Tutorial: Optimizing GFP for N. benthamiana Expression

This tutorial walks through a complete codon optimization workflow using Green Fluorescent Protein (GFP) as an example target, showing how to go from an amino acid sequence to a Nicotiana benthamiana-ready CDS.

Prerequisites

pip install factorforge-cds

Verify installation:

factorforge --version

Input Sequence

We use the Aequorea victoria GFP sequence (239 amino acids) as our target protein. Save it as gfp.fasta:

>GFP|Aequorea_victoria|239aa
MVSKGEELFTGVVPILVELDGDVNGHKFSVSGEGEGDATYGKLTLKFICTTGKLPVPWP
TLVTTLTYGVQCFSRYPDHMKQHDFFKSAMPEGYVQERTIFFKDDGNYKTRAEVKFEGDT
LVNRIELKGIDFKEDGNILGHKLEYNYNSHNVYIMADKQKNGIKVNFKIRHNIEDGSVQL
ADHYQQNTPIGDGPVLLPDNHYLSTQSALSKDPNEKRDHMVLLEFVTAAGITLGMDELYK

Step 1: Run Optimization (CLI)

Optimize with the balanced profile — the recommended starting point for N. benthamiana expression:

factorforge optimize gfp.fasta --engine profile --profile balanced -o gfp_optimized.fasta

For BY-2 bioreactor production:

factorforge optimize gfp.fasta --engine profile --profile balanced --host by2

Expected output:

Optimizing with Profile-based v3.1.6...
Saved to: gfp_optimized.fasta
Metrics:
  - cai: 0.781
  - gc_percent: 57.32
  - score: 0.843

The optimized CDS begins with ATGGTCAGCAAGGGCGAGGAG... — ready for synthesis or downstream assembly.

What happened:

Metric	Value	Target range
CAI	0.781	— (higher is better)
GC%	57.32%	55–65%
Internal stop codons	0	0 (hard requirement)
Rare codon runs	0	0 (ribosome stalling risk)

Step 2: Compare Profiles

Different expression goals call for different profiles. Use --compare-profiles to evaluate all options at once:

factorforge optimize gfp.fasta --engine profile \
  --compare-profiles balanced,high_cai,gc_target,assembly_friendly \
  --scan-mode fast

Output:

Profile comparison results:
─────────────────────────────────────────────
Profile               CAI     GC%    Score
─────────────────────────────────────────────
balanced            0.767   58.86    0.846
high_cai            1.000   31.24    0.936
gc_target           0.897   42.40    0.679
assembly_friendly   0.769   55.09    0.819
─────────────────────────────────────────────

How to choose:

Profile	Best for
balanced	General N. benthamiana expression; good CAI with GC% in target range
high_cai	Maximum translation speed; note GC% may fall outside 55–65% range
gc_target	When GC% must stay near 42.5% (e.g. specific vector requirements)
assembly_friendly	MoClo / Golden Gate workflows; avoids problematic restriction sites

For most N. benthamiana agroinfiltration experiments, balanced is the recommended starting profile.

Step 3: Python API

The same optimization is available programmatically:

from factorforge.engines import EngineRegistry

# Load the profile engine
optimizer = EngineRegistry.get("profile")

gfp_aa = (
    "MVSKGEELFTGVVPILVELDGDVNGHKFSVSGEGEGDATYGKLTLKFICTTGKLPVPWP"
    "TLVTTLTYGVQCFSRYPDHMKQHDFFKSAMPEGYVQERTIFFKDDGNYKTRAEVKFEGDT"
    "LVNRIELKGIDFKEDGNILGHKLEYNYNSHNVYIMADKQKNGIKVNFKIRHNIEDGSVQL"
    "ADHYQQNTPIGDGPVLLPDNHYLSTQSALSKDPNEKRDHMVLLEFVTAAGITLGMDELYK"
)

result = optimizer.optimize(gfp_aa, profile="balanced")

print(f"Optimized CDS: {result.sequence[:60]}...")
print(f"CAI:   {result.metrics['cai']:.3f}")
print(f"GC%:   {result.metrics['gc_percent']:.2f}")
print(f"Score: {result.metrics['score']:.3f}")

To compare profiles programmatically:

profiles = ["balanced", "high_cai", "gc_target", "assembly_friendly"]

for p in profiles:
    r = optimizer.optimize(gfp_aa, profile=p, scan_mode="fast")
    cai = r.metrics["cai"]
    gc  = r.metrics["gc_percent"]
    score = r.metrics["score"]
    print(f"{p:<20} CAI={cai:.3f}  GC={gc:.2f}%  Score={score:.3f}")

Step 4: Custom Restriction Site Removal

For MoClo / Golden Gate assembly, remove specific restriction sites:

factorforge optimize gfp.fasta --engine profile --profile assembly_friendly \
  --scan-include restriction_sites \
  -o gfp_moclo.fasta

The engine performs synonymous substitutions to eliminate recognition sequences while preserving the amino acid sequence.

Step 5: Downstream Use

The output FASTA is ready for:

• Gene synthesis — submit directly to IDT, Twist, or Genscript
• MoClo Level 0 — use with the assembly_friendly profile; check for BsaI/BpiI site removal
• Agroinfiltration — clone into a binary vector (e.g. pEAQ-HT, pK7WG2) for A. tumefaciens-mediated delivery

Wet-lab validation

The 5' Ramp and Viral Delivery profiles are currently pending wet-lab validation and are disabled by default. Submit your expression results via the feedback form to help validate these profiles.

Summary

Step	Command
Install	pip install factorforge-cds
Optimize (balanced)	factorforge optimize gfp.fasta --engine profile --profile balanced -o out.fasta
Compare profiles	factorforge optimize gfp.fasta --engine profile --compare-profiles balanced,high_cai,gc_target
Assembly-ready	factorforge optimize gfp.fasta --engine profile --profile assembly_friendly -o out.fasta

GFP optimization results (balanced profile, N=1):

Metric	Result
Input length	239 aa
Output CDS length	720 bp (239 × 3 + stop)
CAI	0.781
GC%	57.32%
Internal stop codons	0
Rare codon runs (≥3)	0
Composite score	0.843