- Open Access
Increasing the economic value of lignocellulosic stillage through medium-chain fatty acid production
© The Author(s) 2018
- Received: 5 February 2018
- Accepted: 6 July 2018
- Published: 19 July 2018
Lignocellulosic biomass is seen as an abundant renewable source of liquid fuels and chemicals that are currently derived from petroleum. When lignocellulosic biomass is used for ethanol production, the resulting liquid residue (stillage) contains large amounts of organic material that could be further transformed into recoverable bioproducts, thus enhancing the economics of the biorefinery.
Here we test the hypothesis that a bacterial community could transform the organics in stillage into valuable bioproducts. We demonstrate the ability of this microbiome to convert stillage organics into medium-chain fatty acids (MCFAs), identify the predominant community members, and perform a technoeconomic analysis of recovering MCFAs as co-products of ethanol production. Steady-state operation of a stillage-fed bioreactor showed that 18% of the organic matter in stillage was converted to MCFAs. Xylose and complex carbohydrates were the primary substrates transformed. During the MCFA production period, the five major genera represented more than 95% of the community, including Lactobacillus, Roseburia, Atopobium, Olsenella, and Pseudoramibacter. To assess the potential benefits of producing MCFAs from stillage, we modeled the economics of ethanol and MCFA co-production, at MCFA productivities observed during reactor operation.
The analysis predicts that production of MCFAs, ethanol, and electricity could reduce the minimum ethanol selling price from $2.15 to $1.76 gal−1 ($2.68 gal−1 gasoline equivalents) when compared to a lignocellulosic biorefinery that produces only ethanol and electricity.
- Medium-chain fatty acids
- Mixed culture fermentation
- Carboxylate platform
- Chain elongation
The production of food, fuels, pharmaceuticals and many chemicals depends on microbial fermentations. When one considers the sum of microbial biomass, excreted metabolic end-products, and non-metabolized nutrients, there is considerable residual organic matter in the liquid residue (stillage) remaining after distillation. One common co-product of ethanol production is biogas, which is generated by anaerobic digestion of stillage. Combusting lignin and biogas creates heat and power used to operate the biorefinery, and any excess electricity can be sold as a co-product . In a techno-economic analysis (TEA) conducted by the National Renewable Energy Laboratory (NREL), a 61 million gallon per year lignocellulosic ethanol biorefinery produced fuel at a price of $2.15 gal−1 ($3.27 gal−1 gasoline-equivalents) and electricity worth $6.57 million year−1 .
The Renewable Fuel Standards (RFS), created by the Energy Policy Act of 2005 and expanded by the Energy Independence and Security Act of 2007, set production goals for many renewable energy sources, including lignocellulosic-derived ethanol [3, 4]. While several lignocellulosic biorefineries have been opened, total lignocellulosic ethanol production in the United States remains short of original targets. The high costs of obtaining biomass and producing enzymes to hydrolyze biomass are cited as barriers to achieving an acceptable level of profitability for lignocellulosic biorefineries .
One way to potentially improve the economics of lignocellulosic fuel production is to produce valuable co-products, such as medium-chain fatty acid (MCFA), from stillage. MCFAs are monocarboxylic acids containing six to twelve carbon atoms and are utilized for the production of rubbers, dyes, pharmaceuticals, and antimicrobials . They can also be used as precursors for chemicals currently derived from fossil fuels . In addition to being valuable, MCFAs also have decreased solubility compared to short-chain fatty acids (SCFA), which should allow for easier extraction from an aqueous medium.
In this study, we investigated the valorization of switchgrass-derived stillage to MCFAs. Switchgrass has been identified as a promising feedstock for biofuel production that can be cultivated on marginal lands . In this study, we tested the ability of using mixed culture anaerobic fermentation, as in the so-called carboxylate platform [8, 9], to valorize stillage to MCFAs. Here MCFA is the sum of hexanoate and octanoate since it is still largely unknown how to direct metabolism to production of only one MCFA. In several past studies, ethanol has been utilized as an electron donor to drive MCFA production from either added acetate or acetate produced by the community as a fermentation intermediate [10–13]. Conversion of lactic acid to MCFA has also been investigated [14, 15]. Recently, a pure culture of Megasphaera elsdenii was used to convert glucose in lignocellulosic hydrolysate to MCFAs . Stillage from corn-derived ethanol has also been used to produce MCFAs . Andersen et al. utilized a mixture of lignocellulosic stillage and dilute ethanol to produce MCFAs at titers greater than their solubility concentrations . However, MCFA production from industrial streams having minimal amounts of glucose or ethanol remains largely unexplored. In addition, there is no published TEA investigating production of MCFAs from stillage.
Switchgrass stillage production
Shawnee switchgrass, grown in 2010 at the Arlington Agricultural Research Center in Wisconsin, USA, was used as the biomass source for this study. Switchgrass was treated using ammonia-fiber expansion (AFEX), enzymatically hydrolyzed, and fermented, as described previously . During processing, hydrolysate is filtered to remove insoluble components, including insoluble lignin. Past work has demonstrated that switchgrass hydrolysates generated with this process contain sufficient nutrients and trace elements to sustain microbial growth . Ethanol fermentations of switchgrass hydrolysate were performed with Saccharomyces cerevisiae Y128, an engineered yeast strain with improved xylose utilization and lignotoxin tolerance . Ethanol was removed post-fermentation using a glass distillation apparatus consisting of a 1-L boiling flask, heating mantle, distillation column, and condenser. During distillation, the fermented hydrolysate was heated to approximately 100 °C to maintain a distillation neck temperature of 78 °C. Therefore, the distillation process not only removed ethanol but also sterilized the stillage. The stillage remaining after distillation was stored at 4 °C until fed to the bioreactor.
Mixed culture fermentation bioreactor
A mixed culture fermentation bioreactor was inoculated with sludge from an acid-phase digester at the Nine Springs Wastewater Treatment Plant in Madison, Wisconsin. The bench-scale reactor consisted of a vessel with a 150-mL working volume that was continuously stirred at 150 rpm with a magnetic stir bar and maintained at 35 °C using a water bath. The reactor was sealed with a rubber stopper and vented so that any gas produced was released to the atmosphere. For all experiments, the solid retention time (SRT) is equal to the hydraulic retention time.
Initially, we conducted short-term (6 day) experiments to assess if microbial growth could be sustained in stillage and to determine the primary fermentation end products under different pH conditions. For these initial experiments, the pH was either uncontrolled or controlled at set points of 5.0, 5.5, 6.0, or 6.5 with 5 M KOH. A hydraulic retention time of 2 days was utilized for these initial experiments by pumping 75 mL day−1 (3.13 mL h−1) both into and out of the reactor. A shorter SRT was utilized to allow for fast turnover and stabilization of the microbial community. While this short SRT resulted in production of MCFAs, we elected to increase the SRT for a long-term experiment in an attempt to improve overall MCFA titers. For the long-term (252 day) sustained experiment, the pH was controlled at a set point of 5.50 with 5 M KOH and the SRT was controlled at 6 days by pumping 25 mL day−1 (1.04 mL h−1) into and out of the reactor.
We collected samples from the reactor and stillage for chemical analyses. All samples were filtered using 0.22-μm syringe filters (ThermoFisher Scientific SLGP033RS, Waltham, MA, USA). Soluble chemical oxygen demand (COD) analysis was performed using High-Range COD Digestion Vials (Hach 2125915, Loveland, CO, USA) as per standard methods . Soluble carbohydrates were measured with the anthrone method . Total soluble proteins were measured with the bicinchoninic acid assay using the Pierce™ BCA Assay Kit (ThermoFisher Scientific 23225, Waltham, MA, USA) and the Compat-Able™ Protein Assay Preparation Reagent Set (ThermoFisher Scientific 23215, Waltham, MA, USA) .
Glucose, xylose, acetic acid, formic acid, lactic acid, succinic acid, pyruvic acid, glycerol and xylitol were analyzed with high-performance liquid chromatography (HPLC) and quantified with an Agilent 1260 Infinity refractive index detector (Agilent Technologies, Inc. Palo Alto, CA) using a 300 × 7.8 mm Bio-Rad Aminex HPX-87H column with Cation-H guard (BioRad, Inc., Hercules, CA). A column temperature of 50 °C was used and 0.02 N H2SO4 was used for the mobile phase with a flow rate of 0.50 mL min−1.
Acetamide, ethanol, n-propionic acid, n-butyric acid, iso-butyric acid, n-pentanoic acid, iso-pentanoic acid, n-hexanoic acid, iso-hexanoic acid, n-heptanoic acid, and n-octanoic acid were analyzed with tandem gas chromatography–mass spectrometry (GC–MS). An Agilent 7890A GC system (Agilent Technologies, Inc. Palo Alto, CA) with a 0.25-mm Restek Stabilwax DA 30 column (Restek 11008, Belefonte, PA) was used. The GC–MS system was equipped with a Gerstel MPS2 (Gerstel, Inc. Baltimore, MD) autosampler and a solid-phase micro-extraction gray hub fiber assembly (Supelco, Bellefonte, PA). The MS detector was a Pegasus 4D TOF–MS (Leco Corp., Saint Joseph, MI). Stable isotope-labeled internal standards were used for each of the analytes measured with GC–MS.
Aromatic compounds were analyzed with liquid chromatography–tandem mass spectrophotometry (LC–MS/MS). For LC–MS/MS analyses, an Ultimate HPG-3400RS pump and WPS-3000RS autosampler (ThermoFisher) were mated to an ACQUITY UPLC HSS T3 reversed-phase column (2.1 × 150 mm, 1.8 μm particle diameter, Waters Corporation) with a guard cartridge. Gradient elution was performed at 0.400 mL min−1. The LC system was coupled to a TSQ Quantiva Triple Quadrupole mass spectrometer (Thermo Scientific). The Ion Transfer Tub Temp was kept at 350 °C as was the vaporizer temperature. Analytes measured with LC–MS/MS included vanillamide, 4-hydroxybenzyl alcohol, syringamide, coumaryl amide, 4-hydroxybenzoic acid, feruloyl amide, vanillic acid, p-coumaric acid, ferulic acid, and benzoic acid. Detailed chemical analysis data are provided in Additional file 1.
Microbial community analysis
Amplification and sequencing of the V3–V4 region of the 16S rRNA gene were performed to classify and determine the relative abundance of bacteria in the reactor. For the initial short-term (6 day) experiments, biomass samples were collected from the inoculum acid digester sludge and from the reactor every 2 days for 6 days. For the long-term (252 day) experiment, biomass samples were collected from the inoculum acid digester sludge and from the reactor at days 2, 4, and 6, and then every 6 days for the duration of the experiment. Biomass was harvested by centrifuging samples at a relative centrifugal force of 10,000g for 10 min and decanting supernatant. Biomass was then stored at − 80 °C until DNA extraction was performed.
DNA was extracted using a Power Soil® DNA Isolation Kit (MoBIO Laboratories 12888, Carlsbad, CA). The purity of extracted DNA was analyzed using a NanoDrop spectrophotometer (Thermo Fisher Scientific ND-2000, Waltham, MA), and DNA was quantified using a Qubit 3.0 (Thermo Fisher Scientific Q33126, Waltham, MA). The V3 and V4 regions of the 16S rRNA gene were amplified using the primer set S-D-Bact-0341-b-S-17/S-D-Bact-1061-a-A-17 as described by Klindworth et al. . Amplicons were sequenced on an Illumina MiSeq sequencer (Illumina, San Diego, CA) using pair-end 250 base pair kits at the University of Wisconsin-Madison Biotechnology Center.
Paired-end reads were merged with Fast Length Adjustment of Short Reads (FLASH) using default parameters . The merged reads were analyzed with the Qiime pipeline, utilizing the split libraries command to remove low-quality sequences . Sequences were clustered into operational taxonomic units (OTUs) using uclust . Sequences were aligned with PyNast, and chimera detection was performed with ChimeraSlayer [28, 29]. Singleton OTUs were removed, and the samples were rarefied to an equal depth, with 130,000 sequences retained for the long-term (252 day) reactor experiment and 45,000 sequences retained for the short-term (6 day) reactor experiments. A representative sequence for each OTU was taxonomically classified using the SILVA database . Tables of OTUs with taxonomic assignments are provided in Additional file 2. The Phyloseq package version 1.14.0 was used for data visualization and heat maps were generated with the superheat package [31, 32]. To construct phylogenetic trees, multiple sequence alignments were performed using MUSCLE, and maximum-likelihood phylogenetic trees were constructed with RAxML using the GTRGAMMA method with 1000 bootstraps [33, 34].
Statistical analysis of microbial community data was performed using multivariate repeated measures ANOVA with the nlme package in R to generate generalized least square models in which time was correlated to all predictor variables using the corAR1 structure . Redundancy analysis was also performed using the rda command in the vegan package . Environmental factors were iteratively selected until all were statistically significant (p < 0.1) based on 999 model permutations.
To estimate the economic impact of producing MCFAs from ethanol stillage, a TEA was performed based on information provided in the National Renewable Energy Laboratory (NREL) TEA for a 61 million gallon per year lignocellulosic ethanol facility . We assumed that switchgrass has a similar feedstock cost to corn stover ($58.50 U.S. dry ton−1), which is within the range of costs assumed for switchgrass feedstock in other studies [37, 38]. Instead of assuming all stillage undergoes anaerobic digestion, we assumed that a portion of the organic matter was converted to organic acids using data obtained in this study and then simulated the extraction of hexanoic and octanoic acids with ASPEN (AspenTech, Bedford, MA) to select an organic solvent and determine process separation efficiencies, heating demands, and sizes for reactors and equipment. We selected 2-octanol as the solvent for liquid–liquid extraction due to the high extraction efficiencies predicted with ASPEN. We assumed that the organic matter in the aqueous phase that remains after extracting the MCFAs was fed to the anaerobic digester to produce biogas. The specific methane yield (g methane produced per g COD consumed) and biosolid yield (g biomass produced per g COD consumed) were assumed to be the same as in the NREL TEA . The efficiency of combined heat and power generation by combusting biogas, lignin, and biosolids was also assumed to have the same efficiency as the NREL TEA, with a total of 21% of the energy in the combusted material converted to usable heat and power .
The costs for additional reactors and distillation columns were estimated by scaling-related costs presented in the NREL TEA . Costs for the liquid–liquid extraction were determined based on the volumetric flow rate and equations available in Seider et al. . The KOH usage was calculated based on experimental reactor data. The 2-octanol demand (2-octanol lost to the aqueous phase) was based on modeling the liquid–liquid extraction with ASPEN. Prices for hexanoic acid, octanoic acid and 2-octanol were obtained from Zauba for imported quantities greater than 1000 kg in 2016 (Additional file 3) . For consistency with past reporting, all costs and profits are reported in 2007 United States Dollars (USD). To convert from 2016 to 2007 USD, cost indices from the St. Louis Federal Reserve were used . Electricity prices from the NREL TEA were used . A 30-year cash flow was calculated using the cash-flow calculation tool available with the NREL TEA , and the minimum ethanol selling price (MESP) was determined by setting the net present value to zero based on a target 10% internal rate of return, consistent with the NREL TEA . Detailed information related to the TEA is provided in Additional file 3.
Unless otherwise noted, we report concentrations as mass of COD per unit volume. This allows for the direct comparison of relative reducing equivalents contained within each of the compounds consumed and created. The theoretical COD of each compound, or the theoretical amount of oxygen needed to fully oxidize the compound, was used to convert the measured mass units to COD. Protein was assumed to have 1.5 g COD per g of protein, which is consistent with the COD of albumin. A COD of 1.06 g COD per g carbohydrate was used to convert total carbohydrates measured with the anthrone method to COD. This value is consistent with the COD of glucose and xylose. The “Unknown COD” represents the measured COD minus the COD of known components. Where provided, error bars represent standard deviation of technical replicates. The “COD Removed” is calculated as the percentage of COD removed at each time point. “Conversion of Carbohydrates” is calculated based on the difference between total carbohydrates in the switchgrass stillage and the reactor sample for each time point. “Conversion to SCFA” is based on the amount of COD converted to carboxylic acids containing two to five carbons, and “Conversion to MCFA” is based on the COD converted to monocarboxylic acids containing six to eight carbons.
Chemical analyses of switchgrass stillage
Major chemical components contained within hydrolysate and fermented hydrolysate after fermentation with Saccharomyces cerevisiae Y128
56,000 ± 300
44 ± 1.7
36,000 ± 230
19,000 ± 4500
310 ± 0.86
2500 ± 130
2065 ± 30
1600 ± 68
51,000 ± 2900
Composition of major organic matter components and aromatic compounds in the two batches of stillage fed to the mixed culture fermentation bioreactor
Stillage batch 1
Stillage batch 2
Major stillage components (mg COD L−1)
95,400 ± 432
95,800 ± 982
38,300 ± 3250
42,100 ± 3190
20,800 ± 148
20,900 ± 168
19,300 ± 2310
15,500 ± 2230
4030 ± 270
4200 ± 340
3900 ± 32.1
3920 ± 36.3
2550 ± 21.1
2580 ± 20.5
2200 ± 145
1910 ± 162
1220 ± 305
1590 ± 161
Aromatic compounds (μg COD L−1)
13,000 ± 250
5400 ± 200
12,000 ± 130
3200 ± 83
3500 ± 43
1100 ± 34
1700 ± 102
2000 ± 22
290 ± 0.95
230 ± 0.50
380 ± 15
320 ± 0.46
320 ± 0.09
370 ± 4.6
250 ± 13
90 ± 3.2
240 ± 3.7
110 ± 1.9
230 ± 0.06
138 ± 2.3
While major COD components between the two batches of stillage were similar, the aromatic compounds, including known lignotoxins [19, 44], varied between the stillage batches (Table 2). Feruloyl amide, p-coumaroyl amide, and coumaric acid were higher in batch 1 than in batch 2. Only benzoic acid and vanillic acid were higher in batch 2. From a reducing-equivalent standpoint, these aromatic compounds account for less than 0.05% of the COD in stillage, but these concentrations are within the range of lignotoxins shown to inhibit fermentation activity by pure cultures of ethanologenic organisms .
Stillage fermentation under different pH conditions
Due to the relatively low concentration of six-carbon sugars, the complexity of remaining organic materials, and the potential toxicity of aromatic compounds, bacterial growth on stillage derived from AFEX-treated hydrolysate was expected to be challenging. We, therefore, conducted short-term experiments to determine if a microbial community could metabolize organic materials remaining in stillage. Using inoculum from an acid-phase anaerobic digester, we fermented stillage at different pH conditions (uncontrolled, 5.0, 5.5, 6.0, and 6.5) for 6 days utilizing a SRT of 2 days and analyzed both the extracellular end products and the microbial community. Acid-phase digester sludge was used as inoculum because the microbial consortia were expected to contain a variety of fermenting organisms and not expected to contain high levels of methanogens [45, 46].
Conditions in which the pH was uncontrolled led to the pH stabilizing at 3.6 and accumulation of lactic and acetic acids (Additional file 4). SCFA accumulated in the reactor when the pH was maintained between 5.0 and 6.5. Maintaining a pH of 5.5 resulted in the highest accumulation of MCFAs (Additional file 4). Analysis of the microbial community by 16S rRNA gene sequencing showed variations in composition with pH (Additional file 5), with OTUs associated with the genera Lactobacillus (89.9%) and Acetobacter (9.9%) becoming the most abundant when the pH was uncontrolled. Lactobacillus was present in the reactors at all pH conditions. At pH 5.0, Megasphaera was enriched (46.3%), while at pH 5.5, OTUs related to Pseudoramibacter (14.3%) and Olsenella (14.1%) were abundant. At pH 6.0, Mitsuokella (20.8%), Acetitomaculum (17.0%), and Megasphaera (14.2%) were all abundant. When the reactor was maintained at pH 6.5, more OTUs related to the Bacteroidetes phylum were abundant, including OTUs related to the genera Prevotella (12.3%) and Bacteroides (40.8%).
These results demonstrated that a community derived from an acid digester sludge inoculum could ferment stillage to carboxylic acids, including MCFAs, under a variety of pH conditions. Further, organisms identified in the stillage-fed reactors included members of the Clostridia (Megasphaera, Pseudoramibacter) that have previously been associated with MCFA production [5, 10, 13, 15, 18, 47]. Members of Clostridia have been enriched in other MCFA-producing bioreactors under similar pH conditions [12, 18, 48]. In agreement with our observation of Lactobacillus at all pH conditions, Lactobacillus is a common genus in MCFA-producing microbiomes [10, 15, 17, 18, 47]. In total, the fermentation product (Additional file 4) and community (Additional file 5) data confirmed that materials in stillage could be converted to MCFAs by a microbial community originating from a full-scale wastewater treatment plant acid digester.
Sustained MCFA production from switchgrass stillage
Microbial community analysis
After extended operation, we found that the community composition stabilized and was dominated by organisms from five genera, including three Firmicutes (Lactobacillus, Pseudoramibacter and Roseburia) and two Actinobacteria (Olsenella and Atopobium). At later time points (Day 30–Day 252), the OTUs corresponding to these five genera accounted for greater than 95% of the total 16S rRNA gene sequences (Fig. 3). The relative abundance of Pseudoramibacter (p = 0.0045), Lactobacillus (p = 0.0022), and Olsenella (p = 0.014) all correlated with the period of increased MCFA production. Neither Roseburia (p = 0.147) nor Atopobium (p = 0.546) are significantly correlated to increased MCFA production.
The two OTUs within the Actinobacteria phylum, denovo9132 and denovo107219, clustered with members of the Atopobium and Olsenella genera, respectively (Fig. 4), in the Coriobacteriaceae family. Several Atopobium and Olsenella species have been shown to consume carbohydrates and produce lactic acid [59–62]. The most abundant OTU at 252 days of reactor operation (denovo27808) clustered with Roseburia, which are known to utilize carbohydrates and acetic acid and produce butyric and lactic acids [63–65]. Another high-abundance OTU identified in the microbial community (denovo6337) clustered with Pseudoramibacter alactolyticus (previously Eubacterium alactolyticum), a bacterium that has been described as producing hexanoate and octanoate from lactic acid and glucose .
Starting at Day 120, the feed changed from stillage batch 1 to stillage batch 2, which contained lower concentrations of aromatic compounds (Table 2). While initial changes in community compositions occurred (Fig. 3), with an increase in Atopobium and decrease in Roseburia, the major genera remained consistent and the community eventually re-stabilized. This initial change in stillage feed source coincided with a reduction in xylose utilization (Fig. 2); however, xylose utilization eventually increased and overall MCFA production was not impacted by this change in the stillage source (p = 0.415).
Overall, the bacterial community results indicate that a stable fermenting community containing only five genera was enriched from the acid-digester sludge inoculum during growth on stillage. We suspect that Clostridia-related organisms (Pseudoramibacter and/or Roseburia) are responsible for MCFA production and the remaining community members ferment sugars to intermediate compounds (acetate, lactate, and/or ethanol) that provide substrates for MCFA production.
Economic analysis of MCFA production from stillage
Based on the sustained production of MCFAs in this study, we evaluated the potential value of this process. We did this by modifying the NREL TEA for a lignocellulosic ethanol biorefinery to include a process in which stillage is used to produce MCFAs. Using average percent conversions in the bioreactor between Day 30 and Day 252, we estimated that the COD remaining in stillage was converted to end products at the following percentages: 5.4% acetic acid, 15% butyric acid, 16% hexanoic acid, and 1.7% octanoic acid. Further, based on reactor operations during the same time period, 9.1% of the COD is removed from the system as off-gas.
After the liquid–liquid extraction, the aqueous phase is fed to biogas-producing anaerobic digesters (Fig. 7). Anaerobic digestion of lignocellulosic stillage  and acid-digested stillage  for biogas production has been demonstrated by others. The mass flow rate of COD to the anaerobic digesters, including stillage, lignin, and biosolids, is 21,000 kg h−1, resulting in biogas production of 16,600 kg h−1 (compared to 21,900 kg h−1 if the stillage is used directly as in the NREL TEA) . The overall power generation from the remaining organics after MCFA removal is reduced from 41.0 MW to 38.0 MW. The reduction in overall power generation is small because lignin contributes the majority of COD to the anaerobic digesters.
Summary of technoeconomic analysis for co-production of ethanol, electricity, and MCFAs in a lignocellulosic biorefinery
Total capital and installation cost
Additional capital expenses for MCFA production
Mixed culture fermentation reactors
Mixed culture fermentation agitators
Mixed culture fermentation feed pumps
Caustic feed system
Solvent feed system
Distillation column 1 (solvent recovery)
Distillation column 2 (MCFA separation)
Cost per ton
Annual operating expense
Additional operating expenses for MCFA production
Additional revenue for MCFA production
1877 kg h−1
169 kg h−1
Comparison of ethanol–electricity co-production to ethanol–electricity–MCFA co-production
Total co-product revenue
Total capital investment
MESP (gasoline equivalents)
Our work illustrates the potential of using microbial communities to convert stillage into valuable co-products. In the stillage-fed bioreactor, productivities of hexanoic (2.6 ± 0.3 g L−1 day−1) and octanoic (0.27 ± 0.04 g L−1 day−1) acids were sustained for 214 days with titers at 66 ± 8.2 and 97 ± 15% of their solubility in water, respectively. These productivities are consistent with other studies investigating the conversion of organic substrates derived from lignocellulosic materials or ethanol production wastes to MCFAs (Additional file 8: Table S17). Our system is unique, however, in that the primary carbohydrate consumed is xylose and the stillage has already been depleted of a large portion of fermentable sugars and the ethanol that others have used to produce MFCA. While we are proposing the co-production of ethanol and MCFAs in this study, recent work has also explored production of MCFA as the main product of a lignocellulosic biorefinery. In work performed by Nelson et al., Megasphaera consumed glucose in lignocellulosic hydrolysate to generate hexanoic acid, but xylose was not consumed . The microbial community like the one presented in this study could be utilized to convert the remaining xylose to MCFAs.
The simplicity of the microbial community enriched in this study positions it well as a model community for MCFA production. Others have shown enrichments containing OTUs related to primary sugar fermenters, such as Lactobacillus, and OTUs related to Clostridia that may be involved in converting intermediate fermentation products to MCFA [13–15, 17, 18, 47, 69]. In our microbial community, at Day 252, only 10 OTUs are present at greater than 1% relative abundance, and these OTUs make up 89.3% of the total OTUs (Additional file 5: Figure S3). The statistical analyses indicate that Pseudoramibacter and Lactobacillus are co-enriched, and their abundance correlates with higher MCFA production. We, therefore, propose that Lactobacillus converts xylose to lactate and acetate by heterofermentation, and the lactate is elongated to MCFAs by Pseudoramibacter. While 16S rRNA gene sequencing allows for the phylogeny of abundant organisms to be estimated, the function of community members should be investigated further utilizing metagenomic approaches. Due to the simplicity of the microbial community obtained in this study, this microbiome is well positioned for further investigation with metagenomic tools. Furthermore, its simplicity makes this a candidate microbiome for simulation with synthetic communities in the future. Of the OTUs that became enriched in the reactor, only Roseburia (denovo27808) and Pseudoramibacter (denovo6337) emerged as likely MCFA-producing bacteria. While Pseudoramibacter have been shown to produce MCFAs , to our knowledge, the ability of Roseburia to produce MCFAs has not been studied.
The TEA shows that even at the modest productivities of hexanoic and octanoic acids obtained in this study, MCFAs produced from ethanol stillage could improve the economic feasibility of lignocellulosic biorefining if the productivity can be maintained at industrial scale. Improvements in the overall conversion of stillage COD to MCFAs and production of a higher proportion of octanoic acid would further increase the revenue that can be generated by this strategy. Increasing MCFA product specificity towards octanoic acid is an ongoing area of research. One strategy to increase octanoic acid production is to utilize pertractive extraction of MCFAs to reduce product inhibition, as has been performed in past studies [13, 14]. Recent work has also shown that increasing the ratio of ethanol to acetate increases selectivity of octanoic acid production . The model of increasing the ratio of reduced electron donors to acetate suggests that, in the absence of ethanol, increasing the production of lactate as a fermentation intermediate (rather than acetate) could further drive octanoic acid production.
The economy of co-producing MCFAs may also be affected by upstream biomass processing (i.e., the conversion of plant polymers to their constituent monomer units) and ethanol fermentation. For example, utilization of xylose by industrial yeast strains, such as S. cerevisiae, is limited , although attempts to improve pentose utilization by ethanol producers is an area of intense research activity . Even though the S. cerevisiae Y128 strain used in this study was engineered for improved xylose utilization, it only consumed 47% of the xylose available in the switchgrass hydrolysate. Future ethanologenic organisms used in a lignocellulosic biorefinery may leave less xylose available for MCFA production. However, given the higher price of MCFAs compared to ethanol, decreasing xylose consumption by the ethanologenic organism may actually result in an improved economy of the lignocellulosic biorefinery.
Another simple opportunity for improving the economic potential of co-producing MCFAs is utilizing sodium hydroxide for pH control, instead of KOH, as sodium hydroxide is roughly one-sixth the cost of KOH. In our current model, the cost of KOH (Table 3) is a major expense. Alternatives to controlling pH with chemicals, such as electrolytic extraction which both controls the pH and extracts the acid products , should also be explored further.
In this study, we tested the hypothesis that microbial communities could be used to produce valuable compounds from lignocellulosic stillage. We developed conditions for sustained MCFA production by an anaerobic microbiome that uses stillage produced during lignocellulosic biorefining. By fermenting switchgrass stillage, we maintained productivities of hexanoic and octanoic acids of 2.6 ± 0.3 and 0.27 ± 0.04 g L−1 day−1, respectively. To our knowledge, this is the first demonstration of MCFA production with xylose and other organics in lignocellulosic ethanol stillage as the primary substrates. The MCFA-producing microbial community was derived from a diverse wastewater treatment ecosystem, but over time it became enriched with OTUs representing only five genera, including members of the Firmicutes phylum (Lactobacillus, Roseburia, and Pseudoramibacter) and of the Actinobacteria phylum (Olsenella and Atopobium). Pseudoramibacter are Clostridia related to known MCFA-producing organisms, some of which have been shown to produce hexanoic and octanoic acids .
A TEA, based on an update to an industry-accepted model, shows that, at the productivity of MCFAs achieved in this study, valorizing lignocellulosic ethanol stillage to MCFAs could improve the economic sustainability of a biorefinery. For example, using the MCFA production experimentally observed, if 16% of the COD remaining in stillage is converted to hexanoic acid and 1.7% is converted to octanoic acid, the minimum ethanol selling price could be reduced by 18%, from $2.15 to $1.76 gal−1. Optimization of microbiome MCFA productivities, MCFA extraction, solvent recovery and selection of the ethanologenic organism may contribute further to improving the economy of the lignocellulosic biorefinery.
MJS designed and performed the experiments, analyzed the data, and wrote the manuscript. GL and MD assisted with data collection, technoeconomic analyses, and manuscript preparation. MM developed GC–MS methods and performed chemical analyses of samples. TJD and DRN assisted with study design and were major contributors to writing the manuscript. All authors read and approved the final manuscript.
We thank Yaoping Zhang, Ed Pohlmann, and Dan Xie for providing the fermented switchgrass hydrolysate used in this study and Tate Hattervig, Chantel Roberts, and Jesus Santiago for performing testing related to reactor monitoring. We further thank Matt Seib and the Madison Metropolitan Sewerage District for providing the acid digester sludge inoculum and Duygu Celik for assistance with initial reactor setup. We also thank Jason Russell and the Coon Laboratory for LC–MS/MS analyses. We thank the University of Wisconsin Biotechnology Center DNA Sequencing Facility for providing Illumina sequencing services.
The authors declare that they have no competing interests.
Availability of data and materials
The raw sequencing reads from 16S rRNA gene amplicon sequencing are available under NCBI BioProject ID PRJNA393345 (252-day experiment) and NCBI BioProject ID PRJNA432807 (6-day experiments). Stillage and reactor data are available in Additional file 1 and data used for the TEA are provided in Additional file 3.
Consent for publication
Ethics approval and consent to participate
This work was funded by the DOE Great Lakes Bioenergy Research Center (DOE BER Office of Science Grants DE-FC02-07ER64494 and DE-SC0018409). MJS is supported by the National Science Foundation Graduate Research Fellowship Program under Grant no. DGE-1256259.
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