You can’t eat a scientific experiment

I discovered baking recently. It began with Journal Club. At UCL we didn’t have a group big enough to warrant organised lab meetings, let alone Journal Club, but I recently carried out some research at the University of Bristol, and with a few groups with common interests combined, there was enough people to each present a paper once a week for a whole term. Also new to me was the concept that the person doing the presenting brought cake. Journal Club was scheduled for 9.15 am, a time unknown to academics I had worked with at UCL, but there was cake! The split of presenters buying vs making cakes was approximately 50:50 and, never one to shy away from a creative challenge, I began planning my cake when my turn for Journal Club appeared on the horizon.

One morning in the cell culture room I was avidly talking about the cake I planned to make, and a woman confided in me that you can always tell the quality of a Journal Club by the quality of the cake: if the cake’s good, it’s to make up for a poor paper. Alternatively, as in my case, the cake was good because I’d put more effort into planning it than I had preparing my Powerpoint slides (a lemon drizzle cake recipe by Hugh F-W, modified to include blueberries and poppy seeds, courtesy of my brother-in-law) – don’t get me wrong, the paper was good, but the cake was really good. The cake, or perhaps a combination of the cake and the paper, secured me a sought-after job interview, but that’s another story.

Kitchen drawing (2008). Pencil on paper

I came to cooking itself (in life) relatively late. A neurotic mother who seemed to permanently occupy the kitchen, and scream and slam the door when anyone came near, will do that to a kid. On rare occasions I might be allowed to chop carrots, or peel potatoes, but invariably I was told I was too slow and would be sent away to lay the table. Consequently, my own experiences in cooking for other people frequently ended in tears, with my husband having to peel me off of the floor and salvage something edible from what I had started.

A few years ago, my husband began to spend one, and then two, evenings a week at the local indoor climbing wall, rock climbing. For the first few weeks I would starve myself, or perhaps try to survive on various things-on-toast (as I must have done for 3 yrs at Art School), waiting for him to come home. I even followed him climbing for a few months, until my PhD became so intense that I could barely make it out of the lab in time. Eventually I realised that the next best thing I could do would be to treat cooking like a scientific experiment: lots of planning in advance, stringently follow recipes until I was clear in my mind what each component did and its limits in terms of concentration, conditions for cooking (temperature, time, distance from heat source), and so on. I ensured that I’d had something small to eat before I begun so I wouldn’t get too flaky, and allowed myself as much time as possible to complete cooking the meal. When I carry out an experiment for the first time I like to deduce where the exit points are, as it were, at what point can I pause or freeze the whole experiment and go home, go to the toilet, have coffee, etc, and I found one mechanism for coping with cooking was to treat a recipe the same way. As with my scientific experiments, a lot came from experience, how much pasta is too much, how much chopping can you actually get done whilst sauteing an onion, and so on.

Having learnt cooking backwards, as it were, there are some parts of recipes I find utterly baffling. At the weekend I made a carrot cake and some shortbread, and was met by the following lines at the beginning of, and part-way down, the recipes: “Grease a 23 cm springform cake tin …” and “Line a 15 cm cake or tart tin with baking parchment.” For a while I pondered a single dimension of cake. Could they mean the longest tin measurement? The depth of the tin? The diameter of a round tin? The diagonal measurement across the top of a square or rectangle tin, like for a TV? Perhaps people miss off the ^2 or ^3 for cm-squared or cubed? In the end I looked up the meaning of ‘springform cake tin’, and after finding it to be a tin with a removable base, I used the only one of those I have. Incidentally the one I have has a diameter of 20 cm and a height of 9 cm, which seemed to work just fine – if this was a scientific experiment, that would be the kind of error that would cause my experiment to fail and have me tearing my hair out for weeks, with no clear logic. For the shortbread I used a flat baking tray, 23.5 x 33.5 cm. This was less successful because the shortbread burnt. Alternatively it may have burnt because I left it in the oven too long. I will need to collect some more n numbers before I can come to a firm conclusion on that one.

Systems Biology and Signal Transduction

I’ve spent much of this week at the University of Nottingham, meeting other scientists and learning about Mathematical Modelling. I feel like I asked, “So what do you do and where do you come from?” a hundred times.

My biological research is concerned with intracellular signal transduction. Also termed cell signalling, this process describes the way that a single cell receives a signal from the extracellular space, perhaps in the form of a hormone or growth factor, and communicates it to the cell nucleus to effect a change in gene transcription, or other appropriate response. Traditionally cell signalling has been investigated using molecular biology to investigate protein amino acid sequence and structure (gene over-expression, silencing and mutagenesis), and using biochemistry to look at protein-protein interactions and enzyme or protein function. Cell biology then contextualises this information, using microscopy to determine the localisation of the protein of interest within a particular cell type. Over many many man hours and large sums of money, this knowledge on individual protein signalling modules can be built up into larger signalling networks. Eventually clues as to the molecular basis of diseases are unravelled, potential drug targets may be identified and the pharmaceutical industry begins to get excited.

Signalling pathways from cell surface receptors mediating platelet aggregation and blood clot formation.

In a time in which science funding is scarce (to put it mildly), this activity of painstakingly characterising a single protein and its immediate contacts can seem incredibly futile. For the last three years I’ve been working on a previously uncharacterised lipid transfer protein. After all the late nights and weekends in the lab, I can tell you which phospholipids it likes to bind and two proteins it interacts with. I have little clue as to what the protein actually does or what the interactions mean. Despite this, my progress in three years is considered to be good.

Alongside researchers like myself, toiling away on the mysteries of a single gene, others have used high throughput approaches to produce large datasets on particular aspects of a cell or tissue. A good example is a database of phosphorylations, post-translational protein modifications used to regulate protein function. Such databases can tell you exactly which residue of a protein is modified under particular conditions. It won’t tell you who’s doing the modifying or what activity it’s regulating, but it can tell you which residue to mutate to look at regulation of your single protein.

Enter the mathematician: mathematicians and computer scientists are increasingly finding a place for themselves in the world of biological research as bioinformaticians, mathematical biologists and systems biologists. I place these three terms in order of willingness to dirty their hands with actual biological experiments, with bioinformaticians being the least likely, and systems biologists much more likely to be an experimental biologist learning or collaborating closely with researchers doing mathematics. Earlier this year I attended a Systems Biology conference and encountered a group of Bioinformaticians I have worked with in the past, now re-branding themselves as Systems Biologists and moaning about how long experiments to confirm protein-protein interaction predictions were taking.

But this is good. Finally the field is realising the need to present a united front and use mathematics to begin to combine all the seemingly disparate pieces of information. Which brings me back to my week in Nottingham. I have attended many Systems Biology talks over the last few years and I have to be honest in saying that only one or maybe two have left me feeling excited about what the field can offer. Most usually have been talks by mathematicians who don’t appear to quite understand the signalling pathway they are working on, and are all too quick to show how pretty their differential equations are, quickly excluding the maths-shy biologists in the audience. At the Biochemical Society Signalling conference in Edinburgh in June this year, I finally heard a scientist say (paraphrased), “Using our experimental data as a starting point, we used mathematical modelling to bring together spatial and temporal data, which led us to discover two different pools of signalling molecules.” Finally someone has used maths to tell them something they didn’t already know.

So this is why I went to Nottingham, to a course entitled, ‘Mathematical Modelling for Biologists’. It’s going to take a while for my brain cells to recover from the assault, and even more time to process and fully understand what I have learnt. So I’ll have to let you know how I get on.