In this study we used the polymerase chain reaction (PCR), slot blot and Southern blot hybridization, direct sequencing and in situ hybridization (ISH) to show the possible presence of EBV-DNA in pre-ulcerative oral aphthous lesions of patients with recurrent aphthous ulcers (RAU) or Behet's disease (BD). For this purpose, formalin-fixed biopsy specimens were obtained from 13 pre-ulcerative oral aphthous lesions of nine RAU and four BD patients. Five specimens of normal oral mucosa (NOM) from five normal control subjects and 10 specimens of oral erosive or ulcerative lesions from 10 patients with erosive lichen planus (ELP) were also included. EBV-DNA was detected by PCR in 5 of the 13 (38.5%) pre-ulcerative oral aphthous lesions, two from RAU patients and three from BD patients. However, no EBV-DNA was demonstrated in five NOM specimens from normal control subjects and in 10 specimens of oral lesions from ELP patients. EBV-DNA was also demonstrated in patients'peripheral blood lymphocytes and/ or plasma, suggesting that the lymphocytes may be the reservoir of latent EBV infection and there is EBV shedding in the plasma. EBV-DNA was detected by ISH in only one PCR-positive case; the reaction product was found to deposit on the nuclei of some of the epithelial cells and lymphocytes. By immunohistochemistry, expression of Epstein-Barr nuclear antigen and EBV/C3d receptors was also noted in some of the epithelial cells and lymphocytes in this ISH-positive case. Therefore, we suggest that the epithelial cells of pre-ulcerative oral aphthous lesions may be infected by EBV through EBV-infected lymphocytes; also, the cytotoxic T lymphocyte-induced lysis of the EBV-infected epithelial cells, but not the virus-induced cytolysis, may be the main mechanism causing oral ulcer formation. Our data provide preliminary evidence for an association of EBV with pre-ulcerative oral aphthous lesions in RAU and BD patients.
The adult immune system consists of cells that emerged at various times during ontogeny. We aimed to define the relationship between developmental origin and composition of the adult B cell pool during unperturbed hematopoiesis. Lineage tracing stratified murine adult B cells based on the timing of output, revealing that a substantial portion originated within a restricted neonatal window. In addition to B-1a cells, early-life time-stamped B cells included clonally interrelated IgA plasma cells in the gut and bone marrow. These were actively maintained by B cell memory within gut chronic germinal centers and contained commensal microbiota reactivity. Neonatal rotavirus infection recruited recurrent IgA clones that were distinct from those arising by infection with the same antigen in adults. Finally, gut IgA plasma cells arose from the same hematopoietic progenitors as B-1a cells during ontogeny. Thus, a complex layer of neonatally imprinted B cells confer unique antibody responses later in life.
Summary Given that FLT 3 expression is highly restricted on lymphoid progenitors, it is possible that the established role of FLT 3 in the regulation of B and T lymphopoiesis reflects its high expression and role in regulation of lymphoid‐primed multipotent progenitors ( LMPP s) or common lymphoid progenitors ( CLP s). We generated a Flt3 conditional knock‐out ( Flt3 fl/fl ) mouse model to address the direct role of FLT 3 in regulation of lymphoid‐restricted progenitors, subsequent to turning on Rag1 expression, as well as potentially ontogeny‐specific roles in B and T lymphopoiesis. Our studies establish a prominent and direct role of FLT 3, independently of the established role of FLT 3 in regulation of LMPP s and CLP s, in regulation of fetal as well as adult early B cell progenitors, and the early thymic progenitors ( ETP s) in adult mice but not in the fetus. Our findings highlight the potential benefit of targeting poor prognosis acute B‐cell progenitor leukaemia and ETP leukaemia with recurrent FLT 3 mutations using clinical FLT 3 inhibitors.
Hematopoietic stem and progenitor cells (HSPCs) in the fetus and adult possess distinct molecular landscapes that regulate cell fate and change their susceptibility to initiation and progression of hematopoietic malignancies. Here, we applied in-depth quantitative proteomics to comprehensively describe and compare the proteome of fetal and adult HSPCs. Our data uncover a striking difference in complexity of the cellular proteomes, with more diverse adult-specific HSPC proteomic signatures. The differential protein content in fetal and adult HSPCs indicate distinct metabolic profiles and protein complex stoichiometries. Additionally, adult characteristics include an arsenal of proteins linked to viral and bacterial defense, as well as protection against ROS-induced protein oxidation. Further analyses show that interferon α, as well as Neutrophil elastase, has distinct functional effects in fetal and adult HSPCs. This study provides a rich resource aimed toward an enhanced mechanistic understanding of normal and malignant hematopoiesis during fetal and adult life.
A nonthermal plasma with an electron density on the order of 10/sup 12/ cm/sup -3/ and a gas temperature of 2000 K was generated in atmospheric pressure air, using a microhollow cathode discharge as plasma cathode. The plasma was sustained in a /spl sim/1 mm/sup 3/ micro reactor, by a voltage of 470 V between the plasma cathode and a planar anode, and at currents ranging from 12 to 22 mA. This direct current glow discharge has been used to study the remediation of methane and benzene, two of the most stable volatile organic compounds (VOCs). The removal fraction for 300-ppm methane in atmospheric pressure air, flowing through the 0.5-mm thick plasma layer, with a residence time of the gas in the plasma of less than 0.5 ms, was measured at 80% with an energy density of 4 kJ/L. For benzene, the remediation rate is as high as 90%, comparable to results obtained with low pressure glow discharges. The energy efficiency for benzene remediation is 0.9 g/kWh, higher than that obtained for benzene remediation in low pressure glow discharges in noble gases. However, the VOC fraction remaining was found to be limited to values of approximately 0.1 and 0.05 for methane and benzene, respectively. In addition to experimental studies, the VOC dissociation mechanism in a VOC/dry air mixture plasma was modeled using a zero-dimensional plasma chemistry code. The modeling results have shown that atomic oxygen impact reactions are the dominant dissociation reactions for VOC destruction in this kind of glow discharge. Diffusion of atomic oxygen to the dielectric walls of the reactor is assumed to cause the observed limitation in the VOC destruction rate and efficiency.
Article Figures and data Abstract eLife digest Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract A hallmark of adult hematopoiesis is the continuous replacement of blood cells with limited lifespans. While active hematopoietic stem cell (HSC) contribution to multilineage hematopoiesis is the foundation of clinical HSC transplantation, recent reports have questioned the physiological contribution of HSCs to normal/steady-state adult hematopoiesis. Here, we use inducible lineage tracing from genetically marked adult HSCs and reveal robust HSC-derived multilineage hematopoiesis. This commences via defined progenitor cells, but varies substantially in between different hematopoietic lineages. By contrast, adult HSC contribution to hematopoietic cells with proposed fetal origins is neglible. Finally, we establish that the HSC contribution to multilineage hematopoiesis declines with increasing age. Therefore, while HSCs are active contributors to native adult hematopoiesis, it appears that the numerical increase of HSCs is a physiologically relevant compensatory mechanism to account for their reduced differentiation capacity with age. https://doi.org/10.7554/eLife.41258.001 eLife digest As far as we know, all adult blood cells derive from blood stem cells that are located in the bone marrow. These stem cells can produce red blood cells, white blood cells and platelets – the cells fragments that form blood clots to stop bleeding. They can also regenerate, producing more stem cells to support future blood cell production. But, our understanding of the system may be incomplete. The easiest way to study blood cell production is to watch what happens after a bone marrow transplant. Before a transplant, powerful chemotherapy kills the existing stem cells. This forces the transplanted stem cells to restore the whole system from scratch, allowing scientists to study blood cell production in fine detail. But completely replacing the bone marrow puts major stress on the body, and this may alter the way that the stem cells behave. To understand how adult stem cells keep the blood ticking over on a day-to-day basis, experiments also need to look at healthy animals. Säwén et al. now describe a method to follow bone marrow stem cells as they produce blood cells in adult mice. The technique, known as lineage tracing, leaves an indelible mark, a red glow, on the stem cells. The cells pass this mark on every time they divide, leaving a lasting trace in every blood cell that they produce. Tracking the red-glowing cells over time reveals which types of blood cells the stem cells make as well as provides estimates on the timing and extent of these processes. It has previously been suggested that a few types of specialist blood cells, like brain-specific immune cells, originate from cells other than adult blood stem cells. As expected, the adult stem cells did not produce such cells. But, just as seen in transplant experiments, the stem cells were able to produce all the other major blood cell types. They made platelets at the fastest rate, followed by certain types of white blood cells and red blood cells. As the mice got older, the stem cells started to slow down, producing fewer blood cells each. To compensate, the number of stem cells increased, helping to keep blood cell numbers up. This alternative approach to studying blood stem cells shows how the system behaves in a more natural environment. Away from the stresses of transplant, the technique revealed that blood stem cells are not immune to aging. In the future, understanding more about the system in its natural state could lead to ways to boost blood stem cells as we get older. https://doi.org/10.7554/eLife.41258.002 Introduction HSC-derived hematopoiesis has usually been studied in the setting of transplantation (Benz et al., 2012; Biasco et al., 2016; Dykstra et al., 2007; Lu et al., 2011; Rundberg Nilsson et al., 2015; Wu et al., 2014), an experimental paradigm that has been the foundation of hematopoietic research for decades (Siminovitch et al., 1963; Till and McCulloch, 1961) and which has established hallmark properties of HSCs such as multi-potency and self-renewal. However, while the transplantation assay has provided key insights, not the least with relevance for the clinical use in bone marrow (BM) transplantation, it might not accurately reflect the contribution of HSCs to ongoing and unperturbed steady state hematopoiesis. This is because transplantation is conducted under highly non-physiological conditions wherein HSCs are forced to proliferate to rebuild an entire hematopoietic hierarchy in a myeloablated bone marrow micro-environment. Therefore, there is a need to approach HSC biology also in more unperturbed settings. While the overall structure of hematopoiesis is rather well established (Bryder et al., 2006), the degree by which HSCs contribute to adult hematopoiesis in the steady state is more unclear. This includes whether the proposed differentiation routes for the hematopoietic lineages are obligatory, or whether alternative/complementary pathways exist. Furthermore, cells of the different hematopoietic lineages have not only distinct homeostatic functions and maintenance mechanisms (Bando and Colonna, 2016; Dzierzak and Philipsen, 2013; Rodvien and Mielke, 1976) but also display dramatically different lifespans (Galli et al., 2011; Harker et al., 2000; Van Putten, 1958; Westera et al., 2013). As a consequence, the rates by which separate adult-derived blood cell lineages must be replenished differ substantially. At the extreme end, certain hematopoietic cell types generated during the fetal period appear devoid of replenishment from adult progenitors, and rather rely on homeostatic proliferation for their maintenance (Ginhoux and Guilliams, 2016; Kantor et al., 1995). Recent developments of transgenic mouse models that allow for identification (Acar et al., 2015; Chen et al., 2016; Gazit et al., 2014) and evaluation of HSCs biology have facilitated studies of native in vivo hematopoiesis (Busch et al., 2015; Sawai et al., 2016; Sun et al., 2014; Wilson et al., 2008). Using one such model, we recently revealed that most adult HSCs are highly quiescent, which is strikingly different in the transplantation scenario (Säwén et al., 2016). Other models have been used for lineage tracing from HSCs (Busch et al., 2015; Sawai et al., 2016; Sun et al., 2014). In one of these, lineage tracing was conducted via random genetic integration of an inducible transposable genetic element, leading to the proposition that native hematopoiesis involves a large number of actively contributing progenitor cell clones, which are only rarely shared among hematopoietic lineages (Sun et al., 2014). More common approaches for lineage tracing involve the use of cell type specific recombinases, that function to irreversibly mark a cell of interest and with time its descendants. While elegant and extensively used among developmental biologists, such approaches have only sparsely been applied to adult HSCs, and with seemingly contradictory results. Using a Tie2-driven model, Busch et al. concluded a substantial hematopoietic contribution/maintenance from progenitors rather than HSCs (Busch et al., 2015), which at least to some extent would appear compatible with the results from Sun et al. (2014). By contrast, Sawai et al. utilized a Pdzk1ip1-based CreERT2 system and suggested robust HSC labeling and hematopoiesis from adult HSCs (Sawai et al., 2016). To try to assess these potential ambiguities, we here investigated the degree to which HSCs contribute to steady state adult hematopoiesis by using an inducible Fgd5-based HSC lineage tracing model (Gazit et al., 2014). We observed dramatic differences with regards to HSC contribution to adaptive immunity (slow) and the myeloerythroid lineages (fast), with HSCs contributing to the platelet lineage with the most rapid kinetics. The regeneration of terminal cell fates was closely mirrored at the level of each intermediate myeloerythroid precursor. These findings are consistent with adult HSCs as highly active contributors to multilineage hematopoiesis not only following transplantation, but also during the steady state. However, when approached in the situation of chronological aging, we noted diminished mature blood cell output from aged HSCs that could be traced to the first differentiation events from HSCs. These results suggest that the previously proposed fetal to adult switch (Bowie et al., 2007), in which HSCs alter their properties from more excessive proliferation/differatiation to a more dormant state in the adult, extends gradually throughout adulthood. As a consequence, the well-known numerical increase of HSCs with age (Morrison et al., 1996; Rossi et al., 2005; Sudo et al., 2000) appears to represent a physiologically relevant mechanism to account for reduced HSC differentiation with age. Results Fgd5-CreERT2-based lineage tracing allows for assessment of HSC contributions to unperturbed hematopoiesis Using a transcriptome based screen of more than 40 different hematopoietic cell types, Fgd5 (FYVE, RhoGEF and PH domain containing 5) was identified as a HSC-expressed gene that is rapidly downregulated upon differentiation. That Fgd5 expression marks all HSCs was confirmed through functional studies using an Fgd5 knock-in reporter strain (Gazit et al., 2014). To further detail the HSC specificity of Fgd5, we first acquired transcriptome data from 11,581 individual lineage-marker negative, c-kit positive and CD45 positive bone marrow cells (Lin-kit+). The Lin-kit+ population contains a range of different immature hematopoietic progenitor cells (Pronk et al., 2007). Therefore, Lin-kit+ cells provided a benchmark to which other more defined/specific hematopoietic progenitor subsets could be compared. Next, we took advantage of an Fgd5 reporter strain in which a ZsGreen-2A-CreERT2 allele was knocked into the endogenous Fgd5 locus (hereafter Fgd5CreERT2/+ mice) (Figure 1B) (Gazit et al., 2014). We sorted either Lin-kit+Fgd5+ cells (Figure 1A middle; 793 cells, Fgd5+), or Fgd5+ cells with a stringent Lin-kit+Sca-1+CD48-CD150+ HSC phenotype (Figure 1A right, 519 cells, HSC-Fgd5+). All Fgd5+ and HSC-Fgd5+ data were aggregated with the Lin-kit+ transcriptome data, which was followed by identification of the most significant gene vectors using principal component analysis (PCA). Data was then visualized using t-distributed stochastic neighbor embedding (tSNE) dimensionality reduction (Figure 1A). Lin-kit+ cells were extensively scattered across the two dimensions (Figure 1A, left), in agreement with the heterogeneity of these cells. By contrast, Fgd5+ cells, regardless if sorted based on additional HSC markers, formed a distinct and highly overlapping cluster (Figure 1A, middle and right). This cluster localized to a region with very few cells when evaluating Lin-kit+ cells (Figure 1A, left, dotted area), emphasizing the HSC-specificity of the Fgd5 reporter and the low HSC frequency within the larger Lin-kit+ fraction. Figure 1 with 1 supplement see all Download asset Open asset Fgd5-CreERT2 specifically labels HSCs and Fgd5-mediated label progresses throughout the hematopoietic system. (A) Lineage negative c-kit+ cells (Lin-c-kit+, left), lineage negative c-kit+ Fgd5+ cells (Fgd5+, middle) and lineage negative Fgd5+c-kit+Sca-1+CD150+CD48- cells (HSC-Fgd5+, right) were isolated and subjected to single cell RNA-sequencing. The data was aggregated and visualized in a two-dimensional scatter plot after PCA and tSNE dimensionality reduction. Fgd5+ cells are highlighted in pink (middle), Lin-c-kit+ cells are highlighted in black (left plot) and HSC-Fgd5+ cells are highlighted in blue (right plot). The area that Fgd5+ cells occupy in relation to the transcriptomes of Lin-c-kit+ cells and HSC-Fgd5+ cells is marked by a dotted line (left and right plots). (B) Schematic representation of the Fgd5CreERT2/+; Rosa26lsl-Tomato/+ model. ZsGreen and CreERT2 are expressed from the Fgd5 locus and expression of a Tomato allele is driven by a CAG promoter from the Rosa26 locus and is preceded by a LoxP flanked STOP cassette. (C) Model description; HSCs selectively and continuously express ZsGreen in an Fgd5-dependent manner. Upon Tamoxifen (TAM) administration, HSCs express Tomato and expression of Tomato label is inherited by all progeny of Tomato-expressing HSCs. (D) Representative FACS plots showing Tomato label in BM HSPCs from Fgd5CreERT2/+; Rosa26lsl-Tomato/+ mice that were injected with Tamoxifen 48 hr prior to analysis. (D, lower right) Representative histograms depicting Tomato label in PB cells at various time points after the start of Tamoxifen administration from mice in Figure 3B (T cells 48 weeks, B cells 25 weeks, granulocytes and monocytes 8 weeks, platelets and erythrocytes 13 weeks). Numbers in FACS plots depict the mean % of Tomato labeled cells ± SD (n = 5) and dashed lines in histograms indicates the boundary for Tomato positivity. (E) FACS plots showing H2B-mCherry label retention and Tomato labeling in Lineage-c-kit+CD150+CD48- and Sca1+ or Sca1- cells from a representative mouse that had diluted H2B-mCherry label for 5 weeks and were injected with Tamoxifen 5 days prior to analysis (n = 3; 14–19 weeks old at analysis). (F) The fraction of donor-derived cells among different blood cell lineages was assessed in individual mice 16 weeks post-transplantation in recipients of 5 Tomato+ (n = 8) or 5 Tomato- (n = 7) HSCs. Abbreviations: 2A, 2A self-cleaving peptide; CAG, CAG promoter; loxP, LoxP site. https://doi.org/10.7554/eLife.41258.003 We next generated a lineage tracing model by crossing Fgd5CreERT2/+ mice to Rosa26-Lox-Stop-Lox-Tomato mice (hereafter Rosa26lsl-Tomato/+) (Figure 1B). In this model, HSCs can be identified based on ZsGreen expression, while Tamoxifen administration leads to irreversible and heritable Tomato labeling of HSCs and, over time, their offspring (Figure 1C). To confirm the model, we evaluated Tomato label in HSC and BM progenitor cells 48 hr after a single injection (1x) of Tamoxifen. This revealed labeling of a fraction of candidate HSCs, with virtually no labeling in other c-kit+ progenitor fractions (Figure 1D and Figure 1—figure supplement 1). This established HSC specific labeling and a relatively low differentiation rate of HSCs in steady state (Säwén et al., 2016; Wilson et al., 2008). To illustrate our ability to detect Tomato label in peripheral blood (PB) cells, we assessed Tomato expression in defined cell types from mice that had received Tamoxifen 8–48 weeks previously (Figure 1D, lower right). Complementary to immunophenotypic identification of initially labeled BM cells as HSCs (Figure 1D and data not shown), we evaluated the proliferation history of Tomato labeled HSPCs 5 days after a pulse of Tomato labeling by evaluation of transgenic H2B-mCherry label retention (Figure 1E) (Säwén et al., 2016). Among HSCs, this revealed a strong correlation between a restricted proliferative history and Tomato labeling. Of note, a single dose of Tamoxifen was insufficient to label all candidate Fgd5-expressing HSCs (Figure 1E and data not shown). Finally, to corroborate that Tomato labeled phenotypic HSCs are bona fide HSCs, we injected mice with Tamoxifen and isolated candidate Tomato positive and negative HSCs 48 hr later. Sorted cells were transplanted at limiting dilution (5 cells/mouse). This revealed long-term multilineage reconstitution in 5/8 recipients transplanted with Tomato+ HSCs (Figure 1F). Fgd5-lineage tracing reveals that HSCs generate different types of hematopoietic progeny with distinct kinetics Encouraged by the highly specific HSC label observed after Tamoxifen administration to Fgd5CreERT2/+; Rosa26lsl-Tomato/+ mice (Figure 1), we next set out to perform label tracing studies of hematopoietic generation from HSCs. For this, we labeled cohorts of Fgd5CreERT2/+; Rosa26lsl-Tomato/+ mice with one injection of Tamoxifen and chased groups of mice for different periods of time up to 83 weeks after labeling. At end point analyses, the fraction of Tomato+ cells was determined in various hematopoietic compartments to assess the HSC contribution to progenitor pools and mature blood cell subsets (Figure 1—figure supplement 1). The frequencies of Tomato+ cells for each investigated subset were next related to the fraction of Tomato labeled HSCs (Figure 2A, mean 13% ± 9%) in individual mice (Figure 2B, and Figure 2—figure supplement 1). The fraction of labeled HSCs was generally higher in mice analyzed beyond 4 days of chase compared to mice analyzed after shorter chase periods. However, no further increase in HSC labeling was noted after longer periods of chase (Figure 2A). Figure 2 with 2 supplements see all Download asset Open asset Fgd5-CreERT2 mediated lineage tracing reveals robust HSC contribution with distinct kinetics into hematopoietic cell subsets in steady state and after transplantation. Cohorts of Fgd5CreERT2/+; Rosa26lsl-Tomato/+ mice were chased for up to 83 weeks after receiving one Tamoxifen injection before endpoint analysis of the % of Tomato+ cells in HSCs (A) and hematopoietic progenitor and PB cell subsets (B). The fraction of Tomato+ cells in each indicated hematopoietic cell subset was divided by the % Tomato label in HSCs in corresponding mice to determine the ratio of Tomato+ cells relative to HSCs in individual mice. The average ratio is plotted according to time after the Tamoxifen (TAM) injection and displayed in a heat map format. Mice were analyzed at 1–4 days (n = 18) and at 4 (n = 7), 8 (n = 8), 12 (n = 8), 16 (n = 4), 28 (n = 4), 32 (n = 5) and 83 (n = 3) weeks after the Tamoxifen injection. All mice were between 5 and 11 weeks old at the time of Tamoxifen injection. (C) PCA plot of multiplexed qRT-PCR data for 48 genes from triplicates of 10 cells from each of the indicated populations. Ellipses show an area where a new observation from the same group would position itself with a probability of 0.95. Numbers indicate the % of variance in the total data set that the respective PC explains. (D) For individual animals, the % of Tomato+ cells in PB cell types was divided by the % of Tomato+ cells in the indicated progenitor cell types and this value was plotted according to the duration of the chase period. Symbols represent individual mice (number of mice analyzed as in A and B). A dashed line is drawn to indicate an equilibrium-ratio of 1. (E) Ratios calculated as in B and plotted according to the number of weeks after transplantation or after the start of Tamoxifen administration for steady state/native mice (n = 3 for WBM tx in CD45 depleted, n = 5 for WBM tx in irradiated, n = 11 for HSC tx in irradiated, n = 4–8 for 1x TAM, n = 4–9 for continous TAM). All Fgd5CreERT2/+; Rosa26lsl-Tomato/+ mice/cells were between 5 and 11 weeks old at the time of Tamoxifen administration or when used as cell donors for transplantation. https://doi.org/10.7554/eLife.41258.005 First, we investigated Tomato label progression into the immature lineage negative, Sca-1 positive and c-kit positive (LSK) compartment, fractionated further using the Slam markers CD48 and CD150 (Kiel et al., 2005) (Figure 2B and Figure 1—figure supplement 1). We used this approach to identify HSCs (LSKCD150+CD48-) and different multipotent progenitor fractions (MPPs: LSKCD150-CD48-, MPP2: LSKCD150+CD48+, MPP3/4: LSKCD150-CD48+). LSKCD150-CD48- MPPs are immature multipotent progenitors distinguished from HSCs by their limited self-renewal potential (Kiel et al., 2005; Kiel et al., 2008; Ugale et al., 2014). Of the evaluated progenitor subsets in our work, this subset was generated from HSCs with the fastest kinetics, with near equilibrium to HSC label reached already by 4 weeks (Figure 2B). MPP2 cells represent a rare subset of cells with more undefined lineage/developmental affiliations. This prompted us to first elucidate their developmental potential. First, we aimed to place these cells within a transcriptional framework established by other, more established, hematopoietic progenitors. For this, we obtained gene expression data from a panel of defined stem and progenitor cells and MPP2 cells using a multiplexed qRT-PCR approach for 48 genes, selected to include cell surface markers, cell cycle regulators and transcription factors associated with hematopoiesis (Supplementary file 2). Visualization of this data using PCA revealed that MPP2 cells clustered closely to Meg/E progenitors (Figure 2C). Consistent with a close association to the Meg/E lineages, short-term (6 days) culture experiments revealed a more robust generation of both megakaryocyte and erythroid containing colonies from MPP2s compared to other LSK subsets (Figure 2—figure supplement 2). When investigating Tomato label progression, MPP2 cells reached label equilibrium with HSCs after 32 weeks in 1x injected mice (Figure 2B). MPP3/4 cells lack, for the most part, Meg/E lineage potential (Adolfsson et al., 2005; Arinobu et al., 2007; Pietras et al., 2015; Pronk et al., 2007). MPP3/4 cells acquired Tomato label with much slower kinetics compared to other LSK fractions (Figure 2B). Of the distinct progenitor fractions within the Lin-kit+ fraction (Figure 1—figure supplement 1A), megakaryocyte progenitors (MkP) acquired label with the fastest kinetics, reaching label equilibrium with HSCs after 32 weeks. Other myeloerythroid progenitors, including pre-megakaryocytic/erythroid (preMeg/E), pre-colony forming unit-erythroid (pre CFU-E) and pre-granulocyte-macrophage (preGM) progenitors acquired Tomato label with very similar kinetics despite their distinct lineage affiliations, although they never quite reached an equilibrium with HSCs throughout the course of the experiments (Figure 2B and Figure 2—figure supplement 1). Mature effector cells represent the terminal progeny of HSCs. We observed distinct generation kinetics for different lineages (Figure 2B). First, we made the general observation that myeloerythroid cells acquired label more rapidly than lymphoid cells. Among the myeloid subsets, platelets acquired Tomato label with the fastest kinetics, followed by granulocytes and erythrocytes. Among lymphoid cell types, NK cells displayed faster labeling kinetics followed by B cells. T cells showed the slowest labeling kinetics among lymphoid cells and CD4+ T cells acquired label faster than CD8+ T cells (Figure 2B). Because the frequency of Tomato+ cells increased over time in all evaluated lineages, this data demonstrate a continuous contribution of HSCs to all hematopoietic lineages. While multiple studies have defined populations of hematopoietic progenitors that associate with distinct developmental and/or stages of differentiation (Bryder et al., 2006), it is unknown whether such described progenitors are obligatory intermediates and/or their quantitative association relative to their anticipated mature offspring. Therefore, we interrogated the relationships between the rates of (re)generation of candidate committed myeloerythroid progenitors to those of their proposed mature cell lineage. At the earliest time points evaluated, we observed for all evaluated fractions a higher label in their corresponding progenitors (Figure 2D). However, this was resolved during the course of the experiments and reached similar equilibrium ratios for all evaluated lineages, although the erythroid lineage displayed somewhat slower kinetics (Figure 2D). Collectively, these experiments are in line with the view that progenitor generation precedes the generation of mature cells and that previously proposed progenitors appears to be, at least for the most part, obligatory intermediates. Hematopoiesis after transplantation of HSCs is fundamentally different from unperturbed hematopoiesis (Busch et al., 2015; Sun et al., 2014). However, to what extent the pre-conditioning regimen and co-transplantation of mature cells and progenitors influence on hematopoiesis from HSCs is less established. Therefore, we next transplanted wild type recipient mice on continuous Tamoxifen diet with purified Fgd5CreERT2/+; Rosa26lsl-Tomato/+ HSCs or WBM cells. Here, recipient mice were pre-conditioned by either lethal irradiation or antibody mediated CD45-depletion (Palchaudhuri et al., 2016). Due to the HSC specificity of the model, this approach allowed us to monitor the kinetics of the HSC contribution to all lineages after transplantation and compare it to the HSC contribution in steady state (Figure 2E). Compared to steady state, label progression in transplanted mice were faster (Figure 2E). When label progression kinetics was compared between HSC and WBM transplanted animals, HSC transplantation resulted in faster label progression, especially into the B cell lineage (Figure 2E). This likely reflects a significant contribution to the regeneration of the B cell lineage by co-transplanted long-lived B-lineage progenitors and mature cells after WBM transplantation. Comparison of label progression after WBM transplantation into irradiated or non-irradiated/antibody-mediated conditioned recipient mice revealed similar label progression kinetics into most mature lineages, with the exception of platelets that displayed a faster label progression in irradiated mice. This suggests that progenitors for platelets are more effectively ablated by irradiation than antibody-mediated pre-conditioning. Fgd5-mediated HSC lineage tracing corroborates the fetal/juvenile origin of Langerhans cells, B1a B cells and brain microglial cells While a labeling regimen of one Tamoxifen injection allows for accurate kinetic evaluations (Figure 2A–B,D), this experimental strategy labels only a fraction of HSCs (Figure 1E and Figure 2A) and thus necessitates correlation of label in HSCs to other evaluated cell subsets (Busch et al., 2015) (Figure 2B). If the original HSC label is low, this might as a consequence not allow for evaluation of the activity of the entire pool of HSCs. To explore whether we could label the HSC pool more extensively, Fgd5CreERT2/+; Rosa26lsl-Tomato/+ mice were fed Tamoxifen containing food pellets for 16 weeks. To rule out adverse effects of prolonged Tamoxifen treatment on HSC proliferation, these experiments were preceded by a control label retaining experiment using Col1a1tetO-H2B-mCherry/tetO-H2B-mCherry; ROSA26rtTA/rtT mice (Säwén et al., 2016). Following H2B-mCherry induction with Doxycycline, mice were chased for 5 weeks in the presence or absence of Tamoxifen. Prolonged Tamoxifen treatment did not induce any additional proliferation within the HSC compartment, while more differentiated progenitors had readily proliferated in both settings (Figure 3A). Figure 3 Download asset Open asset Fgd5-mediated lineage tracing after complete HSC labeling reveals limited adult HSCs contribution to tissue-resident immune cell subsets. (A) H2B-mCherry label retention in HSCs and myeloid progenitors after 5 weeks of chase in mice continuously fed Tamoxifen (TAM) containing food (blue histograms, n = 7) or normal food (red histograms, n = 6) during the chase period. Green histograms depict an unlabeled control. Dashed lines indicate the boundary for H2B-mCherry positivity. Lineage negative c-kit+Sca1- cells are denoted as myeloid progenitors. (B) Cohorts of Fgd5CreERT2/+; Rosa26lsl-Tomato/+ mice were continuously fed Tamoxifen food for 16 weeks (TAM phase) and thereafter normal chow during a chase phase of 32 weeks (n = 5) or 41 weeks (n = 4). During the TAM and chase phases, PB was regularly analyzed for Tomato label in the indicated subsets. Data points indicate the average % of Tomato label in each indicated subset. (C–E) Endpoint analysis, after 41 weeks chase, in mice from Figure 3B (n = 3). (C) Representative FACS plots showing the gating strategy to identify HSCs in lineage negative BM cells (left, middle) and depiction of the Tomato label in HSCs (right, red histogram) compared to an unlabeled control (blue histogram). Dashed line indicates the boundary for Tomato positivity, arrows indicate the gating strategy. (D) Representative FACS plots of cells isolated from skin tissue (epidermis) or the peritoneal cavity. Histograms show Tomato label (bottom left and right) or ZsGreen label (bottom middle) in the indicated subsets. Dashed line indicate the boundary for Tomato positivity, arrows indicate the gating hierarchy, gates and corresponding histograms are color matched. (E) Representative confocal images of the brain. (Left) IBA1 positive cells (green) are not labeled with Tomato (red, middle) while blood vessels are labeled with Tomato (middle). (Right) Merged images display both IBA1 staining and Tomato label. Scale bar = 50 μm. Mice in B-E were 5–6 weeks old at the start of Tamoxifen administration. https://doi.org/10.7554/eLife.41258.008 The 16 weeks labeling period was followed by an extensive (up to 41 weeks) chase period, during which mice received normal chow (Figure 3B). This labeling strategy resulted in labeling of virtually all candidate HSCs (Figure 3C). The blood of labeled mice was analyzed regularly to determine the fraction of Tomato+ cells in PB cell subsets (Figure 1—figure supplement 1B). Similar to after 1x Tamoxifen labeling, we observed robust label progression into all PB cell subsets, with similar kinetics in between different lineages (Figure 3B). However, a more complete HSC labeling resulted in a somewhat faster and more robust label progressio
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