Journal of Environmental Science and Health Part A, 41:897–922, 2006 Copyright C Taylor & Francis Group, LLC ISSN: 1093-4529 (Print); 1532-4117 (Online) DOI: 10.1080/10934520600614546 Accessing the Black Box of Microbial Diversity and Ecophysiology: Recent Advances Through Polyphasic Experiments Gavin Collins, Siobh ´ an Kavanagh, Sharon McHugh, Sean Connaughton, Aileen Kearney, Olivia Rice, Cora Carrigg, Colm Scully, Niamh Bhreathnach, Th´ er` ese Mahony, P ´ adhraig Madden, Anne-Marie Enright, and Vincent O’Flaherty Microbial Ecology Laboratory, Department of Microbiology and Environmental Change Institute (ECI), National University of Ireland, Galway (NUI, Galway), University Road, Galway, Ireland The microbial ecology of a range of anaerobic biological assemblages (granular sludge) from full- and laboratory-scale wastewater treatment bioreactors, and of crop-growing and peat soils, was determined using a variety of 16S rRNA gene-based techniques, including clone library, terminal restriction fragment length polymorphism (TRFLP) and denaturing gradient gel electrophoresis (DGGE) analyses. Fluorescent in situ hybridization (FISH) using 16S rRNA gene-targeted probes was employed to complete a ”full-cycle rRNA approach” with selected biomass. Genetic fingerprinting (TRFLP and DGGE) was effectively used to elucidate community structure-crop relationships, and to detect and monitor trends in bioreactor sludge and specific enrichment cultures of peat soil. Greater diversity was resolved within bacterial than within archaeal communities, and unexpected reservoirs of uncultured Crenarchaeota were detected in sludge granules. Advanced radiotracer incubations and micro-beta imaging were em- ployed in conjunction with FISH to elucidate the eco-functionalism of these organisms. Crenarchaeota clusters were identified in close associated with methanogenic Archaea and both were localised with acetate uptake in biofilm structure. Address correspondence to Dr. Gavin Collins, Microbial Ecology Laboratory, Depart- ment of Microbiology and Environmental Change Institute (ECI), National Univer- sity of Ireland, Galway (NUI, Galway), University Road, Galway, Ireland; E-mail: [email protected]897
Microbial Ecology Laboratory, Department of Microbiology and EnvironmentalChange Institute (ECI), National University of Ireland, Galway (NUI, Galway),University Road, Galway, Ireland
The microbial ecology of a range of anaerobic biological assemblages (granular sludge)from full- and laboratory-scale wastewater treatment bioreactors, and of crop-growingand peat soils, was determined using a variety of 16S rRNA gene-based techniques,including clone library, terminal restriction fragment length polymorphism (TRFLP)and denaturing gradient gel electrophoresis (DGGE) analyses. Fluorescent in situhybridization (FISH) using 16S rRNA gene-targeted probes was employed to completea ”full-cycle rRNA approach” with selected biomass. Genetic fingerprinting (TRFLP andDGGE) was effectively used to elucidate community structure-crop relationships, andto detect and monitor trends in bioreactor sludge and specific enrichment culturesof peat soil. Greater diversity was resolved within bacterial than within archaealcommunities, and unexpected reservoirs of uncultured Crenarchaeota were detected insludge granules. Advanced radiotracer incubations and micro-beta imaging were em-ployed in conjunction with FISH to elucidate the eco-functionalism of these organisms.Crenarchaeota clusters were identified in close associated with methanogenic Archaeaand both were localised with acetate uptake in biofilm structure.
Address correspondence to Dr. Gavin Collins, Microbial Ecology Laboratory, Depart-ment of Microbiology and Environmental Change Institute (ECI), National Univer-sity of Ireland, Galway (NUI, Galway), University Road, Galway, Ireland; E-mail:[email protected]
The pivotal role of microorganisms in regulating a variety of ecosystem-levelprocesses, such as organic matter decomposition and nutrient cycling, isnow apparent. For example, soil microorganisms play important roles in soilquality and plant productivity.[1] Microbial characteristics of soils are beingevaluated increasingly as sensitive indicators of soil health because of the clearrelationships between microbial diversity, soil and plant quality, and ecosystemsustainability.[2] While the understanding of microbial properties such asbiomass, activity, and diversity are important to scientists in furthering knowl-edge of the factors contributing to soil health, results of such analyses may alsobe useful to extension personnel and farmers in devising practical measures ofsoil quality. Furthermore, increased awareness of greenhouse gas emissionsfrom natural soil habitats,[3] such as peatlands and marshes, has underlinedthe need to study the microbial communities of these environments. Equallyexemplary of the environmental and economic relevance of micrororganisms,are heterogenous biofilm communities of aerobic or anaerobic microbes, whichare widely employed for a variety of anthropogenic waste treatment processesand thus offer biotechnologically important applications for environmentalmanagement and conservation.
The development of effective methods for studying the diversity, distri-bution, and behaviour of microorganisms in the natural environment and inbioengineered ecosystems is essential for a broader understanding of globalnutrient cycles, soil health and potential for drug discovery, bioremediationand biotechnological advancement for environmental management. Becauseof the inherent limitations of culture-based methods[4,5] microbial ecologistsare turning increasingly to culture-independent methods of community anal-ysis. In this way, the composition of communities can be inferred based on(1) the extraction and identification of molecules from biomass that arespecific to certain microorganisms or microbial groups or (2) quantification ofthe molecules by, for example, advanced fluorescence microscopic techniques.Useful molecules for such studies include phospholipid fatty acids and nucleicacids,[6] whereas microscopic techniques involve either the hybridization offluorescent-labeled nucleic acid probes with total DNA/RNA extracted frombiomass or hybridizations with cells in situ (fluorescent in situ hybridization;FISH).[4,7]
This paper is focused on our recent studies of the microbial ecology oftwo broad ecosystem categories: (1) soils and (2) granular anaerobic wastew-ater treatment biofilms (sludge granule). Soil probably harbours most ofour planet’s undiscovered biodiversity and wastewater treatment probably
Microbial Diversity and Ecophysiology 899
best exemplifies the biotechnological potential of anthropognically-harbouredcommunities of microbes. Community-level microbial interactions in both soilsand anaerobic wastewater treatment bioreactors are complex, with individualspecies relying on the presence, function, and interaction of many otherspecies. Therefore, quantitative and qualitative detection of soil and sludgemicrobial community dynamics may serve as important and sensitive indica-tors of both short and long-term changes in soil and bioreactor efficacy. Themicrobial ecology of these communities should involve not only determinationsof microbial biomass and diversity, but also determinations of microbialgrowth, distribution, function, and, if possible, the nature of interactionsamong species. Two of the longstanding challenges in microbial ecology havebeen the development of effective methods to (1) determine which, and howmany, microorganisms are present in the environment and (2) determinemicrobial function in situ.
In light of this, the following paper provides an account of experiments to(1) elucidate the microbial diversity and/or to apply rRNA gene fingerprintingto monitor temporal and reactive community dynamics within various soilsand anaerobic sludges and (2) provide pioneering insights to structure-functionrelationships using a novel approach based on radiotracer and beta-imaging inconjunction with FISH.
MATERIALS AND METHODS
Biomass and Sampling RegimesAnaerobic Bioreactor Sludges. Five anaerobic granular sludges, A, B, C,
D and E were obtained from Irish full-scale wastewater treatment reactors(Table 1). Sludges A, B and C were used to inoculate three pairs oflaboratory-scale reactors, R1/2, R3/4 and R5/6, respectively, in a separate study(O’Flaherty; unpublished data), and reactor biomass samples at the conclusionof the trials were obtained for this study (Table 1).
Soils. Eleven soil samples, soils 1–11, were obtained from agriculturalland in Foaty (S1), Curragh (S2), Coole (S3) and Lisheen (S4) in CountyCork, Newbridge in County Galway (S5), Skerries (S6) and Ballyboghill (S11)in County Dublin, Clonaway, County Meath (S7), and Termonfeckin (S8),Tallonstown (S9) and Dunleer (S10) in County Louth, Ireland, used to growbarley (soils 1–5), potato (soils 6 and 7) and wheat (soils 8–11), respectively.The soil cores (10 cm deep) were obtained at 5 m intervals in a 20 m2
grid and the 25 samples produced were composited and mixed by shakinginside sterile plastic bags. Specimens (1 g) of soil material were removed fromthe bags and placed in respective screw-cap tubes containing 50 mL DNAstabilisation buffer (2.5 M guanidine isothyocyanate). A twelfth sample, soil12, was obtained from an ombrotrophic peat bog in County Galway, Ireland.
900 Collins et al.
Table 1: Sources of sludge biomass samples used in this study.
SludgeReactor
scale/nameWastewater
typeCODa
(g L−1)OperationalTemp (◦C)
Ab Fe Citric acid Variable 37Bc F Alcohol Variable 37Cd F Alcohol Variable 37D F Citric acid Variable 37E F Dairy Variable 37AR1 Lf/R1 Sucrose 10 16AR2 L/R2 VFAg 10 16BR3 L/R3 Whey 10 12BR4 L/R4 Whey 1 12CR5 L/R5h VFA 5 15CR6 L/R6 VFA/phenol 5 15
aCOD = chemical oxygen demand; bSludge A was used as seed inoculum for R1 and R2;cSludge B was used as seed inoculum for R3 and R4; dSludge C was used as seed inoculum forR5 and R6; eF = Full-scale; fL = laboratory-scale; gVFA = volatile fatty acids; hR5 was used asan experimental control for R6.
NUCLEIC ACID EXTRACTION
DNA Extraction from SludgeAn extraction protocol was first optimised for the recovery of total genomic
DNA from sludge granules. A number of methods were examined for isolationof nucleic acids, the merits of which were assessed by determination of the celllysis efficiency, i.e., the fewest unlysed cells while maintaining a high yield ofnon-degraded, high molecular mass DNA. Microorganisms in sludge samplesbefore and after DNA extraction were visualised microscopically according tothe method of Bitton and co-workers,[8] with the exception that Sybr-Gold(Molecular Probes, USA) was used as a stain instead of acridine orange. Asample (0.1 g) of crushed sludge (ground using a pestel and mortar) wassuspended in 500 µL of filter-sterilised (0.2 µm filter pores) water. An aliquot(100 µL) of this was added to 10 mL of filter-sterilised water. An 8 mL volumeof the diluted sample was filtered onto black Isopore (Whatman, Brentford,Middlesex, UK) membrane filters and 200 µL of Sybr-Gold (10 × stock solutionin TE buffer, pH 8) was added to the remaining 2 mL of diluted sample and leftfor 5 min. The 2 mL aliquot was then drawn onto the filter that was mountedonto a glass slide and a minimum amount of mineral oil was added under acoverslip. The samples were viewed using a Nikon Optiphot-2UV microscopefitted with a 100 W mercury bulb, a B-2A excitation filter for blue light, a 100× planar objective lens and 10× eyepieces.
Aggregates were initially disassociated by grinding, or by sonication(UltraSonik, Yucaipa, CA, USA) for 30 s, prior to microbial cell lysis using achemical lysis approach, as described by Zhou et al.[9] Alternatively, granules
Microbial Diversity and Ecophysiology 901
were disrupted and cells were lysed by mechanical disruption through bead-beating combined with chemical lysis. Different combinations of the abovewere tested and it was found that gently crushing the sludge granules witha pestle and mortar, before passing biomass, according to the manufacturersinstructions, through a Soil DNA Kit (MoBio Laboratories, Inc.) gave thehighest yield of good quality DNA with little shearing, and provided overallbest microbial cell lysis.
DNA Extraction from SoilPrior to DNA extraction all solutions were rendered DNase-free by treating
with diethyl pyrocarbonate (DEPC). DNA was extracted from 0.5 g (wetweight) of soil. A mixture (0.5 g) of zirconia, silica and glass beads (BiospecProducts, USA) were added with 1 mL of cetyltrimethylammonium bromide(CTAB) extraction buffer (1% [w/v] CTAB; 10% [v/v] 1 M Tris-HCl; 20% [v/v] 0.5M EDTA, pH 8; 8.8% [w/v] NaCl; 1.1% [w/v] Na3PO4) to 2 mL micro-centrifugetubes, which were beaten for 1 min using the Mini Beadbeater-8 (BiospecProducts, Inc., Bartlesville, OK, USA). Aliquots of 500 µL of lysis extractionbuffer (50 mM Tris-HCl pH 8.0, 40 mM EDTA pH 8.0, 0.75 M filter sterilisedsucrose) and 200 µL of lysozyme (10 mg mL−1; Sigma-Aldrich, Dublin, Ireland)were added. Samples were incubated in a water bath at 37◦C for 30 min,followed by the addition of 200 µL of 10% sodium dodecyl sulphate (SDS) andincubation at 70◦C for 1 h. Then 6 µL of 17.9 mg proteinase K mL−1 stocksolution were added and the tubes were incubated at 50◦C for 30 min. Sampleswere centrifuged (10,000 × g) for 15 min and supernatants were transferredto respective fresh micro-centrifuge tubes. The aqueous phase was extractedby the addition of an equal volume of chloroform:isoamyl alcohol (24:1) andcentrifugation (10,000 × g) for 10 min. Supernatants were transferred to new2 mL micro-centrifuge tubes and DNA was precipitated by adding 0.6 volumesof isopropanol to respective samples prior to over-night incubation at roomtemperature. DNA was pelleted by centrifugation (10,000× g) for 10 min andwashed with 70% (vol/vol) ice-cold ethanol before air drying and re-suspendingin DEPC-treated water. Lysis efficiency of soil extraction experiments wasdetermined as described above but using 0.1 g soil material.
16S rRNA Gene Clone Library AnalysisArchaeal and bacterial 16S rRNA genes (from each sludge except Sludge E)
were amplified with forward primer 21F (5′-TTCCGGTTGATCCYGCCGGA-3′)[10] and reverse primer 958R (5′-YCCGGCGTTGAMTCCAATT-3′),[11] andforward primer 27F (5′-GAGTTTGATCCTGGCTCAG-3′)[11] and reverseprimer 1392R (5′-ACGGGCGGTGTGTRC-3′),[12] respectively.[13] The cycle pro-files used were denaturation at 95◦C for 1.5 min, annealing at 55◦C (archaeal)
902 Collins et al.
or 52◦C (bacterial) for 1.5 min and extension at 72◦C for 1.5 min; the numberof cycles was 30. It was discovered through PCR optimization that a 3 minextension time was necessary for some archaeal PCR experiments using soilDNA. PCR amplicons were ligated into the plasmid vector pCR 2.1-TOPO(Invitrogen) and used to transform TOPO 10 (Invitrogen) competent E. colicells by following the manufacturers instructions. Clone libraries were gener-ated by growing 96 archaeal and bacterial clones in respective 96-well micro-plates and operational taxonomic units (OTUs)[14] were identified throughamplified rDNA restriction analysis of all clones with the tetrameric restrictionendonuclease HaeIII as described by Collins et al.[13] Sequencing of the insertsof representative clone(s) from each OTU was achieved using vector specificprimers on a Licor gel sequencer (MWG Biotech, Milton Keynes, UK). Relevantsequences from this study were deposited in the Genbank database underthe accession numbers AY161236-AY161261, AY228682-AY228701, AY231301-AY231364, AY239506-AY239582 and AY835782-AY835826. Sequences werecompared with the nucleotide database using BLAST (Basic Local AlignmentSearch Tool)[15] and were manually aligned with sequences retrieved from theRibosomal Database Project (RDP).[16]
Terminal Restriction Fragment Length Polymorphism AnalysisArchaeal and bacterial PCR experiments were carried out as described
above, except that forward (21F and 27F) and reverse primers (958R and1392R) were labelled at the 5′ end with the phosphoramidite dyes 6-FAMand HEX, respectively.[13] PCR amplicons were used directly for endonucleaserestriction and separate digestions were processed, in the manufacturer’srecommended buffers, with the four-bp-cutting enzymes HhaI and AluI (sepa-rately) at 37◦C for 6 h. Terminal restriction fragments (TRFs) were sized usingan automated ABI PRISMTM Genetic Analyser (Oswel Genetic Analysis, UK).Genescanő 3.1 software (Applied Biosystems, CA) was used to analyse theelectropherogram output and sample data consisted of the size (base pairs),peak height and peak area for each TRF peak in sample profile. More than 300archaeal and 700 bacterial in silico TRFLP simulations were carried out usingthe primer combinations and endonuclease restriction sites, and sequencesfrom the RDP and Genbank databases. Predicted TRF lengths were thenused for comparison with actual TRFs obtained from this study. In addition,predicted TRF lengths of known archaeal and bacterial species were obtainedusing the TAP-TRFLP tool of the RDP database.[17]
Denaturing Gradient Gel ElectrophoresisFollowing PCR-amplification of 16S rRNA genes as described above,
but by using unlabeled oligonucleotide primer sets, the V3 regions
Microbial Diversity and Ecophysiology 903
of archaeal and bacterial genes were amplified by performing nestedPCR using 1 µL of the domain-specific PCR products as respectivetemplates. The primers used for archaeal[18] and bacterial[19] nestedPCRs were forward primer 340F (5′-TACGGGG(CT)GCA(GC)CAG-3′)and reverse primer 519R (5′-TTACCGCGGC(GT)GCTG-3′), and forwardprimer 341F (5′-CCTACGGGAGGCAGCAG-3′) and reverse primer 517R(5′-ATTACCGCGGCTGCTGG-3′), respectively. The forward primers had a40 base GC clamp attached to the 5′ end.[19] It was necessary to performtouchdown PCR to optimize amplicon quality; denaturation was 95◦C for45 s with an initial annealing temperature of 65◦C for 45 s and extension at72◦C for 1 min. The annealing temperature was dropped by 1◦C every cycleuntil it reached 55◦C and 15 cycles were carried out using this annealingtemperature. A final extension was performed at 72◦C for 10 min. DGGEwas performed using the D-Code system (BioRad, USA). Polyacrylamide gelswere prepared with denaturing gradients ranging from 35% to 70% (where100% denaturant contained 7 M urea and 40% formamide (Sigma-Aldrich)).Running conditions were 60◦C, 60 V over 12 h. Gels were stained for 15 minin Sybr-Gold (Sigma-Aldrich) nucleic acid stain, de-stained for 10 min insterile DEPC treated water and photographed on a UV trans-illuminationtable. DGGE gels were visually analysed by scoring the presence (1) andabsence (0) of bands appearing in each lane of the gel to create binarymatrices. For all binary matrices, distances were calculated based on bothJaccard’s and Dice’s similarity coefficients. Clusters were constructed by theunweighted-pair group method using arithmetic averages (UPGMA)[20] fromresulting distances using MEGA version 2.1.[21]
Enrichment CulturingSludge E was used as inoculum for anaerobic enrichment cultures. Sludge
granules were inoculated to 60 mL sealed hypovials (Pierce, Rockford, IL, USA)containing anaerobic enrichment medium[22] to a final concentration of 2–5 gvolatile suspended solids (VSS) l−1. Different organic substrates were added torespective vials: benzoic acid (3000 ppm), phenol (3000 ppm), 2-chlorophenol(CP; 60 ppm), 2,4-dichlorophenol (DCP; 60 ppm), 2,4,6-trichlorophenol (TCP;60 ppm) and 2,3,4,5,6-pentachlorophenol (PCP; 0.5 ppm) for the isolationof specific microorganisms of biotechnological interest. Cultures were incu-bated at 4◦C, 15◦C and 37◦C, and growth was monitored by measuring thepressure increase in the headspace of vials due to biogas production andby substrate depletion measured by HPLC (liquid chromatograph LC-6A,UV spectrophotometric detector SPD-6A and chromatopac C-R3A; Shimadzu,Duisburf, Germany). Samples were separated on a Hypersil-ODS C18 column,2.1 mm i.d. × 100 mm long × 3 µm particle size. The detection wavelengthwas set at 282 nm and the flow rate of the mobile phase was set at 1 mL
904 Collins et al.
min−1. The mobile phase used contained methanol: acetic acid: H2O (70:1:29).Enrichments were sub-cultured (10%) to fresh medium and substrate after70 days in the case of 37◦C and 15◦C enrichments, and after 120 days inthe case of 4◦C enrichments. The same strategy was employed for soil 12for the enrichment of acetate-, butyrate-, propionate- and hydrogen (H2/CO2)-degrading communities. In the case of soil 12 enrichment cultures, samplesof the liquid culture were obtained, on the same day as sub-cultures wereinoculated, for DNA extraction and PCR-DGGE analysis.
Fluorescent In Situ Hybridization ExperimentsBriefly, biomass samples were washed gently in phosphate buffered saline
(PBS) three times and were fixed in 4% paraformaldehyde (Sigma-Aldrich)in PBS, at 4◦C for 6 h before exposure to PBS:ethanol (1:1 v/v) for 12 hat 4◦C. Soil samples were used directly for FISH, as described by Schrammet al.[23] Sludge granules were embedded in OCT (Sakura, Torrance, CA,USA) freezing medium overnight at 4◦C. Serial sections (8 µm thick) werecut using a cryomicrotome and mounted on glycerol-coated slides before FISH.A hierarchial set of fluorescently labeled 16S rRNA-targeted oligonucleotideprobes (Biomers.net, Germany) was used for FISH: (i) Arch915,[24] specificfor Archaea; (ii) Eub338,[25] specific for Bacteria; (iii) Cren499,[26] specific formost of the Crenarchaeota; (iv) Mx825,[27] specific for Methanosaeta spp. and(v) Sarci551,[28] specific for Methanosarcina spp. were used in this study.Probes were fluorescently labeled at the 5′ end with either Cy3 or Cy5.Based on a comparative analysis of recently available aligned 16S rRNAgene sequences by BLAST <http://www.ncbi.nlm.nih.gov/>, as well as theassistance of the Probe Match program of the RDP-II,[29] the specificity of theprobes was examined theoretically with target and non-target microorganisms.Hybridisations were carried out according to the method of Manz et al.[30] AZeiss LSM 510 confocal microscope with multiphoton laser source (Carl ZeissLtd., Herts, UK) was employed for confocal laser scanning microscopy (CLSM)using hybridized sections.
Radiotracer Incubation and Micro-β-ImagingSubstrate-uptake patterns of Sludge D were investigated using a radioac-
tive tracer technique[31] and beta imaging.[32] Aliquots of 50 µl of sludge(2.8 mg suspended solids [SS]) were added to 1.5 mL microcentrifuge tubes forradiotracer incubations. Sterilised (121◦C, 15 min) biomass samples were usedas negative controls. An organic substrate was tested: [1(2)-14C] acetic acid,sodium salt (specific radioactivity, 59 mCi mmol−1; Amersham Biosciences,Buckinghamshire, UK) and unlabelled substrate was pure grade aceticacid (Sigma-Aldrich). Tests were carried out in triplicate and the startingconcentration of acetate in each tube was 100 mM. After incubation, organic
Microbial Diversity and Ecophysiology 905
substrate was replaced with chilled 4% paraformaldehyde in 1× PBS andincubated at 4◦C for 6 h. Samples were washed in PBS and stored inPBS:ethanol (1:1) at −20◦C, before preparation for cryo-sectioning as before.Sectioned samples were scanned for radioactivity using a micro-beta-imager(Biospace, Paris, France) and in situ hybridizations were carried out asdescribed.
RESULTS
DNA ExtractionDNA extraction protocols carried out using samples of sludge granules and
soil provided cell lysis efficiencies of >99% according to microscopic analysis,which revealed that fewer than 1% of all cells observed prior to extractionsremained unlysed post-extraction (data not shown).
Community Structure Determined By 16S rRNA Gene CloneLibrary Analysis16S rRNA gene clone library analysis identified greater diversity within
the bacterial than archaeal communities of Sludges A-D. For example, theBacteria-specific clone library generated from Sludge C indicated the distri-bution of bacterial clones throughout relatively disparate phylogenetic groups(Figure 1A), while the majority (10 of 13) of archaeal OTUs from Sludge C werefrom the order Methanosarcinales (one of the five methanogenic phylogeneticgroups; data not shown). The range of functions of the major constituents ofthe Bacteria in anaerobic digester ecosystems include hydrolysis, fermenta-tion and the syntrophic metabolism of organic acids, ketones and alcohols,thus giving rise to diverse bacterial communities. On the other hand, lowermethanogenic diversity may reflect the more specific functional role of theseorganisms. However, the three remaining (3 of 13) archaeal OTUs from SludgeC accounted for over 50% of the total number of clones in the library and wereaffiliated to the Crenarchaeota (a sub-domain of the Archaea; data not shown).Furthermore, 75% of all archaeal clones from Sludge D were phylogeneticallyrelated to members of the non-thermophilic Crenarchaeota (Figure 1B). Asummary of the results of clone library analyses from each of the sludgesamples is presented in Table 2.
Ribotyping and Temporal Community AnalysesTRFLP ribotyping was successfully used to monitor the populations
present and determine community dynamics in R1–R6. Importantly, broadagreement between the results of clone library and TRFLP analyses wasobserved. For example, TRFs were routinely observed in reactor biomasssamples, which were of the same length and presumptive phylogeny as
906 Collins et al.
Figure 1: Phylogenetic relationships among (A) bacterial and (B) archaeal SSU rRNA genesfrom sludge C and D, respectively, inferred by neighbour joining. Clonal sequences from thisstudy are in bold typeface and are denoted by an asterix (∗). Bootstrap replicates (out of atotal of 100 replicate samplings) that supported the branching order are shown at relevantnodes. Scale bar represents 1 nucleotide substitution per 100 sequence positions.(Continued)
Microbial Diversity and Ecophysiology 907
Figure 1: (Continued)
clones from the seed sludge clone libraries. The presumptive phylogeny ofpredominant archaeal and bacterial TRFs detected in the seed sludges andthose at the conclusion of the respective trials are presented in Table 3.In general, greater dynamism was detected within bacterial than within
Tab
le2:
Clo
sest
rela
tive
so
fp
red
om
ina
nt
seq
ue
nc
es
inre
spe
ctiv
eg
en
elib
rarie
sg
en
era
ted
fro
mth
ese
ed
slud
ge
(ino
cu
lum
)a
nd
rea
cto
rbio
ma
sssa
mp
les
at
the
co
nc
lusio
no
fre
spe
ctiv
ew
ast
ew
ate
rtre
atm
en
ttr
ials
.
Slud
ge
Arc
hae
aBa
cte
ria
AM
eth
an
osa
eta
(54%
);C
ren
arc
ha
eo
ta(2
8.8%
)G
ram
+ve
[e.g
.Clo
strid
ium
](2
8%);
BCF∗
(11.
7%)
BC
ren
arc
ha
eo
ta(5
9.6%
);M
eth
an
osa
eta
(21%
)γ
-Pro
teo
ba
cte
ria(2
4%);
Pse
ud
om
on
as
(19.
7%)
CM
eth
an
oc
oc
cu
s(6
2%);
Cre
na
rch
ae
ota
(38%
)BC
F∗(4
8.7%
);δ-P
rote
ob
ac
teria
(26.
8%);
DC
ren
arc
ha
eo
ta(7
4.8%
);M
eth
an
oc
ulle
us
sp.(
11%
)δ-P
rote
ob
ac
teria
(37%
);Ba
cte
roid
es
sp.(
23.1
%)
AR
1M
eth
an
oc
orp
usc
ulu
msp
.(84
.2%
);M
eth
an
osa
eta
(12.
7%)
Gra
m+v
e∗∗
(46%
);Ba
cte
roid
es
sp.(
30%
)A
R2
Me
tha
no
co
rpu
scu
lum
sp.(
73%
);M
eth
an
osp
irillu
m(4
.5%
)Ba
cte
roid
es
sp.(
33.4
%);
δ-P
rote
ob
ac
teria
(27.
9%)
B R3
Me
tha
no
co
rpu
scu
lum
sp.(
84%
);C
ren
arc
ha
eo
ta(1
4%)
Bac
tero
ide
ssp
.(39
.7%
);G
ram
+ve
sp.∗∗
∗(1
0.8%
)B R
4C
ren
arc
ha
eo
ta(7
8.3%
);M
eth
an
osa
eta
(15.
2%)
BCF∗
(41.
4%);
vario
us
un
cu
lture
dc
lon
es
(32.
9%)
CR
5M
eth
an
oc
orp
usc
ulu
msp
.(98
%);
Me
tha
no
sae
ta(2
%)
δ-P
rote
ob
ac
teria
(35.
6%);
Cyt
op
ha
ga
sp.(
4.4%
)C
R6
Me
tha
no
co
rpu
scu
lum
sp.(
60%
);M
eth
an
osa
eta
sp.(
40%
)U
nc
ultu
red
clo
ne
s(4
8.9%
);BC
F∗(2
3.2%
)
∗ Va
riou
sm
em
be
rsfr
om
the
Bac
tero
ide
s-C
yto
ph
ag
a-F
lexi
ba
cte
rg
rou
p.
∗∗M
ost
lyA
ce
tob
ac
teriu
m-li
kec
lon
als
eq
ue
nc
es.
∗∗∗ M
ost
lyu
nc
ultu
red
org
an
isms.
908
Tab
le3:
Pre
sum
ptiv
ep
hylo
ge
ny
an
dsiz
e(b
ase
pa
irs)
of
pre
do
min
an
tTR
Fp
ea
k(s)
reso
lve
db
yTR
FLP
an
aly
siso
fse
ed
slud
ge
(ino
cu
lum
)a
nd
rea
cto
rbio
ma
ssa
tth
ec
on
clu
sion
of
resp
ec
tive
wa
ste
wa
tert
rea
tme
nt
tria
ls.
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910 Collins et al.
archaeal reactor communities. The potential value of genetic fingerprintingto practical reactor operation was highlighted by the results obtained fromTRFLP analysis of R3 biomass, when disintegration of the sludge bed granulesand process disturbance could be predicted well in advance by using molecularbiomonitoring (Figure 2). A distinct shift in archaeal population structure wasnoted in R3 during a 500-day trial, with a decrease in the relative abundanceof Methanosaeta sp. and a proliferation of hydrogenotrophic methanogens(Methanomicrobiales sp.). Although the population change was well underwayby day 300—the granulation and performance problems did not manifestuntil day 425.[33] DGGE ribotyping illustrated differences in the commu-nity structure of Soils 1–11 (Figure 3). Furthermore, UPGMA statisticalanalyses based on DGGE genetic fingerprints obtained using the Bacteria-specific oligonucleotide primers illustrated crop-specific microbial diversitypatterns (Figure 3). In addition, two identical fragment bands from wheatand potato profiles were excised from DGGE gels for DNA sequence analysis(Figure 3) and phylogenetic reconstruction as described by Collins et al.[13]
The closest relatives of the shared ribotype were uncultured members of theα-Proteobacteria.
Enrichment of Environmentally and Biotechnologically ImportantMicroorganismsAll phenolic compounds tested were biodegradable, under the three
temperature conditions, by Sludge E as determined by biogas production(Figure 4i) and substrate depletion evaluated by HPLC (data not shown).In the case of soil 12, DGGE fingerprinting illustrated a temporal reductionin the number of phylotypes present in acetate-degrading anaerobic culturesafter successive sub-culturing events, and analyses of DGGE matrices illus-trated the temporal population succession within the culture (Figure 4ii andiii).
FISH and Spatio-Structural AnalysesIn situ hybridizations of fixed granule sections with oligonucleotide probes
specific for the Archaea and Bacteria were viewed using CLSM. The digitalimages obtained indicated the localization of bacterial and archaeal cellson the periphery and towards the centre of granule sections, respectively,thus suggesting an organized distribution of microbial groups within thearchitecture of the seed sludge granules (Figure 5). Hybridizations carried outusing sludges C and D and the Crenarchaeota-specific probe, Cren499, revealedthe overestimation of Crenarchaeota-like species by clone library analysis(hybridizing with 25–40% of all cells present), thus reflecting the value of
Microbial Diversity and Ecophysiology 911
Figure 2: TRFLP profiles generated, by the restriction of Archaea-specific PCR products withHhaI, from R3 reactor biomass on days (i) 0, (ii) 21, (iii) 98, (iv) (218), (v) 285, (vi) 354 and (vii)409 of the trial period, illustrating the shift in archaeal population structure (frompredominantly acetoclastic to hydrogenotrophic) prior to process disturbance (by day 400)and granule disintegration (from McHugh et al.33).
912 Collins et al.
Figure 3: (A) DGGE fingerprints of the 11 soil samples used to cultivate (i) barley (lanes 1–5:soils 1–5, respectively, and lane ‘∗’: DGGE pattern of positive control 16S rRNA gene fromEscherischia coli) and (ii) potato (lanes 6 & 7: soils 6 & 7, respectively) and wheat (lanes8–11: soils 8–11, respectively); bands chosen for sequence analyses are indicated by (•);(iii) UPGMA dendrogram illustrating the stastistical relationship of the different soils, based onDGGE polymorphism patterns.
this polyphasic approach (clone libraries, TRFLP and FISH) to ecologicalinventories. Crenarchaeota cells were rods of length 1.5 µm and width 0.7µm, which occurred in dense clusters within a layered, granular biofilm,architecture (Figure 5). FISH images revealed the presence of Crenarchaeota
Microbial Diversity and Ecophysiology 913
microcolonies at the edge of granule sections (the granule surface) of sludges Cand D, with Bacteria located toward the granule core. Crenarchaeota were alsodetected along channels extending from the surface toward the granule core ofSludge C (data not shown) and D (Figure 5).
Figure 4: (i) Net (after normalization in respect of background gas evolved from control[blank] asssays) biogas production rates of anaerobic pentachlorophenol-degradingcultures at 37◦C, (�) 15◦C (�) and (•) 4◦C; (ii) principal co-ordinate (PCO) analysis illustrationof similarity matrices generated from temporal DGGE analysis of the anaerobic acetatedegrading peat culture: ace 1—first culture immediately prior to sub-culturing; ace2—second culture; ace 3—third culture; ace 4—fourth culture; ace 5—fifth culture;(iii) UPGMA dendogram illustrating the succession within the archaeal community of theacetate enrichment culture. Acetate depletion was confirmed by gas chromatographyanalysis of culture liquid (data not shown). (Continued)
914 Collins et al.
Figure 4: (Continued)
Ecophysiological Structure-Function Relationshipsof Environmental BiofilmsBeta-imaging suggested the localised accumulation of radioactive acetate
in the outer layers of Sludge D biofilm sections. This coincided with anabundance of filamentous Methanosaeta cells in juxtaposition with Cren499-positive cell clusters around the outer layer of these Sludge D granules(Figure 5).
DISCUSSION
In the past, the study of microbial communities has been hampered by theinability to culture the majority of indigenous microorganisms.[4,34] However,the advent of nucleic acid based technologies has provided a means to overcomethis limitation, allowing for the monitoring of organisms or particular genesdirectly from environment samples.[9] The 16S rRNA gene is the most com-monly targeted molecule in studies of microbial diversity and fingerprintingtechniques such as DGGE,[19,35,36] and TRFLP[37–39] are being used on an ever-increasing basis to measure microbial diversity. A prerequisite to any study ofthe total microbial community is the extraction of nucleic acids suitable for
Microbial Diversity and Ecophysiology 915
Figure 5: In situ hybridizations of anaerobic granule sections illustrating (i) the layeredgranule structure: Bacteria (A) on the surface and Archaea (B) in the granule core (x40magnification); (ii) micro-colony of Cren499-positive cells (Crenarchaeota) located at theperiphery of a Sludge D section (x63); (iii) high resolution image of Crenarchaeota cells(x100); (iv) Crenarchaeota cells located along a channel extending from the granulesurface toward the centre of a Sludge D granule (x63). A micro-beta image (v) ofcross-section of typical Sludge D specimen depicting uptake (bright spots) of radiolabelledacetate at 15◦C, which was co-localised with juxtapositioned Methanosaeta andCrenarchaeota cells at the granule surface.
PCR[40] or quantitative measurements such as nucleic acid hybridization (e.g.,Amann et al.[25]). DNA extraction methods are divided into two categories:[41]
cells are either first removed from the sample before being lysed or are directlylysed and extracted within the matrix. The latter approach is generally re-garded as providing the best nucleic acid yield and least bias.[34,42] The lysis ef-ficiency of any nucleic acid extraction technique is critical in order to ensure theresulting DNA/RNA provides an unbiased representation of the total microbialcommunity.[42] Therefore, a robust and efficient cell lysis procedure must beemployed and the methods used in this study fulfilled these criteria, thusproviding satisfactorily representative nucleic acids from the sludge and soilsamples for the generation of microbial community profiles by PCR-mediatedapproaches. However, there are also inherent problems with PCR-based tech-niques, including the bias introduced by PCR itself [43,44] and difficulties withreproducibility of results due to PCR suppression by inhibiting substances,such as humic acids.[45] However, at present such techniques remain the mostcomprehensive and best way to measure total microbial diversity.
916 Collins et al.
Genetic libraries (e.g., 16S rRNA gene libraries) and fingerprints (e.g.,TRFLP/DGGE) allow comprehensive phylogenetic characterization of micro-bial communities and rapidly provide a profile of the community, respectively.Importantly, we demonstrated agreement between gene libraries and TRFLPanalyses, thus permitting the use of genetic fingerprinting as, for example,biomonitoring tools for frequent determination of temporal dynamics in paral-lel with occasional gene library inventories. In this way, unnecessary expenseand effort required by clone library analyses may be circumvented. The valueof using genetic fingerprinting for monitoring natural and engineered ecosys-tems was highlighted by this work, particularly with respect to linking biotech-nological process phenomena with underlying microbial community events(e.g., R3; Figure 2). Although, bacterial populations—in, for example, thebioreactors studied—were more dynamic than archaeal populations, changesin the archaeal community were linked to process instability, while dynamicbacterial communities were observed in the biomass of functionally stablereactors, which concurs with the findings of Fernandez et al.[46] Furthermore,crop-microbes relationships could be statistically identified based on geneticfingerprints obtained from various soils (Figure 3). Despite, the apparentadvantages of TRFLP/DGGE, however, each technique concomitantly presentsvarious experimental drawbacks. For example, although terminal restrictionfragments (TRFs), which are phylogenetically representative of clones foundin genetic libraries, may be monitored throughout a given experimentalperiod, the reliance of this technique on enzyme specificities may preclude thedetection of new species within the community. Conversely, although DGGEis practically useful for monitoring changes in temporal community dynam-ics, the identification of ribotypes requires expensive and labour intensivePCR-amplification and DNA sequencing. Nevertheless, the ultimate phyloge-netic resolution achievable through DGGE analysis is superior to TRFLP dueto the possibility of sequence analyses of excised bands. It follows, that studiescombining both techniques, even in the absence of genetic libraries, wouldgenerate more comprehensive and integrated datasets and this approachshould be adopted in future studies.
Despite the import of data derived from PCR-mediated techniques, thelimitations of this approach viz. potentially unrepresentative nucleic acidextraction, PCR bias, etc. should be addressed using quantitative PCR (e.g.,Brunk and Eis[47]) or PCR-independent techniques such as FISH. In the caseof the latter, by applying a ”full-cycle rRNA approach,” it is possible to firstdescribe the microbial diversity of biomass specimens (clone libraries) and topositively quantify individual species within the whole community (FISH).Furthermore, in the case of, for example, the granule specimens, FISH com-bined with advanced fluorescent microscopy allows the measurement of spatio-structural parameters within biotic communities. This is particularly useful todescribe temporal changes in the architectural structure of biotechnologically
Microbial Diversity and Ecophysiology 917
important biofilms, such as sludge granules, but also for the description of thecellular morphology of previously uncultivated organisms, such as members ofthe Crenarchaeota.
Understanding the functionality of microbial communities in natural andengineered ecosystems is still a major objective for microbial ecologists. Insome cases, PCR-targeted phylogenetic markers can be related to functionalgroups such as nitrifying bacteria, but our lack of knowledge about un-cultured groups and their functions means this approach has only limitedapplication. For example, the widespread possession of denitrification genesin many distantly related species of Bacteria (and Archaea), has meantthat 16S rRNA gene-based methods cannot be used to study the functionaldiversity of the process. Thus, only genes encoding denitrification enzymes canprovide functional markers for ecological studies. However, in this example,complete denitrification requires the sequential action of four enzymes, oftenbiochemically distinct enzymes catalyse the same reaction and it is commonfor microorganisms to have involvement in only a part of the pathway. Thiscomplexity of heterogeneous communities makes it difficult to use a single genemarker to denote specific functionalism.
Virtually nothing is known about the morphology or physiological role(s)of non-thermophilic Crenarchaeota in the biosphere. Despite the detection ofthese organisms in anaerobic wastewater treatment bioreactors,[48] abundantcrenarchaeal populations in anaerobic sludge have not been described before.The approach adopted by this study to elucidate the ecophysiology of Cre-narchaeota in anaerobic sludge granules capitalizes on recent experimentaladvances, which allow the observation of substrate uptake in conjunctionwith in situ molecular microbiology. The results obtained from FISH andbeta-imaging demonstrated that these organisms are closely associated (spa-tially) with metabolically active acetoclastic methanogens. Indeed, the ar-rangement of these organisms at the periphery of sludge granules is unusualwith respect to the other granular sludges studied here, and previouslydescribed granule structures within which, archaeal cores were enveloped bya bacterial surface.[49]
Consequently, a tentative hypothesis as to the ecological role of Cre-narchaeota in anaerobic wastewater treatment biofilms can be formed,whereby these organisms are involved in the supply of intermediate break-down products to methanogens. However, further beta-imaging work andmicroautoradiography-FISH (MAR-FISH)[50] with a broader range of sub-strates are necessary to elucidate the full in situ functionalism and eco-physiology of Crenarchaeota in anaerobic granules. Indeed, greater cellularresolution can be achieved by MAR-FISH to test such hypotheses.[51] Inaddition, stable isotope probing (SIP),[52] which is less expensive than MAR-FISH, can be carried out by incubating biomass with C13-labelled substrates;in this case organisms incorporating label into DNA are identified using a 16S
918 Collins et al.
rRNA gene approach (e.g., clone libraries), following CsCl2 density gradientcentrifugation. This can help identifiy substrate degraders, but also to selectappropriate substrates for MAR-FISH experiments and ensure the most cost-effective use of this technique.
The microbial ecology of soil still presents a challenge to microbiologistsattempting to establish the ways in which microbial communities activelymetabolise substrates, link into food webs and recycle plant and animalremains and provide essential nutrients for plants. Equally, the identity andfunction of many of the species found in anthropogenically-engineered biofilmselude scientists and bioengineers alike. Nevertheless, both extraction andin situ analyses of rRNA genes has enabled identification of functionallyimportant taxa, and recent advances in genomic analysis, like stable isotopeprobing and microautoradiography are the first steps in resolving the linkagebetween structure and function in microbial communities.
CONCLUSIONS
We can draw the following important conclusions from this study: (1) thenucleic acid extraction protocols used provided excellent microbial cell lysisefficiencies to ensure representative recovery of genomic DNA; (2) geneticfingerprinting is suitable for monitoring temporal community dynamics inbiomass from both natural and engineered environments; (3) TRFLP has apotential application for the prediction of biotechnological process disturbancebased on changes in microbial community structure; (4) combined TRFLP andDGGE should be carried out to obtain maximum benefits from environmen-tal genetic fingerprinting (5); (5) the detection of abundant Crenarchaeotapopulations in anaerobic wastewater treatment biofilm is a new and surprisingfinding with potential implications for biotechnological developments.
ACKNOWLEDGMENTS
The financial support of the Higher Education Authority (HEA) Programme forResearch in Third Level Institutes (PRTLI)-Cycle II, through the Environmen-tal Change Institute (ECI) and the National Centre for Biomedical Engineer-ing Sciences (NCBES), NUI, Galway is gratefully acknowledged. EnterpriseIreland and Irish Research Council for Science Engineering and TechnologyResearch Scholarships to G.C. and P.M, respectively, are also acknowledged.
REFERENCES
1. Torsvik, V.; Øvreas, L. Microbial diversity and function in soil: from genes toecosystems. Curr. Opin. Microbiol. 2002, 5 (3), 240–245.
Microbial Diversity and Ecophysiology 919
2. Garbeva, P.; van Veen, J.A.; van Elsas, J.D. Microbial diversity in soil: selection ofmicrobial populations by plant and soil type and implications for disease suppressive-ness. Annu. Rev. Phytopathol. 2004, 42, 243–270.
3. Topp, E.; Pattey, E. Soils as sources and sinks for atmospheric methane. Can. J. SoilSci. 1997, 77, 167–178.
4. Amann, R.I.; Ludwig, W.; Schleifer, K.H. Phylogenetic identification and in situdetection of individual microbial cells without cultivation. Microbiol. Rev. 1995, 59,143–169.
5. Torsvik, V.; Daae, F.L.; Sandaa, R.-A.; Øvreas, L. Novel techniques for analysingmicrobial diversity in natural and perturbed environments. J. Biotechnol. 1998, 64 (1),53–62.
6. Morgan, J.A.W.; Winstanley, C. Microbial biomarkers. In Modern Soil Microbiology;van Elsas, J.D.; Trevors, J.T.; Wellington, E.M.H., Eds.; Marcel Dekker Inc.: New York,1997; 331–352.
7. Hahn, D.; Amann, R.I.; Ludwig, W.; Akkermans, A.D.L.; Schleifer, K.H. Detectionof microorganisms in soil after in situ hybridization with rRNA-targeted, fluorescentlylabelled oligonucleotides. J. Gen. Microbiol. 1992, 138, 879–887.
8. Bitton, G.; Koopman, B.; Jung, K.H.; Voiland, G.; Kotob, M. Modification of the stan-dard epifluorescence microscopic method for total bacterial counts in environmental-samples. Water Res. 1993, 27, 1109–1112.
9. Zhou, J.; Bruns, M.A.; Tiedje, J.M. DNA recovery from soils of diverse composition.Appl. Environ. Microbiol. 1996, 62, 316–332.
10. Stackebrandt, E.; Goodfellow, M. Nucleic Acid Techniques in Bacterial Systemat-ics; Wiley: London, 1991.
11. DeLong, E.F. Archaea in coastal marine environments. Proc. Natl. Acad. Sci. USA1992, 89, 5685–5689.
12. Lane, D.J.; Pace, B.; Olsen, G.J.; Stahl, D.A.; Sogin, M.L.; Pace, N.R. Rapiddetermination of 16S ribosomal RNA sequences for phylogenetic analyses. Proc. Natl.Acad. Sci. USA 1985, 82, 6955–6959.
13. Collins, G.; Woods, A.; McHugh, S.; Carton, M.; O’Flaherty, V. Microbial commu-nity structure and methanogenic activity during start-up of psychrophilic anaerobicdigesters treating synthetic industrial wastewaters. FEMS Microbiol. Ecol. 2003, 46(2), 159–170.
14. Moyer, C.L.; Dobbs, F.C.; Karl, D.M. Estimation of diversity and communitystructure through restriction fragment length polymorphism distribution analysis ofbacterial 16S rRNA genes from a microbial mat at an active, hydrothermal vent system,Loihi Seamount, Hawaii. Appl. Environ. Microbiol. 1994, 60, 871–879.
15. Altschul, S.F.; Madden, T.L.; Schaffer, A.A.; Zhang, J.; Zhang, Z.; Miller, W.;Lipman, D.J. Gapped BLAST and PSI-BLAST: a new generation of protein databasesearch programs. Nucl. Acids Res. 1997, 25, 3389–3402.
17. Marsh, T.L.; Saxman, P.; Cole, J.; Tiedje, J. Terminal restriction fragment lengthpolymorphism analysis program, a web-based research tool for microbial communityanalysis. Appl. Environ. Microbiol. 2000, 66 (8), 3616–3620.
920 Collins et al.
18. Øvreas, L.; Forney, L.; Daae, F.L.; Torsvik, V. Distribution of bacterioplankton inmeromictic Lake Saelenvannet, as determined by denaturing gradient gel electrophore-sis of PCR-amplified gene fragments coding for 16S rRNA. Appl. Environ. Microbiol.1997, 63, 3367–3373.
19. Muyzer, G.; de Waal, E.C.; Uitterlinden, A.G. Profiling of complex microbialpopulations by denaturing gradient gel electrophoresis analysis of polymerase chainreaction-amplified genes coding for 16S rRNA. Appl. Environ. Microbiol. 1993, 59,695–700.
20. Jobson, J.D. Applied Multivariate Data Analysis, Vol. 2. Categorical and Multi-variate Methods; Springer-Verlag: New York, 1992.
21. Kumar, S.; Tamura, K.; Jakobsen, I.B.; Nei, M.MEGA2: molecular evolutionarygenetics analysis software. Arizona State University: Tempe, AZ, 2001.
22. O’Flaherty, V.; Mahony, T.; O’Kennedy, R.; Colleran, E. Effect of pH on the growthkinetics and sulphide toxicity thresholds of a range of methanogenic, syntrophic andsulphate-reducing bacteria. Proc. Biochem. 1998, 33 (5), 555–569.
23. Schramm, A.; de Beer, D.; Wagner, M.; Amann, R.I. Identification and activitiesin situ of Nitrosospira and Nitrospira spp. as dominant populations in a nitrifyingfluidized bed reactor. Appl. Environ. Microbiol. 1998, 64 (9), 3480–3485.
24. Stahl, D.A.; Amann, R.I. Development and application of nucleic acid probesin bacterial systematics. In Sequencing and Hybridization Techniques in BacterialSystematics; E., Stackebrandt.; M., Goodfellow., Eds.; John Wiley and Sons: Chichester,England, 1991; 205–248.
28. Sorensen, A.; Torsvik, V.; Torsvik, T.; Poulsen, L.; Ahring, B. Whole-cell hy-bridization of Methanosarcina cells with two new oligonucleotide probes. Appl. Environ.Microbiol. 1997, 63 (8), 3043–3050.
29. Cole, R.; Chai, B.; Marsh, T.L.; Farris, R.J.; Wang, Q.; Kulam, S.A.; Chandra, S.;McGarrell, D.M.; Schmidt, T.M.; Garrity, G.M.; Tiedje, J.M. The Ribosomal DatabaseProject (RDP-II): previewing a new autoaligner that allows regular updates and thenew prokaryotic taxonomy. Nucl. Acids Res. 2003, 1, 442–443.
30. Manz, W.; Amann, R.I.; Ludwig, W.; Wagner, M.; Schleifer, K.H. Phylogeneticoligodeoxynucleotide probes for the major subclasses of Proteobacteria: problems andsolutions. Syst. Appl. Microbiol. 1992, 15, 593–600.
31. Andreasen, K.; Nielsen, P.H. Application of microautoradiography to the study ofsubstrate uptake by filamentous microorganisms in activated sludge. Appl. Environ.Microbiol. 1997, 63 (9), 3662–3668.
32. Treude, T.; Nauhaus, K.; Gieseke, A.; Knittel, K.; Boetius, A.; Joergensen, B.B.;Michaelis, W.Methanotrophic microbial mats forming reefs in the anoxic Black Sea. InGeophys. Res. Abstracts; 2003, 5, 01732, European Geophysical Society.
Microbial Diversity and Ecophysiology 921
33. McHugh, S.; Collins, G.; O’Flaherty, V. Long-term, high-rate anaerobic biologicaltreatment of whey waste waters at psychotrophilic temperatures. Biores. Technol. 2006,In Press.
34. Roose-Amsaleg, C.L.; Garnier-Sillam, E.; Harry, M. Extraction and purification ofmicrobial DNA from soil and sediment samples. Appl. Soil Ecol. 2001, 18 (1), 47–60.
35. Griffiths, B.S.; Ritz, K.; Wheatley, R.; Kuan, H.L.; Boag, B.; Christensen, S.;Ekelund, F.; Sørensen, S.J.; Muller, S.; Bloem, J. An examination of the biodiversity–ecosystem function relationship in arable soil microbial communities. Soil Biol.Biochem. 2001, 33 (12), 1713–1722.
36. McCaig, A.; Grayston, S.; Prosser, J.; Glover, L.A. Impact of cultivation oncharacterisation of species composition of soil bacterial communities. FEMS Microbiol.Ecol. 2001, 35 (1), 37–48.
37. Liu, W.-T.; Marsh, T.L.; Forney, L.J. Determination of the microbial diversity ofanaerobic-aerobic activated sludge by a novel molecular biological technique. WaterSci. Technol. 1998, 37 (4), 417–422.
38. Marsh, T.L. Terminal restriction fragment length polymorphism (T-RFLP): anemerging method for characterizing diversity among homologous populations of am-plification products. Curr. Opin. Microbiol. 1999, 2 (3), 323–327.
39. Blackwood, C.B.; Paul, E.A. Eubacterial community structure and population sizewithin the soil light fraction, rhizosphere, and heavy fraction of several agriculturalsystems. Soil Biol. Biochem. 2003, 35 (9), 1245–1255.
40. Ogram, A. Soil molecular microbial ecology at age 20: methodological challengesfor the future. Soil Biol. Biochem. 2000, 32 (11–12), 1499–1504.
41. Leff, L.G.; Dana, J.R.; McArthur, J.V.; Shimkets, L.J. Comparison of methods ofDNA extraction from stream sediments. Appl. Environ. Microbiol. 1995, 61, 1141–1143.
42. Robe, P.; Nalin, R.; Capellano, C.; Vogel, T.M.; Simonet, P. Extraction of DNA fromsoil. Europ. J. Soil Biol. 2003, 39 (4), 183–190.
43. Martin-Laurent, F.; Philippot, L.; Hallet, S.; Chaussod, R.; Germon, J.C.; Soulas,G.; Catroux, G. DNA extraction from soils: old bias for new microbial diversity analysismethods. Appl. Environ. Microbiol. 2001, 67 (5), 2354–2359.
45. Hosoya, K.; Kubo, T.; Tanaka, N.; Haginaka, J. A possible purification method ofDNAs’ fragments from humic matters in soil extracts using novel stimulus responsivepolymer adsorbent. J. Pharmaceut. Biomed. Anal. 2003, 30 (6), 1919–1922.
46. Fernandez, A.; Huang, S.; Seston, S.; Xing, J.; Hickey, R.; Criddle, C.; Tiedje,J. How stable is stable? Function versus community composition. Appl. Environ.Microbiol. 1999, 65, 3697–3704.
47. Brunk, C.F.; Eis, N. Quantitative measure of small-subunit rRNA gene sequencesof the kingdom Korarchaeota. Appl. Environ. Microbiol. 1998, 64, 5064–5066.
48. Godon, J.J.; Zumstein, E.; Dabert, P.; Habouzit, F.; Moletta, R. Molecular micro-bial diversity of an anaerobic digestor as determined by small-subunit rDNA sequenceanalysis. Appl. Environ. Microbiol. 1997, 63, 2802–2813.
49. Sekiguchi, Y.; Kamagata, Y.; Nakamura, K.; Ohashi, A.; Harada, H. Fluorescencein situ hybridization using 16S rRNA-targeted oligonucleotides reveals localization of
922 Collins et al.
methanogens and selected uncultured bacteria in mesophilic and thermophilic sludgegranules. Appl. Environ. Microbiol. 1999, 65 (3), 1280–1288.
50. Nielsen, P.H.; Andreasen, K.; Lee, N.; Wagner, M. Use of microautoradiographyand fluorescent in situ hybridization for characterization of microbial activity inactivated sludge. Water Sci. Technol. 1999, 39 (1), 1–9.
51. Nielsen, J.L.; Wagner, M.; Nielsen, P.H. Use of microautoradiography to studyin situ physiology of bacteria in biofilms. In Impact and Exploitation of Biofilms inNatural and Man-Made Ecosystems; O’Flaherty, V.; Mahony, T.; Moran, A.P.; Lens, P.,Eds.; Reviews Environ. Bio/Technol: Amsterdam, Netherlands, 2003; 2 (2–4), 261–268.
52. Radajewski, S.; Ineson, P.; Nisha, R.; Parekh, J.; Murrell, C. Stable-isotopeprobing as a tool in microbial ecology. Nature 2000, 403, 646–649.
