A new paradigm to search for allergenic proteins in novel foods by integrating proteomics analysis and in silico sequence homology prediction: Focus on spirulina and chlorella microalgae

Talanta ◽  
2021 ◽  
pp. 123188
Author(s):  
Mariachiara Bianco ◽  
Giovanni Ventura ◽  
Cosima Damiana Calvano ◽  
Ilario Losito ◽  
Tommaso R.I. Cataldi
Keyword(s):  
Sequence Homology ◽  
In Silico ◽  
New Paradigm ◽  
Proteomics Analysis ◽  
Novel Foods ◽  
Allergenic Proteins

Allergic Reactions to Food Proteins

2011 ◽  
Vol 81 (23) ◽  
pp. 173-180 ◽  
Author(s):  
Barbara K. Ballmer-Weber
Keyword(s):  
Food Allergies ◽  
Allergic Reactions ◽  
Allergenic Food ◽  
Processed Foods ◽  
Legal Regulations ◽  
Pollen Allergens ◽  
Curative Therapy ◽  
Novel Foods ◽  
Allergenic Proteins ◽  
Adolescents And Adults

Four to eight percent of the population are estimated to be food-allergic. Most food allergies in adolescents and adults are acquired on the basis of cross-reaction to pollen allergens. Theses allergens are ubiquitous in the plant kingdom. Therefore pollen-allergic patients might acquire a multitude of different plant food allergies, and even react to novel foods to which they have never previously been exposed. A curative therapy for food allergy does not yet exist. Food-allergic patients have to rely on strict avoidance diets, The widespread use of industrially processed foods poses a general problem for food-allergic patients. Although the most frequent allergens must be declared openly in the list of ingredients, involuntary contamination with allergy-provoking compounds can occur. The precautionary labelling “may contain” is sometimes applied even if the chance of contamination is very low; on the other hand, foods not declared to contain possible traces of allergenic components may actually contain relevant amounts of allergenic proteins. Switzerland is the only country in Europe with legal regulations on contamination by allergenic food; however, the allowance of 1 g/kg is too high to protect a relevant proportion of food-allergic individuals.

scholarly journals Degenerate PCR primers for detecting putative priming glycosyltransferase genes in Bifidobacterium strains

2015 ◽  
Vol 6 (4) ◽  
pp. 553-562 ◽  
Author(s):  
C. Hidalgo-Cantabrana ◽  
I. Ordoñez ◽  
P. Ruas-Madiedo ◽  
A. Margolles
Keyword(s):  
Dna Sequence ◽  
Sequence Homology ◽  
In Silico ◽  
In Silico Analysis ◽  
Pcr Primers ◽  
Degenerate Pcr ◽  
Negative Results ◽  
Galactosyl Transferase ◽  
Undecaprenyl Phosphate ◽  
Silico Analysis

A new PCR-based method to detect putative exopolysaccharide (EPS) producers from the genus Bifidobacterium was developed based on the detection of two priming glycosyltransferase genes: rfbP (undecaprenyl-phosphate sugar phospho-transferase) and cpsD (galactosyl-transferase). An in silico analysis of the genomes of 28 bifidobacterial strains, belonging to 8 different species, allowed us to detect rfbP, cpsD, or both, in the large majority of the genomes. Based on DNA sequence homology studies, 24 degenerated primers were synthesised in order to select the primer pairs with the broadest capacity to detect the presence of these genes. Four primer pairs targeting internal regions of rfbP and cpsD were selected, allowing the detection of at least one of the two genes in 63 out of 99 bifidobacterial strains analysed, whereas control strains from other genera yielded negative results, suggesting that these genes are widely spread in this genus. The use of these primers is recommended to screen for the potential of Bifidobacterium strains to produce EPS.

scholarly journals In silico identification of off-target pesticidal dsRNA binding in honey bees (Apis mellifera)

2017 ◽  
Author(s):  
Christina L Mogren ◽  
Jonathan Gary Lundgren
Keyword(s):  
Honey Bee ◽  
Sequence Homology ◽  
Honey Bees ◽  
In Silico ◽  
Target Gene ◽  
Target Sequence ◽  
Phenotypic Effect ◽  
Dsrna Binding ◽  
High Sequence Homology ◽  
Genomic Regions

Background. Pesticidal RNAs silencing critical gene function have great potential in pest management, but the benefits of this technology must be weighed against non-target organism risks. Methods. Published studies that developed pesticidal dsRNAs were collated into a database. The target gene sequences for these pesticidal RNAs were determined, and the degree of sequence homology with the honey bee genome were evaluated statistically for each. Results. We identified 101 insecticidal dsRNAs sharing high sequence homology with genomic regions in honey bees. The likelihood of off-target sequence homology increased with the parent dsRNA length. Non-target gene binding was unaffected by taxonomic relatedness of the target insect to honey bees, contrary to previous assertions. Gene groups active during honey bee development had disproportionately high sequence homology with pesticidal RNAs relative to other areas of the genome. Discussion. Although sequence homology does not itself guarantee a significant phenotypic effect in honey bees, in silico screening may help to identify appropriate experimental endpoints within a risk assessment framework for pesticidal RNAi.

scholarly journals Application of in silico and in vitro methods in the development of adverse outcome pathway constructs in wildlife

2014 ◽  
Vol 369 (1656) ◽  
pp. 20130584 ◽  
Author(s):  
Judith C. Madden ◽  
Vera Rogiers ◽  
Mathieu Vinken
Keyword(s):  
In Silico ◽  
Adverse Outcome ◽  
Adverse Outcome Pathway ◽  
New Paradigm ◽  
Mechanisms Of Toxicity ◽  
In Vitro Methods ◽  
Diverse Species ◽  
History Of ◽  
Related Wild Species

There is a long history of using both in silico and in vitro methods to predict adverse effects in humans and environmental species where toxicity data are lacking. Currently, there is a great deal of interest in applying these methods to the development of so-called ‘adverse outcome pathway’ (AOP) constructs. The AOP approach provides a framework for organizing information at the chemical and biological level, allowing evidence from both in silico and in vitro studies to be rationally combined to fill gaps in knowledge concerning toxicological events. Fundamental to this new paradigm is a greater understanding of the mechanisms of toxicity and, in particular, where these mechanisms may be conserved across taxa, such as between model animals and related wild species. This presents an opportunity to make predictions across diverse species, where empirical data are unlikely to become available as is the case for most species of wildlife.

In Silico Prediction of Allergenic Proteins

2014 ◽  
pp. 375-388 ◽  
Author(s):  
Gaurab Sircar ◽  
Bodhisattwa Saha ◽  
Swati Gupta Bhattacharya ◽  
Sudipto Saha
Keyword(s):  
In Silico ◽  
In Silico Prediction ◽  
Allergenic Proteins

Sequence homology of the fly proteins tropomyosin, arginine kinase and myosin light chain with known allergens in invertebrates

2016 ◽  
Vol 2 (2) ◽  
pp. 69-81 ◽  
Author(s):  
M.R. Romero ◽  
A.J. Claydon ◽  
E.C. Fitches ◽  
M.E. Wakefield ◽  
A.J. Charlton
Keyword(s):  
Light Chain ◽  
Sequence Homology ◽  
Myosin Light Chain ◽  
Bioinformatics Analysis ◽  
Arginine Kinase ◽  
Mass Rearing ◽  
Proteomics Data ◽  
Allergenic Proteins ◽  
Food And Feed ◽  
Increasing Demand

Due to the rapid growth of the world’s population and the increasing demand for food, there is an urgent need for alternative, more sustainable sources of protein. Insects have an important role in the diet in some societies and current initiatives are exploring the potential that insects have to offer for the production of food and feed. In this context, the safety implications of both producing and consuming insects are an important aspect to investigate. Here we present a bioinformatics analysis of proteomics data obtained for larvae of four different species of fly to assess the homology of tropomyosin, arginine kinase and myosin light chain with the crustacean orthologous proteins and other known allergenic proteins. The results indicate that the three proteins share homology with known allergens and therefore it is likely that they are also potential allergens. The implications in relation to mass rearing of flies are discussed.

scholarly journals AllerStat: Finding Statistically Significant Allergen-Specific Patterns in Protein Sequences by Machine Learning

2021 ◽  
Author(s):  
Kento Goto ◽  
Norimasa Tamehiro ◽  
Takumi Yoshida ◽  
Hiroyuki Hanada ◽  
Takuto Sakuma ◽  
...  
Keyword(s):  
Machine Learning ◽  
Amino Acid ◽  
Amino Acid Sequences ◽  
Allergic Reactions ◽  
Proof Of Concept ◽  
Specific Amino Acid ◽  
Novel Foods ◽  
Allergenic Proteins ◽  
Data Driven Approach ◽  
Allergenicity Prediction

Cutting-edge technologies such as genome editing and synthetic biology allow us to produce novel foods and functional proteins. However, their toxicity and allergenicity must be accurately evaluated. Allergic reactions are caused by specific amino-acid sequences in proteins (Allergen Specific Patterns, ASPs), of which, many remain undiscovered. In this study, we introduce a data-driven approach and a machine-learning (ML) method to find undiscovered ASPs. The proposed method enables an exhaustive search for amino-acid subsequences whose frequencies are statistically significantly higher in allergenic proteins. As a proof-of-concept (PoC), we created a database containing 21,154 proteins of which the presence or absence of allergic reactions are already known, and the proposed method was applied to the database. The detected ASPs in the PoC study were consistent with known biological findings, and the allergenicity prediction accuracy using the detected ASPs was higher than extant approaches.

In Silico Trials of an Open-Source Android-Based Artificial Pancreas: A New Paradigm to Test Safety and Efficacy of Do-It-Yourself Systems

2020 ◽  
Vol 22 (2) ◽  
pp. 112-120 ◽  
Author(s):  
Chiara Toffanin ◽  
Milos Kozak ◽  
Zdenek Sumnik ◽  
Claudio Cobelli ◽  
Lenka Petruzelkova
Keyword(s):  
Open Source ◽  
In Silico ◽  
Artificial Pancreas ◽  
New Paradigm ◽  
Safety And Efficacy ◽  
Do It Yourself
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