Visual agar plate assay of antifungal phenotypes among soil bacteria isolated from pistachio, maize and peanuts field of Iran on PDA plates using a norsolorinic acid (NA) mutant of
Invasion of food, feed and agricultural crops with mycotoxigenic fungi from the genera
To ensure global safety on food and feed supplies, extensive researches have been carried out to effectively control and manage AF contamination of crops. The strategies for preventing AF contamination are generally divided into two categories including pre- and post-harvest controls (Kabak et al., 2006). Pre-harvest control strategies include appropriate field management practices (crop rotation, irrigation, soil cultivation, etc.), enhancing host resistance (transgenic or genetically modified crops), biological (application of antagonistic fungi and bacteria) and chemical control (fungicides, insecticides). Respect to biocontrol approaches, the rapid expansion in our knowledge about the role of microorganisms in inhibiting AF biosynthesis has enabled us to utilize them as potential AF biocontrol agents (Holmes et al., 2008; Raaijmakers et al., 2002). A large number of plants, mushrooms, bacteria, microalgae, fungi and actinomycetes have now been screened for the ability to inhibit toxigenic fungal growth and/or AF production (Alinezhad et al., 2011, Bagheri-Gavkosh et al., 2009; Ongena & Jacques, 2007; Razzaghi-Abyaneh & Shams-Ghahfarokhi, 2011; Razzaghi-Abyaneh et al., 2005, 2007, 2008, 2009, 2010, 2011). Substantial efforts have been carried out in identifying organisms inhibitory to AF biosynthesis through co-culture with aflatoxigenic fungi with the aim of finding potential biocontrol agents as well as novel inhibitory metabolites. The use of beneficial microorganisms is one of the most promising methods to the development of environmentally friendly alternatives to chemical pesticides in preventing the growth of aflatoxigenic fungi and subsequent AF contamination of susceptible crops. Among beneficial microorganisms, antagonistic bacteria are in the first line of investigation because of a much greater diversity than that of any other organism and possessing valuable pharmaceutically active molecules (Ongena & Jacques, 2007; Stein, 2005). Recent advances in analytical methods and enormous expanding of natural products libraries, cloning, and genetic engineering have provided a unique opportunity for isolation and structural elucidation of novel bioactive antifungal compounds from bacterial communities all over the world. It has been reported that, on average, two or three antibiotics derived from bacteria break into the market each year (Clark, 1996). Among an estimated number of 1.5 million bacterial species exists on our planet, only a little portion (less than 1%) has been identified yet of which a more little have tested for bioactive antifungal metabolites. Terrestrial bacteria are an interesting group of antagonistic microorganisms capable of efficiently inhibit toxigenic fungus growth and AF production. They mainly belong to the genera
This chapter highlights comprehensive data on antagonistic bacteria isolated from agricultural soils of pistachio, peanuts and maize fields with an emphasis on their ability for inhibiting growth of aflatoxigenic fungi and AF production. We first describe how we can isolate and identify a large number of soil bacteria with antagonistic activity against toxigenic
2. Biological control: a powerful management strategy
Biological control is defined as i) a method of managing pests by using natural enemies ii) an ecological method designed by man to lower a pest or parasite population to acceptable sub-clinical densities or iii) to keep parasite populations at a non-harmful level using natural living antagonists (Baker, 1987). The history of biological control dates back to an outstanding successful story, the biocontrol of the cottony-cushion scale (
3. Biocompetitive bacteria from agricultural soil
Regard to biocompetitive bacteria,
3.1. Soil sampling and bacterial isolation
One-hundred fifty soil samples were collected from pistachio, maize and peanut fields located in different regions of Damghan, Sari and Astaneh cities during June-July 2009. Sampling was done according to the latitude of each field. Each soil comprised from ten subsamples each of approximately 1000 mm3 which were obtained using a sterile trowel at 10 m intervals. The subsamples were collected from the 50 mm top of the surface soil and then mixed thoroughly in a Nylon bag. The samples were air-dried in sterile Petri-dishes and stored at 4°C before use.
For bacteria isolation, 3 g of each soil sample was added to 10 ml of sterile normal saline solution (0.8 M), mixed vigorously by vortex for 2 min and centrifuge at 2500 rpm for 10 min. The amount of 10 µl aliquots of each sample supernatant was spread on to GY (Glucose 2%, Yeast extract 0.5%) agar and KB (King’s B) agar plates and incubated for 3 days at 28°C. Discrete bacterial colonies were selected every 12 h and their purity was insured after transferring to master GY plate by tooth pick spot technique as shown in Fig. 2.
3.2. Screening for antifungal activity by visual agar plate assay
For selecting bacteria that inhibit either fungal growth or AF production, a visual agar plate assay was used as described by Hua et al. (1999) with some modifications. A 5 µl aliquot of a conidial suspension (200 conidia/µl) of a norsolorinic acid (NA)-accumulating mutant of
Table 1 represents the results of antifungal phenotypes among soil bacteria isolated from pistachio, peanuts and maize fields. Different phenotypes were identified in all soils including NA and fungal growth inhibitors (type I), NA inhibitors (type II), growth inhibitors (type III) and finally non-inhibitors of NA and growth (type IV). The only exception were bacteria type II which was not isolated from peanuts field soils. In all fields, a pattern of type IV > type I > type III > type II were obtained regard to the number of antagonistic bacteria isolated. The phenotypes I and III are suitable candidates for biocontrol of AF-producing fungi in the field, while bacteria from type II are useful for elucidate AF biosynthesis pathway.
3.3. Identification of biocompetitive bacteria
The strongest antagonistic bacteria recognized from initial screening on PDA by visual agar plate assay were selected for identifying at genus and species level.
3.3.1. Biochemical identification
Selected bacteria were first determined to be either Gram-positive or Gram-negative using potassium hydroxide (Gregersen, 1978). Catalase and oxidase enzymatic activities were also determined (Barrow & Feltham, 1993). Gram-positive isolates were identified using GP2 MicroPlates (Biolog), whereas Gram-negative isolates were identified using GN2 MicroPlates (Biolog), according to the instructions of the manufacturer. Identification was based on the similarity index of carbon source utilization by each isolate relative to that of identified reference strains in the Biolog GP and GN databases.
3.3.2. Molecular identification
Fig. 4 illustrates all the steps for molecular identification of antagonistic bacteria. Overnight bacterial cultures on LB medium at 30°C were streaked on TSA plates. Single colonies from cultures grown on 0.5X TSA at 28°C were suspended in 2.0 ml sterile distilled water. Bacterial cells were pelleted by centrifugation at 12,000 × g for 10 min. and resuspended in 0.1 ml sterile distilled water. Total DNA from bacteria was prepared from single colonies grown on TSA according to the QIAGEN instruction. The 16s rRNA gene fragment was amplified in PCR using 1 to 5 µl of each cell suspension as template and universal primers 27F (5´-AGAGTTTGATCMTGGCTCAG-3´) and 1525R (5´AAGGAGGTGWTCCARCC-3´) (Lane, 1991). The PCRs were carried out using approximately 500 ng of total bacterial DNA, 10 µl of 10x PCR buffer, 8 µl of MgCl2 (25 mM), 10 µl of deoxynucleoside triphosphates (dNTPs) (2 mM each), 3.3 µl of each primer (20 µM), 0.5 µl of
The PCR mixtures were denatured at 95°C for 5 min, which was followed by 35 cycles of 94°C for 30s, 55°C for 30s, and 72°C for 90s and then a final extension at 72°C for 5 min. Amplification was checked for purity by electrophoresis on a 1.0% agarose gel. The bands of interest were excised from the gel, and the DNA was purified using QIAquick PCR purification columns (Qiagen, Inc., Valencia, CA). Purified DNA fragments were sequenced using the same sets of primers that were used for amplification by an ABI Prism Big Dye® Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems). Bacteria were identified based on sequence similarities to homologous 16S rRNA gene fragments in the Ribosomal Database Project database (Cole et al., 2005) (accessed at http://rdp.cme.msu.edu/index.jsp).
3.4. Antagonistic activity against aflatoxigenic
A. parasiticusNRRL 2999
Cell free culture supernatants of inhibitory bacteria were used in an antagonistic assay system. Table 2 represents the strongest antagonistic bacteria which were identified by a combination of biochemical and molecular methods in relation to their source of isolation.
Identified bacteria (0.1 ml of bacterial inoculums containing Ca. 107 CFU/ml) were inoculated on 20 ml of PDB prepared in 100 ml capacity flasks and incubated for 48 h at 28°C in shaking condition (100 rpm). Cell free supernatant fluids were prepared by centrifuging the cultures at 23990×g for 15 min. The supernatant was supplemented with PDB to compensate for the consumption of nutrient by bacterial growth the pH of supernatant fluid was adjusted to that of the original medium. Supernatant fluids were sterilized by filtration through a 0.45 µm pore size nylon membrane. Five ml aliquots of sterilized bacterial supernatant were aseptically dispensed in 25 ml Erlenmeyer flasks and inoculated with 0.1 ml of a spore suspension of
4. Purification of antifungal metabolites from soil bacteria: A practical approach
4.1. Culture conditions for metabolite production
As the first step for production of bioactive antifungals, different culture conditions including medium, incubation time and aeration should be optimized. In order to initial purification of inhibitory metabolites, the selected bacterium with strongest antifungal activity in initial screening was cultured on suitable liquid media such as GY (2% glucose, 0.5% yeast extract), SCD (2% bacto dextrose, 20% potato infusion), PDB (potato dextrose broth) or even KB (King´s B). The cultures were checked for optimal conditions of aeration (stationary cultures to shaking at different rpm from 100 to 250), incubation times (for at least 1 to maximum 7 days) and temperature (from 20 to 40°C). After culturing the bacterium at optimized condition, the whole culture as the main source of secretory metabolites was centrifuged at 8,000 x
4.2. Purification of antifungal metabolites
Consecutive steps of purification of bioactive metabolites from bacterial culture filtrate are summarized in Fig. 5. As the first step, the inhibitory bacterium should be cultured at optimized culture conditions from section 4.1. The next steps are Ion exchange column chromatography on Diaion HP20 resin, preparative thin layer chromatography on silica gel 60F254 and finally HPLC purification of bioactive metabolites.
4.2.1. Metabolite production at pre-optimized culture conditions
The selected bacterium with strongest antifungal activity was cultured in 1000 ml capacity flasks contained 250 ml GY as selected medium from section 4.1. The cultures were incubated at pre-optimized conditions (28°C for 5 days with shaking at 120 rpm). The whole culture (2 liters totally) was then centrifuged at 8,000 × g at room temperature for 30 min. The supernatant was used for purification of the inhibitory metabolites.
4.2.2. Ion exchange column chromatography
A glass column (2.5 × 60.0 cm) was equilibrated with MeOH. Five hundred grams of Diaion HP20 resin was suspended in MeOH and then packed onto the glass column. After removing of MeOH, the column was equilibrated with distilled water. The culture broth of selected bacterium (500 ml) was loaded onto the column. The resin was washed with 3 liters of distilled water, and the substances bound to the resin were then stepwise eluted by using 2 liters each of 40, 60, 80, and 100% methanol (MeOH) in water. Each elution was concentrated to dryness with a rotary evaporator and dissolves in desirable amounts of 100% MeOH. The 80% MeOH fraction which showed the highest growth and/or AF inhibitory activity against NA-mutant of
4.2.3. Preparative thin layer chromatography
The 80% MeOH fraction from section 4.2.2 (an approximate of 250 mg dry weight) was applied to Silica gel 60F254 TLC plate and then developed with a mixture of chloroform/methanol/water (65:25:4, v/v/v) as mobile phase. Total area developed on the TLC plate was divided into at least 5 regions under 365 nm UV light, and the silica gel was scraped separately from each region. The substances presented in the silica gel were extracted with ten-fold amounts of 100% MeOH. Each fraction was concentrated to dryness, dissolves in a small amount of MeOH, and subjected to the MPA on 96-well microplates. The fraction "b" (75.6 mg dry weight) which contained the strongest inhibitory activity against fungal growth and/or AF production was selected for further purification (Fig. 5B).
4.2.4. High performance liquid chromatography (HPLC)
The fraction "b" from section 4.2.3 was finally purified by HPLC equipped with a Cosmosil 5C18-AR column (4.6 × 150 mm; 5 µm). After injecting the sample, the column was washed with MeOH/water (50:50, v/v) for 80 min. The flow rate was adjusted at 1.0 ml/min, and elution was monitored at 290 nm wavelength. The number of 6 separated peaks (P1 to P6) were collected from the ODS column as shown in Fig. 5. Based on the MPA results, two peaks i.e. P2 and P3 were able to inhibit fungal growth and pigment production by
4.3. Structural elucidation of antifungal metabolites
With a combination of Liquid chromatography-Mass spectrometry (LC-MS) and Matrix-assisted laser desorption/ionization (MALDI-TOF), we will be able to elucidate the chemical structure of a protein or peptide in a best way. LC-MS spectrum determines retention time and an approximate mass of a purified compound, while complementary MALDI-TOF enable us to explain chemical formula and precise mass of the compound as the final step of identification. LC-MS and MALDI-TOF spectra of purified antifungal are shown in Fig. 6.
4.3.1. Liquid chromatography-Mass spectrometry (LC-MS)
The LC-MS system usually consists of a LC-10Avp separation module equipped with a SPD-M10Avp photodiode array detector and LC-MS2010A single quadruple mass spectrometer with atmospheric pressure photo ionization (APPI) source. The probe can be operated in the positive/negative mode under the condition of defined probe voltage, temperature of 300°C, CDL temperature of 200°C, nabulization gas (N2) flow 2.5 1/min, and scan range 900-1600 m/z (sec/scan). The amount of 2 µl of each inhibitory peak purified from HPLC separation was injected to an Ascentis C18 column (150 mm × 2.1 mm, 5 µm) and washed with MeOH (65% aqueous solution) acidified with 0.1% acetic acid in a flow rate of 0.2 ml/min. The column temperature should be maintained at 40°C during the operation. Approximate mass and retention time of the compound were recorded at the end of analysis.
Matrix-assisted laser desorption ionization-time of flight spectrometer (MALDI-TOF) is a soft ionization technique used in mass spectrometry, allowing the analysis of biomolecules (biopolymers such as DNA, proteins, peptides and sugars) and large organic molecules (polymers, dendrimers and other macromolecules), which tend to be fragile and fragment when ionized by more conventional ionization methods. The MALDI-TOF is a two step process. First, desorption is triggered by a UV laser beam. Matrix material heavily absorbs UV laser light, leading to the ablation of upper layer of the matrix material. The second step is ionization which takes place in the hot plume. Aside from peptide mass fingerprinting and useful application in identifying of microorganisms such as bacteria and fungi, MALDI-TOF is used for the rapid identification of proteins isolated by using gel electrophoresis: SDS-PAGE, size exclusion chromatography, affinity chromatography, strong/weak ion exchange, isotope coded protein labeling (ICPL), and two-dimensional gel electrophoresis. MALDI-TOF analysis of inhibitory compounds with defined retention time and an approximate mass from LC-MS step reveals valuable data about chemical formula and exact mass and provides finally identification of the absolute configuration of the purified inhibitory bacterial metabolite (Fig. 6).
5. Concluding remarks and future prospective
AF contamination of food and feed remains a major risk for human and animal health all over the world. Despite the long history of our knowledge about AF, little has been documented on how we can virtually combat the global distress of AF contamination of crops and agricultural commodities. AF-producing fungi can infect grains from pre-harvest conditions in the field through to post-harvest stages in the stores. Several pre- and post-harvest strategies have being tested to reduce risk of AF contamination. One of the management strategies being developed is biological control using various antagonistic microorganisms such as fungi, bacteria, and actinomycetes by a competitive exclusion mechanism. Biological control in conjunction with other management practices has potential to dramatically reduce AF contamination. Natural population of
This work was supported financially by Pasteur Institute of Iran.