Abstract
With the continuous exposure of environmental pollutants in organisms, determination of abundance variation and spatial distribution of lipids might expand our understanding of toxicological mechanisms occurring in the kidney. Herein, an integrated method involving mass spectrometry (MS)-based lipidomics and matrix-assisted laser desorption/ionization-MS imaging (MALDI-MSI) was developed for the study of nephrotoxicity in mice exposed to 10 and 100 μg bisphenol S (BPS)/kg body weight/day. The BPS exposure remarkable perturbed abundances of 91 potential markers that mainly involved in five metabolic pathways. We elucidated the lipids spatial heterogeneity by using morphological analysis, probabilistic latent semantic analysis, and coregistered multimodal three-dimensional (3D)-MSI. In morphological analysis, both 10 and 100 μg BPS induced significant nephrotoxicity to mice, including glomerular necrosis in renal cortex, cloudy swelling in renal medulla, and interstitial collapsing in renal pelvis. Significant differential signaling lipids such as sphingomyelin (SM) (d22:0/20:4), ceramide (Cer) (d18:2/24:1), and sphingosine (d18:0) related to inflammation were found to be up-regulated and colocalized in the renal cortex, medulla, and pelvis, respectively. Also, seven significant differential lipids, which are considered to be involved in membrane homeostasis and cellular function, were found to be colocalized in the renal cortex. The observed significant variations of morphology, lipid accumulation, and metabolism in the renal cortex implicated that lipids in the renal cortex were more sensitive to BPS exposure than those in the renal medulla and pelvis. Moreover, we reconstructed a 3D-MSI model of kidney and identified two heterogeneous-related substructures in the renal cortex and pelvis upon 100 μg BPS exposure. It might be used in novel specificity evaluation and early diagnosis for environmental pollutant-induced kidney diseases.
| Original language | English |
|---|---|
| Pages (from-to) | 3196-3204 |
| Number of pages | 9 |
| Journal | Analytical Chemistry |
| Volume | 90 |
| Issue number | 5 |
| Early online date | 12 Feb 2018 |
| DOIs | |
| Publication status | Published - 6 Mar 2018 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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