Molecular and chemical based characterization of aflatoxin producing aspergillus species obtained from stored grain samples

Abstract

Background

Aspergillus section Flavi is a group of widely distributed multicellular fungi associated with contamination of stored grain. Some species of it secretes aflatoxin contaminants which is a carcinogenic in nature. Due to this it poses a significant global challenge in the health, agriculture and food processing industries. The aim of present study is quantification by using a chemical based detector and molecular identification of aflatoxin producing fungi from stored grain samples of flood prone area of Bihar, India. The samples (n = 61) were investigated for the presence of aflatoxigenic fungi, which was further confirmed by HPLC-FLD. The aflatoxigenic isolates identified through amplification of the internal transcribed spacer (ITS) region.

Findings

A total of n = 119 fungal isolates from 5 distinct genera were isolated in PDA and CYA. The Aspergillus species were the dominant with occurrence of Aspergillus section Flavi (58.95%), Aspergillus section Nigri (35.79%), Aspergillus section Fumigati (3.16%), Aspergillus section Terrei (1.05%) and Aspergillus section Circumdati (1.05%). The positive isolates were quantified by HPLC-FLD and highest amount of aflatoxin was determined in W7 isolate of wheat as 6907.47 µg/kg of AFB₁ and 68.88 µg/kg of AFB₂. Further, ITS sequencing of five positive isolates for aflatoxin showed that a significant alignment of 99–100% with the previously isolated fungi A. aflatoxiformans DTO 228-G2 and A. austwickii DTO 228-F7 which was confirmed by the BLAST and all the sequences were deposited in the NCBI database.

Conclusions

To our knowledge, this is the initial report concerning the presence of aflatoxigenic species of A. section Flavi. Hence, to conclude contamination of food grain samples with aflatoxin producing fungi is alarming in these flood prone areas.

Introduction

Moulds are widely distributed multicellular fungi associated with food spoilage (Ayofemi 2020). Aspergillus is a group of moulds widespread under favorable environment condition which has the potential of contaminating the stored grains (Adejumo and Adejoro 2014; Chen et al. 2023). Their growth on these stored grains can cause off odour, off flavour, discolorations, decrease in nutritional value and loss in weight. All these changes take place before the gross development of these fungi (Ayofemi 2020; Girish and Goyal 1986). Mycotoxins responsible for degradation of grains are largely produced by Aspergillus spp. of fungi group (Girma et al. 2016; Singh et al. 1983). Some species of Aspergillus can produces the aflatoxins, leading to grain contamination at various stages viz. harvesting, processing and storage. Mycotoxins are the low molecular weight secondary metabolite produced by the filamentous fungi (Bennett et al. 2003). Aflatoxins are difuranoumarin derivatives mainly secreted by Aspergillus section Flavi. These are stable at UHT (Ultra High Temperature) 135–220℃ and decomposes at 237–306℃ (Kumar et al. 2017), therefore boiling or pressure cooking does not assure the complete removal of aflatoxins. They are approximately of 18 types (Okoth et al. 2018), out of which aflatoxin B₁ is the most toxic and class-I carcinogenic agent classified by International Agency for Research on Cancer (IARC 1993; 2016). After consumption the different groups of aflatoxins such as methylene and carbonyl called as polyketides are modified upon consumption and transferred to different body parts (Pandey et al. 2019). The long term aflatoxins exposure leads to aflatoxicosis, a fatal acute poisoning which predominantly causes liver damage (WHO, 2018). Research indicates that children are the most exposed to all food types contaminated with aflatoxins, followed by adolescents, with adults being the group with the lowest exposure (Ezekiel et al. 2021). Current evidence indicates that infants and young children are more likely to experience the harmful effects of mycotoxins because of their underdeveloped metabolic systems, higher intake relative to body weight, faster metabolism, and reduced detoxification capacity compared to adults (Hulin et al. 2014; Milićević et al. 2021; Alameri et al. 2023). Also, it is one of the few mycotoxins that have been developed for use as a biological weapon (Klich 2007). Aflatoxins associated with stored grains are problem of tropical and subtropical region worldwide.

India is predominantly an agrarian country with nearly three fourths of the people depending on agricultural or rural economy. The high temperature, humidity, monsoon rain and flash flood causes fungal proliferation and mycotoxin production (GSI – Eastern Region 2014; ICAR 2018). Flood poses a serious threat to food security and is a significant challenge in agriculture. 12.7% of the nation’s flood prone land is in Bihar (ICAR 2017; NDMA 2008). Considering the above fact the aflatoxin production is temperature dependent, pre-harvest (plant pathogenic) and storage associated (saprophytic fungi) problem (Duricin et al. 2016; FAO 2017).

Thus, in this study, we sought to achieve an understanding of the different drivers of aflatoxigenic mycoflora contamination in stored grain samples of small scale farmers’ food system in Bihar. Also, to determine the presence of aflatoxins in these aflatoxigenic mycoflora by an optimized HPLC-FLD based method coupled with Kobra cell and to construct the maximum likelihood for aflatoxin producing strain based on ITS sequencing. This result will provide the current scenario of aflatoxigenic mycoflora from grain samples in the flood prone areas of Bihar, India.

Materials and methods

Study area

A total of 61 stored grain samples were collected randomly depending on the availability from flood prone areas of Sitamarhi and Madhubani districts of Bihar, India. These samples were collected from small scale farmers’ storage sites and kept in a sterile polythene bag (50–150 g/sample) under the storage condition of 4℃. Information regarding (supplementry information S3) the post-handling of the grain storage practices was collected in a questionnaire Proforma. Samples were collected from December 2020 to April 2021.

Chemicals and reagents

Czapek’s Yeast Extract Agar (CYA) component and Potato Dextrose Agar component were bought from Sigma-Aldrich, while all other chemicals and solvents system for TLC were bought of HPLC grade. The standards of aflatoxins B_1, B_2, G₁ and G₂ were purchased (R-Biopharm Neugen Pvt. Ltd., Hyderabad, India) in a mixture (concentrations are as follow, AFB₁−1 µg/mL, AFB₂- 0.5 µg/mL, AFG_1- 1 µg/mL and AFG_2- 0.5 µg/mL) of 2 mL. The standard was stored at 4℃ away from light before use.

Mycoflora isolation and mycological identification

The grain samples surface were disinfected before plating. Approximately, 15–30 grains were plated in triplicate onto Potato Dextrose Agar (PDA) medium (Pitt and Hocking 2009; 2022). After incubation of the samples, fungal infections were noted and the incidence of fungal species for each sample was determined in percentage. The morphological characteristic of the strains were studied at 10x, 40 × and 100 × respectively (Kong et al. 2014). The potential mycotoxigenic fungal colonies were sub cultured on Czapek’s Yeast Extract Agar (CYA) medium.

$$\mathrm{Percent}\;\mathrm{incidence}=\left(\mathrm{total}\;\mathrm{number}\;\mathrm{of}\;\mathrm{each}\;\mathrm{isolate}\;\mathrm{in}\;\mathrm a\;\mathrm{sample}/\mathrm{total}\;\mathrm{number}\;\mathrm{of}\;\mathrm{all}\;\mathrm{identified}\;\mathrm{isolates}\;\mathrm{in}\;\mathrm a\;\mathrm{sample}\right)\times100$$

Culture condition for extraction of aflatoxins

A total of fifty-six pure culture samples of Aspergillus section Flavi along with positive strain MTCC2798 were grown on CYA medium. Then with the help of inoculating loop, loopfull of conidia was inserted into the 50 mL SKMY broth (Davis et al. 1966; Ranjan et al. 1991). These flasks were incubated in room temperature for seven days in still condition. Three liquid cultures were produced for each strain tested. In the biosafety cabinet 50 mL fully inoculated cultures were filtered through Whatman filter paper No.1 (Whatman International Ltd., Maidstone, England). Then the equal volume of chloroform was added to the filtrate and then contents were shaken for 30 min. The chloroform fraction was passed through separating funnel followed by sodium sulphate column and collected in the glass tube. Then the chloroform fraction was concentrated at 40℃ (Das et al. 2012; Shotwell et al. 1966; Thomas et al. 1975). These crude extract samples were stored at 4℃ in the dark in 1 mL chloroform for 7–10 days till TLC analysis.

Preliminary detection of aflatoxins

For TLC Silica gel 60 F₂₅₄ plate 20 cm X 20 cm (Merck, Dermstadt, Germany) was taken. About 100 µL of sample’s crude extract of all the strains were loaded onto the plate along with positive control strain and mixed standard of B₁, B₂, G₁ & G₂. The plates were developed in mobile phase consisting of toluene, isoamylalcohol and methanol (90:32:2 v/v/v) (Fried 1996; Ranjan et al. 1991; Choudhary et al. 2020). After developing, the plates were visualized under long (366) and short (254) UV wavelength. The bands of standard and positive sample crude extract were scrapped off and mixed with 1 mL methanol and this methanolic extract was subjected to UV Spectrophotometer, at 360 nm for AFB₁ and 362 nm AFB_2, AFG₁ and AFG₂ (with ℇ = 21800 for AFB_1, ℇ = 24000 for AFB_2, ℇ = 17700 for AFG₁ and ℇ = 19300 for AFG₂).

Quantification by HPLC with Kobra-cell derivatization and fluorescence detector

Aflatoxins extraction and purification

All the fungal isolates which were positive for aflatoxin production were selected for further aflatoxin quantification by HPLC. All the crude chloroform extracts of fungal strains along with the positive strain MTCC 2798 were kept at 0℃ till further processing and this analysis was performed at TUV India food lab, Pune. The AFLARHONE®WIDE Column (IAC, R-Biopharm Rhone Ltd; Glasgow, UK) were used for sample purification and extraction of aflatoxins. Briefly, 1 mL PBS, pH-7.2 was combined with pre-weighed crude extract in a vial and it was passed through the column followed by washing with water (1 mL) five times. Finally, all the waste was collected in SPE (Solid Phase Extraction) chamber. Then column was dried for 10–20 s and aflatoxins were eluted with methanol 1 mL and water 1 mL by back flushing. The test-tube was vortexed and passed through 0.45 µm syringe filter and collected in an autosampler glass vial into HPLC system.

Detection of AFB₁, AFB₂, AFG₁ and AFG₂ by RP-HPLC-FLD- Kobra-cell

A reversed phased (RP)—HPLC protocol was used for determination of aflatoxins in the sample. The method was previously reported by Zhu et al. 2013. A 1260 Infinity HPLC system (Agilent Technologies, Santa Clara, CA, USA) equipped with a quaternary pump and vacuum degasser (model G1311B), an autosampler (model G1329B, 100 µL total loop volume) and a FLD detector (model G1321B) was used. The separation column connected to guard cartridge was a Zorabax Eclipse XDB C18 (5 µm, 150 mm, 4.6 I.D.) column and the temperature of the column was maintained at 40℃ in a thermostable column compartment (model G1316A). Post-column derivatization was done with a Kobra cell® (R-Biopharm Rhone Ltd., Glasgow, UK). The mobile phase was a mixture of methanol and KBr (119 mg of KBr and 350 µL of 4 M nitric acid were dissolved in 1 L of D/W) in the ratio of water (with KBr): methanol (60:40) (AOAC 2006). The mobile phase was freshly prepared on the day of analysis, as recommended for the post column derivatization with the Kobra cell®. Level of detection (LOD) of AFB₁, AFB₂, AFG₁ and AFG₂ were established by practical experimentation as being 0.3 µg/kg for all four aflatoxins. Limit of quantification (LOQ) is found to be 0.5 µg/kg for AFB₁, AFB₂, AFG₁ and AFG₂ (Supplementary information S4)_. The filtered samples were injected into the system through autosampler and aflatoxins signals were detected with FLD at excitation of 362 nm and emission at 455 nm. The data were acquired and analyzed with the Agilent data handling Chemstation 3 (Agilent Technologies).

Recovery study

To ensure the accuracy of the test aflatoxins free crude extract of fungal strain was spiked with AFB₁, AFB₂, AFG₁ and AFG₂ at level of 5, 7.5 and 10 µg/kg. The spiked samples were examined followed by the estimation of both the recovery and standard deviation.

Molecular characterisation of Aspergillus section Flavi strain by ITS sequencing

The positive aflatoxin producing strains which were quantified using a HPLC-FLD was subjected to molecular identification by ITS sequencing at NCIM (National Collection of Industrial Microorganism), Pune. DNA was extracted from the colonies of aflatoxin producers. The spin column kit (Himedia, India) was used to extract the DNA. Exonuclease I-Shrimp Alkaline Phosphatase (Exo-SAP) was used to purify the amplified fungal ITS r-RNA gene (600 bp) (White et al. 1990) after it had been amplified using PCR in a thermal cycler (Darby et al. 2005). ABI3500xl genetic analyzer (Life Technologies, USA) used the Sanger technique to sequence purified amplicons. In order to find regions of local similarity between sequences, Basic Local Alignment Search Tool (BLAST) is used to further analyze sequencing files (.ab1) that have been edited using CHROMASLITE (version 1.5) and the closest culture sequence were obtained from the National Center for Biotechnology Information (NCBI) database (Altschul et al. 1990).The statistical significance of matches by comparing the nucleotide or protein sequences to sequence database were determined (Gertz 2005). The BLAST algorithms were used to identify members of gene families and infer functional and evolutionary links between sequences (Altschul et al. 1990). Pairwise alignment was used to determine how similar the query sequence was to the sequences found (States et al. 1991). Therefore, each isolate was reported with the hits observed in the said database. Further, multiple sequence alignment and phylogenetic analysis was done for accurate species prediction and Evolutionary analyses were conducted in MEGA6 (Felsenstein 1985; Karlin et al. 1990; Myers et al. 1988; Tamura et al. 2013). The evolutionary history was inferred using the Neighbor-Joining method (Saitou et al. 1987). The evolutionary distances were computed using the Kimura 2-parameter method (Kimura 1980).

Statistical analysis

The statistical analysis of data was performed by one way ANOVA for grain samples, using Graph Pad Prism (version 8.0). The p-value < 0.05 was considered significant. For rest of the analysis descriptive statistical analysis were done.

Results and discussion

Household survey analyses

A total of 61 samples were collected from small scale farmers in this study. Most of them did not have awareness regarding the toxigenic mouslds and their severe consequences. The Fig. 1B represents 83.33% of farmers disposed the gross mouldy grains and consumed the remaining, unaware of microscopic mycoflora associated with stored grain samples. Remaining 16.66% of farmers used the mouldy grains for animal feeding. The study population included is not dependent on chemical additive during storage of grain samples and mostly dependent only on sun-dry method. The Fig. 1A represents that 8.19% household samples used natural additives such as dried neem leaves and cloves for grain safety along with washing and sun-dry during the storage whereas 91.80% of household samples used traditional methods of washing and sun-dry only. The storage duration of the studied sample is presented in Fig. 1C it shows that 57.38% of samples (includes cereals, pulses and oilseeds) selected were stored for 6 months, while about 40.98% of samples were stored between 9 months to 1 year and 1.63% of the sample were found to be stored for 2 years. Since, farmers were dependent on traditional methods of storage and for long storage there were no proper measures taken leading to contamination of grains with multiple mycoflora, increasing the chances of contamination of grains with potential mycotoxigenic mycoflora. The winter rain and hail storm lead to moistening of grains vulnerable to mycological contamination and these conditions were also observed in previous studies by Kumar et al. 2017 in different regions of India. In this study, Fig. 1D shows that, 11.47% of the total stored samples either experience winter rain or the hail storm during the drying of the grains in the fields, whereas, 88.52% of the samples dried properly by traditional methods and were stored. The Fig. 1E represents that, 8.19% of the total grain samples were stored in the sack such as the rice, wheat and groundnut. The 42.62% of the total grain samples such as pulses, cereals and oilseeds were stored in tin containers. The 11.47% of grain samples mainly oil seeds were stored in plastic containers. About, 37.70% of grain samples mainly cereals were stored in kothi (mud warehouse). The type of storage container had no much impact if the moisture content of the grain is properly removed. The above results indicated that the pattern of farming in these flood prone districts is mostly by the traditional means, due to lack of technical and scientific knowledge. The flood during the pre-winter period and moreover, the water logging in the fields play an important role in increasing the moisture content of grains leading to mycological infection and due to low socioeconomic status farmers depends on this contaminated food commodities. This study identified potential toxigenic fungal contamination of grain samples and possible risk factors associated with it. It did not find any differences in terms of mycotoxigenic fungi present on the samples based on different processing or storage system of food grains. Therefore, it was assumed that, during post-harvest management of food grains, moisture content and favorable temperature are more substantial contributors to a mycoflora contamination which was also previously determined by Shashidharan et al. 1992. Also, this may be due to increase in humidity level of flood prone area of sample collection (Kansal et al. 2017; Pitt and Hocking 2022).

Fig. 1

Summary of (A) house-hold crop protection practice (B) house-hold handling of mouldy food grain samples (C) storage duration of different samples (D) post-harvest unseasonal rain experience of food grain samples (E) house-hold level storage practice by small scale farmers

Mould isolates of tested grain samples

The stored grain samples were analyzed on the PDA medium followed by CYA medium, after 7–10 days incubation of the samples at room temperature. Mostly, the grain samples became mouldy in seven days to a different extent Fig. 2D and 2E. About 119 distinct genera of fungal isolates represented in Fig. 2A such as, Aspergillus (95), Penicillium (16), Alternaria (7) and Fusarium (1) were identified and recorded from the 61 food grain samples of different varieties. Aspergillus and Penicillium prevalence in the samples were noticeably higher in the 119 fungal isolates. About, 95 isolates belonged to Aspergillus spp. and 16 belonged to Penicillium spp. with the incidence of 79.83% and 13.44% respectively. The isolates number of Alternaria and Fusarium were 7 and 1 respectively, representing 5.88% and 0.84% of the total number. Among 95 isolates, 58.95% belonged to Aspergillus section Flavi, 35.79% belonged to Aspergillus section Nigri, 3.16% belonged to Aspergillus section Fumigati, 1.05% belonged to Aspergillus section Circumdati and 1.05% belonged to Aspergillus section Terrei Fig. 2B. Out of 61 samples isolates of different groups (cereals, pulses and oil seeds) represented in Fig. 2C cereals, were found to be significantly contaminated (p < 0.05) with 91.70%, in comparison with oilseeds (89.63%) and pulses (88.39%). These results indicate that all types of grain samples, vulnerable to contamination by the discovered fungal mycoflora notably those from the genera of Aspergillus and Penicillium. These findings were found to be similar with Reddy et al. 2009 which also shows contamination of stored grain samples mostly with Aspergillus in different state of India. Table 1: represents the infection (in percent) of different grain samples with potential mycotoxigenic mycoflora. All the stored grain samples were infected by Aspergillus except the rice (R5) and flaxseed (T4) which did not show contamination by mycotoxigenic mycoflora. With regard to contamination of stored grain samples with mycotoxigenic mycoflora cereal samples (R3) and (R10) of rice, were found to be highly contaminated with 4 different species and in pulses samples (C3) chickpea, (A3) pigeon pea and (Mo1) yellow lentil were highly contaminated with three different species and in oilseed samples (S1) and (S2) of yellow mustard was found to be highly contaminated with five and three different species respectively. The Aspergillus and Penicillium isolates were found to be prevailing in 61 samples of 119 fungal isolates, which were inoculated in PDA medium. Some of the samples of rice, wheat, flax seed, and yellow mustard were found to be contaminated with other fungal isolates such as Alternaria and Fusarium. This indicates the different level of contamination of the grains, which was similar with previous findings (Choudhary et al. 2020; Wenndt et al. 2020). This study indicates the high percentage of mycotoxicogenic Aspergillus species such as, Aspergillus section Flavi, Aspergillus section Nigri, Aspergillus section Circumdati, Aspergillus section Fumigati and Aspergillus section Terrei. Among all the isolates, the Aspergillus section Flavi was clearly dominating, which is consistent with previous studies (Choudhary et al. 2020). In summary, these results indicated that due to altered post-harvesting processes and storage, various fungal isolates infect the grain samples depending on their susceptibility towards different mycotoxigenic mycoflora.

Fig. 2

Incidence of (A) fungal isolates in food grain samples (B) potential mycotoxin producing species (C) contamination level in different food grain samples (D) display of mould in tested flaxseed (T1) sample (E) display of mould in tested Maize (M2) sample

Table 1 Potential mycotoxicogenic fungal isolates and their incidence in tested food grain samples

Quantification of aflatoxins of fungal isolates

All the fifty-six fungal isolates of Aspergillus section Flavi of potential aflatoxigenic mycoflora were further analyzed with TLC, for presence of aflatoxin. It is confirmed by blue-fluorescence of aflatoxin-B₁ and aflatoxin-B₂ and green-fluorescence of aflatoxin-G₁ and aflatoxin-G₂ in the UV-trans illuminator with the aflatoxins standard represented in supplementry information S1. The Rf value of standards were matched with the positive samples. The AFB₁ were present in five isolates followed by AFB₂ in three isolates of Aspergillus section Flavi and this was confirmed by brilliant intensity of fluorescence. The concentration of this toxin was determined by UV spectrophotometer at 360 nm for AFB₁ and 362 nm for AFB₂ and it is shown in Table 2. Among the five positive isolates, the intensity of fluorescence was very high in W7G isolate. The chromatogram and elution times of AFs standards in HPLC-FLD is in the sequence of AFG₂(8.83 min), AFG₁(11.02 min), AFB₂(14.01 min) and AFB₁(17.90 min) represented in supplementry information S2. The real concentration of analytes (such as AFs) in samples is corrected using spiked studies (Trucksess et al. 2011). For recovery study, three different concentration of mixed standard solution 5, 7.5 and 10 µg/kg for AFB₁, AFB₂, AFG₁ and AFG₂ were directly added to the crude extract of fungal isolates which did not produce aflatoxins. The spiked samples were removed, cleaned up in accordance with the aforementioned technique, and the average recovery was examined by HPLC-FLD coupled with Kobra cell® were 100.05% for 5 µg/kg, 99.13% for 7.5 µg/kg and 103.6% for 10 µg/kg having RSD less than 2.5%, which complied with European Union (EU) requirements and AOAC (AOAC 2006) (Zhu et al. 2013). This method has been validated in agreement with EU Commission regulation EC No. 401/2006 (European Commission 2006). The limit of detection (LOD) is found to be 0.3 µg/kg and limit of quantification (LOQ) is found to be 0.5 µg/kg for AFB₁, AFB₂, AFG₁ and AFG₂.

Table 2 Content of aflatoxins determined by TLC and HPLC-FLD in Aspergillus section Flavi isolates

It has been previously known that under favorable condition Aspergillus section Flavi produces aflatoxins (Ayofemi 2020). Utilizing the tested HPLC-FLD-Kobra cell® technique, the positive fungal strain from TLC was tested for presence of AFB₁, AFB₂, AFG₁ and AFG₂. The AFB₁ was identified in Aspergillus section Flavi isolates of rice (R10), wheat (W7), black mustard (Ra2), yellow mustard (S4) and chickpea (C3) was represented in Table 2. The AFB₂ were detected in Aspergillus section Flavi isolates of wheat (W7), yellow mustard (S4) and chickpea (C3). Among all the isolates wheat (W7) isolate chromatogram represented in Fig. 3, produces high amount of aflatoxin-B₁ as 6907.47 µg/kg. The black mustard (Ra2) isolate was found to be low producer of aflatoxin-B₁ as 252.58 µg/kg. Aflatoxin-B₂ were found to be in high amount in wheat (W7) isolate as 68.88 µg/kg and in low amount in yellow mustard (S4) isolate as 11.22 µg/kg. AFG₁ and AFG₂ were not present in any isolates. All the toxicogenic isolates which were found in this study produced very high amount of aflatoxins which was found to be higher from previous reporting’s done by Rajarajan et al. 2021. The reported AFB₁ and AFB₂ are considered to be the most important dietary risk factor due to being a class-I carcinogen compound and found to be hepatotoxic in nature. This investigation is in confirmation with other investigators (Fakruddin et al. 2015; Kong et al. 2014). Present study indicates excessive level of aflatoxins in mycoflora isolated from seed samples of non-industrialized area is of major concern because, post-harvest treatments were not adequate for aflatoxins removal such as alkalization, ammonization and heat or gamma radiation.

Fig. 3

HPLC chromatogram of W7G isolate of Aspergillus section Flavi representing aflatoxins (AFS) concentration

Molecular characterization of Aspergillus section Flavi

Isolates of yellow mustard (S4), chickpea (C3), rice (R10), black mustard (Ra2) and wheat (W7) were found to be positive for aflatoxin production and hence its internal transcribed spacer (ITS) region sequencing were done for its identification. All fungal morphotypes were determined based on their 18S rDNA-ITS region sequence (Arifah et al. 2023; Sukmawati et al. 2018). The sequence result of all the five positive isolates compared with the nucleotide base sequence stored in the NCBI genotype by using the BLAST program to identify closely related species of S4, C3, R10, Ra2 and W7 isolates. The sequence alignment showed that S4 isolate has the highest sequence homology with A. aflatoxiformans DTO 228-G2 and A. austwickii DTO 228-F7 with the sequence similarity of 99.83%, for C3 isolate 100%, for R10 isolate 99.82%, for Ra2 isolate 99.65% and for W7 isolate 99.63%. The retrieved sequences of PCR product were deposited with accession numbers in the gene bank shown in Table 3. Based on phylogenetic tree analysis (Fig. 4), isolates of S4, C3, R10, Ra2 and W7 are shown that they belong to the A. section Flavi.

Table 3 Main macro - and microscopic features of Aspergillus section Flavi isolates after 7 days of culture on CYA at room temperature and Nucleotide accession numbers for ITS sequences

Fig. 4

A The optimal tree with the sum of branch length = 0.31896953 is shown. The analysis involved 22 nucleotide sequences. All positions containing gaps and missing data were eliminated. There were a total of 353 positions in the final dataset. B The optimal tree with the sum of branch length = 0.31893937is shown. The analysis involved 22 nucleotide sequences. All positions containing gaps and missing data were eliminated. There were a total of 363 positions in the final dataset. C The optimal tree with the sum of branch length = 0.32050524 is shown. The analysis involved 22 nucleotide sequences. All positions containing gaps and missing data were eliminated. There were a total of 354 positions in the final dataset. D The optimal tree with the sum of branch length =  = 0.37832727is shown. The analysis involved 22 nucleotide sequences. All positions containing gaps and missing data were eliminated. There were a total of 349 positions in the final dataset. E The optimal tree with the sum of branch length = 0.38177994 is shown. The analysis involved 22 nucleotide sequences. All positions containing gaps and missing data were eliminated. There were a total of 361 positions in the final dataset

Recommendations

The government-sponsored Anganwadi (Rural) program, which is present in every village in India, could be the problem solving by involving the ASHA (Accredited Social Health Activist) workers in creating awareness of the mycoflora contamination and the health risk associated with it along with community screening for mycotoxin exposure risk assessment. This was also suggested previously by Wenndt et al. 2020 and we strongly recommend this.

Conclusion

In the present investigation, the occurrence of mycotoxigenic fungi obtained from the grain samples from farmers’ storage sites in the Madhubani and Sitamarhi districts of Bihar, India were studied. A total of n = 119 fungal isolates from 5 distinct genera were isolated in PDA and CYA. The Aspergillus spp. were the dominant with 95 isolates out of 119 isolates with occurrence of Aspergillus section Flavi (58.95%), Aspergillus section Nigri (35.79%), Aspergillus section Fumigati (3.16%), Aspergillus section Terrei (1.05%) and Aspergillus section Circumdati (1.05%). Among all the isolates, only 8.92% were aflatoxin producers by HPLC-FLD and TLC. The isolates of Aspergillus section Flavi were found to be aflatoxins producers specially AFB₁ and AFB₂. AFG₁ and AFG₂ were not present in any of these isolates. In summary, to our knowledge, this is the initial report concerning the detection of aflatoxin producing A. section Flavi from grain samples of flood prone districts of Bihar, India. It suggests time-to-time monitoring is required for having track record about the presence of toxigenic mycoflora in food grain samples in these flood prone areas. As conventional agricultural practices prevented the essential precautions from being taken during the processing of food grain samples, guidelines for toxigenic fungi must be established. Moreover, the state Government should ensure the distribution of mycotoxin free grains in the market so that the health related issued involved can be prevented.