multiplexed cellular analysis - aacc

Sean Bendall Department of Pathology

Stanford University

AACC ChicagoOct. 2, 2015

MassivelyMultiplexed Cellular

Analysis

Learning Objectives

• Understand the challenges and opportunities for single cell analysis in human pathobiology

• The use of elemental mass spectrometry in highly multiplexed cellular measurements

• Single cell mass spectrometry can be ‘routinely’ applied in the hematopoietic immune system

• ‘Single cell signatures’ can be used to predict disease outcome

• Multi-parameter subcellular imaging – watch out!

• Accessing most interesting cell types is costly (Parameters)

Parameters are the currency of single cell analysis:

• Leaves little room for the measurement of “cellular behavior”

• Major consideration for precious (clinical) samples and rare event analysis

How do we get more parameters?

Adding more parameters to bioanalysis

Fluorescence

• Up to 12 colors can be “routine”• 17 colors have been reported• High background

Elemental Isotopes

• > 100 non-biological elemental mass channels

• No compensation required• Zero background

140 145 150 155 160 165 170 175Isotopic mass (Da)

100 -

90 -

80 -

70 -

60 -

50 -

40 -

30 -

20 -

10 -

0 -

How do you get > 50 parameters?

Europium “152” is actually a 50/50 mix of 151Eu and 153Eu

Each vertical bar in these elements is a different isotope that can be separately measured

Measureby TOF

Mass cytometry enables single-cell proteomics

Stimulatecells in vitro

Crosslinkproteins

Stain with isotope tagged Abs

Nebulize single-celldroplets

Ionize(7500K)

Permeabilizecell membrane

Isotopically enriched

lanthanide ions (+3)

x 6 polymers= 180 atoms per antibody

30-site chelating polymer

• Metal tags instead of fluorescence

• 38 commercial Abparameters

• Up to 42 Ab parameters with optimization

A Rh or Ir based metalointercalator is a cellular indicator signal and yields DNA content information

Mass Cytometry ReagentsHow do we track cellular events?

Ornatsky O, et al. Anal Chem. 2008

Fresh PBMc stained with 27 markers (mix I):

Lymp B

Lymp CD4+T CD2 CD3 CD4CD45

CD45RA; CD20; CD45; CD38; CD19; CD40 CD49dCD71

CD2 175LuCD3 152SmCD4 142NdCD7 139LaCD8 146NdCD10 168ErCD11b 158Gd

CD13 166ErCD15 170ErCD19 171YbCD20 156GdCD31 144NdCD33 141PrCD34 169Tm

CD36 150NdCD38 165HoCD40 172YbCD44 151EuCD45 159TbCD45RA 153EuCD49d 145Nd

CD56 176YbCD64 148NdCD71 167ErCD90 174YbCD117 147SmHLA-DR 160Gd

Be careful what you wish for…

“seeing” single cell information in 30+ dimensions?

Biaxial plots are not a scalable solution

Parameters: 32Plots: 496

Can we create 2D maps representing higher dimensional data?

Deep Profiling of the Human

Hematopoietic Immune System

Bendall & Simonds et al., Science 2011.

Experimental design: Human bone marrow signaling

CD45CD3CD4CD8CD34CD19CD20CD33CD11bCD123

SPADE projects bone marrow as a continuum of phenotypes

0 100Intensity (%max)


pSTAT5

0 100Intensity (%max)

Rediscovery of canonical signaling pathwaysBasal IL-7


Clinical recovery from surgery

correlates with single-cell immune

signatures

Gaudilliere and Fragiadakis et al., Sci Transl Med, 2014

CyTOF enables a systems-level view with single-cell resolution

4. Normalization

Before normalization

After normalization

Sig

nal I

nten

sity

Time

BL 1h 24h72h1mo

1. Barcoding 3. CyTOF

Mass

Tim

e

21 Surface Markers

12 Functional Markers

2. Antibody Staining

Tim

e

5. De-barcoding

Minimum separation

Cel

l cou

nt

6. Analysis


Trauma induces a redistribution of cell subsets in the blood

Gaudilliere and Fragiadakis et. al, Sci Transl Med, 2014

Surgery induces time-dependent and cell-type specific activation of immune signaling networks

1h 24h 72h 1mo -1 10

arcsinh ratio over baseline


Patient n

...

Patient 2

% Pop. A

Patient 1

% Pop. B

Group 1Group 2

Group 1

Group 2

Pop. Characterization Endpoint Association

Cell 1Cell 2 .. ..Cell n

Patient 1

Raw Data

A

B

Pop. Identification

Citrus: A Data-Driven Method for the Identification of Stratifying Cellular Subsets

Prop p...

Patient 2

Prop 1

Patient 1

...

Patient n

Prop 2

Subset CharacterizationSubset Identification

Endpoint

Regularized Model

Group 1

Group 2

Group 2

...

Regularized Regression

G1 G2

Cluster Phenotype

Predictive Features

Stratifying Subsets

Bruggner et. al, PNAS, 2014

• Automatically identify cell subsets

• Calculate properties of clusters on per-sample basis

• Create regularized regression model of experimental endpoint

• Predictive features in model correspond to stratifying clusters and properties

Signaling responses in CD14+ monocyte subsets correlate with surgical recovery


What about phenotype vs.

function in disease?

i.e. AML

Single Cell Proteomic AML Analysis Pipeline

Levine, Simonds & Bendall et al. Cell 2015

Phenograph – a graph-based single cell method for identifying high dimensional ‘neighborhoods’


In ‘Healthy’ – Conserved Phenotypes Have Conserved Signaling Behavior

Levine, Simonds & Bendall et al. Cell In Press

Partition Cells by Function Instead of Phenotype

In AML – A Disconnect Between Cell Phenotype & Signaling Behavior Exists


The Frequency of Inferred Functionally Primitive Cells (IFPC) Can Identify a Corresponding Gene

Expression Signature

Levine, Simonds & Bendall et al. Cell In Press

The IFPC Gene Signature Predicts AML Survival in Two Independent Cohorts

Better than previously identified signatures in these and related studies


Mapping pluripotent stem cell differentiation and de-differentiation• Zunder E et al. Cell Stem Cell 2015• Lujan E et al. Nature 2015

Massive Immune Monitoring and Discovery –• Spitzer MH et al. , Science 2015• Brodin P et al. Cell 2015

Single Cell Clinical Biomarkers and predictive medicine• Gaudillière B et al. Science Trans. Med. 2014

Antigen specific T cell Responses• Newell et al . Nature Biotech 2014• Newell et al. Immunity 2011

Computational Challenges and Opportunities in Single Cell Biology• Shekhar K. et al. PNAS 2014• Qiu P et al. Nature Biotech 2012• Other papers above

Immune Cell Diversity• Strauss-Albee DM et al. Science Trans. Med. 2015• Horowitz A et al. Science Trans. Med. 2013

Other Notable Mass Cytometry Applications

in Cell Biology

There is a lot of room left in the Mass Cytometry analysis space….

103 198

Now 38

6 x PdBarcoding I = IdU

S‐Phase Pt = CisplatingViability

203,05,09

In‐113/15

“Single-cell suspensions not

required”

Viewing the future of high dimensional imaging?Using lanthanide ‘mass reporters’

Giesen Nature Methods, 2014

Angelo Nature Medicine, 2014


MIBI – multiplexed ionbeam imaging


dsDNAH&E

10-D Simultaneous

Imaging of Ductal Breast

Carcinoma

ER+, PR+, Her2+ ER+, PR+, Her2-Clinical Path:

Marker


multiplexed cellular analysis - aacc

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