Fruit consumption as a gut health improving strategy to lower arsenic

Overview

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Key numbers

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• banana, grape, and pitaya, 16% in rice on a dry weight basis) experienced significant reductions in As accu-
• increase from 4.8% in 2020 to 5.2% by 2040 in China (14). Further- The gut microbiota critically affects As bioavailability. Upon inges-
• being exposed to iAsV in drinking water at 25 or 100 mg/L for 14 days, 2.1. Rice, fruits, and mouse basal diet
• sumption may also lower As oral bioavailability via affecting As 88.7% in guava (Table S1). Mouse standard AIN-93G purified rodent
• ability to regulate gut microbiota (38–40), enhance intestinal barrier the predominant species (38.6%–60.8%) (Fig. S1). Low As concentra-
• tinal As paracellular transport (26,34), we hypothesized that fruit con- 1) Bioassay 1: Consuming six fruits in female mice at 16% (w/w)
• bioavailability. We initially assessed the effects of six fruits in rice at 16% (w/w) on
• This study aims to investigate the effects of fruit consumption on rice-As bioavailability. Fruits were added to rice at 16% (w/w) to reflect
• (56). Assuming a water content in the fruits of 80% and a daily con-
• 200 g fresh fruits typically results in a diet containing 16% (w/w) fruits
• tions of a 12:12 h light/dark cycle, 25 ◦ C, and 50% humidity. A total of
• 100% AIN-93G diet to monitor the background As accumulation in mice;
• Rice-3, each amended with 20% AIN-93G diet and 16% Rice-0 to assess C×W
• amended with 20% AIN-93G diet and 16% of one of the six fruits to after contaminated rice consumption, C is the As concentration in rice-
• diets at 20% to ensure balanced nutrition to support mouse growth. In by each mouse over 35 days. For each mouse, the mass of As accumu-
• 2. Bioassay 2: Consuming guava and kiwifruit in female mice at 4%, As urinary excretion factors (UEFs, %) using Eq. 2, which represents the
• 8%, and 16% (w/w) percentage of ingested As that was absorbed and excreted in the urine.
• We selected guava, kiwifruit, and Rice-2 to assess fruit effects at UEF (%) = × 100% (2)
• was 64% Rice-2, 20% AIN-93G rodent diet, and 16% Rice-0. For fruit Where, U is As concentration in urine (μg/mL), V is the volume of urine
• amendment, Rice-0 was replaced with 4%, 8%, and 16% guava or (mL) excreted over the last five days of exposure to contaminated rice in
• 3. Bioassay 3: Consuming guava in male mice at 16% (w/w) five days.
• control fed Rice-1 amended with 20% AIN-93G diet and 16% Rice-0; (2) samples were recorded. Then fecal samples were ground into a powder,
• (FEFs, %) using Eq. 3, which represents the percentage of As not ileum (64). Details are provided in the SI. The gene-specific primers are
• absorbed and excreted via feces. shown in Table S2. The relative mRNA expression data were calculated
• total feces (g) excreted per mouse over the third and fourth weeks, C is Mice fed Rice-1 without or with fruit consumption at 16% (w/w) in
• column (Hamilton, UK). The mobile phase consisted of 42 mM fed Rice-3 without or with guava and kiwifruit (16% w/w) in Bioassay 1
• using the speciation extraction method were 62%–73%. differences in gut microbiota composition from the control group, while
• mixed with edible melanin (0.1%) via gavage and sacrificed 15 min
• × 100% (4) LPS levels reflect impaired intestinal barriers. CEA and LPS were
• intestinal epithelium and protects the gut from harmful substances (61). The mean and standard error of replicate analyses (n = 3 or 6) were
• describe the thickness of mucus and the number of goblet cells in the deviation < 0.5%. Standard solutions were measured using ICP-MS every
• intestine, the ratios of mucus and goblet cell integrated optical density 20 samples, with recoveries of 95%–105% (n = 10). The analyses of As
• 3.1. Gut microbiota and intestinal barriers (p < 0.05) in all fruit groups (ranging from 6.62% ± 3.20% to
• improvement with fruit consumption. In mice consuming Rice-1, partial relative abundances in mice treated with guava (18.7% ± 6.59%,
• least squares-discriminant analysis (PLS-DA) demonstrated a clear sepa- p < 0.001), banana (14.8% ± 9.48%, p < 0.01), and grape
• such as Lachnospiraceae (8.47%–29.5% vs 5.91%), Muribaculaceae p < 0.05), grape (0.14% ± 0.11%, p < 0.05), and pitaya (2.77% ± 5.94%,
• (6.68%–15.5% vs 1.45%), Ruminococcaceae (1.06%–3.75% vs 0.23%), p < 0.05), compared to control mice (0.0087% ± 0.014%). Alistipes was
• Rikenellaceae (0.30%–1.35% vs 0.10%), and Bacteroidaceae (0.06%– significantly increased in the apple (0.77% ± 1.43%, p < 0.05) and ba-
• 0.95% vs 0.02%), as well as their respective genera, was increased in the nana (0.73% ± 0.55%, p < 0.01) groups compared to controls
• with addition of 16% (w/w) fruit; optical density of
• (0.071% ± 0.047%). Bacteroides displayed significantly higher relative (p < 0.05), while mice consuming pitaya showed significantly higher
• abundances in guava (0.34% ± 0.34%, p < 0.05), banana Claudin-4 expression (p < 0.01). The serum LPS level was reduced from

Methods (brief)

• dimethylarsinic acid (DMAV) and monomethylarsonic acid (MMAV), health risks associated with As exposure from rice. We chose six
• concentrations in the liver and kidneys of antibiotic-treated mice fed For mouse bioassays, three As-containing white rice grain samples
• As-containing rice compared to normal mice due to disruption of gut (designated as Rice-1, Rice-2, and Rice-3) collected from a mining-
• plementation with prebiotics and probiotics for antibiotic-treated mice In addition, a sample with low As concentration was purchased from a
• led to the restoration of gut microbiota and recovery of intestinal mucus food market in Nanjing (referred to as Rice-0). All rice samples were
• dietary fiber, fruits contain bioactive components, such as polyphenols coupled plasma mass spectrometry (ICP-MS, NexION300X, Perki-
• collected from wood shavings in the cage. Wood shavings with feces
• 1, three rice samples with different As content were used, with each amended
• with six fruits, and fed to female mice to assess effects of fruit on As bioavail- and kidney samples for As concentration analyses. Blood of each mouse
• ability. (B) In bioassay 2, the dose-response effect of guava and kiwifruit con- was collected in evacuated and coagulating tubes to collect serum
• sumption on As bioavailability was assessed in female mice. (C) In bioassay 3, samples for biochemical analyses. Sections of the ileum were collected
• ples. According to the Chinese Food Guide Pagoda (2022), the recom- microbiota and metabolomics analyses. All samples, except those for
• Following freeze-drying, liver and kidney samples were digested
• ICP-MS. Arsenic tissue accumulation factors (TAFs, %) were calculated
• using three different rice samples in this bioassay was to determine that and transferred to metabolic cages (one mouse in a cage) and fed the
• fruit intake affects rice-As bioavailability independently of rice samples corresponding diets for free consumption to collect cumulative urine.
• and As concentrations in rice. For each mouse, cumulative urine samples were diluted with 0.1 M
• HNO3 and analyzed for As concentration using ICP-MS for calculation of

Implications

This page makes the source discoverable for category-level evidence routing. Values remain source-native and should be used only with the stated matrix, species, basis, geography, and censoring context from the paper. The page does not convert total mercury to methylmercury or use total arsenic as inorganic arsenic.

Wiki pages this source may touch

• Fish — marine, non-predatory (sardines, anchovies, salmon, cod)
• Seaweed/kelp foods (nori, wakame, kombu, dulse — as food products)
• Cadmium
• Arsenic

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Update history

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