Omics data analysis reveals the system-level constraint on cellular amino acid composition

To create a stand-alone environment named aaomics with Python 3 and all the required package versions (especially for cobrapy is also available), run the following code:

$ conda create -n aaomics python=3

$ conda activate aaomics

$ pip install ipykernel $ python -m ipykernel install --user --name aaomics --display-name "aaomics" $ pip install pandas $ pip install Bio $ pip install matplotlib $ pip install seaborn $ pip install cobra

You can read more about using conda environments in the Managing Environments section of the conda documentation.

• Data Acquisition
• Get protein MW/Sequence corresponding to gene id using uniprot API
• Get amino acid composiotion from protein sequence
• Amino acid composition condsider protein sequence
• Amino acids composition of each protein (g / g protein) consider expression level under different conditions
• Amino acids composition of each condaition (g / g total protein) consider expression level

• The mass distribution of each AA in per unit mass of different proteins
• The mass ratio distribution of different proteins in per unit mass of total protein (only the pro-teins with a mean mass ratio among the top 50 are displayed)
• The mass distribution of each AA per unit mass of total protein
• Distribution of the mass ratio of twenty AAs per unit mass of total protein in different species

Yuanyuan Huang, Zhitao Mao, Yue Zhang, Jianxiao Zhao, Xiaodi Luan, Ke Wu, Lili Yun, Jing Yu, Zhenkun Shi, Xiaoping Liao, Hongwu Ma, Omics data analysis reveals the system-level constraint on cellular amino acid composition,Synthetic and Systems Biotechnology, 2024; https://doi.org/10.1016/j.synbio.2024.03.001