Tracking expression one cell at a time

Why do single cell analysis?

Limited Sample

Cellular Complexity

Cellular Heterogeneity

Fluidigm is different

Who wants to be average?

Many cells

Multiple genes

Quality

Flexibility

Throughput

Time

Cost

Technology

Workflow

Stories

Technology

96.96 48.48

9,216 2,304

Dynamic Array IFCs

Architecture

Nanoflex valve open

Fluid Line

Control Line

Nanoflex valve closed

Fluid Line

Fluid Line

Control Line

Cells

RT-TSA

Chip

Data

Workflow

FACS into 10 μL CellsDirect™ master mix

18 cycles

Gene expression analysis

One step RT-TSA

Transcript Specific Amplification

48/96 assay mix0.2x

PreAmp master mixSingle cell

18 cycles

Preamplified cDNA

1:5 dilution

+ +

BioMark™ has excellent correlation with the 7900

BioMark system

ABI 7900

r= 0.99

Workflow is fast and easy

Pipette Load PCR

20 mins 55/90 mins 90 mins

Sample Protocol

Vol/ sample Total VolμL μL

2x master mix 2.50 120Loading reagent 0.25 12Preamp cDNA 2.25 -Total 5

Assay Protocol

Vol/ sampleVol/ sampleμL

20x primer probe 2.5Loading reagent 2.5Total 5

Customer Stories

Targeting Pathways to Critical Cancer Stem CellsOncomed

How does BioMark perform on single cells?

48 Samples

Assays x 5Ct

Expression of 3 genes from a single cell

GSS

β Actin

MALAT1

Δ RN

Cycle

Standard Curves

Ct

pg RNA

R2= 0.99

GSSβ Actin

R2= 0.99

Correlation between RNA and cell number

RNA (pg)

β Actin

GSS

R2= 0.999

R2= 0.999

Number of cells

Single cells from pancreatic a tumour

Ct

High population

Gene assays (x3)

Low population

Ct

High population Low population

Gene 13

Cell number

Gene 2GAPDH

7900

Master mix 184 mlPrimer/probe 18 ml384 well plates 96Time 24 days

384 samples x 96 genes

Master mix 960 μlPrimer/probe 960 μl96.96 chips 4Time 1 day

384 samples x 96 genes

Resolution of cell fate decisions by Single-Cell Gene Expression Analysis from Zygote to Blastocyst

Guo, G. et al. (2010) Developmental Cell.18, 765

Resolution of cell fate decisions

BlastocystMorula8 cell4 cell2 cellZygote

NucleusInner cell mass

(ICM)

Trophectoderm (TE)

ICMPrimitive endoderm (PE)

Epiblast (EPI)

Analysis of individual single cells from blastocysts

Defining cells by gene expression patterns

Developmental progression to 3 blastocyst cell types

Developmental decisions are made at the cellular level

Decisions are affected by expression of multiple genes

How did BioMark enable this study?

Many genes in parallel

Single cell resolution over time

Multiple genes = accurate view of cellular phenotype

Parthenogenic Blastocysts Derived from Cumulus-Free In Vitro Matured Human Oocytes

McElroy, S.L. et al. (2010)PloS. 5, e10979

Natural vs. IVF

Expression of patterns ovarian factors and receptors

Calculated normalised relative quantity

Receptor

Ligand

Expression of patterns ovarian factors and receptors

Receptor

Ligand

Nuclear maturation of cumulus-free oocytes

Culture media No. of oocytes 24 h 48 h

IVM 46 41.5 50.0

SAGE 45 48.9 68.9

Supplement 98 45.9 54.1

IVM 29 72.4 75.9

SAGE 42 88.1 88.1

Supplement 51 94.1 94.1

GV: germinal vesicleMI: metaphase IVM medium + 10% SPSSAGE: IVM medium + 10% SPS, FSH, hCG, estradiolSupplement: IVM medium + 10% SPS, BDNF, estradiol, IGF-1, GDNF, FGF2, leptin

Nuclear maturation rate (%)

MI

GV

GAPDH expression in single cells

0

5

10

15

20

9 10 11 12 13 14 15 16 17

Population 1 Population 2

Number of cells

Ct