Weissman, Jonathan

Some of your research relies on yeast to study amyloid fibers, a protein thought to play a major, possibly causative, role in Alzheimer’s disease. How do you apply what you learn in yeast to the human brain? What have you learned?

We have focused on understanding universal features of prion inheritance that arise from physical properties of amyloid aggregates, and the proteins (such as molecular chaperones) that act on these aggregates. One key finding has been that there is a remarkable degeneracy in protein misfolding, with the same protein being capable of misfolding into multiple self-propagating conformations. Moreover, the specific misfolded conformation can dramatically influence the physiological impact of an aggregate. We also showed that prion conformations that are more fragile actually have a bigger impact on a cell, as they tend to divide and grow exponentially at a faster rate than more stable misfolded forms. This then suggests a strategy for minimizing the toxic effects of a misfolded protein by driving it to more stable conformations.

Your group published a paper last year on ribosome profiling, a technique for monitoring protein translation in vivo. We already know how to monitor mRNA abundance to determine gene expression. Wasn’t that enough for you?
I think the real question now is why would you want to measure mRNA levels when you can directly measure the rate of protein synthesis? Genes act through the proteins they encode, and mRNA levels are often a highly imperfect proxy for the rate of protein production due to extensive use of translational control.

More broadly, we are working in a time when incredibly powerful tools are developing at an increasingly rapid rate. One of the lessons that we see from the $1,000 genome challenge is that the clear enunciation of a well-defined technical goal has the power to focus and motivate extraordinarily imaginative engineering approaches. Thus, a collective goal for biologists is to think clearly about what new types of data and approaches have the potential to be most transformative and exploit the power of technology, not only to do what we already know how to do faster, but to more fundamentally rethink the strategies we use to attack biological problems.

You are coauthor of a Nature paper titled “Molecular basis of infrared detection by snakes.” How did you get involved with snake work?
This arose from a casual conversation I had in the hall with my UCSF colleague David Julius. During that chat it became clear that the expertise that a post doctoral fellow in my lab, Nick Ingolia, had developed in his ribosome profiling work on the analysis of gene expression using deep sequencing, was ideally suited to look in unbiased way for candidate receptors [in snakes]. Nick and a post doctoral fellow in David's group, Elena Gracheva, made a terrific team and were able to find the receptor in a few months’ effort. An important lesson here is the value of taking the time to have a casual free ranging conversation with your colleagues.

What is your lab working on these days?
My research program continues to be divided into three main areas. Two focus on well-defined biological problems: the consequences and causes of protein misfolding, particularly as they relate to prion-based inheritance, and the mechanisms by which cells ensure the integrity of their proteomes, especially in the context of protein folding—and more recently lipid homeostasis—in the endoplasmic reticulum. The third area of interest seeks to develop novel strategies for systematically exploring biological processes.

Where do you see your field in 10 years?
In the next decade and beyond, cell biology will see an acceleration of the trend toward complementing process-centered approaches (in which one focuses on identifying and characterizing the key players that carry out a specific cellular job) with a component-centered view aiming to define systematically the functional roles of a given biological molecule (e.g. a protein or a specific lipid species). This move will be enabled by increasingly sophisticated functional genomic efforts that provide high-resolution and precise information on the location, levels and biological impact of given components. We have already seen the value of these sorts of systematic approaches in yielding not only more data but also qualitatively better information in areas such as genome sequencing, expression analysis, lipidomics and now protein-protein interactions.

Increasingly, these systematic efforts will move towards the comprehensive exploration of more sophisticated cellular phenotypes in which functional genomics will become the driving creative force behind discoveries. This will not only speed up the rate of discovery but also help move biology towards more principled, less ad hoc approaches for defining gene functions. Indeed the type of arguments that we now commonly use to “prove” that we know what a protein’s biological role is may seem rather quaint and descriptive to the next generation of biologists.
The good news for the biology community is that rather than replacing us with automatons, this flood of information will allow those with an intimate knowledge of cell biology to leverage their knowledge.

If you had to change careers today and you could do anything, what would you do?
Bono has a great job but I am sadly not qualified.

What’s your favorite science book?
P.B. Medawar's Advice to a Young Scientist. I read it at a time I was going from the passive learning environment of a classroom to actually doing my own research. Medawar's book was the exact opposite of a text book: he personalized the process of discovery rather than focusing on presenting the polished end product. I have always been as interested in the process as the answers. If we continue to teach science as a set of facts then to most of the public it will seem no different than fundamentalist religion, only perhaps with less appealing answers. Religion, of course, has its place in teaching us about values—but what distinguishes science from mysticism is the process.

What is something about you that most people don't know?
Going straight to graduate school was a bit of a “Plan B” for me. My original plan was to take a year off, get a job on Wall Street or the like, save money for six months, and travel around the world on the proceeds for the next six months. However, I was a senior in college in '87/’88, the year that the Dow dropped 25% in one day, which kind of put a dent in the plan.