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Article

Synergistic Role of Low-Strength Ultrasound and Co-Digestion in Anaerobic Digestion of Swine Wastewater

by
Changgee Lee
,
Jaehun Gwon
,
Min-Sang Kim
,
Taehwan Lee
,
Uijeong Han
,
Yeongmi Park
,
Hongmok Jo
*,† and
Si-Kyung Cho
*,†
Department of Biological and Environmental Science, Dongguk University, 32 Dongguk-ro, Ilsandong-gu, Goyang 10326, Gyeonggi-do, Republic of Korea
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Appl. Sci. 2025, 15(19), 10548; https://doi.org/10.3390/app151910548
Submission received: 5 September 2025 / Revised: 23 September 2025 / Accepted: 26 September 2025 / Published: 29 September 2025
(This article belongs to the Special Issue New Approaches to Water Treatment: Challenges and Trends, 2nd Edition)
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Abstract

Swine manure poses significant challenges for anaerobic digestion due to its low carbon-to-nitrogen (C/N) ratio and elevated ammonia concentrations, both of which restrict methane generation. This study investigated the impact of integrating low-intensity ultrasound with co-digestion of piggery wastewater and food waste leachate. Laboratory-scale upflow anaerobic sludge blanket (UASB) reactors were employed under four operational conditions to evaluate anaerobic digestion performance, track shifts in microbial community structure, and assess the abundance of antibiotic resistance genes (ARGs). Co-digestion significantly enhanced methane production, yielding 1.3–3.2 times more than manure alone, while low-intensity ultrasound further increased methane yields by approximately 36–44% at high loading rates. Moreover, coupling low-intensity ultrasound with co-digestion led to the most rapid recovery following an overloading shock. Unexpectedly, ultrasound treatment alone increased the expression of certain ARGs (tetG, sul1, ermB) and the Integrase gene (intI1), while co-digestion led to a reduction in these genetic markers. These findings clearly indicate that the concurrent application of co-digestion and low-intensity ultrasound achieved the highest methane yield, the fastest recovery after organic overloading, and greater suppression of specific ARGs.

1. Introduction

Due to the rapid expansion of the intensive livestock industry to meet increasing meat demand, the quantity of livestock manure and wastewater has resulted in significant environmental management challenges [1]. In many countries, including South Korea, where ocean disposal of organic waste has been prohibited since 2013, conventional disposal methods have become obsolete; thus, there is an urgent requirement to develop effective land-based treatment technologies for livestock manure and other organic residues [2,3]. Among a wide range of available technologies, anaerobic digestion is attracting considerable interest as it employs various microorganisms to break down organic matter in the absence of oxygen, while concurrently generating valuable biogas [4]. Through anaerobic digestion, the organic fraction of livestock manure can be converted into methane-rich biogas, which serves as a form of renewable energy, providing simultaneous benefits of pollution reduction and resource recovery [5]. As a result, application of AD for agricultural and livestock waste management is being extensively researched worldwide and recognized as a key approach for advancing both environmental protection and energy generation [6].
However, digesting livestock manure as a single substrate faces significant challenges because the intrinsic properties of manure are not ideal. For instance, livestock manure typically exhibits a low C/N ratio, contains relatively small amounts of easily degradable organic matter such as volatile solids, and often has elevated ammonia concentrations. These conditions can suppress microbial activity, resulting in limited methane production and reducing the economic viability of mono-digestion [7,8]. To address these issues, several techniques have been explored. Co-digestion is a widely adopted approach, in which manure is processed alongside additional substrates like food waste leachate to enhance nutrient balance and mitigate inhibitory effects [9,10]. Moreover, engineering solutions such as high-rate anaerobic reactors, notably the UASB and expanded granular sludge blanket (EGSB), have been introduced to facilitate effective microbe–substrate interaction and to increase biomass retention [11,12].
In addition to the issue of low methane production, livestock wastewater presents significant challenges, including the occurrence of antibiotics and the spread of antibiotic resistance genes (ARGs) [13]. In current animal husbandry practices, antibiotics are extensively utilized for both the treatment of disease and for promoting animal growth, and a substantial portion is subsequently excreted without being metabolized [14,15]. Consequently, residues of antibiotics and bacteria carrying ARGs are frequently detected in livestock manure and wastewater [16]. When these materials are released or applied to land with insufficient treatment, they contribute to the dissemination of antibiotic agents and resistant microorganisms in natural environments, raising the risk of developing multi-antibiotic-resistant “superbugs” [17]. The propagation of resistance in these settings is largely facilitated by horizontal gene transfer (HGT), which allows susceptible bacteria to acquire resistance properties [18]. Despite a growing recognition of this concern, available treatment systems generally lack targeted capabilities for removing antibiotics or ARGs [19]. In particular, some existing biological treatment strategies may unintentionally favor the selection of resistance; for example, the presence of antibiotics in activated sludge can promote the selective proliferation of resistant bacteria [20]. These enriched populations of resistant bacteria can persist through, and be further dispersed by, downstream processes such as anaerobic digestion and composting [21].
Recently, low-intensity ultrasound has gained attention as an auxiliary method to improve AD performance, offering potential advantages not only in methane production but also in suppressing antibiotic resistance genes (ARGs) [22]. In contrast to high-power ultrasound, which is usually utilized as a pretreatment step for substrate disintegration before digestion, low-intensity ultrasound is applied directly within the digester and operates via mechanisms like cavitation and free radical generation [23]. Additionally, emerging evidence shows that integrating low-frequency ultrasound with antimicrobial agents can compromise biofilm integrity and promote greater antibiotic penetration [24]. If used at suitable intensities, these mechanisms can initiate microcracks on the surfaces of microbial cells or granular sludge aggregates, which enhances substrate diffusion, increases the transfer of nutrients and metabolites, and stimulates overall microbial function [25]. Prior research confirmed its efficacy: exposing samples to ultrasound at 0.2 W/cm2 for 2.5 min led to an over eightfold increase in methane yield, and extending treatment to 30 min at 0.3 W/cm2 elevated the efficiency of organic matter removal by 10–20% [26]. Likewise, applying 0.2 W/cm2 for 10 min improved organic matter removal by approximately 30% [27]. The enhancements have been linked to increased membrane permeability, greater intercellular mass transfer, and the activation of hydrolytic enzymes, all supporting elevated methane productivity. Nevertheless, intensities above 0.05 W/cm2 combined with exposure times longer than 10 min have been found to impair microbial function, indicating the necessity to optimize operational parameters [28]. Overall, the body of evidence indicates that low-intensity ultrasound has the potential to simultaneously improve the biodegradation of organic substrates and reduce the persistence of ARGs during anaerobic digestion.
Therefore, in this study, we aimed to develop an innovative approach for swine wastewater treatment by integrating multiple methods. A UASB anaerobic digester was employed, and low-intensity ultrasound was directly applied within the reactor. Additionally, co-digestion with food waste leachate was implemented to help balance nutrients. This strategy was expected to stimulate microbial activity in the reactor and enhance methane production compared to traditional digestion methods. In addition, we conducted a characterization of the microbial community and monitored variations in key antibiotic resistance genes under varying operational conditions. The scientific aim of this work was to elucidate how low-intensity ultrasound and co-digestion synergistically influence microbial community dynamics, metabolic pathways, and antibiotic resistance gene dissemination during anaerobic digestion. The practical aim was to develop and validate a scalable strategy that improves renewable energy recovery and reduces environmental risks in real-world livestock wastewater management. Through these investigations, this study seeks to demonstrate that low-intensity ultrasound coupled with co-digestion not only improves renewable energy recovery from livestock wastewater but also provides fundamental knowledge to guide the design of full-scale anaerobic digesters with lower antibiotic-resistance risk.

2. Materials and Methods

2.1. Reactor Setup and Operation Conditions

The substrates used in this study were obtained from local facilities. Piggery wastewater (PW) was collected from a swine farm located in Buyeo, Korea, and food waste leachate (FWL) was obtained from a municipal food waste treatment facility in Goyang, Korea. In this study, FWL was used after removal of solid fraction to allow stable substrate feeding and consistent operation of the anaerobic reactors. The characteristics of the piggery wastewater (PW) and food waste leachate (FWL) are presented in Table 1. Both substrates were stored at 4 °C prior to use in order to minimize biological activity and compositional changes. Granular sludge, which served as inoculum, was obtained from a full-scale anaerobic digester treating brewery effluent. 1 L of granular sludge was introduced into each reactor at the commencement of the experiments, resulting in an effective working volume of 3.1 L per reactor.
The experimental setup included four laboratory-scale Upflow Anaerobic Sludge Blanket (UASB) reactors operated in parallel with differing treatments (Figure 1). All reactors had a diameter of 70 mm, a height of 930 mm, and a combined vessel volume of 3.8 L. The main reactors were constructed of acrylic, though ultrasound-equipped reactors used stainless steel to mitigate vessel damage. Ultrasonic probe tips were installed at 70 mm intervals on the reactor wall, and five sampling ports were positioned every 170 mm for scheduled sludge sampling. The ultrasound was delivered at a power of 0.1 W/mL in 1 s bursts every 60 s, as previously applied in studies on low- intensity ultrasonication for anaerobic digestion [28].
Four operational modes were evaluated: a control reactor without ultrasound or co-substrate (C), a reactor operated with ultrasound alone (U), a co-digestion reactor fed with PW and FWL at a 1:1 ratio (Co-C), and a reactor integrating both ultrasound and co-digestion (Co-U). The reactors operated at 38 °C within a temperature-controlled incubator. Substrate feeds were continuously dosed from a refrigerated storage tank (50 L, held at 4 °C) via a peristaltic pump (MasterFlex L/S, Cole-Parmer, Vernon Hills, IL, USA), ensuring steady upflow feeding.
Reactor operation was organized into successive phases as depicted in Table 2. The start-up involved a brief acclimation period using glucose to reactivate microbial communities in the inoculum. Following this step, reactors proceeded at a constant hydraulic retention time (HRT) of 2 days, with the organic loading rates (OLRs) systematically increased across sequential phases. Process stability was further assessed through a shock loading test involving a sudden doubling of the OLR, succeeded by a recovery phase. To maintain pH control, sodium bicarbonate (3 g/L) was dosed as a buffer, and a trace element solution supplied essential micronutrients. Additional characterization of the substrates and seed sludge is available in Figure S1 and Tables S1 and S2 [29].

2.2. Analytical Methods

Biogas production was quantified using the water displacement method and standardized to standard temperature and pressure (STP) conditions. The methane and carbon dioxide concentrations in the biogas were determined using a gas chromatograph (Gow-Mac Series 580, Gow-Mac Instrument Company, Bethlehem, PA, USA) equipped with a Hayesep Q column and employing high-purity nitrogen as the carrier gas.
Volatile fatty acids (VFAs), including acetate, lactate, propionate, and butyrate, were analyzed using high-performance liquid chromatography (HPLC, Shimadzu LC-20A, Shimadzu Corporation, Kyoto, Japan) with UV detection at 210 nm and a Bio-Rad Fast Acid Analysis column (Bio-Rad, Hercules, CA, USA); 0.005 M H2SO4 served as the mobile phase. Prior to analysis, effluent samples were filtered using 0.45 μm syringe filters.
All physicochemical parameters were determined following the Standard Methods for the Examination of Water and Wastewater (APHA, AWWA, WEF, 2017). The chemical oxygen demand (COD) of both influent and effluent was measured using commercial digestion kits, whereas total solids (TS), volatile solids (VS), and volatile suspended solids (VSS) were quantified gravimetrically by drying at 105 °C followed by incineration at 550 °C.

2.3. Microbial and Genetic Analysis

Sludge samples were collected from each reactor at the end of every operational phase, prior to transitioning to the next phase. As four reactors were operated over five phases, a total of 20 DNA samples were obtained, and including the initial seed sludge, 21 DNA samples were analyzed for microbial and genetic assessments. DNA was isolated from approximately 1 g of sludge utilizing the DNeasy PowerSoil Kit (Qiagen, Hilden, Germany), strictly adhering to the manufacturer’s instructions. To maximize nucleic acid yield, samples underwent homogenization with a sterile pestle before extraction. The purity and concentrations of DNA and cDNA were assessed using a Multiskan Go spectrophotometer (Thermo Scientific, Waltham, MA, USA), and all samples were preserved at –80 °C until further analysis.
Microbial community composition was assessed by polymerase chain reaction (PCR) amplification and sequencing of hypervariable regions of the 16S rRNA gene. Specifically, the V3–V4 region was amplified for Bacteria using primers 518F/805R, whereas the V4–V5 region was targeted for Archaea with primers 787F/1059R. Sequencing was performed on an Illumina iSeq 100 system (Illumina Inc., San Diego, CA, USA) with Nextera XT indices. Low-quality sequence reads (<150 bp) and chimeric sequences were excluded; the remaining high-quality reads (>200 bp) were subsequently clustered into operational taxonomic units (OTUs) at a 97% sequence similarity threshold. Each OTU’s representative sequence was identified taxonomically through the SILVA 16S rRNA database (version 138), enabling robust characterization and cross-comparison of bacterial and archaeal communities across varying operational conditions.
Quantitative PCR (qPCR) analysis was employed to quantify the relative abundances of functional and antibiotic resistance genes (ARGs). Real-time qPCR reactions utilized the SYBR Green Real-time PCR Master Mix (Toyobo, Osaka, Japan) on a Bio-Rad CFX Connect™ platform (Bio-Rad Laboratories, Hercules, CA, USA). The selected target genes included: tetG (tetracycline resistance), sul1 (sulfonamide resistance), ermB (macrolide resistance) for ARGs; intI1 (class 1 integron integrase); mcrA (methyl coenzyme M reductase, a key enzyme in methanogenesis); and universal 16S rDNA as a bacterial marker [30,31,32,33,34,35]. These ARGs were selected because they are among the most frequently reported in livestock wastewater [36]. Table S3 provides detailed primer sequences. Each sample was amplified in triplicate, incorporating no-template controls to monitor contamination.
Thermal cycling parameters included an initial denaturation at 95 °C for 3 min, followed by 40 cycles consisting of denaturation at 95 °C for 30 s, annealing for 30 s at primer-specific temperatures, and an extension at 72 °C for 10 s. After amplification, a final extension was conducted at 72 °C for 5 min, and melting curve analysis was used to validate amplification specificity. Gene abundances were determined by the comparative Ct method (2−ΔΔCt) with 16S rDNA serving as the reference, facilitating the assessment of relative variations in microbial community markers and ARGs throughout different operational stages and treatments [37].

2.4. Statistical Analysis

All statistical analyses were performed in the R software environment (version 4.4.0). The packages dplyr and readr were used for data handling, and the Hmisc package was applied to calculate Pearson correlation coefficients and corresponding p-values. Statistical significance was considered at p < 0.05. All qPCR assays were conducted in triplicate, and values are expressed as mean ± standard error (SE). Error bars in the figures represent SE of the triplicate measurements.

3. Results and Discussion

3.1. Anaerobic Digestion Performance

Across the sequential loading phases (Phases 1–3), the system combining co-digestion and ultrasound (Co-U) produced the highest methane yields, followed by co-digestion without ultrasound (Co-C), ultrasound treatment alone (U), and lastly the control (C) (Figure 2). Co-digestion produced 1.3–3.2 times more methane than mono-digestion at equivalent COD input, primarily due to improved nutrient balance and substrate degradability [38,39]. These observations are in line with findings by Neves et al., who also documented increased biogas output when manure was co-processed with additional nutrient-rich materials [40]. Under maximum sustained OLR conditions (Phase 3), ultrasound treatment increased methane yields by 36–44% compared to untreated controls, consistent with prior reports of ~40% improvement under similar low-intensity sonication conditions [28]. Notably, the methane content in biogas consistently ranged from 60–70% across all reactors under stable operating conditions, demonstrating robust methanogenic performance despite increasing feed rates.
When the digester loading was doubled to 6 g COD/L·day for two days to assess shock resistance, the reactors responded with differing levels of operational stability. The PW-only control exhibited a marked decline in performance, characterized by reduced gas output and a methane conversion efficiency that dropped below 20%. In comparison, the co-digestion reactors exhibited a significantly better capacity to handle the abrupt loading increase. These reactors showed an increase in biogas production that corresponded with the higher feed input, while their methane conversion efficiency remained stable at about 50%, consistent with values observed in conventional glucose-fed digesters. All ultrasound-assisted reactors outperformed those not receiving ultrasound under shock loading. For instance, during the shock test, the Co-U reactor generated approximately 10.2 L of biogas containing around 79% methane, whereas the PW-only control produced just about 3.5 L with 73% CH4. The enhanced shock tolerance observed in co-digestion setups can be ascribed to the effective buffering provided by swine manure. Both mono-digestion reactors (C and U) sustained pH values within 7.8–8.0, while the co-digestion reactors exhibited only minor pH variations due to increased volatile fatty acid (VFA) release from food waste; nevertheless, pH was maintained at an adequate level (7.5–7.7) because of manure’s inherent alkalinity (Figure S2). VFA analysis indicated that effluent pH in all four reactors remained within the optimal range, but the U reactor showed a continual increase in VFA concentrations under higher OLR, reaching up to 480 mg/L, whereas co-digestion reactors sustained levels below 100 mg/L (Figure S3). Analysis of primary VFAs commonly present during anaerobic digestion revealed that lactic and propionic acids were predominant, with butyric acid not detected. Although propionic acid concentrations tend to rise with increasing organic loading, they typically remain below thresholds considered inhibitory, generally not exceeding 600–800 mg/L in manure-based digestion processes [41]. As a result, co-digestion effectively mitigated VFA accumulation due to the strong buffering effect of manure, and the application of low-intensity ultrasound further minimized VFA content [42], thereby supporting stable microbial activity and maintaining process stability during organic shocks.
During recovery phase (2 g COD of glucose/L·day), Co-U restored methane production fastest, followed by Co-C, U, and control reactors. In terms of COD conversion efficiency, Co-U almost fully recovered, reaching a peak methane conversion efficiency of approximately 97.9% of input COD to CH4, compared to around 80.9% for Co-C. The ultrasound-only reactor also achieved a conversion rate of roughly 64.8%, which was substantially greater than that of the control during its recovery. Notably, methane generation in Co-U during recovery (5.05 L) significantly surpassed the theoretical yield anticipated from the daily OLR of 2 g COD/L (≈0.7 L CH4/L). This result underscores the synergistic advantage of combining co-digestion with ultrasound. It should be noted, however, that glucose was used as the recovery substrate to facilitate rapid microbial reactivation, and thus the recovery behavior observed here may not fully represent real piggery wastewater conditions. Further studies with PW–FWL mixtures under shock and recovery scenarios are needed to confirm long-term applicability.
Methane yield, quantified as liters of CH4 produced per gram of COD removed, was also evaluated in all reactors (Table S4). In the initial stage (Phase 1), Co-U achieved the highest yield, reaching 0.26 L/g CODremoved. As the OLR was elevated, methane yield in the U reactor increased accordingly, peaking at 0.36 L/g CODremoved. For reference, earlier studies reported methane yields of 0.28–0.35 L/g CODremoved from full-scale anaerobic digesters integrated into wastewater treatment systems [43], whereas PW-only digesters generally achieve 0.17–0.30 L/g CODremoved. These results suggest that low-intensity ultrasound clearly enhances methane yield beyond what is typically observed in livestock wastewater digestion processes.
Trends in COD removal and methane conversion efficiency mirrored the patterns observed in methane production (Figure 3 and Table S5). Methane conversion efficiency was calculated as the percentage of input COD converted to methane (% COD to CH4). It is important to recognize that a portion of COD removal supported microbial growth and maintenance rather than direct methane generation, which is characteristic of anaerobic digestion systems. The co-digestion of manure with food waste markedly increased the fraction of COD converted to methane. Under stable conditions, Co-C achieved the highest COD-to-CH4 conversion (64–84% with increasing OLR), exceeding the 71% previously reported for synthetic glucose-fed systems despite using complex substrates and a short 2-day HRT [44]. By contrast, the manure-only control showed minimal gains in conversion efficiency with increasing OLR, exhibiting only a 4–7% increase from mid to high load, which reflects a fundamental limitation of single-substrate digestion. In the co-digestion reactors, each stepwise increase in loading resulted, on average, in a 9% improvement in conversion efficiency, demonstrating the mixed substrate’s distinct ability to facilitate additional COD removal as loading was intensified.
Under shock loading, COD conversion efficiency decreased across all reactors, with a significantly greater reduction observed in the control reactor. The control’s COD-to-methane conversion rate remained below 20%, indicating significant VFA accumulation and the persistence of undegraded COD. In the co-digestion configurations, conversion efficiency declined to 50%, indicating that approximately half of the surplus COD introduced was still converted to methane. This capacity to maintain COD conversion aligns with previous findings regarding system buffering and demonstrates that co-digestion can alleviate major disturbances to microbial activity during periods of overloading. During the subsequent recovery phase, Co-U showed a prompt restoration of methane yield, although the unusually high COD conversion observed likely resulted from transient substrate dynamics rather than stable operational conditions. The nearly maximal observed conversion likely resulted from the delayed breakdown of VFAs that had accumulated earlier, once the process environment stabilized. It is also important to note that glucose—a substrate with high biodegradability and fermentation efficiency—was used during this recovery period. Therefore, the exceptionally high conversion efficiency (≈98%) detected in Co-U reflects not only the resilience of the system but also the advantageous properties of the recovery substrate. To assess whether such high conversion rates can be routinely achieved under real-world operational conditions with PW-FWL mixtures, additional investigation is necessary. Furthermore, exploring the effects of consecutive or prolonged OLR shock events is required to thoroughly assess the long-term stability and efficacy of co-digestion and ultrasound as recovery-promoting interventions.

3.2. Microbial Community Dynamics

Bacterial communities were dominated by Firmicutes and Bacteroidetes, with Proteobacteria increasing at higher OLR in PW-only reactors, whereas co-digestion favored Acidobacteria and Actinobacteria (Figure 4). Over the course of the experiment, Firmicutes remained prevalent, while Proteobacteria increased in proportion, particularly in piggery wastewater-only reactors at elevated organic loading rates. By the end of the process, C and U reactors exhibited higher levels of Proteobacteria, whereas Co-C and Co-U demonstrated increased proportions of Acidobacteria and Actinobacteria. These observations suggest that incorporating food waste leachate expanded substrate diversity and promoted a richer microbial community structure.
At the class level, Bacteroidia dominated all reactors, underscoring its primary function in fermenting complex organic substrates (Figure S4). Clostridia was also prevalent, and its relative abundance was elevated in reactors subjected to ultrasound compared to untreated controls. Co-digestion promoted the enrichment of typically less abundant classes such as Synergistia and Aminicenantia, while reactors processing only piggery wastewater at high loading rates showed higher levels of Gammaproteobacteria and Deltaproteobacteria. In co-digesters, Negativicutes abundance varied with organic loading, whereas Spirochaetia declined in all systems as digestion progressed.
Bacteroidales was the dominant order in every reactor studied (Figure S5). The prevalence of minor orders changed in response to treatment conditions. PW-only reactors at higher organic loading rates showed increased levels of Clostridiales, Sphingobacteriales, and an uncultured Clostridia group (DTU014), all linked to the breakdown of fibrous and proteinaceous manure. In contrast, co-digestion reactors supported a greater presence of Aminicenantales and Selenomonadales, reflecting the establishment of ecological niches favoring the fermentation of sugars and amino acids originating from food waste.
Parabacteroides proliferated in co-digestion reactors (Figure S7), stimulated by the presence of easily degradable organics, and are recognized acidogenic bacteria that produce acetate as their major metabolic end product [45]. Prevotella, Christensenellaceae, and Succiniclasticum also increased in abundance; all are acidogenic taxa involved in the rapid conversion of carbohydrates to acids, without participating directly in hydrolysis [46,47]. By continuously metabolizing intermediate hydrolysis products into readily fermentable acids, these taxa help explain the greater methane yields and faster shock recovery observed in Co-U and Co-C.
In reactors lacking co-digestion, microorganisms capable of metabolizing persistently resistant compounds became more prevalent. Comamonas and Pseudomonas increased in prominence, indicative of ecological roles in decomposing residual fermentation products, such as long-chain fatty acids and aromatic substances. In the ultrasound-treated reactor (U), these genera were less abundant relative to the non-sonicated control, signifying that ultrasound modified their ecological roles or supported the expansion of other competing taxa.
Syntrophic bacteria, which form cooperative interactions with methanogens, were also influenced by the substrate composition. Co-digestion reactors had a higher abundance of Syntrophorhabdus, which is involved in the degradation of benzoate and other aromatic compounds, while pig-only reactors exhibited greater populations of Syntrophus and Syntrophomonas, both of which oxidize long-chain fatty acids and mediate the conversion of intermediates such as propionate and butyrate into acetate and hydrogen [48,49]. The higher prevalence of syntrophs in PW only reactors signifies more substantial accumulation of long-chain fatty acids and their intermediates, whereas co-digestion is associated with reduced accumulation and a greater dominance of Syntrophorhabdus. In summary, co-digestion broadened the metabolic network, whereas PW-only digestion relied more on organisms adapted to degrade refractory components of manure. The application of ultrasound treatment further stimulated fermentative groups such as Clostridia, leading to improved overall process performance. This microbial enrichment pattern also explains the lower VFA accumulation (<100 mg/L) and stable pH observed in co-digestion reactors, which supported higher methane conversion and resilience against shock loading.
Archaeal communities were composed of Methanomicrobia and Methanobacteria (Figure S8). As digestion progressed, Methanomicrobia and Methanobacteria became the dominant groups. PW-only reactors featured a higher proportion of Methanomicrobia, whereas co-digestion reactors showed increased abundances of Methanobacteria. These results suggest that the addition of food waste promoted hydrogenotrophic Methanobacteria, while pig manure favored the proliferation of acetoclastic Methanomicrobia.
At the order level, Methanobacteriales, which function as strict hydrogenotrophs, were initially the most prevalent (Figure S9). With elevated organic loading, Methanosarcinales, including Methanosarcina, became increasingly abundant, particularly in PW-only reactors. By the conclusion of the experiment, C and U reactors were mostly populated by Methanosarcinales, whereas co-digestion reactors retained higher abundances of Methanobacteriales. These findings imply that co-digestion sustained hydrogenotrophic methanogenesis, while PW-only digestion supported more acetoclastic and methylotrophic methanogenic pathways.
At the genus level, the observed community dynamics illustrated the changes in methanogenic pathways (Figure 5). Methanobrevibacter and Methanosarcina declined in C and U reactors, whereas Methanobacterium and Methanolinea showed substantial increases across all reactors, highlighting hydrogenotrophic methanogenesis as the dominant pathway.
This conclusion is supported by the elevated ammonia concentrations and the significant presence of hydrogen produced through syntrophic metabolism. Methanosarcina maintained a comparatively elevated abundance in reactors subjected to ultrasound and in co-digestion systems, which aligns with increased acetate levels, while Methanosaeta typically functions as an acetate-dependent methanogen [50]. Ultrasound treatment likely enhanced the growth of Methanosarcina by facilitating mass transfer and promoting closer contact between syntrophic partners. These results are consistent with the observed increase in acetate concentrations under ultrasound treatment and with the enrichment of syntrophic bacteria involved in the conversion of VFAs to acetate and hydrogen. These conditions likely created a favorable environment for Methanosarcina, which can flexibly utilize acetate and hydrogen, thereby reinforcing syntrophic interactions within the reactor [51,52].
Additional methanogenic taxa were supported exclusively in co-digestion reactors. Hydrogenotrophic methanogens remained prevalent under co-digestion, aligning with higher CH4 conversion and recovery. Methanospirillum and Methanosphaera emerged at appreciable levels in conjunction with Methanobrevibacter. Methanospirillum utilizes hydrogen as an energy source, and Methanosphaera metabolizes methanol in the presence of hydrogen, suggesting that food waste addition provided methanol or other methylated compounds as well as trace nutrients [53]. These genera were not detected in pig-only reactors. The greater archaeal diversity observed in co-digestion systems may have contributed to improved process stability, as multiple methanogens offer metabolic flexibility in response to substrate fluctuations. The influence of ultrasound on archaeal communities was modest, though it tended to favor Methanosarcina and potentially Methanospirillum by enhancing syntrophic associations.

3.3. Antibiotic Resistance Genes (ARGs) and mcrA Gene

Antibiotic resistance genes were measured using quantitative real-time PCR, and the relative abundance of each gene was determined using the comparative 2−ΔΔCt method. Results are expressed as mean relative abundance values along with standard error, as shown in Figure 6. In the U reactor, which was fed PW and subjected to low-intensity ultrasound, all three target genes exhibited increased abundance compared with the PW-only control reactor. Specifically, the relative abundance values under ultrasound treatment reached approximately 1.98 ± 0.05 for tetG, 4.08 ± 0.16 for sul1, and 4.98 ± 0.38 for ermB.
This outcome was contrary to our initial expectation. While ultrasound is often hypothesized to damage cell membranes and reduce resistant populations, several studies have shown that low-intensity ultrasound can instead enhance microbial activity and promote horizontal gene transfer. For instance, Ikeda-Dantsuji et al. reported that ultrasound exposure increased survival and metabolic activity of Chlamydia, and Yu et al. demonstrated that low-intensity ultrasound could reactivate dormant antibiotic-tolerant bacteria [53,54]. In our reactors, the enhanced mass transfer and periodic cell stimulation may have increased opportunities for conjugation and integron-mediated gene exchange, explaining the observed rise in tetG and sul1 alongside intI1. Therefore, the increase in ARG abundance under ultrasound treatment is consistent with stimulated horizontal gene transfer rather than selective growth of resistant taxa.
When co-digestion of PW and FWL was implemented, gene-specific responses exhibited distinct patterns. tetG did not display a consistent change in expression, regardless of ultrasound application. sul1 was substantially suppressed in the co-digestion reactors both in the presence and absence of ultrasound, maintaining relative abundance below 0.05. This result suggests nearly complete removal of sulfonamide resistance genes through co-digestion. This finding aligns with the study by Zhang et al., which showed that co-digesting manure and straw at a one-to-one ratio for more than ninety days led to a drop in sul1 abundance by more than 1.0 log unit [55]. Conversely, ermB consistently showed increased expression, yet its abundance was somewhat lower in the co-digester that received ultrasound compared to the control co-digester. However, as only a limited set of representative ARGs was analyzed, broader surveys including additional resistance markers will be required to generalize these findings.
We also examined the gene intI1, which encodes the class I integron integrase and functions as a marker for horizontal gene transfer. In the U reactor, intI1 expression showed a continuous increase, reaching approximately 5.07 with a standard error of 0.22 during the recovery stage. Conversely, intI1 expression in the co-digestion reactors declined over time. Correlation analysis demonstrated a significant positive relationship between intI1 and both tetG and sul1. The Pearson correlation coefficients were 0.82 for tetG (p < 0.01) and 0.89 for sul1 (p < 0.01). No correlation was found between intI1 and ermB. Zhang et al. also indicated that during co-digestion, changes in microbial communities alongside direct degradation of antibiotics under anaerobic conditions may influence ARG behavior [56]. This aligns with the conclusion that class I integrons facilitate the horizontal transfer of selected ARGs but not all. The results of this study, together with prior works, suggest that the observed increase in tetG and sul1 primarily resulted from integron-mediated horizontal gene transfer, rather than from expansion of host microbial populations. Supporting this interpretation, bacterial phyla such as Firmicutes and Bacteroidetes, recognized hosts of ARGs [57], displayed no significant variation in abundance under ultrasound treatment. This indicates that the elevated ARG levels under ultrasound were not due to shifts in host taxa abundance but rather to increased gene mobility, reinforcing the importance of horizontal gene transfer in ARG dissemination.
The mcrA gene encodes the alpha subunit of methyl-coenzyme M reductase, the enzyme responsible for catalyzing the terminal step of methanogenesis and present in all methanogenic archaea. Thus, mcrA has become widely used as a biomarker to evaluate both the population and functional activity of methanogens. Prior studies confirmed a robust association between enhanced mcrA expression and increased methane generation in anaerobic digestion processes [58].
In our study, mcrA expression in the U reactor remained relatively constant, presenting no substantial variation under different operational settings. In contrast, both the control and ultrasound-treated co-digestion reactors demonstrated increased mcrA expression with rising organic loading rates. When a loading shock occurred, the relative mcrA expression was around 4.30 ± 0.85 in the control co-digester and 4.16 ± 0.01 in the Co-U reactor. Notably, the ultrasound-treated reactor generally exhibited higher mcrA levels, while the control reactor displayed greater fluctuations.
The pattern of mcrA expression corresponded to the progressive enhancement in methane production. Correlation analysis demonstrated that elevated mcrA levels were positively linked to methane yields in both co-digestion reactors. The Pearson correlation coefficient reached 0.78 (p < 0.05) [59], which is somewhat lower compared to earlier research that reported a strong linear association (R2 > 0.87) between mcrA transcript levels and methane production rates. This reduced coefficient may indicate increased variability due to the PW substrate, characterized by limited biodegradability and elevated COD, posing challenges for stable correlations. Nonetheless, this study’s findings further support that mcrA is significantly and positively associated with methane yield, reinforcing its value as a biomarker of methanogen activity and methane generation.

4. Conclusions

This study demonstrated that co-digesting food waste leachate with low-intensity ultrasound significantly enhances the treatment efficiency and operational stability of UASB reactors treating swine wastewater. Co-digestion increased methane production by 1.3–3.2 times compared to mono-digestion, while ultrasound further improved methane yields by 36–44% under high organic loading rates. During shock loading, the Co-U reactor produced about 10.2 L of biogas containing approximately 79% CH4, whereas the control yielded only 3.5 L with 73% CH4. In the recovery phase, Co-U rapidly restored methane conversion efficiency up to 97.9% of input COD, markedly higher than other treatments. Analysis of antibiotic resistance genes (ARGs) revealed that ultrasound alone increased the abundances of tetG, sul1, ermB, and intI1, whereas co-digestion substantially suppressed sul1 and reduced intI1, although other ARGs (tetG and ermB) were not consistently reduced. These gene-specific responses indicate that co-digestion contributed to reducing the persistence and mobility of certain ARGs, while ultrasound alone may promote their dissemination. Collectively, these findings indicate that the concurrent application of co-digestion and ultrasound (Co-U) not only achieved the highest methane yield and fastest recovery but also helped suppress selected ARGs, providing a practical and effective approach for sustainable livestock wastewater management. Although this study was conducted at the laboratory scale, the combined strategy of co-digestion and low-intensity ultrasound could be feasibly adapted to pilot or full-scale anaerobic digestion systems. Future work will also evaluate the economic feasibility by comparing the energy cost of ultrasound application with the additional energy recovered from methane, thereby offering practical potential for livestock wastewater management.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/app151910548/s1, Figure S1: Methane gas conversion rate; Figure S2: pH of each reactor; Figure S3: VFA concentration and composition; Figure S4: Bacterial communities at the class level; Figure S5: Bacterial communities at the order level; Figure S6: Bacterial communities at the family level; Figure S7: Bacterial communities at the genus level; Figure S8: Archaeal communities at the class level; Figure S9: Archaeal communities at the order level; Figure S10: Archaeal communities at the family level; Table S1: Initial characteristics of seed sludge; Table S2: Composition of trace element; Table S3: Primers of antibiotic resistance genes (ARGs) and functional genes during Anaerobic digestion; Table S4: Average biogas production, methane yield and content; Table S5: Mass balance and recovery rate of COD.

Author Contributions

Investigation, C.L., M.-S.K., T.L. and H.J.; Methodology and Formal analysis, J.G., U.H. and Y.P.; Writing—original draft, C.L. and H.J.; Writing—review and editing, H.J. and S.-K.C. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (RS-2024-00454869).

Informed Consent Statement

Not applicable.

Data Availability Statement

The original data supporting the findings of this study are included within the article. Additional requests for information should be addressed to the corresponding authors.

Conflicts of Interest

The authors declare that there are no conflicts of interest related to this work.

Abbreviations

The following abbreviations are used in this manuscript:
ARGsAntibiotic resistance genes
C/N ratioCarbon to nitrogen ratio
CODChemical oxygen demand
EGSBExpanded granular sludge blanket
FWLFood waste leachate
GCGas chromatography
HGTHorizontal gene transfer
HPLCHigh performance liquid chromatography
HRTHydraulic retention time
OLROrganic loading rate
CControl reactor
UUltrasound-only reactor
Co-CCo-digestion control reactor
Co-UCo-digestion with ultrasound reactor
OTUOperational taxonomic unit
PCRPolymerase chain reaction
PWPiggery wastewater
qPCRQuantitative polymerase chain reaction
STPStandard temperature and pressure
TSTotal solids
UASBUpflow anaerobic sludge blanket
VFAsVolatile fatty acids
VSVolatile solids
VSSVolatile suspended solids

References

  1. van der Laan, S.; Breeman, G.; Scherer, L. Animal Lives Affected by Meat Consumption Trends in the G20 Countries. Animals 2024, 14, 1662. [Google Scholar] [CrossRef]
  2. Ahn, Y.; Lee, W.; Kang, S.; Kim, S.-H. Enhancement of Sewage Sludge Digestion by Co-Digestion with Food Waste and Swine Waste. Waste Biomass Valorization 2020, 11, 2421–2430. [Google Scholar] [CrossRef]
  3. Kim, C.-J.; Chung, C.S.; Shin, K.-H.; Choi, K.-Y. The Republic of Korea’s Experience with an Ocean Dumping Management System to Enhance Compliance with the London Protocol: Highlights of Major Institutional History over 40 Years. Front. Mar. Sci. 2023, 10, 1282490. [Google Scholar] [CrossRef]
  4. Mao, C.; Feng, Y.; Wang, X.; Ren, G. Review on Research Achievements of Biogas from Anaerobic Digestion. Renew. Sustain. Energy Rev. 2015, 45, 540–555. [Google Scholar] [CrossRef]
  5. Nguyen, D.D.; Yeop, J.S.; Choi, J.; Kim, S.; Chang, S.W.; Jeon, B.-H.; Guo, W.; Ngo, H.H. A New Approach for Concurrently Improving Performance of South Korean Food Waste Valorization and Renewable Energy Recovery via Dry Anaerobic Digestion under Mesophilic and Thermophilic Conditions. Waste Manag. 2017, 66, 161–168. [Google Scholar] [CrossRef]
  6. Rekleitis, G.; Haralambous, K.-J.; Loizidou, M.; Aravossis, K. Utilization of Agricultural and Livestock Waste in Anaerobic Digestion (AD): Applying the Biorefinery Concept in a Circular Economy. Energies 2020, 13, 4428. [Google Scholar] [CrossRef]
  7. Wang, X.; Yang, G.; Feng, Y.; Ren, G.; Han, X. Optimizing Feeding Composition and Carbon–Nitrogen Ratios for Improved Methane Yield during Anaerobic Co-Digestion of Dairy, Chicken Manure and Wheat Straw. Bioresour. Technol. 2012, 120, 78–83. [Google Scholar] [CrossRef] [PubMed]
  8. Rajagopal, R.; Massé, D.I.; Singh, G. A Critical Review on Inhibition of Anaerobic Digestion Process by Excess Ammonia. Bioresour. Technol. 2013, 143, 632–641. [Google Scholar] [CrossRef]
  9. Zhang, C.; Xiao, G.; Peng, L.; Su, H.; Tan, T. The Anaerobic Co-Digestion of Food Waste and Cattle Manure. Bioresour. Technol. 2013, 129, 170–176. [Google Scholar] [CrossRef]
  10. Zhu, J.; Wu, S.; Shen, J. Anaerobic Co-Digestion of Poultry Litter and Wheat Straw Affected by Solids Composition, Free Ammonia and Carbon/Nitrogen Ratio. J. Environ. Sci. Health Part A 2019, 54, 231–237. [Google Scholar] [CrossRef]
  11. Kato, M.T.; Field, J.A.; Lettinga, G. The Anaerobic Treatment of Low Strength Wastewaters in UASB and EGSB Reactors. Water Sci. Technol. 1997, 36, 375–382. [Google Scholar] [CrossRef]
  12. Anijiofor Sandra, C.; Jamil, N.A.M.; Jabbar, S.; Sakyat, S.; Gomes, C. Aerobic and Anaerobic Sewage Biodegradable Processes: The Gap Analysis. Int. J. Res. Environ. Sci. 2017, 3, 9–19. [Google Scholar] [CrossRef]
  13. He, Y.; Yuan, Q.; Mathieu, J.; Stadler, L.; Senehi, N.; Sun, R.; Alvarez, P.J. Antibiotic Resistance Genes from Livestock Waste: Occurrence, Dissemination, and Treatment. NPJ Clean. Water 2020, 3, 4. [Google Scholar] [CrossRef]
  14. Gaskins, H.; Collier, C.; Anderson, D. Antibiotics as Growth Promotants: Mode of Action. Anim. Biotechnol. 2002, 13, 29–42. [Google Scholar] [CrossRef]
  15. Brown, K.; Uwiera, R.R.; Kalmokoff, M.L.; Brooks, S.P.; Inglis, G.D. Antimicrobial Growth Promoter Use in Livestock: A Requirement to Understand Their Modes of Action to Develop Effective Alternatives. Int. J. Antimicrob. Agents 2017, 49, 12–24. [Google Scholar] [CrossRef]
  16. Wang, L.; Wang, J.; Wang, J.; Zhu, L.; Yang, L.; Yang, R. Distribution Characteristics of Antibiotic Resistant Bacteria and Genes in Fresh and Composted Manures of Livestock Farms. Sci. Total Environ. 2019, 695, 133781. [Google Scholar] [CrossRef] [PubMed]
  17. Algammal, A.; Hetta, H.F.; Mabrok, M.; Behzadi, P. Emerging Multidrug-Resistant Bacterial Pathogens “Superbugs”: A Rising Public Health Threat. Front. Microbiol. 2023, 14, 1135614. [Google Scholar] [CrossRef] [PubMed]
  18. Miller, J.H.; Novak, J.T.; Knocke, W.R.; Pruden, A. Survival of Antibiotic Resistant Bacteria and Horizontal Gene Transfer Control Antibiotic Resistance Gene Content in Anaerobic Digesters. Front. Microbiol. 2016, 7, 263. [Google Scholar] [CrossRef]
  19. Van Epps, A.; Blaney, L. Antibiotic Residues in Animal Waste: Occurrence and Degradation in Conventional Agricultural Waste Management Practices. Curr. Pollut. Rep. 2016, 2, 135–155. [Google Scholar] [CrossRef]
  20. Korzeniewska, E.; Harnisz, M. Relationship between Modification of Activated Sludge Wastewater Treatment and Changes in Antibiotic Resistance of Bacteria. Sci. Total Environ. 2018, 639, 304–315. [Google Scholar] [CrossRef]
  21. Sui, Q.; Zhang, J.; Chen, M.; Tong, J.; Wang, R.; Wei, Y. Distribution of Antibiotic Resistance Genes (ARGs) in Anaerobic Digestion and Land Application of Swine Wastewater. Environ. Pollut. 2016, 213, 751–759. [Google Scholar] [CrossRef]
  22. Cho, S.-K.; Yun, Y.-M.; Shin, S.G. Low-Strength Ultrasonication Positively Affects Methanogenic Granules toward Higher AD Performance: Hydrolytic Enzyme Excretions. Ultrason. Sonochem. 2017, 36, 168–172. [Google Scholar] [CrossRef]
  23. Cho, S.-K.; Kim, D.-H.; Quince, C.; Im, W.-T.; Oh, S.-E.; Shin, S.G. Low-Strength Ultrasonication Positively Affects Methanogenic Granules toward Higher AD Performance: Implications from Microbial Community Shift. Ultrason. Sonochem. 2016, 32, 198–203. [Google Scholar] [CrossRef] [PubMed]
  24. Nahum, Y.; Gross, N.; Cerrone, A.; Matouš, K.; Nerenberg, R. Effect of Biofilm Physical Characteristics on Their Susceptibility to Antibiotics: Impacts of Low-Frequency Ultrasound. npj Biofilms Microbiomes 2024, 10, 70. [Google Scholar] [CrossRef] [PubMed]
  25. Gao, S.; Lewis, G.D.; Ashokkumar, M.; Hemar, Y. Inactivation of Microorganisms by Low-Frequency High-Power Ultrasound: 1. Effect of Growth Phase and Capsule Properties of the Bacteria. Ultrason. Sonochem. 2014, 21, 446–453. [Google Scholar] [CrossRef] [PubMed]
  26. Grönroos, A.; Kyllönen, H.; Korpijärvi, K.; Pirkonen, P.; Paavola, T.; Jokela, J.; Rintala, J. Ultrasound Assisted Method to Increase Soluble Chemical Oxygen Demand (SCOD) of Sewage Sludge for Digestion. Ultrason. Sonochem. 2005, 12, 115–120. [Google Scholar] [CrossRef]
  27. Xie, B.; Liu, H.; Yan, Y. Improvement of the Activity of Anaerobic Sludge by Low-Intensity Ultrasound. J. Environ. Manag. 2009, 90, 260–264. [Google Scholar] [CrossRef]
  28. Cho, S.-K.; Kim, D.-H.; Kim, M.-H.; Shin, H.-S.; Oh, S.-E. Enhanced Activity of Methanogenic Granules by Low-Strength Ultrasonication. Bioresour. Technol. 2012, 120, 84–88. [Google Scholar] [CrossRef]
  29. Kim, H.-W.; Shin, H.-S.; Han, S.-K.; Oh, S.-E. Response Surface Optimization of Substrates for Thermophilic Anaerobic Codigestion of Sewage Sludge and Food Waste. J. Air Waste Manag. Assoc. 2007, 57, 309–318. [Google Scholar] [CrossRef]
  30. Chen, J.; Yu, Z.; Michel Jr, F.C.; Wittum, T.; Morrison, M. Development and Application of Real-Time PCR Assays for Quantification of Erm Genes Conferring Resistance to Macrolides-Lincosamides-Streptogramin B in Livestock Manure and Manure Management Systems. Appl. Environ. Microbiol. 2007, 73, 4407–4416. [Google Scholar] [CrossRef]
  31. Pei, R.; Kim, S.-C.; Carlson, K.H.; Pruden, A. Effect of River Landscape on the Sediment Concentrations of Antibiotics and Corresponding Antibiotic Resistance Genes (ARG). Water Res. 2006, 40, 2427–2435. [Google Scholar] [CrossRef]
  32. Apley, M.D.; Bush, E.J.; Morrison, R.B.; Singer, R.S.; Snelson, H. Use Estimates of In-Feed Antimicrobials in Swine Production in the United States. Foodborne Pathog. Dis. 2012, 9, 272–279. [Google Scholar] [CrossRef]
  33. Stokes, H.; Nesbø, C.L.; Holley, M.; Bahl, M.I.; Gillings, M.R.; Boucher, Y. Class 1 Integrons Potentially Predating the Association with Tn 402-like Transposition Genes Are Present in a Sediment Microbial Community. J. Bacteriol. 2006, 188, 5722–5730. [Google Scholar] [CrossRef]
  34. Li, X.; Zeng, C.; Lu, Y.; Liu, G.; Luo, H.; Zhang, R. Development of Methanogens within Cathodic Biofilm in the Single-Chamber Microbial Electrolysis Cell. Bioresour. Technol. 2019, 274, 403–409. [Google Scholar] [CrossRef]
  35. Suzuki, M.T.; Taylor, L.T.; DeLong, E.F. Quantitative Analysis of Small-Subunit rRNA Genes in Mixed Microbial Populations via 5′-Nuclease Assays. Appl. Environ. Microbiol. 2000, 66, 4605–4614. [Google Scholar] [CrossRef]
  36. Zubair, M.; Li, Z.; Zhu, R.; Wang, J.; Liu, X.; Liu, X. The Antibiotics Degradation and Its Mechanisms during the Livestock Manure Anaerobic Digestion. Molecules 2023, 28, 4090. [Google Scholar] [CrossRef] [PubMed]
  37. Livak, K.J.; Schmittgen, T.D. Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2− ΔΔCT Method. Methods 2001, 25, 402–408. [Google Scholar] [CrossRef] [PubMed]
  38. Xu, R.; Zhang, K.; Liu, P.; Khan, A.; Xiong, J.; Tian, F.; Li, X. A Critical Review on the Interaction of Substrate Nutrient Balance and Microbial Community Structure and Function in Anaerobic Co-Digestion. Bioresour. Technol. 2018, 247, 1119–1127. [Google Scholar] [CrossRef] [PubMed]
  39. Zhang, W.; Kong, T.; Xing, W.; Li, R.; Yang, T.; Yao, N.; Lv, D. Links between Carbon/Nitrogen Ratio, Synergy and Microbial Characteristics of Long-Term Semi-Continuous Anaerobic Co-Digestion of Food Waste, Cattle Manure and Corn Straw. Bioresour. Technol. 2022, 343, 126094. [Google Scholar] [CrossRef]
  40. Neves, L.; Ferreira, V.; Oliveira, R. Co-Composting Cow Manure with Food Waste: The Influence of Lipids Content. World Acad. Sci. Eng. Technol. 2009, 58, 986–991. [Google Scholar]
  41. Jiménez, J.; Guardia-Puebla, Y.; Cisneros-Ortiz, M.E.; Morgan-Sagastume, J.M.; Guerra, G.; Noyola, A. Optimization of the Specific Methanogenic Activity during the Anaerobic Co-Digestion of Pig Manure and Rice Straw, Using Industrial Clay Residues as Inorganic Additive. Chem. Eng. J. 2015, 259, 703–714. [Google Scholar] [CrossRef]
  42. Li, R.; Chen, S.; Li, X.; Saifullah Lar, J.; He, Y.; Zhu, B. Anaerobic Codigestion of Kitchen Waste with Cattle Manure for Biogas Production. Energy Fuels 2009, 23, 2225–2228. [Google Scholar] [CrossRef]
  43. Demirel, B.; Scherer, P.; Yenigun, O.; Onay, T.T. Production of Methane and Hydrogen from Biomass through Conventional and High-Rate Anaerobic Digestion Processes. Crit. Rev. Environ. Sci. Technol. 2010, 40, 116–146. [Google Scholar] [CrossRef]
  44. Xie, B.; Cheng, J.; Zhou, J.; Song, W.; Cen, K. Cogeneration of Hydrogen and Methane from Glucose to Improve Energy Conversion Efficiency. Int. J. Hydrogen Energy 2008, 33, 5006–5011. [Google Scholar] [CrossRef]
  45. Sakamoto, M.; Benno, Y. Reclassification of Bacteroides distasonis, Bacteroides goldsteinii and Bacteroides merdae as Parabacteroides distasonis Gen. Nov., Comb. Nov., Parabacteroides goldsteinii Comb. Nov. and Parabacteroides merdae Comb. Nov. Int. J. Syst. Evol. Microbiol. 2006, 56, 1599–1605. [Google Scholar] [CrossRef]
  46. Moore, L.H.; Johnson, J.; Moore, W. Descriptions of Prevotella tannerae Sp. Nov. and Prevotella enoeca Sp. Nov. from the Human Gingival Crevice and Emendation of the Description of Prevotella zoogleoformans. Int. J. Syst. Evol. Microbiol. 1994, 44, 599–602. [Google Scholar] [CrossRef] [PubMed]
  47. Morotomi, M.; Nagai, F.; Watanabe, Y. Description of Christensenella minuta Gen. Nov., Sp. Nov., Isolated from Human Faeces, Which Forms a Distinct Branch in the Order Clostridiales, and Proposal of Christensenellaceae Fam. Nov. Int. J. Syst. Evol. Microbiol. 2012, 62, 144–149. [Google Scholar] [CrossRef]
  48. Morris, B.E.L.; Henneberger, R.; Huber, H.; Moissl-Eichinger, C. Microbial Syntrophy: Interaction for the Common Good. FEMS Microbiol. Rev. 2013, 37, 384–406. [Google Scholar] [CrossRef]
  49. Schink, B. Energetics of Syntrophic Cooperation in Methanogenic Degradation. Microbiol. Mol. Biol. Rev. 1997, 61, 262–280. [Google Scholar] [CrossRef]
  50. Karakashev, D.; Batstone, D.J.; Trably, E.; Angelidaki, I. Acetate Oxidation Is the Dominant Methanogenic Pathway from Acetate in the Absence of Methanosaetaceae. Appl. Environ. Microbiol. 2006, 72, 5138–5141. [Google Scholar] [CrossRef] [PubMed]
  51. Mand, T.D.; Metcalf, W.W. Energy Conservation and Hydrogenase Function in Methanogenic Archaea, in Particular the Genus Methanosarcina. Microbiol. Mol. Biol. Rev. 2019, 83, e00020-19. [Google Scholar] [CrossRef] [PubMed]
  52. Saha, S.; Kurade, M.B.; Ha, G.-S.; Lee, S.S.; Roh, H.-S.; Park, Y.-K.; Jeon, B.-H. Syntrophic Metabolism Facilitates Methanosarcina-Led Methanation in the Anaerobic Digestion of Lipidic Slaughterhouse Waste. Bioresour. Technol. 2021, 335, 125250. [Google Scholar] [CrossRef] [PubMed]
  53. Fricke, W.F.; Seedorf, H.; Henne, A.; Krüer, M.; Liesegang, H.; Hedderich, R.; Gottschalk, G.; Thauer, R.K. The Genome Sequence of Methanosphaera stadtmanae Reveals Why This Human Intestinal Archaeon Is Restricted to Methanol and H2 for Methane Formation and ATP Synthesis. J. Bacteriol. 2006, 188, 642–658. [Google Scholar] [CrossRef]
  54. Ikeda-Dantsuji, Y.; Feril, L.B., Jr.; Tachibana, K.; Ogawa, K.; Endo, H.; Harada, Y.; Suzuki, R.; Maruyama, K. Synergistic Effect of Ultrasound and Antibiotics against Chlamydia Trachomatis-Infected Human Epithelial Cells in Vitro. Ultrason. Sonochem. 2011, 18, 425–430. [Google Scholar] [CrossRef]
  55. Zhang, L.; Gu, J.; Wang, X.; Zhang, R.; Tuo, X.; Guo, A.; Qiu, L. Fate of Antibiotic Resistance Genes and Mobile Genetic Elements during Anaerobic Co-Digestion of Chinese Medicinal Herbal Residues and Swine Manure. Bioresour. Technol. 2018, 250, 799–805. [Google Scholar] [CrossRef]
  56. Zhang, J.; Chen, M.; Sui, Q.; Wang, R.; Tong, J.; Wei, Y. Fate of Antibiotic Resistance Genes and Its Drivers during Anaerobic Co-Digestion of Food Waste and Sewage Sludge Based on Microwave Pretreatment. Bioresour. Technol. 2016, 217, 28–36. [Google Scholar] [CrossRef] [PubMed]
  57. Zhang, M.; Liu, Y.-S.; Zhao, J.-L.; Liu, W.-R.; Chen, J.; Zhang, Q.-Q.; He, L.-Y.; Ying, G.-G. Variations of Antibiotic Resistome in Swine Wastewater during Full-Scale Anaerobic Digestion Treatment. Environ. Int. 2021, 155, 106694. [Google Scholar] [CrossRef]
  58. Morris, R.L.; Tale, V.P.; Mathai, P.P.; Zitomer, D.H.; Maki, J.S. mcrA Gene Abundance Correlates with Hydrogenotrophic Methane Production Rates in Full-Scale Anaerobic Waste Treatment Systems. Lett. Appl. Microbiol. 2016, 62, 111–118. [Google Scholar] [CrossRef]
  59. Wilkins, D.; Lu, X.-Y.; Shen, Z.; Chen, J.; Lee, P.K.H. Pyrosequencing of mcrA and Archaeal 16S rRNA Genes Reveals Diversity and Substrate Preferences of Methanogen Communities in Anaerobic Digesters. Appl. Environ. Microbiol. 2015, 81, 604–613. [Google Scholar] [CrossRef]
Applsci 15 10548 g001
Figure 1. Schematic representation and experimental setup of the UASB reactor integrated with an ultrasonicator: (a) Process flow diagram of the UASB reactor; (b) Photograph of the lab-scale UASB reactors equipped with ultrasound devices used in this study, arranged from left to right as control (C), ultrasound-treated (U), co-digestion control (Co-C), and co-digestion with ultrasound (Co-U).
Figure 1. Schematic representation and experimental setup of the UASB reactor integrated with an ultrasonicator: (a) Process flow diagram of the UASB reactor; (b) Photograph of the lab-scale UASB reactors equipped with ultrasound devices used in this study, arranged from left to right as control (C), ultrasound-treated (U), co-digestion control (Co-C), and co-digestion with ultrasound (Co-U).
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Figure 2. Methane gas production.
Figure 2. Methane gas production.
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Figure 3. COD mass balance and conversion rate of each reactor.
Figure 3. COD mass balance and conversion rate of each reactor.
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Figure 4. Bacterial communities at the phylum level.
Figure 4. Bacterial communities at the phylum level.
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Figure 5. Archaeal communities at the genus level.
Figure 5. Archaeal communities at the genus level.
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Figure 6. Relative abundance of ARGs, intI1, and mcrA genes.
Figure 6. Relative abundance of ARGs, intI1, and mcrA genes.
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Table 1. Characteristics of substrate.
Table 1. Characteristics of substrate.
ParametersPW *FWL **ParametersPWFWL
pH6.913.98COD (g/L)37.0377.71
TS (g/L)17.9560.45SCOD (g/L)22.2659.06
TSS (g/L)9.1620.37T-N (g/L)2.972.04
VS (g/L)11.1647.98T-P (g/L)0.220.42
VSS (g/L)6.0020.80NH4-N (g/L)2.790.54
*: Piggery Wastewater, **: Food Waste Leachate.
Table 2. Operating conditions of the reactors in each phase.
Table 2. Operating conditions of the reactors in each phase.
Phase 1Phase 2Phase 3OLR ShockRecovery
HRT (day)2
Time (day)1~1415~2829~4243~4546~50
OLR (g COD/L·day)22.5362
substratePW * or PW + FWL **Glucose
*: Piggery Wastewater, **: Food Waste Leachate.
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MDPI and ACS Style

Lee, C.; Gwon, J.; Kim, M.-S.; Lee, T.; Han, U.; Park, Y.; Jo, H.; Cho, S.-K. Synergistic Role of Low-Strength Ultrasound and Co-Digestion in Anaerobic Digestion of Swine Wastewater. Appl. Sci. 2025, 15, 10548. https://doi.org/10.3390/app151910548

AMA Style

Lee C, Gwon J, Kim M-S, Lee T, Han U, Park Y, Jo H, Cho S-K. Synergistic Role of Low-Strength Ultrasound and Co-Digestion in Anaerobic Digestion of Swine Wastewater. Applied Sciences. 2025; 15(19):10548. https://doi.org/10.3390/app151910548

Chicago/Turabian Style

Lee, Changgee, Jaehun Gwon, Min-Sang Kim, Taehwan Lee, Uijeong Han, Yeongmi Park, Hongmok Jo, and Si-Kyung Cho. 2025. "Synergistic Role of Low-Strength Ultrasound and Co-Digestion in Anaerobic Digestion of Swine Wastewater" Applied Sciences 15, no. 19: 10548. https://doi.org/10.3390/app151910548

APA Style

Lee, C., Gwon, J., Kim, M.-S., Lee, T., Han, U., Park, Y., Jo, H., & Cho, S.-K. (2025). Synergistic Role of Low-Strength Ultrasound and Co-Digestion in Anaerobic Digestion of Swine Wastewater. Applied Sciences, 15(19), 10548. https://doi.org/10.3390/app151910548

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