iGEM 2025 — Team dnhs-sandiego-ca

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{% block title %}Lab Notebook{% endblock %}
{% block lead %}Comprehensive documentation of our 2025 experimental procedures, protocols, and findings for ASO and aptamer development.{% endblock %}
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#### ASO Experiments

cDNA synthesis, qPCR setup, and protein knockdown assays

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#### Aptamer Development

Cell treatment, staining protocols, and imaging procedures

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#### Data Analysis

Results interpretation and experimental optimization

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### ASO Protocols (July)

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### Aptamer Protocols (August-September)

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### Analysis & Results

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{# ===================== TAB A: ASO PROTOCOLS ===================== #}
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## July 14, 2025 - cDNA Synthesis

#### Protocol Overview

Used the ProtoScript® II First Strand cDNA Synthesis Kit for reverse transcription.

#### Materials and Reagents

All reagents were taken out from -20°C and kept on ice throughout the procedure.

#### Procedure

#### Initial Mix (for each sample)

* RNA
* Oligo(dT)₂₀ primer
* dNTP Mix (10 mM each)
* Nuclease-free water

Tubes were given a quick spin in the centrifuge to bring everything down. No heat block or ice incubation was used after mixing — tubes were kept chilled while moving on.

#### Reverse Transcription Mix

Added the following components directly into the same tubes:

* 10X Reaction Buffer
* 0.1 M DTT
* RNase Inhibitor (40 U/µL)
* ProtoScript® II Reverse Transcriptase (200 U/µL)
* Nuclease-free water to bring total volume

#### Thermocycler Program

Mixed the reaction gently by pipetting and did another quick spin in the centrifuge. Placed tubes in the thermocycler and ran:

* X°C for X minutes
* X°C for X minutes

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## July 16, 2025 - ASO Plate Setup

#### Objective

Set up plates with ASO for protein knockdown experiments.

#### Procedure

#### Dosage Calculations

We wanted a final dose of 5 micromolar of ASO. ASO is originally a 10x mix, and we calculated that we would need to add 2.5 microliter of ASO to get our final dose.

#### Master Mix Preparation

* Made a master mix of 100 microliters of OPTI-MEM and 1 microliter of Lipo 3000
* Added 7.5 microliters of ASO for every 300 microliters of Master Mix
* Let it incubate for 10 minutes
* Added 100 microliters of ASO master mix to each well
* Wait for 5 days, then image the results. We will check on the cells after 24 hours, because lipofection can be toxic to the cell.

#### Observations

#### Initial Cell Confluence

When we started, we observed that there was around 70% confluence of cells in the wells (the cells covered approximately 70% of the plate).

#### ASO Master Mix Quality

While making our ASO master mix, we noted that after our 10 minute incubation period:

* **Less cloudy (potential concern):** E7, D11, F10, and F2 ASOs were not that cloudy
* **Cloudy (optimal):** F8 and E9 were cloudy

This could affect the results of our experiment, as increased cloudiness correlates to more effective formation of complexes.

#### Upcoming Plans

We will finish setting up a qPCR plate and run the qPCR. Once that is complete, we will do some data analysis and get some imaging done.

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## July 17-18, 2025 - qPCR Setup and Execution

#### July 17: Preparation for qPCR PlateSample Assessment When we observed the samples, we recorded that samples 1, 3, 4 (maybe), 5, 9, 11, 22 (maybe) may be uneven in sample size but we are proceeding with the qPCR. Volume Calculations Completed all calculations for plating. Using the amount of cDNA (245 µM) calculated previously, we were able to determine how much µL of ddH₂O each of the replicates required for both the +dox and -dox samples. Reaction Composition We are going to pipette 10 µL in each reaction: * 4.5 µL is going to be ddH₂O + cDNA * 5.0 µL is Poner Syber MM * 0.5 µL is forward and reverse primers at 10 µM + 0.25 µL Forward + 0.25 µL Reverse cDNA Dilution Calculation Using M₁V₁ = M₂V₂ we were able to determine that 0.14694 µL is required to dilute the 245 ng of cDNA into 4.5 µL of 8.0 ng/µL cDNA. ![ASO Plate Setup](https://static.igem.wiki/teams/5697/wiki/notebook/notebookfig1.webp "ASO Plate Setup") Upcoming plans Now that we finished labeling and setting up our qPCR plate, we are going to pipette samples and run the experiment July 18: Running qPCR ExperimentSample Volume Verification First we needed to redo our calculations and also account for the discrepancies in the samples of cDNA that had less than ideal amounts. Using a pipette, we measured how many µL of cDNA were actually in the following samples: Sample 1: 11 µL![Sample 1 - 11µL](https://static.igem.wiki/teams/5697/wiki/notebook/11ul.webp) Sample 3: 11 µL![Sample 3 - 11µL](https://static.igem.wiki/teams/5697/wiki/notebook/11ul.webp) Sample 4: 12 µL![Sample 4 - 12µL](https://static.igem.wiki/teams/5697/wiki/notebook/12ul.webp) Sample 5: 15 µL![Sample 5 - 15µL](https://static.igem.wiki/teams/5697/wiki/notebook/15ul.webp) Sample 9: 13 µL![Sample 9 - 13µL](https://static.igem.wiki/teams/5697/wiki/notebook/13ul.webp) Sample 11: 8 µL![Sample 11 - 8µL](https://static.igem.wiki/teams/5697/wiki/notebook/8ul.webp) Sample 22: 10 µL![Sample 22 - 10µL](https://static.igem.wiki/teams/5697/wiki/notebook/10ul.webp) We are assuming that all the other samples have around 20 µL of cDNA. Calculation Example (Sample 14) Based on our qPCR setup with METTL3, YTHDF2, and a control group, we calculated how much cDNA and DDH₂O each reaction contained. For example, the first group, 14, testing METTL3, cryptic exon, full exon, and GAPDH: * Has 3 technical replicates → total of 15 reactions * Added 3 extra reactions for pipetting error → 18 reactions total * 8 ng cDNA per reaction × 18 reactions = 144 ng total cDNA needed * 5.0 µL Poner Syber MM × 18 = 90 µL * 0.5 µL primer × 18 = 9 µL Calculating cDNA volume needed: 144 ng ÷ 245 ng/µL × 20 µL = 11.75 µL of cDNA stock Total reaction volume calculation: 10 µL × 18 reactions = 180 µL total 180 µL - 90 µL (MM) - 9 µL (primer) - 11.75 µL (cDNA) = **69.25 µL of DDH₂O** We repeated the above for all the wells in the chart and accounted for the lower amounts of cDNA in the listed numbers above. Next Steps Next visit, finish adding the ddH₂O based on the calculations on the spreadsheet.

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## July 21-24, 2025 - RNA Extraction and Processing

#### July 21: Extract RNA and Complete qPCR

What we did: Extract RNA and complete qPCR

#### July 22: Nanodrop Analysis

#### How to Use a Nanodrop

1. Add blanks on all 8 spots (the blank is the same solution the RNA was diluted in)
2. Clean all spots with ddH₂O on a kim wipe
3. Add 1 microliter of each sample to each of the 8 wells, close the nanodrop, and let the system run
4. Ratios 260/280 and 230/280 indicate the purity of the sample; anything above 1.90 indicates low contamination
5. Repeat for all samples

#### Pipetting Amounts for ProtoScript® II Kit

**Determine pipetting amounts:**

1. Record all the concentrations determined from the nanodrop
2. Determine total well amount that will result in >1 microliter pipetted for each sample (in this case, it was 265 microliters)

**Pipetting amounts per sample:**

* **RNA:** 265/concentration (should be >1 microliter, varies per sample)
* **ddH₂O:** 6 - RNA volume
* **Master mix:** We accounted for 2 extra wells for pipetting error
  + 26×2 microliters of Oligo(dT)₂₀ primer
  + 26×2 µL dNTP Mix (10 mM each)
  + 26×10 microliters of reaction buffer

![ASO Plate Setup](https://static.igem.wiki/teams/5697/wiki/notebook/notebookfig2.webp "ASO Plate Setup")

#### Adding Primer to qPCR Plate

* There are 13 reactions being tested for each protein in rows 1-5, so we multiplied 14 (to account for pipetting error) by 5.5 µL of —- to calculate a total of 77 µL for each: METTL3, TDP43, full exon, cryptic exon, and GAPDH
* We repeated this process for rows 6-10, only replacing METTL3 for YTHDF2, and pipetted another 5.5 µL of — in each corresponding well
* For rows 11-22, the control group, we are testing 23 reactions for each protein (METTL3, YTHDF2, TDP43, full exon, cryptic exon, and GAPDH), so we multiplied 24 reactions (account for pipetting error) by 5.5 µL of — to calculate a total of 132 µL for each proteins — of which we added 5.5 into each corresponding well
* Using a multichannel pipette, we added 5.5 of the respected protein’s—- to each corresponding well

We then ran the qPCR and will analyze the results

#### July 23: Prepare for qPCR Plate

#### Updated Calculations

Completed all calculations for plating. Using the amount of cDNA (265 µM) calculated previously, we determined dilution requirements.

**Reaction composition (10 µL total):**

* 4.5 µL ddH₂O + cDNA
* 5.0 µL Poner Syber MM
* 0.5 µL primers (0.25 µL Forward + 0.25 µL Reverse) at 10 µM

**Updated cDNA dilution:**

Using M₁V₁ = M₂V₂: 0.135849 µL is required to dilute the 265 ng of cDNA into 4.5 µL of 8.0 ng/µL cDNA.

![ASO Plate Setup](https://static.igem.wiki/teams/5697/wiki/notebook/notebookfig3.webp "ASO Plate Setup")

#### Calculation Example (Sample 1)

Sample 1, testing METTL3, cryptic exon, full exon, and GAPDH:

* 3 technical replicates = 15 reactions
* Added 3 extra for error = 18 reactions
* 8 ng cDNA × 18 = 144 ng total
* 144 ng ÷ 265 ng/µL × 20 µL = 10.87 µL cDNA needed

**Total volume calculation:**

180 µL (10 × 18) - 90 µL (MM) - 9 µL (primer) - 10.87 µL (cDNA) = **70.13 µL DDH₂O**

#### July 24: Thermocycling and Plating

#### Sample Preparation

Samples 12 and 13 did not have enough master mix so we had to re-mix both samples.

**Thermocycle program:**

* 25°C for 5 minutes
* 42°C for 1 hour
* 12°C on hold

#### Detailed Calculation Example (SND-1)

Before beginning plating for the qPCR, we calculated cDNA and ddH₂O amounts for each well.

**For SND-1 triplicates (6 reactions + 1 extra = 7 reactions):**

1. Concentration calculation: 7 reactions × 8 ng/µL = 56 ng/µL total
2. Stock volume needed: 56 ng/µL ÷ 265 µL total cDNA = 0.21132075471
3. From 20 µL stock: 0.21132075471 × 20 µL = **4.23 µL cDNA**

**ddH₂O calculation for 7 reactions:**

* Total volume: 10 µL × 7 = 70 µL
* Components:
  + cDNA: 4.23 µL
  + Poner Syber MM: 5.0 µL × 7 = 35 µL
  + Primers: 0.5 µL × 7 = 3.5 µL
* ddH₂O: 70 - 35 - 3.5 - 4.23 = **27.27 µL**

After completing calculations for all reactions 1-24, we mixed the calculated cDNA with ddH₂O to create diluted cDNA mixes, then pipetted 4.5 µL of diluted mix into each corresponding well.

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## July 29-30, 2025 - qPCR Completion and Analysis

#### July 29: Master Mix Preparation

#### Cyber and Primer Calculations

We finished adding 4.5 µL of diluted cDNA to the remaining wells and moved on to adding the cyber and primer master mix.

**Primer counts and calculations:**

* **SND:** 57 wells × 1.1 (10% error) = 63 wells
  + Cyber: 5 µL × 63 = 315 µL
  + Primer: 0.5 µL × 63 = 31.5 µL
* **FAM:** Same as SND (315 µL cyber, 31.5 µL primer)
* **DAZ:** Same as SND (315 µL cyber, 31.5 µL primer)
* **GAPDH:** 91 wells × 1.1 = 100 wells
  + Cyber: 5 µL × 100 = 500 µL
  + Primer: 0.5 µL × 100 = 50 µL

#### Primer Efficiency Curve Setup

We decided to simultaneously run our experiment for establishing a primer efficiency curve to see how well our primers were absorbed to amplify the RNA sequence.

**Serial dilutions performed:**

| Dilution | Concentration (ng) |
| --- | --- |
| 1 | 8 |
| 1:2 | 4 |
| 1:4 | 2 |
| 1:8 | 1 |
| 1:16 | 0.5 |
| 1:32 | 0.25 |

**Dilution preparation (using samples 14 and 15):**

* Mixed samples 14 and 15: total 16 ng
* 4.5 µL per well × 3 wells = 13.5 µL per primer
* 4 primer sets × 13.5 µL = 54 µL (account for 60 µL)
* Serial dilutions require 60 µL × 2 = 120 µL total

**Scaling calculations:**

* Scaling factor: 120 ÷ 31.5 = 3.80
* DNA: 4.23 µL × 3.87 = 16.11 µL
* ddH₂O: 27.27 µL × 3.87 = 103.89 µL

#### July 30: qPCR Run and Results

#### Execution

We ran the qPCR plate, but the experiment failed.

#### Issues Encountered

* Got many N/A values for primer efficiency curve readings
* Standard deviations were very high (later redone)
* Possible ddH₂O contamination identified

#### Materials Note

Used Bio-Rad Microseal B Adhesive Sealer

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{# ===================== TAB B: APTAMER PROTOCOLS ===================== #}
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## August 7, 2025 - Aptamer Project Initiation

#### Overview

Started aptamer project with cell treatment and fixation protocol.

#### Initial Treatment

Rachel added sodium arsenic to the top right 4 cells while we were gone.

#### Cell Plate Layout

|  |  |  |  |
| --- | --- | --- | --- |
| 1 | 3 | 2 (arsenic) | 2 (arsenic) |
|  | | 3 (arsenic) | (arsenic) |

*Note: Rachel added sodium arsenic to the top right 4 cells while we were gone.*

#### Fixation Protocol

#### PFA Treatment

* Used M₁V₁=M₂V₂ to calculate PFA needed
* Made solution: 10mL of 20% PFA + 40mL ddH₂O
* Fixed for 15 minutes on rocker

#### Permeabilization Step

* **Solution:** PBST (PBS + 0.3% Triton-X)
* **Duration:** 15 min on rocker at RT
* **Purpose:** Physiological pH and osmolarity (Open up cell membrane so aptamer can bind)

#### Washing

* **Solution:** PBS
* **Frequency:** 3 × 5 min on rocker
* **Purpose:** Removes residual Triton X-100 and cellular debris

#### Blocking Buffer

* **Composition:** PBS, 5% donkey serum, 1 microliter of hsDNA
* **Duration:** Rocked for ~45 minutes

#### Post-Blocking Wash

* **Solution:** PBS
* **Frequency:** 3 × 5 min on rocker
* **Purpose:** Removes excess blocking buffer components

#### Primary Antibody Step

* **Solution:** Blocking buffer + 0.67µM aptamer
* **Duration:** Overnight at 4°C on rocker
* **Purpose:** Aptamer binds specifically to its molecular target

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## August 8, 2025 - Day 2 Protocol (4 hours)

#### Washing Steps

**PBS wash:** 3 × 5min on rocker

#### Pre-blocking

* **Solution:** BSA + PBST (5mL of 1% BSA + 0.3% TritonX)
* **Duration:** 30 min on rocker at RT

#### Blocking with NeutrAvidin

#### Dilution Calculation

Target: 10mg/mL to 10 µg/mL

* Add 1 µL of 10mg/mL stock
* Add 999 µL of preblocking solution (1% BSA + 0.3% TritonX)
* Final: 1 mL of 10 µg/mL NeutrAvidin

#### Incubation

* **Solution:** NeutrAvidin + BSA + PBST
* **Duration:** 15 min on rocker at RT

#### Post-Blocking Wash

**PBS wash:** 3 × 5min on rocker

#### D-biotin Saturation

#### Purpose

To saturate free streptavidin binding sites

#### Preparation

* 1 µL D-biotin
* 999 µL PBST
* Final volume: 1 mL

#### Incubation

* **Solution:** D-biotin + PBST
* **Duration:** 15 min on rocker at RT

#### Final Wash

**PBS wash:** 3 × 5min on rocker

#### Staining

* **Solution:** NeutrAvidin–DyLight 550 conjugate + 1% BSA pre-blocking solution
* **Duration:** 60 min on rocker at RT

#### Post-Staining Wash

**PBS wash:** 3 × 5min on rocker

#### DAPI Counterstain

* **Solution:** DAPI 1:1000 in PBS
* **Duration:** 5 min on rocker at RT

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## August 11, 2025 - Imaging (SY5Y cells)

#### Final Steps

#### Staining

* **Solution:** NeutrAvidin–DyLight 550 conjugate + 1% BSA pre-blocking solution
* **Duration:** 60 min on rocker at RT

#### Washing

**PBS wash:** 3 × 5 min on rocker

#### DAPI Counterstain

* **Solution:** DAPI 1:1000 in PBS
* **Duration:** 5 min on rocker at RT

#### Imaging

Image cells for analysis

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## September 5, 2025 - Revised Aptamer Protocol

#### Protocol Steps

#### Permeabilization

* **Solution:** PBST (PBS + 0.3% Triton-X)
* **Duration:** 15 min on rocker at RT
* **Purpose:** Physiological pH and osmolarity (Open up cell membrane so aptamer can bind)

#### Washing

* **Solution:** PBS
* **Frequency:** 3 × 5 min on rocker
* **Purpose:** Removes residual Triton X-100 and cellular debris

#### Blocking Buffer

* **Composition:** PBS, 5% donkey serum, 1 microliter of hsDNA (4 mL total)
* **Duration:** Rocked for ~45 minutes

#### Post-Blocking Wash

* **Solution:** PBS
* **Frequency:** 3 × 5 min on rocker
* **Purpose:** Removes excess blocking buffer components

#### Primary Antibody Step

* **Solution:** Blocking buffer + 1.007µM aptamer
* **Duration:** Overnight at 4°C on rocker
* **Purpose:** Aptamer binds specifically to its molecular target
* **Note:** TDP-43 from rabbit background

#### Changes from Previous Experiment

* Only adding aptamer in first and third well
* Blocking buffer with 0.1% triton X

#### Experimental Layout

| Condition | Volume |
| --- | --- |
| Aptamer Only | 1 mL aptamer |
| Antibody Only | - |
| Both | 1 mL aptamer |

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{# ===================== TAB C: ANALYSIS & RESULTS ===================== #}
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## Experimental Analysis and Optimization

#### ASO qPCR Analysis

#### Sample Quality Assessment

Throughout our experiments, we monitored sample quality and volumes to ensure accurate results. Key observations included:

| Parameter | Observation | Impact |
| --- | --- | --- |
| Cell Confluence | ~70% at start | Optimal for transfection |
| ASO Cloudiness | Variable (E7, D11, F10, F2 less cloudy) | May affect complex formation efficiency |
| cDNA Volumes | 8-20 µL range | Required individual calculations per sample |
| Nanodrop Ratios | 260/280 and 230/280 | >1.90 indicates low contamination |

#### Primer Efficiency Optimization

#### MCTS Iteration Analysis

We tested multiple iterations (n=10) to balance diversity and convergence. Key findings:

* Initial iterations (1-5) showed rapid score improvement
* Iterations 5-10 provided optimal balance
* Beyond 10 iterations: diminishing returns due to sequence convergence

#### Random Seed Selection

Tested seeds 1001-1005. Seed 1004 consistently produced higher-scoring aptamers and was selected for production runs.

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## Data Integrity and Troubleshooting

#### Common Issues Encountered

#### qPCR Run Failure (July 30)

| Issue | Symptoms | Likely Cause | Resolution |
| --- | --- | --- | --- |
| N/A Values | Multiple wells showing no signal | Primer efficiency issues or contamination | Rerun with fresh reagents |
| High Standard Deviation | Poor technical replicate consistency | Pipetting errors or sample degradation | Increased pipetting care; fresh samples |
| ddH₂O Contamination | Unexpected amplification in negative controls | Contaminated water stock | New ddH₂O aliquot |

#### Sample Volume Discrepancies

#### Measured vs Expected Volumes

Direct pipette measurements revealed several samples with less than expected volume:

##### Low Volume Samples

* Sample 11: 8 µL (expected ~20 µL)
* Sample 22: 10 µL (expected ~20 µL)
* Sample 1: 11 µL (expected ~20 µL)
* Sample 3: 11 µL (expected ~20 µL)

##### Resolution Strategy

* Measured actual volumes directly
* Adjusted calculations per sample
* Maintained consistent ng/µL concentration
* Recalculated ddH₂O requirements

#### Protocol Refinements

#### ASO Transfection Optimization

* **Cell Confluence:** Maintained 70% for optimal uptake
* **Lipofection:** Monitored at 24h for toxicity
* **Incubation Time:** 10 min for complex formation (increased cloudiness correlates with better complexes)
* **Imaging Timeline:** 5 days post-transfection

#### Aptamer Protocol Modifications (Sept 5)

* Increased aptamer concentration: 0.67µM → 1.007µM
* Modified blocking buffer: Added 0.1% Triton X
* Selective well treatment: Only first and third wells
* Added TDP-43 antibody control (rabbit background)

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## Calculation Standards and Best Practices

#### Master Mix Calculations

#### General Formula

For any qPCR setup with technical replicates:

##### Step-by-Step Process

1. **Determine reaction count:** Technical replicates × conditions
2. **Add pipetting error margin:** Multiply by 1.1-1.2 (10-20% extra)
3. **Calculate total cDNA needed:** ng per reaction × total reactions
4. **Determine cDNA volume from stock:** (Total ng needed ÷ Stock concentration) × Stock volume
5. **Calculate other components:** Multiply per-reaction volumes by total reactions
6. **Calculate ddH₂O:** Total volume - (all other components)

#### Example Calculation Template

```
Given:
- Target gene: [Gene name]
- Technical replicates: 3
- Primers tested: [METTL3, TDP43, full exon, cryptic exon, GAPDH] = 5
- Reactions per condition: 3 × 5 = 15
- With error (×1.2): 18 reactions

Per reaction (10 µL total):
- cDNA: 8 ng (in 4.5 µL with ddH₂O)
- Syber MM: 5.0 µL
- Primers: 0.5 µL (0.25 µL forward + 0.25 µL reverse)

Calculations:
1. Total cDNA needed: 8 ng × 18 = 144 ng
2. cDNA volume from stock: (144 ng ÷ [concentration]) × 20 µL = X µL
3. Total Syber MM: 5.0 µL × 18 = 90 µL
4. Total primer: 0.5 µL × 18 = 9 µL
5. Total volume needed: 10 µL × 18 = 180 µL
6. ddH₂O needed: 180 - 90 - 9 - X = Y µL
```

#### Dilution Calculations

#### Using M₁V₁ = M₂V₂

##### Standard Dilution

To dilute 245 ng/µL cDNA to 8 ng/µL in 4.5 µL:

* M₁ = 245 ng/µL
* V₁ = ?
* M₂ = 8 ng/µL
* V₂ = 4.5 µL

**V₁ = (M₂ × V₂) ÷ M₁ = (8 × 4.5) ÷ 245 = 0.147 µL**

##### Serial Dilution

For primer efficiency curves:

| Step | Dilution | Final [ng] |
| --- | --- | --- |
| 1 | Undiluted | 8 |
| 2 | 1:2 | 4 |
| 3 | 1:4 | 2 |
| 4 | 1:8 | 1 |
| 5 | 1:16 | 0.5 |
| 6 | 1:32 | 0.25 |

#### Quality Control Checkpoints

#### Pre-Experiment Checklist

* ✓ All reagents thawed and on ice
* ✓ Cell confluence checked and documented
* ✓ Sample volumes verified by direct pipetting
* ✓ Calculations double-checked
* ✓ Pipetting error margin included (10-20%)
* ✓ Negative controls prepared

#### During Experiment

* ✓ Record actual volumes used
* ✓ Note cloudiness/appearance of mixes
* ✓ Document any deviations from protocol
* ✓ Label all tubes clearly
* ✓ Quick spin after mixing

#### Post-Experiment

* ✓ Check for evaporation in wells
* ✓ Seal plates properly
* ✓ Record thermocycler settings
* ✓ Document any unexpected observations
* ✓ Store samples appropriately

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## Results Summary and Next Steps

#### ASO Project Status

#### Completed Milestones

| Date | Milestone | Status |
| --- | --- | --- |
| July 14 | cDNA Synthesis (ProtoScript® II) | Complete |
| July 16 | ASO Plate Setup (5µM final dose) | Complete |
| July 17-18 | qPCR Plate Setup | Complete |
| July 21 | RNA Extraction | Complete |
| July 22 | Nanodrop Analysis | Complete |
| July 29-30 | qPCR Execution | Needs Repeat |

#### Aptamer Project Status

#### Completed Milestones

| Date | Milestone | Status |
| --- | --- | --- |
| August 7 | Cell Treatment & Fixation | Complete |
| August 8 | Full Staining Protocol (Day 2) | Complete |
| August 11 | Imaging (SY5Y cells) | Complete |
| September 5 | Revised Protocol with Controls | In Progress |

#### Key Learnings

#### Technical Insights

**ASO Optimization**

* Cloudiness indicates proper complex formation
* Cell confluence critical (70% optimal)
* Sample volume verification essential
* Pipetting error margins prevent failures

**Aptamer Optimization**

* Increased aptamer concentration improved binding
* Triton X in blocking buffer enhanced permeability
* Control wells essential for validation
* Overnight incubation at 4°C optimal

#### Future Directions

#### Immediate Next Steps

1. **ASO Project:**
   * Repeat qPCR with fresh ddH₂O
   * Optimize primer efficiency curves
   * Complete data analysis from successful runs
   * Image transfected cells at 5-day timepoint
2. **Aptamer Project:**
   * Complete September 5 protocol
   * Image all experimental conditions
   * Compare aptamer-only vs antibody controls
   * Quantify binding efficiency
3. **Data Analysis:**
   * Process qPCR CT values
   * Calculate relative expression levels
   * Statistical analysis of knockdown efficiency
   * Correlate with computational model predictions

#### Long-term Goals

* Validate top ASO candidates from computational model
* Test aptamer binding specificity with multiple controls
* Optimize dosing for both ASOs and aptamers
* Combine approaches for synergistic effects
* Prepare protocols for in vivo validation

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## Experimental Standards and Documentation

### Lab Notebook Best Practices

This notebook follows standard scientific documentation practices to ensure reproducibility and traceability:

##### Date & Time

All entries include date of experiment with clear timeline of procedures.

##### Detailed Methods

Complete reagent lists, concentrations, volumes, and incubation times documented.

##### Observations

Real-time notes on unexpected findings, deviations, and quality assessments.

### Safety and Compliance

##### Important Safety Notes

* All work with cells performed in biosafety cabinet
* PFA handled with appropriate PPE (toxic fixative)
* Arsenic treatments performed by trained personnel
* Waste disposal followed institutional guidelines
* All reagents stored at recommended temperatures

### Acknowledgments

Special thanks to Rachel for sodium arsenic treatments and all team members who contributed to protocol optimization and troubleshooting throughout this project.

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{% extends "page\_layout.html" %}
{% block title %}Engineering Success{% endblock %}
{% block lead %}Demonstrating engineering success through systematic iteration of the Design-Build-Test-Learn cycle, developing RNA-based therapeutics targeting stress granule dynamics and TDP-43 aggregation in ALS.{% endblock %}
{% block takeaway1 %}

#### Dual-Strategy Approach

ASOs to knock down stress granule proteins (DAZAP1, FAM98A) and RNA aptamers to target TDP-43 aggregation

{% endblock %}
{% block takeaway2 %}

#### Validated ASO Knockdown

Successfully reduced DAZAP1 by 23% and FAM98A by 38-49% using optimized gapmer designs

{% endblock %}
{% block takeaway3 %}

#### Iterative Refinement

Two experimental cycles with improved imaging and quantification methods, identifying clear next steps

{% endblock %}
{% block takeaway1\_expanded %}

## Design: Problem Identification & Strategy

ALS is a neurodegenerative disease characterized by TDP-43 mislocalization and abnormal stress granule dynamics. Despite extensive research, there are currently no therapeutics that directly prevent TDP-43 aggregation. We identified two interconnected molecular problems and designed corresponding RNA-based solutions.

### Strategic Framework

#### Problem 1

Stress granule proteins (DAZAP1, FAM98A, SND1) drive abnormal aggregation when dysregulated

#### Solution 1: ASOs

Antisense oligonucleotides to knock down expression of key stress granule proteins

#### Problem 2

TDP-43 mislocalization and aggregation is a hallmark of ALS pathology

#### Solution 2: RNA Aptamers

RNA aptamers to bind TDP-43 C-terminal domain and regulate demixing behavior

### ASO Gapmer Design Optimization

Through iterative testing, we optimized a 5-10-5 gapmer design with chemical modifications to improve stability and binding affinity while minimizing off-target effects.

*Click on each segment below to learn more about its modifications and purpose.*

5' Flank (1-5)

N
N
N
N
N

2MOEr

DNA Gap (6-14)

N
N
N
N
N
N
N
N
N

iMe-dC

3' Flank (15-19)

N
N
N
N
N

2MOEr

#### 5' Flank (Positions 1-5)

**Modification:** 2'-O-methoxyethyl ribose (2MOEr)

**Purpose:** Improves nuclear resistance and binding affinity

#### DNA Gap (Positions 6-14)

**Modification:** 5-methylcytosine (iMe-dC) substitutions

**Purpose:** Central DNA region optimized for stability

#### 3' Flank (Positions 15-19)

**Modification:** 2'-O-methoxyethyl ribose (2MOEr)

**Purpose:** Improves nuclear resistance and binding affinity

*This systematic design approach balances chemical stability, binding strength, and biological relevance, producing ASOs suitable for in vitro testing.*

{% endblock %}
{% block takeaway2\_expanded %}

## Build: Computational Pipeline & Chemical Optimization

Our build phase involved both computational design and chemical optimization to create the most promising candidates for experimental testing.

### Parallel Development Tracks

Both Tracks
ASO Track Only
Aptamer Track Only

#### ASO Development

✓

##### Computational Screening

Scored candidates based on GC content, secondary structure, conservation, and specificity

✓

##### Chemical Modification

Optimized 5-10-5 gapmer with 2MOEr flanks and iMe-dC DNA gap

✓

##### Primer Design & Validation

Created primers for DAZAP1, FAM98A, and GAPDH with efficiency testing

#### Aptamer Development

✓

##### AptaTrans Generation

Deep learning framework predicted sequences targeting TDP-43 CTD

✓

##### HADDOCK Docking

In silico simulations assessed binding stability and surface area

✓

##### Monte Carlo Optimization

Tested multiple iterations and random seeds to identify top candidates

Both tracks employed iterative computational refinement to maximize the likelihood of experimental success while minimizing time and resource investment in wet-lab testing.

{% endblock %}
{% block takeaway3\_expanded %}

## Test: Experimental Validation

We conducted two main experimental cycles to test our designs: ASO transfection with RT-qPCR analysis, and aptamer binding visualization with immunocytochemistry.

### Preliminary qPCR Workflow Practice

Before conducting our main ASO transfections, we performed a preliminary qPCR experiment to familiarize ourselves with the workflow. We prepared a qPCR plate containing technical triplicates for GAPDH, TDP-43, METTL3, YTHDF2, CE, and Full constructs across multiple biological replicates. Different cDNA dilutions were tested to ensure amplification was within a detectable and consistent range.

#### Purpose

Practice plate setup, pipetting, and qPCR cycling workflow

#### Outcome

Gained confidence and troubleshooting experience before ASO knockdown experiments

#### Status

Not intended to generate final data - preparatory learning step

*This preliminary experiment was crucial for ensuring technical proficiency before moving to our critical ASO validation experiments.*

### Primer Efficiency Validation

Standard curves were generated to validate primer performance. Target efficiency range: 90-110%.

DAZAP1
FAM98A
GAPDH

#### DAZAP1 Primer Efficiency

78.4%

Log(Sample)
Average Cq Value

**Slope:** -3.98

**Efficiency:** 78.4%

**Status:** Below target - optimize for future experiments

#### FAM98A Primer Efficiency

94.4%

Log(Sample)
Average Cq Value

**Slope:** -3.46

**Efficiency:** 94.4%

**Status:** Optimal range ✓

#### GAPDH Primer Efficiency

73.7%

Log(Sample)
Average Cq Value

**Slope:** -4.17

**Efficiency:** 73.7%

**Status:** Below target - optimize for future experiments

### ASO Knockdown Results

RT-qPCR quantification revealed successful gene expression reduction for stress granule proteins.

#### DAZAP1

0%

Knockdown

**ASO-A & ASO-B**

Both achieved 23% reduction in expression

#### FAM98A

0%

Knockdown

**ASO-C & ASO-D**

Reduced expression by 38-49%

#### SND1

⚠

Troubleshooting

Primer Optimization

**Primer Efficiency: 377%**

Excluded from analysis; redesigning primers for future experiments

### Detailed ASO Knockdown Analysis

RT-qPCR data showing relative gene expression (normalized to GAPDH) comparing ASO-treated samples to controls.

DAZAP1 Data
FAM98A Data

#### DAZAP1 Knockdown Results

ASO-A Knockdown:
22.4%

ASO-B Knockdown:
22.0%

Method:
Pfaffl Method

*Relative expression calculated using primer efficiency-corrected Pfaffl method. Both ASOs achieved ~23% knockdown compared to lipofectamine-only control.*

#### FAM98A Knockdown Results

ASO-C Knockdown:
37.6%

ASO-D Knockdown:
48.8%

Method:
ΔΔCt Method

*Relative expression calculated using ΔΔCt method. ASO-D achieved 49% knockdown, demonstrating strong efficacy for FAM98A targeting.*

### RNA Aptamer Cellular Localization

We performed two imaging trials to visualize aptamer localization and assess potential interactions with TDP-43 and stress granules.

#### Trial 1: Initial Merged Channel Imaging

RNA aptamer signal was visualized alongside DAPI (nuclear stain) and G3BP1 (stress granule marker). The overlap of aptamer and DAPI confirms successful cellular uptake and nuclear localization. The aptamer does not consistently co-localize with G3BP1-positive structures in these images, **indicating the aptamer binds a structure whose molecular identity is currently unknown.**

Iteration 2

#### Trial 2: Refined Imaging with Z-Stack and Maximum Intensity Projection

To build on the first trial and gain a more detailed view of aptamer localization, we performed higher-resolution imaging using both single slices and a maximum intensity projection of a Z-stack. Sodium arsenite treatment was applied to ensure stress granule formation, and this 3D imaging approach allowed us to better assess potential colocalization between the aptamer, TDP-43, and G3BP1 across the entire cell volume, rather than relying solely on a single focal plane.

**Improvement:** Z-stack imaging provides superior spatial information for assessing colocalization across 3D cellular structures.

*Although direct binding to TDP-43 was not fully confirmed, these images provided preliminary evidence that the aptamer reaches relevant subcellular locations for potential functional activity.*

*These findings confirmed that ASOs can feasibly reduce stress granule-related transcripts in neuronal-like cells. Aptamer experiments demonstrated successful cellular uptake and nuclear localization, with iterative imaging improvements providing better spatial resolution for future binding validation studies.*

{% endblock %}
{% block takeaway4\_expanded %}

## Learn: Engineering Cycle Analysis

The Design-Build-Test-Learn cycle is not complete until insights from testing inform the next iteration. Our experiments revealed both successes and areas for optimization.

### Design-Build-Test-Learn Cycle

Click each phase to see what we accomplished and what we learned for the next iteration.

DBTL

DESIGN
BUILD
TEST
LEARN

Advance to Next Phase →

#### Design Phase

##### What We Designed:

* Computational pipeline for ASO sequence generation targeting DAZAP1, FAM98A, SND1
* 5-10-5 gapmer architecture with 2MOEr and iMe-dC modifications
* AptaTrans-generated RNA aptamers targeting TDP-43 C-terminal domain
* HADDOCK docking simulations with Monte Carlo optimization

##### Design Rationale:

Dual strategy addresses both upstream (stress granule proteins) and downstream (TDP-43 aggregation) pathological events in ALS.

#### Build Phase

##### What We Built:

* Computationally screened hundreds of ASO sequences, narrowed to top candidates
* Chemically optimized gapmers with iterative modification testing
* Validated primer sets for RT-qPCR quantification
* Generated and computationally ranked aptamer candidates

##### Build Achievements:

Created experimentally-ready ASOs and aptamers with predicted high efficacy and minimal off-target effects or immune activation.

#### Test Phase

##### What We Tested:

* **ASO Experiment:** Transfected SH-SY5Y cells, measured knockdown by RT-qPCR
* **Results:** DAZAP1 reduced 23%, FAM98A reduced 38-49%
* **Aptamer Experiment:** Immunocytochemistry with fluorescence microscopy
* **Results:** Nuclear localization confirmed, partial stress granule colocalization

##### Testing Challenges:

SND1 primer efficiency too high (377%); aptamer binding to TDP-43 not definitively confirmed.

#### Learn Phase

##### Key Learnings - ASOs:

* Current gapmer design is effective for knockdown in neuronal-like cells
* Primer efficiency varies; DAZAP1 and GAPDH need optimization
* SND1 requires complete primer redesign for future cycles

##### Key Learnings - Aptamers:

* Aptamers successfully enter cells and localize to nucleus
* Binding specificity needs validation with additional assays
* Z-stack imaging provides superior spatial information

##### Next Iteration:

**ASOs:** Test in stressed cells, optimize concentration, add more sequence variants. **Aptamers:** Refine sequences, develop binding assays, test functional effects on stress granule dynamics.

### Future Directions: Cycle 2 Planning

Based on our learnings, we have identified specific improvements for the next engineering cycle.

#### ASO Optimization

Iteration 2

1
Test multiple ASO sequence variants per gene (expand from 2 to 5-10 per target)

2
Optimize ASO concentration (dose-response curve: 10-100 nM)

3
Test knockdown in sodium arsenite-stressed cells to assess impact on stress granule formation

4
Redesign and validate SND1 primers for inclusion in analysis

#### Aptamer Refinement

Iteration 2

1
Generate additional aptamer candidates with higher predicted TDP-43 binding affinity

2
Optimize staining protocols (aptamer concentration, blocking conditions, wash stringency)

3
Develop biochemical binding assays (e.g., EMSA, pull-down) to confirm direct TDP-43 interaction

4
Test functional effects on TDP-43 aggregation and stress granule dynamics

**Engineering success is not defined by perfect results, but by systematic iteration and learning. Our dual-strategy approach has demonstrated feasibility at the proof-of-concept level, and the clear path forward ensures continued progress toward an RNA-based therapeutic for ALS.**

{% endblock %}
{% block page\_content %}

{% endblock %}

{% extends "page\_layout.html" %}
{% block title %}Experiments{% endblock %}
{% block lead %}Interactive guide outlining core experimental workflows — from RNA preparation to imaging analysis in ALS therapeutics research.{% endblock %}
{% block takeaway1 %}

#### RNA Preparation & Reverse Transcription

Isolation of RNA, assessment via Nanodrop, and conversion to cDNA for downstream qPCR analysis.

{% endblock %}
{% block takeaway2 %}

#### Transfection & qPCR Analysis

Delivery of antisense oligonucleotides into neuronal cells and quantification of target transcripts.

{% endblock %}
{% block takeaway3 %}

#### Aptamer Staining & Imaging

Visualization of RNA aptamer binding and cellular localization using fluorescence microscopy.

{% endblock %}
{% block takeaway1\_expanded %}

## RNA Preparation & Reverse Transcription

### Nanodrop Analysis of RNA

1. Blank with dilution buffer.
2. Load 1 µL sample per spot.
3. Record concentration and 260/280, 230/280 ratios (>1.9 acceptable).
4. Use concentrations to calculate RNA volume for downstream reactions.

### Reverse Transcription (ProtoScript® II)

#### Reagents

* Total RNA (X µg)
* Oligo(dT)₂₀ primer (X µL)
* dNTP Mix, 10 mM each (X µL)
* 10X Reaction Buffer (X µL)
* 0.1 M DTT (X µL)
* RNase Inhibitor (X µL)
* ProtoScript® II Reverse Transcriptase (X µL)
* Nuclease-free water to X µL

#### Procedure

1. Thaw reagents on ice and mix RNA, primer, dNTPs, and water.
2. Add buffer, DTT, RNase inhibitor, reverse transcriptase, water. Quick spin.
3. Thermocycle: 25°C 5 min → 42°C 1 hr → 12°C hold.

{% endblock %}
{% block takeaway2\_expanded %}

## Transfection & qPCR Analysis

### Lipofection with Antisense Oligonucleotides

#### Reagents

* ASO (10× stock)
* OPTI-MEM (100 µL)
* Lipofectamine 3000 (1 µL)

#### Procedure

1. Prepare Master Mix: 100 µL OPTI-MEM + 1 µL Lipofectamine 3000.
2. Add 7.5 µL ASO per 300 µL Master Mix. Incubate 10 min.
3. Add 100 µL to each well (final 5 µM).
4. Incubate; monitor at 24 hr and 5 days.

### qPCR Reaction Setup

#### Reagents per 10 µL

* 4.5 µL ddH₂O + diluted cDNA (8 ng/µL)
* 5.0 µL SYBR Master Mix
* 0.25 µL Forward primer (10 µM)
* 0.25 µL Reverse primer (10 µM)

#### Procedure

1. Dilute cDNA (M1V1 = M2V2).
2. Mix reagents and plate 10 µL per well.
3. Run thermocycler according to assay.

### Primer Efficiency Curve

* Dilutions: 8, 4, 2, 1, 0.5, 0.25 ng (1:2 serial)

#### Procedure

1. Prepare serial cDNA dilutions.
2. Plate in triplicates and run qPCR to determine efficiency.

{% endblock %}
{% block takeaway3\_expanded %}

## Aptamer Staining & Imaging

### Cell Fixation and Aptamer Staining

#### Fixation

* Prepare 50 mL: 10 mL 20% PFA + 40 mL ddH₂O.
* Fix cells 15 min on rocker.

#### Permeabilization

* PBST 15 min, wash PBS 3×5 min.

#### Blocking

* PBS + 5% donkey serum + 1 µL hsDNA, 45 min on rocker.

#### Primary Aptamer Binding

* Blocking buffer + 0.67 µM aptamer overnight at 4°C.

### Aptamer Assay – Day 2

1. Pre-block 5 mL 1% BSA + 3% Triton-X, 30 min RT.
2. Blocking: NeutrAvidin 10 µg/mL, 15 min.
3. Wash PBS 3×5 min.
4. Saturation: D-biotin 1 µL stock + 999 µL PBST, 15 min.
5. Wash PBS 3×5 min.
6. Stain: NeutrAvidin–DyLight 550 + 1% BSA, 60 min RT.
7. Wash PBS 3×5 min.
8. Counterstain: DAPI 1:1000, 5 min.

### Imaging (SH-SY5Y Cells)

1. Stain cells as above.
2. Wash PBS 3×5 min.
3. Counterstain with DAPI 1:1000, 5 min.
4. Image under fluorescent microscope.

{% endblock %}
{% block page\_content %}
{% endblock %}

{% extends "page\_layout.html" %}
{% block title %}Results{% endblock %}
{% block lead %}
In order to create a successful pipeline for 1) stopping the formation of stress granules through protein knockdown and 2) stop the aggregation of TDP-43 in the stress granules, a series of experiments were conducted to test sequences created in silico. First, each of the ASO sequences were transfected in cells and RNA was extracted from the transfected cells. The RNA was converted to cDNA and an RT-qPCR was prepared for analysis. For our second experiment, SH-SY5Y cells were transfected with the RNA aptamer, and immunofluorescence staining was performed to test binding sites and stress granule knockdown.
{% endblock %}
{% block takeaway1 %}

#### Experiment 1: ASO Protein Knockdown

Analysis of RT-qPCR Cq values, primer efficiency, and ASO-mediated gene expression fold change.

{% endblock %}
{% block takeaway2 %}

#### Experiment 2: Aptamer Mislocalization

Immunofluorescence staining to test the binding sites of the RNA aptamer and its effect on stress granules.

{% endblock %}
{% block takeaway3 %}

#### Key Knockdown Results

The ASO of interest showed an approximate 21 percent knockdown of DAZAP1 expression.

{% endblock %}
{% block takeaway1\_expanded %}

## Experiment 1: ASO Protein Knockdown

### Plate Setup and Translation:

Table 1. Sample Translation.

We set up our sample translation key to map each ASO sequence and its technical replicate with a sample number for easier RT-qPCR well plate translation.

| Sample | Sequence ID | Sample | Sequence ID |
| --- | --- | --- | --- |
| 1 | F8-1 | 13 | M-1 |
| 2 | F8-2 | 14 | M-2 |
| 3 | F8-3 | 15 | M-3 |
| 4 | F10-1 | 16 | L-1 |
| 5 | F10-2 | 17 | L-2 |
| 6 | F10-3 | 18 | L-3 |
| 7 | F2-1 | 19 | E7-1 |
| 8 | F2-2 | 20 | E7-2 |
| 9 | F2-3 | 21 | E7-3 |
| 10 | E9-1 | 22 | D11-1 |
| 11 | E9-2 | 23 | D11-2 |
| 12 | E9-3 | 24 | D11-3 |

### RT-qPCR Plate Set up

![Visual representation of the 384-well RT-qPCR plate setup showing sample locations and targets.](https://static.igem.wiki/teams/5697/wiki/results/igem1.webp)
Table 2. RT-qPCR Plate Set up. We set up our RT-qPCR plate depending on our multi-channel pipette for easy pipetting

We set up our RT-qPCR plate to include each corresponding stress granule protein with its corresponding ASO hypothesized to knock down. We had GAPDH as a control for all proteins, and also tested all proteins against the media and lipo control for a baseline comparison. We set up a primer efficiency curve against different concentrations of protein.

### Raw CQ Data

After RT-qPCR, we obtained Quantification Cycle (Cq) values for each of our wells. Cq represents the cycle number at which the PCR reaction outputs a fluorescent signal, indicating the presence of the target effect.

Table 3. Snippet of raw CQ values. Each well in the 384 well plate had a corresponding CQ value used for further analysis.

| Well | Fluor | Target | $C\_t$ |
| --- | --- | --- | --- |
| A1 | SYBR | Unknown | 17.4888418 |
| A2 | SYBR | Unknown | 17.97278926 |
| A3 | SYBR | Unknown | 17.35276733 |
| A4 | SYBR | Unknown | 17.27687518 |
| A5 | SYBR | Unknown | 16.47634628 |
| A6 | SYBR | Unknown | 16.72385299 |
| A7 | SYBR | Unknown | 37.57573508 |
| A8 | SYBR | Unknown | 37.96026952 |
| B1 | SYBR | Unknown | 24.66717837 |
| B2 | SYBR | Unknown | 24.0139328 |
| B3 | SYBR | Unknown | 24.25665287 |
| B4 | SYBR | Unknown | 24.47493426 |
| B5 | SYBR | Unknown | 23.97851527 |
| B6 | SYBR | Unknown | 24.43964582 |
| B7 | SYBR | Unknown | 38.33198103 |
| B10 | SYBR | Unknown | 21.54228912 |
| B11 | SYBR | Unknown | 21.15599149 |
| B12 | SYBR | Unknown | 20.84109656 |
| B13 | SYBR | Unknown | 21.03476051 |
| C1 | SYBR | Unknown | 18.56623842 |
| C2 | SYBR | Unknown | 18.89703446 |
| C3 | SYBR | Unknown | 17.91677228 |
| C4 | SYBR | Unknown | 18.68972263 |
| C5 | SYBR | Unknown | 20.61733761 |
| C6 | SYBR | Unknown | 18.67075024 |

### Primer Efficiency Curve

We ran a primary efficiency curve to understand how efficiently a pair of primers amplifies a target sequence. To conduct this, we ran serial dilutions and each dilution is subject to RT-qPCR using the corresponding primers of interest. The resulting Cq values were plotted against the logarithm of the template concentration and the slope is used to calculate amplification efficiency. This is a critical step because suboptimal primers may lead to skewed quantification, so it is vital to take into account primer efficiency when calculating resulting values.

**Table 4.** RT-qPCR Ct values for DAZAP, GAPDH, FAM-labeled target across serial dilution series (1, 1:2, 1:4, 1:8, 1:16, 1:32) and no template control \*NTC)

![](https://static.igem.wiki/teams/5697/wiki/results/igem4.webp)

Before conducting any calculations, it is vital to analyze trends across targets. The overall trend is that the Cq values increase with dilution, which is as expected because lower template concentrations take more cycles to reach the fluorescence threshold. Outliers were crossed out to ensure that the standard deviations of technical replicates had low standard deviations. It was necessary to perform this step because technical replicates are expected to have similar values. If two technical replicates have a similar value and the third deviates from this value, we can conclude that the third is an outlier and remove the value to ensure consistent results. N/A values for NTC were expected as no primer was added to ensure low contamination. The standard deviation for most replicates was low, suggesting good reproducibility once outliers were omitted.
Unexpectedly, the NTC values for GAPDH do have values, suggesting low=level contamination with DNA or cDNA into these wells. However our samples amplified much earlier than the NTC values (~15 - 20), so the actual sample signal is strongly above background. GAPDH is highly expressed, which makes primer-dimers or minor contamination more visible in NTC wells, but our experimental samples are clearly amplified as expected.

Table 5. Log(sample quantity) values for each dilution

| Dilution | Log (Sample quantity) |
| --- | --- |
| 1 | 0 |
| 1:2 | -0.3010299957 |
| 1:4 | -0.6020599913 |
| 1:8 | -0.903089987 |
| 1:16 | -1.204119983 |
| 1:32 | -1.505149978 |

In preparation for our primer efficiency curve, we calculate log(sample quantity) for each dilution.
In qPCR, our goal is to measure how the amount of DNA increases during each PCR cycle.
The ideal is that the DNA doubles every cycle, which is exponential growth as shown in the following equation:
$N = N\_0(1+E)^C$
where N is the amount of product at cycle C, N0 is the initial amount of template, and E is the primer efficiency.
Logarithm is used in this case because exponential relationships are tricky to analyze, so to make it linear, we take the logarithm of the entire equation.
The equation then becomes $\log(N) = \log(N\_0) + C\log(1+E)$.
The slope of this line is proportional to primer efficiency.

![Figure 1 Primer efficiency curve: Average Cq Values vs. Log (Sample) for DAZAP1. Line equation: -3.98*x + 19.3 R^2 = 0.975](https://static.igem.wiki/teams/5697/wiki/results/average-vs-log-sample-dazap1.webp)

![Figure 2 Primer efficiency curve: Average Cq Values vs. Log (Sample) for GAPDH. Line equation: -4.17*x + 15.5 R^2 = 0.992](https://static.igem.wiki/teams/5697/wiki/results/average-cq-value-vs-log-sample-gapdh.webp)

**Figure 2** Primer efficiency curve. Average Ct vs Log(sample) for GAPDH.

![Figure 3 Primer efficiency curve: Average Cq Values vs. Log (Sample) for FAM. Line equation: -3.46*x + 22.5 R^2 = 0.94](https://static.igem.wiki/teams/5697/wiki/results/average-vs-log-sample-dazap1.webp)

**Figure 3** Primer efficiency curve. Average Ct vs Log(sample) for FAM.

For all three primers, the plot of the Ct values against the logarithm of the initial template concentration produced a linear relationship as expected for efficient primers, evident in the $R^2$ values shown in the graphs.

Table 6. Efficiency calculations based on slope for DAZAP1, GAPDH, and FAM

| Primer | Slope | Efficiency |
| --- | --- | --- |
| DAZ | -3.977576677 | 78.40595984 |
| GAP | -4.169012789 | 73.72604767 |
| FAM | -3.463829212 | 94.40070548 |

Based on the slope, the efficiency was calculated with the following equation:

\[
\text{Efficiency (\%)} = \left(10^{-\frac{1}{\text{slope}}} - 1\right) \times 100
\]

In qPCR, the efficiency of the PCR reaction says how well the primers amplify the target DNA in each PCR cycle. A slope of -3.32 gives 100% efficiency. A very steep slope means the efficiency is less than 100%, and a more shallow slope says that the efficiency is greater than 100%. The efficiency equation above converts the slope into a percentage. While our efficiencies were low for \*\*DAZAP1\*\* and \*\*GAPDH\*\*, we took this limitation into account for our future calculations to measure expression fold change.

### DAZAP1 - Pfaffl Method

![Table 7 Pfaffl inputs](https://static.igem.wiki/teams/5697/wiki/results/igem6.webp)

**Table 7.** Pfaffl Method inputs (raw Ct for DAZAP1 & GAPDH).

![Table 8 Averages](https://static.igem.wiki/teams/5697/wiki/results/igem7.webp)

**Table 8.** Averages of biological replicates for media & lipo controls.

![Table 9 Delta Ct](https://static.igem.wiki/teams/5697/wiki/results/igem8.webp)

**Table 9.** ΔCt values across conditions.

![Table 10 RQ](https://static.igem.wiki/teams/5697/wiki/results/igem99.webp)

**Table 10.** Relative quantity (RQ) of DAZAP1 and GAPDH.

![Table 11 Relative expression](https://static.igem.wiki/teams/5697/wiki/results/igem10.webp)

**Table 11.** Relative gene expression normalized to GAPDH.

![Table 12 DeltaDeltaCt](https://static.igem.wiki/teams/5697/wiki/results/igem11.webp)

**Table 12.** ΔΔCt & expression fold change.

Tables 7 - 11 show a stepwise analysis of DAZAP1 expression relative to GAPDH using qPCR. After all calculations and accounting for outliers, we see that the expression folder change is ~79 percent, sharing that DAZAP1 causes a 21 percent knockdown of the ASO of interest.

## FAM - Delta Delta Ct Method

**Table 13.** Raw Ct Values for TDP-43 (FAM) and GAPDH Knockdown.

![](https://static.igem.wiki/teams/5697/wiki/results/igem12.webp)

Table 12 has Ct values for FAM expression across three technical and biological replicates for treated, media only, and lipofectamine only samples. The treatment group has six samples (7-12), the media group has three (13-15), and the lipofectamine group has three (16-18). With three biological replicates, we were able to remove outliers between biological replicates to ensure our data points accurately described the true Ct value.

**Table 14.** Average and Standard Deviations of Biological Replicates.

![](https://static.igem.wiki/teams/5697/wiki/results/igem13.webp)

FAM and GAPDH Ct values from biological replicates are compared across different experimental conditions. Average FAM Ct values for the treated samples are lower than that of media and lipo. In GAPDH, we see more grounded values across conditions, supporting its role as a reference gene. The standard deviations of the treated samples are 0 because only one biological replicate produced values outside the outlier range. While less than ideal, both treated technical replicates are similar in value across the two, supporting the Ct values for both.

**Table 15.** Delta CtE Values for FAM and GAPDH.

![](https://static.igem.wiki/teams/5697/wiki/results/igem14.webp)

**Table 16.** Expression Fold Change.

![](https://static.igem.wiki/teams/5697/wiki/results/igem15.webp)

While only one biological replicate produced accurate results in this experiment, this scenario is accounted for by the Delta Delta Ct method used, as shown in table 14. Expression fold changes show a 50–60% difference between the two technical replicates, showing that FAM has a 40–50% knockdown on the expression of the ASO of interest.

{% endblock %}
{% block takeaway2\_expanded %}

## Experiment 2: Aptamer for TDP43 Mislocalization

![Immunofluorescence single slice showing DAPI, G3BP1, and TDP-43 staining with sodium arsenite stress.](https://static.igem.wiki/teams/5697/wiki/results/igem111.webp)

![Immunofluorescence single slice including aptamer staining on the 555 channel.](https://static.igem.wiki/teams/5697/wiki/results/igem222.webp)

![Maximum intensity projection of Z-stack immunofluorescence with aptamer staining.](https://static.igem.wiki/teams/5697/wiki/results/igem333.webp)

In the first image, which shows a single slice with TDP-43 antibody staining, G3BP1 antibody, DAPI, and sodium arsenite stress, the nuclei are clearly stained with DAPI and appear healthy and intact. The cytoplasmic staining, shown in red, appears faint and punctate in some areas but does not form large aggregates or stress granules. This matches the note that no stress granules were observed. Normally, sodium arsenite stress induces strong stress granule formation, but in this case the response was not visible, which may be due to insufficient stress conditions, variability in cell response, or technical issues with staining or imaging.

The second image includes the same staining as the first but adds aptamer staining on the 555 channel. The nuclei remain clearly stained, but the aptamer signal appears as scattered puncta with some background staining. There is weak cytoplasmic signal, possibly from G3BP1, but again there are no distinct stress granules. The scattered nature of the aptamer signal suggests that the staining may not yet be optimized and could be due to nonspecific binding or low target abundance.

The third image is a maximum intensity projection of a Z-stack with the same staining as the second image. The nuclei are again clearly visible, while the cytoplasmic staining is more distinct than in the previous images. The projection enhances weaker signals and allows for better visualization of small puncta. Some red and green puncta are more visible here compared to the single slice, but they still do not form the robust stress granules typically expected under sodium arsenite stress. The aptamer staining shows occasional puncta but does not co-localize strongly with stress granule markers.

{% endblock %}