Deadly viruses like HIV or Ebola and menacing bacteria such as those that cause strep throat infections are true chameleons of nature. These and other disease-causing microorganisms adapt to a seemingly unlimited array of conditions by making rapid genetic changes. This microbial evolution outpaces the evolution of the human species by millions of years and creates a moving target for drug designers. By analyzing the evolution of infectious organisms, researchers now have a leg up on how to outwit potentially dangerous microbes. This understanding has helped explain why some microorganisms cause disease and some do not, and it is helping scientists develop life-saving treatments and vaccines. The predictive power of this relatively new brand of research may also aid in preventing disease outbreaks.
Over the past decade, an explosion of knowledge about the genetics of viruses, bacteria, and fungi has launched a new field that marries evolutionary biology and the study of infectious disease. Sophisticated mathematical and computer-based approaches are helping researchers weave the two areas together. NIGMS has supported discoveries in this field that have clear relevance to public health. Some of these findings are highlighted below. They reflect advances in knowledge about the genetic gymnastics of several different microbes, including Streptococcus pyogenes ( S. pyogenes, one form of strep bacteria), influenza (the flu), and Helicobacter pylori ( H. pylori, the bacterium that is the leading cause of digestive tract ulcers), as well as about the serious problem of antibiotic drug resistance.
S. pyogenes is a master of infection, causing a spectrum of illnesses from strep throat and tonsillitis to scarlet fever, toxic shock syndrome, sepsis, and necrotizing fasciitis ("flesh-eating disease"). Humans are the only known host for this group of bacteria. Scientists believe that S. pyogenes can cause so many different health problems because its set of genetic instructions varies widely among strains. Subtle genetic changes in these strains permit the bacterium to thrive in a variety of body locales, such as the throat or skin. Using mathematical approaches coupled to genetic studies, Dr. Debra E. Bessen of the Yale University School of Medicine has pinpointed several genes that permit this microorganism to live well in either the skin or the throat, but not in both. These genes may be attractive targets for the development of new drugs.
The best way to fight infectious diseases is to prevent them, and a key element of prevention is the ability to predict disease outbreaks accurately. Mathematicians have joined forces with evolutionary biologists and infectious disease specialists to develop powerful ways to track the evolution of viruses such as influenza A, the constantly changing strain usually blamed for major flu epidemics. A multidisciplinary team of scientists that included Dr. Simon A. Levin of Princeton University recently analyzed a computer database containing DNA sequences representing 560 samples of different flu viruses from the last 16 years. The team discovered patterns of genetic changes that may allow better prediction of which strains of flu will emerge in the coming season. If accurate, such predictions will lead to more effective flu vaccines, preventing illness and saving many lives each year.
A recent study by a biologist-mathematician team uncovered important scientific knowledge about H. pylori. Dr. Martin J. Blaser of the New York University School of Medicine and Dr. Glenn F. Webb of Vanderbilt University used mathematical modeling to track different genetic variants of H. pylori over time. After creating their model, the researchers checked its accuracy by testing it in animal experiments. The results indicate that H. pylori, which often lives nearly indefinitely in its host, undergoes constant evolutionary change through indiscriminate mating between different genetic strains, all within the infected host. Dr. Blaser's research also had another unexpected benefit: Modeling the infectious behavior of H. pylori provided important clues to how the deadly bacterium Bacillus anthracis, which causes anthrax, could be spread through the U.S. postal system. Using similar techniques to the H. pylori research, Drs. Blaser and Webb mathematically simulated the outbreak of mail-borne anthrax in the fall of 2001 and concluded that all the known cases of infection could be traced back to contamination through the mail from only six original envelopes. The scientists also concluded from this mathematical model that the rapid and widespread use of antibiotics probably averted many additional, potentially deadly infections from this outbreak.
The ability of bacteria to evolve rapidly enables them to escape the effects of antibiotics designed to kill them. Antibiotic resistance is an increasing problem throughout the world. Recently, scientists using computer simulation have been able to predict genetic changes that allow bacteria to resist antibiotics. Dr. Barry G. Hall of the University of Rochester simulated microbial evolution in the laboratory by choosing certain bacterial genes and determining through experiment which of the genes are most susceptible to changes that cause resistance to commonly used antibiotics. Remarkably, Dr. Hall and his coworkers found that their modeling techniques match the bacterial evolution that occurs in nature. The researchers' novel approach is likely to have practical value in enabling pharmaceutical companies to create drugs for which bacteria have no evolutionary escape route. Such an approach could also allow drug developers to anticipate how long an antibiotic will be useful: a few months, a year, or a decade. The ability to perform such analyses during the development phase will help to prevent the failure of antibiotic medicines in real-life use.
This page last reviewed on
8/9/2018 5:29 PM
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