Occurrence and community composition of fast-growing Mycobacterium in soils contaminated with polycyclic aromatic hydrocarbons

FEMS Microbiology Ecology 51 (2005) 375–388 www.fems-microbiology.org

Occurrence and community composition of fast-growing Mycobacterium in soils contaminated with polycyclic aromatic hydrocarbons Natalie M. Leys a,b,1, Annemie Ryngaert a, Leen Bastiaens a, Pierre Wattiau Eva M. Top b,3, Willy Verstraete b, Dirk Springael a,d,*

c,2

,

a

c

Environmental and Process Technology, Flemish Institute for Technological Research (Vito), Boeretang 200, 2400 Mol, Belgium b Laboratory of Microbial Ecology and Technology, University of Gent (UG), Coupure Links 653, 9000 Gent, Belgium Bioengineering Unit, Catholic University of Louvain La Neuve (UCL), Place Croix du Sud 2 – Box 13, 1348 Louvain La Neuve, Belgium d Laboratory of Soil and Water Management, Catholic University of Leuven, Kasteelpark Arenberg 20, 3001 Heverlee, Belgium Received 1 February 2004; received in revised form 25 May 2004; accepted 28 September 2004 First published online 28 October 2004

Abstract Fast-growing mycobacteria are considered essential members of the polycyclic aromatic hydrocarbons (PAH) degrading bacterial community in PAH-contaminated soils. To study the natural role and diversity of the Mycobacterium community in contaminated soils, a culture-independent fingerprinting method based on PCR combined with denaturing gradient gel electrophoresis (DGGE) was developed. New PCR primers were selected which specifically targeted the 16S rRNA genes of fast-growing mycobacteria, and single-band DGGE profiles of amplicons were obtained for most Mycobacterium strains tested. Strains belonging to the same species revealed identical DGGE fingerprints, and in most cases, but not all, these fingerprints were typical for one species, allowing partial differentiation between species in a Mycobacterium community. Mycobacterium strains inoculated in soil were detected with a detection limit of 106 CFU g
1 of soil using the new primer set as such, or approximately 102 CFU g
1 in a nested PCR approach combining eubacterial and the Mycobacterium specific primers. Using the PCR-DGGE method, different species could be individually recognized in a mixed Mycobacterium community. This approach was used to rapidly assess the Mycobacterium community structure of several PAH-contaminated soils of diverse origin with different overall contamination profiles, pollution concentrations and chemical-physical soil characteristics. In the non-contaminated soil, most of the recovered 16S rRNA gene sequence did not match with previous described PAH-degrading Mycobacterium strains. In most PAH-contaminated soils, mycobacteria were detected which were closely related to fast-growing species such as Mycobacterium frederiksbergense and Mycobacterium austroafricanum, species that are known to include strains with PAH-degrading capacities. Interestingly, 16S rRNA genes related to M. tusciae sequences, a Mycobacterium species so far not reported in relation to biodegradation of PAHs, were detected in all contaminated soils.
2004 Federation of European Microbiological Societies. Published by Elsevier B.V. All rights reserved. Keywords: PAH biodegradation; Mycobacterium; 16S rRNA gene; PCR; DGGE

* Corresponding author. Present address: Catholic University of Leuven (KUL), Laboratory for Soil and Water management, Kasteelpark Arenberg 20, 3001 Heverlee, Belgium. Tel.: +32 16 321604; fax: +32 16 321997. E-mail address: [email protected] (D. Springael). 1 Present address: Belgian Nuclear Research Centre (SCK/CEN), Laboratory of Microbiology, Boeretang, 2400 Mol, Belgium. 2 Present address: Vetinary and Agrochemical Research Institute, Department of Bacteriology, Groesetenberg 99, B-1180 Brussels, Belgium. 3 Present address: University of Idaho, Department of Biological Sciences, 83844-3051 Moscow, Idaho, USA.

0168-6496/$22.00
2004 Federation of European Microbiological Societies. Published by Elsevier B.V. All rights reserved. doi:10.1016/j.femsec.2004.09.015

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1. Introduction Polycyclic aromatic hydrocarbons (PAHs) are hazardous environmental pollutants that are found in high concentrations on sites of old gas factories and wood preservation plants [1]. In spite of the limited bioavailability and poor biodegradability of PAHs, different bacteria, often mycobacteria, have been isolated that are able to use PAHs as sole sources of carbon and energy [2–7]. So far, all PAH-biodegrading Mycobacterium isolates [2–11] have been placed in the phylogenetic branch of the Ôfast-growing mycobacteriaÕ. In the Mycobacterium phylogenetic tree, the Ôfast-growing mycobacteriaÕ form a coherent line of descent, distinct from the more recently evolved slow-growers, within which the wellknown mycobacterial pathogens are clustered [12–15]. The Ôfast-growing mycobacteriaÕ constitute a group of mycobacteria, mostly of environmental origin, that are, based on growth, biochemical characteristics and infectious properties (i.e., mycobacteria of Bio safety Level 1, growth within 7 days), highly different from pathogenic and facultative pathogenic more slowly growing species like Mycobacterium avium, Mycobacterium tuberculosis, Mycobacterium leprae or Mycobacterium ulcerans (i.e., mycobacteria of Bio safety levels 2 & 3, growth after more than 7 days) [12–15]. The diversity of fast-growing mycobacteria in the environment is still largely unknown, but could be of major interest for bioremediation of PAH-contaminated soils. Therefore, methods are needed for community analysis and monitoring of indigenous and/or inoculated fast-growing PAH-degrading mycobacteria in soil. For detection of mycobacteria, direct culture-independent detection methods are preferable over indirect culturedependent techniques because: (i) a large fraction of cells in soil is difficult to culture or even believed to be unculturable (viable but non-culturable – VBNC state) [16– 18], (ii) the hydrophobic Mycobacterium cells are known to adhere strongly to organic soil particles, resulting in difficult recovery [19,20] and (iii) Mycobacterium species, even Ôfast-growersÕ, are relatively slow-growing organisms in comparison to other soil bacteria, which makes them easily overgrown by other bacteria in culture media [21]. In addition, molecular methods based on PCR amplification have been proven to be successful for the diagnosis of mycobacterial diseases in humans [22–26] and fish [27] and for the identification of environmental infection sources of Mycobacterium opportunistic pathogens such as M. avium and M. ulcerans in plants, water and soil [28–30]. PCR amplification of variable 16S rRNA gene-fragments combined with direct analysis of amplicons by denaturing gradient gel electrophoresis (DGGE) is a commonly used technique for rapid molecular assessment of microbial communities. In all previous studies [22–29] except one [30], however, the PCR primers were designed to reveal the presence of slow-

growing mycobacteria in the tested samples and were never combined with a method for direct community diversity analysis such as DGGE. Recently, Cheung and Kinkle [31] designed a Mycobacterium specific primer pair and analyzed the amplicons using temperature gradient gel electrophoresis (TGGE) for fingerprinting. However, none of the described primer sets were specific enough to preferentially target fast-growing mycobacteria, belonging to non-pathogenic and non-opportunistic species. Moreover, the advantages and limits of the PCR-TGGE method were not previously addressed. In this study, we describe the development of a new set of non-degenerated primers that annealed, as exclusively as possible, to 16S rRNA genes of fast-growing mycobacteria and that amplified a short fragment suitable for DGGE-fingerprinting. The PCR-DGGE method was theoretically and practically evaluated for the detection of fast-growing mycobacteria in soil samples and applied to examine the Mycobacterium community composition in PAH-contaminated soils.

2. Materials and methods 2.1. Bacterial strains and growth conditions In total, 80 different bacterial strains from different orders, suborders and families were used in this study, including many strains with reported pollutant-degrading capacities. The following strains of the Mycobacterium genus were used: Mycobacterium aichiense 5545 (DSM44147T), Mycobacterium alvei CR-21 (DSM 44176T), Mycobacterium aurum 358 (DSM43999T), Mycobacterium vanbaalenii PYR-1 (DSM7251T), Mycobacterium austroafricanum E9789 (DSM44191T), M. austroafricanum-related strains VM0456, VM0450, VM0451, VM0447, VM0452, VM0573 (Springael et al., unpublished), Mycobacterium chlorophenolicum PCP-1 (DSM43826T), Mycobacterium diernhoferi SN1418 (DSM43524T), Mycobacterium frederiksbergense FAn9 (DSM44346T), M. frederiksbergense related strains LB501T, VM0503, VM0531, VM0458, VM0579, VM0585 (Springael et al., unpublished), Mycobacterium gilvum strains SM35 (DSM44503T), BB1 (DSM9487), HE5 (DSM44238), Mycobacterium gilvum related strains LB307T, VM0505, VM0504, VM0552, VM 0442, LB208, VM0583 (Springael et al., unpublished), Mycobacterium hodleri EM12 (DSM44183T), Mycobacterium komossense Ko2 (DSM44078T), Mycobacterium neoaurum 3503 (DSM44074T), Mycobacterium parafortuitum 311 (DSM43528T), Mycobacterium peregrinum 6020 (DSM43271T), Mycobacterium petroleophilum RF002 (Lloyd-Jones et al., unpublished), Mycobacterium vaccae-related strains VM0587, VM0588 (Springael et al., unpublished), and Mycobacterium sp. strains WF2 [9] and GP1 (Lloyd-Jones et al., unpublished). Besides

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Mycobacterium strains, also other Coryneform bacteria were used, i.e., Dietzia maris VM0283 [59], Dietzia maris IMV195 (DSM43627T), Corynebacterium glutamicum 2247 (DSM20411T), Tsukumurella paurometabola (DSM 20162T), Nocardia asteroides N3 [32], Nocardia coeliaca AB.4.1.b (DSM44595T), Pseudonocardia hydrocarbonoxydans (DSM43281T), Rhodococcus erythropolis ICPB4417 (DSM43066T), Gordonia hydrophobica 1610/ 1b (DSM44015T), and Gordonia amarae Se 6 (DSM43392T). Other Actinomycetales used, not belonging to the Coryneform bacteria, were Actinomyces sp. A1008 [32], Actinosynnema mirum 101 (DSM43827T), Arthrobacter sufureus 8-3 (DSM20167T), Kineospora aurantiaca A/10312 (DSM43858T), Microbispora rosea IMRU37485 (ATCC21946), Micromonospora chalcea A0919, A2868, A2894 [32], Planomonospora parontospora B-987 (DSM43869T), Promicromonospora citrea INMI 18 (DSM43110T), Streptomyces albus A0818, A1893, A2198, A3986 [32], Streptomyces aureofaciens A-377 (DSM40127T), Streptomyces rutgersensis BJ-608 (DSM40830T), Streptomyces phaeofaciens T-23 (DSM 40367T), and Streptosporangium album A0958 [32]. Strains used belonging to the Proteobacteria phylum were Agrobacterium luteum A61 (DSM5889T), Brevundimonas diminuta 342 (DSM7234T), Sphingomonas chlorophenolica DSM43869T, Ralstonia metallidurans CH34 (DSM2839T), Burkholderia sp. JS150 (DSM8530T), Aeromonas enteropelogenes J11 (DSM6394T), Acinetobacter calcoaceticus 46 (DSM30006T), Pseudomonas putida DSM8368T, Desulfobacter latus AcRS2 (DSM 3381T), Desulfonema magnum 4be13 (DSM2077T), and Desulfolobus rhabdoformis M16 (DSM8777T). In addition, 1 strain from the Flavobacteria phylum, i.e., Flavobacterium resinovorum (ATCC33545T), was included. Most strains were obtained from the DSMZ culture collection (DSMZ, Braunschweig, Germany), provided by other laboratories [5,9,32,33] or selected from the inhouse collection of PAH-degrading strains previously isolated from PAH-contaminated soil (Springael et al., unpublished). For DNA-extraction purposes, strains other than mycobacteria were cultivated in 869-broth [34], while Mycobacterium strains were cultivated in Middelbrook 7H9 Broth (DIFCO, Kansas City, USA). For inoculation purposes, Mycobacterium strains were cultivated in a phosphate-buffered minimal liquid medium as described by Wick et al. [35], containing 2 g l
1 of anthracene or pyrene crystals (ACROS Organics, Fisher Scientific, Boston, USA) floating in the medium as the sole carbon and energy source. All cultures were grown in the dark on an orbital horizontal shaker at 200 rpm at a constant temperature of 30 C. 2.2. Soils used in this study Soil samples were taken from different anthropogenic PAH-contaminated sites (Table 1). The soil tex-

377

ture, pH, total carbon content (TC), total inorganic carbon (TIC) content and total organic carbon (TOC) content (TC – TIC) of each soil sample were determined using standard methods (DIN Method 38414, S4; ISO-CEN ENMethod 1484). The soils were chemically analyzed for the 16 PAHs legislated by the US Environmental Protection Agency [36]. PAHs were extracted through an accelerated solvent extraction (ASE 200 Accelerated Solvent Extractor, Dionex Corp., Sunnyval, CA) using a standard approach (EPA Method 3545). ASE-extracts were purified over an internal silica phase in the extraction cell (i.e., in thimble clean up) followed by an alumina column. For quantification, capillary gas chromatography (GC, MFC 500, Carlo Erba Instruments, Milan, Italy) was used, coupled to a mass-spectrophotometric detector operated in the selected ion-monitoring mode (MS, QMD 100, Fisons Instruments, Loughborough, UK) (EPA Method 8270). The total concentration of mineral oil present in the soil sample was determined after an ultrasonic tetrachloroethene extraction followed by a FLORISIL clean up (FLORISIL, US Silica Company, Berkeley Springs, USA), using an infrared quantification at 2925, 2958 and 3030 cm
1 (NEN Method 5733). 2.3. Design of a 16S rRNA gene primer set specific for fast-growing mycobacteria Primer sequences were selected from a multiple alignment constructed with the Bionumerics software (Version 2.50, Applied Maths, Kortrijk, Belgium) of approximately 200 16S rRNA genes (GenBank, NCBI) [37], representing approximately 100 fast- and 100 slow-growing Mycobacterium species. The alignment was further analyzed with the PLOTCON program (Version 1.9.1, EMBOSS) [38] to identify conserved and variable gene regions. Based on the alignment, new Mycobacterium specific primers were selected in gene regions that are conserved within the group of fast-growing Mycobacterium species, but as variable as possible within slow-growing mycobacteria. In addition, for optimal species differentiation during DGGE-analysis of the PCR-products (see below), the primers were selected so that they amplified a region between 200 and 600 bp long with high variability. The selectivity of the selected primers was evaluated by visual analysis of the primer region within the constructed alignment of Mycobacterium rrn genes, by the Sequence Match program (RDP II) [39] and by the Advanced Blast Search program (GenBank, NCBI) [37,40]. The best primer combination consisted of the forward primer MYCO66f (5 0 -CATGCAAGTCGAACGGAAA-3 0 , Escherichia coli position 66–84) and the reverse primer MYCO600r (5 0 -TGTGAGTTTTCACGAACA-3 0 , E. coli position 600–583). A 40-basepair long GC-clamp [41,42] was attached to the 5 0 end of the MYCO600r primer for

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Table 1 Soil samples used in this study Soil

Origin

Soil type

pH

TOC (%)

S587 S588 S585 S589 S592 S584 S591

Corn field (Belgium) Horse pasture (Belgium) Pine tree forest (Belgium) Ditch in agricultural area (Belgium) Vegetable garden (Belgium) Compost heap (Belgium) Non-paved land road (Belgium)

Sand Sand Sand Sand sand Sand Sand

5.5 6.0 5.8 5.8 7.0 7.3 9.0

2.15 2.46 3.19 4.24 3.16 7.04 0.76

TB3 K3840 B101 E6068 TM Barl AndE

Coal gasification plant (Belgium) Gasoline station site (Denmark) Coal gasification plant (Belgium) Gasoline station site (Denmark) Coal gasification plant (Belgium) Coal gasification plant (Germany) Railway station site (Spain)

Sand Sand Sand Sand Sand Gravel Clay

8.23 8.20 7.00 7.96 8.00 8.90 8.10

1.52 0.50 2.63 9.94 3.85 4.63 2.35

PAH conc. (mg kg
1) 0.289 0.391 0.673 0.721 1.011 1.063 3.357 14 20 107 258 506 1029 3022

DNA conc.a (lg g
1)

MYCOb

Nestedc

<50 <50 <50 <50 <50 <50 <50

31.00 18.00 31.75 49.50 38.25 27.75 6.25

+ + + + + + NP

ND ND ND ND ND ND ND

<50 98 70 300 4600 109 2700

2.65 2.75 27.25 5.40 4.75 6.15 3.40

+ + + + + NP NP

+ + + + + NP +

Oil conc. (mg kg
1)

a

DNA recovery per g soil, mean value of 2 parallel extractions of 1 g of soil. Result of direct PCR with Mycobacterium specific primers MYCO66f and GC40-MYCO600r on soil DNA extract: +, detectable PCR product; NP, no detectable PCR product and ND, not determined. c Result of nested PCR with eubacterial primers 27f and 1492r followed by Mycobacterium specific primers MYCO66f and GC40-MYCO600r on soil DNA extract: +, detectable PCR product; NP, no detectable PCR product and ND, not determined. b

DGGE analysis of the Mycobacterium amplicons. This new primer couple MYCO66f and GC40-MYCO600r amplified a 538 bp sequence of the 16S rRNA gene, resulting in a PCR-product of 578 bp. 2.4. DNA-extraction Genomic DNA from pure bacterial cultures was obtained as described by Belisle et al. [43]. The DNA recovery was approximately 2.7–27.3 lg DNA g
1 soil. For PCR purposes, the DNA-concentration was adjusted to a final concentration of 100 ng ll
1. For fast-growing mycobacteria, 100 ng of template DNA corresponds to approximately 1.2–1.9 · 107 cell equivalents of genomic DNA and 2.4–3.8 · 107 copies of PCR targets, assuming a genomic molecular weight of 3.13–5.20 · 109 Da per cell and two 16S rRNA gene copies per genome [44]. DNA was extracted from 1 g soil, using a protocol described by Boon et al. [45]. After purification over a Wizard column (Promega Corporation, Madison, USA), the DNA concentration in the 50ll soil extract was measured spectrophotometrically. To assure that the soil DNA was of PCR quality, dilution series of soil DNA extracts were tested by PCR with the universal eubacterial 16S rRNA gene primer pair GC40-63f and 518r as previously described [46]. 2.5. PCR amplification of pure strain and soil DNA The PCR protocol used with the MYCO66f and MYCO600r primer pair consisted of a short denaturation of 15 s at 95 C, followed by 50 cycles of denaturation for 3 s at 94 C, annealing for 10 s at 50 C, elongation for 30 s at 74 C, and a final extension for 2 min at 74 C.

Primers designed by Cheung and Kinkle (MycF and MycR) were used for PCR amplification as described [31]. PCR was performed on Biometra (Go¨ttingen, Germany) or Perkin Elmer (Connecticut, USA) thermal cyclers. PCR mixtures contained 100 ng of pure strain DNA or dilutions of soil DNA as templates, 1 U Taq polymerase, 25 pmol of each primer, 10 nmol of each dNTP and 1 · PCR buffer in a final volume of 50 ll. In the nested PCR approach, the eubacterial primers 27fC (5 0 AGAGTTTGATCCTGGCTCAG 3 0 ) and 1492rC (5 0 TACGGCTACCTTGTTTACGACTT 3 0 ) were used in the first amplification round as described elsewhere [47], and 1 ll of the resulting unpurified PCR-product was used as a template in the second PCR with the MYCO66f and MYCO600r primers. All primers were synthesized by Westburg (Westburg BV, Leusden, The Netherlands). The Taq polymerase, dNTPs and PCR buffer were purchased from TaKaRa (TaKaRa Shuzo Co., Ltd., Biomedical Group, Kyoto, Japan). 2.6. DGGE analysis The PCR-products were examined on 1.5% agarose gels (MetaPhor, BioWhittaker, Labtrade Inc., Miami, FL) and directly used for DGGE analysis on polyacrylamide gels as previously described [48]. Optimal denaturing conditions were defined based on the theoretical melting temperatures of amplification fragments, calculated with the Melt Analysis Software (Version 1.0.1, INGENY International BV, Goes, The Netherlands). A 6% polyacrylamide gel with a denaturing gradient of 40–75% (100% denaturant gels contain 7 M urea and 40% formamide) was used for DGGE. Electrophoresis was performed at a constant voltage of 130 V for 16.6

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h in 1 · TAE running buffer at 60 C in the DGGE-machine (INGENYphorU-2, INGENY International BV, Goes, The Netherlands). After electrophoresis, the gels were stained with 1 · SYBR Gold nucleic acid gel stain (Molecular Probes Europe BV, Leiden, The Netherlands) and photographed under UV light, using a Pharmacia digital camera system (Image Master VDS, Pharmacia Biotech, Cambridge, England) with Liscap Image Capture software (Version 1.0, Pharmacia Biotech, Cambridge, England). Photofiles were processed and analyzed using Bionumerics software (Version 2.50, Applied Maths, Kortrijk, Belgium). 2.7. Sensitivity of the PCR-DGGE method To study the sensitivity of the PCR-DGGE method, a known amount of viable Mycobacterium cells was added to white sand (a model soil matrix) or other soil samples (Table 1) at different final cell densities (i.e., a 10-fold dilution series of approximately 108–101 cells g
1), prior to DNA-extraction. Cells were harvested from liquid cultures, washed twice and added in 100 ll aqueous suspensions to 1 g of soil. One, two or three different Mycobacterium strains (LB501T, VM0552 and DSM43524T) were separately or simultaneously added in different cell densities to assess the effect of cell ratios on the detection sensitivity for each single strain within a Mycobacterium population. In parallel, DNA was extracted from serial dilutions of the cell cultures. The different DNA-extracts or dilutions thereof were subsequently used as templates for direct PCR or the nested PCR as described above. 2.8. Sequence analysis of amplified 16S rRNA gene fragments PCR products of Mycobacterium 16S rRNA genes were cloned into plasmid vector pCR2.1-TOPO, using the TOPO Cloning Kit (N.V. Invitrogen SA, Merelbeke, Belgium) as described by the manufacturer. DGGE patterns of cloned fragments were compared with the fingerprints of the parent soil Mycobacterium community to identify which signals from the community fingerprint were cloned. A 500-bp long fragment was sequenced (Westburg BV, Leusden, The Netherlands) from a selection of cloned inserts with different DGGE-patterns. The sequences were analyzed with the ÔChimera CheckÕ program (RDPII) [39] to detect possible chimeras and with the ÔBlast SearchÕ program (GenBank, NCBI) [40]. Cloned sequences were imported into an alignment of Mycobacterium 16S rRNA genes and edited manually to remove nucleotide positions of ambiguous alignment and gaps. Sequence similarities were calculated over the 16S rRNA gene fragment between the MYCO-primers, corrected using KimuraÕs two-parameter algorithm to compensate for multiple nucleotide exchange and used

379

to construct a distance-based evolutionary tree with the Neighbor-Joining algorithm [49]. The topography of the branching order within the dendrogram was evaluated using the Maximum-Likelihood [50] and the Maximum-Parsimony [51] character-based algorithms in parallel combined with bootstrap analysis with a round of 500 reassemblings. An out-group of the closely related genera Rhodococcus and Dietzia was included to root the tree. 2.9. Nucleotide sequence accession numbers The partial 16S rRNA gene sequences of Mycobacterium clones reported in this study are available from GenBank under Accession Nos. AY148197 to AY148217.

3. Results 3.1. Design of specific 16S rRNA gene primers for PCR detection of fast-growing PAH-degrading mycobacteria A new specific primer set was designed to amplify the 16S rRNA genes of fast-growing Mycobacterium species. Based on an alignment of approximately 200 sequences, the 16S rRNA genes of fast- and slow-growing mycobacteria appeared highly conserved in comparison to other bacteria, i.e., only a few short well-defined regions within the gene were found to be highly variable (data not shown). A minimum similarity of 94% over the total length of the 16S RNA gene was found for all fast-growing mycobacteria. The best possible primer combination was selected from the alignment taking into account the amplicon length and amplicon sequence variability and the Blast and sequence match results of both primers. The sequence of the forward primer MYCO66f (E. coli locations 66–84) was conserved in 300 rrn gene sequences of mainly fast-, but also of some slow-growing mycobacteria of the approximately 900 Mycobacterium sequences currently available in the GenBank database (NCBI) (Table 2). The MYCO66f primer also aligned 100% with Corynebacterium, Phytoplasma, Gordonia and Propionibacterium 16S rRNA genes. The sequence of primer MYCO600r (E. coli locations 600–583), however, was 100% conserved in only 165 sequences of exclusively fast-growing environmental Mycobacterium strains, including all known PAH-degrading species (Table 2). It clearly differed with respect to most other 16S rRNA gene sequences from slow-growing mycobacteria and non-mycobacterium strains with 1 to 7 mismatches of the 18 bp long primer region (Table 2). In comparison with the Mycobacterium specific primers MycF and MycR described by Cheung and Kinkle [31], forward primers MYCO66f (this study) and MycF [31] were similarly conserved in mycobacterial 16S rRNA genes, but

380

Table 2 DNA-sequence homology between the Mycobacterium genus-specific primers and the 16S rRNA gene sequence of some reference mycobacteria Organism

16S rRNA genea

Primersb MYCO66f (E. coli 66–84) 5 0 -C A T G C A A G T C G A A C G G A A A-3 0

X55598 AF023664 X55595 X93182 X79094 X55593 AJ276274 X81996 X93184 X55591 M29564 X93183 AF058712 U90876 AF44638 AJ012738 U90877

------------------------------------------------------------------------------------------region unsequenced -------------------------------------------------------

-

-

-

-

-

-

T

-

-

-

-

-

-

-

-

-

-

Slow-growing Mycobacterium species M. gordonae DSM44183T M. genavense ATCC51233 M. branderi ATCC51789T M. leprae M. tuberculosis H37Rv M. ulcerans

X52923 X60070 X82234 X55587 NC_000962 X88926

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

T -

Non-Mycobacterium bacteria Gordonia terrae AB111113 Corynebacterium sp. ATCC43833 Phytoplasma sp. Rhodococcus globerulus NCIB12315 Dietzia maris DSM43672

AF397061 AF262996 AF500334 X77779 X79290

-

-

-

-

-

-

-

-

-

-

-

-

G

-

-

-

T T

a b

Accession No. of 16S rRNA gene sequence in the GenBank (GenBank, NCBI, Rockville, Pike Bethesda, USA). N = A or T or G or C, Dashes indicate homologous sequences.

-

-

-

-

-

-

-

A -

-

-

-

-

-

-

-

-

-

-

-

-

-

C C C C C

C -

C -

C -

C -

G -

A A A A

A -

-

-

-

-

-

-

G -

-

N -

N -

-

-

C C

C T -

C G G A

A -

T G

A A A A

-

-

A -

C C A -

A A A -

C C C A A

A A T G

A -

G -

C C -

G G G G G

-

N.M. Leys et al. / FEMS Microbiology Ecology 51 (2005) 375–388

Fast-growing Mycobacterium species M. aichiense DSM44147T M. alvei DSM44176T M. aurum DSM43999T M. austroafricanum DSM44191T M. chlorophenolicum DSM43826T M. diernhoferi DSM43524T M. frederiksbergense DSM44346T M. gilvum DSM44503T M. hodleri DSM44183T M. komossense DSM44078T M. neoaurum DSM44074T M. parafortuitum DSM43528T M. peregrinum DSM43271T M. petroleophilum RF002 M. vaccae VM0587 M. sp. DSM44238 M. sp. WF2

MYCO600r (E. coli 600–583) 5 0 -T G T G A G T T T T C A C G A A C A-3 0

N.M. Leys et al. / FEMS Microbiology Ecology 51 (2005) 375–388

Fig. 1. Mycobacterium species differentiation by DGGE analysis of Mycobacterium DNA fragments amplified with the Mycobacterium genus-specific primer pair MYCO66f and GC40-MYCO600r. Lanes: 1, M. vaccae VM0587; 2, M. diernhoferi DSM43524T; 3, M. austroafricanum DSM7251; 4, M. austroafricanum DSM44191T; 5, M. aurum DSM43999T; 6, M. chlorophenolicum DSM43826T; 7, Mycobacterium sp. DSM44238; 8, M. hodleri DSM44183T; 9, M. gilvum DSM44503T; 10, M. petroleophilum RF002; 11, Mycobacterium sp. WF2; 12, Mycobacterium sp. GP1; 13, M. peregrinum DSM43271T; 14, Mycobacterium sp. VM0585; 15, Mycobacterium sp. VM0579; 16, M. frederiksbergense DSM44346T; 17, M. neoaurum DSM44074T; 18, M. alvei DSM44176T; 19, M. komossense DSM44078T; 20, M. parafortuitum DSM43528T; 21, M. aichiense DSM44147T. DGGE fingerprints of strains were compared by Bionumerics software based on corunning standard (not shown). The symbol * indicates multiple band DGGE patterns for single strains with arrows indicating the additionally cloned and sequenced bands.

reverse primer MYCO600r (this study) was far more specific for fast-growing mycobacteria than the MycR primer [31]. The primer couple MYCO66f and MYCO600r produced products of the appropriate size with the DNA obtained from the 40 tested Mycobacterium strains representing different fast-growing environmental and PAH-degrading species, as listed in Table 1. Due to the risks associated with most slow-growing Mycobacterium species classified as ÔBiosafety Level 2 & 3 0 -agents [52], only fast-growing reference strains were tested. No PCR-products were obtained with DNA from strains belonging to other related genera such as Actinomyces, Arthrobacter, Dietzia, Corynebacterium, Nocardia, Sphingomonas, Burkolderia, Acinetobacter, Desulfobacter and more. 3.2. Differentiation of fast-growing Mycobacterium species by DGGE-analysis In order to examine the potential of a PCR-DGGE method based on the new primer set to differentiate between species within a Mycobacterium community, pure strain DGGE-patterns of a variety of fast-growing mycobacteria were compared. Different Mycobacterium isolates belonging to the same species showed identical DGGE-patterns. This was observed for 8 M. austroafricanum-related strains tested, 7 M. frederiksbergenserelated strains tested and 10 M. gilvum related strains tested (data not shown). Usually, different species

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showed different DGGE fingerprints (Fig. 1). For example, the PCR-products obtained for the M. frederiksbergense-related strains clearly migrated differently from the products from M. austroafricanum or M. gilvum related strains. However, in some cases the differences in migration between different species were minor, such as seen for M. spaghni, M. hodleri and M. gilvum strains. The species-specific DGGE fingerprints usually displayed one single band. However, some strains revealed extra bands in comparison to other members of the same species (Fig. 1). For example, strains DSM7251 and VM0450 both showed a similar pattern with 5 bands, strains VM0579, VM0531 and VM0503 displayed 3 bands and VM0585 even 10 bands. 3.3. Sensitivity of the Mycobacterium-specific PCRDGGE protocol To examine the sensitivity of the PCR-DGGE protocol for the detection of Mycobacterium strains in soil, a known decreasing amount of Mycobacterium sp. LB501T cells was added prior to DNA-extraction, both to white sand as a model soil matrix and to different PAH-contaminated soil samples (Table 1). For some contaminated soils there was a clear inhibitory effect of the soil matrix on the PCR amplification, so the soil DNA template was diluted 1:10 or 1:100 prior to PCR. In a PCR with primer pair MYCO66f and GC40-MYCO600r, LB501T cells could generally be detected until a minimum cell concentration of 106–108 cells per gram of soil, depending on the soil used. Similar results were also obtained when two or three different Mycobacterium strains (LB501T and VM0552 or LB501T, VM0552 and DSM43524T) were simultaneously added to white sand in equal cell concentrations (ratios 1:1 or 1:1:1 ratio), i.e., all strains were detected equally well until a concentration of 106–107 CFU g
1 soil (Fig. 2(a)). To assess the impact of unequal cell concentration ratios on the detection sensitivity, different concentrations of VM0552 or VM0552 and DSM43524T (1:1) cells were added to white sand in the presence of a constant LB501T concentration of approximately 108 CFU g
1. Decreasing cell amounts of VM0552 and DSM43524T could be detected in the presence of 108 CFU g
1 LB501T cells, but only if the cell concentration was higher than 106 CFU g
1 (Fig. 2(b)). Attempts to significantly improve the detection limit by optimizing the DNA extraction and purification protocol or by reducing the length of the GC-clamp were not successful (data not shown). Similar detection limits were obtained with DNA extracts from dilution series of pure cultures and with dilution series of a pure culture DNA extract (data not shown). However, via a nested PCR approach, consisting of a first PCR with eubacterial primers followed by a second PCR with the MYCO-primers using the product of the first PCR as template, the detection limit

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Fig. 2. Detection efficiency of the PCR-(DGGE) method using the Mycobacterium genus-specific primer pair MYCO66f and GC40-MYCO600r in a direct or nested PCR-approach. (a) PCR-DGGE detection of the simultaneously added M. frederiksbergense LB501T, M. gilvum VM0552 and M. diernhoferi DSM43524T at cell concentrations of approximately 108, 107, 106, 105, 104, 103 and 102 CFU g
1 in white sand, using a direct PCR approach. The symbol * indicates the detection limit on the figure. (b) PCR-DGGE detection of M. gilvum VM0552 and M. diernhoferi DSM43524T added in declining cell concentrations together with a constant cell density of M. frederiksbergense LB501T of 108 CFU g
1 using the direct PCR approach. The symbol * indicates the detection limit on the figure. (c) PCR detection of M. frederiksbergense LB501T at cell concentrations of approximately 109, 108, 107, 106, 105, 104, 103 and 102 CFU g
1 in white sand using the nested PCR approach. In comparison to a marker (M), the lower arrow indicates the 578 bp Mycobacterium 16Sr RNA gene amplicon, the upper arrow indicates a 1465 bp 16S rRNA gene fragment, a residue originating from the first PCR with the 27fC/1492rC primer pair. No signal was obtained without added cells.

could be lowered to approximately 102 cells per gram of soil (Fig. 2(c)). Using this nested PCR protocol, a minimum of 50 fg of pure Mycobacterium chromosomal DNA could be detected in pure culture (data not shown). 3.4. Composition analysis of the fast-growing Mycobacterium community in soil The MYCO-primer PCR-DGGE method was used to assess the Mycobacterium community in a set of PAHcontaminated soil samples with different contamination records and in uncontaminated soils (Table 1). Indigenous mycobacteria could be detected in 6 of the 7 uncontaminated soils tested and in 6 of the 7 PAH-

contaminated soils tested (Fig. 3). PCR-DGGE fingerprinting with eubacterial primers revealed the presence of a heterogeneous bacterial soil community in soils negative by PCR with the MYCO-primer set. Moreover, DNA-extracts from parallel samples containing added Mycobacterium cells were amplified well with the MYCO-primer set, omitting PCR inhibition as a possible cause for the negative PCR results obtained with the MYCO-primer set for the unseeded samples. The DGGE fingerprints of the Mycobacterium community in the positive soil samples were complex, comprising several bands for each soil (Fig. 3(a)). The 16S rRNA gene PCR products from 1 uncontaminated and 3 contaminated samples were randomly cloned, and clones representing different bands from one soil fingerprint

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Table 3 Cloned 16S rRNA gene sequences retrieved from PAH-polluted soil samples Origin

Clones

Accession No.

Nearest match in blast analysis (Accession No.) T

Similarity (%)

Soil S589

S589/1 S589/2 S589/3 S589/4 S589/5 S589/6 S589/7

AY725804 AY725805 AY725806 AY725807 AY725808 AY725809 AY725810

M. M. M. M. M. M. M.

alvei DSM44176 moriokaense DSM44221T lacus lacus anthracenicuma margeritense 1336 hodleri DSM44183T

(AF023664) (AJ429044) (AF406783) (AF406783) (Y15709) (AJ011335) (X93184)

97 94 97 97 98 95 97

Soil K3840

K3840/1 K3840/2 K3840/3 K3840/4 K3840/6 K3840/7 K3840/8

AY148216 AY148200 AY148207 AY148201 AY148214 AY148197 AY148210

Mycobacterium sp. M0183 Mycobacterium sp. HXN1500a M. tusciae DSM44338T M. frederiksbergense LB501Ta M. austroafricanum DSM44191Ta M. gadium ATCC27726 M. tusciae DSM44338T

(AF055332) (AJ457057) (AF058299) (AJ245702) (X93182) (X55594) (AF058299)

99 98 95 98 98 98 99

Soil B101

B101/1 B101/2 B101/3 B101/4 B101/5 B101/6 B101/7

AY148202 AY148208 AY148198 AY148204 AY148212 AY148217 AY148215

Mycobacterium sp. JKD2385 M. isoniacini INA-I M. holsaticum 1406 M. tusciae DSM44338T M. septicum HX1900 M. petroleophilum RF002a Mycobacterium sp. WF2a

(AF221088) (X80768) (AJ310467) (AF058299) (AJ457056) (U90876) (U90877)

98 97 97 96 99 98 97

Soil TM

TM/1 TM/2 TM/3 TM/4 TM/5 TM/6 TM/7 TM/8

AY148211 AY148209 AY148203 AY148205 AY148206 AY148196 AY148213 AY148199

M. M. M. M. M. M. M. M.

tusciae DSM44338T tusciae DSM44338T tusciae DSM44338T tusciae DSM44338T tusciae DSM44338T moriokaense MCR07 septicum HX1900 tusciae DSM44338T

(AF058299) (AF058299) (AF058299) (AF058299) (AF058299) (AF058299) (AJ457056) (AF130308)

99 99 97 97 98 97 98 99

a

Known oil- or PAH-degrading bacterium.

Fig. 3. PCR-DGGE fingerprint of indigenous Mycobacterium cells in soil samples using the Mycobacterium-specific primers MYCO66f and GC40MYCO600r (a) and phylogenetic analysis of detected 16S rRNA gene sequences (b). (a) DGGE-fingerprints of the Mycobacterium population in different soils. Arrows indicate cloned ÔbandsÕ within the soil fingerprint, based on the comparison of migration profiles of pure clones and the soil profile. (b) Phylogenetic positioning of Mycobacterium 16S rRNA gene sequences detected in soil within the Mycobacterium genus. Arrows indicate cloned Mycobacterium 16S rRNA gene sequences retrieved from the different polluted soils. The evolutionary tree was generated by the NeighbourJoining method, based on Kimara 2-parameter corrected similarity percentages of 538 bp 16S rRNA gene fragments between the MYCO primers, and branching orders were evaluated using the Maximum-Parsimony algorithm. The topology was also evaluated by bootstrap analysis (500 reassemblings) and percentages of bootstrap support are indicated at the branch points, with values above 70% indicating reliable branches. An outgroup of the closely related genera Rhodococcus and Dietzia was included to root the tree. The bar at the top indicates the estimated evolutionary distance, i.e., 1% indicating an average of 1 nucleotide substitution at any nucleotide position per 100 nucleotide positions. The evolutionary distance between two strains is the sum of the branch lengths between them.

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Fig. 3 (continued)

were sequenced. All sequences exhibited high levels of similarity to 16S rRNA gene sequences of Mycobacterium strains (Table 3) and could be placed within the phylogenetic group of fast-growing Mycobacterium species (Fig. 3(b)), confirming the specificity of the primer

set. In the uncontaminated soil mainly sequences most similar to non-PAH-degrading mycobacteria were detected. Sequences that were closely related to 16S rRNA gene sequences of known PAH- and oil-degrading bacteria belonging to the species M. frederiksbergense,

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M. austroafricanum and M. petroleophilum were detected in contaminated soils K3840 and B101, but not in soil TM. However, the dominant 16S rRNA gene soil clone sequences from all 3 PAH-contaminated soils showed highest sequence similarities with the 16S rRNA gene of the relatively unknown M. tusciae. M. tusciae related sequences were not retrieved from the non-contaminated soil. Interestingly, the different soil fingerprints revealed bands closely related to M. tusciae, but with different migration profiles. In addition, the cloned sequences showed a relatively high variation in similarity scores (from 99% to 95%). The M. tusciae sequences isolated in this study grouped with other unidentified Mycobacterium sequences cloned from DNA from petroleumcontaminated soils found by Cheung and Kinkle, using the MycF and MycR primer pair [31] (Fig. 3(b)). Besides the M. tuscia strains, only strains of the M. monacence (AF107039) species, a fast-growing species represented by a type strain of clinical origin and an atypical isolate (U46146), seem to be closely linked to this cluster.

4. Discussion We developed a specific PCR-DGGE method to rapidly monitor the community composition of fast-growing mycobacteria in PAH-contaminated soil. The newly designed MYCO66f and MYCO600r primer set is the first primer set that is specifically developed for the detection of fast-growing Mycobacterium species. All previously described primer combinations were specific for the total Mycobacterium genus [22,24–31] or exclusively for pathogenic and facultative pathogenic slow-growing mycobacteria [23,28]. DGGE analysis of gene fragments amplified with the MYCO primer set could differentiate between most fastgrowing Mycobacterium species, including all important PAH-degrading species. For some very closely related species the DGGE fingerprints were identical, due to the strong conservation of the Mycobacterium 16S rRNA genes. For comparison, the 16S rRNA gene amplicons obtained with primer pair MycF and GC40MycR, designed by Cheung and Kinkle [31], were also analyzed by DGGE. Although a different fragment of the 16S rRNA gene was amplified, PCR-DGGE with both primer sets resulted in the same species differentiation degrees for all Mycobacterium strains tested (data not shown). The amplified rrn gene fragments of species that could not be differentiated by DGGE, such as M. spaghni, M. hodleri and M. gilvum, had a similarity of 99–100%. Similarly, other studies using DGGE analysis of 16S rRNA gene fragments could not discriminate between several species of Burkolderia [53] and Bifidobacterium [54] or other Gram-positive coryneform soil bacteria such as Arthrobacter and Nocardoides [55], due to the high conservation levels of the amplified

385

16S rRNA gene fragments. It is clear that the practical resolution limit of the DGGE technique is at the species or genus level or intermediate between the two, depending on the gene conservation level within the taxonomic group that is under investigation. Most Mycobacterium strains were characterized by a single-band DGGE fingerprint. Only a few strains showed satellite bands. The same numbers of DGGE bands per strain were obtained when using the MycF and MycR primers (designed by Cheung and Kinkle) on the test strains [31] (data not shown). Others also reported multiple-band DGGE patterns for pure strains of species such as Paenibacillus polymyxa [56], Burkholderia cepacia [53] and Bifidobacterium adolescentis [54], due to the presence of multiple 16S rRNA gene copies with sequence heterogeneity. However, based on own southern blotting and DNA–DNA hybridization results (data not shown), other reports and analysis of the total genome sequences from 3 mycobacteria from clinical origin, slow-growing and fast-growing mycobacteria possess only 1 and 2 copies, respectively, of rrn genes with minor sequence variations [44,57], theoretically leading to a maximum of 2 homoduplex bands in a DGGE gel. The additional bands in the upper part of the DGGE gel are presumably the result of heteroduplex formation during PCR between the different copies of 16S rRNA genes within one strain [54,58]. Such specific DGGE fingerprints of 16S rRNA gene heteroduplexes have even been used for the identification of Mycobacterium strains [58]. Taking into account the possible heteroduplex formation and the fact that some species or strains may give more than one fragment in DGGE, some caution must be exercised when interpreting the DGGE community fingerprints, especially when estimating strain and species numbers and diversity. On the other hand, multiple bands were only observed for some isolates, so these effects may be minor. With the one-step PCR-DGGE method, using only the MYCO66f and GC40-MYCO600r primer pair, mycobacteria could be detected with a detection limit of approximately 106 cells per gram soil. None of the other Mycobacterium genus specific primer sets developed in the past report on the Mycobacterium abundance or detection limit in environmental samples for comparison [28–31], but we found a similar detection limit when using the primer set developed by Cheung and Kinkle [31]. The value reported for a similar direct PCR-DGGE detection method for Burkholderia species in soil was only slightly lower (detection limit 5 · 105 CFU g
1) [53], although more copies of the rrn genes are present in the target bacterium (6 rrn copies in Burkholderia while 2 in mycobacteria). Nested PCR, using eubacterial primers in the first round and the MYCOprimers with GC-clamp in the second round, drastically lowered the detection limit to approximately 102 cells per gram soil. Another approach could be the use of

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the more abundant rRNA molecules instead of the rRNA gene as targets for the MYCO-primers in a reverse transcription PCR (RT-PCR) protocol. In a RTPCR set up using the MYCO-primer set, Mycobacterium sp. LB501T was detected at a concentration as low as 102 active cells per gram soil (Hendrickx et al., unpublished data). Based on our results, all fast-growing Mycobacterium strains are expected to be detected equally well in a mixed Mycobacterium community. Our results clearly suggest a wide distribution of fastgrowing mycobacteria in the environment, since fastgrowing mycobacteria could be detected in most contaminated and uncontaminated soils. Unlike Cheung and Kinkle [31], we found no clear correlation between Mycobacterium biodiversity (assessed by the number of bands in the Mycobacterium DGGE fingerprints) and the PAH-concentration of the soils. In contrast, strong signals for Mycobacterium were especially obtained with soils containing relatively low concentrations of PAHs with mainly higher molecular weight and hence low-bioavailable PAHs. In comparison, weaker signals for Mycobacterium were obtained with soils containing high concentrations of mostly more bioavailable and more easily degradable 3-ring PAHs such as phenanthrene. In the latter case, mycobacteria might be out-competed by more quickly growing PAH-degrading bacteria such as Sphingomonas or Pseudomonas species. Interestingly, in a parallel study examining the same soils as in this study, high concentrations of Sphingomonas were especially encountered in the soils containing high phenanthrene concentrations [64]. The presence of mycobacteria in soils with lower PAH-concentrations may indicate a natural selection of fast-growing Mycobacterium species in PAH-polluted soil enriched in less bioavailable and more recalcitrant, high(er)-molecular weight PAHs. Mycobacterium species may be better adapted to harsh oligothrophic soil conditions, as they have a low maintenance energy demand and make use of several PAH bioavailability-enhancing mechanisms such as high-affinity uptake systems and special adhesion to the substrate [35,59]. Strains closely related to known, fast-growing PAHdegrading isolates belonging to the M. frederiksbergense and M. austroafricanum species were detected only in PAH-contaminated soils. None of the detected sequences from contaminated soils seemed to originate from strains belonging to M. gilvum species, another species known to comprise many PAH-degrading strains [3,5,60]. Surprisingly, mainly sequences related to the M. tusciae species were repeatedly detected in all PAH-contaminated soils, originating from different countries and different industrial sites, but not in the uncontaminated soil. The M. tusciae sequences isolated in this study grouped with other unidentified Mycobacterium sequences cloned from DNA from petroleum-contaminated soils and found by Cheung and Kinkle using the

MycF and MycR primer pair [31]. These results may indicate an important role for M. tusciae and/or its related species in PAH-degradation processes in soil. The M. tusciae species has never been isolated or detected before in PAH-contaminated soils and the type strain of this species, M. tusciae strain DSM44338T, is a facultative pathogenic clinical isolate from a sick child [61]. However, recently, two unpublished vinyl chloridedegrading soil isolates (Coleman et al., unpublished) were identified as members of the M. tusciae species. Based on the different DGGE bands and the varying similarity of the clones to the type strain, we may have detected two still unknown species relatively closely related to M. tusciae. The repeated detection of Mycobacterium cells in soils with low PAH-concentrations support the natural importance of fast-growing Mycobacterium species in PAH-polluted soil. The developed PCR-DGGE detection system is an important tool to specifically monitor the natural abundance, the diversity and the dynamics of these bacteria in soil for optimization of bioremediation. The developed primer pair may also be useful in a RT-PCR approach with ribosomal RNA soil extracts to analyze the diversity of the actively PAH-degrading population of fast-growing mycobacteria. Eventually, these primers could be combined with primers developed for the detection of messenger RNA of the well-conserved PAH-catabolic genes in mycobacteria [62,63]. This will contribute to a better understanding of the role of mycobacteria in the biodegradation of PAHs in the environment.

Acknowledgments This work was supported by the European Commission, through the contracts BIO4-CT97-2015 and QLRT-1999-00326. We thank E.M.H. Wellington for providing bacterial strains and S. Schioetz-Hansen, J. Amor and J. Vandenberghe for providing soil samples.

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