Functional compensation between hematopoietic stem cell clones in vivo

Abstract

In most organ systems, regeneration is a coordinated effort that involves many stem cells, but little is known about whether and how individual stem cells compensate for the differentiation deficiencies of other stem cells. Functional compensation is critically important during disease progression and treatment. Here, we show how individual hematopoietic stem cell (HSC) clones heterogeneously compensate for the lymphopoietic deficiencies of other HSCs in a mouse. This compensation rescues the overall blood supply and influences blood cell types outside of the deficient lineages in distinct patterns. We find that highly differentiating HSC clones expand their cell numbers at specific differentiation stages to compensate for the deficiencies of other HSCs. Some of these clones continue to expand after transplantation into secondary recipients. In addition, lymphopoietic compensation involves gene expression changes in HSCs that are characterized by increased lymphoid priming, decreased myeloid priming, and HSC self‐renewal. Our data illustrate how HSC clones coordinate to maintain the overall blood supply. Exploiting the innate compensation capacity of stem cell networks may improve the prognosis and treatment of many diseases.

Introduction

Hematopoietic stem cells (HSCs) are scattered throughout the body in dispersed bone marrow niches and must coordinate to maintain a common pool of peripheral blood cells 1. We have recently shown that HSCs can adapt their differentiation programs to the presence of other HSCs at various transplantation doses to ensure overall balanced blood production 2. A similar coordination mechanism may allow HSCs to rescue the functional deficiencies of other impaired HSCs within the same organism.

It is critically important to understand how the functional deficiencies of a subset of HSCs impact the overall HSC network. Many hematopoietic diseases arise from either an abnormal abundance (e.g., myeloproliferative disorder, thrombocytosis, leukocytosis, and erythrocytosis) or an abnormal deficiency (e.g., myelodysplastic syndrome, neutropenia, agranulocytosis, and thrombocytopenia) of certain blood cell types 3, 4, 5. The initial stages of these diseases may involve a latent period during which a patient's healthy HSCs can sufficiently compensate for the deficiencies of diseased cells to ameliorate disease symptoms. In addition, bone marrow transplantation, the primary treatment for many of these diseases, requires donor HSCs to adapt their differentiation programs to the disease environment 6. Functional compensation between HSCs, especially in the lymphoid lineages, may also take place during aging, as lymphopoietic deficiencies often develop in the elderly 7. Few studies have attempted to understand the compensation capacity of regenerative networks. In this study, we offer new insights into the compensation mechanisms at both the cellular and molecular levels.

Previous studies using limiting dilution assays of HSC transplantation show that the number of donor HSCs quantitatively determines the fraction of blood cells that they produce 8, 9, 10. These experiments suggest a coordination model where individual HSCs play equal roles and uniformly alter their blood production in response to changes in hematopoiesis. However, these assays analyze HSCs as a population, and the differences between individual HSCs are hidden. Recent work from our group and others has shown that HSC differentiation is heterogeneous at the clonal level 11, 12, 13, 14, 15, 16, 17, 18. For example, individual HSCs supply differential amounts of blood cells in mice and in human patients 13, 14, 16, 17, 18. Moreover, recent studies of native hematopoiesis suggest that different blood cell types have distinct clonal origins 19. These new findings raise the question of how the diverse differentiation programs of individual HSCs are coordinated in the aftermath of functional disruptions. In this study, we use a co‐transplantation experimental model and high‐throughput genetic barcode tracking technology to address this question. We show how wild‐type (WT) HSCs compensate for genetically mutated HSCs that are deficient in supplying one or multiple types of lymphocytes.

Results and Discussion

To investigate how HSCs functionally compensate for the lineage deficiencies of other HSCs within an organism, we co‐transplanted WT HSCs and lineage‐deficient HSCs into lethally irradiated WT recipient mice (Fig 1A, and Appendix Figs S1 and S2). In our experimental models, we focused on B‐cell deficiency as well as B‐ and T‐cell double deficiencies, because B and T cells are the most abundant lymphocytes (Appendix Fig S3). B‐deficient HSCs were isolated from uMT^−/− mice, and co‐transplanted with WT HSCs at two different doses but at the same ratio (1:3): 1,000 WT CD45.2 HSCs and 3,000 uMT^−/− CD45.1 HSCs (Figs 1, 2, 3, 4, 5); 3,000 WT CD45.2 HSCs and 9,000 uMT^−/− CD45.1 HSCs (Figs EV1 and EV2, and Appendix Fig S4). Results from the two doses are generally consistent (Figs EV1 and EV2, and Appendix Fig S4), suggesting that the transplantation dose plays a minor role in regulating the lymphopoietic compensation. B and T double‐deficient HSCs were isolated from NSG and Rag2^−/−γc^−/− mice. The genetic background of deficient HSCs plays a minor role in regulating lymphopoietic compensation, as our results are generally consistent using the two different strains (Figs EV1 and EV2, and Appendix Fig S4). We co‐transplanted 1,500 WT CD45.2 HSCs and 3,000 NSG or Rag2^−/−γc^−/− CD45.1 HSCs per recipient (Appendix Fig S2). Recipients for all experiments were CD45.1/CD45.2 WT mice. They were lethally irradiated prior to the transplantation, and each received 250,000 whole bone marrow cells (helper cells) that assist in blood production. For the control groups, we co‐transplanted HSCs from WT (CD45.1) and WT (CD45.2) donor mice at the same doses as the deficient co‐transplantation groups.

Figure 1. Wild‐type (WT) HSCs compensate for the lymphopoietic deficiencies of co‐transplanted mutant HSCs in blood production.

• A
  We co‐transplanted barcoded WT HSCs with competitor WT, B cell‐deficient (uMT^−/−), or B cell‐ and T cell‐deficient (NSG or Rag2^−/−γc^−/−) HSCs into irradiated recipient mice. Peripheral blood was harvested from recipient mice at 6–8 months after transplantation and sorted into granulocytes (Gr), B, CD4 T, and CD8 T cells for population and clonal level analyses.
• B, C
  Competitor donor‐derived Gr, B, CD4 T, and CD8 T cells in the peripheral blood. In the control group, competitor donor cells are WT HSCs. In the deficient group, competitor donor cells are uMT^−/− or NSG HSCs.
• D, E
  WT donor‐derived Gr, B, CD4 T, and CD8 T cells in the peripheral blood.
• F, G
  Total production of Gr, B, CD4 T, and CD8 T cells in the peripheral blood (derived from WT HSCs, competitor HSCs, helper whole bone marrow cells, and residual host cells).

Data information: Data are shown as percentages of the total number of white blood cells (WBCs). Data were collected at month 7 post‐transplantation for the uMT^−/− group and month 8 post‐transplantation for the NSG group and presented as mean ± SEM. n = 7 mice for the uMT^−/− group and n = 6 for the NSG group. For each control group, the same number of mice were used as the respective deficient group. *P < 0.05, **P < 0.01, ***P < 0.001 (two‐tailed and two‐sample equal variance Student's t‐test).

Figure 2. Highly expanded HSC clones increase their differentiation in response to the lymphopoietic deficiencies of other HSCs.

• A, B
  Total numbers of barcoded WT clones that give rise to granulocytes (Gr), B cells, CD4 T cells, and CD8 T cells.
• C–J
  Number of HSC clones that produce different amounts of Gr, B, CD4 T, and CD8 T cells. We combined the sequencing data with the flow cytometry data to calculate clonal abundance for each clone as follows: Clonal abundance = 100% × (Each cell population (Gr, B, CD4T or CD8T cells) % WBCs) × (Donor % Each cell population) × (GFP % Donor cells) × (number of reads for each barcode)/(total reads of all barcodes).
• K, L
  Production of Gr, B, CD4 T, and CD8 T cells by expanding WT clones that produce more than 0.1% of WBCs in each lineage.

Data information: Data were collected at month 7 post‐transplantation for the uMT^−/− group and month 8 post‐transplantation for the NSG group, and presented as mean ± SEM. n = 7 mice for the uMT^−/− group and n = 6 for the NSG group. For each control group, the same number of mice were used as the respective deficient group. *P < 0.05 (two‐tailed and two‐sample equal variance Student's t‐test).

Figure 3. Persistence of lymphopoietic compensation in secondary transplantation.

• A
  We co‐transplanted barcoded wild‐type (WT) HSCs and B cell‐deficient (uMT^−/−) competitor HSCs into irradiated recipient mice. WT HSCs were used as competitor HSCs in the control group. Seven months after the primary transplantation, we harvested peripheral blood cells and purified both WT HSCs and competitor HSCs from the bone marrow. HSCs from one primary recipient mouse were transplanted into one secondary recipient mouse. 4 months after the secondary transplantation, peripheral blood cells were sorted into granulocytes (Gr), B, CD4 T, and CD8 T cells for population and clonal level analyses.
• B
  WT donor‐derived Gr, B, CD4 T, and CD8 T cells in the peripheral blood shown as percentages of the total number of white blood cells (WBCs).
• C
  Competitor donor‐derived Gr, B, CD4 T, and CD8 T cells in the peripheral blood shown as percentages of the total number of WBCs. In the control group, competitor donor cells are WT HSCs. In the deficient group, competitor donor cells are uMT^−/− or NSG HSCs.
• D
  Total production of Gr, B, CD4 T, and CD8 T cells in the peripheral blood (derived from WT HSCs, competitor HSCs, helper whole bone marrow cells, and residual host cells) shown as percentages of the total number of WBCs.
• E
  Total numbers of barcoded WT clones that give rise to Gr, B, CD4 T, and CD8 T cells.
• F–I
  Number of HSC clones that produce different amounts of Gr, B, CD4 T, and CD8 T cells. We combined the sequencing data with the flow cytometry data to calculate clonal abundance for each clone as follows: Clonal abundance = 100% × (Each cell population (Gr, B, CD4T or CD8T cells) % WBCs) × (Donor % Each cell population) × (GFP % Donor cells) × (number of reads for each barcode)/(total reads of all barcodes).
• J
  Production of Gr, B, CD4 T, and CD8 T cells by expanding clones that produce more than 0.1% of WBCs in each lineage.
• K
  Percentage of expanding clones in the B‐cell lineage from the primary recipients that continued to expand in the B‐cell lineage of the secondary recipients. Expanding clones are defined as those producing more than 0.1% of WBCs.

Data information: Data were collected at month 4 after secondary transplantation and presented as mean ± SEM. n = 7 mice for the primary control (WT + WT) and deficient co‐transplantation (WT + uMT^−/−) groups. n = 4 mice for the secondary transplantation control group (WT + WT) and n = 6 for the secondary deficient co‐transplantation group (WT + uMT^−/−). *P < 0.05 and **P < 0.01 (two‐tailed and two‐sample equal variance Student's t‐test).

Figure 4. Compensation for lymphopoietic deficiency is manifested as an increase in cell numbers at the progenitor level.

• A, B
  Total amount of progenitors as a percentage of ckit and Il7rα enriched bone marrow (BM) cells. Shown are hematopoietic stem cell (HSC), Flk2⁻ and Flk2⁺ multipotent progenitor (MPP), common lymphoid progenitor (CLP), common myeloid progenitor (CMP), megakaryocyte‐erythroid progenitor (MEP), and granulocyte‐macrophage progenitor (GMP).
• C, D
  WT donor‐derived progenitors as a percentage of ckit and Il7rα enriched BM cells.

Data information: Data were collected at month 7 post‐transplantation for the uMT^−/− group and month 8 post‐transplantation for the NSG group, and presented as mean ± SEM. n = 7 mice for the uMT^−/− group and n = 6 for the NSG group. For each control group, the same number of mice were used as the respective deficient group. *P < 0.05 and **P < 0.01 (two‐tailed and two‐sample equal variance Student's t‐test).

Figure 5. Differential gene expression of HSCs during lymphopoietic compensation.

1. Number of genes that are differentially expressed in WT HSCs co‐transplanted with NSG or uMT^−/− HSCs as compared to WT HSCs co‐transplanted with WT HSCs in the control group. Gene lists are generated by Partek Flow. Thresholds are defined as P < 0.05 and fold change < −2 or > 2.
2. Biological functions that are expected to increase or decrease based on the observed gene expression changes generated by the Ingenuity Pathway Analysis (IPA). Representative genes involved in each biological function are shown on the left. HSPC is an abbreviation for hematopoietic stem and progenitor cells. NK is an abbreviation for natural killer cells. Shown are the functions with Fisher's exact test P‐value < 0.05.
3. Top genes whose expressions are both upregulated or both downregulated in the NSG and uMT^−/− co‐transplantation groups compared to the control group. Shown are the genes whose expression passes the threshold P < 0.05 and fold change < −2 or > 2.
4. Predicted upstream regulators based on the observed gene expression changes and the known gene regulatory relationships in the IPA database.
5. Regulatory genes of key hematopoiesis steps that are significantly changed in the NSG co‐transplantation group compared to the control group. Multipotent progenitor (MPP), common myeloid progenitor (CMP), megakaryocyte‐erythroid progenitor (MEP), granulocyte‐macrophage progenitor (GMP), erythrocyte (Ery), granulocyte (Gr), megakaryocyte (Meg), monocyte (Mon), and macrophage (Mac), and common lymphoid progenitor (CLP).

Data information: Ingenuity Pathway Analysis (IPA) was used to perform gene ontology analysis on differentially expressed genes. Data were collected at month 7 post‐transplantation for the uMT^−/− group and month 8 post‐transplantation for the NSG group. n = 3 mice for each group, except for the NSG control group where n = 2 mice.

Figure EV1. Wild‐type (WT) HSCs compensate for the lymphopoietic deficiencies of co‐transplanted mutant HSCs in blood production (Supplemental data for Fig 1).

• A
  uMT^−/− mice do not produce B cells, but produce normal levels of Gr, CD4 T, and CD8 T cells.
• B, C
  Competitor donor‐derived Gr, B, CD4 T, and CD8 T cells in the peripheral blood. In the control group, competitor donor cells are WT HSCs. In the deficient group, competitor donor cells are uMT^−/−, NSG, or Rag2^−/−γc^−/− HSCs.
• D, E
  WT donor‐derived Gr, B, CD4 T, and CD8 T cells in the peripheral blood.
• F, G
  Total production of Gr, B, CD4 T, and CD8 T cells in the peripheral blood (derived from WT HSCs, competitor HSCs, helper whole bone marrow cells, and residual host cells).

Data information: All panels are shown as percentages of the total number of white blood cells (WBCs). Data from experiments in Fig 1 and Appendix Fig S4 were combined and presented as mean ± SEM. n = 15 mice for each group. *P < 0.05, **P < 0.01, and ***P < 0.001 (two‐tailed and two‐sample equal variance Student's t‐test).

Figure EV2. Highly expanded HSC clones increase their differentiation in response to the lymphopoietic deficiencies of other HSCs (replicate experiment for Fig 2).

• A, B
  Total numbers of barcoded WT clones that give rise to Gr, B, CD4 T, and CD8 T cells.
• C–J
  Number of HSC clones that produce different amounts of Gr, B, CD4 T, and CD8 T cells. We combined sequencing data with flow cytometry data to calculate clonal abundance for each clone as follows: Clonal abundance = 100% × (Each cell population (Gr, B, CD4T or CD8T cells) % WBCs) × (Donor % Each cell population) × (GFP % Donor cells) × (number of reads for each barcode)/(total reads of all barcodes).
• K, L
  Production of Gr, B, CD4 T, and CD8 T cells by expanding clones that produced more than 0.1% of WBCs in each lineage.

Data information: Data were collected at month 6 post‐transplantation and presented as mean ± SEM. n = 8 mice for each group. *P < 0.05 (two‐tailed and two‐sample equal variance Student's t‐test).

We examined the peripheral blood of the recipient mice at 6–8 months after transplantation, when blood production has returned to a steady state and a stable group of HSC clones continuously supplies blood cells over time 9, 20, 21 (Appendix Fig S3). We found that in the uMT^−/− co‐transplantation groups, where deficient HSCs do not produce B cells (Figs 1B and EV1B, Appendix Fig S4A), WT HSCs significantly oversupplied B cells (Figs 1D and EV1D, and Appendix Fig S4C) to maintain normal levels of total B‐cell production (Figs 1F and EV1F, and Appendix Fig S4E). In the Rag2^−/−γc^−/− and NSG co‐transplantation groups, where deficient HSCs are unable to produce B cells, CD4 T cells, and CD8 T cells (Figs 1C and EV1C, and Appendix Fig S4B), WT HSCs significantly oversupplied B cells, CD4 T cells, and CD8 T cells (Figs 1E and EV1E, and Appendix Fig S4D) to maintain normal levels of total B‐ and T‐cell production (Figs 1G and EV1G, and Appendix Fig S4F). These data suggest that WT HSCs increase their differentiation specifically in the deficient lineages to maintain the balance of the overall blood supply.

In addition, we found that the presence of WT HSCs also changed the differentiation of lineage‐deficient HSCs. uMT^−/− mice have slightly higher levels of T cells (Fig EV1A), but uMT^−/− HSCs produced slightly fewer T cells in the co‐transplantation group (Fig 1B). This T‐cell reduction is statistically significant in a replicate experiment (Appendix Fig S4A), and when data from both experiments are combined (Fig EV1B). WT HSCs compensated for the reduction in B and T cells produced by uMT^−/− HSCs (Figs 1D and EV1D, and Appendix Fig S4C) such that the total B‐ and T‐cell levels are similar to the control group (Figs 1F and EV1F, and Appendix Fig S4E).

Lymphopoietic compensation may originate from an increase in the number of differentiating clones or from an elevated expansion in their differentiation. To distinguish between these two possibilities, we used a genetic barcoding technique that we had developed to track WT donor HSCs at the clonal level (Appendix Fig S5) 13. Genetic barcodes drawn from a large semi‐random 33mer DNA barcode library were used to uniquely label and track individual HSCs. We have verified that each barcode uniquely corresponds to a distinct HSC with more than 95% confidence and that the lentiviral vectors deliver the barcodes into quiescent HSCs without altering their properties 13. DNA barcodes are incorporated into the cellular genome and inherited by progeny cells along with regular genomic DNA. The abundance of a genetic barcode in a cell population is proportional to the number of progeny cells that the original barcoded cell produces. Barcodes are recovered by high‐throughput sequencing that reads millions of sequences from each sample and provides quantitative results. We found that the total numbers of WT clones that supply the myeloid and lymphoid lineages are similar between the control and deficient co‐transplantation groups (Figs 2A and B, and EV2A and B), indicating that compensation does not originate from increases in clone number.

To identify the HSC clones that respond to the lymphopoietic deficiencies, we categorized WT clones based on the abundance of their genetic barcodes in each blood cell population, and we called this “clonal abundance”. We found an increase in the number of clones that produced high amounts of B cells in the uMT^−/− co‐transplantation groups, and high amounts of B and T cells in the NSG and Rag2^−/−γc^−/− co‐transplantation groups (Figs 2C and G–I, and EV2C and G–I). In addition, these expanding clones supplied significantly larger amounts of lymphocytes in the deficient lineages (Figs 2K and L, and EV2K and L) that account for the majority of the lymphopoietic compensation (Figs 1D and E, and EV1D and E, Appendix Fig S4C and D). Taken together, these data suggest that lineage deficiency is primarily compensated by clones that highly expand.

At the same time, we found significantly fewer clones that expanded their granulocyte production in the presence of lymphopoietic deficient HSCs, suggesting that the myeloid differentiation of dominant clones was compromised (Fig 2F and J). In the replicate experiments, we found a similar reduction in the Rag2^−/−γc^−/− co‐transplantation group (Fig EV2J), but not in the uMT^−/− co‐transplantation group (Fig EV2F) possibly because of differences in the transplantation dose.

To determine whether the lymphopoietic compensation is determined at the HSC level, we purified both WT and deficient HSCs from primary recipients and transplanted them into WT secondary recipients (Fig 3A). In the secondary recipients, we found that WT donor HSCs from the uMT^−/− co‐transplantation group continued to produce high levels of B cells (Fig 3B) to compensate for the deficiency in B‐cell production of the uMT^−/− HSCs (Fig 3C). Secondary recipients displayed no significant differences in overall blood production (Fig 3D) and in total clone number (Fig 3E). We found that significantly more clones expanded to produce B cells and that significantly fewer clones expanded to produce granulocytes (Fig 3F, G, and J). These data are consistent with results from the primary transplantations (Figs 2 and EV2).

To determine whether compensating clones in the primary recipients remain compensating in the secondary recipients, we compared the WT clones that expanded in the B‐cell lineage. We found that the clones that had expanded in the B‐cell lineage in primary recipients were significantly more likely to maintain their expansion in secondary recipients when uMT^−/− HSCs are present (Fig 3K). Since purified HSCs were the only cells transplanted into the secondary recipients, our results suggest that lymphopoietic compensation may be determined and memorized at the HSC level.

To identify the differentiation stage at which cellular compensation takes place, we quantified the cell numbers of the total (Fig 4A and B) and WT donor‐derived stem and progenitor cells (Fig 4C and D, and Appendix Fig S6). We found significantly fewer total HSCs in both co‐transplantation groups (Fig 4A and B) and significantly fewer WT donor‐derived HSCs in the NSG co‐transplantation group (Fig 4D). Upon differentiation, HSCs first lose their self‐renewal potential and become multipotent progenitors (MPPs) that retain full differentiation potential 22. We found significantly reduced numbers of total MPPs in the NSG co‐transplantation group and WT donor‐derived MPPs in both groups (Fig 4B–D). This is likely the result of reduced HSC number. Further downstream, MPPs differentiate into the common lymphoid progenitor (CLP) and the common myeloid progenitor (CMP) 23, 24, 25. In both co‐transplantation groups, we found a significant increase in the number of total and WT donor‐derived CLPs (Fig 4). As CLPs supply B and T cells, an overproduction of CLPs to compensate for B‐cell deficiency will also increase T‐cell production. This explains the overproduction of CD4 T and CD8 T cells observed in the uMT^−/− co‐transplantation group (Fig EV1D and Appendix Fig S4C). The uMT^−/− co‐transplantation group also exhibited a reduction in the number of total and WT donor‐derived CMPs and granulocyte‐macrophage progenitors (GMPs; Fig 4A and C). Taken together, these data suggest that compensation for lymphopoietic deficiencies arises from CLP expansion, which is associated with compromised HSC self‐renewal and reduced myelopoiesis.

While the lymphopoietic compensation is manifested as an increase in cell numbers at the oligopotent progenitor level (Fig 4), it is possible that the compensation decision has already been made at the HSC stage. This predestination may be accomplished by lineage priming, where HSCs express a low level of key regulatory genes in specific lineages and poise themselves to differentiate toward the corresponding lineages 26, 27, 28. To determine whether this mechanism had taken place during the lymphopoietic compensation, we compared the gene expression profiles of WT phenotypic HSCs purified from the bone marrow of mice co‐transplanted with deficient HSCs with those from the control mice (Appendix Fig S7). The purity of phenotypic HSCs (lineage (CD3, CD4, CD8, B220, Gr1, Mac1, Ter119)⁻/ckit⁺/Sca1⁺/Flk2⁻/CD34⁻/CD150⁺) from previously transplanted bone marrow may differ from the phenotypic HSCs from naïve bone marrow 12. We found significant activation of genes involved in diseases, biological functions, and networks that are related to lymphopoietic compensation (Fig EV3, and Tables EV1 and EV2). We also found significant activation of functions related to cell proliferation, hematological system development, and cell‐to‐cell signaling and interaction (Fig EV3, and Tables EV1 and EV2). These data suggest that compensation for lymphopoietic deficiency may be communicated and determined at the HSC level. Ninety‐six genes changed significantly in both co‐transplantation groups (Fig 5A). The WT HSCs from the two co‐transplantation groups both have up‐regulated genes involved in biological functions that support compensation for lymphopoietic deficiencies, including quantity of lymphocytes and proliferation of blood cells (Fig 5B). In the NSG co‐transplantation group, we found an enrichment for genes involved in natural killer (NK) cell proliferation, including Il7r 27 , Slamf6 29, and Axl 30 (Fig 5B), consistent with the previous findings that HSCs derived from NSG mice are unable to produce NK cells 31, 32. We also identified a group of genes that were important in lymphoid differentiation and were upregulated in both data sets, including Pax5 33 , Ptpro 34, and Bmf 35, 36 (Fig 5C, and Appendix Tables S1A and B).

Figure EV3. A comprehensive list of diseases and biological functions that are activated in WT HSCs co‐transplanted with lineage‐deficient HSCs as compared to WT HSCs co‐transplanted with WT HSCs in the control group.

1. Diseases and biological functions identified from the WT and NSG HSC co‐transplantation group.
2. Diseases and biological functions identified from the WT and uMT^−/− HSC co‐transplantation group.

Data information: Data were collected at month 7 post‐transplantation for the uMT^−/− group and month 8 post‐transplantation for the NSG group. n = 3 mice for each group, except for the NSG control group where n = 2 mice. Functions with fewer than 10 differentially expressed genes are excluded from the list. The threshold is −log (P‐value) = 1.6.

Biological functions related to the myeloid lineage, including myelopoiesis of bone marrow, quantity of monocytes, and megakaryocytopoiesis, were inactivated in the WT HSCs from the NSG co‐transplantation group (Fig 5B). Il11ra signaling, which is involved in expanding myeloid progenitors and megakaryocytes 37, 38, was downregulated in both data sets (Fig 5C and Appendix Table S1A). In the NSG co‐transplantation group where substantially more genes altered their expression (Fig 5A), we found that key regulators of multiple stages of myelopoiesis, including Gata1/2 39 , Hoxa10 40, and Gfi1 41, were downregulated (Fig 5E and Appendix Table S1C). These data suggest that the compensating HSCs had reduced myeloid priming.

We also found molecular evidence of reduced HSC self‐renewal in the NSG co‐transplantation group. Genes that are known to promote HSC self‐renewal, including Hoxb3 42, 43 , Hoxb6 44 , and Gfi‐1 41, were downregulated (Fig 5B). Genes involved in differentiation such as Pax5 33 and Ebf1 45, and in development such as Vpreb2 46 and Zap70 47, were upregulated (Fig 5B). These data are consistent with the reduction in HSC numbers (Fig 4).

The lineage priming and reduction in self‐renewal in HSCs during lymphopoietic compensation suggest that HSCs are involved in lymphopoietic compensation. To identify the genes that may mediate the HSC compensation, we used Ingenuity Pathway Analysis (IPA) to predict the upstream regulators of the genes whose expression significantly changed in WT HSCs co‐transplanted with lymphopoietic deficient HSCs (Fig 5D and Appendix Fig S8B) 48. This analysis identified interleukin 10 receptor alpha subunit (Il10ra) as the top candidate (Fig 5D). Interestingly, Il10ra is predicted to be an active regulator in the uMT^−/− co‐transplantation group and a repressive regulator in NSG co‐transplantation group (Fig 5D), consistent with the changes of Il10ra expression (Appendix Fig S8A). Il10ra encodes a cytokine receptor that mediates the Il10r signal to inhibit the synthesis of proinflammatory cytokines 49. Il10r signaling has both immunostimulatory and immunosuppressive properties, depending on the presence of co‐factors. For example, Il10r immunostimulatory signaling promotes the survival, proliferation, and differentiation of B cells 50. Conversely, Il10r signaling exerts immunosuppressive effects on CD4 T cells by inhibiting the Cd28 and Icos co‐stimulatory pathway 51. In our experiment, Il10ra was activated in the uMT^−/− co‐transplantation group, where only the B‐cell lineage requires compensation. However, in the NSG co‐transplantation group, Il10ra was inactivated, and its downstream targets, Cd28 and Icos, were upregulated (Fig 5E and Appendix Table S1B). These data suggest that Il10r signaling is differentially regulated to compensate for the B‐cell lineage as opposed to both B and T lineages.

In summary, we have presented an experimental model suitable to understand how individual HSC clones compensate for lymphopoietic deficiencies in vivo. By transplanting WT and lineage compromised HSCs into a single recipient, the interactions between normal and deficient hematopoietic stem and progenitor cells can be investigated. Similar approaches can be used to study other tissue and organ systems and other disease models as well. Our data demonstrate how the hematopoietic network operates in vivo as a robust and coordinated system. The compensation capacities that we showed enable the hematopoietic network to tolerate partial loss of function. We discovered that some WT clones highly expand and increase their differentiation to compensate for lymphopoietic deficiencies by specifically overproducing undersupplied cell types. This suggests that individual hematopoietic clones heterogeneously respond to lineage deficiencies in the blood. Some of these expanding clones persistently produced high levels of B cells in secondary recipients, indicating sustained self‐renewal and compensation potential. The heterogeneity in compensation capacity may be essential for maintaining robustness in blood regeneration and suggests that regeneration coordination is a complex process.

Furthermore, we have provided insights on cellular and molecular mechanisms underlying lymphopoietic compensation. Our data show a reduction in HSC and MPP numbers as well as a downregulation of self‐renewal genes in compensating HSCs. This is consistent with previous findings in humans that early lymphoid transcription factors antagonize human HSC self‐renewal 52, 53. We found an increase in cell numbers at the CLP level as well as in the downstream lymphoid lineages. While cellular level compensation is manifested at the oligopotent progenitor level, we have identified molecular changes at the stem cell level. We have discovered molecular regulators and pathways in HSCs that are associated with increased lymphopoiesis, as well as decreased myelopoiesis and HSC self‐renewal. Future studies can manipulate these regulatory molecules to improve the efficacy of bone marrow transplantation and to develop new therapeutic strategies that exploit the endogenous HSC compensation capacity. New approaches to prognosis may be developed by monitoring the compensation activities of endogenous HSCs. A better understanding of stem and progenitor cell interactions can help improve the treatment of many degenerative and age‐related diseases.

Materials and Methods

Mice

Mice were purchased from Jackson Laboratories. WT donor mice used in the co‐transplantation experiments were C57BL/6J (CD45.2). The lymphoid‐deficient donor mice were B6.129S2(B6)‐Ighm ^tm1Cgn/J (uMT^−/−, CD45.1), NOD‐scid IL2Rgamma^null (NSG, CD45.1), and C;129S4‐Rag2 ^tm1.1Flv Il2rg ^tm1.1Flv/J (Rag2^−/−γc^−/−, CD45.1). The recipient mice were off‐springs of C57BL/6J and B6.SJL‐Ptprca Pepcb/BoyJ (CD45.1/CD45.2). Both NSG and Rag2^−/−γc^−/− mice have similar B‐ and T‐cell developmental deficiencies. The Rag2^−/−γc^−/− mice have a pan deletion of Rag2 exon 3. NSG mice carry a mutation on the NOD/ShiLtJ genetic background: severe combined immune deficiency (SCID). The SCID mutation is in the DNA repair complex protein Prkdc and renders the mice B and T cell deficient. HSCs derived from Rag2^−/−γc^−/− and NSG mice lack the ability to respond to Il7 and hence cannot produce lymphoid cell lineages. Although NSG mice are on a NOD background and genetically distinct from the recipient B6 mice, the NSG donor cells were not rejected. We transplanted 1,500 WT HSCs and 3,000 NSG HSCs into each recipient, and found the expected ratio of 1:2 WT to NSG donor‐derived granulocytes (Appendix Fig S2). All donor and recipient mice were 8–12 weeks old at the time of transplantation. Mice of both genders were used without discrimination. Irradiation was performed on all recipient mice before transplantation at 950 cGy. We examined 5–8 mice for each experimental group and performed biological replicates shown in appendix figures. Mice were bred and maintained at the Research Animal Facility of the University of Southern California. Animal procedures were approved by the Institutional Animal Care and Use Committee.

Cell isolation and transplantation

Hematopoietic stem cells [lineage (CD3, CD4, CD8, B220, Gr1, Mac1, Ter119)⁻/ckit⁺/Sca1⁺/Flk2⁻/CD34⁻/CD150⁺] were obtained from the crushed bones of donor mice and isolated using FACS sorting with the FACS‐Aria II (BD Biosciences, San Jose, CA) after enrichment using CD117 microbeads (AutoMACS, Miltenyi Biotec, Auburn, CA; Appendix Fig S1). HSCs were infected for 15 h with lentivirus carrying barcodes and then transplanted via retro‐orbital injection. HSC clonal labeling was performed as described previously 2, 13. In addition to the donor HSCs, we transplanted each recipient mouse 250,000 whole bone marrow cells (helper cells) flushed from the femurs of CD45.1/CD45.2 mice. These helper cells contain HSCs and other hematopoietic progenitors that assist in blood production. During secondary transplantation, HSCs were purified from the bone marrow of primary recipients and transplanted into lethally irradiated secondary recipients.

Blood sample collection and FACS analysis

Blood samples were collected into PBS containing 10 mM EDTA via a small transverse cut in the tail vein. To eliminate red blood cells, 2% dextran was added, and the remaining blood cells were treated with ammonium–chloride–potassium lysis buffer on ice for 5 min to remove residual red blood cells. After a 30‐min antibody incubation at 4°C, samples were suspended in PBS with 2% FBS and 4,6‐Diamidino‐2‐phenylindole to distinguish dead cells. Cells were stained by antibodies and sorted using the FACS‐Aria I and II cell sorters and separated into granulocytes, B cells, CD4 T cells, and CD8 T cells (Appendix Fig S3). Antibodies were obtained from eBioscience (currently Life Technologies/Thermo Fisher) and BioLegend as described previously 13 (Appendix Table S2). Donor cells were sorted based on the CD45 marker. The following cell surface markers were used to harvest hematopoietic populations:

• Granulocyte: CD4⁻/CD8⁻/B220⁻/CD19⁻/Mac1⁺/Gr1⁺/side scatter^high;

• B cell: CD4⁻/CD8⁻/Gr1⁻/Mac1⁻/B220⁺/CD19⁺;

• CD4 T cell: B220⁻/CD19⁻/Mac1⁻/Gr1⁻/TCRαβ⁺/CD4⁺/CD8⁻;

• CD8 T cell: B220⁻/CD19⁻/Mac1⁻/Gr1⁻/TCRαβ⁺/CD4⁻/CD8⁺;

• HSC: lineage (CD3, CD4, CD8, B220, Gr1, Mac1, Ter119)⁻/ckit⁺/Sca1⁺/Flk2⁻/CD34⁻/CD150⁺

• CLP: lineage (CD3, CD4, CD8, B220, Gr1, Mac1, Ter119)⁻/Flk2⁺/Il7rα⁺

• GMP: lineage (CD3, CD4, CD8, B220, Gr1, Mac1, Ter119)⁻/ckit⁺/Sca1⁻/FcγR⁺/CD34⁺

• MEP: lineage (CD3, CD4, CD8, B220, Gr1, Mac1, Ter119)⁻/ckit⁺/Sca1⁻/FcγR⁻/CD34⁻

• CMP: lineage (CD3, CD4, CD8, B220, Gr1, Mac1, Ter119)⁻/ckit⁺/Sca1⁻/FcγR⁻/CD34⁺

• Flk2⁺ MPP: lineage (CD3, CD4, CD8, B220, Gr1, Mac1, Ter119)⁻/ckit⁺/Sca1⁺/Slamf1⁻/Flk2⁺

• Flk2⁻ MPP: lineage (CD3, CD4, CD8, B220, Gr1, Mac1, Ter119)⁻/ckit⁺/Sca1⁺/Slamf1/Flk2⁻/CD34⁺

Flow cytometry data were analyzed using FlowJo software version 10.4.2 (Tree Start, Ashland, OR) and Diva software 8.0.1 (BD Biosciences, San Jose, CA).

DNA barcode extraction and sequencing

Genomic DNA was extracted from sorted hematopoietic cells and amplified using Phusion PCR master mix (Thermo Scientific, Waltham, MA). The PCR products were halted once they had progressed halfway through the exponential phase. PCR product was purified and analyzed using high‐throughput sequencing. Sequencing data were analyzed as previously described 2, 13. We combined sequencing data with FACS data to calculate the clonal abundance for each clone: Clonal abundance = 100% × (Each cell population (Gr, B, CD4T, or CD8T cells) % WBCs) × (Donor % Each cell population) × (GFP % Donor cells) × (number of reads for each barcode)/(total reads of all barcodes).

RNA sequencing

RNA was isolated from 4,000 HSCs (lineage (CD3, CD4, CD8, B220, Gr1, Mac1, Ter119)⁻/ckit⁺/Sca1⁺/Flk2⁻/CD34⁻/CD150⁺; Appendix Fig S1) using the Zymo Research (Irvine, CA) Quick‐RNA MicroPrep. A separate mouse was used for each triplicate sample. RNA was processed and sequenced by the University of Southern California Epigenome Center and Children's Hospital Los Angeles Genomics Core. Data were analyzed by Partek® Flow® software, version 6.0 Copyright©. Transcripts were filtered to exclude those whose maximum raw read counts were less than or equal to 10 counts. We aligned reads to a reference genome (mm10) using the Spliced Transcripts Alignment to a Reference (STAR) algorithm. We quantified to transcriptome using the Partek E/M method. We generated a list of differentially expressed genes with fold changes < −2 and > 2, and with P‐values < 0.05.

The networks and functional analyses were performed using Ingenuity Pathway Analysis (IPA) 48. The biological functional analysis is based on expected causal effects between genes, which are derived from the literature knowledge base of IPA. The analysis examines genes in the data set that are known to affect biological functions. Functions with fewer than 10 differentially expressed genes are excluded from the list. The threshold for all biological functions bar graphs is −log (P‐value) = 1.3, which is calculated using the Fisher's exact test right‐tailed. Predictions of activation or inactivation of functions and pathways were based on the z‐score algorithm, which takes into account the causal relationships between genes and biological functions and networks determined by the direction of effect.

Statistical analysis

Results were shown as mean + SEM, and statistical significance was determined by a two‐tailed and two‐sample equal variance Student's t‐test for two‐group comparisons. Significance in all figures was indicated as follows: ns P > 0.05, *P < 0.05, **P < 0.01, and ***P < 0.001.

Data availability

RNA sequencing data have been deposited at Annotare under accession E‐MTAB‐6776.

Author contributions

LN and RL designed and performed the experiments. ZW and AYC assisted with RNA experiments. EC, JE, and DJ wrote custom Python codes for data analysis. LN and RL wrote the manuscript. All authors edited the manuscript.

Conflict of interest

The authors declare that they have no conflict of interest.

Supporting information

Appendix

Expanded View Figures PDF

Table EV1

Table EV2

Review Process File

EMBO Reports (2018) 19: e45702