Literature DB >> 33279055

The dynamic changes of arsenic biotransformation and bioaccumulation in muscle of freshwater food fish crucian carp during chronic dietborne exposure.

Di Cui1, Peng Zhang2, Haipu Li3, Zhaoxue Zhang1, Yang Song1, Zhaoguang Yang4.   

Abstract

Dietary uptake is the major way that inorganic arsenic (iAs) enters into benthic fish; however, the metabolic process of dietborne iAs in fish muscle following chronic exposure remains unclear. This was a 40-day study on chronic dietborne iAs [arsenite (AsIII) and arsenate (AsV)] exposure in the benthic freshwater food fish, the crucian carp (Carassius auratus), which determined the temporal profiles of iAs metabolism and toxicokinetics during exposure. We found that an adaptive response occurred in the fish body after iAs dietary exposure, which was associated with decreased As accumulation and increased As transformation into a non-toxic As form (arsenobetaine). The bioavailability of dietary AsIII was lower than that of AsV, probably because AsIII has a lower ability to pass through fish tissues. Dietary AsV exhibited a high potential for transformation into AsIII species, which then accumulated in fish muscle. The largely produced AsIII considered more toxic at the earlier stage of AsV exposure should attract sufficient attention to human exposure assessment. Therefore, the pristine As species and exposure duration had significant effects on As bioaccumulation and biotransformation in fish. The behavior determined for dietborne arsenic in food fish is crucial for not only arsenic ecotoxicology but also food safety.
Copyright © 2020. Published by Elsevier B.V.

Entities:  

Keywords:  Adaptation; Arsenic; Bioaccumulation; Biotransformation; Freshwater fish

Year:  2020        PMID: 33279055     DOI: 10.1016/j.jes.2020.07.005

Source DB:  PubMed          Journal:  J Environ Sci (China)        ISSN: 1001-0742            Impact factor:   5.565


  1 in total

1.  Assessment of potential human health risks in aquatic products based on the heavy metal hazard decision tree.

Authors:  Hao-Hsiang Ku; Pinpin Lin; Min-Pei Ling
Journal:  BMC Bioinformatics       Date:  2022-02-17       Impact factor: 3.169

  1 in total

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