Bradley C. Lowekamp

3D visualization of HIV transfer at the virological synapse between dendritic cells and T cells

The efficiency of HIV infection is greatly enhanced when the virus is delivered at conjugates between CD4+ T cells and virus-bearing antigen-presenting cells such as macrophages or dendritic cells via specialized structures known as virological synapses. Using ion abrasion SEM, electron tomography, and superresolution light microscopy, we have analyzed the spatial architecture of cell-cell contacts and distribution of HIV virions at virological synapses formed between mature dendritic cells and T cells. We demonstrate the striking envelopment of T cells by sheet-like membrane extensions derived from mature dendritic cells, resulting in a shielded region for formation of virological synapses. Within the synapse, filopodial extensions emanating from CD4+ T cells make contact with HIV virions sequestered deep within a 3D network of surface-accessible compartments in the dendritic cell. Viruses are detected at the membrane surfaces of both dendritic cells and T cells, but virions are not released passively at the synapse; instead, virus transfer requires the engagement of T-cell CD4 receptors. The relative seclusion of T cells from the extracellular milieu, the burial of the site of HIV transfer, and the receptor-dependent initiation of virion transfer by T cells highlight unique aspects of cell-cell HIV transmission.

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.

Correlative 3D imaging of Whole Mammalian Cells with Light and Electron Microscopy

We report methodological advances that extend the current capabilities of ion-abrasion scanning electron microscopy (IA-SEM), also known as focused ion beam scanning electron microscopy, a newly emerging technology for high resolution imaging of large biological specimens in 3D. We establish protocols that enable the routine generation of 3D image stacks of entire plastic-embedded mammalian cells by IA-SEM at resolutions of ∼10-20nm at high contrast and with minimal artifacts from the focused ion beam. We build on these advances by describing a detailed approach for carrying out correlative live confocal microscopy and IA-SEM on the same cells. Finally, we demonstrate that by combining correlative imaging with newly developed tools for automated image processing, small 100nm-sized entities such as HIV-1 or gold beads can be localized in SEM image stacks of whole mammalian cells. We anticipate that these methods will add to the arsenal of tools available for investigating mechanisms underlying host-pathogen interactions, and more generally, the 3D subcellular architecture of mammalian cells and tissues.

The Design of SimpleITK

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

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

Methylmalonic acidemia is a lethal inborn error of metabolism that causes mitochondrial impairment, multi-organ dysfunction and a shortened lifespan. Previous transmission electron microscope studies of thin sections from normal (Mut(+/+)) and diseased (Mut(-/-)) tissue found that the mitochondria appear to occupy a progressively larger volume of mutant cells with age, becoming megamitochondria. To assess changes in shape and volume of mitochondria resulting from the mutation, we carried out ion-abrasion scanning electron microscopy (IA-SEM), a method for 3D imaging that involves the iterative use of a focused gallium ion beam to abrade the surface of the specimen, and a scanning electron beam to image the newly exposed surface. Using IA-SEM, we show that mitochondria are more convoluted and have a broader distribution of sizes in the mutant tissue. Compared to normal cells, mitochondria from mutant cells have a larger surface-area-to-volume ratio, which can be attributed to their convoluted shape and not to their elongation or reduced volume. The 3D imaging approach and image analysis described here could therefore be useful as a diagnostic tool for the evaluation of disease progression in aberrant cells at resolutions higher than that currently achieved using confocal light microscopy.

SimpleITK Image-Analysis Notebooks: a Collaborative Environment for Education and Reproducible Research

Modern scientific endeavors increasingly require team collaborations to construct and interpret complex computational workflows. This work describes an image-analysis environment that supports the use of computational tools that facilitate reproducible research and support scientists with varying levels of software development skills. The Jupyter notebook web application is the basis of an environment that enables flexible, well-documented, and reproducible workflows via literate programming. Image-analysis software development is made accessible to scientists with varying levels of programming experience via the use of the SimpleITK toolkit, a simplified interface to the Insight Segmentation and Registration Toolkit. Additional features of the development environment include user friendly data sharing using online data repositories and a testing framework that facilitates code maintenance. SimpleITK provides a large number of examples illustrating educational and research-oriented image analysis workflows for free download from GitHub under an Apache 2.0 license: github.com/InsightSoftwareConsortium/SimpleITK-Notebooks.

Hierarchically partitioned implicit surfaces for interpolating large point set models

We present a novel hierarchical spatial partitioning method for creating interpolating implicit surfaces using compactly supported radial basis functions (RBFs) from scattered surface data. From this hierarchy of functions we can create a range of models from coarse to fine, where a coarse model approximates and a fine model interpolates. Furthermore, our method elegantly handles irregularly sampled data and hole filling because of its multiresolutional approach. Like related methods, we combine neighboring patches without surface discontinuities by overlapping their embedding functions. However, unlike partition-of-unity approaches we do not require an additional explicit blending function to combine patches. Rather, we take advantage of the compact extent of the basis functions to directly solve for each patchs embedding function in a way that does not cause error in neighboring patches. Avoiding overlap error is accomplished by adding phantom constraints to each patch at locations where a neighboring patch has regular constraints within the area of overlap (the functions radius of support). Phantom constraints are also used to ensure the correct results between different levels of the hierarchy. This approach leads to efficient evaluation because we can combine the relevant embedding functions at each point through simple summation. We demonstrate our method on the Thai statue from the Stanford 3D Scanning Repository. Using hierarchical compactly supported RBFs we interpolate all 5 million vertices of the model.

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.

Accelerating Discovery in 3D Microanalysis: Leveraging Open Source Software and Deskside High Performance Computing

The recent decade has seen a dramatic elevation in the computing power affordably and routinely available to biological laboratories. Computing cores in servers, desk-side, and even laptop computers have doubled in number and capability on the order of every two years, making workstations today the rivals of supercomputers from the year 2000. 64-bit processors have substantially increased addressable main memory, and computational analysis can now keep pace with the growing size of datasets. Commensurately, the operation of the microscopes has become increasing sophisticated, evolving from analog consoles to digital interfaces. These developments enable the automation of image collection, storage and quantitative analysis of the resulting data. Inexpensive storage and high bandwidth in digital networks promote the sharing of data and broad multidisciplinary interaction among research groups.