Previous Article | Next Article ![]()
Applied and Environmental Microbiology, May 2006, p. 3578-3585, Vol. 72, No. 5
0099-2240/06/$08.00+0 doi:10.1128/AEM.72.5.3578-3585.2006
Copyright © 2006, American Society for Microbiology. All Rights Reserved.
CEMAGREF, Environmental Management and Biological Treatment of Wastes Research Unit, 17 Avenue de Cucillé, CS 64427, 35044 Rennes cedex, France,1 UMR INRA/ENVT 1225 Interactions Hôtes, Agents pathogènes, Ecole nationale vétérinaire de Toulouse, 23, chemin des Capelles, 31076 Toulouse cedex, France,2 Université d'Angers, UMR MA 105 Paysages et Biodiversité, UFR Sciences, 2, Boulevard Lavoisier, 49045 Angers cedex 01, France,3 INRA, Laboratoire de Biotechnologie de l'Environnement, Avenue des Etangs, 11100 Narbonne, France4
Received 17 August 2005/ Accepted 28 February 2006
|
|
|---|
|
|
|---|
The pig slurry microbial community, which was previously characterized by cultural methods (15, 16, 38), has recently been characterized by molecular techniques (37, 43). Of the 109 to 1010 cells per ml present in pig slurry, only 10 to 20% could be cultured on various media based on pig slurry (8, 33). Moreover, less than 50% of the phylotypes observed in pig slurry by 16S rRNA gene analysis were closely related to known microorganisms (37, 43). Nevertheless, based on both cultural and molecular approaches, the pig slurry microbial community appears to be an anaerobic digestion ecosystem that is dominated by groups of fermentative bacteria, such as the Eubacterium-Clostridium (EC) and Lactobacillus-Streptococcus groups of low-G+C-content gram-positive bacteria and the Bacteroides group of gram-negative bacteria. The members of the domain Archaea are dominated by hydrogenotrophic methanogens, as well as by a group of uncultured Archaea whose function is unknown.
Despite the increasing interest now being paid to characterization of pig slurry microbiology (48), few workers have tried to evaluate the impact of pig slurry storage conditions on the composition of the slurry microbial community (2, 26, 27, 33, 49). In most of the studies the researchers used cultural methods and focused on the fate of pathogenic or fecal indicators (26, 27). These studies have shown that the numbers of fecal indicators and pathogenic bacteria decrease rapidly and exponentially with time during pig slurry storage. In contrast, analyses of the whole microbial community by cultural (2, 33) and molecular techniques (20) have suggested that a more static view is possible and that the dominant microbial groups are relatively stable. A more systematic analysis of the pig slurry microbial community dynamics in pig-rearing structures should contribute to our understanding of metabolic transformations which occur during slurry storage. The aim of this work was to monitor the dynamics of a pig slurry microbial community throughout an intensive production installation in order to evaluate the impact of each waste management unit on the pig slurry microbial community. Dominant bacterial and archaeal communities were monitored by 16S rRNA gene-targeted PCR amplification and single-strand conformation polymorphism (SSCP) analysis (18, 28, 36, 50). Fecal indicators (enterococci and Escherichia coli) were monitored by using cultural methods. The most prominent microbial populations observed by PCR-SSCP analysis were identified by DNA sequence analysis.
|
|
|---|
A total of 28 samples were taken at the different stages of the pig slurry accumulation and handling process. Slurry samples were collected at different locations within the indoor pits with a sampling cane and then mixed together. Samples from the outdoor storage tank were taken every 2 or 3 weeks after 1 h of homogenization, starting with the initial filling in December 2002. The pond was sampled four times during refilling in March 2003. Soil sampling was carried out 15 days before and immediately before pig slurry spreading. Samples were also taken just after spreading and during a subsequent 2-month period. At each sampling time, nine core samples from a depth of 0 to 15 cm were obtained with a drill and thoroughly mixed. After mixing, a subsample consisting of about 1 kg of soil was collected. All samples were brought to the laboratory within 12 h.
Physicochemical characterization of pig slurry samples.
pH was determined by direct measurement with a glass electrode pH meter. Total ammonia nitrogen and total Kjeldahl nitrogen were analyzed by steam distillation coupled with a titration unit. For total nitrogen, prior mineralization at 350°C was required to reduce all nitrogen forms to ammonium. The dry matter was analyzed by drying samples at 105°C until the weight was constant. The volatile fatty acid content was analyzed by high-performance liquid chromatography (29).
Enumeration of classical fecal indicators by cultural techniques.
Enumeration was performed by using 25 g of solid samples or, for liquid samples, a 25-ml pellet obtained by centrifugation at 8,000 rpm for 12 min of 500 ml of pig slurry. Samples were homogenized in a stomacher bag with 225 ml of tryptone-salt solution for 10 min. Plate counts of enterococci were determined by using kanamycin esculin azide agar base (Oxoid) that was incubated at 37°C for 24 h. E. coli counts were determined using Select E. coli Count Plate Petrifilm (3 M) that was incubated at 44°C for 24 h. The data were expressed as numbers of CFU per gram (dry weight). Means of unadjusted variables were compared using Student's t test.
DNA extraction.
Liquid pig slurry samples (10 ml) were centrifuged for 10 min at 17,500 x g. Each pellet was homogenized in a mortar containing 4 ml of 4 M guanidine thiocyanate-0.1 M Tris-HCl (pH 7.5) and 0.6 ml of 10% N-lauroyl sarcosine. Fresh soil samples were sieved using a 0.04-cm2 mesh. Ten-gram aliquots were crushed in a mortar in the same way with 8 ml of guanidine thiocyanate and 1.2 ml of N-lauroyl sarcosine. Four 0.5-ml aliquots were transferred into microtubes and immediately stored at 20°C. Nucleic acids were extracted as described previously (13) except for the soil samples, to which 0.2 ml of aluminum ammonium bisulfate [AlNH4(SO4)2] was added at the beginning of the extraction procedure in order to eliminate most PCR inhibitors (3).
Direct and nested PCR-SSCP analysis of microbial 16S rRNA genes.
The pig slurry bacterial and archaeal communities were analyzed by PCR amplification of the 16S rRNA gene V3 region using the W49-W104 and W96-W104 primer pairs, respectively (Table 1), and Pfu Turbo DNA polymerase (Stratagene) as described by Chachkhiani et al. (6). Twenty-five cycles of amplification were performed with a GeneAmp 9700 thermocycler (PE Applied Biosystems). The resulting PCR products were then separated by SSCP capillary electrophoresis with an ABI 310 genetic analyzer (Applied Biosystems) as described by Delbes et al. (10).
|
View this table: [in a new window] |
TABLE 1. Sequences and target positions of the primers used in this study
|
Clone library, sequencing, and identification of dominant 16S rRNA gene fragments.
The dominant peaks in the SSCP profiles for pig slurry samples collected from the storage tank on day 21 were identified. For the Archaea, the 16S rRNA gene V3 region was amplified from total DNA using the redTaq DNA polymerase (Sigma, France) and the archaeal W96-W31 primer pair (Table 1). For each targeted microbial group (BSL, BP, and EC groups), the AccuPrime Taq polymerase PCR products obtained as described above were amplified again using bacterial primers W49 and W31 (Table 1). These amplifications generated the same DNA fragments that the amplifications performed for the SSCP analysis generated, except that, since the W31 primer was not labeled, the DNA fragments could be cloned into E. coli using a TOPO-TA vector cloning kit (Invitrogen) to generate 16S rRNA gene V3 libraries. Then about 40 clones from each library (45 clones for the BSL library, 42 clones for the BP library, 52 clones for the EC library, and 40 clones for the Archaea library) were randomly picked, and their inserts were screened by PCR-SSCP analysis as described previously (6). Inserts that comigrated with distinguishable peaks from the total DNA SSCP profile were sequenced to finalize the identification of peaks. DNA sequences were obtained using a dye terminator cycle sequencing Ready Reaction kit (Big Dye Terminator; Applied Biosystems) and a 373A Genetic Analyzer from Applied Biosystems. DNA sequences were identified by comparison with their closest relatives available in databases using BLAST from the National Center for Biotechnology Information and the Ribosomal Database Project (1, 23) and by fitting the sequences into preexisting trees using the parsimony interactive tool from the ARB software package (22).
Nucleotide sequence accession numbers.
Sequences have been deposited in the EMBL database under accession numbers AM229418 to AM229448.
|
|
|---|
Bacterial 16S rRNA gene dynamics in pig slurry.
The population dynamics of the pig slurry microbial community throughout the pig-rearing system were determined by 16S rRNA gene-targeted PCR-SSCP analysis.
The SSCP profiles obtained for fresh slurry samples (less than 2 weeks of storage) collected from the indoor pit at three different times had 15 to 20 distinguishable peaks that clearly emerged from the background of subdominant bacterial diversity (Fig. 1) (21). The presence of several comigrating peaks in the profiles suggests that there were microbial populations that were present in all samples.
![]() View larger version (17K): [in a new window] |
FIG. 1. Comparison of bacterial 16S rRNA gene-targeted PCR-SSCP profiles for fresh pig slurry (less than 2 weeks old) collected from the fattening building pit at three different times. SSCP electrophoresis was performed from right to left. The horizontal and vertical axes indicate time (number of scans) and detection of fluorescently labeled PCR products, respectively. The SSCP profiles for each sample are aligned for comparison. Peaks that comigrated in all profiles are indicated by solid arrowheads, while peaks 13, 16, 18, and 19, which comigrated in only two profiles, are indicated by open arrowheads. Peaks that were present in only one profile are not labeled.
|
![]() View larger version (10K): [in a new window] |
FIG. 2. Modification of SSCP profiles for the bacterial pig slurry community with time in the storage tank and at the time of spreading onto the field. SSCP profiles obtained for pig slurry collected at different times in the storage tank and at the time of spreading in the pond and onto the soil are aligned for comparison. Peaks present in Fig. 1 are indicated by arrowheads, and the same numbers are used.
|
Finally, alignment of the pond SSCP profile with soil SSCP profiles obtained both just before and after spreading of the liquid from the pond showed that none of the dominant peaks observed in the pond profile could be detected in soil after spreading. This remained true for soil samples collected 3, 7, 15, 28, 49, and 77 days after spreading (data not shown).
Monitoring of bacterial subgroups.
The data presented above suggest that the bacterial community was stable throughout the pig slurry storage system. However, the use of general bacterial primers, the great diversity observed, and the presence of a very dominant peak (peak 3 in this study) may hide the variation of less dominant microbial groups (11). In order to better visualize the data, a nested PCR approach was used to artificially divide the bacterial SSCP profile. A set of primers targeting the Eubacterium-Clostridium, Bacillus-Streptococcus-Lactobacillus, and Bacteroides-Prevotella groups was used in combination with a general bacterial primer. According to data published previously (19, 31, 37, 43), these primers target more than 80% of the phylotypes observed in pig feces and pig slurry.
Figure 3 shows an alignment of the SSCP profiles obtained for the same pig slurry sample for the bacterial community and for each targeted group. Each specific microbial group profile presents an individualized window of electrophoretic mobility in agreement with the expected size of its 16S rRNA V3 region that is centered around 179, 199, and 204 nucleotides for the EC, BP, and BSL groups, respectively. Use of this group-specific approach revealed diversity that was not detectable in the bacterial profiles. Nevertheless, several dominant peaks for each group comigrated with dominant or distinguishable peaks in the total Bacteria profile (Fig. 3). Thus, the very dominant peak 3 of the bacterial profile comigrated perfectly with the dominant peak of the EC profile.
![]() View larger version (7K): [in a new window] |
FIG. 3. Comparison of the bacterial SSCP profile with profiles obtained after nested PCR-SSCP targeting the Clostridiaceae (EC group), the BP group, and the BSL group. Amplification was performed with storage tank pig slurry samples obtained on day 21. The peak numbers are the same as the numbers in Fig. 1 and 2. Peaks that comigrated in the bacterial profile and group profiles are indicated by solid arrowheads for the EC group, by striped arrowheads for the BP group, and by open arrowheads for the BSL group. Peaks that could be identified are designated cl1 to cl4, bp1, and bsl1 to bsl3, as shown in Table 3.
|
Identification of the persistent bacterial populations.
We attempted to identify the dominant peaks observed for each microbial group by cloning and sequencing the corresponding 16S rRNA gene fragments, as described in Materials and Methods. Most of the dominant peaks in the EC and BSL profiles could be identified, while only the dominant peak in the BP profile was assigned (Fig. 3). The phylogenetic affiliations are shown in Table 2. The closest relatives of five of the eight sequences identified were sequences from uncultured bacteria that were obtained either from pig gastrointestinal tracts (peaks cl3 and bp1) (19), from a bioreactor treating piggery waste (peaks cl1 and cl2) (unpublished data), or from a pig slurry storage pit (peak cl4) (43).
|
View this table: [in a new window] |
TABLE 2. Phylogenetic affiliations of 16S rRNA gene sequences
|
![]() View larger version (9K): [in a new window] |
FIG. 4. Archaea pig slurry community dynamics during the pig slurry management process. The SSCP profiles for pig slurry samples collected at different times in the storage tank and in the pond are aligned for comparison. Peaks that dominated the profile at the beginning of pig slurry storage are indicated by solid arrowheads to facilitate comparison of the profiles. Peaks that appeared during storage are indicated by open arrowheads.
|
Fecal indicator dynamics in pig slurry.
In order to obtain more insight into the behavior of the pig fecal microbial community, enterococci and E. coli were enumerated by cultural techniques during the pig slurry management process (Table 3). The concentrations of these microorganisms during the 6 months of storage were not significantly different for the building pit and the anaerobic storage tank, whereas the numbers of both fecal indicators in the pond decreased significantly (P < 0.05). In the soil there was no difference between samples collected before spreading and samples collected after spreading.
|
View this table: [in a new window] |
TABLE 3. Average concentrations and ranges of concentrations of fecal indicators in the pig slurry management process
|
|
|
|---|
When molecular monitoring of the microbial community was used, very good reproducibility was observed for the SSCP profiles obtained from samples collected from the different matrices (pig slurry, pond, and soil) and at different times during the experiment over several months (Fig. 2). This can be explained by technical factors such as (i) the homogenization of the samples, (ii) the reproducibility of the sampling, (iii) the DNA extraction method used, and (iv) the use of capillary electrophoresis and automated DNA band detection, but also by the fact that the PCR-SSCP profiles revealed only the most dominant populations in the microbial community (the populations that were least prone to sampling bias). However, two limitations were clear when general bacterial primers were used (Fig. 2). The first limitation was the reduction in the apparent diversity of the profile in the presence of a very dominant population. The second limitation was the very peculiar shape of the SSCP soil profiles, which may be explained both by the high bacterial diversity present in the soil and by the absence of any very dominant microbial group (21). These two limitations could be partially overcome by the use of a nested PCR-SSCP approach. Focusing on specific microbial groups permitted visualization of subdominant populations that were not clearly visible in the total bacterial profile and allowed easier peak identification (Fig. 3). Each microbial group had a specific window of electrophoretic migration, confirming that SSCP electrophoresis separates single-stranded DNA fragments first according to size and second according to the secondary structure (18). The absence of detection of the spread microorganisms in soil, by both molecular and cultural techniques, was in all likelihood due to the high dilution rate for manure in soil because of the spreading itself and the concomitant dilution of the manure microorganisms in the soil microbial community. With slurry spread at a level of 170 kg hectare1 of organic N and a density of 109 bacteria ml1 of slurry, the number of microorganisms spread on the soil was about 1012 cells m2. If we assume that the density of microorganisms in soil is about 1010 bacteria g1 (39) and the apparent density of soil is 1.5 kg liter1, the bacteria added with the slurry represented about 0.1% of the soil microflora. This value is too low to be detected by the techniques used in this study.
From a manure management perspective, SSCP monitoring of the dominant microbial populations showed that the pig slurry microbial community changed primarily during the first 2 to 3 weeks of anaerobic storage and then after the slurry was transferred to the pond. In contrast, the community remained very stable during passive anaerobic storage in both units. Cultural enumeration of fecal indicators revealed the same trend. The only significant decrease occurred between the storage tank and the pond. This stability of fecal indicator concentrations observed during pig slurry anaerobic storage contrasts with the decrease previously reported in batch studies (26, 27, 33). The difference may have been due to the constant addition of fresh feces to the slurry in real systems, which may logically lead to stabilization of the number of fecal indicators. Indeed, passive conditions that prevail in anaerobic storage tanks may not foster rapid change in the microbial community. According to this hypothesis, important microbial changes were observed in this study when the community was moved from the feces to the manure and then from the storage tank to the pond. Previous studies have demonstrated the stronger effects of drastic conditions like aeration or thermophilic treatment for modifying the pig slurry microbial community (17, 20, 26, 27).
Both methods showed that several microbial populations remained present and dominant from rearing until the time of spreading. The fecal origin of the persistent microorganisms visualized by the SSCP profiles was confirmed by identification of the organisms. The eight bacterial SSCP peaks identified were closely related to microorganisms present in manure or feces (Table 3). Strongly dominant peak cl1 observed in stored pig slurry was identified as Clostridium disporicum (Y18176) and exhibited 99% sequence similarity for a 141-bp fragment. Although identification of microorganisms by using such a short sequence must be used carefully (35), it is interesting that this microorganism has been observed previously in a thermophilic aerobic digestor treating pig slurry (J. W. Lee, S. Y. Lee, and Y. K. Park, unpublished data) and as a persistent population in pig slurry after 7 weeks of aerated or unaerated storage (20). This group of Clostridium may be especially resistant to environmental changes.
The apparent stability of the pig slurry microbial community was tempered by the slow dynamics and increasing diversity observed for the archaeal community. Archaeal SSCP profiles showed that subdominant populations slowly adapted to their new environments in the storage tank and pond. All the peaks identified correspond to cultured H2/CO2 and/or formate-utilizing methanogens, but several subdominant peaks were not identified (Table 3). M. ruminantium, which was dominant in the community at the beginning of the storage stage, was replaced by M. smithii in the pond. Both of these species are commonly isolated from human or animal feces; however, the former requires more growth factors, including acetate (12). Differences between the concentration of organic matter (especially acetate) in the pig slurry in the storage tank and the concentration in the pond may explain this microbial shift. Peak c, which persisted until the end of storage, belongs to a group of microorganisms comprising M. organophilum, Methanogenium frigidum, and uncultured microorganisms observed in Antarctic sediment (32). The persistence of these archaeal groups is consistent with the methane production observed during pig slurry anaerobic storage (5 to 70 g C-CH4 · m3 · day1) (24). No acetotrophic methanogen was identified, despite the high acetate concentration in pig slurry. This absence has been noticed in two previous analyses of other pig slurry ecosystems (37, 44). However, we cannot rule out the possibility that such organisms were represented here by one of the subdominant unidentified peaks that appeared during the experiment.
The persistence of fecal microorganisms in human and animal organic wastes raises questions for all intensive manure management processes. This study showed that 16S rRNA gene-targeted molecular techniques can be used to detect microorganisms discharged into the environment by such processes. Further work should be done to identify these microorganisms and to determine their activity and quantity in effluent. For microorganisms that have not been cultured yet, this requires the use of quantitative molecular tools, such as real-time PCR (34).
We thank G. Meynaud, ASAMIP (Castanet Tolosan Cedex, France), who carried out the sampling, and Théodore Bouchez (CEMAGREF, Antony, France) for helpful reading of the manuscript.
|
|
|---|
This article has been cited by other articles:
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Copyright © 2009 by the American Society for Microbiology. For an alternate route to Journals.ASM.org, visit: http://intl-journals.asm.org | More Info»