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Bacteria and flow cytometry:From enumeration to community structure and

ecological function

Josep M GasolJosep M GasolInstitut de Ciències del MarInstitut de Ciències del Mar--CSICCSIC

Barcelona, Catalunya, SpainBarcelona, Catalunya, Spain

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Bacteria and flow cytometry

• Introduction• Using the structure or the pigments• Staining the DNA• Dealing with concentrated solutions• Measuring size and biomass (protein content)• Determining bacterial activity structure• Linking community structure to function:

cell sorting and molecular determinationscell sorting and activity measurescell sorting and cell isolation

• other applications relevant to marine science...

•• bacteria play far more important ecological roles in naturalbacteria play far more important ecological roles in naturalenvironments than their small sizes would suggest (Brock et environments than their small sizes would suggest (Brock et al.’88) al.’88)

• “L’essentiel est invisible pour les yeux” (Antoine de Saint• “L’essentiel est invisible pour les yeux” (Antoine de Saint--Exupéry)Exupéry)• “small is beautiful !”• “small is beautiful !”

•• Most of Earth’s living biomassMost of Earth’s living biomass• Most abundant living particles in the sea• Most abundant living particles in the sea• Only significant DOM transformers • Only significant DOM transformers • Responsible for most of ocean’s respiration• Responsible for most of ocean’s respiration• Largest living surface in the ocean• Largest living surface in the ocean

• The largest “unknown pool” of genomic and • The largest “unknown pool” of genomic and metabolic (i.e. functional) diversitymetabolic (i.e. functional) diversity

Bacteria are...Bacteria are...

1 µm1 µm Imag

e: K

. Jür

gens

Our ultimate goalOur ultimate goal

Roundicoccus Roundicoccus southamptiisouthamptii

TinymonasTinymonasbremenensisbremenensis

Dalibacter Dalibacter banyuleusbanyuleus

(all names are fiction)(all names are fiction)

SpirovibrioSpirovibriokalmariensiskalmariensis

75% of BCD���75% of BCD���

dominates dominates DMSP��� uptakeDMSP��� uptake

preferentiallypreferentiallygrazed by HNF���grazed by HNF���

very sensitivevery sensitiveto viral attackto viral attack

PhytoPhyto

ZooZoo

Biogeochemical fluxes are a function of community structureBiogeochemical fluxes are a function of community structure

Variability in DAPI counting

Eutrophic reservoir 1.68 107 20 %Med. coast-1 3.63 105 15 %Med. coast-2 2.56 105 5.3 %Mesocosm Exp. 1.03 106 8.2 %Aged seawater 1.02 105 17 %

The standard... At least until 1995

Site BA (ml-1) CV

• Measurement of individual cells• It can measure:

Scattered lightFSC (FALS): light scattered at angles < 10°SSC (RALS): light scattered at 90°

Fluorescence350 nm (UV), 488 nm (Blue), ...

• Up to 7/8 parameters in thousands of cells per second• Advantages

Individual cellsBetter statisticsSupopulations can be identifiedCells can be sorted

• DisadvantagesCells must be isolatedLimited information on structure< 70 µm≤ 800 particles ml-1

Flow Cytometry

1994 Jernaes & Steen “Flow cytometry of

bacteria is still in its infancy”

1977 Bacterial cultures Bailey et al., Paau et al.1977 DNA determination Paau et al. 1978 Protein determination Hutter & Eipel1978 Live and Dead cells Hutter & Eipel1979 DNA and chlorophyll Paau et al.1983 Reserve polymers Srienc et al.1983 Bacterial “diversity” Van Dilla et al.1985 Fluorescent labelled Ab Tyndall et al.1990 Bacterial size Allman et al.

Davey & Kell’96

0

5

10

15

20

25

1988 1990 1992 1994 1996 1998 2000

UV-stains (DAPI, Hoechst)Blue-stains (ToTo, Syto13, SybrGreen)

Year

Pape

rs o

n pl

ankt

onic

bac

teri

a

Li et al. 1995del Giorgio et al. 1996Marie et al. 1997

Robertson & Button 1989Monfort & Baleux 1992Troussellier et al. 1993Monger & Landry 1993

Heterotrophic microbes and flow cytometry

• Introduction• Using the structure or the pigments• Staining the DNA• Dealing with concentrated solutions• Measuring size and biomass (protein content)• Determining bacterial activity structure• Linking community structure to function:

cell sorting and molecular determinationscell sorting and activity measurescell sorting and cell isolation

• other applications relevant to marine science...

5 µm

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• Bacteria with pigments: cyanobacteriaanoxyphotosynthetic bacteria

90° light scatter (SSC, RALS) Orange fluorescence

Red

fluo

resc

ence

90° light scatter (SSC, RALS)

Orange fluorescence

Red

fluo

resc

ence

Red

fluo

resc

ence Peuk

Proc

Syn

Chiprana lagoon Chlorobium vibrioformede

pth

(m) 0 0.5 1 1.5 2

0 5 10 15 20

0

1

2

3

4

5

Chl aBChl aBChl dBChl c

Chl a, BChl a (mg l-1)

BChl c, BChl d (mg l-1)

0 2 4 6 8 10

-200-100 0 100 200 300 400

0

1

2

3

4

5

O2 (mg l-1), H2S (mmol l-1)

Eh (mV)

O2H2SEh

X. Vila, Univ. Girona

Amoebobacter Thiocapsa

LamprocystisChlorobium

LamprocystisChlorobium

SynechococcusChlorobium

SynechococcusChlorobium

L L

SS

X. Cristina

Lake Vilar

FL2-FL3

FL1-FL2FSC-SSC

SSC-FL3

1.45

1.5

1.55

1.6

1.65

1.7

1.75

1.8

0 5 10 15 20

Mostra 475Pop#2S

SC

(rel

ativ

e un

its)

y = 1.842 - 0.025621x R2= 0.9289

y = 1.569 + 0.0675x R2= 0.992

H2S - S0

S0 - SO4

Time (min)

Sulfur as a source of reducing powerFor photosynthesis

Green Chlorobium

• Sulfur• PHB Srienc et al. 1984• Magnetosomes Wallner et al. 1997• Vacuoles Dubelaar et al. 1987• Differentiate bacteria Allman et al. 1993• Size bacteria Troussellier et al. 1999

Usage of light scattering signals

Troussellier et al. 1999

Wallner et al. 1997

Bacteria and flow cytometry

• Introduction• Using the structure or the pigments• Staining the DNA• Dealing with concentrated solutions• Measuring size and biomass (protein content)• Determining bacterial activity structure• Linking community structure to function:

cell sorting and molecular determinationscell sorting and activity measurescell sorting and cell isolation

• other applications relevant to marine science...

Li et al.’95, L&O 40: 1485Li et al.’95, L&O 40: 1485

E. coli Seawater

untreated

RNAse

DNAse

DNAse & RNAse

Guindu

lain e

t al’97

Advantages of counting bacteria with a FC

• Fast ! (> 100 samples a day ?)• Very small volumes (1 µl !)• Allows to know more about “bacteria”• Processing can be automated • It’s 50% cheaper

Seymour et al’04Seymour et al’00

Santa Pola Salterns’99Santa Pola Salterns’99

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Gasol et al’04Gasol et al., submitted

1.000 0.000

POND 37%POND 32%POND 22%POND 15%POND 11%

POND 8%

POND 5%

POND 4%

BACTERIA-DGGE

Sj

4 % 5.4 % 8 % 1 1 % 15 % 22 % 32 %

Blue

flu

ores

cenc

e (D

NA

)

103

102

Threshold101

100 101 102 103

Red fluorescence (protein)

Flow Citometry

DMSP producing phytoplankton bloom in the North SeaEmiliania huxleyi y Prorocentrum minimum

FISH

Roseobacter

Cytophaga/Flavovacterium

SAR86

Zubkov et al. 2001Zubkov et al. 2001

PML/SOC/MPIMMPML/SOC/MPIMM

Abundance highly correlated with DMSP

consumption

Fixation and freezingcounts...

- Cell disappearance- Cell alteration- Better subpop. resolution

Bacteria and flow cytometry

• Introduction• Using the structure or the pigments• Staining the DNA• Dealing with concentrated solutions• Measuring size and biomass (protein content)• Determining bacterial activity structure• Linking community structure to function:

cell sorting and molecular determinationscell sorting and activity measurescell sorting and cell isolation

• other applications relevant to marine science...

• Bacteria in nature are a concentrated solution 105-107 ml-1• 107 ml-1 = 10000 µl-1 at 12 µl min-1, this is 2000 bt s-1

• 2000 bt plus noise, plus beads, plus other things...• Can the electronics handle that w/o coincidence ?

Converting counts to concentrations• Volume-control devices (Ortho Cytoron)• Stabilized flow rates• Ratiometric with beads (why is so instable ?)• Flow calibration• Weight and/or measure• Automatic microinjector (KD Sci)• George: can you build a device for the rest of us ?

0

100

200

300

400

500

600

700

0 2 4 6 8 10

13-Ago-1999

LowMediumHigh

y = 17.3 + 20.7x y = 4.44 + 32.9xy = 14.8 + 67.3x

² wei

ght (

mg)

Time (min)

Low 20.7 µl min-1

Medium 32.9 µl min-1

High 67.3 µl min-1

0

100

200

300

400

500

600

700

0 2 4 6 8 10

1-Oct-99

LowMediumHigh

y = 13.2 + 22.6x r2= 0.98 y = 8.3 + 32.0x r2= 0.99 y = 7.1 + 66.0x r2= 0.99

² wei

ght (

mg)

Time (min)

Getting the job done as fast as possible

Bacteria and flow cytometry

• Introduction• Using the structure or the pigments• Staining the DNA• Dealing with concentrated solutions• Measuring size and biomass (protein content)• Determining bacterial activity structure• Linking community structure to function:

cell sorting and molecular determinationscell sorting and activity measurescell sorting and cell isolation

• other applications relevant to marine science...

A) Estimate size, use a V-to-C equation

Gasol & del Giorgio’00

Scatter & size YES Robertson & Button’93, Steen’90, Troussellier et al’99NO Vives-rego et al’94, Heldal et al’94, Christensen et al’93

DNA and size YES Veldhuis et al’97, Troussellier et al’99...NO ?

(...others measured bacteria > 0.13 µm3, the small bacteria in Robertson et al’98)

The Verity et al. (1992) and the Booth (1988) predictions...

100

1000

10000

0.5 1 1.5 2 2.5 3 3.5

Carb

on (f

gC c

ell-1

)

Size (µm)

10 100 1000 104

“Heterotrophic” bacteria

Prochlorococcus

Synechococcus

“Picoeukaryotes”

Biomass conversion (fgC cell-1)

C conversion factors

B) Use filtration with different filters, then count bacteriaZubkov et al’98, Gin et al.’99...0.2-0.4-0.6-0.8-1 µm

C) Measure protein (Sypro), then use a Protein-to-C factor

Zubkov et al’99

Bacteria and flow cytometry

• Introduction• Using the structure or the pigments• Staining the DNA• Dealing with concentrated solutions• Measuring size and biomass (protein content)• Determining bacterial activity structure• Linking community structure to function:

cell sorting and molecular determinationscell sorting and activity measurescell sorting and cell isolation

• other applications relevant to marine science...

Sieracki & Viles 1992Zweifel & Hagström 1995

2

2.5

3

3.5

4

4.5

5

Estuary Marsh River Marine Lake

FL1

HD

NA

/LD

NA

System

0

0.5

1

1.5

2

2.5

3

Estuary Marsh River Marine Lake

SS

C H

DN

A/L

DN

A

System

Bouvier, del Giorgio & Gasol, in prep.

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Variable cytometric signalsVariable cytometric signals

Blanes Bay, 2003 annual cycle

1 105

2 105

3 105

4 105

5 105

0 20 40 60 80 100 120 140 160

Bac

teria

l abu

ndan

ce (c

ells

ml-1

)

Time (h)

0

50

100

150

200

LIR

(pM

h-1)

40

50

60

70

80

% H

DN

A

LIRLIR

% HDNA% HDNA

HighDNAHighDNA

LowDNALowDNA

HighDNAHighDNA

HighDNAHighDNALowDNALowDNA

LowDNALowDNA

Gasol et al. 1999, AEM 65: 4475Gasol et al. 1999, AEM 65: 4475

10 5

10 6

1

10

100

1000

0 2 4 6 8 10Time (d)

0.065

0.07

0.075

0.08

0.085

0.09

0.095

40

50

60

70

80

90

0

500

1000

1500

2000

LowDNA

HighDNA

EPOC#14° ( ❍ ), 10° ( ● )

Cell volume (µm 3)

LIR (pmol l -1 h-1)

Cell-specific LIR(10 -21 mols Leu cell -1 h-1)

% HighDNA bacteria

Bacterial abundance (ml -1)

Total Count Live&Dead

Total Count DAPI

L&D Live

0 20 40 60 80 100

FC LowDNA

L&D Dead

FC HighDNA

Nucc Cells

Total Count SybrGreen

Total Count Syto13

Experiment #1

% of total (FC) count0 20 40 60 80 100 120

% of total (FC) count

Experiment #2

Gasol et al. 1999, AEM 65: 4475Gasol et al. 1999, AEM 65: 4475

-3

-2

-1

0

1

2

3

-2 -1.5 -1 -0.5 0 0.5 1 1.5 2

Rate of change 0-36 hRate of change 36-84 h

Rate of change of HighDNA bacteria

Rate of change of“Live” bacteria

Gasol et al. 1999, AEM 65: 4475Gasol et al. 1999, AEM 65: 4475

Servais et al. 1999 ME 38: 180

Lebaron et al. 2001 AEM 67: 1775

~HNA~HNA

~LNA~LNA

200

230

260

290

320

350

380

410

0.01 0.10 1.00 10.00

FL 1

Clorofila a (µg L-1)

HDNAFL1=9,75Ln(Cl a)+349,5

LDNA

Corzo et al.’submittedCorzo et al.’submitted

0

20

40

60

80

100

0.03 0.1 1 3 10

Labrador Sea - Grand BanksWestern AtlanticCentral AtlanticEastern Mediterranean

Chlorophyll a (µg L-1)

Data in Li et al. 1995

0.3

Li et al.’95, L&O 40: 1485Li et al.’95, L&O 40: 1485

Mesomed, 1997

All, N = 21, r2 = 0.78Days 0 - 4, slope = 1.1, r2 = 0.67Days 5 - 12, slope = 1.8, r2 = 0.88Days 13 - 20, slope = 2.5, r2 = 0.90

45

50

55

60

65

70

75

80

0 2 4 6 8 10

%HDNA

Nutrient dose (µM N d-1)

Days 0 to 4Days 5 to 12Days 13 to 20

2.0e+06 1.6e+06

8.0e+05

8.0e+05

0102030405060708090

100110120130140150

5.0e+05 1.0e+06 1.5e+06 2.0e+06

Bacteria (cells ml-1)

Bacteria

10 9 8 7 6 5 4 3 2Estación

54.0

63.054.0

45.0

54.0

45.0

40 50 60 70

0102030405060708090

100110120130140150

10 9 8 7 6 5 4 3 2Estación

% HighDNA bacteria

% HDNA

Cruise Incocéano 1997

Cruise Incocéano 1997

120

6060

30

7.50 6.25 5.00 3.75 2.50 1.25

0.5

1.0

1.5

2.0

2.5

3.0

3.5

col

20

50

40

50

30

7.50 6.25 5.00 3.75 2.50 1.25

0.5

1.0

1.5

2.0

2.5

3.0

3.5

1.0e+06

2.0e+06

1.5e+06

1.0e+061.0e+06

7.50 6.25 5.00 3.75 2.50 1.25

0.5

1.0

1.5

2.0

2.5

3.0

3.5

col

Bacteria (cells ml-1)

% HDNA

Actividad bacteriana (pmol Leu l-1 h-1)

Predators absent (< 0.8 µm)

60

70

80

90

100

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8

Time (days)

Predators present (< 150 µm)1000

3000

2000

Gasol et al. 1999, AEM 65: 4475Gasol et al. 1999, AEM 65: 4475

0

5000

1 104

1.5 104

2 104

0

2 106

4 106

6 106

8 106

1 107

1.2 107

A

Heterotrofic flagellatesBacteriaHigh-DNALow-DNA

0 20 40 60 80 100 120

HN

F ab

unda

nce

(cel

ls m

l -1)

Bacterial abundance (cells m

l -1)

Sintes & del Giorgio, submitted

104

105

106

107

108

105 106 107 108Abu

ndan

ce o

f CTC

+ ce

lls (m

l -1)

Abundance of High-DNA cells (ml -1)

CTC+ = 2.41 x HDNA1.57

r2 = 0.66

Sintes & del Giorgio, submitted

10

100

10 100 1000 104 105

%High-DNA%CTC+

Per

cent

Hig

h-D

NA

or C

TC+

cells

Heterotrophic flagellates (ml-1)

Sintes & del Giorgio, submitted

Gasol et al’02

Zubkov et al.,’01Zubkov et al.,’01AEM 67: 5210AEM 67: 5210

Button & Robinson’00,Button & Robinson’00,L&O45:499L&O45:499

Some approaches used to assess bacterial single-cell characteristics

• Microautoradiography, to assess uptake of radiolabeled organic compounds

• RNA content (EUB338+ FISH, Card-fish)• Vital stains as indices of cell metabolism (Fluorescein,

Calcein, INT, CTC)• Stains that reflect membrane polarization and cell integrity

(PI, Oxonol, SYTOX, TOPRO)• Structural integrity under TEM• DNA (or TNA) content of each cell (Syto13, SybrGreen)• Combinations (NADS protocol: PI+SG)• ...

AAII

9010 50 50100100 100100

µ = 1.5µ = 1.5(11 h)(11 h)

µ = 0.01µ = 0.01(166 h)(166 h)

µ = 0.36µ = 0.36(45 h)(45 h)

µ = 1.02µ = 1.02(16 h)(16 h)

IIAA

How does our view of bacterial growth changes if the physiological structure of the assemblage is considered ?

Fact:

• In natural bacterial assemblages (as well as in pure laboratory cultures) there are cells in widely different physiologic states:• Dead or injured• Dormant, quiescent, inactive, non-growing• Metabolically active and growing

- Even within the active fraction there is a wide range in the level of activity

This is the “physiological structure” of bacterioplankton assemblages

This is the “activity structure” of bacterioplankton assemblages

The approaches must be viewed as complementary rather than as exclusive

CTC

Microautoradiography

DNA content

Dibac (depolarization)

PI (damage)

TEM��

High activity

Medium activity

Low activityDormancy

Death Lysis

What is the interpretation of these methods?• There is a continuum in the physiologic state of bacterial cells• The distinction between physiologic states is purely operational• Each method targets a different aspect of cell metabolism or

structure • Each method has a different detection threshold

Del

Gio

rgio

& B

ouvi

er’0

2

NADS(SG1 + PI)

Red

Green

UV-C

0

2 105

4 105

6 105

8 105

1 106

CTC+ cells (ml-1)

0

0.5

1

1.5

2

CTC+ cells relative red fluorescence

A B

0

0.05

0.1

0.15

0.2

0.25

0 50 100 150 200 250

CTC+ cells relative side scatter

Time (min)0 50 100 150 200 250

0

10

20

30

40

50% CTC+

Time (min)

C D

w/o additionswith algal filtrate

Gasol & Arístegui, submittedGasol & Arístegui, submitted

Gasol & Arístegui, submittedGasol & Arístegui, submitted

90° light scatter Green fluorescence

B

CTC- cells

Low DNA

High DNA

B

CTC+ cellsCTF granules

Gasol & Arístegui, submittedGasol & Arístegui, submitted

Activity probesActivity probes

% HDNA% HDNA Active (?)Active (?)CTC+CTC+ Very active (respiration)Very active (respiration)PIPI damaged membranedamaged membraneSytoxSytox damaged membranedamaged membraneCFDA/SECFDA/SE Intracellular esterasesIntracellular esterasesDibacDibac Membrane w/o polarityMembrane w/o polarityMP Live & DeadMP Live & Dead PI + Syto9PI + Syto9NADSNADS PI + SybrGreen IPI + SybrGreen IBD Live & DeadBD Live & Dead PI + Thiazol OrangePI + Thiazol Orange

****

**

**

**

****

Microautoradiography (Leu, Gluc, AA, ATP, DMSP)Microautoradiography (Leu, Gluc, AA, ATP, DMSP)16 rRNA content (FISH & CARD16 rRNA content (FISH & CARD--FISH)FISH)VSP (rRNA + PI + DAPI)VSP (rRNA + PI + DAPI)

0 20 40 60 80 100

%CTC

%CFDA

% HDNA

1-%DIBAC

%CARD-FISH

1-%Sytox

1-%PI

% Live (NADS)

% Live (L&D)

% Live (BD L&D)

% Vives

Mèt

ode

% live cells

Met

hod

Bacteria and flow cytometry

• Introduction• Using the structure or the pigments• Staining the DNA• Dealing with concentrated solutions• Measuring size and biomass (protein content)• Determining bacterial activity structure• Linking community structure to function:

cell sorting and molecular determinationscell sorting and activity measurescell sorting and cell isolation

• other applications relevant to marine science...

Cell sorting by FCM

Further analyses of sorted fractions

* Activity (radioactivity)* Identification* Isolation* Chemical analyses (C; N; P,….)

PrelabelingRadioactive substratesNucleic acid probesPhysiological probes

Laser(488 nm)

Trash

FACSCalibur FACSVantageHigh speed cell sorter

OOBOOB

Radioactivity Cell sorting - 14C-uptake (Rivkin et al. 1986, Li 1994)- 15N-uptake (Lipschultz 1995)- 3H-leucine (Servais et al.’99, ’00, ‘03, Zubkov et al’04)- 35S-methionine (Zubkov et al.’03)- 35S-DMSP (Zubkov et al’01, Vila et al., Maelstrom et al.)

PML/SOC/MPIMMPML/SOC/MPIMM

Epifluorescencemicroscopy

FISH probing

Molecular identification ofbacterioplankton

Polymerase chain reaction (PCR)of 16S ribosomal RNA genes

Cloning & sequencing of 16S rRNA genes

Phylogenetic affiliation,designing of specific probes for

fluorescence in situ hybridisation (FISH)

FISH confirmation ofdominance

Bacterialcells

DNA staining

Genomic DNA

16S rRNA gene primers

Rickettsia et al.

marine snow associated bacterium Oceanospirillum pusillum

marine snow associated bacterium

Sphingomonas et al.

Rhodospirillum salexigenes Rhodospirillum salexigenes

Roseobacter et al.

marine snow associated bacterium Ophiopholis aculeata symbiont ZD0211c, 1427 ZD0207c, 1541

ZD0250, 799 ZD0206, 795 ZD0212, 790 ZD0201, 775 ZD0253, 800

ZD0204, 754 ZD0208, 741 ZD0249, 720 ZD0256, 759

ZD0205, 719 "Marinosulfonas methylotrophus

Paracoccus

Rhodobacter veldkampii

Rhodobacter

Rhodovulum

Tetracoccus/Amaricoccus

Hyphomonas/ Hirschia

Rhodobium Devosia riboflavina

Agrobacterium

Rhizobium et al.

Rhodobium orientum

E.coli with inserted16S rRNA gene

fragments

LabelledProbe

Ribosome

Bernhard Fuchs

Sekar et al’04

Gel microdroplets

Zengler et al’02

Bacteria and flow cytometry

• Introduction• Using the structure or the pigments• Staining the DNA• Dealing with concentrated solutions• Measuring size and biomass (protein content)• Determining bacterial activity structure• Linking community structure to function:

cell sorting and molecular determinationscell sorting and activity measurescell sorting and cell isolation

• other applications relevant to marine science...probing the ecosystem functions ???

• biomass distribution e.g. Campbell et al’94• size, biochemistry and

morphological diversities• physiological diversity• phylotype diversity• carbon flow through populations e.g. Zubkov’s• S-flow through populations e.g. Zubkov’s• enumerating viruses Brussard et al’99, Marie et al’99• detecting infection Brussard et al’01• enumerating heterotrophic protists Guindulain et al’02, Rose et al’04• fast determination of grazing rates Vazquez-Dominguez et al’99• respiration with CTC ??? Sherr et al’99• ...

Role of FC in biodiversity and ecosystem functioning

Rose et al’04Sintes & del Giorgio, subm.

Lyso-Tracker

Syto13-SybrGreen

Guindulain et al’02

Zubkov et al’04

Bacteria and flow cytometry

• Introduction• Using the structure or the pigments• Staining the DNA• Dealing with concentrated solutions• Measuring size and biomass (protein content)• Determining bacterial activity structure• Linking community structure to function:

cell sorting and molecular determinationscell sorting and activity measurescell sorting and cell isolation

• other applications relevant to marine science...probing the ecosystem functions ???

BaBacterial cterial sisinglengle--ccell ell approaches to the approaches to the relationship between relationship between diversity and function diversity and function in the in the SSeaea

www.icm.csic.es/bio/projects/basicswww.icm.csic.es/bio/projects/basics

17-23 October 2005Banyuls-sur-mer, FranceBacterial single-cell analysis workshopWith lectures and congress-like meeting

plus hands-on tutorial on:CARD-Fish, FC cell sorting, MAR,MAR-Fish, etc...