NIAID invests in basic research to understand the biology of microbes, their behavior, and how drug resistance develops. Understanding precisely how microbes cause disease (the process called pathogenesis) is also crucial for finding new ways to combat them.
Insights Into Mechanisms of Resistance
NIAID conducts and supports basic research to understand the fundamental biology of disease-causing microbes and provides insight into the mechanisms they use to block antimicrobial drugs. This knowledge generates new ideas for ways to get around these mechanisms, by restoring the effectiveness of existing drugs or by identifying novel drug targets for the design of new antimicrobials.
How Pathogens Cause Disease
Microbial pathogenesis is a key focus of basic research that studies how microbes cause disease, including how they colonize and invade the host, which toxins they produce, and how they avoid or overcome an attack by the host’s immune defenses. Basic research by NIAID scientists is revealing new details about microbial pathogenesis. For example, investigators have identified bacterial proteins produced by community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) that destroy infection-fighting white blood cells. A better understanding of the role these proteins play in creating the conditions for severe CA-MRSA infections could lead to new ways to treat or prevent the illness.
Investigating the Role of Host Factors
NIAID supports research on host factors—specific traits that may influence an individual’s susceptibility or response to disease—and the pathogenesis of drug-resistant infections. For example, NIAID is advancing research on how to treat infectious diseases by targeting host pathways rather than the microbes themselves. An alternative to conventional antimicrobial drugs, host-targeted interventions could become a powerful new tool in the fight against drug resistance.
Deciphering Microbial Genomes
New pathways towards understanding drug resistance are revealed when scientists determine the sequence of genes that make up a microbe's genome. Genetic analysis can reveal vulnerable areas in a microbe's genome that could be potential drug targets. This information could also aid in developing better diagnostic tests. By isolating the same species of microbe from different geographic locations or from different human populations and comparing their genetic information, scientists may be able to identify when and where resistance first emerged in these species, as well as identify specific mechanisms of resistance.
- Since 2003, NIAID has supported a broad range of microbial genomic research through its Genomic Centers for Infectious Diseases, including transcriptomics, to analyze microbial and human genomes and comparative genomics to evaluate different strains, species, and clinical samples. Scientists at these centers have sequenced the genomes of more than 10,000 antimicrobial-resistant bacterial genomes, including Enterococcus, Klebsiella, Acinetobacter, Carbapenem-resistant Enterobacteriaceae (CRE), MRSA, and Mycobacterium tuberculosis. The Centers have also sequenced numerous viruses (including more than 20,000 influenza viruses), parasites, fungi, and invertebrate vectors of infectious diseases.
- Next generation sequencing technologies are being developed to sequence genomes quickly and cost-effectively. These state-of-the-art technologies are being used to build an integrated high throughput system to rapidly prepare, sequence, and analyze thousands of clinical samples. The system will track and provide genetic information on emerging antimicrobial resistance.
Computer-Assisted Modeling Efforts
Using genomic and additional "omic" information on genes, proteins, and other compounds, the NIAID program in Systems Biology for Infectious Diseases Research investigates and identifies metabolic, regulatory, signaling, and other biological pathways generated by pathogen and host-pathogen interactions. The program's scientists use this information to build computer-based models that reveal clues about possible targets for new antimicrobial drugs. Virtual representations of potential drugs are first built by computer. Only the most promising of these virtual compounds are synthesized in the lab and tested for antimicrobial activity. This innovative method allows many compounds to be judged quickly for their potential utility. In 2016, NIAID launched multi-disciplinary Centers that use systems biology, mathematical modeling, and predictive analytics to model and predict risk, severity, progress, and response to treatment for AMR. This includes the use of big data/machine learning algorithms that predict hospitalized patients at highest risk for Clostridium difficile infections.