Progress toward identification of F. t.
subunit vaccine candidates using
Immunome and Transciptome
approaches
Stephen Albert Johnston, Mitch Magee and
Kathryn Sykes, Alexandre Borovkov
ASU key achievements
• M#25: Informatic phase
– Developed approach for F. t. open-reading frame (ORF) and
library design: Milestone completed.
• M#26: Protocol development phase
– A modular system allowing instant modification of the
existing IVT cassette has been developed
– Applied in HTP format, the set of new protocols reliably
generate ≥25ug of protein per reaction
• M#28: Polypeptide library production
– Scaled up IVT protein production has been demonstrated.
ASU key achievements
• M#32:
– Oligos list refined, 70mer oligos procured, GDP oligo
defined
• M#33:
– Printing and Testing and GDP confirmed
• M #34:
– Pilot studies for optimization of RNA isolation and
hybridization conditions
• M #35:
– Array hybridations with mouse RNAs from virulent SCHU S4
infection and RT PCR confirmation of candidates
Candidate identification part 1
Immunome Milestone 25:
Design SCHU S4 polypeptide library
• Informatically selected and ordered a set of F. t. synthetic
peptides likely to be immunogenic.
– 500 peptides predicted to be MHC I and II binding epitopes
delivered to UNM.
– UNM team is using peptides to facilitate T cell assay development.
• Developed HTP, robust approach for F. t. ORF design and
approach to their synthesis
– New software and protocols have been created for improved gene
synthesis.
– A genomically complete library of genetically-improved ORFs have
been predicted
Immunome Milestone 26:
Prepare a high-throughput protein
production system
• Select and test ORF expression constructs
– A modular system allowing quick modification of the
existing IVT cassette has been developed.
• Select and test IVT Protocols
– Applied in HTP format, the developed protocol reliably
generates ≥25ug of protein per reaction.
• Select and test protein purification protocols
– We have purified a number of F. t. polypeptides, and
these are being tested at UNM.
– The current protocol is associated with significant
losses, solutions are being addressed. Discussion
tomorrow.
Modular components for linear
IVT template
T7
RBS ATG
T7
RBS ATG
T7
RBS ATG
T7
RBS ATG
His
His
ORF
Term
N-term tag
ORF
His
Term
C-term tag
ORF
His
Term
double-tag
Term
w/out-tag
ORF
Optimization of the LEE assembly
conditions
Dbl His
N His
C His
No His
Transcription/translation efficiency of
crude vs. perfect PCR products
Use of the raw gene assembling reaction as an IVT template yielded same quality
and quantity of the IVT products as a perfectly assembled, cloned equivalent.
MW
# Met
ul sample
CPM
CPM Total
CPM #met
ug prot
FTU 728a_a Clone
21,703
4
85
11274
191,658
47,915
20.74
FTU 728a_b Clone
24308
4
85
12653
215,101
53,775
26.07
FTU 1434c_a Clone
19007
5
85
20006
340,102
68,020
25.79
FTU 728a_a mix
21,703
4
85
3725
63,325
15,831
6.85
FTU 728a_b mix
24308
4
85
13990
237,830
59,458
28.83
FTU 1434c_a mix
19007
5
85
23193
394,281
78,856
29.90
CPM
Effects of supplements on FTU
polypeptide yields
140000
Standard LEE IVT w/out feed
120000
Standard LEE IVT with a feed
100000
1 extra LEE spike (3hrs) w/out
extra T7
80000
1 extra LEE spike (3hrs) with 1
extra T7
60000
2 extra LEE spikes (3,6) w/out
extra T7
40000
2 extra LEE spikes (3,6) with 2
extra T7's
3 extra LEE spikes (3,6,12)
w/out extra T7
20000
0
1
2
3
4
5
template
6
7
8
3 extra LEE spikes (3,6,12) with
3 extra T7's
Milestone 26 status and
plans for next 6 months
• Polypeptide purity demands, and sample
complexity limits, will be determined.
• If determined to be needed, new purification
schemes will be incorporated into the
production protocol.
• Interactions with UNM team will increase as
we work together to provide appropriate
antigen material, in sufficient quantities and
formats for the T cell screen.
Immunome Milestone 28:
Build the SCHU4 proteome
• Build ORF expression library corresponding to
proteome.
– HTP protocol developed and demonstrated
• Generate complete protein-fragment library
(inactive)
• Array protein-fragments into measurable pools for T
cell stimulation (inactive)
Project Scale-up
• Digitized gel system enables fast, accurate
visualization and analysis of thousands of ORF
samples.
• QC analysis is electronic. All electronic resultoutputs are automatically entered into the electronic
management system.
• Identifying robust protocols for increasing yield after
purification has been challenging. Corrective
actions will be presented tomorrow.
E- manipulated gel of FTU
ORFs
Milestone 28 status and
plans for next 6 months
• HTP production of ORFs and LEEs are underway.
• For synthetic genes: Agilent oligomixes have been
tested in protocols. Genes can be made from this
source, although further improvements are
anticipated.
• Purification and complexity decisions are pending.
Additional test samples will be provided to UNM.
• HTP IVT protein production can be initiated…
Candidate identification part 2
Transcriptome Specific Aims
• Is there a relation between expression of genes in
vivo and antigenicity?
• Gene expression profiling of F. tularensis in host
tissues will allow us to compare transcriptional
activity to in vitro grown bacteria
• Compare bacterial transcripts in immune and nonimmune animals
• Identify genes or gene islands regulated by host
factors
LAPT Process
TVDC Transcriptome Milestones
• 32 Oligos list refined, 70mer oligos procured, GDP oligo
defined. Will be based on annotated SCHU S4 sequence.
– Designed, obtained, and spotted 1804 70mer oligos for SCHU S4
– Designed and obtained 183 GDP 7mer oligos for SCHU S4
amplification
• Added to this design 185 Oligos for LVS genes not found by probe
made with SCHU S4 design
• Added 12 GDPs for LVS amplification
• 33
Printing and Testing and GDP confirmed
– Printing substrate and labeling process optimized
– GDPs amplification confirmed utilizing purified RNA diluted into
normal lung RNA
TVDC Transcriptome Milestones
• 34 Pilot studies for optimization of RNA isolation
and hybridization conditions
– Defined RNA isolation and purification procedure
– Compared hybridization conditions (Automated vs Static)
• 35 Array hybridations with mouse RNAs from
virulent SCHU S4 infection and RT PCR confirmation
of candidates
– Validated GDPs and LAPT with animals heavily infected
• 4 days, >107 CFU
– Performed analysis after dose response challenge
• 103 – 107 CFU Challenge, 4 hour harvest
Problems Encountered
• Change in cDNA synthesis kits used for
LAPT necessitated search for alternatives
– We have found suitable replacement
reagents and re-verified LAPT process
Differentially Expressed Genes
Between SCHU S4 and LVS
• Insert copy
Up in SCHU S4
Down in SCHU S4
Spearman Correlations of LAPT
Amplified RNA
ng SCHU S4
1000
1000
100
100
10
10
1
1
g Mouse
Lung RNA
10
10
10
10
Spearman
0.609
0.583
0.658
0.626
0.585
0.593
nd
0.576
Spearman Analysis of the Rank
Order Between Samples
MS2 MS3 MS5
MS-2 to MS-3
MS-2 to MS-5
MS-3 to MS-5
Coefficent
0.742
0.715
0.624
Amplification of SCHU S4 from Lungs
of Infected Mice
Infection dose
g after LAPT
# Genes >2 fold to 0
0
18
-
103
5
192
104
42
260
105
51
197
106
30
190
107
42
538
6 Months Goals
• Complete Milestones 33 and 34
– Finalize comparisons of TIGR and ASU arrays
– Verify limits of detection for LAPT in extended dose response
studies with purified SCHU S4 RNA
– Verify probe subsets by hybridization with PCR amplified genes
• Milestone 35
– Finalize in vivo limits of detection in dose response challenge
studies
– Add pathway information into GeneSpring for down stream
analysis
– Generate and process experimental samples from a time course
of challenged animals
– Q-PCR verification of hits identified in the microarray
Questions after Presentation
• High dose of bacteria data is interesting.
Bacteria to bacteria impact on bacterial gene
expression is quite interesting.
• Bob: At LRRI, they can see direct lethal events
with too many bacteria in the lungs, giving a
really high inflammatory response.
• Code Link substrate used by TIGR on their FT
microarrays doesn’t provide as good a
microarray signal relative to ASU’s PLL slides
used for printing microarrays at ASU.