"Long before it's in the papers"
January 27, 2015


First “virtual cell” seen as unlocking new potential for discovery

July 24, 2012
Courtesy of Stanford University
and World Science staff

The first com­plete com­put­er mod­el of an or­gan­ism has been com­pleted, re­search­ers re­ported last week in the jour­nal Cell.

A team led by Markus Cov­ert of Stan­ford Uni­vers­ity used da­ta from more than 900 sci­en­tif­ic pa­pers to ac­count for eve­ry mo­lec­u­lar in­ter­ac­tion that takes place in the life cy­cle of My­co­plas­ma gen­i­tal­ium, the world’s small­est free-liv­ing bac­te­ri­um.

The Cov­ert Lab at Stan­ford Uni­ver­si­ty in­cor­po­rat­ more than 1,900 ex­per­i­men­t ob­served param­e­ters in­to their mod­el of the ti­ny par­a­site My­coplasma gen­i­tal­ium. (Il­lus­tra­tion: Er­ik Ja­cob­sen / Cov­ert Lab)  

“Com­puter mod­els of en­tire cells have the po­ten­tial to ad­vance our un­der­stand­ing of cel­lu­lar func­tion and, ul­ti­mate­ly, to in­form new ap­proaches for the di­ag­no­sis and treat­ment of dis­ease,” said James M. An­der­son, di­rec­tor of the Di­vi­sion of Pro­gram Co­ordina­t­ion, Plan­ning and Stra­te­gic Ini­tia­tives at the Na­t­ional In­sti­tutes of Health, which helped fund the re­search.

Ge­net­ic ex­pe­ri­ments typ­ic­ally in­volve de­acti­vat­ing one gene to see what hap­pens. The draw­back to that, Cov­ert said, is that many of the ques­tions bi­ol­o­gists need to learn about “aren’t sin­gle-gene prob­lems. They’re the com­plex re­sult of hun­dreds or thou­sands of genes in­ter­act­ing.”

This situa­t­ion has led to a yawn­ing gap be­tween in­forma­t­ion and un­der­stand­ing that can only be ad­dressed by “br­ing­ing all of that da­ta in­to one place and see­ing how it fits to­geth­er,” said Stan­ford grad­u­ate stu­dent Jay­o­dita Sangh­vi, who co-authored the re­search. “You don’t really un­der­stand how some­thing works un­til you can re­pro­duce it your­self.”

The bac­te­ri­um mod­eled is is a hum­ble par­a­sit­ic one known mainly for show­ing up un­in­vit­ed in hu­man uro­gen­i­tal and res­pi­ra­to­ry tracts. But it al­so has the dis­tinc­tion of con­tain­ing the small­est ge­nome of any free-liv­ing or­gan­ism – only 525 genes, as op­posed to the 4,288 of E. coli, a more tra­di­tion­al lab­o­r­a­to­ry bac­te­ri­um. The min­i­mal­ism of its ge­nome has made it the fo­cus of sev­er­al re­cent bi­o-en­gi­neer­ing ef­forts. No­ta­bly, these in­clude the J. Craig Ven­ter In­sti­tute’s 2008 syn­the­sis of the first ar­ti­fi­cial chro­mo­some.

“The goal has­n’t only been to un­der­stand M. gen­i­tal­ium bet­ter,” said Stan­ford bio­phys­ics grad­u­ate stu­dent Jon­a­than Karr, who al­so col­la­bo­rat­ed on the stu­dy. “It’s to un­der­stand bi­ol­o­gy gen­er­al­ly.” Even at this small scale, the quan­ti­ty of da­ta that the re­search­ers incorporat­ed in­to the vir­tu­al cel­l’s code was enor­mous. The fi­nal mod­el made use of more than 1,900 ex­pe­ri­men­tally de­ter­mined param­e­ters.

The com­puta­t­ional cell opens up pro­ce­dures that would be hard to per­form in a real or­gan­ism, and op­por­tun­i­ties to re­vis­it ex­pe­ri­men­tal da­ta, the re­search­ers said. In the pa­per, the mod­el is used to dem­on­strate a num­ber of these ap­proaches, in­clud­ing de­tailed in­ves­ti­ga­t­ions of DNA-binding pro­tein dy­nam­ics and the iden­ti­fica­t­ion of new gene func­tions.

Bi­ol­o­gists hope com­puta­t­ional mod­els like this one could br­ing ra­t­ional de­sign to bi­ol­o­gy – al­low­ing not only for com­put­er-guided ex­pe­ri­men­tal regimes, but al­so for the whole­sale crea­t­ion of new microor­gan­isms. “This is po­ten­tially the new Hu­man Ge­nome Pro­ject,” Karr said. “It’s go­ing to take a really large com­mun­ity ef­fort to get close to a hu­man mod­el.”

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The world’s first complete computer model of an organism has been completed, researchers reported last week in the journal Cell. A team led by Markus Covert of Stanford University used data from more than 900 scientific papers to account for every molecular interaction that takes place in the life cycle of Mycoplasma genitalium, the world’s smallest free-living bacterium. “Computer models of entire cells have the potential to advance our understanding of cellular function and, ultimately, to inform new approaches for the diagnosis and treatment of disease,” said James M. Anderson, director of the Division of Program Coordination, Planning and Strategic Initiatives at the National Institutes of Health, which helped fund the research. Genetic experiments typically focus on knocking out a single gene and seeing what happens. The drawback to that, Covert said, is that many of the questions biologists need to learn about “aren’t single-gene problems. They’re the complex result of hundreds or thousands of genes interacting.” This situation has led to a yawning gap between information and understanding that can only be addressed by “bringing all of that data into one place and seeing how it fits together,” said Stanford bioengineering graduate student Jayodita Sanghvi, who co-authored the research. “You don’t really understand how something works until you can reproduce it yourself.” The bacterium modelled is is a humble parasitic one known mainly for showing up uninvited in human urogenital and respiratory tracts. But it also has the distinction of containing the smallest genome of any free-living organism – only 525 genes, as opposed to the 4,288 of E. coli, a more traditional laboratory bacterium. The minimalism of its genome has made it the focus of several recent bioengineering efforts. Notably, these include the J. Craig Venter Institute’s 2008 synthesis of the first artificial chromosome. “The goal hasn’t only been to understand M. genitalium better,” said Stanford biophysics graduate student Jonathan Karr, who also collaborated on the study. “It’s to understand biology generally.” Even at this small scale, the quantity of data that the researchers incorporated into the virtual cell’s code was enormous. The final model made use of more than 1,900 experimentally determined parameters. The computational cell opens up procedures that would be hard to perform in a real organism, and opportunities to revisit experimental data, the researchers said. In the paper, the model is used to demonstrate a number of these approaches, including detailed investigations of DNA-binding protein dynamics and the identification of new gene functions. Biologists hope computational models like this one could bring rational design to biology – allowing not only for computer-guided experimental regimes, but also for the wholesale creation of new microorganisms. “This is potentially the new Human Genome Project,” Karr said. “It’s going to take a really large community effort to get close to a human model.”