In our previous blog post (How to screen SARS-CoV-2 peptides to facilitate T cell research) we have described how the immune system samples all of the pathogenic proteins by looking at the small fragments of each protein and making a determination on whether that fragment (also referred to as peptide) belongs in the body. We have also described in our previous blog post (Find Human MHC Class I Dominant Peptides) the multiple MHC alleles that we tested for their ability to present SARS-CoV-2 peptides.
In our previous blog post (How to screen SARS-CoV-2 peptides to facilitate T cell research) we have described how the immune system samples all of the pathogenic proteins by looking at the small fragments of each protein and making a determination on whether that fragment (also referred to as peptide) belongs in the body. Not all peptides are presented equally and most of the amino acids that make up the proteins of the pathogen remain completely invisible to our immune system. One way the immune system can expand its ability to sample a larger variety of pathogen-derived peptide fragments is to have multiple varieties of MHC molecules each geared to detect a certain type of peptide.
In our previous blog post (How to screen SARS-CoV-2 peptides to facilitate T cell research) we have described how the immune system samples all of the pathogenic proteins by looking at the small fragments of each protein and making a determination on whether that fragment (also referred to as peptide) belongs in the body. Not all peptides are presented to the immune system equally and most of the amino acids that make up the proteins of the pathogen remain completely invisible to our immune system. It is only a small portion of the entire amino acid sequence that gets examined by the immune system. That is why it is crucial to know which peptides from the pathogen you are trying to study are actually presented to the immune system, and, more importantly, which of those peptides are able to stimulate an immune response.
Whenever our immune system is faced with a challenge, be it a multicellular parasite, a bacteria, a virus, or even cancer, this threat is detected and sampled primarily by the protein sequence of the pathogen in question. Other aspects of the pathogen, such as its glycosylation pattern or the peculiar structures of its RNA and DNA molecules could have a strong effect on how the immune system deals with it. But, overall, the adaptive aspect of the mammalian immune system has evolved over many years to examine the protein sequences that make up the invading pathogen. The key function of our immune system relies on its ability to constantly sample all proteins present in our body and determine whether it is a protein that belongs or a protein that must be eradicated together with any cells or organisms that produce it. Unfortunately, most proteins are too large for the immune system to sample at once and so it has developed a mechanism to cut the full-length proteins into small stretches of amino acids which are examined individually.
The use of MHC tetramers for the detection of antigen specific T cells has been a well-established technique since it originally gained prominence in the mid-1990s. Since then, the sophistication of MHC tetramer and multimer design as well as its sensitivity in detecting target T cells has been steadily improving. Most applications of MHC Tetramers involve the use of Flow Cytometry to enumerate, purify or sort specific T cells, but in some cases, it is possible to use tetramers to visualize entire immunological processes taking place inside a whole body.
We want to bring to your attention a recent paper by Welsh and Song et. al. (Plos Biology Feb, 2020)1. In their study, while constantly using MHC Class II tetramers to detect and enumerate pathogenic T cells, responsible for the progression of Rheumatoid Arthritis (RA) as well as Experimental Autoimmune Encephalomyelitis (EAE) induced in mice models, the group performed a number of imaging trials. This imaging procedure involved a modified in vivo NIRF whole-body imaging technique described in the paper. The group was successful in identifying a co-localized population of Collagen peptide specific T-cells and a molecular probe specific for denatured Collagen protein molecules using an IRDye800CW-conjugated CII(280–294) peptide loaded HLA-DR1 tetramer.
Our understanding of how the immune system responds to cancer has increased by leaps and bounds in the past two decades, allowing us to develop a new approach to fight cancer that uses the power of the body’s own immune system to prevent, target, control, and eliminate the disease. Collectively, this technique of battling cancer is known as cancer immunotherapy. Such an approach encompasses many methods from broad ones like applying immune checkpoint blockers (ICB) or using monoclonal antibodies (mAbs) that target known cancer antigens to more personalized ones like adoptive T cell transfer including the use of Chimeric antigen receptor (CAR) T cells.
It is this personalized immunotherapy approach that has sparked a great deal of interest among researchers. This method involves the extraction of a patient’s T cells and the subsequent stimulation of the rare T cells populations that can fight cancer with specific antigens. For this form of therapy to work there needs to be an exact knowledge of the peptide sequences derived from tumor cells (neo-epitopes) that can be used to artificially stimulate a patient’s T cells to fight them.
Previously, we have described how by using the QuickSwitchTM Quant Platform peptides, they can be tested for their ability to bind MHC Class I molecules. This test does not involve prediction algorithms or large swaths of data with a great deal of false positives but provides an in vitro result of whether or not the peptide can be presented on the MHC molecule in about 8 hours. It is our hope that by using our kit, researchers will be able to discover and validate neoantigen peptide sequences more effectively, which would open up new ways for adoptive T cell transfer in cancer immunotherapy.