Comparison of microbial communities in four different composting processes as evaluated by denaturing gradient gel electrophoresis analysis

Authors


K. Ishii, Max-Planck-Institute for Marine Microbiology, Celsiusstrasse 1, 28359 Bremen, Germany (e-mail: kishii@mpi-bremen.de).

Abstract

Aims: We aimed to systematically understand the composting processes by a comparison of microbial communities during four full-scale composting processes.

Methods and Results: Microbial communities during the four different full-scale composting processes were analysed by denaturing gradient gel electrophoresis combined with measurement of physicochemical parameters. Two composting processes utilized sewage sludge and two utilized food-waste. Comparison of the four processes indicated that the concentration of dissolved organic carbon was higher in the food-waste-composting than in the sewage-sludge-composting processes, and microbial communities varied with composting substrate. The tendency for different microbes to appear in the composting process with different concentrations of dissolved organic carbon agreed with a previous study that showed that microbial succession occurred with a decrease in dissolved organic carbon in a laboratory-scale food-waste-composting process.

Conclusions: Our results suggested that the main factor affecting microbial communities in the composting process is the concentration of dissolved organic materials.

Significance and Impact of the Study: In addition to studying microbial communities involved in composting, this research is also the first to study composting mechanisms using molecular methods. The results of our studies may be helpful in the design and management of composting processes.

Introduction

Composting is a microbial decomposition process in which easily degradable and putrescent organic waste is turned into a stable material, compost (e.g. Gray et al. 1971). This process of treating organic waste has useful benefits such as improved sanitation, production of a reuseable product, less load on the ecosystem, and is an effective means of degradation for organic waste containing hazardous compounds. In order to effectively manage composting processes, the effects of various composting conditions have been investigated (e.g. Larsen and McCartney 2000). However, the results of various studies sometimes disagree with each other. For example, Wong and Fang (2000) found that increasing the pH by the addition of lime slightly improved the microbial activity in a bench-scale composting facility to treat sewage sludge, whereas Lei and VanderGheynst (2000) showed no effect of pH on O2 consumption in a 30 l static bed reactor of grape pomace and rice straw composting. The reason for the disagreement might be the various composting conditions such as raw material selection (often a mixture of organic solid waste), facility-scale, aeration rate, pH, C/N ratio, temperature, and moisture content. Consequently, these complex conditions often cause confusion in procedures to effectively manage the composting process. A systematic understanding of the composting mechanism is therefore required.

A current method for understanding the composting mechanism is the investigation of microbial communities in composting ecosystems. Microbes play key roles in these ecosystems and knowledge of microbial communities may suggest common composting mechanisms. Although there have been studies on composting micro-organisms using culture methods (see review by Miller 1996), the overall trend of these studies has been restricted to isolation of population subsets of interest to individual investigators (Miller 1996). Due to the inherent selectivity of culture media during isolation studies, there is a possibility that numerous organisms exist in composting ecosystems that have never been studied to date.

Although there have been many studies of small-scale composting systems, it is unknown to what extent the results obtained in laboratory-scale facilities can be applied to actual full-scale facilities. To our knowledge, there have been only two investigations comparing full-, pilot- or bench-scale composting processes, and the results agree as to the slower progress in full-scale facilities than in small-scale ones (Godden et al. 1983; Herrmann and Shann 1993). On the contrary, Miner et al. (2001) indicated that a critical material volume of more than 0·18 m3 m−1 was required to achieve temperatures of a windrow compost >43°C. As composting involves a variety of conditions, further research on full-scale composting processes is required to obtain systematic information on factors affecting microbial communities. However, there have been few investigations on the effects of composting parameters in a full-scale facility because large-scale facilities have managed to operate under different conditions. It is thus difficult to compare microbial communities using culture techniques in such composting facilities.

Recently, denaturing gradient gel electrophoresis (DGGE) analysis of PCR-amplified small subunit rRNA genes has been applied to microbial ecology to analyse microbial communities in various environments (Muyzer et al. 1993). In a previous study (Ishii et al. 2000), we used DGGE analysis to investigate microbial succession during a laboratory-scale food-waste-composting process. The result showed a dynamic succession from simple fermenting bacterial populations to a complex one, and that DGGE was suited to investigation for composting microbes that are relatively simpler communities than those of natural sediments or activated sludge.

In the present study, microbial communities in four full-scale composting processes were analysed by DGGE, and compared with each other to systematically understand the composting processes. We discussed the factors affecting microbial communities during composting processes. In addition, the microbial succession in the laboratory-scale food-waste-composting process in the previous study (Ishii et al. 2000) was also compared to the present results to obtain a unified base for the composting process.

Materials and methods

Composting samples

Each composting sample, approximately 1 kg, was taken from four full-scale composting facilities (A–D). The raw material of facility A was dehydrated sewage sludge mixed with sawdust (Table 1). The treatment was carried out for a few days in an Earp–Thomas system, followed by a windrow method for 60 days. In the Earp–Thomas system, raw materials are thrown onto the top floor and then gradually brought down with mixing and aeration. The samples were taken from the surfaces of 3-, 30- and 60-day-old windrows on the same day. The raw material of facility B was dehydrated sewage sludge mixed with woodchip (Table 1). The system of facility B was a modified Earp–Thomas system consisting of five floors in which material was mixed by a paddle on each floor with high efficiency. It took 10 days to finish the composting. The samples were taken on the same day from the inner part through the door attached to each floor. The raw material, dehydrated sludge without woodchip, could be obtained only in this system. The raw material of facility C was a mixture of food-waste from food shops, sawdust and pig manure (mainly food-waste). In facility C, the windrow system was carried out for approximately 9 weeks. The samples were taken from the surface of 7-, 21-, 49-, 56- and 63-day-old windrows on the same day. The raw material of facility D was only food-waste from restaurants. The system of facility D was a bin with scoop mixing for 43 days. The samples were taken from the central surface of composting materials aged for 2, 5, 9, 12, 16, 19, 23, 30, 37 and 44 days after the start. The temperature at each composting process was measured by a thermometer at the sampling point except for facility B in which temperatures in the inner part of each floor were electrically monitored each time (possibly higher than the sampling points). All samples were brought to the laboratory ice-packed and then frozen at −20°C until the experiment.

Table 1.  Characteristics of four composting facilities
FacilitiesMaterialsSystem typesTreatment daysTemperature (°C), Max–min (AV)pH, Max–min (AV)
ADehydrated sewage sludgeEarp-Thomas and windrow6054–26 (41·3)8·52–7·38 (8·11)
BDehydrated sewage sludgeEarp-Thomas1086–43 (61·2)8·89–7·91 (8·27)
CGarbage and pig manureWindrow with aeration6352–36 (46·0)7·72–6·68 (7·22)
DGarbageBin with scoop mixing4261–27 (45·8)5·12–4·97 (4·99)

Water and ash contents and C/N ratios

Each frozen composting sample, 1 kg, was mixed well before subsampling. Water contents were determined by weight loss of triplicate 5-g composting subsamples after drying at 105°C for longer than 24 h. The dried samples were ground and mixed well. Large pieces (about >0·1 mm) of woodchips and sawdust that were not finely ground were removed from the samples for ash content and C/N ratio measurement, because lignin, a main component of wood material, is not degraded during the composting process (Iiyama et al. 1994), and such large pieces cause differences in the measured levels. Ash contents were determined by weight loss of 2-g samples after burning at 550°C for 4 h. The C/N ratios of triplicate 10-mg samples were measured by a CHN corder (MT-5; Yanaco, Kyoto, Japan).

Physicochemical parameter measurement

Well-mixed compost samples (5 g) were suspended in sterile ultra-pure water. The suspension was adjusted to 50 ml and shaken for 30 min at 1800 rev min−1. After subsampling 2 ml for nucleic acid extraction and direct bacterial count, the suspensions were centrifuged at 15 000 × g, 4°C for 10 min. The supernatant was filtered through MILLEX®-GP 0·22-μm filter units (Millipore, Bedford, MA). The filtrate was measured for pH and then used for analysis of dissolved components. Total dissolved organic carbon and nitrogen were measured by a CHN recorder (MT-5; Yanaco, Kyoto, Japan) after the filtrates were soaked up by glass filters (GF-F; Whatman) and dried at 60°C. Monosaccharides in the filtrates were measured by the Tauber-Kleiner (1932) method. The detection limit of monosaccharides was approximately 1 mg glucose per gram dry weight. Several organic acids in the filtrates were measured by capillary electrophoresis (CIA; Waters, Milford, MA). Briefly, the filtrate was mixed with 50 mM of standard organic acids and diluted 10 times with ultra-pure water. Electrophoresis was performed at 200 V in supersaturated sodium tetraborate buffer with 1/10 volume of CIA-PakTM OFM Anion BT (Waters, Milford, MA). Absorbance at 252 nm was measured for detection. The standard organic acids for measurement were acetate, propionate and lactate. The detection limit of organic acids was approximately 0·2 mg per gram dry weight.

Direct bacterial count

An aliquot (100 μl) of the compost suspensions described above was diluted to 970 μl with sterile ultra-pure water and mixed well. The diluent was mixed with 30 μl of 50 μg ml−1 4′,6′-diamidino-2-phenylindole dihydrochloride (Wako, Osaka, Japan) solution and left for 5 min in the dark to stain bacterial cells. After mixing again, 100 μl of the mixture was filtered through a 0·2-μm pore Nucleopore® filter (CORNING, New York, USA). The filters were washed with sterilized water and observed by an epifluorescence microscope (BH2-RFCA; Olympus, Tokyo, Japan) with UV light. The average count of more than five random fields on each filter was used for bacteria.

Nucleic acid extraction

To lyse microbial cells, 1 ml of the composting suspension described above was mixed with 0·5 g of glass beads (0·1 mm diameter) and washed by centrifugation at 5000 × g for 10 min twice. Then the resultant pellet was mixed with the following reagents: 0·4 ml of 50 mmol l−1 sodium phosphate buffer (pH 6·8), 0·03 ml of 20% sodium dodecyl sulphate, 0·05 ml of 5 mol l−1 pyrophosphate and 0·6 ml of TE (10 mmol l−1 Tris–HCl, pH 8·0, 10 mmol l−1 EDTA) saturated phenol. The mixture was shaken vigorously (2000 rev min−1) on a beadbeater (Mikrodismembrator U; B. Braun Biotech International, Melsungen, Germany) for 30 s, centrifuged at 10 000 × g for 5 min at 4°C, and the upper phase was collected. The lower phases were extracted twice by the same procedure. Nucleic acids in the collected upper phase were then precipitated by adding 0·1 volumes of 3 mol l−1 sodium acetate (pH 5·3) and two volumes of 99·5% (v/v) ethanol, incubated at −20°C overnight and collected by centrifugation at 10 000 × g for 5 min at 4°C. Next, the nucleic acids were dissolved in 0·5 ml TE buffer and further purified by the polyethylene glycol precipitation method of Selenska and Klingmüller (1991).

PCR condition

PCR amplification was performed in 50-μl volumes containing approximately 100 ng of template DNA, 1× EX TaqTM Buffer (Takara Shuzo, Shiga, Japan), 200 μmol l−1 dNTP, 25 pmol of each primer, and 1·25 units of Taq polymerase (TaKaRa Ex TaqTM, Takara Shuzo, Shiga, Japan). PCR cycling was performed using a thermal cycler (PC800 Astec, Fukuoka, Japan). The temperature programme was as follows: 25 cycles at 94°C for 0·5 min or 2 min, 45°C for 1 min, and 72°C for 1·5 min.

PCR primers

A eubacterial 16S-rRNA-targeted primer set (341F with GC-clamp, 907R) was used for PCR amplification in this study (Muyzer et al. 1997). The sequences were as follows: GC-clamp, 5′-CGCCCGCCGCGCCCCGCGCCCGTCCCGCCGCCCCCGCCCG-3′; 341F, 5′-CCTACGGGAGGCAGCAG-3′; and 907R, 5′-CCGTCAATTCCTTTRAGTTT-3′. The 341F without GC-clamp and 907R primers were used for sequencing reactions.

Denaturing gradient gel electrophoresis

PCR products were analysed by DGGE according to Muyzer et al. (1997). DGGE was performed with a D-gene system (BioRad Laboratories, Hercules, CA). Similarly sized PCR products were separated on a 1·5-mm-thick vertical gel containing 8% (w/v) polyacrylamide (37·5 : 1 acrylamide–bisacrylamide) and a linear gradient of the denaturants urea and formamide, increasing from 0% at the top of the gel to 80% at the bottom. Here, 100% denaturant contains 7 mol l−1 urea and 40% (v/v) formamide. PCR products (10 μl) were applied to individual lanes in the gel. Electrophoresis was performed in a buffer (diluted 50 times) of readymade 50× Tris/Acetic acid/EDTA buffer (BioRad Laboratories, Hercules, CA) and 200 V was applied to the submerged gel for 4 h at 60°C. After electrophoresis, the gel was stained in an aqueous ethidium bromide solution (0·5 μg l−1) and photographed on a UV (302 nm) transillumination table with a Polaroid camera (CE-600; Nihon Polaroid, Tokyo, Japan). The photographs were scanned and the image data were downloaded into a computer. The computerized images were then inverted to negative images. Small pieces of selected DGGE bands were excised from the DGGE gel with Pasteur pipettes, and DNA fragments in the gels were washed and directly reamplified with the same primer. The PCR products were confirmed by DGGE as a single band or not, and if isolated, then purified and sequenced. The PCR product was purified by a Qiaquick PCR purification kit (QIAGEN, Hilden, Germany) according to the manufacturer's instructions.

Sequencing and phylogenetic analysis

Sequencing reactions were carried out with a primer pair 341F (without GC)-907R and an ABI PRISMTM BigDyeTM Terminator Cycle Sequencing Ready Reaction Kit (Perkin Elmer, Foster City, CA) according to the manufacturer's instructions. The products were then analysed by an automatic sequencer (model 377A, Applied Biosystems, San Jose, CA). Sequences were compared to the compilation of 16S rDNA genes available in the database (DDBJ, EMBL and GenBank) by MPsrch (Smith and Waterman 1981) through the DNA bank on the Ministry of Agriculture, Forestry and Fisheries of Japan Internet site. The sequences were then aligned and distances were determined with a CLUSTAL W Ver. 1·7 (Thompson et al. 1994). Neighbour-joining trees were drawn with TREEVIEW (Page 1996).

Nucleotide sequence accession numbers

The sequences obtained in this study are available in DDBJ under accession numbers AB081808–AB081829.

Results

Physicochemical characters in four composting processes

The range of temperatures in the four composting processes was different; however, the maximum temperatures showed over 50°C in all processes (Table 1). All the composting process did not show significant pH change during the treatment periods. The mean pH was relatively higher in the sewage-sludge-composting processes (A and B) than in the food-waste-composting processes (C and D) (Table 1). Ash contents increased with age in the sewage-sludge-composting processes (A and B) (Table 2). This suggested that mineralization of organic materials occurred during both processes. On the contrary, no trend was observed in terms of ash content in the food-waste-composting processes (C and D) (Table 2).

Table 2.  Physicochemical parameters in four composting processes
Sample*Temperature (°C)pHWater (%)Ash (%)C/N (AV†)Soluble fraction, mg g−1 dw (SD)
CNMonosaccharideAcetatePropionateLactate
  1. *The sample nomenclature follows the X-Yd pattern. ‘X’ and ‘Y’ show composting facility and the age in day after start of composting. †Average of three different aged samples during each composting process.

  2. ‡BDL, below detection limits.

A-3d448·5240·411·4514·4721·10 (1·37)2·25 (0·68)BDL‡BDLBDLBDL
A-30d548·4255·112·8214·9016·53 (2·09)1·09 (0·94)BDLBDLBDLBDL
A-60d267·3849·917·4813·66 (14·11)16·60 (1·35)1·57 (1·14)BDLBDLBDLBDL
B-1d868·3552·944·5412·728·24 (0·90)1·39 (0·10)BDL3·36 (0·66)0·85 (0·32)BDL
B-5d538·0865·046·4114·6614·76 (0·86)1·07 (0·70)BDL2·14 (0·16)BDLBDL
B-10d517·9172·849·2513·68 (13·69)12·85 (1·00)0·60 (0·86)BDLBDLBDLBDL
C-7d527·4849·220·687·9973·14 (0·94)3·75 (3·03)2·577·19 (1·65)1·62 (0·62)BDL
C-49d366·7356·015·607·56104·01 (11·25)14·79 (0·44)3·007·82 (0·54)1·03 (0·25)4·53 (0·58)
C-63d527·7270·216·637·99 (7·85)186·36 (4·41)21·59 (4·88)3·88BDLBDLBDL
D-2d575·0835·911·7210·42139·77 (14·42)14·46 (0·90)15·59BDLBDL5·98 (1·30)
D-16d614·9835·810·618·9656·99 (3·81)2·44 (1·29)15·03BDLBDL6·11 (0·87)
D-37d524·9642·412·028·29 (9·22)105·47 (1·57)10·70 (2·82)14·470·28 (0·18)BDL6·97 (0·24)

C/N ratios showed a constant value during each composting process. Average C/N ratios were relatively higher in A and B than in C and D (Table 2). Soluble fraction components also showed clear differences depending on the starting materials (Table 2). The concentrations of soluble C and N, monosaccharides, and organic acids were higher in C and D than in A and B. High concentrations of monosaccharides in D decreased gradually with a concomitant increase in lactate concentration with age. In the sewage-sludge-composting facilities, no organic acids were detected throughout A, or a small amount of acetate was detected only at an early stage in B.

DGGE analysis of 16S-rDNA in composting processes

In the DGGE profiles of the four composting processes, the position and intensities of most bands did not change as the age proceeded except that the 60 day sample in A showed different band intensities from those of earlier samples (Fig. 1). These findings suggest that bacterial communities in each composting process did not change greatly throughout the composting periods. Among the four composting processes, the pattern and number of bands differed from each other (Fig. 1). The DGGE profiles of the sewage-sludge-composting processes (A and B) showed more bands than those of the food-waste ones (C and D), and the number of bands decreased in the order of A, B, C and D. The band positions on the DGGE profile of the starting material differed from those of the composting process in B, where the starting material could be obtained (Fig. 1b). This showed that different bacterial populations from those in the raw material rapidly developed in the composting process.

Figure 1.

Inverted image of DGGE gel stained by ethidium bromide. The number under each lane shows the age in days after the start of composting. The bands represented by arrows were successfully isolated and sequenced

Phylogenetic analysis

Nucleotide sequences in successfully isolated bands on the DGGE profiles showed the highest similarities to the following organisms (with accession numbers) in DNA database: DGGE profile A, Sphingobacterium mizutae (X67853), Flavobacterium heparinum (D14020), Herbaspirillum seropedicae (AJ238361), Acidovorax facilis (AF078765), Bacillus thermocloacae (Z26939), Mycobacterium thermoresistible (M29570), Saccharomonospora viridis (Z38005), Actinoalloteichus cyanogriseus (AB006178), Beutenbergia cavernosa (Y18378) and Thermomicrobium roseum (M34115); profile B, Clostridium thermocellum (L09173), B. thermocloacae (Z26939), Bacillus thermoamylovorans (L27478), Ornithinicoccus hortensis (Y17869) and T. roseum (M34115); profile C, Lactobacillus bifermentans (M58809), Bacillus megaterium (AB022310) and Corynebacterium urearyticum (X84439); profile D, Pediococcus acidilactici (M58833), Lactobacillus salivarius (AF089108) and B. megaterium (AB022310).

The phylogenetic relation of 16S-rDNA partial sequences from successfully isolated DGGE bands was analysed as shown in Fig. 2. Because of short DNA length (approximately 300 bp), the tree did not properly delineate the positions of the members of green non-sulphur bacteria, T. roseum, as reflected by the relatively low bootstrap values of branches near the root. However, phylogenetic position within the phylum might be properly delineated based on comparatively high bootstrap values. Of 24 DNA sequences, 18 fell into the cluster of Gram-positive bacteria. Three sequences (C-01, D-01 and D-02), which fell into the cluster of fermenting bacteria, were only detected from the food-waste-composting processes. On the contrary, the sequences that fell into the actinobacterial cluster were only detected from the sewage-sludge-composting processes (except for C-03), along with six sequences of Gram-negative bacteria.

Figure 2.

The neighbour-joining tree of partial 16S-rDNA sequence (approximately 300 bp) recovered from DGGE bands. The tree was constructed as described in the text. Nucleotide sequences from this study were represented by the band names shown as Fig. 1. Each sequence, except for those from this study, was obtained from the DDBJ. Accession numbers appear before the genus name. Numbers on the branches refer to bootstrap values for 1000 times; only those above 400 are shown

Discussion

In this study, four composting processes in different full-scale facilities were compared in terms of physicochemical aspects and bacterial populations evaluated by DGGE. The microbial communities in each full-scale composting process did not change greatly through its progress and were different among the composting facilities (Figs. 1 and 2). As a result, similar microbial communities tended to be observed in composting processes treating similar starting materials irrespective of the different types of system; fermenting bacteria were found in food-waste-composting processes (C and D), and complex bacterial populations including Bacillus, actinobacteria, and Gram-negative bacteria were found in sewage-sludge-composting processes (A and B). This suggested that the bacteria proliferating during a composting process differed with the materials treated. These bacteria appearing during the composting process might not be derived from the starting materials, or at least, were minor populations in the starting materials, because the DGGE profiles from B were completely different between the starting material and composting ones (Fig. 1b). This result was supported by Klamer and Bååth (1998), and similar change should occur in the other three composting processes. Thus, the microbes proliferating in the composting processes would be adapted to the composting environment, and selected by factors within the composting materials.

The C/N ratio has been often used to represent the qualities of composting materials. Larsen and McCartney (2000) examined the effect of various C/N ratios in starting material, which were adjusted by addition of sulphur-coated urea, to microbial activity and N retention in composting processes. They showed that composting materials with higher C/N ratios had higher microbial activities than those with lower C/N ratios. In the present study, C/N ratios of all materials were within a narrow range. Despite the similar C/N ratios, the microbial communities were different among the four composting processes. Thus, microbial communities would be mainly affected by the qualities of composting materials, not only by the C/N ratios. On the contrary, the differences in composting materials were well represented by the concentrations of dissolved components such as organic carbon, monosaccharides and organic acids. The dissolved components, therefore, were regarded to be one of the important parameters for characterization of composting materials, and might affect microbial communities as discussed below.

Microbial communities detected from dissolved organic carbon-poor composting processes in A and B were similar to each other irrespective of the different managing systems, but were substantially different from dissolved organic carbon-rich composting processes in C and D. Gram-negative bacteria, members of Cytophaga–Flavobacterium–Bacteroides phylum and actinobacteria, were commonly detected from both composting processes in A and B, but not from those in C and D. In addition, two phylogenetically identical bacteria were detected from both A and B. First, B-02 and A-05 were 100% homologous to Bacillus thermocloacae. This species is obligately aerobic, thermophilic, unable to degrade gelatin and isolated from sewage sludge (Demharter and Hensel 1989). Bacillus relatives that often dominated thermophilic composting processes (Webley 1947a,b; Strom 1985a,b; Wong et al. 1990) were detected from all four composting processes; however, commonly occurring species were shared by its materials: mesophilic B. megaterium relatives were detected from food-waste-composting processes instead of thermophilic B. thermocloacae, although the relations between the appearing species and factors included in composting conditions are unknown as yet. Second, A-10 and B-06 were closely related, and were mostly related to a thermophilic heterotroph T. roseum, despite its phylogenetic distance from them (Fig. 2). The organisms corresponding to A-10 and B-06 have never been isolated, and their functions were unknown. These similarities in the microbial communities between A and B suggested similar composting ecosystems. In these ecosystems, a part of the microbial populations seems to have the ability to degrade high-molecular-weight compounds. For example, A-09 closely related to Saccharomonospora viridis, which had often been isolated from composting (Holt et al. 1994). The members of genus Saccharomonospora have abilities to hydrolyse high-molecular-weight compounds such as casein, gelatin, starch and xylan (Holt et al. 1994). In addition, sequence B-01 was closely related to Clostridium thermocellum (Fig. 2 and Table 2), which can hydrolyse cellulose (Cato et al. 1986). These abilities might be important in the composting processes A and B, because dissolved organic carbons are scarce in both processes (Table 2).

In the composting processes in C and D in which higher concentrations of dissolved organic carbon than in A and B were detected, relatively few DGGE bands were observed. Six sequences were determined from the bands on DGGE profiles of C and D. Among the six sequences, three sequences, C-01, D-01 and D-02, related to lactate-fermenting bacteria (Fig. 2). In particular, the band D-01 was the only main band and had stronger intensities over the whole composting period of D (Fig. 1d). This suggested that this organism played important roles in the composting process. As shown by Fig. 2, D-01 was closely related to Pediococcus acidilactici, a thermophilic bacterium with a homolactate-fermenting metabolism. The dominance of this bacterium was supported by high concentrations of monosaccharides and lactate at high temperature with a slight decrease of monosaccharides during the process (Tables 1 and 2). Since homolactate fermentation converts 1 mol of glucose into 2 mol of lactate, i.e. the starting material and end product have the same weight, the weight does not change through the metabolism. This agrees with the fact there was no clear change of ash content in D (Table 2). This would suggest that a lactate-fermentative metabolism might occur in dissolved organic carbon-rich composting processes, but not in composting processes with scarce dissolved organic carbon such as in A and B, based on comparisons of the microbial communities detected. These results suggest that the concentration of dissolved organic carbon is an important factor affecting the microbial community structure.

The microbial communities in each full-scale composting process did not change greatly through its progress (Fig. 1). The temperature and pH in the four composting processes also showed only gradual changes (Table 2). Nevertheless, a laboratory-scale food-waste-composting process showed drastic changes in microbial populations and physicochemical parameters (Ishii et al. 2000). These results suggest that larger-scale composting processes progress slower than smaller-scale ones. This agrees with other studies as follows: in the comparison between full- and bench-scale composting processes performed by Klamer and Bååth (1998), the temperature change in a full-scale facility was slower than that in a bench-scale one. During the full-scale windrow composting process performed by Hellmann et al. (1997), temperature changed from about 70°C to ambient for 60 days after starting, and pH showed a constant value (around 8·0) after day 10. However, Miner et al. (2001) indicated that a critical material volume of more than 0·18 m3 m−1 was required to achieve temperatures of a windrow compost >43°C. Since in situ temperature of composting depends on the balance of rate between heat production and loss, the critical material volume to achieve high temperature may be greatly affected by material types. A food-waste composting of material generally containing much easily degradable compounds as shown by this study may have a higher heat production rate than the other composting processes such as sewage sludge composting and manure composting. Therefore, food-waste composting may generally have a smaller critical material volume than the other processes. In other words, at least regarding food-waste composting, small-scale composting progress faster than a large-scale one. Due to its large scale, the composting material of the last sampling day during the full-scale composting process in D still contained a large amount of easily utilizable compound (Table 2), and might not be sui table for soil fertilizer. Actually, the final composting material was immature and was dried by steam to remove volatile compounds before distribution. However, the further progression of a laboratory-scale composting process with similar starting material (Ishii et al. 2000) suggested that the composting process in D could progress further if the process was longer or was performed under more effective conditions.

Although the speed of composting differed between the laboratory-scale composting process in the previous study (Ishii et al. 2000) and the full-scale ones in the present study, similar microbes were detected from both processes: (i) P. acidilactici-related 16S-rDNA sequences were detected in both the initial stages of a laboratory-scale food-waste-composting process (Ishii et al. 2000) and the full-scale composting process in D, where the concentrations of dissolved organic carbon were high (Tables 2 and 3). Thus, fermenting bacteria may dominate in composting processes where easily degradable organic carbon is abundant. This is supported by Golueke's (1954) suggestion that fermenting bacteria dominate at the beginning of the composting process. (ii) After the appearance of lactate-fermenting bacteria, Corynebacterium-related 16S-rDNA sequences were detected in a laboratory-scale food-waste-composting process (Ishii et al. 2000) (Table 3). Similarly, in the composting process in C in which substantially less monosaccharides was detected than in D, the clear band C-03 detected over the whole process was closely related to Corynebacterium urealyticum, which was not detected from D (Figs 1c and 2). Although many species of this genus have a fermenting metabolism, C. urealyticum is asaccharolytic and has an oxidative metabolism (Funke et al. 1997). Such organisms may proliferate in the composting processes with abundant dissolved organic carbon but few monosaccharides. This might suggest that Corynebacterium proliferates in the composting process when monosaccharides are too few for lactate-fermenting bacteria to proliferate. (iii) In spite of the different starting materials, similar microbial communities were also detected from both the later phase of the laboratory-scale food-waste-composting process (Ishii et al. 2000) and the full-scale composting processes in A and B (Table 3). These comparisons between the laboratory-scale composting process and full-scale ones suggest that similar microbial communities may proliferate not only in both large- and small-scale of composting processes, but also among composting processes with different materials, when the amount and qualities of dissolved organic carbon are similar.

Table 3.  Comparison of microbial communities between laboratory- and full-scale composting facilities
Bacterial taxaLaboratory scaleFull scale
4–9 days13 days20–45 daysDCBA
Lactate-fermenting bacteria+  ++  
Bacillus++ ++++
Corynebacterium +  +  
Clostridium ++  + 
Actinobacteria  +  ++
Gram-negative bacteria  +  ++
CFB phylum  +   +

In conclusion, the phylogenetic positions of sequences obtained in this study could be grouped according to the raw materials across different systems of composting facilities. Fermenting bacteria were only detected from the food-waste-composting processes (C and D), and most actinobacteria and Gram-negative bacteria were detected from the sewage sludge ones (A and B). Thus, the comparison of microbial communities during the four different composting processes suggested that the microbial communities were different depending on the material type in similar thermophilic conditions. Furthermore, by comparing with a laboratory-scale food-waste-composting process, it became clear that the concentration of dissolved organic carbon was an important factor affecting microbial community structure and metabolic type. Thus, a fermenting metabolism seems to occur in the composting processes at a high concentration of dissolved organic carbon and respiratory metabolism occurs in composting process at scarce dissolved organic carbon. Since full-scale composting processes progress slowly, microbial communities do not seem to change during each process, and differ with different composting processes. However, the emergence of similar bacterial communities in the later stage of a laboratory-scale composting process and the full-scale sewage-sludge-composting processes suggests that microbial communities proliferating during composting processes are similar in spite of the different starting materials as long as the composting material contains similar amounts of dissolved organic carbon. In other words, the level of composting progression may be reflected in the amount of dissolved organic carbon. These findings are useful in determining effective composting condition.

Acknowledgements

The authors thank the persons who kindly provided samples. Also Mananubi Fukui for valuable advice and support, and Flynn Picadal for reviewing the manuscript.

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