2010: That was the year that was
December 30, 2010 § 3 Comments
Many blogs seem to end the year by reflecting on the past 12 months: which were the best posts, what were the dominant themes? I thought I might give “what were the dominant themes” a try; I know I’ve been pretty scattered, but surely there are some common threads.
Before I try to do that, in the spirit of reflection, a little background. I started writing this blog as a way of sharing some of the interests of the Department I work in, the Department of Systems Biology at Harvard Medical School. The Department has 19 faculty housed in 6 institutions (Harvard Medical School, Massachusetts General Hospital, Beth Israel Deaconess, the Wyss Institute, Brigham and Women’s Hospital and the Broad Institute) who between them have a very wide range of interests. Some of the posts I write are suggested to me by the faculty; some of them arise because I independently spot a paper that I think is related to an interest in one of our labs; some of them are simply about topics I think are interesting or amusing. I also like to keep an eye on what the Department’s growing band of alumni are up to. All of it, alas (except for the guest posts) is filtered through my own imperfect understanding. [Don’t blame any of the faculty for anything stupid I happen to say.]
So, a bit about what shapes my interests and understanding. I was originally trained as an immunologist with a biochemical slant, but quickly moved out of bench science and into scientific publishing. I’ve worked for Nature (before the clone expansion), Current Biology and Chemistry & Biology, and I also spent a few years at Genentech helping to run a development project aimed at producing an anti-HIV drug (luckily, the efforts of others were more successful). I came to Harvard to work at the Institute of Chemistry and Cell Biology, which aimed to expand the use of chemical tools in biological research; after some changes, this lives on as ICCB-Longwood, run by Caroline Shamu. And I joined the Department of Systems Biology when it was founded in 2003, as the department administrator.
Despite my straight-up biology background, I like mathematics (and mathematicians), perhaps as a result of early habituation: I did my undergraduate degree at Trinity College in the University of Cambridge, which has a long-standing reputation as one of the best places for mathematics in the UK (Newton went there). Trinity also has a reputation for roof-climbing, or night-climbing as it’s also known. I first encountered Trinity’s mathematicians in my first week at college, when several members of the so-called Cambridge University Breaking and Entering Society (CUBES) struck up a conversation with me from a roof opposite my window.
At this point I think of myself as a scientific generalist, knowing a little (sometimes very little) about a lot of topics. Which may be a good type of background for writing a blog, or anyway this blog, because a blog about systems biology has to cover a lot of ground. Systems biology, the study of systems-level properties of biology, is not a subsection of biology, but a new way of looking at (many) biological problems. The components of the system can be molecules, cells, individuals or even whole species. As a consequence of this breadth, people often feel that systems biology is poorly defined; not only are the biological questions drawn from all over the place, but the answers that are offered are wildly divergent in form. What biological systems do have in common, almost by definition, is that they’re complex: so studying them requires a focus on quantitative measurement, and often interpreting the data requires some form of computational or mathematical model. The field is already developing sub-fields — systems cell biology, systems immunology, systems medicine…
But I digress. What did I write about in the last 7 months?
Most prominent theme: cellular circuitry and how cells make decisions. This is not a surprise, as it’s an interest of several of the faculty in the Department. Examples:
A tale of two circuits (fold-change detection in Wnt and EGF signaling)
Playing dead: how bacteria persist in the face of antibiotics (stochastic growth control in bacteria)
Out of randomness, order (pattern formation using Notch-Delta)
The double-edged sword of Damocles (control of apoptosis)
Specifying sex in plants: the Q factor (a single amino acid insertion changes the function of a transcription factor)
Friday Feature: Variable death (decision-making in apoptosis)
Controls are cool (excitable p53 pulses in unstressed cells)
Superoxides eat your brain (control of autophagy and its misregulation in Alzheimer’s disease)
Eve and the tree of knowledge (how do transcriptional outputs depend on the location and nature of transcription factor binding sites?)
It’s all about energy (ATP as a controller of global transcription levels).
I’ve also written fairly often on evolution, the ultimate systems problem:
Reconciling robustness with evolvability (to evolve, you need to survive mutations, i.e. be robust to mutation; how, then do you change?)
Evolving regulation (exploring species-species differences in the phosphoproteome)
Trade balances in microbial communities (how do microbial communities evolve?)
To help or not to help? (what is the role of promiscuity in determining whether birds show cooperative behavior in raising their young?)
Feed me, Seymour (competition between carnivorous plants and spiders)
Efforts to use mathematics to understand biological phenomena also showed up pretty often:
The geometry of evolution (insights into the evolution of Darwin’s finches from studying beak geometry)
Friday Feature: A natural curve (why does metabolic rate scale with size? Or does it?)
More models, better biochemistry (a plea for biologists to look beyond the Michaelis-Menten equation in analyzing biochemical pathways)
Using models to link different varieties of data (how can we connect population measurements to microscopic measurements?)
Redefining optimal (the problem of over-fitting models)
The mathematics of marriage, or, less happily ever after (a discussion of an attempt to describe the course of marriage mathematically; an embarrassingly popular post).
I touched on synthetic biology reasonably often, but really the field deserves its own blog (and has at least one very good one). Synthetic biology could be viewed as the complement to systems biology (if I understand it, can I build it?) but using the tools of biology to build useful things is an interesting area in itself. Sample posts:
Synthetic tools for controlling protein expression (self-explanatory)
Synthetic probes of natural oscillations (redesigning the p53 circuit to probe its interesting dynamical behavior)
Synthetic serendipity (an attempt to create oscillations in bacterial populations that worked for the wrong reasons).
Bacterial electricity (importing an electron transfer chain that transfers electrons to metal into E. coli).
A few specific areas of biology popped up repeatedly: microRNAs, photosynthesis, blood and coagulation, HIV, antibiotic resistance, and the cytoskeleton. Some of these are interests in the Department, others (microRNAs and HIV) interests of mine.
More microRNA mysteries (why are some mRNAs harder to down-regulate than others?)
How do miRNAs affect protein production? (there has been a long-running controversy about whether miRNAs destabilize their target mRNA or reduce its translation. Recent evidence suggests that destabilization is the dominant effect).
Building better biology (Ron Milo, a Department alumnus, is working on improving the process of photosynthesis).
Friday Feature: Carboxysome spacing (carboxysomes, the organelle responsible for carbon fixation in cyanobacteria, turn out to be regularly spaced along the axis of the cell)
The mysteries of blood (a model of red blood cell population dynamics that helps diagnose anemia)
To clot or not: the trigger for coagulation (reductive modeling to help identify the biological roles of different parts of the coagulation cascade)
Physical modeling of clot formation (multi-scale modeling of clot formation, including an examination of the role of shear forces from the flowing blood)
(these posts offer two different, not mutually exclusive, takes on why certain individuals don’t progress to AIDS after infection with HIV)
Looking at a scary future (antibiotic resistance genes are highly prevalent in the wild and can spread to clinical isolates)
Playing dead: how bacteria persist in the face of antibiotics (as noted in “cellular circuits”, this is about stochastic growth control in bacteria; rapidly growing cells typically die in response to (many) antibiotics, while cells that are not growing survive.)
How long is a cell, and why? (Do microtubule dynamics limit the natural length of some cells?)
Excitable motility (how do neutrophils follow gradients?)
Dancing filopodia (a wild bit of biochemical reconstitution)
That covers the majority of the posts you’ll find under the Actual Science category; now that I have them lined up like this and compare them to interests in the Department, I can see some major gaps. I’ll see what I can do about those next year. Suggestions welcome: becky [at] hms.harvard.edu.
Thanks for reading!