skip to: onlinetools | mainnavigation | content | footer



Lab News -- August 1, 2008

August 1 , 2008

LabNews 08/01/2008PDF (500 kb)

The secret life of cells: Sandia, UNM researchersí first-ever video of cellís recognition of danger

By Neal Singer

If you’re physically attacked, you hope you’ll respond.

That hoped-for response to threat includes the molecular level: We want our cells to respond defensively when an antigen lands on a cell membrane and prepares to cause mischief.

But to activate a response, a cell must become aware of the presence of the intruder on its membrane, just as a human first must become aware of a mosquito on a forearm in order to slap it.

In a triumph of joint experimental work, physicists at Sandia and biologists at the University of New Mexico’s Cancer Research and Treatment Center have combined techniques amazing to the layperson to make real-time movies that show exactly how a 50-nm-thick cell membrane notifies the cell it encloses that a hostile alien presence — an antigen — has made a landing.

Characterization in real time

“We were able to characterize the motion of the receptor proteins in the membrane in real time as they respond to the antigen,” says lead Sandia researcher Alan Burns (now 1012). “Perhaps more importantly, we learned the cell membrane is really complicated and highly structured, rather than fluid and unstructured, as is the prevailing notion.”

This new information explains why membrane proteins may not always notify the cell nuclei of problems.

The membrane structures, which resemble holding corrals, says Alan, move around in the membrane. But they restrict the motion of proteins. The response of the cell requires that the antigen receptor proteins cluster with other proteins to commence the cellular signaling network.

“The proteins are like Paul Revere giving a warning,” says Alan. “When proteins bind antigens, they begin to cluster. This causes other proteins to thrash around. That may send a message from the membrane to the cell nucleus that something’s wrong.

“But if there are places on the membrane that are walled off and an antigen lands there, the cell isn’t notified of the problem. No protein, no warning.”

UNM researchers already knew that incoming antigens were detected by proteins present in the lipid matrix of the cell membrane. But how exactly to determine the process?

Alan, working with his former postdoc Keith Lidke (now a UNM professor), modified a special microscope called a total internal reflection fluorescence (TIRF) microscope whose laser-light output is completely contained within the microscope coverslip. This resembles the way optical fibers transport light, except that the TIRF does not ever release any light. But though the light is contained, making its use seem at first an exercise in futility because it penetrates nothing external, it generates a tiny electrical exploratory field that extends about 100 nm into the cell, which lies supported by the coverslip.

“When a cell settles on a piece of bare thin glass,” says Alan, “the membrane of the cell by definition is snuggled up against the glass and available to the radiation field.”

Watching bank robbers

Enter the UNM biology team. Led by professor Diane Lidke (Keith’s wife), the team was able to attach quantum dots of 30 nm and 40 nm respectively to the antigen receptor proteins in the membrane.

Quantum dots emit light when stimulated by an electrical field. The color fluoresced is determined by the size of the dot. So one protein, when stimulated by the laser’s electrical field, emitted orange light. The other emitted red. That way researchers could keep track of the motion of single, individual proteins and see how they interacted; moreover, it allowed them to observe barriers to the motion.

Sensitive CCD cameras picked up and videotaped the motion of the lit-up proteins as they reacted to the introduction of antigens to the membrane.

“It was like using cameras to watch individual bank robbers move around as a holdup progressed,” says Alan.

The work is of interest to Sandia, a national defense lab interested in determining the human response to bioinfectious diseases, and to UNM’s bioscience program.

Other authors on the paper were graduate student Nicholas Andrews and biology professors Bridget Wilson and Janet Oliver, all with UNM’s Cancer Research and Treatment Center.

The Sandia work was funded by its Laboratory Directed Research and Development (LDRD) office. The UNM work was funded by the National Institutes of Health. The work was published online the week of July 20 in the journal Nature Cell Biology.-- Neal Singer

Top of page
Return to Lab News home page

Technique estimates how many people will fall sick in an epidemic

By Chris Burroughs

Imagine an outbreak of a disease like SARS (severe acute respiratory syndrome) that will likely become an epidemic affecting thousands of people. Wouldn’t it be helpful to know early in the epidemic how fast the disease would spread and how many people may be infected so that the medical community could be prepared to treat them?

Sandia/California researcher Jaideep Ray (8964) has developed a computer model that can do just that.

In his third year of internal LDRD (Laboratory Directed Research & Development) funding Jaideep has figured out a way to determine the number of people likely to be infected and die from noncommunicable illnesses like anthrax — ailments that could be caused by a potential bioterrorist attack — as well as communicable diseases like smallpox.

“In the past decision makers were only able to observe — watch people get sick, go to the hospital, and maybe die,” Jaideep says. “They had no idea how many people would get sick tomorrow or two days from now.”

He came to this realization in 2004 when he was working on a project for the Department of Defense where he developed a computer model that had decision makers responding to an epidemic at a naval base.

“It struck me that we were going about this completely backwards,” Jaideep says.

He proposed an LDRD where he would develop mathematical tools that, using information from the first days of an epidemic, would estimate how many people were going to get sick during the course of the epidemic.

He spent the next three years working on the software and in the middle of 2007 successfully developed a model that could infer the characteristics of a bioterrorism-related epidemic of a noncommunicable disease like anthrax. These inferences were drawn from observations of people with symptoms of anthrax exposure collected over the first three to five days of the epidemic. He is within a few months of refining a computer model that would do the same for communicable diseases.

Russian anthrax outbreak

Jaideep says that characterizing diseases requires observations of real outbreaks and then building computer models around them. He did this for a 1979 anthrax outbreak in Sverdlovsk, a city of 1.2 million people in western Siberia. Initially the Soviets said the victims got the disease by eating anthrax-contaminated meat or having contact with dead animals. At the end of the Cold War American physicians reviewed documents published by pathologists who performed autopsies during the epidemic, confirming the pathogen was airborne. Records showed that 80 people were infected by inhaling the pathogen. A total of 68 died of the disease.

Using the computer program, Jaideep ran the data obtained from hospital records of people who became sick in the early days of the epidemic. The program automatically tried many combinations of the unknown number of infected people, time, and dose of anthrax exposure until it got as close to the real observation as possible. In the final runs, using data from the first nine days of the 42-day outbreak, the model inferred that almost certainly less than 100 people had been infected, with the most probable number around 55.

That was “pretty close,” to the real event, he says. The program, which also estimated the time of the release and the dose of anthrax inhaled, took 10 minutes to run.

“If they had had this program in 1979, the Soviet officials would have known that this was going to be a small outbreak,” Jaideep says. “Instead they got into a panic and vaccinated 50,000 to 60,000 people — the whole southern end of the city.”

Nigerian smallpox model

After proving the software actually works, he turned his attention to communicable diseases, specifically smallpox. He modeled a documented smallpox outbreak in Nigeria in 1967, which broke out in a fundamentalist sect (Faith Tabernacle Church, FTC) in the town of Abakaliki. The sect consisted of 120 people who lived in nine different compounds, along with 177 of their nonsectarian brethren. The FTC members mixed strongly in their compounds and across compounds at church four times a week and social visits.

A small girl first introduced the disease into the population. It spread rapidly in her compound and jumped to other compounds via the church and social visits. The sect members refused medical treatment and did not quarantine the sick and contagious members. While the World Health Organization (WHO) monitored the outbreak and kept records of who got sick and when, it did not record the dates of recovery or deaths of the infected people.

Of the 32 people who became infected during the epidemic, 30 were FTC members.

“It was clear from the WHO observations that there was strong transmission inside compounds and weaker ones across compounds,” Jaideep says.

Differentiating the communicable disease model from the noncommunicable disease model is the importance of social networks. Communicable diseases spread faster through people in closer proximity. For example, close family members of an infected small child would have a higher probability of contracting the disease than someone who lives in another compound or house.

Jaideep says the challenge is that making inferences about social networks is hard. There is a tendency for the inference mechanism to quickly “settle down” into one of a few possible network configurations. While he estimates that it will take about four to six months to overcome this “stickiness” of the inference mechanism, he has successfully obtained estimates using a few simplifications.

One simplification is to assume a fully connected social network but allow the disease to progress through the population at two different rates, one for in-compound transmission and a smaller one across compounds. Using this approach he inferred the two transmission rates from observations and found the cross-compound transmission to be about four times slower.

A second simplification is to assume there exists only one transmission rate and explain the slower spread across compounds to fewer and unknown “strong” cross-compound social links. Using this second approach, he inferred the transmission rate as well as the cross-compound social links that existed.

Under both simplifications, he also inferred the chains of transmission, that is, the links in the social network along which the disease traveled, infecting people in its wake. Typically, chains of transmission are identified by painstaking contact tracing by epidemiologists.

Once these disease characterization parameters are inferred from data, they can be entered into conventional epidemic models that predict the evolution of the epidemic in the population and predict the number of people getting sick on a given day.

As of today, these inference techniques can work with incomplete observations. Using data from the first 40 days of the three-month epidemic, Jaideep was able to develop “true” characterizations.

”These preliminary results are useful and encouraging,” Jaideep says. “Within a few months we should be able to remove the simplifications and perform inferences with models which are even more reflective of the actual spread of the disease.” — Chris Burroughs

Top of page
Return to Lab News home page

Rad detection for non-port-of-entry border sites

By Mike Janes

US border and immigration policy remains a central topic of discussion for politicians, the media, and citizens. But even as cable news commentators continue to debate the issue and the presumed Democratic and Republican presidential candidates formulate their own immigration policies, Sandia researchers have been working with the Domestic Nuclear Detection Office (DNDO) and Customs and Border Protection (CBP), specifically the Border Patrol, to study the border for another reason: the nuclear terrorist threat.

For the past three years, Sandia researchers have been studying the problem of how to prevent nuclear smuggling through “non-port-of-entry” border regions, which are loosely defined as the broad swath of land patrolled by Border Patrol where it is illegal to enter the country. Non-POE can include fixed interior checkpoints, regions that are patrolled by agents on horseback or on all-terrain vehicles, and other locations along the US border, which extends nearly 2,500 miles in the southern US and more than 3,000 miles in the north.

The border may itself be a distinct line with clear separation between nations. The Border Patrol, however, is responsible for a region that can extend up to 100 miles wide, and they conduct operations throughout this region. Consequently, the studies Sandia has been conducting have necessarily focused on the diverse operations employed by Border Patrol agents in various parts of the country.

Operational flexibility

“The main tenet for Border Patrol agents, we’ve learned, is operational flexibility,” says Jason Reinhardt (8130), a Sandia electrical engineer who’s been involved in Sandia’s border security and radiation detection work since 2002.

“At a port, you can install large, stationary pieces of equipment and enjoy a higher level of confidence that they’ll perform consistently. Also, you can dedicate personnel whose main focus is operating the portals. For Border Patrol use, the equipment needs to be portable and fit within the scope of the agent’s other equipment and tasks.”

Such operational realities, Jason says, often go against the fundamental physics of radiation detection, adding to the overall challenge of deploying a viable detection system that meets the needs of the end users.

The performance of sophisticated detection equipment, while a current subject of debate among lawmakers, is clearly unsuited to non-POE applications for demonstrable, operational reasons, according to Jason. Such equipment, he explains, is difficult to use in the often-harsh and unpredictable environments that border agents can encounter. Heavy winds, dust, downpours, and other environmental realities all contribute to the problem, and the Border Patrol agents themselves are often patrolling wide-open spaces on foot or in a small vehicle, which makes the packaging and portability of detection equipment next to impossible.

A systematic, step-by-step approach

In addition to trying to understand the operations of the Border Patrol agents, Sandia has at the same time been analyzing specific, off-the-shelf radiation detection equipment that could be made part of the border’s defense posture. This is especially key, Jason says, since the effectiveness of many of the radiation detection products is often “oversold” by manufacturers or may not take into account the operational realities involved.

Taking a phased approach to the work, the researchers typically study the instruments in a controlled laboratory environment first before taking the equipment to the Nevada Test Site or the Albuquerque-based Technical Evaluation Assessment Monitor Site (TEAMS) for further evaluation. Then, they familiarize border agents with the instruments back in the lab and, finally, move out to the field with the agents and begin to integrate the equipment with CBP’s regular operations.

Jason and his Sandia colleagues have spent considerable time examining border regions in the southern and southwestern US and will likely continue to focus in that part of the country for the foreseeable future, with more of an emphasis on systems engineering than testing and evaluation.

Next up: a look at unattended sensors

The research team’s next step, Jason says, is to analyze the voluminous data collected during a recent deployment of equipment at a Southwest border location. Afterward, they’ll deliver a technical report to DNDO that outlines the findings and recommended requirements that Sandia believes may make radiation detection a viable activity in both the short and long term. It’s also possible, Jason says, that a longer test series will occur at a yet-to-be-determined border location sometime next year.

If radiation detection systems turn out to be the direction DNDO and CBP choose to go, unattended sensors could be a part of a future radiation detection system along the border, Jason says. It’s easier said than done, of course, and DNDO will likely need to engage industry partners to develop and engineer new hardware that meets both the performance requirements and operational demands of CBP and its agents.

Until then, Jason says, he and his colleagues will continue to plug away, learning the needs of CBP’s agents along the border, analyzing the radiation detection solutions available today, integrating them into CBP operations, and making technical and operational recommendations for the future. -- Mike Janes

Top of page
Return to Lab News home page