Our Contribution to the Community

iGEM is more than just a competition, it is a place and an opportunity to exchange ideas, knowledge and innovative techniques. Each year, teams from around the world gain invaluable experience in interdisciplinary work and laboratory methods. As the iGEM Team Freiburg 2024, we want to support this collaborative spirit and introduce future teams to the fascinating world of lipid-based nanocarriers.

Our Guide to Lipid-based Nanocarriers

We have developed a comprehensive guide of the production and measurement of lipid-based nanocarriers. This guide is intended to help future iGEM teams and anyone interested in this cutting-edge field.

Our guide provides:

  • Instructional videos that show step by step how to produce:
    • liposomes via PVA swelling followed by extrusion
    • lipid nanoparticles via pipetting
  • Size determination technique where you can learn how to measure the size distribution of lipid-based nanocarriers using Dynamic Light Scattering (DLS).
  • We provide two different plotting tools to visualize and interpret the following data efficiently.
    • DLS data
    • various Excel-data
  • Discover how to fine-tune liposome production process, including guidance on extrusion techniques to achieve the ideal size for CAPTURE liposomes.

With the help of our guide, future teams will gain valuable insights into the entire process of lipid-based vesicle production and characterization. This knowledge will enable them to optimize their experiments and thus save time and resources in their iGEM project.

DLS Plotting Tool

The DLS plotting tool is a method to quantify the distribution of DLS measured particles. It provides an alternative to conventional software and aims to optimize the efficiency of DLS measurements and extrusions.

Step zero:

General information:

Before we dive into the specifics of our guide, let us set up the necessary tools and environments:

Coding tool:

We are using visual studio code (VS Code) for our DLS-plots.

VS Code is a integrated development environment by Microsoft for Linux, Windows and macOS

Download: https://code.visualstudio.com

If you are more familiar with other editors, you can choose any other editor for this plotting tool.

Programming Language: Python

Version: 2024.4.1 Python is a general-purpose dynamic programming language. Find more information at https://www.python.org/about/

Output visualization:

As package manager we use pip in a python environment.

You can download pip via

  • Linux: python -m ensurepip --upgrade
  • macOS: python -m ensurepip --upgrade
  • Windows: py -m ensurepip --upgrade

in your python environment.

Software Repository for Code:

Our project code is available on GitHub or can be downloaded from

1. Creating Python files

  1. Open Visual Studio Code (VSCode).
  2. Create a new file.
  3. Save the file with a unique, descriptive name and add the .py extension (e.g., my_dls_analysis.py). The .py extension tells VSCode that this is a Python file.
  4. Name this file with an individual name with .py ending.

2. Understanding the usage of packages:

  • Python executes the code
  • Packages are code that has been written and provided by someone for various purposes. You can use packages to facilitate your process of coding.

Python uses different packages for various operations:

import pandas as pd                             # provided code for data analysis
import matplotlib.pyplot as plt                 # matplotlib provides code for creating visualizations
import numpy as np                              # provides advanced mathematical functions
from io import StringIO                         # reads and writes string buffer (memory files)

By using these listed packages, we can accomplish our tasks to analyzing the DLS data much more efficiently.

3. Installing required packages

To install the necessary packages, follow these steps:

  1. Create a new virtual environment via python-m venv venv
  2. Activate your virtual environment via source.venv
  3. Install package via pip install package_name

Specifically install the following packages: pandas, numpy and matplotlib

Note: If you see a message stating “Requirement already satisfied,” it means the package is already installed on your system. This is normal and not a cause for concern. If you encounter any issues during installation, please refer to the Python Packaging User Guide for troubleshooting tips and more detailed information.

4. Import your data

  1. Export your DLS data as a .txt file
  2. Copy the data into a new Excel sheet
  3. Save the Excel file as .csv
    • file > save as > file_format > CSV UTF-8”
    • name your file (e.g. “my_filename.csv”) and save it.
  4. In VS code open your folder with your data sheet and copy the path of the .csv file
  5. Paste the file path to the following function to define the filename
  filename = "py.code/neu.csv"
  df = pd.read_csv(filename, delimiter=';').

To do this, however, we need the data. We get this from the Excel file, which you can output as a .txt data sheet. Now, copy the .txt file into a blank Excel sheet. This will create a table with a lot of data. Afterward, save your Excel sheet as a .csv file by going to File > Save As > File Format > CSV UTF-8.

5. Pre-Preprocessing the Data

Our DLS device uses commas (“,”) instead of decimal points (“.”) in its output. Python requires decimal points for numerical values, so we need to convert the data: As python cannot recognize commas as full stops, we have to exchange comma into full stops via

  return [str(x).replace(",", ".") for x in values]

6. Run the Code

Execute the code using the “Run” button in the top-right corner of VS Code.
Now you can execute the code via this button (right, on top of VS Code)

7.1 Interpret your Results

The graph is now plotted. The generated graph shows the intensity and size of your first 5 measured samples (first 5 rows of the table). The yellow rectangle indicates the ideal size for CAPTURE liposomes to which you can compare your samples.

Common Mistakes:

  • the data-sheet is not well-imported and the correctly copied code

Incorrect handling of the USB stick or the device’s software can often lead to data loss, whereupon the tool no longer works. Please be aware that this can happen quickly and that the error in the terminal will also show you this individually. If you are interested, you can read and understand the error message so that you can better understand your data loss.

  • you are using an other operating system

In case you are working with a Microsoft, macOS or a Linux device, be aware that there can be differences in terms of installation and execution of the supplied code.

For individual help, look at the Python documentation

7.2.1 Analyze Extruded Liposomes

If you have extruded your liposomes, use our second tool to determine the optimal number of extrusion for liposomes.

Define your minimal size and maximal size for the result of extrusion.

  x_low = 20                                  # minimal size
  x_high = 250                                # maximal size

7.2.2 Execute the Code

This tool helps you to find the ideal number of extrusions to achieve the ideal size of liposomes.
For example, with our lipid composition, approximately 7 extrusions were required for example_liposomes.
By following these steps and using our tools, you can effectively analyze your DLS data and optimize your liposome production.

Plotting Tool (Uniform Plots from Excel and Google Sheets)

This is a tool to produce uniform looking and visually impaired plots. The colors are preconfigured to match the color theme of iGEM Freiburg 2024 but can easily be changed in the code. Using this tool makes it really easy for your next project to have user friendly and uniform looking graphs. All you need is internet access and the CaoturePlot24.html file, then just paste in your data.

Simply download the plotting tool and open it with your favourite browser. You can find the following explanation there as well.

Copy your data out of your docs sheet/excel sheet and paste it in the input fields, then press plot data.
You can set the scope of your graph with zoom and download it directly as a png. :)
Pay attention to the labeling and the units!
Also dont use “,” use “.” instead If you already have used “,” instead of “.” dont panic and follow this guide

Plot your data

To make bar plots have your excel file in this format and select as plot style "Bar Plot". Provide your error data as shown (optional).

bar plot excel
bar plot excel
bar plot

Line and Dot Plots

To make line and dot plots have your excel file in this format and select as plot style the mode you like. Provide your error data as shown (optional).

line plot excel
line plot excel
line plot