Anaerobic digestion of mixed urban biowaste: The microbial community shift towards stability

Journal Pre-proof Anaerobic digestion of mixed urban biowaste: The microbial community shift towards stability Barbara Tonanzi, Camilla M. Braguglia, Agata Gallipoli, Daniele Montecchio, Pamela Pagliaccia, Simona Rossetti, Andrea Gianico

PII:

S1871-6784(18)31944-7

DOI:

https://doi.org/10.1016/j.nbt.2019.10.008

Reference:

NBT 1214

To appear in:

New BIOTECHNOLOGY

Accepted Date:

15 October 2019

Please cite this article as: Tonanzi B, Braguglia CM, Gallipoli A, Montecchio D, Pagliaccia P, Rossetti S, Gianico A, Anaerobic digestion of mixed urban biowaste: The microbial community shift towards stability, New BIOTECHNOLOGY (2019), doi: https://doi.org/10.1016/j.nbt.2019.10.008

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Anaerobic digestion of mixed urban biowaste: The microbial community shift towards stability

Barbara Tonanzi, Camilla M. Braguglia, Agata Gallipoli, Daniele Montecchio, Pamela Pagliaccia, Simona Rossetti, Andrea Gianico*

Water Research Institute IRSA-CNR, Area della Ricerca RM1, Via Salaria km 29.300, 00015 Monterotondo (Roma), Italy

Corresponding author.

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*

Tel.: +39 0690672799; fax: +39 0690672787.

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E-mail address: [email protected]

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Highlights

(WAS) are presented.

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Food waste anaerobic digestion (AD) and co-digestion (AcoD) with waste activated sludge

Instability and long-term acidification occurred in AD processes

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WAS addition influenced microbial activity ensuring stable AcoD processes WAS addition avoided VFA accumulation due to establishment of stable active Archaea

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WAS provided trace elements and seeding of sludge microorganisms in AcoD reactors

Abstract Anaerobic digestion is applied worldwide to treat food waste (FW) with the aim of obtaining renewable bioenergy by exploiting the methane gas produced. However, there are several problems in practical applications, primarily due to system instability. Although exhaustive knowledge regarding anaerobic microbial community composition has been established, few studies have 1

investigated long-term correlations between microbial consortia, operative conditions and feedstock characteristics. Here, microbial community shifts as a response to feedstock variations were investigated in long-term semi-continuous systems, which were evaluated by an in situ cell detection method and 16S rRNA gene amplicon sequencing. FW digestion showed progressive system instability caused by the inhibition of methanogens, which resulted in volatile fatty acid accumulation and process failure at the low organic loading rate (OLR). Conversely, by codigesting FW with waste-activated sludge (WAS), a stable process with methane yields of up to 0.27 Nm3 kg-1VSfed for OLR = 1.7 gVS L-1d-1 was achieved. This stabilizing effect was not related to the buffering capacity of WAS, but to its capacity to avoid volatile fatty acid accumulation and

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falls in pH by overcoming methanogenic activity inhibition. WAS addition promoted the establishment of a stable and active archaeal population in anaerobic co-digestion (AcoD) reactors. The continuous supply of trace elements together with the seeding of microbial functional groups

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were the main drivers that positively affected process stability.

Abbreviations

AD: anaerobic digestion; AcoD: anaerobic co-digestion; BMP: biochemical methane potential;

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CARD: catalyzed reporter deposition; COD: chemical oxygen demand; FISH: Fluorescence in Situ Hybridization; FW: food waste; HRT: Hydraulic Retention Time; OFMSW: organic fraction of

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municipal solid waste; OLR: organic loading rate; OTU: Operational Taxonomic Unit; ORP: oxidation-reduction potential; TS: total solids; VFA: volatile fatty acid; VS: volatile solids; WAS:

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waste activated sludge.

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Keywords

Anaerobic co-digestion; food waste; waste-activated sludge; inhibition; trace elements; 16S rRNA

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gene amplicon sequencing

Introduction

Food waste (FW) valorization through anaerobic digestion (AD) represents a sustainable solution to decreasing the environmental impact caused by landfill disposal. However, because of the complex succession of biological degradation steps, AD is based on a delicate balance that may affect digester stability and consequently the amount of methane that is produced [1]. The high

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biodegradability of FW, mainly composed of easily degradable carbohydrates, could easily overload anaerobic digesters. Since acidogenesis is the fastest step in the AD process, the kinetic uncoupling between acid producers and consumers could result in an initial accumulation of volatile fatty acids (VFAs) and a consequent drop in pH, if the digester medium does not have sufficient buffering capacity [2]. VFA overload could inhibit the biomass involved in the subsequent methane production step [3–5]. Thus, many AD full-scale plants for mono-digestion of FW operate with low efficiencies due to an unbalanced nutrient ratio, deficiencies in essential elements, an accumulation

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of VFAs and the presence of process inhibitors [4,6]. To overcome these problems, municipal waste activated sludge (WAS) is generally used as a co-substrate with FW to increase buffer capacity, dilute toxic compounds, and adjust micro- and macro-nutrient availability [7–9]. Most studies

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dealing with anaerobic co-digestion (AcoD) of WAS and FW have focused on the operation and performance of digesters [10,11]. However, there is a lack of information regarding the role of

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added sewage sludge on the stability of the digestion process and its synergistic impact on the

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microbial population. Moreover, the biodiversity and metabolic pathways that were established during the steady operation of continuous processes using real sludge and FW as a substrate have

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rarely been reported.

Here, the long-term stability and performance of laboratory scale anaerobic reactors for the mono-

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and co-digestion of FW and WAS were investigated at mesophilic temperature by varying the

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organic loading rate (OLR). The scope of the study was to increase understanding of organics degradation during mono-digestion of FW and co-digestion at different ratios of FW to WAS. Microbial community composition and dynamics during the long-term steady-state operation of continuous-flow systems were also evaluated.

Materials and Methods Feedstocks and Inoculum

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FW was collected from the cafeteria of the research campus “Roma 1” of the National Research Council of Italy. The cafeteria serves approximately 300 meals per day and produces approximately 400 kg FW per week, consisting of mixed raw and cooked food, such as cheese (15%), bread and pasta (15%), and fruit and vegetable peelings (70%). FW was collected in multiple acquisitions and was manually screened to maintain a fixed composition that is typical of household FW. Sorted scraps were first chopped manually and then shredded (particle size below 1 cm) by a laboratory scale knife mill prior to being stored at -20°C. Before the chemical analyses, FW was thawed and

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diluted with deionized water to a 1:5 ratio. WAS was sampled once a week from the WAS recirculation line of Roma Nord wastewater

treatment plant, serving a population of 780,000. The main characteristics of FW and WAS that

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were used as substrate in the experimental tests are reported in Table 1.

The biomethane potential of both substrates were evaluated in duplicate by means of BMP tests

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carried out at mesophilic temperature and an S/I (substrate/inoculum ratio) of 0.5 by using AMPTS

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II (automatic methane potential system, Bioprocess Control, Sweden). For the start-up of the semicontinuous tests, an inoculum originated from a full-scale digester treating sewage sludge was used.

(HRT) of 20 d.

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Such inoculum was then acclimated by feeding FW daily with a constant Hydraulic Retention Time

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Semi-continuous operated reactors: operative parameters and configuration

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AD and AcoD tests were performed with FW alone or mixed with WAS, respectively, to evaluate the impact of the organic load of the feedstocks, calculated on a volatile solids (VS) basis, on digestion performance. Tests were carried out using 10 L stainless steel continuous stirred-tank (CSTR) bioreactors (Bioprocess Control, Sweden). Two semi-continuous AD tests were carried out using two reactors fed with FW only, operated at Organic Loading Rate (OLR) = 0.8 gVS L-1d-1 and OLR = 1.7 gVS L-1d-1 (’Low OLR’ and ’High OLR’), respectively. Two parallel AcoD tests were carried out maintaining the same OLRs, using FW+WAS mixtures as feedstocks (30%FW + 4

70%WAS and 70%FW + 30%WAS, on a VS basis, respectively). Table 2 presents the operating conditions adopted for the anaerobic tests, highlighting the different contributions of FW and WAS on the total OLRs (OLR-FW and OLR-WAS, respectively) that were applied to the AcoD tests. Notably, the OLR-WAS was maintained at 0.5 gVS L-1d-1, while the OLR-FW increased from 0.25 to 1.2 gVS L-1d-1.

The biogas produced in each reactor was collected and passed through a CO2 trap (a bottle filled

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with 3 M NaOH solution) and then through a methane detection unit (µFlow, compact gas flow meter by Bioprocess Control, Sweden) equipped with temperature and pressure compensation for the normalization of the gas flow rate and the volume measurement at T = 0°C and p = 1 atm.

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All reactors were fed manually 5 times per week (Monday to Friday). The digestate samples were analyzed every day for pH, total solids (TS) and VS content, twice per week for soluble COD and

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NH4+-N, soluble protein and carbohydrate.

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VFAs (acetate, propionate, butyrate, iso-butyrate) and once weekly for total COD, total nitrogen,

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Analytical methods

Total and volatile solids were determined according to standard methods [12]. The pH and

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oxidation-reduction potential (ORP) were detected by a Eutech Instruments pH-meter 700. To analyze the soluble phase, the particulate sludge matter was removed by centrifugation (at 4,066 x g

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for 10 min) and the resulting liquid phase was passed through 0.45 µm pore size membrane filters. CODs and CODtot were measured in duplicate by means of a COD Cell Test by Spectroquant Merck [13]. Samples were diluted with distilled water prior to sulfuric acid digestion (2 h at 148°C), in order to avoid any turbidity related impact.

Total nitrogen was determined photometrically after transformation of organic and inorganic nitrogen compounds into nitrate according to Koroleff’s method [14] by treatment with an oxidizing 5

agent in a thermoreactor (T = 120°C for 1 h) and after reaction with 2,6-dimethylphenol (DMP) to form 4-nitro-2,6-dimethylphenol in a solution that was acidified with sulfuric and phosphoric acid, via cell tests by Spectroquant Merck (digestion analogous to EN ISO 11905-1 [15] and determination of nitrate analogous to DIN 38405-9 [16]). Ammonium nitrogen (NH4+-N) was determined according to APHA (American Public Health Association) Standard Methods [12]. VFAs were analysed by injecting 1 mL filtered (0.2 µm porosity) liquid sample into a Perkin Elmer Auto System gas-chromatograph equipped with flame ionization detector (FID) (Perkin Elmer,

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USA). Metals were determined using an Agilent 7500c ICP-M (Agilent, USA), after an extraction phase carried out according to a modified EPA method 200.2 [17]. To analyse the colloidal phase, sample aliquots were passed through glass filters with 1.2 µm pores (GF/C Whatman) and the

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filtrate used for protein and carbohydrate determination. Colloidal protein content was determined by bicinchoninic acid protein assay (Pierce, Rockford, USA) using a standard solution of bovine

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serum albumin (BSA), which was modified from the Lowry method [18]. The determination of

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colloidal carbohydrates was based on a modified DuBois method [19].

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In situ detection methods (FISH and CARD-FISH)

Biomass was sampled from the reactors and was immediately fixed in formaldehyde and ethanol

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(2% and 48% vol/vol final concentration, respectively) and stored at -20°C. The samples were disaggregated by vortexing in the presence of glass beads for a few minutes before analysis. Total

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bacteria were identified using the oligonucleotide probes EUBmix (equimolar concentrations of EUB338, EUB338-II, and EUB338-III, Biomers.net GmbH [20]), whereas the ARC915 probe was used for Archaea detection (http://www.microbial-ecology.net/probebase/). Fluorescence in situ Hybridization (FISH) probes were labelled with fluorescein isothiocyanate (FITC) or sulfoindocyanine dye Cy3 (MWG AG Biotech, Germany) while Catalyzed Reporter Deposition Fluorescence in situ Hybridization (CARD-FISH) probes were labelled with horseradish peroxidase (HRP) (Biomers, Germany). FISH was performed as previously described [21], while CARD-FISH 6

analysis was performed according to the procedure in [22]. After hybridization, slides were mounted with Vectashield Mounting Medium® with 4′,6-diamidino-2-phenylindole (DAPI) (Vector Labs, Italy). Cells were counted by epifluorescence microscopy (Olympus BX51). Standard deviations and means were computed with Microsoft Excel®. The FISH/CARD-FISH ratio was calculated by dividing the average value of archaeal or bacterial relative abundance detected by FISH to that obtained by CARD-FISH analysis. This ratio was used as a gross parameter to estimate the active fraction of each population as previously validated for both pure cultures [23] and mixed

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microbial cultures [24] in engineered laboratory scale systems.

DNA Extraction

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One mL of digestate or activated sludge samples (corresponding to ~ 0.25 g wet weight) was used to extract DNA with the PowerSoil DNA Isolation kit (MoBio, Italy). DNA was eluted with 100 μL

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sterile distilled water, and the concentration and purity determined by a NanoDrop 2000c

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spectrophotometer (Thermo Scientific, USA). The genomic DNA was stored at -20°C for several days and then used for real-time PCR quantification (qPCR) and high-throughput 16S rRNA gene

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sequencing.

16S rRNA gene amplicon library preparation

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Bacterial 16S rRNA amplicon sequencing targets the V1-3 variable regions. 12.5 ng of extracted

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DNA was used as a template for the PCR reaction (25 μL) containing the dNTPs (400 µM), MgSO4 (1.5 mM), Phusion DNA Polymerase High-Fidelity (Thermo Fisher Scientific, USA), and barcoded library adaptors containing V1-3 specific primers 27F (AGAGTTTGATCCTGGCTCAG) and 534R (ATTACCGCGGCTGCTGG). PCR conditions used were previously reported in [25]. The amplicon libraries were purified using the Agencourt® AMpure XP bead protocol (Beckmann Coulter, USA).

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Nextera XT DNA Library Preparation Kit (Illumina, USA) was used to prepare the library. The library concentration was measured with a Qubit 3.0 Fluorometer (Thermo Fisher Scientific, USA). The Archaeal V3-5 16S sequencing libraries were prepared following the above procedure with V35 specific primers 340F (CCCTAHGGGGYGCASCA) and 915R (GWGCYCCCCCGYCAATTC). The purified libraries were pooled in equimolar concentrations at 4 nM. The samples were paired end sequenced (2x301 bp) using a MiSeq Reagent kit v3, 600 cycles (Illumina, USA) on a MiSeq System (Illumina, USA) following the standard procedure for preparing and loading samples. 10%

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of the Phix control library was then added to overwhelm the low complexity issue often observed with amplicon samples.

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Fastq processing and data analysis

Sequences were processed, quality filtered and analysed using QIIME2 version 2018.2 [26]. The

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DADA2 software package was employed to denoise the paired-end sequences, dereplicate them and

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filter chimaeras using the “consensus” method [27]. Fastq files were processed by the qiime dada2 denoise-paired command. Taxonomy was assigned using the relative abundances based on all obtained reads. The QIIME2 q2feature-classifier plugin and the Naïve Bayes classifier was trained

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on the Silva 132 database 97% Operational Taxonomic Units (OTUs) full length sequences [28]. To assess whether microorganisms immigrating from sludge grow in the system, the ratios were

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calculated of their mean read abundance in the system compared to the mean read abundance in the

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sludge fed to the system [29].

Results

Feedstock and digestate characteristics Chemical analysis of the feedstocks may provide useful information for the development of technological approaches to substrate treatment and utilization in the AcoD process. FW resulted in a higher concentration of volatile solids, with a BMP of 0.30 Nm3 CH4 kg-1VSfed compared with 8

0.15 Nm3 CH4 kg-1VSfed of the WAS (Table 1). Activated sludge, due to its biological origin, was rich in N and P, but poor in organic material. The soluble COD fraction of FW varied from 25% to 31% of total COD (Table 1) and was mainly composed of carbohydrates (approximately 80% of the soluble COD). In contrast, WAS was mainly composed of particulate organics that were concentrated in N (5% with respect to TS) and with a low C/N ratio (6.5 compared to 13 of FW). In respect of alkali and alkaline earth metals, WAS presented high concentrations of Ca and Mg, while FW was rich in Na and K. WAS resulted in richer essential micro-nutrients, including Fe, Cu, Ni,

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Mo, Se, and Co, compared to the FW (Table 1). The average characteristics of feedstocks and digestates for AD and AcoD tests are reported in Table 3 (low OLR) and Table 4 (high OLR), respectively. Intrinsically, the addition of WAS decreased the C/N ratio of the feedstock,

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particularly at a low OLR, for which the fraction of the sludge was 70% of the VS.

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AD and AcoD performances at low OLR

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In the first phase of the AD test, which was carried out at low OLR, methane production was always stable, maintaining an average value of 0.29 ± 0.03 Nm3 kg-1VSfed. A second HRT was performed to confirm results after acclimation of the microorganisms to the new substrate, and methane

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production started to decrease after day 25 (day 16 of feeding) to a final cessation of production (Figure 1a). Inhibition followed the same pattern of ORP, which increased to -160 mV. The soluble

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COD level was low and stable until day 20 (<0.5 gCOD L-1) and then increased to a final 4.7 gCOD

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L-1. In contrast, proteins and carbohydrates at the end of the test were found to be stable at low levels (0.6 gCOD L-1 and 0.03 gCOD L-1, respectively). VFAs, as shown in Figure 2a, followed a similar pattern to the COD trend, which confirmed that the majority (up to 80-90%) of the soluble COD in digestates was represented by VFAs. The NH4+-N concentration was stable at a very low level (0.3 g L-1) throughout the digestion test (Figure 1a).

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During the co-digestion test with 70% WAS and 30% FW, in contrast, methane production remained almost constant providing a yield of 0.16 ± 0.05 Nm3 kg-1VSfed during the steady state (Figure 1b). Despite the high initial values (due to the previous operation period with FW alone), the soluble COD concentration decreased progressively during co-digestion and reached values of ~0.2 ± 0.1 g L-1 at a steady state. Organics removal was lower with respect to the mono-digestion test (Table 3), due to the lower degradability of WAS ( 65% inert fraction, assessed through the BMP test). Moreover, addition of the WAS led to higher NH4+-N values in the reactor (up to 600

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mg L-1).

AD and AcoD performances at high OLR

During the first 15 d of the test with high OLR (1.7 gVS L-1d-1), an increase of soluble COD up to

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4-5 g L-1 occurred in both AD and AcoD reactors, coupled with low methane production and

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decrease in pH due to adaptation of the biomass to the increased OLR (Figures 3a,b). Thereafter, both reactors were able to recover their stability and achieved specific methane production of ~0.30

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± 0.04 Nm3CH4 kg-1VSfed. The first signs of instability in the AD process were only observed during the second HRT. After 60 d digestion, the AD reactor started to show a gradual

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accumulation of soluble COD of up to 14 g L-1, together with a gradual accumulation of acetic, propionic and butyric acids, until total system failure due to VFA inhibition (Figure 2b). In

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addition, in this case, acetate started increasing in concentration just before propionate, while butyrate began to accumulate at the end of the test, corresponding with the failure of the anaerobic

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process due to the fall in pH (Figure 3a). The carbohydrate and protein content remained reasonably stable around final values of 1 and 0.04 gCOD L-1, respectively.

The NH4+ concentration, which was high at the beginning due to the origin of the sludge inoculum, decreased during FW loading and reached values of <0.4 g L-1, which was not enough to ensure

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sufficient buffering capacity for the AD system (Figure 3a). The test was stopped after 3 HRTs when methane yield fell below 0.05 Nm3CH4 kg-1VSfed.

In contrast, the AcoD test remained stable for the entire test duration (Figure 3b). During this AcoD test at OLR = 1.7 gVS L-1d-1, no low pH or VFA accumulation occurred. The VS removal efficiency and specific methane production achieved were 71% and 0.27 ± 0.04 Nm3CH4 kg-1VSfed, respectively. It is important to highlight that the NH4+-N concentration was stable at ~0.7 g L-1,

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higher than FW mono-digestion (Figure 3b). Similarly, others [30] have reported a stable methane yield of 0.21 m3CH4 kg-1VSfed in full-scale AcoD of the organic fraction of municipal solid waste (OFMSW) with WAS at OLR = 1.6 gVS L-1d-1 and HRT = 23 d, with an NH4+-N concentration

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approximately 0.4 g L-1.

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Detection of bacteria and archaea using in situ hybridization methods

The relative abundances of total bacteria and archaea were estimated throughout the operation of

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the four anaerobic reactors using FISH and CARD-FISH analysis. As reported in supplementary Table S1, they were similar in most of the samples analysed. The sole exception was represented by

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the archaea in reactors fed with FW at both OLRs, for which the FISH detectability (typically associated with physiologically active cells) was always lower than the CARD-FISH (total archaeal

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cells). The FISH/CARD-FISH ratios estimated for bacteria and archaea over the reactor operation clearly showed that a portion of archaea occurred at a lower activity state in AD systems fed solely

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with FW and ranged between 40% and 50% of the total archaea after one HRT (Figure 4). The latter ratio shows the fraction of active microorganisms out of total members belonging to both investigated domains and is expected to reach values close to 1 under steady state operation and in the absence of inhibitory conditions. As shown in Figures 4a,b, a marked difference between bacteria and archaea was always observed in reactors fed with FW, with the lower FISH/CARDFISH values associated with the archaeal populations (0.4-0.7). This difference further increased

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with the increase of OLR. In the co-digestion systems, this ratio increased over time and reached the same values for both bacteria and archaea (0.9; Figures 4c,d). Bacterial and archaeal microbiome profiling The composition of the bacterial and archaeal communities was investigated by high-throughput 16S rRNA gene sequencing in digestate samples taken at different sampling times in all reactors. The total reads and OTUs obtained for each sample are reported in supplementary Table S2. For bacteria, OTUs and reads ranged between 82 and 918 and between 9,169 and 61,533, respectively,

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whereas the analysis of the archaeal microbiome produced a lower number of OTUs (9-38) and the reads ranging between 6204 and 103,569 (supplementary Table S2). The heat map of OTU

distribution at phylum level among the different bioreactors and in the WAS is shown in Figure 5.

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For WAS, the most abundant phyla were Proteobacteria and Bacteroidetes, as also observed by

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others [31]. Proteobacteria usually predominate in domestic sewage sludges, corresponding to 3065% of total sequences, presenting wide diversity and metabolic capacity, and acting in important

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environmental functions, such as the C, N, and S cycles [31,32]. In the digesters, between 40% and 80% of total OTUs belonged to three main phyla affiliated with Bacteroidetes, Chloroflexi and

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Firmicutes under all operating conditions, in line with previous evidence that showed the dominance of these phyla in co-digestion systems treating FW and WAS [9].

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The most abundant OTUs were affiliated with putative fermentative bacteria (Figure 6). In particular, Anaerolineaceae (Chloroflexi) and Clostridiaceae (Firmicutes) families were found in

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all reactors (both AD and AcoD systems), while members of Rikinellaceae (Bacteroidetes) and Prolixibacteraceae (Bacteroidetes) families were found at high relative abundance only in codigestion systems, reaching 13.9% and 21.7%, respectively. Most archaeal OTUs were affiliated with Methanomicrobia both in reactors fed only with FW and in co-digestion systems (60-99% of total OTUs, Figure 7). Methanomicrobiales represented the main family in each sample. In particular, at the end of operation, members of the Methanoculleus genus, which contains

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hydrogenotrophic methanogens, dominated in reactors fed with the sole FW together with acetoclastic Methanosaeta. Similarly, the main methanogens that are found in co-digestion systems over the reactor operation were members of the Methanoculleus and Methanosaeta genera at low and medium OLRs, respectively. It is worth to noting that OTUs that are affiliated with hydrogenotrophic Candidatus Methanofastidiosum strongly increased in both AcoD reactors.

Discussion

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The AD process carried out solely with FW at a lower OLR, showed a typical inhibition pattern due to a progressive pH decrease (Figure 1a) from an optimal value of 7.4 provided by the inoculum to the inhibitory value of 5.3, observed on the final day of feeding. The concentration of VFAs started

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increasing together with the CODs (day 39), and at the end of the process, acetate represented approximately 30% of the CODs. This is also mirrored by the high relative abundance of

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Paludibacteraceae observed at day 40 of the test (Figure 6). Such bacteria can ferment several

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varieties of sugar while producing acetate and propionate as major fermentation end-products [33] and were found to be dominant in AD systems treating substrates that are rich in complex carbohydrates [34]. In fact, propionate accumulation began immediately after acetate (at day 44),

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while butyrate accumulation started later during the digestion test (at day 58), since the optimal growth conditions for the butyrate-degrading bacteria depend on both hydrogen and acetate

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removal, according to [35].

Moreover, as shown in Figure 4a, after the first HRT, the archaeal FISH/CARD-FISH ratio decreased and remained at a lower level with respect to bacterial FISH/CARD-FISH throughout all tests. In contrast, in the AcoD reactor (OLR = 0.8 gVS L-1d-1), archaeal activity increased after the first HRT and reached the same level as observed for the bacteria (Figure 4c). This was confirmed by the VFA pattern shown in Figure 2, which indicated that no archaeal inhibition occurred in the

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AcoD test, thus resulting in successful VFA removal and a stable co-digestion process in terms of the methane production rate.

During the start-up phase of the mono-AD test at OLR = 1.7 gVS L-1d-1, potential inhibitory factors, such as VFAs, remained at low levels, except for propionate, for which the concentration rose to 1.3 g L-1 in the first days of the test before decreasing to lower levels (Figure 2b). This temporary accumulation of propionate, due to the initial adaptation of the anaerobic biomass to the new OLR,

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is also reflected in a slight decrease of gas production and pH values (Figure 3a). Nevertheless, the system was promptly able to recover its stability. A similar start-up behaviour was also observed for the AcoD test that was carried out at the same OLR (Figures 3b, 2d). However, after 60 d of

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digestion, a gradual accumulation of acetic, propionic, and butyric acid occurred until total system failure due to a fall in pH. As was observed for the AD process at a low OLR, the VFA

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accumulation is related to a decreased archaeal activity in the AD reactor. As shown in Figure 4b,

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after 60 d operation, bacterial activity remained at the same higher values while the FISH/CARDFISH ratio of methanogens underwent a dramatic decrease, thus causing a decrease in CH4 production down to 0.04 Nm3 kg-1VSfed (Figure 3a). In contrast, the AcoD test that was performed

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at the same OLR = 1.7 gVS L-1d-1 showed an increasing trend of archaeal activity throughout, reaching a steady-state value of 0.9 (Figure 4d). The same activity level was observed for the

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bacteria at steady-state conditions, thus indicating the high stability of the AcoD process, also with

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a higher OLR applied.

In all systems, the FW, mainly composed of readily biodegradable carbohydrates, selected a stable, active fermentative microbial population. Firmicutes and Bacteroidetes were the most abundant in AD and AcoD tests at both OLRs (Figure 5). The latter groups comprise known acidogens and were previously found in analogous systems [36–38]. Moreover, Anaerolineaceae and Clostridiaceae families were found in both reactors. They include fermentative, proteolytic and saccharolytic 14

bacteria with versatile metabolic capabilities [37,39]. In line with previous evidence found in fullscale anaerobic digesters [29], WAS addition probably promoted the immigration and establishment of specific microorganisms in AcoD reactors. In particular, high ratios of the mean read abundance of Rikinellaceae and Prolixibacteraceae compared to the mean read abundance in the sludge fed to the AcoD systems were observed at both OLRs (Supplementary Table S3). In addition, the microbiological analysis of the archaeal components revealed, in both AD tests, the marked decrease of Methanosaeta, which are acetoclastic methanogens, during digestion. Overall,

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methanogens were strongly inhibited in the AD reactors, as clearly shown by the FISH/CARDFISH ratio (Figure 4) and by the failure of the mono-digestion process after the full biomass

turnover (~3 HRTs). In contrast, WAS addition in AcoD reactors promoted the establishment of a

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higher biodiversity and activity of hydrogenotrophic methanogens, including both CO2-reducing and heterotrophic archaea, such as Candidatus methanofastidiosum. The latter was the main

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immigrating microorganism, with WAS showing a ratio increase of up to 215 and 234 at the end of

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the AcoD tests at low and high OLRs, respectively (Supplementary Table S3).

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Others [40] have stated that methanogenesis is the rate-limiting step for anaerobic digestion of a carbohydrate-rich FW, such as that used here. The on-average higher growth rate of bacteria

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compared with that of archaea, especially acetoclastic methanogens, may result in VFA accumulation and the consequent fall in pH. All the microorganisms involved are very sensitive to

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pH variations, and each AD step shows a distinct pH sensitivity. For fermentative bacteria, a comprehensive pH range from 4 to 8.5 is suitable, while most methanogens work optimally in a pH range from 6.5 to 7.2 [40]. Notably, the AcoD test at OLR = 1.7 gVS L-1d-1 was stable, with no VFA accumulation, although the FW contribution to the load was higher than that of the mono-AD test (see Table 2); hence, acidification was expected. Process inhibition was, therefore, due to other factors than the high biodegradability of FW.

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As reported elsewhere [41,42], the pH stability typically observed during co-digestion tests with sludge was attributed to the significant buffering capabilities of the system due to the alkalinity produced from NH3 and N compounds of the co-added WAS. However, the results obtained here highlight that the stabilizing effect is not only related to the buffering capacity of WAS addition but is due to the WAS capacity for avoiding VFA accumulation and fall in pH by overcoming methanogenic activity inhibition. The inhibition of methanogens could be related to the presence of

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process inhibitors, an unbalanced nutrient ratio or deficiencies in the essential elements [6]. In AD tests, the FW was diluted with deionized water, while in AcoD tests, the dilution was carried out using WAS. Therefore, the stabilizing effect of WAS could not be related to any dilution effect on

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the possible inhibitors or toxic compounds that are present in FW. Moreover, the macro-nutrient availability (i.e., the C/N ratio) was comparable for all AD and AcoD tests (Tables 3 and 4). As

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reported elsewhere, WAS is generally characterized by a low C/N ratio ranging from 6 to 9 [43].

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While some reports have suggested that the C/N ratio for optimum digestion performance is in the range of 20 to 30, many have demonstrated that digestion can be successfully performed under a wide range of C/N ratios [44–46]. A C/N ratio below 6 could negatively affect the digestion

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process, mainly due to a low C availability in combination with high NH3 concentrations, which are toxic for anaerobic microorganisms [47]. However, the relatively low concentration of NH3

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observed could never result in any detectable inhibition.

Consequently, the micro-nutrient availability could be one possible reason for the decrease in methanogenic activity. To ensure microorganism activity, a good nutritional balance is necessary in terms of trace elements, such as Mg, Se, Co, Ni and Fe [48–51], which favour the synthesis of critical enzymes in the process of hydrogenotrophic methanogenesis, the predominant methaneproducing pathway during AD of FW [52]. As reported in Table 1, WAS always resulted in richer micro-elements, suggesting that WAS addition could adjust the micronutrient composition in 16

anaerobic digesters, thus influencing microbial activity. Trace elements, such as Fe, Co, Ni and Mo, participate in the synthesis of several prosthetic groups, coenzymes and cofactors involved in anaerobic methanogenesis, thus playing an important role in different metabolic pathways [53]. As also shown in Table 1, the FW used here was rich in light metal elements, such as Na and K, but was characterized by low concentrations of trace elements, which resulted in lower-thanrecommended concentrations for maintaining satisfactory process performance and the stability of

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anaerobic systems [53,54].

Fe in particular appeared to play a key role. The WAS used contained approximately 400 times more Fe than FW, and the Fe:P ratio, a factor that is 30 times higher in WAS, could be one

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explanation for its stabilizing effect. In fact, Fe could replace the role of Ca in phosphate

precipitation, thereby forming Fe phosphate precipitates into which VFAs could be adsorbed [55].

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Nevertheless, others [56] found that supplementing a synthetic mix of trace elements for anaerobic

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reactors treating kitchen FW could prevent immediate process failure but would not guarantee stable long-term operation. In contrast, by adding an iron-rich sludge to the same FW, stable

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methane production was achieved under mesophilic conditions [56].

Overall, an AcoD with WAS showed better process efficiency and stability than FW mono-

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digestion by offering several benefits, including the continuous seeding of AD microbial functional

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groups from sludge, as was also observed in full-scale digesters treating sludge [29]. Moreover, the AcoD of FW with WAS can offer valuable synergies for the water industry and for the authorities responsible for FW management [10]. Nevertheless, several bottlenecks, such as regulatory uncertainty, a lack of suitable options for biogas utilization, and the impact on the quality of biosolids for agricultural use, have been reported [24]. A multi-disciplinary approach is therefore advised to promote AcoD as a key technology for a circular economy [57].

17

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Acknowledgements The authors wish to thank Gestione Servizi Integrati S.r.l. and ACEA S.p.a., the Municipal Agency for Electricity and the Environment of Rome, for their generous assistance and cooperation in food waste and sludge sampling, respectively. Metals were analysed with Domenico Mastroianni at IRSA-CNR. This paper is dedicated to the memory of our friend and colleague Dr. Valter Tandoi. His amazing passion and immense dedication in promoting interdisciplinary collaboration among chemists, engineers, and biologists allowed our environmental biotechnology research group to grow.

18

References Ventura JRS, Lee J, Jahng D. A comparative study on the alternating mesophilic and thermophilic two-stage anaerobic digestion of food waste. J Environ Sci (China) 2014;26:1274–83. doi:10.1016/S1001-0742(13)60599-9.

[2]

Capson-Tojo G, Girard C, Rouez M, Crest M, Steyer JP, Bernet N, et al. Addition of biochar and trace elements in the form of industrial FeCl3to stabilize anaerobic digestion of food waste: dosage optimization and long-term study. J Chem Technol Biotechnol 2018. doi:10.1002/jctb.5797.

[3]

Nagao N, Tajima N, Kawai M, Niwa C, Kurosawa N, Matsuyama T, et al. Maximum organic loading rate for the single-stage wet anaerobic digestion of food waste. Bioresour Technol 2012;118:210–8. doi:10.1016/j.biortech.2012.05.045.

[4]

Zhang C, Su H, Baeyens J, Tan T. Reviewing the anaerobic digestion of food waste for biogas production. Renew Sustain Energy Rev 2014;38:383–92. doi:10.1016/j.rser.2014.05.038.

[5]

Kawai M, Nagao N, Tajima N, Niwa C, Matsuyama T, Toda T. The effect of the labile organic fraction in food waste and the substrate/inoculum ratio on anaerobic digestion for a reliable methane yield. Bioresour Technol 2014;157:174–80. doi:10.1016/j.biortech.2014.01.018.

[6]

Ziels RM, Svensson BH, Sundberg C, Larsson M, Karlsson A, Yekta SS. Microbial rRNA gene expression and co-occurrence profiles associate with biokinetics and elemental composition in full-scale anaerobic digesters. Microb Biotechnol 2018;11:694–709. doi:10.1111/1751-7915.13264.

[7]

Appels L, Lauwers J, Degrève J, Helsen L, Lievens B, Willems K, et al. Anaerobic digestion in global bio-energy production : Potential and research challenges. Renew Sustain Energy Rev 2011;15:4295–301. doi:10.1016/j.rser.2011.07.121.

[8]

Forster-Carneiro T, Perez M, Romero LI. Influence of total solid and inoculum contents on performance of anaerobic reactors treating food waste. Bioresour Technol 2008;99:6994– 7002. doi:10.1016/j.biortech.2008.01.018.

[9]

Zhang J, Li W, Lee J, Loh KC, Dai Y, Tong YW. Enhancement of biogas production in anaerobic co-digestion of food waste and waste activated sludge by biological copretreatment. Energy 2017;137:479–86. doi:10.1016/j.energy.2017.02.163.

[10]

Zhang ZL, Zhang L, Zhou YL, Chen JC, Liang YM, Wei L. Pilot-scale operation of enhanced anaerobic digestion of nutrient-deficient municipal sludge by ultrasonic pretreatment and co-digestion of kitchen garbage. J Environ Chem Eng 2013;1:73–8. doi:10.1016/j.jece.2013.03.008.

Jo

ur

na

lP

re

-p

ro of

[1]

[11]

Mata-Alvarez J, Dosta J, Romero-Güiza MS, Fonoll X, Peces M, Astals S. A critical review on anaerobic co-digestion achievements between 2010 and 2013. Renew Sustain Energy Rev 2014;36:412–27. doi:10.1016/j.rser.2014.04.039.

[12]

Federation WE. APHA, Standard Methods for the Examination of Water and Wastewater 1998:2–2. doi:ISBN 9780875532356.

[13]

EPA Cincinnati OH. Method 410 . 4: The Determination of Chemical Oxygen Demand by Semi- Automated Colorimetry. Revision 2 . 0. Office of Water, US 1993:0–12.

[14]

Koroleff F. Gasshoff, K. Methods of seawater analysis, Verlag Chem. Total Org Nitrogen 1976:167–81.

19

EN ISO 11905-1. Water quality - Determination of nitrogen - Part 1: Method using oxidative digestion with peroxodisulfate ISO 11905-1 1997.

[16]

DIN 38405-9. German standard methods for examination of water, waste water and sludge Anions (group D) - Part 9: Spectrometric determination of nitrate (D 9) 2011;09.

[17]

EPA Cincinnati OH. Sample Preparation Procedure for Spectrochemical Determination of Total Recoverable Elements. National Exposure Research Laboratory, Office of Water, US Revision 2012.

[18]

Lowry OH, Rosebrough NJ, Farr AL, Randall RJ. Protein measurement with the folin phenol reagent. J Biol Chem, 1951;193:265–75. doi:10.1016/0304-3894(92)87011-4.

[19]

Dubois M, Gilles KA, Hamilton JK, Rebers PA, Smith F. Colorimetric Method for Determination of Sugars and Related Substances. Anal Chem 1956;28:350–6. doi:10.1021/ac60111a017.

[20]

Olson RJ, Chisholm SW, Devereux R, Stahl DA. Combination of 16S rRNA-Targeted Oligonucleotide Probes with Flow Cytometry for Analyzing Mixed Microbial Populations 1990;56:1919–25.

[21]

Nielsen PH, Kragelund C, Seviour RJ, Nielsen JL. Identity and ecophysiology of filamentous bacteria in activated sludge. FEMS Microbiol Rev 2009;33:969–98. doi:10.1111/j.15746976.2009.00186.x.

[22]

Matturro B, Ubaldi C, Grenni P, Caracciolo AB, Rossetti S. Polychlorinated biphenyl (PCB) anaerobic degradation in marine sediments: microcosm study and role of autochthonous microbial communities. Environ Sci Pollut Res 2016;23:12613–23. doi:10.1007/s11356-0154960-2.

[23]

Matturro B, Tandoi V, Rossetti S. Different activity levels of Dehalococcoides mccartyi revealed by FISH and CARD-FISH under non-steady and pseudo-steady state conditions. N Biotechnol 2013;30:756–62. doi:10.1016/j.nbt.2013.07.003.

[24]

Tonanzi B, Gallipoli A, Gianico A, Montecchio D, Pagliaccia P, Di Carlo M, et al. Longterm anaerobic digestion of food waste at semi-pilot scale: Relationship between microbial community structure and process performances. Biomass and Bioenergy 2018;118:55–64. doi:10.1016/j.biombioe.2018.08.001.

[25]

Crognale S, Casentini B, Amalfitano S, Fazi S, Petruccioli M, Rossetti S. Biological As(III) oxidation in biofilters by using native groundwater microorganisms. Sci Total Environ 2019;651:93–102. doi:10.1016/j.scitotenv.2018.09.176.

[26]

Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Gabriel A, et al. QIIME 2 : Reproducible , interactive , scalable , and extensible microbiome data science. PeerJ Prepr 2018. doi:https://doi.org/10.7287/peerj.preprints.27295v2.

Jo

ur

na

lP

re

-p

ro of

[15]

[27]

Callahan BJ, Mcmurdie PJ, Rosen MJ, Han AW, Jonson AJA, Holmes SP. DADA2: High resolution sample inference from Illumina amplicon data. Nat Methods 2016;13:581–3. doi:10.1038/nmeth.3869.DADA2.

[28]

Kehrmann J, Veckollari B, Schmidt D, Schildgen O, Schildgen V, Wagner N, et al. The lung microbiome in patients with pneumocystosis. BMC Pulm Med 2017;17:1–8. doi:10.1186/s12890-017-0512-5.

[29]

Kirkegaard RH, McIlroy SJ, Kristensen JM, Nierychlo M, Karst SM, Dueholm MS, et al. The impact of immigration on microbial community composition in full-scale anaerobic digesters. Sci Rep 2017;7:1–11. doi:10.1038/s41598-017-09303-0.

[30]

Cavinato C, Bolzonella D, Pavan P, Fatone F, Cecchi F. Mesophilic and thermophilic

20

anaerobic co-digestion of waste activated sludge and source sorted biowaste in pilot- and full-scale reactors. Renew Energy 2013;55:260–5. doi:10.1016/j.renene.2012.12.044. Nascimento AL, Souza AJ, Andrade PAM, Andreote FD, Coscione AR, Oliveira FC, et al. Sewage sludge microbial structures and relations to their sources, treatments, and chemical attributes. Front Microbiol 2018;9:1–11. doi:10.3389/fmicb.2018.01462.

[32]

Meyer DD, de Andrade PAM, Durrer A, Andreote FD, Corção G, Brandelli A. Bacterial communities involved in sulfur transformations in wastewater treatment plants. Appl Microbiol Biotechnol 2016;100:10125–35. doi:10.1007/s00253-016-7839-3.

[33]

Ueki A, Akasaka H, Suzuki D, Ueki K. Paludibacter propionicigenes gen. nov., sp. nov., a novel strictly anaerobic, Gram-negative, propionate-producing bacterium isolated from plant residue in irrigated rice-field soil in Japan. Int J Syst Evol Microbiol 2006;56:39–44. doi:10.1099/ijs.0.63896-0.

[34]

Liu T, Sun L, Nordberg Å, Schnürer A. Substrate-Induced Response in Biogas Process Performance and Microbial Community Relates Back to Inoculum Source. Microorganisms 2018;6:80. doi:10.1088/0264-9381/8/10/008.

[35]

Ahring BK, Westermann P. Product inhibition of butyrate metabolism by acetate and hydrogen in a thermophilic coculture. Appl Environ Microbiol 1988;54:2393–7.

[36]

Wang P, Wang H, Qiu Y, Ren L, Jiang B. Microbial characteristics in anaerobic digestion process of food waste for methane production–A review. Bioresour Technol 2018;248:29– 36. doi:10.1016/j.biortech.2017.06.152.

[37]

Zamanzadeh M, Hagen LH, Svensson K, Linjordet R, Horn SJ. Anaerobic digestion of food waste - Effect of recirculation and temperature on performance and microbiology. Water Res 2016;96:246–54. doi:10.1016/j.watres.2016.03.058.

[38]

Li L, He Q, Ma Y, Wang X, Peng X. Dynamics of microbial community in a mesophilic anaerobic digester treating food waste: Relationship between community structure and process stability. Bioresour Technol 2015;189:113–20. doi:10.1016/j.biortech.2015.04.015.

[39]

Vanwonterghem I, Jensen PD, Rabaey K, Tyson GW. Temperature and solids retention time control microbial population dynamics and volatile fatty acid production in replicated anaerobic digesters. Sci Rep 2015;5:1–8. doi:10.1038/srep08496.

[40]

Braguglia CM, Gallipoli A, Gianico A, Pagliaccia P. Anaerobic bioconversion of food waste into energy: A critical review. Bioresour Technol 2018;248:37–56. doi:10.1016/j.biortech.2017.06.145.

[41]

Kim HW, Han SK, Shin HS. The optimisation of food waste addition as a co-substrate in anaerobic digestion of sewage sludge. Waste Manag Res 2003;21:515–26. doi:10.1177/0734242X0302100604.

Jo

ur

na

lP

re

-p

ro of

[31]

[42]

Mehariya S, Patel AK, Obulisamy PK, Punniyakotti E, Wong JWC. Co-digestion of food waste and sewage sludge for methane production: Current status and perspective. Bioresour Technol 2018;265:519–31. doi:10.1016/j.biortech.2018.04.030.

[43]

Iacovidou E, Ohandja DG, Voulvoulis N. Food waste co-digestion with sewage sludge Realising its potential in the UK. J Environ Manage 2012;112:267–74. doi:10.1016/j.jenvman.2012.07.029.

[44]

Heo NH, Park SC, Lee JS, Kang H, Park DH. Single-Stage Anaerobic Codigestion for Mixture Wastes of Simulated Korean Food Waste and Waste Activated Sludge 2003;105:567–79.

[45]

Heo NH, Park SC, Kang H. Effects of mixture ratio and hydraulic retention time on single-

21

stage anaerobic co-digestion of food waste and waste activated sludge. J Environ Sci Heal Part A Toxic/Hazardous Subst Environ Eng 2004;39:1739–56. doi:10.1081/ESE-120037874. Zhang P, Zeng G, Zhang G, Li Y, Zhang B, Fan M. Anaerobic co-digestion of biosolids and organic fraction of municipal solid waste by sequencing batch process. Fuel Process Technol 2008;89:485–9. doi:10.1016/j.fuproc.2007.11.013.

[47]

Kayhanian M, Hardy S. The impact of four design parameters on the performance of a highsolids anaerobic digestion of municipal solid waste for fuel gas production. Environ Technol (United Kingdom) 1994;15:557–67. doi:10.1080/09593339409385461.

[48]

Choong YY, Norli I, Zuhairi A, Firdaus M. Impacts of trace element supplementation on the performance of anaerobic digestion process : A critical review. Bioresour Technol 2016;209:369–79. doi:10.1016/j.biortech.2016.03.028.

[49]

Feng XM, Karlsson A, Svensson BH, Bertilsson S. Impact of trace element additionon biogas productionfromfood industrial waste-linking process to microbial communities. FEMS Microbiol Ecol 2010;74:226–40. doi:10.1111/j.1574-6941.2010.00932.x.

[50]

Karlsson A, Einarsson P, Schnürer A, Sundberg C, Ejlertsson J, Svensson BH. Impact of trace element addition on degradation efficiency of volatile fatty acids , oleic acid and phenyl acetate and on microbial populations in a biogas digester. J Biosci Bioeng 2012;114:446–52. doi:10.1016/j.jbiosc.2012.05.010.

[51]

Demirel B, Scherer P. Trace element requirements of agricultural biogas digesters during biological conversion of renewable biomass to methane. Biomass and Bioenergy 2011;35:992–8. doi:10.1016/j.biombioe.2010.12.022.

[52]

Capson-Tojo G, Trably E, Rouez M, Crest M, Bernet N, Steyer JP, et al. Methanosarcina plays a main role during methanogenesis of high-solids food waste and cardboard. Waste Manag 2018;76:423–30. doi:10.1016/j.wasman.2018.04.004.

[53]

Zhang W, Xing W, Li R. Real-time recovery strategies for volatile fatty acid-inhibited anaerobic digestion of food waste for methane production. Bioresour Technol 2018;265:82– 92. doi:10.1016/j.biortech.2018.05.098.

[54]

Banks CJ, Zhang Y, Jiang Y, Heaven S. Trace element requirements for stable food waste digestion at elevated ammonia concentrations. Bioresour Technol 2012;104:127–35. doi:10.1016/j.biortech.2011.10.068.

[55]

Kleyböcker A, Liebrich M, Kasina M, Kraume M, Wittmaier M, Würdemann H. Comparison of different procedures to stabilize biogas formation after process failure in a thermophilic waste digestion system: Influence of aggregate formation on process stability. Waste Manag 2012;32:1122–30. doi:10.1016/j.wasman.2012.01.015.

[56]

De Vrieze J, De Lathouwer L, Verstraete W, Boon N. High-rate iron-rich activated sludge as stabilizing agent for the anaerobic digestion of kitchen waste. Water Res 2013;47:3732–41. doi:10.1016/j.watres.2013.04.020.

Jo

ur

na

lP

re

-p

ro of

[46]

[57]

22

Nghiem LD, Koch K, Bolzonella D, Drewes JE. Full scale co-digestion of wastewater sludge and food waste: Bottlenecks and possibilities. Renew Sustain Energy Rev 2017;72:354–62. doi:10.1016/j.rser.2017.01.062.

Legends to Figures and Tables Figure 1. Comparison of CH4 yield, soluble COD, NH4+-N concentration, and pH for AD and

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AcoD at low OLR (0.8 gVS L-1d-1).

Figure 2. VFAs trend observed during the tests. (a) AD with OLR = 0.8 gVS L-1d-1. (b) AD with OLR = 1.7 gVS L-1d-1. (c) AcoD with OLR = 0.8 gVS L-1d-1. (d) AcoD with OLR = 1.7 gVS L-1d-1.

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Figure 3. Comparison of CH4 yield, soluble COD, NH4+-N concentration, and pH for AD and

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AcoD at high OLR (1.7 gVS L-1d-1).

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Figure 4. FISH/CARD FISH ratio assessed for Bacteria and Archaea on samples taken during the reactors’ operation. (a) AD reactor fed with only FW, OLR = 0.8 gVS L-1d-1. (b) AD reactor fed with only FW, OLR = 1.7 gVS L-1d-1. (c) AcoD reactor fed with FW and WAS, OLR = 0.8 gVS L-

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d . (d) AcoD reactor fed with FW and WAS, OLR = 1.7 gVS L-1d-1.

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1 -1

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Figure 5. Distribution of the relative abundance of bacterial OTUs in anaerobic digesters and co-

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digesters and in WAS, presented at the phylum level.

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Figure 6. Detailed composition of the three main phyla retrieved in all screened samples

(Bacteroidetes, Choloflexi and Firmicutes). Only OTUs with relative abundance ≥ 1% are reported.

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c_, class; o_, order; f_, family.

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ro of -p re lP na ur Jo Figure 7. Archaeal OTUs affiliation and distribution in the screened systems within the Euryarchaeota phylum. Only OTUs with relative abundance ≥ 1% are reported.

28

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Parameters

WAS

4.8 ± 0.4

7.04 ± 0.2

TS (g L )

181.5 ± 14.8

19.9 ± 4.0

VS (g L-1)

172.4 ± 13.2

13.7 ± 2.7

95.0 ± 1.1

69.0 ± 4.0

CODtot (g L )

197.8 ± 32.7

18.5 ± 4.1

CODsol (g L-1)

54.8 ± 6.8

0.049 ± 0.007

CODtot/VS

1.1 ± 0.2

1.35 ± 0.01

CODsol/CODtot (%)

27.9 ± 1.7

0.27 ± 0.03

13 ± 1

6.5 ± 0.3

NH4 -N (g kg TS)

7.7 ± 0.6

0.2 ± 0.01

Ntot (g kg-1TS)

29.8 ± 3.1

49.7 ± 5.3

Ptot (g kg TS)

0.78 ± 0.08

10.4 ± 1.3

Soluble Proteins (%CODtot) Soluble Carbohydrates (%CODtot) BMP** (Nm3CH4 kg-1VSfed)

10 ± 1.5 22 ± 3.9 0.30 ± 0.01

0.20 ± 0.01 0.02 ± 0.001 0.15 ± 0.01

Ca (g kg-1TS)

5.03 ± 0.4 21 ± 1.8

0.5 ± 0.04

15 ± 1.5

39 ± 3.5

16,082 ± 1,577

pH -1

VS/TS (%) -1

C/N* -1

+

-1

-1

Na (g kg TS)

4.97 ± 0.5

-1

-1

Al (g kg TS) -1

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Fe (mg kg TS) Cu (mg kg-1TS) -1

Mg (mg kg TS) -1

-1

Se (mg kg TS) -1

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Co (mg kg TS)

2.6 ± 0.2 10 ± 0.9

6.8 ± 0.9

310 ± 40

20 ± 2.3

3,750 ± 328

0.5 ± 0.04

4.8 ± 0.4

< d.l.***

37 ± 4.1

< d.l.***

3.8 ± 0.4

< d.l.***

7.75 ± 0.7

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Mo (mg kg TS) Ni (mg kg-1TS)

50 ± 4.0

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K (g kg TS)

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FW

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Table 1. Detailed characterization of the substrates.

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* C/N value was estimated considering a Carbon/COD ratio of 0.35 ** Biomethane potential tests carried out at Substrate/Inoculum ratio of 0.5 *** Values below the detection limit

30

Table 2. Operative conditions of the semi-continuous tests. AD -1 -1

OLR (gVS L d ) HRT (d) OLRFW+WAS (gVS L-1d1 )

AcoD

AD

0.8 20 0.8

0.25 + 0.55

1.7

AcoD 1.7 20 1.2 + 0.5

Table 3. Characterization of the feedstocks and digestates of the AD and AcoD tests (Low OLR). OLR = 0.8 gVS L-1d-1 AD

AcoD Co-digestate

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Feed 6.4 ± 0.2 20.0 ± 3.7 15.5 ± 2.8 18.0 ± 2.9 1.6 ± 0.19 5.7 ± 1.6 1.1 ± 0.1 9.1 ± 0.7

12.9 ± 1.4 8.7 ± 0.9 11.7 ± 1.2 0.17 ± 0.03 4.1 ± 0.8 1.0 ± 0.1 50 ± 1.0

50 ± 5

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Feed Digestate pH* 4.5 ± 0.4 TS (g L-1) 17.9 ± 1.4 7.2 ± 0.7 VS (g L-1) 16.9 ± 1.4 5.1 ± 0.7 -1 Total COD (g L ) 19.2 ± 2.9 7.0 ± 1.4 -1 Soluble COD (g L ) 6.2 ± 0.3 2.1 ± 1.2 C/N 9.6 ± 2.9 4.1 ± 1.6 -1 Ntot (g L ) 0.7 ± 0.1 0.6 ± 0.1 sNH4+-N (%Ntot) 10 ± 0.5 42 ± 0.8 VSremoval (%) 71 ± 5 *pH values of digestates and co-digestates are plotted in Fig. 1

Table 4. Characterization of the feedstocks and digestates of the AD and AcoD tests (High OLR). OLR = 1.7 gVS L-1d-1

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AD

Feed 4.7 ± 0.4 37.8 ± 2.5 35.5 ± 3.2 37.6 ± 1.7 9.7 ± 0.9 10.1 ± 2.3 1.3 ± 0.2 10.8 ± 0.4

Digestate

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pH* TS (g L-1) 17.6 ± 3.8 -1 VS (g L ) 10.4 ± 2.0 Total COD (g L-1) 12.8 ± 0.7 -1 Soluble COD (g L ) 11.4 ± 2.4 C/N 3.5 ± 0.4 Ntot (g L-1) 1.3 ± 0.1 + sNH4 -N (% Ntot) 23.0 ± 0.5 VSremoval (%) 76 ± 7 *pH values of digestates and co-digestates are plotted in Fig. 2

31

AcoD Feed 5.9 ± 0.2 36.1 ± 4.0 31.3 ± 3.3 40.8 ± 5.7 8.7 ± 1.3 9.5 ± 2.5 1.5 ± 0.2 13.3 ± 0.8

Co-digestate 14.5 ± 1.2 10.0 ± 0.9 14.6 ± 1.0 0.31 ± 0.04 3.9 ± 0.5 1.3 ± 0.1 56.0 ± 1.1 71 ± 4