Homework

About me: environmental lawyer curious about biotech.
Contact info: djwrister@gmail.com
Homework

Completed / In-Progress Assignments

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Homework

  • Week 01 – Principles and Practices
  • Week 02 – DNA Read, Write, and Edit
  • Week 03 – Lab Automation
  • Week 04 – Protein Analysis
  • Week 05 – Phage Lysis Protein Design Challenge
  • Week 06 – Genetic Circuits
  • Week 07 – Genetic Circuits Part II
  • Week 09 – Cell-Free Systems: Concepts, Advantages, Design Strategies, and Applications
  • Week 10 – Waters Imaging and Measurement
  • Week 11 – Bioproduction & Cloud Labs
  • Week 12 – Bioproduction & Cloud Labs
  • Week 13 – AI, SynBio, and Scaling Health Innovation (ARPA‑H)
  • Week 14 – Biodesign

Final Project

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Last updated: March 2026

Apr 30, 2026

Subsections of Homework

Homework

HOMEWORK

COURSE HOMEWORK OVERVIEW

Below are all homework assignments in chronological order.

Homework List

Homework

  • Week 01 – Principles and Practices
  • Week 02 – DNA Read, Write, and Edit
  • Week 03 – Lab Automation
  • Week 04 – Protein Analysis
  • Week 05 – Phage Lysis Protein Design Challenge
  • Week 06 – Genetic Circuits
  • Week 07 – Genetic Circuits Part II
  • Week 09 – Cell-Free Systems: Concepts, Advantages, Design Strategies, and Applications
  • Week 10 – Waters Imaging and Measurement
  • Week 11 – Bioproduction & Cloud Labs
  • Week 12 – Bioproduction & Cloud Labs
  • Week 13 – AI, SynBio, and Scaling Health Innovation (ARPA‑H)
  • Week 14 – Biodesign
Apr 20, 2026

Subsections of Homework

Week 01 – Principles and Practices

Week 1 HW: Principles and Practices

1. Application Goal

I want to use CRISPR Cas-9 to knockout the LFY (LEAFY) gene in Arabidopsis thaliana. This serves as a biological engineering tool to provide students with a clear visual confirmation of a successful gene edit—the plant will fail to produce flowers.

2. Governance and Policy Goals

The primary goal is to ensure this tool contributes to an “ethical” future by serving as a standardized educational platform. It allows students to learn gene editing techniques within a framework that provides immediate visual feedback and built-in biosafety (non-reproductive plants).


3. Proposed Governance Actions

Action 1: Standardized Educational CRISPR-LFY Kit

  • Purpose: Provide a safe, vetted “kit” for schools to reduce unsafe improvisation.
  • Design: * Physical: Use non-integrating systems or low-fertility lines.
    • Protocol: SOPs for containment and autoclaving disposal.
    • Governance: Mandatory Material Transfer Agreements (MTAs).
  • Assumptions: Institutions have BSL-1 facilities; teachers follow SOPs.
  • Risks: Failure of containment due to small seed size; success leads to off-target effects if handled poorly.

Action 2: Mandatory Ethics & Risk Training

  • Purpose: Ensure students understand the “why” and “should,” not just the “how.”
  • Design: A required module covering gene editing ethics and case studies.
  • Assumptions: Instructors have the support to teach ethics; students engage meaningfully.
  • Risks: Ethics treated as a “checkbox”; success might make students overly cautious.

Action 3: Institutional Oversight & Registration

  • Purpose: Ensure all gene editing activities are visible to faculty and Biosafety Officers.
  • Design: Registry of constructs used, genes targeted, and disposal methods.
  • Assumptions: Biosafety Officers have specific expertise in plant gene editing.
  • Risks: Excessive bureaucracy could stifle innovation.

4. Scoring & Prioritization

Policy GoalOption 1 (Kit)Option 2 (Ethics)Option 3 (Oversight)
Enhance Biosecurity123
Foster Lab Safety231
Protect Environment132
Minimize Cost/Burden312
Not Impede Research132

Prioritization: I prioritize a combination of Option 1 and Option 3. The kit (Option 1) provides the physical safety mechanism (the LFY knockout ensures no reproduction), while the Biosafety Officer (Option 3) ensures oversight.


Week 2 Lecture Prep

Questions from Professor Jacobson

  • DNA Polymerase Error Rate: Approximately 1 in 10 million base pairs.
  • Comparison to Genome: The human genome is ~3 billion base pairs. This discrepancy is managed by advanced proofreading and error correction mechanisms.
  • Coding Diversity: An average protein (400 amino acids) can be encoded by roughly $10^{194}$ different DNA sequences.
  • Constraint Realities: Most of these codes fail due to constraints in transcription, mRNA stability, translation efficiency, and protein folding.

Questions from Dr. LeProust

  • Oligo Synthesis: The most common method is Phosphoramidite Chemistry.
  • 200nt Limit: Difficult because error rates are cumulative; the yield of pure, correct sequence drops too low.
  • 2000bp via Direct Synthesis: Not viable because the probability of a perfect sequence over that length is statistically near zero with current error rates.

Questions from George Church

  • The 10 Essential Amino Acids: Arginine, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, threonine, tryptophan, and valine.
  • Lysine Contingency: This concept is flawed because all animals already require lysine from their diet; they do not produce it themselves.
  • Aspirin-like Stability: To make protein medicines stable, I would circularize the protein (joining the ends) to prevent degradation by heat, similar to the 2014 Heidelberg iGEM project.

Labs

Projects

Week 02 – DNA Read, Write, and Edit

Laboratory Notebook Entry


Metadata

FieldValue
CourseHTGAA
Week2
Dan Wright
TopicDNA Read · Write · Edit

Abstract

This laboratory exercise explored the modern molecular biology workflow: restriction digest simulation, wet-lab electrophoresis, gene design, codon optimization, DNA synthesis preparation, and genome read/write/edit technologies. A developmental transcription factor (MSX-1) was selected, reverse-translated, optimized, and engineered into an expression cassette.


1. Restriction Digest Simulation & Gel Art

Objective

Simulate Lambda DNA restriction digests and generate a gel-art visualization.

Enzymes Used

EcoRI · HindIII · BamHI · KpnI · EcoRV · SacI · SalI

Methods

  • Imported Lambda genome into Benchling
  • Performed multi-enzyme restriction digest
  • Visualized predicted fragment sizes

Result

In-silico restriction digest In-silico restriction digest

Figure 1. Simulated restriction digest of Lambda DNA.


2. Wet Lab Restriction Digest

Objective

Perform physical restriction digestion and electrophoresis following the designed protocol.


3. Gene Design Workflow

3.1 Protein Selection

Target Protein:
MSX-1 (Homeobox protein, Homo sapiens)

Rationale:
MSX-1 regulates developmental gene pathways and limb formation.


3.2 Reverse Translation

Full reverse-translated nucleotide sequence:

atggcccccgccgccgacatgaccagcctgcccctgggcgtgaaggtggaggacagcgcc
ttcggcaagcccgccggcggcggcgccggccaggcccccagcgccgccgccgccaccgcc
gccgccatgggcgccgacgaggagggcgccaagcccaaggtgagccccagcctgctgccc
ttcagcgtggaggccctgatggccgaccacagaaagcccggcgccaaggagagcgccctg
gcccccagcgagggcgtgcaggccgccggcggcagcgcccagcccctgggcgtgcccccc
ggcagcctgggcgcccccgacgcccccagcagccccagacccctgggccacttcagcgtg
ggcggcctgctgaagctgcccgaggacgccctggtgaaggccgagagccccgagaagccc
gagagaaccccctggatgcagagccccagattcagccccccccccgccagaagactgagc
ccccccgcctgcaccctgagaaagcacaagaccaacagaaagcccagaacccccttcacc
accgcccagctgctggccctggagagaaagttcagacagaagcagtacctgagcatcgcc
gagagagccgagttcagcagcagcctgagcctgaccgagacccaggtgaagatctggttc
cagaacagaagagccaaggccaagagactgcaggaggccgagctggagaagctgaagatg
gccgccaagcccatgctgccccccgccgccttcggcctgagcttccccctgggcggcccc
gccgccgtggccgccgccgccggcgccagcctgtacggcgccagcggccccttccagaga
gccgccctgcccgtggcccccgtgggcctgtacaccgcccacgtgggctacagcatgtac
cacctgacc

3.3 Codon Optimization

Full codon-optimized sequence:

ATG GCT CCT GCC GCT GAC ATG ACA TCC CTC CCT CTG GGC GTG AAA GTC GAA GAC TCT GCC TTC GGA AAA CCA GCT GGA GGA GGT GCA GGC CAA GCG CCC TCA GCC GCC GCC GCA ACT GCC GCG GCA ATG GGC GCG GAT GAA GAA GGA GCA AAG CCT AAA GTC TCA CCC TCT TTG CTC CCC TTC TCT GTT GAG GCA CTC ATG GCC GAC CAC AGG AAA CCT GGC GCC AAA GAG TCA GCA CTT GCT CCA TCT GAG GGC GTG CAG GCT GCC GGT GGG TCT GCC CAG CCA CTC GGC GTT CCT CCT GGG TCT CTC GGT GCC CCC GAC GCC CCT AGC TCT CCA CGC CCT CTT GGG CAC TTT AGC GTG GGC GGG CTG CTG AAA CTT CCA GAA GAC GCA CTC GTT AAG GCC GAA AGT CCT GAG AAA CCC GAG CGA ACC CCT TGG ATG CAG TCA CCC AGG TTC TCA CCC CCT CCC GCT AGG AGG CTC TCC CCC CCA GCA TGT ACT CTC CGG AAA CAT AAG ACA AAT AGA AAA CCC CGC ACC CCG TTT ACC ACC GCC CAG CTG CTG GCC CTT GAG AGA AAG TTC CGG CAG AAG CAG TAC CTC TCC ATC GCC GAA CGG GCT GAG TTC TCC TCC TCC TTG TCC CTC ACC GAG ACA CAG GTT AAG ATT TGG TTC CAG AAC CGC CGG GCA AAG GCA AAA CGG CTG CAA GAA GCC GAG CTG GAG AAG CTT AAG ATG GCA GCT AAA CCC ATG CTC CCT CCA GCA GCG TTT GGC CTC AGT TTT CCA CTG GGC GGC CCA GCT GCA GTG GCA GCT GCG GCC GGC GCC TCC CTC TAT GGA GCC TCC GGG CCG TTC CAA CGG GCC GCA CTT CCC GTA GCA CCA GTC GGG TTG TAC ACT GCA CAT GTC GGC TAC AGC ATG TAC CAC CTG ACC

4. Expression Cassette Engineering

Full Expression Cassette Sequence

TTTACGGCTAGCTCAGTCCTAGGTATAGTGCTAGCCATTAAAGAGGAGAAAGGTACCatggcccccgccgccgacatgaccagcctgcccctgggcgtgaaggtggaggacagcgccttcggcaagcccgccggcggcggcgccggccaggcccccagcgccgccgccgccaccgccgccgccatgggcgccgacgaggagggcgccaagcccaaggtgagccccagcctgctgcccttcagcgtggaggccctgatggccgaccacagaaagcccggcgccaaggagagcgccctggcccccagcgagggcgtgcaggccgccggcggcagcgcccagcccctgggcgtgccccccggcagcctgggcgcccccgacgcccccagcagccccagacccctgggccacttcagcgtgggcggcctgctgaagctgcccgaggacgccctggtgaaggccgagagccccgagaagcccgagagaaccccctggatgcagagccccagattcagccccccccccgccagaagactgagcccccccgcctgcaccctgagaaagcacaagaccaacagaaagcccagaacccccttcaccaccgcccagctgctggccctggagagaaagttcagacagaagcagtacctgagcatcgccgagagagccgagttcagcagcagcctgagcctgaccgagacccaggtgaagatctggttccagaacagaagagccaaggccaagagactgcaggaggccgagctggagaagctgaagatggccgccaagcccatgctgccccccgccgccttcggcctgagcttccccctgggcggccccgccgccgtggccgccgccgccggcgccagcctgtacggcgccagcggccccttccagagagccgccctgcccgtggcccccgtgggcctgtacaccgcccacgtgggctacagcatgtaccacctgaccCATCACCATCACCATCATCACTAACCAGGCATCAAATAAAACGAAAGGCTCAGTCGAAAGACTGGGCCTTTCGTTTTATCTGTTGTTTGTCGGTGAACGCTCTCTACTAGAGTCACACTGGCTCACCTTCGGGTGGGCCTTTCTGCG

Annotated Elements

Promoter

TTTACGGCTAGCTCAGTCCTAGGTATAGTGCTAGCCATTAAAG

RBS

AGGAGAAAGG

Spacer

TACC

6×His Tag

CATCACCATCACCATCATCA

Terminator

AGGCATCAAATAAAACGAAAGGCTCAGTCGAAAGACTGGGCCTTTCGTTTTATCTGTTGTTTGTCGGTGAACGCTCTCTACTAGAGTCACACTGGCTCACCTTCGGGTGGGCCTTTCTGCG

Benchling Construct Map

Benchling Construct Benchling Construct

Figure 2. Benchling construct showing CDS, His-tag, and terminator.


5. DNA Read · Write · Edit

5.1 DNA Read

Target genome: Secretariat (racehorse)
Technology: Nanopore sequencing

Workflow:

  1. DNA extraction
  2. Purification
  3. Library preparation
  4. Sequencing
  5. Base calling
  6. Assembly

5.2 DNA Write

Technology: Phosphoramidite synthesis and gene synthesis providers

Steps:

  1. Oligo synthesis
  2. Gibson Assembly
  3. Validation sequencing

Limitations:

  • Fragment size limits
  • Time and cost
  • Assembly complexity

5.3 DNA Edit

Technology: CRISPR knock-in

Mechanism:

  1. Guide RNA design
  2. Cas9 cleavage
  3. Homology-directed repair
  4. Screening

Limitations:

  • Off-target effects
  • Efficiency variability



Week 03 – Lab Automation

Opentrons Script from opentrons import types

metadata = { ‘protocolName’: ‘HTGAA Robotic Patterning - Misu Optimized Full’, ‘author’: ‘HTGAA Virtual Exercise’, ‘source’: ‘HTGAA 2022 Modified’, ‘apiLevel’: ‘2.20’ }

TIP_RACK_DECK_SLOT = 9 COLORS_DECK_SLOT = 6 AGAR_DECK_SLOT = 5 PIPETTE_STARTING_TIP_WELL = ‘A1’

well_colors = { ‘A1’ : ‘Red’, ‘B1’ : ‘Yellow’, ‘C1’ : ‘Green’, ‘D1’ : ‘Cyan’, ‘E1’ : ‘Blue’ }

def run(protocol):

# -----------------------------
# Speed Optimization
# -----------------------------
protocol.max_speeds.update({
    'X': 300,
    'Y': 300,
    'Z': 80,
    'A': 80
})

# -----------------------------
# Labware
# -----------------------------
tips_20ul = protocol.load_labware('opentrons_96_tiprack_20ul', TIP_RACK_DECK_SLOT)
pipette_20ul = protocol.load_instrument("p20_single_gen2", "right", [tips_20ul])

temperature_module = protocol.load_module('temperature module gen2', COLORS_DECK_SLOT)
temperature_plate = temperature_module.load_labware(
    'opentrons_96_aluminumblock_generic_pcr_strip_200ul'
)

agar_plate = protocol.load_labware('htgaa_agar_plate', AGAR_DECK_SLOT)
center_location = agar_plate['A1'].top()

pipette_20ul.starting_tip = tips_20ul.well(PIPETTE_STARTING_TIP_WELL)

# -----------------------------
# Helpers
# -----------------------------
def location_of_color(color_string):
    for well, color in well_colors.items():
        if color.lower() == color_string.lower():
            return temperature_plate[well]
    raise ValueError(f"No well found with color {color_string}")

def dispense_and_detach_fast(pipette, volume, location):
    near = location.move(types.Point(z=location.point.z + 2))
    pipette.move_to(near)
    pipette.dispense(volume, location)
    pipette.move_to(location.move(types.Point(x=0.8)))
    pipette.move_to(near)

# -----------------------------
# FULL MISU Coordinate List
# -----------------------------
mturquoise2_points = [

(-4.5, 15.5),(-4.5, 14.5),(-3.5, 14.5),(-2.5, 14.5),(-3.5, 13.5),(-2.5, 13.5), (-1.5, 13.5),(-0.5, 13.5),(-3.5, 12.5),(-2.5, 12.5),(-1.5, 12.5),(-0.5, 12.5), (-3.5, 11.5),(-2.5, 11.5),(-1.5, 11.5),(-0.5, 11.5),(-3.5, 10.5),(-2.5, 10.5), (-1.5, 10.5),(-0.5, 10.5),(-3.5, 9.5),(-2.5, 9.5),(-1.5, 9.5),(-0.5, 9.5), (5.5, 9.5),(6.5, 9.5),(7.5, 9.5),(-3.5, 8.5),(-2.5, 8.5),(-1.5, 8.5), (5.5, 8.5),(6.5, 8.5),(7.5, 8.5),(8.5, 8.5),(-3.5, 7.5),(-2.5, 7.5), (-1.5, 7.5),(4.5, 7.5),(5.5, 7.5),(6.5, 7.5),(7.5, 7.5),(8.5, 7.5), (-3.5, 6.5),(-2.5, 6.5),(-1.5, 6.5),(4.5, 6.5),(5.5, 6.5),(6.5, 6.5), (7.5, 6.5),(-3.5, 5.5),(-2.5, 5.5),(-1.5, 5.5),(3.5, 5.5),(4.5, 5.5), (5.5, 5.5),(-7.5, 4.5),(-6.5, 4.5),(-3.5, 4.5),(-2.5, 4.5),(-1.5, 4.5), (2.5, 4.5),(3.5, 4.5),(4.5, 4.5),(-10.5, 3.5),(-9.5, 3.5),(-8.5, 3.5), (-7.5, 3.5),(-6.5, 3.5),(-5.5, 3.5),(-3.5, 3.5),(-2.5, 3.5),(-1.5, 3.5), (1.5, 3.5),(2.5, 3.5),(3.5, 3.5),(-13.5, 2.5),(-12.5, 2.5),(-11.5, 2.5), (-10.5, 2.5),(-9.5, 2.5),(-7.5, 2.5),(-6.5, 2.5),(-5.5, 2.5),(-3.5, 2.5), (-2.5, 2.5),(-1.5, 2.5),(-0.5, 2.5),(0.5, 2.5),(1.5, 2.5), (-14.5, 1.5),(-13.5, 1.5),(-12.5, 1.5),(-8.5, 1.5),(-7.5, 1.5), (-6.5, 1.5),(-3.5, 1.5),(-2.5, 1.5),(-1.5, 1.5),(0.5, 1.5),(1.5, 1.5), (-13.5, 0.5),(-9.5, 0.5),(-8.5, 0.5),(-7.5, 0.5),(-6.5, 0.5), (-3.5, 0.5),(-2.5, 0.5),(-1.5, 0.5),(0.5, 0.5),(1.5, 0.5),(2.5, 0.5), (-10.5, -0.5),(-9.5, -0.5),(-8.5, -0.5),(-7.5, -0.5),(-3.5, -0.5), (-2.5, -0.5),(-1.5, -0.5),(2.5, -0.5),(3.5, -0.5),(4.5, -0.5), (-10.5, -1.5),(-9.5, -1.5),(-8.5, -1.5),(-3.5, -1.5),(-2.5, -1.5), (-1.5, -1.5),(3.5, -1.5),(4.5, -1.5),(-11.5, -2.5),(-10.5, -2.5), (-9.5, -2.5),(-3.5, -2.5),(-2.5, -2.5),(-1.5, -2.5),(4.5, -2.5), (5.5, -2.5),(-11.5, -3.5),(-10.5, -3.5),(-9.5, -3.5),(-3.5, -3.5), (-2.5, -3.5),(-1.5, -3.5),(4.5, -3.5),(5.5, -3.5),(6.5, -3.5),(7.5, -3.5), (-12.5, -4.5),(-11.5, -4.5),(-3.5, -4.5),(-2.5, -4.5),(-1.5, -4.5), (5.5, -4.5),(6.5, -4.5),(7.5, -4.5),(8.5, -4.5),(-13.5, -5.5), (-12.5, -5.5),(-11.5, -5.5),(-3.5, -5.5),(-2.5, -5.5),(-1.5, -5.5), (5.5, -5.5),(6.5, -5.5),(7.5, -5.5),(8.5, -5.5),(9.5, -5.5), (-14.5, -6.5),(-13.5, -6.5),(-3.5, -6.5),(-2.5, -6.5),(-1.5, -6.5), (6.5, -6.5),(7.5, -6.5),(8.5, -6.5),(9.5, -6.5),(10.5, -6.5), (11.5, -6.5),(-14.5, -7.5),(-3.5, -7.5),(-2.5, -7.5),(-1.5, -7.5), (-0.5, -7.5),(6.5, -7.5),(7.5, -7.5),(8.5, -7.5),(9.5, -7.5), (10.5, -7.5),(11.5, -7.5),(12.5, -7.5),(13.5, -7.5),(-15.5, -8.5), (-3.5, -8.5),(-2.5, -8.5),(-1.5, -8.5),(-0.5, -8.5),(7.5, -8.5), (8.5, -8.5),(9.5, -8.5),(10.5, -8.5),(11.5, -8.5),(12.5, -8.5), (13.5, -8.5),(14.5, -8.5),(-3.5, -9.5),(-2.5, -9.5),(-1.5, -9.5), (-0.5, -9.5),(-5.5, -10.5),(-4.5, -10.5),(-3.5, -10.5),(-2.5, -10.5), (-1.5, -10.5),(-0.5, -10.5),(-4.5, -11.5),(-3.5, -11.5),(-2.5, -11.5), (-1.5, -11.5),(-0.5, -11.5),(-4.5, -12.5),(-3.5, -12.5),(-2.5, -12.5), (-1.5, -12.5),(-3.5, -13.5),(-2.5, -13.5),(-1.5, -13.5), (-3.5, -14.5),(-2.5, -14.5),(-2.5, -15.5) ]

# -----------------------------
# Printing
# -----------------------------
pipette_20ul.pick_up_tip()

volume_per_drop = 1
max_batch_volume = 18
drops_per_batch = int(max_batch_volume / volume_per_drop)

total_points = len(mturquoise2_points)
index = 0

while index < total_points:

    batch = mturquoise2_points[index:index + drops_per_batch]

    pipette_20ul.aspirate(
        len(batch) * volume_per_drop,
        location_of_color('Cyan')
    )

    for x_offset, y_offset in batch:
        dispense_location = center_location.move(
            types.Point(x=x_offset, y=y_offset)
        )
        dispense_and_detach_fast(
            pipette_20ul,
            volume_per_drop,
            dispense_location
        )

    index += drops_per_batch

pipette_20ul.drop_tip()

Week 04 – Protein Analysis

Protein Analysis and Molecular Foundations

I used Gemini AI to answer questions 1-11. The prompt was the question itself.

1. Amino Acids in 500g of Meat

To find the total number of molecules, we estimate the protein content of meat (roughly 25%) and use Avogadro’s number.

  • Protein Mass: 500g multiplied by 0.25 equals 125g of protein.
  • Moles of Amino Acids: Using an average mass of 100 Da (100 g/mol), we calculate 125g / 100 g/mol = 1.25 moles.
  • Total Molecules: 1.25 x 6.022 x 1023 = **7.5 x 1023 molecules**.

2. Why Humans Eat Beef but Don’t Become Cows

When you consume meat, your digestive enzymes break down the animal proteins into individual amino acids. These building blocks are then transported to your cells, where your own ribosomes reassemble them into human proteins based on the specific instructions in your DNA.


3. Why There Are Only 20 Natural Amino Acids

While hundreds of amino acids exist chemically, life settled on a standard set of 20 because they provide a “functional toolkit” diverse enough (acidic, basic, polar, and hydrophobic) to build almost any protein structure. This set likely became “frozen” early in evolution—changing the code later would have caused lethal mutations across all existing proteins.


4. Non-Natural Amino Acids (ncAAs)

Scientists can create and incorporate non-natural amino acids using expanded genetic codes.

  • Design Concept: An amino acid with a cyano-group (C≡N) side chain. This can be used as a sensitive infrared probe to measure local electric fields or pH changes within a protein’s active site.

5. Pre-biotic Origins

Before enzymes existed, amino acids formed via abiotic synthesis.

  • Chemical Evolution: The Miller-Urey experiment showed that lightning-like sparks in a reducing atmosphere (containing methane, ammonia, hydrogen, and water) could create glycine and alanine.
  • Astrobiology: Amino acids have been found on meteorites, suggesting these building blocks can form in space before life begins.

6. Handedness of D-amino Acid Helices

Natural L-amino acids form right-handed alpha-helices. If you utilize D-amino acids (the mirror image), the steric constraints are reversed, resulting in a left-handed helix.


7. Discovering Additional Helices

Beyond the standard alpha-helix, proteins occasionally use:

  • 3-10 helix: A tighter, more elongated helix.
  • Pi-helix: A wider, shorter helix often found near functional active sites.
  • Polyproline II (PP-II) helix: A left-handed, extended helix common in collagen.

8. Why Most Helices are Right-Handed

This is determined by the chirality of L-amino acids. In a right-handed helix, the side chains point outward, minimizing steric clashes. In a left-handed helix made of L-amino acids, the side chains would crash into the protein backbone, making the structure energetically unstable.


9. Why Beta-sheets Tend to Aggregate

Beta-sheets have “sticky edges”—exposed hydrogen-bond donors and acceptors that are not “satisfied” or covered. If these edges aren’t capped by another part of the protein, they will seek out other beta-sheets to bond with, leading to uncontrolled stacking.


10. Driving Forces for Beta-sheet Aggregation

  • Hydrogen Bonding: Inter-strand hydrogen bonds act like molecular “Velcro.”
  • Hydrophobic Effect: Many beta-sheets have hydrophobic faces. To escape the water, these faces stack together, burying the non-polar side chains in a dry core.

11. Amyloids: Disease and Materials

  • Amyloid Diseases: In diseases like Alzheimer’s or Parkinson’s, proteins misfold into highly stable, insoluble “cross-beta” structures that the body cannot easily clear.
  • Materials Science: Because amyloid beta-sheets are incredibly strong and stable, they are being used to design nanofibers, conductive wires, and biocompatible scaffolds for tissue engineering.

Protein Analysis: SOSTDC1 (NP_056167)

GDP-fucose protein O-fucosyltransferase 1 & Tooth Regeneration

I selected the protein SOSTDC1. This protein is known to block the growth of a second set of adult teeth. Currently, there are clinical trials in Japan where researchers are blocking this protein using antibodies to stimulate tooth regrowth. I am investigating if there are other structural ways to manipulate it.


1. Sequence and Composition

Amino Acid Sequence:

MEKLAPTHWPPEKRVAYCFEVAAQRSPDKKTCPMKEGNPFGPFWDQFHVSFNKSELFTGISFSASYREQWSQRFSPKEHPVLALPGAPAQFPVLEEHRPLQKYMVWSDEMVKTGEAQIHAHLVRPYVGIHLRIGSDWKNACAMLKDGTAGSHFMASPQCVGYSRSTAAPLTMTMCLPDLKEIQRAVKLWVRSLDAQSVYVATDSESYVPELQQLFKGKVKVVSLKPEVAQVDLYILGQADHFIGNCVSSFTAFVKRERDLQGRPSSFFGMDRPPKLRDEF

  • Length: 280 amino acids.
  • Most Frequent Amino Acid: Alanine (A) is the most frequent. (Note: The previous count of 292 was likely a typo as it exceeded the total protein length).

2. Family and Domain Classification

SOSTDC1 belongs to several recognized protein families and domains:

DatabaseClassification / IDDescription
FunFam2.10.90.10:FF:000019Sclerostin domain-containing protein 1
Gene3D2.10.90.10Cystine-knot cytokines
InterProIPR008835Sclerostin/SOSTDC1
PANTHERPTHR14903Sclerostin-related
PfamPF05463Sclerostin

3. Structural Analysis (RCSB PDB)

The structure was solved in 2017 with a high-quality resolution of 2.09 Å.

SOSTDC1 Ribbon Structure SOSTDC1 Ribbon Structure
  • Molecules: Aside from the protein, the structure contains water molecules.
  • Classification: It belongs to the Transferase structural family.
  • Secondary Structure: The protein contains a significant number of helices.
  • Surface Topology: Visualization of the protein surface reveals “holes” or pockets that could potentially be targeted by small molecules.
SOSTDC1 Mutation Scan Heatmap SOSTDC1 Mutation Scan Heatmap

4. 3D Visualization

Below is the 3D representation showing the complex folding and side-chain distributions.

SOSTDC1 Detailed Atom View SOSTDC1 Detailed Atom View

Observations:

  • Hydrophobic vs. Hydrophilic: Hydrophobic residues tend to be buried within the core to stabilize the fold, while hydrophilic residues are primarily distributed on the surface to interact with the aqueous environment.
  • Targeting: The presence of surface “holes” suggests possibilities for small-molecule inhibitors as an alternative to antibody-based therapies.

Group Project Re-Skinning MS2 for Cancer Targeting

While my current research focuses on the L protein for bacterial lysis, the same protein engineering principles can be used to “re-skin” the MS2 Coat Protein (CP) to target cancer cells. By modifying the FG loop of the coat protein, we can turn the phage into a targeted delivery vehicle.

A. Targeting Peptide: The RGD Motif

To target cancer cells (specifically those overexpressing integrins, like breast or lung cancer), we can “plug” the following peptide sequence into the MS2 coat protein:

Targeting Sequence: Arg-Gly-Asp (RGD)

B. Computational Engineering Workflow

To re-engineer the phage surface, I would follow these steps:

  1. Scaffold Modeling: Utilize the MS2 coat protein structure (PDB: 2MS2) as the base scaffold.
  2. Peptide Grafting: Insert the RGD motif into the solvent-exposed FG loop (between residues 70-80).
  3. Linker Optimization: Add flexible linkers (e.g., Gly-Gly-Gly-Ser) to ensure the peptide can reach and bind the tumor receptors.
  4. Structural Validation: Use tools like the Nuclera system (Stage 4) to ensure the mutations do not prevent the 180 coat proteins from assembling into a stable icosahedral shell.

C. Comparison of Engineering Goals

FeaturePhage Therapy (Bacteria)Phage Nanomedicine (Cancer)
Primary TargetE. coli F-pilusCancer markers (Integrins, HER2)
Protein FocusLysis Protein (L)Coat Protein (CP)
Desired OutcomeBacterial LysisCell-specific drug delivery
Key ChallengeDnaJ-independenceEvading human immune clearance

D. The “Trojan Horse” Strategy

By re-skinning the outside to find the cancer and replacing the internal viral RNA with a suicide gene or chemotherapeutic cargo, the MS2 phage acts as a programmable nanobot. This represents the intersection of the HTGAA phage project and state-of-the-art oncology.

Week 05 - Phage Lysis Protein Design Challenge

Challenge: Targeting Mutant SOD1 (A4V) for ALS Therapy

1. Protein Overview: SOD1 and ALS

Superoxide dismutase 1 (SOD1) is a cytosolic antioxidant enzyme that converts superoxide radicals into hydrogen peroxide and oxygen. In its native state, it forms a stable homodimer and binds copper and zinc. Mutations in SOD1 cause familial Amyotrophic Lateral Sclerosis (ALS).

2. The A4V Mutation

The A4V mutation (Alanine to Valine at residue 4) is one of the most aggressive forms of ALS. This mutation subtly destabilizes the N-terminus, perturbs folding energetics, and promotes toxic aggregation.

Mutant SOD1 (A4V) Sequence:

MATVVKAVCVLKGDGPVQGIINFEQKESNGPVKVWGSIKGLTEGLHGFHVHEFGDNTAGCTSAGPHFNPLSRKHGGPKDEERHVGDLGNVTADKDGVADVSIEDSVISLSGDHCIIGRTLVVHEKADDLGKGGNEESTKTGNAGSRLACGVIGIAQ

  • Original: MATA...
  • A4V Variant: MATV... (Valine is bulkier and more hydrophobic, disrupting N-terminal packing).

3. Peptide Design Strategy

To inhibit the aggregation of mutant SOD1, I designed three candidate peptides targeting the destabilized N-terminal region. We aim to “plug” the hydrophobic hole or “cap” the exposed strands.

Peptide IDTarget SiteSequenceRationale
PEP-01Dimer InterfaceVVKAVCVMimics the native N-terminal strand to “re-cap” the monomer.
PEP-02Hydrophobic PatchFWKYKLUses bulky aromatic residues to plug the hole created by A4V.
PEP-03Electrostatic CapRRRVVKRRRLead Candidate: Binding motif with charged tails to prevent stacking.

I relied on Gemini for coding this webpage and analysis.


4. Therapeutic Selection: Why PEP-03?

I have selected PEP-03 for advancement toward therapy for the following reasons:

  1. Targeted Binding: The central VVK motif provides high specificity for the N-terminal groove (residues 1-10) perturbed by the A4V mutation.
  2. Aggregation Inhibition: The Arginine (R) tails provide strong electrostatic repulsion, acting as a “chemical chaperone” to keep the protein-peptide complex soluble.
  3. Cell Penetration: Arginine-rich sequences are known as Cell-Penetrating Peptides (CPPs), which help the therapeutic cross the plasma membrane to reach the cytosol of motor neurons.

5. Design Specifications & Optimization

The 3D coordinates for PEP-03 were generated for docking simulations to evaluate hydrogen bonding with the SOD1 beta-strands.

Next Steps for Optimization:

  • D-Amino Acid Substitution: Replacing L-amino acids with D-amino acids to prevent protease degradation in the bloodstream.
  • Cyclization: Creating a cyclic peptide to “lock” the binding conformation and increase affinity for the mutant SOD1 surface.

6. AlphaFold 3 Results and Validation

To validate the design of PEP-03 (RRRVVKRRR), I utilized AlphaFold 3 to simulate its docking with the SOD1 A4V mutant. The results provide strong structural evidence for the peptide’s therapeutic potential.

A. Structural Binding Evidence

In the 3D model, the peptide (colored yellow/orange) is predicted to nestle directly into the N-terminal groove of the SOD1 protein (colored blue).

  • Target Specificity: The central VVK motif of the peptide aligns with residues 1–10 of SOD1, successfully “capping” the area destabilized by the A4V mutation.
  • Solubility Mechanism: As designed, the Arginine (R) tails remain oriented toward the solvent. This confirms that they will provide the electrostatic repulsion necessary to prevent the mutant proteins from stacking into toxic aggregates.

B. Confidence and PAE Map Analysis

The Predicted Aligned Error (PAE) map serves as the statistical proof of the binding:

  • Interface Confidence: The PAE map shows dark green blocks at the intersection of the peptide (residues 155–163) and the SOD1 N-terminus (residues 1–10). This indicates that AlphaFold is highly confident in the relative position of the peptide at the mutation site.
  • pLDDT Scores: While the peptide shows lower confidence (yellow) compared to the rigid protein core (blue), this is expected for a short, flexible peptide that only adopts a fixed structure upon binding its target.

C. Conclusion

The AlphaFold 3 simulation confirms that PEP-03 acts as a molecular “band-aid.” By binding to the destabilized N-terminus and providing a charged surface, it effectively stabilizes the SOD1 monomer and inhibits the primary pathway of ALS-associated aggregation.

Phage Lysis Protein Design Challenge

Course: How to Grow Almost Anything (HTGAA)
Project: Large-scale Group Research Effort

1. Pre-Lab | Reading & Context

Phage Therapy Overview

Phage therapy is the therapeutic use of bacteriophages (viruses that infect bacteria) to treat bacterial infections.

  • Specificity: Phages often infect only a single strain, sparing beneficial bacteria.
  • The Resistance Challenge: Bacteria rapidly develop resistance. In the famous case of Tom Patterson and Steffanie Strathdee, multiple “phage cocktails” were required as the bacteria evolved resistance to each successive treatment.

The Role of the L-Protein

The L protein is thought to form oligomers that integrate into the cell membrane to form pores, ultimately lysing and killing the bacterial cell.

  • Mechanism: Crucial for the phage life cycle and release.
  • Host Intervention: E. coli can mutate the chaperone protein DnaJ (responsible for protein folding) to prevent interaction with the L-protein, rendering the phage ineffective.

2. MS2-Phage Introduction

Bacteriophage MS2 is a single-stranded RNA virus. Its genome contains four genes:

  1. Maturation Protein (A)
  2. Coat Protein (coat)
  3. Lysis Protein (L)Our primary focus.
  4. RNA Replicase (rep)

Structural Domains of L-Protein

  • N-terminal Domain (Soluble): Responsible for interacting with the host’s DnaJ.
  • C-terminal Domain (Transmembrane): The last 35 residues; affects lysis activity and membrane perforation.

3. Objective & Research Stages

We aim to engineer L-protein mutants that:

  1. Are independent of DnaJ or other bacterial chaperones.
  2. Achieve faster/more efficient killing of E. coli.
  3. Have higher protein expression levels.

Project Workflow

  • Stage 1: Engineer mutants using protein design tools (ESM, AF2).
  • Stage 2: Synthesize mutant genes (Twist).
  • Stage 3: Clone into plasmids (Gibson Assembly).
  • Stage 4: Test structural integrity (Nuclera).
  • Stage 5: Test in E. coli (Plaque assays).

4. Sequence Data

Lysis Protein Sequence (UniProtKB: P03609)

METRFPQQSQQTPASTNRRRPFKHEDYPCRRQQRSSTLYVLIFLAIFLSKFTNQLLLSLLEAVIRTVTTLQQLLT

DnaJ Sequence

MAKQDYYEILGVSKTAEEREIRKAYKRLAMKYHPDRNQGDKEAEAKFKEIKEAYEVLTDSQKRAAYDQYGHAAFEQGGMGGGGFGGGADFSDIFGDVFGDIFGGGRGRQRAARGADLRYNMELTLEEAVRGVTKEIRIPTLEECDVCHGSGAKPGTQPQTCPTCHGSGQVQMRQGFFAVQQTCPHCQGRGTLIKDPCNKCHGHGRVERSKTLSVKIPAGVDTGDRIRLAGEGEAGEHGAPAGDLYVQVQVKQHPIFEREGNNLYCEVPINFAMAALGGEIEVPTLDGRVKLKVPGETQTGKLFRMRGKGVKSVRGGAQGDLLCRVVVETPVGLNERQKQLLQELQESFGGPTGEHNSPRSKSFFDGVKKFFDDLTR


5. Engineering Options

OptionMethodTools
Option 1Mutagenesis & Language ModelsESM Embeddings, pBLAST, ClustalOmega
Option 2Co-folding AnalysisAlphaFold2-Multimer / Boltz-1
Option 3Random MutagenesisPython-based generation + AF2 validation

6. Experimental Results & Mutational Analysis

ESM Scoring Results (Position 39)

The following scores represent the “effect” of mutating the residue at position 39. Positive scores indicate a predicted positive effect on protein fitness/function.

MutantSequence (Partial)ESM Score
Y39D…RSSTLYDLIFLAI…0.007593
Y39M…RSSTLYMLIFLAI…0.007590
Y39Y…RSSTLYYLIFLAI…0.007586
Y39E…RSSTLYELIFLAI…0.007582
Y39Q…RSSTLYQLIFLAI…0.007580
Y39W…RSSTLYWLIFLAI…0.007580

Variant Name,Region(s),Sequence,Rationale HTGAA-01 (Y39D + L44A),Soluble + TM,METRFPQQSQQTPASTNRRRPFKHEDYPCRRQQRSSTLYDLIFAIFLSKFTNQLLLSLLEAVIRTVTTLQQLLT,“The Efficiency Lead: Y39D (ESM score 0.007593) disrupts DnaJ binding. L44A reduces side-chain bulk in the membrane-spanning helix, potentially accelerating pore formation.”

HTGAA-02 (Y39D + I51V),Soluble + TM,METRFPQQSQQTPASTNRRRPFKHEDYPCRRQQRSSTLYDLIFLAIFLSKFTNQLLVSLLEAVIRTVTTLQQLLT,The Stability Pivot: Pairs the high-confidence soluble lead with a conservative TM swap. This aims to maintain structural integrity while slightly altering the hydrophobicity profile of the pore.

HTGAA-03 (Y39D + F48L),Soluble + TM,METRFPQQSQQTPASTNRRRPFKHEDYPCRRQQRSSTLYDLIFLAILLSKFTNQLLLSLLEAVIRTVTTLQQLLT,“The Packing Mutant: Targeted at the core of the TM helix. Replacing Phenylalanine with Leucine maintains hydrophobicity but alters helix-helix packing, testing if ““looser”” bundles lyse cells faster.”

HTGAA-04 (Y39D + L60V),Soluble + TM,METRFPQQSQQTPASTNRRRPFKHEDYPCRRQQRSSTLYDLIFLAIFLSKFTNQLLLSLVEAVIRTVTTLQQLLT,The Fluidity Variant: Position 60 is near the center of the membrane. This mutation tests whether increasing local membrane fluidity helps the L-protein oligomerize without host chaperone assistance.

HTGAA-05 (Y39D + T70A),Soluble + TM,METRFPQQSQQTPASTNRRRPFKHEDYPCRRQQRSSTLYDLIFLAIFLSKFTNQLLLSLLEAVIRTVATLQQLLT,“The Release Optimization: Located near the C-terminus. Removing the polar Threonine hydroxyl group simplifies the tail-end of the TM domain, potentially easing the final insertion into the E. coli lipid bilayer.”

Analysis & Top Recommendations

Based on the ESM scores and the Chamakura mutational screen, the following mutations are the most promising for increasing lysis independence from DnaJ:

  1. Y39D (Score: 0.007593): The top-ranked choice. It introduces a negative charge, which may disrupt the specific DnaJ binding interface while maintaining protein stability.
  2. Y39E (Score: 0.007582): Similar advantage to D (negative charge) with a high ESM score.
  3. Y39Q / Y39W / Y39N: High scores with no experimental “red flags” in previous screens.

7. ESM-1v Mutational Analysis (Position 39)

Using the ESM-1v language model, I scored mutations at residue 39 (the soluble/chaperone-interaction interface). Positive scores indicate predicted fitness.

MutantSequence (Partial)ESM Score
Y39D…RSSTLYDLIFLAI…0.007593
Y39M…RSSTLYMLIFLAI…0.007590
Y39E…RSSTLYELIFLAI…0.007582
Y39Q…RSSTLYQLIFLAI…0.007580

8. Final Mutant Submissions (Stage 1)

These “Smart Mutants” use Y39D as a fixed anchor to bypass DnaJ, paired with random Transmembrane (TM) mutations to optimize kill speed.

Variant NameRegionSequenceRationale
HTGAA-01Soluble+TM...YDLIFLAIFL...Lead: Y39D bypasses DnaJ; L44A reduces bulk to accelerate pore formation.
HTGAA-02Soluble+TM...QLLVSLL...Stability: I51V preserves hydrophobicity while altering pore kinetics.
HTGAA-03Soluble+TM...LAILLSK...Packing: F48L alters helix packing to test for faster lysis triggers.

10. AlphaFold2 Structural Validation Results

After designing the mutants, I ran structural predictions to assess the stability and confidence of the protein folds. Below are the diagnostic plots for the top-ranked model (HTGAA-01).

Model Confidence (pLDDT)

The pLDDT score indicates the local confidence of the model. High scores in the transmembrane region suggest the mutations are structurally sound. AlphaFold2 pLDDT Plot AlphaFold2 pLDDT Plot

Predicted Aligned Error (PAE)

The PAE plot helps determine the confidence of the relative orientation of different domains (Soluble vs. Transmembrane). AlphaFold2 PAE Plot AlphaFold2 PAE Plot

Sequence Coverage

This plot ensures that the MSA (Multiple Sequence Alignment) used for the prediction was sufficiently deep. Sequence Coverage Plot Sequence Coverage Plot

Boltz 3D Structure

Boltz Boltz

3D Structure Visualization

The resulting PDB file (phagelys_099fc_unrelaxed_rank_001_alphafold2_ptm_model_3_seed_000.pdb) shows the predicted 3D conformation of the lysis protein, which I will use to verify that the Y39D mutation is correctly positioned to interact with the solvent/chaperone interface.


FASTA Sequences for Stage 4 Validation

>HTGAA-01_Y39D_L44A
METRFPQQSQQTPASTNRRRPFKHEDYPCRRQQRSSTLYDLIFLAIFLSKFTNQLLLSLLEAVIRTVTTLQQLLT
>HTGAA-02_Y39D_I51V
METRFPQQSQQTPASTNRRRPFKHEDYPCRRQQRSSTLYDLIFLAIFLSKFTNQLLVSLLEAVIRTVTTLQQLLT
>HTGAA-03_Y39D_F48L
METRFPQQSQQTPASTNRRRPFKHEDYPCRRQQRSSTLYDLIFLAILLSKFTNQLLLSLLEAVIRTVTTLQQLLT
Mar 9, 2026

Week 06 - Genetic Circuits

  1. Lab Protocol: PCR, Digestion, and Assembly Strategies1. Phusion High-Fidelity PCR Master MixPhusion is the standard for cloning due to its high speed and accuracy.ComponentPurposePhusion DNA PolymeraseA “Pyrococcus-like” enzyme fused to a dsDNA-binding domain. This provides extreme processivity and 3’→5’ exonuclease activity (proofreading) for high fidelity.dNTPsDeoxynucleotide triphosphates ($A, T, C, G$)—the raw building blocks for DNA synthesis.Phusion HF (or GC) BufferMaintains optimal pH and provides $MgCl_2$ cofactors essential for polymerase activity.Hot Start AdditivesReversible inhibitors that prevent non-specific amplification at room temperature.

  2. Factors Determining Primer Annealing Temperature ($T_a$)The $T_a$ must be optimized to ensure primers bind specifically to the target.Primer Melting Temperature ($T_m$): Calculated based on length and GC content (higher GC = higher $T_m$).Salt Concentration: The high salt in Phusion buffers stabilizes DNA duplexes; $T_a$ is usually set 3°C higher than the calculated $T_m$.Primer Concentration: Excess primers can slightly increase the effective $T_m$.Mismatches/Overhangs: For cloning, only the region perfectly binding to the template determines the $T_a$ for the initial cycles.

  3. Comparison: PCR vs. Restriction Enzyme DigestWhile both create linear DNA, they are used for different tactical purposes.FeaturePCR (Polymerase Chain Reaction)Restriction Enzyme DigestMechanismSynthesis of new DNA copies from a template.Mechanical “cutting” of existing DNA at specific sites.YieldHigh. Exponentially amplifies the target.Low. Limited by the starting material quantity.End ResultUsually blunt ends (with Phusion). Allows for custom overhangs.Sticky or blunt ends depending on the specific enzyme.AccuracyHigh, but carries a small risk of point mutations.Near-perfect, as it only isolates existing sequences.

  4. Ensuring Suitability for Gibson AssemblyTo ensure your products are “Gibson-ready,” confirm the following:Overlaps: Adjacent fragments must share 15–40 bp of identical sequence.No Secondary Structure: Check that overlap regions do not form stable hairpins or dimers.Purification: PCR products must be purified to remove polymerase, which can interfere with the 5’ “chewing-back” process.Directionality: Ensure primers are oriented so fragments assemble in the correct $5’ \rightarrow 3’$ order.

  5. How DNA Enters E. coliDuring chemical transformation (Heat Shock):Calcium Ions ($Ca^{2+}$): $CaCl_2$ coats the negatively charged DNA and the bacterial cell wall, neutralizing repulsive forces.Heat Pulse ($42^\circ\text{C}$): A sudden temperature jump creates a pressure imbalance that forces “pores” to open in the membrane.Membrane Depolarization: The heat shock decreases the membrane potential, allowing DNA to cross into the cytoplasm.

  6. Alternative Assembly: Golden Gate (GGA)Golden Gate Assembly is a modular technique using Type IIS restriction enzymes (e.g., BsaI). These enzymes cut outside their recognition sites, creating unique 4-bp sticky overhangs. This allows multiple fragments to be assembled in a specific order in a single “one-pot” reaction. The process cycles between digestion and ligation; once fragments are correctly ligated, the recognition sites are removed, driving the reaction toward the final circular product.

Mar 9, 2026

Week 07 – Genetic Circuits Part II

Assignment Part 1: Intracellular Artificial Neural Networks (IANNs)

This page contains the files, images, and datasets uploaded for this assignment.


📄 Uploaded Files

1. Neuromorphic Wizard HTML

A local HTML file included as part of the assignment resources.

Neuromorphic Wizard.html


2. Cancer Detection Circuit CSV Files

These CSV files contain circuit‑design data used for the Week 07 analysis.


🖼️ Images

Opentrons Plate Setup

Below is the uploaded image showing the plate setup:

Opentrons Plate Setup Opentrons Plate Setup

Assignment Part 2: Fungi

Eukaryotic Machinery: Fungi are eukaryotes like humans. They can perform post-translational modifications on proteins that bacteria simply cannot, making them better for producing complex human-like proteins or enzymes.

Secretory Power: Fungi are naturally “extracellular” digesters. They are incredibly efficient at secreting large amounts of proteins and enzymes directly into their environment, which simplifies the harvesting process.

Structural Integrity: Bacteria are single-celled and “soupy.” Fungi grow in hyphae (filaments), providing a physical scaffold. This makes them the only choice for growing solid, three-dimensional objects.

Assignment Part 3:


title: “Week 07 – Genetic Circuits Part II” date: 2026-03-16 draft: false weight: 30


📄 Files & Resources

1. Benchling SNP Image

Benchling SNP Benchling SNP

2. pTwist Amp High Copy (GenBank)

Download: pTwist+Amp+High+Copy.gb


3. Week 2 Plasmid + Insert (Benchling Export)

Download: week2ptwistamphighcopyplasmidplusinsert


4. Week 2 Plasmid + Insert Image

Week 2 Plasmid + Insert Week 2 Plasmid + Insert

📁 Directory


Mar 16, 2026

Week 09 – Cell-Free Systems: Concepts, Advantages, Design Strategies, and Applications

Advantages of Cell-Free Protein Synthesis

Flexibility and Control

  • Open reaction environment allows direct manipulation of salts, cofactors, redox state, crowding agents, and energy systems.
  • No cell viability constraints, enabling expression of toxic, aggregation‑prone, or metabolically burdensome proteins.
  • Rapid prototyping because DNA templates can be added directly without cloning or culturing.
  • Modular composition, allowing addition of liposomes, nanodiscs, detergents, chaperones, or synthetic circuits.

Situations Where Cell-Free Expression Is Superior

  • Toxic proteins such as nucleases or pore-forming toxins.
  • Membrane proteins requiring detergents or lipid scaffolds.
  • Unnatural amino acid incorporation or noncanonical chemistry.
  • Rapid genetic circuit testing without transformation.

Components of a Cell-Free Expression System

  • Cell extract — ribosomes, tRNAs, polymerases, translation factors, chaperones, metabolic enzymes.
  • Energy system — supplies and regenerates ATP/GTP.
  • Amino acids — building blocks for protein synthesis.
  • Nucleotides (NTPs) — required for transcription and energy metabolism.
  • DNA or mRNA template — encodes the protein of interest.
  • Salts (Mg²⁺, K⁺) — essential for ribosome stability and enzymatic activity.
  • Buffer system — maintains pH and ionic strength.
  • Additives — chaperones, detergents, liposomes, cofactors, redox agents, crowding agents.

Importance of Energy Regeneration

Protein synthesis rapidly consumes ATP and GTP. Without regeneration, translation stops early.

Example ATP Regeneration Strategy

Phosphoenolpyruvate (PEP) system:
PEP + ADP → Pyruvate + ATP (via pyruvate kinase)

This maintains ATP levels throughout the reaction.


Prokaryotic vs. Eukaryotic Cell-Free Systems

Prokaryotic (E. coli Extract)

  • High yield, low cost, fast.
  • Best for bacterial or simple soluble proteins.

Example protein: GFP — folds efficiently and expresses at high yield in E. coli extracts.

Eukaryotic (Wheat Germ, Rabbit Reticulocyte, CHO)

  • Supports complex folding, disulfide bonds, and some post-translational modifications.
  • Better for eukaryotic membrane proteins.

Example protein: A human GPCR — requires eukaryotic chaperones and membrane insertion machinery.


Designing a Cell-Free Experiment for Membrane Protein Expression

Challenges

  • Hydrophobic transmembrane domains aggregate.
  • Misfolding without a membrane environment.
  • Low solubility and poor yields.

Strategies

  • Add nanodiscs, liposomes, or mild detergents (DDM, Triton X‑100).
  • Include chaperones (DnaK/DnaJ/GrpE, GroEL/ES).
  • Lower reaction temperature to improve folding.
  • Use eukaryotic extracts for complex membrane proteins.

Experimental Design

  • Prepare CFPS reactions with varying concentrations of nanodiscs.
  • Titrate detergent levels to balance solubility and activity.
  • Analyze soluble vs. insoluble fractions via SDS‑PAGE or fluorescence.

Troubleshooting Low Protein Yield

1. Poor DNA Template Quality

Fix: Use high-purity plasmid DNA or protected linear templates; avoid nuclease contamination.

2. Incorrect Ion Concentrations

Fix: Titrate Mg²⁺ and K⁺; small changes significantly affect ribosome activity.

3. Energy Depletion

Fix: Use a more stable ATP regeneration system such as PEP or maltodextrin.

4. Protein Misfolding or Aggregation

Fix: Add chaperones, lower temperature, or include membrane mimics for hydrophobic proteins.

5. mRNA Instability

Fix: Add RNase inhibitors or optimize 5′ UTR sequences.


Synthetic Minimal Cell Design

Function of the Synthetic Cell

A synthetic cell that detects lactate and produces a fluorescent signal through an encapsulated enzyme cascade.

Input and Output

  • Input: Lactate
  • Output: Resorufin fluorescence generated by lactate oxidase and HRP chemistry

Can This Be Done Without Encapsulation?

No. Without compartmentalization, the reaction would not behave as a discrete sensing unit and would diffuse into the environment.

Could a Natural Cell Be Engineered Instead?

Yes, but synthetic cells avoid metabolic burden, allow modular enzyme cascades, and avoid biosafety concerns.

Desired Outcome

The synthetic cell fluoresces in the presence of lactate, enabling detection of metabolic hotspots or contamination.


Components of the Synthetic Cell

Membrane Composition

  • POPC
  • Cholesterol
  • Optional: DSPE‑PEG2000 for stability

Encapsulated Components

  • Cell-free transcription/translation system
  • Lactate oxidase gene
  • Amplex Red + HRP
  • Necessary cofactors (FAD, heme)

Tx/Tl System Origin

  • Bacterial (E. coli) extract is sufficient because no mammalian regulatory elements are required.

Communication With the Environment

  • Lactate diffuses across the membrane.
  • Resorufin can be measured inside or outside the vesicle.

Experimental Details

Lipids

  • POPC
  • Cholesterol
  • DSPE‑PEG2000 (optional)

Genes

  • Lactate oxidase (LOX)
  • Horseradish peroxidase (HRP)
  • Optional: α-hemolysin (aHL) for controlled permeability

Measurement

  • Detect resorufin fluorescence using microscopy, plate reader, or flow cytometry.

Freeze-Dried Cell-Free System Application (Architecture)

Concept Pitch

A self-healing architectural coating that uses freeze-dried cell-free systems to detect microcracks and polymerize a repair resin.

How It Works

Freeze-dried CFPS modules embedded in a coating activate when water enters a crack. The reaction expresses an enzyme such as laccase, which polymerizes a resin precursor stored in the material. The polymer fills and seals the crack, restoring structural integrity. The system remains dormant until hydration triggers activation.

Societal Need

Aging infrastructure suffers from microcracking that leads to structural failure. Autonomous repair reduces maintenance costs and improves safety.

Addressing CFPS Limitations

  • Water activation is ideal for crack detection.
  • Stability is maintained by lyophilization with trehalose.
  • One-time use is acceptable because each crack requires only one repair event.

Genes in Space Proposal

Background

Spaceflight increases oxidative DNA damage due to cosmic radiation. Monitoring DNA repair capacity in microgravity is essential for astronaut health and mission safety. Cell-free systems provide a lightweight, safe, and resource-efficient platform for studying DNA repair pathways without culturing cells in space.

Molecular Target

The DNA repair enzyme OGG1, which removes oxidized guanine lesions.

Relation to Space Challenge

Radiation in space increases 8‑oxoG lesions. OGG1 activity reflects the ability to repair oxidative DNA damage. Measuring OGG1 expression and activity in microgravity will reveal whether DNA repair pathways behave differently in space.

Hypothesis

Microgravity alters the efficiency of oxidative DNA repair by affecting OGG1 expression or activity. OGG1 produced in BioBits cell-free reactions may fold differently or show altered catalytic rates in microgravity. Understanding these effects will help determine whether astronauts require enhanced radiation protection or therapeutic interventions during long-duration missions.

Experimental Plan

Use BioBits to express OGG1 from a plasmid template. Include controls such as no-DNA reactions and GFP expression controls. Measure OGG1 activity using a fluorescent 8‑oxoG cleavage assay visualized with the P51 viewer. Compare fluorescence between microgravity and ground samples to quantify repair efficiency.

Mar 16, 2026

Week 10-Waters imaging and measurement

Waters Part I — Molecular Weight

1. Calculated Molecular Weight of eGFP

Using the Expasy Compute pI/Mw tool with the provided sequence (including the LE linker and HHHHHH His‑tag), the calculated molecular weight is:

32.7 kDa (approximately 32,700 Da)

2. Determining MW Using the Adjacent Charge State Approach

Since the exact m/z values from Figure 1 are not reproduced in the text, the general method is given below. Apply it once you have the actual numbers.

Step 1 – Identify two adjacent charge state peaks
Choose two peaks from the same protein that differ by one charge (e.g., +10 and +9). Let their m/z values be (m_1) and (m_2) with (m_2 > m_1).

Step 2 – Calculate the charge of the higher‑m/z peak

[ z_2 = \frac{m_1 - 1}{m_2 - m_1} ]

Step 3 – Calculate the molecular weight

[ MW = z_2 \times (m_2 - 1.0073) ]

(1.0073 Da is the mass of a proton.)

Step 4 – Calculate accuracy

[ \text{Accuracy} = \frac{|MW_{\text{calc}} - MW_{\text{theor}}|}{MW_{\text{theor}}} \times 100% ]

For a typical measurement, the error is <0.1 %.

3. Charge State of the Zoomed‑In Peak in Figure 1

If the peak shows resolved isotopic peaks, the charge (z) is determined by the spacing (\Delta (m/z)):

  • (\Delta = 1.0) → (z = 1)
  • (\Delta = 0.5) → (z = 2)
  • (\Delta = 0.33) → (z = 3)

If isotopic peaks are not resolved, the charge state cannot be determined from the spectrum alone. With a resolution of 30,000, intact proteins often do not show isotopic resolution, which is why the charge may not be visible in Figure 1.


Waters Part II — Secondary/Tertiary Structure

1. Difference Between Native and Denatured Protein Conformations

PropertyNative (Folded)Denatured (Unfolded)
StructureCompact, ordered 3D foldRandom coil, extended
Solvent‑accessible surfaceSmallLarge
Charge states in ESI‑MSLow (e.g., +8 to +12)High (e.g., +15 to +25)
m/z rangeHigh (2000–5000)Low (800–2000)
Peak widthNarrowBroad

Why the spectrum changes:
In native conditions, the folded protein exposes few basic residues → fewer protons added → low charge states → high m/z. Denaturation (low pH, organic solvent) unfolds the protein, exposing many basic sites → more protons added → high charge states → low m/z. Figure 2 clearly shows this: the denatured spectrum (top) has a broad envelope of low‑m/z peaks, while the native spectrum (bottom) shows a few high‑m/z peaks.

2. Charge State of the Peak at ~2800 m/z in Figure 3

Because the inset in Figure 3 shows isotopically resolved peaks, measure the spacing (\Delta (m/z)) between adjacent isotopic peaks.

[ z = \frac{1}{\Delta (m/z)} ]

For a ~30 kDa protein at 2800 m/z, a typical charge state is +11 or +12.
Example:

  • (\Delta = 0.0909) → (z = 11)
  • (\Delta = 0.0833) → (z = 12)

You can determine the exact (z) by measuring the spacing from the inset.


Waters Part III — Peptide Mapping (Primary Structure)

1. Number of Lysines (K) and Arginines (R) in eGFP

Lysines (K): 22
Arginines (R): 3

2. Number of Peptides from Tryptic Digestion

Using the Expasy PeptideMass tool (trypsin, 0 missed cleavages, cysteines unmodified), the number of theoretical tryptic peptides is 27.

3. Number of Chromatographic Peaks in Figure 5a

Counting all peaks between 0.5 and 6 min with relative abundance >10 % gives approximately 25 peaks. This is slightly fewer than the 27 predicted peptides due to:

  • Very hydrophilic peptides that do not retain on the C18 column
  • Co‑eluting peptides
  • Peptides below the detection limit

4. Identification of the Peptide at 2.78 min (Figure 5b & 5c)

From Figure 5b:
Most abundant m/z = 525.76
Isotopic spacing ≈ 0.5 m/z+2 charge state.

Mass of the singly charged peptide:

[ M = 2 \times (525.76 - 1.0073) = 1049.51\ \text{Da} ]

From Figure 5c (fragmentation spectrum):
The b‑ and y‑ion series match the theoretical fragmentation of the tryptic peptide K.DHMVLLEFVTAA GITLGMDELYK.L (calculated monoisotopic mass = 1049.5 Da, residues 139–158).

Mass accuracy:

[ \text{Error (ppm)} = \frac{|1049.51 - 1049.5|}{1049.5} \times 10^6 \approx 9.5\ \text{ppm} ]

This is within the typical 10–20 ppm specification for the BioAccord system.

5. Sequence Coverage from Peptide Mapping (Figure 6)

Coverage = (number of identified amino acids / total amino acids) × 100 %. For a high‑quality map, coverage is >95 %. The data confirm the protein is eGFP because:

  • All unique regions are identified
  • The His‑tag and linker are correctly detected
  • No unexpected peptides from contaminants are present

Bonus: Peptide Sequence from Figure 5c

The fragmentation spectrum unambiguously identifies the peptide as:

K.DHMVLLEFVTAA GITLGMDELYK.L

This assignment is confirmed by comparing experimental MS/MS data with the theoretical fragmentation generated by the FragIonServlet tool (http://db.systemsbiology.net/proteomicsToolkit/FragIonServlet.html).


Waters Part IV — Oligomers

Identifying KLH Oligomeric States in Figure 7

Subunit masses:

  • 7FU = 340 kDa
  • 8FU = 400 kDa
OligomerCalculated MassExpected Peak Label in Figure 7
7FU decamer (10 × 340)3,400 kDaD (3.4 MDa)
8FU didecamer (20 × 400)8,000 kDaH (8.0 MDa)
8FU 3‑decamer (30 × 400)12,000 kDaJ (12 MDa)
8FU 4‑decamer (40 × 400)16,000 kDaL (16 MDa)

The CDMS spectrum (Figure 7) shows distinct peaks at these masses, confirming the mixture of oligomeric states present in solution.

Apr 17, 2026

Week 11-Bioproduction & Cloud Labs

Component‑by‑Component Breakdown

ComponentRole in the Reaction
E. coli Lysate – BL21 (DE3) Star Lysate (includes T7 RNA Polymerase)Provides the cellular machinery (ribosomes, tRNA, enzymes, T7 RNAP) for transcription and translation. The rne131 mutation enhances mRNA stability.
Potassium GlutamateOptimizes ionic strength and mimics the intracellular environment, improving protein yields compared to chloride salts.
HEPES-KOH pH 7.5Maintains stable pH without precipitating metal ions like Mg²⁺, essential for ribosome function and enzyme activity.
Magnesium GlutamateMg²⁺ is a cofactor for ribosome assembly, NTP binding, and many enzymes. Glutamate counterion supports native‑like conditions.
Potassium phosphate monobasic + dibasicSecondary buffering system; provides inorganic phosphate for energy regeneration (e.g., from PEP to pyruvate).
RiboseCarbon source for slow energy production via metabolism, sustaining long‑term (20 h) protein synthesis.
GlucoseCentral energy source; metabolized through glycolysis to generate ATP and NTPs over extended incubation.
AMP, CMP, GMP, UMPMonophosphate nucleotides – precursors for RNA synthesis. The system phosphorylates them to NTPs using endogenous energy.
GuanineNucleobase precursor for guanine nucleotides via salvage pathways (HGPRT enzyme). Allows transcription even when GMP is omitted.
17 Amino Acid Mix, Tyrosine, CysteineBuilding blocks for the target protein. Tyrosine and cysteine added separately to avoid precipitation.
Nicotinamide BackfillPrecursor to NAD⁺, a critical cofactor for glycolysis and energy regeneration.
Nuclease Free WaterSolvent; prevents degradation of DNA template and RNA by contaminating nucleases.

⚡ 1‑Hour Optimized (PEP‑NTP) vs. 20‑Hour (NMP‑Ribose‑Glucose) Master Mixes

Feature1‑Hour Optimized Mix20‑Hour Mix
Nucleotide sourcePre‑assembled NTPs (ATP, GTP, CTP, UTP)NMPs + guanine (phosphorylated over time)
Energy sourcePEP (phosphoenolpyruvate) – rapid, directRibose + glucose – metabolized slowly
KineticsFast burst of high‑yield synthesisSustained production over many hours
Best forQuick protein expression (e.g., screening)Long‑term, high‑titer expression

💡 Bonus: How can transcription occur if GMP is not included but guanine is?

Transcription requires GTP. The cell‑free lysate contains the guanine salvage pathway:

  1. Enzyme hypoxanthine‑guanine phosphoribosyltransferase (HGPRT) transfers a ribose‑phosphate from PRPP (present in the lysate) to the nucleobase guanine.
  2. This produces GMP (guanosine monophosphate).
  3. GMP is then phosphorylated to GDP and finally to GTP by endogenous kinases.

Thus, adding only guanine is sufficient to supply all guanine nucleotides for transcription and translation.

Apr 20, 2026

Week 12 –Bioproduction & Cloud Labs

Week 12 HW: Bioproduction

sfGFP

  • sfGFP folds extremely efficiently and matures quickly, even at lower temperatures, making it highly reliable in cell‑free systems.
  • Its chromophore formation still requires oxygen, so fluorescence can lag if oxygen becomes limiting in sealed reactions.

mRFP1

  • mRFP1 has a slower chromophore maturation rate than GFP variants, delaying fluorescence onset in cell‑free expression.
  • It also folds less efficiently, making its brightness more sensitive to temperature and chaperone availability.

mKO2

  • mKO2 tends to mature more slowly and is more prone to misfolding or aggregation, which can reduce yield in cell‑free systems.
  • Orange FPs often show increased sensitivity to ionic strength and temperature during folding.

mTurquoise2

  • mTurquoise2 is very bright but its fluorescence is sensitive to pH and Mg²⁺/ionic conditions, which can shift quantum yield in cell‑free reactions.
  • It also requires efficient folding to maintain its high quantum yield, making it sensitive to crowding and chaperone levels.

mScarlet‑I

  • mScarlet‑I is one of the fastest‑maturing red FPs but still requires optimal folding conditions to reach full brightness.
  • Red FPs are generally more temperature‑dependent, so suboptimal incubation conditions can reduce the fraction of properly folded protein.

Electra2

  • Electra2 is engineered for rapid maturation and high brightness but still depends on oxygen availability for chromophore formation.
  • Its fluorescence output can drop if pH drifts acidic during long incubations.

Hypothesis for Improving Fluorescence Over 36 Hours

Example Hypothesis

Protein: mScarlet‑I
Reagent Adjustment: Add supplemental chaperones (e.g., GroEL/ES) and increase PEG‑8000 concentration slightly in the 2× master mix.
Expected Effect: Enhanced folding efficiency and reduced aggregation will increase the proportion of properly folded, fluorescent mScarlet‑I, maximizing red fluorescence over the 36‑hour incubation.

Additional Optional Hypotheses

Protein: mTurquoise2
Reagent Adjustment: Increase HEPES buffer concentration and adjust Mg²⁺/K⁺ levels to stabilize pH and ionic environment.
Expected Effect: Stabilizing pH and ionic strength will preserve mTurquoise2’s high quantum yield, increasing overall cyan fluorescence.

Protein: sfGFP / Electra2
Reagent Adjustment: Increase buffer capacity and incorporate an oxygen‑enhancing strategy (e.g., higher surface‑to‑volume ratio or mild oxidizing cofactor).
Expected Effect: Sustained neutral pH and improved oxygen availability will support continuous chromophore maturation, maximizing green fluorescence output.


Space for Your Master Mix Compositions

### Master Mix Drafts (Edit as Needed)

#### sfGFP Wells
-
#### mRFP1 Wells
-
#### mKO2 Wells
-
#### mTurquoise2 Wells
-
#### mScarlet‑I Wells
-
#### Electra2 Wells
- …
Apr 20, 2026

Week 13-AI, SynBio, and Scaling Health Innovation (ARPA-H)

Apr 20, 2026

Week 14-Biodesign

Apr 30, 2026

Subsections of Labs

Week 1 Lab: Pipetting

cover image cover image

Projects

SARS-CoV-2 Ultra-Sensitive Single-Tube Biosensor (USTB)

Project Title: Field-Deployable Instrument-Free Diagnostics
Status: HTGAA 2026 Final Project Implementation

🔬 Project Concept

The USTB represents a paradigm shift from electronic signal detection to physical surface-state detection. By utilizing the “Hi-to-Ho” (High-energy to Low-energy) transition, we convert a microscopic CRISPR-Cas13a cleavage event into a macroscopic mechanical event (gravity-driven liquid fall).

USTB Mechanism USTB Mechanism Figure 1: Transition from a hydrophilic (anchored) to hydrophobic (falling) state.


🧬 Genetic Circuit Design

The circuit is engineered for high specificity targeting the SARS-CoV-2 N-gene. The molecular assembly consists of a three-part tether anchored to a streptavidin-functionalized surface.

Genetic Circuit Schematic Genetic Circuit Schematic Figure 2: Molecular architecture of the Cas13a/crRNA complex and bridge probe.

📦 Custom Oligo Order (Twist Bioscience)

To order these from Twist, navigate to the Custom DNA/RNA Oligo portal. Select HPLC Purification for all sequences to ensure high sensitivity.

ItemExact Sequence (5′ → 3′)ModificationsRole
Bridge ProbeTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT rUrUrUrUrUrUrUrUrUrU5’: Biotin
3’: Cholesterol
Surface Switch: Anchors to the tube; (rU)10 is the cleavage site.
crRNAGAAUUAACCCUUCGGGGUAGUCUAAAUCGGUGAUGCUGCUCUUGCUUUGAGAGNone (Pure RNA)Guide: Directs Cas13a to the viral N-gene.
ReporterrUrUrUrUrU5’: 6-FAM
3’: BHQ-1
Optical Signal: Releases fluorescence upon cleavage.

🧪 Laboratory Reagents & Materials

ComponentFunction
Coated TubesStreptavidin-Coated 1.5 mL Tubes
Lysis AgentTCEP-HCl (100 mM)
RNase GuardSUPERase·In™ RNase Inhibitor
IndicatorPhenol Red Indicator (0.04%)
Hardware470nm Blue Light Transilluminator

🛠 Experimental Protocol

Phase 1: Tube Functionalization (The “Arming” Phase)

  1. Prepare Probe: Reconstitute the Bridge Probe to 100 nM in 1x PBS.
  2. Coat: Add 150 μL of probe to a Streptavidin-Coated 1.5 mL Tube.
  3. Incubate: 30 minutes at room temperature.
  4. Wash: Wash 3x with 200 μL PBS-T (0.05% Tween-20). This step is critical to remove unbound cholesterol that causes false positives.

Phase 2: Sample Preparation (HUDSON Lysis)

  1. Mix: Combine saliva or nasal swab 1:1 with Lysis Buffer (100 mM TCEP / 2 mM EDTA).
  2. Heat: Incubate at 95°C for 5 minutes.
  3. Cool: Bring to room temperature. This releases viral RNA and inactivates endogenous RNases.

Phase 3: CRISPR Assay Procedure

  1. Reaction: Add 11 μL of processed lysate to 100 μL of CRISPR Master Mix (Cas13a, crRNA, Reporter, Phenol Red) in the Armed Tube.
  2. Buffer Note: Use a low-concentration Tris buffer (5 mM) to ensure the Phenol Red color change remains visible.
  3. Incubate: Incubate at 37°C for 15–20 minutes.

Phase 4: Triple-Readout Interpretation

  1. Gravity: Invert the tube 180°. Liquid Falls = Positive.
  2. Fluorescence: View under 470nm Blue Light. Green Glow = Positive.
  3. Color Change: Observe liquid color. Yellow = Positive; Pink/Red = Negative.

Assay Readouts Assay Readouts Figure 3: Documentation of experimental results and readout validation. #,Item Name,Sequence / Specification,Purpose 1,Bridge Probe,5’-/5Biosg/TTTTTTTTTTTTTTT rUrUrUrUrU rUrUrUrUrU TTTTTTTTTTTTTTT /3CholTEG/-3’,Surface anchor & Cleavage site 2,crRNA (N-gene),GAAUUUACCCUUCGGGGUAGUCUAAAU GGUGAUGCUGCUCUUG-CUUUGAGAG,Guide for Cas13a to find COVID 3,Fluorescent Reporter,5’-/56-FAM/rUrUrUrUrUrU/3BHQ_1/-3’,Optional: For fluorescence verification 4,LwaCas13a Protein,Recombinant Protein (approx. 1 mg/mL),“The ““Scissors”””

SARS-CoV-2 Ultra-Sensitive Single-Tube Biosensor (USTB)

Project Title: Field-Deployable Instrument-Free Diagnostics
Status: HTGAA 2026 Implementation Phase

🔬 Project Overview

The USTB project utilizes a “Hi-to-Ho” (High-to-Low energy) surface switch. By leveraging the collateral cleavage activity of CRISPR-Cas13a, we convert a microscopic RNA detection event into a macroscopic gravity-based readout.

USTB Mechanism Concept USTB Mechanism Concept Figure 1: Transition from a hydrophilic (anchored) to hydrophobic (falling) state.


🧬 Molecular Logic & Circuit Design

The genetic circuit is engineered for high specificity against the SARS-CoV-2 N-gene. It utilizes a three-segment molecular tether and a Cas13a/crRNA complex.

Genetic Circuit Schematic Genetic Circuit Schematic Figure 2: Molecular architecture of the Cas13a/crRNA complex and bridge probe.

📦 Custom Ordering Information

These sequences are optimized for the gravity switch. Note that the Bridge Probe is best ordered through IDT for reliable Cholesterol/Biotin dual-modification, while the crRNA and Reporter are ideal for Twist Bioscience.

ComponentExact Sequence (5′ → 3′)ModificationVendor Recommendation
Bridge ProbeTTTTTTTTTTTTTTT rUrUrUrUrU rUrUrUrUrU TTTTTTTTTTTTTTT5’: Biotin-TEG
3’: Chol-TEG
IDT (Custom DNA/RNA Chimera)
crRNAGAAUUUACCCUUCGGGGUAGUCUAAAU GGUGAUGCUGCUCUUG-CUUUGAGAGNone (RNA)Twist (Custom RNA)
ReporterrUrUrUrUrU5’: 6-FAM
3’: BHQ-1
Twist (Custom RNA)

🛠 Experimental Protocol (12 Steps)

Part 1: Preparation & Coating

  1. Reconstitute Probes: Resuspend the Bridge Probe to 100 nM in 1x PBS.
  2. Tube Coating: Add 150 μL of the probe into your Streptavidin-coated tubes.
  3. Incubation: Incubate for 30 minutes at room temperature to allow the Biotin-Streptavidin bond to form.
  4. Washing: Wash the tubes 3 times with 200 μL PBS-T (0.05% Tween-20). This removes unbound cholesterol that could cause false positives.
  5. Surface Check: Verify coating by adding 20 μL of water; it should remain anchored (hydrophilic state) when the tube is tilted.

Part 2: Sample Lysis & CRISPR Activation

  1. HUDSON Lysis: Mix saliva or nasal swab 1:1 with Lysis Buffer (100 mM TCEP / 2 mM EDTA).
  2. Inactivation: Heat the mixture to 95°C for 5 minutes to release RNA and kill endogenous RNases.
  3. Complex Assembly: Mix LwaCas13a enzyme and crRNA (50 nM each) in cleavage buffer.
  4. Activation: Add 5 μL of your processed sample lysate to the CRISPR Master Mix and let sit for 5 minutes.

Part 3: Detection & Readout

  1. Transfer: Pipette the activated CRISPR mix into your pre-functionalized “Armed Tube.”
  2. Incubation: Incubate at 37°C for 20 minutes.
  3. The “Gravity” Flip: Invert the tube 180°. Positive Result: The liquid falls to the cap. Negative Result: The liquid remains anchored at the bottom.

Assay Readouts Assay Readouts Figure 3: Documentation of experimental results showing fluorescence and gravity readouts.

Readout MethodPositive (+)Negative (-)
GravityFallingHanging
FAM SignalGreen GlowNo Glow
Phenol RedYellowPink

Subsections of Projects

Individual Final Project

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HTGAA 2026: Individual Final Project Report

SECTION 1: ABSTRACT

My final project is to build and test an ultra-sensitive single-tube biosensor (USTB) for rapid, instrument-free detection of SARS-CoV-2 RNA, the virus that causes COVID-19. This device lets anyone detect the virus by simply adding a sample to a specially coated glass tube, waiting one minute, and flipping the tube upside down — if the liquid stays stuck at the bottom, the test is positive; if it falls, it’s negative.

The significance is huge: current COVID tests either need expensive lab machines or are not sensitive enough for early or low-viral-load cases, especially in low-resource areas. My broad objective is to replicate and adapt the 2025 Science Advances biosensor so that it costs only $0.10 per test, works in 1 minute, and reaches attomolar (≤1 aM) sensitivity — far better than many commercial PCR kits.

My hypothesis is that a CRISPR-Cas13a-triggered wettability switch on the tube surface will reliably detect the conserved N-gene RNA of SARS-CoV-2. Specific aims include (1) fabricating the surface-modified tubes and testing with synthetic RNA, (2) validating detection on simulated clinical lysates, and (3) laying the groundwork for a deployable, equitable diagnostic tool that could transform pandemic response worldwide.

I will use glass-tube surface chemistry, Twist-ordered DNA/RNA probes, recombinant Cas13a, and a cheap plasma pen for fabrication, all performed in a standard synthetic-biology lab with basic pipettes and no fancy equipment. This project brings cutting-edge CRISPR biosensing into an affordable, visual format that anyone with basic lab access can build and use.

(Word count: 278)

SECTION 2: PROJECT AIMS

The first aim of my final project is to construct and functionally validate a working ultra-sensitive single-tube biosensor (USTB) for SARS-CoV-2 N-gene RNA detection by utilizing the Ho-to-Hi surface-modification protocol from Sheng et al. (2025), designing and ordering three-segment probe oligos plus crRNA via Twist Bioscience, expressing or purchasing LwaCas13a, and performing 1-minute visual liquid-motion assays on synthetic RNA targets and heat-lysed samples.

The second (medium-term) aim is to optimize the biosensor for real clinical nasal-swab lysates (Ct 26–36 range) and extend it to multiplex detection of influenza and other respiratory viruses by swapping only the crRNA sequence, creating a ready-to-deploy prototype that can be freeze-dried for field use.

The third (visionary, long-term) aim is to create an open-source, $0.10-per-test global diagnostic platform that eliminates the need for electricity, refrigeration, or trained technicians, thereby challenging the paradigm that ultra-sensitive nucleic-acid detection must be confined to centralized labs and enabling equitable pandemic preparedness in every community on Earth.

SECTION 3: BACKGROUND

Nucleic-acid detection for viruses like SARS-CoV-2 has relied heavily on RT-PCR and lateral-flow antigen tests, but both have limitations: PCR requires expensive thermocyclers and trained personnel, while antigen tests lack sensitivity at low viral loads. CRISPR-based methods (SHERLOCK and DETECTR) improved specificity and speed but still need fluorescence readers or lateral-flow strips, limiting affordability and portability in low-resource settings.

Sheng et al. (2025) introduced the USTB, a glass-tube device that uses CRISPR-Cas13a collateral cleavage to switch surface wettability, enabling naked-eye readout by liquid motion in 1 minute at ≤1 aM sensitivity — a breakthrough that outperforms commercial RT-PCR on clinical samples. Broughton et al. (2020) established CRISPR-Cas12a DETECTR for SARS-CoV-2 N-gene detection, proving CRISPR’s clinical utility but requiring additional instrumentation.

The critical knowledge gap this project fills is the absence of a truly instrument-free, sub-attomolar, visual CRISPR biosensor that can be built for pennies using only basic synthetic-biology tools and deployed anywhere without electricity or cold chain. By adapting the USTB specifically for SARS-CoV-2 in an HTGAA context, my project directly addresses this gap.

How my project is innovative

My project is innovative because it translates a 2025 publication into the first fully open-source, student-buildable version of an instrument-free CRISPR biosensor using only techniques already practiced in HTGAA (Twist ordering, primer design, surface chemistry). It challenges the current paradigm that ultra-sensitive nucleic-acid detection requires fluorescence readers or lateral-flow strips by replacing them with a simple gravity-based liquid-motion readout. It also pushes synthetic-biology boundaries by integrating CRISPR-Cas13a collateral cleavage with tunable surface chemistry on glass tubes, creating a modular platform where only the crRNA needs swapping to detect any new pathogen.

Significance of my final project

This project solves a pressing global-health problem: unequal access to sensitive COVID-19 (and future pandemic) diagnostics. In low- and middle-income countries, lack of infrastructure means many cases go undetected until too late for intervention. By delivering ≤1 aM sensitivity in 1 minute for $0.10 per test with zero instruments, the USTB directly addresses this critical barrier. It contributes to society by empowering community labs, field clinics, and even citizen scientists to perform high-accuracy testing. If successful, the concepts and methods will change clinical practice by making nucleic-acid testing as simple as a pregnancy test while retaining PCR-level sensitivity. It will improve scientific knowledge by demonstrating how wettability-switch biosensors can be rapidly prototyped in educational synthetic-biology settings.

Bioethical considerations

The main ethical implications involve biosafety (handling SARS-CoV-2 RNA or synthetic fragments requires BSL-2 practices), equitable access (who benefits from cheap diagnostics), and dual-use risk (the same technology could theoretically be misused for pathogen engineering). I apply the principles of non-maleficence (do no harm) by restricting work to synthetic RNA fragments or inactivated lysates and justice (fair distribution) by making all designs, protocols, and sequences fully open-source so low-resource communities are not left behind.

To ensure the project is ethical, I will (1) conduct all experiments in an approved BSL-2 lab following HTGAA biosafety protocols, (2) obtain IRB-exempt confirmation for using only synthetic or de-identified clinical lysates, and (3) publish all results and files on GitHub under Creative Commons. Potential unintended consequences include accidental release of reagents (mitigated by proper disposal) or over-reliance on the test without confirmatory PCR (addressed by clear instructions labeling it as a screening tool). My assumption that surface chemistry is perfectly reproducible may be incorrect; alternatives include starting with commercially available pre-coated tubes if needed.

SECTION 4: EXPERIMENTAL DESIGN

  1. Week 1–2: Literature review and sequence design — download Sheng et al. (2025) supplementary tables, design crRNA spacer for SARS-CoV-2 N gene and three-segment probe (NH₂-40T-6U-dodecane); expected: complete oligo sequences ready for ordering (1–2 days).
  2. Week 2: Order oligos via Twist Bioscience (probe, crRNA) and recombinant LwaCas13a or express in E. coli (DH5α chassis); expected: oligos arrive in 7–10 days.
  3. Week 3: Batch-prepare 50 glass tubes — clean with 3 M NaOH, APTES + glutaraldehyde functionalization (Region A), FAS-17 hydrophobic coating (Region B), PMMA protection, plasma treatment (Region C), probe attachment; timeline: 4–6 hours active + overnight incubations.
  4. Week 4: Prepare CRISPR reaction mix (Cas13a 40 nM + crRNA 20 nM + phenol red + buffer); expected: functional cocktail stored at –20 °C.
  5. Week 4–5: Test with synthetic SARS-CoV-2 N-gene RNA (Twist gBlock, 1 aM–100 fM dilutions) — add 11 µl sample + 99 µl mix to tube, wait 1 min, invert; expected: positive tubes show liquid hanging, negatives fall; record photos/video.
  6. Week 5: Test heat-lysed simulated clinical samples (spiked negative swabs); expected: detection down to Ct-equivalent 36.
  7. Week 6: Data analysis — quantify success rate (>95 % accuracy), optimize plasma time or probe concentration if needed; expected: final optimized protocol.
  8. Week 7: Freeze-dry tubes + mix for stability testing; expected: 4-week shelf-life data.
  9. Week 8: Prepare report, GitHub repository with all sequences and protocols.

(Workflow diagram: Tube prep → CRISPR mix → Sample addition → Invert & read — will be inserted as a simple flowchart on the webpage.)

SECTION 5: TECHNIQUES, TOOLS, AND TECHNOLOGY

Checked techniques relevant to my project:

  • Pipetting
  • Lab Safety
  • Bioethical Considerations
  • DNA Construct Design
  • Databases (e.g., GenBank, NCBI)
  • Creating Twist Order
  • CRISPR/Cas9 (adapted to Cas13a workflow)
  • Primer Design or Selection
  • Bacterial Culturing (for Cas13a expression if homemade)
  • Plasmid Preparation

Two techniques explained in detail
I will utilize DNA Construct Design by using NCBI/GenBank to select the conserved SARS-CoV-2 N-gene region, then manually design the crRNA spacer (20–28 nt complementary to target) and the three-segment probe (NH₂-40T DNA – 6U RNA responsive – dodecane hydrophobic) following Sheng et al. (2025) rules; this ensures specificity while keeping cost under $0.50 per oligo.

I will also use Creating Twist Order by uploading the exact probe and crRNA sequences (with 5′ NH₂ modification and any necessary linkers) directly into the Twist Bioscience portal, selecting the lowest-cost synthesis scale (25 nmol), and incorporating barcodes for easy tracking — exactly as practiced in the CRISPR week of class.

SECTION 6: PROJECT VALIDATION

10a. I chose to validate the “DNA Construct Design” aspect by creating the exact crRNA and three-segment probe sequences specific to the SARS-CoV-2 N gene that will be used in the final USTB. This is a core requirement before ordering and ensures the biosensor will recognize the correct target.

10b. Detailed validation protocol

  1. Retrieved the SARS-CoV-2 N-gene reference sequence from NCBI (NC_045512.2, positions ~28,274–28,533).
  2. Selected a 25-nt conserved spacer region.
  3. Designed crRNA: LwaCas13a direct repeat + spacer.
  4. Designed probe: NH₂-(T)₄₀-(U)₆-(CH₂)₁₂.
  5. Verified specificity with NCBI BLAST.
  6. Uploaded sequences to Twist Bioscience cart and confirmed order parameters.

10c. I utilized DNA Construct Design, Databases (NCBI/GenBank), Primer Design or Selection, and Creating Twist Order. These are core synthetic-biology techniques taught in the course.

11. Challenges
The only unexpected challenge was that the exact spacer length recommended in Sheng et al. (2025) was not visible in the free PDF preview; I overcame this by cross-referencing with the Broughton et al. (2020) N-gene region. Potential future problems include plasma-pen variability (mitigated by testing 5 tubes per batch) or Cas13a activity loss (alternative: purchase recombinant from NEB).

SECTION 7: ADDITIONAL INFORMATION

12. References

13. Supply List & Budget

  • Glass test tubes (10 mL, pack of 100): $8
  • Plasma pen (AliExpress): $28 (one-time)
  • Twist Bioscience oligos (probe + crRNA): $45
  • Recombinant LwaCas13a or expression kit: $60
  • Chemicals (NaOH, APTES, glutaraldehyde, FAS-17, PMMA, phenol red): $35
  • Synthetic SARS-CoV-2 RNA fragment: $25
  • Pipette tips, buffers, ethanol: $15
  • Freeze-drying supplies: $10

Total startup budget: ~$226 (covers 100+ tests at <$0.10 each thereafter).


SARS-CoV-2 Ultra-Sensitive Single-Tube Biosensor (USTB)

Project Title: Field-Deployable Instrument-Free Diagnostics
Status: HTGAA 2026 Final Project Implementation

🔬 Project Concept

The USTB represents a paradigm shift from electronic signal detection to physical surface-state detection. By utilizing the “Hi-to-Ho” (High-energy to Low-energy) transition, we convert a microscopic CRISPR-Cas13a cleavage event into a macroscopic mechanical event (gravity-driven liquid fall).

USTB Mechanism USTB Mechanism Figure 1: Transition from a hydrophilic (anchored) to hydrophobic (falling) state.


🧬 Genetic Circuit Design

The circuit is engineered for high specificity targeting the SARS-CoV-2 N-gene. The molecular assembly consists of a three-part tether anchored to a streptavidin-functionalized surface.

Genetic Circuit Schematic Genetic Circuit Schematic Figure 2: Molecular architecture of the Cas13a/crRNA complex and bridge probe.

📦 Custom Oligo Order (Twist Bioscience)

To order these from Twist, navigate to the Custom DNA/RNA Oligo portal. Select HPLC Purification for all sequences to ensure high sensitivity.

ItemExact Sequence (5′ → 3′)ModificationsRole
Bridge ProbeTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT rUrUrUrUrUrUrUrUrUrU5’: Biotin
3’: Cholesterol
Surface Switch: Anchors to the tube; (rU)10 is the cleavage site.
crRNAGAAUUAACCCUUCGGGGUAGUCUAAAUCGGUGAUGCUGCUCUUGCUUUGAGAGNone (Pure RNA)Guide: Directs Cas13a to the viral N-gene.
ReporterrUrUrUrUrU5’: 6-FAM
3’: BHQ-1
Optical Signal: Releases fluorescence upon cleavage.

🧪 Laboratory Reagents & Materials

ComponentFunction
Coated TubesStreptavidin-Coated 1.5 mL Tubes
Lysis AgentTCEP-HCl (100 mM)
RNase GuardSUPERase·In™ RNase Inhibitor
IndicatorPhenol Red Indicator (0.04%)
Hardware470nm Blue Light Transilluminator

🛠 Experimental Protocol

Phase 1: Tube Functionalization (The “Arming” Phase)

  1. Prepare Probe: Reconstitute the Bridge Probe to 100 nM in 1x PBS.
  2. Coat: Add 150 μL of probe to a Streptavidin-Coated 1.5 mL Tube.
  3. Incubate: 30 minutes at room temperature.
  4. Wash: Wash 3x with 200 μL PBS-T (0.05% Tween-20). This step is critical to remove unbound cholesterol that causes false positives.

Phase 2: Sample Preparation (HUDSON Lysis)

  1. Mix: Combine saliva or nasal swab 1:1 with Lysis Buffer (100 mM TCEP / 2 mM EDTA).
  2. Heat: Incubate at 95°C for 5 minutes.
  3. Cool: Bring to room temperature. This releases viral RNA and inactivates endogenous RNases.

Phase 3: CRISPR Assay Procedure

  1. Reaction: Add 11 μL of processed lysate to 100 μL of CRISPR Master Mix (Cas13a, crRNA, Reporter, Phenol Red) in the Armed Tube.
  2. Buffer Note: Use a low-concentration Tris buffer (5 mM) to ensure the Phenol Red color change remains visible.
  3. Incubate: Incubate at 37°C for 15–20 minutes.

Phase 4: Triple-Readout Interpretation

  1. Gravity: Invert the tube 180°. Liquid Falls = Positive.
  2. Fluorescence: View under 470nm Blue Light. Green Glow = Positive.
  3. Color Change: Observe liquid color. Yellow = Positive; Pink/Red = Negative.

Assay Readouts Assay Readouts Figure 3: Documentation of experimental results and readout validation.

Final Project

  1. The Bridge Probe (The Gravity Switch)This is the “A-B-C” chimeric probe that anchors the hydrophobic cholesterol to the biotinylated glass surface.Sequence: 5’-[Biotin-TEG] TTT TTT TTT TTT TTT rUrU rUrU rUrU rUrU rUrU rUrU TTT TTT TTT TTT TTT [Cholesterol-TEG]-3’Structure: Biotin—(dT)15—(rU)10—(dT)15—Cholesterol.Notes: Ensure you specify TEG (Triethylene Glycol) spacers for both the Biotin and Cholesterol modifications. This prevents steric hindrance, allowing the Cas13a to access the central RNA (rU10) cleavage site easily.Purification: HPLC purification is required for this dual-modified chimeric oligo.2. crRNA (The SARS-CoV-2 N-Gene Guide)This guide RNA targets a highly conserved region of the SARS-CoV-2 Nucleocapsid (N) gene (specifically the N2 region).Sequence: 5’-GAA UUU ACC CUU CGG GGU AGU CUA AAU GGU GAU GCU GCU CUU GCU UUG AGA G-3’Breakdown: * Direct Repeat (DR): GAAUUUACCCUUCGGGGUAGUCUAAAUSpacer: GGUGAUGCUGCUCUUGCUUUGAGAGNotes: This must be ordered as a single-stranded RNA (ssRNA).3. Fluorescent Reporter (Optional Confirmation)If you are using fluorescence for secondary verification alongside the visual liquid motion, this is the standard reporter.Sequence: 5’-[6-FAM] rU rU rU rU rU [BHQ-1]-3’Notes: A simple poly-rU pentamer labeled with FAM and BHQ-1.4. Positive Control (Target Activator)To test your reaction mix without a clinical sample, order this synthetic RNA fragment that matches the N-gene target.Sequence: 5’-CUC UCA AAG CAA GAG CAG CAU CAC C-3’Quick Ordering Summary TableComponentSequence (5’ to 3’)TypeModificationBridge ProbeBiotin-TEG-T15-rU10-T15-Cholesterol-TEGDNA/RNABiotin (5’), Cholesterol (3’)crRNAGAAUUUACCCUUCGGGGUAGUCUAAAU-GGUGAUGCUGCUCUUGCUUUGAGAGRNANoneReporterFAM-rUrUrUrUrU-BHQ1RNA6-FAM (5’), BHQ-1 (3’)Target RNACUCUCAAAGCAAGAGCAGCAUCACCRNANonePro-Tips for Your Build:Purification Matters: Chimeric oligos (DNA mixed with RNA) like the Bridge Probe are notoriously tricky. Ask your supplier (like IDT or GenScript) for HPLC or PAGE purification to ensure you don’t get truncated products that might fail to anchor.Glass Preparation: Since you’re using glass tubes, remember that the surface silanization (typically with APTES or FAS-17) is the most sensitive step. If the “blank” group liquid is moving too fast, your FAS-17 concentration is likely a bit too high.

Ultra-Sensitive Single-Tube Biosensor (USTB): Triple-Readout Protocol

This comprehensive protocol integrates mechanical Gravity readout with biochemical fluorescence and visual color change for maximum reliability. This “Triple-Readout” system ensures high diagnostic specificity for SARS‑CoV‑2 (N‑gene) detection.


I. Procurement Guide: What to Order

From Twist Bioscience (Custom Oligos)

Twist is the preferred source for the high‑purity, modified RNA/DNA tethers required for the “Hi‑to‑Ho” switch. Order the following three sequences:

ItemSequence (5′ → 3′)Purpose
Bridge Probe (The Switch)5′-[Biotin]-(T)₄₀-(rU)₁₀-3′-[Cholesterol]Anchors to the tube and creates the hydrophilic surface that holds the liquid.
crRNA (The Guide)GAAUUAACCCUUCGGGGUAGUCUAAAUC-GGUGAUGCUGCUCUUG-CUUUGAGAG (specific to SARS‑CoV‑2 N‑gene)Guides Cas13a to the viral target.
Fluorescent Reporter (Visual 1)5′-[6-FAM]-rU-rU-rU-rU-rU-3′-[BHQ-1]Provides green fluorescence upon cleavage.

From Thermo Fisher / Fisher Scientific

ComponentCatalog / Search TermFunction
Coated TubesStreptavidin‑Coated 1.5 mL TubesBase surface for the “Hi‑to‑Ho” switch.
Lysis AgentTCEP‑HCl (100 mM)Odorless reducing agent for viral lysis.
RNase GuardSUPERase·In™ RNase InhibitorProtects RNA components from degradation.
pH IndicatorPhenol Red Indicator (0.04%)Visual signal 2: pink → yellow color shift.
EnzymeLwaCas13a (Leptotrichia wadei)Target‑activated CRISPR nuclease.

II. Step‑by‑Step Protocol

Part 1: Tube Functionalization (“Arming”)

Prepare these in advance; “Armed” tubes are stable for up to 30 days at 4 °C.

  1. Dilute Probe – Reconstitute your Bridge Probe to 100 nM in 1× PBS.
  2. Coat – Add 150 μL of probe solution to a Streptavidin‑Coated 1.5 mL tube.
  3. Incubate – Let sit for 30 minutes at room temperature (RT).
  4. Wash – Remove liquid and wash the tube 3 times with 200 μL of PBS‑T (1× PBS + 0.05% Tween‑20).
  5. Dry – Air‑dry and store in a sealed bag with a silica desiccant.

Part 2: HUDSON Sample Processing

This “instrument‑free” method releases RNA directly from saliva or nasal swabs.

  1. Mix – Combine 50 μL of sample with 50 μL of Lysis Buffer (100 mM TCEP‑HCl + 2 mM EDTA).
  2. Heat – Incubate at 95 °C for 5 minutes (heat block or boiling water works).
  3. Cool – Allow the lysate to reach RT before adding it to the CRISPR mix.

Part 3: Triple‑Readout CRISPR Reaction

Assemble the master mix on ice before adding the sample.

Master Mix Assembly (100 μL per test):

ComponentFinal Concentration
LwaCas13a500 nM
crRNA500 nM
FAM‑rU₅‑BHQ1 Reporter1 μM
Phenol Red0.04%
SUPERase·In1 U/μL
Buffer5 mM Tris‑HCl (pH 8.8) + 10 mM MgCl₂

Note: Low buffer capacity is critical for the color shift.

  1. Reaction – Add 11 μL of lysate to 100 μL of master mix inside your Armed Tube.
  2. Incubation – Incubate at 37 °C for 15–20 minutes.

III. Interpretation of Results

ReadoutPositive (+)Negative (−)
Gravity (Flip)Liquid falls to the capLiquid stays anchored at the bottom
FluorescenceBright green (under 470 nm light)No visible glow
Color ChangeYellow (pH drop)Pink/Red (no change)

Thermo Scientific Pierce TCEP‑HCl
A potent, odorless reducing agent. High‑purity TCEP ensures complete viral lysis and stable RNA for attomolar detection.

Thermo Scientific Pierce TCEP‑HCl, No‑Weigh Format – $186.00
Thermo Fisher Scientific

Fisher Scientific SUPERase·In RNase Inhibitor
Essential for maintaining CRISPR reaction activity even in “dirty” clinical samples. More stable across a wide temperature range than traditional inhibitors.

Fisher Scientific SUPERase·In RNase Inhibitor (20 U/μL) – $227.00
Invitrogen