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From interventions to mechanistic explanations

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Abstract

An important strategy in the discovery of biological mechanisms involves the piecing together of experimental results from interventions. However, if mechanisms are investigated by means of ideal interventions, as defined by James Woodward and others, then the kind of information revealed is insufficient to discriminate between modular and non-modular causal contributions. Ideal interventions suffice for constructing webs of causal dependencies that can be used to make some predictions about experimental outcomes, but tell us little about how causally relevant factors are organized together and how they interact with each other in order to produce a phenomenon. I argue that lab research relies on more elaborated types of interventions targeting in a controlled fashion multiple variables at the same time in order to probe the temporal organization of causally-relevant factors along distinct causal pathways and to test for non-modular interaction effects, thus providing crucial spatial-temporal constraints guiding the formulation of more detailed mechanistic explanations.

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Notes

  1. A mechanism is a set of “entities and activities organized such that they are productive of regular changes from start or set-up to finish or termination conditions” (Machamer et al. 2000, p. 3); “a structure performing a function in virtue of its component parts, component operations, and their organization [...] responsible for one or more phenomena” (Bechtel and Abrahamsen 2005, p. 423); “entities and activities organized in such a way that they are responsible for the phenomenon (McKay Illari and Williamson 2012, p. 124); “a complex system which produces that behavior by the interaction of a number of parts according to direct causal laws” (Glennan 1996, p. S344) or by interactions that “can be characterized by direct, invariant, change relating generalization” (Glennan 2002, p. 52).

  2. For the purposes of this paper, I rely on the observation that interventions play an indispensable role in the elucidation of mechanisms, as illustrated in the scientific practice of molecular biology and related fields. I leave aside the more speculative question of figuring out whether mechanistic productivity best describes the ultimate nature of causation while interventions play a strictly epistemic role in the discovery and confirmation of mechanistic explanations, or whether mechanisms presuppose a more primitive notion of causation as difference-making; the issue is debated in (Bogen 2004; Glennan 2010, 2011; Hall 2004; Psillos 2004; Waskan 2011; Woodward 2011).

  3. Machamer, Darden and Craver (2000, p. 18) define a mechanism sketch as “an abstraction for which bottom out entities and activities cannot (yet) be supplied or which contains gaps in its stages. The productive continuity from one stage to the next has missing pieces, black boxes, which we do not yet know how to fill in. A sketch thus serves to indicate what further work needs to be done [...].”

  4. That is, without directly changing Y, or any other variable along the causal pathway from X to Y, or by simultaneously intervening on convergent causal pathways leading to Y. A fourth condition dictates that the intervention must be capable of overriding uncontrolled influences (act as a ‘switch’), such that its effect on the output conditions can be detected (Craver 2007, pp. 96–97; Woodward 2003, pp. 94–99).

  5. This partial description will suffice to illustrate a philosophical point. The mechanism is in fact more complex, and monitors both the presence of lactose and glucose, triggering the expression of the lac operon only when bacteria live in an environment rich in lactose but poor in glucose; a more complete description can be found in (Griffiths et al. 2007, p. 307).

  6. Many authors have challenged the view that mechanisms operate in a strictly regular manner and regularly succeed in producing the phenomena for which they are responsible (Andersen 2012; Bogen 2005; DesAutels 2011; Glennan 2010). Nevertheless, in scientific practice, an interventionist approach requires reproducible events: “if phenomena are infrequent to the point that they amount to irreproducible observations and experimental results, they are indistinguishable from the background noise of accidental happenings, thus making it impossible to distinguish phenomena generated by irregular mechanisms from chance correlations, as well as to interpret the results of experimental interventions required to demonstrate the causal contribution of mechanisms to the phenomena for which they are allegedly responsible” (Baetu 2013, p. 254). On this account, reproducibility amounts to the ability to produce a phenomenon with a consistent rate of success per number of experimental trials, such that, by conducting an adequate number of trials, one can determine whether an intervention on a given variable has or doesn’t have an effect on the phenomenon. The requirement for regularity can be reduced to a minimum as the number of trials increases, but cannot be completely eliminated.

  7. Isopropyl \(\beta \)-d-1-thiogalactopyranoside (IPTG) is a non-hydrolyzable (and therefore non-metabolizable) lactose analog capable of binding the lacI repressor and cause it to detach from the operator side. In lactose-induced cells, lacZ/\(\beta \)-galactosidase expression is turned on, then, as lactose is degraded by \(\beta \)-galactosidase, expression is turned back off. In IPTG-induced cells, this negative feedback loop is absent. Note that mechanisms involving cyclical causal pathways, such as feedback loops, are investigated using the same multi-variable interventions; for an example, consult Baetu (2012).

  8. Subsequent in vitro binding experiments showed that, indeed, lacI binds IPTG, and that IPTG induction correlates with a detachment of lacI from o, the operator DNA sequence (Gilbert and Müller-Hill 1966, 1967).

  9. Complementation refers to a situation where a combination of mutations yields a wild-type phenotype (Benzer 1955; Lewis 1951). Note that complementation posits an immediate threat to the modularity assumption. If the causal contribution of the mechanistic components affected by the mutations is modular, then modifying one component, or the second, or both should lead to the same loss in the ability of the mechanism to produce the wild-type phenotype. Yet this is not what happens. Each separate mutation results in a loss of the wild-type phenotype, while a double mutation results in a wild-type phenotype. One way to account for complementation effects is to hypothesize an interaction between the two components, such that if any single component is modified, it fails to interact with the other—for instance, because their geometrical shapes don’t fit anymore according to a key and lock model of molecular interaction; however, if the two are simultaneously modified, it can happen that a new geometrical fit is produced and they can once again interact.

  10. Mutations in the gene encoding a repressor protein (lacI) reveal that this protein is trans-acting; that is, it can act on any copy of the target DNA site in the cell (Fig. 2c, row 6). In contrast, operator (o) mutations reveal that such a site is cis-acting; that is, it regulates the expression of an adjacent transcription unit on the same DNA molecule (row 7).

  11. This hypothesis was subsequently supported by in vitro binding assays coupled with DNase treatment demonstrating an overlap between the DNA sequences covered by lacI and RNA polymerase (Majors 1975).

  12. Levels are understood here as levels of composition (Wimsatt 1976), namely mechanisms and modules being composed of molecular component parts.

  13. Alternative views include an ontic view, which treats mechanistic explanations as objective features of the world (Craver 2007; Salmon 1984), and a modified epistemic view according to which mathematical models provide a more rigorous understanding of some quantitative-dynamic details of phenomena by showing that they are consequences of rules and assumptions about the operation of mechanisms (Baetu 2015a, b; Bechtel 2012; Bechtel and Abrahamsen 2011; Braillard 2010; Brigandt 2013; Gross 2015).

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  1. Department of Philosophy, University of Bristol, Cotham House, Bristol, BS6 6JL, UK

    Tudor M. Baetu

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Baetu, T.M. From interventions to mechanistic explanations. Synthese 193, 3311–3327 (2016). https://doi.org/10.1007/s11229-015-0930-y

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