Having made substantial progress understanding molecules, cells, genes and pathways, aging biology research is now moving toward integration of these parts, attempting to understand how their joint dynamics may contribute to aging. Such a shift of perspective requires the adoption of a formal complex systems framework, a transition being facilitated by large-scale data collection and new analytical tools. Here, we provide a theoretical framework to orient researchers around key concepts for this transition, notably emergence, interaction networks and resilience. Drawing on evolutionary theory, network theory and principles of homeostasis, we propose that organismal function is accomplished by the integration of regulatory mechanisms at multiple hierarchical scales, and that the disruption of this ensemble causes the phenotypic and functional manifestations of aging. We present key examples at scales ranging from sub-organismal biology to clinical geriatrics, outlining how this approach can potentially enrich our understanding of aging.

Transcription Factor as Computer: Cellular signaling pathways can serve to process information so that cells respond appropriately to various environmental stimuli. Hao et al. (p. 460 ) show that a single yeast transcription factor that is activated in response to stress—Msn2—can act as a signal processor. In an experimental setup in which the amplitude and duration of signaling in the cells could be tightly controlled, sites of phosphorylation on Msn2 that determine its transport into or out of the nucleus allowed it to have different dynamic responses depending upon the amplitude of the signal detected. The transcription factor could either track with the incoming signal, filter (ignore) it, or integrate it. Understanding such properties may be useful in designing behavior of biological control systems.

Programmed aging in yeast cells: Following the fate of individual yeast cells has revealed aging to be more of a programmable decision process rather than a simple accumulation of deleterious events. Li et al. combined single-cell studies and mathematical modeling to show that yeast cells showed two different forms of aging: one with less ribosomal DNA silencing, in which nucleoli were degraded, and another with less heme accumulation and hemedependent transcription, in which mitochondria were more affected. Overexpression of the lysine deacetylase Sir2, which contributes to ribosomal DNA silencing, led to a third cell-aging fate in which the average life span was extended. If other cells age in similar ways, then this study may provide new ways to consider dynamics of aging and strategies to extend the health span. Science this issue p. 325