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基于数据驱动发现细菌生长中基因与环境因素之间的相互作用

Data-driven discovery of the interplay between genetic and environmental factors in bacterial growth.

作者信息

Aida Honoka, Ying Bei-Wen

机构信息

School of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan.

出版信息

Commun Biol. 2024 Dec 24;7(1):1691. doi: 10.1038/s42003-024-07347-3.

DOI:10.1038/s42003-024-07347-3
PMID:39719455
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11668901/
Abstract

A complex interplay of genetic and environmental factors influences bacterial growth. Understanding these interactions is crucial for insights into complex living systems. This study employs a data-driven approach to uncover the principles governing bacterial growth changes due to genetic and environmental variation. A pilot survey is conducted across 115 Escherichia coli strains and 135 synthetic media comprising 45 chemicals, generating 13,944 growth profiles. Machine learning analyzes this dataset to predict the chemicals' priorities for bacterial growth. The primary gene-chemical networks are structured hierarchically, with glucose playing a pivotal role. Offset in bacterial growth changes is frequently observed across 1,445,840 combinations of strains and media, with its magnitude correlating to individual alterations in strains or media. This counterbalance in the gene-chemical interplay is supposed to be a general feature beneficial for bacterial population growth.

摘要

遗传因素和环境因素之间复杂的相互作用会影响细菌的生长。了解这些相互作用对于洞察复杂的生命系统至关重要。本研究采用数据驱动的方法来揭示由于遗传和环境变异而导致细菌生长变化的规律。对115株大肠杆菌菌株和包含45种化学物质的135种合成培养基进行了初步调查，生成了13944个生长曲线。机器学习对该数据集进行分析，以预测化学物质对细菌生长的优先次序。主要的基因-化学网络呈层次结构，葡萄糖起着关键作用。在1445840种菌株和培养基的组合中经常观察到细菌生长变化的偏移，其幅度与菌株或培养基中的个体变化相关。基因-化学相互作用中的这种平衡被认为是有利于细菌种群生长的一个普遍特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5102/11668901/c834c9154ec8/42003_2024_7347_Fig8_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5102/11668901/3a59955b2801/42003_2024_7347_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5102/11668901/c834c9154ec8/42003_2024_7347_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5102/11668901/fedb392ba63a/42003_2024_7347_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5102/11668901/87eed0ea2ce3/42003_2024_7347_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5102/11668901/149bbb5e7a04/42003_2024_7347_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5102/11668901/ace971741a17/42003_2024_7347_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5102/11668901/032cdd23bad6/42003_2024_7347_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5102/11668901/0adc358af905/42003_2024_7347_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5102/11668901/3a59955b2801/42003_2024_7347_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5102/11668901/c834c9154ec8/42003_2024_7347_Fig8_HTML.jpg

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