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Identification of in vitro HSC fate regulators bydifferential lipid raft clustering

Nicola Vannini, Aline Roch, Olaia Naveiras, Alessandra Griffa, Stefan Kobel &Matthias P. Lutolf

To cite this article: Nicola Vannini, Aline Roch, Olaia Naveiras, Alessandra Griffa, Stefan Kobel& Matthias P. Lutolf (2012) Identification of in vitro HSC fate regulators by differential lipid raftclustering, Cell Cycle, 11:8, 1535-1543, DOI: 10.4161/cc.19900

To link to this article: https://doi.org/10.4161/cc.19900

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RepoRt RepoRt

*Correspondence to: Matthias P. Lutolf; Email: matthias.lutolf@epfl.chSubmitted: 01/15/12; Accepted: 03/02/12http://dx.doi.org/10.4161/cc.19900

Introduction

Most long-term HSCs (LT-HSC) in the bone marrow are quies-cent;1 a behavior which is critical for the life-long maintenance of the stem cell pool in the niche,2 as these rare cells can only undergo a limited number of cell divisions due to telomere short-ening.3 Indeed, the loss of the quiescent HSC pool may have a detrimental effect on blood formation.4

Under homeostatic conditions, approximately 65–70% of LT-HSC in mice reside in G

0.5 When challenged by the physiolog-

ical demands of the tissue such as during stress, this quiescent cell population can be reversibly recruited into a cycling state.6,7 Studies conducted on genetic mouse models have begun to identify spe-cific short-range signaling cues emanating from the stem cell niche with a role in controlling the quiescent state, including TGFβ,8 Angiopoietin-1,9 TPO,10 Wnt5a,11 SDF-112 or Osteopontin.13-15 However, the underlying mechanisms regulating the quiescent state remain poorly understood. The PI3K-Akt signaling axis as well as the downstream effectors mTOR and FOXO transcription factors seem to play an important role.16-19 Furthermore, recent work has demonstrated the relevance of metabolic modulators, including Lkb120-22 in the regulation of HSC quiescence.

Interestingly, changes in the distribution of lipid rafts, cell membrane microdomains enriched in cholesterol and

Most hematopoietic stem cells (HSC) in the bone marrow reside in a quiescent state and occasionally enter the cell cycle upon cytokine-induced activation. Although the mechanisms regulating HSC quiescence and activation remain poorly defined, recent studies have revealed a role of lipid raft clustering (LRC) in HSC activation. Here, we tested the hypothesis that changes in lipid raft distribution could serve as an indicator of the quiescent and activated state of HSCs in response to putative niche signals. A semi-automated image analysis tool was developed to map the presence or absence of lipid raft clusters in live HSCs cultured for just one hour in serum-free medium supplemented with stem cell factor (SCF). By screening the ability of 19 protein candidates to alter lipid raft dynamics, we identified six factors that induced either a marked decrease (Wnt5a, Wnt3a and osteopontin) or increase (IL3, IL6 and VeGF) in LRC. Cell cycle kinetics of single HSCs exposed to these factors revealed a correlation of LRC dynamics and proliferation kinetics: factors that decreased LRC slowed down cell cycle kinetics, while factors that increased LRC led to faster and more synchronous cycling. the possibility of identifying, by LRC analysis at very early time points, whether a stem cell is activated and possibly committed upon exposure to a signaling cue of interest could open up new avenues for large-scale screening efforts.

Identification of in vitro HSC fate regulators by differential lipid raft clustering

Nicola Vannini,1 Aline Roch,1 olaia Naveiras,1,2 Alessandra Griffa,3 Stefan Kobel1 and Matthias p. Lutolf1,*

1Laboratory of Stem Cell Bioengineering; Institute of Bioengineering; ecole polytechnique Fédérale de Lausanne (epFL); Lausanne, Switzerland; 2Department of Medicine; Centre Hospitaler Universitaire Vaudois (CHUV); Lausanne, Switzerland; 3Bioimaging and optics platform; ecole polytechnique Fédérale de Lausanne (epFL);

Lausanne, Switzerland

Key words: hematopoietic stem cells, niche, lipid rafts, microwell array, hydrogel

Abbreviations: HSC, hematopoietic stem cell; LR, lipid raft; LRC, lipid raft cluster; MβCD, methyl-β-cyclodextrin

sphingolipids, have been associated with HSC biology.17,23,24 Lipid rafts are involved in key cellular events, such as signaling or protein trafficking in diverse systems,25 the best-characterized being T-cell receptor (TCR) engagement by antigen recogni-tion, which induces lipid raft clustering (LRC) and subsequent TCR segregation. This process results in the formation of an immunological synapse and highlights the importance of LRC in the compartmentalization of membrane chemical units.26 In HSCs, LRC has been linked to stem cell activation induced by cytokine exposure.23 Upon stimulation of HSCs with stem cell factor (SCF or kit-ligand or steel factor), the receptor tyrosine kinase c-Kit (CD 117) is recruited to clustered lipid rafts, induc-ing HSC activation and cycling via signaling through the PI3K-Akt pathway.23,27 Conversely, inhibiting cytokine-induced LRC by TGFβ exposure or by depleting plasma membrane cholesterol with methyl-β-cyclodextrin (MβCD) prevents HSC activation and maintains them in a quiescent and multipotent state.23,24 In addition, lipid rafts have been suggested to play a role in regulat-ing the symmetry of human hematopoietic progenitor cell divi-sion by differentially redistributing membrane surface proteins into daughter cells.28

Based on these findings, we hypothesized that the distribution of lipid rafts on individual HSCs could be used as a very early and generic readout to test how microenvironmental signals influence

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switch from a quiescent to an acti-vated state of HSCs.

Results

Prospective isolation of highly enriched LT-HSC. To select for a homogeneous HSC population for use in our studies, we sorted Linneg c-Kitpos Sca1pos CD150pos (LKS-CD150+) cells from the bone marrow of C57Bl/6 mice (Fig. S1). Consistent with earlier studies in references 29–31, we found that these cells are highly enriched for LT-HSC. When we transplanted 40 GFP+ Ly5.2+ LKS-CD150+ cells into lethally irradiated mice, we detected, after four months, multilineage reconstitution in six of the seven recipient mice analyzed (Fig. S2). Analysis of cells of lymphoid and myeloid lineages revealed average reconstitution levels of approxi-mately 20% and 50%, respectively. Based on double-labeling DNA and RNA of LKS-CD150+ with Hoechst 3342 and Pyronin Y, respectively, we confirmed that the majority of these cells are in G

0 (Fig. S3).5,32

Development of a semi-auto-mated image analysis platform for the detection of LRC in live cells. To identify LRC in live HSCs, we developed an image analysis approach that can detect the distri-bution of lipid rafts in single cells (Fig. 1; Figs. S4 and S5). Based on a comparison to reference images, our image-processing algorithm distinguishes live cells bearing lipid raft clusters from those that do not have them. To validate this sys-tem, we analyzed the occurrence of LRC in HSCs treated with MβCD and TGFβ, two known inhibitors

of LRC (Vids. S1–4).24 It has previously been shown that the majority of freshly isolated CD34-KSL stem cells show a diffusive distribution of lipid rafts when treated with MβCD or TGFβ, in marked contrast to CD34-KSL stimulated with the cytokine SCF, which show induction of LRC.17,23,24 To assess lipid raft dis-tribution in freshly isolated LKS-CD150+, we stained endogenous GM1 ganglioside, a major component of lipid rafts, with fluores-cently labeled cholera toxin subunit B (CTxB). A comparison of automated and manual scoring of single cells from three indepen-dent experiments gave almost identical results, with a variation of

HSC fate in vitro. To test this, we evaluated the ability of 19 protein candidates to influence LRC in live HSCs. We developed an image analysis platform to automatically identify the presence or absence of LRC in single cells. Our experiments identified six factors inducing either a significant decrease or increase in lipid raft clusters. Furthermore, time-lapse microscopy of single HSCs exposed to these factors revealed cell cycle kinetics indicative of a more quiescent vs. activated phenotype, in correlation with LRC. Hence, the clustering of lipid rafts could indeed represent an early phenotypic hallmark reporting the extrinsic signal-induced

Figure 1. Image acquisition and analysis to detect LRC in live cells. (A) Lt-HSC seeded in microwells and stained with CtXB AlexaFluor488 were imaged with a fluorescent microscope to identify LRC. the images were then filtered and processed to identify single cells bearing LRC. (B) Analysis of the effect of known inhibitors of LRC (MβCD, tGFβ and growth factor-free condition) compared with basal condi-tions. examples of images acquired with the final processing steps for the identification of LRC shown on the left, red crosses indicating cells not considered to have LRC. percentage of cells bearing LRC (right part). MβCD, tGFβ and growth factor-free conditions resulted in a strong inhibition of LRC. *p < 0.05, **p < 0.01.

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the population-averaged readout (Fig. 4A–C). However, all LRC inhibitory factors showed a major increase of time to the first cell division (Fig. 5A–C) and time from the first to the second cell division (Fig. 6A–C). In marked contrast, the LRC inducers IL-3 and IL-6 increased HSC proliferation by 25- and 20-fold, while VEGF did not show any significant effect on proliferation (Fig. 4D–F). None of the factors had a toxic effect, but IL-3 showed a slight pro-survival effect (Fig. S8). Interestingly, the time to the first division was not affected by any LRC stimula-tory factor (Fig. 5D–F). However, IL-3 and IL-6 showed a strik-ing acceleration of the time from the first to the second division. At the highest concentration, IL-3 and IL-6 shortened the time from the first to the second division by 10 and 9.3 h, respectively (Fig. 6D–F). Furthermore, the analysis of average division times of each population confirmed the kinetic alterations observed above (Figs. S9 and S10). Taken together, these results underline the coupled effects of the factors on lipid raft distribution and cell cycle kinetics: Wnt5a, OPN and Wnt3a are capable to slow down LRC and division kinetics in contrast to IL-3 and IL-6, which increase LRC and cell cycling.

less than 5%. As expected, MβCD almost completely abrogated the capacity to form clusters, while TGFβ reduced the fraction of cells bearing lipid raft clusters by 25% (Fig. 1B). These results validate our live cell imaging system as a means to discriminate between cells bearing lipid raft clusters or not and set the stage to exploit the platform for larger-scale screening experiments.

Exposure of HSCs to selected niche candidate cues influ-ences the distribution of lipid rafts. To address whether the lipid raft distribution on single HSCs could be used as an indi-cator to evaluate the mode of action of specific signaling cues, we screened a collection of candidate factors that had previously been suggested to play a role in the regulation of HSC in bone marrow niches (Table S1). HSCs were cultured in basal medium (100 ng/ ml SCF and 2 ng/ ml Flt3 ligand) supplemented with each factor to test for its ability to induce or block LRC. Our analysis revealed that Wnt5a, OPN and Wnt3a (at 500 ng/ ml, 1 μg/ml and 100 ng/ ml, respectively) exhibited the most pro-nounced inhibition of LRC, reducing the number of cells with clusters by 15–17% (Fig. 2). In contrast, IL-3, VEGF and IL-6 (at 20 ng/ ml, 100 ng/ ml and 100 ng/ ml) showed opposite behav-iors, increasing the number of cells bearing clusters by 15%, 13% and 7%, respectively. The factors showing the most strik-ing effect on LRC were further investigated with regards to their ability to modulate single HSC behavior in vitro.

LRC and c-Kit co-localize in the plasma membrane. To investigate whether LRC could be linked to signaling and HSC activation through the PI3K-Akt pathway,23,27 we assessed the localization of c-Kit in the plasma membrane of live cells by immunostaining33 for the six factors that had shown the most pronounced effect on LRC. Strikingly, Wnt5a, OPN and Wnt3a, the factors that maintained a diffuse distribution of lipid rafts, also showed a diffuse distribution of c-Kit in the membrane, while HSCs exposed to the LRC-stimulating factors IL-3, VEGF and IL-6 showed polarized c-Kit that co-localized with LRC (Fig. 3; Vids. S5–7). Notably, Sca-1 also polarized and distrib-uted to LRC (Fig. S6).

Modulation of lipid raft distribution by niche factors is accompanied by changes in single cell cycle kinetics. We postu-lated that the distribution of lipid rafts could be correlated with changes in cell proliferation. To test this, we assessed whether the six factors that had the most pronounced effect on lipid raft distribution influenced single cell cycle kinetics (Figs. 4–6). To follow HSC behavior at the single-cell level, we utilized a previ-ously developed microwell array system (Fig. S7).31,34 Individual microwells have a diameter of ca. 100 μm and keep cells in a confined area, thus allowing high-throughput, long-term single-cell tracking by time-lapse microscopy. Single-cell occupancy of microwells was maximized by seeding 200 cells per well of a 96-well plate containing 950 microwells in each well. For each of the six identified factors, we analyzed its effect on cell prolifera-tion and division times. Proliferation was quantified as the total number of cells at each time point normalized to the total num-ber of microwells analyzed.

Cell cycle analysis for the three LRC inhibitory factors revealed that both Wnt5a and Wnt3a slowed down cell proliferation, whereas no significant effect of OPN on cycling was detectable in

Figure 2. Screening of putative niche factors for their ability to modu-late LRC. percentage of cells bearing LRC normalized to basal condition levels. Reference conditions are indicated in black. the factors showing the strongest inhibitory (Wnt5a, opN and Wnt3a) or inducing (IL-3, VeGF and IL-6) effects are shown in red or green, respectively.

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into small debris resembling the formation of proto-platelet processes of megakaryocytes (Fig. S11D and Vid. S8). Therefore, IL-3- and IL-6-stimulated cell cycling appears to result in early commitment, con-sistent with findings from others.35 Overall, these data suggest a role of LRC as an early step of HSC activation, leading to increased and more synchro-nous cell cycling.

Discussion

HSCs enter cell cycle at long intervals, a property that is critical in preventing premature HSC exhaus-tion under stress conditions (reviewed in ref. 36). Numerous niche components, in concert with cell-intrinsic signaling pathways, play a role in regulating the balance between HSC quiescence and activa-tion. These extrinsic signals are transmitted to the cell through its plasma membrane, whose compo-nents are often compartmentalized into lipid rafts.37 What’s more, cell communication within the niche and cytokinesis appear to be finely regulated by a specialized membrane micro-domain as well.38-40 Therefore, an understanding of the dynamics and distribution of lipid rafts and their dependence on microenvironmental signals may be crucial for better understanding HSC biology.

We hypothesized that the distribution of lipid rafts on single HSCs could be used as a very early, generic “reporter” of the cellular state and, in par-ticular, could indicate whether selected extrinsic signals instruct HSC quiescence or activation. To this end, we tested how a set of 19 candidate signals could influence LRC in live HSCs. Our analysis

showed that extrinsic signals can alter the clustering of lipid rafts, both in a stimulatory and inhibitory fashion. Of all the factors tested, Wnt5a, OPN and Wnt3a exhibited the most pronounced inhibitory effect on lipid raft cluster formation (Fig. 2), an effect that was only 10% milder than that of the previously identified niche LRC inhibitor, TGFβ.24 Furthermore, we demonstrated that Wnt5a, OPN and Wnt3a, the factors identified to decrease LRC, also slowed down HSC cycling in vitro, while IL-3 and IL-6 induced increased LRC clustering and cell cycling. Notably, we could exploit the power of dynamic single-cell analyses as opposed to conventional bulk cell cultures: OPN showed a non-significant effect on the population-averaged proliferation com-pared with Wnt5a and Wnt3a, but single-cell time-lapse analysis unequivocally revealed a delay in cell division time. This is a typi-cal example where an opposite effect on a small fraction of cells can lead to completely different and erroneous conclusions.

Our data corroborate previous findings on the role of some of these candidate factors in maintaining HSC quiescence in vivo. Wnt5a has been associated with HSC quiescence through the activation of the non-canonical and inhibition of the canonical Wnt-pathway.11 OPN has been shown to induce stem cell quies-cence as well.13,14 OPN-/- mice display an aberrant localization of

Inhibition of LRC by niche factors goes along with higher fractions of asynchronous cell divisions. We further tested the effect of the six factors on single HSC fate by analyzing their influence on the synchrony of cell division. For each pair of daughter cells generated by a dividing mother HSC, we measured the elapsed time to enter the second division (Fig. S7). Based on these measurements, we determined whether a cell divided syn-chronously (corresponding to an arbitrarily defined time gap Δt between daughter divisions of less than 10 h) or asynchronously (Δt > 5 h). We measured that between 30–50% of single HSCs exposed to Wnt5a, OPN and Wnt3a, factors that decrease LRC, displayed an asynchronous behavior comparable to the basal con-ditions (Fig. 7A). In contrast, IL-3 and IL-6, both conditions inducing LRC, markedly increased the synchrony of division. More than 80% of all single cells cultured under these conditions displayed a synchronous division pattern (Fig. 7B). Of note, our single-cell analyses further revealed that 30–40% of single HSC treated with IL-3 and IL-6 developed into a megakaryocyte-like phenotype, characterized by cells undergoing huge increases in size after the first or second division (Fig. S11A–C). Compared with the basal conditions, the increase in megakaryocyte-like phenotypes was 2-fold. In some cases these cells disaggregated

Figure 3. c-Kit co-localizes with LRC. Live Lt-HSC were stained with CtXB (green) and anti-c-Kit (red). c-Kit co-localize with LRC.

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is not sufficient to rise a signal level necessary for activation of HSC. Moreover, impairing LRC by depleting cholesterol from the membrane with MβCD still allows activation of downstream signaling but not to an extent sufficient to promote cell activa-tion.17,23,24 Therefore, LRC concentrates activated receptors to augment signaling necessary for cellular activation and, at the same time, recruits in the inner leaflet of the membrane impor-tant mediators of the PI3K-Akt pathway that play a pivotal role in c-Kit signaling.52 Consistent with this, FOXO3a, mTOR and GSK3β, downstream targets of the PI3K/Akt pathway, have been shown to be crucial modulators of HSC metabolism and quiescence.19,53-55 Intriguingly, niche signals such as TGFβ, Wnts or OPN could act on HSC fate by blocking this activation pro-cess, which would manifest itself by LRC inhibition.17,23,24 Our experiments also show that other factors affecting LRC had a direct effect on c-Kit (and Sca-1) distribution in the membrane.

HSCs after transplantation as well as increased cycling of LKS pro-genitors. In addition, a thrombin-cleaved OPN fragment, the most abundant form of this protein in the bone marrow, was shown to be a potent chemoattractant for HSCs.15 In contrast, published data on the role of canonical Wnt signaling in HSC regulation is conflicting. By using genetic loss of function of key components of the Wnt signaling pathway such as catenins, some groups have shown no effect on HSC main-tenance and multilineage recon-stitution,41,42 whereas others have found that conditional overexpres-sion of β-catenin led to a loss of a functional HSC pool.43,44 Perhaps more relevant in the context of our studies, others have characterized a mouse model in which niche osteoblasts were manipulated to overexpress the Wnt/β-catenin antagonist Dickkopf1. Altered Wnt signaling resulted in a deple-tion of HSCs in G

0 and a loss of

the stem cell pool,45 indicating that Wnt3a might indeed play a role in sustaining HSC quiescence and long-term self-renewal.

The cytokines IL-3 and IL-6, which increased LRC in our stud-ies, are well known to activate HSCs. Cultured in the presence of these interleukins, HSCs showed faster cell cycling associated with impaired engraftment,46 a behav-ior that was linked to a shift of the cells from G

0 to G

1 or G

2.47,48 We found that VEGF, together with

IL-3 and IL-6, displayed the strongest increase in LRC. VEGF plays a key role in hematopoietic specification from embryonic and pluripotent induced stem cells.49 A potential role of VEGF in the retention of progenitor cells in the bone marrow of adult mice has also been described in references 50 and 51. Exogenous administration of VEGF to mice inhibited progenitor mobiliza-tion induced by a CXCR4-antagonist and stimulated hematopoi-etic progenitor entry into cell cycle.

Our experiments suggest that HSCs could become activated in vitro by extrinsic signals via a common pathway involving lipid raft clustering. Although it is not known whether LRC also occurs in vivo upon HSC activation, in vitro stimulation of HSCs by SCF has been previously shown to result in clus-tering of c-Kit together with lipid rafts, followed by cell cycle entry.16 The mere binding of SCF to c-Kit in the absence of LRC

Figure 4. effect of Wnt5a, opN, Wnt3a, IL-3, VeGF and IL-6 on cell proliferation. Analysis of proliferation of single cells measured as fold-increase at each time point. HSC were seeded in microwells and exposed to different doses (indicated on the graph) of Wnt5a, opN, Wnt3a, IL-3, VeGF and IL-6 and followed by time-lapse microscopy over five days (time interval, 3 h). (A–C) Wnt5a and Wnt3a significantly inhibited prolifera-tion, while opN did not induce any major effect. (D–F) on the other hand, IL-3 and IL-6 induced significant increases in proliferation, in contrast to VeGF. **p < 0.01, ***p < 0.001.

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Figure 5. Analyses of times to first division. the curves indicate the percentage of cells that undergo a first division. the elapsed time compared with the basal condition is calculated for 50% of the population of single cells. the graphs represent the two highest concentrations for each factor. (A–C) Wnt5a, opN and Wnt3a are capable to induce a delay in time to first division. (D–F) None of the other three factors (IL-3, VeGF and IL-6) has a major effect on the time to first division. (G–I) Analyses of elapsed times from the first to the second division. Both interleukins dramatically shortened the time from first to second division, while VeGF did not affect the kinetics of second division.

It is therefore conceivable that LRC inhibition could be a strategy developed by the cell to respond to niche signals, where, through a single, not-yet-understood mechanism of action, the cell can encode different signals targeted to maintain the HSC pool.

Even though the molecular mechanisms of how niche factors interfere with lipid raft clustering have yet to be elucidated, our findings may have practical implications for HSC biology and in particular the discovery and study of novel HSC fate regulators. We believe that lipid raft clustering could serve as a very early phe-notypic hallmark of HSC activation and possibly commitment.

The prospect to identify and pre-dict at very early time points (< 2 h), long before a cell divides, whether a stem cell is activated when exposed to a factor of interest, could be a fruitful avenue to further explore in the context of large-scale screen-ing efforts. Maybe even more sig-nificantly, our approach could help to identify novel “artificial niches” that can revert an activated cell into a quiescent state characterized by an evenly distributed lipid raft organization.

Methods

Mice. C57Bl/6 mice were pur-chased from Charles River Laboratories International and maintained at the Center for Studying Living Systems (CAV) at the EPFL in microisolator cages. Mice were provided continuously with sterile food, water and bed-ding. All in vivo procedures were performed in accordance with the Swiss law.

Isolation and purification of HSCs by FACS. HSCs were iso-lated from flushed bone marrows of 8–12-week-old donor mice. The cell suspension was filtered through a 70 μm cell strainer (BD Bioscences), and erythroid cells were eliminated by incuba-tion with red blood cells lysis buffer (RBC) (eBiosciences) for 5 min on ice. Lineage-positive cells were depleted using a magnetic depletion lineage kit (Milteny Biotechnology) in accordance with manufacturer’s instructions. Cells were stained with 1 μg/ml anti-c-Kit-PE/Cy7 (BioLegend), 2 μg/ ml anti-Sca1-APC (BioLegend),

2 μg/ ml anti-CD150-PE (BioLegend), Streptavidin-TexasRed (Molecular Probe, Invitrogen) for lineage-positive selection and propidium ioidide (PI) to label dead cells. PIneg Linneg c-Kitpos Sca1pos CD150pos (LKS-CD150) were sorted by FACS on a FACS Aria II instrument (BD Bioscences).

Hoechst and pyronin-Y staining. Purified HSCs were incu-bated for 45 min at 37°C in Stemline serum-free medium (Sigma-Aldrich) with 20 μg/ml Hoechst 3342 (Invitrogen). Pyronin-Y (Sigma Aldrich) was added at 1 μg/ml, and cells were incubated for another 15 min.

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with 1 μg/ ml AlexaFluor488-conjugated cholera toxin sub-unit B (CTxB) (Invitrogen) and 0.1 μg/ml anti-c-Kit-PE/Cy7 (BioLegend) and 0.2 μg/ml anti-Sca1-APC (BioLegend) directly added to the medium.

Analysis of single cell cycle kinetics. To follow the behav-ior of HSCs at single-cell level, cells were sorted directly into 96-well plates coated with microwell arrays. Microwells contain-ing a single cell at the time of plating were tracked by time-lapse microscopy. Cells were cultured in basal medium (Stemline II containing 2 ng/ ml Flt3 and 100 ng/ ml SCF) supplemented with variable concentrations of the following proteins (all purchased from R&D Systems): Wnt5a (0.5 ng/ ml, 5 ng/ ml, 50 ng/ ml, 500 ng/ ml, 1 mg/ml), OPN (1 ng/ ml, 10 ng/ ml, 100 ng/ ml, 1 mg/ml, 2 mg/ml), Wnt3a (0.1 ng/ ml, 1 ng/ ml, 10 ng/ ml,

Competitive repopulation assay. Competitive repopulation assays were performed to assess in vivo long-term blood reconstitution capability. In brief, BL6/Ly 5.2 mice were lethally irradiated at 800 RAD and transplanted with 250 x 103 total bone marrow competitor cells from BL6/Ly 5.1 mice mixed with 40 highly purified LKS-CD150 donor cells from BL6-GFP+ mice. The efficiency of transplantation was measured as percentage of chi-merism of GFP+/Ly5.1.

Hydrogel microwell array pro-duction. Hydrogel microwell arrays were directly casted within indi-vidual wells of a 96-well plate as described in reference 34. Briefly, stoichiometrically balanced aqueous solutions of multi-arm poly(ethylene glycol) (PEG), end-functionalized with thiol and vinylsulfone groups were mixed and molded against a PDMS microstamp. Upon comple-tion of cross-linking, the stamp was removed, and the hydrogel microw-ell array was hydrated overnight at 4°C and then sterilized with UV light.

Lipid raft staining and image analysis. Freshly isolated live HSCs were stained with AlexaFluor488-conjugated cholera toxin subunit B (CTxB) (Invitrogen) at 1 μg/ml and directly added to the medium. Images were acquired using a Zeiss Axio Observer microscope. To quantify the percentage of HSCs bearing clusters (or not), we devel-oped a MatLab-based image-pro-cessing algorithm (MatLab2009b) capable of automatically identifying LRC. Acquired images were filtered to minimize noise, and morphological “Top-hat” filter-ing was applied to increase the contrast between the cells and the background. A fixed threshold was applied, and threshold images were used to create a mask that was applied on the origi-nal image. The mask was then used to identify lipid raft clusters of a cell based on pixel intensity (Fig. S4). To overcome the problem of variation of intensity within each image (Fig. S5), we applied the MatLab function k-mean, which groups the pixel independently of a threshold.

Live-cell staining with antibodies. In order to evaluate the role of LRC in HSCs signaling and activation, we analyzed the co-localization of c-Kit (and Sca1) and lipid raft clusters. Freshly isolated HSCs were stimulated with proteins and stained

Figure 6. Analyses of time from first to second division. the curves indicate the percentage of cells that undergo a second division over the course of the experiment. (A–C) Wnt5a, opN and Wnt3a induced a delay in time to first division with a stronger effect of both Wnts. (D–F) Both interleukins dramatically shortened the time from first to second division, while VeGF did not affect the kinetics of second division.

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Disclosure of Potential Conflicts of Interest

No potential conflicts of interest were disclosed.

Acknowledgments

We thank Girieca Lorusso and Marta Roccio for critical reading of the manuscript, Jose Artacho and Thierry Laroche for help with image acquisition and analysis, Gonzalo Tapia, Miguel Garcia and Sintia Winkler and members of the Center for the Study of Living Systems (EPFL) for animal care. We thank Regis Doyonnas for initial discussions. This work was supported by the SNSF grant FN 205321-112323/1 and by a EURYI award to M.P.L.

Note

Supplemental material can be found at:www.landesbioscience.com/journals/cc/article/19900

100 ng/ ml, 200 ng/ ml), IL-3 (0.02 ng/ ml, 0.2 ng/ ml, 2 ng/ ml, 20 ng/ ml, 40 ng/ ml), VEGF (0.1 ng/ ml, 1 ng/ ml, 10 ng/ ml, 100 ng/ ml, 200 ng/ ml) an IL-6 (0.1 ng/ ml, 1 ng/ ml, 10 ng/ ml, 100 ng/ ml, 200 ng/ ml). Proliferation kinetics was assessed using a Zeiss Axio Observer microscope equipped with an incubator chamber, temperature and CO

2 control. Images were automati-

cally acquired every 3 hours over 5 days using the imaging analy-sis software of MetaMorph (Visitron).

Statistics. Data were statistically analyzed by Student t-test and one-way ANOVA followed by Dunnett’s multiple com-parison test. Growth curves were compared by linear regression followed by testing equality of slopes. Significance was set at p < 0.05. The analysis was performed using the GrphPad Prism software.

Figure 7. Analyses of synchrony of cell divisions. the time gaps between the divisions of two daughter cells generated by the division of the mother stem cell were measured. (A) effect of Wnt5a, opN and Wnt3a on synchrony of cell division. pie charts show the percentage of daughter cells that divided within 5 h (blue), 5 to 10 h (red) and more than 10 h (green). No significant changes compared with basal conditions were observed. (B) effect of IL-3, VeGF and IL-6 on synchrony of cell division. HSC exposed to IL-3 and IL-6 conditions showed a mostly synchronous division behavior in contrast to VeGF. *p < 0.05, **p < 0.01

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