DEVELOPMENT OF FAST PCR SYSTEM FOR AFLR GENE DETECTION
Pichai Chaichanachaichan11,*, Wannaporn Muangsuwan22,, Pattarawan Ruangsuj32,, Kosum
Chansiri43, Srichan Phornchirasilp54, Montri Yasawong62,#
1
Pharmacology and Biomolecular science, Bangkok
2
Department of Biochemistry, Mahidol University, Bangkok
3
Department of Medicine, Srinakarinwirot University, Bangkok
4
Deparment of Pharmacology, Mahidol University, Bangkok
*e-mail: extra_top@hotmail.com, #e-mail: montri.yas@mahidol.ac.th
Abstract
Aflatoxins are secondary metabolite. The toxins were produced from fungal strains in
the genus Aspergillus. Consuming of agricultural products, which were contaminated with
the aflatoxin is cause of aflatoxicosis-nausea, vomiting, muscle cramp, hepatitis and
hepatocarcinoma. There are many methods to detect aflatoxins either quality or quantity
however, the detection spends much time and requires complicated procedures. In this study,
an indirect method for aflatoxin detection was proposed using aflR gene as a biological
marker. The aflR gene sequences of fungal strains in the genus Aspergillus were collected
from NCBI database. The relationship of the gene among the Aspergillus strains was
described by Bayesian inference tree. Conserved regions of the gene were determined and
then utilized for primers design. The aflR-primers were validated under a standard PCR
protocol. There were four protocols for fast PCR system had developed. Only protocol A was
successfully amplified the aflR amplicon. The fast PCR protocol was faster than the standard
PCR protocol around 2.6 times. The fast PCR system may apply or incorporate with other
techniques which have to enrich DNA target before detection of the results such as DNA
biosensors.
Keywords: aflatoxin, aflR, fast PCR system
Introduction
Aflatoxins are a secondary metabolites produced mainly by Aspergillus spp. There are
many precursors and proteins, such as polyketide synthase, that function in convert acetate to
polyketide intermediates and are produced by the expression of aflC gene, the transcriptional
activator is controlled by the aflR gene and aflS gene [1]. The aflR gene encodes a sequencespecific zinc binuclear DNA-binding protein, a Gal 4-type 47-kDa polypeptide, and has been
shown to be required for transcriptional activation. After binding of aflR gene to the
palindromic sequence 5’-TCGN5CGA-3’ (aflR-binding motif) in the promoter region, the
transcription of aflatoxin pathway genes be motivated [2]. The role of aflS gene has revealed
in the research model that using aflS knockout mutants, the lack of aflS transcript is
associated with a 5- to 20-fold reduction of expression of some of the aflatoxin pathway
genes [3]. It can be implied that the alfR gene and the aflS gene interact together to promote
the transcription process. There are the major four types of aflatoxin classified by detection
under UV light. Addition, showing in green and blue are aflatoxin G and aflatoxin B
respectively. The most potent natural carcinogen is aflatoxin B1 [4] and is commonly the
major aflatoxin produced by toxigenic strains. Chronic exposure of aflatoxins, including all
types of aflatoxins, increases cancer incidence, especially hepatocarcinoma [5]. In human,
acute toxicosis is manifested by vomiting, abdominal pain, pulmonary edema, convulsion,
coma, and death with cerebral edema, and fat buildup of the liver, kidney, and heart [6].
Because of these toxicities, national and international institutions and organizations such as
the European commission (EC), the US food and drug administration (FDA) the world health
organization (WHO), and the food and agriculture organization (FAO) have recognized the
potential health risks to animals and humans posed by consuming aflatoxin-contaminated
food [7]. The current maximum residue levels (MRL) for aflatoxins set by the EC are 2 μg/kg
for AFB1 and 4 μg/kg for total aflatoxins in groundnuts, nuts, dried fruits and cereals for
direct human consumption.
Chromatography techniques are commonly used for aflatoxin detection. They are
gas chromatography (GC), liquid chromatography (LC), high performance liquid
chromatography (HPLC) and thin layer chromatography (TLC) [8]. LC, TLC and HPLC are
the most quantitative methods in routine and research analysis [9]. Overall disadvantages of
these methods are spending much of time for performing and interpreting of the results. To
overcome these problems, the polymerase chain reaction (PCR) is used for indirect detection
of the aflatoxin by detection of the aflR gene. The aim of this study is developing a PCR
condition for fast amplification of aflR amplicon by using a normal PCR reagent.
Methodology
Collection of aflR gene and Phylogenetic analysis
Multiple sequences alignment was performed based on iterative refinement method using
MUSCLE version 3.8.31. Evolutionary model of aflR gene was selected depened on AIC and
hLRTs criteria working by MrModeltest version 2.3. Phylogenetic tree was analyzed by
Bayesian inference method using parallel version of MrBayes. The phylogenetic analysis was
obtained by computer cluster (KIRI cluster). The cluster was assembled from four IBM
servers (x3250 M4), which were connected by a gigabit switch (HP ProCurve 1410-16G).
The Bayesian posterior probabilities were obtained by performing two separate runs with
twelve Markov chains. Each run was conducted with 2×107 generations and sampled every
100 generations. A consensus tree was calculated after discarding the first 25% of the
iterations as burn-in. Phylogenetic tree drawing was performed using TreeView version 1.6.6.
AflR-primer design
The aflR gene was used because it acts as a positive regulator in aflatoxin biosynthesis
in fungal genus Aspergillus. According to previous report, lacking of this gene affects
directly in various types of enzyme in synthetic process. All aflR gene sequences of the
different fungi were searched from the oligonucleotide database of the national center for
biotechnology information (NCBI). All sequences were aligned by MUSCLE version 3.8.31.
Forward and reverse primers were selected from the area that contained high conserved
region of aflR gene.
Primer validation
In this experiment, Aspergillus flavus was a standard fungus while it contained aflR
gene. As stated in manufacture’s guidance, genomic DNA was extracted from Aspergillus
flavus using DNA extraction kit (MOBIO, USA). The gDNA concentration was measured by
spectrophotometer. A PCR assay for Aspergillus flavus was carried out in a final volume of
50 µl containing 39.7 µl of water, 5 µl of buffer, 2 µl of dNTPs (10mM), 1 µl of each
forward, reverse aflR-primer and sample PCR was performed in a thermal cycler. Initiation
with denaturation step was set at 95oC for 2min, 30 cycles of denaturation at 95oC for 30s,
annealing 57oC for 30s, and extension at 72oC for 60s, and a final extension step at 72oC for
10min. The amplification products were resolved in 1.0% agarose gel electrophoresis at 80V
for 40min, stained with non-toxic dye visualized under UV transilluminator.
Optimization of fast PCR systems
Aim of this research is to decrease time taking in PCR procedure, so only three main
steps were selected. Four fast PCR protocols (Table 1) were established and detected under
UV illumination and photographed using an image analyzer.
Table 1. Development of fast PCR system
Protocol
A
B
C
D
Denaturing time
(second)
10
10
5
7
Annealing time
(second)
10
5
10
7
Extension time
(second)
10
5
5
7
Cycle
30
30
30
28
Time
(minute)
32
27
27
16
Result
Collection of aflR gene and phylogenetic analysis
Eleven sequences of aflR gene were obtained from national center for biotechnology
information (NCBI). The size of both complete and partial aflR gene sequences were ranged
from 466 to 2,844 bases (Table 2). The phylogeny based on Bayesian inference method
represented an evolution of aflR gene among fungal strains in the genus Aspergillus (Figure
1).
Table 2. Details of Aspergillus strains using in this experiment
No.
Acession No.
Organism
Phylum
Length(bp)
1
L26220
Aspergillus parasticus
Ascomycota
2,844
2
3
4
5
6
7
8
9
10
11
AY650937
Y16967
AF264763
AF441427
AF441416
AF441414
FJ491458
AF547172
FJ491462
FJ491457
Aspergillus flavus
Aspergillus oryzae
Aspergillus sojae
Aspergillus pseudotamarii
Aspergillus nomius
Aspergillus bombycis
Aspergillus arachidicola
Aspergillus alliaceus
Aspergillus minisclerotigenes
Aspergillus parvisclerotigenus
Ascomycota
Ascomycota
Ascomycota
Ascomycota
Ascomycota
Ascomycota
Ascomycota
Ascomycota
Ascomycota
Ascomycota
1,666
1,155
1,155
1,350
1,329
1,329
491
785
472
466
Figure 1. Bayesian tree of aflR gene. The tree was constructed using Bayesian inference method with the
HKY+G model of nucleotide substitution. The values associated with nodes correspond to the clade
credibility support in %.
Validation of aflR primer
The primer validation was declared in Table3. Standard PCR protocol was operated
for aflR gene amplification. Gel electrophoresis showed the aflR amplicons from designed
primer in the PCR protocol 2 and 4 (Table 3).
Table 3. Results of primer validation with standard PCR protocol
Protocol
1
Negative
Addition of
control
DMSO
Result
+ = positive , - = negative
2
Sample
+0. 0%DMSO
+
3
Sample
+0.4%DMSO
4
Sample
+0.8%DMSO
5
Sample
+1.6%DMSO
-
+
-
S = secondary
structures such as primer-dimer formation , + = positive , - = negative
Fast
PCR system
The results of reducing time protocol were performed on Table 4. Only this condition;
denaturation time 10s, annealing time 10s, and extension time 10s, was success for
amplifying amplicons. At denaturation time 5s and 7s, it had shown a genomic DNA in gel
electrophoresis instead of targeted PCR band. At denaturation time 10s and annealing time 5
s, it was not shown the targeted PCR band and genomic DNA band. So the best condition for
this primer was the protocol A.
Table 4. Results of fast PCR system
Protocol
Denaturation
(s)
Standard
30
A
10
B
10
C
5
D
7
+ = positive, - = negative
Annealing
(s)
30
10
5
10
7
Extension
(s)
60
10
5
5
7
Cycle
30
30
30
30
28
Total time
(m)
82
32
27
27
16
Result
+++
++
-
Discussion and conclusion
The aflR genes of fungal strains in the genus Aspergillus shared several conserved
regions. This information was sufficient for aflR-primers design. The primers were tested by
the standard PCR protocol. The PCR was successfully performed by giving aflR amplicon.
Normaly, PCR is spending one to two hours for performing 30-35 cycles of the reaction.
However, this study was given a PCR condition which required less time than that in the
standard protocol. The standard protocol of this experiment spent 82 minutes for obtaining
the aflR amplicon. In contrast, the fast PCR protocol A resulted 32 minutes for finishing 30
cycles of the aflR amplification. The fast PCR protocol A was faster than the standard PCR
protocol approximately 2.6 times. The time for producing of aflR amplicon was decreasing
due to the reducing of time during denaturation, annealing and extension step of the PCR.
However, there was no aflR amplicon detected from fast PCR protocol B, C and D. These
results might occurred when gave insufficient time to the PCR conditions. The fast PCR
protocol A was suitable for aflR gene detection and may apply for indirect detection of
aflatoxin. Moreover, this protocol may be applied for other gene detection that based on PCR
technique. To perform a fast PCR system, it is not necessary to use any expensive
thermostable DNA polymerase or advance PCR machine. The most important criterion for
designing a fast PCR system is only adjusting a suitable time for the PCR conditions. The fast
PCR system may apply or incorporate with other techniques which have to enrich DNA
target before detection of the results such as DNA lateral flow sensor, piezoelectric sensor,
ISFET and etc.
Reference
1.
Ehrlich KC, Montalbano BG, Bhatnagar D, Cleveland TE. Alteration of different domains in AFLR
affects aflatoxin pathway metabolism in Aspergillus parasiticus transformants. Fungal Genet Biol.
1998;23:279-87.
2.
Ehrlich KC, Cary JW, Montalbano BG. Characterization of the promoter for the gene encoding the
aflatoxin biosynthetic pathway regulatory protein AFLR. Biochim Biophys Acta. 1999:412-7.
3.
Chang P-K. The Aspergillus parasiticus protein AFLJ interacts with the aflatoxin pathway-specific
regulator AFLR. Mol Genet Genomics. 2003;268:711-9.
4.
Squire RA. Ranking animal carcinogens: a proposed regulatory approach. Science 1981;214:877-80
5.
Peng KY, Chen CY. Prevalence of aflatoxin M-1 in milk and its potential liver cancer risk in Taiwan. J
FOOD PROTECT. 2009;72:1025-9.
6.
Strosnider H, Azziz-Baumgartner E, Banziger M, Bhat RV, Breiman R, Brune MN, et al. Workgroup
report: public health strategies for reducing aflatoxin exposure in developing countries. Environmental
health perspectives. 2006;114(12):1898-903. Epub 2006/12/23.
7.
Laura M-T, Angel MC-O, M oises AV -C, Irineo T -P, Ramón GG-G. In: Torres-Pacheco DI, editor.
Aflatoxins biochemistry and molecular biology-biotechnological approaches for control in crops,
aflatoxins - detection, measurement and control. 2011.
8.
Mehrdad Tajkarimi MHS, HassanYazdanpanah and Salam A. Ibrahim. Aflatoxin in agricultural
commodities and herbal medicine. In: Guevara-Gonzalez RG, editor. Aflatoxins - biochemistry and
molecular biology. 2011.
9.
Vosough M, Bayat M, Salemi A. Matrix-free analysis of aflatoxins in pistachio nuts using parallel
factor modeling of liquid chromatography diodearray detection data. Anal Chim Acta. 2010;663(1):118.