Enhancement of methane production and antibiotic resistance genes reduction by ferrous chloride during anaerobic digestion of swine manure

Journal Pre-proofs Enhancement of methane production and antibiotic resistance genes reduction by ferrous chloride during anaerobic digestion of swine manure Tiedong Lu, Junya Zhang, Ping Li, Peihong Shen, Yuansong Wei PII: DOI: Reference:

S0960-8524(19)31749-3 https://doi.org/10.1016/j.biortech.2019.122519 BITE 122519

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Bioresource Technology

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30 September 2019 26 November 2019 27 November 2019

Please cite this article as: Lu, T., Zhang, J., Li, P., Shen, P., Wei, Y., Enhancement of methane production and antibiotic resistance genes reduction by ferrous chloride during anaerobic digestion of swine manure, Bioresource Technology (2019), doi: https://doi.org/10.1016/j.biortech.2019.122519

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Enhancement of methane production and antibiotic resistance genes reduction by ferrous chloride during anaerobic digestion of swine manure Tiedong Lu a, b, c,1, Junya Zhang a, d, e,1, Ping Li b, c, Peihong Shen b, c, Yuansong Wei a, d, e, * a

State Key Joint Laboratory of Environmental Simulation and Pollution Control, Research Center

for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China b

College of Life Science and Technology, Guangxi University, Nanning, 530005, Guangxi, China

c

State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources,

Nanning, 530005, Guangxi, China d

Department of Water Pollution Control, Research Center for Eco-Environmental Sciences,

Chinese Academy of Sciences, Beijing,100085, China e

University of Chinese Academy of Sciences, 100049 Beijing, China

1

Tiedong Lu and Junya Zhang contributed equally to this work

*

Corresponding author’s e-mail: [email protected] (Yuansong Wei);

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Abstract: In this study, effects of ferrous chloride (FeCl2) addition on methane production and antibiotic resistance genes (ARGs) reduction were investigated during anaerobic digestion (AD) of swine manure. FeCl2 could both improve the accumulative methane production and reduce the abundance of total ARGs, i.e., the maximum increase of CH4 production of 21.51% at FC5, and the maximum ARGs reduction of 33.3% at FC25. A significant reduction of pathogenic bacteria and metal resistance genes (MRGs). Acetate and propionate utilization were intensified by enhancing H2 utilization and direct interspecies electron transfer (DIET), where DIET was further enhanced by the reaction of the FeCl2 and acetic acid. The bacterial community played important role in the evolution of ARGs (68.26%), which were also affected by MRGs, mobile genetic elements (MGEs), and environmental factors. Therefore, FeCl2-based AD is a feasible and attractive way to improve methane production and ARG reduction. Keywords: swine manure, anaerobic digestion, ferrous chloride, high-throughput quantitative PCR, ARGs

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1. Introduction In recent years, it was estimated that China produced 3.8 billion tons per year of livestock and poultry manure, and the comprehensive utilization rate is less than 60% (Bluemling and Wang, 2018). Improper disposal of these wastes can cause significant environmental pollution, including surface and groundwater contamination, odour problems and the spread of pathogens (Philip R. Goodrich and David Schmidt, 2013). Consequently, the Action Plan for Livestock and Poultry Manure Utilization (2017–2020) was implemented by the Chinese government in 2017 to promote the utilization of livestock and poultry manure resources; in this plan, anaerobic digestion (AD) was the core treatment method for swine wastewater and manure (Ma et al., 2018). Veterinary antibiotics (including tetracycline and tylosin) as feed additives were widely used in intensive livestock and poultry farming, as antibiotics not only prevent disease, but also improve feed efficiency, and promote the growth of the livestock and poultry (Larson, 2015; Wang et al., 2008). However, approximately 30%-90% of antibiotics cannot be absorbed and were thus excreted in the feces or urine. Therefore, antibiotic residues and ARGs were found in many manure and organic sludge sources, leading to ARGs enrichment, such that farm animal feces now contains an important ARG library (Ji et al., 2012). AD technology is a very effective technique for treating pig manure. It not only avoids pig manure pollution, obtains biogas clean energy, realizes waste recycling, and anaerobic digestion can remove pathogens and ARGs (Sui et al., 2016). However, low energy recovery efficiencies still limit its industrial application. (Bharathiraja et al., 2018). Therefore, research has recently focused on the improvement of AD and the concomitant reduction of ARGs in agricultural waste streams. In order to address both of these problems, many different treatment technologies have been investigated and utilized, such as chemical (Doǧan and Sanin, 2009), thermal (Song et al., 2004), enzymatic (Roman et al., 2006), ect. Unfortunately, most of these methods require high-energy inputs, making pretreatment processes costly (Wang et al., 2016).

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In recent years, iron-based materials, was low-cost and non-toxic additives such as iron (Fe) iron oxide, and iron salts, which were applied in AD considered to be an effective means of increasing methane production and sulfate control from AD systems (Nordell et al., 2016; Wei et al., 2018; Yun et al., 2019). Iron-enhanced AD system has evaluated by life cycle assessment (LCA), which revealed that scrap iron was favorable in economy and could reduce both operational costs and carbon emissions for carbon-neutral oriented WWTPs (Wei et al., 2018). Previous studies have shown that adding zero-valent iron and magnetite to the AD of swine manure can not only strengthen methane production but also promote the reduction of ARGs in the AD residue (Zhang et al., 2018, 2019b). However, due to the morphology of the zero-valent iron and magnetite, the optimum addition amount can be up to up to 20 g/L based on the molar mass of iron. In contrast, Qin et al., 2019 found that adding an appropriate amount of ferrous chloride or FeCl2, (determined to be 0.2 g/L) during sludge AD could increase methane production by 6.4% (Qin et al., 2019). In addition, the appropriate dosage of FeCl2 had the potential to create a favorable environment AD environment, including optimization of VFAs, COD and NH4+-N in the sludge system. Another benefit of FeCl2 additions on AD performance was the direct promotion of protease, dehydrogenase, and cellulase activities (Qin et al., 2019; H. Zhang et al., 2016). Other studies have shown that Fe2+ considerably enhanced the utilization of acetate, propionate, and H2 during the AD of organic matter at 37°C (Sai Ram et al., 2000). The current literature supports the possibility of enhancing methane production using appropriate FeCl2 additions, but the optimum concentrations and the mechanism of FeCl2 effects have not been resolved for the AD of swine manure. There was also very limited information available on the potential effects of FeCl2 additions on ARG dynamics during AD of swine manure, so research on the potential of FeCl2 as a benficial additive in the AD of swine manure is needed. In this study, we used batch experiments to optimize and characterize the effects of FeCl2 additions, including the potential mechanisms of the effects of FeCl2, on the performance and methane production dynamics of swine manure AD. And the fate and changes of ARGs in response 4

to FeCl2 additions were also investigated using a high-throughput quantitative PCR technology including 296 primer sets targeting almost all major classes of ARGs. 2. Materials and methods 2.1 Experiment setup Swine manure and inocula were collected from a swine farm in Beijing, China and immediately stored at 4°C until further use. The physicochemical properties of swine manure and inoculated sludge were shown in the supporting information. FeCl2.4H2O (99% metals basis; CAS, 3748-10-9) was purchased from Aladdin Reagent Co. Ltd., China. Batch experiments were conducted at 37°C and performed by AMPTS II instrument (Bioprocess Control AB, Sweden) as described previously (Lu et al., 2019). Briefly, the substrate and inoculum were mixed at a ratio of 3:1 (based on the total solids (TS) content) with a working volume of 0.4 L per bottle, and a final TS of approximately 8%. Mixing was conducted intermittently using a mixing motor to ensure adequate mass transfer. Treatments were based on the amount of FeCl2 added to the bottles, characterized by final elemental iron concentrations of 0 mmol/L (CK), 5 mmol/L (FC5), 10 mmol/L (FC10), 25 mmol/L (FC25), and 40 mmol/L (FC40). Methane production was continuously measured and recorded after removing carbon dioxide (CO2) and hydrogen sulfide (H2S) from the biogas by passing all biogas samples through a 3M NaOH solution. The batch experiment lasted 41 days, and samples were taken for analysis on days 0, 9, 16, 24, and 41. 2.2 Physicochemical analysis The liquid samples were collected through the centrifugation at 8000 rpm for 15 minutes followed by filtering through a 0.45 μm cellulose membrane. The filtrate obtained was used for the measurement of the SCOD (soluble chemical oxygen demand), NH4+-N, volatile fatty acids (VFAs), carbonates, polysaccharide and protein. These indicators were all measured by standard methods, as previously described (Lu et al., 2019). The concentration of iron in the filtrate was determined by ICP-OES (Inductively Coupled Plasma Optical Emission Spectrometer). Lastly, PO43- and SO42- were determined through ion chromatography. 5

2.3 Bacterial and archaeal community analysis DNA was extracted from 0.4 ml primary samples using the FAST DNA Spin Kit for Soil (MP Biomedicals, USA), and DNA qualities and quantities were measured by 0.8% agarose gel electrophoresis and measurement on a NanoDrop ND-1000 (NanoDrop, USA) spectrophotometer, respectively. Bacterial community structure analysis was carried out using primers 515F/806R (Caporaso et al., 2010). Arch340F/Arch1000R and Arch349F/Arch806R were used to analyze the structure of archaeal community (Zhang et al., 2016). Sequencing was conducted at the Sangon Co., Ltd. (Shanghai, China) sequencing centre using pair-end Illumina sequencing (Illumina Miseq, USA). Raw data were processed to obtain clean sequences that were then taxonomically annotated using the Ribosomal Database Project (RDP) classifier, as previously described (Lu et al., 2019). Taxa with relative abundances < 0.01% were removed from the dataset. The resultant filtered dataset was then subjected to diversity analyses by calculating diversity indices using the Mothur software package (Lu et al., 2019). Clean 16S rRNA gene sequences were submitted to the NCBI Sequence Read Archive (SRA) under the project accession PRJNA574860. 2.4 Quantitative PCR (qPCR) and High-throughput quantitative PCR (HT-qPCR) The functional genes cel5, cel48, hydA, dsrA, Acas, and mcrA were quantified to evaluate the activity of two types of cellulose degradation, fermenters, SO42- reducing bacteria, aceticlastic methanogens, and all methanogens, respectively (data in the supporting information). The qPCR steps followed did not deviate from those well-described in the literature (Zhang et al., 2019a). The primers and annealing temperatures were described as the previous research (Lu et al., 2019), and corresponding amplification efficiencies are provided in the supporting information. The highthroughput qPCR reactions were performed using the Wafergen SmartChip Real-time PCR system. There were 296 pairs of primers, including 252 ARGs, 28 mobile genetic elements (MGEs), 6 pathogens, and 10 MRGs in accordance with the current literature (Ouyang et al., 2015; Zhu et al., 2013). The 252 ARGs assays in this research contain almost all major ARGs (Aminoglycoside, Beta-Lactamase, Chloramphenicol, Macrolide-Lincosamide-Streptogramin (MLSB), Multidrug, 6

Sulfonamide, Tetracycline, Vancomycin and Others) and covered six resistance mechanisms (antibiotic efflux, antibiotic inactivation, antibiotic target alteration, antibiotic target protection, antibiotic target replacement and unknown). Amplification was conducted in 100 nL reaction containing (final concentration) 1× LightCycler 480 SYBR Green I Master Mix (Roche Inc., USA), Nuclease-free PCR-Grade water, 1 ng μL-1 BSA, 2 ng μL-1 DNA template, 1μM of each forward and reverse primer. The thermal cycle was: initial denaturation at 95 ℃ for 10 min, followed by a 40 cycles of denaturation at 95 ℃ for 30s, annealing at 60 ℃ for 30s, finally with amelting curve analysis auto-generated by the program. For each primer set, amplification was conducted in triplicate and a non-template control was included (data in the supporting information). 2.5 Data analysis The maximum production potential and rate were calculated using the modified Gompertz model as previously described (Lu et al., 2019). The free ammonia (FAN) concentration was calculated using the formula: FAN= (Total NH4+-N) × (1+10−pH/10− (0.09018 + 2729.92/T)) −1, where T is temperature (in Kelvin). The correlation between ARGs and microbial community was determined by Mantel test showing through the PAST 3.0. The significant difference of the OTUs between groups (p < 0.05) were computed by using STAMP 2.1.3 and the ternary plot was further drawn to show the significantly enriched OTUs through the R package of ggtern. Principal component analysis (PCA) and Procrustes analysis were used to evaluate relationships among measured biological and chemical data using Canoco 5.0. Network analysis based on the spearman correlation established through the Gephi platform. 3. Results and Discussion 3.1 Enhancement of methane production by FeCl2 addition and evolutions of VFAs The paired samples t-test indicated that ferric oxide significantly influenced the methane production during AD of swine manure at FC-5 (p<0.01). FeCl2 increased the accumulative methane production by maximum 21.5% from 221.5 mL CH4 g-1VSadded (CK) to 269.1 mL CH4 g1

VSadded when adding 5mmol/L FeCl2 (FC5; Fig. 1a). However, a low cumulative methane 7

production was observed with supplementation levels higher than 5mmol/L FeCl2. The increase in methane production occurred mainly during the peak days of 5-10 and 22-32 days. Degradation of the easily-degradable organics formed the first peak, and the poorly-biodegradable organics formed the second peak. This was easy to understand, because swine manure was a mixture of organic components with different biodegradation potentials (Wu et al., 2017). In addition, treatments with FeCl2 addition had extended periods of time with high daily methane yields, and resulted in higher cumulative methane yields. These results indicated that FeCl2 could enhance the degradation of the poorly-biodegradable organics. The maximum methane production rate (R) was significantly increased by 14.3% in the FC-5 treatment versus the CK treatment according to the Gompertz model analysis (Table 1). VFAs were intermediate products of AD processes and have a strong influence on the pH, alkalinity (ALK), and methanogenesis activity of digesters (Lin et al., 2013). The total amount of VFAs in the five groups had not reduced at the first time point (D9; Fig. 1b) because macromolecular substances (e.g., polysaccharides and proteins) had degraded and were converted into VFAs at this stage of the AD process. The changes of VFAs indicated that hydrolysis (the first step in anaerobic organic degradation) was not the limiting step for the AD of swine manure, and butyrate and acetate were degraded rapidly before D9. FeCl2 additions could promote degradation of iso-valerate and is-butyrate by D9. Then, iso-valerate and propionate generally accumulated along with AD due to the energetically unfavorable at D16 and D24, but the appropriate dosage of FeCl2 (FC-5) could alleviate the accumulation. At the end of AD (41), the energetically unfavorable VFAs were gradually degraded, and FeCl2 additions obviously enhanced this transformation, especially for propionic acid (Fig. 1c). The pH controlled by the endogenous ternary buffer system consisting of ammonia, VFAs, and carbonate, and reflected the changes in the AD stability (Yu et al., 2018). Acetic acid was the frequently the dominated constituent of VFAs in the AD process. According to Eq. (1) and Eq. (2), acetic acid could also be reacting with Fe2+ and attach to the sludge particles (Jin et al., 2015). 8

Besides, Fe2+ could be the main form considering its high standard reduction potential (𝐹𝑒 3+ + 𝑒 − ↔ 𝐹𝑒 2+ , 𝐸ℎ0 = 0.771𝑣) and reversible reactions, as shown in Eq. (1) and Eq. (2). Thus, adding FeCl2 into the swine manure AD process could promote acetic acid utilization for methane production. The pH and concentration of FAN decreased slightly in treatments with FeCl2 additions before D41, but had increased he starting levels on D41. Therefore, FeCl2 addition decreased the pH and FAN at early stage, but ensured that the ternary pH buffer system was in the normal range by promoting VFAs and organic matter degradation (Fig. 1d). At the end of AD (D41), the ammonia became the dominant factor in the ternary pH buffer system and lead to increasing of the pH because of FeCl2 improving the consumption of VFAs and carbonate. 𝐹𝑒 2+ + 2𝐶𝐻3 𝐶𝑂𝑂− ⇌ 𝐹𝑒(𝐶𝐻3 𝐶𝑂𝑂)2

(1)

Fe(𝐶𝐻3 𝐶𝑂𝑂)2 + 2𝐻2 𝑂 ⇋ 𝐹𝑒(𝑂𝐻)(𝐶𝐻3 𝐶𝑂𝑂) + 𝐶𝐻3 𝐶𝑂𝑂𝐻

(2)

3.2 Fate of ARGs, MGEs, MRGs and pathogens response to FeCl2 during AD of swine manure The fate of ARGs in swine manure AD could be divided into three stages corresponding to D9, D16 and D41. The dominant ARGs were Tetracycline, MLSB, Aminoglycoside, accounting for 35.54%, 30.94%, 24.28% of the total ARG content, respectively (data in supporting information), which is likely related to the use of antibiotics in pig farming. The addition of 25mmol FeCl2 increased the reduction of the abundance of total ARGs by a maximum of 33.3%; and there was increased reduction of both pathogenic microorganisms and MRGs. In addition, 25mmol FeCl2 enhanced the abundance reduction in the abundance of Tetracycline, MLSB and Aminoglycoside, accounting for 30.61%, 36.61% and 32.39% decreased abundance, respectively, by the end of the batch AD process (Fig. 2A). At D9, the ARGs of Aminoglycoside, Beta-Lactamase, Chloramphenicol, Multidrug, Sulfonamide were decreased after adding FeCl2 compared with CK. FeCl2 did not significantly influence the ARGs of MLSB and Tetracycline at D9. At D16, the ARGs of Aminoglycoside and Others had decreased after adding FeCl2, but Chloramphenicol, MLSB, Multidrug and Tetracycline 9

showed an opposite trend. As for Beta-Lactamase, its abundance decreases when the addition amount is greater than FC5. At the end of AD process (D41), FeCl2 treatments showed decreased the abundances of Tetracycline and Others. However, for Aminoglycoside and MLSB, the negative effect was only when FeCl2 concentrations exceed those in the FC5 treatment. When the concentration of FeCl2 was less than FC40, the abundance of Multidrug and Sulfonamide decreases. In addition, FeCl2 decreases the abundance of Beta-Lactamase and Chloramphenicol. In general, the abundance of total ARGs decreased after AD, and FeCl2 strengthens the reduction of main types of ARGs (Fig. 2A). In order to explore the effects of FeCl2 on the antibiotic resistance mechanism, all ARGs were divided into five categories according to different resistance mechanisms, including antibiotic efflux, antibiotic inactivation, antibiotic target alteration, antibiotic target protection, antibiotic target replacement and unknown, as showed in Fig. 2B. The dominant mechanisms were antibiotic inactivation, antibiotic target alteration, and antibiotic target protection, which account 38.18%, 28.42%, 21.71% of total resistance mechanisms, respectively (data in supporting information). In addition, 10mmol FeCl2 enhanced the abundance reduction of antibiotic inactivation, antibiotic target alteration, and antibiotic target protection by 22.47%, 24.97%, 20.06%, respectively, by the end of AD (Fig .2B). FeCl2 decreased the number of ARGs and the abundance of antibiotic efflux, antibiotic inactivation, antibiotic target replacement, and unknown, but it did not affect antibiotic target alteration and antibiotic target protection on D9. On D16, the antibiotic inactivation were decreased after adding FeCl2, but antibiotic target alteration showed the opposite trend. The abundance of antibiotic inactivation, antibiotic target protection, antibiotic target replacement, and unknown were all decreased after adding FeCl2 by the end of AD (D41), but the antibiotic efflux had increased. The antibiotic target alteration was decreased when the ferrous chloride concentrations exceeded levels in the FC5 treatment. This may be related to the enrichment of microorganisms by FeCl2.

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The dominant relative abundance MGEs was the mechanism of transposase, and FeCl2 strengthened the abundance of total MGEs at the end of AD (data in supporting information). The relative abundance of tcrB (as response to Cu) was the highest among the MRGs (Fig. 2C), and FeCl2 decreased the reduction of tcrB during AD. Moreover, merA (as a response to Hg) increased at D41 for the CK treatment, but FeCl2 additions enhanced the reduction of merA. The dominant pathogens were Enterococci, E. coli and Staphylococci (Fig. 2D), and their abundances were decreased after adding FeCl2. 3.3 Changes of physicochemical parameters The TS increased after AD, particularly with the addition of FeCl2, which included the oxidation of Fe2+, and the rapid hydrolysis of Fe2+ and Fe3+ (Eqs. 3, 4, 5) (Yu et al., 2016). Since the VS/TS reduction enhanced along with the FeCl2 addition (data in supporting information), because FeCl2 enhanced the he degradation of organic matter. With the addition of FeCl2, pH dropped sharply compared with control at the start-up phase (D0), likely due to the oxidation of Fe2+ and the rapid hydrolysis of Fe2+ and Fe3+( Fig. 3a). Subsequently, the pH value began to increase on D9 and D16, probably due to the decomposition of protein to produce a large amount of ammonia nitrogen. At the end of AD (D41), the pH value increased above 7.9 due to the addition of FeCl2. This change was ascribed to the addition of FeCl2 that promoted the consumption of VFAs later in the AD process. SCOD and TCOD decreased as AD progressed, and FeCl2 additions enhanced TCOD and SCOD reduction by maximum 53.9% and 45.7% (FC-5), respectively (Fig. 3b c). As previously described in the literature that the appropriate dosage of FeCl2 could promote the COD utilization (Qin et al., 2019). The free ammonia (FAN) concentration was increase throughout AD process, but additions of FeCl2 could alleviate its increase before D24 (Fig. 3d). The changes of soluble polysaccharides showed the same negative pattern as SCOD (Fig. 3f). In contrast, the soluble proteins increased as AD progressed, but FeCl2 improved the degradation (Fig. 3e). The PO43- (phosphate) decreased significantly during AD, and its reduction was proportional to the addition of FeCl2, which was 11

consistent with the formation of precipitates, such as vivianite [Fe3 (PO4) 2·8H2O] (An et al., 2014). Moreover, the significant decrease of SO42- in the FeCl2 treatments indicated sulfate reduction enhanced by FeCl2, and Fe-S precipitate was easily formed during AD (Puyol et al., 2017). Thus, it was hypothesized that the Fe-S precipitate was formed at the surface of ferrous hydroxide (Fe (OH) 2)

or iron hydroxide (Fe (OH) 3), which could contribute to the improvement of the methane

production. The concentration of soluble Fe did not increase significantly with FeCl2 addition (Fig. 3i), and it might be due to the adsorption of hydroxy iron. The changes of soluble Fe showed the same pattern of PO43- and SO42-. 𝐹𝑒 2+ − 𝑒 − → 𝐹𝑒 3+

(3)

𝐹𝑒 2+ + 2𝐻2 𝑂 → 𝐹𝑒(𝑂𝐻)2 + 2𝐻 +

(4)

𝐹𝑒 3+ + 3𝐻2 𝑂 → 𝐹𝑒(𝑂𝐻)3 + 3𝐻 +

(5)

3.4 Changes in the microbial community The alpha diversity of microbial community generally decreased along with AD, and there existed limited effects of FeCl2 on the diversity, as shown in the supporting information. Firmicutes, Bacteroidetes, and Proteobacteria were the three most abundant phyla in the AD process, and the relative abundance of Firmicutes (61.1%–87.9%) was generally higher than Bacteroidetes (7.1%–31.8%), as shown in the supporting information. FeCl2 increased the abundance of Bacteroidetes and significantly decrease the Firmicutes on D9 and D16, highlighting the positive and significant correlation between Bacteroidetes and FeCl2 (p < 0.05). Nevertheless, the abundance of Firmicutes and Bacteroidetes showed an opposite trend at D41 compared with D9 and D16 (data in supporting information). Clostridium sensu stricto, unclassified_Ruminococcaceae, Clostridium III, Unclassified Bacteroidales, unclassified Clostridiales, were the five most abundant genus throughout the AD process, with average abundances all above 5% (Fig. 4A and B). Clostridium is an important syntrophic bacterium for the acetate along with methanogens. Additions of FeCl2 did not significantly influence the changes of these microbes, and these genera were typical fermentative 12

microbes present in AD that participated in the degradation of macromolecular compounds (Venkiteshwaran et al., 2017). In contrast, FeCl2 did significantly increase the abundance of Alkaliflexus at D9 and D16, but showed an opposite tendency by the end of AD process on D41. Alkaliflexus could mainly utilize several types of carbohydrates to produce VFAs, and particularly those that can result from the hydrolysis of cellulose, hemicelluloses, and other natural polysaccharides (Zhao et al., 2018). This can be attributed to the exhaustion of easily degraded after D16. The abundance of organisms in the genus Petrimonas, which was typically described as containing mesophilic, strictly anaerobic, and fermentative bacterium, increased after adding FeCl2; acetic acid, H2, and CO2 were the major end products (Grabowski et al., 2005). This also indicated that FeCl2 enhances the conversion of other substances to acetic acid, which in turn increases methane production. The abundance of Terrisporobacter was increased on D41 after adding FeCl2, which has main fermentation products of acetate and CO2 (Deng et al., 2015). The abundance of Syntrophomonas, which was capable of syntrophic degradation of butyrate degradation with methanogens, was increased at D16 and D41(Zhang et al., 2004). Thus, the accumulation of acetate and butyrate is not severe, but the degradation of propionate degradation happened after D24, when the FeCl2 had enhanced the methane production rate, and thus extended the period of methane production peak compared with CK treatment (Fig. 1b). In addition, adding FeCl2 decreased the abundance of the unclassified_Clostridiales_Incertae Sedis XI, unclassified_Lachnospiraceae, Thiopseudomonas and unclassified_Marinilabiliaceae genera after D16; these genera were generally fast-growing bacteria that could endure oligotrophic environments, and correspond to the low methane production at D9-D24. PCA analysis showed that the changes of microbial community could be divided into three stages, and that FeCl2 addition significantly altered community composition (p < 0.05; Fig. 4C). The three stages could be attributed to the hydrolysis, acetogenesis, and methanogenesis phase of anaerobic digestion. The abundance of Alkaliflexus was enriched in the FeCl2 treatments at D9, which could correspond to its enhanced ability to use of several types of carbohydrates to produce 13

VFAs for increasing the methane production. The FeCl2 at D16 enriched in Clostridium III. The genus of Clostridium III are generally fast-growing bacteria that can endure oligotrophic environments, which is also the reason for the low peak of methane production from D12-20 (Fig. 1b) (Castellano-Hinojosa et al., 2018). The FeCl2- treated at D41 were enriched in the genus of Clostridium sensu stricto, Terrisporobacter, Syntrophomonas. The Clostridium sensu stricto is a kind of fermentative microbes that degradeds the macro-substances, producing both acid and alcohol during fermentation (Peng et al., 2018). These microbes could enhance the syntrophic association with methanogens for the methane production. The dominant archaea were Methanosarcina, Methanosphaera and Methanobrevibacter, and an average of all samples of 45.1%, 37.3%, 14.4%, respectively (Fig. 4D). The FeCl2 additions significantly affected the archaeal community (p < 0.05). The dominant archaea at each stage was different. At D9, the dominant archaea were Methanosphaera and Methanosarcina, and FeCl2 increased the abundance of both genera. The abundance of Methanosphaera was much higher than Methanosarcina. Methanosphaera could only obtain energy for growth using H2 to reduce methanol to methane (Blaut, 1994). In contrast, Methanosarcina can use acetate, methanol, monomethylamine, dimethylamine, trimethylamine, H2/CO2, and CO to produce methane. The much higher abundance of Methanosphaera corresponding to the higher amounts of methane production indicated that methanol might be very important for the production of methane at the hydrolysis and acetogenesis phase. At D16, the dominant archaea were still Methanosphaera and Methanosarcina, and FeCl2 increased the abundance of Methanosarcina compared with CK. The Methanosarcina and Methanosphaera consumed the acetate and part of the H2 and CO2 for the methane production at this stage. By the end of AD (D41), FeCl2 significantly increased the abundance of Methanosarcina due to the decomposition of refractory organic matter by FeCl2, in which Methanosarcina can utilize these organic matters for methane production. During all three stages, the Methanobrevibacter always decreased after adding FeCl2; these organisms can only use H2 or formate during methanogenesis, rather than acetate. 14

3.5 Effects of FeCl2 addition on key functional genes To evaluate the activity of two types of cellulose-degrading bacteria, fermenters, sulfate reducing bacteria, acetoclastic methanogens, and all methanogens, functional genes that correspond to these processes (cel5, cel48, hydA, dsrA, Acas and mcrA, respectively) were quantified (Fig. 5). The relative abundance of cel5 increased on D9 and D16 after adding FeCl2. In addition, the cel48 always increased after adding appropriate dose of FeCl2 (FC5) on D9 and D16, but the opposite trend was observed in FC10, FC25 and FC40 at D16. This is the reason why there was a low peak period of methane production for FC10, FC25 and FC40 treatments compared with the CK and FC5 treatments from D12-D22. At D41, the relative abundance of Cel5 and Cel48 decreased after FeCl2 was added, likely due to the large amount of cellulose degraded for test group at early stages. In the case of fermenters, the hydA gene was chosen because it encodes an Fe hydrogenase that catalyzes H2 evolution. The hydA gene abundance continuously increased only in the FC5 treatment, indicating that an appropriate dose of FeCl2 can enhance the fermentation of organic matter and utilization of H2. Meanwhile, H2 utilization was conducive to the consumption of propionic acid, which corresponds to an increase in methane production. There was an upward trend in the relative abundance of the dsrA gene after adding the optimal amount of FeCl2 (FC5) on D9 and D16, which indicated that FeCl2 enhanced the formation of Fe-S precipitates. The Acas encoding the acetyl-coA synthetase could represent acetoclastic methanogenesis, which uses the acetate in the methane production (Aydin et al., 2015), and the much lower ratio of Acas/mcrA indicated that methanogenesis in our system was primarily conducted by hydrogenotrophic methanogens rather than acetoclastic methanogens. The abundance of Acas and Acas/mcrA ratio increased after adding FeCl2 on D9, while the relative abundances of Acas and Acas/mcrA decreased on D16 and D41. These results indicate that FeCl2 strengthened the acetoclastic methanogenesis pathway during the early stage of AD (D9), but enhanced the hydrogenotrophic methanogens after D16. This is consistent with the consumption of VFAs and increased methane production. 15

3.6 Potential mechanisms of the performance response to FeCl2 This study investigated the effects of FeCl2 additions on methane production t using biomethane potential tests. As shown in the Fig. 1, the FeCl2 enhanced step of hydrolysis, acidogenesis and methanogenesis. Generally, iron could improve or change the microbial community through its role as a trace elements. In this study, there was obvious soluble iron from the FeCl2 at D0, but it showed the opposite trend after D9 due to the adsorption of hydroxy Fe (Eqs. 3, 4, 5). Meanwhile, the microbial community structure changed significantly after D9. The appropriate concentration of FeCl2 (FC5) can cnhance the methane production at this stage (D0-D9). Howere, the excessive FeCl2 (e.g., the FC10, FC25, and FC40 treatments) inhibited the rate of methane production before D5, because of high levels of ferrous ion caused the pH to drop sharply due to the oxidation of Fe2+ and the rapid hydrolysis of Fe2+ and Fe3+. The enrichment of the Alkaliflexus and Petrimonas by the FeCl2 at this stage (D0-D9) could also have enhanced the methane production. Meanwhile, FeCl2 increased the abundance of Methanosphaera and Methanosarcina at this stage, which are both capable of consuming acetate and part of the H2 and CO2 during methane production. Moreover, the key gene of Acas gene increased after adding FeCl2, which suggested the utilization of acetic acid was also enhanced. During the next stage (D9-D24), the refractory substances began the degradation, and the VFAs and H2/CO2 was consumed, leading to a relatively low rate of methane production. Morover, excessive FeCl2(e.g., the FC10, FC25, and FC40 treatments) inhibited the rate of methane production and enhanced the accumulation of propionic; due to the higher partial H2 pressure at this stage, propionate further accumulated because low H2 concentrations were essential for the propionate oxidation to be energetically favorable. In contrast, adding the appropriate concentration of FeCl2 (e.g., the FC5 treatment) enhanced the rate of methane production and the consumption of propionate. This enhancement was due to the abundant Fe2+ enabling bonding that allowed the extracellular polymeric substances (EPS) of sludge to form stable complexes, which is crucial to maintaining an intact structure in an anaerobic sludge (Shen et al., 1993). 16

In contrast, the toxic effects of high levels of Fe2+ are caused by disruption of enzyme structure and function via replacement of original metals in enzyme prosthetic groups by Fe2+, or through binding of functional groups with protein molecules (Chen et al., 2014). In addition to the toxic effects of enzymes, excessive addition of Fe2+ may disrupt the structure of EPS, which play a vital role in protecting the system against possible inhibition by metals (Wei et al., 2017). The the key gene ratio of Acas/mcrA also showed that adding the FeCl2 increased the hydrogenotrophic methanogens at this stage. Thus, the addition of appropriate concentration Fe2+ could intensify the utilization of acetate and propionate by considerably enhancing H2 utilization by microorganism (Sai Ram et al., 2000). At the last stage (D24-D41), the methane production increased significantly and was proportional to the concentration of FeCl2. As described in the literature, the propionate should be syntrophic oxidized into H2/CO2 (IHT), H+/e−/CO2 (DIET) and acetate first (Jing et al., 2017). However, this study found no syntrophic propionate bacteria (Narihiro et al., 2012); therefore, we posit that FeCl2 increased the degradation of propionic by DIET. We also observed that FeCl2 promoted the abundance of its dominant bacterial (Syntrophomonas) and archaeal (Methanosarcina, Methanosphaera) genera during the methanogenesis stage, which have been previously shown to conduct DIET (Zhao et al., 2018). Furthermore, as showed in Fig. 3i, the concentration of iron in group FC25 and group FC40 increased significantly, which may be attributed to the DIR (dissimilatory iron reduction) effect of hydroxyl iron (Li et al., 2019). Therefore, the high concentration of FeCl2 to promote methane production was more obvious at this stage, and it was speculated that the hydroxy Fe reacted with acetic acid to form magnetite perform the DIET (Eqs. (6)) (Prakash et al., 2019). 𝐶𝐻3 𝐶𝑂𝑂− + 24𝐹𝑒(𝑂𝐻)3 (𝑠)(𝑓𝑒𝑟𝑟𝑖ℎ𝑦𝑑𝑟𝑖𝑡𝑒) → 8𝐹𝑒3 𝑂4 (𝑠)(magnetite) + 2𝐻𝐶𝑂3− + 36𝐻2 𝑂 (6) In conclusion, FeCl2 could improve or change the microbial community through its role as trace elements before D9 and enhance the DIET and DIR by hydroxyl Fe after D9. Exactly how the

17

surface biochemistry of FeCl2 promotes the DIR and DIET pathways will require further investigation. 3.7 Deciphering the fate of ARGs response to FeCl2 The fate of ARGs was significantly correlated with microbial community (p=0.0001), environmental variables (p=0.0064), MGEs (p=0.0005), MRGs (p=0.0086) and FeCl2 (p=0.0222) by mantel test. This result shows that FeCl2 and other factors are equally important to the fate of ARGs. To elucidate the relationship between ARGs variation and bacterial community, we conducted a Procrustes analysis was conducted by rotating the ordination of changes in the bacterial community to match the profiles of ARGs based on PCA analysis. We could explain 68.26% of the variables of the evolution of ARGs using the changes of bacterial community. Procrustes analysis further elucidated the positive and significant correlations (R=0.8563 and 0.8993) between microbial community and ARGs variation respectively (Fig. 6A). In order to analyze the influence of FeCl2 on ARGs, the top 10 most abundance ARGs were selected for heatmap (Fig. 6B). Network analysis showed the potential hosts of top 10 ARGs and the relationship among the top 10 ARGs, environmental variables, MGEs, MRGs and other factors (Fig. 6C). The results showed that microbial community was the main factor affecting ARGs, followed by MGEs and MRGs. However, the host of ARGs were not important, functional bacteria for methane production during AD, which could be well explained by the fact that these bacteria were not enriched after adding FeCl2; FeCl2 additions only increased the abundance of key functional microbes, which does not correlate with ARB through network analysis (Fig. 6C). The microbial community changes throughout AD with the accumulation of VFAs, material degradation, and methane production. At different stages, specific microorganisms were enhanced or decreased, and the ARGs changed accordingly with the change of ARB. Meanwhile, horizontal gene transfer (HGT) happened. The significant correlation between ARGs and MGEs indicated the importance of HGT on the ARGs fate. The 5 types of MGEs (tnpA-06, tnpA-03, tnpA-04, IS613, Tp614) were positively correlated with ARGs, which increased after adding FeCl2, evidence for a 18

transposase mechanism at the end of AD (D41) (data in supporting information). Network analysis showed that the significant correlation between tnpA-06 with ermT-01,vaE-01, vaE-02, tetPA generally existed in AD, and these ARGs were increased after adding FeCl2. The tnpA-03 and tnpA04 gene abundances were significant correlated with the ermT-02 and ermB genes, which were increased after adding FeCl2. Thus, some ARGs were increased due to FeCl2 changes the enzyme activity of some MGEs. Meanwhile, the dominant factors influencing the specific ARGs could vary, and there existed significantly positive correlation between tcrB, merA, pcoA, copA, which indicated that the coselection from heavy metals could have contributed the fate of those ARGs. The significant correlation between the genus of Streptococcus with ermT-01, vatE-02, and tetM-01 genes supports a common host bacteria, and that multiple resistance existed widely. 4. Conclusions FeCl2 could both improve the accumulative methane production and reduce the abundance of total ARGs during the AD of swine manure. The accumulative methane production was increased by 21.51% at FC5, and the maximum reduction of total ARGs was increased by 33.3% at FC25. The reduction of both pathogenic microorganisms and MRGs was enhanced. FeCl2 intensified the utilization of acetate and propionate by considerably enhancing H2 utilization in microorganisms and DIET. The bacterial community played important role in the evolution of ARGs (68.26%), which were also affected by MRGs, mobile genetic elements (MGEs), and environmental factors.

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Acknowledgements This work was financially supported by the National Major Science and Technology Projects for Water Pollution Control and Management of China (2017ZX07102-002), the National Natural Science Foundation of China (51808540), the National Key R&D Plan of China (No. 2016YFD0501405), and the Guangxi Key Research and Development Program (AB16380025). We thank LetPub (www.letpub.com) for its linguistic assistance during the preparation of this manuscript.

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Figure and table captions Table 1. Results of the fitting of the modified Gompertz model. Figure 1. Cumulative (a), daily methane production (b), changes in VFA accumulation (c), and profiles of pH values and the ternary buffer system(d) during AD of swine manure at different FeCl2 addition levels. Figure 2. Changes the abundance of different types ARGs (A), the abundance of different mechanisms of ARGs (B), MRGs (C) and pathogen (D) response to FeCl2 during AD of swine manure. Figure 3. Dynamic changes in physicochemical parameters during AD of swine manure at different dosages of FeCl2. Figure 4. Heatmap (A) showing the dynamics of the top 10 genus response to FeCl2; the ternary plot (B) indicating the enriched genus at different groups, and each point corresponds to a genus; principal component analysis (PCA, C) based on the bacterial community; changes of the archaeal community (D) response to FeCl2 during AD of swine manure. Figure 5. Changes in microbial functional gene abundances during AD of swine manure. Figure 6. Procrustes analysis showing the relationship between ARGs and microbial community (A); heatmap (B) showing the dynamics of the top 10 ARGs, MGEs and MRGs response to FeCl2; network analysis (C) indicating the factors influencing the target ARGs.

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29

30

31

32

33

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Table 1. Results of the fitting of the modified Gompertz model. * Treatments

R2

Rm (mL/ (g VSadded)

P (mL/g VSadded)

Control

0.994

10.32

229.9

FC5

0.991

11.8

279.3

FC10

0.99

9.9

249.0

FC25

0.988

9.7

267.7

FC40

0.981

9

277.4

*

The number in the brackets indicated the extent of the improvement by the addition of FeCl2

compared to the control. Rm is the maximum specific methane production rate (NmL d−1 gVSadded−1); P is the bio-methane production potential (NmL d−1·g-VSadded−1) and λ is the lag phase time (d).

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Highlights: 

Methane production was enhanced by adding FeCl2 through utilization of propionate.



The acetoclastic and hydrogenotrophic methanogens were strengthened by FeCl2.



FeCl2 could enhance the abundance reduction of ARGs, pathogenic and MRGs.



The main evolution of ARGs was explained by the changes of bacterial community.

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