FIB-SEM imaging of carbon nanotubes in mouse lung tissue

Ultrastructural characterisation is important for understanding carbon nanotube (CNT) toxicity and how the CNTs interact with cells and tissues. The standard method for this involves using transmission electron microscopy (TEM). However, in particular, the sample preparation, using a microtome to cut thin sample sections for TEM, can be challenging for investigation of regions with agglomerations of large and stiff CNTs because the CNTs cut with difficulty. As a consequence, the sectioning diamond knife may be damaged and the uncut CNTs are left protruding from the embedded block surface excluding them from TEM analysis. To provide an alternative to ultramicrotomy and subsequent TEM imaging, we studied focused ion beam scanning electron microscopy (FIB-SEM) of CNTs in the lungs of mice, and we evaluated the applicability of the method compared to TEM. FIB-SEM can provide serial section volume imaging not easily obtained with TEM, but it is time-consuming to locate CNTs in the tissue. We demonstrate that protruding CNTs after ultramicrotomy can be used to locate the region of interest, and we present FIB-SEM images of CNTs in lung tissue. FIB-SEM imaging was applied to lung tissue from mice which had been intratracheally instilled with two different multiwalled CNTs; one being short and thin, and the other longer and thicker. FIB-SEM was found to be most suitable for detection of the large CNTs (Ø ca. 70 nm), and to be well suited for studying CNT agglomerates in biological samples which is challenging using standard TEM techniques. [Figure: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00216-013-7566-x) contains supplementary material, which is available to authorized users

Determination of Membrane Protein Transporter Oligomerization in Native Tissue Using Spatial Fluorescence Intensity Fluctuation Analysis

Membrane transporter proteins exist in a complex dynamic equilibrium between various oligomeric states that include monomers, dimers, dimer of dimers and higher order oligomers. Given their sub-optical microscopic resolution size, the oligomerization state of membrane transporters is difficult to quantify without requiring tissue disruption and indirect biochemical methods. Here we present the application of a fluorescence measurement technique which combines fluorescence image moment analysis and spatial intensity distribution analysis (SpIDA) to determine the oligomerization state of membrane proteins in situ. As a model system we analyzed the oligomeric state(s) of the electrogenic sodium bicarbonate cotransporter NBCe1-A in cultured cells and in rat kidney. The approaches that we describe offer for the first time the ability to investigate the oligomeric state of membrane transporter proteins in their native state

Developments in cell biology for quantitative immunoelectron microscopy based on thin sections: a review

Quantitative immunoelectron microscopy uses ultrathin sections and gold particle labelling to determine distributions of molecules across cell compartments. Here, we review a portfolio of new methods for comparing labelling distributions between different compartments in one study group (method 1) and between the same compartments in two or more groups (method 2). Specimen samples are selected unbiasedly and then observed and expected distributions of gold particles are estimated and compared by appropriate statistical procedures. The methods can be used to analyse gold label distributed between volume-occupying (organelle) and surface-occupying (membrane) compartments, but in method 1, membranes must be treated as organelles. With method 1, gold counts are combined with stereological estimators of compartment size to determine labelling density (LD). For volume-occupiers, LD can be expressed simply as golds per test point and, for surface-occupiers, as golds per test line intersection. Expected distributions are generated by randomly assigning gold particles to compartments and expressing observed/expected counts as a relative labelling index (RLI). Preferentially-labelled compartments are identified from their RLI values and by Chi-squared analysis of observed and expected distributions. For method 2, the raw gold particle counts distributed between compartments are simply compared across groups by contingency table and Chi-squared analysis. This identifies the main compartments responsible for the differences between group distributions. Finally, we discuss labelling efficiency (the number of gold particles per target molecule) and describe how it can be estimated for volume- or surface-occupiers by combining stereological data with biochemical determinations