IBEX:A versatile multiplex optical imaging approach for deep phenotyping and spatial analysis of cells in complex tissues

The diverse composition of mammalian tissues poses challenges for understanding the cell–cell interactions required for organ homeostasis and how spatial relationships are perturbed during disease. Existing methods such as single-cell genomics, lacking a spatial context, and traditional immunofluorescence, capturing only two to six molecular features, cannot resolve these issues. Imaging technologies have been developed to address these problems, but each possesses limitations that constrain widespread use. Here we report a method that overcomes major impediments to highly multiplex tissue imaging. “Iterative bleaching extends multiplexity” (IBEX) uses an iterative staining and chemical bleaching method to enable high-resolution imaging of >65 parameters in the same tissue section without physical degradation. IBEX can be employed with various types of conventional microscopes and permits use of both commercially available and user-generated antibodies in an “open” system to allow easy adjustment of staining panels based on ongoing marker discovery efforts. We show how IBEX can also be used with amplified staining methods for imaging strongly fixed tissues with limited epitope retention and with oligonucleotide-based staining, allowing potential cross-referencing between flow cytometry, cellular indexing of transcriptomes and epitopes by sequencing, and IBEX analysis of the same tissue. To facilitate data processing, we provide an open-source platform for automated registration of iterative images. IBEX thus represents a technology that can be rapidly integrated into most current laboratory workflows to achieve high-content imaging to reveal the complex cellular landscape of diverse organs and tissues

Ion-Abrasion Scanning Electron Microscopy Reveals Surface-Connected Tubular Conduits in HIV-Infected Macrophages

HIV-1-containing internal compartments are readily detected in images of thin sections from infected cells using conventional transmission electron microscopy, but the origin, connectivity, and 3D distribution of these compartments has remained controversial. Here, we report the 3D distribution of viruses in HIV-1-infected primary human macrophages using cryo-electron tomography and ion-abrasion scanning electron microscopy (IA-SEM), a recently developed approach for nanoscale 3D imaging of whole cells. Using IA-SEM, we show the presence of an extensive network of HIV-1-containing tubular compartments in infected macrophages, with diameters of ∼150–200 nm, and lengths of up to ∼5 µm that extend to the cell surface from vesicular compartments that contain assembling HIV-1 virions. These types of surface-connected tubular compartments are not observed in T cells infected with the 29/31 KE Gag-matrix mutant where the virus is targeted to multi-vesicular bodies and released into the extracellular medium. IA-SEM imaging also allows visualization of large sheet-like structures that extend outward from the surfaces of macrophages, which may bend and fold back to allow continual creation of viral compartments and virion-lined channels. This potential mechanism for efficient virus trafficking between the cell surface and interior may represent a subversion of pre-existing vesicular machinery for antigen capture, processing, sequestration, and presentation

The Design of SimpleITK

SimpleITK is a new interface to the Insight Segmentation and<br/>Registration Toolkit (ITK) designed to facilitate rapid prototyping, education<br/>and scientific activities, via high level programming<br/>languages. ITK is a templated C++ library of image processing<br/>algorithms and frameworks for biomedical and other applications, and<br/>it was designed to be generic, flexible and extensible. Initially, ITK<br/>provided a direct wrapping interface to languages such as Python and<br/>Tcl through the WrapITK system. Unlike WrapITK, which exposed ITK's<br/>complex templated interface, SimpleITK was designed to provide an easy<br/>to use and simplified interface to ITK's algorithms. It includes<br/>procedural methods, hides ITK's demand driven pipeline, and provides a<br/>template-less layer. Also SimpleITK provides practical conveniences<br/>such as binary distribution packages and overloaded operators. Our<br/>user-friendly design goals dictated a departure from the direct<br/>interface wrapping approach of WrapITK, towards a new facade<br/>class structure that only exposes the required functionality, hiding<br/>ITK's extensive template use. Internally SimpleITK utilizes a manual<br/>description of each filter with code-generation and advanced C++<br/>meta-programming to provide the higher-level interface, bringing the<br/>capabilities of ITK to a wider audience. SimpleITK is licensed as<br/>open source software under the Apache License Version 2.0 and more information<br/>about downloading it can be found at http://www.simpleitk.org

Image segmentation, registration and characterization in R with simpleITK

Many types of medical and scientific experiments acquire raw data in the form of images. Various forms of image processing and image analysis are used to transform the raw image data into quantitative measures that are the basis of subsequent statistical analysis. In this article we describe the SimpleITK R package. SimpleITK is a simplified interface to the insight segmentation and registration toolkit (ITK). ITK is an open source C++ toolkit that has been actively developed over the past 18 years and is widely used by the medical image analysis community. SimpleITK provides packages for many interpreter environments, including R. Currently, it includes several hundred classes for image analysis including a wide range of image input and output, filtering operations, and higher level components for segmentation and registration. Using SimpleITK, development of complex combinations of image and statistical analysis procedures is feasible. This article includes several examples of computational image analysis tasks implemented using SimpleITK, including spherical marker localization, multi-modal image registration, segmentation evaluation, and cell image analysis

Ion-abrasion scanning electron microscopy reveals distorted liver mitochondrial morphology in murine methylmalonic acidemia

Photograph of the interior of Oklahoma's First Legislative Hall