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Networks in Biology – Protein-Protein Interaction Networks in Yeast.

We are living the era of the biological revolution. Barely 10 years ago, biologists sequenced the human genome, and since then the fields of genetics and genomics have grown exponentially. Predictions were made that the sequencing of the human genome (and of other species) would lead to a massive increment in the number of cures for genetic diseases, and the betterment of medicine in general.

Actually, these predictions have not been fulfilled to their fullest extent. While many disorders have been associated with specific genes, few have had a simple genetic explanation. And even for those diseases where the guilty genes are known (Huntington’s, Down’s syndrome, etc…), knowledge of the culprit has not led to a significant increase in the number of drugs available to treat them.  Why is this? One possible reason lies in our almost complete ignorance about the interconnectedness of the molecular processes going on in our cells.  At our most basic level, cells operate based on a massive network called the interactome. The interactome, in turn, can be broken down into a transcriptome (a network of transcription factor-DNA interactions), a metabolome (enzyme-metabolite interaction network) and a proteome (protein-protein interaction network). Without a good understanding of the role each protein plays in this complicated system, we have limited capacity to predict the effect a mutation in a particular gene will have. Fortunately, researchers are making rapid advances to map the first interactomes.

Recently, researchers have presented the first attempts to map the yeast interactome. Current estimates are that the yeast interactome will contain around 20,000 interactions (there are around 5,500 genes in the yeast genome, for comparison). Current attempts have managed to recapitulate up to 2080 protein-protein interactions.  Such attempts have shed light on biological networks. Firstly, these networks are built for robustness: They follow a power law distribution, which essentially means there are many nodes with one or two edges, and a very few nodes with many edges (hubs). Such networks have been tested and shown to have multiple cyclic properties (i.e, a pair of nodes is involved in one or more cycles), thus helping to make the yeast cells less susceptible to random mutation, and giving evolution a flexible framework on which  to operate.  Another crucial property of the yeast interactome is the presence of a giant connected component too large to exist simply by chance. Although all the implications of such a giant connected component are not well understood, this agrees well with intuition. A predominant concept in biology, and particularly in ecology, is the interdepence of every organism with one another. An organism itself is the result of interdependent cells. As such, that a cell is the result of a totally connected network with a finite diameter is not surprising, but rather illustrates the beauty prevalent in biological systems.

Further research is necessary to begin to understand how to carefully analyze and generate interactomes for more complicated organisms. Generation of a high quality binary interactome for human protein protein interactions is likely to be crucial for the rapid development of human medicines and for the analysis of diseases as complicated as cancer or neurological disorders.
*This blog post was written strongly referencing the following article:

High-Quality Binary Protein Interaction Map of the Yeast Interactome Network

  • Haiyuan Yu,
  • Pascal Braun,
  • Muhammed A. Yıldırım,
  • Irma Lemmens,
  • Kavitha Venkatesan,
  • Julie Sahalie,
  • Tomoko Hirozane-Kishikawa,
  • Fana Gebreab,
  • Na Li,
  • Nicolas Simonis,
  • Tong Hao,
  • Jean-François Rual,
  • Amélie Dricot,
  • Alexei Vazquez,
  • Ryan R. Murray,
  • Christophe Simon,
  • Leah Tardivo,
  • Stanley Tam,
  • Nenad Svrzikapa,
  • Changyu Fan,
  • Anne-Sophie de Smet,
  • Adriana Motyl,
  • Michael E. Hudson,
  • Juyong Park,
  • Xiaofeng Xin,
  • Michael E. Cusick,
  • Troy Moore,
  • Charlie Boone,
  • Michael Snyder,
  • Frederick P. Roth,
  • Albert-László Barabási,
  • Jan Tavernier,
  • David E. Hill,
  • and Marc Vidal

Science 3 October 2008: 322 (5898), 104110.Published online 21 August 2008[DOI:10.1126/science.1158684]


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