PUBS 2018

Biophysics 205A: Physical Underpinnings of Biological Systems

Fall 2018 Syllabus


Location: Genentech Hall Teaching Lab - Room 227

Course Days/Hours: Monday, Tuesday, Wednesday 1pm-5pm

Final presentations: November 5, 1 pm

Instructor: Martin Kampmann

PUBS fellow / Course Coordinator: Robert Newberry

Co-Instructors: Sy Redding

TAs: Jean Costello, George Hartoularos, Snow Naing, Maureen Pittman, Nish Reddy

Lecturers/Facilitators: Martin Kampmann, Jason Gestwicki, Hiten Madhani, Charles Joseph, Eric Chow, DeLaine Larson, Sy Redding, Stephen Floor, Bill DeGrado, Tanja Kortemme, Lisa McConlogue


  • Last, but not yeast (TA: Jean): Bryan, Laura, Calla, Jack
  • LAMMDA (TA: Snow): Laurel, Matt, Aji, Maru
  • The Degenerates (TA: George): Daniel, Elissa, Wren, Christina
  • Synucleus (TA: Nish): Elizabeth, Hayarpi, Garrett
  • Sleeping Giants (TA: Maureen): Miriam, Nick, Stephanie


Course Credit: 4 units

Course Format: 12 hours of lab per week

Prerequisites: All incoming first year iPQB graduate students are required to enroll in this course.

Although TAs, instructors, and your fellow students will be happy to help out, it is important to be familiar with basic scripting and the principles of python PRIOR to starting the class. This will be covered in bootcamp.

Grading: Letter grade

Textbook: None. Lab protocols and course materials will be available in class or online


Current initiatives in biomedical research seek detailed understanding of the complex molecular basis for both normal physiology and disease pathology with the aim of developing targeted therapies uniquely suited to individual patients. This effort toward “precision medicine” involves a variety of discovery- and hypothesis-driven studies of the molecular, cellular, genetic, systems, and environmental contributions to biology and disease. Comprehensive, unbiased explorations of the cell and its components are key to this effort, as they illuminate the specific lesions underlying disease processes. Targeted interventions in cancer represent the greatest success story of precision medicine to date; many patients can be screened for disease-driving mutations that can be treated with specific molecules. Nevertheless, much remains to be unraveled about the physical, chemical, and biological basis for many diseases, particular those affecting the brain. Moreover, it has become clear that genetic factors are incomplete for describing many normal and aberrant processes, indicating an important contribution from environmental factors, whether they derive from the particular palette of components specific to different cell types, the unique tissue microenvironment, or agents encountered by the organism writ large.

An excellent example of this challenge concerns the protein α-synuclein. An abundant protein expressed predominantly in neurons, α-synuclein gained notoriety in 1997 when genetic and pathological studies implicated it in Parkinson’s disease, which affects at least 500,000 people in the United States alone. In Parkinson’s disease, α-synuclein misfolds and aggregates into toxic protein assemblies that can cause neuronal death. How α-synuclein contributes to neurodegeneration remains unclear and controversial, owing in part to an incomplete understanding of its biophysical properties and cellular interactions. Though mutations to α-synuclein can cause Parkinson’s disease, most Parkinson’s cases have little or no genetic basis. In addition, though expressed widely throughout the brain, α-synuclein pathology impacts only a small subset of neurons, indicating a strong contribution from cellular context. How this protein interacts with its cellular environment is therefore of significant interest for understanding the etiology of Parkinson’s disease.

In this course, we will examine how environmental factors affect α-synuclein misfolding and toxicity with the goal of clarifying how α-synuclein contributes to neurodegeneration.

Suggested Reading

Bendor, J. T.; Logan, T. P.; Edwards, R. H. The function of α-synuclein. Neuron 2013, 79, 1044–1066.

Downey, A., Think Python. Green Tea Press: Needham, MA, 2012.

Fowler, D. M.; Fields, S. Deep mutational scanning: a new style of protein science. Nat. Methods 2014, 11, 801–807.

Lashuel, H. A.; Overk, C. R.; Oueslati, A.; Masliah, E. The many faces of α-synuclein: from structure and toxicity to therapeutic target. Nat. Rev. Neurosci. 2013, 14, 38–48.

Sherman, F. Getting started with yeast. Methods Enzymol. 2002, 350, 3–41.

Course Description

The centerpiece of this course is an interdisciplinary research project that will be completed in teams. Students will perform the experiment, collect and analyze the data, and draw conclusions. Though extensive support will be provided by faculty and instructional staff, students will be encouraged to explore and execute their own ideas. The results thereby obtained will be integrated into a manuscript for peer-reviewed publication. Course content will be delivered through a combination of lectures from guest faculty, technique-focused talks from instructional staff, and literature reviews by students. Students will also present oral progress reports and give a final oral presentation of their findings for a wide audience.

Course Goals

The goal of the course is to provide an immersive, hands-on experience in the context of genuine research questions. As articulated by Vale and colleagues (, there are tremendous advantages when graduate students work "pursuing a research question with unknown answers and uncertain outcomes, students and faculty combine their wits and skills to design experiments, evaluate progress, and troubleshoot along the way". These advantages are likely to be common accross all learning levels ( In our course, teams may use whatever literature, software, and resources that are available publicly, and are encouraged to write their own scripts and software where necessary.

This course will introduce students to approaches and methodologies for interrogating biological systems in high throughput, which will require the integration of experiment and computation. In addition to fundamental techniques in modern molecular biology and bioinformatics, students will learn to interpret and leverage large datasets, draw original conclusions, and present findings in written and oral formats.

The "official" language of the class is python ( - beginners should try Learn Python The Hard Way (, people with a background in other languages should try Google's python course ( The QB3 Berkeley intensive python course ( provides many biological examples. Students should be comfortable with basic syntax and scripting prior to the start of instruction.

Spreadsheet with a listing of multiple Python resources:

Student Learning Objectives

  • Laboratory safety
  • Scientific documentation
  • Experimental design
  • Yeast manipulation
  • Molecular biology techniques
  • Library preparation
  • Deep sequencing
  • Bioinformatics
  • Computer programming
  • High-content microscopy
  • Image processing
  • Biophysical computation


Class Policies

Ethics: This course is more than a training experience; it is an active research project whose results will be published to the broader scientific community. The community must be able to understand our work, replicate it, and have confidence in its findings. We must therefore ensure the integrity of the information we disseminate. To do so, it is essential that students perform and document their experiments and analyses as faithfully as possible. Mistakes and oversights are normal and to be expected, but they must not be ignored, concealed, or disguised. In addition, to merit authorship, students must contribute to three aspects of the project: intellectual conception or interpretation of the methods or data, technical execution of the experiments and/or analyses, and documentation or dissemination of the results. We fully expect that by actively participating in the course and working toward the course objectives, all students will merit authorship.

Respect: This course is built around an open research project performed in teams. Successful completion of the course objectives will require that students work together effectively, so please respect the time and effort of your classmates and instructors. Moreover, as part of the research process, we will consider and debate a variety of ideas and approaches; however, we must not allow our position on a particular idea or argument to compromise our respect for its author. We therefore expect course participants to give all instructors and students, regardless of academic or personal background, their complete professional respect; anything less will not be tolerated.

Absences: The instructor must be notified by the second week of classes for any planned absences, or in advance of class due to illness. Active participation in the laboratory is essential and students are required to attend normal class hours. Occasional attendance outside of regular class hours will also be necessary, as indicated by the syllabus. Attendance during the final presentation is absolutely mandatory, except in cases of doctor-excused medical illness. Any class material or lecture that is missed will be the responsibility of the student. Unexcused absences may affect the final course grade. Written evaluations of each team and its members will be provided to the Graduate Tracking System for inclusion into the graduate record, and provided to oral committee members and thesis committee members.

Accommodations for students with disabilities: The Graduate Division embraces all students, including students with documented disabilities. UCSF is committed to providing all students equal access to all of its programs, services, and activities. Student Disability Services (SDS) is the campus office that works with students who have disabilities to determine and coordinate reasonable accommodations. Students who have, or think they may have, a disability are invited to contact SDS ([email protected]); or 415-476-6595) for a confidential discussion and to review the process for requesting accommodations in classroom and clinical settings. More information is available online at Accommodations are never retroactive; therefore students are encouraged to register with Student Disability Services ( as soon as they begin their programs. UCSF encourages students to engage in support seeking behavior via all of the resources available through Student Life, for consistent support and access to their programs.



Week 1 – Orientation, perturbation selection, growth optimization

Monday, September 17


by Martin Kampmann 



by Robert Newberry 


Labwork: Choose team names, select chemical perturbants, plan growth experiments

Group Presentation: Compound Choice



Tuesday, September 18

Computation: Set up cluster access

Server Basics, by Jean Costello:


Protocol Talk (Bryan): Growth Experiments

Tech Talk:

by Nish Reddy


Labwork: Preculture for growth experiment; prepare media

7:30pm: Induce expression


Wednesday, September 19

8:30am: Collect growth data


by Martin Kampmann


Labwork: Analyze growth data, repeat growth experiment 

Computation: aSynuclein Barcode Analysis [pickle dictionary, plasmid sequence (FASTA), plasmid sequence (SnapGene), plasmid map (PNG)]

7:30pm: Induce expression


Thursday, September 20

8:30am: Collect growth data


Week 2 – Library selection

Monday, September 24

Lecture: Proteostasis, by Jason Gestwicki

Journal Club (Laurel): Outeiro and Lindquist. Yeast Cells Provide Insight into Alpha-Synuclein Biology and Pathobiology. Science 2003, 302, 1772-1775.

Journal Club (Daniel): Hillenmeyer, et al. The Chemical Genomic Portrait of Yeast: Uncovering a Phenotype for All Genes. Science 2008, 320, 362-365.

1 minute presentations from each group on growth experiment results

Protocol Talk (Elizabeth): Selection experiments

Labwork: Prepare media for selection experiments

Computation: a-Synuclein barcode association

by Snow Naing


7:30pm: Induce expression, replicate 1


Tuesday, September 25

8:30am: Collect miniprep samples, replicate 1 timepoint 1

Lecture: Everything you wanted know about yeast, but were afraid to ask, by Hiten Madhani

Journal Club (Miriam): Olzscha, et al. Amyloid-like aggregates sequester numerous metastable proteins with essential cellular functions. Cell 2011, 144, 67-78.

Journal Club (Laura): Khurana, et al. Genome-Scale Networks Link Neurodegenerative Disease Genes to α-Synuclein through Specific Molecular Pathways. Cell Syst. 2017, 4, 157-170.

1 minute presentations from each group on barcode analysis

Labwork: Growth selection for replicate 1; Preculture for replicate 2

Computation: a-Synuclein barcode association

7:30pm: Collect miniprep sample, replicate 1 timepoint 2

7:30pm: Induce expression, replicate 2


Wednesday, September 26

8:30am: Collect miniprep sample, replicate 2 timepoint 1

Lecture: DNA Synthesis Technologies & Advances in Library Generation, by Charles Joseph

Journal Club (Matt): Starr, et al. Alternative evolutionary histories in the sequence space of an ancient protein. Nature 2017549, 409-413.

Journal Club (Hayarpi): Chong, et al. Yeast Proteome Dynamics from Single Cell Imaging and Automated Analysis. Cell 2015, 161, 1413-1424.

Labwork: Growth selection for replicate 2

Computation: a-Synuclein barcode association

7:30pm: Collect miniprep sample, replicate 2 timepoint 2


Week 3 – Microscopy, molecular biology

Monday, October 1

Lecture: Next-Generation Sequencing, by Eric Chow

Protocol Talk (Nick): Yeast miniprep

Labwork: DNA miniprep

Team presentations: a-Synuclein barcodes


Tuesday, October 2

8:30am: Induce expression


by DeLaine Larson


Protocol Talk (Calla): Microscopy

Protocol Talk (Aji): PCR Overview 

Protocol Talk (Wren): PCR Day 1, PCR Day 2

Labwork: PCR Day 1; imaging


Wednesday, October 3

Lecture: Image Analysis, by Sy Redding

Labwork: PCR Day 2, sample pooling and submission

Computation: Begin image analysis


Week 4 – Biophysical computation, sequence analysis

Monday, October 8

Journal Club (Garrett): Toth-Petroczy, et al. Structured States of Disordered Proteins from Genomic Sequences. Cell 2016, 167, 158-170.

Journal Club (Stephanie): Vavouri, et al. Intrinsic protein disorder and interaction promiscuity are widely associated with dosage sensitivity. Cell 2009138, 198-208.

Computation: Barcode counting


Tuesday, October 9

Lecture: Biological Phase Separation, by Stephen Floor

Journal Club (Jack): Galvagnion, et al. Lipid vesicles trigger α-synuclein aggregation by stimulating primary nucleation. Nat. Chem. Biol. 2015, 11, 229-234.

Journal Club (Maru): Dettmer, et al. Loss of native α-synuclein multimerization by strategically mutating its amphipathic helix causes abnormal vesicle interactions in neuronal cells. Hum. Mol. Genet. 2017, 26, 3466-3481.

Tech Talk:

by Maureen Pittman

Multiple Hypotheses Resource

Computation: Microscopy analysis, Fitness calculations


Wednesday, October 10

Lecture: Structural Biology of Amyloids, by Bill DeGrado

Followed by: Group presentations on progress update and next steps

Regrouping into focused subgroups


Week 5 – Subgroups

Monday, October 15

Lecture: Protein Biophysics, by Tanja Kortemme

Journal Club (Christina): Guerrero-Ferreira, et al. Cryo-EM structure of alpha-synuclein fibrils. eLife 2018, 7, e36402.

Journal Club (Elissa): Bousset, et al. Structural and functional characterization of two alpha-synuclein strains. Nat. Commun. 2013, 4, 2575.

Work in subgroups


Tuesday, October 16

Work in subgroups


Wednesday, October 17

Lecture:  Alpha-Synuclein Therapeutics: Navigating the Energy Landscape, by Lisa McConlogue

Work in subgroups

3 pm: Subgroup presentations


Week 6 – Data analysis, presentation preparation

Monday, October 29

Robert: Presentation of background slides that will be shown before the presentations next week

Work in teams on presentations

Practice presentations around 3:30 pm (faculty will visit each team for this)


Tuesday, October 30

Work in teams on finalizing presentations


Wednesday, October 31

Work in teams on finalizing presentations

Practice presentations starting at 3 pm (each group: 10 min presentation, 10 min discussion)


Final Presentations

Monday, November 5, 3 pm