MutAtlas

A lightweight Sanger-based mutation profiling tool for plasmid engineering

MutAtlas is an automated Sanger sequencing analysis tool designed for plasmid validation and mutation profiling in molecular biology workflows.

It integrates sequence alignment, Phred quality assessment, multi-primer evidence aggregation, and confidence-based mutation identification to reduce manual chromatogram inspection and facilitate mutation landscape analysis.

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Overview

In protein engineering and molecular cloning workflows, Sanger sequencing is commonly used to verify engineered variants. However, manually inspecting chromatograms from multiple clones and primers is time-consuming and prone to subjective judgment.

MutAtlas provides an automated workflow to:

• Process multiple Sanger .ab1 files
• Identify sequence variants against a reference plasmid
• Evaluate mutation reliability using sequencing quality metrics
• Aggregate evidence from multiple sequencing primers
• Generate mutation profiling reports

Workflow:

Sanger chromatograms (.ab1)
|
↓
Sequence alignment
|
↓
Quality-based evaluation
|
↓
Multi-primer mutation analysis
|
↓
Mutation profiling report

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Features

Automated Sanger Data Processing

• Batch processing of multiple .ab1 sequencing files
• Automatic forward/reverse sequence orientation handling
• Reference-guided sequence alignment

Mutation Identification

• Whole plasmid mutation scanning
• ORF-level mutation annotation
• DNA mutation and amino acid substitution reporting

Example:

DNA:
GAA → GGA

Protein:
E125G

Mutation Confidence Assessment

MutAtlas integrates multiple factors to estimate mutation reliability:

• Phred sequencing quality score
• Local sequencing quality around mutation sites
• Potential mixed peak detection
• Multi-primer support evidence

Each detected mutation receives a confidence score for downstream filtering.

Mutation Profiling

Generated reports summarize:

• Mutation position
• Base substitution
• Amino acid change
• Supporting sequencing reads
• Confidence score
• Mutation frequency distribution

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Installation

Clone the repository:

git clone https://github.com/yourname/MutAtlas.git
cd MutAtlas

Install dependencies:

pip install -r requirements.txt

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Requirements

Python >= 3.9

Dependencies:

biopython
numpy
pandas
openpyxl
psutil

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Usage

Run the graphical interface:

python MutAtlas.py

Input:

• Reference plasmid sequence (.fasta)
• Sanger sequencing files (.ab1)
• Optional ORF/CDS information

Output:

• Excel mutation profiling report
• Mutation confidence assessment
• Summary statistics

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Output Example

The generated report contains:

Clone	Mutation	AA Change	Confidence
Clone_01	A376G	E125G	96
Clone_02	T890C	V297A	82
Clone_03	G1205A	-	45

High-confidence variants can be selected for downstream experiments.

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Applications

MutAtlas can be applied to:

• Plasmid construction verification
• Protein engineering workflows
• Directed evolution screening
• Mutant library characterization
• AI-designed protein variant validation

Example workflow:

AI-designed variants
          |
          ↓
Gene synthesis & cloning
          |
          ↓
Sanger sequencing
          |
          ↓
MutAtlas mutation profiling
          |
          ↓
Functional characterization

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Why MutAtlas?

Unlike traditional sequence comparison tools, MutAtlas focuses on reliable mutation extraction from experimental sequencing data by combining sequence information with sequencing quality evidence.

It bridges the gap between:

Experimental sequencing data
              ↓
Reliable mutation information
              ↓
Protein engineering decisions

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Future Development

Potential extensions:

• Command-line interface
• Automated mutation landscape visualization
• Support for larger variant libraries
• Integration with protein design pipelines

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License

MIT License

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Citation

If you use MutAtlas in your research, please cite this repository.

MutAtlas: A lightweight Sanger-based mutation profiling tool for plasmid engineering.