The term ICOS —inducible T cell co-stimulators— has been prominent in my work as a science writer at Promega, recently. Here is a brief look at ICOS, how it works, and how it can be used in therapeutics research and development.
T cells do amazing things, like driving or blocking production of B cells and their related antibodies and antibody maturation, and they are the primary drivers of innate immunity. T cells have a variety of surface molecules, the primary and omnipresent T cell receptor (TCR), as well as CD3.
In the past 15 years or so, researchers have identified other, inducible receptors on T cells. These receptors appear when T cells are stimulated, enabling interactions with other cell types. The following information is summarized from a Frontiers in Immunology review by Wikenheiser et al.
Imagine you’re taking a refreshing night swim in the warm blue waters of Vieques in Puerto Rico. You splash into the surf and head out to some of the deeper waters of the bay, when what to your wondering eyes should appear, but blue streaks of light in water that once was clear. Do you need to get your eyes checked? Are you hallucinating? No! You’ve just happened upon a cluster of dinoflagellates, harmless bioluminescent microorganisms called plankton, that emit their glow when disturbed by movement. These dinoflagellates are known to inhabit waters throughout the world but are generally not present in large enough numbers to be noticed. There are only five ecosystems in the world where these special bioluminescent bays can be seen, and three of them are in Puerto Rico.
But you don’t have to travel to Puerto Rico or swim with plankton to see bioluminescence. There are bioluminescent organisms all over the world in many unexpected places. There are bioluminescent mushrooms, bioluminescent sea creatures—both large and small (squid, jellyfish, and shrimp, in addition to the dinoflagellates)—and bioluminescent insects, to name a few. Bioluminescence is simply the ability of living things to produce light.
This post was contributed by guest blogger, Scott Messenger, Technical Support Scientist 2 at Promega Corporation.
It’s always an exciting time in the lab when you find a new assay to answer an important research question. Once you get your hands on the assay, it is always good to confirm it will work for your experimental setup. Repeating the control experiment shown in the technical manual is a great way to test the assay in your hands.
After running that first experiment of your assay, it looks pretty good. The trends of control and treatment are consistent. Time to get on with the experiments…but wait—the RLUs (Relative Light Units) are two orders of magnitude lower than the example data! I can’t show this data to my colleagues; it doesn’t match. What did I do wrong?
This is a concern that we in Technical Services hear frequently. The concern is real, and I had this same thought when doing some of my first experiments using luminescence. When a question like this comes in, a Technical Service Scientist will make sure the experiment was performed as we described, and in most cases it is. We then start talking about RLUs (Relative Light Units).
Clostridiumdifficile is a bacterium that infects around half a million people per year in the United States. The infection causes symptoms ranging from diarrhea to severe colitis, and it’s one of the most common infections contracted while staying in the hospital. As the global incidence of C. diff infection has risen over the past decade, so has the pressure to develop novel therapeutic strategies. This requires a thorough exploration of all aspects of C. difficile biology.
Two recent papers published by researchers at the University of Leiden have shed light on C. difficile physiology using HiBiT protein tagging. The HiBiT system allows detection of proteins in live cells using an 11 amino acid tag. The HiBiT tag binds to the complementary LgBiT polypeptide to reconstitute the luminescent NanoBiT® enzyme. The resulting luminescence is proportional to the amount of HiBiT-tagged protein that is present.
Many cell biology researchers can name their department’s or institutions’s “cell culture wizard”—the technician with 20+ years of experience whose cell cultures are always free from contamination, exhibit reliable doubling rates and show no phenotype or genotype weirdness. Cell culture takes skill and experience. Primary cell culture can be even more difficult still, and many research and pharmaceutical applications require primary cells.
Yet, among the many causes of failure to replicate study results, variability in cell culture stands out (1). Add to the normal challenges of cell culture a pandemic that shut down cell culture facilities and still limits when and how often researchers can monitor their cell culture lines, and the problem of cell culture variability is magnified further.
Treating Cells as Reagents
A good way to reduce variability in cell-based studies is to use the thaw-and-use frozen stock approach. This involves freezing a large batch of “stock” cells, then performing quality control tests to ensure they respond appropriately to treatment. Then whenever you need to perform an assay, just thaw another vial of cells from that batch and begin your assay—just like an assay reagent! This approach eliminates the need to grow your cells to a specific stage, which could take days and introduce more variability.
There is still a lot we don’t know about COVID-19 and the virus, SARS-CoV-2, that caused the pandemic and changed the way we live. But there are two things we do know about the disease: 1) Patients with diabetes and high blood glucose levels are more likely to develop severe COVID-19 symptoms with higher mortality. 2) Patients that experience an uncontrolled inflammatory response, called the cytokine storm, also develop more severe COVID-19 symptoms. The fact that both high glucose levels and an exaggerated immune response drive severe disease suggests that the two may be linked. But how? The answer may lie in the metabolism of immune cells in the lungs of COVID-19 patients, according to a recent study published in Cell Metabolism.
Science is the practice of figuring out how things work and then using that knowledge to further our understanding or to create tools that can solve problems facing the world. Bioluminescent tools and assays are examples of science doing all these things. Bioluminescence is the light-yielding (luminescence) chemical reaction that is used by many lifeforms. When fireflies flicker in the twilight, they are using bioluminescence to flash on and off. Chemically, bioluminescence happens when an enzyme called luciferase acts on a light-emitting compound, luciferin, in the presence of adenosine triphosphate (ATP), magnesium and oxygen.
For scientists, bioluminescence can serve as a tool to help them understand many cellular functions. Since few animal or plant cells produce their own light, there is little to no background signal (light) to be concerned about. This lack of background means that all light coming from the sample can be measured. In fact, bioluminescence is often a preferred tool for scientists because it does not require an external light source or special filters, which are required for fluorescence-based technologies.
Promega scientists have developed bioluminescent tools and assays to support leading edge scientific research for decades, beginning in 1990 with the Luciferase biosensor technology based on firefly luciferase. Luciferase is a wonderful tool for studying how enzymes work because its output (light) is so easy to measure: samples are placed into a special instrument called a luminometer, and the amount of light being produced (Relative Light Units) is recorded. Bioluminescence technology can be configured to measure a variety of cellular biology, ranging from cell health to enzyme activity down to the specific event of turning a gene on or off. The advent of new techniques for genetic manipulation, along with an enhanced understanding of bioluminescence and the discovery and engineering of better luciferases, enables science to use bioluminescence in even more unique ways.
Our skin, respiratory system and gastrointestinal tract are continually bombarded by environmental challenges from potential pathogens like SARS-CoV-2. Yet, these exposures do not often cause illness because our immune system protects us. The human immune system is complex. It has both rapid, non-specific responses to injury and disease as well as long-term, pathogen-specific responses. Understanding how the immune response works helps us understand how some pathogens get past it and how to stop that from happening. It also provides key information to help us develop safe and effective vaccines.
The immune response involves two complementary pathways: Innate Immunity and Adaptive Immunity. Innate immunity is non-specific, rapid and occurs quickly after an injury or infection. As a result of the innate immune response, cytokines (small signaling molecules) are secreted to recruit immune cells to an injury or infection site. Innate immunity does not develop “memory” of an antigen or confer long-term immunity.
The immune response involves to complementary pathways: Innate Immunity and Adaptive Immunity.
Unlike innate immunity, adaptive immunity is both antigen-dependent and antigen-specific, meaning that adaptive immune response requires the presence of a triggering antigen—something like a spike protein on the surface of a virus. The adaptive immune response is also specific to the antigen that triggers the response. The adaptive immune response takes longer to develop, but it has the capacity for memory in the form of memory B and T cells. This memory is what enables a fast, specific immune response (immunity) upon subsequent exposure to the antigen.
Jonathan Campbell, PhD, asked me to write that he is taller and a bit more handsome than most scientists. I will neither confirm nor deny those assertions, but I will acknowledge that Dr. Campbell has a unique way of describing his recent collaborations and research on metabolism and Type 2 diabetes.
“The rest of the world has been thinking that it’s almost like the emperor has no clothes,” he says. “But we’re the guys who came right in and said ‘Hm, that dude’s naked.’”
On March 13, only a few days before the COVID-19 pandemic caused widespread shutdowns in Wisconsin, Jon visited the Promega headquarters in Madison, Wisconsin to meet with R&D scientists and discuss opportunities for new technologies. Over the course of a few hours, Jon and his collaborator Matthew Merrins, PhD, demonstrated how their research challenges dogma and could fundamentally change our understanding of postprandial metabolism. For five decades, the paradigm of glucose control focused on a model that positioned insulin and glucagon as diametrically opposing forces to raise or lower glycemia. As Jon states, things did not always add up.
“For years, everybody has been saying ‘Glucagon is the antithesis of insulin,’ right? Insulin is a good guy. It makes glucose come down. Glucagon is a bad guy. It makes glucose go up. And these two are in this cosmic battle against each other over the control of glycemia. Well, we asked, ‘Why do the beta cells that secrete insulin have glucagon receptors?’ And as you follow the breadcrumbs, you find that these two things are actually working in cooperation. Without that cooperation, the whole thing falls apart,” Jon says.
The Incretin Effect
In addition to exploring the complex biology of glucagon, Jon’s lab studies the Incretin Effect, a mechanism by which the gut influences the secretion of insulin in the pancreas. Past research revealed that rises in blood-glucose matched closely whether glucose was administered orally or intravenously. However, the amount of insulin secreted was 3—4 times higher following oral intake. This is a result of the actions of GLP1 and GIP, the two major human incretins. GLP1 and GIP bind to G-protein coupled receptors in the beta cells of the pancreas to induce insulin secretion. Insulin then acts to promote glucose uptake, reducing glycemia. Many researchers believe that dysfunction of the incretin mechanisms contributes to the reduced insulin secretion seen in individuals with Type 2 diabetes.
“If we can understand the mechanisms of the incretin effect,” Jon says, “We may be able to understand the pathophysiology driving Type 2 diabetes. My hope is that people are going to realize that diabetes is not just a glucose disease. Maybe we have been looking at this too much from a glucose-centric viewpoint. Clearly, glucose is a big problem with diabetes, but it’s not just glucose. This is a metabolic disease, and in order to understand how to fix a metabolic disease, you need to look at all the metabolites and the way overall metabolism is dysregulated.”
Research on the incretin effect has already supported the development of two new classes of drugs for Type 2 diabetes: GLP1R agonists and DPP4 inhibitors (DPP4 is an enzyme that degrades GLP1).
“We collaborate with industry quite a bit, especially pharmaceuticals. We are helping them understand the mechanism of action by which their drugs may work, and that funding has allowed us to expand and grow our program a lot in our first five years. I like to bridge that line between basic and translational science—translating basic science into the clinic.”
The Search for New Technology
Jon wasn’t visiting Promega in mid-March with the goal of seeing the world before COVID-19-related travel restrictions were announced. He’s constantly looking for new collaborations in which both parties can bring something unique to the table. Jon was one of the first to try the new Lumit™ Insulin and Glucagon Immunoassays, which he says are easier to use and have produced better results in his work with glucagon than radioimmunoassays or ELISAs.
“People like Promega scientists say they have a new technology, and they’re looking for someone to try it out it in real-world situations. I don’t have that kind of technology, but I know how to apply it, so there’s a lot of value there. It’s a no-brainer to talk to people about how we can find synergy when the two of us both bring something like that to the table. For some applications, the Lumit™ assays are blowing out whatever we can do, and they’re also incredibly easy to use. So that was a significant improvement in our workflow.”
When asked what he hopes to accomplish in the next few years, Jon similarly points to innovative technology and techniques.
“We have to say, ‘What’s the next innovative step forward, and what new tools can we bring?’ We need to figure out new ways to interrogate the systems that we’re interested in. Then we can start to strip away new biology. If we ask the right question and we answer definitively, we’ll end up with three more questions. Which is great, because we’ll always have more work to do.”
Lumit™ Immunoassays provide a simple and fast alternative to conventional immunoassay methods including sandwich ELISAs and Western blots. Learn more here.
Working on diabetes research? Read more about Promega assays to measure insulin activity in real time.
Studying protein function in live cells is limited by the tools available to analyze the expression and interactions of those proteins. Although mass spectrometry and antibody-based protein detection are valuable technologies for protein analysis, both methods have drawbacks that limit the range of targets and contexts in which proteins can be investigated.
Mass spectrometry is often poor at detecting low-abundance proteins. Antibody-based techniques require high quality, specific antibodies, which can be difficult to impossible to acquire. Both methods require cell lysis, preventing real-time analysis and limiting the physiological relevance, and both methods can be limiting for higher-throughput analysis. While plasmid-based overexpression of tagged target proteins simplifies detection and can allow for real time analysis, protein levels don’t typically resemble endogenous levels. Overexpression also has the potential to create experimental artifacts or limit the dynamic range of an observed response.
While their findings showed that this method provides efficient and specific tagging of endogenous proteins, the research was limited to just five different proteins within a single signaling pathway in two cell lines. This left unanswered questions about whether this approach was scalable, had broader applications and how accurately the natural biology of the cells was represented.