To understand how cells behave, researchers also need to understand the molecules that make them work. “If someone wants to know how the kidney functions, they have to know what’s going on inside the kidney cells,” says Yang Liu, PhD, assistant professor of pathology. “This is defined by the protein activity.”
But most spatial transcriptome sequencing studies don’t include the proteins, leaving out vital information about the mechanisms of disease progression. Now, in their latest study, a Yale team performed a high-plex protein and whole-transcriptome co-mapping that measured nearly 300 proteins and transcriptome in human tissues. They published their findings in Nature Biotechnology on February 23.
“This is a game changer—crossing the central dogma of molecular biology and looking at hundreds of proteins simultaneously,” says Rong Fan, PhD, Harold Hodgkinson Professor of Biomedical Engineering and of Pathology and the study’s senior author.
Protein data has been largely absent from studies because of the technical limitations of immunofluorescence and immunohistochemistry, which made it challenging to image proteins in large numbers. “About 10 years ago, if someone simultaneously imaged a handful of protein markers, it was stunning,” says Fan. But in 2020, the team published a study in Cell using a technique called deterministic barcoding in tissues. The work involved delivering DNA tags into tissues using antibodies that can target specific proteins, tagging 22 proteins in total, in addition to mRNA molecules. This was the first study to co-map the transcriptome and proteins.
In their latest study, the team built on their previous work by using these methods to profile the whole transcriptome and 189 proteins in several mouse tissues. They also measured the whole transcriptome and 273 proteins in human tissue. “Our study is unique for two reasons. First, we co-profile RNA and proteins at the same time in the same tissue sections. There are no other technologies that can do this,” says Liu, who was the first author of the study. “Second, nearly 300 proteins imaged in the same tissue section is really a world record.”
Among the human tissues collected were skin samples following vaccination by the COVID-19 Moderna vaccine. With the guidance and expertise of David Hafler, MD, chair and William S. and Lois Stiles Edgerly Professor of Neurology and professor of immunobiology, Mary Tomayko, MD, PhD, associate professor of dermatology and of pathology, and Marcello DiStasio, MD, PhD, assistant professor of pathology, the team performed human skin biopsies to better understand immune activation responses at the injection site. They discovered a unique subset of cells known as peripheral helper T cells aggregated at the site. “The way we were able to identify the cells and visualize where they are highlights the power of our technology,” says Fan. The team also used their technology to measure human lymphoid tissues such as tonsils and revealed distinct immune reactions in collaboration with Joseph Craft, MD, Paul B. Beeson Professor of Medicine (Rheumatology) and professor of immunobiology, Stephanie Halene, MD, Arthur H. and Isabel Bunker Associate Professor of Medicine and chief of hematology, and Mina Xu, MD, associate professor of pathology and laboratory medicine, and director of hematopathology.
The study only observed surface proteins, or proteins on the cell membrane. The team hopes to apply its technology to also look at intracellular signaling proteins and extracellular matrix proteins. “In the future, we want to continue to make this technology more powerful and increase the number of proteins we study to thousands,” says Fan.
The team is excited about the study’s implications in terms of better understanding disease and aging. For instance, they are interested in using their technology to learn more about inflammation in aged or diseased tissues. They also are optimistic about using this technology to study tumors and the tumor microenvironment. “Now we can study hundreds of proteins and define different cell types. Then, we can see how these different cell types interact with tumor cells,” says Fan. “This is a powerful technology, and it’s prime time to dive into these challenging human health and disease research questions.”