Biol Fertil Soils (2008) 44:557–569 DOI 10.1007/s00374-007-0235-5 ORIGINAL PAPER Diversity of heterotrophic aerobic cultivable microbial communities of soils treated with fumigants and dynamics of metabolic, microbial, and mineralization quotients Stefano Mocali & Donatella Paffetti & Giovanni Emiliani & Anna Benedetti & Renato Fani Received: 20 June 2006 / Revised: 31 July 2007 / Accepted: 1 August 2007 / Published online: 6 September 2007 # Springer-Verlag 2007 Abstract A combination of molecular and classical techniques was used to study the composition, structure, diversity, and dynamics of an aerobic heterotrophic cultivable bacterial community isolated from five different soil samples treated with the fumigant agent 1,3-dichloropropene (1,3-D) and further subjected to nitrogen–phosphorous–potassium (NPK) fertigation (F), amendment (C2 and C4), and NPK fertigation plus amendment (F+C) in two different periods (May and July). The restriction and sequence analysis of 16S rDNA from 189 isolates revealed a very high percentage (94%) of Gram-positive bacterial isolates, most of which (83%) belonging to the genus Bacillus. The degree of intraspecific genetic diversity was high, as shown by random amplified polymorphic DNA analysis. These data seem to be related with the increase in microbial biomass C (Cmic) content and the decrease in the total organic C (Corg) and metabolic quotient (qCO2) values, especially in amended Stefano Mocali and Donatella Paffetti contributed equally to this work. S. Mocali : A. Benedetti C.R.A.-Istituto Sperimentale per la Nutrizione delle Piante, Via della Navicella 2-4, 00184 Rome, Italy D. Paffetti : G. Emiliani Dipartimento di Scienze e Tecnologie Ambientali Forestali, University of Florence, Via S. Bonaventura, 13, 50145 Florence, Italy R. Fani (*) Dipartimento di Biologia Animale e Genetica, University of Florence, Via Romana 17-19, 50125 Florence, Italy e-mail: r_fani@dbag.unifi.it soils (C2, C4) where soil microflora mineralized the organic matter of the added fertilizers. In a short term, it is suggested that the presence of very high percentage of Gram-positive bacteria might be related to the ability of these bacteria to form spores so as to be resistant to fumigants rather than being the result of a selective pressure in the predominance of microbial species with a set of genes involved in biodegradation of 1,3-D. Keywords Biodiversity . Fumigants . Soil fertility Introduction One of the most important problems in crop production is represented by parasites of plants such as nematodes (Baldwin et al. 2004). In particular, the nematode Heterodera carotae causes damages in carrots and in some other Umbrelliferae. For many years, the fumigant methyl bromide (MeBr) has been used to provide an effective control of nematodes in agricultural soils. However, it was recognized to have negative effects on stratospheric ozone (Park et al. 2004; Prather et al. 1984); hence, according to the protocol of Montreal (1997), it was phased-out of use in Europe and in USA on January 1, 2005. Most of the fumigants commonly used to replace MeBr can have broad biocidal activity in agricultural soils (Giannakou et al. 2002), but their effects on soil microflora are still largely unknown. Repeated application of fumigants to agricultural soils for many years may modify soil microbial diversity, biomass, and activities with indirect effects on soil “quality” that, according to Doran and Parkin (1994), can be defined as “the capacity of the soil to interact with the ecosystem in order to maintain biological productivity, environmental quality and to promote animal and plant health.” 558 Recently, the effects of 1,3-dichloropropene (1,3-D), methyl isothiocyanate, and chloropicrin on the structure of soil microbial community have been studied using both culture-dependent and culture-independent approaches (Ibekwe et al. 2001a). It was shown that Gram-positive bacteria survived better than Gram-negative to the fumigant treatment and that 1,3-D was the least effective fumigant in affecting the structure of soil microbial community. Ibekwe et al. (2001b) also showed that, after treating microcosm with 1,3-D for 6 months, Pseudomonas and Actinomadura were the predominant soil bacterial species. Furthermore, Smelt et al. (1989) and Ou et al. (1995) found that, after repeated applications of 1,3-D, the effect of the fumigantnematocide was markedly decreased due to the microbial degradation that probably was also stimulated by the application of compost manure (Gan et al. 1998). On the other hand, very little information on the effect of the addition of different amendments on microbial activity and soil quality of fumigated soils is available. Because biological parameters have assumed particular importance in the assessment of soil quality, because organisms respond more rapidly than most chemical and physical parameters to changes in land use, environmental conditions, or contamination (Burns et al. 2006), a number of soil criteria related with soil microbiological functions, such as the metabolic quotient (qCO2), the microbial quotient (Cmic/Corg ×100), and the mineralization quotient (qM), have been used to evaluate the efficiency of utilization and conservation of organic matter after different agronomical treatments. Indices based on the combination of microbial respiration and microbial biomass measurement, such as qCO2, may be more sensitive than microbial activity or microbial biomass alone to assess effects of soil pollution (Nannipieri et al. 1990; Brookes 1995; Dilly and Munch 1998). The qCO2 can reflect the maintenance of carbon requirement of cells, and an increase of qCO2 can be related to microbial stress (Anderson 2003) or to changes in the bacterial/fungal ratio (Sakamoto and Oba 1994; Landi et al. 2000). The microbial quotient is a sensitive parameter of changes in the organic C content (Anderson and Domsch 1990) and usually ranges between 1 and 4% with values below 1% being indicative of microbial stress (Jenkinson and Ladd 1981). The mineralization quotient representing the ratio between respiration and the total organic C content indicates the efficiency of microflora in metabolizing organic matter. To date, no study concerning with the effect of nematode fumigant on the abovementioned ratios is available, and this work may help in understanding better soil functionality after the fumigant treatment, by integrating data Biol Fertil Soils (2008) 44:557–569 regarding “soil quality” with taxonomical analysis of cultivable bacteria. The main objective of this work was to evaluate the effect of the 1,3-D fumigant on microbial activity, microbial biomass, and diversity of heterotrophic culturable microbial communities of soil, although they represent a minor proportion of bacteria inhabiting soil. We wanted also to evaluate the effects of different agronomical treatments on soil recovery in cases of negative effects by the fumigant. Materials and methods Soil treatments and sample collection This study was conducted in the agricultural cooperative S. Antonio of Maccarese, near Rome (Italy), one of the most important agricultural areas for carrots (Daucus carota). The soil had a loamy-sandy texture (IUSS) with pH 8.3 and a high content of exchangeable Ca (2.74 cmol(+) kg−1). The content of total N and organic matter was very low (0.04 and 0.43%, respectively) as well as the cationic exchange capacity (7.11 meq/100 g). This soil has been fumigated for more than 20 years with 1,3-D against nematodes. Samples were collected from the top 20 cm of soil in May 2002 (40 days after sowing) and at the end of July 2002 (after harvesting) with a spade because the soil was too sandy (92%) for a hole digger. The field experiment was based on the following four treatments, which were carried out adopting a randomized-block experimental design in five plots with three replicates, with a total of 15 different plots: 1. F; fertigation with 100 kg of ammonium nitrate applied before sowing, 50 kg of ammonium nitrate added at the end of May, and 50 kg of potassium nitrate added at the end of June. 2. F+C; soil was amended with 4 t of mixed compost amendment ha−1 before sowing and fertigated at the end of May with 100 kg of ammonium nitrate. 3. C2; soil was amended with 16 t of mixed compost amendment ha−1 before sowing (in February). 4. C4; soil was amended with 32 t of mixed compost amendment ha−1 before sowing (in February). 5. T is the control (not treated) soil. The compost (C; N content of 25%) was produced aerobically by composting a mixture of residual borlande from the distillation of grape cake (50–60%), olive cake (10–15%), residual of pruning of olive, grape vine, and other fructiferous (25–40%). Biol Fertil Soils (2008) 44:557–569 Each treatment was applied in plots of 5×5 m located at a distance of 1.5 m from each other, and for each of the 15 plots, 4 subsamples were collected at each sampling period (May and July), air-dried, and sieved (2 mm). Subsamples of the same plot were then pooled, and the resulting sample was mixed and stored for subsequent analyses. Biochemical and microbial parameters The soil used for this experiment was analyzed according to the official methods of Ministero delle Politiche Agricole e Forestali (1997, 1999). The total organic carbon (Corg), expressed as mg kg−1, was determined according to Springer and Klee (1954). Soil respiration was expressed as mg C-CO2 Kg−1soil d−1 and measured in a closed environment after 1, 2, 4, 7, 10, 14, 17, and 21 days according to Isermeyer (1952). Soil respiration data were fitted according to the first-order exponential equations Ct = C0(1−e−kt), representing the cumulative mineralization curves, where Ct is the total amount of mineralized carbon in laboratory conditions during 21 days of analysis (Riffaldi et al. 1996). A nonlinear regression square analysis was used to calculate the potentially mineralizable carbon pool C0 [mg(C) kg−1 soil] for each investigated soil. Basal respiration (Cbas) represents the value of mineralized C in a definite period of time (21 days), when steady-state condition has been reached. Microbial biomass carbon Cmic (mg C kg−1 soil) was measured by the fumigation– extraction method (Vance et al. 1987) on air-dried soils which were conditioned at −33 kPa water tension and preincubated for 10 days in open glass jars at 30°C. Several derived parameters were then calculated: the qCO2 (metabolic quotient), calculated by the ratio Cbas/Cmic [(mg CCO2 basal mg Cmic−1) h−1], the ratio Cmic/Corg (microbial quotient) expressed as a percentage [mg C biomass/mg total organic C × 100], and qM (mineralization quotient), expressed as mg C-CO2 kg−1 soil h−1 and calculated from cumulative respiration after 21 days by the relationship: CCO2 cum/Corg. Bacterial counts Bacteria were extracted from fresh soil and diluted in saline solution (0.85% NaCl) at suitable concentrations (10−1, 10−2, 10−3, 10−4, 10−5, 10−6, 10−7). Aliquots (0.1 ml) of each dilution were plated in triplicate onto Luria–Bertani (LB) medium. Plates were incubated at 28°C for 2 days; thereafter, colonies were counted, and the results reported in Table 2 expressed as n° of bacteria/g of fresh soil. Twenty visually distinct colonies were picked up at random 559 from each sample at each sampling date and transferred to Multiwell plates (Corning, New York, NY, USA). Each colony was purified on Nutrient Starch Agar (NSA) and stored at −20°C in LB (Difco Laboratories) with 20% glycerol. PCR amplification, restriction, sequencing, and analysis of bacterial 16S rDNA Bacterial colonies grown overnight on LB plates were resuspended in 20 μl sterile distilled water, heated to 95°C for 10 min, and cooled on ice for 2 min; each lysate (2 μl) was used for the amplification reaction via polymerase chain reaction (PCR). Amplification of 16S rRNA gene was performed in a total volume of 20 μl containing 2 μl of 10× reaction buffer (Polymed, Italy), 1.5 mM MgCl2, 150 ng of each primer [27f, 5′ GAGAGTTTGATCCTGG CTCAG, and 1495r, 5′ CTACGGCTACCTTGTTACGA] (Grifoni et al. 1995), 200 μM of each dNTP, 0.5 U of Taq DNA polymerase (Polymed). The reaction mixtures, after incubation at 95°C for 90 s, were subjected to the following temperature cycle: denaturation at 94°C for 30 s, annealing temperature for 30 s, extension at 72°C for 4 min; the annealing temperature was 60°C for the first five cycles, 55°C for the following five cycles, and 50°C for the last 25 cycles. Then the mixtures were incubated at 72°C for 10 min; 2 μl of each amplification mixture was analyzed by agarose gel (1.2% w/v) electrophoresis in Tris–acetate– ethylene diamine tetraacetic acid (TAE) buffer (0.04 M Tris–acetate, 0.001 M EDTA) containing 0.5 μg/ml (w/v) ethidium bromide. For restriction analysis, amplified 16S rRNA gene (1.5 μg) was digested with 3 U of the endonuclease AluI (Boehringer, Mannheim, Germany) in 30 μl, for 3 h at 37°C. The enzyme was then inactivated at 65°C for 10 min. Reaction products were resolved by agarose gel (2.5% w/v) electrophoresis in TAE buffer and stained with 0.5 μg/ml (w/v) ethidium bromide. The band of interest (observed under UV, 312 nm) was excised from the gel and purified using the “QIAquick” gel extraction kit (QiAgen, Chatsworth, CA, USA) according to manufacturer’s instructions. Direct sequencing was performed on both DNA strands using an ABI PRISM 310 Genetic Analyzer (Applied Biosystems) and the chemical dye terminator (Sanger et al. 1977). Nucleotide sequences were retrieved from the GenBank, EMBL, and RDP databases. BLAST probing of the DNA databases was performed with the BLASTN option of the BLAST program (Altschul et al. 1997). The ClustalW program (Thompson et al. 1994) was used to align the 16S 560 rRNA sequences obtained with the most similar ones retrieved from the databases. Each alignment was checked manually, corrected, and then analyzed using the neighborjoining method (Saitou and Nei 1987) according to the model of Kimura 2-parameter distances (Kimura 1980). Phylogenetic trees were constructed with the aligned sequences using Molecular Evolutionary Genetics Analysis 3 software (Kumar et al. 2004). The robustness of the inferred trees was evaluated by 500 bootstrap resamplings. Biol Fertil Soils (2008) 44:557–569 computes the statistical significance of each partition. This method allows computing the proportion of the overall community variation, which accounts for the differences between groups formed, joining together isolates from different samplings. Analyses were only performed on haplotype frequencies and for each analysis; 16,000 permutations were computed to obtain the significance levels of the variance. Results RAPD fingerprinting Soil properties Random amplification of DNA fragments was carried out in 25 μl of Platinum buffer (Gibco BRL) containing 3 mM MgCl2, 2 μl of lysed cell suspension, 500 ng of primer AP12 (5′-CGGCCCCTGC-3′), 200 mM of each dNTP, and 0.625 U of Platinum Taq polymerase (Gibco BRL; Mori et al. 1999). The reaction mixtures were incubated in a thermal cycler (model 9600; Applied Biosystems) at 94°C for 2 min. They were then subjected to 45 cycles, each consisting of incubation at 95°C for 30 s, 36°C for 1 min, and 72°C for 2 min; finally, the reactions were incubated at 75°C for 10 min and then at 60°C for 10 min. Reaction products were analyzed by agarose (2%, w/v) gel electrophoresis in TAE buffer containing 1 μg/ml of ethidium bromide. Using fingerprinting pattern of each random amplified polymorphic DNA (RAPD) product, genetic similarities in the different samples belonging to the same haplotype group were determined by pairwise comparison of the presence and absence of bands with Gelcompare II software (Applied Maths). A matrix containing similarity values was obtained with the Dice coefficient. This matrix was used to construct a dendrogram according to the unweighted-pair group method, using arithmetic average (UPGMA) cluster analysis. Statistical analysis Soil biochemical and microbiological data were tested for homogeneity of variance with the Levene test before undergoing the analysis of variance (ANOVA) using the program SPSS for Windows (vers. 11.0, 2001). After obtaining a statistically significant F test from the ANOVA, a post hoc comparison method (Tukey HSD) was used to identify which groups are particularly different from each other. To assess the partitioning of the genetic variance between different groups of communities, the analysis of molecular variance (AMOVA; Excoffier et al. 1992) using the program ARLEQUIN 2.000 (Schneider et al. 1997) was used. AMOVA divides the total variance into three hierarchical partitions, that is among groups, among populations within groups, and within populations. A test of permutation Samples collected in May from plots T and F (Table 1) did not show significant differences in any chemical or microbiological parameter (p>0.05). As expected, the fertilization with mixed C2 and C4 compost produced a significant increase in the Corg content (+46.1% and +75%, respectively; p<0.05) and in the basal respiration (+112.8% and +250.5%, respectively; p<0.05) with respect to values of T. Moreover, a consistent increase in Cmic values in F+C (+169.9%), C2 (+121.6%), and C4 (+207.6%) samples and in C0 values in C2 (+135.3%), C4 (+210.6%), and F+C (+88.6%) samples with respect to values of the untreated control (p<0.005) was observed. The metabolic quotient was the lowest in the F+C sample, but differences among soil samples were not significant, whereas the mineralization quotient in C2, C4, and F+C samples was significantly higher than values of F and T samples. The highest values of the microbial quotient (Cmic/Corg ×100) were shown by soils amended with F+C (+134.6%; p<0.05) with respect to the value of the control plots, whereas C2 and C4 samples showed values higher than F and T samples but lower than the value of the F+C sample (p<0.05). In July (Table 1), the content of the total organic carbon generally showed lower values than in May, but in C2 and C4 plots, it was still higher than in F+C soils (+19.6%, p< 0.05 and +34.7%, p<0.001, respectively); the T and F soils showed the lowest values. In comparison to May, Corg values decreased more in T (−44%), F (−41%), C2 (−27%), and C4 (−32%) than in F+C soils (−23%). Basal respiration was not significantly different between different soils (p>0.05), but C4 samples maintained high values of C0. Microbial biomass of C2 and C4 plots was greater than in any other sample (p<0.001), and it was significantly higher in July than in May (p<0.05), while a strong decrease in F+ C soil was observed (−33.6%). The metabolic quotient of C2 and C4 soils was significantly lower than in control soils (p<0.05), while the qCO2 of the F+C soils showed intermediary values between F and T soils. The mineralization quotient of the T soil was significantly higher than the other treated soils (p<0.05). Finally, Biol Fertil Soils (2008) 44:557–569 561 Table 1 Chemical and microbiological parameters of soils (Corg total organic C, Cbas basal respiration, C0 potentially mineralizable C, Cmic microbial biomass C, qCO2 metabolic quotient, qM mineralization quotient, and Cmic/Corg contribution of microbial biomass carbon to soil organic carbon) Parameter Units May Corg g C/100 g soil Cbas mg(C-CO2) kg−1soil (21st day) mg(C-CO2) kg−1soil mg C kg−1soil C0 Cmic qCO2 qM Cmic/Corg [(mg C-CO2 bas mg−1 Cmic) h−1] 104 (mg C-CO2 mg−1C) mg Cmic mg−1 C July T F F+C C2 C4 T F F+C C2 C4 0.52a (0.06) 1.94a (0.28) 0.60a (0.04) 2.56a (0.61) 0.60a (0.02) 3.93a (0.99) 0.76b (0.03) 4.13ab (0.92) 0.91c (0.06) 6.80b (1.77) 0.29a (0.04) 3.93a (2.97) 0.35a (0.01) 3.40a (1.25) 0.46b (0.03) 4.22a (2.34) 0.55c (0.04) 4.06a (1.53) 0.62c (0.03) 5.54a (0.64) 109.27a (7.13) 52.8a (11.5) 15.4a (4.7) 139.80a (10.91) 68.6a (8.2) 15.5a (5.3) 206.11b (21.24) 142.4bc (17.2) 11.5a (3.0) 257.08c (23.06) 116.9b (19.3) 14.7a (1.8) 316.86d (19.84) 163.8c (18.0) 17.3a (4.6) 170.20a (38.75) 81.8a (16.5) 25.1a (11.0) 199.54a (62.15) 93.8a (14.1) 15.1ab (3.7) 213.24a (44.24) 94.4a (17.3) 18.6a (6.8) 213.72a (54.83) 184.6b (16.9) 9.2b (4.4) 315.92b (48.90) 353.4c (41.3) 6.5b (1.2) 3.73a (0.44) 1.01a (0.12) 4.27a (0.23) 1.14a (0.22) 6.55b (0.31) 2.37b (0.23) 5.43b (0.52) 1.54c (0.31) 7.47b (0.49) 1.80c (0.09) 13.55a (0.81) 2.81a (0.24) 9.71b (1.21) 2.67a (0.36) 9.17b (0.99) 2.05a (0.25) 7.38b (1.21) 3.35b (0.10) 8.93b (0.87) 5.70c (0.91) For each parameter, different letters indicate significant differences (Tukey HSD Test). Standard deviation is reported in parenthesis. the C4 sample showed the highest value of Cmic/Corg ×100, while F and F+C soils showed values very similar to the untreated soil. Bacterial counts and molecular characterization Data concerning the bacterial counts are reported in Table 2 and showed that the number of viable cells ranged between 106 and 107 CFU/g of soil. Twenty colonies from each plate were further characterized using a combination of molecular PCR-based techniques, with a total of 189 isolates. Firstly, the 16S rRNA gene was amplified, and each amplicon was treated with the enzyme AluI as described in “Materials and methods.” A total of 23 amplified ribosomal DNA restriction analysis (ARDRA) (Vaneechoutte et al. 1992, 1993, 1995) patterns were obtained, and some of the restriction profiles appeared very similar, with many monomorphic bands, thus suggesting a taxonomical closeness of bacterial isolates. Eighteen of the 23 haplotypes were represented by only a few isolates (Table 3). The remaining five (A, C, E, N, and Q) were the main haplotypes, which accounted for about 65% of the total culturable bacteria. The nucleotide sequence of the 16S rRNA gene of one isolate from each ARDRA group was determined. Each of the sequences obtained was used to probe the nucleotide databases using the BLASTN option of the BLAST program (Altschul et al. 1997). The most similar orthologous sequences retrieved were then aligned with the program ClustalW (Thompson et al. 1994) to the sequences obtained. The phylogenetic analysis revealed that the 23 haplotypes were representative of seven bacterial genera. In particular: 1. Bacteria belonging to 15 different haplotypes (A, B, D, E, F, I, J, K, M, N, O, Q, R, S, and T) owned to the genus Bacillus. They represented the largest fraction of the bacterial community (about 83%). The 15 sequences felt in nine different clusters and corresponded to nine different Bacillus species, that is B. firmus, B. lentus, B. pumilus, B. licheniformis, B. megaterium, B. cereus, B. simplex, B. endophyticus, and B. psychrodurans. Table 2 Growth of bacterial colonies on LB medium expressed as n° of bacteria/g fresh soil (data reported are the mean of three replicates) Month May July Soil treatment T F F+C C2 C4 2.9±1.1×106 4.2±1.7×106 4.8±1.2×106 7.2±2.3×106 1.6±0.5×107 1.6±0.3×106 1.1±0.2×107 7.8±1.8×106 2.9±1.4×106 4.2±1.5×106 562 Table 3 Distribution of 23 ARDRA haplotypes obtained by restriction analysis of 16S rDNA with the endonuclease AluI from 189 bacteria isolated from different soil samples ARDRA group (haplotype) Soil treatment T Number of isolates/ haplotype F F+C % of total 16S rDNA sequence determined C4 C2 July May July May July May July May July A B C D E F 8 1 1 0 3 0 6 0 0 0 7 0 7 0 0 0 3 0 1 1 0 1 8 0 9 1 5 0 1 1 7 1 3 0 0 4 1 1 0 0 0 0 5 0 2 3 1 1 1 0 0 0 0 0 4 2 0 1 1 1 49 7 11 5 24 7 26.0 3.7 5.8 2.7 12.7 3.7 G 0 0 0 0 0 0 0 0 3 0 3 1.6 H I J K L M N O P Q R S T U V Z Number of isolates analyzed 1 0 1 0 0 0 0 0 0 1 0 0 0 1 1 1 19 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 19 0 0 0 2 1 0 0 0 0 3 0 3 0 0 0 0 19 0 0 1 1 1 0 0 0 0 2 0 2 1 0 0 0 19 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 18 0 0 0 2 0 0 0 0 0 1 0 1 0 0 0 0 19 0 0 0 0 0 0 10 0 2 2 0 0 0 0 0 4 20 2 0 0 3 1 0 0 0 0 1 0 0 0 0 0 0 19 0 2 0 0 0 0 10 2 1 0 0 0 0 0 0 0 19 0 0 0 0 0 2 2 0 2 0 3 0 0 0 0 0 18 3 2 2 9 3 2 22 2 5 16 3 6 1 1 1 5 189 1.6 1.1 1.1 4.7 1.6 1.1 11.6 1.1 2.6 8.4 1.6 3.2 0.5 0.5 0.5 2.6 100 According to 16S rDNA % identity sequence and phylogenetic tree (see also Fig. 1) B. firmus B. pumilus Arthrobacter sp. B. cereus B. firmus B. lentus B. lentus Sporosarcina sp. Sporosarcina sp. Staphylococcus B. firmus B. megaterium B. simplex Staphylococcus sp. B. lentus B. simplex B. lentus Alcaligenes sp. B. licheniformis B. psychrodurans B. endophyticus B. firmus Brachybacterium sp. Pseudomonas sp. Pseudomonas sp. Strain Accession number C2L8 F+CM18 F+CM7 C2L18 FL13 F+CL14 F+CL17 C4M11 C4M5 C2L11 C4M15 FL1 C2L3 C2L16 C4M16 C2M7 C4M20 C4M17 FL3 C2M6 FL7 FL20 TM6 TM16 C2M11 DQ073459 DQ073460 DQ073463 DQ073461 DQ073462 DQ112356 DQ112357 DQ112359 DQ112360 DQ076322 DQ089747 DQ089745 DQ089751 DQ089746 DQ089753 DQ073464 DQ112358 DQ089749 DQ089750 DQ089754 DQ089755 DQ089748 DQ089752 DQ078780 – Biol Fertil Soils (2008) 44:557–569 May a Taxonomya Biol Fertil Soils (2008) 44:557–569 2. Isolates belonging to haplotype C were clustered in the genus Arthrobacter. 3. Haplotype G joined the genus Sporosarcina. 4. Isolates belonging to haplotypes H and L felt in the genus Staphylococcus. 5. The five isolates belonging to haplotype P were clustered in the genus Alcaligenes. 6. Isolate representing haplotype U felt within the genus Brachybacterium. 7. Isolates belonging to the last two haplotypes (V and Z) were clustered in the genus Pseudomonas. The analysis of the data reported above revealed that 20 out of the 23 haplotypes (about 94.2% of the entire bacterial community studied) were Gram positive with a prevalence of the genus Bacillus. The alignment of the 16S rDNA sequences of the genus Bacillus isolates was then used to construct the phylogenetic tree shown in Fig. 1. Fluctuations of the bacterial community The bacterial community was analyzed to check the existence of a haplotype sharing and to investigate the effect of two parameters (sampling month and soil treatment) on variations in bacterial species/genera density within the community. Data obtained revealed that 19 and 17 haplotypes were found in May and July, respectively (Fig. 2). Thirteen haplotypes were shared between May and July samples, whereas six and four haplotypes were exclusive of May and July samples, respectively. The distribution of ARDRA haplotypes was analyzed to check the effect of soil treatment on the dynamics of each (or group of) ARDRA haplotype. This analysis revealed that just 1 of the 23 haplotypes, i.e., ARDRA group A (B. firmus), was represented in all of the samples collected in May and July (Fig. 3). In addition to this, the total number of different haplotypes was higher in C (13 in C2 and 12 in C4) than in T (10), F (10), and F+C (8) soil samples; this was parallel to the increase in unique haplotypes (7 in sample C, 2 in T, 1 in F, and 0 in F+C). Therefore, in C samples, the number of isolates per haplotype was generally lower than that found in T and F samples. The only exception was represented by isolates belonging to haplotype N that, according to 16S rDNA analysis, were assigned to the species B. simplex. Interestingly, all of these isolates (22), representing more than 28% of the entire C2 + C4 community, were only found in C samples, suggesting that the amendment might have positively affected the growth of these isolates. Apparently, the increase in haplotype N frequency in May was parallel to the decrease in the presence of isolates belonging to ARDRA group E and, although at a lesser extent, to group A, whose isolates were assigned to the species B. firmus. 563 Statistical analysis of ARDRA data To give a statistical support to the ARDRA distribution, the AMOVA was carried out on ARDRA profiles. AMOVA data confirmed that most of the total molecular variance (p=0.001) was ascribed to divergence among strain-specific haplotypes (91.9%) and in minor part (8.1%) to the partition of soil types (Table 4). Partitioning the genetic variance among different groups, a percentage of variation of 6.9% was ascribed to divergence between group 1 without or with low organic C input (T, F, F+C) and group 2 with high organic inputs (C2, C4). The AMOVA of ARDRA haplotypes belonging to Bacillus genus indicated that the molecular variance among soils increased to 10.6%, and it was probably due to the divergence among soils (Table 4). Considering the groups 1 and 2 composed only by Bacillus spp., the divergence increased to 10.2%. B. firmus H haplotype, B. lentus M haplotype, and B. simplex species present in group 2 and absent in group 1 showed a high divergence value. RAPD fingerprinting and statistical analysis of RAPD data The degree of intraspecific genetic variability between strains belonging to four main ARDRA groups (A, E, N, and Q, containing 49, 22, 24, and 16 isolates, respectively) was analyzed by RAPD fingerprinting (Williams et al. 1990; Welsh and McClelland 1990) as described in “Materials and methods.” As expected the amplification patterns of strains belonging to different haplotypes were very different. In addition to this, a high degree of genetic diversity was found between isolates belonging to the same ARDRA haplotypes, and 15 RAPD profiles of haplotypes belonging to group A are shown in Fig. 4. The AMOVA performed on RAPD profiles of isolates belonging to ARDRA group A showed that the 91.9% of the total molecular variance was attributed to divergence among isolates and only 8.0% to soils. The AMOVA of groups 1 and 2 showed a low value (6.93%) of divergence. Discussion In this work, we have analyzed the effect of fumigant 1,3-D on the diversity and dynamics of soil heterotrophic aerobic culturable microbial communities. Although the plate counts usually estimate only 1–10% of the overall soil microflora, in our opinion, the integration of data concerning culturable microbial flora and soil parameters may help in understanding better the effect of fumigants on bacterial response to changes of environmental parameters. Nevertheless ratios between microbiological parameters have 564 Biol Fertil Soils (2008) 44:557–569 Fig. 1 Phylogenetic tree showing the relationships among the 16S rDNA sequences of the Bacillus isolates. Scale bars represent the Kimura 2-parameter distance. Bootstrap values are indicated at the node. The accession number of each sequence is also given often been used for evaluating the response of microbial activity to environmental factors (Anderson 2003). In this study, the responses of microbial quotient, qCO2, and qM to different fertilization treatments, observed during 3 months, seemed to be strongly affected by the nutritional status of the soil. It is known that nutrient uptake by microbial cells is an energetically expensive process, particularly when microbes are forced to degrade stable organic matter to get Biol Fertil Soils (2008) 44:557–569 565 30 25 Number of isolates 20 15 10 5 0 A B C D E F G H I J K L M N O P Q R S T U V Z ARDRA haplotype Fig. 2 Distribution of ARDRA haplotypes in May (white columns) and July (black columns) new available substrates. Furthermore, changes in nutrient availability can modify microbial maintenance energy requirements. This nutritional “stress” of fumigated soils could explain the fact that the percentage of organic C present as microbial biomass C (the microbial quotient) in May was lower than 2.0, which is considered a critical threshold for soil health (Anderson 2003). In May, the highest value of microbial quotient in F+C samples probably reflects a more efficient use of easily degradable substrates by microbial biomass (Anderson 2003; Pinzari et al. 1999). Data obtained in May showed no significant differences in chemical and microbiological properties between T and F samples, indicating that the fertigation alone had no significant short-time effects on tested soil properties and microbial activities. As expected, Corg is a stable parameter, and in May, its values only significantly changed in soils amended with high amounts of compost (C2 and C4). The F+C soils showed the lowest difference between the numbers of haplotypes from May to July, indicating the maintenance of the indigenous microbial diversity, although the relative frequency of each bacterial species changed. Nevertheless, it is known that, during organic matter mineralization, a succession of organisms occurs, and this suggests that different catabolic capabilities are sequentially required to complete the decomposition process. Most studies on succession have shown that highly active, zymogenous, and r-selected organisms dominate the beginning of decomposition, whereas autochthonous or K-selected, more energy-efficient organisms occur during later stages (Dilly et al. 2001). Thus, probably in F+C soils, indigenous rstrategists survived and increased their biomass in May by mineralizing readily available organic matter and using the added ammonium nitrate (Dilly 2005). However, the significant decrease in Cmic in July indicates that the effect of F+C treatment was just temporary, and it suggests a decline in organic matter quality and transformation intensity. Further investigations may provide more data and reveal fundamental ecological information about the nutritional physiology of the microbiota, their role in the mineralization of organic compounds, and their ecophysiological adjustment to environmental conditions. The highest values of potential mineralization (C0) and Cmic were observed in soils amended with different amount of compost (F+C, C2, and C4), probably because the amendment of soil with compost increased the amount of degradable organic matter, which may be the main variable of microbial physiological status; indeed, the qM in July indicates a stable metabolism in soils treated with compost while increased in T and F soils probably due to the depletion of the organic matter. Overall, bacterial counts were not related to their Cmic values, thus suggesting that the majority of microbial biomass is formed by uncultur- 566 Biol Fertil Soils (2008) 44:557–569 25 Number of isolates 20 15 10 5 0 A B C D E F G H I J K L M N O P Q R S T U V Z Haplotype Fig. 3 Number of strains belonging to the 21 ARDRA haplotypes in relation to soil treatment: T (black columns), F (light gray), F+C (white columns), C2/C4 (dark gray) able bacteria and/or by other soil microorganisms such as fungi or protozoa added with compost. The values of metabolic quotient were not significantly different among the different treatments in May; however, Table 4 AMOVA of 189 bacterial isolates from fumigated soils Source of variation df Sum of squares Variance components AMOVA of total ARDRA haplotypes Among soils 4 7.2 0.04 Within soils 184 76.3 0.41 Total 188 83.4 0.45 Among groups 1 3.9 0.03 Among soils 3 3.2 0.02 within groups Within soils 184 76.3 0.41 Total 188 83.4 0.46 AMOVA of Bacillus spp. ARDRA haplotypes Among soils 4 7.3 0.05 Va Within soils 152 58.5 0.38 Vb Total 156 65.8 0.43 Among groups 1 4.4 0.05 Va Among soils 3 2.9 0.02 Vb within groups Within soils 152 58.5 0.38 Vc Total 156 65.8 0.45 Percentage of variation 8.1 91.9 6.9 3.7 89.4 10.6 89.4 10.3 4.2 85.6 in July, C2 and C4 samples exhibited values significantly lower than those of T, F, and F+C samples. Increases in qCO2 could be induced by nutritional stresses as well as by the increase in the bacterial/fungal ratio (Landi et al. 2000); it may be possible that the metabolic quotient of T, F, and F+C soils might have been affected by the low values of organic matter in July. Furthermore, the increase in qCO2 value in F+C soils in July indicates a short-time effect of the treatment, and it could be due to the depletion of the organic C added as compost, as previously discussed. Both C2 and C4 treatments seem to select specific microbial species such as B. simplex, which represents almost the 40% of culturable bacteria isolated in May; this percentage decreased ten times in July, and B. firmus, which showed a low number in May, increased 4.5 times in July, reaching values similar to those of the control. In spite of fact that the qCO2 value decreased and the microbial quotient was high probably because mineralization of organic matter decreased under the stressed conditions in C2 and C4 samples, the bacterial structure of these samples in July was similar to that of low-fertilized soils. It is possible that the addition of high amounts of new organic matter as compost might have initially favored the growth of less-represented bacterial species such as B. simplex; afterwards, the microbial community recovered the preexisting equilibrium. However, we cannot a priori rule com- Biol Fertil Soils (2008) 44:557–569 Fig. 4 a Example of RAPD patterns of total DNA with primer AP12 from isolates of ARDRA haplotype A. b Cluster analysis based on UPGMA of RAPD profiles. Scale bar numbers indicate divergences among profiles 567 a A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 A15 b A6 A9 A8 A1 A5 A7 A12 A14 A3 A15 A10 A11 A4 A2 A13 pletely out the possibility that the addiction of compost might have introduced not detectable and/or less-represented microbial species (e.g., B. simplex), which resulted in an initially change in the composition of soil microflora. The AMOVA performed on ARDRA haplotypes belonging to Bacillus genus showed that the divergence between groups 1 (without or very low fertilization rate) and 2 (with high fertilization rate) was 10.2%, thus indicating a different distribution of Bacillus spp. strains among soils. On the basis of molecular content in G+C, phenotypic similarity, and 16S rDNA group, Priest (1993) subdivided 568 the genus Bacillus into five different groups. The phylogenetic tree reported in Fig. 1 revealed that a very high percentage of the Bacillus isolates (more than 94%) were placed within group 2, which is mostly composed by species which are facultative anaerobes, grow strongly in absence of oxygen, produce ellipsoidal endospores, and swell the mother cell (Priest 1993). In particular, B. firmus and related halotolerant bacteria such as B. lentus are particularly common in marine and estuarine habitats and salt marshes (Gordon and Hyde 1982; Gordon et al. 1977). Alkaliphilic bacilli are widespread in soils, being found in acidic soils but being more common in alkaline soils like the one analyzed in this work. Therefore, it is possible that the selective pressure induced by 1,3-D had strongly favored microorganisms resistant to the fumigant through the formation of spores. However, we cannot a priori exclude the possibility that a number of strains might have survived by degrading the fumigant agents. If this idea is correct, the RAPD analysis should have revealed a selection of particular strain(s). The findings of a high degree of genetic variability between strains belonging to the main ARDRA groups and the fact that this biodiversity was not influenced by the soil treatments as shown by AMOVA contradicts what was previously reported by Gan et al. (1998), that the fumigants select at the species rather than at the strain level. Thus, it is quite possible that the presence of a high percentage of Gram-positive bacteria in the fumigated soil, according to Ibekwe et al. (2001a), and in particular, the prevalence of the genus Bacillus might be related to the ability of these bacteria to form spores to protect themselves from the fumigants rather than to the presence of a set of genes involved in biodegradation of 1,3-D. In conclusion, the amendment of fumigated soils is a temporary solution to recover the loss of soil fertility by 1,3-D, which selects the bacterial community. However, further researches, such as analysis of the unculturable microflora, the analysis of composition of compost bacterial communities, and/or longer-term analysis of the effect of the compost addiction, are required to improve one of these treatments as a possible solution for recovering the fertility of the fumigated soils. Acknowledgment We are very grateful to two anonymous reviewers and to the Editor-in-chief for the revision of the manuscript and for their useful suggestions and comments in improving the manuscript. References Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucl Acids Res 25:3389–3402 Biol Fertil Soils (2008) 44:557–569 Anderson TH (2003) Microbial eco-physiological indicators to assess soil quality. Agric Ecosyst Environ 98:285–293 Anderson TH, Domsch KH (1990) Application of eco-physiological quotients (qCO2 and qD) on microbial biomass from soils of different cropping histories. Soil Biol Biochem 10:251–255 Baldwin JG, Nadler SA, Adams BJ (2004) Evolution of plant parasitism among nematodes. Annu Rev Phytopathol 42:83–105 Brookes PC (1995) The use of microbial parameters in monitoring soil pollution by heavy metals. Biol Fertil Soils 19:269–279 Burns RG, Nannipieri P, Benedetti A, Hopkins DW (2006) Defining soil quality. In: Bloem J, Hopkins DW, Benedetti A (eds) Microbiological methods for assessing soil quality. CABI publishing, pp 15–22 Dilly O (2005) Microbial energetics in soils. In: Buscot F, Varma A (eds) Microrganisms in soils: roles in genesis and functions. Springer, Berlin, pp 123–128 Dilly O, Munch JC (1998) Rations between estimates of microbial biomass content and microbial activity in soils. Biol Fertil Soils 27:374–379 Dilly O, Bartsch S, Rosenbrock P, Buscot F, Munch JC (2001) Shifts in physiological capabilities of the microbiota during the decomposition of leaf litter in a black alder (Alnus glutinosa (Gaertn.) L.) forest. Soil Biol Biochem 33:921–930 Doran JW, Parkin TB (1994) Defining and assessing soil quality. In: Doran JW, Coleman DC, Bezdicek DF, Stewart BA (eds) Defining soil quality for a sustainable environment. Soil Science Society of America, Madison, Wisconsin, pp 3–22 (Special Publication no.35 SSSA) Excoffier L, Smouse PE, Quattro M (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131:479–491 Gan J, Yates SR, Crowley D, Becker JO (1998) Acceleration of 1,3dichloropropene degrading by organic amendments and potential application for emission reduction. J Environ Qual 27:408–414 Giannakou IO, Sidiropoulos A, Prophetou-Athanasiadou D (2002) Chemical alternatives to methyl bromide for the control of rootknot nematodes in greenhouses. Pest Manag Sci 58:290–296 Gordon RE, Hyde JL (1982) The Bacillus firmus–Bacillus lentus complex and pH 7.0 variants of some alkalophilic strains. J Gen Microbiol 128:1109–1116 Gordon RE, Hyde JL, Moore JA Jr (1977) Bacillus firmus. –Bacillus lentus: a series or one species. Int J Syst Bacteriol 27:256–262 Grifoni A, Bazzicalupo M, Di Serio C, Fancelli S, Fani R (1995) Identification of Azospirillum strains by restriction fragment length polymorphism of the 16S rDNA and of the histidine operon. FEMS Microbiol Lett 127:85–91 Ibekwe AM, Papiernik SK, Gan J, Yates SR, Yang CH, Crowley DE (2001a) Impact of fumigants on soil microbial communities. Appl Environ Microbiol 67:3245–3257 Ibekwe AM, Papiernik SK, Gan J, Yates SR, Yang CH, Crowley DE (2001b) Microcosm enrichment of 1,3-dichloropropene-degrading soil microbial communities in a compost-amended soil. J App Microbiol 91:668–676 Isermeyer H (1952) Eine Einfache Methode sur Bestimmung der Bodenatmung und der Karbonate im Boden. Z Pflanzanernah Bodenk 56:6–38 Jenkinson DS, Ladd JN (1981) Microbial biomass in soil: measurements and turnover. In: Paul EA, Ladd JN (eds) Soil biochemistry, vol. 5. Marcel Dekker, New York, pp 415–471 Kimura M (1980) A simple method for estimating evolutionary rate of base substitutions through comparative studies of nucleotide sequences. J Mol Evol 16:11–120 Kumar S, Tamura K, Nei M (2004) MEGA3: integrated software for molecular evolutionary genetics analysis and sequence alignment. Brief Bioinf 5:150–163 Biol Fertil Soils (2008) 44:557–569 Landi L, Renella G, Moreno JL, Falchini L, Nannipieri P (2000) Influence of cadmium on the metabolic quotient, L-:D-glutamic acid respiration ration and enzyme activity: microbial biomass ratio under laboratory conditions. Biol Fertil Soils 32:8–16 Ministero delle Politiche Agricole e Forestali (1997) Metodi ufficiali di analisi fisica del suolo. Decreto Ministeriale 1° agosto 1997. In: Supplemento ordinario alla Gazzetta Ufficiale n°204 del 2 Settembre 1997 Ministero delle Politiche Agricole e Forestali (1999) Metodi ufficiali di analisi chimica del suolo. Decreto Ministeriale 13 settembre 1999. In: Supplemento ordinario alla Gazzetta Ufficiale n°248 del 21 Ottobre 1999 Mori E, Lio’ P, Daly S, Damiani G, Perito B, Fani R (1999) Molecular nature of RAPD markers amplified from Haemophilus influenzae rd genome. Res Microbiol 150:83–93 Nannipieri P, Grego S, Ceccanti B (1990) Ecological significance of the biological activity in soil. In: Bollag JM, Stotzky G (eds) Soil biochemistry, vol 6. Marcel Dekker, New York, pp 293–356 Ou LT, Chung KY, Thomas JE, Obreza TA, Dickson DW (1995) Degradation of 1,3-dichloropropene (1,3-D) in soils with different histories of field applications of 1,3-D. J Nematol 27:127– 242 Park MK, Kim JH, Dungan RS (2004) Sorption of the fumigant 1,3dichloropropene on soil. J Environ Sci Health B 39:603–612 Pinzari F, Trinchera A, Benedetti A, Sequi P (1999) Use of biochemical indices in the Mediterranean environment: comparison among soils under different forest vegetation. J Microbiol Meth 36:21–28 Prather MJ, McElroy MR, Wofsy SC (1984) Reduction in ozone at high concentrations of stratospheric halogens. Nature 31:227– 231 Priest FG (1993) Systematics and ecology of Bacillus. In: Hoch JA, Losick R (eds) Bacillus subtilis and other Gram-positive bacteria, systematics and ecology of Bacillus. American Society for Microbiology, Washington, DC, pp 3–16 Riffaldi R, Saviozzi A, Levi-Minzi R (1996) Carbon mineralization kinetics as influenced by soil properties. Biol Fertil Soil 22:293– 298 Saitou N, Nei M (1987) The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 4:406–425 569 Sakamoto K, Oba Y (1994) Effect of fungal to bacterial biomass ratio on the relationship between CO2 evolution and total soil microbial biomass. Biol Fertil Soil 17:39–44 Sanger F, Nicklesen S, Coulson AR (1977) DNA sequencing with chain terminating inhibitors. Proc Natl Acad Sci U S A 74:5463–5467 Schneider S, JM Kueffer, D Roessli, L Excoffier (1997) ARLEQUIN: a software for population genetics data analysis. Version 1.1, University of Geneva Smelt JH, Teunissen W, Crum SJH, Leistra M (1989) Accelerated transformation of 1,3-dichloropropene in loamy soils. Neth J Agric Sci 37:173–183 Springer U, Klee J (1954) Prüfung der Leistungsfähigkeit von einigen wichtigeren Verfahren zur Bestimmung des Kohlemstoffs mittels Chromschwefelsäure sowie Vorschlag einer neuen Schnellmethode. Z Pflanzenernähr Dang Bodenk 64:1 Thompson JD, Higgins DG, Gibson TJ (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucl Acids Res 22:4673– 4680 Vance ED, Brookes PC, Jenkinson DS (1987) An extraction method for measuring soil microbial biomass C. Soil Biol Biochem 19:703–707 Vaneechoutte M, Rossau R, De Vos P, Gillis M, Janssens D, Paepe N (1992) Rapid. identification of the bacteria of the Comamonadaceae with amplified ribosomal DNA-restriction analysis (ARDRA). FEMS Microbiol Lett 93:227–234 Vaneechoutte M, De Beenhouwer H, Claeys G, Verschraegen GM, De Rouck A, Paepe N (1993) Identification. of Mycobacterium species with amplified rDNA restriction analysis. J Clin Microbiol 31:2061–2065 Vaneechoutte M, Dijkshoorn L, Tjernberg A, Eilachouni A, De Vos P, Claeys G, Verschraegen G (1995) Identification. of Acinetobacter genomic species by amplified ribosomal DNA restriction analysis. J Clin Microbiol 33:11–15 Welsh J, McClelland M (1990) Fingerprinting genomes using PCR with arbitrary primers. Nucl Acids Res 18:7213–7218 Williams JGK, Kubelik AR, Livak KJ, Rafalski JA, Tingey SV (1990) DNA polymorphisms amplified by arbitrary primers are useful as genetic markers. Nucl Acids Res 18:6531–6535