Traditionally, flow cytometry has been the preferred method to characterize immune cells at the single-cell level. Flow cytometry is used in immunology mostly to measure the expression of identifying markers on the cell surface, but—with good antibodies—can also be used to assess the expression of intracellular proteins. The advent of single-cell RNA-sequencing has paved the road to study immune development at an unprecedented resolution. Single-cell RNA-sequencing studies have not only allowed us to efficiently chart the make-up of heterogeneous tissues, including their most rare cell populations, it also increasingly contributes to our understanding how different omics modalities interplay at a single cell resolution. Particularly for investigating the immune system, this means that these single-cell techniques can be integrated to combine and correlate RNA and protein data at the single-cell level. While RNA data usually reveals a large heterogeneity of a given population identified solely by a combination of surface protein markers, the integration of different omics modalities at a single cell resolution is expected to greatly contribute to our understanding of the immune system.

T cell development in the mouse thymus has been studied extensively, but less is known regarding T cell development in the human thymus. We used a combination of single-cell techniques and functional assays to perform deep immune profiling of human T cell development, focusing on the initial stages of prelineage commitment. We identified three thymus-seeding progenitor populations that also have counterparts in the bone marrow. In addition, we found that the human thymus physiologically supports the development of monocytes, dendritic cells, and NK cells, as well as limited development of B cells. These results are an important step toward monitoring and guiding regenerative therapies in patients after hematopoietic stem cell transplantation.

An effective immune system is characterized by a diverse immune repertoire. There is a strong demand for accurate and quantitative methods to assess the diversity of the immune repertoire for various (pre-)clinical applications, including the diagnosis and prognosis of primary immune deficiencies, or to assess the response to therapy. Current strategies for immune diversity assessment generally comprise the visual inspection of the length distribution of rearranged T- and B-cell receptors. Visual inspections, however, are prone to subjective assessments and thus lead to biases. Here, we introduce ImSpectR, a unified approach to quantify immunodiversity using either spectratype, repertoire sequencing or single cell RNA sequencing data. ImSpectR scores various types of deviations from the expected length distribution and integrates these into one measure, allowing for robust quantitative comparisons of immune diversity across individuals or conditions.