课号:08411207    学分:4       

  

主持人:汤超






指导老师齐志,林一瀚,罗春雄,宋晨,魏平,汤超,李志远,张磊,刘峰,欧阳颀,罗冬根,来鲁华,韩敬东

 

‣ 助教:关国业 - 电邮1801111472@pku.edu.cn

 

时间:周二 15:10 - 18:00 (第7, 8, 9节课)

 

地点:定量生物学中心102会议室 (老化学楼东配楼)

 

 

 

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本课以深度文献阅读为主,重点介绍生物学中理论与实验相结合而产生的概念、原理、方法,及其当前的发展趋势和面临的挑战。每堂课针对一个方面,深入讨论一篇文章,适当参考第二篇文章。学生在课前(至少一周前)应仔细阅读要讨论的文章(一般至少4-6小时),并在课堂上积极参与讨论。指导老师介绍背景知识,启发、引导讨论。课程涉及的内容包括:生物系统中的随机性和噪声,协同性,双稳态,信号转导中的定量问题,生物系统的鲁棒性,能耗与精确性,细菌菌群的竞争与共生,发育中的信息流,图灵斑图,定量神经生物学,细菌生长定律,合成生物学,从生物网络的角度来理解疾病、衰老及药物相互作用。本课为定量生物学中心研究生必修课。欢迎其它院系的研究生及本科生选修。

 

 

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‣ 参考书

✓ Alberts, et al. Molecular Biology of the Cell.

✓ Hartl and Jones. Genetics: Analysis of Genes and Genomes.

✓ Alon. An introduction to systems biology: design principles of biological circuits.

 课程网站:http://221.216.6.54:16288/qsjh/xjskc/xtswxxj/253441.shtml

另:前几周采用网上开课方式。同学们提前阅读要讨论的文章,上课时间登录指定的视频会议(具体另行通知)。有困难及时告知助教。

 

评分方式

阅读报告25%,  课堂参与50%,Project 25%

阅读报告

每堂课开始前提交关于该课将要讨论的文章的阅读报告,内容可以包括:该文章讨论了什么科学问题,用了什么方法,得到了什么结论,有什么意义,对你有什么启发,你有什么问题,等 。一页纸左右。

课堂参与

发言,提问,回答问题,互动 ,感想,体会,辩论,上黑板讲解、推公式等

Project

学生自己分组(3-4人)。其中两组讲最后两次课,其它组自选一个project来present ,不能讲与自己研究有关的内容。

 

        课程安排        

 

 

 

Class 1: Course Introduction(汤超)2/18

 

Class 2: DNA-Protein Interactions: Transcription Factor Search and Binding(齐志)2/25

 Riggs, A. D., Bourgeois, S. & Cohn, M. The lac repressor-operator interaction. 3. Kinetic studies. J. Mol. Biol. 53, 401-417 (1970).

 Wang, F. et al. The promoter-search mechanism of Escherichia coli RNA polymerase is dominated by three-dimensional diffusion. Nat. Struct. Mol. Biol. 20, 174-181, doi:10.1038/nsmb.2472 (2013).

 

Class 3: Fluctuations and Noise - Gene Products(林一瀚)3/3

Elowitz MB, Levine AJ, Siggia ED, Swain PS. 2002. Stochastic gene expression in a single cell. Science 297: 1183-6. Supplementary Material will also be discussed.

Maamar H, Raj A, Dubnau D. 2007. Noise in gene expression determines cell fate in Bacillus subtilis. Science 317: 526-9.

 

Class 4: All-or-none Transition I - Cooperativity(宋晨)3/10

 Monod J, Wyman J, and Changeux J-P. 1965. On the nature of allosteric transitions: a plausible model. J MolBiol 12: 88-118.

 Duke TAJ, Bray D. 1999. Heightened sensitivity of a lattice of membrane receptors. PNAS 96: 10104-10108.

 

Class 5: All-or-none Transition II - Bistability(罗春雄)3/17

(两篇文献都要阅读、讨论)

 Novick A, Wiener M. 1957. Enzyme induction as an all-or-none phenomenon. PNAS 43: 553-66.

 Paul J. Choi, Long Cai, Kirsten Frieda, X. SunneyXie. 2008. A stochastic single-molecule event triggers phenotype switching of a Bacterial cell. Science 322: 442-5.

 

Class 6: Quantitative Signaling(魏平)3/24 

 Long Cai, Chiraj K. Dalal& Michael B. Elowitz. 2008, Frequency-modulated nuclear localization bursts coordinate gene regulation. Nature 455: 485-490.

 Joe H. Levine, Yihan Lin, and Michael B. Elowitz. 2013, Functional roles of pulsing in genetic circuits. Science 342: 1193-1200.

 

Class 7: Energy Accuracy Relation (汤超) 3/31

 Hopfield JJ. 1974. Kinetic proofreading: a new mechanism for reducing errors in biosynthetic processes requiring high specificity. PNAS 71: 4135-9.

 Lan G, Sartori P, Neumann S, Sourjik V, Tu Y. 2012. The energy–speed–accuracy trade-off in sensory adaptation. Nature Physics 8: 422-428.

 

Class 8: Microbial Community (李志远) 4/7

 JE Goldford, Emergent simplicity in microbial community assembly. Science, 2018.

 MA Fischbach, Signaling in host-associated microbial communities, Cell, 2016.

 

Class 9: Turing Pattern(张磊)4/14 

  Kondo, S.,& Miura, T. (2010). Reaction-diffusion model as a framework for understanding biological pattern formation. Science, 329: 1616-1620.

  J. D. Murray, Mathematical Biology II (Springer Verlag, Berlin, 2003. Chapter 2: Spatial Pattern Formation with Reaction Diffusion Systems.

 

Class 10: Information Flow in Development(刘峰)4/21

Gregor T, Tank DW, Wieschaus EF, Bialek W (2007) Probing the limits to positional information. Cell 130: 153–164.

Bahram Houchmandzadeh, Eric Wieschaus,& Stanislas Leibler. 2002. Establishment of developmental precision and proportions in the early Drosophila embryo. Nature 415: 798-802.

 

Class 11: Synthetic Biology(欧阳颀) 4/28

 Gardner, Timothy S., Charles R. Cantor, and James J. Collins. 2000. Construction of a genetic toggle switch in Escherichia coli. Nature 403: 339-42.

 Elowitz M, Leibler S. 2000. A synthetic oscillatory network of transcriptional regulators. Nature 403: 335-8.

 

Class 12: Neuroscience(罗冬根) 5/10

 Selig Hecht, Simon Shlaer, Maurice Henri Pirenne. 1942. Energy, Quanta, and vision. The Journal of General Physiology. 25 (6): 819-840.

 D. A. BAYLOR, T. D. LAMB AND K.-W. YAU. 1979. RESPONSES OF RETINAL RODS TO SINGLE PHOTONS. J. Physiol. 288: 613-634.

 

Class 13: Disease and Drug Networks (来鲁华) 5/12

 Behar M, Barken D, Werner SL, Hoffmann A. 2013. The dynamics of signaling as a pharmacological target. Cell 155: 448-461.

 Yang K et al. 2008. Finding multiple target optimal intervention in disease- related molecular network. Mol Sys Biol 4:228.

 

Class 14: System Biology of Aging and Development (韩敬东) 5/19

(文章待定)

 

Class 15: Robustness(学生) 5/26

Barkai N, Leibler S. 1997. Robustness in simple biochemical networks. Nature 38: 913-7.

Li F, Long T, Lu Y, Ouyang Q, and Tang C. 2004. The yeast cell-cycle network is robustly designed. Proc Natl Acad Sci USA. 101: 47814786.

 

Class 16: Bacteria Growth Laws(学生) 6/2

Scott M, Gunderson CW, Mateescu EM, Zhang Z, Hwa T. 2010. Interdependence of cell growth and gene expression: origins and consequences. Science 330: 1099-1102.

Monod J. 1949. The growth of bacterial cultures. Ann Rev Microbiol 3:371-394.

 

Project Presentation:(学生) 6/9



 

         文献补充       

 

 

 

Class 1: Course Introduction

 

Class 2: DNA-Protein Interactions:

 The promoter-search mechanism of Escherichia coli RNA polymerase

 The lac repressor-operator interaction

 Probing Transcription Factor Dynamics

 

Class 3: Fluctuations and Noise - Gene Products 

Stochastic gene expression in a single cell

Stochastic gene expression in a single cell (supplementary)

 Noise in gene expression determines cell fate in Bacillus subtilis

Regulation of noise in the expression of a single gene

Summing up the noise in gene networks

Models of stochastic gene expression

Control of stochasticity in eukaryotic gene expression

 

 Mutations of bacteria from virus sensitivity to virus resistance

 Metastasis results from preexisting variant cells within a malignant tumor  

 Muscular dystrophy meets the mesangioblast

✓ A multigenic program mediating breast cancer metastasis to bone

 

Class 4: All-or-none Transition I – Cooperativity

 On the nature of allosteric transitions: a plausible model

 Heightened sensitivity of a lattice of membrane receptors

 An amplified sensitivity arising from covalent modification in biological systems

 Folding of chymotrypsin inhibitor 2. 1. evidence for a two-state transition

 

Class 5: All-or-none Transition II  Bistability

 Enzyme induction as an all-or-none phenomenon

 A stochastic single-molecule event rriggers phenotype switching of a bacterial cell

 Multistability in the lactose utilization network of Escherichia coli

 

Class 6: Quantitative Signaling

 Frequency-modulated nuclear localization bursts coordinate gene regulation

 Functional roles of pulsing in genetic circuits

 

Class 7: Energy-Accuracy Relation

 Kinetic proofreading 1974 

 The energy speed accuracy trade off in sensory adaptation

 Folding of chymotrypsin Inhibitor 2. 1. evidence for a two-state transition

 Dynamic instability of microtubule growth

 Kinetic amplification of enzyme discrimination

 The role of proofreading in signal transduction specificity

 A kinetic proofreading mechanism for disentanglement of DNA by topoisomerases

 

Class 8: Microbial Community

 Emergent simplicity in microbial community assembly

 Signaling in host-associated microbial communities

 

Class 9: Turing Pattern

 Reaction-diffusion model as a framework for understanding biological pattern formation

 Spatial pattern formation with reaction diffusion systems

 The chemical basis of morphogenesis

 

Class 10: Information flow in development

 Establishment of developmental precision and proportions in the early Drosophila embryo

 Probing the limits to positional information

 

Class 11: Synthetic Biology

 Construction of a genetic toggle switch in Escherichia coli

 A synthetic oscillatory network of transcriptional regulators

 Robust multicellular computing using genetically encoded NOR gates and chemical 'wires'

 Build life to understand it

 Synthetic biology: applications come of age

 

Class 12: Neuroscience  

 Croonian Lecture, Ionic movements and electrical activity in giant nerve fibres

 Theory of threshold fluctuation in nerves I

 

Class 13: Disease and drug networks

 The dynamics of signaling as a pharmacological target

 Finding multiple target optimal intervention in disease - related molecular network

 Drug interactions and the evolution of antibiotic resistance

 Systematic discovery of nonobvious human disease models through orthologous phenotypes

 The growth of bacterial cultures

 

Class 14: System Biology of Aging and Development

(TBA)

 

Class 15: Robustness

Robustness in simple biochemical networks

The yeast cell-cycle network is robustly designed

Robustness in bacterial chemotaxis

A molecular mechanism for sensory adaptation based on ligand-induced receptor modification

A model of excitation and adaptation in bacterial chemotaxis

Receptor sensitivity in bacterial chemotaxis

Robustness and modular design of the Drosophila segment polarity network

Circuit topology and the evolution of robustness in two-gene circadian oscillators

The segment polarity network is a robust developmental module

 

Class 16: Bacteria Growth Laws

Interdependence of cell growth and gene expression: origins and consequences

The growth of bacterial cultures

 

Class S: Genome-Wide Analysis

 CellNet network biology applied to stem cell engineering

 Dissecting engineered cell types and enhancing cell fate conversion via CellNet

 Cluster analysis and display of genome-wide expression patterns

 The consensus coding sequences of human breast and colorectal cancers

✓ Comment on 'The consensus coding sequences of human breast and colorectal cancers'

 Response to comment on 'The consensus coding sequences of human breast and colorectal cancers'