W3150 / W4150 - Fall 2002
The Cell as a Machine: Cell Biophysics and Biosystems Engineering

Dr. Michael Sheetz

TA: Volodymyr Nikolenko

Cells are complex micron-sized machines that may best be understood through reverse systems engineering, i.e. through an understanding of the details of cellular functions and how they were optimized. To understand the functions, we will review basic solution physical chemistry, mechanics, and diffusion theory.

The reference books are "Molecular Biology of the Cell" by Alberts et al., (3rd Edition) and "Biomechanics" by Y.C. Fung (1981)

The assignments for undergrads will primarily involve the solution of practical cellular problems using equations given in class. Graduate students will read and critique original papers in addition to solving the problems.

Prerequisites: calculus and physics

Co-requisites: cell biology or biochemistry (Of course, these can also be taken in a prior semester)

Outline of Course
This is a general survey of a variety of cell functions, which emphasizes a problem-based approach to understanding the functions. Because cell functions are based upon a wide range of physical principles, the physical principles will only be introduced and references are provided in case you wish to delve further in any area. Many of the principles are discussed in Molecular Biology of the Cell (Alberts et al.) and in other Biophysics (e.g. Random Walks in Biology, Berg) and Physical Chemistry (Atkins) texts. Problems are meant to facilitate a quantitative understanding of cellular functions and lower the energy barrier to future back-of-the-envelope calculations that can determine if something is physically possible or worthless tripe.

Take-Home Lessons
Cells are nanomachines that have an intermediate number of components and typically work in a Low Reynold’s number size regime. Thus, most cell functions are based upon stochastic processes that vary from cell to cell and over time. It is perhaps surprising that cells function properly under a wide variety of conditions and exhibit a “robustness” of function that belies highly developed feedback control systems. In other words, how can a machine that shows stochastic variability be programmed to reliably execute complex inter-related functions under widely varied environmental conditions? For a variety of cell functions, we will explore by quantitative analyses the magnitude of the tasks that trillions upon trillions of cells routinely perform. For example, human cells can faithfully replicate two meters of linear DNA in an hour within the confines of a five micrometer nucleus and then sort and delivery equal copies of DNA to two daughter cells.

Grading will be on a curve with a median grade of a B. Half of points for the grade will come from the problems that are at the end of each lecture. Answers are to be submitted electronically within one week of the lecture, i.e. e-mail time stamped before the time of the lecture one week later. Collaboration on problems is allowed but one should understand how to solve the problems because the in-class tests will be based upon the take-home problems. The two in-class tests (mid-term and final) will be weighted differently (20% and 30% of the grade respectively) and notes from the lectures will be allowed.

Office Hours
Thursday afternoons beginning at 3 PM, I will meet with people to discuss any questions that were submitted by e-mail (first priority) and raised at the time (second priority). E-mail questions to the TA can be submitted at any time and will be answered within the week.

There is no one textbook for the course but Molecular Biology of the Cell (Alberts et al. 4th edition) is recommended as a resource for the Cell Biology and Physical Chemistry (Peter Atkins) is recommended for the Physical Chemistry.

Outline of Lectures (tentative)

1. Introduction
overview and outline: Lecture 1

2. How Nano-BioMachines Work (diffusion and transport) (Lectures 2 & 3)
overview and outline: Lecture 2 | Lecture 3

3. DNA Packaging and Replication (Lectures 4, 5 and 6)
overview and outline: Lecture 4 | Lecture 5 | Lecture 6

4. RNA Transcription and Processing (Lectures 7 and 8)
overview and outline: Lecture 7 | Lecture 8

5. Lipid Bilayer and Plasma membrane (hydrophobic effect, Guoy-Chapman potential, mechanics, and diffusion in 2-D) (Lectures 9, 10, and 11)
 overview and outline: Lecture 9 | Lecture10 | Lecture 11

6. Midterm (note that the course organization is different from last year)
solution set

7. Protein synthesis and processing (polymerases, processing (hybridization), ribosomes, and translocation) (Lectures 12, and 13)
overview and outline: Lecture 12 | Lecture 13

8. Cytoskeleton, which defines a non-spherical shape and mechanical properties (polymer assembly, mechanics) (Lectures 14, 15, 16 and 17)
overview and outline: Lecture 14 | Lecture 15 | Lecture 16 & 17

9. Glycoprotein and Secreted Protein Processing (Membrane transport, flow, and stabilization) (Lectures 18, and 19)
overview and outline: Lecture 18 | Lecture 19

10. Endocytosis and Protein Degradation (Lecture 20)
overview and outline: Lecture 20

11. Ion balance and volume regulation (membrane potential, osmotic pressure, and resealing) (Lecture 21)
overview and outline:

12. Signal Integration (Biosystems Engineering) (Lecture 22)
overview and outline:

13. Migration, Force generation and Chemotaxis (Lectures 23, 24 and 25)
overview and outline: Lecture 23 |
PowerPoint files :: Neural Crest | Lecture 25 (Force)

14. Final Exam (Will contain problems from whole course with emphasis on last half)

Lectures 1-7  |  Lectures 8-14  |  Lectures 15-23  |  Midterm