scholarly journals Cryo-OrbiSIMS for 3D molecular imaging of a bacterial biofilm in its native state

2019 ◽  
Author(s):  
Junting Zhang ◽  
James Brown ◽  
David Scurr ◽  
Anwen Bullen ◽  
Kirsty MacLellan-Gibson ◽  
...  
Keyword(s):  
Molecular Imaging ◽  
High Spatial Resolution ◽  
Bacterial Biofilm ◽  
High Mass ◽  
Label Free ◽  
High Pressure Freezing ◽  
Native State ◽  
Sample Handling ◽  
Signalling Molecules ◽  
High Mass Resolution

AbstractWe describe a method for label-free molecular imaging of biological materials, preserved in a native state, by using an OrbiSIMS instrument equipped with cryogenic sample handling and developing a high-pressure freezing protocol compatible with mass spectrometry. We studied the 3D distribution of quorum sensing signalling molecules, nucleobases and bacterial membrane molecules, in a mature Pseudomonas aeruginosa biofilm, with high spatial-resolution and high mass-resolution.

scholarly journals Cryo-OrbiSIMS for 3D Molecular Imaging of a Bacterial Biofilm in Its Native State

2020 ◽  
Vol 92 (13) ◽  
pp. 9008-9015 ◽  
Author(s):  
Junting Zhang ◽  
James Brown ◽  
David J. Scurr ◽  
Anwen Bullen ◽  
Kirsty MacLellan-Gibson ◽  
...  
Keyword(s):  
Molecular Imaging ◽  
Bacterial Biofilm ◽  
Native State

scholarly journals Cryogenic OrbiSIMS Localizes Semi-Volatile Molecules in Biological Tissues

2019 ◽  
Author(s):  
Clare L. Newell ◽  
Jean-Luc Vorng ◽  
James I. MacRae ◽  
Ian S. Gilmore ◽  
Alex P. Gould
Keyword(s):  
Ion Beam ◽  
Biological Tissues ◽  
High Mass ◽  
Label Free ◽  
Vapor Pressures ◽  
Large Molecules ◽  
High Mass Resolution ◽  
High Vapor ◽  
Chemical Resolution ◽  
Resolution Imaging

AbstractOrbiSIMS is a recently developed instrument for label-free imaging of chemicals with micron spatial resolution and high mass resolution. Here we report a cryogenic workflow for OrbiSIMS (Cryo-OrbiSIMS) that improves chemical detection of lipids and other biomolecules in tissues. Cryo-OrbiSIMS decreases ion-beam induced fragmentation, allowing large molecules such as triglycerides to be more reliably identified. It also increases chemical coverage to include biomolecules with intermediate or high vapor pressures, such as free fatty acids and semi-volatile organic compounds (SVOCs). We find that Cryo-OrbiSIMS reveals the hitherto unknown localization patterns of SVOCs with high spatial and chemical resolution in diverse plant, animal and human tissues. We also show that Cryo-OrbiSIMS can be combined with genetic analysis to identify enzymes regulating SVOC metabolism. Cryo-OrbiSIMS is applicable to high resolution imaging of a wide variety of non-volatile and semi-volatile molecules across many areas of biomedicine.

High‐mass resolution molecular imaging of organic compounds on the surface of Murchison meteorite

2018 ◽  
Vol 54 (2) ◽  
pp. 452-468 ◽  
Author(s):  
Minako Hashiguchi ◽  
Hiroshi Naraoka
Keyword(s):  
Molecular Imaging ◽  
Organic Compounds ◽  
Mass Resolution ◽  
High Mass ◽  
Murchison Meteorite ◽  
High Mass Resolution

scholarly journals Exemplifying the Screening Power of Mass Spectrometry Imaging over Label-Based Technologies for Simultaneous Monitoring of Drug and Metabolite Distributions in Tissue Sections

2015 ◽  
Vol 21 (2) ◽  
pp. 187-193 ◽  
Author(s):  
Richard J. A. Goodwin ◽  
Anna Nilsson ◽  
C. Logan Mackay ◽  
John G. Swales ◽  
Maria K. Johansson ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Mass Spectrometry Imaging ◽  
Cyclic Peptide ◽  
Analysis Data ◽  
Resolving Power ◽  
High Mass ◽  
Whole Body ◽  
Ion Cyclotron Resonance ◽  
Label Free ◽  
Tissue Sections

Mass spectrometry imaging (MSI) provides pharmaceutical researchers with a suite of technologies to screen and assess compound distributions and relative abundances directly from tissue sections and offer insight into drug discovery–applicable queries such as blood-brain barrier access, tumor penetration/retention, and compound toxicity related to drug retention in specific organs/cell types. Label-free MSI offers advantages over label-based assays, such as quantitative whole-body autoradiography (QWBA), in the ability to simultaneously differentiate and monitor both drug and drug metabolites. Such discrimination is not possible by label-based assays if a drug metabolite still contains the radiolabel. Here, we present data exemplifying the advantages of MSI analysis. Data of the distribution of AZD2820, a therapeutic cyclic peptide, are related to corresponding QWBA data. Distribution of AZD2820 and two metabolites is achieved by MSI, which [14C]AZD2820 QWBA fails to differentiate. Furthermore, the high mass-resolving power of Fourier transform ion cyclotron resonance MS is used to separate closely associated ions.

New approach to 3‐D, high sensitivity, high mass resolution space plasma composition measurements

1990 ◽  
Vol 61 (10) ◽  
pp. 3095-3097 ◽  
Author(s):  
David J. McComas ◽  
Jane E. Nordholt
Keyword(s):  
High Sensitivity ◽  
Space Plasma ◽  
Mass Resolution ◽  
High Mass ◽  
Plasma Composition ◽  
New Approach ◽  
High Mass Resolution ◽  
Composition Measurements

Label-Free Measurement of Cell–Electrode Cleft Gap Distance with High Spatial Resolution Surface Plasmon Microscopy

ACS Nano ◽  
2014 ◽  
Vol 8 (12) ◽  
pp. 12612-12619 ◽  
Author(s):  
Koji Toma ◽  
Hiroshi Kano ◽  
Andreas Offenhäusser
Keyword(s):  
Surface Plasmon ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Label Free ◽  
Cell Electrode ◽  
Surface Plasmon Microscopy

Three-dimensional representation of metastable peaks at high mass resolution

1978 ◽  
Vol 13 (5) ◽  
pp. 243-247 ◽  
Author(s):  
Michael J. Lacey ◽  
Colin G. Macdonald
Keyword(s):  
Three Dimensional ◽  
Mass Resolution ◽  
High Mass ◽  
Dimensional Representation ◽  
Three Dimensional Representation ◽  
High Mass Resolution

scholarly journals Coarse Raman and optical diffraction tomographic imaging enable label-free phenotyping of isogenic breast cancer cells of varying metastatic potential

2020 ◽  
Author(s):  
Santosh Kumar Paidi ◽  
Vaani Shah ◽  
Piyush Raj ◽  
Kristine Glunde ◽  
Rishikesh Pandey ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Raman Spectroscopy ◽  
Molecular Imaging ◽  
Single Cell ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
Metastatic Potential ◽  
Optical Diffraction ◽  
Multivariate Curve Resolution ◽  
Label Free

AbstractIdentification of the metastatic potential represents one of the most important tasks for molecular imaging of cancer. While molecular imaging of metastases has witnessed substantial progress as an area of clinical inquiry, determining precisely what differentiates the metastatic phenotype has proven to be more elusive underscoring the need to marry emerging imaging techniques with tumor biology. In this study, we utilize both the morphological and molecular information provided by 3D optical diffraction tomography and Raman spectroscopy, respectively, to propose a label-free route for optical phenotyping of cancer cells at single-cell resolution. By using an isogenic panel of cell lines derived from MDA-MB-231 breast cancer cells that vary in their metastatic potential, we show that 3D refractive index tomograms can capture subtle morphological differences among the parental, circulating tumor cells, and lung metastatic cells. By leveraging the molecular specificity of Raman spectroscopy, we demonstrate that coarse Raman microscopy is capable of rapidly mapping a sufficient number of cells for training a random forest classifier that can accurately predict the metastatic potential of cells at a single-cell level. We also leverage multivariate curve resolution – alternating least squares decomposition of the spectral dataset to demarcate spectra from cytoplasm and nucleus, and test the feasibility of identifying metastatic phenotypes using the spectra only from the cytoplasmic and nuclear regions. Overall, our study provides a rationale for employing coarse Raman mapping to substantially reduce measurement time thereby enabling the acquisition of reasonably large training datasets that hold the key for label-free single-cell analysis and, consequently, for differentiation of indolent from aggressive phenotypes.

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