Single cell mass cytometry adapted to measurements of the cell cycle
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Single-cell mass cytometry adapted to measurements of the cell cycle. S. G2. G0/1. Cell cycle analysis by mass cytometry. Method for cell cycle analysis Markers of cell cycle phases S-phase G0 G1, G2, M Validation with cycling T Cells

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Single-cell mass cytometry adapted to measurements of the cell cycle

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Single cell mass cytometry adapted to measurements of the cell cycle

Single-cell mass cytometry adapted to measurements of the cell cycle

S

G2

G0/1


Single cell mass cytometry adapted to measurements of the cell cycle

Cell cycle analysis by mass cytometry

  • Method for cell cycle analysis

    • Markers of cell cycle phases

      • S-phase

      • G0

      • G1, G2, M

    • Validation with cycling T Cells

  • System-level analysis of cell cycle in normal and malignant hematopoiesis

    • SPADE clustering

    • 35 parameter analysis of normal bone marrow cell cycle

    • Application to hematologic malignancies


Mass cytometry dna staining

Mass cytometry DNA staining

G0

G1

(pentamethylcyclopentadienyl)-Ir(III)-dipyridophenazine

S

G2

Hoechst

IrIntercalator


Single cell mass cytometry adapted to measurements of the cell cycle

IdU incorporates rapidly into S-phase cells

Fluorescent

Cytometry

Mass Cytometry

Uridine

Uridine

56.5%

47.6%

IrIntercalator

Hoechst


Single cell mass cytometry adapted to measurements of the cell cycle

IdU incorporates rapidly into S-phase cells

Fluorescent

Cytometry

Mass Cytometry

Uridine

Uridine

56.5%

47.6%

IrIntercalator

Hoechst


Single cell mass cytometry adapted to measurements of the cell cycle

IdU incorporates rapidly into S-phase cells

0.3%

21.9%

20.6%

24.2%

No IdU

5 min

10 min

15 min

24.3%

28.9%

26.6%

IdU I127

Intercalator Ir193

30 min

60 min

120 min


Additional markers allow for complete cell cycle state assignment

Additional markers allow for complete cell cycle state assignment

p-histone H3

-Andrew Hughes, Gene TherMol Biol., 2006; 10:41


Additional markers allow for complete cell cycle state assignment1

Additional markers allow for complete cell cycle state assignment

p-histone H3

p-Rb (S807/S811)

G0

Uridine


Additional markers allow for complete cell cycle state assignment2

Additional markers allow for complete cell cycle state assignment

G2

p-histone H3

p-histone H3

S

Cyclin B1

G0/G1

Uridine


Additional markers allow for complete cell cycle state assignment3

Additional markers allow for complete cell cycle state assignment

p-histone H3

p-histone H3

M

p-Histone H3 (S28)

Uridine


Single cell mass cytometry adapted to measurements of the cell cycle

Cell cycle assessment is robust and consistent across multiple cell types

human T cells

U937 cells

HL60 cells

NALM6 cells

A

G0

IdU I127

p-Rb Ho165

B

S

IdU I127

Cyclin B1 Dy164

G0/G1

G2/M

C

M

IdU I127

p-Histone H3 Er168


Single cell mass cytometry adapted to measurements of the cell cycle

Cell cycle assessment is robust and consistent across multiple cell types

human T cells

U937 cells

HL60 cells

NALM6 cells

A

G0

IdU I127

p-Rb Ho165

B

S

IdU I127

Cyclin B1 Dy164

G0/G1

G2/M

C

M

IdU I127

p-Histone H3 Er168


Single cell mass cytometry adapted to measurements of the cell cycle

Phosphorylated Rb (S807/S811) discriminates G0 and G1 phase cells

C

A

23.8%

Pyronin Y

Pyronin Y

76.3%

Hoechst

IdU FITC

B

D

27.6%

24.4%

p-RbAlexa 647

p-RbAlexa 647

p-Rb Ho165

p-Rb Ho165

75.6%

72.3%

IdU I127

Hoechst

IdU FITC

Intercalator Ir193


The same cell cycle markers can be used for fluorescence cytometry

The same cell cycle markers can be used for fluorescence cytometry

Fluorescence Cytometry

S

G0

Mass Cytometry

IdU

G0

S

IdU

G2/M

G0/G1

pRb

Cyclin B1

G2/M

G0/G1

S

pRb

Cyclin B1

Pyronin Y

IdU

G0

G0/G1

G2/M

Hoechst

Hoechst


Mass cytometry cell cycle analysis is equivalent to fluorescent methodologies

Mass cytometry cell cycle analysis is equivalent to fluorescent methodologies

Fluorescent cytometry

Mass cytometry

0h

28h

48h


Mass cytometry cell cycle analysis is equivalent to fluorescent methodologies1

Mass cytometry cell cycle analysis is equivalent to fluorescent methodologies

Fluorescent cytometry

Mass cytometry

0h

28h

48h


Mass cytometry cell cycle analysis is equivalent to fluorescent methodologies2

Mass cytometry cell cycle analysis is equivalent to fluorescent methodologies

Fluorescent cytometry

Mass cytometry

0h

28h

48h


Mass cytometry cell cycle analysis is equivalent to fluorescent methodologies3

Mass cytometry cell cycle analysis is equivalent to fluorescent methodologies

0h

28h

48h


Single cell mass cytometry adapted to measurements of the cell cycle

Cell cycle analysis by mass cytometry

  • Method for cell cycle analysis

    • Markers of cell cycle phases

      • S-phase

      • G0

      • G1, G2, M

    • Validation with cycling T Cells

  • System-level analysis of cell cycle in normal and malignant hematopoiesis

    • SPADE clustering

    • 35 parameter analysis of normal bone marrow cell cycle

    • Application to hematologic malignancies


Panel for analysis of cell cycle in human marrow

Panel for analysis of cell cycle in human marrow


Biaxial plots are not a scalable solution

Biaxial plots are not a scalable solution

Parameters:

4

8

14

32

Plots:

6

28

91

496

Sean Bendall, Erin Simonds. Science,May 2011


Spade spanning tree progression analysis of density normalized events peng qiu

SPADE: Spanning-tree Progression Analysis of Density-normalized Events – Peng Qiu

  • Determine Tree Structure

  • Overlay regions with surface marker expression levels


Spade clustering of normal bone marrow mirrors immunophenotypic differentiation

SPADE clustering of normal bone marrow mirrors immunophenotypic differentiation.

CD45


Spade clustering of normal bone marrow mirrors immunophenotypic differentiation1

SPADE clustering of normal bone marrow mirrors immunophenotypic differentiation.

NK

Naïve CD8 T

Naïve CD4 T

CD4 T

NKT

CD8 T

CD45

CD3


Spade clustering of normal bone marrow mirrors immunophenotypic differentiation2

SPADE clustering of normal bone marrow mirrors immunophenotypic differentiation.

Myeloblasts

CD45

CMP

Myelocytes

Late

Early

Promyelocytes

CD15

Meta-myelocytes

Mature

Myeloid


Spade clustering of normal bone marrow mirrors immunophenotypic differentiation3

SPADE clustering of normal bone marrow mirrors immunophenotypic differentiation.

Mature Monocytes

Early

Monocytes

Macrophages

Pro-monocytes

PC-DCs

Monoblasts

CD45

CD14


Spade clustering of normal bone marrow mirrors immunophenotypic differentiation4

SPADE clustering of normal bone marrow mirrors immunophenotypic differentiation.

CD45

Pre-BI

Pre-BII

Pro-B

Immature

B cells

Plasma

Mature B cells

CD20


Spade clustering of normal bone marrow mirrors immunophenotypic differentiation5

SPADE clustering of normal bone marrow mirrors immunophenotypic differentiation.

MEP

CD45

Pro-erythroblasts

Erythroblasts

Nucleated

RBCs

CD235


Spade clustering of normal bone marrow mirrors immunophenotypic differentiation6

SPADE clustering of normal bone marrow mirrors immunophenotypic differentiation.

Vasc. Progen?

MPP

HSC

MEP

GMP

Monoblasts

Myeloblasts

CD45

Pre-BI

CMP

Pro-erythroblasts

Pro-B

CD34


Spade clustering of normal bone marrow mirrors immunophenotypic differentiation7

SPADE clustering of normal bone marrow mirrors immunophenotypic differentiation.

Vasc. Progen?

NK

Mature Monocytes

MPP

Naïve CD8 T

HSC

Naïve CD4 T

Early

Monocytes

CD4 T

Macrophages

MEP

NKT

Pro-monocytes

CD8 T

GMP

PC-DCs

Monoblasts

CD45

Myeloblasts

Pre-BI

Pre-BII

CMP

Pro-erythroblasts

Pro-B

Erythroblasts

Immature

B cells

Plasma

Myelocytes

Nucleated

RBCs

Mature B cells

Late

Early

Promyelocytes

Meta-myelocytes

Mature

Myeloid


B cell proliferation is concentrated in pre bii population

B cell proliferation is concentrated in pre-BII population

G1

CD34

Pro-B

CD10

Pre-BI

S

Pre-BII

CD19

G2

Normal Human Bone Marrow

Colored for CD45

CD20

= 200 Cells

= 67%

Mature B


Erythroid cell proliferation is concentrated in erythroblast population

Erythroid cell proliferation is concentrated in erythroblast population

MEP

Pro-

erythro-

blast

Nucleated

RBC

Erythro-

blast

CD34

CD71

CD235

Normal Human Bone Marrow

Colored for CD45

= 200 Cells

G1

S

G2

= 67%


Myelocyte proliferation peaks at early promyelocyte stage

Myelocyte proliferation peaks at early promyelocyte stage

Late

Promyelo-

cytes

Early

Promyelo-

cytes

G1

CD11b

Myelocyte

Metamyelocyte

S

CD15

Normal Human Bone Marrow

Colored for CD45

Mature

myelocyte

= 3500 Cells

= 67%

G2

CD16


Spade analysis allows for identification of distinct aml immunophenotypes

SPADE analysis allows for identification of distinct AML immunophenotypes

HSC /

Early Progenitor

Mature Monocytic

Promyelocyte /

Myelocyte

Promonocyte

Mature Myeloid

?Pro-B /

Pre-B

Myleo/mono-

blast

NK Cell

T Cell

B Cell

Normal human bone marrow

Clustered alongside AML samples

Colored for CD45


Cell cycle distribution varies across the immunophenotypic subsets within each aml sample

Cell cycle distribution varies across the immunophenotypic subsets within each AML sample

AML5

AML9

CD34

S

= 20%


Conclusions

Conclusions

  • Validated methodology for using mass cytometry to asses cell cycle state in combination with high-parameter immunophenotypic analysis

  • System-wide analysis of proliferation across normal human hematopoiesis

  • The ability to combine cell cycle state with multiple other variables in the monitoring of cellular responses at the single-cell level

  • We intend to use this methodology to characterize the cell cycle within complex human cancer samples


Acknowledgements

Acknowledgements

  • Nolan Lab

    • Garry Nolan

    • Wendy Fantl

    • Sean Bendall

    • Erin Simmonds

    • Rachel Fink

    • Matt Clutter

    • Angelica Trejo

    • Matt Hale

  • Stanford

    • Michael Linderman

    • Sylvia Plevritis

  • MD Anderson

    • Peng Qiu

  • Hematology

    • Bruno Medeiros

    • Peter Greenberg

    • Beverly Mitchell

      • AparnaRaval

  • Cytobank

    • NikeshKotecha


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