Tyler O'Neal, Staff Editor APPLICATIONS

Kaneko Lab shows that leaking away essential resources isn't wasteful, actually helps cells grow

Math reveals the potential answer to a persistent evolutionary mystery

Experts have been unable to explain why cells from bacteria to humans leak essential chemicals necessary for growth into their environment. New mathematical models reveal that leaking metabolites - substances involved in the chemical processes to sustain life with the production of complex molecules and energy - may provide cells both selfish and selfless benefits.

Previously, biologists could only say that leaking is an inherent property of cell membranes caused by fundamental rules of chemistry.

"It is in the nature of membranes to leak, but if leaking is undesirable, why has evolution not stopped it? This question of 'Why?' was never solved," said Professor Kunihiko Kaneko, a theoretical biology expert from the University of Tokyo Research Center for Complex Systems Biology.

The research team used calculations that can measure the changes in multiple factors over time, called dynamical-system modeling, in combination with supercomputer simulations. In this modeling, the researchers considered the nonlinear processes for cell growth where a cell takes in external nutrients and converts them to cellular body and energy by intracellular chemical reactions, by representing the cellular state as the concentrations of intracellular chemicals including nutrients, enzymes, and components to synthesize cellular body. All calculations assumed that the model cells were in a steady state of growth where their internal metabolism and relative concentration of chemicals inside the cells were all stable. {module INSIDE STORY}

The calculations were designed to identify what types of chemical synthesis pathways would become more efficient if some of their components leaked out to the environment. The mathematical models of chemical synthesis paths are simpler than the complex branching pathways in living cells, but allow researchers to look for fundamental patterns.

Researchers identified two such model chemical pathways with catalytic reactions that use enzymes to enhance the reaction rate, which they call the "flux control" and "growth-dilution" mechanisms. In both mechanisms, leaking one essential upstream chemical component of the pathway allows the end product to be produced more efficiently. Thus, leaking is something cells do to selfishly enhance their own growth.

"In theory, the flux control mechanism enhances the pathway for biomass synthesis by the leakage of an essential chemical in an alternative branching pathway, whereas the growth-dilution mechanism enhances the biomass synthesis by the leakage of the precursors of biomass (e.g., amino acids) essential for cell growth. These are a result of the balance between chemical reactions and concentration dilution associated with cellular volume growth," said Jumpei Yamagishi, a first-year graduate student who has worked in Kaneko's laboratory since his undergraduate years.

The models that the research team created so far only consider one type of cell at a time. However, leaking upstream components might become a problem for cells living only with identical types of cells leaking the same components.

"In many cases, if all cells are leaking the same molecule, their environment will become 'polluted.' But if multiple cell types live together, then they can leak one chemical and use a different chemical leaked by the others," said Kaneko.

This mutually beneficial exchange of leaked essential nutrients may be a selfless way to enhance the growth of the whole community of cells.

"Our work may partially answer why the natural environment is so different from artificial lab conditions where bacteria are grown in pure monocultures, but we will need additional models to be sure," said Yamagishi.

The researchers are planning to design more complex mathematical calculations to better simulate natural conditions where multiple types of cells coexist to see if that reveals other types of synthesis pathways that benefit from leaking.

The Antarctica Factor: model uncertainties reveal upcoming sea level risk

Tyler O'Neal, Staff Editor APPLICATIONS

Sea level rise due to ice loss in Antarctica could become a major risk for coastal protection even in the near term, scientists say

"The 'Antarctica Factor' turns out to be the greatest risk, and also the greatest uncertainty, for sea-levels around the globe," says lead-author Anders Levermann from the Potsdam Institute of Climate Impact Research (PIK) and Columbia University's LDEO in New York. "While we saw about 19 centimeters of sea-level rise in the past 100 years, Antarctic ice loss could lead to up to 58 centimeters within this century. Coastal planning cannot merely rely on the best guess. It requires a risk analysis. Our study provides exactly that: The sea-level contribution of Antarctica is very likely not going to be more than 58 centimeters."

Thermal expansion of the ocean water under global warming and melting of mountain glaciers, which to date have been the most important factors for sea-level rise, will come on top of the contribution from Antarctic ice-loss. The overall sea-level rise risk is thus even bigger, yet the 'Antarctica Factor' is about to become the most important one, according to the study now published in the journal Earth System Dynamics of the European Geosciences Union (EGU). {module INSIDE STORY}

Large range of estimates makes the results very robust

The range of sea-level rise estimates from the 'Antarctica Factor' provided by the scientists is rather large. Assuming that humanity keeps on emitting greenhouse gases as before, the range the scientists call "very likely" to capture the future is between 6 and 58 centimeters for this century. If greenhouse gas emissions were to be reduced rapidly, it is between 4 and 37 centimeters. Importantly, the difference between a scenario of business-as-usual and a scenario of emissions reductions becomes substantially greater on longer time-scales, hence farther in the future.

The researchers accounted for a number of uncertainties in the computations, from the atmospheric warming response to carbon emissions to oceanic heat transport to the Southern ocean. 16 ice sheet modeling groups comprised of 36 researchers from 27 institutes contributed to the new study, which was coordinated by PIK. A similar study six years earlier had to rely on the output of only five ice sheet models. This development reflects the increasing importance of research on the Antarctic ice sheet.

aaRisks for coastal metropolises from New York to Mumbai, Hamburg to Shanghai

"The more supercomputer simulation models we use, all of them with slightly different dynamic representations of the Antarctic ice sheet, the wider the range of results that we yield - but also the more robust the insights that we gain," says co-author Sophie Nowicki of the NASA Goddard Space Flight Center and lead author of the Intergovernmental Panel on Climate Change who led the overarching ice sheet model intercomparison project, ISMIP6. "There are still large uncertainties, but we are constantly improving our understanding of the largest ice sheet on Earth. Comparing model outputs is a forceful tool to provide society with the necessary information for rational decisions."

Over the long-term, the Antarctic ice sheet has the potential to raise sea levels by tens of meters. "What we know for certain," says Levermann, "is that not stopping to burn coal, oil, and gas will drive up the risks for coastal metropolises from New York to Mumbai, Hamburg or Shanghai."

Rosetta stone for urban scaling makes sense of how cities change across time, space

Tyler O'Neal, Staff Editor APPLICATIONS

Cities change as they grow -- not only by adding area or population but also in a variety of other ways, from the length and width of their roads to economic growth to the distribution of elementary schools. Social scientists often clash over the best way to measure change as a city swells. Traditionally, they've taken a cross-sectional approach, which means collecting data on a large number of cities of diverse sizes at the same moment in time. More recently, some researchers have begun studying individual cities over time, in what's called temporal scaling.

"These two dimensions, time and population size, need to be treated separately because they express different phenomena," says Luís Bettencourt, an external professor at the Santa Fe Institute and director of the University of Chicago's Mansueto Institute for Urban Innovation. "We need both of them to make sense of what is happening in a complex system like a city."

New work, led by Bettencourt, maps out the common ground between these two approaches. In a paper published this week in the Journal of the Royal Society Interface, the authors argue that while the two methodologies measure different mixtures of the same phenomena, they can be used together to reveal new insights about a city's behavior.

Each approach can be used to calculate an exponent describing the growth rate of some property. (Cross-sectional analyses suggest, for example, that traffic congestion scales exponentially as the size of the city, with an exponent of 7/6.) Those exponents don't necessarily line up, but they don't have to be at odds.

"Now, we're able to have this way to disentangle the two approaches, and bring these two scaling methods back together," says Vicky Chuqiao Yang, an Omidyar Fellow at the Santa Fe Institute who worked on the paper. "With the formalism, we've derived in the paper, we've shown mathematically how these exponents are related between the two approaches."

Scaling behaviors have long been observed and analyzed in physical systems of liquids and gases. Similarly, researchers have long found successful ways to map how properties scale for biological organisms--with the size of animals, for example. "They've compared mice with cows with elephants and found properties that change in a predictable way with size, which spans orders of magnitude," says Yang. But temporal scaling is not obvious in biology, because social systems like cities can grow indefinitely and organisms stop once they reach maturity.

In recent years, as large datasets on urban areas around the world have become available, researchers like Bettencourt and Yang have begun analyzing scaling behaviors that emerge in human systems -- including cities. The field really ignited about a decade ago, she says, when researchers from the Santa Fe Institute first showed that many properties of cities also changed in a predictable way over orders of magnitude in city size. CAPTION Space-shifting reflective sculpture in Chicago, Il. CREDIT Petr Kratochvil/Public Domain{module INSIDE STORY}

"There was this mysterious phenomenon that the properties of cities change in systematic ways with its size," says Yang. "That included things like fewer gas stations per capita, and a boost in socioeconomic activity, such as more research and development." Since then, researchers have found that many interesting socioeconomic properties increase disproportionally fast with population, said to be "superlinear." Some others grow disproportionally slowly and are said to be "sublinear."

Such scaling behavior has been found in systems ranging from hunter-gatherer societies to modern companies. The new framework offers a way to better understand and quantify properties with systematic trajectories -- and even understand which ones contribute to the health of human institutions. It could, for example, give researchers a way to analyze how a phenomenon like economic growth changes with time and with population size (but does so along both dimensions in different ways). Bettencourt likens the new work to a Rosetta Stone that allows researchers to translate their findings between the two types of scaling.