Protein familiarity is a fundamental but rarely operationalized concept in the safety assessment of genetically modified crops: example of phosphomannose isomerase (PMI).

Fundamental to the safety assessment of genetically modified (GM) crops is the concept of negligible risk for newly expressed proteins for which there is a history of safe use. Although this simple concept has been stated in international and regional guidance for assessing the risk of newly expressed proteins in GM crops, its full implementation by regulatory authorities has been lacking. As a result, safety studies are often repeated at a significant expenditure of resources by developers, study results are repeatedly reviewed by regulators, and animals are sacrificed needlessly to complete redundant animal toxicity studies. This situation is illustrated using the example of the selectable marker phosphomannose isomerase (PMI) for which familiarity has been established. Reviewed is the history of safe use for PMI and predictable results of newly conducted safety studies including bioinformatic comparisons, resistance to digestion, and acute toxicity that were repeated to gain regulatory reapproval of PMI expressed from constructs in recently developed GM maize. As expected, the results of these newly repeated hazard-identification and characterization studies for PMI indicate negligible risk. PMI expressed in recently developed GM crops provides an opportunity to use the concept of familiarity by regulatory authorities to reduce risk-disproportionate regulation of these new events and lessen the resulting waste of both developer and regulator resources, as well as eliminate unnecessary animal testing. This would also correctly imply that familiar proteins like PMI have negligible risk. Together, such modernization of regulations would benefit society through enabling broader and faster access to needed technologies.

Evidence-based regulations for bioinformatic prediction of allergen cross-reactivity are needed.

The bioinformatic criteria adopted by regulatory agencies to predict the potential cross reactivity between newly expressed proteins in genetically engineered crops and known allergens involves amino acid identity thresholds and was formulated nearly two decades ago based on the opinion of allergy experts. Over the subsequent years, empirical evidence has been developed indicating that better bioinformatic tools based on amino acid similarity are available to detect real allergen cross-reactive risk while substantially reducing false-positive detections. Although the formulation of safety regulations, in the absence of empirical evidence, may require reliance on expert opinion, such expert opinion should not trump empirical evidence once it becomes available. The failure of regulation to maintain consistency with the best available scientific evidence diminishes its value and creates arbitrary barriers to the use of beneficial technologies by society.

Trypsin cleavage sites are highly unlikely to occur in celiac-causing restricted epitopes.

To assess risk, the European Food Safety Authority requires that the amino-acid sequences of newly expressed proteins in genetically engineered (GE) crops should be searched for partial matches with 9-mer restricted epitopes known to cause celiac disease. None of the 26 known celiac-causing 9-mer epitopes contain an in-silico predicted trypsin cleavage site. The probability of this occurring by chance alone is 0.000056. Based on the absence of in-silico predicted trypsin cleavage sites within 9-mer epitopes known to cause celiac disease, it can be concluded with very high confidence that true celiac-causing epitopes are highly unlikely to contain in-silico predicted trypsin cleavage sites and that this criterion can reliably be used to exclude the risk that imperfect 9-mer peptide matches within newly expressed proteins from GE crops cause celiac disease.

Safety assessment of coleopteran active IPD072Aa protein from Psuedomonas chlororaphis.

The ipd072Aa gene from Pseudomonas chlororaphis encodes the IPD072Aa protein which confers protection against certain coleopteran pests when expressed in genetically modified (GM) plants. A weight of evidence approach was used to assess the safety of the IPD072Aa protein. This approach considered the history of safe use of the source organism and bioinformatic comparison of the protein sequence with known allergenic and toxic proteins. The IPD072Aa protein was assessed for resistance to degradation in the presence of simulated gastric fluid containing pepsin as well as heat stability. There was no hazard identified with the IPD072Aa protein. Furthermore, an acute oral toxicity study found no evidence of adverse effects. Collectively, these studies support the human health safety assessment of the IPD072Aa protein.

Comparative assessment of multiple criteria for the in silico prediction of cross-reactivity of proteins to known allergens.

Genetically modified crops are becoming important components of a sustainable food supply and must be brought to market efficiently while also safeguarding the public from cross-reactivity of novel proteins to known allergens. Bioinformatic assessments can help to identify proteins warranting further experimental checks for cross-reactivity. This study is a large-scale in silico evaluation of assessment criteria, including searches for: alignments between a query and an allergen having ≥ 35% identity over a length ≥ 80; any sequence (of some minimum length) found in both a query and an allergen; any alignment between a query and an allergen with an E-value below some threshold. The criteria and an allergen database (AllergenOnline) are used to assess 27,243 Viridiplantae proteins for potential allergenicity. (A protein is classed as a "real allergen" if it exceeds a test-specific level of identity to an AllergenOnline entry; assessment of real allergens in the query set is against a reduced database from which the identifying allergen has been removed.) Each criterion's ability to minimize false positives without increasing false negative levels of current methods is determined. At best, the data show a reduction in false positives to ∼6% (from ∼10% under current methods) without any increase in false negatives.

Assessment of possible allergenicity of hypothetical ORFs in common food crops using current bioinformatic guidelines and its implications for the safety assessment of GM crops.

Before a genetically modified (GM) crop can be commercialized it must pass through a rigorous regulatory process to verify that it is safe for human and animal consumption, and to the environment. One particular area of focus is the potential introduction of a known or cross-reactive allergen not previously present within the crop. The assessment of possible allergenicity uses the guidelines outlined by the Food and Agriculture Organization (FAO) and World Health Organization's (WHO) Codex Alimentarius Commission (Codex) to evaluate all newly expressed proteins. Some regulatory authorities have broadened the scope of the assessment to include all DNA reading frames between stop codons across the insert and spanning the insert/genomic DNA junctions. To investigate the utility of this bioinformatic assessment, all naturally occurring stop-to-stop frames in the non-transgenic genomes of maize, rice, and soybean, as well as the human genome, were compared against the AllergenOnline (www.allergenonline.org) database using the Codex criteria. We discovered thousands of frames that exceeded the Codex defined threshold for potential cross-reactivity suggesting that evaluating hypothetical ORFs (stop-to-stop frames) has questionable value for making decisions on the safety of GM crops.

Systems biology approaches for understanding cellular mechanisms of immunity in lymph nodes during infection.

Adaptive immunity is initiated in secondary lymphoid tissues when naive T cells recognize foreign antigen presented as MHC-bound peptide on the surface of dendritic cells. Only a small fraction of T cells in the naive repertoire will express T cell receptors specific for a given epitope, but antigen recognition triggers T cell activation and proliferation, thus greatly expanding antigen-specific clones. Expanded T cells can serve a helper function for B cell responses or traffic to sites of infection to secrete cytokines or kill infected cells. Over the past decade, two-photon microscopy of lymphoid tissues has shed important light on T cell development, antigen recognition, cell trafficking and effector functions. These data have enabled the development of sophisticated quantitative and computational models that, in turn, have been used to test hypotheses in silico that would otherwise be impossible or difficult to explore experimentally. Here, we review these models and their principal findings and highlight remaining questions where modeling approaches are poised to advance our understanding of complex immunological systems.

A model of the cell-autonomous mammalian circadian clock.

Circadian timekeeping by intracellular molecular clocks is evident widely in prokaryotes and eukaryotes. The clockworks are driven by autoregulatory feedback loops that lead to oscillating levels of components whose maxima are in fixed phase relationships with one another. These phase relationships are the key metric characterizing the operation of the clocks. In this study, we built a mathematical model from the regulatory structure of the intracellular circadian clock in mice and identified its parameters using an iterative evolutionary strategy, with minimum cost achieved through conformance to phase separations seen in cell-autonomous oscillators. The model was evaluated against the experimentally observed cell-autonomous circadian phenotypes of gene knockouts, particularly retention of rhythmicity and changes in expression level of molecular clock components. These tests reveal excellent de novo predictive ability of the model. Furthermore, sensitivity analysis shows that these knockout phenotypes are robust to parameter perturbation.