Abstract
Impacts of microbial diversity and macronutrients levels (expressed as C:N and C:P ratios) on the methane production from an untreated lignocellulosic feedstock were assessed. Next-generation sequencing technology revealed the bacterial diversity of a lignocellulolytic inoculum. This inoculum comprised 75 bacterial species that were well distributed in 14 phyla, 67% of which belonged to Firmicutes and Bacteroidetes. The families Ruminococcaceae, Clostridiaceae, Bacteroidaceae, Bacillaceae, and Fibrobacteraceae comprised 46% of the identified families and were associated with hydrolytic members. Nutrient adjustment reduced 40% of the length of the lag phase and doubled methane production rate compared with a control. The highest methane production of 0.197 m3 per kg of total volatile solids observed at C:N of 31:1 and C:P of 428:1, peaked 20 days earlier than in previous studies using untreated lignocellulosic feedstock. Interestingly, the highest hydrolytic activities and solids removal rates were observed at high nitrogen contents; however, the conditions (pH > 8.0) inhibited methanogenesis.
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Characterization of a Lignocellulolytic Consortium and Methane Production from Untreated Wheat Straw: Dependence on Nitrogen and Phosphorous Content
Idania Valdez-Vazquez,a,* Gabriela J. Torres-Aguirre,b Carlos Molina,c and Graciela M. L. Ruiz-Aguilar b
Impacts of microbial diversity and macronutrients levels (expressed as C:N and C:P ratios) on the methane production from an untreated lignocellulosic feedstock were assessed. Next-generation sequencing technology revealed the bacterial diversity of a lignocellulolytic inoculum. This inoculum comprised 75 bacterial species that were well distributed in 14 phyla, 67% of which belonged to Firmicutes and Bacteroidetes. The families Ruminococcaceae, Clostridiaceae, Bacteroidaceae, Bacillaceae, and Fibrobacteraceae comprised 46% of the identified families and were associated with hydrolytic members. Nutrient adjustment reduced 40% of the length of the lag phase and doubled methane production rate compared with a control. The highest methane production of 0.197 m3 per kg of total volatile solids observed at C:N of 31:1 and C:P of 428:1, peaked 20 days earlier than in previous studies using untreated lignocellulosic feedstock. Interestingly, the highest hydrolytic activities and solids removal rates were observed at high nitrogen contents; however, the conditions (pH > 8.0) inhibited methanogenesis.
Keywords: Anaerobic digestion; Consortium; Pyrosequencing; Winter wheat (Triticum aestivum L.)
Contact information: a: Unidad Académica Juriquilla, Instituto de Ingeniería, Universidad Nacional Autónoma de México, Blvd. Juriquilla 3001, 76230 Querétaro, Mexico; b: División de Ciencias de la Vida, Universidad de Guanajuato, Irapuato, Mexico; c: División de Ciencias e Ingenierías, Universidad de Guanajuato, León, Mexico; *Corresponding author: IValdezV@iingen.unam.mx
INTRODUCTION
Anaerobic digestion (AD) transforms diverse organic wastes into a methane-rich gas, which is used worldwide for generating power. Anaerobic digestion is the most efficient technology compared with other means of energy production through biological or thermochemical routes (Gerardi 2003; Deublein and Steinhauser 2008). Thus, there are thousands of full-scale digesters worldwide, most of which are fed with industrial wastewater, food waste, animal manure, and sewage sludge (Sawatdeenarunat et al. 2015).
Recently, there has been renewed interest in the anaerobic digestion of lignocellulosic biomass (LB), primarily because of the urgent need for bioenergy to satisfy growing energy demands, to reduce the use of non-renewable fossil fuels, and to decrease CO2 emissions. Lignocellulosic biomass is a primary candidate for generating bioenergy due to its abundance and renewability (Chandra et al. 2012). In Mexico, crop wastes are the most abundantly available LB (Rios and Kaltschmitt 2013), from which wheat straw (WS) is generated with an annual output of over 2 million tons of dry matter (Valdez-Vazquez et al. 2010). With respect to its chemical composition, wheat straw is comprised of greater than 60% fermentable complex carbohydrates in the form of cellulose and hemicellulose, which bind strongly to lignin, resulting in low biodegradability (Kaparaju et al. 2009). Several physical, chemical, and biological treatments and their combinations have been applied to increase the biodegradability and conversion of lignocellulosic biomass into methane, but most methods are expensive or unfavorable for the environment (Sawatdeenarunat et al. 2015).
Anaerobic digestion is performed using many microorganisms that coexist, forming a stable, self-regulating consortium (Valdez-Vazquez and Poggi-Varaldo 2009). To obtain complete substrate conversion and a high methane yield, specialized lignocellulolytic microorganisms require the optimal nutritional balance and conditions for methanogenic activity. Macronutrients, such as nitrogen (N) and phosphorous (P), must be kept at optimal ratios with respect to carbon. A high C:N ratio indicates a deficiency in N, such that microorganisms are unable to synthesize the enzymes that are required to hydrolyze and ferment the substrate. Conversely, a low C:N ratio allows the release of ammonium ions, increasing the pH and causing toxicity in the methanogenic population (Chandra et al. 2012). The optimal C:N ratio in anaerobic digesters is between 15 and 30, depending on the substrate (Mshandete et al. 2004; Wang et al. 2012). However, the N and P contents in LB vary widely. In wheat straw, N ranges between 3.5 and 11.6 g/kg, and P varies from 0.05 to 3.5 g/kg (De et al. 2003; Contreras-Ramos et al. 2004; Kaboneka et al. 2004; Bakisgan et al. 2009; Burhenne et al. 2013; Gupta et al. 2013; Krishania et al. 2013). These variations are attributed to crop age, climate, and nutrient availability in the soil (Bonde and Rosswall 1987; Takahashi and Anwar 2007). Because of these variations, it is necessary to study the effects of N and P levels on anaerobic digestion. Thus, co-digestion with other wastes is a useful strategy to balance these macronutrients. However, first it is necessary to study the N and P requirements for methane production from single wheat straw sources in its native form, as this knowledge can improve the design of anaerobic digesters using lignocellulosic substrates alone or co-digested with other materials. This study characterized a lignocellulolytic consortium using pyrosequencing to define the microbial diversity. This microbial population was used for the direct anaerobic digestion of untreated wheat straw. The C:N and C:P ratios were optimized for methane production using a response surface methodology based on a central composite design.
EXPERIMENTAL
Inoculum and Substrate
The inoculum consisted of anaerobic sludge from a 10-m3 tubular plug flow digester fed with cow manure, the characteristics of which were previously described by Pérez-Rangel et al. (2015). Winter wheat (Triticum aestivum L.) was harvested mechanically using a cultivar (Urbina S2007) in Guanajuato, Mexico. Chopped wheat straw samples were processed as reported (Lara-Vázquez et al. 2014). Samples retained on a 3.35-mm sieve were tested. The wheat straw was washed with tap water and dried at 70 °C overnight. Components of the wheat straw on a per kilogram basis were determined according to methods previously reported (Allison 1965; Bartlett et al. 1994; Cunniff 1995; APHA 1999): 956 g of total solids, 867 g of volatile solids, 419 g of total organic carbon, 387 g of cellulose, 190 g of hemicellulose, 173 g of lignin, 4.4 g of total Kjeldahl nitrogen, 2.7 g of total P, and 86 g of ash.
DNA Extraction, Pyrosequencing, and Data Processing
Genomic DNA was extracted from 0.5 ± 1.0 mg of anaerobic sludge using the Power Soil DNA Extraction Kit® (Mo Bio Laboratories Inc., Carsbad, CA, USA), according to the manufacturer’s instructions. Genomic DNA samples were sent to the Research and Testing Laboratory Company (RTL, Lubbock, TX, USA) for 16S rRNA gene amplification and pyrosequencing. The V1 to V3 region of the bacterial 16S rRNA gene was amplified with the primers 28F and 519R and subsequently sequenced at RTL (Dowd et al. 2008). Short and singleton sequences, noisy reads, and chimeric sequences were removed using the USEARCH algorithm and UCHIME software (drive5.com/index.htm) executed in de novo mode (Edgar 2010; Edgar et al. 2011). The minimum sequence length was 250 base pairs with a quality score of greater than 30. Operational taxonomic units (OTUs) were selected using the UPARSE algorithm (Edgar 2013). The USEARCH global alignment algorithm was used to assign the taxonomic identity for each of the OTUs against the RTL database of high quality sequences derived from the NCBI database (http://www.ncbi.nlm.nih.gov). Pyrosequencing results were displayed as KRONA charts by using the RTL server.
Optimization of C:N and C:P Ratios for Methane Production
Batch reactors were run in 120-mL serological bottles with a working volume of 100 mL. The reactors were loaded with 20 mL of inoculum and 5.0 ± 0.1 g of untreated wheat straw in an inoculum to substrate volatile solid ratio of 0.2 to 1.0. N- and P-free mineral medium was used to charge the reactors (composition in grams per liter: NaHCO3, 10; MgCl2, 0.1; CaCl2, 0.020; MnSO4, 0.015; FeSO4, 0.025; CuSO4, 0.005; CaCl2, 0.000125). The initial pH was adjusted to 7.0, and the batch reactors were incubated statically at 37 °C for 30 days.
To maximize the biogas and methane production, the C:N and C:P ratios were studied as independent variables and adjusted per response surface methodology (RSM) using a central composite design. The C:N and C:P ratios were adjusted with urea and potassium phosphate monobasic, respectively. The N and P contents in the wheat straw were not considered in the adjustment since the availability of such nutrients was unknown, and it could be affected by factors not considered in this study (Soon and Arshad 2002). The biogas and methane yields, total volatile solid removal, final pH, and enzymatic activity were the dependent output responses. The experiments were performed in three replicates for the factorial and axial points and in five replicates for the central points to account for the nonadjustable data and to allow calculations viaanalysis of variance (ANOVA). The factors and levels of independent input variables are shown in Table 1.
Table 1. Levels of Factors Selected for the Central Composite Design
To determine the endogenous methane production, two control treatments were used: control 1) with inoculum, N- and P-free mineral medium, and wheat straw, and control 2) with inoculum and N- and P-free mineral medium without straw. The relationship between the response output variables and the independent variables was expressed using a second-degree quadratic polynomial equation (Box et al. 1978). The analysis of the response surface, ANOVA results, and optimal conditions were performed using Design Expert 8.0.7.1® (Stat-Ease Inc., Minneapolis, MN). The significant effects on dependent variables were determined using a t-test, with a probability value (p-value) of less than 0.05.
Analytical Methods
Biogas accumulation was measured periodically using the displacement of a lubricated syringe. Biogas composition (H2, O2, N2, CO2, and CH4) was analyzed by gas chromatography on a Clarus 580 GC System (Perkin-Elmer, Waltham, MA), equipped with a thermal conductivity detector and a Molsieve column (30 m x 0.53 mm). The following program was run: oven 50 to 100 °C at a rate of 7 °C/min. The injector and detector temperatures were 150 and 200 °C, respectively. The total volatile solids (TVS) and pH were determined according to standard methods (APHA 1999). The cellulase activity (IU/mL) was determined in the reactor supernatants according to methods by Mandels and Weber (1969). For this enzyme assay, the controls included supernatant without substrate and substrate without supernatant.
RESULTS AND DISCUSSION
Taxonomic Composition of the Lignocellulolytic Consortium
Figure 1 shows the taxonomic composition and abundance of bacteria in the lignocellulolytic inoculum. A total of 9,987 sequences were obtained and compared with the database, and 36% of the sequences could not be taxonomically identified. The lack of knowledge of these species could be related to difficulties in their cultivation and study. Complementary studies are required to identify them and to establish their role in the microbial community. From the sequences with taxonomical affiliation, the anaerobic sludge comprised 14 phyla, of which Firmicutes and Bacteroidetes represented 67% of the inoculum.
Fig. 1. Taxonomic classification and abundance of lignocellulolytic bacterial phyla
The distribution and abundance of the identified families revealed a well-balanced bacterial population (Fig. 2). Members of the families Ruminococcaceae (Latham and Wolin 1977), Clostridiaceae (Sleat et al. 1984), Bacteroidaceae (Murray et al. 1984), Bacillaceae (Robson and Chambliss 1984), and Fibrobacteraceae (Stewart and Flint 1989) are relevant hydrolytic species in anaerobic environments, with the potential for solubilizing lignocellulosic substrates.
Fig. 2. Taxonomic classification and abundance of lignocellulolytic bacteria at the family level
Optimization of C:N and C:P Ratios for CH4 Production from Wheat Straw
Kinetic behavior
Batch digesters produced biogas for 30 days to determine the methane potential from direct anaerobic digestion of a single untreated wheat straw sample. Representative treatments were characterized with regard to kinetic behaviors including biogas production, methane content, and the methane production in the digesters for the central points of the central composite design (C:N 101:1 and C:P 253:1). The results are shown with respect to conditions offering the best performance (C:N 31:1 and C:P 428:1), those that performed worst (C:N 2:1 and C:P 253:1), and the control 1 (with inoculum and wheat straw but without N or P adjustments) (Fig. 3). The control 2 (self-digestion of the inoculum) had a negligible biogas accumulation in the whole incubation time without methane content. For all of the treatments (except for C:N 2:1 and C:P 253:1), the biogas production by day 30 remained in the log phase, meaning that more time was required to attain complete digestion of the untreated wheat straw. However, the methane content had stabilized at 63% to 70% by day 14 in the digesters (C:N 31:1 and C:P 428:1) and by day 20 for the other treatments. Digesters with the highest N content (C:N 2:1 and C:P 253:1) showed erratic behavior between replicates, which was attributed to disrupted microbial activity. For example, some had high methane content before the other treatments (ranging from 23% to 63%). However, the high N level inhibited the biological process, resulting in low biogas production (320 mL/L) and, consequently, the lowest methane potential. The methane production was highly dependent on the N and P supplements. At C:N 31:1 and C:P 428:1, the lag phase declined from 10 to 6 days, and the methane potential rose from 0.091 to 0.197 m3/kg TVS compared with the control treatment. When N and P were added in excess, methane production was nearly completely inhibited.
Fig. 3. Kinetic behavior of the direct anaerobic digestion of single untreated wheat straw with adjustment of the C:N and C:P ratios. Treatments: C:N 101:1 and C:P 253:1 (◆), C:N 31:1 and C:P 428:1 (▲), C:N 2:1 and C:P 253:1 (), and control 1 (■). Results are average measurements based on three replicates for the treatment (n = 3) and five replicates for the central points (n = 5). The errors bars represent the standard deviation of the measurements.
Methane production
Table 2 shows the average values of methane production for each treatment. ANOVA showed that the C:N and C:P ratios had a highly significant effect on this dependent response (p < 0.0001). For methane production (m3/kg TVS), regression analysis generated the following quadratic equation (in terms of coded factors):
Ln (CH4 production) = – 2.18 + 0.96 X1 + 0.75 X2 – 1.13 X1X2 – 0.89 X12 – 0.15 X22 (1)
The regression equation had an R2 value of 0.86, consistent with the adjusted R2 of 0.83 (R2 > 0.75 indicates the aptness of the model), ensuring adequate adjustment of the experimental data to the quadratic model. The significant model terms were X1, X2, X1X2, and X12 (p < 0.0001). The regression analysis of the model (Eq. 1) predicts a maximum methane potential of 0.27 m3/kg TVSadded at C:N ratio of 76:1 and a C:P ratio of 500:1 after 30 days of incubation.
Figure 4a shows the response surface and contour plots of the methane production as a function of the C:N and C:P ratios. In addition to the peak of methane production, a longitudinal crest is visible. Here, higher methane production was attained beginning from the peak until C:N 200:1 and C:P 5:1, at which point the methane production was 0.18 m3/kg TVSadded.
Total volatile solid removal
Table 2 shows the average TVS removal in the treatments and control. ANOVA showed that only the C:P ratio had a significant effect on this response variable (p < 0.0001). For TVS removal (%), the regression analysis generated the following equation (in terms of coded factors):
TVS removal = 21.72 + 0.21 X1 + 6.58 X2 – 4.01 X1X2 (2)
The regression equation had an R2 value of 0.84, which agreed reasonably with the adjusted R2 of 0.81, ensuring adequate adjustment of the experimental data to the model. The significant model terms were X2 and X1 X2 (p < 0.0001 and p < 0.01, respectively). Figure 4b shows the response surface and contour plot of TVS removal as a function of the C:N and C:P ratios. Notably, greater substrate consumption was reached when the C:P ratio was greater than 370:1 and C:N ratio greater than 101:1.
Cellulase activity
Table 2 shows the average cellulase activity in the supernatants of the treatments and control. By ANOVA, only C:N ratio had a significant effect on this response (p < 0.0001). For enzyme activity (IU/mL), the regression analysis generated the following equation (in terms of coded factors):
Cellulase activity = 0.41 – 0.16 X1 + 0.06 X2 – 0.01 X1X2 + 0.16 X12 + 0.02 X22 (3)
The regression equation had an R2 value of 0.86, which is in reasonable agreement with the adjusted R2 of 0.81. The significant model terms were X1 and X12 (p < 0.0001). Figure 4c shows the response surface and contour plot of the cellulase activity as a function of the C:N and C:P ratios. Higher enzymatic activities were consistent with the C:N and C:P levels at which greater substrate consumption occurred (low C:N ratio and high C:P ratio).
Table 2. Experimental and Predicted Results of the Central Composite Design for Methane Production, Total Volatile Solid Removal, Cellulase Activity, and Final pH
Fig. 4. Response surface and contour plots of (a) methane production (m3/kg TVS), (b) total volatile solid removal (%), (c) cellulase activity (IU/mL) and (d) final pH as function of the C:N and C:P ratios from the anaerobic digestion of single wheat straw
Final pH
The final pH values after 30 days of anaerobic digestion of single, untreated wheat straw specimens are shown in Table 2. By ANOVA, only C:N ratio influenced this response (p < 0.0001). The regression analysis generated the following quadratic equation (in terms of coded factors):
Final pH = 6.59 – 0.5 X1 + 0.07 X2 – 0.06 X1X2 + 0.45 X12 – 0.33 X22 (4)
The R2 value of 0.77, versus the adjusted R2 of 0.72, ensured acceptable adjustment of the experimental data with the quadratic model. Two terms, X1 and X1X2, were the most significant (p< 0.001). As shown in Fig. 4d, the pH exceeded 7.5 when the C:N ratio was greater than 30:1, wherein the treatment with C:N 2 and C:P 253 had a final pH of 8.8.
Of the various types of lignocellulosic substrate, wheat straw is one of the most recalcitrant to biological transformation (Sharma et al. 1988; Gunaseelan 1997; Liew et al. 2012). The methane production that typically occurs with untreated wheat straw ranges from 0.067 to 0.249 m3/kg TVS, and greater production requires thermophilic incubation temperatures and conversion times of greater than 100 days (Table 3). Here, we examined a broad range of C:N and C:P ratios in the AD of untreated wheat straw to determine beneficial and inhibitory levels.
The optimal nutrient adjustment showed advantages in several ways. The microbial activity behaved better when nutrients were added than without nutrient balancing, thus the length of lag phase diminished by 40% (Fig. 3), and the methane production rate doubled to 0.006 m3/kg TVS-d. As a result, the potential and productivity of methane production well exceeded the results of other studies using untreated wheat straw (Table 3). Indeed, methane production approximates the potential under a thermophilic range but was four times faster.
Table 3. Biochemical Methane Potential from Single, Untreated Wheat Straw
Conversely, high N levels exhibited an inhibitory effect on the methanogenic activity, a phenomenon that is well known (Rajagopal et al. 2013). However, the hydrolytic bacterial activity and TVS removal reached its highest values in these conditions. Many hydrolytic enzymes from members of the families identified in our lignocellulolytic inoculum show high stability at basic pH. Examples include Ruminococcus (Ohmiya et al. 1982), Clostridium (Song et al. 1985), and Bacteroides (Huang et al. 1988). It seems that despite having no growth, the hydrolytic enzymes remained active in the treatment with high N and P levels (treatment at C:N 2:1 and C:P 253:1; Fig. 3), resulting in substrate degradation. When the ammonia levels became inhibitory to the methanogens, biogas production stopped, but hydrolytic activity and solid removal continued.
Activities of diverse microbial groups (hydrolytic and fermentative micro-organisms as well as methanogens) should be coordinated to degrade lignocellulosic biomass ending up in a CH4-rich biogas. This study presents different response variables, revealing deeper information about the process. In this way, methane production, cellulase activity, and pH responded differently to the N levels. First, a C:N ratio of 2:1 promoted the highest hydrolytic activity, but the basic pH stopped the methanogenic activity. Then, at a C:N ratio of 31, the reactors produced the highest observed value of 0.197 m3/kg TVSadded in agreement with guidelines for anaerobic digesters (Deublein and Steinhauser 2008). In fact, the observed value doubled the predicted value. This fact could be related to the favorable conditions for expression and activity of hydrolytic enzymes besides an adequate pH of 6.8 for the growth of methanogens (Table 2). After, at a C:N ratio of 101, the observed value was 40% lower than the predicted value. Under such conditions, the hydrolytic activity diminished but above all an acidic pH of 6.3 could be the primary factor detrimental to the methanogens. By Eq. 1, the model predicted the highest methane production of 0.270 m3/kg TVSadded at a C:N ratio of 76. However, it seems that a cellulase activity ~ 0.8 IU/mL and a pH ~ 7.0 will be the prerequisites to achieve this methane potential.
Hydrolytic bacteria present in the inoculum such as Ruminococcus, Clostridium, and Bacteroidesbehaved better at high N levels (C:N ratio of 2 and 31) at both neutral or basic pH, which is justified by their requirements for enzyme synthesis. Contrary to this, methanogen activity was maximized at C:N ratios between 31 to 101 but at pH strictly between 6.8 and 7.3. As a result, predicted and observed values of methane production showed discrepancies if these conditions were not satisfied. A better knowledge of the requirements of microbial diversity and nutrients for the direct conversion of lignocellulosic feedstock into biomethane will lead to modern digesters with robust hydrolytic capacities. The solid retention times will be decreased and, therefore, the size and cost of such facilities. The results presented here demonstrate that an adequate inoculum and the optimal nutrient levels improved the performance of methane production from an untreated lignocellulosic feedstock.
CONCLUSIONS
- The anaerobic sludge used as the inoculum comprised at least 46% of members belonging to the Ruminococcaceae, Clostridiaceae, Bacteroidaceae, Bacillaceae, and Fibrobacteraceae families, which participate in the solubilization of lignocellulosic biomass.
- Nitrogen and phosphorus adjustments for the direct conversion of untreated wheat straw into biomethane accelerated the exponential phase and doubled the methane productivity compared with a control without macronutrient additions.
- The maximum methane production of 0.197 m3/kg TVSadded was observed at a C:N ratio of 76:1 and C:P ratio of 500:1 and was three times higher than the control treatment.
- The highest C:N ratio of 2:1 stimulated hydrolytic activity and solid removal but led to a pH of greater than 8.0, which inhibited methanogenic activity.
ACKNOWLEDGMENTS
G. J. T.-A. is grateful for the CONACYT scholarship. The authors thank Dr. Arturo Sanchez, CINVESTAV, Guadalajara, for help with the Design Expert software and data analysis. The authors are grateful to Jaime Perez for the technical support. Financial support was received from CONACYT projects (Grant No. 168921 and 188432).
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Article submitted: September 15, 2015; Peer review completed: December 19, 2015; Revised version received: January 13, 2016; Accepted: January 14, 2016; Published: March 24, 2016.
DOI: 10.15376/biores.11.2.4237-4251