Unraveling interactive characteristics of microbial community associated with bioelectric energy production in sludge fermentation fluid-fed microbial fuel cells

Bioresource Technology 289 (2019) 121652

Contents lists available at ScienceDirect

Bioresource Technology journal homepage: www.elsevier.com/locate/biortech

Unraveling interactive characteristics of microbial community associated with bioelectric energy production in sludge fermentation fluid-fed microbial fuel cells Xiaodong Xina, Bor-Yann Chena,b, Junming Honga, a b

T

⁎

Department of Environmental Science and Engineering, Huaqiao University, Xiamen 361021, PR China Department of Chemical and Materials Engineering, National I-Lan University, I-Lan 26047, Taiwan

G R A P H I C A L A B S T R A C T

A R T I C LE I N FO

A B S T R A C T

Keywords: Waste activated sludge Fermentation fluid Microbial fuel cells Anodic microbial community Electric energy production

This first-attempt study deciphered the interactive characteristics of anodophilic microbial community-associated bioelectricity production in waste activated sludge (WAS) fermentation fluid-fed microbial fuel cells (MFCs). A novel schematic elucidation for illustrating synergistic interactions in anodic microbial consortia towards electrogenesis was proposed. Moreover, the specific genera of Pseudomonas, Desulfovibrio, Phyllobacterium, Desulfuromonas, Chelatococcus and Aminivibrio were dominant in anodic biofilms, leading to an electrogenesis efficiency of 1.254 kWh/kg COD and peak power density of 0.182 W/m2 (at feeding level of 1.20 g COD/L). It was apparently higher than those MFCs fed with glucose/acetate. The fermentative species contributed positively in reorganizing microbial community structure in anodic biofilms, positively relating to electrogenesis via interactions with exoeletrogens in MFCs. Finally, a more electrogenesis was positively associated to larger anodic microbial diversity, relatively medium anodic community evenness, together with higher abundance of functional genes related to electrogenesis in functional species in MFCs fed with WAS fermentation fluid.

1. Introduction Nowadays, significant increases of waste activated sludge (WAS) production from wastewater treatment plants (WWTPs) has inevitably

⁎

been top-priority concern to environmental protection due to the exponentially-growing population worldwide and rapidly-expanding global industrialization and urbanization. In fact, approximately 6,514,000 dry metric tonnes sewage sludge was produced from WWTPs

Corresponding author. E-mail address: [email protected] (J. Hong).

https://doi.org/10.1016/j.biortech.2019.121652 Received 24 April 2019; Received in revised form 11 June 2019; Accepted 12 June 2019 Available online 13 June 2019 0960-8524/ © 2019 Elsevier Ltd. All rights reserved.

Bioresource Technology 289 (2019) 121652

X. Xin, et al.

degradation (Liu et al., 2018), electrodes material improvement (Luo et al., 2016), or process combination for better voltage output (Wu et al., 2019) from WAS management. Rare studies tended to decipher evolution processes of microbial ecology associated with bioelectricity conversion in MFCs fed with different complex feeds (e.g. sludge fermentation liquid). Thus, this first-attempt study deciphered the interactive relationship between bioelectricity production and anodophilic microbial community characteristics in MFCs fed with WAS fermentation fluid. On the other hand, the effect of different feed streams (e.g., SCSFs vs WAS fermentation fluid) on keystone microbial species (e.g., fermenters and exoelectrogens) in anodic community of MFCs and individual contributions towards electrogenesis were disclosed. According to aforementioned findings, a novel scheme for synergistic interactions taken place in microbial consortia related to electrogenesis in MFCs was proposed afterwards.

in America in 2008 (Yin et al., 2016), while over 6.25 million metric tonnes in China for the year of 2013 with an average annual increase of 13% (Yang et al., 2015). In addition, abundant organic substance fraction was enriched in solid phase with ca. 70–80% of VS/TS of WAS from developed countries (He et al., 2007). To achieve sustainable waste treatment with alleviating environmental burden, pursuing sludge stabilization and reduction towards resource/bioenergy recovery without second waste discharge through an integrated management approach tended to become a popular consensus in current practice (Chen et al., 2014; Yang et al., 2015). Recently, attentions have been considerably paid on a holistic approach for WAS management (Xin et al., 2019a), in which the WAS was initially solubilized by enzymatic pretreatment to accelerate further anaerobic acidogenesis for 10-day fermentation. After the liquid-solid separation, the solid residue could be efficiently recycled to be alternative substitutes for cement use. The remaining liquid portion (i.e. fermentation fluid) plentiful in volatile fatty acids (VFAs) could be utilized directly for bioenergy production [e.g., microbial fuel cells (MFCs)]. Currently, MFCs as a bioelectrochemical device have been widely applied for bioenergy recovery from different types of organic wastes due to simultaneous organic waste reduction and bioelectricity production without extra energy supply or harmful gas emissions (Li et al., 2014; Wang et al., 2014). It was noticeable that MFCs were electrochemically-favorable in terms of electric energy bioconversion efficiency from organic oxidation compared to anaerobic methanogenesis through methane combustion (McCarty et al., 2011; Xin et al., 2018b). Nevertheless, bioelectric energy production in MFCs was remarkably influenced by feeding fuel type (i.e. species of electron donor) (Xin et al., 2019b) and electron transfer efficiency from anode to cathode (Song et al., 2015). As a matter of fact, the latter would be considerably controlled by biodegradation efficiency of feeding substrate for anodophilic microbes (e.g. fermenters and exoelectrogens) (Mei et al., 2017). For example, glucose and acetate have previously been used as typical single carbon source feeds (SCSFs) for bioelectricity production (Song et al., 2015), with the peak power density of 506 mW/m2 at acetate COD level of 800 mg/L (ca. 856.0 mg COD/L) through a 140-h operation by membrane-free single-chamber MFCs (Liu et al., 2005). In addition, more promising performance of 1205 ± 65 mW/m2 power density was achieved by feeding with mixed carbon source feed (e.g. sludge fermentation fluid enriched in VFAs) (Chen et al., 2013). As Wu et al. (2019) proposed, a maximal voltage output of 0.477 V and power density of 8.07 W/m3 for bioelectricity generation could be obtained from WAS fermentation liquid-fed MFCs (Wu et al., 2019). Essentially, the composition of feed (e.g. SCSFs or WAS fermentation fluid) to MFCs also strongly affected species evolution in microbial community [e.g., anodic respiring bacteria (ARB)], directly influencing bioelectricity-converting efficiency of MFCs (Wang et al., 2014). Moreover, anodic microbial ecology (e.g., species diversity and community evenness) closely reflected he characteristics of electrogenesis in MFCs (i.e., bioreactor performance and operation stability) (Song et al., 2015). Jia et al found that the combination of exoelectrogenic Geobacter and fermentative Bacteroides effectively drove highly efficient and reliable MFCs with functions of food waste degradation and electricity generation (Jia et al., 2013). The synergy of functional genes expression of microbes for electrogenesis (e.g., fermenters and exoelectrogens) for MFC processes also directly affect the efficiency of electricity bioconversion and organics biodegradation (Xin et al., 2019b). Park et al also reported that in anodic biofilms of air-cathode MFCs (treating domestic wastewater), growth of non-anode respiring bacteria (ARB), including fermentative bacteria (e.g., Anaerolinaceae family) seemed to play a more important role than that of ARBs (Park et al., 2017). Consequently, revealing carbon source-microbial community nexus in MFCs fed with sludge fermentation fluid would be of great significance to WAS management for maximal bioenergy recovery. However, as literature indicated for MFC studies, most focused on electricity generation (Jia et al., 2013), complex organics

2. Materials and methods 2.1. Feeds of MFCs The fermentation fluid taken from a WAS fermentation bioreactor contained VFA proportion of 60.11% acetate, 27.04% propionate, 3.21% iso-butyrate, 2.95% N-butyrate, 3.75% iso-valerate and 2.95% N-valerate as described previously (Xin et al., 2018a). Both glucose and sodium acetate were used as model SCSFs to elucidate association of bioelectricity production and microbial community by comparison with that using WAS fermentation liquid. These MFCs (denoted as R1, R2 and R3) were fed with glucose, sodium acetate and WAS fermentation liquid, respectively. Prior to feeding to MFCs for study, the three feeds were sterilized via moist heat (121 °C for 30 min). The influent COD of each feed was adjusted to 1.20 g/L as mentioned previously (Xin et al., 2018b, 2019b) with detailed compositions as listed in Table 1. The phosphate buffered saline (PBS), mineral and vitamins solutions used in MFC processes were prepared as indicated in Xin et al. (2018b). 2.2. MFC reactor operations Single-chamber MFC reactors (i.e. R1, R2 and R3) used in this study were made of polymethyl methacrylate with a total effective volume of 28.0 mL (Xin et al., 2019b; Jia et al., 2013). A cylinder-type air-cathode (made of plain carbon cloth) with 1.5-cm in semidiameter (E-Tek, USA) containing a platinum catalyst (0.35 mg/cm2, E-Tek, USA) was installed at one side of each MFC reactor (Jia et al., 2013), while a carbon brushmade anode was fixed at the other side of each MFC with a working surface area of 7.8 cm2. The MFC external circuit was constructed by a titanium wire linked the air-cathode to anode across an external resistor (R) of 500 Ω. The MFCs output voltage was detected by a data acquisition card (USB-miniDAQ, China), connected to a computer for recording at each time interval of one second. The seeding sludge (about 0.1 mL for each reactor) for MFCs start-up was taken from a local fullscale wastewater treatment plant in Xiamen City in China, with the total solid (TS) of 12.55 ± 0.08 g/L and volatile solid (VS) of 9.11 ± 0.02 g/L. All the MFC reactors were operated in sequential batch mode at room temperature (25 °C). The biofilm samples were obtained by flushing the anode of MFCs with sterilized water when the maximal Table 1 Comparative list of feed composition of MFC for this study.

2

Feed

R1

R2

R3

Carbon source PBS solution (mL) Mineral elements (mL) Vitamins (mL) Total COD (mg/L)

Glucose 2.0 0.1 0.1 1242 ± 36

Sodium acetate 2.0 0.1 0.1 1164 ± 41

WAS fermentation fluid 2.0 0.1 0.1 1291 ± 46

Bioresource Technology 289 (2019) 121652

X. Xin, et al.

working area (m2) and the external resistance (Ω), respectively. The power density (P) could be obtained as follows:

voltage output was reached in each cycle of stable operation. Samples were taken from anodic biofilms of MFCs in triplicate from three consecutive operational cycles, and then were centrifuged at 7000 rpm for 10 min. The mix of the biofilm sediments was then used for genomic DNA extraction and analysis. Once voltage outputs of MFCs decreased to < 0.05 V in each cycle, about 1 mL of liquor sample was collected to determine compositions of remaining soluble organic matters.

P= U 2/( R× A)

The polarization and power density curves were implemented by switching the external resistance from 500 Ω to 5000 Ω at an increasing interval of 500 Ω when the MFC voltage output was stabilized at such applied resistance. Here, the efficiency of bioelectric energy conversion (E, in kW h/ kg COD) of MFCs fed with various feeds was obtained in as mentioned previously (Xin et al., 2018b, 2019b):

2.3. General analysis Chemical oxygen demand (COD) of feeds was determined as suggested from Hach Test Kits (Hach, USA) (Xin et al., 2018b). The TS and VS were measured as mentioned in Rice et al. (2012). The pH was detected by a pH meter (Hanna, Italy). The VFAs were detected by gas chromatography (GC) (Agilent 6890) according to a previous study (Xin et al., 2018a). All the tests were conducted in triplicate to guarantee data reproducibility.

E=

(U 2/R)t (1.2×10−3kgCOD/L × 92\% × 0.028L) × 103

(3)

where t represented the stable voltage output time (h), which was set to 2 d in this study (i.e. 48 h), and the average COD removal was determined to be 92% in the MFCs. The theoretical electricity conversion efficiency (TECE) through methane combustion could be calculated as follows (Xin et al., 2018b):

2.4. Microbial community analysis

TECE = ( −ΔU) × M× a × b

The genomic DNA of anodic biofilm samples were extracted by a FastDNA® Spin Kit for Soil (MPbio Company, USA) according to the protocol of instruction. The quality and quantity of the extracts were determined using a Nanodrop 1000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA) and then stored at −20 °C until use with being normalized to a required content of 50 ng/μL. The regions of V3V4 in fragments of 16S rRNA gene were amplified from the obtained genomic DNA using primer sets of 341F (CCCTACACGACGCTCTTCCG ATCTG-barcode- CCTACGGGNGGCWGCAG) and reverse primer of 805R (GACTGGAGTTCCTTGGCACCCGAG AATTCCAGACTACHVGGGTATCTAATCC) through polymerase chain reaction (PCR). The PCR reaction mixture consisted of 2 × Taq master Mix (15 μL), Bar-PCR primer 341F (10 μM) (1 μL), Primer 805R (10 μM) (1 μL), Genomic DNA (10–20 ng) in a final reaction volume of 30 μL with added ddH2O. The PCR reaction conditions in series contained: (i) 94 °C for 3 min; (ii) 5 cycles at 94 °C for 30 s, 45 °C for 20 s and 65 °C for 30 s; (iii) 20 cycles at 94 °C for 20 s, 55 °C for 20 s and 72 °C for 30 s; and (iv) a final extension step at 72 °C for 5 min. The PCR products were purified by the PCR Purification Kit (Sangon, China) for Illumina MiSeq Sequencing analysis. The operational taxonomic unit (OTU) cluster analysis was conducted by Usearch software (5.2.236 version), while species taxonomy was assigned by the RDP classifier (http://rdp.cme.msu.edu/misc/ resources.jsp). The richness rarefaction curve (by mother software), Venn diagram (by VennDiagram package), Bray tree plot (by vegan package) and phylogenetic map (by GraPhlAn software) were constructed according to MiSeq sequencing results with R package. The STAMP software was used to implement the species analysis of relative abundance between two communities from different MFC reactors. The α-diversity estimators of microbial populations were calculated with Mothur (version 1.30.1) (http://www.mothur.org/wiki/Schloss_SOP# Alpha_diversity), comprising Ace index, Chao1 index, Shannon index and the coverage. The prediction of functional genes of the microbial communities based on the 16S rRNA gene sequences was conducted with PICRUSt program (version 1.0.0) (Han et al., 2016), while the relative abundance of functional genes was predicted based on Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Lorenz curve was adopted to evaluate the anodic community evenness figuratively in MFCs (Premier et al., 2011) based on MiSeq sequencing results.

(4)

where −ΔU is the energy of combustion at constant volume for methane, equal to 40 MJ/m3 (Yin et al., 2016). M is the methane volume for combustion (m3). Here, 1 kg of COD is assumed to generate 0.35 m3 of methane (Samson and LeDuyt, 1986). Parameter a was the conversion coefficient of chemical energy in methane to electricity through combustion, equal to 35% (McCarty et al., 2011). Parameter b is assigned to be 0.28, indicating the conversion coefficient of energy (MJ) to electric energy (kW h) (Xin et al., 2018b). 3. Results and discussion 3.1. Bioelectricity-producing evaluation The performance of bioelectric energy production and organics removal through MFCs with various feeds were depicted in Fig. 1. After ca. 14–16 days operation for serial acclimation, stable voltage outputs of MFCs fed with the feeds of glucose, sodium acetate and WAS fermentation fluid were gradually achieved to 0.45 ± 0.03 V, 0.47 ± 0.02 V and 0.62 ± 0.03 V, respectively (Fig. 1A). The corresponding power densities were 0.123 ± 0.009 W/m2, 2 0.132 ± 0.008 W/m and 0.182 ± 0.009 W/m2 (Fig. 1B), respectively. Compared to similar MFCs fed with other organic waste matters (Table 2), apparently WAS fermentation fluid seemed to be electrochemically favorable for bioelectric energy production as appropriate organic feed for MFCs. It was noticeable that R3 (i.e. fed with WAS fermentation fluid) displayed a much better capability of power density compared to MFC reactors R1 and R2 fed with SCSFs (glucose or acetate). Furthermore, all of the COD removal efficiencies in three MFCs were > 92% for steady-state operation (Fig. 1C), indicating that MFCs could exhibit relatively high operation performance in terms of organic nutrients removal. This also supported by the results of compositions as indicated in Table 2. 3.2. Microbial community profiles associated with electrogenesis by different feeds 3.2.1. Microbial community similarity and diversity Species similarity analysis of microbial communities in MFCs fed with various feeds was shown in Fig. 2. The different cutoffs of rarefaction curves (Fig. 2A) depicted the unprecedented levels of observed OTUs, implying that most of the OTUs in biofilm samples had been analyzed with a good level of confidence. In particular, R3 presented a comparatively higher level than the SCSFs-fed MFCs (R1 and R2). This was also in consistent with the statistical results of community diversity and richness (Table 3). The Venn diagram (Fig. 2B) illustrated

2.5. Data analysis Regarding bioelectricity-generating performance in MFCs, the current density (I) was calculated based on the following formula:

I= U/( R× A)

(2)

(1)

where U, A and R represented the output voltage (V), the effective 3

Bioresource Technology 289 (2019) 121652

X. Xin, et al.

Fig. 1. The performance of MFCs fed with different feeds. (A): Voltage output; (B): Polarization and power density curves at the maximum voltage output; (C): COD removal efficiency (arrows denoted times of nutrient feeding).

abundance of 17.64% in R1, 18.40% in R2 and 14.17% in R3. Similarly, the Clostridium (10.77% in R1, 4.96% in R2 and 3.42% in R3), Geobacter (9.34% in R1, 1.56% in R2 and 1.04% in R3), Proteiniphilum (3.47% in R1, 1.83% in R2 and 5.27% in R3) and Rhodococcus (2.25% in R1, 3.77% in R2 and 4.16% in R3) seemed to be species in-common for all MFCs. Moreover, the genera of Petrimonas (7.40% in R1 and 4.60% in R2), Rhodanobacter (7.49% in R1, 2.27% in R2), Alicycliphilus (3.83% in R1 and 5.20% in R2), Aquamicrobium (2.86% in R1 and 4.04% in R2), Burkholderia (2.19% in R1 and 3.99% in R2) and Castellaniella (3.31% in R1 and 0.96% in R2) tended to dominate in SCSFs-fed MFCs. In contrast, genera of Pseudomonas (15.26%), Desulfovibrio (3.54%), Phyllobacterium (2.92%), Desulfuromonas (4.14%), Chelatococcus (3.17%) and Aminivibrio (3.14%) apparently dominated in R3. It might suggest that WAS fermentation liquid stimulate populations of these genera over-growing under such organic nutrients provided from sludge fermentation liquid, effectively augmenting bioconversion into electric energy for electrogenesis. Moreover, Fig. 3B and C summarized the difference of core ARBs in MFCs with various nutrient sources. It was found that sludge fermentation fluid-fed MFC comprised major functional genera of Aminivibrio [dealing with degradation of amino acids and organic acids (Honda et al., 2013)], Desulfuromonas [implementing oxidation of acetate for cell growth (Zhang et al., 2019)], Desulfovibrio [performing enzymatic ferric reduction for in situ redox reactions (Ahmed et al., 2019)], Aminobacter [acting to degrade NO2− via denitrification (Kostrytsia et al., 2018)], Pseudomonas [expressing electrochemical activities towards electrogenesis (Croese et al., 2014)], Chelatococcus [employing denitrification for N removal (Li et al., 2016)] and Phyllobacterium [performing capabilities to fix N and remove P (Ji et al., 2011)] (p < 0.05). On the contrary, the genera of Moheibacter [handling glucose degradation in anaerobic condition (Zhang et al., 2014)], Petrimonas [fermenting sugars to generate acetate (Chen et al., 2017)], Rhodanobacter [conducting carbohydrates degradation (Patil et al., 2009)], Burkholderia [implementing electricity generation (Patil et al., 2009)], Alicycliophilus [presenting as electrochemically active denitrifier (Xie et al., 2014)] and Castellaniella dominated in the SCSFs-fed MFCs (i.e. R1 and R2) (p < 0.05). It was remarkable that both typical

similarities in terms of OTUs among all biofilm samples. The common OTUs number in Venn diagram between R3 and the inoculum reached 219, while 173 between R3 and R1, 189 between R3 and R2, but it arrived to 423 between R1 and R2. The above-mentioned results implied that the WAS fermentation fluid played a vital role on distribution of OTUs in anodic communities of MFCs, which effectively improved community dissimilarity compared to SCSFs. This phenomenon was also confirmed by the result of Bray tree plot (Fig. 2C), suggesting relatively larger difference emerged between R3 and SCSFs-fed MFCs (R1 and R3). The coverage range indicated that 95.3–96.4% of the species in terms of OTUs had been detected here in all biofilm samples (Table 3). Both species biodiversity estimators of Shannon index and detected OTU number and richness indicators of ACE index and Chao1 index all supported that R3 owned a higher level compared to SCSFs-fed MFCs (R1 and R2). This revealed that high species diversity was responsible for promising bioelectricity-generating characteristics to be expressed in R3. Microbial diversity was inevitably a pivotal parameter in community ecology, which played a key role in affecting community function and correlated positively with the performance stability of a given ecosystem (Reinthaler et al., 2005; Miura et al., 2007). In fact, species diversity was influenced not only by the population of species, but also by the uniformity of community distribution. In addition, relative individual abundance and species richness were the key elements of biodiversity. It could be obtained that mixed carbon source feed (e.g. WAS fermentation liquid) contained abundant and diverse nutrient sources to effectively produce more power generation through MFCs, suggesting that higher bioelectricity-generating anodic community was evolved in higher species diversity compared to MFCs fed with the SCSFs. This result also supported the finding of a prior study (Xin et al., 2019b). 3.2.2. Microbial community evolution Compared to species distribution in the microbial community and dominant species in different ARBs, MFCs fed with various nutrient sources were implemented as shown in Fig. 3. In Fig. 3A, Azospirillum emerged simultaneously in these three MFCs with the relative

Table 2 Comparison of bioelectricity generation in MFCs fed with various organic waste feeds. Feeds

Influent COD (g/L)

MFC type

Power density (mW/ m2)

Peak voltage (mV)

COD removal (%)

Reference

Vegetable waste Organic fraction of municipal solid waste Kitchen garbage Food waste WAS fermentation fluid

3.20 1.18 NRa 1.20 1.20

Single-chamber Single-chamber Single-chamber Single-chamber Single-chamber

57.4 123 60 173 182

< 300 260 620 570 620

62.9 > 86 68.5 91 > 90

Venkata Mohan et al. (2010) El-Chakhtoura et al. (2014) Moqsud et al. (2014) Xin et al. (2018b) This study

Average value was reported above. NRa denoted data not reported. 4

Bioresource Technology 289 (2019) 121652

X. Xin, et al.

Fig. 2. The similarity analysis of microbial communities among all samples. (A) Richness rarefaction plot of all communities. (B) Comparison of OTUs number by mean of Venn diagram; (C) Bray tree plot.

community compositions (at phylum and genus level, respectively) in MFCs fed with various mixed carbon sources were compared deeply. Moreover, it is noticeable that the type of organic wastes played a vital role on functional genera-power generation nexus in MFCs. Regarding species distribution in anodic community, Lorenz curve was also adopted to evaluate the evolution of species evenness in microbial community of MFCs responding to different feed supply. The value of the vertical axis in accordance with 20% abscissa axis was used to interpret the Lorenz curve based on Pareto's law (Wittebolle et al., 2008). Evidently, it has been recognized that community evenness would play a vital role in shaping the community structure and functionality stability (Wittebolle et al., 2009). Tao et al (2013) also pointed out that initial evenness of species distribution had a positive impact in stimulating effective start-up of anammox reactor (Tao et al., 2013). As seen in Fig. 4B, Lorenz curve for R3 seemed to be far off the theoretical perfect curve of 45° diagonal (i.e. 100% evenness) compared to R1 and R2 curves. It indicated that R3 presented a high dominance (i.e. relatively low evenness) compared to the poorest evenness emerged in the seed sludge. This result implied that the anodic community evenness in WAS fermentation fluid-fed MFC (R3) simply fell in between the SCSFsfed MFCs (i.e. R2) and the seed sludge in terms of microbial ecology. In other words, R3 presented a promising organics-degrading and bioelectricity-generating community in which dominant portions were occupied by a relatively small number of microbial species. Moreover, the remaining species solely accounted for a slight proportion in the community by comparison with the evenness in R1 and R2, but less than that in seed sludge (i.e. relatively medium microbial evenness). A community with such distributive characteristics exhibited relatively highly functioning consortia (Marzorati et al., 2008) and owned far more influence on enhancing community function as supported by Carballa et al. (2015). Consequently, such microbial evenness in MFCs might be acclimated more successfully by complex feed (e.g. WAS fermentation liquid) against SCSFs to facilitate effective power for electrogenesis. This was also in consistent with the result in Fig. 1.

Table 3 Microbial community estimators determined from different nutrient-fed MFCs. Sample

Sequence number

OTU number

Shannon index

ACE index

Chao1 index

Coverage

Inoculum R1 R2 R3

35,079 50,932 51,341 47,144

2195 2270 2372 2318

4.055 3.960 3.916 4.170

26,039 43,616 38,873 54,899

13,536 15,899 17,232 23,493

0.953 0.964 0.963 0.959

exoelectrogens- Geobacter and Clostridium emerged in all MFCs, implying that their wide-ranged adaptabilities to different carbon sources effectively augment bioelectricity-generating capabilities (Logan, 2009; Song et al., 2015). These all clearly suggested that the supplement nutrient sources were capable to redistribute the anodic microbial community structure. The complex nutrients in WAS fermentation liquid effectively improved a more diversified microbial inhabit in MFCs compared to R1 and R2 (Table 3). Furthermore, the robustness of functional genera with high flexibility and versatility in WAS fermentation liquid-fed MFC was clearly enhanced. 3.2.3. Phylogenetic classification and community evenness As Fig. 4A described, phylogenetic classifications of main ARBs in anodic communities of all MFCs indicated that 21 genera were in five phyla of Actinobacteria, Bacteroidetes, Deinococcus-Thermus, Firmicutes and Proteobacteria. The genera of Castellaniella, Burkholderia, Alicycliphilus, Chelatococcus, Aquamicrobium, Phyllobacterium, Azospirillum, Rhodanobacter, Pseudomonas, Geobacter, Desulfuromonas, and Desulfovibrio belonging to the Proteobacteria phylum. This was in agreement with a previous study with proposing that abundant anode-respiring microbes were present in the Proteobacteria phylum and owned capabilities to degrade organics for bioelectricity generation through the extracellular electron transport using various electron donors (different feeds) (Park et al., 2017). The genera of Clostridium and Anoxybacter were subordinated to Firmicutes phylum, while Rhodococcus and Mycobacterium [enriched in R3 and related to biodegradation of a variety of nitrogen compounds (e.g., NH4+, NO2−, NO3−) (Chen et al., 2008)] belonged to the Acinobacteria phylum. The Bacteroidetes phylum was suspected to be closely associated with carbohydrate degradation (Ito et al., 2012), including genera of Petrimonas, Proteiniphilum, Moheibacter. Similar functional anode-respiring microorganisms were also found in microbial community of anodic biofilms in other studies by using air-cathode MFCs-fed with hydrolysate of rice straw (Wang et al., 2014) or food waste (Xin et al., 2019b). These all suggested that such Actinobacteria, Bacteroidetes, Firmicutes and Proteobacteria (at phylum level) played primary roles for organics degradation and electrogenesis through MFCs fed with mixed carbon sources. This finding was in consistent with previous studies (Table 4), in which the anodic

3.2.4. Interactive analysis of community towards electrogenesis The relative abundances of functional genes in MFCs fed with different substrates was analyzed by the KEGG database to elucidate the differences monitored in bioelectricity production by the 16S rRNAbased software of PICRUSt (Han et al., 2016). As shown in Table 5, it was noted that nearly half of the relative abundances of functional genes in R3 emerged to be higher than those in R1 and R2 (SCSFsMFCs). These metabolic functions contained Amino Acid Metabolism (10.908%), Carbohydrate Metabolism (9.944%), Cell Growth and Death (0.599%), Cellular Processes and Signaling (3.653%), Energy Metabolism (5.739%), Genetic Information Processing (2.369%), Lipid Metabolism (3.960%), Membrane Transport (13.761%), Metabolism of Cofactors and Vitamins (4.196%), Metabolism of Other Amino Acids 5

Bioresource Technology 289 (2019) 121652

X. Xin, et al.

6

(caption on next page)

Bioresource Technology 289 (2019) 121652

X. Xin, et al.

Fig. 3. Microbial community evolutions and core genera in MFCs fed with different substrates (p < 0.05). (A) Dominant genera evolutions. (B) Core genera comparison between R1 and R3 (p < 0.05). (C) Core genera comparison between R2 and R3 (p < 0.05).

fermentation liquid. The MFCs (R1 and R3) displayed a similar VFAs profile during a fed-batch cycle of operation, while acetate presented a dominant intermediate followed by propionate and then butyrate (data not shown). Acetate reached a maximum of 294 ± 17 mg/L (in R1) and 382 ± 24 mg/L (in R3) at 24 h after feeding and then decreased to low levels (< 10 mg/L) at the end of a batch cycle. Similarly, the propionate (another key intermediate product) elevated to ca. 98 mg/L (in R1) and 112 mg/L (in R3) at 24 h and decreased to < 15 mg/L at the end of the cycle. The butyrate also maximized at 24 h followed with lower levels of 15–34 mg/L comparatively. It was possible completely that 1 mol butyrate can be converted into 2 mol acetate by butyratedegrading acetogenic bacteria (Liu et al., 2005). Moreover, H2 partial pressure above 10-2 kPa would inhibit the oxidation of short-chain carboxylic acids thermodynamically (De Vrieze et al., 2018). The H2 partial pressures in R1 and R3 were much lower than the standard value of 10−2 kPa, which hinted that the VFAs oxidation (conversion to acetate) is favorable thermodynamically and contributed to electrogenesis positively in this study. Based on above-mentioned results, a schematic illustration on bioelectric energy production in terms of key microbial genera and combined interactions in anodic biofilm of MFCs affected by different feed (e.g., glucose vs. WAS fermentation fluid) was proposed (Fig. 5). Indeed, the cooperation between fermentative bacteria (in fermentation zone of anodic biofilm) and electrogenic anodophilic bacteria (in electrogenesis zone) was crucial for achieving stable electrogenesis through MFCs. As seen in R1, in fermentation zone of anodic biofilm matrix, glucose was converted to organic fatty acids (e.g., acetate, propionate, butyrate) initially via the effective bacteria of Petrimonas [related to convert sugars to acetic acids (Chen et al., 2017)], Rhodanobacter [responsible for carbohydrates degradation (Patil et al., 2009)], Castellaniella and Moheibacter [associated with glucose bioconversion into organic acids via fermentation (Zhang et al., 2014)]. Subsequently, fatty acids and their byproducts (e.g., formate, H2) obtained from fermentation could be further utilized by electro-active members (i.e., electrogenic species) in electrogenesis zone, such as Geobacter [with electrochemical activities (Logan, 2009)], Burkholderia [related to electricity generation (Patil et al., 2009)], Clostridium [responsible for electricity production (Song et al., 2015)], Alicycliphilus [an electrochemically active denitrifier (Xie et al., 2014)]. However, microbial community structure has been significantly evolved in R3. Sludge fermentation liquid enriched in considerable organic acids could be directly consumed by organic acids utilizers, including Desulfovibrio [related to enzymatic ferric reduction for redox reactions (Ahmed et al., 2019)], Aminivibrio [organic acids degradation (Honda et al., 2013)], Desulfuromonas [responsible for acetate oxidation (Zhang et al., 2019)], and N, P removers (e.g. Chelatococcus) [dealing with denitrification for N removal (Li et al., 2016)], Phyllobacterium [related to N fixing and P removal (Ji et al., 2011)], Rhodococcus [associated with N removal (Chen et al., 2008)]. Then metabolic intermediates (e.g., acetate, H2) could be further utilized by exoelectrogens for bioelectricity generation (e.g., Geobacter, Pseudomonas [with electrochemical activities for electrogenesis (Croese et al., 2014)] and Clostridium). The complexity of WAS fermentation liquid and the variety of intermediates and metabolites that could sustain different functional groups of bacteria, including electricity generating and fermentative bacteria (El-Chakhtoura et al., 2014). These functional genera played positive roles in dual functions of organic matters degradation and exoelectron transfer from the chemical transformations at the anode (i.e., (CH2O)n + nH2O → nCO2 + 4ne− + 4n H+). Meanwhile, the protons moved through MFC system to cathode with the reduction reaction of 4e− + O2 + 4H+ → 2H2O emergence after electrons passing through the external circuit from anode to cathode (Xin et al., 2019b).

Fig. 4. Phylogenetic classification and community evenness changes in MFCs fed with various feeds. (A). The phylogenetic analysis of main ARB in all samples. (A-Clostridium. B-Anoxybacter. C-Petrimonas. D-Proteiniphilum. EMoheibacter. F-Rhodococcus. G-Mycobacterium. H-Deinococcus-Thermus. ITruepera. J-Castellaniella. K-Burkholderia. L-Alicycliphilus. M-Chelatococcus. NAquamicrobium. O-Phyllobacterium. P-Azospirillum. Q-Rhodanobacter. RPseudomonas. S-Geobacter. T-Desulfuromonas. U-Desulfovibrio). (B) Anodic community evenness changes assessed by Lorenz curves.

(2.279%), Nucleotide Metabolism (3.282%), Signal Transduction (2.410%), Transcription (2.310%) and Transport and Catabolism (0.347%). The relatively high abundance of these functional genes related to KEGG pathways in R3 likely exerted positive contributions to ehance bioelectricity conversion by exoelectrogens. More specifically, R3 (fed with sludge fermentation liquid) enriched the dominant genera of Chelatococcus (3.17%), Pseudomonas (15.26%), Desulfovibrio (3.54%), Phyllobacterium (2.92%), Desulfuromonas (4.14%) and Aminivibrio (3.14%). In fact, Chelatococcus was related to N removal by denitrification (Li et al., 2016). Pseudomonas as one kind of electro-active microorganisms was responsible for electrogenesis (Croese et al., 2014). Moreover, Phyllobacterium was contributed to N and P removal (Ji et al., 2011), while Desulfovibrio, Aminivibrio and Desulfuromonas were able to degrade organic acids (Honda et al., 2013; Zhang et al., 2019). Thus, the changes of relative abundance of functional genes in R3 could be explained as a reflection upon the comprehensive metabolism of these functional species towards electrogenesis by consuming sludge 7

Bioresource Technology 289 (2019) 121652

This study Actinobacteria, Bacteroidetes, DeinococcusThermus, Firmicutes and Proteobacteria

Main functional gene relative frequency (%) R1

R2

R3

KEGG_Pathways

10.267 0.893

10.848 0.943

10.908 0.908

9.809 0.556 4.236 3.630 5.604 0.141 1.817 2.195

9.323 0.571 3.106 3.495 5.448 0.123 1.714 2.072

9.944 0.599 3.755 3.653 5.739 0.139 1.707 2.064

2.260 1.945 0.057 3.557 12.990

2.221 1.813 0.048 3.952 13.274

2.369 1.704 0.052 3.960 13.761

4.004 1.902 2.053

3.999 2.066 2.311

4.196 2.279 2.125

3.019 6.589

3.042 6.390

3.282 6.078

2.329

2.110

2.410

0.157

0.166

0.137

2.211 0.297 3.626

2.214 0.337 4.430

2.310 0.347 4.172

Metabolism; Amino Acid Metabolism Metabolism; Biosynthesis of Other Secondary Metabolites Metabolism; Carbohydrate Metabolism Cellular Processes; Cell Growth and Death Cellular Processes; Cell Motility Unclassified; Cellular Processes and Signaling Metabolism; Energy Metabolism Organismal Systems; Environmental Adaptation Metabolism; Enzyme Families Genetic Information Processing; Folding, Sorting and Degradation Unclassified; Genetic Information Processing Metabolism; Glycan Biosynthesis and Metabolism Organismal Systems; Immune System Metabolism; Lipid Metabolism Environmental Information Processing; Membrane Transport Metabolism; Metabolism of Cofactors and Vitamins Metabolism; Metabolism of Other Amino Acids Metabolism; Metabolism of Terpenoids and Polyketides Metabolism; Nucleotide Metabolism Genetic Information Processing; Replication and Repair Environmental Information Processing; Signal Transduction Environmental Information Processing; Signaling Molecules and Interaction Genetic Information Processing; Transcription Cellular Processes; Transport and Catabolism Metabolism; Xenobiotics Biodegradation and Metabolism

Certainly, it should be recognized that the repeatability of synergistic relationships among species obtained in the WAS fermentation liquid-fed MFCs relied considerably on the premise of accordant biochemical reaction conditions (e.g. WAS characteristics, organics concentration, inoculum source, operational parameters, MFC configuration, electrode material, solution conductivity and internal resistance) (El-Chakhtoura et al., 2014). It was reasonably concluded that the fermentative bacteria not only played a vital role to evolve microbial community structure adapted toward nutrients oxidation in complex substrates, but also contributed positively to maintain stable functions of anodic biofilms for electrogenesis via interactive associations with exoeletrogens in MFCs. On the other hand, WAS fermentation fluid could cultivate to evolve a microbial community with higher diversity and a relatively medium species distribution, which would aid the stability for high-performance electrogenesis simultaneously taken place in anodic biofilm. Although this study was partly in agreement with previous works, several novel findings could be concluded based on the aforementioned results: (i) A schematic diagram illustrating the comparison of potential key members in microbial community affected by glucose versus WAS fermentation fluid was proposed with elucidation of combined interactions towards electrogenesis in MFCs. (ii) No matter what nutrient sources were used (e.g., SCSFs or complex feed), fermentative species all played a crucial role in shaping microbial community structure in anodic biofilm, directly affecting the efficiency for electrogenesis through combined interactions with exoelectrogens. (iii) Complex feed (i.e. WAS fermentation fluid) effectively cultivated electro-active microbial community with higher biodiversity in anodic biofilms (Table 3). It suggested that complex feed may prompt the potential interactions among various functional species (Table 5 and

182 Single-chamber aircathode MFCs Waste activated sludge fermentation liquid

173 1.2 Single-chamber aircathode MFCs

Rice straw hydrolysate

Food waste hydrolysate

137.6 0.4

462 2

Table 5 Analysis of metabolic functions based on KEGG database in MFCs fed with various feeds (red color for the higher relative abundance in WAS fermentation fluid-fed MFC).

1.2

Xin et al. (2019a,b)

El-Chakhtoura et al. (2014) Jia et al. (2013)

Eubacteriaceae (61%), Geobacter (1%), Bacteroides (ca.20%), Parabacteroides (ca. 10%), etc. Geobacter (37.72%), Bacteroides (34.66%), Aeromonas (0.73%), Klebsiella (0.28%) and Enterobacter (0.18%). Shewanella putrefacies IR-1, Geobacter sulfurreducens, Ochrobacrum anthropi YZ-1, Clostridium butyricum EG3, Desulfitobacterium hafniense strain DCB2, Thermincola sp. strain JR and Thermincola ferriacetica Clostridium (32.41%), Petrimonas (1.37%), Rummeliibacillus (18.06%), Enterococcus (5.92%), Propionispira (2.20%), Burkholderia (13.61%) and Lactobacillus (1.90%). Azospirillum (14.17%), Clostridium (3.42%), Geobacter (1.04%), Proteiniphilum (5.27%), Rhodococcus (4.16%), Pseudomonas (15.26%), Desulfovibrio (3.54%), Phyllobacterium (2.92%), Desulfuromonas (4.14%), Chelatococcus (3.17%) and Aminivibrio (3.14%) 123

Single-chamber air cathode MFCs Single-chamber air cathode MFCs Single-chamber aircathode MFCs Organic fraction of municipal solid waste Food waste

1.18

Firmicutes (67%), Bacteroidetes (18%), Proteobacteria (6%), etc. Proteobacteria (40.9%), Bacteroidetes (39.8%) and Firmicutes (14.4%). Proteobacteria (44.2%), Bacteroidetes (7.7%), Firmicutes (20.1%), Chloroflexi (8.4%). Actinobacteria, Bacteroidetes, DeinococcusThermus, Firmicutes and Proteobacteria

Wang et al. (2014)

Reference Power density (mW/m2) COD feeding level (g/L) MFC type Feed

Table 4 Comparison of anodic community composition in various nutrient-fed MFCs.

Main phyla

Main family/genera

X. Xin, et al.

8

Bioresource Technology 289 (2019) 121652

X. Xin, et al.

Fig. 5. Comparison of schematic illustration of potential keystone members in microbial community and combined interactions in MFCs: glucose versus WAS fermentation fluid, supported by: [1] (Honda et al., 2013), [2] (Zhang et al., 2019), [3](Ahmed et al., 2019), [4] (Croese et al., 2014), [5] (Logan. 2009), [6] (Song et al.,2015), [7] (Zhang et al., 2014), [8] (Chen et al., 2017), [9] (Patil et al., 2009), [10] (Xie et al., 2014), [11] (Li et al., 2016).

generated from 1 kg of soluble COD of WAS fermentation liquid, which was twice higher than those from MFCs fed with glucose and acetate feeds. That is, it accounted for nearly 91.4% of the TECE standard value (1.372 kW h/kg COD) via methane combustion. As prior study (Xin et al., 2019a) indicated, 14.86 g TS of WAS could produce 3.58 g COD (enriched in VFAs) after pretreatment and 10-d fermentation. Considering 6.25 million metric tonnes of WAS production in year of 2013 in China (Yang et al., 2015), about 1.506 million metric tonnes of soluble COD could be generated based on such fermentation efficiency. According to the electricity conversion efficiency achieved in the study of 1.254 kWh/kg COD in R3, about 1.889 billion kW h electricity can be theoretically produced from the annual WAS production in China. That is approx. equal to ¥1.133 billion yuan at the unit electricity price of ¥ 0.6 yuan in China.

Fig. 5) toward effective enhancement of bioelectricity generation. (iv) A relatively medium distributive evenness could be constructed in WAS fermentation fluid-fed MFC compared with SCSFs-fed MFCs. This possibly stimulated to enhance the electrogenesis output through the reconstructed microbial community with relatively high electro-active capabilities.

3.3. Economic feasibility evaluation As shown in Fig. 6, approx. 1.254 kWh of electric energy could be

4. Conclusion The power density of 0.182 W/m2 and electricity conversion efficiency of 1.254 kWh/kg COD could be achieved from WAS fermentation liquid-fed MFCs with 92% of organics removal after two-day operation at the influent COD of 1.20 g/L. Compared with SCSFs-fed MFCs, WAS fermentation liquid facilitated a higher microbial biodiversity with enrichment of Pseudomonas, Desulfovibrio, Phyllobacterium, Desulfuromonas, Chelatococcus and Aminivibrio for electrogenesis in anodic biofilms. Apparently, the reconstruction of relatively medium evenness, higher abundance of corresponding functional genes coupled with enhancement of metabolic interactions all played significant roles on electric energy production in MFCs.

Acknowledgements This study was financially supported by the Scientific Research Funds of Huaqiao University (605-50Y18055). Part of financial support (MOST 106-2221-E-197-020-MY3) from Taiwan's Ministry of Science and Technology to Bor-Yann Chen for study was very much appreciated.

Fig. 6. Comparison of electric energy conversion efficiency of MFCs fed with different substrates (TECE denoted theoretical efficiency of bioelectricity production via methane combustion). 9

Bioresource Technology 289 (2019) 121652

X. Xin, et al.

References

Adaptation of microbial community of the anode biofilm in microbial fuel cells to temperature. Bioelectrochemistry 117, 29–33. Miura, Y., Hiraiwa, N.H., Ito, T., Itonaga, T., Watanabe, Y., Okabe, S., 2007. Bacterial community structures in MBRs treating municipal wastewater: relationship between community stability and reactor performance. Water Res. 41, 627–637. Moqsud, M.A., Omine, K., Yasufuku, N., Bushra, Q.S., Hyodo, M., Nakata, Y., 2014. Bioelectricity from kitchen and bamboo waste in a microbial fuel cell. Waste Manage. Res. 32, 124–130. Park, Y., Cho, H., Yu, J., Min, B., Kim, H.S., Kim, B.G., Lee, T., 2017. Response of microbial community structure to pre-acclimation strategies in microbial fuel cells for domestic wastewater treatment. Bioresour. Technol. 233, 176–183. Patil, S.A., Surakasi, V.P., Koul, S., Ijmulwar, S., Vivek, A., Shouche, Y.S., Kapadnis, B.P., 2009. Electricity generation using chocolate industry wastewater and its treatment in activated sludge based microbial fuel cell and analysis of developed microbial community in the anode chamber. Bioresour. Technol. 100, 5132–5139. Premier, G.C., Kim, J.R., Michie, I., Dinsdale, R.M., Guwy, A.J., 2011. Automatic control of load increases power and efficiency in a microbial fuel cell. J. Power Sources 196, 2013–2019. Reinthaler, T., Winter, C., Herndl, G.J., 2005. Relationship between Bacterioplankton Richness, Respiration, and Production in the Southern North Sea. Appl. Environ. Microbiol. 71 (5), 2260–2266. Rice, E.W., Baird, R.B., Eaton, A.D., Clesceri, L.S., 2012. Standard Methods for the Examination of Water and Wastewater. American Public Health Association American Water Works Association, Water Environment Federation, Washington, DC. Samson, R., LeDuyt, A., 1986. Detailed study of anaerobic digestion of spirulina maxima algal biomass. Biotechnol. Bioeng. 28 (7), 1014–1023. Song, Y., Xiao, L., Jayamani, I., He, Z., Cupples, A.M., 2015. A novel method to characterize bacterial communities affected by carbon source and electricity generation in microbial fuel cells using stable isotope probing and Illumina sequencing. J. Microbiol. Meth. 108, 4–11. Tao, Y., Gao, D.W., Wang, H.Y., de Kreuk, M., Ren, N.Q., 2013. Ecological characteristics of seeding sludge triggering a prompt start-up of anammox. Bioresour. Technol. 133, 475–481. Venkata Mohan, S., Mohanakrishna, G., Sarma, P.N., 2010. Composite vegetable waste as renewable resource for bioelectricity generation through non-catalyzed open-air cathode microbial fuel cell. Bioresour. Technol. 101, 970–976. Wang, Z.J., Lee, T., Lim, B.S., Choi, C.S., Park, J.H., 2014. Microbial community structures differentiated in a single-chamber air-cathode microbial fuel cell fueled with rice straw hydrolysate. Biotechnol. Biofuels 7 (9), 1–10. Wittebolle, L., Marzorati, M., Clement, L., Balloi, A., Daffonchio, D., 2009. Initial community evenness favours functionality under selective stress. Nature 458 (7238), 623–626. Wittebolle, L., Vervaeren, H., Verstraete, W., Boon, N., 2008. Quantifying community dynamics of nitrifiers in functionally stable reactors. Appl. Environ. Microbiol. 74 (1), 286–293. Wu, D., Sun, F.Q., Chua, F.J.D., Lu, D., Stuckey, D.C., Zhou, Y., 2019. In-situ power generation and nutrients recovery from waste activated sludge-Long-term performance and system optimization. Chem. Eng. J. 361, 1207–1214. Xie, D.H., Yu, H., Li, C.C., Ren, Y., Wei, C.H., Feng, C.H., 2014. Competitive microbial reduction of perchlorate and nitrate with a cathode directly serving as the electron donor. Electrochim. Acta 133, 217–223. Xin, X.D., He, J.G., Li, L., Qiu, W., 2018a. Enzymes catalyzing pre-hydrolysis facilitated the anaerobic fermentation of waste activated sludge with acidogenic and microbiological perspectives. Bioresour. Technol. 250, 69–78. Xin, X.D., Hong, J.M., He, J.G., Qiu, W., 2019a. An integrated approach for waste activated sludge management towards electric energy production/resource reuse. Bioresour. Technol. 274, 225–231. Xin, X.D., Hong, J.M., Liu, Y., 2019b. Insights into microbial community profiles associated with electric energy production in microbial fuel cells fed with food waste hydrolysate. Sci. Total Environ. 670, 50–58. Xin, X.D., Ma, Y.Q., Liu, Y., 2018b. Electric energy production from food waste: microbial fuel cells versus anaerobic digestion. Bioresour. Technol. 255, 281–287. Yang, G., Zhang, G.M., Wang, H.C., 2015. Current state of sludge production, management, treatment and disposal in China. Water Res. 78, 60–73. Yin, Y., Liu, Y.J., Meng, S.J., Kirran, E.U., Liu, Y., 2016. Enzymatic pretreatment of activated sludge, food waste and their mixture for enhanced bioenergy recovery and waste volume reduction via anaerobic digestion. Appl. Energy 179, 1131–1137. Zhang, L.F., Fu, G.K., Zhang, Z., 2019. Electricity generation and microbial community in long-running microbial fuel cell for high-salinity mustard tuber wastewater treatment. Bioelectrochemistry 126, 20–28. Zhang, R.G., Tan, X., Zhao, X.M., Deng, J., Lv, J., 2014. Moheibacter sediminis gen. nov., sp. nov., a member of the family Flavobacteriaceae isolated from sediment, and emended descriptions of Empedobacter brevis, Wautersiella falsenii and Weeksella virosa. Int. J. Syst. Evol. Microbiol. 64, 1481–1487.

Ahmed, M., Lin, O., Saup, C.M., Wilkins, M.J., Lin, L.S., 2019. Effects of Fe/S ratio on the kinetics and microbial ecology of an Fe(III)-dosed anaerobic wastewater treatment system. J. Hazard. Mater. 369, 593–600. Carballa, M., Regueiro, L., Lema, J.M., 2015. Microbial management of anaerobic digestion: exploiting the microbiome-functionality nexus. Curr. Opin. Biotechnol. 33, 103–111. Chen, G.W., Choi, S.J., Lee, T.H., Lee, G.Y., Cha, J.H., Kim, C.W., 2008. Application of biocathode in microbial fuel cells: cell performance and microbial community. Appl. Microbiol. Biotechnol. 79 (3), 379–388. Chen, H.H., Zhang, C., Rao, Y., Jing, Y.H., Luo, G., Zhang, S.C., 2017. Methane potentials of wastewater generated from hydrothermal liquefaction of rice straw: focusing on the wastewater characteristics and microbial community compositions. Biotechnol. Biofuels 10 (1), 140. Chen, Y., Yu, F., Liang, S., Wang, Z., Liu, Z., Xiong, Y., 2014. Utilization of solar energy in sewage sludge composting: fertilizer effect and application. Waste Manage 34, 2014–2021. Chen, Y.G., Luo, J.Y., Yan, Y.Y., Feng, L.Y., 2013. Enhanced production of short-chain fatty acid by co-fermentation of waste activated sludge and kitchen waste under alkaline conditions and its application to microbial fuel cells. Appl. Energy 102, 1197–1204. Croese, E., Jeremiasse, A.W., Marshall, I.P.F., Spormann, A.M., Euverink, G.-J.W., Geelhoed, J.S., Stams, A.J.M., Plugge, C.M., 2014. Influence of setup and carbon source on the bacterial community of biocathodes in microbial electrolysis cells. Enzyme Microb. Tech. 61–62, 67–75. De Vrieze, J., Arends, J.B.A., Verbeeck, K., Gildemyn, S., Rabaey, K., 2018. Interfacing anaerobic digestion with (bio)electrochemical systems: potentials and challenges. Water Res. 146, 244–255. El-Chakhtoura, J., El-Fadel, M., Rao, H.A., Li, D., Ghanimeh, S., Saikaly, P.E., 2014. Electricity generation and microbial community structure of air-cathode microbial fuel cells powered with the organic fraction of municipal solid waste and inoculated with different seeds. Biomass Bioenergy 67, 24–31. Han, G.G., Lee, J.Y., Jin, G.D., Park, J., Choi, Y.H., Chae, B.J., Kim, E.B., Choi, Y.J., 2016. Evaluating the association between body weight and the intestinal microbiota of weaned piglets via 16S rRNA sequencing. Vet. Microbiol. 196 (14), 55–62. He, P.J., Lu, F., Zhang, H., Shao, L.M., Lee, D.J., 2007. Sewage sludge in China: challenges toward a sustainable future. Water Pract. Technol. 2 (4), 1–8. Honda, T., Fujita, T., Tonouchi, A., 2013. Aminivibrio pyruvatiphilus gen. nov., sp. nov., an anaerobic, amino-acid-degrading bacterium from soil of a Japanese rice field. Int. J. Syst. Evol. Micr. 63, 3679–3686. Ito, T., Yoshiguchi, K., Ariesyady, H.D., Okabe, S., 2012. Identification and quantification of key microbial trophic groups of methanogenic glucose degradation in an anaerobic digester sludge. Bioresour. Technol. 123, 599–607. Ji, G.D., Tong, J.J., Tan, Y.F., 2011. Wastewater treatment efficiency of a multi-media biological aerated filter (MBAF) containing clinoptilolite and bioceramsite in a brickwall embedded design. Bioresour. Technol. 102, 550–557. Jia, J.N., Tang, Y., Liu, B.F., Wu, D., Ren, N.Q., Xing, D.F., 2013. Electricity generation from food wastes and microbial community structure in microbial fuel cells. Bioresour. Technol. 144, 94–99. Kostrytsia, A., Papirio, S., Morrison, L., Ijaz, U.Z., Collins, G., Lens, P.N.L., Esposito, G., 2018. Biokinetics of microbial consortia using biogenic sulfur as a novel electron donor for sustainable denitrification. Bioresour. Technol. 270, 359–367. Li, H., Huang, S.B., Wei, Z.D., Chen, P.F., Zhang, Y.Q., 2016. Performance of a new suspended filler biofilter for removal of nitrogen oxides under thermophilic conditions and microbial community analysis. Sci. Total Environ. 562, 533–541. Li, W.W., Yu, H.Q., He, Z., 2014. Towards sustainable wastewater treatment by using microbial fuel cells-centered technologies. Energy Environ. Sci. 7, 911–924. Liu, H., Cheng, S., Logan, B.E., 2005. Production of electricity from acetate or butyrate in a single chamber microbial fuel cell. Environ. Sci. Technol. 39 (2), 658–662. Liu, S.-H., Lai, C.-Y., Ye, J.-W., Lin, C.-W., 2018. Increasing removal of benzene from groundwater using stacked tubular air-cathode microbial fuel cells. J. Clean. Prod. 194, 78–84. Logan, B.E., 2009. Exoelectrogenic bacteria that power microbial fuel cells. NAT. Rev. Microbiol. 7, 375–381. Luo, H.P., Yu, S.X., Liu, G.L., Zhang, R.D., Teng, W.K., 2016. Effect of in-situ immobilized anode on performance of the microbial fuel cell with high concentration of sodium acetate. Fuel 182, 732–739. Marzorati, M., Wittebolle, L., Boon, N., Daffonchio, D., Verstraete, W., 2008. How to get more out of molecular fingerprints: practical tools for microbial ecology. Environ. Microbiol. 10 (6), 1571–1581. McCarty, P.L., Bae, J., Kim, J., 2011. Domestic wastewater treatment as a net energy producer-can this be achieved? Environ. Sci. Technol. 45, 7100–7106. Mei, X.X., Xing, D.F., Yang, Y., Liu, Q., Zhou, H.H., Guo, C.H., Ren, N.Q., 2017.

10