Genomics and Society Today’s Answers Tomorrow’s Questions · From molecules to systems / mechanisms Structures are illuminating because they give insight into the mechanisms associated

Genomics and SocietyToday’s AnswersTomorrow’s Questions25-26 October 2007

www.genomicsnetwork.ac.uk

Cellular Biological Systems:

Structure Meets Emergence

Alexander Powell, Egenis, University of Exeter


Overview

I. From molecules to systems

- molecules & mechanisms

- systems perspectives & emergence

- synthetic biology

II. Disciplinary identity and discipline names

- case study: bioinformatics

- a mirror of nature?


Where I’m coming from

My principal interest: scientific explanation (in molecular / cellular biology,

and more generally)

This is about the relationship between the mind and the world

- what’s the connection between our capacities to know and the way

the world is?

- central topic: causation

It connects with debates about disciplines and their relations


From molecules to systems / standard picture

One view of the past 50 years:

Molecular Biology Systems Biology

Positivist philosophy

of science

Anti-reductionist

philosophy of science

REDUCTIONISM EMERGENTISM


From molecules to systems / molecular biology

A common view about molecular biology (MB):

- MB was/is reductionist

- reductionism is bad

- MB has failed

BUT

What is meant by reductionism? (Various possibilities)

Surely MB has delivered an outstandingly rich base of knowledge?


From molecules to systems / molecular biology

Think instead about the nature of MB’s many explanatory successes

What they show is that sometimes the fundamental biological processes

that play out in the cell (or at higher levels) can be accounted for in

terms of the details of molecular structure


From molecules to systems / mechanisms

Structures are illuminating because they give insight into the mechanisms

associated with the performance of particular functions

Molecular mechanisms are analogous to macroscopic mechanical devices:

- they involve relatively stable, constrained configurations of ‘parts’

- there are far fewer degrees of freedom than in the same amount of

gaseous matter

- this means we can mentally simulate their operation (causal tracking)


From molecules to systems / fluidity & interactions

But alas cells are in important respects unlike mechanical devices: fluidity

is intrinsic to their working

Cellular causal fluxes are underpinned by the specificity of molecular

interactions, in place of the more-or-less fixed spatial relationships

between the parts in solid-state mechanisms

This is a very different mode of operation, one that allows for much greater

complexity

- processes can become co-adapted and intertwined

- functions need not map neatly to discrete, localized, stable structures


From molecules to systems / causal complexity

Signalling examples show how causal influences often fail to respect level

boundaries (and can act in a highly non-linear fashion)

Causes can work top-down as well as bottom-up

This means we can’t necessarily just look inwards at the properties of

entities to account for their behaviour: often must take into account their

context and interactions

In addition, it is clear that – notwithstanding the explicability of the

molecular mechanisms of gene expression and protein synthesis – the

coupling between genotype and phenotype is far from straightforward


From molecules to systems / systems approaches

Such worries motivate doubts that knowledge of individual molecules and

sequences alone can fully account for biological phenomena

- apparently confirmed by e.g. slow progress in developing

understanding (and therapies) based on narrowly molecular

approaches

Systems biology (SB): we need to treat systems as systems

• A response to:

– large quantities of genomic and other ‘omic data

– availability of computing resources, algorithms, infrastructure, standards

• Able to draw on long-standing and recent scientific research streams


From molecules to systems / emergence

SB came into being in a scientific climate sympathetic to the concept of

emergence (formerly seen as metaphysically excessive)

- interactions between system components can give rise to properties

not attributable to (identifiable with) the components in isolation

- think of the way musical effects often arise from the simultaneous

performance of independent parts by different instruments

So, structures can be explanatory, but not comprehensively so;

and emergence looks like a significant influence that we need to

take into account


From molecules to systems / structure vs. emergence

Problem: how to do this

SB currently emphasizes interactions by representing cellular processes in

terms of gene circuits and reaction networks. Where has the structure

gone?

We want to know not just what reactions occur, when, and how fast, but

how the structures that result become organized and how that

constrains / directs cellular events

Key issue: at what point does molecular structural knowledge become

inadequate for explaining cellular phenomena? When must we get to

grips with emergence?


From molecules to systems / synthetic biology

This could be where synthetic biology plays a crucial role

- just how much must be removed in order to create chassis that won’t

interfere with added components?

- how easy is it to create components that are portable across contexts

without loss of functionality?

Synthetic biology is interesting in disciplinary respects too:

- historical continuities with genetic, protein and metabolic engineering;

dependence on DNA synthesis; ambivalent relationship with systems

biology

- distinct schools with different aims, assumptions, methods

Synthetic biology: three schools


(From O’Malley et al., forthcoming in BioEssays)


Disciplinary identity and discipline names(Second part of talk!)

Synthetic biology shows how discipline names can give coherence to quite

disparate groups

- names are elastic

- they can contain and mask complex interactions and evolving

practices

- but at a certain point the capacity of names to stabilize particular

disciplinary configurations is stretched to breaking point

(see Powell et al., forthcoming in HPLS)

Bioinformatics makes an interesting case study concerning the

relationship between names and practices


Disciplinary identity and discipline names

1988:





NB



1996 - No mention here either:



1997 – How about here?



Tentative!



- cf. Lesk (1988) “Computational molecular biology has become a mature

field of science”




cf. 1999



Meanwhile in 1998…



cf. 1997



1998 – Reticent and self-conscious despite the title!



2000 – consolidation in view?



downplaying

previous

work?



Wow – sounds like systems biology!



2001

Doesn’t seem very clear-cut



2005 – big ambitions?


Conclusions / 1

Findings?

• The relationship between names and practices is pretty loose

• New names can hide significant continuities

• Discipline names increasingly fail to map neatly onto significant

research structures and patterns of interaction

• Perhaps the process of disciplinization is changing

– broad monolithic disciplines giving way to patchwork assemblies of practice

(Rheinberger)

– increasing disciplinary granularity and fluidity

• Important factor: increasing dependence on techniques (e.g.

algorithms) applicable in diverse areas

– leads to epistemic modularity and mobility of expertise (cf. stabilizing effect

of single-purpose physical expt’l equipment)


Conclusions / 2

Parallels between biological disciplines and the systems they study:

• Involve complex, dynamic, interacting structures and entities

• Susceptible to specific influences that generate non-linear effects

(signalling and gene expression in cells ↔ personal contacts, chance

events in disciplinary settings)

• Striking ontological dubiousness of dynamic, high-turnover or emergent

structures

(To what extent can disciplines be said to exist? – to the extent that

their names pick out groupings that can figure usefully in our thinking)


Conclusions / 3

Implications for regulators, policy makers?

• Simple conceptions of disciplinary identities and interests are likely to

be simplistic

• The lability of disciplinary structures, and the complex patterns of inter-

connection within and between them, may give rise to unexpected

patterns of sensitivity to external influences

• So interventions need to be well-informed, in terms of both level of

detail and breadth of view

• Need to look beyond names to see what people are doing

• Data markup standards can help here (another overlap: XML in

publishing and in science, e.g. SBML)


Acknowledgements

Jane Calvert, Jonathan Davies, John Dupré, Staffan Műller-Wille,

Maureen O’Malley

& Egenis colleagues

The University of Exeter for £inancial assistance

Documents

Genomics and Society Today’s Answers Tomorrow’s Questions · From molecules to systems / mechanisms Structures are illuminating because they give insight into the mechanisms associated