Rigor & Reproducibility

Our lab designs “causal”, robust experiments that provide a clear answer.  A key point is that we are not biased to a particular answer. Thus, negative data is equally informative as positive data. As long as the key controls are performed, then we take a parsimonious interpretation i.e. avoid over interpretation of the data.  A recent example is we tested whether “A decrease in mitochondrial complex I is sufficient to accelerate aging or age-related diseases”.  We discovered that loss of one allele of mitochondrial complex I NDUFS2 gene, catalytic subunit, is not beneficial or detrimental to aging process. Although this is a negative study, it highlights that the decrease in mRNA typically 20-50% observed in many tissues during aging is likely not detrimental to healthspan or lifespan.

 

A key publication that every new member discusses with Dr. Chandel in detail is Dr. William. Kaelin’s perspective in Nature Cancer Reviews that covers common pitfalls in science research. This wonderful article discusses the key features practiced in the lab including testing “necessary and sufficient” experiments as well as “off target” effects of experimental perturbations.