The UChicago Pritzker School of Molecular Engineering's Immunoengineering theme applies PME's interdisciplinary lens to some of the most pressing health problems facing the world today.
Whether developing new vaccines with the potential to prevent cancers and multiple sclerosis, researching the causes of sepsis and food allergies, or applying AI and machine learning insights to the human body, here is a look at just a few recent ways PME immunoengineers innovate for human health.
How a microbe and a prebiotic work together against food allergies
New research from Cathryn Nagler’s lab at the PME and the University of Chicago Biological Sciences Division (BSD) could have broad impact for people suffering from food allergies.
In a paper published in Cell Host and Microbe, Nagler’s lab reported a mutually beneficial relationship between an unassuming microbial species and the prebiotic lactulose – together, they encourage the production of an important metabolite known for its positive influence on gut health, butyrate, that’s generated as bacteria feed in the gut. The team found that treatment with a concoction of A. caccae and the prebiotic lactulose increased butyrate levels in the intestinal tracts of mice, stifling allergic responses to cow’s milk.
“The primary goal of gut microbiota is to digest dietary fiber, which humans don’t have the capacity to break down themselves,” Nagler said. “Instead, humans have co-evolved to rely on bacteria to do this job and to produce key metabolites through fermentation – like butyrate – that prevent inflammation and enhance overall gut health.”
One vaccine, many cancers
Acute myeloid leukemia (AML) is a type of blood cancer that forms in the soft marrow of the bones, typically attacking cells that would otherwise form the key component of the body’s immunodefense system, white blood cells.
In a new study published in Blood Advances, researchers from the UChicago Pritzker School of Molecular Engineering’s Hubbell Lab created a novel approach to develop in-situ cancer vaccines that could increase the effectiveness of immunotherapies in AML and other blood cancers.
“We are trying to come up with cancer vaccine approaches that could be more easily scaled and applied, in other words, one type of vaccine that works with a number of cancers,” said Prof. Jeffrey Hubbell, the Eugene Bell Professor in Tissue Engineering at PME.
First author Anna Slezak recently obtained her PhD from PME, graduating as part of the University of Chicago’s 538th Convocation.
Getting dynamic information from static snapshots
Single-cell RNA-sequencing (scRNA-seq) provides researchers the best available transcriptome-wide snapshot of cells and genes. But researchers looking to study how embryos develop, cells differentiate, cancers form, and the immune system reacts need information on how cells transition over time. They need to know how a cell becomes cancerous or how a particular gene program behaves during an immune response.
In a paper published in Proceedings of the National Academy of Sciences, researchers from the UChicago Pritzker School of Molecular Engineering and the Chemistry Department have created TopicVelo. The team took an interdisciplinary, collaborative approach, incorporating concepts from classical machine learning, computational biology, and chemistry to create a powerful new method of using the static snapshots from scRNA-seq to get dynamic information on how cells and genes change over time.
Spinning, magnetic micro-robots help researchers probe immune cell recognition
Researchers at the Pritzker School of Molecular Engineering and the Department of Chemistry at the University of Chicago have engineered tiny, spinning micro-robots that bind to immune cells to probe their function. The robot, or “hexapod,” gives scientists a new, highly adaptable way to study immune cells and to aid in the design of immunotherapies against cancer, infection, or autoimmune diseases.
Their results were published in Nature Methods.
Each hexapod robot has six arms containing molecules that might be recognized as foreign by the immune system — such as protein fragments from a tumor, virus, or bacterium. Researchers can use the hexapods to scan large collections of immune cells and discover which immune cells bind the foreign molecules of interest and how the hexapods’ movements impact that binding.
UChicago immunoengineering researchers decode the “cytokine storm” in sepsis
While many studies have examined the dynamics that lead to sepsis, the molecules of the immune system that are thought to produce significant damage to the body — cytokines — have not been fully understood. These proteins help control inflammation, but when the immune system responds more aggressively than it should, it can release a “cytokine storm” on all tissues, causing tissue injury, organ failure, and death.
To better understand sepsis and the role of cytokines, University of Chicago Pritzker School of Molecular Engineering (PME) researchers measured gene expression across tissues and organs affected by sepsis in a mouse model.
“We created the first organism-wide map of the effect of sepsis which uncovered a hierarchy within the cytokine storm,” said Asst. Prof. Nicolas Chevrier, co-author of the research. “And despite the chaotic nature of the storm, the rule that can explain this chaos turned out to be much simpler than we thought.”
The results, which could ultimately lead to new therapies for the condition, were published in Nature Immunology.
Researchers boost vaccines and immunotherapies with machine learning to drive more effective treatments
Small molecules called immunomodulators can help create more effective vaccines and stronger immunotherapies to treat cancer.
But finding the molecules that instigate the right immune response is difficult —the number of drug-like small molecules has been estimated to be 10^60, much higher than the number of stars in the visible universe.
A team from the Pritzker School of Molecular Engineering (PME) at the University of Chicago tackled the problem by using machine learning to guide high-throughput experimental screening of this vast search space.
In a potential first for the field of vaccine design, machine learning guided the discovery of new immune pathway-enhancing molecules and found one particular small molecule that could outperform the best immunomodulators on the market. The results are published in the journal Chemical Science.
“Inverse vaccine” shows potential to treat multiple sclerosis and other autoimmune diseases
A typical vaccine teaches the human immune system to recognize a virus or bacteria as an enemy that should be attacked. The new “inverse vaccine” does just the opposite: it removes the immune system’s memory of one molecule. While such immune memory erasure would be unwanted for infectious diseases, it can stop autoimmune reactions like those seen in multiple sclerosis, type I diabetes, or rheumatoid arthritis, in which the immune system attacks a person’s healthy tissues.
The inverse vaccine, described in Nature Biomedical Engineering, takes advantage of how the liver naturally marks molecules from broken-down cells with “do not attack” flags to prevent autoimmune reactions to cells that die by natural processes.
"What is so exciting about this work is that we have shown that we can treat diseases like multiple sclerosis after there is already ongoing inflammation, which is more useful in a real-world context," said PME Prof. Jeffrey Hubbell, who recently received the 2023 Kabiller Prize in Nanoscience and Nanomedicine.
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