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Sodium fluoride (NaF) and sodium arsenite (NaAsO2) were purchased from Nanjing Shengqinghe Chemical Co. Ltd. and Shanghai Kanglang Biotechnology Co. Ltd., respectively.
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Sixty SD rats (6–7 weeks old, 40 female rats weighing 160 ± 10 g, and 20 male rats weighing 200 ± 10 g) were purchased from Beijing SiPeiFu Biotechnology Co. The rats were housed at SPF level in a controlled environment (temperature, 24 ± 1 °C; relative humidity, 50%) with unrestricted access to food and water. All experiments were performed in accordance with the guidelines of the Animal Experimentation Center and approved by the Ethics Committee of Shanxi Medical University.
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After one week of adaptation in separate cages for male and female rats, the rats were randomly divided into control (Con, drinking water only), arsenic (As, 70 mg/L NaAsO2), fluoride (F, 100 mg/L NaF), and arsenic-fluoride group (AsF, 70 mg/L NaAsO2 and 100 mg/L NaF). Rats were exposed to free water drinking according to the grouping described above, from first day of mating (female: male = 2:1) until the end of the gestation period. Subsequently, offspring were exposed to arsenic and/or fluoride through parental lactation during the 21-day lactation period. Afterwards, the weaned rats were continued to be exposed to the chemicals in similar manner until postnatal day (PND) 90.
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Feces and urine were collected from six rats per group on the day of PND 90 before euthanasia. The urine was cryogenically centrifuged, and the supernatant was removed and stored at ‒80 °C. Urinary arsenic and fluoride levels were measured as described in later context. Meanwhile, the feces were collected under the principle of asepsis, rapidly frozen in a liquid nitrogen tank for 30 s, and stored at a ‒80 °C. The fecal samples were used for 16S rRNA sequencing to detect gut microbiomes and LC-MC to detect gut nontargeted metabolomics. Finally, the hippocampal region of the brain tissue was collected after intraperitoneal injection of 20% Uratan in anesthetized littermates, and pathological changes in the CA1 region of the hippocampus were observed by hematoxylin and eosin (H&E) staining.
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The Morris water maze test, consisting of a spatial navigation training and a spatial exploration task, was used to evaluate their spatial learning and memory abilities. The water maze testing tank was 150 cm in diameter and 50 cm in depth. The circular water maze test chamber divided the pool into equal quadrants I, II, III, and IV. Black ink was added to the water before the experiment to prevent the camera from being able to track the white rats. The white rats were transferred to darkroom for at least 30 min before the experiment to adapt to the darkroom environment to reduce stress. The Morris water maze test was divided into two phases: spatial navigation training (days 1–5) and spatial exploration task (day 6). In the first phase, the rats were placed in the water from the appropriate position facing the wall of the pool each time and allowed to swim for up to 120 s. The escape latency was recorded for rats that found the platform and stayed on it for at least 5 s; otherwise, it was recorded for 120 s, and the rats were finally guided to find the platform and stay there for 5 s. The experiment was performed four times per day per rat for five consecutive days. In the second phase, the rats’ metrics (time spent in the target quadrant, swimming distance in the target quadrant, and number of crossing the platform) were recorded using a behavioral video tracking system (Hayward) after removal of the platform for subsequent analysis. Consistency of the experimental conditions was maintained throughout the experiments.
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Following preconditioning of cardiac perfusion, hippocampal CA1 regions of rat brain tissues were collected and fixed in 4% paraformaldehyde for 24 h at room temperature. After continuous ethanol dehydration (70%, 80%, 90%, and 100% alcohol), it was embedded in paraffin and sectioned, followed by rehydration, H&E staining, and sealing. Lastly, the sections were observed under an inverted microscope and photographed for neuronal and nuclear analysis.
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The urinary arsenic and fluorine levels were measured to assess the in vivo metabolism of arsenic and fluorine. First, urine was mixed with total ionic strength adjustment buffer (TISAB) in equal volumes, and the urinary fluorine content was measured using a fluoride ion meter (Shanghai Xianfan Instruments Co., Ltd.) with reference to the fluorine standard curve. While urine arsenic content was measured by digestion at low- temperature after centrifugation and dilution. Then, thiourea-vitamin C solution was added, and the volume was fixed using 5% dilute hydrochloric acid. Finally, urinary arsenic content was determined with an ASF-8530 atomic fluorescence photometer (Beijing Haiguang Instrument Company) using the arsenic standard curve as a reference.
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Total genomic DNA extraction, PCR amplification, and library construction for fecal samples were performed by Shanghai Obio Technology Co. DNA was extracted using the MagPure Soil DNA LQ Kit. Next, primer 343F (5’-TACGGRAGGCAGCAG-3’) and 798R (5’-AGGGTATCTAATCCT-3’), targeting the high variability region V3V4 were selected for PCR amplification.
The original image data file obtained by high-throughput sequencing was transformed into raw data using base-calling analysis. Raw data processing flow: quality filtering, sequence splicing, base sequence removal, chimera removal to obtain valid tags for later operational taxonomic units (OTU) delineation. The average length of valid tags ranged from 408.87 to 420.07 bp, and the number of OTUs in each sample ranged from 1,838 to 2,514. Subsequently, the OTU classification of the quality sequence valid tags was performed according to 97% similarity using Vsearch2.4.2 software (Oslo, Norway) to obtain the representative sequences. Following OTU cluster analysis, the species were annotated and the relative abundance was calculated at the phylum, class, order, family, and genus levels.
The alpha and beta diversities were analyzed reflecting microbial community differences within and between samples. Principal coordinate analysis (PCoA) using the unweighted UniFrac distance metric can simplify complex multidimensional data into intuitive two-dimensional data to identify similarities or differences between communities. Finally, linear discriminant analysis effect size (LEfSe) was used to reveal the composition of different species in two or more groups of biomes. The results of LEfSe analysis are presented as differential species contribution to the magnitude of differences analysis and differential species annotation analysis, respectively.
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Fecal metabolomics analysis was performed using a QE high-resolution mass spectrometer (Thermo Fisher World Technology Corporation) and Nexera ultra-performance liquid chromatography (UPLC) (Shimadzu Corporation). The gut metabolites were extracted as follows: First, 20 μL of the internal standard, 600 μL of methanol, and water were added to 60 mg of the sample. After grinding, sonication (10 min), resting (‒20 °C, 30 min), and low-temperature centrifugation (4 °C), 300 μL of supernatant was obtained and evaporated dry. The dried extract was redissolved in 400 μL of methanol/water (v:v = 1:4), vortexed for 30 s, sonicated (2 min), and centrifuged. Finally, 50 μL of the supernatant was aspirated for onboard LC-MS analysis.
Metabolites were quantified with UPLC. Chromatographic separation was carried out on a column (ACQUITY UPLC HSST3, 100 mm × 2.1 mm, 1.8 um) at 45 °C. The mobile phase consisted of water and acetonitrile and separation was achieved using a gradient (Supplementary Table S1, available in www.besjournal.com). The flow rate was 0.35 mL/min, and the injection volume was 2 μL. The mass range was m/z 125 to 1,000. The resolution was set at 70,000 for full MS scans and 17,500 for HCD MS/MS scans. The mass spectrometer operated as follows: spray voltage, 3,500 V (+) and 3,000 V (−); capillary temperature, 350 °C.
Time A% B% 0.01 95 5 2 95 5 4 70 30 8 50 50 10 20 80 14 0 100 15 0 100 15.1 95 5 16 95 5 Note. A-water (0.1% formic acid), B-acetonitrile (0.1% formic acid). Table S1. Elution gradient of mobile phase
Raw data were collected using UNIFI software (version 1.8.1) and analyzed qualitatively using the metabolomics processing software Progenesis QI (version 2.3) (Nonlinear Dynamics, Newcastle, UK). The positive and negative ion data (30-point scale) were combined into a data matrix table for subsequent analysis. Data analysis included univariate (Student’s t-test and fold-change analysis) and multivariate analyses. Multivariate statistical analyses included principal component analysis (PCA), supervised partial least squares analysis (PLS-DA), and orthogonal partial least-squares analysis (OPLS-DA). In this study, Variable important in projection (VIP) > 1 and P < 0.05 were adopted to screen for differential metabolites. Finally, screening of differential metabolites was enriched to a complete set of metabolic pathways using KEGG enrichment analysis.
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Data analysis was conducted using SPSS24.0 software (IBM, USA). All values are presented as the mean ± standard error of the mean (SEM). Statistical analysis of multiple comparisons was performed by analysis of variance (ANOVA) or Wilcoxon’s test. After ANOVA, the least significant difference (LSD) test was used between the two groups. Escape latency was analyzed using repeated measures ANOVA. Correlations between the microbiome, metabolome, and learning memory metrics were analyzed using the Spearman correlation test. The interaction between As and F was analyzed by single variable statistical method of general linear model. The determination of arsenic and fluorine contents was calculated from the regression equation of the standard curve. Statistical significance was set at P < 0.05.
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Chemicals and Reagents
Animals
Arsenic and/or Fluoride Exposure
Biological Sample Collection
Morris Water Maze
Hematoxylin and Eosin (H&E) Staining of Hippocampus
Determination of Excretion of Arsenic and Fluorine
16S rRNA Gene Sequencing for the Gut Microbiome
LC-MS for the Gut Metabolome
Statistical Analysis
22169Supplementary Materials.pdf |