A well-respected researcher who is now a chief of an immunology laboratory of the National Institutes of Health (NIH) has rocked the boat in the past few years for the experts in the understanding of the autoimmune system.
NIH’s Polly Matzinger has developed the "danger model," suggesting that the immune system is more concerned with damage detected on the basis of a biological cell’s death than with the introduction of foreign invaders, such as viruses. If Matzinger is correct, then decades of scientific and medical diagnostic thinking could be in jeopardy.
As immunologists consider the relatively new concept, a new NIH grant, awarded to Amy Bell, an electrical and computer engineer (ECE), and Karen Duca, a research assistant professor at the Virginia Bioinformatics Institute (VBI), both of Virginia Tech, could answer some of the questions about the human body’s responses to viruses. Viruses cause a number of diseases, from the common cold, to herpes, to AIDS. Even some types of cancer have been linked to viruses.
Prior to Matzinger’s model, the common assumption was that the body’s cells recognize substances or germs that do not come from within the body. The recognition triggers the immune system’s attempt to eliminate the invader. But what the immune system actually does, according to Matzinger, is discriminate between things that are dangerous and things that are not. And it does this by defining anything that does damage as dangerous. Through this selectivity process, the immune system does not respond to things that don't do damage.
Examples she uses to support her thesis that the body recognizes some invading substances are not dangerous include the development of a fetus during a woman’s pregnancy and the production of milk by lactating women.
So the question remains: do we really know what a body’s host cell does when a virus infects it?
Bell and Duca’s collaboration is an attempt to profile the host-virus system using the electrical engineering concepts of signal and image processing. As Duca, a biophysicist, introduces viruses into cells in a laboratory dish, she infects only the cell’s center. Then, she and Bell, who is also a VBI faculty fellow, study the response as the virus moves outward. Their method differs from conventional laboratory studies of viruses that generally involve infecting the entire dish at once.
As the virus moves out from the center in its attempt to infect other healthy cells, Duca identifies and stains relevant markers from the virus and the host. Under ultraviolet lighting, the chemical stains become fluorescent, allowing Bell and Duca to capture images of the laboratory dish at regular time intervals as the infection progresses. The images then provide Bell and Duca with information about innate immune responses to viruses.
Using the NIH support of almost $400,000, Bell plans to next remove the noise from these low-resolution images, creating what she calls a clean immuno-fluorescent intensity signal. The noise she refers to is not audible to the human ear. From an electrical engineering standpoint, noise in this example includes the spurious artifacts that appear in the image due to the microscope’s uneven source illumination. Noise can also result from the spectral overlap of the fluorescent markers that Duca uses.
Also, since the microscope cannot capture the entire laboratory dish at once, multiple sub-images must be taken quickly, then reassembled in the proper matrix. The “montage” artifact arises from the microscope’s uneven illumination, which is brighter in the center and dissipates nearer the edges of the dish for each sub-image.
To compensate for this artifact or noise, Bell’s lab has developed “a method to remove the grid created by assembling the montage of sub-images. Our method – based on a model we developed that reflects the physics of fluorescent microscopy – also estimates and corrects the effect of the microscope’s uneven illumination and the markers’ spectral overlap,” Bell explains.
As Bell and Duca are able to develop their composite images, they will be able to mathematically produce a quantitative description of the spreading of the virus as well as the host-virus interaction. “The immuno-fluorescent intensity signals (IIS) depict how the virus and host are interacting over time, from the point of origin to the point of infection,” Bell says.
Ultimately, the interdisciplinary team hopes their efforts will provide a quantitative method that derives a characteristic profile or fingerprint from the IIS of any host-virus system. If their method can achieve results in hours instead of days, their techniques could be used in clinical and field settings to quickly identify known viruses, or to map unknown viruses to existing profiles to better predict their behavior and start appropriate treatment.
Ultimately, their work should contribute to what starts an immune response. And as NIH’s Matzinger says, knowing what initiates an immune response will affect and, researchers hope, improve medical treatment.
Bell is an associate member of the Virginia Tech – Wake Forest University’s School of Medicine School of Biomedical Engineering and Science. SBES research focuses on imaging and medical physics, as well as biomechanics and cell and tissue engineering. Imaging has the invaluable potential to greatly extend the reach of medical research beyond detecting the anatomical presence of the disease. Employing applied engineering technologies to treatment will allow more intensive study of diseases at the cellular level. A greater understanding of the physiology of an illness will lead to more targeted treatments.