five

Raw data and tidy data from the pre-adaptation experiment

收藏
Figshare2025-12-22 更新2026-04-28 收录
下载链接:
https://figshare.com/articles/dataset/Raw_data_and_tidy_data_from_the_pre-adaptation_experiment/30933734
下载链接
链接失效反馈
官方服务:
资源简介:
This dataset accompanies the manuscript titled "Rapid evolution in necromass use under resource limitation reduces persistence in producer-decomposer microbial biospheres." The study investigates how microbial evolution under resource-limited conditions affects the stability and persistence of synthetic microbial ecosystems. Using a closed-system microbial biosphere model, the research examines adaptive changes in Escherichia coli during 60 days of monoculture under spatially homogeneous (HMG) and heterogeneous (HTG) conditions, followed by co-culture with the autotrophic alga Chlamydomonas reinhardtii.Key experimental outcomes include phenotypic shifts in E. coli such as loss of motility, enhanced biofilm formation, and improved carbon source utilization—particularly on necromass derived from both E. coli and C. reinhardtii. Contrary to expectations, these adaptive traits, while beneficial in monoculture, reduced system-level persistence in producer-decomposer co-cultures, especially in spatially heterogeneous environments.The dataset includes raw and processed data from growth curve analyses, phenotypic assays (motility, biofilm, curli fimbriae, pellicle formation), chlorophyll fluorescence measurements (as a proxy for system persistence), and cell viability counts over time. Statistical analyses, survival models, and correlation matrices are also provided.This work highlights an important eco-evolutionary trade-off: traits that enhance decomposer performance in isolation can undermine multisystem coexistence, with spatial structure during adaptation playing a critical role in shaping community outcomes. The data support further investigation into how microbial evolution influences ecosystem sustainability and cross-species interactions under resource scarcity.
创建时间:
2025-12-22
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作