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Amit Meshulam Bioinformatics Seminar Technion, Spring 06

Combinatorial Synthesis of Genetic Networks Calin C. Guet, Michael B. Elowitz, Weihong Hsing, Stanislas Leibler. Amit Meshulam Bioinformatics Seminar Technion, Spring 06. Combinatorial Synthesis of Genetic Networks. Phenomena description and biological background Biological system description

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Amit Meshulam Bioinformatics Seminar Technion, Spring 06

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  1. Combinatorial Synthesis ofGenetic NetworksCalin C. Guet, Michael B. Elowitz, Weihong Hsing,Stanislas Leibler Amit Meshulam Bioinformatics SeminarTechnion, Spring 06

  2. Combinatorial Synthesis ofGenetic Networks • Phenomena description and biological background • Biological system description • Construction of combinatorial libraries and genetic engineering techniques • Description and Analysis of experiments results • Summary • Remarks

  3. Combinatorial Synthesis ofGenetic Networks • Phenomena description and biological background • Biological system description • Construction of combinatorial libraries and genetic engineering techniques • Description and Analysis of experiments results • Summary • Remarks

  4. Phenomena description and biological background • Complex pathways occur in the cell, including interactions between biological element • Biological elements such as: proteins, chemical molecules, DNA fragments etc.. • The goal is to predict the cell behavior, in various growth conditions, under the activation of signals etc..

  5. Phenomena description and biological background (cont) • Live cells react to inputs from the environment. • The reactions are based on interactions between big number of molecules types organized as complex network cells. • A central problem in biology is determining how genes interact as parts of functional networks. • Biological network analysis – mapping of inter-genes interactions in specific organism.

  6. Phenomena description and biological background (cont)

  7. Regulator Protein Enhancer DNA Promoter Exons Gene expression and regulation mechanism

  8. Example - Inter biological elements interactions (Ecoli)

  9. Example of biological network

  10. Combinatorial Synthesis ofGenetic Networks • Phenomena description and biological background • Biological system description • Construction of combinatorial libraries and genetic engineering techniques • Description and Analysis of experiments results • Summary • Remarks

  11. Biological system description • The genetic structure and cell networks is required in order to analyze the cell behavior. • An in vivo synthetic system that enables the generation of combinatorial libraries of genetic networks was created. • The networks exhibit a large variety of connectivity of E.coli.

  12. Biological system description (cont) • 3 well-characterized prokaryotic transcriptional regulators were chosen: - LacI - TetR - lambda cI • The binding state of LacI and TetR can be changed with the small molecule inducers, isopropyl b-D-thiogalactopyranoside (IPTG) and anhydrotetracycline (aTc), respectively: - IPTG – The inducer that binds to the LacI protein and prevent the binding to the target DNA. - aTc – The inducer that binds to the TetR protein and prevent the binding to the target DNA.

  13. Biological system description (cont) • 5 promoters regulated by these proteins, covering a broad range of regulatory characteristics such as repression, activation, leakiness, and strength were chosen: - 2 promoters repressed by LacI - 1 repressed by TetR - 1 regulated by lambda cI: 1 positively and 1 negatively.

  14. Pi lacI Pj Lambda cI Pk tetR Biological system description (cont) • Any network in the library will form the following configuration: • Pi, Pj and Pk represent one of the 5 promoters selected for the system. • Each promoter has 5 options resulting in 5*5*5 = 125 optional networks

  15. Pi lacI Pj Lambda cI Pk tetR PcI GFP Biological system description (cont) • The encoding gene to the florescent protein (GFP), was added downstream to the promoter repressed by lambda cl. • The fragment is transformed into two different host strains of E. coli

  16. Biological system description (cont) • Network input: - X and Y Booleans: X – true if IPTG inducer was added, false otherwise. Y – true if aTc inducer was added, false otherwise. • Network output: various levels of florescent signal reflecting the expression level of the protein GFP.

  17. GFP protein as biological indicator • GFP - Green Fluorescent Protein. • The gene transformation into cells organisms

  18. Combinatorial Synthesis ofGenetic Networks • Phenomena description and biological background • Biological system description • Construction of combinatorial libraries and genetic engineering techniques • Description and Analysis of experiments results • Summary • Remarks

  19. Combinatory library construction • Using modular genetic cloning strategy generating combinatorial libraries of logical circuits. • Construction of the library proceeded in two steps Step 1 – Creating DNA fragments. Every DNA fragment is constructed from the fusion between one of the 5 promoters with one of the 3 proteins. 3*5 = 15 different fragments. Step 2 – Fusion of all fragments in the right order, insertion of the fragment into the plasmid and transformation of the plasmid into the hosting cell.

  20. Combinatory library construction:Step 1 - Amplification of the promoters and the genes by PCR technique. - Every gene has a transcription terminator. - At the end of every promoter and the beginning of every gene an identical RBS was added by PCR. (RBS = Ribosome Binding Site) - In order to control the number and the insertion direction of the fragments to the plasmid a DNA fragment was inserted. - This fragment include restriction site of the restriction enzyme (BglI) and was inserted upstream to the promoter and downstream to the gene. - Sticky ends are created once cutting the restriction enzyme. - After ligation the sticky ends fused to each other to create the required fragment.

  21. Step 1: Network component constructions(Fragment containing gene & promoter)

  22. techniquePCR

  23. 5’ 3’ 3’ 5’ 5’ 3’ 3’ 5’ techniquePCR

  24. Pi lacI Pj Lambda cI Pk tetR PcI GFP Step 2: In-order fragment fusion Step 1 products are cloned into the plasmid according to the required order.

  25. TAACGGTAGCCNNNNNGGCAGCGTTA ATTGCCATCGGNNNNNCCGTCGCAAT TAACGGTAGCCNNNN NGGCAGCGTTA ATTGCCATCGGN NNNNCCGTCGCAAT Step 2: In-order fragment fusion • How to ensure the in-order fragments fusion? • Restriction site of the Bgl I (pre-restriction): • Post-restriction:

  26. Y X Pb Gene B Pa Gene A Pa Gene A Pb Gene B TAACGGTAGCCNNNN NGGCAGCGTT ATTGCCAT CGGN NNNNCCGTCGCAAT Step 2: In-order fragment fusion • Y represents the restriction site fragment fused downstream the gene of fragment A. • X represents the restriction site fragment fused upstream the gene of fragment B.

  27. Step 2: In-order fragment fusion • The characterization of the fusion sites: - YlacI complimentary to Xcl - Ycl complimentary to XtetR etc.. • Shuffling of all fragments.

  28. Insertion the resulting fragment into a plasmid • Plasmid restriction by restriction enzyme in the right position. • Fragment insertion into the plasmid:

  29. Transformation into hosting cell • The plasmids transformed into 2 hosting E.coli strains (3-4 copies) - lacI+ (wt) - lacI- • Every clone was grown in different conditions:

  30. Combinatorial Synthesis ofGenetic Networks • Phenomena description and biological background • Biological system description • Construction of combinatorial libraries and genetic engineering techniques • Description and Analysis of experiments results • Summary • Remarks

  31. Introducing & analysis of specific binary logical circuit • To the 2 clones lacI+ and lacI- the following network was inserted:

  32. Introducing & analysis of specific binary logical circuit • 2 of the strains were raised on agar plat in those conditions. • The following fluorescents outputs were received:

  33. Scenario demonstration Input: IPTG – aTc +

  34. tetR aTc tetR Origin tetR Origin aTc aTc Pt lacI Pl Lambda cI Pt tetR PcI GFP

  35. tetR aTc tetR Origin tetR Origin aTc aTc Pt lacI Pl Lambda cI Pt tetR PcI GFP

  36. tetR aTc tetR Origin aTc Pt Pt lacI lacI Pl Pl Lambda cI Lambda cI Pt Pt tetR tetR PcI PcI GFP GFP lacI

  37. tetR aTc tetR Origin tetR Origin aTc aTc Pt Pt lacI lacI Pl Pl Lambda cI Lambda cI Pt Pt tetR tetR PcI PcI GFP GFP lacI

  38. Pt lacI Pl Lambda cI Pt tetR PcI GFP cI GFP

  39. Graphical representation

  40. tetR aTc lacI tetR Origin GFP lacI Origin cI

  41. aTc lacI GFP lacI Origin cI

  42. aTc lacI GFP lacI Origin cI

  43. aTc lacI GFP lacI Origin

  44. aTc lacI GFP lacI Origin

  45. Scenario demonstration Input: IPTG – aTc –

  46. Pt lacI Pl Lambda cI Pt tetR PcI GFP tetR tetR Origin

  47. Pt lacI Pl Lambda cI Pt tetR PcI GFP tetR lacI- lacI+ tetR Origin

  48. Pt lacI Pl Lambda cI Pt tetR PcI GFP tetR lacI- lacI+ Pl Pl Lambda cI Lambda cI Pt Pt tetR tetR PcI PcI GFP GFP From the origin gene lacI lacI Origin tetR Origin

  49. Pt lacI Pl Lambda cI Pt tetR PcI GFP tetR lacI- lacI+ Pl Pl Lambda cI Lambda cI Pt Pt tetR tetR PcI PcI GFP GFP From the origin gene lacI lacI Origin tetR Origin

  50. Pl Pl Lambda cI Lambda cI Pt Pt tetR tetR PcI PcI GFP GFP cI GFP cI

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