Multimodal imaging distribution assessment of a liposomal antibiotic in an infectious disease model

Cheng, Shih-Hsun; Groseclose, M. Reid; Mininger, Cindy; Bergström, Mats; Zhang, Lily; Lenhard, Steve C; Skedzielewski, Tinamarie; Kelley, Zachary D; Comroe, Debra; Hong, HyunDae; Cui, Haifeng; Hoover, Jennifer L.; Rittenhouse, Steve; Castellino, Stephen; Jucker, Beat M.; Alsaid, Hasan

doi:10.1016/j.jconrel.2022.08.061

Cited by 6 publications

(3 citation statements)

References 54 publications

(34 reference statements)

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“…11 Furthermore, specific ether lipids have been identified in neutrophils and other leukocytes in vitro and have been spatially detected at sites of inflammation in animal models of bacterial infections. 28,47–49 In our data, ether lipids have a high propensity to localize to bone marrow regardless of infection status, indicating some specificity to the hematopoietic stem cell niche under homeostatic conditions. Following bacterial invasion into the intramedullary cavity, myelopoiesis occurs in the same region, giving rise to a dense population of myeloid lineage cells.…”

Section: Discussionmentioning

confidence: 55%

In situlipidomics ofStaphylococcus aureusosteomyelitis using imaging mass spectrometry

Good,

Butrico,

Colley

et al. 2023

Preprint

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SUMMARYOsteomyelitis occurs whenStaphylococcus aureusinvades the bone microenvironment, resulting in a bone marrow abscess with a spatially defined architecture of cells and biomolecules. Imaging mass spectrometry and microscopy are invaluable tools that can be employed to interrogate the lipidome ofS. aureus-infected murine femurs to reveal metabolic and signaling consequences of infection. Here, nearly 250 lipids were spatially mapped to healthy and infection-associated morphological features throughout the femur, establishing composition profiles for tissue types. Ether lipids and arachidonoyl lipids were significantly altered between cells and tissue structures in abscesses, suggesting their roles in abscess formation and inflammatory signaling. Sterols, triglycerides, bis(monoacylglycero)phosphates, and gangliosides possessed ring-like distributions throughout the abscess, indicating dysregulated lipid metabolism in a subpopulation of leukocytes that cannot be discerned with traditional microscopy. These data provide chemical insight into the signaling function and metabolism of cells in the fibrotic border of abscesses, likely characteristic of lipid-laden macrophages.

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Section: Discussionmentioning

confidence: 55%

In situlipidomics ofStaphylococcus aureusosteomyelitis using imaging mass spectrometry

Good,

Butrico,

Colley

et al. 2023

Preprint

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“…230 When being utilized as radiolabeled nanotheranostics to deliver various antimicrobial agents, they are available for positron emission tomography imaging by introducing the radioactive isotope ions, such as 64 Cu 2+ , 99m Tc and 89 Zr. [231][232][233] Given the convenient incorporation of various agents into the structures, the lipid nanoparticles/nanoliposomes can be functionalize maltohexaose 234 or folic acid 229 for better targeting of bacteria or bacteria-infected macrophages. Notably, the construction of lauric acid and stearic acid-based thermoresponsive nanostructures with IR780 and imipenem loading and lecithin/DSPE-PEG2000 coatings could bring novel theranostic platforms with irradiation-induced phase change, leading to imipenem killing, photothermal eradication and fluorescence tracking of the MDR bacteria (Fig.…”

Section: Polymeric Biomacromolecule and Lipid-based Nanoparticlesmentioning

confidence: 99%

Nano-based theranostic approaches for infection control: current status and perspectives

Huang,

Hu,

et al. 2024

Mater. Chem. Front.

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“…The spatial aspect of MSI makes it possible to obtain anatomical images of any ion detected in the mass spectra in a given experiment. MSI has been widely used to map diverse analytes, but it is particularly effective in analyzing lipids [4,5] and has been used to map lipids and lipid fine structure in brain tissue [6], simultaneously map host and bacterial lipids [7], liposomal drug distribution [8,9], and cancer [10] in tissues.…”

Section: Mass Spectrometry Imagingmentioning

confidence: 99%

Interpretable dimensionality reduction and classification of mass spectrometry imaging data in a visceral pain model via non-negative matrix factorization

Pathirage

Virmani

Scott

et al. 2023

Preprint

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Mass spectrometry imaging (MSI) is a powerful scientific tool for understanding the spatial distribution of biochemical compounds in tissue structures. MSI data analysis presents problems due to the large file sizes and computational resource requirements and also due to the complexity of interpreting the raw spectral data. Dimensionality reduction techniques that address the first issue do not necessarily result in readily interpretable features. In this paper, we present non-negative matrix factorization (NMF) as a dimensionality reduction algorithm that reduces the size of MSI datasets by three orders of magnitude with limited loss of information, yielding spatial and spectral components with meaningful correlation to tissue structure. This analysis is demonstrated on an MSI dataset for an animal model of comorbid visceral pain hypersensitivity (CPH). The significant findings are: 1) High-dimensional MSI data (~ 100,000 ions per pixel) was reduced to 20 spectral NMF components with < 20% loss in reconstruction accuracy. 2) Spatial NMF components are reproducible and correlate well with H&E-stained tissue images. 3) Spatial NMF components may be used to provide images with enhanced specificity for different tissue types. 4) Small patches of NMF data (i.e., 20 spatial NMF components over 15 x 15 pixels) provide an accuracy of ~87% in classifying CPH vs naive control subjects. This paper presents novel methodologies for data augmentation to support classification, ranking of features according to their contribution to classification, and image registration to support tissue-specific imaging.

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Multimodal imaging distribution assessment of a liposomal antibiotic in an infectious disease model

Cited by 6 publications

References 54 publications

In situlipidomics ofStaphylococcus aureusosteomyelitis using imaging mass spectrometry

In situlipidomics ofStaphylococcus aureusosteomyelitis using imaging mass spectrometry

Nano-based theranostic approaches for infection control: current status and perspectives

Interpretable dimensionality reduction and classification of mass spectrometry imaging data in a visceral pain model via non-negative matrix factorization

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