Cell and Systems Biology

Module Leaders: 
Tamas Nagy (tamas@tamasnagy.com - Weiner Lab)
Cole Helsell (cole.helsell@ucsf.edu - Kokel Lab)

Facilitators:
Taylor Cavazos (taylor.cavazos@ucsf.edu)
Matt Jones (matthew.jones@ucsf.edu)

SURVEY:
TBD

Module Goals: 
The goals of this module are to: 
  1. Expose all incoming students to current research and key tools in systems and cell biology. 
  2. Let incoming students who are interested in cell and systems biology know what labs ask those types of questions and use those tools here at UCSF. 
  3. Introduce them to some specific research projects from those labs (to help inform rotation decisions). 

Introduction: 
Aristotle said "The whole is greater than the sum of its parts" and nowhere is that more true than in biology!
One of the most-studied systems in biology are cell, the basic structural units of living organisms. Understanding cellular structure and basic processes within the cell is important for answering a broad range of biologically-relevant research questions. Moreover, asking questions about how cells interact with one another requires an understanding of how those cells function. Most research questions will touch on cell biology at one point or another. However, there are also research projects that focus much more in depth on how cells work. The Cell Biology Module will attempt to introduce to the latest in cell biology at UCSF.
Ultimately, a cell is a large collection of systems that all work together to allow an organism to survive, which is why the Cell Biology Module is paired with the Systems Biology Module. Systems Biology attempts to discover the appropriate level of resolution/abstraction to use to study a complex biological system in a variety of ways including: 
- Detailed dynamical systems modeling of interactions, calibrated with quantitative data ("Bottom-up"), and
- Using "Omics" level data to map the cell/organism to an appropriate level of resolution ("Top-down").
The Systems Biology Module will expose you to some of the ideas and methodologies which make up this relatively new field, especially as they pertain to research here at UCSF. 


Key Questions asked in these Sessions: 
What makes a cell? What levels of complexity can you study in cell biology?
Which techniques are best suited to study each level of complexity within the cell?
What is systems biology and how can you approach studying it?
What types of questions are particularly best suited to a systems approach?
Why is it important to use quantitative models in Systems Biology?
Why is it important to quantify results in Cell Biology?
How do we avoid making spurious conclusions in large "omics" data-sets? 


Module Schedule:
Friday 9/14
9:00 ~ 9:30 Module introduction
9:30 ~ 10:00 Student talk: Doug Tischer
10:00 ~ 10:30 Intro to modeling
10:30 ~ 12:30 Exercise on computational modeling 
12:30 ~ 1:30 Lunch
1:30 ~ 2:00 Intro to machine learning
2:00 ~ 4:00 Exercise on machine learning



Resources for exercises:
Reference paper for the computational modeling exercise:
        Sumino, Yutaka, et al. "Large-scale vortex lattice emerging from collectively moving microtubules" Nature 483.7390 (2012): 448–452



Labs in UCSF specialized in cell and/or systems biology (Alphabetical order):
Cell Biology:
Most labs do cell biology to a certain extent but this is a (by all means NOT comprehensive) list of ones that specialize in Cell Biology: 

Bassem Al-Sady - Epigenetic Inheritance
Fred ChangCell morphogenesis, regulation of cell shape and size, and cell mechanics
Sophie Dumont - Biophysics of the kinetechore, how cells divide
Joanne Engel – bacterial pathogen – host cell interactions
Jennifer Fung - Chromosome Synapsis and Recombination Control During Meiosis
Zev Gartner – tissue structure and function 
Bo Huang - super resolution optical microscopy of protein/lipid/DNA  organization and dynamics
Sandy Johnson - Evolution of transcriptional regulation; Candida Albicans
Natalia Jura – membrane organization and control of signaling 
Yuriy Kirichok - mitochondrial membrane dynamics and brown fat metabolism
Wendell Lim – cellular signaling systems 
Hiten Madhani - fungual pathogen-host cell interactions and genome defense 
Wallace Marshall – how cells measure and count 
David Morgan – protein machines that drive the cell cycle 
Keith Mostov – epithelial polarity, morphogenesis and regeneration 
Dyche Mullins – dynamics and structure of the cytoskeleton 
Kevan Shokat – novel tools to study signal transduction 
Jack Taunton – actin/membrane dynamics 
Ron Vale – molecular motors 
Mark von Zastrow – linking cell signaling and membrane traffic 
Peter Walter – organelle homeostasis and protein sorting 
Valerie Weaver - Mechanical and topological properties of the extracellular matrix
Orion Weiner – cell polarity and chemotaxis, signaling dynamics
Torsten Wittmann – microtubules, cell shape and polarity 
Frances Brodsky – intracellular membrane traffic 

Some departmental websites of interest: 
• BMS Graduate program: https://bms.ucsf.edu/research-area/tissueorgan-biology-endocrinology 
• Developmental Biology Grad Program: http://dscb.ucsf.edu/ 
• Developmental biology (Tetrad): https://tetrad.ucsf.edu/people/developmental-biology 
• Cell Biology (Tetrad): https://tetrad.ucsf.edu/people/cell-biology
• Department of Cell and Tissue Biology: http://ctb.ucsf.edu/ 

An important tool in cell biology is microscopy.  If you are interested in microscopy, you should be aware of the resources available in UCSF's Nikon Center.

Systems Biology:
Adam Abate - Droplet-based microfluidics for high-throughput processing of biological reactions. 
Steven Altschuler and Lani Wu  Cancer heterogeneity and drug resistance, high content screening, tissue organization. 
Sourav Bandyopadhyay - Systems approaches to map cancer network rewiring
Al Burlingame - Mass Spec - proteomics. 
Rahul Deo - Understanding how genetic variation contributes to cardiac and metabolic disease pathogenesis. 
Joe DeRisi  - Whole Genome approaches to understand human diseases (viruses, malaria) and yeast molecular biology
Hana El-Samad - Modeling and systems approaches to quantitatively study cellular stress responses
Zev Gartner - Tissue structure, cell-cell interactions
Hani Goodarzi -Cancer systems biology and translational genomics
Carol Gross - Bacterial stress responses
Martin Kampmann - protein homeostasis in normal & disease states,  CRISPR-based functional genomics & bioinformatics
David KokelHigh-throughput behavior based neuroactive drug discovery
Nevan Krogan - Large scale genetic and physical interaction maps. 
Hao Li - Gene regulatory networks, molecular mechanisms of aging. 
Wendell Lim - Design principles of cellular signaling. Synthetic Biology 
Leor Weinberger - Experimental & modeling approaches to understand fate-selection of viruses, engineer next-generation therapies
Wallace Marshall - Cellular morphogenesis.  Uses a variety of model organisms. 
Orion Weiner - Cell Polarity, mechanotransduction, optogenetics. 
Jonathan Weissman - Protein folding, protein translation using whole cell measurements (i.e. Ribosome Profiling)


Additional References
Collection of Classic Papers for Systems Biology:
Wingreen, Ned, and David Botstein. “Back to the future: Education for Systems-level Biologists.” Nature Reviews Molecular Cell Biology 7.November (2006): 829–832.
Texts:

S. H. Strogatz, Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering. (Westview, Cambridge MA, 1994).

Alon. U. An Introduction to Systems Biology: Design Principles of Biological Circuits. (Chapman and Hall/CRC Mathematical Computational Biology, 2006).

Network Modeling:
Tsai, Tony Yu-Chen et al. Robust, Tunable Biological Oscillations from Interlinked Positive and Negative Feedback Loops. Science (2008)

Ferrell, James E, Tony Yu-Chen Tsai, and Qiong Yang. Modeling the Cell Cycle: Why Do Certain Circuits Oscillate? Cell 144.6 (2011)

Ma, Wenzhe et al. Defining Network Topologies That Can Achieve Biochemical Adaptation. Cell 138.4 (2009)
Weinberger, Leor S et al. Stochastic Gene Expression in a Lentiviral Positive-feedback Loop: HIV-1 Tat Fluctuations Drive Phenotypic Diversity. Cell 122.2 (2005)

Strogatz, S H. Exploring Complex Networks. Nature 410.6825 (2001): 26876.

Milo, R et al. Network Motifs: Simple Building Blocks of Complex Networks. Science (New York, N.Y.) 298.5594 (2002): 8247. Web. 13 July 2012.

Archive - Papers from previous years' bootcamps:
2016 Cell Biology
Defining the rate-limiting processes of bacterial cytokinesis. Colthart et al., 2016. PNAS
Using Optogenetics to Interrogate the Dynamic Control of Signal Transmission by the Ras/Erk Module. Toettcher et al., 2013. Cell
The Biochemical Basis of an All-or-None Cell Fate Switch in Xenopus Oocytes. Machleder et al., 1998. Science

2016 Systems
Exploiting Natural Fluctuations to Identify Kinetic Mechanisms in Sparsely Characterized Systems. Hilfinger et al., 2016. Cell Systems.
Dynamics of epigenetic regulation at the single-cell level. Bintu et al., 2016. Science.
A Genome-wide CRISPR Screen in Primary Immune Cells to Dissect Regulatory Networks. Parnas et al., 2015. Cell.

2014 Systems
Alex K. Shalek Rahul Satija Joe Shuga John J. Trombetta Dave Gennert Diana Lu Peilin Chen Rona S. Gertner Jellert T. Gaublomme Nir Yosef Schraga Schwartz Brian Fowler Suzanne Weaver Jing Wang Xiaohui Wang Ruihua Ding Raktima Raychowdhury Nir Friedman Nir Hacohen Hongkun Park Andrew P. May & Aviv Regev. Single-cell RNA-seq reveals dynamic paracrine control of cellular variation. Nature aop, (2014) | doi:10.1038/nature13437. 

Toettcher JE, Weiner OD, Lim WA. Using optogenetics to interrogate the dynamic control of signal transmission by the Ras/Erk module. Cell. 2013 Dec
5;155(6):1422-34. doi: 10.1016/j.cell.2013.11.004. Figures 4-end

2014 Cell Biology
Toettcher JE, Weiner OD, Lim WA. Using optogenetics to interrogate the dynamic control of signal transmission by the Ras/Erk module. Cell. 2013 Dec
5;155(6):1422-34. doi: 10.1016/j.cell.2013.11.004. Figures 1-3

2013 Systems
An endogenous accelerator for viral gene expression confers a fitness advantage. Teng et al. Cell 2012. 
Designing synthetic regulatory networks capable of self-organizing cell polarization. Chau et al. Cell. 2012. See discussion question file below.

2013 Cell Biology:
Deformations Within Moving Kinetochores Reveal Different Sites of Active and Passive Force Generation. Dumont et al, 2012. PNAS.

A pH-Regulated Quality Control Cycle for Surveillance of Secretory Protein Assembly. Vavassori et al, 2013. Cell.
2012 Systems

“A Biological Solution to a Fundamental Distributed Computing Problem” Nature (2011).

“Cis-interactions between Notch and Delta generate mutually-exclusive signaling states” Nature (2010).

“Bacterial Virulence Proteins as Tools to Rewire Kinase Pathways in Yeast and Immune Cells. Nature (2012).

“Interpreting Cancer Genomes Using Systematic Host Network Perturbations by Tumour Virus Proteins. Nature (2012).

2012 Cell Biology:
Membrane Tension Maintains Cell Polarity by Confining Signals to the Leading Edge during Neutrophil Migration. Houk et al, 2012. Cell