Sandia LabNews

Sandia researchers take new approach to understand biochemistry of immunity to pathogens

A Sandia team led by researcher Anup Singh (8321) is taking a new approach to studying how immune cells respond to pathogens in the first few minutes and hours of exposure.

Their method looks at cells one at a time as they start trying to fight the invading pathogens.

Called the Microscale Immune Studies Laboratory (MISL) Grand Challenge, the work is in its second of three years of funding by the internal Laboratory Directed Research and Development (LDRD) program. Sandia is partnering on the project with the University of Texas Medical Branch (UTMB) at Galveston and the University of California, San Francisco (UCSF).

Anup says the researchers are interested in studying the early events in immune response when a pathogen invades a body. Understanding the early steps could lead to better ways to diagnose and stop disease before there are symptoms, and development of more effective therapeutics.

Most existing research into how immune cells respond has been done by looking at large cell populations. The Sandia researchers say information gathered from a large population of cells may mask underlying mechanisms at the individual cell level.

“Cells have different life cycles, just like any living being. And not all cells are exposed to the pathogen at the same time,” Anup says. “We wanted to look at cells in the same life cycle and same infectious state. This can only be done cell by cell. We also want to study populations, but one cell at a time.”

The research is possible because of advances in several Sandia-developed tools, including:

  • Microfluidics that allows researchers to do single-cell experiments
  • Advanced imaging that allows researchers to image individual cells with much higher information content than possible with current commercial imaging technologies
  • Powerful computational modeling that allows researchers to make sense of data obtained from microfluidic analysis and imaging

“Early on we realized that we did not have sufficient biological expertise needed for this project, so in addition to building collaborations with universities, we aggressively pursued hiring biologists at Sandia,” Anup says. “The addition of five new biologists has greatly increased our ability to develop biological understanding and reagents required to perform MISL experiments.”

Real immune cells are short-lived outside of bodies. To do the type of experiments they wanted, the researchers needed cells that can stay alive more than a couple of hours, have the ability grow, and represent a relevant model of human immune cells. They obtained “immortalized mouse immune cells” from a collaborator at UCSF that have the needed life span, and are accepted as a model system by the immunology research community.

“We’re starting with robust and well-characterized cells, which really simplifies development of our new technologies and methods, says biologist Steve Branda (8321). “We’ll soon be working with other cell types, though, like white blood cells directly isolated from human patients. Our approach is designed to be flexible enough to handle many different cell types, and it also minimizes the number of cells needed for analysis, so it should enable us to do some unique studies on rare cell types.”

Proteins in the cells of interest are tagged with fluorescent molecules, essentially colored dyes. The dyes range from green to red and give researchers the opportunity to track proteins and see, for example, the dynamic cellular production of proteins or protein-binding processes inside or on the surface of the cells.

The team is developing one platform with two complementary microfluidic modules — one developed for trapping and imaging viable cells during stimulation with pathogens. The second module combines cell preparation steps, cell selection, and sorting followed by analysis of protein content in the selected cell subpopulations.

Mechanical engineer Amy Herr (8321) and coworkers are working on the module that allows for sensitive, robust, and rapid protein quantification. They are analyzing protein levels and protein modifications in both single-cell and small cell populations of less than 1,000 cells at critical time points in the pathogen invasion. The engineering team interfaces directly with Sandia biologists, allowing the engineers to both develop methods useful to addressing biological hypotheses and validate the new tools against accepted methods.

“Specifically our module seeks to quantify protein events with sensitivity that is not currently attainable,” Amy says. “Further, we have designed tools that allow complete control over cell introduction, challenge, and analysis — thus enabling measurements of special interest to the ongoing predictive simulations.”

Conrad James (1744) and his team are working on the module for trapping and arraying cells so they can be imaged, and ensuring that cells are kept alive and healthy during the experiment. Hyperspectral fluorescence imaging with multivariate curve resolution (MCR) is then used to provide quantitative measurements on multiple proteins simultaneously. The goal is to analyze as many as 10 to 40 proteins and cellular stains at a time in three dimensions.

David Haaland (8332), lead member of the hyperspectral fluorescence imaging team, says his group provides 3D hyperspectral fluorescence imaging of 15-micrometer-diameter cells and their interactions between the cells in real time.

“This gives us the unique ability to quantitatively image many labeled molecules simultaneously in the cells during the host-pathogen interactions,” he says.

The end results of the imaging and protein analysis are large amounts of data that must be categorized and understood. That’s where computation modeling comes into play, says Jean-Loup Faulon (8333), coordinator of the computational core of the project.

“The goal of the computational core is twofold — to generate hypotheses to be measured experimentally by the biology and platform cores, and to produce a predictive model of immune responses,” he says.

Hypotheses are generated using a variety of bioinformatics tools to predict novel interactions between proteins and regulators involved in the innate immune pathways. The predictive model makes use of stochastic dynamics simulations — processes that can be described by a probability distribution. These can be used to ask and answer “what-if” questions about cell pathway responses and complement the experimental efforts.

The computational modeling is performed at both Sandia/California and Sandia/New Mexico.

Anup says using an integrated microfluidic platform sets Sandia apart from the rest of the world. Sandia researchers have been working in the area of microfluidics — the science of designing, manufacturing, and formulating devices and processes that deal with volumes of fluid on the order of nanoliters — since the 1990s and have a good understanding about how to use microfluids to analyze cell activity. The microfluidic platform is fast and highly parallel and can perform hundreds of measurements 50 to 100 times faster than alternate methods.

Sandia’s growing cadre of biological scientists provides key contributions to the grand challenge through the biology core of the project, coordinated by Tony Martino (8332).

“This project integrates a number of areas in which Sandia has a lot of expertise,” Tony says. “We are bringing together host-pathogen biology, cell and protein manipulation using microfluidic and BioMEMS technologies, and computational biology. We are building something bigger than the sum of the parts, and that is a great strength for Sandia.”

He adds, “We are challenging the way people think about doing biological experimentation. Single-cell measurements and simultaneously measuring protein behavior when there might be just one or a few molecules present will revolutionize biology.”

Anup says the end goal is to make a benchtop miniaturized system expected in about two years. It would be placed in Biosafety Level 3 or 4 labs to study immune response to highly pathogenic organisms. Moreover, the integrated platform, biological reagents and computational models developed under this project have applicability beyond infectious disease research. These technologies can also be used for studying cellular signaling involved in diseases such as cancer or by pharmaceutical companies for biomarker discovery.

Glenn Kubiak (8320), MISL project manager, emphasizes the importance to the project of the partnerships with UTMB and UCSF.

“Sandia’s expertise in microsystems, advanced chemical imaging, and computing, combined with their expertise in emerging infectious disease and cellular signaling has created a team that is unique in its ability to contribute both to defense against infectious diseases and to therapeutics,” he says. “Folks we’ve briefed in government agencies and companies have been pretty amazed by the strength of our partnership and also by the audacity of what we’re doing together. That’s why we call it a grand challenge.

Team members:

Principal investigator: Anup Singh (8321)

Project manager: Glenn Kubiak (8320)

Platform core: Anup Singh (8321, coordinator), Amy Herr (8321), Igal Brener (1721), Jim Brennan (8321), Susan Brozik (1714), Conrad James (1744), Ron Manginell (1744), Matt Moorman (1744), Kamlesh Patel (8324), Thomas Perroud (8324), Surendra Ravula (1727), Ron Renzi (8125), Nimisha Srivastava (8321), Dan Throckmorton (8321)

Biology core: Tony Martino (8332, coordinator), Steve Branda, Catherine Branda, Zhaoduo Zhang, Todd Lane, Meiye Wu (all 8321), Jens Poschet (8332), Bryan Carson, Roberto Rebeil , Bryce Ricken, Kevin Crown, Amanda Carroll-Portillo (all 8331),

Imaging team: David Haaland (8322), Mike Sinclair (1824), Howland Jones (8332), Mark Van Benthem (8332), Rachel Noek (8332), David Melgaard (5534), Chris Stork (1823)

Computational core: Jean-Loup Faulon (8333, coordinator), Jaewook Joo (8333), Shawn Martin (1412), Steve Plimpton (1412), Susan Rempe (8333), Ken Sale (8321)