Next Article in Journal
Stochastic Modeling and Simulation of Filament Aggregation in Alzheimer’s Disease
Next Article in Special Issue
Comparison of the Work of Wastewater Treatment Plant “Ravda” in Summer and Winter Influenced by the Seasonal Mass Tourism Industry and COVID-19
Previous Article in Journal
Research on AGC Nonlinear Compensation Control for Electro-Hydraulic Servo Pump Control of a Lithium Battery Pole Strip Mill
Previous Article in Special Issue
Comparative Study of Rhodamine B Treatment: Assessing of Efficiency Processes and Ecotoxicity of By-Products
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Processes
Volume 12
Issue 1
10.3390/pr12010159
processes-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Microbiome Structure of Activated Sludge after Adaptation to Landfill Leachate Treatment in a Lab-Scale Sequencing Batch Reactor

by
Mihaela Kirilova
1,2,*,
Ivaylo Yotinov
1,2,
Yovana Todorova
1,2,
Nora Dinova
1,2,
Stilyana Lincheva
3,
Irina Schneider
1,2 and
Yana Topalova
1,2
1
Faculty of Biology, Sofia University “St. Kliment Ohridski”, 8 Dragan Tsankov Blvd., 1504 Sofia, Bulgaria
2
Center of Competence “Clean Technologies for Sustainable Environment—Water, Waste, Energy for Circular Economy”, 1000 Sofia, Bulgaria
3
Municipal Enterprise for Waste Treatment, Locality Sadinata, 1805 Yana, Bulgaria
*
Author to whom correspondence should be addressed.
Processes 2024, 12(1), 159; https://doi.org/10.3390/pr12010159
Submission received: 27 November 2023 / Revised: 29 December 2023 / Accepted: 4 January 2024 / Published: 9 January 2024
(This article belongs to the Special Issue Integrated Approaches to Eco-Friendly Processes for Persistent Pollutants Contamination)
Browse Figures
Versions Notes

Abstract

:
During adaptation to waters that are rich in xenobiotics, biological systems pass through multiple stages. The first one is related to the restructuring of communities, pronounced destruction of the structure, and multiplication of active biodegradants. The purpose of the present research was to describe the microbiome restructuring that occurs during the adaptation stage in landfill leachate treatment. In a model SBR (sequencing batch reactor), a 21-day purification process of landfill leachate was simulated. Wastewater was fed in increasing concentrations. When undiluted leachate entered, the activated sludge structure disintegrated (Sludge Volume Index—4.6 mL/g). The Chemical Oxygen Demand and ammonium nitrogen concentration remained at high values in the influent (2321.11 mgO2/L and 573.20 mg/L, respectively). A significant amount of free-swimming cells was found, and the number of aerobic heterotrophs and bacteria of the genera Pseudomonas and Acinetobacter increased by up to 125 times. The Azoarcus-Thauera cluster (27%) and Pseudomonas spp. (16%) were registered as the main bacterial groups in the activated sludge. In the changed structure of the microbial community, Gammaproteobacteria, family Rhizobiaceae, class Saccharimonadia were predominantly represented. Among the suspended bacteria, Microbactericeae and Burkholderiaceae, which are known for their ability to degrade xenobiotics, were present in larger quantities. The enzymological analysis demonstrated that the ortho-pathway of cleavage of aromatic structures was active in the community. The described changes in the leachate-purifying microbial community appear to be destructive at the technological level. At the microbiological level, however, trends of initial adaptation were clearly outlined, which, if continued, could provide a highly efficient biodegradation community.

1. Introduction

Municipal solid waste (MSW) generation has increased dramatically around the world during the past few decades as a result of human overpopulation, urbanization, and economic growth [1,2]. While innovative and effective solutions are still being developed and implemented to reduce, reuse, and recycle these huge amounts of waste materials, landfilling remains the most widely used concept in waste management and sanitary landfills are the most commonly used final disposal option around the world [3,4]. Although landfilling is a well-established technology, it has environmental consequences such as greenhouse gas emissions and leachate formation. The impact of waste disposal sites can be severe due to improper operation and the release of leachate is commonly rated as the highest priority concern in the risk assessment of landfills. Among the 17 sustainable development goals (SDGs), at least 4 are related to the effective treatment of landfill leachate—clean water and sanitation, affordable and clean energy, sustainable cities and communities, and climate action [5,6]. Achieving these is impossible without managing the treatment of the highly polluted landfill leachate generated by the waste—a problem faced by every city.
Leachate is a highly concentrated organic liquid, produced by the percolation of rainwater during the decomposition of wastes, and is considered one of the most harmful types of wastewater [1,7]. It contains a wide variety of pollutants including heavy metals, inorganic salts, ammonium nitrogen, both biodegradable and refractory organic matter, and xenobiotic compounds [8]. The presence of xenobiotics poses an additional challenge due to the extremely concentrated and complicated composition of leachate. Leachate contains an unknown number of dangerous chemicals with varying chemical compositions and concentrations. Numerous studies have found different hydrophobic aliphatic and aromatic organic substances (benzene, toluene, ethylbenzene, and xylenes—BTEX), polyaromatic hydrocarbons, toxic metals, phenols, phthalates, pesticides, microplastics, polyethylene, plasticizers, per- and polyfluoroalkyl substances (PFASs and their derivates), and halogenated organic compounds such as PCBs and dioxins [9,10,11,12]. This nitrogen- and toxic compound-rich composition requires highly specialized treatment technologies aimed at solving specific problems—the removal of high nitrogen content—and emerging contaminants.
On-site treatment plants, transport to a wastewater treatment plant for co-treatment with municipal wastewater, and reinjection or recycling to a landfill cell are the options for leachate treatment [8]. Successful technologies for leachate treatment include physicochemical (coagulation/flocculation, advanced oxidation, precipitation, membrane separation, reverse osmosis, air stripping, filtration), biological (activated sludge processes, sequencing batch reactors, moving bed biofilm reactors, trickling filters, anaerobic processes), and hybrid processes (different combinations of above) [13,14,15,16]. Due to their simplicity, good-quality effluents, and low cost, biological methods for treatment are regarded as promising options for removing organic compounds and nitrogen species from landfill leachates. However, their successful application requires specially developed strategies to enhance the biological systems to achieve a high efficiency. These strategies include the use of different techniques and processes such as cometabolism, algal–bacterial symbiosis, quorum sensing, augmentation, bioaugmentation, granulation, and perhaps the most accessible and widely used: the prior adaptation of the biological system [17].
In general, a step-by-step adaptation of sludge to the toxic effect of leachate improves the breakdown rates of persistent organic components and reduces the risk of sludge disintegration or deactivation. There are several interconnected adaptation mechanisms including (i) the restructuring of microbial community with selective enrichment of some microbial species or groups, (ii) activation and/or inhibition of certain enzymes, and (iii) genetic modifications that result in novel metabolic capacities [18]. Usually, the shift in microbial populations is expressed in the predominance of active biodegradants and some functionally important genera from the groups of heterotrophic bacteria, denitrifying bacteria, ammonia-oxidizing bacteria, nitrite-oxidizing bacteria, and/or Anammox bacteria [18,19].
However, there is a knowledge gap regarding the restructuring and changes in the composition of microbial communities throughout the initial adaptation period to the leachate biodegradation process. This stage of development is crucial for the evolving community—the key biodegraders multiply when they are in an environment with abundant substrates while the non-biodegraders are inhibited or even eliminated from the community. Lab-scale modeling may be used to imitate the real full-scale adaptation process under controlled and defined conditions. In our study, we investigated the initial phase of activated sludge adaptation to leachate in a model sequencing batch reactor. For this aim, the activated sludge community was exposed to leachate in increasing concentrations and the changes in structure, composition, and enzymological profile were investigated.

2. Materials and Methods

2.1. Experimental Design

The modeling of the treatment of increasing concentrations leachate was carried out in a laboratory reactor-type SBR (sequencing batch reactor) with a volume of 4 L. It simulated the real purification process in a WWTP, where the same leachate goes through biological treatment in a full-scale SBR—the municipal waste treatment plant (MWTP) of Sofia, Bulgaria.
This MWTP is a municipal enterprise responsible for treating waste generated in the city of Sofia, Bulgaria. It is one of the largest plants of this type in Europe, processing around 1100 tons of waste daily. About 85% of the waste is recycled into various products—compost, RDF fuel, biogas, etc. The remaining 15% of the waste, which is not integrated into the city’s circular economy, is deposited in a closed-type landfill. It generates 15,000 L of leachate per day, which enters 3 storage tanks. It is then fed to a dedicated wastewater treatment plant. There, with the help of 4 SBRs, the highly polluted leachate is treated biologically. A significant challenge for this plant is achieving complete purification due to the high degree of pollution of the leachate (COD is approximately 4776 mgO2/L). One of the main approaches to managing such detoxification processes is the adaptation of microbial communities to pollutants and activating their biodegradation potential in the specific biotechnological situation.
Therefore, to study the biodegradation capacity of a biological system and its adaptation response to the pollutants in the leachate, a 21-day aerobic purification process was simulated. The treatment cycle in the model laboratory SBR lasted for 48 h (aeration 47 h, sedimentation 30 min, discharge of effluent 15 min, feeding influent 15 min) (Figure 1). Activated sludge from the MWTP was used. At each cycle, the wastewater was replaced with new water containing pollutants at a certain dilution. Landfill leachate dilutions (50- and 25-fold) were used during the first and second weeks of the experiment (days 0–7 and days 8–14). During days 15–21, undiluted leachate was fed into the reactor. Glycerol was added to the influent once a week until a ratio of 4:1 COD/BOD was reached, as is regularly performed in the MWTP.
Four critical control points (CCPs) were determined for analyzing the functioning of the system consisting of activated sludge and landfill leachate. The CCPs were at the beginning of the process (0 h) and at the end of the first (7th day), the second (14th day), and the third (21st day) week. The main technological, microbiological, and enzymological parameters were investigated at these CCPs.

2.2. Methods and Reagents

The following standards were used: technological indicators—SVI ISO 18749:2004 [20]; NH4—ISO 7150/1 [21]; NO2—BDS EN 26777 [22]; NO3—ISO 7890-3 [23]; PO4—BDS EN 1189 [24]; and COD—BDS 17.1.4.02-77 [25,26]. These parameters were determined after removing the suspended solids.
To study the microbiological characteristics of activated sludge, various methods for obtaining information about microbial biodiversity were applied including plate count techniques, fluorescence in situ hybridization with digital image analysis, and sequencing.
The nutrient media used for the cultivation microbiological analyses were nutrient agar (Merck, Darmstadt, Germany) for aerobic heterotrophs; glutamate starch pseudomonas agar (Merck, USA) for Pseudomonas sp.; Sellers agar (HiMedia Laboratories, Mumbai, India) for Acinetobacter sp.; and Hiltay agar (2 g/L KNO3 (Honeywell, Charlotte, NC, USA), 1 g/L asparagine (Honeywell, USA), 5 g/L Na-citrate, 2 g/L KH2PO4 (Honeywell, USA), 2 g/L MgSO4·7H2O (Honeywell, USA), 0.2 g/L CaCl2·6H2O (Honeywell, USA), 0.08 g/L bromothymol blue, traces of FeCl3 (Honeywell, USA), agar agar (Merck, USA), pH 6.8) was used for denitrifying bacteria. The bacteria were cultured for 24 h at 30 °C under aerobic conditions. The denitrifying microorganisms were incubated under anaerobic conditions (anaerobic jars with oxygen-adsorbing sachets (Merck, USA) for seven days at 30 °C). The bacteria from all the groups were determined in the mixed liquor of activated sludge. Before cultivation, the samples were homogenized by sonication at 22 Hz and 40% intensity using an ultrasonic disintegrator (Sonics VCX750; Sonics, Newtown, CT, USA).
To directly study the amount and spatial distribution of key groups of microorganisms in the activated sludge without destroying its structure, fluorescence in situ hybridization was used. The samples were preserved according to the method of Amann [27]. Table 1 shows the oligonucleotide probes applied in this study. They were labeled with Cy3 dye. The labeled oligonucleotides were supplied by Merck, USA. In situ hybridization was performed according to the Nielsen protocol [28]. A nonsense probe was used as a negative control.
The resulting fluorescence images were subjected to digital image analysis by the DAIME 2.0 software [34] using a custom segmentation criterion. The proportion of target microorganisms was calculated based on images of the corresponding DAPI-stained microorganisms.
The community structure at the end of the model process was also investigated by sequencing. Analyses of the V3–V4 region of the 16S rRNA gene were performed to study the microbial composition of the activated sludge. Since the activated sludge showed a high abundance of free-swimming bacteria at the final stage of the experiment, the sludge and the free-swimming bacteria were tested separately. First, the samples were allowed to sediment for 1 h. Then, DNA extraction using a Zymo Quick-DNA Fungal/Bacterial Miniprep Kit (Zymo Research, Irvine, CA, USA) was performed separately on the sludge and the supernatant. The quantity of DNA was checked using a QuickDrop™ UV-Vis Spectrophotometer (Molecular Devices, San Jose, CA, USA) and samples with more than 7 ng/μL DNA were sent for sequencing.
16S V3–V4 libraries were prepared using custom fusion primers including a P5/P7 Illumina adapter sequence, an 8 nt index sequence, and the gene-specific primer sequence (Table 2). The libraries were purified with Agencourt AMPure XP (Beckman Coulter Diagnostics, Brea, CA, USA) beads and the sequencing was performed on an Illumina HiSeq 2500 (Illumina, San Diego, CA, USA) in the 2 × 300 bp mode.
The bioinformatic analysis was performed using omics2view.consulting GbR (Kiel, Germany). The sequencing data were demultiplexed and the quality of demultiplexed reads was checked with FastQC v0.11.7. The remaining contigs (ASVs—amplicon sequence variants) were taxonomically classified through the IDTAXA approach implemented in the R package DECIPHER v2.18.1 [35] using the GTDB database release 202 [36,37]. A neighbor-joining phylogenetic tree was constructed from aligned ASVs using the R package DECIPHER. The ASV copy numbers were normalized by dividing them by their respective copy number. The result was multiplied by the ratio of original to normalized ASV counts to preserve the total count per sample. Taxonomic data were taken from the OTU counts at the species level. The taxa were merged at the class level. Those with a frequency less than 0.5% were classified as “other”. The results from the sequencing were deposited into the NCBI database under accession number PRJNA1056534.
The activity of the key biochemical pathways of biodegradation was investigated by determining the activities of (1) catechol-1,2-dioxygenase, an indicator of the ortho-pathway of decyclization of aromatic substances using the method of Willetts and Cain [38]; (2) catechol-2,3-dioxygenase, a good indicator of the activity of the meta-pathway of decyclization of aromatic substances, using the method of Farr and Cain [39]; (3) protocatechuate-3,4-dioxygenase, which reflects the decyclization activity of aromatic xenobiotics through a key metabolite (protocatechuate) using the method of Fujisawa and Hayashi [40]; and (4) total dehydrogenase activity (TDA), which reflects the enzymatic activity of dehydrogenases in cells and is an indication of the general metabolic activity of organisms in the community, and was determined using the method of Lenhard [41].
The analyses were performed in triplicates. Excel MS Office was used for data calculations and visualization.

3. Results

The results for the main technological parameters are shown in Table 3, with these parameters being assessed at four Critical Control Points (CCPs) during the leachate treatment—0 h, 7th day, 14th day, and 21st day. At the beginning of the process (0 h), a low sludge volume index (SVI) was found, indicating a deformation in the structure of the activated sludge which was characterized by pin-point flocs. Such a change is often found in communities treating waters with a high degree of toxicity. From the data shown, it can be seen that when the load was reduced (7th and 14th days), the index increased, reaching values considered normal for activated sludge (80–180 mL/g). This normalization suggests an improved purification process under conditions of reduced toxicity (50 and 25 times lower dilution than the landfill leachate). At this stage of the process, a decrease in COD to 309 mgO2/L was also found at influent values of 2150 mgO2/L. At the same time, the concentration of nitrates remained significant (154–452 mg/L), indicating a low degree of denitrification. This is related to the treatment of the landfill leachate in an aerobic regime. It allows for a limited elimination of nitrates—only through the conventional denitrification, taking place inside the flocs, where the oxygen concentration is lower—and through aerobic denitrification, a still poorly understood process. However, the concentration of ammonium ions was low (3–6 mg/L, Table 3), which showed that the activated sludge successfully performed nitrification.
At the end of the model process, when undiluted leachate was fed into the system, a significant increase in pollutants in the effluent was found—the COD increased by 2.6 times, phosphates increased by 218 times, nitrites increased by 49 times, and ammonium ions increased by 98 times up to 573 mg/L. This high value indicates a strong inhibition of nitrification, which is also the reason for the low concentration of nitrates (4.39 mg/L), indicating that ammonium ions were not transformed into nitrates. At this CCP (21st days), an extremely low SVI (4.6 mL/g) was also registered, indicating an almost complete disintegration of the activated sludge structure. All the technological data indicated that when undiluted leachate was fed into the system, inhibition of the biological processes and intoxication of the microorganisms that support them occurred.
To elucidate the processes underlying the obtained data, it is important to analyze the community treating the landfill leachate, considering the technological indicators. Figure 2 illustrates the results of the cultivation analyses showing the number of bacteria from several key groups—aerobic heterotrophs, bacteria from the g. Pseudomonas, g. Acinetobacter, and denitrifying bacteria. The data demonstrated an increase in the number of aerobic heterotrophs at the end of the process by nearly 7 times compared the beginning. Such an increase was also registered in all the other studied groups. In the case of bacteria from the g. Pseudomonas, the increase was 58 times; in the case of g. Acinetobacter, it increased by 299 times; and in the case of denitrifying bacteria, it increased by 17 times. The substantial variations in the number of bacteria from the xenobiotic-degrading groups (Pseudomonas and Acinetobacter) indicated a specialization of the community towards the biodegradation of the specific pollutants in the landfill leachate. Notably, within these groups, an increase in CFU/mL was registered at each subsequent CCP (2 to 6 times), with the largest increase in Acinetobacter occurring after adding the first part of the diluted filtrate (×50) to the system (increase by 56 times).
At the end of the model process, numerous free-swimming cells were found in the reactors. These were bacteria that were well adapted to the toxic conditions in the reactor. They used pollutants as a substrate for their development, which is why they had a competitive advantage and develop more rapidly. Since they were part of the biodegradation potential of the system that was capable of efficient adaptation, they were subjected to additional cultivation analyses. Thus, in the homogeneous phase, an especially high number of aerobic heterotrophs was found, constituting 71% of the total number of microorganisms on the 21st day of the process. In the same phase of the mixed liquor, 5% of the bacteria were a Pseudomonas sp., 11% of the microorganisms were an Acinetobacter sp., and 5% were bacteria capable of denitrification (Figure 2). The high difference in the part of the aerobic heterotrophs and narrower bacterial groups indicated that there are other microbial groups with important role in the treatment process. Thus, sequencing was performed to further elucidate the taxonomic structure of this adaptationally important segment.
The quantity of several more taxonomic groups that are also important in the biodegradation of xenobiotics in the leachate was investigated in situ. For this, the FISH method was used and the obtained data are presented in Figure 3.
The predominant portion of the community was occupied by bacteria from the Azoarcus-Thauera cluster (13–27%). Their average share for the process was 17.50%, which exceeded the other studied groups by 39% to 300%. The high proportion of these microorganisms was due to their ability to degrade toxic substances in landfill leachates. The gradually increasing concentration of the pollutants activated Azoarcus-Thauera, and their amount in the activated sludge rose nearly two-fold by the end of the model process and reached 27%.
Pseudomonas microorganisms exhibited a significant increase according to cultivation methods, which was confirmed by the data obtained from the in situ analyses. The proportion of Pseudomonas in the community ranged from 7% to 24% in the period 0 h–14th day. In the final stage, however, the proportion decreased to levels similar to those at 0 h (8%).
The FISH analyses also showed that g. Paracoccus, the key group for the detoxification and aerobic denitrification processes, decreased over the course of the model process from 12% to 4%. The bacteria from the g. Alcaligenes were activated during the model process of leachate treatment. At the end (21st day), this bacterial group increased its proportion by 2.4 times—from 2% at 0 h to over 5%.
The data from the sequencing analyses are presented in Figure 4. It can be seen that the proportion of Alphaproteobacteria was the largest one (32%). These ancient bacteria inhabit diverse niches and are well adapted to extreme conditions. Some of them are well-known biodegraders of xenobiotics, such as the bacteria of the genus Paracoccus, which were well represented in the activated sludge in the model SBR. These included Paracoccus alkenifer and unclassified Paracoocus, which were 4% of the established OTUs (operational taxonomic units). Additionally, the presence of the higher taxonomic group to which they belong, Rhodobacteriaceae (5%), was also observed. The bacterial group with the highest OTU share was the family Rhizobiaceae (13%). These organisms are common representatives of soil microbiomes. Since the leachate was generated in a closed-type landfill, there is a large amount of topsoil between the layers of waste to which these microorganisms had most likely adapted to.
Among the identified bacterial groups, the Actinomycetia class was represented by a significant percentage (10%). These microorganisms, which are also normal inhabitants of soils, include extremophiles that are capable of thriving in highly contaminated habitats, such as solid waste landfills and activated sludge leachate. Many of them form spores, which makes them particularly resistant to toxic influences. It is known that representatives of this class participate in the nitrogen cycle and, as shown in Table 3, the leachate used in the described experiments is extremely rich in different forms of nitrogen. The main representatives of this group were Microbacteriaceae (3%), Nakamurella (5%), and Micropruina (3%).
Gammaproteobacteria, which are known as the most active biodegraders of xenobiotics, were represented in 6% of the determined OTUs. They were identified as part of the order Burkholderiales. The bacteria in this group include xenobiotic-degrading and phosphate-accumulating bacteria. With the help of sequencing, their important role in the treatment of wastewater contaminated with toxicants is being increasingly recognized.
An interesting group found in 10% of the OTUs was the class Saccharimonadia. These microorganisms have never been isolated in pure cultures. They were discovered only thanks to sequencing methods. The reason for this is thought to be due to their incomplete biochemical pathways, which force them to exist only as symbiotic organisms. They are often associated with Alphaproteobacteria [42].
Figure 5 presents the results of the metagenomic analysis of the free-swimming cells found at the end of the model experiment. They appeared during the period of strong deterioration of the technological indicators. As mentioned, the presence of such cells was detected microscopically and a metagenomic analysis was performed. In this segment of the biodegradation system, the main groups found in the sludge were Actinomycetia, Alphaproteobacteria, Gammaproteobacteria, and Saccharimonadia. Actinomycetia (23%) and Alphaproteobacteria were the most abundant (22%). Microbacteriaceae (13%) were found in the most OTUs. They are found in many soil and water habitats, but are not known to have particularly pronounced biodegradation properties. Burkholderiaceae were also found in a high percentage (8%), which was significantly higher than that recorded in the sludge (2%). Since these bacteria are known to be active biodegradants of xenobiotics, it is most likely that their multiplication within the free-swimming segment of the microbiome was related to the detoxification of pollutants. A significant share of the recorded OTUs were bacteria from the family Rhizobiaceae. They were most likely soil inhabitants of the landfill, and were adapted to the pollutants found there.
Also, among Actinomycetia, Nakamurella (4%), Micropruina (3%), and Leucobacter (4%) had significant OTU proportions. They are known to participate in the biodegradation of carbon-containing pollutants. The family Rhodobacteraceae was also registered with 4% of the OTUs, pointing to the key role of Paracoccus as its representative, Paracoccus alkenifer, constituted 2% of the OTUs.
Saccharimonadia was found as a considerable proportion (6%) of the free-swimming cells, indicating the development of a complex symbiont structure not only within the activated sludge but also among the free-swimming bacteria.
In addition to the taxonomic structure, analyses were also performed to determine the biodegradation potential of the landfill leachate community. The obtained data showed that at the beginning of the model process in the community, there were two pathways for the degradation of aromatic pollutants: an ortho-pathway through catechol metabolites (catechol-1,2-dioxygenase activity was 0.82 µg H+/mL/min/mgP) and an ortho-pathway through protocatechuate metabolites (protocatechuate-3,4-dioxygenase activity was 0.87 µg H+/mL/min/mgP) (Figure 6). After 48 h, in the conditions with reduced toxicity, the total dioxygenase activity (sum of the activity of the three tested oxygenases) decreased by 39%. At the same time, a decrease in COD was recorded, mostly related to the increased activity of the general metabolism of the cells and the accumulation of biomass in the system. The TDA and protein concentration per ml of mixed liquor increased 3-fold.
The highest dioxygenase activity was recorded on day 7 when the filtrate was diluted by 50 times (3.07 µg H+/mL/min/mgP). The highest dehydrogenase activity was also found at the same time point (0.94 µg H+/mL/min/mgP). This result corresponded to the release of the toxic pressure on the biological system and the activation of its biodegradation potential. At the end of the model process, at the highest concentration of pollutants, a C12DO activity of 2.2 µg H+/mL/min/mgP was recorded, which exceeded the initially demonstrated one (at 0 h) by 2.7 times (Figure 6). This was indicative of the community’s adaptation and specialization toward the biodegradation of cyclic xenobiotics through the most active pathway in the community—using the key enzyme C12DO. The average activity for this enzyme was 14 times higher than that of C23DO and 75% higher than that of P34DO.
The high COD recorded at the end of the process was related to the inhibition of the general metabolism of the biodegradants; the TDA was reduced by 4 times, which was also accompanied by destructive changes in the structure of the activated sludge.

4. Discussion

Studies of a biological system treating increasing concentrations of leachate in a model SBR revealed a complex picture of an initial adaptive response. Despite significant deterioration in purification activity based on the technological indicators (Table 3), a detailed examination of the bacterial community showed an increase in the groups with a high biodegradation potential. The registered SVI of only 4.6 mL/g at the end of the process was related to the overall restructuring of the community—destruction of flocs and multiplication of active biodegradants that had found a suitable substrate for their development. Therefore, the multiplication of free-swimming bacteria up to 2.2 × 107 CFU/mL was also found. They accounted for 71% of all cells found per mL of the mixed liquor. Among them, bacteria from the xenobiotic-degrading groups—Pseudomonas (5.3 × 104 CFU/mL) and Acinetobacter (1.7 × 105 CFU/mL)—were well represented. Through the metagenomic analysis, Actinomycetia and Alphaproteobacteria were found to predominate in this segment of the biological system. Of the former, Microbacteriaceae (13%), Nakamurella (4%), Leucobacter (4%), and Micropruina (3%) were represented in the largest percentages. Microbacteriaceae are known to be a diverse group that occurs widely in soil [43] and aquatic [44] habitats. Therefore, they are likely to be found to a significant extent in leachate-treated samples as well. This type of wastewater is formed by the infiltration of water through landfills, which inevitably trains the landfill’s soil microorganisms. They are adapted to the pollutants emitted by the waste at the particular site. They are then successfully incorporated into the leachate treatment communities. A similar result was also found by González-Cortés et al. [45], who observed an increase in the same bacterial group after the adaptation of activated sludge to leachate treatment. The Leucobacter group was also identified as a key group by other scientific teams. Remmas et al. [46] demonstrated that this was the dominant group (41%) in the microbiome of leachate from a solid waste landfill. A study by Zou et al. [47] demonstrated that the amount of these organisms increased with a gradual increase in the leachate concentration in a model process, as Leucobacter is believed to have a high resistance to heavy metals, especially chromium. Bacteria of the Nakamurella group are little studied, but what is known about them is that they are capable of degrading large amounts of carbon-containing pollutants [48]. A high COD most likely favors the development of these organisms in the homogeneous phase of the system. Of interest were bacteria from the Micropruina group, which were found as a significant part of the microbiome of both the free-swimming microorganisms and sludge. They belong to the group of glycogen-accumulating organisms (GAOs) [49]. A high concentration of phosphates (25 mg/L) was detected in the effluent on the 21st day, which exceeded the initial concentration by 61 times. This was likely due to GAOs, which are competitors of phosphate-accumulating bacteria [50]. Their presence is often associated with a low phosphate elimination efficiency. Kong et al. showed such a role for Micropruina in a model SBR [51].
A significant proportion of Alphaproteobacteria was found both in the sediment (32%) and in the single, free-swimming bacteria in the water layer (22%). Different species of the genus Paracoccus were found in both fractions of mixed liquor (4% each). These bacteria were also detected by the FISH analysis (4%). Their important role in the biodegradation of xenobiotics, which are abundant in the leachate, is known [52,53]. Also, they were identified by Zheng et al. [54] as bacteria capable of aerobic denitrification and heterotrophic nitrification, which makes their development in waters rich in ammonium ions and xenobiotics very successful.
Rhizobiaceae had a high share of the identified OTUs—14% in the sediment and 10% in the homogeneous phase of the samples. Although bacteria from this taxonomic group are known as plant symbionts [55], they are also highly active biodegraders of various xenobiotics [56,57]. This is a prerequisite for their establishment in the community treating infiltrate.
Through the FISH analysis, the presence of key groups of the Betaproteobacteria, Azoarcus-Thauera cluster and Alcaligenes spp., was detected. The Azoarcus-Thauera cluster reached a significant 27% of the community, which was an indication of their leading role in contaminant purification. The role of g. Azoarcus in the biodegradation of xenobiotics in landfill leachate is known. Sun et al. showed their dominant role in the bioremediation of solid waste landfills [58]. The bacteria in g. Thauera are known as biodegraders of toxic substances, but they also belong to the group of aerobic denitrifying microorganisms [59]. The role of this group of organisms was important in the model treatment process in which aerobic conditions were maintained. Our results are also supported by Remmas et al. [60] who demonstrated a shift in the dominant group from Gammaproteobacteria to Betaproteobacteria when treated with glycerol-supplemented leachate.
The FISH analysis of Gammaproteobacteria was focused on the key group of bacteria of the genus Pseudomonas. In the course of the purification process, their proportion reached 24% (on 14th day), but in the end, at the highest applied concentrations, these microorganisms decreased 3-fold. This was an indication of the reduction in their biodegradation role in the final stage with high intoxication. These data supported the results for the metabolic activity of the community. Bacteria of the genus Pseudomonas have a proven high dioxygenase enzyme activity, using catechol and protocatechate as substrates [61]. Thus, at the initial activation of the genus on day 7 (increase in CFU/mL by 2.3 times) and at low concentrations of landfill leachate, the maximum activity of the three investigated dioxygenases was also detected (Figure 6).
The cultivation methods showed an increase in Pseudomonas sp. on the 21st day compared to the 14th day which is a 5-fold increase. However, a more detailed analysis showed that the bacteria of this genus reached 1.07 × 107 CFU/mL on day 17, after which, the number fell by 9-fold due to inhibition of this group of bacteria. The lower amount of Gammaproteobacteria was also observed in the metagenomic analysis results. These bacteria, generally considered the main bacteria leading the biodegradation of organic pollutants in the leachate [62,63], only accounted for 6% of the OTUs in the sludge and 12% in the suspended portion. In this final stage of the process, a decrease in the activity of dioxygenase enzymes characteristic of Gammaproteobacteria was also recorded. At the highest degree of toxicity, in aerobic conditions, Actinomycetia, Alphaproteobacteria, and some representatives of Betaproteobacteria acquire leading importance.
The other major group found in the leachate-treating activated sludge were representatives of Saccharimonadia (9%). Although bacteria of this class have been very little studied, more and more investigations are being published showing the presence of Saccharimonadia populations in reactors treating toxic wastewater and landfill leachate [64,65,66].

5. Conclusions

The obtained data in this research showed that with an increase in toxicity, the system undergoes disintegration changes (SVI—5 mL/g) and a decrease in the efficiency of the purification processes (COD—2321 mgO2/L). At the same time, a segment of very active bacteria appeared, a large part of which floated freely outside the structure of the activated sludge. The number of aerobic heterotrophs and bacteria of the genera Pseudomonas and Acinetobacter increased by up to 125 times. In this stage, microorganisms from the groups Actinomycetia, Alphaproteobacteria, Betaproteobacteria, and especially the representatives of the genera Paracoccus, Azoarcus, and Thauera, and the families Rhizobiaceae, Microbacteriaceae, and Saccharimonadaceae played a key role. The ortho-pathway of cleavage of aromatic structures was found to be active in the community. The obtained results demonstrated that in the period when the treatment process was seemingly inefficient, dynamic changes in the microbiome structure took place in terms of increasing the overall bacterial numbers and especially the bacteria involved in xenobiotic degradation.

Author Contributions

Conceptualization, M.K., I.S. and Y.T. (Yana Topalova); methodology, M.K. and I.Y.; validation, M.K and I.Y.; investigation, M.K., N.D., S.L. and I.Y.; writing—original draft preparation, M.K., I.Y. and Y.T. (Yovana Todorova); writing—review and editing, M.K. and Y.T. (Yana Topalova); visualization, M.K. and I.Y.; funding acquisition, Y.T. (Yana Topalova). All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by Grant No. BG05M2OP001-1.002-0019: “Clean Technologies for Sustainable Environment—Water, Waste, Energy for a Circular Economy”, financed by the Science and Education for Smart Growth Operational Program (2014–2020), which is co-financed by the EU through the ESIF.

Data Availability Statement

All data are contained within the article.

Conflicts of Interest

Stilyana Lincheva was employed by the company Municipal Enterprise for Waste Treatment. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. Kumar, V.; Sharma, N.; Umesh, M.; Chakraborty, P.; Kaur, K.; Duhan, L.; Sarojini, S.; Thazeem, B.; Pasrija, R.; Vangnai, A.S.; et al. Micropollutants Characteristics, Fate, and Sustainable Removal Technologies for Landfill Leachate: A Technical Perspective. J. Water Process Eng. 2023, 53, 103649. [Google Scholar] [CrossRef]
  2. Zhang, F.; Peng, Y.; Wang, Z.; Jiang, H.; Ren, S.; Qiu, J. New Insights into Co-Treatment of Mature Landfill Leachate with Municipal Sewage via Integrated Partial Nitrification, Anammox and Denitratation. J. Hazard Mater. 2021, 415, 125506. [Google Scholar] [CrossRef] [PubMed]
  3. Ilmasari, D.; Kamyab, H.; Yuzir, A.; Riyadi, F.A.; Khademi, T.; Al-Qaim, F.F.; Kirpichnikova, I.; Krishnan, S. A Review of the Biological Treatment of Leachate: Available Technologies and Future Requirements for the Circular Economy Implementation. Biochem. Eng. J. 2022, 187, 108605. [Google Scholar] [CrossRef]
  4. Abdel-Shafy, H.I.; Ibrahim, A.M.; Al-Sulaiman, A.M.; Okasha, R.A. Landfill Leachate: Sources, Nature, Organic Composition, and Treatment: An Environmental Overview. Ain. Shams Eng. J. 2023, 15, 102293. [Google Scholar] [CrossRef]
  5. Chang, H.; Zhao, Y.; Bisinella, V.; Damgaard, A.; Christensen, T.H. Climate change impacts of conventional sewage sludge treatment and disposal. Water Res. 2023, 240, 120109. [Google Scholar] [CrossRef] [PubMed]
  6. Gabr, M.E. Impact of climatic changes on future irrigation water requirement in the Middle East and North Africa’s region: A case study of upper Egypt. Appl. Water Sci. 2023, 13, 158. [Google Scholar] [CrossRef]
  7. Bandala, E.R.; Liu, A.; Wijesiri, B.; Zeidman, A.B.; Goonetilleke, A. Emerging Materials and Technologies for Landfill Leachate Treatment: A Critical Review. Environ. Pollut. 2021, 291, 118133. [Google Scholar] [CrossRef]
  8. Ren, Y.; Ferraz, F.; Lashkarizadeh, M.; Yuan, Q. Comparing Young Landfill Leachate Treatment Efficiency and Process Stability Using Aerobic Granular Sludge and Suspended Growth Activated Sludge. J. Water Process Eng. 2017, 17, 161–167. [Google Scholar] [CrossRef]
  9. Vaverková, M.D.; Elbl, J.; Koda, E.; Adamcová, D.; Bilgin, A.; Lukas, V.; Podlasek, A.; Kintl, A.; Wdowska, M.; Brtnický, M.; et al. Chemical Composition and Hazardous Effects of Leachate from the Active Municipal Solid Waste Landfill Surrounded by Farmlands. Sustainability 2020, 12, 4531. [Google Scholar] [CrossRef]
  10. Baun, A.; Ledin, A.; Reitzel, L.A.; Bjerg, P.L.; Christensen, T.H. Xenobiotic Organic Compounds in Leachates from Ten Danish MSW Landfills-Chemical Analysis and Toxicity Tests. Water Res. 2004, 38, 3845–3858. [Google Scholar] [CrossRef]
  11. Yan, H.; Cousins, I.T.; Zhang, C.; Zhou, Q. Perfluoroalkyl Acids in Municipal Landfill Leachates from China: Occurrence, Fate during Leachate Treatment and Potential Impact on Groundwater. Sci. Total Environ. 2015, 524, 23–31. [Google Scholar] [CrossRef] [PubMed]
  12. Busch, J.; Ahrens, L.; Sturm, R.; Ebinghaus, R. Polyfluoroalkyl Compounds in Landfill Leachates. Environ. Pollut. 2010, 158, 1467–1471. [Google Scholar] [CrossRef] [PubMed]
  13. Belouhova, M.; Yotinov, I.; Schneider, I.; Dinova, N.; Todorova, Y.; Lyubomirova, V.; Mihaylova, V.; Daskalova, E.; Lincheva, S.; Topalova, Y. Purposely Development of the Adaptive Potential of Activated Sludge from Municipal Wastewater Treatment Plant Focused on the Treatment of Landfill Leachate. Processes 2022, 10, 460. [Google Scholar] [CrossRef]
  14. Torretta, V.; Ferronato, N.; Katsoyiannis, I.A.; Tolkou, A.K.; Airoldi, M. Novel and Conventional Technologies for Landfill Leachates Treatment: A Review. Sustainability 2016, 9, 9. [Google Scholar] [CrossRef]
  15. Scandelai, A.P.J.; Sloboda Rigobello, E.; de Oliveira, B.L.C.; Tavares, C.R.G. Identification of Organic Compounds in Landfill Leachate Treated by Advanced Oxidation Processes. Environ. Technol. 2019, 40, 730–741. [Google Scholar] [CrossRef] [PubMed]
  16. Elmaadawy, K.; Liu, B.; Hu, J.; Hou, H.; Yang, J. Performance Evaluation of Microbial Fuel Cell for Landfill Leachate Treatment: Research Updates and Synergistic Effects of Hybrid Systems. J. Environ. Sci. 2020, 96, 1–20. [Google Scholar] [CrossRef]
  17. Jagaba, A.H.; Kutty, S.R.M.; Lawal, I.M.; Abubakar, S.; Hassan, I.; Zubairu, I.; Umaru, I.; Abdurrasheed, A.S.; Adam, A.A.; Ghaleb, A.A.S.; et al. Sequencing Batch Reactor Technology for Landfill Leachate Treatment: A State-of-the-Art Review. J. Environ. Manag. 2021, 282, 111946. [Google Scholar] [CrossRef]
  18. Xu, S.; Zhang, Y.; Sims, A.; Bernards, M.; Hu, Z. Fate and Toxicity of Melamine in Activated Sludge Treatment Systems after a Long-Term Sludge Adaptation. Water Res. 2013, 47, 2307–2314. [Google Scholar] [CrossRef]
  19. Cheng, L.; Yang, W.; Liang, H.; Nabi, M.; Li, Y.; Wang, H.; Hu, J.; Chen, T.; Gao, D. Nitrogen Removal from Mature Landfill Leachate through Enhanced Partial Nitrification-Anammox Process in an Innovative Multi-Stage Fixed Biofilm Reactor. Sci. Total Environ. 2023, 877, 162959. [Google Scholar] [CrossRef]
  20. ISO 18749:2004; Water Quality—Adsorption of Substances on Activated Sludge—Batch Test Using Specific Analytical Methods. ISO: Geneva, Switzerland, 2004.
  21. BDS ISO 7150/1; Water Quality—Determination of Ammonium—Part 1: Manual Spectrometric Method. ISO: Sofia, Bulgaria, 2002.
  22. BDS EN 26777; Water Quality—Determination of Nitrite—Molecular Absorption Spectrometric Method. ISO: Sofia, Bulgaria, 1997.
  23. ISO 7890-3; Water Quality—Determination of Nitrate—Part 3: Spectrometric Method Using Sulfosalicylic Acid. ISO: Sofia, Bulgaria, 1998.
  24. BDS EN 1189; Water Quality—Determination of Phosphorus—Ammonium Molybdate Spectrometric Method. ISO: Sofia, Bulgaria, 2002.
  25. Bulgarian Institute for Standardization. Available online: https://bds-bg.org/en/ (accessed on 25 December 2023).
  26. BDS 17.1.4.02-77; Nature Protection. Hydrosphere. Water Quality Indicators. Method for Determination of Oxidizability. ISO: Sofia, Bulgaria, 1977.
  27. Amann, R.; Ludwig, W.; Schleifer, K.-H. Phylogenetic Identification and in Situ Detection of Individual Microbial Cells without Cultivation. Microbiol. Rev. 1995, 59, 143–169. [Google Scholar] [CrossRef]
  28. Nielsen, P.H.; Daims, H.; Lemmer, H.; Arslan-Alaton, I.; Olmez-Hanci, T. FISH Handbook for Biological Wastewater Treatment: Identification and Quantification of Microorganisms in Activated Sludge and Biofilms by FISH; IWA Publishing: London, UK, 2009; p. 123. [Google Scholar]
  29. Schleifer, K.-H.; Amann, R.; Ludwig, W.; Rothemund, C.; Springer, N.; Dorn, S. Nucleic Acid Probes for the Identification and In-Situ Detection of Pseudomonads. In Pseudomonas: Molecular Biology and Biotechnology; Galli, E., Silver, S., Witholt, B., Federation of European Microbiological Societies, Eds.; FEMS Symposium; American Society for Microbiology: Washington, DC, USA, 1992; ISBN 9781555810511. [Google Scholar]
  30. Neef, A.; Zaglauer, A.; Meier, H.; Amann, R.; Lemmer, H.; Schleifer, K.H. Population Analysis in a Denitrifying Sand Filter: Conventional and in Situ Identification of Paracoccus spp. in Methanol-Fed Biofilms. Appl. Environ. Microbiol. 1996, 62, 4329–4339. [Google Scholar] [CrossRef] [PubMed]
  31. Rabus, R.; Wilkes, H.; Schramm, A.; Harms, G.; Behrends, A.; Amann, R.; Widdel, F. Anaerobic Utilization of Alkylbenzenes and N-Alkanes from Crude Oil in an Enrichment Culture of Denitrifying Bacteria Affiliating with the Beta-Subclass of Proteobacteria. Environ. Microbiol. 1999, 1, 145–157. [Google Scholar] [CrossRef] [PubMed]
  32. Friedrich, U.; Van Langenhove, H.; Altendorf, K.; Lipski, A. Microbial Community and Physicochemical Analysis of an Industrial Waste Gas Biofilter and Design of 16S RRNA-Targeting Oligonucleotide Probes. Environ. Microbiol. 2003, 5, 183–201. [Google Scholar] [CrossRef] [PubMed]
  33. Wallner, G.; Amann, R.; Beisker, W. Optimizing Fluorescent in Situ Hybridization with RRNA-Targeted Oligonucleotide Probes for Flow Cytometric Identification of Microorganisms. Cytometry 1993, 14, 136–143. [Google Scholar] [CrossRef]
  34. Daims, H.; Lücker, S.; Wagner, M. Daime, a Novel Image Analysis Program for Microbial Ecology and Biofilm Research. Environ. Microbiol. 2006, 8, 200–213. [Google Scholar] [CrossRef] [PubMed]
  35. Wright, E.S. Using DECIPHER v2.0 to Analyze Big Biological Sequence Data in R. R J. 2016, 8, 352–359. [Google Scholar] [CrossRef]
  36. Parks, D.H.; Chuvochina, M.; Chaumeil, P.-A.; Rinke, C.; Mussig, A.J.; Hugenholtz, P. A Complete Domain-to-Species Taxonomy for Bacteria and Archaea. Nat. Biotechnol. 2020, 38, 1079–1086. [Google Scholar] [CrossRef]
  37. Parks, D.H.; Chuvochina, M.; Waite, D.W.; Rinke, C.; Skarshewski, A.; Chaumeil, P.-A.; Hugenholtz, P. A Standardized Bacterial Taxonomy Based on Genome Phylogeny Substantially Revises the Tree of Life. Nat. Biotechnol. 2018, 36, 996–1004. [Google Scholar] [CrossRef]
  38. Willetts, A.J.; Cain, R.B. Microbial Metabolism of Alkylbenzene Sulphonates. Bacterial Metabolism of Undecylbenzene-p-Sulphonate and Dodecylbenzene-p-Sulphonate. Biochem. J. 1972, 129, 389–402. [Google Scholar] [CrossRef]
  39. Farr, D.R.; Cain, R.B. Catechol Oxygenase Induction in Pseudomonas Aeruginosa. Biochem. J. 1968, 106, 879–885. [Google Scholar] [CrossRef]
  40. Fujisawa, H.; Hayaishi, O. Protocatechuate 3,4-Dioxygenase. I. Crystallization and Characterization. J. Biol. Chem. 1968, 243, 2673–2681. [Google Scholar] [CrossRef] [PubMed]
  41. Lenhard, G.; Nourse, L.D.; Scwartz, M. The Measurement of Dehydrogenase Activity of Activated Sludge. In Proceedings of the 2nd International Conference on Water Pollution Research, Tokyo, Japan, 24–28 August 1964. [Google Scholar]
  42. Wang, Y.; Zhang, Y.; Hu, Y.; Liu, L.; Liu, S.J.; Zhang, T. Genome-Centric Metagenomics Reveals the Host-Driven Dynamics and Ecological Role of CPR Bacteria in an Activated Sludge System. Microbiome 2023, 11, 56. [Google Scholar] [CrossRef] [PubMed]
  43. Duan, H.; Fernando, C.E.; Crupper, S.S.; Fields, S.D. Genome Sequence of a Novel Soil Actinomycete, Protaetiibacter sp. Strain SSC-01. Microbiol. Resour. Announc. 2021, 10, e01029-20. [Google Scholar] [CrossRef] [PubMed]
  44. Tarlachkov, S.V.; Ospennikov, Y.V.; Demidov, A.V.; Starodumova, I.P.; Dorofeeva, L.V.; Prisyazhnaya, N.V.; Chizhov, V.N.; Subbotin, S.A.; Evtushenko, L.I. Draft Genome Sequences of 9 Actinobacteria from the Family Microbacteriaceae Associated with Insect- and Nematode-Damaged Plants. Microbiol. Resour. Announc. 2022, 11, e00487-22. [Google Scholar] [CrossRef] [PubMed]
  45. González-Cortés, J.J.; Valle, A.; Ramírez, M.; Cantero, D. Characterization of Bacterial and Archaeal Communities by DGGE and Next Generation Sequencing (NGS) of Nitrification Bioreactors Using Two Different Intermediate Landfill Leachates as Ammonium Substrate. Waste Biomass Valorization 2022, 13, 3753–3766. [Google Scholar] [CrossRef]
  46. Remmas, N.; Roukouni, C.; Ntougias, S. Bacterial Community Structure and Prevalence of Pusillimonas-like Bacteria in Aged Landfill Leachate. Environ. Sci. Pollut. Res. 2017, 24, 6757–6769. [Google Scholar] [CrossRef] [PubMed]
  47. Zou, X.; Mohammed, A.; Gao, M.; Liu, Y. Mature Landfill Leachate Treatment Using Granular Sludge-Based Reactor (GSR) via Nitritation/Denitritation: Process Startup and Optimization. Sci. Total Environ. 2022, 844, 157078. [Google Scholar] [CrossRef] [PubMed]
  48. Tice, H.; Mayilraj, S.; Sims, D.; Lapidus, A.; Nolan, M.; Lucas, S.; Glavina Del Rio, T.; Copeland, A.; Cheng, J.F.; Meincke, L.; et al. Complete Genome Sequence of Nakamurella Multipartita Type Strain (Y-104). Stand Genomic. Sci. 2010, 2, 168–175. [Google Scholar] [CrossRef]
  49. McIlroy, S.J.; Onetto, C.A.; McIlroy, B.; Herbst, F.A.; Dueholm, M.S.; Kirkegaard, R.H.; Fernando, E.; Karst, S.M.; Nierychlo, M.; Kristensen, J.M.; et al. Genomic and in Situ Analyses Reveal the Micropruina spp. as Abundant Fermentative Glycogen Accumulating Organisms in Enhanced Biological Phosphorus Removal Systems. Front. Microbiol. 2018, 9, 337530. [Google Scholar] [CrossRef]
  50. Lopez-Vazquez, C.M.; Oehmen, A.; Hooijmans, C.M.; Brdjanovic, D.; Gijzen, H.J.; Yuan, Z.; van Loosdrecht, M.C.M. Modeling the PAO–GAO Competition: Effects of Carbon Source, PH and Temperature. Water Res. 2009, 43, 450–462. [Google Scholar] [CrossRef]
  51. Kong, Y.H.; Beer, M.; Seviour, R.J.; Lindrea, K.C.; Rees, G.N. Structure and Functional Analysis of the Microbial Community in an Aerobic: Anaerobic Sequencing Batch Reactor (SBR) with No Phosphorus Removal. Syst. Appl. Microbiol. 2001, 24, 597–609. [Google Scholar] [CrossRef]
  52. Puri, A.; Bajaj, A.; Singh, Y.; Lal, R. Harnessing Taxonomically Diverse and Metabolically Versatile Genus Paracoccus for Bioplastic Synthesis and Xenobiotic Biodegradation. J. Appl. Microbiol. 2022, 132, 4208–4224. [Google Scholar] [CrossRef] [PubMed]
  53. Cao, Q.; Chen, Y.; Li, X.; Li, C.; Li, X. Low C/N Promotes Stable Partial Nitrification by Enhancing the Cooperation of Functional Microorganisms in Treating High-Strength Ammonium Landfill Leachate. J. Environ. Manag. 2023, 329, 116972. [Google Scholar] [CrossRef] [PubMed]
  54. Zheng, L.; Lin, H.; Dong, Y.; Li, B.; Lu, Y. A Promising Approach for Simultaneous Removal of Ammonia and Multiple Heavy Metals from Landfill Leachate by Carbonate Precipitating Bacterium. J. Hazard Mater. 2023, 456, 131662. [Google Scholar] [CrossRef] [PubMed]
  55. Carrareto Alves, L.M.; De Souza, J.A.M.; Varani, A.D.M.; Lemos, E.G.D.M. The Family Rhizobiaceae. In The Prokaryotes; Springer: Berlin/Heidelberg, Germany, 2014; pp. 419–437. [Google Scholar] [CrossRef]
  56. Jahan, K.; Hoque, S.; Ahmed, T. Activated Sludge and Other Suspended Culture Processes. Water Environ. Res. 2012, 84, 1029–1080. [Google Scholar] [CrossRef]
  57. Palma, T.L.; Shylova, A.; Costa, M.C. Isolation and Characterization of Bacteria from Activated Sludge Capable of Degrading 17α-Ethinylestradiol, a Contaminant of High Environmental Concern. Microbiology 2021, 167, 001038. [Google Scholar] [CrossRef] [PubMed]
  58. Sun, F.; Sun, B.; Li, Q.; Deng, X.; Hu, J.; Wu, W. Pilot-Scale Nitrogen Removal from Leachate by Ex Situ Nitrification and in Situ Denitrification in a Landfill Bioreactor. Chemosphere 2014, 101, 77–85. [Google Scholar] [CrossRef]
  59. Wang, G.; Chen, R.; Huang, L.; Ma, H.; Mu, D.; Zhao, Q. Microbial Characteristics of Landfill Leachate Disposed by Aerobic Moving Bed Biofilm Reactor. Water Sci. Technol. 2018, 77, 1089–1097. [Google Scholar] [CrossRef]
  60. Remmas, N.; Melidis, P.; Katsioupi, E.; Ntougias, S. Effects of High Organic Load on AmoA and NirS Gene Diversity of an Intermittently Aerated and Fed Membrane Bioreactor Treating Landfill Leachate. Bioresour. Technol. 2016, 220, 557–565. [Google Scholar] [CrossRef]
  61. Michalska, J.; Piński, A.; Zur, J.; Mrozik, A. Selecting Bacteria Candidates for the Bioaugmentation of Activated Sludge to Improve the Aerobic Treatment of Landfill Leachate. Water 2020, 12, 140. [Google Scholar] [CrossRef]
  62. Xie, B.; Xiong, S.; Liang, S.; Hu, C.; Zhang, X.; Lu, J. Performance and Bacterial Compositions of Aged Refuse Reactors Treating Mature Landfill Leachate. Bioresour. Technol. 2012, 103, 71–77. [Google Scholar] [CrossRef]
  63. Song, L.; Wang, Y.; Tang, W.; Lei, Y. Bacterial Community Diversity in Municipal Waste Landfill Sites. Appl. Microbiol. Biotechnol. 2015, 99, 7745–7756. [Google Scholar] [CrossRef]
  64. Remmas, N.; Melidis, P.; Zerva, I.; Kristoffersen, J.B.; Nikolaki, S.; Tsiamis, G.; Ntougias, S. Dominance of Candidate Saccharibacteria in a Membrane Bioreactor Treating Medium Age Landfill Leachate: Effects of Organic Load on Microbial Communities, Hydrolytic Potential and Extracellular Polymeric Substances. Bioresour. Technol. 2017, 238, 48–56. [Google Scholar] [CrossRef]
  65. Li, Y.; Dong, R.; Guo, J.; Wang, L.; Zhao, J. Effects of Mn2+ and Humic Acid on Microbial Community Structures, Functional Genes for Nitrogen and Phosphorus Removal, and Heavy Metal Resistance Genes in Wastewater Treatment. J. Environ. Manag. 2022, 313, 115028. [Google Scholar] [CrossRef]
  66. Tong, J.; Cui, L.; Wang, D.; Wang, X.; Liu, Z. Assessing the Performance and Microbial Structure of Biofilms in Membrane Aerated Biofilm Reactor for High P-Nitrophenol Concentration Treatment. J. Environ. Chem. Eng. 2022, 10, 108635. [Google Scholar] [CrossRef]
Processes 12 00159 g001
Figure 1. Experimental design.
Figure 1. Experimental design.
Processes 12 00159 g001
Processes 12 00159 g002
Figure 2. Number of the bacteria from the key groups, determined by plate counting techniques.
Figure 2. Number of the bacteria from the key groups, determined by plate counting techniques.
Processes 12 00159 g002
Processes 12 00159 g003
Figure 3. Digital image analysis of FISH images of samples at the four control points during the experiments.
Figure 3. Digital image analysis of FISH images of samples at the four control points during the experiments.
Processes 12 00159 g003
Processes 12 00159 g004
Figure 4. Metagenomic analysis of the activated sludge at the end of the model SBR treatment of landfill leachate (21st day).
Figure 4. Metagenomic analysis of the activated sludge at the end of the model SBR treatment of landfill leachate (21st day).
Processes 12 00159 g004
Processes 12 00159 g005
Figure 5. Metagenomic analysis of the free-swimming bacteria in the activated sludge at the end of the model SBR treatment of landfill leachate (21st day).
Figure 5. Metagenomic analysis of the free-swimming bacteria in the activated sludge at the end of the model SBR treatment of landfill leachate (21st day).
Processes 12 00159 g005
Processes 12 00159 g006
Figure 6. Activity of the key detoxifying enzymes (C12DO—catechol-1,2-dioxygenase; C23DO—catechol-2,3-dioxygenase; P34DO—protocatechuate-3,4-dioxygenase; TDA—total dehydrogenase activity) and the remaining pollutants which was measured as COD.
Figure 6. Activity of the key detoxifying enzymes (C12DO—catechol-1,2-dioxygenase; C23DO—catechol-2,3-dioxygenase; P34DO—protocatechuate-3,4-dioxygenase; TDA—total dehydrogenase activity) and the remaining pollutants which was measured as COD.
Processes 12 00159 g006
Table 1. Oligonucleotide probes used in the experiments.
Table 1. Oligonucleotide probes used in the experiments.
Target MicroorganismsProbes for FISHNucleotide SequenceFA, %Reference
Pseudomonas sp.PsGCT GGC CTA GCC TTC20Schleifer, 1992 [29]
Paracoccus spp.PAR1244GGA TTA ACC CAC TGT CAC C20Neef, 1996 [30]
Azoarcus-Thauera clusterAT1458GAA TCT CAC CGT GGT AAG CGC50Rabus, 1999 [31]
Alcaligenes spp.ALBO577CCG AAC CGC CTG CGC AC
Competitor—GCG AAC CGC CTG CGC AC		35Friedrich, 2003 [32]
None (nonsense probe)NON-EUBACT CCT ACG GGA GGC AGC0–80Wallner, 1993 [33]
Table 2. Gene-specific primer sequences.
Table 2. Gene-specific primer sequences.
Primer NameSequence
341FACTCCTACGGGAGGCAGCAG
806RGGACTACHVGGGTWTCTAAT
Table 3. Main indicators of the landfill leachate treatment process at the end of the treatment cycles.
Table 3. Main indicators of the landfill leachate treatment process at the end of the treatment cycles.
Control PointLeachate DilutionSVI, mL/gCOD, mgO2/LNH4, mg/LNO2, mg/LNO3, mg/LPO4, mg/L
0 h-30 ± 21858 ± 5520.1 ± 2.10.02 ± 0.01452.1 ± 24.30.25 ± 0.06
7th day×5066 ± 3309 ± 222.8 ± 0.80.03 ± 0.02154.4 ± 14.40.07 ± 0.02
14th day×25105 ± 5890 ± 65.9 ± 1.10.02 ± 0.01235.3 ± 18.70.07 ± 0.03
21st day×15 ± 12321 ± 9573.2 ± 18.30.97 ± 0.14.4 ± 0.915.27 ± 3.7
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Kirilova, M.; Yotinov, I.; Todorova, Y.; Dinova, N.; Lincheva, S.; Schneider, I.; Topalova, Y. Microbiome Structure of Activated Sludge after Adaptation to Landfill Leachate Treatment in a Lab-Scale Sequencing Batch Reactor. Processes 2024, 12, 159. https://doi.org/10.3390/pr12010159

AMA Style

Kirilova M, Yotinov I, Todorova Y, Dinova N, Lincheva S, Schneider I, Topalova Y. Microbiome Structure of Activated Sludge after Adaptation to Landfill Leachate Treatment in a Lab-Scale Sequencing Batch Reactor. Processes. 2024; 12(1):159. https://doi.org/10.3390/pr12010159

Chicago/Turabian Style

Kirilova, Mihaela, Ivaylo Yotinov, Yovana Todorova, Nora Dinova, Stilyana Lincheva, Irina Schneider, and Yana Topalova. 2024. "Microbiome Structure of Activated Sludge after Adaptation to Landfill Leachate Treatment in a Lab-Scale Sequencing Batch Reactor" Processes 12, no. 1: 159. https://doi.org/10.3390/pr12010159

APA Style

Kirilova, M., Yotinov, I., Todorova, Y., Dinova, N., Lincheva, S., Schneider, I., & Topalova, Y. (2024). Microbiome Structure of Activated Sludge after Adaptation to Landfill Leachate Treatment in a Lab-Scale Sequencing Batch Reactor. Processes, 12(1), 159. https://doi.org/10.3390/pr12010159

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop