To characterize adaptive changes in methanogenic microbial community in response to substrate overloading and identify potential linkages between process performance and microbial community composition.
To characterize adaptive changes in methanogenic microbial community in response to substrate overloading and identify potential linkages between process performance and microbial community composition.
Triplicate continuous anaerobic digesters were developed as model anaerobic digestion processes, which were subsequently disrupted by substrate overloading. The clone library analysis of archaeal communities experiencing substrate overloading showed that populations related to Methanosaeta were the dominant methanogens before and after substrate overloading, suggesting the functional importance of these acetoclastic methanogens in balanced anaerobic digestion processes characterized with low organic acids concentrations. Population redundancy in Methanosaeta increased following substrate overloading with the emergence of additional populations of Methanosaeta. More importantly, the methanogenic community responded to process imbalance with greater functional diversity with increased abundance of functionally distinct hydrogenotrophic and acetoclastic methanogens, which likely enhanced the functional stability of anaerobic digestion during disruptions in the anaerobic food web under process perturbation. Crenarchaeota were identified as persistent constituents of the archaeal communities in anaerobic digestion, warranting further efforts to identifying the functions of these phylogenetically distinct populations in anaerobic digestion.
Substrate overloading in anaerobic digestion resulted in an increased functional diversity of the methanogenic community, which enhanced the capacity to overcome subsequent occurrences of process perturbations without performance disruption, providing a potential strategy to maintain process stability in anaerobic digestion.
Anaerobic digestion is a sustainable option for waste treatment and renewable energy production. However, process instability resulting from variations in substrate loading has been one of the obstacles to the broader adoption of anaerobic digestion technology. Insight into the linkages between process performance and microbial community gained in this study is valuable for developing strategies for the mitigation of the impact of substrate overloading on anaerobic digestion processes.
Anaerobic digestion is an important biological process capable of simultaneous waste treatment and renewable energy recovery. Interest in anaerobic digestion has grown considerably in recent years, particularly with the need for increases in renewable energy production and reduction in greenhouse gas emission (McKendry 2002). Despite the advantages of anaerobic digestion, the broader adoption of this technology for waste treatment has been hindered by concerns of potential process instability resulting from the susceptibility of methanogenic microbial populations to changes in process conditions (Chen et al. 2008), such as fluctuations in organic loading rates (OLRs) and changes in waste composition, which are frequently encountered in the anaerobic digestion of animal wastes.
Previous studies of anaerobic digestion processes have shown that substrate overloading frequently leads to process imbalance, characterized by the accumulation of organic acids and inhibition of biogas production (Leitão et al. 2006). As anaerobic biotransformation of organic wastes involves a complex anaerobic food web, efficient anaerobic digestion requires the balanced activities of diverse anaerobic microbial populations including acidogenic and methanogenic micro-organisms (Schink 1997; Ahring 2003). The terminal step in anaerobic decomposition of organic wastes, methanogenesis, is carried out exclusively by methanogens, a group of micro-organisms associated with Archaea (Luo et al. 2009). Methanogenesis is often considered as the limiting step in anaerobic digestion processes under perturbation, due to both the slow growth rates and the susceptibility to fluctuating process conditions characteristic of methanogens (Kotzé et al. 1969; Chen et al. 2008). Thus, the dynamics of archaeal populations in anaerobic digestion may provide insight into the linkage between process performance and microbial activities in anaerobic conversion under perturbation.
Animal waste generated from large-scale livestock operations has been a source of environmental pollution and public health risk, because the natural decomposition of animal waste releases large quantities of pathogens, excess nutrients, organic matter, solids, methane, ammonia and odourants into the environment (Jongbloed and Lenis 1998). Anaerobic digestion has been shown to be an effective technology to overcome these challenges (Chen and Cheng 2005). More recently, anaerobic codigestion of animal waste has been explored to enhance the economic feasibility of animal waste treatment (Mata-Alvarez et al. 2011). The success of anaerobic codigestion typically exploits the potentially significant improvement in biogas production by supplementing the primary substrate with an organic-rich cosubstrate, thus overcoming challenges presented by the low biogas yield of the primary substrate. This practice, however, frequently leads to fluctuations in OLRs, which may subsequently result in undesirable disruptions in process performance.
Interestingly, it has been noted that anaerobic digestion processes can adapt to perturbations resulting from organic overloading, likely through long-term changes in microbial community structures (Xing et al. 1997; Hashsham et al. 2000). While it is suggested that increased population diversity may be linked to the adaptation to process perturbations, much remains to be learned on the changes in specific microbial populations before and after perturbations. Therefore, to gain insight into the responses of microbial populations to process disturbances in anaerobic digestion, the specific objective of this study is to investigate the impact of substrate overloading on the methanogenic populations, which complete the terminal step of the anaerobic food web, by comparing the archaeal populations before and after performance disruption in continuous anaerobic codigestion of dairy and poultry wastes as a model anaerobic digestion process.
Triplicate mesophilic continuous anaerobic codigesters were established with dairy waste as the primary substrate and poultry waste as the cosubstrate following the configuration described previously (Fernandez et al. 2000). The codigestion process exploited the higher solids content of poultry waste as compared with the primary substrate dairy waste (Table 1) to enhance biogas production. All three completely mixed digesters had a working volume of 3·6 l and were operated in a constant temperature room at 35°C. During normal operation, the digesters were fed at 4-h intervals and the hydraulic retention time was maintained at 20 days. These digesters were initiated with inoculum from an operating laboratory-scale dairy manure anaerobic digester and established using dilute diary waste as the only feed. Following the establishment of stable anaerobic digestion performance, poultry waste was added as an organic-rich cosubstrate to achieve enhanced methane production. Poultry waste was also used to cause organic overloading when added at excessive levels. All digesters exhibited stable operation with consistent pH, methane yield and volatile fatty acids (VFAs) level prior to stepwise increases in the loading rate of poultry waste that eventually resulted in organic overloading and inhibition of biogas production. During this study, the initial OLR in the triplicate digesters was maintained at 1·3 g volatile solids (VS)−1 l−1 day−1, consisting of 1·0 g VS−1 l−1 day−1 from dairy waste and 0·3 g VS−1 l−1 day−1 from poultry waste. With the addition of more poultry waste to the feed, the OLR in the anaerobic digesters were raised stepwise to 1·5 g VS−1 l−1 day−1 and subsequently to 1·8 g VS−1 l−1day−1 when normal process performance was disrupted by substrate overloading (Fig. 1). To recover the digesters from disturbance, feeding was stopped and later restored stepwise to 0·5, 1·0 and eventually 1·5 g VS−1 l−1 day−1, when stable operation was again achieved. Dairy waste was the only substrate in the feed, when OLR was 0·5 or 1·0 g VS−1 l−1 day−1; subsequently, poultry waste was added to the feed to raise the OLR from 1·0 to 1·5 g VS−1 l−1 day−1, resulting in a substrate mixture consisting of diary waste and poultry waste with a ratio of 2 : 1 (gVS/gVS).
|Parameters||Dairy waste||Poultry waste|
|Total solids (TS), % wet mass||2·3||55·7|
|Volatile solids (VS), % TS||57·6||60·6|
|Total chemical oxygen demand (mg COD per g VS)||1460||389|
|Total ammonia (mg N per g VS)||18·4||14·1|
|Total Kjeldahl nitrogen (mg N per g VS)||56·1||70·7|
|Total alkalinity (mg CaCO3 per g VS)||270||83·0|
Biogas production from the anaerobic digesters was used as the primary parameter to monitor digestion performance (Michaud et al. 2002) and was determined using a water-displacement method described previously (Zhu et al. 2011). VFAs in the digestate were quantified using a Hewlett Packard 5890 gas chromatograph equipped with a flame ionization detector (FID) and a Restek Stabilwax®-DA column as previously described (He et al. 2009). Methane content in biogas was analysed using a Hewlett Packard 5890 Series II gas chromatograph equipped with a thermal conductivity detector (TCD) and a Supelco packing column (60/80 Carbonxen®-1000; Sigma-Aldrich, St Louis, MO, USA). Argon was used as the carrier gas with a flow rate of 5 ml min−1 and the following temperature scheme: oven 125°C, injection port 150°C and detector 170°C. Chemical oxygen demand (COD), total alkalinity (TA), total solids (TS), VS and ammonia-nitrogen (NH4+-N) were all determined according to standard methods (APHA 2005): COD was measured with the ‘5220C’ Close Reflux-Titrimetric Method; TA was quantified using the ‘2320B’ titration method; TS and VS were measured using the ‘2540 B and E’ method; and NH3-N was quantified using the ‘4500-NH3 D’ method with an Orion 9512 ammonia ion selective electrode (Orion Research Inc., Beverly, MA, USA).
For archaeal microbial community analysis, pre-overloading sludge samples were taken from the anaerobic codigesters at day 0 when the performance of the digesters were stable; post-overloading samples were taken at day 340 following the complete recovery from performance disruption due to substrate overloading. Samples were stored at −80°C until analysis. Triplicate samples taken at the same time point were pooled before whole community DNA was extracted and purified as previously described (Zhang et al. 2009). Archaeal 16S rRNA genes were subsequently amplified by polymerase chain reaction (PCR) using the Archaea-specific primers Arch21F (5′-TTCCGGTTGATCCYGCCGGA-3′) and Arch958R (5′-YCCGGCGTTGAMTCCAATT-3′) following PCR conditions described previously (Delong 1992).
The amplified products were purified using the Qiagen PCR purification kit (Qiagen, Valencia, CA, USA) and cloned into the pGEM-T Easy vector (Promega, Madison, WI, USA) following the manufacturer's instructions. For each clone library, approximately 100 cloned plasmid inserts were randomly selected for sequencing with the ABI Prism BigDye chemistry (Applied Biosystems, Foster City, CA, USA) using M13 forward and reverse primers. The obtained sequences were screened for chimeric artefacts by the programme Chimera Check at the Ribosomal Database Project II (Cole et al. 2003). Subsequently, the 16S rRNA gene sequences were searched in the NCBI GenBank database using the Blast program to locate the most similar sequences as the closest relatives to the 16S rRNA gene clones retrieved from the anaerobic digesters. Sequences were assigned preliminary phylogenetic associations based on the RDP Classifier programs at http://rdp.cme.msu.edu/classifier/classifier.jsp (Cole et al. 2003). These 16S rRNA gene sequences were further aligned with homologous sequences using ClustalX (Thompson et al. 1997) and used for the construction of phylogenetic trees by the neighbor-joining algorithm (1000 bootstrap resamplings) with mega 4.0 (Tamura et al. 2007). A sequence or cluster of sequences with <3% dissimilarity to the adjacent sequence(s) was defined as an operational taxonomic unit (OTU) as previously described (Zhang et al. 2011). Partial 16S rRNA gene sequences recovered in this study were deposited at GenBank under the following accession numbers: JN052741–JN052771 and JN083826–JN083830.
To compare the archaeal community structures of the anaerobic codigesters predisturbance and postdisturbance, the Shannon diversity index (H′) was calculated for the pre-overloading and post-overloading clone libraries as previously described (Hill et al. 2003):
where ni is the number of clones in the ith OTU and N is the total number of clones in the library.
The similarity between the methanogen communities was further characterized with the Morisita–Horn similarity index (CM-H), which ranges between 0 and 1. A CM-H value of 1 indicates that two identical communities are identical, and a CM-H value of 0 indicates that two communities share no common members. The Morisita–Horn similarity index (CM-H) was calculated using the equation below for the pre-overloading and post-overloading clone libraries (i.e. community A and B) as previously described (Magurran 2004):
where SA,i = the number of clones from community A in the ith OTU
SB,i = the number of clones from community B in the ith OTU
n = the number of clones in community A
m = the number of clones in community B
Following the establishment of the triplicate continuous bench-scale anaerobic codigesters with diary waste as the primary substrate and poultry waste as the cosubstrate, stepwise increases in OLR were achieved by increasing the proportion of poultry waste in the feed to the digesters (Fig. 1). Poultry waste contained 55·7% of TS, which was much greater than the 2·3% solids content of dairy waste (Table 1). Given that the volatile fraction of the solids content of poultry waste was slightly higher than that of dairy waste, poultry waste offered a much higher total VS content (33·8%) than that of dairy waste (1·3%). Thus, the addition of poultry waste raised the OLR of anaerobic digestion without altering the hydraulic loading rate. As expected, stepwise increases in methane production were observed in response to the addition of poultry waste before the process was ultimately overwhelmed when OLR reached 1·8 g VS−1 l−1 day−1 (Fig. 2), confirming the effectiveness of poultry waste as an organic-rich cosubstrate to enhance biogas production in anaerobic digestion.
Before the onset of substrate overloading, balanced anaerobic digestion performance was evident with stable biogas production at 1583 ± 41 ml day−1 when the OLR was maintained at 1·3 g VS−1 l−1 day−1 (Fig. 2). Upon the increase in OLR by 15% to 1·5 g VS−1 l−1 day−1, biogas production reached 1912 ± 20 ml day−1, an increase proportional to that of the OLR, suggesting that anaerobic digestion performance remained stable at this OLR level. Accordingly, the concentration of VFAs remained constantly below 0·5 mmol l−1 at OLR levels of 1·3 and 1·5 g VS−1 l−1 day−1 (Fig. 3), despite increases in OLR and biogas production, further confirming process stability at these OLR levels (Ahring et al. 1995).
A further increase in OLR, however, led to substrate overloading and disruptions in anaerobic digestion performance. Following the sampling of pre-overloading biomass at Day 0, the OLR was raised from 1·5 to 1·8 g VS−1 l−1 day−1 (Fig. 1). The digesters responded with an initial spike of biogas production to 2431 ± 38 ml day−1; but a rapid decline in biogas production ensued, indicative of the deterioration of process performance (Fig. 2). Accompanying the rapid decline in biogas production, VFA concentration rose quickly (Fig. 3), providing further evidence for process imbalance as a result of substrate overloading. To prevent further deterioration of process performance, feeding of substrate ceased at Day 35. However, VFA concentration continued to climb until reaching ~40 mmol l−1, while biogas production continued its precipitous drop (Fig. 2).
To recover the anaerobic digestion process from substrate overloading, feeding of animal waste was suspended for a period of 30 days (Fig. 1). Feeding was resumed with a low OLR of 0·5 g VS−1 l−1 day−1 when biogas production diminished and VFA concentration fell from 40 to 14·5 mmol l−1. Immediately following the resumption of substrate feeding, the VFA level rose quickly from 14·5 to 44 mmol l−1 (Fig. 3). However, the VFA level fell below 1 mmol l−1 on Day 110 and stable anaerobic digestion performance was re-established at this feeding rate with biogas production stabilized at 522 ± 20 ml day−1 in a 90-day period (Fig. 2).
With the objective to restore the digestion process to the stable performance achieved at the original OLR of 1·5 g VS−1 l−1 day−1 prior to overloading, stepwise increases in OLR were implemented to raise OLR from 0·5 g VS−1 l−1 day−1, to 1·0 g VS−1 l−1 day−1 and then to 1·5 g VS−1 l−1 day−1 (Fig. 1). Consequently, biogas production increased to 1086 ± 102 ml day−1 and 1620 ± 149 ml day−1 with OLR at 1·0 and 1·5 g VS−1 l−1 day−1, respectively (Fig. 2). Similar to the spike in VFA concentration observed immediately following the resumption of substrate feeding to 0·5 g VS−1 l−1 day−1, the digesters experienced spikes in VFA concentration when the OLR was raised from 0·5 to 1·0 g VS−1 l−1 day−1 and again from 1·0 to 1·5 g VS−1 l−1 day−1 (Fig. 3). In all three occurrences of VFA accumulation following increases in OLR, spikes in VFA level followed by rapid declines and subsequently remained below 1 mmol l−1 as indications of the establishment of stable performance. Notably, the spike in VFA level in response to increases in OLR became less and less pronounced, with the maximum VFA accumulation decreasing from a high of 44 mmol l−1 at OLR of 0·5 g VS−1 l−1 day−1, to 8·0 mmol l−1 at OLR of 1·0 g VS−1 l−1 day−1 and to a very moderate 2·5 mmol l−1 at OLR of 1·5 g VS−1 l−1 day−1 (Fig. 3). While fluctuations in biogas production post-overloading were still visible with the relatively greater standard deviations in biogas production as compared to those under pre-overloading conditions (Fig. 2), it could be concluded that the anaerobic digesters had recovered from the performance collapse induced by substrate overloading.
As methanogens as members of the Archaea are among the microbial populations most sensitive to process disturbances in anaerobic digestion (Chen et al. 2008), the responses of archaeal microbial populations before and after substrate overloading were further studied by clone library analysis to understand the responses of these populations to process disturbance.
Clone library analysis identified 11 archaeal OTUs involved in the anaerobic digestion process (Table 2). OTUs 2, 3, 4, 7, 8 and 11 persisted throughout the disturbance and recovery process, representing 98% of the archaeal abundance in the pre-overloading archaeal community. The most abundant methanogen populations pre-overloading included those closely related to Methanosaeta concilii (OTU 2) and Methanocorpusculum-like organisms (OTU 8) (Fig. 4a). Methanosaeta-related organisms are acetoclastic methanogens suggested to be competitive in established methanogenic communities with low acetate concentration (Jetten et al. 1990). Indeed, 16S rRNA gene sequences related to Methanosaeta represented 52% of the methanogen sequences in the pre-overloading clone library (Fig. 4a). The dominance of Methanosaeta-related methanogens is consistent with the pre-overloading condition in the anaerobic codigesters with balanced performance and low VFA concentration. The roles of Methanocorpusculum-like populations, however, are less clear. These hydrogenotrophic methanogens have been found to be the predominant methanogen populations in psychrophilic anaerobic digestion processes and are suggested to be specifically adapted to psychrophilic conditions (McKeown et al. 2009; O'Reilly et al. 2010). The persistence of these methanogens in the mesophilic anaerobic digestion processes of this study raises the possibility that Methanocorpusculum-like organisms may function in a broader temperature range.
|OTU||Taxonomic identification||Closest relative||GenBank accession no.||Representative clonesa||Relative abundance, %b|
|1||Crenarchaeota||Uncultured Crenarchaeote||CU916928||12B (99%)||0||4|
|2||Euryarchaeota||Methanosaeta concilii||NR_028242|| |
|3||Crenarchaeota||Uncultured Crenarchaeote||AY464784|| |
|4||Crenarchaeota||Uncultured Crenarchaeote||GU196174|| |
|5||Euryarchaeota||Methanosarcina barkeri||AF028692||2B (99%)||0||9|
|6||Euryarchaeota||Methanomethylovorans sp.||EF174501||65A (99%)||2||0|
|7||Crenarchaeota||Uncultured Crenarchaeote||EF552166|| |
|8||Euryarchaeota||Methanocorpusculum sp.||AY260434|| |
|9||Euryarchaeota||Methanobacterium beijingense||AY552778||4B (98%)||0||3|
|10||Euryarchaeota||Methanosaeta harundinacea||AY970347||41B (98%)||0||21|
|11||Euryarchaeota||Methanoculleus palmolei||NR_028253|| |
To characterize the microbial community in response to substrate overloading, the Morisita–Horn similarity index (CM-H) was calculated as a measure of the similarity in the population structure between the pre- and post-overloading methanogenic communities. The CM-H value of 0·71 indicates that the two microbial communities shared considerable similarities. The differences between the two communities could be attributed to the observation that the post-overloading methanogenic community became more diverse (Fig. 4b), as the Shannon diversity index (H′) increased from the pre-overloading value of 1·45 to the post-overloading value of 2·07. Similar to the pre-overloading methanogenic community, methanogens related to M. concilii (OTU 2) remained prevalent; however, the relative abundance of these micro-organisms in the methanogen populations decreased from 52% pre-overloading to 33% post-overloading (Fig. 4). Contributing to the increased diversity was the emergence of additional methanogen OTUs in response to substrate overloading, which included those closely related to Methanosaeta harundinacea (OTU 10), Methanosarcina barkeri (OTU 5) and Methanobacterium beijingense (OTU 9).
Notably, the sequence abundance of OTU 10 reached approximately the same level as that of OTU 2, which was the most abundant methanogen population both pre- and post-overloading (Fig. 4). As both OTU 10 and OTU 2 are closely related to Methanosaeta (Ma et al. 2006), it is likely that both would share the same physiology of adaptation to methanogenic processes with low acetate levels (Jetten et al. 1990). Thus, the presence of OTU 10 post-overloading resulted in a significant level of functional redundancy for methanogenesis at low acetate conditions. In contrast, Methanosarcina-related methanogens (OTU 5) are known to be more competitive than Methanosaeta-related methanogens (OTUs 2 and 10) at high acetate conditions (Jetten et al. 1990). Therefore, the presence of Methanosarcina-related methanogens in post-overloading microbial community could be a response to the accumulation of organic acids accompanying process imbalance resulting from organic overloading.
While methanogens were the most prominent members of the archaeal community in the anaerobic digesters analysed in this study, a number of clones phylogenetically unrelated to methanogens formed a cluster within the archaeal phylum Crenarchaeota (Fig. 5), which was unexpected because it is typically assumed that all archaeal populations involved in anaerobic digestion are methanogens, yet no known methanogens belong to Crenarchaeota (Luo et al. 2009). In particular, of the 11 archaeal OTUs identified in the anaerobic co-digesters, 4 represented the archaeal phylum Crenarchaeota and 7 represented the Euryarchaeota (Table 2). Thus, a considerable portion of the archaeal community in the anaerobic digesters was likely nonmethanogen populations.
Anaerobic digestion is a sustainable option for waste treatment and renewable energy production. However, process instability resulting from variations in substrate loading has been one of the obstacles to the broader adoption of anaerobic digestion technology. It is thus important to identify mechanisms that can mitigate the impact of substrate overloading on anaerobic digestion processes. Using anaerobic codigesters treating dairy and poultry wastes as the model system, results from this study show that the archaeal community recovered from substrate overloading acquired greater population diversity, suggesting the development of enhanced functional diversity potentially beneficial to overcoming subsequent occurrences of higher substrate loading.
The linkage between greater archaeal diversity and adaptation to substrate overloading is reflected in the enhanced functional diversity in the post-overloading methanogenic community. Methanosaeta-related populations known to be competitive for acetate at low concentrations were found to be the dominant methanogens in both pre- and post-overloading conditions (Fig. 4), suggesting the importance of these methanogens in balanced anaerobic digestion processes characterized by low VFA concentrations (Jetten et al. 1990; Ahring et al. 1995). However, the identification of Methanosarcina-related acetoclastic methanogens as abundant populations post-overloading represented a major enhancement in the functional diversity of the post-overloading community, because the Methanosarcina-related methanogens are known to be more competitive than Methanosaeta at high acetate conditions, which are frequently encountered in unstable anaerobic digestion processes (Jetten et al. 1990). Thus, the greater functional diversity as a result of increased Methanosarcina abundance likely improved the capacity of the post-overloading methanogenic community to overcome the detrimental impact of fluctuating substrate loading rates characterized by the transient accumulation of high concentrations of VFAs (Hashsham et al. 2000; Briones and Raskin 2003). Indeed, the post-overloading anaerobic digestion process was increasingly adaptable to higher OLR as the accumulation of VFAs diminished further following each stepwise OLR increase (Fig. 4).
The increase in methanogenic functional diversity post-overloading was also demonstrated by the detection of Methanobacterium-related populations (Table 2), which are hydrogenotrophic methanogens physiologically distinct from Methanosarcina and Methanosaeta (Ma et al. 2005), adding another element in functional diversity and parallel processing for improved process stability. Moreover, substrate overloading also increased the population diversity of Methanosaeta-related methanogens in the post-overloading methanogenic community, likely providing additional functional redundancy important for maintaining process stability under disturbance as suggested in other studies (Girvan et al. 2005).
It is noted that all the Euryarchaeota OTUs detected in the digesters had known methanogens as the closest relatives and belonged to the class Methanomicrobia (Table 2). The Crenarchaeota OTUs, however, were more phylogenetically diverse and only had close relatives of uncultured clones lacking detailed physiological characterization (Table 2). More importantly, these Crenarchaeota populations were persistent, present in both the pre-overloading and post-overloading archaeal communities (Table 2). The closest known relative to OTU 4, the most abundant Crenarchaeota group in the digesters, is Candidatus Nitrososphaera gargensis, a crenarchaeote shown to be an ammonia oxidizer in an enrichment culture (Hatzenpichler et al. 2008). Indeed, recent findings suggest the broad distribution of mesophilic Crenarchaeota and their roles in ammonia oxidation in the environment (Nicol and Schleper 2006; Gubry-Rangin et al. 2010). However, ammonia oxidation is unlikely the function of the Crenarchaeota identified in the anaerobic digesters of this study due to the lack of relevant electron acceptors. Given that Crenarchaeota were also found in other studies as abundant populations in anaerobic digestion (Godon et al. 1997; Collins et al. 2005; Zhang et al. 2011), more efforts are needed to identify their functions in anaerobic processes.
This work was partly supported by the Science Alliance – Tennessee Center of Excellence and a US Environmental Protection Agency grant SU-83431801.