Friday, September 4, 2015

Geneticist studies how plants cope with drought

Click here if video does not appear on screen.

By Carol Clark

California produces two-thirds of the fresh fruits and vegetables consumed in the U.S. As the worst drought in the state’s history continues, it is turning into a testing ground for how the world will cope with the clash of growing populations, dwindling water resources and a changing climate.

“California has all of these water-intensive crops growing in a drought-stricken area where the groundwater is also drying up,” says Roger Deal, a geneticist at Emory University who researches the ways plants build and adapt their bodies. “At the same time, the climate is changing. Obviously, something has got to give.”

Deal is among a consortium of scientists, funded by the National Science Foundation’s Plant Genome Research program, who are doing collaborative studies on how plants cope with weather extremes.

“If you look across a range of different plant species they have very different levels of tolerance to drought,” Deal says. “There is clearly something genetic and physiological about those differences. We’re trying to understand the mechanisms at play for how plants deal with the stresses of weather extremes, and how they succeed or don’t succeed.”

Medicago truncatula
One group in the consortium is looking at strains of rice, while another is focused on two different species of tomatoes: One wild and one domestic. The Deal lab is researching Medicago truncatula, a close relative of alfalfa.

Alfalfa is an important forage crop for livestock around the world and is also part of the legume family, so it serves as a model for an entire group of plants that are agriculturally relevant to humans.

The last common ancestor between rice and alfalfa goes back at least 300 million years. The consortium is looking at plants that cover this huge evolutionary span of time to see similarities and differences in the type of stress responses in different cell types in roots – the first line of a plant’s defense.

“Plants can actually remember when they’ve been exposed to drought,” Deal says. “If you restrict the amount of water an alfalfa plant receives, it’s going to begin to wilt. Then, if you water it and bring it back to life, it’s basically more resistant to drought. We’re trying to learn the basis of this remembrance. Plants don’t have a brain, but somehow their cells remember when they’ve been exposed to drought so they can be ready when it happens again.”

Research into plant genetics is only one aspect of what we may need to do to cope in a world where weather extremes are becoming more common. The geography of agriculture may also have to change, along with people’s eating habits.

“We’ve gotten into this situation where we’re completely cut off from where our food comes from,” Deal says. “When we go to the grocery story, we expect to have a huge variety of fresh fruits and vegetables available, no matter the season. Maybe we should only be getting fresh peaches in the summer.”

Image of Medicago truncatula via ninjatacoshell/Wikipedia

How zinnias shaped a budding biologist

Monday, August 31, 2015

Why women rule, and other hot science topics at the Decatur Book Festival

Illustration: Don Morris

Women can forget about equality with men, warns Emory anthropologist Mel Konner.

It’s even better than that. Why should women embrace mere equality when their movement is toward superiority? It is maleness that has Konner worried in his latest book, “Women After All: Sex, Evolution and the End of Male Supremacy,” which looks at the history and future of gender and power dynamics.

Konner will be one of the featured authors in the ever-popular Science track of the Decatur Book Festival this weekend. He’ll take the stage at 3 pm on Saturday, September 5, at the Marriot Conference Center.

The last line of Konner’s book jacket reads: “Provocative and richly informed, ‘Women After All’ is bound to be controversial across the sexes.”

As Konner acknowledges on his personal web site, the first murmurings came about after a short adaptation of the book ran in the Wall Street Journal. Hundreds of angry men responded within a couple of days. His wife, home alone during that period, double-locked the door. Konner’s editor at the Wall Street Journal apologized for failing to instruct him not to read the comments.

For his part, Konner is hiding in plain sight, saying “Clearly, I’ve touched a nerve, and I’m happy about that.”

Konner is clearly genuine when he talks about a future that his grandson will inhabit, a “new world” that “will be better for him because women help run it.”

You can read more about Konner’s book in the latest issue of Emory Magazine.

Another provocative issue at the intersection of science and society is explored in “Vaccine Nation: America’s Changing Relationships with Immunization,” by Emory historian Elena Conis. She will discuss her book at 4:15 pm on Saturday at the Marriott Conference Center.

Tuesday, August 25, 2015

Biophysicists take small step in quest for 'robot scientist'

The researchers dubbed their algorithm "Sir Isaac," in a nod to one of the greatest scientists of all time, Sir Isaac Newton. 

By Carol Clark

Biophysicists have taken another small step forward in the quest for an automated method to infer models describing a system’s dynamics – a so-called robot scientist. Nature Communications published the finding – a practical algorithm for inferring laws of nature from time-series data of dynamical systems.

“Our algorithm is a small step,” says Ilya Nemenman, lead author of the study and a professor of physics and biology at Emory University. “It could be described as a toy version of a robot scientist, but even so it may have practical applications. For the first time, we’ve taught a computer how to efficiently search for the laws that underlie arbitrary, natural dynamical systems, including complex, non-linear biological systems.”

Nemenman’s co-author on the paper is Bryan Daniels, a biophysicist at the University of Wisconsin.

Everything that is changing around us and within us – from the relatively simple motion of celestial bodies, to weather and complex biological processes – is a dynamical system. A large part of science is guessing the laws of nature that underlie such systems, summarizing them in mathematical equations that can be used to make predictions, and then testing those equations and predictions through experiments.

“The long-term dream is to harness large-scale computing to make the guesses for us and speed up the process of discovery,” Nemenman says.

Isaac Newton contemplates gravity beneath an apple tree. The intuition of a genius like Newton is one quality that distinguishes human intelligence from even the highest-powered computer and algorithmic program.

While the quest for a true robot scientist, or computerized general intelligence, remains elusive, this latest algorithm represents a new approach to the problem. “We think we have beaten any automated-inference algorithm that currently exists because we focus on getting an approximate solution to a problem, which we can get with much less data,” Nemenman says.

In previous research, John Wikswo, a biophysicist at Vanderbilt University, along with colleagues at Cornell University, applied a software system to automate the scientific process for biological systems.

“We came up with a way to derive a model of cell behavior, but the approach is complicated and slow, and it is limited in the number of variables that it can track – it can’t be scaled to more complicated systems,” Wikswo says. “This new algorithm increases the speed of the necessary calculation by a factor of 100 or more. It provides an elegant method to generate compact and effective models that should allow prediction and control of complex systems.”

Nemenman and Daniels dubbed their new algorithm “Sir Issac.”

The real Sir Isaac Newton serves as a classic example of how the scientific method involves forming hypotheses, then testing them by looking at data and experiments. Newton guessed that the same rules of gravity applied to a falling apple and to the moon in orbit. He used data to test and refine his guess and generated the law of universal gravitation.

To test their algorithm, Nemenman and Daniels created an artificial, model solar system by generating numerical trajectories of planets and comets that move around a sun. In this simplified solar system, only the sun attracted the planets and comets.

Images of the moon by NASA's Galileo spacecraft. Everything that is changing around us and within us – from the relatively simple motion of celestial bodies, to weather and complex biological processes – is a dynamical system.

“We trained our algorithm how to search through a group of laws which were limited enough to be practical, but also flexible enough to explain many different dynamics,” Nemenman explains. “We then gave the algorithm some simulated planetary trajectories, and asked it what makes these planets move. It gave us the universal gravitational force. Not perfectly, but with very good accuracy. The error was just a few percent.”

The algorithm also figured out that force changes velocity, not the position directly. “It gets Newton’s First Law,” Nemenman says, “the fact that in order to predict the possible trajectory of a planet, whether it stays near the sun or flies off into infinity, just knowing its initial position is not enough. The algorithm understands that you also need to know the velocity.”

While most modern-day high school student know Newton’s First Law, it took humanity 2,000 years beyond the time of Aristotle to discover it.

One limitation of the algorithm is inexactness. Getting an approximate model, however, is beneficial as long as the approximation is close enough to make good predictions, Nemenman says.

“Newton’s laws are also approximate, but they have been remarkably beneficial for 350 years,” he says. “We’re still using them to control everything from electron microscopes to rockets.”

Getting an exact description of any complex dynamical system requires large amounts of data, he adds. “In contrast, with our algorithm, we can get an approximate description by using just a few measurements of a system. That makes our method practical.”

The researchers demonstrated, for example, that the algorithm can infer the dynamics of a caricature of an immune receptor in a leukocyte. This type of model could lead to a better understanding of the time-course for the response to an infection or a drug.

In another experiment, the researchers fed the algorithm data on concentrations of just three different species of chemicals involved in glycolysis in yeast. The algorithm generated a model that makes accurate predictions for the full system of this basic metabolic process to consume glucose, which involves seven chemical species.

“If you applied other methods of automatic inference to this system it would typically take tens of thousands of examples to reliably generate the laws that drive these chemical transformations,” Nemenman says. “With our algorithm, we were able to do it with fewer than 100 examples.”

With their experimental collaborators, the researchers are now exploring whether the algorithm can model more complex biological processes, such as the dynamics of insulin secretion in the pancreas and its relationship to the onset of a disease like diabetes. “The biology of insulin secreting cells is extremely complex. Understanding their dynamics on multiple scales is going to be difficult, and may not be possible for years with traditional methods,” Nemenman says. “But we want to see if we can get a good enough approximation with our method to deliver a practical result.”

The intuition of a genius mind like that of Isaac Newton is one quality that distinguishes human intelligence from even the highest-powered computer and algorithmic program.

“You can’t give a machine intuition – at least for now,” Nemenman says. “What we’re hoping we can do is get our computer algorithm to spit out models of phenomena so that we, as scientists, can use them and our intuition to make useful generalizations. It’s easier to generalize from models of specific systems then it is to generalize from various data sets directly.”

Physicists eye neural fly data, find formula for Zipf's law
Biology may not be so complex after all

Friday, August 21, 2015

Chestnut leaves yield extract that disarms deadly bacteria

Ethnobotanist Cassandra Quave collecting chestnut leaf specimens in the field in Italy. Photo by Marco Caputo.

By Carol Clark

Leaves of the European chestnut tree contain ingredients with the power to disarm dangerous staph bacteria without boosting its drug resistance, scientists have found.

PLOS ONE is publishing the study of a chestnut leaf extract, rich in ursene and oleanene derivatives, that blocks Staphlococcus aureus virulence and pathogenesis without detectable resistance.

The use of chestnut leaves in traditional folk remedies inspired the research, led by Cassandra Quave, an ethnobotanist at Emory University. “We’ve identified a family of compounds from this plant that have an interesting medicinal mechanism,” Quave says. “Rather than killing staph, this botanical extract works by taking away staph’s weapons, essentially shutting off the ability of the bacteria to create toxins that cause tissue damage. In other words, it takes the teeth out of the bacteria’s bite.” 

The discovery holds potential for new ways to both treat and prevent infections of methicillin-resistant S. aureus, or MRSA, without fueling the growing problem of drug-resistant pathogens. 

Antibiotic-resistant bacteria annually cause at least two million illnesses and 23,000 deaths in the United States, according to the Centers for Disease Control and Prevention. MRSA infections lead to everything from mild skin irritations to fatalities. Evolving strains of this “super bug” bacterium pose threats to both hospital patients with compromised immune systems and young, healthy athletes and others who are in close physical contact.

Quave researches the interactions of people and plants – a specialty known as ethnobotany.

“We’ve demonstrated in the lab that our extract disarms even the hyper-virulent MRSA strains capable of causing serious infections in healthy athletes,” Quave says. “At the same time, the extract doesn’t disturb the normal, healthy bacteria on human skin. It’s all about restoring balance.”

Quave, who researches the interactions of people and plants – a specialty known as ethnobotany – is on the faculty of Emory’s Center for the Study of Human Health and Emory School of Medicine’s Department of Dermatology. She became interested in ethnobotany as an undergraduate at Emory. 

For years, she and her colleagues have researched the traditional remedies of rural people in Southern Italy and other parts of the Mediterranean. “I felt strongly that people who dismissed traditional healing plants as medicine because the plants don’t kill a pathogen were not asking the right questions,” she says. “What if these plants play some other role in fighting a disease?”

Hundreds of field interviews guided her to the European chestnut tree, Castanea sativa. “Local people and healers repeatedly told us how they would make a tea from the leaves of the chestnut tree and wash their skin with it to treat skin infections and inflammations,” Quave says.

For the current study, Quave teamed up with Alexander Horswill, a microbiologist at the University of Iowa whose lab focuses on creating tools for use in drug discovery, such as glow-in-the-dark staph strains.

The researchers steeped chestnut leaves in solvents to extract their chemical ingredients. “You separate the complex mixture of chemicals found in the extract into smaller batches with fewer chemical ingredients, test the results, and keep honing in on the ingredients that are the most active,” Quave explains. “It’s a methodical process and takes a lot of hours at the bench. Emory undergraduates did much of the work to gain experience in chemical separation techniques.”

The work produced an extract of 94 chemicals, of which ursene and oleanene based compounds are the most active.

Tests showed that this extract inhibits the ability of staph bacteria to communicate with one another, a process known as quorum sensing. MRSA uses this quorum-sensing signaling system to manufacture toxins and ramp up its virulence.

“We were able to trace out the pathways in the lab, showing how our botanical extract blocks quorum sensing and turns off toxin production entirely,” Quave says. “Many pharmaceutical companies are working on the development of monoclonal antibodies that target just one toxin. This is more exciting because we’ve shown that with this extract, we can turn off an entire cascade responsible for producing a variety of different toxins.”

A single dose of the extract, at 50 micrograms, cleared up MRSA skin lesions in lab mice, stopping tissue damage and red blood cell damage. The extract does not lose activity, or become resistant, even after two weeks of repeated exposure. And tests on human skin cells in a lab dish showed that the botanical extract does not harm the skin cells, or the normal skin micro-flora.

The Emory Office of Technology Transfer has filed a patent for the discovery of the unique properties of the botanical extract.

The researchers are doing further testing on individual components of the extract to determine if they work best in combination or alone. “We now have a mixture that works,” Quave says. “Our goal is to further refine it into a simpler compound that would be eligible for FDA consideration as a therapeutic agent.”

Potential uses include a preventative spray for football pads or other athletic equipment; preventative coatings for medical devices and products such as tampons that offer favorable environments for the growth of MRSA; and as a treatment for MRSA infections, perhaps in combination with antibiotics.

“It’s easy to dismiss traditional remedies as old wives’ tales, just because they don’t attack and kill pathogens,” Quave says. “But there are many more ways to help cure infections, and we need to focus on them in the era of drug-resistant bacteria.”

The research was funded by the NIH National Center for Complementary and Integrative Health. In addition to Quave and Horswill, the study’s authors include: Emory researchers James Lyles and Kate Nelson; and Jeffery Kavanaugh, Corey Parlet, Heidi Crosby and Kristopher Heilmann from the University of Iowa.

Her patient approach to health

Thursday, August 13, 2015

Marks on 3.4-million-year-old bones not due to trampling, analysis confirms

Detail of the marks on a fossilized rib bone, one of the two controversial bones. “The best match we have for the marks, using currently available data, would still be butchery with stone tools," says anthropologist Jessica Thompson. Photo by Zeresenay Alemseged.

By Carol Clark

Marks on two 3.4 million-year-old animal bones found at the site of Dikika, Ethiopia, were not caused by trampling, an extensive statistical analysis confirms. The Journal of Human Evolution published the results of the study, which developed new methods of fieldwork and analysis for researchers exploring the origins of tool making and meat eating in our ancestors.

“Our analysis clearly shows that the marks on these bones are not characteristic of trampling,” says Jessica Thompson, an assistant professor of anthropology at Emory University and lead author of the study. “The best match we have for the marks, using currently available data, would still be butchery with stone tools.”

The 12 marks on the two specimens – a long bone from a creature the size of a medium antelope and a rib bone from an animal closer in size to a buffalo – most closely resemble a combination of purposeful cutting and percussion marks, Thompson says. “When these bones were hit, they were hit with enormous force and multiple times.”

The paper supports the original interpretation that the damage to the two bones is characteristic of stone tool butchery, published in Nature in 2010. That finding was sensational, since it potentially pushed back evidence for the use of stone tools, as well as the butchering of large animals, by about 800,000 years.

The Nature paper was followed in 2011 by a rebuttal in the Proceedings of the National Academy of Sciences (PNAS), suggesting that the bones were marked by incidental trampling in abrasive sediments. That sparked a series of debates about the significance of the discovery and whether the bones had been trampled.

Anthropologist Jessica Thompson at work in the field in Africa. She specializes in the study of what happens to bones after an animal dies.

For the current paper, Thompson and her co-authors examined the surfaces of a sample of more than 4000 other bones from the same deposits. They then used statistical methods to compare more than 450 marks found on those bones to experimental trampling marks and to the marks on the two controversial specimens.

“We would really like to understand what caused these marks,” Thompson says. “One of the most important questions in human evolution is when did we start eating meat, since meat is considered a likely explanation for how we fed the evolution of our big brains.”

Evidence shows that our genus, Homo, emerged around 2.8 million years ago. Until recently, the earliest known stone tools were 2.6 million years old. Changes had already been occurring in the organization of the brains of the human lineage, but after this time there was also an increase in overall brain size. This increased size has largely been attributed to a higher quality diet.

While some other apes are known to occasionally hunt and eat animals smaller than themselves, they do not hunt or eat larger animals that store abundant deposits of fat in the marrow of their long bones. A leading hypothesis in paleo-anthropology is that a diet rich in animal protein combined with marrow fat provided the energy needed to fuel the larger human brain.

The animal bones in the Dikika site, however, have been reliably dated to long before Homo emerged. They are from the same sediments and only slightly older than the 3.3-million-year-old fossils unearthed from Dikika belonging to the hominid species Australopithecus afarensis.

Thompson specializes in the study of what happens to bones after an animal dies. “Fossil bones can tell you stories, if you know how to interpret them,” she says.

A whole ecosystem of animals, insects, fungus and tree roots modify bones. Did they get buried quickly? Or were they exposed to the sun for a while? Were they gnawed by a rodent or chomped by a crocodile? Were they trampled on sandy soil or rocky ground? Or were they purposely cut, pounded or scraped with a tool of some kind?

"Fossil bones can tell you stories, if you know how to interpret them," Jessica Thompson says. For instance, the marks on this fossilized bone from the Dikika site are diagnostic of punctures made by crocodile teeth. Photo by Jessica Thompson.

One way that experimental archeologists learn to interpret marks on fossil bones is by modifying modern-day bones. They hit bones with hammer stones, feed them to carnivores and trample them on various substrates, then study the results.

Based on knowledge from such experiments, Thompson was one of three specialists who diagnosed the marks on the two bones from Dikika as butchery in a blind test, before being told the age of the fossils or their origin.

The PNAS rebuttal paper, however, also used experimental methods and came to the conclusion that the marks were characteristic of trampling.

Thompson realized that data from a larger sample of fossils were needed to chip away at the mystery.

The current paper investigated with microscopic scrutiny all non-hominin fossils collected from the Hadar Formation at Dikika. The researchers collected a random sample of fossils from the same deposits as the controversial specimens, as well as nearby deposits. They measured shapes and sizes of marks on the fossil bones. Then they compared the characteristics of the fossil marks statistically to the experimental marks reported in the PNAS rebuttal paper as being typical of trampling damage. They also investigated the angularity of sand grains at the site and found that they were rounded – not the angular type that might produce striations on a trampled bone.

“The random population sample of the fossils provides context,” Thompson says. “The marks on the two bones in question don’t look like other marks common on the landscape. The marks are bigger, and they have different characteristics.”

Trample marks tend to be shallow, sinuous or curvy. Purposeful cuts from a tool tend to be straight and create a narrow V-shaped groove, while a tooth tends to make a U-shaped groove. The study measured and quantified such damage to modern-day bones for comparison to the fossilized ones.

“Our analysis shows with statistical certainty that the marks on the two bones in question were not caused by trampling,” Thompson says. “While there is abundant evidence that other bones at the site were damaged by trampling, these two bones are outliers. The marks on them still more closely resemble marks made by butchering.”

One hypothesis is that butchering large animals with tools occurred during that time period, but that it was an exceedingly rare behavior. Another possibility is that more evidence is out there, but no one has been looking for it because they have not expected to find it at a time period this early.

The Dikika specimens represent a turning point in paleoanthropology, Thompson says. “If we want to understand when and how our ancestors started eating meat and moving into that ecological niche, we need to refine our search images for the field and apply these new recovery and analytical methods. We hope other researchers will use our work as a recipe to go out and systematically collect samples from other sites for comparison.”

In addition to Dikika, other recent finds are shaking up long held views of hominin evolution and when typical human behaviors emerged. This year, a team led by archeologist Sonia Harmand in Kenya reported unearthing stone tools that have been reliably dated to 3.3 million years ago, or 700,000 years older than the previous record.

“We know that simple stone tools are not unique to humans,” Thompson says. “The making of more complex tools, designed for more complex uses, may be uniquely human.”

Complex cognition shaped the Stone Age hand axe, study shows
Brain trumps hand in Stone Age tool study