Within a given tissue or organ, cells may appear very similar or even identical. But at the molecular level, these cells can have small differences that lead to wide variations in their functions.
Alex K. Shalek, an MIT associate professor of chemistry, relishes the challenge of uncovering those small distinctions. In his lab, researchers develop and deploy technologies such as single-cell RNA-sequencing, which lets them analyze differences in gene expression patterns and allows them to figure out how each cell contributes to a tissue’s function.
“Single-cell RNA-sequencing is an incredibly powerful way to examine what cells are doing at a given moment. By looking at associations among the different mRNAs that cells express, we can identify really important features of a tissue — like what cells are present and what are those cells trying to do,” says Shalek, who is also a core member of MIT’s Institute for Medical Engineering and Science and an extramural member of the Koch Institute for Integrative Cancer Research, as well as a member of the Ragon Institute of MGH, MIT and Harvard and an institute member of the Broad Institute of Harvard and MIT.
While his work focuses on identifying small-scale differences, he hopes that it will have large-scale implications, as he seeks to better understand globally important diseases such as HIV, tuberculosis, and cancer.
“A lot of what we do now is global collaborative work that really focuses on understanding the cellular and molecular basis of human diseases — partnering with people in over 30 countries on six continents,” he says. “I love fundamental work and the precision possible in model systems, but I’ve always been very motivated to connect our science to human health, and to understand what’s happening in different diseases so we can develop better preventions and cures.”
An individual approach
Shalek’s work in graduate school stimulated his interest in systems biology, which involves comprehensively measuring many aspects of a biological system using genomics and other techniques, then building models that account for the observed measurements, and finally testing the models in living cells using perturbation techniques. However, to his frustration, he often found that when he tried to test a prediction of a model, not all of the cells in the system would show the expected outcome.
“There was a lot of variability,” he says. “I’d see differences in the level of mRNAs, or in the expression or activity of proteins, or sometimes all my cells wouldn’t differentiate into the same thing.”
He began to wonder if it would be worthwhile to try to study each individual cell within a system, instead of the traditional approach of doing pooled sequencing of their mRNA. During his postdoc, he worked with Park and Aviv Regev, an MIT professor of biology and member of the Broad Institute, to develop technologies for sequencing all of the mRNA found in large sets of individual cells. This information can then be used to classify cells into distinct types and reveal the state they’re in at a given moment in time.
In his lab at MIT, Shalek now uses improvements he’s helped make to this approach to analyze many types of cells and tissues, and to study how their identities are shaped by their environments. His recent work has included studies of how cancer cell state impacts response to chemotherapy, the cellular targets of the SARS-CoV-2 virus, analysis of cell types involved in lactation, and identification of T cells primed to produce inflammation during allergic responses.
An overarching theme of this work is how cells maintain homeostasis, or the steady state of physical and chemical conditions within living organisms.
“We know how important homeostasis is because we know that imbalances can lead to autoimmune diseases and immunodeficiencies, or to the growth of cancers,” Shalek says. “We want to really define at a cellular level, what is balance, how do you maintain balance, and how do various environmental factors like exposures to different infections or diets alter that balance?”
Source – MIT News
