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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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The content of this presentation is the exclusive property of its author. Any
use is prohibited.If you wish to use any material
for any purpose whatsoever, permission must be obtained
from the author.
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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...
![Page 4: Bacteria and flow cytometry - · PDF fileBacteria and flow cytometry: From enumeration to community structure and ecological function Josep M Gasol Institut de Ciències del Mar-CSIC](https://reader033.vdocumento.com/reader033/viewer/2022051523/5a797ed57f8b9a6c158c6eb4/html5/thumbnails/4.jpg)
•• 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...
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1 µm1 µm Imag
e: K
. Jür
gens
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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
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PhytoPhyto
ZooZoo
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Biogeochemical fluxes are a function of community structureBiogeochemical fluxes are a function of community structure
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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
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• 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
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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
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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
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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...
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5 µm
Se necesita QuickTime
y un descompresor Photo
CD para utilizar esta imagen.
• 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
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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
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Amoebobacter Thiocapsa
LamprocystisChlorobium
LamprocystisChlorobium
SynechococcusChlorobium
SynechococcusChlorobium
L L
SS
X. Cristina
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Lake Vilar
FL2-FL3
FL1-FL2FSC-SSC
SSC-FL3
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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
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Green Chlorobium
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• 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
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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...
![Page 22: Bacteria and flow cytometry - · PDF fileBacteria and flow cytometry: From enumeration to community structure and ecological function Josep M Gasol Institut de Ciències del Mar-CSIC](https://reader033.vdocumento.com/reader033/viewer/2022051523/5a797ed57f8b9a6c158c6eb4/html5/thumbnails/22.jpg)
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Li et al.’95, L&O 40: 1485Li et al.’95, L&O 40: 1485
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E. coli Seawater
untreated
RNAse
DNAse
DNAse & RNAse
Guindu
lain e
t al’97
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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
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Santa Pola Salterns’99Santa Pola Salterns’99
Se necesita QuickTime
y un descompresor Photo
CD para utilizar esta imagen.
Gasol et al’04Gasol et al., submitted
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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 %
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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
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Fixation and freezingcounts...
- Cell disappearance- Cell alteration- Better subpop. resolution
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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...
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• 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 ?
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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)
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Getting the job done as fast as possible
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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...
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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)
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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
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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
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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...
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Sieracki & Viles 1992Zweifel & Hagström 1995
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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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Para ver esta película, debedisponer de QuickTime™ y de
un descompresor Vídeo.
Variable cytometric signalsVariable cytometric signals
Blanes Bay, 2003 annual cycle
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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
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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)
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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
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-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
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Servais et al. 1999 ME 38: 180
Lebaron et al. 2001 AEM 67: 1775
~HNA~HNA
~LNA~LNA
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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
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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
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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
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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)
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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
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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
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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
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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
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Gasol et al’02
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Zubkov et al.,’01Zubkov et al.,’01AEM 67: 5210AEM 67: 5210
Button & Robinson’00,Button & Robinson’00,L&O45:499L&O45:499
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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)• ...
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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 ?
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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
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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
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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
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Del
Gio
rgio
& B
ouvi
er’0
2
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NADS(SG1 + PI)
Red
Green
UV-C
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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
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Gasol & Arístegui, submittedGasol & Arístegui, submitted
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90° light scatter Green fluorescence
B
CTC- cells
Low DNA
High DNA
B
CTC+ cellsCTF granules
Gasol & Arístegui, submittedGasol & Arístegui, submitted
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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)
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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
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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...
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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
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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.)
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PML/SOC/MPIMMPML/SOC/MPIMM
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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
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Bernhard Fuchs
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Sekar et al’04
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Gel microdroplets
Zengler et al’02
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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...probing the ecosystem functions ???
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• 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
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Rose et al’04Sintes & del Giorgio, subm.
Lyso-Tracker
Syto13-SybrGreen
Guindulain et al’02
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Zubkov et al’04
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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...probing the ecosystem functions ???
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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...