The

influence

of

cultivation

methods

on

Shewanella

oneidensis

physiology

and

proteome

expression

High-throughput

analyses

that

are

central

to

microbial

systems

biology

and

ecophysiology

research

benefit

from

highly

homogeneous

and

physiologically

well-defined

cell

cultures

While

attention

has

focused

on

the

technical

variation

associated

with

high-throughput

technologies

biological

variation

introduced

as

a

function

of

cell

cultivation

methods

has

been

largely

overlooked

This

study

evaluated

the

impact

of

cultivation

methods

controlled

batch

or

continuous

culture

in

bioreactors

versus

shake

flasks

on

the

reproducibility

of

global

proteome

measurements

in

Shewanellaoneidensis

Variability

in

dissolved

oxygen

concentration

and

consumption

rate

metabolite

profiles

and

proteome

was

greater

in

shake

flask

than

controlled

batch

or

chemostat

cultures

Proteins

indicative

of

suboxic

and

anaerobic

growth

-LRB-

e.g.

fumarate

reductase

and

decaheme

c-type

cytochromes

-RRB-

were

more

abundant

in

cells

from

shake

flasks

compared

to

bioreactor

cultures

a

finding

consistent

with

data

demonstrating

that

aerobic

flask

cultures

were

deficient

due

to

poor

mass

transfer

kinetics

The

work

described

herein

establishes

the

necessity

of

controlled

cultivation

for

ensuring

highly

reproducible

and

homogenous

microbial

cultures

By

decreasing

cell

to

cell

variability

higher

quality

samples

will

allow

for

the

interpretive

accuracy

necessary

for

drawing

conclusions

relevant

to

microbial

systems

biology

research

Introduction

The

cultivation

of

microorganisms

has

been

performed

for

more

than

a

century

beginning

with

Louis

Pasteur

-LRB-

-RRB-

Robert

Koch

-LRB-

-RRB-

and

R.

J.

Petri

-LRB-

-RRB-

-LRB-

Sedgwick

Gest

-RRB-

with

ever

increasingly

sophisticated

methods

becoming

available

over

time

These

methods

range

from

using

undefined

medium

-LRB-

e.g.

boiled

meat

extracts

-RRB-

in

shake

flask

cultures

where

growth

rate

and

substrate

utilization

-LRB-

Narang

et

al.

-RRB-

as

well

as

proteomic

profiles

-LRB-

Valentine

et

al.

Wunschel

et

al.

-RRB-

can

vary

widely

to

defined

culturing

media

combined

with

state-of-the-science

bioreactors

-LRB-

Nethe-Jaenchen

and

Thauer

Vasconcelos

et

al.

Elias

et

al.

-RRB-

A

considerable

amount

of

physiological

-LRB-

Keltjens

et

al.

Dolla

et

al.

Elias

et

al.

-RRB-

and

high-throughput

functional

genomic

data

-LRB-

Beliaev

et

al.

Thompson

et

al.

Wan

et

al.

-RRB-

has

been

generated

from

microbial

samples

produced

using

shake

flask

batch

cultures

Although

results

may

be

statistically

defensible

the

inherent

short-comings

of

this

cultivation

technique

are

that

essential

parameters

directly

impacting

organism

physiology

are

poorly

described

and

difficult

to

control

These

parameters

include

nutrient

availability

metabolite

production

specific

growth

rate

and

poor

mixing

leading

to

cultural/environmental

heterogeneity

Poor

mass

transfer

kinetics

can

lead

to

unwanted

limitations

in

dissolved

gasses

for

use

by

the

organism

-LRB-

such

as

oxygen

or

hydrogen

-RRB-

and

the

buildup

of

gaseous

metabolic

byproducts

such

as

and

that

can

have

secondary

effects

on

cellular

metabolism

For

example

the

accumulation

of

dissolved

and

the

production

of

dissolved

organic

acids

can

significantly

alter

pH

in

poorly

buffered

systems

-LRB-

Ji

et

al.

Narang

et

al.

Mayville

et

al.

Miller

and

Bassler

-RRB-

Fluctuations

of

pH

in

bacterial

cultures

induce

physiological

responses

in

various

organisms

-LRB-

Snoep

et

al.

Blankenhorn

et

al.

Stancik

et

al.

Yohannes

et

al.

-RRB-

Hence

the

conditions

of

cultivation

at

the

beginning

of

growth

can

be

far

different

than

those

when

the

cells

are

harvested

for

analysis

Furthermore

the

time

of

cell

harvest

during

different

phases

of

growth

will

also

impact

biochemical

reaction

rates

-LRB-

Wright

and

Holland

-RRB-

and

the

complement

of

cellular

proteins

-LRB-

Lipton

et

al.

Wunschel

et

al.

-RRB-

In

actuality

the

functional

characteristics

and

relative

abundance

of

proteins

measured

are

derived

from

a

heterogeneous

cell

population

including

cells

in

various

stages

of

growth

that

are

potentially

expressing

a

range

of

metabolic

states

within

relatively

short

time

periods

We

argue

that

the

term

aerobic

shake

flask

therefore

is

more

an

operational

description

than

an

accurate

description

of

the

physiological

growth

conditions

In

bioreactors

all

relevant

physiological

parameters

including

pH

dissolved

oxygen

-LRB-

-RRB-

temperature

agitation

and

the

incoming

gas

flow

rate

and

composition

can

be

monitored

and

controlled

Because

the

nutrient

medium

can

be

of

variable

composition

and

added

to

the

bioreactor

at

discreet

rates

cells

can

be

cultured

with

varying

degrees

of

electron

donor/carbon

source

or

electron

acceptor

limitation

and

over

a

range

of

growth

rates

The

former

has

important

ramifications

given

the

effects

of

these

limitations

on

cell

physiology

while

being

able

to

address

the

issue

of

different

growth

rates

enables

studies

that

more

closely

mimic

the

variable

and

potentially

long

generation

times

typical

of

many

habitats

including

sedimentary

and

aquatic

environments

A

complete

mass

-LRB-

fermentation

-RRB-

balance

can

also

be

obtained

by

measuring

biogenic

gases

produced

during

the

cultivation

by

using

in-line

mass

spectrometry

-LRB-

MS

-RRB-

in

addition

to

the

byproducts

of

carbon

and

energy

source

metabolism

and

the

amount

of

produced

biomass

The

utilization

of

such

advanced

technologies

are

allowing

for

unprecedented

insights

into

the

metabolic

complexities

of

microbiological

systems

Controlled

cultivation

technologies

such

as

chemostats

and

turbidostats

minimize

culture

heterogeneity

through

continual

and

thorough

agitation

and

by

monitoring

and

controlling

all

culture

parameters

This

mixing

substantially

increases

the

mass

transfer

rates

of

both

the

influent

gas

stream

and

those

gases

resulting

from

microbial

metabolism

thus

creating

a

more

homogenous

gas

profile

throughout

the

culture

-LRB-

Pin

et

al.

-RRB-

and

reducing

the

gas

effect

on

pH.

Any

change

in

pH

that

occurs

during

cell

growth

due

to

non-gaseous

metabolic

by-products

is

compensated

for

by

monitoring

probes

and

the

addition

of

acid

or

base

-LRB-

typically

HCl

or

NaOH

-RRB-

via

computer

controlled

pumps

While

there

is

a

greater

upfront

capital

investment

for

bioreactors

the

investment

is

minor

relative

to

the

expense

associated

with

high-throughput

functional

genomics

techniques

Systems

biology

seeks

to

integrate

high-throughput

and

comprehensive

analytical

techniques

such

as

DNA

and

RNA

microarrays

proteomics

and

protein

interaction

analyses

and

metabolite

measurements

with

computational

biology

-LRB-

i.e.

modeling

-RRB-

to

describe

the

structure

of

the

system

and

responses

to

individual

perturbations

Such

knowledge

can

be

used

for

example

to

predict

systems

level

responses

to

environmental

changes/perturbations

In

our

opinion

a

key

element

of

systems

microbiology

research

is

the

use

of

controlled

cultivation

techniques

to

generate

samples

under

well-defined

conditions

where

variations

in

intra

as

well

as

inter-culture

variability

are

minimized

The

work

described

herein

was

designed

to

quantitatively

assess

the

relative

suitability

and

limitations

of

various

cultivation

approaches

for

systems

biology

research

Cells

cultivated

in

shake

flasks

controlled

batch

bioreactors

and

chemostats

were

subjected

to

targeted

as

well

as

comprehensive

proteomic

analysis

via

two-dimensional

gel

electrophoresis

-LRB-

Beliaev

et

al.

Abboud

et

al.

-RRB-

and

the

MS

based

accurate

mass

and

time

-LRB-

AMT

-RRB-

tag

approach

-LRB-

Conrads

et

al.

Smith

et

al.

-RRB-

to

determine

the

extent

of

biological

variation

Recent

reports

have

used

controlled

cultivation

to

determine

the

metabolic

flux

with

different

carbon

electron

donor

or

nitrogen

sources

-LRB-

Daran-Lapujade

et

al.

Kolkman

et

al.

Adams

et

al.

-RRB-

However

this

is

the

first

report

documenting

the

metabolic

differences

with

varied

electron-acceptor

between

cultures

Finally

while

others

have

utilized

steady

state

cultures

and

cite

advantages

similar

to

those

mentioned

above

this

is

to

our

knowledge

the

first

report

that

assesses

and

quantifies

the

effect

of

cultivation

methods

on

microbial

physiology

and

cell

proteome

Materials

and

methods

Materials

Acetonitrile

and

methanol

were

purchased

from

Fisher

Scientific

-LRB-

Fair

Lawn

NJ

USA

-RRB-

Urea

dithiothreitol

-LRB-

DTT

-RRB-

and

were

obtained

from

Sigma-Aldrich

-LRB-

St

Louis

MO

USA

-RRB-

while

thiourea

trifluoroacetic

acid

-LSB-

-LRB-

-RRB-

dimethylammonio

-RSB-

and

ammonium

bicarbonate

were

obtained

from

Aldrich

Chemical

Company

Inc.

-LRB-

Milwaukee

WI

USA

-RRB-

Sequencing

grade

modified

trypsin

was

purchased

from

Promega

-LRB-

Madison

WI

USA

-RRB-

while

ammonium

formate

was

obtained

from

Fluka

-LRB-

St

Louis

MO

USA

-RRB-

Water

was

purified

using

a

Barnstead

Nanopure

Infinity

water

purification

system

-LRB-

Dubuque

IA

USA

-RRB-

Cell

cultivation

and

harvesting

Shake

flask

cultures

Shewanella

oneidensis

-LRB-

ATCC

-RRB-

were

cultivated

in

a

defined

medium

as

described

elsewhere

-LRB-

Elias

et

al.

-RRB-

except

that

mM

lactate

was

used

instead

of

mM

and

the

PIPES

concentration

was

increased

to

mM

since

there

was

no

pH

control

Shake

flask

cultures

-LRB-

l

-RRB-

were

grown

aerobically

at

°C

with

constant

shaking

at

rpm

Duplicate

cultures

were

inoculated

at

intervals

over

h

After

an

additional

h

of

incubation

the

optical

density

-LRB-

OD

-RRB-

pH

and

were

recorded

and

culture

samples

for

organic

acid

analysis

were

taken

via

syringe

filtered

-LRB-

μm

-RRB-

and

stored

at

°C

until

analyzed

The

cultures

that

had

grown

for

h

were

in

the

late

log

phase

of

growth

and

were

then

harvested

as

previously

described

-LRB-

Elias

et

al.

-RRB-

First

ml

of

culture

was

centrifuged

and

the

resulting

pellet

dehydrated

for

dry

weight

biomass

measurement

-LRB-

moisture

analyzer

Sartorius

Inc.

-RRB-

Then

the

remaining

cells

were

pelleted

by

centrifugation

-LRB-

g

min

°C

-RRB-

The

resulting

pellets

and

approximately

ml

of

the

supernatant

were

transferred

to

cryovials

-LRB-

ml

-RRB-

and

centrifuged

-LRB-

g

min

°C

-RRB-

After

removal

of

the

supernatant

the

cryovials

containing

packed

cell

pellets

were

immediately

stored

at

°C

for

later

analysis

by

and

AMT

MS.

Controlled

batch

cultures

Cells

were

cultured

in

controlled

batches

using

Bioflow

model

reactors

-LRB-

New

Brunswick

Scientific

Edison

NJ

USA

-RRB-

For

the

direct

proteome

comparison

lactate

was

used

at

mM

as

in

the

shake

flasks

but

the

PIPES

concentration

was

lowered

to

mM

since

pH

control

was

present

Cells

were

grown

with

oxygen

at

of

dissolved

saturation

-LRB-

-RRB-

using

a

combination

of

air

and

gas

while

pH

was

constantly

maintained

at

by

the

addition

of

N

HCl

or

N

NaOH

The

temperature

was

a

constant

°C

and

the

reactors

were

stirred

at

rpm

to

minimize

mass

transfer

limitations

of

and

Samples

were

taken

for

organic

acid

analysis

as

described

above

until

the

late

log

phase

of

growth

at

At

this

point

cells

were

harvested

for

the

analyses

as

described

above

for

the

shake

flasks

Chemostat

cultures

Steady

state

cultures

were

attained

using

Bioflow

model

reactors

-LRB-

New

Brunswick

Scientific

Edison

NJ

USA

-RRB-

with

the

same

medium

and

identical

parameters

and

controls

as

described

for

the

controlled

batch

cultures

Once

the

optical

density

-LRB-

OD

-RRB-

was

approximately

fresh

medium

was

pumped

into

the

reactor

at

a

dilution

rate

of

h

and

a

constant

l

volume

maintained

Culturing

continued

until

a

constant

OD

and

acid

addition

rate

-LRB-

i.e.

steady

state

-RRB-

was

attained

Samples

for

organic

acids

were

collected

periodically

and

the

cells

harvested

as

above

Organic

acid

quantitation

The

organic

acids

lactate

acetate

pyruvate

formate

and

fumarate

were

measured

using

isocratic

flow

-LRB-

ml/min

-RRB-

with

both

high

performance

liquid

chromatography

-LRB-

HPLC

-RRB-

and

ion

chromatography

-LRB-

IC

-RRB-

The

HPLC

-LRB-

Agilent

series

HPLC

with

a

mm

Rezex

organic

acid

column

-LRB-

Phenomenex

Torrance

CA

USA

-RRB-

°C

min

run

time

-RRB-

used

a

dilute

acid

mobile

phase

of

N

Quantification

was

accomplished

by

injecting

the

sample

-LRB-

μl

-RRB-

and

using

either

a

diode

array

detector

or

a

fixed

wavelength

detector

at

nm

-LRB-

nm

bandwidth

-RRB-

Samples

were

prepared

by

filtering

ml

-LRB-

μm

-RRB-

and

acidifying

with

μl

of

N

Lactate

had

a

retention

time

of

min

and

detection

limit

of

mM

while

pyruvate

acetate

and

formate

retention

times

were

and

min

respectively

with

a

detection

limit

each

of

mM

For

IC

-LRB-

Dionex

-RRB-

analysis

was

performed

for

the

above

organic

acids

as

previously

described

-LRB-

Senko

et

al.

Elias

et

al.

-RRB-

proteomic

analysis

Frozen

cell

pellets

were

mixed

with

vols

of

a

solution

containing

M

urea

ampholytes

-LRB-

pH

BioRad

-RRB-

and

Nonidet

-LRB-

a

nonionic

detergent

-RRB-

The

cell

lysate

was

then

ultracentrifuged

-LRB-

g

min

-RRB-

using

a

Beckman

tabletop

ultracentrifuge

and

the

soluble

denatured

proteins

were

recovered

in

supernatants

from

centrifugation

Protein

concentrations

were

determined

using

a

modification

of

the

Bradford

protein

assay

-LRB-

Ramagli

and

Rodriguez

-RRB-

Aliquots

of

sample

containing

μg

of

protein

were

separated

in

the

first

dimension

by

isoelectric

focusing

using

polyacrylamide

gels

containing

pH

with

pH

carrier

ampholytes

-LRB-

Anderson

and

Anderson

-RRB-

After

V-h

the

first-dimension

gels

were

equilibrated

with

sodium

dodecyl

sulfate

-LRB-

SDS

-RRB-

and

the

proteins

were

separated

by

SDS-polyacrylamide

gel

electrophoresis

as

described

-LRB-

O'Farrell

-RRB-

using

a

linear

gradient

of

acrylamide

-LRB-

Anderson

and

Anderson

-RRB-

Proteins

were

then

detected

by

staining

with

silver

nitrate

-LRB-

Giometti

et

al.

-RRB-

The

images

were

digitized

using

an

scanner

interfaced

with

a

VAX

workstation

The

images

were

then

transferred

to

a

PC

converted

to

TIFF

format

and

then

processed

for

spot

detection

and

pattern

matching

using

the

Progenesis

software

-LRB-

Nonlinear

USA

-RRB-

One

image

was

used

as

a

reference

pattern

for

the

experiment

All

patterns

in

the

experiment

were

matched

to

the

reference

pattern

so

that

the

protein

spots

were

given

identification

numbers

Statistical

analysis

of

the

relative

abundance

of

each

matched

protein

spot

across

the

data

set

was

done

using

a

two-tailed

Student

's

t-test

as

previously

described

-LRB-

Giometti

and

Taylor

-RRB-

Proteins

to

be

identified

were

cut

from

two

to

three

replicate

gels

stained

with

Coomassie

Blue

-LRB-

approximately

μg

of

protein

was

loaded

on

each

gel

-RRB-

and

the

proteins

were

digested

in-gel

with

trypsin

-LRB-

Promega

sequence-grade

trypsin

ng/μg

-RRB-

The

resulting

peptides

were

eluted

from

the

gel

pieces

by

extracting

three

times

first

with

equal

parts

of

mM

ammonium

bicarbonate

and

acetonitrile

then

twice

with

equal

parts

of

-LRB-

v/v

-RRB-

formic

acid

and

acetonitrile

The

eluted

tryptic

peptides

were

desalted

and

concentrated

with

a

commercial

ZipTip

pipette

tip

-LRB-

Millipore

-RRB-

Peptide

samples

were

then

loaded

onto

a

μm

fused

silica

capillary

-LRB-

FSC

-RRB-

column

packed

with

μm

POROS

packing

material

-LRB-

PE

Biosystem

-RRB-

at

a

length

of

cm

Peptides

were

separated

with

a

linear

gradient

of

solvent

containing

acetonitrile

and

acetic

acid

and

then

entered

into

an

LCQ

ion

trap

mass

spectrometer

-LRB-

Finnigan

MAT

-RRB-

Tandem

mass

spectra

were

automatically

collected

under

computer

control

during

the

LC

MS

runs

MS/MS

spectra

were

then

directly

subjected

to

SEQUEST

database

searches

-LRB-

Eng

et

al.

Sadygov

et

al.

-RRB-

by

correlating

experimental

MS/MS

spectra

to

predicted

protein

sequences

in

the

S.

oneidensis

open

reading

frame

database

Mass

spectrometry

proteomic

analysis

Cell

lysis

and

tryptic

digestion

Whole

cell

lysis

was

achieved

by

bead

beating

while

tryptic

digestion

was

achieved

with

sequencing

grade-modified

trypsin

as

previously

described

-LRB-

Elias

et

al.

-RRB-

and

digested

for

h

at

°C

using

a

-LRB-

w/w

-RRB-

trypsin-to-protein

ratio

Samples

were

quick

frozen

in

liquid

and

stored

at

°C

until

analyzed

Protein

concentration

was

determined

by

the

BCA

assay

kit

-LRB-

Pierce

Rockford

IL

USA

-RRB-

Mass

spectrometric

analysis

The

capillary

LC

system

used

was

described

previously

-LRB-

Elias

et

al.

-RRB-

using

psi

reversed-phase

packed

capillaries

at

μl/min

-LRB-

μm

i.d.

μm

o.d.

Polymicro

Technologies

-RRB-

-LRB-

Shen

et

al.

-RRB-

with

two

mobile

phase

solvents

consisting

of

acetic

acid

and

TFA

in

water

-LRB-

A

-RRB-

and

TFA

in

water

-LRB-

B

-RRB-

The

LTQ-FT

data

was

processed

using

the

PRISM

data

analysis

system

as

described

previously

for

LC-FTICR-MS

data

-LRB-

Elias

et

al.

-RRB-

Since

the

separation

systems

for

both

the

LTQ-FT

and

the

LCQ

analyses

were

identical

peptide

confirmation

was

based

on

both

the

calculated

-LRB-

from

the

mass

tag

database

-RRB-

and

measured

mass

-LRB-

from

the

FTICR

analysis

-RRB-

of

the

peptide

matching

to

within

ppm

and

the

elution

times

matching

to

within

All

samples

were

analyzed

as

previously

described

-LRB-

Lipton

et

al.

Elias

et

al.

-RRB-

using

an

LTQ-FT

-LRB-

Thermo-Finnigan

MI

USA

-RRB-

The

mass

spectrometer

measurements

were

analyzed

with

SEQUEST

-LRB-

Eng

et

al.

-RRB-

using

our

current

database

as

previously

described

-LRB-

Elias

et

al.

-RRB-

Mass

spectra

were

acquired

with

approximately

resolution

The

peptide

identifications

were

determined

using

the

spatially

localized

confidence

scoring

-LRB-

SLiC

-RRB-

algorithm

-LRB-

Norbeck

et

al.

-RRB-

that

incorporates

a

number

of

constraints

and

estimates

the

confidence

of

each

peptide

identification

by

yielding

a

score

of

Recent

work

in

our

laboratory

shows

that

a

SLiC

score

of

at

least

is

sufficiently

rigorous

-LRB-

unpublished

-RRB-

and

is

used

herein

Further

at

least

one

high-confidence

unique

peptide

-LRB-

i.e.

mapping

to

only

one

possible

parent

protein

-RRB-

and

a

total

of

two

peptides

was

required

for

protein

identification

in

each

analysis

Results

Effect

of

cultivation

method

on

growth

and

metabolism

Duplicate

cultures

were

grown

in

-LRB-

-RRB-

shake

flasks

-LRB-

uncontrolled

batch

-RRB-

-LRB-

-RRB-

controlled

batch

and

-LRB-

-RRB-

continuous

flow

reactors

operating

as

steady

state

chemostats

all

with

as

the

sole

terminal

electron

acceptor

Shake

flask

cultures

exhibited

an

extended

lag

phase

-LRB-

approximately

h

-RRB-

which

compared

with

the

shorter

lag

phase

-LRB-

-LRB-

h

-RRB-

in

controlled

batch

cultures

-LRB-

Fig.

b

-RRB-

The

extended

lag

and

slow

growth

rates

-LRB-

-LRB-

h

-RRB-

in

shake

flasks

correlated

with

elevated

concentration

that

gradually

decreased

from

nearly

of

air

saturation

to

approximately

of

air

saturation

-LRB-

Fig.

-RRB-

Below

growth

rates

increased

to

approximately

h

which

is

close

to

the

growth

rate

observed

for

controlled

batch

culture

operated

at

DOT

of

air

saturation

-LRB-

Fig.

b

-RRB-

By

definition

chemostat

cultures

operating

at

steady

state

were

maintained

at

a

constant

growth

rate

-LRB-

h

-RRB-

and

throughout

the

course

of

the

experiment

-LRB-

data

not

shown

-RRB-

Fig.

comparison

of

duplicate

uncontrolled

versus

duplicate

controlled

-LRB-

right

-RRB-

batch

culturing

of

S.

oneidensis

a

The

inconsistency

in

decreasing

-LRB-

dark

filled

diamond

open

diamond

-RRB-

and

growth

-LRB-

dark

filled

triangle

open

triangle

-RRB-

in

the

uncontrolled

cultures

is

apparent

when

compared

to

those

for

controlled

batch

cultures

-LRB-

b

-RRB-

using

the

same

symbols

This

variation

is

reflected

in

the

-LRB-

c

d

-RRB-

organic

acid

profiles

The

lactate

-LRB-

dark

filled

diamond

open

diamond

-RRB-

pyruvate

-LRB-

dark

filled

square

open

square

-RRB-

and

acetate

-LRB-

dark

filled

triangle

open

triangle

-RRB-

all

exhibited

more

similar

profiles

between

culture

replicates

in

the

controlled

batches

Despite

the

similarity

in

growth

rates

between

the

duplicate

flask

cultures

-LRB-

Fig.

-RRB-

the

decrease

in

i.e.

the

consumption

rates

were

dissimilar

These

differences

correlated

with

variations

in

the

organic

acid

concentration

profiles

in

shake

flask

cultures

-LRB-

Fig.

-RRB-

Although

the

order

of

appearance

and

disappearance

of

the

organic

acids

was

the

same

between

the

flask

culture

replicates

the

rate

of

lactate

consumption

varied

significantly

as

did

the

transient

concentrations

of

pyruvate

and

acetate

The

differences

in

these

profiles

presumably

reflect

the

metabolic

variability

between

cultures

at

any

given

point

along

the

growth

curve

and

may

result

from

increased

variability

in

the

mass

transfer

kinetics

in

poorly

mixed

cultures

compared

to

controlled

batch

In

comparison

maintaining

a

constant

concentration

in

the

controlled

batch

cultures

resulted

in

a

shorter

lag

phase

with

nearly

identical

growth

rates

-LRB-

Fig.

-RRB-

Cells

in

well-mixed

controlled

batch

cultures

were

continuously

exposed

to

a

constant

concentration

as

opposed

to

variable

concentrations

typical

in

aerobic

flask

cultures

that

in

fact

become

as

cell

densities

increase

due

to

poor

mass

transfer

rates

This

resulted

in

much

greater

consistency

in

organic

acid

concentration

profiles

between

the

replicates

-LRB-

Fig.

-RRB-

Relating

cultivation

data

to

metabolic

activity

Not

only

does

controlled

cultivation

result

in

more

consistent

metabolic

activities

within

and

between

cultures

as

shown

above

but

the

very

nature

of

highly

instrumented

and

controlled

cultivation

provides

important

characterization

data

that

help

to

relate

cellular

metabolism

with

the

environmental

conditions

experienced

by

the

culture

In

a

controlled

batch

experiment

designed

to

illustrate

these

relationships

cell

growth

-LRB-

Fig.

-RRB-

was

correlated

with

the

consumption

and

the

amount

of

acid

needed

to

maintain

a

constant

pH

-LRB-

Fig.

-RRB-

as

well

as

the

organic

acid

profiles

-LRB-

Fig.

-RRB-

Figure

illustrates

the

increase

in

optical

density

measured

during

the

course

of

the

experiment

The

solid

circles

indicate

optical

density

of

samples

taken

directly

from

the

culture

while

solid

squares

represent

optical

density

measurements

on

the

same

samples

after

the

addition

of

μM

Na-EDTA

This

treatment

destabilized

cell

aggregates

-LRB-

flocs

-RRB-

by

chelating

calcium

which

can

cross-link

polysaccharides

in

extracellular

polymeric

substances

The

ratio

of

flocculated

deflocculated

cultures

is

termed

the

flocculation

index

-LRB-

FCI

-RRB-

and

is

represented

by

the

open

triangles

Hence

flocculation

indices

above

indicate

the

presence

of

cell

aggregates

while

values

at

or

slightly

below

indicate

the

absence

of

flocculated

cells

The

cultures

lacked

flocculated

cells

during

the

first

h

of

growth

-LRB-

Fig.

-RRB-

Acid

addition

-LRB-

Fig.

red

line

-RRB-

during

this

period

directly

tracked

increases

in

optical

density

Lactate

served

as

the

primary

electron

donor

and

carbon

source

and

decreased

while

pyruvate

and

acetate

accumulated

in

the

medium

-LRB-

Fig.

-RRB-

Fig.

of

the

-LRB-

a

-RRB-

growth

-LRB-

b

-RRB-

controlled

parameters

and

-LRB-

c

-RRB-

organic

acid

profile

for

S.

oneidensis

cells

grown

in

controlled

batch

to

indicate

consequent

shifts

in

metabolism

a

The

growth

of

flocculated

-LRB-

dark

filled

square

after

EDTA

addition

-RRB-

and

non-flocculated

cells

-LRB-

dark

filled

circle

-RRB-

were

initially

compared

to

profile

the

degree

of

flocculation

-LRB-

dark

filled

triangle

-RRB-

during

growth

When

coordinated

with

changes

in

-LRB-

b

-RRB-

pH

and

acid

addition

and

-LRB-

c

-RRB-

the

appearance

and

exhaustion

of

the

organic

acids

lactate

-LRB-

dark

filled

diamond

-RRB-

pyruvate

-LRB-

dark

filled

square

-RRB-

acetate

-LRB-

dark

filled

triangle

-RRB-

changes

in

metabolism

can

be

identified

These

include

the

spike

-LRB-

solid

arrow

-RRB-

signaling

lactate

exhaustion

with

the

concomitant

increase

in

cell

floculation

as

well

as

the

decreased

acid

addition

rate

-LRB-

broken

arrow

-RRB-

showing

major

carbon

source

exhaustion

and

the

concomitant

disappearance

of

flocculation

The

point

at

which

lactate

was

completely

consumed

-LRB-

h

solid

gray

arrow

-RRB-

corresponded

with

a

transient

spike

in

-LRB-

Fig.

blue

line

-RRB-

This

peak

resulted

from

a

rapid

decrease

in

consumption

rate

and

a

delayed

response

of

the

control

loop

used

by

the

reactor

to

maintain

constant

values

The

coordinated

decrease

in

respiration

rate

and

the

complete

consumption

of

lactate

as

the

primary

electron

donor

also

correlated

with

the

onset

of

flocculation

as

indicated

by

an

increased

FCI

The

organic

acid

analyses

clearly

indicated

that

pyruvate

assumed

the

role

of

primary

electron

donor

with

no

apparent

change

in

acetate

concentration

Cell

flocculation

peaked

at

h

just

as

the

last

of

detectable

pyruvate

was

consumed

The

subsequent

decrease

in

the

FCI

was

bimodal

The

initial

decrease

in

the

FCI

corresponded

to

a

slow

decline

in

alkalinity

production

as

measured

by

decreasing

acid

addition

to

maintain

pH.

When

the

concentration

of

acetate

fell

to

mM

and

the

FCI

entered

its

second

phase

and

decreased

sharply

acid

addition

increased

dramatically

This

was

likely

a

result

of

both

the

decrease

in

microbial

metabolism

and

the

aeration

of

the

bioreactor

During

active

growth

lactate

will

be

mineralized

to

both

and

bicarbonate

with

the

being

stripped

from

the

culture

via

aeration

and

bicarbonate

modestly

increasing

the

alkalinity

of

the

culture

As

the

metabolic

rate

of

the

culture

decreases

due

to

nutrient

limitation

and

bicarbonate

generation

will

also

decrease

but

the

will

continue

to

be

removed

from

the

system

while

increasing

amounts

of

bicarbonate

will

form

carbonic

acid

and

This

will

result

in

a

net

loss

of

protons

from

the

system

thus

increasing

the

pH

and

cause

the

increased

addition

of

acid

to

the

culture

Correlating

protein

expression

with

culture

conditions

Significant

differences

were

observed

between

the

proteomes

of

cells

from

uncontrolled

aerobic

flasks

and

controlled

aerobic

batch

reactors

when

analyzed

by

and

MS.

In

general

proteins

predicted

to

be

expressed

in

cells

growing

under

low

oxygen

tensions

or

anaerobically

-LSB-

e.g.

fumarate

reductase

-LRB-

Myers

and

Myers

Maier

et

al.

-RSB-

OmpW

glutamine

synthase

decaheme

cytochrome

c

MtrA

MtrC

and

OmcA

-LRB-

Beliaev

et

al.

Fang

et

al.

-RRB-

were

exclusively

expressed

or

detected

with

increased

abundance

in

samples

from

shake

flasks

when

compared

to

those

from

controlled

batch

and

chemostat

cultures

Fumarate

reductase

-LRB-

spot

-RRB-

an

enzyme

required

for

anaerobic

growth

with

fumarate

-LRB-

Maier

et

al.

-RRB-

was

detected

in

high

abundance

in

patterns

of

lysate

proteins

from

cells

grown

in

the

flask

cultures

but

was

not

detected

in

samples

from

aerobic

controlled

batch

reactors

-LRB-

Fig.

-RRB-

Similarly

the

outer

membrane

protein

OmpW

-LRB-

spot

-RRB-

and

a

hypothetical

protein

-LRB-

spot

-RRB-

were

present

in

patterns

of

proteins

from

flask

culture

lysates

but

not

detected

in

aerobic

controlled

batch

reactors

A

significant

increase

in

the

number

of

peptides

corresponding

to

OmpW

and

fumarate

reductase

-LRB-

and

higher

respectively

in

the

flask

samples

compared

to

controlled

batch

samples

-RRB-

was

observed

in

the

MS-based

AMT

tag

analyses

of

these

lysates

-LRB-

Table

-RRB-

confirming

the

results

It

is

presently

unclear

why

OmpW

and

the

hypothetical

protein

abundances

increased

in

low

but

our

laboratory

has

observed

this

trend

in

the

former

protein

several

times

-LRB-

unpublished

-RRB-

In

addition

peptides

representing

the

multiheme

cytochromes

MtrA

MtrC

and

OmcA

and

outer

membrane

β-barrel

protein

MtrB

were

observed

in

two

to

fivefold

higher

abundance

in

the

AMT

tag

analysis

of

samples

from

shake

flasks

versus

those

from

controlled

batch

cultures

These

observations

strongly

suggest

the

use

of

shake

flask

cultures

to

assess

changes

in

protein

expression

patterns

related

to

aerobic

versus

anaerobic

metabolism

could

yield

inaccurate

results

Fig.

gel

electrophoresis

patterns

of

whole

cell

lysate

proteins

from

S.

oneidensis

grown

in

shake

flasks

or

continuous

batch

cultures

The

proteins

indicated

by

spot

number

correspond

to

those

identified

as

varying

with

statistical

significance

between

the

two

different

culture

methods

-LRB-

see

Table

-RRB-

The

gel

images

are

oriented

with

the

basic

proteins

to

the

right

acidic

proteins

to

the

left

high

molecular

weight

toward

the

top

and

low

molecular

weight

toward

the

bottom

Flask

shake

flask

cultures

-LRB-

two

replicate

experiments

-RRB-

CB

controlled

batch

cultures

-LRB-

two

replicate

experiments

-RRB-

Table

protein

detection

between

flask

and

controlled

batch

cultures

as

determined

by

and

MSORFProtein

nameSpot

flaskAvg

CBP-valueFlask/CB

ratioAvg

flaskAvg

CBFlask/CB

stress

protein

synthetase

type

cytochrome

c

cytochrome

c

cytochrome

c

ORF

open

reading

frame

-LRB-

-RRB-

Protein

name

annotation

for

open

reading

frame

-LRB-

-RRB-

Spot

number

spot

number

assigned

by

Progenesis

software

using

images

shown

in

Figs.

and

Avg

flask

average

integrated

spot

density

in

images

-LRB-

images

per

sample

-RRB-

from

shake

flask

samples

Avg

CB

average

integrated

spot

density

in

images

-LRB-

images

per

sample

-RRB-

from

continuous

batch

culture

samples

P-valueP-value

from

two-tailed

Student

's

t-test

analysis

of

average

integrated

density

values

Flask/CB

ratio

ratio

of

average

integrated

density

values

for

flask

and

continuous

batch

culture

samplesaNote

that

the

difference

in

spot

is

a

function

of

the

variability

in

the

protein

between

the

two

flask

cultures

In

Flask

the

average

integrated

density

was

with

a

coefficient

of

variation

-LRB-

CV

-RRB-

of

whereas

in

Flask

the

average

integrated

density

was

with

a

CV

of

The

represents

the

averaging

of

integrated

densities

from

all

of

the

patterns

from

these

two

flasks

together

with

a

resulting

CV

of

bThe

average

MS

abundance

data

the

standard

deviation

resulting

from

triplicate

analysis

of

each

biological

sample

Chemostats

provide

enhanced

experimental

consistency

Chemostat

cultures

provide

the

highest

level

of

control

of

any

known

cultivation

technology

-LRB-

Monod

Novick

and

Szilard

Wimpenny

-RRB-

To

evaluate

the

reproducibility

of

chemostat

cultures

duplicate

bioreactors

were

operated

in

steady

state

with

S.

oneidensis

under

as

above

and

the

growth

and

carbon

metabolism

parameters

were

measured

Each

of

the

aerobic

cultures

attained

an

initial

maximum

optical

density

of

by

h

and

eventually

achieved

a

steady

state

cell

density

at

-LRB-

nm

-RRB-

-LRB-

Fig.

-RRB-

The

two

reactors

were

highly

similar

in

terms

of

growth

and

acid

addition

rates

as

well

as

organic

acid

concentrations

at

the

time

of

sampling

of

h.

Lactate

acetate

fumarate

and

succinate

were

all

below

detectable

limits

suggesting

that

the

cultures

were

in

fact

carbon-limited

during

steady

state

growth

Pyruvate

was

present

in

both

chemostatic

cultures

at

mM

Dry

weight

biomass

measurements

confirmed

the

highly

similar

cell

densities

of

mg/l

with

only

a

variance

between

the

reactors

In

comparison

the

duplicate

controlled

batch

and

shake

flask

cultures

used

in

this

study

yielded

similar

biomass

amounts

but

varied

by

and

respectively

These

results

support

our

contention

of

greater

biological

variability

among

replicate

flask

cultures

relative

to

bioreactor

cultures

Fig.

oneidensis

cultured

in

duplicate

bioreactors

at

The

same

inoculum

culture

was

used

for

both

bioreactors

Cells

were

harvested

from

each

reactor

when

the

optical

density

and

organic

acid

concentrations

were

similar

The

average

dry

weight

biomass

was

mg/l

Culture

and

proteome

variability

When

the

intercultural

variability

of

the

proteomes

of

cells

from

duplicate

shake

flasks

controlled

batch

bioreactors

and

chemostat

cultures

was

assessed

using

and

MS

notable

differences

were

identified

For

analysis

digital

images

of

the

gels

were

processed

for

spot

detection

and

pattern

matching

with

one

image

as

a

reference

pattern

and

all

others

matched

to

it

to

give

the

protein

spots

identification

numbers

Statistical

analysis

of

the

relative

abundance

of

each

matched

protein

spot

across

the

datasets

employed

a

two-tailed

Student

's

t-test

as

previously

described

-LRB-

Giometti

and

Taylor

-RRB-

Differences

in

spot

patterns

were

observed

between

the

replicate

flask

cultures

-LRB-

Fig.

d

-RRB-

including

one

unidentified

protein

-LRB-

spot

P

-RRB-

In

contrast

there

was

relatively

little

variability

-LRB-

P

-RRB-

in

proteome

profiles

from

the

replicate

gels

from

either

the

controlled

batch

or

chemostat

cultures

Fig.

protein

patterns

from

biological

replicates

of

the

three

growth

methods

The

within

method

replicates

show

few

significant

differences

The

chemostat

and

controlled

batch

replicates

showed

no

quantitative

differences

with

a

statistical

significance

of

P

whereas

the

flask

culture

replicates

showed

one

quantitative

difference

-LRB-

Spot

-RRB-

with

a

difference

of

P

SS

steady

state

culture

CB

controlled

batch

culture

The

gel

images

are

oriented

with

the

basic

proteins

to

the

right

acidic

proteins

to

the

left

high

molecular

weight

toward

the

top

and

low

molecular

weight

toward

the

bottom

Data

from

MS-proteome

analysis

was

consistent

with

the

results

Triplicate

samples

from

duplicate

cultures

from

shake

flask

controlled

batch

and

chemostats

were

analyzed

and

Venn

diagrams

-LRB-

Fig.

-RRB-

were

constructed

to

illustrate

the

similarities

and

differences

between

biological

and

analytical

replicates

based

on

the

cultivation

method

A

comparison

of

protein

detection

consistency

between

the

biological

duplicates

showed

that

the

flask

grown

cells

-LRB-

Fig.

-RRB-

exhibit

a

higher

degree

of

variability

Flask

A

averaged

proteins

detected

from

triplicate

analyses

while

flask

B

averaged

proteins

with

only

proteins

-LRB-

-RRB-

in

common

The

consistency

of

detected

proteins

between

biological

replicates

was

higher

in

the

controlled

batch

-LRB-

Fig.

-RRB-

and

chemostat

cultures

-LRB-

Fig.

-RRB-

This

was

not

due

to

a

lack

of

consistency

in

the

analytical

replicates

since

protein

detection

consistency

was

between

and

for

all

three

cultivation

methods

-LRB-

Fig.

f

-RRB-

Secondly

there

was

an

overall

decrease

in

the

number

of

proteins

detected

from

the

flask

grown

-LRB-

-RRB-

to

the

controlled

batch

-LRB-

-RRB-

and

to

the

chemostat

-LRB-

-RRB-

cultures

This

can

be

explained

by

the

presumed

homogeneity

of

the

culture

increasing

as

the

degree

of

control

over

pH

and

increased

thus

allowing

the

entire

culture

to

experience

similar

environmental

conditions

Fig.

proteomic

analysis

of

the

same

duplicate

-LRB-

left

-RRB-

shake

flask

-LRB-

middle

-RRB-

controlled

batch

and

-LRB-

right

-RRB-

chemostat

grown

cells

that

were

analyzed

by

The

consistency

in

the

proteins

detected

between

biological

duplicates

from

shake

flask

-LRB-

a

-RRB-

controlled

batch

-LRB-

c

-RRB-

and

chemostat

-LRB-

e

-RRB-

cultures

shows

the

increased

similarity

in

proteomes

with

increased

control

over

culturing

parameters

This

was

not

an

effect

of

the

instrumentation

since

analytical

replicates

from

each

of

the

shake

flask

-LRB-

b

-RRB-

controlled

batch

-LRB-

d

-RRB-

and

chemostat

-LRB-

f

-RRB-

cultures

consistently

had

-LRB-

of

the

detected

proteins

in

common

The

values

below

each

Venn

diagram

circle

are

the

number

of

detected

proteins

for

each

biological

-LRB-

a

c

e

-RRB-

or

analytical

-LRB-

b

d

f

-RRB-

replicate

The

value

in

the

overlap

region

is

the

number

of

proteins

in

common

between

the

replicates

with

the

corresponding

percentage

for

ease

of

comparison

The

percentage

shown

is

the

number

of

proteins

in

common

divided

by

the

average

of

the

two

replicates

presented

Discussion

The

advantages

of

controlled

cultivation

have

been

demonstrated

for

many

different

research

applications

in

microbiology

including

the

determination

of

carbon

nitrogen

or

electron

flow

-LRB-

Vasconcelos

et

al.

Daran-Lapujade

et

al.

Kolkman

et

al.

Adams

et

al.

-RRB-

kinetic

constants

for

specific

reactions

-LRB-

Nethe-Jaenchen

and

Thauer

-RRB-

alternate

roles

for

traditionally

well-defined

enzymes

-LRB-

Snoep

et

al.

-RRB-

and

whole

cell

protein

fingerprinting

-LRB-

Wunschel

et

al.

-RRB-

While

there

have

been

statements

touting

the

advantages

of

controlled

cultivation

an

in

depth

investigation

of

the

differences

in

metabolism

between

cultivation

methods

has

not

been

performed

The

closest

exception

to

this

reported

that

microarray

results

between

three

chemostatic

cultures

from

three

different

laboratories

were

significantly

more

reproducible

compared

to

a

previous

study

that

performed

a

similar

comparison

using

shake

flask

cultures

-LRB-

Piper

et

al.

-RRB-

However

the

authors

reported

that

there

were

differences

in

harvesting

and

other

procedures

which

may

well

have

skewed

the

findings

To

this

end

the

experiments

reported

here

were

specifically

directed

toward

determining

whether

or

not

controlled

cultivation

results

in

a

more

homogenous

culture

with

regard

to

both

targeted

and

comprehensive

proteome

profiles

from

three

cultivation

methods

in

our

laboratory

Our

results

demonstrate

that

variations

in

concentration

and

consumption

rates

between

replicate

flask

cultures

in

the

late

log

phase

of

growth

can

impact

metabolism

This

was

evidenced

by

the

increased

lag

time

in

the

uncontrolled

flask

cultures

relative

to

the

controlled

cultivations

The

data

suggests

that

this

may

be

an

effect

of

oxygen

toxicity

when

levels

are

above

This

has

been

recently

tested

in

S.

oneidensis

using

sealed

culturing

vessels

and

levels

above

headspace

were

found

to

be

inhibitory

-LRB-

McLean

et

al.

-RRB-

Two

possible

explanations

exist

for

this

observation

It

is

possible

that

the

extended

lag

and

initial

slow

growth

rate

was

the

result

of

oxygen

toxicity

at

values

above

However

the

uncontrolled

batch

cultures

contained

mM

PIPES

buffer

to

aid

in

the

maintenance

of

pH

during

growth

while

the

controlled

batch

and

chemostatic

cultures

contained

only

mM

PIPES

Hence

there

would

have

been

a

large

difference

in

the

ionic

strength

of

the

two

media

and

so

while

toxicity

may

be

the

reason

for

the

extended

lag

phase

other

reasons

can

not

be

ruled

out

Separately

differences

in

acetate

concentrations

of

the

replicate

shake

flask

cultures

compared

to

controlled

batch

and

chemostat

cultures

indicated

that

such

differences

may

well

have

promoted

additional

biological

variability

The

difference

in

acetate

concentrations

between

replicate

shake

flask

cultures

compared

to

the

consistent

acetate

concentrations

in

controlled

batch

and

chemostat

cultures

has

particular

implications

for

S.

oneidensis

strain

can

use

lactate

and

pyruvate

as

an

electron

donor

during

anaerobic

growth

but

not

acetate

-LRB-

Lovley

et

al.

Nealson

and

Myers

-RRB-

Thus

variations

in

the

concentration

of

acetate

and

the

variable

uptake

rates

in

shake

flask

cultures

will

cause

a

temporal

shift

in

carbon

source

usage

and

electron

flux

Such

shifts

can

be

expected

to

result

in

variable

metabolic

transcriptomic

and

proteomic

profiles

between

independent

shake

flask

cultures

if

only

a

small

number

-LRB-

-RRB-

of

samples

are

taken

since

one

culture

may

have

exhausted

a

carbon

source

and

consequently

shifted

metabolism

and

electron

flow

while

the

biological

replicate

has

not

Given

the

general

metabolic

flexibility

of

bacteria

including

S.

oneidensis

and

their

ability

to

respond

rapidly

to

changes

in

environmental

conditions

changes

in

the

expressed

proteins

-LRB-

proteome

-RRB-

would

be

expected

as

a

result

of

exposing

cultures

to

different

environmental

conditions

Through

the

use

of

comprehensive

proteome

measurements

the

results

presented

here

demonstrate

that

chemostat

cultures

provide

the

most

consistent

source

of

cellular

material

for

biochemical

measurements

involving

microbial

cells

with

a

minimum

contribution

to

those

measurements

from

biological

variation

Two

independent

methods

of

proteome

measurement

and

AMT

MS

both

showed

that

flask

cultures

yielded

protein

samples

with

more

culture-to-culture

variability

than

observed

in

either

controlled

batch

cultures

or

continuous

chemostat

cultures

primarily

among

proteins

thought

to

be

associated

with

anaerobic

or

microaerobic

metabolism

A

similar

effect

was

found

with

respect

to

differential

regulation

of

genes

via

microarrays

when

the

results

of

two

different

investigations

were

compared

from

yeast

cells

showing

less

discrepancy

between

chemostatic

cultures

-LRB-

Daran-Lapujade

et

al.

-RRB-

Many

of

the

proteins

present

in

higher

abundance

in

the

aerobic

shake

flask

cultures

relative

to

the

controlled

batch

or

chemostat

cultures

in

this

study

have

previously

been

reported

to

be

up-regulated

in

anaerobic

compared

to

aerobic

cultures

-LRB-

Beliaev

et

al.

Fang

et

al.

-RRB-

MtrA

B

C

and

OmcA

are

involved

in

metal-reduction

in

anaerobic

cultures

supplied

with

metals

as

terminal

electron

acceptors

-LRB-

Beliaev

and

Saffarini

Beliaev

et

al.

Myers

and

Myers

Pitts

et

al.

-RRB-

while

the

outer

membrane

protein

OmpW

and

fumarate

reductase

have

both

been

observed

to

be

significantly

more

abundant

in

anaerobic

cultures

supplied

with

iron

or

fumarate

as

electron

acceptor

than

in

aerobic

cultures

-LRB-

Fang

et

al.

-RRB-

Thus

the

shake

flask

cultures

in

the

experiments

described

here

must

have

included

cells

experiencing

a

lack

of

oxygen

due

to

the

nutrient

depletion

that

is

an

inherent

complication

of

such

cultures

resulting

in

a

greater

range

of

expressed

proteins

Achieving

a

systems-level

understanding

of

microorganisms

including

the

underlying

metabolic

and

regulatory

networks

that

control

cell

physiology

and

the

ability

to

predict

responses

to

perturbations

is

indeed

an

ambitious

goal

Systems

biology

takes

full

advantage

of

the

state-of-the-science

technology

and

genomic

information

with

the

scientific

as

well

as

the

practical

benefits

expected

to

be

plentiful

Our

results

emphasize

that

functional

genomics

can

greatly

benefit

from

well-defined

and

homogeneous

cell

cultures

provided

by

controlled

cultivation

techniques

The

use

of

controlled

cultivation

techniques

ensures

that

the

large

and

comprehensive

datasets

used

in

systems

biology

research

are

derived

from

well-characterized

and

homogeneous

biological

samples

thus

reducing

the

inherent

variability

that

often

complicates

drawing

biological

conclusions

and

will

allow

for

more

accurate

and

robust

identifications

of

metabolic

and

regulatory

networks

O O O O O O B O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O B I O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

controlled cultivation
systems biology
proteomics
shewanella


Does Practice Make Perfect ? Extensive literature supports the correlation between surgical volume and improved clinical outcome in the management of various cancers . It is this evidence that has catalysed the creation of centres of excellence . However , on closer inspection , many of these studies are poor quality , low weight and use vastly heterogenous end points in assessment of both volume and outcome . We critically appraise the English language literature published over the last ten years pertaining to the volume outcome relationship in the context of cancer care . Future balanced unbiased studies may enable equipoise in planning international cancer management strategies . No longer is there room for eminence-based complacency or misguided arrogance in healthcare delivery . The day of the autonomous clinician is gone with a vogue towards standardised , evidence-based clinical excellence . Cynics would erroneously attribute this to a parallel increase in litigation but increasing patient knowledge and expectations with a move toward subspecialisation are the main catalysts driving change . When offered operative intervention , the question frequently asked by the patient is `` How many of these have you done before ? '' This article aims to critically analyse recent literature and explore the correlation between volume and clinical outcome in the context of cancer care . Background Mortality rates are reported to be influenced by the number of particular operations performed in a given hospital or by a specific surgeon -LRB- i.e. outcomes are better in high-volume centres -RRB- . In 1999 , the US National Cancer Policy Board recommended that patients requiring complex procedures be transferred from low - to high-volume hospitals in its report entitled `` Ensuring Quality Cancer Care '' .1 The following year , the Institute of Medicine held a workshop to discuss cancer care , publishing a document -LRB- `` Interpreting the Volume-Outcome Relationship in the Context of Cancer Care '' 2 -RRB- which concluded that existing evidence was strong enough to recommend the regionalisation of high-risk operations . Hence , the impact of volume on outcome has been assessed in several tumour types but the majority of data relates to gastrointestinal , hepatobiliary , urological , and breast cancers . The literature Patients undergoing pancreatic and oesophageal procedures have lower operative mortality and shorter hospital stay in the hands of experienced surgeons in high-volume units .3 With regard to gastric cancer , the findings are less consistent . Some suggest that high-volume centres have lower in-house mortality4 but no change in long-term survival .5 Various end points have been examined in colorectal cancer -LRB- Table 1 -RRB- . Schrang and Billingsley both showed that it was surgeon-specific experience combined with multidisciplinary support rather than centre experience that afforded significant survival advantage .6,7 Table 1 . Colorectal cancer outcome : high - and low-volume unitsHigh volumeLow volumeRef.APR versus LAR ↓ APR ↑ APRMeyerhardt et al. 19 ↑ LAR ↓ LARSphincter preservation ↑ ↑ ↓ Purves et al.2030-day postoperative mortality ↔ ↔ Schrag et al. 21Survival -LRB- overall and cancer specific -RRB- ↑ ↓ Schrag et al. 21Permanent stoma formation ↓ ↑ McGrath et al. 22Colonic pouch formation ↑ ↓ McGrath et al. 22APR , abdominoperineal resection ; LAR , low anterior resection . ↑ increased , ↓ decreased , ↔ no variation . Comprehensive albeit retrospective studies unequivocally state that patients who undergo radical prostatectomy at lower-volume institutions are at significant risk of requiring adjuvant therapy due to adverse surgical factors , prolonged hospital admission , increased hospital charges and postoperative complications .8 The hospital structure of high-volume units , including easy availability of consultative , diagnostic and ancillary services , were cited as likely contributors to the association between procedure volume and short-term cystectomy outcomes .9 A minimum case load of only 11 radical cystectomies per year was cited to be associated with the lowest mortality rate .10 Less certainty exists in relation to breast cancer but a variety of end points have been examined , including number of visits required to obtain a nonoperative diagnosis , mastectomy rates for < 15 mm tumours and rate of referral for adjuvant radiotherapy .11 Skinner et al. were adamant that volume alone could not be used as a surrogate for expertise but , like most studies , conceded that patients with breast cancer operated on in high-volume units compared to very low-volume units had better survival . However there is ambiguity surrounding the exact causal relationship : volume effect alone versus surgical skill versus appropriate use of adjuvant therapy .12 The Flaws The majority of studies are poor quality , heterogenous and potentially flawed . Even the best literature stems from retrospective review of large databases which are up to 40 % inaccurate13 and pertain to selected patient groups . Most papers are published from a few very high-volume US centres , thus introducing immediate potential for bias . No consistent end point is used and , incredibly , few studies explore cancer-specific outcomes . Mortality rates , when not corrected for comorbidities or stage at diagnosis , are poor surrogates for more robust comparators of volume -- outcome analysis such as cancer-specific survival , patient satisfaction and quality of life . American data can not be used as a basis for the formation of European cancer strategies because so many inherent differences exist . These include earlier disease stage at time of operation -LRB- a function of screening -RRB- ,14 wide variance in population15 and socioeconomic status16 as well as insured versus noninsured outcomes .17 Comparison of very high-volume centres and very low-volume centres is as redundant as measuring revenue from a supermarket versus a corner store . Is it not intuitive that analysis of such extremes will yield vastly different results ? Looking at the structure -- process -- outcome model , structure is relatively fixed -LRB- health service , institution -RRB- but process is entirely variable and volume is but one component of it . Therefore , in the absence of multivariable data , subgroup analysis is entirely inappropriate , rendering the aforementioned studies at best biased , at worst invalid . The Surgeon To identify procedure volume in a single institution is easy but not so for quantifying specific operations done by a single surgeon , many of whom practise in several centres . Without asking individuals to record caseload prospectively , obtaining accurate figures may be very difficult . Surely significant bias could occur in that those willing to share details of operations may be confident of their own justification in performing such procedures . Furthermore , who counts as more experienced : a mature surgeon who has performed two colonic resections a week for 20 years but now does only two a month or a younger , specialist trained surgeon who performs three a week ? How do you weight lifetime experience against current volume ? Should a centralised database of surgeons ' logbooks exist , and should permission to operate be granted or denied based on this ? What governing body should be afforded such a task ? Should operating surgeons be ranked in their ability or would this border on defamation for the less fortunate ones ? Regarding referral pattern , does volume attract quantity or do excellent clinicians attract patients ? Many studies have compared the significance of surgeon experience to unit volume with varied conclusions as to which has more impact . Do excellent surgeons naturally aggregate in excellent high-volume units , thus giving a self-propagating explanation for improved outcome ? The Institution Many papers allude to the importance of the multidisciplinary approach in cancer care . Higher-volume units are far more likely to have subspecialised radiologists , radiation and medical oncologists , high dependency and intensive care units , cancer specialist nurses , dedicated psychologists and palliative care support . Anecdotally , the involvement of such services translates into better patient outcome regardless of unit volume , thus confounding results . The resounding evidence in favour of the volume -- outcome relationship pertains to those cancers requiring adjuvant therapy : oesophagus , pancreas and advanced colorectal . It seems , therefore , that good surgical technique or individual surgeon experience do not exclusively guarantee positive outcomes and that much depends on availability of radiation and medical oncology . More often than not , within a short period of the introduction of a new service , its resources are saturated . At what point does a dedicated unit declare that available services can no longer provide for patient throughput ? The worry is that potential exists for patients to receive suboptimal care just before this saturation point is reached -LRB- Fig. 1 -RRB- . Surely stretched resources in a high-volume centre are just as dangerous as absence of resources in smaller institution . A study on the difference in time lapse between diagnosis and intervention between institutions with different volumes would be welcome . Would prognosis be improved if a patient with aggressive disease underwent early intervention at a lower-volume centre rather than late intervention at a higher-volume centre ? As cancer management is a dynamic process , the question of safety in transferring postoperative follow-up of a patient operated on in a high-volume unit to a less experienced lower-volume local centre is a pertinent one . On the other hand , should surgery be performed in low-volume units and adjuvant therapies in specialist centres ? Without a doubt , the idea of hospital units functioning as a syncitium rather than single buildings must be engendered and skill-appropriate tasks assigned to each component , as recommended in breast cancer management by the Clinical Oncology Information Network -LRB- COIN -RRB- group .18 Fig. 1 . Volume -- outcome relationship . The Patient Quality of life and patient satisfaction , apart from in colorectal and prostate cancers , are largely ignored when assessing impact of volume on clinical outcome . Is it preferential for elderly patients to travel long distances for management of a low-grade tumour or would they be better served by treatment in a lower-volume local centre where follow-up will be on their doorstep ? Decisions like this are made on a daily basis in the context of primary care and so this begs the question of higher-volume specialist centres receiving selected patient cohorts , thus falsely improving outcome . This is confirmed by Morris et al. who showed that patients treated in the Australian private sector were likely to be younger , male and to have an earlier disease stage .17 The Future The literature supports a correlation between surgical volume and improved clinical outcome in cancer care . However , a rather simplistic approach is evident in many studies and much potential remains for unbiased , prospective , statistically sound investigations with the aim of numerically stratifying appropriate volume and its impact on disease specific cancer outcomes . While traditionally graph 1 in Fig. 1 has been used to represent the volume -- outcome relationship , it seems probable that it is more accurately represented by graph 2 in Fig. 1 , and can be interpreted as an area under a curve rather than a strictly linear relationship .

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