Nanostructure Initiator Mass Spectrometry: Tissue Imaging and Direct Biofluid Analysis

Yanes, Óscar; Woo, Hin-Koon; Northen, Trent; Oppenheimer, Stacey R.; Shriver, Leah P.; Apon, J. M. B.; Estrada, Mayra N.; Potchoiba, Michael J.; Steenwyk, Rick C.; Manchester, Marianne; Siuzdak, Gary

doi:10.1021/ac802576q

Cited by 114 publications

(142 citation statements)

References 34 publications

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“…Along with attempts to apply SIMS to biological samples, 8 recently other IMS techniques have been developed and successfully applied in biology, including desorption electrospray ionization (DESI), 9 graphite-assisted laser desorption/ ionization (GALDI), 10 laser ablation electrospray ionization (LAESI), 11 and nanostructure-initiator mass spectrometry (NIMS). 12 Surface enhanced laser desorption ionization (SELDI)-IMS was shown to be useful in histological analysis. 13 Despite the impressive technological advance of MALDIimaging and other IMS techniques, at the present time only a few papers have been published concerned with computational methods for MALDI-imaging data.…”

Section: Introductionmentioning

confidence: 99%

Spatial Segmentation of Imaging Mass Spectrometry Data with Edge-Preserving Image Denoising and Clustering

et al. 2010

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In recent years, matrix-assisted laser desorption/ionization (MALDI)-imaging mass spectrometry has become a mature technology, allowing for reproducible high-resolution measurements to localize proteins and smaller molecules. However, despite this impressive technological advance, only a few papers have been published concerned with computational methods for MALDI-imaging data. We address this issue proposing a new procedure for spatial segmentation of MALDI-imaging data sets. This procedure clusters all spectra into different groups based on their similarity. This partition is represented by a segmentation map, which helps to understand the spatial structure of the sample. The core of our segmentation procedure is the edge-preserving denoising of images corresponding to specific masses that reduces pixel-to-pixel variability and improves the segmentation map significantly. Moreover, before applying denoising, we reduce the data set selecting peaks appearing in at least 1% of spectra. High dimensional discriminant clustering completes the procedure. We analyzed two data sets using the proposed pipeline. First, for a rat brain coronal section the calculated segmentation maps highlight the anatomical and functional structure of the brain. Second, a section of a neuroendocrine tumor invading the small intestine was interpreted where the tumor area was discriminated and functionally similar regions were indicated.

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Section: Introductionmentioning

confidence: 99%

Spatial Segmentation of Imaging Mass Spectrometry Data with Edge-Preserving Image Denoising and Clustering

et al. 2010

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“…Some encouraging matrix-free strategies to overcome this issue have been introduced, such as nanostructure initiator mass spectrometry (NIMS) [33,34] and laser desorption/ionisation on porous silicon (DIOS) [35]; in addition to several ambient ionisation platforms that require minimal sample preparation.…”

Section: Maldi-imaging Sample Preparationmentioning

confidence: 99%

Foodomics imaging by mass spectrometry and magnetic resonance

et al. 2016

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This work explores the use of advanced imaging MS (IMS) and magnetic resonance imaging (MRI) techniques in food science and nutrition to evaluate food sensory characteristics, nutritional value and health benefits. Determining the chemical content and applying imaging tools to food metabolomics offer detailed information about food quality, safety, processing, storage and authenticity assessment. IMS and MRI are powerful analytical systems with an excellent capability for mapping the distribution of many molecules, and recent advances in these platforms are reviewed and discussed, showing the great potential of these techniques for small molecule-based food metabolomics research.

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“…It has been applied for the analysis of broad range of analytes such as single cells, metabolites, and peptides (Northen et al, 2007). It has also been applied in mass spectrometric imaging studies (Yanes et al, 2009). In a recent study by Gulbakan et al (2010), anodic nanoporous alumina was used efficiently to make well-ordered nanowell array surfaces.…”

Section: Nanostructured Surfacesmentioning

confidence: 99%

Post-Genomics Nanotechnology Is Gaining Momentum: Nanoproteomics and Applications in Life Sciences

Kobeissy

Gülbakan

Alawieh

et al. 2014

OMICS: A Journal of Integrative Biology

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The post-genomics era has brought about new Omics biotechnologies, such as proteomics and metabolomics, as well as their novel applications to personal genomics and the quantified self. These advances are now also catalyzing other and newer post-genomics innovations, leading to convergences between Omics and nanotechnology. In this work, we systematically contextualize and exemplify an emerging strand of post-genomics life sciences, namely, nanoproteomics and its applications in health and integrative biological systems. Nanotechnology has been utilized as a complementary component to revolutionize proteomics through different kinds of nanotechnology applications, including nanoporous structures, functionalized nanoparticles, quantum dots, and polymeric nanostructures. Those applications, though still in their infancy, have led to several highly sensitive diagnostics and new methods of drug delivery and targeted therapy for clinical use. The present article differs from previous analyses of nanoproteomics in that it offers an in-depth and comparative evaluation of the attendant biotechnology portfolio and their applications as seen through the lens of post-genomics life sciences and biomedicine. These include: (1) immunosensors for inflammatory, pathogenic, and autoimmune markers for infectious and autoimmune diseases, (2) amplified immunoassays for detection of cancer biomarkers, and (3) methods for targeted therapy and automatically adjusted drug delivery such as in experimental stroke and brain injury studies. As nanoproteomics becomes available both to the clinician at the bedside and the citizens who are increasingly interested in access to novel post-genomics diagnostics through initiatives such as the quantified self, we anticipate further breakthroughs in personalized and targeted medicine.

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Nanostructure Initiator Mass Spectrometry: Tissue Imaging and Direct Biofluid Analysis

Cited by 114 publications

References 34 publications

Spatial Segmentation of Imaging Mass Spectrometry Data with Edge-Preserving Image Denoising and Clustering

Spatial Segmentation of Imaging Mass Spectrometry Data with Edge-Preserving Image Denoising and Clustering

Foodomics imaging by mass spectrometry and magnetic resonance

Post-Genomics Nanotechnology Is Gaining Momentum: Nanoproteomics and Applications in Life Sciences

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