Using Flow Cytometry to Speed Determination of Eukaryotic Genome Sizes and Cell Type-Specific Gene Expression

Using Flow Cytometry to Speed Determination of Eukaryotic

Genome Sizes and Cell Type-Specific Gene Expression

Broadcast Date: Wednesday, February 1, 2012

Time: 1:00 pm EST, 10:00 am PST

Sponsored by

Using Flow Cytometry to Speed Determination of

Eukaryotic Genome Sizes and Cell Type-Specific

Gene Expression



Your Moderator

Tamlyn Oliver Managing Editor

Genetic Engineering & Biotechnology News



David Galbraith, Ph.D. Professor

BIO5 Institute and School of Plant Sciences

University of Arizona

Using Flow Cytometry to Speed Determination of Eukaryotic Genome Sizes and Cell Type-Specific Gene Expression

Technical aspects of flow analysis and sorting in plants

http://cba.musc.edu/flowcytometry

Dealing with Multicellular Tissues in Flow Cytometry

• How to fit a plant through a flow tip?

70 μm

B A

C D

Make protoplasts (single cells lacking a cell wall)

DNA flow histogram of fixed tobacco leaf protoplasts. Poor CV due to uneven illumination within the flow stream.

CRBC

CV ~7-10%

DNA flow histogram of tobacco nuclei released from lysed leaf protoplasts. Improved CV since nuclei are more evenly illuminated.

CRBC

CV ~3.5%

Problem with this approach: • Protoplasts are not easy to prepare. Some species and

organs cannot be made into protoplasts.

Simple solution: release nuclei by “chopping”

Method for DNA content and ploidy estimation 1. Select tissue of interest. 2. Place tissue in petri dish, in cold “chopping” medium. 3. Chop tissue using a single-edge razor blade, for approximately 1 min. 4. Filter tissue through nylon mesh (pore size 15-50 μm). 5. Add appropriate fluorochrome to desired concentration. 6. Analyze fluorescence emission using flow cytometry.

Galbraith et al., Science 220:1049-1052 (1983)

A. DNA flow histogram of a chopped tobacco leaf.

B. DNA flow histogram of a chopped arabidopsis leaf.

B

CV ~3.5%

Applications of the chopping technology

Genome size measurements for essentially all plant species and tissue/organ types. Characterization of natural and agricultural populations: ploidy screening and identification of distributions. Ecology and crop improvement. Identification of aneuploidy. Characterization of unsuspected phenomena (for example, somatic endoreduplication). Molecular and cellular biology of the nucleus (more later).

DAPI Fluorescence (log)

0 200 400 600 800

Num

ber

of N

ucle

i

0

1000

2000

3000

4000

Chopping can be used with animal tissues and organs

This includes insects and nematodes, as well as mammalian species.

Brain

nuclei

Extending genome size observations to the entire angiosperms

We estimate about 500,000 species of flowering plants in the world. Approximately 15,000 species are becoming extinct per year due to anthropogenic change. Some of these will be plant species, and some will be as yet undescribed. Approximately 2% of known species have a minimal basal molecular description. There is a need for a global molecular census of the angiosperms.

A global inventory of flowering plants

Start with Genome Size Measurements: Fundamental to our understanding of eukaryotic species. Limited information available in the RBG Kew C-value database (~1-2% of angiosperms). Flow cytometry is ideal for measurements of this type, and can be extended to all 600,000 species. Problem of large dynamic range of C values.

Gregory TR (2005). Ann. Bot. 95:133-146.

The Accuri C6 Portable Flow Cytometer

• Two lasers. • No user adjustments. • 24-bit ADC. • No pressurized sheath.

Dynamic range of the Accuri flow

cytometer (1.9 x 107 bins) is greater

than this range of DNA content values

FL2-A (x 10-5)

0 5 10 15

Nu

mb

er

of N

ucle

i

0

200

400

600

800

FL2-A

102 103 104 105 106

FL

3-A

103

104

105

106

P (1.8%)

A B

FIGURE 1

Gated on Region P

Pisum sativum

FL2-A

103 104 105 106

FL3-A

105

106

B

FL2-A

103 104 105 106

FL3-A

105

106

P1 1.8%

P1 1.2%

FL2-A

102 103 104 105 106

103

104

105

106

A

FL2-A

Nu

mb

er

of n

ucle

i

0

250

500

750

104

105

C

E

FL2-A

102 103 104 105 106

FL3-A

103

104

105

106

D

104

105

Gated on P1

FL2-AN

um

be

r o

f n

ucle

i

0

250

500

750

F

Gated on P1

FIGURE 2

R1

R1

Arabidopsis thaliana

FL2-A

104 105 106 107

FL3-A

104

105

106

107

B

P2 4.3%

FL2-A

102 103 104 105 106

103

104

105

106

A

FL2-A (x 10-6) FL2-A

105 106

2C

DN

A C

onte

nt (p

g)

2C

DN

A C

onte

nt (p

g)

FL3-A

D Er2 = 0.999r

2 = 0.999

FIGURE 3

0.0 1.0 2.0 3.0

0

20

40

60

80

FL2-A

Num

ber

of nucle

i

0

250

500

750

104

105

CGated on P2

106

107

At (2C)

At (4C)

At (8C)

Ps (2C)

Ta (2C)

Aa (2C)

R2

At (2C-8C) Ps (2C)

Ta (2C)

Aa (2C)

At (2C)

At (4C)

Ps (2C)

At (8C)

Ta (2C)

Aa (2C)

1

10

100 At: Arabidopsis thaliana

Ps: Pisum sativum

Ta: Triticum aestevum

Aa: Alstroemeria aurea

• The smallest reported angiosperm genome size is that of Genlisea margaretae (Lentibulariaceae), having a 2C value of 0.129 pg. The largest currently measured is that of Paris japonica (Melanthiaceae) with a 2C value of 304.46 pg, representing a genome of ~150 billion base pairs.

• This is still smaller than the dynamic range measurable using the Accuri C6.

Spanning the Angiosperms

• ~500,000 species.

• 30 machines.

• 8 samples / hr; 40 hrs/week

• Only 52 weeks total time required for analysis of all species…

• Collection and availability of local taxonomic expertise will

clearly be problems.

Throughput and Time-Frame

Where does this lead us?

• Availability of the C6 means we are no longer limited in our technological ability to access a complete description of genome sizes for flowering plants.

• Simple technologies (GPS-enabled cell phones with cameras) allows linking of samples and locations.

• This would be followed by NextGen and Gen3 sequencing to describe each of these samples, starting at low coverage.

Flow Sorting in Plants Given the ability to make suspensions of nuclei, we can now think about experiments involving sorting.

• Analysis of cell type-specific gene expression.

Nuclear Genome

mRNA

Translation

Degradation

Stages in Gene Expression

Poly A+ RNA sampling

mRNA

Translation

Degradation

Nuclear Genome

Analysis of gene expression is typically done by sampling total cellular polyA+ RNA, which estimates the steady state concentration within the cell.

We are looking at transcripts in the nucleus of specific cell types

(Nuclear Transcriptomics) • Zhang et al. (2005): Cell type-specific

characterization of nuclear DNA contents within complex tissues and organs. Plant Methods 2005, 1:7 doi:10.1186/1746-4811-1-7.

• Zhang et al. (2008). Characterization of cell-specific gene expression through fluorescence-activated sorting of nuclei. Plant Physiology 147:30-40.

HTA6 GFP

Strategy:

Nuclear GFP targeting achieved by fusing GFP to histones.

pSUL2-1::HTA6:GFP (phloem CCs)

pSCR::HTA6:GFP (endodermis)

Cell type-specific labeling of nuclei

Wild Type

2C 4C 8C 16C

DNA

content

GF

P flu

ore

scence

p35S

GF

P flu

ore

scence

DNA

content

GF

P flu

ore

scence

p35S

The C6 is very

useful for

identification of

suitable transgenic

plants, since

screening is very

rapid.

Col-0

pRPL16B

pSCR

A B

C

E F

p35S

pSultr 2-1

pSHR D

Transcriptomics using sorted nuclei

A

C

B

D

E

• Transcripts were amplified from GFP-positive nuclei sorted from phloem companion cell homogenates

• Microarrays were hybridized and genes identified whose transcripts were up (0.2% of total) by factors of two-fold or more (P-value < 0.01).

• We selected the top 12 genes, and employed the 5’-regions for regulating GFP expression in transgenic plants.

A

C

B

D

E • All 12 showed phloem- or vascular-

specific GFP expression.

Transcriptomics using sorted nuclei

NPCC4 NPCC3

NPCC6 NPCC5

NPCC2 NPCC1 NPCC7

NPCC12

NPCC10 NPCC9

NPCC11

NPCC8

How does this compare to “conventional” transcriptomics?

Transcript levels estimated from nuclei are broadly concordant with those estimated from protoplasts. Our results using nuclei agree with those of other groups using sorted protoplasts.

Birnbaum et al. (2003). Science 302:1956-1960.

Is this approach applicable to animal systems? Flow sorting of specific cell types, labeled through FP expression is a widely used technology. Identification of different cell types in complex tissues can be simple, but preparation of single cells can be very difficult (cf. the CNS). Sorting nuclei would get around this problem, and we can use histone-GFP fusions to label these nuclei.

(1) Confocal image of live HeLa cells constitutively expressing Histone 2B–GFP. GFP fluorescence (green) was overlaid onto a differential interference contrast image. H2B-GFP is detected in cells at all phases of the cell cycle. H2B-GFP is contained solely in the nucleus.

Image courtesy K. Sullivan

Does the spectrum of RNA transcripts of animal nuclei correlate with that of the cytoplasm?

Barthelson et al. (2007).

HepG2 cells grown in culture. Analysis and FACS sorting of DAPI-stained nuclei. Isolation of polyA+ RNA. Comparison of expression profiles between cells and nuclei using microarrays.

Expression profiling using mammalian nuclei

Conclusions • The nucleus is a valuable source of important

information in eukaryotic organisms.

• The BD Accuri C6 flow cytometer provides unique features that make it particularly suitable for analyzing nuclei.

• The type of information that can be obtained using this instrument will be of profound significance in the future of scientific research in this area.

Using Flow Cytometry to Speed Determination of Eukaryotic Genome Sizes and Cell Type-Specific Gene Expression

Technical aspects of flow analysis and sorting in plants



Chuck Cannon, Ph.D. Associate Professor

Texas Tech University

Professor, Xishuangbanna Tropical Botanic Garden

Chinese Academy of Sciences



Clare Rogers Senior Marketing Applications Specialist

BD Biosciences-Cell Analysis

For Research Use Only. Not for use in diagnostic or therapeutic procedures.

The BD Accuri® C6 flow cytometer

• Overview of the system

• Ease of use attributes

• DNA analysis-specific attributes

• QC tools for DNA analysis

• Data Analysis

The BD Accuri C6 flow cytometer

An affordable, full-featured, easy-to-use flow cytometer

Two lasers and six detectors

The BD Accuri C6 flow cytometer

Innovations in all the major components of a flow cytometer

• Fluidics: Peristaltic pumps and pulse dampeners allow miniaturization

and direct-volume measurement

• Optics: locked-down alignment

• Signal detection: broad dynamic range obviates voltage adjustments

• Software: developed by “high tech anthropologists” trained to facilitate

human-computer interactions

Fluidics

• Laminar flow fluidics

• Non-pressurized, peristaltic pump-

driven system

• Patented pulse dampeners

• User controls both flow rate and core

diameter

• Volume measurement for absolute

counts

• Minimum sample volume 50 µL if using

a 1.5 mL conical tube

• Up to 10,000 events/second

Sheath

Purge

Waste

Flow Cell Laser

Sa

mp

le

Dete

cto

r

FSC

SSC

488 nm

solid state laser

640 nm diode laser

PMTs for fluorescence

Detection

Diodes for scatter

detection

Compact optical system

design reduces cost and

eliminates alignment issues

510/15

540/20

565/20

610/20

780/60

3 blue 1 red

2 blue 2 red

4 blue

User changeable

optical filters

Selectable Lasers

Alignment and signal detection are optimized and

locked down at manufacture


Instrument-to-instrument variation is minimal

8-peak data, multiple C6 instruments manufactured over a six-

month period.


Instrument set-up is simplified

• Power on

• Water – Bleach – Water

• Validate with beads


High Tech Anthropology: Menlo Innovations

National Oceanic and Atmospheric Administration:

Great Lakes Microcystis research project – Lake Erie

The Ecosystem Centre:

Palmer Peninsula, Antarctica

A Robust and Portable Tool for Challenging Environments

2nd Norwich Flow Day:

Institute for Food Research


BD Accuri C6 functionalities for DNA analysis

• Particle rate control: adjustable fluidics

• Threshold on any parameter: light scatter or fluorescence

o Primary and secondary thresholds allowed

• Area versus Height for aggregate exclusion (all parameters)

• Linear response across the broad dynamic range

• Virtual Gain tool to compensate for sample-to-sample

staining variation


BD DNA QC Particles kit for performance validation

The chicken erythroid nuclei (CEN) preparation will contain singlets,

doublets, triplets, and other aggregates which allow one to check

instrument linearity and resolution.

Singlet Peak

CV = 2.5%

PI FL2-A

CEN

2.0

3.0

4.0 4.9

5.9

6.9


BD DNA QC Particles kit for performance validation

The calf thymus nuclei (CTN) preparation allows one to check the doublet

discrimination ability of the C6 using an Area versus Height plot and to check

resolution for a cycling population

PI FL2-A

PI F

L2-H

Singlet gating

PI FL2-A

CTN

ModFit LT™

as well


FCS Express:

Multicycle FlowJo

Original

BD Accuri

Data

Popular cell cycle analysis software packages can

analyze BD Accuri data files





Q&A



Your Moderator

Tamlyn Oliver Managing Editor

Genetic Engineering & Biotechnology News



David Galbraith, Ph.D. Professor

BIO5 Institute and School of Plant Sciences

University of Arizona



Chuck Cannon, Ph.D. Associate Professor

Texas Tech University

Professor, Xishuangbanna Tropical Botanic Garden

Chinese Academy of Sciences



Clare Rogers Senior Marketing Applications Specialist

BD Biosciences-Cell Analysis



Thank You For Attending

Using Flow Cytometry to Speed Determination of

Eukaryotic Genome Sizes and Cell Type-Specific

Gene Expression

Broadcast Date: Wednesday, February 1, 2012

Time: 1:00 pm EST, 10:00 am PST

Sponsored by

Documents

Using Flow Cytometry to Speed Determination of Eukaryotic Genome Sizes and Cell Type-Specific Gene Expression