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2013-07-19

The Heterogeneity and Metastability ofMultipotent Hematopoietic CellsWendy W. WestonUniversity of Miami, wengem00@yahoo.com

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UNIVERSITY OF MIAMI

THE HETEROGENEITY AND METASTABILITY OF MULTIPOTENT HEMATOPOIETIC CELLS

By

Wendy W. Weston

A DISSERTATION

Submitted to the Faculty of the University of Miami

in partial fulfillment of the requirements for the degree of Doctor of Philosophy

Coral Gables, Florida

August 2013

©2013 Wendy W. Weston All Rights Reserved

UNIVERSITY OF MIAMI

A dissertation submitted in partial fulfillment of the requirements for the degree of

Doctor of Philosophy

THE HETEROGENEITY AND METASTABILITY OF MULTIPOTENT HEMATOPOIETIC CELLS

Wendy W. Weston Approved: ________________ _________________ Roland Jurecic, Ph.D. M. Brian Blake, Ph.D. Associate Professor of Dean of the Graduate School Microbiology and Immunology and Cell Biology ________________ _________________ Nevis Fregien, Ph.D. Mike Xu, Ph.D. Associate Professor of Cell Biology Professor of Cell Biology ________________ Robert Levy, Ph.D. Professor of Microbiology and Immunology

WESTON, WENDY W. (Ph.D., Molecular Cell and Developmental Biology) The Heterogeneity and Metastability of (August 2013) Multipotent Hematopoietic Cells Abstract of a dissertation at the University of Miami. Dissertation supervised by Associate Professor Roland Jurecic. No. of pages in text. (101)

Increasing numbers of studies are reporting phenotypic and functional

heterogeneity within a variety of stem cell types as well as the existence of inter-

convertible subsets within hematopoietic stem cells (HSCs), suggesting that

these cells are alternating between several metastable states. The extent of

heterogeneity and metastability in HSCs remains to be explored in depth. The

metastability of HSCs is most likely positively and negatively regulated by

currently unknown cell intrinsic and extrinsic mechanisms emanating from HSC

niches. But the regulation of HSC metastability by bone marrow (BM) niche cells

is not currently understood.

Numerous studies have shown that phenotypic, functional and molecular

features of EML cells closely resemble or are identical to the features of adult

HSCs and multipotent hematopoietic progenitors (MPPs). Thus, EML cells

represent the closest known in vitro counterpart of HSC/MPPs.

This investigation sought to analyze in depth the heterogeneity and

metastability of the EML cell line, as well as investigate the effect of BM niche

cells on their metastability. Our data illustrate that EML cells are very

heterogeneous and consist of several cell subsets with distinct expression of

HSC markers, cell cycle profile and capacity to differentiate. Remarkably, each

cell subset has the capacity to self-renew, as well as to produce other subsets

and restore the parental EML cell population. Our findings show that EML cells

oscillate between several inter-convertible metastable states with distinct

phenotypic and functional features. Equally important, our in depth studies have

also found that the metastability of EML cell line is homeostatically maintained

and tightly regulated by currently unidentified cell intrinsic mechanisms.

We therefore sought to investigate whether bone marrow (BM) niche cells will

affect the metastability of EML cells in a co-culture environment. Our results

indicate that mesenchymal and osteoblast cells do affect the metastability of EML

cells by shifting the metastability process towards increased production and

maintenance of more quiescent cell subsets.

Understanding how the metastability of HSCs is regulated is imperative to

deciphering the characteristics of HSCs when in a particular “state”. This

knowledge will ultimately help provide us the ability to alter the state of HSCs for

specific purposes, for example, more effective bone marrow transplant,

accelerated differentiation of HSCs post-transplant, reduced GVHD, lower

susceptibility to chemotherapy, etc.

iii

ACKNOWLEDGEMENTS

I would like to thank Jennifer Zayas for her mentorship, serial culture and PCR

work. Additionally, I would like to thank John George for his work obtaining the

microarray data and Ruben Perez for all his time and effort, particularly with

PCR. Additionally, I would like to acknowledge Shannon Opiela at the Sylvester

Flow Cytometry Core Lab for all her help in flow cytometry and cell sorting.

Finally, thank you to my mentor, Dr. Roland Jurecic, for passing on some of his

expansive knowledge about hematopoietic stem cells and for his mentorship,

critical thinking and editing abilities.

iv

TABLE OF CONTENTS

Page

LIST OF FIGURES ......................................................................................... vi LIST OF TABLES ........................................................................................... x Chapter 1 INTRODUCTION ........................................................................... 1 Chapter 2 MATERIALS AND METHODS ....................................................... 11 Cell lines and cell culture........................................................................... 11 Flow cytometry analysis and cell sorting ................................................... 11 Hematopoietic colony forming assays ....................................................... 13 Microarray expression analysis ................................................................. 14 RT-PCR expression analysis .................................................................... 14 Western Blotting ........................................................................................ 15 Statistics .................................................................................................. 16 Chapter 3 RESULTS ...................................................................................... 17 3.1 The extent of heterogeneity of EML cells ............................................ 17

Phenotypic heterogeneity .................................................................... 17 Functional heterogeneity ...................................................................... 19 Molecular heterogeneity ....................................................................... 27 3.2 The extent of metastability of EML cells .............................................. 34

Phenotypic metastability ...................................................................... 34 Phenotypic and functional metastability ............................................... 36 Serial sorting and culture ..................................................................... 38

v

3.3 The regulation of metastability of EML cells ........................................ 41 The effect of OP9 mesenchymal cells on EML metastability ............... 42 The effect of MC3T3 osteoblast cells on EML metastability................. 58 The effect of 3T3 fibroblast cells on metastability ................................ 73 Chapter 4 CONCLUSION AND DISCUSSION ............................................... 78 WORKS CITED…………… ............................................................................ 89

vi

LIST OF FIGURES

Page

Figure 1. HSCs give rise to all the blood cell types. ........................................ 2 Figure 2. The maintenance and multilineage differentiation of multipotent hematopoietic cell line EML. ........................................................................... 6 Figure 3. Adult HSC reside in the osteoblastic and vascular niches in the bone marrow. .................................................................................................. 8 Figure 4. The HSC-niche synapse .................................................................. 8 Figure 5. Flow cytometry analysis shows that the multipotent hematopoietic cell line EML is phenotypically heterogeneous. .................................................... 18 Figure 6. The broad spectrum of CD34 expression and gating ...................... 18 Figure 7. The CD34 subsets of EML cells are heterogeneous for expression of HSC markers. ................................................................................................. 20 Figure 8. The EML cell line and its cell subsets are functionally heterogeneous and exhibit distinct multilineage differentiation pattern. .................................. 21 Figure 9. The EML cell line and its cell subsets are functionally heterogeneous and exhibit distinct cell cycle profiles .............................................................. 23 Figure 10. The analysis of proliferation kinetics of CD34neg, CD34low, CD34int and CD34high EML cell subsets. ............................................................................. 25 Figure 11. The existence of a separate population with reduced initial CFSE labeling in CD34neg and CD34low EML cell subsets. ........................................ 26 Figure 12. CFSE labeling of EML cells distinguished two separate populations, designated CFSEmain and CFSEsatellite populations ......................................... 26 Figure 13. The molecular heterogeneity of the multipotent hematopoietic cell line EML .................................................................................................. 30 Figure 14. EML cells are predominantly Sca-1 positive .................................. 30 Figure 15. EML cells differ in their expression of STK and JAM4 but not C/EBP±. .................................................................................................. 33

vii

Figure 16. The cells within EML cell line oscillate between several inter-convertible and self-renewing metastable states. ........................................... 35 Figure 17. Flow cytometry analysis of CD27, VEGFR1, CD201 and CD150 HSC marker expression on day 14 progeny of total EML cells and each parental EML cell subset. .................................................................................................. 37 Figure 18. Flow cytometry analysis of cell cycle on day 14 progeny of total EML cells and each parental EML cell subset. ....................................................... 39 Figure 19. Each EML subset and its progeny retain the capacity to re-establish parental population of EML cells after serial sorting and cell culture. ............. 40 Figure 20. Flow cytometry analysis shows that EML cells can be separated from OP9-GFP cells. ............................................................................................... 43 Figure 21. OP9 cells do not express CD34, CD150 and VEGR1 HSC markers 44 Figure 22. Representative flow cytometry data of CD34 expression on the progeny of EML cells alone or in the presence of OP9-GFP cells. ................. 46 Figure 23. The progeny of EML cells grown on OP9 cells contain a higher percentage of CD34neg and CD34low EML cells .............................................. 47 Figure 24. EML cells were co-cultured with OP9-GFP cells for 8 days and returned to culture without OP9-GFP cells for another 7 days........................ 49 Figure 25. EML cells grown in the presence of OP9 cells express significantly less CD150 .................................................................................................. 50 Figure 26. EML cells co-cultured with OP9-GFP cells contain a higher percentage of cells in the G0 phase of the cell cycle. ..................................... 52 Figure 27. The analysis of the progeny of CD34neg EML cells cultured in the absence or presence of OP9-GFP cells. ........................................................ 53 Figure 28. The analysis of the progeny of CD34low EML cells cultured in the absence or presence of OP9-GFP cells. ........................................................ 54 Figure 29. The analysis of the progeny of CD34int EML cells cultured in the absence or presence of OP9-GFP cells. ........................................................ 55 Figure 30. The analysis of the progeny of CD34high EML cells cultured in the absence or presence of OP9-GFP cells. ........................................................ 56

viii

Figure 31. OP9 cells promote the maintenance of CD34neg and CD34low EML subsets .................................................................................................. 57 Figure 32. MC3T3 cells express CD34 and VEGR1 HSC markers but do not express c-kit or CD150 ................................................................................... 59 Figure 33. Gating strategy ensures evaluation of EML cells ........................... 60 Figure 34. Representative flow cytometry data of CD34 expression on the progeny of EML cells alone or in the presence of MC3T3 cells. ..................... 62 Figure 35. The progeny of EML cells grown on MC3T3 cells contain a higher percentage of CD34neg and CD34low EML cells .............................................. 63 Figure 36. EML cells were co-cultured with MC3T3 cells for 14 days and returned to culture without MC3T3 cells for 3 and 7 days. ............................................ 64 Figure 37. EML cells grown in the presence of MC3T3 cells express significantly less CD150 .................................................................................................. 66 Figure 38. EML cells co-cultured with MC3T3 cells contain a higher percentage of cells in the G0 phase of the cell cycle. ........................................................ 67 Figure 39. The analysis of the progeny of CD34neg EML cells cultured in the absence or presence of MC3T3 cells. ............................................................ 68 Figure 40. The analysis of the progeny of CD34low EML cells cultured in the absence or presence of MC3T3 cells. ............................................................ 69 Figure 41. The analysis of the progeny of CD34int EML cells cultured in the absence or presence of MC3T3 cells. ............................................................ 70 Figure 42. The analysis of the progeny of CD34high EML cells cultured in the absence or presence of MC3T3 cells. ............................................................ 71 Figure 43. MC3T3 cells promote the maintenance of CD34neg and CD34low EML subsets .................................................................................................. 72 Figure 44. NIH/3T3 cells do not express the HSC markers CD34, c-kit, CD150 or VEGFR1 .................................................................................................. 74 Figure 45. Gating strategy for selection of EML cells in co-culture with NIH/3T3 cells .................................................................................................. 75 Figure 46. Representative flow cytometry data of CD34 expression on EML cells with and without NIH/3T3 cells. ...................................................................... 76

ix

Figure 47. There is no significant change in the frequency of CD34 subsets when EML cells are grown in the presence of NIH/3T3 cells. ................................ 77 Figure 48. Model showing the intrinsic metastability of EML cells .................. 81 Figure 49. Model showing the effect of BM niche cells on EML cell metastability .................................................................................................. 84 Figure 50. Model of HSC metastability in the BM niche .................................. 86

x

LIST OF TABLES

Page

Table 1. Microarray results reveal little difference between CD34neg and CD34pos subsets of EML cells in hematopoiesis and HSC-relevant genes as well as lineage-associated genes.. ............................................................ 28 Table 2. Microarray results reveal little difference between CD34neg and CD34pos subsets of EML cells in hematopoietic cell surface markers, receptors and adhesion molecules. ................................................................ 29

1

Chapter 1: Introduction

Adult hematopoietic stem cells (HSCs) are multipotent stem cells that reside in

the bone marrow and give rise to all the blood cell types from the myeloid

(monocytes and macrophages, neutrophils, basophils, eosinophils, erythrocytes,

megakaryocytes/ platelets, dendritic cells), and lymphoid lineages (T-cells, B-

cells, NK-cells) (Figure 1). The HSCs maintain homeostasis of the hematopoietic

system by replacing differentiated blood cells lost through physiological turnover,

disease, or injury. The life-long maintenance and regenerative capacity of the

hematopoietic system depend on self-renewal and differentiation of HSCs.

HSCs undergo symmetric or asymmetric self-renewal division in order to

maintain the HSC pool and produce new mature blood cells1-7.

The population of HSCs constitutes ~0.01% of cells in the adult human and

mouse bone marrow and contains cells with long-term and short-term

regeneration capacities, which in turn give rise to multipotent hematopoietic

progenitors (MPPs), common myeloid and lymphoid progenitors (CMPs and

CLPs) (Figure 1). The functional definition of HSCs in the HSC field is the ability

to produce at least 1% of lympho-myeloid progeny in the recipient’s peripheral

blood at 16 weeks post-transplantation.

Numerous studies have reported the phenotypic and functional heterogeneity

within a variety of stem cell types, including ES cells and adult neural, intestinal

and hematopoietic stem cells (HSCs), which arises from the coexistence of

different cell subsets8-28. More importantly an increasing number of studies is

also reporting the existence of inter-convertible metastable cell subsets within

2

Adapted from: Pallavi Sontakke, et. al. (2012) Mechanisms involved in HSC self-renewal and hematopoietic lineage commitment. Univ. of Groningen Figure 1. HSCs give rise to all the blood cell types. Division of HSCs produces daughter cells and may produce a progenitor which can differentiate into myeloid or lymphoid progeny, ultimately producing all the hematopoietic cell types. LT-HSC=long term HSC, ST-HSC=short term HSC, MPP=multipotent progenitor, CMP=common myeloid progenitor, CLP=common lymphoid progenitor, GMP=granulocyte/macrophage progenitor, MEP=megakaryocyte/erythroid progenitor, mK=megakaryocyte.

3

the pool of ES cells, intestinal stem cells, HSCs and cancer stem cells17, 21, 27, 29-

43.

Mounting experimental evidence supports the notion that the hematopoietic

system is maintained by a consortium of HSC subtypes with distinct functional

characteristics8, 9, 11, 16, 18, 21, 24. Differential expression of certain HSC markers

(e.g. CD34 and CD150) and Hoechst dye efflux capacity have enabled

identification of functionally distinct and inter-convertible subsets of HSCs. The

studies by the Ogawa group were the first to reveal that mouse long-term

repopulating HSCs (LTR-HSCs) alternate in vivo between LSK CD34- and LSK

CD34+/low states44-49. Other reports suggested that mouse LTR-HSCs oscillate

between LKS Flk2- CD34- dormant and LKS Flk2- CD34+ activated states38, 39, 50.

Based on differential expression of CD150 marker and Hoechst dye efflux

capacity, several studies have shown that LTR-HSCs could be divided into two

functionally and potentially inter-convertible distinct subsets: (1) a CD150hi subset

with a high propensity to generate myeloid progeny, and (2) a CD150low subset

with a high propensity for differentiation into lymphoid lineages8, 18, 22, 31, 51. These

findings are profoundly shifting our perception of HSCs from being a functionally

uniform cell pool to a dynamic pool of multiple inter-convertible cell subsets.

The precise role of metastability in HSC biology remains unclear, and the

characteristics, extent and the regulation of HSC metastability remain to be fully

explored. The ability to “switch” between different inter-convertible functional

states could be enabling HSCs and multipotent hematopoietic cells in general to

respond differently to various external cues and signals from cells in the bone

4

marrow (BM) environment in which HSCs reside and other hematopoietic cells,

as well as to stress, infection, inflammation, and injury caused by radiation and

chemotherapy agents. Since the cellular and molecular components of BM

niches regulate the survival, self-renewal and differentiation of HSCs and

multipotent hematopoietic cells16, 39, 52-77, it is likely that they also are involved in

the cell extrinsic regulation of the metastability of HSCs and multipotent

hematopoietic cells.

Studying the regulation of HSC metastability in vivo or in vitro is technically

and practically complicated because of the low frequency of HSCs and

associated difficulties in capturing oscillating cell states in vivo, as well as the

difficulties in long-term in vitro maintenance of functional HSCs. The multipotent,

self-renewing murine hematopoietic cell line EML is a well characterized in vitro

surrogate for HSCs and multipotent progenitors (MPPs), and is emerging as a

unique model to study the heterogeneity and metastability of multipotent

hematopoietic cells36, 41, 42, 78-105.

The multipotent SCF-dependent hematopoietic cell line EML was derived from

the bone marrow (BM) cells of 5-FU treated BDF1 mice99. This cell line has

normal karyotype, is not transformed, and is the only known hematopoietic cell

line with well documented multilineage (erythroid, myeloid, lymphoid)

differentiation capacity79, 87, 89, 90, 92, 98-100, 105. In the presence of SCF, EML cells

undergo proliferative self-renewal, while in the presence of specific cytokines

and/or stroma they differentiate into erythroid, granulocyte-macrophage,

megakaryocyte, and B cell progenitors (Figure 2) 87, 89, 92, 98, 99, 105. Moreover, we

5

have reported that in the OP9-DL1 co-culture system, supplemented with

cytokines (SCF, IL-7 and Flt3L), EML cells undergo T cell differentiation90, 106

(Figure 2).

Numerous studies including our own have shown that phenotypic, functional

(lineage commitment, differentiation) and molecular features (transcriptional

regulation, signal transduction pathways, cellular and molecular responses to

cytokines, etc.) of EML cells closely resemble or are identical to the features of

adult HSCs and multipotent hematopoietic progenitors (MPPs). Thus, the EML

cell line represents the most similar in vitro counterpart of HSCs and MPPs to

date, and is being used as an important and relevant model to study the

maintenance, lineage commitment and differentiation of multipotent

hematopoietic cells36, 41, 42, 78-105.

Papers by Chang et al.32 and Pina et al.36 have shown that EML cells

reversibly oscillate between several cell subsets, and include analysis of certain

characteristics of EML cell metastability based on the range of expression of

HSC marker Sca-1. These studies suggested that inter-convertible metastable

states of EML cells reflect either (a) slowly fluctuating transcriptomes that may

govern reversible priming and cell fate decision, or (b) the oscillation between

self-renewing and committed cell states32, 36. Based on differential expression of

CD34 marker our laboratory has previously reported that EML cells reversibly

oscillate between CD34- and CD34+ metastable cell states41, 42.

6

Figure 2. The maintenance and multilineage differentiation of multipotent hematopoietic cell line EML.

7

In this study, we sought to analyze in depth the heterogeneity and metastable

properties of EML cells. Our findings have revealed extensive phenotypic and

functional cell heterogeneity within EML cell line, due to the coexistence of

several cell subsets with distinct HSC marker expression patterns, cell cycle

profile and the propensity to differentiate. Furthermore, our data show that each

EML cell subset is metastable with the capacity to both self-renew and produce

all other cell subsets, and re-establish the parental EML cell population. Taken

together, our findings show that EML cell line consists of distinct cell subsets that

co-exist in a dynamic equilibrium and oscillate between self-renewing and inter-

convertible metastable states with distinct phenotypic and functional features.

Equally important, our results support the notion that the dynamic equilibrium of

metastable EML cell subsets is homeostatically maintained and regulated by

currently unknown cell intrinsic mechanisms.

Within the BM, HSCs reside in at least two specialized areas (niches): (1) an

endosteal niche, containing osteoblasts, mesenchymal stem cells (MSCs) and

CXCL12-abundant reticular (CAR) cells, and (2) a perivascular endothelial niche,

containing vascular endothelial cells, MSCs, macrophages and CAR cells

(Figure 3). The cellular and molecular components (adhesion proteins, secreted

and membrane-bound cytokines, chemokines, extracellular matrix components,

etc.) of BM niches comprise the so called HSC-niche synapse, which regulates

HSC survival, self-renewal, lineage priming and differentiation (Figure 4)54, 73-77,

107-112.

8

Figure 3. Adult HSC reside in the osteoblastic and vascular niches in the bone marrow.

Figure 4. HSC self-renewal and differentiation are regulated by cell intrinsic and extrinsic pathways which interact through the synapse between HSC and niche cells.

Anne Wilson & Andreas Trumpp (2006).

Ehninger A , and Trumpp A J Exp Med 2011;208:421-428

9

Since the EML cell line is perpetually maintained in the absence of cellular

and molecular components of BM niches (with an exception of SCF)99, 105, our

findings support the notion that the dynamic equilibrium of metastable EML cell

subsets is maintained and regulated by currently unknown cell intrinsic

mechanisms. Furthermore, the perpetual metastability of EML cells without the

influence of cellular and molecular components of BM niches points to the cell

intrinsic propensity of EML cells to be metastable. Thus, we sought to determine

(1) whether and how specific types of BM niche cells affect EML cell

metastability, and (2) if the changes in EML cell metastability, induced by specific

types of niche cells, are transient or persist long-term, and are irreversible or not.

Our results indicate that mesenchymal and osteoblast cells do affect the

metastability of EML cells by shifting the metastability process towards increased

production and maintenance of more quiescent cell subsets. There was a

concurrent decrease in the production and maintenance of more proliferative cell

subsets. This niche cell effect was reversible, indicating that the intrinsic

heterogeneous distribution and metastable profile is not permanently affected by

the BM niche cells.

Moreover, these results provide the first demonstration that the EML cell

metastability can be influenced by niche cells, further underscoring the biological

significance of this approach. Our findings also strengthen and emphasize the

biological relevance of EML cell line as a unique experimental model to study the

characteristics and regulation of multipotent hematopoietic cell metastability.

10

Since the cellular and molecular components of BM niches regulate the

survival, self-renewal and differentiation of HSCs and multipotent hematopoietic

cells73-77, it is likely that the components of the BM niches are also involved in the

cell extrinsic regulation of the metastability of HSCs and multipotent

hematopoietic cells.

Based on our findings we hypothesize that under homeostatic (non-stressed

or diseased) conditions, the metastability of HSCs within the BM is attenuated,

due to niche influences. However, HSCs may increase their level of metastability

after injury to BM niches or themselves (caused by radiation, chemotherapy

agents, or chronic inflammation), or upon the exit of HSCs from BM niches113, 114.

Thus, in response to stress and damage HSCs may become more metastable to

better balance their self-renewal and differentiation.

The ability to “switch” between different inter-convertible functional states

could be enabling HSCs and multipotent hematopoietic cells in general to

respond differently to various external cues and signals from the BM niches and

other hematopoietic cells, as well as to stress, infection, inflammation, and injury

caused by radiation and chemotherapy agents.

Learning how the metastability of multipotent hematopoietic cells is regulated,

and how this can be manipulated, is central for the better understanding of this

fascinating cellular process. This knowledge may also provide us the ability to

alter the state of HSCs for more effective bone marrow transplant, accelerated

differentiation of HSCs post-transplant, lower susceptibility to chemotherapy, etc.

11

Chapter 2: Materials and Methods

Cell lines and cell culture

The Stem Cell Factor (SCF)-dependent EML cell line was kindly provided by

Dr. Steve Collins (Fred Hutchinson Cancer Research Center, Seattle, WA). EML

cells were maintained in IMDM with L-glutamine (Gibco), and supplemented with

20% (vol/vol) equine serum (Hyclone), 1% Penicillin/Streptomycin (Sigma) and

10% (vol/vol) conditioned media from the BHK/MKL cell line (constitutively

expressing recombinant soluble SCF) as previously described99. EML cells were

maintained at a density of 0.5 - 5.0 x 105 cells/ml, and were passaged every

other day. The BHK/MKL cell line was maintained in DMEM with L-glutamine

(Gibco), 10% fetal bovine serum (Hyclone), and 1% Penicillin/Streptomycin

(Sigma). Conditioned media was collected from confluent BHK/MKL cell cultures

at 48 and 96 hours, centrifuged at 1200 rpm for 10 minutes, filtered through a

0.45 μm membrane and frozen in 50 ml aliquots at -20oC.

Co-culture experiments were conducted in 6-well plates. Adherent cell lines

were grown to 90% confluency in their respective optimal media. EML cells were

seeded onto adherent cultures at a concentration of 0.75 x 105 cells/ml in EML

growth media. EML cells were passed onto fresh 90% confluent adherent

cultures every 2 days at 0.75 x 105 cells/ml. Parallel suspension cultures were

maintained in the same manner without adherent cells.

Flow cytometry analysis and cell sorting

EML cells were harvested, washed with phosphate buffered saline (PBS), and

incubated with antibodies at the recommended concentrations for 40 min on ice,

12

followed by double wash in PBS. Centrifugation steps were carried out at 1200

rpm for 10 min at 4°C. The cells were analyzed live or after fixation in 10%

neutral buffered formalin. The following antibodies were used: IgG2a and IgG2b

isotype controls (eBioscience), anti-c-kit APC (eBioscience, clone 2B8), anti-Sca-

1 PE-Cy7 (eBioscience, clone D7), anti-Flk-2 PE (eBioscience, clone A2F10),

anti-CD49b PE-Cy7 (eBioscience, clone DX5), anti-CD34 FITC (eBioscience,

clone RAM34), anti-CD34 eFluor660 (eBioscience, clone RAM34), anti-CD150

APC (eBioscience, clone 9D1), anti-CD201 AlexaFluor647 (eBioscience, clone

mRCR-16), anti-VEGFR1 APC (R&D Systems, clone 141522) and anti-CD27

PE-Cy7 (eBioscience, clone LG.7F9). Before labeling of cells with multiple

antibodies, different fluorochromes were checked for compatibility and

compensation utilizing the BD Fluorescence Spectrum Viewer. The cell cycle

profile of total EML cells and purified CD34neg, CD34low, CD34int and CD34high

EML cell subsets was analyzed by Propidium Iodide (PI), Hoechst 33342, and Ki-

67/7-AAD staining. For staining with PI (BIOTIUM) the cells were re-suspended

in cold 70% ethanol, washed in PBS, treated with 0.1 mg/ml RNase A, and

incubated with 0.1 μg/μl PI. For staining with Hoechst 33342 (SIGMA) the cells

were re-suspended in cold PBS/1% formaldehyde, and incubated with 5 μg/ml

Hoechst at 37oC for 15 minutes. For analysis of Ki-67 expression, the EML cells

were first labeled with anti-CD34 FITC antibody. Staining of labeled EML cells

with Ki-67-eFluor450 (eBioscience, clone B56) followed the eBioscience Protocol

B for Staining Intracellular Antigens for Flow Cytometry

(http://www.ebioscience.com/media/pdf/best-protocols/staining-intracellular-

13

antigens-for-flow-cytometry.pdf), utilizing the Foxp3/Transcription factor staining

buffer set (eBioscience), followed by addition of 1:100 μl of 7-AAD (BioLegend) in

PBS. To examine their proliferation kinetics, total EML cells and EML cell subsets

were first labeled with anti-CD34 eFluor660 antibody (eBioscience) as described.

Staining of live cells was performed by adding 1.5 uM CFSE in 1 ml of 0.1%

FBS/1X PBS for 8 minutes at room temperature, followed by addition of 1 ml of

warm FBS and 10 minute incubation in 37oC water bath. The cells were washed

3 times in 2% FBS/1X PBS and placed in culture. The expression of various

markers was analyzed on BD LSR II or BD LSRFortessa flow cytometers (BD

Biosciences) and data analyzed with FlowJo software (Tree Star). The cells were

sorted on a FACSAria II sorter (BD Biosciences).

Hematopoietic colony forming assays

To assess their multilineage differentiation capacity, total EML cells and

purified CD34neg, CD34low, CD34int and CD34high EML cell subsets were plated in

2 ml of 0.3% low melting temperature agarose (SeaPlaque, Cambrex) with 2X

IMDM (Gibco), 20% heat inactivated equine serum (Hyclone) and 10% SCF-

conditioned medium in replicate 6-well plates (103 cells/well). The media was

supplemented with 0.1 ng/ml of recombinant mouse interleukin 3 (IL-3) (R&D

Systems), 8 U/ml of recombinant human erythropoietin (Epo) (Ortho Biotech), or

3 ng/ml of recombinant mouse thrombopoietin (Tpo) (R&D Systems). Cultures

were maintained at 37oC, 5% CO2 for 7-10 days. The burst-forming erythroid

units (BFU-E), granulocyte/macrophage colony forming units (CFU-GM) and

megakaryocyte colony forming units (CFU-Meg) were counted 7-10 days after

14

plating. Data from multiple independent experiments are shown as mean +

standard deviation (SD).

Microarray expression analysis

To examine molecular differences between EML cell subsets we analyzed the

transcriptomes in three separately purified samples of CD34neg cells and

combined CD34int and CD34high subsets, refrerred to in the text as CD34+ cells.

The microarray expression analysis was performed by Ocean Ridge Biosciences

(ORB, Palm Beach Gardens, FL) using Agilent mouse microarrays. The mRNA

samples were prepared from total EML cells and purified CD34neg and CD34+

EML cells using Micro-FastTrack™ 2.0 mRNA and mRNA DIRECT Isolation Kits

(Life Technologies). Ocean Ridge Biosciences performed additional purification

of mRNA, sample labeling, microarray hybridization and data analysis. The

results were provided by ORB in Log2 transformed form and are presented as

mean ± s.d. (n=3). The < 1.5-fold difference in expression was not considered

significant. To identify differences in the hematopoietic transcriptomes between

EML cell subsets we specifically examined the expression of (1) genes important

for overall hematopoiesis and HSC maintenance and function, (2) hematopoietic

cell surface markers, receptors and adhesion molecules, and (3) genes

associated with erythroid, megakaryocytic, myeloid and lymphoid lineage

specification and development.

RT-PCR expression analysis

Total RNA and mRNA were isolated using the RNeasy Mini and Micro Kits

(Qiagen) and Micro-FastTrack™ 2.0 mRNA and mRNA DIRECT Isolation Kits

15

(Life Technologies). Equal amount of total or mRNA from each cell sample was

reverse transcribed using Superscript III System (Invitrogen). Polymerase chain

reactions (PCR) were performed in an Eppendorf Mastercyler for 35-40 cycles

(95°C for 30-45 seconds, 57-62°C for 45 seconds, and 72°C for 30-45 seconds).

Serial dilutions of cDNA were used in semi-quantitative reverse transcription

(RT)-PCR analysis. PCR products were run on 1% agarose (SeaKem, Cambrex)

gels and visualized with ethidium bromide staining on AlphaImager 3400 (Alpha

Innotech). The RNA content of samples was normalized based on the

amplification of HPRT as a control gene. Primer sequences are listed in the table

below.

Rae-28 5’-GTGCTACATGGTGACAGCTT 3’-AGCTAGGAAAGCTGACCTCT

GATA2 5’-GGCGTCAAGTACCAAGTGTCAC 3’-CTCCCGGCCTTCTGAGCAGGAG

Bmi-1 5’-AAGGAAGAGGTGAATGATAAAAGG 3’-ACTACAAAAGGAAGCAAACTGGAC

c-kit 5’-TCCTCACTCACGGGCGGATC 3’-TGGAGGTGGGGTGGGGAACT

GATA1 5’-GGAGCCCTCTCAGCTCAGC 3’-GACTTCCTGGTCGACCACCG

PU.1 5’-CGGATGACTTGGTTACTTACG 3’-TTGGACGAGAACTGGAAGGTA

HPRT 5’-GTTGAGAGATCATCTCCACC 3’-AGCGATGATGAACCAGGTTA

STK/RON 5’-CACCCTTTGTGGCTCCAACTTC 3’-TTCCATTGACCAGCACAGCTCG

JAM4 5’-TAACCAAATGGTGGTGCTGA 3’-CCACCATGACAGACACTTGG

C/EBP± 5’-TAGGTTTCTGGGCTTTGTGG 3’-AGCATAGACGTGCACACTGC

Western blotting

The cells were lysed in 100 μl of modified RIPA buffer (150 mM NaCl, 1% NP-

40, 150 mM Tris, pH 7.5, 1 mM EDTA), supplemented with protease inhibitor

(Roche), PhosStop (Roche), 10mM HEPES and 200mM PMSF. 25 μg of protein

was run on 12% SDS-PAGE gels (Bio-Rad Mini Protean-TGX) and transferred to

16

nitrocellulose membranes (Bio-Rad Trans-Blot). The membranes were incubated

overnight with 1:500 rabbit anti-C/EBP± monoclonal antibody (Epitomics, clone

EP709Y) in 5% BSA at 4oC, washed and then incubated overnight at 4oC with

1:10,000 goat anti-rabbit polyclonal IgG (H&L)-HRP secondary antibody

(Rockland). The proteins were detected with TMB Membrane Peroxidase

Substrate System (KPL) for detection of HRP. The human monocytic cell line U-

937 (ATCC, CRL-1593.2) was used as a positive control for expression of

C/EBP± protein. The membranes were stripped and incubated with rabbit anti-

GAPDH antibody (Sigma-Aldrich).

Statistics

Statistical significance was determined using a two-tailed unpaired Student t-

test (Prism Software, Graphpad). Data are expressed as mean + standard

deviation (SD). The number of independent samples and experiments are

provided in the figure legends. Statistical significance and P values are indicated

by asterisks and specified in the figure legends. P values of < 0.05 were

considered statistically significant.

17

Chapter 3: Results

3.1 The extent of heterogeneity of EML cells

Phenotypic heterogeneity

A precise characterization of EML cell heterogeneity remained to be explored

from a combined phenotypic, functional and molecular perspective. To evaluate

the heterogeneity of EML cell line we first examined the expression of several

classical HSC cell surface markers28, 115-124. The flow cytometry analysis revealed

that almost all EML cells are Sca-1+ c-kit+ Flk2– and CD49b– (alpha2-integrin),

but reproducibly exhibit varying expression levels of CD34, CD27, VEGFR1,

CD201 and CD150 markers (Figure 5A and B).

Range of expression of certain HSC markers (e.g. CD34 and CD150) and

differential Hoechst dye efflux capacity have enabled identification of functionally

distinct subsets of HSCs, such as Lin-Sca1+c-kit+(LSK) CD34– and LSK CD34low

LTR-HSCs, and CD150hi myeloid-biased and CD150low lymphoid-biased HSCs 8,

18, 22, 31, 45, 47-50, 125.

Based on the range of expression of the commonly used HSC marker,

CD3436, 40, 42, 105, 120, 125, 126, EML cells can be divided into CD34neg, CD34low,

CD34int and CD34high cell subsets (Figure 6). Although the frequency of each cell

subset within EML cell line fluctuates slightly, their overall average proportions

remained very stable throughout multiple cell passages. The analysis of

expression of CD27, CD201, VEGFR1 and CD150 markers has revealed further

reproducible phenotypic heterogeneity within EML cell subsets, with e.g. CD34neg

and CD34low subsets containing the highest percentage of VEGFR1+ cells, and

18

Figure 5. Flow cytometry analysis shows that the multipotent hematopoietic cell line EML is phenotypically heterogeneous. A) Representative flow cytometry analysis of HSC marker expression on EML cells. These data show that almost all EML cells express Sca-1 and c-kit markers on the cell surface and do not express Flk2 and CD49b markers, but reproducibly exhibit heterogeneous expression of CD150, CD201, VEGFR1(FLT1), CD27 and CD34 markers. B) Average percent of cells expressing CD27, CD201, VEGFR1, CD150 and CD34 on EML cells. Data are mean ± s.d. (n=4).

Figure 6. Based on the broad spectrum of CD34 expression EML cells can be reproducibly divided into CD34neg, CD34low, CD34int and CD34high cell subsets.

A

B C

D20

1 A

lexa

Flu

or6

47

19

CD34int and CD34high subsets containing the highest percentage of CD150+,

CD27+ and CD201+ cells (Figure 7).

Cumulatively, these results further underscore the phenotypic cell

heterogeneity within EML cell line, which consists of CD34neg, CD34low, CD34int

and CD34high EML cell subsets with distinct HSC marker expression profiles.

Functional heterogeneity

To investigate the functional differences between CD34neg, CD34low, CD34int

and CD34high EML cell subsets, we analyzed their multilineage differentiation

potential, cell cycle profile and proliferation kinetics. The multilineage

differentiation potential of FACS purified CD34neg, CD34low, CD34int and CD34high

cell subsets (~99% purity) was analyzed by colony forming cell (CFC) assays for

hematopoietic progenitors 87, 105. These assays have reproducibly shown that

CD34neg cells differentiate minimally or not at all, whereas CD34low, CD34int and

CD34high cells show an increasing propensity to differentiate into myeloid,

erythroid and megakaryocytic lineages in response to single or multiple cytokines

(Figure 8).

Notably, these findings are very similar to the report that in CFC assays,

mouse LSK CD34high BM cells differentiate efficiently into myelo-erythroid

lineages, while the CD34low and CD34- BM cells differrentiate poorly or not at

all16. Although the difference in the propensity of EML cell subsets to differentiate

is evidenced by their variances in ability to respond to cytokines, it may also be

affected by differences in proliferation kinetics and cell cycle status. For this

reason we did extensive evaluation of the cell cycle profile of each CD34 subset.

20

Figure 7. The CD34 subsets of EML cells are heterogeneous for expression of HSC markers. A) Representative flow cytometry data showing HSC marker expression on CD34 subsets of EML cells. These data show that CD34 subsets of EML cells reproducibly exhibit heterogeneous expression of CD27, CD201, VEGFR1 and CD150 markers. B) Average percent of cells expressing CD27, CD201, VEGFR1 and CD150 on each of the CD34 subsets of EML cells. This analysis has revealed differential and heterogeneous expression of the CD27, CD201, VEGFR1 and CD150 markers within CD34neg, CD34low, CD34int and CD34high EML cell subsets. Data are mean ± s.d. *p<0.05, **p<0.01 (n=3-4)

A

B

CD

201

Ale

xaF

luo

r647

CD

201

Ale

xaF

luo

r647

CD

201

Ale

xaF

luo

r647

CD

201

Ale

xaF

luo

r647

21

Figure 8. The EML cell line and its cell subsets are functionally heterogeneous and exhibit distinct multilineage differentiation pattern. The analysis of multilineage differentiation capacity of EML cells and FACS purified CD34neg, CD34low, CD34int and

CD34high EML cell subsets through CFC assays has (1) revealed that EML cell line is functionally heterogeneous, and (2) reproducibly shown that only a very small percentage of CD3neg cells differentiates into erythroid and myeloid lineages, whereas CD34low, CD34int and CD34high cells show an increasing propensity to differentiate into myeloid, erythroid and megakaryocytic lineages in response to single or multiple cytokines. (n=15).

22

When a cell is in the G0 phase of the cell cycle, it is not dividing. When cells

are in the S and G2/M phases, they are either duplicating their DNA in

preparation for division or are in the process of dividing. The cell cycle profile of

CD34neg, CD34low, CD34int and CD34high EML cell subsets was analyzed by

Propidium iodide (PI), Hoechst 33342 and Ki-67 vs. 7-AAD staining. PI staining

has reproducibly shown that each cell subset contains a significantly different

percentage of cells in G0/G1 and S/G2/M phases as compared to all other

subsets. The majority of CD34neg are in G0/G1 phase, whereas the percentage of

cells in S and G2/M phases gradually, but significantly, increases from CD34low to

CD34high cell subset (Figure 9A).

Hoechst staining reproducibly generated similar results, with the majority of

CD34neg being in G0/G1 phase, and significant differences in the frequency of

cells in G0/G1 phase between CD34low, CD34int and CD34high cell subsets

(Figure 9B). The Ki-67 vs. 7-AAD analysis further underscored our cell cycle

analysis by revealing that significantly more CD34neg cells were in G0 phase

specifically compared to CD34low, CD34int and CD34high EML cell subsets (Figure

9C). Also in agreement with PI and Hoechst data, there are significantly more

cells in S/G2/M in CD34high EML cells compared to CD34int, CD34int compared to

CD34low and CD34low compared to CD34neg cells (Figure 9C). Based on the cell

cycle data, the CD34neg subset of EML cells is composed of cells that are not

dividing, while more division is occurring in the each cell subset expressing

progressively more CD34. These results further underscore the functional

heterogeneity of EML cell subsets and suggest that the varied

23

Figure 9. The EML cell line and its cell subsets are functionally heterogeneous and exhibit distinct cell cycle profiles. The analysis of the cell cycle profile of CD34neg, CD34low, CD34int and CD34high EML cell subsets by A) Propidium iodide, B) Hoechst 33342 and C) Ki-67 vs, 7-AAD has revealed that the majority of CD34neg cells are in G0/G1 phase, whereas the percentage of cells in S and G2/M phases gradually, but significantly, increases from CD34low to CD34high cell subset. Data are shown as mean + SD. * P value <0.05, ** P value <0.001

A

B

C

Propidium Iodide

Hoechst 33342

Ki-67 vs. 7-AAD

(n=7)

(n=3)

(n=3)

G0/G1

S

G2/M

Gating strategy for PI based on Watson model

of cell cycle gates.

G0/G1 G2/M

S

Gating strategy for Hoechst 33342 based on

Watson model of cell cycle gates.

G0

G1 S/G2/M

Propidium Iodide

Co

un

t C

ou

nt

Hoechst 33342

Ki-

67

7-AAD

Gating strategy for Ki-67 vs. 7-AAD based on

negative controls and DNA content.

24

propensity to differentiate may be due, at least in part, to their differences in cell

cycle status.

To examine proliferation kinetics, purified CD34neg, CD34low, CD34int and

CD34high cell subsets were labeled with CFSE and their division evaluated at 24

hour time points for 5 days (Figure 10). While the cells in the CD34int and

CD34high subsets divided synchronously and with similar frequency, the cells in

the CD34low subset divided slightly asynchronously with a small portion of cells

dividing less frequently. On the other hand, the cells within CD34neg subset

exhibited more asynchronous and delayed division at all time points (Figure 10).

The CFSE labeling also revealed two distinct cell populations within the

CD34neg and CD34low subsets: a CFSEMain population with a uniformly high level

of CFSE labeling, and a CFSESatellite population (~30% and ~14% of CD34neg and

CD34low cells, respectively) with a lower level of CFSE labeling (Figure 11A).

Moreover, these CFSESatellite fractions of CD34neg and CD34low subsets appear to

be proliferating slower than the CFSEMain population (Figure 11B). In contrast,

the CD34int and CD34high cell subsets contained very small percentage of or

almost no CFSESatellite cells, respectively, which divided more synchronously with

the CFSEMain population (Figure 11A and B).

Importantly, the CFSE labeling of total EML cells also revealed two distinct

populations: a CFSEMain population (90-92% cells), and a CFSESatellite population

(8-10% cells) (Figure 12). Notably, the CFSESatellite population consists of

significantly more CD34neg and CD34low cells and significantly less CD34int and

CD34high cells than the CFSEMain population (Figure 12).

25

Figure 10. The analysis of proliferation kinetics of CD34neg, CD34low, CD34int and CD34high EML cell subsets. A) Overlay of CFSE signal for each CD34 subset at 24 hour time points following labeling shows division of the CFSE signal. B) Histograms of the overlay in (A) showing CFSE signal for each 24 hour time point. The CD34neg and CD34low cells (or a subset of these cells) exhibited reduced division compared to the CD34int and CD34high EML cell subsets (n=2). For example, in one experiment at 96 hours, 13.12% of CD34neg cells may not have divided from the 24 hour time point compared to 0.04% of CD34high cells that may not have divided.

A

B

26

Figure 11. The existence of a separate population with reduced initial CFSE labeling in CD34neg and CD34low EML cell subsets. A) CFSE labeling shows some cells in the CD34neg and CD34low cell subsets have reduced CFSE labeling at 0 hours compared to CD34int and CD34high cell subsets. (n=2) B) Overlay of CFSE labeling at 0 and 24 hours reveals that the cells in the CD34neg and CD34low subsets with reduced initial labeling has not divided by 24 hours. (n=2). Figure 12. CFSE labeling of EML cells distinguished two separate populations, designated CFSEmain and CFSEsatellite populations. CD34 labeling of the CFSEmain population shows a similar distribution to EML total. In contrast, cells in the CFSEsatellite population are primarily CD34neg and CD34low (n=2).

A

B

CFSEmain small cells

CFSEsatellite small cells

Cell size is not responsible for the

reduced CFSE levels.

27

These findings suggest that the CFSESatellite population within CD34neg and

CD34low subsets could be contributing to observed asynchronous division within

these EML cell subsets. The CFSE labeling has revealed an additional

heterogeneity within EML cell line, and particularly within the CD34neg cell subset,

which may be due to 1) an increased CFSE efflux capacity of CFSESatellite cells,

or 2) reduced activity or amount of intracellular esterases required to cleave the

acetate groups and render CFSE fluorescence. It is unlikely that immediate

division is responsible for the CFSEsatellite population, as EML cells divide

approximately every 18 hours and we have shown that the CD34neg subset of

EML cells were primarily in G0.

Cumulatively, these findings have revealed additional phenotypic and

functional cell diversity within the EML cell line, and support the notion that the

EML cell line consists of several cell subsets with distinct HSC marker

expression patterns, cell cycle profile and the propensity to differentiate.

Molecular heterogeneity

To investigate if molecular heterogeneity exists within the EML cell line, the

transcriptomes were analyzed in three batches of separately purified CD34neg

and total CD34+ EML cells (containing CD34 low, CD34int and CD34high subsets) to

examine the expression of: (1) genes important for HSC maintenance and overall

hematopoiesis, (2) hematopoietic cell surface markers, receptors and adhesion

molecules, and (3) genes associated with erythroid, megakaryocytic, myeloid and

lymphoid lineage specification and development87, 90, 98 (Table 1, Table 2 and

Figure 13). Interestingly, there was very little or no difference in the expression

28

Table 1. Microarray results reveal little difference between CD34neg and CD34pos subsets of EML cells in hematopoiesis and HSC-relevant genes as well as lineage-associated genes. nd= no difference defined as fold change < 1.5, NE= not expressed (n=3).

Gene symbol

Fold difference in expression CD34- EML/ CD34+ EML

Gene symbol

Fold difference in expression CD34- EML/ CD34+ EML

GATA-2 ndRae28 nd Mdr1 ndHoxA3 nd c-mpl ndHoxA4 nd Lnk ndHoxA9 nd GATA-1 ndHoxB4 nd Fog1 ndRunx1 nd Klf1 1.79

Runx2 nd Nfe2 nd

Runx3 nd EpoR ndSCL/Tal1 nd VWF 1.68

Jarid2 ndTie2/Tek 1.91 PU.1 nd

Tgm2 nd Mzf1 ndGrb10 nd Irf8 ndE2f1 nd Junb nd

Mdm2 nd c-myc ndElf4 nd Id1 -1.81

Foxo1 nd Id2 ndFoxo3a ndCdc42 ndPML nd

Esam1 ndBmi-1 ndEvi1 1.52

Fbxw7alpha nd

C/EBPα -2.26C/EBPβ ndC/EBPδ nd Pbx1 NE

Cbfb ndAldh1 nd RAG1 NEAbcg2 nd Tcfe2a nd

Pax5 ndIkaros nd

Abcc1 nd LYL1 ndSox4 nd Gfi1 ndJun nd E2A (Tcf3) nd

STAT3 nd HEB (Tcf12) ndSMAD1 nd E2-2 (Tcf4) nd

Ets 1 ndEts 2 nd

Hes1 1.87 T-bet ndBcl3 nd GATA-3 ndBcl6 nd Lck -1.83Bcl9 nd Ebf1 NE

Ctla2 ndDntt (TdT) -2.12

Tcf7 -2.65

NE

Myeloperoxidase (Mpo)

nd

nd

Hematopoiesis and HSC-relevant genes

Lineage-associated genes

MkE lineages

Macrophage expressed gene

1 (Mpeg1)

Myeloid lineages

ndMFNG (manic

fringe)

Abcb1(b)p-glycoprotein

nd

Myeloid cell leukemia

sequence 1 (Md1)

Lymphoid lineages

29

Table 2. Microarray results reveal little difference between CD34neg and CD34pos subsets of EML cells in hematopoietic cell surface markers, receptors and adhesion molecules. nd= no difference defined as fold change < 1.5, NE= not expressed (n=3).

Gene symbol

Fold difference in expression CD34- EML/ CD34+ EML

Gene symbol

Fold difference in expression CD34- EML/ CD34+ EML

c-kit nd Syndecan 1 NECD34 -1.83 N-cadherin NECD38 4.9 CXCR4 nd

CD150 nd CCR5 ndCD244 nd CCR7 ndCD48 nd CCR9 ndCD44 nd Pecam1 (CD31) nd

Notch1 nd

Flk-2/Flt3 ndThy-1 (CD90) NE VCAM1 NE

STK/RON/Mst1r 1.86 ICAM-1 ndCD27 -2.4 ICAM-2 nd

CD47 (IAP) nd Integrin ±1 ndCD41 (Itga2b) nd Integrin ±2 NE

CD105 (Endoglin) nd Integrin ±4 ndTnfrsf1± -2.52 Integrin ±5 ndTnfrsf1² nd Integrin ±6 nd

IL-1R NE Integrin ±7 ndIL-3Ra nd Integrin ±8 NEIL-6R nd Integrin ±9 1.88

G-CSFR nd Integrin ±M NEM-CSFR nd Integrin ±V NE

GM-CSFR± nd Integrin ±X NETGFR 1 nd Integrin ² 1 nd

Integrin ² 2 nd

Integrin ² 3 ndFc³ R II low afinity nd Integrin ² 4 nd

Integrin ² 5 ndIntegrin ² 8 NE

CD154 (CD40L) NE Notch1 ndNotch2 ndNotch3 nd

JAM3 -1.98 Notch4 ndJAM4 2.3

Cell surface markers, receptors and adhesion molecules

L-selectin (CD62L)

NE

Fc³ R I high affinity

-2.6

Fc³ R III low afinity

nd

CD71 (Transferrin receptor)

nd

Cell surface markers, receptors and adhesion molecules

30

Figure 13. The molecular heterogeneity of the multipotent hematopoietic cell line EML. A) Microarray data (log2 transformed) of some hematopoietic genes reveals that CD34neg and CD34pos EML cells are very similar in their expression of many HSC/MPP genes. B) PCR verifies the microarray data shown in (A). C) PCR dilutions showing increasing expression of PU.1 RNA and decreasing expression of GATA1 RNA as CD34 expression increases. Data are mean ± s.d. (n=2).

Figure 14. EML cells are predominantly Sca-1 positive. All CD34 subsets of EML cells express Sca-1. Importantly, CD34negSca-1pos cells are a large portion of the CD34neg population (n=3).

A

B

** **

**

C

31

of most of the genes examined, including transcription factors (TFs) important for

hematopoiesis (GATA-2, Bmi-1, Rae28 etc.) (Table 1, Table 2 and Figure 13).

These results are similar to findings of previous studies, which examined the

gene expression profiles of CD34+ and CD34- EML cells using microarrays and

RNA-Seq technology, and revealed that the overall expression levels of most

mRNAs are similar in CD34+ and CD34- EML cells42, 102.

However, we did detect differences in the expression of PU.1, GATA-1 and

C/EBP± TFs, associated with myeloid and erythroid lineage specification and

restriction32, 36, 84, 127-133 (Table 1 and Figure 13). Slightly higher expression of

GATA-1 was found in CD34neg cells, whereas total CD34+ EML cells expressed

higher levels of PU.1 and especially C/EBP± (Table 1 and Figure 13).

The expression of these genes was further examined by RT-PCR and

Western analysis in purified CD34neg and total CD34+ EML cells, as well as

purified CD34neg, CD34 low, CD34int and CD34high cell subsets. The semi-

quantitative RT-PCR analysis found that the expression of PU.1 is indeed slightly

but not significantly higher in CD34int and CD34high cell subsets than in CD34neg

and CD34 low cells, while the expression of GATA-1 was slightly but not

significantly higher in CD34neg cells than in CD34 low, CD34int and CD34high cell

subsets (Figure 13C).

These results are in partial agreement with the findings of previous studies32,

36, 128, 131, 132, which found significantly higher expression of GATA-1 and lower

expression of PU.1 in Sca-1neg/low than in Sca-1high EML cells. Additionally, the

Sca-1neg/low EML cells were found to express significantly higher levels of GATA-1

32

than Sca-1high EML cells, although at the single cell level the population of Sca-

1neg/low EML cells is quite heterogeneous for expression of GATA-1. Further

subdivision of Sca-1neg/low EML cells on the basis of CD34 expression has shown

that the expression of GATA-1 is confined to Sca1neg/low CD34− cells, while the

expression of GATA-1 in the Sca1neg/low CD34+ cell compartment is minimal36.

The analysis of different EML cell subpopulations most likely accounts for the

differences in the GATA-1 and PU.1 expression levels between these studies

and our studies. Flow analysis shows that the majority of cells in the CD34neg

EML subset are Sca-1+, with only a small fraction of cells being Sca-1neg/low

(Figure 14). Thus, the analysis of CD34− and CD34+ subpopulations of

Sca1neg/low EML cells is actually excluding CD34neg Sca-1int/high cells and CD34+

Sca-1int/high cells, which constitute the majority of CD34neg and CD34+ EML cell

subsets (Figure 14).

Previous studies have shown that loss of C/EBP± results in increased self-

renewal of HSCs134. Notably, although the total CD34+ EML cells and CD34 low,

CD34int and CD34high cell subsets expressed higher level of C/EBP± transcript

than CD34neg subset (Figure 13A), the Western analysis detected no significant

difference in the expression of C/EBP± protein between all four cell subsets

(Figure 15B). Among other genes confirmed to be expressed at a higher level in

CD34neg cells is a HSC-derived receptor STK, and a junctional adhesion

molecule 4 (JAM4), expressed in LSK CD34- and LSK CD34+ BM cells

containing HSCs and MPPs, but not in more differentiated cells (Figure 15A)135,

136. Other important genes with slightly up-regulated expression in CD34neg EML

33

Figure 15. EML cells differ in their expression of STK and JAM4 but not C/EBP±. A) PCR analysis of purified CD34neg and CD34pos EML cells reveals that CD34pos EML cells express less STK and JAM4 RNA than CD34neg EML cells. B) In contrast to microarray data, PCR analysis on purified CD34neg, CD34low, CD34int, and CD34high EML cells shows no significant difference in C/EBP± RNA levels. C) In agreement, Western blot of the purified CD34 subsets reveals no significant difference in C/EBP± protein expression.

A

B

C

34

cells include: CD38 (another marker for mouse HSCs), Tie2/TEK, Klf1, EpoR and

VWF (Table 1and Table 2). The genes found to be down-regulated in CD34neg

EML cells include: CD27 and CD34, c-mpl, JAM3, Tnfrsf1±, Gfi1, Sox4, Dnt, Lck

and Tcf7 (Table 1 and Table 2). Interestingly, Tcf7 was also found to be strongly

down-regulated in Sca-1- CD34- EML cell subset in comparison to Sca-1+ CD34+

subset, and appears to be regulating the switch between self-renewal and

differentiation in EML cells102.

Overall, these studies have revealed that the hematopoietic transcriptome

signatures of EML cell subsets are quite similar and are less diverse than their

functional heterogeneity suggests.

3.2 The extent of metastability of EML cells

Phenotypic metastability

Since the average frequency of each EML cell subset is stable throughout

multiple cell passages, it was important to determine how each of the EML cell

subsets were continuously maintained. The CD34-, CD34low, CD34int and

CD34high EML cell subsets were purified (>99%) by sorting on a FACSAria II, and

individually cultured (Figure 16). To maximally avoid cross-contamination

between cell subsets and variable cell viability, only sorts which yielded the

highest cell purity (>99%) and viability (>95%) were used for these experiments.

Multiple independent cultures of purified cell subsets were maintained by serial

cell passage for up to 14 days, and the expression of CD34 on the progeny of

each cell subset analyzed every 2 days (Figure 16). Remarkably, this temporal

analysis of the progeny of each EML cell subset found that by day 12 of

35

Figure 16. The cells within EML cell line oscillate between several interconvertible and self-renewing metastable states. The CD34neg, CD34low, CD34int and CD34high EML cell subsets were purified by FACS (>99% purity, >95% viability). Multiple independent cultures of purified cell subsets were maintained by serial cell passage for 12 days, and the expression of CD34 on the progeny of each cell subset analyzed every 2 days. This temporal analysis of the progeny of each EML cell subset reproducibly revealed that by day 12 of culture each cell subset reproducibly generated all other subsets and reestablished complete parental EML population. The CD34neg cell subset exhibited the slowest kinetics while the CD34high cells ubset exhibited the fastest kinetics of generating other cell subsets and reestablishing the parental EML population.

36

culture each cell subset had reproducibly generated all other subsets and

reestablished the complete parental EML population (Figure 16). However, the

kinetics with which each EML cell subset generated other subsets and

reestablished parental EML population differed. Specifically, CD34neg cells were

the slowest and CD34high cells exhibited the most rapid kinetics. For example, it

took 6 to 8 days for CD34high and CD34int cell subsets, 8 to 10 days for the

CD34low subset, and 10 and 12 days for the CD34neg subset to generate all other

subsets and re-establish the complete parental EML population (Figure 16 and

data not shown).

Phenotypic and functional metastability

In order to address how the distribution of common HSC markers or the cell

cycle profiles were affected, another set of experiments were performed. In these

experiments, the purified CD34neg, CD34low, CD34int and CD34high cell subsets

were cultured separately for 14 days, and the expression of HSC markers on the

total day 14 progeny analyzed by flow cytometry. Notably, each parental cell

subset reproducibly generated new CD34neg, CD34low, CD34int and CD34high cell

subsets with a heterogeneous expression pattern of CD27, VEGFR1, CD201 and

CD150 markers (Figure 17A), which was not different (no statistical significance)

from the pattern on parental EML cells (Figure 17B). More importantly, all new

CD34neg, CD34low, CD34int and CD34high cell subsets, generated by each of the

parental EML cell subsets, exhibited a heterogeneous expression pattern of

CD27, VEGFR1, CD201 and CD150 markers (Figure 17C), which was also not

37

Figure 17. Flow cytometry analysis of CD27, VEGFR1, CD201 and CD150 HSC marker expression on day 14 progeny of total EML cells and each parental EML cell subset. The parental and purified CD34neg, CD34low, CD34int and CD34high EML cell subsets were cultured for 14 days and the progeny was analyzed by flow cytometry. A) The average percent of cells expressing CD27, CD201, VEGFR1 and CD150 on the 14 day progeny of parental EML cells. B) The analysis of 14 day progeny of parental and CD34 subsets shows that each subset has re-established the same average expression levels of CD27, CD201, VEGFR1 and CD150 markers as the parental EML cells. Data are mean ± s.d. (n=3) *p<0.05. C) The 14 day progeny of purified CD34 subsets were again gated for CD34neg, CD34low, CD34int and CD34high. The expression pattern of CD27, CD201, VEGFR1 and CD150 markers reveal that each subset re-established a similar distribution to the parental EML cells (A), even at the level of the CD34 subsets. Data shown as means + s.d. (n=2).

A

B

CD34 neg CD34 low CD34 int CD34 high

C

Progeny of parental EML

Progeny of CD34 neg

Progeny of CD34 low

Progeny of CD34 int

Progeny of CD34 high

38

statistically different versus the pattern expressed by parental EML cell subsets

(Figure 17B).

The analysis of the cell cycle profile of the day 14 progeny of each parental

EML cell subset also reproducibly showed that (1) the cell cycle profile of the

cumulative progeny of each cell subset closely resembled the cell cycle profile of

the parental population of EML cells (Figure 18A and B), and (2) the cell cycle

profile of each of the new CD34neg, CD34low, CD34int and CD34high cell subsets

generated by each parental cell subset closely resembled the cell cycle profiles

of parental cell subsets (Figure 18B and C). It is clear that CD34neg EML cells

had a higher percentage of cells in G0 with decreasing percentages of cells in G0

in CD34low, CD34int and CD34high cell subsets, as well as lower percentages of

cells in G2/M within the CD34neg EML subset and increasing percentages of cells

in G2/M in CD34low, CD34int and CD34high cell subsets.

Serial sorting and culture

The metastability of each EML cell subset was further tested through serial

cell sorting and culture. The EML cells were sorted into parental CD34neg,

CD34low, CD34int and CD34high subsets (cell purity >99% and viability >95%) and

cultured for 14 days (Figure 19A). The analysis of CD34 expression on day 14

progeny of each parental cell subset again showed that each subset generated

all other subsets and reestablished the parental EML cell population (Figure

19A). After 14 days of culture the primary progeny of each of the parental cell

subsets (Figure 5a) was sorted into separate sets of “primary” CD34neg, CD34

low, CD34int and CD34high subsets (99% purity) (Figure 19A). The CFC assays

39

Figure 18. Flow cytometry analysis of cell cycle on day 14 progeny of total EML cells and each parental EML cell subset. The parental and purified CD34neg, CD34low, CD34int and CD34high EML cell subsets were cultured for 14 days and the progeny was analyzed for cell cycle status by flow cytometry. A) The average percent of cells in G0, S, or G2/M for the 14 day progeny of parental EML cells. B) The analysis of 14 day progeny of parental and CD34 subsets shows that each subset has re-established the same average cell cycle profile as the parental EML cells. Data are mean ± s.d. (n=3) *p<0.05. C) The 14 day progeny of purified CD34 subsets were again gated for CD34neg, CD34low, CD34int and CD34high. The cell cycle profiles reveal that each subset re-established a similar distribution to the parental EML cells (A), even at the level of the CD34 subsets. Data shown as means + s.d. (n=2).

A

B

G1/G0 S G2/M

C

40

Figure 19. Each EML subset and its progeny retain the capacity to re-establish parental population of EML cells after serial sorting and cell culture. A) The CD34neg, CD34low, CD34int and CD34high EML cell subsets were purified by FACS and independently cultured for 2 weeks. The progeny of each of the “parental” CD34neg, CD34low, CD34int and CD34high EML cell subset was again sorted into CD34neg, CD34low, CD34int and CD34high “primary” cell subsets. B) The CFC assays on these primary cell subsets have shown that the CD34high subset retained their distinct differentiation pattern. Data are shown as mean + s.d. (n = 15). C) All of the primary CD34neg, CD34low, CD34int and CD34high cell subsets were cultured independently for another 2 weeks. D) The analysis of CD34 expression on their progeny after 14 days of culture has shown that each of the secondary cell subsets has produced other cell subsets and restored the CD34 expression profile of parental EML cell population (n=5).

A

B

C

D

41

found that each of the primary cell subsets retained their distinct differentiation

pattern (Figure 19B and data not shown). Each of these primary cell subsets

was then cultured for 14 days (Figure 19C). The analysis of CD34 expression

profile on their progeny showed that each of the primary cell subsets again

produced all other cell subsets and reestablished the parental EML cell

population (Figure 19D and data not shown).

These experiments demonstrated that even after serial sorting and culture,

each of the serially generated EML cell subsets retained the capacity to generate

all other subsets and to re-establish the parental EML cell population, while

maintaining distinct phenotypic and functional properties of each cell subset.

Cumulatively, these findings: (1) demonstrate that each cell subset has the

capacity to generate all other subsets and reestablish the parental EML cell

population, while maintaining distinct features of each cell subset, and (2) confirm

the notion that EML cell line consists of cells alternating between several inter-

convertible and self-renewing metastable states.

3.3 The regulation of metastability of EML cells

The regulation of HSC metastability remains to be fully explored. The

continuous maintenance and metastability of EML cells in an environment that

has no other cellular components (niche-free) make this cell line a truly

exceptional model to study the factors from within the cells (cell intrinsic) and

factors from outside the cells (cell extrinsic) mechanisms that regulate the

metastability of multipotent hematopoietic cells. To address if distinct populations

of BM niche cells can regulate the metastability of EML cells, we initiated co-

42

culture experiments consisting of EML cells with or without specific cells known

to be a part of the BM niche.

The effect of OP9 mesenchymal cells on EML metastability

EML cells were first co-cultured with the murine MSC-like cell line OP9137,

which has been used to study the maintenance and differentiation of ES cells

and mouse and human HSCs 106, 138-143. OP9 cells were established from the

calvaria of op (osteopetrosis) newborn mice. These mice have a mutation in the

gene encoding macrophage colony-stimulating factor (M-CSF) therefore, the

cells do not produce functional M-CSF. OP9 cells have been shown to support

hematopoietic differentiation99, 130-135 and are thought to be mesenchymal stem

cells by some137.

In the OP9 co-cultures a portion of EML cells remains in suspension in close

proximity to OP9 cells, while other cells adhered loosely to OP9 cells and could

be separated from OP9 cells by short trypsinization (which does not affect CD34

expression) (data not shown). In the experiments described below, because OP9

cells grew very well and were healthy in complete EML media, OP9-GFP cells

(produced from the GFP-only retroviral vector MigR1) were used to exclude them

during the analysis of EML cells and their progeny (Figure 20). OP9 cells were

evaluated for endogenous expression of CD34, CD150 and VEGFR1 and did not

express these proteins (Figure 21).

To explore for an effect of OP9 cells on EML cell metastability, total EML cells

were co-cultured with OP9 cells for 8 days as previously described90. The co-

cultures were established by seeding 3 X 104 EML cells/well into multiple 6-well

43

Figure 20. Flow cytometry analysis shows that EML cells can be separated from OP9-GFP cells. A) Unstained EML cells were used to set the negative gate for GFP expression. B) OP9-GFP cells were evaluated for expression of GFP and were 100% positive for GFP expression. C) Backgating of the EML and OP9-GFP populations together show that EML cells can be individually analyzed based on FSC vs. SSC parameters followed by negative selection for GFP expression.

C

A B

44

Figure 21. OP9 cells do not express CD34, CD150 and VEGR1 HSC markers. OP9 cells were stained for CD34, CD150 and VEGFR1. Representative flow cytometry data shows that the OP9 cell line is negative for CD34, CD150 and VEGR1. (n=3)

0.3%

99.7%

99.6%

0.4%

99.0%

98.8%

1.0%

1.2%

99.7%

99.1%

0.3%

0.9%

CD34 CD150 VEGFR1

45

plates containing a confluent monolayer of OP9 cells, and maintained in

complete EML media 99, 105. Every 48 hours of co-culture, the non-adherent and

adherent progeny of EML cells was collected and combined. An aliquot of these

cells was used to analyze for expression of HSC markers and cell cycle profile.

Cells were passaged and/or expanded on alternating days from collection to

avoid over-handling and ensure proper health and cell concentration of both EML

and OP9 cells.

Remarkably, in striking contrast to the same batches of EML cells cultured

without OP9 cells, the EML cells co-cultured with OP9 cells have reproducibly

(n=3) generated progeny containing (a) statistically significantly higher

percentage of CD34neg EML cells, (b) similar percentage of CD34low EML cells

and (c) significantly lower percentage of CD34int and CD34high EML cells than the

same batches of EML cells cultured without OP9 cells (Figure 22 and Figure

23). From this data we can surmise that the presence of OP9 cells both

attenuates the metastability of EML cells by reducing the range of oscillation and

promoting the maintenance of CD34neg and CD34low EML cells.

In order to determine if the ability of OP9 cells to alter population frequencies

of EML CD34 subsets required the continual presence of OP9 cells, or some

transient period of interaction could induce this long lasting change, the EML

cells cultured on OP9 cells for 8 days were removed from co-culture and placed

back in suspension, without OP9 cells. The CD34 expression on the EML cells

returned to suspension approached the parental expression levels after 7 days

46

Figure 22. Representative flow cytometry data of CD34 expression on the progeny of EML cells alone or in the presence of OP9-GFP cells. Cells were harvested and stained with CD34 antibody conjugated to APC and analyzed by flow cytometry. Selection of intact EML cells based on FSC vs. SSC (A) was followed by selection of GFP-FITC negative cells (B). Unstained EML cells grown on OP9-GFP cells were used to establish the negative APC gate for CD34-APC (C). The parental EML cells were evaluated for CD34 expression and split into two populations: 1) EML cells grown in suspension and 2) EML cells grown on OP9-GFP cells (D). Samples were collected every two days from each population and evaluated for CD34 expression.

D

Day 8

D

A B

Day 2

EML with OP9 Elimination of GFPpos cells

EML with OP9 Unstained

C

Day 4 Day 6

Day 0

EML without OP9 EML without OP9 EML without OP9 EML without OP9

EML without OP9

EML with OP9 EML with OP9 EML with OP9 EML with OP9

47

Figure 23. The progeny of EML cells grown on OP9 cells contain a higher percentage of CD34neg and CD34low EML cells. The progeny of EML cells grown on OP9 cells showed a significant increase in the percentage of CD34neg and CD34low EML cells with a concurrent significant decrease in the percentage of CD34int and CD34high EML cells. Values shown are average ± s.d., *p value<0.05, **p value<0.01 (n=3).

EML without OP9-GFPEML with OP9-GFP

48

without OP9 cells (Figure 24A and 24B). This indicates that either contact with

or paracrine signaling from OP9 cells was required for maintenance of the

reduced metastability.

The previous experiment was designed to determine if OP9 cells affected the

frequencies of EML CD34 subsets hence, the course of study was designed as

long as previously required for EML cells to re-establish the parental population

(Figure 16). In order to ensure that the results were not due to an extended

period of instability or adjustment in the presence of OP9 cells, we co-cultured

EML cells on OP9 cells for 20 days as described above. The analysis of CD34

expression on the EML cells from these cultures revealed that EML cells cultured

with OP9 cells still had significantly more CD34neg and CD34low EML cells

compared to EML cells grown in suspension and significantly less CD34int and

CD34high EML cells compared to EML cells grown in suspension (Figure 24C). It

is clear that the OP9 cell effect on EML cell metastability is not due to a period of

instability or adjustment, but is maintained.

Based on the findings that: (1) CD34neg and CD34low EML cells express less

CD150 and more VEGFR1 than CD34int and CD34high EML cells (Figure 8), and

(2) OP9 cells promote the maintenance of more CD34neg and CD34low EML cells

(Figure 23) EML cells grown on OP9 cells were investigated to determine if they

exhibited a change in CD150 and VEGFR1 expression. Interestingly, the progeny

of EML cells from OP9 co-cultures contained a significantly lower percentage of

CD150+ cells than the cells grown without OP9 cells (Figure 25). The reduced

amount of CD150 on the cell surface of EML cells grown on OP9 cells is

49

Figure 24. EML cells were co-cultured with OP9-GFP cells for 8 days and returned to culture without OP9-GFP cells for another 7 days. The CD34 expression on the EML cells returned to suspension for 7 days was approaching the parental expression levels. A) Representative flow cytometry showing the CD34 expression on EML cells in suspension and EML cells returned to suspension following growth on OP9 cells for 7 days. B) The average CD34 expression on the EML cells returned to suspension was approaching the parental expression levels after 7 days without OP9 cells. Values shown are average ± s.d., *p value<0.05, **p value<0.01 (n=3). C) Flow cytometry data shows that the increased percentage of CD34neg and CD34low EML cells when grown on OP9 cells persists for 20 days.

Day 15 Day 20

EML without OP9-GFPEML with OP9-GFP

EML without OP9 EML without OP9

EML with OP9 EML with OP9

EML with OP9

50

Figure 25. EML cells grown in the presence of OP9 cells express significantly less CD150. A) Representative flow cytometry data showing gating for data collection of 8 day progeny of EML cells from OP9-GFP co-culture experiment. All cells were collected and stained for CD150 conjugated to PE-Cy7 or stained for VEGFR1 conjugated to PE. Intact EML cells were selected by FSC vs. SSC profile followed by negative for GFP. Unstained EML cells grown on OP9 cells were used to set the negative gate for PE-Cy7 and PE. B) The average percentage of EML cells expressing CD150 or VEGFR1 following 8 days of suspension or co-culture with OP9 cells shows that there are significantly less EML cells expressing CD150 when EML cells are grown on OP9 cells compared to EML cells grown in suspension. Values shown are average ± s.d., *p value<0.05, **p value<0.01 (n=3).

A

B

EML without OP9-GFP EML with OP9-GFP

EML with OP9

EML with OP9

EML with OP9 EML with OP9 EML with OP9

EML without OP9 EML without OP9 EML without OP9 EML without OP9

51

consistent with the findings that EML cells grown on OP9 cells contain

significantly more CD34neg and CD34low subsets which we have reproducibly

shown express less CD150. The expression of VEGFR1 on the surface of EML

cells grown on OP9 cells was reduced, although not significantly. In summary,

this data indicate that EML cells in co-culture with OP9 cells have a reduced

expression of CD150.

Our earlier findings showed that CD34neg and CD34low EML cells contain more

cells in G0 than CD34int and CD34high EML cells (Figure 9), so we investigated

the cell cycle profiles of EML cells grown on OP9 cells. The cell cycle status was

analyzed by Ki-67 vs 7-AAD of EML cells cultured with and without OP9 cells for

10 days. The results reproducibly found that EML cells cultured with OP9 cells

had a significant increase in the percentage of cells in G0 (38.61 ± 5.92%)

compared to EML cells grown in suspension (9.14 ± 1.14%) (Figure 26). This

data further illustrates that the EML cells grown on OP9 cells contain significantly

more cells in G0 phase and fewer cells in S/G2/M phase, reflecting an increase

in the frequency of more quiescent CD34neg and CD34low EML cells.

To determine how each particular EML subset was affected, experiments were

performed with purified CD34neg, CD34low, CD34int, and CD34high EML cell

subsets co-cultured with OP9 cells for 12 days as described earlier. After 12 days

of co-culture with OP9 cells, each EML cell subset was found to have progeny

containing (a) a higher percentage of CD34neg and CD34low cells, and (b) a lower

percentage of CD34int and CD34high cells than subsets cultured without OP9 cells

(Figure 27 through Figure 31). Moreover, none of the cell subsets were

52

Figure 26. EML cells co-cultured with OP9-GFP cells contain a higher percentage of cells in the G0 phase of the cell cycle. A) Representative flow cytometry data showing gating for data collection of EML cells from the 8 day OP9-GFP co-culture experiment. All cells were collected from suspension and from concurrent culture on OP9-GFP cells. The collected cells were stained with Ki-67 antibody conjugated to eFluor450 followed by addition of 7-AAD. Intact EML cells were selected by FSC vs. SSC profile followed by negative for GFP. Unstained EML cells grown with OP9-GFP cells were used to set the negative gate for eFluor450 and 7-AAD. B) The average percentage of EML cells in each indicated stage of the cell cycle shows that EML cells grown with OP9-GFP cells contain a significantly higher percentage of cells in G0 than EML cells grown without OP9-GFP cells. Values shown are average ± s.d., *p value<0.05, **p value<0.01 (n=3).

A

B

EML w/out OP9-GFP EML with OP9-GFP

EML without OP9 EML with OP9

EML with OP9 EML with OP9

EML with OP9

53

Figure 27. The analysis of the progeny of CD34neg EML cells cultured in the absence or presence of OP9-GFP cells. Purified CD34neg EML cells were split into two populations: 1) EML cells grown in suspension and 2) EML cells grown on OP9-GFP cells. Every two days, cells from each population were collected and stained with CD34 antibody conjugated to APC. EML cells were selected based on FSC vs. SSC profile followed by negative for GFP expression. Unstained CD34neg cells in suspension were used to establish the negative gate for APC. The flow cytometry data shows that when CD34neg EML cells are grown on OP9 cells, higher percentages of CD34neg and CD34low EML cells are maintained compared to EML cells grown in suspension, whereas CD34int and CD34high EML cells are not.

Day 0

Day 2 Day 4 Day 6 Day 8 Day 10 Day 12

neg

54

Figure 28. The analysis of the progeny of CD34low EML cells cultured in the absence or presence of OP9-GFP cells. Purified CD34low EML cells were split into two populations: 1) EML cells grown in suspension and 2) EML cells grown on OP9-GFP cells. Every two days, cells from each population were collected and stained with CD34 antibody conjugated to APC. EML cells were selected based on FSC vs. SSC profile followed by negative for GFP expression. Unstained CD34low cells in suspension were used to establish the negative gate for APC. The flow cytometry data shows that when CD34low EML cells are grown on OP9 cells, higher percentages of CD34neg and CD34low EML cells are maintained compared to EML cells grown in suspension, whereas CD34int and CD34high EML cells are not.

Day 2 Day 4 Day 6 Day 8 Day 10 Day 12

Day 0

55

Figure 29. The analysis of the progeny of CD34int EML cells cultured in the absence or presence of OP9-GFP cells. Purified CD34int EML cells were split into two populations: 1) EML cells grown in suspension and 2) EML cells grown on OP9-GFP cells. Every two days, cells from each population were collected and stained with CD34 antibody conjugated to APC. EML cells were selected based on FSC vs. SSC profile followed by negative for GFP expression. Unstained CD34int cells in suspension were used to establish the negative gate for APC. The flow cyto metry data shows that when CD34lint EML cells are grown on OP9 cells, higher percentages of CD34neg and CD34low EML cells are maintained compared to EML cells grown in suspension, whereas the percentage of CD34int and CD34high EML cells are decreased.

Day 2 Day 4 Day 6 Day 8 Day 10 Day 12

Day 0

56

Figure 30. The analysis of the progeny of CD34high EML cells cultured in the absence or presence of OP9-GFP cells. Purified CD34high EML cells were split into two populations: 1) EML cells grown in suspension and 2) EML cells grown on OP9-GFP cells. Every two days, cells from each population were collected and stained with C D34 antibody conjugated to APC. EML cells were selected based on FSC vs. SSC profile followed by negative for GFP expression. Unstained CD34 high cells in suspension were used to establish the negative gate for APC. The flow cytometry data shows that when CD34 high EML cells are grown on OP9 cells, higher percentages of CD34neg and CD34low EML cells are maintained compared to EML cells grown in suspension, whereas the percentage of CD34int and CD34high EML cells are decreased.

Day 2 Day 4 Day 6 Day 8 Day 10 Day 12

Day 0

57

Figure 31. OP9 cells promote the maintenance of CD34neg and CD34low EML subsets. The increase in the percentage of CD34neg and CD34low EML subsets occurs with concurrent decline in the percentage of CD34int and CD34high EML subsets.

CD34 neg without OP9-GFP CD34 neg with OP9-GFP

CD34 high without OP9-GFP CD34 high with OP9-GFP

CD34 int without OP9-GFP CD34 int with OP9-GFP

CD34 low without OP9-GFP CD34 low with OP9-GFP

58

able to completely reestablish the CD34 expression profile and cell subset

content of the parental EML cell line.

In total, the results from these studies indicated that OP9 cells affect EML cell

metastability by attenuating and shifting the metastability process towards

increased production and maintenance of CD34neg and CD34low cell subsets, and

decreased production of CD34int and CD34high cell subsets.

The effect of MC3T3 osteoblast cells on EML metastability

Osteoblasts are a large component of the endosteal niche for HSCs. In order

to evaluate if osteoblasts can regulate the metastability of EML cells, EML cells

were co-cultured with subclone 4 (ATCC CRL-2593) of murine osteoblast cell line

MC3T3-E1 (derived from the BM of C57BL/6 mice)144, 145. These cells have been

used extensively to study bone production and osteogenic differentiation145-147

MC3T3 cells were grown in complete growth medium to establish healthy

growing cultures. Flow cytometry analysis showed that MC3T3 cells did not

express c-kit and CD150, but some expressed CD34, Sca-1 and VEGFR1

(Figure 32). Since all EML cells, their subsets and their progeny are 100% c-kit+,

and MC3T3 cells are c-kitneg, in this co-culture system the progeny of EML cells

were analyzed by gating on c-kit+ cells (Figure 33).

Total EML cells were first co-cultured with MC3T3 cells for 14 days as

described above for the OP9 co-cultures. Notably, by day 14 the EML cells co-

cultured with MC3T3 cells reproducibly (n=3) generated progeny containing (a)

significantly higher (p<0.05) percentages of CD34neg cells, (b) similar

percentages of CD34low cells and (c) lower percentages (p<0.05) of CD34int and

59

Figure 32. MC3T3 cells express CD34 and VEGR1 HSC markers but do not express c-kit or CD150. MC3T3 cells were stained for CD34, CD150 and VEGFR1. Representative flow cytometry data shows that MC3T3 cells do not express CD150 and c-kit proteins, but do express CD34 and VEGFR1. (n=3.).

60

Figure 33. Gating strategy ensures evaluation of EML cells. The gating strategy for elimination of MC3T3 cells involved selection of characteristic FSC vs. SSC distribution followed by selection of cells that are positive for c-kit expression.

61

CD34high cells than the populations of EML cells cultured without MC3T3 cells

(Figure 34 and Figure 35). As a result, the overall CD34 expression profile and

cell subset content of day 14 progeny of EML cells from MC3T3 co-cultures

differed from day 14 progeny of EML cells cultured without MC3T3 cells and

parental EML cell line (Figure 35 and data not shown).

In summary, the presence of MC3T3 cells attenuates the metastability of EML

cells and promotes the production and maintenance of CD34neg and CD34low

EML cells.

In order to determine if the effect of MC3T3 cells on EML metastability

required the continual presence of MC3T3 cells or represented a permanent

change in the CD34 distribution, the EML cells cultured on MC3T3 cells for 14

days were removed from co-culture and returned to suspension, without MC3T3

cells. The CD34 expression on the EML cells which had been returned to

suspension for 3 days approximated the CD34 expression of the parental

population (Figure 36A). This experiment was repeated and the 14 day co-

cultured cells were returned to suspension for 7 days. The CD34 expression

onthese EML cells returned to suspension was not significantly different (p<0.05)

from the parental population (Figure 36B), indicating that either permanent

contact with MC3T3 cells, or continued paracrine signaling from MC3T3 cells, is

required for maintenance of the reduced CD34 expression level.

Based upon the finding that MC3T3 cells promote the maintenance of more

CD34neg and CD34low EML cells, it was decided to investigate if EML cells grown

on MC3T3 cells exhibited a change in CD150 and VEGFR1 expression. Similar

62

Figure 34. Representative flow cytometry data of CD34 expression on the progeny of EML cells alone or in the presence of MC3T3 cells. Collected cells were stained with CD34 antibody conjugated to APC and analyzed by flow cytometry. Selection of intact EML cells based on FSC vs. SSC (A) was followed by selection of c-kit positive cells (B). Unstained EML cells grown on MC3T3 cells were used to establish the negative gate for CD34 (C). The parental EML cells were evaluated for CD34 expression and split into two populations: 1) EML cells grown in suspension and 2) EML cells grown on MC3T3 cells (D). Samples were collected from each population every two days for 14 days and evaluated for CD34 expression.

Day 0

Day 2 Day 4 Day 6 Day 8 Day 10 Day 12 Day 14

A B C

D EML without MC3T3

EML without MC3T3

EML without MC3T3 EML without MC3T3 EML without MC3T3 EML without MC3T3 EML without MC3T3 EML without MC3T3

EML with MC3T3 EML with MC3T3 EML with MC3T3 EML with MC3T3 EML with MC3T3 EML with MC3T3 EML with MC3T3

63

Figure 35. The progeny of EML cells grown on MC3T3 cells contain a higher percentage of CD34neg and CD34low EML cells. The progeny of EML cells grown on MC3T3 cells showed a significant increase in the percentage of CD34neg and CD34low EML cells with a concurrent significant decrease in the percentage of CD34int and CD34high EML cells compared to EML cells grown in suspension. Values shown are average shown are average ± s.d., *p value<0.05, **p value<0.01 (n=3).

EML without MC3T3EML with MC3T3

64

Figure 36. EML cells were co-cultured with MC3T3 cells for 14 days and returned to culture without MC3T3 cells for 3 and 7 days. The CD34 expression on the EML cells returned to suspension for 7 days was approaching the parental expression levels. A) Representative flow cytometry of EML cells in suspension and EML cells returned to suspension following growth with MC3T3 cells for 14 days. The CD34 expression on the EML cells returned to suspension was approaching the parental expression levels after 3 days without MC3T3 cells. B) Representative flow cytometry data and graphs of a separate experiment showing that EML cells returned to suspension for 7 days following co-culture with MC3T3 cells for 14 days are not significantly different from the progeny of parental EML cells continuously cultured without MC3T3 cells. Values shown are average ± s.d., *p value<0.05, **p value<0.01 (n=3).

EML without MC3T3EML with MC3T3

EML without MC3T3EML with MC3T3

EML without MC3T3 EML without MC3T3

EML with MC3T3- 14 days EML with MC3T3- 14 days

65

to findings in OP9 co-culture experiments, the 14 day progeny of EML cells from

MC3T3 co-cultures contained a significantly lower percentage of CD150+

cells(14.23 ± 4.20%) than the cells grown without MC3T3 cells (42.40 ± 4.77%)

(Figure 37). The expression of VEGFR1 on EML cells grown on MC3T3 cells

was reduced, although not significantly. These data indicate that EML cells in co-

culture with MC3T3 cells had significantly reduced expression of CD150, as seen

in CD34neg and CD34low subsets of EML cells.

We next investigated the cell cycle profiles of EML cells grown on MC3T3

cells. The progeny of EML cells from MC3T3 co-cultures reproducibly contained

significantly more cells in G0 phase (non-dividing) and fewer cells in S/G2/M

phase (actively dividing) as compared to EML cells grown without MC3T3 cells,

reflecting the increase in percentage of CD34neg and CD34low EML cells (Figure

38).

In the next set of experiments, purified CD34neg, CD34low, CD34int, and

CD34high EML cell subsets were co-cultured with MC3T3 cells for 14 days as

previously described. As seen with EML cells grown on OP9 cells, co-culture of

each EML cell subset with MC3T3 cells generated progeny containing higher

percentages of CD34neg and CD34low cells, as well as lower percentages of

CD34int and CD34high cells compared to subsets cultured without MC3T3 cells

(Figure 39 through Figure 43). Moreover, the CD34 cell subset content of the

parental population was not re-established by any of the cell subsets grown on

MC3T3 cells.

66

Figure 37. EML cells grown in the presence of MC3T3 cells express significantly less CD150. A) Representative flow cytometry data showing gating for data collection of 8 day progeny of EML cells from MC3T3 co-culture experiment. All cells were collected and stained for CD150 conjugated to PE-Cy7 or stained for VEGFR1 conjugated to PE. Intact EML cells were selected by FSC vs. SSC profile followed by positive for c-kit. Unstained EML cells grown on MC3T3 cells were used to set the negative gate for PE-Cy7 and PE. B) The average percentage of EML cells expressing CD150 or VEGFR1 following 14 days of suspension or co-culture with MC3T3 cells shows that there are significantly less EML cells expressing CD150 when EML cells are grown on MC3T3 cells compared to EML cells grown in suspension. Values shown are average ± s.d., *p value<0.05, **p value<0.01 (n=3).

A

B

EML without MC3T3 EML with MC3T3

EML with MC3T3 EML with MC3T3

EML without MC3T3 EML without MC3T3 EML without MC3T3 EML without MC3T3

67

Figure 38. EML cells co-cultured with MC3T3 cells contain a higher percentage of cells in the G0 phase of the cell cycle. A) Representative flow cytometry data showing gating for data collection of EML cells from the 14 day MC3T3 co-culture experiment. All cells were collected from suspension and from concurrent culture on MC3T3 cells. The collected cells were stained with Ki-67 antibody conjugated to eFluor450 followed by addition of 7-AAD. Intact EML cells were selected by FSC vs. SSC profile followed by positive for c-kit. Unstained EML cells grown on MC3T3 cells were used to set the negative gate for eFluor450 and 7-AAD. B) The average percentage of EML cells that are in each indicated stage of the cell cycle shows that EML cells grown on MC3T3 cells have a significantly higher percentage of cells in G0 than EML cells in suspension. Values shown are average ± s.d., *p value<0.05, **p value<0.01 (n=3).

A

B

EML w/out MC3T3 EML with MC3T3

EML with MC3T3

EML without MC3T3 EML without MC3T3

EML with MC3T3

68

Figure 39. The analysis of the progeny of CD34neg EML cells cultured in the absence or presence of MC3T3 cells. Purified CD34neg EML cells were split into two populations: 1) EML cells grown in suspension and 2) EML cells grown on MC3T3 cells. Every two days, cells from each population were collected and stained with CD34 antibody conjugated to APC. EML cells were selected based on FSC vs. SSC profile followed by positive for c-kit expression. Unstained CD34neg cells in suspension were used to establish the negative gate for APC. The flow cytometry data shows that when CD34neg EML cells are grown on MC3T3 cells, higher percentages of CD34neg and CD34low EML cells are maintained compared to EML cells grown in suspension, whereas CD34int and CD34high EML cells are not.

Day 0

Day 4 Day 6 Day 8 Day 14

CD34neg without MC3T3

CD34neg with MC3T3

CD34neg Post-sort

high

int

low

neg

high

int

low

neg

69

Figure 40. The analysis of the progeny of CD34low EML cells cultured in the absence or presence of MC3T3 cells. Purified CD34low EML cells were split into two populations: 1) EML cells grown in suspension and 2) EML cells grown on MC3T3 cells. Every two days, cells from each population were collected and stained with CD34 antibody conjugated to APC. EML cells were selected based on FSC vs. SSC profile followed by positive for c-kit expression. Unstained CD34low cells in suspension were used to establish the negative gate for APC. The flow cytometry data shows that when CD34low EML cells are grown on MC3T3 cells, higher percentages of CD34neg and CD34low EML cells are maintained compared to EML cells grown in suspension, whereas CD34int and CD34high EML cells are not.

Day 0

Day 4 Day 6 Day 8 Day 14

CD34low without MC3T3

CD34low with MC3T3

CD34low Post-sort

high

int

low

neg

high

int

low

neg

70

Figure 41. The analysis of the progeny of CD34int EML cells cultured in the absence or presence of MC3T3 cells. Purified CD34int EML cells were split into two populations: 1) EML cells grown in suspension and 2) EML cells grown on MC3T3 cells. Every two days, cells from each population were collected and stained with CD34 antibody conjugated to APC. EML cells were selected based on FSC vs. SSC profile followed by positive for c-kit expression. Unstained CD34int cells in suspension were used to establish the negative gate for APC. The flow cytometry data shows that when CD34lint EML cells are grown MC3T3 cells, higher percentages of CD34neg and CD34low EML cells are maintained compared to EML cells grown in suspension, whereas the percentage of CD34int and CD34high EML cells are decreased.

Day 0

Day 4 Day 6 Day 8 Day 14

CD34int without MC3T3

CD34int with MC3T3

CD34int Post-sort

high

int

low

neg

high

int

low

neg

71

Figure 42. The analysis of the progeny of CD34high EML cells cultured in the absence or presence of MC3T3 cells. Purified CD34high EML cells were split into two populations: 1) EML cells grown in suspension and 2) EML cells grown on MC3T3 cells. Every two days, cells from each population were collected and stained with CD34 antibody conjugated to APC. EML cells were selected based on FSC vs. SSC profile followed by positive for c-kit expression. Unstained CD34 high cells in suspension were used to establish the negative gate for APC. The flow cytometry data shows that when CD34 high EML cells are grown on MC3T3 cells, higher percentages of CD34neg and CD34low EML cells are maintained compared to EML cells grown in suspension, whereas the percentage of CD34int and CD34high EML cells are decreased.

Day 0

Day 4 Day 6 Day 8 Day 14

CD34high without MC3T3

CD34high with MC3T3

CD34high Post-sort

high

int

low

neg

high

int

low

neg

72

Figure 43. MC3T3 cells promote the maintenance of CD34neg and CD34low EML subsets. The increase in the percentage of CD34neg and CD34low EML subsets occurs with concurrent decline in the percentage of CD34int and CD34high EML subsets. Values shown are average ± s.d., *p value<0.05, **p value<0.01 (n=3).

Per

cen

t C

D34

neg

EM

L c

ells

P

erce

nt

CD

34 n

eg E

ML

cel

ls

Per

cen

t C

D34

neg

EM

L c

ells

P

erce

nt

CD

34 n

eg E

ML

cel

ls

CD34 high without MC3T3 CD34 high with MC3T3

CD34 int without MC3T3 CD34 int with MC3T3

CD34 low without MC3T3 CD34 low with MC3T3

CD34 neg without MC3T3 CD34 neg with MC3T3

73

These results indicate that the metastability of EML cells is attenuated by MC3T3

cells, resulting in the production and maintenance of more CD34neg and CD34low cell

subsets and reduced production and maintenance of CD34int and CD34high EML cells.

The effect of 3T3 fibroblast cells on metastability

NIH/3T3 cells are a fibroblast cell line established in 1962 from Swiss mouse embryo

tissue.148 Fibroblasts are not thought to be a component of the bone marrow niche,

hence this cell line was chosen to investigate if the effect observed is specific to BM

niche cells. NIH/3T3 cells grew well in complete EML media and, with the exception of a

small percentage of VEGFR1+ cells, did not express other HSC markers (Figure 44).

Total EML cells were co-cultured with NIH3T3 cells for 12 days as described for OP9

co-cultures. Since NIH3T3 cells do not express CD34 or c-kit, in this co-culture system

the progeny of EML cells was again analyzed by gating on c-kit+ cells (Figure 45).

These experiments have reproducibly (n=3) shown that co-culture with NIH3T3 cells

had no significant effect (p<0.05) on the production or maintenance of any EML CD34

subsets (Figure 46 and Figure 47).

74

Figure 44. NIH/3T3 cells do not express the HSC markers CD34, c-kit, CD150 or VEGFR1. Representative flow cytometry data showing that NIH/3T3 cells do not express CD34, VEGFR1, CD150 or c-kit. (n=3)

75

Figure 45. Gating strategy for selection of EML cells in co-culture with NIH/3T3 cells. The gating strategy for selection of EML cells involved selection based on FSC vs. SSC profile, followed by selection of cells that are positive for c-kit expression.

76

Figure 46. Representative flow cytometry data of CD34 expression on EML cells with and without NIH/3T3 cells. Collected cells were stained with CD34 antibody conjugated to APC and analyzed by flow cytometry. Selection of intact EML cells based on FSC vs. SSC (A) was followed by selection of c-kit positive cells (B). Unstained EML cells grown on NIH/3T3 cells were used to establish the negative gate for CD34 (C). The parental EML cells were evaluated for CD34 expression and split into two populations: 1) EML cells grown in suspension and 2) EML cells grown on NIH/3T3 cells (D). Samples were collected every two days from each population and evaluated for CD34 expression.

D

Day 0

Day 2 Day 4 Day 6 Day 8

A B C EML with NIH/3T3

EML without NIH/3T3

EML with NIH/3T3

EML without NIH/3T3

77

Figure 47. There is no significant change in the frequency of CD34 subsets when EML cells are grown in the presence of NIH/3T3 cells. EML cells grown on NIH/3T3 cells showed no significant change in all subsets of CD34 expression Values shown are average ± s.d., *p value<0.05, **p value<0.01 (n=3).

EML without NIH/3T3EML with NIH/3T3

78

Chapter 4: Conclusion and Discussion

An apparent and increasingly better characterized phenotypic and functional

heterogeneity among HSCs supports the notion that the hematopoietic system is

maintained by an increasingly complex pool of HSC subsets with distinct

phenotypic and functional characteristics8-20, 22-24, 28. More importantly, some of

these HSC subsets are inter-convertible and exist as “metastable” cell states9, 16-

18, 24, 29-33, 36, 38-43, 45, 47-50, 125. These findings are profoundly changing our

perception of the HSC pool from being a functionally uniform cell population to a

dynamic pool of multiple inter-convertible cell subsets, and are also resurrecting

the question, are the stem cells permanent cellular entities or do they exist in

several states with distinct functional features30, 43?

Studies by Chang et al. and Pina et al. have shown that EML cells reversibly

oscillate between several inter-convertible states, and analyzed certain

characteristics of EML cell metastability based on the range of expression of

HSC marker Sca-132, 36. These studies suggested that inter-convertible

metastable states of EML cells reflect either (a) slowly fluctuating transcriptomes

that may govern reversible priming and cell fate decision, or (b) the oscillation

between self-renewing and committed cell states. Based on differential

expression of CD34 marker we previously reported that EML cells reversibly

oscillate between CD34- and CD34+ metastable cell states34, 35.

In this study we (1) analyzed in depth the phenotypic and functional

characteristics and the extent of EML cell metastability, and (2) determined

79

whether and how specific types of BM niche cells affect the metastability of EML

cells.

Previous studies have clearly indicated that EML cell line is phenotypically and

functionally heterogeneous. The analysis of the expression of an array of HSC

cell surface markers on EML cells has revealed extensive phenotypic cell

heterogeneity within EML cell line, which is due to the coexistence of several cell

subsets with distinct HSC marker expression profiles. Based on the range of

expression of CD34 marker EML cells can be reproducibly divided into CD34neg,

CD34low, CD34int and CD34high cell subsets, which themselves are phenotypically

heterogeneous and exhibit distinct expression patterns of HSC markers.

The in depth analysis of multilineage differentiation potential, cell cycle profile

and proliferation kinetics of CD34neg, CD34low, CD34int and CD34high EML cell

subsets has revealed that each cell subset exhibits distinct cell cycle profile and

the propensity to differentiate into myelo-erythroid lineages.

To study the molecular differences between EML cell subsets we analyzed the

expression of (1) genes important for HSC maintenance and overall

hematopoiesis, (2) hematopoietic cell surface markers, receptors and adhesion

molecules, and (3) erythroid, megakaryocytic, myeloid and lymphoid-lineage

associated genes80, 83, 91 in CD34– and total CD34+ EML cells (containing CD34

low, CD34int and CD34high subsets). Interestingly, the microarray-based

transcriptome analysis has revealed that the hematopoietic transcriptome

signatures of EML cell subsets are quite similar and are less diverse than their

functional heterogeneity suggests.

80

Our in depth studies have revealed further rather extensive phenotypic and

functional cell heterogeneity within EML cell line, which resembles the

heterogeneity within mouse HSC pool. More importantly, our findings strongly

support the notion that EML cell line consists of several cell subsets with distinct

HSC marker expression pattern, cell cycle profile and the propensity to

differentiate.

Since the average frequency of each EML cell subset is stable throughout

multiple cell passages, we sought to determine how all EML cell subsets are

continuously maintained. These studies have reproducibly demonstrated that

each EML cell subset has the capacity to generate all other subsets and to re-

establish the parental EML cell population, while maintaining distinct phenotypic

and functional properties of each cell subset. Moreover, these studies have

clearly demonstrated that even after serial sorting and culture, each of the

serially generated EML cell subsets retained the capacity to generate all other

subsets and re-establish the parental EML cell population, while maintaining

distinct phenotypic and functional properties of each cell subset. Cumulatively,

these results strongly confirm the notion that EML cell line consists of cells

alternating between several inter-convertible and self-renewing metastable states

(Figure 48).

In summary, our results (1) strongly confirm the notion that EML cell line is

phenotypically and functionally heterogeneous, and (2) show that EML cell line

consists of distinct cell subsets that co-exist in a dynamic equilibrium and

81

Figure 48. Model showing the intrinsic metastability of EML cells. In suspension culture, EML cells are intrinsically metastable. EML cells will oscillate between CD34neg, CD34low, CD34int and CD34high expression, with the phenotypic and functional differences for each subset.

VEGFR1

G0

CD150

differentiation

proliferation

EML cells in suspension culture

82

oscillate between self-renewing and inter-convertible metastable states with

distinct phenotypic and functional features.

Within the BM, HSCs reside in at least two specialized niches: (1) an

endosteal niche, consisting of osteoblasts, mesenchymal stem cells (MSCs) and

CXCL12-abundant reticular (CAR) cells, and (2) a perivascular endothelial niche,

consisting of vascular endothelial cells, MSCs, macrophages and CAR cells. The

cellular and molecular components (adhesion proteins, secreted and membrane-

bound cytokines, chemokines, extracellular matrix components, etc.) of BM

niches comprise the so called HSC-niche synapse, which regulates HSC

survival, self-renewal, lineage priming and differentiation47, 66-70, 100-105.

Since the EML cell line is perpetually maintained in the absence of cellular and

molecular components of BM niches (with an exception of SCF)99, 105, our results

support the notion that the dynamic equilibrium of metastable EML cell subsets is

homeostatically maintained and regulated by currently unknown cell intrinsic

mechanisms.

Furthermore, the perpetual metastability of EML cells without the influence of

cellular and molecular components of BM niches points to the cell intrinsic

propensity of EML cells to be metastable.

To study the metastability of EML cells in the biological context of BM niche

components, we sought to determine whether and in what way specific types of

BM niche cells affect EML cell metastability.

The analysis of EML cell metastability in co-culture system with mesenchymal

stem cells and osteoblasts has reproducibly revealed that these niche cell types

83

do affect EML cell metastability by attenuating and shifting the metastability

towards increased production and maintenance of CD34neg and CD34low cell

subsets, and decreased production of the CD34high cell subset (Figure 49).

Additionally, the reduced amount of CD150 on the cell surface of EML cells

grown on mesenchymal stem cells and osteoblasts agrees with the fact that EML

cells grown on mesenchymal stem cells and osteoblasts have significantly more

CD34neg and CD34low EML subsets, which has been shown to express less

CD150.

The experiments designed to determine whether the changes in the

metastability of EML cells, induced by specific types of BM niche cells, are

transient or persist long-term, and are irreversible or not, have shown: (1) that the

observed effects of niche cells on EML cell metastability persist for as long as the

EML cells are in co-culture with these cells, and (2) that the effects of niche cells

on the metastability of EML cells are reversible.

More importantly, these findings infer that that a contact with and/or paracrine

signals from niche cells are responsible for affecting the EML cell metastability.

Our results are the first to show that the EML cell metastability can be influenced

by niche cells, further underscoring and emphasizing the biological relevance of

EML cell line as a unique experimental model to study the characteristics and

regulation of multipotent hematopoietic cell metastability.

Moreover, EML cell line represents a unique experimental model to (1) test the

effects of an array of different cell lines and primary cells, representing specific

types of BM niche cells (osteoblasts, mesenchymal stem cells (MSCs),

84

Figure 49. Model showing the effect of BM niche cells on EML cell metastability. Osteoblasts and mesenchymal cells attenuate the metastability of EML cells towards the production and maintenance of more CD34neg and CD34low EML cells.

G0

CD150

differentiation

proliferation

EML cells in co-culture with BM niche cells

Osteoblasts or mesenchymal cells

85

Vascular endothelial cells, CAR cells, macrophages) on metastability, and (2)

analyze the cumulative effect of several specific types of BM niche cells on the

metastability of EML cells to more appropriately mimic the BM niche

environment. In the latter case total EML cells and all four cell subsets would be

co-cultured with different combinations of niche cell types: (1) Osteoblasts +

MSCs (1:1 cell ratio; partially mimicking the composition of endosteal niche), (2)

Vascular endothelial cells (VECs) + MSCs (1:1 cell ratio; partially mimicking the

composition of perivascular niche), and (3) Osteoblasts + VECs + MSCs (1:1:1

cell ratio; partially mimicking the composition of both niches)54, 73-77, 107-112.

Lastly, our studies are providing a strong platform to (1) determine whether

the specific types of BM niche cells are affecting EML cell metastability through

direct cell-cell contact, via secreted bioactive factors (cytokines, chemokines) or

through both venues, and (2) identify molecular pathways that are involved in

cell-intrinsic and niche-mediated cell extrinsic regulation of metastability.

Since the cellular and molecular components of BM niches regulate the

survival, self-renewal and differentiation of HSCs and multipotent hematopoietic

cells30, 73-76, it is likely that they also are involved in the cell extrinsic regulation of

the metastability of HSCs and multipotent hematopoietic cells. Based on our

findings we hypothesize that under homeostatic conditions the metastability of

BM-residing HSCs is likely very attenuated, due to niche influences. Thus,

removal of HSCs from BM niches could results in increased metastability and

proliferative rate (Figure 50).

86

Metastability Figure 50. Model of HSC metastability in the BM niche. Under normal conditions the cells of the BM niche attenuate the metastability of HSCs. When the niche is perturbed, the HSCs are no longer regulated by the BM niche cells. They respond by exhibiting their intrinsic metastability in response to the insult. When the niche is recovered, the regulation exerted by the niche cells will, once again, attenuate the metastability and promote the maintenance of more quiescent HSCs.

Ost

eob

last

s an

d m

esen

chym

al c

ells

Endosteal niche

HSCs during normal conditions HSCs during niche damage

87

In addition, HSCs may increase their level of metastability after injury to BM

niches or themselves (caused by radiation, chemotherapy agents, or chronic

inflammation) 113, 114. Thus, in response to stress and damage HSCs may

become more metastable to better balance their self-renewal and differentiation.

The ability to “switch” between different inter-convertible functional states

could be enabling HSCs and multipotent hematopoietic cells in general to

respond differently to various external cues and signals from the BM niches and

other hematopoietic cells, as well as to stress, infection, inflammation, and injury

caused by radiation and chemotherapy agents.

Learning how the metastability of multipotent hematopoietic cells is regulated,

and how it can be manipulated, is of central importance for better understanding

of this fascinating cellular process. This knowledge may also provide us the

ability to alter the state of HSCs for more effective bone marrow transplant,

accelerated differentiation of HSCs post-transplant, lower or higher susceptibility

to chemotherapy, etc.

Further studies of EML cells will significantly improve our understanding of the

regulation of the metastability of multipotent hematopoietic cells, and will pave

the way for studying the characteristics and regulation of metastability of primary

HSCs. These studies also have the potential to uncover mechanisms that will

enable us to manipulate the metastability, and “push” multipotent hematopoietic

cells into specific functional states, which could be very useful in the future for ex

vivo manipulation and transplantation of HSCs.

88

In summary, this project has shown that multipotent hematopoietic EML cell

line is phenotypically and functionally heterogeneous, consisting of cells that

oscillate between different self-renewing and inter-convertible metastable states

with distinct phenotypic and functional features. Equally important, our in depth

studies have also shown that the metastability of EML cell line is homeostatically

maintained and seems to be tightly regulated by currently unknown cell intrinsic

mechanisms. Furthermore, our data have shown for the first time and also

support the notion that the heterogeneity and metastability of EML cells can be

affected and manipulated by BM niche cells in a reversible manner.

89

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