Biodiversity and Distribution of Aspergillus and Their Toxins in Maize from Western and Eastern Regions of South Africa

Aspergillus species and aflatoxins production are more prevalent during times of high heat and drought. In South Africa, there is frequent occurrence of drought as a result of climate change. The aim of this study was to investigate the biodiversity and distribution of Aspergillus species with their corresponding toxins in maize from main maize producing regions of South Africa; [Western Regions (WR) and Eastern Regions (ER)]. One hundred and twen-ty-three (64 from WR and 59 from ER) maize samples from the two agro-climatic regions in South Africa were analyzed using cultural, molecular and analytical methods. Across agro-climatic regions, Aspergillus species contaminated about 62% of the maize samples, while Aspergillus flavus was the most prevalent (47.15%) followed by Aspergillus fumigatus (4.69%) while the least was Aspergillus parasiticus (0.81%). The Western Regions showed a higher distribution of varieties of Aspergillus species compared to the Eastern Regions. Aflatoxins contaminated only 27.64% of the maize samples with a mean total aflatoxin concentration of 2.40 μg/kg which is below the South Africa’s set standard for total aflatoxin in food (5 μg/kg). About 10.57% of the samples produce aflatoxins above the 5 μg/kg permissible limit for total aflatoxin in foods. The ratio of toxigenic to atoxigenic strains of Aspergillus flavus was generally low in all the regions of South Africa. This study could aid policy makers to make informed decisions in developing remediation strategies for Aspergillus mycotoxins.


Introduction
The filamentous fungus; Aspergillus flavus is a cosmopolitan soil-borne saprophytic organism with opportunistic parasitic behaviors to plants, animals and humans. Aflatoxins are metabolites produced mainly by toxigenic strains of Aspergillus flavus and A. parasiticus, which grow in soil, hay, decaying vegetation and grains [1]. Aflatoxins (AFs) are toxic and carcinogenic to livestock and humans [2] [3] [4]. Contamination by aflatoxin is one of the most serious food and feed safety problems worldwide and causes significant economic losses yearly [5]. Thus, food safety has become a very important issue worldwide and the potential effects of climate change on yields and quality of crops especially for mycotoxins, have received special attention in the past years from a risk analysis perspective [6] [7]. Benkerroum [8] reported past major outbreaks of aflatoxicosis associated with maize-based foods which occurred in West-India (1974), Kenya (1981 and 2004) and Tanzania (2016Tanzania ( , 2017. Due to the toxicity and impact of aflatoxins on health, there exist regulatory limits on the quantity of aflatoxins permitted in food and feed in several countries [9] [10].
In particular high temperatures and drought stress directly affect maize and the occurrence of A. flavus favoring fungal growth, conidiation and spore dispersal, and impairing the growth and development of maize [17]. Aspergillus flavus is the dorminant fungal spp. in maize kernels during warm and dry seasons [18] [19] [20] [21] resulting in high levels of aflatoxin contamination of maize in the field [22]. Events related to contamination by aflatoxins are more prevalent during times of high heat and drought which can stress the host plant thereby facilitating infection by A. flavus [23].
Mycotoxin toxicity occurs at very low concentrations, therefore sensitive and reliable methods for their detection are required. Different qualitative and quan- This study will aid policy makers to make informed decisions in developing strategies based on monitoring and characterization of risks, prevention, intervention and remediation strategies for Aspergillus mycotoxins, which start from critical points along the production chain such as field, storage, processing and transportation. It will also provide useful information that will enhance global efforts in ensuring production of quality food/feed as well as food security. Figure 1 The dotted lines divide the maize production areas in the country into Western (North West and Western part of Free State) and Eastern (Guateng and Eastern part of Free State) regions [24]. Maize samples were collected from main State (45%), North West (17%) and Guateng (5%) [25]. The Western regions situated in the drier and warmer areas of the country and the Eastern regions with higher rainfall and cooler areas [24]. Samples from these regions were collected from silos managed by SENWESS.

Samples
One hundred and twenty three (123) maize samples were randomly collected from selected silo sites from different agricultural regions of South Africa (Gauteng, North West and Free State). A structured sampling model was used for sampling where 10 kg of maize was taken from different points of the silos while the maize was routinely moved. The collected samples were mixed and 5 kg subsequently collected. The samples were collected separately, finely milled using a warring blender (IKA, Model M20, Germany) and put into sterile zip lock polythene bags, labeled and stored at 4˚C prior analysis to arrest any formation of mycotoxins before analysis. Fifty nine samples (59) were from the Eastern region (ER) while sixty four (64) were from the Western region (WR).

Determination of Moisture Content
The moisture content of samples was determined using the AOAC method [26]. Five grams (5 g

Mycobiota Enumeration in Maize Samples
The mycobiota population in the maize samples was enumerated using the dilution plate techniques as described by [27]. Appropriate 10-fold dilutions of milled maize samples in sterile water were spread plated on potato dextrose agar (PDA) and incubated in the dark at 28˚C for 72 h. Thereafter, the mycobiota present in each sample was enumerated and reported as colony forming units per gram (cfu/g) of maize.

( )
Number of colonies reciprocal of the dilution factor cfu Plating volume 1 ml

× =
The percentage occurrence of each of the isolates was calculated by comparing the ratio of the number of individual organism to the total number of organism present in each sample.
Percentage of appearance (PA) was calculated according to the following formula:

Isolation and Purification
The previously cultured plates were returned to the incubator for additional 2 -4 days for isolation of surface sample mycoflora and purification [28] [29]. Purified isolates from various plates were grouped on the basis of their colony morphology (colour and pigmentation of colony) and characteristics of spores (sclerotial production) [30] [31] [32] among others. Actual identification was carried out using the Polymerase Chain Reaction (PCR) method with different primers. A representative from all the various groups was scrapped using a wooden spatula and put in special extraction tubes (lysis tube) prior extraction of DNA. (BLASTn) for homology in order to identify probable organisms in question [38].

Molecular Identification of Aspergillus Isolates
The sequences were later deposited in the GenBank for allocation of accession number.

Cultural Method for Detection of Aflatoxigenic Fungi in Maize
Yeast Extract Sucrose (YES) Agar (yeast extract; 20 g, sucrose; 150 g, agar; 20 g and MgSO 4 ; 0.5 g) was used as described by Criseo, Bagnara [39]. Mycelia plugs of Aspergillus isolates were inoculated on petri dishes containing YES medium in duplicates and the isolates incubated unilluminated at 28˚C for 3 -14 days.
The YES agar plates checked on the 7 th and 14 th day for aflatoxin producing ability by the ammonium hydroxide vapour-induced colour change test as described by Jefremova, Ostrý [40]. 2 ml of concentrated ammonium hydroxide solution (W/V, 25%,) was placed on the inside of the lid of the inverted petri dish containing the isolate on YES agar and left for 5 -10 minutes. Colour change at the reverse side of the agar plate was then observed for those that tested positive. Plates that tested negative were re-examined on the 14 th day for colour change.

Thin Layer Chromatographic Method for Qualitative Detection of Aflatoxins Producing Isolates among Aspergillus Species
Extraction of aflatoxin from the isolates was done in accordance with Midorikawa, Pinheiro [41] and Yin, Yan [42]. The 7-day old Aspergillus isolates on YES agar were divided into two equal halves using sterile surgical blades (one half for TLC analysis while the other half was kept for other analyses). The first half of the agar containing the isolates was scooped into 50 ml centrifuge tubes and 15 -20 ml of 70% methanol-water (70:30) added to it and kept on a shaker for 30 minutes. Thereafter, it was centrifuged at 5000 rpm for 5 minutes and the extracts decanted into clean tubes. The extracts were then evaporated to dryness by air blowing in the dark evolution chamber. The residues were then reconstituted with 500 μl of 100% methanol. A 20 μl volume of each of the reconstituted extracts were spotted on a 20 × 20 glass backed 250 μm thick silica gel coated TLC plates (Merck KGaA, Darmstadt Germany) and developed in the TLC tank containing the mobile phase; chloroform-ethyl acetate-propane-2-ol (90:5:5, v/v/v). The presence of aflatoxins was determined by viewing the plates under the UV light at 365 nm for the presence of a bright blue or blue green fluorescence at the same migration level with the total aflatoxin standard (Sigma Aldrich) on the silica plate.

Detection of Aflatoxin Producing Gene in Aspergillus Isolates
The DNA of suspected Aspergilla were examined for the presence of five important aflatoxin-producing genes (aflR, aflJ, aflM, aflQ, aflD and omt-A) present in  [33]. The PCR amplified products were resolved on 1% agarose gel and stained with ethidium bromide. After electrophoresis, gel was removed from the gel-casting platform and exposed to UV transillumination.
The following primers were used for the detection of the aflatoxin producing  Table 1.

Liquid Chromatography Mass Spectrometry Mass Tandem (LCMS/MS) Parameters
An LC-MS/MS method was designed and validated for the analysis of 123 analytes. A Waters Acquity UPLC system coupled to a Xevo TQS mass spectrometer was calculated as three times the standard error of the intercept divided by the slope of the standard curve; the limit of quantification (LOQ) was computed in a similar way except for the standard error, which was by a factor of six. The calculated LOD and LOQ were verified by the signal-to-noise ratio (s/n), which was more than 3 and 10 respectively in accordance with the IUPAC guidelines [45].

Moisture Content and Mycobiota Count in Maize Sample
The moisture content of the maize samples ranged from 7.38% -8.84% across both regions, with ranges of 7.38% -8.81% and 7.64% -8.84% for ER and WR respectively. The mean moisture content for maize in both regions (8.30% and 8.26%) is not significantly different (p > 0.05) from one another ( Table 2).
Mycobiota count in the maize ranged from 0 -48 cfu/g and 0 -23 cfu/g for WR and ER respectively, with mean count in WR (9.75 cfu/g) higher than those obtained in the ER (5.93 cfu/g). Sample 045/M/2015 from ER had the highest Aspergillus spp. load (9 cfu/g), with fungal load ranging from 0 -7.33 cfu/g and 0 -9 cfu/g for WR and ER respectively ( Table 2).

Mycobiota Distribution in Maize from Different Regions
A total of 123 maize samples were analyzed (WR; 64 and ER; 59). Fungi spp. belonging to eight genera; Fusarium, Aspergillus, Penicillium, Rasamsonia, Talaromyces, Paecilomyces, Byssochlamys and Verticillium were isolated from the maize and four distinct genera Talaromyces, Paecilomyces, Byssochlamys, Verticillium found in maize were from the ER (Table 3). Fusarium spp. had the highest distribution while Penicillium spp. remained the least distributed among other fungal spp. from both regions (Figure 2).

Incidence of Aflatoxin Producing Genes in Aspergillus Species
The result of screening for aflatoxin producing genes in the Aspergillus section flavi revealed that none of the isolates from both regions possessed the AflR gene ( Figure 3(a)). The hierarchy of distribution of the other genes screened for in isolates from WR and ER is; aflM (33%) > aflJ (19%) > aflD (8%) > Omt-A (3%) and aflM (17%) > aflJ (7%) > aflD (7%) > Omt-A (2%). The aflatoxin producing ability of the isolates was also confirmed with the cultural and TLC methods.
Only 14% and 5% of the isolates in WR and ER respectively tested positive using the cultural NRDCA method and 6.25% and 1.7% with TLC method ( Figure   3(b)). A 9.09% of the isolates from both region tested positive for aflatoxigenicity using the polyphasic approach (molecular, cultural and TLC), 20.45% were positive for two methods while 70.45% were positive for at least one of the methods.

Analysis of Liquid Chromatography Mass Spectrometry Mass Tandem (LCMS/MS) for Fungal Metabolites in Maize Samples
Aflatoxin was not detected in any of the maize samples analyzed using the LCM-S/MS. However, other detected metabolitesviz: 3-Nitropropionic acid; Sterigmatocystin; seco-sterigmatocystin; averufin; Kojic acid; and orsellinic acid.
At least 36.59% of maize samples had one or more of the metabolites mentioned above while 20.33% of the samples had traceable amounts of kojic acid, but below limit of quantification (data not shown).
In all the regions, orsellinic acid had the highest percentage of occurrence (29.27%; concentration range between 235.76 and 829.60 µg/kg), followed by kojic acid (5.69%; concentration range of 65.61 to 587.51 µg/kg) while the rest were found in only one sample (0.81%). Fifty percent (50%) of maize samples from WR contained at least, one of these metabolites while about twenty-two percent (22.03%) of maize samples from ER had these metabolites (Table 7).

Detection of Aflatoxins in Maize Samples Using High
Performance Liquid Chromatography Standard curves were constructed by calculating the ratio of the peak areas for each aflatoxin standard samples spiked before and after extraction at three levels of 25, 50 and 100 µg/ kg for all aflatoxins analyzed (Suppl. Figure 1). The toxins (G 2 , G 1 , B 2 and B 1 ) were eluted at 6 -7, 7 -8, 8 -9 and 10 -11 minutes respectively. The aflatoxin content of the maize samples was measured in µg/kg. Aflatoxins G 1 and G 2 were absent in all analyzed samples as revealed by HPLC technique. However, aflatoxins B 1 and B 2 were found in both regions in varying amounts. The ranges for aflatoxin B 1 concentration (0 -65 and 0 -10.70 µg/kg) was higher than AFB 2 (0 -17 µg/kg to 0 -12.9 µg/kg) across WR and ER. The ER had a mean value of aflatoxins B 1 of 1.04 µg/kg compared to the WR with a mean value of 3.11 µg/kg. The same trend was observed for AFB 2 with WR having a higher mean value of 0.05 µg/kg and ER with a mean value of 0.98 µg/kg. Thus, the mean total aflatoxin was higher in WR (3.59 µg/kg) compared to ER (1.09 µg/kg) ( Table 6). There was no significant difference between aflatoxins B 2 and B 1 in ER and WR. The WR recorded a higher percentage contamination of samples for both aflatoxins B 1 (25%) and B 2 (14.06%) compare to aflatoxins B 1 (18.64%) and B 2 (5.08%) from ER (Table 6).

Discussion
Moisture content of grain at post-harvest and during storage is critical in the quality of the product after storage. A moisture content of 13% is the maximum moisture content required for grain storage [46]. Analysis of moisture content in maize samples in this study revealed a lower range of mean moisture content hence, fungi are classified as field and/or storage microbes. Aspergillus species are both field and storage fungi [49]. Therefore, with such low moisture, the fungal load observed and contamination by aflatoxin in maize in this study could have been due to invasion in the field and proliferation during storage [50] [51].
For example, Kimanya, De Meulenaer [52] found levels of aflatoxin up to 21,667 μg/kg in freshly harvested maize before sorting and 1758 μg/kg in the same stocks of maize after sorting and stored for 5 months. Moisture content was found to have no significant effect on contamination by aflatoxin in maize. Studies have shown that moisture below 13% has little or no influence on the growth of fungi and mycotoxin production during storage.
The three main genera of fungi known for producing mycotoxins; Aspergillus, Fusarium, and Penicillium [53] were found in maize grown in SA. Although this study focused onAspergillus spp., fungal spp. belonging to eight genera (Fusarium, Aspergillus, Penicillium, Rasamsonia, Talaromyces, Paecilomyces, Byssochlamys and Verticillium) were found in maize from the different agro-climatic regions of SA. Out of the eight genera, four distinct genera (Talaromyces, Paecilomyces, Byssochlamys and Verticillium) were not found in maize from the Eastern Regions. From this study the mycotoxin producing genera were more in the WR than the ER. This result corroborate earlier studies in SA maize where similar genera of microbes were isolated in their maize [54] [55]. The latter author reported incidence of mycotoxin-producing genera of Aspergillus, Penicillium and Fusarium in maize produced in Tunisia and Egypt; Fusarium spp. 95.3%, Aspergillus 87.5% and Penicillium 64.0% [55]. The geographic location of sample could be the primary factor affecting composition of microbiota in grains [56].
Out of the thirteen Aspergillus species isolated in this study, A. flavus (47.15%) was the most predominant followed by A. niger (4.69%) and A. fumigatus (4.69%), which contradicts the reports of Egbuta [57] and Chilaka, De Kock [54] who found higher occurrences of A. fumigatus (45%) than A. flavus (43%) in SA commercial maize (73.4%) and Nigeria (66.7%) respectively. The high incidence of A. flavus in both regions compared to other members of Aspergillus section flavi group (A. parasiticus, A. mnutus etc.) could be due to previous reports that Aspergillus flavus are more prevalent during times of high heat and drought [23]. Also, A. flavus are natural habitant of soil, hay, decaying vegetation, and grains acting as the reservoir of inoculums for infection of kernels in the field. Aspergillus flavus possess a higher adaptability to growth substrates in a range of environments (field and storage fungi) and can produce spores that remain viable even under extremely strict conditions [1] [58] [59]. Fungi that thrive in a particular area are strongly determined by the prevailing climatic conditions [56] [60]. The findings of this study corroborate those of Kankolongo, Hell [61] in Zambian maize in which A. flavus and A. niger were the most prevalent fungal isolates of maize grains.
In this study, 27.64% of the A. flavus isolates were aflatoxins producers where rainfall that amounted to 141 mm from 1991 to 2014 [62]. In already hot climates, more frequent drought may result in higher mycotoxin production [66].
Numerous studies agree on the main role of drought and high temperatures in higher aflatoxin production in maize [23] [67] [68].
Aspergillus flavus were found in 61% of the maize samples from both regions where about 28% did produce aflatoxins. Fungal growth and AFs production in cereals depends on temperature, moisture, etc. [69]. The non-production of aflatoxins could be attributed to: high temperatures and water stress which reduces production of AFB 1 , despite the growth of A. flavus under these conditions [70], then 2015 been a year of drought and very low rainfall (141 mm). Interactions between water activity and temperature have prominent effects on Aspergillus spp. and production of aflatoxin [71] [72]. These authors studied the effect of interactions of temperature and water activity (aw) on the biosynthetic regulatory gene (aflR) expression and production of AFB 1 by A. flavus in maize. They observed the greatest growth of A. flavus at 30˚C/0.99 aw with no growth at 20˚C/0.90 aw [71] [72]. Based on the investigation by Battilani, Toscano [73] on the possible emergence of AFB 1 in cereals as a result of climate change, they projected that for every 2˚C increase in temperature, there is an increase in AFs risk. In addition, Shooshtari, Mohammadi [74] found that a mutation including substitution of some bases and many other different physiological conditions affecting biosynthesis of aflatoxin, does affect production of aflatoxin. Furthermore, isolated spp. are genetically different and the nucleotide sequence is not associated with the mentioned primer. For example, the ITS molecular marker identified most of the Aspergillus flavus as Aspergillus oryzea. A. oryzae is a domesticated variant of A. flavus [75], which could be another reason aflatoxins were not produced.  [76], as they are teratogenic and mutagenic and chronic exposure to aflatoxins have resulted in reduced immune activities [77], malnutrition [78] and growth impairment [79]. All South Africans consume maize in one form or another due to its use as an ingredient in different food products (maize meal, grits, corn flakes and snacks) [80] [81]. Maizeconsumed by livestock and poultry, also end up in the human food chain, through meat products, dairy products, cheeses and eggs. Therefore, SA maize quality has a direct impact on the health of humans and animals who consume the products. To find the problem attributable to aflatoxin contamination of food, both detected concentrations and consumption habits mustn't be ignored [82]. Unfortunately, these standards did not exist for the co-metabolites, therefore could not be picked up by the HPLC method. On the other hand, LC-MS/MS is the most successful interface and a powerful approach for identification of the unknown constituents [84]. The reason might be that LC-MS/MS is effective in quantifying trace level contaminants in food and feed as well as a range of parent compounds and their metabolites [85], many of which are easy to ionise and give good sensitivity often with crude sample preparation. This is because most of these metabolites (averufin, sterigmatocystin and seco-sterigmatocystin) are active precursors of AFB1 formation [86].  [103]. Also, 3-NPA inhibits succinate dehydrogenase, a key enzyme for oxidative energy production [104], and causing ATP levels in the brain to fall. This effect develops fast and is not limited to the sites of morphological damage [101]. Since the nervous system requires lots of energy to work, mitochondrial damage is probably reflected in the electrical activity of the brain. Kojic acid (5-hydroxy-2-(hydrxymethyl)-4-pyrone; KA), a non-regulated metabolite, is an organic acid secreted by several species of Aspergillus, especially A. oryzae [105]. It is multifunctional and has weak acidic property, non-hazardous biodegradation, making it an attractive and profitable skeleton for development of biologically active compounds by its derivatives [106]. Kojic acid (KA) is use as food derivative, antibiotic, antioxidant [105], a skin whitening agent, treatment of chloasma [107], antitumor agent [108] and radio protective agent [109].
This metabolite was the second highest detected in samples from both regions, while other samples had it but in unquantifiable amounts.
Orsellinic acid is a common salicylic acid unit in the biosynthesis of secondary metabolites in actinomycetes, fungi and lichens, formally isolated from chaetomium cochliodes in 1959 [110]. Orsellinic acid is a key biosynthetic intermediate of many depside metabolites in lichen and fungi. Orsellinic acid is also an important polar co-metabolite present in many fungi; however, its contribution to overall bioactivity is not well understood. Orsellinic acid is a useful standard for bioassay and analytical techniques for dereplication of common co-metabolites.
This non-regulated metabolite was the most frequent metabolite detected in maize samples from both regions. Most of the metabolites detected (KA, orsellinic acid and seco-sterigmatocystin), usually colonise plant tissues and offer significant benefits to their host plants, by producing growth regulators, antimicrobials and antiviral, which are survival advantages [111].
Among the 58 Aspergillus flavus isolates tested if any of the five aflatoxigenic genes were present (aflD, aflM, omtA, aflJ and aflR), no Aspergillus flavus isolate had the regulatory aflR gene, three isolates possessed the omt-A gene (two isolates from WR and one from ER) eleven isolates possessed the aflD gene (seven from WR and four from ER) while sixteen isolates possessed the aflJ gene (twelve from WR and four from ER). Majority of the isolates that tested positive, possessed the aflM gene (twenty-one from WR and ten from ER). One isolate (from ER) possessed up to three of the five genes tested, fifteen isolates possessed two out of the five genes tested (thirteen from WR and two from ER) while twenty-eight isolates possessed, at least, one of the genes tested. 50% and 25.86% of tested isolates from WR and ER respectively tested positive for aflatoxigenicity.
Mahmoud [117] also reported a correlation between PCR amplification of four aflatoxin biosynthetic pathway genes (aflD, aflM, aflP, and aflQ), with the aflatoxins production ability of A. flavus isolates from stored peanuts in Egypt. Aflatoxins-producing genes present in an Aspergillus isolate does not necessarily confirm the isolate to be aflatoxigenic [44] [114] [118] [119]. PCR-based techniques are important to detect aflatoxigenic potential of Aspergillus isolates [120] [121] [122], since these genes encode the key enzymes and regulatory factors in the pathway of biosynthesis of aflatoxins.

Conclusion
Climate change is clear and has been increasing over the past few years and this could join a threat to food security and safety. Even though the findings of this study show that irrespective of the climatic variations of the different regions in South Africa, Aspergillus species and aflatoxin production is not yet a threat to South Africa's commercial food/feed industry, the frequent occurrence of drought in South Africa as experienced in 2015 is a clear sign that climatic zones that appear safe now might later lead to risk of disease and/or loss in crop production as climatic conditions change. There is, therefore, a need for long-term and continuous monitoring of Aspergillus species and their toxins in maize across different agro-climatic areas of South Africa (4 to 5 years) as well as other suppliers of agricultural maize and maize grown and stored by small-scale farmers. This will help simulate and model a trend that can clearly predict the long-term effects of climate change on aflatoxins in South African maize. Extensive studies will be carried out on strategies such as competitive exclusion and touch inhibition and real application be done on South African fields comparatively in the different agro-climatic regions.

Funding
This research was funded by North West University, Mafikeng and The APC was funded by North West University, Mafikeng.