UNM TVDC - ASU Tech Call Minutes: 6/26/2007
Prepared by Barbara Griffith: 6/28/2007
Sent to ASU for review: 6/28/07
Reviewed by Kathryn Sykes, Stephen Johnston, Mitch Magee: 7/05/2007
Distributed to NIAID on: 7/5/2007
Present: Barbara Griffith, Rick Lyons, Terry Wu, Marlene Hammer, Joe Breen, Mitch Magee,
Philip Stafford
Absent: Ann Sutton, Kristin DeBord, Freyja Lynn, Stephen Johnston, Alexandre Borokov, Vicki
Pierson
Action Items from 6/26/07 meeting:
1. Kathy- share polypeptide gels in the 7/6/07 report, to demonstrate the integrity data
described for the products of the overnight feed ivt reactions
2. Kathy- share the data for the improved purification for multiple proteins in the next Tech
report and Technical call.
3. Kathy- could provide 1 or 2 more of the His purified polypeptides and unpurified
polypeptides to UNM
4. Terry- titrate the urea to determine the highest molar concentration urea that still works
in the T cell assay
5. Rick will talk to Karl about purchasing a few of his Affy FT slides and getting them to ASU
The meeting was recorded for the purposes of the minutes.
1. Slide 1: Progress Report – ASU 6/26/07
a. Competed Milestones: 25 & 32
b. Active Milestones: 26, 28, 33, 34 & 35
c. Inactive Milestones: 30, 36-38
2. Slide 2: Milestone 26 Flow Diagram
3. Slide 3: Test ORF synthesis and select expression constructs
4. Slide 4: Previous Status
5. Slide 5: Current Status
a. Template modifications have been made but new protein hasn’t been made
from these new templates yet.
6. Slide 6: IVT Expression Template
a. K : has correct spacing and 2 his tags and should be the final template
7. Slide 7: Select and test IVT Protocols
a. Has been reactivated
b. Previously adding multiple templates and substrates at multiple time points,
to increase quantity of polypeptide produced. It works but is expensive in
labor
c. Tried getting Invitrogen to sell at lower cost by purchasing in bulk, but there is
intellectual property issues for Invitrogen—owned by Roche; volume
purchasing wasn’t standard; Invitrogen didn’t want to accommodate ASU’s
bulk purchasing needs
8. Slide 8: Previous Status
9. Slide 9: Current Status
10. Slide 10: Yield vs. Cost tests
a. Previously, ASU was supplementing up to 5 times, with DNA and substrate
feed, which was time consuming
b. Millions cpm / methionine are the units
11. Slide 11: Table 1: Multiple feed additions increase polypeptide yields at any
given amount of starting template
a. Normalized due to different number of methionines/ template used in the ivt
reactions
b. Overnight is not advantageous relative to 6 hrs; reaction product quantity
plateaus out.
c. More advantageous to start with more template. 0.5 ug levels out and can
start with 1 ug to be sure on the plateau
12. Slide 12: Isolating effect of more feed
a. Feed is composed of 5 supplement components, which are all
advantageous. Buffer is the feed as a mastermix and the vendor provides
enough buffer to do one full reaction and then to feed in the kit already. So,
per single reaction, the vendor provides twice the required amount of buffer,
so there is sufficient for a feed after starting the reaction.
13. Slide 13: Table 2: Effect of feed: Impact of single time-point “feed” addition at
0.5 h
a. Original reaction and then added feed at 30 minutes
b. J: is this 1 ug template?
c. K: yes
d. Ran overnight, with just 1 feed
e. R: is the product of good integrity after overnight run?
f. K: yes, didn’t degrade overnight
g. Barbara reviewed the 5/7 and 6/7 ASU Tech reports; there was a polypeptide
gel in the 5/7 report but not in the 6/7 report)
h. Action: Kathy- share polypeptide gels in the 7/6/07 report, to demonstrate the
integrity data described for the products of the overnight feed ivt reactions
i. Add 1 DNA template at 6hrs to restimulate the reaction
14. Slide 14: Isolating effect of adding template
15. Slide 15: Table 3: Effect of only one template supplement
a. Tul 4 is the protein being made
b. Adding components as they become limiting and only adding at this point, is
cost effective and productive
c. 1 ug in 50ul starts the rxn, then at 3 hrs are adding more template, then
continue to 6 hrs
d. ASU doesn’t have to push invitrogen or Roche for bulk reagents at this point.
16. Slide 16: Testing protocol for FTU polypeptides
17. Slide 17: Table 4: Assessing yields of different FTU polypeptides
a. All the different templates give similar yields, though calmodulin is a good
yield
b. J: how many ugs are made?
c. K: approximately 20ug are being made per reaction, based on cpm
incorporated.
d. K: could be more if added more feed and template but price would go up and
we don’t need more than 20 ug/rxn
18. Slide 18: Conclusions
19. Slide 19: Select and test protein purification protocols
a. Purification may not be necessary if unpurified lysates work in the T cell
assays at UNM
20. Slide 20: Previous Status
21. Slide 21: Current Status
a. Urea concentration should not be a step down, as proteins have been
snapping back and sticking to the beads
b. K: prefers sufficient urea , but not so little that the His tags loose exposure
c. R: if purification is required, what molar urea is needed?
d. K: 8 molar
e. R: how remove the urea?
f.
K: do acetone precipitation or a dialysis step down, but will test different
concentrations of urea in the T cell assays as too little may be problematic .
g. R: even very little urea interferes with the T cell assays
h. Alex: want a robust protocol for all proteins so using 8 M urea currently.
i. R: high urea may be a second problem for the T cell assay
j. K: Does DMSO impact the T cell assay?
k. Terry: 0.1% DMSO should be okay in T cell assay
l. K: use urea initially, then precipitates and resuspends in 0.1% DMSO before
the T cell assays.
m. K: now recovering the protein
n. R: please show the data next time for multiple proteins
o. Action; Kathy- share the data for the improved purification for multiple
proteins in the next Tech report and Technical call.
p. K: previously sticking the protein to the purification beads too tightly.
22. Slide 22: Purification protocol improvements
23. Slide 23: Completed Pilot Prep Experiment #1
a. For each template, 3 types of polypeptides are ready to ship to UNM
i. Unpurified lysates
ii. Precipitated lysates, and then resuspended in urea, and may now
move into 0.1% DMSO
iii. Purified lysates
b. R: If His purification is working better, then ASU could give UNM more
proteins that are unpurified vs his tag purified
c. Action: Kathy – could provide 1 or 2 more of the His purified polypeptides
and unpurified polypeptides to UNM
24. Slide 24: Table 5: Test samples ready for delivery to UNM
25. Slide 25: Conclusions
a. ASU likes the new purification method
26. Slide 26: Work plan for upcoming month:
a. Try on Tul 4 and Gro EL
b. J: So ASU will lower the urea concentration and then later remove the urea?
So why use urea at all?
c. K: need urea present to get unfolding of the protein and then get binding and
then get elution; urea is needed for just enough unfolding to expose the His
tags to get binding to the purification columns
d. K: trying to drop urea down from 8 M and to 4M urea.
e. R: some urea will be left behind
f. Action: Terry- titrate the urea to determine the highest molar concentration
urea that still works in the T cell assay
g. R: this is a big step in progress for ASU
h. J: We are now seeing multiple peptides produced at a high enough quantity,
which is great progress for ASU
i. Alex: will acetone precipitate, and send as a pellet
i. Unpurified (no urea)
ii. Acetone precipitated , wash to remove urea, and send as pellet
iii. column purified, acetone precipitated, washed to remove urea, and
then send as a pellet
27. Slide 27: MILESTONE 28
28. Slide 28: Build ORF expression library corresponding to proteome
29. Slide 29: Previous Status
a. Made ORFs with wild type sequences, well
30. Slide 30: Current Status
a. Scaled up for all natural sequence ORFs
b. Jerry is making the natural sequence ORFs and should be done in 2 weeks
31. Slide 31: Consistent amplification products
a. Robot loads the e gels
b. Running double reactions and both samples look the same, which is great
reproducibility
c. Performed in duplicates and Kathy thinks are identical; two independent
reactions gave the same results
d. Overlay screening on gels, computer slices the information that looks like
slide 33
32. Slide 32: Scale-up
33. Slide 33: Manipulated e-Gel for microtiter plate
a. 12 lanes and then standard= row A
b. 12 lanes and then standard= row B
c. Instrument digitizes and barcodes
d. Scans all lanes, finds center and computes molecular weights
e. Determines whether there is a appropriate band
34. Slide 34: HTP Gene synthesis
a. Build a gene on tiny chips for genes that won’t work naturally;
b. These are codon manipulated for technical building of the ORF
c. LC sciences don’t guarantee their product and ASU had 50 % success which
is too low a success rate. LC Science only sells oligomix for hybs rather than
gene building
d. Alex: found that Agilent is making chips by different technology with better
step wise yield. Not available commercially but Alex is getting 4 chips from
Agilent, which promises their quality of the chips
e. R: will Agilent maintain this relationship?
f. Alex: yes, if we have financial commitment; ASU will try the Agilent chips and
then decide
g. R: price difference?
h. Alex: $700/ LC chip and half don’t work but Agilent is $1200/ chip if bought 4
for $4800. So really, if half the LC chips don’t work, then the half that do
work are effectively costing $1400
35. Slide 35: Conclusions
a. Finish wildtype orf production for sure
b. Push on ORF chips
c. R: great progress!
36. Slide 36: Work plan for upcoming month:
37. Slide 37: MILESTONE 33
a. Philip Stafford- introduced as a biostatistcian and microarray data analysis
expert
38. Slide 38: Genes Identified After Amplification
a. Mixing normal mouse RNA with bacterial RNA
b. Two sets of Venn diagrams (Red is SCHU S4)
c. Took average of 6 slides, using top 1 sigma of all data, to get 600 genes
d. These genes are approximately 1.3 fold above median and higher
e. Green circle of the Venn diagram: 1 ug to 0.1 ug below
f. In the yellow overlap, there are ~270 genes detected but 54 were not
detected in the high level for the unamplified samples. Didn’t expect new
genes being detected.
g. 200 of the 600 genes are being detected down to the 0.1ug level
h. .001 ug didn’t give good data and didn’t analyze
i. 0.1 and 0.01 ug showed a few genes (33+21) that were not picked up in the
unamplified.
j. So, ASU is picking up 300 genes at 1 ug , 200 genes at 0.1 ug, and 113
genes at 0.01 ug
39. Slide 39: Whole slide images of SCHU S4 on ASU and TIGR array
a. Finally got the TIGR slides and hyb data shown is for unmodified,
unamplified SCHU S4 RNA
b. Raw image of ASU and TIGR slide shown
c. Used random primers and not GDP primers for this experiment, so that the
targets could be synthesized and then hyb’d to the TIGR slides. GDP
directed cDNA synthesis products would not hyb to the TIGR slides.
40. Slide 40: Hybridization of SCHU S4 RNA to ASU and TIGR Slides
a. ASU slides have 2 logs of intensity range and TIGR slides have a more
compressed range, with approx 1 log of intensity range to work with
b. In the normalized data, colorized for ASU range and TIGR slides appear
compressed
i. Expected coloration is for red to be on the top and the yellow to be in
the middle and the blue on the bottom.
ii. TIGR gives surprising, unexpected rainbow and the spearman
correlation is poor for the TIGR slides
iii. Used exact same hyb solution and labeled targets are being used for
the ASU slides and the TIGR slides.
iv. ASU is PLL and TIGR is corning ultragaps (Confirmed by Joe from
the TIGR website)
v. J: what does this data mean?
vi. M: will return to this question at the end of this call; This is a big
question. “If you have one thermometer, you know what the
temperature is but is you have two thermometers, you never know
what the temperature is”
vii. B: comparing across platforms is not really easy
viii. Phil: microarray literature comparison of ilumina, affymetrix, and
others commercial arrays- use cell extracts across two different
platforms, see 40-50% of the genes going in the same direction and
intensity maybe 60% similar between 1 or 2 fold. This is for
commercial arrays. The reasons relate to priming location, like the 3’
untranslated region or from inside the translated region. You can
make your array data match the Q rtPCR data by picking the same
primers or probes for both. You can make the arrays match by
picking the exact same probe, but can’t make your arrays match if
you are picking different probes along the untranslated region. Can
compare within a slide for 5-7 genes that are known expressed and
computing the ratios and using the ratios to average out the slides
as controls.
41. Slide 41: Gene Identification Discrepancies
a. Looked at genes differing by more than 8 fold. 38 of the 1810 genes that
were more than 2 fold up or down.
b. Most were higher in the ASU slides than he TIGR slides
c. Histogram shows the locations
d. Red are at top of ASU slides and then they are at the bottom of the TIGR
slides- flipping positions.
42. Slide 42: Milestone 33 Summary
a. Need a system for comparing and understanding the discrepancies between
the TIGR and ASU slides
43. Slide 43: MILESTONE 34
a. Terry’s RNAs from UNM are hyb’d on this slide and most of the data was
reported previously
44. Slide 44: Diagram: PLL vs. Corning
a. Mimics the TIGR vs ASU slides, with broader range of signal with the ASU
PLL slides
b. J: confirmed that TIGR slides are Corning slides
45. Slide 45: Continued from slide 44
a. Normalized intensities Blue at bottom and red at top of most of the arrays:
this is what was expected
46. Slide 46: Diagram: Maui vs. Arraylt
a. Two different type hyb chambers; Maui is a mixing chamber and A=array it
is a static chamber
b. M= Maui and A=array it
47. Slide 47: Continued from slide 46
48. Slide 48: Reproducibility between Experiments and Hybridization conditions
49. Slide 49: Diagram: In Vitro SHU4 vs. In Vivo Amplified
a. Good spearman correlation between Maui data and Array it data
50. Slide 50: Milestone 34 Summary
a. Compared all in vitro and in vivo samples, across 6-7 slides
b. Use 6-7 slides and achieve confident comparisons below 2 fold differences
between the samples. Found 208 genes that are up or down regulated in
vivo relative to the single control of unamplified SCHU S4 RNA.
c. This is all ASU data comparison now; will use TIGR differences in the future
51. Slide 51: Upcoming Monthly Transcriptome Goals
a. PLL is working great with higher , broader range of signal detection
b. Maui mixing can enhance but not enough for the $20 disposable chambers
and $48,000 instrument cost for a 12 chamber system.
c. Take highly differentially expressed genes (38 high on ASU and low on
TIGR) and could analyze by Q rt PCR. OR could spike in a sample from
Kathy’s production
d. Another option would be to generate a 3rd array perhaps from Agilent,
custom slide of the differentially expressed genes
e. R: how much time should we spend on figuring out the differences between
ASU and TIGR slides?
f. M: Perhaps we could also send Karl some of our slides and since Karl is
using TIGR slides?
g. J: what is needed to move ASU project along to refine ASU’s conditions, for
their arrays? Joe sees the limit coming in comparing ASU and TIGR slides.
h. R: sees more issues in the future with in vivo samples. If use GDP primers,
they won’t work very well with the TIGR slides and need GDP for the in vivo
samples. Would be worth confirming with Q PCR and then focusing on in
vivo samples rather than trying to sort out ASU vs TIGR slides differences.
i. Phil: spike in could be helpful also for limit of detection. Can titrate to
determine the physical limit of detection. If you are hitting most of the genes,
then you have determined the limit of detection. J: compare to a 3rd type of
slide?
j. J: doesn’t recommend to compare to a third type of slide
k. R: Karl has a deal with Affy with Francisella?
l. J: knows a source of Affy FT slides, but privately funded and we can’t get
them
m. R: perhaps buy a few from Karl, if Karl used the PPG funds to purchase the
slides? Action: Rick will talk to Karl about purchasing a few of his Affy FT
slides and getting them to ASU
n. M: has Affy system and could run some of Karl’s slides
o. M: could make multiple probes for same gene , to be more similar to the Affy
if needed.
p. R: will talk to Karl first. Confirm what is being seen and helps FT community
so a 3rd slide may be a good approach. FT community likely to use the affy
slides. Develop short, crips plan for this comparison
q. R: making good progress!
Next Calls:
7/31: will hold ASU Tech call on 5th Tuesday in July. Kathy, Stephen, Mitch, Alex, Phil,
Joe and Marlene can attend
Personnel:
1. Barbara away: 8/15 Wed to 8/29