Molecular biology research at the molecular level is the phenomenon of life science. By studying biological macromolecules (nucleic acids, proteins) of the structure, function and biosynthesis of various aspects to clarify the nature of the phenomenon of life. The study includes a variety of life processes. Such as photosynthesis, the molecular mechanisms of development, the mechanism of neural activity, the incidence of cancer and so on.
NewsBytes described in the March 2010 issue of the space of another molecule. The most Simulating PLoS Computational Biology. complex scenario they ran included Crowded Cytoplasm “This is an attempt to build a virtu- excluded volume, electrostatic interac- In biology textbooks, the carefully al lab, in which we can study various tions, and favorable short-range rendered cross-section of an E. coli cell biological and biophysical processes as hydrophobic interactions. The more often resembles a well-organized and they might occur inside the cell,” says complex simulations performed surpris- spacious apartment, with everything in Adrian Elcock, PhD, coauthor and ingly well when asked to predict molecu- its place and ample room for move- associate professor of biochemistry at lar behaviors, such as diffusion and stabil- ment. But a recent computational the University of Iowa. ity, in the E. coli cytoplasm. recreation of the scene looks more like The sea of floating proteins inside The model was able to match exper- a Friday night dance floor, with mole- every cell is the background against imental observations of how quickly cules bumped up against one another in which many cellular reactions take place. green fluorescent protein diffuses in the every direction. In addition to provid- Scientists realized years ago that the cyto- E. coli cytoplasm. And it was able to ing a dramatic, qualitative description plasm is generally not an invisible player predict the greater stability of the of the crowded cytoplasm, this first in those reactions. One of the best-stud- unfolded state of the protein CRABP, ied examples is macro- cellular retinoic acid binding protein, molecular crowding over the folded state inside E. coli. (also called excluded Although the presence of close neigh- volume effect). Having bors (crowding) generally stabilizes a large neighbors on large folded protein, the specific elec- every side changes a trostatic and hydrophobic interactions protein’s effective con- of unfolded CRABP with other cyto- centration and influ- plasmic proteins counteract the crowd- ences its movement ing effect. and ability to react. “What this doesn’t mean,” Elcock A biological reaction emphasizes, “is that crowding effects observed in dilute are unimportant. It means that crowd- solution can be much ing is only part of the story.” faster or slower than A computational box of 1008 pro- the same reaction teins is still a far stretch from the com- inside a crowded cell. plex E. coli cytoplasm, says Allen To create the model, Minton, PhD, a pioneer in the study of Elcock and then gradu- crowding effects and researcher of ate student Sean physical biochemistry at the National McGuffee, PhD, start- Institutes of Health. “But there are a lot ed by gathering known of questions that only this type of com- structural data for 50 of putation can answer,” he says. “From a the most common E. computational point of view, it is a real coli proteins. They then tour-de-force.” Combining all available known details about the atomic structures and combined the detailed —By Louisa Dalton concentrations of 50 of the most common proteins within E. coli’s cyto- representations inside a plasm, Elcock and McGuffee created a model of what it might be like computer model at inside the crowded cell. They then simulated 20 microseconds of known cellular con- Animating jostling with and without various types of molecular interactions, centrations, creating a Molecular Biology including crowding (excluded volume effect) and electrostatic and strikingly dense model These days, molecular biologists hydrophobic interactions. They then compared the results to experi- of 1008 proteins. The often gather data over a period of mental observations. Reprinted from McGuffee SR, Elcock AH, 2010 researchers then set time—observing shifts as they occur Diffusion, Crowding & Protein Stability in a Dynamic Molecular Model that image in motion, inside groups of cells undergoing natural of the Bacterial Cytoplasm. PLoS Comput Biol 6(3): e1000694. running independent changes. The researchers then face the doi:10.1371/journal.pcbi.1000694. Brownian dynamics daunting task of making sense of it all. simulations governed Now, computational biologists have atomically detailed computational by varying energetic descriptions of inter- devised a software program to easily model of E. coli innards is also a tool for molecular interactions. The simplest visualize and analyze these mountains of quantitative predictions of molecular description included only the excluded time-series data in animated movie conduct within the cell. The model is volume effect: no molecule could take form. While these flicks might never Published by Simbios, the NIH National Center for Physics-Based Simulation of Biological Structures 3 NewsBytes appear at a theater near you, scientists work, led by Ihor Lemischka, PhD, the grid, representing molecular shifts studying such disparate areas as stem cell Mount Sinai professor of gene and cell over the time course of the experimen- development and the microbial commu- medicine, was published in Nature in tal series. Although GATE was devel- nities of the Pacific Ocean will be play- November 2009. “It was a relatively oped for stem cell biologists, its poten- ing them on their computer screens to simple approach but it hadn’t been tial applications are broad, Ma’ayan explore how all the genes and proteins done before,” Ma’ayan says. But says. Recently, he was contacted by a group at the University of British Columbia that wants to use the soft- ware to analyze changes in marine flora and fauna in the Pacific Ocean. In this case, the movies will look at changes both over time and distance, as the researchers sample further from the coast. Oliver Hofmann, PhD, a computa- tional biology research scientist at the Harvard School of Public Health, says the technology will be very useful for the field of molecular biology. “It’s a very neat way of visualizing time series,” he says. “But it’s not just a pret- ty picture you can look at. You can explore it interactively too.” It is still difficult to coordinate more than two types of data timecourses in GATE, Hofmann says, and Ma’ayan agrees. He says their to-do list includes plans to better overlay multiple movies. —By Rachel Tompa, PhD This screenshot from the GATE software program shows RNA expression levels from experi- Capturing Mitosis ments on stem cells that were genetically manipulated to differentiate. Each hexagon repre- Genes in Action sents a single gene; red hexagons are genes with increased RNA levels and green are those During the one-hour drama that is with decreased levels. Commonalities among gene annotations are highlighted in blue, and human cell division, many genes enter white lines represent known interactions between proteins. GATE movies animate a series of and exit the stage. Until now, these images to show changes over time. Courtesy of Avi Ma’ayan. researchers did not know the identities of many of these actors, nor understand of a cell type or organism change over Ma’ayan’s group realized that GATE their various roles. Now, using a combi- the timespan of experiments. movies would be even more useful if nation of high-throughput screening “This is a tool that is really useful for they could incorporate existing biologi- methods, time-resolved movies and a interrogating datasets collected as a time cal data, such as libraries of protein-pro- supervised machine-learning algorithm, series at multiple layers of regulation,” tein interactions or annotations of researchers have identified 572 genes says Avi Ma’ayan, PhD, assistant profes- genes’ functions. The updated software that are involved in mitosis in human sor of pharmacology and systems thera- was further described in Bioinformatics cells. The raw data and images are avail- peutics at the Mount Sinai School of in January 2010. able to the research community at Medicine who spearheads the project. The movies GATE generates show a www.mitocheck.org. “It allows you to form hypotheses for 2-D honeycomb of small hexagons, “Researchers can go to the database, future experimentation very quickly.” each representing a single gene or pro- do a clustering analysis, and extract the The software, called GATE (Grid tein and colored red (for increased genes that are most interesting from Analysis of Time-Series Expression), expression) or green (for decreased). their research question point of view,” was originally designed to analyze clus- The hexagons are clustered near other says Jan Ellenberg, PhD, head of the tered gene and protein expression data genes or proteins with similar behavior Cell Biology and Biophysics Unit at the taken at various time points during stem patterns in the experiments. When the European Molecular Biology Laboratory cell development, Ma’ayan says. This movie plays, waves of color shift across and senior author on the paper pub- 4 BIOMEDICAL COMPUTATION REVIEW Summer 2010 www.biomedicalcomputationreview.org lished in Nature on and transcription factors to describe April 1, 2010. the information flow within cells. The research The work serves as part of a larger addressed an age-old effort within Gerstein’s group to develop problem in the study real-world analogies to explain how bio- of cell division, logical systems use and process informa- Ellenberg says. “We tion. Previously, the group had shown didn’t know all the that hierarchies in biological regulatory genes or the proteins systems resemble directed social struc- involved,” he says. tures such as governments and corpora- “So we decided that tions. That study, published in PNAS in we had to do this gene 2006, found that “middle managers discovery ourselves.” rule,” Gerstein says. Transcription fac- First, Ellenberg and This microscopy image captures the mitotic spindle (green) tors in the middle layers of the networks his colleagues in the and the chromosomes (red) of a dividing cell. EMBL have the most regulatory interactions Mitocheck consor- researchers videotaped mitosis for 22,000 different gene with other genes. “The genes in the tium developed the knockouts. Videos and data for all 22,000 genes are available middle are much more essential. If you technology to do sys- at www.mitocheck.org. Courtesy of Thomas Walter & Jutta knock them out, the organism is much tematic high through- Bulkescher / EMBL. more likely to die.” put screens of multiple In a paper published online in PNAS samples of all 22,000 human genes and at the Broad Institute, who was not in March 2010, Gerstein and his col- then visually match each knockout to a involved in the research. “[The insights leagues took that work a step farther, phenotype. They relied on RNA inter- into mitosis are] just the tip of the ice- seeking to understand how cells avoid ference to knock out each of the berg of the knowledge that will be failure at the sites of middle manager approximately 22,000 individual genes. extracted from this single experiment,” bottlenecks in five species ranging from They then printed more than 384 of Carpenter says. E. coli to humans. First, they identified these samples at a time on microarray The researchers’ next project, called which genes are regulated by other chips. Because mitosis occurs transient- Mitosys, will explore the molecular genes in each organism. They then ly (approximately once every 24 activity of the 572 mitosis-related genes. stacked the levels of regulators in hierar- hours), the researchers developed —By Sarah A. Webb, PhD chies and placed them between two microscopes to capture movies of each extreme types of social hierarchies, auto- sample from four such microarrays in cratic and democratic, and showed cel- parallel over the course of 48 hours. Cells’ Collaborative lular regulatory hierarchies have "inter- Analysis of so much visual data— Middle Management mediate" structures. They found that, in nearly 200,000 movies—required Like corporate and governmental all five organisms, coregulation happens supervised machine learning. First, a organizations, cells rely on middle man- most at the middle level and least at the human expert annotated examples of agers to keep things running smoothly. bottom. And more complex organisms different morphologies observed within These “middle managers” function as a exhibit more collaborative, “democrat- the movies. A computer then extracted critical bridge that controls the flow of ic” regulatory structures with more a numerical signature with 200 differ- information traffic. According to recent interconnections. For example, yeast ent parameters that it correlated with research, however, the middle managers has about one regulator for every 25 tar- those characteristics. After iterative often partner with one another, ensur- gets whereas in humans the ratio is training with movies of just 3000 dif- ing that the failure of one manager does- much smaller, about one to 10. ferent individual cells, the computer n’t bring down the entire organization. “The parallels between government analyzed additional movies and identi- Moreover, this partnering becomes more structure and regulatory network struc- fied phenotypes with 90 percent accu- extensive in more complex organisms. ture are provocative,” says Trey Ideker, racy. The researchers also developed “Understanding the system isn’t PhD, associate professor of medicine and new distance measures for clustering about the function of the individual bioengineering at the University of algorithms to categorize the differences parts. [It’s about] understanding the California, San Diego, who was not in cell division behavior. importance of these information flow involved with the study. One question, The scale of these experiments and bottlenecks and how natural systems says M. Madan Babu, PhD, an investiga- the use of time-lapse imaging over two get around them,” says Mark Gerstein, tor in the MRC-Laboratory of Molecular days are “unparalleled and nothing short PhD, professor of bioinformatics at Biology at the University of Cambridge, of phenomenal,” says Anne Carpenter, Yale University. He and his colleagues is the function of these hierarchies with- PhD, director of the Imaging Platform have been studying networks of genes in a cell. “Are they really important? Or Published by Simbios, the NIH National Center for Physics-Based Simulation of Biological Structures 5 NewsBytes are they something that is emergent have a better chance of eventually because of the complexity of the system landing in our lungs. and has no consequence whatsoever?” “The conventional wisdom is that Regulatory networks are definitely the thermal plume from your body pro- important for organism function, tects you from particles falling from Gerstein notes. So the question of above,” says John B. McLaughlin, whether the networks emerged in PhD, professor of chemical and bio- response to complex roles or the sys- molecular engineering at Clarkson The positions of 2-micrometer particles University and coauthor of the study. inside a 20-degree-Celsius room with a man- “We found that, in our small room at nequin heated to 25 degrees Celsius, three least, that is not true.” Such findings minutes after particles were released can help engineers design better venti- through a floor event. In this simulation, 31 lation systems, McLaughlin says. out of 1000 particles fell directly onto the “Studies have shown that schoolchild- mannequin’s warm body; none managed to ren learn more and office workers are leave the room through the ceiling vent. Yet more productive in environments when the mannequin was the same temper- where the concentration of particles in ature as the room, no particles fell onto the the air is very low.” body, and 160 out of 1000 particles escaped. Airflow dynamics are notoriously Results were similar for simulations with 10- tough to model computationally, large- micrometer-diameter particles. ly because of the huge range of physi- cal scales in equations for turbulent meeting in Portland, Oregon. fluids. McLaughlin and his colleagues “The computational and the experi- used a direct numerical simulation mental go hand in hand when studying approach that offers accuracy but complex turbulent flows such as those requires intensive computational around human beings,” says Mark N. resources. Their computational mod- Glauser, PhD, professor of mechanical els of airflow and particle paths were and aerospace engineering at Syracuse built in a 4.8-square-meter virtual University, whose empirical results Diagrams of hierarchical networks: In an room at two-centimeter resolution helped guide McLaughlin’s modeling. autocratic network, such as the military, using three-millisecond time steps over Fundamentally, experiments can help there is a clear chain of command. In a dem- about three minutes of total simulated validate computational models and ocratic network, many members interact and time. In each simulation, a mannequin give physical insights that spur new regulate each other. And in an intermediate sits motionless in the middle of the simulations. “Then the simulation network, such as exists within a law firm and room. A stream of air suffused with tools can be used to probe a broader many cells, the hierarchy shares features of particles—each with the density of range of parameter space ‘virtually,’ as both types. As biological organisms become sand and about the size of a grain of well as look in more detail at flow increasingly complex, their organization pollen—shoots up through a floor vent physics,” Glauser says. For example, the becomes more democratic. in front of the chair. Particles fan out models from McLaughlin’s team can throughout the room, with a ceiling track individual particles in a turbulent tem’s complexity allows organisms to vent as the only exit. flow—a feat that’s nearly impossible in carry on these complex interaction is a In simulations where the man- real-life experiments. “chicken and egg type of issue.” nequin was bestowed with realistic —By Regina Nuzzo, PhD —By Sarah A. Webb, PhD body heat, researchers could see the hot air surging off the body and inter- Hot Bodies a Lure acting with particulates. This thermal Brain Folding plume pulled rising particles directly In the four months before birth, a for Unseen Specks into the mannequin’s breathing zone. fetus’s brain grows from a smooth tube We can’t see them, but tiny parti- At the same time, the plume blocked of neurons into a highly crinkled, con- cles—dust, pollen, microbes, and the the path of particles traveling near the volved mass of tissue. Because the cere- like—swirl around us in complicated, ceiling, forcing them to fall down into bral cortex has a surface area nearly turbulent pathways. New numerical the mannequin’s personal space, dou- three times as big as that of its skull cav- simulations suggest that, at least in bling the trapping effect of the plume. ity, scientists have proposed that this tiny indoor spaces, our body heat may The work was presented in March 2010 real-estate-space squeeze is what drives pull them even closer, where they at the American Physical Society the brain’s folding process. Now results 6 BIOMEDICAL COMPUTATION REVIEW Summer 2010 www.biomedicalcomputationreview.org from a computational three-dimension- geometry of the cortex. ers, this imbalance subtly shapes what al geometric model agree that the skull The team simulated how the cortex kinds of folds become most prominent. does help guide the wrinkling—but grows under various conditions: with- Computational models can help they also suggest that a growing brain out a skull, with a skull of fixed size, explain normal brain development as folds up regardless of its container. and with a skull that grows at the same well as what happens when things go “Mechanical constraints imposed time as the brain does. As expected, wrong, says Bernard S. Chang, MD, by the skull are important regulators,” brains grown in a skull were more con- assistant professor of neurology at says Tianming Liu, PhD, assistant pro- voluted than those allowed to develop Harvard Medical School. For example, fessor of computer science at unfettered. But even without a skull to in some forms of microcephaly, the University of Georgia and lead author confine it, a cortex will still fold in on brain surface is almost completely on the study, which was published in itself, results showed. This happens as smooth with no folds; in others, the May 2010 in the Journal of Theoretical a natural response in a fast-growing folding is normal. “A model that pre- Biology. “But our simulations indicate cortex, as the tissue attempts to reduce dicts how folding is affected by the that skull constraint is not necessarily the increasing mechanical tension skull’s physical constraints might help the dominant mechanism.” among axons, dendrites, and neu- us to understand why some patients The computational model under- roglia, Liu says. have one form and not another,” he Growth of the cortex under different assumptions. From left to right, a fetus' developing skull). Major cortical folds developed much earli- the images show simulated development of the cortex over time. The er and faster during simulations with skull constraints. But the cortex cortex grows (a) within a skull of fixed size, (b) without a skull, or (c) increases its surface area and convolutes itself to reduce the fast- within a skull that also grows at the same time (which corresponds to growing internal tension, with or without skull constraint. neath the simulations had two main Tweaking other parameters in the says. Since animal models don’t cap- features: geometric constraints of the model revealed how cellular growth ture the complexity of the human skull, and partial differential equations affects these folding patterns. When brain, and doing repeated MRIs of that model biological processes driving neurons themselves grow rapidly — developing fetuses for research isn’t fea- the growth of neurons. To start off the during synapse development and neu- sible, Chang says, “we need to rely on simulation, researchers used MRI data ron dendritic projection, for example— these theoretical models as tools to from the brains of two human fetuses; the cortical folding increases dramati- help us understand what we’re observ- then solutions to the differential equa- cally too. And when certain areas of ing clinically.” tions guided the changing surface the cortex grow more quickly than oth- —By Regina Nuzzo, PhD ■ Published by Simbios, the NIH National Center for Physics-Based Simulation of Biological Structures 7
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