Predicting the allergenicity of legume proteins using a PBMC gene expression assay.

BACKGROUND: Food proteins differ in their allergenic potential. Currently, there is no predictive and validated bio-assay to evaluate the allergenicity of novel food proteins. The objective of this study was to investigate the potential of a human peripheral blood mononuclear cell (PBMC) gene expression assay to identify biomarkers to predict the allergenicity of legume proteins. RESULTS: PBMCs from healthy donors were exposed to weakly and strongly allergenic legume proteins (2S albumins, and 7S and 11S globulins from white bean, soybean, peanut, pea and lupine) in three experiments. Possible biomarkers for allergenicity were investigated by exposing PBMCs to a protein pair of weakly (white bean) and strongly allergenic (soybean) 7S globulins in a pilot experiment. Gene expression was measured by RNA-sequencing and differentially expressed genes were selected as biomarkers. 153 genes were identified as having significantly different expression levels to the 7S globulin of white bean compared to soybean. Inclusion of multiple protein pairs from 2S albumins (lupine and peanut) and 7S globulins (white bean and soybean) in a larger study, led to the selection of CCL2, CCL7, and RASD2 as biomarkers to distinguish weakly from strongly allergenic proteins. The relevance of these three biomarkers was confirmed by qPCR when PBMCs were exposed to a larger panel of weakly and strongly allergenic legume proteins (2S albumins, and 7S and 11S globulins from white bean, soybean, peanut, pea and lupine). CONCLUSIONS: The PBMC gene expression assay can potentially distinguish weakly from strongly allergenic legume proteins within a protein family, though it will be challenging to develop a generic method for all protein families from plant and animal sources. Graded responses within a protein family might be of more value in allergenicity prediction instead of a yes or no classification.

Allergenicity prediction of novel and modified proteins: Not a mission impossible! Development of a Random Forest allergenicity prediction model.

Alternative and sustainable protein sources (e.g., algae, duckweed, insects) are required to produce (future) foods. However, introduction of new food sources to the market requires a thorough risk assessment of nutritional, microbial and toxicological risks and potential allergic responses. Yet, the risk assessment of allergenic potential of novel proteins is challenging. Currently, guidance for genetically modified proteins relies on a weight-of-evidence approach. Current Codex (2009) and EFSA (2010; 2017) guidance indicates that sequence identity to known allergens is acceptable for predicting the cross-reactive potential of novel proteins and resistance to pepsin digestion and glycosylation status is used for evaluating de novo allergenicity potential. Other physicochemical and biochemical protein properties, however, are not used in the current weight-of-evidence approach. In this study, we have used the Random Forest algorithm for developing an in silico model that yields a prediction of the allergenic potential of a protein based on its physicochemical and biochemical properties. The final model contains twenty-nine variables, which were all calculated using the protein sequence by means of the ProtParam software and the PSIPred Protein Sequence Analysis program. Proteins were assigned as allergenic when present in the COMPARE database. Results show a robust model performance with a sensitivity, specificity and accuracy each greater than ≥85%. As the model only requires the protein sequence for calculations, it can be easily incorporated into the existing risk assessment approach. In conclusion, the model developed in this study improves the predictability of the allergenicity of new or modified food proteins, as demonstrated for insect proteins.

Rational design of a multiepitope vaccine encoding T-lymphocyte epitopes for treatment of chronic hepatitis B virus infections.

Protein sequences from multiple hepatitis B virus (HBV) isolates were analyzed for the presence of amino acid motifs characteristic of cytotoxic T-lymphocyte (CTL) and helper T-lymphocyte (HTL) epitopes with the goal of identifying conserved epitopes suitable for use in a therapeutic vaccine. Specifically, sequences bearing HLA-A1, -A2, -A3, -A24, -B7, and -DR supertype binding motifs were identified, synthesized as peptides, and tested for binding to soluble HLA. The immunogenicity of peptides that bound with moderate to high affinity subsequently was assessed using HLA transgenic mice (CTL) and HLA cross-reacting H-2(bxd) (BALB/c x C57BL/6J) mice (HTL). Through this process, 30 CTL and 16 HTL epitopes were selected as a set that would be the most useful for vaccine design, based on epitope conservation among HBV sequences and HLA-based predicted population coverage in diverse ethnic groups. A plasmid DNA-based vaccine encoding the epitopes as a single gene product, with each epitope separated by spacer residues to enhance appropriate epitope processing, was designed. Immunogenicity testing in mice demonstrated the induction of multiple CTL and HTL responses. Furthermore, as a complementary approach, mass spectrometry allowed the identification of correctly processed and major histocompatibility complex-presented epitopes from human cells transfected with the DNA plasmid. A heterologous prime-boost immunization with the plasmid DNA and a recombinant MVA gave further enhancement of the immune responses. Thus, a multiepitope therapeutic vaccine candidate capable of stimulating those cellular immune responses thought to be essential for controlling and clearing HBV infection was successfully designed and evaluated in vitro and in HLA transgenic mice.

Construction and optimization of a CC49-based scFv-beta-lactamase fusion protein for ADEPT.

CC49 is a clinically validated antibody with specificity for TAG-72, a carbohydrate epitope that is over-expressed and exposed on a large fraction of solid malignancies. We constructed a single chain fragment (scFv) based on CC49 and fused it to beta-lactamase. The first generation fusion protein, TAB2.4, was expressed at low levels in Escherichia coli and significant degradation was observed during production. We optimized the scFv domain of TAB2.4 by Combinatorial Consensus Mutagenesis (CCM). An improved variant TAB2.5 was identified that resulted in an almost 4-fold improved expression and 2.5 degrees higher thermostability relative to its parent molecule. Soluble TAB2.5 can be manufactured in low-density E.coli cultures at 120 mg/l. Our studies suggest that CCM is a rapid and efficient method to generate antibody fragments with improved stability and expression. The fusion protein TAB2.5 can be used for antibody directed enzyme prodrug therapy (ADEPT).

Identification and Characterization of a New Alkaline Thermolysin-Like Protease, BtsTLP1, from Bacillus thuringiensis Serovar Sichuansis Strain MC28.

Thermolysin and its homologs are a group of metalloproteases that have been widely used in both therapeutic and biotechnological applications. We here report the identification and characterization of a novel thermolysin-like protease, BtsTLP1, from insect pathogen Bacillus thuringiensis serovar Sichuansis strain MC28. BtsTLP1 is extracellularly produced in Bacillus subtilis, and the active protein was purified via successive chromatographic steps. The mature form of BtsTLP1 has a molecule mass of 35.6 kDa as determined by mass spectrometry analyses. The biochemical characterization indicates that BtsTLP1 has an apparent Km value of 1.57 mg/ml for azocasein and is active between 20°C and 80°C. Unlike other reported neutral gram-positive thermolysin homologs with optimal pH around 7, BtsTLP1 exhibits an alkaline pH optimum around 10. The activity of BtsTLP1 is strongly inhibited by EDTA and a group of specific divalent ions, with Zn(2+) and Cu(2+) showing particular effects in promoting the enzyme autolysis. Furthermore, our data also indicate that BtsTLP1 has potential in cleaning applications.

Characterization of a CC49-based single-chain fragment-beta-lactamase fusion protein for antibody-directed enzyme prodrug therapy (ADEPT).

CC49 is a clinically validated antibody with specificity for TAG-72, a carbohydrate epitope that is overexpressed and exposed on the cell surface in a large fraction of solid malignancies. We constructed a single-chain fragment (scFv) based on CC49 and fused it to beta-lactamase (BLA). Following optimization of the scFv domain by combinatorial consensus mutagenesis (CCM) for increased expression and stability, we characterized the protein variant for binding, in vivo pharmacokinetics (PK), and antitumor efficacy. The fusion protein TAB2.5 possessed a similar binding specificity relative to the parent antibody CC49. TAB2.5 also showed prolonged retention (T(1/2) = 36.9 h) in tumor-bearing mice with tumor/plasma ratios of up to 1000. Preliminary evaluation of TAB2.5, in combination with a novel prodrug, GC-Mel, resulted in significant efficacy in a colorectal xenograft tumor model and supports the utility of the protein as an agent for tumor-selective prodrug activation.