Team:FCB-UANL/Engineering
SECOND CYCLE
THIRD CYCLE
FOURTH CYCLE
WESTERN BLOTS
PURIFICATIONS
FOAM TESTS
MODELS
FUTURE
REFERENCES
This year, we divided our wet lab efforts into two important stages. First, we developed the
molecular protocols needed for transforming bacteria with our synthetic DNA (for further
explanation go to our results section ).
Then, we engaged into a cycle of continuous Learning and improvement of the expression of
our proteins in our transformed bacteria. The complete laboratory protocols used this year
can be found in the next file.
After we successfully transformed three E. coli Top 10 strains with the vector pSB1C3 containing Rsn-2 (BBa_K3498009 ) and Rsn-3-5 (BBa_K3498010 , BBa_K3498011 , BBa_K3498012 ) DNA respectively (for further information of the parts visit our project description section , and for the mentioned process visit our results section ), the second part of our biofoam creation was the Ranaspumins production and characterization. This step was a complete new experience for us, where every experiment and its analysis represented a new knowledge. According to the results of the experiments and our models' predictions, we adjusted the experiments and started over several times, fulfilling the engineering cycle.
Our main objective was to produce the core components of firefighting biofoam by successfully transforming E. coli Top 10 with the vectors containing our Ranaspumin DNA genes Rsn-2 and Rsn-3-5, and achieving their production. However, we also aimed to determine the best conditions for protein expression, using both models and experimental results (more details are available in our model section ) and test out the effectiveness of our firefighting biofoam.
Here we report, step by step, the whole process for constructing our foam: from the clonation and molecular techniques, going through the characterization of the Ranaspumins induction, and finally testing out the foam properties for its proposed implementation section .
After we successfully transformed three E. coli Top 10 strains with the vector pSB1C3 containing Rsn-2 (BBa_K3498009 ) and Rsn-3-5 (BBa_K3498010 , BBa_K3498011 , BBa_K3498012 ) DNA respectively (for further information of the parts visit our project description section , and for the mentioned process visit our results section ), the second part of our biofoam creation was the Ranaspumins production and characterization. This step was a complete new experience for us, where every experiment and its analysis represented a new knowledge. According to the results of the experiments and our models' predictions, we adjusted the experiments and started over several times, fulfilling the engineering cycle.
Our main objective was to produce the core components of firefighting biofoam by successfully transforming E. coli Top 10 with the vectors containing our Ranaspumin DNA genes Rsn-2 and Rsn-3-5, and achieving their production. However, we also aimed to determine the best conditions for protein expression, using both models and experimental results (more details are available in our model section ) and test out the effectiveness of our firefighting biofoam.
Here we report, step by step, the whole process for constructing our foam: from the clonation and molecular techniques, going through the characterization of the Ranaspumins induction, and finally testing out the foam properties for its proposed implementation section .
FIRST CYCLE (Rsn-2 pSB1C3)
FIRST ITINERATION: DESIGN
Last year, the expression model of the FCB-UANL team 2020 (1) had already predicted
that to have an optimal expression of Ranaspumins, a plasmid of low number of copies
was necessary. In order to validate these results, we Designed the first cycle of
experiments.
Aiming to express Rsn-2, we inserted the gene in our vector of high number of copies pSB1C3. According to the protocol described by Meyer and his collaborators (2), we inoculated with 1 mL of an overnight E. coli Top 10 culture in 100 mL of LB medium, adding a final concentration of vanillic acid of 100 mM. This culture was grown for 2 hours at 200 rpm and 37°C.
Aiming to express Rsn-2, we inserted the gene in our vector of high number of copies pSB1C3. According to the protocol described by Meyer and his collaborators (2), we inoculated with 1 mL of an overnight E. coli Top 10 culture in 100 mL of LB medium, adding a final concentration of vanillic acid of 100 mM. This culture was grown for 2 hours at 200 rpm and 37°C.
BUILD
The induced culture was incubated at 37°C with constant agitation at 200 rpm and
37°C for 12 hours.
TEST
We collected a 1mL sample every two hours for analysis in SDS-PAGE gel,
which is shown in the next image.
LEARN
We observed there was no Rsn-2 expression, which validated the
predictive model mentioned above. Thus, we needed to repeat the
experiment using our vector of low number of copies: pSB3K3.
SECOND CYCLE (Rsn-2 pSB3K3)
FIRST ITINERATION: DESIGN
With this knowledge, we repeated the past experiment for 24
hours, but this time using our low number of copies of vector on this link pSB3K3.
At this time, the expression model for Ranaspumins production (explained in our model section ) had already predicted that the best production was obtained with 100 mM and 1000 mM of inducer, achieving a steady production since the first pair of hours after induction. With that information, we decided to use 100 mM and 1000 mM of inducer for our next set of experiments. The overall culture conditions were the same used in the first cycle: constant agitation at 200 rpm and 37°C).
At this time, the expression model for Ranaspumins production (explained in our model section ) had already predicted that the best production was obtained with 100 mM and 1000 mM of inducer, achieving a steady production since the first pair of hours after induction. With that information, we decided to use 100 mM and 1000 mM of inducer for our next set of experiments. The overall culture conditions were the same used in the first cycle: constant agitation at 200 rpm and 37°C).
BUILD
Based on the model predictions, we collected a 1mL sample
for the culture induced with 100 mM and 1000 mM
respectively, at 4, 6, 8, 10, 12, 20, 22, and 24 hours for
their analysis on a SDS-PAGE gel, which is shown in the next
image.
TEST
The concentrations of the expressed Ranspumin were
determined by the pixel analysis program, ImageJ, which
analyzes the difference between the density of pixels in
the bands of an image from a SDS gel. The first step was
to calibrate the program to a set of density standards,
this can be done with the Calibrated Step Tablet
provided in the ImageJ website (3)
Then, the program was tested out with an standar SDS gel, running different known concentrations (0.3, 0.1, 0.06, 0.03 and 0.01 mg/mL) of BSA according to Alonso and her collaborators (4). The final step was to analyze the SDS-PAGE gel and collect the results, for the complete analysis results you can see the complete file by clicking here .
Then, the program was tested out with an standar SDS gel, running different known concentrations (0.3, 0.1, 0.06, 0.03 and 0.01 mg/mL) of BSA according to Alonso and her collaborators (4). The final step was to analyze the SDS-PAGE gel and collect the results, for the complete analysis results you can see the complete file by clicking here .
LEARN
After analyzing the concentrations of the protein,
we realized the expression was higher at 20, 22 and
24 hours, but started to be significant eight hours
after induction. The obtained results are shown in
the following table, where the highest
concentrations are highlighted.
| Rsn-2 induction 100 mM and 1000 mM | ||
| Condition | Concentration (mg/mL) | Peak |
| 100 mM - 8 hours | 0.1456 | 18.66 |
| 100 mM - 20 hours | 0.0911 | 13.606 |
| 100 mM - 20 hours | 0.3701 | 39.489 |
| 100 mM - 22 hours | 0.0794 | 12.522 |
| 100 mM - 22 hours | 0.4472 | 46.632 |
| 100 mM - 24 hours | 0.0770 | 12.299 |
| 100 mM - 24 hours | 0.6014 | 60.931 |
This behavior drastically differed from the
one predicted by our model. For this reason,
the gathered data was essential to feed and
improve our model, making the proper
adjustments that are detailedly described in
our model
section .
CYCLE 2, SECOND ITERATION: DESIGN
Since the difference between the
concentrations with 100 and 1000 mM
was huge, we carried out another
experiment with different final
concentrations of vanillic acid
trying to find out if there was a
more functional concentration of
inducer. Hence, we made a second
iteration of cycle two. The overall
culture conditions were the same
previously used: constant agitation
at 200 rpm and 37°C).
BUILD
For this iteration, we used 100,
200, 400, 600, 800, and 1000 mM
of our inducer, and only
collected 1 mL sample at 20 and
24 hours for their analysis on a
SDS-PAGE gel, which is shown in
the next image.
TEST
After the analysis with
ImageJ, we concluded that
the best conditions for
Rsn-2 production were 800 mM
for 20 hours after the
induction. The results are
shown in the following
table. The highest
concentrations are
highlighted.
| Rsn-2 induction 100 mM to 1000 mM | ||
| Condition | Concentration (mg/mL) | Peak |
| 100 mM - 20 hours | 0.202 | 7.031 |
| 200 mM - 20 hours | 0.0435 | 9.199 |
| 4000 mM - 20 hours | 0.1171 | 16.017 |
| 600 mM - 20 hours | 0.3929 | 41.6 |
| 800 mM - 20 hours | 0.4253 | 44.608 |
| 1000 mM - 20 hours | 0.2948 | 32.501 |
| 100 mM - 24 hours | 0.0655 | 11.233 |
| 200 mM - 24 hours | 0.0744 | 12.056 |
| 4000 mM - 24 hours | 0.1148 | 16.138 |
| 600 mM - 24 hours | 0.2081 | 24.46 |
| 800 mM - 24 hours | 0.2099 | 24.624 |
| 1000 mM - 24 hours | 0.2376 | 27.199 |
LEARN
In order to ensure our
results were correct, we
ran a SDS gel comparing
Rsn-2 production induced
with 800 mM of vanillic
acid for 20 hours,
against its production
without adding any
inducer. The results can
be seen in the following
image.
As observed, there is no expression of Rsn-2 without the addition of the inducer, meaning there is no basal expression.
As observed, there is no expression of Rsn-2 without the addition of the inducer, meaning there is no basal expression.
THIRD CYCLE (Rsn-3
pSB3K3)
FIRST ITINERATION: DESIGN
Just as with
Rsn-2, we used
the first
results of our
model to shape
our production
experiments,
hence, we
decided to check
out different
concentrations
of vanillic acid
for 8 hours and
analyze it with
a SDS gel. The
overall culture
conditions were
the same
previously used:
constant
agitation at 200
rpm and
37°C).
BUILD
We collected
a 1mL sample
for the
culture
induced with
100, 400,
600, and 800
mM of
vanillic
acid 8 hours
after
induction,
for their
analysis on
a SDS-PAGE
gel, which
is shown in
the next
image.
TEST
The
production
of Rsn-3
was
determined
using
ImageJ.
The
obtained
results
are
shown in
the
following
table,
where
the
highest
values
are
highlighted.
| Rsn 3 | ||
| Condition | Concentration (mg/mL) | Peak |
| 100 mM - 8 hours | 0.3006 | 33.042 |
| 400 mM - 8 hours | 0.4366 | 45.648 |
| 600 mM - 8 hours | 0.3287 | 35.647 |
| 800 mM - 8 hours | 0.5794 | 58.891 |
| 1000 mM - 8 hours | 0.6014 | 60.932 |
LEARN
These
experiments
revealed
that
the
best
inducer
concentration
was
1000
mM.
Due
to
this,
we
decided
to
make
a
second
iteration
of
this
cycle,
with
the
aim
of
better
understanding
the
functioning
of
our
system’s
production.
CYCLE 3, SECOND ITERATION: DESIGN
The
next
readjustment
was
to
extend
the
experiment
duration
until
24
hours,
since
we
wanted
to
find
the
best
induction
time
with
a
final
concentration
of
1000
mM
of
vanillic
acid.
The
overall
culture
conditions
were
the
same
previously
used:
constant
agitation
at
200
rpm
and
37°C).
BUILD
We
collected
a
1mL
sample
for
the
culture
induced
with
1000
mM
of
vanillic
acid
at
4,
6,
8,
10,
12,
20,
22,
and
24
hours
after
induction
for
their
analysis
on
a
SDS-PAGE
gel,
which
is
shown
in
the
next
image.
TEST
We
observed
that
at
12
hours
after
induction.we
had
our
highest
protein
production.
The
obtained
results
from
ImageJ
are
shown
in
the
following
table.
The
highest
values
are
highlighted.
| Rsn 3 | ||
| Condition | Concentration (mg/mL) | Peak |
| 100 mM - 8 hours | 0.1904 | 22.83 |
| 1000 mM - 10 hours | 0.1471 | 18.807 |
| 1000 mM - 12 hours | 0.5070 | 52.18 |
| 1000 mM - 20 hours | 0.2381 | 27.238 |
LEARN
These
continuous
rounds
of
new
information
fed
the
expression
model,
which
offered
essential
feedback
suggesting
the
conditions
in
which
the
production
would
be
more
efficient.
As
it
can
be
observed,
this
model
was
of
great
importance
since
it
saved
us
effort
and
time.
For
reading
the
other
side
of
this
loop
of
information,
visit
our
model
section
.
FOURTH
CYCLE
(Rsn-3-5
pSB3K3)
FIRST ITENARATION: DESIGN
Just
as
with
Rsn-2
production,
the
expression
model
for
Ranaspumins
production
had
already
predicted
that
the
best
production
was
obtained
with
1000
mM
of
inducer,
achieving
a
steady
production
since
the
first
pair
of
hours
after
induction.
Hence,
we
decided
to
repeat
the
100
and
1000
mM
experiment,
but
this
time
for
Rsn-3-5
for
24
hours.
The
overall
culture
conditions
were
the
same
previously
used:
constant
agitation
at
200
rpm
and
37°C.
BUILD
Based
on
the
model
predictions,
we
collected
a
1mL
sample
for
the
culture
induced
with
100
mM
and
1000
mM
respectively,
at
4,
6,
8,
10,
12,
20,
22,
and
24
hours
for
their
analysis
on
a
SDS-PAGE
gel,
which
is
shown
in
the
next
image.
In
addition,
we
added
a
sample
of
Rsn-3
induced
with
600
mM
of
vanillic
acid
at
24
hours
(the
same
culture
conditions
previously
mentioned)
to
visually
compare
the
results
of
the
production.
TEST
The
obtained
SDS-PAGE
gel
was
analyzed
to
determine
the
concentrations
using
ImageJ.
The
obtained
results
are
shown
in
the
following
table.
The
highest
values
are
highlighted.
| Rsn3-5 induction 100 mM / 1000 | ||
| Condition | Concentration (mg/mL) | Peak |
| 100 mM - 20 hours | 0.2246 | 25.991 |
| 1000 mM - 20 hours | 0.1215 | 16.425 |
| 100 mM - 22 hours | 0.0896 | 13.474 |
| 1000 mM - 22 hours | 0.0525 | 10.025 |
| 100 mM - 24 hours | 0.1246 | 16.719 |
| 1000 mM - 24 hours | 0.0812 | 12.691 |
LEARN
Once
again,
we
observed
a
considerable
difference
between
100
and
1000
mM,
but
this
time
the
concentration
was
higher
at
100
mM
of
inducer
and
in
fewer
hours.
With
these
results,
we
made
a
second
iteration
of
this
cycle,
adjusting
the
parameters
to
better
understand
the
expression.
CYCLE 4, SECOND ITERATION: DESIGN
We
repeated
the
experiment
with
lower
concentrations
of
inductor,
using
8
hours
as
indicated
on
the
first
approach
of
our
model.
The
overall
culture
conditions
were
the
same
previously
used:
constant
agitation
at
200
rpm
and
37°C.
BUILD
We
collected
a
1mL
sample
for
the
culture
induced
with
10,
25,
50,
and
75
mM
of
vanillic
acid
at
8
hours
after
induction
for
their
analysis
on
a
SDS-PAGE
gel,
which
is
shown
in
the
next
image.
TEST
We
obtained
the
following
concentrations
of
the
expressed
Ranaspumins
using
ImageJ.
The
highest
values
are
highlighted.
| Rsn 3-5 | ||
| Condition | Concentration (mg/mL) | Peak |
| 10 mM | 0.0503 | 9.827 |
| 25 mM | 0.0402 | 8.892 |
| 50 mM | 0.0785 | 12.445 |
| 75 mM | 0.0791 | 12.493 |
LEARN
The
analysis
with
ImageJ
revealed
that
the
best
inducer
concentration
was
75
mM.
Once
we
determined
the
best
inducer
concentration,
we
decided
to
make
a
third
iteration
of
the
cycle
to
get
to
know
the
time
of
the
highest
protein
production.
CYCLE 4, THIRD ITERATION: DESIGN
Finally,
we
extended
the
experiment
for
24
hours.
The
overall
culture
conditions
were
the
same
previously
used:
constant
agitation
at
200
rpm
and
37°C.
BUILD
We
collected
a
1mL
sample
for
the
culture
induced
with
75
mM
of
vanillic
acid
at
4,
6,
8,
10,
12,
20,
22,
and
24
hours
after
induction
for
their
analysis
on
a
SDS-PAGE
gel,
which
is
shown
in
the
next
image.
TEST
The
SDS
gel
was
analyzed
to
determine
the
concentrations
using
ImageJ.
The
obtained
results
are
shown
in
the
following
table.
The
highest
values
are
highlighted.
| Rsn 3-5 | ||
| Condition | Concentration (mg/mL) | Peak |
| 75 mM - 10 hours | 0.0974 | 14.193 |
| 75 mM - 12 hours | 0.2014 | 23.843 |
| 75 mM - 20 hours | 0.1317 | 17.372 |
| 75 mM - 22 hours | 0.1206 | 16.341 |
| 75 mM - 24 hours | 0.1296 | 17.181 |
LEARN
Finally,
we
noticed
that
the
major
protein
was
12
hours
after
the
induction
with
vanillic
acid.
As
occurred
with
Rsn-2,
this
data
fed
the
already
mentioned
expression
model
of
the
Ranaspumins,
which
can
be
found
in
our
model
section
.
WESTERN
BLOTS
For
validation,
we
realized
a
Western
Blot
analysis,
transferring
the
SDS-PAGE
gel
to
a
nitrocellulose
membrane.
The
obtained
results
are
shown
in
the
following
images.
As
shown
in
the
figures,
Rsn
3-5
is
not
appreciable
in
the
Western
Blot.
This
is
probably
due
to
the
small
amount
of
total
protein
production,
since
the
production
of
the
combined
Rsn
3-5
is
lower
in
comparison
to
Rsn-2
and
3,
as
previously
shown
in
our
production
results.
PROTEIN
PURIFICATIONS
Entering
this
stage
of
our
process,
we
purificated
every
Ranaspumin
using
a
Ni+
resin.
As
explained
in
the
protocols
document
provided
above.
The
SDS-PAGE
gel
is
shown
in
the
following
images.
Another
Western
Blot
was
made
to
verify
the
correct
purification
of
the
proteins,
shown
in
the
next
images.
As
last
time,
Rsn
3-5
is
not
visible,
but
a
low
intensity
band
in
the
normal
induction
and
the
purification,
as
seen
in
the
image.
FOAM
TESTS
Once
we
had
our
proteins
production
optimized,
we
carried
out
the
tests
to
characterize
the
foaming
properties
of
each
one
of
our
Ranaspumin
proteins.
The
general
objectives
were
to
determine
[1]
the
most
effective
method
for
foam
creation,
[2]
the
foamability
and
half-life
of
the
sonicated
proteins,
and
[3]
the
foamability
and
half-life
of
the
different
foam
solutions.
All
the
experiments
were
carried
out
in
environmental
conditions
(25°C),
the
complete
methods
and
results
are
explained
below.
Taking into consideration the evaluation of foaming compounds developed by Petkova (5), in which she applied agitation to corning tubes; we Designed our next set of experiments. Hence, we tested this method (hand shaking for 30 seconds) against the pressure release using a syringe (control). In addition, we also took into account the times for the study of surfactants and stabilizers. We used 24 hours given the natural Ranaspumins durability reported by Mackenzie (6) and the time used in literature (5). Since this time we wanted to test the effect of the surfactants against a solution with no surfactants on it, we used water as the negative control.
Taking into consideration the evaluation of foaming compounds developed by Petkova (5), in which she applied agitation to corning tubes; we Designed our next set of experiments. Hence, we tested this method (hand shaking for 30 seconds) against the pressure release using a syringe (control). In addition, we also took into account the times for the study of surfactants and stabilizers. We used 24 hours given the natural Ranaspumins durability reported by Mackenzie (6) and the time used in literature (5). Since this time we wanted to test the effect of the surfactants against a solution with no surfactants on it, we used water as the negative control.
DETERMINATION
OF
THE
BEST
FOAMING
METHOD
DESIGN
For
this
experiment,
we
used
15
mL
corning
tubes
containing
5
mL
of
each
of
our
sonicated
proteins
from
the
culture
media
with
the
optimized
conditions
previously
reported.
All
the
test
conditions
followed
the
general
conditions
explained
at
the
beginning
of
this
section.
The
aim
of
this
experiment
was
to
prove
if
the
agitation
(used
for
mechanical
firefighting
foams)
would
be
effective
with
our
components.
BUILD
We
measured
the
volume
of
foam
using
the
mL
scale
of
the
corning
tube
at
different
times
and
recorded
it.
TEST
In
the
following
image,
we
can
observe
the
initial
volume
(mL)
of
foam
and
the
initial
volume
(mL)
of
liquid
containing
our
proteins.
After
analyzing
the
results
it
was
found
that,
on
average,
the
stirring
method
generates
0.74
mL
more
foam
per
mL
of
initial
solution
compared
to
using
the
syringe.
This
is
shown
most
strongly
in
the
foams
of
Rsn-2,
which
generates
3.6
times
more
foam
with
agitation
than
syringe.
LEARN
Through
our
results
analysis,
the
agitation
proved
to
be
a
much
more
effective
method
than
the
use
of
the
syringe
for
the
creation
of
foam;
with
this
result
we
proved
Ranaspumin
proteins
must
be
efficient
for
a
mechanical
firefighting
foam,
since
agitation
is
the
best
foaming
method.
In
addition,
we
realized
the
vital
importance
of
standardizing
the
concentrations
of
the
concentrates.
Thus,
to
study
the
foamability
and
half-life,
the
initial
concentrations
will
be
controlled
during
the
following
studies.
CHARACTERIZATION
OF
THE
PROTEINS
PHYSICOCHEMICAL
FEATURES
DESIGN
Considering
our
previous
conclusions,
we
took
the
highest
concentrations,
obtained
in
our
characterization
of
the
Ranaspumins
induction
experiments
explained
above.
They
are
as
follows:
0.4253
mg/mL
of
Rsn-2,
0.5070
mg/mL
of
Rsn-3,
and
0.2014
mg/mL
of
Rsn-3-5.
The
correct
ratio
to
have
the
same
amount
of
protein
is
shown
in
the
table
above,
these
amounts
of
sonicate
will
be
diluted
to
perform
the
foamability
and
half-life
tests
at
the
same
protein
concentrations.
| Foam Solution | Rsn-2 | Rsn-3 | Rsn-3-5 |
| mL | 2.37 mL (1.01 mg) | 1.99 mL (1.01 mg) | 5.0 mL (1.01 mg) |
BUILD
The
experiment
was
performed
with
the
same
conditions
explained
in
the
past
experiment,
with
the
exception
of
the
specific
concentrations
shown
in
the
table
above
(1.01
mg/
5mL)
=
0.202
mg/mL
for
Rsn-2,
Rsn-3,
and
Rsn-3-5.
Here,
we
used
SDS
as
a
positive
control,
in
order
to
compare
our
foam
with
a
well-known
surfactant.
TEST
In
the
following
image,
we
can
observe
the
initial
volume
(mL)
of
foam
and
the
initial
volume
(mL)
of
liquid
containing
our
proteins.
As
expected,
water
did
not
create
foam,
while
SDS
produced
a
foam
with
a
volume
of
1.9
mL
per
inicial
volume.
Of
all
the
Ranaspumins,
the
Rsn-3-5
generated
the
greatest
amount
of
foam,
specifically
0.9
mL
per
mL
of
initial
sonicated
volume.
Followed
by
Rsn-2
and
Rsn-3,
with
0.8
times
the
initial
volume
in
foam.
Then,
it
can
be
observed
that
Rsn-3
has
a
very
similar
foamability
to
Rsn-2
under
the
same
concentrations.
In the next image, we show the volume of foam in mL generated by water, Rsn-2, Rsn-3, Rsn-3-5, and SDS at 12 hours.
Regarding
the
durability,
the
Rsn-2
sonicated
foam
dropped
after
510
minutes
(8.5
hours),
while
the
one
of
Rsn-3
sonicated
foam
passed
720
minutes
(12
hours)
of
experimentation
with
more
than
50%
of
initial
volume.
On
the
other
hand,
Rsn-3-5
sonicate
foam
passed
540
minutes
(9
hours)
of
experimentation
still
at
50%;
Finally,
positive
control
SDS
lasted
720
minutes
(12
hours)
with
74%.
This
supports
our
hypothesis
since
Ranaspumins
3,
4,
5
are
known
to
be
foam
stabilizers
based
on
their
lectins’
characteristics
making
the
foam
more
durable.
In the next image, we show the volume of foam in mL generated by water, Rsn-2, Rsn-3, Rsn-3-5, and SDS at 12 hours.
LEARN
In
terms
of
half-life,
Rsn-2
and
Rsn-3-5
showed
the
lowest
half-life
of
510
minutes
(8.5
hours).
On
the
contrary,
Rsn-3
presented
the
longest
half-life,
passing
12
hours
with
50%
of
the
initial
foam
volume.
CHARACTERIZATION
OF
THE
FOAMS
PHYSICOCHEMICAL
FEATURES
DESIGN
In
order
to
have
a
final
formulation
of
our
foam,
based
on
the
features
previously
describe,
we
Designed
different
foam
formulations
based
on
the
proportion
of
each
of
the
elements
(Rsn-2:
0.4253
mg/mL,
Rsn-3:
0.5070
mg/mL,
Rsn-3-5:
0.2014
mg/mL).
Hence,
we
made
the
following
formulations
to
make
the
proper
tests
and
determine
the
best
final
foam.
Solution 1: 1/3 sonicated of Rsn-2 culture and 1/3 of sonicated of Rsn-3, and 1/3 of sonicated of Rsn-3-5 culture:
Solution 1: 1/3 sonicated of Rsn-2 culture and 1/3 of sonicated of Rsn-3, and 1/3 of sonicated of Rsn-3-5 culture:
0.4253x=
0.5070y=0.2014z
x+y+z=5
Rsn-2=1.26
mL
Rsn-3
=1.06
mL
Rsn-
3-5=2.67
mL
Solution
2:
2/4
sonicated
from
Rsn-2
culture
and
1/4
sonicated
from
Rsn-3
culture
and
1/4
sonicated
from
Rsn-3-5
culture:0.4253x=
0.5070y+0.2014z
0.5070y=0.2014z
x+y+z=5
Rsn-2=2.02
mL
Rsn-3
=0.85
mL
Rsn-
3-5=2.13
mL
Solution
3:
3/5
sonicated
from
culture
Rsn-2
and
1/5
sonicated
from
culture
Rsn-3
and
1/5
sonicated
from
Rsn-
3-5
culture:0.4253x=
1.667
0.5070y+0.2014z
0.5070y=0.2014z
x+y+z=5
Rsn-2=2.59
mL
Rsn-3
=0.68
mL
Rsn-
3-5=1.72
mL
Solution
4:
SDS
Solution
with
the
same
concentration
as
protein
concentration
solution
3
(1.79
mg).
TEST
In
the
following
image,
we
can
observe
the
initial
volume
(mL)
of
foam
and
the
initial
volume
(mL)
of
liquid
containing
our
proteins.
Of
all
the
combinations,
the
Solution
3
generated
the
greatest
amount
of
foam,
with
0.9
times
the
initial
sonicated
volume.
This
was
followed
by
Solution
1
and
2,
with
0.8
times
the
initial
volume
in
foam.
As
in
all
the
past
experiments,
water
did
not
create
foam.
Meanwhile,
SDS
formed
a
foam
with
a
volume
of
1.9
times.
As
it
can
be
observed
in
the
image
below,
the
Solution
1
foam
dropped
after
630
minutes
(10.5
hours),
the
Solution
2
sonicated
foam
720
minutes
(12
hours),
and
finally,
the
Solution
3
foam
passed
600
minutes
(10
hours)
of
experimentation
still
at
50%.
Last,
the
positive
control
SDS
lasted
720
minutes
(12
hours)
with
74%
of
the
initial
volume.
Since
Rsn-3-5
are
known
to
be
foam
stabilizers
based
on
their
lectins’
characteristics,
it
can
be
explained
its
effect
on
the
foam
extended
durability.
In
fact,
the
most
durable
solution
is
the
second
one,
in
which
Rsn
3-5
are
found
to
a
greater
extent
(Rns-2
2/4,
Rsn-3:
1/4,
Rsn
3-5:
1/4.
However,
it
shows
less
foamability
than
the
foam
with
the
higher
amount
of
Rsn-2
(Solution
3,
Rsn-2:
2/3,
Rsn-3:
1/6,
Rsn
3-5:
1/6).
Learn
With
this
experiment,
Solution
3
was
chosen
due
its
large
foamability
and
lasting
half-life.
Then,
our
final
foam
composition
was
Rsn-2
at
a
concentration
of
60%
(vol/vol),
Rsn-3
at
a
concentration
of
20%,
and
Rsn
3-5
at
20%
of
the
concentrate.
Here,
even
though
Rsn-2
was
not
the
most
efficient
behavior
(compared
to
Rsn-3
and
Rsn-3-5),
we
noticed
that
it
has
to
be
the
most
abundant
protein
in
the
final
foam
formulation. If you want to learn more about the tests we made with the foam please visit ourproof of concept section.
This
is
probably
due
to
interactions
between
the
proteins,
but
further
research
is
needed
to
prove
this
hypothesis.
GENERATING
DATA
TO
FEED
OUR
MODEL
Modeling
is
a
very
important
part
of
the
development
of
a
project.
However,
in
some
cases
they
require
experimental
data
in
order
to
work
properly.
Next,
we
present
some
of
the
experimental
work
we
developed
to
feed
our
models;
the
detailed
information
of
how
we
used
the
experimental
outcomes
is
explained
in
our
model
section
.
MODELING
A
FED
BATCH
BIOREACTOR
FOR
THE
PRODUCTION
OF
RSN
2-5
USING
E. coli
For
this
simulation,
we
needed
a
growth
curve
of
our
E. coli
Top
10
cultures
with
the
production
genes
inserted.
The
curve
was
determined
experimentally
reading
the
absorbance
at
600
nM
of
different
samples
for
24
hours.
Then,
we
obtained
an
average
of
the
three
cultures.
With
this,
the
model
was
fed,
allowing
us
to
theoretically
up-scale
the
production
of
our
proteins.
For
more
information
about
this
model,
please
visit
our
model
section
.
OPTIMIZATION
OF
CULTURE
CONDITIONS
FOR
RSN
PRODUCTION
IN
E. coli
USING
SURFACE
RESPONSE
METHODOLOGY
On
the
other
hand,
we
also
developed
a
model
that
would
allow
us
to
optimize
the
following
culture
conditions
for
achieving
the
highest
Rsn
production:
inductor
concentration,
induction
time,
and
concentration
of
carbon
source
medium
components.
This
model
uses
a
Box-Behnken
Design
(BBD),
which
is
an
experimental
Design
based
on
the
evaluation
of
three
different
parameters
(the
mentioned
conditions),
with
three
different
values
each
going
in
a
scale
of
-1,
0
and
1.
In
order
to
optimize
the
Ranaspumins
production,
this
model
predicts
the
best
combinations
of
these
conditions.:
| Parameter | -1 | 0 | 1+ |
| Induction time | 2 hours | 3.5 hours | 5 hours |
| Inducer concentration | 100 mM | 350 mM | 600 mM |
| Glucose concentration | 0.5 g/L | 1.25 g/L | 2 g/L |
Every
parameter
combination
was
grown
at
37°C
at
200
rpm
for
20
hours
after
the
induction
time,
and
a
SDS-PAGE
gel
was
made
to
see
the
results,
which
are
shown
in
the
following
image.
Every parameter combination was grown at 37°C at 200 rpm for 20 hours after the induction time, and a SDS-PAGE gel was made to see the results, which are shown in the following image.
Every parameter combination was grown at 37°C at 200 rpm for 20 hours after the induction time, and a SDS-PAGE gel was made to see the results, which are shown in the following image.
AN
EYE
IN
THE
FUTURE
Even
though
we
accomplished
this
year’s
wet
lab
objectives,
the
work
is
far
from
over.
We
had
the
chance
to
start
the
experimental
testing
of
one
of
our
secondary
foam
components,
that
is,
the
optimization
of
surfactin
production
in
B.
subtilis
using
the
genetic
circuits
reported
in
our
project
description
section
.
We
were
able
to
assemble
the
surfactin
pieces
received
from
Twist,
and
to
transform
E. coli
Top10
bacteria
with
those
DNA
fragments
for
cloning
purposes.
In
the
future,
we
expect
to
use
this
assembly
to
transform
and
produce
it
in
B.
subtilis,
to
achieve
the
production
of
our
Minimum
Viable
Product
(explained
in
our
entrepreneurship
section
)
to
enter
the
market.
REFERENCES
(1)
FCB-UANL.
(2020).
Synbiofoam:
a
synthetic
alternative
to
fluorosurfactants.
https://bit.ly/3mlaf1W)
(2) FCB-UANL. (2020). Synbiofoam: a synthetic alternative to fluorosurfactants. https://bit.ly/3mlaf1W
(3) Schneider, C., Rasband, W. & Eliceiri, K. (2012). NIH Image to ImageJ: 25 years of image analysis. Natural Methods, 9, 671–675. doi:10.1038/nmeth.2089
(4) Alonso, S. Kraiem, H., Bouhaouala-Zahar, B., Bideaux, C., Aceves, C., & Fillaudeau, L. (2020). A protocol for recombinant protein quantification by densitometry. Microbiology Open, 6(9), 1175-1182. doi:10.1002/mbo3.1027
(5) Petkova, B., Tcholakova, S., Chenkova, M., Golemanov, K., Denkov, N., Thorley, D., & Stoyanov, S. (2020). Foamability of aqueous solutions: Role of surfactant type and concentration. Advances in Colloid and Interface Science, 276, 102084. doi:10.1016/j.cis.2019.102084
(6) Mackenzie, C. D., Smith, B. O., Meister, A., Blume, A., Zhao, X., Lu, J. R., Kennedy, M. W., & Cooper, A. (2009). Ranaspumin-2: Structure and Function of a Surfactant Protein from the Foam Nests of a Tropical Frog. Biophysical Journal, 96(12), 4984–4992. doi:10.1016/j.bpj.2009.03.044
(2) FCB-UANL. (2020). Synbiofoam: a synthetic alternative to fluorosurfactants. https://bit.ly/3mlaf1W
(3) Schneider, C., Rasband, W. & Eliceiri, K. (2012). NIH Image to ImageJ: 25 years of image analysis. Natural Methods, 9, 671–675. doi:10.1038/nmeth.2089
(4) Alonso, S. Kraiem, H., Bouhaouala-Zahar, B., Bideaux, C., Aceves, C., & Fillaudeau, L. (2020). A protocol for recombinant protein quantification by densitometry. Microbiology Open, 6(9), 1175-1182. doi:10.1002/mbo3.1027
(5) Petkova, B., Tcholakova, S., Chenkova, M., Golemanov, K., Denkov, N., Thorley, D., & Stoyanov, S. (2020). Foamability of aqueous solutions: Role of surfactant type and concentration. Advances in Colloid and Interface Science, 276, 102084. doi:10.1016/j.cis.2019.102084
(6) Mackenzie, C. D., Smith, B. O., Meister, A., Blume, A., Zhao, X., Lu, J. R., Kennedy, M. W., & Cooper, A. (2009). Ranaspumin-2: Structure and Function of a Surfactant Protein from the Foam Nests of a Tropical Frog. Biophysical Journal, 96(12), 4984–4992. doi:10.1016/j.bpj.2009.03.044
Our 2020-2021 iGEM project is generously supported by
