{"id":538,"date":"2016-10-20T07:13:46","date_gmt":"2016-10-20T07:13:46","guid":{"rendered":"http:\/\/joshmitteldorf.peachpuff-wolverine-566518.hostingersite.com\/?p=538"},"modified":"2016-10-20T07:21:22","modified_gmt":"2016-10-20T07:21:22","slug":"putting-the-system-back-in-systems-biology","status":"publish","type":"post","link":"https:\/\/scienceblog.com\/joshmitteldorf\/2016\/10\/20\/putting-the-system-back-in-systems-biology\/","title":{"rendered":"Putting the “system” back in Systems Biology"},"content":{"rendered":"

Cold Spring Harbor labs<\/a> on Long Island has a diverse offering of conferences that attract experts from all areas of biology. For the last six years, there has been a sister group organizing conferences in Suzhou, China. I spent last week at the 2016 CSH Asia<\/a> conference on Systems Biology.<\/p>\n

While I have been to many conferences on aging and a few on evolution, this was my first Systems Biology conference. I looked forward to learning how biologists think about whole-body issues of homeostasis, organization, and (maybe if I was lucky) blood signals that regulate aging.<\/p>\n

What I found instead was that researchers in systems biology are doing what other biologists are doing: they are babes in toyland, exploring the potential of a seductive array of new biomolecular tools. They are compiling catalogs and making maps and correlating every chemical they can find with every other chemical, and collaborating with statisticians to look for patterns in the data. If \u201csystems thinking\u201d is from the top down, what I found at this meeting was just the opposite.<\/p>\n

A hundred years ago, Lord Rutherford<\/a> said that \u201cAll science is either physics or stamp collecting.\u201d He was mocking the biologists\u2019 program of collecting specimens, classifying and cataloging them. Twentieth century biology turned this around; it was neither physics nor stamp collecting, but model-building. Systems biologists in particular have analyzed living organisms in terms of signals and networks and energy flows, and have generated a great deal of understanding. At its best, biology has forged a new mode of science.<\/p>\n

So why is it that 21st<\/sup> Century systems biology is looking once more like stamp collecting? It\u2019s a question I asked one of the conference organizers (in more polite terms), and he responded that \u201cwe are working from a reductionist framework. We are trying to build understanding from the bottom up.\u201d<\/p>\n

There\u2019s a deeper answer<\/b><\/p>\n

Why, after the revolutionary successes of late 20th<\/sup> century biology, should bioscience find itself back at square one, trying to build a foundation? The short answer: genetics is simple; epigenetics is complicated.<\/p>\n

The heyday of genetics started from Crick\u2019s decoding of the genetic code<\/a>\u00a0in 1961. DNA was revealed to be a blueprint for producing proteins that would do the body\u2019s work. The code was just as simple and elegant as it could be, and the machinery to do the translation was segregated in ribosomes<\/a>, which could be isolated and picked apart. The era of genetics ended in 2003 with the completion of the human genome project. Results were a surprise to everyone, and the message took awhile to filter into conceptual thinking: The genome is 3% genes and 97% gene regulation. All the impressive tasks of development, homeostasis, and metabolism are performed by an exquisitely adapted system that turns genes on and off in the right place at the right time.<\/p>\n

2003 ended the era of genetics and began the era of epigenetics. How is gene expression regulated and contolled? DNA methylation<\/a> was the first mechanism discovered. But as clues appeared and mechanisms were partially elucidated, it has become apparent that epigenetics is as complicated and intractable as it can possibly be. Besides methylation, there are more than 100 modifications of the DNA and its associated proteins (histones) that affect gene expression. There is also the way in which DNA folds around itself, leaving some regions open where they can be transcribed and keeping other regions under tight wraps. Finally, there is a variety of post-translational modifications; even after a stretch of DNA has been transcribed into RNA and translated into a protein, the protein can be turned on or off by adding a phosphate group or a methyl or acetate at any number of receptor sites.<\/p>\n

Metabolism is now seen as a dense web of interacting processes, intertwined causes and effects. Gene network maps draw lines between genes that are co-expressed, and can divide the territory into subsets (modules) that are more closely related to each other than to other modules.\"\"<\/p>\n

 <\/p>\n

But this is a picture that only a computer could love; it contains intricacies on a scale that human consciousness cannot grasp with conceptual understanding.<\/p>\n

Contrast this to the naive simplicity of Crick\u2019s Central Dogma of Molecular Biology<\/a>: Information flows in one direction, from DNA to RNA to proteins. Crick lived to see his insight de-dogmatized by exceptions, but it has been since his death (2004) that the essential, bewildering complexity of biochemical networks has been revealed.<\/p>\n

No wonder the community of systems biologists feels that they are starting over again, collecting, classifying and cataloging stamps.<\/p>\n

New Tools<\/b><\/p>\n

Biochemical science this last few years seems to be driven by newly available technologies. These are so powerful and coming so fast that just exploring what they can tell us is occupying the lion\u2019s share of available funding and lab space. I knew about some of these, and several more were new to me last week.<\/p>\n