good morning and good afternoon
welcome to today's webinar titled
tools and methods for crisper cast 9 screening for functional genomics and drug discovery
our presenter today is Luis Baskin
senior product manager for functional genomics at Thermo Fisher Scientific
my name is Matt poling also Thermo Fisher Scientific
and I'll be your moderator for today's event.
today's educational webinar is brought
to you by lab roots
and sponsored by in vitro gen by thermo Fisher Scientific.
infusion offers tools and solutions for every step and the CRISPR genome editing workflow.
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I'd like to now introduce our presenter Lewis Baskin
Lewis has 15 years of experience in product management marketing and technical sales of reagents and tools for gene modulation
encompassing RNA interference and CRISPR caffeine
she was responsible for managing the thermo Fisher portfolio of Si RNA custom RNA synthesis and CRISPR guide RNA products
she received a master's degree in molecular biology and genetics from
Northwestern University.
and with that, Louis I will hand it over to you
good morning and good afternoon everyone
thank you for joining today
I'm I'm sure many of you are growing tired of looking
at computer screens
but hopefully you will extract some value in the time we
spend today
discussing tools and methods for crisper screening for functional genomics and drug discovery.
now it's it's I'm sure many of you already know something about Thermo Fisher Scientific
I'm not going to spend a lot of time
about who we are and what we do
but I do want to mention our company's mission statement
enabling our customers to make the world healthier cleaner and safer.
for me this is recently taken on a whole new meaning as we kind of navigate this
Kovach 19 landscape
both kind of in my own stay at home life
as well as in
appreciating my company's contributions to the pandemic response
with instruments consumables safety supplies
and most importantly diagnostic tests
you know staying healthy clean and safe has really never been so important as it is now.
and hopefully you're joining today because you you know see the
potential of functional genomics
as a way to make progress
you know toward your own mission.
so what I hope to provide today is insight from you know my corner of the thermo world to help in advancing your research.
I'll do a brief overview of the role of CRISPR cash 9 for functional genomics
and how it's used to carry out loss of function studies
I'll next review the available CRISPR reagent types
with a quick overview of considerations for choosing each type
and I'll cover our guide RNA algorithm
development and it's validation.
and then I'll spend time sharing details about our lentiviral guide RNA libraries
and then get into applications with those
libraries you know really showing them in action.
I'll share the workflow from a pilot screen we carried out to look at pathway analysis.
and I'll close with results from a kinase screen library being used for drug discovery.
using functional genomics
researchers gain an understanding of how a change in a genes expression level
whether that's one gene or many
will give rise to changes in a cell's phenotype
for kind of foundational or basic research
the purpose might be to determine a genes
role in a particular biological pathway or process
you know in other settings
may be like in a biotech or pharma
we see functional genomics being used to
identify a potential druggable target
so my talk today I'll walk through examples
of each of these types of investigations
specific to the type of functional
genomics
I'm talking about our loss of function studies
where in essence were reducing the expression of individual genes and looking for changes in the cellular phenotype
for research studies, these typically are going to rely on cell based phenotypes
to you know just give us kind of a slice of biological information
about the role that genes play in our system of interest.
the tool sets that are most commonly used for loss of function are RNA interference or RNAi.
I where we can knock down expression at mRNA level
or using CRISPR caste 9 to completely knock out expression.
now thermo has excellent tools in both of these areas
but today's topic is going to be focused on CRISPR knockout.
so like most good presentations
I'm going to start with a brief review
of the biology
so CRISPR casts 9 mediated gene editing is part of a bacterial immune response
and strep pyogenes which is the most widely adopted system for mammalian gene editing
small RNA is called CRISPR RNAs
are transcribed
they have a 20 nucleotide unique spacer drive region
and a 22 nucleotide conserved repeat derived region.
separately a long RNA called tracer RNA
has also transcribed
and the CRISPR and the tracer RNA hybridized through the repeat derived sequence
and this CRISPR tracer hybrid is collectively known as the guide RNA.
it can then recruit the cast nine and a nuclease
which is shown in my figure in green.
and this catheline complex then uses the unique spacer drive sequence as a guide
to its DNA target
which is a region that's always going to be immediately proximal to a three nucleotide proto spacer adjacent motif or Pam.
so for s pyogenes this motif is ngg.
so the genomic DNA is then pleased by the
caste 9 nucleus just adjacent to that pam site
and again in s pyogenes this is
an immune response mechanism that's used to defend against foreign genetic
material
but a number of years ago it was adapted for use in mammalian cells
and animal models for targeted genomic cleavage
so how are researchers using this technology for functional genomics?
when we create double strand breaks in the genome the cells and Nate repair
mechanism kicks in
for a straight-up repair of a break the mechanism is typically going to be non-homologous end joining or nhej.
a and the thing about
nae-ga is that it's not always perfect
it is just as likely to introduce errors
such as insertions or deletions
you'll see me later collectively call these in
Dells
you know while it's in the process
of trying to stitch everything back
together
so when we use CRISPR Cass 9 to deliberately target the coding sequence
of a protein
this imperfect repair can lead to a frameshift a nonsense mutation
or a premature stop codon
and knock out functional expression of the gene
so there can still be functional wild-type protein expressed if the break is
repaired
but improvement in the design of guide RNAs which I'll discuss in a
few slides
has really helped to kind of tip the scales towards that imperfect
repair so that we get a higher rate of knockouts
and there are a lot of other applications for genome engineering using these targeted nucleases knock ins or other precise editing
but for today I'm just focusing on the application of
functional knockouts
so as for being able to do those loss-of-function studies.
so I want to take a minute and look closer at the two components that are needed for doing a knockout experiment with CRISPR.
again this isn't an endogenous mechanism.
so both of those components need to be introduced into our cells of interest.
the Cassadine
nucleus and the guide RNA
both of which need to be expressed or delivered at high efficiency to achieve robust editing.
so I'm going to take a quick
walk through both of these components
so first is the caste 9 nucleus which can take many forms
I'm showing two of them here on the screen
listed with the name of the reagent as it's available from in beiträge.
in the earliest days of CRISPR mostly utilized cast 9 Express from a plasmid
but that quickly fell out of
favor mostly for reasons of efficiency
so both protein and mRNA is shown here on the screen
offer DNA free transient
expression of path 9
so if you're engineering a cell line you're not going to have residual catheline expression
or any kind of genomic incorporation as you might have with a plasmid.
both of these can be easily code transfected or Co electroporated along with a synthetic guide RNA when cells are amenable to that delivery.
caste 9 proteins ours is called drew cut caste 9 protein
v2
has really emerged as the most popular format for both knockout and not
in experiment
due to the ability to complex it with a guide RNA
to form kind
of a ready-to-go ribonuclease or RMP
because there's no transcription or
translation required
the entire complex is ready to go as soon as you deliver it
the other popular method forecasts nine
expression and settles is to express it from a lentiviral vector.
this gives you the benefit of enriching the transduced population because you can also call express an antibiotic resistance marker
you also have the option of using an inducible promoter to turn on cast 9 expression at a particular time point
and then you also have the advantage of working in a wide range of cell types
you know even those that might be really difficult to transfect
because lentiviral transduction can generally be successful in a very wide range of cell types.
so for the applications I'll talk about today
the main advantage to learn to
broadcast 9
is being able to create cast 9 Staveley expressing cells.
this approach is optimal for experimental setups like high-throughput screenings that I'll be talking about today
or even any situation where a cell
line of interest is going to be used over and over again for CRISPR studies.
it creates a nice stable background of past 9 expression so you can focus just on delivery of the guide RNA.
Guide rnas also come in multiple formats
to support a range of workflows.
synthetic single guide RNAs or SD RNAs
are where the CRISPR and the tracer are catenate it into a single long RNA
and these are most populous systems that can support that RMT delivery
where you complex the guide with the catheline protein and deliver either by transfection or electroporation.
the Invitrogen true guide s tRNAs incorporate three prime and Phi prime chemical modifications that enhance stability.
and these modified guides have demonstrated higher efficiency and a number of experimental systems and cell types.
synthetic guides can also be easily transected into caffeine expressing
cells
and again since the transient they're very suitable for knock out as well as knock in gene-editing
where you don't want any residual
crisper components left behind.
as with the cast 9 nucleus there's also
a lentiviral option for expression of guide RNAs.
from our company these are
known as lengthy array guides.
these are delivered as high titer Lenti viral
particles.
selection markers can be utilized you know in ours and as well as any platform.
and again this is a way to be able to enrich the population of transduce cells.
the guys can be delivered into cast 9 expressing cells
or code transduced
with length of RL cast 9 in a single delivery step.
and again you have that advantage of being of the work in cell types that are
difficult to transect
due to that ability of transduction in to a wide
range of cells
As we developed our guid RNA product lines we also spent a lot of time and effort on our algorithm
to find the most efficient guide RNA sequences.
so I'm just going to show you a very high-level overview of how we accomplish
this.
so first we identified target loci
where the in Bell formation would result
in editing of all isoforms.
so in most cases this is done by a targeting conserved exons typically in the five prime end
since it has been shown that
in Della's formed in the in the earlier part of the transcript are going to have a better likelihood of causing functional knockout.
到这里next we identify all available guide
RNAs in that conserved region based on
the presence of that Pam site so the ngg
motif that is required for the guide RNA
recognition and then we looked at all of
the guide designs and scored them based
on functionality and expected binding
efficiency to cast 9 so there's a number
of target sequence characteristics that
contribute to this such as sequence
complexity GC content whether certain
bases are in certain positions along the
guide there is a lot of data that
demonstrates there's certain base
positions that can improve efficiency we
also give preference to certain NDG
motifs over others it has been shown
that some can be more active
so for those remaining guides that
scored well in functionality we then
take and score them based on sequence
specificity so we had done our work to
decide if we thought they'd be efficient
and now I need to make sure they're not
also going to target other regions of
the genome so we analyze potential off
target sites sites based on sequence
matches to different regions of the
genome but there's different levels of
tolerance for different types of
sequence similarity so examples of
similarities that could be tolerated or
shown here with with green checkmarks if
there's multiple mismatches in the seed
region which is the portion closest to
the pam site this is the most critical
for guide RNA recognition of that
genomic site or if that off target site
lacks the presence of a Pam these are
going to be you know pretty much
tolerated by our specificity score
because they're not likely to to cleave
in that off target site but if there are
perfect matches or even just perfect
matches in the seed region shown as the
examples with the red X's these types of
mismatches have shown the ability to
still engage in cleavage events and so
therefore would be considered off target
so so these guides would be discarded as
being too nonspecific and then out of
those remaining we choose our top four
non-overlapping guides for everything
that's designed against a certain gene
and then offer them as pre-designed
guide RNA reagents
so this is a measure of the kleva
deficiency for those top four designs
targeting 18 different genes so here we
delivered true guide synthetic sgrna
into cast nine expressing spells and
then analyze cleavage efficiency and you
can see we've got greater than 60% on
average and and this is from a genomic
cleavage assay that can often
underrepresented editing so the
algorithm is really doing a good job in
determining guides that have high
efficiency we did some additional
validation experiments using our Lenti
array products not just to see how well
they knocked down but see how well they
worked in an array format so in this
case we did an assessment with a dual
transduction so delivering calf nine and
lentiviral CRISPR guide RNAs at the same
time we targeted eight different genes
in an arrayed format following pure mice
and selection for five days we used
again night genomic cleavage detection
assay to assess editing
so these gels show the results from that
geumja cleavage assay and then they're
quantified on the bar graph on the right
and really as you can see demonstrated
very high efficiency in delft formation
so these results really was part of what
encouraged us to pursue an arrayed
library product format with the lengthy
array guide RNA product line as we did
the build out of those libraries we did
more experiments to look at our
efficiency so here's a set of results
targeting 155 genes that are part of the
Atlantia Rea human cancer biology
library so we did these experiments at
two different mo AI or multiplicity of
infection if you're unfamiliar with this
that is a ratio of the number of viral
particles to the number of cells you can
say that in the upper graph at an ml I
of 177 percent of the targets achieved
at 50% or greater editing efficiency and
this time we're asking using next-gen
sequencing instead of genomic cleavage
at the higher mo I in the lower graph we
had 87% of targets at or above that that
50% cut off if we set the bar even
higher the my of one has over half of
the guide that 70% are better editing
and the my F 10 still looks really good
with 77 percent achieving that 70
percent are better editing efficiency so
now I'm going to shift into a little
more of the technical details of the
arrayed lentiviral CRISPR libraries so
many in the screening world have readily
acknowledged the utility of CRISPR
knockout for loss of function studies
given that we can achieve complete
permanent knockout of gene expression
and not just partial silencing it gives
us more robust phenotypes and therefore
a much larger assay window leading to
the entire confidence in our heads and
better hit confirmation
talk about functional genomics screening
there's always a need to discuss both
strategies both pooled and arranged
screening so most of the talk is going
to focus on a raid screening today but I
don't want to ignore pools completely
given that they're a great product and
most pooled screens end up eventually as
in a raid screen because you do need to
look at the individual guides RNAs in
doing hit confirmations from a primary
screen so I've listed on the slide what
I what I've always thought are the
biggest differentiators between these
two approaches although others certainly
do exist and I think it's worth
mentioning neither one of these is
better than the other you know it's
really about educating yourself on these
distinctions to determine which format
is best for your particular experiment
in your particular assay so a pooled
library contains lenta Braille guide
RNAs targeting all of your genes in a
single tube and the transduction into
your cells will take place in one or
very few large dishes so the need for
liquid handling or any other kind of
robotic infrastructure is pretty low a
rave screening where each guide or maybe
a pool of multiple guides is arranged in
a one gene per well format this is
potentially going to require a lot more
infrastructure for dispensing of
reagents into tens or hundreds of plates
but the biggest differentiator between
the two from a scientific point of view
is the type of assay that can be
supported full screening requires a
somewhat basic sort of yes/no FA you
know viability or survival that
separates life from dead potentially
upon treatment with a drug or some other
sort of survival pressure or you can use
a fax analysis readout to separate you
know a green from non green in a
reporter assay in contrast a raid
screening lets you go well beyond
viability into high content assays for
cell morphology transportation migration
assays nuclear alter agents really
anything that can be visualized under a
microscope there's also much more
ability to look at quantitative loss of
function results since you can actually
rank the hits by the degree of intensity
or penetrance
measured in each well
so in support of both of these
strategies we have lengthy pool v2
CRISPR libraries which include four
guide RNA spur genes that are delivered
to you as high titer virus as of one
times ten to the eighth all of our pools
go through extensive quality control to
ensure guide RNA representation those
same lentiviral guides are also
available in an array format so to
support high-throughput studies we do
pool the four guys per gene into a
single well this is a great method for
reducing the number of plates required
for your screen and still get really
good efficient editing of your target
each lengthy array library is delivered
as two aliquot for 50 microliters each
again at a titer of one times 10 to the
8th in addition to lenta viral particles
we offer the individual length array
guides as glycerol stocks do you have a
renewable resource of guides for making
your own libraries or using for
follow-up studies regardless of the
format all of our CRISPR libraries are
available as 19 different genes family
libraries like kinases or GPCRs or they
are arranged by function like
epigenetics or cancer biology and we
also have whole genome collections for
doing you know really completely
unbiased investigations so in support of
pilot studies or doing follow-up or any
groups that have their own list of
important genes we can also assemble any
of these formats into a custom
collection that suits your needs
so to show you a bit more
the vectors in the in of lentiviral
products so the lenten rate has nine new
clays shown here on the Left
encodes a human code on optimized s
pyogenes cast nine protein with two
nuclear localization signals cast nine
and less decidin resistance are both
driven off and ef-s or a short EF 1
alpha promoter the linty array guide RNA
expresses a specific guide RNA from a u6
promoter while the pure mice and
resistance gene is separately driven
again by an EFS promoter all of these
contracts constructs our sequence
verifies following production and as
you'll see in my examples coming up they
can be used either transiently or with
selection from pure mice and treatment
to enrich for the population that has
received the guides and here's a look at
our Lenti array controls so as most
screeners know or will quickly find out
the key to a good screen is optimization
both of the delivery of the guide RNAs
as well as the si readout so using these
validated controls gives you a GFP
expression as a visual readout of
transduction efficiency it's a really
nice straightforward visual tool to help
optimize transduction to determine the
appropriate mo AI there's two different
lengthy array controls we have an on
targeting control which of course should
target nowhere in the genome but
provides a nice control for nonspecific
effects because of the transduction and
then any subsequent treatment treatments
required for the phenotypic assay for a
knockout positive control we target the
hprt gene which can be used to estimate
the overall efficiency of editing but
you can also use this gene as a knockout
as a phenotypic negative control because
generally speaking hprt silencing or
knockout will be inert in most
biological pathways you can use as a
positive control for knockout and
potentially a negative control in your
phenotypic assays
does not have touched on the technical
aspects of the leant ear a guide RNAs
I'm going to go into those two different
case studies that show these arrayed
libraries in action
a high-level these are the steps I'm
going to take to take you through our
pilot study workflow we established a
cache 9 expressing cell line we
optimized our transduction and assay
conditions set up our plates and
controls to run the screen and then I
went through a series of steps for hit
confirmation so the data I'm showing you
is from an in-house pilot study but a
much larger screen using the same si has
recently been submitted for publication
by our collaborators at AstraZeneca
so first step is to generate that stable
cation expressing selling so as I said
before constitutive caste nine
expression is recommended for high
throughput studies so starting with our
cells of interest we transduced with the
lengthy broadcast nine following an
antibiotic kill curve we treated with
appropriate amount of blastocyte in did
selection for about three weeks and then
carried out clonal isolation we then
expanded those cells to verify and
characterize functional cassadine
expression so in the lower left you'll
see our results with a Western blot
where those alpha numeric labels are
different clonal isolates which beta
acting as a loading control we looked at
expression of caste nine and solve
really good expression of caste nine and
all of these clones on the right you'll
see some of those same clones analyzed
now for cleavage efficiency upon
treatment with the guide RNA using that
positive control targeting hprt
now you'll notice that there is some
variation in the cleavage results
between the different clones which isn't
necessarily you know kind of visually
represented in the Western blot for the
cast nine presence but what this does to
me is it illustrates the importance of
ensuring that your clonal lines are not
just assess forecasts nine expression
but also for the degree of functional
efficiency you can see so our goal in
selecting a clone to to expand and use
for our studies is to have the best
cleavage along with demonstration of
similar growth rates and morphology as
the parental spelling
cells that we used for this study are
one of the cell sensor cell lines these
are engineered for the study of various
biological pathways through analysis of
signal transduction now there are a few
dozen cell sensor lines available there
for analysis of different pathways and
they're derived from different cell
types but what they all have in common
is the use of this reporter system to
determine pathway activity through beta
lactamase activation so the DLA
substrate is a coumarin like molecule so
on the left that can be excited by UV
light and it's linked to a flora scene
or a 50 like model molecule that emits
green when it's excited so these are
connected by a beta lactam ring shown in
red so when a pathway of interest gets
activated beta lactamase is expressed
which cleaves that beta-lactam ring but
then results in an altered floor force
such that when excited by UV light it
now emits blue sense of energy isn't
able to be transferred to the green
fluorophore so what this all comes down
to is a nice measurable method of
determining the levels of beta lactamase
expression so let's look at this assay
in action for the screen that we carried
out we're looking at NF kappa-b
activation when we treat this stylus of
a TNF alpha this triggers a signal
cascade for activation of NF Kappa B
which translocates
into the nucleus and triggers the
expression of beta lactamase
so here's where that dla substrate comes
in in the absence of beta lactamase we
get green emission so without tnf-alpha
cells are green but when TNF alpha is
added to the cells the NF kappa-b is
activated beta lactamase is expressed
and the cells become blue so our plan
for our first pilot study was to treat
these cells with a number of lengthy
rate guide RNAs targeting genes in that
NF kappa-b activation pathway and then
see how effectively we could block the
green the blue change in the presence of
the TNF alpha activator
but before we get to the guides
themselves first things first we need to
make sure we're working with optimal
transduction conditions so delivery of
guide RNAs whether you're using
lentiviral transduction or a
transfection or agent is a very
important step to optimize to make sure
you get the maximum efficiency of
editing so the two variables we worked
with were the cell density and the mo I
of the viral particles we tested two
different cell densities at four
different mos in a 384-well plate
delivering guide RNAs targeting hprt as
a negative control since I mentioned it
it's not a gene that plays a role in
this particular pathway of interest we
also looked at T rad which is a gene
within that NF kappa-b
signaling pathway and then we also
targeted beta lactamase itself as our
reporter molecule so not found F T read
and beta lactamase gives us a decrease
in the percent activation compared to
the HP RT control so what we're looking
for is conditions that give us virtually
no effect and hprt knockouts but the
greatest effect with T read and beta
lactamase at the lowest mo eye you can
see we got good separation of the
positive and negative controls
specifically if you look at the blue
bars representing an MRI of - this is a
condition that best meets our criteria
so we won't with that amount of the
guide RNA for the screen and then found
really that we could use either cell
density and get pretty similar results
so we used the lower amount of cells we
also tested whether we needed to do pure
mice in selection to give us the best
separation of hits from non hiss along
with establishing an optimal time point
so we looked at day 5 and day 9 post
transduction both with and without pure
mice and selection you can see in
comparing those red and blue bars that
there's little need for doing selection
we had really great penetrance from the
knockout without it so while we knew we
could use it it was really unnecessary
and we also found that we could easily
read the essay by day 5 so that was what
we went with in all of our subsequent
experiments
so now we were ready to run our pilot we
used our stable cast 9 cell sensor line
with our optimized conditions we
transduced Delancy rate guide RNAs
targeting genes known to be either
positive or negative in this assay four
days later we added TNF alpha and then
took our measurements of the readout so
as expected in the absence of TNF alpha
ourselves remains green for cells that
were treated with TNF alpha our negative
controls within this case you can see is
a non targeting control or that hprt
targeting guide RNA we see very
effective conversion of green to blue
indicating the NF kappa-b pathway was
activated and beta lactamase was
efficiently expressed so when we look at
genes within that NF kappa-b pathway we
see that in including our positive
controls of targeting beta lactamase
itself we see really effective
inhibition of the assay readout
demonstrating really again now efficient
knockout of that target in virtually
every cell and keep in mind this is
without any antibiotic selection for
enrichment of those cells so even though
the visual results were pretty
convincing we followed best practice to
verify that our results were due to
actual editing at the indicated genomic
position so this first figure is just a
quantification of the NF kappa-b
inhibition that we observed so just like
visual you see lots of green cells you
can see by quantifying this we saw 80 to
90% effective inhibition of the pathway
for the T ret and ikk alpha knockout
then we did next-gen sequencing to look
at actual in del formation by those two
guide RNAs as you can see we had over
95% genomic editing with T rad and 85%
with ikk alpha so excellent correlation
of that knockout with the phenotypic
penetrance
we then expanded those cells for 14 days
to get enough to run a Western blot to
look at protein levels so for untreated
cells we had very strong bans for both
target proteins and the knockout cells
as expected and very nice to see there's
clearly no ban that's visible
you know at this point we're pretty
certain that our results were real you
know the knock out of the target gene
was effectively blocking and if kappa-b
activation we did one more verification
on these hits and this time stepping
away from the beta lactamase reporter
system completely and just looking at NF
kappa-b itself so we know that in the
presence of PMF alpha NF kappa-b will
activate and translocate to the nucleus
so in untreated cells that's exactly
what we see here we see green
cytoplasmic NF kappa-b in the upper
panel and upon treatment with TNF alpha
it becomes nuclear in the lower panel
but in our t red and ikk alpha knockout
it's very clear that this pathway is
being disrupted as shown by the lack of
the green nuclear NF kappa-b
in the presence of TNF alpha in those
lower panels so this type of orthogonal
verification is really essential to any
kind of hit analysis following a screen
so our conclusions from this pilot study
we're really very encouraging
we had highly penetrant robust
phenotypes and we were able to
accomplish this without the requirement
of enriching with selection markers we
had excellent efficiency of knockout as
measured at the genomic level and this
knockout showed really good correlation
with our cellular phenotypes and then
lastly our strong hints were very easily
verified with orthogonal assays
my talk today is to review some really
promising results from a collaborator
who used the lengthy array libraries to
do CRISPR screening for drug discovery
so this is a published example of an
early beta tester who was working with
the Atlantean library to find potential
therapeutic targets dr. Simone Sydney is
a pathologist at Lori's Children's
Hospital in Chicago and dr. shreddy
studies at pediatric cancer called
malignant Reptoid tumor or MRT this is a
universally lethal disease it's rare
only about 60 infants per year are
diagnosed but it is the most frequent
cause of tumors in infants under six
months of age 90 percent of the cases
occur in children under 3 years of age
so really as you can imagine a really
horrible prognosis being a pathologist
dr. shred knee has a collection of Selin
tissue samples that she's used in her
research to try to identify potential
new therapeutic targets for this patient
population that has a very urgent need
however using traditional gene
expression techniques she has not yet
identified she had not yet identified
any potential targets now about three
years ago dr. shreddy participated in
our beta test program and we provided
her with the lengthier a guide RNA
library targeting 160 gene targets from
the human kinase so I'm not going to
repeat all of the optimization steps
that were essentially the same as what I
showed in our pilot study but I do want
to hit a lot of the highlights of this
screen so she utilized bone cells which
were established from a patient rhabdo
tumor tissue the upper figure here is
from the transduction optimization using
GFP expressing control guide RNA named Z
generally B cells exhibited very high
transflexion transduction efficiency Mon
cells that stabili expressed cast 9 were
generated and in this case they've
worked with the stable expressing
population rather than go through those
steps for clonal selection and and
clonal characterization these Mon casts
9 cells were transduced in 96-well
dishes with guide RNA targeting 160
different kinases and then expanded
under selection for 7 days stealth were
then transferred in equal numbers to 12
well plates and the time to reach
confluence was measured
so the goal of the screen is to identify
genes that when knocked out would slow
the growth of patient-derived mrt cells
following all that number of divisions
so this pie chart shows the distribution
of that proliferation asked a results
for all hundred and sixty genes and the
controls this is this is relevant to
therapeutic development in the sense
that slower growth of a tumor means more
time for chemotherapy or other anti
tumour treatments to take hold so 70% of
the gene study to reach confluence in
seven to ten days a smaller subset took
a bit longer eleven and twelve days but
the genes of highest interest to this
team were the eight kinase is that when
they were knocked out took at least
fourteen days to reach confluence plk
four which was the top hit took 22 days
important is plk for in these cells this
gene had not come up in any prior
studies using differential expression
analysis but in normal brain tissue or
non embryonal brain tumor tissues
compared to brain tumors there is no
there is excuse me if there is
significant difference in pol k for
expression levels both when measured by
microarray analysis shown on the figure
on the left or by qPCR shown on the
right this differential expression
really strengthens the case for POF case
four as a relevant target in these
embryonal brain tumors
dr. shred knee then further demonstrated
that knock out of plk for resulted in
significant reduction of a marker for
cell proliferation ki67 you can see that
above in the production in the dark red
color in the cell image which is then
quantified in the bar graph again
showing a significant difference between
the Mon cast nine cells with and without
the pol k4 guide RNA furthermore knock
out of PL k4 also reduced the malignant
tendencies of the cells as shown by this
clone of Jena Cafe so spells again with
the PL k4 knockout compared to the the
untreated cast 9 mo cells had a reduced
capacity to generate colony forming
units
the team then stepped away from Chris
forecast nine and went on to test a
compound a specific top-4 inhibitor vfi
494 five the CFD effects could be
repeated this is a very common follow-up
strategy for lots of function screens
using CRISPR to look for orthogonal
results using si RNA or a known chemical
inhibitor of your target gene we're here
I'm showing you that they got very
similar responses in that Kelowna genic
assay not just in the Mon cells that
also in three other cancers you can see
the very significant impact on the
ability of these cells to generate those
colony forming units when they're
treated with the pl case for inhibitor
later that same year doctor shred knee
pushed this work even further and
published a follow-up paper to further
validate these findings this time using
an animal model of MRT it was part of
this study they created a xenograft
model using nude mice and injecting
patient MRT cells into their brains to
establish tumors the mice were then
treated with that same pops4 inhibitor
BF i-494 v and it was found to reduce
the size of the tumors and extend the
life of those mice
so these very encouraging results took
dr. shreddin II and her team to the next
logical step which was to look at how to
leverage this as a potential anti-cancer
treatment in patients so late last year
dr. shred nee and her team published
these results of an evaluation looking
at a wider range of inhibitors in a
political model of embryonal tumors so
the study's goal was to understand the
potential of available T looking for
inhibitors for treatment of these rabid
Lloyd tumors although they had mouse
model data showing that you know that
one of these molecules was effective
there's much more work that needs to be
done to determine a compound suitability
for use in humans especially if it
requires crossing the blood-brain
barrier so the author's evaluated eight
different PKI or protein kinase
inhibitor compounds in a preclinical
model with regard to their anti-cancer
properties and potential for brain
exposure I've put a few of the example
assays that they used to assess or score
these these different molecules they
looked at docking selectivity in the
catalytic domain of PL k4 they looked at
the BBB permeability index which is a
way to measure the capability to
penetrate the blood-brain barrier and
then also looked at inhibition of kinase
activity and in doing these acids they
look not just at the PL k4 target but
they looked at a much wider range of
kinase is to determine potential for
cross reactivity now I'm not going to
get into any of these analyses in any
depth it would simply take too long and
it's really kind of getting too far
afield of functional genomics but I do
want to show just one figure from this
paper that's a familiar assay from what
we just looked at so here you see that
same colony-forming assay as we saw in
the initial screening paper this time
used across five embryonal tumor cell
lines with three of the eight compounds
that were being assessed so in each data
set the cells on the Left are untreated
and the cells on the right are treated
with the corresponding inhibitor as you
can see the first two compounds were
effective in some cell types but not all
whereas TFI 447 on the right had pretty
complete
inhibition of colony formation in all
five tumor loins
as I said a minute ago a deep dive here
just is not possible I'm going to go
right to there staring conclusions and
if you're curious I really encourage you
to look more at this paper I certainly
learned a lot from it so although my
previous slide made it look like CFI 400
437 might be a good candidate it as well
as the compounds like that in that mouse
model turned out to not be optimal for
brain exposure in doing those
permeability tests and and all of the
others tested had shortcomings as well
either poor activity with good brain
penetration or vice versa so the
author's were able to conclude that a
selective pha-4 inhibitor which
favorable brain exposure properties
could definitely be beneficial for the
treatment of these brain tumors that
show POC for overexpression they also
concluded the strong need to improve the
existing inhibitors for better
selectivity and brain exposure or to
develop new ones that have these desired
characteristics so in essence they
didn't find a silver bullet but they do
still believe to looking for to be a
valid target for these embryonal brain
tumors
now just to close up on this particular
story I borrowed this slide from one of
the RD scientists in our group who
presented this paper at a journal Club
and I felt like it nicely captured not
just the extent of the work required
following target identification it also
shows the degree to which the thermo
Fisher Scientific products and services
that are shown in blue were able to play
a part in these efforts that go well
beyond that initial NT array screen the
scientists Illustrated these as lanters
kind of helping to light the way along
this path and I feel like this visual
kind of helps bring things full circle
back to their Mo's mission of helping
our customers to make the world
healthier cleaner and safer and seeing
this story come this far certainly you
know gives me hope
you know when I'm able to see it go
beyond a functional genomic screen and
and into this space where we can truly
see a therapeutic benefit
so I hope you've taken away something
useful from today's session I stayed
away from a deep dive on the entire
portfolio but hopefully gave you an idea
of the breadth of tools available to you
from thermo for crisper cast 9 to meet
virtually any experimental need from the
examples I've shown you hopefully
appreciate the power of functional
genomic screening as a method for
discovery but also came away with the
importance of proper optimization and
use of controls for reproducible results
and then lastly how the Lenti array
CRISPR libraries are effective
high-throughput loss-of-function
screening tools or pathway analysis and
drug discovery and so with that I'll
thank you again for joining take any
questions that have come in and turn it
over to Matt for those questions
you
thank you very much that was great but a
lot of questions come in so we'll get
right to those if you still have a
question that you'd like to ask please
do so now just click the ask a question
box locate on the far left side side of
your screen
our first question came in kind of early
in the presentation so you might have
already addressed this but why should
one use lentiviral guys instead of
synthetic guides
oh sure um there is a slide on this but
yet sometimes these come in before they
we get to it um and it really is very
often going to be a matter of which one
is a better fit for your experiment but
also preference can play in that as well
so both the lent array and the true
guide synthetic guides will give good
knockout right they're designed with the
same algorithm synthetic guides as
delivered with cast 9 protein is really
optimal for experiments where you want
the CRISPR components to be transient in
this cell where you you don't want any
ongoing expression of the guide and
there's no need to do any kind of
selection or enrichment of the edited
cells that that transient approach is
also really optimal if you're creating
an engineered cell line because you
don't want any again you don't want that
residual components in the cell the
lentiviral guys give you that additional
advantage of being self delivering you
know there's no transfection or agents
needed they can be used very often in
cells that are otherwise resistance to
transfection reagents and then of course
they have the the use of those
antibiotic resistance markers to do the
enrichment and both formats can be used
in an arrayed you know layout for
screening so really you just kind of
need to do a checklist of your cells
characteristics you know your as a
requirements and your own experimental
goals to kind of determine the best
option
awesome thank you um why don't Pawlenty
array guys Express GFP so that there's a
visual indication of their delivery oh
right I gosh I might not have said this
in the in appreciation
so we deliberately chose not to express
GFP or any fluorophore on the guide
really due to the potential for
interference in reporter assays or you
know any other reason you might have
stabili Express to work for than
yourself
we wanted to make sure that researchers
had all available channels open for
their experiments so you can imagine if
you think about that NF kappa-b si
anything green or blue that was
expressing from the guide RNA would have
made it impossible to use that reporter
system we we do as I as I showed have
the GFP on are controlled so they can
still be used like on every plate during
a screen or during that optimization
phase to help identify the best
conditions but there's nothing in being
expressed that will get in the way of
the actual screen
awesome thank you next question we have
here is is it required to do clonal
isolation when making your caste 19
expressing cell line yeah and I showed
examples of both doing clonal and using
a population I think it's still kind of
a mixed bag in terms of you know
opinions and results of using kind of
that parental or mixed cell line versus
doing clonal isolation so one school of
thought is that expression is more
consistent and can be monitored more
easily when you're working with a clonal
line
so once you've characterized it you can
very easily monitor changes but on the
flip side a mixed population kind of
gives you the advantage of no single
incorporation event being the same in
every cell so any possible bias from you
know disruption in the genome is going
to be diluted out I've also heard that
not all cell types are amenable to you
know kind of the isolation and the steps
required for doing clonal cell lines so
obviously you need to do what keeps
yourself happy and if that means keeping
them kind of in a heterogeneous mix and
you do honestly I've seen publications
and excellent results with both so I
think it matters kind of how much you
want to utilize that caste line version
of your cells over time and you know
kind of your comfort level with with
potentially heterogeneous levels of
caste and expression from from cell to
cell
awesome um next question we had here is
uh what kind of stability data do we
have on the lentiviral guides oh we have
data showing out to three years so far
with no loss in tighter this of course
is using all the recommended you know
storage conditions of keeping them up
minus eighty we haven't gone further out
than that yet timewise really because
the product isn't old enough
as with any Lenti viral particles the
biggest risk to stability or really
maintaining that functional titer is
avoiding freeze thaws so for instance
with the library that we deliver we do
that in two aliquot of 50 microliters
and the recommendation is to make
daughter plaits immediately upon arrival
so they only need to take them out of
the freezer when it's time to do your
screen and the and the others can can
stay happy in frozen
awesome thank you next question here
oops that just clicked away for a second
um you said that people will use si RNA
as a follow-up for the screening results
could you elaborate on this a little bit
more RSI RNA is the best tool for this
particular follow-up
yeah and then it's not like it's not
about best it's about if you have a
knockout result that you have reason to
believe results in an interesting
phenotype it's nice to step away from
kind of that crisper cast lying system
and say are there other ways I can
induce a loss of function in these cells
to verify these results and make sure
it's not you know some element of
crisper somehow you know that might be
causing it so sRNA is a kind of
tried-and-true way of knocking down a
gene expression you know at the mRNA
level so by moving from crisper cast 90s
RNA you now are working at the mRNA
level instead of at the genome level you
know you're stepping away from anything
involving a nucleus so you can have kind
of an orthogonal loss of function system
so if the SRA results agrees with your
CRISPR knockout result you can feel
pretty confident that the result you're
seeing you know the phenotype you're
seeing is because you have reduced that
genes expression but with that being
said it is entirely possible as well
that those results might not agree now
that does not mean that it's not a real
result it might mean that the phenotype
you saw for instance required complete
knockout whereas we know that RNA I
leave some residual level of expression
and maybe that wasn't enough to push
towards your phenotype so that doesn't
mean the hit is a real it just might
mean that s RNA wasn't the right tool
for that particular validation but when
they do agree it's a pretty good data
point to have to show that different
ways of lots of functions they'll give
you the same phenotype
thank you ah next question we had here
was what about getting individual guides
into the well and I think that's in
reference to that since this is an array
of pools into a single of a single of
guys into first single gene as their
individual guide options right okay so
for these lengthy array libraries that I
showed like the kinase library the ones
used in the in the last couple of
experiments we do pool for up to four
guides expressing different guides but
targeting the same gene but if you want
individuals if you want just a single
guide as a link about construct we can
do that for custom collections so that
way you can get you know one or more
different guides per gene in different
Wells targeting your genes of interest
and then just to be clear in the
glycerol stock option that I mentioned
those are always provided as one guide
per well it's only the Lenti viral
particles that we ever do some as a pool
awesome you think you got one or two
more in yeah I know we've had you
talking for for about an hour let's find
one more yeah great alright about about
selection and and delivering one or both
vectors oh yeah I think that's this one
here I'm okay so it's okay yeah so if
you deliver cast nine via one vector and
the guide RNA on another vector is it
possible for only one of the vectors to
get rid of the cell yeah so of course
it's possible you know so generally
speaking it is that's why it's
recommended for screening especially
that you would produce a cast nine
stable cell line certainly the only
delivery variable you have is with with
that guide RNA but if you do a code
transduction with the cast nine and the
guide as I said of course it's possible
only one gets in so then you could just
do you know selection with both of
antibiotic resistance markers but you
may not even need to do selection at all
you might just be able to directly assay
for knockout with the assumption that
enough of your cell population got both
the cast nine and the guide and you're
able to see it so some of this is going
to depend on the overall efficiency
our final comments here and I just
wanted to say before we go I want to
thank Thank You Louise for for your
great presentation I think our audience
for joining us today as I said in the
opening questions that we did not get
time to answer or any of those that come
in from during the on demand period will
be addressed by email that you provided
during your registration we'd like to
thank lab roots for hosting this for us
and thermo Fisher Scientific for
underwriting today's educational webcast
this can be viewed on-demand in the
future lab roots will alert you by email
when this is available for replay and we
encourage you to share that with your
colleagues who have may have missed
today's a live event and with that I
want to thank you all for joining and
hope you guys have a great rest of your
day
