The human population in Sub-Saharan Africa is increasing at the rate of 2% per year (https://data.worldbank.org/region/sub-saharan-africa) and estimated at 1,061 billion in 2017 (https://data.worldbank.org/region/sub-saharan-africa). This exponential population growth in addition to erratic rainfall, climate variability (drought and flood) and agricultural pests has contributed to food shortages. This food insecurity may lead to population migration and further poverty in the Sahel region.

 

Adoption of genetically modified crops with improved grain yield and drought resistance is a mean to alleviate food shortage. Genetically modified organism (GMO) is defined as an organism in which the genetic material has been altered in a way that does not occur by mating and/or natural recombination (Plan and Van den Eede, 2010). Presently, genetically modified (GM) crops are a main agricultural product worldwide with GM crops having a global value of UDS$15.8 billion in 2016 (Briefs, 2017). In order to preserve the biodiversity, several countries have adopted the Cartagena protocol on biosafety (a legally binding global framework), that ensures the safe transport, handling and use of living modified organisms (LMO) created through gene engineering. The Cartagena protocol assists member country authorities in building the capacity to transfer technology and knowledge to prevent illegal shipment and accidental releases of GM products across member country boundaries. The Malian government has ratified the Cartagena protocol and has taken a set of regulations for importation, production, distribution and use of genetically living organisms (Law N⁰ 08-042, December 2008). In addition, the Regional Biosafety Program of the Economic Community of West African States (ECOWAS) and the West African Economic Monetary Union (WAEMU) was implemented and has provided to each country member a platform to identify GMO crops and food product within its territorial region.

 

GM crops can be detected using several techniques (Cottenet et al., 2019; Dobnik et al., 2018; Fraiture et al., 2018).   DNA-based   approaches   are   more  popular  in detecting and quantifying GM crops than protein-based methods (Lipton et al., 2000), and real-time quantitative polymerase chain reaction (qPCR) is the standard in GMO analytics. The objective of the present study was to evaluate 15 maize varieties using PCR based strategies to detect GM varieties in germplasm from Mali.

 

centrifuged at 5,000 x g for 1 min. The column was washed 3 times using 450 µl of washing solution at 5,000 x g for 1 minute. To remove residual washing buffer solution, the column was centrifuged for 10 s at 13,000 x g. Lastly, 200 µl of a warm elution buffer (70°C) was added to the column (placed in the sterile tube), incubated at 25°C for 5 min, and centrifugation at 5,000 x g for 5 min. Purified DNA was stored at -20°C prior to the PCR amplification.

 

Markers used for amplification

 

Three screening elements (Table 2) from the Foodproof®GMO screening 1 Lyokit (Biotecon Diagnostics, Potsdam, Germany) were used for qPCR amplification which were the 35s promoter of the Cauliflower mosaic virus (CaMV), the nopaline synthase (NOS terminator) from Agrobacterium tumefaciens and the 35s promoter from the Figwort mosaic virus (FMV). In addition, event markers such as bar, 35S-Pat, CTP2 were used for PCR amplification. The plant universal marker provided with the Kit Biotecon was used to amplify plant DNA.

 

 

Quantitative PCR (qPCR) to estimate the cycle threshold (Ct) value

 

The Foodproof®GMO screening 1 Lyokit was used to perform the qPCR. The DNA samples were diluted to 25 ng/µl and a 25 µl sample was added to an individual well containing the lyophilized PCR reagents. Negative (25 µl of sterile H₂O) and positive controls (25 µl of Foodproof®GMO screening 1 control template) were included. Two steps qPCR were performed using StepOne Real Time PCR system (Applied Biosystems, Foster City CA, USA) with initial incubation for 1 cycle at 37°C for 4 min and denaturation process for 95°C for 10 min, followed by amplification step consisting of 50 cycles, a denaturation at 95°C for 15 s followed by annealing at 60°C for 60 s.

 

Gel electrophoresis

 

After amplification, 12 µl of each qPCR product was electrophoresed on a 2% agarose gel using 0.5X TBE running buffered (Euromedex, France). DNA fragments were stained with 0.3 mg/ml of ethidium bromide (Sigma, St-Louis, Mo, USA). Fragments were electrophoresed at 120 volts for 2 h and then photographed by UV transillumination with a KODAK EDAS 290 camera (Kodak, Rochester, NY, USA). The molecular weight of the products was estimated with DNA molecular weight marker 100 bps DNA ladder (Quick load, New England Biolabs, Ipswich, MA).

 

Ct estimations

 

The cycle threshold (Ct), the fractional cycle number at which the well’s accumulating  fluorescence  crosses  a  set  threshold  that  is several standard deviations above base fluorescence, was determined. Any amplification curve below the threshold line between the first and the fifth cycles was considered as negative for a specific screening element marker.

 

The 14 maize varieties were negative for P35s CaMV and T-NOs markers (Table 4). In contrast, the unknown dark color seeded maize was positive with 94 bp PCR product for P35s CaMV (forward) and T-NOs (reverse) markers. In addition, the use of event markers did not produce PCR fragments (Table 3).

 

 

The presence of PCR fragment was consistent with the Ct values obtained during qPCR. The Ct values for the 14 varieties were above 50 (Table 3). In contrast, Ct values for the unknown variety were 23 for P-35s-CaMV and 28 for the T-NOS. This confirms the dark seeded maize variety was genetically modified maize with the genome containing the 35s promoter of the Cauliflower mosaic virus (CaMV) and the nopaline synthase (NOS terminator) from Agrobacterium tumefaciens. However, the 35s promoter sequence from the Figwort mosaic virus (FMV) was not amplified for the 15 varieties. In South Africa, 10% of varieties contained genes for insect resistance and 15% were associated with herbicide tolerant events (Iversen et al., 2014). These data along with the identification of a transgenic dark seeded maize variety from Mali would suggest additional screening of maize germplasm from Mali should be conducted.

 

The study demonstrates the ability in detecting the GM maize using screening elements and the usefulness of our laboratory in training and reinforcing regional concern about GMO circulation. The presence of molecular platform (qPCR and Sanger sequencing techniques) and immunological technique such as Elisa within in our laboratory constitutes a valuable asset. The next step will include reference material for GMO detection and quantification in food. Taken together, the country will be in a better position to screen all entering maize seeds and to fulfill the regulatory requirements such as the Cartagena Protocol.

The authors have not declared any conflict of interests.

The authors thank the Focal Point of the WAEMU Regional Biosafety  program  (Saïdou  Kina  and  Zourata Ouedrago Lompo)through  funding from GEF project (ID 2911), the European Commission Joint Research Center (Towards Global Harmonisation of GMO analysis by Creating    and    Supporting    Regional     Networks     of Excellence” Project) through Dr Maddalena Quercy, the Convention for Biological Diversity (CBD) for support to IT and HD, the French IRD JEAI CoANA Dr. Valerie Verdier, Dr. Christiane Kouatchoua and also thank Dr Doumbia Lassina and Dr Diarra Youssouf for the review of the manuscript.