1 / 32

Synthetic Systems for Teaching and Learning

Synthetic Systems for Teaching and Learning. Winston Retreat June 25th, 2007 Natalie Kuldell. Unreal Irrational. Undergraduate teaching with SAGA deletions. Regulating RNA degradation in yeast mitochondria. Why hack the yeast mitochondria?.

glendakirk
Download Presentation

Synthetic Systems for Teaching and Learning

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. Synthetic Systems for Teaching and Learning Winston Retreat June 25th, 2007 Natalie Kuldell

  2. Unreal Irrational Undergraduate teaching with SAGA deletions Regulating RNA degradation in yeast mitochondria

  3. Why hack the yeast mitochondria? “ (we often) imagine the mitochondrion as a lonely participant in the cell, working tirelessly to produce the energy required for life.” McBride et. al. Curr Biol 2006 • Other mt functions • coordinates with nuclear gene expression (disease/aging) • spatially isolated enzymatic reaction center • viability on nonfermentable carbon sources http://grocs.dmc.dc.umich.edu/gallery/organelle/Interface2

  4. Hacking yeast mitochondria ? = Wish list (incomplete) Orthogonal draw from different pools of reagents Decoupled run system independent of growth rate Generic run same system in different chassis Tunable vary operation at will

  5. Current contents: in mt from mt mt promoters TATAAGTA (+1) mt RNAP RPO41 = catalytic subunit MTF1 = specificity factor nuclear-encoded • mt genome includes • 8 protein coding genes • 7 oxphos, 1 riboprot • 2 rRNAs • 24 tRNAs

  6. Targeted mtRNA degradation Part 1: mRNA target e.g. mtGFP Part 2: guide RNA Part 3: dsRNase

  7. Snapshot of wild type role for Rnt1 • Localized to the nucleus even when overexpressed Catala et al, MCB (2004) 15:3015

  8. Snapshot of wild type role for Rnt1 • Localized to the nucleus even when overexpressed • Processes some noncoding RNAs (U2 snRNA, U3 snoRNPs) Henras et al.RNA (2004) 10: 1572

  9. Snapshot of wild type role for Rnt1 • Localized to the nucleus even when overexpressed • Processes some noncoding RNAs (U2 snRNA, U3 snoRNPs) • Processes some coding RNA, e.g. Mig2 Ge et al, Current Biology (2005) 15:140

  10. Snapshot of wild type role for Rnt1 • Localized to the nucleus even when overexpressed • Processes some noncoding RNAs (U2 snRNA, U3 snoRNPs) • Processes some coding RNA, e.g. Mig2 • Needed for normal cell cycle progression Catala et al, MCB (2004) 15:3015

  11. Expression vector for mitochondrial Rnt1 CYC1 CMV tTA modified RNT1 2x tetO pRS41n

  12. Expression vector for mitochondrial Rnt1 signal sequence + epitope tag ∆NLS (11 aa) RNT1 pRS41n ∆NLS in Henras et al RNA (2004) 10:1572

  13. Initial experiments with mtRnt1 Expression? by Western with epitope Ab Phenotypes? Respiration, growth, existing markers Overall? Microarray wt vs mtRnt

  14. Targeted mtRNA degradation Part 1: mRNA target e.g. mtGFP Part 2: guide RNA Part 3: dsRNase

  15. Protein import into mitochondria Pfanner and Geissler Nat Rev (2001) 2:339

  16. RNA import into mitochondria “poorly understood”/”mechanisms appear to differ”

  17. RNA import into mitochondria “poorly understood”/”mechanisms appear to differ” ~all mt tRNAs encoded on nuclear genome RNA receptor (“RIC”) in mt membrane Entelis et al Gene Engineering: Principles and Methods (2001) 24:191

  18. RNA import into mitochondria “poorly understood”/”mechanisms appear to differ” no mt tRNAs encoded by mt RIC + ytRNA--> repair mt defect in human cell line Mahata et al Science (2006) 314:471

  19. RNA import into mitochondria “poorly understood”/”mechanisms appear to differ” all but one tRNA encoded on mt genome import depends on protein import

  20. Specialized import into mitochondria Piggyback on tRNA import protein:RNA conjugate Bind to mtRNA binding protein

  21. Unreal Irrational Undergraduate teaching with SAGA deletions Regulating RNA degradation in yeast mitochondria

  22. RT Expression Engineering Experiment Day 1 Day 2 Day 3 Day 6 Day 5 Day 4

  23. FY2068 A ura3-52 his3∆200 leu2∆1 lys2-128d Subunit Deleted?

  24. FY2068 A ura3-52 his3∆200 leu2∆1 lys2-128d Subunit Deleted? NY389 aura3-52 his4-917d leu3∆1 trp1-63 spt8∆320::LEU2

  25. Day 3

  26. wt/sus1∆ Andrew Ji and Kate Broadbent, W/F Team Blue, 20.109 Spring ‘07 Follow-up with microarray wt/sgf73∆ teacher

  27. Follow-up with spot tests

  28. Follow-up with spot tests Hi Natalie, I've attached my rewrite. Thanks! See you tomorrow, Andrew P.S. This was one of the most time-consuming assignments I've ever had to do, yet it was easily the most fun and rewarding thing I've ever accomplished for any school-related project.

  29. Sus1’s role in SAGA-dependent gene motility, transcription, and expression under different cellular conditions Andrew Ji and Kate Broadbent May 10, 2007

  30. From: Neal Lerner <nlerner@MIT.EDU> Subject: Re: 109 writing assignment Date: Thu, 11 Jan 2007 11:07:34 -0500 To: natalie kuldell <nkuldell@mit.edu> Natalie, as I prepare to give a writing-across-the-curriculum talk next week, I came across this quote from John Bean: WAC is about creating opportunities for students to have an "authentic desire to converse with interested readers about real ideas." Now, in most school settings that's pretty darn hard to achieve, but I think when students have the chance to write/talk about lab work and ideas they find interesting (as in 20.109), we have a shot at it. See you on the 22nd. Neal

  31. the end

  32. Current contents: in mt from nucleus • nuclear genome sends • ~750 proteins to mt • 87 of these are putative proteins of no known function

More Related