The DNA translation machines in the cell show unexpected complexity, forcing molecular biologists to revise what they thought they knew about ribosomes. In particular, they appear optimized for speed of self-duplication and modularized for flexibility.
Last September, we evaluated a fascinating paper about ribosomes that showed how this molecular machine that translates DNA “requires the orchestrated function of hundreds of proteins” — and that’s just to get to the “pre-ribosome” stage! Ribosomes are marvels of organization and function. Since then, more discoveries have shown additional design features of ribosomes.
A cell doesn’t have all day to build and operate these machines. In July, a paper in Science Advances revised the half-life of RNAs significantly downward. Instead of 5-20 minutes to float around and get translated, most messenger RNAs (mRNAs) last only about 2 minutes before being degraded by complex recycling pathways (see this from the University of Basel). The production rate and decay rate are important factors in gene regulation. So if you think of “orchestrated function” again, the sheet music won’t do any good if the stage isn’t already set up and the players aren’t in their seats.
The ribosome is composed of large RNAs and proteins. The paper doesn’t state the half-life of the ribosomal RNAs, which make up the bulk of the ribosome, but it’s safe to assume the lifetime of each RNA is finite — probably a matter of minutes. An extra reason for assuming this is the rapid doubling of ribosomes during cell division. Before the cell can divide, all the proteins needed by the two daughter cells must be translated. This requirement effectively doubles the work for these machines.
How does the cell prepare for this increased workload? Rather than speed up translation, the ribosomes first duplicate themselves, effectively doubling the production capacity. This means that they have to prepare and assemble all their own RNAs and proteins first. Without efficient ways to accomplish this prerequisite, cell division could be seriously delayed.
An interesting model, published in Nature by Johan Paulsson’s team at Harvard, suggests that “Ribosomes are optimized for autocatalytic production.” They knew that ribosomes are already optimized in three ways. Now, they add a fourth:
Many fine-scale features of ribosomes have been explained in terms of function, revealing a molecular machine that is optimized for error-correction, speed and control. Here we demonstrate mathematically that many less well understood, larger-scale features of ribosomes — such as why a few ribosomal RNA molecules dominate the mass and why the ribosomal protein content is divided into 55–80 small, similarly sized segments — speed up their autocatalytic production. [Emphasis added.]
The authors, as evolutionists, will assume that Darwinian processes achieved this optimization. In their own words, however, we sense their astonishment at what these machines accomplish.
Ribosomes translate sequences of nucleic acids into sequences of amino acids. Their features are therefore typically explained in terms of how they affect translation. However, in recent years it has also become clear that ribosomes are exceptional as products of the ribosomal machinery. Not only do ribosomal proteins (r-proteins) make up a large fraction of the total protein content in many cells, but the autocatalytic nature of ribosome production introduces additional constraints. Specifically, the ribosome doubling time places a hard bound on the cell doubling time, because for every additional ribosome to share the translation burden there is also one more to make. Even for the smallest and fastest ribosomes, it takes at least 6 min, and typically much longer, for one ribosome to make a new set of r-proteins (Supplementary Information); and this estimate does not account for the substantial time that is invested in the synthesis of ternary complexes. This bound seems to explain the observed limits on bacterial growth, because ribosomes must also spend much of their time making other proteins, and shows that ribosomes are under very strong selective pressure to minimize the time they spend reproducing.
Whether “selective pressure” is the mother of invention is debatable to those of us who are Darwin skeptics, but the authors point out something important. The “orchestrated function of hundreds of proteins” has time limits. The conductor is pounding his foot and tapping his baton on the podium, rushing the orchestra to get in place. Imagine how much harder if each player, instrument, chair, and music stand has to make a copy of itself first for a show across town!
Based on observed facts about ribosomal RNAs and proteins, and how quickly they duplicate, the team created a mathematical model based on the assumption that “selective pressure” forces cells to optimize their ribosomes’ doubling time. Although the model worked for fast-reproducing bacteria, they presume the same time pressure constrains eukaryotic cells:
Similar principles might also apply to some eukaryotes, because the ribosomes of eukaryotes are larger and slower. In fact, even organisms in which cell doubling times are not limited by ribosome doubling times would benefit from faster ribosome production, allowing ribosomes to spend more of their time producing the rest of the proteome. This efficiency constraint was recently shown to have broad physiological consequences for cells, and here we demonstrate mathematically that it might also explain many broader features of the ribosome (Fig. 1).
In the figure, they show that ribosomes are dominated by a few large RNAs and lots of small proteins, about 55 to 80 of them of similar size. The reason for this arrangement has long puzzled molecular biologists. According to the new model, ribosomes can reproduce their parts quicker when the proteins are relatively short, and there are lots of them. The existing ribosomes can crank out smaller building blocks faster, and the construction workers can assemble them faster, than if they had to wait for long, complex pieces to arrive.
It’s not necessary to get into the weeds to see the elegance of the solution. Ribosomes assemble faster with more, smaller proteins, reducing the time to duplicate themselves, so that they can get on with their main job of translating all the other proteins the cell needs before dividing. The faster you double the translating machinery, the faster you can double everything else in the cell.
The model also needs to explain why ribosomes include a few large RNAs. Evolutionists have typically invoked the “RNA World” story to suggest that ribosomal RNAs represent transitional forms or vestiges from the origin of life before cells happened upon ways to make proteins. Paulsson’s model suggests a different reason — a functional reason. RNAs only need to be transcribed, not translated. RNA enzymatic activity is not as efficient as protein, but RNA is quicker to make. The cell, therefore, is better off using it when time is of the essence.
The above analysis suggests a great efficiency advantage of using rRNA [ribosomal RNA] over protein, whenever chemically possible, and so could explain why ribosomes defy the general rule that enzymes are made mostly of protein (Fig. 1). This finding does not mean that the role of rRNA is merely to ensure appropriate overall dimensions of the ribosome; however, it does provide a fundamental reason for why proteins must be used sparingly in the ribosome, for example, to increase accuracy or speed up translation, whereas rRNA should be used wherever possible without compromising function. If even one-quarter of the rRNA mass were replaced with r-protein without increasing translation rates, many bacteria would not be able double as quickly as they do (Fig. 4b).
Do you see optimization (a form of intelligent design) at work? The authors go into more detail about why rRNAs must be large. Their model shows that small rRNAs, unlike the small ribosomal proteins, would actually slow down duplication. Suffice it to say that the observed ratio of rRNA to ribosomal protein increases the efficiency by two orders of magnitude. Here’s a pithy analogy from a layman’s summary of the paper at Science Daily:
“An analogy for our findings would be to think of ribosomes not as a group of carpenters who merely build a lot of houses, but as carpenters who also build other carpenters,” Paulsson said. “There is then an incentive to divide the job into many small pieces that can be done in parallel to more quickly assemble another complete carpenter to help in the process.”
One other mystery about ribosomes might be solved by looking at it as an optimization problem: why do ribosomes vary? Mitochondrial ribosomes differ from those in the cytosol. Eukaryotic ribosomes differ from those of bacteria. If they perform the same function, why aren’t they all the same? Here’s a paper in PLOS ONE from last November that opens a window on a possible reason: ribosome structure is modularized. In “The Modular Adaptive Ribosome,” a team from India says this:
The ribosome is an ancient machine, performing the same function across organisms. Although functionally unitary, recent experiments suggest specialized roles for some ribosomal proteins. Our central thesis is that ribosomal proteins function in a modular fashion to decode genetic information in a context dependent manner.
Interested readers can delve further into this open-access paper to see why ribosomes vary in different cell types or different environments. “A clear example is nervous tissue that uses a ribosomal protein module distinct from the rest of the tissues in both mice and humans,” they say. “Our results suggest a novel stratification of ribosomal proteins that could have played a role in adaptation, presumably to optimize translation for adaptation to diverse ecological niches and tissue microenvironments.”
When it comes to ribosomes, it appears to be a case of optimization all the way down.
Let’s give the last word to the Science Daily article.
Rather than being mere relics of an evolutionary past, the unusual features of ribosomes thus seem to reflect an additional layer of functional optimization acting on collective properties of its parts, the team writes.
“While this study is basic science, we are addressing something that is shared by all life,” Paulsson said. “It is important that we understand where the constraints on structure and function come from, because like much of basic science, it is unpredictable what the consequences of new knowledge can unlock in the future.”
Notice how that downplays evolution’s role, in spite of the authors’ Darwinian views. It also, even if not intending to do so, supports a design pespective, while showing how such a focus leads to productive science.
Image credit: University of Basel, Biozentrum.