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Zhang C, Tian Z, Chen R, Rowan F, Qiu K, Sun Y, Guan JL, Diao J. Advanced imaging techniques for tracking drug dynamics at the subcellular level. Adv Drug Deliv Rev 2023; 199:114978. [PMID: 37385544 PMCID: PMC10527994 DOI: 10.1016/j.addr.2023.114978] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 06/17/2023] [Accepted: 06/26/2023] [Indexed: 07/01/2023]
Abstract
Optical microscopes are an important imaging tool that have effectively advanced the development of modern biomedicine. In recent years, super-resolution microscopy (SRM) has become one of the most popular techniques in the life sciences, especially in the field of living cell imaging. SRM has been used to solve many problems in basic biological research and has great potential in clinical application. In particular, the use of SRM to study drug delivery and kinetics at the subcellular level enables researchers to better study drugs' mechanisms of action and to assess the efficacy of their targets in vivo. The purpose of this paper is to review the recent advances in SRM and to highlight some of its applications in assessing subcellular drug dynamics.
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Affiliation(s)
- Chengying Zhang
- Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Zhiqi Tian
- Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Rui Chen
- Department of Chemistry, University of Cincinnati, Cincinnati, OH 45221, USA
| | - Fiona Rowan
- Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Kangqiang Qiu
- Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Yujie Sun
- Department of Chemistry, University of Cincinnati, Cincinnati, OH 45221, USA
| | - Jun-Lin Guan
- Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Jiajie Diao
- Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA.
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Brunet MA, Gorman BL, Kraft ML. Depth Correction of 3D NanoSIMS Images Shows Intracellular Lipid and Cholesterol Distributions while Capturing the Effects of Differential Sputter Rate. ACS NANO 2022; 16:16221-16233. [PMID: 36218061 DOI: 10.1021/acsnano.2c05148] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Knowledge of the distributions of drugs, metabolites, and drug carriers within cells is a prerequisite for the development of effective disease treatments. Intracellular component distribution may be imaged with high sensitivity and spatial resolution by using a NanoSIMS in the depth profiling mode. Depth correction strategies that capture the effects of differential sputtering without requiring additional measurements could enable producing accurate 3D NanoSIMS depth profiling images of intracellular component distributions. Here we describe an approach for depth correcting 3D NanoSIMS depth profiling images of cells that accounts for differential sputter rates. Our approach uses the secondary ion and secondary electron depth profiling images to reconstruct the cell's morphology at every raster plane. These cell morphology reconstructions are used to adjust the z-positions and heights of the voxels in the component-specific 3D NanoSIMS images. We validated this strategy using AFM topography data and reconstructions created from depth profiling images acquired with focused ion beam-secondary electron microscopy. Good agreement was found for the shapes and relative heights of the reconstructed morphologies. Application of this depth correction strategy to 3D NanoSIMS depth profiling images of a metabolically labeled cell better resolved the transport vesicles, organelles, and organellar membranes containing 18O-cholesterol and 15N-sphingolipids. Accurate 3D NanoSIMS images of intracellular component distributions may now be produced without requiring correlated analyses with separate instruments or the assumption of a constant sputter rate. This will allow visualization of the subcellular distributions of lipids, metabolites, drugs, and nanoparticles in 3D, information pivotal to understanding and treating disease.
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Verkhoturov DS, Crulhas BP, Eller MJ, Han YD, Verkhoturov SV, Bisrat Y, Revzin A, Schweikert EA. Nanoprojectile Secondary Ion Mass Spectrometry for Analysis of Extracellular Vesicles. Anal Chem 2021; 93:7481-7490. [PMID: 33988360 DOI: 10.1021/acs.analchem.1c00689] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
We describe a technique based on secondary ion mass spectrometry with nanoprojectiles (NP-SIMS) for determining the protein content of extracellular vesicles, EVs, via tagged antibodies. The technique uses individual gold nanoprojectiles (e.g., Au4004+ and Au28008+), separated in time and space, to bombard a surface. For each projectile impact (10-20 nm in diameter), the co-emitted molecules are mass analyzed and recorded as an individual mass spectrum. Examining these individual mass spectra for co-localized species allows for nanoscale mass spectrometry to be performed. The high lateral resolution of this technique is well suited for analyzing nano-objects. SIMS is generally limited to analyzing small molecules (below ∼1500 Da); therefore, we evaluated three molecules (eosin, erythrosine, and BHHTEGST) as prospective mass spectrometry tags. We tested these on a model surface comprising a mixture of all three tags conjugated to antibodies and found that NP-SIMS could detect all three tags from a single projectile impact. Applying the method, we tagged two surface proteins common in urinary EVs, CD63 and CD81, with anti-CD63-erythrosine and anti-CD81-BHHTEGST. We found that NP-SIMS could determine the relative abundance of the two proteins and required only a few hundred or thousand EVs in the analysis region to detect the presence of the tagged antibodies.
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Affiliation(s)
- Dmitriy S Verkhoturov
- Department of Chemistry, Texas A&M University, College Station, Texas 77843, United States
| | - Bruno P Crulhas
- Department of Physiology and Biomedical Engineering, Mayo Clinic, 200 1st Street SW St-11-14, Rochester, Minnesota 55905, United States
| | - Michael J Eller
- Department of Chemistry and Biochemistry, California State University Northridge, Northridge, California 91330, United States
| | - Yong D Han
- Department of Physiology and Biomedical Engineering, Mayo Clinic, 200 1st Street SW St-11-14, Rochester, Minnesota 55905, United States
| | | | - Yordanos Bisrat
- Materials Characterization Facility, Texas A&M University, College Station, Texas 77843, United States
| | - Alexander Revzin
- Department of Physiology and Biomedical Engineering, Mayo Clinic, 200 1st Street SW St-11-14, Rochester, Minnesota 55905, United States
| | - Emile A Schweikert
- Department of Chemistry, Texas A&M University, College Station, Texas 77843, United States
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Affiliation(s)
- Keke Hu
- Department of Chemistry and Molecular Biology, University of Gothenburg, Kemivägen 10, 41296 Gothenburg, Sweden
| | - Tho D. K. Nguyen
- Department of Chemistry and Molecular Biology, University of Gothenburg, Kemivägen 10, 41296 Gothenburg, Sweden
| | - Stefania Rabasco
- Department of Chemistry and Molecular Biology, University of Gothenburg, Kemivägen 10, 41296 Gothenburg, Sweden
| | - Pieter E. Oomen
- Department of Chemistry and Molecular Biology, University of Gothenburg, Kemivägen 10, 41296 Gothenburg, Sweden
- ParaMedir B.V., 1e Energieweg 13, 9301 LK Roden, The Netherlands
| | - Andrew G. Ewing
- Department of Chemistry and Molecular Biology, University of Gothenburg, Kemivägen 10, 41296 Gothenburg, Sweden
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