Garry Nolan was recently interviewed by the science blog MendelsPod.com. Garry discusses the origins of his interest in single cell analysis, his lab’s work with Mass Cytometry, and moving past scientific low hanging fruit. He also discusses how his lab makes their techniques publicly available to the scientific community, and even gives his opinion on radical life extension. You can find the interview here, or you can read our summary below.
The interview begins with Garry explaining why, in coming from a flow cytometry background, he thought it necessary to increase the number of parameters available in single cell analysis. Traditional flow cytometry uses 3-6 surface markers to positively identify a population, leaving only a handful of open channels to identify other populations or signaling targets. More channels allows far more populations to be identified in a heterogeneous sample. Previous signaling targets in molecular biology have been, he describes, low hanging fruit since there are considerable overall changes in mass action signaling derived from a western blot or ELISA. Now there are tools available to measure many parameters at the same time and correlate them to each other. This involves a significant degree of computational analysis, and Garry admits that between 1/3 and 1/2 of his lab members are computationally inclined, with several more members being bioinformaticians – specializing in both computation and biology.
When asked about the response of the scientific community to his lab’s use of mass cytometry, Garry states that it has “been tremendous” and that he has been busier than ever. This is in part due to his philosophy that “The best way to present information and data is to do it in a manner that gives other people the possibility of seeing their own personal success through what it is that you’re doing.” – a point that he emphasizes in his lab. This view has led to many labs seeking protocols and advice, so many that the Nolan lab has set up a once yearly phospho-flow course (protocols available here). Once they collect the data, many labs don’t necessarily have the computational resources required to effectively analyze the results, which is why Garry recommends Cytobank as their main resource for analysis and computational tools. The Nolan lab publicly distributes all of the FCS files and figures from their recently published papers, as well as the protocols used to generate the data, on the Nolan Lab Resource, hosted by Cytobank.
Garry continues by stating that he is trying to move people away from the One Idea One Hypothesis One Answer model which has been the established standard for scientific discovery. When one has the power of recent advancements in instrumentation, hundreds of thousands of questions can be asked at the same time and then examined to determine the most relevant answer and subsequently the best question. Looking forward, he says he is the most excited about using extra channels in mass cytometry to mathematically encode and decode samples to enable the equivalent of hundreds of parameters and the subsequent development of biology via inferrment by the use of special tags and computational approaches.