For the first time ever, scientists have developed a complete model of an organism, accounting for every molecular interaction in the entire life span of the bacterium Mycoplasma genitalium.
The research is published today in the journal Cell and shows how Stanford researchers led by Professor Markus Covert brought together over 900 papers on the bacterium in order to depict the inner-workings of the organism.
The model has allowed scientists to get a much closer look into the cellular interactions and biological behavior of M. genitalium, a very simple bacterium that is sexually transmitted between primates and can cause itching, burning or discharge.
Essentially the model reproduces the inner workings of all of the proteins within the organism and allows scientists to see everything from how cells interact with each other to the functions of genes in a larger context that had not been previously understood.
But the reason this research is so momentous has very little to do with bacteria at all, rather it signals the beginning of modeling organisms. Computer models will allow scientists to look at the molecular behavior of organisms from a microscopic level and learn things that have never even been conceived of before.
Jonathan Karr, one of the study's researchers, emphasized that "the goal hasn't only been to understand M. genitalium better, it's to understand biology generally."
Scientists hope to eventually get to the point where they can create a computer model of a human, or even just the molecular workings of a human cell, but that's still a dream with the next step being the modeling of larger and more complex bacteria.
Nevertheless, this research is monumental because a better understanding of how our cells behave could eventually allow for such world-changing breakthroughs such as personalized medicine.
Below is the model of M. genitalium. It matches up with the observed entire life cycle and doubling rate (about every 8 hours) of the single celled organism.
Courtesy of: Karr JR, Sanghvi JC, Macklin DN, Gutschow MV, Jacobs JM, Bolival B, Assad-Garcia N, Glass JI, Covert MW. A Whole-Cell Computational Model Predicts Phenotype from Genotype. Cell 150, 389-401 (2012).