What is a cell village?

It is well known that differences in our genetics and environment contribute to diversity (or dysfunction) in how people think, socialize, and behave. What we do not fully understand though is how these factors shape the brain to influence complex traits and risk for disorders. Some of these questions have been answered over the past 20 years through genome-wide association studies (GWAS) that identified statistical relationships between human genotypes and phenotypes. However, these studies typically require thousands to millions of human participants, struggle to quantify environmental contributions, and do not tell us much about the where (e.g. tissue or cell type) or the when (e.g. stage of development) of the gene-trait association.  While stem cell-based models of early human brain development have filled in some knowledge gaps, these experiments in a dish often only investigate a few human cell lines at a time. As such, we are often left wondering if experimental results can be applied universally at the population level.

Cell villages capture genetic, molecular, and cellular phenotypic heterogeneity in a shared culture environment.

We reasoned that one way to overcome the limitations of human subject and human in vitro studies is to simply pool cells from different individuals (known as donors) into the same dish for experiments and multi-modal analysis. This system—dubbed a cell village—allows us to determine how natural genetic variation percolates across several levels of biology, including gene expression, epigenetics, and cellular phenotypes like proliferation, differentiation, and survival.

There are several benefits to the village approach. First, it virtually eliminates the well-to-well and plate-to-plate technical noise that tends to mask biological signals in conventional arrayed (e.g. one-donor-per-well) experimental designs. This improved sensitivity increases our chances of making meaningful discoveries with relatively small sample sizes.  Second, it reduces the number of samples needed for large-scale experiments. For example, if you wanted to study how 100 donors respond to 3 different treatments, a typical arrayed approach would require at least 300 samples (not including technical replicates or controls), whereas that same experiment in a village would require only 3 samples. Third, because of these technical advantages, we can characterize dozens to hundreds of different donors simultaneously under uniform culture conditions and reach conclusions that have population-level significance. Thus far, we have used villages to discover genetic risk factors for viral infection, common genetic variants that influence cell proliferation, and genetic factors that modify sensitivity to environmental pollutants.