Understanding & Treating Infection

LSP teams use interdisciplinary approaches to address ongoing and emerging infectious diseases.   

LSP investigators apply several approaches to improve how we understand and combat infectious diseases. This work spans numerous diseases with immense global health burdens, from tuberculosis to antibiotic resistance, to emerging infectious agents.

Tuberculosis (TB) infection is the leading cause of death by infectious disease worldwide. It remains challenging to treat, in part because the TB bacteria, Mycobacterium tuberculosis, often become resistant to therapies. Additionally, after infection, tuberculosis can enter a latent phase, where the bacteria remain dormant in the body and threaten disease reemergence later in life. Work by Tufts University Prof. Bree Aldridge and collaborators pairs sophisticated high-throughput experiments with computational modeling to predict novel treatment strategies for TB.  An LSP team led by Prof. Peter Sorger applies spatial biology and digital pathology tools to understand the pathological changes associated with primary and reactivated TB infection, with an emphasis on how the inflammatory environment changes with infection. LSP researchers also collaborate with the Bill and Melinda Gates Foundation to make spatial TB datasets accessible through an online TB Data Resource.

Antibiotic resistance is an evolving global health threat that accounts for 2.8 million yearly infections in the U.S. alone. To combat it, an LSP team led by Prof. Michael Baym uses various approaches, including imaging, genomics, novel algorithms, and innovative experimental methods to understand how and why microbes evolve. This interdisciplinary approach combines novel methods for tracking microbial genomes over time with analysis of real-world samples and agents that exert evolutionary pressure on bacteria, such as phages and prophages. Understanding how microbes respond to pressures improves our ability to adapt to and address emerging threats from antibiotic-resistant bacteria.