ACS Publications. Most Trusted. Most Cited. Most Read
Understanding the Anaerobic Digestibility of Lignocellulosic Substrates Using Rumen Content as a Cosubstrate and an Inoculum
My Activity
  • Open Access
Article

Understanding the Anaerobic Digestibility of Lignocellulosic Substrates Using Rumen Content as a Cosubstrate and an Inoculum
Click to copy article linkArticle link copied!

  • Xavier Fonoll
    Xavier Fonoll
    Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States
    Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, 08028 Barcelona, Spain
  • Shilva Shrestha
    Shilva Shrestha
    Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States
    Department of Molecular Biosciences and Bioengineering, University of Hawai’i at Ma̅noa, Honolulu, Hawaii 96822, United States
  • Samir Kumar Khanal
    Samir Kumar Khanal
    Department of Molecular Biosciences and Bioengineering, University of Hawai’i at Ma̅noa, Honolulu, Hawaii 96822, United States
  • Joan Dosta
    Joan Dosta
    Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, 08028 Barcelona, Spain
    More by Joan Dosta
  • Joan Mata-Alvarez
    Joan Mata-Alvarez
    Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, 08028 Barcelona, Spain
  • Lutgarde Raskin*
    Lutgarde Raskin
    Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States
    *Email: [email protected]
Open PDFSupporting Information (1)

ACS ES&T Engineering

Cite this: ACS EST Engg. 2021, 1, 3, 424–435
Click to copy citationCitation copied!
https://doi.org/10.1021/acsestengg.0c00164
Published January 31, 2021

Copyright © 2021 The Authors. Published by American Chemical Society. This publication is licensed under

CC-BY-NC-ND 4.0 .

Abstract

Click to copy section linkSection link copied!

While rumen microorganisms are known to facilitate the hydrolysis of lignocellulosic substrates in anaerobic digestion (AD), it is unclear how rumen content can be used to maintain rumen microorganisms in continuous-flow AD systems. We used rumen content as either an inoculum or a cosubstrate in two separate AD experiments, and performed microbial and multivariate statistical analyses to study how to best use this resource to enhance AD. Hydrolytic bacteria such as Fibrobacter spp. remained present for two months of reactor operation when the rumen content was used as an inoculum, producing 0.3–0.5 g of short-chain fatty acids (SCFA) as acetic acid per gram of volatile solids (VS)fed. The lack of acetoclastic methanogens in the rumen content initially led to the accumulation of SCFA (10–15 g of SCFA as acetic acid per liter) as well as a low pH (5.9–6.8) and a low methane yield (0.02–0.05 L of CH4 per gram of VSfed). The reactor performed similarly (0.1–0.2 L of CH4 per gram of VSfed) to the control, which was not inoculated with rumen content, toward the end of the experiment, and the microbial analyses showed a washout of the rumen bacteria. Rumen hydrolytic bacteria remained in the reactor during the codigestion experiment. However, the methane yield (0.1–0.2 L CH4 per gram of VSfed) was similar to that of the control reactor, which did not receive the rumen content as a cosubstrate, because the reactor conditions (pH > 6.9) were not favorable for the activity of rumen bacteria. Our analyses suggest that using rumen content as a cosubstrate at a low pH (6.0–6.5) is necessary to maintain rumen hydrolytic bacteria and enhance hydrolysis.

This publication is licensed under

CC-BY-NC-ND 4.0 .
  • cc licence
  • by licence
  • nc licence
  • nd licence
Copyright © 2021 The Authors. Published by American Chemical Society

Introduction

Click to copy section linkSection link copied!

The anaerobic digestion (AD) of a variety of biomass streams has been implemented worldwide to reduce waste, produce energy, and mitigate greenhouse gas emissions. Approximately 2200 AD plants are operational in the U.S., (1) and regulatory changes in regard to waste management in some U.S. states are expected to further expand AD applications. (2,3) In Europe, approximately 18 000 AD plants are operational, with an installed electric capacity of 10 000 MW. (4) The number of European AD plants has been steadily increasing due to legislation related to the treatment and disposal of organic wastes (European directive 2008/98/EC) as well as the implementation of renewable energy directives (European directive 2009/28/EC). These data suggest that AD is a mature technology that has the potential to continue to expand across the world.
One of the bottlenecks of AD, especially for substrates with high lignocellulosic content, is hydrolysis. (5) The cross-linking between cellulose, hemicellulose, and lignin makes the lignocellulosic biomass highly recalcitrant to microbial degradation. Lignocellulosic biomass streams are readily available as they are produced in urban environments (e.g., food, paper, and park waste streams), food and beverage industries (e.g., fruit and vegetable processing waste), and rural areas (e.g., energy crops and agricultural waste streams). Various physical, chemical, and biological pretreatment methods as well as combinations of these approaches have been applied to enhance hydrolysis. (5) While such pretreatment strategies can be effective, they are often energy intensive and sometimes generate biomass degradation byproducts (e.g., phenolic and furfural compounds), which inhibit AD microbial communities. (5)
Nature continuously demonstrates that the efficient degradation of lignocellulosic substrates is feasible in anaerobic environments without high energy inputs. (5,6) For example, the microbial community in one of the stomachs of ruminants (rumen) degrades lignocellulosic biomass (grass) efficiently under anaerobic conditions. (7) Rumen content has been used as an inoculum and a cosubstrate for different types of laboratory-scale AD systems since the late 1980s. (8−33) Its use as an inoculum in batch experiments demonstrated that rumen populations can enhance hydrolysis in AD. (23−25) However, in continuous-flow systems that used rumen content as an inoculum, rumen microbial populations were typically washed out over time, and hydrolysis was only enhanced at the beginning of the experiments. (16,24) Only Agematu et al. (22) were able to maintain rumen bacteria for 60 days in a continuous-flow bioreactor seeded with rumen content. Using rumen content as a cosubstrate could be a strategy to avoid the wash-out of rumen microbial populations and maintain a high hydrolysis rate in continuous-flow AD systems. Wall et al. (15) examined rumen content and grass silage codigestion; however, they demonstrated a similar performance in terms of methane production and the removal of volatile solids (VS) with and without the addition of rumen content. While the addition of rumen content has the potential to improve hydrolysis in AD, it is unclear which conditions are needed for rumen microbial populations to grow in a continuous-flow bioreactor.
The aim of this study was to evaluate the use of rumen content as an inoculum and a cosubstrate and establish the conditions necessary to enhance the hydrolysis of lignocellulosic biomass in AD. The use of high-throughput 16S rRNA gene sequencing and a multivariate statistical analysis suggested new strategies for maintaining rumen microbial populations and thus for enhancing hydrolysis in AD systems.

Materials and Methods

Click to copy section linkSection link copied!

Two experiments were conducted to understand how the anaerobic digestibility of lignocellulosic substrates is affected by the availability of rumen microbial populations. In one experiment, rumen content was used as the inoculum. In a second experiment, rumen content was used as a cosubstrate. Both experiments were run in semicontinuously fed stirred-tank reactors.

Inocula

Two types of inocula were used in this study. One inoculum consisted of the effluent from a full-scale AD plant treating food waste and cow manure at Michigan State University, East Lansing, MI, USA, (34) and is referred to as AD inoculum. The second inoculum consisted of rumen content collected from a fistulated cow from a dairy farm at Michigan State University. Solid and liquid fractions of the rumen content were collected separately and then mixed according to the ratio needed to simulate the rumen content generated in a slaughterhouse (total solids (TS) concentration of approximately 120 g L–1). (35,36) Both AD and the rumen content inocula were used and characterized (Table S1) within 1 h of collection using the methods described below.

Substrates

Four different substrates were used for this study. Napier grass (Pennisetum purpureum), a second generation lignocellulosic energy crop, was used as the primary substrate. Napier grass was hand-harvested from the Waimanalo Research Station (Waimanalo, HI, USA), shredded using a cutting mill (Vincent Corporation, Tampa, FL, USA), and air-dried to reduce the moisture content to less than 10% to facilitate downstream processing. The dried substrate was then milled using a laboratory cutting mill (Retch SM2000, Haan, Germany) with a screen size of 2 mm. The second substrate consisted of cow feces collected from the same dairy farm at Michigan State University. The third substrate was cow manure, a mixture of cow feces and urine, that was collected from the same farm. Cow manure was used in this study as a cosubstrate to supplement nutrients and balance the C/N ratio of the mixture. (37) Cow feces and urine were collected when cows were defecating and urinating, respectively. Cow feces and urine were mixed at a mass ratio of 30:70 (wet weight) to represent the concentration of TS in the cow manure fed to the full-scale AD plant at Michigan State University. The fourth substrate consisted of the rumen content collected and mixed as described above. All substrates were characterized (Table S2) using the methods described below and were stored at 4 °C except for the rumen content, which was stored at −20 °C until use. While keeping the rumen content at −20 °C did not affect the microbial fermentation patterns in previous studies, (38) preserving the samples at −20 °C might have decreased the microbial load in the cosubstrate.

Bioreactor Operating Conditions

For both experiments, three 2 L bottles with a working volume of 1.3 L were operated as semicontinuously fed stirred-tank reactors in a shaking water bath (gyrotory water bath shaker g76, New Brunswick Scientific, NJ, USA) at 130 rpm. The reactors were briefly opened once a day after stopping agitation both to remove digestate and for feeding. Even though some air exposure was inevitable, oxygen was expected to be quickly consumed by the facultative microbes without affecting the anaerobic environment. (39) The reactors were operated at 39 °C to simulate the rumen temperature. (36)
For the inoculum experiment, the three reactors were filled with 1.3 L of inocula. Reactor Inoc_AD received the AD inoculum (control), reactor Inoc_RC+AD was filled with a 50:50 (VS/VS) mixture of AD and the rumen content inocula, and reactor Inoc_RC was inoculated with the rumen content only. All reactors were inoculated within 1 h after the inocula were collected and transported to the laboratory. The rumen content was diluted with distilled water so that the VS content of the inoculum was the same in all three reactors (25.2 ± 3.7 g VS L–1). The C/N ratio of the individual substrates was estimated through different studies from the literature. (40−43) To have a C/N ratio between 20 and 30 in the feedstock, the three reactors were fed with a 30:70 (wet weight) mixture of Napier grass and either cow feces (first 80 days) or cow manure (days 81–140). The cow feces and cow manure were diluted with distilled water to reach 60 g VS L–1 and provide an optimal rheology to facilitate analyses and reactor mixing. Initially, buffers were added to Inoc_RC+AD and Inoc_RC to maintain the pH around 7.0. NaHCO3 was added to Inoc_RC on days 1 (4.0 g), 3 (2.0 g), and 4 (2.0 g). However, to avoid Na+ toxicity, (44) NH4HCO3 was added on days 5 (6.0 g), 8 (2.0 g), 22 (5.0 g), and 37 (5.0 g) to Inoc_RC and on days 7 (2.0 g) and 44 (2.0 g) to Inoc_RC+AD. When adding NH4HCO3 in Inoc_RC and Inoc_RC+AD, the C/N ratio changed from 20 to 10; however, the addition of NH4HCO3 was not frequent enough to have a negative effect on the system stability. Starting from day 81, the cow urine was mixed with cow feces (referred to as cow manure) as described above to increase the buffering capacity of the substrate.
For the codigestion experiment, the general operating conditions were similar to those of the inoculum experiment except that all three reactors were inoculated with 1.3 L of AD inoculum and fed with different substrates. Reactor Co_NG+CM (control) was fed with a mixture of Napier grass and cow manure (30:70, wet weight); reactor Co_NG+CM+RC was fed with a mixture of Napier grass, cow manure, and rumen content (25:60:15, wet weight); and reactor Co_NG+RC was fed with a mixture of Napier grass and rumen content (85:15, wet weight). The amount of rumen content that was fed was determined by considering the average production of rumen content in the US and the average amount of lignocellulosic feedstock fed in AD plants (see Section S1). Before feeding the rumen content, it was thawed in a water bath at 39 °C. Again, all substrate proportions generated a feedstock C/N ratio of 20–30 according to the literature data. (40−43) NH4HCO3 was added daily to Co_NG+RC from day 44 to keep the pH at 7.0. The operating conditions of the six reactors are summarized in Table S3.

Chemical Analyses

TS, VS, alkalinity, SCFA, free ammonia, and biogas production and composition were analyzed regularly as described in Section S2.

Biomass Sampling, DNA Extraction, and 16S rRNA Gene Sequencing

Biomass sample preservation and DNA extraction methods are described in Section S3. DNA samples were submitted to the Host Microbiome Initiative (University of Michigan, Ann Arbor, MI, USA) for 16S rRNA gene sequencing via Illumina MiSeq (San Diego, CA, USA). Universal primers F515 and R806 that target the V4 region of the 16S rRNA gene were used for PCR amplification. (45) The sequences obtained were processed using mothur (ver. 1.34.4) following the MiSeq SOP. (46) The SILVA database (Release 119) was used for taxonomic classification, and sequences were grouped into operational taxonomic units (OTUs) using the average neighbor algorithm at a 3% sequence divergence cutoff. Unclassified OTUs were further classified using the basic local alignment search tool (BLAST; NCBI, Bethesda, MD), and only the hits with a query cover of 100% and an identity greater than 90% were selected. Sequences for which no significant match was found in the databases using BLAST were termed “unclassified”. The relative abundance was calculated by dividing the number of reads of a particular OTU or genus by the total number of reads in the sample. The raw sequence data were submitted to NCBI with accession number SUB8879343.

Statistical Analyses

Performance data of the reactors within each study were compared using the Kruskal–Wallis test (nonparametric one-way ANOVA). The comparison of the reactor performance though a Kruskal–Wallis statistical test was performed with data collected for at least 14 days. To allow for comparisons among samples represented by different numbers of sequences, subsampling (as implemented in mothur) was performed using the sample with the lowest number of sequences, i.e., 4729 reads for the inoculum study and 6454 reads for the codigestion study. β-Diversity was represented in a two-dimensional graph using nonmetric multidimensional scaling (NMDS) analyses based on the Bray–Curtis dissimilarity index as implemented in mothur. A canonical correspondence analysis (CCA) was performed to study the relationship between the microbial community structure and various chemical conditions and operational parameters. Parameters with multicorrelations were removed if the variance inflation factor value was higher than 10. (47) The optimum CCA model was selected after applying Akaike’s information criterion, and its significance was tested with ANOVA. (47,48) The variance inflation factor calculation, Akaike’s information criterion, and the CCA were performed using the vegan package (2.4–4) in R 3.3.3. (47) For the CCA inoculum model, the parameter “Rumen content only as inoculum” was introduced to evaluate if mixing the rumen content and the AD inoculum had an effect on the differences among the microbial communities in the reactors. For the CCA codigestion model, the parameter “Rumen content only as cosubstrate” was introduced to evaluate if mixing the rumen content and the cow manure had an effect on the differences among the microbial communities in the reactors. Both parameters were yes or no parameters. A significance level of α ≤ 0.05 was used to interpret the significance of the results in all the statistical tests. While other studies have shown that long-term experiments can help address concerns when operating anaerobic digesters in replicates is not possible, (49,50) we acknowledge that the lack of replicates is a limitation of the statistical analysis.

Results and Discussion

Click to copy section linkSection link copied!

Using the Rumen Content as an Inoculum Enhances Hydrolysis But Limits Stable Methanogenesis

Performance results of the inoculum experiment for reactors Inoc_AD, Inoc_RC+AD, and Inoc_RC, all three of which were fed the same mixture of Napier grass and cow feces or manure, are presented in Figures 1, S1, and S2. During the first two weeks of operation, the SCFA accumulation (grams of SCFA per gram of VS–1fed) for reactors Inoc_RC and Inoc_RC+AD were significantly higher than for Rreactor Inoc_AD (p = 1.4 × 10–04 for Inoc_RC vs Inoc_AD and p = 3.77 × 10–03 for Inoc_RC+AD vs Inoc_AD) (Figure 1A). Specifically, the reactors inoculated with the rumen content (Inoc_RC and Inoc_RC+AD) produced a maximum of 0.79 g of SCFA as acetic acid (HAc) per gram of VSfed and 0.57 g of SCFA as HAc per gram of VSfed, respectively (Figure 1A). This indicates that the rumen content provided hydrolytic microbes that accelerated the hydrolysis step, producing high levels of SCFA. The SCFA accumulation by Inoc_RC was especially high considering that acidogenic reactors typically produce 0.15–0.55 g of SCFA as HAc per gram of VSfed. (51−53) Moreover, in previous studies that used rumen content as the inoculum and lignocellulosic biomass as the substrate, the SCFA accumulation ranged from 0.18 to 0.22 g of SCFA as HAc per gram of VSfed. (22,23,25) The reason for a higher SCFA accumulation in our study could be our use of a mixture of rumen fluid and solids instead of only rumen fluid like in other studies. Including the solids from the rumen content to accelerate hydrolysis is important because they harbor a higher concentration of hydrolytic microbes than the fluid. (7)

Figure 1

Figure 1. (A) Short-chain fatty acid (SCFA) accumulation, (B) pH, and (C) specific methane production in the reactors. Organic loading rate (OLR) and retention time in Inoc_AD, Inoc_RC+AD (−·−), and Inoc_RC (− −). The vertical line indicates the change from cow feces to cow manure on day 81. The red arrow and green lines with circles indicate the buffer addition in Inoc_RC and Inoc_RC+AD, respectively. The legend refers to the three reactors with the type of inocula used.

The high hydrolytic activity led to high SCFA levels in reactor Inoc_RC (10.8 ± 3.0 g of SCFA as HAc L–1 in the first 50 days), which affected the stable methanogenesis. The low partial alkalinity (826 ± 142 mg of CaCO3 L–1) and pH (5.4 ± 0.2) in the rumen content (Table S1) and the low pH in Inoc_RC (5.0–6.8 during the first 50 days) were also not favorable for the growth of acetoclastic methanogens. These conditions are not typical in the rumen, where SCFA concentrations are around 7 g of SCFA as HAc L–1 with a hydraulic retention time of 5–20 h and there is the continuous removal of SCFA via absorption through the rumen walls. (36,54) Therefore, a buffer in the form of NaHCO3 or NH4HCO3 was added several times in an attempt to increase the pH and restore the reactor stability (Figure 1B). The frequent addition of NH4HCO3 resulted in an increase in the free ammonia concentration in the reactor; however, it did not reach inhibitory levels for methanogens (<124 mg of NH3–N L–1), and the concentration was still low in comparison to the optimal levels in the rumen (41–248 mg of NH3–N L–1) (Figure S1C). (36,44) However, since the SCFA levels remained high, the pH only increased temporarily (Figures 1B and S1A). The high concentration of SCFA (10–16 g of SCFA as HAc L–1) (Figure S1A) and low pH (5.8–6.8) (Figure 1B) resulted in a very low methane yield (0.02 ± 0.02 L of CH4 per gram of VSfed, 57 ± 4% CH4) (Figure 1C) during the first 50 days of operation for reactor Inoc_RC. The situation changed between days 49 and 56 when the pH increased from 6.3 to 7.4 (Figure 1B), the partial alkalinity increased from 1.7 to 4.2 g of CaCO3 L–1 (Figure S1B), the free ammonia levels increased from 4.9 to 44.6 mg of NH3–N per liter (Figure S1C), the SCFA accumulation decreased (Figure 1A), and the specific methane production increased (Figure 1C). The degradation of SCFA (especially acetate, Figure S2A) seems to be related to an increase in the pH and not an increase in the levels of free ammonia because Inoc_RC+AD and Inoc_AD presented very low acetate (<0.5 g of HAc L–1) and free ammonia levels (<10 mg of NH3–N per liter) in between days 25 to 54.
The specific methane production in reactor Inoc_RC+AD was higher during the first 30 days compared to those of Inoc_RC (p = 5 × 10–07) and Inoc_AD (p = 3 × 10–04) (Figure 1C). This may be explained if the hydrolytic microbes originating from the rumen content hydrolyzed the Napier grass into SCFA, which would be converted to methane by methanogens in the AD inoculum. A previous batch study also reported a higher methane production when the rumen content was mixed with an adapted inoculum from an anaerobic digester. (25) Inoc_RC+AD also exhibited a greater stability with respect to pH (Figure 1B) and SCFA levels (Figure S1A) compared to reactor Inoc_RC; alkalinity as NH4HCO3 was supplemented only on days 7 and 44 when the pH dropped below 6.5 (Figure 1B). Reactor Inoc_AD took 32 days to adapt to the new substrate, as indicated by an increase in the specific methane production to 0.15 L of CH4 per gram of VSfed and SCFA levels of 1.7 g of SCFA per liter, which are adequate for methanogenesis. (55) The performance of reactor Inoc_AD did not differ from the performance of reactor Inoc_RC+AD after day 44 (Figures 1, S1, and S2).
Starting from day 81, cow manure was fed to all three reactors instead of cow feces. This change increased the buffering capacity (Figure S1B), the pH (Figure 1B), and the free ammonia levels without reaching inhibitory conditions (<124 mg of NH3–N per liter) (Figure S1C). Since all three reactors were operating at a steady state for almost 40 days, their retention times were decreased to 20 days to study the performance under a shorter retention time. The retention time was slowly decreased to avoid organic overloading. From day 95, the three reactors demonstrated similar performances with a specific methane production of 0.16 ± 0.02 L of CH4 per gram of VSfed (Figure 1). All parameters remained the same as those reported for the previous conditions except the specific methane production in Inoc_RC. The specific methane production in Inoc_RC was higher before (0.21 ± 0.03 L of CH4 per gram of VSfed from day 61 to 90), probably due to the longer retention time (60 vs 20 days) that allowed a better degradation of the organic matter.

Using the Rumen Content As an Inoculum Provides Hydrolytic Bacteria But They Are Washed Out while Promoting Stable Methanogenesis

On day 7, when the of SCFA accumulation in Reactor Inoc_RC was 0.79 g of SCFA as HAc per gram of VSfed (Figure 1A), >90% of OTUs present in the reactor were also present in the rumen inoculum (Figure 2).

Figure 2

Figure 2. Relative abundances of OTUs grouped by origin in reactors Inoc_RC, Inoc_RC+AD, and Inoc_AD. OTUs were grouped in eight categories depending on whether they were present in the rumen content inoculum only, the AD inoculum only, the cow manure only, various combinations of these three sources, or none of them (“Others”). Samples from day 28 for Inoc_RC+AD and Day 75 for Inoc_AD could not be sequenced.

However, these OTUs were not exclusively present in that rumen content, as 1.2%, 17.9%, and 8.5% of OTUs were present in the rumen content and the AD inocula, the rumen content inoculum and the cow manure, and all three sources, respectively. The predominant OTUs in Inoc_RC present on day 7 belonged to genera that are commonly found in the rumen and are involved in the hydrolysis of cellulose (Fibrobacter) (56−58) and the fermentation of its products (Treponema, Prevotella, and Succiniclasticum) (Figure S3). (56−60) A recent study reported that Fibrobacter succinogenes produces an array of hydrolytic enzymes that are attached to the cell surface or transported to the extracellular environment by means of outer membrane vesicles, which protect the enzymes from external inhibitors. (57)Fibrobacter was indeed present at a relative abundance higher than 3.0% in reactor Inoc_RC during the first three weeks of the experiment (Figure S3) when hydrolysis was rapid. These results suggest that the addition of the rumen content had a positive effect on hydrolysis and that Fibrobacter likely contributed to this.
Methanobrevibacter, an obligate hydrogenotrophic methanogen that is prevalent in the rumen, was the most abundant archaeal population (relative abundances of 2.5–7.0%) in reactor Inoc_RC until day 34 (Figure S4). The absence of syntrophic bacteria (e.g., Syntrophomonas), syntrophic acetate-oxidizing bacteria (e.g., Thermotoga), and acetoclastic methanogens (e.g., Methanosarcina and Methanothrix) in the rumen content (Figures S3, S4, and S5) explains the accumulation of SCFA and the low pH in reactor Inoc_RC during the first 50 days of operation (Figure 1A and B).
Reactor Inoc_RC experienced two substantial shifts (from day 34 to 56 and from day 56 to 75) in the community structure, as shown in the NMDS plot in Figure S6. The first shift took place between days 34 and 56 and corresponded to a dramatic change in the reactor performance (Figure 1). The OTUs coming from only the rumen content decreased from 45% to 15%, and the OTUs originally found in the AD inoculum increased from 22% to 43% (Figure 2). The decrease in the SCFA accumulation starting from day 55 might be due to the increase in the relative abundance of OTU 108 (Methanosarcina), a methanogen capable of degrading acetate, hydrogen, methylamine, and methanol (Figure S4).
After day 75, the relative abundance of OTUs that were not detected in the biomass sources (“Others”) became a substantial portion of the community (40–48%) in Inoc_RC (Figure 2). These OTUs originated from the cow manure, the AD inoculum, or the rumen content but were not detected in these sources, likely because their relative abundances were low and below the detection limit obtained with the current sequencing depth (Figure S7). These OTUs were detected as the reactor conditions became more favorable for their growth and their relative abundances increased. Most of the abundant OTUs in reactor Inoc_RC (e.g., Alkaliflexus, Petrimonas, and Sedimentibacter) were acidogenic microorganisms involved in the production of SCFA. Interestingly, Sedimentibacter has also been found in other systems that used rumen content as the inoculum. (20,22,24,61)
Reactor Inoc_AD initially had 91.4% of its OTUs associated with the AD inoculum (Figure 2). A community shift took place after day 34 (Figure S6), and OTUs that were not detected previously in any of the biomass sources (“Others”) increased in relative abundance (40–60% of the total OTUs) (Figure 2). The predominant OTUs associated with the AD inoculum remained in the reactor throughout the experiment except for OTU 7 (Sedimentibacter) and OTU 25 (unclassified Firmicutes), which disappeared after day 34 (Figure S5).
The microbial community structure in reactor Inoc_RC+AD was more dynamic than those in the other reactors during the first 50 days (Figure S6). On days 7 and 34, the OTUs coming only from the rumen represented 29.6% and 21.0% of total number of OTUs, respectively. The only parameter in Inoc_RC+AD that was identical on days 7 and 34 but different from days 21 and 56 was pH, which was 6.5 (Figures 1, S1, and S2). On days 7 and 34, the OTUs associated with the rumen content were similar to those in Inoc_RC on day 34 (Figure S3). However, when the pH was 7.0 on day 21, only 6.5% of the OTUs originally present only in rumen content were also in Inoc_RC+AD (Figures 2 and S3). These observations suggest that rumen bacteria are strongly impacted by the pH. The microbial community structure in Inoc_RC+AD became similar to that in Inoc_AD after day 56 (Figure S6). At this time, the OTUs that were not initially detected in the rumen content, cow manure, or AD inoculum (“Others”) became a large portion of the total community (40–68%) in Inoc_RC+AD and Inoc_AD (Figure 2).
At the end of the experiment, the microbial community structures in all three reactors were similar, as shown in the NMDS plot (Figure S6), which is consistent with the observation of similar reactor performance results. In all three reactors, a significant part of the OTUs (45–55%) belonged to the fraction “Others”. Most of the OTUs present at high relative abundances in the three reactors on day 140 were unclassified; however, those that were classified and present at a relative abundance higher than 1.5% were related to Petrimonas (OTU 31), Treponema (OTUs 3, 61, and 81), Alkaliflexus (OTU 6), Bacteroides (OTU 50), and Methanospirillum (OTU 198) (Figures S3 and S5). Bacteroides is a common genus in biogas plants, where species such as Bacteroides cellulosolvens and Bacteroides xylanolyticus are able to degrade cellulose and xylan, respectively. (62)

Using the Rumen Content as the Only Cosubstrate Compromises Methanogenesis Stability But Keeps Rumen Bacteria in the Reactor

In a second experiment, all reactors were inoculated only with an AD inoculum, but the addition of rumen content as a cosubstrate was evaluated. Reactors Co_NG+RC and Co_NG+CM+RC were operated to evaluate whether the hydrolytic activity of the rumen bacteria could be retained through the continuous addition of rumen content. Reactor Co_NG+CM was operated to represent the codigestion of crops and manure, the most common practice in agriculture. (37) Despite the use of rumen content, hydrolysis was not enhanced, as was apparent from the low SCFA accumulation (maximum of 0.07 g of SCFA per gram of VSfed) and methane production (0.12 ± 0.04 L or CH4 per gram of VSfed from days 60–113) (Figure 3A and C).

Figure 3

Figure 3. (A) Short-chain fatty acid (SCFA) accumulation, (B) pH, and (C) methane production in the reactors showing (A) the organic loading rate (OLR) (− −) and (B) retention time (− −) applied in the reactors. The vertical line on day 44 indicates the start of continuous buffer addition.

Moreover, none of the reactors experienced inhibitory conditions because the pH was never below 6.9 and the free ammonia levels were always below 124 mg of NH3–N per liter (Figures 3 and S8C). Nonetheless, Co_NG+RC had free ammonia levels that were not ideal for the development of rumen microbes (<41 mg of NH3–N per liter) (Figure S8C). To enhance the methane production, the retention time in all three reactors was increased from 20 to 30 days after a steady state was reached for 20 days on day 60 (Table S3). However, increasing the retention time to 30 days (OLR= 2.6 g of VS per liter per day) only enhanced the specific methane production slightly (from 0.10 ± 0.01 to 0.13 ± 0.02 L of CH4 per gram of VSfed) (Figures 3C).
Again, the microbial community structure was analyzed to help understand the reactor performance. During the first 23 days of the experiment, the microbial community structures in all three reactors were similar (Figure S9), with more than 80% of the reactor OTUs initially present in the AD inoculum (Figure 4). In fact, most of the abundant OTUs in the AD inoculum (OTUs 10, 6, 26, 25, 8, 32, 2, and 24) were also prevalent in the reactors (Figure S10).

Figure 4

Figure 4. Relative abundances of OTUs grouped by origin in reactors Co_NG+CM, Co_NG+CM+RC, and Co_NG+RC. OTUs were grouped in eight categories depending on whether they were present in the rumen content only, the AD inoculum only, the cow manure only, a combination of these three sources, or none of them (“Others”). Samples from day 72 for Co_NG+CM and day 51 for Co_NG+RC could not be sequenced.

From day 23, the pH, partial alkalinity, and free ammonia levels started to decrease only in reactor Co_NG+RC (Figures 3B, S8B, and S8C). Starting from day 44, NH4HCO3 was added daily (100 mg) in Co_NG+RC to maintain the pH above 7.0 and thus avoid the inhibition of methanogens. This strategy allowed the establishment of both acetoclastic and hydrogenotrophic methanogens, promoting stable methanogenesis (Figures 3C and S11) while maintaining a free ammonia concentration below inhibitory levels (<124 mg of NH3–N per liter, Figure S8C). However, the free ammonia levels (5.5 ± 1.7 mg of NH3–N per liter) were still below the optimal level for rumen microbes (41–248 mg of NH3–N per liter), and no more NH4+ was added to maintain the C/N ratio within the optimal range of 20–30 for AD. Nevertheless, low free ammonia levels were not an impediment for rumen microbes to grow in Co_NG+RC, such as in Inoc_RC. The microbial community in reactor Co_NG+RC began to deviate from the communities present in reactors Co_NG+CM and Co_NG+CM+RC (Figure S9). Specifically, the fraction of OTUs associated only with the rumen content in Co_NG+RC increased from 1.7% to 17.8%, and some of the abundant OTUs in Co_NG+RC were present only in the rumen content, e.g., OTUs 28 and 147 (Prevotella), OTU 55 (Treponema), and OTU 71 (Fibrobacter) (Figures 4 and S12). Toward the last 30 days of the experiment, 26–36% of the OTUs in Co_NG+RC belonged only to the rumen content, 29–35% belonged to the AD inoculum and cow manure, and 27–30% belonged to the group “Others” (Figure 4). Again, the fraction “Others” contained OTUs that were present in the cow manure, AD inoculum, or rumen content but were not detected because their relative abundances were low, and they were not captured because of the current sequencing depth (Figure S13). These big changes in the microbial community seemed to be related to the decrease in the pH, partial alkalinity, and free ammonia levels. The decrease of these parameters in Co_NG+RC was linked to the substrate composition. Co_NG+RC was not fed with cow manure, which has a high concentration of free ammonia (2755.9 ± 281.3 mg of NH3–N per liter) and provides high levels of partial alkalinity, promoting a higher pH in Co_NG+CM+RC and Co_NG+CM.
Co_NG+CM+RC was also fed with rumen content in addition to Napier grass and cow manure, and the fraction of OTUs belonging to only the rumen content was only 0.8–3.9% during the last 40 days of operation (Figure 4). Rumen OTUs were low in Co_NG+CM+RC even though the free ammonia levels were within the usual range for the rumen (41–248 mg of NH3–N per liter) (Figure S8C). These results suggest that, contrary to observations for the rumen, free ammonia levels are not that important for maintaining rumen bacteria in AD. When free ammonia levels are low in the rumen, bacterial growth is slow, and the breakdown of carbohydrates is retarded. (36) However, the solid retention time in the rumen is only 60–90 h, whereas the reactors were operated at a minimum retention time of 20 days. Therefore, having concentrations of free ammonia lower than 41 mg of NH3–N per liter seems not to be an impediment to the growth of rumen bacteria. On the other hand, the decrease in free ammonia levels lowered the partial alkalinity and pH levels in Co_NG+RC. The pH seemed to be responsible for the microbial community change in Co_NG+RC. In both Inoc_RC and Co_NG+RC, rumen OTUs were dominant when the pH was below 7.0; meanwhile for Co_NG+CM+RC, which was also fed with the rumen content, the pH was never lower than 7.2 (Figure 3B), and rumen OTUs were present at a lower relative abundance (Figure 4). In fact, among the different studies that used rumen content as an inoculum, (16,19,22,24,27) only Agematu et al. (22) maintained the rumen bacterial populations in the reactor for 50 days. Agematu et al. (22) maintained their reactor pH around 6.5 and produced as much as 5.1 g of SCFA as HAc per liter from cedar. This study thus confirmed that pH was a critical factor for the growth of rumen hydrolytic bacteria in AD, which was further evaluated using a multivariate statistical analysis (below).
During the last 30 days of operation, 70–80% of the OTUs in Co_NG+CM and Co_NG+CM+RC originated from the AD inoculum and cow manure, and 16–25% belonged to the group called “Others” (OTUs not detected in the AD inoculum, rumen content, or cow manure). At the same time, 26–36% of the OTUs in Co_NG+RC belonged to the rumen content only, and hydrolytic rumen bacteria like Fibrobacter were present (Figure 4). These bacteria might be responsible for the higher SCFA levels in Co_NG+RC compared to the SCFA levels in Co_NG+CM+RC (p = 3 × 10–09) and Co_NG+CM (p = 2 × 10–08) (Figures 3A and S14, respectively). However, the specific methane production in Co_NG+RC was similar to that in the other two reactors (p = 0.106). Furthermore, the accumulation of SCFA was also low (maximum of 0.07 g of SCFA as HAc per gram of VSfed) compared to that in Inoc_RC (maximum of 0.79 g of SCFA as HAc per gram of VSfed) in which a higher percentage of the OTUs originated from the rumen content (more than 90% on day 7). This behavior might be due to the fact that the pH in Co_NG+RC was not low enough to support the activity of rumen microorganisms. McDonald et al. reported that the pH in the rumen fluctuates between 5.5 and 7.0, (36) and the optimal pH for F. succinogenes falls between 6.0 and 6.8 with the highest activity at pH values between 6.2 to 6.5. (63−65) In Inoc_RC, the pH was 6.2–6.5 when the accumulation of SCFA was as high as 0.79 g of SCFA as HAc per gram of VSfed, suggesting that these reactor conditions were optimal for the development of rumen hydrolytic bacteria. However, RNA-based analyses would be necessary to further confirm this.

Favorable Conditions for Rumen Bacteria Are Unfavorable for Methanogenesis: pH as the Crucial Factor

The reactor performance and microbial data suggest that pH is an important parameter when considering strategies to maintain rumen bacteria in continuous-flow AD systems. To further evaluate this observation and determine which other factors are favorable for rumen microorganisms, a multivariate statistical analysis using the reactor performance and microbial data was applied for each experiment. Previous studies have demonstrated that such an analysis with long-term time-series experiments can provide results similar to those obtained with anaerobic digesters operated in replicate. (49,50)Tables 1 and 2 show the results of CCA models for the inoculum and codigestion experiments, respectively.
Table 1. CCA model (Akaike’s Information Criterion = 36.57) for the Inoculum Experiment
parameterseigenvalueexplained inertia (%)ANOVA (Pf > F)
acetate concentration0.69330.001
free ammonia0.42200.007
pH0.39190.001
partial alkalinity0.23110.001
propionate concentration0.1990.006
rumen content only as inoculum0.1680.011
residualn.a.n.a. 
Table 2. CCA Model (Akaike’s Information Criterion = 3.95) for the Co-digestion Experiment
parameterseigenvalueexplained inertia (%)ANOVA (Pf > F)
rumen content only as the cosubstrate0.58380.001
pH0.44280.001
partial alkalinity0.23150.001
acetate concentration0.1390.001
propionate concentration0.0960.009
butyrate concentration0.0840.031
residualn.a.n.a. 
The CCA model built for the inoculum experiment (Table 1) was responsible for 55% of the distances between the different microbial communities in the respective reactors. A substantial portion of the distances (83%) was explained by the acetate, free ammonia levels, pH, and partial alkalinity levels. While rumen content populations were abundant during the first 50 days of the inoculum experiment, the acetate concentration (p = 2 × 10–09), pH (p = 1.5 × 10–14), and partial alkalinity (p = 3 × 10–05) were significantly different in Inoc_RC compared to in Inoc_RC+AD and Inoc_AD; however, this was not the case for the free ammonia levels (p = 0.077). The multivariate statistical analysis confirmed the experimental results that maintaining a pH below 7.0 is critically important to maintain rumen microorganisms. In other studies that supported the growth of rumen hydrolytic microorganisms, the pH was between 6.0 and 6.5. (16,19,22,24,27,63−65) When using the rumen content as the inoculum, Fibrobacter was present at a high relative abundance, which accelerated the hydrolysis of the substrate and resulted in a higher production of SCFA (specially acetate and propionate) and a lowered buffering capacity. High levels of SCFA and low levels of partial alkalinity and free ammonia could maintain the pH between 6.0 and 6.5 in Inoc_RC, which promoted the growth of rumen bacteria (Figure 2). For this reason, the parameters of acetate, partial alkalinity and free ammonia levels explained 64% of the CCA model (Table 1). Free ammonia levels and pH had very similar eigenvalues (0.42 for free ammonia and 0.39 for pH). As discussed earlier, free ammonia levels did not seem very important for the growth of rumen hydrolytic microbes, and the levels did not differ statistically between the three reactors (p = 0.077). However, free ammonia appears as an important parameter in Table 1 because the pH is dependent on the free ammonia concentration (their trends were very similar, Figures 1B and S1C). Other parameters in the model, such as the propionate concentration and the “rumen content only as inoculum”, contributed much less to the distances (17% total). The “rumen content only as inoculum” explained only 8% of the variation observed in the microbial community structure. This indicates that, if the pH is within the range of 6.0–6.5, rumen bacteria can still grow in the system whether the AD inoculum is mixed with rumen inoculum at the beginning of the experiment or not. The relative abundance of rumen bacteria in Inoc_RC+AD increased whenever the pH was lower than 6.5 (Figures 2 and S3).
For the codigestion experiment, the same CCA model could have been built using either the pH level or the free ammonia level as a parameter because their trends were similar (Tables 2 and S4). Similar to the inoculum experiment, the pH was dictated by the level of free ammonia. When the pH and free ammonia levels were both considered for the CCA model, the variance inflation factor was 98 for pH and 133 for free ammonia, meaning that these two variables were strongly dependent on each other. Since, as discussed earlier, pH has a more important effect on the growth of rumen microbes, the model was build considering pH. This model (Table 2) was responsible for 73% of the distances between the microbial communities in the different reactors. Parameters such as “rumen content only as cosubstrate”, the pH, and the partial alkalinity explained a large part of the model (81%). The low buffering capacity of the substrate fed in Co_NG+RC lowered the buffering capacity and the pH in the reactor, while the relative abundance of rumen bacteria started to increase (Figures 3B, 4, and S8B). The pH values explained 28% of the total distances observed. Again, the experimental results and the multivariate statistical analysis for the codigestion experiment suggest that pH is a critical factor when developing a system that supports the growth of rumen microorganisms. Furthermore, the factor “rumen content only as cosubstrate” was shown to be an important parameter by the CCA model (explained 38% of the distances). Adding the rumen content as the only cosubstrate with Napier grass could be beneficial because the microbial populations in cow manure could out-compete the rumen bacteria when mixing these two substrates together. Another study in which rumen content was mixed with the effluent of a digester treating municipal solid waste in batch experiments also observed similar out-competition. (14) Unfortunately, the pH in the batch experiments was not reported. Since pH was shown to be a very important factor in this study, mixing cow manure and rumen content is likely detrimental for rumen bacteria not because of the out-competition of rumen microorganisms but because of the increased buffering capacity contributed by the cow manure (Figure S8B), which prevents the reactor pH from being sufficiently low (6.0–6.5, Figure 3B).
The results obtained in this study indicate that the activity of rumen hydrolytic bacteria, such as Fibrobacter, can only be supported at low pH (6.0–6.5) levels, a condition unfavorable for acetoclastic methanogens that are key microorganisms in AD for avoiding the accumulation of acetate. Acetoclastic methanogens are not present in the rumen either, but acetate does not accumulate because it is removed via absorption through the rumen walls. (36) Moreover, free ammonia levels are not as critical for rumen bacteria growth in AD as they are in the rumen, where a minimum of 41 mg of NH3–N per liter is needed, probably because the solid retention times in AD (20–30 days) are higher than those in the rumen (60–90 h). (36) The observations suggest that a two-phase configuration would be beneficial, as it provides the opportunity to promote rumen hydrolytic activity and methanogenesis. Specifically, Napier grass could be fed to a first-phase acidogenic reactor inoculated with rumen content and operated at a low pH. To retain rumen populations in the reactor, either the rumen content would need to be fed continuously as a cosubstrate or the reactor would need to be operated with a solid retention time greater than the hydraulic retention time. Gijzen et al. (8,28) operated such a fermentor designed to simulate rumen conditions; however, they did not perform microbial analyses to evaluate if the rumen hydrolytic bacteria were retained. The first-phase effluent that is rich in SCFA can be diverted to a second-phase reactor for the production of methane or other valuable products, such as medium-chain fatty acids. (66)

Supporting Information

Click to copy section linkSection link copied!

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsestengg.0c00164.

  • Calculations to estimate the rumen content availability in the US, description of chemical and microbial analyses, characterization of inocula and substrates, reactor operating parameters, experimental design, and reactor performance data (PDF)

Terms & Conditions

Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

Author Information

Click to copy section linkSection link copied!

  • Corresponding Author
    • Lutgarde Raskin - Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States Email: [email protected]
  • Authors
    • Xavier Fonoll - Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, Michigan 48109, United StatesDepartment of Chemical Engineering and Analytical Chemistry, University of Barcelona, 08028 Barcelona, SpainOrcidhttp://orcid.org/0000-0003-3304-2437
    • Shilva Shrestha - Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, Michigan 48109, United StatesDepartment of Molecular Biosciences and Bioengineering, University of Hawai’i at Ma̅noa, Honolulu, Hawaii 96822, United States
    • Samir Kumar Khanal - Department of Molecular Biosciences and Bioengineering, University of Hawai’i at Ma̅noa, Honolulu, Hawaii 96822, United StatesOrcidhttp://orcid.org/0000-0001-6680-5846
    • Joan Dosta - Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, 08028 Barcelona, Spain
    • Joan Mata-Alvarez - Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, 08028 Barcelona, Spain
  • Author Contributions

    Contributed equally to this study

  • Notes
    The authors declare no competing financial interest.

Acknowledgments

Click to copy section linkSection link copied!

This work was supported by REFRESCH (Global Challenges for the Third Century program, Office of the Provost, University of Michigan), the U.S. National Science Foundation (Sustainability Research Networks 1444745), Fundació Crèdit Andorra, Supplemental Grant, College of Tropical Agriculture and Human Resources (CTAHR), University of Hawaii, and the Sun Grant Western Regional Center at Oregon State University through a grant provided by the United States Department of Agriculture and National Institute of Food and Agriculture under proposal no. 2012-03373.

References

Click to copy section linkSection link copied!

This article references 66 other publications.

  1. 1
    American Biogas Council. ABC Biogas 101 Handbook. https://americanbiogascouncil.org/resources/ (accessed 2018-02-01).
  2. 2
    The Environmental Research & Education Foundation. Anaerobic Digestion of Municipal Solid Waste: Report on the State of Practice. EREF, 2015. https://erefdn.org/product/anaerobic-digestion-of-msw-report/
  3. 3
    California’s Laws to Accelerate Organics Recycling (2014). BioCycle , 2014.https://www.biocycle.net/2014/09/30/californias-new-laws-to-accelerate-organics-recycling/ (accessed 2017-01-01).
  4. 4
    European Biogas Association. EBA Statistical Report 2017 , 2017. https://www.europeanbiogas.eu/eba-statistical-report-2017-published-soon/ (accessed 2018-02-07).
  5. 5
    Shrestha, S.; Fonoll, X.; Khanal, S. K.; Raskin, L. Biological Strategies for Enhanced Hydrolysis of Lignocellulosic Biomass during Anaerobic Digestion: Current Status and Future Perspectives. Bioresour. Technol. 2017, 245, 12451257,  DOI: 10.1016/j.biortech.2017.08.089
  6. 6
    Bayané, A.; Guiot, S. R. Animal Digestive Strategies versus Anaerobic Digestion Bioprocesses for Biogas Production from Lignocellulosic Biomass. Rev. Environ. Sci. Bio/Technol. 2011, 10 (1), 4362,  DOI: 10.1007/s11157-010-9209-4
  7. 7
    Yue, Z.-B.; Li, W.-W.; Yu, H.-Q. Application of Rumen Microorganisms for Anaerobic Bioconversion of Lignocellulosic Biomass. Bioresour. Technol. 2013, 128, 738744,  DOI: 10.1016/j.biortech.2012.11.073
  8. 8
    Gijzen, H. J.; Zwart, K. B.; Verhagen, F. J.; Vogels, G. P. High-Rate Two-Phase Process for the Anaerobic Degradation of Cellulose, Employing Rumen Microorganisms for an Efficient Acidogenesis. Biotechnol. Bioeng. 1988, 31 (5), 418425,  DOI: 10.1002/bit.260310505
  9. 9
    Gijzen, H. J.; Schoenmakers, T. J. M.; Caerteling, C. G. M.; Vogels, G. D. Anaerobic Degradation of Papermill Sludge in a Two-Phase Digester Containing Rumen Microorganisms and Colonized Polyurethane Foam. Biotechnol. Lett. 1988, 10 (1), 6166,  DOI: 10.1007/BF01030025
  10. 10
    Kivaisi, A. K.; Gijzen, H. J.; Op den Camp, H. J. M.; Vogels, G. D. Conversion of Cereal Residues into Biogas in a Rumen-Derived Process. World J. Microbiol. Biotechnol. 1992, 8 (4), 428433,  DOI: 10.1007/BF01198760
  11. 11
    Ezeonu, F. C.; Okaka, a. N. C. Process Kinetics and Digestion Efficiency of Anaerobic Batch Fermentation of Brewer’s Spent Grains (BSG). Process Biochem. 1996, 31 (1), 712,  DOI: 10.1016/0032-9592(94)00064-6
  12. 12
    Nair, S.; Kuang, Y.; Pullammanappallil, P. Enhanced Degradation of Waste Grass Clippings in One and Two Stage Anaerobic Systems. Environ. Technol. 2005, 26 (9), 10031011,  DOI: 10.1080/09593332608618488
  13. 13
    Zhang, M.; Zhang, G.; Zhang, P.; Fan, S.; Jin, S.; Wu, D.; Fang, W. Anaerobic Digestion of Corn Stovers for Methane Production in a Novel Bionic Reactor. Bioresour. Technol. 2014, 166, 606609,  DOI: 10.1016/j.biortech.2014.05.067
  14. 14
    Chapleur, O.; Bize, A.; Serain, T.; Mazéas, L.; Bouchez, T. Co-Inoculating Ruminal Content Neither Provides Active Hydrolytic Microbes nor Improves Methanization of 13C-Cellulose in Batch Digesters. FEMS Microbiol. Ecol. 2014, 87 (3), 616629,  DOI: 10.1111/1574-6941.12249
  15. 15
    Wall, D. M.; Straccialini, B.; Allen, E.; Nolan, P.; Herrmann, C.; O’Kiely, P.; Murphy, J. D. Investigation of Effect of Particle Size and Rumen Fluid Addition on Specific Methane Yields of High Lignocellulose Grass Silage. Bioresour. Technol. 2015, 192, 266271,  DOI: 10.1016/j.biortech.2015.05.078
  16. 16
    Deng, Y.; Huang, Z.; Ruan, W.; Zhao, M.; Miao, H.; Ren, H. Co-Inoculation of Cellulolytic Rumen Bacteria with Methanogenic Sludge to Enhance Methanogenesis of Rice Straw. Int. Biodeterior. Biodegrad. 2017, 117, 224235,  DOI: 10.1016/j.ibiod.2017.01.017
  17. 17
    Murali, N.; Fernandez, S.; Ahring, B. K. Fermentation of Wet-Exploded Corn Stover for the Production of Volatile Fatty Acids. Bioresour. Technol. 2017, 227, 197204,  DOI: 10.1016/j.biortech.2016.12.012
  18. 18
    Wall, D. M.; Allen, E.; O’Shea, R.; O’Kiely, P.; Murphy, J. D. Investigating Two-Phase Digestion of Grass Silage for Demand-Driven Biogas Applications: Effect of Particle Size and Rumen Fluid Addition. Renewable Energy 2016, 86, 12151223,  DOI: 10.1016/j.renene.2015.09.049
  19. 19
    Ozbayram, E. G.; Kleinsteuber, S.; Nikolausz, M.; Ince, B.; Ince, O. Enrichment of Lignocellulose-Degrading Microbial Communities from Natural and Engineered Methanogenic Environments. Appl. Microbiol. Biotechnol. 2018, 102 (2), 10351043,  DOI: 10.1007/s00253-017-8632-7
  20. 20
    Deng, Y.; Huang, Z.; Zhao, M.; Ruan, W.; Miao, H.; Ren, H. Effects of Co-Inoculating Rice Straw with Ruminal Microbiota and Anaerobic Sludge: Digestion Performance and Spatial Distribution of Microbial Communities. Appl. Microbiol. Biotechnol. 2017, 101 (14), 59375948,  DOI: 10.1007/s00253-017-8332-3
  21. 21
    Li, K.; Zhu, H.; Zhang, Y.; Zhang, H. Characterization of the Microbial Communities in Rumen Fluid Inoculated Reactors for the Biogas Digestion of Wheat Straw. Sustainability 2017, 9 (2), 243,  DOI: 10.3390/su9020243
  22. 22
    Agematu, H.; Takahashi, T.; Hamano, Y. Continuous Volatile Fatty Acid Production from Lignocellulosic Biomass by a Novel Rumen-Mimetic Bioprocess. J. Biosci. Bioeng. 2017, 124 (5), 528533,  DOI: 10.1016/j.jbiosc.2017.06.006
  23. 23
    Ozbayram, E. G.; Akyol; Ince, B.; Karakoç, C.; Ince, O. Rumen Bacteria at Work: Bioaugmentation Strategies to Enhance Biogas Production from Cow Manure. J. Appl. Microbiol. 2018, 124 (2), 491502,  DOI: 10.1111/jam.13668
  24. 24
    Deng, Y.; Huang, Z.; Ruan, W.; Miao, H.; Shi, W.; Zhao, M. Enriching Ruminal Polysaccharide-Degrading Consortia via Co-Inoculation with Methanogenic Sludge and Microbial Mechanisms of Acidification across Lignocellulose Loading Gradients. Appl. Microbiol. Biotechnol. 2018, 102 (8), 38193830,  DOI: 10.1007/s00253-018-8877-9
  25. 25
    Quintero, M.; Castro, L.; Ortiz, C.; Guzmán, C.; Escalante, H. Enhancement of Starting up Anaerobic Digestion of Lignocellulosic Substrate: Fique’s Bagasse as an Example. Bioresour. Technol. 2012, 108, 813,  DOI: 10.1016/j.biortech.2011.12.052
  26. 26
    Song, H.; Clarke, W. P.; Blackall, L. L. Concurrent Microscopic Observations and Activity Measurements of Cellulose Hydrolyzing and Methanogenic Populations during the Batch Anaerobic Digestion of Crystalline Cellulose. Biotechnol. Bioeng. 2005, 91 (3), 369378,  DOI: 10.1002/bit.20517
  27. 27
    Li, K.; Zhu, H.; Zhang, Y.; Zhang, H. Characterization of the Microbial Communities in Rumen Fluid Inoculated Reactors for the Biogas Digestion of Wheat Straw. Sustainability 2017, 9 (2), 243,  DOI: 10.3390/su9020243
  28. 28
    Gijzen, H. J.; Zwart, K. B.; van Gelder, P. T.; Vogels, G. D. Continuous Cultivation of Rumen Microorganisms, a System with Possible Application to the Anaerobic Degradation of Lignocellulosic Waste Materials. Appl. Microbiol. Biotechnol. 1986, 25, 155162,  DOI: 10.1007/BF00938940
  29. 29
    Nagler, M.; Kozjek, K.; Etemadi, M.; Insam, H.; Podmirseg, S. M. Simple yet Effective: Microbial and Biotechnological Benefits of Rumen Liquid Addition to Lignocellulose-Degrading Biogas Plants. J. Biotechnol. 2019, 300, 110,  DOI: 10.1016/j.jbiotec.2019.05.004
  30. 30
    Zamorano-López, N.; Borrás, L.; Giménez, J. B.; Seco, A.; Aguado, D. Acclimatised Rumen Culture for Raw Microalgae Conversion into Biogas: Linking Microbial Community Structure and Operational Parameters in Anaerobic Membrane Bioreactors (AnMBR). Bioresour. Technol. 2019, 290 (July), 121787,  DOI: 10.1016/j.biortech.2019.121787
  31. 31
    Martí-Herrero, J.; Soria-Castellón, G.; Diaz-de-Basurto, A.; Alvarez, R.; Chemisana, D. Biogas from a Full Scale Digester Operated in Psychrophilic Conditions and Fed Only with Fruit and Vegetable Waste. Renewable Energy 2019, 133, 676684,  DOI: 10.1016/j.renene.2018.10.030
  32. 32
    Ferraro, A.; Massini, G.; Mazzurco Miritana, V.; Rosa, S.; Signorini, A.; Fabbricino, M. A Novel Enrichment Approach for Anaerobic Digestion of Lignocellulosic Biomass: Process Performance Enhancement through an Inoculum Habitat Selection. Bioresour. Technol. 2020, 313 (June), 123703,  DOI: 10.1016/j.biortech.2020.123703
  33. 33
    Abbas, Y.; Jamil, F.; Rafiq, S.; Ghauri, M.; Khurram, M. S.; Aslam, M.; Bokhari, A.; Faisal, A.; Rashid, U.; Yun, S. Valorization of Solid Waste Biomass by Inoculation for the Enhanced Yield of Biogas. Clean Technol. Environ. Policy 2020, 22 (2), 513522,  DOI: 10.1007/s10098-019-01799-6
  34. 34
    Anaerobic Digestion Research and Education Center (ADREC). South Campus Anaerobic Digester. Michigan State University. https://www.egr.msu.edu/bae/adrec/ (accessed 2017-05-12).
  35. 35
    Tritt, W. P.; Schuchardt, F. Materials Flow and Possibilities of Treating Liquid and Solid Wastes from Slaughterhouses in Germany. A Review. Bioresour. Technol. 1992, 41 (3), 235245,  DOI: 10.1016/0960-8524(92)90008-L
  36. 36
    McDonald, P.; Edwards, R. A.; Greenhalgh, J. F. D.; Morgan, C. A.; Sinclair, L. A.; Wilkinson, R. G. Animal Nutrition, 7th ed.; Benjamin-Cummings Publishing Company: San Francisco, CA, 2011.
  37. 37
    Mata-Alvarez, J.; Dosta, J.; Romero-Güiza, M. S.; Fonoll, X.; Peces, M.; Astals, S. A Critical Review on Anaerobic Co-Digestion Achievements between 2010 and 2013. Renewable Sustainable Energy Rev. 2014, 36, 412427,  DOI: 10.1016/j.rser.2014.04.039
  38. 38
    Prates, A.; de Oliveira, J. A.; Abecia, L.; Fondevila, M. Effects of Preservation Procedures of Rumen Inoculum on in Vitro Microbial Diversity and Fermentation. Anim. Feed Sci. Technol. 2010, 155 (2–4), 186193,  DOI: 10.1016/j.anifeedsci.2009.12.005
  39. 39
    Nguyen, D.; Wu, Z.; Shrestha, S.; Lee, P.-H.; Raskin, L.; Khanal, S. K. Intermittent Micro-Aeration: New Strategy to Control Volatile Fatty Acid Accumulation in High Organic Loading Anaerobic Digestion. Water Res. 2019, 166, 115080,  DOI: 10.1016/j.watres.2019.115080
  40. 40
    Sanaei-Moghadam, A.; Abbaspour-Fard, M. H.; Aghel, H.; Aghkhani, M. H.; Abedini-Torghabeh, J. Enhancement of Biogas Production by Co-Digestion of Potato Pulp with Cow Manure in a CSTR System. Appl. Biochem. Biotechnol. 2014, 173, 1858,  DOI: 10.1007/s12010-014-0972-5
  41. 41
    Estevez, M. M.; Sapci, Z.; Linjordet, R.; Morken, J. Incorporation of Fish By-Product into the Semi-Continuous Anaerobic Co-Digestion of Pre-Treated Lignocellulose and Cow Manure, with Recovery of Digestate’s Nutrients. Renewable Energy 2014, 66, 550558,  DOI: 10.1016/j.renene.2014.01.001
  42. 42
    Rekha, B. N.; Pandit, A. B. Performance Enhancement of Batch Anaerobic Digestion of Napier Grass by Alkali Pre-Treatment. Int. J. ChemTech Res. 2013, 5 (2), 558564
  43. 43
    Frigon, J. C.; Roy, C.; Guiot, S. R. Anaerobic Co-Digestion of Dairy Manure with Mulched Switchgrass for Improvement of the Methane Yield. Bioprocess Biosyst. Eng. 2012, 35 (3), 341349,  DOI: 10.1007/s00449-011-0572-5
  44. 44
    Chen, Y.; Cheng, J. J.; Creamer, K. S. Inhibition of Anaerobic Digestion Process: A Review. Bioresour. Technol. 2008, 99 (10), 40444064,  DOI: 10.1016/j.biortech.2007.01.057
  45. 45
    Caporaso, J. G.; Lauber, C. L.; Walters, W. A.; Berg-Lyons, D.; Lozupone, C. A.; Turnbaugh, P. J.; Fierer, N.; Knight, R. Global Patterns of 16S RRNA Diversity at a Depth of Millions of Sequences per Sample. Proc. Natl. Acad. Sci. U. S. A. 2011, 108, 45164522,  DOI: 10.1073/pnas.1000080107
  46. 46
    Kozich, J. J.; Westcott, S. L.; Baxter, N. T.; Highlander, S. K.; Schloss, P. D. Development of a Dual-Index Sequencing Strategy and Curation Pipeline for Analyzing Amplicon Sequence Data on the MiSeq Illumina Sequencing Platform. Appl. Environ. Microbiol. 2013, 79 (17), 51125120,  DOI: 10.1128/AEM.01043-13
  47. 47
    Oksanen, J. Multivariate Analysis of Ecological Communities in R: Vegan Tutorial. http://phylodiversity.net/azanne/csfar/images/8/85/Vegan.pdf (accessed 2018-02-07).
  48. 48
    ter Braak, C. J. F.; Verdonschot, P. F. M. Canonical Correspondence Analysis and Related Multivariate Methods in Aquatic Ecology. Aquat. Sci. 1995, 57 (3), 255289,  DOI: 10.1007/BF00877430
  49. 49
    Werner, J. J.; Garcia, M. L.; Perkins, S. D.; Yarasheski, K. E.; Smith, S. R.; Muegge, B. D.; Stadermann, F. J.; Derito, C. M.; Floss, C.; Madsen, E. L. Microbial Community Dynamics and Stability during an Ammonia-Induced Shift to Syntrophic Acetate Oxidation. Appl. Environ. Microbiol. 2014, 80 (11), 33753383,  DOI: 10.1128/AEM.00166-14
  50. 50
    Vanwonterghem, I.; Jensen, P. D.; Dennis, P. G.; Hugenholtz, P.; Rabaey, K.; Tyson, G. W. Deterministic Processes Guide Long-Term Synchronised Population Dynamics in Replicate Anaerobic Digesters. ISME J. 2014, 8 (10), 20152028,  DOI: 10.1038/ismej.2014.50
  51. 51
    Sträuber, H.; Schröder, M.; Kleinsteuber, S. Metabolic and Microbial Community Dynamics during the Hydrolytic and Acidogenic Fermentation in a Leach-Bed Process. Energy. Sustain. Soc. 2012, 2 (1), 13,  DOI: 10.1186/2192-0567-2-13
  52. 52
    Meng, Y.; Mumme, J.; Xu, H.; Wang, K. A Biologically Inspired Variable-PH Strategy for Enhancing Short-Chain Fatty Acids (SCFAs) Accumulation in Maize Straw Fermentation. Bioresour. Technol. 2016, 201, 329336,  DOI: 10.1016/j.biortech.2015.11.064
  53. 53
    Zhang, M.; Zhang, G.; Zhang, P.; Fan, S.; Jin, S.; Wu, D.; Fang, W. Anaerobic Digestion of Corn Stovers for Methane Production in a Novel Bionic Reactor. Bioresour. Technol. 2014, 166, 606609,  DOI: 10.1016/j.biortech.2014.05.067
  54. 54
    Ziemer, C. J.; Sharp, R.; Stern, M. D.; Cotta, M. A.; Whitehead, T. R.; Stahl, D. A. Comparison of Microbial Populations in Model and Natural Rumens Using 16S Ribosomal RNA-Targeted Probes. Environ. Microbiol. 2000, 2 (6), 632643,  DOI: 10.1046/j.1462-2920.2000.00146.x
  55. 55
    Yenigün, O.; Demirel, B. Ammonia Inhibition in Anaerobic Digestion: A Review. Process Biochem. 2013, 48 (5–6), 901911,  DOI: 10.1016/j.procbio.2013.04.012
  56. 56
    Ransom-Jones, E.; Jones, D. L.; McCarthy, A. J.; McDonald, J. E. The Fibrobacteres: An Important Phylum of Cellulose-Degrading Bacteria. Microb. Ecol. 2012, 63 (2), 267281,  DOI: 10.1007/s00248-011-9998-1
  57. 57
    Arntzen, M.; Várnai, A.; Mackie, R. I.; Eijsink, V. G. H.; Pope, P. B. Outer Membrane Vesicles from Fibrobacter Succinogenes S85 Contain an Array of Carbohydrate-Active Enzymes with Versatile Polysaccharide-Degrading Capacity. Environ. Microbiol. 2017, 19 (7), 27012714,  DOI: 10.1111/1462-2920.13770
  58. 58
    Weimer, P. J.; Russell, J. B.; Muck, R. E. Lessons from the Cow: What the Ruminant Animal Can Teach Us about Consolidated Bioprocessing of Cellulosic Biomass. Bioresour. Technol. 2009, 100 (21), 53235331,  DOI: 10.1016/j.biortech.2009.04.075
  59. 59
    Stanton, T. B. Glucose Metabolism of Treponema Bryantii, an Anaerobic Rumen Spirochete. Can. J. Microbiol. 1984, 30 (5), 526531,  DOI: 10.1139/m84-080
  60. 60
    Kudo, H.; Cheng, K.-J.; Costerton, J. W. Interactions between Treponema Bryantii and Cellulolytic Bacteria in the in Vitro Degradation of Straw Cellulose. Can. J. Microbiol. 1987, 33 (3), 244248,  DOI: 10.1139/m87-041
  61. 61
    Hahnke, S.; Langer, T.; Koeck, D. E.; Klocke, M. Description of Proteiniphilum Saccharofermentans Sp. Nov., Petrimonas Mucosa Sp. Nov. and Fermentimonas Caenicola Gen. Nov., Sp. Nov., Isolated from Mesophilic Laboratory-Scale Biogas Reactors, and Emended Description of the Genus Proteiniphilum. Int. J. Syst. Evol. Microbiol. 2016, 66 (3), 14661475,  DOI: 10.1099/ijsem.0.000902
  62. 62
    Azman, S.; Khadem, A. F.; Van Lier, J. B.; Zeeman, G.; Plugge, C. M. Presence and Role of Anaerobic Hydrolytic Microbes in Conversion of Lignocellulosic Biomass for Biogas Production. Crit. Rev. Environ. Sci. Technol. 2015, 45 (23), 25232564,  DOI: 10.1080/10643389.2015.1053727
  63. 63
    Chow, J. M.; Russell, J. B. Effect of PH and Monensin on Glucose Transport by Fibrobacter Succinogenes, a Cellulolytic Ruminal Bacterium. Appl. Environ. Microbiol. 1992, 58 (4), 11151120,  DOI: 10.1128/AEM.58.4.1115-1120.1992
  64. 64
    Russell, J. B.; Dombrowski, D. B. Effect of PH on the Efficiency of Growth by Pure Cultures of Rumen Bacteria in Continuous Culture. Appl. Environ. Microbiol. 1980, 39 (3), 604610,  DOI: 10.1128/AEM.39.3.604-610.1980
  65. 65
    Weimer, P. J. Effects of Dilution Rate and PH on the Ruminal Cellulolytic Bacterium Fibrobacter Succinogenes S85 in Cellulose-Fed Continuous Culture. Arch. Microbiol. 1993, 160, 288294,  DOI: 10.1007/BF00292079
  66. 66
    Kleerebezem, R.; Joosse, B.; Rozendal, R.; Van Loosdrecht, M. C. M. Anaerobic Digestion without Biogas?. Rev. Environ. Sci. Bio/Technol. 2015, 14, 787,  DOI: 10.1007/s11157-015-9374-6

Cited By

Click to copy section linkSection link copied!
Citation Statements
Explore this article's citation statements on scite.ai

This article is cited by 26 publications.

  1. Wachiranon Chuenchart, K. C. Surendra, Samir Kumar Khanal. Understanding Anaerobic Co-digestion of Organic Wastes through Meta-Analysis. ACS ES&T Engineering 2024, 4 (5) , 1177-1192. https://doi.org/10.1021/acsestengg.3c00598
  2. Xavier Fonoll, Kuang Zhu, Lucy Aley, Shilva Shrestha, Lutgarde Raskin. Simulating Rumen Conditions Using an Anaerobic Dynamic Membrane Bioreactor to Enhance Hydrolysis of Lignocellulosic Biomass. Environmental Science & Technology 2024, 58 (3) , 1741-1751. https://doi.org/10.1021/acs.est.3c06478
  3. Zhuoying Wu, Duc Nguyen, Shilva Shrestha, Lutgarde Raskin, Samir Kumar Khanal, Po-Heng Lee. Evaluation of Nanaerobic Digestion as a Mechanism to Explain Surplus Methane Production in Animal Rumina and Engineered Digesters. Environmental Science & Technology 2023, 57 (33) , 12302-12314. https://doi.org/10.1021/acs.est.2c07813
  4. Sherif Ismail, Mohamed Elsamadony, Mohnad Abdalla, Shou-Qing Ni, Ahmed Tawfik. Stimulating the Fermentation Process of Industrial Food Waste via Nonionic Surfactant/Graphene Nanosheet Combined Supplementation. ACS ES&T Engineering 2022, 2 (11) , 2043-2057. https://doi.org/10.1021/acsestengg.2c00140
  5. Zi-Qian Geng, Ding-Kang Qian, Zhi-Yi Hu, Shuai Wang, Yang Yan, Mark C. M. van Loosdrecht, Raymond Jianxiong Zeng, Fang Zhang. Identification of Extracellular Key Enzyme and Intracellular Metabolic Pathway in Alginate-Degrading Consortia via an Integrated Metaproteomic/Metagenomic Analysis. Environmental Science & Technology 2021, 55 (24) , 16636-16645. https://doi.org/10.1021/acs.est.1c05289
  6. Ding-Kang Qian, Zi-Qian Geng, Jie Tang, Shuai Wang, Zhi-Yi Hu, Kun Dai, Mark C. M. van Loosdrecht, Raymond Jianxiong Zeng, Fang Zhang. Highly Selective Fermentation of Waste-Activated Sludge by Alginate-Degrading Consortia. ACS ES&T Engineering 2021, 1 (11) , 1606-1617. https://doi.org/10.1021/acsestengg.1c00257
  7. Sachin Krushna Bhujbal, Amrita Preetam, Pooja Ghosh, Virendra Kumar Vijay, Vivek Kumar. Machine learning and response surface methodology for optimization of bioenergy production from sugarcane bagasse biochar-improved anaerobic digestion. Process Safety and Environmental Protection 2025, 196 , 106907. https://doi.org/10.1016/j.psep.2025.106907
  8. Anastasia Makri, Spyridon Ntougias, Paraschos Melidis. Enhancing Anaerobic Degradation of Corn Stover Residues and Biogas Production via Rumen Microorganisms. Environmental Processes 2024, 11 (4) https://doi.org/10.1007/s40710-024-00738-y
  9. Ajay Thapa, Onita D. Basu, Xunchang Fei, Kaushik Venkiteshwaran, Abid Hussain. Biological pretreatment of organic waste for short-chain fatty acids production: State-of-the-art, advances, challenges and prospectives. Chemical Engineering Journal 2024, 500 , 157018. https://doi.org/10.1016/j.cej.2024.157018
  10. Yihang Xiao, Hamish R. Mackey, Wentao Tang, Hui Lu, Tianwei Hao. Disentangling microbial niche balance and intermediates’ trade-offs for anaerobic digestion stability and regulation. Water Research 2024, 261 , 122000. https://doi.org/10.1016/j.watres.2024.122000
  11. Sugumar Mohanasundaram, Venkatramanan Varadharajan, Mayakannan Selvaraju, Sivasubramanian Manikandan, Subbaiya Ramasamy, Mani Jayakumar, Venkatesa Prabhu Sundramurthy, Gurunathan Baskar, Arivalagan Pugazhendhi. RETRACTED: Green ammonia as peerless entity for realm of clean-energy carrier toward zero carbon emission: Purviews, neoteric tendencies, potentialities and downsides. Fuel 2024, 365 , 131118. https://doi.org/10.1016/j.fuel.2024.131118
  12. Jinsong Liang, Ru Zhang, Jianning Chang, Le Chen, Mohammad Nabi, Haibo Zhang, Guangming Zhang, Panyue Zhang. Rumen microbes, enzymes, metabolisms, and application in lignocellulosic waste conversion - A comprehensive review. Biotechnology Advances 2024, 71 , 108308. https://doi.org/10.1016/j.biotechadv.2024.108308
  13. Yuchao Zhao, Shiqiang Yu, Jian Tan, Ying Wang, Liuxue Li, Huiying Zhao, Ming Liu, Linshu Jiang. Bioconversion of citrus waste by long-term DMSO-cryopreserved rumen fluid to volatile fatty acids and biogas is feasible: A microbiome perspective. Journal of Environmental Management 2024, 351 , 119693. https://doi.org/10.1016/j.jenvman.2023.119693
  14. Xuejiao Lyu, Mujaheed Nuhu, Pieter Candry, Jenna Wolfanger, Michael Betenbaugh, Alexis Saldivar, Cristal Zuniga, Ying Wang, Shilva Shrestha. Top-down and bottom-up microbiome engineering approaches to enable biomanufacturing from waste biomass. Journal of Industrial Microbiology and Biotechnology 2024, 51 https://doi.org/10.1093/jimb/kuae025
  15. Wenwen Chen, Yiwei Zeng, Huanying Liu, Dezhi Sun, Xinying Liu, Haiyu Xu, Hongbin Wu, Bin Qiu, Yan Dang. Granular activated carbon enhances volatile fatty acid production in the anaerobic fermentation of garden wastes. Frontiers in Bioengineering and Biotechnology 2023, 11 https://doi.org/10.3389/fbioe.2023.1330293
  16. Sachin Krushna Bhujbal, Pooja Ghosh, Virendra Kumar Vijay, Manish Kumar. Ruminal content biochar supplementation for enhanced biomethanation of rice straw: Focusing on biochar characterization and dose optimization. Science of The Total Environment 2023, 905 , 167250. https://doi.org/10.1016/j.scitotenv.2023.167250
  17. Jinsong Liang, Muhammad Zubair, Le Chen, Jianning Chang, Wei Fang, Mohammad Nabi, Wenjing Yang, Yajie Zhang, Yuehan Li, Panyue Zhang, Guangming Zhang, Aijie Wang. Rumen microbe fermentation of corn stalk to produce volatile fatty acids in a semi-continuous reactor. Fuel 2023, 350 , 128905. https://doi.org/10.1016/j.fuel.2023.128905
  18. Ankita Das, Sandeep Das, Nandita Das, Prisha Pandey, Birson Ingti, Vladimir Panchenko, Vadim Bolshev, Andrey Kovalev, Piyush Pandey. Advancements and Innovations in Harnessing Microbial Processes for Enhanced Biogas Production from Waste Materials. Agriculture 2023, 13 (9) , 1689. https://doi.org/10.3390/agriculture13091689
  19. Christy E. Manyi-Loh, Ryk Lues. Anaerobic Digestion of Lignocellulosic Biomass: Substrate Characteristics (Challenge) and Innovation. Fermentation 2023, 9 (8) , 755. https://doi.org/10.3390/fermentation9080755
  20. Estelle Leca, Bastien Zennaro, Jérôme Hamelin, Hélène Carrère, Cecilia Sambusiti. Use of additives to improve collective biogas plant performances: A comprehensive review. Biotechnology Advances 2023, 65 , 108129. https://doi.org/10.1016/j.biotechadv.2023.108129
  21. Xavier Fonoll, Kuang Zhu, Lucy Aley, Shilva Shrestha, Lutgarde Raskin. Simulating Rumen Conditions using an Anaerobic Dynamic Membrane Bioreactor to Enhance Hydrolysis of Lignocellulosic Biomass. 2023https://doi.org/10.1101/2023.02.20.529314
  22. Laura E. Walls, Peter Otoupal, Rodrigo Ledesma-Amaro, Sharon B. Velasquez-Orta, John M. Gladden, Leonardo Rios-Solis. Bioconversion of cellulose into bisabolene using Ruminococcus flavefaciens and Rhodosporidium toruloides. Bioresource Technology 2023, 368 , 128216. https://doi.org/10.1016/j.biortech.2022.128216
  23. Diana Cestari Bon, Dagoberto Yukio Okada, Cassiana Maria Reganhan Coneglian. Benefits of biological additive inoculation in the treatment of effluent from the paper recycling industry. Journal of Water Process Engineering 2022, 50 , 103269. https://doi.org/10.1016/j.jwpe.2022.103269
  24. Muhammad Sohail, Alam Khan, Malik Badshah, Allan Degen, Guo Yang, Hu Liu, Jianwei Zhou, Ruijun Long. Yak rumen fluid inoculum increases biogas production from sheep manure substrate. Bioresource Technology 2022, 362 , 127801. https://doi.org/10.1016/j.biortech.2022.127801
  25. Jinsong Liang, Wei Fang, Jianning Chang, Guangming Zhang, Weifang Ma, Mohammad Nabi, Muhammad Zubair, Ru Zhang, Le Chen, Jianghao Huang, Panyue Zhang. Long-term rumen microorganism fermentation of corn stover in vitro for volatile fatty acid production. Bioresource Technology 2022, 358 , 127447. https://doi.org/10.1016/j.biortech.2022.127447
  26. Tianwei Hao, Yihang Xiao, Sunita Varjani. Transiting from the inhibited steady-state to the steady-state through the ammonium bicarbonate mediation in the anaerobic digestion of low-C/N-ratio food wastes. Bioresource Technology 2022, 351 , 127046. https://doi.org/10.1016/j.biortech.2022.127046
  27. Yeadam Jo, Chaeyoung Rhee, Hyungmin Choi, Juhee Shin, Seung Gu Shin, Changsoo Lee. Long-term effectiveness of bioaugmentation with rumen culture in continuous anaerobic digestion of food and vegetable wastes under feed composition fluctuations. Bioresource Technology 2021, 338 , 125500. https://doi.org/10.1016/j.biortech.2021.125500

ACS ES&T Engineering

Cite this: ACS EST Engg. 2021, 1, 3, 424–435
Click to copy citationCitation copied!
https://doi.org/10.1021/acsestengg.0c00164
Published January 31, 2021

Copyright © 2021 The Authors. Published by American Chemical Society. This publication is licensed under

CC-BY-NC-ND 4.0 .

Article Views

2684

Altmetric

-

Citations

Learn about these metrics

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.

Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.

The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated.

  • Abstract

    Figure 1

    Figure 1. (A) Short-chain fatty acid (SCFA) accumulation, (B) pH, and (C) specific methane production in the reactors. Organic loading rate (OLR) and retention time in Inoc_AD, Inoc_RC+AD (−·−), and Inoc_RC (− −). The vertical line indicates the change from cow feces to cow manure on day 81. The red arrow and green lines with circles indicate the buffer addition in Inoc_RC and Inoc_RC+AD, respectively. The legend refers to the three reactors with the type of inocula used.

    Figure 2

    Figure 2. Relative abundances of OTUs grouped by origin in reactors Inoc_RC, Inoc_RC+AD, and Inoc_AD. OTUs were grouped in eight categories depending on whether they were present in the rumen content inoculum only, the AD inoculum only, the cow manure only, various combinations of these three sources, or none of them (“Others”). Samples from day 28 for Inoc_RC+AD and Day 75 for Inoc_AD could not be sequenced.

    Figure 3

    Figure 3. (A) Short-chain fatty acid (SCFA) accumulation, (B) pH, and (C) methane production in the reactors showing (A) the organic loading rate (OLR) (− −) and (B) retention time (− −) applied in the reactors. The vertical line on day 44 indicates the start of continuous buffer addition.

    Figure 4

    Figure 4. Relative abundances of OTUs grouped by origin in reactors Co_NG+CM, Co_NG+CM+RC, and Co_NG+RC. OTUs were grouped in eight categories depending on whether they were present in the rumen content only, the AD inoculum only, the cow manure only, a combination of these three sources, or none of them (“Others”). Samples from day 72 for Co_NG+CM and day 51 for Co_NG+RC could not be sequenced.

  • References


    This article references 66 other publications.

    1. 1
      American Biogas Council. ABC Biogas 101 Handbook. https://americanbiogascouncil.org/resources/ (accessed 2018-02-01).
    2. 2
      The Environmental Research & Education Foundation. Anaerobic Digestion of Municipal Solid Waste: Report on the State of Practice. EREF, 2015. https://erefdn.org/product/anaerobic-digestion-of-msw-report/
    3. 3
      California’s Laws to Accelerate Organics Recycling (2014). BioCycle , 2014.https://www.biocycle.net/2014/09/30/californias-new-laws-to-accelerate-organics-recycling/ (accessed 2017-01-01).
    4. 4
      European Biogas Association. EBA Statistical Report 2017 , 2017. https://www.europeanbiogas.eu/eba-statistical-report-2017-published-soon/ (accessed 2018-02-07).
    5. 5
      Shrestha, S.; Fonoll, X.; Khanal, S. K.; Raskin, L. Biological Strategies for Enhanced Hydrolysis of Lignocellulosic Biomass during Anaerobic Digestion: Current Status and Future Perspectives. Bioresour. Technol. 2017, 245, 12451257,  DOI: 10.1016/j.biortech.2017.08.089
    6. 6
      Bayané, A.; Guiot, S. R. Animal Digestive Strategies versus Anaerobic Digestion Bioprocesses for Biogas Production from Lignocellulosic Biomass. Rev. Environ. Sci. Bio/Technol. 2011, 10 (1), 4362,  DOI: 10.1007/s11157-010-9209-4
    7. 7
      Yue, Z.-B.; Li, W.-W.; Yu, H.-Q. Application of Rumen Microorganisms for Anaerobic Bioconversion of Lignocellulosic Biomass. Bioresour. Technol. 2013, 128, 738744,  DOI: 10.1016/j.biortech.2012.11.073
    8. 8
      Gijzen, H. J.; Zwart, K. B.; Verhagen, F. J.; Vogels, G. P. High-Rate Two-Phase Process for the Anaerobic Degradation of Cellulose, Employing Rumen Microorganisms for an Efficient Acidogenesis. Biotechnol. Bioeng. 1988, 31 (5), 418425,  DOI: 10.1002/bit.260310505
    9. 9
      Gijzen, H. J.; Schoenmakers, T. J. M.; Caerteling, C. G. M.; Vogels, G. D. Anaerobic Degradation of Papermill Sludge in a Two-Phase Digester Containing Rumen Microorganisms and Colonized Polyurethane Foam. Biotechnol. Lett. 1988, 10 (1), 6166,  DOI: 10.1007/BF01030025
    10. 10
      Kivaisi, A. K.; Gijzen, H. J.; Op den Camp, H. J. M.; Vogels, G. D. Conversion of Cereal Residues into Biogas in a Rumen-Derived Process. World J. Microbiol. Biotechnol. 1992, 8 (4), 428433,  DOI: 10.1007/BF01198760
    11. 11
      Ezeonu, F. C.; Okaka, a. N. C. Process Kinetics and Digestion Efficiency of Anaerobic Batch Fermentation of Brewer’s Spent Grains (BSG). Process Biochem. 1996, 31 (1), 712,  DOI: 10.1016/0032-9592(94)00064-6
    12. 12
      Nair, S.; Kuang, Y.; Pullammanappallil, P. Enhanced Degradation of Waste Grass Clippings in One and Two Stage Anaerobic Systems. Environ. Technol. 2005, 26 (9), 10031011,  DOI: 10.1080/09593332608618488
    13. 13
      Zhang, M.; Zhang, G.; Zhang, P.; Fan, S.; Jin, S.; Wu, D.; Fang, W. Anaerobic Digestion of Corn Stovers for Methane Production in a Novel Bionic Reactor. Bioresour. Technol. 2014, 166, 606609,  DOI: 10.1016/j.biortech.2014.05.067
    14. 14
      Chapleur, O.; Bize, A.; Serain, T.; Mazéas, L.; Bouchez, T. Co-Inoculating Ruminal Content Neither Provides Active Hydrolytic Microbes nor Improves Methanization of 13C-Cellulose in Batch Digesters. FEMS Microbiol. Ecol. 2014, 87 (3), 616629,  DOI: 10.1111/1574-6941.12249
    15. 15
      Wall, D. M.; Straccialini, B.; Allen, E.; Nolan, P.; Herrmann, C.; O’Kiely, P.; Murphy, J. D. Investigation of Effect of Particle Size and Rumen Fluid Addition on Specific Methane Yields of High Lignocellulose Grass Silage. Bioresour. Technol. 2015, 192, 266271,  DOI: 10.1016/j.biortech.2015.05.078
    16. 16
      Deng, Y.; Huang, Z.; Ruan, W.; Zhao, M.; Miao, H.; Ren, H. Co-Inoculation of Cellulolytic Rumen Bacteria with Methanogenic Sludge to Enhance Methanogenesis of Rice Straw. Int. Biodeterior. Biodegrad. 2017, 117, 224235,  DOI: 10.1016/j.ibiod.2017.01.017
    17. 17
      Murali, N.; Fernandez, S.; Ahring, B. K. Fermentation of Wet-Exploded Corn Stover for the Production of Volatile Fatty Acids. Bioresour. Technol. 2017, 227, 197204,  DOI: 10.1016/j.biortech.2016.12.012
    18. 18
      Wall, D. M.; Allen, E.; O’Shea, R.; O’Kiely, P.; Murphy, J. D. Investigating Two-Phase Digestion of Grass Silage for Demand-Driven Biogas Applications: Effect of Particle Size and Rumen Fluid Addition. Renewable Energy 2016, 86, 12151223,  DOI: 10.1016/j.renene.2015.09.049
    19. 19
      Ozbayram, E. G.; Kleinsteuber, S.; Nikolausz, M.; Ince, B.; Ince, O. Enrichment of Lignocellulose-Degrading Microbial Communities from Natural and Engineered Methanogenic Environments. Appl. Microbiol. Biotechnol. 2018, 102 (2), 10351043,  DOI: 10.1007/s00253-017-8632-7
    20. 20
      Deng, Y.; Huang, Z.; Zhao, M.; Ruan, W.; Miao, H.; Ren, H. Effects of Co-Inoculating Rice Straw with Ruminal Microbiota and Anaerobic Sludge: Digestion Performance and Spatial Distribution of Microbial Communities. Appl. Microbiol. Biotechnol. 2017, 101 (14), 59375948,  DOI: 10.1007/s00253-017-8332-3
    21. 21
      Li, K.; Zhu, H.; Zhang, Y.; Zhang, H. Characterization of the Microbial Communities in Rumen Fluid Inoculated Reactors for the Biogas Digestion of Wheat Straw. Sustainability 2017, 9 (2), 243,  DOI: 10.3390/su9020243
    22. 22
      Agematu, H.; Takahashi, T.; Hamano, Y. Continuous Volatile Fatty Acid Production from Lignocellulosic Biomass by a Novel Rumen-Mimetic Bioprocess. J. Biosci. Bioeng. 2017, 124 (5), 528533,  DOI: 10.1016/j.jbiosc.2017.06.006
    23. 23
      Ozbayram, E. G.; Akyol; Ince, B.; Karakoç, C.; Ince, O. Rumen Bacteria at Work: Bioaugmentation Strategies to Enhance Biogas Production from Cow Manure. J. Appl. Microbiol. 2018, 124 (2), 491502,  DOI: 10.1111/jam.13668
    24. 24
      Deng, Y.; Huang, Z.; Ruan, W.; Miao, H.; Shi, W.; Zhao, M. Enriching Ruminal Polysaccharide-Degrading Consortia via Co-Inoculation with Methanogenic Sludge and Microbial Mechanisms of Acidification across Lignocellulose Loading Gradients. Appl. Microbiol. Biotechnol. 2018, 102 (8), 38193830,  DOI: 10.1007/s00253-018-8877-9
    25. 25
      Quintero, M.; Castro, L.; Ortiz, C.; Guzmán, C.; Escalante, H. Enhancement of Starting up Anaerobic Digestion of Lignocellulosic Substrate: Fique’s Bagasse as an Example. Bioresour. Technol. 2012, 108, 813,  DOI: 10.1016/j.biortech.2011.12.052
    26. 26
      Song, H.; Clarke, W. P.; Blackall, L. L. Concurrent Microscopic Observations and Activity Measurements of Cellulose Hydrolyzing and Methanogenic Populations during the Batch Anaerobic Digestion of Crystalline Cellulose. Biotechnol. Bioeng. 2005, 91 (3), 369378,  DOI: 10.1002/bit.20517
    27. 27
      Li, K.; Zhu, H.; Zhang, Y.; Zhang, H. Characterization of the Microbial Communities in Rumen Fluid Inoculated Reactors for the Biogas Digestion of Wheat Straw. Sustainability 2017, 9 (2), 243,  DOI: 10.3390/su9020243
    28. 28
      Gijzen, H. J.; Zwart, K. B.; van Gelder, P. T.; Vogels, G. D. Continuous Cultivation of Rumen Microorganisms, a System with Possible Application to the Anaerobic Degradation of Lignocellulosic Waste Materials. Appl. Microbiol. Biotechnol. 1986, 25, 155162,  DOI: 10.1007/BF00938940
    29. 29
      Nagler, M.; Kozjek, K.; Etemadi, M.; Insam, H.; Podmirseg, S. M. Simple yet Effective: Microbial and Biotechnological Benefits of Rumen Liquid Addition to Lignocellulose-Degrading Biogas Plants. J. Biotechnol. 2019, 300, 110,  DOI: 10.1016/j.jbiotec.2019.05.004
    30. 30
      Zamorano-López, N.; Borrás, L.; Giménez, J. B.; Seco, A.; Aguado, D. Acclimatised Rumen Culture for Raw Microalgae Conversion into Biogas: Linking Microbial Community Structure and Operational Parameters in Anaerobic Membrane Bioreactors (AnMBR). Bioresour. Technol. 2019, 290 (July), 121787,  DOI: 10.1016/j.biortech.2019.121787
    31. 31
      Martí-Herrero, J.; Soria-Castellón, G.; Diaz-de-Basurto, A.; Alvarez, R.; Chemisana, D. Biogas from a Full Scale Digester Operated in Psychrophilic Conditions and Fed Only with Fruit and Vegetable Waste. Renewable Energy 2019, 133, 676684,  DOI: 10.1016/j.renene.2018.10.030
    32. 32
      Ferraro, A.; Massini, G.; Mazzurco Miritana, V.; Rosa, S.; Signorini, A.; Fabbricino, M. A Novel Enrichment Approach for Anaerobic Digestion of Lignocellulosic Biomass: Process Performance Enhancement through an Inoculum Habitat Selection. Bioresour. Technol. 2020, 313 (June), 123703,  DOI: 10.1016/j.biortech.2020.123703
    33. 33
      Abbas, Y.; Jamil, F.; Rafiq, S.; Ghauri, M.; Khurram, M. S.; Aslam, M.; Bokhari, A.; Faisal, A.; Rashid, U.; Yun, S. Valorization of Solid Waste Biomass by Inoculation for the Enhanced Yield of Biogas. Clean Technol. Environ. Policy 2020, 22 (2), 513522,  DOI: 10.1007/s10098-019-01799-6
    34. 34
      Anaerobic Digestion Research and Education Center (ADREC). South Campus Anaerobic Digester. Michigan State University. https://www.egr.msu.edu/bae/adrec/ (accessed 2017-05-12).
    35. 35
      Tritt, W. P.; Schuchardt, F. Materials Flow and Possibilities of Treating Liquid and Solid Wastes from Slaughterhouses in Germany. A Review. Bioresour. Technol. 1992, 41 (3), 235245,  DOI: 10.1016/0960-8524(92)90008-L
    36. 36
      McDonald, P.; Edwards, R. A.; Greenhalgh, J. F. D.; Morgan, C. A.; Sinclair, L. A.; Wilkinson, R. G. Animal Nutrition, 7th ed.; Benjamin-Cummings Publishing Company: San Francisco, CA, 2011.
    37. 37
      Mata-Alvarez, J.; Dosta, J.; Romero-Güiza, M. S.; Fonoll, X.; Peces, M.; Astals, S. A Critical Review on Anaerobic Co-Digestion Achievements between 2010 and 2013. Renewable Sustainable Energy Rev. 2014, 36, 412427,  DOI: 10.1016/j.rser.2014.04.039
    38. 38
      Prates, A.; de Oliveira, J. A.; Abecia, L.; Fondevila, M. Effects of Preservation Procedures of Rumen Inoculum on in Vitro Microbial Diversity and Fermentation. Anim. Feed Sci. Technol. 2010, 155 (2–4), 186193,  DOI: 10.1016/j.anifeedsci.2009.12.005
    39. 39
      Nguyen, D.; Wu, Z.; Shrestha, S.; Lee, P.-H.; Raskin, L.; Khanal, S. K. Intermittent Micro-Aeration: New Strategy to Control Volatile Fatty Acid Accumulation in High Organic Loading Anaerobic Digestion. Water Res. 2019, 166, 115080,  DOI: 10.1016/j.watres.2019.115080
    40. 40
      Sanaei-Moghadam, A.; Abbaspour-Fard, M. H.; Aghel, H.; Aghkhani, M. H.; Abedini-Torghabeh, J. Enhancement of Biogas Production by Co-Digestion of Potato Pulp with Cow Manure in a CSTR System. Appl. Biochem. Biotechnol. 2014, 173, 1858,  DOI: 10.1007/s12010-014-0972-5
    41. 41
      Estevez, M. M.; Sapci, Z.; Linjordet, R.; Morken, J. Incorporation of Fish By-Product into the Semi-Continuous Anaerobic Co-Digestion of Pre-Treated Lignocellulose and Cow Manure, with Recovery of Digestate’s Nutrients. Renewable Energy 2014, 66, 550558,  DOI: 10.1016/j.renene.2014.01.001
    42. 42
      Rekha, B. N.; Pandit, A. B. Performance Enhancement of Batch Anaerobic Digestion of Napier Grass by Alkali Pre-Treatment. Int. J. ChemTech Res. 2013, 5 (2), 558564
    43. 43
      Frigon, J. C.; Roy, C.; Guiot, S. R. Anaerobic Co-Digestion of Dairy Manure with Mulched Switchgrass for Improvement of the Methane Yield. Bioprocess Biosyst. Eng. 2012, 35 (3), 341349,  DOI: 10.1007/s00449-011-0572-5
    44. 44
      Chen, Y.; Cheng, J. J.; Creamer, K. S. Inhibition of Anaerobic Digestion Process: A Review. Bioresour. Technol. 2008, 99 (10), 40444064,  DOI: 10.1016/j.biortech.2007.01.057
    45. 45
      Caporaso, J. G.; Lauber, C. L.; Walters, W. A.; Berg-Lyons, D.; Lozupone, C. A.; Turnbaugh, P. J.; Fierer, N.; Knight, R. Global Patterns of 16S RRNA Diversity at a Depth of Millions of Sequences per Sample. Proc. Natl. Acad. Sci. U. S. A. 2011, 108, 45164522,  DOI: 10.1073/pnas.1000080107
    46. 46
      Kozich, J. J.; Westcott, S. L.; Baxter, N. T.; Highlander, S. K.; Schloss, P. D. Development of a Dual-Index Sequencing Strategy and Curation Pipeline for Analyzing Amplicon Sequence Data on the MiSeq Illumina Sequencing Platform. Appl. Environ. Microbiol. 2013, 79 (17), 51125120,  DOI: 10.1128/AEM.01043-13
    47. 47
      Oksanen, J. Multivariate Analysis of Ecological Communities in R: Vegan Tutorial. http://phylodiversity.net/azanne/csfar/images/8/85/Vegan.pdf (accessed 2018-02-07).
    48. 48
      ter Braak, C. J. F.; Verdonschot, P. F. M. Canonical Correspondence Analysis and Related Multivariate Methods in Aquatic Ecology. Aquat. Sci. 1995, 57 (3), 255289,  DOI: 10.1007/BF00877430
    49. 49
      Werner, J. J.; Garcia, M. L.; Perkins, S. D.; Yarasheski, K. E.; Smith, S. R.; Muegge, B. D.; Stadermann, F. J.; Derito, C. M.; Floss, C.; Madsen, E. L. Microbial Community Dynamics and Stability during an Ammonia-Induced Shift to Syntrophic Acetate Oxidation. Appl. Environ. Microbiol. 2014, 80 (11), 33753383,  DOI: 10.1128/AEM.00166-14
    50. 50
      Vanwonterghem, I.; Jensen, P. D.; Dennis, P. G.; Hugenholtz, P.; Rabaey, K.; Tyson, G. W. Deterministic Processes Guide Long-Term Synchronised Population Dynamics in Replicate Anaerobic Digesters. ISME J. 2014, 8 (10), 20152028,  DOI: 10.1038/ismej.2014.50
    51. 51
      Sträuber, H.; Schröder, M.; Kleinsteuber, S. Metabolic and Microbial Community Dynamics during the Hydrolytic and Acidogenic Fermentation in a Leach-Bed Process. Energy. Sustain. Soc. 2012, 2 (1), 13,  DOI: 10.1186/2192-0567-2-13
    52. 52
      Meng, Y.; Mumme, J.; Xu, H.; Wang, K. A Biologically Inspired Variable-PH Strategy for Enhancing Short-Chain Fatty Acids (SCFAs) Accumulation in Maize Straw Fermentation. Bioresour. Technol. 2016, 201, 329336,  DOI: 10.1016/j.biortech.2015.11.064
    53. 53
      Zhang, M.; Zhang, G.; Zhang, P.; Fan, S.; Jin, S.; Wu, D.; Fang, W. Anaerobic Digestion of Corn Stovers for Methane Production in a Novel Bionic Reactor. Bioresour. Technol. 2014, 166, 606609,  DOI: 10.1016/j.biortech.2014.05.067
    54. 54
      Ziemer, C. J.; Sharp, R.; Stern, M. D.; Cotta, M. A.; Whitehead, T. R.; Stahl, D. A. Comparison of Microbial Populations in Model and Natural Rumens Using 16S Ribosomal RNA-Targeted Probes. Environ. Microbiol. 2000, 2 (6), 632643,  DOI: 10.1046/j.1462-2920.2000.00146.x
    55. 55
      Yenigün, O.; Demirel, B. Ammonia Inhibition in Anaerobic Digestion: A Review. Process Biochem. 2013, 48 (5–6), 901911,  DOI: 10.1016/j.procbio.2013.04.012
    56. 56
      Ransom-Jones, E.; Jones, D. L.; McCarthy, A. J.; McDonald, J. E. The Fibrobacteres: An Important Phylum of Cellulose-Degrading Bacteria. Microb. Ecol. 2012, 63 (2), 267281,  DOI: 10.1007/s00248-011-9998-1
    57. 57
      Arntzen, M.; Várnai, A.; Mackie, R. I.; Eijsink, V. G. H.; Pope, P. B. Outer Membrane Vesicles from Fibrobacter Succinogenes S85 Contain an Array of Carbohydrate-Active Enzymes with Versatile Polysaccharide-Degrading Capacity. Environ. Microbiol. 2017, 19 (7), 27012714,  DOI: 10.1111/1462-2920.13770
    58. 58
      Weimer, P. J.; Russell, J. B.; Muck, R. E. Lessons from the Cow: What the Ruminant Animal Can Teach Us about Consolidated Bioprocessing of Cellulosic Biomass. Bioresour. Technol. 2009, 100 (21), 53235331,  DOI: 10.1016/j.biortech.2009.04.075
    59. 59
      Stanton, T. B. Glucose Metabolism of Treponema Bryantii, an Anaerobic Rumen Spirochete. Can. J. Microbiol. 1984, 30 (5), 526531,  DOI: 10.1139/m84-080
    60. 60
      Kudo, H.; Cheng, K.-J.; Costerton, J. W. Interactions between Treponema Bryantii and Cellulolytic Bacteria in the in Vitro Degradation of Straw Cellulose. Can. J. Microbiol. 1987, 33 (3), 244248,  DOI: 10.1139/m87-041
    61. 61
      Hahnke, S.; Langer, T.; Koeck, D. E.; Klocke, M. Description of Proteiniphilum Saccharofermentans Sp. Nov., Petrimonas Mucosa Sp. Nov. and Fermentimonas Caenicola Gen. Nov., Sp. Nov., Isolated from Mesophilic Laboratory-Scale Biogas Reactors, and Emended Description of the Genus Proteiniphilum. Int. J. Syst. Evol. Microbiol. 2016, 66 (3), 14661475,  DOI: 10.1099/ijsem.0.000902
    62. 62
      Azman, S.; Khadem, A. F.; Van Lier, J. B.; Zeeman, G.; Plugge, C. M. Presence and Role of Anaerobic Hydrolytic Microbes in Conversion of Lignocellulosic Biomass for Biogas Production. Crit. Rev. Environ. Sci. Technol. 2015, 45 (23), 25232564,  DOI: 10.1080/10643389.2015.1053727
    63. 63
      Chow, J. M.; Russell, J. B. Effect of PH and Monensin on Glucose Transport by Fibrobacter Succinogenes, a Cellulolytic Ruminal Bacterium. Appl. Environ. Microbiol. 1992, 58 (4), 11151120,  DOI: 10.1128/AEM.58.4.1115-1120.1992
    64. 64
      Russell, J. B.; Dombrowski, D. B. Effect of PH on the Efficiency of Growth by Pure Cultures of Rumen Bacteria in Continuous Culture. Appl. Environ. Microbiol. 1980, 39 (3), 604610,  DOI: 10.1128/AEM.39.3.604-610.1980
    65. 65
      Weimer, P. J. Effects of Dilution Rate and PH on the Ruminal Cellulolytic Bacterium Fibrobacter Succinogenes S85 in Cellulose-Fed Continuous Culture. Arch. Microbiol. 1993, 160, 288294,  DOI: 10.1007/BF00292079
    66. 66
      Kleerebezem, R.; Joosse, B.; Rozendal, R.; Van Loosdrecht, M. C. M. Anaerobic Digestion without Biogas?. Rev. Environ. Sci. Bio/Technol. 2015, 14, 787,  DOI: 10.1007/s11157-015-9374-6
  • Supporting Information

    Supporting Information


    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsestengg.0c00164.

    • Calculations to estimate the rumen content availability in the US, description of chemical and microbial analyses, characterization of inocula and substrates, reactor operating parameters, experimental design, and reactor performance data (PDF)


    Terms & Conditions

    Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.