Common aquatic animals show resistance to radiation

Scientists at Harvard University have found that a common class of freshwater invertebrate animals called bdelloid rotifers are extraordinarily resistant to ionizing radiation, surviving and continuing to reproduce after doses of gamma radiation much greater than that tolerated by any other animal species studied to date.

Because free radicals such as those generated by radiation have been implicated in inflammation, cancer, and aging in higher organisms, the findings — published this week in the Proceedings of the National Academy of Sciences by Harvard’s Matthew Meselson and graduate student Eugene Gladyshev — could stimulate new lines of research into these medically important problems.

“Bdelloid rotifers are far more resistant to ionizing radiation than any of the hundreds of other animal species for which radiation resistance has been examined,” says Meselson, Thomas Dudley Cabot Professor of the Natural Sciences in Harvard’s Faculty of Arts and Sciences. “They are able to recover and resume normal reproduction after receiving a dose of radiation that shatters their genomes, causing hundreds of DNA double-strand breaks which they are nevertheless able to repair.”

Meselson and Gladyshev found that the bdelloid rotifers Adineta vaga and Philodina roseola remained reproductively viable after doses of radiation roughly five times greater than other classes of rotifers and other animals could endure.

Such radiation resistance appears not to be the result of any special protection of DNA itself against breakage, the researchers say, but instead reflects bdelloid rotifers’ extraordinary ability to protect their DNA-repairing machinery from radiation damage.

Roughly a half-millimeter in size and commonly observed under microscopes in high school biology classes, bdelloid rotifers are highly unusual in several regards: They appear to be exclusively asexual, have relatively few transposable genes, and can survive and reproduce after complete desiccation at any stage of their life cycle. Meselson and Gladyshev hypothesize that it’s this last property that explains bdelloids’ apparently unique resistance to radiation.

Bdelloid rotifers have been widely studied since at least 1702, when the renowned Dutch scientist and microscopy pioneer Anton van Leeuwenhoek added water to dust retrieved from a rain gutter on his house and observed the organisms in the resulting fluid. He subsequently described the creatures in a letter to Britain’s Royal Society, which still counts an envelope of van Leeuwenhoek’s rain-gutter dust among its holdings.

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Language of a fly proves surprising

A group of researchers has developed a novel way to view the world through the eyes of a common fly and partially decode the insect’s reactions to changes in the world around it. The research fundamentally alters earlier beliefs about how neural networks function and could provide the basis for intelligent computers that mimic biological processes.

In an article published in the Public Library of Science Computational Biology Journal, Los Alamos physicist Ilya Nemenman joins Geoffrey Lewen, William Bialek and Rob de Ruyter van Steveninck of the Hun School of Princeton, Princeton University and Indiana University, respectively, in describing the research.

The team used tiny electrodes to tap into motion-sensitive neurons in the visual system of a common blowfly. Neurons are nerve cells that emit tiny electric spikes when stimulated. The electrodes detected pulses from the motion-sensitive neurons in the fly. The fly uses the neurons to estimate, and subsequently control, how it moves through the world.

The team harnessed the wired fly into an elaborate turntable-like mechanism that mimics the kind of acrobatic flight a fly might undergo while evading a predator or chasing another fly. The mechanism can spin extremely fast and change velocities quickly. A fly in the mechanism sees changes in the world around it and its motion-sensitive neurons react much in the same way as they would if the insect were actually flying.

Under complex flight scenarios, the fly’s neurons fired very quickly. The researchers looked at the firing patterns and mapped them with a binary code of ones and zeroes, much like computer instructions, or binary messages in digital phone communications.

The team found that the impulses were like a primitive, but very regular “language”—with the neuron firing at precise times depending on what the fly’s visual sensors were trying to tell the rest of the fly about the visual stimulus. When they examined this language, it spoke volumes about how the harnessed fly reacted to its world.

“In this system, the motion-sensitive neurons emit spikes very often and very precisely,” said Nemenman. “Historically, people have observed a lot more random spike intervals. This research is a departure from the traditional understanding in that we see that the precision of spike timing that carries information about the fly’s rotation is a factor of ten higher than even the most daring previous estimates.”

Similar-though-much-simpler experiments on different subjects, including flies, and going back to the seminal work of E. D. Adrian and Yngve Zotterman in 1926, seemed to show that sensory neurons would fire a certain number of impulses during a given period, but that the precise timing of the impulses was largely irrelevant. Nemenman and his team believe the timing of the spikes was not as crucial during those early experiments largely because the artificial stimulation was in some sense unnatural, bordering on the monotonous and predictable.

“Biological organisms have an interest in conserving energy,” Nemenman said. “Fly eyes account for about one-tenth of the fly’s energy consumption. The fly wants to be very efficient, but it costs energy and molecular resources to emit many precise spikes in the neurons.

“If you are presenting simple stimuli where little changes with time, then the most efficient way to encode them may be to generate few randomly positioned spikes, which would be sufficient to convey whatever small changes, if any, happened. Similarly, if the stimulus is unnaturally fast, the neurons may not be able to encode it well.

“However, if you put an organism in an environment with fast and naturally changing velocity profiles, the fly starts using all the bandwidth available to it,” Nemenman said. “The motion-sensitive neuron adjusts its coding strategy and it uses the precise positioning of the spikes to tell the rest of the fly exactly what is happening.”

In addition to the complex motions possible with the team’s apparatus, they conducted their experiment in a wooded setting similar to the fly’s natural environment, adding to the complexity and realism of the experiment.

Nemenman and his colleagues’ research is significant because it re-examines fundamental assumptions that became the basis of neuromimetic approaches to artificial intelligence, such as artificial neural networks. These assumptions have developed networks based on reacting to a number of impulses within a given time period rather than the precise timing of those impulses.

“This may be one of the main reasons why artificial neural networks do not perform anywhere comparable to a mammalian visual brain,” said Nemenman, who is a member of Los Alamos’ Computer, Computational and Statistical Sciences Division. “In fact, the National Science Foundation has recognized the importance of this distinction and has recently funded a project, led by Garrett Kenyon of the Laboratory’s Physics Division, to enable creation of large, next-generation neural networks.”

New understanding of neural function in the design of computers could assist in analyses of satellite images and facial-pattern recognition in high-security environments, and could help solve other national and global security problems.

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