Integrated molecular imaging technologies for investigation of metals in biological systems: A brief review

Abstract

Metals play an essential role in biological systems and are required as structural or catalytic co-factors in many proteins. Disruption of the homeostatic control and/or spatial distributions of metals can lead to disease. Imaging technologies have been developed to visualize elemental distributions across a biological sample. Measurement of elemental distributions by imaging mass spectrometry and imaging X-ray fluorescence are increasingly employed with technologies that can assess histological features and molecular compositions. Data from several modalities can be interrogated as multimodal images to correlate morphological, elemental, and molecular properties. Elemental and molecular distributions have also been axially resolved to achieve three-dimensional volumes, dramatically increasing the biological information. In this review, we provide an overview of recent developments in the field of metal imaging with an emphasis on multimodal studies in two and three dimensions. We specifically highlight studies that present technological advancements and biological applications of how metal homeostasis affects human health.

Keywords: 3D imaging; Data-driven image fusion; IMS; Image fusion; Imaging mass spectrometry; Integrated imaging; Metal imaging; Metallomics; Molecular imaging; Multimodal.

Figure 1:. Overview of recent studies employing elemental imaging in 2D.

A) Bright field microscopy images of sectioned bone (left) from two sample preparations (top and bottom). Images depicting the abundance of two lipids (m/z 760 in red, m/z 725 in green) as well as calcium distributions (blue) as detected by MALDI IMS and μXFI respectively are shown on the right. Adapted from Svirkova et al [38] B) NanoSIMS ion image overlay of copper (blue) and phosphorous (red) from zebrafish retina (left) and an electron micrograph of similar region (right) with false colored labels highlighting nuclei (red) and megamitochondria (blue). Inset, corresponds to one megamitochondrion and indicates co-localization of copper puncta and megamitochondria. Adapted from Ackerman et al [***]

Figure 2:. Data-driven image fusion applied to MALDI FT-ICR IMS of intact proteins from a S. aureus infected murine renal tissue section.

Multivariate linear regression is used to construct a cross modality model from H&E stained microscopy (1 μm spatial resolution) and MALDI FT-ICR IMS of intact proteins (75 μm spatial resolution, unknown protein at m/z 9,183.46, S100A8 at m/z 10,164.07) acquired from the same 7 day post S. aureus infected murine renal tissue section. The fused IMS-Microscopy data set enables prediction of protein ion images to higher spatial resolution (15 μm spatial resolution). Statistical measures of confidence are provided for both predictions (Reconstruction Scores) [46].

Figure 3:. Overview of recent studies employing elemental imaging in 3D.

A) Multimodal imaging of a murine kidney infected with S. aureus. Iron distribution (yellow, determined by LA-ICP-MS) and bacterial Fe-starvation dependent reporter activity (red sphere, assessed by BLI) are co-registered to blockface images. This image depicts one representative view of an entire 3D volume. Adapted from Cassat et al [***] B) μCT 3D renderings of C. dubia (a-b) and distribution of selected elements (calcium: red, manganese: green, zinc: blue) as determined by μ-XRF (c-d). Adapted from Van Malderen et al [**] C) μCT 3D image of Triticum aestivum. L. grain and elemental distribution throughout the sample as determined by LA-ICP-MS. Adapted from Van Malderen et al [55]