AKTA_chromatogram

This is a Python script to help extracting the data from Unicorn file acquired using ÄKTA purifier and reconstruct the chromatogram.

This repository is based in the great pyCORN python library. The pyCORN repository contains an amazing shiny web app. You can just drag and drop your report.res file from Unicorn software and get your interactive view of chromatogram. If you want to customize the elements in your chromatogram, then this Repo can help you out in a easy was.

You can find a reference using Size Exclusion Chromatography to characterize different snake venom samples with ÄKTA here:

Gren ECK, Kitano ES, Andrade-Silva D, Iwai LK, Reis MS, Menezes MC, Serrano SMT. Comparative analysis of the high molecular mass subproteomes of eight Bothrops snake venoms. Comp Biochem Physiol Part D Genomics Proteomics. 2019 Jun;30:113-121. doi: 10.1016/j.cbd.2019.01.012. Epub 2019 Jan 30. PMID: 30825662.

Install the pyCORN package.

pip install pycorn

Import the module pc_res3 from pycorn to extract the data from the unicorn file and the module rc from matplotlib to use LaTex sythax. Load the matplotlib and numpy libraries.

from pycorn import pc_res3
import matplotlib.pyplot as plt
from matplotlib import rc
import numpy as np

# activate latex text rendering
rc('text', usetex=True)

Create an object of the class pc_res3. The class pc_res3 is used to parse ÄKTA report.res files.

# load the unicorn file from the path
unicorn_file = pc_res3("/AKTA/report.res")

# Parse the file
unicorn_file.load()

# This will show the available data in the file (detectors, etc.)
print(list(unicorn_file.keys()))

There are 2 elements in the unicorn_data, the absorbance (mAu) and the elution volume (mL). We will separate them to plot the absorbance against the elution volume.

# data: contains the actual data with x/y-pairs as tuples
unicorn_data = unicorn_file["UV1_280nm"]["data"]
elution = [elem1 for elem1, elem2 in unicorn_data]
absorbance = [elem2 for elem1, elem2 in unicorn_data]

# extract the fraction annotation
fraction_data = unicorn_file["Fractions"]["data"]
fraction_ellution = [elem1 for elem1, elem2 in fraction_data]
fraction = [elem2 for elem1, elem2 in fraction_data]

# remove the last fraction annotation as it has the waste entry
fraction_ellution.pop()
fraction.pop()

# coerse the fraction annotation to integer
fraction = [int(i) for i in fraction]

Now we can plot the data using matplotlib.

plt.plot(elution, absorbance, linewidth=2.0, color = 'steelblue')
plt.ylabel('Absorbance (mAu)', weight='bold')
plt.xlabel('Elution volume (mL)', weight='bold')
plt.title(r'SEC of $B. jararacussu$ venom')
plt.legend(['280 nm'])
plt.style.use('default')
plt.gcf().set_size_inches(10, 5)
plt.savefig('SEC_adult.png', dpi=300)

We can also add the fraction annotation to the chromatogram.

plt.plot(elution, absorbance, linewidth=2.0, color = 'steelblue')
plt.ylabel('Absorbance (mAu)', weight='bold')
plt.xlabel('Elution volume (mL)', weight='bold')
plt.title(r'SEC of $B. jararaca$ venom - Adult')
plt.legend(['280 nm'])
plt.style.use('default')
for i in range(len(fraction)):
    plt.text(fraction_ellution[i], fraction[i], str(i+1), fontsize=5, color='red')
plt.gcf().set_size_inches(10, 5)
plt.savefig('SEC_adult_fractions.png', dpi=300)