~ Pergamon

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Wat. Sci. Tech. Vol. 36, No. 6-7, pp. 49-55,1997.© 1997 IAWQ. Published by Elsevier Science Ltd

Printed in Great Britain.0273-1223/97 $17'00 + 0'00

MICROBIAL 16S rDNA DIVERSITY IN ANANAEROBIC DIGESTER

Jean-Jacques Godon, Emmanuelle Zumstein,Patrick Dabert, Frederic Habouzit and Rene Moletta

Laboratoire de BiotechnoLogie de I'Environnement, Institut NationaL de La RechercheAgronomique, Avenue des Etangs, 11100 Narbonne, France

ABSTRACT

The bacterial community structure of a fluidized bed reactor fed by vinasses was analysed by molecularidentification. After PCR amplification, three 16S rDNA clone libraries of Bacteria, Archaea, and Procaryapopulations were established. Community structure was determined by phylogenetic analysis of 556 partialrDNA sequences (about 500 bp long). 139 OTUs (Operational Taxonomic Unit) were found among which133 and 6 were from the Bacteria and Archaea domains respectively. The majority of bacterial OTUs are notclosely related to all other hitherto-determined sequences. The ratio ArchaealBacteria is 1/4 and the mostfrequent bacterial OTU represents less than 5% of the characterised bacterial population. © 1997 IAWQ.Published by Elsevier Science Ltd

KEYWORDS

Anaerobic digestion; biodiversity; fluidized bed; microbial ecology; phylogeny; 16S rRNA.

INTRODUCTION

Anaerobic digestion is exploited in a large scale as a simple and effective biotechnological process to reducethe pollution caused by organic wastes. However, our knowledge of microbial communities involved in thiscomplex food web has been limited since they consist of both cultivable and non-cultivable organisms. Theuse of molecular biological techniques, especially those that take advantage of the 16S rRNA molecule(ribosomal small sub-unit) has eliminated the dependence upon isolation of pure cultures as a means ofstudying the diversity and structure of microbial communities (Amann et al., 1995). The nucleotidesequence of the 16S rRNA (about 1500 bp) is generally specific for each micro-organism. The evolution ofthis molecule from a common ancestor and the bulk of data available (about 6000 sequences) allow us toplace each organism into a huge phylogenetic tree. From sequences alignment, it is possible to design smallnucleic acid probes targeted theoretically either to one species, one genus or one phylum. These probesassociated to various molecular techniques allows us to follow either one species, one genus or one phyluminto a complex medium.

Nucleic acid probes were already applied on anaerobic reactors (Raskin et al., 1994). However, these probeswere designed either from micro-organisms or phylogenetic groups of micro-organisms previously isolatedin pure culture. Thus, the new tools were not free of old cultivation limitation. The molecular inventory ofthe ecosystem was a necessary step to overcome this limitation.

49

50 1.-1. GODON et al.

We used 16S rRNA sequences, to obtain an overview of microbial species present in a biofilm structure of afluidized bed anaerobic digester. The reactor studied was fed by vinasses from a local wine distillery. Thisindustrial waste, residue of wine distillation, presented several advantages. It is a complex organic wastewhich generates real pollution in the vineyard area. The collect at 800C during the distillation processguarantees that it was almost free of micro-organisms. This is an important point because the molecularapproach does not distinguish between endogenous and transient micro-organisms.

MATERIALS AND METHODS

Anaerobic reactor analysed

The experimental apparatus consisted of a 0.6 litre tubular reactor (Fig. 1). The support material used formicrobial fixation was granular pouzzolane (a volcanic stone) and the fluidization produced an expandingrate of 25%. The reactor was fed by a peristaltic pump. The average composition of the vinasses was 10 g oftotal organic carbon (TOC)/l and 25 g of chemical oxygen demand (COD)/l. The organic load was 5.85 g ofCODllJd. The pH and the temperature were maintained respectively around 7 and 35OC. The averagemeasures of the TOC in liquid phase and volatile fatty acids were respectively of 800 mg/l and 250 mg/l.The inoculum represented 100% of the volume and came directly from a similar 15 I fluidized bed reactorwhich had run continuously for 1 year (Buffiere et ai., 1995). The unique sample used for analysis wascollected into a stable digester (40 days after inoculation).

6

1. Reactor2. Alimentation pump3. Circulation pump4. Temperature regulation (35CO)5. Liquid outlet6. Gas outlet7. pH meter

5

3

Figure 1. Experimental apparatus.

Strategy of molecular invent0O'

The ~trategy. used is. su~arised in Figure 2. This molecular approach was already successfully used todescnbe vanous IDlcroblal co~so~ia such as soil, blanket bog peat, marine microbial community,hydrothermal vent, human colomc bIOta and termite gut (Borneman et ai., 1996; Hales et ai., 1996; Fuhrmanet ai., 1993; Moyer et ai., 1995; Wilson and Blitchington, 1996; Ohkuma and Kudo, 1996).

Extraction of total genomic DNA. amplification. cloning. and seQuencing of 16S rONA

Four. millilitres ~ere collected from the middle of the fluidized bed reactor and DNA was extracted aspreVIOusly descnbed (Godon et ai., 1997).

Amplification o~ 16S rDNA genes from purified genomic DNA was carried out using primers fromconserved domaIns. Three rRNA gene libraries were done: Archaea total (E. coli position 6 to 1509

Microbial 16S rONA diversity 51

(B.rosius et ai., 1981), primers w03 + w02 and w17 + w02), Bacteria total (E. coli position 8 to 1509,pnmers w01 + w02 and w18 + w02) and Procarya partial (E. coli position 778 to 1509, primers wl5 +w02). The primers used are listed in Table 1. PCR amplifications were performed as previously described(Godon et ai., 1997). PCR products were electrophoresed on a 0.7% agarose gel and bands of the proper sizerange (ca. 1500 bases) were excised out and eluted using Qiaex II gel extraction kit (Qiagen, Hilden,Germany). The purified DNA were ligated into the pGEMt plasmid (Promega, Madison, Wis., USA). Theligation products were transformed into E. coli TG1 competent cells using ampicillin selection andblue/white screening (Sambrook et ai., 1989). Plasmid preparations for DNA sequencing were performed byQiagen microcolumns according to manufacturer's instructions (Qiagen, Hilden, Germany). The nucleotidesequence of plasmid inserts were determined by automated DNA sequencing using the dideoxy chain•termination method (Sanger, 1977) and the ABI model 373A sequencer stretch from Applied Biosystems(Perkin Elmer, Forster City, CA, USA). Plasmid DNAs were sequenced by using the "dye-terminator cyclesequencing ready reaction" kit with AmpliTaq DNA polymerase FS kit buffer (Perkin Elmer, Forster City,CA, USA) and primer w015 (Table 1).

. Anaerobicdigator

.~9systeJP ..

Overviewit of

;.;.

ecosystem

Figure 2. Strategy applied

Table 1. Sequence and target position of the primers used in this study

Name

w01w02w03w15w17w18

Sequence

AGAGTTTGATC(AC)TGGCTCG(ATGC)TACCTTGTTACGACTTATTC(TC)GGTTGATCC(TC)G(GC)CAGC(AG)AACAGGATTAGATACATTC(TC)GGTTGATCC(TC)G(GC)C(AG)GGAGTTTGATC(AC)TGGCTCAG

Target

16S rRNA bacteria16S rRNA universal16S rRNA archaea16S rRNA bacteria16S rRNA archaea16S rRNA bacteria

Position*

F8R1509F6F777F6F9

*The position corresponds to the primer 5'-end, using E coli 16S rRNA as reference (Brosius, 1981); Fand R correspond respectively to forward and reverse primer.

Sequence analysis and nucleotide sequence accession numbers

A partial sequence of at least 500 bp was performed from each clone and an equal portion which rep~esents athird of the 16S rRNA molecule (E. coli position 812 to 1307) was used for sequence analysIs. Eachsequence was compared with sequences available in databases (Genbank and RDP) (Maidak et ai., 1994).DNA sequence comparisons between themselves were performed using Lasergene software (Dnastar,Madison, USA). Phylogenetic relationships were calculated by Jukes-Cantor (Jukes and ~anto.r, 1969) ~dneighbor-joining algorithms (Saitou et ai., 1987). The nucleotide sequence data reported In th~s paper WIllappear in the EMBL, GenBank and DDBJ Nucleotide Sequence Databases under the acceSSIOn numbersU81640 to U81785 with the generic name of VADIN for Vinasses Anaerobic DIgester of Narbonne.

52 1.-1. GODON et al.

RESULTS AND DISCUSSION

Microbial diversity

The 556 clones analysed were grouped in 139 OTUs (Operational taxonomic unit) (Moyer et al., 1995) onthe basis of having more than 96% of sequence similarity within an OTU. The bacterial clones represent awide diversity with 133 OTUs identified among 460 bacterial clones analysed whereas six Archaea OTUsonly were found among 96 clones analysed.

Phylogenetic diversity (qualitative approach)

The phylogenetic distribution of the 139 OTUs into the major phyla is detailed on Figure 3. 79% of theOTUs belong to the three major phyla of bacteria: Proteobacteria, Gram positive low G+C and Cytophaga•Flexibacter-Bacteroides (CFB). The other OTUs are scattered among minor phyla and, for some of them,the phylogenetic position is too deep to be easily affiliated. The percentages of divergence with the closerbacterial sequence available are indicated on Table 1. Only OTUs found with a frequency up to 0.5 % (3 ormore clones) are listed. None of the bacterial 16S rRNA sequenced has less than 3% of divergence withsequence found in database. It is worth noting that the threshold of 3% of divergence is generally admitted todistinguish species on 16S rRNA level. The 16S rRNA sequences of the methanogenic Archaea are similar(less than 3%) to already known methanogenic 16S rRNA sequences of Methanosarcina barkeri, Ms.frisiusand Methanobacteriumformicicum (Table 2). In contrast, the three other Archaea OTUs are very atypical.

A B

Archaea methanogene 2% Archaea others 2% Non affiliated 3%

Planctomyces 5%

Gram +High GC4%

Green non sulfur 4%

Proteobacteria alpha 5%Proteobacteria beta 2%

Figure 3. OTUs distribution. A: prokaryotic OTUs (bacterial and archaea). B: Bacterial OTUs.

Distribution of clones (quantitative approach)

The phylogenetic analysis presented above describes the diversity of the population on the basis of OTUs.The following analysis is presented at the clone level to estimate the representativeness of each OTU in thepopul~tion. ~on? t~e clones analysed, 460 and 96 belong respectively to the Bacteria and Archaeadomams. The .dIstnbutlOn of bac.terial cl?n~s within Bacteria and Procarya libraries is similar. Figure 4 andTable 2 .co~bme both results. FIgure 4 mdIcates the clone frequency into the phylogenetic groups whereasTable 2 mdIcates the clone frequency of each OTU. This frequency is reported only for the OTUs containing3 or ~ore clones. The mo~t frequent. bacterial. OTU includes 22 clones which correspond to 5% of the totalbacter~al clones.. 14 bactenal OTUs mclude mne or more clones and their frequency is higher than 2%. 17bactenal OTUs mclude between 5 to 8 clones and have a frequency between 1 to 2%. 39 OTUs includebetween 2 to 4 clones and have a frequency between 0.2 to 0.9%.63 bacterial OTUs include only one cloneand have a frequency lower than 0.2%. The most frequent archaea OTU includes 43 clones whichcorrespond to 44% of the Archaea clones and 11 % of the prokaryotic clones.

Microbial 16S rDNA diversity 53

Table 2. Frequency and phylogeny of the most frequent OTUs

OTUs Distribution PhylogenyNumber Frequency Phylum Closer organisms *of clones Name Divergence* *

Bacterial domainHA17 22 4.8% CFB Bacteroides splanchnicus 13.9%HA61 17 3.7% CFB Bacteroides jorsythus 13.6%BC38 16 3.5% Proteobacteria delta Desuljobulbus propionicus 12.8%HA60 15 3.3% Proteobacteria delta Desu/fosarcinavariabilis 7.3%HB04 15 3.3% Gram+ Low G+C Phascolarctobacterium jaecium 6.4%HA42 14 3.0% Gram+ Low G+C Eubacterium plautii 5.9%HA41 14 3.0% Gram+ High G+C Propionibacterium freudenreichii 5.9%CA02 13 2.8% Synergistes Synergistes jonesii 13.3%HA28 13 2.8% CFB Bacteroides jorsythus 12.8%HA40 12 2.6% Proteobacteria delta Desuljovibrio desuljuricans 9.3%BA07 11 2.4% Deep Non affiliated non relevantBC27 11 2.4% CFB Bacteroides jorsythus 18.3%HA21 10 2.2% CFB Rikenella microjusus 18.4%BB60 9 2.0% Gram+ Low G+C Haloanaerobium a/caliphi/um 22.6%BA08 8 1.7% Gram+ Low G+C Clostridium cellulolyticum 9.3%BB35 8 1.7% Gram+ Low G+C Clostridium butyricum 18.6%HA73 7 1.5% Synergistes Synergistes jonesii 17.3%BAJO 7 1.5% Planctomyces Planctomyces staleyi 19.2%HA64 7 1.5% Green Non Sulfur Thermomicrobium roseum 24.3%HA31 7 1.5% Gram+ Low G+C Haloanaerobium alcaliphi/um 22.6%HA67 7 1.5% Gram+ Low G+C Clostridium c/ostridiiforme 4.3%HA54 7 1.5% CFB Bacteroides jorsythus 12.0%HA55 6 1.3% Gram+ High G+C Eubacterium suis 7.7%HA45 6 1.3% CFB Bacteroides fragi/is 5.5%HB56 6 1.3% CFB Bacteroides jorsythus 17.3%BA43 5 1.1% Spirochaetes Serpulina innocens 16.4%BB56 5 1.1% Proteobacteria gamma Escherichia coli 4.0%BAOI 5 1.1% Proteobacteria delta Desuljobulbus propionicus 14.3%BA26 5 1.1% Green Non Sulfur Thermomicrobium roseum 23.0%CA16 5 1.1% GramT Low G+C Clostridium aminobutyricum 7.9%BC07 5 1.1% CFB Prevotella ruminicola 16.0%HA24 4 0.9% Spirochaetes Treponema pallidum 14.3%DC43 4 0.9% Proteobacteria beta Burkholderia gladioli 10.4%BB14 4 0.9% Gram+ Low G+C Eubacterium siraeum 10.6%

CA17 4 0.9% Gram+ Low G+C Clostridium butyricum 18.6%BB59 3 0.7% Proteobacteria gamma Acinetobacter IwojJii 3.1%

HA49 3 0.7% Planctomyces Planctomyces staleyi 21.0%

BC14 3 0.7% Gram+ Low G+C Clostridium aminobutyricum 4.9%

HA08 3 0.7% Gram+ Low G+C Eubacterium plautii 5.1%

HA19 3 0.7% Gram+ Low G+C Eubacterium desmolans 11.8%

HA75 3 0.7% Gram+Low G+C Megasphaera elsdenii 9.0%

HB09 3 0.7% Gram+ Low G+C Eubacterium plautii 6.9%

HBll 3 0.7% Gram+ Low G+C Clostridium c/ostridiiforme 7.7%

BA21 3 0.7% Gram+ High G+C Eubacterium suis 6.5%

BA25 3 0.7% Gram+ High G+C Atopobium parvulum 6.8%

BA22 3 0.7% CFB Bacteroides jorsythus 13.4%

BBS3 3 0.7% CFB Bacteroides splanchnicus 12.3%

HAJS 3 0.7% CFB Prevotella ruminicola 14.1%

Total 353 76.7% ***Archaea domain

DC06 43 44.8% Archaea Methanobacterium jormicicum 3.0%

CA25 30 31.3% Archaea Methanosarcina barkeri 1.2%

DAOS 14 14.6% Archaea Methanosarcina frisius 0.2%

DC69 3 3.1% Archaea Crenarchaeotal sp.5 14.9%

CAll 3 3.1% Archaea Thermoplasma acidophi/um 18.8%

DC79 3 3.1% Archaea Thermoplasma acidophi/um 19.4%

Total 96 100%

.: Closer organisms were previously determined using neighbor-joining algorithms (Godon, 1997)

..: Divergence was done with about 500 bp (E. coli position 812 to 1307)

.":23.3% of clones belong to OTU which have a frequency lower than 0.5% (less than 3 clones by OTU)

54 1.-1. GODON et al.

A BMethanobacter fonnicicwn Green non sulfur 7%

lO%Methanosarcina Non affiliated 3%frisius 4% Planctomyces 4%

Methano- Gram+ Highsarcina GC 6% :·:~~V:\·

barkeri 8% ...>:.>\: '/'llil-.Archaea others _. :::"':::~?:::':*:

I!~-"".~ 2%

•Proteobacteria alpha 2%Proteobacteria beta 1%

Proteobacteria gamma 2%

Proteobacteria delta 12%

Figure 4. Clones distribution. A: prokaryotic clones (bacterial and archaea). B: bacterial clones.

Overview of the population

This closed and stable ecosystem is composed of more than 139 different organisms belonging to theprokaryotic domains. This inventory is not exhaustive, the total number of species remains unknown ~dstill out of reach. After 460 clones were analysed, the discovery of new OTUs was less frequent. At thIspoint, the identification of a new OTU occurred only once in every ten clones sequenced.

160....-----------------------------------1

140

45040010050 150 200 250 300 350

Number of bacterial clones sequenced

Figure 5. Estimation of the bacterial diversity. The sequential detection of new OTUs following sequence analysisof 460 bacterial 165 rDNA clones is represented. The clones were picked up from alphanumeric order.

b

1120

~ 100 + .otil'5 80 ~ .

~..0

~ 60';:J

'"1 40U

20

Bias of the method

The significance of these results depends on the bias introduced by this approach. Several parameters couldhamper the results: GC content of 16S rDNA, differential cell lysis, Taq polymerase specificity, primerspecificity, chimera formation, copy number of the 16S rRNA genes. Nevertheless, the large diversity of theresults obtained suggests that these disruptive factors were minimised. The most tricky problem remains inchimera which can arise during PCR amplification of mixed DNA populations. A chimeric rDNA clone is

Microbial 16S rDNA diversity 55

composed of rDNAs from different organisms and is difficult to detect. A comparison of a large number ofidentical sequences obtained from independent PCR amplifications allowed us to solve partially this crucialproblem. 26 chimera were found and withdrawn from the bacterial clones (5.4%). Although the frequency ofthe micro-organisms within the ecosystem given by this approach is probably not an exact picture of the trueone, it can be used as a starting point for further investigations.

CONCLUSION

This work gave an overall description of an anaerobic digestion ecosystem using 16S rDNA identificationand reveals a high biodiversity within a common ecosystem. In spite of this large bacterial diversity, fewOTUs represent a large percentage of clones (Fig. 5). Characterisation of the ecosystem by 16S rRNAsequences allowed the identification of members of all genus or taxon expected with a known function; i.e.:Bacteroides, Eubacterium, Clostridium, Proteobacteria delta (sulfato-reducing bacteria), Syntrophomonas,methanogenic Archaea, etc.

On the other hand, this free of cultivation approach reveals members of several genera whose function isunknown, including Spirochaetes, GNS, Planctomyces, non methanogenic Archaea. The challenge will be toassociate a function for these new identified micro-organisms into the complex anaerobic digestion foodweb. Information on the function of a micro-organism is barely associated with the phylogeneticclassification obtained by the 16S rRNA molecule.

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