The first moments of life unfold with incredible precision. Now researchers from Princeton have discovered new findings on the mechanisms behind this precision with the aid of mathematical tools and the help of fruit flies.
In a new study published in the journal CellThe team showed that cells determine exactly where they should be and therefore which body parts they will become by optimizing the use of all available information from the genetic code. With this optimization, each cell can position itself within the width of one cell where it should be located, instead of making mistakes that are corrected later.
The study also shows that a complex biological system can work according to a mathematically optimal process. The team was able to predict the placement of cells to 1 percent of their actual locations along the length of the embryo, demonstrating that biological behavior can be calculated and predicted on the basis of theoretical principles.
"The information needed to specify precise cell sites – and thus which body parts they will become – is present and used in the earliest development stages of fruit flies," said Thomas Gregor, associate professor of physics and the Lewis-Sigler Institute for integrative genomics. "This is in stark contrast to the prevailing view that the position of the cells is gradually being refined over time."
"The theoretical idea is very simple, meaning that every cell uses all the information it can extract from the relevant genes," says William Bialek, John Archibald Wheeler / Battelle Professor of Physics and the Lewis-Sigler Institute for Integrative Genomics. "Something we've known for a while, but always amaze, is that the whole system is incredibly accurate, and this fact has led us to believe that the cells use all the information they can."
Cells take indications of genes, or more specifically, of the protein molecules that produce those genes. But do the cells use all the information to get everything right? Or is the system messy, with faults that have been repaired before irreparable damage has been caused to the embryo?
The question was exactly the type of problem with the broad lines that the team of biologists and physicists, who have been working together since the beginning of the 2000s, like to tackle.
Thanks to previous work by team member Eric Wieschaus, the Squibb Professor in Molecular Biology and professor in molecular biology and the Lewis-Sigler Institute for Integrative Genomics, scientists know exactly which genes and molecules are involved in the creation of streaks in the embryo that the segments marking the fly larva. If something goes wrong, the stripes are in the wrong places or not at all.
"The experiment defines the first truly quantitative measure of how many information cells are available for crucial development decisions and how much of that information they actually use," says Wieschaus, researcher at the Howard Hughes Medical Institute, and earned the Nobel Prize in Physiology of 1995 or Medicinal Product. to the genetic control of early embryonic development.
"This gives us a great tool to understand how decision making in biology really works, one that is useful at levels ranging from the way proteins bind to DNA to how new biological pathways arise and compete during evolution," he said. .
Mariela Petkova, a co-lead author of the study, was an undergraduate who worked in Gregor's laboratory when she asked how the cells use genetic and molecular information to find their locations and fate.
"We take seriously the idea that cells in a developing embryo need to" know "their position to make the right development decisions," said Petkova, Class of 2012. "One can imagine cells as GPS devices that, instead of satellite signals, are molecular collect those to find their locations. We can decode how such molecular signals specify positions along the length of the early-flying embryo. & # 39;
Scientists have known for a long time that the stripes arise as a result of a waterfall of steps that starts with the flying mother, who puts in each egg an instruction set that consists of three different types of signaling molecules.
These signaling molecules spread through the body of the embryo and form concentration gradients that activate four so-called "gap" genes. The expression of these genes produces protein molecules that act on DNA segments known as amplifiers to drive "pair line" genes to produce the striped pattern.
Petkova made detailed measurements of the gap gene expression and the exact amounts of molecules produced in the cells along the long body axis. She started the research as part of her thesis and then graduated for a year to continue studying the project. She ended the work during breaks of her studies at the Graduate Program of Biophysics at Harvard University.
With these measurements in hand, the theoretical physics part of the team was able to model how the cells use information to find their place in the embryo. The team consisted of the co-first author Gašper Tkačik, who received his Ph.D. in Princeton physics in 2007 and is now a faculty member of the Institute of Science and Technology Austria.
There are many ways in which the cells can use the information encoded in the molecules. But the researchers chose to assume that the embryo uses all available information encoded in the molecules. They called this the "optimal decoding approach."
With this assumption, Tkačik and Bialek used a relatively simple mathematical approach to predict where the stripes would arise. The team then compared the predictions with the actual measurements of gap molecules and discovered that they had accurately anticipated the locations of the stripes.
The real evidence came when Petkova studied the eggs that had been laid by flying with mutations in the genes that code for the maternal signaling molecules at the beginning of the cascade. The team accurately predicted how different gene mutations changed the stripe pattern – for example by having part of the stripes disappear or forming in the wrong place.
"We used genetic manipulations to place the gap gene patterns in random order and to take the cells into the grind in thinking that they are somewhere else in the length of the embryo. "Petkova said." We placed these shuffled patterns through our decoder and built decoding cards, which told us where the cells were and where they thought they were. Using these cards we predicted where the embryo's stripes would make. When we looked at these mutant embryos under a microscope we found the stripes at the predicted locations! It was very satisfying. "
The study examines whether it is possible to make robust predictions about biological systems based on theoretical principles, according to the authors.
"This finding gives us theorists the hope that our work in biology will not forever be degraded to appropriate models of data, but actually predicts and quantitatively understands why evolution came with certain solutions," Tkačik said. "This promises, for at least a few examples, that there can be a" predictive theory for biology "- an excellent motivation for future work."
Bialek added: "A characteristic of modern physics is that general theoretical principles can be linked to an experiment with excellent quantitative details," he said. "It was long difficult to come up with this kind of theory – experiment interaction in the physics of biological systems – living beings seemed too complex, too messy. This work is one of the strongest examples of theory experiment comparison I have seen. I had always hoped that we would come to this level, but I did not know when it would happen. "
Wieschaus added: "Most scientists often think that biological processes are inherently sloppy and that cells achieve precision through multiple corrective steps and complicated interactive networks. Such processes certainly exist. Because it is amazing how accurate and reproducible information can be a single step in development, and once that information is there, how evolution and natural selection can push the cells to make the most efficient use of that information. "
The fruit fly (Drosophila melanogaster) is often used to learn general principles of biology that may apply to more advanced organisms such as humans. Whether or not organisms other than the fruit fly adhere to this optimal use of information remains to be seen, said Gregor.
"This research gives us a look at how genetic networks encode information, how networks work together and how they do the calculations they can do," Gregor said. "There are genetic networks that do all kinds of things in biology, so this is certainly a rich area for further exploration."
This work was partially supported by the US National Science Foundation grants PHY-1607612, CCF-0939370 (Center for the Science of Information), and PHY-1734030 (Center for the Physics of Biological Function); by National Institutes of Health scholarships P50GM071508, R01GM077599 and R01GM097275; by the Austrian Science Fund grant FWF P28844; and by an International Predoctoral Fellowship from Howard Hughes Medical Institute.