Complexity_ A Guided Tour - Melanie Mitchell [118]
As I mentioned in chapter 7, humans have about 25,000 genes, roughly the same number as the mustard plant arabidopsis. What seems to generate the complexity of humans as compared to, say, plants is not how many genes we have but how those genes are organized into networks.
There are many genes whose function is to regulate other genes—that is, control whether or not the regulated genes are expressed. A well-known simple example of gene regulation is the control of lactose metabolism in E. coli bacteria. These bacteria usually live off of glucose, but they can also metabolize lactose. The ability to metabolize lactose requires the cell to contain three particular protein enzymes, each encoded by a separate gene. Let’s call these genes A, B, and C. There is a fourth gene that encodes a protein, called a lactose repressor, which binds to genes A, B, and C, in effect, turning off these genes. If there is no lactose in the bacterium’s local environment, lactose repressors are continually formed, and no lactose metabolism takes place. However, if the bacterium suddenly finds itself in a glucose-free but lactose-rich environment, then lactose molecules bind to the lactose repressor and detach it from genes A, B, and C, which then proceed to produce the enzymes that allow lactose metabolism.
Regulatory interactions like this, some much more intricate, are the heart and soul of complexity in genetics. Network thinking played a role in understanding these interactions as early as the 1960s, with the work of Stuart Kauffman (more on this in chapter 18). More recently, network scientists teaming up with geneticists have demonstrated evidence that at least some networks of these interactions are approximately scale-free. Here, the nodes are individual genes, and each node links to all other genes it regulates (if any).
Resilience is mandatory for genetic regulatory networks. The processes of gene transcription and gene regulation are far from perfect; they are inherently error-ridden and often affected by pathogens such as viruses. Having a scale-free structure helps the system to be mostly impervious to such errors.
Metabolic Networks
As I described in chapter 12, cells in most organisms have hundreds of different metabolic pathways, many interconnecting, forming networks of metabolic reactions. Albert-László Barabási and colleagues looked in detail at the structure of metabolic networks in forty-three different organisms and found that they all were “well fitted” by a power-law distribution—i.e., are scale free. Here the nodes in the network are chemical substrates—the fodder and product of chemical reactions. One substrate is considered to be linked to another if the first participates in a reaction that produces the second. For example, in the second step of the pathway called glycolysis, the substrate glucose-6-phosphate produces the substrate fructose-6-phosphate, so there would be a link in the network from the first substrate to the second.
Since metabolic networks are scale-free, they have a small number of hubs that are the products of a large number of reactions involving many different substrates. These hubs turn out to be largely the same chemicals in all the diverse organisms studied—the chemicals that are known to be most essential for life. It has been hypothesized that metabolic networks evolved to be scale-free so as to ensure robustness of metabolism and to optimize “communication” among different substrates.
Epidemiology
In the early 1980s, in the early stages of the worldwide AIDS epidemic, epidemiologists at the Centers for Disease Control in Atlanta identified a Canadian flight attendant, Gaetan Dugas, as part of a cluster of men with AIDS who were responsible for infecting large numbers of other gay men in many different cities around the world. Dugas was later vilified in the media as “patient zero,” the first North American with AIDS, who was responsible for introducing and widely spreading the AIDS virus in the United States and elsewhere. Although later studies debunked the theory that Dugas