What if the key to safer genetically modified foods and feeds was hiding in plain sight in their DNA and RNA? Discover more in our latest publication in the EFSA Journal, which focuses on the refinement of risk assessment methodologies for Open Reading Frames (ORFs) in genetically modified organisms (GMOs) applications.
At the heart of our collaboration with EFSA, are ORFs, crucial elements in molecular genetics. Consider ORFs to be specific segments within an organism’s genetic code, separated by ‘start’ and ‘stop’ signals, like sentences in a book. These “sentences” in DNA and RNA determine which proteins an organism produces. This is especially important in genetically modified foods and feeds, as the proteins may contain allergens or toxins. Our team worked in collaboration with Prof. Penzo at the University of Bologna and embarked on an exhaustive literature search in the quest of identifying advanced methods for accurately predicting whether these genetic segments in GMOs will express any protein, which is critical for ensuring the safety of our food and feed. We analysed 15,484 unique references to isolate 358 relevant documents.
Our findings revealed that specific genetic criteria such as codon identity, nucleotide composition, and mRNA structure are paramount in determining GMO safety. These components are critical for developing new methods to assess GMO risks. However, our research also revealed several challenges: the current data is not well-structured, there is a wide range of applications, and there is a significant lack of specific information for food and feed. Furthermore, the reliability of the in silico methods used to define, predict, and select ORFs requires additional validation. While we identified some characteristics in the ORF nucleotide sequences that may be useful in assessing their actual expression and potential impact on GMO safety, more research is needed in this area. The currently available prediction tools have strengths and weaknesses, and combining them into a single, unified tool is complicated by their diversity and the nature of the datasets they use, which frequently focus on specific organisms.
In our effort to decipher the genetic blueprint of GMO safety, we are laying the groundwork for innovations that could redefine our relationship with food safety.
“Science is a way of thinking much more than it is a body of knowledge” – Carl Sagan