Detecting the bioaccumulation patterns of chemicals through data-driven approaches

Francesca Grisoni, Viviana Consonni, Marco Vighi

Research output: Contribution to journalArticleAcademicpeer-review

6 Citations (Scopus)

Abstract

This work investigates the bioaccumulation patterns of 168 organic chemicals in fish, by comparing their bioconcentration factor (BCF), biomagnification factor (BMF) and octanol-water partitioning coefficient (KOW). It aims to gain insights on the relationships between dietary and non-dietary bioaccumulation in aquatic environment, on the effectiveness of KOW and BCF to detect compounds that bioaccumulate through diet, as well as to detect the presence of structure-related bioaccumulation patterns. A linear relationship between logBMF and logKOW was observed (logBMF = 1.14·logBCF – 6.20) up to logKOW ≈ 4, as well as between logBMF and logBCF (logBMF = 0.96·logBCF – 4.06) up to a logBCF ≈ 5. 10% of compounds do not satisfy the linear BCF-BMF relationship. The deviations from such linear relationships were further investigated with the aid of a self-organizing map and canonical correlation analysis, which allowed us to shed light on some structure-related patterns. Finally, the usage of KOW- and BCF-based thresholds to detect compounds that accumulate through diet led to many false positives (47%–91% for KOW), and a moderate number of false negatives (up to 5% for BCF). These results corroborate the need of using the experimental BMF for hazard assessment practices, as well as of developing computational tools for BMF prediction.

Original languageEnglish
Pages (from-to)273-284
Number of pages12
JournalChemosphere
Volume208
DOIs
Publication statusPublished - Oct 2018
Externally publishedYes

Bibliographical note

Funding Information:
Additionally, some important caveats must be highlighted for the selection of experimental BMF data. First, some dataset compounds showed a species-dependent BMF. For example, musk-xylene does not bioaccumulate through diet in common carp (BMF = 0.38 ± 0.02), but it has high BMF values in rainbow trout (BMF = 0.93 ± 0.11). This inter-species variability was observed also for several other compounds, but musk xylene was the only case we reported with a difference in the final assessment of bioaccumulation. In addition, the experimental data used in this work refer to freshwater fish BMF and are relatively homogeneous. However, the biomagnification may differ extremely according to the species, because of physiological and metabolic processes. An example is that of the bioaccumulation in the Arctic food chain of two of the most studied global POPs: DDT and PFOS. While there is a wide experimental evidence supporting low dietary accumulation of DDT in polar bears (BMF ≈ 0.5–0.6), the corresponding BMF for ringed seal - the main food of bears - is approximatively 4.0 (Letcher et al., 1998; Villa et al., 2017). This was ascribed to the capability of polar bears to metabolize DDT and DDE (Letcher et al., 1998; Muir et al., 1994; Polischuk et al., 2002), which is, as far as we know, unique in the animal world. On the contrary, PFOS, which resulted here to have a BMF below the assessment threshold on fish (logBMF = −0.38), is, to date, the most dangerous compound for polar bears, on which the BMF is extremely high (Dietz et al., 2008; Villa et al., 2017).

Publisher Copyright:
© 2018 Elsevier Ltd

Keywords

  • Bioaccumulation
  • Bioconcentration
  • Canonical correlation analysis
  • Machine-learning
  • Self-organizing map

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