北京大学定量生物学中心
学术报告
题 目: Resource conservation manifests in the genetic code
报告人: Dr. David Zeevi
Center for Studies in Physics and Biology, the Rockefeller University
时 间: 10月19日(周一)9:00-10:00
地 点: Online (Zoom会议)
会议 ID:627 9242 4126
https://zoom.com.cn/j/62792424126
主持人: Lucas Carey
摘 要:
Nutrient
limitation is a strong selective force, driving competition for
resources. However, much is unknown about how selective pressures
resulting from nutrient limitation shape microbial coding sequences.
Here, we study this ‘resource-driven’ selection using metagenomic and
single-cell data of marine microbes, alongside environmental
measurements. We show that a significant portion of the selection
exerted on microbes is explained by the environment and is strongly
associated with nitrogen availability. We further demonstrate that this
resource conservation optimization is encoded in the structure of the
standard genetic code, providing robustness against mutations that
increase carbon and nitrogen incorporation into protein sequences.
Overall, we demonstrate that nutrient conservation exerts a significant
selective pressure on coding sequences and may have even contributed to
the evolution of the genetic code.
报告人简介:
David
Zeevi is an independent postdoctoral fellow at the Rockefeller
University Center for Studies in Physics and Biology. His research
focuses on developing computational methods for studying the human gut
and marine microbiomes, and their contribution to human and
environmental health. David applies these tools in clinical settings in
order to understand the relationship between nutrition, health, and gut
microbes in humans; and in environmental settings in order to find new
microbial mechanisms for combating pollution. David has coauthored
several publications in the human microbiome field, linking the
microbiome to the effects of artificial sweeteners (Suez et al., Nature
2014) and host circadian rhythm (Thaiss et al., Cell 2015), inferring
bacterial growth dynamics (Korem et al., Science 2015), predicting the
glycemic responses of individuals to complex meals (Zeevi et al., Cell
2015; Korem et al., Cell Metab 2017), and characterizing microbial
genomic variability across individuals (Zeevi et al., Nature 2019).