Yesterday was one of those gorgeous spring days in Missouri – warm and windy, with everything coming into bloom. I drove over to the WashU non-medical campus to hear the annual Viktor Hamburger memorial lecture, given this year by Dr. Sydney Brenner. The auditorium was filled to the brim, with attendees finally sitting on the steps and standing in the back of the room. It was unsurprising not only because he’s a Nobel laureate, but also revered among the nematode research community which in St. Louis is quite large.
It turns out that Dr. Brenner, who was born in South Africa, has a charming accent and a bit of a rambling style, which he’s certainly allowed. He is a clear proponent of what he calls “the scientist at the bench” – the lone researcher or graduate student working late into the night – and not a fan of large-scale genomics. Dr. Brenner joked that many people say sequencing the genome was like sending a man to the moon, and he agrees, because “it’s easy. The hard part is bringing him back.”
The Cell as the Correct Level of Abstraction
He went on to address the complexity of understanding biology at its various levels of abstraction – gene, protein, cell, tissue, organism, etc. – and argued that the cell is the “correct level of abstraction” to talk about the genome. The genome itself presents a problem of complexity – 20,000 genes, each encoding one or more proteins. If the genes are the templates, then what they encode might be called “instantiations” of genes, and can vary widely. In fact, Dr. Brenner posited that the human genome may encode as many as 150,000 “instantiations” from 20,000 genes.
Reducing Genome Complexity
So how does one reduce the complexity? This is a problem, Dr. Brenner said, that has already been solved by nature: by assembling small groups of proteins into sub-machinery complexes (e.g. spliceosome), the complexity is reduced by modularization. He likened it to two watch-makers, one of whom assembles watches one piece at a time, while the other assembles pieces into subcomponents before putting them all together. The second watchmaker is the one who will ever finish a watch.
Dr. Brenner filled the hour with little metaphors like these; there were no slides. He was like a storyteller, and the audience listened with rapt attention.
Systems Biology: What They Should Be Doing
The speaker remarked that many questions asked by scientists are “inverse problems” – using observations (data) to infer mechanisms and function underlying them. He gave as an example fellow Nobel laureates Watson and Crick, who had sought to use X-ray diffraction data to infer the structure of DNA. They were all three at Cambridge at the same time, it turns out. Unfortunately, the output of diffraction experiments provide a value that is the square of what’s being measured – the phasing information is lost, so there was no way to know if it was 1 or -1. There is not enough computing power in the world to test all of the possible combinations, not even if they started calculating 2,000 years ago. So instead, Watson and Crick took a more direct approach – they built models, predicted what the diffraction output of each model would be, and then compared it to the actual output.
Artificial Intelligence Combined with Human Stupidity
Omics sciences, Dr. Brenner argued, instead try to measure everything (e.g. sequence the entire genome) and hope that a magical computer program will provide the answers, something he called “Artificial intelligence combined with human stupidity.” He said that such an approach to science was low input, high throughput, no output – where you put garbage in and get garbage out. Instead, Dr. Brenner encouraged us to start with high input, which, he said, is what’s in your head.