Early HSC engraftment kinetics at the single cell level 

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The effect of cytokines on HSC differentiation

HSCs guarantee the production of a particularly large number of different cell types with each having a crucial and specific role for the functioning of our body. When physiological needs change, following invasion of pathogens, malignancies, or mere physical activity, also the requirement for the production of each of these different hematopoietic cell types changes. The fast and adequate adaptation of the hematopoietic differentiation is needed to match the current demand. Hormones and cytokines, as erythropoietin, are important players in this process and can act on cells throughout the hematopoietic tree, including on HSCs.

Cytokines act throughout the hematopoietic tree

For a long time, the enhanced production of specific hematopoietic cell subsets in times of need was mainly considered to results from the induction of proliferation of mature hematopoietic cells, or uni-lineage committed hematopoietic progenitors. A prime example is the proliferation of mature antigen-specific lymphoid cells upon antigen-recognition to guarantee an adaptive immune response after pathogen exposure. Also during innate immune responses this principle was considered to be major. Emergency granulopoiesis, the rapid production of neutrophils after infection, has for example been described to be initiated by the cytokine-mediated induction of proliferation and maturation in committed myeloid progenitor cells (Manz & Boettcher, 2014; J. L. Zhao & Baltimore, 2015). Likewise, erythropoietin was described to induce erythroid cell production in anemic conditions by increasing survival of committed erythroid progenitors (Richmond, Chohan, & Barber, 2005). Only more recently, the action of cytokines on less committed hematopoietic progenitors gained more/new interest. To allow the production of a specific hematopoietic cell type, cytokines have been envisaged to act here, not by induction of proliferation, but rather through the instruction of lineage, meaning a “biasing” of differentiation. Such effect has for example been shown for M-CSF, and IFN-g acting on GMP (Rieger, Hoppe, Smejkal, Eitelhuber, & Schroeder, 2009) (De Bruin et al., 2012). More recently, also insulin has been described to induce such bias, namely a lymphoid lineage commitment in MPPs (Xia et al., 2015). All in all, it seems today established that the combination of cytokine-induced proliferation and lineage instruction can regulate hematopoietic differentiation for most hematopoietic progenitors. The action of cytokines on HSC themselves is still more controversial.

HSC contribution to different lineages changes over time

After assessing the barcode lineage contributions in blood from the cohort of mice analyzed at week 2, 4 and 6, we went on to assess if clonal succession and stability are similarly important for each lineage and which lineage changes occur. Indeed, switches in output pattern, and from detection to no detection, were not evenly present in the different lineages (Figure 5 A-G). E-restricted clones were for example more likely not to be detected at a subsequent timepoint than clones with other output patterns (Figure 5 A, C and Figure S6). Clones detected as ME-restricted at week 2 were more likely to be producing B (as MB, MBE, or B) at week 4, as M- and E-restricted clones. Indeed, in general, B production was more than M- and E-production preceded by detection. This is in line with a longer production time (or delayed production) for B-cells at the single cell level. Besides, multi-outcome clones were more likely to stay, and to stay multi-outcome (Figure 5 A and Figure S6). In line with this, while from all clones detected throughout none kept its exact output pattern, some were detected in ME, MBE, and MBE over the different timepoints, staying multi-outcome throughout. For the clones detected in two lineages over several timepoints, we did assess the bias over the different timepoints (Figure 5 E-G). Switches in all directions existed. It was however apparent that strongly biased clones had a lower chance to be detected at the next timepoint. So not only multilineage, but also balanced production of the three lineages favored subsequent detection, and detection in B-cells.

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High output in the myeloid, but not erythroid lineage characterizes stable clones

After analyzing the switches in output for all detected barcodes, we next thought to focus on lineage switches of the highest output clones; e.g. the clones producing over 1% of a lineage at a specific timepoint (Figure 6 A-B). Interestingly, the high output clones in the erythroid lineage behaved differently than the high output clones in the myeloid and B-cell lineage. At the week 2 timepoint, the high E output clones were detected only in the E-lineage and mostly not detected at subsequent timepoints (Figure 6 A-B). At the week 4 timepoint again a high percentage of erythroid clones was only detected at this timepoint. However, the high E output clones were not found in this category but rather among ME-restricted and multi-outcome MBE clones, and many of these clones were also detected at week 6 (Figure 6 A-B). Thereby, early high erythroid output clones were not stable; distinct clones maintained early high erythroid cell production. In contrast, the high M producing clones at week 2, 4, and 6 were evenly distributed between the different myeloid-outcome categories, and often detected thereafter. All of these clones kept producing myeloid cells, and some stayed among the highest abundant clones from week 2 till the week 6 timepoint (Figure 6 A-B). High myeloid output, contrary to early high erythroid output thereby was correlated to clonal stability. The high B producing cells at week 4 were mostly found in the multi-lineage outcome category (Figure 6 A-B). Besides, in contrast to high E and M producing clones, the majority had already been detected at week 2 (Figure 6 A-B). Which is, as for all clones, in line, with on a clonal level longer production time for B-cells, and speaking against existence of B-restricted HSCs.

Table of contents :

Chapter I: General introduction 
1.1 HSC definition and HSC differentiation models
1.2 Lineage tracing in the study of HSC differentiation
1.3 Lineage tracing of HSC at the single cell level by cellular barcoding
1.4 Lineage tracing reveals heterogeneity in HSC output-HSCs are “biased”
1.5 The effect of cytokines on HSC differentiation
1.6 Erythropoietin and HSCs
1.7 Aims of my thesis
Chapter 2: Early HSC engraftment kinetics at the single cell level 
2.1 Introduction
2.2 Results
2.3 Discussion
2.4 Materials and methods
2.5 Supplementary information
Chapter 3: The effect of erythropoietin on HSC differentiation 
3.1 Introduction
3.2 Results
3.3 Discussion
3.4 Materials and methods
3.5 Supplementary information
Chapter 4: What next? Outlook on cellular barcoding 
4.1 The promises of available HSC barcoding libraries
4.2 HSC barcoding entering the “omics” era
4.3 HSC barcoding and other dimensions
4.4 Beyond the single-cell level, intra-clonal heterogeneity
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