Near real-time, autonomous detection of marinebacterioplankton on a coastal mooring in MontereyBay, California, using rRNA-targeted DNA probes

Christina M. Preston,1* Roman Marin III,1

Scott D. Jensen,1 Jason Feldman,1,2

James M. Birch,1 Eugene I. Massion,1

Edward F. DeLong,3 Marcelino Suzuki,4

Kevin Wheeler1,5 and Christopher A. Scholin1

1Monterey Bay Aquarium Research Institute, MossLanding, CA 95039, USA.2Jet Propulsion Laboratory, Pasadena, CA 91125, USA.3Massachussets Institute of Technology, Department ofCivil and Environmental Engineering and Division ofBiological Engineering, Cambridge, MA 02139, USA.4Chesapeake Biological Laboratory, University ofMaryland, Solomons, MD 20668, 5NASA AmesResearch Center, Moffett Field, CA 94035, USA.

Summary

A sandwich hybridization assay (SHA) was developedto detect 16S rRNAs indicative of phylogeneticallydistinct groups of marine bacterioplankton in a96-well plate format as well as low-density arraysprinted on a membrane support. The arrays wereused in a field-deployable instrument, the Environ-mental Sample Processor (ESP). The SHA employs achaotropic buffer for both cell homogenization andhybridization, thus target sequences are captureddirectly from crude homogenates. Capture probes forseven of nine different bacterioplankton clades exam-ined reacted specifically when challenged with targetand non-target 16S rRNAs derived from in vitrotranscribed 16S rRNA genes cloned from naturalsamples. Detection limits were between 0.10–1.98 and4.43– 12.54 fmole ml-1 homogenate for the 96-wellplate and array SHA respectively. Arrays printed withfive of the bacterioplankton-specific capture probeswere deployed on the ESP in Monterey Bay, CA, twicein 2006 for a total of 25 days and also utilized in alaboratory time series study. Groups detectedincluded marine alphaproteobacteria, SAR11, marinecyanobacteria, marine group I crenarchaea, and

marine group II euryarchaea. To our knowledge thisrepresents the first report of remote in situ DNAprobe-based detection of marine bacterioplankton.

Introduction

Application of molecular analytical techniques has becomewell established in ocean science, yet the vast majority ofwork typically occurs in a shore-based laboratory after thereturn of a discrete set of samples. Although manymolecular-based analyses are described as ‘high-throughput’, those methods generally are restricted tolaboratory use and typically require a substantial effort tocollect and process samples prior to batch mode analyses.Often, acquisition of data in real- or near-real time isimpossible or impractical, prohibiting rapid characteriza-tion and response to dynamic, stochastic and variablebiological phenomena in the environment. Limited sam-pling opportunities also restrict our ability to documentmicrobial community dynamics. Samples are oftenobtained in time series surveys or expeditions at intervalsthat reflect practical and fiscal constraints of ship opera-tions (Karl and Lukas, 1996; Fasham et al., 2001). Whileinvaluable, such snapshots may not necessarily capturemicrobial population dynamics or patterns of gene expres-sion on scales that reflect a continuum of environmentalfluctuations.

To overcome this impediment a host of new instrumentsand next generation observing systems are being con-structed. Most biological sensors in use today utilizeoptical techniques to derive presence, abundance andphotosynthetic activities of organisms (Gentien et al.,1995; Dubelaar et al., 1999; Kirkpatrick et al., 2000; Sosiket al., 2003; Babin et al., 2005; Wang et al., 2005), butnew molecular analytical-based sensors are also emerg-ing (e.g. Paul et al., 2007). Coined ‘ecogenomic sensors’,these devices aim to provide measures of microbial pres-ence and/or function at the molecular level, in many waysparalleling wet chemistry techniques used in the labora-tory (NOPP, 2005). Included in the latter are the Autono-mous Microbial Genosensor and Environmental SampleProcessor (ESP) (Scholin et al., 2001; 2008; Paul et al.,2007). Work presented here centres on the ESP.

Received 3 June, 2008; accepted 11 November, 2008. *For corre-spondence. E-mail preston@mbari.org; Tel. (+1) 831 775 1754; Fax(+1) 831 775 1620.

Environmental Microbiology (2009) 11(5), 1168–1180 doi:10.1111/j.1462-2920.2009.01848.x

© 2009 MBARIJournal compilation © 2009 Society for Applied Microbiology and Blackwell Publishing Ltd

The ESP (Fig. 1) is an electromechanical/fluidic systemthat collects discrete water samples from the ocean sub-surface and allows for the application of DNA probe arraysto detect target rRNAs present in a crude homogenateusing a sandwich hybridization assay (SHA) methodology(Roman et al., 2005; Greenfield et al., 2006; 2008;Haywood et al., 2007; Jones et al., 2008). The entire auto-mated process of collecting a live sample to broadcast ofan imaged array takes approximately 2.5 h. Previousapplications of the ESP have focused on detectingharmful algae and invertebrate larvae in situ (Goffrediet al., 2006; Greenfield et al., 2006; 2008; Metfies et al.,2006; Scholin et al., 2008; Haywood, 2007; Jones et al.,2008). Here, we demonstrate the utility of the ESP fordirectly detecting rRNA of marine bacterioplankton (BAC)and illustrate how this device can be used to track com-munity population shifts remotely. A 96-well plate versionof the assay was used for probe development, specificitytesting and for validating results obtained using the ESP.

Results

Tests of the SHA capture and signal probes

Individual capture probes in combination with the twosignal probes (Table 1) were tested against samples con-taining target and non-targets using the 96-well plateformat. Negative reactions returned an average A450 of< 0.08, while those greater than 0.110 were scored aspositive (Table 2). Probes for marine alphaproteobacteria,SAR11, SAR86 subgroups, and marine cyanobacteriahybridized only to their intended targets. Both the marinegroup 1 (G1) crenarchaea and marine group 2 (G2)euryarchaeal probes showed specificity for archaea.However, both probes cross-reacted with rRNA transcriptfrom marine group III (G3) euryarchaeota (pcr clone 1#6F,V. Orphan, unpublished). Although not specific for theirintended archeal clades, the G3 euryarchaeota are notroutinely recovered in libraries constructed from MontereyBay BAC (Beja et al., 2000; Suzuki et al., 2004), and more

Fig. 1. Schematic diagram of the fluid path within the ESP instrument for sample collection and array processing. Seawater is brought into theinstrument and filtered through a puck until the specified volume is reached or until the filter clogged.A. The collection syringe presents various reagents to the particulates collected on the filter in the puck, resulting in cell lysis followed bydilution of the lysate.B. The diluted lysate is passed to the processing syringe. The processing syringe delivers the lysate to a puck containing an array; then afterincubation cleared to waste. The process is repeated for subsequent reagents.C. The array is positioned under CCD camera and photographed.D. The resulting image file is sent ashore via surface radio mooring.E. Black circles represent valves that make connections between the syringes and puck, reagents, air or waste. See Experimental proceduresand Greenfield et al. (2006) for further details.

Autonomous detection of bacterioplankton 1169

© 2009 MBARIJournal compilation © 2009 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 11, 1168–1180

specifically have not been recovered from the ESPdeployment site (C. Preston, unpublished data). Thus,both were advanced to field trials. The probe for G3 eur-yarchaea failed to react with its intended target but didreact with chloroplast rRNA (not shown). The captureprobe for Cytophaga-Flavobacteria cross-reacted withseven of the eight non-target transcripts tested. Conse-quently, probes targeting G3 euryarchaea andCytophaga-Flavobacteria were not considered further.

To assess probe specificity using the ESP, homoge-nates as used in the 96-well plate assay were provideddirectly to the instrument, which then developed andimaged an array. Background signal from non-spottedregions on the arrays averaged 1814 � 128 counts. Allnon-targets and negative controls gave reaction intensi-ties below array background except for marine cyanobac-teria where counts where consistently 1000 counts abovebackground (Table 2). Control probes reacted success-fully on every array. Targets positive in the 96-well plateassay also reacted successfully in the array format. Probespots exceeding three standard deviations above overallarray background were considered positive for marinealphaproteobacteria, SAR11, SAR86 subgroup i–ii,SAR86 subgroup iii, G1 crenarchaea and G2 eur-yarchaea. A positive reaction for the marine cyanobacteriaprobe exceeded that definition by an additional 1000counts.

No cross reactivity was observed when eight non-target bacterial transcripts (each at 50 ng ml-1 lysate)and lysed Escherichia coli cells (1 ¥ 108 cells ml-1 lysate)were combined. When all target and non-target tran-scripts were mixed, signals from the marine alphapro-teobacteria, SAR11, SAR86i–ii and SAR86iii captureprobes were within 10% of the pure transcript. In con-trast, a lower signal (82–83% of the pure signal) wasobserved in the complex mixture for both archaealprobes (Table 2).

Standard curves were determined by diluting the sixtarget transcripts in a constant background of eight non-target bacterial transcripts each at 50 ng ml-1 lysate(Fig. 2). For every probe tested, the 96-well plate formatwas more sensitive (Fig. 2, Table 2). An A450 value of atleast 0.25 was required to obtain a positive signal on thearray. The lower limit of detection for each capture probewas in the low fmol ml-1 range for both assay formats(Table 2). The reproducibility of the arrays was assessedusing samples that contained six target transcripts (eachat 12.5 ng ml-1 lysate) and eight negative transcripts(each at 50 ng ml-1 lysate). Three replicate arrays had acoefficient of variation below 20%. Similar results andsignal intensities were obtained after combining the tran-scripts in a background of 108 cells ml-1E. coli. Althoughthe signal was reproducible within a single batch ofarrays, the absolute signal varied when the same samplesTa

ble

1.S

andw

ich

hybr

idiz

atio

nca

ptur

ean

dsi

gnal

prob

esus

edfo

rth

eE

SP

arra

yan

d96

-wel

lpla

tefo

rmat

s.

Pro

bena

me

Pro

bety

peTa

rget

clad

eS

eque

nce

(5′-

3′)a

Com

men

tsR

efer

ence

CF

319a

Cap

ture

Cyt

opha

ga-F

lavo

bact

eria

Bio

tin-(

C9)

3-T

GG

TC

CG

TG

TC

TC

AG

TAC

Cro

ssre

acts

with

man

ygr

oups

;no

tus

edin

stud

yM

anz

etal

.(1

996)

Mal

ph-1

_488

Cap

ture

Mar

ine

alph

apro

teob

acte

riaB

iotin

-(C

9)3-

GC

CG

GG

GT

TT

CT

TTA

CC

AG

elpu

rified

Gon

zale

zet

al.

(199

6)G

onza

lez

and

Mor

an(1

997)

Pic

ophy

to49

6C

aptu

reM

arin

ecy

anob

acte

riaB

iotin

-(C

9)3-

GG

CA

CG

GA

AT

TAG

CC

GW

GG

CT

TAW

eakl

yta

rget

sS

ynne

choc

occu

san

dP

roch

loro

cocc

usM

odifi

edfr

omS

uzuk

iet

al.

(200

0)S

AR

11_4

41C

aptu

reS

AR

11B

iotin

-(C

9)3-

TAC

AG

TC

AT

TW

TC

TT

CC

CC

KA

CG

AA

GA

GM

odifi

edfr

omM

orris

etal

.(2

002)

SA

R86

i–ii_

470

Cap

ture

SA

R86

subg

roup

sI

and

IIB

iotin

-(C

9)3-

GC

AG

GTA

AC

AT

CA

SG

GW

TATA

GG

Thi

sst

udy

SA

R86

iii_4

70C

aptu

reS

AR

86su

bgro

upIII

Bio

tin-(

C9)

3-G

AT

GG

TAA

TG

TC

AC

GG

TTA

TT

GG

Thi

sst

udy

Mar

ineC

ren_

554

Cap

ture

Mar

ine

G1

cren

arch

aea

Bio

tin-(

C9)

3-G

AT

GC

TT

TAG

GC

CC

AA

TAA

TC

AM

CC

TC

ross

reac

tsw

ithm

arin

eG

3eu

ryar

chae

aM

odifi

edfr

omM

assa

naet

al.

(199

7)M

arin

eEur

yII_

547

Cap

ture

Mar

ine

G2

cren

arch

aea

Bio

tin-(

C9)

3-T

TAG

GC

CC

AA

TAA

AA

KT

GA

CK

AC

CA

CT

Cro

ssre

acts

with

mar

ine

G3

eury

arch

aea

Mod

ified

from

Suz

uki

etal

.(2

000)

Mar

ineE

uryI

II_68

2bC

aptu

reM

arin

eG

3cr

enar

chae

aB

iotin

-(C

9)3-

GG

AT

TAC

AA

CA

TT

TC

AC

CG

CT

CC

CC

Cro

ssre

acts

with

Rap

hido

phyt

es,

not

used

inst

udy

Thi

sst

udy

Eub

338

Sig

nal

Bac

teria

Dig

-C9-

GC

WG

CC

WC

CC

GTA

GG

WG

T-C

9-D

igIn

clud

esP

lanc

tom

ycet

ales

and

Ver

ruco

mic

robi

aD

aim

set

al.

(200

6)

Uni

v519

abS

igna

lU

nive

rsal

Dig

-C9-

TTA

CC

GC

GG

CK

GC

TG

GC

AC

-C9-

Dig

Uni

vers

albu

tbi

ased

tow

ards

Arc

haea

and

Bac

teria

Mod

ified

from

Suz

uki

etal

.(2

000)

Ale

xCom

pC

aptu

reB

iotin

-(C

9)3-

GG

GA

AA

TAT

GA

AA

AG

GA

CT

TT

GA

AP

ositi

veco

ntro

lon

arra

ysG

reen

field

etal

.(2

006)

Ale

x-al

t-S

Sig

nal

Dig

-C9-

GT

CC

TT

TT

CA

TAT

TT

CC

CT

CA

TG

G-C

9-D

igC

ompl

imen

tary

toA

lexC

omp

Gre

enfie

ldet

al.

(200

6)

a.U

nder

lined

base

ofsi

gnal

prob

ein

dica

teth

epo

sitio

nof

the

inte

rnal

diox

ygen

in(D

ig);

(C9)

3=

3C

9sp

acer

s.

1170 C. Preston et al.

© 2009 MBARIJournal compilation © 2009 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 11, 1168–1180

Tab

le2.

The

spec

ifici

tyof

the

vario

usca

ptur

epr

obe

inth

e96

wel

land

arra

yfo

rmat

SH

Aus

ing

targ

etan

dno

n-ta

rget

rRN

As.

Tran

scrip

t/RN

Aso

urce

aC

lade

Cap

ture

prob

eb

CF

319a

Mal

ph-1

_488

SA

R11

441

SA

R86

i–ii

470

SA

R86

iii47

0M

arC

ren5

54M

arE

ury5

47P

icop

hyto

496

Lysi

sbu

ffer

NA

0.07

2�

0.00

2N

VS

0.05

7�

0.00

1N

VS

0.06

5�

0.00

7N

VS

0.06

1�

0.00

3N

VS

0.06

1�

0.00

2N

VS

0.06

5�

0.00

7N

VS

0.07

6�

0.00

9N

VS

0.07

9�

0.00

024

58�

105

M0_

P4A

7C

ytop

haga

3.5

1000

5�

457

0.05

0�

0.00

2N

VS

0.05

1�

0.00

3N

EG

0.05

9�

0.00

2N

VS

0.05

8�

0.00

8N

VS

0.07

5�

0.01

0N

EG

0.07

0�

0.00

9N

EG

0.06

9�

0.01

526

66�

202

M0_

P1G

4M

arin

eal

phap

rote

obac

teria

0.10

2�

0.00

42.

812

�0.

052

8914

�68

80.

064

�0.

007

NV

S0.

069

�0.

003

NV

S0.

074

�0.

010

NV

S0.

052

�0.

007

NV

S0.

083

�0.

009

NV

S0.

071

�0.

006

2212

�67

M0_

P1D

2S

AR

110.

351

�0.

008

0.05

0�

0.00

11.

738

�0.

066

1078

1�

748

0.05

1�

0.00

1N

EG

0.06

1�

0.00

6N

EG

0.06

3�

0.00

322

33�

134

0.05

9�

0.00

3N

EG

0.08

4�

0.00

322

93�

99M

0_P

1H12

SA

R86

subg

roup

II0.

170

�0.

008

0.05

0�

0.00

1N

VS

0.06

8�

0.00

3N

VS

0.72

9�

0.01

050

28�

246

0.06

3�

0.00

7N

VS

0.05

7�

0.00

9N

VS

0.05

7�

0.00

2N

VS

0.07

5�

0.00

424

76�

109

M0_

P2C

4S

AR

86su

bgro

upIII

0.17

0�

0.00

90.

055

�0.

002

NV

S0.

067

�0.

010

2183

�15

40.

060

�0.

003

NV

S3.

521

828

�79

70.

053

�0.

001

NV

S0.

055

�0.

001

NV

S0.

067

�0.

000

2593

�16

0M

0_05

0405

a8M

arin

eG

1cr

enar

chae

a0.

458

�0.

017

0.05

4�

0.00

1N

VS

0.09

3�

0.00

1N

VS

0.06

6�

0.01

3N

VS

0.07

0�

0.00

1N

VS

3.5

1990

3�

379

0.06

5�

0.00

124

00�

127

0.06

0�

0.00

324

42�

78M

0_05

0405

A5

Mar

ine

G2

eury

arch

aea

0.05

6�

0.05

30.

056

�0.

001

NE

G0.

056

�0.

000

NV

S0.

066

�0.

01N

VS

0.06

4�

0.00

6N

VS

0.05

9�

0.00

5N

VS

3.5

1581

6�

1122

0.06

7�

0.00

125

01�

437

Syn

ecco

cocc

ussp

.C

CM

P13

34c

Mar

ine

cyan

obac

teria

0.54

6�

0.00

80.

073

�0.

007

NV

S0.

067

�0.

004

NV

S0.

056

�0.

002

NV

S0.

070

�0.

012

NV

S0.

058

�0.

003

NV

S0.

057

�0.

002

NV

S0.

208

�0.

018

3966

�29

21#

6FM

arin

eG

3eu

ryar

chae

aN

D0.

056

�0.

001

0.05

7�

0.00

10.

056

�0.

002

0.05

5�

0.00

20.

523

�0.

019

0.19

0�

0.01

60.

060

�0.

002

M0_

P1B

1A

RC

TIC

BD

96-1

9N

D0.

053

�0.

004

NV

S0.

052

�0.

002

NV

S0.

062

�0.

002

NV

S0.

057

�0.

001

NV

S0.

057

�0.

013

NV

S0.

073

�0.

01N

VS

0.06

2�

0.00

820

98�

27M

0_P

3C11

Ver

ruco

mic

robi

ales

ND

0.09

5�

0.01

7N

VS

0.09

2�

0.01

4N

VS

0.05

7�

0.00

2N

VS

0.05

8�

0.00

1N

VS

0.06

7�

0.00

7N

VS

0.06

2�

0.00

4N

VS

0.07

5�

0.00

529

29�

85M

0_P

3A6

HT

CC

230

ND

0.05

5�

0.00

1N

VS

0.05

4�

0.00

1N

VS

0.05

6�

0.00

1N

VS

0.06

3�

0.00

4N

VS

0.06

0�

0.00

7N

VS

0.05

8�

0.00

2N

VS

0.05

8�

0.00

321

72�

38M

0_P

3B5

NA

C11

-7N

D0.

057

�0.

008

NV

S0.

051

�0.

001

NV

S0.

060

�0.

005

NV

S0.

062

�0.

006

NV

S0.

061

�0.

003

NV

S0.

060

�0.

004

NV

S0.

055

�0.

005

¥N

VS

M0_

P3D

120M

60N

D0.

060

�0.

005

NV

S0.

061

�0.

004

NV

S0.

057

�0.

001

NV

S0.

061

�0.

003

NV

S0.

069

�0.

013

NV

S0.

058

�0.

003

NV

S0.

068

�0.

002

2462

�71

M0_

P3C

12E

B03

6A07

ND

0.05

7�

0.00

6N

VS

0.04

9�

0.00

2N

VS

0.04

8�

0.00

1N

VS

0.05

8�

0.00

6N

VS

0.05

1�

0.00

5N

VS

0.04

9�

0N

VS

0.04

9�

0.00

224

89�

63M

0_P

3A5

KT

C11

19N

D0.

048

�0.

001

NV

S0.

054

�0.

007

NV

S0.

052

�0.

004

NV

S0.

056

�0.

008

NV

S0.

052

�0.

002

NV

S0.

048

�0

NV

S0.

053

�0.

001

2394

�46

M0_

P1A

8S

AR

156

ND

0.05

3�

0.00

7N

VS

0.04

7�

0.00

1N

VS

0.06

3�

0.00

3N

VS

0.06

2�

0.00

1N

VS

0.06

1�

0.00

7N

VS

0.06

2�

0.00

7N

VS

0.05

2�

0.00

4N

VS

E.c

olic

Ent

erob

acte

riace

aeN

D0.

056

�0.

001

NV

S0.

054

�0

NV

S0.

054

�0.

002

NV

S0.

060

�0.

001

NV

S0.

067

�0

NV

S0.

055

�0.

004

NV

S0.

054

�0

2288

�74

Non

-tar

get

tran

scrip

ts+

E.c

olid

ND

0.05

3�

0.00

30.

058

�0.

001

0.05

3�

0.00

40.

052

�0.

001

0.05

0�

0.00

20.

058

�0.

008

0.05

8�

0.01

3Ta

rget

&no

n-ta

rget

tran

scrip

tse

ND

2.97

9�

0.03

01.

642

�0.

044

0.66

2�

0.01

31.

803

�0.

043

1.03

0�

0.03

31.

332

�0.

029

ND

Targ

ettr

ansc

ripte

ND

2.81

2�

0.05

21.

738

�0.

066

0.72

9�

0.01

01.

714

�0.

098

1.23

8�

0.05

71.

628

�0.

092

ND

Lim

itof

dete

ctio

nf

(fm

oles

ml-1

lysa

te)

NA

0.22

7.31

1.98

4.59

0.10

12.5

40.

113.

660.

185.

610.

374.

43N

A

a.Tr

ansc

ripts

and

nativ

eR

NA

at50

ngm

l-1ly

sate

(app

roxi

mat

ely

2.1–

9.7

¥10

10co

pies

ml-1

)fo

rsp

ecifi

city

test

sex

cept

for

the

arra

yus

ing

Syn

ecch

ococ

cus

RN

A(1

50ng

ml-1

lysa

te).

b.

Top

valu

eis

the

A45

0(s

tand

ard

devi

atio

n)fr

om96

wel

lpla

teas

say;

botto

mco

mm

entf

rom

ES

Pde

velo

ped

arra

yas

follo

ws:

NV

S,n

ovi

sibl

esp

ot;N

EG

,les

sth

anth

ree

stan

dard

devi

atio

nsab

ove

back

grou

nd;

raw

CC

Dpi

xeli

nten

sity

(sta

ndar

dde

viat

ion)

;N

D,

not

dete

rmin

ed.

Bol

ded

valu

esin

dica

tepo

sitiv

ehy

brid

izat

ion

sign

als;

grey

-sha

ded

boxe

sin

dica

tepr

obe-

targ

etm

atch

es.

c.R

NA

isol

ated

from

cultu

re.

d.

Eig

htno

n-ta

rget

bact

eria

ltra

nscr

ipts

(eac

hat

50ng

ml-1

)w

ithly

sed

E.c

olic

ells

(1¥

108

cells

ml-1

lysa

te).

e.E

ight

non-

targ

etba

cter

ialt

rans

crip

tsat

50ng

ml-1

and

targ

ettr

ansc

ript

conc

entr

atio

nas

follo

ws

50ng

ml-1

lysa

tefo

rM

0_P

1G4,

M0_

P1H

12,

M0_

P1D

2,25

ngm

l-1ly

sate

for

M0_

P2C

4,M

0_05

0405

A5

and

12.5

ml-1

lysa

tefo

rM

0_05

0405

a8.

f.Li

mit

ofde

tect

ion

dete

rmin

edfr

omF

ig.2

.P

ositi

vesi

gnal

>A

450

=0.

11or

2500

CC

Dco

unts

;N

A,

not

appl

icab

le.

Autonomous detection of bacterioplankton 1171

© 2009 MBARIJournal compilation © 2009 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 11, 1168–1180

were run using different batches of arrays (data notshown).

Samples prepared by the ESP were similar to if notmore reactive than those prepared manually. Forexample, native seawater samples collected, lysed anddiluted for hybridization by the ESP (n = 1) were com-pared with the same sample collected, lysed and dilutedmanually (n = 3). Samples processed by the ESP for G2euryarchaea yielded an A450 of 3.128 � 0.099, whereasthose processed manually had A450 values of2.911 � 0.171, 3.033 � 0.060 and 2.575 � 0.028.Experiments targeting marine alphaproteobacteriayielded similar results: 0.309 � 0.020 from the ESP-processed sample versus 0.217 � 0.007, 0.230 � 0.005and 0.214 � 0.099 for samples processed manually. Inaddition, positive SHA values indicated the presence ofrRNA rather than rRNA genes as both untreated andDNase-treated samples resulted in positive reactions(0.437 � 0.004 and 0.454 � 0.010 respectively), and

samples treated with RNase produced no signal(0.084 � 0.008).

Environmental Sample Processor field deployments

Arrays fielded on the ESP were printed with captureprobes for marine alphaproteobacteria, SAR11, marinecyanobacteria, G1 crenarchaea and G2 euryarchaea(Fig. 3A). Prior to deployment, the ESP was providedfiltered sterilized seawater and native surface seawaterfor negative and positive controls respectively (e.g.Fig. 3B and C). For the positive test, the ESP detected thepresence of marine alphaproteobacteria and G2 eur-yarchaea (Fig. 3C, Table 3). The 96-well plate SHA usingthe same sample and sample volume confirmed the pres-ence of marine alphaproteobacteria and G2 euryarchaea.SAR11 and marine cyanobacteria were also present butbelow the detection limit of the arrays. G1 crenarchaeawere not detected in either SHA format.

Fig. 2. Standard curves showing the response of the SHA for different targets using the 96-well plate (open circles, grey dashed line) andESP array formats (black circles, solid black line) for the targeted bacterioplankton groups. The concentration of target transcripts was variedin a constant background of non-target transcripts (see Experimental procedures). Probes are listed in Table 1.

1172 C. Preston et al.

© 2009 MBARIJournal compilation © 2009 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 11, 1168–1180

All BAC arrays (n = 7) were processed and imagedsuccessfully during the deployments and were similar inappearance to those processed in the lab (e.g. Fig. 3Cand D). Non-probe background values for the arraysduring the March deployment were slightly lower (average2153 � 345 counts) than in April (average 2497 � 342counts). These values are similar to the native samplepositive controls run prior to the deployment and 200–600CCD counts higher than backgrounds observed duringthe transcripts tests. Volumes sampled by the ESP duringthe deployments ranged from 225 to 600 ml (Table 3). Thedepth of the sample intake valve during the first deploy-

ment averaged 4.2 m (range 2.3–7.1 m) and the chloro-phyll concentration ranged from 3.8 to 24.36 mg m-3.There was a general warming trend during the twodeployments (Fig. 3E).

Positive reactions were observed for all capture probeson at least one array developed in situ (Table 3). Arraysindicated the presence and persistence of the marinealphaproteobacteria, SAR11 and G2 euryarchaea duringthe two deployments. The marine cyanobacteria probewas positive from Julian day 83 (JD83) through the end ofthe deployment, while that for G1 crenarchaea weaklypositive on JD83 and JD103. The sample collected on

Fig. 3. Custom 25 mm diameter probe arrays printed for use with the ESP (A–D) and environmental conditions during the March and AprilESP field deployments (E). The location of capture probes on DNA arrays for deployments (A) are as follows: Cytophaga-Flavobacteria (cf),marine alphaproteobacteria (a), SAR11 (11), G1 crenarchaea (i), G2 euryarchaea (ii), G3 euryarchaea (ch), and ‘+’ (Positive control,AlexComp) (Table 1). Empty white circles indicate non-printed areas. Arrays represent a filtered seawater negative control (B), apre-deployment positive control using 225 ml surface seawater (C), and the BAC5 array (JD106) from the deployed ESP (D). Results fromthe Cytophaga-Flavobacteria and marine G3 euryarchaea probes are not considered due to their cross reactivity (see Table 2). Depth,temperature and salinity (black and grey symbols respectively), and chlorophyll and percent transmission (black and grey symbolsrespectively) recorded during the field deployments. Contextual data up to JD86 was obtained from the CTD mounted on the ESP, and fromJD86–108 from the surface water CTD on the CIMT/M0 mooring. Horizontal lines indicate timing of the BAC arrays 1–5. No contextual datawas available for BAC6 and BAC7 arrays. Results from BAC1–7 arrays are presented in Table 3.

Autonomous detection of bacterioplankton 1173

© 2009 MBARIJournal compilation © 2009 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 11, 1168–1180

JD83 showed the presence of all five targeted BACgroups.

In addition to samples collected by the ESP, fivesamples were also collected manually from a boatnear the ESP mooring and were analysed using the96-well plate assay (Fig. 4, open symbols). Of the fivesamples obtained, two corresponded with ESP BACarray runs (JD83 and 103). Those two samples con-firmed the presence of groups detected on the arraysexcept for the weak G1 crenarchaea signal on JD103. Inthat case, the concentration of the sample used in theESP exceeded that of the 96-well plate assay (287 mlseawater ml-1 lysate versus 100 ml seawater ml-1 lysate,respectively).

Laboratory time series

Seven native samples from 5 m at station M0 inMonterey Bay were collected between JD73 and JD270,2006, and were analysed using the 96-well plate andESP SHA, and RT-qPCR. Samples obtained repre-sented microbial communities associated with varyingenvironmental conditions (Table 4). Arrays included thesame groups used during field deployments and bothSAR86-targeted capture probes. The same batch ofarrays and reagents was used for processing allsamples. Using the 96-well plate assay, positive signalswere observed on each day for marine alphaproteo-bacteria, SAR11 and G2 euryarchaea. Assays for G1crenarchaea, marine cyanobacteria, SAR86i–ii, andSAR86iii were below the limit of detection of the assayin at least one sample and never exceeded an A450 of0.5 (Fig. 4). SAR11 and marine cyanobacteria had a bio-modal distribution with peaks in abundance in the springand late summer. In contrast, marine alphaproteobacte-ria and the SAR86 subgroup i–ii peaked in late summer.G1 crenarchaea was detected only once during anupwelling event (low temperature, low chlorophyll sea-water; Table 4).

Sandwich hybridization assay capture probes forSAR11, G1 crenarchaea and G2 euryarchaea target asimilar phylogenetic clade and are located near theprimers and Taqman probe used in RT-qPCR analyses,so are well matched for comparison. For those groupsthe SHA and PCR analyses revealed similar trends(Fig. 4B–D). In contrast, the phylogenetic affinities of SHAcapture probes for marine alphaproteobacteria, SAR86and marine cyanobacteria differ significantly from theRT-qPCR assays. Consequently direct comparison ofresults of those two assays is problematic, but theRT-qPCR assays did confirm the presence of thosetargets as detected by SHA (data not shown). With twoexceptions, the ESP arrays revealed the presence of thesame BAC groups as were detected using the 96-wellTa

ble

3.S

umm

ary

ofco

ntro

land

2006

depl

oyed

ES

Par

rays

for

the

dete

ctio

nof

vario

usba

cter

iopl

ankt

ongr

oups

.a

Sam

ple

Sam

ple

date

Sam

ple

volu

me

(ml)

Mal

phS

AR

11M

arin

ecy

anob

acte

riaG

1cr

enar

chae

aG

2eu

ryar

chae

aB

ackg

roun

d

Neg

ativ

eN

A50

NV

SN

VS

NE

GN

VS

NV

S16

53�

67M

onte

rey

Wha

rfN

A22

561

06�

420

NE

GN

EG

NV

S42

84�

218

2346

�95

BA

C1

JD77

.640

053

88�

347

4502

�17

6N

EG

NE

G62

76�

194

2550

�34

3B

AC

2JD

80.4

275

6297

�50

141

19�

121

NE

GN

EG

4786

�14

619

33�

130

BA

C3

JD83

.427

577

33�

764

4299

�16

444

07�

339

2870

�10

158

05�

315

1974

�18

4B

AC

4JD

103.

457

544

81�

254

5063

�15

256

40�

405

2749

�10

448

87�

246

2105

�15

8B

AC

5JD

106.

460

056

00�

469

6146

�39

661

58�

382

NE

G73

48�

221

2470

�29

0B

AC

6JD

109.

422

549

84�

131

4596

�30

848

46�

550

NE

G46

34�

332

2470

�29

0B

AC

7JD

112.

457

566

58�

549

6270

�34

159

49�

204

NE

G65

19�

483

2940

�30

4

a.F

orex

ampl

eof

arra

yim

age

see

Fig

.2.

Julia

nda

y(J

D)

in20

06.

See

Fig

.3fo

ren

viro

nmen

talc

ondi

tions

for

BA

C1–

5.N

A,

not

appl

icab

le.

1174 C. Preston et al.

© 2009 MBARIJournal compilation © 2009 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 11, 1168–1180

assay, so long as the A450 was above 0.25 (Fig. 5). Rela-tive to the plate assay, the sample from JD200 returned afalse positive for marine GI crenarchaea and a false nega-tive for G2 euryarchaea.

Discussion

A major advantage of the SHA methodology is that itallows for simultaneous detection of a variety of target

Fig. 4. Results from the 96-well plate SHA of field samples (100 ml seawater ml-1 lysate) collected from Station M0 during monthly sampling(black circles) or during the March and April ESP deployments (open circles). In addition for SAR11, G1 crenarchaea and G2 euryarchaea, therRNA copy number ml-1 seawater (grey triangles) was also estimated using RT-qPCR from extracts made from the same lysate used in SHA.Environmental conditions for the monthly samples are presented in Table 4 and for the ESP deployments in Fig. 2.

Autonomous detection of bacterioplankton 1175

© 2009 MBARIJournal compilation © 2009 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 11, 1168–1180

sequences in near real-time without invoking nucleicacid purification or amplification. In this investigation, wetested whether this technique was extensible to ninecommon groups of marine bacterioplankton. Of those, fiveassays targeting different groups of bacteria were shownto be specific and two assays for archaea were deemeduseful (with the caveat of potentially cross reacting withG3 euryarchaea) based on in vitro transcribed 16S rRNAgenes and extracted RNA. Using those probes we provedthat direct detection of rRNA indicative of marinealphaproteobacteria, SAR11, SAR86 subgroups i–ii andsubgroup iii, marine cyanobacteria, G1 crenarchaea andG2 euryarchaea, collected from natural seawater, is fea-sible. Further, we demonstrated for the first time that suchmolecular signatures can be assessed remotely, in situ,using probe array technology and the ESP. Deployment ofthe instrument coincided with a relatively stable period, sothe observed shifts in microbial populations were minimal.However, the time series from samples collectedduring monthly CTD casts (Fig. 4) clearly shows that theSHA technique reveals major shifts in microbial rRNAcommunity structure that are in keeping with changingenvironmental conditions. Thus, the ESP thus offers a

novel means for accessing the ocean and microbes thatinhabit it.

Direct detection of marine BAC using SHA

Previous studies using SHA to detect RNA have primarilyutilized NaCl-based buffers, with or without formamide,with capture probes attached to either glass slide arrays(Small et al., 2001; Chandler et al., 2003; Chandler andJarrell, 2004) or magnetic beads (Spiro et al., 2000;Rowan et al., 2005). Direct detection of rRNA genes hasalso been accomplished using suspension arrays and aLuminex flow cytometer (Ellison and Burton, 2005). Themajority of these assays required target purificationand/or long incubations at high hybridization tempera-tures. Here, we used a GuSCN-based reagent that iseffective at disrupting cells, inactivates nucleases andpermits direct, specific hybridization at much lower tem-peratures compared with NaCl-based buffers (Van Nessand Chen, 1991). Detection limits using SHA in eitherformat are similar to other microarray-based detectiontechniques (Small et al., 2001; El Fantroussi et al., 2003;Peplies et al., 2004).

Table 4. Environmental conditions of monthly M0 5 m seawater samples.

Julian day (2006) Temperature (°C) Salinity (PSU) Transmission (%) Chlorophyll (mg m-3)

73 11.9 33.12 84.6 0.8107 12.9 32.47 76.2 2.0130 10.5 33.59 83.4 2.5158 11.4 33.79 50.7 26.3200 13.2 33.80 68.7 9.2229 14.3 33.55 75.7 5.0270 14.0 33.50 82.0 2.4

Fig. 5. Comparison of results obtained usingthe ESP array and 96-well plate SHAs onmatched field samples. Array signals abovebackground + 3SD (solid symbols) and below(open symbol) are shown for marinealphaproteobacteria (dash), SAR11 (circle),SAR86i–ii (up triangle), SAR86iii (downtriangle), marine cyanobacteria (diamond), G1crenarchaea (black squares) and G2euryarchaea (dark grey squares). Dashed lineindicates the limit of detection (A450 < 0.110)for the 96-well plate assay. Linear regressionsfor capture probes with least two fieldsamples with an A450 > 0.25 were as follows:marine alphaproteobacteria, y = 2674x + 2364(r2 = 0.891); S11, y = 4901x + 2332(r2 = 0.867); and G2 euryarchaea,y = 2681x + 1893 (r2 = 0.630).

1176 C. Preston et al.

© 2009 MBARIJournal compilation © 2009 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 11, 1168–1180

As theoretical predictions of probe specificity and Tmbased on sequence homology often differ from laboratorytests (Pozhitkov et al., 2006; Haywood et al., 2007),probes were tested experimentally. Capture-target-signalcombinations that worked well in the 96-well plate format,also worked well using the array format. Reaction condi-tions reported here were acceptable (i.e. specific), butwere not necessarily optimal for any given probe. Eachprobe had its own characteristic reactivity towards thetarget (Fig. 2, Table 2). Thus, similar signal intensitiesobtained using different capture probes do not indicate asimilar abundance of the target rRNA. Moreover, recordedsignal variations could reflect changes in the abundanceof organisms or cellular rRNA content (DeLong et al.,1989; Smith et al., 1992; Kemp et al., 1993), volume ofseawater collected, or some combination thereof. Non-specific hybridizations cannot be ruled out conclusivelywhen considering results of tests that employed nativesamples. Nevertheless, signals reported here are reason-able, as none of the field samples gave results thatexceed values tested in controlled laboratory tests usingdominant non-target clades. In addition, the distributionand population dynamics of the target organisms weresimilar to those observed previously (C. Preston, M.Suzuki and E. DeLong, unpublished data). Thus, theassays appear to reflect natural variations in the nativerRNA pool.

Environmental Sample Processor performanceand validation

We interpreted positive signals on the arrays as indicatingthe presence or absence of targeted clades, and proofthat the concepts underlying the detection methodologyare promising and worthy of further investigation. Noattempt was made to normalize arrays to account forvariations that arise outside of the actual abundance ofthe targeted sequence or to estimate relative changes inrRNA abundance of the various clades. Presently, abun-dance estimates for the BAC groups would have to rely onstandard curves generated by in vitro transcribed rRNA(Fig. 2) rather than native rRNA. In the future, the perfor-mance of the SHA will be characterized using cultureswhen available as well as natural samples. Given currentprotocols, we found that the ESP arrays were susceptibleto variable and sometimes elevated background with fieldsamples collected at different times, whereas the 96-wellplate SHA was very stable and appears insensitive tosample matrix. The reasons underlying this difference areunder investigation.

The best means of validating the performance of theESP was to apply different analytical techniques to a largevolume of lysate created from replicate samples. Attemptsto confirm SHA results using RT-qPCR were successful

for those assays whose probes targeted near identicalclades. Clearly, matching specificity of probes for a varietyof assays including SHA, RT-qPCR and qPCR assays willimprove opportunities for comparing performance of dif-ferent detection methods. However, discrepancies evenwith matched target clades are possible as the twoapproaches have their own biases and limitations.Regardless of the approach, the use and development ofthe sample archival function of the ESP will enhanceoptions for assessing quality of data obtained in real-timeusing the SHA arrays.

Conclusions

The 96-well and ESP array SHA formats accuratelyreflected the presence of various bacterial and archaealclades in both laboratory and field settings. To our knowl-edge this represents the first report of remote in situ DNAprobe-based detection of marine BAC. The requirementsassociated with obtaining and processing a sample makedata rates from the ESP slow compared with othersensors that yield almost nearly continuous chemical andphysical measurements (e.g. CTD or optical sensors).Such high-frequency measurements can be incorporatedinto an event detection capability to trigger samplingevents.

As with any methodology there are both advantagesand limitations. The SHA method is simple, employsreagents that are stable for extended periods at tempera-tures 4–25°C, and is highly amenable to automation.However, when there is a need to detect low copy numbertargets, then more demanding methodologies such asthose that use nucleic acid purification and amplificationmay be required (Suzuki et al., 2001; Casper et al., 2004;Short and Zehr, 2005). The choice of methodology willdepend on the specific target analytes, detecting require-ments, and questions being addressed.

Experimental procedures

In vitro T7 Transcription of 16S rRNAs

Selected 16S bacterial or archaeal rRNA genes were clonedfrom DNA extracted from seawater samples collected in 2004from station M0 (36.8342 N, 121.898 W), and transcribed invitro to produce synthetic rRNA for probe specificity studies.Cloned 16S rRNA genes were amplified using M13 forwardand reverse primers using the 1¥ reaction buffer, 0.2 mMdNTP, 3 mM MgCl2, 0.5 mM each primer, 0.025 U ml-1 Plati-num Taq (Invitrogen) and 20 ng plasmid. Reactions werecarried out on a ABI9700 (Applied Biosystems) using a tem-perature profile of 95°C for 5 min followed by 30 cycles of95°C for 30 s, 55°C for 30 s, and 72°C for 30 s, and lastly72°C for 7 min. Amplifications producing the expected sizefragment were used in transcription reactions (T7 or T3Ampliscribe Kit, Epicentre) according to the manufacturer’s

Autonomous detection of bacterioplankton 1177

© 2009 MBARIJournal compilation © 2009 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 11, 1168–1180

instructions. Reactions were treated with DNase for 15 minafter transcription. Transcripts were further purified usingTurbo DNA-free (Applied Biosystems).

Sample collection and preparation for SHA

Cultures of E. coli were grown overnight in Difco Luria–Bertani broth (Benton, Dickinson and Co.). Bacterial cell con-centrations were estimated by direct count on 0.2 mm GTBPpolycarbonate filters (Millipore, Bedford, MA) using an epif-luoresence microscope after DAPI staining (Porter and Feig,1980). Synnechococcus CCMP 1334 cells were provided byJ. Zehr.

Bacterial cultures or 200 ml native seawater samples werecollected using gentle vacuum (< 10 mmHg) onto 25 mm0.2 mm Durapore hydrophilic membranes (Millipore). Filterswere transferred to a 2 ml screw top polypropylene vial andused immediately or frozen in liquid N2 until use. Frozensamples were thawed to near room temperature beforeproceeding with lysis.

To homogenize samples, 1 ml of lysis buffer [3 M GuSCN,50 mM Tris, 15 mM EDTA, 2% Sarkosyl and 0.2% SDS (v/v),at pH 8.9; modified from 48, Saigene Corp.] was added toeach filter, vortexed, and incubated at 85°C for 10 min, with abrief vortexing midway through the heating. Thereafter, anequal volume of diluent [50 mM Tris, 15 mM EDTA, 2% Sar-kosyl and 0.2% SDS (v/v), at pH 8.9] was added, and thenfiltered through a 0.2 mm hydrophilic Durapore syringe filter(Millipore). To generate volumes > 1.75 ml, replicate sampleswere homogenized, diluted, combined and filtered. Theresulting lysate was used in the 96-well plate and/or ESParray SHA formats. For some samples, RNA was purifiedfrom an aliquot of the undiluted lysate (see below). In vitrorRNA transcripts or purified RNA from cultures were addeddirectly to lysis buffer and treated as above.

To determine that molecules captured were rRNA or rDNA,a 600 ml seawater sample was collected as above. Totalnucleic acids were then extracted (Massana et al., 1997). Thesample was split into three aliquots, each containing approxi-mately 15.4 mg total nucleic acid. Two aliquots were incu-bated for 1 h at 37°C with either 2 U DNase (Epicentre) or8 mg RNase (Promega). The DNase-treated aliquot was thenincubated at 70°C for 10 min to inactivate the enzyme. Thelast aliquot was left untreated. Volumes were adjusted to35 ml with RNase-free water after treatment. To each, 0.5 mllysis buffer was added, heated to 85°C, diluted for hybridiza-tion, and applied to the 96-well plate SHA.

Sandwich hybridization assay

The SHA employs capture and signal probes (Scholin et al.,1996). In this study, capture probes were group-specific whilesignal probes targeted universally conserved regions of 16SrRNA (Table 1). Capture and signal probes (Oligo’s Etc.,Eugene, OR) were handled and designed as described else-where (Greenfield et al., 2006; Haywood, 2007; Jones et al.,2008). Capture and Alex-comp (positive control) probes(Table 1) were printed on Predator® membrane (Pall Corp.,East Hills, NY; after Greenfield et al., 2006). Signal probesEub338 and Univ519ab were combined (each at 100 ng ml-1)

in 500 mM GuSCN, 50 mM Tris pH 8.55–8.65, 10 mM EDTA.For a positive control on arrays, 3.125 ng ml-1 Alex-alt-S wasadded (Greenfield et al., 2006). Sandwich hybridizationassays in the 96-well plate format were carried out usinga robotic processor (Saigene Corporation, Seattle, WA)(Scholin et al., 1998; Tyrrell et al., 2001; Goffredi et al., 2006;Greenfield et al., 2006). At least three replicate wells wereperformed for each sample and capture probe combination;the averaged A450 values are reported. Replicate samples foreach capture-signal probe combination showed less than a10% coefficient of variation.

Environmental Sample Processor deployment, arrayprocessing, and sample archiving

The ESP was deployed in Monterey Bay, CA, at Station M0(36.83 N, 121.90 W) March 16–27 (JD75–86) and again April10–23, 2006 (JD100–113), on a mooring that positions theinstrument subsurface (Scholin et al., 2008). For the firstdeployment, the ESP was fitted with a Seabird SBE 16+ CTD(Bellevue, WA) with fluorometer (Turner Cyclops-7) andtransmissometer (WetLABS Cstar) that provided environ-mental measurements every 20 min. During the seconddeployment the ESP CTD failed and temperature and salinitydata were obtained from the CIMT/M0 mooring (Ryan et al.,2005) that was located within 0.5 km of the ESP mooring.

Environmental Sample Processor deployments includedassays for harmful algal bloom species and phycotoxins,invertebrates and BAC (Greenfield et al., 2006; Jones et al.,2008). Only the results from the BAC arrays are presentedhere. A ‘BAC phase’ consisted of a series of operations thatincluded sample collection and lysis, dilution and filtration oflysate for hybridization, SHA probe array development, andsample archival. The ESP initiated sampling daily at 9AMlocal time. It was programmed to collect a 0.4 l sample ontoa 0.2 mm duropore filter during the March deployment and 1 lsample in April During sample filtration a ~10 psi differentialwas maintained using pressure transducers mounted aboveand below the filter puck until the volume specified wasreached. If the instrument could not filter 25 ml within 2.5 min,filtering was terminated and the sampled volume wasrecorded. The material retained on the filter was homog-enized with 1.1 ml 3 M GuSCN lysis buffer at 85°C for 10 min.The lysate was recovered, diluted 1:1 as above, passedthrough the collection puck once more and recovered. Thislysate was filtered through a second 0.2 mm Duropore beforepassage to the array. The remainder of the operationswere as previously described (Greenfield et al., 2008). Arrayimages (when available), data from the CTD and a log ofinstrument operations were transmitted to shore hourly usinga radio modem. The intensity of probe spots was determinedusing ImageJ v.1.36b (W. Rasband, NIH, Bethesda Mary-land) by defining a constant circular area from which pixelintensity was derived. Probe intensities reported here wereaveraged from five to seven replicate probe spots (Fig. 3A).

RNA extraction and RT-qPCR analysis

RNA was purified from field samples collected and lysed asabove. To 1 ml of undiluted lysate, NaOAc (pH 5.2) and

1178 C. Preston et al.

© 2009 MBARIJournal compilation © 2009 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 11, 1168–1180

ethanol were added to a final concentration of 0.4 M and 40%(v/v) respectively. The entire sample was then applied bycentrifugation in multiple aliquots to an RNeasy column(Qiagen, Valencia, CA). Subsequent washes and elutionwere as per the manufacturer’s recommendation. DNA con-tamination was eliminated using Turbo DNA-free. cDNA wassynthesized from 2 ml RNA using 2.5 ng ml-1 random primersand Superscript III (Invitrogen) as per manufacturer’s instruc-tion. RT reactions (2.5 ml) were used in group-specific qPCRassays as previously described (Suzuki et al., 2000; 2001;Shi, 2005).

Acknowledgements

We are grateful for the expertise and work of the engineers,technicians and machinists at MBARI for maintaining theinstrument. We thank J. Zehr for providing the Synechococ-cus culture, V. Orphan for providing the group III euryarchaealplasmid 1#6, and three anonymous reviewers for their edito-rial comments. We also thank the Moss Landing MarineLaboratories Small Boats Operation and the captains andcrews of the R/V Zephyr. This work was supported in part bygrants from the David and Lucille Packard Foundation toC.A.S., Keck Foundation to E.F.D. and C.A.S., NSF MicrobialObservatory grant to E.F.D. and Gordon and Betty MooreFoundation grant to C.A.S and E.F.D.

References

Babin, M., Cullen, J.J., Roesler, C.S., Donaghay, P.L., Dou-cette, G.J., Kahru, M., et al. (2005) New approaches andtechnologies for observing harmful algal blooms. Ocean-ography 18: 210–227.

Beja, O., Suzuki, M.T., Koonin, E.V., Aravind, L., Hadd, A.,Nguyen, L.P., et al. (2000) Construction and analysis ofbacterial artificial chromosome libraries from a marinemicrobial assemblage. Environ Microbiol 2: 516–529.

Casper, E.T., Paul, J.H., Smith, M.C., and Gray, M.(2004) Detection and quantification of the red tidedinoflagellate Karenia brevis by real-time nucleic acidsequence-based amplification. Appl Environ Microbiol 70:4727–4732.

Chandler, D.P., and Jarrell, A.E. (2004) Automated purifica-tion and suspension array detection of 16S rRNA from soiland sediment extracts by using tunable surface micropar-ticles. Appl Environ Microbiol 70: 2621–2631.

Chandler, D.P., Newton, G.J., Small, J.A., and Daly, D.S.(2003) Sequence versus structure for the direct detectionof 16S rRNA on planar oligonucleotide microarrays. ApplEnviron Microbiol 69: 2950–2958.

Daims, H., Bruhl, A., Amann, R., Schleifer, K.H., and Wagner,M. (1999) The domain-specific probe EUB338 is insuffi-cient for the detection of all Bacteria: development andevaluation of a more comprehensive probe set. Syst ApplMicrobiol 22: 434–444.

DeLong, E.F., Wickham, G.S., and Pace, N.R. (1989) Phylo-genetic stains: ribosomal RNA-based probes for the iden-tification of single cells. Science 243: 1360–1363.

Dubelaar, G.B., Gerritzen, P.L., Beeker, A.E., Jonker, R.R.,and Tangen, K. (1999) Design and first results of Cyto-

Buoy: a wireless flow cytometer for in situ analysis ofmarine and fresh waters. Cytometry 37: 247–254.

El Fantroussi, S., Urakawa, H., Bernhard, A.E., Kelly, J.J.,Noble, P.A., Smidt, H., et al. (2003) Direct profiling of envi-ronmental microbial populations by thermal dissociationanalysis of native rRNAs hybridized to oligonucleotidemicroarrays. Appl Environ Microbiol 69: 2377–2382.

Ellison, C.K., and Burton, R.S. (2005) Application of beadarray technology to community dynamics of marine phy-toplankton. Mar Ecol Prog Series 288: 75–85.

Fasham, M.J.R., Balino, B.M., Bowles, M.C., Anderson, R.,Archer, D., Bathmann, U., et al. (2001) A new vision ofocean biogeochemistry after a decade of the Joint GlobalOcean Flux Study (JGOFS). Ambio: 4–31.

Gentien, P., Lunven, M., Lehaitre, M., and Duvent, J.L. (1995)In-situ depth profiling of particle sizes. Deep Sea Res PartI 42: 1297–1312.

Goffredi, S.K., Jones, W.J., Scholin, C.A., Marin, R., 3rd, andVrijenhoek, R.C. (2006) Molecular detection of marineinvertebrate larvae. Mar Biotechnol 8: 149–160.

Gonzalez, J.M., and Moran, M.A. (1997) Numerical domi-nance of a group of marine bacteria in the alpha-subclassof the class Proteobacteria in coastal seawater. ApplEnviron Microbiol 63: 4237–4242.

Gonzalez, J.M., Whitman, W.B., Hodson, R.E., and Moran,M.A. (1996) Identifying numerically abundant culturablebacteria from complex communities: an example from alignin enrichment culture. Appl Environ Microbiol 62: 4433–4440.

Greenfield, D.I., Marin, R., III, Jensen, S., Massion, E.,Roman, B., Feldman, J., and Scholin, C. (2006) Applicationof the Environmental Sample Processor (ESP) for quanti-fying Pseudo-nitzschia australis using ribosomal RNA-targeted probes in sandwich and fluorescent in situhybridization. Limnol Oceanogr, Methods 4: 426–435.

Greenfield, D.I., R.M., III, Doucette, G.J., Mikulski, C.,Jensen, S., Roman, B., et al. (2008) Field applications ofthe second-generation Environmental Sample Processor(ESP) for remote detection of harmful algae: 2006–07.Limnol Oceanogr, Methods (in press).

Haywood, A.J., Scholin, C.A., Marin, R., III, Steidinger, K.A.,Heil, C., and Ray, J. (2007) Molecular detection of thebrevetoxin-producing dinoflagellate Karenia brevis andclosely related species using rRNA-targeted probes and asemiautomated sandwich hybridization assay. J Phycol 43:1271–1286.

Jones, W.J., Preston, C., Marin, R., III, Scholin, C.A., andVrijenhoek, R.C. (2008) A robotic molecular method forin situ detection of marine invertebrate larvae. Mol EcolResour 8: 540–550.

Karl, D.M., and Lukas, R. (1996) The Hawaii Ocean Time-series (HOT) program: Background, rationale and fieldimplementation. Deep Sea Res Part II 43: 129–156.

Kemp, P.F., Lee, S., and Laroche, J. (1993) Estimating thegrowth rate of slowly growing marine bacteria from RNAcontent. Appl Environ Microbiol 59: 2594–2601.

Kirkpatrick, G.J., Millie, D.F., Moline, M.A., and Schofield, O.(2000) Optical discrimination of a phytoplankton species innatural mixed populations. Limnol Oceanogr 45: 467–471.

Manz, W., Amann, R., Ludwig, W., Vancanneyt, M., andSchleifer, K. (1996) Application of a suite of 16S rRNA-

Autonomous detection of bacterioplankton 1179

© 2009 MBARIJournal compilation © 2009 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 11, 1168–1180

specific oligonucleotide probes designed to investigatebacteria of the phylum cytophaga-flavobacter-bacteroidesin the natural environment. Microbiology 142: 1097–1106.

Massana, R., Murray, A.E., Preston, C.M., and DeLong, E.F.(1997) Vertical distribution and phylogenetic characteriza-tion of marine planktonic Archaea in the Santa BarbaraChannel. Appl Environ Microbiol 63: 50–56.

Metfies, K., Töbe, K., Scholin, C., and Medlin, L.K. (2006)Laboratory and field applications of ribosomal RNA probesto aid the detection and monitoring of harmful algae. InEcology of Harmful Algae, vol. 189. Graneli, E., and Turner,J.T. (eds). Berlin Heidlelberg, Germany: Springer Verlag,pp. 311–326.

Morris, R.M., Rappe, M.S., Connon, S.A., Vergin, K.L.,Siebold, W.A., Carlson, C.A., and Giovannoni, S.J. (2002)SAR11 clade dominates ocean surface bacterioplanktoncommunities. Nature 420: 806–810.

National Oceanographic Partnership Program (NOPP)(2005) Sensing the Living Ocean: Report of the OceanEcogenomics Workshop. Washington DC URL http://www.neptune.washington.edu/documents/document.jsp?id=520

Paul, J.H., Scholin, C., van Den Engh, G., and Perry, M.J.(2007) In situ instrumentation. Oceanography 20: 58–66.

Peplies, J., Lau, S.C., Pernthaler, J., Amann, R., and Glock-ner, F.O. (2004) Application and validation of DNA micro-arrays for the 16S rRNA-based analysis of marinebacterioplankton. Environ Microbiol 6: 638–645.

Porter, K.G., and Feig, Y.S. (1980) The use of DAPI foridentifying and counting aquatic microflora. Limnol Ocean-ogr 25: 943–948.

Pozhitkov, A., Noble, P.A., Domazet-Loso, T., Nolte, A.W.,Sonnenberg, R., Staehler, P. et al. (2006) Tests of rRNAhybridization to microarrays suggest that hybridizationcharacteristics of oligonucleotide probes for species dis-crimination cannot be predicted. Nucleic Acids Res 34:e66.

Roman, B., Scholin, C., Jensen, S., Marin, R., III, Massion,E., and Feldman, J. (2005) The 2nd generation environ-mental sample processor: evolution of a robotic underwa-ter biochemical laboratory. In OCEANS 2005 MTS/IEEEConference. Washington DC: Marine Technology Society.

Rowan, A.K., Davenport, R.J., Snape, J.R., Fearnside, D.,Barer, M.R., Curtis, T.P., and Head, I.M. (2005) Develop-ment of a rapid assay for determining the relative abun-dance of bacteria. Appl Environ Microbiol 71: 8481–8490.

Ryan, J.P., Chavez, F.P., and Bellingham, J.G. (2005)Physical–biological coupling in Monterey Bay, California:topographic influences on phytoplankton ecology. Mar EcolProg Ser 287: 23–32.

Scholin, C.A., Buck, K.R., Britschgi, T., Cangelosi, G., andChavez, F.P. (1996) Identification of Pseudo-nitzschia aus-tralis (Bacillariophyceae) using rRNA-targeted probes inwhole cell and sandwich hybridization formats. Phycologia35: 190–197.

Scholin, C.A., Massion, E.I., Mellinger, E., Brown, M., Wright,D.E., and Cline, D.K. (1998) The development and appli-cation of molecular probes and novel instrumentation fordetection of harmful algae. Ocean Community Conference.Proceedings. Mar Technol. Soc, pp. 367–370.

Scholin, C.A., Massion, E.I., Wright, D., Cline, D., Mellinger,E., and Brown, M. (2001) Aquatic Autosampler Device. USpatent 6187530.

Scholin, C.A., Doucette, G.J., and Cambella, A.D. (2008)Prospects for developing automated systems for in situdetection of harmful algae and their toxins. In Real-TimeCoastal Observing Systems for Ecosystem Dynamics andHarmful Algal Blooms. Babin, M., Roesler, C.S. and Cullen,J.J. (eds). Paris, France: UNESCO Publishing, pp. 413–462.

Shi, Y. (2005) Measurement of in situ expression of proteor-hodopsin genes at the North Pacific Central Gyre StationALOHA. Msc. Thesis. University of Maryland, CollegePark.

Short, S.M., and Zehr, J.P. (2005) Quantitative analysis ofnifH genes and transcripts from aquatic environments.Methods Enzymol 397: 380–394.

Small, J., Call, D.R., Brockman, F.J., Straub, T.M., andChandler, D.P. (2001) Direct detection of 16S rRNA in soilextracts by using oligonucleotide microarrays. ApplEnviron Microbiol 67: 4708–4716.

Smith, G.J., Zimmerman, R.C., and Alberte, R.S. (1992)Molecular and physiological responses of diatoms to vari-able levels of irradiance and nitrogen availability: growth ofSkeletonema costatum in simulated upwelling conditions.Limnol Oceanogr 37: 989–1007.

Sosik, H.M., Olson, R.J., Neubert, M.G., Shalapyonok, A.,and Solow, A.R. (2003) Growth rates of coastal phy-toplankton from time-series measurements with a sub-mersible flow cytometer. Limnol Oceanogr 48: 1756–1765.

Spiro, A., Lowe, M., and Brown, D. (2000) A bead-basedmethod for multiplexed identification and quantitation ofDNA sequences using flow cytometry. Appl Environ Micro-biol 66: 4258–4265.

Suzuki, M.T., Taylor, L.T., and DeLong, E.F. (2000) Quantita-tive analysis of small-subunit rRNA genes in mixed micro-bial populations via 5′-nuclease assays. Appl EnvironMicrobiol 66: 4605–4614.

Suzuki, M.T., Preston, C.M., Chavez, F.P., and DeLong, E.F.(2001) Quantitative mapping of bacterioplankton popula-tions in seawater: field tests across an upwelling plume inMonterey Bay. Aquat Microb Ecol 24: 117–127.

Suzuki, M.T., Preston, C.M., Beja, O., de la Torre, J.R.,Steward, G.F., and DeLong, E.F. (2004) Phylogeneticscreening of ribosomal RNA gene-containing clones inBacterial Artificial Chromosome (BAC) libraries fromdifferent depths in Monterey Bay. Microb Ecol 48: 473–488.

Tyrrell, J.V., Bergquist, P.R., Bergquist, P.L., and Scholin,C.A. (2001) Detection and enumeration of Heterosigmaakashiwo and Fibrocapsa japonica (Raphidophyceae)using RNA-targeted oligonucleotide probes. Phycologia40: 457–467.

Van Ness, J., and Chen, L. (1991) The use of oligodeoxy-nucleotide probes in chaotrope-based hybridization solu-tions. Nucleic Acids Res 19: 5143–5151.

Wang, X., Chan, R.K., and Cheng, A.S. (2005) Underwatercytometer for in situ measurement of marine phytoplanktonby a technique combining laser-induced fluorescence andlaser Doppler velocimetry. Opt Lett 30: 1087–1089.

1180 C. Preston et al.

© 2009 MBARIJournal compilation © 2009 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 11, 1168–1180