modified mycotoxins, emerging mycotoxins

and interactions

The probability of finding raw materials to be contaminated with more than one mycotoxin is high and their effects are determined by the interactions between them.

Mariano Gorrachategui

Animal nutrition consultant and president of CESFAC

Co-occurrence of mycotoxins

We know that a certain mycotoxin can be produced by several types of fungi and that the same toxigenic fungus can produce several mycotoxins.

Moreover, nowadays there are different sources of raw materials. Cereals, plant protein crops, and oilseeds grow and are harvested in a diverse range of climatological conditions, determining the growth of the fungi and the toxins produced. The storage and transport conditions also affect the fungus and toxins that can be produced during that time.

Under these conditions, it’s easy to understand that the odds of finding only one mycotoxin contaminating raw materials or feed are slim. Thus, the term “co-occurrence” is increasingly being used when referring to the simultaneous presence of two or more mycotoxins in the same sample.

There are many publications in literature that highlight the co-occurrence of mycotoxins:

In Germany, Goertz et al. (2010) found corn to be simultaneously contaminated with at least 14 Fusarium mycotoxins:

  • ⇰ Deoxynivalenol (DON) and its acetylated forms
    ⇰  Zearalenone (ZEA)
  • ⇰ Moniliformin (MON)
  • ⇰ Beauvericin (BEA)
  • ⇰ Nivalenol (NIV)
  • ⇰ Eniantins (ENNs)
  • ⇰ Fumonisins (FBs)
  • ⇰ HT2 Toxin

En un seguimiento global, Streit y col. (2013a) indicaron que, en piensos y materias primas, el 72% de las muestras contenían más de una micotoxina.

Streit et al.., (2013b) observed 83 samples of feed and raw materials to be contaminated with 7 to 69 mycotoxins per sample, having detected up to 169 different compounds.

Other studies have revealed the simultaneous presence of several mycotoxins in samples from European countries (Almeida et al., 2011; Blajet-Kosicka et al., 2014; Driehuis et al., 2008; Labuda et al., 2005a, 2005b; Monbaliu et al., 2010), finding a high percentage of samples to be contaminated with trichothecenes (DON, AcDon, T2, HT2) and FBs at the same time, as well as with ZEA in many cases.

In Spain, the study published by Ibáñez-Bea et al. (2012) regarding the simultaneous presence of AFB1, ZEA, and OTA in samples of barley harvested in 2007 and 2008, revealed:

  • ⇰ The presence of the three mycotoxins in 27% of the samples
  • ⇰ The presence of AFB1, together with any one of the other two in 43% of the samples

The same authors detected DON in 95% of the samples and two mycotoxins from this group in 43% of the samples.

Taken together, the results of these studies reveal that 96% of the samples contained three or more mycotoxins. The most frequent combinations are:

  • AFB1, OTA, and DON in 29% of the samples
  • AFB1, OTA, DON, and ZEA en 26% of the samples

More recent data (Biomin, 2017) from the analysis of 1.378 samples indicated that 94% of the samples contained more than 10 mycotoxins and metabolites and that the average was of 28 mycotoxins.

In another study, Raj et al. (2017), after screening 113 samples of maize from Serbia and Bosnia and Herzegovina for mycotoxin contamination, found 28% of the samples to be contaminated with more than one mycotoxin. In another study, the authors reported 76% samples contaminated with one or more mycotoxins (Raj et al., 2019).

Regarding fodder, recently there has also been data published (Panasiuk et al., 2019).


Modified mycotoxins 

In addition to co-occurrence, there is another phenomenon, the presence of the so-called “masked mycotoxins”.

This term was first coined by Gareis et al. (1990)

in reference to some cases of mycotoxicosis in which, the clinical signs observed in the animals couldn’t be explained by the low content of the mycotoxins detected in the feed.

Masked mycotoxins are defined as “mycotoxins that are not detectable through standard routine analytical techniques”.

Years later, Berthiller y col. (2013) and, particularly, Rychlik y col. (2014) introduced the terms following terms:

  • “Matrix-associated mycotoxins” refer to mycotoxins that are associated with oligosaccharides and starch, and that are physically trapped or bound by covalent bonds, as in the case of Fumonisins.
  • “Modified mycotoxins” including:
    • “Biologically” modified mycotoxins, for example, by conjugation, with polar compounds, mainly β-glycoside, sulfate or even glutathione, and that would fall under the denomination of “masked”.

    • “Chemically” modified mycotoxins, produced as a consequence of thermal processes or other kinds of processes that take place during the production of feed.

EFSA (2014a) refers to “modified mycotoxins” as all the forms that have been structurally modified in relation to their “parental compound” o the free mycotoxin.


Emerging mycotoxins

The development of methods based on chromatographic techniques and mass spectrophotometry enables us to reliably detect smaller quantities of more and more compounds. Therefore, we are discovering new molecules that may have toxic effects and interactions that we know little about, making it important to study them in order to produce safe food.

We are referring to the so-called “emerging mycotoxins”. Although this term hasn’t been clearly defined, in general, we refer to:

  • Fusarium metabolites such as eniantins (ENNs), beauvericin (BEA), moniliformin (MON), fusaproliferin (FP), fusidic acid (FA), culmorin (CUL), and butenolide (BUT).
  • Aspergillus metabolites such as sterigmatocystin (STE) and emodin (EMO).
  • The Penicillium metabolite, mycophenolic acid (MPA).
  • Alternaria metabolites, that include more than 70 toxins. The best-known ones are alternariol (AOH), monomethyl alternariol ether (AME), altenuene (ALT), altertoxin (ATX) and tenuazonic acid (TeA) (Gruber- Dorninger y col., 2017).

This list is a non-exclusive list and, although these mycotoxins are not routinely screened for at the moment and they are not contemplated in animal feed legislation, there can be issues of toxicity or interactions between them.


What do we know about the toxicity of emerging mycotoxins?


ENNs colonize cereals and can accumulate in grains. However, they have not been linked to any transcendent pathologies in animals (Marín García, 2010).

According to EFSA (2014b), there is a low probability that acute exposure to BEA and ENNs has adverse effects on the health of livestock and companion animals. It is also improbable to see adverse effects due to chronic exposure in birds, although there isn’t enough information to assess them in other species.


Regarding MON toxicity (EFSA, 2018), the available data on birds, pigs, and minks indicates that exposure to MON via consumption of feed poses a low or insignificant risk for these species under current feeding practices.

For the rest of the species, EFSA concludes that the risk is low or insignificant, but there isn’t enough information available on its toxicity to assess the risk.


Information relative to animal sensitivity to Alternaria toxin (EFSA, 2011) is scarce and doesn’t allow to estimate the levels of tolerance for individual toxins and their combinations. There is only some information about toxicity in birds for evaluating the risk of these mycotoxins.

EFSA concludes that it is improbable for AOH to pose a risk in broilers, but it is not entirely possible to exclude it as a risk for the species. Lack of toxicological data prevents us from drawing conclusions regarding other species.


Interactions between mycotoxins

A veces se observan sintomatologías difíciles de explicar por la presencia de una única o varias micotoxinas o por la cantidad presente en pienso (Trenholm et al., 1983). Estos problemas se han relacionado con la interacción entre varias micotoxinas presentes, muchas de las cuales no se determinan analíticamente.

This basic theory also explains the well-known fact that naturally contaminated food/feed is more toxic than the ones equally contaminated with purified mycotoxins (Trenholm et al., 1994).

Klaasen and Eaton (1991) classify the effects of the interactions between mycotoxins as:

  • Less than additive
  • Additive
  • Synergic
  • Enhanced
  • Antagonistic

Synergic effects of mycotoxins

In general, we know or sense that in most cases there are additive or synergic effects (Speijers and Speijers, 2004; Pedrosa, 2010). Many authors have highlighted this additivity, synergy or enhancement:

Grenier et al. (2011) demonstrated in corn that the liver tumors initiated by AFB1 are exacerbated by the presence of FB1.

Furthermore, after reviewing 112 publications on the toxicological interactions between mycotoxinsGrenier y Oswald (2011) found synergies and additivities associated with performance in most of the studies published. However, in relation to other parameters, especially biochemical ones, the results are more variable, ranging from synergic to antagonistic effects for the same combination of toxins.

Stoev y col. (2010) came to a similar conclusion when studying nephropathies in poultry and pigs that could not be explained only by the content of OTA, under the limit recommended by the EU, finding the explanation in the simultaneous presence of OTA, FB1, and penicillic acid (PCA).

Phenomena such as the ones previously described justify the need to carry out multi-mycotoxins analysis in order to understand the effects that are seen in the field.


Antagonistic effects of mycotoxins

Although most results reveal the additive or synergic effects of mycotoxins, it should be noted that antagonistic effects can also be seen (Koshinsky y Khachatourians, 1992; Bernhoft y col., 2004).

Thus, antagonism has been observed between:

  • DON and FB1 (Ficheux et al., 2012; Wam et al., 2013a)
  • DON and ZEA (Bensassi et al., 2014; Wam et al., 2013)
  • DON and T2 (Thuvander et al., 1999; Ruíz et al., 2011)
  • DON and DAS (Thuvander et al., 1999)
  • NIV and DON or FB1 (Wam et al., 2013)
  • NIV and ZEA (Wam et al., 2013)
  • BEA with DON or T2 (Ruiz et al., 2011)

Some publications reveal antagonistic effects associated with the simultaneous presence of three or more mycotoxins. For example, DON, NIV y FB1; NIV, ZEA, FB1 and DON, NIV, ZEA, and FB1 (Wam et al., 2013).

Yang et al. (2017) demonstrated the antagonistic effect between some modified DON toxins (acetylated derivatives), such as 15-ADON + NIV and 15-ADON + FX.


Interactions between mycotoxins – In vitro vs in vivo

Most of these studies have been conducted in in vitro scenarios, with cell viability as the main parameter, although there are other criteria, such as:

  • ⇰ Apoptosis and cell necrosis
  • ⇰ DNA damage
  • ⇰ Oxidative damage
  • ⇰ Immunotoxicity

Obviously, the combined toxic effects that are observed will depend on the experimental design:

  1. Type of cells that are exposed
  2. Exposure time
  3. Dosage and relation between mycotoxins
  4. Final points and tests used
  5. Statistical aspects of the models

A clear example that highlights the importance of the experimental design is the study carried out by Klaric y col. (2012)

to asses the interactions between OTA and citrinin (CIT) in a model with PK15 kidney epithelial cells from pigs, determining the final effect via cell viability, apoptosis, necrosis, and genotoxicity, obtaining the following results:

  • Synergic effect on cell viability, apoptosis, and necrosis.
  • Antagonistic effect for genotoxicity.

Another factor that has complicated the interpretations up to now is that the response that is observed in vivo does not always correlate with what is seen in vitro.

To illustrate this phenomenon, we can refer to the example of the interaction between DON and T-2.

In vitro studies reveal antagonism  (EFSA, 2002), probably due to the competence for binding sites.

However, results from in vivo studies with mice (Schiefer y col., 1986)

demonstrate that the negative effects of DON in the animals are exacerbated in the presence of T-2, while in vivo studies with pigs (Friend y col., 1992) indicate that DON combined with T-2 present antagonism (with T-2 at half of the dose of DON).

There are other published examples, such as the interaction between DON and ZEA, in which Swamy y col. (2002) highlight their in vivo synergic effects in piglets, while Ji y col. (2017) demonstrate their antagonistic effects in mice.

Regarding the loss of growth that is sometimes observed in vivo in response to the presence of mycotoxins, Andretta y col. (2015) point out that it is due to an increase in the energy required for the animals’ maintenance, which is supported by Pastorelli y col. (2012).

It is clear that the effects of the combination of mycotoxins cannot be predicted based solely on their individual effects and that, in addition to additivities and synergies, there can also be antagonisms.

It is very difficult to predict these responses as they are dose, species, and toxin-dependent, in addition to the variability due to methodology-related factors.



It goes without saying that the in vitro methodology must be standardized at an international level in order to expand our knowledge about the interactions between mycotoxins and to have access to comparable data.

These standards would only be valid if they could predict the in vivo response in animals.

Analysing a single mycotoxin may not be enough to explain many cases. However, excessive analytical information, if not correctly interpreted, isn’t a solution either, making it important to carry out further studies.

Under these circumstances, without renouncing to other tools, the best way to reduce the risk is prevention through good agricultural practices and risk analysis in the primary links of the food chain.

The application of atoxic fungi that grow on the crops, as well as varieties that are resistant to the colonization of toxigenic fungi or climate models that predict the presence of mycotoxins are some of the methods that are available to counteract the negative effects of mycotoxins and significantly reduce the risk.



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