector. Compared to conventional methods, our method shows better robustness to noise and good ability to resolve signals that are spatially close. Tests on image data show that the method has equivalent accuracy in signal detection in comparison to visual detection by experts. The proposed method can be used as an efficient point-like signal detection tool for various types of biological 3D image data.