Single cell RNA sequencing identifies distinct macrophage populations found in the liver!

Single cell RNA sequencing identifies distinct macrophage populations found in the liver!

A map of the cells in the human liver has been created, revealing for the first time differences between individual cells at the molecular level which can have a profound impact on their behavior in tissue, tumors and disease.

Using powerful, state-of-the-art technologies and software engineering, the research team mapped out the cellular landscape of 8,444 individual cells obtained from the tissues of healthy deceased donor human livers.

"For the past 20 years, we have studied the liver as a soup of cells as opposed to its individual components. This makes it difficult to target individual cells that are driving liver disease," says the lead author of the study.

By examining the gene expression profiles of each of these cells - about 1,500 active genes per cell - the research team found 20 distinct cell populations made up of hepatocytes, endothelial cells, cholangiocytes and various immune cells such as B cells, T cells and Natural Killer (NK) cells.

"These evaluations reveal new aspects of the immunobiology of the liver, such as the presence of two surprisingly distinct populations of liver resident macrophages ("big-eaters" of cellular debris) with inflammatory and non-inflammatory functions," write the authors in their paper published today in Nature Communications.

"We present a comprehensive view of the liver at single cell resolution that outlines new characteristics of resident cells in the liver, and in particular provides a new map of the human hepatic immune microenvironment," note the authors.

The researchers were able to develop the best protocols using enzyme mixtures to gently dislodge cells embedded in the spider web-like net of connective tissue of the liver, without actually harming the fragile cells themselves. Only then could the team begin studying the molecular make-up of each cell individually. This step is absolutely essential in gaining a deeper understanding of how a small but critical change in a cell can precipitate a disease state within a complex mix of many other cells.

The latest technological advances helped the team to overcome the limitations of previous techniques such as genomics. Although it can analyze many cell types simultaneously "in bulk", it cannot tease out the critical differences between cells or do so in combination with multiple other data.