Availability of glucose and light modulates the structure and function of a microbial biofilm

R E S E A R C H A R T I C L E

Availabilityofglucoseand lightmodulates the structureandfunctionofamicrobial bio¢lmIrene Ylla1, Carles Borrego2, Anna M. Romanı1 & Sergi Sabater1,3

1Institute of Aquatic Ecology, University of Girona, Girona, Spain; 2Group of Molecular Microbial Ecology, Institute of Aquatic Ecology, University of

Girona, Girona, Spain; and 3Catalan Institute for Water Research (ICRA), Scientific and Technologic Park of the University of Girona, Girona, Spain

Correspondence: Irene Ylla, Institute of

Aquatic Ecology, University of Girona,

Campus Montilivi, E-17071 Girona, Spain.

Tel.: 134 972 418 177; fax: 134 972 418

150; e-mail: irene.ylla@udg.edu

Received 14 October 2008; revised 12 March

2009; accepted 7 April 2009.

Final version published online 18 May 2009.

DOI:10.1111/j.1574-6941.2009.00689.x

Editor: Riks Laanbroek

Keywords

microbial biofilm; extracellular enzymes;

glucose; light; algae–bacteria coupling; biofilm

composition.

Abstract

We have studied the differences in the organic matter processing and biofilm

composition and structure between autoheterotrophic and heterotrophic biofilm

communities. Microbial communities grown on artificial biofilms were mon-

itored, following incubation under light and dark conditions and with or without

the addition of glucose as a labile organic compound. Glucose addition greatly

affected the microbial biofilm composition as shown by differences in 16S rRNA

gene fingerprints. A significant increase in b-glucosidase and peptidase enzyme

activities were also observed in glucose-amended biofilms incubated in the dark,

suggesting an active bacterial community. Light enhanced the algal and bacterial

growth, as well as higher extracellular enzyme activity, thereby indicating a tight

algal–bacterial coupling in biofilms incubated under illumination. In these

biofilms, organic compounds excreted by photosynthetic microorganisms were

readily available for bacterial heterotrophs. This algal–bacterial relationship

weakened in glucose-amended biofilms grown in the light, probably because

heterotrophic bacteria preferentially use external labile compounds. These results

suggest that the availability of labile organic matter in the flowing water and the

presence of light may alter the biofilm composition and function, therefore

affecting the processing capacity of organic matter in the stream ecosystem.

Introduction

Biofilms are energy transducers in flowing waters (Battin

et al., 2003) and they play a key role in the uptake or

retention of inorganic and organic nutrients (Sabater et al.,

2000). Biofilm microbial metabolism is responsible for the

decomposition and uptake of organic matter. Organic

matter available to microorganisms growing on biofilms

comes from the water column and from material produced

or entrapped within the biofilm matrix [including algal

exudates and extracellular polymeric substances (EPS)](Sa-

bater & Admiraal, 2005). The organic matter in freshwater

ecosystems mainly comprises dissolved organic carbon

(DOC), of which 70–90% is recalcitrant (Munster, 1993).

The remaining 10–30% is in a labile form that can be rapidly

consumed by heterotrophs (Wetzel, 1992), which show a

preferential use for the most labile molecules (Kaplan &

Newbold, 2003). Although the availability of biodegradable

labile organic compounds in the flowing water is usually

low, biodegradable DOC can increase to about 40% of total

DOC during flooding episodes in intermittent Mediterra-

nean streams (Romanı et al., 2006). Besides, an increase in

the content of total polysaccharides (including monomers

and polymers) can be also measured (I. Ylla, unpublished

data). These flooding periods have a similar impact on

streams as those derived from anthropogenic urban con-

tamination.

Biofilm microbial composition and their autotrophic and

heterotrophic metabolism may change in relation to quan-

tity and quality of the organic matter available in the flowing

water, and this could affect the whole stream ecosystem

organic matter processing capacity (Sabater et al., 2006).

The heterotrophic use of organic matter by biofilm micro-

biota has been detected by analyzing the extracellular

enzyme activity (Sinsabaugh et al., 1994). In microbial

heterotrophs, extracellular enzymes convert polymeric com-

pounds to low-molecular-weight molecules that are readily

assimilated (Chrost, 1990). In particular, the activity of

leucine-aminopeptidase has been linked to the activity of

photosynthetic primary producers (Espeland et al., 2001),

and to the use of algal-released proteinaceous compounds

by microbial heterotrophs (Romanı et al., 2004a). In con-

trast, b-glucosidase activity is involved in polysaccharide

decomposition and is correlated with the degradation of

either organic compounds of algal origin (algal exudates and

EPS) or polysaccharidic organic compounds dissolved in

flowing water (Jones & Lock, 1993).

The capacity to use organic matter may further differ

between microbial biofilms, depending on the species com-

position of the community (Olapade & Leff, 2005). Given

that no single species expresses all extracellular enzyme

activities (Martinez et al., 1996), any variation in the

bacterial community will be reflected by enzymatic activ-

ities. Probably, bacterial communities have the capacity to

express only the enzymes necessary for hydrolyzing a certain

range of high-molecular-weight organic compounds (Kirch-

man et al., 2004). Judd et al. (2006) demonstrated that the

bacterial community composition is controlled by the

nature of the organic matter available.

The development of an autoheterotrophic biofilm in

contrast to a heterotrophic biofilm could further modulate

the biofilm response to changes in available DOC. Algae and

heterotrophs coexist and interact within autotrophic bio-

films (Stock & Ward, 1989). When an algal biomass is

developed, microorganisms preferentially use and take up

the fresh molecules released by algae, such as algal exudates

and lysis products (Wetzel, 1993; Romanı & Sabater, 2000).

Several studies of epilithic biofilms conclude that algal

exudates are a major carbon source for bacteria (Rier &

Stevenson, 2002). This algal–bacterial link reduces the

uptake of dissolved organic compounds from the flowing

water pool in biofilms growing in light in comparison with

those growing in the dark (Romanı et al., 2004a). However,

other studies report that this algal–bacterial coupling is

weak or undetectable (Findlay et al., 1991; Gao et al., 2004).

The degree of coupling between algae and bacteria may

depend on the trophic state of the system and dissolved

organic matter content (Findlay et al., 1993a; Scott et al.,

2008), light availability (Findlay et al., 1993b) or even

substratum type (Kaplan & Bott, 1989).

In this study, we aim to determine differences in organic

matter processing and biofilm composition and structure

between autoheterotrophic and heterotrophic biofilm com-

munities, when allochthonous labile organic matter is avail-

able (provided by addition of glucose). We used a factorial

experiment that included the presence and absence of light

and glucose to control single and interactive effects in the

biofilm. The analysis of biofilm composition (molecular

analysis and microscopic observations) and function

(photosynthetic efficiency, b-glucosidase and peptidase en-

zyme activities) under the laboratory-tested conditions

might add interesting knowledge to the potential expected

changes in organic matter processing in stream biofilms

when labile organic matter is available. A differential re-

sponse of light-grown vs. dark-grown biofilms is expected

due to the potential significant effect of autotrophic meta-

bolism on biofilm structure and function.

Materials and methods

Experimental procedure

Sand-blasted glass tiles (1 cm2) were used as substrata for

epilithic biofilm colonization and were incubated in

12 microcosms with algal inoculum from the oligotrophic

Fuirosos stream (Veraart et al., 2008). Each microcosm

consisted of a sterile glass jar (19 cm in diameter, 9 cm high)

with 70–90 autoclaved glass tiles attached to the bottom by a

plastic rod. The microcosms were filled with 1.5 L of

simulated river water, which was recirculated by means of a

submersible pump (Hydor, Pico 300, 230 V 50 Hz, 4.5 W).

Simulated river water was obtained by dissolving pure salts

(12 mg L�1 Na2SO4, 20 mg L�1 Na2SiO3, 30 mg L�1 CaCl2,

1 mg L�1 KCl, 2 mg L�1 MgSO4 and 20 mg L�1 NaHCO3) in

MilliQ water in order to reproduce the chemical composi-

tion of the Fuirosos stream (Bernal et al., 2002; Vazquez

et al., 2007). The simulated water was sterilized by filtration

through 0.22-mm pore-diameter sterile filters (Acrodisc,

PALL Life Sciencess) before its use. Every 3–4 days, all the

water from each microcosm was replaced by fresh sterile

simulated river water. All microcosms were maintained

under a controlled atmosphere at 18 1C in a constant day–

night light cycle (12 h/12 h) using an incubator (Radiber

AGP-570). The irradiance reaching the glass substrata ran-

ged between 160 and 180 mmol photons m�2 s�1.

The experiment comprised four treatments: light–no

glucose (LnG), light–glucose (LG), dark–no glucose (DnG)

and dark–glucose (DG). For each treatment, three replicate

microcosms were established. Dark conditions were

achieved by covering the corresponding six microcosms

with opaque black plastic. Glucose enrichment was achieved

by adding pure glucose to the corresponding microcosms at

a final concentration of 10 mg C L�1 at the beginning of the

experiment and when water was renewed. To prevent

phosphorus and nitrogen depletion, ammonium phosphate

(30 mg L�1) and ammonium nitrate (750mg L�1) were added

to all the treatments at the beginning of the experiment and

every time the water was replaced.

To stimulate biofilm colonization of the glass substrata, a

biofilm previously scraped under sterile conditions from

rocks collected from the Fuirosos stream (10 mL containing

60–70 mg of chlorophyll) was suspended in each microcosm.

This inoculum was added at the beginning of the experi-

ment to promote the colonization of the glass substrata, and

new biofilm suspensions were repeated after 4, 8 and 11

days, to improve and accelerate colonization. After the

28 I. Ylla et al.

colonization phase, biofilms in the microcosms were

sampled every week (days 15, 22 and 29).

Glass tiles were sampled at random from each micro-

cosm. Enzymatic activities, photon yield, and bacterial

density were measured immediately after collection. Sam-

ples for chlorophyll determination were frozen (� 20 1C)

until analysis.

Samples for extracellular polysaccharide content at the

EPS, algal observation and scanning electron microscope

(SEM) observations were collected from day 29. Samples for

molecular analyses, PCR and denaturing gradient gel elec-

trophoresis (DGGE), were also taken after 29 days of

incubation. The inoculum was also analyzed for bacterial

and algal community.

Chemical conditions in the microcosms

The water nutrient content and chemical parameters were

monitored every time water was renewed (every 3–4 days).

Water was replaced eight times during the experiment.

Oxygen concentration (Hach DO meter), pH (pH meter,

WTW) and conductivity (conductivity meter, WTW) were

measured. Triplicate water samples for each microcosm were

passed through a 0.2-mm pore-diameter nylon filter (What-

man) and used to analyze inorganic nutrients. Phosphate

was analyzed spectrophotometrically, as described by Mur-

phy & Riley (1962). DOC and dissolved organic nitrogen

(DON) were determined with a Shimadzu TOC 5050A.

Algal and bacterial biomass and communitycomposition

Chlorophyll concentration

Chlorophyll (Chl) a concentration on the glass tiles (two

replicates for each microcosm, for each sampling date) was

measured after extraction in 90% acetone for 12 h in the

dark at 4 1C. To ensure complete extraction of chlorophyll,

samples were further sonicated for 2 min in a Selecta

sonication bath operating at 40 W and 40 kHz and pre-

viously protected from light. Extracts were passed through

47-mm-diameter and 1.45-mm-mesh fiberglass filters (GF/C

Whatman), and Chl a concentration was further determined

spectrophotometrically using a Lambda UV/Vis spectro-

photometer (Hitachi), following Jeffrey & Humphrey

(1975). The ratio of carotenoids to Chlorophyll and/or

Chlorophyll degradation products (OD430 nm/OD665 nm ra-

tio, Margalef, 1983) was also calculated.

Algal composition

Glass substrata from day 29 (one tile for each microcosm)

were preserved and stored with 4% formalin until analysis.

Glass substrata were sonicated for 2 min using an ultrasoni-

cation bath (Selecta) to achieve complete detachment of the

microbial community. The inoculum samples and three

aliquots from each scraped biofilm sample were observed

under a light microscope (Nikon E600) at � 400 to identify

species/genus level. The algal community composition was

determined qualitatively.

Bacterial density

Live and dead bacteria were counted using the Live/Dead

Baclight bacterial viability kit (Invitrogens Molecular

probes Inc.) (Freese et al., 2006). The bacterial density was

estimated after ultrasonication of each glass tile (one per

microcosm on each sampling date) for 90 s using a sonica-

tion bath (Selecta) operating at 40 W and 40 kHz. After

appropriate dilution (10 times) with sterile water, a 1 : 1

mixture of SYTOs 9 and propidium iodide was added to

the sample under analysis and incubated for 15 min. Sam-

ples were then filtered (0.2-mm pore-diameter black poly-

carbonate filters, Nucleopore, Whatman) and at least 20

randomly chosen fields were counted for each slide (Nikon

E600 epifluorescence microscope). The fraction of live

bacteria was calculated as the abundance of live cells divided

by the total counts obtained with the live/dead method.

Molecular analyses

DNA extraction

DNA extraction was performed in the inoculum samples

(two replicates) and the biofilm samples collected after 29

days of incubation (one tile from each microcosm) to check

for differences in the bacterial community composition

caused by the treatments. Samples for DNA extraction

included 1 mL of the two inoculum samples (in duplicate)

and the biofilm samples (in triplicate). The latter were

obtained by scrapping the glass tiles under sterile condi-

tions. DNA was extracted from wet cell pellets obtained after

centrifugation of samples at 13 400 g for 30 min in a 5415D

centrifuge (Eppendorfs). Total nucleic acids were extracted

as described previously (Lliros et al., 2008). DNA extracts

were stored at � 80 1C until use. DNA concentration and

purity were determined spectrophotometrically from ex-

tracts using a Nanodrop ND-1000 UV-Vis spectrophot-

ometer (Nanodrop, DE).

PCR amplification

The bacterial richness of the biofilms was determined by PCR

using the universal primer pair 357F-907R, targeting the 16S

rRNA gene sequences for the Domain Bacteria (Lane, 1991).

Because PCR products were later used for DGGE analysis, a

GC-rich sequence was attached at the 50 end of the forward

29Biofilm shifts caused by glucose and light

primer (Muyzer et al., 1993, 1998). Each PCR mixture (50mL)

had 5mL of 10�PCR buffer containing 15 mM MgCl2 (Qiagen

GmbH, Hilden, Germany), 4mL of premixed dNTPs (2.5 mM

each, GeneAmps, Applied Biosystemss, Warrington, UK),

0.5mL of MgCl2 (50 mM, Qiagen GmbH), 2mL of bovine

serum albumin (10 mg mL�1, Sigma-Aldrich, Steinhem, Ger-

many), 1mL of each primer (10mM), 0.25mL of Taq DNA

polymerase (5 UmL�1, Qiagen GmbH) and 1mL of the DNA

template (10–50 ng). All amplification reactions were run in a

GeneAmps 2700 thermocycler (Applied Biosystems, Perkin-

Elmers, CA), following a step-down PCR program as de-

scribed previously (Bruns et al., 2003). A positive amplification

was confirmed by analyzing 4mL of the resulting PCR products

in 1.5% (w/v) agarose gels stained with ethidium bromide.

DGGE fingerprinting

The community analysis by DGGE (Muyzer et al., 1993)

provided a high resolution and allowed easy comparison of

fingerprints to examine potential changes in the predomi-

nant bacterial composition of each biofilm between treat-

ments. DGGE was carried out in an Ingeny phorU-2 (Ingeny

International BV, the Netherlands) system. Between 800 and

1000 ng of PCR product was loaded onto 6% (w/v) poly-

acrylamide [acrylamide/N,N(-methylene bisacrylamide) ra-

tio, 37 : 1 (w/w)] gels prepared with a 30–70% linear

gradient of denaturant [100% denaturant agent contains

7M urea and 40% (v/v) deionized formamide (McCaig et al.,

2001)]. Electrophoresis was run at 60 1C and at a constant

voltage of 160 V for 12 h in 1�TAE (Tris-acetate EDTA).

After electrophoresis, gels were stained for 30 min with

1� SYBR Gold nucleic acid stain (Molecular Probes Inc.)

in 1�TAE buffer. They were then rinsed and viewed under

UV radiation using a GelPrinter system (TDI, Spain). The

digitalized gel images were analyzed with GEL COMPARE II

IMAGE ANALYSES software package (Applied Maths NV,

Belgium). Within each treatment, bands located at the same

position were considered to be the same phylotype. Accord-

ingly, only one representative band for each position and

treatment was excised and sequenced. A total of 55 clear and

discrete bands representative of each treatment were excised

from the gels using a sterile scalpel and rehydrated in 50mL

of Tris-HCl 10 mM buffer (pH = 7.4). DNA was eluted after

incubation of the excised bands at 65 1C for 3 h and forward

and reverse amplified using the same primers (without GC

clamp) and PCR conditions as cited above. Sequencing

reactions were carried out using external facilities (http://

www.macrogen.com).

Phylogenetic affiliation and analyses

All the sequences retrieved were compared for closest

relatives to partial 16S rRNA gene sequences in the NCBI

sequence database (http://www.ncbi.nlm.nih.gov/blast/)

using the BLASTN algorithm tool (Altschul et al., 1990).

Sequences were properly aligned using NAST (DeSantis et al.,

2006a) aligner web server. The presence of chimera was

checked using the BELLEROPHON (Huber et al., 2004) tool

implemented at the Greengenes website (http://greengenes.

lbl.gov/; DeSantis et al., 2006b). A phylogenetic backbone

tree for the Domain Bacteria was constructed with the

ARB software package (Ludwig et al., 2004) using the 16S

rRNA gene GreenGenes ARB-compatible database (May

2007). All partial sequences obtained from DGGE bands

(c. 400–600 bp), as well as other closely related sequences

(c. 500–1300 bp) from databases, were then added to the

backbone tree using the parsimony ‘quick add marked tool’

implemented in ARB, thereby maintaining the overall tree

topology. For better clarity, only selected subsets of the

sequences used for treeing are shown in the final tree

(Supporting Information, Fig. S1). All the sequences ob-

tained in this study have been deposited in GenBank under

accession numbers FJ183981–FJ184030.

Biofilm structure

SEM observations

Samples for SEM (one glass tile from each microcosm

collected after 29 days of incubation) were fixed immedi-

ately after sampling with 2.5% glutaraldehyde in 0.1M

cacodilate buffer, pH 7.2–7.4. Afterwards, a series of ethanol

baths (65–100%) were used to dehydrate the samples, which

were further dried by the critical point of CO2 (CPD).

Samples were finally coated with gold using a sputtering

diode. Samples were viewed under a Zeiss DSM 960 SEM.

Polysaccharide content of EPS

Glass samples for polysaccharide content in EPS were

collected from one glass tile per microcosm at the end of

the incubation period (day 29) and preserved frozen at

� 20 1C until analysis. EPS were extracted using cation-

exchange resin (Dowex Marathon C, Na1-form, strongly

acid, Sigma-Aldrich), following the procedure described in

Romanı et al. (2008). The polysaccharide content was

measured by the phenol–sulfuric acid assay (Dubois et al.,

1956) after the extraction of EPS. Standards of glucose

(0–200 mg mL�1) were also prepared. Results are given as

glucose equivalents per cm2 of biofilm surface area.

Biofilm function

Extracellular enzyme activity measurements

The extracellular enzyme activities of b-D-1,4-glucosidase (EC

3.2.1.21) and leucine-aminopeptidase (EC 3.4.11.1) were

30 I. Ylla et al.

measured spectrofluorometrically using 4-methylumbelliferyl-

b-D-glucopyranoside (Sigma-Aldrich) and 7-aminomethyl-

coumarin-leucine (Sigma-Aldrich) as the respective sub-

strate analogues. Glass substrata (18 tiles per microcosm

– nine for each enzyme and sampling date) were collected for

the measurement of extracellular kinetics of each enzyme.

Incubations were performed at increasing concentrations of

each substrate analogue (separately) as follows: 0, 0.01, 0.025,

0.05, 0.075, 0.1, 0.2, 0.3 and 0.5 mM. Blanks and standards of

methylumbelliferone and aminomethylcoumarin were also

included. Incubations for enzyme activity measurements

were performed in the dark under continuous shaking for

1 h at 18 1C immediately after sampling. At the end of the

incubation, glycine buffer (pH 10.4) was added (1 : 1 v/v) and

fluorescence was measured at 365/455 and 364/445 nm

excitation/emission for methylumbelliferone and amino-

methylcoumarin, respectively. The fluorescence intensity of

the blanks was subtracted from all the samples to correct for

hydrolysis of the substrate or fluorescent substances in the

water solution. Values are expressed as nmol methylumbelli-

ferone or aminomethylcoumarin cm�2 h�1. Results for each

enzyme were fitted into the Michaelis–Menten approach

(rectangular hyperbola). Vmax and Km values were obtained

by nonlinear regression using the SIGMAPLOT GRAPH software

(Systat Software Inc., San Jose, CA).

Photosynthetic efficiency

Two randomly selected colonized glass tiles per microcosm

were used to determine the photon yield of algae on each

sampling day. Photon yield is defined as a measure of the

photosynthetic efficiency of a community (Schreiber et al.,

2002). Samples were placed in a Petri dish with 10 mL of

water from the microcosm. Saturating light pulses simulta-

neously emitted at four wavelengths (470, 520, 645 and

665 nm) were provided by a phytoPAM (Pulse Amplitude

Modulated) fluorometer (Heinz Walz GmbH). The photon

yield of the main algal groups was measured by the

emitter–detector unit (PHYTO-EDF) at the sample surfaces.

The mean of the photon yield corresponding to each algal

group was used as the photon yield for each tile.

Statistical analyses

t-Test analyses of paired values were used to control the

stability of the physical–chemical parameters during the

experiment by comparing water samples for every 3–4-day

period (each water renewal) from each microcosm.

Variability in the descriptors of biofilm function and

structure (b-glucosidase, leucine-aminopeptidase, photon

yield, chlorophyll and bacterial density) was analyzed by

MANOVA. This analysis was used to test for the single-source

effects and the interactions between three factors: light–

dark, glucose–no glucose and sampling time. All variables

included in the analyses were log [log (x)] transformed,

except for chlorophyll and photon yield, which were

log (x11) transformed. Correlation analysis (Pearson’s coef-

ficient) was used to determine potential relationships be-

tween the analyzed variables. The relationships between

photosynthetic efficiency and enzymatic activities in light

treatments were analyzed by linear regression. Model II

linear regression (geometric mean regression) was applied

because the two variables used for the regression were

measurements (with errors; Sokal & Rohlf, 1995). All

statistical analyses were performed using the SPSS software

package for Windows (ver.14.0.1, SPSS Inc., 1989–2005).

DGGE fingerprints were analyzed using GELCOMPAR II

(Applied Maths NV). A DGGE marker comprising a mix-

ture of known 16S rRNA PCR amplified genes was loaded in

several gel lanes and used as an internal standard for the

comparison between fingerprints. For sample comparison, a

presence–absence matrix was used to calculate similarities

between patterns, and statistical analysis based on hierarch-

ical cluster analysis was performed with the Jaccard distance

and the unweighted pair group method with arithmetic

mean grouping algorithm.

Results

Physical and chemical conditions in themicrocosms

During the incubation, oxygen, pH and conductivity re-

mained steady at 9–9.8 mg L�1, 7.5–8.5, and 105–130mS cm�1,

respectively. Nutrient content, especially phosphate, decreased

in each 3–4-day period (from 35 to 4mg L�1), but the nutrient

depletion was prevented by periodical water replacement at

the same interval. The initial DOC concentration in the

‘renewed water’ decreased slightly after each 3–4-day period

in glucose-amended treatments (from 9.5 to 4 mg L�1), while

DOC clearly increased in treatments without glucose supple-

mentation (from 0.5 to 2 mg L�1). Thus, water replacement

every 3–4 days was considered necessary to maintain the

imposed treatment conditions throughout the study period.

Mean DON values were maintained at 12.3� 2.3 mg L�1 in all

treatments.

Algal and bacterial biomass and communitycomposition

Chl a density was higher in the LnG (up to 25.3 mg cm�2 on

day 29) than in the LG treatment (up to 11.6mg cm�2 on day

29, Table 1). The OD430/665 nm was positively affected by

glucose (ANOVA, Po 0.0005), thereby indicating an increase

in carotenoids and/or chlorophyll degradation products.

Chl a in the biofilms incubated in the dark was almost

undetectable. In addition, a negative correlation was found

between DOC and Chl a (r =� 0.792, P = 0.011).

The concentration of live bacteria was significantly higher

in biofilms grown under light (1.24� 107 bacteria cm�2)

than in those grown in the dark (5.13� 106 bacteria cm�2),

although the differences between treatments receiving

no glucose or glucose amendments were not significant

(Table 1). However, in light treatments, live bacteria ratio

tended to increase in the absence of glucose, from 32% to

44%, while they decreased when this monosaccharide was

added, from 31% to 22% (Glucose�Time interaction, for

live bacteria cm�2 and ratio of live to total bacteria, Table 1).

The algal community in the biofilms was qualitatively

described by optical microscopy and by SEM observations.

The bacterial community was studied both by SEM (Fig. 1)

and by molecular fingerprinting and sequencing of the

bacterial SSU rRNA genes. Nearly identical DGGE finger-

prints were obtained for the triplicate samples for each

treatment, and only fingerprints from the LG treatment

showed some discordance between replicas (Fig. 2a). De-

spite these differences, the results obtained from triplicate

treatment samples were consistent and allowed a reliable

comparison between fingerprints. In this regard, up to 82

distinct bands were observed in fingerprints from all treat-

ments (Fig. 2a). Of these, 55 representative bands were

excised and sequenced, resulting in 50 high-quality partial

16S rRNA gene sequences that were further used for

phylogenetic analyses. The total phylotypes retrieved (those

from the inoculum plus those from the treatments) grouped

in nine major phylogenetic phyla, namely Alphaproteobac-

teria, Cyanobacteria, Betaproteobacteria, Actinobacteria,

Gammaproteobacteria, Deinococcus-Thermus, Deltaproteo-

bacteria, Bacteroidetes and Gemmatimonadetes (Table 2 and

Fig. 3).

The initial biofilm suspension from the Fuirosos stream,

which was used as the inoculum, comprised mainly diatoms,

cyanobacteria and bacteria. Visual inspection of the optical

microscope images did not allow proper identification of the

main bacterial genera or species developed in the biofilms,

although some major algal groups were identified (Ach-

nanthidium minutissimum, Scenedesmus obliquus, Stigeoclo-

nium tenue). The molecular fingerprinting of the inoculum

sample gave a total of 12 bands, seven of which were selected

for sequencing because of their intensity and representative-

ness (Fig. 2a and Fig. S1). Phylotypes retrieved from the

inoculum affiliated with Alphaproteobacteria (3), Deinococ-

cus-Thermus (2), Cyanobacteria (1) and Actinobacteria (1)

(Fig. 3). Although other faint bands were observed in this

sample, it was not possible to excise them from the gel

because of their weak intensity under UV illumination. One

of these nonexcised bands was located at the same position

as band b9 (LnG and LG treatments, Fig. 2a). Although no

molecular data support this notion, it is plausible that the

sequence retrieved from b9 (a chloroplast signature from

S. obliquus, 98% similarity) was already present in the water

from the Fuirosos stream. After 29 days of incubation, the

algal and bacterial communities in the microcosms differed

clearly from that in the inoculum, and these differences were

related to the conditions under which the biofilm was

grown. In fact, most of the bands that were clearly visible in

fingerprints from the different treatments were not detected

in the inocula (Fig. 2a). These new bands were attributed to

phylotypes whose abundance in the inoculum was below the

detection limit of the technique (c. 1%, Muyzer et al., 1993),

but that they were enriched under the new conditions

imposed by the treatments. Interestingly, most of the intense

bands detected in samples from biofilms grown under light

(b9, b10, b13, b21, b22, b24, b25, b27, b28 and b56 in Fig.

2a) gave sequences affiliating with either cyanobacteria or

chloroplast from green algae (Table 2, Fig. 3 and Fig. S1),

thereby suggesting that photosynthetic microorganisms

were predominant in these samples. Optical microscopic

Table 1. ANOVA results for enzymatic activity variables (Vmax) and biofilm structure (bacteria, chlorophyll a and photon yield) after the MANOVA analysis,

considering single source effects and interactions of the three factors glucose, light and sampling time

Source

of variation Glucose Light Time Glucose� Light Glucose� Time Light� Time

Glucose� Light

� Time

Chl a 0.006 Po 0.0005 Po 0.0005 Po 0.0005 0.257 Po 0.0005 0.017

F1,24 = 9.037 F1,24 = 724.379 F2,24 = 39.604 F1,24 = 67.156 F2,24 = 1.44 F2,24 = 59.907 F2,24 = 4.892

Live bacteria cm�2 0.340 Po 0.0005 0.069 0.110 0.003 0.307 0.583

F1,24 = 0.946 F1,24 = 30.002 F2,24 = 2.991 F1,24 = 2.755 F2,24 = 7.577 F2,24 = 1.243 F2,24 = 0.551

Live bacteria (%) Po 0.0005 0.064 0.143 0.120 Po 0.0005 0.301 0.074

F1,24 = 40.318 F1,24 = 3.758 F2,24 = 2.115 F1,24 = 2.597 F2,24 = 10.862 F2,24 = 1.261 F2,24 = 2.904

Vmax peptidase Po 0.0005 Po 0.0005 0.002 Po 0.0005 0.020 0.387 0.332

F1,24 = 44.891 F1,24 = 121.330 F2,24 = 8.033 F1,24 = 42.762 F2,24 = 4.671 F2,24 = 1.045 F2,24 = 1.158

Vmax glucosidase Po 0.0005 Po 0.0005 0.018 Po 0.0005 0.017 0.063 0.159

F1,24 = 193.203 F1,24 = 20.914 F2,24 = 4.652 F1,24 = 38.394 F2,24 = 4.837 F2,24 = 3.138 F2,24 = 1.971

Photon yield 0.769 Po 0.0005 0.186 0.729 0.082 0.107 0.059

F1,24 = 0.088 F1,24 = 139.473 F2,24 = 1.804 F1,24 = 0.123 F2,24 = 2.775 F2,24 = 2.455 F2,24 = 3.197

Values o 0.05 are indicated in bold. F-ratios and degrees of freedom are also included. n = 18.

32 I. Ylla et al.

DG 1 DG 2

LnG 2LnG 1

Fig. 1. SEM photographs of the colonized glass substrata at the end of the experiment (day 29). LnG treatment: LnG1, Stigeoclonium tenue; LnG2,

diatom cells (Achnanthidium minutissmum) and Scenedesmus obliquus. LG treatment: LG1, high abundance of diatoms; LG2, bacterial filaments. DnG

treatment: DnG 1 and 2, high abundance of bacteria. DG treatment: DG1, filamentous bacteria; DG2, bacterial cells.

observations and SEM images obtained from biofilms grown

under light showed the presence of abundant algal filaments,

resembling those of the freshwater algae S. tenue, and diatoms

such as A. minutissimum and Melosira varians. Minor densi-

ties of S. obliquus were also observed in these samples (Fig. 1,

LnG 2). In glucose-amended biofilms, most of the phylotypes

retrieved grouped in Alphaproteobacteria (Figs 2a and 3 and

Fig. S1) and, at the same time, the SEM observations revealed

a high abundance of bacterial filaments (LG and DG, Fig. 1).

Additionally, several representatives of protozoa, such as

Vorticella sp., were observed under the SEM in glucose-

amended treatments. Biofilms grown under dark conditions,

1 2 31 2 1 2 3 1 2 3 1 2 3

IN LnG LG DnG DG

LnG1LnG2LnG3DnG1DnG3DnG2LG1LG3LG2DG1DG2DG3IN1IN2Inoculum

+ Gluc

No Gluc

+ Gluc

No Gluc10

9590858075706560555045

+ Gluc

No Gluc

Averaged similarity (%)(b)

Fig. 2. (a) Negative image of the DGGE fingerprint of the bacterial biofilm community developed in the inoculum and in each microcosm after 29 days

of incubation. Only one representative band at the same position was excised and sequenced from each treatment. Bands are numbered to indicate

those that yielded clear sequences and were used in phylogenetic analyses. L, DGGE ladder. (b) Unweighted pair group method with arithmetic mean

Jaccard distance dendrogram generated by considering all resolved bands (82) from the DGGE fingerprint shown above (see text for details).

34 I. Ylla et al.

in turn, showed mixed bacterial communities comprising

mostly either Actinobacteria and Betaproteobacteria (DnG

treatment) or Alpha- and Betaproteobacteria (DG treatment)

(Figs 2a and 3). In both cases, the closest-cultivated repre-

sentatives of the phylotypes retrieved from these samples

were photo- or chemoheterotrophic bacteria [Rhodococcus

Table 2. Phylogenetic affiliation of the 16S rRNA partial gene sequences obtained from DGGE bands (Fig. 2a)

Band Nearest species and taxon Accession no. % Similarity

2 Uncult. cyanobacterium clone TAF-A34 AY038729 98

3 Uncult. Phyllobacteriaceae clone Amb_16S_1129 EF018496 80

4 Hyphomicrobium sp. LAT3 AY934489 91

5 Uncult. Deinococcus sp. clone CG1-25 EF438206 82

6 Uncult. bacterium clone BTX10 EF488244 76

7 Actinobacterium kmd_307 EU723162 79

8 Uncult. Deinococcus sp. clone CG1-3 EF438203 86

9 Scenedesmus obliquus strain UTEX 393 chloroplast DQ396875 98

10 Scenedesmus obliquus strain UTEX 393 chloroplast DQ396875 99

13 Uncult. cyanobacterium isolate DGGE band 5 AY942894 93

14 Uncult. bacterium clone 255b2 EF459912 97

15 Comamonas sp. strain P-120 AM412126 93

16 Uncult. alphaproteobacterium clone EV818FW062101BH4MD6 DQ079651 80

17 Alphaproteobacterium BAC247 EU180521 94

18 Uncult. actinobacterium clone TH1-77 AM690872 75

19 Rhodococcus erythropolis strain K22-22 EU326491 96

20 Uncult. Gemmatimonadetes bacterium clone MVS-78 DQ676418 84

21 Phaeodactylum tricornutum chloroplast EF067920 97

22 Phaeodactylum tricornutum chloroplast EF067920 97

25 Uncult. cyanobacterium clone LPR90 DQ130046 89

26 Legionella pneumophila ssp. pascullei AF122885 97

29 Agrobacterium sp. CBCEN3 EF427846 90

30 Agrobacterium sp. C13 EF189105 100

31 Uncult. Rhodospirillaceae clone HrhB62 AM159277 86

32 Uncult. bacterium clone BTX10 EF488244 77

33 Uncult. alphaproteobacterium clone JG35-K2-AG57 AM116746 82

34 Rhodobacter sp. DQ12-45T EF186075 95

35 Uncult. deltaproteobacterium clone AS105 EU283398 76

36 Uncult. bacterium clone 1548 AB286604 74

38 Rhizobiales bacterium isolate D11-29 AM403229 92

39 Rhizobiales bacterium isolate D11-29 AM403229 88

40 Uncult. bacterium clone M1-53 EU015116 96

41 Ideonella sp. 0-0013 AB211233 94

42 Betaproteobacterium A0640 AF236010 95

43 Actinobacterium KV-537 AB249842 90

47 Saprospiraceae bacterium clone MS-Wolf2-H AJ786323 99

48 Agrobacterium sp. C13 EF189105 99

49 Uncult. bacterium clone RVW-06 AB199573 97

50 Uncult. bacterium clone RVW-06 AB199573 95

51 Uncult. bacterium clone 29 DQ413088 99

52 Uncult. bacterium clone FW104-022 EF693423 74

53 Uncult. Aquabacterium sp. clone GASP-WA2W2_F08 EF072951 98

55 Uncult. bacterium isolate S01_H01 AB374505 78

Bands not appearing in the table correspond to bad sequences (see text for details).

erythroplis (Actinobacteria); Rhodobacter spp. and Agrobacter-

ium spp. (Alphaproteobacteria); and Rubrivivax gelatinosus and

Sphaerotilus spp. (Betaproteobacteria)] (Table 2 and Fig. S1).

A dendrogram using the Jaccard similarity index on the

DGGE band patterns (including the total number of bands

resolved) clearly discriminated between the inoculum and

the microcosm samples, which were distributed in two

major groups, depending on the availability of labile

organic matter, i.e. glucose addition (Fig. 2b). Within each

of these two groups, microbial communities differed,

depending on the illumination conditions during the

incubation period.

Polysaccharides in EPS

The highest EPS content (measured at day 29) occurred in

the LnG microcosms (82.5� 12.8 mg glucose-equivalents

cm�2), followed by the LG (44.6� 19.5 mg glucose-equiv-

alents cm�2) and DG treatment (12.6� 7.1mg glucose-

equivalents cm�2). In comparison, the EPS content in the

Deinococcus/Thermus

Alphaproteobacteria(43%)

Cyanobacteria(14%)

Actinobacteria(14%)

Inoculum

Bacteroidetes(12.5%)

Betaproteobacteria(62.5%)

Betaproteobacteria(10%)

LnGCyanobacteria

Gemmatimonadetes(10%)

Gammaproteobacteria(10%)

Actinobacteria(20%)

Betaproteobacteria(33.5%)

Actinobacteria(44.5%)

Deltaprobacteria(12.5%)

Cyanobacteria(44%)

Alphaproteobacteria(37.5%)

Gammaproteobacteria(6%)

Fig. 3. Distribution of the phylotypes recovered both from the inoculum samples and from each treatment (in %) within the major taxonomic phyla

identified after the phylogenetic analysis.

36 I. Ylla et al.

DnG microcosm was very low (0.6� 2.2 mg glucose-equiv-

alents cm�2).

Extracellular enzyme activities

The experimental data fitted well with the Michaelis–Men-

ten expression for the two enzymes analyzed (Fig. 4).

Glucose and light, as separate factors, significantly enhanced

leucine aminopeptidase and b-glucosidase activities (Table

1). Leucine aminopeptidase activity had a much higher Vmax

in glass substrata under light than under dark conditions

(Table 1, Fig. 4a). Glucose enhanced Vmax in darkness, while

in biofilms exposed to light, no response to this mono-

saccharide was observed (Table 1, Glucose� Light

Fig. 4. (a) Leucine aminopeptidase enzyme saturation curves at the colonized substrata for LnG, LG, DnG and DG treatments throughout the

experiment. Values are means� SE (n = 3). The Michaelis–Menten saturation curves obtained after nonlinear regression analyses of the data are shown.

(b) b-Glucosidase enzyme saturation curves at the colonized substrata for LnG, LG, DnG and DG treatments throughout the experiment. Values are

means� SE (n = 3). The Michaelis–Menten saturation curves obtained after nonlinear regression analyses of the data are shown.

interaction, Fig. 4a). A progressive increase in peptidase

activity was observed throughout the experiment (Table 1,

Time effect, Fig. 4a). Km values were similar among all

treatments, ranging between 0.08 and 0.20 mM. In turn,

b-glucosidase activity showed a higher Vmax in glucose-

enriched treatments both under light and dark conditions

(Table 1, Fig. 4b). However, under light conditions, the

glucose treatment caused a slight increase in the Vmax, while

in the dark, this increase was much higher (Table 1,

Glucose� Light interaction, Fig. 4b). No significant differ-

ences were obtained for the b-glucosidase Km values

(0.01–0.07 mM).

Photosynthetic efficiency

Photon yield in the treatments was affected by light avail-

ability (Table 1), with mean values under light of 0.43� 0.4,

in contrast to nonsignificant photosynthetic efficiency un-

der dark conditions. Although no significant effect of

glucose was detected (Table 1), in the LnG treatment, the

photosynthetic yield increased throughout the experiment,

while it decreased in LG treatments (Table 1, Glucose

� Light�Time interaction). At day 29, the photosynthetic

efficiency was higher for the LnG than for the LG treatment

(P = 0.002).

Structural--functional relationships

Positive and highly significant relationships between algal

and bacterial parameters were observed in LnG microcosms,

but not in the LG ones. Hence, the photosynthetic activity

(photon yield) in the former systems was related to leucine-

aminopeptidase and b-glucosidase activities (Fig. 5). In

addition, Chl a was positively related to leucine aminopep-

tidase (r = 0.727, P = 0.026) and b-glucosidase activities

(r = 0.800, P = 0.01) in the LnG treatment, but not in LG

(r = 0.023, P = 0.952; r =� 0.432, P = 0.245, respectively).

None of these relationships were found for microcosms

incubated in the dark.

Discussion

Freshwater biofilms take up and decompose organic com-

pounds from allochthonous sources (from the flowing

water) and/or autochthonous sources (from within the

biofilm). A strong link between algae and bacteria has been

described in biofilms growing under light (Haack &

McFeters, 1982), as shown by the use of fresh autochtho-

nous organic compounds released by photosynthetic micro-

organisms. This link affects the uptake of organic matter by

biofilm microbiota (Romanı et al., 2004b). The quality and

quantity of dissolved organic matter in the flowing water

might also determine the biofilm function and structure

(Judd et al., 2006). Specifically, the addition of glucose

provides a labile organic matter source and, consequently,

increases heterotrophic biomass and activity (Olapade &

Leff, 2006).

Our results indicate interactive effects of light and glucose

on the biofilm composition and function, glucose differen-

tially affecting dark- and light-grown biofilms. The micro-

bial community composition was clearly discriminated by

glucose addition as a first factor, but secondary light and

dark communities were clearly discriminated (Fig. 2b). In

the dark, a major heterotrophic response (increase in extra-

cellular enzyme activities) due to glucose addition was

measured, while the heterotrophic response in light-grown

biofilms might be ‘buffered’ by the availability of organic

compounds excreted by photosynthetic microorganisms.

As deduced from SEM and optical microscopic observa-

tions, the addition of glucose promoted the growth of

filamentous bacteria, which formed a dense web on the glass

substratum. Although the proper identification of these

filaments from SEM images is unfeasible, the observation

that many of the phylotypes recovered from DG microcosms

Photosynthetic efficiency at PSII

800 LnG r= 0.74, P=0.022LG r= –0.42, P=0.258

50 LnG r= 0.83, P=0.005LG r=0.01, P=0.962

Photosynthetic efficiency at PSII

0.35 0.40 0.45 0.50

0.30 0.35 0.40 0.45 0.50

Fig. 5. Relationships between photosynthetic efficiency (photon yield)

and the Vmax activities of peptidase and b-glucosidase for biofilms

growing in light with or without glucose addition (LG and LnG). Model

II linear regressions (geometric mean regression) are expressed by solid

lines. Correlation coefficients and probability values are also shown.

38 I. Ylla et al.

were similar to filamentous members of Betaproteobacteria

(4 95% of sequence identity with Leptothrix spp. and

Sphaerotilus spp.) provides a plausible identification for the

dominant bacteria enriched under these conditions. The

preference for labile organic matter showed by species of the

Genus Sphaerotilus (Gao et al., 2005; Olapade & Leff, 2006)

also agree with the results obtained from these microcosms.

The prevalence of phylotypes affiliated within the Alpha-

subclass of Proteobacteria in LG microcosms does not

preclude the occurrence of filamentous forms, although the

closest relatives obtained by BLAST corresponded to nonfila-

mentous species (i.e. Rhodobacter sphaeroides, Rhizobium

spp. or Agrobacterium tumefaciens).

Glucose amendment, however, did not increase bacterial

cell density, but it decreased the proportion of living cells.

This lack of effect could be due to the effect of protozoa

grazing on bacterial density (Bott & Kaplan, 1990; Sobczak,

1996). In fact, Vorticella cells were easily identified in SEM

micrographs from glucose-amended microcosms. The het-

erotrophic bacterial community under these conditions

(glucose addition) showed strong activity in hydrolyzing

polysaccharides (high activity of b-glucosidase). The high

activity of b-glucosidase might be caused by the availability

of polysaccharides in the EPS. In this regard, the metabolic

response of the biofilm to glucose addition differed between

biofilms grown under light or dark conditions. The higher

enzymatic response on adding glucose in the latter biofilms

(Fig. 4a and b) might indicate stronger dependence of the

heterotrophic members of the biofilm community on avail-

able organic matter in the flowing water (Romanı et al.,

2004b).

In biofilms grown under light conditions, bacterial bio-

mass and heterotrophic extracellular enzyme activities are

favored by the presence and activity of photosynthetic

microorganisms, suggesting an algal–bacterial link. The high

extracellular enzyme activities (especially leucine aminopep-

tidase) and high bacterial density in biofilms grown under

light indicate that bacterial settlement and growth are

favored by the presence of algae, which probably increase

the amount of organic matter available to heterotrophs

(Romanı & Sabater, 1999; Espeland et al., 2001; Sekar et al.,

2002). Several authors have reported that proteinaceous

substances released by living or senescent algal cells enhance

leucine aminopeptidase activity (Middelboe et al., 1995;

Francoeur & Wetzel, 2003), while b-glucosidase activity is

enhanced mainly by polysaccharides released by algae (Jones

& Lock, 1993; Espeland et al., 2001). The large amount of

EPS detected in the biofilms grown under light could also

provide a major source of organic matter for bacteria

(Zhang & Bishop, 2003).

However, the influence of photosynthetic biomass on

bacterial biomass and extracellular enzyme activities de-

creased when glucose was available (Fig. 5). The obtained

results suggested that heterotrophic bacteria preferentially

use the most labile compounds such as glucose, which is

more easily and rapidly taken up than organic molecules

released by algae, which are usually of high molecular weight

(4 5000 Da; Sundh, 1989), therefore needing enzymatic

breakdown before uptake. However, changes in the trophic

relationships between algae and bacteria could be further

modulated by the effect of glucose on algal physiology and

on the structure of the microbial community (Kirchman

et al., 2004). The addition of glucose to the microcosms

lowered chlorophyll density and photosynthetic efficiency,

findings that are consistent with other observations (Sobc-

zak, 1996). The high OD ratio (OD430/665 nm) in glucose-

amended microcosms indicated a higher amount of de-

graded pigments in comparison with functional Chl a. This

observation suggests that under these conditions photosyn-

thetic microorganisms were not favored to compete with

microbial heterotrophs for space and nutrients. Therefore,

the possibility that some diatoms facultatively used organic

matter in the glucose treatment cannot be ruled out (Tuch-

man et al., 2006).

Our results indicate that the availability of glucose and

light modulates biofilm structure and function (Fig. 6).

Glucose availability affects the microbial community com-

position considerably and leads to a greater use of poly-

saccharides, whereas light availability allows the

development of a mixed, more diverse biofilm community

comprising auto- and heterotrophic members and favors the

heterotrophic use of peptides released by algae. Here, we

have confirmed that the effects of readily available organic

carbon are greater in biofilms grown in the dark than in

those grown under light. Under the latter conditions, the

release of organic molecules by phototrophs clearly benefits

the activity and growth of heterotrophic microbiota by

buffering their response to the artificial addition of organic

matter. Consequently, the autoheterotrophic biofilm

showed a tighter bacterial–algal link when it was not

supplemented with readily available organic carbon.

The extrapolation of the results to the ecosystem (stream)

scale can be performed in oligotrophic streams where

dissolved organic matter availability is usually low and of

low biodegradability. In these systems, there occur periods

of higher availability of dissolved organic matter, and these

might have a remarkable effect on the biofilm community

composition and function. Although in the present experi-

ment a very high input (designed to obtain clear effects) was

simulated, analogous increases in labile DOC might occur.

These have been described both in intermittent streams

during flood episodes after drought periods (Romanı et al.,

2006), as well as in streams suffering from anthropogenic

urban contamination. The potential effect would therefore

differ between those stream biofilms developing on illumi-

nated surfaces (upper surfaces of rocks, cobbles and sand

grains) and those developing on dark surfaces (in sediments,

under rocks and cobbles, and on leaves).

Acknowledgements

This study was funded by the projects CGL2005-06739-C02-

02 and CGL2008-05618-C02-01/BOS of the Spanish Minis-

try of Science and Technology and by the BBVA Foundation

project GLOBRIO. We thank Joan Artigas for his help with

the SEM photographs.

References

Altschul SF, Gish W, Miller W, Myers EW & Lipman DJ (1990)

Basic local alignment search tool. J Mol Biol 215: 403–410.

Battin TJ, Kaplan LA, Newbold JD & Hansen CME (2003)

Contributions of microbial biofilms to ecosystem processes in

stream mesocosms. Nature 426: 439–442.

Bernal S, Butturini A & Sabater F (2002) Variability of DOC and

nitrate responses to storms in a small Mediterranean forested

catchment. Hydrol Earth Syst Sc 6: 1031–1041.

Bott TL & Kaplan LA (1990) Potential for protozoan grazing of

bacteria in streambed sediments. J N Am Benthol Soc 9:

336–3445.

Bruns A, Hoffelner H & Overmann J (2003) A novel approach for

high throughput cultivation assays and the isolation of

planktonic bacteria. FEMS Microbiol Ecol 45: 161–171.

Chrost RJ (1990) Microbial ectoenzymes in aquatic

environments. Aquatic Microbial Ecology: Biochemical and

Molecular Approaches (Overbeck J & Chrost RJ, eds),

pp. 47–48. Springer-Verlag, New York.

DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller

K, Huber T, Dalevi D, Hu P & Andersen GL (2006a)

Greengenes, a chimera-checked 16S rRNA gene database and

workbench compatible with ARB. Appl Environ Microb 72:

5069–5072.

DeSantis TZ, Hugenholtz P, Keller K, Brodie EL, Larsen N, Piceno

YM, Phan R & Andersen GL (2006b) NAST: a multiple

FLOWING WATERDOM, POMDARK

No algal exudates

PeptidaseB-Glucosidase

DARK GLUCOSE

No algal exudates

LIGHTFLOWING WATER

DOM, POM

Algalexudates

Peptidaseb-Glucosidase

FLOWING WATERDOM, POM

Algalexudates

Extracellular enzyme

AlgaeNon filamentous bacteria

Filamentous bacteria Protozoa

FLOWING WATERDOM, POM

LIGHT GLUCOSE

Fig. 6. Schematic figure of the biofilm structure and function related to glucose and light availability. The higher photosynthesis and algal biomass

under light conditions provide fresh organic material for heterotrophs. Algal exudates preferentially increase leucine aminopeptidase activity. Addition

of glucose caused the community composition to shift toward a more heterotrophic one (filamentous-like bacteria). Under these conditions, the

availability of polysaccharides and their use (b-glucosidase activity) is increased. Under dark conditions and without any labile organic matter source

available, a low diverse thin biofilm is developed and heterotrophs depend on recalcitrant organic matter from the flowing water. When glucose is

available in heterotrophic biofilms, filamentous bacteria develop easily and the availability of polysaccharides caused by EPS production is increased,

although proteinaceous compounds are less abundant than in biofilms incubated under light.

40 I. Ylla et al.

sequence alignment server for comparative analysis of 16S

rRNA genes. Nucleic Acids Res 34: 394–399.

Dubois M, Giles KA, Hamilton JK, Rebers PA & Smith F (1956)

Colorimetric method for the determination of sugars and

related substances. Anal Chem 28: 350–356.

Espeland EM, Francoeur SN & Wetzel RG (2001) Influence of

algal photosynthesis on biofilm bacterial production and

associated glucosidase and xylosidase activities. Microb Ecol

42: 524–530.

Findlay S, Pace ML, Lints D & Cole JJ (1991) Weak coupling of

bacterial and algal production in a heterotrophic ecosystem:

the Hudson River estuary. Limnol Oceanogr 36: 268–278.

Findlay S, Howe K & Fontvieille D (1993a) Bacterial–algal

relationships in streams of the Hubbard Brook experimental

forest. Ecology 74: 2326–2336.

Findlay S, Strayer D, Goumbala C & Gould K (1993b)

Metabolism of streamwater dissolved organic carbon in the

shallow hyporheic zone. Limnol Oceanogr 38: 1493–1499.

Francoeur SN & Wetzel RG (2003) Regulation of periphytic

leucine-aminopeptidase activity. Aquat Microb Ecol 31:

249–258.

Freese HM, Karsten U & Schumannn R (2006) Bacterial

abundance, activity, and viability in the etutrophic river

Warnow, Northeast Germany. Microb Ecol 51: 117–127.

Gao X, Olapade OA, Kershner MW & Leff LG (2004)

Algal–bacterial co-variation in streams: a cross-stream

comparison. Arch Hydrobiol 159: 253–261.

Gao X, Olapade OA & Leff LG (2005) Comparison of benthic

bacterial community composition in nine streams. Aquat

Microb Ecol 40: 51–60.

Haack TK & McFeters GA (1982) Microbial dynamics of an

epilithic mat community in a high alpine stream. Appl Environ

Microb 42: 702–707.

Huber T, Faulkner G & Hugenholtz P (2004) Bellerophon: a

program to detect chimeric sequences in multiple sequence

alignments. Bioinformatics 20: 2317–2319.

Jeffrey SW & Humphrey GF (1975) New spectrophotometric

equations for determining chlorophylls a, b, and c in higher

plants, algae and natural phytoplankton. Biochem Physiol Pfl

167: 191–194.

Jones SE & Lock MA (1993) Seasonal determinations of

extracellular hydrolytic activities in heterotrophic and mixed

heterotrophic/autotrophic biofilms from two contrasting

rivers. Hydrobiologia 257: 1–16.

Judd KE, Crump BC & Kling GW (2006) Variation in dissolved

organic matter controls bacterial production and community

composition. Ecology 87: 2068–2079.

Kaplan LA & Bott TL (1989) Diel fluctuations in bacterial activity

on streambed substrata during vernal algal blooms: effects of

temperature, water chemistry and habitat. Limnol Oceanogr

34: 718–733.

Kaplan LA & Newbold JD (2003) The role of monomers in stream

ecosystem metabolism. Aquatic Ecosystems. Interactivity of

Dissolved Organic Matter (Findlay SEG & Sinsabaugh RL, eds),

pp. 99–119. Academic Press, San Diego, CA.

Kirchman DL, Dittel AI, Findlay SE & Fischer D (2004) Changes

in bacterial activity and community structure in response to

dissolved organic matter in the Hudson River, New York.

Aquat Microb Ecol 35: 243–257.

Lane DJ (1991) 16S/23S rRNA sequencing. Nucleic Acid

Techniques in Bacterial Systematics (Stackebrandt E &

Goodfellow M, eds), pp. 115–175. John Wiley & Sons, New

Lliros M, Casamayor EO & Borrego CM (2008) High archaeal

richness in the water column of a freshwater sulphurous

karstic lake along an inter-annual study. FEMS Microbiol Ecol

66: 331–342.

Ludwig W, Strunk O, Westram R et al. (2004) ARB: a software

environment for sequence data. Nucleic Acids Res 32:

1363–1371.

Margalef R (1983) Limnologıa. Omega, Barcelona.

Martinez J, Smith DC, Steward GF & Azam F (1996) Variability in

ectohydrolytic enzyme activities of pelagic marine bacteria and

its significance for substrate processing in the sea. Aquat

Microb Ecol 10: 223–230.

McCaig AE, Glover LA & Prosser JI (2001) Numerical analysis of

grassland bacterial community structure under different land

management regimens by using 16S ribosomal DNA sequence

data and denaturing gradient gel electrophoresis banding

patterns. Appl Environ Microb 67: 4554–4559.

Middelboe M, Sondergaard M, Letarte Y & Borch NH (1995)

Attached and free-living bacteria: production and polymer

hydrolysis during a diatom bloom. Microb Ecol 29: 231–248.

Munster U (1993) Concentrations and fluxes of organic carbon

substrates in aquatic environment. Antonie van Leeuwenhoek

63: 243–274.

Murphy J & Riley JP (1962) A modified single solution for the

determination of phosphate in natural waters. Anal Chim Acta

27: 31–36.

Muyzer G, de Waal EC & Uitterlinden AG (1993) Profiling of

complex microbial populations by denaturing gradient gel

electrophoresis analysis of polymerase chain reaction

amplified genes coding for 16S rRNA. Appl Environ Microb 59:

695–700.

Muyzer G, Brinkhoff T, Nubel U, Santegoeds C, Schafer H &

Wawer C (1998) Denaturing gradient gel electrophoresis

(DGGE) in microbial ecology. Molecular Microbial Ecology

Manual (Akkermans ADL, van Elsas JD & de Bruijn FJ, eds),

pp. 1–27. Kluwer Academic Publishers, Dordrecht.

Olapade OA & Leff LG (2005) Seasonal response of stream

biofilm communities to dissolved organic matter and nutrient

enrichments. Appl Environ Microb 71: 2278–2287.

Olapade OA & Leff LG (2006) Influence of dissolved organic

matter and inorganic nutrients on the biofilm bacterial

community on artificial substrates in a northeastern Ohio,

USA, stream. Can J Microbiol 52: 540–549.

Rier ST & Stevenson RJ (2002) Effects of light, dissolved organic

carbon, and inorganic nutrients on the relationship between

algae and heterotrophic bacteria in stream periphyton.

Hydrobiologia 489: 179–184.

Romanı AM & Sabater S (1999) Effect of primary producers on

the heterotrophic metabolism of a stream biofilm. Freshwater

Biol 41: 729–736.

Romanı AM & Sabater S (2000) Influence of algal biomass on

extracellular enzyme activity in river biofilms. Microb Ecol 40:

16–24.

Romanı AM, Giorgi A, Acuna V & Sabater S (2004a) The

influence of substratum type and nutrient supply on biofilm

organic matter utilization in streams. Limnol Oceanogr 49:

1713–1721.

Romanı AM, Guasch H, Munoz I, Ruana J, Vilalta E, Schwartz T,

Emtiazi F & Sabater S (2004b) Biofilm structure and function

and possible implications for riverine DOC dynamics. Microb

Ecol 47: 316–328.

Romanı AM, Vazquez E & Butturini A (2006) Microbial

availability and size fractionation of dissolved organic carbon

after drought in an intermittent stream: biogeochemical link

across the stream–riparian interface. Microb Ecol 52: 501–512.

Romanı AM, Fund K, Artigas J, Schwartz T, Sabater S & Obst U

(2008) Relevance of polymeric matrix enzymes during biofilm

formation. Microb Ecol 56: 427–436.

Sabater S & Admiraal W (2005) Biofilms as biological indicators

in managed aquatic ecosystems. Periphyton: Ecology,

Exploitation and Management (Azim ME, Verdegem MCJ, Van

Dam AA & Beveridge MCM, eds), pp. 159–177. CABI

Publishing, Cambridge, MA.

Sabater S, Guasch H, Romanı A & Munoz I (2000) The effect of

biological factors on the efficiency of river biofilms in

improving water quality. Hydrobiologia 469: 149–156.

Sabater S, Guasch H, Munoz I & Romanı AM (2006) Hydrology,

light and the use of organic and inorganic materials as

structuring factors of biological communities in

Mediterranean streams. Limnetica 25: 335–348.

Schreiber U, Gademann R, Bird P, Ralph PJ, Larkum AWD &

Kuhl M (2002) Apparent light requirement for activation of

photosynthesis upon rehydration of desiccated beachrock

microbial mats. J Phycol 38: 125–134.

Scott JT, Back JA, Taylor JM & King RS (2008) Does nutrient

enrichment decouple algal–bacterial production in

periphyton? J N Am Benthol Soc 27: 332–344.

Sekar R, Nair KVK, Rao VNR & Venugopalan VP (2002) Nutrient

dynamics and successional changes in a lentic freshwater

biofilm. Freshwater Biol 47: 1893–1907.

Sinsabaugh RL, Osgood MP & Findlay S (1994) Enzymatic

models for estimating decomposition rates of particulate

detritus. J N Am Benthol Soc 13: 160–169.

Sobczak WV (1996) Epilithic bacterial responses to variations in

algal biomass and labile dissolved organic carbon during

biofilm colonization. J N Am Benthol Soc 15: 143–154.

Sokal RR & Rohlf FJ (1995) Biometry: The Principles and Practice

of Statistics in Biological Research, 3rd edn. WH Freeman, New

Stock MS & Ward AK (1989) Establishment of a bedrock epilithic

community in a small stream: microbial (algal and bacterial)

metabolism and physical structure. Can J Fish Aquat Sci 46:

1874–1883.

Sundh I (1989) Characterization of phytoplankton extracellular

products (PDOC) and their subsequent uptake by

heterotrophic organisms in a mesotrophic forest lake.

J Plankton Res 11: 463–486.

Tuchman NC, Schollet MA, Rier ST & Geddes P (2006)

Differential heterotrophic utilization of organic compounds

by diatoms and bacteria under light and dark conditions.

Hydrobiologia 561: 167–177.

Vazquez E, Romanı AM, Sabater F & Butturini A (2007) Effects of

the dry–wet hydrological shift on dissolved organic carbon

dynamics and fate across stream–riparian interface in a

mediterranean catchment. Ecosystems 10: 239–251.

Veraart A, Romanı A, Tornes E & Sabater S (2008) Algal response

to nutrient enrichment in a forested oligotrophic stream.

J Phycol 44: 564–572.

Wetzel RG (1992) Gradient-dominated ecosystems: sources and

regulatory functions of dissolved organic matter in freshwater

ecosystem. Hydrobiologia 229: 181–198.

Wetzel RG (1993) Microcommunities and microgradients:

linking nutrient regeneration, microbial mutualism, and high

sustained aquatic primary production. Neth J Aquat Ecol 27:

3–9.

Zhang X & Bishop PL (2003) Biodegradability of biofilm

extracellular polymeric substances. Chemosphere 50: 63–69.

Supporting Information

Additional Supporting Information may be found in the

online version of this article:

Fig. S1. Phylogenetic tree showing the affiliation of the

representative bacterial partial 16S rRNA gene sequences

obtained from the DGGE bands.

Please note: Wiley-Blackwell is not responsible for the

content or functionality of any supporting materials sup-

plied by the authors. Any queries (other than missing

material) should be directed to the corresponding author

for the article.

42 I. Ylla et al.

Availability of glucose and light modulates the structure and function of a microbial biofilm

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