سيمينار الزيرالينون.ppt. University of Damanhour University

سيمينار الزيرالينون.ppt. University of Damanhour University

1. BIOINFORMATICS STUDIES IN MYCOTOXINS:
ZEARALENONE AS AN EXAMPLE
نونيلاريزلا :نيسكوتوكيملا يف ةيويحلا ةيتامولعملا تاسارد
لاثمك
By
Sarah Ossama Al-Ghazali
Supervised by
Prof. Dr. Mona El-Sayed MabroukProf. Dr. Mohammed Magdy El-Metwally
Prof. Dr. Gamal Mohamed Hamad
,Professor of Food safety, Food technology Department
,Arid Lands Cultivation Research Institute (ALCRI)
City of Scientific Research and Technological Applications (SRTA-City)
Professor of Microbiology.
Vice President for Community Service and Environment Development, Faculty of Science, Damanhour
University

Professor of Microbiology.
Vice Dean for Postgraduate Studies and Research,
Faculty of Science, Damanhour University
Assistant Prof. Dr.Mohamed E. Hasan
Assistant Professor of Bioinformatics, University of Sadat City

2. MYCOTOXINS
•Mycotoxins are natural secondary metabolites of fungi and
estimated to contaminate approximately 25% of the related food
products.
•These toxins are resistant to processing temperatures and tend to
remain in the food chain, as they cannot be completely removed
technically.
•More than 300 mycotoxins produced by about 350 different fungi
species are known.
•The main mycotoxin producers belong to the genera Aspergillus,
Penicillium and Fusarium.

3. FUSARIUM SPECIES
•Fusarium species are a group of soil and phytopathogenic fungi
that belong to the division Ascomycota.
•Fusarium is the main pathogen of grain crops and is likely to
spread from one country to another with increasing global grain
trade.
• Some Fusarium species have been found to produce mycotoxins,
such as fumonisin, trichothecene and zearalenone.

4. ZEARALENONE (ZEA)
•Among the Fusarium mycotoxins, Zearalenone (ZEA) is of special
importance as it is formed at the field prior to harvest and because
their occurrence cannot completely be avoided by plant production
minimizing strategies due to the major impact of weather
conditions.
•Zearalenone is a polyketide mycotoxin produced as a secondary
metabolite by a number of Fusarium species including Fusarium
cerealis and Fusarium graminearum.
• ZEA is soluble in alkaline solutions, ether, benzene, acetonitrile,
methyl chloride, chloroform, acetone and alcohols, but insoluble in
water.

5. ZEARALENONE (ZEA)
•It is heat stable, which makes it difficult to remove and/or
decompose from food.
•ZEA has toxic effects on human and animal health due to its
mutagenicity, teratogenicity, carcinogenicity, nephrotoxicity,
immunotoxicity, and genotoxicity.
• Zearalenone has chronic hyperestrogenic effects on mammals by
causing reproductive problems.

6. BACKGROUND
Bioinformatics is the application of computational techniques to
analyze the information associated with biomolecules on a large-scale.

7. AIMS OF BIOINFORMATICS
To organize data
To develop tools and resources
To analyze the data and interpret the
results

10. ROLE OF BIOINFORMATICS IN
MYCOTOXINS PREDICTION
•Analyzing the genetic sequences of the mycotoxins and comparing
them to known sequences of other mycotoxins.
•This can help to identify the presence of mycotoxins in a sample
and can also be used to predict the potential toxicity of the
mycotoxins.
•Develop models that can predict the production of mycotoxins in
different environmental conditions.
•These models can be used for the management of mycotoxins
contamination.

11. Aim of work

12. AIM OF WORK
The aim of the work is to isolate zearalenone-producing Fusarium
species, molecular identification and DNA sequencing of the toxin
gene, and analysis of data via bioinformatics tools in order to predict
epitope and antigenicity which is necessary for the design of a specific
antibody to be used for rapid detection of different zearalenone-
producing Fusarium species in crops and prediction of degradation
enzymes of the mycotoxin.

13. Proteomic LevelProteomic Level
3-D structure prediction,
Functional and Structural
analysis, Epitopes prediction,
Molecular Docking and ADMET
prediction for the three target
proteins

14. Genomic LevelGenomic Level
Detailed genetic Detailed genetic
characterization and characterization and
comparative genome comparative genome
analysis of the available analysis of the available
Egyptian strainsEgyptian strains
Proteomic LevelProteomic Level
3-D structure prediction,
Functional and Structural
analysis, Epitopes prediction,
Molecular Docking and
prediction of new enzymes for
mycotoxins degradation

15. Samples Collection and
Isolation
Purification
Zearalenone Production
Qualitative and quantitative
estimation of zearalenone
Molecular identification
and DNA sequencing
RESEARCH METHODOLOGY
Microscopic Identification

16. Data analysis via
bioinformatics tools
Epitope prediction
and antigenicity
Detection of orthologous proteins within
different species
Screening the genome for enzymes
that may catalyze zearalenone
Annotation of protein-coding and non-
coding components

17. Assembly Genome
Annotation
Multiple sequence
alignment (MSA)
Phylogenetic
analysis
Single nucleotide
polymorphisms
(SNPs)
WGS retrieval
Genomic Level
NCBI
ENA
Bioinformatics Tools

18. MSA
Gene prediction
Genomic Level
GeneMark.hmm
GeneMarkS-2
EasyGene - 1.2
Clustal
Omega server
Conserved
regions
Bioedit 7.2
Software
Molecular
Evolutionary
Phylogenetic
analysis
MEGA11
Software
Materials and Methods

19. Proteomic Level
Sequence
retrieval of
proteins
Uniprot
Secondary
Structure
SOPMA, Predict
Protein, PSIPRED,
Lambada, CFSSP,
GOR, PROTEUS2,
RaptorX, PSSpred
3D-structure
prediction
I-TASSER,
AlphaFold,
C-Quark,
CEthreader,
Swiss-Model,
Robetta,
LOMETS3,
Phyre2
Model
Refinement
DeepRefiner
ModRefiner
GalxyWeb
trRosetta
ReFOLD
PREFMD
Domain
Separation
CDD
SMART
Model
Evaluation
TM-Score
QMEAN
SAVES
PROCHECK,
Structure
Assessment
Server
Materials and Methods

20. Proteomic Level
B-cell
epitopes
prediction
T-cell
epitopes
prediction
Antigenicity,
Allergenicity,
and Toxicity
SVMTriP
Bepipred
ElliPro
RANKPEP
SYFPEITHI
MHCII-NP
VaxiJen
AllergenFP
ToxinPred
Molecular
Docking
MOE
Software
Autodock
Vina
Functional Motifs
prediction
Structural
Classification
Motif Finder
Scanprosite
Motif Scan
Superfamily,
CATH,
Materials and Methods

21. WHAT HAVE ALREADY DONE
Isolation on tap water
agar medium

22. Purification on PDA

23. Cultivation on starch
glutamate medium for
zearalenone production

24. Filteration and
centrifugation

25. NEXT STEPS
•Qualitative and quantitative estimation of zearalenone via
immunoaffinity chromatography.
•Molecular identification and DNA sequencing of the toxin
gene for the best high-yield isolate.
•Data analysis via bioinformatics tools for epitope prediction
and detection of degradation enzymes.