Airborne fine particulate matter induces cognitive and emotional disorders in offspring mice exposed during pregnancy

Zhao, Chao; Xie, Peisi; Yong, Ting Ting; Wei, Huang; Li, Jianjun; Wu, Desheng; Ji, Fenfen; Li, Min; Zhang, Doudou; Li, Ruijin; Dong, Chuan; Ma, Juan; Zheng, Dong; Liu, Sijin; Cai, Zongwei

doi:10.1016/j.scib.2020.08.036

Cited by 28 publications

(31 citation statements)

References 87 publications

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“…With the advancements in computer hardware as well as user-friendly software suites, whole-body 3D imaging of a small animal model as the natural extension of the whole-body 2D image may be available. Recently, the whole-body 3D MALDI-MSI has been applied for investigating PM 2.5 toxicity in mouse fetus and demonstrating the disturbed lipid metabolism caused by the gestational exposure to PM 2.5 , 29 which suggested the possibility to obtain a comprehensive understanding of the biochemical processes in the whole-organism level.…”

Section: ■ Introductionmentioning

confidence: 99%

Three-Dimensional Imaging of Whole-Body Zebrafish Revealed Lipid Disorders Associated with Niemann–Pick Disease Type C1

et al. 2021

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Imaging of lipids of whole-body specimens in two-dimensional (2D) analysis provides a global picture of the lipid changes in lipid-disturbed diseases, enabling a better understanding of lipid functions and lipid-modulation processes in different organs. However, 2D imaging of a single cross section can hardly characterize the whole-body lipid alterations. In this work, a three-dimensional matrix-assisted laser desorption/ionization mass spectrometry imaging (3D MALDI-MSI) approach was developed for analysis of whole-body zebrafish, for the first time, and applied to identify altered lipids and map their spatial distributions by using a zebrafish model of Niemann–Pick disease type C1 (NPC1), a neurovisceral lipid storage disorder causing both neurodegenerative disorder and visceral organ damage. The constructed 3D fish model provided comprehensive information on the 3D distribution of lipids of interest and allowed direct correlations between these lipids and organs of the fish. Obtained results revealed that several sphingolipids and phospholipids showed significant alterations and exhibited different localization patterns in various organs such as the brain, spinal cord, intestines, and liver–spleen region in the npc1 gene mutant fish compared to those of the wild type. The whole-body 3D MALDI-MSI approach revealed unique lipid signatures for different NPC1-affected organs, which might offer insights into the link between the impaired lipid storage and subsequent clinical symptoms, such as neurodegeneration and hepatosplenomegaly.

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Section: ■ Introductionmentioning

confidence: 99%

Three-Dimensional Imaging of Whole-Body Zebrafish Revealed Lipid Disorders Associated with Niemann–Pick Disease Type C1

et al. 2021

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“…And then, females are placed in a separate cage after successful mating. We collect the whole-body mouse fetus at embryonic day 18 for MALDI-MSI The procedures of MALDI-MSI and histological analysis are described in the previous work of Zhao et al 22,36 . In short, the mouse fetus and human breast tumor samples are sectioned at a 14 μm-thickness by using CryoStar Nx79 cryostat (Thermo Fisher Scientific, Germany).…”

Section: Experimental Datasetsmentioning

confidence: 99%

Divide-and-conquer: a flexible deep learning strategy for exploring metabolic heterogeneity from mass spectrometry imaging data

Guo

Dong

et al. 2022

Preprint

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There is growing awareness that metabolic heterogeneity of organism provides vital insight into the disease with molecular mechanism and personalized therapy. The screening of metabolism-related sub-regions that affect disease development is essential for the more focused exploration how disease progress aberrant phenotypes, even carcinogenesis and metastasis. Mass spectrometry imaging (MSI) technique has distinct advantages to reveal the heterogeneity of organism based on the in situ molecular profiles. The challenge of heterogeneous analysis has been to perform an objective identification among biological tissues with different characteristics. By introducing the divide-and-conquer strategy to architecture design and application, we establish here a flexible unsupervised deep learning model, called divide-and-conquer (dc)-DeepMSI, for metabolic heterogeneity analysis from MSI data without prior knowledge of histology. dc-DeepMSI can be used to identify either spatially contiguous region-of-interest (ROIs) or spatially sporadic ROIs. We demonstrate that the novel learning strategy successfully obtain sub-regions that are statistically linked to invasion status and molecular phenotypes of breast cancer, as well as organizing principles during developmental phase.

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“…Interestingly, two substructures (SM [d22:0/ 20:4] and Cer [d18:2/24:1]) were identified for the nephrontoxicological assessment of BPS (Figure 4B). We also evaluated the toxicity of airborne fine particulate matter by reconstructing the mouse fetus and acquired the targeted microorgans, such as the dorsal pallium and hippocampal formation regions of fetal brain, placenta, and offspring hippocampus (Zhao, Xie, Yong, et al, 2020). The screening of targeted organ based on 3D-MSI provided a novel approach for pollutant-induced disease studies.…”

Section: Environmental Toxicologymentioning

confidence: 99%

“…To broaden 3D‐MSI applications in environmental toxicology research, our lab has recently carried out a series of studies (Zhao, Xie, Wang, et al, 2018; Zhao, Xie, Yang, et al, 2018; Zhao, Xie, Yong, et al, 2018, 2020; Zhao et al, 2020). Exposure to bisphenol or its alternatives have been associated with the occurrence and development of disease and malignant tumor, including diabetes, cardiovascular diseases and breast cancer (Pupo et al, 2012; Rochester & Bolden, 2015).…”

Section: Applicationsmentioning

confidence: 99%

Three‐dimensional quantitative mass spectrometry imaging in complex system: From subcellular to whole organism

Zhao

Cai

2020

Mass Spectrometry Reviews

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Mass spectrometry imaging (MSI) has been applied for label-free threedimensional (3D) imaging from position array across the whole organism, which provides high-dimensional quantitative data of inorganic or organic compounds that may play an important role in the regulation of cellular signaling, including metals, metabolites, lipids, drugs, peptides, and proteins.While MSI is suitable for investigation of the spatial distribution of molecules, it has a limitation with visualization and quantification of multiple molecules. 3D-MSI, however, can be applied toward exploring metabolic pathway as well as the interactions of lipid-protein, protein-protein, and metal-protein in complex systems from subcellular to the whole organism through an untargeted methodology. In this review, we highlight the methods and applications of MS-based 3D imaging to address the complexity of molecular interaction from nano-to micrometer lateral resolution, with particular focus on: (a) common and hybrid 3D-MSI techniques; (b) quantitative MSI methodology, including the methods using a stable isotope labeling internal standard (SILIS) and SILIS-free approaches with tissue extinction coefficient or virtual calibration; (c) reconstruction of the 3D organ; (d) application of 3D-MSI for biomarker screening and environmental toxicological research. 3D-MSI quantitative analysis provides accurate spatial information and quantitative variation of biomolecules, which may be valuable for the exploration of the molecular mechanism of the disease progresses and toxicological assessment of environmental pollutants in the whole organism. Additionally, we also discuss the challenges and perspectives on the future of 3D quantitative MSI.

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Airborne fine particulate matter induces cognitive and emotional disorders in offspring mice exposed during pregnancy

Cited by 28 publications

References 87 publications

Three-Dimensional Imaging of Whole-Body Zebrafish Revealed Lipid Disorders Associated with Niemann–Pick Disease Type C1

Three-Dimensional Imaging of Whole-Body Zebrafish Revealed Lipid Disorders Associated with Niemann–Pick Disease Type C1

Divide-and-conquer: a flexible deep learning strategy for exploring metabolic heterogeneity from mass spectrometry imaging data

Three‐dimensional quantitative mass spectrometry imaging in complex system: From subcellular to whole organism

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