Getting organized--from mitochodrial gene expression to public dialog

1. Getting organized--from mitochodrial gene expression to public dialog Winston Retreat 06.18.08

2. "Out of clutter, find simplicity... From discord find harmony... In the middle of difficulty lies opportunity." ---Albert Einstein

3. grey from black from (overexp’d) from Artemisia annua Many genes, many sources Pathway for the production of the anti-malarial drug precursor, amorphadiene Red = toxic intermediates

4. One Approach: Flux BalanceEnzymes have different levels of activity (turnover fluxes) Loss of intermediates to bulk solution Enzymes freely diffuse in the cell Especially problematic for cytotoxic intermediates slide from John Dueber, UCB

5. Synthetic ScaffoldsCo-localize pathway enzymes and reduce intermediate runoff slide from John Dueber, UCB

6. Synthetic ScaffoldsCo-localize pathway enzymes and reduce intermediate runoff since scaffold is modular, can also mulitmerize ENZYME 2 slide from John Dueber, UCB

7. Complementary approach: compartmentalization Build spatially-isolated, biochemically-distinct microenvironment 1. functionalized (poly guanylic acid) 2. coat (PMOXA-PDMS-PMOXA) 3. payload (fluorescent BSA) functionalized polymer vesicle (fPV) “artificial organelle” ~200 nm diameter innocuous in cell culture Ben-Haim et. al. Nano Lett (2008) 8(5): 1368

8. Complementary approach: compartmentalization Build spatially-isolated, biochemically-distinct microenvironment functionalized polymer vesicle (fPV) Ben-Haim et. al. Nano Lett (2008) 8(5): 1368

9. Complementary approach: compartmentalization Build spatially-isolated, biochemically-distinct microenvironment macrophage engulf fPV with fluor-BSA, stable ~48hrs Ben-Haim et. al. Nano Lett (2008) 8(5): 1368

10. Alternative approach to compartmentalization Use existing microenvironment self-assembling, stable, spatially isolated, biochemically-distinct

11. Budweiser beer factory, Czech Republic Alternative approach to compartmentalization Use existing microenvironment self-assembling, stable, spatially isolated, biochemically-distinct, genetically manipulated

12. S. cerevisiae mt: current contents • mt genome includes • 8 protein coding genes • 7 oxphos, 1 riboprot • 2 rRNAs • 24 tRNAs • Can read and write mt DNA, • but what to say?? • Selectable marker • Tunable expression

13. S. cerevisiae mt: selectable marker Existing markers for mtDNA manipulation 2 other mtDNA markers: GFP, BARSTAR Steele et al PNAS (1996) 93:5253

14. S. cerevisiae mt: selectable marker HEM1 549 aa nuclear-encoded protein normally localized to mt matrix Step 1: hem1::KanMX 0 deletion strain Step 2: synthesis of mitochondrially encoded HEM1 Step 3: biolistic transformation

15. mt RNAP RPO41 = catalytic subunit MTF1 = specificity factor mt promoters TAtAaGtN (+1) nuclear-encoded 15X strong if +2= purine S. cerevisiae mt: tunable expression Existing mt gene expression • transcriptional regulation @ initiation PNAS (1990) 87:9338

16. S. cerevisiae mt: tunable expression Existing mt gene expression • transcriptional regulation @ initiation • translational @ inner membrane http://www.mbg.cornell.edu/faculty-staff/faculty/fox.cfm

17. S. cerevisiae mt: tunable expression Part 1: mRNA target e.g. mtGFP Part 2: guide RNA Part 3: dsRNase

18. S. cerevisiae mt: tunable expression Expression vector for mitochondrial Rnt1 signal sequence + HA tag ∆NLS (11 aa) RNT1 pRS416 ∆NLS in Henras et al RNA (2004) 10:1572

19. S. cerevisiae mt: short term goals mtHEM1 marker mtRNT1p +/- dox, check protein, mtRnt1 RNA, plate phenotypes repeat microarray? localization to mt? then look at plate phenotypes, western, PCR of mtDNA

20. “it’s just a theory”

21. An ongoing communication network of science-interested parties • Objectives: • Provide a shared appreciation of science • Inform and engage the public in and about science • Make science more accessible to everyone

23. the end "Out of clutter, find simplicity... From discord find harmony... In the middle of difficulty lies opportunity." ---Albert Einstein

24. “Because Darwin’s Theory is a theory, it continues to be tested as new evidence is discovered. . . . Gaps in the Theory exist for which there is no evidence. . . . Intelligent design is an explanation of the origin of life that differs from Darwin’s view.” --Read-aloud from Dover, PA school board for 9th grade teachers “it’s just a theory”

25. “it’s just a theory” In November 8, 2005 the Kansas Board of Education approved the following changes to its science standards: 1. Add to the mission statement a goal that science education should seek to "inform.” 2. Provide a definition of science that does not preclude supernatural explanations. 3. Allow intelligent design to be presented as an alternative explanation to evolution as presented in mainstream biology textbooks, without endorsing it. 4. State that evolution is a theory and not a fact. 5. Require informing students of purported scientific controversies regarding evolution.

26. “it’s just a theory” PLoS Biol (2008) 6(5): e124 Winning in the courts Losing in the classroom

27. SW: Lee Allison took up the post of Kansas state geologist just two weeks before the school board's vote. He thinks scientists mistakenly think good science will stand on its own merit; they shy away from political debate, and they're no match for what he sees as the well-oiled political machine of the creation lobby. [Lee Allison 'Kansas State Geologist'] Lee Allison: Over the past twenty or thirty years, we've seen a very sophisticated, well funded, well trained, actually well educated group of people who are trying to push forward a religious agenda. They've been building up their support, by putting people into elected offices for many years, for a decade, of getting enough people in until they have a majority and when none of us expected this to happen in Kansas, it caught us all by surprise. SW: There seems to be uh, almost a sense of victory if these people can persuade scientists to admit that 'evolution is just a theory;' is that a misuse of the word theory? LA: The anti-evolution group is misusing the concept of a theory. They're using 'theory' as is generally used out on the streets by anybody; 'Gee, I have a theory that, uh its going to rain tonight.' Well, it's it's just a hunch, it's a speculation, a guess--- that's not how we use 'theory' in science. A theory is a well documented explanation of natural phenomena based on multiple observations, multiple tests, developed from many arenas and brought together to develop a theory.

28. …principal energy policy and planning arm of state government. The council's task is to "formulate and coordinate a comprehensive state energy plan."

30. Today's Topics: • 1. Re: systemic limitation of biobricks for combinatorial logic? • (Dr. Markus Schmidt) • 2. Re: systemic limitation of biobricks for combinatorial logic? • (Deepak Chandran) • ---------------------------------------------------------------------- • Message: 1 • Date: Tue, 20 May 2008 13:46:15 +0200 • From: "Dr. Markus Schmidt" <markus.schmidt@idialog.eu> • Subject: Re: [BBF Standards] systemic limitation of biobricks for • combinatorial logic? • To: standards@biobricks.org • Thanks JC for bringing the issues back into the disussion. The system- • wide visibility of all gate outputs is a serious obstacle to the • development of the standardized biopart concept. When I posted the • message on lacking specifity in February there was hardly any • reaction, which really surprised me. Sure as long as the experimental • phase of biobricks now runs systems that contain only few parts, all • these problems do not arise, but thinking about the future and about • the prospect of this approach we should dedicate a susbstantial amount • of time and energy to come up with solutions. • If we take electronic integrated circuits as an example (and not as a • metapher), than producing compartiments is the goal. • Which ways are there to produce compartiments? • To begin with I would say there are spacial, chemical, sematic or time- • based compartiments. • 1. Spacial: • 1.1. new organelles. This is a nice idea but how many organelles can • you engineer into a cell? Tens, hundreds, but certainly not millions. • 1.2. cell-cell communications. of course this is an option but it is • basically the same situation as in the organelles, although with the • option to increase the number of differnet cells without the packing • problems of organelles. Basically the way by wich the cells • communicate is the bottleneck. • 2. Chemical: • 2.1. Number of molecules to be used as an information carrier is • extremely large but at the cost of reduced specifity and increasing • cross talk. • 2.2. Quorum sensing. This is done by molecules and only because it • involves the extracellular environment it doesn't mean it solves the • problem of open logic gates. • 3. Semantic: • 3.1. I guess the zinc finger story comes in here, an approach that • target the genetic code. The information you can store on a lets say • x bp long DNA is 4^x (may be reduced for some mutation-robustness • meassures) and could provide enough specifity to deal with ultra large • scale circuits. This is actually a promising approach, programming an • RNA computer • 4. Time-based • 4.1. PoPS, for Polymerase Per Second. This is a nice idea (and the • comic is fun) and transcends/converts the problem of chemical • specifity to a unambigous signal unit. OK, lets say you found a way to • meassure the PoPS rigt on the DNA. Say you meassuered x PoPS. Then you • have a subsequent PoPS analyzer that makes e.g. the following • decision: if x<y output=0; if y<x<z output undefined; if z<x output=1. • Problem solved, isn't it? Well it is but only in the case if the PoPS • analyzer (counter) sits right after the PoPS relevant piece of DNA, • otherwise you would have to transfer the result x into a chemical • signal to transport it to another part of DNA or elsewhere and then • you run into the same problem of open logic gates. So if you avoid • that and realize a linear logic line (a Ford like assembly line) you • are quite limited in running your software. • However, what I think can be done is to combine all these approaches • in order to push the limit of the maximum number (Nmax) of realizable • "logic gates" or operations a little bit. Maybe each approach can help • us to push the Nmax by a factor of 100 or 1000 (or maybe more). • However, this is way a different story than with Moore's law, where • basically the reduction of size ( and packaging) of logic gates was • and is the main driving force to improve the number of transistor per • chip. • Cheers, Markus