Ockham’s Broom

The Journal of Biology has begun an interesting thematic series entitled “Ockham’s Broom“[1], which they describe thusly:

Ockham’s broom is an implement conceived by Sydney Brenner as the device whereby inconvenient facts are swept under the carpet. This is common practice in biological research where the facts often cannot be explained all at once; but in due course the edge of the carpet must be lifted and the untidy reality confronted. In this eclectic series, contributors examine the sweepings from their fields and offer a fresh perspective on generally accepted views. (Ockham’s broom should not be confused with the more familiar Ockham’s razor which inspired this less philosophically correct concept.)

Lifting the edge of the carpet and confronting the untidy reality was something which Rosen continually pursued. As he wrote in his Autobiographical Reminiscences[2]:

Quite early in my professional life, a colleague said to me in exasperation, “The trouble with you, Rosen, is that you keep trying to answer questions nobody wants to ask.” This is doubtless true. But I have no option in this; and in any event, the questions themselves are real, and will not go away by virtue of not being addressed.


The first article in the Ockham’s Broom series, “Molecular machines or pleiomorphic ensembles: signaling complexes revisited“[3] is almost certainly one Rosen would have appreciated. The article begins:

A cell must constantly monitor cues from its environment and adjust its activities accordingly. Faithful and reliable signal transduction is not only essential for normal life, but its malfunctioning underlies many human health problems. Enormous strides have been made in the past several decades toward understanding how this process works at the molecular level. It is notable that when describing the fruits of that work, those of us who work on cell signaling would be hard-pressed to avoid terms such as ‘machinery’ and ‘mechanism’. The analogy between cell signaling and man-made machines is all-pervasive, frequently adopting the imagery of elaborate clockwork mechanisms or electronic circuit boards. This perception is undoubtedly shaped by what we know: the machines that we use in our everyday life and the ways that we describe such machines in diagrams or in words. But is this really an accurate, or useful, description of the actual processes used by cells? We will argue that signaling complexes typically consist of pleiomorphic and highly dynamic molecular ensembles that are challenging to study and to describe accurately. Conventional mechanical descriptions not only misrepresent this reality, they can be actively counterproductive by misdirecting us from investigating critical issues.

The authors go on to explain how the systems involved have enormous number of potential states and so the systems themselves may have a range of behaviors far exceeding the behavior of machine-like models of those systems. In Rosennean terms, the physical systems are open to many interactions and degrees of freedom to which the machine-like models are closed.

Facing this situation, either one somehow has to demonstrate that the behaviors not captured by these models can be ignored as being “noise” or unimportant variations, or one has to widen the classes of models used in order to more fully capture the behavior of the systems being modeled. It does not suffice for this untidy situation to be ignored, to be “swept under the carpet”. As Rosen said, “the questions themselves are real, and will not go away by virtue of not being addressed”. The authors conclude:

The pleiomorphic, heterogeneous, non-stoichiometric nature of signaling complexes provides a serious conceptual challenge for biologists, who are naturally more comfortable thinking of mechanical devices with states that are clearly defined and limited in number. But the current practice of avoiding these properties because they are difficult to study and to describe is likely to be a mistake. Only by confronting this issue head-on will be able to assess, once and for all, its real impact on signal transduction.



[1] Editorial: Robertson, M. 2009. Journal of Biology. 8(9):79. DOI:10.1186/jbiol187 Series: http://jbiol.com/series/ockhams_broom

[2] Rosen, R. 2006. “Autobiographical Reminiscences of Robert Rosen”. Axiomathes 16(1-2):1-23. DOI:10.1007/s10516-006-0001-6

[3] Mayer, B., Blinov, M., Loew, L. 2009. “Molecular machines or pleiomorphic ensembles: signaling complexes revisited”. Journal of Biology. 8(9):81. DOI:10.1186/jbiol185

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