1 / 21

Multistability in the lactose utilization network of Escherichia coli

Multistability in the lactose utilization network of Escherichia coli. Advisors: Tang Leihan & Namiko Mitarai Group two members: He Xiaojuan Bi Hongjie Wang Peng Wang Jinshui Li Xiang Li Mengyao Zheng Muhua Jiang Chongming. our photo & introduction. O utline.

bin
Download Presentation

Multistability in the lactose utilization network of Escherichia coli

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Multistability in the lactose utilization network of Escherichia coli Advisors: Tang Leihan & NamikoMitarai Group two members: He XiaojuanBi HongjieWang Peng Wang JinshuiLi Xiang Li Mengyao ZhengMuhua Jiang Chongming

  2. our photo&introduction

  3. Outline • Backgrounds • The lactose utilization network • Deterministic model • Deterministic model&Noise • Stochastic model • The lactose utilization network + lactose metabolism

  4. Backgrounds: • Regulatorynetwork: regulatorysystemthatconsistsofacollectionofnodes,pairsofwhichareconnectedbylinks. • Feedback loops: a cyclic chain of links in a regulatory network. • Positive feedback loops: self-activation or double negative feedback. • Multistability: thecapacity to achieve multiple internal states in response to a single set of external inputs. • Biological switch: cell fate, cell-cycle oscillations.

  5. Thelactoseutilizationnetwork Two external inputs: Glucose & TMG(thio-methylgalactoside) TMG: a non-metabolizable lactose analogue. Redlines:regulatoryinteractions. Black arrows: protein creation through transcription and translation. Dotted arrows: uptake process Operon: promoter + expressible genes

  6. Thelactoseutilizationnetwork and reportor system Bi-stability !!! Two transcriptional regulators: LacI: a repressor. CRP: an activator. GFP: green fluorescent protein, expressed at the lac promoter. HcRed: red fluorescent protein, expressed at the gat promoter. LacYcatalyses the uptake of TMG, which induces further expression of LacY, resulting in a positive feedback.

  7. Experimental results: b. Behavior of alarge cell population c. The phase diagram describing the state of the lactose utilization network in wild-type cells

  8. Deterministic model ρ: dissociation constant of LacI from its main DNA-binding site. ρ=1+RT/R0 : describes how tightly LacI is able to regulate the expression of the lacoperon.

  9. Our results

  10. Theoretical phase diagram

  11. Model analysis

  12. Model analysis & Add noise

  13. Stochastic model & Gillespie algorithm

  14. Stochastic model & Gillespie algorithm

  15. Lactose LacY (y) Lactose (x) Allolactose (w) LacZ (z) LacI Plac The lactose utilization network + lactose metabolism (S2) (S3) (S4) (S5)

  16. Lactose LacY (y) Lactose (x) Allolactose (w) LacZ (z) LacI Plac The lactose utilization network + lactose metabolism simplified model:

  17. The lactose utilization network + lactose metabolism steady state: Analyze the third equation, and let: We find:

  18. The lactose utilization network + lactose metabolism phase diagram

  19. Conclusion

  20. References: • Ertugrul M. Ozbudak, Mukund Thattai, Han N. Lim,Boris I. Shraiman& Alexander van Oudenaarden. 2004. Multistabilityin the lactose utilizationnetwork of Escherichia coli. • Kim Sneppen, Sandeep Krishna, and Szabolcs Semsey. 2010. Simplified models of biological networks. • Danlel T. Gillespie. 1977. Exact stochastic simulation of coupled chemical reactions. • Michael B. Elowitz et al. 2002. Stochastic gene expression in a single cell. • Jerome T. Mettetal, Dale Muzzey, Juan M. Pedraza, Ertugrul M. Ozbudak, and Alexander van Oudenaarden. Predicting stochastic gene expression dynamics in single cells.

  21. Thanks for your listening!

More Related