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. 2025 Feb 4;59(4):1957-1968.
doi: 10.1021/acs.est.4c09874. Epub 2025 Jan 22.

Mass Spectrometry-Based Spatial Multiomics Revealed Bioaccumulation Preference and Region-Specific Responses of PFOS in Mice Cardiac Tissue

Affiliations

Mass Spectrometry-Based Spatial Multiomics Revealed Bioaccumulation Preference and Region-Specific Responses of PFOS in Mice Cardiac Tissue

Rui Shi et al. Environ Sci Technol. .

Abstract

The distribution and bioaccumulation of environmental pollutants are essential to understanding their toxicological mechanism. However, achieving spatial resolution at the subtissue level is still challenging. Perfluorooctanesulfonate (PFOS) is a persistent environmental pollutant with widespread occurrence. The bioaccumulation behavior of PFOS is complicated by its dual affinity for phospholipids and protein albumin. It is intriguing to visualize the distribution preference of PFOS and investigate the differential microenvironment responses at a subtissue level. Herein, we developed a mass-spectrometry (MS)-based spatial multiomics workflow, integrating matrix-assisted laser desorption/ionization MS imaging, laser microdissection, and liquid chromatography MS analysis. This integrated workflow elucidates the spatial distribution of PFOS in mouse cardiac tissue, highlighting its preferential accumulation in the pericardium over the myocardium. This distribution pattern results in greater toxicity to the pericardium, significantly altering cardiolipin levels and disrupting energy metabolism and lipid transport pathways. Our integrated approach provides novel insights into the bioaccumulation behavior of PFOS and demonstrates significant potential for revealing complex molecular mechanisms underlying the health impacts of environmental pollutants.

Keywords: Mass spectrometry analysis; PFOS; bioaccumulation; mass spectrometry imaging; spatial proteomics.

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Conflict of interest statement

The authors declare no competing financial interest.

Figures

Figure 1
Figure 1
MALDI-MSI revealed spatial preference of PFOS accumulation in the mouse cardiac tissue. (A) The overall workflow of the study. (B) MALDI mass spectra of the PFOS standard ([M–H], m/z 498.92) were spotted on the steel plate under negative-ion detection mode. (C) Representative MALDI mass spectra of the PFOS ([M–H], m/z 498.92) spiking on the cardiac section under negative-ion detection mode. (D) Representative MALDI-MSI Image of PFOS distribution in cardiac sections from control and exposure groups. The optical micrograph of a H&E-stained parallel tissue section. Relative ion intensity is represented using a color bar. Orange dashed lines marked pericardium regions. (E) Representative pictures of enlarged pericardium areas (orange dashed lines) from adjacent slices upon PFOS exposure with H&E staining (left) and MALDI MSI (right). (F) Statistical analysis of PFOS peak intensities in different cardiac regions. (*) AUC > 0.75. Red dots represent outliers. Peak intensities were normalized to the total ion count.
Figure 2
Figure 2
Representative MALDI-MSI images of altered lipids post PFOS exposure. (A) Segmentation map of cardiac sections based on the MALDI-MSI. The representative pericardium region was marked using white dashed lines. (B) Representative spatial distribution of the four cardiolipins in the cardiac sections. (C) Representative spatial distribution of phosphatidylinositol and phosphatidylethanolamine in the cardiac sections. Relative ion intensity is shown using a color bar. The intensity values were normalized to the TIC. All scale bars were 2 mm.
Figure 3
Figure 3
Region-specific dysregulation of protein expression in cardiac tissue upon PFOS exposure. (A) Schematic diagram of the selected regions of analysis by LMD. (B) UpSet plots illustrated the overlap of identified protein groups in each region. (C, D) Heatmap of the DEPs across MR region (C) and PR region (D) between the control and exposure group. The heatmap is based on the normalized abundance intensities of the significant DEPs by unsupervised hierarchical clustering. Statistical analysis used a two-tailed unpaired t-test; p-value is indicated for levels of significance p-value <0.01 (**), p-value <0.001 (***). (E) Sankey diagram of significantly enriched GO terms of the common DEPs of PR region between control and exposure samples. The sizes of dot indicate protein counts, and the colors represent the adjusted p-value. Abbreviations: PR, pericardium region; MR, myocardial region distant from the pericardium; Con-PR, the pericardium of the control group; Con-MR, the myocardium of the control group; Exp-PR, the pericardium of the PFOS exposure group; Exp-MR, the myocardium of the PFOS exposure group.
Figure 4
Figure 4
Impairment of TCA cycle activity in PR region following PFOS exposure. Targeted relative quantitation of metabolites in the PR region is associated with glycolysis and TCA cycle, with/without the exposure of PFOS. Statistical significance was calculated using the unpaired two-tailed Student’s t test. *P < 0.05; **P < 0.01.
Figure 5
Figure 5
Schematic diagram to illustrate the mechanisms that impact lipid transport and cholesterol homeostasis and induce mitochondrial dysfunction.

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