Aging research in C. elegans has come a long way since the early 80s, spurred by the characterization of single-gene mutations (e.g. age-1 and daf-2) that extend the worm's lifespan. The discovery of a growing number of genes and conditions with similar effects led to the recognition that broad classes of physiological variables—metabolic rate and respiration, reproduction, sensory perception, stress responses and associated developmental states—undergird lifespan. Perhaps it is not too surprising that lifespan is the collective outcome of many integrated processes. Yet, this is precisely why understanding aging solely in terms of molecular mechanisms is a daunting task. Aging is a case in which a bottom-up approach may not be meaningful without an accompanying top-down approach.
A bottom-up approach identifies how specific biochemical and biophysical processes shape lifespan, while a top-down approach systematically characterizes lifespan distributions and their variability. The former might convey some ultimate understanding, but the latter can identify quantitative phenomenological variables and their interrelations that determine dimensions along which lifespan is particularly malleable. Identifying these dimensions is required to properly define and contextualize the molecular mechanisms that aging research is seeking.
The lifespan distribution as a phenotype
We acquired quantitative and highly-resolved mortality statistics (lifespan distributions and associated statistics, such as hazard and survival) as a function of genetic and environmental conditions. The shape of empirical hazard functions and their responsiveness to genetic interventions are critical in guiding the development of more structured computational models of aging and for hypothesizing about molecular mechanisms of aging. While lifespan distributions and hazard rates are routine datatypes for bio-demographics, current high-resolution data appear limited to a few genes or conditions. Some organisms are too long-lived, others are too complex (inscrutably entangling aging with disease), and the process of counting is boring and time consuming. Most of these problems can be mitigated by using C. elegans as a model and automating the process of lifespan acquisition.
Our lab has established an inexpensive and robust technology for the automated acquisition of survival curves at arbitrary statistical resolution using flatbed scanners as a scalable imaging and analysis platform to observe nematodes over multiple weeks across square meters of agar surface at 8 µm resolution. This approach enabled us to discover that C. elegans mortality statistics respond to many physical, chemical, and genetic interventions only by rescaling time.
We achieved spatially resolved quantitative measurements of in vivo redox potential that support the idea that glutathione facilitates the sensitive control of the thiol–disulfide balance of target proteins in response to cellular redox events. Details are described in this paper.
Microfluidics for C.elegans
In collaboration with the Whitesides Lab at Harvard's Department of Chemistry we helped develop microfluidics technology to facilitate quantitative longitudinal measurements in single organisms.