on December 2, 2015http://rsif.royalsocietypublishing.org/Downloaded from

rsif.royalsocietypublishing.org

ResearchCite this article: Medina A, Schmidt-Heydt

M, Cardenas-Chavez DL, Parra R, Geisen R,

Magan N. 2013 Integrating toxin gene

expression, growth and fumonisin B1 and B2

production by a strain of Fusarium verticillioides

under different environmental factors. J R Soc

Interface 10: 20130320.

http://dx.doi.org/10.1098/rsif.2013.0320

Received: 8 April 2013

Accepted: 30 April 2013

Subject Areas:systems biology, biotechnology,

computational biology

Keywords:fumonisin genes, systems biology, water

activity, temperature, predictive modelling,

ternary relationships

Author for correspondence:Naresh Magan

e-mail: n.magan@cranfield.ac.uk

& 2013 The Author(s) Published by the Royal Society. All rights reserved.

Integrating toxin gene expression, growthand fumonisin B1 and B2 production by astrain of Fusarium verticillioides underdifferent environmental factors

Angel Medina1, Markus Schmidt-Heydt2, Diana L. Cardenas-Chavez3,Roberto Parra3, Rolf Geisen2 and Naresh Magan1

1Applied Mycology Group, Cranfield Health, Cranfield University, Bedfordshire, ALCS MK43 0AL, UK,2MaxRubner-Institute, Haid-und-Neu-Str. 9, 76131 Karlsruhe, Germany3Centro del Agua para America Latina y el Caribe (CAALCA), Instituto Tecnologico de Monterrey,Campus Monterrey, NL 64849, Mexico

The objective of this study was to integrate data on the effect of water activity

(aw; 0.995–0.93) and temperature (20–358C) on activation of the biosynthetic

FUM genes, growth and the mycotoxins fumonisin (FB1, FB2) by Fusariumverticillioides in vitro. The relative expression of nine biosynthetic cluster

genes (FUM1, FUM7, FUM10, FUM11, FUM12, FUM13, FUM14, FUM16and FUM19) in relation to the environmental factors was determined using

a microarray analysis. The expression was related to growth and phenotypic

FB1 and FB2 production. These data were used to develop a mixed-growth-

associated product formation model and link this to a linear combination

of the expression data for the nine genes. The model was then validated by

examining datasets outside the model fitting conditions used (358C). The

relationship between the key gene (FUM1) and other genes in the cluster

(FUM11, FUM13, FUM9, FUM14) were examined in relation to aw, tempera-

ture, FB1 and FB2 production by developing ternary diagrams of relative

expression. This model is important in developing an integrated systems

approach to develop prevention strategies to control fumonisin biosynthesis

in staple food commodities and could also be used to predict the potential

impact that climate change factors may have on toxin production.

1. IntroductionFusarium verticillioides (teleomorph, Gibberella moniliformis) is an economically

important maize pathogen which colonizes ripening cobs and contamina-

tes the maize with fumonisins (FB; B1–B4). These toxins are important as

they have toxic effects by inhibition of sphingolipid metabolism which can

impact on human and animal health. For example, fumonisins cause leuko-

encephalomalacia, a brain lesion which can be fatal to horses after consumption

of contaminated animal feed. Fumonisins have also been associated epidemio-

logically with human oesophageal cancer and birth defects, especially neural

tube defects in humans [1]. The genome of F. verticillioides has been elucidated

[2] and the FB biosynthetic genes are clustered together as for other mycotoxi-

genic fungi (e.g. Aspergillus flavus; Fusarium graminearum). This may facilitate

horizontal transfer and co-ordinated transcriptional regulation of the genes in

the FB biosynthetic cluster which consists of 17 transcriptionally co-regulated

genes. Fumonisin polyketide synthase (FUM1) is the important gene of the cluster

of co-regulated fumonisin biosynthetic genes. The cluster also encodes an amino-

transferase (FUM8), a C-3 carbonyl reductase (FUM13), and cytochrome P450

and other enzymes that catalyse oxygenation at C-5 (FUM3), C-10 (FUM2) and at

another undefined site (FUM6) [3]. Four other genes (FUM7, FUM10, FUM11,

FUM14) are also required for tricarballylic acid esterification. At the opposite end

of the cluster from FUM1 there are transporter encoding genes (FUM19, FUM17

rsif.royalsocietypublishing.orgJR

SocInterface10:20130320

2

on December 2, 2015http://rsif.royalsocietypublishing.org/Downloaded from

and FUM18). These have been suggested as being involved in

fumonisin self-protection and sphingolipid metabolism.

The biosynthesis of mycotoxins is strongly dependent on

growth conditions such as substrate composition [4] or phys-

ical factors including pH, water availability, temperature or

modified atmospheres [5–8]. Water activity (aw) is a good

measure of the amount of freely available water in a substrate

for microbial growth and is related to pure water, which has a

aw of 1.00 or 100 per cent equilibrium relative humidity. This

aw is related to the total moisture content of a specific sub-

strate by a moisture sorption curve [9]. Thus, depending on

the combination of abiotic factors the biosynthetic pathway

for FBs will be activated or completely inhibited. Marin

et al. [10] showed that the aw � temperature conditions for

germination, growth and phenotypic FB production were

different with much narrower limits of these two interacting

parameters for mycotoxin production. Models of the pro-

duction of FB in relation to interacting abiotic conditions

have been examined [11,12], although such data have not pre-

viously been related to the FB gene cluster expression. Studies

by Jurado et al. [13] showed that expression of the FUM1 gene

was significantly increased under water stress conditions

(0.95 aw) which may indicate an increase in FB production

by F. verticillioides under such conditions. In contrast, studies

with Fusarium proliferatum, which has a much broader host

range than the former species, showed that FUM1 gene

expression was more stable under water stress, suggesting

that FB production may not be an important determinant of

pathogen infection of maize by this species [14].

Previous studies using a mycotoxin microarray with sub-

arrays for specific mycotoxins, developed by Schmidt-Heydt &

Geisen [15] have shown the impact of key environmental

factors (aw, temperature) on important mycotoxin genes of the

aflatoxin gene cluster (A. flavus) and of the trichothecene gene

cluster (F. graminearum, Fusarium culmorum) and phenotypic

mycotoxin production [16]. Recently, Schmidt-Heydt et al. [17]

showed that for F. culmorum and F. graminearum it is possible

to integrate such microarray data on relative TRI gene expression

under different environmental conditions, growth and deoxyni-

valenol (DON) production and develop models which can be

used to predict DON concentrations. In 2012 Abdel-Hadi et al.[18] demonstrated that data on key genes in the biosynthesis of

aflatoxin, including the key regulatory genes (aflR, aflS) could

be integrated with growth and aflatoxin production by using a

mixed-growth model. This also enabled the relatively accurate

prediction of aflatoxin production at increased temperatures

and water stress conditions relevant to climate change type scen-

arios. No such integrated systems approach has been attempted

for such datasets for F. verticillioides.Here, we have used the mycotoxin microarray sub-array

described previously [15] for the FB genes as a tool for examin-

ing the changes that interacting environmental factors may have

on the relative expression of the F. verticillioides gene cluster, as

well as effects on growth and phenotypic fumonisin pro-

duction. The objectives of this study were (i) to examine the

effect of aw � temperature conditions on growth, FB1 and FB2

production and relative expression of nine genes of the FUM

cluster (FUM1, FUM7, FUM10, FUM11, FUM12, FUM13,

FUM14, FUM16 and FUM19) in the fumonisin biosynthetic

pathway using the mycotoxin gene microarray; (ii) to quantify

the amounts of FB1 and FB2 produced under these interacting

conditions; (iii) to evaluate the mixed-growth model appli-

cation to integrate the relationship between the expression of

these genes, environmental factors, growth and FB1 and FB2

production; (iv) to validate the model with datasets outside

the range of the model and (v) to examine the possible ternary

interactions and relationships between FUM1, a key gene, and

some other genes in the biosynthetic pathway in relation to

aw, temperature and fumonisin FB1 and FB2 production.

2. Material and methods2.1. Fungal strain usedThe F. verticillioides strain (MPVP No 294) has been kindly sup-

plied by Prof. P. Battilani, University Sacre Cuore, Piacenza,

Italy and is from the Italian Culture Collection and was stored

at 48C or sub-cultured on a 2 per cent maize meal agar when

required. It has a known fumonisin production capacity [19].

2.2. Growth studiesThese were carried out with a conducive YES medium (20 g yeast

extract, 150 g sucrose, 1 g MgS04. 7H20, 1 l). The agar medium

was modified with glycerol to adjust the water availability to

0.995, 0.98, 0.95, 0.93 aw as described previously [20,21]. The

accuracy of the modifications was confirmed using an Aqualab

3TE instrument (Decagon, Pullman, WA, USA) and found to

be within +0.005 of the target aw.

Petri plates (Ø 9 cm) containing media treatments and over-

laid with sterile 8.5 cm cellophane discs (P400, Cannings Ltd,

Bristol, UK) were inoculated using small agar plugs (Ø 3 mm)

taken from 7–8-day-old growing cultures grown at 258C. Repli-

cates (five per treatment) were incubated at 20, 25 and 308C for

model design and temperature outside the model boundaries:

358C was used to validate the model. Assessment of growth

was made daily during the 10-day incubation period, the optimal

time for FUM1 gene expression [13]. Two diameters of the grow-

ing colonies were measured at right angles to each other until the

whole colony biomass was scraped from the cellophane surface

into Eppendorf tubes and frozen at 2808C for RNA extraction.

2.3. Isolation of RNA from samplesTo perform microarray experiments RNA was isolated using the

RNAeasy Plant Mini kit (Qiagen, Hilden, Germany). The procedure

was made according to the manufacturer’s instructions except for

the ground of 1 g of mycelium with a mortar and pestle in liquid

nitrogen, of which 250 mg of resulting powder was suspended in

750 ml lysis buffer, mixed with 7.5 ml b-mercaptoethanol and 100

glass beads with a diameter of 1 mm (B. Braun Biotech International

GmbH, Melsungen, Germany) in a 2 ml RNase-free micro reaction

tube. These extracts were mixed thoroughly and incubated for

15 min at 558C and 42 kHz in an S10H ultrasonic bath (Elma,

Singen, Germany).

2.4. Microarray experimentscDNA synthesis and labelling were performed using 50 mg of the

DNase I treated total RNA and the Micromax Direct Labeling kit

(Perkin Elmer Life And Analytical Sciences, Inc., Boston, USA).

The cDNA was subsequently purified with the QiaQuick Min

Elute kit (Qiagen, Hilden, Germany), dried in a vacuum con-

centrator (Speed Vac, Savant Instruments, Farmingdale, USA),

re-suspended in 60 ml hybridization buffer (Scienion, Berlin,

Germany), heated for 2 min at 958C, placed on ice to prevent

strand rearrangement and hybridized for 18 h at 428C to the

microarray by using an automatic hybridization station (Perkin

Elmer, Boston, USA). This array was scanned with a confocal

laser system (Scanarray lite, Perkin Elmer) at a resolution of

5 mm. The results were normalized using the Lowess algorithm

rsif.royalsocietypublishing.orgJR

SocInterface10:20130320

3

on December 2, 2015http://rsif.royalsocietypublishing.org/Downloaded from

(locally weighted scatter plot smoothing) together with sub-

traction of the background signal. The constitutively expressed

b-tubulin gene was used as a control.

2.5. Fumonisin B1 and B2 analyses2.5.1. Fumonisins extraction and derivatizationFumonisins were extracted from agar plugs cut out with the aid of

a cork borer (Ø ¼ 5 mm) 10-day-old cultures of Fusarium. The

plugs were then placed in pre-weighed 2 ml Eppendorff tubes.

The tubes and their contents were weighed and the mass recorded.

Fumonisins were extracted by adding 1 ml of acetonitrile/water

(50 : 50, v/v) and then shaking the mixture for 60 min [22].

Sample extract (50 ml) was derivatized by mixing with 200 ml

of o-phthaldehyde (OPA) solution. The solution was prepared by

dissolving 40 mg OPA in 1 ml of methanol followed by addi-

tion of 5 ml of 0.1 M sodium tetraborate solution and 50 ml

of 2-mercaptoethanol [22]. The different concentrations of FB1

and FB2 standard (50 mg ml21: Sigma-Aldrich, Chemie GmbH,

Steinheim, Germany) were similarly derivatized prior to injection.

2.5.2. HPLC-FLD detection and quantificationThe derivatized sample (25 ml) was analysed by HPLC (Agilent

1200 series) with a fluorescence detector set at excitation and emis-

sion wavelengths of 355 and 440 nm, respectively. Separation was

achieved using C18 chromatographic analytical column (Phenom-

enex Gemini; 150 � 4.6, 3 mm particle size: Phenomenex, CA,

USA). The mobile phases were (A) methanol/0.05 M sodium di-

hydrogen phosphate aqueous solution adjusted to pH 5.0 with

2 M NaOH (50/50, v/v) and (B) acetonitrile/water (80/20, v/v).

Each mobile phase was filtered by passing through a 0.45 mm

filter and degassed by means of an on-line degassing device

(Agilent). The gradient program was 100 per cent A during

5 min followed by a rapid increase to 50 per cent A þ 50 per cent

B with a final hold of 15 min. The column was kept at 308C with

a flow rate of 1.0 ml min21. Quantification of fumonisins was

achieved through comparison of peak areas of the chromatograms

of the samples with those of the fumonisins standard.

2.6. Data analysis and model developmentThis study has used a mixed-growth-associated product for-

mation model [23], which takes account of both specific growth

rate and metabolite accumulation. This includes the fact that pro-

duct formation is a combination of growth rate and the specific

rate of product formation which is given by equation (2.1). This

has been previously used for production of compounds such

as xanthan gum and for examining A. flavus growth and aflatox-

ins production [18]:

qP ¼ amþ b; ð2:1Þ

where qP is the total production of fumonisin B1 or B2 produced; a

and b are constants of fumonisin production associated with pri-

mary and secondary metabolism and m is the specific growth

rate. The specific rate of product formation is proportional to the

total biomass and the rate of product formation:

qP ¼1

XdPdt: ð2:2Þ

The rate of product formation for a growth-associated product is

related to the initial biomass (Xo) and the specific growth rate (m)

and the time (t). Thus, combining equations (2.1) and (2.2) results in

dPdt¼ ðamþ bÞX ð2:3Þ

and

dPdt¼ X0emt: ð2:4Þ

The rate of microbial growth is characterized by the specific

growth rate, defined as

m ;1

XdXdt

: ð2:5Þ

After integration form from t ¼ 0 to t (days) and X(0) ¼ X0 to

X(t) ¼ X.

X ¼ X0emt X0 ¼ Xe�mt: ð2:6Þ

Substituting equation (2.6) and (2.3) we obtain:

dPdt¼ ðamþ bÞX0emt: ð2:7Þ

A temperature-dependent rate coefficient for growth rep-

resented by Arrhenius’s empirical equation is given by

m ¼ e�Ea=RT ; ð2:8Þ

Ea is the activation energy and R is the universal constant of the

gases (8.31 � 1023 J mol K21) and T is the absolute temperature

(K). If we assume that the rate of production is affected directly

by fungal growth rate and activation energy, we obtain

dPdt¼ ðamþ bÞX0emt � e�Ea=RT : ð2:9Þ

Based on previous experiments (data not shown), it was

observed that the activation energy could be adjusted as a quad-

ratic function:

Ea ¼ b1aw: ð2:10Þ

Thus,

dPdt¼ ðamþ bÞX0emte�b1aw=RT ð2:11Þ

andðP

0

dP ¼ ðamþ bÞX0e�b1aw=RTðt

0

emtdt: ð2:12Þ

After integration:

P ¼ aþ b

m

� �X0e�b1aw=RTðemt � 1Þ: ð2:13Þ

2.7. Generation of ternary contour surfacesof interactions between gene expression,environmental factors and fumonisinsproduction

In order to plot the ternary contour surfaces of the genetic

expression, a standardized signal from the microarray was calcu-

lated as follows for aw and for temperature to relate the relative

abundance of mRNA of the FB cluster genes (e.g. FUM11,

FUM13, FUM19) to the regulatory gene (FUM1):

fðawÞ ¼�

FUM1ðFUM1þ FUM11þ FUM13Þ ;

� FUM11ðFUM1þ FUM11þ FUM13Þ ;

� FUM13ðFUM1þ FUM11þ FUM13Þ

�

fðtemperatureÞ ¼�

FUM1ðFUM1þ FUM11þ FUM13Þ ;

� FUM11ðFUM1þ FUM11þ FUM13Þ ;

� FUM13ðFUM1þ FUM11þ FUM13Þ

�;

0

2

4

6

8

10

12

14

16

0.93 0.95 0.98 0.995

diam

etri

c gr

owth

rat

e (m

m d

–1)

water activity

20 25 30 35

Figure 1. Effect of temperature and water activity on the growth rate of astrain of F. verticillioides. Means of five replicates per treatment.

rsif.royalsocietypublishing.orgJR

SocInterface10:20130320

4

on December 2, 2015http://rsif.royalsocietypublishing.org/Downloaded from

where the standardized value ¼ actual value2minimum value/

maximum value2minimum value. For FB1 and FB2 production

the following equation was used:

f ðfumonisinB1 orB2 ðppmÞÞ¼�

FUM1ðFUM1þFUM11þFUM13Þ ;

� FUM11ðFUM1þFUM11þFUM13Þ ;

� FUM13ðFUM1þFUM11þFUM13Þ

�:

3. Results3.1. Effect of environmental factors on growth and

fumonisin B1 and B2 production by the strain ofF. verticillioides

Figure 1 shows the effect of interacting conditions of aw

and temperature on growth of the F. verticillioides strain

used in this study. This shows that optimum was at

0.995 aw and 20–258C but this changed to 0.98 aw at

30–358C. At 0.93 aw there was some growth but only

at 25–308C and this was less than 20 per cent of that under

optimum conditions.

Figure 2 shows the impact of aw � temperature effects on

the relative expression of the nine genes used in this study.

This shows that under some conditions there was an

increased expression of certain genes indicative of the effect

of drought�temperature stress.

Figures 3 and 4 show the effects of (i) aw and (ii) tempera-

ture on the production of FB1 and FB2, respectively.

The optimal temperature and aw for FB1 production were at

208C and 0.98–0.995, respectively, in contrast to that for

growth (308C and 0.98 aw). For FB2 production the optimum

aw was 0.98, while the optimum temperature for pro-

duction was broader than that for growth (20–308C). This

suggests marked differences in the growth optimum and

in the range of aw � temperature conditions when compared

with that for FB1 and FB2 production by F. verticillioides.

These data were used in conjunction with the relative gene

expression of nine genes involved in the biosynthesis of

fumonisins for modelling their relationship.

3.2. Modelling the relationship betweenenvironmental factors, gene expression andfumonisin B1 and B2 production

For assessing the relationship between physiological and

thermodynamic conditions, FB1 and FB2 production and

the expression of the gene clusters involved in toxin pro-

duction, the physical model previously described in §2.6

was combined with the gene expression data as a linear

combination. The generic cluster was

½g� ¼ a1FUM1þ a2FUM7þ a3FUM10þ a4FUM11þ a5FUM12þ a6FUM13þ a7FUM14þ a8FUM16þ a9FUM19;

ð3:1Þ

where a1 to a9 are the parameter estimates from the linear

combination of the expression of genes so that [g] represents

the sum of the effect of the individual genes expressed

under specific conditions. The final model which considers

aw, temperature, growth rate and gene expression on the

regulation of FB1 and FB2 is given by

P ¼ ½g� � aþ b

m

� �X0e�b1aw=RTðemt � 1Þ; ð3:2Þ

where P is the FB1 or FB2 production (ppm) and b1, b2, a and

b are parameter estimates from the model and m was calcu-

lated based on a period of 10 days growth and the

assumption that growth occurs in cylindrical fungal hyphal

extension with a constant radius simplified as

mt ¼ lnXf

Xi¼ ln

mf � r

mi � r

� �¼ ln

mf � vf=mf

mi � vi=mi

� �

¼ lnp� r2

A � Lf

p� r2A � Li

� �¼ ln

Lf

Li

� �; ð3:3Þ

Xf and Xi are final and initial biomass, mf and mi are

initial and final fungal mass, vf and vi are the initial

and final fungal road volume, r is the fungal density, rA is

the F. verticillioides hyphal radius and Lf and Li are the

radial growth.

Table 1 shows the actual mean data (n ¼ 3) for FB1 and

FB2 production and that predicted by this model in relation

to different combinations of temperature and aw and the rela-

tive mean growth rate.

Table 2 shows the ANOVA for the fit of the model and the

regressed coefficients and the corrected totals for FB1 and

FB2. This suggests that the model showed a good fit to the

data and was statistically significant. Table 3 shows the over-

all estimates and the dependence for the main areas that are

related to the model. All the parameters are statistically sig-

nificant at p , 0.01.

Figure 5a,b shows the model fit for the observed versus

predicted effects on FB1 and FB2, respectively. The fitted

line gave a good correlation between these parameters (FB1,

r2 ¼ 0.9736; FB2, r2 ¼ 0.9530).

3.3. Validation of the modelThe model was subsequently tested to examine whether it

could be used at temperatures of 358C at different aw levels.

These conditions were not originally included in the model

because of the limited data at these conditions. Table 4 shows

the effect on the observed and predicted FB1 and FB2 pro-

duction under these conditions. At 358C and 0.98 aw the

0.950

0.980

0.995

0.9300.950

0.9800.995

0.9500.995

0

5000

10 000

15 000

20 000

25 000

FUM19

FUM14

FUM11

FUM13

FUM1

FUM16

FUM12

FUM10

FUM7

20

25

30

gene

exp

ress

ion

(rel

ativ

e to

B-t

ubul

in g

ene)

FUM genes wat

er a

ctiv

ity-te

mpe

ratu

re (°

C)

Figure 2. Effect of temperature�water activity interactions on relative expression of nine FUM genes grown on a YES medium. (Online version in colour.)

rsif.royalsocietypublishing.orgJR

SocInterface10:20130320

5

on December 2, 2015http://rsif.royalsocietypublishing.org/Downloaded from

model predicted much higher FB1 production than was actu-

ally observed, whereas the FB2 model-predicted production

was slightly lower than observed in the same conditions of

aw and temperature. In contrast, the FB2 produced was similar

to the predicted value at 358C and 0.995 aw.

3.4. Ternary relationships between gene expression,environmental factors and FB1 and FB2 production

By using a standardized signal from the microarray dataset, it

was possible to examine the relative relationship between the

activity of the important FUM1 gene in the biosynthetic

pathway and related cluster genes in the pathway (FUM7,FUM10, FUM11, FUM12, FUM13, FUM14, FUM16 and

FUM19) at the same time in ternary diagrams in relation to

aw, temperature and FB1 and FB2 production. Only the

expression of FUM1, FUM11, FUM13, FUM14 and FUM19showed a significant effect on the synthesis of both fumoni-

sins, while the other genes exhibited very little response or

the effects were variable (data deposited in Cranfield

Health share point facility; Applied Mycology).

Figure 6 shows the effect of FUM1, FUM11 and FUM13relative gene expression on FB1 (i) and FB2 (ii) production,

respectively. These were calculated using the model below:

FB1 production ðmg ml�1Þ

¼ 10:7FUM1

ðFUM1þ FUM11þ FUM13Þ

� �

� 28:28FUM11

ðFUM1þ FUM11þ FUM13Þ

� �

þ 32:9FUM13

ðFUM1þ FUM11þ FUM13Þ

� �ð3:4Þ

and

FB2 production ðmg ml�1Þ

¼ �0:67FUM1

ðFUM1þ FUM11þ FUM13Þ

� �

� 11:0FUM11

ðFUM1þ FUM11þ FUM13Þ

� �

þ 15:89FUM13

ðFUM1þ FUM11þ FUM13Þ

� �:

ð3:5Þ

The production of FB1 proportionally increased to FUM11gene transcription but not FUM13. Notably, FUM1 was

down-regulated during FB1 overexpression.

For FB2 production, the relative expression of FUM11 and

FUM13 was inversely related to this parameter. As the

FUM11 and FUM13 expression increased, the production of

FB2 was reduced. FUM1 expression was weakly correlated

to the production of fumonisin B2.

Similar ternary diagrams for the interaction between

FUM1 and the FUM cluster genes FUM19 and FUM14 are

presented in figure 7. The relative expression of the three

genes in relation to FB1 and FB2 production was calculated

based on

FB1 production ðmg ml�1Þ

¼ 8:7FUM1

ðFUM1þ FUM19þ FUM14Þ

� �

þ 0:8FUM19

ðFUM1þ FUM19þ FUM14Þ

� �

þ 19:7FUM14

ðFUM1þ FUM19þ FUM14Þ

� �ð3:6Þ

mean(a)

(b)

mean ± 0.95 s.e.

meanmean ± 0.95 s.e.

0.92

0.93

0.94

0.95

0.96

0.97

0.98

0.99

1.00

1.01

water activity

0

2

4

6

8

10

12

14

16FB

1 (µ

g m

l–1 )

FB1

(µg

ml–

1 )

temperature (°C)

020 22 24 26 28 30 32 34

2

4

6

8

10

12

14

16

Figure 3. The effect of (a) water activity (aw) and (b) temperature on thefumonisin B1 production by a strain of F. verticillioides. Bars indicate standarderror of the means.

(a)

(b)

meanmean ± 0.95 s.e.

meanmean ± 0.95 s.e.

water activity

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

20 22 24 26 28 30 32 34temperature (°C)

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

FB2

(µg

ml–

1 )FB

2 (µ

g m

l–1 )

0.92

0.93

0.94

0.95

0.96

0.97

0.98

0.99

1.00

1.01

Figure 4. The effect of (a) water activity (aw) and (b) temperature on thefumonisin B2 production by a strain of F. verticillioides. Bars indicate standarderror of the means.

rsif.royalsocietypublishing.orgJR

SocInterface10:20130320

6

on December 2, 2015http://rsif.royalsocietypublishing.org/Downloaded from

Table 1. Experimental data and model estimation for FB1 and FB2 at different temperatures, water activity and fungal growth rate of the strain of Fusariumverticillioides.

temp.(88888C)

wateractivity

m+++++ s.d.(mm d21)

experimental model estimation

FB1+++++ s.d.(mg ml21)

FB2+++++ s.d.(mg ml21)

FB1+++++ s.d.(mg ml21)

FB2+++++ s.d.(mg ml21)

20 0.95 3.52+ 0.03 9.27+ 0.62 1.67+ 0.17 9.32+ 0.08 1.65+ 0.01

20 0.98 8.29+ 0.37 13.49+ 5.69 4.31+ 0.27 13.59+ 0.89 5.65+ 2.48

20 0.995 9.86+ 0.16 15.25+ 1.11 0.00+ 0.00 15.21+ 0.25 20.35+ 1.2

25 0.93 1.70+ 0.08 0.71+ 0.71 0.47+ 0.47 0.85+ 0.05 0.45+ 0.00

25 0.95 5.26+ 0.09 11.65+ 2.46 6.96+ 1.96 11.58+ 0.21 6.99+ 0.12

25 0.98 11.72+ 0.39 5.39+ 1.11 2.76+ 0.82 5.15+ 0.17 1.66+ 0.35

25 0.995 14.68+ 0.12 2.46+ 1.83 0.00+ 0.00 2.48+ 0.02 0.16+ 0.01

30 0.95 6.21+ 0.32 1.54+ 0.25 0.87+ 0.10 1.46+ 0.08 1.03+ 0.08

30 0.995 10.47+ 0.29 3.56+ 0.99 0.06+ 0.06 3.59+ 0.09 0.28+ 0.13

Table 2. Statistical analysis of the ANOVA for the fit of the model and the regressed coefficients and the corrected totals for FB1 and FB2 by F. verticillioides.

sum of squares d.f. mean squares F-value p-value

ANOVA: FB1

regression 1819.656 13 139.9735 120.35 0

residual 23.260 20 1.1630

total 1842.916 33

corrected total 847.539 32

regression versus corrected total 1819.656 13 139.9735 5.2849 0.000061

ANOVA: FB2

regression 202.5820 13 15.58323 49.97915 0

residual 6.2359 20 0.31179

total 208.8179 33

corrected total 132.6695 32

regression versus corrected total 202.5820 13 15.58323 3.75869 0.001121

rsif.royalsocietypublishing.orgJR

SocInterface10:20130320

7

on December 2, 2015http://rsif.royalsocietypublishing.org/Downloaded from

and

FB2 production ðmg ml�1Þ

¼ �2:98FUM1

ðFUM1þ FUM19þ FUM14Þ

� �

þ 1:83FUM19

ðFUM1þ FUM19þ FUM14Þ

� �

þ 5:92FUM14

ðFUM1þ FUM19þ FUM14Þ

� �:

ð3:7Þ

The production of both fumonisins FB1 and FB2 was

increased with higher relative expression of the FUM19gene. In contrast, this fumonisin production was inversely

related to FUM14 signal. As the FUM1 gene expression was

increased, the production of FB1 was reduced and that of

FB2 increased.

The effect of aw on the relative gene expression (standar-

dized) of the genes (i) FUM1, FUM11 and FUM13 and (ii)

FUM1, FUM14 and FUM19 was calculated using the relative

fractions ( f ) of these individual genes (figure 8).

For aw, this was

aw ¼ 0:99FUM1

ðFUM1þ FUM11þ FUM13Þ

� �

þ 1:09FUM11

ðFUM1þ FUM11þ FUM13Þ

� �

þ 0:79FUM13

ðFUM1þ FUM11þ FUM13Þ

� �ð3:8Þ

and

aw ¼ 0:93FUM1

ðFUM1þ FUM14þ FUM19Þ

� �

þ 1:07FUM14

ðFUM1þ FUM14þ FUM19Þ

� �

þ 0:88FUM19

ðFUM1þ FUM14þ FUM19Þ

� �: ð3:9Þ

As the aw increased, the expression of the genes FUM11 and

FUM14 was reduced. The higher expression of FUM1 was

observed under dried conditions (0.94 aw), and FUM13signal decreased at these aw levels. The transcription of

FUM19 was less affected by water availability.

Figure 9 shows the relative expression of FUM1 and the

biosynthetic genes FUM11, FUM13, and FUM14, FUM19 in

relation to temperature. These relationships were calculated

as shown below:

Tð8CÞ ¼ 19:3FUM1

ðFUM1þ FUM11þ FUM13Þ

� �

þ 96:07FUM11

ðFUM1þ FUM11þ FUM13Þ

� �

� 37:7FUM13

ðFUM1þ FUM11þ FUM13Þ

� �ð3:10Þ

and

Tð8CÞ ¼ 17:0FUM1

ðFUM1þ FUM14þ FUM19Þ

� �

þ 28:0FUM14

ðFUM1þ FUM14þ FUM19Þ

� �

þ 31:7FUM19

ðFUM1þ FUM14þ FUM19Þ

� �: ð3:11Þ

There was an inverse proportional effect of temperature on

the expression of FUM11 and FUM19. Thus, the higher the

temperature, the lower FUM11 and FUM19 gene signal. The

FUM1 gene transcription was proportionally increased with

temperature. The expression of FUM13 and FUM14 was simi-

lar under different temperature conditions.

4. DiscussionThis study has examined the impact that environmental factors

can have on FUM cluster genes and the effects that they have on

FB1 and FB2 production by a strain of F. verticillioides. This has

shown that temperature and aw have a profound effect on both

gene expression of key biosynthetic genes as well as signifi-

cantly affecting growth and the phenotypic production of the

toxic secondary metabolites.

The main factors influencing the growth of the strain of

F. verticillioides included environmental temperature and

water availability of the substrate [10,24]. Previous studies

have shown that fungal growth occurs within a wide range

of temperatures, with the optimum ranging from 22.5 to

27.58C and a minimum water availability of 0.87 [25,26].

Table 3. The estimates and the dependence on the main factors that arerelated to the model for (a) FB1 and (b) FB2 production by F. verticillioides.

parameter estimate

(a)

gene cluster for FB1 biosynthesis

a1 (FUM19) 6.1055

a2 (FUM14) 27.5810

a3 (FUM11) 21.5341

a4 (FUM13) 27.3617

a5 (FUM1) 29.9819

a6 (FUM16) 2.0508

a7 (FUM12) 9.1501

a8 (FUM10) 1.2260

a9 (FUM7) 2.7745

mixed-growth-associated product formation

a 1.2446

b 27.8988

initial inoculum

X0 2.1364

Arrhenius’s coefficient

b1 24.7994

(b)

gene cluster for FB2 biosynthesis

a1 (FUM19) 2.5770

a2 (FUM14) 24.0061

a3 (FUM11) 25.5225

a4 (FUM13) 28.1792

a5 (FUM1) 26.7091

a6 (FUM16) 1.5228

a7 (FUM12) 5.8662

a8 (FUM10) 6.2729

a9 (FUM7) 1.4678

mixed-growth-associated product formation

a 22.3613

b 6.8545

initial inoculum

X0 4.4922

Arrhenius’s coefficient

b1 28.8764

18(a)

(b)

1614

1210

8

8

7

6

5

4

3

2

1

0

64

2

0

1 2 3 4 5 6

2 4 6

pred

icte

d FB

2 (µ

g m

l–1 )

pred

icte

d FB

1 (µ

g m

l–1 )

observed FB2 (µg ml–1)

observed FB1 (µg ml–1)

8 10 12 14 16 18

Figure 5. The correlations between the observed and predicted values based onthe models developed for (a) FB1 and (b) FB2 production by F. verticillioides.

rsif.royalsocietypublishing.orgJR

SocInterface10:20130320

8

on December 2, 2015http://rsif.royalsocietypublishing.org/Downloaded from

Our data indicate that 20–258C and 0.995 aw were the opti-

mum conditions for growth of the strain used in this study.

For FB1 and FB2 production, the optimum conditions were

0.98–0.995 aw and 208C or 20–308C, respectively. The opti-

mum temperature and aw previously reported for inducing

fumonisin production ranged from 20 to 258C and 0.95–

0.99, while no production observed at �0.93 aw and 108C[10,27]. Similar results were shown by Samapundo et al.[12], although with lowered aw values and a temperature

range of 15–258C. For a F. verticillioides type strain (NRRL

3248), toxin production was higher when it was grown

with 50 per cent water content and 218C [28]. There are

strain differences in terms of both FUM1 gene expression

and fumonisin production. Previous studies with different

strains of both F. verticillioides and F. proliferatum showed

that relative expression on glycerol-modified water stress

media resulted in relative similar effects on FUM1 gene

expression by different strains. However, with ionic solutes

such as NaCl this was not so, perhaps owing to toxicity of

the ionic solute at higher concentrations [13,14].

The FB biosynthetic gene cluster consists of 17 transcrip-

tional co-regulated genes, nine of which encode enzymes

that catalyse reactions of this pathway [29]. The function of

the others is not known yet. Few studies have investigated

the relationship between the fumonisin production, FUMgene expression and ecological factors [13,14,30–32]. Here,

we developed ternary diagrams to examine the link between

the FUM1 a key gene and eight other pathway genes (FUM7,FUM10, FUM11, FUM12, FUM13, FUM14, FUM16 and

FUM19) in relation to environmental conditions and fumoni-

sin synthesis. This has shown that the relative expression of

FUM1 to that of FUM11, FUM13, FUM14 and FUM19 are

related and influenced by aw and temperature for both FB1

and FB2 production. Jurado et al. [13] described that signifi-

cant and prolonged increase in water stress (e.g. 0.93 aw)

enhanced FUM1 expression, while a mild water stress

(0.98–0.95 aw) did not significantly affect gene transcripts.

According to Marin et al. [14], FUM1 transcription was

enhanced with an increase in non-ionic water stress and the

peak of expression occurred at 208C.

Our results also showed the correlation of FUM1, FUM11,

FUM13, FUM14 and FUM19 expression with FB1 and FB2 pro-

duction under different conditions. The synthesis of these

fumonisins was reduced at higher expression levels of

Table 4. Validation of the model under conditions not included in the model for (a) FB1 and (b) FB2 production by a strain of F. verticillioides.

temp. (88888C) water activity

growth FB1 (mg ml21) FB2 (mg ml21)

m+++++ s.d. (mm d21) experimental model experimental model

(a)

35 0.98 0.17 0.24 4.69 2.86 1.5

s.d. +0.017 +0.03 +1.20 +0.23 +0.15

temp. (88888C) water activity m+++++ s.d. (mm d21)FB2 (mg ml21)experimental

FB2 (mg ml21)model +++++s.d.

(b)

35 0.98 5.79 2.86 1.28 0.42

35 0.995 2.2 6.59 7.80 0.80

0

0.25

0.50

0.75

1.00FUM10

0.25

0.50

0.75

1.00

FUM110 0.25 0.50 0.75 1.00

0 0.25 0.50 0.75 1.00

FUM13

2010

30

0

0

0.25

0.50

0.75

1.00FUM10

0.25

0.50

0.75

1.00

FUM11 FUM13

0

10

5

(a)

(b)

Figure 6. Ternary diagrams of the relative relationship between expression ofFUM1 and FUM11 and FUM13 in relation to (a) FB1 (FB1 mg ml21 ¼

228.28 � FUM11 þ 32.94 � FUM13 þ 10.70 � FUM1) and (b) FB2

(FB2 mg ml21¼211.09 � FUM11þ15.89 � FUM13 2 0.67 � FUM1)production by F. verticillioides.

0

0.25

0.50

0.75

1.00FUM1

0

0.25

0.50

0.75

1.00

FUM190 0.25 0.50 0.75 1.00

FUM14

10

146

2 18

0

0.25

0.50

0.75

1.00FUM10

0.25

0.50

0.75

1.00

FUM190 0.25 0.50 0.75 1.00

FUM14

0

2

4

Figure 7. Ternary diagrams of the relative relationship between expression of FUM1and FUM19 and FUM14 on (a) FB1 (FB1 mg ml21¼20.80� FUM19 þ19.70� FUM14 þ 8.70 � FUM1) and (b) FB2 (FB2 mg ml21 ¼21.83 �FUM19 þ 5.92� FUM14 2 2.98� FUM1) production by F. verticillioides.

rsif.royalsocietypublishing.orgJR

SocInterface10:20130320

9

on December 2, 2015http://rsif.royalsocietypublishing.org/Downloaded from

FUM14, while a higher expression of FUM19 was correlated

with an increased production of both fumonisins. FUM11modulated positively or negatively the production of FB1 and

FB2, respectively. Previously, Lopez-Errasquın et al. [32] sugges-

ted a linear relationship between FUM1 and FUM19 transcripts

and fumonisin production for a strain of F. verticillioidesincubated at 208C for 14 days. Lazzaro et al. [30] identified a

0

0.25

0.50

0.75

1.00FUM10

0.25

0.50

0.75

1.00

FUM110 0.25 0.50 0.75 1.00

0 0.25 0.50 0.75 1.00

FUM13

0.850.900.95

1.00

0

0.25

0.50

0.75

1.00FUM10

0.25

0.50

0.75

1.00

FUM14 FUM19

0.900.940.98

1.00

(a)

(b)

0.80

Figure 8. Ternary diagrams of the relative relationship between expression of (a)FUM1, FUM11 and FUM13 (aw ¼ 1.09 � FUM11 þ 0.79� FUM13 þ0.99 � FUM1) and (b) between FUM1, FUM19, FUM14 (aw ¼ 1.07 �FUM14 þ 0.88 � FUM19 þ 0.93� FUM1) in relation to water activity (aw).

0

0.25

0.50

0.75

1.00FUM1

0

0.25

0.50

0.75

1.00

FUM110 0.25 0.50 0.75 1.00

FUM13

FUM140 0.25 0.50 0.75 1.00

FUM19

40

60

20

080

0

0.25

0.50

0.75

1.00FUM1

0

0.25

0.50

0.75

1.00

28

26

24

22

20

18

30

(a)

(b)

Figure 9. Ternary diagrams of the relationship between expression of (a)FUM1, FUM11 and FUM13 (temperature (8C) ¼ 96.07 � FUM11 2

37.79 � FUM13 þ 19.36 � FUM1) and (b) between FUM1, FUM19 andFUM14 (temperature (8C) ¼ 28.09 � FUM14 þ 31.77 � FUM19 þ17.0 � FUM1) in relation to temperature for F. verticillioides.

rsif.royalsocietypublishing.orgJR

SocInterface10:20130320

10

on December 2, 2015http://rsif.royalsocietypublishing.org/Downloaded from

positive correlation between fumonisin synthesis and

expression of two FUM genes, FUM2 and FUM21, at different

aw and temperature regimes. In the present study effects on

FUM21, considered a regulatory gene of fumonisin biosynthesis

[33], was not included because the role of this gene was not elu-

cidated when the microarray was developed. However, effects

on the FUM1 gene may provide an insight into the way

FUM21 may respond. This variable correlation of gene

expression and production of the toxin may not be that unex-

pected, because usually the expression of only a few genes

(key genes) is directly correlated with the toxin biosynthesis.

Scherm et al. [34], for example, showed this aspect for aflatoxin

biosynthetic genes. Taken together, our findings further sup-

port the use of ternary diagrams as a reliable approach to

investigate the relationship between different key structural

and regulatory genes and their impact on the production of sec-

ondary metabolites such as aflatoxins [18,35] and fumonisins

(the present study).

Besides water availability, several factors can affect fumoni-

sin production including nitrogen limitation and pH of 5.9 [36].

Kohut et al. [31] reported that FUM1 and FUM8 expression,

together with fumonisin production, was induced by nitrogen

starvation in F. proliferatum cultures. However, the presence

of a mycotoxin gene, for example FUM11, does not comple-

tely confirm that the pathogen has the potential to produce

fumonisin [37].

It is necessary to also consider this study in the context

of what might happen when biotic variables are included.

Thus, the interaction with ripening maize kernels, especially

where plant physiological and nutritional effects may be

important, also needs to be considered [38]. Indeed they

suggest that the rate of drying of the maturing maize kernels

critically affects the contamination with fumonisins. Thus, at

the very early dough stage the moisture content (m.c.) is

about 40 per cent (¼0.99 aw) with no water stress effects,

this decreases to 30–35% m.c. at the mid-dough stage

(¼ 0.95 aw) and to 20–25% (0.90–0.85 aw) at full maturity

over a period of about 4–6 weeks [38,39]. This shows that

the window of opportunity for colonization by F. verticillioidesand fumonisin contamination is limited to more than 0.93 aw.

Thus, the range of conditions we have chosen in relation

to aw � temperature stress interactions is in the relevant

range. However, the nutritional quality of maize changes

during ripening and this may further influence the capacity

for biosynthesis of fumonisins. This may also influence the

interaction with other mycobiota including A. flavus, which

rsif.royalsocietypublishing.orgJR

SocInterfa

11

on December 2, 2015http://rsif.royalsocietypublishing.org/Downloaded from

colonizes the ripening maize cobs over a wider aw range than

Fusarium section Liseola during these critical phases of plant

development.

Very few attempts have been made to try and integrate

molecular expression data under different environmental

stresses with phenotypic secondary metabolite data to

develop predictive models. Recently, Abdel-Hadi et al. [18]

demonstrated that for A. flavus and aflatoxin production it

was possible to use the mixed growth model for secondary

metabolite production and link this to a linear model of the

gene expression data of up to 10 key genes for predicting afla-

toxin production under different interacting environmental

conditions. The present study has used this mixed growth

model to try and relate the relative expression of nine bio-

synthetic genes under different environmental conditions

to growth and production of FB1 and FB2 for a strain of

F. verticillioides. This made it possible to develop a predictive

model which provided a good linear regression fit between

the predicted and observed fumonisin production. This

model is important for developing an integrated systems

approach by combining gene expression, ecophysiological

influences and growth data to predict fumonisin production.

This could further help in developing a more targeted

approach to design prevention strategies to control fumonisin

biosynthesis in staple food commodities. For example, use of

RNAi systems to interfere and reduce the function of the

FUM1 or FUM21 gene may be an approach for the minimiz-

ation of fumonisins in cereals [20]. This approach could be a

powerful tool in examining the impact of climate change

factors on toxin production [39].

ce10:20130

References

320

1. Sydenham EW, Thiel PG, Marasas WFO, ShephardGS, Van Schalkwyk DJ, Koch KR. 1990 Naturaloccurrence of some Fusarium mycotoxins in cornfrom low and high esophageal cancer prevalenceareas of the Transkei, Southern Africa. J. Agric. FoodChem. 38, 1900 – 1903. (doi:10.1021/jf00100a004)

2. Missmer SA, Suarez L, Felkner M, Wang E, Merrill JrAH, Rothman KJ, Hendriks KA. 2006 Exposure tofumonisins and the occurrence of neural tubedefects along the Texas – Mexico border. Environ.Health Perspect. 114, 237 – 241. (doi:10.1289/ehp.8221)

3. Proctor RH, Plattner RD, Desjardins AE, Busman M,Butchko RAE. 2006 Fumonisin production in themaize pathogen Fusarium verticillioides: geneticbasis of naturally occurring chemical variation.J. Food Agric. Chem. 54, 2424 – 2430. (doi:10.1021/jf0527706)

4. Luchese RH, Harrigan WF. 1993 Biosynthesis ofaflatoxin—the role of nutritional factors. J. Appl.Bact. 74, 5 – 14. (doi:10.1111/j.1365-2672.1993.tb02989.x)

5. Ellis WO, Smith PJ, Simpson BK, Khanizadeh S,Oldham JH. 1993 Control of growth and aflatoxinproduction of Aspergillus flavus under modifiedatmosphere packaging conditions. Food Microbiol.10, 9 – 21. (doi:10.1006/fmic.1993.1002)

6. Molina M, Gianuzzi L. 2002 Modelling of aflatoxinproduction by Aspergillus parasiticus in a solidmedium at different temperatures, pH andpropionic acid concentrations. Food Res. Int. 35,585 – 594. (doi:10.1016/S0963-9969(01)00161-2)

7. Sanchis V, Magan N. 2004 Environmental profiles forgrowth and mycotoxin production. In Mycotoxins infood: detection and control (eds N Magan, M Olsen).Cambridge, UK: Woodhead Publishing Ltd.

8. Magan N, Aldred D, Mylona KR, Lambert JM. 2010Limiting mycotoxions in wheat. Food Contam. Addit.27, 644 – 650. (doi:10.1080/19440040903514523)

9. Magan N. 2007 Fungi in extreme environments. InEnvironmental and microbial relationships. TheMYCOTA IV (eds CP Kubicek, IS Druzhinina), Ch. 6,pp. 85 – 103, 2nd edn, Berlin, Germany: Springer.

10. Marin S, Magan N, Ramos AJ, Sanchis V. 2004Fumonisin producing strains of Fusarium: areview of their ecophysiology. J. Food Protect. 67,1792 – 1805.

11. Marin S, Sanchis V, Canella R, Magan N. 1995 Effectof water activity and temperature on fumonisin B1

and B2 production by Fusarium proliferatum andF. moniliforme on maize grain. Lett. Appl. Microbiol.21, 298 – 301. (doi:10.1111/j.1472-765X.1995.tb01064.x)

12. Samapundo S, Devliehgere F, De Meulenaer B,Debevere J. 2005 Effect of water activity andtemperature on growth and the relationshipbetween fumonisin production and the radialgrowth of Fusarium verticillioides and Fusariumproliferatum on corn. J. Food Prot. 68, 1054 – 1059.

13. Jurado M, Marın P, Magan N, Gonzalez-Jaen MT.2008 Relationship between solute and matricpotential stress, temperature, growth, and FUM1gene expression in two Fusarium verticillioidesstrains from Spain. Appl. Environ. Microbiol. 74,2032 – 2036. (doi:10.1128/AEM.02337-07)

14. Marın P, Magan N, Vazquez C, Gonzalez-Jaen MT.2010 Differential effect of environmental conditionson the growth and regulation of the fumonisinbiosynthetic gene FUM1 in the maize pathogensand fumonisin producers Fusarium verticillioides andFusarium proliferatum. FEMS Microbiol. Ecol. 73,303 – 311.

15. Schmidt-Heydt M, Geisen R. 2007 A microarray formonitoring the production of mycotoxins in food.Int. J. Food Microbiol. 117, 131 – 140. (doi:10.1016/j.ijfoodmicro.2007.01.014)

16. Schmidt-Heydt M, Magan N, Geisen R. 2008 Stressinduction of mycotoxin biosynthesis genes inrelation to abiotic factors. FEMS Microbiol. Lett. 284,142 – 149. (doi:10.1111/j.1574-6968.2008.01182.x)

17. Schmidt-Heydt M, Parra R, Geisen R, Magan N.2011 Modelling the relationship betweenenvironmental factors, transcriptional genes anddeoxynivalenol mycotoxin production by twoFusarium species. J. R. Soc. Interface 8, 117 – 120.(doi:10.1098/rsif.2010.0131)

18. Abdel-Hadi A, Schmidt-Heydt M, Parra R, Geisen R,Magan N. 2012 A systems approach to model therelationship between aflatoxin gene clusterexpression, environmental factors, growth and toxinproduction by Aspergillus flavus. J. R. Soc. Interface9, 757 – 767. (doi:10.1098/rsif.2011.0482)

19. Formenti S, Magan N, Pietri A, Battilani P. 2012 Invitro impacts on growth and fumonisins andaflatoxin production by Fusarium verticillioides andAspergillus flavus using anti-fungal compounds anda biological control agent. Phytopathol. Mediteranea51, 247 – 256.

20. Abdel-Hadi A, Caley DP, Carter DRF, Magan R. 2011Control of aflatoxin production of Aspergillus flavusand Aspergillus parasiticus using RNA silencingtechnology by targeting aflD (nor-1) gene. Toxins 3,647 – 659. (doi:10.3390/toxins3060647)

21. Mitchell D, Parra R, Aldred D, Magan N. 2004 Waterand temperature relations of growth and ochratoxinA production by Aspergillus carbonarius strains fromgrapes in Europe and Israel. J. Appl. Microbiol. 97,439 – 445. (doi:10.1111/j.1365-2672.2004.02321.x)

22. Hinojo MJ, Medina A, Valle-Algarra FM, Gimeno-Adelantado JV, Jimenez M, Mateo R. 2006Fumonisin production in rice cultures of Fusariumverticillioides under different incubation conditionsusing an optimized analytical method. FoodMicrobiol. 23, 119 – 127. (doi:10.1016/j.fm.2005.03.006)

23. Shuler ML, Kargi F. 2007 How cells grow. In:Bioprocess engineering, pp. 155 – 206. Upper SaddleRiver, NJ: Prentice Hall.

24. Bacon CW, Nelson PE. 1994 Fumonisin production incorn by toxigenic strains of Fusarium moniliformeand Fusarium proliferatum. J. Food Prot. 57,514 – 521.

25. Pitt JI, Hocking AD. 1997 Fungi and food spoilage,p. 593, 2nd edn. London, UK: Blackie Academic &Professional.

26. Frisvad JC, Samson RA. 1991 Filamentous fungiin foods and feeds; ecology, spoilage andmycotoxins productions. In Handbook of appliedmycology: foods and feeds, vol. 3 (eds DK Arora,

rsif.royalsocietypublishing.orgJR

SocInterface10:20130320

12

on December 2, 2015http://rsif.royalsocietypublishing.org/Downloaded from

KG Mukerji, EH Marth), p. 621. New York, NY:Marcel Dekker.

27. Mogensen JM, Nielsen KF, Samson RA, Frisvad JC,Thrane U. 2009 Effect of temperature and wateractivity on the production of fumonisins byAspergillus niger and different Fusarium species.BMC Microbiol. 9, 281. (doi:10.1186/1471-2180-9-281)

28. Bailly JD, Querin A, Tardieu D, Guerre P. 2005Production and purification of fumonisins from ahighly toxigenic Fusarium verticilloides strain. RevueMed. Vet. 156, 547 – 554.

29. Desjardins AE, Proctor RH. 2007 Molecularbiology of Fusarium mycotoxins. Int. J. FoodMicrobiol. 119, 47 – 50. (doi:10.1016/j.ijfoodmicro.2007.07.024)

30. Lazzaro I, Susca A, Mule G, Ritieni A, Ferracane R,Marocco A, Battilani P. 2012 Effects of temperatureand water activity on FUM2 and FUM21 geneexpression and fumonisin B production in Fusariumverticillioides. Eur. J. Plant Pathol. 134, 685 – 695.(doi:10.1007/s10658-012-0045-y)

31. Kohut G, Adam AL, Fazekas B, Hornok L. 2009 N-starvation stress induced FUM gene expression andfumonisin production is mediated via the HOG-typeMAPK pathway in Fusarium proliferatum. Int. J. FoodMicrobiol. 130, 65 – 69. (doi:10.1016/j.ijfoodmicro.2009.01.002)

32. Lopez-Errasquın E, Vazquez C, Jimenez M, Gonzalez-Jaen MT. 2007 Real-time RT-PCR assay to quantifythe expression of FUM1 and FUM19 genes from thefumonisin-producing Fusarium verticillioides.J. Microbiol. Methods 68, 312 – 317. (doi:10.1016/j.mimet.2006.09.007)

33. Brown DW, Butchko R, Busman M, Proctor RH. 2011The Fusarium verticillioides FUM gene clusterencodes a Zn(II)Cys6 protein that affects FUM geneexpression and fumonisin production. Eukaryot. Cell6, 1210 – 1218. (doi:10.1128/EC.00400-06)

34. Scherm B, Palomba M, Serra D, Marcello A, MigheliQ. 2005 Description of transcripts of the aflatoxingenes aflD, aflO and aflP by reverse-phasetranscription-polymerase chain reaction allowsdifferentiation of aflatoxin-producing and non-

producing isolates of Aspergillus flavus andA. parasiticus. Int. J. Food Microbiol. 98, 201 – 2010.(doi:10.1016/j.ijfoodmicro.2004.06.004)

35. Miller JD. 2001 Factors that affect the occurrence offumonisin. Environ. Health Perspect. 109, 321 – 324.

36. Karthikeyan V, Rajarajan R, Patharjan S, KarthikeyanPP, Saravanakumar P, Siva M, Aruna Bhavani PS, PalaniP. 2011 PCR based detection of fumonisin producingstrains of Fusarium verticillioides and gene related totoxin production. Curr. Bot. 2, 34– 37.

37. Battilani P, Formenti S, Ramponi C, Rossi V. 2011Dynamic of water activity in maize hybrids is crucialfor fumonisin contamination in kernels. J. CerealChem. 54, 467 – 472. (doi:10.1016/j.jcs.2011.08.014)

38. Brooking IB. 1990 Maize ear moisture during grainfilling, and its relation to physiological maturity andgrain drying. Field Crops Res. 23, 55 – 68. (doi:10.1016/0378-4290(90)90097-U)

39. Magan N, Medina A, Aldred D. 2011 Possibleimpacts of climate change on mycotoxins in foodcrops pre- and post-harvest. Plant Pathol. 60,150 – 163. (doi:10.1111/j.1365-3059.2010.02412.x)