iGEM 2025 — Team asu

{% extends "layout.html" %} {% block title %}Notebook{% endblock %} {% block
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* [All Enzymes](#allenznb)
* [Cold-Adapted Enzymes](#coldadaptednb)
* [Protein Purification](#proteinpurifynb)
* [Lectin](#lectinnb)
* [Colorimetric Assay](#colorimetricnb)
* [Porcine Blood (Conversion and Crossmatch)](#porcinebloodnb)

# An In-depth Documentation of Our Project

Dive into our wet lab notebooks to explore the full progression of our
iGEM project. Each PDF offers an detailed account of our experiments,
including protocols, observations, results, and reflections that guided
the development of our project.

# All Enzymes Notebook

## A1 (AmGH36A) Notebook

## A2 (AmGH35A) Notebook

## A3 (AmGH95B) Notebook

## B1 (AmGH110A) Notebook

## B2 (AmGH20A) Notebook

# Cold-Adapted Enzyme Notebook

# Protein Purification Notebook

# Lectin Notebook

# Colorimetric Assay Notebook

# Porcine Blood (Conversion and Crossmatch) Notebook

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{% extends "layout.html" %} {% block title %}Engineering Success{% endblock %}
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* [Introduction](#engintro)
* [Wet Lab](#engcloningcycle)
* [Software](#dryeng)
* [Hardware](#hardeng)
* [References](#referenceseng)

# Introduction

Our wet lab team achieved engineering success by systematically applying
the Design–Build–Test–Learn (DBTL) cycle. While our project as a whole
aims to create a portable system to convert blood types A, B, and AB
into type O, this section highlights the
**iterative laboratory work** that allowed us to develop our
functional enzymes.

We documented the challenges we faced during cloning, expression, and
purification, the strategies we used to troubleshoot, and the lessons
learned at each stage. By showing these DBTL iterations, we demonstrate
not only the final outcomes but also the engineering process that made
them possible.

Our engineering journey focused on cloning and expressing five glycoside
hydrolases from *Akkermansia muciniphila*: AmGH36A (A1), AmGH35A
(A2), AmGH95B (A3), AmGH110A (B1), and AmGH20A (B2) (Jensen et al.,
2024). Each enzyme was designed, cloned, and tested through iterative
Design–Build–Test–Learn (DBTL) cycles, with troubleshooting at each step
to refine protocols. Visible pink coloration from the mScarlet-I served
as a marker of successful expression in T7 E. coli.

# Wet Lab

## 1. Cloning Cycles

Iteration 1: Initial One-Step Cloning of Enzymes

**Design**
Based on the size and structure of our synthetic DNA (gBlocks), we
designed our entire cloning strategy around Gibson Assembly (for A2, A3,
B2, B1) and MEGAWHOP (for A1). We anticipated a high-efficiency,
one-step build for all five enzymes into our P31 backbone.

**Build**
We performed the assembly reactions and transformed the resulting
constructs into NEB Stable E. coli for cloning and propagation.

**Test**
We verified successful assembly using colony PCR and Next Generation
sequencing. A2 and B2 were successfully cloned and verified on the first
attempt. A1 and B1 sequencing results showed a point mutation. A3 failed
to yield colonies.

**Figure 1.** A2 and B2 Successful Sequencing Results

Iteration 2: Troubleshooting A1, B1, and A3 Cloning

**Design**
Based on the failure, we designed new primers to overlap the point
mutation of A1 and B1. We also added a DPNI digest step to remove
template DNA. We repeated the Gibson Assembly for A3 with more
caution.

**Build**
We successfully corrected two previously unsuccessful constructs (A1 and
B1) by using the designed primers and then used PCR to amplify the
remaining gBlocks. A3 successfully yielded colonies on the LB plate. We
purified the plasmids and sent A1, A3, and B1 for sequencing. After
sequencing, the plasmids with the correct sequence were transformed onto
T7 Express cells.

**Test**
Final verification using gel electrophoresis and Next Generation
sequencing confirmed the correct sequence for A1 and A3. B1 still
exhibited a point mutation outside of the coding region, which would not
affect the protein expression. This achievement meant all five
engineered plasmids were ready for characterization assays.

**Figure 2.** A1, A3, B1 Successful Sequencing Results

**Learn**
This success validated our repair process. We achieved our goal of
building all five constructs by using data from a partial failure to
inform a successful change in our engineering strategy. We then
proceeded to the protein expression optimization cycle to ensure we
could produce the required amount of functional enzyme.

## 2. Protein Expression Cycle

Iteration 1: Autoinduction Media 50 mL Experiment

**Design**
We adopted 2 different autoinduction media protocols from Simplified
Autoinduction Media by The Bumbling Biochemist and Studier’s
Autoinduction media (Studier, 2005).

**Build**
We inoculated T7 Express cells transformed with A1, A2, A3, B1, and B2
directly into 50 mL tubes containing each type of media and incubated at
30°C for 24 hours.

**Test**
None of the enzymes turned pink in either medium.

**Learn**
We realized that 50 mL of culture volume was too large for visible color
development, as the expressed protein was too dilute to turn the entire
medium pink.

Iteration 2: Autoinduction Media 3 mL Experiment Trial 1

**Design**
We designed an improved experiment using only 3 mL of each media to
increase the chance of growing colonies. Colonies were grown a day
before inoculation with autoinduction media. We also tested them under
different time and temperature according to Table 1 to find the optimal
condition.

![Table 1. Testing conditions of 2 different media for protein expression](https://static.igem.wiki/teams/5679/engineeringsuccess/table-1-engineering-success.avif)

**Table 1.** Testing conditions of 2 different media for protein
expression

**Build**
3 mL liquid culture tubes were first grown in LB medium containing
ampicillin at 30°C for 24 hours. A 1:500 dilution was then prepared by
transferring 6 μL of the LB – ampicillin culture into 3 mL of
autoinduction media, which was then incubated at different conditions
for an additional 48 – 72 hours.

**Test**
None of the cultures turned pink in either medium for all
temperature/time conditions.

**Learn**
Dilution of 1:500 did not work. The high dilution likely reduced the
initial cell density, limiting bacterial growth even in 3 mL of media.
Additionally, choosing pink colonies would likely improve the chances of
obtaining cells that actively produce the target protein.

Iteration 3: Autoinduction Media 3 mL Experiment Trial 2

**Design**
This trial followed the same setup as Trial 1, but instead of using
diluted cultures, visibly pink colonies were directly inoculated into
autoinduction media and incubated under varying temperature and time
conditions in Table 1.

**Build**
Visibly pink colonies from LB plates were picked and inoculated directly
in the media.

**Test**
A1, A2, A3, and B2 successfully developed the "Very pink" color and
yielded high cell density with Simplified Autoinduction media. However,
the B1 culture failed to turn pink neither on the LB plate nor after the
initial incubation and subsequent days in our media, indicating a
specific failure in its protein expression or stability.

![Figure 3: Examples of Pink Levels in Expression Cultures](https://static.igem.wiki/teams/5679/results/fig3-pinkcolors.webp)

**Figure 3:** Examples of Pink Levels in Expression Cultures

**Learn**
We learned that the protocol was insufficient for B1. The problem was
likely due to B1's specific sequence, making it prone to toxicity,
degradation, or inclusion body formation. Our redesign aimed to
implement a troubleshooting protocol specifically for B1, testing
alternative, less-strenuous expression methods, such as Studier's medium
(Studier, 2005) and IPTG induction, and different temperature conditions
to trigger expression differently.

Iteration 4: Troubleshooting of B1

**Design**
Based on the failure of B1 transgenic expression in autoinduction media,
we designed to test two alternative induction methods. First, we tried
Studier’s standard autoinduction media, as it worked for other enzymes
and contains additional minerals/nutrients. Secondly, we chose IPTG
induction (manual induction after reaching an optical density of 0.6 at
600 nm), as this was the method for protein expression utilized in
previous literature that expressed this enzyme.

**Build**
We started new liquid cultures of B1 and tested the new conditions. For
the IPTG cultures, we monitored growth and added 0.1 uM IPTG at OD600 =
0.6.

**Test**
Both the Studier’s culture and the IPTG cultures were monitored over
several days, but neither trial produced a visible pink color. This
confirmed that the protein was not expressed via an induction method.

**Learn**
Ultimately, the lack of visible expression in all methods prevented us
from purifying and characterizing B1, leading us to focus our final
functional assays solely on the four successfully expressed enzymes (A1,
A2, A3, B2).

## 3. Functional Assay Experiment Cycle

Iteration 1: Colorimetric Assay

**Design**
We designed a qualitative colorimetric assay protocol which tests each
enzyme against its specific p-nitrophenol (pNP) substrate. Successful
cleavage releases a yellow pNP group which can be used to visually
confirm enzyme activity.

**Build**
We used the purified enzymes obtained from the optimized A1, A2, A3, B2,
and CA expression runs. We prepared individual reactions using their
specific substrates (e.g., A1 against its pNP substrate). B1 was
excluded due to the lack of successful protein
expression/purification.

**Test**
The A1 and B2 reactions immediately developed a yellow color after
incubation, clearly demonstrating their ability to cleave their
respective substrates. This visually confirmed the successful expression
of functional protein. However, A2 and A3 showed no visible color
change.

![Figure 4: Colorimetric Assay Shows Successful A1 and B2 Enzyme Activity](https://static.igem.wiki/teams/5679/results/colorimetric/figure-16-plate-layout.webp)

**Figure 4:** Colorimetric Assay Shows Successful A1 and B2
Enzyme Activity

Iteration 2: Quantitative Assay

**Design**
We designed a quantitative assay to measure how absorbance changes when
combined with substrates at different concentrations. We created a pNP
standard curve to establish the relationship between absorbance and pNP
concentration and solve for Michaelis-Menten kinetics values (Figure
17).

**Build**
We used the purified enzymes (A1, A2, A3, B2, CA) combined with varying
concentrations of their matching substrate to spectrophotometrically
measure absorbance at A405 over a 3 hour period.

**Test**
A1 and B2 had quantifiable data with varying absorbances for each
concentration, while A2, A3, and CA showed similar absorbances to the
blank and negative controls.

![Figure 5: pNP standard curve (80 µM - 10 mM) at 405 nm with linear fit y = 0.0202x + 01236, R2 = 0.9807](http://static.igem.wiki/teams/5679/results/colorimetric/figure-17-pnp.webp)

**Figure 5:** pNP standard curve (80 µM - 10 mM) at 405 nm with
linear fit y = 0.0202x + 01236, R2 = 0.9807

**Learn**
Both A1 and B2 had varying levels of absorbance in relation to the
concentration of substrate, values that we used to determine the Km and
Vmax in accordance with Michaelis-Menten kinetics. We were not able to
perform this analysis with A2, A3, and CA since they did not have any
detectable activity.

## 4. Biological Assay Experiment Cycle

Iteration 1: Initial Hemagglutination Assay at 22 Degrees Celsius

**Design**
We designed our one-pot enzymatic conversion based on the previous study
on Akkermansia enzymes. From our meeting with ASU Professor of
Immunohematology, Jeffery Wolz, we designed a tube-test crossmatch
hemagglutination assay to determine blood compatibility.

**Build**
Enzymes (A1–B2) were prepared from protein purification of several
autoinduction cultures. Then, A and O type porcine red blood cells were
isolated from whole blood and washed with a conversion buffer. Reactions
with corresponding enzymes were run on a tube shaker at 22 C for 30
minutes, 1 hour, and 2 hours.

**Test**
Following blood conversion, samples of each reaction were taken and
diluted to 3-5% suspension to be tested against human AB serum and/or O
plasma. Agglutinates were qualitatively measured by viewing
agglutination in 2 mL centrifugation tubes. Additionally, converted
samples were tested for blood type on commercial EldonCards and compared
to controls (unprocessed blood).

**Learn**
While this assay cycle first allowed us to view agglutination, which was
clear clumping of the cells in the plasma/serum solution, it was
difficult to identify clear differences between experimental groups. For
example, viewing of agglutinated cells requires gentle shaking of the
tube, which can be difficult if overshaking occurs. Possibly, some
macroscopic results can be skewed by improper technique, so we decided
to use microscopic images to identify agglutination instead.
Secondly, testing a 30-50% suspension of converted blood cells on the
blood typing card resulted in reaction with the control field, which
invalidates the result of the card. We hypothesized that the saline
solution used to dilute the red blood cells may have resulted in the
undesired reaction.

Iteration 2: Second Hemagglutination Assay at 4 Degrees Celsius

**Design**
Based on information from the previous cycle, we set aside an additional
reaction for the enzyme treatments that would be tested on the
EldonCard. 4 Degrees was chosen for all reactions to assess whether they
would be functional while stored in colder temperatures. The
cold-adapted enzyme targeting the B antigen (also the alpha-gal antigen
on porcine blood) was also crucial to test at 4 C, since it was
hypothesized that activity is likely better at lower temperatures.

**Build**
Using enzymes and washed red blood cells from the previous iteration,
reactions for A and O blood with their corresponding enzymes were run on
a tube rotator at 4 C for 30 minutes, 1 hour, and 2 hours. Following
conversion, blood was diluted to 3-5%. Reactions used in the EldonCard
were diluted to 30-50% using the previously separated plasma of the
converted to reflect original blood components.

**Test**
The 3-5% blood suspensions were crossmatched against either O plasma or
AB human serum. The reactions for the EldonCard from the last iteration
(at 22 C) were repeated and tested for the presence of A and a-gal
antigens.

**Learn**
Because we used microscope imaging in this iteration, agglutination was
easier to view compared to viewing in test tubes. Here, we learned that
A1 was capable of cleaving antigens on A type porcine red blood cells,
but activity at the concentration we used (1 uM) was not enough to
completely cleave all antigens and eliminate agglutination.
For the cold-adapted enzyme, we learned that it was likely that the
enzyme works better at 4 C due to reduced agglutination in the
microscope images. We learned that design for future experiments would
have to include crossmatching with samples containing antibodies against
the extended antigen structures. This way, we can isolate specific
extended structures and identify whether or not they are being cleaved.

# Software

## 1. Computational Identification of Psychrophilic Enzymes using CAZy and NCBI

Iteration 1: Using CAZy and the NCBI Database to Cross-compare to
Consider Organisms that Only Have the Particular Enzyme

**Design**
To ensure our enzyme conversion system can function at blood storage
temperatures (1–6 °C), we planned a workflow to identify enzymes within
the GH families of interest (A2–GH35A, A1–GH36A, A3–GH95A, B1–GH110A,
B2–GH20A) that are likely cold-adapted.

**Build**
Using the CAZy database, we obtained datasets of enzyme information for
each required GH family. We compiled a list of genera that, based on
literature, are of organisms that are native to colder temperatures, and
therefore, likely to have cold-adapted enzymes. We filtered the list of
enzymes to only include those from our genus list. Using the NCBI
protein IDs, we verified that the shortlisted enzymes exist, have the
required function, and are likely to work within our desired temperature
range.
**Test**
We used this workflow to manually shortlist enzymes in the GH36 and
GH110 families. The shortlisting resulted in a significant decrease in
the number of entries.

**Learn**
Doing this process manually requires a substantial amount of time and
manpower, especially considering some of our GH families had over 25000
enzyme entries in the database. To increase efficiency, we decided to
automate this process using code.

Iteration 2: Automating the Filtering Process

**Design**
We decided to automate and build a preliminary code. We compared protein
IDs from CAZy with the NCBI Protein database to output organisms that
contain the name of the enzyme we were looking at.

**Build**
After gathering the enzyme list with their names, we used a CSV file
with the filtered proteins from the psychrophilic genera from CAZy and
used that to compare with a DataFrame with filtered Protein IDs with
organisms from the NCBI Protein database using Entrez.esummary.

![Figure 1: Preliminary code used to filter required enzymes from the CAZy database.](https://static.igem.wiki/teams/5679/software/fig2-prelim-code.webp)

**Figure 1:** Preliminary code used to filter required enzymes
from the CAZy database.

**Test**
We got 19142 counts for GH family GH36 before the NCBI, and only 15
counts for GH family GH36 after passing it through the NCBI Database.
Moreover, we got 1244 counts for GH family GH110 before the NCBI, and
only 61 counts for GH family GH110 after passing it through the NCBI
Database.

**Learn**
The problem we ran into was that we had no way of determining whether
the organisms were cold-adapted or not. While the list was made to have
that concept in mind, we realized we needed to confirm that the enzymes
themselves were psychrophilic.
We solved the problem immediately by researching the source of the
species and shortlisted any that were likely to function below 10
degrees Celsius.

Iteration 3: Improving Output Readability and Optimizing Code for Larger
Databases

**Design**
The code could handle small databases; we decided to improve the code
with a focus on the characterization of only A and B antigens, and
compare structural similarities between those. We decided to do so by
testing the existing code on complete GH families (GH20, GH35, GH95), to
improve the clarity of the output.

**Build**
We modified the code so that it could display results as a dictionary
instead of a list, with each entry including the enzyme name, accession
ID, and organism name. The updated code then ran on the full GH family
datasets to check performance and accuracy.

**Test**
The code successfully reduced entries and accurately filtered and
categorized most enzymes, as verified by manual inspection. Processing
time for roughly 18000 entries was 5 to 6 hours, suggesting it could
handle large datasets with moderate efficiency.

**Learn**
The filtration system was functional but limited by runtime and minor
data mismatches. An important update that could eventually be done would
be a method for the code to significantly reduce time and address any of
these small inconsistencies in formatting found with the NCBI titles.

## 2. Proof of Concept: Testing *Colwellia* Psychrophilic Enzyme in Porcine Type O Blood

Iteration 1: Use CLUSTAL to Find Sequence Alignment in Identified
Enzymes

**Design**
Filtered **Project 1** hits for
**psychrophilic α-galactosidases** predicted to target the B-antigen
chain for cold-active conversion during pre-transfusion (4–10 °C).
Selected two candidates: Polaribacter sejongensis AUC20683.1 and
Colwellia sp. ARD46000.1.

**Build**
Cloned the Colwellia candidate (ARD46000.1) and prepared porcine Type O
whole blood for assays; B2 (ExtB-cleaving) enzyme available for
combination testing.

**Test**

![psychrophilic hemagglutination image](https://static.igem.wiki/teams/5679/software/ca-hema-assay.avif)

**Figure 1.** Microscope images of O-type porcine blood
crossmatched with human serum after treatment for 2 hours with 0.5
µM *Colwellia* cold-adapted (CA) enzyme and 0.4 µM B2 (ExtB
cleaving) enzyme. (A) CA + B2 treatment at 22 C, (B) CA treatment at
4 C, and (C) CA + B2 treatment at 4 C.

To test the effectiveness of the Colwellia cold-adapted (CA) enzyme on
blood, we treated O-type porcine blood for 2 hours at two different
temperatures. While this ɑ-galactosidase enzyme was intended to cleave
the human B antigen, it is also capable of cleaving the ɑ-galactose
antigen on porcine blood, which is detectable by human antibodies.
Figure 1A highlights that at 22 C, the CA and B2 enzymes are not capable
of cleaving the ɑ-galactose antigen on porcine blood, resulting in
detection by human antibodies and severe clumping. However, Figure 1B
and 1C indicate that treatment with CA alone and CA + B2 is capable of
ɑ-galactose cleavage, as shown by a reduced amount of agglutinated cells
and an increased prevalence of single red blood cells.

**Learn**
**The Colwellia cold-adapted enzyme is functional at low
temperature,**
supporting the cold-active conversion concept. Room-temperature
treatment is insufficient, underscoring the need to operate near storage
temps.

## 3. Temperature-Based Sequence Alignment and Structure Analysis

Iteration 1: Use CLUSTAL to Find Sequence Alignment in Identified
Enzymes

**Design**
After identifying the potential psychrophilic enzymes in Project 1, we
aimed to determine whether there were any structural and functional
similarities between the cold-adapted and the mesophilic enzymes.

**Build**
We started with a plan of action to complete the CLUSTAL sequence
alignment; first, identify a list of 5 enzymes per group (thermophilic,
mesophilic, and psychrophilic), then obtain the protein sequences from
the NCBI Protein Database, run the CLUSTALW program, and compare the
regions of similarity in the groups. Using this, we performed multiple
sequence alignments between psychrophilic enzymes and known mesophilic
counterparts to identify the conserved residues and motifs associated
with catalytic activity.

**Test**
The CLUSTAL alignments revealed that key catalytic residues and active
site motifs were conserved across both enzyme types, which suggested
that psychrophilic enzymes retained functional similarities to their
mesophilic counterparts. This could be said to indicate a strong cold
activity potential in the selected psychrophilic enzymes.

**Learn**
The sequence alignment confirmed that psychrophilic enzymes could, under
low temperature conditions, perform similar functions due to the
structural similarities. These results allowed for further comparative
analysis within the same GH families to explore the regions of
adaptation that they share.

Iteration 2: Researched Enzymes Within the Same Families to find Regions
of Similarity Between Selected Bacteria

**Design**
We aimed to identify the regions of similarity among the enzymes in the
GH families used across different bacterial species. This analysis would
help determine whether a specific structural region is responsible for
the psychrophilic adaptations.

**Build**
Using literature review and database analysis, we compared the sequences
of psychrophilic and mesophilic enzymes within the GH36 and GH110
families. We examined the conserved domains and active site
architecture, with a focus on the flexibility and stability at lower
temperatures.

**Test**
Comparative analysis showed that there were regions of similarity
between the enzymes in the same family. Psychrophilic enzymes displayed
certain amino acid substitutions consistent with an enhanced degree of
flexibility, which is a known feature of cold-adapted enzymes.

**Learn**
Through the intra-familial comparison, the observed psychrophilic and
mesophilic enzymes preserve key structural motifs, differing mainly in
peripheral or stabilizing regions. These variations are likely to
contribute to temperature-specific activity, like that looked for in
cold-active enzyme optimization.

# Hardware

## 1. Biological Experiments Cycle

Iteration 1: SCOBY Filtering Tests

**Design**
After a literature search on strategies to leukodeplete immune cells
from whole blood, we learned the only available strategy was to filter
out RBCs. We chose a different strategy of extracting white blood cells
(WBCs) using their natural affinity for some materials. We chose SCOBY
hydrogels as a potential filter material because of their partial chitin
content. Literature searches showed that immune cells have a high
affinity for chitin, however SCOBY hydrogels were not inflammatory, and
already being tested as wound dressings. Based on this we hypothesized
they would have the ability to both filter plasma and trap white blood
cells in blood samples. A successful design would result in a low-cost
material that could improve on the function of WBC filters.

**Build**
The SCOBY hydrogel was first decellularized by incubation with 1M NaOH
overnight, followed by 3 washes in deionized water over another 24h. The
decellularized SCOBY was processed into thinner fragments to improve
flow-through and WBC binding. Decellularizing the SCOBY removed all
color indicating chemicals other than the bacteriocellulose/chitin
matrix had been removed. Potentially making it easier to push blood
through the hydrogel while still providing sites for binding.

**Test**
We examined the effects of dehydration/rehydration and
decellularization, and tracked how well it worked in reducing plasma vs.
binding white blood cells. Weighing the SCOBY material pre and post
hydration, we found the hydrogel was 99% water by mass. We then exposed
the SCOBY to pork blood samples with WBC labeled using trypan blue
stain. Pork blood had fewer WBCs than estimated for healthy blood, but
all trypan labeled cells were removed from our blood samples and visibly
labeled the SCOBY surface, allowing us to successfully validate the
filtering process.

**Learn**
Pork blood had low white blood cell levels, but the SCOBY did bind white
blood cells. Its potential impact on plasma components remains
undetermined. This was useful because it showed that natural
biomaterials can interact with blood cells, and it gave us first-hand
experience with decellularization methods that we could apply to other
materials later. We also realized that if WBCs only bound to the SCOBY
surface there would be a limit to leukodepletion in a higher volume of
blood. This had to be solved in future iterations.

Iteration 2: SCOBY Surface Optimization

**Design**
To optimize the leukoreducing capability of SCOBY, we looked for
processing methods to maximize its surface area within the bag. We
reasoned that a freeze thaw cycle of the hydrogel would create pores and
surface disruptions to increase its surface area for WBC binding.

**Build**
We again decellularized the SCOBY like in iteration 1, and then tested 3
preservation conditions- air-dried, lyophilized, and frozen, thawed,
then lyophilized.

**Test**
To look at the SCOBY surface structure we used scanning electron
microscopy (SEM) on lyophilized SCOBY. We placed 1mm x 1mm x 0.1mm
slices of SCOBY onto carbon tape and applied a sputtered gold coat to
preserved structures and increase SEM contrast. Samples were prepped
onto a gold stage, and analyzed with SEM. We identified that the frozen,
thawed, and lyophilized sample altered SCOBY’s surface topography,
increasing the surface area for leukocytes to bind to.

**Learn**
We learned that the optimal processing technique for SCOBY within our
filtration bag is freezing, thawing, and lyophilizing. Further testing
is required to quantify leukoreduction compared to traditional methods.

Iteration 3: Enzyme Lyophilization

**Design**
To integrate our purified enzymes with our blood type conversion
hardware we sought a way to preserve enzymes for long periods of time
without significant loss in enzyme activity. We began by testing the
viability of freeze drying enzymes, using a sucrose stabilizing
solution.

**Build**
10ul aliquots of purified enzymes were mixed with 500 ul of 30% sucrose,
and lyophilized using the lab’s freeze-dryer. Lyophilized enzyme was
kept at -80 for 2 weeks.

**Test**
We rehydrated enzymes to perform a colorimetric substrate assay. We then
compared the enzymatic activity using data collected from enzymes before
and after lyophilizing to determine losses in enzyme activity. Before
finalizing our results, we used Michaelis-Menten kinetics to evaluate
enzyme performance. The values used for this method, Vmax and Km,
allowed us to compare and contrast.

**Learn**
We got hands-on experience using the lyophilizer and preparing
freeze-dried enzymes. This process was new to the team, so part of the
“build” stage was learning how to prepare samples and operate the
machine properly. This iteration helped us build confidence with enzyme
preservation techniques and set the foundation for longer-term and
future storage solutions.
While resuspending the lyophilized enzymes, we discovered that our
desired concentration was not feasible for some of our samples; the high
amounts of sucrose in the tube would not be properly dissolved in the
low volumes required to reach a concentration of 0.1 ug/ml of enzyme. A
key lesson of the process was to aliquot enzymes not based on volume but
on higher molar concentrations, making resuspension easier.
Overall, we learned lyophilization’s effect on enzyme activity was
almost minimal but affected each enzyme differently. A1 retained some
activity but showed signs of inconsistency, resulting in inaccurate Vmax
and Km measurements while B2 maintained its activity with an increased
Vmax and decreased Km values, suggesting lower substrate affinity but a
higher potential reaction rate. The remaining enzymes showed no activity
after lyophilization, suggesting that the process was not effective in
preservation for all proteins. From these tests, analyzing the
differences helped us better understand how to interpret Vmax and Km
values before and after via enzyme lyophilization.

## 2. Physical Design Cycle

Iteration 1: Biosensor

![dbtl1sensor](https://static.igem.wiki/teams/5679/hardware/engineeringsuccess/dbtl1sensor.avif)

**Figure 1.** First Iteration of the biosensor

**Design**
The first idea was to build the sensor system around an Arduino, since
it’s affordable and flexible for prototyping. We focused on simple
circuit features (basic wiring, sensor input, microcontroller output)
and making sure it could connect with the biosensor concept.

**Build**
We created CAD prototypes for housings, testing different shapes and
sizes to fit the Arduino and wiring. The goal was to make it
lightweight, accessible, and sustainable so anyone could use or rebuild
it easily. We developed an initial prototype of the potentiostat circuit
using wires on a breadboard.

**Test**
We performed early runs to check if the Arduino could handle the circuit
setup and if the sensor inputs responded the way we expected.

**Learn**
We concluded that turning our breadboard design into a printed circuit
board would both simplify its design, increase its reproducibility, and
allow for easier testing.

Iteration 2: PCB Potentiostat Circuit

![Second Iteration of the biosensor](https://static.igem.wiki/teams/5679/hardware/engineeringsuccess/dbtl2sensor.avif)

**Figure 2.** Second Iteration of the biosensor

**Design**
We designed the first version of our custom PCB potentiostat as an
Arduino shield in KiCad to run cyclic voltammetry and linear sweep
voltammetry by applying a voltage to the working electrode, allowing the
counter electrode to adjust based on the rate of reaction occurring, and
the reference electrode to maintain a stable voltage.

**Build**
We designed, ordered, and soldered the board together and set up the
circuit for initial runs. Furthermore we soldered a screen printed
electrode with a working, reference, and counter electrode onto our
circuit. We also included a potentiometer to adjust the resistance
between the reference electrode and operational amplifier so we could
determine the optimal resistance to reduce noise.

**Test**
We tested the circuit using a test solution of CuSO4 and HCl to
determine whether it could detect the rate of a redox reaction. We took
50 measurements at a high resistance (~10kΩ) and 50 measurements at a
low resistance (~1kΩ).

**Learn**
We concluded that a higher resistance (~10kΩ) greatly reduced noise, but
found limitations in the design because it had to be connected to a
laptop to collect data and it used an Arduino which is bulky in size and
has suboptimal memory. In future iterations, we aimed to optimize our
printed circuit board by switching to an ESP32 and to allow data to be
collected wirelessly.

Iteration 3: ESP32 Potentiostat Circuit with WIFI Capability

![Third Iteration of the biosensor](https://static.igem.wiki/teams/5679/hardware/engineeringsuccess/dbtl3sensor.avif)

**Figure 3.** Third Iteration of the biosensor

**Design**
An ESP32 version was used to add Wi-Fi and improve the setup. This meant
re-thinking both the mechanical layout of the board and the electrical
design to fit in new features. We also designed housing to hold the
electrode and reagent bottles. We swapped out the Arduino for an ESP32,
and from the Nanostat design, we altered the ESP32-PICO-D4 to an
ESP32-PICO-V3, which has a newer chip core (ECO V3) with more features
than the D4’s ECO V1 chip, and has 16KB of RTC SRAM and security
enhancements, which gives it better flash encryption and RSA support.
This enhances our circuit’s ability to efficiently collect data and
promotes the security of the data collected that is sent over a network
to an external device. We also included a port for a 3.7V battery to
power the circuit so a laptop would not be required.

**Build**
We optimized the printed circuit board based on the design of the
Nanostat. Furthermore, we designed housing to hold the new printed
circuit board, the electrode, and the holder in SolidWorks.

**Test**
We tested the new board with the same test solution from iteration 2
(CuSO4 and HCl), and then also with lectin-NOS, arginine, and treated
blood. Using the NanoStat platform, we collected data wirelessly, sent
over a network, and found the sensor data to be comparable to the
previous iteration, but with a more compact and wireless design.

**Learn**
This design greatly reduced the size from the PCB from iteration 2 and
increased its overall portability and ease of use through wireless data
collection. In future designs, optimization of the electrode would
greatly improve the user experience by minimizing interaction with
blood. One way to achieve this is by utilizing capillary action by
directly printing the working, counter, and reference electrode onto a
membrane with metal ink and allowing reagents to flow through the
membrane and into contact with the electrodes rather than pipetting
directly onto them.

# References

[1] Jensen, M., Stenfelt, L., Ricci Hagman, J., Pichler, M. J., Weikum,
J., Nielsen, T. S., Hult, A., Morth, J. P., Olsson, M. L., & Abou
Hachem, M. (2024). Akkermansia muciniphila exoglycosidases target
extended blood group antigens to generate ABO-universal blood. Nature
Microbiology, 9(5), 1176–1188.
https://doi.org/10.1038/s41564-024-01663-4

[2] Studier, F. W. (2005). Protein production by auto-induction in
high-density shaking cultures. Protein Expression and Purification,
41(1), 207–234. https://doi.org/10.1016/j.pep.2005.01.016

{% endblock %}

{% extends "layout.html" %} {% block title %}Experiments{% endblock %} {% block
body\_class%}page-experiments{% endblock %} {% block page\_content %}

* [Colorimetric Assay](#colorimetricexp)
* [Porcine Blood Conversion and Crossmatch Hemagglutination Assay](#hemagglutinationexp)
* [Protocols](#protocolsexp)
* [References](#referencesexp)

# Colorimetric Assay

## Purpose:

The colorimetric assay was used to determine whether our cloned enzymes
were functional by testing their ability to cleave their respective
substrates. These substrates were obtained from Sigma Aldrich (A1, A2,
A3), Fisher Scientific (B1), and RPI (B2). They contain a 4-nitrophenol
(pNP) group that turns yellow upon successful cleavage. The
concentration of 4-nitrophenol can be quantified at 405 nm using a
96-well plate assay.

## Experimental Design:

1. **Qualitative assay**

   Small-scale colorimetric tests were performed in PCR tubes with a
   total volume of 10 μL. Each tube contained 5 μL of 10 mM substrate
   stock solution, 1 μL of 0.1 μM enzyme, 1 μL of 10X GlycoBuffer 1
   (500 mM sodium acetate, 50 mM CaCl2, pH 5.5), 1 μL of purified BSA
   (100 μg/mL). The remaining volume was adjusted with water to reach
   10 μL. Reactions were incubated at 37 °C for 1 hour, then enzymatic
   activity was assessed by the development of yellow solution from pNP
   release.
2. **Quantitative assay: Michaelis – Menten Kinetics Model**

   A pNP standard curve was generated using concentrations from 80 µM
   to 10 mM, and a linear regression was performed to establish the
   relationship between pNP concentration and absorbance. This
   calibration allowed absorbance values from enzyme reactions to be
   converted into pNP concentrations, which were then used to calculate
   product formation over time.

   To quantify the enzyme activity, reactions were performed for our
   enzymes (A1, A2, A3, Cold-Adapted enzyme CA, B2) across a range of
   substrate concentrations (0.15625 mM, 0.3125 mM, 0.625 mM, 1.25 mM,
   2.5 mM, 5 mM). Each well contains 50 μL of substrate stock solution,
   10 μL of 0.1 μM enzyme, 10 μL of 10X GlycoBuffer 1, and 30 μL of
   water. Absorbance at 405 nm was recorded every minute over a 3-hour
   period to track product formation. Each reaction was run in
   triplicate, and averaged results for each enzyme were used to
   calculate Michaelis – Menten constants for enzyme efficiency. The
   overall experiment was repeated in duplicate at 24°C.

   To analyze enzyme kinetics, the change in product concentration
   between t = 0 min and t = 10 min was calculated for each substrate
   concentration to determine the initial reaction rate (Vo). The
   10-minute time point was selected to capture the initial linear
   phase of the reaction, where product formation reflects true enzyme
   activity before substrate depletion or saturation effects occur.
   These initial rates were then plotted against substrate
   concentration, and the data were fitted using least squares
   regression to generate Michaelis–Menten curves. From the fitted
   curve, Vmax (maximum reaction velocity) and Km (substrate affinity
   constant) were determined for each enzyme using Equation 1.

![Equation 1](https://static.igem.wiki/teams/5679/experiments/new-eqn-1.webp)

**Equation 1.** Initial Reaction Rate Equation in terms of Vmax,
Substrate Concentration [S], and Km [1]

# Porcine Blood Conversion and Crossmatch Hemagglutination Assay

## Purpose:

The crossmatch porcine hemagglutination assay was designed to allow us
to qualitatively assess the effectiveness of our enzymes to cleave
antigens on blood. Human blood would be a more accurate model, but
porcine blood was chosen as an alternative to remain within safety
limitations. Porcine blood does not contain the type B antigen, but the
enzyme, a-galactosidase, that targets the B antigen chain also cleaves
alpha-gal, which is present in porcine blood. Humans universally have an
immune reaction to alpha-gal, so this allows us to assess how active our
enzymes are.

While there is not extensive literature on the existence of antigens
that extend from the A and a-gal antigens on porcine blood, pigs also
express the genes that are responsible for the extended antigens in
humans:

* FUT1/FUT2 is responsible for H Type 3 (Targeted by A3)
* B3GALNT1 is responsible for ExtB (Targeted by B2)

Thus, we treated A Type red blood cells (RBCs) with A1, A1-3, and all
enzymes, respectively to assess change in agglutination. O Type Blood
was also treated with B1-2, and crossmatched with human serum.

## Experimental Design:

The procedure for blood conversion was adapted from the 2023 paper by
Jensen et al [3]. Type A and Type O porcine blood from Lampire
Biological Laboratories was centrifuged to separate blood components,
processed into packed red blood cells, and diluted in a saline
conversion buffer (200 mM glycine, 3 mM NaCl adjusted to pH 6.8). From
the centrifuged blood, type O porcine plasma was also collected and used
to test for the presence of A antigens on A type Blood, since it
contains anti-A antibodies. To test for the presence of alpa-gal,
commercial human AB serum was used, as all human serum contains
antibodies against alpha-gal (Sigma Aldrich).

1. Tube Test Crossmatch Hemagglutination

   A tube test which involves grading reactions based on observable
   agglutinates was utilized to assess cleavage of antigens on blood
   before and after conversion. Normal and microscopic pictures were
   taken of these reactions.
2. EldonCard

   The EldonCard, a commercially available dry blood-typing card, was
   used to detect A and B antigens. All cards contain anti-A, anti-B,
   and control fields. An anti-D field is also included to detect
   positive and negative types, which is not on porcine blood.

Enzyme treatments and their expected outcomes are shown in the table
below:

![Table 1](https://static.igem.wiki/teams/5679/experiments/hema-table-new.avif)

**Table 1.** Enzyme treatments and their expected outcomes.

# Protocols

## Common Wet Lab Protocols

## Protein Purification Protocols

## Colorimetric Assay Protocols

## Porcine Blood Conversion and Crossmatch Assay Protocols

# References

[1] Michaelis-Menten Kinetics. (2013, October 2). Chemistry LibreTexts.
https://chem.libretexts.org/Bookshelves/Biological\_Chemistry/Supplemental\_
Modules\_(Biological\_Chemistry)/Enzymes/Enzymatic\_Kinetics/Michaelis-Menten\_Kinetics

[2] Ricci Hagman, J. (2023). Atypical Carbohydrate Blood Groups and
Their Removal: Implications in Transfusion Medicine. [Doctoral Thesis
(compilation), Department of Laboratory Medicine]. Lund University,
Faculty of Medicine.

[3] Jensen, M., Stenfelt, L., Ricci Hagman, J. et al. Akkermansia
muciniphila exoglycosidases target extended blood group antigens to
generate ABO-universal blood. Nat Microbiol 9, 1176–1188 (2024).
https://doi.org/10.1038/s41564-024-01663-4

{% endblock %}

{% extends "layout.html" %} {% block title %}Results{% endblock %} {% block
body\_class%}page-results{% endblock %} {% block page\_content %}

* [Cloning](#cloning)
* [Colorimetric Assay](#colorimetric)
* [Hemagglutination Assay](#hemagglutinationres)
* [Dry Lab](#dry-lab)
* [Hardware](#hardwareresults)
* [Future Work](#future)
* [References](#resultsref)

# CLONING

## 1. Plasmid construction

We designed and assembled plasmids containing a T7 promoter and
terminator, ribosome binding site (RBS), 10X His Tag, red fluorescent
reporter gene mScarlet-I, and one of the five target exoglycosidase
sequences from *Akkermansia muciniphila* (Jensen et al., 2024).
The enzyme sequences were designated as follows: A1 - AmGH36A, A2 -
AmGH35A, A3 - AmGH95B, B1 - AmGH110A, and B2 - AmGH20A. Figure 1 shows
the constructs of 5 plasmids. All the sequences were synthesized through
IDT.

![plasmid constructs](https://static.igem.wiki/teams/5679/results/cloning/figure-1.webp)

**Figure 1.** Plasmid constructs contain a T7 promoter and
terminator, ribosome binding site (RBS), 10X His Tag, red fluorescent
reporter gene mScarlet-I, and one of the five target exoglycosidase
sequences from
 *Akkermansia muciniphila.*

## 2. Cloning

Our constructs were built using MEGAWHOP (A1) and Gibson Assembly
methods (A2, A3, B1, B2). The constructs were first transformed into NEB
Stable Competent E. coli cells, followed by colony PCR and gel
electrophoresis to confirm the presence of the correct insert size.
Plasmids from positive colonies were then purified by miniprep and sent
for sequencing to verify sequence accuracy. We transformed each
construct into T7 Express cells for protein production. We verified
successful cloning results via gel electrophoresis, sequencing, and
visualization of a pink color in the colonies. Glycerol stocks were
prepared from the positive T7 colonies for long-term storage and future
use.

### 2.1. Gel electrophoresis Results

NEB 1kb Plus DNA Ladder was used in all gel electrophoresis experiments.

![Figure 2](https://static.igem.wiki/teams/5679/results/cloning/gel/figure-2-a1-gel.webp)

**Figure 2.** A1 insert gel electrophoresis showing the bands at ~2
kb, slightly below the expected size of 2490 bp.

![Figure 3](https://static.igem.wiki/teams/5679/results/cloning/gel/figure-3-a2-gel.webp)

**Figure 3.**  Gel electrophoresis confirming successful cloning of
the A2 insert at Lane 1 to 5 (~1863 bp).

![Figure 4](https://static.igem.wiki/teams/5679/results/cloning/gel/figure-4-a3-gel.webp)

**Figure 4.** Gel electrophoresis showing successful cloning of A3
insert in lanes 2, 3, and 7, each with a band at the expected size of
~2391 bp.

![Figure 5](https://static.igem.wiki/teams/5679/results/cloning/gel/figure-5-b1-gel.webp)

**Figure 5.** Gel electrophoresis result of B1 insert cloning.
Lane 5 shows a band at a slightly smaller size of 2kb while expecting
~2385 bp.

![Figure 6](https://static.igem.wiki/teams/5679/results/cloning/gel/figure-6-b2-gel.webp)

**Figure 6.** Successful cloning of B2 insert is shown in lane 1,
2, 3, 4 and 7 with an expected band around ~1941bp.

### 2.2. Sequencing Results

**Figure 7.** Sequencing result of A1 (AmGH36A) showing no
mismatches compared to the designed sequence.

**Figure 8.** Sequencing result of A2 (AmGH35A) showing a single
mismatch (G → T), which is silent and still codes for Serine.

**Figure 9.** Sequencing result of A3 (AmGH95B) showing no
mismatches.

**Figure 10.** Sequencing result of B1 (AmGH110A) showing one added
nucleotide in the origin region, not affecting the cloning process.

**Figure 11.** Sequencing result of B2 (AmGH20A) showing no
mismatches.

### 2.3. T7 Expression Results

Our plasmid constructs contain mScarlet-I reporter, enabling direct
visualization of successful protein expression as colonies will develop
a pink color (Fig. 12 A-C, D). However, B1 colonies did not display the
expected pink color (Fig. 12D). We hypothesize that the B1 likely
encodes a product that is toxic upon expression, eliminating pink
expressing colonies and leaving only white, non-expressing cells.

![t7 plates](https://static.igem.wiki/teams/5679/results/cloning/figure-12-t7-expression.webp)

**Figure 12.** T7 transformations showing pink colonies for (A)
A1, (B) A2, (C) A3, and (E) B2. (D) B1 did not display pink colonies.

## 3. Protein Purification

### 3.1. Autoinduction media experiment

To optimize protein production, we compared two different autoinduction
media formulations under multiple growth conditions. The first was
Studier’s standard autoinduction media (Studier, 2005), and the second
was a simplified formulation without the use of salts and metals,
adapted from
[The Bumbling Biochemist](https://thebumblingbiochemist.com/365-days-of-science/autoinduction/) (“Autoinduction for Recombinant Protein Overexpression,” 2024). The
experiment was performed for all five enzyme plasmids and protein
expression was monitored by the intensity of the pink color. Table 1
summarizes different testing conditions and representative results of
this experiment. The data shown were obtained using cultures starting
from B2 colonies, and similar trends were observed across the other
enzyme constructs.

![Table 1](https://static.igem.wiki/teams/5679/results/cloning/table-1-no-cap.webp)

**Table 1.** Testing conditions of 2 different media for protein
expression

Cultures starting with a 1:500 dilution failed to produce any visible
protein expression. Direct colony inoculation successfully led to
protein expression in both media types. Overall, the simplified
autoinduction media produced brighter pink cultures than Studier’s
medium, with the exception of Conditions 3a and 3b, where Studier’s
formulation yielded slightly stronger color. The most effective
condition for both media was Condition 2, which consistently produced
the brightest pink cultures observed after two days (Figure 13). Based
on these results, we selected Condition 2b for use in subsequent protein
purification experiments.

![Cultures pink comparison](https://static.igem.wiki/teams/5679/results/cloning/figure-13-compare-pink.webp)

**Figure 13.** Comparison of 8 conditions that yielded a pink color
in the culture. Conditions 2a, 2b, and 3a are categorized as very
pink; 1b and 3b are pink; 1a and 4b are slightly pink; 4a is not pink.

### 3.2. Protein purification

Using two protocols from
[**NEBExpress**](https://www.neb.com/en-us/protocols/2019/08/28/nebexpress-ni-spin-column-reaction-protocol-neb-s1427?pdf=true)
and
[**Irvine Valley College**](https://bio.libretexts.org/Courses/Irvine_Valley_College/Lab_manual_%3A_Protein_Biomanufacturing_and_Biochemistry_%28Biot274_%40IVC%29/01%3A_Activity_1-1_-_Protein_Extraction_Using_Bacterial_Cell_Lysis) , we adopted our own protein purification protocol. Throughout the
purification process, flow-through samples from each step were collected
and analyzed by SDS-PAGE. Results of A1, A2, A3, B2 show a slightly
larger band size than expected bands (Figure 14). This may be due to the
incomplete denaturation process of protein although the samples were
heated at 95℃ for 5 minutes. Cold-adapted enzyme from
*Colwellia* (denoted as CA) displayed a smaller band size, which
may explain its lack of activity in subsequent assays. Enzyme
concentrations were assessed using a NanoDrop spectrophotometer, with
the dye-specific mode confirming the amount of the mScarlet-I.

![](https://static.igem.wiki/teams/5679/results/cloning/sds/figure-14a-sds.webp)

![](https://static.igem.wiki/teams/5679/results/cloning/sds/figure-14b-sds.webp)

![](https://static.igem.wiki/teams/5679/results/cloning/sds/figure-14c-sds.webp)

**Figure 14.** A1, A2, A3, B2 show slightly larger than expected
bands while cold-adapted (CA) enzyme display a smaller band size.

# COLORIMETRIC SUBSTRATE ASSAY

Colorimetric assay was performed to evaluate whether our enzymes were
functional. Each enzyme was tested against its specific substrate,
which, upon cleavage, released a p-nitrophenol (pNP) group, turning the
solution yellow. The concentration of p-nitrophenol can be quantified at
absorbance 405 nm (Figure 15). Because we were unable to successfully
purify B1 enzyme, we elected to use
[**GH110 enzyme from *Colwellia sp.***](https://2025.igem.wiki/asu/software)
to substitute for the following assays, which cleave the same sugar
bond.

![Colorimetric substrates](https://static.igem.wiki/teams/5679/results/colorimetric/figure-15-substrates.webp)

**Figure 15.** Colorimetric substrates for 5 enzymes

## 1. Enzymatic Function Verification

Small-scale colorimetric tests were performed to verify the enzymatic
function, with results shown in Figure 16. Each well contained 20 μL of
10 mM substrate stock solution, 4 μL of enzyme, 4 μL of 10X GlycoBuffer
1 (500 mM sodium acetate, 50 mM CaCl2, pH 5.5), 4 μL of purified BSA
(100 μg/mL). Negative control used 4 μL of heat-killed enzyme. The
remaining volume was adjusted with water when needed to reach a total of
40 μL. The A1 and B2 reactions developed a yellow solution after
incubation, showing their ability to cleave their respective substrates.
However, A2, A3, and B1 using cold-adapted enzyme from
*Colwellia sp.*
show a visible color change.

![Figure 16](https://static.igem.wiki/teams/5679/results/colorimetric/figure-16-plate-layout.webp)

**Figure 16.** A1 and B2 developed yellow solutions while A2, A3,
B1 did not show a color change.

## 2. Enzymatic Activity Quantification

### 2.1. Standard Curve

Figure 17 shows a pNP standard curve measured at A405 was generated
using concentrations from 80 µM to 10 mM and fit to a linear regression
of y = 0.0202x + 0.1236 (R2 = 0.9807).

![pNP standard curve](https://static.igem.wiki/teams/5679/results/colorimetric/figure-17-pnp.webp)

**Figure 17.** pNP standard curve (80 µM - 10 mM) at 405 nm with
linear fit y = 0.0202x + 01236, R2 = 0.9807

### 2.2. Michaelis – Menten Kinetics Model

To quantify the enzyme activity, reactions were performed for our
enzymes (A1, A2, A3, CA, and B2) across a range of substrate
concentrations (0.15625 mM, 0.3125 mM, 0.625 mM, 1.25 mM, 2.5 mM, 5 mM)
using 0.1 μM of enzyme. Absorbance at 405 nm was recorded every minute
over a 3-hour period to track product formation. Each reaction was run
in triplicate, and averaged results were used to calculate Michaelis –
Menten constants (Vmax and Km) for enzyme efficiency. A1 and B2 enzymes
showed a consistent activity across all substrate concentrations,
further validating previous assay results. In contrast, A2, A3, and CA
showed no detectable activity during the 3-hour period. The overall
experiment was repeated in duplicate. Figure 18 shows a representative
Michaelis – Menten plot for A1 at 24°C, with Vmax = 0.257 mM/min and Km
= 1.2 mM, while A3 demonstrated a slower binding rate with Vmax = 0.133
mM/min and Km = 0.38 mM.

![Figure 18](https://static.igem.wiki/teams/5679/results/colorimetric/figure-18-mm.webp)

**Figure 18.** Representative Substrate concentration vs. Reaction
rate graph of Michaelis – Menten Model for A1 enzyme.

# PORCINE HEMAGGLUTINATION ASSAY

## 1. Conversion and Crossmatch Testing of A Type Porcine Blood

To verify the blood types of the A and O type porcine blood, a blood
typing test was performed using a commercial EldonCard with anti-A and
anti-B antibody reagents. A type was crossmatched with plasma from O
blood to verify incompatibility between blood types. Then, both types
were crossmatched with human AB serum to verify incompatibility with
human blood.

First, porcine blood type A was handled in different ways to serve as
control groups. Type A packed red blood cells (RBCs) washed with our
conversion buffer and crossmatched with human AB serum showed clear
agglutination (Figure 19A). Similarly, unwashed type A RBCs and washed
RBCs crossmatched with type O plasma also displayed agglutination
(Figures 19B and red arrow in 19C), though some single RBCs were visible
in Figure 19C (green arrow). As shown in Figure 19D, unwashed type A
whole blood exhibited strong agglutination in the anti-A field and weak
agglutination in the anti-B field. This confirmed that the porcine blood
sample used was type A and also contained ⍺-Gal, which is structurally
similar to the B antigen .

![Figure 19. ](https://static.igem.wiki/teams/5679/results/hemag/figure-19.webp)

**Figure 19.** Porcine blood type A samples served as control
groups. (A) Type A packed RBCs washed with conversion buffer and
crossmatched with human AB serum, (B) Unwashed type A RBCs
crossmatched with type O plasma, (C) Washed type A RBCs crossmatched
with type O plasma with some single RBCs (green arrow). (D) Blood
typing using an EldonCard confirmed the blood sample as type A.

Porcine type A blood was treated with various enzyme combinations at
22°C. Samples treated with A1 enzyme alone and crossmatched with type O
plasma (Figure 20A) displayed noticeably fewer clumps and more single
cells, suggesting reduced agglutination compared to untreated controls.
Treatment with A1, A2, and A3 combined (Figure 20B) did not show a clear
difference in agglutination compared to treatment with A1 alone. This is
consistent with colorimetric assays indicating limited or no activity
for A2 and A3. When all five enzymes were combined and crossmatched with
human serum (Figure 20C), mild agglutination persisted, indicating that
the enzyme that targets a-gal/the B antigen was not effective. EldonCard
testing (Figure 20D) of blood treated with the full enzyme mix showed
weaker agglutination in the anti-A field while the anti-B field remained
similarly weak compared to control groups. A1 was confirmed to exhibit
the most effective antigen-cleaving activity, while additional testing
with multiple replicates or lectin-based assays for H-antigen detection
would be required to further validate antigen conversion efficiency of
A2 and A3.

![Figure 20](https://static.igem.wiki/teams/5679/results/hemag/figure-20.webp)

**Figure 20.** Enzyme-treated porcine type A blood at 22°C. (A)
Blood treated with A1 and crossmatched with O plasma, (B) Blood
treated with A1, A2, and A3 combined and crossmatched with O plasma,
(C) Blood treated with all five enzymes and crossmatched with human
serum, (D) EldonCard test of blood treated with all enzymes showed
weaker agglutination in the anti-A field and weak reaction in the
anti-B field.

## 2. Conversion and Crossmatch Testing of O Type Porcine Blood

To serve as a positive control for enzymatic conversion, porcine type O
blood samples were tested at 22°C to confirm the absence of A and B
antigens, as well as the presence of ⍺-Gal. Washed O-type RBCs
crossmatched with human serum (Figure 21A) showed minimal agglutination,
while unwashed O-type RBCs (Figure 21B) displayed similar results. When
tested on an EldonCard (Figure 21C), the O-type blood showed weak
agglutination in the anti-B field, which may be due to nonspecific
interactions.

![Figure 21](https://static.igem.wiki/teams/5679/results/hemag/figure-21.webp)

**Figure 21.** Crossmatching porcine type O blood at 22°C. (A)
Washed O-type RBCs crossmatched with human serum, (B) Unwashed O-type
RBCs crossmatched with human serum, (C) EldonCard testing confirmed
type O blood with weak agglutination in the anti-B field.

Porcine type O blood was treated with the cold-adapted enzyme (CA) and
B2 at different temperatures. Samples treated with CA + B2 at 22°C
(Figure 22A) showed visible clumping, indicating little to no enzymatic
cleavage. Treatment with C alone at 4°C (Figure 22B) resulted in more
single cells, suggesting that the cold-adapted enzyme may perform more
effectively at lower temperatures. However, when CA + B2 were combined
at 4 °C (Figure 22C), no significant qualitative difference was observed
compared to treatment with CA alone. EldonCard testing (Figure 22D) of
the same sample showed very minimal reduction in agglutination in the
anti-B field, which was also seen in untreated A-type RBCs in Figure
19D. It remains uncertain whether the porcine blood used expressed the
extended B antigen targeted by B2. While pigs have the same gene
B3GALNT1 that encodes the glycosyltransferase responsible for this
antigen, cleavage by B2 is difficult to determine qualitatively by
reduction in agglutination. Additionally, because the serum sample was
pooled from multiple donors, it is unclear whether it contained
antibodies against the extended B structure. Given that the cold-adapted
enzyme CA showed no verified activity in prior assays, the observed
reduction in agglutination could reflect either minimal B2 activity or
improved CA performance at 4°C. Further testing using B2-only controls,
verified extended-B antigen samples, and multiple biological replicates
will be necessary to confirm enzyme specificity and function.

![Figure 22.](https://static.igem.wiki/teams/5679/results/hemag/figure-22.webp)

**Figure 22.** O-type porcine blood treated with cold-adapted and
B2 enzymes. (A) Blood treated with CA + B2 at 22°C, (B) Treatment with
CA at 4°C, (C) CA + B2 treatment at 4°C. (D) EldonCard testing showed
a slight reduction in anti-B agglutination.

# DRY LAB

Due to the strict temperature requirements our kit would need to be
stored at, considering cold-adapted enzymes was a crucial step in this
project. There is, however, a lack of literature regarding cold-adapted
enzymes for blood group modifications. Therefore, we developed our own
code with the goals of identifying potential cold-adapted enzymes and
streamlining the broader process of searching and organizing enzymes
from large databases.

## 1. Computational Identification of Cold-Adapted Enzymes from CAZy and NCBI

To identify cold-adapted enzymes, the CAZy database was cross-compared
to the NCBI database. Manual shortlisting to find enzymes within their
respective families was successful for enzymes GH110 and GH35. For
enzymes GH20, GH36, and GH95, an automated filtration process was done
in Colab. The general process is outlined in Figure 23.

![Filtration Process](https://static.igem.wiki/teams/5679/results/drylab/figure-23.webp)

**Figure 23.** Outline of Filtration Process

The enzymes were further validated for use by shortlisting any that
could function under 10 °C. Code was confirmed to be working on smaller
databases, as two psychrophile enzymes were found that fit our
parameters for alpha-galactosidase: Polaribacter sejongensis and
*Colwellia sp.* PAMC 2182. Constructs shown in Figure 24. Both
enzymes were ordered through IDT, with a codon-optimized version of
*Colwellia sp.*
PAMC 2182. Gibson Assembly was used to insert the sequence into the
backbone. The constructs were first transformed into NEB Stable
Competent E. coli cells, which was followed by colony PCR and gel
electrophoresis to confirm their presence, which were then miniprepped
and nanodropped. Only *Colwellia sp.* PAMC 2182 was successfully
cloned into the backbone as shown in Figure 25 and the sequence was
confirmed as shown in Figure 26.

![Cold adapted Constructs ](https://static.igem.wiki/teams/5679/results/drylab/figure-24.webp)

**Figure 24.** Constructs of cold-adapted enzyme
*Colwellia sp.*
PAMC 2182 with similar components to the five enzymes we did.

![Gel electrophoresis result of Colwellia ](https://static.igem.wiki/teams/5679/results/drylab/figure-25-gel.webp)

**Figure 25.** Gel electrophoresis result of
*Colwellia sp.* PAMC 2182 (C1 - C4) and Polaribacter
sejongensis (P1 - P4). C1, C3, and C4 show bands at the expected size
of ~1835 bp, indicating successful cloning of
*Colwellia sp.* PAMC 2182.

**Figure 26.** Successful sequencing comparison showing no
mismatch between ideal sequence and our *Colwellia sp.* PAMC
2182.

## 2. Temperature-Based Sequence Alignment and Structure Analysis

We then aimed to find similar regions between the three temperature
groups of enzymes, thermophilic, mesophilic, and psychrophilic, that
allow for cold temperature functionality. This was to recognize mutation
sites in our original 5 enzymes in order to make them cold-adapted.

Using CLUSTAL sequence alignment, we identified 5 enzymes within each
temperature range, and found there were no significant regions of
similarity for the thermophilic and psychrophilic enzymes. We then ran
protein sequences within the Alteromonadales order, the order of
*Colwellia sp. PAMC 2182* found in project 1. By doing this, we
were able to compile enzymes from 5 families, the Colwelliaceae (other
than  *Colwellia sp. PAMC 21821* ), Alteromonadalaceae,
Pseudoalteromonadaceae, Psychromonadaceae, and Shewanellaceae, for a
total of 25 enzymes in the GH110 family. Sequence alignments between the
enzymes, including *Colwellia sp. PAMC 2182*, was run in CLUSTAL.
Between *Colwellia sp. PAMC 21821* and Akkermansia muciniphila,
distinct regions of similarity were found as shown in Figure 27.

![Sequence comparison of GH110 enzyme from Colwellia           sp](https://static.igem.wiki/teams/5679/results/drylab/figure-27.webp)

**Figure 27.** Sequence comparison of GH110 enzyme from
*Colwellia sp.* PAMC 21821 (Accession ID: ARD46000.1) and
Akkermansia muciniphila (Accession ID: WP\_435331545.1). Colors
correspond to the amino acid category (i.e., blue: hydrophobic, red:
positive/magenta: negative charges, green: polar).

# HARDWARE: Development of UNIglobin Enzymatic Blood Conversion Kit

We developed a hardware conversion kit that would detect residual
antigens left over after a round of enzyme cleavage to ensure safety
before a transfusion. This kit includes enzymes required for the blood
conversion, a miniaturized biosensor to measure antigen cleavage, and a
filter that removes leukocytes and plasma while keeping red blood cells
and platelets.

![Figure 28](https://static.igem.wiki/teams/5679/results/hardware/figure-28-kit.webp)

**Figure 28.** Model of the conversion kit

## 1. Lyophilized Enzymes

Small aliquots of each enzyme (10 µL) were mixed with 50% sucrose and
lyophilized using a lyophilizer, then stored at – 20°C. Their activity
was quantified and compared with recently purified enzymes using the
Michaelis – Menten model to evaluate whether lyophilization is a viable
method for maintaining enzymatic function over long storage periods.
Among the tested enzymes, A1 and B2 retained measurable activity;
however, the A1 dataset showed high variability and could not be
accurately fitted to least squares regression to generate Michaelis –
Menten graph. Therefore, Vmax and Km of A1 were not determined. In
contrast, B2 produced a clear reaction with Vmax = 0.39 mM/min and Km =
1.42 mM, indicating that the lyophilized enzyme required a higher
substrate concentration to reach half of its maximum velocity compared
to recently purified B2.

## 2. Miniaturized Electronic Antigen Biosensor (MEAB)

To complement our enzymatic conversion system, we developed a
miniaturized electronic biosensor capable of detecting nitric oxide (NO)
released when our lectin is bound to O type blood. The biosensor
integrates a custom-built circuit that measures peak current from NO
redox reactions, which correlates with the amount of antigen bound. We
successfully assembled the biosensor and validated its functionality at
the circuit level. Figure 29 shows the biosensor phototype.

![Prototype ](https://static.igem.wiki/teams/5679/results/hardware/figure-29-meab.webp)

**Figure 29.** Prototype of the biosensor: 3D model (left), circuit
board (middle), sensor electrode and reagents in one housing (right)

To test functionality of the sensor, we conducted preliminary testing
using voltammetry with a solution of CuSO4, HCl, and water. As shown in
Figure 30, an increasing voltage was applied while the resulting current
was measured, implying that the sensor could detect redox reactions.
This signal will be used to determine the rate at which the nitric oxide
synthase forward reaction occurs, which can then be correlated to the
amount of antigen bound.

![Figure 30](https://static.igem.wiki/teams/5679/results/hardware/figure-30-slope.webp)

**Figure 30.** Current versus Voltage plot obtained from
voltammetry testing using a CuSO4 and HCl solution.

Similarly to the process of cloning enzymes, we successfully cloned the
Aleuria Aurantia Lectin (AAL) sequence together with Bacillus subtilis
Nitric Oxide Synthase (bsNOS) sequence in our plasmid backbone. Figure
31 shows the designed sequence map similar to the 5 enzymes, Figure 32
presents the sequencing confirmation for the construct, Figure 33 gives
a visualization of the protein expression with T7 express cells. This is
then purified to obtain AAL+bsNOS protein using in our MEAB.

![Figure 31](https://static.igem.wiki/teams/5679/results/hardware/lectin/figure-31-lectin.webp)

**Figure 31.** Plasmid map showing the designed construct
containing AAL and bsNOS fragments.

**Figure 32.** Sequencing alignment confirming successful cloning
of the lectin and bsNOS with no mismatch.

![Figure 33](https://static.igem.wiki/teams/5679/results/hardware/lectin/figure-33-lectin-t7.webp)

**Figure 33.** T7 transformations showing pink colonies for
successful lectin expression.

Cyclic voltammetry testing was performed to test the NO detection of the
MEAB using varying AAL- bsNOS complex concentrations. Figure 34 shows
current per unit of voltage vs. time for three conditions - porcine O
blood, porcine A blood, and enzymatically treated porcine blood. In a
paired t-test, type O (positive control) and treated blood were highly
significant compared to type A (negative control) (p<0.001).

![Figure 34](https://static.igem.wiki/teams/5679/results/hardware/lectin/figure-34.webp)

**Figure 34.** Example assay comparing positive control (Type O),
negative control (Type A) and enzymatically treated (Treated Type A)
porcine red blood cells labeled with the lectin-NOS. Comparing current
slopes over time showed consistent separation of Type O (Slope = 0.74
µA/ms) from Type A (Slope = 0.44 µA/ms). Treated Type A blood appeared
highly similar to Type O (Slope = 0.73 µA/ms) and significantly
different from Type A (p < 0.001), indicative of lectin labeling
and enzymatic cleavage across samples (n = 3 cycles and 2 replicate
experiments using the 2 available blood samples)

## 3. Filtration Bag

Access to centrifuges for blood processing is limited in low-resourced
communities, and costly leukoreduction filters are not practical. Our
two-part filter provides a low-cost solution: SCOBY cellulose binds
leukocytes, while a PTFE membrane allows plasma to pass through. After
filtration, red blood cells and platelets remain in the bag for
collection, reducing the probabilities of immune reactions and disease
transmission due to residual antibodies and leukocytes.

![Figure 35](https://static.igem.wiki/teams/5679/results/hardware/figure-35-filtration-bag.webp)

**Figure 35.** Prototype of the filtration bag with SCOBY for
leukocyte binding and a PTFE membrane for plasma separation.

## 4. SCOBY

Immunofluorescence staining with DAPI and anti-CD45 antibody staining on
a SCOBY sample to assess leukocyte binding (Figure 36). However, the
number observed was lower than we expected. Further optimization is
needed to maximize the effective surface area of SCOBY or to enhance
leukocyte binding.

![Figure 36](https://static.igem.wiki/teams/5679/results/hardware/figure-36-new.webp)

**Figure 36.** Fluorescence microscopy image of a 1mm SCOBY
sample. Whole mount imaging (A scale bar = 1mm) and 40X magnification
(B scale bar = 25µm) Cells were stained with DAPI nuclear stain (blue)
and the leukocyte marker CD45 (green) to visualize bound WBCs.

SCOBY was treated using different processing techniques: air-drying,
lyophilizing, and freezing/lyophilizing to increase binding
effectiveness. Scanning electron microscopy images in Figure 37 show
freezing and lyophilizing SCOBY greatly alters surface topography,
increasing the surface area that leukocytes can bind to. We also
determined that the pore size of SCOBY ranges from 0.2 µm - 1.5 µm,
which suggests that SCOBY could be used to filter small proteins and
antibodies within plasma.

![EM results](https://static.igem.wiki/teams/5679/results/hardware/figure-37-new-sem.avif)

**Figure 37.** Scanning electron microscopy images of SCOBY
treated by air drying (A), lyophilization (B) and a freeze thaw cycle,
followed by lyophilization (C) (Scale bar = 50µm). High resolution
image of lyophilized samples showing pores (Scale bar = 5µm).

## 5. PTFE

We obtained our PTFE membrane from JVLAB but accidentally purchased the
hydrophobic version instead of the hydrophilic one required for plasma
separation. Due to time constraints, we were unable to replace it,
though the design remains compatible with hydrophilic PTFE for future
testing.

# FUTURE WORK

Moving forward, we plan to build on our progress by refining several
aspects of the project. In the wet lab, future experiments are needed to
troubleshoot the expression of enzyme B1. Alongside this, we aim to
optimize the conditions for purifying larger amounts of enzymes and
investigate the lack of activity observed in enzymes A2 and A3. Further
work into testing cold-adaptive and lyophilized enzymes to evaluate
their activity and stability under different conditions will need to be
performed to improve future versions of the blood conversion kit. On the
hardware side, the next steps include obtaining the appropriate
hydrophilic PTFE membrane and developing improved prototypes of the
conversion kit, which will then undergo systematic testing and
optimization.

# REFERENCES

[1] Autoinduction for recombinant protein overexpression. (2024, June
7). The Bumbling Biochemist.
https://thebumblingbiochemist.com/365-days-of-science/autoinduction/

[2] Jensen, M., Stenfelt, L., Ricci Hagman, J., Pichler, M. J., Weikum,
J., Nielsen, T. S., Hult, A., Morth, J. P., Olsson, M. L., & Abou
Hachem, M. (2024). Akkermansia muciniphila exoglycosidases target
extended blood group antigens to generate ABO-universal blood. Nature
Microbiology, 9(5), 1176–1188.
https://doi.org/10.1038/s41564-024-01663-4

[3] Studier, F. W. (2005). Protein production by auto-induction in
high-density shaking cultures. Protein Expression and Purification,
41(1), 207–234. https://doi.org/10.1016/j.pep.2005.01.016

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