Value of eight-amino-acid matches in predicting the allergenicity status of proteins: an empirical bioinformatic investigation

The use of biotechnological techniques to introduce novel proteins into food crops (transgenic or GM crops) has motivated investigation into the properties of proteins that favor their potential to elicit allergic reactions. As part of the allergenicity assessment, bioinformatic approaches are used to compare the amino-acid sequence of candidate proteins with sequences in a database of known allergens to predict potential cross reactivity between novel food proteins and proteins to which people have become sensitized. Two criteria commonly used for these queries are searches over 80-amino-acid stretches for >35% identity, and searches for 8-amino-acid contiguous matches. We investigated the added value provided by the 8-amino-acid criterion over that provided by the >35%-identity-over-80-amino-acid criterion, by identifying allergens pairs that only met the former criterion, but not the latter criterion. We found that the allergen-sequence pairs only sharing 8-amino-acid identity, but not >35% identity over 80 amino acids, were unlikely to be cross reactive allergens. Thus, the common search for 8-amino-acid identity between novel proteins and known allergens appears to be of little additional value in assessing the potential allergenicity of novel proteins

Evaluation of the Allergenicity Potential of TcPR-10 Protein from Theobroma cacao

Background: The pathogenesis related protein PR10 (TcPR-10), obtained from the Theobroma cacao-Moniliophthora perniciosa interaction library, presents antifungal activity against M. perniciosa and acts in vitro as a ribonuclease. However, despite its biotechnological potential, the TcPR-10 has the P-loop motif similar to those of some allergenic proteins such as Bet v 1 (Betula verrucosa) and Pru av 1 (Prunus avium). The insertion of mutations in this motif can produce proteins with reduced allergenic power. The objective of the present work was to evaluate the allergenic potential of the wild type and mutant recombinant TcPR-10 using bioinformatics tools and immunological assays. Methodology/Principal Findings: Mutant substitutions (T10P, I30V, H45S) were inserted in the TcPR-10 gene by sitedirected mutagenesis, cloned into pET28a and expressed in Escherichia coli BL21(DE3) cells. Changes in molecular surface caused by the mutant substitutions was evaluated by comparative protein modeling using the three-dimensional structure of the major cherry allergen, Pru av 1 as a template. The immunological assays were carried out in 8-12 week old female BALB/c mice. The mice were sensitized with the proteins (wild type and mutants) via subcutaneous and challenged intranasal for induction of allergic airway inflammation. Conclusions/Significance: We showed that the wild TcPR-10 protein has allergenic potential, whereas the insertion of mutations produced proteins with reduced capacity of IgE production and cellular infiltration in the lungs. On the other hand, in vitro assays show that the TcPR-10 mutants still present antifungal and ribonuclease activity against M. perniciosa RNA. In conclusion, the mutant proteins present less allergenic potential than the wild TcPR-10, without the loss of interesting biotechnological properties. (Résumé d'auteur

Precision oncology for acute myeloid leukemia using a knowledge bank approach

Underpinning the vision of precision medicine is the concept that causative mutations in a patient's cancer drive its biology and, by extension, its clinical features and treatment response. However, considerable between-patient heterogeneity in driver mutations complicates evidence-based personalization of cancer care. Here, by reanalyzing data from 1,540 patients with acute myeloid leukemia (AML), we explore how large knowledge banks of matched genomic\u2013clinical data can support clinical decision-making. Inclusive, multistage statistical models accurately predicted likelihoods of remission, relapse and mortality, which were validated using data from independent patients in The Cancer Genome Atlas. Comparison of long-term survival probabilities under different treatments enables therapeutic decision support, which is available in exploratory form online. Personally tailored management decisions could reduce the number of hematopoietic cell transplants in patients with AML by 20\u201325% while maintaining overall survival rates. Power calculations show that databases require information from thousands of patients for accurate decision support. Knowledge banks facilitate personally tailored therapeutic decisions but require sustainable updating, inclusive cohorts and large sample sizes