1 / 23

Candidato : Antonino Ida’

Optimising Biofuel production computational characterisation of gene and related promoter and enhancer involved in fatty acid production in algae. Candidato : Antonino Ida’. Relatore: Prof. Giovanni Perini Supervisione : Prof. Ugur Sezerman.

alaric
Download Presentation

Candidato : Antonino Ida’

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Optimising Biofuel productioncomputational characterisation of gene and related promoter and enhancer involved infatty acid production in algae Candidato : Antonino Ida’ Relatore: Prof. Giovanni Perini Supervisione : Prof. Ugur Sezerman Facolta’ di Scienze Matematiche, Fisiche e Naturali. Corso di Laura Magistrale in Bioinformatica 5 March 2009

  2. Statement of the problem Energetic crisis requires a new renovable source of fuel Biofuel: • Bioethanol (produced by fermenting plant-based raw materials i.e. sugar) • Biogas (produced through anaerobic fermentation of biomass) • Biodiesel (is a methyl ester made from raw materials, such as plant-based oil)

  3. Biodiesel Product from the trans-esterification of triaglycerides whit methanol • Consisting of a long chain of • Alkyl • Methyl • Propyl • Ethyl

  4. Current Biodiesel Production Algae: 2763 dm3 Hemp: 1535 dm3 Chinese tallow: 772 dm3 Palm oil: 780 - 1490 dm3 Coconut: 353 dm3 Rapeseed: 157 dm3 Soy: 76-161 dm3 Peanut: 138 dm3 Sunflower: 126 dm3

  5. Advantages in algae • Synthesis and accumulation large quantities of neutral lipids/oil (20-50% DCW) • Grow at high rate • Thrive in the saline/brackish water/costal seawater • Tolerate marginal land that are not suitable for the conventional agriculture • Utilize growth nutrient such as nitrogen and phosphores from a variety of waste water sources • Sequester carbon dioxide from flue gasses emitted from fossil fuel fired • Produced value added co-product or by-product (e.g. Byopolimers, protein, pigments, animal feed, fertilizer) • Grown in suitable culture vessels (photo-bioreactor) with an annual biomass productivity exceeding that of terrestrial plant by approsimately tenfold

  6. Algae : large number of species The ability to survive over a wide enviromental condition, reflects a wide range of fatty acids product and the ability to modify lipid metabolism efficently in responce to changes in enviromental condition

  7. Biosynthesis of fatty acids • From Acetyl-CoA pool the following reaction takes place: • Carboxylation • Condensation • Reduction • Dehydration • Reduction

  8. Regulation of fatty acids synthesis A major challenge for the future is to discover how the level of expression of genes lipid synthesis is controlled • Acetyl CoA carboxylase (ACCase) is the major candidate to regulate this pathway • Displaced from equilibrium • Light dependent step • Feedback regulation • Compartmentalization

  9. Aim of the project • Finding out the conservative motif on upsteam region between the strains • Comparing the difference in the upsteam region of ACCase according to the amount of fatty acids • Identifing the sequence of ACCase in Scenedesmus Protuberans • Available data: • Experimental caracterization of one gene from Cyclotella Criptica • some draft genomic sequence

  10. Genome sequences NCBI JGI EBI Gene sequences Refinement and classification

  11. Strategy of selection • Autor’s annotation (literature) • Keyword search • BlastN against all draft genome sequence and EST db • PsiBlast against protein sequence db • TblastN against translate nucleotide • Refinement by ClustalW in local

  12. Phylogenetic footprinting A single gene was investigated and non-coding flanking region were compared to their homologs „TFBSs are Island of conservation in a sea of much less conserved DNA” Giulio Pavesi • Exaustive search is prohibitive due to the exponential growth. Thus heuristic methods have been used in: • Bioprospector • GALF_P

  13. Bioprospectora Gibbs sampling algorithm • How Gibbs captures a motif • Probabilistic matrix of a motif with length w • The goal of Gibbs sampling is to maximize the rate between motif base composition and background base distribution.

  14. Initial Motif Motif Without a1' Segment Bioprospector Initialization : Randomly initialize the beginning motif Iterative update: take out one sequence at a time with its segment a1' a2' a3' a4' ak'

  15. Motif Without a1' Segment Bioprospector Iterative Update: Scoring each segment with the current motif Ax=Qx/Px Where: Qx= probability of genereting segment x from the current motif matrix Px= probability of generating segment x from the indipendent background model Sequence 1 Segment (1-6): 1.5 Segment (3-8): 2.7 Segment (6-11): 27.1 Segment (4-9): 9.0 Segment (5-10): 3.2 Segment (2-7): 3 Sequence 1 Sequence 1 Sequence 1 Sequence 1 Sequence 1 a2' a3' a4' ak'

  16. a1" Bioprospector Repeat the process until convergence Score sequence 1 in all possible alignments a2' a3' a4' ak' Motif Without a2' Segment Candidate Motif

  17. GALF_PGenetic Algorithm with local filtering • Motif rappresentation: • Positional led • Consensus led • Where • bi= is the nucleotide i of the motif istance • PWM(bi, i) = is the score of bi at position i in the matrix

  18. GALF_P : feature Genetic operator Local Filtering Operator Shift operator 62 62 387 387 60 60 12 272 71 43 366 366 432 272 mutation 3 Crossing over 753 Single parent Double parents

  19. GALF_P : flow Generate initial population randomly y Local filtering for each new individual N Shift operator Trigger local filtering Evaluate the fitness And perform replace N Converge or reach The maximal generation y Output stagnate y N Genetic Operator

  20. Results Both softwares were run 5 times with the same data set consisting of 1000 bp of the upstream alpha gene region with different motif width (8; 10 ;12; 14; 16), • The shared region were found in 8 and 10 fragment • Some overlap motives were found between -719 and 793 bp upstream encode region of ClamidomonasReinardtii

  21. Experimental procedure • Primer design • PCR • Gradient PCR • Digestion

  22. Conclusions We managed to identify the Alpha fragment in Scenedesmus protuberans by a sequence analysis . The method used to search for hypothetical TFBSs has allowed to identify a cluster of sequences that can be considered “significantly conserved”, hence likely to posses a regulatory function. Future perspectives • Building a descriptor as position specific weight matrices • in Transfact format and searching for conservative region that fits • the descriptor in other species. • The study of the sequence identified shall proceed, in order to capture its flanking regions.

  23. Thanks...

More Related