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Assessing interactions of binary mixtures of Penicillium mycotoxins (PMs) by using a bovine macrophage cell line
Se-Young Oh1, Nina Cedergreen2, Alexandros Yiannikouris3
1Department of Animal Biosciences, Ontario Agriculture College (OAC), University of Guelph, Guelph, ON N1G 2W1, Canada.
Abstract:
Penicillium mycotoxins (PMs) are toxic contaminants commonly found as mixtures in animal feed. Therefore, it is important to investigate potential joint toxicity of PM mixtures. In the present study, we assessed the joint effect of binary combinations of the following PMs: citrinin (CIT), ochratoxin A (OTA), patulin (PAT), mycophenolic acid (MPA) and penicillic acid (PA) using independent action (IA) and concentration addition (CA) concepts. Previously published toxicity data (i.e. IC25; PM concentration that inhibited bovine macrophage (BoMacs) proliferation by 25%) were initially analyzed, and both concepts agreed that OTA+PA demonstrated synergism (p<0.05), while PAT+PA showed antagonism (p<0.05). When a follow-up dilution study was carried out using binary combinations of PMs at three different dilution levels (i.e. IC25, 0.5∗IC25, 0.25∗IC25), only the mixture of CIT+OTA at 0.5∗IC25 was determined to have synergism by both IA and CA concepts with Model Deviation Ratios (MDRs; the ratio of predicted versus observed effect concentrations) of 1.4 and 1.7, respectively. The joint effect of OTA+MPA, OTA+PA and CIT+PAT complied with the IA concept, while CIT+PA, PAT+MPA and PAT+PA were better predicted with the CA over the IA concept. The present study suggests to test both IA and CA concepts using multiple doses when assessing risk of mycotoxin mixtures if the mode of action is unknown. In addition, the study showed that the tested PMs could be predicted by IA or CA within an approximate two-fold certainty, raising the possibility for a joint risk assessment of mycotoxins in food and feed.
Insights
Penicillium mycotoxins (PMs) mixtures pose joint toxicity risks. Assessing combinations like citrinin (CIT) and ochratoxin A (OTA) using independent action (IA) and concentration addition (CA) concepts is crucial for feed safety.
Area of Science:
- * Food Science and Toxicology
- * Animal Nutrition and Feed Safety
- * Mycotoxicology
Background:
- * Penicillium mycotoxins (PMs) are common, toxic contaminants in animal feed, often occurring as mixtures.
- * Understanding the joint toxicity of these PM mixtures is critical for accurate risk assessment.
- * Previous studies have highlighted the need for evaluating combined effects rather than individual toxins.
Purpose of the Study:
- * To assess the joint toxicity of binary combinations of five Penicillium mycotoxins (PMs).
- * To compare the predictive power of independent action (IA) and concentration addition (CA) concepts for PM mixtures.
- * To investigate the synergistic or antagonistic effects of PM combinations on bovine macrophage proliferation.
Main Methods:
- * Analysis of previously published toxicity data (IC25 values) for PM combinations.
- * Conducting a dilution study using binary PM combinations at three different concentration levels (IC25, 0.5*IC25, 0.25*IC25).
- * Applying independent action (IA) and concentration addition (CA) models to evaluate joint toxicity and calculate Model Deviation Ratios (MDRs).
Main Results:
- * Initial analysis indicated synergism for Ochratoxin A (OTA) + Penicillic Acid (PA) and antagonism for Patulin (PAT) + PA.
- * A follow-up study found synergism for Citrinin (CIT) + OTA at 0.5*IC25 using both IA and CA concepts (MDRs 1.4 and 1.7).
- * Specific PM combinations were better predicted by IA (e.g., OTA+MPA) or CA (e.g., CIT+PA), with predictions within an approximate two-fold certainty.
Conclusions:
- * Both IA and CA concepts should be tested using multiple doses when the mode of action of mycotoxin mixtures is unknown.
- * The study demonstrates the potential for joint risk assessment of mycotoxins in food and feed, considering their combined effects.
- * Predictive models (IA/CA) offer valuable insights into mycotoxin mixture toxicity within a defined certainty range.
