Long-term field release of bioluminescent Sinorhizobium meliloti strains to assess the influence of a recA mutation on the strains' survival.

A field release experiment was carried out to study the fate of the isogenic, firefly luciferase (luc) gene-tagged Sinorhizobium meliloti strains L1 (RecA-) and L33 (RecA+) in the environment. Both strains were released at concentrations of approximately 10(6) cfu g(-1) soil in replicate and randomized field plots, which had been sown with alfalfa (Medicago sativa). The survival of both strains during the following 7 years could be subdivided into three phases: a sharp decline for more than two orders of magnitude within the first 4 months (phase I), followed by fluctuations around an average number of 10(4) cfu g(-1) soil for nearly 4 years (phase II), and a further decline to approximately 60 cfu g(-1) (phase III). At most sampling dates, no significant differences in the survival of both strains were detected, indicating that the recA gene function was dispensable under these environmental conditions. During the field inoculation, both strains were dispersed accidentally by wind in small numbers to noninoculated field plots. Strain L33 established at a concentration of more than 10(3) cfu g(-1) soil with subsequent seasonal fluctuations. Although strain L1 must have been disseminated to a similar extent, it could never be recovered from noninoculated field plots, indicating that the recA mutation interfered with the strain's capability to establish there. At the beginning of the field experiment, an indigenous alfalfa-nodulating population was below the limit of detection. In the following years, however, an indigenous population arose, which finally outcompeted both strains for saprophytic growth and alfalfa nodulation. RecA- strain L1 was outcompeted for alfalfa nodulation slightly faster than its RecA+ counterpart L33. The diversity of the indigenous population was characterized by employing the Enterobacterial Repetitive Intergenic Consensus polymerase chain reaction fingerprint method. Typing of 2731 root nodule isolates revealed a total of 38 fingerprint groups. More than 80% of the isolates could be grouped into six dominant fingerprint groups, indicating that a few dominant bacterial strain types had outcompeted the released strains.

Effect of primers hybridizing to different evolutionarily conserved regions of the small-subunit rRNA gene in PCR-based microbial community analyses and genetic profiling.

Genetic profiling techniques of microbial communities based on PCR-amplified signature genes, such as denaturing gradient gel electrophoresis or single-strand-conformation polymorphism (SSCP) analysis, are normally done with PCR products of less than 500-bp. The most common target for diversity analysis, the small-subunit rRNA genes, however, are larger, and thus, only partial sequences can be analyzed. Here, we compared the results obtained by PCR targeting different variable (V) regions (V2 and V3, V4 and V5, and V6 to V8) of the bacterial 16S rRNA gene with primers hybridizing to evolutionarily conserved flanking regions. SSCP analysis of single-stranded PCR products generated from 13 different bacterial species showed fewer bands with products containing V4-V5 (average, 1.7 bands per organism) than with V2-V3 (2.2 bands) and V6-V8 (2.3 bands). We found that the additional bands (>1 per organism) were caused by intraspecies operon heterogeneities or by more than one conformation of the same sequence. Community profiles, generated by PCR-SSCP from bacterial-cell consortia extracted from rhizospheres of field-grown maize (Zea mays), were analyzed by cloning and sequencing of the dominant bands. A total of 48 sequences could be attributed to 34 different strains from 10 taxonomical groups. Independent of the primer pairs, we found proteobacteria (alpha, beta, and gamma subgroups) and members of the genus Paenibacillus (low G+C gram-positive) to be the dominant organisms. Other groups, however, were only detected with single primer pairs. This study gives an example of how much the selection of different variable regions combined with different specificities of the flanking "universal" primers can affect a PCR-based microbial community analysis.

Effect of field inoculation with Sinorhizobium meliloti L33 on the composition of bacterial communities in rhizospheres of a target plant (Medicago sativa) and a non-target plant (Chenopodium album)-linking of 16S rRNA gene-based single-strand conformation polymorphism community profiles to the diversity of cultivated bacteria.

Fourteen weeks after field release of luciferase gene-tagged Sinorhizobium meliloti L33 in field plots seeded with Medicago sativa, we found that the inoculant also occurred in bulk soil from noninoculated control plots. In rhizospheres of M. sativa plants, S. meliloti L33 could be detected in noninoculated plots 12 weeks after inoculation, indicating that growth in the rhizosphere preceded spread into bulk soil. To determine whether inoculation affected bacterial diversity, 1,119 bacteria were isolated from the rhizospheres of M. sativa and Chenopodium album, which was the dominant weed in the field plots. Amplified ribosomal DNA restriction analysis (ARDRA) revealed plant-specific fragment size frequencies. Dominant ARDRA groups were identified by 16S rRNA gene nucleotide sequencing. Database comparisons indicated that the rhizospheres contained members of the Proteobacteria (alpha, beta, and gamma subgroups), members of the Cytophaga-Flavobacterium group, and gram-positive bacteria with high G+C DNA contents. The levels of many groups were affected by the plant species and, in the case of M. sativa, by inoculation. The most abundant isolates were related to Variovorax sp., Arthrobacter ramosus, and Acinetobacter calcoaceticus. In the rhizosphere of M. sativa, inoculation reduced the numbers of cells of A. calcoaceticus and members of the genus Pseudomonas and increased the number of rhizobia. Cultivation-independent PCR-single-strand conformation polymorphism (SSCP) profiles of a 16S rRNA gene region confirmed the existence of plant-specific rhizosphere communities and the effect of the inoculant. All dominant ARDRA groups except Variovorax species could be detected. On the other hand, the SSCP profiles revealed products which could not be assigned to the dominant cultured isolates, indicating that the bacterial diversity was greater than the diversity suggested by cultivation.

Succession of microbial communities during hot composting as detected by PCR-single-strand-conformation polymorphism-based genetic profiles of small-subunit rRNA genes.

A cultivation-independent technique for genetic profiling of PCR-amplified small-subunit rRNA genes (SSU rDNA) was chosen to characterize the diversity and succession of microbial communities during composting of an organic agricultural substrate. PCR amplifications were performed with DNA directly extracted from compost samples and with primers targeting either (i) the V4-V5 region of eubacterial 16S rRNA genes, (ii) the V3 region in the 16S rRNA genes of actinomycetes, or (iii) the V8-V9 region of fungal 18S rRNA genes. Homologous PCR products were converted to single-stranded DNA molecules by exonuclease digestion and were subsequently electrophoretically separated by their single-strand-conformation polymorphism (SSCP). Genetic profiles obtained by this technique showed a succession and increasing diversity of microbial populations with all primers. A total of 19 single products were isolated from the profiles by PCR reamplification and cloning. DNA sequencing of these molecular isolates showed similarities in the range of 92.3 to 100% to known gram-positive bacteria with a low or high G+C DNA content and to the SSU rDNA of gamma-Proteobacteria. The amplified 18S rRNA gene sequences were related to the respective gene regions of Candida krusei and Candida tropicalis. Specific molecular isolates could be attributed to different composting stages. The diversity of cultivated bacteria isolated from samples taken at the end of the composting process was low. A total of 290 isolates were related to only 6 different species. Two or three of these species were also detectable in the SSCP community profiles. Our study indicates that community SSCP profiles can be highly useful for the monitoring of bacterial diversity and community successions in a biotechnologically relevant process.

A new approach to utilize PCR-single-strand-conformation polymorphism for 16S rRNA gene-based microbial community analysis.

Single-strand-conformation polymorphism (SSCP) of DNA, a method widely used in mutation analysis, was adapted to the analysis and differentiation of cultivated pure-culture soil microorganisms and noncultivated rhizosphere microbial communities. A fragment (approximately 400 bp) of the bacterial 16S rRNA gene (V-4 and V-5 regions) was amplified by PCR with universal primers, with one primer phosphorylated at the 5' end. The phosphorylated strands of the PCR products were selectively digested with lambda exonuclease, and the remaining strands were separated by electrophoresis with an MDE polyacrylamide gel, a matrix specifically optimized for SSCP purposes. By this means, reannealing and heteroduplex formation of DNA strands during electrophoresis could be excluded, and the number of bands per organism was reduced. PCR products from 10 of 11 different bacterial type strains tested could be differentiated from each other. With template mixtures consisting of pure-culture DNAs from 5 and 10 bacterial strains, most of the single strains could be detected from such model communities after PCR and SSCP analyses. Purified bands amplified from pure cultures and model communities extracted from gels could be reamplified by PCR, but by this process, additional products were also generated, as detected by further SSCP analysis. Profiles generated with DNAs of rhizosphere bacterial communities, directly extracted from two different plant species grown in the same field site, could be clearly distinguished. This study demonstrates the potential of the selected PCR-single-stranded DNA approach for microbial community analysis.